&EPA
United States
Environmental Protection
Agency
Air and
Radiation
(6204J)
EPA# 450R13002
November 2013
Documentation for
EPA Base Case v.5.13
Using the Integrated Planning
Model
WEC_LADW
WEC^SOGE
WECC IID'
S_D_WOTA S_D_AMSO
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Cover: EPA Base Case v.5.13 and associated policy cases are used by the U.S. Environmental
Protection Agency to project the impact of emissions policies on the electric power sector in the 48
contiguous states and the District of Columbia in the lower continental U.S. Representation of the electric
power sector in Canada is also included for purposes of integrated projections. The map appearing on the
cover shows the 64 model regions used to characterize the operation of the U.S. electric power system in
the lower continental U.S. and 11 model regions in Canada. EPA Base Case v.5.13 was developed by
EPA's Clean Air Markets Division with technical support from ICF International, Inc. The IPM modeling
platform is a product of ICF Resources, LLC, an operating company of ICF International, Inc and is used
in support of its public and private sector clients. IPMฎ is a registered trademark of ICF Resources, L.L.C.
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Documentation for
EPA Base Case v.5.13
Using the Integrated Planning Model
U.S. Environmental Protection Agency
Clean Air Markets Division
1200 Pennsylvania Avenue, NW(6204J)
Washington, D.C. 20460
(www.epa.gov/airmarkets)
November 2013
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Acknowledgment
This document was prepared by U.S. EPA's Clean Air Markets Division, Office of Air and Radiation. ICF
Incorporated, L.L.C., an operating company of ICF International, provided technical support under EPA
Contracts EP-W-13-009 and EP-W-08-018.
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TABLE OF CONTENTS
Acknowledgment i
1. Introduction 1-1
2. Modeling Framework 2-1
2.1 IPM Overview 2-1
2.1.1 Purpose and Capabilities 2-1
2.1.2 Applications 2-2
2.2 Model Structure and Formulation 2-2
2.2.1 Objective Function 2-2
2.2.2 Decision Variables 2-3
2.2.3 Constraints 2-4
2.3 Key Methodological Features of IPM 2-4
2.3.1 Model Plants 2-5
2.3.2 Model Run Years 2-6
2.3.3 Cost Accounting 2-6
2.3.4 Modeling Wholesale Electricity Markets 2-7
2.3.5 Load Duration Curves (LDC) 2-7
2.3.6 Dispatch Modeling 2-9
2.3.7 Fuel Modeling 2-10
2.3.8 Transmission Modeling 2-10
2.3.9 Perfect Competition and Perfect Foresight 2-11
2.3.10 Air Regulatory Modeling 2-11
2.4 Hardware and Programming Features 2-11
2.4.1 Data Parameters for Model Inputs 2-12
2.4.2 Model Outputs 2-13
Attachment 2-1 Load Duration Curves3 Used in EPA Base Case v.5.13 2-14
3. Power System Operation Assumptions 3-1
3.1 Model Regions 3-1
3.2 Electric Load Modeling 3-2
3.2.1 Demand Elasticity 3-5
3.2.2 Net Internal Demand (Peak Demand) 3-5
3.2.3 Regional Load Shapes 3-6
3.3 Transmission 3-6
3.3.1 Inter-regional Transmission Capability 3-6
3.3.2 Joint Transmission Capacity and Energy Limits 3-12
3.3.3 Transmission Link Wheeling Charge 3-14
3.3.4 Transmission Losses 3-14
3.4 International Imports 3-14
3.5 Capacity, Generation, and Dispatch 3-14
3.5.1 Availability 3-15
3.5.2 Capacity Factor 3-15
3.5.3 Turndown 3-18
3.6 Reserve Margins 3-18
3.7 Power Plant Lifetimes 3-20
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3.8 Heat Rates 3-20
3.9 Existing Environmental Regulations 3-21
3.9.1 SO2 Regulations 3-21
3.9.2 NOX Regulations 3-22
3.9.3 Multi-Pollutant Environmental Regulations 3-25
3.9.4 CO2 Regulations 3-26
3.9.5 State-Specific Environmental Regulations 3-27
3.9.6 New Source Review (NSR) Settlements 3-27
3.9.7 Emission Assumptions for Potential (New) Units 3-27
3.9.8 Energy Efficiency and Renewable Portfolio Standards 3-27
3.10 Capacity Deployment Constraints 3-28
Attachment 3-1 NOX Rate Development in EPA Base Case v.5.13 3-31
Attachment 3-2 Capacity Deployment Limits for Advanced Coal with CCS and New Nuclear in EPA
Base Case v.5.13 3-36
Attachment 3-3 Nuclear Capacity Deployment Constraint in EPA Base Case v.5.13 3-37
4. Generating Resources 4-1
4.1 National Electric Energy Data System (NEEDS) 4-1
4.2 Existing Units 4-1
4.2.1 Population of Existing Units 4-1
4.2.2 Capacity 4-4
4.2.3 Plant Location 4-5
4.2.4 Online Year 4-5
4.2.5 Unit Configuration 4-6
4.2.6 Model Plant Aggregation 4-6
4.2.7 Cost and Performance Characteristics of Existing Units 4-10
4.2.8 Life Extension Costs for Existing Units 4-16
4.3 Planned-Committed Units 4-16
4.3.1 Population and Model Plant Aggregation 4-16
4.3.2 Capacity 4-22
4.3.3 State and Model Region 4-22
4.3.4 Online and Retirement Year 4-22
4.3.5 Unit Configuration, Cost and Performance 4-22
4.4 Potential Units 4-22
4.4.1 Methodology Used to Derive the Cost and Performance Characteristics of
Conventional Potential Units 4-23
4.4.2 Cost and Performance for Potential Conventional Units 4-23
4.4.3 Short-Term Capital Cost Adder 4-23
4.4.4 Regional Cost Adjustment 4-24
4.4.5 Cost and Performance for Potential Renewable Generating and Non-Conventional
Technologies 4-31
4.5 Nuclear Units 4-59
4.5.1 Existing Nuclear Units 4-59
4.5.2 Potential Nuclear Units 4-60
5. Emission Control Technologies 5-1
5.1 Sulfur Dioxide Control Technologies - Scrubbers 5-1
5.1.1 Methodology for Obtaining SO2 Controls Costs 5-2
5.2 Nitrogen Oxides Control Technology 5-5
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5.2.1 Combustion Controls 5-5
5.2.2 Post-combustion NOX Controls 5-5
5.2.3 Methodology for Obtaining SCR Costs for Coal 5-6
5.2.4 Methodology for Obtaining SCR Costs for Oil/Gas Steam Units 5-8
5.2.5 Methodology for Obtaining SNCR Costs 5-8
5.2.6 SO2 and NOX Controls for Units with Capacities from 25 MW to 100 MW (25 MW <
capacity < 100 MW) 5-8
5.3 Biomass Co-firing 5-9
5.4 Mercury Control Technologies 5-10
5.4.1 Mercury Content of Fuels 5-10
5.4.2 Mercury Emission Modification Factors 5-11
5.4.3 Mercury Control Capabilities 5-15
5.4.4 Methodology for Obtaining ACI Control Costs 5-17
5.5 Hydrogen Chloride (HCI) Control Technologies 5-18
5.5.1 Chlorine Content of Fuels 5-18
5.5.2 HCI Removal Rate Assumptions for Existing and Potential Units 5-20
5.5.3 HCI Retrofit Emission Control Options 5-20
5.6 Fabric Filter (Baghouse) Cost Development 5-22
5.6.1 MATS Filterable Particulate Matter (PM) Compliance 5-24
5.7 Coal-to-Gas Conversions 5-25
5.7.1 Boiler Modifications For Coal-To-Gas Conversions 5-25
5.7.2 Natural Gas Pipeline Requirements For Coal-To-Gas Conversions 5-27
5.8 Natural Gas Co-firing 5-33
6. CO2 Capture, Transport, and Storage 6-1
6.1 CO2 Capture 6-1
6.2 CO2 Storage 6-2
6.3 CO2 Transport 6-5
7. Set-up Parameters and Rules 7-1
7.1 Run Year Mapping 7-1
7.2 Retrofit Assignments 7-1
7.3 Emissions Trading and Banking 7-4
8. Financial Assumptions 8-6
8.1 Introduction to Risk 8-6
8.1.1 Market Structure Risks 8-6
8.1.2 Technology Risks 8-7
8.1.3 Financing Structure Risks and Approach 8-7
8.2 Calculation of the Financial Discount Rate 8-8
8.2.1 Introduction to Discount Rate Calculations 8-8
8.2.2 Choosing a Discount Rate 8-8
8.2.3 Discount Rate Components 8-8
8.2.4 Market Structure: Utility-Merchant Financing Ratio 8-9
8.2.5 Debt and Equity Shares and Technology Risk 8-10
8.3 Calculation of Capital Charge Rate 8-13
8.3.1 Introduction to Capital Charge Rate Calculations 8-13
8.3.2 Capital Charge Rate Components 8-14
IV
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8.3.3 Capital Charge Rate Calculation Process 8-15
9. Coal 9-1
9.1 Coal Market Representation in EPA Base Case v.5.13 9-1
9.1.1 Coal Supply Regions 9-2
9.1.2 Coal Demand Regions 9-3
9.1.3 Coal Quality Characteristics 9-12
9.1.4 Emission Factors 9-13
9.1.5 Coal Grade Assignments 9-15
9.2 Coal Supply Curves 9-15
9.2.1 Nature of Supply Curves Developed for EPA Base Case v.5.13 9-15
9.2.2 Cost Components in the Supply Curves 9-17
9.2.3 Procedures Employed in Determining Mining Costs 9-17
9.2.4 Procedure Used In Determining Mine Productivity 9-18
9.2.5 Procedure to Determine Total Recoverable Reserves by Region and Type 9-19
9.2.6 New Mine Assumptions 9-19
9.2.7 Other Notable Procedures 9-19
9.2.8 Supply Curve Development 9-21
9.2.9 EPA Base Case v.5.13 Assumptions and Outlooks for Major Supply Basins 9-23
9.3 Coal Transportation 9-24
9.3.1 Coal Transportation Matrix Overview 9-24
9.3.2 Calculation of Coal Transportation Distances 9-25
9.3.3 Overview of Rail Rates 9-26
9.3.4 Truck Rates 9-28
9.3.5 Barge and Lake Vessel Rates 9-29
9.3.6 Transportation Rates for Imported Coal 9-29
9.3.7 Other Transportation Costs 9-30
9.3.8 Long-Term Escalation of Transportation Rates 9-30
9.3.9 Market Drivers Moving Forward 9-32
9.3.10 Other Considerations 9-34
9.4 Coal Exports, Imports, and Non-Electric Sectors Demand 9-35
Attachment 9-1 Mining Cost Estimation Methodology and Assumptions 9-37
10. Natural Gas 10-1
10.1 Overview of IPM's Natural Gas Module 10-1
10.2 Key Components of the New IPM Natural Gas Module 10-3
10.2.1 Note on the Modeling Time Horizon and Pre- and Post-2040 Input Assumptions..10-
14
10.3 Resource Characterization and Economic Evaluation 10-15
10.3.1 Resource and Reserves Assessment 10-16
10.3.2 Frontier Resources (Alaska and Mackenzie Delta) 10-18
10.3.3 Use of the HSM resource and reserves data in EPA Base Case using IPM v.5.13
Natural Gas Module 10-18
10.3.4 Undiscovered Resource Appreciation 10-21
10.4 Exploration, Development, and Production Costs and Constraints 10-22
10.4.1 Exploration and Development Cost 10-22
10.4.2 Resource Discovery and Drilling Constraints 10-25
10.4.3 Reserves-to-Production (R/P) Ratio 10-27
10.4.4 Variable Costs, Natural Gas Liquid Share, and Crude Oil Share 10-27
10.4.5 Lease and Plant Gas Use 10-27
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10.5 Liquefied Natural Gas (LNG) Imports 10-28
10.5.1 Liquefaction Facilities and LNG Supply 10-28
10.5.2 Regasification Facilities 10-29
10.5.3 LNG Regasification Capacity Expansions 10-30
10.6 End Use Demand 10-31
10.6.1 Step 1: Developing Sector Specific Econometric Models of Non-Power Sector
Demand 10-31
10.6.2 Step 2: Use projections based on the GMM econometric models to produce
monthly gas demand curves by sector and demand node 10-33
10.6.3 Step 3: Develop non-electric sector natural gas demand curves that correspond to
the seasons and segments in the load duration curves used in IPM 10-33
10.6.4 The Use of Firm Gas Demand to Represent LNG Exports 10-35
10.7 Pipeline Network 10-35
10.7.1 Network Structure 10-35
10.7.2 Pipeline Transportation Costs 10-36
10.7.3 Pipeline Capacity Expansion Logic 10-37
10.8 Gas Storage 10-38
10.8.1 Storage Capacity and Injection/Withdrawal Constraints 10-40
10.8.2 Variable Cost and Fuel Use 10-41
10.8.3 Storage Capacity Expansion Logic 10-42
10.9 Fuel Prices 10-43
10.9.1 Crude Oil and Natural Gas Liquids Prices 10-43
10.9.2 Natural Gas Prices 10-44
10.10 Outputs and Glossary of Terms 10-44
10.10.1 Outputs from the IPM Natural Gas Module 10-44
10.10.2 Glossary of Terms Used in this Section 10-44
11. Other Fuels and Fuel Emission Factor Assumptions 11-1
11.1 Fuel Oil 11-1
11.2 Biomass 11-2
11.3 Nuclear Fuel 11-5
11.4 Waste Fuels 11-5
11.5 Fuel Emission Factors 11-5
VI
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LIST OF TABLES
Table 1-1 Updates in the EPA Base Case v.5.13 1-2
Table 1-2 Plant Types in EPA Base Case v.5.13 1-3
Table 1-3 Emission Control Technologies in EPA Base Case v.5.13 1-3
Table 3-1 Mapping of NERC Regions and NEMS Regions with EPA Base Case v.5.13 Model Regions 3-
3
Table 3-2 Electric Load Assumptions in EPA Base Case v.5.13 3-5
Table 3-3 National Non-Coincidental Net Internal Demand 3-5
Table 3-4 Annual Transmission Capabilities of U.S. Model Regions in EPA Base Case v.5.13 3-6
Table 3-5 Annual Joint Capacity and Energy Limits to Transmission Capabilities Between Model Regions
in EPA Base Case v.5.13 3-13
Table 3-6 International Electricity Imports in EPA Base Case v.5.13 3-14
Table 3-7 Availability Assumptions in the EPA Base Case v.5.13 3-15
Table 3-8 Seasonal Hydro Capacity Factors (%) in the EPA Base Case v.5.13 3-16
Table 3-9 Planning Reserve Margins in EPA Base Case v.5.13 3-18
Table 3-10 Lower and Upper Limits Applied to Heat Rate Data in NEEDS v.5.13 3-21
Table 3-11 State-of-the-Art Combustion Control Configurations by Boiler Type 3-24
Table 3-12 Emission and Removal Rate Assumptions for Potential (New) Units in EPA Base Case v.5.13
3-30
Table 3-1.1 Cutoff and Floor NOX Rates (Ib/MMBtu) in EPA Base Case v.5.13 3-35
Table 3-1.2 NOX Removal Efficiencies for Different Combustion Control Configurations in EPA Base Case
v.5.13 3-35
Table 3-13 State Power Sector Regulations included in EPA Base Case v.5.13 3-39
Table 3-14 New Source Review (NSR) Settlements in EPA Base Case v.5.13 3-47
Table 3-15 State Settlements in EPA Base Case v.5.13 3-66
Table 3-16 Citizen Settlements in EPA Base Case v.5.13 3-69
Table 3-17 Renewable Portfolio Standards in EPA Base Case v.5.13 3-71
Table 3-18 Complete Availability Assumptions in EPA Base Case v.5.13 3-73
Table 3-19 BART Regulations included in EPA Base Case v.5.13 3-74
Table 4-1 Data Sources for NEEDS v.5.13 for EPA Base Case v.5.13 4-2
Table 4-2 Rules Used in Populating NEEDS v.5.13 for EPA Base Case v.5.13 4-2
Table 4-3 Summary Population (through 2010) of Existing Units in NEEDS v.5.13 4-4
Table 4-4 Hierarchy of Data Sources for Capacity in NEEDS v.5.13 4-4
Table 4-5 Capacity-Parsing Algorithm for Steam Units in NEEDS v.5.13 4-5
Table 4-6 Data Sources for Unit Configuration in NEEDS v.5.13 for EPA Base Case v.5.13 4-6
Table 4-7 Aggregation Profile of Model Plants as Provided at Set Up of EPA Base Case v.5.13 4-7
Table 4-8 VOM Assumptions in EPA Base Case v.5.13 4-10
Table 4-9 FOM Assumptions Used in EPA Base Case v.5.13 4-12
Table 4-10 Life Extension Cost Assumptions Used in EPA Base Case v.5.13 4-16
Table 4-11 Summary of Planned-Committed Units in NEEDS v.5.13 for EPA Base Case v.5.13 4-16
Table 4-12 Planned-Committed Units by Model Region in NEEDS v.5.13 for EPA Base Case v.5.13 .4-17
Table 4-13 Performance and Unit Cost Assumptions for Potential (New) Capacity from Conventional
Technologies in EPA Base Case v.5.13 4-25
Table 4-14 Short-Term Capital Cost Adders for New Power Plants in EPA Base Case v.5.13 (2011$)4-25
Table 4-15 Regional Cost Adjustment Factors for Conventional and Renewable Generating Technologies
in EPA Base Case v.5.13 4-26
Table 4-16 Performance and Unit Cost Assumptions for Potential (New) Renewable and Non-
Conventional Technology Capacity in EPA Base Case v.5.13 4-29
VII
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Table 4-17 Onshore Regional Potential Wind Capacity (MW) by Wind and Cost Class in EPA Base Case
v.5.13 4-31
Table 4-18 Offshore Shallow Regional Potential Wind Capacity (MW) by Wind and Cost Class in EPA
Base Case v.5.13 4-39
Table 4-19 Offshore Deep Regional Potential Wind Capacity (MW) by Wind and Cost Class in EPA Base
Case v.5.13 4-42
Excerpt of Table 4-20 Representative Wind Generation Profiles in EPA Base Case v.5.13 4-45
Table 4-21 Onshore Reserve Margin Contribution an Average Capacity Factor by Wind Class 4-46
Table 4-22 Offshore Shallow Reserve Margin Contribution an Average Capacity Factor by Wind Class ..4-
46
Table 4-23 Offshore Deep Reserve Margin Contribution an Average Capacity Factor by Wind Class .4-46
Table 4-24 Capital Cost Adjustment Factors for New Wind Plants in Base Case v.5.13 4-47
Table 4-25 Example Calculations of Wind Generation Potential, Reserve Margin Contribution, and
Capital Cost for Onshore Wind in WECC_CO at Wind Class 3, Cost Class 2 4-47
Table 4-26 Solar PV Regional Potential Capacity (MW) in EPA Base Case v.5.13 4-48
Table 4-27 Solar Thermal Regional Potential Capacity (MW) in EPA Base Case v.5.13 4-51
Excerpt of Table 4-28 Representative Solar Generation Profiles in EPA Base v.5.13 4-52
Table 4-29 Solar Photovoltaic Reserve Margin Contribution and Average Capacity Factor by State and
Solar Thermal Reserve Margin Contribution and Average Capacity Factor by Class 4-53
Table 4-30 Regional Assumptions on Potential Geothermal Electric Capacity 4-54
Table 4-31 Potential Geothermal Capacity and Cost Characteristics by Model Region 4-54
Table 4-32 Regional Assumptions on Potential Electric Capacity from New Landfill Gas Units (MW) ..4-56
Table 4-33 Nuclear Upratings (MW) as Incorporated in EPA Base Case v.5.13 4-60
Table 4-34 Characteristics of Existing Nuclear Units 4-60
Excerpt from Table 4-35 Capacity Not Included Based on EIA Form 860 - Existing Units 4-62
Table 4-36 Capacity Not Included Due to Recent Announcements 4-62
Table 5-1 Summary of Emission Control Technology Retrofit Options in EPA Base Case v.5.13 5-1
Table 5-2 Summary of Retrofit SO2 Emission Control Performance Assumptions in Base Case v.5.13 ..5-2
Table 5-3 Illustrative Scrubber Costs (2011 $) for Representative Sizes and Heat Rates under the
Assumptions in EPA Base Case v.5.13 5-4
Table 5-4 Cost (2011$) of NOX Combustion Controls for Coal Boilers (300 MWSize) 5-5
Table 5-5 Summary of Retrofit NOX Emission Control Performance Assumptions 5-6
Table 5-6 Illustrative Post-combustion NOX Control Costs (2011$) for Coal Plants for Representative
Sizes and Heat Rates under the Assumptions in EPA Base Case v.5.13 5-7
Table 5-7 Post-Combustion NOX Controls for Oil/Gas Steam Units in EPA Base Case v.5.13 5-8
Table 5-8 Biomass Co-firing for Coal Plants 5-9
Table 5-9 Assumptions on Mercury Concentration in Non-Coal Fuel in EPA Base Case v.5.13 5-11
Table 5-10 Mercury Emission Modification Factors Used in EPA Base Case v.5.13 5-12
Table 5-11 Definition of Acronyms for Existing Controls 5-14
Table 5-12 Key to Burner Type Designations in Table 5-10 5-14
Table 5-13 Assignment Scheme for Mercury Emissions Control Using Activated Carbon Injection (ACI) in
EPA Base Case v.5.13 5-16
Table 5-14 Illustrative Activated Carbon Injection (ACI) Costs (2011$) for Representative Sizes and Heat
Rates underthe Assumptions in EPA Base Case v.5.13 5-19
Table 5-15 HCI Removal Rate Assumptions for Potential (New) and Existing Units in EPA Base Case
v.5.13 5-20
Table 5-16 Summary of Retrofit HCI (and SO2) Emission Control Performance Assumptions in v.5.13 5-21
Table 5-17 Illustrative Dry Sorbent Injection (DSI) Costs for Representative Sizes and Heat Rates under
Assumptions in EPA Base Case v.5.13 5-23
VIM
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Table 5-18 Illustrative Particulate Controls for Costs (2011$) for Representative Sizes and Heat Rates
under the Assumptions in EPA Base Case v.5.13 5-23
Table 5-19 Electrostatic Precipitator (ESP) Upgrades as Implemented in EPA Base Case v.5.13
Characteristics, Trigger Points, Associated Costs, and Performance Improvements 5-24
Excerpt from Table 5-20 ESP Upgrade Provided to Existing Units without Fabric Filters so that They Meet
Their Filterable PM Compliance Requirement 5-26
Table 5-21 Cost and Performance Assumptions for Coal-to-Gas Retrofits 5-26
Excerpt from Table 5-22 Cost of Building Pipelines to Coal Plants 5-32
Table 6-1 Performance and Unit Cost Assumptions for Carbon Capture Retrofits on Pulverized Coal
Plants 6-1
Excerpt from Table 6-2 CO2 Storage Cost Curves in EPA Base Case v.5.13 6-4
Excerpt from Table 6-3 CO2 Transportation Matrix in EPA Base Case v.5.13 6-6
Table 7-1 Run Years and Analysis Year Mapping Used in the EPA Base Case v.5.13 7-1
Table 7-2 First Stage Retrofit Assignment Scheme in EPA Base Case v.5.13 7-2
Table 7-3 Second and Third Stage Retrofit Assignment Scheme in EPA Base Case v.5.13 7-3
Table 7-4 Trading and Banking Rules in EPA Base Case v.5.13 7-5
Table 8-1 Capital Structure Assumptions in EPA Base Case v.5.13 8-10
Table 8-2 Debt Rates for EPA Base Case v.5.13 8-11
Table 8-3 U.S. Real Capital Charge Rates3 for EPA Base Case v.5.13 8-13
Table 8-4 Book Life, Debt Life and Depreciation Schedules for EPA Base Case v. 5.13 8-14
Table 9-1 Coal Supply Regions in EPA Base Case 9-2
Table 9-2 Coal Demand Regions in EPA Base Case 9-4
Table 9-3 Coal Rank Heat Content Ranges 9-12
Table 9-4 Coal Grade SO2 Content Ranges 9-12
Table 9-5 Coal Quality Characteristics by Supply Region and Coal Grade 9-13
Table 9-6 Example of Coal Assignments Made in EPA Base Case 9-15
Table 9-7 Basin-Level Groupings Used in Preparing v.5.13 Coal Supply Curves 9-16
Table 9-8 Rail Competition Definitions 9-26
Table 9-9 Assumed Eastern Rail Rates for 2012 (2011 mills/ton-mile) 9-27
Table 9-10 Assumed Midwestern Rail Rates for 2012 (2011 mills/ton-mile) 9-27
Table 9-11 Assumed Non-PRB Western Rail Rates for 2012 (2011 mills/ton-mile) 9-28
Table 9-12 Assumed PRB Western Rail Rates for 2012 (2011 mills/ton-mile) 9-28
Table 9-13 Assumed Truck Rates for 2012 (2011 Real Dollars) 9-28
Table 9-14 Assumed Barge Rates for 2012 (2011 Real Dollars) 9-29
Table 9-15 Assumed Other Transportation Rates for 2012 (2011 Real Dollars) 9-30
Table 9-16 EIA AEO Diesel Fuel Forecast, 2012-2030 (2011 Real Dollars) 9-32
Table 9-17 ABARES Forecast of Iron Ore Prices 9-33
Table 9-18 Summary of Expected Escalation for Coal Transportation Rates, 2013-2050 9-34
Table 9-19 Coal Exports 9-35
Table 9-20 Residential, Commercial, and Industrial Demand 9-35
Table 9-21 Coal to Liquids Demand 9-36
Table 9-22 Coal Import Limits 9-36
Table 9-24 Coal Supply Curves in EPA Base Case v.5.13 9-38
Table 10-1 List of Nodes 10-4
Table 10-2 List of Gas Supply Regions 10-7
Table 10-3 List of Key Pipelines 10-9
Table 10-4 U.S. and Canada Natural Gas Resources and Reserves 10-19
Table 10-5 Exploration and Development Assumptions for EPA Base Case v.5.13 10-25
IX
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Table 10-6 North American LNG Regasification Facilities 10-29
Table 10-7 Summer and Winter Load Segments in EPA Base Case v.5.13 10-33
Table 10-8 List of Storage Nodes 10-39
Table 10-9 Storage Capacity and Injection/Withdrawal Rates (BOY 2015) 10-41
Table 10-10 Base Year 2015 Average Levelized Storage Capital Cost 10-43
Table 10-11 Glossary of Natural Gas Terms Used in Documentation 10-44
Table 11-1 Fuel Oil Prices by NEMS Region in EPA Base Case v.5.13 11-1
Excerpt from Table 11-2 Biomass Supply Curves in EPA Base Case v.5.13 11-3
Table 11-3 Non-Electric Biomass Demand by Census Division in EPA Base Case v.5.13 11-4
Table 11-4 Waste Fuels in NEEDS v.5.13 and EPA Base Case v.5.13 11-5
Table 11-5 Fuel Emission Factor Assumptions in EPA Base Case v.5.13 11-6
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LIST OF FIGURES
Figure 1-1 Modeling and Data Structures in EPA Base Case v.5.13 1-4
Figure 2-1 Hypothetical Chronological Hourly Load Curve and Seasonal Load Duration Curve in EPA
Base Case v.5.13 2-8
Figure 2-2 Stylized Depiction of Load Duration Curve Used in EPA Base Case v.5.13 2-9
Figure 2-3 Stylized Dispatch Order in EPA Base Case v.5.13 2-10
Figure 3-1 EPA Base Case v.5.13 Model Regions 3-2
Figure 3-2 Scheduled Retirements of Existing Nuclear Capacity Under 60-Year Life Assumption 3-20
Figure 3-3 Modeling Process for Obtaining Projected NOX Emission Rates 3-23
Figure 3-4 How One of the Four NOX Modes Is Ultimately Selected fora Unit 3-24
Figure 5-1 Calculations Performed in Costing Lateral Pipeline Requirement 5-28
Figure 5-2 Number of Laterals Required per Boiler 5-29
Figure 5-3 Miles of Pipeline Required per Boiler 5-29
Figure 5-4 Diameter of Laterals 5-30
Figure 5-5 Total Inch-Miles of Laterals Required per Boiler 5-30
Figure 5-6 Total Cost to Each Boiler 5-31
Figure 5-7 Cost per kW of Boiler Capacity 5-31
Figure 9-1 Map of the Coal Supply Regions in EPA Base Case v.5.13 9-3
Figure 9-2 Coal Mine Productivity (2000-2011) 9-20
Figure 9-3 Average Annual Cost Growth Assumptions by Region (2012-2050) 9-20
Figure 9-4 Maximum Annual Coal Production Capacity 9-21
Figure 9-5 Illustration of Preliminary Step in Developing a Cumulative Coal Supply Curve 9-21
Figure 9-6 Illustration of Final Step in Developing a Cumulative Coal Supply Curve 9-22
Figure 9-7 Example Coal Supply Curve in Stepped Format 9-22
Figure 9-8 Calculation of Multi-Mode Transportation Costs (Example) 9-25
Figure 9-9 Rail Cost Indices Performance (2Q2008-4Q2011) 9-31
Figure 9-10 Long-Run Marginal Cost Breakdown by Transportation Mode 9-32
Figure 10-1 Modeling and Data Structure in EPA Base Case v.5.13 10-2
Figure 10-2 Natural Gas Module in EPA Base Case v.5.13 10-2
Figure 10-3 Gas Transmission Network Map 10-4
Figure 10-4 Gas Supply Regions Map 10-7
Figure 10-5 Gas Demand Regions Map 10-9
Figure 10-6 Natural Gas Storage Facility Node Map 10-15
Figure 10-7 Resource Cost Curves at the Beginning of Year 2015 10-21
Figure 10-8 Exploration & Development and Production Processes and Costs to Bring Undiscovered
Resource into Reserves and Production 10-22
Figure 10-9 E&D and Production Technology Improvement Factor 10-23
Figure 10-10 Incremental E&D Cost (BOY 2015) by Percentage of Dry Gas Resource Found 10-24
Figure 10-11 Drilling Rig Speed Constraint 10-27
Figure 10-12 North American LNG Supply Curves 10-29
Figure 10-13 North American LNG Regasification Facilities Map 10-30
Figure 10-14 Examples of Firm Demand Curves by Electric Load Segment 10-34
Figure 10-15 Examples of Interruptible Demand Curves by Electric Load Segment 10-34
Figure 10-16 LNG Export Assumptions in EPA Base Case v.5.13 10-35
Figure 10-17 New England Pipeline Corridors in 2020 10-36
Figure 10-18 Example Pipeline Discount Curve 10-37
Figure 10-19 Pipeline Cost Growth Factor 10-37
Figure 10-20 Storage Cost Growth Factor 10-41
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Figure 10-21 Example Maximum Storage Capacity Expansion 10-42
Figure 10-22 Crude Oil and NGL Prices 10-43
XII
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1. Introduction
This document describes the nature, structure, and capabilities of the Integrated Planning Model (IPM)
and the assumptions underlying the base case (designated EPA Base Case v.5.13) that was developed
by the U.S. Environmental Protection Agency (EPA) with technical support from ICF, Inc. (ICF). IPM is a
multi-regional, dynamic, deterministic linear programming model of the U.S. electric power sector. It
provides forecasts of least cost capacity expansion, electricity dispatch, and emission control strategies
while meeting energy demand and environmental, transmission, dispatch, and reliability constraints. IPM
can be used to evaluate the cost and emissions impacts of proposed policies to limit emissions of sulfur
dioxide (SO2), nitrogen oxides (NOX), carbon dioxide (CO2), mercury (Hg), and HCI from the electric
power sector.
This new base case (v.5.13) incorporates important structural improvements and data updates with
respect to the previous version (v.4.10). A new version number (moving from v.4 to v.5) indicates a
substantial change to Base Case architecture (such as this version's significant increase in the number of
model regions). Changing the portion of the version name after the 'dot' (moving from .10 to .13) indicates
the calibration of the model to more recent information (most importantly electricity demand projections)
from a particular iteration of the Energy Information Agency's (EIA) Annual Energy Outlook (AEO) , in this
caseAE02013.
Base cases, like EPA Base Case v.5.13, serve as the starting point against which policy scenarios are
compared. Base Case v.5.13 is a projection of electricity sector activity that takes into account only those
Federal and state air emission laws and regulations whose provisions were either in effect or enacted and
clearly delineated at the time the base case was finalized in August 2013 (prior to publication of this
documentation). Section 3.9 contains a detailed discussion of the environmental regulations included in
EPA Base Case v.5.13, which are summarized below.
EPA Base Case v.5.13 includes the Clean Air Interstate Rule (CAIR), a Federal regulatory measure
for achieving the 1997 National Ambient Air Quality Standards (NAAQS) for ozone (8-hour average of
0.08 ppm) and fine particles (24-hour average of 65 ug/m3 or less and annual average of 15 ug/m3
for particles of diameter 2.5 micrometers or less, i.e., PM 2.5). Originally issued on March 10, 2005,
CAIR was remanded back to EPA by the U.S. Court of Appeals for the District of Columbia Circuit in
December 2008 and EPA was required to correct legal flaws in the regulations that had been cited in
a ruling by the Court in July 2008. CAIR remains in effect until replaced by EPA pursuant to the
Court's ruling. CAIR's provisions were still in effect when EPA Base Case v.5.13 was released.
EPA Base Case v.5.13 includes NAAQS to the extent that state regulations included in EPA Base
Case v.5.13 contain measures to bring non-attainment areas into attainment. A summary of these
state regulations can be found in Appendix 3-2. Apart from these state regulations, individual permits
issued by states in response to NAAQS are captured (a) to the extent that they are reflected in the
NOX rates reported to EPA under CAIR, Title IV and the NOX Budget Program which are incorporated
in the base case and (b) to the extent that SO2 permit limits are used in the base case to define the
choice of coal sulfur grades that are available to specific power plants.
EPA Base Case v.5.13 includes the Mercury and Air Toxics Rule (MATS), which was finalized in
2011. MATS establishes National Emissions Standards for Hazardous Air Pollutants (NESHAPS) for
the "electric utility steam generating unit" source category.
EPA Base Case v.5.13 also reflects the final actions EPA has taken to implement the Regional Haze
Rule. This regulation requires states to submit revised State Implementation Plans (SIPs) that include
(1) goals for improving visibility in Class I areas on the 20% worst days and allowing no degradation
on the 20% best days and (2) assessments and plans for achieving Best Available Retrofit
Technology (BART) emission targets for sources placed in operation between 1962 and 1977. Since
2010, EPA has approved SIPs or, in a very few cases, put in place regional haze Federal
Implementation Plans for several states. The BART limits approved in these plans (as of August 29,
2013) that will be in place for EGUs are represented in the EPA Base Case v.5.13.
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Table 1-1 lists updates included in EPA Base Case v.5.13 listed in the order they appear in this
documentation report. Updates that are highlighted in gray were "non-routine" in the sense that they
constituted new modeling capabilities, notable extensions beyond the capabilities provided in previous
EPA base cases, or significant reviews of important assumptions.
Table 1-1 Updates in the EPA Base Case v.5.13
Description
For More
Information
Modeling Framework
Expansion of US model regions from 32 to 64
Incorporation of three stages of environmental retrofits
Section 3.1
Section 7.2
Power System Operation
Updated capacity deployment constraints (for new advanced coal with carbon capture,
carbon capture retrofits, and new nuclear)
Updated inventory of state emission regulations, including RGGI and AB32 (as of August
2013)
Updated inventories of NSR, state, and citizen settlements (as of August 201 3)
Updated transmission TTC's (2012-2013 ISO/RTO and NERC reports)
Updated regional reserve margins (NERC 2012)
AEO NEMS region level electricity demand is disaggregated to IPM model region level
Section 3.10 and
Attachment 3-1
Table 3-1 2
Table 3-1 3
Table 3-4 and
Table 3-5
Table 3-9
Table 3-2
Generating Resources
Updates to NEEDS, the database of existing and planned-committed units and their
emission control configurations (Primary Sources: 201 0, 201 1 EIA Form 860, ETS 201 1 ,
NERC ES&D 201 1 , AEO 201 3)
Updated cost and performance characteristics for potential (new) conventional, nuclear and
renewable generating units (AEO 2013 and NETL)
New renewable units including biomass, wind, solar, geothermal and landfill gas are
modeled at a state level within each IPM region (Resource assumptions from NREL)
Table 4-1
Table 4-1 3 and
Table 4-1 6
Section 4.4.5
Emission Control Technologies
Complete update of cost and performance assumptions for SO2, NOX, Hg and HCI emission
controls based on engineering studies by Sargent and Lundy
Updated cost and performance assumptions for coal-to-gas and retrofit options
Section 5.7
Set-Up Parameters and Rules
Modeling time horizon with seven model run years (2016, 2018, 2020, 2025, 2030, 2040,
2050)
CAIR, MATS, and BART are part of Base Case
All costs and prices are in 201 1 dollars
Section 7.1
Section 7.3
Financial assumptions
Update of discount and capital charge rate assumptions based on a hybrid capital cost
model of utility and merchant finance structures for new units
Use of separate capital charge rates for retrofits based on utility and merchant finance
structures
Section 8.2.2
Section 8.3.2
Coal
Complete update of coal supply curves and transportation matrix (Wood Mackenzie 2012-
2013 and Hellerworx 2012-2013)
Coal demand regions are now disaggregated to the coal facility (ORIS) level
Table 9-23 and
Table 9-24
Table 9-2
Natural Gas
Update of unconventional gas resource base (ICF 2013) Section 10.4
Other Fuels
Update of price assumptions for fuel oil, nuclear fuel and waste fuel (AEO 201 3)
Incorporation of biomass supply curves at a state level (AEO 2013)
Biomass storage costs are added to the agricultural residues component of the biomass
supply curves
Section 11.1
Section 11.2
Section 11.2
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Table 1-2 lists the types of plants included in the EPA Base Case v.5.13.
Table 1-2 Plant Types in EPA Base Case v.5.13
Fossil Fuel Fired
Coal Steam
Oil/Gas Steam
Combustion Turbine
Combined-Cycle Combustion Turbine
Integrated Gasification Combined-Cycle (IGCC) Coal
Advanced Coal with Carbon Capture
Fluidized Bed Combustion
Non-Fossil Fuel Fired
Nuclear
Renewables and Non-Conventional Technologies
Hydropower
Pumped Storage
Biomass
Onshore Wind
Offshore Shallow Wind
Offshore Deep Wind
Fuel Cells
Solar Photovoltaics
Solar Thermal
Geothermal
Landfill Gas
Other3
Note:
a Includes fossil and non-fossil waste plants.
Table 1-3 lists the emission control technologies available for meeting emission limits in EPA Base Case
v.5.13.
Table 1-3 Emission Control Technologies in EPA Base Case v.5.13
Sulfur Dioxide (SO2) and Hydrochloric Acid (HCI)
Limestone Forced Oxidation (LSFO)
Lime Spray Dryer (LSD)
Dry Sorbent Injection (with milled Trona)
FGD Upgrade Adjustment
Nitrogen Oxides (NOX)
Combustion controls
Selective catalytic reduction (SCR)
Selective non-catalytic reduction (SNCR)
Mercury (Hg)
Combinations of SO2, NOX,
Activated Carbon Injection
and particulate control technologies
Particulate Matter (PM)
Pulse-Jet Fabric Filter (FF)
Electrostatic Precipitator (ESP) Upgrade Adjustment
Carbon Dioxide (CO2)
Heat rate improvement
Coal-to-gas
Carbon Capture and Sequestration
Notes:
a Units may also select among different coal types to manage
emissions in EPA Base Case v.5.13.
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Figure 1-1 provides a schematic of the components of the modeling and data structure used for EPA
Base Case v.5.13. This report devotes a separate chapter to all the key components shown in Figure
1-1. Chapter 2 provides an overview of IPM's modeling framework (sometimes referred to as the "IPM
Engine"), highlighting the mathematical structure, notable features of the model, programming elements,
and model inputs and outputs. The remaining chapters are devoted to different aspects of EPA Base
Case v.5.13. Chapter 3 covers the power system operating characteristics captured in EPA Base Case
v.5.13. Chapter 4 explores the characterization of electric generation resources. Emission control
technologies (chapter 5) and carbon capture, transport and storage (chapter 6) are then presented.
Chapter 7 describes certain set-up rules and parameters employed in EPA Base Case v.5.13. Chapter 8
summarizes the base case financial assumptions. The last three chapters discuss the representation and
assumptions for fuels in the base case. Coal is covered in chapter 9, natural gas in chapter 10, and other
fuels (i.e., fuel oil, biomass, nuclear fuel, and waste fuels) in chapter 11 (along with fuel emission factors).
Figure 1-1 Modeling and Data Structures in EPA Base Case v.5.13
Emission Control
Technologies
Chapter 5
Sulfur Dioxide
Hydrogen Chloride
Nitrogen Oxides
Mercury
Carbon Capture and Storage
Participate Controls
Coal To Gas Conversion
Generation Resources
Chapter 4
Existing EGUst
Planned EGUs T
Potential New EGUs
Future Placeholder Technologies
Conditioned by
Short-term Capital Cost Adder
Regional Cost Adjustments
Capacity Deployment Constraints
\
CO2 Capture,
Transport, and
Storage
Chapter 6
Capture Technologies
Transportation
Storage Regions
\^
, IPM Eng
7 Chapte
/ n
/ Mnripl Di
Set-Up Rule
Paramete
Chapter 7
Run Years
Aggregation Schemes
Retrofit Assignments
Trading and Banking
Post-2040 Assumptia
/
ineft
,2
fnntc.
Power System Operation
: Chapter 3 1
Regional Configurations
Capacity Generation, and Dispatch Assumptions
Transmission Assumptions
Turndown Constraints
Reliability Constraints
Electricity Demand Growth
Environmental Regulations
Emissions
Costs
Capacity Expansion and Generation
Retrofit Decisions
Fuel Consumption and Prices
Electricity Usage and Prices
Parsing Outputs
Individual Boiler Level Data
Notes
Outputs for Air
Quality Modeling
Criteria Air Pollutants
Non-critena Air Pollutants
Toxics Air Pollutants
Point Source Locators
t Information on existing and planned electnc generating units (EGUs) is contained in (he National Electrical
Energy Data System (NEEDS) data base maintained for EPA by ICF International Planned EGUs are those
which were under construction or had obtained financing at the time that the EPA Base Case was finalized
ttlPM Engine is (he model structure described in Chapter 2
Financial Assumptions
I Chapter 8
Discount Rate
Capital Charge Rate
Book Life
Capital Cost Adder for Cftmate Uncertainty
Production Tax Credit
Investment Tax Credit
Coal & Other Fuel
Assumptions
Chapter 9 & 11
Coal
Fuel Oil
Nuclear Fuel
Biomass
Waste Fuels
Emission Factors
Natural Gas Module
(Endogenous)
I Chapter 10
North American Supply (from GMM
Hydrocarbon Supply Model)
Reserves and Resources
- Production Costs LNG Supply and Costs
Pipeline Network
Storage
Non-EGU Demand (Residential. Commercial.
Industrial)
Pncing Mechanism
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2. Modeling Framework
ICF developed the Integrated Planning Model (IPM) to support analysis of the electric sector. The EPA, in
addition to other state air regulatory agencies, utilities, and public and private sector clients, has used IPM
extensively for various air regulatory analyses, market studies, strategy planning, and economic impact
assessments.
The first section of this chapter provides a brief overview of the model's purpose, capabilities, and
applications. The following sections are devoted to describing the IPM model's structure and formulation,
key methodological characteristics, and programming features, including its handling of model inputs and
outputs. Readers may find some overlap between sections. For example, transmission decision
variables and constraints are covered in the discussion of model structure and formulation in section 2.2',
and transmission modeling is covered as a key methodological feature in section 2.3.8. The different
perspectives of each section are designed to provide readers with information that is complementary
rather than repetitive.
2.1 IPM Overview
IPM is a well-established model of the electric power sector designed to help government and industry
analyze a wide range of issues related to this sector. The model represents economic activities in key
components of energy markets - fuel markets, emission markets, and electricity markets. Since the
model captures the linkages in electricity markets, it is well suited for developing integrated analyses of
the impacts of alternative regulatory policies on the power sector. In the past, applications of IPM have
included capacity planning, environmental policy analysis and compliance planning, wholesale price
forecasting, and asset valuation.
2.1.1 Purpose and Capabilities
IPM is a dynamic linear programming model that generates optimal decisions under the assumption of
perfect foresight. It determines the least-cost method of meeting energy and peak demand requirements
over a specified period. In its solution, the model considers a number of key operating or regulatory
constraints (e.g. emission limits, transmission capabilities, renewable generation requirements, fuel
market constraints) that are placed on the power, emissions, and fuel markets. In particular, the model is
well-suited to consider complex treatment of emission regulations involving trading, banking, and special
provisions affecting emission allowances (like bonus allowances and progressive flow control), as well as
traditional command-and-control emission policies.
IPM represents power markets through model regions that are geographical entities with distinct
characteristics. While they are more numerous (for purposes of respecting smaller-scale transmission
limitations where adequate information was available), the model regions representing the U.S. power
market in EPA Base Case v.5.13 are largely consistent with the North American Electric Reliability
Council (NERC) assessment regions and with the organizational structures of the Regional Transmission
Organizations (RTOs) and Independent System Operators (ISOs), which handle dispatch on most of the
U.S. grid. IPM represents the least-cost arrangement of electricity supply (capacity and generation) within
each model region to meet assumed future load (electricity demand) while constrained by a transmission
network of bulk transfer limitations on interregional power flows. All existing utility power generation units,
including renewable resources, are modeled, as well as independent power producers and cogeneration
facilities that sell electricity to the grid.
IPM provides a detailed representation of new and existing resource options, including fossil generating
options (coal steam, gas-fired simple cycle combustion turbines, combined cycles, and oil/gas steam),
nuclear generating options, and renewable and non-conventional (e.g., fuel cells) resources. Renewable
resource options include wind, landfill gas, geothermal, solar thermal, solar photovoltaic and biomass.
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IPM can incorporate a detailed representation of fuel markets and can endogenously forecast fuel prices
for coal, natural gas, and biomass by balancing fuel demand and supply for electric generation. The
model also includes detailed fuel quality parameters to estimate emissions from electric generation.
IPM provides estimates of air emission changes, regional wholesale energy and capacity prices,
incremental electric power system costs, changes in fuel use, and capacity and dispatch projections.
2.1.2 Applications
IPM's structure, formulation and set-up make it very adaptable and flexible. The necessary level of data,
modeling capabilities exercised, and computational requirements can be tailored to the particular
strategies and policy options being analyzed. This adaptability has made IPM suitable for a variety of
applications. These include:
Air Regulatory Assessment: Since IPM contains extensive air regulatory modeling features, state and
federal air regulatory agencies have used the model extensively in support of air regulatory assessment.
Integrated Resource Planning: IPM can be used to perform least-cost planning studies that
simultaneously optimize demand-side options (load management and efficiency), renewable options and
traditional supply-side options.
Strategic Planning: IPM can be used to assess the costs and risks associated with alternative utility and
consumer resource planning strategies as characterized by the portfolio of options included in the input
data base.
Options Assessment: IPM allows industry and regulatory planners to "screen" alternative resource
options and option combinations based upon their relative costs and contributions to meeting customer
demands.
Cost and Price Estimation: IPM produces realistic estimates of energy prices, capacity prices, fuel
prices, and allowance prices. Industry and regulatory agencies have used these cost reports for due
diligence, planning, litigation and economic impact assessment.
2.2 Model Structure and Formulation
IPM employs a linear programming structure that is particularly well-suited for analysis of the electric
sector to help decision makers plan system capacity and model the dispatch of electricity from individual
units or plants. The model consists of three key structural components:
A linear "objective function,"
A series of "decision variables," and
A set of linear "constraints".
The sections below describe the objective function, key decision variables, and constraints included
in IPM for EPA Base Case v.5.13.
2.2.1 Objective Function
IPM's objective function is to minimize the total, discounted net present value, of the costs of meeting
demand, power operation constraints, and environmental regulations over the entire planning horizon.
The objective function represents the summation of all the costs incurred by the electricity sector on a net
present value basis. These costs, which the linear programming formulation attempts to minimize,
include the cost of new plant and pollution control construction, fixed and variable operating and
maintenance costs, and fuel costs. Many of these cost components are captured in the objective function
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by multiplying the decision variables by a cost coefficient. Cost escalation factors are used in the
objective function to reflect changes in cost overtime. The applicable discount rates are applied to derive
the net present value for the entire planning horizon from the costs obtained for all years in the planning
horizon.
2.2.2 Decision Variables
Decision variables represent the values for which the IPM model is solving, given the cost-minimizing
objective function described in section 2.2.1 and the set of electric system constraints detailed in section
2.2.3. The model determines values for these decision variables that represent the optimal least-cost
solution for meeting the assumed constraints. Key decision variables represented in IPM are described in
detail below.
Generation Dispatch Decision Variables: IPM includes decision variables representing the generation
from each model power plant.1 For each model plant, a separate generation decision variable is defined
for each possible combination of fuel, season, model run year, and segment of the seasonal load duration
curve applicable to the model plant. (See section 2.3.5 below for a discussion of load duration curves.) In
the objective function, each plant's generation decision variable is multiplied by the relevant heat rate and
fuel price (differentiated by the appropriate step of the fuel supply curve) to obtain a fuel cost. It is also
multiplied by the applicable variable operation and maintenance (VOM) cost rate to obtain the VOM cost
for the plant.
Capacity Decision Variables: IPM includes decision variables representing the capacity of each
existing model plant and capacity additions associated with potential (new) units in each model run year.
In the objective function, the decision variables representing existing capacity and capacity additions are
multiplied by the relevant fixed operation and maintenance (FOM) cost rates to obtain the total FOM cost
for a plant. The capacity addition decision variables are also multiplied by the investment cost and capital
charge rates to obtain the capital cost associated with the capacity addition.
Transmission Decision Variables: IPM includes decision variables representing the electricity
transmission along each transmission link between model regions in each run year. In the objective
function, these variables are multiplied by variable transmission cost rates to obtain the total cost of
transmission across each link.
Emission Allowance Decision Variables: For emission policies where allowance trading applies, IPM
includes decision variables representing the total number of emission allowances for a given model run
year that are bought and sold in that or subsequent run years. In the objective function, these year-
differentiated allowance decision variables are multiplied by the market price for allowances prevailing in
each run year. This formulation allows IPM to capture the inter-temporal trading and banking of
allowances.
Fuel Decision Variables: For each type of fuel and each model run year, IPM defines decision variables
representing the quantity of fuel delivered from each fuel supply region to model plants in each demand
region. Coal decision variables are further differentiated according to coal rank (bituminous, sub-
bituminous, and lignite), sulfur grade, chlorine content and mercury content (see Table 9-5). These fuel
quality decision variables do not appear in the IPM objective function, but in constraints which define the
types of fuel that each model plant is eligible to use and the supply regions that are eligible to provide fuel
to each specific model plant.
1 Model plants are aggregate representations of real-life electric generating units. They are used by IPM to model the
electric power sector. For a discussion of model plants in EPA Base Case v.5.13, see section 4.2.6.
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2.2.3 Constraints
Model constraints are implemented in IPM to accurately reflect the characteristics of and the conditions
faced by the electric sector. Among the key constraints included in EPA Base Case v.5.13 are:
Reserve Margin Constraints: Regional reserve margin constraints capture system reliability
requirements by defining a minimum margin of reserve capacity (in megawatts) per year beyond the total
capacity needed to meet future peak demand that must remain in service to that region. These reserve
capacity constraints are derived from reserve margin targets that are assumed for each region based on
information from reliability planning officials at NERC, RTOs or ISOs. If existing plus planned capacity is
not sufficient to satisfy the annual regional reserve margin requirement, the model will "build" the required
level of new capacity. Please see Section 3.6 for more information on reserve margin constraints.
Demand Constraints: The model categorizes regional annual electricity demand into seasonal load
segments which are used to form summer (May 1 - September 30) and winter (October 1 - April 30) load
duration curves (LDC). The seasonal load segments when taken together represent all the hourly
electricity load levels that must be satisfied in a region in the particular season for a particular model run
year. As such, the LDC defines the minimum amount of generation required to meet the region's
electrical demand during the specific season. These requirements are incorporated in the model's
demand constraints.
Capacity Factor Constraints: These constraints specify how much electricity each plant can generate
(a maximum generation level), given its capacity and seasonal availability.
Turn Down/Area Protection Constraints: The model uses these constraints to take into account the
cycling capabilities of the units, i.e., whether or not they can be shut down at night or on weekends, or
whether they must operate at all times, or at least at some minimum capacity level. These constraints
ensure that the model reflects the distinct operating characteristics of peaking, cycling, and base load
units.
Emissions Constraints: IPM can endogenously consider an array of emissions constraints for SO2,
NOX, HCI, mercury, and CO2. Emission constraints can be implemented on a plant-by-plant, regional, or
system-wide basis. The constraints can be defined in terms of a total tonnage cap (e.g., tons of SO2) or a
maximum emission rate (e.g., Ib/MMBtu of NOX). The scope, timing, and definition of the emission
constraints depend on the required analysis.
Transmission Constraints: IPM can simultaneously model any number of regions linked by
transmission lines. The constraints define either a maximum capacity on each link, or a maximum level of
transmission on two or more links (joint limits) to different regions.
Fuel Supply Constraints: These constraints define the types of fuel that each model plant is eligible to
use and the supply regions that are eligible to provide fuel to each specific model plant. A separate
constraint is defined for each model plant.
2.3 Key Methodological Features of IPM
IPM is a flexible modeling tool for obtaining short- and long-term projections of production activity in the
electric generation sector. The projections obtained using IPM are not statements of what will happen,
but they are estimates of what might happen given the assumptions and methodologies used. Chapters 3
to 11 contain detailed discussions of the cost and performance assumptions specific to the EPA Base
Case v.5.13. This section provides an overview of the essential methodological and structural features of
IPM that extend beyond the assumptions that are specific to EPA Base Case v.5.13.
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2.3.1 Model Plants
Model plants are a central structural component that IPM uses in three ways: (1) to represent
aggregations of existing generating units, (2) to represent retrofit and retirement options that are available
to existing units, and (3) to represent potential (new) units that the model can build.
Existing Units: Theoretically, there is no predefined limit on the number of units that can be included in
IPM. However, to keep model size and solution time within acceptable limits, EPA utilizes model plants to
represent aggregations of actual individual generating units. The aggregation algorithm groups units with
similar characteristics for representation by model plants with a combined capacity and weighted-average
characteristics that are representative of all the units comprising the model plant. Model plants are
defined to maximize the accuracy of the model's cost and emissions estimates by capturing variations in
key features of those units that are critical in the base case and anticipated policy case runs. For EPA
Base Case v.5.13, IPM employed an aggregation algorithm which allowed 16,330 actual existing electric
generating units to be represented by 4,971 model plants. Section 4.2.6 describes the aggregation
procedure used in the EPA Base Case v.5.13.
Retrofit and Retirement Options: IPM also utilizes model plants to represent the retrofit and retirement
options that are available to existing units. EPA Base Case v.5.13 provides existing model plants with a
wide range of options for retrofitting with emission control equipment as well as with an option to retire.
(See Chapters 5 and section 7.3 in Chapter 7 for a detailed discussion of the options that are included in
the EPA Base Case v.5.13.) EPA Base Case v.5.13 model plants that represent potential (new) units are
not given the option to take on a retrofit or retire.
The options available to each model plant are pre-defined at the model's set-up. The retrofit and
retirement options are themselves represented in IPM by model plants, which, if actuated in the course of
a model run, take on all or a portion of the capacity initially assigned to a model plant which represents
existing generating units2. In setting up IPM, parent-child-grandchild relationships are pre-defined
between each existing model plant (parent) and the specific retrofit and retirement model plants (children
and grandchildren) that may replace the parent model plant during the course of a model run. The "child"
and "grandchild" model-plants are inactive in IPM unless the model finds it economical to engage one of
the options provided, e.g., retrofit with particular emission controls or retire.
Theoretically, there are no limits on the number of "child," "grandchild," and even "great-grandchild" model
plants (i.e., retrofit and retirement options) that can be associated with each existing model plant.
However, model size and computational considerations dictate that the number of successive retrofits be
limited. In EPA Base Case v.5.13, a maximum of three stages of retrofit options are provided (child,
grandchild and great-grandchild). For example, an existing model plant may retrofit with a limestone
forced oxidation (LSFO) SO2 scrubber and with a selective catalytic reduction (SCR) control for NOX in
one model run year (stage 1), with an activated carbon injection (ACI) for mercury control in the same or
subsequent run year (stage 2) and with a CCS for CO2 control in the same or subsequent run year (stage
3). However, if it exercises this succession of retrofit options, no further retrofit or retirement options are
possible beyond the third stage.
Potential (New) Units: IPM also uses model plants to represent new generation capacity that may be
built during a model run. All the model plants representing new capacity are pre-defined at set-up,
differentiated by type of technology, regional location, and years available. When it is economically
advantageous to do so (or otherwise required by reserve margin constraints to maintain electric
reliability), IPM "builds" one or more of these predefined model plants by raising its generation capacity
from zero during the course of a model run. In determining whether it is economically advantageous to
"build" new plants, IPM takes into account cost differentials between technologies, expected technology
2 IPM has a linear programming structure whose decision variables can assume any value within the specified
bounds subject to the constraints. Therefore, IPM can generate solutions where model plants take retrofits/retire a
portion of the model plants capacity. IPM's standard model plant outputs explicitly present these partial investment
decisions.
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cost improvements (by differentiating costs based on a plant's vintage, i.e., build year) and regional
variations in capital costs that are expected to occur over time.
Since EPA Base Case v.5.13 results are presented at the model plant level, EPA has developed a post-
processor "parsing" tool designed to translate results at the model plant level into generating unit-specific
results. The parsing tool produces unit-specific emissions, fuel use, emission control retrofit and capacity
projections based on model plant results. Another post-processing activity involves deriving inputs for air
quality modeling from IPM outputs. This entails using emission factors to derive the levels of pollutants
needed in EPA's air quality models from emissions and other parameters generated by IPM. It also
involves using decision rules to assign point source locators to these emissions. (See Figure 1-1 for a
graphical representation of the relationship of the post-processing tools to the overall IPM structure. The
air quality ready flat file documentation is available at http://www.epa.gov/airmarkets/progsregs/epa-
ipm/BaseCase513.html)
2.3.2 Model Run Years
Another important structural feature of IPM is the use of model run years to represent the full planning
horizon being modeled. Mapping each year in the planning horizon into a representative model run year
enables IPM to perform multiple year analyses while keeping the model size manageable. Although IPM
reports results only for model run years, it takes into account the costs in all years in the planning horizon.
(See section 2.3.3 below for further details.)
Often models like IPM include a final model run year that is not included in the analysis of results. This
technique reduces the likelihood that modeling results in the last represented year will be skewed due to
the modeling artifact of having to specify an end point in the planning horizon, whereas, in reality,
economic decision-making will continue to take information into account from years beyond the model's
time horizon. Due to the number of model run years required by EPA for analytical purposes (seven in
the 2016-2050 time period) and a greatly expanded suite of modeling capabilities, such an approach
could not be used in EPA Base Case v.5.13. It would have increased the model's size beyond
acceptable solution time constraints. However, boundary distortions are a potential factor only for results
in 2050, the last modeled year. In addition, any tendency toward end-year distortions should be reduced
by the longer modeling time horizon of this base case and by the relatively large number of calendar
years (9) that are mapped into model run year 2050 (see Table 7-1)3. Nevertheless, the possibility of
residual boundary effects is something to bear in mind when interpreting the model's results from the
2050 run year.
2.3.3 Cost Accounting
As noted earlier in the chapter, IPM is a dynamic linear programming model that finds the least cost
investment and electricity dispatch strategy for meeting electricity demand subject to resource availability
and other operating and environmental constraints. The cost components that IPM takes into account in
deriving an optimal solution include the costs of investing in new capacity options, the cost of installing
and operating pollution control technology, fuel costs, and the operation and maintenance costs
associated with unit operations. Several cost accounting assumptions are built into IPM's objective
function that ensures a technically sound and unbiased treatment of the cost of all investment options
offered in the model. These features include:
3 The primary impact of end year distortion occurs on the investment decisions as they are made by the model while
accounting for costs and revenues over a short (number of years mapped to that run year) time period. As the
number of years mapped to the last run year increases, more of the costs and revenues of the plant's life are
captured and thus improving the quality of the decision.
The longer modeling horizon does not directly reduce the end year distortion. However, the discounting occurring
over a longer time period does reduce the impact of the end year results on the overall model solution.
2-6
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All costs in IPM's single multi-year objective function are discounted to a base year. Since the model
solves for all run years simultaneously, discounting to a common base year ensures that IPM properly
captures complex inter-temporal cost relationships.
Capital costs in IPM's objective function are represented as the net present value of levelized stream of
annual capital outlays, not as a one-time total investment cost. The payment period used in calculating
the levelized annual outlays never extends beyond the model's planning horizon: it is either the book life
of the investment or the years remaining in the planning horizon, whichever is shorter. This approach
avoids presenting artificially higher capital costs for investment decisions taken closer to the model's time
horizon boundary simply because some of that cost would typically be serviced in years beyond the
model's view. This treatment of capital costs ensures both realism and consistency in accounting for the
full cost of each of the investment options in the model.
The cost components informing IPM's objective function represent the composite cost over all years in
the planning horizon rather than just the cost in the individual model run years. This permits the model to
capture more accurately the escalation of the cost components overtime.
2.3.4 Modeling Wholesale Electricity Markets
Another important methodological feature worth noting about IPM is that it is designed to simulate
electricity production activity in a manner that would minimize production costs, as is the intended
outcome in wholesale electricity markets. For this purpose, the model captures transmission costs and
losses between IPM model regions, but it is not designed to capture retail distribution costs. However,
the model implicitly includes distribution losses since net energy for load,4 rather than delivered sales,5 is
used to represent electricity demand in the model. Additionally, the production costs calculated by IPM
are the wholesale production costs. In reporting costs, the model does not include embedded costs, such
as carrying charges of existing units, that may ultimately be part of the retail cost incurred by end-use
consumers.
2.3.5 Load Duration Curves (LDC)
IPM uses Load Duration Curves (LDCs) to provide realism to the dispatching of electric generating units.
Unlike a chronological electric load curve, which is simply an hourly record of electricity demand, the
LDCs are created by rearranging the hourly chronological electric load data from the highest to lowest
(MW) value. In order to aggregate such load detail into a format enabling this scale of power sector
modeling, EPA applications of IPM use a 6-step piecewise linear representation of the LDC.
IPM can include any number of separate LDCs for any number of user-defined seasons. A season can
be a single month or several months. For example, EPA Base Case v.5.13 contains two seasons:
summer (May 1 - September 30) and winter (October 1- April 30). Separate summer and winter LDCs
are created for each of IPM's model regions. Figure 2-1 below presents side-by-side graphs of a
hypothetical chronological hourly load curve and a corresponding load duration curve for a season
consisting of 3,672 hours.
4 Net energy for load is the electrical energy requirements of an electrical system, defined as system net generation,
plus energy received from others, less energy delivered to others through interchange. It includes distribution losses.
5 Delivered sales is the electrical energy delivered under a sales agreement. It does not include distribution losses.
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Figure 2-1 Hypothetical Chronological Hourly Load Curve and Seasonal Load Duration Curve
in EPA Base Case v.5.13
Chronological Hourly Load Curve
Seasonal Load Duration Curve
MW
Hours in Season
3672
Hours in Season
3672
Regional forecasts of peak and total electricity demand (from AEO 2013 for EPA Base Case v5.13) and
hourly load curves from FERC Form 714 and ISO/RTOs (2011 for EPA Base Case v5.13) are used to
derive future seasonal load duration curves for each IPM run year in each IPM region. The results of this
process are individualized seasonal LDCs that capture the unique hourly electricity demand profile of
each region. The LDCs change overtime to reflect projected changes in load factors.
Within IPM, LDCs are represented by a discrete number of load segments, or generation blocks, as
illustrated in Figure 2-2. EPA Base Case v.5.13 uses six load segments in its seasonal LDCs for model
run years 2016-2030 and four load segments in its LDCs for model run years 2040 and 2050. The
reduced number of load segments in the later years was adopted out of model size considerations and a
view that having a finer grained representation of dispatch was less important that far into the future.
Figure 2-2 illustrates and the following text describes the 6-segment LDCs used in the base case's earlier
years. Length of time and system demand are the two parameters which define each segment of the load
duration curve. The load segment represents the amount of time (along the x-axis) and the capacity that
the electric dispatch mix must be producing (represented along the y-axis) to meet system load.
Segment 1 in Figure 2-2 generally contains one percent of the hours in the period (i.e., "season") but
represents the highest load demand value. IPM has the flexibility to model any number of load segments;
however, the greater the number of segments, the greater the computational time required to reach a
solution. The LDC shows all the hourly electricity load levels that must be satisfied in a region in a
particular season of a particular model run year. Segment 1 (the "super peak" load segment with 1 % of
all the hours in the season) and Segment 2 (the "peak" load segment with 4% of all the hours in the
season) represent all the hours when load is at the highest demand levels. Segments 2 through 6
represent hourly loads at progressively lower levels of demand. Plants are dispatched to meet this load
based on economic considerations and operating constraints. The most cost effective plants are
assigned to meet load in all 6 segments of the load duration curve. This is discussed in greater detail in
section 2.3.6 below. In 2040 and 2050 run years, segments 1 & 2 are aggregated into a single segment
and segments 3 & 4 are aggregated into a single segment for a total of 4 segments.
Use of seasonal LDCs rather than annual LDCs allows IPM to capture seasonal differences in the level
and patterns of customer demand for electricity. For example, in most regions air conditioner cycling only
impacts customer demand patterns during the summer season. The use of seasonal LDCs also allows
IPM to capture seasonal variations in the generation resources available to respond to the customer
demand depicted in an LDC. For example, power exchanges between utility systems may be seasonal in
nature. Some air regulations affecting power plants are also seasonal in nature. This can impact the type
of generating resources that are dispatched during a particular season. Further, because of maintenance
2-8
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scheduling for individual generating units, the capacity and utilization for these supply resources also vary
between seasons.
Attachment 2-1 contains data of the 2012 summer and winter load duration curves in each of the 64
model regions in the lower continental U.S. for EPA Base Case v.5.13.
Figure 2-2 Stylized Depiction of Load Duration Curve Used in EPA Base Case v.5.13
Stylized Six Segment Load Duration Curve
Load
(MW)
Segment 1 Segment 2
Percentage of Hours:
Segment 1 -1%
Segment 4 - 30%
Segment 2-4%
Segment 5 - 30%
Duration (Hours)
Segments -10%
Segments -25%
2.3.6 Dispatch Modeling
In IPM, the dispatching of electricity is based on the variable cost of generation. In the absence of any
operating constraints, units with the lowest variable cost generate first. The marginal generating unit, i.e.,
the power plant that generates the last unit of electricity, sets the energy price. Physical operating
constraints also influence the dispatch order. For example, IPM uses turndown constraints to prevent
base load units from cycling, i.e., switching on and off. Turndown constraints often override the dispatch
order that would result based purely on the variable cost of generation. Variable costs in combination
with turndown constraints enable IPM to dispatch generation resources in a technically realistic fashion.
Figure 2-3 below depicts a highly stylized dispatch order based on the variable cost of generation of the
resource options included in the EPA Base Case v.5.13. In Figure 2-3, a hypothetical load duration curve
is subdivided according to the type of generation resource that responds to the load requirements
represented in the curve. Notice that the generation resources with the lowest operating cost (i.e., hydro
and nuclear) respond first to the demand represented in the LDC and are accordingly at the bottom of
"dispatch stack." They are dispatched for the maximum possible number of hours represented in the LDC
because of their low operating costs. Generation resources with the highest operating cost (e.g., peaking
turbines) are at the top of the "dispatch stack," since they are dispatched last and for the minimum
possible number of hours.
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Figure 2-3 Stylized Dispatch Order in EPA Base Case v.5.13
MW
Combustion Turbine
Oil/Gas Steam
Gas Combined Cycle
Coal Steam
Nuclear
Hydro
Hours
Note: Figure 2-3 does not include all the plant types that are modeled in EPA Base Case v.5.13.
Intermittent renewable technologies such as wind and solar are considered non dispatchable and are
assigned a specific hourly generation profile.
2.3.7 Fuel Modeling
Another key methodological feature of IPM is its capability to model the full range of fuels used for electric
power generation. The cost, supply, and (if applicable) quality of each fuel included in the model are
defined during model set-up. Fuel price and supply are represented in EPA Base Case v.5.13 in one of
three alternative ways: (1) through an embedded modeling capability that dynamically balances supply
and demand to arrive at fuel prices (natural gas), (2) through a set of supply curves (coal and biomass) or
(3) through an exogenous price stream (fuel oil and nuclear fuel). With the first and second approaches,
the model endogenously determines the price for that fuel by balancing the supply and demand. IPM
uses fuel quality information (e.g., the sulfur, chlorine or mercury content of different types of coal from
different supply regions) to determine the emissions resulting from combustion of that fuel.
EPA Base Case v.5.13 includes coal, natural gas, fuel oil, nuclear fuel, biomass, and fossil and non-fossil
waste as fuels for electric generation. The specific base case assumptions for these fuels are examined
in chapters 9 to 11.
2.3.8 Transmission Modeling
IPM includes a detailed representation of existing transmission capabilities between model regions. The
maximum transmission capabilities between regions are specified in IPM's transmission constraints. Due
to uncertainty surrounding the building of new transmission lines in the U.S., EPA Base Case v5.13 does
not exercise IPM's capability to model the building of new transmission lines. However, that capacity of
the model is described here in case it is applied in future analyses. Additions to transmission lines are
represented by decision variables defined for each eligible link and model run year. In IPM's objective
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function, the decision variables representing transmission additions are multiplied by new transmission
line investment cost and capital charge rates to obtain the capital cost associated with the transmission
addition. The specific transmission assumptions in EPA Base Case v.5.13 are described in section 3.3.
2.3.9 Perfect Competition and Perfect Foresight
Two key methodological features of IPM are its assumptions of perfect competition and perfect foresight.
The former means that IPM models production activity in wholesale electric markets on the premise that
these markets subscribe to all assumptions of perfect competition. The model does not explicitly capture
any market imperfections such as market power, transaction costs, informational asymmetry or
uncertainty. However, if desired, appropriately designed sensitivity analyses or redefined model
parameters can be used to gauge the impact of market imperfections on the wholesale electric markets.
IPM's assumption of perfect foresight implies that agents know precisely the nature and timing of
conditions in future years that affect the ultimate costs of decisions along the way. For example, under
IPM there is complete foreknowledge of future electricity demand, fuel supplies, and other variables
(including regulatory requirements) that in reality are subject to uncertainty and limited foresight.
Modelers frequently assume perfect foresight in order to establish a decision-making framework that can
estimate cost-minimizing courses of action given the best-guess expectations of these future variables
that can be constructed at the time the projections are made.
2.3.10 Air Regulatory Modeling
One of the most notable features of IPM is its detailed and flexible modeling of air regulations. Treatment
of air regulations is endogenous in IPM. That is, by providing a comprehensive representation of
compliance options, IPM enables environmental decisions to be made within the model based on least
cost considerations, rather than exogenously imposing environmental choices on model results. For
example, unlike other models that enter allowance prices as an exogenous input during model set-up,
IPM obtains allowance prices as an output of the endogenous optimization process of finding the least
cost compliance options in response to air regulations. (In linear programming terminology, they are the
"shadow prices" of the respective emission constraints a standard output produced in solving a linear
programming problem.) IPM can capture a wide variety of regulatory program designs including
emissions trading policies, command-and-control policies, and renewable portfolio standards. IPM's
representation of emissions trading policies can include allowance banking, trading, borrowing, bonus
allowance mechanisms, and progressive flow controls. Air regulations can be tailored to specific
geographical regions and can be restricted to specific seasons. Many of these regulatory modeling
capabilities are exploited in EPA Base Case v.5.13.
2.4 Hardware and Programming Features
IPM produces model files in standard MPS linear programming format. IPM runs on most PC-platforms.
Its hardware requirements are highly dependent on the size of a particular model run. For example, with
almost 16.6 million decision variables and 1.8 million constraints, EPA Base Case v.5.13 is run on a 64 bit
Enterprise Server - Windows 2008 R2 platform with two Intel Xeon X5675 3.07 GHz processors and 72
GB of RAM. Due to the size of the EPA base case, a commercial grade solver is required.
(Benchmarking tests performed by EPA's National Environmental Scientific Computing Center using
research grade solvers yielded unacceptable results.) For current EPA applications of IPM, the FICO
Xpress Optimization Suite 7.5 (64 bit with multi-threads barrier and MIP capabilities) linear programming
solvers are used.
Two data processors - a front-end and the post-processing tool - support the model. The front-end
creates the necessary inputs to be used in IPM, while the post-processing tool maps IPM model-plant
level outputs to individual generating units (a process called "parsing," see section 2.3.1) and creates
input files in flat file format as needed by EPA's air quality models.
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Before it can be run, the model requires an extensive set of input parameters. These are discussed in
Section 2.4.1 below. Results of model runs are presented in a series of detailed reports. These are
described in Section 2.4.2 below.
2.4.1 Data Parameters for Model Inputs
IPM requires input parameters that characterize the US electric system, economic outlook, fuel supply
and air regulatory framework. Chapters 3-11 contain detailed discussions of the values assigned to these
parameters in EPA Base Case v.5.13. This section simply lists the key input parameters required by IPM:
Electric System
Existing Generating Resources
Plant Capacities
Heat Rates
Maintenance Schedule
Forced Outage Rate
Minimum Generation Requirements (Turn Down Constraint)
Fuels Used
Fixed and Variable O&M Costs
Emissions Limits or Emission Rates for NOX, SO2, HCI, CO2, Mercury
Existing Pollution Control Equipment and Retrofit Options
Output Profile for Non-Dispatchable Resources
New Generating Resources
Cost and Operating Characteristics
Performance Characteristics
Limitations on Availability
Other System Requirements
Inter-regional Transmission Capabilities
Reserve Margin Requirements for Reliability
Area Protection
System Specific Generation Requirements
Regional Specification
Economic Outlook
Electricity Demand
Firm Regional Electricity Demand
Load Curves
Financial Outlook
Capital Charge Rate
Discount Rate
Fuel Supply
Fuel Supply Curves for Coal and Biomass
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Embedded Natural Gas Model
Fuel Price
Fuel Quality
Transportation Costs for Coal, Natural Gas, and Biomass
Air Regulatory Outlook
Air Regulations for NOX, SO2, HCI, CO2, and Mercury
Other Air Regulations
2.4.2 Model Outputs
IPM produces a variety of output reports. These range from extremely detailed reports, which describe
the results for each model plant and run year, to summary reports, which present results for regional and
national aggregates. Individual topic areas can be included or excluded at the user's discretion. Standard
IPM reports cover the following topics:
Generation
Capacity mix
Capacity additions and retirements
Capacity and energy prices
Power production costs (capital, VOM, FOM and fuel costs)
Fuel consumption
Fuel supply and demand
Fuel prices for coal, natural gas, and biomass
Emissions (NOX, SO2, HCI, CO2, and Mercury)
Emission allowance prices
2-13
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Attachment 2-1 Load Duration Curves3 Used in EPA Base Case v.5.13
This is a small excerpt of the data in Attachment 2-1. The complete data set in spreadsheet format can be downloaded via the link found at
www.epa.qov/airmarkets/proqsreqs/epa-ipm/BaseCasev513.htm
Month
Hours
Day
Hours
ERC
REST
ERC
WEST
FRCC
MAP
WAU
E
MIS I
A
MIS I
L
MIS I
NKY
MIS
LMI
MIS
MAPP
MIS
MIDA
MIS
MNWI
MIS
MO
MIS
WUM
S
NENG
_CT
NENG
_ME
NENG
REST
NY Z
_ASB
1
1
1
29,087
2,655
17,709
2,551
2,332
5,892
10,885
10,211
967
3,205
10,338
5,133
5,657
3,117
954
7,761
2,064
1
2
2
29,081
2,678
16,861
2,528
2,308
5,842
10,709
9,916
943
3,172
10,083
5,049
5,529
3,006
878
7,478
2,003
1
3
3
29,428
2,726
16,336
2,531
2,276
5,823
10,617
9,712
927
3,128
9,916
5,004
5,462
2,948
850
7,318
1,955
1
4
4
30,073
2,765
16,045
2,545
2,266
5,855
10,588
9,605
919
3,115
9,828
4,988
5,427
2,921
851
7,265
1,945
1
5
5
31,131
2,836
15,996
2,577
2,262
5,911
10,645
9,552
916
3,109
9,799
5,022
5,429
2,932
874
7,278
1,958
1
6
6
32,672
2,903
16,303
2,654
2,275
6,045
10,757
9,557
920
3,127
9,841
5,073
5,476
2,969
919
7,413
1,996
1
7
7
33,837
2,961
16,879
2,733
2,324
6,207
11,010
9,629
930
3,194
9,949
5,205
5,580
3,047
997
7,680
2,057
1
8
8
34,243
3,110
17,602
2,749
2,372
6,299
11,302
9,793
956
3,260
10,226
5,358
5,732
3,145
1,111
7,987
2,132
1
9
9
33,469
2,989
19,095
2,772
2,408
6,319
11,470
10,034
980
3,310
10,474
5,446
5,832
3,308
1,238
8,432
2,201
1
10
10
32,063
2,762
20,808
2,750
2,433
6,281
11,525
10,198
993
3,345
10,620
5,465
5,944
3,466
1,343
8,906
2,288
1
11
11
30,593
2,582
21,921
2,746
2,440
6,250
11,482
10,389
1,000
3,354
10,697
5,423
6,032
3,555
1,399
9,194
2,352
1
12
12
29,370
2,490
22,566
2,692
2,442
6,204
11,438
10,547
1,001
3,357
10,701
5,391
6,075
3,608
1,399
9,357
2,393
1
13
13
28,122
2,358
22,995
2,666
2,437
6,143
11,368
10,623
994
3,350
10,631
5,345
6,104
3,635
1,403
9,419
2,435
1
14
14
27,173
2,249
23,070
2,628
2,414
6,071
11,272
10,680
992
3,318
10,611
5,289
6,101
3,620
1,369
9,401
2,444
1
15
15
26,764
2,188
22,956
2,661
2,400
6,019
11,157
10,675
984
3,299
10,519
5,218
6,100
3,602
1,343
9,354
2,457
1
16
16
27,133
2,181
22,784
2,786
2,393
6,059
11,088
10,675
977
3,289
10,451
5,170
6,095
3,642
1,336
9,432
2,471
1
17
17
29,534
2,350
22,750
2,939
2,431
6,313
11,206
10,665
985
3,341
10,532
5,213
6,191
3,856
1,515
10,064
2,565
1
18
18
32,765
2,603
23,609
2,943
2,526
6,693
11,701
10,839
1,022
3,472
10,928
5,462
6,523
4,069
1,645
10,580
2,757
1
19
33,125
2,716
25,136
2,885
2,620
6,774
12,306
11,503
1,080
3,602
11,552
5,820
6,739
4,053
1,595
10,519
2,776
1
20
20
33,279
2,750
24,741
2,805
2,596
6,765
12,417
11,984
1,089
3,569
11,648
5,892
6,732
3,988
1,516
10,300
2,752
1
21
21
32,700
2,749
23,876
2,756
2,573
6,691
12,382
11,971
1,073
3,536
11,470
5,882
6,663
3,894
1,420
9,987
2,701
1
22
22
31,281
2,713
22,478
2,637
2,536
6,539
12,225
11,813
1,051
3,486
11,235
5,810
6,499
3,736
1,258
9,496
2,608
1
23
23
29,582
2,593
20,971
2,562
2,442
6,333
11,929
11,458
1,020
3,356
10,904
5,664
6,288
3,531
1,128
8,896
2,465
1
24
24
28,464
2,579
19,160
2,490
2,348
6,149
11,548
11,025
976
3,227
10,430
5,467
6,063
3,330
1,025
8,332
2,317
1
25
1
28,103
2,565
17,682
2,478
2,292
6,066
11,230
10,605
945
3,150
10,108
5,299
5,884
3,211
970
7,986
2,215
1
26
2
28,113
2,585
16,839
2,502
2,259
6,039
11,087
10,292
926
3,105
9,898
5,225
5,793
3,141
935
7,797
2,166
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3. Power System Operation Assumptions
This section describes the assumptions pertaining to the North American electric power system as
represented in EPA Base Case v.5.13.
3.1 Model Regions
EPA Base Case v.5.13 models the US power sector in the contiguous 48 states and the District of
Columbia and the Canadian power sector in the 10 provinces (with Newfoundland and Labrador
represented as two regions on the electricity network even though politically they constitute a single
province6) as an integrated network.
There are 64 IPM model regions covering the US 48 states and District of Columbia. The IPM model
regions are approximately consistent with the configuration of the NERC assessment regions in the
NERC Long-Term Reliability Assessments. These IPM model regions reflect the administrative structure
of regional transmission organizations (RTOs) and independent system operators (ISOs). Further
disaggregation of the NERC assessment regions and RTOs allows a more accurate characterization of
the operation of the US power markets by providing the ability to represent transmission bottlenecks
across RTOs and ISOs, as well as key transmission limits within them.
The IPM regions also provide disaggregation of the regions of the National Energy Modeling System
(NEMS) to provide for a more accurate correspondence with the demand projections of the Annual
Energy Outlook (AEO). Notable disaggregations are further described below:
NERC assessment regions MISO and PJM cover the areas of the corresponding RTOs and are designed
to better represent transmission limits and dispatch in each area. In IPM, the MISO area is disaggregated
into 9 IPM regions and the PJM assessment area is disaggregated into 9 IPM regions, where the IPM
regions are selected to represent planning areas within each RTO and/or areas with internal transmission
limits.
New York is now disaggregated into 7 IPM regions, to better represent flows around New York City and
Long Island, and to better represent flows across New York state from Canada and other US regions.
The NERC assessment region SERC is divided into North, South, West and Southeast areas; IPM further
disaggregates the North and West areas to better represent transmission between areas, including
disaggregating SERC-West into four IPM regions to reflect transmission constraints in Southern
Louisiana.
IPM retains the NERC assessment areas within the overall WECC regions, and further disaggregates
these areas using sub-regions from the WECC Power Supply Assessment.
The 11 Canadian model regions are defined strictly along provincial political boundaries.
Figure 3-1 contains a map showing all the EPA Base Case 5.13 model regions. Using these shares of
each NEMS region net energy for load that falls in each IPM region, calculate the total net energy for load
for each IPM region from the NEMS regional load in AEO 2013.
Table 3-1 defines the abbreviated region names appearing on the map and gives a crosswalk between
the IPM model regions, the NERC assessment regions, and regions used in the Energy Information
Administration's (ElA's) National Energy Model System (NEMS) which is the basis for ElA's Annual
Energy Outlook (AEO) reports.
' This results in a total of 11 Canadian model regions being represented in EPA Base Case v.5.13.
3-1
-------
3.2 Electric Load Modeling
Net energy for load and net internal demand are inputs to IPM that together are used to represent the
grid-demand for electricity. Net energy for load is the projected annual electric grid-demand, prior to
accounting for intra-regional transmission and distribution losses. Net internal demand (peak demand) is
the maximum hourly demand within a given year after removing interruptible demand. Table 3-2 shows
the electricity demand assumptions (expressed as net energy for load) used in EPA Base Case v.5.13. It
is based on the net energy for load in AEO 2013.7
Figure 3-1 EPA Base Case v.5.13 Model Regions
WEC_LADW
WEC_SDGE
WECCJID
For purposes of documentation, Table 3-2 presents the national net energy for load. However, EPA Base
Case v.5.13 models regional breakdowns of net energy for load in each of the 64 IPM US regions in the
following steps:
The net energy for load in each of the 22 NEMS electricity regions is taken from the NEMS reference
case.
NERC balancing areas are assigned to both IPM regions and NEMS regions to determine the share
of the NEMS net energy for load in each NEMS regions that falls into each IPM region. These shares
are calculated in the following steps.
Map the NERC Balancing Authorities/ Planning Areas in the US to the 64 IPM regions.
7 The electricity demand in EPA Base Case v.5.13 for the U.S. lower 48 states and the District of Columbia is
obtained for each IPM model region by disaggregating the "Total Net Energy for Load" projected for the
corresponding NEMS Electric Market Module region as reported in the Electricity and Renewable Fuel Tables 73-
120" at http://www.eia.gov/forecasts/aeo/tables ref.cfm.
3-2
-------
Map the Balancing Authorities/ Planning Areas in the US to the 22 NEMS regions.
Using the 2007 data from FERC Form 714 on net energy for load in each of the balancing areas,
calculate the proportional share of each of the net energy for load in 22 NEMS regions that falls in
each of the 64 IPM Regions.
Using these shares of each NEMS region net energy for load that falls in each IPM region, calculate
the total net energy for load for each IPM region from the NEMS regional load in AEO 2013.
Table 3-1 Mapping of NERC Regions and NEMS Regions with EPA Base Case
v.5.13 Model Regions
NERC Assessment
Region
ERGOT3
FRCC
MAPP
MISO
ISO-NE
NYISO
PJM
SERC-E
SERC-N
AEO 201 3 NEMS
Region
ERCT(1)
FRCC (2)
MROW (4)
MROE(3), RFCW(11)
MROW (4)
RFCM(10)
RFCW(11), SRCE
(15)
SRGW(13)
NEWE (5)
NYCW (6)
NYLI (7)
NYUP (8)
NYUP (8), NYCW (6)
RFCE(9)
RFCW(11)
SRVC(16)
SRVC(16)
SRCE (15)
Model
Region
ERC_FRNT
ERC_GWAY
ERC_REST
ERC WEST
FRCC
MAP_WAUE
MIS MAPP
MIS WUMS
MISJA
MIS_MIDA
MIS MNWI
MIS LMI
MIS INKY
MISJL
MIS MO
NENG_CT
NENG_ME
NENGREST
NY_Z_J
NY Z K
NY_Z_A&B
NY_Z_C&E
NY_Z_D
NY Z F
NY Z G-l
PJM_EMAC
PJM_PENE
PJM_SMAC
PJM WMAC
PJM_AP
PJM_ATSI
PJM_COMD
PJM West
PJM Dom
S_VACA
S_C_KY
Model Region Description
ERCOT_Tenaska Frontier Generating Station
ERCOT_Tenaska Gateway Generating
Station
ERCOT_Rest
ERGOT West
FRCC
MAPP_WAUE
MISO MT, SD, ND
MISO Wisconsin- Upper Michigan (WUMS)
MISOJowa
MISO_lowa-MidAmerican
MISO Minnesota and Western Wisconsin
MISO Lower Michigan
MISO Indiana (including parts of Kentucky)
MISOJIIinois
MISO Missouri
ISONE_Connecticut
ISONE_Maine
ISONE_MA, VT, NH, Rl (Rest of ISO New
England)
NY_Zone J (NYC)
NY_Zone K (LI)
NY_Zones A&B
NY_Zone C&E
NY_Zones D
NY_Zone F (Capital)
NY_Zone G-l (Downstate NY)
PJM_EMAAC
PJM_PENELEC
PJM_SWMAAC
PJM Western MAAC
PJM_AP
PJM_ATSI
PJM_ComEd
PJM West
PJM Dominion
SERC_VACAR
SERC Central Kentucky
3-3
-------
NERC Assessment
Region
SERC-SE
SERC-W
SPPb
Basin (BASN)
Northern California
(CALM)
Southern California
(CALS)
Northwest (NORW)
Rockies (Rock)
Desert Southwest (DSW)
Canada
AEO2013NEMS
Region
SRSE(14)
SRDA(12)
SRDA(12), SRCE(15)
MROW (4)
SPNO(17), SRGW
(13)
SPSO(18)
SPSO(18), SRDA(12)
NWPP(21)
CAMX (20)
AZNM(19)
CAMX (20)
NWPP(21)
NWPP(21), RMPA
(22)
RMPA (22)
AZNM(19)
Model
Region
S_C_TVA
S_SOU
S_D_AMSO
S_D_WOTA
S_D_REST
S D N AR
SPP NEBR
SPP N
SPP_KIAM
SPP_SE
SPP_SPS
SPP WEST
WECCJD
WECC_NNV
WECC_UT
WEC_CALN
WECC SF
WECC I ID
WEC_LADW
WEC_SDGE
WECC SCE
WECC_MT
WECC PN
W
WECC_WY
WECC_CO
WECC_AZ
WECC_NM
WECC_SNV
CN_AB
CN_BC
CN_MB
CN_NB
CN_NF
CN_NL
CN_NS
CN_ON
CN_PE
CN_PQ
CN_SK
Model Region Description
SERC_Central_TVA
SERC_Southeastern
SERC_Delta_Amite South (including DSG)
SERC_Delta_WOTAB (including Western)
SERC_Delta_Rest of Delta (Central Arkansas)
SERC Delta Northern Arkansas (including
AECI)
SPP Nebraska
SPP North- (Kansas, Missouri)
SPP_Kiamichi Energy Facility
SPP Southeast (Louisiana)
SPP SPS (Texas Panhandle)
SPP West (Oklahoma, Arkansas, Louisiana)
WECCJdaho
WECC_Northern Nevada
WECC_Utah
WECC_Northern California (including SMUD)
WECC San Francisco
WECC Imperial Irrigation District (IID)
WECC_LADWP
WECC_San Diego Gas and Electric
WECC Southern California Edison
WECC_Montana
WECC Pacific Northwest
WECC_Wyoming
WECC_Colorado
WECC_Arizona
WECC_New Mexico
WECC_Southern Nevada
Alberta
British Columbia
Manitoba
New Brunswick
Newfoundland
Labrador
Nova Scotia
Ontario
Prince Edward Island
Quebec
Saskatchewan
.FRNT) and ERCOT_Tenaska Gateway Generating Station (ERC_GWAY)
internal demand created to capture the ability to sell power to multiple power
ERCOT_Tenaska Frontier Generating Station (ERC.
regions in ERGOT are switching regions without any
markets.
SPP_Kiamichi Energy Facility [SPP_KIAM] region in SPP is a switching region without any internal demand created to capture
the ability to sell power to multiple power markets.
3-4
-------
Table 3-2 Electric Load Assumptions in EPA Base Case v.5.13
Year
2016
2018
2020
2025
2030
2040
2050
Net Energy for Load
(Billions of KWh)
4,049
4,135
4,215
4,390
4,535
4,887
5,271
Notes:
This data is an aggregation of the model-region-specific
net energy loads used in the EPA Base Case v.5.13.
3.2.1 Demand Elasticity
EPA Base Case v.5.13 has the capability to consider endogenously the relationship of the price of power
to electricity demand. However, this capability is typically only exercised for sensitivity analyses where
different price elasticities of demand are specified for purposes of comparative analysis. The default base
case assumption is that the electricity demand shown in Table 3-2, which was originally derived from EIA
modeling that did consider price elasticity of demand, must be met as IPM solves for least-cost electricity
supply. This approach maintains a consistent expectation of future load between the EPA Base Case and
the corresponding EIA Annual Energy Outlook reference case (e.g., between EPA Base Case v5.13 and
the AEO2013 reference case).
3.2.2 Net Internal Demand (Peak Demand)
EPA Base Case v5.13 has separate regional winter and summer peak demand values, as derived from
each region's seasonal load duration curve (found in Attachment 2-1). Peak projections were estimated
based on AEO 2013 load factors and the estimated energy demand projections shown in Table 3-2.
Table 3-3 illustrates the national sum of each region's winter and summer peak demand. Because each
region's seasonal peak demand need not occur at the same time, the national peak demand is defined as
non-coincidental (i.e., national peak demand is a summation of each region's peak demand at whatever
point in time that region's peak occurs across the given time period).
Table 3-3 National Non-Coincidental Net Internal Demand
Year
2016
2018
2020
2025
2030
2040
2050
Peak
Winter
657
670
686
725
763
845
916
Demand (GW)
Summer
746
761
780
826
873
972
1,053
Notes:
This data is an aggregation of the model-region-specific
peak demand loads used in the EPA Base Case v.5.13.
3-5
-------
3.2.3 Regional Load Shapes
As of 2013, EPA has adopted year 2011 as the meteorological year in its air quality modeling. In order for
EPA Base Case v.5.13 to be consistent, the year 2011 was selected as the "normal weather year"8 for all
IPM regions. The proximity of the 2011 cumulative annual heating degree days (HDDs) and cooling
degree days (CDDs) to the long-term average cumulative annual HHDs and CDDs over the period 1981
to 2010 was estimated and found to be reasonably close. The 2011 chronological hourly load data were
assembled by aggregating individual utility load curves taken from Federal Energy Regulatory
Commission Form 714 data and individual ISOs and RTOs.
3.3 Transmission
The United States and Canada can be broken down into several power markets that are interconnected
by a transmission grid. As discussed earlier, EPA Base Case 5.13 characterizes the U.S. lower 48
states, the District of Columbia, and Canada into 75 different model regions by means of 61 power
market regions and 3 power switching regions9 in the U.S. and 11 power market regions in Canada. EPA
Base Case 5.13 includes explicit assumptions regarding the transmission grid connecting these modeled
power markets. This section details the assumptions about the transfer capabilities, wheeling costs and
inter-regional transmission used in EPA Base Case 5.13.
3.3.1 Inter-regional Transmission Capability
Table 3-410 shows the firm and non-firm Total Transfer Capabilities (TTCs) between model regions. TTC
is a metric that represents the capability of the power system to import or export power reliably from one
region to another. The purpose of TTC analysis is to identify the sub-markets created by key
commercially significant constraints. Firm TTCs, also called Capacity TTCs, specify the maximum power
that can be transferred reliably, even after the contingency loss of a single transmission system element
such as a transmission line or a transformer (a condition referred to as N-1, or "N minus one"). Firm
TTCs provide a high level of reliability and are therefore used for capacity transfers. Non-firm TTCs, also
called Energy TTCs, represent the maximum power that can be transferred reliably when all facilities are
under normal operation (a condition referred to as N-0, or "N minus zero"). They specify the sum of the
maximum firm transfer capability between sub-regions and incremental curtailable non-firm transfer
capability. Non-firm TTCs are used for energy transfers since they provide a lower level of reliability than
Firm TTCs, and transactions using Non-firm TTCs can be curtailed under emergency or contingency
conditions.
Table 3-4 Annual Transmission Capabilities of U.S. Model Regions in
EPA Base Case v.5.13
From
To
2016
Capacity
TTC (MW)
Energy
TTC (MW)
2018
Incremental
Capacity TTC
(MW)
Incremental
Energy TTC (MW)
Transmission Tariff
(2011 mills/kWh)
ERC_REST 860 860 0
SPP_WEST 860 860 6
The term "normal weather year" refers to a representative year whose weather is closest to the long-term (e.g., 35
year) average weather. The selection of a "normal weather year" can be made, for example, by comparing the
cumulative annual heating degree days (HDDs) and cooling degree days (CDDs) in a candidate year to the long-term
average. For any individual day, heating degree days indicate how far the average temperature fell below 65 degrees
F; cooling degree days indicate how far the temperature averaged above 65 degrees F. Cumulative annual heating
and cooling degree days are the sum of all the HDDs and CDDs, respectively, in a given year.
9 Power switching regions are regions with no market load that represent individual generating facilities specifically
configured so they can sell directly into either ERGOT or SPP: these plants are implemented in IPM as regions with
transmission links only to ERGOT and to SPP.
10 In the column headers in Table 3-4 the term "Energy TTC (MW)" is equivalent to non-firm TTCs and the term
"Capacity TTC (MW)" is equivalent to firm TTCs.
3-6
-------
From
To
2016
Capacity
TTC (MW)
Energy
TTC (MW)
2018
Incremental
Capacity TTC
(MW)
Incremental
Energy TTC (MW)
Transmission Tariff
(2011 mills/kWh)
ERC GWAY
ERC_REST
SPP WEST
845
845
845
845
ERC REST
ERC_WEST
SPP WEST
5,529
600
5,529
600
ERC WEST
ERC_REST
SPP WEST
10,555
220
10,555
220
FRCC
S SOU
3,600
3,600
MAP WAUE
CN_SK
MISJA
MIS_MAPP
MIS_MIDA
MIS_MNWI
SPP NEBR
0
0
1,000
600
2,000
700
100
100
1,500
1,000
3,000
1,000
MIS IA
MAP_WAUE
MISJL
MIS_MIDA
MIS_MNWI
MIS_MO
PJM_COMD
S D N AR
0
0
900
1,195
223
0
0
100
100
2,000
2,000
711
600
100
MIS IL
MISJA
MISJNKY
MIS_MIDA
MIS_MO
PJM_COMD
PJM_West
S C TVA
0
240
0
3,400
2,500
0
1,200
100
1,195
100
4,500
3,000
1,300
1,500
MIS INKY
MISJL
MISJ.MI
PJM_COMD
PJM_West
S_C_KY
S C TVA
240
0
2,044
5,441
2,257
300
1,195
100
3,355
6,509
3,787
500
MIS LMI
CNJDN
MISJNKY
MIS_WUMS
PJM_ATSI
PJM West
400
0
0
1,262
1,400
1,200
100
100
2,036
2,800
MIS MAPP
CN_MB
MAP_WAUE
MIS MNWI
300
1,000
2,150
500
1,500
5,000
MIS MIDA
MAP_WAUE
MISJA
MISJL
MIS MNWI
600
900
0
0
1,000
2,000
100
0
MIS_MO
PJM_COMD
SJD_N_AR
SPP_N
SPP NEBR
0
2,000
0
0
1,000
500
3,000
30
50
2,000
MIS MNWI
CN MB
200
1,700
3-7
-------
From
To
2016
Capacity
TTC (MW)
Energy
TTC (MW)
2018
Incremental
Capacity TTC
(MW)
Incremental
Energy TTC (MW)
Transmission Tariff
(2011 mills/kWh)
CNJDN
MAP_WAUE
MISJA
MIS_MAPP
MIS_MIDA
MIS WUMS
0
2,000
1,195
2,150
0
1,480
162
3,000
2,000
5,000
0
2,400
MIS MO
MISJA
MISJL
MIS_MIDA
S_D_N_AR
SPP N
223
3,400
0
2,100
300
711
4,500
500
2,804
1,000
MIS WUMS
MIS_LMI
MIS_MNWI
PJM COMD
0
1,480
0
100
2,400
1000
NENG CT
NENGREST
NY_Z_G-I
NY Z K
2,600
900
760
2,600
900
760
800
800
NENG ME
CN_NB
NENGREST
800
1,600
800
1,600
NENGREST
CN_PQ
NENG_CT
NENG_ME
NY_Z_D
NY Z F
1,650
2,600
1,600
0
800
1,650
2,600
1,600
0
800
800
800
NY Z A&B
CNJDN
NY_Z_C&E
PJM PENE
1,200
1,550
500
1,200
1,550
1,000
NY Z C&E
NY_Z_A&B
NY_Z_D
NY_Z_F
NY_Z_G-I
PJM PENE
1,300
1,600
3,250
1,700
755
1,300
1,600
3,250
1,700
1,500
NY Z D
CN_PQ
NENGREST
NY Z C&E
1,200
150
2,650
1,200
150
2,650
NY Z F
NENGREST
NY_Z_C&E
NY Z G-l
800
1,999
3,450
800
1,999
3,450
NENG_CT
PJM EMAC
NY Z G-l
NY_Z_C&E
NY_Z_F
NY_Z_J
NY Z K
1,130
1,000
1,130
1,000
1,600
1,999
4,350
1,290
1,600
1,999
4,350
1,290
NY Z J
NY_Z_G-I
NY_Z_K
PJM EMAC
3,500
175
1,300
3,500
175
1,900
NY Z K
NENG_CT
NY_Z_G-I
NY_Z_J
PJM EMAC
760
530
283
660
760
530
283
660
3-8
-------
From
To
2016
Capacity
TTC (MW)
Energy
TTC (MW)
2018
Incremental
Capacity TTC
(MW)
Incremental
Energy TTC (MW)
Transmission Tariff
(2011 mills/kWh)
PJM ATS I
PJM AP
PJM_Dom
PJM_PENE
PJM_SMAC
PJM West
1,212
2,731
5,400
2,400
1,100
4,800
8,000
3,200
2,200
6,300
PJM ATSI
MISJ.MI
PJM_AP
PJM_PENE
PJM West
1,262
1,212
0
7,400
2,036
2,731
1,500
9,700
PJM COMD
MISJA
MISJL
MISJNKY
MIS_MIDA
MIS_WUMS
PJM West
0
2,500
3,840
2,000
0
980
600
3,000
5,098
3,000
1,000
4,000
PJM Dom
PJM_AP
PJM_SMAC
PJM_West
S VACA
5,400
1,195
1,530
1,000
8,000
2,812
3,800
2,598
PJM EMAC
NY_Z_J
NY_Z_K
NY_Z_G-I
PJM_SMAC
PJM WMAC
1,300
660
500
300
6,900
1,900
660
500
1,095
6,900
PJM PENE
NY_Z_A&B
NY_Z_C&E
PJM_AP
PJM_ATSI
PJM WMAC
500
755
2,400
0
3,565
1,000
1,500
3,200
1,500
3,565
PJM SMAC
PJM_AP
PJM_Dom
PJM_EMAC
PJM WMAC
1,100
1,195
300
800
2,200
2,812
1,095
2,000
MISJL
MIS INKY
PJM West
MISJ.MI
PJM_AP
PJM_ATSI
PJM COMD
PJM_Dom
S_C_KY
S_C_TVA
S VACA
0
5,125
1,300
6,415
1,400
4,800
7,400
980
2,800
6,300
9,700
4,000
1,530
1,255
2,119
700
3,800
2,074
3,118
1,000
PJM WMAC
PJM_EMAC
PJM_PENE
PJM SMAC
6,900
3,565
800
6,900
3,565
2,000
S C KY
MISJNKY
PJM West
2,257
1,255
3,787
2,074
S C TVA
MISJL
MISJNKY
PJM West
1,200
300
2,119
1,500
500
3,118
3-9
-------
From
To
2016
Capacity
TTC (MW)
Energy
TTC (MW)
2018
Incremental
Capacity TTC
(MW)
Incremental
Energy TTC (MW)
Transmission Tariff
(2011 mills/kWh)
S_D_N_AR
S_D_REST
S_SOU
S VACA
1,732
1,195
3,196
216
3,019
2,494
5,098
276
S D AMSO
S_D_REST
S_SOU
SPP SE
2,450
420
300
2,450
700
500
S D N AR
MISJA
MIS_MIDA
MIS_MO
S_C_TVA
SPP_N
SPP WEST
0
0
2,100
1,732
1,792
2,000
100
30
2,804
3,019
2,955
3,000
S D REST
S_C_TVA
S_D_AMSO
S_D_WOTA
S_SOU
SPP_SE
SPP WEST
1,195
2,450
290
1,700
1,639
100
2,494
2450
1,050
2,000
3,136
900
S D WOTA
S_D_REST
SPP SE
1,250
1,491
1,250
2,835
S SOU
FRCC
S_C_TVA
S_D_AMSO
S_D_REST
S VACA
3,600
4,411
420
1,700
1,400
3,600
5,893
700
2,000
3,000
S VACA
PJM_Dom
PJM_West
S_C_TVA
S SOU
1,000
700
216
1,400
2,598
1,000
276
3,000
SPP KIAM
ERC_REST
SPP WEST
1,178
1,178
1,178
1,178
SPP N
MIS_MIDA
MIS_MO
S_D_N_AR
SPP_NEBR
SPP_SPS
SPP WEST
0
300
1,792
1,217
0
2,253
50
1,000
2,955
1,666
900
3,600
500
500
500
500
SPP NEBR
MAP_WAUE
MIS_MIDA
SPP N
700
1,000
1,217
1,000
2,000
1,666
500
500
SPP SE
S_D_AMSO
S_D_REST
S_D_WOTA
SPP WEST
300
1,639
1,491
0
500
3,136
2,835
852
SPP SPS
SPP_N
SPP_WEST
WECC NM
0
1,239
610
900
2,205
610
750
750
SPP WEST
ERC_REST
ERC_WEST
S D N AR
600
220
2,000
600
220
3,000
3-10
-------
From
To
2016
Capacity
TTC (MW)
Energy
TTC (MW)
2018
Incremental
Capacity TTC
(MW)
Incremental
Energy TTC (MW)
Transmission Tariff
(2011 mills/kWh)
S_D_REST
SPP_N
SPP_SE
SPP SPS
100
2,500
0
1,239
900
2,700
688
2,205
500
750
500
750
WEC CALN
WECC_NNV
WECC_PNW
WECC_SCE
WECC SF
100
3,675
1,275
1,272
100
3,675
1,275
1,272
WEC LADW
WECC_AZ
WECC_PNW
WECC_SCE
WECC_SNV
WECC UT
468
2,858
3,750
3,883
1,400
468
2,858
3,750
3,883
1,400
WEC SDGE
WECC_AZ
WECCJID
WECC SCE
1,168
150
2,440
1,168
150
2,440
WECC AZ
WEC_LADW
WEC_SDGE
WECCJID
WECC_NM
WECC_SCE
WECC_SNV
WECC UT
362
1,163
195
5,522
1,600
4,727
250
362
1,163
195
5,522
1,600
4,727
250
WECC CO
WECC_NM
WECC UT
614
650
614
650
WECC WY
1,400
1,400
WECC ID
WECC_MT
WECC_NNV
WECC_PNW
WECC_UT
WECC WY
200
350
1,800
680
0
200
350
1,800
680
0
WECC I ID
WEC_SDGE
WECC_AZ
WECC SCE
150
163
600
150
163
600
WECC MT
WECCJD
WECC_PNW
WECC WY
325
2,000
400
325
2,000
400
WECC NM
SPP_SPS
WECC_AZ
WECC_CO
WECC UT
610
5,582
664
530
610
5,582
664
530
WECC NNV
WEC_CALN
WECCJD
WECC_PNW
WECC UT
100
185
300
235
100
185
300
235
WECC PNW
CNJ3C
WEC_CALN
WECJ.ADW
WECCJD
WECC_MT
WECC NNV
1,000
4,200
2,600
500
1,000
300
1,000
4,200
2,600
500
1,000
300
3-11
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From
To
2016
Capacity
TTC (MW)
Energy
TTC (MW)
2018
Incremental
Capacity TTC
(MW)
Incremental
Energy TTC (MW)
Transmission Tariff
(2011 mills/kWh)
WECC SCE
WEC_CALN
WEC_LADW
WEC_SDGE
WECC_AZ
WECCJID
WECC SNV
3,000
3,750
2,200
1,082
50
2,814
3,000
3,750
2,200
1,082
50
2,814
WECC SF
WEC CALN
1,100
1,100
WECC SNV
WEC_LADW
WECC_AZ
WECC_SCE
WECC UT
2,300
4,785
1,700
250
2,300
4,785
1,700
250
WECC UT
WEC_LADW
WECC_AZ
WECC_CO
WECCJD
WECC_NM
WECC_NNV
WECC_SNV
WECC WY
1,920
250
650
775
600
360
140
400
19,20
250
650
775
600
360
140
400
WECC CO
1,400
1,400
WECC WY
WECCJD
WECC_MT
WECC UT
2,200
200
400
2,200
200
400
The amount of energy and capacity transferred on a given transmission link is modeled on a seasonal
(summer and winter) basis for all run years in the EPA Base Case v.5.13. All of the modeled transmission
links have the same Total Transfer Capabilities for both the winter and summer seasons, which means
that the maximum firm and non-firm TTCs for each link is the same for both winter and summer. The
maximum values for firm and non-firm TTCs were obtained from public sources such as market reports
and regional transmission plans, wherever available. Where public sources were not available, the
maximum values for firm and non-firm TTCs are based on ICF's expert view. ICF analyzes the operation
of the grid under normal and contingency conditions, using industry-standard methods, and calculates the
transfer capabilities between regions. ICF uses standard power flow data developed by the market
operators, transmission providers, or utilities, as appropriate.
It should be noted that each transmission link between model regions shown in Table 3-4represents a
one-directional flow of power on that link. This implies that the maximum amount of flow of power possible
from region A to region B may be more or less than the maximum amount of flow of power possible from
region B to region A, due to the physical nature of electron flow across the grid.
3.3.2 Joint Transmission Capacity and Energy Limits
Table 3-5 shows the annual joint limits to the transmission capabilities between model regions, which are
identical for the firm (capacity) and non-firm (energy) transfers. The joint limits were obtained from public
sources where available, or based on ICF's expert view. A joint limit represents the maximum
simultaneous firm or non-firm power transfer capability of a group of interfaces. It restricts the amount of
firm or non-firm transfers between one model region (or group of model regions) and a different group of
model regions). For example, the New England market is connected to the New York market by four
transmission links. As shown in Table 3-4, the transfer capabilities from New England to New York for the
individual links are:
3-12
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NENG_CT to NY_Z_G-I: 900 MW
NENGREST to NY_Z_F: 800 MW
NENG_CT to NY_Z_K: 760 MW
NENGREST to NY Z D: 0 MW
Without any simultaneous transfer limits, the total transfer capability from New England to New York
would be 2,460 MW. However, current system conditions and reliability requirements limit the total
simultaneous transfers from New England to New York to 1,730 MW. ICF uses joint limits to ensure that
this and similar reliability limits are not violated. Therefore each individual link can be utilized to its limit as
long as the total flow on all links does not exceed the joint limit.
Table 3-5 Annual Joint Capacity and Energy Limits to Transmission Capabilities
Between Model Regions in EPA Base Case v.5.13
Region Connection
NYlSOtoNYISO
NYlSOtoNYISO
NYlSOtolSO-NE
NYlSOtolSO-NE
ISO-NE to NYISO
PJM to PJM
PJM to PJM
PJM to SERC-E
SERC-EtoPJM
MAPPtoMISO
MISOtoMAPP
SERC-N to PJM
PJM to SERC-N
SERC-N to MISO
Transmission Path
NY_Z_G-I to NY_Z_K
NY_Z_J to NY_Z_K
NY_Z_K to NY_Z_G-I
NY Z K to NY Z J
NY_Z_G-I to NENG_CT
NY_Z_F to NENGREST
NY_Z_KtoNENG_CT
NY Z D to NENGREST
NY_Z_G-I to NENG_CT
NY_Z_F to NENGREST
NY_Z_KtoNENG_CT
NY Z D to NENGREST
NENG_CTtoNY_Z_G-l
NENGREST to NY_Z_F
NENG_CTtoNY_Z_K
NENGREST to NY Z D
PJM_WesttoPJM_ATSI
PJM_PENE to PJM_ATSI
PJM_AP to PJM_ATSI
PJM_ATSI to PJM_West
PJM_ATSI to PJM_PENE
PJM ATSI to PJM AP
PJM_WesttoS_VACA
PJM_Dom to S_VACA
S_VACAtoPJM_West
S VACAtoPJM Dom
MIS_MAPPtoMIS_MNWI
MAP_WAUE to MIS_MNWI
MIS_MNWItoMIS_MAPP
MIS MNWItoMAP WAUE
S_C_TVAtoPJM_West
S_C_KYtoPJM_West
PJM_WesttoS_C_TVA
PJM West to S C KY
S_C_TVAtoMIS_INKY
S_C_KYtoMIS_INKY
Capacity TTC (MW)
Energy TTC (MW)
1,465
285
1,730
2,205
1,730
5,417
5,417
1,300
1,300
3,000
3,000
3,000
3,000
2,257
12,000
12,000
2,598
2,598
5,000
5,000
4,500
4,500
4,000
3-13
-------
Region Connection
MISOtoSERC-N
MISOtoPJM
PJMtoMISO
Transmission Path
MIS_INKYtoS_C_TVA
MIS INKY to S C KY
MIS_INKYtoPJM_COMD
MIS_INKYtoPJM_West
PJM_COMD to MISJNKY
PJM_WesttoMIS_INKY
Capacity TTC (MW)
2,257
4,586
5,998
Energy TTC (MW)
4,000
6,509
8,242
3.3.3 Transmission Link Wheeling Charge
Transmission wheeling charge is the cost of transferring electric power from one region to another using
the transmission link. The EPA Base Case 5.13 has no charges within individual IPM regions and no
charges between IPM regions that fall within the same RTO. Charges between other regions vary to
reflect the cost of wheeling. The wheeling charges in 2011 mills/kWh are shown in Table 3-4 in the
column labeled "Transmission Tariff'.
3.3.4 Transmission Losses
The EPA Base Case 5.13 assumes a 2.8 percent inter-regional transmission loss of energy
transferred.This is based on the average loss factor for the transmission grid calculated from the U.S
Energy Information Administration (EIA) State Electricity Profiles 2010 report.11 The results were
validated using average loss factors derived from standard power flow data developed by the market
operators, transmission providers, and utilities.
3.4 International Imports
The U.S. electric power system is connected with the transmission grids in Canada and Mexico and the
three countries actively trade in electricity. The Canadian power market is endogenously modeled in EPA
Base Case v.5.13 but Mexico is not. International electric trading between the U.S. and Mexico is
represented by an assumption of net imports based on information from AEO 2013. Table 3-6
summarizes the assumptions on net imports into the US from Mexico.
Table 3-6 International Electricity Imports in EPA Base Case v.5.13
2016 2018 2020 2025 2030 2040 2050
Net Imports from Mexico
(billions kWh)
0.67 0.55 0.31 -0.29 -0.53 -0.53 -0.53
Notes:
Imports & exports transactions from Canada are endogenously modeled in IPM.
Source: AEO 2013
3.5 Capacity, Generation, and Dispatch
While the capacity of existing units is an exogenous input into IPM, the dispatch of those units is an
endogenous decision that the model makes. The capacity of existing generating units included in EPA
Base Case v.5.13 can be found in the National Electrical Energy Data System (NEEDS v.5.13), a
database which provides IPM with information on all currently operating and planned-committed electric
generating units. NEEDS v.5.13 is discussed in full in Chapter 4.
A unit's generation over a period of time is defined by its dispatch pattern over that duration of time. IPM
determines the optimal economic dispatch profile given the operating and physical constraints imposed
State Electricity Profiles 2010, Table 3-10, U.S. Energy Information Administration, January 2012.
(http://vwvw.eia.qov/electricitv/state/pdf/sep2010.pdf).
3-14
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on the unit. In EPA Base Case v.5.13 unit specific operational and physical constraints are generally
represented through availability and turndown constraints. However, for some unit types, capacity factors
are used to capture the resource or other physical constraints on generation. The two cases are
discussed in more detail in the following sections.
3.5.1 Availability
Power plant "availability" is the percentage of time that a generating unit is available to provide electricity
to the grid. Availability takes into account both scheduled maintenance and forced outages; it is formally
defined as the ratio of a unit's available hours adjusted for derating of capacity (due to partial outages) to
the total number of hours in a year when the unit was in an active state. For most types of units in IPM,
availability parameters are used to specify an upper bound on generation to meet demand. Table 3-7
summarizes the availability assumptions used in EPA Base Case v.5.13. They are based on data from
NERC Generating Availability Data System (GADS) 2007-2011 and AEO 2012. Table 3-18 shows the
availability assumptions for all generating units in EPA Base Case v.5.13.
Table 3-7 Availability Assumptions in the EPA Base Case v.5.13
Unit Type
Biomass
Coal Steam
Combined Cycle
Combustion Turbine
Fossil Waste
Fuel Cell
Geothermal
Hydro
IGCC
Landfill Gas
Municipal Solid Waste
Non-Fossil Waste
Nuclear
O/G Steam
Pumped Storage
Solar PV
Solar Thermal
Tires
Wind
Annual Availability (%)
82-86
77-90
84-90
85-93
90
87
97-98
81 -91
79-88
90
90
90
58-100
70-92
83-90
90
90
90
95
Notes:
Values shown are a range of all of the values modeled within the EPA Base Case v.5.13. The range depends on the
source of information: GADS data vary by size, AEO 2012 data may vary by projected year.
In the EPA Base Case v.5.13, separate seasonal (summer and winter) availabilities are defined. For the
fossil and nuclear unit types shown in Table 3-7, summer and winter availabilities differ only in that no
planned maintenance is assumed to be conducted during the on-peak summer (June, July and August)
months. Characterizing the availability of hydro, solar and wind technologies is more complicated due to
the seasonal and locational variations of the resources. The procedures used to represent seasonal
variations in hydro are presented in section 3.5.2 and of wind and solar in section 4.4.5.
3.5.2 Capacity Factor
Generation from certain types of units is constrained by resource limitations. These technologies include
hydro, wind and solar. For such technologies, IPM uses capacity factors or generation profiles, not
availabilities, to define the upper bound on the generation obtainable from the unit. The capacity factor is
3-15
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the percentage of the maximum possible power generated by the unit. For example, a photovoltaic solar
unit would have a capacity factor of 27% if the usable sunlight were only available that percent of the
time. For such units, explicit capacity factors or generation profiles mimic the resource availability. The
seasonal capacity factor assumptions for hydro facilities contained in Table 3-8 were derived from EIA
Form-923 data 2007-2011. A discussion of capacity factors and generation profiles for wind and solar
technologies is contained in section 4.4.5 and Table 4-32 and Table 4-33.
Table 3-8 Seasonal Hydro Capacity Factors (%) in the EPA Base Case v.5.13
Model Region
ERC_REST
FRCC
MIS_MAPP
MAP_WAUE
MISJL
MISJNKY
MISJA
MIS_MIDA
MIS_LMI
MIS_MO
MIS_WUMS
MIS_MNWI
NENG_CT
NENGREST
NENG_ME
NY_Z_C&E
NY_Z_F
NY_Z_G-I
NY_Z_A&B
NY_Z_D
PJM_WMAC
PJM_EMAC
PJM_West
PJM_AP
PJM_COMD
PJM_ATSI
PJM_Dom
PJM_PENE
S_VACA
S_C_KY
S_C_TVA
S_SOU
S_D_WOTA
S_D_N_AR
S_D_REST
SPP_NEBR
SPP_N
SPP_WEST
WECC_ID
WECC_NNV
WECC_UT
WEC_CALN
WECC_IID
Winter Capacity Factor
12.9%
44.0%
81.0%
29.2%
55.0%
76.2%
38.5%
41.6%
68.8%
42.7%
66.2%
33.0%
47.3%
45.8%
65.5%
56.9%
67.0%
35.8%
70.4%
88.3%
41.5%
48.3%
33.8%
64.6%
36.5%
23.5%
21.1%
63.0%
21.1%
29.2%
38.8%
22.8%
20.1%
23.9%
49.2%
32.1%
15.7%
32.1%
32.3%
49.6%
30.1%
26.9%
45.7%
Summer Capacity Factor
25.0%
31.8%
87.4%
40.2%
64.3%
95.9%
48.6%
49.6%
44.4%
58.7%
61.5%
36.3%
40.2%
34.5%
58.1%
55.0%
58.9%
34.6%
65.0%
83.3%
20.3%
24.6%
28.0%
45.5%
48.0%
32.8%
12.9%
34.1%
14.2%
30.2%
28.3%
14.5%
23.0%
26.7%
56.6%
43.7%
22.8%
39.9%
52.3%
62.6%
42.5%
45.1%
78.5%
Annual Capacity Factor
18.0%
38.9%
83.7%
33.8%
58.9%
84.4%
42.7%
44.9%
58.6%
49.4%
64.2%
34.4%
44.4%
41.1%
62.4%
56.1%
63.6%
35.3%
68.1%
86.2%
32.6%
38.4%
31.4%
56.6%
41.3%
27.4%
17.7%
50.9%
18.2%
29.6%
34.4%
19.3%
21.3%
25.1%
52.3%
36.9%
18.7%
35.4%
40.7%
55.1%
35.3%
34.5%
59.5%
3-16
-------
Model Region
WEC_LADW
WEC_SDGE
WECC_SCE
WECC_MT
WECC_PNW
WECC_CO
WECC_WY
WECC_AZ
WECC_NM
WECC_SNV
Winter Capacity Factor
17.1%
30.8%
28.3%
34.4%
41.7%
28.8%
22.8%
28.9%
30.1%
20.4%
Summer Capacity Factor
27.9%
53.7%
52.9%
52.2%
46.5%
36.8%
54.1%
33.3%
43.0%
25.6%
Annual Capacity Factor
21.6%
40.4%
38.6%
41.9%
43.7%
32.2%
36.0%
30.8%
35.5%
22.6%
Notes:
Annual capacity factor is provided for information purposes only. It is not directly used in modeling.
Capacity factors are also used to define the upper bound on generation obtainable from nuclear units.
This rests on the assumption that nuclear units will dispatch to their availability, and, consequently,
capacity factors and availabilities are equivalent. The capacity factors (and, consequently, the
availabilities) of existing nuclear units in EPA Base Case v.5.13 vary from region to region and over time.
Further discussion of the nuclear capacity factor assumptions in EPA Base Case v.5.13 is contained in
Section 4.5.
In EPA Base Case v5.13 capacity factors for oil/gas (O/G) steam units are treated separately and
assigned minimum capacity factors under certain conditions. These capacity factors are a result of
stakeholder comments that many of the O/G steam units in the national fleet may not operate under the
economic conditions reflected in EPA power sector modeling. These comments note that these units
often operate due to local transmission constraints, unit-specific grid reliability requirements, or other
drivers that are not captured in EPA's modeling. EPA examined its modeling treatment of these units and
has introduced minimum capacity factor constraints in EPA Base Case v5.13 to reflect better the real-
world behavior of these units where drivers of that behavior are not fully represented in the model itself.
This approach is designed to balance the continued operation of these units in the near term while also
allowing for economic forces to influence decision-making over the modeling time horizon; as a result, the
minimum capacity factor limitations are phased out overtime and are completely removed if the capacity
in question reaches 60 years of age Review of the historical operation of these units indicate that units
with high capacity factors continue at similar levels over time; in order to reflect persistent operation of
these units, minimum capacity factors for higher capacity factor units are phased out more slowly than
lower capacity factor units. The steps followed in assigning these capacity constraints are as follows:
1) For each O/G steam unit, calculate an seasonal capacity factor over a six year baseline (2007-2012).
2) Identify the minimum capacity factor over this baseline period for each unit.
3) Remove the minimum capacity factor limitation when the unit reaches 60 year old.
4) For units less than 60 years old, remove the constraints based on the assigned minimum capacity
factor and the model year, on the following schedule:
For model year 2016, keep minimum capacity factor unless unit>
For model year 2018, remove minimum constraint from units with
For model year 2020, remove minimum constraint from units with
For model year 2025, remove minimum constraint from units with
For model year 2030, remove minimum constraint from units with
For model year 2040, remove minimum constraint from units with
60 years old.
capacity factor < 2.5%
capacity factor < 5%
capacity factor < 15%
capacity factor < 25%
capacity factor < 45%
3-17
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3.5.3 Turndown
Turndown assumptions in EPA Base Case v.5.13 are used to prevent coal and oil/gas steam units from
operating strictly as peaking units, which would be inconsistent with their operating capabilities.
Specifically, the turndown constraints in EPA Base Case v.5.13 require coal steam units to dispatch no
less than 50% of the unit capacity in the five base- and mid-load segments of the load duration curve in
order to dispatch 100% of the unit in the peak load segment of the LDC. Oil/gas steam units are required
to dispatch no less than 25% of the unit capacity in the five base- and mid-load segments of the LDC in
order to dispatch 100% of the unit capacity in the peak load segment of the LDC. These turndown
constraints were developed by ICF through detailed assessments of the historical experience and
operating characteristics of the existing fleet of coal steam and oil/gas steam units' capacities.
3.6 Reserve Margins
A reserve margin is a measure of the system's generating capability above the amount required to meet
the net internal demand (peak load) requirement. It is defined as the difference between total dependable
capacity and annual system peak load divided by annual system peak load. It is expressed in percent.
The reserve margin capacity contribution for renewable units is described in Section 4.4.5; the reserve
margin capacity contribution for other units is the dependable capacity in the NEEDS for existing units or
the capacity build by IPM for new units. In practice, each NERC region has a reserve margin
requirement, or comparable reliability standard, which is designed to encourage electric suppliers in the
region to build beyond their peak requirements to ensure the reliability of the electric generation system
within the region.
In IPM reserve margins are used to depict the reliability standards that are in effect in each NERC region.
Individual reserve margins for each NERC region are derived either directly or indirectly from NERC's
electric reliability reports. They are based on reliability standards such as loss of load expectation
(LOLE), which is defined as the expected number of days in a specified period in which the daily peak
load will exceed the available capacity. EPA Base Case v.5.13 reserve margin assumptions are shown in
Table 3-9.
Table 3-9 Planning Reserve Margins in EPA Base Case v.5.13
Model Region
CN_AB
CN_BC
CN_MB
CN_NB
CN_PE
CN_NS
CN_NF
CN_NL
CNJDN
CN_PQ
CN_SK
ERC_FRNT
ERC_GWAY
ERC_REST
ERC_WEST
FRCC
MAP_WAUE
MISJA
MISJL
MISJNKY
MISJ.MI
MIS_MAPP
Reserve Margin - Summer
12.2%
12.5%
12.0%
20.0%
20.0%
20.0%
20.0%
20.0%
19.2%
11.4%
11.0%
13.8%
13.8%
13.8%
13.8%
19.3%
15.0%
16.3%
16.3%
16.3%
16.3%
15.0%
Reserve Margin -Winter
1 1 .7%
16.2%
12.0%
20.0%
20.0%
20.0%
20.0%
20.0%
20.0%
12.2%
1 1 .0%
13.8%
13.8%
13.8%
13.8%
19.3%
15.0%
16.3%
16.3%
16.3%
16.3%
15.0%
3-18
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Model Region
MIS_MIDA
MIS_MNWI
MIS_MO
MIS_WUMS
NENG_CT
NENG_ME
NENGREST
NY_Z_A&B
NY_Z_C&E
NY_Z_D
NY_Z_F
NY_Z_G-I
NY_Z_J
NY_Z_K
PJM_AP
PJM_ATSI
PJM_COMD
PJM_Dom
PJM_EMAC
PJM_PENE
PJM_SMAC
PJM_West
PJM_WMAC
S_C_KY
S_C_WA
S_D_AMSO
S_D_N_AR
S_D_REST
S_D_WOTA
S_SOU
S_VACA
SPP_KIAM
SPP_N
SPP_NEBR
SPP_SE
SPP_SPS
SPP_WEST
WEC_CALN
WEC_LADW
WEC_SDGE
WECC_AZ
WECC_CO
WECCJD
WECCJID
WECC_MT
WECC_NM
WECC_NNV
WECC_PNW
WECC_SCE
WECC_SF
WECC_SNV
WECC_UT
WECC_WY
Reserve Margin - Summer
16.3%
16.3%
16.3%
16.3%
15.0%
15.0%
15.0%
16.0%
16.0%
16.0%
16.0%
16.0%
16.0%
16.0%
15.4%
15.4%
15.4%
15.4%
15.4%
15.4%
15.4%
15.4%
15.4%
15.0%
15.0%
15.0%
15.0%
15.0%
15.0%
15.0%
15.0%
13.6%
13.6%
13.6%
13.6%
13.6%
13.6%
14.7%
15.1%
15.1%
13.5%
14.7%
12.6%
15.1%
17.9%
13.5%
12.6%
17.9%
15.1%
14.7%
13.5%
12.6%
14.7%
Reserve Margin -Winter
16.3%
16.3%
16.3%
16.3%
15.0%
15.0%
15.0%
16.0%
16.0%
16.0%
16.0%
16.0%
16.0%
16.0%
15.4%
15.4%
15.4%
15.4%
15.4%
15.4%
15.4%
15.4%
15.4%
15.0%
15.0%
15.0%
15.0%
15.0%
15.0%
15.0%
15.0%
13.6%
13.6%
13.6%
13.6%
13.6%
13.6%
1 1 .9%
1 1 .0%
1 1 .0%
14.0%
15.7%
13.5%
1 1 .0%
19.9%
14.0%
13.5%
19.9%
1 1 .0%
1 1 .9%
14.0%
13.5%
15.7%
3-19
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3.7 Power Plant Lifetimes
EPA Base Case v5.13 does not include any pre-specified assumptions about power plant lifetimes except
for nuclear units. All conventional fossil units (i.e., coal, oil/gas steam, combustion turbines, and combined
cycle) and nuclear units can be retired during a model run if their retention is deemed uneconomic. Other
types of units are not provided an economic retirement option.
Nuclear Retirement at Age 60: EPA Base Case v.5.13 assumes that commercial nuclear reactors will
be retired upon license expiration, which includes a 20 year operating extension that is assumed to be
granted for each reactor by the Nuclear Regulatory Commission (NRC). EPA Base Case v.5.13
continues the assumption of a 60 year life from the previous base case platforms. EPA Base Case v.5.13
modeling uses a maximum 60 year lifetime for nuclear reactors based on the current NRC licensing
extension program, which states; "Based on the Atomic Energy Act, the Nuclear Regulatory Commission
(NRC) issues licenses for commercial power reactors to operate for up to 40 years and allows these
licenses to be renewed for up to another 20 years. Economic and antitrust considerations, not limitations
of nuclear technology, determined the original 40-year term for reactor licenses. "12 Today's nuclear fleet
totals more than 100 GW. Assuming a 60-year lifetime13 reduces the current fleet to under 5 GW in 2050.
This is illustrated in Figure 3-2. Fora complete listing of the existing nuclear units including their online
year and other characteristics, see Table 4-34.
Figure 3-2 Scheduled Retirements of Existing Nuclear Capacity Under 60-Year Life Assumption
Impact of 60-Year Lifetime on Existing Nuclear
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12 For more info regarding the NRC's licensing extension program, see NRC website:
http://www.nrc.gov/reading-rm/doc-collections/fact-sheets/fs-reactor-license-renewal.html.
For an up to date list regarding license renewal status, see "Status of License Renewal Applications and Industry
Activities"; NRC website: http://www.nrc.qov/reactors/operatinq/licensinq/renewal/applications.html."
13 Real-world retirement decisions affecting some nuclear units such as Oyster Creek and San Onofre have occurred
prior to those units reaching 60 years in service.
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Heat rates, expressed in BTUs per kWh, are a metric of the efficiency of a generating unit. As in previous
versions of NEEDS, it is assumed in NEEDS v.5.13 that heat rates of existing units will remain constant
overtime. This assumption reflects two offsetting factors: (1) plant efficiencies tend to degrade overtime
and (2) increased maintenance and component replacement work to maintain or improve plant efficiency.
The heat rates in EPA Base Case v.5.13 are based on values from AEO 2013. These values were
screened and adjusted using a procedure developed by EPA to ensure that the heat rates used in EPA
Base Case v.5.13 are within the engineering capabilities of the generating unit types. Based on
engineering analysis, the upper and lower heat rate limits shown in Table 3-10 were applied to coal
steam, oil/gas steam, combined cycle, combustion turbine, and internal combustion engines. If the
reported heat rate for such a unit was below the applicable lower limit or above the upper limit, the limit
was substituted for the reported value.
Table 3-10 Lower and Upper Limits Applied to Heat Rate Data in NEEDS v.5.13
Plant Type
Coal Steam
Oil/Gas Steam
Combined Cycle - Natural Gas
Combined Cycle - Oil
Combustion Turbine - Natural Gas - > 80 MW
Combustion Turbine - Natural Gas < 80 MW
Combustion Turbine - Oil and Oil/Gas - > 80 MW
Combustion Turbine - Oil and Oil/Gas < 80 MW
1C Engine - Natural Gas
1C Engine - Oil and Oil/Gas - 5 MW and above
1C Engine - Oil and Oil/Gas < 5 MW
Heat Rate
Lower Limit
8,300
8,300
5,500
6,000
8,700
8,700
6,000
6,000
8,700
8,700
8,700
(Btu/kWh)
Upper Limit
14,500
14,500
15,000
15,000
18,700
36,800
25,000
36,800
18,000
20,500
42,000
3.9 Existing Environmental Regulations
This section describes the existing federal, regional, and state SO2, NOX, mercury, HCI and CO2
emissions regulations that are represented in the EPA Base Case v.5.13. The first four subsections
discuss national and regional regulations. The next two subsections describe state level environmental
regulations and a variety of legal settlements. The last subsection presents emission assumptions for
potential units.
3.9.1 SO2 Regulations
Unit-level Regulatory SO2 Emission Rates and Coal Assignments: Before discussing the national
and regional regulations affecting SO2, it is important to note that unit-level SO2 regulations arising out of
State Implementation Plan (SIP) requirements, which are not only state-specific but also county-specific,
are captured at model set-up in the coal choices given to coal fired existing units in EPA Base Case
v.5.13. The SIP requirements define "regulatory SO2 emission rates." Since SO2 emissions are
dependent on the sulfur content of the fuel used, the regulatory SO2 emission rates are used in IPM to
define fuel capabilities.
For instance, a unit with a regulatory SO2 emission rate of 3.0 Ibs/MMBtu would be provided only with
those combinations of fuel choices and SO2 emission control options that would allow the unit to achieve
an out-of-stack rate of 3.0 Ibs/MMBtu or less. If the unit finds it economical, it may elect to burn a fuel that
would achieve a lower SO2 rate than its specified regulatory emission limit. In EPA Base Case v.5.13
there are six different sulfur grades of bituminous coal, four different grades of subbituminous coal, five
different grades of lignite, and one sulfur grade of residual fuel oil. There are two different SO2 scrubber
options and one DSI option for coal units. Further discussion of fuel types and sulfur content is contained
in Chapter 9. Further discussion of SO2 control technologies is contained in Chapter 5.
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National and Regional SO2 Regulations: The national program affecting SO2 emissions in EPA Base
Case v.5.13 is the Acid Rain Program established under Title IV of the Clean Air Act Amendments
(CAAA) of 1990, which set a goal of reducing annual SO2 emissions by 10 million tons below 1980 levels.
The program, which became fully operational in year 2000, affects all SO2 emitting electric generating
units greater than 25 MWs. The program provides trading and banking of allowances over time across all
affected electric generation sources.
The annual SO2 caps over the modeling time horizon in EPA Base Case v.5.13 reflect the provisions in
Title IV. Since EPA Base Case v.5.13 uses year 2016 as the first analysis year, a projection of allowance
banking behavior through the end of 2015 and specification of the available 2016 allowances are needed
to initialize the modeling. EPA developed the projection of the banked allowances (30.6 million) going
into 2016. Calculating the available 2016 allowances involved deducting allowance surrenders due to
NSR settlements and state regulations from the 2016 SO2 cap of 8.95 million tons. The surrenders
totaled 142 thousand tons in allowances, leaving 8.808 million of 2016 allowances remaining. Table 7-4
shows the initial bank and 2016 allowance specification along with the SO2 caps for the entire modeling
time horizon. Specifics of the allowance surrender requirements understate regulations and NSR
settlements can be found in Table 3-13 and Table 3-14.
EPA Base Case v.5.13 also includes a representation of the Western Regional Air Partnership (WRAP)
Program, a regional initiative involving New Mexico, Utah, and Wyoming directed toward addressing
visibility issues in the Grand Canyon and affecting SO2 emissions starting in 2018. The WRAP
specifications for SO2 are presented in Table 7-4.
3.9.2 NOX Regulations
Much like SO2 regulations, existing NOX regulations are represented in EPA Base Case v.5.13 through a
combination of system level NOX programs and generation unit-level NOX limits. The NOX SIP Call trading
program is no longer represented since it was replaced by the requirements of the Clean Air Interstate
Rule (CAIR), described in section 3.9.4 below. Rhode Island is the only state from the NOx SIP Call that
is not covered in CAIR. Its NOX emission obligations under the NOX SIP Call are still included in EPA Base
Case v.5.13.
By assigning unit-specific NOX rates based on 2011 data, EPA Base Case v.5.13 is implicitly representing
Title IV unit-specific rate limits and Clean Air Act Reasonably Available Control Technology (RACT)
requirements for controlling NOX emissions from electric generating units in ozone non-attainment areas
or in the Ozone Transport Region (OTR).14 Unlike SO2 emission rates, NOX emission rates are assumed
not to vary with fuel, but are dependent on the combustion properties of the generating unit. Under the
EPA Base Case v.5.13 the NOX emission rate of a unit can only change if the unit is retrofitted with NOX
pollution control equipment or if it is assumed to install state-of-the-art NOX combustion controls.
NOy Emission Rates
Future emission projections for NOX are a product of a unit's utilization (heat input) and emission rate
(Ibs/mmbtu). A unit's NOX emission rate can vary significantly depending on the NOX reduction
requirements to which it is subject. For example, a unit may have a post-combustion control installed
(e.g., SCR or SNCR), but only operate it during the particular time of the year in which it is subject to NOX
reduction requirements (i.e., the unit only operates its post-combustion control during the ozone season).
Therefore, its ozone-season NOX emission rate would be lower than its non-ozone-season NOX emission
rate. Because the same individual unit can have such large variation in its emission rate, the model
needs a suite of emission rate "modes" from which it can select the value most appropriate to the
conditions in any given model scenario. The different emission rates reflect the different operational
conditions a unit may experience regarding upgrades to its combustion controls and operation of its
14 The OTR consists of the following states: Maine, New Hampshire, Vermont, Massachusetts, Rhode Island,
Connecticut, New York, New Jersey, Pennsylvania, Delaware, Maryland, District of Columbia, and northern Virginia.
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existing post-combustion controls. Four modes of operation are developed for each unit, with each mode
carrying a potentially different NOX emission rate for that unit under those operational conditions.
The emission rates assigned to each mode are derived from historic data (where available) and
presented in the NEEDS file. When the model is run, IPM selects one of these four modes through a
decision process depicted in
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Figure 3-4 below. The four modes address whether or not units upgrade combustion controls and/or
operate existing post-combustion controls; the modes themselves do not address what happens to the
unit's NOx rate if it is projected to add a new post-combustion NOx control. In such cases, after the
model selects the appropriate mode, the emission rate originally assigned to that mode is further adjusted
downward to reflect the retrofit of a SCR or SNCR. In this case, an emission rate is assumed that reflects
a percentage removal from the mode's emission rate or an emission rate floor (whichever is greater). The
full process for determining the NOx rate of units in EPA Base Case v.5.13 model projections is
summarized in Figure 3-3 below.
Figure 3-3 Modeling Process for Obtaining Projected NOX Emission Rates
Model Projection
Assignment of emission rates
(derived from historic data) to
each of four NOX Modes. Modes
reflect different potential
operational conditions at a unit.
Assignment of NOX emission rate
based on one of four NEEDS
"modes" rates with potential
adjustment if the unit is projected to
add post-combustion retrofit control
technology.
NOy Emission Rates in NEEDS, v.5.13 Database
The NOX rates in the current base case were derived, wherever possible, directly from actual monitored
NOX emission rate data reported to EPA under the Acid Rain and NOX Budget Program in 2011. The
emission rates themselves reflect the impact of applicable NOX regulations. For coal-fired units, NOX rates
were used in combination with detailed engineering assessments of NOX combustion control performance
to prepare a set of four possible starting NOX rates to assign to a unit, depending on the specific NOX
reduction requirements affecting that unit in a model run.
The reason for having a framework of four potential NOX rate "modes" applicable to each unit in NEEDS is
to enable the model to select from a range of NOX rates possible at a unit, given its configuration of NOX
combustion controls and its assumed operation of existing post-combustion controls. There are up to four
basic operating states for a given unit that significantly impact its NOX rate, and thus there are four NOX
rate "modes".
Mode 1: No post-combustion control operating; existing combustion controls
Mode 2: Post-combustion control operating, existing combustion controls
Mode 3: No post-combustion control operating; state-of-the-art (SOA) combustion controls (where
applicable)
Mode 4: Post-combustion control operating; state-of-the-art (SOA) combustion controls (where
applicable)
Emission rates derived for each unit operating under each of these four modes are presented in the
NEEDS file. Note, not every unit has a different emission rate for each mode, because certain units
cannot in practice change their NOX rates to conform to all potential operational states described above.
For instance, a unit without a post-combustion control will not have different emission rates between
modes 1 and 2, or between modes 3 and 4, as there is no post-combustion control that would potentially
turn on or off at these units. For such units, the mode 2 rate will simply equal the mode 1 rate, and the
mode 4 rate will equal the mode 3 rate.
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Figure 3-4 How One of the Four NOX Modes Is Ultimately Selected for a Unit
Did the source operate a
post-combustion control
in 2011?
Is the unit subject
to any new (post-
201 1)NOx
reduction
requirement?
For what season is
the model
assigning the
e rate?
Is it a seasonal or annual
requirement?
Mode 1: Existing combustion controls, no post-
combustion control operating
Mode 2 : Existing combustion controls, post-
combustion control operating (where applicable)
Mode 3 :
If SNCR - SOA combustion controls, no post
combustion control operating
If SCR - Mode 3 = Mode 1
Existing combustion controls, no post-combustion
controls operating (where applicable)
Annual
Mode 4:
If SNCR - SOA combustion controls, post-
combustion controls operating
If SCR-Mode 4 = Mode 2
Existing combustion controls, post-combustion
controls operating (where applicable)
State-of-the-art combustion controls (SOA combustion controls)
The definition of "state-of-the-art" varies depending on the unit type and configuration. Table 3-11
indicates the incremental combustion controls that are required to achieve a "state-of-the-art" combustion
control configuration for each unit. For instance if a wall-fired boiler (highlighted below) currently has
LNB, the "state-of-the-art" rate calculated for such a unit would assume a NOX emission rate reflective of
overfire air being added at the unit. The cost assumptions behind such an upgrade are described in
chapter 5. As described in the attachment of this chapter, the "state-of-the-art" combustion controls
reflected in the modes are only assigned to a unit if it is subject to a new (post-2011) NOX reduction
requirement (i.e., a NOX reduction requirement that did not apply to the unit during its 2011 operation that
forms the historic basis for deriving NOX rates for units in Base Case v.5.13). Existing reduction
requirements as of 2011 (e.g., NOX SIP Call) under which units have already made combustion control
decisions would not trigger the assignment of the "state-of-the-art" modes that reflect additional
combustion controls.
Table 3-11 State-of-the-Art Combustion Control Configurations by Boiler Type
Boiler Type
Cell
Cyclone
Stoker/SPR
Tangential
Vertical
Wall
Existing NOX
Combustion Control
LNB NCR
-
LA
LNB
LNB + OFA
LNC1a
LNC2
OFA
ROFA
-
LA
Incremental Combustion Control Necessary
to Achieve "State-of-the-Art"
OFA
LNB AND OFA
OFA
OFA
LNC3
LNC3
CONVERSION FROM LNC1 TO LNC3
CONVERSION FROM LNC1 TO LNC3
CONVERSION FROM LNC1 TO LNC3
CONVERSION FROM LNC2 TO LNC3
LNC1
LNB
NOX Combustion Control - Vertically Fired Units
LNB AND OFA
LNB AND OFA
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Boiler Type
Existing NOX
Combustion Control
LNB
LNF
OFA
Incremental Combustion Control Necessary
to Achieve "State-of-the-Art"
OFA
OFA
LNB
a LNC1 = low NOX coal-and air nozzles with close-coupled overfire air, LNC2 = Low NOX Coal-and-Air Nozzles with Separated
Overfire Air, LNC3 = Low NOX Coal-and-Air Nozzles with Close-Coupled and Separated Overfire Air
The emission rates for each generating unit under each mode are included in the NEEDS v5.13
database, described in Chapter 4. Attachment 3-1 and accompanying Tables 3-1.land 3-1.2 give further
information on the procedures employed to derive the four NOX modes.
Additional NOX rate assumptions include default NOX rates of 0.23 Ibs/MMBtu for existing biomass units
and 0.044 Ibs/MMBtu for existing landfill gas units.
Because of the complexity of the fleet and the completeness/incompleteness of historic data, there are
instances where the derivation of a unit's modeled NOX emission rate is more detailed than the
description provided above. For a more complete step-by-step description of the decision rules used to
develop the NOX rates, please see attachment 3-1.
3.9.3 Multi-Pollutant Environmental Regulations
CAIR
The Clean Air Interstate Rule (CAIR) uses a cap and trade system to reduce the target pollutantsSO2
and NOXfor 27 eastern states and DC.15 CAIR uses Title IV SO2 allowances as currency for the SO2
trading program. The initial bank and allowance totals for CAIR are the same as for the Acid Rain
Program above. For the Annual NOX trading program, the total Annual NOX allowances issued for 2016
was 1.2 million and the initial bank for 2016 was projected to be 1.5 million allowances. For the Ozone
Season NOX trading program, the total seasonal NOX allowances was 0.48 million and the initial bank
going into 2016 was projected to be 0.74 million. Table 7-4shows the initial bank and 2016 allowance
specification along with the caps for the entire modeling time horizon.
In 2008, the U.S. Court of Appeals for the District of Columbia Circuit remanded CAIR to EPA to correct
legal flaws in the proposed regulations as cited in the Court's July 2008 ruling. The Court allowed EPA to
proceed with implementation of the CAIR trading programs while EPA works on a replacement rule
addressing the Court's findings. CAIR's provisions were still in effect when EPA Base Case v.5.13 was
released and were included in the modeling. For more information on CAIR, go to
http://www.epa.gov/cair/.
MATS
Finalized in 2011, the Mercury and Air Toxics Rule (MATS) establishes National Emissions Standards for
Hazardous Air Pollutants (NESHAPS) for the "electric utility steam generating unit" source category,
which includes those units that combust coal or oil for the purpose of generating electricity for sale and
distribution through the electric grid to the public. EPA v.5.13 applies the input-based (Ibs/MMBtu) MATS
control requirements for mercury and hydrogen chloride to covered units. Treatment of the filterable PM
standard in the model is detailed in section 5.6.1. EPA Base Case v.5.13 does not model the alternative
SO2 standard offered under MATS for units to demonstrate compliance with the rule's HCI control
requirements. Coal steam units with access to lignite in the modeling are required to meet the "existing
15 The states included in the Clean Air Interstate Rule are Alabama, Arkansas, Connecticut, Delaware, Florida,
Georgia, Illinois, Indiana, Iowa, Kentucky, Louisiana, Maryland, Massachusetts, Michigan, Mississippi, Missouri, New
Jersey, New York, North Carolina, Ohio, Pennsylvania, South Carolina, Tennessee, Texas, Virginia, West Virginia
and Wisconsin.
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coal-fired unit low Btu virgin coal" standard. For more information on MATS, go to
http://www.epa.gov/mats/.
Regional Haze
The Clean Air Act establishes a national goal for returning visibility to natural conditions through the
"prevention of any future, and the remedying of any existing impairment of visibility in Class I areas [156
national parks and wilderness areas], where impairment results from manmade air pollution." On July 1,
1999, EPA established a comprehensive visibility protection program with the issuance of the regional
haze rule (64 FR 35714). This rule implements the requirements of section 169B of the CAAA and
requires states to submit State Implementation Plans (SIPs) establishing goals and long-term strategies
for reducing emissions of air pollutants (including SO2 and NOX) that cause or contribute to visibility
impairment. The requirement to submit a regional haze SIP applies to all 50 states, the District of
Columbia, and the Virgin Islands. Among the components of a long-term strategy is the requirement for
states to establish emission limits for visibility-impairing pollutants emitted by certain source types
(including EGUs) that were placed in operation between 1962 and 1977. These emission limits are to
reflect Best Available Retrofit Technology (BART). States may perform individual point source BART
determinations, or meet the requirements of the rule with an approved BART alternative. An alternative
regional SO2 cap for EGUs under Section 309 of the regional haze rule is available to certain western
states whose emission sources affect Class 1 areas on the Colorado Plateau.
Since 2010, EPA has approved or, in a very few cases, put in place regional haze Federal
Implementation Plans for several states. The BART limits approved in these plans (as of August 29,
2013) that will be in place for EGUs are represented in the EPA Base Case v.5.13 as follows.
Source-specific NOX or SO2 BART emission limits, minimum SO2 removal efficiency requirements for
FGDs, limits on sulfur content in fuel oil, constraints on fuel type (e.g., natural gas only or prohibition
of certain fuels such as petroleum coke), or commitments to retire units are applied to the relevant
EGUs.
EGUs in states that rely on CAIR trading programs to satisfy BART must meet the requirements of
CAIR.
EGUs in states that rely on state power plant rules to satisfy BART must meet the emission limits
imposed by those state rules.
For the three western states (New Mexico, Wyoming, and Utah) with approved Section 309 SIPs for
SO2 BART, emission constraints were not applied as current and projected emissions are well under
the regional SO2 cap.
Table 3-19 lists the NOX and SO2 limits applied to specific EGUs and other implementations applied in
IPM. For more information on Regional Haze Rule, go to: http://www.epa.qov/visibility/proqram.html
3.9.4 CO2 Regulations
The Regional Greenhouse Gas Initiative (RGGI) is a CO2 cap and trade program affecting fossil fired
electric power plants 25 MWor larger in Connecticut, Delaware, Maine, Maryland, Massachusetts, New
Hampshire, New York, Rhode Island, and Vermont. Table 7-4 shows the specifications for RGGI that are
implemented in EPA Base Case v.5.13.
As part of California's Assembly Bill 32 (AB32), the Global Warming Solutions Act, a multi-sector GHG
cap-and-trade program was established that targets 1990 emission levels by 2020. The cap begins in
2013 for electric utilities and large industrial facilities, with distributors of transportation, natural gas and
other fuels joining the capped sectors in 2015. In addition to in-state sources, the cap-and-trade program
also covers the emissions associated with qualifying, out-of-state EGUs that sell power into California.
Due to the inherent complexity in modeling a multi-sector cap-and-trade program where the participation
of out-of-state EGUs is determined based on endogenous behavior (i.e. IPM determines whether
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qualifying out-of-state EGUs are projected to sell power into California), EPA has developed a simplified
methodology to model California's cap-and-trade program:
Adopt the AB32 cap-and-trade allowance price from ElA's AEO2013 Reference Case, which fully
represents the non-power sectors. All qualifying fossil-fired EGUs in California are subject to this
price signal.
Estimate a marginal CO2 emission rate for each IPM region that exports power to California. This rate
is assumed to be the CO2 rate of the model plant with the highest variable cost in EPA Base Case
v.5.13.
For each IPM region that exports power to California, convert the $/ton CO2 allowance price
projection into a mills/kWh transmission wheeling charge using the marginal emission rate from the
previous step. The additional wheeling charge for qualifying out-of-state EGUs is equal to the
allowance price imposed on affected in-state EGUs. Applying the charge to the transmission link
ensures that power imported into California from out-of-state EGUs must account for the cost of CO2
emissions represented by its generation, such that the model may clear the California market in a
manner consistent with AB32 policy treatment of CO2 emissions.
3.9.5 State-Specific Environmental Regulations
EPA Base Case v.5.13 represents enacted laws and regulations in 26 states affecting emissions from the
electricity sector. Table 3-13 summarizes the provisions of state laws and regulations that are
represented in EPA Base Case v.5.13.
3.9.6 New Source Review (NSR) Settlements
New Source Review (NSR) settlements refer to legal agreements with companies resulting from the
permitting process under the CAAA which requires industry to undergo an EPA pre-construction review of
proposed environmental controls either on new facilities or as modifications to existing facilities where
there would result a "significant increase" in a regulated pollutant. EPA Base Case v.5.13 includes NSR
settlements with 31 electric power companies. A summary of the units affected and how the settlements
were modeled can be found in Table 3-14.
Eight state settlements and nine citizen settlements are also represented in EPA Base Case v.5.13.
These are summarized in Table 3-15 and Table 3-16 respectively.
3.9.7 Emission Assumptions for Potential (New) Units
Emissions from existing and planned/committed units vary from installation to installation based on the
performance of the generating unit and the emissions regulations that are in place. In contrast, there are
no location-specific variations in the emission and removal rate capabilities of potential new units. In IPM,
potential new units are modeled as additional capacity and generation that may come online in each
model region. Across all model regions the emission and removal rate capabilities of potential new units
are the same, and they reflect applicable federal emission limitations on new sources. The specific
assumptions regarding the emission and removal rates of potential new units in EPA Base Case v.5.13
are presented in Table 3-12. (Note: Nuclear, wind, solar, and fuel cell technologies are not included in
Table 3-12 because they do not emit any of the listed pollutants.) For additional details on the modeling
of potential new units, see Chapter 4.
3.9.8 Energy Efficiency and Renewable Portfolio Standards
Renewable Portfolio Standards (RPS) generally refers to various state-level policies that require the
addition of renewable generation to meet a specified share of state-wide generation. In EPA Base Case
v.5.13 the state RPS requirements are represented at a regional level utilizing the aggregate regional
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representation of RPS requirements that is implemented in AEO 2013 as shown in Table 3-17.16 This
table shows the RPS requirements that apply to the NEMS (National Energy Modeling System) regions
used in AEO. In addition, state level solar carve-out requirements have been implemented at a NEMS
region level in EPA Base Case v.5.13.
3.10 Capacity Deployment Constraints
EPA Base Case v.5.13 includes capacity deployment constraints for the more capital intensive generation
technologies and retrofits (new nuclear, advanced coal with carbon capture, and carbon capture retrofits).
The deployment constraints are intended to capture factors that are likely to place an upper bound on the
amount of these technologies that can be built in the real world in any given model run year over the
modeling time horizon. Such limiting factors include:
production capacity limitations (including the number of engineering and construction (E/C) firms
capable of executing large power projects in the U.S., the number of large projects each such firm
can handle, and the number of multi-billion dollar projects a firm can take on in parallel),
general limitations in the domestic infrastructure for heavy manufacturing,
financial limitations (number of projects that can obtain financing simultaneously at an acceptable
level of risk),
workforce limitations (limitations in the skilled engineering and construction labor force, replacement
challenges caused by an aging workforce, on the one hand, and inadequate training infrastructure for
new entrants, on the other).
The capacity deployment constraints are based on assessments by EPA power sector engineering staff
of historical trends and projections of capability going forward. Conceptually, the procedure used to
develop these constraints consisted of the following steps:
1. Start by estimating the maximum number of E/C firms that will be available over the time horizon.
2. Estimate the maximum number of a particular type of generating unit (e.g., 600 MW advanced coal
plant with carbon capture) that a single E/C firm can complete in the first 5-year period (2015-2020).
3. Multiply the number of E/C firms estimated in Step 1 by the number of units per firm found in Step 2
to obtain the maximum number of these generating units that can be completed in the first period.
4. Determine if there will be competition from other competing technologies for the same productive
capacity and labor force used for the technology analyzed in steps 2 and 3. If not, go to Step 7. If so,
go to Step 5.
5. Establish an equivalency table showing how much capacity could be built if the effort required to build
1 MWof the type of technology analyzed in steps 2 and 3 were instead used to build another type of
generating technology (e.g., 1600 MW nuclear plant).
6. Based on these calculations build a production possibility frontier showing the maximum mix of the
two generating technologies that can be added in the first 5-year period.
7. Over the subsequent five year periods assume that the E/C firms have increased capabilities relative
to the previous five year period. Represent the increased capability by a capability multiplier. For
example, it might be assumed that each succeeding 5-year period the E/C firms can design and build
1.4 as much as in the immediately preceding 5-year period. Multiply the capacity deployment limit(s)
from the preceding period by the capability multiplier to derive the capacity deployment limit for the
subsequent period.
16 Energy Information Administration, U.S. Department of Energy, Assumptions to Annual Energy Outlook 2013:
Renewable Fuels Module (DOE/EIA-0554(2010)), April 15, 2013, Table 13.2 "Aggregate Regional Renewable
Portfolio Standard Requirements," http://www.eia.qov/forecasts/aeo/assumptions/pdf/renewable.pdf.
3-29
-------
8. If necessary, prevent sudden spikes in capacity in later periods when there has been little or no build
up in preceding periods by tying the amount of capacity that can be built in a given period to the
amount of capacity built in preceding periods.
Attachment 3-2 shows the joint capacity deployment constraint on advanced coal with carbon capture and
storage (CCS) and new nuclear. Attachment 3-3 shows the capacity deployment constraint on new
nuclear in itself. The bar graph in Attachment 3-3 illustrates how building capacity in earlier years
increases the maximum capacity that can be built over the entire modeling time horizon.
3-30
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Table 3-12 Emission and Removal Rate Assumptions for Potential (New) Units in EPA Base Case v.5.13
SO2
NOx
Hg
CO2
HCL
Controls,
Removal,
and
Emissions
Rates
Removal /
Emissions
Rate
Emission
Rate
Removal /
Emissions
Rate
Removal /
Emissions
Rate
Removal /
Emissions
Rate
Supercritical
Pulverized
Coal
96% with a
floor of 0.06
Ibs/MMBtu
0.07
Ibs/MMBtu
90%
202.8-215.8
Ibs/MMBtu
99% 0.0001
Ibs/MMBtu
Integrated
Gasification
Combined
Cycle
99%
0.013
Ibs/MMBtu
90%
202.8-215.8
Ibs/MMBtu
99% 0.0001
Ibs/MMBtu
Integrated
Gasification
Combined Cycle
with Carbon
Sequestration
99%
0.01 3 Ibs/MMBtu
90%
90%
99% 0.0001
Ibs/MMBtu
Advanced
Combined
Cycle
None
0.011
Ibs/MMBtu
Natural Gas:
0.000138
Ibs/MMBtu
Oil:
0.483
Ibs/MMBtu
Natural Gas:
117.08
Ibs/MMBtu
Oil:
161.39
Ibs/MMBtu
Advanced
Combined Cycle
with Carbon
Sequestration
None
0.011 Ibs/MMBtu
Natural Gas:
0.000138
Ibs/MMBtu
Oil:
0.483 Ibs/MMBtu
90%
Advanced
Combustion
Turbine
None
0.011
Ibs/MMBtu
Natural Gas:
0.000138
Ibs/MMBtu
Oil:
0.483
Ibs/MMBtu
Natural Gas:
117.08
Ibs/MMBtu
Oil:
161.39
Ibs/MMBtu
Biomass-
Bubbling
Fluid ized
Bed (BFB)
0.08
Ibs/MMBtu
0.02
Ibs/MMBtu
0.57
Ibs/MMBtu
None
Geothermal
None
None
3.70
None
Landfill
Gas
None
0.09
Ibs/MMBtu
None
None
3-31
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Attachment 3-1 NOX Rate Development in EPA Base Case v.5.13
The following questions (Q) and answers (A) are intended to provide further background on the four NOX
rates found in the NEEDS v5.13 database.
Q1: Why are four NOX rates included in NEEDS?
A1: The four NOX rates in NEEDS represent a menu of all the NOX rates applicable to a specific
generating unit with only its current configuration of NOX combustion and post-combustion controls under
all the conceivable operating conditions involving NOX controls that might be modeled in the future. By
defining this menu up front for every generating unit, the program that sets up an IPM run can follow a set
of decision rules to select the rate(s) appropriate for the unit in the particular scenario being modeled
consistent with the unit's existing set of combustion and post-combustion NOX controls.
Q2: What operational states do the four NOX rates represent?
A2: Before answering this question, let's name the four NOX rates that are in NEEDS and the general
control states they reflect
Mode 1= Existing combustion controls, no post-combustion control operation
Mode 2= Existing combustion controls, post-combustion control operation (where applicable)
Mode 3= SOA combustion controls (where applicable), no post-combustion control operation
Mode 4 = SOA combustion controls, post-combustion control operation (where applicable)
Please see Figure 3-4 in Section 3.9.2 for an explanation of how the model selects the appropriate NOx
mode for each unit in the projection scenario.
Q3: How are emission rates calculated for each unit for each of the four NOX modes?
A3: We start with the emission data reported to EPA for a specific year under Title IV of the Clean Air Act
Amendments of 1990 (Acid Rain Program) and NOX Budget Program. Using this data, NOX rates are
derived for the summer and winter seasons.
Calculations can get complex, so we'll illustrate it here for coal units only and with the assumption that the
data were absolutely complete and consistent with what engineering theory tells us its values should be.
Otherwise, we apply additional screens. Explaining the additional steps involved in those anamolous
case-by-case evaluations is beyond the scope of this illustration. However, the process below describes
how the values would generally be derived:
The procedure employs the following hierarchy of NOX rate data sources:
1. 2011 ETS
2. Comments on NOX rate
3. 2009 ETS
4. 2010 EIA Form 860
5. Defaults
The existing coal steam boilers in US are categorized into three groups depending on the configuration of
NOX combustion and post-combustion controls.
Group 1 - Coal boilers without post-combustion NOX controls
Mode 1 =2011 ETS Annual Average NOX Rate
Mode 2 = Mode 1
Mode 3
Mode 3 calculation follows Steps 1-7:
Step 1: Pre-screen units that already have state of art (SOA) combustion controls from units that have
non- SOA combustion controls from units that have no combustion controls
3-32
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Step 2: For units listed as not having combustion controls
Make sure their NOX rates do not indicate that they really do have SOA control
If Mode 1 > Cut-off (in Table 3-1.1), then Mode 1 = Base NOX rate. Go to Step 6
If Mode 1 < Cut-off (in Table 3-1.1), then the unit has SOA control and
Mode 3 = Mode 1
Step 3: For units listed as having SOA combustion controls.
Mode 3 = Mode 1
Step 4: For units listed as not having SOA combustion controls
Make sure their NOX rates do not indicate that they really do have SOA control
If Mode 1 < Cut-off (in Table 3-1.1), then the unit has SOA control and
Mode 3 = Mode 1
If Mode 1 > Cut-off (in Table 3-1.1), then go to Step 5
Step 5: Determine the unit's Base NOX rate, i.e., the unit's uncontrolled emission rate without combustion
controls, using the appropriate equation (not in boldface italics) in Table 3-1.2 to back calculate their Base
NOX rate. Use the default Base NOX rate values if back calculations can't be performed. Once the Base
NOX rate is obtained, go to Step 6.
Step 6: Use the appropriate equations (in boldface italics) in Table 3-1.2 to calculate the NOX rate with
SOA combustion controls.
Step 7: Compare the value calculated in Step 6 to the applicable NOX floor rate in Table 3-1.1.
If the value from Step 6 is > floor, use the Step 6 value as Mode 3. Otherwise, use the floor as the Mode 3
NOX rate.
Mode 4
Mode 4 =Mode 3
Group 2 - Coal boilers with SCR
Pre-screen coal boilers with 2011 ETS NOX rates into the following four operating regimes. A coal boiler is
assumed to be operating its SCR when the seasonal NOX rate is less than 0.2 Ibs/MMBtu
Group 2.1 SCR is not operating in both summer and winter seasons
Follow the NOX rate rules summarized for Group 1 boilers. No state of the art combustion controls are
implemented.
Mode 1 = 2011 ETS Annual Average NOX Rate Mode 2 = maximum {(1 -0.9) * Mode 1, 0.07} Mode 3 =
Mode 1
Mode 4 = Mode 2
Group 2.2 SCR is operating in summer only
Mode 1 = 2011 ETS Winter NOX Rate
Mode 2 = 2011 ETS Summer NOX Rate
Mode 3 = Mode 1
Mode 4 = Mode 2
Group 2.3 SCR is operating in winter only
Mode 1 = 2011 ETS Summer NOX Rate
Mode 2 = 2011 ETS Winter NOX Rate
Mode 3 = Mode 1
Mode 4 = Mode 2
3-33
-------
Group 2.4 SCR is operating year-round
Mode 1 = if (2009 ETS Winter NOX Rate > 0.2, 2009 ETS Winter NOX Rate, 2011 ETS Annual Average
NOX Rate)17
Mode 2 = 2011 ETS Annual Average NOX Rate
Mode 3 = Mode 1
Mode 4 = Mode 2
Group 3 - Coal boilers with SNCR
Step 1: Pre-screen coal boilers with 2011 ETS NOX rates to verify if they have not operated their SNCR in
both summer and winter seasons. A coal boiler is assumed to be not operating its SNCR when the NOX
rate is greater than 0.3 Ibs/MMBtu in both summer and winter seasons.
Group 3.1 SNCR is not operating in both summer and winter seasons
Follow the NOX rate rules summarized for Group 1 boilers
Step 2: Pre-screen coal boilers with 2011 ETS NOX rates into the following three operating regimes. First
estimate the implied removal for a coal boiler using the following equation:
Implied Removal (%) = ((Winter NOX Rate - Summer NOX Rate)/ Winter NOX Rate) * 100
Second, assign the coal boiler to a specific operating regime based on the following logic.
If Implied Removal > 20% then SNCR is operating in summer season only,
Else if Implied Removal < -20% then SNCR is operating in winter season only,
Else SNCR is operating year-round
Second, assign the coal boiler to a specific operating regime based on the following logic.
Group 3.2 SNCR is operating in summer only
Mode 1 = 2011 ETS Winter NOX Rate
Mode 2= 2011 ETS Summer NOX Rate
Mode 3 = same as Group 1 Mode 3
Mode 4 = maximum {(1-0.25)* Mode 3, 0.1}fornon FBC units
Mode 4 = maximum {(1-0.50) * Mode 3, 0.08} for FBC units
Note: The (1-.25) and (1-0.5) terms in the equations above represents the NOX removal efficiencies of
SNCR for non FBC and FBC boilers.
Group 3.3 SNCR is operating in winter only
Mode 1 = 2011 ETS Summer NOX Rate
Mode 2 = 2011 ETS Winter NOX Rate
Mode 3 = same as Group 3.2 Mode 3
Mode 4 = same as Group 3.2 Mode 4
Group 3.4 SNCR is operating year-round
Mode 1= if (2009 ETS Winter NOX Rate > 0.3, 2009 ETS Winter NOX Rate, 2011 ETS Annual Average
NOX Rate)
Mode 2 = 2011 ETS Annual Average NOX Rate
Mode 3 = same as Group 3.2 Mode 3
Mode 4 = Mode 3
Other things worth noting are:
17 This equation implies that if a unit with a SCR operates year round in ETS 2011 and in winter in ETS 2009, then Mode 1 NOX rate
will reflect SCR operation.
3-34
-------
(a) In general, winter NOX rates reported in EPA's Emission Tracking System were used as proxies for
assigning emission rates to Mode 1.
(b) If a unit does not report having combustion controls, but has an emission rate below a specific cut-off
rate (shown in Table 3-1.1), it is considered to have combustion controls.
(c) For units with combustion controls that were not state-of-the-art, the derivation of an emission rate
reflecting an upgrade to state-of-the-art combustion controls necessitated calculating (as an interim step)
the unit's emission rate if it were to "uninstall" its existing combustion controls. That interim "no
combustion controls" emission rate becomes the departure point for calculating the unit's emission rate
assuming a state-of-the-art combustion control configuration.
(d) The NOX rates achievable by state-of-the-art combustion controls vary by coal rank (bituminous and
subbituminous) and boiler type. The equations used to derive these rates are shown in Table 3-1.2
3-35
-------
Table 3-1.1 Cutoff and Floor NOX Rates (Ib/MMBtu) in EPA Base Case v.5.13
Boiler Type
Wall-Fired Dry-Bottom
Tangentially-Fired
Cell-Burners
Cyclones
Vertically-Fired
Cutoff Rate (Ibs/MMBtu)
Bituminous Subbituminous
0.43 0.33
0.34 0.24
0.43 0.43
0.62 0.67
0.57 0.44
Lignite
0.29
0.22
0.43
0.67
0.44
Floor Rate (Ibs/MMBtu)
Bituminous Subbituminous
0.32 0.18
0.24 0.12
0.32 0.32
0.47 0.49
0.49 0.25
Lignite
0.18
0.17
0.32
0.49
0.25
Table 3-1.2 NOX Removal Efficiencies for Different Combustion Control Configurations in EPA Base Case v.5.13
(State of the art configurations are shown in bold italic.)
Boiler Type
Dry Bottom Wall-Fired
Dry Bottom Wall-Fired
Tangentially-Fired
Tangentially-Fired
Coal Type
Bituminous
Subbituminous/Lignite
Bituminous
Subbituminous/Lignite
Combustion Control Technology
LNB
LNB + OFA
LNB
LNB + OFA
LNC1
LNC2
LNC3
LNC1
LNC2
LNC3
Fraction of Removal
0.1 63 + 0.272* Base NOX
0.31 3 + 0.272* Base NOX
0.135 + 0.541* Base NOX
0.285 + 0.541* Base NOX
0.1 62 + 0.336* Base NOX
0.212 + 0.336* Base NOX
0.362 + 0.336* Base NOX
0.20 + 0.71 7* Base NOX
0.25 + 0.71 7* Base NOX
0.35 + 0.71 7* Base NOX
Default Removal
0.568
0.718
0.574
0.724
0.42
0.47
0.62
0.563
0.613
0.713
Notes:
LNB = Low NOX Burner
OFA = Overfire Air
LNC = Low NOX Control
3-36
-------
Attachment 3-2 Capacity Deployment Limits for Advanced Coal with CCS and
New Nuclear in EPA Base Case v.5.13
Run
Year
2016
2018
2020
2025
2030
2040
2050
Advanced Coal with New Nuclear
CCS (MW) (MW) Notes:
I he 2020 through 2050 limits tor Advanced Coal with CCS and New
Nuclear technologies are a joint constraint, with the maximum amount of
possible development for each technology shown by run year. If the
' o.uuu maximum amount of one technology is developed in a given run year, zero
17,254 13,272 MW Of the other may be developed. See the production possibility chart
31,750 24,423 below.
106,211 81,701
301,097 231,613
250,000 -i
200,000
^
03
o 150,000
Z
z
100,000
50.00C
C
)
Production Possibility Curves (Incremental Capacity in MW by Run Year)
**.
---,,
----....
*"^ซ.^ 2050
****^
----,..
*ปซป 2040 "**ซ.
*^""-""-._ """---.
0 50,000 100,000 150,000 200,000 250,000 300
Advanced Coal with CCS
>
,000
3-37
-------
Attachment 3-3 Nuclear Capacity Deployment Constraint in EPA Base Case v.5.13
Run
Year
Base New
Nuclear
Capacity
Base New Nuclear Capacity Deployment
Equation
Possible Additional New Nuclear
Capacity Deployment Equation1
Maximum Annual Incremental New Nuclear Capacity
Deployment Allowed Equation
2020
2025
2030
2040
2050
5,000
4,400
3,872
19,208
37,648
5,000
0.88 * 2020_Base_Capacity
0.88 * 2025_Base_Capacity
4.96 * 2030_Base_Capacity
1.96 * 2040_Base_Capacity
0
+ 0.88 * 2020_lncremental_Capacity
+ 0.88 * 2025_lncremental_Capacity
+ 4.96 * 2030_lncremental_Capacity
+ 1.96 * 2040_lncremental_Capacity
5,000
= 0.88 * (2020_Base_Capacity + 2020_lncremental_Capacity)
0.88 * (2025_Base_Capacity + 2020_lncremental_Capacity)
4.96 * (2030_Base_Capacity + 2030_lncremental_Capacity)
1.96 * (2040_Base_Capacity + 2040_lncremental_Capacity)
Run
Year
2020
2025
2030
2040
2050
Maximum Possible New Nuclear Capacity Deployment Allowed
Deployment Starts 2020
Incremental Cumulative
5,000 5,000
8,272 13,272
11,151 24,423
57,278 81 ,701
149,912 231,613
Deployment Starts 2025
Incremental Cumulative
0 0
4,400 4,400
7,744 12,144
43,010 55,154
121,948 177,102
Deployment Starts 2030
Incremental Cumulative
0 0
0 0
3,872 3,872
26,797 30,669
90,170 120,839
Deployment Starts 2040
Incremental Cumulative
0 0
0 0
0 0
19,208 19,208
75,295 94,503
Deployment Starts 2050
Incremental Cumulative
0 0
0 0
0 0
0 0
37,648 37,648
Notes:
No nuclear deployment is allowed before 2020
1Addtional new nuclear capacity deployment is only possible if nuclear capacity has been built in the previous run year.
3-38
-------
Maximum Possible Cumulative New Nuclear Capacity Each Run Year
2050
2040
Run Years
2030
2025
2020
50,000
100,000
150,000 200,000
Capacity (MW)
250,000
300,000
350,000
A Deployment Starts 2050 ป Deployment Starts 2040 & Deployment Starts 2030 Deployment Starts 2025 Deployment Starts 2020
3-39
-------
Table 3-13 State Power Sector Regulations included in EPA Base Case v.5.13
State/Region
Alabama
Arizona
California
Colorado
Connecticut
Delaware
Bill
Alabama Administrative Code
Chapter 335-3-8
Title 18, Chapter 2, Article 7
CA Reclaim Market
CA AB 32
40 C.F.R. Part 60
Clean Air, Clean Jobs Act
Executive Order 19 and Regulations
of Connecticut State Agencies
(RCSA)22a-1 74-22
Executive Order 19, RCSA 22a-198
& Connecticut General Statues
(CGS)22a-198
Public Act No. 03-72 & RCSA 22a-
198
Regulation 1148: Control of
Stationary Combustion Turbine
EGU Emissions
Regulation No. 1146: Electric
Generating Unit (EGU) Multi-
Pollutant Regulation
Emission Type
NOX
Hg
NOX
SO2
CO2
Hg
NOX, SO2, Hg
NOX
SO2
Hg
NOX
NOX
SO2
Emission Specifications
0.02 Ibs/MMBtu for combined cycle EGUs which commenced
operation after April 1, 2003; For combined-cycle electric
generating units fired by natural gas: 4.0 ppmvd at 15% O2
(0.0178 Ibs/MMBtu), by fuel oil- 15.0 ppmvd at 15% O2 (0.0667
Ibs/MMBtu)
90% removal of Hg content of fuel or 0.0087 Ibs/GWh annual
reduction for all non-cogen coal units > 25 MW
9.68 MTons annual cap for list of entities in Appendix A of "Annual
RECLAIM Audit Market Report for the Compliance Year 2005"
(304 entities)
4.292 MTons annual cap for list of entities in Appendix A of
"Annual RECLAIM Audit Market Report for the Compliance Year
2005" (304 entities)
Power sector and Non-power Sector Cap in Million metric tons:
382.40 in 2016, 358.30 in 2018 and 334.20 2020 onwards.
2012 & 2013: 80% reduction of Hg content of fuel or 0.01 74
Ibs/GWh annual reduction for Pawnee Station 1 and Rawhide
Station 101.
201 4 through 2016: 80% reduction of Hg content of fuel or 0.01 74
Ibs/GWh annual reduction for all coal units > 25 MW
2017 onwards: 90% reduction of Hg content of fuel or 0.0087
Ib/GWh annual reduction for all coal units > 25 MW
Retire Arapahoe 3 by 2014; Cherokee 1 & 2 by 2012, Cherokee 3
by 2017; Cameo 1 & 2; Valmont 5 by 2018; W N Clark 55 & 59
by 201 5
Convert following units to natural gas: Arapahoe 4 by 2015;
Cherokee 4 by 201 8
Install SCRs in Hayden 1 & 2 by 2016; SCR + FGD in Pawnee 1
[already installed]
0.15 Ibs/MMBtu annual rate limit for all fossil units > 15 MW
0.33 Ibs/MMBtu annual rate limit for all fossil units > 25 MW (Title
IV Sources)
0.55 Ibs/MMBtu annual rate limit for all non-fossil units > 15 MW
and fossil units < 25MW and > 15MW (Non-Title IV Sources)
90% removal of Hg content of fuel or 0.0087 Ibs/GWh annual
reduction for all coal-fired units
0.19 Ibs/MMBtu ozone season PPMDV for stationary, liquid fuel
fired CT EGUs >1 MW
0.39 Ibs/MMBtu ozone season PPMDV for stationary, gas fuel
fired CT EGUs >1 MW
0.125 Ibs/MMBtu rate limit of NOX annually for all coal and
residual-oil fired units > 25 MW
0.26 Ibs/MMBtu annual rate limit for coal and residual-oil fired
units > 25 MW
Implementation
Status
2003
2017
1994
2012
2012
2010
2003
2008
2009
2009
Notes
Since the Reclaim Trading
Credits are applicable to entities
besides power plants, we
approximate by hardwiring the
NOX and SO2 allowance prices
for the calendar year 2006.
Refer to Section 3.9.4 for details
The following units have
specific NOX, SO2, and Hg
annual caps in MTons:
Edge Moor 3: 0.773 NOX, 1 .391
3-40
-------
State/Region
Georgia
Illinois
Bill
Regulation 1108: Distillate Fuel Oil
rule
Multi-pollutant Control for Electric
Utility Steam Generating Units
Title 35, Section 21 7.706
Title 35, Part 225, Subpart B
225.230
Title 35 Part 225 Subpart B 225.233
Title 35 Part 225 Subpart B 225.233
(MPS Ameren specific)
Title 35 Part 225; Subpart F:
Combined Pollutant Standards
(REPEALED)
Emission Type
Hg
SO2
SCR, FGD, and
Sorbent Injection
Baghouse controls
to be installed
NOX
Hg
NOX
SO2
Hg
NOx
SO2
NOX
SO2
Hg
Emission Specifications
2012: 80% removal of Hg content of fuel orO.0174 Ibs/GWh
annual reduction for all coal units > 25 MW
2013 onwards: 90% removal of Hg content of fuel or 0.0087
Ibs/GWh annual reduction for all coal units > 25 MW
Any relevant units are to use 0.3% sulfur distillate fuel oil
The following plants must install controls: Bowen, Branch,
Hammond, McDonough, Scherer, Wansley, and Yates
0.25 Ibs/MMBtu summer season rate limit for all fossil units > 25
MW
90% removal of Hg content of fuel; or a standard of .0080 Ib
Hg/GWh for sources at or above 25 MW; If facility commenced
operation on or before December 31 , 2008, start date for
implementation must be July 1 , 2009
0.11 Ibs/MMBtu annual rate limit and ozone season rate limit for
all coal steam units > 25 MW
2015 onwards: 0.25 Ibs/MMBtu annual rate limit for all coal steam
units > 25 MW or a rate equivalent to 35% of the base SO2
emissions (whichever is more stringent)
90% removal of Hg content of fuel or 0.08 Ibs/GWh annual
reduction for all coal units > 25 MW
0.11 Ibs/MMBtu annual rate limit and ozone season rate limit
Ameren coal steam units > 25 MW
2015 & 2016 onwards: 0.25 Ibs/MMBtu annual rate limit for all
Ameren coal steam units > 25 MW
2017 onwards: 0.23 Ibs/MMBtu annual rate limit for all Ameren
coal steam units > 25 MW
0.11 Ibs/MMBtu ozone season and annual rate limit for all
specified Midwest Gen coal steam units
0.44 Ibs/MMBtu annual rate limit in 2013, decreasing annually to
0.11 Ibs/MMBtu in 201 9 for all specified Midwest Gen coal steam
units
90% removal of Hg content of fuel or 0.08 Ibs/GWh annual
reduction for all specified Midwest Gen coal steam units
Implementation
Status
2012
Implementation from
2008 through 201 5,
depending on plant
and control type
2003
2009
2012
2015
2015
2012
2015
2012
2013
2015
Notes
SO2, & 2012: 0.0000083 Hg,
2013 onwards: 0.0000033 Hg
Edge Moor 4: 1.339 NOX, 2.41
SO2, & 2012: 0.0000144 Hg,
2013 onwards: 0.0000057 Hg
Edge More 5: 1 .348 NOX &
2.427 SO2
Indian River 3: 0.977 NOX,
1 .759 SO2, & 2012: 0.0000105
Hg, 2013 onwards: 0.0000042
Hg
Indian River 4: 2.032 NOX,
3.657 SO2, & 2012: 0.0000219
Hg, 2013 onwards: 0.0000087
Hg
McKeeRun30.244NOx&
0.439 SO2
Fuel rule modeled through unit
emission rates
Not Ameren Specific
Not Ameren Specific
REPEALED
3-41
-------
State/Region
Louisiana
Maine
Maryland
Massachusett
s
Bill
Title 33 Part 1 1 - Chapter 22 , Control
of Nitrogen Oxides
Title 33, Part III - Chapter 15,
Emission Standards for Sulfur
Dioxide
Chapter 145 NOX Control Program
38 MRSA Section 603-A Low Sulfur
in Fuel Rule
Statue 585-B Title 38, Chapter 4:
Protection and Improvement of Air
Maryland Healthy Air Act
310 CMR 7.29
310 CMR 7.04
Emission Type
NOX
SO2
NOX
SO2
Hg
NOX
SO2
Hg
NOX
SO2
Hg
SO2
Emission Specifications
For units >/= 80 MMBtu/hr, rate limit in Ibs/MMBtu:
Coal fired : 0.21
Oil-fired: 0.18
All others (gas or liquid): 0.1
Stationary Sources >/= 10 MMBtu/hr, rate limit in Ibs/MMBtu:
Oil-fired: 0.3
Gas-fired: 0.2
1 .2 Ibs/MMBtu ozone season ppmvd for all single point sources
that emit or have the potential to emit 5 tons or more of SO2
0.22 Ibs/MMBtu annual rate limit for all fossil fuel units > 25 MW
built before 1995 with a heat input capacity < 750 MMBtu/hr.
0.15 Ibs/MMBtu annual rate limit for all fossil fuel units > 25 MW
built before 1995 with a heat input capacity > 750 MMBtu/hr.
0.20 Ibs/MMBtu annual rate limit for all fossil fuel fired indirect
heat exchangers, primary boilers, and resource recovery units
with heat input capacity > 250 MMBtu/hr
All fossil units require the use of 0.5% sulfur residual oil [0.52
Ibs/MMBtu]
25 Ibs annual cap for any facility including EGUs
7.3 MTons summer cap and 16.7 MTons annual cap for 15
specific existing coal steam units
2009 through 2012: 48.6 MTons annual cap for 15 specific
existing coal steam units
2013 onwards: 37.2 MTons annual cap for 15 specific existing
coal steam units
2010 through 2012: 80% removal of Hg content of fuel for 15
specific existing coal steam units
2013 onwards: 90% removal of Hg content of fuel for 15 specific
existing coal steam units
1 .5 Ibs/MWh annual GPS for Brayton Point, Mystic Generating
Station, Mount Tom, Canal, and Salem Harbor
3.0 Ibs/MWh annual GPS for Brayton Point, Mystic Generating
Station, Mount Tom, Canal, and Salem Harbor
2012: 85% removal of Hg content of fuel or 0.00000625 Ibs/MWh
annual GPS for Brayton Point, Mystic Generating Station, Mount
Tom, Canal, and Salem Harbor
2013 onwards: 95% removal of Hg content of fuel or 0.0000025
Ibs/MWh annual GPS for Brayton Point, Mystic Generating
Station, Mount Tom, Canal, and Salem Harbor
Sulfur in Fuel Oil Rule requires the use of 0.5% sulfur residual oil
[0.52 Ibs/MMBtu] by July 1, 2014 for units greater than 250
MMBtu energy input; by July 1, 201 8 for all residual oil units
except for those located in the Berkshire APCD.
Implementation
Status
2005
2005
2018
2010
2009
2006
2014
Notes
Applicable for all units in Baton
Rouge Nonattainment Area &
Region of Influence.
Willow Glenn, located in
Iberville, obtained a permit that
allows its gas-fired units to
maintain a cap. These units are
separately modeled.
Fuel rule modeled through unit
emission rates
Brayton units 1 through 3 have
an annual Hg cap of 0.0000733
MTons
Mt. Tom 1 has an annual Hg
cap of 0.00000205 MTons
Salem Harbor units 1 through 3
have an annual Hg cap of
0.0000106 MTons
Fuel rule modeled through unit
emission rates
3-42
-------
State/Region
Michigan
Minnesota
Missouri
Montana
New
Hampshire
Bill
Part 18 Rules - R 336.1801 (2) (a)
Part 15. Emission Limitations and
Prohibitions - Mercury
Minnesota Hg Emission Reduction
Act
10 CSR 10-6.350
Montana Mercury Rule Adopted
10/16/06
RSA125-O: 11-18
ENV-A2900 Multiple pollutant
annual budget trading and banking
program
Haze
N.J.A.C. 7:27-27.5, 27.6, 27.7, and
27.8
N.J. A. C. Title 7, Chapter 27,
Subchapter 19, Table 1
Emission Type
NOX
Hg
Hg
NOX
Hg
Hg
NOX
SO2
SO2
NOX
Hg
NOX
Emission Specifications
For all fossil units > 25 MW, and annual PTE of NOX >25 tons,.25
Ibs/MMBtu ozone season rate, OR 65% NOX reductions from
1990 levels
SO2 ppmvd rates in 50% excess air for units in Wayne county:
Pulverized coal: 550;Other coal: 420;Distillate oil Nos. 1 & 2:
120;Used oil: 300;Crude and Heavy oil: 400
For all other units,
with 0-500,000 Ibs Steam per Hour Plant Capacity: 2.5
with >500,000 Ibs Steam per Hour Plant Capacity: 1 .67
90% removal of Hg content of fuel annually for all coal units > 25
MW
90% removal of Hg content of fuel annually for all coal facilities >
500 MW combined; Dry scrubbed units must implement by
December 31, 2010; Wet scrubbed units must implement by
December 31, 2014.
0.25 Ibs/MMBtu annual rate limit for all fossil fuel units > 25 MW in
the following counties: Bellinger, Butler, Cape Girardeau, Carter,
Clark, Crawford, Dent, Dunklin, Gasconade, Iron, Lewis, Lincoln,
Madison, Marion, Mississippi, Montgomery, New Madrid, Oregon,
Pemiscot, Perry, Phelps, Pike, Rails, Reynolds, Ripley, St.
Charles, St. Francois, Ste. Genevieve, Scott, Shannon, Stoddard,
Warren, Washington and Wayne
0.18 Ibs/MMBtu annual rate limit for all fossil fuel units > 25 MW
the following counties: City of St. Louis, Franklin, Jefferson, and
St. Louis
0.35 Ibs/MMBtu annual rate limit for all fossil fuel units > 25 MW in
the following counties: Buchanan, Jackson, Jasper, Randolph,
and any other county not listed
0.90 Ibs/TBtu annual rate limit for all non-lignite coal units
1 .50 Ibs/TBtu annual rate limit for all lignite coal units
80% reduction of aggregated Hg content of the coal burned at the
facilities for Merrimack Units 1 & 2 and Schiller Units 4, 5, & 6
2.90 MTons summer cap for all fossil steam units > 250 MMBtu/hr
operated at any time in 1990 and all new units > 15 MW
3.64 MTons annual cap for Merrimack 1 & 2, Newington 1 , and
Schiller 4 through 6
7.29 MTons annual cap for Merrimack 1 & 2, Newington 1 , and
Schiller 4 through 6
90% SO2 control at Merrimack 1 & 2; 0.5 Ib SO2/MMBtu 30 day
rolling average at Newington 1
0.30 Ib NOx/MMBtu 30-day rolling average at Merrimack 2; 0.35 Ib
NOx/MMBtu when burning oil and 0.25 Ib NOx/MMBtu when
burning oil and gas at Newington 1 (permit condition).
90% removal of Hg content of fuel annually for all coal-fired units
or <= 3.0 mg/MWh (net)
95% removal of Hg content of fuel annually for all MSW
incinerator units or <= 28 ug/dscm
Annual rate limits in Ibs/MMBtu for the following technologies:
1 .0 for tangential and wall-fired wet-bottom coal boilers serving an
ECU
0.60 for cyclone-fired wet-bottom coal boilers serving an ECU
Implementation
Status
2004
2015
2006
2004
2010
2012
2007
2013
2007
2007
Notes
Not modeled in IPM as limits
are within SIP rates
3-43
-------
State/Region
New York
Bill
N.J. A. C. Title?, Chapter 27,
Subchapter 19, Table 2
N.J. A. C. Title?, Chapter 27,
Subchapter 19, Table 3
N.J. A. C. Title?, Chapter 27,
Subchapter 19, Table 6; non- High
Electricity demand Day (HEDD) unit
N.J. A. C. Title?, Chapter 27,
Subchapter 19, Table 7; High
Electricity demand Day (HEDD) unit
Part 237
Part 238
Mercury Reduction Program for
Coal-Fired Electric Utility Steam
Generating Units
Subpart 227-2 Reasonably
Available Control Technology
(RACT) For Major Facilities of
Oxides Of Nitrogen (NOX)
Emission Type
NOX
NOX
NOX
NOX
NOX
SO2
Hg
NOX
Emission Specifications
Annual rate limits in Ibs/MMBtu for the following technologies:
0.38 for tangential dry-bottom coal boilers serving an EGU
0.45 for wall-fired dry-bottom coal boilers serving an EGU
0.55 for cyclone-fired dry-bottom coal boilers serving an EGU
Annual rate limits in Ibs/MMBtu for the following technologies:
0.20 for tangential oil and/or gas boilers serving an EGU
0.28 for wall-fired oil and/or gas boilers serving an EGU
0.43 for cyclone-fired oil and/or gas boilers serving an EGU
2.2 Ibs/MWh annual GPS for gas-burning simple cycle
combustion turbine units
3.0 Ibs/MWh annual GPS for oil-burning simple cycle combustion
turbine units
1 .3 Ibs/MWh annual GPS for gas-burning combined cycle CT or
regenerative cycle CT units
2.0 Ibs/MWh annual GPS for oil-burning combined cycle CT or
regenerative cycle CT units
1 .0 Ibs/MWh annual GPS for gas-burning simple cycle
combustion turbine units
1 .6 Ibs/MWh annual GPS for oil-burning simple cycle combustion
turbine units
0.75 Ibs/MWh annual GPS for gas-burning combined cycle CT or
regenerative cycle CT units
1 .2 Ibs/MWh annual GPS for oil-burning combined cycle CT or
regenerative cycle CT units
39.91 Mtons [Thousand tons] non-ozone season cap for fossil fuel
units > 25 MW
131.36 MTons [Thousand tons] annual cap for fossil fuel units >
25 MW
786 Ibs annual cap through 201 4 for all coal fired boiler or CT
units >25 MW after Nov. 15, 1990.
0.60 Ibs/TBtu annual rate limit for all coal units > 25 MW
developed after Nov. 15 1990
Annual rate in Ibs/MMBtu for very large boilers >250 MMBtu/hr
that commenced operation prior to July 1, 2014;
Gas only, tangential & wall fired : 0.2
Gas/oil tangential & wall fired : 0.25; cyclone: 0.43
Coal Wet Bottom, tangential & wall fired : 0.1 ; cyclone: 0.6
Coal Dry Bottom, tangential: 0.42; wall fired : 0.45; stokers: 0.301
Annual rate in Ibs/MMBTu for very large boilers >250 MMBtu/hr
that commenced operation after July 1, 2014;
Gas only, tangential & wall fired : 0.8
Gas/oil tangential & wall fired : 0.15; cyclone: 0.2
Coal Wet Bottom, tangential & wall fired : 0.12; cyclone: 0.2
Coal Dry Bottom, tangential & wall fired : 0.12; stokers: 0.08
Implementation
Status
2007
2007
2007
2007
2004
2005
2010
2004
Notes
On and after May 1 , 2015, the
owner or operator of a
stationary combustion turbine
that is a HEDD unit or a
stationary combustion turbine
that is capable of generating 15
MW or more and that
commenced operation on or
after May 1 , 2005 shall comply
with limits outlines "in Table 7
during operation on high
electricity demand days,
regardless of the fuel
combusted, unless combusting
gaseous fuel is not possible due
to gas curtailment."
3-44
-------
State/Region
Bill
Part 251
Emission Type
CO2
Emission Specifications
Annual rate in Ibs/MMBTu for large boilers between 100 and 250
MMBtu/hr that commenced operation prior to July 1, 2014;
Gas Only: 0.20
Gas/Oil: 0.30
Pulverized Coal: 0.50
Coal (Overfeed Stoker):0.301
Annual rate in Ibs/MMBTu for large boilers between 100 and 250
MMBtu/hr that commenced operation after July 1, 2014;
Gas Only: 0.06
Gas/Oil: 0.15
Pulverized Coal: 0.20
Coal (Overfeed Stoker/FBC): 0.8
Annual rate in Ibs/MMBTu for mid-size boilers between 25 and
100 MMBtu/hr that commenced operation prior to July 1, 2014;
Gas Only: 0.10
Distillate Oil/Gas: 0.1 2
Residual Oil/Gas: 0.30
Annual rate in Ibs/MMBTu for mid-size boilers between 25 and
100 MMBtu/hr that commenced operation after July 1, 2014;
Gas Only: 0.05
Distillate Oil/Gas: 0.08
Residual Oil/Gas: 0.20
For simple cycle and regenerative combustion turbines:
(i) 50 parts per million on a dry volume basis (ppmvd), corrected
to 15 percent oxygen, for sources designed to burn gaseous fuels
(gaseous fuels include, but are not limited to, natural gas, landfill
gas, and digester gas) only; and
(ii) 100 ppmvd, corrected to 15 percent oxygen, for sources
capable of firing distillate oil or more than one fuel.
For combined cycle combustion turbines:
(i) prior to July 1, 2014, 42 ppmvd (0.1869 Ibs/MMBtu), corrected
to 15 percent oxygen, when firing gas; and
(ii) priorto July 1, 2014, 65 ppmvd (0.2892 Ibs/MMBtu), corrected
to 15 percent oxygen, when firing oil.
Stationary internal combustion engines having a maximum
mechanical output => 200 brake horsepower in a severe ozone
nonattainment area or having a maximum mechanical output
rating =>400 brake horsepower outside a severe ozone
nonattainment:
(1) For internal combustion engines fired solely with natural gas:
1 .5 grams per brake horsepower-hour.
(2) For internal combustion engines fired with landfill gas or
digester gas (solely or in combination with natural gas): 2.0 grams
per brake horsepower-hour.
(3) For internal combustion engine fired with distillate oil (solely or
in combination with other fuels): 2.3 grams per brake horsepower-
hour.
1450 Ibs/MWh rate limit for New Combustion Turbines =>25MW
925 Ibs/MWh rate limit for New Fossil Fuel except CT =>25MW
Implementation
Status
2012
Notes
Compliance with these emission
limits must be determined with a
one hour average during the
ozone season and a 30-day
average during the non-ozone
season unless the owner or
operator chooses to use a
CEMS under the provisions of
section 227- 2.6(b) of this
Subpart.
3-45
-------
State/Region
North Carolina
Oregon
Texas
Utah
Washington
Bill
NC Clean Smokestacks Act: Statute
143-215.107D
SECTION .2500 - Mercury Rules
for Electric Generators
15ANCAC02D.2511
Oregon Administrative Rules,
Chapter 345, Division 24
Oregon Utility Mercury Rule -
Existing Units
Oregon Utility Mercury Rule -
Potential Units
Senate Bill 7 Chapter 101
Chapter 117
R307-424 Permits: Mercury
Requirements for Electric
Generating Units
Washington State House Bill 3141
Emission Type
NOX
SO2
Hg
Hg
CO2
Hg
Hg
SO2
NOX
NOX
Hg
CO2
Emission Specifications
25 MTons annual cap for Progress Energy coal plants > 25 MW
and 31 MTons annual cap for Duke Energy coal plants > 25 MW
2012: 100 MTons annual cap for Progress Energy coal plants >
25 MW and 150 MTons annual cap for Duke Energy coal plants >
25 MW
2013 onwards: 50 MTons annual cap for Progress Energy coal
plants > 25 MW and 80 MTons annual cap for Duke Energy coal
plants > 25 MW
Coal-fired electric steam >25 MW to comply with the mercury
emission caps of 1 .133 tons (36,256 ounces) per year between
2010 and 2017
inclusive and 0.447 tons (14,304 ounces) per year for 2018 and
thereafter
Duke Energy and Progress Energy Hg control plans submitted on
January 1, 2013 and are awaiting approval. All control
technologies and limitations must be implemented by December
31,2017.
675 Ibs/MWh annual rate limit for new combustion turbines
burning natural gas with a CF >75% and all new non-base load
plants (with a CE <= 75%) emitting CO2
90% removal of Hg content of fuel reduction or 0.6 Ibs/TBtu
limitation for all existing coal units >25 MW
25 Ibs limit for all potential coal units > 25 MW
273.95 MTons cap of SO2 for all grandfathered units built before
1971 in East Texas Region
Annual cap for all grandfathered units built before 1971 in MTons:
84.48 in East Texas, 18.10 in West Texas, 1.06 in El Paso Region
East and Central Texas annual rate limits in Ibs/MMBtu for units
that came online before 1996:
Gas fired units: 0.14
Coal fired units: 0.165
Stationary gas turbines: 0.14
Dallas/Fort Worth Area annual rate limit for utility boilers, auxiliary
steam boilers, stationary gas turbines, and duct burners used in
an electric power generating system except for CT and CC units
online after 1992:
0.033 Ibs/MMBtu or 0.50 Ibs/MWh output or 0.0033 Ibs/MMBtu on
system wide heat input weighted average for large utility systems
0.06 Ibs/MMBtu for small utility systems
Houston/Galveston region annual Cap and Trade (MECT) for all
fossil units:
17.57 MTons
Beaumont-Port Arthur region annual rate limits for utility boilers,
auxiliary steam boilers, stationary gas turbines, and duct burners
used in an electric power generating system: 0.10 Ibs/MMBtu
90% removal of Hg content of fuel annually for all coal units > 25
MW
$1 .45/MTons cost (2004$) for all new fossil-fuel power plant
Implementation
Status
2007
2009
2010
2017
1997
2012
2009
2003
2007
2013
2004
Notes
Vacated
Units are also allowed to
comply by reducing the same
amount of NOX on a monthly
basis using a system cap or by
purchasing credits.
East and Central Texas,
Dallas/Fort Worth Area,
Beaumont-Port Arthur region
units are assumed to be in
compliance based on their
reported 2011 ETS rates. The
regulations for these regions
are not modeled.
3-46
-------
State/Region
Wisconsin
Bill
Washington State House Bill 5769
NR 428 Wisconsin Administration
Code
Chapter NR 44.12/446.13 Control of
Mercury Emissions
Chapter NR 446.14 Multi-pollutant
reduction alternative for coal-fired
electrical generating units
Emission Type
CO2
NOX
Hg
Hg
SO2
NOX
Emission Specifications
1 100 Ibs/MWh rate limit for new coal plants
Annual rate limits in Ibs/MMBtu for coal fired boilers > 1 ,000
MMBtu/hr :
Wall fired, tangential fired, cyclone fired, and fluidized bed: 2013
onwards: 0.10
Arch fired: 2009 onwards: 0.18
Annual rate limits in Ibs/MMBtu for coal fired boilers between 500
and 1,000 MMBtu/hr:
Wall-fired with a heat release rate=> 17,000 Btu per cubic feet per
hour; 2013 onwards: 0.17 ; if heat input is lesser:
Tangential fired: 2009 onwards: 0.15
Cyclone fired: 2013 onwards: 0.15
Fluidized bed: 2013 onwards: 0.10
Arch fired: 2009 onwards: 0.18
Annual rate limits in Ibs/MMBtu for coal fired boilers between 250
and 500 MMBtu/hr:
Same as for coal boiled between 500 and 1000 MMBtu/hr in
addition to:
Stoker Fired: .20
Annual rate limits in Ibs/MMBtu for coal fired boilers between 50
and 250 MMBtu/hr:
Same as for coal boiled between 500 and 1000 MMBtu/hr in
addition to:
Stoker Fired: .25
Annual rate limits for CTs in Ibs/MMBtu:
Natural gas CTs > 50 MW: 0.1 1
Distillate oil CTs > 50 MW: 0.28
Biologically derived fuel CTs > 50 MW: 0.15
Natural gas CTs between 25 and 49 MW: 0.19
Distillate oil CTs between 25 and 49 MW: 0.42
Biologically derived fuel CTs between 25 and 49 MW: 0.15
Annual rate limits for CCs in Ibs/MMBtu:
Natural gas CCs > 25 MW: 0.04
Distillate oil CCs > 25 MW: 0.19
Biologically derived fuel CCs > 25 MWs: 0.15
Natural gas CCs between 10 and 24 MW: 0.19
Large (150MW capacity or greater) or small (between 25 and 150
MW) coal-fired EGU, 2015 onwards: 90% removal of Hg content
of fuel or 0.0080 Ibs/GWh reduction in coal fired EGUs > 150 MW
All Coal>25MW;
70% reduction in fuel, or .0190 Ibs per GW-hrfrom CY 2015 - CY
2017 (0.00005568 Ibs/MMBtu)
80% reduction in fuel, or .0130 Ibs per GW-hrfrom CY2018 - CY
2020 (0.0000381 Ibs/MMBtu)
90% reduction in fuel, or .0080 Ibs per GW-hrfrom January 1,
2021 onwards (0.00000234 Ibs/MMBtu)
All Coal>25MW; .10 Ibs per mmBTU by January 1, 2015
All Coal>25MW; 07 Ibs per mmBTU by January 1,2015
Implementation
Status
2011
2009
2015
2015
Notes
Alternative already modeled in
IPM
3-47
-------
Table 3-14 New Source Review (NSR) Settlements in EPA Base Case v.5.13
Company
and Plant
State
Unit
Settlement Actions
Retire/Repower
Action
Effective
Date
SOz control
Equipment
Percent
Removal or
Rate
Effective
Date
NOX Control
Equipment
Rate
Effective
Date
PM or Mercury Control
Equipment
Rate
Effective
Date
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
Effective
Date
Notes
Reference
Alabama Power
James H.
Miller
Alabama
Alabama
Unit 3
Unit 4
Install and
operate FGD
continuously
Install and
operate FGD
continuously
95%
95%
12/31/11
12/31/11
Operate existing
SCR
continuously
Operate existing
SCR
continuously
0.1
0.1
05/01/08
05/01/08
0.03
0.03
12/31/06
12/31/06
Within 45 days of
settlement entry,
ARC must retire
7,538 SO2 emission
allowances.
ARC shall not sell,
trade, or otherwise
exchange any Plant
Miller excess SO2
emission allowances
outside of the APC
system
1/1/21
1/1/21
1) Settlement requires 95%
removal efficiency for SO2 or 90%
in the event that the unit combust a
coal with sulfur content greater than
1% by weight. 2) The settlements
require APC to retire $4,900,000 of
SO2 emission allowances within 45
days of consent decree entry. 3)
EPA assumed a retirement of 7,
538 SO2 allowances based on a
current allowance price of $650.
http ://www2.
epa.gov/enfo
rcement/alab
am a-power-
company-
clean-air-act-
settlement
Minnkota Power Cooperative
Milton R.
Young
North Dakota
North Dakota
Unit 1
Unit 2
Beginning 1/01/2006, Minnkota shall not emit more than 31,000 tons of SC>2/year, no more than 26, 000 tons beginning 2011, no more than 11,500 tons beginning 1/01/2012. If Unit 3 is not operational by
12/31/2015, then beginning 1/01/2014, the plant wide emission shall not exceed 8,500.
Install and
continuously
operate FGD
Design,
upgrade, and
continuously
operate FGD
95% if wet
FGD, 90% if
dry
90%
12/31/11
12/31/10
Install and
continuously
operate Over-fire
AIR, or
equivalent
technology with
emission rate <
.36
Install and
continuously
operate over-fire
AIR, or
equivalent
technology with
emission rate <
.36
0.36
0.36
12/31/09
12/31/07
0.03 if wet
FGD, .015
f dry FGD
0.03
Before
2008
Plant will surrender
4,346 allowances for
each year 2012 -
2015, 8,693
allowances for years
2016-2018, 12,170
allowances for year
2019, and 14,886
allowances/year
thereafter if Units 1 -
3 are operational by
12/31/2015. If only
Units 1 and 2 are
operational
by1 2/31/201 5, the
plant shall retire
17, 886 units in 2020
and thereafter.
Minnkota shall not sell
or trade NOK
allowances allocated to
Units 1, 2, or 3 that
would otherwise be
available for sale or
trade as a result of the
actions taken by the
settling defendants to
comply with the
requirements
1) Settlement requires 95%
removal efficiency for SO2 at Unit 1
if a wet FGD is installed, or 90% if a
dry FGD is installed. The FGD for
Units 1 and 2 and the NO* control
for Unit 1 are modeled as emission
constraints in EPA Base Case, the
NO* control for Unit 2 is hardwired
into EPA Base Case. 2) Beginning
12/31/2010, Unit 2 will achieve a
phase II average NOX emission rate
established through its NOK BACT
determination. Beginning
12/31/2011, Unit 1 will achieve a
phase II NO* emission rate
established by its BACT
determination.
ittp ://www2.
eoa.aov/enfo
rcement/min
nkota-oower-
cooperative-
and-square-
putte-
electric-
cooperative-
settlement
SIGECO
FB Culley
Indiana
Indiana
Indiana
Unit 1
Unit 2
Units
Repower to
natural gas
(or retire)
12/31/06
Improve and
continuously
operate
existing FGD
(shared by
Units 2 and 3)
Improve and
continuously
operate
existing FGD
(shared by
Units 2 and 3)
95%
95%
06/30/04
06/30/04
Operate Existing
SCR
Continuously
0.1
09/01/03
Install and
continuously
operate a
Baghouse
0.015
06/30/07
The provision did not
specify an amount of
SO2 allowances to be
surrendered. It only
provided that excess
allowances resulting
from compliance with
NSR settlement
provisions must be
retired.
http://www2.
epa.gov/enfo
rcem ent/sout
hern-indiana-
gas-and-
electric-
company-
sigeco-fb-
cu 1 ley-pi ant-
el ean-air-act-
caa
PSEG FOSSIL
Bergen
Hudson
New Jersey
New Jersey
Unit 2
Unit 2
Repower to
combined
cycle
12/31/02
nstall Dry FGD
(or approved
alt. technology)
and continually
operate
0.15
12/31/06
Install SCR (or
approved tech)
and continually
operate
0.1
05/01/07
Install
Baghouse (or
approved
technology)
0.015
12/31/06
The provision did not
specify an amount of
SO2 allowances to be
surrendered. It only
provided that excess
allowances resulting
from compliance with
NSR settlement
provisions must be
retired.
The settlement requires coal with
monthly average sulfur content no
greater than 2% at units operating
FGD - this limit is modeled as a
coal choice exception in EPA Base
Case.
http ://www2.
epa.gov/enfo
rcement/pse
g-fossil-llc-
settlement
3-48
-------
Company
and Plant
Mercer
State
New Jersey
New Jersey
Unit
Unit 1
Unit 2
Settlement Actions
Retire/Repower
Action
Effective
Date
SOz control
Equipment
nstall Dry FGD
(or approved
alt. technology)
and continually
operate
nstall Dry FGD
(or approved
alt. technology)
and continually
operate
Percent
Removal or
Rate
0.15
0.15
Effective
Date
12/31/10
12/31/12
NOX Control
Equipment
Install SCR (or
approved tech)
and continually
operate
Install SCR (or
approved tech)
and continually
operate
Rate
0.1
0.1
Effective
Date
01/01/07
01/01/07
PM or Mercury Control
Equipment
Rate
0.015
0.015
Effective
Date
12/31/10
12/31/10
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
Effective
Date
Notes
The settlement requires coal with
monthly average sulfur content no
greater than 2% at units operating
FGD this limit is modeled as a
coal choice exception in EPA Base
Case.
The settlement requires coal with
monthly average sulfur content no
greater than 2% at units operating
FGD this limit is modeled as a
coal choice exception in EPA Base
Case.
Reference
TECO
Big Bend
Gannon
Florida
Florida
Florida
Florida
Florida
Unit 1
Unit 2
Unit 3
Unit 4
Six units
Retire all six
coal units
and repower
at least 550
MW of coal
capacity to
natural gas
12/31/04
Existing
Scrubber
(shared by
Units 1 & 2)
Existing
Scrubber
(shared by
Units 1 & 2)
Existing
Scrubber
(shared by
Units 3 & 4)
Existing
Scrubber
(shared by
Units 3 & 4)
95% (95% or
.25)
95% (95% or
.25)
93% if Units
3 & 4 are
operating
93% if Units
3 & 4 are
operating
09/1/00
(01/01/13)
09/1/00
(01/01/13)
2000
(01/01/10)
06/22/05
Install SCR
Install SCR
Install SCR
Install SCR
0.1
0.1
0.1
0.1
05/01/09
05/01/09
05/01/09
07/01/07
The provision did not
specify an amount of
SOs allowances to be
surrendered. It only
provided that excess
allowances resulting
from compliance with
NSR settlement
provisions must be
retired.
http ://www2.
epa.gov/enfo
rcem ent/tam
pa-electric-
company-
teco-clean-
air-act-caa-
settlement
WEPCO
Presque Isle
Pleasant
Prairie
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Units
1-4
Units 5, 6
Units/, 8
Unit 9
Unit 1
WEPCO shal comply with the following system wide average NO, emission rates and total NOX tonnage perm ssible: by 1/1/2005 an em ssion rate of 0.27 and 31,500 tons, by 1/1/2007 an emission rate of
0.19 and 23,400 tons, and by 1/1/2013 an emission rate of 0.17 and 17, 400 tons. For SO2 emissions, WEPCO will comply with: by 1/1/2005 an emission rate of 0.76 and 86,900 tons, by 1/1/2007 an
emission rate of 0.61 and 74,400 tons, by 1/1/2008 an emission rate of 0.45 and 55,400 tons, and by 1/1/2013 an emission rate of 0.32 and 33,300 tons.
Retire or
install SO2
and NO*
controls
12/31/12
Install and
continuously
operate FGD
(or approved
equiv. tech)
Install and
continuously
operate FGD
(or approved
control tech)
95% or 0.1
95% or 0.1
12/31/12
12/31/06
Install SCR (or
approved tech)
and continually
operate
Install and
operate lowNOK
burners
Operate existing
ow NOX burners
Operate existing
ow NO* burners
Install and
continuously
operate SCR (or
approved tech)
0.1
0.1
12/31/12
12/31/03
12/31/05
12/31/06
12/31/06
Install
Baghouse
Install
Baghouse
The provision did not
specify an amount of
SO2 allowances to be
surrendered. It only
provided that excess
allowances resulting
from compliance with
NSR settlement
provisions must be
retired.
http ://www2.
epa.gov/enfo
rcement/wisc
on sin-
el ectric-
power-
company-
wepco-clean-
air-act-civil-
settlement
3-49
-------
Company
and Plant
Oak Creek
Port
Washington
Valley
State
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Unit
Unit 2
Units 5, 6
Unit/
Unit 8
Units
1-4
Boilers
1-4
Settlement Actions
Retire/Repower
Action
Retire
Effective
Date
12/31/04
for Units 1
-3. Unit 4
by entry of
consent
decree
SOz control
Equipment
Install and
continuously
operate FGD
(or approved
control tech)
Install and
continuously
operate FGD
(or approved
control tech)
Install and
continuously
operate FGD
(or approved
control tech)
Install and
continuously
operate FGD
(or approved
control tech)
Percent
Removal or
Rate
95% or 0.1
95% or 0.1
95% or 0.1
95% or 0.1
Effective
Date
12/31/07
12/31/12
12/31/12
12/31/12
NOX Control
Equipment
Install and
continuously
operate SCR (or
approved tech)
Install and
continuously
operate SCR (or
approved tech)
Install and
continuously
operate SCR (or
approved tech)
Install and
continuously
operate SCR (or
approved tech)
Operate existing
low NOK burner
Rate
0.1
0.1
0.1
0.1
Effective
Date
12/31/03
12/31/12
12/31/12
12/31/12
30 days
after entry
of consent
decree
PM or Mercury Control
Equipment
Rate
Effective
Date
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
Effective
Date
Notes
Reference
VEPCO
Mount Storm
Chesterfield
Chesapeake
Energy
Clover
Possum
Point
West Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Units
1-3
Unit 4
Unit 5
Unit 6
Units 3, 4
Units 1,2
Units 3, 4
The Total Permissible NOK Emissions (in tons) from VEPCO system are: 1 04,000 in 2003, 95,000 in 2004, 90,000 in 2005, 83,000 in 2006, 81 ,000 in 2007, 63,000 in 2008 - 201 0, 54,000 in 201 1 , 50,000 in
2012, and 30,250 each year thereafter. Beginning 1/1/2013 they will have a system wide emission rate no greater than 0.15 Ibs/mmBTU.
Retire and
repower to
natural gas
05/02/03
Construct or
improve FGD
Construct or
improve FGD
Construct or
improve FGD
Improve FGD
95% or 0.1 5
95% or 0.1 3
95% or 0.1 3
95% or 0.1 3
01/01/05
10/12/12
01/01/10
09/01/03
Install and
continuously
operate SCR
Install and
continuously
operate SCR
Install and
continuously
operate SCR
Install and
continuously
operate SCR
Install and
continuously
operate SCR
0.11
0.1
0.1
0.1
0.1
01/01/08
01/01/13
01/01/12
01/01/11
01/01/13
On or before March
31 of every year
beginning in 2013
and continuing
thereafter, VEPCO
shall surrender
45,000 SO2
allowances.
http://www2.
epa.gov/enfo
rcement/virgi
nia-electric-
and-power-
company-
vepco-clean-
air-act-caa-
settlement
Santee Cooper
Cross
South
Carolina
Unit 1
Santee Cooper shall comply with the following system wide averages for NOX emission rates and combined tons for emission of: by 1/01/2005 facility shall comply with an emission rate of 0.3 and 30,000
tons, by 1/1/2007 an emission rate of 0.18 and 25,000 tons, by 1/1/2010 and emission rate of 0.15 and 20,000 tons. For SO2 emission the company shall comply with system wide averages of: by 1/1/2005
an emission rate of 0.92 and 95, 000 tons, by 1/1/2007 and emission rate of 0.75 and 85,000 tons, by 1/1/2009 an emission rate of 0.53 and 70 tons, and by 1/1/2011 and emission rate of 0.5 and 65 tons.
Upgrade and
continuously
operate FGD
95%
06/30/06
Install and
continuously
operate SCR
0.1
05/31/04
The provision did not
specify an amount of
SOs allowances to be
http://www2.
epa.gov/enfo
rcem ent/sout
h-carolina-
public-
service-
3-50
-------
Company
and Plant
Winyah
Grainger
Jeffries
State
South
Carolina
South
Carolina
South
Carolina
South
Carolina
South
Carolina
South
Carolina
South
Carolina
South
Carolina
Unit
Unit 2
Unit 1
Unit 2
Unit 3
Unit 4
Unit 1
Unit 2
Units 3, 4
Settlement Actions
Retire/Repower
Action
Effective
Date
SOz control
Equipment
Upgrade and
continuously
operate FGD
Install and
continuously
operate FGD
Install and
continuously
operate FGD
Upgrade and
continuously
operate
existing FGD
Upgrade and
continuously
operate
existing FGD
Percent
Removal or
Rate
87%
95%
95%
90%
90%
Effective
Date
06/30/06
12/31/08
12/31/08
12/31/08
12/31/07
NOX Control
Equipment
Install and
continuously
operate SCR
Install and
continuously
operate SCR
Install and
continuously
operate SCR
Install and
continuously
operate SCR
Install and
continuously
operate SCR
Operate low NO*
burner or more
stringent
technology
Operate low NO,
burner or more
stringent
technology
Operate low NOK
burner or more
stringent
technology
Rate
0.11/0.1
0.11/0.1
0.12
0.14/0.12
0.13/0.12
Effective
Date
05/31/04
and
05/31/07
11/30/04
and
11/30/04
11/30/04
11/30/200
Sand
11/30/08
11/30/05
and
11/30/08
06/25/04
05/01/04
06/25/04
PM or Mercury Control
Equipment
Rate
Effective
Date
Allowance
Retirement
Retirement
surrendered. It only
provided that excess
allowances resulting
from compliance with
NSR settlement
provisions must be
retired.
Allowance Restriction
Restriction
Effective
Date
Notes
Reference
authority-
santee-
cooper-
settlement
OHIO EDISON
W.H.
Sammis
Plant
Ohio
Ohio
Ohio
Ohio
Unit 1
Unit 2
Unit 3
Unit 4
Ohio Edison shall achieve reductions of 2,483 tons NOX between 7/1/2005 and 12/31/2010 using any combination of: 1) low sulfur coal at Burger Units 4 and 5, 2) operating SCRs currently installed at
Mansfield Un ts 1 - 3 during the months of October through April, and/or 3) emitting fewer tons than the Plant-Wide Annual Cap for NOX required for the Sammis Plant. Ohio Edison must reduce 24,600 tons
system-wide of SO2 by 12/31/2010.
Mo later than 8/11/2005, Ohio Edison shall install and operate low NO* burners on Sammis Units 1, 2,4,5,6, and 7 and overtired air on Sammis Units 1,2,3,6, and 7. No later than 12/1/2005, Ohio Edison shall
install advanced combustion control optimization with software to minimize NOK emissions from Sammis Units 1-5.
Install Induct
Scrubber (or
approved
equiv.
control tech)
Install Induct
Scrubber (or
approved
equiv.
control tech)
Install Induct
Scrubber (or
approved
equiv.
control tech)
Install Induct
Scrubber (or
approved
equiv.
control tech)
50% removal
or 1.1
Ibs/mmBTU
50% removal
or 1.1
Ibs/mmBTU
50% removal
or 1.1
Ibs/mmBTU
50% removal
or 1.1
bs/mmBTU
12/31/08
12/31/08
12/31/08
06/30/09
Install SNCR
(or approved
alt. tech) &
operate
continuously
Operate
existing SNCR
continuously
Operate low NOK
burners and
overfire air by
12/1/05; install
SNCR
(or approved
alt. tech) &
operate
continuously by
12/31/07
Install SNCR
(or approved
alt. tech) &
operate
continuously
0.25
0.25
0.25
0.25
10/31/07
02/15/06
12/01/05
and
10/31/07
10/31/07
Beginning on
1/1/2006, Ohio
Edison may use, sell
or transfer any
restricted SO2 only to
satisfy the
Operational Needs at
the Sammis, Burger
and Mansfield Plant,
or new units within
the FirstEnergy
System that comply
with a 96% removal
for SO2. For
calendar year 2006
through 2017, Ohio
Edison may
accumulate SO2
allowances for use at
the Sammis, Burger,
and Mansfield plants,
or FirstEnergy units
equipped with SO2
Emission Control
Standards.
Beginning in 2018,
Ohio Edison shall
surrender unused
restricted SO2
Plant-wide NOx Annual Caps:
11 ,371 tons 7/1/2005 - 12/31/2005;
21 ,251 tons 2006; 20,596 tons
2007; 18, 903 tons 2008; 17,328
tons 2009 - 201 0; 1 4,845 tons
2011; 11, 863 201 2 onward.
Sammis Plant-Wide Annual SO2
Caps: 58, 000 tons SO2 7/1/2005-
12/31/2005; 116,000 tons 1/1/2006
-12/31/2007; 114, 000 tons
1/1/2008-12/31/2008; 101, 500 tons
1/1/2009 - 12/31/2010; 29,900 tons
1/1/2011 onward. SammisUnits!
- 5 are also subject to the following
SO2 Monthly Caps if Ohio Edison
installs the improved SO2 control
technology (Unit 5's option A):
3,242 tons May, July, and August
2010; 3,137 tons June and
September 2010. Ohio Edison has
installed the required SO2
technology (Unit 5's option B), so
the Monthly Caps are: 2,533 tons
May, July, and August 2010; 2,451
tons June and September 2010.
Add'l Monthly Caps are: 2,533 tons
May, July, and August 201 1 ; 2,451
tons June and September 2011
thereafter.
http://www2.
epa.gov/enfo
rcement/ohio
-edi son-
corn pany-wh-
sammis-
power-
station-clean-
air-act-2005-
and-2009
3-51
-------
Company
and Plant
Mansfield
Plant
Eastlake
Burger
State
Ohio
Ohio
Ohio
Pennsylvania
Pennsylvania
Pennsylvania
Ohio
Ohio
Ohio
Unit
Units
Unite
Unit/
Unit 1
Unit 2
Units
Unit 5
Unit 4
Units
Settlement Actions
Retire/Repower
Action
Repower
with at least
80%biomass
fuel, up to
20% low
sulfur coal
OR Retire by
12/31/2010
Effective
Date
12/31/11
12/31/11
SOz control
Equipment
Install Flash
Dryer Absorber
or ECO2 (or
approved
equiv.
control tech) &
operate
continuously
nstall FGD3 (or
approved
equiv.
control tech) &
operate
continuously
Install FGD (or
approved
equiv.
control tech) &
operate
continuously
Upgrade
existing FGD
Upgrade
existing FGD
Upgrade
existing FGD
Percent
Removal or
Rate
50% removal
or 1.1
Ibs/mmBTU
95% removal
or 0.13
Ibs/mmBTU
95% removal
or 0.13
Ibs/mmBTU
95%
95%
95%
Effective
Date
06/29/09
06/30/11
06/30/11
12/31/05
12/31/06
10/31/07
NOX Control
Equipment
Install SNCR
(or approved
alt. tech) &
Operate
Continuously
Install SNCR
(or approved
alt. tech) &
operate
continuously
Operate
existing SNCR
Continuously
Install lowNOK
burners, over-
fired
air and SNCR &
operate
continuously
Rate
0.29
"Minimum
Extent
Practicable"
"Minimum
Extent
Practicable"
"Minimize
Emissions
to the
Extent
Practicable"
Effective
Date
03/31/08
06/30/05
08/11/05
12/31/06
PM or Mercury Control
Equipment
Operate
Existing
ESP
Continuously
Operate
Existing
ESP
Continuously
Rate
0.03
0.03
Effective
Date
01/01/10
01/01/10
Allowance
Retirement
Retirement
allowances.
Allowance Restriction
Restriction
Effective
Date
Notes
n addition to SNCR, settlement
requires installation of first SCR (or
approved alt tech) on either Unit 6
or 7 by 12/31/2010; second
installation by 12/31/2011. Both
SCRs must achieve 90% Design
Removal Efficiency by 180 days
after installation date. Each SCR
must provide a 30-Day Rolling
average. NO,, Emission Rate of 0.1
Ibs/mmBTU starting 180 days after
installation dates above.
Additional Mansfield Plant-wide
SO2 reductions are as follows:
4,000 tons in 2006, 8,000 tons in
2007, and 1 2,000 tons/yr for every
year after. Settlement allows
relinquishment of SO2 requirement
upon shutdown of unit, after which
the SO2 reductions must be made
by another plant(s).
Settlement requires Eastlake Plant
to achieve additional reductions of
1 1 ,000 tons of NO* per year
commencing in calendar year 2007,
and no less than 10,000 tons must
comefrom this unit. The extra
1,000 tons may comefrom this unit
or another unit in the region. Upon
shutdown of Eastlake, another plant
must achieve these reductions.
Reference
Ml RANT1'6
Potomac
River Plant
Virginia
Virginia
Virginia
Virginia
Unit 1
Unit 2
Unit 3
Unit 4
System-wide NO* Emission Annual Caps: 36, 500 tons 2004; 33,840 tons 2005; 33, 090 tons 2006; 28,920 tons 2007; 22, 000 tons 2008; 19,650 tons 2009; 16, 000 tons 2010 onward. System-wide NOK
Emission Ozone Season Caps: 14, 700 tons 2004; 13,340 tons 2005; 12, 590 tons 2006; 10, 190 tons 2007; 6,150 tons 2008- 2009; 5,200 tons 2010 thereafter. Beginning on 5/1/2008, and continuing for
each and every Ozone Season thereafter, the Mirant System shall not exceed a System-wide Ozone Season Emission Rate of 0.150 Ibs/mmBTU NO*.
Install lowNOK
burners (or more
effective tech) &
operate
continuously
Install low NO,
burners (or more
effective tech) &
operate
continuously
05/01/04
05/01/04
Settlement requires installation of
Separated Overfire Air tech (or
more effective technology) by
5/1/2005. Plant-wide Ozone
Season NO, Caps: 1,750 tons
2004; 1,625 tons 2005; 1,600 tons
2006 - 2009; 1 ,475 tons 201 0
thereafter. Plant-wide annual NOX
Caps are 3,700 tons in 2005 and
each year thereafter.
http://www2.
epa.gov/enfo
rcement/mira
nt-clean-air-
settlement
3-52
-------
Company
and Plant
Morgantown
Plant
Chalk Point
State
Virginia
Maryland
Maryland
Maryland
Maryland
Unit
Unit 5
Unit 1
Unit 2
Unit 1
Unit 2
Settlement Actions
Retire/Repower
Action
Effective
Date
SOz control
Equipment
operate FGD
technology)
Install and
continuously
operate FGD
Percent
Removal or
Rate
95%
95%
Effective
Date
06/01/10
06/01/10
NOx Control
Equipment
Install lowNOK
burners (or more
effective tech) &
operate
continuously
Install SCR
(or approved
alt. tech) &
operate
continuously
Install SCR
(or approved
alt. tech) &
operate
continuously
Rate
0.1
0.1
Effective
Date
05/01/04
05/01/07
05/01/08
PM or Mercury Control
Equipment
Rate
Effective
Date
Allowance
Retirement
Retirement
For each year after
Mirant commences
FGD operation at
shall surrender the
number of SO2
Allowances equal to
the amount by which
the SO2 Allowances
allocated to the Units
at the Chalk Point
Plant are greater
of SO2 emissions
allowed under this
Section XVIII.
Allowance Restriction
Restriction
Effective
Date
Notes
Mirant must install and operate
FGD by 6/1/2010 if authorized by
court to reject ownership interest in
Morgantown Plant, or by no later
than 36 months after they lose
ownership interest of the
Morgantown Plant. [Installed]
Reference
ILLINOIS POWER
Baldwin
Havana
Illinois
Illinois
Illinois
Illinois
Unit 1
Unit 2
Units
Unite
System-wide NOK Emission Annual Caps: 15,000 tons 2005; 14,000 tons 2006; 13, 800 tons 2007 onward. System-wide SO2 Emission Annual Caps: 66, 300 tons 2005- 2006; 65, 000 tons 2007; 62,000
tons 2008 - 201 0; 57,000 tons 201 1 ; 49,500 tons 201 2; 29,000 tons 2013 onward.
Install wet or
dry FGD (or
approved
equiv.
alt. tech) &
continuously
dry FGD (or
approved
equiv.
alt. tech) &
continuously
Install wet or
dry FGD (or
approved
equiv.
alt. tech) &
operate
continuously
Install wet or
dry FGD (or
approved
equiv.
alt. tech) &
operate
continuously
0.1
0.1
0.1
1.2
Ibs/mmBTU
until
12/30/2012;
0.1
Ibs/mmBTU
from
12/31/2012
onward
12/31/11
12/31/11
12/31/11
08/11/05
and
12/31/12
Operate OFA &
existing SCR
continuously
Operate OFA &
existing SCR
continuously
Operate OFA
and/or low NOK
burners
Operate OFA
and/or low NO,
burners &
operate existing
SCR
continuously
0.1
0.1
0.1 2 until
12/30/12;
0.1
from
12/31/12
0.1
08/11/05
08/11/05
08/11/05
and
12/31/12
08/11/05
continuously
Baghouse
Install &
continuously
Baghouse
Install &
continuously
operate
Baghouse
Install &
continuously
operate
Baghouse,
then install
ESP or alt.
PM equip
0.015
0.015
0.015
house:
.015
Ibs/mmBT
U; For
ESP: .03
Ibs/mmBT
12/31/10
12/31/10
12/31/10
For
Baghous
e:
12/31/12;
For ESP:
12/31/05
By year end 2008,
Dynegy will surrender
12,OOOSO2 emission
allowances, by year
end 2009 it will
surrender 18,000, by
year end 2010 it will
surrender 24,000,
any by year end 2011
thereafter it will
surrender 30,000
allowances. If the
surrendered
allowances result in
insufficient remaining
to the units
comprising the DMG
system, DMG can
request to surrender
fewer SO2
allowances.
http://www2.
epa.gov/enfo
rcement/illino
is-power-
company-
and-dynegy-
generation-
settlement
3-53
-------
Company
and Plant
Hennepin
Vermilion
Wood River
Kentucky Ut
State
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Unit
Unit 1
Unit 2
Unit 1
Unit 2
Unit 4
Unit 5
Settlement Actions
Retire/Repower
Action
Effective
Date
SOz control
Equipment
Percent
Removal or
Rate
1.2
1.2
1.2
1.2
1.2
1.2
Effective
Date
07/27/05
07/27/05
01/31/07
01/31/07
07/27/05
07/27/05
NOX Control
Equipment
Operate OFA
and/or low NO,
burners
Operate OFA
and/or low NO,
burners
Operate OFA
and/or low NOK
burners
Operate OFA
and/or low NO,
burners
Operate OFA
and/or low NO,
burners
Operate OFA
and/or low NOK
burners
Rate
"Minimum
Extent
Practicable"
"Minimum
Extent
Practicable"
"Minimum
Extent
Practicable"
"Minimum
Extent
Practicable"
"Minimum
Extent
Practicable"
"Minimum
Extent
Practicable"
Effective
Date
08/11/05
08/11/05
08/11/05
08/11/05
08/11/05
08/11/05
PM or Mercury Control
Equipment
Install ESP
(or equiv. alt.
tech) &
continuously
operate
ESPs
Install ESP
(or equiv. alt.
tech) &
continuously
operate
ESPs
Install ESP
(or equiv. alt.
tech) &
continuously
operate
ESPs
Install ESP
(or equiv. alt.
tech) &
continuously
operate
ESPs
Install ESP
(or equiv. alt.
tech) &
continuously
operate
ESPs
Install ESP
(or equiv. alt.
tech) &
continuously
operate
ESPs
Rate
0.03
0.03
0.03
0.03
0.03
0.03
Effective
Date
12/31/06
12/31/06
12/31/10
12/31/10
12/31/05
12/31/05
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
Effective
Date
Notes
Settlement requires first installation
of ESP at either Unit 1 or 2 on
12/31/2006; and on the other by
12/31/2010.
Settlement requires first installation
of ESP at either Unit 4 or 5 on
12/31/2005; and on the other by
12/31/2007.
Reference
ities Company
3-54
-------
Company
and Plant
EW Brown
Generating
Station
State
Kentucky
Unit
Unit 3
Settlement Actions
Retire/Repower
Action
Effective
Date
SOz control
Equipment
Install FGD
Percent
Removal or
Rate
97% or 0.1 00
Effective
Date
12/31/10
NOX Control
Equipment
Install and
continuously
operate SCR by
12/31/2012,
continuously
operate low NO,
boiler and OFA.
Rate
0.07
Effective
Date
12/31/12
PM or Mercury Control
Equipment
Continuously
operate ESP
Rate
0.03
Effective
Date
12/31/10
Allowance
Retirement
Retirement
KU must surrender
53,000 SO2
allowances of 2008
or earlier vintage by
March 1,2009. All
surplus NOX
allowances must be
surrendered through
2020.
Allowance Restriction
Restriction
SO2 and NOK
allowances may not be
used for compliance,
and emissions
decreases for purposes
of complying with the
Consent Decree do not
earn credits.
Effective
Date
Notes
Annual SO2 cap is 31 ,998 tons
through 2010, then 2,300 tons each
year thereafter. Annual NOX cap is
4,072 tons.
Reference
http://www2.
epa.gov/enfo
rcement/kent
ucky-utilities-
company-
clean-air-act-
settlement
Salt River Project Agricultural Improvement and Power District (SRP)
Coronado
Generating
Station
Arizona
Arizona
Unit 1 or
Unit 2
Unit 1 or
Unit 2
Immediately
begin
continuous
operation of
existing FGDs
on both units,
install new
FGD.
Install new
FGD
95% or 0.08
95% or 0.08
New FGD
installed by
1/1/2012
01/01/13
Install and
continuously
operate lowNOK
burner and SCR
Install and
continuously
operate lowNOK
burner
0.32 prior to
SCR
installation,
0.080 after
0.32
LNB by
06/01/200
9, SCR by
06/01/201
4
06/01/11
Optimization
and
continuous
operation of
existing
ESPs.
0.03
Optimiza
tion
begins
im medial
ely, rate
limit
begins
01/01/12
(date of
new
FGD
installatio
n)
Optimiza
tion
begins
im medial
ely, rate
limit
begins
01/01/13
(date of
new
FGD
installatio
n)
Beginning in 2012, al
surplus SO2
allowances for both
Coronado and
Springerville Unit 4
must be surrendered
through 2020. The
allowances limited by
this condition may,
however, be used for
compliance at a
prospective future
plant using BACT
and otherwise
specified in par. 54 of
the consent decree.
SO2 and NO,
allowances may not be
used for compliance,
and emissions
decreases for purposes
of complying with the
Consent Decree do not
earn credits.
Annual plant-wide NOX cap is 7,300
tons after 6/1/2014.
eoa.aov/enfo
rcem ent/salt-
aariculture-
imDrovement
district-
settlement
American Electric Power
Eastern System -Wide [Modified
L mils for SO2]
Eastern System-Wide
Annual Cap
(tons)
145,000
113,000
110,000
102,000
94,000
Annual Cap
(tons)
450,000
450,000
420,000
350,000
Year
2016-2018
2019-2021
2022-2025
2026-2028
2029 and
thereafter
Year
2010
2011
2012
2013
Annual Cap
(tons)
96,000
92,500
92,500
85,000
Year
2009
2010
2011
2012
NOxand SO2
allowances that
would have been
made available by
emission reductions
pursuant to the
Consent Decree
must be surrendered.
NOxand SO2
allowances may not be
used to comply with
any of the limits
imposed by the
Consent Decree. The
Consent Decree
includes a formula for
calculating excess NO,,
allowances relative to
the CAIR Allocations,
htto://www.ct.
aov/aa/lib/aa/
oress releas
es/20 13/201
cdmod.pdf
http ://www2.
epa.gov/enfo
rcem ent/am e
ri can-el ectri c-
service-
corporation
3-55
-------
Company
and Plant
At least
eOOMWfrom
various units
Amos
Big Sandy
Cardinal
Clinch River
State
West Virginia
Virginia
Indiana
West Virginia
West Virginia
West Virginia
West Virginia
Kentucky
Kentucky
Ohio
Ohio
Ohio
Virginia
Unit
Sporn
1-4
Clinch
River
1-3
Tanners
Creek
1-3
Kammer
1-3
Unit 1
Unit 2
Units
Unit 1
Unit 2
Unit 1
Unit 2
Unit 3
Units
1-3
Settlement Actions
Retire/Repower
Action
Retire,
retrofit, or re-
power
Effective
Date
12/31/18
SOz control
Equipment
Install and
continuously
operate FGD
Install and
continuously
operate FGD
Install and
continuously
operate FGD
Burn only coal
with no more
than 1 .75
Ibs/mmBTU
annual average
Install and
continuously
operate FGD
Install and
continuously
operate FGD
Install and
continuously
operate FGD
Install and
continuously
operate FGD
Percent
Removal or
Rate
340,000
2/5,000
260,000
235,000
184,000
174,000
Plant-wide
annual cap:
21 ,700 tons
from 2010 to
2014, then
16, 300 after
1/1/2015
Effective
Date
2014
2015
2016
2017
2018
2019 and
thereafter
12/31/09
12/31/10
12/31/09
Date of
entry
12/31/15
12/31/08
12/31/08
12/31/12
2010-
2014,2015
and
thereafter
NOX Control
Equipment
Install and
continuously
operate SCR
Install and
continuously
operate SCR
Install and
continuously
operate SCR
Continuously
operate low NO,
burners
Install and
continuously
operate SCR
Install and
continuously
operate SCR
Install and
continuously
operate SCR
Install and
continuously
operate SCR
Continuously
operate lowNOK
burners
Rate
85,000
85,000
75,000
72,000
Effective
Date
2013
2014
2015
2016 and
thereafter
01/01/08
01/01/09
01/01/08
Date of
entry
01/01/09
01/01/09
01/01/09
01/01/09
Date of
entry
PM or Mercury Control
Equipment
Continuously
operate ESP
Continuously
operate ESP
Rate
0.03
0.03
Effective
Date
12/31/09
12/31/09
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
and restricts the use of
some. See par. 74-79
for details. Reducing
emissions below the
Eastern System-Wide
Annual Tonnage
LimitationsforNOKand
SO2 earns
supercom pliant
allowances.
Effective
Date
Notes
Reference
3-56
-------
Company
and Plant
Conesville
Gavin
Glen Lynn
Kam m er
Kanawha
River
Mitchell
Mountaineer
Mu skin gum
River
Picway
State
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Virginia
Virginia
West Virginia
West Virginia
West Virginia
West Virginia
West Virginia
Ohio
Ohio
Ohio
Unit
Unit 1
Unit 2
Units
Unit 4
Unit 5
Unite
Unit 1
Unit 2
Units
1-3
Units 5, 6
Units
1-3
Units 1,2
Unit 1
Unit 2
Unit 1
Units
1-4
Units
Unit 9
Settlement Actions
Retire/Repower
Action
Retire,
retrofit, or re-
power
Retire,
retrofit, or re-
power
Retire,
retrofit, or re-
power
Retire,
retrofit, or re-
power
Effective
Date
Date of
entry
Date of
entry
12/31/12
12/31/15
SOz control
Equipment
Install and
continuously
operate FGD
Upgrade
existing FGD
Upgrade
existing FGD
Install and
continuously
operate FGD
Install and
continuously
operate FGD
Burn only coal
with no more
than 1 .75
Ibs/mmBTU
annual average
Burn only coal
with no more
than 1 .75
Ibs/mmBTU
annual average
Install and
continuously
operate FGD
Install and
continuously
operate FGD
Install and
continuously
operate FGD
Install and
continuously
operate FGD
Percent
Removal or
Rate
95%
95%
Plant-wide
annual cap:
35,000
Effective
Date
12/31/10
12/31/09
12/31/09
Date of
entry
Date of
entry
Date of
entry
01/01/10
Date of
entry
12/31/07
12/31/07
12/31/07
12/31/15
NOX Control
Equipment
Install and
continuously
operate SCR
Continuously
operate lowNOK
burners
Continuously
operate lowNOK
burners
Install and
continuously
operate SCR
Install and
continuously
operate SCR
Continuously
operate lowNOK
burners
Continuously
operate over-fire
air
Continuously
operate lowNOK
burners
Install and
continuously
operate SCR
Install and
continuously
operate SCR
Install and
continuously
operate SCR
Install and
continuously
operate SCR
Continuously
operate low NO,
burners
Rate
Effective
Date
12/31/10
Date of
entry
Date of
entry
01/01/09
01/01/09
Date of
entry
Date of
entry
Date of
entry
01/01/09
01/01/09
01/01/08
01/01/08
Date of
entry
PM or Mercury Control
Equipment
Continuously
operate ESP
Rate
0.03
Effective
Date
12/31/02
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
Effective
Date
Notes
Reference
3-57
-------
Company
and Plant
Rockport
Spom
Tanners
Creek
State
Indiana
Indiana
West Virginia
Indiana
Indiana
Unit
Unit 1
Unit 2
Units
Units
1-3
Unit 4
Settlement Actions
Retire/Repower
Action
Effective
Date
SOz control
Equipment
Percent
Removal or
Rate
Effective
Date
NOX Control
Equipment
Rate
Effective
Date
PM or Mercury Control
Equipment
Rate
Effective
Date
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
Effective
Date
Rockport Un ts 1 & 2 sha I not exceed an Annual Tonnage Limit of 28 MTons of SO2 in 201 6- 201 7, 26 Mtons in 2018-2019, 22 MTons in 2020-2025, 1 8 MTons in 2026-2028 and 1 0 MTons in 2029 and each
year thereafter.
Retire,
retrofit, or re-
power
12/31/13
Install DSI
Install and
continuously
operate FGD
Install DSI
Install and
continuously
operate FGD
Burn only coal
with no more
than 1.2
Ibs/mmBTU
annual average
Burn only coal
with no more
than 1.2%
sulfur content
annual average
4/16/2015
12/3172025
4/16/2015
12/3172028
Date of
entry
Date of
entry
Install and
continuously
operate SCR
Install and
continuously
operate SCR
Continuously
operate low NO,
burners
Continuously
operate over-fire
air
12/31/25
12/31/28
Date of
entry
Date of
entry
Notes
Reference
East Kentucky Power Cooperative Inc.
Dale Plant
System -wide
Kentucky
Kentucky
Kentucky
Unit 1
Unit 2
Install and
continuously
operate low NO,
burners by
10/31/2007
Install and
continuously
operate lowNOK
burners by
10/31/2007
0.46
0.46
01/01/08
01/01/08
EKPC must
surrender 1, 000 NOX
allowances
immediately under
the ARP, and 3,107
under the NOK SIP
Call. EKPC must
also surrender
15,311 SO2
allowances.
Date of
entry
By 12/31/2009, EKPC shall choose whether to: 1) install and cont nuously operate NO, controls at Cooper 2 by 12/31/2012 and SO2 controls by 6/30/2012 or 2) retire Dale 3 and Dale 4 by 12/31/2012.
System-wide
12-month
rolling tonnage
limits apply
12-month
rolling limit
(tons)
57,000
40,000
28,000
Start of 12-
month
cycle
10/01/08
07/01/11
01/01/13
All units must
operate lowNOK
boilers
12-month
rolling limit
(tons)
11,500
8,500
8,000
Start of
12-month
cycle
01/01/08
01/01/13
01/01/15
PM control
devices must
be operated
continuously
system-wide,
ESPsmust
be optimized
within 270
days of entry
date, or
EKPC may
choose to
submit a PM
Pollution
Control
Upgrade
Analysis.
0.03
1 year
from
entry
date
All surplus SO2
allowances must be
surrendered each
year, beginning in
2008.
SO2 and NO*
allowances may not be
used to comply with the
Consent Decree. NOX
allowances that would
become available as a
result of compliance
with the Consent
Decree may not be
sold or traded. SO2
and NOK allowances
allocated to EKPC
must be used within the
EKPC system.
Allowances made
available due to
supercompliance may
be sold or traded.
http://www2.
epa.gov/enfo
rcement/east
-kentucky-
cooperative-
settlement
3-58
-------
Company
and Plant
Spurlock
Dale Plant
Cooper
State
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Kentucky
Unit
Unit 1
Unit 2
Units
Unit 4
Unit 1
Unit 2
Settlement Actions
Retire/Repower
Action
EKPCmay
choose to
retire Dale 3
and 4 in lieu
of installing
controls in
Cooper 2
Effective
Date
12/31/2012
SOz control
Equipment
Install and
continuously
operate FGD
Install and
continuously
operate FGD
by 10/1/2008
If EKPC opts to
install controls
retiring Dale, it
must install
continuously
operate FGD
or equiv.
technology
Percent
Removal or
Rate
95% or 0.1
95% or 0.1
95% or 0.10
Effective
Date
6/30/2011
1/1/2009
NOX Control
Equipment
Continuously
operate SCR
Continuously
operate SCR and
OFA
If EKPC elects to
install controls, it
must
continuously
operate SCR or
install equiv.
technology
Rate
0.12forUnt
1 until
01/01/2013,
at which
point the
unit limit
drops to
0.1. Priorto
01/01/2013,
the
combined
average
when both
units are
operating
must be no
more than
0.1
0.1 for Unit
2,0.1
combined
average
when both
units are
operating
0.08 (or
90%ifnon-
SCR
technology
is used)
Effective
Date
60 days
after entry
60 days
after entry
12/31/12
PM or Mercury Control
Equipment
Rate
Effective
Date
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
Effective
Date
Notes
EKPC has installed a DFGD on
this unit and Dale continues to
operate.
Reference
Nevada Power Company
Clark
Generating
Station
Nevada
Nevada
Unit 5
Unite
Beginning 1/1/2010, combined NOX emissions from Units 5, 6, 7, and 8 must be no more than 360 tons per year.
Units may
only fire
natural gas
Increase water
injection
immediately,
then install and
operate ultra-low
NOX burners
(ULNBs) or
equivalent
technology. In
2009, Units 5
and 8 may not
emit more than
180 tons
combined
5ppm 1-
hour
average
5ppm 1-
hour
average
12/31/08
(ULNB
installation
),
01/30/09
(1-hour
average)
12/31/09
(ULNB
installation
),
01/30/10
(1-hour
average)
Allowances may not be
used to comply with the
Consent Decree, and
no allowances made
available due to
compliance with the
Consent Decree may
be traded or sold.
http ://www2.
epa.gov/enfo
rcement/nev
ada-power-
company-
clean-air-act-
caa-
settlement
3-59
-------
Company
and Plant
State
Nevada
Nevada
Unit
Unit/
Units
Settlement Actions
Retire/Repower
Action
Effective
Date
SOz control
Equipment
Percent
Removal or
Rate
Effective
Date
NOX Control
Equipment
Rate
5ppm 1-
hour
average
5ppm 1-
hour
average
Effective
Date
12/31/09
(ULNB
installation
),
01/30/10
(1-hour
average)
12/31/08
(ULNB
installation
),
01/30/09
(1-hour
average)
PM or Mercury Control
Equipment
Rate
Effective
Date
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
Effective
Date
Notes
Reference
Dayton Power & Light
Stuart
Generating
Station
Ohio
Station-
Non-EPA Settlement of 10/23/2008
Complete
installation of
FGDs on each
unit.
96% or 0.10
82%
including
data from
periods of
including
periods of
malfunctions
07/31/09
7/31/09
through
7/30/1 1
after
7/31/1 1
Owners may not
purchase any
new catalyst with
SO2 to SO3
conversion rate
greater than
Install control
technology on
one unit
0.17
station-wide
station-wide
0.10 on any
single unit
station-wide
station-wide
30 days
after entry
60 days
after entry
date
12/31/12
07/01/12
12/31/14
0.030 Ibs
per unit
nstall rigid-
type
unit's ESP
07/31/09
NOxand SO2
allowances may not be
used to comply with the
monthly rates specified
n the Consent Decree.
PSEG FOSSIL, Amended Consent Decree of November 2006
Keamy
Hudson
New Jersey
New Jersey
New Jersey
Unit/
Unit 8
Unit 2
Retire unit
Retire unit
01/01/07
01/01/07
nstall Dry FGD
(or approved
alt. technology)
and continually
operate
0.15
12/31/10
Install SCR (or
approved tech)
and continually
operate
0.1
12/31/10
Install
Baghouse (or
approved
technology)
0.015
12/31/10
Allowances allocated
to Kearny, Hudson,
and Mercer may only
be used for the
operational needs of
surplus allowances
must be surrendered.
Within 90 days of
amended Consent
Decree, PSEG must
surrender 1, 230 NOX
Allowances and
8,568 SO2
already allocated to
or generated by the
units listed here.
Kearny allowances
must be surrendered
with the shutdown of
those units.
http://www2.
epa.gov/enfo
rcement/pse
settlement
3-60
-------
Company
and Plant
Mercer
State
New Jersey
New Jersey
Unit
Unit 1
Unit 2
Settlement Actions
Retire/Repower
Action
Effective
Date
SOz control
Equipment
nstall Dry FGD
(or approved
alt. technology)
and continually
operate
nstall Dry FGD
(or approved
alt. technology)
and continually
operate
Percent
Removal or
Rate
Annual Cap
(tons)
5,547
5,270
5,270
5,270
0.15
0.15
Effective
Date
Year
2007
2008
2009
2010
12/31/10
12/31/10
NOX Control
Equipment
Install SCR (or
approved tech)
and continually
operate
Install SCR (or
approved tech)
and continually
operate
Rate
Annual Cap
(tons)
3,486
3,486
3,486
3,486
0.1
0.1
Effective
Date
Year
2007
2008
2009
2010
01/01/07
01/01/07
PM or Mercury Control
Equipment
Install
Baghouse (or
approved
technology)
Install
Baghouse (or
approved
technology)
Rate
0.015
0.015
Effective
Date
12/31/10
12/31/10
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
Effective
Date
Notes
Reference
Westar Energy
Jeffrey
Energy
Center
Kansas
All units
Units 1 , 2, and 3 have a total annual limit
of 6,600 tons of SO2 starting 201 1
Units 1 , 2, and 3 must all insta I FGDs by
2011 and operate them cont nuously.
FGDs must maintain a 30-Day Rolling
Average Unit Removal Efficiencyfor SC>2
of at least 97% or a 30-Day Rolling
Average Unit Emission Rate for SC>2 of no
greater than 0.070 Ibs/mmBTU.
Units 1-3 must continuously operate Low
NOK Combustion Systems by 2012 and
achieve and ma ntain a 30-Day Rolling
Average Unit Emission Rate for NO* of no
greater than 0.180 Ibs/mmBTU.
One of the three units must install an
SCR by 2015 and operate it continuously
to maintain a 30-Day Rolling Average
Unit Emission Rate for NOK of no greater
than 0.080 Ibs/mmBTU.
By 201 3 Westar shall elect to either (a)
install a second SCR on one of the other
JEC Units by 201 7 or (b) meet a 0.100
bs/mmBTU Plant-Wide 12-Month Rolling
Average Emission Rate for NO* by 201 5
Units 1, 2, and 3 must operate each
ESP and FGD system continuously
by 2011 and maintain a 0.030
Ibs/mmBTU PM Emissions Rate.
Units 1 and 2's ESPs must be
rebuilt by 2014 in orderto meet a
0.030 Ibs/mmBTU PM Emissions
Rate
http://www2.
epa.gov/enfo
rcem ent/west
ar-energy-
inc-
settlement
Duke Energy
Gallagher
Indiana
Units 1 &
3
Units 2 &
4
Retire or
repower as
natural gas
1/1/2012
Install Dry
sorbent
injection
technology
80%
1/1/2012
http://www2.
epa.gov/enfo
rcement/duk
e-energy-
gallagher-
Dlant-clean-
air-act-
settlement
American Municipal Power
Gorsuch
Station
Ohio
Units 2 &
3
Units 1 &
4
Elected to Retire Dec 15,
2010 (must retire by Dec
31,2012)
htto://www2.
epa.qov/enfo
rcem ent/am e
rican-
municipal-
oower-clean-
air-act-
settlement
Hoosier Energy Rural Electric Cooperative
Ratts
Indiana
Units 1 &
2
Install &
continually
operate SNCRS
0.25
12/31/201
1
Continuously operate ESP
Annually surrender any NO* and SO2 allowances that
Hoosier does not need in orderto meet its regulatory
obligations
htto://www2.
eoa.aov/enfo
rcement/hoo
3-61
-------
Company
and Plant
Merom
State
Indiana
Unit
Unit 1
Unit 2
Settlement Actions
Retire/Repower
Effective
Action Date
SOz control
Equipment
Continuously
run current
FGD for 90%
removal and
update FGD for
98% removal
by 201 2
Continuously
run current
FGD for 90%
removal and
update FGD for
98% removal
by 201 4
Percent
Removal or
Rate
98%
98%
Effective
Date
2012
2014
NOX Control
Equipment
Continuously
operate existing
SCRs
Rate
0.12
Effective
Date
PM or Mercury Control
Equipment
Rate
Effective
Date
Continuously operate ESP and
achieve PM rate no greater than
0.007 by 6/1/12
Continuously operate ESP and
achieve PM rate no greater than
0.007 by 6/1/13
Allowance
Retirement
Retirement
Allowance Restriction
Effective
Restriction Date
Notes
Reference
rural-el ectri c-
coooerative-
mc-
settlement
Northern Indiana Public Service Co.
Bailly
Michigan
City
Schahfer
Dean H
Mitchell
Indiana
Indiana
Indiana
Indiana
Indiana
Indiana
Units 7 &
8
Unit 12
Unit 14
Unit 15
Units 17
&18
Units 4,
5, 6, &
11
Retire 12/31/2010
Upgrade
existing FGD
FGD
FGD
FGD
Upgrade
existing FGD
95% by 01/01/11
97% by 01/01/1 4 (95% if
low sulfur coal only is
burned)
0.1
Ibs/mmBTU
0.08
Ibs/mmBTU
0.08
Ibs/mmBTU
97%
12/31/2018
12/31/2013
12/31/2015
1/31/2011
OFA & SCR
OFA & SCR
OFA & SCR
LNB/OFA
Either: SCR or
SNCR
LNB/OFA
0.15 Ibs/mmBTU by
12/31/10
0.13 Ibs/mmBTU by
12/31/13
0.12 Ibs/mmBTU by
12/31/15
0.14 Ibs/mmBTU by
12/31/10
0.12 Ibs/mmBTU by
12/31/11
0.10 Ibs/mmBTU by
12/31/13
0.14 Ibs/mmBTU by
12/31/10
0.12 Ibs/mmBTU by
12/31/12
0.10 Ibs/mmBTU by
12/31/14
0.16
0.08
0.15
0.2
3/31/201 1
12/31/201
5
12/31/201
2
3/31/201 1
0.3
Ibs/mmBT
U (0.015 if
a
Baghouse
s installed
0.3
Ibs/mmBT
U (0.015 if
a
Baghouse
is installed)
0.3
Ibs/mmBT
U (0.015 if
a
baghouse
is installed)
0.3
Ibs/mmBT
U (0.015 if
a
baghouse
is installed)
0.3
Ibs/mmBT
U (0.015 if
a
baghouse
is installed)
12/31/20
10
12/31/20
18
12/31/20
13
12/31/20
15
12/31/20
10
Tennessee Valley Authority
Colbert
Widows
Creek
Paradise
Alabama
Alabama
Kentucky
Units 1-
4
Units
Units 1 -
Unit 7
Unit 8
Units 1 &
2
Units
Retire 2 units 7/31/1 3
Retire 2 units 7/31/1 4
Retire 2 unts 7/31/1 5
FGD
FGD
6/30/2016
12/31/15
Upgrade FGD
Wet FGD
93%
12/31/12
Effective
Date
SCR
SCR
6/30/2016
Effective
Date
SCR
SCR
SCR
SCR
Effective
Date
Effective
Date
Effective
Date
Effective
Date
Shall surrender all
calendar year NOX
and SOs Allowances
allocated to TVA that
are not needed for
compliance with its
own CAA reqts.
Allocated allowances
may be used for
TVA's own
compliance with CAA
reqts.
http://www2.
epa.gov/enfo
rcement/nort
hern-indiana-
public-
service-
company-
clean-air-act-
settlement
Shall not use NOKor
SO2 Allowances to
comply with any
requirement of the
Consent Decree,
Nothing prevents TVA
from purchasing or
otherwise obtaining 201 1
NOxandSO2
allowances from other
sources for its
compliance with CAA
reqts.
TVA may sell, bank,
use, trade, or transfer
htto://www2.
eoa.aov/enfo
essee-val lev-
authority^
clean-air-act-
settlementl
3-62
-------
Company
and Plant
Shawnee
Allen
Bull Run
Cumberland
Gallatin
John Sevier
Johnsonville
Kingston
State
Kentucky
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Unit
Units 1 &
4
Units 5 -
10
Units 1 -
3
Unit 1
Units 1 &
2
Units 1 -
4
Units 1 &
2
Units 3 &
4
Units 1 -
10
Units 1 -
Settlement Actions
Retire/Repower
Action
Effective
Date
Retire 2 Units 12/31/1 2
and 12/31/15
Retire 6 Units 12/31/15
Retire 4 Units 12/31/17
SOz control
Equipment
FGD
FGD
Wet FGD
Wet FGD
FGD
FGD
Percent
Removal or
Rate
1.2
1.2
Effective
Date
12/31/17
Effective
Date
12/31/18
Effective
Date
Effective
Date
12/31/17
12/31/15
FGD
Effective
Date
NOX Control
Equipment
SCR
Rate
Effective
Date
12/31/17
SCR
SCR
12/31/17
12/31/15
SCR
Effective
Date
PM or Mercury Control
Equipment
Rate
Effective
Date
0.3
0.3
12/31/18
Effective
Date
0.3
12/31/17
0.3
Effective
Date
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
any NOK and SO2
Super-Compliance"
Allowances resulting
from meeting System-
wide limits. Except that
reductions used to
support new CC/CT will
not be Super
Allowances in that year
and thereafter.
Effective
Date
Notes
Reference
Wisconsin Public Service
Pulliam
West on
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Units 5-6
Units 7-8
Unit 1
Units 2
Units 3
Units 4
Retire, refuel
or repower
as natural
gas
Retire, refuel
or repower
as natural
gas
6/1/2015
6/1/2015
ReACT by
12/31/2016
Continuously
Operate the
existing DFGD
& burn only
Powder River
Basin Coal
0.750
Ibs/mmBTU
0.750
Ibs/mmBTU
& plant-wide
cap of 2100
tons starting
2016
0.750
Ibs/mmBTU
0.750
Ibs/mmBTU
0.750
Ibs/mmBTU
until 201 6
0.080
Ibs/mmBTU
2016
onwards
0.080
bs/mmBTU
1/1/2013
until
retirement
1/1/2013
1/1/2013
until
retirement
1/1/2013
until
retirement
12/31/16
2/31/2013
ReACT by
12/31/2016
Continuously
Operate the
existing SCR
0.250
Ibs/mmBTU
& plant-
wide cap of
1500 tons
starting
2016
0.250
Ibs/mmBTU
0.280
Ibs/mmBTU
0.130
Ibs/mmBTU
until 201 6
0.100
Ibs/mmBTU
2016
onwards
0.060
Ibs/mmBTU
12/31/12
12/31/201
2 until
retirement
12/31/201
2 until
retirement
12/31/16
2/31/2013
The modeled SO2 rate in IPM is
ower; only tonnage limitation
imposed through a constraint.
http://www2.
epa.gov/enfo
rcement/wisc
onsin-public-
service-
corporation-
settlement
Louisiana Generating LLC
Plant-Wide Annual Tonnage Limitations for SC>2 is 18,950 tons in
Plant-Wide Annual Tonnage Limitations
3-63
-------
Company
and Plant
Big Cajun 2
State
Louisiana
Unit
Unit 1
Unit 2
Unit 3
Settlement Actions
Retire/Repower
Action
Effective
Date
SOz control
Equipment
Percent
Removal or
Rate
Effective
Date
201 6 and thereafter
Retirement,
Refueling,
Repowering,
or Retrofit
Refuel/conve
rt to NG fired
04/01/25
04/15/15
install and
Continuously
Operate DSI
install and
Continuously
Operate Dry
FGD
0.380
Ibs/mmBTU
[2015]
0.070
Ibs/mmBTU
4/15/2015
[DSI]
4/1/2025
[DFGD]
NOX Control
Equipment
Rate
Effective
Date
for NOX is 8,950 tons in 201 5 and
thereafter
install and
Continuously
Operate SNCR
install and
Continuously
Operate SNCR
install and
Continuously
Operate SNCR
0.150
Ibs/mmBTU
0.150
Ibs/mmBTU
0.135
Ibs/mmBTU
05/01/14
05/01/14
05/01/14
PM or Mercury Control
Equipment
Continuously
Operate
each ESP
Continuously
Operate
each ESP
Rate
0.030
Ibs/mmBT
U
0.030
Ibs/mmBT
U
Effective
Date
04/15/15
04/15/15
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
Effective
Date
Notes
May trade Super-Compliant
Allowances, may buy external
allowances to comply.
"Commencing January 1, 2013, and
continuing thereafter, Settling
Defendant shall burn only coal with
no greater sulfur content than 0.45
percent by weight on a dry basis at
Big Cajun II Units 1 and 3. "
Reference
ittp ://www2.
eoa.aov/enfo
rcement/louis
i ana-
settlement
Dairyland Power Cooperative
Dairyland Power Cooperative shall not exceed an Annual Plant-wide Tonnage Limitation of 6800 tons of NOX in calendar years 2016, 3700 tons 2017-2019, and 3200 tons in 2020 and thereafter; and an
Annual Plant-wide Tonnage Limitation of 6070 tons of SO2 in 2016, 6060 tons 201 7-201 9 and 4580 tons in 2020 and thereafter.
Alma
J.P. Madgett
Wisconsin
Wisconsin
Unit 1
Unit 2
Unit 3
Unit 4
Units
Unit 1
Cease
Burning Coal
Cease
Burning Coal
Cease
Burning Coal
Option 2:
Retrofit and
Regulate
both units
more
stringently
06/30/12
06/30/12
06/30/12
12/31/14
Install and
continuously
operate DFGD
or DSI at Alma
4
Install and
continuously
operate DFGD
1.00
Ibs/mmBTU
at Alma 4
And a joint
cap of 3,737
tons until
2019, and
2, 242 tons
thereafter. In
the event
that one
retires,
Tonnage
Cap of 2, 136
tons for the
remaining
unit until
2019 and
1 ,282 tons
thereafter
0.090
bs/mmBTU
12/31/2014
12/31/14
Continuously
Operate the
existing Low NO*
Combustion
System
(including OFA)
and SNCR
Continuously
Operate existing
Low NO*
Combustion
System
Install an SCR
0.350
Ibs/mmBTU
Joint cap of
1308 tons
for- until
2019, and
785 tons
thereafter.
n the event
that one
retires,
Tonnage
Cap of 746
tons for
remaining
unit until
2019 and
449 tons
thereafter
0.30
Ibs/mmBTU
0.080
Ibs/mmBTU
8/1/2012
12/31/201
4
8/1/2012
6/30/2016
Continuously
Operate an
ESPorFF
on
Alma Unit 4
Continuously
Operate the
existing
Baghouse
0.030
Ibs/mmBT
U[with
ESP]
0.015
Ibs/mmBT
U [with FF]
at Alma 4.
Joint cap of
112 tons
until 2019,
and 67
tons
thereafter.
In the
event that
one retires,
Tonnage
Cap of 64
tons for the
remaining
unit until
2019 and
39 tons
thereafter
0.0150
Ibs/mmBT
U
12/31/14
07/01/13
Dairyland was provided with two
options for compliance. It chose
Option 2 and it is the one modeled
in IPM. Details on Option 1 can be
found in the settlement document
referenced in the adjoining column.
ittp ://www2.
eoa.aov/enfo
rcement/dair
vland-oower-
cooperative-
settlement
3-64
-------
Company
and Plant
Genoa
State
Wisconsin
Unit
Unit 1
Settlement Actions
Retire/Repower
Action
Effective
Date
SOz control
Equipment
Continuously
Operate the
FGD
Percent
Removal or
Rate
0.090
Ibs/mmBTU
Effective
Date
12/31/12
NOX Control
Equipment
Continuously
Operate existing
Low NOX
Combustion
System including
OFA
Install an SNCR
Rate
0.14
Ibs/mmBTU
Annual
Tonnage
Cap of
1,1 40 tons
Effective
Date
12/31/201
4
6/1/2015
PM or Mercury Control
Equipment
Continuously
Operate the
existing
Baghouse
Rate
0.0150
Ibs/mmBT
U
Effective
Date
07/01/13
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
Effective
Date
Notes
Reference
Dominion Energy, Inc.
Brayton
Point
Kincaid
Power
Station
State Line
Power
Station
Massachuset
ts
Illinois
Indiana
Unit 1
Unit 2
Units
Unit 1
Unit 2
Units
Unit 4
In calendar year 2014, and in each calendar year thereafter, Kincaid shall not exceed a Plant-Wide Annual Tonnage Limitation of 3,500 tons of NOX & 4,400 tons of SC>2, and Brayton Point shall not exceed a
Plant-Wide Annual Tonnage Limitation of 4,600 tons of NOK & 4,100 tons of SO2.
Retire
06/01/12
Continuously
Operate the
existing dry
FGD
Continuously
Operate dry
FGD
Continuously
Operate DSI
0.150
bs/mmBTU
0.080
Ibs/mmBTU
0.100
Ibs/mmBTU
06/01/13
07/01/13
01/01/14
Continuously
Operate the
SCR, OFA, and
LNB
Continuously
Operate the LNB
and OFA
Continuously
Operate the
SCR, OFA, and
LNB
Continuously
Operate each
SCR and OFA
0.080
Ibs/mmBTU
0.280
Ibs/mmBTU
0.080
Ibs/mmBTU
0.080
Ibs/mmBTU
05/01/13
05/02/13
05/01/13
05/01/13
Install/Contin
uously
Operate a
Baghouse
Install/Contin
uously
Operate a
Baghouse
Continuously
Operate the
ESP
0.015
Ibs/mmBT
U [PM by
2013]
0.01
Ibs/mmBT
U[PM
post- 201 3]
0.015
Ibs/mmBT
U [PM by
2013]
0.01
Ibs/mmBT
U[PM
post-2013]
0.030
Ibs/mmBT
U [PM by
2013]
0.015
Ibs/mmBT
U [PM by
post-2013]
06/01/13
07/01/13
06/01/13
htto ://www2.
epa.aov/enf
orcem ent/d
ominion-
enerqy-inc
Wisconsin Power and Light
Edgewater
Generating
Station
Wisconsin
Units
Unit 4
Retire,
Refuel, or
Repower
Retire,
Refuel, or
Repower
12/31/15
12/31/18
Edgewater 3-5- shall not exceed an Annual Tonnage Limitat on of 2,500 tons of NO, n calendar years 2016-2018, and
11 00 tons 2019 onwards & an Annual Tonnage Limitation of 12,500 tons of SO2 in 2016, 6000 tons 2017-2018 and 1100
tons 2019 onwards. Columb a 1 & 2 shall not exceed an Annual Tonnage Limitation of 5,600 tons of NOK in calendar
years 2016-2018, and 4300 tons 2019 onwards & an Annual Tonnage Limitation of 3290 tons of SO2 in 2016 and
thereafter.
Unit-Specific
Annual
Tonnage
Cap of 700
Tons of SO2
0.700
bs/mmBTU
05/21/13
05/21/13
Operate SNCR
and LNB
Unit-
Specific
Annual
Tonnage
Cap of 250
tons of NO,
0.150
Ibs/mmBTU
05/21/13
01/01/14
Continuous
Operation of
the existing
ESP
0.030
Ibs/mmBT
U
12/31/13
ittp ://www2.
eoa.aov/enfo
rcement/wisc
al-settlement
3-65
-------
Company
and Plant
Columbia
Generating
Station
Nelson
Dewey
Generating
Station
State
Wisconsin
Wisconsin
Unit
Units
Unit 1
Unit 2
Unit 1
Unit 2
Settlement Actions
Retire/Repower
Action
Retire,
Refuel, or
Repower
Retire,
Refuel, or
Repower
Effective
Date
12/31/15
12/31/15
SOz control
Equipment
Install and
continuously
operate DFGD
Install and
continuously
operate DFGD
commence
burning 100%
Powder River
equivalent fuel
containing <
1.00
Ibs/mmBTU of
SO2
Percent
Removal or
Rate
0.075
Ibs/mmBTU
0.075
Ibs/mmBTU
Ibs/mmBTU
0.800
Ibs/mmBTU
Effective
Date
12/31/16
01/01/15
05/22/13
NOX Control
Equipment
Install and
continuously
operate SCR
Operation of the
Low NOx
Combustion
System
Operation of the
Low NOx
Combustion
System
-
Install and
continuously
operate SCR
Rate
0.070
Ibs/mmBTU
0.150
Ibs/mmBTU
0.150
Ibs/mmBTU
~
RTI
mm
0.300
Ibs/mmBTU
Effective
Date
05/01/13
07/21/13
7/21/2013
12/31/201
8
04/22/13
PM or Mercury Control
Equipment
Install and
continuously
operate
Fabric Filter
Install and
continuously
operate
Fabric Filter
Rate
0.015
Ibs/mmBT
U
0.015
Ibs/mmBT
0.015
Ibs/mmBT
U
O.IOOIbs/
mmBTU
Effective
Date
12/31/16
12/31/14
12/31/14
04/22/13
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
Effective
Date
Notes
Cease Burning Petcoke and
Coal or
Equivalent at Nelson Dewey Units 1
and 2.
Reference
3-66
-------
Table 3-15 State Settlements in EPA Base Case v.5.13
Company
and Plant
State
Unit
State Enforcement Actions
Retire/Repower
Action
Effective
Date
SO2 Control
Equipment
Percent
Removal or
Rate
Effective Date
NOX Control
Equipment
Rate
Effective
Date
PM Contro
Equipment
Rate
Effective
Date
Mercury Control
Equipment
Rate
Effective Date
Notes
AES
Greenidge
West over
Hickling
Jennison
New York
New York
New York
New York
New York
New York
New York
Unit 4
Units
Units
Unit/
Unit 1
Unit 2
Unit 1
If the MPC project is discontinued at Greenidge Unit 4 by 12/31/2009, Unit 4 will be subject to the following SO2 emission caps: 2005 will be 12, 125 tons, 2006 will be 11, 800 tons, 2007 will be 11, 475 tons,
2008 will be 1 1,150 tons, 2009 will be 10,825 tons. By 12/31/2009, AES shall control, repower, or cease operations at Westover Unit 7. Beginn ng in 2005, Unit 8 will be subject to the following SO2 emission
caps: 2005 is 9500 tons, 2006 is 9250, 2007 is 9000, 2008 is 8750, 2009 is 8500 tons.
Update: as of May 2009, CONSOL and AES describe the Greenidge Unit 4 MPC effort as a success.
nstall
BACT,
repower, or
cease
operations
Install FGD
Install BACT
90%
09/01/07
12/31/09
nstall SCR
Install BACT
0.15
09/01/07
12/31/09
Update: as of May 2009, NOK emissions appear to be above the specified 0.15 Ibs/mmBtu
Install
BACT,
repower, or
cease
operations
Install
BACT,
repower, or
cease
operations
Install
BACT,
repower, or
cease
operations
Install
BACT,
repower, or
cease
Install BACT
Install BACT
Install BACT
Install BACT
90%
12/31/10
12/31/09
05/01/07
05/01/07
05/01/07
nstall SCR
nstall BACT
nstall BACT
nstall BACT
nstall BACT
0.15
12/31/10
12/31/09
05/01/07
05/01/07
05/01/07
ittp ://www.ag. ny.gov/press-
rel ease/govern or-and-attorney-g en eral-
an noun ce-new-yorks-largest-coal-pl ants-
si ash-pollution
ittp://investor.aes.com/phoenix.zhtml?c=
202639&p=irol-
newsArticle&ID=1274075&highlight=
1) Except when Greenidge Unit 4 is
operating below minimum operating load,
it will make good faith efforts to achieve a
MOK emission rate of 0.1 Ibs/mmBtu. If
this level cannot be achieved, the
emission limit shall be the level achieved
within one year of commencement of
operation, no less stringent than 0.15
Ibs/mmBtu. 2) Unit 4 will make good faith
efforts to achieve a SO2 removal
efficiency of 95%. If this removal
efficiency cannot be achieved, the
emission limit shall be the level achieved
by 9/1/2007, but no less stringent than
90% removal efficiency, resulting in a
0.38 Ibs/mmBtu permitted limit.
ittp://www.powerm ag.com/print/environm
ental/Apply-the-fundamentals-to-improve-
emissions-performance_574.html
1) Except when Westover Unit 8 is
operating below minimum operating load,
it will make good faith efforts to achieve a
MOK emission rate of O.llbs/mmBtu. If
this level cannot be achieved, the
emission limit will be the level achieved
within one year of operation that is no
ess stringent than 0.15 Ibs/mmBtu. 2)
Unit 8 will make good faith efforts to
achieve a SO2 removal efficiency of 95%.
If this level cannot be achieved, a removal
efficiency no less than 90% will be used,
resulting in a 0.34 Ibs/mmBtu permit.
3-67
-------
Company
and Plant
State
New York
Unit
Unit 2
State Enforcement Actions
Retire/Repower
Action
operations
nstall
BACT,
repower, or
cease
operations
Effective
Date
SO2 Control
Equipment
Install BACT
Percent
Removal or
Rate
Effective Date
05/01/07
NOX Control
Equipment
nstall BACT
Rate
Effective
Date
05/01/07
PM Contra
Equipment
Rate
Effective
Date
Mercury Control
Equipment
Rate
Effective Date
Notes
Miagara Mohawk Power
Huntley
New York
Units
63-66
NRG shall comply with the below annual tonnage limitationsfor its Huntley and Dunkirk Stations: In 2005 59,537 tons of SO2 and 10,777 tons of NOX, in 2006 34,230 of SO2 and 6,772 of NOX, in 2007 30,859
of SO2 and 6,211 ofNOx, in 2008 22, 733 tons of SO2 and 6,211 tons of NOซ, in 2009 19,444 of SO2 and 5,388 of NOซ, in 2010 and 2011 19,444 of SO2 and 4,861 of NOX, in 2012 16,807 of SO2 and 3,241 of
NOX, 2013 and 14,169 of SO2 and 3,241 of NOซ thereafter.
Retire
Before
2008
ittp ://www.ag. ny.gov/press-
rel ease/govern or-and-attorney-g en eral-
an noun ce-new-yorks-largest-coal-pl ants-
si ash-pollution
Public Service Co. of NM
San Juan
Mew Mexico
Mew Mexico
Mew Mexico
New Mexico
Unit 1
Unit 2
Units
Unit 4
State-of-the-art
technology
90%
10/31/08
03/31/09
04/30/08
10/31/07
State-of-the-art
technology
0.3
10/31/08
03/31/09
04/30/08
10/31/07
Operate
Baghouse and
demister
technology
0.015
12/31/09
12/31/09
04/30/08
10/31/07
Design
activated
carbon
njection
(or
comparable
tech)
12/31/09
12/31/09
04/30/08
10/31/07
All four units have installed Wet
Scrubbers. Unit 1 and 4 NO* controls
[SNCR] are hardwired into EPA Base
Case.
ittp://nmsierraclub.org/sites/default/files/2
0055-
10SanJuanfinaldecreeasentered%20%28
2%29.pdf
Public Service Co of Colorado
Comanche
Colorado
Colorado
Colorado
Unit 1
Unit 2
Units
Install and
operate FGD
Install and
operate FGD
Install and
operate FGD
0.1
bs/mmBtu
combined
average
0.1
Ibs/mmBtu
07/01/09
07/01/09
nstall low-NOK
emission controls
nstall low-No*
emission controls
nstall and operate
SCR
0.15 Ibs/mmBtu
combined
average
0.08
07/01/09
07/01/09
Install and
operate a fabric
filter dust
collection
system
0.013
Install
sorbent
injection
:echnology
Install
sorbent
injection
:echnology
Install
sorbent
injection
technology
07/01/09
07/01/09
Within 180
days of start-up
Comanche units 1 and 2 taken together
shall not exceed a 0.15 heat rate for NO*,
nor 0.10forSO2,no later than 180 days
after initial start-up of control equipment,
or by 7/01/2009, whichever is earlier.
ittp://content. si erraclub.org/coal/sites/con
tent . si erracl ub . org . coal/fi 1 es/el p/d ocs/co-
comanche_agree-sign_2004-12-02.pdf
Rochester Gas & Electric
Russell Plant
New York
Units
1 -4
Retire all
units
ittp ://www.ag. ny.gov/press-
rel ease/cu om o-an noun ces-settl em ent-
cl ose-roch ester-gas-el ectri cs-coal-
Durning-russell-power
Mi rant New York
Lovett Plant
New York
New York
Unit 1
Unit 2
Retire
Retire
05/07/07
04/30/08
http://www.nytimes.com/2007/05/11/nyreg
ion/11 plant. html?_r=1&pagewanted=print
Retirements are pursuant to a 2003
consent decree, and the plant's failure to
comply with the required reductions.
TVA
Allen
Bull Run
Colbert
Tennessee
Tennessee
Alabama
Units 1 - 3
Unit 1
Units 1 - 4
Rem ove from
Service, FGD, or
Retire
Install Wet FGD
Rem ove from
Service, FGD,
Repower to
Renewable
Biomass, or
Retire
12/31/2015
Effective Date
6/30/2016
nstall SCR
nstall SCR
Rem ove from
Service, SCR,
Repower to
Renewable
Biomass, or Retire
Effective
Date
Effective
Date
6/30/2016
http://www2.epa.gov/sites/production/files
/documents/tvacoal-fired-cd.pdf
3-68
-------
Company
and Plant
Cumberland
Gallatin
John Sevier
Johnsonville
Kingston
Paradise
Shawn ee
Widows
Creek
State
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Kentucky
Kentucky
Alabama
Unit
Units
Units 1 & 2
Units 1 - 4
Units 1 & 2
Units3&4
Units 1-10
Units 1 - 9
Units 1 & 2
Units
Units 1 & 4
Units 1 & 2
Unit 3 & 4
Units5&6
Units7&8
State Enforcement Actions
Retire/Repower
Action
Effective
Date
Retire
Rem ove
from
Service
Retire
12/31/2012
12/31/2012
6 Units by
12/31/15,4
Units by
12/31/18
Retire
Retire
Retire
7/31/2013
7/31/2014
7/31/2015
SO2 Control
Equipment
Rem ove from
Service, FGD, or
Retire
Install Wet FGD
FGD, Repowerto
Renewable
Biomass, or
Retire
Percent
Removal or
Rate
Effective Date
12/31/2015
Effective Date
12/31/2017
FGD, Repowerto
Renewable
Biomass, or
Retire
12/31/2015
Install Wet FGD
Upgrade FGD
Install Wet FGD
FGD, Repowerto
Renewable
Biomass, or
Retire
93%
Rem oval
Effective Date
12/31/2012
Effective Date
12/31/2017
Install Wet FGD
Effective Date
NOX Control
Equipment
nstall SCR
nstall SCR
nstall SCR,
Rep ower to
Renewable
Biomass, or Retire
Rate
Effective
Date
Effective
Date
Effective
Date
12/31/2017
nstall SCR,
Rep ower to
Renewable
Biomass, or Retire
12/31/2015
nstall SCR
nstall SCR
nstall SCR
nstall SCR,
Rep ower to
Renewable
Biomass, or Retire
Effective
Date
Effective
Date
Effective
Date
12/31/2017
Install SCR
Effective
Date
PM Contro
Equipment Rate
Effective
Date
RC Cape May Holdings, LLC
B L England
New Jersey
Unit 1
Unit 2
Retire/Rep
ower
Retire/Rep
ower
[Decision
to be made
by
December
2013]
05/01/14
05/01/14
Mercury Control
Equipment
Rate
Effective Date
Notes
httD://www.ni.aov/deD/docs/20120613104
728. odf
3-69
-------
Table 3-16 Citizen Settlements in EPA Base Case v.5.13
Company and
Plant
State
Unit
Citizen Suits Provided by DOJ
Retire/Repower
Action
Effective
Date
SC-2 control
J Percent Remova
or Rate
Effective
Date
NOX Control
Equipment) Rate
Effective
Date
PM Control
Equipment
Rate
Effective
Date
Mercury Control
Equipment|Rate
Effective
Date
Notes
SWEPCO (AEP)
Welsh
Texas
Units
1-3
Install and
operate CEMs
12/31/2010
SWEPCO may attempt to demonstrate that PM
CEMs are infeasible after two years of operation.
http://www.ocefoundation.org/PDFs/ConsentDecr
ee&CLtoDOJ.pdf
Allegheny Energy
Hatfi eld's Ferry
Pennsylvania
Pennsylvania
Pennsylvania
Unit 1
Unit 2
Unit 3
Install and
operate
wet FGD
6/30/2010
Install and
operate sulfur
trioxide injection
systems, improve
ESP
performance
0.1 Ibs/mmBtu in
2006, then 0.075
bs per hour
(filterable) and 0.1
Ibs/mmBtu for
sarticles less than
:en microns in
2010
7/31/2006
and
6/30/2010
1 1/31/2006
and
6/30/2010
PennFuture_EIP_Lawsuit.php
Wisconsin Public Service Corp
Pulliam
Wisconsin
Wisconsin
Unit 3
Unit 4
Retire
12/31/2007
ittp://milwaukee. bizjournals.com/milwaukee/stori
es/2006/10/23/daily29.html
University of Wisconsin
Charter Street
Heating Plant
Wisconsin
^epower to
burn 100%
biomass
12/31/2012
Sierra Club suit was based on NSR.
http://wisconsin.sierraclub.org/PDF/press/112607
PR WIStateOwnedCoalSettlement.pdf
Tucson Electric Power
Springerville
Plant
Arizona
Arizona
Arizona
Arizona
Unit 1
Unit 2
Unit 3
Unit 4
Dry FGD,
85%
reduction
required
0.27lbs/mmBtu
Four-unit cap of
10, 662 tons per
year once units 3
and 4 are
operational
12/31/2006
SCR, LNB
0.22lbs/mmBtu
Four-unit cap of
8,940 tons per
year once units
3 and 4 are
operational
12/31/2006
Baghouse
0.03 Ibs/mmBtu
1/1/2006
Lawsuit filed by Grand Canyon Trust. Consent
decree is not published. For the compliance
details, see the EPA's own copy of the plant's
permit revisions:
http://xrl.us/springerville and
http://xrl.us/springerville2
Kansas City Board of Public Utilities
Quindaro
Nearman
Kansas
Kansas
Kansas
Units 1
Units 2
Unit 1
Cease burning
coal/Convert to
natural gas
04/16/15
Install and
continuously
operate a
bag house
0.01 Ibs/mmBtu
09/01/17
httD://www.bDu.com/AboutBPU/MediaNewsRelea
ses/BPUUnifiedGovernmentSettleThreatenedLaw
suit.aspx
httD://www.Dlatts.com/RSSFeedDetailedNews/RS
S Feed/Electric Power/21 1 93551
"end coal-fired operations at two coal units
:otaling 1 67 MW at its Quindaro station by April
2015 and to install a baghouse at its 232-MW
Nearman-1 coal unit by September 2017."
"BPU spokesman David Mehlhaff said the muni
Dlans to convert the Quindaro-1 and -2 coal units
:o only natural gas firing, probably by April 201 5;
both units currently have dual-fuel capabilities."
3-70
-------
Company and
Plant
State
Unit
Citizen Suits Provided by DOJ
Retire/Repower
Action
Effective
Date
SOz control
J Percent Remova
or Rate
Effective
Date
NOX Control
Equipment) Rate
Effective
Date
PM Control
Equipment
Rate
Effective
Date
Mercury Control
Equipment|Rate
Effective
Date
Notes
MidAmerican Energy Company
Walter Scott, Jr
Energy Center
George Neal
Energy Center
Riverside
Energy Center
Iowa
Iowa
Iowa
Iowa
Iowa
Iowa
Iowa
Units 1
Units 2
Units 1
Units 2
Units 7
Units 8
Units 9
Cease burning
coal/Convert to
natural gas
04/16/16
httD://www.sec.aov/Archives/edaar/data/928576/0
0009285761300001 4/llcm ec33113form10-a.htm
"MidAmerican Energy has committed to cease
Durning solid fuel, such as coal, at its Walter
Scott, Jr. Energy Center Units 1
and 2, George Neal Energy Center Units 1 and 2
and Riverside Energy Center by April 16,
2016. ..The George Neal Energy Center Unit 1
and Riverside Energy Center currently have the
capability to burn natural gas in the production of
electricity, although under current operating and
economic conditions, production utilizing natural
gas would be very limited"
Dominion Energy
Salem Harbor
Massachusetts
4
Retire
12/31/2011
for units
1&2
6/1/2014
for units
3&4
http://www.clf.ora/wp-
content/u D! oad s/20 1 2/02/Si an ed-Con sent-
Decree-12 11.pdf
Duke Energy
Wabash River
Wabash River
Indiana
Indiana
Unit 2-
5
Unite
Retire
Coal to Gas
Conversion
2014
6/12018
http://www.duke-enerav.com/about-us/retired-
coal-units-potential-retirements.asp
3-71
-------
Table 3-17 Renewable Portfolio Standards in EPA Base Case v.5.13
Regional Renewable Portfolio Standards- AEO 2013
NEMS Region
ERGOT (1)
MORE (3)
MROW (4)
NEWE (5)
NYCW (6), NYLI (7),
NYUP(8)
RFCE (9)
RFCM(10)
RFCW(11)
SRDA(12)
SRGW(13)
SRCE(15)
SRVC(16)
SPNO(17)
SPSO(18)
AZNM(19)
CAMX (20)
NWPP(21)
RMPA (22)
IPM Regions Covered
ERC_REST, ERC_FRNT, ERC_GWAY, ERC_WEST
MIS_WUMS (42%)
MAP WAUE, MIS IA, MIS MIDA, MIS MNWI, MIS MAPP,
SPP_NEBR
NENG_CT, NENGREST, NENG_ME
NY_Z_J, NY_Z_K, NY_Z_C&E, NY_Z_F, NY_Z_G-I, NY_Z_A&B
PJM_EMAC, PJM_PENE, PJM_SMAC, PJM_WMAC
MIS_LMI
MIS INKY (90%), MIS WUMS (58%), PJM West, PJM AP,
PJM ATSI, PJM COMD
S D AMSO, S D N AR, S D REST, S D WOTA, SPP WEST
(10%)
MISJL, MIS_MO, SPP_N (3%)
S_C_KY, S_C_TVA, MIS_INKY(10%)
PJM_Dom, S_VACA
SPP_N (97%)
SPP_SE, SPP_SPS, SPP_WEST (90%), SPP_KIAM
WECC_AZ, WECC_IID, WECC_NM, WECC_SNV
WEC_LADW, WEC_CALN, WEC_SDGE, WECC_SF, WECC_SCE
WECC ID, WECC MT, WECC NNV, WECC PNW, WECC UT,
WECC_WY (58%)
WECC_CO, WECC_WY (42%)
Units
%
%
%
%
%
%
%
%
%
%
%
%
%
%
%
%
%
%
2016 2018 2020 2025 2050
4.5% 4.5% 4.4% 4.4% 4.4%
10.1% 10.0% 10.0% 9.9% 10.0%
8.9% 9.6% 10.3% 11.3% 11.4%
11.6% 13.0% 14.3% 14.5% 14.6%
25.0% 24.8% 24.6% 24.5% 24.6%
9.7% 11.6% 13.6% 14.7% 14.8%
10.1% 10.1% 10.0% 9.9% 10.0%
5.0% 6.0% 7.1% 9.2% 9.3%
0.7% 0.6% 0.6% 0.6% 0.6%
7.3% 10.2% 11.2% 15.7% 15.8%
0.0% 0.0% 0.0% 0.1% 0.1%
3.3% 4.2% 5.0% 5.5% 5.5%
8.5% 9.7% 11.9% 13.1% 13.2%
1.8% 1.9% 2.1% 2.2% 2.2%
7.4% 8.0% 9.4% 11.1% 11.1%
25.6% 29.3% 33.0% 32.9% 33.0%
7.2% 7.2% 10.1% 10.9% 11.0%
10.6% 13.1% 15.5% 15.3% 15.5%
Regional RPS Solar Carve-outs
NEMS Region
ERGOT (1)
MORE (3)
MROW (4)
NEWE (5)
NYCW (6), NYLI (7),
NYUP(8)
IPM Regions Covered
ERC_REST, ERC_FRNT, ERC_GWAY, ERC_WEST
MIS_WUMS (42%)
MAP WAUE, MIS IA, MIS MIDA, MIS MNWI, MIS MAPP,
SPP_NEBR
NENG_CT, NENGREST, NENG_ME
NY_Z_J, NY_Z_K, NY_Z_C&E, NY_Z_F, NY_Z_G-I, NY_Z_A&B
Units
%
%
%
%
%
2016 2018 2020 2025 2P}?'
&U5U
-
.
0.01% 0.01% 0.58% 0.58% 0.59%
0.08% 0.08% 0.08% 0.08% 0.08%
0.00% 0.00% 0.00% 0.00% 0.00%
3-72
-------
Regional Renewable Portfolio Standards- AEO 2013
NEMS Region
RFCE (9)
RFCM(10)
RFCW(11)
SRDA(12)
SRGW(13)
SRCE(15)
SRVC(16)
SPNO(17)
SPSO(18)
AZNM(19)
CAMX (20)
NWPP(21)
RMPA (22)
IPM Regions Covered
PJM_EMAC, PJM_PENE, PJM_SMAC, PJM_WMAC
MIS_LMI
MIS INKY (90%), MIS WUMS (58%), PJM West, PJM AP,
PJM ATSI, PJM COMD
S D AMSO, S D N AR, S D REST, S D WOTA, SPP WEST
(10%)
MISJL, MIS_MO, SPP_N (3%)
S_C_KY, S_C_TVA, MIS_INKY(10%)
PJM_Dom, S_VACA
SPP_N (97%)
SPP_SE, SPP_SPS, SPP_WEST (90%), SPP_KIAM
WECC_AZ, WECC_IID, WECC_NM, WECC_SNV
WEC_LADW, WEC_CALN, WEC_SDGE, WECC_SF, WECC_SCE
WECC ID, WECC MT, WECC NNV, WECC PNW, WECC UT,
WECC_WY (58%)
WECC_CO, WECC_WY (42%)
Units
%
%
%
%
%
%
%
%
%
%
%
%
%
9mn
2016 2018 2020 2025 2050
0.30% 0.49% 0.67% 0.71% 0.71%
-
0.18% 0.25% 0.32% 0.43% 0.45%
-
0.29% 0.39% 0.46% 0.68% 0.72%
0.001% 0.001% 0.001% 0.001% 0.001%
0.06% 0.09% 0.09% 0.09% 0.09%
0.03% 0.05% 0.05% 0.08% 0.08%
0.10% 0.10% 0.14% 0.14% 0.14%
0.48% 0.47% 0.58% 0.60% 0.61%
.
0.05% 0.05% 0.06% 0.06% 0.06%
0.01% 0.01% 0.02% 0.02% 0.02%
3-73
-------
Table 3-18 Complete Availability Assumptions in EPA Base Case v.5.13
This is a small excerpt of the data in Table 3-18. The complete data set in spreadsheet format can be
downloaded via the link found at www.epa.qov/airmarkets/proqsreqs/epa-ipm/BaseCasev513.html.
Please see Table 3-19 for summary data
Unit ID
55522_G_CT1
55522_G_CT10
55522_G_CT2
55522_G_CT3
55522_G_CT4
55522_G_CT5
55522_G_CT6
55522_G_CT7
55522_G_CT8
55522_G_CT9
55257_G_1
55257_G_2
55257_G_3
55257_G_4
55257_G_5
55257_G_6
55257_G_7
82755_C_1
6088_G_5
118_G_GE1
124_G_GT2
82757_C_1
2468_G_6
82759_C_1
54814_G_GENA
Plant Name
Sundance
Sundance
Sundance
Sundance
Sundance
Sundance
Sundance
Sundance
Sundance
Sundance
Ina Road Water Pollution
Control Fac
Ina Road Water Pollution
Control Fac
Ina Road Water Pollution
Control Fac
Ina Road Water Pollution
Control Fac
Ina Road Water Pollution
Control Fac
Ina Road Water Pollution
Control Fac
Ina Road Water Pollution
Control Fac
AZNM_AZ_Combustion Turbine
North Loop
Saguaro
Demoss Petrie
AZNM_CA_Combustion Turbine
Raton
AZNM_NM_Combustion
Turbine
Milagro Cogeneration Plant
Plant Type
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Combustion
Turbine
Winter
Availability
89.2
89.2
89.2
89.2
89.2
89.2
89.2
89.2
89.2
89.2
88.4
88.4
88.4
88.4
88.4
88.4
88.4
89.8
89.2
89.8
89.8
89.8
88.4
89.8
89.2
Summer
Availability
90.8
90.8
90.8
90.8
90.8
90.8
90.8
90.8
90.8
90.8
90.4
90.4
90.4
90.4
90.4
90.4
90.4
92.2
90.8
92.2
92.2
92.2
90.4
92.2
90.8
Annual
Availability
89.9
89.9
89.9
89.9
89.9
89.9
89.9
89.9
89.9
89.9
89.2
89.2
89.2
89.2
89.2
89.2
89.2
90.8
89.9
90.8
90.8
90.8
89.2
90.8
89.9
3-74
-------
Table 3-19 BART Regulations included in EPA Base Case v.5.13
BART Affected Plants
Colstrip
Colstrip
Comanche
Comanche
Craig
Craig
Four Corners
Four Corners
Four Corners
Four Corners
Four Corners
Gerald Gentleman
Gerald Gentleman
Hayden
Hayden
J E Corette Plant
Martin Drake
Martin Drake
Martin Drake
Nebraska City
Reid Gardner
Reid Gardner
Reid Gardner
San Juan
San Juan
San Juan
San Juan
Tecumseh Energy Center
Apache Station
Apache Station
Cherokee
Cholla
Cholla
Cholla
Coal Creek
Coal Creek
Coronado
Coronado
Jeffrey Energy Center
Jeffrey Energy Center
UniquelD
6076_B_1
6076_B_2
470_B_1
470_B_2
6021_B_C1
6021_B_C2
2442_B_1
2442_B_2
2442_B_3
2442_B_4
2442_B_5
6077_B_1
6077_B_2
525_B_H1
525_B_H2
2187_B_2
492_B_5
492_B_6
492_B_7
6096_B_1
2324_B_1
2324_B_2
2324_B_3
2451_B_1
2451_B_2
2451_B_3
2451_B_4
1252_B_10
160_B_2
160_B_3
469_B_4
113_B_2
113_B_3
113_B_4
6030_B_1
6030_B_2
6177_B_U1B
6177_B_U2B
6068_B_1
6068_B_2
BART Status/ CAIR/
Shutdown/ Coal-to-Gas
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
NOX BART Limit
0.15lb/MMBtu
0.15lb/MMBtu
0.20 Ib/MMBtu
0.20 Ib/MMBtu
0.27 Ib/MMBtu
0.08 Ib/MMBtu
0.05 Ib/MMBtu
0.05 Ib/MMBtu
0.05 Ib/MMBtu
0.05 Ib/MMBtu
0.05 Ib/MMBtu
0.23 Ib/MMBtu
0.23 Ib/MMBtu
0.08 Ib/MMBtu
0.07 Ib/MMBtu
0.35 Ib/MMBtu
0.31 Ib/MMBtu
0.32 Ib/MMBtu
0.32 Ib/MMBtu
0.23 Ib/MMBtu
0.20 Ib/MMBtu
0.20 Ib/MMBtu
0.20 Ib/MMBtu
0.11 Ib/MMBtu
0.11 Ib/MMBtu
0.11 Ib/MMBtu
0.11 Ib/MMBtu
0.18 Ib/MMBtu
0.07 Ib/MMBtu
across 2 units
0.07 Ib/MMBtu
across 2 units
0.12 Ib/MMBtu
0.055 Ib/MMBtu
across 3 units
0.055 Ib/MMBtu
across 3 units
0.055 Ib/MMBtu
across 3 units
0.13 Ib/MMBtu
(combined both
units)
0.13 Ib/MMBtu
(combined both
units)
0.065 Ib/MMBtu
across 2 units
0.065 Ib/MMBtu
across 2 units
0.15 Ib/MMBtu
0.15 Ib/MMBtu
SO2 BART
Limit
Acutal
emissions
Acutal
emissions
Acutal
emissions
Acutal
emissions
Acutal
emissions
TBD
TBD
Acutal
emissions
Acutal
emissions
Acutal
emissions
Acutal
emissions
0.15
Ib/MMBtu
0.15
Ib/MMBtu
7.81 tpy(12
month rolling)
0.15
Ib/MMBtu
0.15
Ib/MMBtu
0.15
Ib/MMBtu
0.15
Ib/MMBtu or
95%
efficiency
0.15
Ib/MMBtu or
95%
efficiency
0.08
Ib/MMBtu
0.08
Ib/MMBtu
0.15
Ib/MMBtu
0.15
Ib/MMBtu
NOX
Compliance
Date
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
12/1/17
12/1/17
2018
12/1/17
12/1/17
12/1/17
2018
2018
12/1/17
12/1/17
2018
2018
S02
Compliance
Date
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
12/1/16
12/1/16
2018
12/5/13
12/5/13
12/5/13
2018
2018
6/5/13
6/5/13
2018
2018
3-75
-------
BART Affected Plants
La Cygne
La Cygne
Leland Olds
Leland Olds
Merrimack
Milton R Young
Milton R Young
Muskogee
Muskogee
Pawnee
Ray D Nixon
Sooner
Sooner
Stanton
Lansing Smith
Lansing Smith
Northeastern
Boardman
Northeastern
Seminole
Seminole
Northside Generating Station
Northside Generating Station
Northside Generating Station
Deerhaven Generating Station
Merrimack
Yates
Yates
George Neal North
George Neal North
George Neal North
Walter Scott Jr. Energy Center
A B Brown
Ames Electric Services Power Plant
UniquelD
1241_B_1
1241_B_2
2817_B_1
2817_B_2
2364_B_2
2823_B_B1
2823_B_B2
2952_B_4
2952_B_5
6248_B_1
8219_B_1
6095_B_1
6095_B_2
2824_B_1
643_B_1
643_B_2
2963_B_3313
6106_B_1SG
2963_B_3314
136_B_1
136_B_2
667_B_1
667_B_2
667_B_3
663_B_B2
2364_B_2
728_B_Y6BR
728_B_Y7BR
1091_B_1
1091_B_2
1091_B_3
1082_B_3
6137_B_1
1122_B_7
BART Status/ CAIR/
Shutdown/ Coal-to-Gas
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2
BART NOX & BART SO2;
Shutdown by 2016
BART NOX & BART SO2;
Shutdown by 2020
BART NOX & BART SO2;
Shutdown by 2024
BART SO2
BART SO2
BART SO2
BART SO2
BART SO2
BART SO2
BART SO2
Coal-to-Gas by 2016
Coal-to-Gas by 2016
Coal-to-Gas by 4/16/2016
Coal-to-Gas by 4/16/2016
Coal-to-Gas by 4/16/2016
Coal-to-Gas by 4/16/2016
CAIR
CAIR
NOX BART Limit
0.13lb/MMBtu
(combined both
units)
0.13lb/MMBtu
(combined both
units)
0.19lb/MMBtu
0.35 Ib/MMBtu
0.30 Ib/MMBtu
0.36 Ib/MMBtu
0.35 Ib/MMBtu
0.15 Ib/MMBtu
0.15 Ib/MMBtu
0.07 Ib/MMBtu
0.21 Ib/MMBtu
0.15 Ib/MMBtu
0.15 Ib/MMBtu
0.29 Ib/MMBtu
4700 tpy across 2
units
4700 tpy across 2
units
0.23 Ib/MMBtu
0.7 Ib/MMBtu
0.15 Ib/MMBtu
SO2 BART
Limit
0.15
Ib/MMBtu
0.15
Ib/MMBtu
0.15
Ib/MMBtu or
95%
efficiency
0.15
Ib/MMBtu or
95%
efficiency
90 % control
0.15
Ib/MMBtu or
95%
efficiency
0.15
Ib/MMBtu or
95%
efficiency
0.06
Ibs/MMBtu
0.06
Ibs/MMBtu
0.12
Ib/MMBtu
0.11
Ib/MMBtu
0.06
Ibs/MMBtu
0.06
Ibs/MMBtu
0.24
Ib/MMBtu
0.74
Ib/MMBtu
0.74
Ib/MMBtu
0.60
Ib/MMBtu
1.2 Ib/MMBtu
0.40
Ib/MMBtu
0.25
Ib/MMBtu
0.25
Ib/MMBtu
3600 tpy
across 3 units
3600 tpy
across 3 units
3600 tpy
across 3 units
5500 tpy
Actual
Emissions
[with FGD]
NOX
Compliance
Date
6/1/15
6/1/15
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
S02
Compliance
Date
6/1/15
6/1/15
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
2018
3-76
-------
BART Affected Plants
Asbury
Bailly
Bailly
Barry
Barry
Belle River
Belle River
Big Brown
Big Brown
Big Cajun 2
Big Stone
Blue Valley
Bowen
Bowen
Bowen
Bowen
Bridgeport Station
Bruce Mansfield
Bruce Mansfield
Bruce Mansfield
Bull Run
Burlington
Capitol Heat and Power
Capitol Heat and Power
Cardinal
Cardinal
Cardinal
Cayuga
Cayuga
Charles R Lowman
Charles R Lowman
Charles R Lowman
Chesterfield
Chesterfield
Cheswick
Colbert
Coleto Creek
Columbia
Columbia
Conemaugh
Conemaugh
Conesville
Conesville
Conesville
Cooper
Cooper
Crawfordsville
Cumberland
Cumberland
Dean H Mitchell
Dolphus M Grainger
Dolphus M Grainger
Dover
E C Gaston
UniquelD
2076_B_1
995_B_7
995_B_8
3_B_4
3_B_5
6034_B_1
6034_B_2
3497_B_1
3497_B_2
6055_B_2B1
6098_B_1
2132_B_3
703_B_1BLR
703_B_2BLR
703_B_3BLR
703_B_4BLR
568_B_BHB3
6094_B_1
6094_B_2
6094_B_3
3396_B_1
1104_B_1
54406_G_1
54406_G_2
2828_B_1
2828_B_2
2828_B_3
1001_B_1
1001_B_2
56_B_1
56_B_2
56_B_3
3797_B_5
3797_B_6
8226_B_1
47_B_5
6178_B_1
8023_B_1
8023_B_2
3118_B_1
3118_B_2
2840_B_4
2840_B_5
2840_B_6
1384_B_1
1384_B_2
1024_B_6
3399_B_1
3399_B_2
996_B_1 1
3317_B_1
3317_B_2
2914_B_4
26_B_4
BART Status/ CAIR/
Shutdown/ Coal-to-Gas
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
NOX BART Limit
SO2 BART
Limit
NOX
Compliance
Date
S02
Compliance
Date
3-77
-------
BART Affected Plants
E C Gaston
E W Brown
E W Brown
East Bend
Eckert Station
Eckert Station
Eckert Station
Elmer Smith
Elmer Smith
Erickson Station
F B Culley
F B Culley
Fair Station
Fayette Power Project
Fayette Power Project
Fort Martin Power Station
Fort Martin Power Station
General James M Gavin
General James M Gavin
Genoa
George Neal South
Ghent
Ghent
Ghent
Gibson
Gibson
Gibson
Gibson
Gorgas
Greene County
Greene County
H L Spurlock
H L Spurlock
Hamilton
Hamilton
Hammond
Harding Street
Harrington
Harrington
Harrington
Harrison Power Station
Harrison Power Station
Harrison Power Station
Hatfields Ferry Power Station
Hatfields Ferry Power Station
Hatfields Ferry Power Station
Henderson
HMP&L Station Two Henderson
Homer City Station
Homer City Station
Homer City Station
latan
J H Campbell
J H Campbell
UniquelD
26_B_5
1355_B_2
1355_B_3
6018_B_2
1831_B_4
1831_B_5
1831_B_6
1374_B_1
1374_B_2
1832_B_1
1012_B_2
1012_B_3
1218_B_2
6179_B_1
6179_B_2
3943_B_1
3943_B_2
8102_B_1
8102_B_2
4143_B_1
7343_B_4
1356_B_1
1356_B_2
1356_B_3
6113_B_1
6113_B_2
6113_B_3
6113_B_4
8_B_10
10_B_1
10_B_2
6041_B_1
6041_B_2
2917_B_8
2917_B_9
708_B_4
990_B_70
6193_B_061B
6193_B_062B
6193_B_063B
3944_B_1
3944_B_2
3944_B_3
3179_B_1
3179_B_2
3179_B_3
2062_B_H3
1382_B_H2
3122_B_1
3122_B_2
3122_B_3
6065_B_1
1710_B_1
1710_B_2
BART Status/ CAIR/
Shutdown/ Coal-to-Gas
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
NOX BART Limit
SO2 BART
Limit
NOX
Compliance
Date
S02
Compliance
Date
3-78
-------
BART Affected Plants
J H Campbell
J M Stuart
J M Stuart
J M Stuart
J M Stuart
Jack McDonough
Jack McDonough
Jack Watson
Jack Watson
James De Young
James De Young
James H Miller Jr
James H Miller Jr
James River Power Station
James River Power Station
Jasper 2
John E Amos
John E Amos
John E Amos
John P Madgett
Kenneth C Coleman
Kenneth C Coleman
Kenneth C Coleman
Keystone
Keystone
Labadie
Labadie
Labadie
Labadie
Lake Road
Lake Road
Lake Shore
Lansing
Logansport
Manitowoc
Marshall
Martin Lake
Martin Lake
Martin Lake
Mclntosh
Merom
Merom
Miami Fort
Miami Fort
Michigan City
Mill Creek
Mill Creek
Mill Creek
Mill Creek
Milton L Kapp
Mitchell
Mitchell
Mitchell Power Station
Monroe
UniquelD
1710_B_3
2850_B_1
2850_B_2
2850_B_3
2850_B_4
710_B_MB1
710_B_MB2
2049_B_4
2049_B_5
1830_B_4
1830_B_5
6002_B_2
6002_B_1
2161_B_4
2161_B_5
6225_B_1
3935_B_1
3935_B_2
3935_B_3
4271_B_B1
1381_B_C1
1381_B_C2
1381_B_C3
3136_B_1
3136_B_2
2103_B_1
2103_B_2
2103_B_3
2103_B_4
2098_B_6
2908_G_1 1
2838_B_18
1047_B_4
1032_B_6
4125_B_7
2144_B_5
6146_B_1
6146_B_2
6146_B_3
6124_B_1
6213_B_1SG1
6213_B_2SG1
2832_B_7
2832_B_8
997_B_12
1364_B_1
1364_B_2
1364_B_3
1364_B_4
1048_B_2
3948_B_1
3948_B_2
3181_B_33
1733_B_1
BART Status/ CAIR/
Shutdown/ Coal-to-Gas
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
NOX BART Limit
SO2 BART
Limit
NOX
Compliance
Date
S02
Compliance
Date
3-79
-------
BART Affected Plants
Monroe
Monroe
Monroe
Monticello
Monticello
Monticello
Montrose
Mountaineer
Mt Storm
Mt Storm
Mt Storm
Muscatine Plant #1
Muskingum River
New Madrid
New Madrid
Orrville
Ottumwa
Paradise
Paradise
Paradise
Petersburg
Petersburg
Petersburg
Pleasant Prairie
Pleasants Power Station
Pleasants Power Station
PPL Brunner Island
PPL Brunner Island
PPL Montour
PPL Montour
Prairie Creek
Presque Isle
Presque Isle
Presque Isle
Presque Isle
Presque Isle
Pulliam
R D Green
R D Green
R D Morrow
R D Morrow
R M Schahfer
R M Schahfer
R S Nelson
Robert A Reid
Rodemacher
Rush Island
Rush Island
Sandow
Scherer
Scherer
Shelby Municipal Light Plant
Shelby Municipal Light Plant
Shiras
UniquelD
1733_B_2
1733_B_3
1733_B_4
6147_B_1
6147_B_2
6147_B_3
2080_B_3
6264_B_1
3954_B_1
3954_B_2
3954_B_3
1167_B_8
2872_B_5
2167_B_1
2167_B_2
2935_B_13
6254_B_1
1378_B_1
1378_B_2
1378_B_3
994_B_1
994_B_2
994_B_3
6170_B_1
6004_B_1
6004_B_2
3140_B_2
3140_B_3
3149_B_1
3149_B_2
1073_B_4
1769_B_5
1769_B_6
1769_B_7
1769_B_8
1769_B_9
4072_B_8
6639_B_G1
6639_B_G2
6061_B_1
6061_B_2
6085_B_14
6085_B_15
1393_B_6
1383_B_R1
6190_B_2
6155_B_1
6155_B_2
6648_B_4
6257_B_1
6257_B_2
2943_B_1
2943_B_2
1843_B_2
BART Status/ CAIR/
Shutdown/ Coal-to-Gas
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
NOX BART Limit
SO2 BART
Limit
NOX
Compliance
Date
S02
Compliance
Date
3-80
-------
BART Affected Plants
Sibley
Sibley
Sikeston Power Station
Sioux
Sioux
South Oak Creek
South Oak Creek
Southwest Power Station
St Clair
St Marys
Streeter Station
Streeter Station
Tanners Creek
Thomas Hill
Thomas Hill
Trenton Channel
Valley
Valley
Valley
Valley
Victor J Daniel Jr
Victor J Daniel Jr
W A Parish
W A Parish
W A Parish
WH Sammis
WH Sammis
WH Sammis
WH Sammis
Wabash River
Wansley
Wansley
Warrick
Warrick
Warrick
Wateree
Wateree
Welsh
Weston
Whitewater Valley
Widows Creek
Williams
Winyah
Winyah
Asheville
Asheville
Belews Creek
Belews Creek
Cliffside
Marshall
Marshall
Marshall
Marshall
Roxboro
UniquelD
2094_B_2
2094_B_3
6768_B_1
2107_B_1
2107_B_2
4041_B_7
4041_B_8
6195_B_1
1743_B_7
2942_B_6
1131_B_6
1131_B_7
988_B_U4
2168_B_MB1
2168_B_MB2
1745_B_9A
4042_B_1
4042_B_2
4042_B_3
4042_B_4
6073_B_1
6073_B_2
3470_B_WAP5
3470_B_WAP6
3470_B_WAP7
2866_B_4
2866_B_5
2866_B_6
2866_B_7
1010_B_6
6052_B_1
6052_B_2
6705_B_2
6705_B_3
6705_B_4
3297_B_WAT1
3297_B_WAT2
6139_B_1
4078_B_3
1040_B_2
50_B_8
3298_B_WIL1
6249_B_1
6249_B_2
2706_B_1
2706_B_2
8042_B_1
8042_B_2
2721_B_5
2727_B_1
2727_B_2
2727_B_3
2727_B_4
2712_B_1
BART Status/ CAIR/
Shutdown/ Coal-to-Gas
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR
CAIR/State EGU Rule
CAIR/State EGU Rule
CAIR/State EGU Rule
CAIR/State EGU Rule
CAIR/State EGU Rule
CAIR/State EGU Rule
CAIR/State EGU Rule
CAIR/State EGU Rule
CAIR/State EGU Rule
CAIR/State EGU Rule
NOX BART Limit
SO2 BART
Limit
NOX
Compliance
Date
S02
Compliance
Date
3-81
-------
BART Affected Plants
Roxboro
Roxboro
Roxboro
Roxboro
Roxboro
Lee
L V Sutton
Portland
Harllee Branch
Canadys Steam
Canadys Steam
Canadys Steam
Harllee Branch
Chesapeake
Welsh
Conesville
HMP&L Station Two Henderson
Menasha
Pella
Pella
Jefferies
Jefferies
Big Sandy
Frank E Ratts
Frank E Ratts
Harbor Beach
Nelson Dewey
Cane Run
Cane Run
Cane Run
Harllee Branch
Harllee Branch
Kraft
J T Deely
J T Deely
State Line
Avon Lake
Walter C Beckjord
Walter C Beckjord
New Castle
Big Sandy
Bay Shore
Bay Shore
Eastlake
Edgewater
Dave Johnston
Dave Johnston
Jim Bridger
Jim Bridger
Jim Bridger
UniquelD
2712_B_2
2712_B_3A
2712_B_3B
2712_B_4A
2712_B_4B
2709 B 3
2713_B_3
3113_B_2
709_B_2
3280_B_CAN1
3280_B_CAN2
3280_B_CAN3
709_B_1
3803_B_4
6139_B_2
2840_B_3
1382_B_H1
4127_B_B24
1175_B_6
1175_B_7
3319_B_3
3319_B_4
1353_B_BSU2
1043_B_1SG1
1043_B_2SG1
1731_B_1
4054_B_2
1363_B_4
1363_B_5
1363_B_6
709_B_3
709_B_4
733_B_3
6181_B_1
6181_B_2
981_B_4
2836_B_12
2830_B_5
2830_B_6
3138_B_5
1353_B_BSU1
2878_B_3
2878_B_4
2837_B_5
4050_B_4
4158_B_BW43
4158_B_BW44
8066_B_BW71
8066_B_BW72
8066_B_BW73
BART Status/ CAIR/
Shutdown/ Coal-to-Gas
CAIR/State EGU Rule
CAIR/State EGU Rule
CAIR/State EGU Rule
CAIR/State EGU Rule
CAIR/State EGU Rule
CAIR/State EGU Rule;
Shutdown by 2013
CAIR/State EGU Rule;
Shutdown by 2017
CAIR; Shutdown by 1/7/2015
CAIR; Shutdown by 10/1/13
CAIR; Shutdown by
12/1/2017
CAIR; Shutdown by
12/1/2017
CAIR; Shutdown by
12/1/2017
CAIR; Shutdown by 12/31/13
CAIR; Shutdown by 12/31/14
CAIR; Shutdown by 12/31/14
CAIR; Shutdown by
12/31/2012
CAIR; Shutdown by 2008
CAIR; Shutdown by 2009
CAIR; Shutdown by 2012
CAIR; Shutdown by 2012
CAIR; Shutdown by 2013
CAIR; Shutdown by 2013
CAIR; Shutdown by 2015
CAIR; Shutdown by 2015
CAIR; Shutdown by 2015
CAIR; Shutdown by 2015
CAIR; Shutdown by 2015
CAIR; Shutdown by 2016
CAIR; Shutdown by 2016
CAIR; Shutdown by 2016
CAIR; Shutdown by 2016
CAIR; Shutdown by 2016
CAIR; Shutdown by 2016
CAIR; Shutdown by 2018
CAIR; Shutdown by 2018
CAIR; Shutdown by 3/25/12
CAIR; Shutdown by 4/1/2015
CAIR; Shutdown by 4/1/2015
CAIR; Shutdown by 4/1/2015
CAIR; Shutdown by
4/16/2015
CAIR; Shutdown by 6/1/2015
CAIR; Shutdown by 9/1/2012
CAIR; Shutdown by 9/1/2012
CAIR; Shutdown by 9/1/2012
CAIR; Shutdown or Coal-to-
Gas by 12/31/2018
Proposal 5/23/1 3
Proposal 5/23/1 3
Proposal 5/23/1 3
Proposal 5/23/1 3
Proposal 5/23/1 3
NOX BART Limit
SO2 BART
Limit
NOX
Compliance
Date
S02
Compliance
Date
3-82
-------
BART Affected Plants
Jim Bridger
Laramie River Station
Laramie River Station
Naughton
Naughton
Naughton
Neil Simpson
Wyodak
Navajo
Navajo
Navajo
Indian River Generating Station
Cherokee
Valmont
Crystal River
Crystal River
Transalta Centralia Generation
Transalta Centralia Generation
Brayton Point
Brayton Point
Brayton Point
Baldwin Energy Complex
Baldwin Energy Complex
Baldwin Energy Complex
C P Crane
Chalk Point LLC
Chalk Point LLC
Coffeen
Coffeen
Dallman
Dallman
Dallman
Dickerson
Duck Creek
E D Edwards
E D Edwards
Edge Moor
Havana
Herbert A Wagner
Indian River Generating Station
Joliet 29
Joliet 29
Joliet 29
Joliet 29
Kincaid Generation LLC
Kincaid Generation LLC
Marion
Marion
Morgantown Generating Plant
Morgantown Generating Plant
Newton
Newton
Pearl Station
Powerton
UniquelD
8066_B_BW74
6204_B_1
6204_B_2
4162_B_1
4162_B_2
4162_B_3
4150_B_5
6101_B_BW91
4941_B_1
4941_B_2
4941_B_3
594_B_3
469_B_3
477_B_5
628_B_1
628_B_2
3845_B_BW21
3845_B_BW22
1619_B_1
1619_B_2
1619_B_3
889_B_1
889_B_2
889_B_3
1552_B_2
1571_B_1
1571_B_2
861_B_01
861_B_02
963_B_31
963_B_32
963_B_33
1572_B_3
6016_B_1
856_B_2
856_B_3
593_B_4
891_B_9
1554_B_3
594_B_4
384_B_71
384_B_72
384_B_81
384_B_82
876_B_1
876_B_2
976_B_4
976_B_123
1573_B_1
1573_B_2
6017_B_1
6017_B_2
6238_B_1A
879_B_51
BART Status/ CAIR/
Shutdown/ Coal-to-Gas
Proposal 5/23/1 3
Proposal 5/23/1 3
Proposal 5/23/1 3
Proposal 5/23/1 3
Proposal 5/23/1 3
Proposal 5/23/1 3
Proposal 5/23/1 3
Proposal 5/23/1 3
Proposed
Proposed
Proposed
Shutdown by 12/31/13; State
ECU Rule
Shutdown by 12/31/16
Shutdown by 12/31/17
Shutdown by 2020
Shutdown by 2020
Shutdown by 2020
Shutdown by 2025
State Alternative Program
State Alternative Program
State Alternative Program
State ECU Rule
State ECU Rule
State ECU Rule
State ECU Rule
State ECU Rule
State ECU Rule
State ECU Rule
State ECU Rule
State ECU Rule
State ECU Rule
State ECU Rule
State ECU Rule
State EGU Rule
State EGU Rule
State EGU Rule
State EGU Rule
State EGU Rule
State EGU Rule
State EGU Rule
State EGU Rule
State EGU Rule
State EGU Rule
State EGU Rule
State EGU Rule
State EGU Rule
State EGU Rule
State EGU Rule
State EGU Rule
State EGU Rule
State EGU Rule
State EGU Rule
State EGU Rule
State EGU Rule
NOX BART Limit
SO2 BART
Limit
NOX
Compliance
Date
S02
Compliance
Date
3-83
-------
BART Affected Plants
Powerton
Powerton
Powerton
PSEG Hudson Generating Station
Waukegan
Will County
Wood River
Austin Northeast
Clay Boswell
Clay Boswell
H Wilson Sundt GS
Nibbing
Nibbing
Nibbing
Hoot Lake (Otter Tail)
Sherburne County
Sherburne County
Silver Bay Power
Silver Lake
Silver Lake
Allen S King
Big Bend
Big Bend
Big Bend
Crist
Crist
Crystal River
Crystal River
Deerhaven Generating Station
Lansing Smith
Lansing Smith
Flint Creek
Hunter
Hunter
Huntington
Huntington
White Bluff
White Bluff
UniquelD
879_B_52
879_B_61
879_B_62
2403_B_2
883_B_8
884_B_4
898_B_5
1961_B_NEPP
1893_B_3
1893_B_4
126_B_4
1979_B_1
1979_B_2
1979_B_3
1943_B_3
6090_B_1
6090_B_2
10849_B_BLR2
2008_B_3
2008_B_4
1915_B_1
645_B_BB01
645_B_BB02
645_B_BB03
641_B_6
641_B_7
628_B_4
628_B_5
663_B_B2
643_B_1
643_B_2
6138_B_1
6165_B_1
6165_B_2
8069_B_1
8069_B_2
6009_B_1
6009_B_2
BART Status/ CAIR/
Shutdown/ Coal-to-Gas
State ECU Rule
State ECU Rule
State ECU Rule
State ECU Rule
State EGU Rule
State EGU Rule
State EGU Rule
TBD
TBD
TBD
TBD
TBD
TBD
TBD
TBD
TBD
TBD
TBD
TBD
TBD
TBD
TBD Proposed
TBD Proposed
TBD Proposed
TBD Proposed
TBD Proposed
TBD Proposed
TBD Proposed
TBD Proposed
TBD Proposed
TBD Proposed
TBD State SIP disapproved
TBD State SIP disapproved
TBD State SIP disapproved
TBD State SIP disapproved
TBD State SIP disapproved
TBD State SIP disapproved
TBD State SIP disapproved
NOX BART Limit
SO2 BART
Limit
NOX
Compliance
Date
S02
Compliance
Date
3-84
-------
4. Generating Resources
"Existing", "planned-committed", and "potential" are the three general types of generating units modeled in
EPA Base Case v.5.13. Units that are currently operational in the electric industry are termed as
"existing" units. Units that are not currently operating but are firmly anticipated to be operational in the
future, and have either broken ground (initiated construction) or secured financing are termed "planned-
committed". "Potential" units refer to new generating options used in IPM for capacity expansion
projections of the electric industry. Existing and planned-committed units are entered as exogenous
inputs to the model, whereas potential units are endogenous to the model in the sense that the model
determines the location and size of all the potential units that end up in the final solution for a specific
model run.
This chapter is organized into the following five sections:
(1) Section 4.1 provides background information on the National Electric Energy Data System (NEEDS),
the database which serves as the repository for information on existing and planned-committed units
which are modeled in the EPA Base Case v.5.13,
(2) Section 4.2 provides detailed information on existing non-nuclear generating units modeled in EPA
Base Case v.5.13,
(3) Section 0 provides detailed information pertaining to planned-committed units which are assumed in
EPA Base Case v.5.13,
(4) Section 4.4 provides detailed information pertaining to the EPA Base Case assumptions for potential
plants, and
(5) Section 4.5 describes the handling of existing and potential nuclear units in EPA Base Case v.5.13
4.1 National Electric Energy Data System (NEEDS)
EPA Base Case v.5.13 uses the NEEDS database as its source for data on all existing and planned-
committed units. Table 4-1 below summarizes the resources used in developing data on existing units in
NEEDS v.5.13. The data sources for planned-committed units in NEEDS are discussed below in Section
0. The population of existing units in NEEDS v.5.13 represents generating units that were in operation
through the end of 2010. The population of planned-committed includes any units online or scheduled to
come online from 2011 to the end of 2015 (with five exceptions listed in the note under Table 4-2 below).
4.2 Existing Units
EPA Base Case v.5.13 models existing units based on information contained in NEEDS. The sections
below describe the procedures followed in determining the population of units in NEEDS, as well as each
unit's capacity, location, and configuration. Details are also given on the model plant aggregation scheme
and the cost and performance characteristics associated with the existing non-nuclear units represented
in EPA Base Case v.5.13.
4.2.1 Population of Existing Units
The population of existing units was taken primarily from EIA 860 (2010). A number of rules were used to
screen the various data sources. These rules helped to ensure data consistency, but also made the
population data adaptable for use in EPA Base Case v.5.13. Table 4-2 below summarizes the rules used
in populating the NEEDS v.5.13 database. Excerpt from Table 4-35 lists all units that were not included
in the NEEDS v.5.13 database based on these criteria.
4-1
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Table 4-1 Data Sources for NEEDS v.5.13 for EPA Base Case v.5.13
Data Source3
DOE's Form EIA-860
NERC Electricity Supply
and Demand (ES&D)
database
DOE's Annual Energy
Outlook (AEO)
Ventyx's New Entrants
database
EPA's Emission Tracking
System
Utility and Regional EPA
Office Comments
Data Source Documentation
DOE's Form EIA-860 is an annual survey of utility and non-utility power plants at the
generator level. It contains data such as summer, winter and nameplate capacity,
location (state and county), operating status, prime mover, energy sources and in-
service date of existing and proposed generators. NEEDS v.5. 1 3 uses EIA Form 860
(201 0, 201 1 ) data as one of the primary generator data inputs.
DOE's Form EIA-860 also collects data of steam boilers such as energy sources, boiler
identification, location, operating status and design information; and associated
environmental equipment such as NOX combustion and post-combustion control, FGD
scrubber, mercury control and particulate collector device information. Note that boilers
in plants with less than 10 MW do not report all data elements. The association
between boilers and generators is also provided. Note that boilers and generators are
not necessarily in a one-to-one correspondence. NEEDS v.5.13 uses EIA Form 860
(201 0, 201 1 ) data as one of the primary boiler data inputs.
The NERC ES&D is released annually. It contains generator-level information such as
summer, winter and nameplate capacity, state, NERC region and sub-region, status,
primary fuel and on-line year. NEEDS v.5.13 uses NERC ES&D (2011) data as one of
the data inputs.
The Energy Information Administration (EIA) Annual Energy Outlook presents annually
updated forecasts of energy supply, demand and prices covering a 20-25 year time
horizon. The projections are based on results from ElA's National Energy Modeling
System (NEMS). Information from AEO 2012 such as heat rates, planned committed
units were used in NEEDS v.5.13. Nuclear unit capacities and uprates are from AEO
2013.
Ventyx's New Entrants database has information on new power plant builds, rerates
and retirements. NEEDS v.5.13 uses the dataset downloaded on April 13, 2012 and
April 23, 201 3, as one of the sources of development of committed generating units.
The Emission Tracking System (ETS) database is updated quarterly. It contains boiler-
level information such as primary fuel, heat input, SC>2 and NOX controls, and SO2 and
NOX emissions. NEEDS v.5.13 uses annual and seasonal ETS (2011) data as one of
the primary data inputs for NOX rate development and environmental equipment
assignment.
Comments from utilities and regional EPA offices regarding the population in NEEDS
(retirements, new units) as well as unit characteristics were incorporated in NEEDS
v.5.13.
Note:
a Shown in Table 4-1 are the primary issue dates of the indicated data sources that were used. Other vintages of these data
sources were also used in instances where data were not available for the indicated issued date or where there were
methodological reasons for using other vintages of the data.
Table 4-2 Rules Used in Populating NEEDS v.5.13 for EPA Base Case v.5.13
Scope
Capacity
Status
Planned or
Committed
Units
Rule
Excluded units with reported summer capacity, winter capacity and nameplate capacity of zero or
blank.
Excluded units that were out of service for two or three consecutive years (i.e., generators with
status codes "OS" in the latest three reporting years and boilers with status codes "OS" in the latest
two reporting years) and units that were no longer in service and not expected to be returned to
service (i.e., generators or boilers with status codes of "RE"). Status of boiler(s) and associated
generator(s) were taken into account for determining operation status
Included planned units that had broken ground or secured financing and were expected to be online
by the end of 2015; one geothermal unit and four nuclear units that are scheduled to come online
after 201 5 were also included3
4-2
-------
Scope
Firm/Non-firm
Electric Sales
Rule
Excluded non-utility onsite generators that do not produce electricity for sale to the
basis
Excluded all mobile and distributed generators
grid on a net
Note:
a The geothermal unit is Bonnett, unit ST2; the four nuclear units are Vogtle, units 3&4, and V C Summer, units 2&3
As with previous versions of the database, NEEDS v.5.13 includes steam units at the boiler level and
non-steam units at the generator level (nuclear units are also at the generator level). A unit in NEEDS
v.5.13, therefore, refers to a boiler in the case of a steam unit and a generator in the case of a non-steam
unit. Table 4-3 provides a summary of the population and capacity of the existing units included in
NEEDS v.5.13 through 2010. EIA Form 860 (2010) is the starting point and largest component of the
existing unit population in NEEDS v.5.13 but the final population of existing units is supplemented based
on information from other sources, including comments from utilities, submissions to EPA's Emission
Tracking System, Annual Energy Outlook, and reported capacity in Ventyx's New Entrants database.
EPA removed capacity from the NEEDS inventory based on public announcements of future closures.
Removal of such capacity from the NEEDS inventory pre-empts the model itself from making any
decisions regarding that capacity's future status or configuration; such capacity is simply no longer
available for the model to consider in optimizing electricity supply to meet demand. The list of units
considered for removal from NEEDS is built from several data sources including:
1. Edison Electric Institute (EEI), "Coal Fleet Retirement Announcements", July 29, 2011
2. PJM, "Future Deactivation Requests", "PJM Generator Deactivations", 2012 (updated frequently)
3. EIA, "Retired U.S. Electric Generating Units by Operating Company, Plant and Month, 2012
4. Research by EPA and ICF staff
EPA only removed units from the NEEDS inventory if a high degree of certainty could be assigned to
future implementation of the announced action. The available retirement-related information was
reviewed for each unit individually, and a determination was made regarding the removal of the unit from
NEEDS v.5.13. This assessment is based on the rules below, applied in the following order:
1. All units that are listed as retired in the 2010, 2011, 2012 and February 2013 versions of EIA Electric
Power Monthly are flagged for removal from NEEDS.
2. All units with a status flag of "RE" or with a planned retirement year prior to 2016 in 2011 EIA 860 are
flagged for removal from NEEDS.
3. All units that have been cleared by a regional transmission operator (RTO) or independent system
operator (ISO) to retire before 2016, or whose RTO/ISO clearance to retire is contingent on actions
that can be completed before 2016, are flagged for removal from NEEDS.
4. All units that have committed specifically to retire before 2016 under federal or state enforcement
actions or regulatory requirements are flagged for removal from NEEDS.
5. Finally, if a retirement announcement for a given unit can be corroborated by other available
information then the unit is flagged for removal from NEEDS.
Note that units which are required to retire pursuant to enforcement actions or state rules in 2016 or later
are retained in the NEEDS database. Such 2016-and-later retirements are captured as constraints on
those units in IPM modeling, and the capacity is retired in future year projections per the terms of the
related requirements.
4-3
-------
Table 4-36 lists all units that were removed from EPA's inventory based on announcements that were
reviewed using the rules outlined above.
Table 4-3 Summary Population (through 2010) of Existing Units in NEEDS v.5.13
Plant Type
Biomass
Coal Steam
Combined Cycle
Combustion Turbine
Fossil Waste
Fuel Cell
Geothermal
Hydro
IGCC
Landfill Gas
Municipal Solid Waste
Non-Fossil Waste
Nuclear
O/G Steam
Pumped Storage
Solar PV
Solar Thermal
Tires
Wind
US Total
Number of Units
161
949
1659
5419
58
15
201
3749
6
1315
174
100
99
529
151
151
15
2
665
15,418
Capacity (MW)
3,140
275,568
203,181
135,353
372
3
2,304
77,946
539
1,437
2,142
1,328
98,173
92,909
22,310
390
548
46
39,150
956,837
4.2.2 Capacity
The NEEDS unit capacity values implemented in EPA Base Case v.5.13 reflect net summer dependable
capacity18, to the extent possible. Table 4-4 summarizes the hierarchy of primary data sources used in
compiling capacity data for NEEDS v.5.13; in other words, data sources are evaluated in this order, and
capacity values are taken from a particular source only if the sources listed above it do not provide
adequate data for the unit in question.19
Table 4-4 Hierarchy of Data Sources for Capacity in NEEDS v.5.13
Sources Presented in Hierarchy
Summer Net Dependable Capacity from Comments
2010 EIA 860 Summer Capacity
2011 EIA 860 Summer Capacity
2010 EIA 860 Winter Capacity
2011 EIA 860 Winter Capacity
2010 EIA 860 Nameplate Capacity
2011 EIA 860 Nameplate Capacity
Notes:
Presented in hierarchical order that applies.
If capacity is zero, unit is not included.
As noted earlier, NEEDS v.5.13 includes boiler level data for steam units, and generator level data for
non-steam units. Capacity data in EIA are generator-specific and not boiler specific. Therefore, it was
necessary to develop an algorithm for parsing generator-level capacity to the boiler level for steam
producing units.
18 As used here, net summer dependable capacity is the net capability of a generating unit in megawatts (MW) for
daily planning and operation purposes during the summer peak season, after accounting for station or auxiliary
services.
19 EIA 860 2010 was reviewed before 2011 because 2010 was the most recent data year available at the time
NEEDS development began.
4-4
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The capacity-parsing algorithm used for steam units in NEEDS v.5.13 took into account boiler-generator
mapping. Fossil steam electric units have boilers attached to generators that produce electricity. There
are generally four types of links between boilers and generators: one boiler to one generator, one boiler to
many generators, many boilers to one generator and many boilers to many generators.
The capacity-parsing algorithm used for steam units in NEEDS utilized steam flow data with the boiler-
generator mapping. Under EIA 860, steam units report the maximum steam flow from the boiler to the
generator. There is, however, no further data on the steam flow of each boiler-generator link. Instead,
EIA 860 contains only the maximum steam flow for each boiler. Table 4-5 summarizes the algorithm
used for parsing capacity with data on maximum steam flow and boiler-generator mapping. In Table 4-5,
MFB/ refers to the maximum steam flow of boiler; and MWG; refers to the capacity of generatory. The
algorithm uses the available data to derive the capacity of a boiler, referred to as MWB; in Table 4-5.
Table 4-5 Capacity-Parsing Algorithm for Steam Units in NEEDS v.5.13
Type of Boiler-Generator Links
For Boiler B-i to BN linked to Generators
GI to GN
One-to-One
MWB, =
MWG;
One-to-Many
MWB, =
I;MWG;
Many-to-One
MWB, =
(MFB,/r,MFe,)*
MWG;
Many-to-Many
MWB, =
(MFB//I,MFB/)*
I;MWG;
Notes:
MFB, = maximum steam flow of boiler /
MWG; = electric generation capacity of generator/
Since EPA Base Case v.5.13 uses net energy for load as demand, NEEDS v.5.13 only includes
generators that sell the majority of their power to the electric grid; this approach is intended to be broadly
consistent with the generating capacity used in the AEO projections used as the source where demand is
net energy for load. The generators that should be in NEEDS v.5.13 by this qualification are determined
from the 2010 EIA Form 923 non-utility source and disposition data set.
4.2.3 Plant Location
NEEDS v.5.13 uses state, county and model region data to represent the physical location of each plant.
State and County
NEEDS v.5.13 used the state and county data in EIA 860 (2010, 2011).
Model Region
For each unit the associated model region was derived based on NERC assessment regions reported
in NERC ES&D 2011 for that unit. For units with no NERC assessment region data, state and county
were used to derive associated model regions. Using these shares of each NEMS region net energy
for load that falls in each IPM region, calculate the total net energy for load for each IPM region from
the NEMS regional load in AEO 2013.
Table 3-1 in Chapters provides a summary of the mapping between NERC assessment regions and EPA
Base Case v.5.13 model regions.
4.2.4 Online Year
The EPA Base Case v.5.13 uses online year to capture when the unit entered service. NEEDS includes
online years for all units in the database. In NEEDS v.5.13, online years for boilers, utility and non-utility
generators were primarily derived from reported in-service dates in EIA Form 860 (2010, 2011).
4-5
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EPA Base Case v.5.13 includes constraints to set the retirement year for generating units that are firmly
committed to retire after 2015 based on state or federal regulations and enforcement actions. In addition,
existing nuclear units must retire when they reach age 60. (See section 0 for a discussion of the nuclear
lifetime assumption.) EPA Base Case v.5.13 also provides economic retirement options to coal, oil and
gas steam, combined cycle, combustion turbines and nuclear units. This means that the model may elect
to retire these units if it is economical to do so. In IPM, a retired plant ceases to incur FOM and VOM
costs. However, retired units do continue to service debt on any previously incurred capital cost for
model-installed retrofits if the model projected a retrofit on the unit prior to retirement.
4.2.5 Unit Configuration
Unit configuration refers to the physical specification of a unit's design. Unit configuration in EPA Base
Case v.5.13 drives model plant aggregation, modeling of pollution control options and mercury emission
modification factors. NEEDS v.5.13 contains information on the firing and bottom type of coal steam
boilers in the database. Great effort was taken to ensure that the inventory of existing and committed
controls represented in EPA Base Case v.5.13 was comprehensive and as up-to-date as possible. The
hierarchy of data sources used is shown in Table 4-6.
Table 4-6 Data Sources for Unit Configuration in NEEDS v.5.13 for EPA Base Case v.5.13
Unit
Component
Firing Type
Bottom Type
SO2 Pollution
Control
NOX Pollution
Control
Mercury Control
Particulate
Matter Control
HCI Control
Primary Data Source
2010EIA860
2010EIA860
NSR Settlement or
Comments
NSR Settlement or
Comments
NSR Settlement or
Comments
NSR Settlement or
Comments
NSR Settlement or
Comments
Secondary Data
Source
EPA's Emission
Tracking System
(ETS)-2011
EPA's Emission
Tracking System
(ETS)-2011
EPA's Emission
Tracking System
(ETS)-2011
EPA's Emission
Tracking System
(ETS)-2011
2010EIA860
EPA's Emission
Tracking System
(ETS)-2011
-
Tertiary
Data
Source
-
-
2010 EIA
860
2010 EIA
860
-
2010 EIA
860
-
Other
Sources
-
-
See Note
See Note
-
-
See Note
Default
-
Dry
No
Control
No
Control
No
Control
No
Control
No
Control
Note:
In addition to the primary, secondary and tertiary data sources listed here, the following sources were consulted and emission
controls were updated when corroborating information could be found: Reports filed with the Securities and Exchange Commission;
websites of generating unit owners and operators; GenerationHub; state public utility service commissions; state permitting
agencies; architecture and engineering firm announcements (eg.: Shaw, URS, Stanley, Black &Veatch, Peter Kewit, etc.);
equipment supplier announcements (Alstom, B&W, Babcock Power); Power-Eng.com; MclLVAINE Utility Upgrade Database; ICAC
(Institute of Clean Air Companies).
4.2.6 Model Plant Aggregation
While EPA Base Case using IPM is comprehensive in representing all the units contained in NEEDS, an
aggregation scheme is used to combine existing units with similar characteristics into "model plants". The
aggregation scheme serves to reduce the size of the model and makes the model manageable while
capturing the essential characteristics of the generating units. The EPA Base Case v.5.13 aggregation
scheme is designed so that each model plant only represents generating units from a single state. This
4-6
-------
design makes it possible to obtain state-level results directly from IPM outputs. In addition, the
aggregation scheme supports modeling plant-level emission limits on fossil generation.
The "model plant" aggregation scheme encompasses a variety of different classification categories
including location, size, technology, heat rate, fuel choices, unit configuration, SO2 emission rates and
environmental regulations among others. Units are aggregated together only if they match on all the
different categories specified for the aggregation. The 11 major categories used for the aggregation
scheme in EPA Base Case v.5.13 are the following:
(1) Model Region
(2) Unit Technology Type
(3) Fuel Demand Region
(4) Applicable Environmental Regulations
(5) State
(6) Facility (ORIS) for fossil units
(7) Unit Configuration
(8) Emission Rates
(9) Heat Rates
(10) Fuel
(11) Size
Table 4-7 shows the number of actual units by generation technology type and the related number of
aggregated "model plants" used in the EPA Base Case v.5.13. For each plant type, the table shows the
number of real plants and the number of model plants representing these real plants in EPA Base Case
v.5.13.""
20
Table 4-7 Aggregation Profile of Model Plants as Provided at Set Up of EPA Base Case v.5.13
Existing and Planned/Committed Units
Plant Type
Biomass
Coal Steam
Combined Cycle
Combustion Turbine
Fossil Other
Fuel Cell
Number of Units
194
1,003
1,727
5,552
60
25
Number of IPM Model
Plants
119
759
702
2,200
18
12
20 (1) The "Number of IPM Model Plants" shown for many of the "Plant Types" in the "Retrofits" block in Table 4-7
exceeds the "Number of IPM Model Plants" shown for "Plant Type" "Coal Steam" in the block labeled "Existing and
Planned/Committed Units", because a particular retrofit "Plant Type" can include multiple technology options and
multiple timing options (e.g., Technology A in Stage 1 + Technology B in Stage 2 + Technology C in Stage 3, the
reverse timing, or multiple technologies simultaneously in Stage 1). (3) Since only a subset of coal plants is eligible
for certain retrofits, many of the "Plant Types" in the "Retrofits" block that represent only a single retrofit technology
(e.g., "Retrofit Coal with Selective Non-catalytic Reduction (SNCR)") have a "Number of IPM Model Plants" that is a
smaller than the "Number of IPM Model Plants" shown for "Plant Type" "Coal Steam". (4) The total number of model
plants representing different types of new units often exceeds the 64 US model regions and varies from technology to
technology for several reasons. First, some technologies have multiple vintages (i.e., different cost and/or
performance parameters depending on which run-year in which the unit is created), which must be represented by
separate model plants in each IPM region. Second, some technologies are not available in particular regions (e.g.,
geothermal is geographically restricted to certain regions).
4-7
-------
Existing and Planned/Committed Units
Plant Type
Geothermal
Hydro
Import
Integrated Gas Combined Cycle
Landfill Gas
Non Fossil Other3
Nuclearb
Oil/Gas Steam
Pumped Storage
Solar PV
Solar Thermal
Wind
Total
Number of Units
219
3,807
1
10
1,414
308
105
532
152
370
27
824
16,330
Number of IPM Model
Plants
28
160
1
5
225
135
105
347
24
47
10
74
4,971
New Units
Plant Type
New Advanced Coal with CCS
New Biomass
New Combined Cycle
New Combined Cycle with Carbon Capture
New Combustion Turbine
New Fuel Cell
New Future Technology
New Geothermal
New IGCC
New Landfill Gas
New Nuclear
New Offshore Wind
New Onshore Wind
New Solar PV
New Solar Thermal
New SPC-WetFGD_SCR
Total
Number of Units
-
-
-
-
-
-
Number of IPM Model
Plants
51
123
61
61
61
122
305
64
56
369
122
714
1480
228
91
51
3,959
Retrofits
Plant Type
Retrofit Coal with ACI
Retrofit Coal with ACI + CCS
Retrofit Coal with ACI + CCS + HRI
Retrofit Coal with ACI + CCS + HRI + SCR
Retrofit Coal with ACI + CCS + HRI + SCR + Scrubber
Retrofit Coal with ACI + CCS + HRI + Scrubber
Retrofit Coal with ACI + CCS + SCR
Retrofit Coal with ACI + CCS + SCR + Scrubber
Retrofit Coal with ACI + CCS + Scrubber
Retrofit Coal with ACI + DSI
Retrofit Coal with ACI + DSI + HRI
Number of Units
-
Number of IPM Model Plants
414
164
158
78
138
152
78
138
152
389
385
4-8
-------
Retrofits
Plant Type
Retrofit Coal with ACI + DSI + HRI + SCR
Retrofit Coal with ACI + DSI + HRI + SCR + Scrubber
Retrofit Coal with ACI + DSI + HRI + Scrubber
Retrofit Coal with ACI + DSI + HRI + SNCR
Retrofit Coal with ACI + DSI + HRI + SNCR + Scrubber
Retrofit Coal with ACI + DSI + SCR
Retrofit Coal with ACI + DSI + SCR + Scrubber
Retrofit Coal with ACI + DSI + Scrubber
Retrofit Coal with ACI + DSI + Scrubber + SNCR
Retrofit Coal with ACI + DSI + SNCR
Retrofit Coal with ACI + HRI
Retrofit Coal with ACI + HRI + SCR
Retrofit Coal with ACI + HRI + SCR + Scrubber
Retrofit Coal with ACI + HRI + Scrubber
Retrofit Coal with ACI + HRI + SNCR
Retrofit Coal with ACI + HRI + SNCR + Scrubber
Retrofit Coal with ACI + SCR
Retrofit Coal with ACI + SCR + Scrubber
Retrofit Coal with ACI + Scrubber
Retrofit Coal with ACI + Scrubber + SNCR
Retrofit Coal with ACI + SNCR
Retrofit Coal with C2G
Retrofit Coal with C2G + SCR
Retrofit Coal with CCS
Retrofit Coal with CCS + HRI
Retrofit Coal with CCS + HRI + SCR
Retrofit Coal with CCS + HRI + SCR + Scrubber
Retrofit Coal with CCS + HRI + Scrubber
Retrofit Coal with CCS + SCR
Retrofit Coal with CCS + SCR + Scrubber
Retrofit Coal with CCS + Scrubber
Retrofit Coal with DSI
Retrofit Coal with DSI + HRI
Retrofit Coal with DSI + HRI + SCR
Retrofit Coal with DSI + HRI + SCR + Scrubber
Retrofit Coal with DSI + HRI + Scrubber
Retrofit Coal with DSI + HRI + SNCR
Retrofit Coal with DSI + SCR
Retrofit Coal with DSI + SCR + Scrubber
Retrofit Coal with DSI + Scrubber
Retrofit Coal with DSI + SNCR
Retrofit Coal with HRI
Retrofit Coal with HRI + SCR
Retrofit Coal with HRI + SCR + Scrubber
Retrofit Coal with HRI + Scrubber
Retrofit Coal with HRI + Scrubber + SNCR
Retrofit Coal with HRI + SNCR
Retrofit Coal with SCR
Retrofit Coal with SCR + Scrubber
Retrofit Coal with Scrubber
Number of Units
-
Number of IPM Model Plants
525
354
362
151
74
528
356
364
76
173
406
570
883
737
162
302
576
886
742
307
166
621
621
410
352
124
168
200
122
168
200
239
473
658
383
333
129
661
385
334
200
646
782
1,347
1,034
440
209
399
1,353
524
4-9
-------
Retrofits
Plant Type
Retrofit Coal with Scrubber + SNCR
Retrofit Coal with SNCR
Retrofit Combined Cycle with CCS
Retrofit Oil/Gas steam with SCR
Total
Number of Units
-
-
Number of IPM Model Plants
452
106
424
227
25,670
Retirements
Plant Type
CC Retirement
Coal Retirement
CT Retirement
IGCC Retirement
Non-Fossil Retirement
Nuke Retirement
O/G Retirement
Total
Number of Units
-
-
Number of IPM Model Plants
702
5,372
2,200
5
680
105
1,195
10,259
Grand Total (Existing and Planned/Committed + New + Retrofits + Retirements): 44,859
Notes:
a Non FossilJDther includes units whose fuel is municipal solid waste, tires, and other non-fossil waste.
b The 105 nuclear units include 99 currently operating units, 1 unit scheduled to retire in 2014 (Vermont Yankee), plus Watts
Bar Nuclear Plant (Unit 2), Vogtle (Units 3&4), and V C Summer (Units 2&3), which are scheduled to come online during 2015 -
2018. All except Vermont Yankee Nuclear unit are listed in Table 4-34
4.2.7 Cost and Performance Characteristics of Existing Units
In EPA Base Case v.5.13 heat rates, emission rates, variable operation and maintenance cost (VOM) and
fixed operation and maintenance costs (FOM) are used to characterize the cost and performance of all
existing units in NEEDS v.5.13. For existing units, only the cost of maintaining (FOM) and running (VOM)
the unit are modeled. Embedded costs, such as carrying capital charges, are not modeled; however,
because such historically invested capital costs are sunk costs, they are economically irrelevant for
projecting least-cost investment and operational decisions for electricity supply going forward. The
section below contains a discussion of the cost and performance assumptions for existing units used in
the EPA Base Case v.5.13.
Variable Operating and Maintenance Cost (VOM)
VOM represents the non-fuel variable cost associated with producing electricity. If the generating unit
contains pollution control equipment, VOM includes the cost of operating the control equipment. Table
4-8 below summarizes VOM assumptions used in EPA Base Case v.5.13. The values shown in this table
were obtained using a procedure developed jointly by EPA's power sector engineering staff and ICF.
Table 4-8 VOM Assumptions in EPA Base Case v.5.13
Capacity Type
Biomass
Coal Steam
SO2 Control
-
No SO2 Control
NOX Control
-
No NOX Control
SCR
SNCR
Hg Control
-
No Hg Control
ACI
No Hg Control
ACI
No Hg Control
ACI
Variable O&M (2011$/mills/kWh)
2.41
0.84
2.28
1.29
2.73
1.85
3.29
4-10
-------
Capacity Type
Combined Cycle
Combustion Turbine
Fuel Cell
Geothermal
Hydro
IGCC
Landfill Gas / Municipal Solid Waste
O/G Steam
Pumped Storage
Solar PV
Solar Thermal
Wind
SO2 Control
Dry FGD
Wet FGD
DSI
No SO2 Control
No SO2 Control
-
-
-
-
-
No SO2 Control
Wet FGD
-
-
-
-
NOX Control
No NOX Control
SCR
SNCR
No NOX Control
SCR
SNCR
No NOX Control
SCR
SNCR
No NOX Control
SCR
SNCR
No NOX Control
SCR
SNCR
-
-
-
-
-
No NOX Control
SCR
SNCR
No NOX Control
SCR
SNCR
-
-
-
-
Hg Control
No Hg Control
ACI
No Hg Control
ACI
No Hg Control
ACI
No Hg Control
ACI
No Hg Control
ACI
No Hg Control
ACI
No Hg Control
ACI
No Hg Control
ACI
No Hg Control
ACI
No Hg Control
No Hg Control
-
-
-
-
-
No Hg Control
-
-
-
-
Variable O&M (2011$/mills/kWh)
4.29
5.73
4.74
6.18
5.30
6.74
4.77
6.21
5.22
6.66
5.78
7.22
10.07
11.51
10.52
11.96
11.08
12.52
2.82 - 5.96
2.95 - 6.09
3.41 - 6.55
3.35 - 22.44
3.48 - 22.57
3.94 - 23.03
0.00
2.86
1.70
3.24-6.38
2.44
0.76
0.89
1.35
0.76
0.89
1.35
9.43
0.00
3.51
2.20
Fixed Operation and Maintenance Cost (FOM)
FOM represents the annual fixed cost of maintaining a unit. FOM costs are incurred independent of
generation levels and signify the fixed cost of operating and maintaining the unit's availability to provide
generation.
4-11
-------
Table 4-9 summarizes the FOM assumptions used in EPA Base Case v.5.13. Note that FOM varies by
the age of the unit, and the total FOM cost incurred by a unit depends on its capacity size. The values
appearing in this table include the cost of maintaining any associated pollution control equipment. The
values in
4-12
-------
Table 4-9 are based on FERC (Federal Energy Regulatory Commission) Form 1 data maintained by
Ventyx and ICF research.
4-13
-------
Table 4-9 FOM Assumptions Used in EPA Base Case v.5.13
Plant Type
Biomass
Coal Steam
SO2 Control
NoSO2
Control
DryFGD
NOX Control
NoNOx
Control
SCR
SNCR
NoNOx
Control
SCR
Hg Control
NoHg
Control
AC I
NoHg
Control
AC I
NoHg
Control
AC I
NoHg
Control
AC I
NoHg
Control
AC I
Age of Unit
All Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
FOM (2011$ /kW-
Yr)
35.28
36.49
38.61
49.13
50.83
36.58
38.70
49.22
50.92
37.13
39.26
49.78
51.48
37.22
39.35
49.86
51.57
37.11
39.23
49.75
51.45
37.20
39.32
49.84
51.54
46.51
48.63
59.15
60.85
46.60
48.72
59.24
60.94
47.15
49.28
59.80
61.50
47.24
49.37
4-14
-------
Plant Type
SO2 Control
Wet FGD
DSI
NOX Control
SNCR
NoNOx
Control
SCR
SNCR
NoNOx
Control
Hg Control
NoHg
Control
ACI
NoHg
Control
ACI
NoHg
Control
ACI
NoHg
Control
ACI
NoHg
Control
ACI
Age of Unit
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
FOM(2011$/kW-
Yr)
59.88
61.59
47.13
49.25
59.77
61.47
47.22
49.34
59.86
61.56
45.90
48.02
58.54
60.24
45.99
48.11
58.63
60.33
46.54
48.67
59.19
60.89
46.63
48.76
59.27
60.98
46.52
48.64
59.16
60.86
46.61
48.73
59.25
60.95
37.99
40.11
50.63
52.33
38.08
40.20
4-15
-------
Plant Type
Combined Cycle
Combustion
Turbine
Fuel Cell
Geothermal
Hydro
IGCC
Landfill Gas /
Municipal Solid
Waste
O/G Steam
SO2 Control
NoSO2
Control
NoSO2
Control
-
NoSO2
Control
-
NoSO2
Control
NOX Control
SCR
SNCR
NoNOx
Control
SCR
SNCR
NoNOx
Control
SCR
SNCR
-
NoNOx
Control
-
NoNOx
Control
SCR
Hg Control
NoHg
Control
ACI
NoHg
Control
ACI
NoHg
Control
NoHg
Control
NoHg
Control
NoHg
Control
NoHg
Control
NoHg
Control
-
-
-
NoHg
Control
NoHg
Control
Age of Unit
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
-
-
-
-
-
-
All Years
All Years
All Years
All Years
All Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
FOM(2011$/kW-
Yr)
50.72
52.42
38.63
40.76
51.28
52.98
38.72
40.85
51.36
53.07
38.61
40.73
51.25
52.95
38.70
40.82
51.34
53.04
24.29
25.56
24.42
16.47
18.41
16.91
370.36
40.07
19.28
36.89
46.10
20.31
21.22
23.68
23.68
21.34
22.25
24.71
4-16
-------
Plant Type
Pumped Storage
Solar PV
Solar Thermal
Wind
SO2 Control
Wet FGD
-
-
NOX Control
SNCR
NoNOx
Control
SCR
SNCR
-
-
Hg Control
NoHg
Control
NoHg
Control
NoHg
Control
NoHg
Control
-
-
Age of Unit
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
0 to 30 Years
30 to 40 Years
40 to 50 Years
Greater than 50
Years
All Years
All Years
All Years
All Years
FOM(2011$/kW-
Yr)
24.71
20.47
21.39
23.84
23.84
20.31
21.22
23.68
23.68
21.34
22.25
24.71
24.71
20.47
21.39
23.84
23.84
7.37
20.53
31.94
19.54
Heat Rates
Heat Rates describe the efficiency of the unit expressed as BTUs per kWh. The treatment of heat rates
in EPA Base Case v.5.13 is discussed in Section 3.8.
Lifetimes
Unit lifetime assumptions in EPA Base Case v.5.13 are detailed in Sections 0 and 4.2.8.
SO? Rates
Section 3.9.1 contains a detailed discussion of SO2 rates for existing units.
NOy Rates
Section 3.9.2 contains a detailed discussion of NOX rates for existing units.
Mercury Emission Modification Factors (EMF)
Mercury EMF refers to the ratio of mercury emissions (mercury outlet) to the mercury content of the fuel
(mercury inlet). Section 5.4.2 contains a detailed discussion of the EMF assumptions in EPA Base Case
v.5.13.
4-17
-------
4.2.8 Life Extension Costs for Existing Units
The modeling time horizon in EPA Base Case 5.13 extends to 2050 and covers a period of almost 40
years. This time horizon requires consideration in EPA Base Case v.5.13 of investments, beyond routine
maintenance, necessary to extend the life of existing units. The life extension costs for units with
retirement options are summarized in Table 4-10 below. These costs were based on a review of FERC
Form 1 data regarding reported annual capital expenditures made by older units.
Table 4-10 Life Extension Cost Assumptions Used in EPA Base Case v.5.13
Plant Type
Biomass -
Fluidized Bed
Coal Steam
Combined Cycle
Combustion
Turbine & 1C
Engine
Oil/Gas Steam
IGCC
Nuclear
Landfill Gas
Lifespan without Life
Extension
Expenditures
40
40
30
30
40
40
40
20
Life Extension Cost as
Proportion of New Unit
Capital Cost (%)
6.6%
7.0%
9.3%
4.2%
3.4%
7.4%
9.0%
9.1%
Capital Cost of
New Unit
(2011$/kW)
4,429
3,160
1,047
691
2,923
3,254
6,168
9,023
Life Extension
Cost (201 1$/kW)
291
221
98
29
98
241
555
823
Notes:
Life extension expenditures double the lifespan of the unit.
4.3 Planned-Committed Units
EPA Base Case v.5.13 includes all planned-committed units that are likely to come online because
ground has been broken, financing obtained, or other demonstrable factors indicate a high probability that
the unit will be built before 2016.
4.3.1 Population and Model Plant Aggregation
Like existing units, planned-committed units are contained in NEEDS. A comprehensive update of
planned-committed units contained in NEEDS was performed for EPA Base Case v.5.13 using the
information sources listed in Table 4-1. Table 4-11 summarizes the extent of inventory of planned-
committed units in EPA Base Case v.5.13 indicating its generating capacity by unit types.
Table 4-11 Summary of Planned-Committed Units in NEEDS v.5.13 for EPA Base Case v.5.13
Type
Capacity (MW)
Year Range Described
Renewables/Non -conventional
Biomass
Fuel Cell
Geothermal
Hydro
Landfill Gas
Municipal Solid Waste
Non-Fossil Waste
Pumped Storage
Solar PV
Solar Thermal
Wind
Subtotal
901
33
332
689
576
119
254
40
5,262
1,777
18,951
28,933
2011 -2015
2011 -2015
2011 -2016
2011 -2015
2011 -2015
2011 -2015
2011 -2015
2015-2015
2011 -2015
2012-2015
2011 -2015
4-18
-------
Type
Capacity (MW)
Year Range Described
Fossil/Conventional
Coal Steam
Combined Cycle
Combustion Turbine
Fossil Waste
IGCC
Nuclear
O/G Steam
Subtotal
Grand Total
9,498
18,597
8,899
40
1,168
5,522
4
44,528
72,661
2011 -2015
2011 -2015
2011 -2015
2015-2015
2012-2014
2015-2018
2015-2015
Due to data confidentiality restrictions, NEEDS v.5.13 does not list the planned-committed units on a unit-
by-unit basis. Rather, all units having similar technologies and located within the same model region are
aggregated together as one record. Table 4-12 gives a breakdown of planned-committed units by IPM
region, unit type, number of units, and capacity included in EPA Base Case v.5.13.
Table 4-12 Planned-Committed Units by Model Region in NEEDS v.5.13 for EPA Base Case v.5.13
IPM Region
ERC_REST
ERC WEST
FRCC
MAP_WAUE
MIS IA
MIS IL
MISJNKY
MIS_LMI
Plant Type
Biomass
Coal Steam
Combined Cycle
Combustion Turbine
Hydro
Landfill Gas
Non-Fossil Waste
Solar PV
Wind
Wind
Biomass
Combined Cycle
Combustion Turbine
Landfill Gas
Non-Fossil Waste
Solar PV
Combustion Turbine
Wind
Combustion Turbine
Wind
Biomass
Coal Steam
Combustion Turbine
Wind
Hydro
IGCC
Landfill Gas
Non-Fossil Waste
Solar PV
Landfill Gas
Non-Fossil Waste
Solar PV
Wind
Capacity (MW)
144
2,869
620
166
0.19
15
4
78
311
585
110
2,388
465
10
15
74
60
102
5
460
15
1,600
20
415
162
586
6
4
17
26
4
1
391
4-19
-------
IPM Region
MIS_MAPP
MIS MIDA
MIS_MNWI
MIS_MO
MIS_WUMS
NENG_CT
NENG_ME
NENGREST
NY_Z_A&B
NY_Z_C&E
NY Z D
NY_Z_F
NY Z G-l
NY_Z_J
NY_Z_K
PJM_AP
Plant Type
Coal Steam
Geothermal
Non-Fossil Waste
Solar PV
Wind
Wind
Combined Cycle
Combustion Turbine
Hydro
Landfill Gas
Non-Fossil Waste
Wind
Combustion Turbine
Landfill Gas
Non-Fossil Waste
Biomass
Coal Steam
Combustion Turbine
Landfill Gas
Wind
Combined Cycle
Combustion Turbine
Combined Cycle
Hydro
Landfill Gas
Wind
Biomass
Combustion Turbine
Hydro
Landfill Gas
Non-Fossil Waste
Solar PV
Wind
Biomass
Landfill Gas
Wind
Combustion Turbine
Landfill Gas
Wind
Wind
Hydro
Non-Fossil Waste
Landfill Gas
Combined Cycle
Combustion Turbine
Fuel Cell
Combustion Turbine
Solar PV
Coal Steam
Combined Cycle
Hydro
Landfill Gas
Solar PV
Wind
Capacity (MW)
99
23
6
0
431
956
300
5
10
2
6
807
6
15
3
57
615
58
23
162
628
763
25
2
3
131
77
40
2
42
1
54
288
15
5
141
2
13
129
21
2
20
2
540
466
5
0.23
75
700
570
0.01
10
20
253
4-20
-------
IPM Region
PJM_ATSI
PJM_COMD
PJM_Dom
PJM_EMAC
PJM_PENE
PJM_SMAC
PJM_West
PJM_WMAC
S_C_KY
S C TVA
Plant Type
Combined Cycle
Fossil Waste
Landfill Gas
Non-Fossil Waste
Solar PV
Wind
Biomass
Landfill Gas
Solar PV
Wind
Biomass
Combined Cycle
Combustion Turbine
Landfill Gas
Solar PV
Biomass
Combined Cycle
Combustion Turbine
Hydro
Landfill Gas
Non-Fossil Waste
Solar PV
Wind
Biomass
Combustion Turbine
Landfill Gas
O/G Steam
Wind
Biomass
Combustion Turbine
Landfill Gas
Solar PV
Coal Steam
Combined Cycle
Hydro
Landfill Gas
Non-Fossil Waste
Solar PV
Wind
Biomass
Combined Cycle
Combustion Turbine
Landfill Gas
Solar PV
Wind
Coal Steam
Hydro
Landfill Gas
Biomass
Combined Cycle
Hydro
IGCC
Landfill Gas
Nuclear
Solar PV
Capacity (MW)
666
23
21
135
19
5
55
7
23
996
50
589
52
42
31
30
545
990
137
32
1
431
5
1
2
7
4
511
4
5
5
7
585
539
47
14
3
3
806
30
100
10
16
27
69
732
105
2
13
878
66
582
8
1,122
23
4-21
-------
IPM Region
S D AMSO
S D N AR
S D WOTA
S SOU
S_VACA
SPP N
SPP_NEBR
SPP SE
SPP SPS
SPP_WEST
WEC_CALN
WEC_LADW
WEC SDGE
Plant Type
Municipal Solid Waste
Combined Cycle
Hydro
Biomass
Combined Cycle
Landfill Gas
Non-Fossil Waste
Nuclear
Solar PV
Biomass
Coal Steam
Combined Cycle
Combustion Turbine
Hydro
Landfill Gas
Municipal Solid Waste
Non-Fossil Waste
Nuclear
Solar PV
Coal Steam
Hydro
Landfill Gas
Municipal Solid Waste
Solar PV
Wind
Coal Steam
Wind
Combustion Turbine
Non-Fossil Waste
Combustion Turbine
Solar PV
Wind
Coal Steam
Combustion Turbine
Hydro
Wind
Biomass
Combined Cycle
Combustion Turbine
Fuel Cell
Hydro
Landfill Gas
Non-Fossil Waste
Solar PV
Solar Thermal
Wind
Combined Cycle
Combustion Turbine
Fuel Cell
Solar PV
Biomass
Combustion Turbine
Fuel Cell
Pumped Storage
Solar PV
Capacity (MW)
115
495
24
122
2,552
18
2
2,200
3
58
800
4,203
727
33
73
2
2
2,200
124
279
5
3
2
0.09
1,274
220
244
33
21
507
55
458
609
20
20
1,673
21
1,240
1,252
3
8
3
9
1,057
30
468
560
1,133
1
178
2
38
6
40
35
4-22
-------
IPM Region
WECC_AZ
WECC_CO
WECC_ID
WECCJID
WECC_MT
WECC_NM
WECC_NNV
WECC_PNW
WECC_SCE
WECC SF
Plant Type
Combustion Turbine
Landfill Gas
Non-Fossil Waste
Solar PV
Solar Thermal
Wind
Combined Cycle
Combustion Turbine
Hydro
Landfill Gas
Solar PV
Solar Thermal
Wind
Combined Cycle
Hydro
Non-Fossil Waste
Solar PV
Wind
Combined Cycle
Geothermal
Solar PV
Biomass
Combustion Turbine
Hydro
Landfill Gas
Wind
Combined Cycle
Fossil Waste
Geothermal
Hydro
Solar PV
Solar Thermal
Wind
Combustion Turbine
Geothermal
Landfill Gas
Solar PV
Solar Thermal
Wind
Biomass
Geothermal
Hydro
Landfill Gas
Non-Fossil Waste
Solar PV
Wind
Combustion Turbine
Fuel Cell
Landfill Gas
Solar PV
Solar Thermal
Wind
Fuel Cell
Capacity (MW)
516
6
0.15
1,153
250
109
200
200
8
8
89
1
546
299
4
10
10
593
94
92
249
12
172
13
2
221
142
17
10
3
75
1
50
1
138
6
3
110
150
86
30
39
83
10
10
3,057
1,158
5
37
1,185
1,385
2,027
13
4-23
-------
IPM Region
WECC_SNV
WECC_UT
WECC_WY
Plant Type
Combined Cycle
Landfill Gas
Solar PV
Combustion Turbine
Geothermal
Wind
Coal Steam
Wind
Capacity (MW)
424
11
155
28
40
104
390
2
Note:
Any unit in NEEDS v.5.13 that has an online year of 2011 or later was considered a Planned and Committed Unit
4.3.2 Capacity
The capacity of planned-committed units in NEEDS v.5.13 was obtained from the information sources
reported above in Table 4-1.
4.3.3 State and Model Region
State location data for the planned-committed units in NEEDS v.5.13 came from the information sources
noted in Section 4.3.1. The state information was then used to assign planned-committed units to their
respective model regions.
4.3.4 Online and Retirement Year
As noted above, planned-committed units included in NEEDS v.5.13 are only those units which are likely
to come on-line before 2016. All planned-committed units were given a default online year of 2015 since
2016 is the first analysis year in EPA Base Case v.5.13.
4.3.5 Unit Configuration, Cost and Performance
All planned-committed units in NEEDS v.5.13 assume the cost, performance, and unit configuration
characteristics of potential units that are available in 2015. A detailed description of potential unit
assumptions is provided below in Section 4.4.
4.4 Potential Units
The EPA Base Case v.5.13 includes options for developing a variety of potential units that may be "built"
at a future date in response to electricity demand and the constraints represented in the model. Defined
by region, technology, and the year available, potential units with an initial capacity of 0 MW are inputs
into IPM. When the model is run, the capacity of certain potential units is raised from zero to meet
demand and other system and operating constraints. This results in the model's projection of new
capacity.
In Table 4-7 the block labeled "New Units" gives a breakdown of the type and number of potential units
provided in EPA Base Case v.5.13. The following sections describe the cost and performance
assumptions for the potential units represented in the EPA Base Case v.5.13.
4-24
-------
4.4.1 Methodology Used to Derive the Cost and Performance Characteristics of Conventional
Potential Units
The cost and performance characteristics of conventional potential units in EPA Base Case v.5.13 are
derived primarily from assumptions used in the Annual Energy Outlook (AEO) 2013 published by the U.S.
Department of Energy's Energy Information Administration. The capital costs for IGCC and IGCC+CCS
technologies in Table 4-13 are derived from a recently updated study21 by DOE's National Energy
Technology Laboratory (NETL).
4.4.2 Cost and Performance for Potential Conventional Units
EPA's assumed cost and performance characteristics for potential conventional units are shown in Table
4-13. The cost and performance assumptions are based on the size (i.e., net electrical generating
capacity in MW) indicated in the table. However, the total new capacity that is added in a given model
run for these technologies is not restricted to these capacity levels.
This table includes several components of cost. The total installed cost of developing and building a new
plant is captured through the capital cost. It includes expenditures on pollution control equipment that
new units are assumed to install to satisfy air regulatory requirements. The capital costs shown in Table
4-13 are typically referred to as "overnight" capital costs. They include engineering, procurement,
construction, startup, and owner's costs (for such items as land, cooling infrastructure, administration and
associated buildings, site works, switchyards, project management, licenses, etc). The capital costs in
Table 4-13 do not include interest during construction (IDC). IDC is added to the capital costs shown in
Table 4-13 during the set-up of an IPM run. Calculation of IDC is based on the construction profile and
the discount rate. Details on the discount rates used in the EPA Base Case v.5.13 are discussed in
Chapters under financial assumptions.
Table 4-13 also shows fixed operating and maintenance (FOM) and variable operating and maintenance
(VOM) components of cost. FOM is the annual cost of maintaining a generating unit. It represents
expenses incurred regardless of the extent that the unit is run. It is expressed in units of $ per kWper
year. VOM represents the non-fuel costs incurred in running an electric generating unit. It is proportional
to the electrical energy produced and is expressed in units of $ per MWh.
In addition to the three components of cost, Table 4-13 indicates the first run year available, lead time,
vintage periods, heat rate, and availability for each type of unit. Lead time represents the construction
time needed for a unit to come online. Vintage periods are used to capture the cost and performance
improvements resulting from technological advancement and learning-by-doing. Mature technologies and
technologies whose first year available is not at the start of the modeling time horizon may have only one
vintage period, whereas newer technologies may have several vintage periods. Heat rate indicates the
efficiency of the unit and is expressed in units of energy consumed (Btus) per unit of electricity generated
(kWh). Availability indicates the percentage of time that a generating unit is available to provide electricity
to the grid once it has come on line. Availability takes into account estimates of the time consumed by
planned maintenance and forced outages. The emission characteristics of the potential units are not
presented in Table 4-13, but can be found in Table 3-12.
4.4.3 Short-Term Capital Cost Adder
In addition to the capital costs shown in Table 4-13 and
21 http://www.netl.doe.qov/enerqy-analvses/pubs/BaselineCostUpdate.pdf.
4-25
-------
Table 4-16 EPA Base Case v.5.13 includes a short-term capital cost adder that kicks in if the new
capacity deployed in a specific model run year exceeds certain upper bounds. This adder is meant to
reflect the added cost incurred due to short-term competition for scarce labor and materials. Table 4-14
shows the cost adders for each type of potential unit for model run years through 2030. The adder is not
imposed after 2030 on the premise that by that time market adjustments in anticipation of such longer-
term deployment patterns will have eliminated the short term scarcity experienced in earlier years.
The column labeled "Step 1" in Table 4-14 indicates the total amount of capacity of a particular plant type
that can be built in a given model run year without incurring a cost adder. However, if the Step 1 upper
bound is exceeded, then either the Step 2 or Step 3 cost adder is incurred. Above the Step 1 upper
bound, the Step 2 cost adder applies until the cumulative capacity exceeds the Step 1 + Step 2 upper
bound. Beyond that point, the Step 3 capital cost adder applies. For example, the Step 1 upper bound
in 2016 for coal steam potential units is 6,913 MW. If no more than this total new coal steam capacity is
built in 2016, only the capital cost shown in Table 4-13 is incurred. Between 6,913 and 11,522 MW (the
sum of the Step 1 and Step 2 upper bounds, i.e., 6,913 MW +4,609 MW= 11,522 MW), the Step 2 cost
adder of $916/kW applies. For all the new coal capacity built in that model run year (not just the
increment of new capacity above the Step 1 upper bound of 6,913 MW), this extra cost is added to the
capital cost shown in Table 4-13. If the total new coal steam capacity exceeds the Step 1 + Step 2 upper
bound of 11,522 MW, then the Step 3 capacity adder of $2,370/kW is incurred.
The short-term capital cost adders shown in Table 4-14 were derived from AEO assumptions.
4.4.4 Regional Cost Adjustment
The capital costs reported in Table 4-14 are generic. Before EPA implements these capital cost values
values they are converted to region-specific costs. This is done through the application of regional cost
cost adjustment factors which capture regional differences in labor, material, and construction costs and
and ambient conditions. The regional adjustment factors used in EPA Base Case v.5.13 are shown in
in Table 4-15. They were developed from AEO 2013 by multiplying the regional and ambient multipliers
and are applied to both conventional technologies shown in Table 4-13 and renewable and non-
conventional technologies shown in
4-26
-------
Table 4-16 below.
4-27
-------
Table 4-13 Performance and Unit Cost Assumptions for Potential (New) Capacity from Conventional Technologies
in EPA Base Case v.5.13
Size (MW)
First Run Year Available
Lead Time (Years)
Availability
Advanced
Combined
Cycle
400
2016
3
87%
Advanced
Combustion
Turbine
210
2016
2
92%
Nuclear
2236
2020
6
90%
Integrated
Gasification
Combined Cycle
600
2018
4
85%
Integrated Gasification
Combined Cycle with Carbon
Sequestration
520
2020
4
85%
Supercritical
Pulverized Coal
1300
2018
4
85%
Vintage #1 (2016-2054)
Heat Rate
(Btu/kWh)
Capital
(2011$/kW)
Fixed O&M (2011$/kW/yr)
Variable O&M (2011$/MWh)
6,430
1,006
15.1
3.2
9,750
664
6.9
10.2
10,452
5,429
91.7
2.1
8,700
2,969
62.3
7.2
10,700
4,086
70.6
8.2
8,800
2,883
30.6
4.4
Notes:
Capital cost represents overnight capital cost.
Table 4-14 Short-Term Capital Cost Adders for New Power Plants in EPA Base Case v.5.13 (2011$)
ID#
1
2
3
4
5
6
Plant Type
Biomass
Coal Steam
Combined Cycle
Combustion Turbine
Fuel Cell
Geothermal
Upper Bound (MW)
Adder ($/kW)
Upper Bound (MW)
Adder ($/kW)
Upper Bound (MW)
Adder ($/kW)
Upper Bound (MW)
Adder ($/kW)
Upper Bound (MW)
Adder ($/kW)
Upper Bound (MW)
Adder ($/kW)
2016
Step 1 Step 2 Step 3
600 400
1,285 3,322
6,913 4,609
916 2,370
46,157 30,771 -
313 809
23,668 15,778 -
200 518
600 400
2,215 5,727
205 137
2,268 5,865
2018
Step 1 Step 2 Step 3
1 ,200 800
1,285 3,322
13,826 9,218
916 2,370
92,314 61,542 -
313 809
47,335 31,557 -
200 518
1 ,200 800
2,215 5,727
410 274
2,268 5,865
2020
Step 1 Step 2 Step 3
1 ,200 800
1,285 3,322
13,826 9,218
916 2,370
92,314 61,542 -
313 809
47,335 31,557 -
200 518
1 ,200 800
2,215 5,727
410 274
2,268 5,865
2025
Step 1 Step 2 Step 3
3,000 2,000
1,285 3,322
34,566 23,044 -
916 2,370
230,784 153,856 -
313 809
118,338 78,892 -
200 518
3,000 2,000
2,215 5,727
1 ,026 684
2,268 5,865
2030
Step 1 Step 2 Step 3
3,000 2,000
1,285 3,322
34,566 23,044 -
916 2,370
230,784 153,856 -
313 809
118,338 78,892 -
200 518
3,000 2,000
2,215 5,727
1 ,026 684
2,268 5,865
4-28
-------
ID#
7
8
g
10
11
12
13
Plant Type
IGCC and
Advanced Coal with
Carbon Capture
Landfill Gas
Nuclear
Solar Thermal
Solar PV
Onshore Wind
Offshore Wind
Upper Bound (MW)
Adder ($/kW)
Upper Bound (MW)
Adder ($/kW)
Upper Bound (MW)
Adder ($/kW)
Upper Bound (MW)
Adder ($/kW)
Upper Bound (MW)
Adder ($/kW)
Upper Bound (MW)
Adder ($/kW)
Upper Bound (MW)
Adder ($/kW)
2016
Step 1 Step 2 Step 3
2,400 1,600
944 2,441
600 400
2,669 6,904
11,244 7,496
1,789 4,626
90 60
1,439 3,722
286 190
1,025 2,651
11,618 7,746
694 1 ,794
600 400
2,256 5,833
2018
Step 1 Step 2 Step 3
4,800 3,200
944 2,441
1 ,200 800
2,669 6,904
22,488 14,992 -
1,789 4,626
180 120
1,439 3,722
571 381
1,025 2,651
23,237 15,491 -
694 1 ,794
1 ,200 800
2,256 5,833
2020
Step 1 Step 2 Step 3
4,800 3,200
944 2,441
1 ,200 800
2,669 6,904
22,488 14,992 -
1,789 4,626
180 120
1,439 3,722
571 381
1,025 2,651
23,237 15,491 -
694 1 ,794
1 ,200 800
2,256 5,833
2025
Step 1 Step 2 Step 3
12,000 8,000
944 2,441
3,000 2,000
2,669 6,904
56,220 37,480 -
1,789 4,626
450 300
1,439 3,722
1 ,428 952
1,025 2,651
58,092 38,728 -
694 1 ,794
3,000 2,000
2,256 5,833
2030
Step 1 Step 2 Step 3
12,000 8,000
944 2,441
3,000 2,000
2,669 6,904
56,220 37,480 -
1,789 4,626
450 300
1,439 3,722
1 ,428 952
1,025 2,651
58,092 38,728 -
694 1 ,794
3,000 2,000
2,256 5,833
Table 4-15 Regional Cost Adjustment Factors for Conventional and Renewable Generating Technologies in EPA Base Case v.5.13
Model Region
ERC_REST
ERC_WEST
FRCC
MIS_MAPP
MAP_WAUE
MISJL
MISJNKY
MISJA
MIS_MIDA
Pulverized
Coal
0.905
0.905
0.921
0.952
0.952
1.072
1.049
0.952
0.952
Integrated
Gasification
Combined
Cycle
0.943
0.943
0.961
0.956
0.956
1.067
1.056
0.956
0.956
Integrated
Gasification
Combined
Cycle with
Carbon
Capture
0.959
0.959
0.981
0.956
0.956
1.052
1.042
0.956
0.956
Advanced
Combustion
Turbine
0.985
0.985
0.977
0.994
0.994
1.057
1.078
0.994
0.994
Advanced
Combined
Cycle
0.954
0.954
0.959
0.971
0.971
1.059
1.061
0.971
0.971
Fuel
Cell
0.963
0.963
0.972
0.981
0.981
1.017
1.001
0.981
0.981
Advanced
Nuclear
0.960
0.960
0.966
0.980
0.980
1.028
1.029
0.980
0.980
Biomass
0.925
0.925
0.940
0.961
0.961
1.029
1.017
0.961
0.961
Geothermal
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
Landfill
Gas
0.927
0.927
0.944
0.964
0.964
1.030
1.000
0.964
0.964
Onshore
Wind
0.952
0.952
0.963
1.032
1.032
1.036
1.019
1.032
1.032
Offshore
Wind
0.918
0.918
1.000
1.008
1.008
1.000
1.011
1.008
1.008
Solar
Thermal
0.858
0.858
0.891
0.953
0.953
1.057
1.000
0.953
0.953
Solar
Photovoltaic
0.871
0.871
0.901
0.954
0.954
1.051
0.999
0.954
0.954
4-29
-------
Model Region
MISJ.MI
MIS_MO
MIS_WUMS
MIS_MNWI
NENG_CT
NENGREST
NENG_ME
NY_Z_C&E
NY_Z_F
NY_Z_G-I
NY_Z_J
NY_Z_K
NY_Z_A&B
NY_Z_D
PJM_WMAC
PJM_EMAC
PJM_SMAC
PJM_West
PJM_AP
PJM_COMD
PJM_ATSI
PJM_Dom
PJM_PENE
S_VACA
S_C_KY
S_C_TVA
S_SOU
S_D_WOTA
Pulverized
Coal
0.980
1.072
1.049
0.952
1.096
1.096
1.096
1.107
1.107
1.107
1.326
1.326
1.107
1.107
1.152
1.152
1.152
1.049
1.049
1.049
1.049
0.885
1.152
0.885
0.927
0.927
0.919
0.917
Integrated
Gasification
Combined
Cycle
0.968
1.067
1.042
0.956
1.056
1.056
1.056
1.071
1.071
1.071
1.267
1.267
1.071
1.071
1.123
1.123
1.123
1.042
1.042
1.042
1.042
0.925
1.123
0.925
0.948
0.948
0.957
0.950
Integrated
Gasification
Combined
Cycle with
Carbon
Capture
0.959
1.052
1.021
0.956
1.008
1.008
1.008
1.012
1.012
1.012
1.243
1.243
1.012
1.012
1.068
1.068
1.068
1.021
1.021
1.021
1.021
0.932
1.068
0.932
0.954
0.954
0.973
0.962
Advanced
Combustion
Turbine
0.992
1.057
1.057
0.994
1.147
1.147
1.147
1.180
1.180
1.180
1.651
1.651
1.180
1.180
1.232
1.232
1.232
1.057
1.057
1.057
1.057
0.959
1.232
0.959
0.970
0.970
1.011
0.993
Advanced
Combined
Cycle
0.978
1.059
1.040
0.971
1.105
1.105
1.105
1.119
1.119
1.119
1.631
1.631
1.119
1.119
1.184
1.184
1.184
1.040
1.040
1.040
1.040
0.918
1.184
0.918
0.944
0.944
0.979
0.964
Fuel
Cell
0.994
1.017
1.001
0.981
1.009
1.009
1.009
0.996
0.996
0.996
1.141
1.141
0.996
0.996
1.018
1.018
1.018
1.001
1.001
1.001
1.001
0.956
1.018
0.956
0.970
0.970
0.969
0.969
Advanced
Nuclear
0.992
1.028
1.029
0.980
1.054
1.054
1.054
1.067
1.067
1.067
1.136
1.136
1.067
1.067
1.085
1.085
1.085
1.029
1.029
1.029
1.029
0.954
1.085
0.954
0.968
0.968
0.964
0.965
Biomass
0.982
1.029
1.017
0.961
1.038
1.038
1.038
1.034
1.034
1.034
1.246
1.246
1.034
1.034
1.070
1.070
1.070
1.017
1.017
1.017
1.017
0.906
1.070
0.906
0.938
0.938
0.933
0.933
Geothermal
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
Landfill
Gas
0.985
1.030
1.000
0.964
1.016
1.016
1.016
0.996
0.996
0.996
1.263
1.263
0.996
0.996
1.034
1.034
1.034
1.000
1.000
1.000
1.000
0.911
1.034
0.911
0.940
0.940
0.937
0.941
Onshore
Wind
0.998
1.036
1.019
1.032
1.058
1.058
1.058
1.008
1.008
1.008
1.246
1.246
1.008
1.008
1.048
1.048
1.048
1.019
1.019
1.019
1.019
0.947
1.048
0.947
0.963
0.963
0.961
0.962
Offshore
Wind
0.981
1.000
1.011
1.008
1.031
1.031
1.031
0.988
0.988
0.988
1.294
1.294
0.988
0.988
1.026
1.026
1.026
1.011
1.011
1.011
1.011
0.921
1.026
0.921
1.000
1.000
0.930
1.000
Solar
Thermal
0.965
1.057
1.000
0.953
1.035
1.035
1.035
0.976
0.976
0.976
1.501
1.501
0.976
0.976
1.055
1.055
1.055
1.000
1.000
1.000
1.000
0.824
1.055
0.824
0.883
0.883
0.877
0.879
Solar
Photovoltaic
0.968
1.051
0.999
0.954
1.028
1.028
1.028
0.977
0.977
0.977
1.449
1.449
0.977
0.977
1.048
1.048
1.048
0.999
0.999
0.999
0.999
0.841
1.048
0.841
0.894
0.894
0.888
0.890
4-30
-------
Model Region
S_D_AMSO
S_D_N_AR
S_D_REST
SPP_NEBR
SPP_N
SPP_SE
SPP_WEST
SPP_SPS
WECCJD
WECC_NNV
WECC_UT
WECC_SF
WEC_CALN
WECC_IID
WEC_LADW
WEC_SDGE
WECC_SCE
WECC_MT
WECC_PNW
WECC_CO
WECC_WY
WECC_AZ
WECC_NM
WECC SNV
Pulverized
Coal
0.917
0.917
0.917
0.952
1.072
0.980
0.980
0.980
1.015
1.015
1.015
1.193
1.193
1.000
1.193
1.193
1.193
1.015
1.015
0.989
1.015
1.000
1.000
1.000
Integrated
Gasification
Combined
Cycle
0.950
0.950
0.950
0.956
1.082
1.002
1.007
1.002
1.044
1.044
1.044
1.186
1.186
1.092
1.186
1.186
1.186
1.044
1.044
1.103
1.126
1.092
1.092
1.092
Integrated
Gasification
Combined
Cycle with
Carbon
Capture
0.962
0.962
0.962
0.956
1.073
1.007
1.014
1.007
1.045
1.045
1.045
1.139
1.139
1.135
1.139
1.139
1.139
1.045
1.045
1.142
1.174
1.135
1.135
1.135
Advanced
Combustion
Turbine
0.993
0.993
0.993
0.994
1.078
1.032
1.039
1.032
1.079
1.079
1.079
1.311
1.311
1.188
1.311
1.311
1.311
1.079
1.079
1.239
1.239
1.188
1.188
1.188
Advanced
Combined
Cycle
0.964
0.964
0.964
0.971
1.080
1.016
1.024
1.016
1.059
1.059
1.059
1.267
1.267
1.166
1.267
1.267
1.267
1.059
1.059
1.185
1.190
1.166
1.166
1.166
Fuel
Cell
0.969
0.969
0.969
0.981
1.017
0.991
0.991
0.991
0.994
0.994
0.994
1.030
1.030
0.995
1.030
1.030
1.030
0.994
0.994
0.976
0.994
0.995
0.995
0.995
Advanced
Nuclear
0.965
0.965
0.965
0.980
1.028
0.992
0.992
0.992
1.007
1.007
1.007
1.093
1.093
1.001
1.093
1.093
1.093
1.007
1.007
1.005
1.007
1.001
1.001
1.001
Biomass
0.933
0.933
0.933
0.961
1.029
0.979
0.979
0.979
1.004
1.004
1.004
1.083
1.083
1.000
1.083
1.083
1.083
1.004
1.004
0.973
1.004
1.000
1.000
1.000
Geothermal
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
1.000
Landfill
Gas
0.941
0.941
0.941
0.964
1.030
0.982
0.982
0.982
0.984
0.984
0.984
1.057
1.057
0.988
1.057
1.057
1.057
0.984
0.984
0.954
0.984
0.988
0.988
0.988
Onshore
Wind
0.962
0.962
0.962
1.032
1.036
1.018
1.018
1.018
1.047
1.047
1.047
1.119
1.119
1.035
1.119
1.119
1.119
1.047
1.047
1.033
1.047
1.035
1.035
1.035
Offshore
Wind
1.000
1.000
1.000
1.008
1.000
1.000
1.000
1.000
1.017
1.017
1.017
1.049
1.049
1.000
1.049
1.049
1.049
1.017
1.017
1.000
1.017
1.000
1.000
1.000
Solar
Thermal
0.879
0.879
0.879
0.953
1.057
0.974
0.974
0.974
0.990
0.990
0.990
1.129
1.129
0.993
1.129
1.129
1.129
0.990
0.990
0.929
0.990
0.993
0.993
0.993
Solar
Photovoltaic
0.890
0.890
0.890
0.954
1.051
0.974
0.974
0.974
0.987
0.987
0.987
1.111
1.111
0.991
1.111
1.111
1.111
0.987
0.987
0.931
0.987
0.991
0.991
0.991
4-31
-------
Table 4-16 Performance and Unit Cost Assumptions for Potential (New) Renewable and Non-Conventional Technology Capacity
in EPA Base Case v.5.13
Size (MW)
First Run Year Available
Lead Time (Years)
Availability
Generation Capability
Heat Rate (Btu/kWh)
Capital (2011 $/kW)
Fixed O&M (2011$/kW/yr)
Variable O&M (2011$/MWh)
Biomass-
Bubbling
Fluidized Bed
(BFB)
50
2018
4
83%
Economic Dispatch
Geothermal
50
2018
4
87%
Economic Dispatch
Landfill Gas
LGHI
LGLo
LGVLo
50
2016
3
90%
Economic Dispatch
Vintage#1 (2016-2054)
13,500
4,041
103.79
5.17
30,000
1,187-15,752
50 - 541
0.00
13,648
8,408
381 .74
8.51
13,648
10,594
381.74
8.51
13,648
16,312
381 .74
8.51
Heat Rate (Btu/kWh)
Capital (201 1$/kW)
Fixed O&M (2011$/kW/yr)
Variable O&M (2011$/MWh)
Heat Rate (Btu/kWh)
Capital (201 1$/kW)
Fixed O&M (2011$/kW/yr)
Variable O&M (2011$/MWh)
Heat Rate (Btu/kWh)
Capital (201 1$/kW)
Fixed O&M (2011$/kW/yr)
Variable O&M (2011$/MWh)
Heat Rate (Btu/kWh)
Capital (201 1$/kW)
Fixed O&M (2011$/kW/yr)
Variable O&M (2011$/MWh)
Fuel Cells
10
2016
3
87%
Economic Dispatch
Solar Photovoltaic
150
2016
2
90%
Generation Profile
Solar Thermal
100
2016
3
90%
Generation Profile
Onshore Wind
100
2016
3
95%
Generation Profile
Offshore Wind
400
2018
4
95%
Generation Profile
Vintage #1 (2016)
9,246
7,117
357.47
0.0
9,756
3,364
21.37
0.0
9,756
4,690
66.09
0.0
9,756
2,258
38.86
0.0
9,756
6,298
72.71
0.0
Vintage #2 (201 8)
8,738
6995
357.5
0.0
9,756
3,281
21.4
0.0
9,756
4,636
66.1
0.0
9,756
2,250
38.9
0.0
9,756
6233
72.7
0.0
Vintage #3 (2020)
8,230
6806
357.5
0.0
9,756
3,217
21.4
0.0
9,756
4,594
66.1
0.0
9,756
2,220
38.9
0.0
9,756
6108
72.7
0.0
Vintage #4 (2025)
6,960
6276
357.5
0.0
9,756
3,027
21.4
0.0
9,756
4,470
66.1
0.0
9,756
2,123
38.9
0.0
9,756
5739
72.7
0.0
Vintage #5 (2030)
6,960
5,799
357.5
0.0
9,756
2,859
21.4
0.0
9,756
4,360
66.1
0.0
9,756
2,039
38.9
0.0
9,756
5411
72.7
0.0
Vintage #6 (2040)
4-32
-------
Heat Rate (Btu/kWh)
Capital (201 1$/kW)
Fixed O&M (2011$/kW/yr)
Variable O&M (2011$/MWh)
Biomass-
Bubbling
Fluidized Bed
(BFB)
Geothermal
Landfill Gas
LGHI
LGLo
LGVLo
Heat Rate (Btu/kWh)
Capital (201 1$/kW)
Fixed O&M (2011$/kW/yr)
Variable O&M (2011$/MWh)
Fuel Cells
6,960
4,872
357.5
0.0
Solar Photovoltaic
9,756
2,533
21.4
0.0
Solar Thermal
9,756
4,147
66.1
0.0
Onshore Wind
9,756
1,864
38.9
0.0
Offshore Wind
9,756
4,759
72.7
0.0
Vintage #7 (2050)
6,960
4872
357.5
0.0
9,756
2,533
21.4
0.0
9,756
4,147
66.1
0.0
9,756
1,864
38.9
0.0
9,756
4759
72.7
0.0
Notes:
3 Assumptions for Biomass Co-firing for Coal Plants can be found in Table 5-9
4-33
-------
4.4.5 Cost and Performance for Potential Renewable Generating and Non-Conventional
Technologies
4-34
-------
Table 4-16 summarizes the cost and performance assumptions in EPA Base Case v.5.13 for potential
renewable and non-conventional technology generating units. The parameters shown in
4-35
-------
Table 4-16 are based on AEO 2013. The size (MW) presented in
4-36
-------
Table 4-16 represents the capacity on which unit cost estimates were developed and does not indicate
the total potential capacity that the model can build of a given technology. Due to the distinctive nature of
generation from renewable resources, some of the values shown in
4-37
-------
Table 4-16 are averages or ranges that are discussed in further detail in the following subsections. Also
discussed below are additional types of data from sources other than AEO 2013 that play a role in the
representation of these types of generation in EPA Base Case v.5.13
It should be noted that the short term capital cost adder in Table 4-14 and the regional cost adjustment
factors in Table 4-15 apply to the renewable and non-conventional generation technologies as they do to
the conventional generation technologies
Wind Generation
EPA Base Case v.5.13 includes onshore wind, offshore-shallow and offshore-deep wind generation. The
following sections describe four key aspects of the representation of wind generation: wind quality and
resource potential, generation profiles, reserve margin contribution, and capital cost calculation.
Wind Quality and Resource Potential: EPA worked with the U.S. Department of Energy's (DOE) National
Renewable Energy Laboratory (NREL), to conduct a complete update of the wind resource assumptions
for use in EPA Base Case v.5.13. The result is a complete representation of the potential onshore,
offshore (shallow and deep) wind generating capacity (in MW) broken into five wind quality classes
(described in greater detail below) in each IPM model region.Table 4-17, Table 4-18, and Table 4-19
present the onshore, offshore shallow and offshore deep wind resource assumptions that are used in
EPA Base Case v.5.13. Wind resources in EPA Base Case v.5.13 are aggregated into five wind classes,
ranging from class 3 (designated to be the least productive for wind generation) to class 7 (designated to
be the most productive for wind generation).
Table 4-17 Onshore Regional Potential Wind Capacity (MW) by Wind and Cost Class
in EPA Base Case v.5.13
IPM Region
ERC REST
ERC WEST
FRCC
MAP_WAUE
State
TX
TX
FL
MN
MT
ND
SD
Wind Class
3
4
5
6
7
3
4
5
6
7
3
3
4
3
4
5
6
7
3
4
5
6
7
3
Cost Class
1235
3,091 12,363 1,236 601,483
309 1,237 124 60,176
52 208 21 10,112
7 27 3 1,318
0.061 0.244 0.024 12
1,910 7,642 764 371,768
1,215 4,860 486 236,421
611 2,445 244 118,943
222 890 89 43,298
63 250 25 12,181
0.202 0.398 0.204 0.396
45 190 63 8,728
12 52 17 2,398
45 190 63 8,731
79 330 110 15,191
25 106 35 4,869
4 16 5 757
0.411 2 1 79
19 80 27 3,662
49 205 68 9,441
52 220 73 10,144
26 110 37 5,078
1 2 1 112
42 175 58 8,078
4-38
-------
IPM Region
MIC IA
MIS IL
MIS INKY
MIS LMI
MIS MAPP
MIS MIDA
MIC IV /I M\ A/I
State
IA
MN
IL
IN
KY
Ml
MT
ND
SD
IA
IL
Ml
MN
Wind Class
4
5
6
7
3
4
5
6
7
3
4
5
6
7
3
4
3
4
3
3
4
5
6
7
3
4
5
6
7
3
4
5
6
7
3
4
5
6
7
3
4
5
6
7
3
4
3
3
Cost Class
1235
337 1,416 472 65,220
125 526 175 24,219
35 147 49 6,746
14 58 19 2,658
834 3,503 1,168 161,316
399 1,676 559 77,184
141 593 198 27,319
40 167 56 7,676
1 3 1 131
7 31 10 1,411
24 101 34 4,660
37 155 52 7,149
30 128 43 5,891
8 35 12 1,628
10,275 25,688 14,128 78,349
39 98 54 298
8,570 19,045 17,141 50,470
420 934 840 2,475
0.054 0.120 0.108 0.318
1,620 10,798 10,798 30,774
10 67 67 190
1 3 3 10
0.201 1 1 4
0.102 1 1 2
739 3,103 1,034 142,878
633 2,660 887 122,473
391 1,644 548 75,689
148 621 207 28,585
30 126 42 5,795
462 1,940 647 89,326
1,468 6,167 2,056 283,981
1,112 4,669 1,556 215,001
556 2,336 779 107,578
105 440 147 20,282
412 1,731 577 79,691
1,141 4,792 1,597 220,646
1,171 4,920 1,640 226,544
625 2,623 874 120,798
125 525 175 24,168
509 2,138 713 98,454
419 1,759 586 81,018
333 1,398 466 64,366
165 692 231 31,867
5 21 7 990
57 241 80 11,089
0.215 1 0.301 42
1 4 1 170
1,652 6,939 2,313 319,537
4-39
-------
IPM Region
MIS MO
MIS_WUMS
NENG_CT
NENG ME
NENGREST
NY Z A&B
State
SD
Wl
IA
MO
Ml
Wl
CT
ME
MA
NH
Rl
VT
NY
Wind Class
4
5
6
7
3
4
5
6
7
3
3
3
4
5
3
4
5
6
3
4
5
6
3
3
4
5
6
7
3
4
5
6
7
3
4
5
6
7
3
4
5
3
4
5
6
7
3
4
Cost Class
1235
311 1,304 435 60,052
136 571 190 26,285
154 648 216 29,818
36 153 51 7,046
0.137 1 0.192 26
11 45 15 2,078
39 164 55 7,564
35 146 49 6,702
6 23 8 1,081
109 456 152 20,991
140 351 193 1,070
12,356 30,891 16,990 94,218
326 814 448 2,483
5 13 7 40
25 42 4 4,142
0.214 0.356 0.036 35
0.029 0.049 0.005 5
0.006 0.010 0.001 1
494 824 82 80,959
2 4 0.403 396
0.259 0.432 0.043 42
0.055 0.092 0.009 9
2 4 4 11
1,093 2,186 2,186 5,464
60 120 120 300
23 46 46 115
15 30 30 75
19 39 39 96
75 150 150 374
26 52 52 130
14 27 27 68
6 12 12 29
5 10 10 26
177 354 354 886
19 38 38 94
9 17 17 44
5 10 10 24
5 10 10 24
4 7 7 18
1113
3 5 5 13
248 496 496 1,239
24 49 49 122
10 21 21 52
6 12 12 30
6 12 12 31
2,095 2,095 2,095 4,189
4448
4-40
-------
IPM Region
NY_Z_C&E
NY_Z_D
NY_Z_F
NY_Z_G-I
NY_Z_K
PJM_AP
PJM_ATSI
PJM_COMD
PJM_Dom
State
NY
NY
NY
NY
NY
MD
PA
VA
WV
OH
IL
NC
VA
Wind Class
3
4
5
6
7
3
4
5
6
7
3
4
5
6
7
3
4
5
6
7
3
4
5
3
4
3
4
5
6
3
4
5
6
7
3
4
5
6
7
3
4
3
4
3
3
4
5
6
Cost Class
1235
1,847 1,847 1,847 3,694
19 19 19 38
4448
2224
3335
570 570 570 1,139
28 28 28 55
8 8 8 17
4447
4447
472 472 472 944
17 17 17 34
5 5 5 10
3336
4449
66 66 66 132
1113
1111
0.400 0.400 0.400 1
0.240 0.240 0.240 0.480
55 55 55 110
12 12 12 23
2225
45 101 91 267
1114
52 116 105 308
1338
1113
0.018 0.040 0.036 0.106
17 39 35 103
3 7 7 19
2 4 3 10
0.360 1 1 2
0.162 0.360 0.324 1
142 316 284 837
14 31 28 82
3 7 6 18
1226
1226
2,019 4,486 4,037 11,887
1227
9,743 21,651 19,486 57,375
99 220 198 583
34 34 34 68
71 71 71 141
5 5 5 10
2224
1111
4-41
-------
IPM Region
PJM EMAC
PJM_PENE
PJM_SMAC
PJM_West
PJM_WMAC
S C KY
S_C_TVA
S_D_AMSO
S_D_N_AR
State
DE
MD
NJ
VA
PA
MD
IN
KY
Ml
OH
TN
VA
WV
PA
KY
AL
GA
KY
NC
TN
VA
LA
AR
Wind Class
7
3
3
3
3
4
3
4
5
6
3
3
3
3
3
3
4
5
3
4
5
6
3
4
5
6
7
3
4
3
3
3
4
3
3
4
5
6
7
3
4
5
6
7
3
3
3
4
Cost Class
1235
0.120 0.120 0.120 0.240
2224
313 313 313 626
51 51 51 101
362 362 362 724
2223
415 415 415 831
16 16 16 31
2225
0.020 0.020 0.020 0.040
1112
4,353 9,674 8,707 25,637
1327
202 449 404 1,191
2,931 6,513 5,862 17,260
2 4 4 11
0.288 1 1 2
0.108 0.240 0.216 1
36 80 72 212
3 7 6 19
1339
0.297 1 1 2
4 10 9 26
0.387 1 1 2
1113
0.414 1 1 2
0.261 1 1 2
107 107 107 213
2223
10 10 10 19
10 10 10 20
7 7 7 15
0.160 0.160 0.160 0.320
0.200 0.200 0.200 0.400
31 31 31 62
6 6 6 11
3335
2224
1112
55 55 55 110
1112
1111
0.040 0.040 0.040 0.080
1111
0.080 0.080 0.080 0.160
48 192 192 529
38 152 152 417
0.495 225
4-42
-------
IPM Region
S_D_REST
S_D_WOTA
S_SOU
S_VACA
SPP_N
SPP_NEBR
SPP_SE
SPP_SPS
SPP_WEST
State
MO
AR
LA
TX
AL
GA
NC
SC
KS
MO
NE
LA
NM
OK
TX
AR
Wind Class
5
3
3
3
3
3
3
4
3
4
5
6
7
3
4
3
4
5
6
7
3
4
3
4
5
6
7
3
3
4
5
6
7
3
4
5
6
7
3
4
5
6
7
3
4
5
6
7
Cost Class
1235
0.050 0.200 0.200 1
49 196 196 539
0.220 1 1 2
10 40 40 109
98 392 392 1,079
13 13 13 26
18 18 18 35
1112
122 122 122 244
3335
1111
1112
0.340 0.340 0.340 1
48 48 48 97
0.040 0.040 0.040 0.080
1,949 8,230 3,899 202,509
2,297 9,697 4,594 238,608
2,687 11,346 5,374 279,175
1,426 6,021 2,852 148,161
211 889 421 21,880
1,021 4,312 2,043 106,102
6 25 12 619
811 3,404 1,135 156,753
1,436 6,031 2,010 277,691
1,412 5,930 1,977 273,063
738 3,100 1,033 142,746
133 559 186 25,741
0.406 2 1 55
1,128 5,318 1,612 153,108
253 1,192 361 34,322
45 210 64 6,045
20 95 29 2,724
3 15 5 433
25 117 35 3,372
123 580 176 16,699
225 1,060 321 30,520
85 398 121 11,470
32 149 45 4,296
696 3,282 995 94,481
582 2,744 831 78,989
462 2,176 659 62,645
663 3,126 947 90,002
256 1,206 365 34,718
58 273 83 7,859
1 5 2 148
0.129 1 0.184 17
0.032 0.149 0.045 4
0.022 0.102 0.031 3
4-43
-------
IPM Region
WEC_CALN
WEC_LADW
WEC_SDGE
WECC_AZ
WECC_CO
WECC_ID
WECC_IID
WECC_MT
WECC_NM
State
MO
OK
TX
CA
CA
CA
AZ
CO
ID
CA
MT
NM
Wind Class
3
3
4
5
6
7
3
3
4
5
6
7
3
4
5
6
7
3
4
5
6
7
3
4
5
3
4
5
6
7
3
4
5
6
7
3
4
5
3
4
5
6
7
3
4
5
6
7
Cost Class
1235
0.042 0.198 0.060 6
2,002 9,437 2,860 271,662
816 3,846 1,165 110,705
240 1,131 343 32,558
70 331 100 9,515
6 30 9 864
0.099 0.465 0.141 13
187 623 218 2,088
5 18 6 59
1 5 2 16
1217
0.360 1 0.420 4
111 369 129 1,235
41 137 48 460
7 22 8 75
5 18 6 59
3 12 4 39
55 183 64 613
14 47 17 159
4 13 5 44
1217
0.384 1 0.448 4
98 392 218 10,170
0.233 1 1 24
0.014 0.058 0.032 1
1,071 4,284 2,678 259,744
314 1,257 786 76,222
145 578 361 35,052
18 72 45 4,388
1 5 3 307
50 451 669 15,547
1 11 16 382
0.323 3 4 100
0.104 1 1 32
0.038 0.346 1 12
26 103 57 2,674
0.325 1 1 34
0.015 0.061 0.034 2
1,260 11,340 16,800 390,608
229 2,065 3,059 71,112
60 542 803 18,673
17 157 232 5,396
8 76 113 2,629
1,464 5,855 3,253 152,057
567 2,269 1,260 58,928
365 1,460 811 37,926
142 569 316 14,774
27 108 60 2,802
4-44
-------
IPM Region
WECC_NNV
WECC_PNW
WECC_SCE
WECC_SF
WECC_SNV
WECC_UT
WECC_WY
State
TX
NV
CA
ID
OR
WA
CA
CA
NV
UT
NE
Wind Class
3
4
5
6
7
3
4
5
6
3
4
5
6
3
4
5
6
7
3
4
5
6
7
3
4
5
6
7
3
4
5
6
7
3
4
5
6
3
4
3
4
5
6
7
4
5
6
7
Cost Class
1235
219 875 486 22,725
9 38 21 982
2 6 4 168
1 2 1 58
0.326 1 1 34
21 188 278 6,471
0.456 4 6 141
0.068 1 1 21
0.013 0.119 0.176 4
1 5 7 173
0.036 0.324 0.480 11
0.007 0.065 0.096 2
0.001 0.011 0.016 0.372
2 15 23 527
0.252 2 3 78
0.123 1 2 38
0.105 1 1 33
0.088 1 1 27
76 681 1,008 23,440
4 34 50 1,158
1 10 15 355
1 5 7 168
0.355 3 5 110
51 462 685 15,930
3 25 37 861
1 7 10 238
0.368 3 5 114
0.241 2 3 75
989 3,295 1,153 11,039
69 229 80 768
34 112 39 375
15 50 18 169
28 93 33 313
237 790 277 2,648
28 92 32 309
26 87 30 290
4 12 4 39
1 5 3 138
0.004 0.014 0.008 0.374
39 350 519 12,062
0.279 3 4 86
0.039 0.351 1 12
0.006 0.054 0.080 2
0.003 0.027 0.040 1
2 22 32 745
15 138 204 4,748
16 146 216 5,026
0.471 4 6 146
4-45
-------
IPM Region
State
SD
WY
Wind Class
3
4
5
6
7
3
4
5
6
7
Cost Class
1235
125 1,124 1,665 38,719
38 344 510 11,863
11 95 141 3,286
1 13 19 447
0.018 0.162 0.240 6
918 8,261 12,238 284,541
338 3,046 4,513 104,927
188 1,694 2,509 58,337
114 1,027 1,521 35,370
98 878 1,301 30,238
Table 4-18 Offshore Shallow Regional Potential Wind Capacity (MW) by Wind and
Cost Class in EPA Base Case v.5.13
IPM Region
ERC_REST
FRCC
MISJNKY
MIS_LMI
MIS_MNWI
MIS WUMS
NENG_CT
NENG_ME
State
TX
FL
IN
Ml
Ml
MN
Wl
Ml
Wl
CT
ME
Wind Class
3
4
5
6
3
4
3
4
5
3
4
5
6
3
4
3
3
4
3
4
5
6
7
3
4
5
6
3
4
3
4
5
Cost Class
1 2 4
850 1,700 1,700
6,423 12,846 12,846
1,079 2,158 2,158
2,625 5,251 5,251
57,921 115,842 115,842
7 13 13
63 125 125
259 517 517
85 169 169
1,739 3,478 3,478
3,784 7,567 7,567
1,899 3,799 3,799
416 831 831
118 236 236
14 29 29
134 269 269
911 1,822 1,822
141 282 282
2,275 4,550 4,550
3,095 6,189 6,189
477 953 953
59 117 117
92 185 185
525 1,049 1,049
1,472 2,944 2,944
737 1,473 1,473
84 167 167
287 574 574
162 323 323
619 1,238 1,238
419 837 837
166 331 331
4-46
-------
IPM Region
NENGREST
NY_Z_A&B
NY_Z_C&E
NY Z G-l
NY_Z_J
NY_Z_K
PJM_ATSI
PJM_COMD
PJM_Dom
PJM_EMAC
State
MA
NH
Rl
NY
NY
NY
NY
NY
OH
IL
NC
VA
DE
MD
Wind Class
6
7
3
4
5
6
7
3
4
5
3
4
5
6
3
4
5
3
4
5
3
3
4
5
3
4
5
6
3
4
5
3
4
5
6
3
4
5
6
3
4
5
6
3
4
5
3
4
Cost Class
1 2 4
234 469 469
16 33 33
181 363 363
579 1,158 1,158
661 1,321 1,321
2,307 4,615 4,615
3,112 6,224 6,224
24 48 48
52 103 103
31 62 62
43 87 87
89 177 177
85 170 170
225 449 449
205 410 410
1,092 2,184 2,184
244
249 499 499
524 1,048 1,048
255
1 1 1
46 93 93
118 237 237
488
258 517 517
881 1,763 1,763
787 1,573 1,573
1,533 3,067 3,067
173 347 347
2,628 5,256 5,256
1,261 2,523 2,523
100 200 200
267 534 534
418 836 836
244
706 1,413 1,413
2,776 5,551 5,551
3,843 7,687 7,687
553 1,107 1,107
809 1,619 1,619
979 1,958 1,958
1,313 2,626 2,626
1 1 1
214 428 428
1,079 2,159 2,159
170 340 340
1,303 2,607 2,607
1,696 3,392 3,392
4-47
-------
IPM Region
PJM_PENE
PJM_SMAC
PJM_West
S_D_AMSO
S_D_WOTA
S SOU
S_VACA
SPP_SE
WEC_CALN
WEC LADW
WECC_PNW
State
NJ
VA
PA
MD
Ml
LA
LA
TX
AL
FL
GA
MS
NC
SC
LA
CA
CA
CA
OR
WA
Wind Class
5
3
4
5
6
3
4
5
3
4
5
3
4
3
4
3
3
4
3
4
3
3
3
4
3
3
4
5
6
3
4
5
3
3
4
5
6
3
3
4
5
6
3
4
5
6
7
3
Cost Class
1 2 4
366 732 732
365 729 729
1,626 3,253 3,253
2,981 5,962 5,962
1,953 3,907 3,907
365 730 730
3,555 7,110 7,110
1,525 3,050 3,050
23 45 45
649 1,297 1,297
427 853 853
567 1,134 1,134
0.040 0.080 0.080
62 123 123
440 880 880
8,846 17,693 17,693
3,590 7,181 7,181
586 1,172 1,172
639 1,278 1,278
1,145 2,290 2,290
1,939 3,877 3,877
4,827 9,654 9,654
5,135 10,270 10,270
4,146 8,292 8,292
1,056 2,113 2,113
1,437 2,874 2,874
8,366 16,733 16,733
6,468 12,935 12,935
94 188 188
381 762 762
9,932 19,864 19,864
2,993 5,986 5,986
1,828 3,656 3,656
196 391 391
37 73 73
11 23 23
499
10 21 21
122 243 243
43 86 86
24 48 48
244
876 1,753 1,753
150 300 300
46 92 92
64 128 128
9 18 18
610 1,220 1,220
4-48
-------
IPM Region
WECC SCE
WECC SF
State
CA
CA
Wind Class
4
5
3
4
5
6
3
4
Cost Class
1 2 4
404 808 808
1 1 1
170 339 339
55 109 109
7 15 15
0.080 0.160 0.160
326 652 652
1 3 3
Table 4-19 Offshore Deep Regional Potential Wind Capacity (MW) by Wind and
Cost Class in EPA Base Case v.5.13
IPM Region
ERC_REST
FRCC
MIS INKY
MIS_LMI
MIS MNWI
MIS WUMS
NENG CT
NENG_ME
NENGREST
State
TX
FL
IN
Ml
Ml
MN
Wl
Ml
Wl
CT
ME
MA
NH
Rl
Wind Class
3
4
5
3
3
3
4
5
3
3
3
3
4
5
6
3
4
5
3
3
4
5
6
7
3
4
5
6
3
4
5
6
3
4
Cost Class
1 2 4
10,991 21,982 21,982
7,963 15,926 15,926
97 194 194
61,964 123,927 123,927
298 596 596
5,068 10,136 10,136
16,868 33,736 33,736
259 518 518
464 928 928
4,795 9,590 9,590
3,608 7,216 7,216
9,225 18,450 18,450
7,779 15,558 15,558
8,557 17,114 17,114
5,572 11,145 11,145
1,427 2,854 2,854
8,953 17,906 17,906
300 599 599
19 38 38
499 999 999
962 1,924 1,924
1,789 3,579 3,579
7,377 14,755 14,755
7,582 15,165 15,165
279 558 558
817 1,633 1,633
8,923 17,845 17,845
15,734 31,467 31,467
70 140 140
369 737 737
359 717 717
660 1,319 1,319
205 411 411
300 600 600
4-49
-------
IPM Region
NY_Z_A&B
NY_Z_C&E
NY_Z_J
NY_Z_K
PJM ATSI
PJM_COMD
PJM Dom
PJM EMAC
PJM_PENE
PJM SMAC
PJM_West
S_D_AMSO
S D WOTA
SQOI 1
SWAP A
SPP SE
WEC_CALN
State
NY
NY
NY
NY
OH
IL
NC
VA
DE
MD
NJ
VA
PA
MD
Ml
LA
LA
AL
FL
GA
MS
NC
SC
LA
CA
Wind Class
5
3
4
3
4
3
4
3
4
5
6
3
3
4
3
4
5
3
4
3
4
3
4
3
4
5
3
4
3
3
3
4
3
3
3
3
3
3
3
4
3
4
3
3
4
5
6
7
Cost Class
1 2 4
2,624 5,248 5,248
4,384 8,767 8,767
37 74 74
1,377 2,754 2,754
0.160 0.320 0.320
1 2 2
0.240 0.480 0.480
432 865 865
981 1,963 1,963
10,948 21,896 21,896
69 137 137
477
491 981 981
1,269 2,538 2,538
938 1,875 1,875
11,658 23,316 23,316
588 1,177 1,177
142 284 284
713 1,426 1,426
469 938 938
10 19 19
3,802 7,603 7,603
29 58 58
1,281 2,562 2,562
5,085 10,171 10,171
3,280 6,560 6,560
3,637 7,274 7,274
568 1,135 1,135
230 461 461
6 13 13
1,462 2,925 2,925
355 710 710
10,146 20,293 20,293
222 444 444
3,564 7,129 7,129
14,264 28,527 28,527
2,379 4,757 4,757
5 10 10
4,338 8,677 8,677
9,454 18,909 18,909
7,383 14,766 14,766
91 182 182
125 249 249
12,809 25,617 25,617
5,277 10,555 10,555
6,043 12,087 12,087
12,939 25,878 25,878
3,678 7,356 7,356
4-50
-------
IPM Region
WEC LADW
WECC_PNW
WECC SCE
WECC_SF
State
CA
CA
OR
WA
CA
CA
Wind Class
3
3
4
5
6
7
3
4
5
6
7
3
4
3
4
5
3
4
5
6
Cost Class
1 2 4
6,527 13,054 13,054
299 598 598
322 644 644
469 938 938
1,103 2,206 2,206
1,538 3,076 3,076
6,530 13,061 13,061
12,517 25,035 25,035
3,759 7,518 7,518
4,667 9,334 9,334
4,598 9,197 9,197
6,716 13,431 13,431
6,304 12,607 12,607
17,439 34,877 34,877
10,699 21,398 21,398
5,028 10,056 10,056
3,883 7,766 7,766
3,907 7,814 7,814
4,064 8,127 8,127
49 98 98
Generation Profiles: Unlike other renewable generation technologies, which dispatch on an economic
basis subject to their availability constraint, wind and solar technologies can only be dispatched when the
wind blows and the sun shines. To represent intermittent renewable generating sources like wind and
solar, EPA Base Case v.5.13 uses generation profiles which specify hourly generation patterns for a
representative day in winter and summer. Each eligible model region is provided with a distinct set of
winter and summer generation profiles for wind, solar thermal and solar photovoltaic plants.
For Hour 1 through Hour 24 the generation profile indicates the amount of generation (kWh) per MW of
available capacity. The wind generation profiles were prepared with data from NREL. This provided the
separate winter and summer generation profiles for wind classes 3-7 for onshore and offshore (shallow
and deep) generation in each IPM region. As an illustrative example, Excerpt of Table 4-20 shows the
generation profile for onshore wind in model region WECC_CO. In IPM the seasonal average "kWh of
generation per MW" (shown in the last row of the Excerpt of Table 4-20) is used to derive the generation
from a particular wind class in a specific model region.
Excerpt of Table 4-20 Representative Wind Generation Profiles in EPA Base Case v.5.13
Illustrative Hourly Wind Generation Profile (kWh of Generation per MW of Electricity)
The complete data set in spreadsheet format can be downloaded via the link found at
www.epa.qov/airmarkets/proqsreqs/epa-ipm/BaseCasev513.html
Winter Hour
01
02
03
04
05
06
Wind Class
1
410
404
400
388
366
351
2
483
478
474
462
439
423
3
504
499
497
486
465
449
4
521
517
514
504
485
471
5
539
536
533
526
511
499
Summer Hour
01
02
03
04
05
06
Wind Class
1
273
263
252
234
208
187
2
326
314
303
285
257
234
3
385
373
362
343
312
286
4
407
396
386
366
335
308
5
431
422
412
394
364
339
4-51
-------
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Winter
Average
348
355
346
331
319
317
317
319
322
319
308
309
332
369
395
410
415
413
357
419
427
420
406
394
391
388
389
389
384
373
374
399
438
467
483
488
486
428
443
448
440
426
415
412
409
410
411
405
390
389
412
450
480
497
504
505
448
467
471
463
452
443
441
440
441
441
436
423
422
444
478
503
517
522
522
472
495
500
493
483
475
474
473
475
475
471
459
458
478
506
525
536
540
540
500
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Summer
Average
170
166
159
162
175
191
202
210
216
218
215
220
241
268
284
289
286
281
224
213
206
198
204
220
238
248
255
260
261
257
262
284
313
332
341
340
335
270
263
254
243
244
254
267
273
276
279
279
275
280
306
342
370
386
392
391
310
284
276
265
267
280
293
298
300
303
303
299
304
330
367
394
408
413
412
333
315
306
294
298
312
326
332
334
336
336
330
333
357
391
417
430
435
435
362
Notes:
Based on Onshore Wind in Model Region WECC_CO.
This is an example of the wind data used in EPA Base Case v.5.13
To obtain the seasonal generation for the units in a particular wind class in a specific region, one must
multiply the installed capacity by the capacity factor (which represents the ratio of actual productivity in a
time period to the theoretical maximum in the period). Capacity factor is the average "kWh of generation
per MW from the applicable generation profile multiplied by the number of days in the time period (i.e.,
summer or winter) to obtain the level of generation. The capacity factors for wind generation that are
used in EPA Base Case v.5.13 were obtained from NREL and are shown in Table 4-21, Table 4-22,
and.Table 4-23.
Reserve Margin Contribution (also referred to as capacity credit): EPA Base Case v.5.13 uses reserve
margins, discussed in detail in Section 3.6, to model reliability. Each region has a reserve margin
requirement which is used to determine the total capacity needed to reliably meet peak demand. The
ability of a unit to assist a region in meeting its reliability requirements is modeled through the unit's
contribution to reserve margin. If the unit has 100 percent contribution towards reserve margin, then the
entire capacity of the unit is counted towards meeting the region's reserve margin requirement. However,
if any unit has less than a 100 percent contribution towards reserve margin, then only the designated
share of the unit's capacity counts towards the reserve margin requirement.
All units except those that depend on intermittent resources have 100% contributions toward reserve
margin. This means that wind and solar have limited (less than 100 percent) contributions toward reserve
margins in the EPA Base Case v.5.13.
Table 4-21, Table 4-22, and Table 4-23 present the reserve margin contributions apportioned to new wind
plants in the EPA Base Case v.5.13 as derived from AEO 2012 and NREL. NREL is the source for
capacity factors; AEO 2012 Reference Case outputs are used to develop a ratio of capacity factors to
reserve contribution. The tables show the onshore and offshore (shallow and deep) reserve margins for
each wind class.
Table 4-21 Onshore Reserve Margin Contribution an Average Capacity Factor by Wind Class
Wind Class
1
2
3
4
5
4-52
-------
Capacity Factor
Reserve Margin Contribution3
30%
20%
36%
24%
39%
26%
41%
27%
44%
29%
Note:
Reserve Margin Contribution for ERC_REST and ERC_WEST is 8.7%.
Table 4-22 Offshore Shallow Reserve Margin Contribution an
Average Capacity Factor by Wind Class
Capacity Factor
Reserve Margin Contribution3
Wind Class
1
31%
20%
2
40%
26%
3
43%
28%
4
46%
30%
5
50%
33%
Note:
Reserve Margin Contribution for ERC_REST and ERC_WEST is 8.7%.
Table 4-23 Offshore Deep Reserve Margin Contribution an
Average Capacity Factor by Wind Class
Capacity Factor
Reserve Margin Contribution3
Wind Class
1
36%
24%
2
45%
30%
3
49%
32%
4
51%
34%
5
53%
35%
Note:
a Reserve Margin Contribution for ERC_REST and ERC_WEST is 8.7%.
Capital cost calculation: EPA Base Case v.5.13 uses multipliers similar to the LT (long term) multipliers
from the Energy Information Administration's NEMS model22 to capture differences in the capital cost of
new wind capacity caused by such factors as distance from existing transmission, terrain variability, slope
and other causes of resource degradation, site accessibility challenges, population proximity, competing
land uses, aesthetics, and environmental factors. Five cost classes are used in EPA Base Case v.5.13
with class 1 having the lowest cost adjustment factor (1) and class 5 having the highest adjustment factor
(ranging from 2.00 to 2.50 depending on whether the wind resource is onshore, offshore shallow or
offshore deep), as shown in Table 4-24. To obtain the capital cost for a particular new wind model plant,
the base capital costs shown in
Revising the Long Term Multipliers in NEMS: Quantifying the Incremental Transmission Costs Due to Wind Power,
Report to ElAfrom Princeton Energy Resources International, LLC. May 2007.
4-53
-------
Table 4-16 are multiplied by the cost adjustment factor for the wind cost class applicable to the new plant.
Table 4-24 Capital Cost Adjustment Factors for New Wind Plants in Base Case v.5.13
Onshore
Offshore Deep Water
Offshore Shallow Water
Cost Class
1
1
1
1
2
1.1
1.35
1.35
3
1.25
-
-
4
2.5
2.5
5
2.00
-
-
Many factors figure in whether the model determines that adding wind capacity yields the greatest
incremental improvement in the system-wide (least cost) solution available to the model at a particular
point in the solution process. These factors include trade-offs between such items as the cost, capacity
factor, reserve margin contribution, and dispatch capabilities and constraints on the new wind capacity
relative to other choices. However, to perform its trade-off computations, the model requires the values
described above.
As an illustrative example, Table 4-25 shows the calculations that would be performed to derive the
potential electric generation, reserve margin contribution, and cost of new (potential) onshore capacity in
wind class 3, cost class 2 in the WECC_CO model region in run year 2020.
Table 4-25 Example Calculations of Wind Generation Potential, Reserve Margin Contribution, and
Required Data
Table 4-17 Potential wind capacity (C) = 578 MW
Table 4-20 Winter average generation (Gw) per available MW = 448 kWh/MW
Table 4-20 Summer average generation (Gs) per available MW = 310kWh/MW
Hours in Winter (Hw) season (October - April) = 5,088 hours
Hours in Summer (Hs)season (May - September) = 3,672 hours
Table 4-21 Reserve Margin Contribution (RM) WECC_CO, Wind Class 3 = 26 percent
Table 4-16 Capital Cost (Cap2o2o) in vintage range for year 2020 = $2,220/kW
Table 4-24 Capital Cost Adjustment Factor (CAFON,c2) for onshore cost class 2 = 1.1
Table4-15 Regional Factor(RF) 1.033
Calculations
Generation Potential = Cx Gw *HW + C xGs xH s
= 578MW x 448 kWh/MWx 5088 hours +
578MW x3WkWh/MWx3672hours
= l,975GWh
ReserveMarginContribition = RMxC
= 26%x578MFF
= 149 MW
Capital Cost = Cap 2020 x CAP ON a x RF x C
= $2,220/kW x 1.1 x 1.033 x
= $1,458,055
Capital Cost for Onshore Wind in WECC_CO at Wind Class 3, Cost Class 2
4-54
-------
Solar Generation
EPA Base Case v.5.13 includes solar PV and solar thermal generation technologies. The following
sections describe four key aspects of the representation of solar generation: solar resource potential,
generation profiles, reserve margin contribution, and capital cost calculation.
Solar Resource Potential: The resource potential estimates for solar PV and solar thermal technologies
were developed by NREL by model region and state. These are summarized in Table 4-26 and
4-55
-------
Table 4-27.
Table 4-26 Solar PV Regional Potential Capacity (MW) in EPA Base Case v.5.13
Model Region
FRCC
ERC REST
ERC WEST
MAP_WAUE
MISJA
MIS IL
MISJNKY
MIS LMI
MIS_MAPP
MIS_MIDA
MIS_MNWI
MIS_MO
MIS_WUMS
NENG CT
NENG ME
NENGREST
NY Z A&B
NY Z C&E
NY Z D
NY Z F
NY Z G-l
NY Z J
NY Z K
PJM_AP
State
FL
TX
TX
MN
MT
ND
SD
IA
MN
IL
IN
KY
Ml
MT
ND
SD
IA
IL
Ml
MN
SD
Wl
IA
MO
Ml
Wl
CT
ME
MA
NH
Rl
VT
NY
NY
NY
NY
NY
NY
NY
MD
PA
VA
WV
Class
1
2 3 4
5 6
466,717 2,016,007 2
5,330,140 6,734,722 17,494
4,352,761 1,172,478 1,508,010 960,326
13,256
846
97,901
177,744
248,206
991,602
2,792,414
205,901
-
-
3,840,608
1 1 ,692
1,187,823
575,717
2,660,403
454,286
1,910,779
2,526,463
5,813,548
5,361,555
-
__
-
2,636,683
151,384
38,128
1,628,979
215,333
32,825
5,292,787
167,192
1,174,605
-
52,502
2,718,802
437,954
541,446
6,300
1,174,023
30,548
34,503
49
88,147
321,929
482,549
223,636
82,765
5,299
465,821
2,293,924
74,375
305,524
118,009
101,436
34,073
11,168
152,829
176,823
75,990
64,662
58,250
-
__
-
__
676
25,646
2,017
76,636
7,588
59,871
78,377
122,956
76,925
-
4-56
-------
Model Region State
OH
PJM ATSI
PA
PJM COMD IL
PJM Dom NC
VA
DE
MD
PJM_EMAC NJ
PA
VA
PJM PENE PA
no
PJM SMAC uu
MD
IN
KY
Ml
PJM_West OH
TN
VA
WV
PJM WMAC PA
KY
S_C_KY OH
VA
AL
GA
KY
S_C_TVA MS
NC
TN
VA
S D AMSO LA
S D N AR AR
MO
AR
S_D_REST LA
MS
S D WOTA LA
TX
AL
S SOU FL
GA
MS
GA
S_VACA NC
SC
SPP_N KS
Class
1234
474,342 869,085
151,543 2,456
5 6
-
546 1,576,218
441,910
1,742,725
175,165
329,397
183 316,902
146,075
53,494
276,816 30,194
35
180,702
11,570 745,754
18,542
52,303 87,422
88,741 1,452,563
684
155,747
272 28,898
72,963 208,057
816,227
10,749
3
591,879
71,479
736,215
1,174,913
7,785
2,239,778
5,167
271,634 8,334
1,619,623
807,954
716,350
1,131,420
1,951,363
214,557 252
627,283
3,052,382 60,455
493,841 86,080
3,322,002 986,103
948,473 2,612
23,380
2,773,996
2,110,013 123,622
3,558,781 5,141,266 280
4-57
-------
Model Region
SPP NEBR
SPP SE
SPP_SPS
SPP_WEST
WEC CALN
WEC LADW
WEC SDGE
WECC AZ
WECC CO
WECC ID
WECC II D
WECC MT
WECC_NM
WECC NNV
WECC_PNW
WECC SCE
WECC SF
WECC SNV
WECC UT
WECC_WY
State
MO
NE
LA
NM
OK
TX
AR
LA
MO
OK
CA
CA
CA
AZ
CO
ID
CA
MT
NM
TX
NV
CA
ID
OR
WA
CA
CA
NV
UT
NE
SD
WY
Class
1 2
1,721,823
4,965,449
1,122,714
-
1,206,494
123,494
3,278
2,497,664
5 17,827
190
71,601
531,421
__
3
1,966,681
731
452,416
1,263,287
3,662,342
1,686,553
1,721
3,150
4,752,161
2,050,967
__
4
109,326
198,521
1,705,702
-
252,117
2,111
4,613
4,413
608,847
1,822
5
1,514,976
4,648
653,658
-
76,837
11,541
2,169
173,124
210,420
294
6
698,712
-
15,751
125,266
48,580
6,915,162
171,178
351,868
1,211 4,618,469
-
343
3,935
137,335
90,067 700,240
310,047 1,361,856
1 ,638
2,481
25,168
2,079,313
413,255
2,032,709
3,472
191,598
114,703
432,099
896,221
-
276,918
999
1,882,143
7,033
587,765
-
61,789
__
4,735,551
521,127
1,587,307
-
1,474,690
__
201,386
3,040
437,434
1,828,509
1,896,010
110,382
47,535
3,173,479
751,291
-
521,256
-
275,303
-
4-58
-------
Table 4-27 Solar Thermal Regional Potential Capacity (MW) in EPA Base Case v.5.13
Model
Region
FRCC
ERC REST
ERC WEST
MIS_MAPP
S_SOU
S VACA
SPP N
SPP NEBR
SPP_SPS
SPP WEST
WEC CALM
WEC LADW
WEC SDGE
WECC AZ
WECC CO
WECC ID
WECC IID
WECC MT
WECC_NM
WECC NNV
WECC_PNW
WECC SCE
WECC SF
WECC SNV
WECC UT
WECC_WY
State
FL
TX
TX
MT
ND
SD
AL
FL
SC
KS
NE
NM
OK
TX
OK
CA
CA
CA
AZ
CO
ID
CA
MT
NM
TX
NV
CA
ID
OR
WA
CA
CA
NV
UT
NE
SD
WY
Class
1
95,433
2,115,870
2,659,629
2
740
1,949,748
3 i.
__
__
4,854
I 5
_
_
_
298,407
23,728
834,490
41
1,740
322
3,918,845
74,124
__
_
2,195,753
187,119
411,642
1,448,536
215,536
1,842,654
957
-
2,119,578
1,040,697
566
1,755
1,634,219
1,351,218
1,292
223,718
8,894
5,221
43,388
1,546,981
73,561
24,647
24
_
9,262 12,719 48,426
4,542 10,439 1,001
420,953 1,953,964 1,203,911
110,412 99,734 2,319
__
42,366 121
_
604 34,391
544,703
26,098
213,922
89,511
262
1,097,342
436,316
307,385
80,914
571,368
68,643
191,888
1,976,069
991,156
64,109
1,493,428
135,681
46,192
74,751
450
7,080
1,056,308
102,883
1,051,211 1,072,218 325,541
225,279 3,306
209,881 208
-
65,694 130
__
912 448,126
-
995 512,927
_
4,996 25,427 49,166
114,414 64,245 1,491
-
-
Generation profiles: Like wind, solar is an intermittent renewal technology. Since it can only be dispatched
when the sun shines, not on a strictly economic basis, it is represented in EPA Base Case v.5.13 with
generation profiles which specify hourly generation patterns for typical winter and summer days in each
eligible region. The generation profiles were prepared with data from NREL which provided separate
winter and summer generation profiles for solar thermal and photovoltaic in each eligible IPM region. As
an illustrative example,
4-59
-------
Excerpt of Table 4-28 shows the solar thermal and solar photovoltaic winter and summer generation
profiles in model region WECC_AZ.
4-60
-------
Excerpt of Table 4-28 Representative Solar Generation Profiles in EPA Base v.5.13
Illustrative Hourly Solar Generation Profile (kWh of Generation per MW of Electricity)
The complete data set in spreadsheet format can be downloaded via the link found at
www.epa.qov/airmarkets/proqsreqs/epa-ipm/BaseCasev513.html
Winter Hour
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Winter
Average
Solar
Thermal
0
0
0
0
0
0
70
481
869
937
856
819
832
909
987
761
245
2
0
0
0
0
0
0
324
Solar
Photovoltaic
0
0
0
0
0
446
446
446
446
446
446
446
552
552
552
552
64
64
64
64
64
0
0
0
236
Summer Hour
01
02
03
04
05
06
07
08
09
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
Summer
Average
Solar
Thermal
0
0
0
0
0
4
702
1348
1446
1468
1418
1383
1317
1295
1261
1212
962
273
0
0
0
0
0
0
587
Solar
Photovoltaic
3
3
3
3
3
574
574
574
574
574
574
574
600
600
600
600
155
155
155
155
155
3
3
3
301
Note:
Based on model region WECC_AZ.
This is an example of the solar data used in EPA Base Case v.5.13
Reserve margin contribution:
4-61
-------
Table 4-29 presents the annual average capacity factors (CFs) and reserve margin contributions by
model region for new solar thermal and photovoltaic units in EPA Base Case v.5.13. The state specific
capacity factors included in this table are from NREL and the associated reserve margin contribution
estimates are based on AEO 2012 projections. NREL is the source for capacity factors; AEO 2012
Reference Case outputs are used to develop a ratio of capacity factors to reserve contribution.
4-62
-------
Table 4-29 Solar Photovoltaic Reserve Margin Contribution and Average Capacity Factor by State
and Solar Thermal Reserve Margin Contribution and Average Capacity Factor by Class
State
Alabama
Alaska
Arizona
Arkansas
California
Colorado
Connecticut
Delaware
Florida
Georgia
Hawaii
Idaho
Illinois
Indiana
Iowa
Kansas
Kentucky
Louisiana
Maine
Maryland
Massachusetts
Michigan
Minnesota
Mississippi
Missouri
Montana
Nebraska
Nevada
New Hampshire
New Jersey
New Mexico
New York
North Carolina
North Dakota
Ohio
Oklahoma
Oregon
Pennsylvania
Rhode Island
South Carolina
South Dakota
Tennessee
Texas
Utah
Vermont
Virginia
Washington
West Virginia
Wisconsin
Wyoming
Solar Photovoltaic
Average Capacity
Factor
20%
11%
26%
21%
25%
26%
18%
19%
21%
20%
21%
22%
19%
18%
20%
24%
19%
20%
19%
18%
18%
17%
19%
20%
19%
21%
22%
26%
18%
20%
26%
18%
21%
20%
17%
22%
23%
18%
18%
20%
21%
20%
22%
25%
18%
20%
20%
17%
18%
23%
Reserve Margin
Contribution
23%
12%
30%
24%
29%
30%
21%
21%
24%
23%
24%
25%
21%
21%
23%
27%
21%
22%
22%
20%
21%
20%
22%
22%
22%
24%
25%
30%
21%
23%
30%
21%
23%
23%
20%
25%
26%
20%
20%
23%
24%
23%
25%
28%
20%
23%
23%
20%
21%
26%
Solar
Class
1
2
3
4
5
Solar Thermal
Average Capacity
Factor
32%
39%
43%
43%
45%
Reserve Margin
Contribution
39%
49%
53%
54%
56%
4-63
-------
Geothermal Generation
Geothermal Resource Potential: Ten model regions in EPA Base Case v.5.13 have geothermal potential.
The potential capacity in each of these regions is shown in Table 4-30. The values are based on AEO
2013 data.
Table 4-30 Regional Assumptions on Potential Geothermal Electric Capacity
IPM Model Region
WEC CALN
WEC LADW
WECC AZ
WECCJID
WECC NM
WECC NNV
WECC PNW
WECC SCE
WECC SF
WECC_UT
Total
Capacity (MW)
191
83
70
5,058
292
820
1,069
621
579
127
8,910
Notes:
This data is a summary of the geothermal data used in EPA Base Case v.5.13.
Cost Calculation: EPA Base Case v.5.13 does not contain a single capital cost, but multiple
geographically-dependent capital costs for geothermal generation. The assumptions for geothermal were
developed using AEO 2013 cost and performance estimates for 100 known sites. Both dual flash and
binary cycle technologies23 were represented. In EPA Base Case v.5.13 the 100 sites were aggregated
into 62 different options based on geographic location and cost and performance characteristics of
geothermal sites in each of the ten eligible IPM regions where geothermal generation opportunities exist.
Table 4-31 shows the potential geothermal capacity and cost characteristics for applicable model regions.
Table 4-31 Potential Geothermal Capacity and Cost Characteristics by Model Region
IPM Region
WEC_CALN
WEC_LADW
Capacity
(MW)
5
6
6
9
11
13
16
16
19
29
29
32
10
73
Capital Cost
(2011$)
24,731
20,629
29,144
20,017
14,841
17,615
5,051
10,073
1 1 ,692
4,495
7,613
9,122
10,361
7,200
FO&M
(2011$/kW-yr)
822
920
791
572
493
487
221
352
348
161
315
282
324
196
In dual flash systems, high temperature water (above 400ฐF) is sprayed into a tank held at a much lower pressure
than the fluid. This causes some of the fluid to "flash," i.e., rapidly vaporize to steam. The steam is used to drive a
turbine, which, in turn, drives a generator. In the binary cycle technology, moderate temperature water (less than
400ฐF) vaporizes a secondary, working fluid which drives a turbine and generator. Due to its use of more plentiful,
lower temperature geothermal fluids, these systems tend to be most cost effective and are expected to be the most
prevalent future geothermal technology.
4-64
-------
IPM Region
WECC_AZ
WECCJID
WECC_NM
WECC_NNV
WECC_PNW
WECC_SCE
WECC_SF
WECC_UT
Capacity
(MW)
26
44
10
19
38
72
84
88
128
135
347
359
1,866
1,912
9
11
24
62
186
66
78
93
152
431
9
18
19
36
38
81
101
113
124
264
266
7
8
11
32
274
289
14
17
35
240
273
52
75
Capital Cost
(2011$)
29,114
27,769
14,320
9,217
1 1 ,395
4,999
8,041
6,930
8,349
4,082
3,533
2,735
7,447
6,581
23,780
28,310
18,793
6,998
4,016
3,366
2,602
4,080
4,387
5,247
24,402
24,198
17,474
15,350
20,609
9,215
7,760
3,481
2,654
4,408
4,074
19,885
23,338
16,931
19,802
3,091
2,196
24,018
28,523
12,225
4,495
2,713
2,684
4,049
FO&M
(2011$/kW-yr)
1,001
652
434
351
360
203
230
244
234
139
116
96
118
104
756
714
481
197
103
142
119
139
194
187
986
653
535
490
620
252
237
119
110
126
93
705
643
553
586
119
113
775
737
417
136
115
132
147
4-65
-------
Landfill Gas Electricity Generation
Landfill Gas Resource Potential: Estimates of potential electric capacity from landfill gas are based on
the AEO 2012 inventory. EPA Base Case v.5.13 represents three categories of potential landfill gas
units; "high", "low", and "very low". The categories refer to the amount and rate of methane production
from the existing landfill site. Table 4-32 summarizes potential electric capacity from landfill gas used in
EPA Base Case v.5.13.
There are several things to note about Table 4-32. The AEO 2012 NEMS region level estimates of the
potential electric capacity from new landfill gas units are disaggregated to IPM regions based on
electricity demand. The limits listed in Table 4-32 apply to the IPM regions indicated in column 1. In EPA
Base Case v.5.13 the new landfill gas electric capacity in the corresponding IPM regions shown in column
1 cannot exceed the limits shown in columns 3-5. As noted earlier, the capacity limits for three categories
of potential landfill gas units are distinguished in this table based on the rate of methane production at
three categories of landfill sites: LGHI = high rate of landfill gas production, LGLo = low rate of landfill gas
production, and LGLVo = very low rate of landfill gas production. The values shown in Table 4-32
represent an upper bound on the amount of new landfill capacity that can be added in each of the
indicated model regions and states for each of the three landfill categories.
The cost and performance assumptions for adding new capacity in each of the three landfill categories
are presented in
4-66
-------
Table 4-16.
Table 4-32 Regional
from
Assumptions on Potential Electric Capacity
New Landfill Gas Units (MW)
IPM Region
ERC REST
ERC WEST
FRCC
MAP_WAUE
MISJA
MIS IL
MISJNKY
MIS_LMI
MIS_MAPP
MIS_MIDA
MIS_MNWI
MIS_MO
MIS_WUMS
NENG CT
NENG ME
NENGREST
NY Z A&B
NY_Z_C&E
NY_Z_D
NY Z F
NY Z G-l
NY_Z_J
NY_Z_K
PJM_AP
PJM_ATSI
State
TX
TX
FL
MN
MT
ND
SD
IA
MN
IL
IN
KY
Ml
MT
ND
SD
IL
IA
Ml
MN
SD
Wl
IA
MO
Ml
Wl
CT
ME
MA
NH
Rl
VT
NY
NY
NY
NY
NY
NY
NY
MD
PA
VA
WV
OH
Class
LGHI
12
1
16
0
0
0
0
0
0
12
9
0
7
0
0
0
0
0
0
1
0
0
0
10
0
10
6
2
11
2
1
1
5
5
1
2
4
13
5
0
3
0
1
7
LGLo
19
1
24
0
0
1
2
3
0
18
14
1
11
0
0
0
0
5
0
13
0
2
0
15
1
17
9
3
17
3
2
1
8
8
2
3
6
20
8
1
4
0
1
11
LGLVo
296
23
159
3
0
5
9
16
0
99
103
7
97
0
4
2
0
23
0
59
2
9
0
83
6
99
14
4
25
5
4
2
19
17
4
8
14
43
17
7
33
4
12
77
4-67
-------
IPM Region
PJM_COMD
PJM_Dom
PJM_EMAC
PJM_PENE
PJM_SMAC
PJM_West
PJM_WMAC
S_C_KY
S_C_TVA
S D AMSO
S_D_N_AR
S_D_REST
S_D_WOTA
S_SOU
S_VACA
SPP_N
SPP_NEBR
State
PA
IL
NC
VA
DE
MD
NJ
PA
VA
PA
MD
DC
IN
KY
Ml
OH
TN
VA
WV
PA
KY
OH
VA
AL
GA
KY
MS
NC
TN
VA
LA
AR
MO
AR
LA
MS
LA
TX
AL
FL
GA
MS
GA
NC
SC
KS
MO
NE
Class
LGHI
0
11
0
3
1
0
12
6
0
2
8
1
3
1
0
12
0
2
2
8
2
0
0
1
0
0
0
0
6
0
0
0
0
0
0
0
0
0
2
0
6
0
0
5
2
0
0
0
LGLo
0
17
0
5
1
1
18
10
0
3
12
1
5
2
0
18
0
3
3
12
3
0
0
1
0
0
1
0
8
0
1
1
0
0
1
1
0
1
3
0
8
0
0
8
4
0
0
6
LGLVo
6
122
2
46
9
7
92
52
0
19
65
8
37
14
6
133
0
26
23
64
27
0
0
13
4
8
10
2
77
0
12
11
4
1
9
9
2
9
30
8
77
7
1
73
37
36
28
26
4-68
-------
IPM Region
SPP SE
SPP_SPS
SPP_WEST
WEC_CALN
WEC_LADW
WEC SDGE
WECC AZ
WECC CO
WECCJD
WECCJID
WECC MT
WECC_NM
WECC_NNV
WECC_PNW
WECC SCE
WECC SF
WECC SNV
WECC_UT
WECC_WY
State
LA
NM
OK
TX
AR
LA
MO
OK
TX
CA
CA
CA
AZ
CO
ID
CA
MT
NM
TX
NV
CA
ID
OR
WA
CA
CA
NV
UT
NE
SD
WY
Class
LGHI
0
0
0
0
0
0
0
1
0
64
14
11
0
0
2
0
1
0
0
1
0
0
5
10
61
3
0
3
0
0
0
LGLo
0
0
0
0
0
0
0
1
0
97
22
17
0
0
3
0
1
0
0
1
0
0
8
15
92
4
0
5
0
0
0
LGLVo
11
5
0
17
24
4
0
59
5
306
70
55
40
27
15
0
7
6
2
8
0
3
41
73
291
15
9
26
0
1
5
4.5 Nuclear Units
4.5.1 Existing Nuclear Units
Population, Plant Location, and Unit Configuration: To provide maximum granularity in forecasting the
behavior of existing nuclear units, all 104 nuclear units in EPA Base Case v.5.13 are represented by
separate model plants. As noted in Table 4-7 the 104 nuclear units include 100 currently operating units
plus Watts Bar Nuclear Plant (Unit 2), Vogtle (Units 3&4), and V C Summer (Units 2&3), which are
scheduled to come online during 2015 - 2018. All are listed in Table 4-34. The population characteristics,
plant location, and unit configuration data in NEEDS v.5.13 were obtained primarily from EIA Form 860
andAE02013.
Capacity: Nuclear units are baseload power plants with high fixed (capital and fixed O&M) costs and low
variable (fuel and variable O&M) costs. Due to their low VOM and fuel costs, nuclear units are run to the
maximum extent possible, i.e., up to their availability. Consequently, a nuclear unit's capacity factor is
equivalent to its availability. Thus, EPA Base Case v.5.13 uses capacity factor assumptions to define the
upper bound on generation from nuclear units. Nuclear capacity factor assumptions in EPA Base Case
4-69
-------
v.5.13 are based on an Annual Energy Outlook projection algorithm. The nuclear capacity factor
projection algorithm is described below:
For each reactor, the capacity factor over time is dependent on the age of the reactor.
Capacity factors increase initially due to learning, and decrease in the later years due to aging.
For individual reactors, vintage classifications (older and newer) are used.
For the older vintage (start before 1982) nuclear power plants, the performance peaks at 25 years:
Before 25 years: Performance increases by 0.5 percentage point per year;
25-60 years: Performance remains flat; and
For the newer vintage (start in or after 1982) nuclear power plants, the performance peaks at 30
years:
Before 30 years: Performance increases by 0.7 percentage points per year;
30-60 years: Performance remains flat; and
The maximum capacity factor is assumed to be 90 percent. That is, any given reactor is not allowed
to grow to a capacity factor higher than 90 percent. However, if a unit began with a capacity factor
above 90 percent, it is allowed to retain that capacity factor. Given that some units' historical capacity
factors are above 90 percent, the projected capacity factors range from 60 percent to 96 percent.
Cost and Performance: Unlike non-nuclear existing conventional units discussed in section 4.2.7,
emission rates are not needed for nuclear units, since there are no SO2, NOX, CO2, or mercury emissions
from nuclear units.
As with other generating resources, EPA Base Case v.5.13 uses variable operation and maintenance
(VOM) costs and fixed operation and maintenance (FOM) costs to characterize the cost of operating
nuclear units. The heat rate, FOM, and VOM values from AEO 2013, which were used to characterize
the cost and performance of existing nuclear units in EPA Base Case v.5.13 are shown in Table 4-34.
EPA Base Case v.5.13 also incorporates the planned nuclear capacity uprates sourced from AEO 2013
and EPA research. These are shown in Table 4-33.
Table 4-33 Nuclear Upratings (MW) as Incorporated in EPA Base Case v.5.13
Name
Fort Calhoun
McGuire
McGuire
Plant ID
2289
6038
6038
Unit ID
1
1
2
Year
2017
2013
2013
Change in MWs
75
18.7
18.7
4.5.2 Potential Nuclear Units
The cost and performance assumptions for nuclear potential units that the model has the option to build in
EPA Base Case v.5.13 are shown in Table 4-13 above. The cost assumptions are from AEO 2013.
Table 4-34 Characteristics of Existing Nuclear Units
Region
ERC_REST
State
Texas
Plant Name
Comanche Peak
Comanche Peak
South Texas Project
South Texas Project
On-
Unique Line Capacity Heat Rate
ID Year (MW) (Btu/kWh)
6145_1 1990 1,205 10,460
6145_2 1993 1,195 10,460
6251_1 1988 1,280 10,460
6251_2 1989 1,280 10,460
FOM VOM
(2011$ (2011
/kW-yr) mills/kWh)
182.1 0.18
182.1 0.18
199.2 0.18
199.2 0.18
4-70
-------
Region
FRCC
MISJA
MISJL
MIS_LMI
MIS_MNWI
MIS_MO
MIS_WUMS
NENG_CT
NENGREST
NY_Z_A&B
NY_Z_C&E
NY_Z_G-I
PJM_ATSI
PJM_COMD
PJM_Dom
PJM_EMAC
PJM_SMAC
PJM_West
PJM_WMAC
State
Florida
Iowa
Illinois
Michigan
Minnesota
Missouri
Wisconsin
Connecticut
Massachusetts
New Hampshire
New York
New York
New York
Ohio
Illinois
Virginia
New Jersey
Pennsylvania
Maryland
Michigan
Pennsylvania
Pennsylvania
Plant Name
St Lucie
St Lucie
Turkey Point
Turkey Point
Duane Arnold Energy Center
Clinton Power Station
Fermi
Palisades
Monticello
Prairie Island
Prairie Island
Callaway
Point Beach Nuclear Plant
Point Beach Nuclear Plant
Millstone
Millstone
Pilgrim Nuclear Power Station
Seabrook
R E Ginna Nuclear Power Plant
James A Fitzpatrick
Nine Mile Point Nuclear Station
Nine Mile Point Nuclear Station
Indian Point 2
Indian Point 3
Davis Besse
Perry
Braidwood Generation Station
Braidwood Generation Station
Byron Generating Station
Byron Generating Station
Dresden Generating Station
Dresden Generating Station
LaSalle Generating Station
LaSalle Generating Station
Quad Cities Generating Station
Quad Cities Generating Station
North Anna
North Anna
Surry
Surry
Oyster Creek
PSEG Hope Creek Generating Station
PSEG Salem Generating Station
PSEG Salem Generating Station
Limerick
Limerick
Peach Bottom
Peach Bottom
Calvert Cliffs Nuclear Power Plant
Calvert Cliffs Nuclear Power Plant
Donald C Cook
Donald C Cook
Beaver Valley
Beaver Valley
PPL Susquehanna
On-
Unique Line Capacity Heat Rate
ID Year (MW) (Btu/kWh)
6045_1 1976 961 10,460
6045_2 1983 949 10,460
621_3 1972 802 10,460
621_4 1973 802 10,460
1060_1 1975 601 10,460
204_1 1987 1,065 10,460
1729_2 1988 1,085 10,460
1715_1 1972 803 10,460
1922_1 1971 633 10,460
1925_1 1974 594 10,427
1925_2 1974 592 10,427
6153_1 1984 1,190 10,460
4046_1 1970 591 10,460
4046_2 1972 593 10,460
566_2 1975 869 10,460
566_3 1986 1,233 10,460
1590_1 1972 685 10,460
6115_1 1990 1,246 10,460
6122_1 1970 581 10,460
6110_1 1976 828 10,460
2589_1 1969 630 10,460
2589_2 1987 1,143 10,460
2497_2 1973 1,006 10,460
8907_3 1976 1,031 10,460
6149_1 1977 894 10,460
6020_1 1987 1,256 10,460
6022_1 1988 1,178 10,460
6022_2 1988 1,152 10,460
6023_1 1985 1,164 10,460
6023_2 1987 1,136 10,460
869_2 1970 867 10,460
869_3 1971 867 10,460
6026_1 1984 1,118 10,427
6026_2 1984 1,120 10,427
880_1 1972 908 10,460
880_2 1972 911 10,460
6168_1 1978 943 10,460
6168_2 1980 943 10,460
3806_1 1972 838 10,427
3806_2 1973 838 10,427
2388_1 1969 614 10,460
6118_1 1986 1,173 10,460
2410_1 1977 1,166 10,460
2410_2 1981 1,160 10,460
6105_1 1986 1,146 10,460
6105_2 1990 1,150 10,460
3166_2 1974 1,122 10,460
3166_3 1974 1,122 10,460
601 1_1 1975 855 10,460
601 1_2 1977 850 10,460
6000_1 1975 1,009 10,460
6000_2 1978 1,060 10,460
6040_1 1976 921 10,460
6040_2 1987 914 10,460
6103 1 1983 1,260 10,460
FOM VOM
(2011$ (2011
/kW-yr) mills/kWh)
160.8 0.15
160.8 0.15
227.2 0.21
227.2 0.21
187.5 0.18
199.2 0.18
178.8 0.18
200.3 0.18
251.6 0.25
173.8 0.88
173.8 0.89
124.4 0.12
203.6 0.18
203.6 0.18
194.4 0.19
180.2 0.19
225.7 0.18
199.2 0.19
216.8 0.18
216.1 0.18
204.2 0.18
199.2 0.18
207.2 0.18
194.9 0.18
180.2 0.20
186.6 0.63
194.1 0.18
194.1 0.18
194.3 0.17
194.3 0.17
212.4 0.17
212.4 0.18
169.1 0.80
169.1 0.82
197.0 0.17
197.0 0.18
114.1 0.10
114.1 0.11
129.2 0.62
129.2 0.61
225.4 0.19
180.2 0.18
199.2 0.18
199.2 0.18
199.9 0.17
199.9 0.17
198.7 0.18
198.7 0.17
199.2 0.18
199.2 0.17
150.6 0.24
150.6 0.14
229.6 0.56
229.6 0.57
186.3 0.20
4-71
-------
Region
S_C_TVA
S_D_AMSO
S_D_N_AR
S_D_REST
S_SOU
S_VACA
SPP_N
SPP_NEBR
WEC_CALN
WECC_AZ
WECC_PNW
State
Alabama
Tennessee
Louisiana
Arkansas
Louisiana
Mississippi
Alabama
Georgia
North Carolina
South Carolina
Kansas
Nebraska
California
Arizona
Washington
Plant Name
PPL Susquehanna
Three Mile Island
Browns Ferry
Browns Ferry
Browns Ferry
Sequoyah
Sequoyah
Watts Bar Nuclear Plant
Watts Bar Nuclear Plant
Waterford 3
Arkansas Nuclear One
Arkansas Nuclear One
River Bend
Grand Gulf
Joseph M Farley
Joseph M Farley
Edwin 1 Hatch
Edwin 1 Hatch
Vogtle
Vogtle
Vogtle
Vogtle
Brunswick
Brunswick
Harris
McGuire
McGuire
Catawba
Catawba
H B Robinson
Oconee
Oconee
Oconee
V C Summer
V C Summer
V C Summer
Wolf Creek Generating Station
Cooper
Fort Calhoun
Diablo Canyon
Diablo Canyon
Palo Verde
Palo Verde
Palo Verde
Columbia Generating Station
On-
Unique Line Capacity Heat Rate
ID Year (MW) (Btu/kWh)
6103_2 1985 1,260 10,460
801 1_1 1974 805 10,460
46_1 1974 1,101 10,460
46_2 1975 1,104 10,460
46_3 1977 1,105 10,460
6152_1 1981 1,152 10,460
6152_2 1982 1,126 10,460
7722_1 1996 1,123 10,460
7722_2 2015 1,122 10,460
4270_3 1985 1,159 10,460
8055_1 1974 834 10,460
8055_2 1980 989 10,460
6462_1 1986 974 10,460
6072_1 1985 1,368 10,460
6001_1 1977 874 10,460
6001_2 1981 860 10,460
6051_1 1975 876 10,460
6051_2 1979 883 10,460
649_1 1987 1,150 10,460
649_2 1989 1,152 10,460
649_3 2017 1,100 10,400
649_4 2018 1,100 10,400
601 4_1 1977 938 10,460
601 4_2 1975 932 10,460
601 5_1 1987 900 10,460
6038_1 1981 1,100 10,460
6038_2 1984 1,100 10,460
6036_1 1985 1,129 10,460
6036_2 1986 1,129 10,460
3251_2 1971 724 10,460
3265_1 1973 846 10,460
3265_2 1974 846 10,460
3265_3 1974 846 10,460
6127_1 1984 966 10,460
6127_2 2017 1,100 10,400
6127_3 2018 1,100 10,400
210_1 1985 1,175 10,460
8036_1 1974 766 10,460
2289_1 1973 479 10,460
6099_1 1985 1,122 10,460
6099_2 1986 1,118 10,460
6008_1 1986 1,311 10,460
6008_2 1986 1,314 10,460
6008_3 1988 1,312 10,460
371_2 1984 1,097 10,460
FOM VOM
(2011$ (2011
/kW-yr) mills/kWh)
186.3 0.18
194.3 0.18
199.2 0.19
199.2 0.19
199.2 0.20
210.3 0.18
210.3 0.18
198.0 0.18
137.0 2.16
180.1 0.13
161.7 0.13
161.7 0.12
163.2 0.17
158.2 0.13
149.5 0.14
149.5 0.14
133.2 0.14
133.2 0.14
111.3 0.09
111.3 0.09
112.9 2.16
112.9 2.16
155.7 0.14
155.7 0.14
186.9 0.16
137.5 0.11
137.5 0.11
137.7 0.13
137.7 0.12
142.2 0.16
137.0 0.13
137.0 0.12
137.0 0.12
170.6 0.17
112.9 2.16
112.9 2.16
159.6 0.16
199.2 0.18
187.2 0.18
169.8 0.18
169.8 0.18
236.2 0.23
236.2 0.23
236.2 0.23
202.3 0.19
Excerpt from Table 4-35 Capacity Not Included Based on EIA Form 860 - Existing Units
This is a small excerpt of the data in Excerpt from Table 4-35. The complete data set in spreadsheet
format can be downloaded via the link found at http://www.epa.gov/airmarkets/proqsreqs/epa-
ipm/BaseCasev513.html.
Plant Name
Hospira Inc
ORIS
Plant
Code
55788
Unit
ID
GEN1
Plant Type
Combustion Turbine
State Name
New York
Capacity
(MW)
1.1
Notes
Dropped - Onsite Unit
4-72
-------
Plant Name
Hospira Inc
AG Processing Inc
Oxford Cogeneration Facility
Oxford Cogeneration Facility
South Belridge Cogeneration Facility
South Belridge Cogeneration Facility
South Belridge Cogeneration Facility
Lost Hills Cogeneration Plant
Lost Hills Cogeneration Plant
Lost Hills Cogeneration Plant
AES Hawaii
Agrium Kenai Nitrogen Operations
Agrium Kenai Nitrogen Operations
Agrium Kenai Nitrogen Operations
Agrium Kenai Nitrogen Operations
Agrium Kenai Nitrogen Operations
Southside Water Reclamation Plant
Southside Water Reclamation Plant
Southside Water Reclamation Plant
Southside Water Reclamation Plant
Martin Dam
Martin Dam
ORIS
Plant
Code
55788
10223
52093
52093
50752
50752
50752
52077
52077
52077
10673
54452
54452
54452
54452
54452
10339
10339
10339
10339
16
16
Unit
ID
GEN2
E.G.
GEN1
GEN2
GEN1
GEN2
GENS
GEN4
GENS
GEN6
GEN1
744A
744B
744C
744D
744E
GEN1
GEN2
GENS
GEN4
1
2
Plant Type
Combustion Turbine
Coal Steam
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Coal Steam
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Non-Fossil Waste
Non-Fossil Waste
Non-Fossil Waste
Non-Fossil Waste
Hydro
Hydro
State Name
New York
Iowa
California
California
California
California
California
California
California
California
Hawaii
Alaska
Alaska
Alaska
Alaska
Alaska
New Mexico
New Mexico
New Mexico
New Mexico
Alabama
Alabama
Capacity
(MW)
1.1
8.5
2.4
2.4
19
19
19
2.7
2.7
2.7
180
2.5
2.5
2.5
2.5
2.5
2.1
2.1
1.1
1.1
46.5
46.5
Notes
Dropped - Onsite Unit
Dropped - Onsite Unit
Dropped - PLANNED_RETIREMENT_YEAR <=2015
Dropped - PLANNED_RETIREMENT_YEAR <=2015
Dropped - Onsite Unit
Dropped - Onsite Unit
Dropped - Onsite Unit
Dropped - Onsite Unit
Dropped - Onsite Unit
Dropped - Onsite Unit
Dropped - in Alaska or in Hawaii
Dropped - Onsite Unit
Dropped - Onsite Unit
Dropped - Onsite Unit
Dropped - Onsite Unit
Dropped - Onsite Unit
Dropped - Onsite Unit
Dropped - Onsite Unit
Dropped - Onsite Unit
Dropped - Onsite Unit
Dropped - PLANNED_RETIREMENT_YEAR <=2015
Dropped - PLANNED_RETIREMENT_YEAR <=2015
Table 4-36 Capacity Not Included Due to Recent Announcements
Plant Name
5 in 1 Dam Hydroelectric
5 in 1 Dam Hydroelectric
5 in 1 Dam Hydroelectric
Abilene Energy Center Combustion Turbine
ACE Cogeneration Facility
AES Greenidge LLC
AES Thames
AES Thames
AES Westover
Albany
Alliant SBD 9801 Aegon Martha's Way
Alloy Steam Station
Alma
Alma
Alma
Alma
Alma
Alvarado Hydro Facility
Animas
Arapahoe
Astoria Generating Station
B C Cobb
B C Cobb
B C Cobb
B C Cobb
B C Cobb
B L England
B L England
B L England
B L England
B L England
B L England
Balefill LFG Project
Balefill LFG Project
ORIS
Plant
Code
10171
10171
10171
1251
10002
2527
10675
10675
2526
2113
56072
50012
4140
4140
4140
4140
4140
54242
2465
465
8906
1695
1695
1695
1695
1695
2378
2378
2378
2378
2378
2378
55159
55159
Unit ID
GEN1
GEN2
GENS
GT1
CFB
6
A
B
13
3
01
BLR4
B1
B2
B3
B4
B5
AHF
4
4
20
1
2
3
4
5
1
2
IC1
IC2
IC3
IC4
UNT1
UNT2
Plant Type
Hydro
Hydro
Hydro
Combustion Turbine
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Combustion Turbine
Combustion Turbine
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Hydro
O/G Steam
Coal Steam
O/G Steam
O/G Steam
O/G Steam
O/G Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Landfill Gas
Landfill Gas
State Name
Iowa
Iowa
Iowa
Kansas
California
New York
Connecticut
Connecticut
New York
Missouri
Iowa
West Virginia
Wisconsin
Wisconsin
Wisconsin
Wisconsin
Wisconsin
California
New Mexico
Colorado
New York
Michigan
Michigan
Michigan
Michigan
Michigan
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
Capacity
(MW)
0.7
0.7
0.7
64
101
108
90
90
84
0.6
1
38
17.4
17.4
20.9
48
72
1.4
16
109
181
62
62
62
156
156
113
155
2
2
2
2
0.1
0.1
Retirement
Year
2015
2015
2015
2012
2015
2012
2012
2012
2012
2015
2012
2007
2013
2013
2013
2015
2015
2015
2015
2013
2012
2015
2015
2015
2015
2015
2013
2015
2015
2015
2015
2015
2010
2010
4-73
-------
Plant Name
Ben French
Berlin
Berlin Gorham
Big Sandy
Binghamton Cogen
Biodyne Lyons
Biodyne Lyons
Biodyne Lyons
Biodyne Peoria
Biodyne Peoria
Biodyne Peoria
Biodyne Peoria
Biodyne Pontiac
Biodyne Pontiac
Biodyne Pontiac
Biron
Bluebonnet
Bountiful City
Bountiful City
Brunot Island
Brunot Island
Bryan
Bryan
Bryan
Bryan
Canadys Steam
Canadys Steam
Canadys Steam
Cane Run
Cane Run
Cane Run
Cape Canaveral
Cape Canaveral
Cape Fear
Cape Fear
Cape Fear
Carbon
Carbon
Cedar Station
Cedar Station
CES Placerita Power Plant
CES Placerita Power Plant
Chamois
Chamois
Cherokee
Chesapeake
Chesapeake
Chesapeake
Chesapeake
Chesapeake
Chesapeake
Chesapeake
Chesapeake
Clinch River
Coal Canyon
Conesville
Conners Creek
Conners Creek
Conners Creek
Conners Creek
Crawford
ORIS
Plant
Code
3325
6565
54639
1353
55600
55060
55060
55060
55057
55057
55057
55057
55054
55054
55054
3971
55552
3665
3665
3096
3096
3561
3561
3561
3561
3280
3280
3280
1363
1363
1363
609
609
2708
2708
2708
3644
3644
2380
2380
10677
10677
2169
2169
469
3803
3803
3803
3803
3803
3803
3803
3803
3775
226
2840
1726
1726
1726
1726
867
Unit ID
1
3A
GOR1
BSU2
1
001
002
004
001
002
004
005
1
3
GEN2
6
UNT2
2
6
1B
1C
3
4
5
6
CAN1
CAN2
CANS
4
5
6
PCC1
PCC2
5
6
1B
1
2
CED1
CED2
UNT2
UNT3
1
2
3
1
2
3
4
7
8
9
10
3
1
3
15
16
17
18
7
Plant Type
Coal Steam
Combustion Turbine
Hydro
Coal Steam
Combustion Turbine
Landfill Gas
Landfill Gas
Landfill Gas
Landfill Gas
Landfill Gas
Landfill Gas
Landfill Gas
Landfill Gas
Landfill Gas
Landfill Gas
Hydro
Landfill Gas
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
O/G Steam
O/G Steam
O/G Steam
O/G Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
O/G Steam
O/G Steam
Coal Steam
Coal Steam
Combined Cycle
Coal Steam
Coal Steam
Combustion Turbine
Combustion Turbine
Combined Cycle
Combined Cycle
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Coal Steam
Hydro
Coal Steam
O/G Steam
O/G Steam
O/G Steam
O/G Steam
Coal Steam
State Name
South Dakota
Maryland
New Hampshire
Kentucky
New York
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Wisconsin
Texas
Utah
Utah
Pennsylvania
Pennsylvania
Texas
Texas
Texas
Texas
South Carolina
South Carolina
South Carolina
Kentucky
Kentucky
Kentucky
Florida
Florida
North Carolina
North Carolina
North Carolina
Utah
Utah
New Jersey
New Jersey
California
California
Missouri
Missouri
Colorado
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
Virginia
California
Ohio
Michigan
Michigan
Michigan
Michigan
Illinois
Capacity
(MW)
21.6
1.8
1.2
800
42
0.9
0.9
0.9
0.8
0.8
0.8
0.8
4.2
4.2
4.2
0.4
1
1.2
2.5
15
15
12
22
25
50
105
115
180
155
168
240
396
396
144
172
11
67
105
44
22.3
46
23
16
47
152
111
111
156
217
16
16
16
16
230
0.9
165
58
58
58
58
213
Retirement
Year
2014
2015
2015
2014
2012
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2011
2011
2015
2015
2015
2015
2012
2013
2013
2015
2015
2015
2010
2010
2012
2012
2012
2015
2015
2015
2015
2015
2015
2013
2013
2014
2014
2014
2014
2014
2011
2011
2011
2011
2015
2015
2012
2011
2011
2011
2011
2012
4-74
-------
Plant Name
Crawford
Crosscut
Crosscut
Crosscut
Crosscut
Crosscut
Crosscut
Crystal River
CTV Power Purchase Contract Trust
Cutler
Cutler
Cytec 1 , 2 & 3
Cytec 1 , 2 & 3
Cytec 1 , 2 & 3
Danskammer Generating Station
Danskammer Generating Station
Danskammer Generating Station
Danskammer Generating Station
Danskammer Generating Station
Danskammer Generating Station
DeCordova Power Company LLC
Deepwater
Deepwater
Dolphus M Grainger
Dolphus M Grainger
Dunbarton Energy Partners LP
Dunbarton Energy Partners LP
E F Barrett
Eagle Mountain
Eagle Mountain
Eagle Mountain
Eagle Valley
Eagle Valley
Eagle Valley
East Third Street Power Plant
Edgewater
El Segundo Power
Elrama Power Plant
Elrama Power Plant
Elrama Power Plant
Elrama Power Plant
FirstEnergy Albright
FirstEnergy Albright
FirstEnergy Albright
FirstEnergy Armstrong Power Station
FirstEnergy Armstrong Power Station
FirstEnergy Ashtabula
FirstEnergy Bay Shore
FirstEnergy Bay Shore
FirstEnergy Bay Shore
FirstEnergy Eastlake
FirstEnergy Eastlake
FirstEnergy Eastlake
FirstEnergy Eastlake
FirstEnergy Eastlake
FirstEnergy Lake Shore
FirstEnergy Mitchell Power Station
FirstEnergy Mitchell Power Station
FirstEnergy Mitchell Power Station
FirstEnergy Mitchell Power Station
FirstEnergy R E Burger
ORIS
Plant
Code
867
143
143
143
143
143
143
628
54300
610
610
56257
56257
56257
2480
2480
2480
2480
2480
2480
8063
2384
2384
3317
3317
55779
55779
2511
3489
3489
3489
991
991
991
10367
4050
330
3098
3098
3098
3098
3942
3942
3942
3178
3178
2835
2878
2878
2878
2837
2837
2837
2837
2837
2838
3181
3181
3181
3181
2864
Unit ID
8
1
2
3
4
5
6
3
SX1S
PCU5
PCU6
CY1
CY2
CY3
1
2
3
4
5
6
1
1
8
1
2
MA1
MA2
7
1
2
3
3
4
5
CB1302
3
3
1
2
3
4
1
2
3
1
2
7
2
3
4
1
2
3
4
5
18
1
2
3
33
5
Plant Type
Coal Steam
O/G Steam
O/G Steam
O/G Steam
O/G Steam
O/G Steam
O/G Steam
Nuclear
Wind
O/G Steam
O/G Steam
Combustion Turbine
Combustion Turbine
Combustion Turbine
O/G Steam
O/G Steam
Coal Steam
Coal Steam
Combustion Turbine
Combustion Turbine
O/G Steam
O/G Steam
Coal Steam
Coal Steam
Coal Steam
Landfill Gas
Landfill Gas
Combustion Turbine
O/G Steam
O/G Steam
O/G Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
O/G Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
O/G Steam
O/G Steam
O/G Steam
Coal Steam
Coal Steam
State Name
Illinois
Arizona
Arizona
Arizona
Arizona
Arizona
Arizona
Florida
California
Florida
Florida
Connecticut
Connecticut
Connecticut
New York
New York
New York
New York
New York
New York
Texas
New Jersey
New Jersey
South Carolina
South Carolina
New Hampshire
New Hampshire
New York
Texas
Texas
Texas
Indiana
Indiana
Indiana
California
Wisconsin
California
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
West Virginia
West Virginia
West Virginia
Pennsylvania
Pennsylvania
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Ohio
Capacity
(MW)
319
7.5
7.5
7.5
2.5
2.5
2.5
1028
0.1
68
137
2
2
2
66
62
138
237
2.5
2.5
818
78
81
83
83
0.6
0.6
16.6
115
175
375
40
56
62
18.7
70
325
93
93
103
171
73
73
137
172
172
244
138
142
215
132
132
132
240
597
245
27
27
27
278
47
Retirement
Year
2012
2015
2015
2015
2015
2015
2015
2013
2015
2012
2012
2011
2011
2011
2013
2013
2013
2013
2013
2013
2011
2015
2015
2013
2013
2012
2012
2011
2015
2015
2015
2015
2015
2015
2012
2015
2013
2012
2012
2012
2012
2012
2012
2012
2012
2012
2015
2012
2012
2012
2015
2015
2015
2012
2012
2015
2013
2013
2013
2013
2011
4-75
-------
Plant Name
FirstEnergy R E Burger
FirstEnergy R Paul Smith Power Station
FirstEnergy R Paul Smith Power Station
FirstEnergy Rivesville
FirstEnergy Rivesville
FirstEnergy Willow Island
FirstEnergy Willow Island
Fisk Street
Frank E Ratts
Frank E Ratts
G W Ivey
Gaylord
George Neal North
George Neal North
Geysers Unit 5-20
Geysers Unit 5-20
Gilbert
Gilbert
Gilbert
Gilbert
Gilbert
Glen Gardner
Glen Gardner
Glen Gardner
Glen Gardner
Glen Gardner
Glen Gardner
Glen Gardner
Glen Gardner
Glen Lyn
Glen Lyn
Glen Lyn
Green River
Green River
Greenport
Greenport
Groveton Paper Board
Groveton Paper Board
H B Robinson
Hanford
Hansel
Hansel
Hansel
Harbor Beach
Harllee Branch
Harllee Branch
Harvey Couch
Hatfields Ferry Power Station
Hatfields Ferry Power Station
Hatfields Ferry Power Station
Herington
Herington
Herington
Herington
Herkimer
Herkimer
Herkimer
Herkimer
High Street Station
HMDC Kingsland Landfill
HMDC Kingsland Landfill
ORIS
Plant
Code
2864
1570
1570
3945
3945
3946
3946
886
1043
1043
665
1706
1091
1091
286
286
2393
2393
2393
2393
2393
8227
8227
8227
8227
8227
8227
8227
8227
3776
3776
3776
1357
1357
2681
2681
56140
56140
3251
10373
672
672
672
1731
709
709
169
3179
3179
3179
1283
1283
1283
1283
52057
52057
52057
52057
1670
55604
55604
Unit ID
6
9
11
7
8
1
2
19
1SG1
2SG1
18
5
1
2
U10
U9
8
C1
C2
C3
C4
1
2
3
4
5
6
7
8
6
51
52
4
5
2
7
TUR1
TUR2
1
CB1302
21
22
23
1
3
4
1
1
2
3
1
2
3
5
01
02
03
04
3
UNT1
UNT2
Plant Type
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Combustion Turbine
Combustion Turbine
Coal Steam
Coal Steam
Geothermal
Geothermal
Combined Cycle
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Coal Steam
Coal Steam
Combined Cycle
Combined Cycle
Combined Cycle
Coal Steam
Coal Steam
Coal Steam
O/G Steam
Coal Steam
Coal Steam
Coal Steam
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Hydro
Hydro
Hydro
Hydro
Combustion Turbine
Landfill Gas
Landfill Gas
State Name
Ohio
Maryland
Maryland
West Virginia
West Virginia
West Virginia
West Virginia
Illinois
Indiana
Indiana
Florida
Michigan
Iowa
Iowa
California
California
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
Virginia
Virginia
Virginia
Kentucky
Kentucky
New York
New York
New Hampshire
New Hampshire
South Carolina
California
Florida
Florida
Florida
Michigan
Georgia
Georgia
Arkansas
Pennsylvania
Pennsylvania
Pennsylvania
Kansas
Kansas
Kansas
Kansas
New York
New York
New York
New York
Massachusetts
New Jersey
New Jersey
Capacity
(MW)
47
28
87
37
88
54
181
326
120
121
8
14
137
301
30
30
90
23
25
25
25
20
20
20
20
20
20
20
20
235
45
45
68
95
1.5
1.6
4
4
177
25
30
8
8
95
509
507
12
506
506
506
1.6
1
3.1
0.9
0.1
0.1
0.1
0.1
0.7
0.1
0.1
Retirement
Year
2011
2012
2012
2012
2012
2012
2012
2012
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2012
2012
2012
2012
2012
2015
2015
2015
2015
2013
2013
2013
2012
2012
2012
2012
2015
2015
2015
2015
2015
2010
2010
4-76
-------
Plant Name
HMDC Kingsland Landfill
Holcomb Rock
Howard Down
Hutsonville
Hutsonville
Indian River Generating Station
Indian River Generating Station
Ivy River Hydro
Ivy River Hydro
Ivy River Hydro
Ivy River Hydro
Ivy River Hydro
Ivy River Hydro
J C Weadock
J C Weadock
J R Whiting
J R Whiting
J R Whiting
Jefferies
Jefferies
John Sevier
John Sevier
Johnsonville
Johnsonville
Johnsonville
Johnsonville
Kammer
Kammer
Kammer
Kanawha River
Kanawha River
Kaw
Kaw
Kaw
Kewaunee
Kitty Hawk
Kitty Hawk
Kraft
L V Sutton
L V Sutton
L V Sutton
Lake Creek
Lake Creek
Lansing
Lansing
Lee
Lee
Lee
Lee
Lilliwaup Falls Generating
Lilliwaup Falls Generating
Lilliwaup Falls Generating
Lilliwaup Falls Generating
Lilliwaup Falls Generating
Lilliwaup Falls Generating
Lilliwaup Falls Generating
Loveridge Road Power Plant
Maine Energy Recovery
Maine Energy Recovery
Marysville
Marysville
ORIS
Plant
Code
55604
56314
2434
863
863
594
594
50890
50890
50890
50890
50890
50890
1720
1720
1723
1723
1723
3319
3319
3405
3405
3406
3406
3406
3406
3947
3947
3947
3936
3936
1294
1294
1294
8024
2757
2757
733
2713
2713
2713
3502
3502
1047
1047
2709
2709
2709
2709
50700
50700
50700
50700
50700
50700
50700
10368
10338
10338
1732
1732
Unit ID
UNT3
HG2
10
05
06
1
2
GEN1
GEN2
GENS
GEN4
GENS
GEN6
7
8
1
2
3
3
4
3
4
1
2
3
4
1
2
3
1
2
1
2
3
1
GT1
GT2
3
1
2
3
D1
D2
2
3
GT1
GT2
GTS
GT4
4735
4736
4737
4738
4739
4740
4741
CB1302
ABLR
BBLR
9
10
Plant Type
Landfill Gas
Hydro
O/G Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Hydro
Hydro
Hydro
Hydro
Hydro
Hydro
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
O/G Steam
O/G Steam
O/G Steam
Nuclear
Combustion Turbine
Combustion Turbine
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Combustion Turbine
Combustion Turbine
Coal Steam
Coal Steam
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Hydro
Hydro
Hydro
Hydro
Hydro
Hydro
Hydro
Coal Steam
Municipal Solid Waste
Municipal Solid Waste
Coal Steam
Coal Steam
State Name
New Jersey
Virginia
New Jersey
Illinois
Illinois
Delaware
Delaware
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
North Carolina
Michigan
Michigan
Michigan
Michigan
Michigan
South Carolina
South Carolina
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
Tennessee
West Virginia
West Virginia
West Virginia
West Virginia
West Virginia
Kansas
Kansas
Kansas
Wisconsin
North Carolina
North Carolina
Georgia
North Carolina
North Carolina
North Carolina
Texas
Texas
Iowa
Iowa
North Carolina
North Carolina
North Carolina
North Carolina
Washington
Washington
Washington
Washington
Washington
Washington
Washington
California
Maine
Maine
Michigan
Michigan
Capacity
(MW)
0.1
0.2
23
75
76
89
89
0.2
0.2
0.2
0.2
0.2
0.2
155
151
97
101
124
152
150
176
176
107
107
107
107
200
200
200
200
200
42
42
56
566
16
15
101
97
104
389
2
2
8.4
21
12
21
21
21
0.2
0.2
0.2
0.2
0.2
0.2
0.2
18
9
9
42
42
Retirement
Year
2010
2015
2010
2011
2011
2011
2010
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2012
2012
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2013
2013
2013
2013
2011
2011
2015
2013
2013
2013
2009
2009
2012
2014
2012
2012
2012
2012
2015
2015
2015
2015
2015
2015
2015
2012
2012
2012
2011
2011
4-77
-------
Plant Name
Marysville
Marysville
Mclntosh
Meredosia
Meredosia
Meredosia
Meredosia
Meredosia
Meredosia
Miami Fort
Middle Station
Middle Station
Middle Station
Missouri Avenue
Missouri Avenue
Missouri Avenue
Montgomery
Morgan City
Morgan City
Morgan Creek
Morgan Creek
Morris Sheppard
Morris Sheppard
Muskingum River
Muskingum River
Muskingum River
Muskingum River
Muskingum River
Neil Simpson
Nelson Dewey
Nelson Dewey
Neosho
New Albany Energy Facility
New Albany Energy Facility
New Albany Energy Facility
New Albany Energy Facility
New Albany Energy Facility
New Albany Energy Facility
Nichols Road Power Plant
Niles
Niles
Nine Mile
North Branch
North Branch
Norton
Norton
Norton
Norton
Norton
O H Mulchings
O H Mulchings
O H Mulchings
O H Mulchings
O H Mulchings
O H Mulchings
Oakely
Oakely
Oakely
Oakely
Oakland Dam Hydroelectric
Oakland Dam Hydroelectric
ORIS
Plant
Code
1732
1732
6124
864
864
864
864
864
864
2832
2382
2382
2382
2383
2383
2383
8025
1449
1449
3492
3492
3557
3557
2872
2872
2872
2872
2872
4150
4054
4054
1243
55080
55080
55080
55080
55080
55080
10371
2861
2861
3869
7537
7537
1310
1310
1310
1310
1310
2848
2848
2848
2848
2848
2848
1311
1311
1311
1311
10433
10433
Unit ID
11
12
1
01
02
03
04
05
06
6
MIDI
MID2
MID3
MISB
MISC
MISD
1
1
2
5
6
1
2
1
2
3
4
5
5
1
2
7
1
2
3
4
5
6
CB1302
1
2
1
A
B
1
2
3
4
5
H-1
H-2
H-3
H-4
H-5
H-6
1
2
4
6
1
2
Plant Type
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
O/G Steam
Coal Steam
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
O/G Steam
O/G Steam
O/G Steam
O/G Steam
Hydro
Hydro
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
O/G Steam
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Coal Steam
Coal Steam
Coal Steam
Hydro
Coal Steam
Coal Steam
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Hydro
Hydro
State Name
Michigan
Michigan
Georgia
Illinois
Illinois
Illinois
Illinois
Illinois
Illinois
Ohio
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
Minnesota
Louisiana
Louisiana
Texas
Texas
Texas
Texas
Ohio
Ohio
Ohio
Ohio
Ohio
Wyoming
Wisconsin
Wisconsin
Kansas
Mississippi
Mississippi
Mississippi
Mississippi
Mississippi
Mississippi
California
Ohio
Ohio
Washington
West Virginia
West Virginia
Kansas
Kansas
Kansas
Kansas
Kansas
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Kansas
Kansas
Kansas
Kansas
Pennsylvania
Pennsylvania
Capacity
(MW)
42
42
156
26
26
26
26
203
166
163
19.1
19.5
36
20.5
20.5
20.6
20.6
5.8
5.8
175
511
12
12
190
190
205
205
585
14.6
115
111
67
60
60
60
60
60
60
17.8
108
108
8.9
37
37
0.9
1.3
2.4
3.1
2.2
58
55
63
63
63
63
1.2
0.3
0.8
3.2
0.5
0.5
Retirement
Year
2011
2011
2015
2011
2011
2011
2011
2011
2011
2015
2015
2015
2015
2015
2015
2015
2012
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2014
2014
2015
2015
2012
2015
2015
2015
2015
2015
2015
2012
2012
2012
2015
2014
2014
2011
2011
2011
2011
2011
2015
2015
2015
2013
2015
2015
2012
2012
2012
2012
2015
2015
4-78
-------
Plant Name
Osage
Osage
Osage
Pearl Station
Pella
Pella
Pella
Permian Basin
Philip Sporn
Philip Sporn
Philip Sporn
Philip Sporn
Philip Sporn
Picway
Port Everglades
Port Everglades
Port Everglades
Port Everglades
Porterdale Hydro
Porterdale Hydro
Portland
Portland
Powerdale
Prairie Creek
Prairie River
Prairie River
PSEG Burlington Generating Station
PSEG Burlington Generating Station
PSEG Burlington Generating Station
PSEG Burlington Generating Station
PSEG Burlington Generating Station
PSEG Burlington Generating Station
PSEG Burlington Generating Station
PSEG Burlington Generating Station
PSEG Edison Generating Station
PSEG Edison Generating Station
PSEG Edison Generating Station
PSEG Edison Generating Station
PSEG Edison Generating Station
PSEG Edison Generating Station
PSEG Edison Generating Station
PSEG Edison Generating Station
PSEG Edison Generating Station
PSEG Edison Generating Station
PSEG Edison Generating Station
PSEG Edison Generating Station
PSEG Essex Generating Station
PSEG Essex Generating Station
PSEG Essex Generating Station
PSEG Essex Generating Station
PSEG Essex Generating Station
PSEG Essex Generating Station
PSEG Essex Generating Station
PSEG Essex Generating Station
PSEG Essex Generating Station
PSEG Essex Generating Station
PSEG Essex Generating Station
PSEG Essex Generating Station
PSEG Sewaren Generating Station
PSEG Sewaren Generating Station
PSEG Sewaren Generating Station
ORIS
Plant
Code
4151
4151
4151
6238
1175
1175
1175
3494
3938
3938
3938
3938
3938
2843
617
617
617
617
50242
50242
3113
3113
3031
1073
378
378
2399
2399
2399
2399
2399
2399
2399
2399
2400
2400
2400
2400
2400
2400
2400
2400
2400
2400
2400
2400
2401
2401
2401
2401
2401
2401
2401
2401
2401
2401
2401
2401
2411
2411
2411
Unit ID
1
2
3
1A
6
7
8
5
11
21
31
41
51
9
PPE1
PPE2
PPE3
PPE4
TB-1
TB-2
1
2
1
2
1
2
91
92
93
94
111
112
113
114
11
12
13
14
21
22
23
24
31
32
33
34
101
102
103
104
111
112
113
114
121
122
123
124
1
2
3
Plant Type
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
O/G Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
O/G Steam
O/G Steam
O/G Steam
O/G Steam
Hydro
Hydro
Coal Steam
Coal Steam
Hydro
Coal Steam
Hydro
Hydro
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
O/G Steam
O/G Steam
O/G Steam
State Name
Wyoming
Wyoming
Wyoming
Illinois
Iowa
Iowa
Iowa
Texas
West Virginia
West Virginia
West Virginia
West Virginia
West Virginia
Ohio
Florida
Florida
Florida
Florida
Georgia
Georgia
Pennsylvania
Pennsylvania
Oregon
Iowa
Minnesota
Minnesota
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
New Jersey
Capacity
(MW)
10.1
10.1
10.1
22.2
11.5
11.5
11.5
115
145
145
145
145
440
95
213
213
387
392
0.7
0.7
158
243
6
2.1
0.3
0.3
46
46
46
46
46
46
46
46
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
42
46
46
46
46
46
46
46
46
104
118
107
Retirement
Year
2010
2010
2010
2012
2012
2012
2012
2011
2015
2015
2015
2015
2012
2015
2013
2013
2013
2013
2015
2015
2015
2015
2015
2010
2015
2015
2014
2014
2014
2014
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
4-79
-------
Plant Name
PSEG Sewaren Generating Station
Pulliam
Pulliam
R Gallagher
R Gallagher
Ravenswood
Reid Gardner
Reid Gardner
Reid Gardner
Riverside
Riverton
Riverton
Riviera
Riviera
Rochester 5
Rochester 5
Rochester 5
Sabetha Power Plant
Sabetha Power Plant
San Francisquito 2
San Onofre Nuclear Generating Station
San Onofre Nuclear Generating Station
Schuylkill Generating Station
Schuylkill Generating Station
Shawville
Shawville
Shawville
Shawville
Shelby Municipal Light Plant
Shelby Municipal Light Plant
Small Hydro of Texas
Small Hydro of Texas
Small Hydro of Texas
Smart Papers LLC
Smart Papers LLC
Smart Papers LLC
Somerset Station
Steamboat 1
Steamboat 1
Steamboat 1
Steamboat 1
Steamboat 1
Steamboat 1
Steamboat 1
Steamboat 1A Power Plant
Swift 2
Taconite Harbor Energy Center
Tangier
Tangier
Tanners Creek
Tanners Creek
Tanners Creek
Tanners Creek
Teche
Tecumseh Energy Center
Tecumseh Energy Center
Thomas C Ferguson
Thousand Springs
Thousand Springs
Tillotson Rubber
Tillotson Rubber
ORIS
Plant
Code
2411
4072
4072
1008
1008
2500
2324
2324
2324
1559
1239
1239
619
619
2641
2641
2641
1320
1320
6480
360
360
3169
3169
3131
3131
3131
3131
2943
2943
55000
55000
55000
50247
50247
50247
1613
50763
50763
50763
50763
50763
50763
50763
52138
6265
10075
6390
6390
988
988
988
988
1400
1252
1252
4937
820
820
50095
50095
Unit ID
4
5
6
1
3
GTS
1
2
3
GT6
39
40
PRV3
PRV4
2
HY1
HY3
4
8
1
2
3
1
IC1
1
2
3
4
1
2
01
02
03
B010
B020
B022
6
OE11
OE12
OE13
OE14
OE21
OE22
OE23
DE32
21
3
3
4
U1
U2
U3
U4
2
1
2
1
1
2
IC1
IC2
Plant Type
O/G Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Combustion Turbine
Coal Steam
Coal Steam
Coal Steam
Combustion Turbine
Coal Steam
Coal Steam
O/G Steam
O/G Steam
Hydro
Hydro
Hydro
Combustion Turbine
Combustion Turbine
Hydro
Nuclear
Nuclear
O/G Steam
Combustion Turbine
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Hydro
Hydro
Hydro
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Geothermal
Geothermal
Geothermal
Geothermal
Geothermal
Geothermal
Geothermal
Geothermal
Hydro
Coal Steam
Combustion Turbine
Combustion Turbine
Coal Steam
Coal Steam
Coal Steam
Coal Steam
O/G Steam
Combustion Turbine
Combustion Turbine
O/G Steam
Hydro
Hydro
Combustion Turbine
Combustion Turbine
State Name
New Jersey
Wisconsin
Wisconsin
Indiana
Indiana
New York
Nevada
Nevada
Nevada
Maryland
Kansas
Kansas
Florida
Florida
New York
New York
New York
Kansas
Kansas
California
California
California
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Pennsylvania
Ohio
Ohio
Texas
Texas
Texas
Ohio
Ohio
Ohio
Massachusetts
Nevada
Nevada
Nevada
Nevada
Nevada
Nevada
Nevada
Nevada
Washington
Minnesota
Virginia
Virginia
Indiana
Indiana
Indiana
Indiana
Louisiana
Kansas
Kansas
Texas
Idaho
Idaho
New Hampshire
New Hampshire
Capacity
(MW)
124
52
71
140
140
20
100
100
98
115
38
54
277
288
12.9
12.9
18
0.7
2.1
14.5
1094
1080
166
2.7
122
125
175
175
12
12
0.4
0.4
0.4
26
15.1
4.5
109
0.9
0.9
0.9
0.9
0.9
0.9
0.9
0.9
34
76
0.6
0.8
145
145
200
500
33
18
19
420
0.8
0.8
0.4
0.6
Retirement
Year
2015
2015
2015
2012
2012
2015
2014
2014
2014
2014
2015
2015
2011
2011
2015
2015
2015
2012
2012
2015
2013
2013
2013
2013
2015
2015
2015
2015
2012
2012
2015
2015
2015
2012
2012
2012
2011
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2015
2014
2011
2012
2012
2013
2015
2015
2012
2012
4-80
-------
Plant Name
Tillotson Rubber
Tillotson Rubber
Titus
Titus
Titus
Tradinghouse Power Company LLC
Trigen Syracuse Energy
Trigen Syracuse Energy
Trigen Syracuse Energy
Trigen Syracuse Energy
Tulsa
Turkey Point
TXU Sweetwater Generating Plant
TXU Sweetwater Generating Plant
TXU Sweetwater Generating Plant
Tyrone
Union Carbide Seadrift Cogen
Upper Androscoggin
Venice
Vermilion
Vermilion
Vermilion
Vermont Yankee
Viking Energy of Northumberland
W N Clark
W N Clark
WS Lee
WS Lee
WS Lee
Wabash River
Wabash River
Wabash River
Wabash River
Walter C Beckjord
Walter C Beckjord
Walter C Beckjord
Walter C Beckjord
Walter C Beckjord
Walter C Beckjord
Walter Scott Jr Energy Center
Walter Scott Jr Energy Center
Wanapum
Washington Parish Energy Center
Washington Parish Energy Center
Washington Parish Energy Center
Watts Bar Fossil
Watts Bar Fossil
Watts Bar Fossil
Watts Bar Fossil
Webbers Falls
Welsh
Werner
Werner
Werner
Werner
Western Renewable Energy
Weston
Weston
Wilbur East Power Plant
Wilbur West Power Plant
Williston
ORIS
Plant
Code
50095
50095
3115
3115
3115
3506
50651
50651
50651
50651
2965
621
50615
50615
50615
1361
50150
54202
913
897
897
897
3751
50771
462
462
3264
3264
3264
1010
1010
1010
1010
2830
2830
2830
2830
2830
2830
1082
1082
3888
55486
55486
55486
3419
3419
3419
3419
2987
6139
2385
2385
2385
2385
56358
4078
4078
10370
10369
2791
Unit ID
TG2
TGI
1
2
3
2
2
3
4
5
1403
PTP2
GT01
GT02
GT03
5
IGT
2
GT1
1
2
3
1
B1
55
59
1
2
3
2
3
4
5
1
2
3
4
5
6
1
2
2
CTG1
CTG2
ST1
A
B
C
D
3
2
GT1
GT2
GTS
GT4
1
1
2
CB1302
CB1302
2
Plant Type
Biomass
Biomass
Coal Steam
Coal Steam
Coal Steam
O/G Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
O/G Steam
O/G Steam
Combined Cycle
Combined Cycle
Combined Cycle
Coal Steam
Combined Cycle
Hydro
Combustion Turbine
Coal Steam
Coal Steam
Combustion Turbine
Nuclear
Biomass
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Hydro
Combined Cycle
Combined Cycle
Combined Cycle
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Hydro
Coal Steam
Combustion Turbine
Combustion Turbine
Combustion Turbine
Combustion Turbine
Biomass
Coal Steam
Coal Steam
Coal Steam
Coal Steam
Combustion Turbine
State Name
New Hampshire
New Hampshire
Pennsylvania
Pennsylvania
Pennsylvania
Texas
New York
New York
New York
New York
Oklahoma
Florida
Texas
Texas
Texas
Kentucky
Texas
Maine
Illinois
Illinois
Illinois
Illinois
Vermont
Pennsylvania
Colorado
Colorado
South Carolina
South Carolina
South Carolina
Indiana
Indiana
Indiana
Indiana
Ohio
Ohio
Ohio
Ohio
Ohio
Ohio
Iowa
Iowa
Washington
Louisiana
Louisiana
Louisiana
Tennessee
Tennessee
Tennessee
Tennessee
Oklahoma
Texas
New Jersey
New Jersey
New Jersey
New Jersey
Arizona
Wisconsin
Wisconsin
California
California
North Dakota
Capacity
(MW)
0.6
0.7
81
81
81
818
24.6
24.6
12.3
12.3
65
392
41
86
86
71
12
0.5
26
62
99
10
620.3
16.2
17.6
24.9
100
100
170
85
85
85
95
94
94
128
150
238
414
43
88
97
172
172
215
56
56
56
56
23
528
53
53
53
53
2.5
58
81
18.1
18.2
4.7
Retirement
Year
2012
2012
2015
2015
2015
2011
2013
2013
2013
2013
2015
2013
2009
2009
2009
2013
2015
2015
2015
2011
2011
2011
2014
2012
2013
2013
2015
2015
2015
2014
2014
2014
2014
2012
2015
2015
2015
2015
2015
2015
2015
2012
2015
2015
2015
2011
2011
2011
2011
2015
2014
2015
2015
2015
2015
2015
2015
2015
2012
2012
2012
4-81
-------
Plant Name
Wisconsin Rapids
Wisconsin Rapids
Wiscoy 1 70
Wiscoy 1 70
Worcester Energy
Worcester Energy
Worcester Energy
Wythe Park Power Petersburg Plant
Yorktown
Yuma
ORIS
Plant
Code
3974
3974
2646
2646
10165
10165
10165
54045
3809
524
Unit ID
6
8
1
2
1
2
3
1
1
3
Plant Type
Hydro
Hydro
Hydro
Hydro
Biomass
Biomass
Biomass
Fossil Waste
Coal Steam
Combustion Turbine
State Name
Wisconsin
Wisconsin
New York
New York
Maine
Maine
Maine
Virginia
Virginia
Colorado
Capacity
(MW)
0.3
0.3
0.6
0.4
5.7
5.7
5.7
3
159
0.2
Retirement
Year
2015
2015
2015
2015
2015
2015
2015
2013
2014
2015
4-82
-------
5. Emission Control Technologies
EPA Base Case v.5.13 includes an update of emission control technology assumptions. EPA contracted
with engineering firm Sargent and Lundy to update and add to the retrofit emission control models
previously developed for EPA and used in EPA Base Case v.4.10. EPA Base Case v.5.13 thus includes
updated assumptions regarding control options for sulfur dioxide (SO2), nitrogen oxides (NOX), mercury
(Hg), and particulate matter (PM). These emission control options are listed in Table 5-1. They are
available in EPA Base Case v.5.13 for meeting existing and potential federal, regional, and state emission
limits. It is important to note that, besides the emission control options shown in Table 5-1 and described
in this chapter, EPA Base Case v.5.13 offers other compliance options for meeting emission limits. These
include fuel switching, adjustments in the dispatching of electric generating units, and the option to retire
a unit.
Table 5-1 Summary of Emission Control Technology Retrofit Options in EPA Base Case v.5.13
SO2 and HCI
Control
Technology
Options
Limestone Forced
Oxidation (LSFO)
Scrubber
Lime Spray Dryer
(LSD) Scrubber
Dry Sorbent
Injection (DSI)
FGD Upgrade
Adjustment
NOX Control
Technology Options
Selective Catalytic
Reduction (SCR)
System
Selective Non-
Catalytic Reduction
(SNCR) System
Combustion Controls
Mercury Control
Technology Options
Activated Carbon
Injection (ACI) System
SO2 and NOX Control
Technology Removal
Co-benefits
Particulate Matter
Control Technology
Options
Pulse-Jet Fabric Filter
(FF)
Electrostatic
Precipitator (ESP)
Upgrade Adjustment
CO2 Control
Technology
Options
CO2 Capture and
Sequestration
Coal-to-Gas
Conversion
Heat Rate
Improvement
Detailed reports and example calculation worksheets for Sargent & Lundy retrofit emission control models
used by EPA are available in Attachments 5-1 through 5-7 at: www.epa.gov/airmarkets/progsregs/epa-
ipm/BaseCasev513.html.
5.1 Sulfur Dioxide Control Technologies - Scrubbers
Two commercially available Flue Gas Desulfurization (FGD) "scrubber" technology options for removing
the SO2 produced by coal-fired power plants are offered in EPA Base Case v.5.13: Limestone Forced
Oxidation (LSFO) a wet FGD technology and Lime Spray Dryer (LSD) a semi-dry FGD technology
which employs a spray dryer absorber (SDA). In wet FGD systems, the polluted gas stream is brought
into contact with a liquid alkaline sorbent (typically limestone) by forcing it through a pool of the liquid
slurry or by spraying it with the liquid. In dry FGD systems the polluted gas stream is brought into contact
with the alkaline sorbent in a semi-dry state through use of a spray dryer. The removal efficiency for SDA
drops steadily for coals whose SO2 content exceeds 3 Ibs SO2/MMBtu, so this technology is provided only
to plants which have the option to burn coals with sulfur content no greater than 3 Ibs SO2/MMBtu. In
EPA Base Casev.5.13 when a unit retrofits with an LSD SO2 scrubber, it loses the option of burning
certain high sulfur content coals (see Table 5-2).
In EPA Base Case v.5.13 the LSFO and LSD SO2 emission control technologies are available to existing
"unscrubbed" units. They are also available to existing "scrubbed" units with reported removal
efficiencies of less than fifty percent. Such units are considered to have an injection technology and
classified as "unscrubbed" for modeling purposes in the NEEDS database of existing units which is used
in setting up the EPA base case. The scrubber retrofit costs for these units are the same as regular
unscrubbed units retrofitting with a scrubber.
5-1
-------
Default SO2 removal rates for wet and dry FGD were based on data reported in EIA 860 (2010). These
default removal rates were the average of all SO2 removal rates for a dry or wet FGD as reported in EIA
860 (2010) for the FGD installation year.
To reduce the incidence of implausibly high, outlier removal rates, units whose reported EIA Form 860
(2010) SO2 removal rates are higher than the average of the upper quartile of SO2 removal rates across
all scrubbed units are instead assigned the upper quartile average unless the reported EIA 860 rate was
recently confirmed by utility comments. One upper quartile removal rate is calculated across all
installation years and replaces any reported removal rate that exceeds it no matter the installation year.
Existing units not reporting FGD removal rates in form EIA 860 (2010) will be assigned the default SO2
removal rate for a dry or wet FGD for that installation year.
As shown in Table 5-2, for FGD retrofits installed by the model, the assumed SO2 removal rates will be
96% for wet FGD and 92% for dry FGD. These are the average of the SO2 removal efficiencies reported
in EIA 860 (2008) for dry and wet FGD installed in 2008 or later. These rates have been subjected to
numerous reviews from utilities and other stakeholders recently, so they remain unchanged and continue
to be used in EPA Base Case v.5.13.
The procedures used to derive the cost of each scrubber type are discussed in detail in the following
sections.
Table 5-2 Summary of Retrofit SO2 Emission Control Performance
Assumptions in Base Case v.5.13
Performance
Assumptions
Percent Removal
Capacity Penalty
Heat Rate Penalty
Cost (2011$)
Applicability
Sulfur Content
Applicability
Applicable Coal Types
Limestone Forced Oxidation (LSFO)
96%
with a floor of 0.06 Ibs/MMBtu
Calculated based on characteristics of the unit:
See Table 5-3
Units > 25 MW
BA, BB, BD, BE, BG, BH, SA, SB, SD, SE, LD, LE,
LG, LH, PKandWC
Lime Spray Dryer (LSD)
92%
with a floor of 0.08 Ibs/MMBtu
Calculated based on characteristics
of the unit:
See Table 5-3
Units > 25 MW
Coals < 3 Ibs SO2/MMBtu1
BA, BB, BD, BE, SA, SB, SD, SE,
LD, and LE
FBC units burning WC and PK fuels are provided with LSD retrofit options
Potential (new) coal-fired units built by the model are also assumed to be constructed with a scrubber
achieving a removal efficiency of 96%. In EPA Base Case v.5.13 the costs of potential new coal units
include the cost of scrubbers.
5.1.1 Methodology for Obtaining SO2 Controls Costs
Sargent and Lundy's updated performance and cost models for wet and dry SO2 scrubbers are
implemented in EPA Base Case v.5.13 to develop the capital, fixed O&M (FOM), and variable O&M
(VOM) components of cost. See Attachments 5-1 and 5-2 (www.epa.qov/airmarkets/proqsreqs/epa-
ipm/BaseCasev513.html).
Capacity and Heat Rate Penalty: In IPM the amount of electrical power required to operate a retrofit
emission control device is represented through a reduction in the amount of electricity that is available for
sale to the grid. For example, if 1.6% of the unit's electrical generation is needed to operate the scrubber,
the generating unit's capacity is reduced by 1.6%. This is the "capacity penalty." At the same time, to
capture the total fuel used in generation both for sale to the grid and for internal load (i.e., for operating
5-2
-------
the control device), the unit's heat rate is scaled up such that a comparable reduction (1.6% in the
previous example) in the new higher heat rate yields the original heat rate24. The factor used to scale up
the original heat rate is called "heat rate penalty." It is a modeling procedure only and does not represent
an increase in the unit's actual heat rate (i.e., a decrease in the unit's generation efficiency). In EPA Base
Case v.5.13 specific LSFO and LSD heat rate and capacity penalties are calculated for each installation
based on equations from the Sargent and Lundy models that take into account the rank of coal burned, its
uncontrolled SO2 rate, and the heat rate of the model plant.
Table 5-3 presents the capital, VOM, and FOM costs as well as the capacity and heat rate penalty for two
SO2 emission control technologies (LSFO and LSD) included in EPA Base Case v.5.13 for an illustrative
set of generating units with a representative range of capacities and heat rates.
Mathematically, the relationship of the heat rate and capacity penalties (both expressed as positive percentage
values) can be represented as follows:
Heat Rate Penalty =
1
Capacity Penalty
1-
100
-1
xlOO
5-3
-------
Table 5-3 Illustrative Scrubber Costs (2011$) for Representative Sizes and Heat Rates under the Assumptions in EPA Base Case v.5.13
Scrubber
Type
LSFO
LSD
Heat Rate
(Btu/kWh)
9,000
10,000
1 1 ,000
9,000
10,000
1 1 ,000
Capacity
Penalty
(%)
-1.50
-1.67
-1.84
-1.18
-1.32
-1.45
Heat Rate
Penalty
(%)
1.53
1.70
1.87
1.20
1.33
1.47
Variable O&M
(mills/kWh)
2.03
2.26
2.49
2.51
2.79
3.07
Capacity (MW)
50
Fixed
Capital O&M
Cost ($/kW-
($/kW) yr)
819 23.7
860 24.2
899 24.6
854 29.1
894 29.6
933 30.0
100
Fixed
Capital O&M
Cost ($/kW-
($/kW) yr)
819 23.7
860 24.2
899 24.6
701 17.3
734 17.7
766 18.0
300
Fixed
Capital O&M
Cost ($/kW-
($/kW) yr)
600 1 1 .2
629 1 1 .5
658 1 1 .8
513 8.6
538 8.9
561 9.1
500
Fixed
Capital O&M
Cost ($/kW-
($/kW) yr)
519 8.3
544 8.6
569 8.9
444 6.5
465 6.8
485 7.0
700
Fixed
Capital O&M
Cost ($/kW-
($/kW) yr)
471 7.7
495 8.0
517 8.2
422 5.7
442 5.9
461 6.1
1000
Fixed
Capital O&M
Cost ($/kW-
($/kW) yr)
426 6.4
447 6.6
467 6.8
422 5.3
442 5.5
461 5.7
Note: The above cost estimates assume a boiler burning 3 Ib/MMBtu SO2 Content Bituminous Coal for LSFO and 2 Ib/MMBtu SO2 Content Bituminous Coal for LSD.
5-4
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5.2 Nitrogen Oxides Control Technology
The EPA Base Case v.5.13 includes two categories of NOX reduction technologies: combustion and post-
combustion controls. Combustion controls reduce NOX emissions during the combustion process by
regulating flame characteristics such as temperature and fuel-air mixing. Post-combustion controls
operate downstream of the combustion process and remove NOX emissions from the flue gas. All the
specific combustion and post-combustion technologies included in EPA Base Case v.5.13 are
commercially available and currently in use in numerous power plants.
5.2.1 Combustion Controls
The EPA Base Case v.5.13 representation of combustion controls uses equations that are tailored to the
boiler type, coal type, and combustion controls already in place and allow appropriate additional
combustion controls to be exogenously applied to generating units based on the NOX emission limits they
face. Characterizations of the emission reductions provided by combustion controls are presented in
Table 3-1.3 in Attachment 3-1. The EPA Base Case v.5.13 cost assumptions for NOX Combustion
Controls are summarized in Table 5-4. Table 3-11 provides a mapping of existing coal unit configurations
and incremental combustion controls applied in EPA Base Case v.5.13 when units under certain
conditions are assumed to achieve a state-of-the-art combustion control configuration.
Table 5-4 Cost (2011$) of NOX Combustion Controls for Coal Boilers (300 MW Size)
Boiler Type
Dry Bottom Wall-
Fired
Tangentially-Fired
Vertically-Fired
Technology
Low NOX Burner without Overfire Air (LNB without OFA)
Low NOX Burner with Overfire Air (LNB with OFA)
Low NOX Coal-and-Air Nozzles with Close-Coupled
Overfire Air (LNC1)
Low NOX Coal-and-Air Nozzles with Separated Overfire
Air(LNC2)
Low NOX Coal-and-Air Nozzles with Close-Coupled and
Separated Overfire Air (LNC3)
NOX Combustion Control
Fixed Variable
Capital O&M O&M
($/kW) ($/kW-yr) (mills/kWh)
48 0.3 0.07
65 0.5 0.09
26 0.2 0.00
35 0.2 0.03
41 0.3 0.03
31 0.2 0.06
Scaling Factor
The following scaling factor is used to obtain the capital and fixed operating and maintenance costs applicable to the
capacity (in MW) of the unit taking on combustion controls. No scaling factor is applied in calculating the variable
operating and maintenance cost.
LNB without OFA & LNB with OFA = ($/kW forXMW Unit) = ($/kW for 300 MW Unit) x (300/X)0359
LNC1, LNC2, and LNC3 = ($/kW forXMW Unit) = ($/kWfor 300 MW Unit) x (300/X)0359
Vertically-Fired = ($/kW forXMW Unit) = ($/kW for 300 MW Unit) x (300/X)0553
where ($/kW for 300 MW Unit) is a value from the above table and X is the capacity (in MW) of the unit taking on
combustion controls.
5.2.2 Post-combustion NOX Controls
The EPA Base Case v.5.13 includes two post-combustion retrofit NOX control technologies for existing
coal units: Selective Catalytic Reduction (SCR) and Selective Non-Catalytic Reduction (SNCR). In EPA
Base Case v.5.13 oil/gas steam units are eligible for SCR only. NOX reduction in a SCR system takes
place by injecting ammonia (NH3) vapor into the flue gas stream where the NOX is reduced to nitrogen
(N2) and water (H2O) abetted by passing over a catalyst bed typically containing titanium, vanadium
oxides, molybdenum, and/or tungsten. As its name implies, SNCR operates without a catalyst. In SNCR
a nitrogenous reducing agent (reagent), typically urea or ammonia, is injected into, and mixed with, hot
flue gas where it reacts with the NOX in the gas stream reducing it to nitrogen gas and water vapor. Due
5-5
-------
to the presence of a catalyst, SCR can achieve greater NOX reductions than SNCR. However, SCR costs
are higher than SNCR costs.
Table 5-5 summarizes the performance and applicability assumptions in EPA Base Case v.5.13 for each
post-combustion NOX control technology and provides a cross-reference to information on cost
assumptions.
Table 5-5 Summary of Retrofit NOX Emission Control Performance Assumptions
Control Performance
Assumptions
Unit Type
Percent Removal
Rate Floor
Size Applicability
Costs (2011$)
Selective Catalytic Reduction
(SCR)
Coal
90%
Bituminous: 0.07 Ib/MMBtu
Subbituminous and Lignite: 0.05
Ib/MMBtu
Units > 25 MW
See Table 5-6 Illustrative Post-
combustion NOx Control
Costs (201 1$) for Coal Plants
for Representative Sizes and
Heat Rates under the
Assumptions in EPA Base
Case v.5.13
Oil/Gas
80%
-
Units > 25
MW
See Table
5-7
Selective Non-Catalytic
Reduction
(SNCR)
Coal
Pulverized Coal: 25%
Fluidized Bed: 50%
Pulverized Coal: 0.1 Ib/MMBtu
Fluidized Bed: 0.08 Ib/MMBtu
Pulverized Coal: Units >25 MW
and<100MW
Fluidized Bed: Units > 25 MW
See Table 5-6 Illustrative Post-
combustion NOx Control Costs
(201 1 $) for Coal Plants for
Representative Sizes and Heat
Rates under the Assumptions
in EPA Base Case v.5.13
5.2.3 Methodology for Obtaining SCR Costs for Coal
Sargent and Lundy's updated performance/cost models for SCR and SNCR technologies are
implemented in EPA Base Case v.5.13 to develop the capital, fixed O&M (FOM), and variable O&M
(VOM) components of cost. See Attachments 5-3 and 5-4 (www.epa.gov/airmarkets/progsregs/epa-
ipm/BaseCasev513.html).
Table 5-6 presents the SCR and SNCR capital, VOM, and FOM costs and capacity and heat rate
penalties for an illustrative set of coal generating units with a representative range of capacities and heat
rates.
5-6
-------
Table 5-6 Illustrative Post-combustion NOX Control Costs (2011$) for Coal Plants for Representative Sizes and Heat Rates under the
Assumptions in EPA Base Case v.5.13
Control
Type
SCR
SNCR-
Tangential
SNCR-
Fluidized
Bed
Heat Rate
(Btu/kWh)
9,000
10,000
1 1 ,000
9,000
10,000
1 1 ,000
9,000
10,000
1 1 ,000
Capacity
Penalty
(%)
-0.54
-0.56
-0.58
-0.05
-0.05
Heat Rate
Penalty
(%)
0.54
0.56
0.59
0.78
0.78
Variable O&M
(mills/kWh)
1.23
1.32
1.41
1.04
1.15
1.27
1.04
1.15
1.27
Capacity (MW)
100
Fixed
Capital O&M
Cost ($/kW-
($/kW) yr)
321 1.76
349 1 .86
377 1.96
55 0.48
56 0.50
57 0.51
41 0.36
42 0.37
43 0.38
300
Fixed
Capital O&M
Cost ($/kW-
($/kW) yr)
263 0.76
287 0.81
311 0.87
30 0.26
30 0.27
31 0.27
22 0.20
23 0.20
23 0.21
500
Fixed
Capital O&M
Cost ($/kW-
($/kW) yr)
243 0.64
266 0.69
289 0.73
22 0.20
23 0.20
23 0.21
17 0.15
17 0.15
17 0.15
700
Fixed
Capital O&M
Cost ($/kW-
($/kW) yr)
232 0.58
255 0.63
277 0.67
18 0.16
19 0.17
19 0.17
14 0.12
14 0.12
14 0.13
1000
Fixed
Capital O&M
Cost ($/kW-
($/kW) yr)
222 0.53
244 0.57
265 0.62
15 0.13
15 0.14
16 0.14
11 0.10
12 0.10
12 0.10
Note: Assumes a boiler burning bituminous coal with an input NOX rate of 0.5 Ibs/MMBtu. The technology is applied to boilers larger than 25 MW.
5-7
-------
5.2.4 Methodology for Obtaining SCR Costs for Oil/Gas Steam Units
The cost calculations for SCR described in section 5.2.2 apply to coal units. For SCR on oil/gas steam
units the cost calculation procedure shown in Table 5-7 is used in EPA Base Case v.5.13. The scaling
factor for capital and fixed O&M costs, described in footnote a, applies to all size units from 25 MW and
up.
Table 5-7 Post-Combustion NOX Controls for Oil/Gas Steam Units in EPA Base Case v.5.13
Post-Combustion
Control Technology
SCRa
Capital
($/kW)
80
Fixed O&M
($/kW-yr)
1.16
Variable O&M
($/MWh)
0.13
Percent
Removal
80%
Notes:
The "Coefficients" in the table above are multiplied by the terms below to determine costs.
"MW" in the terms below is the unit's capacity in megawatts.
Cost data are adjusted to 2011$ by EPA.
SCR Capital Cost and Fixed O&M: (200/MW)035
SCR Cost Equations:
:R Capital Cost and Fi>
The scaling factors shown above apply up to 500 MW. The cost obtained for a 500 MW unit applies for units larger than 500 MW.
Example for 275 MW unit:
SCR Capital Cost ($/kW) = 80 * (200/275)ฐ35 = 71.64 $/kW
SCR FOM Cost ($/kW-yr) = 1.16* (200/275)035 = 1.04 $/kW-yr
SCR VOM Cost ($/MWh) = 0.13 $/MWh
5.2.5 Methodology for Obtaining SNCR Costs
In the Sargent and Lundy's cost update for SNCR a generic NOX removal efficiency of 25% is assumed.
However, the capital, fixed and variable operating and maintenance costs of SNCR on circulating
fluidized bed (CFB) units are distinguished from the corresponding costs for other boiler types (e.g.
cyclone, and wall fired). As with SCR an air heater modification cost applies for plants that burn
bituminous coal whose SO2 content is 3 Ibs/MMBtu or greater.
5.2.6 SO2 and NOX Controls for Units with Capacities from 25 MW to 100 MW (25 MW < capacity
<100MW)
In EPA Base Case v.5.13 coal units with capacities between 25 MW and 100 MW are offered the same
SO2 and NOX emission control options as larger units. However, for purposes of modeling, the costs of
controls for these units are assumed to be equivalent to that of a 100 MW unit for SCR, 50 MW for Dry
FGD, and 100 MW for Wet FGD. These assumptions are based on several considerations. First, to
achieve economies of scale, several units in this size range are likely to be ducted to share a single
common control, so the minimum capacity cost equivalency assumption, though generic, would be
technically plausible. Second, single units in this size range that are not grouped to achieve economies
of scale are likely to have the option of hybrid multi-pollutant controls currently under development.25
These hybrid controls achieve cost economies by combining SO2, NOX and particulate controls into a
single control unit. Singly, the costs of the individual control would be higher for units below 100 MWthan
for a 100 MW unit, but when combined in the Multi-Pollutant Technologies (MPTs) their costs would be
roughly equivalent to the cost of individual controls on a 100 MW unit. While MPTs are not explicitly
represented in EPA Base Case v.5.13, single units in the 25-100 MW range that take on combinations of
SO2 and NOX controls in a model run can be thought of as being retrofitted with an MPT.
25 See, for example, the Greenidge Multi-Pollutant Control Project, which was part of the U.S. Department of Energy,
National Energy Technology Lab's Power Plant Improvement Initiative. A joint effort of CONSOL Energy Inc. AES
Greenidge LLC, and Babcock Power Environmental, Inc., the project is described in greater detail at
www.netl.doe.ciov/technolociies/coalpower/cctc/PPII/bibliociraphv/demonstration/environmental/bib greenidcie.html.
5-8
-------
Illustrative SCR costs for 25-100 MW coal units with a range of heat rates can be found by referring to the
100 MW "Capital Costs ($/kW)" and "Fixed O&M" columns in Table 5-6 and illustrative scrubber costs for
25-100 MW coal units with a range of heat rates can be found by referring to the LSFO 100 MW and LSD
50MW "Capital Costs ($/kW)" and "Fixed O&M" columns in Table 5-3. The Variable O&M cost
component, which applies to units regardless of size, can be found in the fifth column in these tables.
5.3 Biomass Co-firing
Biomass co-firing is provided as a fuel choice for all coal-fired power plants in EPA Base Case v.5.13.
However, logistics and boiler engineering considerations place limits on the extent of biomass that can be
fired. The logistic considerations arise because it is only economic to transport biomass a limited
distance from where it is grown given the low energy density of the fuel. In addition, the extent of storage
that can be devoted at a power plant to this relatively low density fuel is another limiting factor. Boiler
efficiency and other engineering considerations, largely due to the relatively higher moisture content and
lower heat content of biomass compared to fossil fuel, also plays a role in limiting the level of co-firing.
In EPA Base Case v.5.13 the limit on biomass co-firing is expressed as the percentage of the facility level
power output that is produced from biomass. Based on analysis by EPA's power sector engineering staff,
a maximum of 10% of the facility level power output (not to exceed 50 MW) can be fired by biomass in
modeling projections. In EPA Base Case v.5.13 "facility level" is defined as the set of generating units
which share the same ORIS code26 in NEEDS v.5.13.
The capital and FOM cost assumptions informing EPA Base Case v.5.13 regarding biomass co-firing are
summarized in Table 5-8, developed by EPA's power sector engineering staff and updated to 2011$.27
Table 5-8 Biomass Co-firing for Coal Plants
Output From Biomass (MW)
Capital Cost (2011 $/kW From Biomass)
Fixed O&M (2011$/kW-yr)
5
521
25.8
10
439
17.3
15
396
12.5
20
368
10.0
25
349
8.5
30
333
11.8
35
320
10.6
40
309
9.5
45
301
8.6
50
293
8.0
In order to economize on model space, instead of designing a biomass co-firing "retrofit" modification for
units that would include direct representations of the capital and FOM costs shown in Table 5-8. The
26 The ORIS plant locator code is a unique identifying number (originally assigned by the Office of Regulatory
Information Systems from which the acronym derived). The ORIS code is given to power plants by EIA and remains
unchanged ownership changes.
27 Among the studies consulted in developing these costs were:
(a) Briggs, J. and J. M. Adams, Biomass Combustion Options for Steam Generation, Presented at Power-Gen
97, Dallas, TX, December 9-11,1997.
(b) Grusha, J and S. Woldehanna, K. McCarthy, and G. Heinz, Long Term Results from the First US Low NOx
Conversion of a Tangential Lignite Fired Unit, presented at 24th International Technical Conference on
Coal & Fuel Systems, Clearwater, FL, March 8-11, 1999.
(c) EPRI, Biomass Co-firing: Field Test Results: Summary of Results of the Bailly and Seward
Demonstrations, Palo Alto, CA, supported by U.S. Department of Energy Division of Energy Efficiency and
Renewable Energy, Washington D.C.; U.S. Department of Energy Division Federal Energy Technology
Center, Pittsburgh PA; Northern Indiana Public Service Company, Merrillville, IN; and GPU Generation,
Inc., Johnstown, PA: 1999. TR-113903.
(d) Laux S., J. Grusha, and D. Tillman, Co-firing of Biomass and Opportunity Fuels in Low NOx Burners,
PowerGen 2000 - Orlando, FL, www.fwc.com/publications/tech papers/powqen/pdfs/clrw bio.pdf.
(e) Tillman, D. A., Co-firing Biomass for Greenhouse Gas Mitigation, presented at Power-Gen 99, New
Orleans, LA, November 30 - December 1, 1999.
(f) Tillman, D. A. and P. Hus, Blending Opportunity Fuels with Coal for Efficiency and Environmental Benefit,
presented at 25th International Technical Conference on Coal Utilization & Fuel Systems, Clearwater, FL.,
March 6-9, 2000
5-9
-------
capital and FOM costs were implemented by in EPA Base Case v.5.13 as a $/MMBtu biomass fuel cost
adder. The discrete costs shown in Table 5-8 are first represented as continuous exponential cost
functions showing the FOM and capital costs for all biomass outputs between 0 and 50 MW in size. Then,
for every coal generating unit represented in EPA Base Case 5.13, the annual payment to capital for the
biomass co-firing capability was derived by multiplying the total capital cost obtained from the capital cost
exponential function by a 12.1% capital charge rate for utility-owned units and a 16.47% capital charge
rate for merchant units. The resulting value was added to the annual FOM cost obtained from the FOM
exponential function to obtain the total annual cost for the biomass co-firing for each generating unit.
Then, the annual amount of fuel (in MMBtus) required for each generating unit was derived by multiplying
the size of a unit (in MW) by its heat rate (in Btu/kWh) by its capacity factor (in percent) by 8,760 hours
(i.e., the number of hours in a year). Dividing the resulting value by 1000 yielded the annual fuel required
by the generating unit in MMBtus. Dividing this number into the previously calculated total annual cost for
biomass co-firing capability resulted in the cost of biomass co-firing per MMBtu of biomass combusted.
This was represented in IPM as a fuel cost adder incurred when a coal unit co-fires biomass. In this
manner, the model's decision process for determining biomass consumption takes into account not just
the cost of the biomass fuel, but also the capital and FOM costs associated with biomass co-firing at the
units in question.
Chapter 11 discusses factors related to the delivered cost of biomass fuel in EPA Base Case v.5.13.
5.4 Mercury Control Technologies
For any power plant, mercury emissions depend on the mercury content of the fuel used, the combustion
and physical characteristics of the unit, and the emission control technologies deployed. In the absence of
activated carbon injection (ACI), mercury emission reductions below the mercury content of the fuel are
strictly due to characteristics of the combustion process and incidental removal resulting from other
pollution control technologies, e.g., the SO2, NOX, and particulate matter controls. The following
discussion is divided into three parts. Sections 5.4.1 and 5.4.2 explain the two factors that determine
mercury emissions that result from unit configurations lacking ACI under EPA Base Case v.5.13. Section
5.4.1 discusses how mercury content of fuel is modeled in EPA Base Case v.5.13. Section 5.4.2 looks at
the procedure used to capture the mercury reductions resulting from different unit and (non-mercury)
control configurations. Section 5.4.4 explains the mercury emission control options that are available
under EPA Base Case v.5.13. Each section indicates the data sources and methodology used.
5.4.1 Mercury Content of Fuels
Coal: The assumptions in EPA Base Case v.5.13 on the mercury content of coal (and the majority of
emission modification factors discussed below in Section 5.4.2) are derived from EPA's "Information
Collection Request for Electric Utility Steam Generating Unit Mercury Emissions Information Collection
Effort" (ICR). A two-year effort initiated in 1998 and completed in 2000, the ICR had three main
components: (1) identifying all coal-fired units owned and operated by publicly-owned utility companies,
Federal power agencies, rural electric cooperatives, and investor-owned utility generating companies, (2)
obtaining "accurate information on the amount of mercury contained in the as-fired coal used by each
electric utility steam generating unit... with a capacity greater than 25 megawatts electric [MWe]), as well
as accurate information on the total amount of coal burned by each such unit," and (3) obtaining data by
coal sampling and stack testing at selected units to characterize mercury reductions from representative
unit configurations.
28 Data from the ICR can be found at http://www.epa.qov/ttn/atw/combust/utiltox/mercurv.html.
In 2009, EPA collected some additional information regarding mecury through the Collection Effort for New and
Existing Coal- and Oil-Fired Electricty Utility Steam Generating Units (EPA ICR No.2362.01 (OMB Control Number
2060-0631), however the information collected was not similarly comprehensive and was thus not used to update
mercury assumptions in this EPA base case.
5-10
-------
The ICR resulted in more than 40,000 data points indicating the coal type, sulfur content, mercury content
and other characteristics of coal burned at coal-fired utility units greater than 25 MW. To make this data
usable, these data points were first grouped by IPM coal types and IPM coal supply regions. IPM coal
types divide bituminous, subbituminous, and lignite coal into different grades based on sulfur content.
Oil, natural gas, and waste fuels: The EPA Base Case v.5.13 also includes assumptions on the mercury
content for oil, gas and waste fuels, which were based on data derived from previous EPA analysis of
mercury emissions from power plants.29 Table 5-9 provides a summary of the assumptions on the
mercury content for oil, gas and waste fuels included in EPA Base Case v.5.13.
Table 5-9 Assumptions on Mercury Concentration in Non-Coal Fuel in EPA Base Case v.5.13
Fuel Type
Oil
Natural Gas
Petroleum Coke
Biomass
Municipal Solid Waste
Geothermal Resource
Mercury Concentration (Ibs/TBtu)
0.48
0.00 a
2.66 b
0.57
71.85
2.97-3.7
Note:
a The values appearing in this table are rounded to two decimal places. The zero value shown for natural gas is based on an EPA
study that found a mercury content of 0.000138 Ibs/TBtu. Values for geothermal resources represent a range.
b A previous computational error in the mercury emission factor for petroleum coke as presented in Table 6-3 of the EPA report
titled Control of Mercury Emissions from Coal-fired Electric Utility Boilers: Interim Report Including Errata, 3-21-02 was corrected
(from 23.18 Ibs/TBtu to 2.66 Ib/TBtu) based on re-examination of the 1999 ICR data for petroleum coke and implementation of a
procedure for flagging and excluding outlier values above the 95 percentile value.
5.4.2 Mercury Emission Modification Factors
Emission Modification Factors (EMFs) represent the mercury reductions attributable to the specific burner
type and configuration of SO2, NOX, and particulate matter control devices at an electric generating unit.
An EMF is the ratio of outlet mercury concentration to inlet mercury concentration, and depends on the
unit's burner type, particulate control device, post-combustion NOX control and SO2 scrubber control. In
other words, the mercury reduction achieved (relative to the inlet) during combustion and flue-gas
treatment process is (1-EMF). The EMF varies by the type of coal (bituminous, subbituminous, and
lignite) used during the combustion process.
Deriving EMFs involves obtaining mercury inlet data by coal sampling and mercury emission data by
stack testing at a representative set of coal units. As noted above, EPA's EMFs were initially based on
1999 mercury ICR emission test data. More recent testing conducted by the EPA, DOE, and industry
participants3 has provided a better understanding of mercury emissions from electric generating units
and mercury capture in pollution control devices. Overall the 1999 ICR data revealed higher levels of
mercury capture for bituminous coal-fired plants than for subbituminous and lignite coal-fired plants, and
significant capture of ionic Hg in wet-FGD scrubbers. Additional mercury testing indicates that for
bituminous coals, SCR systems have the ability to convert elemental Hg into ionic Hg and thus allow
easier capture in a downstream wet-FGD scrubber. This understanding of mercury capture with SCRs is
incorporated in EPA Base Case v.5.13 mercury EMFs for unit configurations with SCR and wet
scrubbers.
29 Analysis of Emission Reduction Options for the Electric Power Industry," Office of Air and Radiation, US EPA,
March 1999.
30 For a detailed summary of emissions test data see Control of Emissions from Coal-Fired Electric Utility Boilers: An
Update, EPA/Office of Research and Development, February 2005. This report can be found at
www.epa.qov/ttnatw01/utilitv/hqwhitepaperfinal.pdf.
5-11
-------
Table 5-10 below provides a summary of EMFs used in EPA Base Case v.5.13. Table 5-11 provides
definitions of acronyms for existing controls that appear in
5-12
-------
Table 5-16. Table 5-12 provides a key to the burner type designations appearing in
5-13
-------
Table 5-16.
Table 5-10 Mercury Emission Modification Factors Used in EPA Base Case v.5.13
Burner
Type
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Cyclone
Participate Control
Cold Side ESP
Cold Side ESP
Cold Side ESP
Cold Side ESP
Cold Side ESP
Cold Side ESP
Cold Side ESP + FF
Cold Side ESP + FF
Cold Side ESP + FF
Cold Side ESP + FF
Cold Side ESP + FF
Cold Side ESP + FF
Cold Side ESP +
FGC
Cold Side ESP +
FGC
Cold Side ESP +
FGC
Cold Side ESP +
FGC
Cold Side ESP +
FGC
Cold Side ESP +
FGC
Cold Side ESP +
FGC + FF
Cold Side ESP +
FGC + FF
Cold Side ESP +
FGC + FF
Cold Side ESP +
FGC + FF
Cold Side ESP +
FGC + FF
Cold Side ESP +
FGC + FF
Fabric Filter
Fabric Filter
Fabric Filter
Fabric Filter
Fabric Filter
Fabric Filter
Hot Side ESP
Hot Side ESP
Hot Side ESP
Hot Side ESP
Hot Side ESP
Hot Side ESP
Hot Side ESP + FF
Hot Side ESP + FF
Hot Side ESP + FF
Hot Side ESP + FF
Hot Side ESP + FF
Hot Side ESP + FF
Hot Side ESP + FGC
Hot Side ESP + FGC
Hot Side ESP + FGC
Hot Side ESP + FGC
Hot Side ESP + FGC
Hot Side ESP + FGC
Post-combustion
Control - NOX
SCR
SCR
SCR
No SCR
No SCR
No SCR
SCR
SCR
SCR
No SCR
No SCR
No SCR
SCR
SCR
SCR
No SCR
No SCR
No SCR
SCR
SCR
SCR
No SCR
No SCR
No SCR
SCR
SCR
SCR
No SCR
No SCR
No SCR
SCR
SCR
SCR
No SCR
No SCR
No SCR
SCR
SCR
SCR
No SCR
No SCR
No SCR
SCR
SCR
SCR
No SCR
No SCR
No SCR
Post-combustion
Control - SO2
None
Wet FGD
DryFGD
None
Wet FGD
DryFGD
None
Wet FGD
DryFGD
None
Wet FGD
DryFGD
None
Wet FGD
DryFGD
None
Wet FGD
DryFGD
None
Wet FGD
DryFGD
None
Wet FGD
DryFGD
None
Wet FGD
DryFGD
None
Wet FGD
DryFGD
None
Wet FGD
DryFGD
None
Wet FGD
DryFGD
None
Wet FGD
DryFGD
None
Wet FGD
DryFGD
None
Wet FGD
DryFGD
None
Wet FGD
DryFGD
Bituminous
EMF
0.64
0.1
0.64
0.64
0.34
0.64
0.2
0.1
0.05
0.2
0.3
0.05
0.64
0.1
0.64
0.64
0.34
0.64
0.2
0.1
0.1
0.2
0.1
0.1
0.11
0.1
0.05
0.11
0.1
0.05
0.9
0.1
0.6
0.9
0.58
0.6
0.11
0.1
0.05
0.11
0.03
0.05
0.9
0.1
0.6
0.9
0.58
0.6
Subbituminous
EMF
0.97
0.84
0.65
0.97
0.84
0.65
0.75
0.3
0.75
0.75
0.3
0.75
0.97
0.84
0.65
0.97
0.84
0.65
0.75
0.3
0.3
0.75
0.3
0.3
0.27
0.27
0.75
0.27
0.27
0.75
0.9
0.8
0.85
0.94
0.8
0.85
0.27
0.15
0.75
0.27
0.27
0.75
0.9
0.8
0.85
0.94
0.8
0.85
Lignite
EMF
1
0.56
1
1
0.56
1
1
0.56
1
1
0.56
1
1
0.56
1
1
0.56
1
1
0.56
0.56
1
0.56
0.56
1
0.56
1
1
0.56
1
1
1
1
1
1
1
1
0.56
1
1
0.56
1
1
1
1
1
1
1
5-14
-------
Burner
Type
Cyclone
Cyclone
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
Participate Control
No Control
No Control
Cold Side ESP
Cold Side ESP
Cold Side ESP + FF
Cold Side ESP + FF
Fabric Filter
Fabric Filter
Fabric Filter
Fabric Filter
Hot Side ESP + FGC
Hot Side ESP + FGC
No Control
Cold Side ESP
Cold Side ESP
Cold Side ESP
Cold Side ESP
Cold Side ESP
Cold Side ESP
Cold Side ESP + FF
Cold Side ESP + FF
Cold Side ESP + FF
Cold Side ESP + FF
Cold Side ESP + FF
Cold Side ESP + FF
Cold Side ESP +
FGC
Cold Side ESP +
FGC
Cold Side ESP +
FGC
Cold Side ESP +
FGC
Cold Side ESP +
FGC
Cold Side ESP +
FGC
Cold Side ESP +
FGC + FF
Cold Side ESP +
FGC + FF
Cold Side ESP +
FGC + FF
Cold Side ESP +
FGC + FF
Cold Side ESP +
FGC + FF
Cold Side ESP +
FGC + FF
Fabric Filter
Fabric Filter
Fabric Filter
Fabric Filter
Fabric Filter
Fabric Filter
Hot Side ESP
Hot Side ESP
Hot Side ESP
Hot Side ESP
Hot Side ESP
Hot Side ESP
Hot Side ESP + FF
Hot Side ESP + FF
Hot Side ESP + FF
Post-combustion
Control - NOX
SCR
No SCR
No SCR
No SCR
No SCR
No SCR
SCR
SCR
No SCR
No SCR
No SCR
No SCR
No SCR
SCR
SCR
SCR
No SCR
No SCR
No SCR
SCR
SCR
SCR
No SCR
No SCR
No SCR
SCR
SCR
SCR
No SCR
No SCR
No SCR
SCR
SCR
SCR
No SCR
No SCR
No SCR
SCR
SCR
SCR
No SCR
No SCR
No SCR
SCR
SCR
SCR
No SCR
No SCR
No SCR
SCR
SCR
SCR
Post-combustion
Control - SO2
Wet FGD
Wet FGD
None
Dry FGD
None
Dry FGD
None
Dry FGD
None
Dry FGD
None
Dry FGD
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Bituminous
EMF
0.1
0.1
0.65
0.64
0.05
0.05
0.11
0.05
0.05
0.05
1
0.6
1
0.64
0.1
0.64
0.64
0.34
0.64
0.2
0.1
0.05
0.2
0.3
0.05
0.64
0.1
0.64
0.64
0.34
0.64
0.2
0.1
0.05
0.2
0.3
0.05
0.11
0.1
0.05
0.11
0.1
0.05
0.9
0.1
0.6
0.9
0.58
0.6
0.11
0.1
0.05
Subbituminous
EMF
0.7
0.7
0.65
0.65
0.43
0.75
0.27
0.75
0.43
0.43
1
0.85
1
0.97
0.84
0.65
0.97
0.84
0.65
0.75
0.3
0.75
0.75
0.3
0.75
0.97
0.84
0.65
0.97
0.84
0.65
0.75
0.3
0.75
0.75
0.3
0.75
0.27
0.27
0.75
0.27
0.27
0.75
0.9
0.8
0.85
0.94
0.8
0.85
0.27
0.15
0.75
Lignite
EMF
1
1
0.62
1
0.43
1
1
1
0.43
0.43
1
1
1
1
0.56
1
1
0.56
1
1
0.56
1
1
0.56
1
1
0.56
1
1
0.56
1
1
0.56
1
1
0.56
1
1
0.56
1
1
0.56
1
1
1
1
1
1
1
1
0.56
1
5-15
-------
Burner
Type
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
Participate Control
Hot Side ESP + FF
Hot Side ESP + FF
Hot Side ESP + FF
Hot Side ESP + FGC
Hot Side ESP + FGC
Hot Side ESP + FGC
Hot Side ESP + FGC
Hot Side ESP + FGC
Hot Side ESP + FGC
Hot Side ESP + FGC
+ FF
Hot Side ESP + FGC
+ FF
Hot Side ESP + FGC
+ FF
No Control
No Control
No Control
No Control
No Control
No Control
PM Scrubber
PM Scrubber
PM Scrubber
PM Scrubber
PM Scrubber
PM Scrubber
Post-combustion
Control - NOX
No SCR
No SCR
No SCR
SCR
SCR
SCR
No SCR
No SCR
No SCR
SCR
No SCR
No SCR
SCR
SCR
SCR
No SCR
No SCR
No SCR
SCR
SCR
SCR
No SCR
No SCR
No SCR
Post-combustion
Control - SO2
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Dry FGD
None
Dry FGD
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Bituminous
EMF
0.11
0.03
0.05
0.9
0.1
0.6
0.9
0.58
0.6
0.05
0.11
0.05
1
0.1
0.6
1
0.58
0.6
0.9
0.1
0.6
0.9
0.58
0.6
Subbituminous
EMF
0.27
0.27
0.75
0.9
0.8
0.85
0.94
0.8
0.85
0.75
0.27
0.75
1
0.7
0.85
1
0.7
0.85
1
0.7
0.85
0.91
0.7
0.85
Lignite
EMF
1
0.56
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Table 5-11 Definition of Acronyms for Existing Controls
Acronym
Description
ESP
HESP
ESP/O
FF
FGD
DS
SCR
PMSCRUB
Electro Static Precipitator - Cold Side
Electro Static Precipitator - Hot Side
Electro Static Precipitator - Other
Fabric Filter
Flue Gas Desulfurization -Wet
Flue Gas Desulfurization - Dry
Selective Catalytic Reduction
Particulate Matter Scrubber
Table 5-12 Key to Burner Type Designations in Table 5-10
"PC" refers to conventional pulverized coal boilers. Typical configurations include wall-fired and tangentially fired
boilers (also called T-fired boilers). In wall-fired boilers the burner's coal and air nozzles are mounted on a single wall
or opposing walls. In tangentially fired boilers the burner's coal and air nozzles are mounted in each corner of the
boiler.
"Cyclone" refers to cyclone boilers where air and crushed coal are injected tangentially into the boiler through a
"cyclone burner" and "cyclone barrel" which create a swirling motion allowing smaller coal particles to be burned in
suspension and larger coal particles to be captured on the cyclone barrel wall where they are burned in molten slag.
"FBC" refers to "fluidized bed combustion" where solid fuels are suspended on upward-blowing jets of air, resulting in
a turbulent mixing of gas and solids and a tumbling action which provides especially effective chemical reactions and
heat transfer during the combustion process.
5-16
-------
5.4.3 Mercury Control Capabilities
EPA Base Case v.5.13 offers two options for mercury pollution control: (1) combinations of SO2, NOX, and
particulate controls which deliver mercury reductions as a co-benefit and (2) Activated Carbon Injection
(ACI), a retrofit option specifically designed for mercury control. These two options are discussed below.
Mercury Control through SO? and NOy_Retrofits
In EPA Base Case v.5.13, units that install SO2, NOX, and particulate controls, reduce mercury emissions
as a byproduct of these retrofits. Section 5.4.2 described how EMFs are used in the base case to capture
mercury emissions depending on the rank of coal burned, the generating unit's combustion characteristics,
and the specific configuration of SO2, NOX, and particulate controls (i.e., hot and cold-side electrostatic
precipitators (ESPs), fabric filters (also called "baghouses") and particulate matter (PM) scrubbers).
Activated Carbon Injection (ACI)
The technology used for mercury control in EPA Base Case v.5.13 is Activated Carbon Injection (ACI)
downstream of the combustion process in coal fired units. Sargent & Lundy's updated cost and
performance assumptions for ACI are used.
Three alternative ACI options are represented as capable of providing 90% mercury removal for all possible
configurations of boiler, emission controls, and coal types used in the U.S. electric power sector. The
three ACI options differ, based on whether they are used in conjunction with an electrostatic precipitator
(ESP) or a fabric filter (also called a "baghouse"). The three ACI options are:
ACI with Existing ESP
ACI with Existing Baghouse
ACI with an Additional Baghouse (also referred to as Toxecon)
In the third option listed above the additional baghouse is installed downstream of the pre-existing
particulate matter device and the activated carbon is injected after the existing controls. This configuration
allows the fly ash to be removed before it is contaminated by the mercury.
For modeling purposes, EPA currently assumes that all three configurations use brominated ACI, where a
small amount of bromine is chemically bonded to the powdered carbon which is injected into the flue gas
stream. EPA recognizes that amended silicates and possibly other non-carbon, non-brominated
substances are in development and may become available as alternatives to brominated carbon as a
mercury sorbent.
The applicable ACI option depends on the coal type burned, its SO2 content, the boiler and particulate
control type and, in some instances, consideration of whether an SO2 scrubber (FGD) system and SCR
NOX post-combustion control are present.
5-17
-------
Table 5-13 shows the ACI assignment scheme used in EPA Base Case v.5.13to achieve 90% mercury
removal.
5-18
-------
Table 5-13 Assignment Scheme for Mercury Emissions Control Using Activated Carbon Injection
(ACI) in EPA Base Case v.5.13
Air pollution controls
Burner SCR FGD
Type Participate Control Type System System
FBC Cold Side ESP + Fabric Filter without FGC -
FBC Cold Side ESP without FGC
FBC Fabric Filter - Dry FGD
FBC Fabric Filter
FBC Hot Side ESP with FGC
Non-FBC Cold Side ESP + Fabric Filter with FGC - Dry FGD
Non-FBC Cold Side ESP + Fabric Filter with FGC
Non-FBC Cold Side ESP + Fabric Filter with FGC - Wet FGD
Non-FBC Cold Side ESP + Fabric Filter with FGC SCR
Non-FBC Cold Side ESP + Fabric Filter with FGC SCR Dry FGD
Non-FBC Cold Side ESP + Fabric Filter with FGC SCR Wet FGD
Non-FBC Cold Side ESP + Fabric Filter without FGC - Dry FGD
Non-FBC Cold Side ESP + Fabric Filter without FGC -
Non-FBC Cold Side ESP + Fabric Filter without FGC - Wet FGD
Non-FBC Cold Side ESP + Fabric Filter without FGC SCR
Non-FBC Cold Side ESP + Fabric Filter without FGC SCR Dry FGD
Non-FBC Cold Side ESP + Fabric Filter without FGC SCR Wet FGD
Non-FBC Cold Side ESP with FGC - Dry FGD
Non-FBC Cold Side ESP with FGC
Non-FBC Cold Side ESP with FGC - Wet FGD
Non-FBC Cold Side ESP with FGC SCR
Non-FBC Cold Side ESP with FGC SCR Dry FGD
Non-FBC Cold Side ESP with FGC SCR Wet FGD
Non-FBC Cold Side ESP without FGC - Dry FGD
Non-FBC Cold Side ESP without FGC
Non-FBC Cold Side ESP without FGC - Wet FGD
Non-FBC Cold Side ESP without FGC SCR
Non-FBC Cold Side ESP without FGC SCR Dry FGD
Non-FBC Cold Side ESP without FGC SCR Wet FGD
Non-FBC Fabric Filter - Dry FGD
Non-FBC Fabric Filter
Non-FBC Fabric Filter - Wet FGD
Non-FBC Fabric Filter SCR Dry FGD
Non-FBC Fabric Filter SCR
Non-FBC Fabric Filter SCR Wet FGD
Non-FBC Hot Side ESP + Fabric Filter with FGC
Non-FBC Hot Side ESP + Fabric Filter with FGC - Wet FGD
Non-FBC Hot Side ESP + Fabric Filter with FGC - Dry FGD
Non-FBC Hot Side ESP + Fabric Filter with FGC SCR Wet FGD
Non-FBC Hot Side ESP + Fabric Filter with FGC SCR Dry FGD
Non-FBC Hot Side ESP + Fabric Filter with FGC SCR
Non-FBC Hot Side ESP + Fabric Filter without FGC - Dry FGD
Non-FBC Hot Side ESP + Fabric Filter without FGC -
Non-FBC Hot Side ESP + Fabric Filter without FGC - Wet FGD
Non-FBC Hot Side ESP + Fabric Filter without FGC SCR Dry FGD
Non-FBC Hot Side ESP + Fabric Filter without FGC SCR
Non-FBC Hot Side ESP + Fabric Filter without FGC SCR Wet FGD
Non-FBC Hot Side ESP with FGC - Dry FGD
Non-FBC Hot Side ESP with FGC
Non-FBC Hot Side ESP with FGC - Wet FGD
Non-FBC Hot Side ESP with FGC SCR Dry FGD
Non-FBC Hot Side ESP with FGC SCR
Bituminous Coal
Sorbentlnj
Rate
ACI Toxecon (Ib/million
Required? Required? acf)
Yes No 2
Yes No 5
No No 0
Yes No 2
Yes Yes 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes No 5
Yes No 5
Yes No 5
Yes No 5
Yes No 5
Yes No 5
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
No No 0
Yes No 2
No No 0
Yes No 2
No No 0
Yes No 2
Yes No 2
No No 0
Yes No 2
Yes No 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Subbituminous Coal
Sorbent Inj
Rate
ACI Toxecon (Ib/million
Required? Required? acf)
Yes No 2
Yes No 5
Yes No 2
Yes No 2
Yes Yes 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes No 5
Yes No 5
Yes No 5
Yes No 5
Yes No 5
Yes No 5
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Lignite Coal
Sorbentlnj
Rate
ACI Toxecon (Ib/million
Required? Required? acf)
Yes No 2
Yes No 5
Yes No 2
Yes No 2
Yes Yes 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes No 5
Yes No 5
Yes No 5
Yes No 5
Yes No 5
Yes No 5
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Y(b) No 2
Yes No 2
Y(b) No 2
Y(b) No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes No 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
5-19
-------
Air pollution controls
Burner SCR FGD
Type Particulate Control Type System System
Non-FBC Hot Side ESP with FGC SCR Wet FGD
Non-FBC Hot Side ESP without FGC - Dry FGD
Non-FBC Hot Side ESP without FGC
Non-FBC Hot Side ESP without FGC - Wet FGD
Non-FBC Hot Side ESP without FGC SCR Dry FGD
Non-FBC Hot Side ESP without FGC SCR
Non-FBC Hot Side ESP without FGC SCR Wet FGD
Non-FBC No Control - Dry FGD
Non-FBC No Control
Non-FBC No Control - Wet FGD
Non-FBC No Control SCR Dry FGD
Non-FBC No Control SCR
Non-FBC No Control SCR Wet FGD
Non-FBC PH Scrubber - Dry FGD
Non-FBC PH Scrubber
Non-FBC PH Scrubber - Wet FGD
Non-FBC PH Scrubber SCR Dry FGD
Non-FBC PH Scrubber SCR
Non-FBC PH Scrubber SCR Wet FGD
Bituminous Coal
Sorbent Inj
Rate
ACI Toxecon (Ib/million
Required? Required? act)
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Subbituminous Coal
Sorbent Inj
Rate
ACI Toxecon (Ib/million
Required? Required? act)
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Lignite Coal
Sorbent Inj
Rate
ACI Toxecon (Ib/million
Required? Required? act)
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
Yes Yes 2
5.4.4 Methodology for Obtaining ACI Control Costs
Sargent & Lundy's ACI model assumes that the carbon feed rate dictates the size of the equipment and
resulting costs. The feed rate in turn is a function of the required removal (in this case 90%) and the type
of particulate control device. Sargent & Lundy established that a carbon feed rate of 5 pounds of carbon
injected for every 1,000,000 actual cubic feet per minute (acfm) of flue gas would provide the stipulated
90% mercury removal rate for units shown in Table 5-14 as qualifying for ACI systems with existing ESP.
For generating units with fabric filters a lower injection rate of 2 pound per million acfm is required.
Alternative sets of costs were developed for each of the three ACI options: ACI systems for units with
existing ESPs, ACI for units with existing fabric filters (baghouses), and the combined cost of ACI plus an
additional baghouse for units that either have no existing particulate control or that require ACI plus a
baghouse in addition to their existing particulate control. There are various reasons that a combined ACI
plus additional baghouse would be required. These include situations where the existing ESP cannot
handle the additional particulate load associate with the ACI or where SO3 injection is currently in use to
condition the flue gas for the ESP. Another cause for combined ACI and baghouse is use of PRB coal
whose combustion produces mostly elemental mercury, not ionic mercury, due to this coal's low chlorine
content.
For the combined ACI and fabric filter option a full size baghouse with an air-to-cloth (A/C) ratio of 4.0 is
assumed, as opposed to a polishing baghouse with a 6.0 A/C ratio
31
Table 5-14 presents the capital, VOM, and FOM costs as well as the capacity and heat rate penalties for
the three ACI options represented in EPA Base Case v.5.13. For each ACI option values are shown for
an illustrative set of generating units with a representative range of capacities and heat rates. See
Attachment 5-6 (www.epa.qov/airmarkets/proqsreqs/epa-ipm/BaseCasev513.html) for details on the
Sargent & Lundy model of ACI for Hq control.
The "air-to-cloth" (A/C) ratio is the volumetric flow, (typically expressed in Actual Cubic Feet per Minute, ACFM) of flue gas
entering the baghouse divided by the areas (typically in square feet) of fabric filter cloth in the baghouse. The lower the A/C ratio,
e.g., A/C = 4.0 compared to A/C = 6.0, the greater area of the cloth required and the higher the cost for a given volumetric flow
5-20
-------
5.5 Hydrogen Chloride (HCI) Control Technologies
The following sub-sections describe how HCI emissions from coal are represented in IPM for EPA Base
Case v.5.13, the emission control technologies available for HCI removal, and the cost and performance
characteristics of these technologies.
5.5.1 Chlorine Content of Fuels
HCI emissions from the power sector result from the chlorine content of the coal that is combusted by
electric generating units. Data on chlorine content of coals had been collected as part EPA's 1999
"Information Collection Request for Electric Utility Steam Generating Unit Mercury Emissions Information
Collection Effort" (ICR 1999) described above in section 5.4.1 This data is incorporated into the model in
order to provide the capability for EPA Base Case v.5.13 to project HCI emissions. The procedures used
for this are presented below.
Western subbituminous coal (such as that mined in the Powder River Basin) and lignite coal contain
natural alkalinity in the form of non-glassy calcium oxide (CaO) and other alkaline and alkaline earth
oxides. This fly ash (classified as 'Class C' fly ash) has a natural pH of 9 and higher and the natural
alkalinity can effectively neutralize much of the HCI in the flue gas stream prior to the primary control
device.
Eastern bituminous coals, by contrast, tend to produce fly ash with lower natural alkalinity. Though
bituminous fly ash (classified as 'Class F' fly ash) may contain calcium, it tends to be present in a glassy
matrix and unavailable for acid-base neutralization reactions.
In order to assess the extent of expected natural neutralization, the 2010 ICR32 data was examined.
According to that data, units burning some of the subbituminous coals without operating acid gas control
technology emitted substantially lower HCI emissions than would otherwise be expected from the chlorine
content of those coals The data also showed that some other units burning subbituminous or lignite coals
with higher levels of Cl were achieving 50-85 % HCI control with only cold-side ESP (i.e., with no flue gas
desulfurization or other acid gas control technology). Comparing the Cl content of the subbituminous
coals modeled in IPM with the ICR results supports an assumption that combustion of those coals can
expect to experience at least 75% natural HCI neutralization from the alkaline fly ash. Therefore, the HCI
emissions from combustion of lignite and subbituminous coals are reduced by 75% in EPA Base Case
v.5.13.
32 Collection Effort for New and Existing Coal- and Oil-Fired Electricty Utility Steam Generating Units (EPA ICR
No.2362.01 (OMB Control Number 2060-0631)
5-21
-------
Table 5-14 Illustrative Activated Carbon Injection (ACI) Costs (2011$) for Representative Sizes and Heat Rates
under the Assumptions in EPA Base Case v.5.13
Control Type
ACI System with an
Existing ESP
Sorbent Injection
Rate of 5 Ibs/million
acfm
ACI System with an
Existing Baghouse
Sorbent Injection
Rate of 2 Ibs/million
acfm
ACI System with an
Additional
Baghouse
Sorbent Injection
Rate of 2 Ibs/million
acfm
Heat Rate
(Btu/kWh)
9,000
10,000
1 1 ,000
9,000
10,000
1 1 ,000
9,000
10,000
1 1 ,000
Capacity
Penalty (%)
-0.10
-0.11
-0.12
-0.04
-0.04
-0.05
-0.64
-0.64
-0.65
Heat Rate
Penalty (%)
0.10
0.11
0.12
0.04
0.04
0.05
0.64
0.65
0.65
Variable O&M
cost (mills/kWh)
2.19
2.43
2.68
1.57
1.75
1.92
0.47
0.52
0.57
Capacity (MW)
100
Capital
Cost
($/kW)
37.89
38.51
39.07
33.03
33.54
34.02
291.26
314.32
336.91
Fixed
O&M
($/kW-yr)
0.32
0.32
0.33
0.28
0.28
0.29
1.02
1.10
1.18
300
Capital
Cost
($/kW)
14.90
15.14
15.35
12.98
13.18
13.38
219.74
238.18
256.26
Fixed
O&M
($/kW-yr)
0.13
0.13
0.13
0.11
0.11
0.11
0.77
0.83
0.90
500
Capital
Cost
($/kW)
9.65
9.81
9.95
8.41
8.54
8.66
195.35
212.02
228.37
Fixed
O&M
($/kW-yr)
0.08
0.08
0.08
0.07
0.07
0.07
0.68
0.74
0.80
700
Capital
Cost
($/kW)
7.25
7.36
7.47
6.32
6.42
6.51
181.36
196.97
212.28
Fixed
O&M
($/kW-yr)
0.06
0.06
0.06
0.05
0.05
0.06
0.63
0.69
0.74
1000
Capital
Cost
($/kW)
5.35
5.44
5.52
4.66
4.74
4.81
167.98
182.55
196.83
Fixed
O&M
($/kW-yr)
0.04
0.05
0.05
0.04
0.04
0.04
0.59
0.64
0.69
Note: The above cost estimates assume bituminous coal consumption.
5-22
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5.5.2 HCI Removal Rate Assumptions for Existing and Potential Units
SO2 emission controls on existing and new (potential) units provide the HCI reductions indicated in Table
5-15. New supercritical pulverized coal units (column 3) that the model builds include FGD (wet or dry)
which is assumed to provide a 99% removal rate for HCI. For existing conventional pulverized coal units
with pre-existing FGD (column 5), the HCI removal rate is assumed to be 5% higher than the reported SO2
removal rate up to a maximum of 99% removal. In addition, for fluidized bed combustion units (column 4)
with no FGD and no fabric filter, the HCI removal rate is assumed to be the same as the SO2 removal rate
up to a maximum of 95%. FBCs with fabric filters are assumed to have an HCI removal rate of 95%.
Table 5-15 HCI Removal Rate Assumptions for Potential (New) and Existing Units
in EPA Base Case v.5.13
Gas
HCI
Controls
Removal
Rate
Potential (New)
Supercritical
Pulverized Coal with
Wet or Dry FGD
99%
Existing Units with FGD
Fluidized Bed
Combustion (FBC)
Without fabric filter:
Same as reported SO2
removal rate up to a
maximum of
95%
With fabric filter: 95%
Conventional
Pulverized Coal (CPC)
with Wet or Dry FGD
Reported SO2
removal rate +
5% up to a
maximum of
99%
Existing Coal Steam Units with
FGD Upgrade Adjustment
If reported SO2 removal < 90%, unit
incurs cost to upgrade FGD, so that
SO2 removal is 90%. Then, the
resulting HCI removal rate is 99%
If reported SO2
removal is > 90% and
< 94%, then the unit incurs a cost to
upgrade FGD and the HCI removal
rate is 99%. (The SO2 removal rate
remains as reported.)
If the reported SO2 removal rate is >
94%, the unit incurs no upgrade cost
and the HCI removal rate is 99%.
In EPA Base Case v.5.13, coal steam units with existing FGD that do not achieve an SO2 removal rate of
at least 90% are assumed to upgrade their FGDs in order to obtain at least 90% SO2 removal and 99%
HCI removal. The cost of this "FGD Upgrade Adjustment" is assumed to be $100/kW and is considered
a sunk cost for modeling purposes.
5.5.3 HCI Retrofit Emission Control Options
The retrofit options for HCI emission control are discussed in detail in the following sub-sections and
summarized in
5-23
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Table 5-16. The scrubber upgrade adjustment was discussed above in 5.5.2.
Wet and Dry FGD
In addition to providing SO2 reductions, wet scrubbers (Limestone Forced Oxidation, LSFO) and dry
scrubbers (Lime Spray Dryer, LSD) reduce HCI as well. For both LSFO and LSD the HCI removal rate is
assumed to be 99% with a floor of 0.0001 Ibs/MMBtu. This is summarized in columns 2-5 of
5-24
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Table 5-16.
5-25
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Table 5-16 Summary of Retrofit HCI (and SO2) Emission Control Performance
Assumptions in v.5.13
Performance
Assumptions
Percent
Removal
Capacity
Penalty
Heat Rate
Penalty
Cost (2011$)
Applicability
Sulfur Content
Applicability
Applicable
Coal
Types
Limestone Forced Oxidation (LSFO)
SO2
96%
with a floor of
0.06 Ibs/MMBtu
HCI
99%
with a floor of
0.0001 Ibs/MMBtu
Calculated based on characteristics of
the unit:
See Table 5-3
Units > 25 MW
BA, BB, BD, BE, BG, BH, SA, SB, SD,
SE, LD, LE, LG, LH, PKandWC
Lime Spray Dryer (LSD)
SO2
92%
with a floor of
0.08 Ibs/MMBtu
HCI
99%
with a floor of
0.0001
Ibs/MMBtu
Calculated based on characteristics
of the unit:
See Table 5-3
Units >
25 MW
Coals < 3.0 Ibs of SO2/MMBtu
BA, BB, BD, BE, SA, SB, SD, SE, LD,
andLE
Dry Sorbent Injection (DSI)
SO2
70%
HCI
90%
with a floor of 0.0001
Ibs/MMBtu
Calculated based on
characteristics of the unit:
See
Excerpt from Table 5-22
Units > 25 MW
Coals < 2.0 Ibs of
SO2/MMBtu
BA, BB, BD, SA, SB, SD,
and LD
Dry Sorbent Injection
EPA Base Case v.5.13 includes dry sorbent injection (DSI) as a retrofit option for achieving (in
combination with a particulate control device) both SO2 and HCI removal. In DSI for HCI reduction, a dry
sorbent is injected into the flue gas duct where it reacts with the HCI and SO2 in the flue gas to form
compounds that are then captured in a downstream fabric filter or electrostatic precipitator (ESP) and
disposed of as waste. (A sorbent is a material that takes up another substance by either adsorption on its
surface or absorption internally or in solution. A sorbent may also chemically react with another
substance.) The sorbent assumed in the cost and performance characterization discussed in this section
is Trona (sodium sesquicarbonate), a sodium-rich material with major underground deposits found in
Sweetwater County, Wyoming. Trona is typically delivered with an average particle size of 30 urn
diameter, but can be reduced to about 15 urn through onsite in-line milling to increase its surface area and
capture capability.
Removal rate assumptions: The removal rate assumptions for DSI are summarized in
5-26
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Table 5-16. The assumptions shown in the last two columns of
5-27
-------
Table 5-16 were derived from assessments by EPA engineering staff in consultation with Sargent &
Lundy. As indicated in this table, the assumed SO2 removal rate for DSI + fabric filter is 70%. The retrofit
DSI option on an existing unit with existing ESP is always provided in combination with a fabric filter
(Toxecon configuration) in EPA Base Case v.5.13.
Methodology for Obtaining DSI Control Costs: Sargent & Lundy's updated performance/cost model for
DSI is used in EPA Base Case v.5.13 to derive the cost of DSI retrofits with two alternative, associated
particulate control devices, i.e., ESP and fabric filter "baghouse". Their analysis of DSI noted that the cost
drivers of DSI are quite different from those of wet or dry FGD. Whereas plant size and coal sulfur rates
are key underlying determinants of FGD cost, sorbent feed rate and fly ash waste handling are the main
drivers of the capital cost of DSI with plant size and coal sulfur rates playing a secondary role.
In EPA Base Case v.5.13 the DSI sorbent feed rate and variable O&M costs are based on assumptions
that a fabric filter and in-line trona milling are used, and that the SO2 removal rate is 70%. The
corresponding HCI removal effect is assumed to be 90%, based on information from Solvay Chemicals (H.
Davidson, Dry Sorbent Injection for Multi-pollutant Control Case Study, CIBO IECT VIM, August, 2010).
The cost of fly ash waste handling, the other key contributorto DSI cost, is a function of the type of
particulate capture device and the flue gas SO2.
Total waste production involves the production of both reacted and unreacted sorbent and fly ash.
Sorbent waste is a function of the sorbent feed rate with an adjustment for excess sorbent feed. Use of
sodium-based DSI may make the fly ash unsalable, which would mean that any fly ash produced must be
landfilled along with the reacted and unreacted sorbent waste. Typical ash contents for each fuel are used
to calculate a total fly ash production rate. The fly ash production is added to the sorbent waste to account
for the total waste stream for the VOM analysis.
For purposes of modeling, the total VOM includes the first two component costs noted in the previous
paragraph, i.e., the costs for sorbent usage and the costs associated with waste production and disposal.
Table 5-17 presents the capital, VOM, and FOM costs as well as the capacity and heat rate penalties of a
DSI retrofit for an illustrative and representative set of generating units with the capacities and heat rates
indicated. See Attachment 5-5 (www.epa.gov/airmarkets/progsregs/epa-ipm/BaseCasev513.html) for
details on the Sargent & Lundy DSI model.
5.6 Fabric Filter (Baghouse) Cost Development
Fabric filters are not endogenously modeled as a separate retrofit option. In EPA Base Case v.5.13, an
existing or new fabric filter particulate control device is a pre-condition for installing a DSI retrofit, and the
cost of these retrofits at plants without an existing fabric filter include the cost of installing a new fabric
filter. This cost was added to the DSI costs discussed in section 5.5.3.2. The costs associated with a new
fabric filter retrofit are derived from Sargent & Lundy's performance/cost model. Similarly, dry scrubber
retrofit costs also include the cost of a fabric filter.
The engineering cost analysis is based on a pulse-jet fabric filter which collects particulate matter on a
fabric bag and uses air pulses to dislodge the particulate from the bag surface and collect it in hoppers for
removal via an ash handling system to a silo. This is a mature technology that has been operating
commercially for more than 25 years. "Baghouse" and "fabric filters" are used interchangeably to refer to
such installations.
Capital Cost: The major driver of fabric filter capital cost is the "air-to-cloth" (A/C) ratio. The A/C ratio is
defined as the volumetric flow, (typically expressed in Actual Cubic Feet per Minute, ACFM) of flue gas
entering the baghouse divided by the areas (typically in square feet) of fabric filter cloth in the baghouse.
The lower the A/C ratio, e.g., A/C = 4.0 compared to A/C = 6.0, the greater the area of the cloth required
5-28
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and the higher the cost for a given volumetric flow. An air-to-cloth ratio of 4.0 is used in EPA Base Case
v.5.13, and it is assumed that the existing ESP remains in place and active.
Table 5-18 presents the capital, VOM, and FOM costs for fabric filters as represented in EPA Base Case
v.5.13 for an illustrative set of generating units with a representative range of capacities and heat rates.
See Attachment 5-7 (www.epa.gov/airmarkets/progsregs/epa-ipm/BaseCasev513.html') for details of the
Sargent & Lundy fabric filter PM control model.
5-29
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Table 5-17 Illustrative Dry Sorbent Injection (DSI) Costs for Representative Sizes and Heat Rates
under Assumptions in EPA Base Case v.5.13
Control Type
DSI
Assuming
Bituminous
Coal
Heat Rate
(Btu/kWh)
9,000
10,000
1 1 ,000
S02
Rate
(Ib/
MMBtu)
2.0
2.0
2.0
Capacity
Penalty (%)
-0.64
-0.71
-0.79
Heat Rate
Penalty
(%)
0.65
0.72
0.79
Variable O&M
(mills/kWh)
8.49
9.44
10.39
Capacity (MW)
100
Capital Fixed
Cost O&M
($/kW) ($/kW-yr)
138.5 3.71
142.8 3.75
146.8 378
300
Capital Fixed
Cost O&M
($/kW) ($/kW-yr)
63.1 1.38
65.0 1.40
66.9 141
500
Capital Fixed
Cost O&M
($/kW) ($/kW-yr)
43.7 0.88
45.1 0.89
46-4 0.90
700
Capital Fixed
Cost O&M
($/kW) ($/kW-yr)
34.4 0.65
35.1 0.66
38-6 0.69
1000
Capital Fixed
Cost O&M
($/kW) ($/kW-yr)
31.6 0.52
35.1 0.55
38-6 0.58
Table 5-18 Illustrative Particulate Controls for Costs (2011$) for Representative Sizes and Heat Rates
under the Assumptions in EPA Base Case v.5.13
Coal Type
Bituminous
Heat Rate
(Btu/kWh)
9,000
10,000
1 1 ,000
Capacity
Penalty (%)
-0.60
Heat Rate
Penalty (%)
0.60
Variable
O&M
(mills/kWh)
0.05
0.06
0.07
Capacity (MW)
100
Capital
Cost Fixed O&M
($/kW) ($/kW-yr)
251 0.9
274 1.0
296 1 .0
300
Fixed
Capital O&M
Cost ($/kW-
($/kW) yr)
204 0.7
222 0.8
240 0.8
500
Fixed
Capital O&M
Cost ($/kW-
($/kW) yr)
185 0.6
202 0.7
218 0.8
700
Fixed
Capital O&M
Cost ($/kW-
($/kW) yr)
174 0.6
189 0.7
204 0.7
1000
Fixed
Capital O&M
Cost ($/kW-
($/kW) yr)
162 0.6
177 0.6
191 0.7
5-30
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5.6.1 MATS Filterable Particulate Matter (PM) Compliance
EPA Base Case v.5.13 assumes that all coal-fired generating units with a capacity greater than 25 MW
will comply with the MATS filterable PM requirements through the operation of either electrostatic
precipitator (ESP) or fabric filter (FF) particulate controls. The control mechanism is not modeled
endogenously but supplied as an input when setting up the run as specified below.
Units with existing fabric filters are assumed to be able to meet the filterable PM compliance requirement.
For units with existing ESPs the following procedure is used to determine if they already meet the
filterable PM requirement, can meet it by one of three possible ESP upgrades, or can only meet it by
installing a FF.
First, PM emission rate data derived either from 2005 EIA Form 767 or (where available) from EPA's
2010 Information Collection Request33 are compared to the applicable filterable PM compliance
requirement. If the unit's emission rate is equal to or less than the compliance requirement, adequate
controls are assumed already to be in place and no additional upgrade costs are imposed. For units that
do not meet the filterable PM compliance requirement, the incremental reduction needed (in Ibs/mmBtu)
is calculated by subtracting the filterable PM compliance standard from the reported emission rate.
Depending on the magnitude of the incremental reduction needed, the unit is assigned one of three ESP
upgrade costs (designated ESP1, ESP2, and ESPS) or the cost of a FF installation (designated ESP4), if
the required incremental reduction cannot be achieved by an ESP upgrade. Table 5-19 shows the four
levels of ESP upgrades (column 1), the key technologies included in each upgrade (column 2), trigger
points for the upgrades (column 3), the capital cost of each upgrade (column 4), and the percent increase
in collection efficiency provided by the upgrade, differentiated according to the rank (subbituminous,
bituminous, or lignite) of coal burned.
The percentage improvements in collection efficiency shown in column 5 in Table 5-19 are additive in the
sense that the values shown in this column are added to the pre-upgrade collection efficiency to obtain
the after-upgrade collection efficiency.
Table 5-19 Electrostatic Precipitator (ESP) Upgrades as Implemented in EPA Base Case v.5.13
Characteristics, Trigger Points, Associated Costs, and Performance Improvements
Upgrade
Level
1
2
Key Technologies
Employed in
Upgrade
High Frequency transformer-
rectifier
(TR) sets
High frequency transformer-
rectifier
(TR) sets + New internals
(rigid electrodes, increased
plate spacing, increased
plate height)
Trigger Points for ESP
Upgrade
(Expressed in terms of
incremental reduction
needed (Ibs/mmBtu) to
meet the filterable PM
Compliance Standard)
> 0.0 to < 0.005
> 0.005 to < 0.01
Capital Cost
SSS/kW3
SSO/kW"
Additive Percent Improvement6 in
Collection Efficiency as a Result of
the Upgrade (differentiated by the
rank of coal combusted)
0.12 for subbituminous
0.05 for bituminous
0.01 for lignite
0.25 for subbituminous
0.10 for bituminous
0.02 for lignite
33 2005 EIA Form 767 is the last year where the data was reported in the format of Ib/MMBtu, which is compatible
with this analysis. Since any changes to facilities since 2005 would likely have improved (reduced) emissions, the
use of this data is conservative. More recent 2010 ICR test data is used where available. (Collection Effort for New
and Existing Coal- and Oil-Fired Electricty Utility Steam Generating Units (EPA ICR No.2362.01 (OMB Control
Number 2060-0631).
5-31
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Upgrade
Level
3
4
Key Technologies
Employed in
Upgrade
High frequency transformer-
rectifier
(TR) sets + New internals
(rigid electrodes, increased
plate spacing, increased
plate height) + Additional field
Replacement with fabric filter
(baghouse)
Trigger Points for ESP
Upgrade
(Expressed in terms of
incremental reduction
needed (Ibs/mmBtu) to
meet the filterable PM
Compliance Standard)
> 0.01 to < 0.02
>0.02
Capital Cost
$100/kWฐ
Use capital cost
equations for a
fabric filterd
Additive Percent Improvement6 in
Collection Efficiency as a Result of
the Upgrade (differentiated by the
rank of coal combusted)
0.50 for subbituminous
0.20 for bituminous
0.05 for lignite
(Not Applicable)
a Assumes upgrading the specific collection area (SCA) to 250 square-feet/1000 afm (actual feet per minute).
b Assumes upgrading the specific collection area (SCA) to 300 square-feet/1000 afm (actual feet per minute).
c Assumes upgrading the existing specific collection area (SCA) by 100 square-feet/1000 afm (actual feet per minute), a 20% height increase, and
additional field.
d The cost equations for fabric filters are described in Section 5.5.4
8 The percentage improvement due to the ESP upgrade as shown in this column is added to the pre-upgrade collection efficiency to obtain the after-
upgrade collection removal efficiency.
Excerpt from Table 5-20 contains a complete listing of coal generating units with either cold- or hot-side
ESPs but no fabric filters. For each generating unit in Excerpt from Table 5-20 shows the incremental
reductions needed to meet the PM filterable compliance requirement and the corresponding ESP upgrade
(if any) assigned to the unit to enable it to meet that requirement. A filterable PM limit of 0.279 Ib/mmBtu
was used in this analysis. This value is roughly 10% below the limit in the final MATS rule, therefore
resulting in a conservative estimate of the need to upgrade existing ESPs.
5.7 Coal-to-Gas Conversions34
In EPA Base Case v.5.13 existing coal plants are given the option to burn natural gas in addition to coal by
investing in a coal-to-gas retrofit. There are two components of cost in this option: Boiler modification
costs and the cost of extending natural gas lateral pipeline spurs from the boiler to a natural gas main
pipeline. These two components of cost and their associated performance implications are discussed in
the following sections.
5.7.1 Boiler Modifications For Coal-To-Gas Conversions
Enabling natural gas firing in a coal boiler typically involves installation of new gas burners and
modifications to the ducting, windbox (i.e., the chamber surrounding a burner through which pressurized
air is supplied for fuel combustion), and possibly to the heating surfaces used to transfer energy from the
exiting hot flue gas to steam (referred to as the "convection pass"). It may also involve modification of
environmental equipment. Engineering studies are performed to assess operating characteristics like
furnace heat absorption and exit gas temperature; material changes affecting piping and components like
superheaters, reheaters, economizers, and recirculating fans; and operational changes to sootblowers,
spray flows, air heaters, and emission controls.
As discussed here coal-to-gas conversion refers to the modification of an existing boiler to allow it to fire natural gas.
It does not refer to the addition of a gas turbine to an existing boiler cycle, the replacement of a coal boiler with a new
natural gas combined cycle plant, or to the gasification of coal for use in a natural gas combustion turbine
5-32
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Excerpt from Table 5-20 ESP Upgrade Provided to Existing Units without Fabric Filters so that
They Meet Their Filterable PM Compliance Requirement
This is a small excerpt of the data in Excerpt from Table 5-20. The complete data set in spreadsheet
format can be downloaded via the link found at www.epa.gov/airmarkets/proqsreqs/epa-
ipm/BaseCasev513.html)
Plant Name
A B Brown
AES Beaver Valley Partners Beaver Valley
AES Beaver Valley Partners Beaver Valley
AES Beaver Valley Partners Beaver Valley
AES Cayuga
AES Cayuga
AES Deepwater
AES Somerset LLC
Allen Steam Plant
Allen Steam Plant
Allen Steam Plant
Alma
Alma
Ames Electric Services Power Plant
Ames Electric Services Power Plant
Apache Station
Apache Station
Asbury
Asheville
Asheville
Unit ID
2
2
3
4
1
2
AAB001
1
1
2
3
B4
B5
7
8
2
3
1
1
2
State
Name
Indiana
Pennsylvania
Pennsylvania
Pennsylvania
New York
New York
Texas
New York
Tennessee
Tennessee
Tennessee
Wisconsin
Wisconsin
Iowa
Iowa
Arizona
Arizona
Missouri
North Carolina
North Carolina
Unique ID
6137_B_2
10676 B 2
10676_B_3
10676_B_4
2535 B 1
2535_B_2
10670_B_AAB001
6082 B 1
3393_B_1
3393 B 2
3393_B_3
4140_B_B4
4140 B B5
1122_B_7
1122_B_8
160 B 2
160_B_3
2076 B 1
2706_B_1
2706_B_2
Capacity
(MW)
245
43
43
43
150
151
139
681
245
245
245
51
77
33
70
175
175
213
191
185
Level of
ESP
Upgrade
Required
to Meet
Filterable
PM
Requirement
...
ESP-4
ESP-4
ESP-1
...
...
...
...
...
...
...
...
ESP-4
...
...
...
...
ESP-4
...
The following table summarizes the cost and performance assumptions for coal-to-gas boiler modifications
as incorporated in EPA Base Case v.5.13. The values in the table were developed by EPA's engineering
staff based on technical papers35 and discussions with industry engineers familiar with such projects. They
were designed to be applicable across the existing coal fleet.
Table 5-21 Cost and Performance Assumptions for Coal-to-Gas Retrofits
Factor
Applicability:
Capacity Penalty:
Description
Existing pulverized coal (PC) fired and
cyclone boiler units of a size greater
than 25 MW:
None
Notes
Not applicable for fluidized bed
combustion (FBC) and stoker boilers.
The furnace of a boiler designed to burn coal is
oversized for natural gas, and coal boilers
include equipment, such as coal mills, that are
not needed for gas. As a result, burning gas
should have no impact on net power output.
For an example see Babcock and Wilcox's White Paper MS-14 "Natural Gas Conversions of Exiting Coal-Fired
Boilers" 2010 (vwwv.babcock.com/librarv/tech-utilitv.html#14).
5-33
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Factor
Heat Rate
Penalty:
Incremental Capital
Cost:
Incremental
Fixed O&M:
Incremental
Variable O&M:
Fuel Cost:
NOX emission rate:
SO2 emissions:
Description
+ 5%
PC units: $/kW = 267*(75/MW)A0.35
Cyclone units: $/kW =
374*(75/MW)A0.35
-33% of the FOM cost of the existing
coal unit
-25% of the VOM cost of the existing
coal unit
Natural gas
50% of existing coal unit NOX
emission rate, with a floor of
0.05 Ibs/MMBtu
Zero
Notes
When gas is combusted instead of coal, the
stack temperature is lower and the moisture
loss to stack is higher. This reduces
efficiency, which is reflected in an increase in
the heat rate.
The cost function covers new gas burners and
piping, windbox modifications, air heater
upgrades, gas recirculating fans, and control
system modifications.
Example for 50 MW PC unit:
$/kW = 267*(75/50)A0.35 = 308
Due to reduced needs for operators,
maintenance materials, and maintenance staff
when natural gas combusted, FOM costs
decrease by 33%.
Due to reduced waste disposal and
miscellaneous other costs, VOM costs
decrease by 25%.
To obtain natural gas the unit incurs the cost of
extending lateral pipeline spurs from the boiler
location to the natural gas transmission
pipeline. See section 5.7.2.
The 0.05 Ibs/MMBtu floor is the same as the
NOX rate floor for new retrofit SCR on units
burning subbituminouscoal
5.7.2 Natural Gas Pipeline Requirements For Coal-To-Gas Conversions
For every individual coal boiler in the U.S., EPA tasked ICF to determine the miles and associated cost of
extending pipeline laterals from each boiler to the interstate natural gas pipeline system.
To develop these costs the following principles were applied:
For each boiler, gas volume was estimated based on size and heat rate.
Direct distance to the closest pipeline was calculated. (The analysis only considered mainlines with
diameters that were 16 inches or greater. The lateral distance represented the shortest distance-"as
the crow flies" - between the boiler and the mainline.)
Gas volume (per day) of the initial lateral was not allowed to exceed more than 10 percent of the
estimated capacity of the mainline.
The mainline capacities were estimated from the pipe's diameter using the Weymouth equation36.
If the gas requirement exceeded 10 percent of the estimated capacity of the mainline, the cost of a
second lateral to connect to the next closest mainline was calculated.
This procedure was repeated until the entire capacity required for the boiler was reached.
Diameters of each lateral were then calculated using the Weymouth equation based on their required
capacities.
The Weymouth equation in classical fluid dynamics is used in calculating compressible gas flow as a function of
pipeline diameter and friction factors. It is used for pipe sizing.
5-34
-------
The cost of all the laterals was calculated based on the pipeline diameter and mileage required. Thus,
the final pipeline cost for each boiler was based on the total miles of laterals required.
Figure 5-1 shows the calculations performed.
Figure 5-1 Calculations Performed in Costing Lateral Pipeline Requirement
Mainline Flow Capacity, Qm (million cubic feet per day)
Qm = 0.06745 * d2667, where d is the diameter of the mainline in inches
Required Capacity of Lateral/s for Each Boiler. QHmlllion cubic feet per day)
Ql = (Boiler Capacity * Heat Rate *24) /1,030,000, where Boiler Capacity is in MW and the Heat
Rate is in Btu/kWh
Diameter of Each Lateral, D (Inches)
D = (14.83 * Ql) ฐ 374%p where each lateral's capacity may not exceed 10% of the mainline capacity to which the lateral connects
Cost per Lateral, C($)
C = 90,000'D' Number of Miles
Note: The above calculations assume a pipeline cost of $90,000 per inch-mile based on recently completed projects.
There are several points to note about the above approach. First, for relatively large boilers or in cases
where the closest mainline has a relatively small diameter, multiple laterals are required to connect the
boilerto the interstate gas transmission grid. This assures that each individual boiler will not become a
relatively large portion of a pipelines' transmission capacity. It also reflects real-world practices where
larger gas-fired power plants typically have multiple laterals connecting them to different mainlines. This
increases the reliability of their gas supply and provides multiple options for gas purchase allowing them to
capture favorable prices from multiple sources of gas supply at different points in time.
Second, expansion of mainlines was not included in the boiler specific pipeline cost, because the
integrated gas model within IPM already includes corridor expansion capabilities. However, if in future IPM
runs, multiple converted boilers are concentrated on a single pipeline along a corridor that includes
multiple pipelines, a further assessment may be required to make sure that the mainline expansion is not
being understated due to modeled efficiencies that may not actually be available in the field.
Figures 5-2 through 5-7 summarize the results of the pipeline costing procedure described above. They
provide histograms of the number of laterals required per boiler (
5-35
-------
Figure 5-2), miles of pipeline required per boiler (Figure 5-3), diameters of the laterals in inches (
5-36
-------
Figure 5-4), total inch-miles of laterals required per boiler (Figure 5-5), total cost to each boiler in millions
(Figure 5-6), and cost (in $) per kW of boiler capacity (Figure 5-7). Excerpt from Table 5-22 shows the
pipeline costing results for each qualifying existing coal fired unit represented in EPA Base Case v.5.13.
5-37
-------
Figure 5-2 Number of Laterals Required per Boiler
700
Number of Laterals
Minimum 1
Maximum 8
Average 1.7
Median 1
4 5
Number of Laterals
300
250
8
(N 200
t-l
II
Figure 5-3 Miles of Pipeline Required per Boiler
Mites per Boiler
Minimum 0.2
Maximum 766.4
Average 58.7
Median 27.1
Otol
Ito5 5 to 10
300 to More than
400 400
Miles of Pipeline
5-38
-------
Figure 5-4 Diameter of Laterals
600 -
Diameter of Laterals
Minimum
Maximum
Average
Median
1.2
20.5
9.6
9.3
ltd 2 2 to 4 4 to 6 6 to 8 8 to 10 10 to 12 12 to 14 14 to 16 16 to 18 18 to 20 More
than 20
Diameter of Laterals, in Inches
Figure 5-5 Total Inch-Miles of Laterals Required per Boiler
250
Inch-Miles per Boiler
Minimum 2
Maximum 7,017
Average 547
Median 230
Ito25
1500 to
2000
2000 to
3000
3000 to More
5000 than
5000
Number of Inch-Miles per Boiler
5-39
-------
300
Figure 5-6 Total Cost to Each Boiler
Cost per Boiler (MillionsS)
Minimum
Maximum
Average
Median
0.20
631.54
49.19
20.73
Otol
1 to 5 5 to 10
300 to
400
More than
400
Cost Increment (Million$)
300
Figure 5-7 Cost per kW of Boiler Capacity
Cost per kW(S)
Minimum 0.6
Maximum 6,355.1
Average 341.3
Median 144.8
OtolO
500 to
1000
1000 to 2000 to
2000 4000
More
than
4000
Cost Increment ($)
5-40
-------
Excerpt from Table 5-22 Cost of Building Pipelines to Coal Plants
This is a small excerpt of the data in Table-22. The complete data set in spreadsheet format can be
downloaded via the link found at http://www.epa.qov/airmarkets/proqsreqs/epa-ipm/BaseCasev513.html.
Unique ID
3_B_1
3_B_2
3_B_3
3_B_4
3_B_5
7_G_1
7_G_2
8_B_10
8_B_6
8_B_7
8_B_8
8_B_9
10_B_1
10_B_2
26_B_1
26_B_2
26_B_3
26_B_4
26_B_5
47_B_1
47_B_2
47_B_3
47_B_4
47_B_5
50_B_7
50_B_8
51_B_1
56_B_1
56_B_2
56_B_3
59_B_1
60_B_1
60_B_2
87_B_1
108_B_SGU1
113_B_1
113_B_2
113_B_3
Coal
Cap
Plant Name State Name (IV
Barry Alabama
Barry Alabama
Barry Alabama
Barry Alabama
Barry Alabama
Gadsden Alabama
Gadsden Alabama
Gorgas Alabama
Gorgas Alabama
Gorgas Alabama
Gorgas Alabama
Gorgas Alabama
Greene County Alabama
Greene County Alabama
E C Gaston Alabama
E C Gaston Alabama
E C Gaston Alabama
E C Gaston Alabama
E C Gaston Alabama
Colbert Alabama
Colbert Alabama
Colbert Alabama
Colbert Alabama
Colbert Alabama
Widows Creek Alabama
Widows Creek Alabama
Dolet Hills Louisiana
Charles R Lowman Alabama
Charles R Lowman Alabama
Charles R Lowman Alabama
Platte Nebraska
Whelan Energy Center Nebraska
Whelan Energy Center Nebraska
Escalante New Mexico
Holcomb Kansas
Cholla Arizona
Cholla Arizona
Cholla Arizona
Miles of
Number New Pipeline
Boiler of Required to
acity Laterals Hook Up Unit
1W) Required (miles)
138 2 8.5
137 2 8.5
249 2 8.5
362 2 8.5
726 2 8.5
64 1 28.7
66 1 28.7
703 2 68.4
103 1 7.6
104 1 7.6
161 1 7.6
170 1 7.6
254 1 6.9
243 1 6.9
254 1 23.0
256 1 23.0
254 1 23.0
256 1 23.0
842 3 162.4
178 1 0.7
178 1 0.7
178 1 0.7
178 1 0.7
472 2 4.6
473 3 253.0
465 3 253.0
638 4 28.3
80 1 17.3
235 2 43.8
235 2 43.8
100 1 25.8
77 1 8.1
220 1 8.1
247 2 11.4
362 5 77.1
116 1 27.5
260 1 27.5
271 1 27.5
Cost of New
Pipeline
(2011$)
2324786
2136794
7209727
8979092
12412831
22383509
22617875
87979597
6250679
6269532
7407093
7533473
7898586
7776757
26126943
26294370
26143766
26143766
201898208
725276
722785
722785
723409
5183155
231385577
227553333
28812871
13132673
38349442
38128365
21561000
6169545
9036600
7831404
43429164
23648324
32391059
32691880
Cost of New
Pipeline
perKW
of Coal
Capacity
(2011$/kW)
16.85
15.60
28.95
24.80
17.10
349.74
342.70
125.15
60.69
60.28
46.01
44.31
31.10
32.00
102.86
102.71
102.93
102.12
239.78
4.07
4.06
4.06
4.06
10.98
489.19
489.36
45.16
164.16
163.19
162.25
215.61
80.12
41.08
31.71
119.97
203.86
124.58
120.63
5-41
-------
5.8 Natural Gas Co-firing
Existing coal plants with existing natural gas pipelines have an option of co-firing with natural gas. Gas
co-firing at these units is limited to 10% of the unit's power output.
The option of co-firing with gas at an existing coal boiler is only offered if one of the following two criteria
based on 2012 EIA 860, 2012 ElAForm 923 and NEEDS v.5.13 is met: (1) the unit reported the use of
gas as a startup fuel, or (2) an existing gas-fired unit (e.g., NGCC) is located at the same facility (with the
same ORIS) as the coal-fired unit. EPA assumes that in either of these cases, sufficient pipeline capacity
exists to supply up to 10% of total power output of the coal steam boiler located at these sites. These
units are detailed below in Excerpt from Table 5-23.
Similar to the coal-to-gas retrofit option, there is a 5% increase in heat rate for the share of generation
fueled by natural gas (accounting for the increased flue gas moisture and stack heat loss). On a $/kWh
basis, any change in capital or operating costs of co-firing with natural gas at low levels is very small.
Hence, EPA do not include additional capital or operating costs for this option.
Excerpt from Table 5-23 List of Coal Steam Units with Natural Gas Co-firing option
This is a small excerpt of the data in Excerpt from Table 5-23. The complete data set in spreadsheet
format can be downloaded via the link found at http://www.epa.gov/airmarkets/progsregs/epa-
ipm/BaseCasev513.html
UniquelD
10684_G_TG5
1077_G_3
1554_G_2
2943_G_3
511_G_1
54407_G_1
54407_G_2
56564_G_1
56785_G_WG01
7_G_1
7_G_2
728_G_4
728_G_5
10_B_1
10_B_2
Plant Name
Argus Cogen Plant
Sutherland
Herbert A Wagner
Shelby Municipal Light Plant
Trinidad
Waupun Correctional Central Heating Pit
Waupun Correctional Central Heating Pit
John W Turk Jr Power Plant
Virginia Tech Power Plant
Gadsden
Gadsden
Yates
Yates
Greene County
Greene County
ORIS Code
10684
1077
1554
2943
511
54407
54407
56564
56785
7
7
728
728
10
10
State Name
California
Iowa
Maryland
Ohio
Colorado
Wisconsin
Wisconsin
Arkansas
Virginia
Alabama
Alabama
Georgia
Georgia
Alabama
Alabama
Capacity (MW)
7
78
135
5
3.8
0.2
0.5
609
2.5
64
66
133
135
254
243
5-42
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6. CO2 Capture, Transport, and Storage
6.1 CO2 Capture
Among the potential (new) units that the model can build in EPA Base Case v.5.13 are advanced coal-
fired units with CO2 capture (carbon capture).37 The cost and performance characteristics of these units
are shown in Table 4-13 and are discussed in Chapter 4.
In addition to offering carbon capture capabilities on potential units that the model builds as new capacity,
EPA Base Case v.5.13 provides carbon capture as a retrofit option for existing pulverized coal plants.
The incremental costs and performance assumptions for these retrofits are shown in Table 6-1.
Table 6-1 Performance and Unit Cost Assumptions for Carbon Capture
Retrofits on Pulverized Coal Plants
Applicability (Original MW Size)
Incremental3 Capital Cost (2011 $/kW)
Incremental3 FOM (2011 $/kW-yr)
Incremental3 VOM (2011 (mills/kWh)
Capacity Penalty (%)
Heat Rate Penalty (%)
CO2 Removal (%)
> 400 MW
1,794
27.2
3.2
-25%
33%
90%
Note:
a Incremental costs are applied to the derated (after retrofit) MW size.
The capital costs shown in Table 6-1 are based on the costs reported for Case 1 in a study performed for
the U.S. Department of Energy's (DOE) National Energy Technology Laboratory (NETL) by a team
consisting of Alstom Power, Inc., American Electric Power (AEP), ABB Global, and the Ohio Coal
Development Office.38 For Case 1 this comprehensive engineering study, conducted from 1999-2001,
evaluated the impacts on plant performance and the required cost to add facilities to capture greater than
90% of the CO2 emitted by AEP's Conesville Ohio Unit #5. This is a 450 MWsubcriticalpulverized
bituminous coal plant with a lime based FGD, and an electrostatic precipitator for particulate control/
The carbon capture method that was evaluated was an amine-based scrubber using the Kerr-
McGee/ABB Lummus Global commercially available monoethanolamine (MEA) process. In this system
the flue gas leaves the FGD (which has been modified to reduce the SO2 concentration as required by the
MEA process) and is cooled and ducted to the MEA system where more than 96% of the CO2 can be
removed. For use in EPA Base Case v.5.13 the capital cost was converted to constant 2011 $ from the
2006$ costs reported in the NETL study.
39
A capacity derating penalty of 25% was assumed, based on reported research and field experience as of
2010. The corresponding heat rate penalty was 33%. (For an explanation of the capacity and heat rate
penalties and how they are calculated, see the discussion under VOM in section 5.1.1.)
The term "New Advanced Coal with CCS" encompasses various technologies that can provide carbon capture.
These include supercritical steam generators with carbon capture and integrated gasification combined cycle (IGCC)
with carbon capture. For purposes of characterizing the cost and performance characteristics of advanced coal with
carbon capture, supercritical steam generators with carbon capture was used in Table 4-13.
38 Carbon Dioxide Capture from Existing Coal-Fired Power Plants" DOE/NETL-401/110907. Final Report (Original
Issue Date, December 2006) Revision Date, November 2007 (http://www.netl.doe.gov/energy-
analyses/pubs/CO2%20Retrofit%20From%20Existing%20Plants%20Revised%20November%202007.pdf. A
summary of costs for each of the cases appears in Table 3-65 (p. 139).
39 Subcritical" refers to thermal power plants that operate below the "critical temperature" and "critical pressure" (220
bar) where boiling (i.e., the formation of steam bubbles in water) no longer occurs. Such units are less efficient than
"supercritical" and "ultra supercritical" steam generators.
6-1
-------
Since the fixed (FOM) and variable operating and maintenance (VOM) costs from the Conesville study
were given without documentation, EPA relied on a NETL study that fully documented these costs
coupled with the expert judgment of EPA's engineering staff to obtain the FOM and VOM values shown in
Table 6-1.40
6.2 CO2 Storage
The capacity and cost assumptions for CO2 storage in EPA Base Case v.5.13 are based on GeoCAT
(Geosequestration Cost Analysis Tool), a spreadsheet model developed for EPA by ICF in support of
EPA's draft Federal Requirements under the Underground Injection Control (DIG) Program for Carbon
Dioxide Geologic Storage Wells.41 The GeoCAT model combines detailed characteristics of
sequestration capacity by state and geologic setting for the U.S. with costing algorithms for individual
components of geologic sequestration of CO2. The outputs of the model are regional sequestration cost
curves that indicate how much potential storage capacity is available at different CO2 storage cost points.
The GeoCAT model includes three modules: a unit cost specification module, a project scenario costing
module, and a geologic and regional cost curve module. The unit cost module includes data and
assumptions for 120 unit cost elements falling within the following cost categories:
Geologic site characterization
Monitoring the movement of CO2 in the subsurface
Injection well construction
Area of review and corrective action (including fluid flow and reservoir modeling during and after
injection and identification, evaluation, and remediation of existing wells within the area of review)
Well operation
Mechanical integrity testing
Financial responsibility (to maintain sufficient resources for activities related to closing and
remediation of the site)
General and administrative
Of the ten cost categories for geologic CO2 sequestration listed above, the largest cost drivers (in roughly
descending order of magnitude) are well operation, injection well construction, and monitoring.
The costs derived in the unit cost specification module are used in the GeoCAT project scenario costing
module to develop commercial scale costs for seven sequestration scenarios of geologic settings:
Saline reservoirs
Depleted gas fields
Depleted oil fields
Enhanced oil recovery
Enhanced coal bed methane recovery
40 Cost and Performance Baseline for Fossil Energy Plants" DOE/NETL-2007/1281, Volume 1: Bituminous Coal and
Natural Gas to Electricity, Final Report (Original Issue Date, May 2007) Revision 1, August 2007
(http://vwvw.netl.doe.qov/enerqv-analvses/pubs/Bituminous%20Baseline Final%20Report.pdf). The VOM and FOM
cost calculations for Case 9 appear in Exhibits 4-14 (p. 349) and for Case 10 in Exhibit 4-24 (p. 373).
41 Federal Requirements underthe Underground Injection Control (UIC) Program for Carbon Dioxide (CO2) Geologic
Sequestration (GS) Wells," Federal Register, July 25, 2008 (Volume 73, Number 144), pp. 43491-43541.
www.epa.qov/fedrqstr/EPA-WATER/2008/Julv/Dav-25/w16626.htm and www.epa.qov/safewater/uic/
wells sequestration.html#reqdevelopment.
6-2
-------
Enhanced shale gas
Basalt storage
EPA's application of GeoCAT includes only storage capacity for the first four scenarios. The last three
reservoir types are not included because they are considered technically uncertain and minor for the
foreseeable future.
The results of the project scenario costing module are taken as inputs into the geologic and regional cost
curve module of GeoCAT which generates national and regional "cost curves" indicating the volume of
sequestration capacity in each region and state in the U.S. as a function of cost. This module contains a
database of sequestration capacity by state and geologic reservoir type. It incorporates assessments
from the U.S. Department of Energy's "Carbon Sequestration Atlas of the United States and Canada,"
enhanced by ICF to include assessments of the Gulf of Mexico, shale gas sequestration potential, and
the use of distribution of proved oil and gas recovery by region to estimate CO2 potential in areas not
covered in the DOE atlas.42 The geologic and regional cost curve module also has a characterization of
regionalized costs, drilling depths, and other factors that go into the regional cost curves.43
For EPA Base Case v.5.13, GeoCAT identified storage opportunities in 33 of the lower 48 continental
states and storage cost curves were developed for each of them.44 The storage curve for California is
designated as California offshore. Louisiana and Texas have both onshore and offshore storage cost
curves. In addition, there are Atlantic offshore and Pacific offshore storage cost curves. The result is a
total of 37 storage cost curves which are shown in Excerpt from Table 6-2.45
The cost curves shown in Excerpt from Table 6-2 are in the form of step functions. This implies that in any
given year a specified amount of storage is available at a particular step price until either the annual
storage limit (column 4) or the total storage capacity (column 5) is reached. In determining whether the
total storage capacity has been reached, the model tracks the cumulative storage used up through the
current year. Once the cumulative storage used equals the total storage capacity, no more storage is
available going forward at the particular step price.
CO2 storage opportunities are relevant not just to power sector sources, but also to sources in other
industrial sectors. Therefore, before being incorporated as a supply representation into EPA Base Case
v.5.13, the original CO2 storage capacity in each storage region was reduced by an estimate of the
storage that would be occupied by CO2 generated by other industrial sector sources at the relevant level
of cost effectiveness (represented by $/ton CO2 storage cost). To do this, ICF first estimated the level of
industrial demand for CO2 storage in each CO2 storage region in a scenario where the value of abating
CO2 emissions is assumed to be $150 per ton (this abatement value is relevant not only to willingness to
42 Carbon Sequestration Atlas of the United States and Canada", U.S. Department of Energy, National Energy
Technology Laboratory, Morgantown, WV, March, 2007.
43 Detailed discussions of the GeoCAT model and its application for EPA can be found in U.S. Environmental
Protection Agency, Office of Water, "Geologic CO2 Sequestration Technology and Cost Analysis, Technical Support
Document" (EPA 816-B-08-009) June 2008, http://www.epa.qov/oqwdwOOO/uic/pdfs/
support uic co2 technoloqvandcostanalvsis.pdf and Harry Vidas, Robert Hugman and Christa Clapp, "Analysis of
Geologic Sequestration Costs for the United States and Implications for Climate Change Mitigation," Science Digest,
Energy Procedia, Volume 1, Issue 1, February 2009, Pages4281-4288.Availableonlineatwww.sciencedirect.com.
44 The states without identified storage opportunities in EPA Base Case v.5.13 are Connecticut, Delaware, Idaho,
Iowa, Maine, Maryland, Massachusetts, Minnesota, Missouri, New Hampshire, New Jersey, North Carolina, Rhode
Island, Vermont, and Wisconsin. This implies that these states did not present storage opportunities for the four
sequestration scenarios included in EPA's inventory, i.e., saline reservoirs, depleted gas fields, depleted oil fields,
and enhanced oil recovery.
45 For consistency across the emission costs represented in v.5.13, the costs shown in Tables 9-23 and 9-24 are
expressed in units of dollars per short ton. In IPM documentation and outputs the convention is to use the word
"tons" to indicate short tons and the word "tonnes" to indicate metric tons. In discussing CO2 outside of the modeling
framework, the international convention is to use metric tons. To obtain the $/tonne equivalent multiply the $/ton
values shown In Tables 9-34 and 9-24 by 1.1023.
6-3
-------
pay for storage but also for the cost of capture and transportation of the abated CO2).46 Then, for each
region ICF calculated the ratio of the industrial demand to total storage capacity available for a storage
price of less than $10/ton. (An upper limit of $10/ton was chosen because the considerable amount of
storage available up to that price could be expected to exhaust the industrial demand.) Converting this to
a percent value and subtracting from 100%, ICF obtained the percent of storage capacity available to the
electricity sector at less than $10/ton. Finally, the "Annual Step Bound (MMTons)" and "Total Storage
Capacity (MMTons)" was multiplied by this percentage value for each step below $10/ton47 in the cost
curves for the region to obtain the reduced storage capacity that went into the storage cost curves for the
electric sector in EPA Base Case v.5.13. Thus, the values shown in Excerpt from Table 6-2 represent the
storage available specifically to the electric sector.
The price steps in the Excerpt from Table 6-2 are the same from region to region. (That is, STEPS
[column 2] has a step cost value of $4.84/Ton [column 3] across all storage regions [column 1]. This
across-region price equivalency holds for every step.) However, the amount of storage available in any
given year (labeled "Annual Step Bound (MMTons)" in column 4) and the total storage available over all
years (labeled "Total Storage Capacity (MMTons)" in column 5) vary from region to region. In any given
region, the cost curves are the same for every run year. This feature implies that over the modeling time
horizon no new storage will be added to augment the current storage inventory. This assumption is not
meant to imply that additional storage is unavailable and may be revisited if model runs exhaust key
components in the storage inventory.
Excerpt from Table 6-2 CO2 Storage Cost Curves in EPA Base Case v.5.13
This is a small excerpt of the data in Excerpt from Table 6-2. The complete data set in spreadsheet format
can be downloaded via the link found at http://www.epa.gov/airmarkets/progsregs/epa-
ipm/BaseCasev513.html.
CC>2 Storage Region Step Name
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
Alabama STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
CO2 Storage
Step Cost
(2011$/Ton)
-14.52
-9.68
-4.84
0.00
4.84
9.68
14.52
19.36
24.20
29.04
33.88
38.72
43.56
48.41
53.25
58.09
62.93
Annual Step
Bound
(MMTons)
1
0
0
0
31
39
38
0
4
13
0
0
0
1
0
0
0
Total Storage
Capacity
(MMTons)
45
0
0
6
1,568
1,967
1,895
9
186
639
7
14
0
68
0
14
0
46 The approach that ICF employed to estimate industrial demand for CC>2 storage is described in ICF International,
"Methodology and Results for Initial Forecast of Industrial CCS Volumes," January 2009.
47 Zero and negative cost steps represent storage available from enhanced oil recovery (EOR) where oil producers
either pay or offer free storage for CO2 that is injected into mature oil wells to enhance the amount of oil recovered.
There is also a market for CO2 injection in enhanced coal bed methane (ECBM) production. ECBM is excluded from
EPA's inventory as discussed earlier.
6-4
-------
CO2 Storage Region Step Name
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
Arizona STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
CO2 Storage
Step Cost
(2011$/Ton)
67.77
72.61
-14.52
-9.68
-4.84
0.00
4.84
9.68
14.52
19.36
24.20
29.04
33.88
38.72
43.56
48.41
53.25
58.09
62.93
67.77
72.61
Annual Step
Bound
(MMTons)
0
0
0
0
0
0
121
145
113
0
38
0
0
0
0
0
0
0
0
0
0
Total Storage
Capacity
(MMTons)
0
0
0
0
0
0
6,026
7,275
5,659
0
1,887
1
0
0
0
0
0
0
0
0
0
Note: The curves for each region are applicable in each model run year 2016 - 2050.
6.3 CO2 Transport
Each of the 64 IPM model regions can send CO2 to the 37 regions represented by the storage cost
curves in Excerpt from Table 6-2. The associated transport costs (in 2011 $/Ton) are shown in Excerpt
from Table 6-3.
These costs were derived by first calculating the pipeline distance from each of the CO2 Production
Regions to each of the CO2 Storage Regions listed in Excerpt from Table 6-3. Since there are large
economies of scale for pipelines, CO2 transportation costs depend on how many power plants and
industrial CO2 sources could share a pipeline over a given distance. Consequently, the method assumes
that the longer the distance from the source of the CO2 to the sink for the CO2 the greater the chance for
other sources to share in the transportation costs, including pipeline costs (in $/inch-mile) and cost of
service (in $/ton per 75 miles). These cost components are functions of the required diameter and
thickness of the pipeline and the flow capacity of the pipeline, which themselves are functions of the
assumed number of power plants using the pipeline.
6-5
-------
Excerpt from Table 6-3 CO2 Transportation Matrix in EPA Base Case v.5.13
This is a small excerpt of the data in Table 6-3. The complete data set in spreadsheet format can be
downloaded via the link found at http://www.epa.qov/airmarkets/proqsreqs/epa-ipm/BaseCasev513.html.
CO2 Production
Region
ERC_REST
CC>2 Storage Region
Alabama
Arizona
Arkansas
Atlantic Offshore
California
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana
Louisiana Offshore
Michigan
Mississippi
Montana
Nebraska
Nevada
New Mexico
New York
North Dakota
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas
Texas Offshore
Utah
Virginia
Washington
West Virginia
Wyoming
Cost
(2011$/Ton)
13.20
18.75
8.27
24.44
30.21
17.79
20.86
19.97
17.01
18.43
12.54
20.25
8.48
8.61
23.76
9.94
26.83
17.88
25.95
16.77
28.40
26.53
23.70
9.35
37.00
27.83
26.33
20.72
23.53
17.12
4.48
6.64
21.96
23.60
967.14
22.32
22.76
Notes:
Production Regions are equal to IPM model regions
6-6
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7. Set-up Parameters and Rules
The EPA Base Case v.5.13 includes a number of assumptions that affect the way IPM treats the analysis
time horizon, retrofit assignments, and environmental specifications for trading and banking. This section
provides an overview of those assumptions.
7.1 Run Year Mapping
Although IPM is capable of representing every individual year in an analysis time horizon, individual years
are typically grouped into model run years to increase the speed of modeling. While the model makes
decisions only for run years, information on non-run years can be captured by mapping run years to the
individual years they represent.
The analysis time horizon for EPA Base Case v.5.13 extends from 2016 through 2054, with IPM seeking
the least cost solution that meets all constraints and minimizes the net present value of system cost. The
seven years designated as "model run years" and the mapping of calendar years to run years is shown in
Table 7-1.
Table 7-1 Run Years and Analysis Year Mapping Used in the EPA Base Case v.5.13
Run Year
2016
2018
2020
2025
2030
2040
2050
Years Represented
2016-2017
2018
2019-2022
2023 - 2027
2028-2033
2034 - 2045
2046 - 2054
7.2 Retrofit Assignments
In IPM, model plants that represent existing generating units have the option of maintaining their current
system configuration, retrofitting with pollution controls, or retiring. The decision to retrofit or retire is
endogenous to IPM and based on the least cost approach to meeting demand subject to modeled system
and operational constraints. IPM is capable of modeling retrofits and retirements at each applicable
model unit at three different points in time, referred to as three stages. At each stage a retrofit set may
consist of a single retrofit (e.g. LSFO Scrubber) or pre-specified combinations of retrofits (e.g., ACI +
LSFO Scrubber +SCR). In EPA Base Case v.5.13 first stage retrofit options are provided to existing coal-
steam and oil/gas steam plants. These plants - as well as combined cycle plants, combustion turbines,
and nuclear plants - are also given retirement as an option in stage one. Third stage retrofit options are
offered to coal-steam plants only.
Table 7-2 presents the first stage retrofit options available by plant type; Table 7-3 presents the second
and third stage retrofit options available to coal-steam plants. The cost of multiple retrofits on the same
model plant, whether installed in one or multiple stages, are additive. In linear programming models such
as IPM, projections of pollution control equipment capacity and retirements are limited to the pre-specified
combinations listed in Table 7-2 and Table 7-3 below.
7-1
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Table 7-2 First Stage Retrofit Assignment Scheme in EPA Base Case v.5.13
Plant Type
Retrofit Option 1st Stage
Criteria
Coal Steam
Coal Retirement
Coal Steam SCR
Coal Steam SNCR - Non FBC
Boilers
Coal Steam SNCR - FBC Boilers
LSD Scrubber
LSFO Scrubber
CO2 Capture and Storage
ACI - Hg Control Option
(with and without Toxecon)
LSD Scrubber + SCR
LSD Scrubber + SNCR
LSFO Scrubber + SCR
LSFO Scrubber + SNCR
ACI + SCR
ACI + SNCR
ACI + LSD Scrubber
ACI + LSFO Scrubber
ACI + LSD Scrubber + SCR
ACI + LSFO Scrubber + SCR
ACI + LSD Scrubber + SNCR
ACI + LSFO Scrubber + SNCR
DSI
DSI + Fabric Filter
DSI + SCR
DSI + SNCR
ACI + DSI
ACI + DSI + SCR
ACI + DSI + SNCR
Heat Rate Improvement
Coal-to-Gas
All coal steam boilers
All coal steam boilers that are 25 MW or larger and do not
possess an existing SCR control option
All non FBC coal steam boilers that are 25 MW or larger and
smaller than 100 MW, and do not possess an existing post-
combustion NOX control option
All coal FBC units that are 25 MW or larger and do not possess
an existing post-combustion NOX control option
All unscrubbed coal steam boilers 25 MW or larger and burning
less than 3 Ibs/MMBtu SO2 coal
All unscrubbed and non FBC coal steam boilers 25
MW or larger
All scrubbed coal steam boilers 400 MW or larger
All coal steam boilers larger than 25 MW that do not have an ACI
and have an Hg EMF greater than 0.1. Actual ACI technology
type will be based on the boilers fuel and technology
configuration. See discussion in Chapters.
Combination options - Individual technology level restrictions
apply
All unscrubbed and non FBC coal steam boilers 25 MW or larger
with Fabric Filter and burning less than 2 Ibs/MMBtu SO2 coal.
All unscrubbed and non FBC-coal steam boilers 25 MW or larger
without Fabric Filter and with CESP or HESP and burning less
than 2 Ibs/MMBtu SO2 coal.
Combination options Individual technology level restrictions
apply
All coal steam boilers with a heat rate larger than 9,500 Btu/kWh
All coal steam boilers that are 25 MW or larger
Integrated Gasification Combined Cycle
IGCC Retirement
All integrated gasification combined cycle units
Combined Cycle
CC Retirement
All combined cycle units
Combustion Turbine
CT Retirement
All combustion turbine units
Nuclear
Nuclear Retirement
All nuclear power units
7-2
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Plant Type
Retrofit Option 1st Stage
Criteria
Oil and Gas Steam
Oil/Gas Retirement
Oil and Gas Steam SCR
All O/G steam boilers
All O/G steam boilers 25 MW or larger that do
existing post-combustion NOX control option
not possess an
Table 7-3 Second and Third Stage Retrofit Assignment Scheme in EPA Base Case v.5.13
Plant Type
Retrofit Option 1st Stage
Retrofit Option 2nd Stage
Retrofit Option 3rd
Stage
Coal Steam
NOX Control Option3
SO2 Control Optionb
Hg Control Option0
CO2 Control Optiond
NOX Control Option3 + SO2 Control
Option"
NOX Control Option3 + Hg Control
Option3
SO2 Control Optionb + Hg Control
Option3
NOX Control Option3 + SO2 Control
Option13 + Hg Control Option0
HCI Control Option8
NOX Control Option3 + HCI Control
Option8
Hg Control Option0 + HCI Control
SO2 Control Option
HCI Control Option
CO2 Control Option
Heat Rate Improvement
Coal Retirement
NOX Control Option
CO2 Control Option
Heat Rate Improvement
Coal Retirement
NOX Control Option
SO2 Control Option
HCI Control Option
CO2 Control Option
Heat Rate Improvement
Coal Retirement
None
CO2 Control Option
Heat Rate Improvement
Coal Retirement
SO2 Control Option
HCI Control Option
CO2 Control Option
Heat Rate Improvement
Coal Retirement
NOX Control Option
CO2 Control Option
Heat Rate Improvement
Coal Retirement
CO2 Control Option
Heat Rate Improvement
Coal Retirement
NOX Control Option
SO2 Control Option
Heat Rate Improvement
Coal Retirement
SO2 Control Option
Heat Rate Improvement
Coal Retirement
NOX Control Option
Heat Rate Improvement
Heat Rate Improvement
None
CO2 Control Option
None
Heat Rate Improvement
None
CO2 Control Option
None
Heat Rate Improvement
Heat Rate Improvement
Heat Rate Improvement
None
CO2 Control Option
None
None
None
CO2 Control Option
None
Heat Rate Improvement
Heat Rate Improvement
None
CO2 Control Option
None
Heat Rate Improvement
None
CO2 Control Option
None
None
CO2 Control Option
None
Heat Rate Improvement
Heat Rate Improvement
None
None
Heat Rate Improvement
None
None
Heat Rate Improvement
7-3
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Plant Type
Retrofit Option 1st Stage
Option8
NOX Control Option3 + HCI Control
Option8 + Hg Control Option0
Heat Rate Improvement
Coal-to-Gas
Coal Retirement
Retrofit Option 2nd Stage
SO2 Control Option
Heat Rate Improvement
Coal Retirement
SO2 Control Option
Heat Rate Improvement
Coal Retirement
NOX Control Option
SO2 Control Option
HCI Control Option
CO2 Control Option
Coal Retirement
NOX Control Option
Oil/Gas Retirement
None
Retrofit Option 3rd
Stage
Heat Rate Improvement
None
None
Heat Rate Improvement
None
None
None
None
None
None
None
None
None
None
Oil and Gas Steam
NOX Control Option3
Oil/Gas Retirement
Oil/Gas Retirement
None
None
None
Notes:
a "NOX Control Option" implies that a model plant may be retrofitted with one of the following NOX control technologies: SCR,
SNCR - non-FBC, or SNCR - FBC
b "SO2 Control Option" implies that a model plant may be retrofitted with one of the following SO2 control technologies: LSFO
scrubber or LSD scrubber
0 "Hg Control Option" implies that a model plant may be retrofitted with one of the following activated carbon injection technology
options for reduction of mercury emissions: ACI or ACI + Toxecon
d "CO2 Control Option" implies that a model plant may be retrofitted with carbon capture and storage technology
e "HCI Control Option" implies that a model plant may be retrofitted with a DSI (with milled Trona)
7.3 Emissions Trading and Banking
Five environmental air regulations included in EPA Base Case v.5.13 involve regional trading and
banking of emission allowances48: The three programs of the Clean Air Interstate Rule (CAIR) -Annual
SO2, Annual NOX and Ozone Season NOX; the Regional Greenhouse Gas Initiative (RGGI) for CO2; and
the West Region Air Partnership's (WRAP) program regulating SO2 (adopted in response to the federal
Regional Haze Rule). Table 7-4 below summarizes the key parameters of these five trading and banking
programs as incorporated in EPA Base Case v.5.13. EPA Base Case v.5.13 does not include any explicit
assumptions on the allocation of emission allowances among model plants under any of the programs.
The NOX SIP Call requirements for ozone season NOX for the state of Rhode Island are also included in
EPA Base Case v.5.13.49
Intertemporal Allowance Price Calculation
Under a perfectly competitive cap-and-trade program that allows banking (with a single, fixed future cap
and full "banking" allowed), the allowance price always increases by the discount rate between periods if
affected sources have allowances banked between those two periods. This is a standard economic result
for cap-and-trade programs and prevents sources from profiting by arbitraging allowances between two
periods.
For a detailed discussion of the assumptions modeled for all environmental air regulations in the EPA Base Case
v.5.13, refer to Chapters.
49
For more information on individual state emission caps and constraints, see the All Constraints worksheet in the
SSR file.
7-4
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The EPA Base Case v.5.13 uses the same discount rate assumption (4.77%) that governs all
intertemporal economic decision-making in the model in order to compute the increase in allowance price
for cap-and-trade programs when banking is engaged as a compliance strategy. This approach is based
on the assumption that allowance trading is a standard activity engaged in by generation asset owners
and that their intertemporal investment decisions as related to allowance trading will not fundamentally
differ from other investment decisions. For more information on how this discount rate was calculated,
please see Section 8.2.
Table 7-4 Trading and Banking Rules in EPA Base Case v.5.13
Coverage
Timing
Size of Initial
Bank (MTons)
CAIR Annual SO2
All fossil units > 25
MWa
Annual
pre2010:
5,985.7682010-
2014:22,298.08
2015-2015:2,333.776
CAIR Annual NOX
All fossil units > 25
MW1
Annual
2016: 1,514.702
CAIR - Ozone
Season NOX
All fossil units > 25
MWb
Ozone Season (May -
September)
2016:740.665
WRAP- SO2
All fossil units > 25
MWd
Annual
The bank starting in
2018 is assumed to be
zero
RGGI - CO2
All fossil units > 25
MWe
Annual
2016: 107,743
Rules
Total Allowances
(MTons)
Total Allowances
Less NSR
(MTons)
Retirement Ratio
2016-2054: 8,950
2016-2017:8,808
2018: 8,740
2019: 8,682
2020 - 2054: 8,662
2016-2054:2.86
2016-2054: 1,242
2016-2054: 1,242
2016-2054: 1.0
2016-2054:484.5
2016-2054:484.5
2016-2054: 1.0
2018-2054:89.6
NA
2016-2054: 1.0
2016: 68,459
2017: 66,297
2018: 64,188
2019: 62,132
2020: 60,1282021
-2054:78,175
NA
2016-2054: 1.0
Notes:
a Alabama, Delaware, District of Columbia, Florida, Georgia, Illinois, Indiana, Iowa, Kentucky, Louisiana, Maryland, Michigan,
Mississippi, Missouri, New Jersey, New York, North Carolina, Ohio, Pennsylvania, South Carolina, Tennessee, Texas, Virginia,
West Virginia, and Wisconsin.
b Alabama, Arkansas, Connecticut, Delaware, District of Columbia, Florida, Illinois, Indiana, Iowa, Kentucky, Louisiana, Maryland,
Massachusetts, Michigan, Mississippi, Missouri, New Jersey, New York, North Carolina, Ohio, Pennsylvania, South Carolina,
Tennessee, Virginia, West Virginia, and Wisconsin.
0 Rhode Island is the only NOX SIP Call state not covered by the CAIR Ozone Season NOX program.
d New Mexico, Utah, Wyoming
e Connecticut, Delaware, Maine, New Hampshire, New York, Vermont, Rhode Island, Massachusetts, Maryland
7-5
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8. Financial Assumptions
This chapter presents the financial assumptions used in the EPA Base Case v.5.13 along with an in-depth
explanation of the theoretical underpinnings and methods used to develop the two most important financial
parameters - the discount rate and capital charge rate. Investment options in IPM are selected by the
model given the cost and performance characteristics of available options, forecasts of customer demand
for electricity, reliability criteria and environmental regulations. The investment decisions are made based
on minimizing the net present value of capital plus operating costs over the full planning horizon. The
pattern of capital costs over time is determined using capital charge rates to represent the financing of
capital investments. The net present value of all future capital and operating costs is determined with the
use of a discount rate.
EPA Base Case v.5.13 uses real 2011 dollars (2011 $) as its real dollar baseline.50
8.1 Introduction to Risk
The risk of an investment in the power sector is heavily dependent on market structure risks. The range of
risks has increased due to deregulation, which has resulted in a greater share of U.S. generation capacity
being deregulated IPP (Independent Power Producer) capacity. For example, merchant IPPs selling into
spot market have more market risk than regulated plants or IPPs having long-term, known-price contracts
with credit worthy counter parties. There are also technology risks and financing structure risks (corporate
vs. project financings). Lastly, there is financial risk related to the extent of leverage.
The risk, especially to the extent it is correlated with overall market conditions, is an important driver of
financing costs. Other risks are handled in the cash flows and are treated as non-correlated with the
market. This emphasis on correlated market risk is based on the Capital Asset Pricing Model (CAPM) and
associated financial theory. This analysis takes into account differences in technology and market
structure risks.
Differences between corporate and project financings are highlighted but no specific adjustment has been
made for them.
8.1.1 Market Structure Risks
The power sector in North America can be divided into the traditional regulated sector (also known as
"cost of service" sector) and deregulated merchant sector (also known as "competitive" sector).
Traditional Regulated
The traditional regulated market structure is typical of the vertically integrated utilities where generation
(and transmission and distribution, abbreviated T&D) investments are approved through a regulatory
process and the investment is provided a regulated rate of return. In theory, returns on investment in this
form of market structure are cost plus regulated returns that are administratively determined. Returns are
affected by market conditions due to regulatory lag and other imperfections in the process, but overall
regulated investments are less exposed to the market than deregulated investments, all else held equal.
In this report, the term "utility financing" refers to this type of market structure. A closely related market
structure is the situation where a plant is built under a power purchase agreement (PPA) with a utility with
known pricing that allows for a very high degree of investment amortization during the contract period. In
such an arrangement, the risks are more credit- and performance-related and much less market-related.
50 Unless otherwise indicated, all rates presented in this document are provided in real terms.
51 SNL classifies power plants as merchant and unregulated if a plant in question was not part of any rate case.
Based on this classification criterion, in 2012, about 52% of all operating capacity is merchant and unregulated
capacity.
8-6
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Deregulated Merchant
In a deregulated merchant market structure, investments bear the full or a very high degree of market risk
as the price at which that they can sell electricity is dependent on what the short-term markets will bear.
Return on investment in this form of market structure is not only dependent on the state of the economy,
but also on commodity prices, as well as on capital investment cycles and remaining price-related
regulation, e.g., FERC price caps on capacity prices. The capital investment cycle can create a "boom
and bust" cycle which imparts source risk or uncertainty in the sector that can be highly correlated with
overall macro-economic trends. The operating cash flows from investments in this sector are more volatile
as compared to the traditional regulated sector and hence carry more business or market risk. In this
documentation, the term "merchant financing" refers to this type of market structure.
8.1.2 Technology Risks
The selection of new technology investment options is partially driven by the risk profile of these
technology investments. For instance, in a deregulated merchant market, an investment in a combustion
turbine is likely to be much more risky than an investment in a combined cycle unit because while a
combustion turbine operates as a peaking unit and is able to generate revenues only in times of high
demand, a combined cycle unit is able to generate revenues over a much larger number of hours in a
year. An investor in a combined cycle unit, therefore, would require a lower risk premium than an investor
in a combustion turbine.
8.1.3 Financing Structure Risks and Approach
While investments in new units differ based on market structure and technology risks, differences also
may occur because of financing schemes available. There are two major types of financing schemes:
Corporate finance
Corporate finance is a category of financing where a developer raises capital on the strength of the
balance sheet of a company rather than a single project. In this type of financing, the debtors have
recourse to the entire company's assets. Also, a common assumption is that debt is refinanced rather
than repaid such that overall debt is eliminated.
Project finance
Project finance allows developers to seek financing using only the project as recourse for the loan. For
instance, a project developer may wish to develop a new combined cycle unit but will seek to use project
financing in such a way that if the developer defaults on the loan, creditors have recourse only to the
project itself and not against the larger holdings of the project developer. This approach can be more risky
for investors than corporate finance, all else being equal, because there is less diversification of assets
than the assets held by a corporation (which can be thought as a collection of projects). However, there
are some projects more suitable for project financing because: (1) they may have a self-sustaining
revenue stream that is greater than the corporate average, or (2) risk is reduced through a long-term PPA
with a credit-worthy counterparty such as a vertically integrated utility or a regulated affiliate of a merchant
company. In this situation, debt principal is commonly assumed to be repaid at the end of the asset's
useful life.
There are many benefits of a project financing structure but there are also costs associated with it. A
project financing structure typically has higher transaction costs (and even higher debt costs as debt
financing is largely privately placed), but it also solves some of the agency problems and underinvestment
issues that corporate financed structures face.52
52 For more information on project financing, see paper titled "The Economic Motivations for Using Project Finance"
by Benjamin C. Esty, Harvard Business School, Feb 2003.
8-7
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However, as noted above, this analysis does not make an effort to quantify the relative costs and benefits
of one structure over the other. Rather, the approach is based on the premise that regardless of financial
structure, each project has its own risks based on market structure and technology. Further, because
corporate financing is more observable than project financing,53 and has evolved in the power sector to
the level of making key risk inferences possible (e.g., IPP and utility stock trades), assessment of market-
correlated risks for the purposes of deriving the financial assumptions used in EPA Base Case v.5.13
were based on IPP and utility corporate financing.
8.2 Calculation of the Financial Discount Rate
8.2.1 Introduction to Discount Rate Calculations
The real discount rate for expenditures54 (e.g., capital, fuel, variable operations and maintenance, and
fixed operations and maintenance costs) in the EPA Base Case v.5.13 is 4.77%. This serves as the
default discount rate for all expenditures.
A discount rate is used to translate future cash flows into current dollars by taking into account factors
(such as expected inflation and the ability to earn interest), which make one dollar tomorrow worth less
than one dollar today. The discount rate allows intertemporal trade-offs and represents the risk adjusted
time value of money.
8.2.2 Choosing a Discount Rate
The choice of discount rate often has a major effect on analytical results. The discount rate adopted for
modeling investment behavior should reflect the time preference of money or the rate at which investors
are willing to sacrifice present consumption for future consumption. The return on private investment
represents the opportunity cost of money and is commonly used as an appropriate approximation of a
discount rate.
8.2.3 Discount Rate Components
The discount rate is a function of the following parameters:
Capital structure (Share of Equity vs. Debt)
Post-tax cost of debt (Pre-tax cost of debt*(1 -tax rate))
Post-tax cost of eq u ity
The weighted average cost of capital (WACC) is used as the discount rate and is calculated as follows:
WACC = [Share of Equity * Cost of Equity]
+ [Share of Preferred Stock * Cost of Preferred Stock]
+ [Share of Debt *After Tax Cost of Debt]
The focal point is on debt and equity (common stock) because preferred stock is generally a small share
of capital structures. Its intermediate status between debt and equity in terms of access to cash flow also
tends not to change the weighted average.
53 Project financing data is less observable as the securities, debt and equity, are usually not explicitly traded. Also,
often key financing parameters are unavailable due to confidentiality reasons. Thus, the analysis is implicitly
assuming that the corporate risks and financing costs are equal to the project risks. This is especially reasonable
when the corporate activities are aggregations of projects.
54 This rate is equivalent to the real discount rate for a combine cycle plant under hybrid 75:25 utility to merchant ratio
assumption. It represents a most common type of investment.
8-8
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8.2.4 Market Structure: Utility-Merchant Financing Ratio
The first step in calculating the discount rate was to determine proper utility-merchant financing ratio. In
EPA Base Case v.5.13, a hybrid financing model is used that assumes future new unit development
activity would be split 75:25 between utility financings and pure merchant financings. This is designed to
reflect a shift in the market in ownership and risk profiles for power generation assets, and recent
development trends and emphasis on long term contracts.55 This approach assumes that new units are
financed as a weighted average of utility and merchant financing parameters. For new units the
assumption is that utility and merchant components get the 75:25 weights. However, since existing coal
units can be classified as belonging to a merchant or regulated structure, for retrofit investments the EPA
Base Case v.5.13 assumption is that plants owned by a utility get pure utility financing parameters,
whereas plants owned by merchant companies get pure merchant financing parameters.
Example 1: The debt to equity capital structure of a combustion turbine is 55/45 under
utility financing and 40/60 under merchant financing. Under the assumption that utility
and merchant components get 75:25 weights, the debt-to-equity ratio under hybrid
financing is D = (0.75*55 + 0.25*40) = 51 / E = (0.75*45 + 0.25*60) = 49.
Example 2: The debt to equity capital structure of a retrofit is 55/45 under both utility and
merchant financing. Under the assumption that utility owned plants are financed through
pure utility financing parameters, and merchant owned plants are financed through pure
merchant financing parameters, the debt to equity ratio remains unchanged regardless of
the ownership type. A full summary for all technologies appears in Table 8-1 below.
Capital Structure: Debt-Equity Share
The second step in calculating the discount rate is the determination of the capital structures (D/E)57
shares for the various technology types using an appropriate utility-merchant financing ratio. The utility
debt capacity (and returns) is assumed to be independent of technology type based on the theoretical
assumption that regulation will provide an average return to the entire rate base. This assumption is
supported by empirical evidence which suggests that utility rate of return is based on an average return to
the entire rate base.58 The merchant debt capacity is based on market risk where a base load plant is
55 An alternate approach is to categorize the United States into the two previously discussed financial regions - Cost-
of-service and competitive. The cost-of-service region will have capital charge rates based on utility financial
assumptions and the competitive region will have capital charge rates based on merchant financial assumptions.
Such an approach could result in overbuilding in the cost-of-service region due to lower capital charge rates in the
absence of regulatory prohibitions of external sales. This is similar to the public vs. IOU financing arbitrage problem,
i.e. what stops government utilities from supplying all power? In fact, there are formal and informal limits, and
because fully characterizing these limits are extremely complex, the EPA Base Case v.5.13 uses a hybrid approach.
For example, recent proposals in PJM explicitly limit capacity expansion by some entities to be such that the total
capacity does not exceed internal requirements. (Source: Current MOPR modification proposal).
56 Based on ICF research, current operating capacity in U.S. is approximately evenly split between IPP and utility
owned generation. However, in the last five years (2008-2011), 62% of all large fossil plants were built by regulated
companies. In addition, another 12% of all new entrants secured long-term PPA agreements in which the risk is
expected to be similar to that of utilities generally. Thus, future capacity expansion has a lower merchant component
than the existing mix which is closer to 52%.
57 A project's capital structure is the appropriate debt capacity given a certain level of equity, commonly represented
as "D/E," i.e., debt/equity. The debt is the sum of all interest bearing short term and long term liabilities while equity is
the amount that the project sponsors inject as equity capital.
58 The U.S. wide average authorized rate of return on equity, authorized return on rate base, and authorized equity
ratio during last 5 years (2008-2012) for all 108 companies was 10.26%, 8.00%, and 48.32% respectively. For the
subset of 50 utilities that completed new rate base cases without financing new generation capacity, those averages
were only slightly lower with average authorized rate of return on equity, authorized return on rate base, and
authorized equity ratio of 10.09%, 7.90%, and 47.43% respectively. The lack of a substantial difference between
these averages suggests that authorized rates of return and equity ratios for regulated companies are not that
responsive to differences in investment choices, and are more reflective of an entire company's rate base.
8-9
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likely to have a higher debt capacity than a combustion turbine plant. Table 8-1 presents the capital
structure assumptions used in EPA Base Case v.5.13.
Table 8-1 Capital Structure Assumptions in EPA Base Case v.5.13
Technology
Combustion Turbine
Combined Cycle
Coal & Nuclear
Renewables
Retrofits
Utility
55/45
55/45
55/45
55/45
55/45
Merchant
40/60
55/45
65/35
55/45
55/45
Hybrid
51/49
55/45
58/43
55/45
N.A.
The risk differences across technologies are implemented by varying the capital structure. As shown in
Table 8-1 and discussed above, a peaking unit such as a combustion turbine is estimated to have a
capital structure of 40/60 while a base load unit such as nuclear and coal is assumed to have a capital
structure of 65/35. This is based on the expectation that less risky technologies can carry more leverage.
As debt is less expensive than equity, this will automatically translate into a lower discount rate that is
used in deriving capital charge rate for base load technologies, and a higher discount rate that is used in
deriving capital charge rate for peaking technology, assuming other components of the capital charge rate
calculation remain the same.
8.2.5 Debt and Equity Shares and Technology Risk
The capitalization structure for merchant financings was estimated to be 55/45 based on empirical
analyses. This ratio is based on the assumption that the overall IPP risk was an average reflective of the
risk profile of combined cycle units, which in turn was assumed to be intermediate between base load and
peaking. The combined cycle technology is considered to have "average" market risk being an
intermediate type technology. Also, in the aggregate, the five selected IPP companies59 have more
combined cycle capacity in their supply mix than any other technology. Additionally, going forward, it is
expected that gas will continue to play an increasingly important role in the supply mix of both utilities and
merchant companies, with combined cycle technology playing a dominant role. For all of these reasons, it
is appropriate to use the ROE corresponding to a combined cycle facility.
Each generation technology was considered to have its own risk profile because base load technologies
have multiple sources of revenues, both energy and capacity, which decreases risk and facilitates
hedging relative to IPP peaking units. Nearly 75% of load is in IMP markets, and the liquidity of these
electrical energy markets creates the potential for near-term cross commodity hedging if the plant has
significant energy sales, i.e., if the plant is non-peaking. The potential for capacity revenue hedging is
more limited than for energy. Hence, greater the base load share, the lower the asset risk. Additional
differentiation among different technologies e.g. nuclear, versus coal, was not implemented because
there is a lack of publicly traded securities that provide an empirical basis for differentiating between the
risks, and hence, financing parameters for different activities.
There are two main mechanisms for reflecting the greater risk for peak load units and the lower risk for
base load. First, the ROE could have been adjusted such that for a given target leverage the ROE would
be higher for peaking units, and lower for base load units. For example, an unlevered beta and ROE
(which assumes zero leverage) could have been calculated using the risk differentiated capital structures
and then relevered at some target leverage. This would have yielded a different ROE for each technology
but the same capital structure across all technologies.
The second option was to keep the same ROE while varying the capital structure. This method was
adopted for EPA Base Case v.5.13. Thus, even though the leverage of peaking units was lowered, the
ROE was not lowered. This raised the weighted average cost of capital and the resulting capital charge
59
The merchant parameters are derived from market observations of five IPP companies - Merchant ROE.
8-10
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rate. This effectively also raised the unlevered beta for peaking relative to combined cycle. For base load,
leverage was raised without raising ROE, effectively lowering the unlevered beta and the cost of capital.
Debt and Equity Shares
The target capitalization structure for utilities was determined using US utility capitalization ratios derived
from Bloomberg data. Similar CAPM parameters were used to estimate the ROE of the utility sector. The
capitalization structure for utility financings was estimated to be 55/45 based on empirical analyses and
this capitalization structure was assumed to be on average reflective of all technologies.60
Technology Risks
For the utility financing, EPA Base Case v.5.13 assumes that the required returns for regulated utilities
are independent of technology. This is a simplifying assumption, and further empirical work may be
warranted here.
Cost of Debt
The third step in calculating the discount rate was an assessment of the cost of debt. The summary of
historical assessment of debt rates across merchant and utility entities is summarized in Table 8-2. The
utility and merchant cost of debt is assumed to be the same across all technologies.
Table 8-2 Debt Rates for EPA Base Case v.5.13
Technology
Combustion Turbine
Combined Cycle
Coal & Nuclear
Renewables
Retrofits
Utility
5.72%
5.72%
5.72%
5.72%
5.72%
Merchant
7.58%
7.58%
7.58%
7.58%
7.58%
Hybrid
6.19%
6.19%
6.19%
6.19%
N.A.
Merchant Cost of Debt. The cost of debt for the merchant sector was estimated to be 7.6%. It is
calculated by taking a 5-year (2008-2012) weighted average of debt yields from existing company debt
with eight or more years to maturity. The weights assigned to each company debt yields were based on
that company's market capitalization. During the most recent 5 years, none of the existing long-term debt
exceeded twelve years to maturity, hence above average yields are based on debt with maturity between
eight and twelve years.
Utility Cost of Debt
The cost of debt for the utility sector was estimated to be 5.7%. It is calculated by taking a 5-year (2008-
2012) weighted average of debt yields from four long-term (20 years) Bloomberg Utility Indexes with
different debt ratings. The four indices' debt ratings ranged from BBB- to A. The weights assigned to each
index were based on the number of regulated companies with the same debt rating. 1
In the last 3 years, the average utility debt/equity ratio was approximately 1.23, which translates to 55/45
debt/equity ratio.
61 In all, 29 different regulated companies were considered when assigning weights to the Bloomberg Utility Indexes.
They are: Allete Inc., Ameren Corp., American Electric Power Co. Inc., Cleco Corp., CMS Energy Corp., Empire
District Electric Co., Great Plains Energy Inc., MGE Energy Inc. Vectren Corp., Westar Energy Inc., Wisconsin
Energy Corp., Consolidated Edison Inc., Northeast Utilities, Southern Co., UIL Holdings Corp., Avista Corp.,
IDACORP Inc., PG&E Corp., Pinnacle West Capital Corp., and Xcel Energy Inc.
8-11
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Return on Equity (ROE)
The final step in calculating the discount rate was the calculation of a return on equity (ROE) using a
weighted average ROE under utility financing (8.8% in nominal terms) and merchant financing (16.1% in
nominal terms) at a 75:25 utility/merchant ratio. These utility and merchant ROE's are estimated
assuming a 55:45 debt/equity ratio. This resulted in a hybrid ROE of 10.6% (nominal). This ROE is kept
the same across each technology62 but the risk differences across technologies are implemented through
the capital structure. See the discussion of capital structures in subsection 8.3.2.5 "Debt and Equity
Shares and Technology Risk", and subsection 8.3.2.5.1 "Debt and Equity Shares".
Merchant ROE. The Independent Power Producer (IPP) aftertax return on equity parameter was
estimated to be 16.1% (nominal). This was based on empirical analysis of stock price data of five pure
play comparable merchant generation companies, namely NRG, Dynegy, Calpine, RRI Energy, and
Mirant.63 First, levered betas64 (a measure of total corporate risk, which includes business and financial
risk) for the five companies were calculated using five years (2008-2012) of historical stock price data.
Five years is a standard time period. Weekly returns were also used as supplementary data in the
analysis. Second, unlevered betas (a measure of business risk, i.e., those affected by a firm's investment
decisions) were calculated using the estimated levered beta, the companies' market debt/equity ratio, and
the riskiness of debt. The goal is to correctly handle business or systemic risk and financial risk. As most
comparables historically had periods of financial distress, the unlevering65 approach was modified to
include the riskiness of debt, instead of purely using the Hamada equation.6 The unlevered betas were
then relevered67 at the target debt/equity ratio of 55/45 to get the relevered equity betas and return on
equity. The target debt/equity ratio of 55/45 is based on average levels of debt/equity ratios across
merchant and regulated companies over the last 3 years (2010-2012). The return on equity was
determined using the Capital Asset Pricing Model (CAPM).
The CAPM parameters used to estimate the ROE are as follows:
Risk Free Rate68 based on 20 year T bond rate: 3.8%
Market Risk69 Premium: 1926-2011: 6.62%
Size16 Premium: 1.14%
The risk free rate assumption of 3.8% represents a 5-year (2008-2012) average of U.S. Treasury 20 year
bond rates. A common practice within the CAPM construct is to utilize the most recent U.S. Treasury 20-
62 As indicated previously in Table 8-1 a 3% adder is applied to the cost of debt prior to adjustment for income taxes,
and to cost of equity when calculating capital charge rates for Supercritical Pulverized Coal and Integrated
Gasification Combined Cycle without Carbon Capture technologies.
63 Mirant and RRI Energy merged in December 2010 to form GenOn. Prior to their merger ICF analyzed these two
companies separately, while after their merger the analysis was of the merged company. Dynegy Holdings began
Chapter 11 proceedings on November 2011. The ICF analysis of Dynegy analyzed the company data until 2011.
Parts of 2011 and 2012 data were not available for further analysis of Dynegy.
64 Levered beta is directly measured from the company's stock returns with no adjustment made for the debt
financing undertaken by the company.
65 The unlevering process removes a company's financing decision from the beta calculation. The calculation
therefore, attempts to isolate the business (operating risk) of the firm.
66 The Hamada equation is described at http://www.answers.com/topic/hamada-equation as "A fundamental analysis
method of analyzing a firm's costs of capital as it uses additional financial leverage, and how that relates to the overall
riskiness of the firm. The measure is used to summarize the effects this type of leverage has on a firm's cost of
capital (over and above the cost of capital as if the firm had no debt).
67 The relevering process estimates the levered beta of the firm given a target capital structure and the pure business
risks of the firm as determined from the unlevering process.
68 Federal Reserve Statistical Release (H15 data), September 2012.
69 Source: Stocks, Bonds, Bills, and Inflation, 2012 Yearbook Valuation Edition, Morningstar/lbbotson's Associates.
8-12
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year bond rate70 which in September 2012 was 2.5%. Were EPA Base Case v.5.13 to adopt 2.5% as a
risk free rate assumption, it would lower all nominal ROEs by 1.3%. Thus, capital investment would have
a lower cost. The EPA Base Case v.5.13 assumptions deviate from that practice for several reasons:
Current rates are unsustainably low due to the latest recession, and slow pace of recovery.
Second, the EPA analysis begins in the year 2016; by that time the treasury yields are assumed to
recover from their current low levels.
The EPA Base Case financial assumptions are changed infrequently, and hence, it should not use
temporary unsustainable assumptions.
Merchant and utility cost of debt, debt-equity ratios, and historical betas are all calculated based on
the last 5 years (2008-2012) of historical data. The same approach to calculate the risk free rate is
used in order to remain consistent in its methodology.
The estimation of the IPP ROE described here is fairly close to what EIA has published. EIA estimates71
an ROE of roughly 16% by 2012.
Utility ROE. The utility return on equity was calculated to be 8.8%. This was based on empirical analysis
of the correlation of returns on the S&P utility Index vs. the broader S&P 500 market index for the
previous five years (2008-2012) to determine the levered beta and then unlevering and relevering based
on a process similar to that for merchant sector. The ROE is slightly lower than what state commissions
have awarded the shareholder-owned electric utilities recently.
8.3 Calculation of Capital Charge Rate
8.3.1 Introduction to Capital Charge Rate Calculations
EPA Base Case v.5.13 models a diverse set of generation and emission control technologies, each of
which requires financing.73
The capital charge rate is used to convert the capital cost into a stream of levelized annual payments that
ensures capital recovery of an investment. The number of payments is equal to book life of the unit or the
years of its book life included in the planning horizon (whichever is shorter). Table 8-3 presents the capital
charge rates by technology type used in EPA Base Case 5.13. Capital charge rates are a function of
underlying discount rate, book and debt life, taxes and insurance costs, and depreciation schedule.
Table 8-3 U.S. Real Capital Charge Rates3 for EPA Base Case v.5.13
New Investment Technology Capital
Environmental Retrofits - Utility Owned
Environmental Retrofits - Merchant Owned
Advanced Combined Cycle
Advanced Combustion Turbine
Supercritical Pulverized Coal and Integrated Gasification Combined Cycle without Carbon
Capture13
Capital Charge
Rate
12.10%
16.47%
10.26%
10.63%
12.57%
70 An important source of statistics and common practices associated with calculating cost of capital with CAPM
model is based on the Morningstar's 2012 issue of the Ibbotsonฎ Cost of Capital Yearbook.
71 See Electricity Market Module of NEMS, EIA Annual Energy Outlook, June 2012.
72 SNL based rate case statistics for 2011 suggest nationwide average ROE rate of 10.3%.
73 The capital charge rates discussed here apply to new (potential) units and environmental retrofits that IPM installs.
The capital cost of existing and planned/committed generating units and the emission controls already on these units
are considered "sunk costs" and are not represented in the model.
8-13
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Advanced Coal with Carbon Capture
Nuclear without Production Tax Credit (PTC)
Nuclear with Production Tax Credit (PTC)C
Biomass
Wind, Landfill Gas, Solar and Geothermal
9.68%
9.44%
7.97%
9.53%
10.85%
Notes:
a Capital charge rates were adjusted for expected inflation and represent real rates. The expected inflation rate used to convert
future nominal to constant real dollars is 2.0%. The future inflation rate of 2.0% is based on an assessment of implied inflation
from an analysis of yields on 10 year U.S. Treasury securities and U.S. Treasury Inflation Protected Securities (TIPS) over a
period of 5 years (2008-2012).
b EPA has adopted the procedure followed in ElA's Annual Energy Outlook 2013; the capital charge rates shown for Supercritical
Pulverized Coal and Integrated Gasification Combined Cycle (IGCC) without Carbon Capture include a 3% adder to the cost of
debt and equity. See Levelized Cost of New Generation Resources in the Annual Energy Outlook 2013 (p.2),
http://www.eia.gov/forecasts/aeo/er/pdf/electricitv generation.pdf
0 The Energy Policy Act of 2005 (Sections 1301, 1306, and 1307) provides a production tax credit (PTC) of 18 mills/kWh for 8
years up to 6,000 MW of new nuclear capacity. The financial impact of the credit is reflected in the capital charge rate shown in
for "Nuclear with Production Tax Credit (PTC)." NEEDS v.5.13 integrates 4,400 MW of new nuclear capacity at V C Summer and
Vogtle nuclear power plants. Therefore, in EPA Base Case v.5.13, only 1,600 MW of incremental new nuclear capacity will be
provided with this tax credit.
8.3.2 Capital Charge Rate Components
The capital charge rate is a function of the parameters that overlap in part with the discount rate such as
the level of the capital investment and recovery of capital, but also include parameters related to the
amortization of capital:
Capital structure (Debt/Equity shares of an investment)
Pre-tax debt rate (or interest cost)
Debt Life
Post-tax Return on Equity (ROE) (or cost of equity)
Other costs such as property taxes and insurance
State and Federal corporate income taxes
Depreciation Schedule
Book Life
Table 8-4 presents a summary of various assumed lives at the national level. The EPA Base Case v.5.13
assumes a book life of 15 years for retrofits. This assumption is made to account for recent trends in
financing of retrofit types of investments.
Table 8-4 Book Life, Debt Life and Depreciation Schedules for EPA Base Case v. 5.13
Technology
Combine Cycle
Combustion Turbine
Coal Steam and IGCC
Nuclear
Solar, Geothermal, Wind and Landfill Gas
Biomass
Retrofits
Book Life
(Years)
30
30
40
40
20
40
15
Debt Life
(Years)
20
15
20
20
20
20
15
US MACRS Depreciation
Schedule
20
15
20
15
5
7
15
8-14
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Book Life
The book life or useful life of a plant was estimated based on researching financial statements of utility
and merchant generation companies. The financial statements74 typically list the period over which long
lived assets are depreciated for financial reporting purposes. The research conducted broadly supports
the numbers outlined in the table above.
Debt Life
The debt life is assumed to be on a 20 year schedule except in the case of combustion turbine and
environmental retrofits where debt life is assumed to be on a 15 year schedule.
Depreciation Schedule
The US MACRS75 depreciation schedules were obtained from IRS Publication 94676 that lists the
schedules based on asset classes. The document specifies a 5 year depreciation schedule for wind
energy projects and 20 years for Electric Utility Steam Production plants. These exclude combustion
turbines which have a separate listing at 15 years. Nuclear Power Plants are separately listed as 15 years
as well.
Taxation and Insurance Costs
Corporate and State Income Taxes: The maximum US corporate income tax rate77 is 35%. State taxes
vary but on a national average basis, the state taxes78 are 6.45%. This yields a net effective tax rate of
39.1%.
US state property taxes are approximately 0.9% based on a national average basis. This is based on
extensive primary and secondary research conducted by ICF using property tax rates obtained from
various state agencies.
Insurance costs are approximately 0.3%. This is based on estimates of insurance costs on a national
average basis.
8.3.3 Capital Charge Rate Calculation Process
The capital charge rate is calculated by solving for earnings before interest, taxes, and depreciation
(EBITDA) or pure operating earnings such that the project is able to recover the cost of equity as the
internal rate of return over the lifetime of the project. The sum of discounted cash flows to the equity
holders over the lifetime of the project, discounted at the cost of equity is set equal to the initial
investment. Put another way, it creates an annuity value when multiplied by the capital investment to
recover all capital related charges and provide an IRR equal to the required return on equity. The capital
charge rate so calculated is defined as follows:
Capital Charge Rate = EBITDA/Total Investment
74 SEC 10K filings of electric utilities and pure merchant companies. For example, Calpine's 10K lists 35 years of
useful life for base load plants, DTE energy uses 40 years for generation equipment; Dynegy gives a range of 20-40
years for power generation facilities; Mirant reports 14-35 years for power production equipment; Reliant: 10-35
years.
75 MACRS refers to the Modified Accelerated Cost Recovery System, issued after the release of the Tax Reform Act
of 1986. It allowed faster depreciation than with previous methods.
76 IRS Publication 946, "How to Depreciate Property", Table B-2, Class Lives and Recovery Periods.
77 Internal Revenue Service, Publication 542.
78 Represents weighted average state corporate marginal income tax rate.
8-15
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In other words, the capital charge rate is the annuity charge that provides for the rate of return required on
invested capital, resulting from pure operations.
The discounted cash flow to the equity holders of the project is characterized in terms of the Free Cash
Flow to Equity (FCFE). FCFE is a valuation technique to estimate cash flows paid to the equity
shareholders of a company after all expenses, reinvestment, and debt repayment have been made. The
FCFE approach is suited for valuation of assets that have finite economic lives and where debt levels
vary from year to year. In the FCFE approach, it is assumed that the asset has a finite life and debt
reduces overtime based on a mortgage-style repayment structure.
Specifically the cash flows to the equity79 are calculated as follows:
Cash Flows to Equity80 = EBIT (1-tax rate)
-Interest (1-tax rate)
+ Depreciation
-Capital Expenditures
-Working Capital Change81
-Principal Payments
+ New Debt Issued
yn
An alternative definition of free cash flow to equity is as follows:
Net Income + Depreciation -capital expenditures -working capital change - Principal Payments + New Debt Issued
80 Property taxes and insurance are incorporated in cash flow calculations.
81 NERA Economic Consulting estimates that working capital and inventory constitutes about 2% of direct capital
costs. NERA also indicates that working capital and inventories (inventories refer to the initial inventories of fuel,
consumables, and spare parts) are normally capitalized. Therefore, this item does not need to be in the capital
charge rate. See "Independent Study to Establish Parameters of the ICAP Demand Curve for the New York
Independent System Operator", August 27, 2010.
8-16
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9. Coal
The next three chapters cover the representation and underlying assumptions for fuels in EPA Base Case
v.5.13. The current chapter focuses on coal, chapter 10 on natural gas, and chapter 11 on other fuels
(fuel oil, biomass, nuclear fuel, and waste fuels) represented in the base case.
This chapter presents four main topics. The first is a description of how the coal market is represented in
EPA Base Case v.5.13. This includes a discussion of coal supply and demand regions, coal quality
characteristics, and the assignment of coals to power plants.
The next topic is the coal supply curves which were developed for EPA Base Case v.5.13 and the
bottom-up, mine-based approach used to develop curves that would depict the coal choices and
associated prices that power plants will face over the modeling time horizon. Included are discussions of
the methods and data used to quantify the economically recoverable coal reserves, characterize their
cost, and build the 67 coal supply curves that are implemented in EPA Base Case v.5.13. Illustrative
examples are included of the step-by-step approach employed in developing the supply curves.
The third topic is coal transportation. It includes a description of the transport network, the methodology
used to assign costs to the links in the network, and a discussion of the geographic, infrastructure, and
regulatory considerations that come into play in developing specific rail, barge and truck transport rates.
The last topic covered in this chapter is coal exports, imports, and non-electric sector demand.
The assumptions for the coal supply curves and coal transportation were finalized in June 2013, and were
developed through a collaborative process with EPA supported by the following team of coal experts (with
key areas of responsibility noted in parenthesis): TetraTech (coal transportation and team coordination),
Wood Mackenzie (coal supply curve development), Hellerworx (coal transportation and third party
review), and ICF (representation in IPM). The coal supply curves and transportation matrix implemented
in EPA Base Case v.5.13 are included in tables and attachments at the end of this chapter.
9.1 Coal Market Representation in EPA Base Case v.5.13
Coal supply, coal demand, coal quality, and the assignment of specific types of coals to individual coal
fired generating units are the four key components of the endogenous coal market modeling framework in
EPA Base Case v.5.13. The modeling representation attempts to realistically reflect the actual options
available to each existing coal fired power plant while aggregating data sufficiently to keep the model size
and solution time within acceptable bounds.
Each coal-fired power plant modeled is reflected as its own coal demand region. The demand regions are
defined to reflect the coal transportation options (rail, barge, truck, conveyer belt) that are available to the
plant. These demand regions are interconnected by a transportation network to at least one of the 36
geographically dispersed coal supply regions. The model's supply-demand region links reflect actual on-
the-ground transportation configurations. Every coal supply region can produce and each coal demand
region can demand at least one grade of coal. Based on historical and engineering data (as described in
Section 9.1.5 below), each coal fired unit is also assigned several coal grades which it may use if that
coal type is available within its demand region.
In EPA Base Case v.5.13 the endogenous demand for coal is generated by coal fired power plants
interacting with a set of exogenous supply curves (see Table 9-24 for coal supply curve data) for each
coal grade in each supply region. The curves show the supply of coal (by coal supply region and coal
grade) that is available to meet the demand at a given price. The supply of and demand for each grade of
coal is linked to and affected by the supply of and demand for every other coal grade across supply and
demand regions. The transportation network or matrix (see
Excerpt from Table 9-23 for coal transportation matrix data) also factors into the final determination of
delivered coal prices, given coal demand and supply. IPM derives the equilibrium coal consumption and
9-1
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prices that result when the entire electric system is operating, emission, and other requirements are met
and total electric system costs over the modeling time horizon are minimized.
9.1.1 Coal Supply Regions
There are 36 coal supply regions in EPA Base Case v.5.13, each representing geographic aggregations
of coal-mining areas that supply one or more coal grades. Coal supply regions may differ from one
another in the types and quality of coal they can supply. Table 9-1 lists the coal supply regions included in
EPA Base Case v.5.13.
Figure 9-1 provides a map showing the location of both the coal supply regions listed in Table 9-1 and the
broader supply basins commonly used when referring to U.S. coal reserves.
Table 9-1 Coal Supply Regions in EPA Base Case
Region
State
Supply Region
Central Appalachia
Central Appalachia
Central Appalachia
Central Appalachia
Dakota Lignite
Dakota Lignite
East Interior
East Interior
East Interior
Gulf Lignite
Gulf Lignite
Gulf Lignite
Northern Appalachia
Northern Appalachia
Northern Appalachia
Northern Appalachia
Northern Appalachia
Rocky Mountains
Rocky Mountains
Rocky Mountains
Rocky Mountains
Southern Appalachia
Southwest
Southwest
West Interior
West Interior
West Interior
West Interior
Western Montana
Western Montana
Western Wyoming
Wyoming Northern PRB
Wyoming Southern PRB
Alberta
British Columbia
Saskatchewan
Kentucky, East
Tennessee
Virginia
West Virginia, South
Montana, East
North Dakota
Illinois
Indiana
Kentucky, West
Mississippi
Louisiana
Texas
Maryland
Ohio
Pennsylvania, Central
Pennsylvania, West
West Virginia, North
Colorado, Green River
Colorado, Raton
Colorado, Uinta
Utah
Alabama
Arizona
New Mexico, San Juan
Arkansas, North
Kansas
Missouri
Oklahoma
Montana, Bull Mountains
Montana, Powder River
Wyoming, Green River
Wyoming, Powder River Basin
Wyoming, Powder River Basin
Alberta, Canada
British Columbia, Canada
Saskatchewan, Canada
KE
TN
VA
WS
ME
ND
IL
IN
KW
MS
LA
TX
MD
OH
PC
PW
WN
CG
CR
CU
UT
AL
AZ
NS
AN
KS
MO
OK
MT
MP
WG
WH
WL
AB
BC
SK
9-2
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Figure 9-1 Map of the Coal Supply Regions in EPA Base Case v.5.13
Coal Supply Regions
9.1.2 Coal Demand Regions
Coal demand regions are designed to reflect coal transportation options available to power plants. Each
existing coal plant is reflected as its own individual demand region. The transportation infrastructure (i.e.,
rail, barge, or truck/conveyor belt), proximity to mine (i.e., mine mouth or not mine mouth), and
transportation competitiveness levels (i.e., non-competitive, low-cost competitive, or high-cost
competitive) are developed specific to each coal plant (demand region).
When IPM is run, it determines the amount and type of new generation capacity to add within each of
IPM's 64 US model regions. These model regions reflect the administrative, operational, and
transmission geographic structure of the electricity grid. Since these new plants could be located at
various locations within the region, a generic transportation cost for different coal types is developed for
these new plants and the methodology for deriving that cost is described in the transportation section of
this chapter. See Table 9-2 for the list of coal plant demand regions reflected in the transportation matrix.
9-3
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Table 9-2 Coal Demand Regions in EPA Base Case
Plant ORIS
Code
1004
1010
10684
1077
1554
1606
1943
2682
2943
3319
511
54407
55856
56564
56785
56808
7
7242
728
991
10
10003
1001
10043
10071
10075
1008
10113
1012
10143
10148
10151
1024
1032
10328
10333
10343
1037
10377
10378
10380
10382
10384
1040
1043
10464
1047
1048
10495
10566
10603
10640
10641
10670
Plant Name
Edwardsport
Wabash River
Argus Cogen Plant
Sutherland
Herbert A Wagner
Mount Tom
Hoot Lake
S A Carlson
Shelby Municipal Light Plant
Jefferies
Trinidad
Waupun Correctional Central Heating Pit
Prairie State Generatng Station
John W Turk Jr Power Plant
Virginia Tech Power Plant
Virginia City Hybrid Energy Center
Gadsden
Polk
Yates
Eagle Valley
Greene County
Colorado Energy Nations Company
Cayuga
Logan Generating Company LP
Portsmouth Genco LLC
Taconite Harbor Energy Center
R Gallagher
John B Rich Memorial Power Station
F B Culley
Colver Power Project
White Pine Electric Power
Grant Town Power Plant
Crawfordsville
Logansport
T B Simon Power Plant
Central Power & Lime
Foster Wheeler Mt Carmel Cogen
Peru
James River Genco LLC
CPI USA NC Southport
Elizabethtown Power LLC
Lumberton
Edgecombe Genco LLC
Whitewater Valley
Frank E Ratts
Black River Generation
Lansing
Milton L Kapp
Rumford Cogeneration
Chambers Cogeneration LP
Ebensburg Power
Stockton Cogen
Cambria Cogen
AES Deepwater
Coal Demand
Region Codes
C181
C183
C563
C194
C227
C232
C259
C303
C339
C365
C131
C624
C637
C644
C651
C653
C101
C495
C151
C176
C103
C514
C180
C517
C518
C519
C182
C520
C184
C521
C522
C523
C185
C186
C528
C529
C530
C187
C540
C541
C542
C543
C544
C188
C189
C546
C191
C192
C548
C550
C552
C554
C555
C556
IPM Model Region for Which the Existing
Demand Region Serves as the Surrogate*
MISJL
SPP_WEST
NENG_ME
WEC_CALN
9-4
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Plant ORIS
Code
10671
10672
10675
10676
10678
1073
10743
10768
10769
10784
108
1081
1082
10849
1091
1104
1122
113
1131
1167
1217
1218
1241
1250
1252
126
127
1295
130
1355
1356
136
1364
1374
1378
1379
1381
1382
1383
1384
1385
1393
1552
1571
1572
1573
160
1619
165
1695
1702
1710
1720
1723
1731
Plant Name
AES Shady Point LLC
Cedar Bay Generating Company LP
AES Thames
AES Beaver Valley Partners Beaver Valley
AES Warrior Run Cogeneration Facility
Prairie Creek
Morgantown Energy Facility
Rio Bravo Jasmin
Rio Bravo Poso
Colstrip Energy LP
Holcomb
Riverside
Walter Scott Jr Energy Center
Silver Bay Power
George Neal North
Burlington
Ames Electric Services Power Plant
Cholla
Streeter Station
Muscatine Plant #1
Earl F Wisdom
Fair Station
La Cygne
Lawrence Energy Center
Tecumseh Energy Center
H Wilson Sundt Generating Station
Oklaunion
Quindaro
Cross
E W Brown
Ghent
Seminole
Mill Creek
Elmer Smith
Paradise
Shawnee
Kenneth C Coleman
HMP&L Station Two Henderson
Robert A Reid
Cooper
Dale
R S Nelson
C P Crane
Chalk Point LLC
Dickerson
Morgantown Generating Plant
Apache Station
Brayton Point
GRDA
B C Cobb
Dan E Karn
J H Campbell
J C Weadock
J R Whiting
Harbor Beach
Coal Demand
Region Codes
C557
C558
C560
C561
C562
C193
C564
C565
C566
C570
C113
C195
C196
C572
C197
C198
C199
C114
C200
C201
C203
C204
C206
C207
C208
C115
C116
C209
C117
C211
C212
C118
C216
C217
C218
C219
C220
C221
C222
C223
C224
C225
C226
C229
C230
C231
C119
C234
C120
C236
C237
C238
C239
C240
C241
IPM Model Region for Which the Existing
Demand Region Serves as the Surrogate*
NENG_CT
MIS_MIDA
ERC_WEST
S_C_KY
S_C_TVA
S_D_WOTA
PJM_SMAC
9-5
-------
Plant ORIS
Code
1733
1740
1743
1745
1769
1771
1825
1830
1831
1832
1843
1866
1891
1893
1915
1961
1979
2008
2018
2022
2049
207
2076
2079
2080
2094
2098
2103
2104
2107
2123
2132
2144
2161
2167
2168
2171
2187
2240
2277
2291
2324
2364
2367
2378
2403
2408
2442
2451
2526
2527
2535
2549
2554
26
Plant Name
Monroe
River Rouge
St Clair
Trenton Channel
Presque Isle
Escanaba
J B Sims
James De Young
Eckert Station
Erickson Station
Shiras
Wyandotte
Syl Laskin
Clay Boswell
Allen S King
Austin Northeast
Nibbing
Silver Lake
Virginia
Willmar
Jack Watson
St Johns River Power Park
Asbury
Hawthorn
Mont rose
Sibley
Lake Road
Labadie
Meramec
Sioux
Columbia
Blue Valley
Marshall
James River Power Station
New Madrid
Thomas Hill
Missouri City
J E Corette Plant
Lon Wright
Sheldon
North Omaha
Reid Gardner
Merrimack
Schiller
B L England
PSEG Hudson Generating Station
PSEG Mercer Generating Station
Four Corners
San Juan
AES Westover
AES Greenidge LLC
AES Cayuga
C R Huntley Generating Station
Dunkirk Generating Plant
E C Gaston
Coal Demand
Region Codes
C243
C244
C245
C246
C247
C248
C249
C250
C251
C252
C253
C254
C255
C256
C258
C260
C261
C262
C263
C264
C265
C121
C267
C268
C269
C270
C271
C272
C273
C274
C275
C276
C277
C278
C279
C280
C282
C283
C284
C285
C286
C287
C288
C289
C290
C292
C293
C295
C296
C298
C299
C300
C301
C302
C104
IPM Model Region for Which the Existing
Demand Region Serves as the Surrogate*
MIS_LMI
MIS_MO
WECC_SNV
NENGREST
PJM_EMAC
NY_Z_C&E
9-6
-------
Plant ORIS
Code
2706
2712
2718
2721
2727
2790
2817
2823
2824
2828
2836
2840
2850
2866
2876
2878
2914
2917
2935
2936
2952
2963
298
3
3118
3122
3130
3136
3138
3140
3149
3152
3179
3181
3287
3295
3297
3298
3393
3396
3399
3403
3407
3470
3497
3775
3796
3797
3809
384
3845
3935
3943
3944
3948
Plant Name
Asheville
Roxboro
G G Allen
Cliffside
Marshall
R M Heskett
Leland Olds
Milton R Young
Stanton
Cardinal
Avon Lake
Conesville
J M Stuart
FirstEnergy W H Sammis
Kyger Creek
FirstEnergy Bay Shore
Dover
Hamilton
Orrville
Painesville
Muskogee
Northeastern
Limestone
Barry
Conemaugh
Homer City Station
Seward
Keystone
New Castle Plant
PPL Brunner Island
PPL Montour
Sunbury Generation LP
Hatfields Ferry Power Station
FirstEnergy Mitchell Power Station
McMeekin
Urquhart
Wateree
Williams
Allen Steam Plant
Bull Run
Cumberland
Gallatin
Kingston
W A Parish
Big Brown Power Company LLC
Clinch River
Bremo Bluff
Chesterfield
Yorktown
Joliet 29
Transalta Centralia Generation
John E Amos
FirstEnergy Fort Martin Power Station
FirstEnergy Harrison Power Station
Mitchell
Coal Demand
Region Codes
C304
C306
C309
C311
C312
C314
C315
C316
C317
C318
C322
C325
C328
C331
C333
C334
C335
C336
C337
C338
C340
C341
C122
C100
C345
C346
C347
C349
C350
C351
C352
C353
C355
C356
C360
C361
C362
C363
C367
C368
C369
C370
C373
C375
C376
C378
C381
C382
C384
C123
C385
C386
C390
C391
C395
IPM Model Region for Which the Existing
Demand Region Serves as the Surrogate*
S_VACA
MAP_WAUE
MIS_MNWI
PJM_PENE
PJM_WMAC
WECC_PNW
9-7
-------
Plant ORIS
Code
3954
3992
4041
4042
4050
4072
4078
4125
4127
4140
4143
4158
4162
4259
4271
465
469
47
470
477
492
4941
50
50039
50130
50366
50388
50397
50410
50611
50776
508
50806
50835
50879
50888
50931
50951
50974
50976
51
52007
52071
525
527
54035
54081
54144
54304
54408
54556
54634
54677
54755
54775
Plant Name
Mt Storm
Blount Street
South Oak Creek
Valley
Edgewater
Pulliam
Weston
Manitowoc
Menasha
Alma
Genoa
Dave Johnston
Naughton
Endicott Station
John P Madgett
Arapahoe
Cherokee
Colbert
Comanche
Valmont
Martin Drake
Navajo
Widows Creek
Kline Township Cogen Facility
G F Weaton Power Station
University of Notre Dame
Phillips 66 Carbon Plant
P H Glatfelter
Chester Operations
WPS Westwood Generation LLC
Panther Creek Energy Facility
Lamar Plant
Stone Container Florence Mill
TES Filer City Station
Wheelabrator Frackville Energy
Northampton Generating Company LP
Yellowstone Energy LP
Sunnyside Cogen Associates
Scrubgrass Generating Company LP
Indiantown Cogeneration LP
Dolet Hills
Mecklenburg Power Station
Sandow Station
Hayden
Nucla
Roanoke Valley Energy Facililty I
Spruance Genco LLC
Piney Creek Project
Birchwood Power
UW Madison Charter Street Plant
Corn Products Illinois
St Nicholas Cogen Project
CM Carbon LLC
Roanoke Valley Energy Facility II
University of Iowa Main Power Plant
Coal Demand
Region Codes
C396
C397
C398
C399
C400
C402
C403
C404
C405
C406
C407
C410
C411
C412
C413
C125
C126
C105
C127
C128
C129
C414
C106
C580
C581
C588
C590
C592
C594
C597
C599
C130
C601
C602
C603
C604
C606
C607
C609
C610
C107
C611
C612
C132
C133
C614
C615
C616
C621
C625
C626
C627
C628
C629
C630
IPM Model Region for Which the Existing
Demand Region Serves as the Surrogate*
WECC_CO
WECC_SF
9-8
-------
Plant ORIS
Code
55076
55479
55749
56
56068
56163
56224
56319
564
56456
56596
56609
56611
56671
56708
56786
568
56848
57046
59
593
594
60
6002
6004
6009
6016
6017
6018
6019
602
6021
6030
6031
6034
6041
6052
6055
6061
6064
6065
6068
6071
6073
6076
6077
6082
6085
6089
6090
6094
6095
6096
6098
6101
Plant Name
Red Hills Generating Facility
Wygen 1
Hardin Generator Project
Charles R Lowman
Elm Road Generating Station
KUCC
TS Power Plant
Wygen 2
Stanton Energy Center
Plum Point Energy Station
Wygen III
Dry Fork Station
Sandy Creek Energy Station
Longview Power LLC
CFB Power Plant
Spiritwood Station
Bridgeport Station
Haverhill North Cogeneration Facility
Archer Daniels Midland Columbus
Platte
Edge Moor
Indian River Generating Station
Whelan Energy Center
James H Miller Jr
FirstEnergy Pleasants Power Station
White Bluff
Duck Creek
Newton
East Bend
W H Zimmer
Brandon Shores
Craig
Coal Creek
Killen Station
Belle River
H L Spurlock
Wansley
Big Cajun 2
R D Morrow
Nearman Creek
latan
Jeffrey Energy Center
Trimble County
Victor J Daniel Jr
Colstrip
Gerald Gentleman
AES Somerset LLC
R M Schahfer
Lewis & Clark
Sherburne County
FirstEnergy Bruce Mansfield
Sooner
Nebraska City
Big Stone
Wyodak
Coal Demand
Region Codes
C633
C635
C636
C108
C639
C640
C641
C642
C134
C643
C645
C646
C647
C649
C650
C652
C135
C210
C654
C109
C136
C137
C110
C415
C416
C417
C418
C419
C420
C421
C138
C422
C423
C424
C425
C426
C427
C428
C429
C430
C431
C432
C433
C434
C435
C436
C437
C438
C439
C440
C441
C442
C443
C444
C445
IPM Model Region for Which the Existing
Demand Region Serves as the Surrogate*
MIS_WUMS
WECC_NNV
FRCC
S_D_N_AR
WECC_WY
PJM_AP
MIS_MAPP
SPP_NEBR
S_D_REST
SPP_N
WECC_MT
NY_Z_A&B
9-9
-------
Plant ORIS
Code
6106
6113
6124
6136
6137
6138
6139
6146
6147
6155
6165
6166
6170
6177
6178
6179
6180
6181
6183
6190
6193
6194
6195
6204
6213
6225
6248
6249
6250
6254
6257
6264
628
641
642
643
645
6469
6481
663
6639
6641
6648
6664
667
6705
676
6761
6768
6772
6823
703
7030
708
709
Plant Name
Boardman
Gibson
Mclntosh
Gibbons Creek
A B Brown
Flint Creek
Welsh
Martin Lake
Monticello
Rush Island
Hunter
Rockport
Pleasant Prairie
Coronado
Coleto Creek
Fayette Power Project
Oak Grove
J T Deely
San Miguel
Brame Energy Center
Harrington
Tolk
Southwest Power Station
Laramie River Station
Merom
Jasper 2
Pawnee
Winyah
Mayo
Ottumwa
Scherer
Mountaineer
Crystal River
Crist
Scholz
Lansing Smith
Big Bend
Antelope Valley
Intermountain Power Project
Deerhaven Generating Station
R D Green
Independence
Sandow No 4
Louisa
Northside Generating Station
Warrick
C D Mclntosh Jr
Rawhide
Sikeston Power Station
Hugo
D B Wilson
Bowen
Twin Oaks Power One
Hammond
Harllee Branch
Coal Demand
Region Codes
C446
C447
C448
C449
C450
C451
C452
C453
C454
C455
C456
C457
C458
C459
C460
C461
C462
C463
C464
C465
C466
C467
C468
C469
C470
C471
C473
C474
C475
C476
C477
C478
C139
C140
C141
C142
0143
C480
C481
C144
C482
C483
C484
C485
0145
0486
C146
0487
C488
0489
C490
0147
C491
0148
C149
IPM Model Region for Which the Existing
Demand Region Serves as the Surrogate*
MISJNKY
WECC_UT
ERC_REST
SPP_SE
SPP_SPS
MISJA
S_SOU
9-10
-------
Plant ORIS
Code
7097
7210
7213
727
733
7343
7504
753
7549
7737
7790
7902
8
8023
8042
8066
8069
8102
8219
8222
8223
8224
8226
856
861
87
874
876
879
883
884
887
889
891
892
898
963
976
983
990
994
995
997
83551
55360
56664
70194
70195
70243
70269
70309
70035
70441
70449
70450
Plant Name
J K Spruce
Cope
Clover
Mitchell
Kraft
George Neal South
Neil Simpson II
Crisp Plant
Milwaukee County
Cogen South
Bonanza
Pirkey
Gorgas
Columbia
Belews Creek
Jim Bridger
Huntington
General James M Gavin
Ray D Nixon
Coyote
Springerville
North Valmy
Cheswick Power Plant
E D Edwards
Coffeen
Escalante
Joliet 9
Kincaid Generation LLC
Powerton
Waukegan
Will County
Joppa Steam
Baldwin Energy Complex
Havana
Hennepin Power Station
Wood River
Dallman
Marion
Clifty Creek
Harding Street
AES Petersburg
Bailly
Michigan City
Plant Ratcliffe - the Kemper IGCC Project
Two Elk Generating Station
Greene Energy Resource Recovery Project
Genesee #3
Genesee
HR Milner
Keephills
Lingan
Belledune
Poplar River
Pt. Aconi
Pt. Tupper
Coal Demand
Region Codes
C492
C493
C494
C150
C152
C496
C497
C153
C499
C501
C502
C503
C102
C504
C505
C672
C506
C507
C508
C509
C510
C511
C512
C154
C155
C112
C158
C159
C160
C161
C162
C164
C165
C166
C167
C169
C170
C171
C173
C175
C177
C178
C179
C633
C634
C678
C661
C661
C662
C663
C664
C658
C665
C666
C667
IPM Model Region for Which the Existing
Demand Region Serves as the Surrogate*
PJM_Dom
WECC_AZ
WECC_NM
PJM_COMD
CN_AB
CN_NB
CN_NS
9-11
-------
Plant ORIS
Code
70514
70517
70056
70562
70587
3264
3406
3803
2480
2837
10002
70058
1353
Plant Name
Shand
Sheerness
Boundary Dam
Sundance
Trenton NS
WSLee
Johnsonville
Chesapeake
Danskammer Generating Station
FirstEnergy Eastlake
ACE Cogeneration Facility
Brandon G.S.
Big Sandy
Coal Demand
Region Codes
C668
C669
C659
C670
C671
C358
C372
C383
C676
C297
C675
C323
C677
C513
C660
C210
IPM Model Region for Which the Existing
Demand Region Serves as the Surrogate*
CN_SK
NY_Z_F
NY_Z_G-I
NY_Z_D
PJM_ATSI
S_D_AMSO
WECC_SCE
CN_MB
PJM_West
*lf IPM elects to build a new coal plant, that coal plant will be assigned to a particular IPM region. Therefore, the base case
modeling relies on a particular existing plant in that region - generally one considered to be representative of average transportation
cost for plants in that region - and uses that plant's transportation cost as a surrogate for coal transportation cost for a projected
new coal plant.
9.1.3 Coal Quality Characteristics
Coal varies by heat content, SO2 content, HCI content, and mercury content among other characteristics.
To capture differences in the sulfur and heat content of coal, a two letter "coal grade" nomenclature is
used. The first letter indicates the "coal rank" (bituminous, subbituminous, or lignite) with their associated
heat content ranges (as shown in Table 9-3). The second letter indicates their "sulfur grade," i.e., the SO2
ranges associated with a given type of coal. (The sulfur grades and associated SO2 ranges are shown in
Table 9-4.).
Table 9-3 Coal Rank Heat Content Ranges
Coal Type
Bituminous
Subbituminous
Lignite
Heat Content (Btu/lb)
>10,260- 13,000
> 7,500 -10,260
less than 7,500
Classification
B
S
L
Table 9-4 Coal Grade SO2 Content Ranges
SO2 Grade
A
B
D
E
G
H
SO2 Content Range (Ibs/MMBtu)
0.00-0.80
0.81 -1.20
1.21 -1.66
1.67-3.34
3.35-5.00
>5.00
9-12
-------
The assumptions in EPA Base Case v.5.13 on the heat, HCI, mercury, SO2, and ash content of coal are
derived from EPA's "Information Collection Request for Electric Utility Steam Generating Unit Mercury
Emissions Information Collection Effort" (ICR)
82
A two-year effort initiated in 1998 and completed in 2000, the ICR had three main components: (1)
identifying all coal-fired units owned and operated by publicly-owned utility companies, Federal power
agencies, rural electric cooperatives, and investor-owned utility generating companies, (2) obtaining
"accurate information on the amount of mercury contained in the as-fired coal used by each electric utility
steam generating unit... with a capacity greater than 25 megawatts electric, as well as accurate
information on the total amount of coal burned by each such unit,", and (3) obtaining data by coal
sampling and stack testing at selected units to characterize mercury reductions from representative unit
configurations. Data regarding the SO2, chlorine, and ash content of the coal used was obtained along
with mercury content.
The 1998-2000 ICR resulted in more than 40,000 data points indicating the coal type, sulfur content,
mercury content, ash content, chlorine content, and other characteristics of coal burned at coal-fired utility
units greater than 25 MW.
9.1.4 Emission Factors
To make this data usable in EPA Base Case v.5.13, the ICR data points were first grouped by IPM coal
grades and IPM coal supply regions. Using the grouped ICR data, the average heat, SO2, mercury, HCI,
and ash content were calculated for each coal grade/supply region combination. In instances where no
data were available for a particular coal grade in a specific supply region, the national average SO2 and
mercury values for the coal grade were used as the region's values. The coal characteristics of Canadian
coal supply regions are based on the coal characteristics of the adjacent US coal supply regions. The
resulting values are shown in Table 9-5.
Table 9-5 Coal Quality Characteristics by Supply Region and Coal Grade
Coal
Supply
Region
AB
AL
AN
AZ
BC
CG
CR
CU
IL
IN
KE
Coal
Grade
SA
SB
SD
BB
BE
BG
BB
BD
BB
SB
BB
BB
BE
BG
BH
BB
BE
BG
BH
BB
Heat Content
(MMBtu/Ton)
16.12
15.60
15.00
25.50
24.00
22.00
21.50
21.40
22.74
20.00
23.36
23.56
23.75
23.50
22.00
22.00
22.70
22.40
22.40
25.00
SO2 Content
(Ibs/MMBtu)
0.59
0.94
1.43
1.09
2.68
4.23
1.05
1.40
0.90
0.93
1.05
0.86
2.25
4.56
5.58
1.00
2.31
4.27
6.15
1.04
Mercury
Content
(Ibs/Tbtu)
5.29
6.06
5.35
4.18
12.58
9.36
5.27
6.98
4.09
2.03
5.27
4.01
6.52
6.53
5.43
2.29
5.21
7.20
7.11
4.79
Ash Content
(Ibs/MMBtu)
5.47
6.94
11.60
9.76
10.70
7.83
7.86
8.34
8.42
7.06
7.86
7.83
6.61
8.09
9.06
6.67
7.97
8.22
8.63
6.41
HCI Content
(Ibs/MMBtu)
0.009
0.013
0.008
0.012
0.028
0.079
0.067
0.096
0.021
0.007
0.067
0.009
0.214
0.113
0.103
0.050
0.036
0.028
0.019
0.112
CO2 Content
(Ibs/MMBtu)
214.9
211.0
214.9
204.7
204.7
202.8
207.1
205.4
209.6
209.6
209.6
209.6
203.1
203.1
203.1
203.1
203.1
203.1
203.1
206.4
82
Data from the ICR can be found at http://www.epa.qov/ttn/atw/combust/utiltox/mercurv.html..
9-13
-------
Coal
Supply
Region
KS
KW
LA
MD
ME
MO
MP
MS
MT
ND
NS
OH
OK
PC
PW
SK
TN
TX
UT
VA
WG
WH
WL
WN
WS
Coal
Grade
BD
BE
BG
BD
BG
BH
LE
BD
BE
LE
BG
SA
SD
LE
BB
LE
SB
SE
BE
BG
BH
BG
BE
BG
BE
BG
LD
LE
BB
BE
LE
LG
LH
BA
BE
BB
BD
BE
BB
SD
SA
SB
BE
BH
BB
BD
BE
Heat Content
(MMBtu/Ton)
24.80
24.64
22.00
23.80
23.80
23.00
13.80
23.00
23.20
12.97
22.00
18.20
17.20
10.39
20.90
13.10
19.60
18.40
24.20
24.10
24.20
22.00
24.41
24.40
26.00
25.40
13.82
10.58
26.20
25.23
13.47
12.47
10.68
23.00
23.90
25.90
25.20
25.00
22.00
18.80
17.60
16.79
25.35
25.15
24.40
24.50
23.83
SO2 Content
(Ibs/MMBtu)
1.44
2.12
4.84
1.56
4.46
5.73
2.49
1.55
2.78
1.83
4.54
0.62
1.49
2.76
1.05
2.27
0.89
1.90
3.08
3.99
6.43
4.65
2.57
3.79
2.51
3.69
1.51
2.76
1.14
2.13
3.00
3.91
5.67
0.67
2.34
1.05
1.44
2.09
1.13
1.33
0.58
0.94
2.55
6.09
1.09
1.32
1.94
Mercury
Content
(Ibs/Tbtu)
5.97
7.93
4.09
5.56
6.90
8.16
7.32
7.82
15.62
11.33
5.91
4.24
4.53
12.44
5.27
8.30
4.60
8.65
18.70
18.54
13.93
26.07
17.95
21.54
8.40
8.56
7.53
12.44
3.78
8.43
14.65
14.88
30.23
4.37
9.20
4.61
5.67
8.40
1.82
4.33
5.61
6.44
10.28
8.82
5.75
8.09
8.80
Ash Content
(Ibs/MMBtu)
7.45
7.71
8.47
6.19
8.01
10.21
17.15
9.53
11.70
11.69
9.46
3.98
10.13
21.51
7.86
12.85
14.51
23.97
7.08
8.00
9.13
13.54
9.23
9.59
5.37
6.48
11.57
21.51
10.35
6.47
25.65
25.51
23.95
7.39
7.41
6.97
7.97
8.05
5.58
10.02
5.47
6.50
7.89
9.62
9.15
9.25
9.89
HCI Content
(Ibs/MMBtu)
0.087
0.076
0.133
0.280
0.097
0.053
0.014
0.029
0.072
0.019
0.023
0.007
0.006
0.018
0.067
0.014
0.014
0.008
0.075
0.071
0.058
0.051
0.096
0.092
0.090
0.059
0.014
0.018
0.083
0.043
0.020
0.036
0.011
0.015
0.095
0.054
0.028
0.028
0.005
0.008
0.010
0.012
0.092
0.045
0.091
0.098
0.102
CO2 Content
(Ibs/MMBtu)
206.4
206.4
202.8
203.1
203.1
203.1
212.6
204.7
204.7
219.3
202.8
215.5
215.5
212.6
215.5
219.3
209.2
209.2
204.7
204.7
204.7
202.8
204.7
204.7
204.7
204.7
219.3
215.3
206.4
206.4
212.6
212.6
212.6
209.6
209.6
206.4
206.4
206.4
214.3
214.3
214.3
214.3
204.7
204.7
206.4
206.4
206.4
9-14
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9.1.5 Coal Grade Assignments
The grades of coal that may be used by specific generating units were determined by an expert
assessment of the ranks of coal that a unit had used in the past, the removal efficiency of the installed
FGD, and the SO2 permit rate of the unit. Examples of the coal grade assignments made for individual
plants in EPA Base Case v.5.13 are shown in Table 9-6. Not all of the coal grades allowed to a plant by
the coal grade assignment are necessarily available in the plant's assigned coal demand region (due to
transportation limitations). IPM endogenously selects the coal burned by a plant by taking into account
both the constraint of the plant's coal grade assignment and the constraint of the coals actually available
within a plant's coal demand region.
Table 9-6 Example of Coal Assignments Made in EPA Base Case
Plant Name
Mt Storm
Mitchell
Scherer
Newton
Weston
Sandow No 4
Monticello
Laramie River Station
Big Cajun 2
W A Parish
Unique ID
3954 B 3
3948 B 1
6257_B_1
6017_B_1
4078 B 4
6648 B 4
6147_B_3
6204_B_3
6055_B_2B1
3470_B_WAP8
SIP SO2
Limit
(Ibs/MMBtu)
0.15
1.2
1.2
0.5
0.1
1.2
1.2
0.2
0.38
0.36
Scrubber?
Yes
Yes
Yes
No
Yes
Yes
Yes
Yes
No
Yes
Fuels Allowed
BA.BB.BD
BA,BB,BD,BE,BG,BH
BA,BB,BD,BE,BG,BH,SA,SB, SD.SE
BA.SA
BA.SA.SB
LA,LD,LE,LG,LH
LA,LD,LE,LG,LH,SA,SB,SD,SE
LA.SA.SB
SA
SA,SB,SD,SE
9.2 Coal Supply Curves
9.2.1 Nature of Supply Curves Developed for EPA Base Case v.5.13
In keeping with IPM's data-driven bottom-up modeling framework, a bottom-up approach (relying heavily
on detailed economic and resource geology data and assessments) was used to prepare the coal supply
curves for EPA Base Case v.5.13. Wood Mackenzie was chosen to develop the curves based on their
extensive experience in preparing mine-by-mine estimates of cash operating costs for operating mines in
the U.S., their access to both public and proprietary data sources, and their active updating of the data
both through research and interviews.
In order to establish consistent nomenclature, Wood Mackenzie first mapped its internal list of coal
regions and qualities to EPA's 36 coal supply regions (described above in sections 0) and 14 coal grades
(described above in section 9.1.3). The combined code list is shown in Table 9-7 below with the IPM
supply regions appearing in the rows and the coal grades in the columns. Wood Mackenzie then created
supply curves for each region and coal-grade combination (indicated by the "x" in Table 9-7) for forecast
years 2016, 2018, 2020, 2025, 2030, 2040, and 2050.
9-15
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Table 9-7 Basin-Level Groupings Used in Preparing v.5.13 Coal Supply Curves
Table 9-7 Basin Level Groupings Used in Preparing v.5.13 Coal Supply Curves
9-16
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9.2.2 Cost Components in the Supply Curves
Costs are represented as total cash costs, which is a combination of a mine's operating cash costs plus
royalty & levies. These costs are estimated on a Free on Board (FOB) basis at the point of sale. Capital
costs (either expansionary or sustaining) are not included in the cash cost estimate. We believe that total
cash cost is the best metric for the supply curves as coal prices tend to be ultimately determined by the
incremental cost of production (i.e. total cash cost).
Operating cash cost
These are the direct operating cash costs and includes, where appropriate, mining, coal preparation,
product transport, and overheads. No capital cost component or depreciation & amortization charge is
included. Operating cash costs consist of the following elements:
Mining costs - Mining costs are the direct cost of mining coal and associated waste material for
surface and underground operations. It includes any other mine site costs, such as ongoing
rehabilitation / reclamation, security, community development costs. It also includes the cost of
transporting raw coal from the mining location to the raw coal stockpile at the coal preparation plant.
Coal preparation - The cost of coal preparation includes raw coal stockpile reclaim, crushing and
screening, washing and marketable coal product stockpiling (if applicable).
Transport - This covers all transport costs of product coal to point of sale. Transport routes with
multiple modes (e.g. truck and rail) are shown as total cost per marketable ton for all stages of the
transport route. Loading charges are included in this cost if relevant.
Overheads - This is any off mine site general and administration overheads that are essential to the
production and sale of a mine's coal product. Examples would be essential corporate management
or a sales and marketing charge.
It is important to note that although the formula for calculating mine costs is consistent across regions,
some tax rates and fees vary by state and mine type. In general, there are two mine types: underground
(deep) or surface mines. Underground mining is categorized as being either a longwall (LW) or a
continuous room-and-pillar mine (CM). Geologic conditions and characteristics of the coal seams
determine which method will be used. Surface mines are typically categorized by the type of mining
equipment used in their operation such as draglines (DL), or truck & shovels (TS). These distinctions are
important because the equipment used by the mine affects productivity measures and ultimately mine
costs. Further information on operating cost methodology and assumptions can be found in Attachment
9-1.
Royalties and Levies
These include, where appropriate, coal royalties, mine safety levies, health levies, industry research
levies and other production taxes.
9.2.3 Procedures Employed in Determining Mining Costs
The total cash costs of mines have been estimated in current year terms using public domain information
including; geological reports, reported statistics on production, labor and input costs, and company
reports. The estimates have been validated by reference to information gained by visits to operations, and
discussions with industry participants.
Because the estimates are based only on public information and analysis, and do not represent private
knowledge of an operation's actual costs, there may be deviations from actual costs. In instances where
confidential information is held by Wood Mackenzie, it has not been used to produce the published
estimates. Several methods are employed for cost estimation depending on the availability of information
and the diversity of mining operations. When possible, Wood Mackenzie analysts developed detailed lists
9-17
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of mine related costs. Costs such as employee wages & benefits, diesel fuel, spare parts, roof bolts and
explosives among a host of others are summed to form a mine's operating cash costs.
Where information is incomplete, cost items are grouped into categories that can be compared with
industry averages by mine type and location. These averages can be adjusted up or down based on new
information or added assumptions. The adjustments take the form of cost multipliers or parameter values.
Specific cost multipliers are developed with the aid of industry experts and proprietary formulas. This
method is at times used to convert materials and supplies, on-site trucking costs and mine and division
overhead categories into unit removal costs by equipment type. To check the accuracy of these cost
estimates, cash flow analysis of publicly traded companies is used. Mine cash-costs are extracted from
corporate cash flows and compared with the initial estimates. Adjustments for discrepancies are made on
a case-by-case basis.
Many of the cost assumptions associated with labor and productivity were taken from the Mine Safety
Health Administration (MSHA) database. All active mines report information specific to production levels,
number of employees and employee hours worked. Wood Mackenzie supplements the basic MSHA data
with information obtained from mine personnel interviews and industry contacts. Phone conversations
and conferences with industry professionals provide additional non-reported information such as work
schedules, equipment types, percentages of washed coal, and trucking distances from the mine to wash-
plants and load-out terminals.
For each active or proposed mine, Wood Mackenzie reports the estimated cost to take coal from the mine
to a logical point-of-sale. The logical point-of-sale may be a truck or railcar load-out or even a barge
facility. This is done to produce a consistent cost comparison between mines. Any transport costs beyond
the point-of-sale terminal are not part of this analysis and are not reflected in the supply curves
themselves.
9.2.4 Procedure Used In Determining Mine Productivity
Projected production and stripping ratios are the key determinants of surface mine productivity. Wood
Mackenzie assumes mining costs increase as stripping ratios increase. The stripping ratio is the quantity
of overburden removed relative to the quantity of coal recovered. Assuming that reserves are developed
where they are easiest to mine and deliver to market, general theory suggests that as the easy reserves
are depleted, greater amounts of overburden must be handled for the same amount of coal production;
thus causing a decrease in mining productivity. However, this productivity loss is often offset by
technology improvements in labor saving equipment.
While an understanding of the forces affecting productivity is important, no attempt is made to develop a
complex algorithm that tries to balance increased stripping ratios with added technology improvements.
Instead, Wood Mackenzie uses reported aggregate productivity (in tons per employee hour) provided by
MSHA as a starting point and divides the production by the productivity calculation to obtain aggregate
employee-hours. Allocating aggregate employee hours among specific mines, production forecasts for
these mines can be converted back into mine-specific productivity forecasts. These forecasts are then
examined on a mine-by-mine basis by an industry expert with region-specific knowledge.
A similar approach is used for underground mines. First, as background, the specific factors affecting
productivity at such mines are identified. For example, underground mines do not have stripping ratios.
Productivity estimates for these mines largely depend on the type of mining technique used (which is a
function of the region's geology). For instance, longwall-mines can produce a high volume of low cost
coal but geologic constraints like small reserve blocks and the occurrence of faulting tends to limit this
technique to certain regions. In addition to geologic constraints, there are many variables that can impact
underground-mine productivity but they are often difficult to quantify and forecast.
9-18
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9.2.5 Procedure to Determine Total Recoverable Reserves by Region and Type
Before mine operators are allowed to mine coal, they must request various permits, conduct
environmental impact studies (EIS) and, in many cases, notify corporate shareholders. In each of these
instances, mine operators are asked to estimate annual production and total recoverable reserves. Wood
Mackenzie uses the mine operators' statements as the starting point for production and reserves
forecasts. If no other material is available, interviews with company personnel will provide an estimate.
Region and coal type determinations for unlisted reserves are based on public information reported for
similarly located mines. Classifying reserves this way means considering not only a mine's geographic
location but also its geologic conditions such as depth and type of overburden and the specific identity of
the coal seam(s) being mined. For areas where public information is not available or is incomplete, Wood
Mackenzie engineers and geologists estimate reserve amounts based on land surveys and reports of
coal depth and seam thickness provided by the U.S. Geologic Service (USGS). This information is then
used to extrapolate reserve estimates from known coal sources to unknown sources. Coal quality
determinations for unknown reserves are assigned in much the same way.
Once a mine becomes active, actual production numbers reported in corporate SEC filings and MSHA
reports are subtracted from the total reserve number to arrive at current reserve amounts. Wood
Mackenzie consistently updates the reserves database when announcements of new or amended
reserves are made public. As a final check, the Wood Mackenzie supply estimates are balanced against
the Demonstrated Reserve Base (DRB)83 estimates to ensure that they do not exceed the DRB
estimates.
9.2.6 New Mine Assumptions
New mines have been included based on information that Wood Mackenzie maintains on each supply
region. They include announced projects, coal lease applications and unassigned reserves reported by
mining companies. Where additional reserves are known to exist, additional incremental steps have been
added and designated with the letter "N" in the "Step Name" field of the supply curves. These incremental
steps were added based on characteristics of the specific region, typical mine size, and cost trends. They
do not necessarily imply a specific mine or mine type.
In the IL basin, there is a significant amount of mine projects announced and/or underway that will be
completed and available by 2016. These "on the way" mines are designated as existing mines in the
"step name" field as they already are, or expected to be, available by the first model run year of 2016.
Wood Mackenzie has also identified technical coal reserves that may be commercial in the longer-term,
but would most likely not be developed until after the completion of mine development already underway
or announced. Therefore, the new mines reflecting these additional reserves are not available until 2018.
9.2.7 Other Notable Procedures
Currency Assumptions
For consistency with the cost basis used in EPA Base Case v.5.13, costs are converted to real 2011$.
Future Cost Adjustments
Changes in mine productivity are a key factor impacting the evolution of costs over time. In general, mine
productivity is expected to continue to decline - in large part due to worsening geology and more difficult
to mine reserves Productivity has declined at -2.7% CAGR from 2000-2011 as shown in Figure 9-2.
83 Posted by the Energy Information Administration (EIA) in its Coal Production Report.
9-19
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Figure 9-2 Coal Mine Productivity (2000-2011)
7 -i
5 6^
o
.c
CD 5 ~
_0
0- A.
E
OJ
S. 3
in
c
5 2
1 -
0
2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Source: U.S. Department of Labor, Mine Safety and Health Administration
Figure 9-3 Average Annual Cost Growth Assumptions by Region
(2012-2050)
2.3 -
I.LJ -
n
.
.
_
s
_
.
:
,
-
..
Figure 9-3 shows the compounded average annual growth rate (CAGR) of mining costs by basin over the
forecast period. It should be noted that cost increases will ultimately be linked to market demand (as
demand grows, the faster the rate of depletion of lower cost reserves). Costs in some supply basins are
expected to increase more quickly than others due to issues such as mining conditions, productivity,
infrastructure limitations, etc. Region-specific information can be found in section 9.2.9.
9-20
-------
Supply Growth Limitations
To the maximum extent possible, the IPM model is set up to determine the optimal volume of coal supply
which can be profitably supplied. For two of the lower cost basins (Powder River and Illinois basins),
maximum production capacities are included as constraints (production ceilings) to more accurately
reflect the upper bound of what could be produced in a given year. Those limits, represented in millions
of tons per year, are shown in Figure 9-4 below. These ceilings are necessary to guard against modeling
excess annual production capacity in certain basins. For instance, in the PRB, several of the "new" mines
reflect expansion mines that would not be developed until the initial mine is further depleted. In this case,
the production ceiling helps safeguard against a modeling scenario that would simultaneously produce
from both of these mines.
Figure 9-4 Maximum Annual Coal Production Capacity
Maximum Thermal Coal Production Capacity per Year (million tons)
ILB
PRB
2016
165.5
509
2018
190
525.5
2020
203.4
552.5
2025
220.1
572.3
2030
239.5
609.5
2040
254.6
609.5
2050
254.6
609.5
9.2.8 Supply Curve Development
The description below describes the development of the coal supply curves. The actual coal supply
curves can be found www.epa.gov/airmarkets/progsregs/epa-ipm/BaseCasev513.html. For illustrative
purposes, there is also an excerpt of the coal supply curves in Table 9-24 of this chapter.
Once costs are estimated for all new or existing mines, they are sorted by cash cost, lowest to highest,
and plotted cumulatively by production to form a supply curve. The supply curve then represents all mines
- new or existing as well as both underground and surface mines- irrespective of market demand. Mines
located toward the bottom of the curve have the lowest cost and are most likely to be developed while the
mines at the top of the curve are higher cost and will likely wait to be developed. The process for
developing a cumulative supply curve is illustrated in Figure 9-5 and Figure 9-6 below.
Figure 9-5 Illustration of Preliminary Step in Developing a Cumulative Coal Supply Curve
Key
E = EXISTING MINE
N = NEW MINE
U = UNDERGROUND MINE
S = SURFACE MINE
New or
Existing?
N
E
N
N
E
N
E
E
E
N
Mine
A
B
C
D
E
F
G
H
I
J
Type
S
U
S
S
S
S
U
U
U
S
Cost
$ 30
I 20
$ 32
$ 36
$ 29
$ 28
$ 25
$ 23
$ 27
$ 35
Production
2
4
1
0.5
2
2.5
5
4
3
0.25
Mine Cost and Production Amts 1Ct)St
140
130
120
110
lllllll
C D E F G H
Mine Names
In the table and graph above, mine costs and production are sorted alphabetically by mine name. To
develop a supply curve from the above table the values must be sorted by mine costs from lowest to
highest. A new column for cumulative production is added, and then a supply curve graph is created
which shows the costs on the 'Y' axis and the cumulative production on the 'X' axis. Notice below that the
9-21
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curve contains all mines - new or existing as well as both underground and surface mines. The resulting
curve is a continuous supply curve but can be modified to show costs as a stepped supply curve. (Supply
curves in stepped format are used in linear programming models like IPM.) See Figure 9-7 for a stepped
version of the supply curve example shown in Figure 9-6. Here each step represents an individual mine,
the width of the step reflects the mine's production, and its height shows the cost of production.
Figure 9-6 Illustration of Final Step in Developing a Cumulative Coal Supply Curve
New 01
Existing? fr"
E
E
E
E
N
E
N
N
N
N
Mine[ฃ
B
H
G
1
F
E
A
C
J
D
Ia>ซIZ
u
u
u
u
s
s
s
s
s
s
Cost(^~
I 20
$ 23
IE 25
IE 27
IE 28
I 29
I 30
I 32
IE 35
I 36
Production fr"
4
4
5
3
2.5
2
2
1
0.25
0.5
Cum
ProductioM
4
8
13
16
18.5
20.5
22.5
23.5
23.75
24.25
Smooth Supply Curve
$40
ฃ? $30 -
f 120
<-> J10
"~"-"*^
*-- *~~
0 5 10 15 20 25
Cumul.itive Production (Tons)
Figure 9-7 Example Coal Supply Curve in Stepped Format
Stepped Supply Curve
Mine
B
IH
O
I
IF
E
A
C
IJ
ID
9 13 17
Cumulative Production
25
MINE NAME
New cr Existing]
E
E
E
E
E
E
E
E
E
E
E
E
E
E
E
N
N
N
E
E
N
N
N
N
N
PRODUCTION AMOUNT
G I F E A C J D
13 16 18.5 20.5 22.5 24 25 25.5
20
20
20
23
23
23
23
25
25
25
25
25
27
27
27
28
23
23
29
29
30
30
35
36
9-22
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9.2.9 EPA Base Case v.5.13 Assumptions and Outlooks for Major Supply Basins
Powder River Basin (PRB)
The PRB is somewhat unique to other US coal basins; in that producers have the ability to add significant
production volumes relatively easily and at a profit. That said, the decisions on production volumes are
largely based on the market conditions, namely the price. For instance, in a low price environment
producers tend to moderate production volumes to maintain attractive prices, and choose to ramp up
production when prices are higher. The evolution of costs in the PRB will be strongly correlated to the
rate at which producers ramp up production at existing mines, which as indicated will depend on market
conditions.
Wood Mackenzie anticipates productivity at most existing PRB mining operations to decline at very
modest rates over the forecast horizon, with increasing strip ratios at least partly offset by improved usage
of labor and capital. As most PRB mines are progressing downward, the ratios of overburden to coal
(strip ratios) will increase in the future. The productivity of new mines will be quite low during the early
stages of their life span.
Mining at several locations is steadily proceeding production westward toward the Joint Line railroad and,
at current and forecasted levels of production, around 2019 several mines are expected to eventually
reach the line. This event will result in a costly movement across the railroad, requiring significant capital
investment and reduced production as the transition is made. During the move across the Joint Line
railroad, strip ratios will spike and productivity will fall as new box cuts are created.
Illinois Basin (ILB)
Production costs in the Illinois basin have been steadily decreasing in recent years as new low cost mines
are opened using more efficient longwall mining techniques. Wood Mackenzie expects that average
costs will continue to decline as additional new mines are developed. However, as new low cost mines
are brought on, higher cost mines will be unable to compete. In the long-term, the shape of the ILB
supply curve is expected to decrease in cost and increase in production capacity.
Given its large scale growth potential, investments in rail infrastructure development will have to keep
pace. While Wood Mackenzie expect there to be some bottlenecks in expanding transportation in the
basin early on, they project that once utilities begin committing to taking ILB coal, railroads will make the
necessary changes to accommodate the change. However, there is a risk that rail infrastructure in the
basin will not be able to keep up with the rate of growth in ILB which could limit the region's otherwise
strong growth potential.
Central Appalachia (CAPP)
Geologic conditions in the CAPP region are challenging, with thin seams and few underground reserves
amenable to more efficient longwall mining techniques. Costs of production in CAPP have risen
substantially in recent years as the region has struggled with mining thinner seams as reserves deplete,
mining accidents have led to increased inspections, and mine permitting has become increasingly difficult
as opposition to surface mining intensifies - with the revocation of some section 404 permits that regulate
the discharge into US waterways. Since surface mining is the lowest cost form of production in CAPP,
reduced growth in surface mining operations is adding to increasing cost in the region
As producers cut back on production over the course of 2012 in order to manage the falling demand,
productivity suffered and production costs per ton in the region rose roughly 10%. In an effort to retain
margins, producers implemented a variety of tactics to try to keep production costs from continuing to
increase; including, shifting more production to lower cost operations and selling lesser quality raw coal to
save on coal preparation/washing costs.
9-23
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Northern Appalachia (NAPP)
Mining cost escalation in NAPP has slowed considerably recently. Future cost for the basin as a whole
will depend largely on the development of new reserve areas.
Northern Appalachia has an estimated 5 billion short tons (Bst) of thermal coal reserves. However, only
about 2.3 Bst is associated with currently operating mines and 90 Mst of that with existing mines that are
idled. Many major producers within the region are within years of depleting currently assigned reserves.
9.3 Coal Transportation
The description below describes the transportation matrix. The actual transportation matrix can be found
www.epa.gov/airmarkets/progsregs/epa-ipm/BaseCasev513.html. For illustrative purposes, there is also
an excerpt of the transportation matrix in Excerpt from Table 9-23 of this chapter.
Within the United States, steam coal for use in coal-fired power plants is shipped via a variety of
transportation modes, including barge, conveyor belt, rail, truck, and lake/ocean vessel. A given coal-fired
plant typically only has access to a few of these transportation options and, in some cases, only has
access to a single type. The number of transportation options that a plant has when soliciting coal
deliveries influences transportation rate levels that plant owners are able to negotiate with transportation
providers.
Within the Eastern United States, rail service is provided predominately by two major rail carriers in the
region, Norfolk Southern (NS) and CSX Transportation (CSX). Within the Western United States, rail
service is also provided predominately by two major rail carriers, Burlington Northern Santa Fe (BNSF)
and Union Pacific (UP). Plants in the Midwestern United States may have access to rail service from
BNSF, CSX, NS, UP, the Canadian National (CN), Canadian Pacific (CP), or short-line railroads. Barge,
truck, and vessel service is provided by multiple firms, and conveyor service is only applicable to coal-
fired plants directly located next to mining operations (e.g., mine-mouth plants).
In recent years, transportation rates for most modes of coal transportation have increased significantly
due to significant increases in input costs (including fuel prices, steel prices and labor costs), as well as a
number of Surface Transportation Board (STB) rail rate case decisions that have allowed higher rail rates
to be charged at plants that are served only by a single railroad.
The transportation methodology and rates presented below reflect expected long-run equilibrium
transportation rates as of March 2012, when the coal transportation rate assumptions for EPA Base Case
v.5.13 were finalized. The forecasted changes in transportation rates during the 2016-2050 forecast
period reflect expected changes in long-term equilibrium transportation rate levels, including the long-term
market dynamics that will drive these pricing levels.
All rates are represented in 2011 real dollars.
9.3.1 Coal Transportation Matrix Overview
Description
In previous versions of EPA Base Case using IPM, the coal transportation matrix connected coal supply
regions with coal demand regions that represented the aggregated coal demand from several coal-fired
generating plants. In EPA Base Case v.5.13, the demand side of the coal transportation matrix has been
expanded, so that each of the approximately 560 U.S. and Canadian coal-fired generating plants included
in EPA Base Case v.5.13 is individually represented in the coal transportation matrix. This allows the
coal transportation routings, coal transportation distances, and coal transportation rates associated with
each individual coal-fired generating plant to be estimated more accurately in EPA Base Case v. 5.13.
9-24
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The coal transportation matrix shows the total coal transportation rate which is expected to be required to
transport coal from selected coal supply regions to each individual coal-fired generating plant.
The coal supply regions associated with each coal-fired generating plant in EPA Base Case v.5.13 are
largely unchanged from previous versions of IPM. The coal supply regions associated with each coal-
fired generating plant are the coal supply regions which were supplying each plant as of late 2011, have
supplied each plant in previous years, or are considered economically and operationally feasible sources
of additional coal supply during the forecast period in EPA Base Case v. 5.13 (2016-2050.) A more
detailed discussion of the coal supply regions can be found in previous sections.
Methodology
Each coal supply region and coal-fired generating plant is connected via a transportation link, which can
include multiple transportation modes. For each transportation link, cost estimates, in terms of $/ton, were
calculated utilizing mode-based transportation cost factors, analysis of the competitive nature of the
moves, and overall distance that the coal type must move over each applicable mode. An example of the
calculation methodology for movements including multiple transportation modes is shown in Figure 9-8.
Figure 9-8 Calculation of Multi-Mode Transportation Costs (Example)
Rail Cost ($/ton) = ^MrranZkiarlrvr^M Bal"9e CฐSt ($/ton) =
Rail Mill Rate (mills/ton-mile) x Rail Wm cogm/ton\ E9 Loadin9 Cost ($/ton) + Bar9e MNI Rate
Mileage B^^^^^^^^^^^BB (mills/ton-mile) x Barge Mileage
9.3.2 Calculation of Coal Transportation Distances
Definition of applicable supply/demand regions
Coal-fired generating plants are linked to coal supply regions based on historical coal deliveries, as well
as based on the potential for new coal supplies to serve each coal-fired generating plant going forward. A
generating plant will almost always have transportation links with more than one supply region, depending
on the various coal types that can be physically delivered and burned at that particular plant. On
average, each coal-fired generating plant represented in IPM is linked with about nine coal supply
regions. Some plants may have more than the average number of transportation links and some may
have fewer, depending on the location of each plant, the transportation modes available to deliver coal to
each plant, the boiler design and emissions control technologies associated with each plant, and other
factors that affect the types of coal that can be burned at each plant.
For "mine-mouth" plants (plants for which the current coal supply is delivered from a single nearby mine,
generally by conveyor belt or using truck transportation) that are 200 MW or larger, Hellerworx and
Tetratech have estimated the cost of constructing facilities that would allow rail delivery of alternative coal
supplies, and the transportation rates associated with the delivery of alternative coal supplies. This
includes the construction of rail spurs (between one and nine miles in length depending on the proximity
of each plant to existing railroad lines) to connect each plant with existing railroad lines.
Transportation Links for Existing Coal-Fired Plants
Transportation routings from particular coal supply regions to particular coal-fired generating plants were
developed based on third-party software84 and other industry knowledge available to Hellerworx and
Tetratech. Origins for each coal supply region were based on significant mines or other significant
84 Rail routing and mileage calculations utilize ALK Technologies PC*Miler software.
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delivery points within the supply region, and the destination points were plant-specific for each coal-fired
generating plant represented in IPM. For routes utilizing multiple modes (e.g. rail-to-barge, truck-to-rail,
etc.), distances were developed separately for each transportation mode.
Transportation Links for New Coal-Fired Plants
Transportation links for new coal-fired plants that were under construction as of March 2012 were
developed using the same methodology as for existing plants, and these committed new plants were
included in IPM as of their expected date of commercial operation.
Coal transportation costs for new coal-fired plants not yet under construction (i.e., coal transportation
costs for new coal plants modeled by IPM) were estimated by selecting an existing coal plant within each
IPM Region whose coal supply alternatives, and coal transportation costs, were considered
representative of the coal supply alternatives and coal transportation costs that would likely be faced by
new coal plants within that same IPM Region. This methodology helps ensure that coal transportation
costs for new coal plants are properly integrated with and assessed fairly vis-a-vis existing coal-fired
assets within the IPM modeling structure.
9.3.3 Overview of Rail Rates
Competition within the railroad industry is limited. Two major railroads in the Western U.S. (BNSF and
UP) and two major railroads in the Eastern U.S. (CSX and NS) currently originate most of the U.S. coal
traffic that moves by rail.
In recent years, railroads have increased coal transportation rates in real terms wherever they have the
opportunity. However, rail rates at plants captive to a single rail carrier are now close to the maximum
levels prescribed by the STB, which limits the potential for further real increases in these rates. Moreover,
as of March 2012, the differential between rates at captive plants and rates at competitively-served plants
was relatively narrow. The current relatively small differentials between captive and competitive rates are
expected to persist over the long-term.
All of the rail rates discussed below include railcar costs, and include fuel surcharges at expected 2012
fuel price levels.
Overview of Rail Competition Definitions
Within the transportation matrix, rail rates are classified as being either captive or competitive (seeTable
9-8), depending on the ability of a given coal demand region to solicit supplies from multiple suppliers.
Competitive rail rates are further subdivided into high- and low-cost competitive subcategories.
Competition levels are affected both by the ability to take delivery of coal supplies from multiple rail
carriers, the use of multiple rail carriers to deliver coal from a single source (e.g., BNSF/UP transfer to
NS/CSX for PRB coal moving east), or the option to take delivery of coal via alternative transportation
modes (e.g., barge, truck or vessel).
Table 9-8 Rail Competition Definitions
Competition Type
Captive
High-Cost Competitive
Low-Cost Competitive
Definition
Demand source can only access coal supplies through a single provider; demand source
has limited power when negotiating rates with railroads.
Demand source has some, albeit still limited, negotiating power with rail providers;
definition typically applies to demand sources that have the option of taking delivery from
either of the two major railroads in the region.
Demand source has a strong position when negotiating with railroads; typically, these
demand sources also have the option of taking coal supplies via modes other than rail
(e.g., barge, truck, or lake/ocean vessel).
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Rail Rates
As previously discussed, rail rates are subdivided into three competitive categories: captive, high-cost
competitive, and low-cost competitive. Moves are further subdivided based on the distance that the coal
supply must move over rail lines: <200 miles, 200-299 miles, 300-399 miles, 400-649 miles, and 650+
miles. Within the Western U.S., mileages are only subdivided into two categories (<300 miles and 300+
miles), given the longer distances that these coal supplies typically move.
Initial rate level assumptions were determined based on an analysis of recent rate movements, current
rate levels in relation to maximum limits prescribed by the STB, expected coal demand, diesel prices,
recent capital expenditures by railroads, and projected productivity improvements. In general, shorter
moves result in higher applicable rail rates due to the lesser distance over which fixed costs can be
spread. As previously discussed, rail rates reflect anticipated 2012 costs in 2011 real dollars.
Rates Applicable to Eastern Moves
Rail movements within the Eastern U.S. are handled predominately by the region's two major carriers, NS
and CSX. Some short movements are handled by a variety of short-line railroads. Most plants in the
Eastern U.S. are served solely by a single railroad (i.e., they are captive plants). The practical effect of
this is that CSX and NS do not compete aggressively at the limited number of plants that have access to
both major railroads, and the rates for high-cost competitive plants tend to be similar to the rates for
captive plants. Table 9-9 presents the 2012 eastern rail rates.
Table 9-9 Assumed Eastern Rail Rates for 2012
(2011 mills/ton-mile)
Mileage Block
<200
200-299
300-399
400-649
650+
Captive
85
71
69
61
43
High-Cost Competitive
85
71
69
61
43
Low-Cost Competitive
72
60
59
52
37
Rates Applicable to Midwestern Moves
Plants in the Midwestern U. S. may be served by BNSF, CN, CP, CSX, NS, UP or short-line railroads.
However, the rail network in the Midwestern U.S. is very complex, and most plants are served by only one
of these railroads. The Midwestern U.S. also includes a higher proportion of barge-served and truck-
served plants than is the case in the Eastern or Western U.S. Table 9-10 depicts 2012 rail rates in the
Midwest.
Table 9-10 Assumed Midwestern Rail Rates for 2012
(2011 mills/ton-mile)
Mileage Block
<200
200-299
300-399
400-649
650+
Captive
85
67
49
46
43
High-Cost Competitive
85
67
49
46
43
Low-Cost Competitive
72
57
42
39
37
Rates Applicable to Western Moves
Rail moves within the Western U.S. are handled predominately by BNSF and UP. Due to industry
concerns about potential future regulation of carbon dioxide (CO2) emissions and other factors, it now
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appears very unlikely that the CP will construct a third rail line into the PRB, so this analysis assumes the
PRB will continue to be served only by BNSF and UP. Rates for Western coal shipments from the PRB
are forecast separately from rates for Western coal shipments from regions other than the PRB. This
reflects the fact that in many cases coal shipments from the PRB are subject to competition between
BNSF and UP , while rail movements of Western coal from regions other than the PRB consist primarily
of Colorado and Utah coal shipments that originate on UP, and New Mexico coal shipments that originate
on BNSF. PRB coal shipments also typically involve longer trains moving over longer average distances
than coal shipments from the other Western U.S. coal supply regions, which means these shipments
typically have lower costs per ton-mile than non-PRB coal shipments. In the west, there are enough
plants that have access to both BNSF and UP or a neutral carrier that the western railroads are
concerned of losing coal volume to the competing railroad, and do offer more of a rate discount to plants
that can access both railroads (e.g., high-cost competitive).
Non-PRB Coal Moves
The assumed non-PRB western rail rates for 2012 are shown in Table 9-11.
Table 9-11 Assumed Non-PRB Western Rail Rates for 2012
(2011 mills/ton-mile)
Mileage Block
<300
300+
Captive
53
28
High-Cost Competitive
45
25
Low-Cost Competitive
45
25
The assumed PRB western rail rates for 2012 are available in Table 9-12.
PRB Moves Confined to BNSF/UP Rail Lines
Table 9-12 Assumed PRB Western Rail Rates for 2012
(2011 mills/ton-mile)
Mileage Block
<300
300+
Captive
32
26
High-Cost Competitive
27
23
Low-Cost Competitive
27
23
PRB Moves Transferring to Eastern Railroads
For PRB coal moving west-to-east, the coal transportation matrix assumes that the applicable low-cost
competitive assumption is applied to the BNSF/UP portion of the rail mileage, and an assumption of either
$2.20 per ton or 41 mills per ton-mile (whichever is higher) is applied to the portion of the movement that
occurs on railroads other than BNSF and UP. (The $2.16 per ton assumption is a minimum rate for short-
distance movements of PRB coal on Eastern railroads.)
9.3.4 Truck Rates
Truck rates include loading and transport components, and all trucking flows are considered competitive
because highway access is open to any trucking firm. The truck rates shown in Table 9-13 are expected
long-term equilibrium levels reflective of current rates as of March 2012, and expected changes in labor
costs, fuel prices, and steel prices.
Table 9-13 Assumed Truck Rates for 2012
(2011 Real Dollars)
Market
All Markets
Loading Cost ($/ton)
1.00
Transport (mills/ton-mile)
120
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9.3.5 Barge and Lake Vessel Rates
As with truck rates, barge rates include loading and transport components, and all flows are considered
competitive because river access is open to all barge firms. The transportation matrix subdivides barge
moves into three categories, which are based on the direction of the movement (upstream vs.
downstream) and the size of barges that can be utilized on a given river. As with the other types of
transportation rates forecast in this analysis, the barge rate levels shown in Table 9-14 are expected long-
term equilibrium levels reflective of current rates as of March 2012, and expected changes in labor costs,
fuel prices, and steel prices.
Table 9-14 Assumed Barge Rates for 2012
(2011 Real Dollars)
Type of Barge Movement
Upper Mississippi River, and Downstream on the Ohio River System
Upstream on the Ohio River System
Lower Mississippi River
Loading Cost
($/ton)
2.70
2.45
2.70
Transport
(mills/ton-mile)
9.7
11.5
6.9
Notes:
1. The Upper Mississippi River is the portion of the Mississippi River north of St. Louis.
2. The Ohio River System includes the Ohio, Big Sandy, Kanawha, Allegheny, and Monongahela Rivers.
3. The Lower Mississippi River is the portion of the Mississippi River south of St. Louis.
Rates for transportation of coal by lake vessel on the Great Lakes were forecast on a plant-specific basis,
taking into account the lake vessel distances applicable to each movement, the expected backhaul
economics applicable to each movement (if any), and the expected changes in labor costs and fuel and
steel prices over the long-term.
9.3.6 Transportation Rates for Imported Coal
Transportation rates for imported coal reflect expectations regarding the long-term equilibrium level for
ocean vessel rates, taking into account expected long-run equilibrium levels for fuel and steel prices, and
expected continued strong demand for shipment of dry bulk commodities (especially coal and iron ore)
from China and other Asian nations.
In EPA Base Case v.5.13, it is assumed that imported coal is likely to be used only at plants that can
receive this coal by direct water delivery (i.e., via ocean vessel or barge delivery to the plant). This is
based on an assessment of recent transportation market dynamics, which suggests that railroads are
unlikely to quote rail rates that will allow imported coal to be cost-competitive at rail-served plants.
Moreover, import rates are higher for the Alabama and Florida plants than for New England plants
because many of the Alabama and Florida plants are barge-served (which requires the coal to be
transloaded from ocean vessel to barge at an ocean terminal, and then moved by barge to the plant),
whereas most of the New England plants can take imported coal directly by vessel. The assumed costs
are summarized in
Excerpt from Table 9-23.
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9.3.7 Other Transportation Costs
In addition to the transportation rates already discussed, the transportation matrix assumes various other
rates that are applied on a case-by-case basis, depending on the logistical nature of a move. These
charges apply when coal must be moved between different transportation modes (e.g., rail-to-barge or
truck-to-barge) - see Table 9-15.
Table 9-15 Assumed Other Transportation Rates for 2012
(2011 Real Dollars)
Type of Transportation
Rail-to-Barge Transfer
Rail-to-Vessel Transfer
Truck-to-Barge Transfer
Rail Switching Charge for Short line
Conveyor
Rate ($/ton)
1.50
2.00
2.00
2.00
1.00
9.3.8 Long-Term Escalation of Transportation Rates
Overview of Market Drivers
According to data published by the Association of American Railroads (AAR), labor costs accounted for
about 33% of the rail industry's operating costs in 2010, and fuel accounted for an additional 18%. The
remaining 49% of the rail industry's costs relate primarily to locomotive and railcar ownership and
maintenance, and track construction and maintenance.
QC
The RCAF Unadjusted for Productivity (RCAF-U), which tracks operating expenses for the rail industry,
increased at an annualized rate of 3.3%/year between the second quarter of 2008 and the fourth quarter
of 2011, see Table 9-9, more than double the increase of 1.5%/year in general inflation (GDP-IPD) over
the same period. This is largely the result of unusually steep increases in labor costs, which reflected the
effect of new labor agreements negotiated prior to the economic downturn that occurred in late 2008 and
2009. Hellerworx expects that going forward, the rail industry's labor costs will increase at a more
moderate rate (assumed to be 1% more than overall inflation), which is more in line with longer-term
historical increases in these costs.
According to data from the AAR, the net change in the rail industry's fuel costs between 2Q2008 and
4Q2011 was a nominal decline of about 9% (or an annualized decline of about 2.6% per year. Over the
same time period, equipment and other costs for the rail industry increased by an average of about 2.0%
per year, only slightly faster than overall inflation of 1.5% per year.
85
The Rail Cost Adjustment Factor (RCAF) refers to several indices created for regulatory purposes by
the STB, calculated by the AAR, and submitted to the STB for approval. The indices are intended to serve
as measures of the rate of inflation in rail inputs. The meaning of various RCAF acronyms that appear in
this section can be found in the insert in
Figure 9-9.
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Figure 9-9 Rail Cost Indices Performance
(2Q2008-4Q2011)
1.400
Performance of Rail Cost Indices, 2Q2008-4Q2011
(annualized nominal S change)
RCAF-U RCAF-A
All-LF
-GDP-IPD
RCAF-U Labor Component
The other major transportation modes used to ship coal (barge and truck) have cost drivers broadly
similar to those for rail transportation (labor costs, fuel costs, and equipment costs). However, a
significant difference in cost drivers between the transportation modes relates to the relative weighting of
fuel costs for the different transportation modes. Estimates as shown in Figure 9-10 show that, at 2012
fuel prices, fuel costs accounted for about 20% of long-run marginal costs for the rail industry, 35% of
long-run marginal costs for barges, and 50% of long-run marginal costs for trucks.
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Figure 9-10 Long-Run Marginal Cost Breakdown by Transportation Mode
Rail
Barge
Truck
Fuel
n Other
9.3.9 Market Drivers Moving Forward
Diesel Fuel Prices
The Energy Information Administration's (ElA's) Annual Energy Outlook (AEO)86 forecast of long-term
equilibrium prices fordiesel fuel used in the transportation sector (see Table 9-16) shows expected prices
ranging from about $3.83/gallon in 2012 to about $4.58/gallon in 2035 (2011 real dollars). This represents
an annual real increase in diesel fuel prices of about 0.8%/year during 2012-2035. The coal
transportation rate forecast for EPA Base Case v.5.13 assumes that this average rate of increase in
diesel fuel prices will apply over EPA's entire forecast period (2016-2050).
Table 9-16 EIA AEO Diesel Fuel Forecast, 2012-2030
(2011 Real Dollars)
Year
Annualized
2012
2015
2020
2025
2030
2035
% Change, 2025-2035
Rate ($/gallon)
3.83
3.84
4.06
4.27
4.48
4.58
0.8%
Source: EIA
As noted at the beginning of this section, the coal transportation rate assumptions for EPA Base Case v5.13 were
finalized in March 2012. At that time, the Annual Energy Outlook 2012 forecast was the latest available.
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Iron Ore Prices
ABARES's87 forecast of iron ore prices as depicted in Table 9-17 shows an expectation that iron ore
prices will decline by about 22% in real terms for their 5-year forecast period (2012-2017) as a whole.
Table 9-17 ABARES Forecast of Iron Ore Prices
ABARE Forecast of Average Contract Price for Australian Iron Ore Exports, 2012
ABARE Forecast for 201 3
ABARE Forecast for 2014
ABARE Forecast for 201 5
ABARE Forecast for 2016
ABARE Forecast for 201 7
Total Percent Change (2012-2017)
2011 US$/metric tonne
137
129
125
121
115
107
-22%
Source: ABARES, Resources and Energy Quarterly, March 2012.
Labor Costs
As noted earlier, labor costs for the rail industry are expected to increase approximately 1% faster than
overall inflation, on average over the forecast period. Due to the fact that competition is stronger in the
barge and trucking industries than in the rail industry, labor costs in the barge and truck industries are
expected to increase at approximately the same rate as overall inflation, on average over the forecast
period.
Productivity Gains
The most recent data published by AAR (covering 2006-2010) shows that rail industry productivity
increased at an annualized rate of approximately 0.8% per year during this period. However, due to
limited competition in the rail industry, these productivity gains were generally not passed through to
shippers. In addition, the potential for significant productivity gains in the trucking industry is relatively
limited since truck load sizes, operating speeds, and truck driver hours are all regulated by law. Although
increased lock outages and the associated congestion on the inland waterway system as the river
infrastructure ages may reduce the rate of future productivity gains in the barge industry, limited
productivity gains are expected to occur, and these productivity gains are expected to be largely passed
through to shippers since the barge industry is highly competitive.
Long-Term Escalation of Coal Transportation Rates
Based on the foregoing discussion, rail rates are expected to escalate at an average rate of 0.5% per
year in real terms during 2013-2050. Over the same period, barge and lake vessel rates are expected to
decline at an average rate of 0.2% per year, which reflects some pass-through of productivity gains in
those highly competitive industries. Truck rates are expected to escalate at an average rate of 0.4%/year
during 2013-2050, rates for conveyor transportation and transloading services are expected to be flat in
real terms, on average over the forecast period.
The basis for these forecasts is summarized in
Table 9-18.
87 ABARES (the Australian Bureau of Agricultural and Resource Economics and Sciences) is a branch of the
Australian government that forecasts prices and trade volumes for a wide variety of commodities that Australia
exports. Australia is a major exporter of iron ore, accounting for about 41% of total worldwide iron ore exports in
2011. Seewww.daff.gov.au/abares.
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Mode
Rail
Barge & Vessel
Truck
Conveyor
Transloading
Terminals
Component
Fuel
Labor
Equipment
Total
Fuel
Labor& Equip.
Total
Fuel
Labor & Equip.
Total
Total
Total
Component
Weighting
20%
35%
45%
100%
35%
65%
100%
50%
50%
100%
Real
Escalation
Before
Productivity
Adjustment
(%/year)
0.8%
1.0%
0.0%
0.5%
0.8%
0.0%
0.3%
0.8%
0.0%
0.4%
0.0%
0.0%
Productivity
Gains Passed
Through to
Shippers
(Wyear)
0.0%
0.5%
0.0%
0.0%
0.0%
Real
Escalation
After
Productivity
Adjustment
(%/year)
0.5%
-0.2%
0.4%
0.0%
0.0%
Table 9-18 Summary of Expected Escalation for Coal Transportation Rates, 2013-2050
9.3.10 Other Considerations
Estimated Construction Costs for Railcar Unloaders and Rail Spurs at Mine-Mouth Plants
In order to allow mine-mouth generating plants (i.e., coal-fired generating plants which take all of their
current coal supply from a single nearby mine) to access additional types of coal, the costs of
constructing facilities that would allow rail delivery of coal was estimated for almost all88 of the mine-
mouth generating plants with total capacity of 200 MW or more.
The facilities needed for rail delivery of coal to generating plants of this relatively large size were assumed
to be: a) a rotary dump railcar unloader capable of handling unit train coal shipments, which is estimated
to cost about $25 million installed (in 2011$). b) at least three miles of loop track, which would allow for
one trainload of coal to be unloaded, and a second trainload of coal to simultaneously be parked on the
plant site preparatory to unloading, and c) at least one mile of additional rail spur track to connect the
trackage on the plant site with the nearest railroad main line. Since construction costs for rail trackage
capable of handling coal trains is estimated at about $3 million per mile (in 2011 $), the minimum
investment required to construct the facilities needed for rail delivery of coal was estimated at $37 million.
In some cases, the length of the rail spur required to reach the nearest main line (which was estimated on
a plant-specific basis) is considerably longer than one mile. In cases where a rail spur longer than one
mile was required to reach the main line, the cost of the additional trackage was estimated using the
same construction cost of $3 million per mile (2011$) referenced earlier.
The costs of rail coal delivery were not estimated for mine-mouth plants located in the Powder River Basin or
Illinois Basin coal fields, since the coal reserves in these coal fields are among the largest, and among the cheapest
to mine, anywhere in the United States.
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The total cost of the facilities required for rail delivery of coal was converted to an annualized basis based
on each plant's historical average coal burn from 2007-2011, and a capital recovery factor of 11.29%.
The cost of transporting additional types of coal to each mine-mouth generating plant was then calculated
using the same methodology described earlier in this section, and added to the annualized cost for the
rail delivery facilities, to arrive at an estimated "all-in" cost for delivering additional types of coal to the
mine-mouth plants.
9.4 Coal Exports, Imports, and Non-Electric Sectors Demand
The coal supply curves used in EPA Base Case v.5.13 represent the total steam coal supply in the United
States. While the U.S. power sector is the largest consumer of native coal - roughly 93% of mined U.S.
coal in 2012 was used in electricity generation - non-electricity demand must also be taken into
consideration in IPM modeling in order to determine the market clearing price. Furthermore, some coal
mined within the U.S. is exported out of the domestic market, and some foreign coal is imported for use in
electricity generation, and these changes in the coal supply must also be detailed in the modeling of the
coal supply available to coal power plants. The projections for imports, exports, non-electric sector coal
demand, and coal to liquids demand are based on ElA's AEO 2013.
In EPA Base Case v.5.13, coal exports, coal-serving residential, commercial and industrial demand, and
coal to liquids demand are designed to correspond as closely as possible to the projections in AEO 2013
both in terms of the coal supply regions and coal grades that meet this demand. The projections used
exclude exports to Canada, as the Canadian market is modeled endogenously within IPM. First, the
subset of coal supply regions and coal grades in EPA Base Case v.5.13 are identified that are contained
in or overlap geographically with those in EIA Coal Market Module (CMM) supply regions and coal grades
that are projected as serving exports and non-electric sector demand in AEO 2013. Next, coal for exports
and non-electricity demand are constrained by CMM supply region and coal grade to meet the levels
projected in AEO 2013. These levels are shown in Table 9-19.
Table 9-19 Coal Exports
Name
Alaska/Washington - Subbituminous Low Sulfur
Central Appalachia - Bituminous Medium Sulfur
East Interior - Bituminous High Sulfur
Northern Appalachia - Bituminous High Sulfur
Northern Appalachia - Bituminous Medium Sulfur
Rocky Mountain - Bituminous Low Sulfur
Western Montana - Subbituminous Low Sulfur
Wyoming Southern PRB - Subbituminous Low Sulfur
2016
1.37
9.33
16.54
4.18
0.44
3.21
8.22
0.42
2018
1.44
9.08
18.23
4.15
0.32
3.54
9.07
0.31
2020
1.52
8.78
20.10
4.07
0.23
3.90
4.85
6.21
2025
1.71
7.58
25.65
3.58
0.10
3.92
12.83
0.10
2030
2.04
7.73
32.74
3.65
0.10
4.73
16.49
0.10
2040-2050
2.84
6.33
45.51
2.98
0.10
4.45
27.28
0.10
Table 9-20 and Table 9-21. (Since the AEO 2013 time horizon extends to 2040 and EPA Base Case
v.5.13 to 2050, the AEO projected levels for 2040 are maintained through 2050.). IPM then endogenously
determines which IPM coal supply region(s) and coal grade(s) will be selected to meet the required export
or non-electric sector coal demand as part of the cost-minimization coal market equilibrium. Since there
are more coal supply regions and coal grades in EPA Base Case v.5.13 than in AEO 2013, the specific
regions and coal grades that serve export and non-electric sector demand are not pre-specified but
modeled.
Table 9-20 Residential, Commercial, and Industrial Demand
Name
Alaska/Washington
Central Appalachia
Central Appalachia
- Subbituminous Low Sulfur
- Bituminous Low Sulfur
- Bituminous Medium Sulfur
2016
0.59
4.02
11.68
2018
0.59
4.03
11.68
2020
0.59
4.05
11.75
2025
0.59
4.08
11.82
2030
0.59
4.08
11.83
2040-2050
0.60
4.28
12.41
9-35
-------
Name
East Interior - Bituminous High Sulfur
East Interior - Bituminous Medium Sulfur
Northern Appalachia - Bituminous High Sulfur
Northern Appalachia - Bituminous Medium Sulfur
Rocky Mountain - Bituminous Low Sulfur
Southern Appalachia - Bituminous Low Sulfur
Southern Appalachia - Bituminous Medium Sulfur
Wyoming Southern PRB - Subbituminous Low Sulfur
Dakota Lignite - Lignite Medium Sulfur
Wyoming Northern PRB - Subbituminous Low Sulfur
West Interior - Bituminous High Sulfur
Arizona/New Mexico - Bituminous Low Sulfur
Arizona/New Mexico - Subbituminous Medium Sulfur
Western Wyoming - Subbituminous Low Sulfur
Western Wyoming - Subbituminous Medium Sulfur
Gulf Lignite - Lignite High Sulfur
2016
7.04
0.82
1.63
3.04
4.05
0.17
1.13
2.58
6.37
5.04
0.67
0.46
0.11
1.03
1.12
0.84
2018
7.00
0.83
1.62
3.05
4.06
0.17
1.13
2.56
6.34
5.04
0.67
0.47
0.11
1.03
1.13
0.85
2020
7.00
0.83
1.62
3.06
4.08
0.17
1.14
2.56
6.34
5.06
0.68
0.47
0.11
1.04
1.13
0.85
2025
6.97
0.83
1.62
3.08
4.10
0.17
1.15
2.55
6.31
5.09
0.69
0.47
0.11
1.04
1.14
0.87
2030
6.89
0.83
1.61
3.08
4.10
0.18
1.16
2.52
6.25
5.09
0.69
0.47
0.12
1.05
1.15
0.87
2040-2050
7.04
0.85
1.66
3.24
4.36
0.19
1.24
2.58
6.38
5.31
0.74
0.50
0.12
1.12
1.24
0.93
Table 9-21 Coal to Liquids Demand
Name
Rocky Mountain - Bituminous Low Sulfur
Wyoming Southern PRB - Subbituminous Low Sulfur
Wyoming Northern PRB - Subbituminous Low Sulfur
Western Montana - Subbituminous Low Sulfur
2016
0
0
0
0
2018
0
0
0
0
2020
0
0
0
0
2025
5.61
0.00
0.42
0.00
2030
3.36
0.00
5.49
0.00
2040-2050
4.02
8.94
0.00
1.36
Imported coal is only available to 39 coal facilities which are eligible to receive imported coal. These
facilities which may receive imported coal, along with the cost of transporting this coal to the demand
regions, are in Excerpt from
Excerpt from Table 9-23. The total US imports of steam coal are limited to AEO 2013 projections as
shown in Table 9-22.
Table 9-22 Coal Import Limits
Annual Coal Imports Cap (Million Short Tons)
2016
1.50
2018
0
2020
0
2025
3.60
2030
3.78
2040-2050
34.28
9-36
-------
Attachment 9-1 Mining Cost Estimation Methodology and Assumptions
Labor Costs
Productivity and labor cost rates are utilized to estimate the total labor cost associated with the mining
operation. This excludes labor involved in any coal processing / preparation plant.
Labor productivity is used to calculate mine labor and salaries by applying an average cost per employee
hour to the labor productivity figure reported by MSHA or estimated based on comparable mines.
Labor costs rates are estimated based on employment data reported to MSHA. MSHA data provides
employment numbers, employee hours worked and tons of coal produced. These data are combined with
labor rate estimates from various sources such as union contracts, census data and other sources such
as state employment websites to determine a cost per ton for mine labor. Hourly labor costs vary between
United Mine Workers of America (UMWA) and non-union mines, and include benefits and payroll taxes.
Employees assigned to preparation plants, surface activities, and offices are excluded from this category
and are accounted for under coal washing costs and mine overhead.
Surface Mining
The prime (raw coal) strip ratio and overburden volume is estimated on a year by year basis. Estimates
are entered of the amount of overburden89 moved each year, split by method to allow for different unit
mining costs. The unit rate cost for each method excludes any drill and blast costs, and labor costs, as
these are accounted for separately. Drill and blast costs are estimated as an average cost per volume of
prime overburden. If applicable, dragline re-handle is estimated separately and a summation gives the
total overburden moved.
The different overburden removal methods are:
Dragline - the estimated volume of prime overburden moved
Dragline re-handle - the estimated volume of any re-handled overburden
Truck and shovel - including excavators.
Other - examples would be dozer push, front end loader, or cast blasting. If overburden is moved by
cast blasting the unit rate is taken to be zero as the cost is already included in the drill and blast
estimate.
Surface mining costs also include the cost of coal mining estimated on a raw ton basis.
Underground Mining
Raw coal production is split by type into either continuous miner or longwall. Cost estimates can be input
either on a unit rate or a fixed dollar amount, as the cost structure of underground mining generally has a
large fixed component from year to year. Costs are divided into:
Longwall
Continuous miner
Underground services
Underground services costs cover categories such as ventilation, conveyor transport, gas drainage,
secondary roof support etc.
Overburden refers to the surface soil and rock that must be removed to uncover the coal.
9-37
-------
Mine Site Other
This covers any mine site costs that are outside the direct production process. Examples are ongoing
rehabilitation/reclamation, security, community development costs.
Raw Haul
Costs for transporting raw coal from the mining location to the raw coal stockpile at the coal preparation
plant or rail load out. A distance and a unit rate allows for an increasing cost over time if required.
Excerpt from Table 9-23 Coal Transportation Matrix in EPA Base Case v.5.13
This is a small excerpt of the data in Table 9-23. The complete data set in spreadsheet format can be
downloaded via the link found atwww.epa.gov/airmarkets/progsregs/epa-ipm/BaseCasev513.html
Link
#
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
Plant Name
Aurora Energy LLC Chena
Eielson AFB Central Heat &
Power Plant
Healy
Barry
Barry
Barry
Barry
Barry
Barry
Barry
Barry
Barry
Barry
Barry
Barry
Barry
Charles R Lowman
Charles R Lowman
Charles R Lowman
Charles R Lowman
ORIS
Plant
Code
79
50392
6288
3
3
3
3
3
3
3
3
3
3
3
3
3
56
56
56
56
Coal
Supply
Region
Code
AK
AK
AK
CG
CR
CU
IL
IN
KE
KW
PW
WH
WL
WN
WS
11
CG
CR
CU
IL
Coal Supply Region
Description
Alaska
Alaska
Alaska
Colorado, Green River
Colorado, Raton
Colorado, Uinta
Illinois
Indiana
Kentucky East
Kentucky West
Pennsylvania, West
Wyoming, Powder River Basin
(8800)
Wyoming, Powder River Basin
(8400)
West Virginia, North
West Virginia, South
lmports-1 (Colombia)
Colorado, Green River
Colorado, Raton
Colorado, Uinta
Illinois
Total Cost
(20 12 Rate in
2011$/Ton)
$3.52
$4.32
$1.00
$44.85
$42.85
$48.85
$20.50
$24.00
$26.04
$19.78
$25.77
$43.13
$42.90
$23.04
$27.45
$14.75
$45.25
$43.25
$49.25
$20.90
Escalation/Year
(2013-2025)
1 .0050
1 .0050
1 .0000
1 .0039
1 .0039
1 .0040
1.0031
1 .0034
1.0031
1.0031
1 .0028
1 .0039
1 .0039
1 .0028
1.0031
0.9995
1 .0039
1 .0039
1 .0040
1.0031
Escalation/Year
(2026-2050)
1 .0050
1 .0050
1 .0000
1 .0039
1 .0039
1 .0040
1.0031
1 .0034
1.0031
1.0031
1.0028
1 .0039
1 .0039
1.0028
1.0031
0.9995
1 .0039
1 .0039
1 .0040
1.0031
Table 9-24 Coal Supply Curves in EPA Base Case v.5.13
This is a small excerpt of the data and graphs in Table 9-24. The complete data set in spreadsheet
format can be downloaded via the link found at www.epa.gov/airmarkets/progsregs/epa-
ipm/BaseCasev513.html.
Year
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
Coal Supply
Region
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
Coal
Grade
BB
BB
BB
BB
BB
BB
BB
BB
BB
BE
Step
Name
E1
E2
E3
E4
E5
E6
E7
E8
N1
E1
Heat Content
(MMBtu/short ton)
25.5
25.5
25.5
25.5
25.5
25.5
25.5
25.5
25.5
24
Cost of Production
(2011$/shortton)
47.51
75.16
81.84
88.23
96.45
101.89
103.68
110.04
115.74
35.96
Coal Production (Million
short tons per annum)
0.09
0.06
1.18
0.14
0.47
0.07
0.10
0.08
0.12
0.21
End 2015 Coal Reserves
(Million short tons)
0.19
0.30
8.37
1.39
4.51
0.69
0.94
0.75
500.00
0.36
9-38
-------
Year
2016
2016
2016
2016
2016
2016
2016
2016
Coal Supply
Region
AL
AL
AL
AL
AL
AL
AL
AL
Coal
Grade
BE
BE
BE
BE
BE
BE
BE
BE
Step
Name
E2
E3
E4
E5
E6
E7
E8
N1
Heat Content
(MMBtu/short ton)
24
24
24
24
24
24
24
24
Cost of Production
(2011$/shortton)
47.51
52.89
71.05
90.23
102.49
104.83
137.98
108.27
Coal Production (Million
short tons per annum)
0.30
3.41
0.38
2.20
2.64
0.30
0.09
0.28
End 2015 Coal Reserves
(Million short tons)
0.37
13.66
1.87
18.68
25.32
2.80
0.90
500.00
9-39
-------
10. Natural Gas
This chapter describes how natural gas supply, demand, and costing are modeled in EPA Base Case
v.5.13. Section 0 indicates that natural gas supply dynamics are directly (i.e., endogenously) modeled in
the base case. Section 10.2 gives an overview of the new natural gas module. Sections 10.3 and 10.4
describe the very detailed process-engineering model and data sources used to characterize North
American conventional and unconventional natural gas resources and reserves and to derive all the cost
components incurred in bringing natural gas from the ground to the pipeline. These sections also discuss
resource constraints affecting production and the assumptions (in the form of cost indices) used to depict
expected changes in costs over the 2016-2050 modeling time horizon.
Section 10.5 describes how liquefied natural gas (LNG) imports are represented in the natural gas
module. The section covers the assumptions regarding liquefaction facilities, LNG supply, regasification
capacity, and related costs. Section 10.6 turns to demand-side issues, in particular, how non-power
sector residential, commercial, and industrial consumer demand is represented. This section also
describes the use of the gas demand sub-module to model LNG exports. Section 10.7 describes the
detailed characterization of the natural gas pipeline network, the pipeline capacity expansion logic, and
the assumptions and procedures used to capture pipeline transportation costs. Section 10.8 treats issues
related to natural gas storage: capacity characterization and expansion logic, injection/withdrawal rates,
and associated costs. Section 10.9 describes the crude oil and natural gas liquids (NGL) price
projections that are exogenous inputs in the natural gas module. They figure in the modeling of natural
gas because they are a source of revenue which influence the exploration and development of
hydrocarbon resources. The chapter concludes in Section 10.10 with a discussion of key gas market
parameters in the natural gas report of EPA Base Case v.5.13.
10.1 Overview of IPM's Natural Gas Module
In EPA Base Case v.5.13 natural gas supply, demand, transportation, storage, and related costs are
modeled directly in IPM through the incorporation of a natural gas module. Natural gas supply curves are
generated endogenously for each region, and the balance between the natural gas supply and demand is
solved in all regions simultaneously. Figure 10-1 and Figure 10-2 illustrate the integration of the natural
gas module in IPM. The integration allows direct interaction between the electric and the gas modules
and captures the overall gas supply and demand dynamic.
To a certain extent, the design and assumptions of the new natural gas module are similar to those in ICF
International's private practice Gas Market Model (GMM) which has been used extensively for forecasting
and market analyses in the North American natural gas market. To provide these new natural gas
modeling capabilities within IPM and still maintain an acceptable model size and solution time, however,
simplifications of some of the GMM design and assumptions were made.
Seasonality in the gas module is made consistent with that in IPM and is currently modeled with two
seasons (summer and winter), each with up to six IPM load periods that correspond to the IPM electric
sector load duration curve (LDC) segments. The gas module also employs a similar run year concept as
in IPM where, in order to manage model size, individual calendar years over the entire modeling period
are mapped to a lesser number of run years. In the current version, both modules use the same run year
mapping.
10-1
-------
Figure 10-1 Modeling and Data Structure in EPA Base Case v.5.13
Emission Control
Technologies
Chapter 5
Sulfur Dioxide
Hydrogen Chlonde
Nitrogen Oxides
Mercury
Carbon Capture and Storage
Particulate Controls
Coal To Gas Conversion
\
CO2 Capture,
Transport, and
Storage
Chapter 6 *
Capture Technologies
Transportation
Storage Regions
\
Set-Up Rules and
Parameters
Chapter 7
Run Years
Aggregation Schemes
Retrofit Assignments
Trading and Banking
Post-2040 Assumptions
Generation Resources
* Chanter 4
Existing EGUST
Planned EGUs f
Potential New EGUs
Future Placeholder Technologies
Conditioned bv
Snort-term Capital Cost Adder
Regional Cos! Adjustments
Capacity Deployment Constraints
Power System Operation
* Chapter 3
Regional Configurations
Capacity. Generation, and Dispatch Assumptions
Transmission Assumptions
Turndown Constraints
Reliability Constraints
Electricity Demand Growth
Environmental Regulations
\
/
^ I
IPM Engineft
Chapter 2
1
Model Outputs
Emissions
Costs
Capacity Expansion and Generation
Retrofit Decisions
Fuel Consumption and Prices
Electncrty Usage and Prices
*
Post-Processor
^^\
Notes
t Information on existing and planned eiectnc generating units (EGUsi is contained in the National Etectncal
Energy Data System (NEEDS) data base maintained for EPA by ICF International Planned EGUs are those
which were under construction a had obtained financing at the time that the EPA Base Case was finalized
Tt IPM Engine is the model structure described in Chapter 2
Financial Assumptions
' Chapter 8
Discount Rate
Capital Charge Rate
Book Life
Capital Cost Adder for Climate Uncertainty
Production Tax Credit
Investment Tax Credit
Parsing
Individual Baler
Outputs
Level Data
Outputs for Air
Quality Modeling
Criteria Ajr Pollutants
Non-criteria Air Pollutants
Tones Air Pollutants
Point Source Locators
Coal & Other Fuel
Assumptions
: Chapter 9 & 11
C 0.1
Fuel Oil
Nuclear Fuel
Biomass
Wasle Fuels
Emission Factors
Natural Gas Module
(Endogenous)
; Chapter 10
Noon American Supply (from GMM
Hydrocarbon Supply Model)
- Reserves and Resources
Production Costs LNG Supply and Costs
Pf>eline Network
Storage
Non-EGU Demand (Residential. Commercial.
Industrial)
Pricing Mechanism
Figure 10-2 Natural Gas Module in EPA Base Case v.5.13
E&D Factors Considered
Location \
Field type. size. & depth
Success rates
Drilling & other costs
O&M Factors Considered
Production costs
Processing plant costs
Lease and plant gas use
Factors Considered
Technology drivers
Improved success rates
Improved recovery per we
Cost reductions (platform, drilling etc
Economic drivers
Oil prices
Labor and materials scarcity
GMM Econometric
Demand Model
on-Electric Sector
Natural
Gas Demand
Sub-Module
Natural Gas
Supply Sub-Module
Residential Commercial
Industrial
Reserves &
Resources
Characterization
Resource
Constraints
Natural Gas
Pipeline
Sub-Module
.,_ Conventional
\ Unconventional
Discovery constraints
Drilling constraints
Base Year
E&D costs
OSM costs
Natural Gas
Storage
Sub-Module
Sub-Module
supply and cost
Regasification capacity and cost
OUTPUTS
Notes
GMM refers to ICF's Gas Market Model
E&D costs = exploration and development costs
O&M costs = operations and maintenance costs
LNG = liquefied natural gas
10-2
-------
10.2 Key Components of the New IPM Natural Gas Module
The gas module is a full supply/demand equilibrium model of the North American gas market. Most of the
structure and data for the gas module are derived from ICF's Gas Market Model (GMM). It consists of
118 supply/demand/storage nodes, 15 LNG regasification (import) facility locations, and 3 LNG export
facility locations that are tied together by a series of links that represent the North American natural gas
transmission network as shown in Figure 10-3. The list of the 118 nodes is tabulated in Table 10-1.
Key elements of the natural gas module (which are described in detail in Sections 10.3-10.9) include:
Natural Gas Resources are modeled by a set of base year resource cost curves, which represent
undiscovered resource availability or recoverable resource as a function of exploration & development
(E&D) cost for 81 supply regions. "Resource Appreciation"90 is added to the resource base to account for
additional resources from plays that are not included in the resource base estimates due to lack of
knowledge and technology to economically recover the resources. The construction of the resource cost
curves are based on resource characterizations and economic evaluations from the Hydrocarbon Supply
Model (HSM) of the GMM. (The HSM is discussed in greater detail in Sections 10.3 and 10.4 below.)
Figure 10-4 depicts the geographic locations of the supply regions and Table 10-2 provides a list of the
supply regions and a mapping of the regions to the modeling nodes.
Natural Gas production from the 81 supply regions is calculated from the resource cost curves based on
exploration and development activities that are a function of drilling success rate, rigs availability,
reserves-to-production (R/P) ratio, and the costs of exploration, reserves development, and production
that are applicable in the specific regions.
LNG import level for each of the LNG regasification facilities is calculated from LNG supply availability
curves (derived from the LNG supply curve module of GMM) based on the solution gas price and the
regasification capacity at the corresponding LNG node. Availability and regasification capacity of the
facilities are specified as inputs. The model has the capability to expand regasification capacity.
However, due to a current excess of LNG regasification capacity and robust natural gas supply in the
U.S. and Canada combined with a relatively low electricity demand growth assumption in the EPA Base
Case v.5.13, the regasification expansion feature is currently turned off. If future economic growth
demands more LNG capacity, it can be turned back on.
End use natural gas demand for the non-power sectors (i.e. the residential, commercial, and industrial
sectors) is incorporated in IPM through node-level interruptible and firm demand curves derived from the
GMM natural gas demand module. (These are discussed in greater detail in Section 10.6 below.) The
gas consumption in the non-power sectors is calculated within the gas module and the power sector
consumption is calculated within the IPM electricity dispatch module. Figure 10-5 shows the geographic
locations of the demand regions.
LNG export modeling
The gas module does not currently have a specific sub-module for LNG exports. The modeling of
LNG export is currently performed within the gas demand sub-module using a set of fixed or
inelastic firm demand curves. The EPA Base Case v.5.13 includes two LNG export terminals in
the U.S. Gulf Coast and one LNG export terminal in Western Canada. The LNG export modeling
is discussed in more detail in Section 10.6 below.
90 Resource appreciation represents growth in ultimate resource estimates attributed to success in extracting
resource from known plays such as natural gas from shale, coal seams, offshore deepwater, and gas hydrates that
are not included in the resource base estimates.
10-3
-------
Figure 10-3 Gas Transmission Network Map
..,....,<. 200*. XI
Table 10-1 List of Nodes
Node
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
Name
New England
Everett TRANS
Quebec
New York City
Niagara
Southwest PA
Cove Point TRANS
Georgia
Elba Is TRANS
South Florida
East Ohio
Maumee/Defiance
Lebanon
Indiana
South Illinois
North Illinois
Southeast Michigan
East KY/TN
MD/DC/Northern VA
Wisconsin
Northern Missouri
Minnesota
Crystal Falls
Ventura
Emerson Imports
Nebraska
Great Plains
Kansas
East Colorado
Supply
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Demand
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Transit,
Import/
Export
X
X
X
X
X
Underground
Storage
X
X
X
X
X
X
X
X
X
X
X
X
X
Peakshaving Storage
(existing and potential)
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
10-4
-------
Node
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
Name
Opal
Cheyenne
San Juan Basin
EPNG/TW
North Wyoming
South Nevada
SOCAL Area
Enhanced Oil Recovery Region
PGE Area
Pacific Offshore
Monchy Imports
Montana/North Dakota
Wild Horse Imports
Kingsgate Imports
Huntingdon Imports
Pacific Northwest
NPC/PGT Hub
North Nevada
Idaho
Eastern Canada Offshore
Atlantic Offshore
Reynosa Imp/Exp
Juarez Imp/Exp
Naco Imp/Exp
North Alabama
Alabama Offshore
North Mississippi
East Louisiana Shelf
Eastern Louisiana Hub
Viosca Knoll/Desoto/Miss Canyon
Henry Hub
North Louisiana Hub
Central and West Louisiana Shelf
Southwest Texas
Dallas/Ft Worth
E. TX (Katy)
S. TX
Offshore Texas
NWTX
Garden Banks
Green Canyon
Eastern Gulf
North British Columbia
South British Columbia
Caroline
Empress
Saskatchewan
Manitoba
Dawn
Philadelphia
West Virginia
Eastern Canada Demand
Supply
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Demand
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Transit,
Import/
Export
X
X
X
X
X
X
X
X
Underground
Storage
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Peakshaving Storage
(existing and potential)
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
10-5
-------
Node
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
Name
Alliance Border Crossing
Wind River Basin
California Mexican Exports
Whitehorse
MacKenzie Delta
South Alaska
Central Alaska
North Alaska
Arctic
Norman Wells
Southwest VA
Southeast VA
North Carolina
South Carolina
North Florida
Arizona
Southwest Michigan
Northern Michigan
Malin Interchange
Topock Interchange
Ehrenberg Interchange
SDG&E Demand
Eastern New York
New Jersey
Toronto
Carthage
Southwest Oklahoma
Northeast Oklahoma
Southeastern Oklahoma
Northern Arkansas
Southeast Missouri
Uinta/Piceance
South MS/AL
West KY/TN
Kosciusko MS
Northeast PA
Leidy
Supply
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Demand
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Transit,
Import/
Export
X
X
X
X
X
X
X
X
Underground
Storage
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Peakshaving Storage
(existing and potential)
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
10-6
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Figure 10-4 Gas Supply Regions Map
Table 10-2 List of Gas Supply Regions
Supply Region Number
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
Node Number
5
6
96
11
12
13
14
15
16
17
18
92
20
21
22
23
24
26
28
29
30
31
32
33
34
97
36
38
Region Name
Niagara
Southwest PA
Florida
East Ohio
Maumee/ Defiance
Lebanon
Indiana
South Illinois
North Illinois
Southeast Michigan
Eastern KY/TN
SW Virginia
Wisconsin
Northern Missouri
Minnesota
Crystal Falls
Ventura
Nebraska
Kansas
East Colorado
Opal
Cheyenne
San Juan Basin
EPNG/TW
North Wyoming
Arizona
SOCAL Area
PGE Area
10-7
-------
Supply Region Number
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
Node Number
39
41
45
47
48
49
50
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
74
76
77
78
80
83
86
87
88
89
90
91
37
98
99
107
108
109
110
111
112
113
114
Region Name
California Offshore
Montana/ North Dakota
Pacific Northwest
North Nevada
Idaho
Eastern Canada Offshore
Atlantic Offshore
North Alabama
Alabama Offshore
North Mississippi
East Louisiana Shelf
Eastern Louisiana Hub
Viosca Knoll S7 Desoto Canyon/Mississippi Canyon
Henry Hub
North Louisiana Hub
Central and West Louisiana Shelf
Southwest Texas
Dallas/Fort Worth
E. TX (Katy)
S. TX
Offshore Texas
NWTX
Garden Banks
Green Canyon
Florida off-shore moratorium area
North British Columbia
Caroline
Saskatchewan
Manitoba
Dawn
West Virginia
Wind River Basin
McKenzie Delta
Southern Alaska
Central Alaska
Northern Alaska
Arctic
Norman Wells
Enhanced Oil Recovery Region
Southwest Michigan
Central Michigan
Carthage
Southwest Oklahoma
Northeast Oklahoma
Southeastern Oklahoma
Northern Arkansas
Southeast Missouri
Uinta/Piceance
South MS/AL
10-8
-------
Supply Region Number
78
79
80
81
Node Number
115
3
117
118
Region Name
Western KY/TN
Eastern Canada Onshore
NE PA/SC NY
Leidy
Figure 10-5 Gas Demand Regions Map
Natural gas pipeline network is modeled by 380 transmission links or segments (excluding pipeline
connections with LNG import nodes) that represent major interstate transmission corridors throughout
North America (Figure 10-3). The pipeline corridors represent a group of interstate pipelines along the
corridor. The list of key interstate pipelines by links is tabulated in Table 10-3. Each of the links has an
associated discount curve (derived from GMM natural gas transportation module), which represents the
marginal value of gas transmission on that pipeline segment as a function of the pipeline's load factor.91
Starting year of operation and transmission capacity (in units of BBtu/day) are specified as inputs and the
model allows for capacity expansions.
Table 10-3 List of Key Pipelines
Link
1 -4
1 -104
1 -104
3-104
5-6
5-104
5-117
6-5
6-11
6-11
6-19
6-79
Pipeline
Iroquois Pipeline Co
Tennessee Gas Pipeline Co
Algonquin Gas Trans Co
Iroquois Pipeline Co
Tennessee Gas Pipeline Co
Tennessee Gas Pipeline Co
Tennessee Gas Pipeline Co
National Fuel Gas Supply Co
Dominion Trans (CNG)
Columbia Gas Trans Corp
Dominion Trans (CNG)
Texas Eastern Trans Corp
91
In this context "load factor" refers to the percentage of the pipeline capacity that is utilized at a given time.
10-9
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Link
6-80
6-80
6-118
6-118
8-18
8-95
8-96
9-8
10-96
11 -6
11 -6
11-80
12-11
12-17
12-17
12-98
13-11
13-11
13-14
14-12
14-12
14-13
14-98
15-14
15-16
16-20
16-98
17-78
17-98
17-99
18-8
18-11
18-11
18-13
18-80
18-80
18-92
19-79
19-92
19-93
21 -15
23-20
23-22
23-99
23-106
24-16
25-23
26-24
27-24
Pipeline
Dominion Trans (CNG)
Columbia Gas Trans Corp
Dominion Trans (CNG)
Tennessee Gas Pipeline Co
Southern Natural Gas Co
Transcontinental Gas Pipeline Co
Southern Natural Gas Co
Southern Natural Gas Co
Florida Gas Trans Co
Texas Eastern Trans Corp
Tennessee Gas Pipeline Co
Columbia Gas Trans Corp
Columbia Gas Trans Corp
ANR Pipeline Co
Panhandle Eastern Pipeline Co
ANR Pipeline Co
Dominion Trans (CNG)
Texas Eastern Trans Corp
Panhandle Eastern Pipeline Co
Panhandle Eastern Pipeline Co
ANR Pipeline Co
Texas Eastern Trans Corp
Trunkline Gas Co
Panhandle Eastern Pipeline Co
Nat Gas Pipeline Co of America
ANR Pipeline Co
ANR Pipeline Co
Great Lakes Gas Trans Ltd
Panhandle Eastern Pipeline Co
Michcon
East Tennessee Nat Gas Co
Texas Eastern Trans Corp
Tennessee Gas Pipeline Co
Columbia Gas Trans Corp
Columbia Gas Trans Corp
Tennessee Gas Pipeline Co
East Tennessee Nat Gas Co
Transcontinental Gas Pipeline Co
Columbia Gas Trans Corp
Dominion Trans (CNG)
Panhandle Eastern Pipeline Co
ANR Pipeline Co
Great Lakes Gas Trans Ltd
Great Lakes Gas Trans Ltd
Great Lakes Gas Trans Ltd
Nat Gas Pipeline Co of America
Great Lakes Gas Trans Ltd
Nat Gas Pipeline Co of America
Williston Basin Pipeline Co
10-10
-------
Link
27-41
28-15
28-16
28-21
28-26
28-29
28-68
28-108
28-109
30-31
30-48
30-113
31 -28
31 -29
32-33
32-33
32-113
33-63
33-68
33-97
33-101
33-101
34-27
34-31
36-37
36-103
37-38
40-41
41 -83
43-73
44-45
45-46
46-48
48-47
51 -66
54-8
54-8
55-114
56-18
56-54
56-54
56-58
56-114
57-58
57-58
57-58
58-56
58-56
58-56
Pipeline
Williston Basin Pipeline Co
Panhandle Eastern Pipeline Co
ANR Pipeline Co
Panhandle Eastern Pipeline Co
Nat Gas Pipeline Co of America
Colorado Interstate Gas
Colorado Interstate Gas
Nat Gas Pipeline Co of America
Southern Star Central (Williams)
Colorado Interstate Gas
Northwest Pipeline Corp
Northwest Pipeline Corp
Southern Star Central (Williams)
Colorado Interstate Gas
El Paso Nat Gas Co
Transwestern Pipeline Co
Northwest Pipeline Corp
El Paso Nat Gas Co
Transwestern Pipeline Co
El Paso Nat Gas Co
El Paso Nat Gas Co
Transwestern Pipeline Co
Williston Basin Pipeline Co
Wyoming Interstate Co
Socal Gas
Socal Gas
Pacific Gas & Electric
Northwest Energy
Williston Basin Pipeline Co
Terasen (BC Gas)
Northwest Pipeline Corp
Northwest Pipeline Corp
Northwest Pipeline Corp
Northwest Pipeline Corp
Texas Eastern Trans Corp
Transcontinental Gas Pipeline Co
Southern Natural Gas Co
Transcontinental Gas Pipeline Co
Tennessee Gas Pipeline Co
Transcontinental Gas Pipeline Co
Southern Natural Gas Co
Gulf South (Koch)
Gulf South (Koch)
Tennessee Gas Pipeline Co
Southern Natural Gas Co
Texas Eastern Trans Corp
Transcontinental Gas Pipeline Co
Southern Natural Gas Co
Tennessee Gas Pipeline Co
10-11
-------
Link
58-60
58-60
58-60
58-60
58-60
58-114
58-114
58-116
59-57
60-61
60-61
60-61
60-61
60-65
61 -18
61 -56
61 -115
61 -115
61 -116
62-60
62-60
62-60
62-60
62-60
63-53
63-64
63-64
63-65
63-66
63-68
63-68
63-97
64-65
64-108
65-60
65-60
65-60
65-61
65-107
66-51
66-65
66-65
66-65
66-65
66-65
67-65
67-66
68-28
68-108
Pipeline
Transcontinental Gas Pipeline Co
Southern Natural Gas Co
Texas Eastern Trans Corp
Tennessee Gas Pipeline Co
Florida Gas Trans Co
Florida Gas Trans Co
Gulf South (Koch)
Texas Eastern Trans Corp
Tennessee Gas Pipeline Co
Trunkline Gas Co
Gulf South (Koch)
ANR Pipeline Co
Tennessee Gas Pipeline Co
Nat Gas Pipeline Co of America
Tennessee Gas Pipeline Co
Southern Natural Gas Co
ANR Pipeline Co
Trunkline Gas Co
Texas Eastern Trans Corp
Tennessee Gas Pipeline Co
ANR Pipeline Co
Trunkline Gas Co
Transcontinental Gas Pipeline Co
Texas Eastern Trans Corp
El Paso Nat Gas Co
Epgt Texas Pipeline (Valero)
Txu Lonestar Gas Pipeline
Oasis
Epgt Texas Pipeline (Valero)
Epgt Texas Pipeline (Valero)
Nat Gas Pipeline Co of America
El Paso Nat Gas Co
Txu Lonestar Gas Pipeline
Nat Gas Pipeline Co of America
Trunkline Gas Co
Transcontinental Gas Pipeline Co
Texas Eastern Trans Corp
Tennessee Gas Pipeline Co
Nat Gas Pipeline Co of America
Tennessee Gas Pipeline Co
Epgt Texas Pipeline (Valero)
Texas Eastern Trans Corp
Tennessee Gas Pipeline Co
Nat Gas Pipeline Co of America
Transcontinental Gas Pipeline Co
Nat Gas Pipeline Co of America
Transcontinental Gas Pipeline Co
Nat Gas Pipeline Co of America
Nat Gas Pipeline Co of America
10-12
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Link
77-25
78-106
79-105
79-105
80-11
80-19
80-92
83-31
92-18
92-93
94-19
94-92
94-93
95-94
97-102
98-99
99-17
101 -35
101 -36
101 -37
101-102
102-36
104-1
104-4
104-79
105-4
105-4
105-104
106-5
107-15
107-61
107-61
107-64
107-111
108-28
108-107
108-109
108-110
109-21
110-107
110-109
110-111
111 -112
111 -115
112-15
113-30
114-54
114-96
115-14
Pipeline
Great Lakes Gas Trans Ltd
Union Gas
Texas Eastern Trans Corp
Transcontinental Gas Pipeline Co
Dominion Trans (CNG)
Columbia Gas Trans Corp
Columbia Gas Trans Corp
Colorado Interstate Gas
Dominion Trans (CNG)
Columbia Gas Trans Corp
Transcontinental Gas Pipeline Co
Transcontinental Gas Pipeline Co
Transcontinental Gas Pipeline Co
Transcontinental Gas Pipeline Co
El Paso Nat Gas Co
ANR Pipeline Co
Great Lakes Gas Trans Ltd
El Paso Nat Gas Co
Socal Gas
Pacific Gas & Electric
El Paso Nat Gas Co
Socal Gas
Iroquois Pipeline Co
Tennessee Gas Pipeline Co
Columbia Gas Trans Corp
Transcontinental Gas Pipeline Co
Texas Eastern Trans Corp
Algonquin Gas Trans Co
Tennessee Gas Pipeline Co
Nat Gas Pipeline Co of America
Gulf South (Koch)
Centerpoint Energy (Reliant)
Txu Lonestar Gas Pipeline
Texas Eastern Trans Corp
ANR Pipeline Co
Nat Gas Pipeline Co of America
Nat Gas Pipeline Co of America
Centerpoint Energy (Reliant)
Southern Star Central (Williams)
Nat Gas Pipeline Co of America
Centerpoint Energy (Reliant)
Centerpoint Energy (Reliant)
Texas Eastern Trans Corp
Centerpoint Energy (Reliant)
Nat Gas Pipeline Co of America
Wyoming Interstate Co
Transcontinental Gas Pipeline Co
Florida Gas Trans Co
Trunkline Gas Co
10-13
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Link
115-14
116-18
117-5
117-104
117-105
117-118
117-118
117-118
117-118
118-5
Pipeline
ANR Pipeline Co
Texas Eastern Trans Corp
Dominion Trans (CNG)
Dominion Trans (CNG)
Transcontinental Gas Pipeline Co
Transcontinental Gas Pipeline Co
Dominion Trans (CNG)
Tennessee Gas Pipeline Co
National Fuel Gas Supply Co
National Fuel Gas Supply Co
Natural gas storage is modeled by 190 underground and LNG peak shaving92 storage facilities that are
linked to individual nodes. The underground storage is grouped into three categories based on storage
"Days Service"93: (1) 20-day for high deliverability9 storage such as salt caverns, (2) 80-day for
depleted95 and aquifer96 reservoirs, and (3) over 80 days mainly for depleted reservoirs. The level of gas
storage withdrawals and injections are calculated within the supply and demand balance algorithm based
on working gas97 levels, gas prices, and extraction/injection rates and costs. Starting year of operation
and working gas capacity (in units of BBtu) are specified as inputs and the model allows for capacity
expansions. The location of the storage facilities is shown in Figure 10-6.
Natural gas prices are market clearing prices derived from the supply and demand balance at each of
the model's nodes for each segment of IPM's electricity sector's seasonal load duration curve (LDC). On
the supply-side, prices are determined by production and storage price curves that reflect prices as a
function of production and storage utilization. Prices are also affected by the "pipeline discount" curves
discussed earlier, which represent the marginal value of gas transmission as a function of a pipeline's
load factor and result in changes in basis differential. On the demand-side, the price/quantity relationship
is represented by demand curves that capture the fuel-switching behavior of end-users at different price
levels. The model balances supply and demand at all nodes and yields market clearing prices
determined by the specific shape of the supply and demand curves at each node.
10.2.1 Note on the Modeling Time Horizon and Pre- and Post-2040 Input Assumptions
The time horizon of the EPA's Base Case v.5.13 extends through 2050. Projections through the year
2040 in EPA's Base Case v.5.13 are based on a detailed bottom-up development of natural gas
assumptions from available data sources. Beyond 2040, where detailed data are not readily available,
various technically plausible simplifying assumptions were made. For example, natural gas demand
growth from 2040 to 2050 for the non-power sectors (i.e. residential, commercial, and industrial) is
LNG peak shaving facilities supplement deliveries of natural gas during times of peak periods. LNG peak shaving
facilities have a regasification unit attached, but may or may not have a liquefaction unit. Facilities without a
liquefaction unit depend upon tank trucks to bring LNG from nearby sources.
93 "Days Service" refers to the number of days required to completely withdraw the maximum working gas inventory
associated with an underground storage facility.
94 High deliverability storage is depleted reservoir storage facility or Salt Cavern storage whose design allows a
relatively quick turnover of the working gas capacity.
95 A gas or oil reservoir that is converted for gas storage operations. Its economically recoverable reserves have
usually been nearly or completely produced prior to the conversion.
96 The underground storage of natural gas in a porous and permeable rock formation topped by an impermeable cap
rock, the pore space of which was originally filled with water.
97 The term "working gas" refers to natural gas that has been injected into an underground storage facility and stored
therein temporarily with the intention of withdrawing it. It is distinguished from "base (or cushion) gas" which refers to
the volume of gas that remains permanently in the storage reservoir in order to maintain adequate pressure and
deliverability rates throughout the withdrawal season.
10-14
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assumed to be the same as the level of growth from 2020 to 2040. Resource growth assumptions (for
resource appreciation) that were applied for pre-2040 are extended beyond 2040. Post-2040 price
projections for crude oil and natural gas liquids98 (NGLs) are assumed to be flat at 2040 price levels. The
pre-2040 price projections were adapted from AEO 2013.
Figure 10-6 Natural Gas Storage Facility Node Map
0
O 20-Day
fr 80-Day
A Over 80 Days
3 LNG Peakshaving
10.3 Resource Characterization and Economic Evaluation
The GMM Hydrocarbon Supply Model (HSM) provides data related to resource characterization and
economic evaluation for use in the IPM natural gas module. The current section describes data sources
and methods used in the HSM to characterize the North American natural gas resource base. This
section concludes with a description of how the HSM resource characterization is used in the EPA Base
Case v.5.13 gas module. The next section (i.e., Section 10.4) describes the economic evaluation
procedures applied to Exploration and Development (E&D) activities in the HSM and various constraints
affecting E&D activities.
The HSM was designed for the simulation, forecasting and analysis of natural gas, crude oil and natural
gas liquids supply and cost trends in the United States and Canada. The HSM includes a highly detailed
description of both the undiscovered and discovered resources in the U.S. and Canada. The resource
base is described on a field-by-field basis. The individual fields are characterized by type (i.e., oil or gas),
size, and location. Location is defined both geographically and by depth. The HSM is a process-
engineering model with a very detailed representation of potential gas resources and the technologies
Those hydrocarbons in natural gas that are separated from the gas as liquids in gas processing or cycling plants.
Generally such liquids consist of ethane, propane, butane, and heavier hydrocarbons.
10-15
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with which those resources can be proven" and produced. The degree and timing by which resources
are proven and produced are determined in the model through discounted cashflow analyses of
alternative investment options and behavioral assumptions in the form of inertial and cashflow
constraints, and the logic underlying producers' market expectations (e.g., their response to future gas
prices).
Supply results from the HSM model include undeveloped resource accounting and detailed well, reserve
addition, decline rate, and financial results. These results are utilized to provide estimates of base year
economically recoverable natural gas resources and remaining reserves as a function of E&D cost for the
81 supply regions in the IPM natural gas module. The HSM also provides other data such as the level of
remaining resource that could be discovered and developed in a year, exploration and development
drilling requirements, production operation and maintenance (O&M) cost, resource share of crude oil and
natural gas liquids, natural gas reserves to production ratio, and natural gas requirement for lease and
plant use.100
10.3.1 Resource and Reserves101 Assessment
Data sources: The HSM uses the U.S. Geological Survey (USGS), Minerals Management Service
(MMS), and Canadian Gas Potential Committee (CGPC) play-level102 resource assessments as the
starting point for the new field/new pool103 assessments. Beyond the resource assessment data, ICF has
access to numerous databases that were used for the HSM model development and other analysis.
Completion-level production is based on IHS Energy completion level oil and gas production databases
for the U.S. and Canada. The U.S. database contains information on approximately 300,000 U.S.
completions. A structured system is employed to process this information and add certain ICF data
(region, play, ultimate recovery, and gas composition) to each record. ICF also performs extensive
quality control checks using other data sources such as the MMS completion and production data for
Outer Continental Shelf (OCS) areas and state production reports.
In the area of unconventional gas104, ICF has worked for many years with the Gas Research Institute
(GRI)/Gas Technology Institute (GTI) to develop a database of tight gas, coalbed methane, and Devonian
Shale reservoirs in the U.S. and Canada. Along with USGS assessments of continuous plays, the
The term "proven" refers to the estimation of the quantities of natural gas resources that analysis of geological and
engineering data demonstrate with reasonable certainty to be recoverable in future years from known reservoirs
under existing economic and operating conditions. Among the factors considered are drilling results, production, and
historical trends. Proven reserves are the most certain portion of the resource base.
100 As discussed more fully in Section 10.4, natural gas for "lease and plant use" refers to the gas used in well, field,
and lease operations (such as gas used in drilling operations, heaters, dehydrators, and field compressors) and as
fuel in gas processing plants.
101 When referring to natural gas a distinction is made between "resources" and "reserves." "Resources" are
concentrations of natural gas that are or may become of potential economic interest. "Reserves" are that part of the
natural gas resource that has been fully evaluated and determined to be commercially viable to produce.
102 A "play" refers to a set of known or postulated natural gas (or oil) accumulations sharing similar geologic,
geographic, and temporal properties, such as source rock, migration pathway, timing, trapping mechanism, and
hydrocarbon type.
103 A "pool" is a subsurface accumulation of oil and other hydrocarbons. Pools are not necessarily big caverns. They
can be small oil-filled pores. A "field" is an accumulation of hydrocarbons in the subsurface of sufficient size to be of
economic interest. A field can consist of one or more pools.
104 Unconventional gas refers to natural gas found in geological environments that differ from conventional
hydrocarbon traps. It includes: (a) "tight gas," i.e., natural gas found in relatively impermeable (very low porosity and
permeability) sandstone and carbonate rocks; (b) "shale gas," i.e., natural gas in the joints, fractures or the matrix of
shales, the most prevalent low permeability low porosity sedimentary rock on earth; and (c) "coal bed methane,"
which refers to methane (the key component of natural gas) found in coal seams, where it was generated during coal
formation and contained in the microstructure of coal. Unconventional natural gas is distinguished from conventional
gas which is extracted using traditional methods, typically from a well drilled into a geological formation exploiting
natural subsurface pressure or artificial lifting to bring the gas and associated hydrocarbons to the wellhead at the
surface.
10-16
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database was used to help develop the HSM's "cells", which represent resources in a specific geographic
area, characterizing the unconventional resource in each basin, historical unconventional reserves
estimates and typical decline curves.105 ICF has recently revised the unconventional gas resource
assessments based on new gas industry information on the geology, well production characteristics, and
costs. The new assessments include major shale units such as the Fort Worth Barnett Shale, the
Marcellus Shale, the Haynessville Shale, and Western Canada shale plays. ICF has built up a database
on gas compositions in the United States and has merged that data with production data to allow the
analysis of net versus raw gas production.106
In Canada, gas composition data are obtained from provincial agencies. These data were used to
develop dry gas107 production/reserves by region and processing costs in the HSM and to characterize
ethane rejection108 by regions. Information on oil and gas fields and pools in the U.S. come originally
from Dwight's Energydata (now IMS Energy) TOTL reservoir database. ICF has made extensive
modifications to the database during the creation of the Gas Information System (GASIS) database for
the U.S. Department of Energy (DOE) and other projects. Field and reservoir data for Canada comes
from the provincial agency databases. These data are used to estimate the number and size of
undiscovered fields or pools and their rate of discovery per increment of exploratory drilling. Additional
data were obtained from the Significant Field Data Base of NRG Associates.
Methodology and assumptions: Resources in the HSM model are divided into three general categories:
new fields/new pools, field appreciation, and unconventional gas. The methodology for resource
characterization and economic evaluation differs for each.
Conventional resource - new fields/new pools: The modeling of conventional resource is based on a
modified "Arps Roberts" equation to estimate the rate at which new fields are discovered. The
fundamental theory behind the find-rate methodology is that the probability of finding a field is proportional
to the field's size as measured by its area extent, which is highly correlated to the field's level of reserves.
For this reason, larger fields tend to be found earlier in the discovery process than smaller fields. Finding
that the original Arps-Roberts equation did not replicate historical discovery patterns for many of the
smaller field sizes, ICF modified the equation to improve its ability to accurately track discovery rates for
mid- to small-size fields. Since these are the only fields left to be discovered in many mature areas of the
U.S. and Western Canada Sedimentary Basin (WCSB), the more accurate find-rate representation is an
important component in analyzing the economics of exploration activity in these areas. An economic
evaluation is made in the model each year for potential new field exploration programs using a standard
discounted after-tax cash flow (DCF) analysis. This DCF analysis takes into account how many fields of
each type are expected to be found and the economics of developing each.
105 A decline curve is a plot of the rate of gas production against time. Since the production rate decline is associated
with pressure decreases from oil and gas production, the curve tends to smoothly decline from a high early
production rate to lower later production rate. Exponential, harmonic, and hyperbolic equations are typically used to
represent the decline curve.
106 Raw gas production refers to the volumes of natural gas extracted from underground sources, whereas net gas
production refers to the volume of purified, marketable natural gas leaving the natural gas processing plant.
107 Natural gas is a combustible mixture of hydrocarbon gases. Although consisting primarily of methane, the
composition of natural gas can vary widely to include propane, butane, ethane, and pentane. Natural gas is referred
to as 'dry' when it is almost pure methane, having had most of the other commonly associated hydrocarbons
removed. When other hydrocarbons are present, the natural gas is called 'wet'.
108 Ethane rejection occurs when the ethane component in the natural gas stream is not recovered in a gas
processing plant but left in the marketable natural gas stream. Ethane rejection is deployed when the value of ethane
is worth more in the gas stream than as an a separate commodity or as a component of natural gas liquids (NGL),
which collectively refers to ethane, propane, normal butane, isobutane, and pentanes in processed and purified
finished form. Information that characterizes ethane rejection by region can play a role in determining the production
level and cost of natural gas by region.
109 "Arps-Roberts equation" refers to the statistical model of petroleum discovery developed by J. J. Arps, and T. G.
Roberts, T. G., in the 1950's.
10-17
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Conventional resource - field appreciation: The model maintains inventories of potential resources that
can be proved from already discovered fields. These inventories are referred to as appreciation, growth-
to-known or "probables." As the model simulation proceeds, these probables inventories are drawn down
as the resources are proved. At the same time, the inventories of probables are increased due to future
year appreciation of new fields that are added to the discovered fields' data set during the model
simulation.
Unconventional resource: Originally, the assessments of the unconventional resources were based on
the Enhanced Recovery Module (or ERM) within the HSM. The ERM covers that portion of the resource
base which falls outside the scope of the "conventional" oil and gas field discovery process dealt with
elsewhere in the model. The ERM includes coalbed methane, shale gas, and tight gas. These resources
generally correspond to the "continuous plays" designated by the USGS in its resource assessments.
The ERM is organized by "cells", which represent resources in a specific geographic area. A cell can
represent any size of area ranging from the entire region/depth interval to a single formation in a few
townships of a basin. Each cell is evaluated in the model using the same discounted cashflow analysis
used for new and old field investments. The ERM cells also are subject to the inertial and cashflow
constraints affecting the other types of investment options in the model. The model reports total wells
drilled, reserve additions, production, and dollars invested for each type of ERM cell (e.g., coalbed
methane) within a region.
As described earlier, ICF has recently revised the unconventional gas resource assessments based on
new gas industry information on the geology, well production characteristics, and costs. The new
assessment method is a "bottom-up" approach that first generates estimates of unrisked and risked gas-
in-place (GIP) from maps of depth, thickness, organic content, and thermal maturity. Then ICF uses a
reservoir simulator to estimate well recoveries and production profiles. Unrisked GIP is the amount of
original gas-in-place determined to be present based upon geological factors without risk reductions.
Risked GIP includes a factor to reduce the total gas volume on the basis of proximity to existing
production and geologic factors such as net thickness (e.g., remote areas, thinner areas, and areas of
high thermal maturity have higher risk). ICF calibrates well recoveries with specific geological settings to
actual well recoveries by using a rigorous method of analysis of historical well data.
10.3.2 Frontier Resources (Alaska and Mackenzie Delta)
Besides the three general categories of resources described above, the handling of frontier resources in
the HSM is worth noting. Frontier resources such as Alaska North Slope and Mackenzie Delta are
subject to similar resource assessment and economic evaluation procedures as applied to other regions.
However, unlike other regions, the resources from these regions are stranded to date due to lack of
effective commercial access to markets. In fact, 6-8 Bcf/d of gas that is currently produced as part of the
oil activities in the Alaska North Slope is re-injected back into the Slope's oil reservoirs as part of the
pressure maintenance programs. Several development proposals have been put forward for bringing this
Alaska North Slope and Mackenzie Delta gas to market.
In developing the gas resource assumptions for EPA Base Case v.5.13, two gas pipeline projects were
identified for bringing the two frontier gas supply resources to the markets in the U.S. and Canada.
However, due to uncertainties in the economics and the timing of these pipeline projects, they are not
included in the EPA Base Case v.5.13.
10.3.3 Use of the HSM resource and reserves data in EPA Base Case using IPM v.5.13 Natural
Gas Module
The base year for the integrated gas-electricity module in EPA Base Case using IPM v.5.13 is 2016.
Having a base year in the future has implications on how the model is run and how the gas reserves and
resources data are set up. The IPM run begins with a gas module only run for year 2015 to provide
beginning of year (BOY) 2016 reserves and resources as the starting point for the integrated run from
2016 onward. This in turn requires the reserves and resources data to be provided for the BOY 2015.
Since the data from the HSM are as of BOY 2011, adjustments have to be made to account for reserves
10-18
-------
development, production, and also resource appreciation between 2011 and 2014. In the EPA Base
Case using IPM v.5.13, these adjustments are made based on a four-year production and reserves
development forecast using the GMM and a set of resource appreciation growth assumptions. The
resource growth assumptions are discussed in "Undiscovered Resource Appreciation" section below.
Table 10-4 provides a snapshot of the starting natural gas resource and reserve assumptions for the EPA
Base Case v.5.13. In this table, undiscovered resources represent the economic volume of dry gas that
could be discovered and developed with current technology through exploration and development at a
specified maximum wellhead gas price. Since the IPM natural gas module differentiates conventional gas
from unconventional gas, these are shown separately in Table 10-4. The conventional gas is
subcategorized into non-associated gas from gas fields and associated gas110 from oil fields. The
unconventional gas is subdivided into coalbed methane (CBM), shale gas, and tight gas. In Table 10-4,
the shale gas resource availability in the Northeast region is constrained by as assumption of limited
access in accordance with current permitting procedures mostly affecting the Marcellus play. The full
resource is about 925 Tcf.
The reserves are remaining dry gas volumes to be produced from existing developed fields. For EPA
Base Case v.5.13 the maximum wellhead price for the resource cost curves is capped at $16/MMBtu (in
real 2011 dollars). The ultimate potential undiscovered resources available are actually higher than those
presented in Table 10-4 but it would cost more than $16/MMBtu to recover them. (It is important to note
that this price is for wet111 gas at the wellhead in the production nodes. The dry gas price at the receiving
nodes can be higher than $16/MMBtu which depends on the share of dry gas, lease and plant use, gas
processing cost, production O&M cost, and pipeline transportation costs.) The approach used in the HSM
to derive these costs is described more fully in section 10.4 below.
Table 10-4 U.S. and Canada Natural Gas Resources and Reserves
Region
Lower 48 Onshore Non Associated
Conventional (includes tight)
Northeast
Gulf Coast
Midcontinent
Southwest
Rocky Mountain
West Coast
Shale Gas
Northeast
Gulf Coast
Midcontinent
Southwest
Rocky Mountain
West Coast
Coalbed Methane
Northeast
Gulf Coast
Beginning of Year 2015
Undiscovered Dry Gas Resource (Tcf)
2,049
566
49
144
48
19
288
18
1,408
647
492
151
67
50
0
75
10
4
Dry Gas Reserves (Tcf)
325
101
9
18
16
13
46
0
212
79
89
22
15
8
-
11
1
1
110 Associated gas refers to natural gas that is produced in association with crude oil production, whereas non-
associated gas is natural gas that is not in contact with significant quantities of crude oil in the reservoir.
111 A mixture of hydrocarbon compounds and small quantities of various non-hydrocarbons existing in the gaseous
phase or in solution with crude oil in porous rock formations at reservoir conditions. The principal hydrocarbons
normally contained in the mixture are methane, ethane, propane, butane, and pentane. Typical non-hydrocarbon
gases that may be present in reservoir natural gas are water vapor, carbon dioxide, hydrogen sulfide, nitrogen and
trace amounts of helium.
10-19
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Region
Midcontinent
Southwest
Rocky Mountain
West Coast
Lower 48 Offshore Non Associated
Gulf of Mexico
Pacific
Atlantic
Associated-Dissolved Gas
Alaska
Total U.S.
Canada Non Associated
Conventional and Tight
Shale Gas
Coalbed Methane
Canada Associated-Dissolved Gas
Total Canada
Total U.S and Canada
Beginning of Year 2015
Undiscovered Dry Gas Resource (Tcf)
10
50
1
85
85
116
51
2,300
858
104
723
31
4
862
3,162
Dry Gas Reserves (Tcf)
1
9
6
6
0
13
10
355
59
30
24
5
3
62
416
Figure 10-7 presents dry gas resource cost curves for the BOY 2015 initializing gas assumptions for EPA
Base Case v.5.13. The resource cost curves show the undiscovered recoverable dry gas resources at
different price levels. The curves do not include dry gas reserves. Separate resource cost curves are
shown for conventional, shale, coalbed methane (CBM), and tight gas. The recoverable resources
shown at maximum wellhead prices in these graphs are those tabulated in Table 10-4 under
"Undiscovered Dry Gas Resource" column. The y-axis of the resource cost curves shows the cost at the
wellhead of bringing the volume of undiscovered resource indicated on the x-axis into the reserves
category. Figure 10-8 diagrams the exploration & development and production processes and the
associated costs required to bring undiscovered resource into reserves and production.
10-20
-------
Figure 10-7 Resource Cost Curves at the Beginning of Year 2015
$18
500 1,000 1,500 2.000 2,500 3,000
Undiscovered Recoverable Dry Gas Resource (Tcf)
Does not include proven reserves
Conventional ^^Shale CBM ^Tight ^Total
3,500
10.3.4 Undiscovered Resource Appreciation
Undiscovered resource appreciation is additional resources from hydrocarbon plays that were not
included in the resource base estimates. It differs from field appreciation or reserves appreciation
category discussed above which comes from already discovered fields. Natural gas from shales, coal
seams, offshore deepwater, and gas hydrates may not be included in the resource base assessments
due to lack of knowledge and technology to economically recover the resource. As new technology
becomes available, these untapped resources can be produced economically in the future. One example
is the advancements in horizontal drilling and hydraulic fracture technologies to produce gas from shale
formations. For EPA Base Case, the undiscovered gas resource is assumed to grow at 0.2% per year for
conventional gas and 0.75% per year for unconventional gas. The BOY 2015 undiscovered recoverable
gas resources in Table 10-4 and Figure 10-7 include resource appreciation between 2011 and 2014.
10-21
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Figure 10-8 Exploration & Development and Production Processes and Costs to Bring
Undiscovered Resource into Reserves and Production
Hydrocarbon*
Production
Dry Gas
Production
Gas Processing
- Dry gas share
- Lease and plant gas use
- Production O&M and Gas processing costs
Production
- Reserves-to-production
(R/P) ratio
- Production cost
Hydrocarbon*
Reserves
Hydrocarbon*
Recoverable
Resource
Exploration & Development
- Resource discovery rate
- Exploration & development drilling requirements
- Exploration & development costs
*Hydrocarbon includes oil, natural gas liquids, and dry gas.
10.4 Exploration, Development, and Production Costs and Constraints
10.4.1 Exploration and Development Cost
Exploration and development (E&D) cost or resource cost is the expenditure for activities related to
discovering and developing hydrocarbon resources. The E&D cost for natural gas resources is a function
of many factors such as geographic location, field type, size, depth, exploratory success rates, and
platform, drilling and other costs. The HSM contains base year cost for wells, platforms, operating costs
and all other relevant cost items. In addition to the base year costs, the HSM contains cost indices that
adjust costs overtime. These indices are partly a function of technology drivers such as improved
exploratory success rates, cost reductions in platform, drilling and other costs, improved recovery per
well, and partly a function of regression-based algorithms that relate cost to oil and gas prices and
industry activity. As oil and gas prices and industry activity increase, the cost for seismic, drilling &
completion services, casing and tubing and lease equipment goes up.
Other technology drivers affect exploratory success rates and reduce the need to drill exploratory wells.
A similar adjustment is made to take into account changes over time in development success rates, but
the relative effect is much smaller because development success rates are already rather high. The
technology drivers that increase recovery per well are differentiated in the HSM by region and by type of
gas. Generally, the improvements are specified as being greater for unconventional gas because their
recovery factors are much lower than those of conventional gas.
The HSM model provides estimates of E&D cost and the level of economically viable gas resource by
region as a function of E&D cost. The HSM increased recovery as a function of technology improvement
by region is converted to E&D and production technology improvement overtime in the form of cost
reduction factors by onshore, offshore shelf, and offshore deepwater as shown in Figure 10-9. The
average cost reduction factors for onshore, offshore shelf, and offshore deepwater E&D activities are -
0.9% per year, -0.7% per year, and -0.4% per year, respectively. These factors are predominantly
affected by the level of E&D investments in the regions. The expected aggressive onshore E&D activities
to find and produce unconventional gas resources, such as shale gas, will lead to more research in
horizontal drilling and hydraulic fracturing technologies to improve productions and lower the costs. This
is reflected in higher cost reduction factors for the onshore regions.
10-22
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Figure 10-9 E&D and Production Technology Improvement Factor
05
2010 2020 2030 2040 2050 2060
Onshore ^^ Offshore Shelf -Offshore Deepwater
Figure 10-10 shows E&D cost needed to discover and develop 2.5%, 5%, and 7.5% of the remaining
undiscovered resource in BOY 2015 by natural gas supply region.
10-23
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Figure 10-10 Incremental E&D Cost (BOY 2015) by Percentage of Dry Gas Resource Found
(118)l_eidy
(117) Northeast PA
(116)KosciuskoMS
(115)WestKY/TN
(114) South MS/AL
(113)Uinta/Piceance
(111) Northern Arkansas
(110) Southeastern Oklahoma
(109) Northeast Oklahoma
(108) Southwest Oklahoma
(107) Carthage
(99) Northern Michigan
(98) Southwest Michigan
(96) North Florida
(92)SouthwestVA
(89) North Alaska
(87) South Alaska
(83) Wind River Basin
(80) West Virginia
(76) Saskatchewan
(74) Caroline
(72) North British Columbia
(71) Eastern Gulf
(70) Green Canyon
(69) Garden Banks
(68)NWTX
(67) Offshore Texas
(66) S. TX
(G5)E. TX (Katy)
(64) Dallas/Ft Worth
(63) Southwest Texas
(62) Central and West Louisiana Shelf
(61) North Louisiana Hub
(60) Henry Hub
(59) Viosca KnollOesoto/Miss Canyon
(58) Eastern Louisiana Hub
(57) East Louisiana Shelf
(55) Alabama Offshore
(54) North Alabama
(49) Eastern Canada Offshore
(45) Pacific Northwest
(41) Montana/North Dakota
(38)PGEArea
(37) Enhanced Oil Recovery Region
(36)SOCALArea
(34) North Wyoming
(32) San Juan Basin
(30) Opal
(29) East Colorado
(28) Kansas
(21) Northern Missouri
(18) Tennessee/Kentucky
(15) South Illinois
(14) Indiana
(11) East Ohio
(6)Leidy
(5) Niagara
Resource Cost at Wellhead (2011$/MMBtu)
D2.5% B50% D7.5%
10-24
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10.4.2 Resource Discovery and Drilling Constraints
As mentioned above the simulation in HSM also provides other data such as resource discovery factors
which describe the maximum share of remaining undiscovered resource that could be discovered and
developed in a year and drilling requirements which describe the drilling required for successful
exploration and development. These two parameters are constraints to the development of the resource
and their values are not time dependent. The resource discovery constraint is the same for all regions
and is assumed to be 6% of the remaining undiscovered resource (column 4 in Table 10-5). The drilling
requirement constraint (column 5 in Table 10-5) varies from 2,500 feet for every billion cubic feet of
incremental resource discovered (feet/Bcf) for offshore U.S. and between 3,000 feet/Bcf to 10,000
feet/Bcf for onshore regions and offshore Canada.
Table 10-5 Exploration and Development Assumptions for EPA Base Case v.5.13
Region
(5) Niagara
(6) Leidy
(11) East Ohio
(14) Indiana
(15) South Illinois
(16) North Illinois
(1 8) Tennessee/Kentucky
(21) Northern Missouri
(28) Kansas
(29) East Colorado
(30) Opal
(32) San Juan Basin
(34) North Wyoming
(36) SOCAL Area
(37) Enhanced Oil Recovery Region
(38) PGE Area
(41) Montana/North Dakota
(45) Pacific Northwest
(49) Eastern Canada Offshore
(54) North Alabama
(55) Alabama Offshore
(57) East Louisiana Shelf
(58) Eastern Louisiana Hub
(59) Viosca Knoll/Desoto/Miss Canyon
(60) Henry Hub
(61) North Louisiana Hub
(62) Central and West Louisiana Shelf
(63) Southwest Texas
(64) Dallas/Ft Worth
(65) E. TX (Katy)
(66) S. TX
(67) Offshore Texas
(68) NW TX
(69) Garden Banks
(70) Green Canyon
(71) Eastern Gulf
Fraction of
Hydrocarbons
that are
Natual Gas
Liquids (NGLs)
(Fraction)
0.02
0.01
0.10
0.00
0.00
0.00
0.11
0.11
0.12
0.11
0.08
0.11
0.11
0.08
0.04
0.08
0.05
0.14
0.03
0.07
0.01
0.04
0.13
0.07
0.13
0.11
0.04
0.17
0.06
0.14
0.12
0.09
0.22
0.07
0.07
0.04
Fraction of
Hydrocarbons
that are
Crude Oil
(Fraction)
0.12
0.02
0.01
0.99
0.96
1.00
0.02
0.00
0.25
0.03
0.29
0.04
0.00
0.56
0.74
0.61
0.64
0.00
0.00
0.04
0.84
0.74
0.24
0.56
0.25
0.01
0.74
0.36
0.05
0.42
0.24
0.31
0.08
0.49
0.53
0.71
Max Share
of Resources
that can be
Developed
per Year
(Fraction)
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
Exploration,
Development
Drilling
Required
(Ft/Bcf)
10,000
4,556
9,400
10,000
10,000
10,000
10,000
10,000
7,454
9,349
4,862
6,323
3,688
9,320
10,000
9,376
10,000
10,000
10,000
6,099
2,500
2,500
6,884
2,500
6,927
9,823
2,500
7,925
4,510
8,819
7,596
2,500
7,584
2,500
2,500
2,500
Lease and
Plant Use
(Fraction)
0.05
0.03
0.01
0.02
0.30
0.30
0.04
0.04
0.04
0.05
0.05
0.13
0.05
0.13
0.13
0.13
0.13
0.02
0.06
0.03
0.03
0.04
0.04
0.04
0.04
0.04
0.04
0.05
0.05
0.05
0.05
0.05
0.05
0.04
0.04
0.04
10-25
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Region
(72) North British Columbia
(74) Caroline
(76) Saskatchewan
(80) West Virginia
(83) Wind River Basin
(86) MacKenzie Delta
(87) South Alaska
(89) North Alaska
(90) Arctic
(92) Southwest VA
(96) North Florida
(98) Southwest Michigan
(99) Northern Michigan
(107) Carthage
(108) Southwest Oklahoma
(109) Northeast Oklahoma
(110) Southeastern Oklahoma
(111) Northern Arkansas
(113) Uinta/Piceance
(1 14) South MS/AL
(115)WestKY/TN
(116) Kosciusko MS
(11 7) Northeast PA
(118)Leidy
Fraction of
Hydrocarbons
that are
Natual Gas
Liquids (NGLs)
(Fraction)
0.01
0.04
0.01
0.06
0.11
0.00
0.05
0.04
0.00
0.00
0.01
0.08
0.05
0.07
0.15
0.16
0.16
0.00
0.10
0.06
0.11
0.11
0.01
0.01
Fraction of
Hydrocarbons
that are
Crude Oil
(Fraction)
0.00
0.04
0.54
0.00
0.01
1.00
0.59
0.62
1.00
0.00
0.94
0.09
0.21
0.02
0.06
0.03
0.02
0.05
0.13
0.16
0.06
0.00
0.01
0.01
Max Share
of Resources
that can be
Developed
per Year
(Fraction)
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
0.06
Exploration,
Development
Drilling
Required
(Ft/Bcf)
9,948
9,752
10,000
3,539
7,013
10,000
10,000
10,000
10,000
5,787
9,937
10,000
7,946
3,228
6,905
9,089
4,445
4,437
7,715
7,012
10,000
10,000
3,394
3,993
Lease and
Plant Use
(Fraction)
0.08
0.10
0.07
0.05
0.05
0.08
0.08
0.99
0.08
0.02
0.21
0.04
0.04
0.05
0.04
0.04
0.04
0.04
0.05
0.03
0.04
0.04
0.04
0.04
Other drilling constraints include rig capacity, rig retirement, rig growth, and drilling speed. Values for the
constraints are specified for each of the three drilling category: (1) onshore, (2) offshore shelf, and (3)
offshore deepwater. The drilling rig capacity constraint shows the number of drilling rigs initially available
in the BOY 2015. The initial rig counts are 4,050 rigs for onshore, 125 rigs for offshore shelf, and 125 rigs
for offshore deepwater and the numbers can change overtime controlled by rig retirement and rig growth
constraints. The drilling rig retirement constraint is the share of rig capacity that can retire in a year. The
drilling rig growth constraint is the maximum increase of total rig count in a year. The drilling retirement
and growth are assumed to be the same for all drilling category and the constraints are set to 0.5% per
year and 3.5% per year, respectively.
Another growth constraint, minimum drilling capacity increase, is implemented to force the rig count to
grow by at least one rig in each drilling category. The drilling speed constraint is the required speed in
feet/day/rig for successful exploration and development. The drilling speed required for successful E&D
grows overtime, as shown in Figure 10-11 and differs for onshore and offshore (which in this case
includes both shelf and deep shelf).
10-26
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Figure 10-11 Drilling Rig Speed Constraint
2010
2020
2030
2040
2050
2060
Onshore
Offshore
10.4.3 Reserves-to-Production (RIP) Ratio
The reserves-to-production ratio is the remaining amount of reserves, expressed in years, to be produced
with a current annual production rate. In the IPM gas module, the R/P data obtained from the HSM is
provided in the form of production-to-reserves (P/R) ratio (or reciprocal of the R/P ratio). The P/R ratio is
used to calculate annual wet gas production from the reserves and the value varies by resource type and
production node. For conventional gas the P/R ratio ranges from 0.04 (or 25 years of R/P) to 0.25 (or 4
years of R/P) with average of 0.13 (or 8 years of R/P). The P/R ratio of shale and tight gas is half of that
of the conventional gas with average P/R ratio of 0.06 (or 17 years of R/P). Coalbed methane gas has
the lowest P/R ratio with average of 0.04 (or 25 years of R/P).
10.4.4 Variable Costs, Natural Gas Liquid Share, and Crude Oil Share
In the IPM natural gas module, the variable costs include production operations and maintenance (O&M)
cost and gas processing cost. The production O&M cost for 2015 is estimated to be $0.54/MMBtu (in real
2011 dollars) and is assumed to be the same for all supply regions. The production O&M cost is
expected to decline overtime due to improvements in production technology. In the model the same
technology improvement factor shown in Figure 10-9 is applied to the production O&M cost.
The resource data from the HSM is provided in the form of total hydrocarbon (oil, gas, and NGL)
resource. The HSM also provides the allocations of the hydrocarbon for dry gas, oil, and NGL. Table
10-5 shows the shares of NGL (column 2) and crude oil (column 3) by supply region. Wet gas production
from the wellhead is processed in gas processing plants to produce pipeline quality dry gas. Node level
gas processing cost for IPM natural gas module is obtained from the GMM. The processing cost varies
from $0.07/MMBtu (of wet gas in real 2011 dollars) to $0.61/MMBtu with average of $0.23/MMBtu.
10.4.5 Lease and Plant Gas Use
The term "lease and plant gas" refers to the gas used in well, field, and lease operations (such as gas
used in drilling operations, heaters, dehydrators, and field compressors) and as fuel in gas processing
plants. The data for lease and plant gas use is derived for the HSM as a fraction of wet gas production
and varies by region. The value ranges from 0.01 to as high as 0.3 with an average of around 0.06
(column 6 in Table 10-5). Lease and plant for North Alaska is set to 0.99 to represent the portion of gas
production that is re-injected back into the Slope's oil reservoirs.
10-27
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10.5 Liquefied Natural Gas (LNG) Imports
As described earlier, most of the data related to North American LNG imports is derived from the GMM
LNG model. Based on a comprehensive database of existing and potential liquefaction and regasification
facilities and worldwide LNG import/export activities, the model uses a simulation procedure to create the
BOY 2015 North American LNG supply curves and projections of regasification capacity and costs.
Key elements of the LNG model are described below.
10.5.1 Liquefaction Facilities and LNG Supply
The supply side of the GMM LNG model takes into account capacities from existing as well as potential
liquefaction facilities. The lower and upper boundaries of supply capacity allocated for each North
American regasification facility are set by available firm contracts and swing supplies. Three point LNG
supply curves are generated within this envelope where: (1) the lower point is the amount of firm LNG
supply, (2) the upper bound is the firm imports plus the maximum swing imports available for that facility,
and (3) the midpoint is the average of the minimum and maximum values. Prices for the minimum and
maximum points are tied to Refiner Acquisition Cost of Crude (RACC) price.112 The minimum price
represents minimum production cost for liquefaction facilities and is set at 0.5 of RACC price and the
maximum price is set at 1.5 of RACC price. The prices are then shifted up for winter months and shifted
down in the summer months to represent the seasonal variation in competition from Asian and European
LNG consumers.
The individual LNG supply curves from the GMM LNG model are aggregated to create total North
American LNG supply curves describing LNG availability serving the North American regasification
facilities. The three point curves are converted to six points by linear interpolation to provide more supply
steps in the IPM natural gas module. Two LNG supply curves, one for winter and one for summer, are
specified for each year starting from 2015 until 2054 to capture growth as well as seasonal variation of
the LNG supplies. Figure 10-12 shows the North American LNG supply curves for the winters and
summers of 2015 and 2050.
112 Refiner Acquisition Cost of Crude Oil (RACC) is a term commonly use in discussing crude oil. It is the cost of
crude oil to the refiner, including transportation and fees. The composite cost is the weighted average of domestic
and imported crude oil costs.
10-28
-------
Figure 10-12 North American LNG Supply Curves
Winter 2015
en
I 50-
g
E 40
o 30 -
d
0 ?0
a.
ป 10
_i
0 -
c
JT
^r
J^
/
5 10 15 20 25 30
Max quantity LNG (Bcf/day)
Summer 2015
en
2 50 -
CD
o 30 -
ฐ 20 -
a.
z 10
0 -
C
.y*>*
5 10 15 20 25 30
Max quantity LNG (Bcf/day)
Winter 2050
5 10 15 20 25
Max quantity LNG (Bcf/day)
30
Summer 2050
0 5 10 15 20 25
Max quantity LNG (Bcf/day)
10.5.2 Regasification Facilities
For the EPA Base Case, 15 North American LNG regasification facilities are considered in the IPM
natural gas module. Table 10-6 lists the 15 facilities, the destination nodes where the LNG are delivered,
and the BOY 2015 capacity for each of the regasification facility. Figure 10-13 provides a map of these
facilities. Existing Penuelas LNG facilities in Puerto Rico are not included because they are not part of
the natural gas network in the IPM gas module. In EPA Base Case v.5.13. the Penuelas LNG facilities
are modeled with a fixed 150 MMcfd gas supply into Florida node and a link to connect the gas supply to
the electric generating units in Puerto Rico.
Table 10-6 North American LNG Regasification Facilities
No
1
2
3
4
5
6
7
LNG Regasification Facility
Cove Point
Elba Island
Everett
Gulf Gateway
Lake Charles
Altamira
Costa Azul
Node Location
(7) Cove Point TRANS
(9) Elba Is TRANS
(2) Everett TRANS
(69) Garden Banks
(60) Henry Hub
(51) Reynosa Imp/Exp
(84) California Mexican Exports
Beginning of Year 2015
Regasification Capacity
(Bcf/day)
1.50
2.40
0.70
0.50
2.10
1.00
2.00
10-29
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No
8
9
10
11
12
13
14
15
LNG Regasification Facility
Cameron LNG
Freeport LNG
Golden Pass
Canaport
Sabine Pass
Gulf LNG Energy LLC
Northeast Gateway
Manzanillo
Node Location
(60) Henry Hub
(65) E. TX(Katy)
(65) E. TX(Katy)
(81) Eastern Canada Demand
(60) Henry Hub
(114)SouthMS/AL
(1) New England
(51) Reynosa Imp/Exp
Beginning of Year 2015
Regasification Capacity
(Bcf/day)
1.50
1.50
2.00
1.00
2.60
1.00
0.80
0.75
Figure 10-13 North American LNG Regasification Facilities Map
(11) Canaport
6
X3) Everett
4) NE Gateway
(1) Cove Point
O
(?) Costa Azul
(10) Golden Pass
(8) Cameron LNG
\ (12) Sabin Pass O (2) Elba Island
Q13) Gulf LNG Energy
15) Lake Charles V
(9) Freeport LNG Q
(4) Gulf Gateway
O(6) Altamira
(15) ManzanilloQ
m
10.5.3 LNG Regasification Capacity Expansions
The IPM natural gas module has two constraints for the regasification capacity expansion: (1) minimum
LNG regasification facility capacity expansion and (2) maximum LNG regasification facility capacity
expansion. The values are specified for each facility and year where the minimum constraint is used to
force the model to add regasification capacity and the maximum constraint is the upper bound for the
capacity expansion.
The decision of whether to expand regasification capacity is controlled by the two constraints and by a
levelized capital cost for regasification capacity expansion. The BOY 2015 levelized capital cost for
capacity expansion (in real 2011 dollars per MMBtu of capacity expansion) is specified for each facility. A
cost multiplier can be applied to represent the increase in levelized capital cost overtime. The
10-30
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constraints for the capacity expansion can be used to turn on or off the regasification capacity expansion
feature in the model. Setting both constraints to zero will deactivate this feature.
If the regasification capacity is allowed to expand, the model can add capacity to a facility within the
minimum and maximum constraints if the cost of the regasification expansion contributes to the optimal
solution, i.e., minimizes the overall costs to the power sector, including the capital cost for adding new
regasification capacity less their revenues. The model takes into account all possible options/projects
(including regasification capacity expansions) in any year that do not violate the constraints and selects
the combination of options/projects that provide the minimum objective function value. In this way,
regasification capacity expansion projects will compete with each other and even with other projects such
as pipeline expansions, storage expansions, etc.
Due to excess LNG regasification capacity already in the system, the regasification capacity expansion
feature is not deployed in EPA Base Case v.5.13. EPA scenario results show very low total LNG
utilizations throughout the projection period because of robust natural gas supply in the U.S. and Canada
combined with a relatively low electricity demand growth assumption. The results suggest the base year
LNG regasification capacity is already high and requires no expansion.
10.6 End Use Demand
Non-power sector demand (i.e. the residential, commercial, and industrial) is modeled in the new gas
module in the form of node-level firm and interruptible demand curves113. The firm demand curves are
developed and used for residential, commercial, and some industrial sources, while the interruptible
demand curves are developed and used exclusively for industrial sources.
A three step process is used to prepare these curves for use in the IPM gas module. First, GMM is used
to develop sector specific econometric models representing the non-power sector demand. Since the
GMM econometric models are functions of weather, economic growth, price elasticity, efficiency and
technology improvements, and other factors, these drivers, in effect, are embedded in the resulting IPM
natural gas module demand curves. Second, projections are made using the GMM econometric models
and assembled into monthly gas demand curves by sector and demand node. Third, using a second
model, seasonal and load segment specific demand curves are derived from the monthly gas demand
curves. The sections below describe each of these steps in further detail.
10.6.1 Step 1: Developing Sector Specific Econometric Models of Non-Power Sector Demand
Residential/Commercial Sector
The GMM econometric models of residential and commercial demand are based on regression analysis
of historical data for 41 regions and are adjusted to reflect conservation, efficiency, and technology
changes overtime. The regional data is allocated to the node level based on population data and
information from the Energy Information Administration's "Annual Report of Natural and Supplemental
Gas Supply & Disposition" (EIA Form-176). Specifically, the econometric models used monthly
Department of Energy/Energy Information Administration (DOE/EIA) data from January 1984 through
December 2002 for the U.S. and monthly Statistics Canada data from January 1988 through December
2000 for Canada.
The GMM econometric models showed node-level residential and commercial gas demand to be a
function of heating degree days, elasticity of gas demand relative to GDP, and elasticity of gas demand
relative to gas price. The GDP elasticity was generally about 0.4 for the residential sector and 0.6 for the
commercial sector. The gas price elasticity was generally less than 0.1 for both sectors. Since gas
demand in these sectors is relatively inelastic, GDP and price changes have small effects on demand.
113 "Firm" refers to natural gas demand that is not subject to interruptions from the supplier, whereas "interruptible"
refers to natural gas demand that is subject to curtailment or cessation by the supplier.
10-31
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U.S. Industrial Sector
The GMM econometric model of U.S. industrial gas demand employed historical data for 11 census-
based regions and ten industry sectors, focusing on gas-intensive industries such as:
Food
Pulp and Paper
Petroleum Refining
Chemicals
Stone, Clay and Glass
Iron and Steel
Primary Aluminum
Other Primary Metals
Other Manufacturing
Non-Manufacturing
For each of these sectors three end-use categories (process heat, boilers, and other end uses) are
modeled separately:
Process heat: This includes all uses of gas for direct heating as opposed to indirect heating (e.g.,
steam production). The GMM econometric modeling indicated that forecasts for process heat for
each industrial sector are a function of growth in output, the energy intensity trend, and the price
elasticity. Growth in output overtime for most industries is controlled by industrial production indices.
Energy intensity is a measure of the amount of gas consumed per unit of output. Energy intensity
tends to decrease overtime as industries become more efficient.
Boilers: This category includes natural gas-fired boilers whose purpose is to meet industrial steam
demand. GMM econometric models indicated that gas demand for boilers is a function of the growth
in industrial output and the amount of gas-to-oil switching. Industry steam requirements grow based
on industrial production growth. A large percentage of the nominally "dual-fired" boilers cannot switch
due to environmental and technical constraints.
Other end uses: This category includes all other uses for gas, including non-boiler cogeneration, on-
site electricity generation, and space heating. Like the forecasts for process heat, the GMM
econometric modeling showed "other end uses" for each industrial sector to be a function of growth in
output, the energy intensity trend, and the price elasticity.
In addition to these demand models, a separate regression model was use to characterize the chemicals
sector's demand for natural gas as a feedstock for ammonia, methanol, and non-refinery hydrogen.
Growth in the chemicals industry is represented by a log-linear regression model that relates the growth
to GDP and natural gas prices. As GDP growth increases, chemical industry production increases; and
as gas prices increase, chemical industry production decreases.
The GMM econometric models for the U.S. industrial sector used DOE/EIA monthly data from January
1991 through December 2000.
Canada Industrial Sector
The industrial sector in Canada is modeled in less detail. Canada is divided into 6 regions based on
provincial boundaries. The approach employs a regression fit of historic data similar to that used in the
residential/commercial sectors. Sub-sectors of Canadian industrial demand are not modeled separately.
The Canadian industrial sector also includes power generation gas demand. The model used Statistics
Canada monthly data from January 1991 through December 2000.
10-32
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10.6.2 Step 2: Use projections based on the GMM econometric models to produce monthly gas
demand curves by sector and demand node
The regression functions resulting from the econometric exercises described in Step 1 are used to create
monthly sector- and nodal-specific gas demand curves. To do this the functions are first populated with
the macroeconomic assumptions that are consistent with those used in EPA Base Case v.5.13. Then, a
range of natural gas prices are fed into the regression functions. At each gas price the regression
functions report out projected monthly demand by sector and node. These are the GMM's nodal demand
curves.
10.6.3 Step 3: Develop non-electric sector natural gas demand curves that correspond to the
seasons and segments in the load duration curves used in IPM
A second model, the Daily Gas Load Model (DGLM), is used to create daily gas load curves based on the
GMM monthly gas demand curves obtained in Step 2. The DGLM uses the same gas demand algorithms
as the GMM, but uses a daily temperature series to generate daily variations in demand, in contrast to the
seasonal variations in gas demand that are obtained from the GMM.
The resulting daily nodal demand data for each non-power demand sector are then re-aggregated into
the two gas demand categories used in the IPM gas module: all of the residential and commercial
demand plus 10% of the industrial demand is allocated to the firm gas demand curves, and the remaining
90% of the industrial demand is allocated to the interruptible gas demand curves.
IPM, the power sector model, has to take into account natural gas demand faced by electric generating
units that dispatch in different segments of the load duration curves, since demand for natural gas and its
resulting price may be very different for units dispatching in the peak load segment than it is for units
dispatching in the base, high shoulder, mid shoulder, or low shoulder load segments. In addition, since
seasonal differences in demand can be significant, IPM requires separate load segment demand data for
each season that is modeled. In EPA Base Case v.5.13, there are two seasons: Summer (May 1 -
September 30) and winter (October 1 - April 30). Therefore, the firm and interruptible daily gas demand
and associated prices are allocated to the summer and winter load segment based on the applicable
season and prevailing load conditions to produce the final non-electric sector gas demand curves that are
used in IPM.
In EPA Base Case v.5.13, each of the summer and winter periods uses 6 load segments for pre-2030
and 4 load segments for post-2030 as shown in Table 10-7. The "Peak" load segment in post-2030 is an
aggregate of "Needle Peak" and "Near Peak" load segments in the pre-2030. The "High Shoulder" load
segment in post-2030 is an aggregate of "High Shoulder" and "Middle Shoulder" load segments in the
pre-2030. The same definitions of "Low Shoulder" and "Base" load segments are applied to both pre-
2030 and post-2030. Input data for firm and interruptible demand curves are specified for all six load
segments listed in the pre-2030 column of Table 10-7.
Table 10-7 Summer and Winter Load Segments in EPA Base Case v.5.13
Pre 2030
1
2
3
4
5
6
Needle Peak
Near Peak
High Shoulder
Middle Shoulder
Low Shoulder
Base
Post 2030
1
2
3
4
Peak
High Shoulder
Low Shoulder
Base
Aggregation of summer and winter load segments from six in the pre-2030 to four in the post-2030 is
performed endogenously in the model.
10-33
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The non-electric sector demand curves (firm and interruptible) are generated based on GMM regressions
described above with macroeconomic assumptions consistent with those of EPA Base Case v.5.13. A
set of firm and interruptible gas demand curves is generated for each node and year. Examples of node-
specific firm and interruptible demand curves, for summer and winter load segments are shown in Figure
10-14 and Figure 10-15. Figure 10-14 is very inelastic; only a small fraction of demand is shed as prices
increase. The interruptible gas demand in the peak segments is also very inelastic as expected with
higher elasticities in the shoulder and base load segments.
It is important to note that the non-electric gas demand curves provided to the IPM/Gas model are static
inputs. The implied elasticities in the curves represent short-term elasticities based on EPA Base Case
v.5.13 macroeconomic assumptions. Long-term elasticity is not factored into the gas demand curves. In
other words, changes in the assumptions that affect the price/volume solutions have no effect to the long-
term gas demand elasticity assumed here.
Figure 10-14 Examples of Firm Demand Curves by Electric Load Segment
8
D.
$
New England (Node 1), Winter 2015
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Figure 10-15 Examples of Interruptible Demand Curves by Electric Load Segment
New England (Node 1), Winter 2015
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10-34
-------
10.6.4 The Use of Firm Gas Demand to Represent LNG Exports
As described earlier, the gas module does not currently have a specific sub-module for LNG exports. In
the EPA Base Case v.5.13, the LNG exports are treated as firm demand in the form of fixed or inelastic
firm demand curves. Three additional demand nodes are added to represent the three LNG export
terminals, two in the U.S. Gulf Coast and one in Western Canada. The U.S. Gulf Coast LNG nodes are
linked to nodes (60) Henry Hub and (65) E. TX (Katy) and the Western Canada LNG export node is linked
to node (72) North British Columbia. The assumptions for LNG exports from the U.S. Gulf Coast, starting
from 2016, are adapted from AEO 2013. The assumptions for LNG exports from Western Canada,
starting from 2017, are derived from GMM LNG Model. Figure 10-16 shows LNG exports projection from
the U.S. and Canada.
Figure 10-16 LNG Export Assumptions in EPA Base Case v.5.13.
1.800
1.600
1.400
1,200
1.000
O
800
GOO
400
200
2010
2020
2030
2040
2050
2060
U.S. Gulf Coast
Western Canada
10.7 Pipeline Network
10.7.1 Network Structure
The pipeline network in the IPM natural gas module represents major transmission corridors (not
individual pipelines) throughout North America. It contains 380114 gas pipeline corridors (including bi-
directional links) between the 118 nodes (Figure 10-3). Each corridor is characterized by maximum
capacity and a "value of service" (discount curve) relationship that determines the market value of
capacity as a function of load factor.115 The node structure is developed to reflect points of change or
influence on the pipeline system such as:
Major demand and supply centers
Pipeline Hubs and market centers
Points of divergence in pipeline corridors
To illustrate the relationship of corridors and pipelines, Figure 10-17 shows the flow and capacity of five
pipeline corridors in New England in 2020. Gas flows into New England along three pipeline corridors
115
Excluding LNG import Terminal nodes and their pipeline connections.
See footnote 88 above for a definition of "load factor."
10-35
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(indicated in Figure 10-17 by 3 of the 4 arrows that point into the region) representing a total of seven
pipeline systems (indicated by name labels in Figure 10-17). New England also receives gas via the
Everett LNG terminal (indicated in Figure 10-17 by the 4th arrow that points into the region). Also, some
of the gas that flows into New England on the Iroquois system flows through the region and back to
downstate New York; this is represented on the map as an export from New England (indicated in Figure
10-17 by the arrow that points away from the region).
Figure 10-17 New England Pipeline Corridors in 2020
aritimes & Northeast
Portland Natural Gas
Granite State
1 Vermont Gas
1 Algonquin
Iroquois
Tennessee
10.7.2 Pipeline Transportation Costs
In the IPM natural gas module, the natural gas moves over the pipeline network at variable cost. The
variable cost as a function pipeline throughput (or pipeline discount curve) is used to determine
transportation basis116 (i.e., the market value of capacity) for each period in the forecast for each pipeline
link. The 4-point pipeline discount curves in the IPM natural gas module are simplified forms of the more
robust continuous discount curves from the GMM pipeline module. The GMM pipeline discount curves
have been derived in the course of extensive work to calibrate the model to actual history. The curves
have been fit to basis differentials observed from actual gas prices and to annual load factors from
pipeline electronic bulletin boards via Lippman Consulting, Inc.
The GMM continuous discount curves are converted to 4-point linear curves for the IPM natural gas
module capturing deflection points in the GMM discount curves. Figure 10-18 depicts the BOY 2015
discount curve for the pipeline corridor connecting nodes (61) North Louisiana Hub and (18)
Tennessee/Kentucky. Cost growth factors shown in
116
In natural gas discussions "basis" refers to differences in the price of natural gas in two different geographical
locations. In the marketplace "basis" typically means the difference between the NYMEX futures price at the Henry
Hub and the cash price at other market points. In the modeling context "basis" means the difference in natural gas
prices between any two nodes at the same instance in time.
10-36
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Figure 10-19 are applied to the pipeline discount curves to reflect cost increase overtime. The cost is
assumed to grow at an average rate of 0.5 percent per year.
Figure 10-18 Example Pipeline Discount Curve
1.00
QQ
> 0.00
NLAHub(61)toTN/KY(18)
20% 40% 60% 80%
Pipeline Utilization (%)
100%
Figure 10-19 Pipeline Cost Growth Factor
1.30
1.25
1.20
1.00
2010
2020
2030
2040
2050
20GO
10.7.3 Pipeline Capacity Expansion Logic
Initial pipeline capacity, derived from GMM, includes existing capacities and planned capacities that are
expected to be operational from the beginning of 2015. The IPM natural gas module has the capability to
endogenously expand the pipeline capacity. The decision of whether to expand pipeline capacity is
controlled by two constraints, which stipulate minimum and maximum capacity additions and by the
levelized capital cost of expanding pipeline capacity in the specific corridor and year. The minimum
capacity addition constraint forces the model to add capacity in a specified corridor and year. The
10-37
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maximum capacity constraint is the upper bound on capacity additions in a specified corridor and year.
For most pipeline corridors there is no minimum or maximum capacity requirement, and so they are
assigned a value of zero as their minimum capacity addition requirement and infinity117 as their maximum
capacity addition requirement. Where this occurs, the pipeline expansion is only controlled by the
pipeline capital cost.
The model is allowed to add capacity to a pipeline corridor within the minimum and maximum capacity
addition constraints if the cost of the pipeline expansion contributes to the optimal solution, i.e., minimizes
the overall costs to the power sector, including the capital cost for pipeline capacity expansion, less their
revenues. The model takes into account all possible options/projects including capacity additions for
pipeline corridors in any year that do not violate the constraints and selects the combination of
options/projects that provide the minimum objective function. In this way, pipeline corridor expansion
projects will compete with each other and even with other projects such as LNG regasification capacity
expansions, storage expansions, etc.
For EPA Base Case v.5.13, pipeline corridors connecting North Alaska (node 89) and Mackenzie Delta
(node 86) to North British Columbia (node 72) have the minimum and maximum capacity addition
constraints. Due to uncertainties of these pipeline projects as discussed in Section 3, the North Alaska
and Mackenzie Delta pipeline projects are not made available throughout the projection. Both capacity
addition constraints for North Alaska and Mackenzie delta pipeline corridors are set to zero.
Expansions in other pipeline corridors are not restricted. The model is allowed to build capacity to any
pipeline corridors at anytime as long as it contributes to minimization of the objective function.
The BOY 2015 levelized pipeline capital cost (in real 2011 dollars per MMBtu/Day of pipeline capacity
addition) is specified for each of the 380 pipeline links. The cost growth factors shown in
Figure 10-19 are applied to derive the cost increase overtime. The average levelized capital cost for
pipeline capacity expansion for 2015 is $165 per MMBtu/Day.
10.8 Gas Storage
The IPM natural gas module has 118 underground storage facilities that are linked to 51 nodes. The
underground storage is grouped into three categories based on storage "Days Service."118
"20-Day" high deliverability storage - 37 storage facilities
"80-Day" depleted/aquifer reservoirs - 41 storage facilities
"Over 80 Days" depleted/aquifer reservoirs - 40 storage facilities
The model also includes existing and potential LNG peak shaving storage facilities. The existing facilities
are linked to 24 nodes with allocations based on historical capacity data. There are 48 other nodes that
are linked to LNG peakshaving storage. These facilities do not currently have capacity but are included in
the storage database for the purpose of future expansion. The map of storage facility locations is shown
in Figure 10-6 and the list of storage facility nodes is shown in
Table 10-8.
In
Table 10-8 an X in columns 2 ("20-Day"), 3 ("80-Day"), or 4 ("Over 80-Days") represents an underground
storage facility. There are 118 such X's which correspond to the 118 underground storage facilities noted
117 In the model this is achieved by assigning a large number, e.g., 100 Bcfd, for every year where there is no
constraint on maximum capacity.
118 See footnote 90 above for a definition of "Days Service."
10-38
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in the previous paragraph. These 118 X's appear in 51 rows, which represent the linked nodes noted in
the previous paragraph. The identities of these nodes are found in column 1 ("Node"). Similarly, 24 X's
in columns 5 ("Existing") represent the 24 existing LNG peakshaving facilities and 48 X's in column 6
("Potential") represent the 48 prospective LNG storage facilities.
Table 10-8 List of Storage Nodes
Node
(1) New England
(3) Quebec
(4) New York City
(5) Niagara
(6) Southwest PA
(8) Georgia
(10) South Florida
(11) East Ohio
(12) Maumee/Defiance
(13) Lebanon
(14) Indiana
(15) South Illinois
(16) North Illinois
(17) Southeast Michigan
(18)EastKY/TN
(19)MD/DC/Northern VA
(20) Wisconsin
(21) Northern Missouri
(22) Minnesota
(23) Crystal Falls
(24) Ventura
(26) Nebraska
(28) Kansas
(29) East Colorado
(30) Opal
(31) Cheyenne
(32) San Juan Basin
(33) EPNG/TW
(34) North Wyoming
(35) South Nevada
(36) SOCAL Area
(38) PGE Area
(41) Montana/North Dakota
(45) Pacific Northwest
(46) NPC/PGT Hub
(47) North Nevada
(48) Idaho
(54) North Alabama
(56) North Mississippi
(58) Eastern Louisiana Hub
(60) Henry Hub
Underground Storage Facility
20-Day
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
80-Day
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Over 80 Days
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
LNG Peakshaving Facility
Existing
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Potential
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
10-39
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Node
(61) North Louisiana Hub
(63) Southwest Texas
(64) Dallas/Ft Worth
(65) E. TX (Katy)
(66) S. TX
(68) NW TX
(72) North British Columbia
(73) South British Columbia
(74) Caroline
(76) Saskatchewan
(77) Manitoba
(78) Dawn
(79) Philadelphia
(80) West Virginia
(81) Eastern Canada Demand
(83) Wind River Basin
(92) Southwest VA
(93) Southeast VA
(94) North Carolina
(95) South Carolina
(96) North Florida
(97) Arizona
(98) Southwest Michigan
(99) Northern Michigan
(1 03) SDG&E Demand
(104) Eastern New York
(105) New Jersey
(106) Toronto
(107) Carthage
(108) Southwest Oklahoma
(109) Northeast Oklahoma
(110) Southeastern Oklahoma
(111) Northern Arkansas
(112) Southeast Missouri
(113) Uinta/Piceance
(11 4) South MS/AL
(115)WestKY/TN
(11 7) Northeast PA
(118)Leidy
Underground Storage Facility
20-Day
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
80-Day
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Over 80 Days
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
LNG Peakshaving Facility
Existing
X
X
X
X
X
X
X
X
Potential
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
10.8.1 Storage Capacity and Injection/Withdrawal Constraints
The expected working gas capacity as of BOY 2015 by location and storage type is obtained from the
GMM as are injection and withdrawals rates. These serve as inputs to the IPM gas module, which uses
them to endogenously derive gas storage withdrawals, injections, storage expansions, and associated
costs. To give a sense of the BOY 2015 GMM storage input assumption in the IPM gas module, Table
10-9 shows the total working gas capacity and the average daily injection and withdrawal rates as
percentage of working gas capacity for the four types of storage. Note that these are aggregated values
10-40
-------
(i.e., totals and averages); the actual GMM BOY 2015 inputs to the IPM gas module vary by location and
storage type.
Table 10-9 Storage Capacity and Injection/Withdrawal Rates (BOY 2015)
Underground Storage
20 Day
80 Day
Over 80 Days
Total
LNG Peakshaving Storage
Working Gas
Capacity (Bcf)
622
3,522
1,235
5,379
84
Average Daily Injection Rate
(Percent of WG Capacity)
6.3%
1.4%
0.6%
0.4%
Average Daily Withdrawal
Rate (Percent of WG Capacity)
9.6%
2.3%
1.0%
12.5%
10.8.2 Variable Cost and Fuel Use
In the IPM natural gas module, the natural gas is injected to storage or withdrawn from storage at variable
cost. The BOY 2015 variable cost or commodity119 charge for underground storage facilities is assumed
to be 1.6 cents/MMBtu (in real 2011 dollars) and is the same for all underground storage nodes and
types. The variable cost for LNG peakshaving facility is much higher at 37.4 cents/MMBtu as it includes
variable costs for gas liquefaction (in gas injection cycle) and LNG regasification (in gas withdrawal cycle).
The variable cost is assumed to be the same for all LNG peakshaving nodes. A storage cost growth
factor shown in Figure 10-20 is applied to the injection/withdrawal cost to reflect cost increase overtime.
The cost is assumed to grow at an average rate of 0.5 percent per year.
Figure 10-20 Storage Cost Growth Factor
1.30
1.25
1.20
1.15
1.00
2010
2020
2030
2040
2050
20GO
Storage commodity (variable) charge is generally a charge per unit of gas injected and/or withdrawn from storage
as per the rights and obligations pertaining to a gas storage lease. Analogous to commodity charges for gas pipeline
service
10-41
-------
Fuel use for injection and withdrawal for underground storage is 1% of the gas throughput. The
withdrawal fuel use for the LNG peakshaving storage is also 1% but the injection fuel use is much higher
at 11% of the injection gas as it includes fuel use for gas liquefaction.
10.8.3 Storage Capacity Expansion Logic
The endogenous modeling decision of whether to expand working gas storage capacity is controlled by
two constraints, which stipulate minimum and maximum capacity additions for each storage facility and
year, and by the levelized capital cost of the storage expansion. The two constraints are specified as
input data for each storage facility and year. The minimum constraint forces the model to add working
gas capacity to the specified facility and year and the maximum constraint is the cap for the expansion.
Figure 10-21 shows projected maximum storage expansion constraints for the "80-day" category storage
facility in supply area Katy, Texas.
Figure 10-21 Example Maximum Storage Capacity Expansion
Storage category: "80-day"
Supply area: Katy, Texas
fin
*iO
4n -
*B Tn -
ฃ JU
?n
in
n
/
, /
/
2010 2020 2030 2040 2050 2060
The model is allowed to add working gas capacity to a storage facility within the two constraints if the cost
of storage expansion contributes to the optimal solution, i.e., minimizes the overall costs to the power
sector, including the capital cost for working gas capacity expansion less their revenues. The model
takes into account all possible options/projects including working gas capacity additions for storage
facilities in any year that do not violate the constraints and selects the combination of options/projects that
provide the minimum objective function value. In this way, storage capacity expansion projects will
compete with each other and even with other projects such as LNG regasification capacity expansions,
pipeline expansions, etc.
The BOY 2015 levelized storage capital cost (in real 2011 dollars per MMBtu of storage capacity addition)
is specified for each of the 190 storage facilities. Table 10-10 lists the average BOY 2015 levelized
storage capital cost for the four types of storage facility. Amongst the underground storage facilities the
higher capital costs represent more storage cycles120 that could be achieved in a year. On average, the
capital costs for the "80-Day" and "20-Day" storage facilities are assumed to be about 20 percent and 40
One storage cycle is the theoretical time required to completely inject and withdraw the working gas quantity for
any given underground gas storage facility or the turnover time for the working gas capacity rating of the facility. The
cycle rate of any storage facility is usually expressed in cycles per year and is the number of times the working gas
volumes can theoretically be turned over each storage year. The cycle rating for Porous Storage varies from 1 to 6
per year while that for Salt Cavern Storage are as high as 12 per year.
10-42
-------
percent, respectively, higher than that of the "Over 80 Days" storage facility. The levelized capital cost for
LNG peakshaving storage is much higher due to higher capital cost for the liquefaction unit. The cost
growth factors shown in Figure 10-20 are applied to the capital cost to derive the cost increase overtime.
The capital cost is assumed to grow at an average rate of 0.5 percent per year.
Table 10-10 Base Year 2015 Average Levelized Storage Capital Cost
Storage Type
Underground Storage
20-Day
80-Day
Over 80 Days
LNG Peakshaving Storage
Average Levelized
Storage Capital Cost
(2011 $/MMBtu)
1.19
0.99
0.83
5.34
10.9 Fuel Prices
10.9.1 Crude Oil and Natural Gas Liquids Prices
Since a fraction of the hydrocarbons produced in the natural gas exploration and development process
are crude oil and NGLs (see columns 2 and 3 in Table 10-5), revenues from crude oil and NGL
production play a key role in determining the extent of exploration and development for natural gas. To
take into account these revenues, crude oil and NGL price projections are provided as inputs to the IPM
natural gas module and factored into the calculation of costs in the IPM objective function.
The crude oil and NGL price projections used in the IPM natural gas module are shown in Figure 10-22.
These price projections were adapted from AEO 2013. No attempt was made to project prices beyond
2040 other than to assume that prices remain at their 2040 levels. The projected prices shown in Figure
10-22 are expressed in units of 2011$ per MMBtu. Using a crude oil Btu content of 5.8 MMBtu/Bbl, the
projected crude oil prices in Figure 10-22 can be translated into the more familiar units of dollars per
barrel (Bbl), in which case, prices in this figure are equivalent to $93/Bbl in 2015, $102/Bbl in 2020,
$126/Bbl in 2020, and constant at $155/Bbl from 2040 (in real 2011 dollars) onward.
Figure 10-22 Crude Oil and NGL Prices
10-43
-------
30.00
25.00
20.00
15.00
-------
Term
Basis
Decline curve
Depleted reservoir storage
Dry gas
Ethane rejection
Firm and interruptible demand
High deliverability storage
Lease and plant use
Liquefied Natural Gas (LNG)
LNG peakshaving facility
Load factor
Natural gas liquids (NGL)
Definition
In natural gas discussions "basis" refers to differences in the price of natural
gas in two different geographical locations. In the marketplace "basis"
typically means the difference between the NYMEX futures price at the Henry
Hub and the cash price at other market points. In the modeling context
"basis" means the difference in natural gas prices between any two nodes at
the same instance in time.
A decline curve is a plot of the rate of gas production against time. Since the
production rate decline is associated with pressure decreases from oil and
gas production, the curve tends to smoothly decline from a high early
production rate to lower later production rate. Exponential, harmonic, and
hyperbolic equations are typically used to represent the decline curve.
A gas or oil reservoir that is converted for gas storage operations. Its
economically recoverable reserves have usually been nearly or completely
produced prior to the conversion.
Natural gas is a combustible mixture of hydrocarbon gases. Although
consisting primarily of methane, the composition of natural gas can vary
widely to include propane, butane, ethane, and pentane. Natural gas is
referred to as 'dry' when it is almost pure methane, having had most of the
other commonly associated hydrocarbons removed. When other
hydrocarbons are present, the natural gas is called 'wet'.
Ethane rejection occurs when the ethane component in the natural gas
stream is not recovered in a gas processing plant but left in the marketable
natural gas stream. Ethane rejection is deployed when the value of ethane is
worth more in the gas stream than as an a separate commodity or as a
component of natural gas liquids (NGL), which collectively refers to ethane,
propane, normal butane, isobutane, and pentanes in processed and purified
finished form. Information that characterizes ethane rejection by region can
play a role in determining the production level and cost of natural gas by
region.
"Firm" refers to natural gas demand that is not subject to interruptions from
the supplier, whereas "interruptible" refers to natural gas demand that is
subject to curtailment or cessation by the supplier.
High deliverability storage is depleted reservoir storage facility or Salt Cavern
storage whose design allows a relatively quick turnover of the working gas
capacity.
Natural gas for "lease and plant use" refers to the gas used in well, field, and
lease operations (such as gas used in drilling operations, heaters,
dehydrators, and field compressors) and as fuel in gas processing plants.
LNG is natural gas converted to liquid form by cooling it down to about -260ฐ
F. Known as liquefaction, the cooling process is performed in an "LNG train"
(the liquefaction and purification facilities in LNG plants), which reduces the
gas to 1/600th of its original volume. The volume reduction resulting from
liquefaction makes it cost effective to transport the LNG over long distances,
typically by specially designed, double-hulled ships known as LNG carriers.
Once the carriers reach their import terminal destination, the LNG is
transferred in liquid form to specially designed storage tanks. When needed
for customers, the LNG is warmed back to a gaseous state in a regasification
facility and transported to its final destination by pipelines.
LNG peakshaving facilities supplement deliveries of natural gas during times
of peak periods. LNG peak shaving facilities have a regasification unit
attached, but may or may not have a liquefaction unit. Facilities without a
liquefaction unit depend upon tank trucks to bring LNG from nearby sources.
In the natural gas context "load factor" refers to the percentage of the pipeline
capacity that is utilized at a given time.
Those hydrocarbons in natural gas that are separated from the gas as liquids
in gas processing or cycling plants. Generally such liquids consist of ethane,
propane, butane, and heavier hydrocarbons.
10-45
-------
Term
Play
Pool
Proven (or proved)
RACC price
Raw gas
Reserves-to-production (R/P) ratio
Resource and reserves
Resource appreciation
Storage "Days Service"
Storage commodity charge
Storage cycle
Definition
A "play" refers to a set of known or postulated natural gas (or oil)
accumulations sharing similar geologic, geographic, and temporal properties,
such as source rock, migration pathway, timing, trapping mechanism, and
hydrocarbon type.
A "pool" is a subsurface accumulation of oil and other hydrocarbons. Pools
are not necessarily big caverns. They can be small oil-filled pores. A "field" is
an accumulation of hydrocarbons in the subsurface of sufficient size to be of
economic interest. Afield can consist of one or more pools.
The term "proven" refers to the estimation of the quantities of natural gas
resources that analysis of geological and engineering data demonstrate with
reasonable certainty to be recoverable in future years from known reservoirs
under existing economic and operating conditions. Among the factors
considered are drilling results, production, and historical trends. Proven
reserves are the most certain portion of the resource base.
Refiner Acquisition Cost of Crude Oil (RACC) is a term commonly use in
discussing crude oil. It is the cost of crude oil to the refiner, including
transportation and fees. The composite cost is the weighted average of
domestic and imported crude oil costs.
Raw gas production refers to the volumes of natural gas extracted from
underground sources, whereas net gas production refers to the volume of
purified, marketable natural gas leaving the natural gas processing plant.
Reserves-to-production ratio is the remaining amount of reserves, expressed
in years, to be produced with a current annual production rate.
When referring to natural gas a distinction is made between "resources" and
"reserves." "Resources" are concentrations of natural gas that are or may
become of potential economic interest. "Reserves" are that part of the natural
gas resource that has been fully evaluated and determined to be
commercially viable to produce.
Resource appreciation represents growth in ultimate resource estimates
attributed to success in extracting resource from known plays such as natural
gas from shales, coal seams, offshore deepwater, and gas hydrates that are
not included in the resource base estimates.
Storage "Days Service" refers to the number of days required to completely
withdraw the maximum working gas inventory associated with an
underground storage facility.
Storage commodity (variable) charge is generally a charge per unit of gas
injected and/or with drawn from storage as per the rights and obligations
pertaining to a gas storage lease. Analogous to commodity charges for gas
pipeline service
One storage cycle is the theoretical time required to completely inject and
withdraw the working gas quantity for any given underground gas storage
facility or the turnover time for the working gas capacity rating of the facility.
The cycle rate of any storage facility is usually expressed in cycles per year
and is the number of times the working gas volumes can theoretically be
turned over each storage year. The cycle rating for Porous Storage varies
from 1 to 6 per year while that for Salt Cavern Storage are as high as 12 per
year.
10-46
-------
Term
Unconventional gas
Underground storage
Wet gas
Working gas
Definition
Unconventional gas refers to natural gas found in geological environments
that differ from conventional hydrocarbon traps. It includes: (a) "tight gas,"
i.e., natural gas found in relatively impermeable (very low porosity and
permeability) sandstone and carbonate rocks; (b) "shale gas," i.e., natural gas
in the joints, fractures or the matrix of shales, the most prevalent low
permeability low porosity sedimentary rock on earth; and (c) "coal bed
methane," which refers to methane (the key component of natural gas) found
in coal seams, where it was generated during coal formation and contained in
the microstructure of coal. Unconventional natural gas is distinguished from
conventional gas which is extracted using traditional methods, typically from a
well drilled into a geological formation exploiting natural subsurface pressure
or artificial lifting to bring the gas and associated hydrocarbons to the
wellhead at the surface.
The underground storage of natural gas in a porous and permeable rock
formation topped by an impermeable cap rock, the pore space of which was
originally filled with water.
A mixture of hydrocarbon compounds and small quantities of various
nonhydrocarbons existing in the gaseous phase or in solution with crude oil in
porous rock formations at reservoir conditions. The principal hydrocarbons
normally contained in the mixture are methane, ethane, propane, butane, and
pentane. Typical nonhydrocarbon gases that may be present in reservoir
natural gas are water vapor, carbon dioxide, hydrogen sulfide, nitrogen and
trace amounts of helium.
The term "working gas" refers to natural gas that has been injected into an
underground storage facility and stored therein temporarily with the intention
of withdrawing it. It is distinguished from "base (or cushion) gas" which refers
to the volume of gas that remains permanently in the storage reservoir in
order to maintain adequate pressure and deliverability rates throughout the
withdrawal season.
10-47
-------
11. Other Fuels and Fuel Emission Factor Assumptions
Besides coal (chapter 9) and natural gas (chapter 10), EPA Base Case v.5.13 also includes assumptions
for residual fuel oil, distillate fuel oil, biomass, nuclear fuels, and various waste fuels. The assumptions
described in this chapter pertain to fuel characteristics, fuel market structures, and fuel prices for these
fuels. As seen in the previous chapter, there is an endogenous resource costing model for natural gas
built into EPA Base Case v.5.13. Coal is represented via an elaborate set of supply curves and a detailed
representation of the associated coal transport network. Together they are designed to capture the
intricacies of the resource base and market for these fuels which accounted for about 68% of U.S. electric
generation in 2012. As with coal, the price and quantity of biomass combusted is determined by balancing
supply and demand using a set of geographically differentiated supply curves. In contrast, fuel oil and
nuclear fuel prices are exogenously determined and entered into IPM during model set-up as constant
price points which apply to all levels of supply. Generally, the waste fuels are also modeled using price
points. In this chapter each of the remaining fuels is treated in turn. The chapter concludes with a
discussion of the emission factors for all the fuels represented in EPA Base Case v.5.13.
11.1 Fuel Oil
Two petroleum derived fuels are included in EPA Base Case v.5.13. As its name implies distillate fuel oil
is distilled from crude oil, whereas residual fuel oil is left as a residue of the distillation process. The fuel
oil prices in EPA Base Case v.5.13 are from AEO 2013 and are shown in Table 11-1. They are regionally
differentiated according to the NEMS (National Energy Modeling System) regions used in AEO 2013 and
are mapped to their corresponding IPM regions for use in EPA Base Case v.5.13.
Table 11-1 Fuel Oil Prices by NEMS Region in EPA Base Case v.5.13
NEMS Region
ERCT
FRCC
MROE
MROW
NEWE
NYCW
NYLI
NYUP
RFCE
RFCM
RFCW
SRDA
SRGW
SRSE
SRCE
SRVC
SPNO
SPSO
AZNM
CAMX
NWPP
RMPA
2016
21.94
16.93
83.45
20.32
11.00
12.29
12.29
12.29
15.05
92.33
84.13
20.92
83.45
16.09
82.14
16.09
20.32
21.94
21.94
10.31
24.78
83.91
Residual Fuel
2018
26.06
21.06
87.58
24.45
11.65
12.94
12.94
12.94
16.02
96.45
88.26
25.05
87.58
20.22
86.26
16.74
24.45
26.06
26.06
14.44
25.46
88.03
Oil Prices
2020
30.09
25.09
91.61
28.48
12.27
13.56
13.56
13.56
16.63
100.48
92.29
29.08
91.61
24.25
90.29
17.36
28.48
30.09
30.09
18.47
26.07
92.06
(2011$/MMBtu)
2025
41.37
36.37
102.89
39.76
14.04
15.33
15.33
15.33
19.13
111.76
103.57
40.36
102.89
35.53
101.57
19.13
39.76
41.37
41.37
29.75
28.17
103.34
2030
53.54
48.54
115.05
51.92
24.33
17.50
17.50
17.50
21.30
123.93
115.73
52.52
115.05
47.69
113.74
31.30
51.92
53.54
53.54
41.91
30.15
115.51
2040 - 2050
82.89
77.88
144.40
81.27
23.74
22.14
22.14
22.14
25.94
153.28
145.08
81.87
144.40
77.04
143.09
60.65
81.27
82.89
82.89
71.26
34.93
144.86
11-1
-------
NEMS Region
ERCT
FRCC
MROE
MROW
NEWE
NYCW
NYLI
NYUP
RFCE
RFCM
RFCW
SRDA
SRGW
SRSE
SRCE
SRVC
SPNO
SPSO
AZNM
CAMX
NWPP
RMPA
2016
21.40
21.56
20.44
20.09
21.17
20.36
20.36
20.36
20.74
20.44
20.67
21.40
20.40
21.32
20.92
21.56
20.07
21.31
22.08
21.76
21.68
22.08
Distillate Fuel
2018
22.17
22.35
21.23
20.90
21.96
21.15
21.15
21.15
21.53
21.23
21.46
22.17
21.19
22.08
21.70
22.35
20.86
22.08
23.01
22.75
22.61
23.01
Oil Prices
2020
22.96
23.13
22.01
21.69
22.75
21.93
21.93
21.93
22.33
22.01
22.25
22.96
21.97
22.86
22.48
23.13
21.64
22.87
23.73
23.47
23.41
23.73
(2011$/MMBtu)
2025
25.13
25.29
24.18
23.85
24.91
24.09
24.09
24.09
24.48
24.18
24.41
25.13
24.14
25.03
24.64
25.29
23.80
25.04
25.88
25.62
25.55
25.88
2030
27.30
27.46
26.43
26.04
27.08
26.26
26.26
26.26
26.68
26.43
26.63
27.30
26.38
27.19
26.83
27.46
25.98
27.21
28.13
27.87
27.81
28.13
2040 - 2050
32.56
32.72
31.68
31.30
32.34
31.52
31.52
31.52
31.94
31.68
31.89
32.56
31.63
32.46
32.09
32.72
31.25
32.47
33.29
33.02
32.97
33.29
11.2 Biomass
Biomass is offered as a fuel for existing dedicated biomass power plants and potential (new) biomass
direct fired boilers. In addition to its use as the prime mover fuel for these plants, it is also offered for co-
firing to all coal fired power plants. (See section 5.3 for a discussion of the representation of biomass co-
firing in EPA Base Case v.5.13.)
EPA Base Case v.5.13 uses biomass supply curves based on those in AEO 2013. These NEMS-coal
demand region level supply curves are translated into state-level supply curves for use in EPA Base Case
v.5.13 using proportions developed from agricultural statistic district (ASD) level intermediate AEO 2011
biomass supply curves. Plants demand biomass from the supply curve corresponding to the state in
which they are located. No inter-state trading of biomass is allowed. Each biomass supply curve depicts
the price-quantity relationship for biomass and varies overtime. There is a separate curve for each model
run year. Each supply curve contains 74 price steps for each run year. The supply component of the
curve represents the aggregate supply in each state of four types of biomass fuels: urban wood waste
and mill residue, public forestry residue, private forestry residue and agricultural residue121. The price
component of the curve includes transportation costs, which AEO122 assumed to be $121 dry ton for all
four biomass types in all states. The supply curves represent the state-specific delivered biomass fuel
cost at the plant gate. IPM adds a storage cost of $20/dry ton to each step of the agricultural residue
supply curves to reflect the limited agricultural growing season
123
121 The AEO 2013 biomass supply is described in the NEMS Renewable Fuels Module documentation,
http://www.eia.qov/forecasts/aeo/assumptions/pdf/renewable.pdf
122 http://www.eia.qov/forecasts/aeo/nems/documentation/renewable/pdf/m069(2013).pdf. p. 83.
123 http://www.extension.iastate.edu/aqdm/crops/pdf/a1-22.pdf.
http://www.rand.org/content/dam/rand/pubs/technical reports/2011/RAND TR876.pdf
11-2
-------
Excerpt from Table 11-2 Biomass Supply Curves in EPA Base Case v.5.13
This is a small excerpt of the data in Excerpt from Table 11-2. The complete data set in spreadsheet
format can be downloaded via the link found at www.epa.gov/airmarkets/progsregs/epa-
ipm/BaseCasev513.html
Year
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
Biomass Supply Region
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
Step Name
BM01
BM02
BM03
BM04
BM05
BM06
BM07
BM08
BM09
BM10
BM11
BM12
BM13
BM14
BM15
BM16
BM17
BM18
BM19
BM20
BM21
BM22
BM23
BM24
BM25
BM26
BM27
BM28
BM29
BM30
BM31
BM32
BM33
BM34
BM35
BM36
BM37
BM38
BM39
BM40
BM41
BM42
BM43
BM44
BM45
BM46
BM47
BM48
Cost of Production
(2011$/MMBtu)
0
1.42
1.74
2.06
2.38
2.71
3.03
3.35
3.67
3.79
4.00
4.13
4.32
4.48
4.64
4.82
4.96
5.16
5.28
5.51
5.61
5.85
5.93
6.19
6.25
6.54
6.57
6.88
6.89
7.22
7.22
7.54
7.57
7.86
7.91
8.18
8.25
8.51
8.60
8.83
8.94
9.15
9.28
9.47
9.62
9.79
9.97
10.12
Biomass Production
(TBtu/Year)
0
0.87
0
25.12
0
29
0
2.44
0
0
2.78
0.23
0
2.59
3.83
0.89
0
0.28
9.94
0.24
0
0.53
18.47
0.13
0.74
0
0.74
0
0.74
0.74
0.14
0.74
0.07
0.74
0.10
0.74
0
0.74
0
0.74
0
0.74
0.28
0.74
0
0.74
0
0.74
11-3
-------
Year
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
2016
Biomass Supply Region
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
Step Name
BM49
BM50
BM51
BM52
BM53
BM54
BM55
BM56
BM57
BM58
BM59
BM60
BM61
BM62
BM63
BM64
BM65
BM66
BM67
BM68
BM69
BM70
BM71
BM72
BM73
BM74
Cost of Production
(2011$/MMBtu)
10.31
10.44
10.65
10.76
11.00
11.08
11.34
11.41
11.68
11.73
12.03
12.05
12.37
12.37
12.69
13.02
13.34
13.66
13.98
14.31
14.63
14.95
15.27
15.59
15.92
16.24
Biomass Production
(TBtu/Year)
0
0.74
0
0.74
0
0.74
0
0.74
0.13
0.74
0
0.74
0
0.74
0.74
0.74
0.74
0.74
0.74
0.74
0.74
0.74
0.74
0.74
0.74
0.74
The supply curves in Excerpt from Table 11-2 represent the biomass available to both the electric and
non-electric sectors. In any given region at any point in time the power sector demand from IPM has to be
combined with the non-electric sector demand for biomass to obtain the price faced by the power sector.
The non-electric sector demand distribution is by census division based on AEO 2013. Table 11-3 shows
the non-electric sector demand by run year and census divisions.
Table 11-3 Non-Electric Biomass Demand by Census Division in EPA Base Case v.5.13
Non-Electric Biomass
1
2
3
4
5
6
7
8
9
Census Division
CT, MA, ME, NH, Rl, and VT
NJ, NY, and PA
IL, IN, Ml, OH, andWI
IA, KS, MN, MO, ND, NE, and SD
DE, FL, GA, MD, NC, SC, VA, and WV
AL, KY, MS, and TN
AR, LA, OK, and TX
AZ, CO, ID, MT, NM, NV, UT, and WY
CA, OR, and WA
2016
2.16
5.74
6.80
1.08
1.10
2.70
Demand (TBtu)
2018
0.0004
2.16
5.74
6.80
1.08
1.10
2.70
2020
1.70
1.16
3.07
5.13
0.58
0.59
7.35
2025
1.87
1.76
0.26
0.70
7.69
0.13
0.13
7.02
2030
0.80
1.62
2.06
0.22
5.38
2.92
2.33
0.89
3.35
2040-2050
0.51
1.15
9.01
0.14
3.98
1.71
1.34
0.53
1.19
Once the non-electricity demand for biomass is factored in, biomass prices in EPA Base Case v.5.13 are
derived endogenously based on the aggregate power sector demand for biomass in each state. The
results are unique market-clearing prices for each state. All plants using biomass from that state face the
same market-clearing price.
11-4
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11.3 Nuclear Fuel
The AEO 2013 price assumption for nuclear fuel is used as the nuclear fuel price assumption for 2016-
2050 in EPA Base Case v.5.13. The 2016, 2018, 2020, 2025, 2030 and 2040 prices are 0.89, 0.90, 0.90,
0.96, 1.01 and 1.062011 $/MMBtu, respectively.
11.4 Waste Fuels
Among the "modeled fuels" shown for existing generating units in the NEEDS v.5.13 (the database which
serves as the source of data on existing units for EPA Base Case v.5.13), are a number of waste fuels,
including waste coal, petroleum coke, fossil waste, non-fossil waste, tires, and municipal solid waste
(MSW). Table 11-4 describes these fuels, shows the extent of their representation in NEEDS, and then
indicates the assumptions adopted in EPA Base Case v.5.13 to represent their use and pricing. It should
be noted that these fuels are only provided to existing and planned committed units in EPA Base Case
v.5.13. Potential new generating units that the model "builds" are not given the option to burn these fuels.
In IPM reported output, tires, MSW, and non-fossil waste are all included under existing non-fossil other,
while waste coal and petroleum coke are included under coal.
Table 11-4 Waste Fuels in NEEDS v.5.13 and EPA Base Case v.5.13
NEEDS
Modeled
Fuel
Waste
Coal
Petroleum
Coke
Fossil
Waste
Non-
Fossil
Waste
Tires
Municipal
Solid
Waste
Number
of Units
27
22
60
143
2
179
Capacity
(MW)
2,432
3,170
412
1,600
46
2,279
Description
"Usable material that is a byproduct of previous coal
processing operations. Waste coal is usually composed of
mixed coal, soil, and rock (mine waste). Most waste coal is
burned as-is in fluidized-bed combustors. For some uses,
waste coal may be partially cleaned by removing some
extraneous noncombustible constituents. Examples of waste
coal include fine coal, coal obtained from a refuse bank or
slurry dam, anthracite culm, bituminous gob, and lignite
waste."
http://www.eia.gov/tools/glossary/index. cfm?id=W
A residual product, high in carbon content and low in
hydrogen, from the cracking process used in crude oil refining
Waste products of petroleum or natural gas including blast
furnace and coke oven gas. They do not include petroleum
coke or waste coal which are specified separately among the
"Modeled Fuels"
Non-fossil waste products that do not themselves qualify as
biomass. These include waste products of liquid and gaseous
renewable fuels (e.g., red and black liquor from pulping
processes, digester gases from waste water treatment). They
do not include urban wood waste which is included in
biomass.
Discarded vehicle tires.
"Residential solid waste and some nonhazardous commercial,
institutional, and industrial wastes."
http://www.eia.doe.gov/glossary/index.cfm
Supply and Cost
Modeled
By
Supply
Curve
Based on
AEO
2013
Price
Point
Price
Point
Price
Point
Price
Point
Price
Point
Assumed
Price
AEO
2013
$83.3/Ton
0
0
0
0
11.5 Fuel Emission Factors
Table 11-5 brings together all the fuel emission factor assumptions as implemented in EPA Base Case
v.5.13. For sulfur dioxide, chlorine, and mercury in coal, where emission factors vary widely based on the
rank, grade, and supply seam source of the coal, cross references are given to tables that provide more
11-5
-------
detailed treatment of the topic. Nitrogen oxides (NOX) are not included in Table 11-5 because NOX
emissions are a factor of the combustion process, and are not primarily fuel based.
Table 11-5 Fuel Emission Factor Assumptions in EPA Base Case v.5.13
Fuel Type
Coal
Bituminous
Subbituminous
Lignite
Natural Gas
Fuel Oil
Distillate
Residual
Biomass
Waste Fuels
Waste Coal
Petroleum Coke
Fossil Waste
Non-Fossil Waste
Tires
Municipal Solid Waste
Carbon Dioxide
(Ibs/MMBtu)
202.8-209.6
209.2-215.8
212.6-219.3
117.1
161.4
173.9
b
204.7
225.1
321.1
0
189.5
91.9
Sulfur Dioxide
(lbs/MMBtu)a
0.67-6.43
0.58-1.90
1.46-5.67
0
0-2.65
1.04
0.08
7.14
7.27
0.08
0
1.65
0.35
Mercury
(Ibs/TBtuf
1.82-26.07
2.03-8.65
7.51 -30.23
0.00014
0.48
0.48
0.57
63.9
2.66C
0
0
3.58
71.85
HCI
(Ibs/MMBtuf
0.005-0.280
0.006-0.014
0.011 -0.036
0
0
0
0
0.0921
0.0213
0
0
0
0
Notes:
a Also see Table 5-9
b CO2 emissions from biomass are not currently included in EPA Base Case v.5.13. CO2 emission factors are not currently
available for the four aggregate biomass fuels used in the biomass supply representation in EPA Base Case v. 5.13. EPA is
currently developing methods to estimate the amount of CO2 emitted on-site during biomass co-firing at coal fired power plants.
0 A previous computational error in the mercury emission factor for petroleum coke as presented in Table 6-3 of the EPA report
titled Control of Mercury Emissions from Coal-fired Electric Utility Boilers: Interim Report Including Errata, 3-21-02 was corrected
(from 23.18 Ibs/TBtu to 2.66 Ib/TBtu) based on re-examination of the 1999 ICR data for petroleum coke and implementation of a
procedure for flagging and excluding outlier values above the 95 percentile value.
11-6
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