&EPA
United States
Environmental Protection
Agency
Air and
Radiation
(6204J)
EPA #430R10010
August 2010
Documentation for
EPA Base Case v.4.10
Using the Integrated Planning
Model
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Cover: EPA Base Case v.4.10 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, Alaska, Hawaii, Puerto Rico, and U.S. Virgin Islands is also
included for purposes of integrated projections. The map appearing on the cover shows the 32
model regions used to characterize the operation of the U.S. electric power system in the lower
continental U.S., 11 model regions in Canada, and the 4 self-contained model regions in Alaska,
Hawaii, Puerto Rico, and U.S. Virgin Islands. EPA Base Case v.4.10 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 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.4.10
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)
August 2010
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Acknowledgment
This document was prepared by U.S. EPA's Clean Air Markets Division, Office of Air and
Radiation. ICF Services Company, L.L.C. provided technical support under EPA Contract EP-W-
08-018.
IV
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TABLE OF CONTENTS
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 2-4
2.3.2 Model Run Years 2-6
2.3.3 Cost Accounting 2-6
2.3.4 Modeling Wholesale Electric Markets 2-6
2.3.5 Load Duration Curves (LDC) 2-7
2.3.6 Dispatch Modeling 2-9
2.3.7 Reliability Modeling 2-9
2.3.8 Fuel Modeling 2-10
2.3.9 Transmission Modeling 2-10
2.3.10 Perfect Competition and Perfect Foresight 2-10
2.3.11 Air Regulatory Modeling 2-10
2.4 HARDWARE AND PROGRAMMING FEATURES 2-11
2.4.1 Data Parameters for Model Inputs 2-11
2.4.2 Model Outputs 2-12
Appendix 2-1 Load Duration Curves Used in EPA Base Case v.4.10 2-1
3 POWER SYSTEM OPERATION ASSUMPTIONS 3-1
3.1 MODEL REGIONS 3-1
3.2 ELECTRIC LOAD MODELING 3-1
3.2.1 Demand Elasticity 3-4
3.2.2 Net Internal Demand (Peak Demand) 3-4
3.2.3 Regional Load Shapes 3-5
3.3 TRANSMISSION 3-5
3.3.1 Inter-regional Transmission Capability 3-5
3.3.2 Joint Transmission Capacity and Energy Limits 3-9
3.3.3 Transmission Link Wheeling Charge 3-10
3.3.4 Transmission Losses 3-11
3.4 INTERNATIONAL IMPORTS 3-11
3.5 CAPACITY, GENERATION, AND DISPATCH 3-11
3.5.1 Availability 3-11
3.5.2 Capacity Factor 3-12
3.5.3 Turndown 3-13
3.6 RESERVE MARGINS 3-13
3.7 POWER PLANT LIFETIMES 3-15
3.8 HEAT RATES 3-17
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3.9 EXISTING ENVIRONMENTAL REGULATIONS 3-17
3.9.1 SO2 Regulations 3-17
3.9.2 NOX Regulations 3-18
3.9.3 CO2 Regulations and Renewable Portfolio Standards 3-20
3.9.4 State Specific Environmental Regulations 3-20
3.9.5 New Source Review (NSR) Settlements 3-20
3.9.6 Emission Assumptions for Potential (New) Units 3-20
3.10 CAPACITY DEPLOYMENT CONSTRAINTS 3-21
Appendix 3-1 NOX Rate Development in EPA Base Case v.4.10 3-1.1
Appendix 3-2 State Power Sector Regulations included in EPA Base Case v.4.10 3-2.1
Appendix 3-3 New Source Review (NSR) Settlements in EPA Base Case v.4.10 3-3.1
Appendix 3-4 State Settlements in EPA Base Case v.4.10 3-4.1
Appendix 3-5 Citizen Settlements in EPA Base Case v.4.10 3-5.1
Appendix 3-6 Renewable Portfolio Standards in EPA Base Case v.4.10 3-6.1
Appendix 3-7 Capacity Deployment Limits for Advanced Coal with CCS and New
Nuclear in EPA Base Case v.4.10 3-7.1
Appendix 3-8 Nuclear Capacity Deployment Constraint in EPA Base Case v.4.10 3-8.1
Appendix 3-9 Complete Availability Assumptions in EPA Base Case v.4.10 3-9.1
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 4-5
4.2.6 Model Plant Aggregation 4-5
4.2.7 Cost and Performance Characteristics of Existing Units 4-9
4.2.8 Life Extension Costs for existing units 4-10
4.3 PLANNED-COMMITTED UNITS 4-13
4.3.1 Population and Model Plant Aggregation 4-13
4.3.2 Capacity 4-17
4.3.3 State and Model Region 4-17
4.3.4 Online and Retirement Year 4-18
4.3.5 Unit Configuration and Cost-and-Performance 4-18
4.4 POTENTIAL UNITS 4-18
4.4.1 Methodology Used to Derive the Cost and Performance Characteristics of
Conventional Potential Units 4-18
4.4.2 Cost and Performance for Potential Conventional Units 4-19
4.4.3 Short-Term Capital Cost Adder 4-21
4.4.4 Regional Cost Adjustment 4-21
4.4.5 Cost and Performance for Potential Renewable Generating and Non-4-
Conventional Technologies 4-25
4.5 NUCLEAR UNITS 4-44
4.5.1 Existing Nuclear Units 4-44
4.5.2 Potential Nuclear Units 4-45
Appendix 4-1 Representative Wind Generation Profiles in EPA Base Case v.4.10 4-1.1
Appendix 4-2 Representative Solar Generation Profiles in EPA Base v.4.10 4-2.1
Appendix 4-3 Characteristics of Existing Nuclear Units 4-3.1
5 EMISSION CONTROL TECHNOLOGIES 5-1
VI
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5.1 SULFUR DIOXIDE CONTROL TECHNOLOGIES 5-1
5.1.1 Methodology for Obtaining SO2 Controls Costs 5-2
5.2 NITROGEN OXIDES CONTROL TECHNOLOGY 5-7
5.2.1 Combustion Controls 5-7
5.2.2 Post-combustion Controls 5-8
5.2.3 Methodology for Obtaining SCR Costs for Coal Units 5-9
5.2.4 Methodology for Obtaining SCR Costs for Oil/Gas Steam units 5-12
5.2.5 Methodology for Obtaining SNCR Costs 5-12
5.2.6 SO2 and NOX Controls for Units with Capacities from 25 MWto 100 MW(25 M
< capacity < 100 MW) 5-13
5.3 BIOMASS CO-FIRING 5-14
5.4 MERCURY CONTROL TECHNOLOGIES 5-15
5.4.1 Mercury Content of Fuels 5-16
5.4.2 Mercury Emission Modification Factors 5-17
5.4.3 Mercury Control Capabilities 5-18
Appendix 5-1 Example Cost Calculation Worksheets for SO2 Control Technologies in
EPA Base Case v.4.10 5-1
Appendix 5-2 Example Cost Calculation Worksheets for NOX Post-Combustion Control
Technologies in EPA Base Case v.4.10 5-1
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
Appendix 6-1 CO2 Storage Cost Curves in EPA Base Case 4.10 6-1.1
Appendix 6-2 CO2 Transportation Matrix in EPA Base Case v.4.10 6-2.1
7 SET-UP PARAMETERS AND RULES 7-1
7.1 RUN YEAR MAPPING 7-1
7.2 RETROFIT ASSIGNMENTS 7-1
7.3 TRADING AND BANKING 7-3
7.4 PosT-2030 MODELING ASSUMPTIONS AND CAPABILITIES 7-4
8 FINANCIAL ASSUMPTIONS 8-1
8.1 SUMMARY OF KEY FINANCIAL PARAMETERS 8-1
8.1.1 Capital Charge Rate, Book Life, and Discount Rate for Capital Expenditures 8-1
8.1.2 ARRA Production and Investment Tax Credit (PTC and ITC) for Renewables 8-2
8.1.3 Discount Rate for Non-Capital Expenditures 8-3
8.1.4 Inter-temporal Allowance Price Calculation 8-3
8.1.5 Nominal and Real Dollars 8-3
8.2 DEVELOPMENT OF THE FINANCIAL ASSUMPTIONS FOR EPA BASE CASE v.4.10 8-3
8.2.1 Introduction 8-3
8.2.2 Method for Deriving Discount Rate and Capital Charge Rate in EPA Base
Case v 4.10 8-4
8.2.3 Calculation of the Hybrid Capital Charge Rates 8-7
8.2.4 Development of Merchant Financing Parameters 8-8
8.2.5 Development of Utility Financing Parameters 8-10
8.2.6 Development of Other Parameters 8-10
9 COAL 9-1
VII
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9.1 COAL MARKET REPRESENTATION IN EPA BASE CASE v.4.10 9-1
9.1.1 Coal Supply Regions 9-2
9.1.2 Coal Demand Regions 9-3
9.1.3 Coal Quality Characteristics 9-9
9.1.4 Emission Factors 9-10
9.1.5 Coal Grade Assignments 9-15
9.2 COAL SUPPLY CURVES 9-16
9.2.1 Nature of Supply Curves Developed for EPA Base Case v.4.10 9-16
9.2.2 Procedure Employed in Determining Mining Costs 9-17
9.2.3 Supply Curve Development 9-20
9.2.4 Data Sources Used to Build the Curves 9-21
9.2.5 Procedure Used In Determining Mine Productivity 9-22
9.2.6 Procedure to Determine Total Recoverable Reserves by Region and Type 9-22
9.2.7 New Mine Assumptions 9-23
9.2.8 Other Notable Procedures 9-23
9.2.9 Region Specific Assumptions and Outlooks 9-23
9.2.10 Explanation of Coal Supply Curve Extensions to 2040 9-25
9.3 COAL TRANSPORTATION 9-25
9.3.1 Coal Transportation Matrix Overview 9-26
9.3.2 Calculation of Supply/Demand Region Distances 9-26
9.3.3 Overview of Rail Rates 9-27
9.3.4 Truck rates 9-30
9.3.5 Barge and Lake Vessel Rates 9-30
9.3.6 Transportation Rates for Imported Coal 9-31
9.3.7 Other Transportation Costs 9-32
9.3.8 Long-Term Escalation of Transportation Rates 9-32
9.3.9 Market Drivers Moving Forward 9-34
9.3.10 Other Considerations 9-36
9.4 COAL EXPORTS, IMPORTS, AND NON-ELECTRIC SECTORS DEMAND 9-36
Appendix 9-1. Illustrative Example of Wood Mackenzie Costing Procedure Used in
Developing EPA's Coal Supply Curves 9-1.1
Appendix 9-2 New Mines Included in 2040 Curves 9-2.1
Appendix 9-3 Coal Transportation Matrix in EPA Base Case v.4.10 9-3.1
Appendix 9-4 Coal Supply Curves in EPA Base Case v.4.10 9-4.1
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 10-4
10.2.1 Note on the Modeling Time Horizon and Pre- and Post-2030 Input
Assumptions 10-6
10.3 RESOURCE CHARACTERIZATION AND ECONOMIC EVALUATION 10-7
10.3.1 Resource and Reserves Assessment 10-8
10.3.2 Frontier Resources (Alaska and Mackenzie Delta) 10-10
10.3.3 Use of the HSM resource and reserves data in EPA Base Case using IPM
v.4.10 Natural Gas Module 10-12
10.3.4 Undiscovered Resource Appreciation 10-13
10.4 EXPLORATION, DEVELOPMENT, AND PRODUCTION COSTS AND CONSTRAINTS 10-14
10.4.1 Exploration and Development Cost 10-14
10.4.2 Resource Discovery and Drilling Constraints 10-17
10.4.3 Reserves-to-Production (R/P) Ratio 10-19
10.4.4 Variable Costs, Natural Gas Liquid Share, and Crude Oil Share 10-19
10.4.5 Lease and Plant Gas Use 10-20
VIM
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10.5 LIQUEFIED NATURAL GAS (LNG) IMPORTS 10-20
10.5.1 Liquefaction Facilities and LNG Supply 10-20
10.5.2 Regasification Facilities 10-21
10.5.3 LNG Regasification Capacity Expansions 10-22
10.6 END USE DEMAND 10-23
10.6.1 Step 1: Developing Sector Specific Econometric Models of Non-Power Sector
Demand 10-23
10.6.2 Step 2: Use projections based on the GMM econometric models to produce
monthly gas demand curves by sector and demand node 10-25
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 10-25
10.7 PIPELINE NETWORK 10-27
10.7.1 Network Structure 10-27
10.7.2 Pipeline Transportation Costs 10-28
10.7.3 Pipeline Capacity Expansion Logic 10-29
10.8 GAS STORAGE 10-30
10.8.1 Storage Capacity and Injection/Withdrawal Constraints 10-33
10.8.2 Variable Cost and Fuel Use 10-33
10.8.3 Storage Capacity Expansion Logic 10-34
10.9 FUEL PRICES 10-35
10.9.1 Crude Oil and Natural Gas Liquids Prices 10-35
10.9.2 Natural Gas Prices 10-36
10.10 OUTPUTS AND PROXY NATURAL GAS SUPPLY CURVES 10-36
10.10.1 Outputs from the New IPM Natural Gas Module 10-36
10.10.2 Proxy Natural Gas Supply Curves 10-36
Appendix 10-1 EPA Base Case v.4.10 with AEO Gas Resource Assumptions 10-1.1
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 11-3
11.4 WASTE FUELS 11-3
11.5 FUEL EMISSION FACTORS 11-5
Appendix 11-1 Biomass Supply Curve in EPA Base Case v.4.0 11-1
IX
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LIST OF TABLES
Table 1-1 Plant Types in EPA Base Case v.4.10 1-2
Table 1-2 Emission Control Technologies in EPA Base Case v.4.10 1-3
Table 1-3 Key Updates in the EPA Base Case v.4.10 1-4
Table 3-1 Mapping of NERC Regions and NEMS Regions with EPA Base Case v.4.10
Model Regions 3-3
Table 3-2 Electric Load Assumptions in EPA Base Case v.4.10 3-4
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.4.10 3-6
Table 3-5 Annual Joint Capacity and Energy Limits to Transmission Capabilities Between
Model Regions in EPA Base Case v.4.10 3-9
Table 3-6 International Electricity Imports in EPA Base Case v.4.10 3-11
Table 3-7 Availability Assumptions in the EPA Base Case v.4.10 3-12
Table 3-8 Seasonal Hydro Capacity Factors (%) in the EPA Base Case v.4.10 3-12
Table 3-9 Planning Reserve Margins in EPA Base Case v.4.10 3-14
Table 3-10 Lower and Upper Limits Applied to Heat Rate Data in NEEDS v.4.10 3-17
Table 3-11 Emission and Removal Rate Assumptions for Potential (New) Units in EPA
Base Case v.4.10 3-23
Table 4-1 Data Sources for NEEDS v.4.10 for EPA Base Case v.4.10 4-2
Table 4-2 Rules Used in Populating NEEDS v.4.10 for EPA Base Case v.4.10 4-3
Table 4-3 Summary Population (through 2006) of Existing Units in NEEDSv.4.10 for EPA
Base Case v.4.10 4-3
Table 4-4 Hierarchy of Data Sources for Capacity in NEEDS v.4.10 4-4
Table 4-5 Capacity-Parsing Algorithm for Steam Units in NEEDS v.4.10 4-4
Table 4-6 Data Sources for Unit Configuration in NEEDS v.4.10 for EPA Base Case v.4.10 4-6
Table 4-7 Aggregation Profile of Model Plants as Provided at Set Up of EPA Base Case
v.4.10 4-7
Table 4-8 VOM Assumptions (2007$) in EPA Base Case v.4.10 4-9
Table 4-9 FOM Assumptions Used in EPA Base Case v.4.10 4-11
Table 4-10 Life Extension Cost Assumptions Used in EPA Base Case v.4.10 4-13
Table 4-11 Summary of Planned-Committed Units in NEEDS v.4.10 for EPA Base Case
v.4.10 4-14
Table 4-12 Planned-Committed Units by Model Region in NEEDS v.4.10 for EPA Base
Case v.4.10 4-14
Table 4-13 Performance and Unit Cost Assumptions for Potential (New) Capacity from
Conventional Technologies in EPA Base Case v4.10 4-20
Table 4-14 Short-Term Capital Cost Adders for New Power Plants in EPA Base Case
v.4.10 (2007$) 4-23
Table 4-15 Regional Cost Adjustment Factors for Conventional and Renewable Generating
Technologies in EPA Base Case v.4.10 4-25
Table 4-16 Performance and Unit Cost Assumptions for Potential (New) Renewable and
Non-Conventional Technology Capacity in EPA Base Case v4.10 4-27
Table 4-17 Onshore Regional Potential Wind Capacity (MW) by Wind and Cost Class in
EPA Base Case v.4.10 4-29
Table 4-18 Offshore Shallow Regional Potential Wind Capacity (MW) by Wind and Cost
Class in EPA Base Case v.4.10 4-32
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Table 4-19 Offshore Deep Regional Potential Wind Capacity (MW) by Wind and Cost Class
in EPA Base Case v.4.10 4-34
Table 4-20 Onshore Reserve Margin Contribution an Average Capacity Factor by Wind
Class and Model Region 4-37
Table 4-21 Offshore Shallow Reserve Margin Contribution an Average Capacity Factor by
Wind Class and Model Region 4-37
Table 4-22 Offshore Deep Reserve Margin Contribution an Average Capacity Factor by
Wind Class and Model Region 4-38
Table 4-23 Capital Cost Adjustment Factors for New Wind Plants in Base Case v.4.10 4-39
Table 4-24 Example Calculations Of Wind Generation Potential, Reserve Margin
Contribution, And Capital Cost For Onshore Wind In CA-N At Wind Class 7,
Cost Class 2 4-40
Table 4-25 Solar Reserve Margin Contribution and Average Capacity Factor by Model
Region 4-41
Table 4-26 Regional Assumptions on Potential Geothermal Electric Capacity 4-42
Table 4-27 Potential Geothermal Capacity and Cost Characteristics by Model Region 4-42
Table 4-28 Regional Assumptions on Potential Electric Capacity from New Landfill Gas
Units (MW) 4-43
Table 4-29 Nuclear Upratings (MW) as Incorporated in EPA Base Case v.4.10 from AEO
2010 4-45
Table 5-1 Summary of Emission Control Technology Retrofit Options in EPA Base Case
v.4.10 5-1
Table 5-2 Summary of Retrofit SO2 Emission Control Performance Assumptions 5-2
Table 5-3 Capital Cost Modules and Their Governing Variables for SO2 and NOX Emission
Controls 5-3
Table 5-4 Illustrative Scrubber Costs (2007$) for Representative Sizes and Heat Rates
under the Assumptions in EPA Base Case v.4.10 5-6
Table 5-5 Cost (2007$) of NOX Combustion Controls for Coal Boilers (300 MWSize) 5-7
Table 5-6 Incremental Combustion NOX Controls in EPA Base Case v.4.10 5-8
Table 5-7 Summary of Retrofit NOX Emission Control Performance Assumptions 5-8
Table 5-8 Illustrative Post Combustion NOX Controls for Coal Plants Costs (2007$) for
Representative Sizes and Heat Rates under the Assu Assumptions in EPA
Base Case v.4.10 5-11
Table 5-9 Post-Combustion NOX Controls for Oil/Gas Steam Units in EPA Base Case
v.4.10 5-12
Table 5-10 Biomass Cofiring for Coal Plants 5-15
Table 5-11 Mercury Clusters and Mercury Content of Coal by IPM Coal Types 5-17
Table 5-12 Assumptions on Mercury Concentration in Non-Coal Fuel in EPA Base Case
v.4.10 5-17
Table 5-13 Mercury Emission Modification Factors Used in EPA Base Case v.4.10 5-19
Table 5-14 Definition of Acronyms for Existing Controls 5-26
Table 5-15 Key to Burner Type Designations in Table 5-13 5-26
Table 5-16 Illustrative Activated Carbon Injection Costs (2007$) for Representative Sizes
under the Assumptions in EPA Base Case v.4.10 5-28
Table 5-17 Assignment Scheme for Mercury Emissions Control Using Activated Carbon
Injection (ACI) in EPA Base Case v.4.10 5-29
Table 6-1 Performance and Unit Cost Assumptions for Carbon Capture Retrofits on
Pulverized Coal Plants 6-1
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Table 6-2 CO2 Transport Cost Calculation Example - MACS to Louisiana Onshore 6-5
Table 7-1 Run Years and Analysis Year Mapping Used in the EPA Base Case v.4.10 7-1
Table 7-2 First Stage Retrofit Assignment Scheme in EPA Base Case v.4.10 7-2
Table 7-3 Second Stage Retrofit Assignment Scheme in EPA Base Case v.4.10 7-3
Table 7-4 Trading and Banking Rules in EPA Base Case v.4.10 7-4
Table 7-5 Post-2030 Assumptions in EPA Base Case v.4.10 7-5
Table 8-1 U.S. Discount Rates and Capital Charge Rates in EPA Base Case v4.10 8-2
Table 8-2 Capital Structure Assumptions for EPA Base Case v4.10 8-6
Table 8-3 Debt Rates for EPA Base Case v4.10 8-8
Table 8-4 Book Life, Debt Life and Depreciation Schedules for EPA Base Case v. 4.10 8-11
Table 9-1 Coal Supply Regions in EPA Base Case 9-2
Table 9-2 Coal Demand Regions in EPA Base Case 9-3
Table 9-3 Coal Rank Heat Content Ranges 9-10
Table 9-4 Coal Grade SO2 Content Ranges 9-10
Table 9-5 Coal Quality Characteristics by Supply Region and Coal Grade 9-11
Table 9-6 SO2 Emission Factors of Coal Used in EPA Base Case v.4.10 9-13
Table 9-7 Mercury Emission Factors of Coal Used in EPA Base Case v.4.10 9-14
Table 9-8 Ash Emission Factors of Coal Used in EPA Base Case v.4.10 9-14
Table 9-9 CO2 Emission Factors of Coal Used in EPA Base Case v.4.10 9-15
Table 9-10 Example of Coal Assignments Made in EPA Base Case 9-16
Table 9-11 Basin-Level Groupings Used in Preparing v.4.0 Coal Supply Curves 9-17
Table 9-12 Rail Competition Definitions 9-28
Table 9-13 Assumed Eastern Rail Rates (2007 mills/ton-mile) 9-29
Table 9-14 Assumed Midwestern Rail Rates (2007 mills/ton-mile) 9-29
Table 9-15 Assumed Non-PRB Western Rail Rates (2007 mills/ton-mile) 9-30
Table 9-16 Assumed PRB Western Rail Rates (2007 mills/ton-mile) 9-30
Table 9-17 Assumed Truck Rates (2007 Real Dollars) 9-30
Table 9-18 Assumed Barge Rates (2007 Real Dollars) 9-31
Table 9-19 Assumed Transportation Rates for Imported Coal (2007 Real Dollars) 9-31
Table 9-20 Assumed Other Transportation Rates (2007 Real Dollars) 9-32
Table 9-21 EIA AEO Diesel Fuel Forecast, 2012-2030 (2007 Real Dollars) 9-34
Table 9-22 ABARE Forecast of Iron Ore Prices 9-35
Table 9-23 Assumed Production Growth Rates 9-36
Table 9-24 Coal Exports 9-37
Table 9-25 Residential, Commercial, and Industrial Demand 9-38
Table 9-26 Coal Import Limits 9-38
Table 10-1 List of Nodes 10-5
Table 10-2 List of Gas Supply Regions 10-1
Table 10-3 List of Key Pipelines 10-3
Table 10-4 U.S. and Canada Natural Gas Resources and Reserves 10-10
Table 10-5 Exploration and Development Assumptions for EPA Base Case v.4.10 10-17
Table 10-6 North American LNG Regasification Facilities 10-21
Table 10-7 Summer and Winter Load Segments in EPA Base Case v.4.10 10-26
Table 10-8 List of Storage Nodes 10-31
Table 10-9 Storage Capacity and Injection/Withdrawal Rates (EOY2010) 10-33
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Table 10-10 Base Year 2011 Average Levelized Storage Capital Cost 10-35
Table 10-11 Proxy Natural Gas Supply Curves for EPA Base Case v.4.10 10-37
Table 10-12 Glossary of Natural Gas Terms Used in Documentation 10-38
Table 11-1 Fuel Oil Prices by NEMS Region in EPA Base Case v.4.10 11-1
Table 11-2 Non-Electric Biomass Demand by NEMS Region in EPA Base Case v.4.10 11-2
Table 11-3 Waste Fuels in NEEDS, v.4.10 and EPA Base Case v.4.10 11-4
Table 11-4 Fuel Emission Factor Assumptions in EPA Base Case v.4.10 11-5
IV
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LIST OF FIGURES
Figure 1-1 Modeling and Data Structures in EPA Base Case v.4.10 1-4
Figure 2-1 Hypothetical Chronological Hourly Load Curve and Seasonal Load Duration
Curve in EPA Base Case v.4.10 2-7
Figure 2-2 Stylized Depiction of Load Duration Curve Used in EPA Base Case v.4.10 2-8
Figure 2-3 Stylized Dispatch Order in EPA Base Case v.4.10 2-9
Figure 3-1 EPA Base Case v.4.10 Model Regions 3-2
Figure 3-2 Scheduled Retirements of Existing Nuclear Capacity Under 60-Year Life
Assumption 3-15
Figure 9-1 Map of the Coal Supply Regions in EPA Base Case v.4.10 9-3
Figure 9-2 Cluster Mapping Example BG Coal 9-15
Figure 9-3 Cost Calculations Included When Developing Coal Supply Curves (based on a
Powder River Basin Mine Supply Curve Example) 9-18
Figure 9-4 Illustration of Preliminary Step in Developing a Cumulative Coal Supply Curve 9-20
Figure 9-5 Illustration of Final Step in Developing a Cumulative Coal Supply Curve 9-21
Figure 9-6 Example Coal Supply Curve in Stepped Format 9-21
Figure 9-7 Calculation of Multi-Mode Transportation Costs (Example) 9-26
Figure 9-8 Coal Demand Region with Multiple Coal Supply Regions 9-27
Figure 9-9 Rail Cost Indices Performance (2Q2003-2Q2008) 9-33
Figure 9-10 Long-Run Marginal Cost Breakdown by Transportation Mode 9-34
Figure 10-1 Modeling and Data Structure in EPA Base Case v.4.10 10-2
Figure 10-2 Natural Gas Module in EPA Base Case v.4.10 10-3
Figure 10-3 Gas Transmission Network Map 10-5
Figure 10-4 Gas Supply Regions Map 10-8
Figure 10-5 Gas Demand Regions Map 10-3
Figure 10-6 Natural Gas Storage Facility Node Map 10-7
Figure 10-7 Resource Cost Curves at the End of Year 2010 10-13
Figure 10-8 Exploration & Development and Production Processes and Costs to Bring
Undiscovered Resource into Reserves and Production 10-14
Figure 10-9 E&D and Production Technology Improvement Factor 10-15
Figure 10-10 Incremental E&D Cost (EOY 2010) by Percentage of Resource Found 10-15
Figure 10-11 Drilling Rig Speed Constraint 10-19
Figure 10-12 North American LNG Supply Curves 10-21
Figure 10-13 North American LNG Regasification Facilities Map 10-22
Figure 10-14 Examples of Firm Demand Curves by Electric Load Segment 10-26
Figure 10-15 Examples of Interruptible Demand Curves by Electric Load Segment 10-27
Figure 10-16 New England Pipeline Corridors in 2020 10-28
Figure 10-17 Example Pipeline Discount Curve 10-29
Figure 10-18 Pipeline Cost Growth Factor 10-29
Figure 10-19 Storage Cost Growth Factor 10-34
Figure 10-20 Example Maximum Storage Capacity Expansion 10-34
Figure 10-21 Crude Oil and NGL Prices 10-36
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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.4.10) that
was developed by the U.S. Environmental Protection Agency (EPA) with technical support from
ICF Consulting, Inc. 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), and mercury (Hg) from the electric power sector.
Base cases, like EPA Base Case v.4.10, serve as the starting point against which policy scenarios
are compared. It 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 2010. (Chapter
3 contains a detailed discussion of the environmental regulations included in EPA Base Case
v.4.10.) Regulations, mandated under the Clean Air Act Amendments of 1990 (CAAA), but whose
provisions either have not yet been finalized or will expire due to Court action, were not included in
the base case. These include.
Ozone and Particulate Matter (PM) Standards: EPA Base Case v.4.10 does not include the
provisions of the Clean Air Interstate Rule (CAIR), a Federal regulatory measure for achieving
the National Ambient Air Quality Standards (NAAQS) for ozone (8-hour standard of 0.08 ppm)
and fine particles (24-hour average of 65 ug/m3 or less and annual mean 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. Until EPA's work was
completed, CAIR was temporarily reinstated. However, although CAIR's provisions were still
in effect when EPA Base Case v.4.10 was released, it is not included in the base case to
allow EPA Base Case v.4.10 to be used to analyze the regulations proposed to replace CAIR.
EPA Base Case v.4.10 includes ozone and particulate matter standards to the extent that
some of the state regulations included in EPA Base Case v.4.10 contain measures to bring
non-attainment areas into attainment. A summary of these state regulations can be found in
Appendix 3-2 below. Apart from these state regulations, individual permits issued by states in
response to ozone and PM standards are only captured (a) to the extent that they are
reflected in the NOX rates reported to EPA under 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.
Regional Haze: On July 1, 1999, EPA issued Regional Haze Regulations to meet the national
goal for visibility established in Section 169A of the CAAA, which calls for "prevention of any
future, and the remedying of any existing, impairment of visibility in Class I areas [156 national
parks and wilderness areas], which impairment results from manmade air pollution." The
regulations required 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 1962-1977. The revised SIPs were to be submitted between 2004-2006 for areas
designated as "attainment" and "unclassified" and between 2006-2008 for "nonattainment"
areas. They are represented in EPA Base Case v.4.10 to the extent that SO2 permit limits
derived from the SIPs are used in the base case to define the choice of coal sulfur grades that
are available to specific power plants. As discussed in chapter 3, however, the base case
includes the sulfur dioxide emission cap (144.7 MTons for all affected fossil fired generating
units larger than 25 MW), adopted by the Western Regional Air Partnership states of Arizona,
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New Mexico, Oregon, Utah, and Wyoming in response to Section 309 of the federal Regional
Haze Rule.
In effect, EPA Base Case v.4.10 offers a projection of the electric sector assuming that the only
future environmental regulations are those that were in place at the time the base case was
finalized and that have a high likelihood of remaining in force. This simplifying assumption
ensures that the base case is policy neutral with respect to prospective, future environmental
policies. Table 1-1 lists the types of plants included in the EPA Base Case v.4.10. Table 1-2 lists
the emission control technologies available for meeting emission limits in EPA Base Case v.4.10.
Table 1-1 Plant Types in EPA Base Case v.4.10
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 IGCC
Onshore Wind
Offshore Shallow Wind
Offshore Deep Wind
Fuel Cells
Solar Photovoltaics
Solar Thermal
Geothermal
Landfill Gas
Other1
Note:
1 Includes fossil and non-fossil waste plants
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Table 1-2 Emission Control Technologies in EPA Base Case v.4.10
Sulfur Dioxide (SO2)
Limestone Forced Oxidation (LSFO)
Lime Spray Dryer (LSD)
Mercury (Hg)
Combinations of SO2, NOX, and participate
control technologies
Activated Carbon Injection
Nitrogen Oxides (NOX)
Combustion controls
Selective catalytic reduction (SCR)
Selective non-catalytic reduction (SNCR)
Carbon Dioxide (CO2)
Carbon Capture and Sequestration
Notes:
1. Though not listed in Table 1-2, biomass co-firing, which is offered as a fuel option in EPA
Base Case v.4.10, is also used as a CO2 emission control option. See section 5.3 in Chapters
fora description of the implementation of biomass co-firing in EPA Base Case v.4.10.
2. Fuel switching between coal types and to natural gas is also a compliance option for
reducing emissions in EPA Base Case v.4.10
Figure 1-1 provides a schematic of the components of the modeling and data structure used for
EPA Base Case v.4.10. 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.4.10. Chapters covers the power system operating
characteristics captured in EPA Base Case v.4.10. 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.4.10. 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).
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Figure 1-1 Modeling and Data Structures in EPA Base Case v.4.10
Emission Control
Technologies
Chaptei 5
Sulfur Dioxide
Nitrogen Oxides
Mercun/
Carbon Capture and Storage
Generation Resources
_; Chapter 4
Existing EGUsf
Planned EGUst
Potential New EG Us
Future Place holder Technologies
Conditioned bY;
Short-term Capital Cost Adder
Regional Cost Adjustments
Capacity Deployment Constraints
Power System Operation
'_ Chapter 3 1
Regional Configurations
Capacity. Generation, and Dispatch Assumptions
Transmission Assumptions
Turndown Constraints
Reliability Constraints
Electricity Demand Growth
Environmental Regulations
CO, Capture,
Transport, and
Storage
Chapter 6
Capture Technologies
Transportation
Storage Regions
Set-Up Rules and
Parameters
Chanter 7
Run Yea rs
Aggregation Sdi ernes
R etrofit Assi gnm ents
Trading and Banking
P ost-2JD30 Assu mptio ns
IPM Engineft
Chapter 2
Model Outputs
Emissions
Costs
Retro lit Decisions
Fuel Consumption and Prices
Electricity Usage and Prices
Post-Processor
Financial Assumptions
J Chapter 8
Discount Rate
Capita! Charge Rate
Book Life
Capital Cost Adder for Climate Uncertainty
Production Tax Credit
I nvestment Tax C redit
Coal & Other Fuel
Assumptions
Chapter 9-11
Coa!
Fuel Oil
Nudear Fuel
Biomass
Waste Fuels
Emission Factors
Natural Gas Module
{Endogenous)
'__ Chaptei 10
North American Supply(from GMM
Hyd ro ca rbo n Su pply M od el)
- Reserves and Resources
- Production Costs LNG Supply and Costs
Pipeline NetAeik
Storage
Non-EGU Demand (Residential, Commercial.
Industrial)
Pricing Mechanism
Parsing Outputs
IndM dual Boiler Level Data
Outputs for Air
Quality Modeling
Criteria Air Pollutants
N on- criteria flit Pollutants
Toxics Air Pollutants
P oint So u ree Locato rs
f Information on existing and planned electric gene rating units (EGUs) is contained in the National Electrical
Energy Data System (NEEDS) data base maintained for EPA by ICF International- Planned EOUs are those
which were under construction or had obtained financing at 1he time ihatthe EPA Base Case was finalized.
t"flPM Engine is the model structure described in Chapter2
Table 1-3 lists key updates included in EPA Base Case v.4.10 listed in the order they appear in
this documentation report. Noted by asterisks in the second column are updates that were "non-
routine" in the sense that they constituted new modeling capabilities or notable extensions beyond
the capabilities provided in previous EPA base cases or significant reviews of important
assumptions. The updates that are not starred represent more routine updates. Equal in
importance to the non-routine updates, the routine updates typically require substantial effort and
great discipline to maintain. They are critical to the technical credibility of a detailed, bottom-up,
data driven model like IPM.
Table 1-3 Key Updates in the EPA Base Case v.4.10
Description
Non-
Routine
(*)
For More
Information
Modeling Framework
Use of six-segment load duration curves (2012-2030) to enable
differentiation of peak and super-peak generating unit dispatch
ง2.3.5-
2.3.6
Power System Operation
Model region update and inclusion of Canada, Alaska, Hawaii,
Puerto Rico, and U.S. Virgin Islands
Updates based on recent data from EIA, NERC, FERC, etc.
Capacity deployment constraints (for new advanced coal with
carbon capture, carbon capture retrofits, and new nuclear)
*
*
ง3.1
(multiple)
ง3.10
App. 3-07 -
3-08
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Description
Updated inventory of state emission regulations
Updated inventories of NSR, state, and citizen settlements
Nuclear retirement at age 60
Non-
Routine
(*)
*
For More
Information
App.3-02
App. 3-03 -
3-05
ง3.7
Generating Resources
Updates to NEEDS, the database of existing and planned-
committed units and their emission control configurations
Providing life extension cost option to allow existing units to
continue operation over the extended 2012-2050 modeling time
horizon in the new base case
Updated cost and performance characteristics for potential (new)
conventional and nuclear generating units, based on comparative
cost analyses
Adding biomass gasification combined cycle and offshore (shallow
and deep) wind as potential (new) renewable generating options
Expanding wind resource base to include 5 wind classes (3-7) by
adding new wind classes 3 and 7 using data provided by NREL
*
*
*
ง4.1-4.3
ง4.2.8
ง4.4.1 -
4.4.2
ง4.4.5
ง4.4.5
Emission Control Technologies
Complete update of cost and performance assumptions for SO2
and NOX emission controls based on engineering studies by
Sargent and Lundy
Inclusion of cost and performance assumptions forSO2 and NOX
emission controls for units with capacities ranging from 25-1 OOMW
Updated cost and performance assumptions for biomass co-firing
by coal units
*
*
ง5.1-5.2
ง5.2.6
ง5.3
Carbon Capture, Transport and Storage
Update of the cost and performance characteristics used to
represent carbon capture retrofits and new generating units with
carbon capture
CO2 transport and storage represented through state level
transportation matrix and regional storage cost curves rather than
a single cost adder
*
ง6.1
ง6.2-6.3
Set-Up Parameters and Rules
Expanded modeling time horizon out to 2050 with six model run
years (2012, 2015, 2020, 2030, 2040, 2050)
Five generic placeholder future generation technologies for later
use in comparative scenario analyses
*
ง7.1 and 7.4
ง7.4
Financial assumptions
Update of discount and capital charge rate assumptions based on
a new hybrid capital cost model of utility and merchant finance
structures
Capital cost adder for climate change uncertainty
ง8.1.1 and
8.2
ง8.1.1
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Description
Incorporation of latest legislation based tax credits for renewables
and nuclear generation
Non-
Routine
(*)
For More
Information
ง8.1.1-
8.1.2
Coal
Complete update of coal supply curves and transportation matrix
*
ง9
Natural Gas
Development of IPM natural gas module providing completely
endogenous comprehensive modeling of North American natural
gas system
Major revision of unconventional gas resource base, particularly
view of shale gas resources
Base case variant with natural gas resource assumptions similar
toAEO2010
*
*
ง10
ง10.3
Appendix
10.1
Other Fuels
Update of biomass supply curves and price assumptions for fuel
oil, nuclear fuel and waste fuel
*
ง11
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2 Modeling Framework
ICF International 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 section 2.2's discussion of model
structure and formulation, and transmission modeling is covered as a key methodological feature
in section 2.3.9. 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 picking up local transmission
behavior and bottlenecks), the model regions representing the U.S. power market in EPA Base
Case v.4.10 are largely consistent with the regions and sub-regions constituting the North
American Electric Reliability Council (NERC) regions and with the organizational structures of the
Regional Transmission Organizations (RTOs) and Independent System Operators, which handle
dispatch on most of the U.S. grid. IPM models the electric demand, generation, transmission, and
distribution within each region as well as the inter-regional transmission grid. 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.
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
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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 conservation), 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.4.10.
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. The total resulting cost is expressed as the net present value of all the
component costs. 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 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
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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 which the IPM model is "solving for," 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 decision variables values are the model's "outputs" and 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 plant1. 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 (see section 1 and Table 9-4), and mercury
content (see sections 5.4.land 1 and Table 9-7). 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.4.10, 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.4.10 are:
Reserve Margin Constraints: Regional reserve margin constraints capture system reliability
requirements by defining a minimum margin of reserve capacity (in megawatts) per year. If
existing plus planned capacity is not enough to satisfy the annual regional reserve margin
requirement, the model will "build" the required level of new capacity.
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 consider an array of emissions constraints for SO2, NOX,
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 what might happen given the assumptions and methodologies used. Chapters 3-
11 contain detailed discussions of the cost and performance assumptions specific to the EPA
Base Case v.4.10. 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.4.10.
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.
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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 into 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.4.10, IPM employed an
aggregation algorithm which allowed 15,023 actual existing electric generating units to be
represented by 4,738 model plants. Section 4.2.6 describes the aggregation procedure used in
the EPA Base Case v.4.10.
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.4.10 provides existing
model plants with the option to retire early and with a wide range of options for retrofitting with
emission control equipment. (See Chapters 5 and section 7.2 in Chapter 7 for a detailed
discussion of the options that are included in the EPA Base Case v.4.10.)
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 units. EPA Base Case v.4.10 model plants that represent
potential (new) units are not given the option to take on a retrofit or retire. 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 early.
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.4.10, a maximum of two stages of
retrofit options are provided (child and grandchild, but not great-grandchild). For example, an
existing model plant may be 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) and with
an activated carbon injection (ACI) for mercury control in the same or subsequent run year (stage
2). However, if it exercises this succession of retrofit options, no further retrofit or retirement
options are possible beyond the second 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, 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 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 overtime.
Since EPA Base Case v.4.10 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, pollution 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
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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.)
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 decisions are likely to persist beyond that end point. Due to the
number of model run years required by EPA for analytical purposes (six in the 2012-2050 time
period) and a greatly expanded suite of modeling capabilities, such an approach could not be
used in EPA Base Case v.4.10. It would have increased model size too much. However
boundary distortions are only a potential factor 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). Nevertheless, the possibility of residual boundary effects is
something to bear in mind when interpreting model results for 2050.
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 electric 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:
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 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 appearing in 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 over time.
2.3.4 Modeling Wholesale Electric Markets
Another important methodological feature worth noting about IPM is that it is designed to depict
production activity in deregulated wholesale electric markets, not in retail markets. The model
captures transmission costs and losses between IPM model regions. It is not designed to capture
2-6
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retail distribution costs. However, the model implicitly includes distribution losses since net energy
for load,2 rather than delivered sales,3 is used to represent electric 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 be part of the retail cost.
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 electric
demand, the LDCs are created by rearranging the hourly chronological electric load data from the
highest to lowest (MW) value. For modeling tractability a 6-step piecewise linear representation of
the LDC is used in EPA applications of IPM.
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.4.10 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 fora season consisting of 3,672 hours.
Figure 2-1 Hypothetical Chronological Hourly Load Curve and Seasonal Load Duration
Curve in EPA Base Case v.4.10
Chronological Hourly Load Curve
Seasonal Load Duration Curve
MW
Hours in Season
3672
Hours in Season
3672
National electric demand growth assumptions (from AEO for EPA Base Case v.4.10) and NERC's
forecasts of peak and energy demand in each region are used to derive future seasonal load
duration curves for each IPM run year in each IPM region from the historical data. The results of
this process are individualized seasonal LDCs that capture the unique hourly electric demand
profile of each region. The LDCs change overtime to reflect projected future variations in
electricity consumption patterns.
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.4.10 uses six load segments in its seasonal LDCs
2Net 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.
3Delivered sales is the electrical energy delivered under a sales agreement. It does not include
distribution losses.
2-7
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for model run years 2012-2030 and 4 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 2-3 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 2-3
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.
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 scheduling for individual generating units, the
capacity and utilization for these supply resources also vary between seasons.
Appendix 2-1 contains data and graphs of the 2012 summer and winter load duration curves in
each of the 32 model regions in the lower continental U.S. for EPA Base Case v.4.10.
Figure 2-2 Stylized Depiction of Load Duration Curve Used in EPA Base Case v.4.10
Stylized Six Segment Load Duration Curve
Load
(MW)
\
Segment 1 Segment 2
Percentage of Hours:
Duration (Hours
Segment 1-1% Segment2-4% Segments-10%
Segment 4 - 30% Segment 5 - 30% Segment 6 - 25%
2-8
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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.4.10. 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 so
are 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 (i.e., peaking turbines) are at the top of the "dispatch stack," since they
are dispatched last and for the minimum possible number of hours.
Figure 2-3 Stylized Dispatch Order in EPA Base Case v.4.10
MW
Combustion Turbine
Oil/Gas Steam
Gas Combined Cycle
Coal Steam
Nuclear
Hydro
Hours
2.3.7 Reliability Modeling
Another methodological feature of IPM is its modeling of reliability through reserve margin
requirements, which specify the amount of installed capacity that must be in excess of peak power
demand. IPM includes regional reserve margin requirements for each run year. Section 3.6
contains a discussion of the reserve margin assumptions in EPA Base Case v.4.10.
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2.3.8 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.4.10 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 the fuel quality information (e.g., the sulfur or
mercury content of different types of coal from different supply regions) to determine the
emissions resulting from the combustion of that fuel.
The EPA Base Case v.4.10 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 9-11.
2.3.9 Transmission Modeling
IPM includes a detailed representation of existing transmission capabilities between model
regions along with options for building new transmission lines. The maximum transmission
capabilities between regions are specified in IPM's transmission constraints. Additions to
transmission lines are represented by decision variables defined for each eligible link and model
run year. In IPM's objective 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. Due to extensive unresolved policy issues
and long-term uncertainty surrounding the building of new transmission lines in the U.S., EPA
Base Case v.4.10 does not exercise IPM's capability to model the building of new transmission
lines. The specific transmission assumptions in EPA Base Case v.4.10 are described in section
3.3.
2.3.10 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. Since the retail electric market is not modeled in IPM, there
are no assumptions about the extent or timing of retail deregulation.
IPM's assumption of perfect foresight implies that economic agents know precisely the nature and
timing of the constraints that will be imposed in future years. For example, under IPM there is
complete foreknowledge of the levels, timing, and regulatory design of emission limits that will be
imposed over the entire modeling time horizon. In making decisions, agents optimize based on
this foreknowledge. However, by performing an iterative series of runs, in which new emission
limits are successively added in subsequent model run years, imperfect foresight can be
incorporated in IPM's projections.
2.3.11 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
2-10
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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 cap-and-trade, command-
and-control and renewable portfolio standards. IPM's representation of cap-and-trade programs
can include allowance banking, trading, borrowing, bonus allowance mechanisms, progressive
flow controls or emission taxes. 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.4.10.
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 7.3 million decision variables and 1.2 million constraints, EPA Base
Case v.4.10 is run on a 64 bit Windows Enterprise Server 2008 platform with four Intel Xeon 2.93
GHz dual core processors and 32 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 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 input files 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 ORL (one record line) format as needed by EPA's air quality
models.
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.4.10. This section simply lists the key input
parameters required by IPM:
Electric System
Existing Utility 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, 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
2-11
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Other System Requirements
Inter-regional Transmission Capabilities
Reserve Margin Requirements for Reliability
Area Protection
System Specific Generation Requirements
Regional Specification
Economic Outlook
Electric Demand
Firm Regional Electric Demand
Load Curves
Financial Outlook
Capital Charge Rate
Discount Rate
Fuel Supply
Fuel Supply Curves for Coal, Natural Gas, and Biomass
Fuel Price
Fuel Quality
Transportation Costs for Coal, Natural Gas, and Biomass
Air Regulatory Outlook
Air Regulations for NOX, SO2, CO2, 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. Since the entire model solution is stored, IPM can generate additional detailed
reports from the stored solution as needed. Standard IPM reports cover the following topics:
Generation
Capacity mix (by plant type and presence or absence of emission controls)
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, CO2, and Hg)
Emission allowance prices
2-12
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Appendix 2-1 Load Duration Curves Used in EPA Base Case v.4.10
This is a small exerpt of the data and graphs in Appendix 2-1. The complete data set in spreadsheet format and complete set of graphs can be
downloaded via the link found at www.epa.gov/airmarkets/progsregs/epa-ipm/BaseCasev410.htm
Month
Hours
Day
Hours
AZNM
CA-N
CA-S
COMD
DSNY
ENTG
ERCT
FRCC
GWAY
LILC
MACE
MACS
MACW
MECS
MRO
NENG
NWPE
NYC
PNW
RFCO
RFCP
RMPA
SNV
1
1
1
11,182
11,127
15,323
10,119
2,861
14,747
29,987
19,757
9,016
2,189
14,997
6,474
6,418
9,332
20,437
12,380
6,242
4,838
19,729
17,029
21,425
5,995
2,666
1
2
2
10,866
11,196
14,636
9,763
2,708
14,695
29,796
18,688
8,918
2,080
14,408
6,267
6,000
9,063
19,616
11,716
6,086
4,645
19,289
16,735
20,589
5,904
2,637
1
3
3
10,659
11,477
14,234
9,444
2,597
14,588
29,710
17,471
8,852
1,991
13,928
6,056
5,606
8,867
19,012
11,272
6,018
4,449
19,068
16,335
19,799
5,914
2,609
1
4
4
10,628
11,976
14,056
9,264
2,526
14,491
29,857
16,766
8,782
1,937
13,663
5,908
5,463
8,732
18,599
11,035
5,990
4,295
19,035
16,166
19,483
6,068
2,601
1
5
5
10,724
12,082
14,129
9,140
2,497
14,478
30,395
16,412
8,857
1,910
13,575
5,885
5,441
8,683
18,593
11,020
6,027
4,237
19,342
16,167
19,512
6,205
2,602
1
6
6
10,969
12,262
14,347
9,137
2,519
14,554
31,487
16,476
8,995
1,909
13,629
5,961
5,552
8,758
18,901
11,181
6,149
4,238
19,827
16,397
19,932
6,281
2,621
1
7
7
11,250
12,645
14,275
9,220
2,575
14,924
32,637
16,780
9,200
1,927
13,818
6,070
5,719
8,882
19,603
11,502
6,296
4,315
20,403
16,785
20,607
6,484
2,595
1
8
8
11,306
12,877
14,448
9,419
2,638
15,411
33,019
17,054
9,298
1,949
14,003
6,114
5,905
9,032
20,370
11,867
6,431
4,376
20,925
17,214
21,420
6,718
2,515
1
9
9
11,553
12,812
14,940
9,414
2,758
15,669
33,024
18,787
9,475
1,995
14,204
6,194
6,206
9,078
20,737
12,438
6,605
4,477
21,531
17,480
22,257
6,783
2,486
1
10
10
11,707
12,615
15,427
9,489
2,936
16,072
33,208
21,128
9,781
2,085
14,781
6,458
6,713
9,272
21,386
13,283
6,759
4,671
22,174
17,852
23,435
6,736
2,488
1
11
11
11,533
12,457
15,690
9,698
3,107
16,337
32,996
23,288
10,000
2,192
15,363
6,742
7,208
9,582
21,798
14,097
6,818
4,889
22,697
18,625
24,540
6,613
2,494
1
12
12
11,294
12,274
15,785
9,908
3,229
16,392
32,351
24,514
10,019
2,276
15,771
6,963
7,495
9,829
21,936
14,625
6,815
5,058
22,843
19,267
25,256
6,641
2,491
1
13
13
10,977
12,418
15,713
10,016
3,291
16,108
31,188
25,262
9,874
2,325
16,002
7,051
7,516
9,938
21,733
14,769
6,762
5,175
22,768
19,642
26,276
6,568
2,477
1
14
14
10,643
13,410
15,619
10,032
3,286
15,654
30,011
25,431
9,718
2,342
16,044
7,022
7,418
9,946
21,288
14,685
6,673
5,246
22,505
19,673
26,255
6,599
2,446
1
15
15
10,367
15,256
15,598
10,048
3,256
15,183
28,906
25,229
9,546
2,348
16,064
6,934
7,246
9,912
20,761
14,545
6,621
5,304
22,248
19,682
26,253
7,137
2,432
1
16
16
10,304
15,213
15,599
9,987
3,282
14,898
28,277
25,051
9,509
2,369
16,133
6,938
7,254
9,955
20,829
14,670
6,652
5,354
22,334
19,755
26,421
8,185
2,439
1
17
17
10,515
14,885
16,951
9,965
3,454
14,956
28,409
24,845
9,863
2,485
16,702
7,038
7,591
10,149
21,990
15,597
7,010
5,507
23,178
20,141
27,018
8,384
2,576
1
18
18
11,676
14,386
19,009
10,552
3,711
15,495
30,699
25,636
10,775
2,615
17,567
7,519
8,267
10,693
25,094
16,268
7,390
5,687
23,768
21,036
28,753
8,247
2,786
1
19
19
12,475
13,566
19,111
11,448
3,710
16,581
34,030
26,465
10,895
2,607
17,540
7,543
8,286
10,910
26,505
16,043
7,370
5,664
23,545
21,358
29,207
8,069
2,805
1
20
20
12,511
12,501
18,803
11,495
3,611
17,184
34,697
25,716
10,860
2,568
17,324
7,500
8,185
10,846
26,416
15,595
7,273
5,593
23,064
21,162
29,066
7,693
2,788
1
21
21
12,414
11,793
18,261
11,428
3,489
17,320
35,016
24,569
10,778
2,517
17,013
7,355
8,036
10,765
25,724
14,985
7,145
5,500
22,354
20,915
28,838
6,966
2,762
1
22
22
12,076
11,242
17,322
11,295
3,283
17,205
34,568
23,236
10,558
2,416
16,389
7,149
7,644
10,575
24,612
14,039
6,845
5,358
21,360
20,370
27,913
6,355
2,712
1
23
23
11,547
10,899
16,040
11,037
2,999
16,942
33,283
21,474
10,140
2,256
15,520
6,793
6,976
10,231
23,102
12,816
6,423
5,110
20,104
19,687
26,515
5,998
2,648
1
24
24
10,898
10,829
14,941
10,545
2,718
16,309
31,783
19,419
9,725
2,085
14,538
6,456
6,300
9,833
21,442
11,738
6,066
4,772
18,906
18,920
24,912
5,773
2,559
1
25
1
10,467
10,943
14,260
10,025
2,520
15,539
30,789
17,658
9,516
1,959
13,919
6,198
5,973
9,553
20,074
11,053
5,943
4,463
18,185
18,246
23,868
5,681
2,500
1
26
2
10,332
11,443
13,937
9,654
2,421
15,586
30,379
16,542
9,436
1,892
13,590
6,060
5,745
9,342
19,395
10,664
5,852
4,269
17,856
17,890
23,330
5,732
2,465
Appendix 2-1.1
-------
ERCT 2012 Summer
70000
60000
50000
40000
30000
20000
10000
601 901 1201 1501 1801 2101 2401 2701 3001 3301 3601
1 301
Appendix 2-1.2
-------
ERCT 2012 Winter
60000
50000
40000
30000
20000
10000
1 301 601 901 1201 1501 1801 2101 2401 2701 3001 3301 3601 3901 4201 4501 4801
Hour
Appendix 2-1.3
-------
-------
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.4.10.
3.1 Model Regions
EPA Base Case v.4.10 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 province4) as an integrated network. Alaska, Hawaii, Puerto Rico, and US Virgin Islands
are represented in Base Case v.4.10 as separate entities with their own self contained electricity
grids.
There are 32 IPM model regions covering the US 48 states and District of Columbia. The IPM
model regions are approximately consistent with the configuration of the 8 NERC regions, being
disaggregations of North American Reliability Council (NERC) control areas. An attempt has been
made to have the US IPM model regions reflect the administrative structure of regional
transmission organizations (RTOs) and independent system operators (ISOs). Further
disaggregation into 32 model regions allows a more accurate characterization of the operation of
the US power markets by providing the ability to represent transmission bottlenecks within the 8
NERC regions and across RTOs and ISOs.
Disaggregations that were made in the most recent previous IPM base case were retained in
Base Case 2010. Notable disaggregations include
NERC region RFC (Reliability First Corporation) includes three portions of former NERC
regions the non-Kentucky part of ECAR, MAAC, and a portion of MAIN. The remaining
portion of MAIN has been renamed COMD. ECAR has been disaggregated into RFCO,
MEGS, and RFCP and MAAC has been disaggregated into MACE, MACS, and MACW.
NERC subregion WECC-AZ-NM-SNV has been disaggregated into AZNM and SNV
NERC subregion WECC-California ISO has been disaggregated into CA-N and CA-S
NERC Region SERC has been disaggregated into 7 IPM regions (ENTG, SOU, VACA,
VAPW, TVA, TVAK (formerly ECAK), and GWAY (formerly a portion of MANO).
Several region boundaries were adjusted to reflect recent organizational changes. There were
also several name changes: MANO to GWAY, ECAM to RFCO, ECAP to RFCP, and ECAK to
TVAK.
The 11 Canadian model regions are defined strictly along provincial political boundaries.
Figure 3-1 contains a map showing all the EPA Base Case 2010 model regions. Table 3-1
defines the abbreviated region names appearing on the map and gives an approximate crosswalk
between the IPM model regions, the NERC 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.
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
4This results in a total of 11 Candian model regions being represented in EPA Base Case v.4.10
3-1
-------
(peak demand) is the maximum hourly demand within a given year after removing interruptible
demand. Table 3-2 shows the electric demand assumptions (expressed as net energy for load)
used in EPA Base Case v.4.10. It is based on the net energy for load in AEO 20105.
Figure 3-1 EPA Base Case v.4.10 Model Regions
EPA Base Case v4.10 Regions
For purposes of documentation, Table 3-2 presents the national net energy for load. However,
EPA Base Case v.4.10 models regional breakdowns of net energy for load. The regional net
energy for load is derived from the national net energy for load based on the regional demand
distribution in NERC electric demand forecasts. Model regions that represent subregions of a
NERC region are apportioned their net energy for load based on the regional load shapes, which
are developed by aggregating load for control areas within each model region.
5The electricity demand in EPA Base Case v.4.10 for the U.S. lower 48 states and the District of
Columbia is obtained by summing the "Total Net Energy for Load" for the NEMS Electric Market
Module regions as reported in the "Electric Power Projections for Electricity Market Module
Regions - Electricity and Renewable Fuel Tables 72-84" at
http://www.eia.doe.gov/oiaf/aeo/aeoref tab.html.
3-2
-------
Table 3-1 Mapping of NERC Regions and NEMS Regions with EPA Base Case v.4.10 Model
Regions
NERC
Region
TRE
FRCC
MRO
NPCC
RFC
SERC
SPP
WECC-
AZ-NM-
SNV
WECC-
California
ISO
WECC-
NWPP
WECC-
RMPA
Canada
NEMS
Region
ERGOT
FL
MAPP
MAIN
NE
NY
ECAR
MAAC
MAIN
MAIN
ECAR
STV
SPP
RA
CNV
NWP
RA
Model
Region
ERCT
FRCC
MRO
WUMS
NENG
DSNY
LILC
NYC
UPNY
RFCO
MEGS
RFCP
MACE
MACS
MACW
COMD
GWAY
TVAK
SOU
TVA
ENTG
VACA
VAPW
SPPN
SPPS
AZNM
SNV
CA-N
CA-S
PNW
NWPE
RMPA
CNAB
CNBC
CNMB
CNNB
CNNF
CNNL
CNNS
CNON
Model Region Description
Texas Regional Entity
Florida Reliability Coordinating Council
Midwest Regional Planning Organization
Wisconsin-Upper Michigan
New England Power Pool
Downstate New York
Long Island Company
New York City
Upstate New York
Reliability First Corporation - MISO
Michigan Electric Coordination System
Reliability First Corporation - PJM
Legacy Mid-Atlantic Area Council - East
Legacy Mid-Atlantic Area Council - South
Legacy Mid-Atlantic Area Council - West
Commonwealth Edison
Gateway
Tennessee Valley Authority - MISO-KY
Southern Company
Tennessee Valley Authority
Entergy
Virginia-Carolinas
Dominion Virginia Power
Southwest Power Pool - North
Southwest Power Pool - South
Western Electricity Coordinating Council -
Mexico
Western Electricity Coordinating Council -
Western Electricity Coordinating Council -
Western Electricity Coordinating Council -
Western Electricity Coordinating Council -
Western Electricity Coordinating Council -
Pool East
Western Electricity Coordinating Council -
Power Area
Alberta
British Columbia
Manitoba
New Brunswick
Newfoundland
Labrador
Nova Scotia
Ontario
Arizona, New
Southern Nevada
California North
California South
Pacific Northwest
Northwest Power
Rocky Mountain
3-3
-------
NERC
Region
Other
NEMS Model
Region Region
CNPE
CNPQ
CNSK
ALSK
HAWI
VIUS
PRCW
Model
Prince Edward Island
Quebec
Saskatchewan
Alaska
Hawaii
U.S. Virgin Islands
Puerto Rico
Region Description
Table 3-2
Year
2012
2015
2020
2030
2040
2050
Electric Load Assumptions in
EPA Base Case v.4.10
Net Energy for Load
(Billions of kWh)
4,043
4,086
4,302
4,703
5,113
5,568
Note:
This data is an aggregation of the model-region-specific net energy loads
used in the EPA Base Case v.4.10.
3.2.1 Demand Elasticity
EPA Base Case v.4.10 has the capability to model the impact of the price of power on 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 is not affected by
price and must be met, i.e., the price elasticity of demand is zero6.
3.2.2 Net Internal Demand (Peak Demand)
EPA Base Case v.4.10 has separate regional winter and summer peak demand values, as
derived from each region's seasonal load duration curve (found in Appendix 2-1). Peak projections
were estimated based on AEO 2010 load factors and the estimated energy demand projections
shown in Table 3-2. Table 3-3 ("National Non-Coincidental Net Internal Demand") 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.
Occasionally, e.g., when performing modeling of climate policies, the demand assumptions
shown in Table 3-2 will be replaced with projections of demand from economy-wide computable
general equilibrium (CGE) models which themselves take into account demand elasticity.
However, even in such cases the IPM demand elasticity capabilities will not be utilized and the
resulting IPM runs will be considered "policy" rather than "base case" runs.
3-4
-------
Table 3-3 National Non-Coincidental Net Internal Demand
Year
2012
2015
2020
2030
2040
2050
Peak
Winter
646
655
693
768
843
929
Demand (GW)
Summer
758
771
816
908
1,001
1,105
Note:
This data is an aggregation of the model-region-specific peak
demand loads used in the EPA Base Case v.4.10.
3.2.3 Regional Load Shapes
EPA uses year 2007 as the meteorological year in its air-quality modeling. In order for EPA Base
Case v.4.10 to be consistent, the year 2007 was selected as the "normal weather year"7 for all
IPM regions. The proximity of the 2007 cumulative annual heating degree days (HDDs) and
cooling degree days (CDDs) to the long-term average cumulative annual HHDs and CDDs over
the period 1971 to 2000 was estimated and found to be reasonable close. The 2007
chronological hourly load data were assembled by aggregating individual utility load curves taken
from Federal Energy Regulatory Commission Form 714 data.
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 4.10 characterizes
the U.S. lower 48 states, the District of Columbia, and Canada into 43 different power market
regions by means of 32 model regions in the U.S. and 11 in Canada. EPA Base Case 4.10
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 4.10.
3.3.1 Inter-regional Transmission Capability
Table 3-48 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 (N-1). 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 (N-0). They specify the sum of the maximum firm
transfer capability between sub-regions plus incremental curtailable non-firm transfer capability.
Non-firm TTCs are used for energy transfers since they provide a lower level of reliability than
7The 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.
8ln the column headers in Table 3-4 the term "Energy (MW)" is equivalent to non-firm TTCs and
the term "Capacity (MW)" is equivalent to firm TTCs.
3-5
-------
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.4.10
From
AZNM
CA-N
CA-S
COMD
DSNY
ENTG
ERCT
FRCC
GWAY
LILC
To
CA-S
NWPE
RMPA
SNV
SPPS
CA-S
NWPE
PNW
AZNM
CA-N
NWPE
PNW
SNV
GWAY
MRO
RFCO
RFCP
WUMS
LILC
MACE
NENG
NYC
UPNY
GWAY
MRO
SOU
SPPN
SPPS
TVA
ENTG
SPPS
SOU
COMD
ENTG
MRO
RFCO
SPPN
TVA
TVAK
DSNY
MACE
NENG
Energy
(MW)
3,627
300
690
4,634
400
3,700
150
3,675
3,627
3,000
1,400
3,100
4,688
2,050
825
1,620
4,500
825
1,290
2,000
1,120
3,700
3,400
910
150
2,250
1,120
4,494
1,681
1,001
979
2,000
1,100
2,804
405
6,299
285
1,812
200
530
650
616
Capacity
(MW)
2,428
300
690
4,634
400
3,700
100
3,675
2,428
2,400
1,400
3,100
4,688
2,050
825
1,110
788
825
1,290
2,000
1,120
3,700
3,400
140
150
2,250
140
735
1,681
1,001
979
2,000
1,100
2,100
405
1,848
285
1,812
200
530
590
616
Wheeling Charge
(mills/kWh)
2.9
~
~
~
2.9
2.9
2.9
2.9
~
2.9
2.9
2.9
2.9
2.9
2.9
2.9
~
2.9
2.9
~
~
2.9
2.9
2.9
2.9
2.9
2.9
2.9
2.9
2.9
2.9
2.9
~
~
2.9
2.9
2.9
~
2.9
2.9
3-6
-------
From
MACE
MACS
MACW
MEGS
MRO
NENG
NWPE
NYC
PNW
RFCO
To
NYC
DSNY
LILC
MACW
NYC
MACW
RFCP
VAPW
MACE
MACS
RFCO
RFCP
UPNY
CNON
RFCO
RFCP
COMD
CNON
CNSK
ENTG
GWAY
NWPE
RMPA
SPPN
WUMS
CNNB
CNPQ
DSNY
LILC
AZNM
CA-N
CA-S
MRO
PNW
RMPA
SNV
DSNY
LILC
CA-N
CA-S
CNBC
NWPE
COMD
GWAY
MACW
MEGS
Energy
(MW)
420
500
650
2,000
1,200
3,500
2,500
2,600
6,200
5,000
2,208
3,300
1,085
1,968
2,776
3,900
610
100
165
2,000
320
200
310
1,494
800
1,000
803
980
616
265
160
1,920
150
2,002
749
300
1,999
175
4,000
3,100
2,000
1,505
2,760
7,078
3,100
4,603
Capacity
(MW)
420
500
521
2,000
600
3,000
750
2,600
5,800
1,350
504
2,044
1,085
1,968
1,904
683
610
100
165
2,000
320
200
310
1,494
800
1,000
803
980
473
265
120
1,920
150
2,002
749
250
1,999
175
4,000
3,100
1,000
1,505
1,360
3,504
2,274
825
Wheeling Charge
(mills/kWh)
~
2.9
2.9
2.9
~
~
~
~
2.9
~
2.9
2.9
~
2.9
2.9
2.9
2.9
2.9
~
2.9
2.9
2.9
~
2.9
2.9
2.9
2.9
~
2.9
2.9
2.9
~
~
~
~
2.9
2.9
2.9
~
2.9
~
2.9
~
3-7
-------
From
RFCP
RMPA
SNV
SOU
SPPN
SPPS
TVA
TVAK
UPNY
VACA
To
RFCP
TVAK
COMD
MACS
MACW
MEGS
RFCO
TVA
TVAK
VACA
VAPW
AZNM
MRO
NWPE
AZNM
CA-S
NWPE
ENTG
FRCC
TVA
VACA
ENTG
GWAY
MRO
SPPS
AZNM
ENTG
ERCT
SPPN
ENTG
GWAY
RFCP
SOU
TVAK
VACA
GWAY
RFCO
RFCP
TVA
CNON
CNPQ
DSNY
MACW
NENG
RFCP
SOU
TVA
Energy
(MW)
12,908
815
3,100
2,500
3,900
3,700
15,041
1,000
1,000
3,002
3,080
690
310
735
4,785
4,688
300
2,950
3,600
3,742
1,358
3,745
1,200
600
700
400
9,030
650
1,200
2,919
1,550
1,500
2,258
2,000
664
200
3,365
1,000
1,500
2,000
1,000
4,550
735
150
4,117
3,242
3,586
Capacity
(MW)
7,951
270
3,100
350
1,075
1,762
8,525
1,000
537
2,042
953
690
310
735
4,785
4,688
300
2,950
3,600
3,742
1,358
1,260
1,200
600
700
400
2,310
650
1,200
2,919
1,550
263
2,258
1,073
664
200
1,225
175
632
1,325
1,000
4,550
735
150
438
3,242
3,586
Wheeling Charge
(mills/kWh)
2.9
2.9
~
~
~
2.9
2.9
2.9
2.9
2.9
-
~
2.9
~
~
2.9
~
2.9
2.9
2.9
2.9
2.9
2.9
2.9
~
2.9
2.9
2.9
~
2.9
2.9
2.9
2.9
~
2.9
2.9
2.9
2.9
~
2.9
2.9
~
2.9
2.9
2.9
2.9
2.9
3-8
-------
From
VAPW
WUMS
To
VAPW
MACS
RFCP
VACA
COMD
MRO
Energy
(MW)
1,942
2,100
5,460
1,849
1,125
270
Capacity
(MW)
1,942
2,100
1,952
1,849
1,125
270
Wheeling Charge
(mills/kWh)
2.9
2.9
2.9
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 4.10. 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. Wherever available, the maximum values for firm and non-firm
TTCs were obtained from public sources. Where public sources were not available, the maximum
values for firm and non-firm TTCs are based on ICF's expert view.
It should be noted that each transmission link between model regions shown in Table 3-4
represents 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.
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
developed from the 2004 NERC Summer Assessment and 2004 NERC Winter Assessment. 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 model region is connected to multiple model regions contained in the state of New York,
with each link between New England and a New York model region described by its own TTCs.
However, there is a maximum limit on the total amount of transfers that the New England region
may transfer to the whole of New York, which is represented by the annual joint capacity limit
between the New England model region and the relevant New York model regions.
Table 3-5 Annual Joint Capacity and Energy Limits to Transmission Capabilities Between
Model Regions in EPA Base Case v.4.10
Region Connections
ECAR to MAAC
ECARtoMAIN
ECAR to TVA
ECAR to VACAR
ENTG to SPP
Transmission Path
RFCO to MACW
RFCP to MACS
RFCP to MACW
RFCO to COMD
RFCP to COMD
RFCO to GWAY
TVAK to GWAY
TVAK to TVA
RFCP to TVA
RFCP to VACA
RFCP to VAPW
ENTG to SPPN
ENTG to SPPS
Joint Constraint Limit
1,385
2,593
3,561
2,022
338
3-9
-------
Region Connections
LILCtoNYC&DSNY
MAAC to ECAR
MAAC to NPCC
MAIN to ECAR
MAIN to MAPP
MAPP to MAIN
MAPP to WECC
NENGtoNY
NPCC to MAAC
NYtoNENG
NYC&DSNYtoLILC
SPP to ENTG
TVA to ECAR
VACAR to ECAR
WECC to MAPP
Transmission Path
LILC to DSNY
LILC to NYC
MACS to RFCP
MACWto RFCO
MACWtoRFCP
MACE to DSNY
MACE to LILC
MACE to NYC
MACWto UPNY
COMD to RFCO
COMD to RFCP
GWAY to TVAK
GWAY to RFCO
COMD to MRO
GWAY to MRO
WUMS to MRO
MRO to COMD
MRO to GWAY
MRO to WUMS
MRO to NWPE
MRO to RMPA
NENG to DSNY
NENG to UPNY
NENG to LILC
DSNY to MACE
LILC to MACE
NYC to MACE
UPNY to MACW
DSNY to NENG
LILC to NENG
UPNY to NENG
DSNY to LILC
NYC to LILC
SPPN to ENTG
SPPS to ENTG
TVA to TVAK
TVA to RFCP
VACA to RFCP
VAPWtoRFCP
NWPE to MRO
RMPA to MRO
Joint Constraint Limit
530
4,715
1,708
3,649
962
1,238
710
1,550
2,353
1,750
1,465
1,362
1,226
4,278
660
Note:
Source: 2004 NERC Summer Assessment, 2004 NERC Winter Assessment
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 4.10 assumes a wheeling charge of 2.9 mills per
kWh for electricity transmission between IPM model regions that fall within different market
3-10
-------
regions, such as transmission between Northern California and the Pacific Northwest. However,
the wheeling charge is not applied to transmission between model regions that are within the
same market region, such as transmission between Northern California (model region CA-N) and
Southern California (model region CA-S). The wheeling charge applied between IPM model
regions can be found in Table 3-4.
3.3.4 Transmission Losses
The EPA Base Case 4.10 assumes a two percent inter-regional transmission loss of energy
transferred, in line with ElA's Annual Energy Outlook (AEO) 2010.
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.4.10 but Mexico is not. International electric trad ing between the
U.S. and Mexico is represented by an assumption of net imports based on information from AEO
2010. 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.4.10
Net Imports from Mexico
(billions kWh)
2012
1.57
2015
1.57
2020
1.11
2030
0.89
2040
0.89
2050
0.89
Notes:
Imports & exports transactions from Canada are endogenously modeled in IPM.
Source: AEO 2010
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.4.10 can be found in the National Electrical Energy Data System (NEEDS
v.4.10), a database which provides IPM with information on all currently operating and planned-
committed electric generating units. NEEDS v.4.10 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 on the unit. In EPA Base Case v.4.10 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.4.10. They are based on data from North American Electric Reliability
Council's Generating Availability Data System (NERC GADS) 2001 to 2005 and AEO 2010.
Appendix 3-9 shows the availability assumptions for all generating units in EPA Base Case v.4.10.
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Table 3-7 Availability Assumptions in the EPA Base Case v.4.10
Unit Type
Biomass
Coal Steam
Combined Cycle
Combustion Turbine
Gas/Oil Steam
Geothermal
IGCC
Pumped Storage
Solar
Wind
Annual Availability (%)
83
32-95
85
89-91
78-92
87
85
90
90
95
Notes:
Values shown are a range of all of the values modeled within the EPA Base Case v.4.10.
Availabilities of coal steam units are based on historical capacity factors.
In the EPA Base Case v.4.10, 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 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 906 from 2002 through 2006 data. A
discussion of capacity factors and generation profiles for wind and solar technologies is contained
in section 4.4.5 and Appendices 4-1 and 4-2.
Table 3-8 Seasonal Hydro Capacity Factors (%) in the EPA Base Case v.4.10
Model
Region
AZNM
CA-N
CA-S
COMD
DSNY
ENTG
ERCT
FRCC
GWAY
MACE
MACS
MACW
MEGS
Winter Capacity
Factor
27.4%
36.7%
38.7%
40.6%
57.8%
35.4%
13.5%
48.4%
19.2%
30.9%
14.8%
47.5%
54.1%
Summer Capacity
Factor
32.2%
50.1%
50.4%
45.5%
50.2%
32.5%
19.6%
47.4%
22.5%
29.2%
18.7%
33.7%
56.9%
Annual Capacity
Factor
29.4%
42.3%
43.6%
42.6%
54.6%
34.2%
16.1%
48.0%
20.6%
30.2%
16.4%
42.3%
55.3%
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Model
Region
MRO
NENG
NWPE
PNW
RFCO
RFCP
RMPA
SNV
SOU
SPPN
SPPS
TVA
TVAK
UPNY
VACA
VAPW
WUMS
Winter Capacity
Factor
31 .8%
44.9%
28.7%
40.6%
66.0%
32.7%
18.0%
18.0%
25.3%
16.5%
21 .2%
43.2%
32.4%
66.8%
23.7%
22.8%
52.6%
Summer Capacity
Factor
43.7%
41.1%
47.6%
44.0%
89.2%
30.9%
31 .5%
23.3%
22.1%
17.8%
27.2%
37.1%
38.6%
63.1%
22.8%
19.0%
57.3%
Annual Capacity
Factor
36.8%
43.3%
36.6%
42.0%
75.6%
31 .9%
23.7%
20.2%
24.0%
17.0%
23.7%
40.7%
35.0%
65.2%
23.3%
21 .2%
54.6%
Note:
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.4.10 vary from
region to region and over time. Further discussion of the nuclear capacity factor assumptions in
EPA Base Case v.4.10 is contained in Section 4.5.
3.5.3 Turndown
Turndown assumptions in EPA Base Case v.4.10 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.4.10 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 International 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. 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
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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.4.10 reserve
margin assumptions are shown in Table 3-9.
Table 3-9 Planning Reserve Margins in EPA Base Case v.4.10
Model Region
AZNM
CA-N
CA-S
CNAB
CNBC
CNMB
CNNB
CNNF
CNNL
CNNS
CNON
CNPE
CNPQ
CNSK
COMD
DSNY
ENTG
ERCT
FRCC
GWAY
LILC
MACE
MACS
MACW
MEGS
MRO
NENG
NWPE
NYC
PNW
RFCO
RFCP
RMPA
SNV
SOU
SPPN
SPPS
TVA
TVAK
UPNY
VACA
VAPW
WUMS
Reserve Margin
15.7%
16.7%
16.7%
12.8%
12.8%
15.0%
20.0%
20.0%
20.0%
20.0%
18.3%
20.0%
10.0%
15.0%
15.0%
16.5%
15.0%
12.5%
15.0%
15.0%
16.5%
15.0%
15.0%
15.0%
15.0%
15.0%
16.0%
10.8%
16.5%
10.8%
15.0%
15.0%
14.3%
15.7%
15.0%
13.6%
13.6%
12.0%
15.0%
16.5%
15.0%
15.0%
16.0%
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3.7 Power Plant Lifetimes
EPA Base Case v.4.10 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 for
economic reasons. Other types of units are not provided an economic retirement option.
Nuclear Retirement at Age 60: Existing nuclear units are forced to retire in EPA Base Case
v.4.10 at the completion of age 60. Today's nuclear fleet totals more than 100 GW. A 60-year
lifetime reduces the current fleet to under 5 GW in 2050. This is illustrated in Figure 3-2. For a
complete listing of the existing nuclear units represented in EPA Base Case v.4.10, including their
online year and other characteristics, see Appendix 4-3.
Figure 3-2 Scheduled Retirements of Existing Nuclear Capacity Under 60-Year Life
Assumption
Impact of 60-Year Lifetime on Existing Nuclear Fleet
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The 60-year lifetime assumption is based on several factors. At the time that this base case was
prepared there were many instances of the U.S. Nuclear Regulatory Commission (NRC) granting
license extensions of 20 years beyond the initial 40 year operating licenses authorized by the
NRC for commercial nuclear power plants under the Atomic Energy Act of 1954. At the time of
the release of EPA Base Case v.4.10, the NRC had granted license renewals to 50 operating
reactors allowing them to operate for 60 years with fifteen additional applications under review and
the owners of 21 other units announcing their intention to file for 20-year license extensions. All of
these applications would allow the units to operate to age 60.
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At the same time, there were no units in the U.S. nuclear fleet licensed to operate past age 609.
In keeping with the practice of the EPA base case representing legal provisions that are on the
books or immediately pending, a conservative approach was adopted of reflecting the current
maximum licensing period of 60 years for the nuclear units in EPA Base Case v.4.10.
Another factor in the decision to implement the 60-year nuclear life assumption is the degree of
uncertainty surrounding nuclear life extensions past age 60. As noted in ElA's review of the 60
year nuclear life question, uncertainties include:
The absence, to date, of publicly available plans and cost estimates for potential major capital
expenditures involved with extensions to age 80 such as the replacement of reactor vessels,
containment structures, or buried piping and cables.
Possible future additional regulatory requirements which could result in expensive upgrades at
nuclear power plants and figure into life extension decisions. Among those mentioned in
ElA's review was a rule that was recently the subject of the Supreme Court case Entergy Corp
v. RiverkeepeMO, which focused on whether or not the EPA could conduct cost-benefit
analyses to determine whether a plant needed to replace open-cycle cooling water systems
with closed-cycle systems.
The assumption of nuclear retirements at age 60 in EPA Base Case v.4.10 contrasts to a certain
degree with the assumption made in AEO 2010. Due to AEO 2010's shorter time horizon
compared to the EPA base case (i.e., 2035 compared to 2050), EIA did not have to explicitly
adopt an 80 year nuclear life assumption (as would have been necessary in EPA Base Case
v.4.10), only that "the operating lives of existing nuclear power plants would be extended at least
through 2035.11" The basis for the decision appears to be that "The nuclear industry has
expressed strong interest in continuing the operation of existing nuclear facilities, and no particular
technical issues have been identified that would impede their continued operation.12"
Although the adopted assumptions differ in EPA Base Case v.4.10 and AEO 2010, there is
agreement on the importance of performing side cases using the alternative assumptions. In the
case of EPA Base Case v.4.10 this will mean performing sensitivity analysis runs with an 80
nuclear lifetime assumption.
9 The Energy Information Administration has an excellent review and summary of the issues
involved in the 60 year nuclear life question. Although EPA's base case does not adopt the same
assumption as AEO 2010, the text in this section relied heavily on the EIA review. With respect to
the status of applications for renewals beyond age 60, the EIA review notes the following: "In
December 2009, the Oyster Creek Generating Station in Lacey Township, New Jersey, became
the first nuclear power plant in the United States to begin its 40th year of operation. With Oyster
Creek and other nuclear plants of similar vintage just beginning to enter their first period of license
renewal, it probably will be at least 5 to 10 years before there is any clear indication as to whether
plant operators will be likely to seek further extensions of their plants' operating lives." The EIA
review also observes ". . . the NRC and the nuclear power industry are preparing applications for
license renewals that would allow continued operation beyond 60 years, the first of which is
scheduled to be submitted by 2013. In February 2008, DOE and the NRC hosted a joint workshop
titled "Life Beyond 60," with a broad group of nuclear industry stakeholders meeting to discuss this
issue. The workshop's summary report outlined many of the technical research needs that
participants agreed were important to extending the life of the existing fleet of U.S. nuclear plants."
Energy Information Administration (EIA), U.S. Department of Energy, "U.S. nuclear power plants:
Continued life or replacement after 60?" Annual Energy Outlook 2010 with Projections to 2035
(DOE/EIA-0383(2010)), May 11, 2010, www.eia.doe.qov/oiaf/aeo/nuclear power.html.
10Supreme Court of the United States, "Entergy Corp. v. Riverkeeper, Inc., et al.," No. 07-588
(October Term, 2008 www.supremecourtus.gov/opinions/ 08pdf/07-588.pdf.
11EIA, op.cit.
12EIA, ibid.
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3.8 Heat Rates
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.4.10 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.4.10 are based on values from AEO 2008. These values were
screened and adjusted using a procedure developed by EPA to ensure that the heat rates used in
EPA Base Case v.4.10 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.4.10
Plant Type
Coal Steam
Oil/Gas Steam
Combined Cycle - Natural Gas
Combined Cycle - Oil
Combustion Turbine - Natural Gas - 80
Combustion Turbine - Natural Gas < 80
Combustion Turbine - Oil and Oil/Gas -
Combustion Turbine - Oil and Oil/Gas <
1C Engine - Natural Gas
1C Engine - Oil and Oil/Gas - 5 MWand
1C Engine - Oil and Oil/Gas < 5 MW
MW and above
MW
80 MW and above
80 MW
above
Heat Rate (Btu/kWh)
Lower Upper
Limit Limit
8,300 14,500
8,300 14,500
5,500 15,000
6,000 15,000
8,700 18,700
8,700 36,800
6,000 25,000
6,000 36,800
8,700 18,000
8,700 20,500
8,700 42,000
3.9 Existing Environmental Regulations
This section describes the existing federal, regional, and state SO2, NOX, mercury, and CO2
emissions regulations that are represented in the EPA Base Case v.4.10. The first three
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.
Note on Clean Air Interstate Rule (CAIR): In December 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. Until EPA's work was completed, CAIR, which
includes a cap-and-trade system for SO2 and NOX emissions, was temporarily reinstated.
However, although CAIR's provisions were still in effect when EPA Base Case v.4.10 was
released, it is not included in the base case to allow EPA Base Case v.4.10 to be used to analyze
the regulations proposed to replace CAIR.
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.4.10. The SIP requirements define "regulatory SO2
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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.4.10 there are 6 different sulfur grades of bituminous coal, 3 different grades
of sub-bituminous coal, 3 different grades of lignite, and 1 sulfur grade of residual fuel oil. There
are 2 different SO2 scrubber options 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.
National and Regional SO2 Regulations: The national program affecting SO2 emissions in EPA
Base Case v.4.10 is the SO2 allowance trading 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 overtime across all affected electric generation sources.
The annual SO2 caps over the modeling time horizon in EPA Base Case v.4.10 reflect the
provisions in Title IV. Since EPA Base Case v.4.10 uses year 2012 as the first analysis year, a
projection of allowance banking behavior through the end of 2011 and specification of the
available 2012 allowances are needed to initialize the modeling. EPA developed the projection of
the banked allowances (11 million) going into 2012. Calculating the available 2012 allowances
involved deducting allowance surrenders due to NSR settlements and state regulations from the
2012 SO2 cap of 8.95 million tons. The surrenders totaled 270.6 thousand tons in allowances,
leaving 8.679 million of 2012 allowances remaining. Table 7-4 shows the initial bank and 2012
allowance specification along with the SO2 caps for the entire modeling time horizon. Specifics of
the allowance surrender requirements under state regulations and NSR settlements can be found
in Appendices 3-2 and 3-3.
EPA Base Case v.4.10 also includes a representation of the Western Regional Air Partnership
(WRAP) Program, a regional initiative involving Arizona, New Mexico, Oregon, Utah, 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.4.10
through a combination of system level NOX programs and generation unit-level NOX limits.
The system level NOX regulation represented in EPA Base Case v.4.10 is the NOX SIP Call trading
program. This trading program affects all fossil units in 20 northeastern states13 and the District of
Columbia. The program is only in effect during the ozone season (May - September). The
program includes state-specific NOX budgets. However, since the program allows for trading
among units in different states, the total annual NOX SIP Call budget of 527,580 tons is used in
EPA Base Case v.4.10, rather than the state-specific budgets. The specifications for the SIP Call
are presented in Table 7-4.
13The states included in the SIP Call program are Alabama, Connecticut, Delaware, Illinois,
Indiana, Kentucky, Maryland, Massachusetts, Michigan, Missouri, New Jersey, New York, North
Carolina, Ohio, Pennsylvania, Rhode Island, South Carolina, Tennessee, Virginia, and West
Virginia.
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The representation of unit-level NOX limits includes Title IV unit specific rate limits and Clean Air
Act Reasonable Available Control Technology (RACT) requirements for controlling NOX emissions
from electric generating units in ozone non-attainment areas or in the Ozone Transport Region14
(OTR). Both of these limits are captured in the specific NOX emission rates assigned to each unit
represented in the base case. 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.4.10 the NOX emission rate of a unit can only change if the unit is retrofitted with
NOX pollution control equipment.
NOX Rates in NEEDS, v.4.10 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 2007. The emission rates themselves reflect the
impact of the 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 policy affecting that
unit in a model run.
The reason for having four NOX rates in NEEDS is to allow all possible modeling scenarios
involving NOX controls to be set up. The four NOX rates are designated as Mode 1-4, and are
designed to include all the NOX rates possible for a unit with its current configuration of NOX
combustion and post-combustion controls. The four NOX rates are:
Mode 1: Applies to units not covered by a NOX control policy. Specifically, this is the NOX
rate with post-combustion controls shut off. For units without post-combustion controls, it's
their uncontrolled NOX rate.
Mode 2: A unit, which has post-combustion controls, runs them, but a unit without post-
combustion controls operates as usual.
Mode 3: Applies to the off-season NOX rate for units affected by a seasonal NOX policy. For
units with post-combustion controls, this is the NOX rate with post-combustion controls shut
off. For units without post-combustion controls, it's the NOX rate with state-of-the-art
combustion controls operating. (Exception: In the SIP Call region current combustion controls
are assumed to be retained.)
Mode 4: NOX rate applicable under a NOX policy. For SCR units, it's the NOX rate with the
SCR operating. For SNCR units, it's the NOX rate with SNCR operating plus state-of-the-art
combustion controls operating if required to attain rate limits. For units without post-
combustion controls, it's the NOX rate with state-of-the-art combustion controls operating.
(Exception: In the SIP Call region current combustion controls are assumed to be retained.)
The program that sets up a new model run uses a series of algorithms (decision rules) to
determine which of the four NOX rates is selected:
A unit covered under an annual NOX emission limit is assigned the Mode 4 NOX rate (winter
and summer seasons).
A unit covered by a summer season NOX emission limit, but not an annual NOX limit, is
assigned the Mode 4 NOX rate in the summer season but the Mode 3 NOX rate in the winter
season.
A unit covered by a mercury emission limit and not by a NOX emission limit is assigned the
Mode 2 NOX rate in both winter and summer seasons. (Note: In the case of mercury limits,
Mode 2 applies since it implies operation of an SCR or SNCR. This equipment, in
combination with SO2 and particulate controls, offers as a co-benefit the reduction and capture
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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of mercury. See Chapters in the v.4.10 documentation fora discussion of the calculation
mercury emission modification factors (EMF).)
A unit not covered by either an annual or a summer NOX limit nor mercury control
requirements is assigned the Mode 1 NOX rate in both winter and summer seasons.
The Mode 1-4 NOX rates for each generating unit are included in the NEEDS, v.4.10 database,
described in Chapter 4. Appendix 3-1 and accompanying Tables 3-1.1, 3-1.2, and 3-1.3 give
further information on the procedures employed to derive the four NOX rate modes and give
specific examples of generating units that fit each of the Mode 1-4 specifications.
Additional NOX rate assumptions include default NOX rates of 0.25 Ibs/MMBtu for existing biomass
units and 0.09 Ibs/MMBtu for existing landfill gas units.
3.9.3 CO2 Regulations and Renewable Portfolio Standards
The Regional Greenhouse Gas Initiative (RGGI) is a year-round CO2 cap and trade program
affecting fossil fired electric power plants 25 MWor larger in Connecticut, Delaware, Maine, New
Hampshire, New Jersey, New York, Vermont, Rhode Island, Massachusetts, and Maryland. Table
7-4 shows the specifications for RGGI that are implemented in EPA Base Case v.4.10.
Renewable Portfolio Standards (RPS) generally refer 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.4.10 the state RPS requirements are represented at a regional level utilizing the
aggregate regional representation of RPS requirements that is implemented in AEO 201015 as
shown in Appendix 3-6. This appendix shows the RPS requirements that apply to the NEMS
(National Energy Modeling System) regions used in AEO. The RPS requirement for a particular
NEMS region applies to all IPM regions that are predominantly contained in that NEMS region.
3.9.4 State Specific Environmental Regulations
EPA Base Case v.4.10 represents laws and regulations in 25 states affecting emissions from the
electricity sector. The laws and regulations had to either be on the books or expected to come
into force. Appendix 3-2 summarizes the provisions of state laws and regulations that are
represented in EPA Base Case 4.10.
3.9.5 New Source Review (NSR) Settlements
The 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.4.10 includes NSR settlements with 20 electric power companies. A summary of the
units affected and how the settlements were modeled can be found in Appendix 3-3.
Seven state settlements and five citizen settlements are also represented in EPA Base Case
v.4.10. These are summarized in Appendices 3-4 and 3-5 respectively.
3.9.6 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 on line in each model region. Across all model regions the emission and removal
15Energy Information Administration, U.S. Department of Energy, Assumptions to Annual Energy
Outlook 2010: Renewable Fuels Module (DOE/EIA-0554(2010)), April 9, 2010, Table 13.4
"Aggregate Regional RPS Requirements, www.eia.doe.gov/oiaf/aeo/assumption/renewable.html
and www.eia.doe.qov/oiaf/aeo/assumption/pdf/renewable tbls.pdf
3-20
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rate capabilities of potential new units are the same. It should be noted that, new coal units cannot
be built in the CA-N, CA-S, NYC, LILC, or NENG model regions due to particularly stringent state
emission limits placed on fossil fired units. The specific assumptions regarding the emission and
removal rates of potential new units in EPA Base Case v.4.10 are presented in Table 3-11. (Note:
Nuclear, wind, solar, and fuel cell technologies are not included in Table 3-11 because they do
not emit any of the listed pollutants.) For additional details on the modeling of potential new units
see Chapter 4.
3.10 Capacity Deployment Constraints
Due to its extended time horizon and the policies that EPA Base Case v.4.10 is expected to be
used to analyze, capacity deployment constraints for the more capital intensive generation
technologies and retrofits (new nuclear, advanced coal with carbon capture, and carbon capture
retrofits) were incorporated into the base case. 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 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.
3-21
-------
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.
Appendix 3-07 shows the joint capacity deployment constraint on advanced coal with carbon
capture and storage (CCS) and new nuclear. Appendix 3-08 shows the capacity deployment
constraint on new nuclear in itself. The bar graph in Appendix 3-08 illustrates how building
capacity in earlier years increases the maximum capacity that can be built over the entire
modeling time horizon.
3-22
-------
Table 3-11 Emission and Removal Rate Assumptions for Potential (New) Units in EPA Base Case v.4.10
Gas
SO2
NOX
Hg
C02
Controls,
Removal,
and
Emissions
Rates
Removal /
Emissions
Rate
Emission
Rate
Removal /
Emissions
Rate
Removal /
Emissions
Rate
Supercritical
Pulverized
Coal - Wet
Scrubber
98% with a
floor of 0.06
Ibs/MMBtu
0.06
Ibs/MMBtu
90%
205.2-217.3
Ibs/MMBtu
Supercritical
Pulverized
Coal - Dry
Scrubber
93% with a
floor of 0.065
Ibs/MMBtu
0.06
Ibs/MMBtu
90%
205.2-217.3
Ibs/MMBtu
Integrated
Gasification
Combined
Cycle
99%
0.013
Ibs/MMBtu
90%
205.2-217.3
Ibs/MMBtu
Advanced
Coal with
Carbon
Capture
99%
0.013
Ibs/MMBtu
90%
90%
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
Combustio
n Turbine
None
0.011
Ibs/MMBtu
Natural
Gas:
.0001 38
Ibs/MMBtu
Oil:
0.483
Ibs/MMBtu
Natural
Gas:
117.08
Ibs/MMBtu
Oil:
161.39
Ibs/MMBtu
Biomass
Conventional
Direct-Fired
Boiler
0.08
Ibs/MMBtu
0.36
Ibs/MMBtu
0.57
Ibs/MMBtu
None
Biomass
Gasification
Combined
Cycle
0.08
Ibs/MMBtu
0.102
Ibs/MMBtu
0.57
Ibs/MMBtu
None
Geothermal
None
None
3.70
None
Landfill
Gas
None
0.09
Ibs/MMBtu
None
None
3-23
-------
-------
Appendix 3-1 NOX Rate Development in EPA Base Case v.4.10
The following questions (Q) and answers (A) are intended to provide further background on the
four NOX rates found in the NEEDS, v.4.10 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 policies 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 policy
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:
Mode 1= Uncontrolled Base Rate
Mode 2= Controlled Base Rate
Mode 3= Uncontrolled Policy Rate
Mode 4 = Controlled Policy Rate
The operational states associated with each of the four NOX rates are shown in the second and
third columns in the table below.
Q3: What NOX policies in a model run result in the assignment of each of the NOX rates?
A3: The policies causing each rate to be assigned are shown in the last column in the table below.
Interpreting the Mode 1-4 NOX Rates in NEEDS
Name
Mode 1 =
Uncontrolled
Base Rate
Controlled
Base Rate
Mode 3 =
Uncontrolled
Policy Rate
Operational State of NOX
Controls
Units with post combustion
NOX controls: Do they
operate the controls?
Units without post-
combustion controls: Do
they upgrade to state-off-
the-art combustion controls?
Units with post combustion
NOX controls: Do they
operate the controls?
Units without post-
combustion controls: Do
they upgrade to state-off-
the-art combustion controls?
Units with post combustion
NOX controls: Do they
operate the controls?
Units without post-
combustion controls: Do
they upgrade to state-off-
No
No
Yes
No
No
Yes
NOX Policies Causing This Rate
To be Assigned
If the unit is not covered by any NOX limit
in the run, pre-assign this as its NOX rate
If the unit is covered by a mercury
policy, pre-assign this as its NOX rate
Explanation: Post-combustion NOX
controls figure in mercury reduction but
NOX combustion controls do not, so the
operational state (in column 2) fits the
requirements of the policy
If the unit is covered by a summer NOX
limit pre-assign this as its winter NOX
rate.
Appendix 3-1.1
-------
Name
Mode 4 =
Controlled
Policy Rate
Operational State of NOX
Controls
the-art combustion controls?
Units with post combustion
NOX controls: Do they
operate the controls?
Units without post-
combustion controls: Do
they upgrade to state-off-
the-art combustion controls?
Yes
Yes
NOX Policies Causing This Rate
To be Assigned
If the unit is covered by a summer NOX
limit pre-assign this as its summer NOX
rate.
If the unit is covered by an annual NOX
limit, pre-assign this as its winter and
summer NOX rates.
Q4: How are the values of the Mode 1-4 NOX rates derived?
A4: 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 them is beyond the scope
of this illustration. Basically, here's how the values would be derived:
Mode 1
For all coal units Mode 1 = Winter NOX rate
Mode 2
For coal units without NOX
Mode 2 = Mode 1 rate
post-combustion controls
For coal units with NOX post-combustion controls,
Min{max[Mode 1 NOX rate * (1-removal efficiency), floor rate], ETS Summer NOX rate}
Where
For an SCR,
Removal efficiency = 90%
Floor rate = 0.06 Ib/MMBtu;
For an SNCR,
Removal efficiency = 35%
No floor rate is applicable
Mode3
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
For coal units without post-combustion NOX controls
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 3-1.2), then Mode 1 = Base rate. Go to Step 3
If Mode 1 < Cut-off (in Table 3-1.2), then the unit has SOA control and
Go to Step 5 using the Mode 1 rate as the provisional SOA NOX rate.
For coal listed with combustion controls
If Mode 1 > Cut-off (in Table 3-1.2), then unit has non-SOA combustion controls.
Go to Step 2
Appendix 3-1.2
-------
If Mode 1 < Cut-off (in Table 3-1.2), then the unit has SOA control and
Go to Step 5 using the Mode 1 rate as the provisional SOA NOX rate.
For coal units with post-combustion NOX controls
For coal units with SCR
Mode 1 = Mode 3
For coal units with SNCR
If Mode 1 < Cut-off (in Table 3-1.2), then the unit has SOA control and
Mode 1 = Mode 3
If Mode 1 > Cut-off (in Table 3-1.2), then unit has non-SOA combustion controls.
Go to Step 2
Step 2: For units with non-SOA combustion controls, determine their Base NOX rate, i.e., the unit's
uncontrolled emission rate without combustion controls, using the appropriate equation (not in
boldface italics) in Table 3-1.3 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 3.
Step 3: Use the appropriate equations (in boldface italics) in Table 3-1.3 to calculate the NOX rate
with SOA combustion controls.
Step 4: Compare the value calculated in Step 3 to the applicable NOX floor rate in Table 3-1:2.
For units with post-combustion controls
If the value from Step 3 is > floor, use the Step 3 value as Mode 3 NOX rate. Otherwise, use the
floor as the Mode 3 NOX rate.
For units without post-combustion controls
If the value from Step 3 is > floor, use the Step 3 value as the provisional SOA NOX rate.
Otherwise, use the floor as their provisional SOA NOX rate.
Go to Step 5.
Step 5: For units without post combustion controls compare the provisional SOA NOX rate
obtained in previous steps to their Summer NOX rate.
If Summer NOX rate < provisional SOA NOX rate, then Mode 3 = summer NOX rate.
If Summer NOX rate > provisional SOA NOX rate, then
Mode 3 = provisional SOA NOX rate.
Mode 4
For units without post-combustion controls
Mode 4 = Mode 3
For units with SCR post-combustion controls
Mode 4 = Mode 2
For units with SNCR post-combustion controls
Mode 4 = minimum {(1-.35) * Mode 3, Summer NOX rate}
Note: The (1-.35) term in the equation above represents the 35% NOX removal efficiency of
SNCR.
Q5: Is there anything else that might be useful to understand about the Mode 1 - 4 NOX rates.
Appendix 3-1.3
-------
A5: There are several things to note about the Modes 1-4 designations. "Controlled" refers to the
rates provided by post combustion NOX controls, i.e., selective catalytic reduction (SCR) or
selective non-catalytic reduction (SNCR), if they are present at the unit. For generating units that
do not have post-combustion controls, the controlled rate will be the same as the uncontrolled
rate. For generating units that do have post-combustion controls, the controlled and uncontrolled
rates will differ. Base and Policy NOX rates will be same if the unit has state-of-the-art NOX
combustion controls or is in the SIP Call region where current combustion controls are assumed to
be retained. Base and policy rates will differ if a unit does not currently have state-of-the-art
combustion controls that would be installed in response to a NOX policy. Examples of each of
these instances are shown in Table 3-1.1.
Other things worth noting are:
(a) In general, winter NOX rates reported in EPA's Emission Tracking System were used as
proxies for the uncontrolled base NOX rates.
(b) If a unit does not report having combustion controls, but has an emission rate below a specific
cut-off rate (shown in Table 3-1.2), it is considered to have combustion controls.
(c) For units with combustion controls that were not state-of-the-art, emission rates without those
combustion controls were back-calculated and then policy rates were derived assuming the
reductions provided by state-of-the art combustion controls.
(d) The NOX rates achievable by state-of-the-art combustion controls vary by coal rank
(bituminous and sub-bituminous) and boiler type. The equations used to derive these rates are
shown in Table 3-1.3.
Q6: What are examples of the Mode 1-4 NOX for some actual operating generating units?
A6: Table 3-1.1 gives the Mode 1-4 NOX rates for real generating units. They are meant to
illustrate a range of situations that can arise.
Appendix 3-1.4
-------
Table 3-1.1 Examples of Base and Policy NOX Rates Occurring in EPA Base Case v.4.10
Plant
Name
Unique ID
Post-
Combustion
Control
Uncontrolled
NOX Base
Rate
Controlled
NOX Base
Rate
Uncontrolled
NOX Policy
Rate
Controlled
NOX Policy
Rate
Explanation
Situation 1 : For generating units that do not have post-combustion controls, the controlled and uncontrolled rates will be the same.
Four
Corners
2442_B_1
None
0.809
0.809
0.524
0.524
Situation 4 also applies, i.e., unit had LNB and
now added OFA so see drop in policy rates.
Situation 2: For generating units that do have post-combustion controls, the controlled and uncontrolled rates will differ.
Big Sandy
1353_B_BSU2
SCR
0.638
0.064
0.638
0.064
(1) Has SCR so see difference between
uncontrolled and controlled rates
(2) Situation 3b also applies.
Situation 3a: Base and Policy NOX rates will be same if the unit has state-of-the-art NOX combustion controls or ...
Greene
County
Roxboro
10_B_2
2712_B_1
None
SCR
0.316
0.900
0.316
0.084
0.316
0.900
0.316
0.084
Situation 1 also applies.
Situation 2 also applies.
Situation 3b: ... is in the SIP Call region where current combustion controls are assumed to be retained.
Thomas Hill
Waukegan
2168 B MBS
883_B_17
SCR
None
0.223
0.710
0.060
0.710
0.223
0.710
0.060
0.710
Situation 2 also applies.
(1) Has NOX combustion control and is in SIP so
doesn't get added combustion control. High NOX
rate because it is a cyclone unit
(2) Situation 1 also applies.
Situation 4: Base and policy rates will differ if a unit does not currently have state-of-the-art combustion controls and would install such controls in
response to a NOX policy.
Clay
Boswell
1893_B_4
SNCR
0.231
0.150
0.152
0.099
(1) Drop in uncontrolled policy NOX rate
compared to uncontrolled base rate is due to
addition of combustion controls. (Note 0.32 is
floor.)
(2) Unit has SNCR so Situation #2a also applies
and you see a 35% drop between uncontrolled
and controlled NOX rates.
Appendix 3-1.5
-------
Table 3-1.2 Cutoff and Floor NOX Rates (Ib/MMBtu) in EPA Base Case v.4.10
Boiler Type
Wall-Fired
Dry- Bottom
Tangentially-
Fired
Cell-Burners
Cyclones
Vertically-
Fired
Cutoff Rate (Ibs/MMBtu)
Bituminous
0.43
0.34
0.43
0.62
0.57
Subbituminous Lignite
0.33 0.29
0.24 0.22
0.43 0.43
0.67 0.67
0.44 0.44
Floor
Bituminous
0.32
0.24
0.32
0.47
0.49
Rate (Ibs/MMBtu)
Subbituminous
0.18
0.12
0.32
0.49
0.25
Lignite
0.18
0.17
0.32
0.49
0.25
Table 3-1.3 NOX Removal Efficiencies for Different Combustion Control Configurations in
EPA Base Case v.4.10
(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 + OF A
LNB
LNB + OF A
LNC1
LNC2
LNC3
LNC1
LNC2
LNC3
Fraction of
Removal
0.163 + 0.272*
Base NOX
0.373 + 0.272*
Base NOX
0.135 + 0.541*
Base NOX
0.285 + 0.547*
Base NOX
0.162 + 0.336*
Base NOX
0.212 + 0.336*
Base NOX
0.362 + 0.336*
Base NOX
0.20 + 0.717*
Base NOX
0.25 + 0.717*
Base NOX
0.35 + 0.777*
Base NOX
Default
Removal
0.568
0.778
0.574
0.724
0.42
0.47
0.62
0.563
0.613
0.773
Notes:
LNB = Low NOX Burner
OFA = Overfire Air
LNC = Low NOX Control
Appendix 3-1.6
-------
Appendix 3-2 State Power Sector Regulations included in EPA Base Case
v.4.10
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
40C.F.R. Part
60
Executive
Order 19 and
Regulations of
Connecticut
State Agencies
(RCSA) 22a-
174-22
Executive
Order 19,
RCSA22a-198
& Connecticut
General
Statues (CGS)
22a-1 98
Public Act No.
03-72 & RCSA
22a-1 98
Regulation
1148: Control
of Stationary
Combustion
Turbine ECU
Emissions
Regulation No.
1146: Electric
Generating
Unit (ECU)
Multi-Pollutant
Regulation
Emission
Type
NOX
Hg
NOX
SO2
Hg
NOX
S02
Hg
NOX
NOX
S02
Emission Specifications
0.02 Ibs/MMBtu annual PPMDV for combined
cycle EGUs which commenced operation after
April 1 , 2003
90% removal of Hg content of fuel or 0.0087
Ib/GWH-hr 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)
2012 & 2013: 80% reduction of Hg content of
fuel or 0.01 74 Ib/GW-hr annual reduction for
Pawnee Station 1 and Rawhide Station 101
201 4 through 201 6: 80% reduction of Hg
content of fuel or 0.01 74 Ib/GW-hr annual
reduction for all coal units > 25 MW
2017 onwards: 90% reduction of Hg content of
fuel or 0.0087 Ib/GW-hr annual reduction for all
coal units > 25 MW
0.15 Ibs/MMBtu annual rate limit for all fossil
units > 15MW
0.33 Ibs/MMBtu annual rate limit for all fossil
units > 15MW
90% removal of Hg content of fuel or 0.0087
Ib/GW-hr 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 NOxannually 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
2003
2008
2009
2009
Appendix 3-2.1
-------
State/ Region
Georgia
iii-
INinois
Louisiana
Maine
Bill
Multipollutant
Control for
Electric Utility
Steam
Generating
Units
Title 35,
Section
217.706
Title 35, Part
225, Subpart
B: Control of
Hg Emissions
from Coal Fired
Electric
Generation
Units
Title 35 Part
225; Subpart F:
Combined
Pollutant
Standards
Title 33 Part II -
Chapter 22,
Control of
Nitrogen
Oxides
Chapter 145
NOX Control
Program
Statue 585-B
Title 38,
Chapter 4:
Protection and
Improvement
of Air
Emission
Type
Hg
SCR,
FGD, and
Sorbent
Injection
Baghouse
controls to
be
installed
NOX
NOX
SO2
Hg
NOX
S02
Hg
NOX
NOX
Hn
ny
Emission Specifications
2012: 80% removal of Hg content of fuel or
0.01 74 Ib/GW-hr annual reduction for all coal
units > 25 MW
2013 onwards: 90% removal of Hg content of
fuel or 0.0087 Ib/GW-hr annual reduction for all
coal units > 25 MW
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
0.1 1 Ibs/MMBtu annual rate limit and ozone
season rate limit for all Dynergy and Ameren
coal steam units > 25 MW
2013 & 2014: 0.33 Ibs/MMBtu annual rate limit
for all Dynergy and Ameren coal steam units >
25 MW
2015 onwards: 0.25 Ibs/MMBtu annual rate limit
for all Dynergy and Ameren coal steam units >
25 MW
90% removal of Hg content of fuel or 0.08
Ibs/GW-hr annual reduction for all Ameren and
Dynergy coal units > 25 MW
0.1 1 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 0.1 1 Ibs/MMBtu in 2019
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
1 .2 Ibs/MMBtu ozone season PPMDV for all
single point sources that emit or have the
potential to emit 5 tons or more of SO2 into the
atmosphere
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
25 Ibs annual cap for any facility including
EGUs
Implementation
Status
Implementation
from 2008
through 2015,
depending on
plant and control
type
2004
2012
2013
2015
2012
2013
2015
2005
2005
2010
Appendix 3-2.2
-------
State/ Region
Maryland
Massachusetts
Michigan
Minnesota
Missouri
Montana
Bill
Maryland
Healthy Air Act
310 CMR 7.29
Part 15.
Emission
Limitations and
Prohibitions -
Mercury
Minnesota Hg
Emission
Reduction Act
10CSR10-
6.350
Montana
Mercury Rule
Adopted
10/16/06
Emission
Type
NOX
SO2
Hg
NOX
S02
Hg
Hg
Hg
NOX
Hg
Emission Specifications
7.3 MTons summer cap and 1 6.7 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 Bayton Point,
Mystic Generating Station, Somerset Station,
Mount Tom, Canal, and Salem Harbor
3.0 Ibs/MWh annual GPS for Bayton Point,
Mystic Generating Station, Somerset 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, Somerset
Station, Mount Tom, Canal, and Salem Harbor
2013 onwards: 95% removal of Hg content of
fuel or 0.00000250 Ibs/MWh annual GPS for
Brayton Point, Mystic Generating Station,
Somerset Station, Mount Tom, Canal, and
Salem Harbor
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 units > 250 MW
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 MWthe 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
Implementation
Status
2009
2006
2015
2008
2004
2010
Appendix 3-2.3
-------
State/ Region
New
Hampshire
New Jersey
New York
North Carolina
Bill
RSA 125-0:
11-18
ENV-A2900
Multiple
pollutant
annual budget
trading and
banking
program
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
N.J.A.C. Title
7, Chapter 27,
Subchapter 19,
Table 4
Part 237
Part 238
Mercury
Reduction
Program for
Coal-Fired
Electric Utility
Steam
Generating
Units
NC Clean
Smokestacks
Act: Statute
143-21 5.1 07D
Emission
Type
Hg
NOX
SO2
Hg
NOX
NOX
NOX
S02
Hg
NOX
SO2
Emission Specifications
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% removal of Hg content of fuel annually for
all coal-fired units
95% removal of Hg content of fuel annually for
all MSW incinerator units
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
0.38 for tangential dry-bottom coal boilers
serving an ECU
0.45 for wall-fired dry-bottom coal boilers
serving an ECU
0.55 for cyclone-fired dry-bottom coal boilers
serving an ECU
0.20 for tangential oil and/or gas boilers serving
an ECU
0.28 for wall-fired oil and/or gas boilers serving
an ECU
0.43 for cyclone-fired oil and/or gas boilers
serving an ECU
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
39.91 MTons non-ozone season cap for fossil
fuel units > 25 MW
1 31 .36 MTons 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. 1 5,
1990.
0.60 Ibs/TBtu annual rate limit for all coal units
> 25 MW developed after Nov.1 5 1 990
25 MTons annual cap for Progress Energy coal
plants > 25 MW and 31 MTons annual cap for
Duke Energy coal plants > 25 MW
201 2: 1 00 MTons annual cap for Progress
Energy coal plants > 25 MWand 150 MTons
annual cap for Duke Energy coal plants
>25MW
2013 onwards: 50 MTons annual cap for
Progress Energy coal plants > 25 MWand 80
Implementation
Status
2012
2007
2007
2007
2007
2004
2005
2010
2007
2009
Appendix 3-2.4
-------
State/ Region
Oregon
Pacific
Northwest
Texas
Utah
Wisconsin
Bill
Oregon
Administrative
Rules, Chapter
345, Division
24
Oregon Utility
Mercury Rule -
Existing Units
Oregon Utility
Mercury Rule -
Potential Units
Washington
State House
Bill 3141
Senate Bill 7
Chapter 101
Chapter 117
R307-424
Permits:
Mercury
Requirements
for Electric
Generating
Units
NR428
Wisconsin
Administration
Code
Emission
Type
C02
Hg
Hg
CO2
S02
NOX
NOX
Hg
NOX
Emission Specifications
MTons annual cap for Duke Energy coal plants
>25MW
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
>25MW
25 Ibs rate limit for all potential coal units > 25
MW
$1 .45/Mton cost (2004$) for all new fossil-fuel
power plant
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 1 992:
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
Annual rate limits in Ibs/MMBtu for coal fired
boilers > 1,000 MMBtu/hr :
Wall fired, tangential fired, cyclone fired, and
fluidized bed: 2009: 0.15, 2013 onwards: 0.10
Arch fired: 2009 onwards: 0.18
Implementation
Status
1997
2012
2009
2004
2003
2007
2013
2009
Appendix 3-2.5
-------
State/ Region
Bill
Chapter NR
446. Control of
Mercury
Emissions
Emission
Type
Hg
Emission Specifications
Annual rate limits in Ibs/MMBtu for coal fired
boilers between 500 and 1 ,000 MMBtu/hr:
Wall fired: 2009: 0.20; 2013 onwards: 0.17 in
2013
Tangential fired: 2009 onwards: 0.15
Cyclone fired: 2009: 0.20; 2013 onwards: 0.15
Fluidized bed: 2009: 0.15; 2013 onwards: 0.10
Arch fired: 2009 onwards: 0.18
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: 0.41
Biologically derived fuel CTs between 25 and
49 MW: 0.1 5
Annual rate limits for CCs in Ibs/MMBtu:
Natural gas CCs > 25 MW: 0.04
Distillate oil CCs > 25 MW: 0.1 8
Biologically derived fuel CCs > 25 MWs: 0.15
Natural gas CCs between 10 and 24 MW: 0.19
2012 through 2014: 40% reduction in total Hg
emissions for all coal-fired units in electric
utilities with annual Hg emissions > 100 Ibs
2015 onwards: 90% removal of Hg content of
fuel or 0.0080 Ibs/GW-hr reduction in coal fired
EGUs>150MW
80% removal of Hg content of fuel or 0.0080
Ibs/GW-hr reduction in coal fired EGUs > 25
MW
Implementation
Status
2010
Appendix 3-2.6
-------
Appendix 3-3 New Source Review (NSR) Settlements in EPA Base Case v.4.10
Company
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
Reference
Alabama Power
James H.
Miller
Alabama
Units 3 &
4
Install and
operate FGD
continuously
95%
12/31/2011
Operate existing
SCR continuously
0.1
5/1/2008
0.03
12/31/2006
With 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 ARC system
1/1/2021
http://www.epa.gov
/compliance/resour
ces/cases/civil/caa
/alabamapower.ht
ml
Minnkota Power Cooperat ve
Beginning 1/01/2006, Minnkota shall not emit more than 31 ,000 tons of SO2/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.
Milton R.
Young
Minnesota
Unifl
Unit 2
Install and
continuously
operate FGD
Design,
upgrade, and
continuously
operate FGD
95% if wet
FGD, 90%
if dry
90%
12/31/2011
12/31/2010
continuously operate
Over-fire AIR, or
equivalent
technology with
emission rate < .36
Install and
continuously operate
over-fire AIR, or
equivalent
technology with
0.36
0.36
12/31/2009
12/31/2007
wet
FGD,
.01 5 if
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 2/31/2015, 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
http://www.epa.gov
/compliance/resour
ces/cases/civil/caa
/minnkota.html
SIGECO
FB Culley
Indiana
Unifl
Repower to
natural gas
(or retire)
12/31/2006
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://www.epa.gov
/compliance/resour
ces/cases/civil/caa
/si gecofb.htm I
Appendix 3-3.1
-------
Company
State
Unit
Unit 2
Units
Settlement Actions
Retire/Repower
Acซion ซ|Jฃป
SOz control
Equipment
Improve and
continuously
operate existing
FGD (shared by
Units 2 and 3)
Improve and
continuously
operate existing
FGD (shared by
Units 2 and 3)
P
Removal
95%
95%
Effective
Date
6/30/2004
6/30/2004
NOX Control
Equipment
Rate
Effective
Date
Operate Existing
SCR Continuously
0.1
9/1/2003
PM or Mercury Control
Equipment Rate Eff^ve
Install and
continuously 0.01 5 6/30/2007
operate a Baghouse
Allowance
Retirement
Retirement
Allowance Restriction
Restriction ซฃซ
Reference
PSEG FOSSIL
Bergen
Hudson
Mercer
New Jersey
New Jersey
New Jersey
Unit 2
Unit 2
Units 1 &
Repower to
combined 12/31/2002
Install Dry FGD
(or approved alt.
technology) and
continually
operate
Install Dry FGD
or approved alt.
technology) and
continually
operate
0.15
0.15
12/31/2006
12/31/2010
Install SCR (or
approved tech) and
continually operate
Install SCR (or
approved tech) and
continually operate
0.1
0.13
5/1/2007
5/1/2006
Install Baghouse (or
approved 0.015 12/31/2006
technology)
The provision did not
specify an amount of
SC>2 allowances to be
surrendered. It only
provided that excess
from compliance with
NSR settlement
provisions must be
retired.
http://www.epa.gov
/compliance/resour
/psegllc.html
TECO
Big Bend
Florida
Units 1 &
2
Units
Existing
Scrubber
(shared by Units
1 &2)
Existing
Scrubber
95% (95%
or .25)
93% if
Units 3 & 4
09/1/00
(01/01/13)
2000
Install SCR
Install SCR
0.1
0.1
5/1/2009
5/1/2009
The provision did not
specify an amount of
SO2 allowances to be
surrendered. It only
allowances resulting
http://www.epa.gov
/compliance/resour
ces/cases/civil/caa
/teco.html
Appendix 3-3.2
-------
Company
and Plant
Gannon
State
Florida
Unit
Unit 4
Six units
Settlement Actions
Retire/Repower
Action EfDMeVe
Retire all six
coal units
MW of coal
capacity to
natural gas
SOz control
Equipment
(shared by Units
3&4)
Existing
Scrubber
(shared by Units
3&4)
Percent
Removal
or Rate
are
operating
93% if
Units 3 & 4
are
operating
Effective
Date
(01/01/10)
6/22/2005
NOx Control
Equipment
Install SCR
Rate
0.1
Effective
Date
7/1/2007
PM or Mercury Control
Equipment
Rate
Effective
Date
Allowance
Retirement
Retirement
from compliance with
NSR settlement
provisions must be
retired.
Allowance Restriction
Restriction _
Reference
WEPCO
WEPCO shall comply with the following system wide average NO* emission rates and total NO* tonnage permissible: by 1/1/2005 an emission 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 1/1/201 3 an emission rate of 0.32
and 33,300 tons.
Presque Isle
Pleasant
Prairie
Wisconsin
Wisconsin
Units 1 -
4
Units 5 &
6
Units 7 &
8
Unit 9
1
2
Retire or
controls
Install and
continuously
operate FGD (or
approved equiv.
tech)
95% or 0.1
12/31/2012
Install and
continuously
operate FGD (or
approved control
tech)
Install and
continuously
operate FGD (or
approved control
tech)
95% or 0.1
95% or 0.1
12/31/2006
12/31/2007
Install SCR (or
approved tech) and
continually operate
Install and operate
low NOK burners
Operate existing low
NOK burners
Operate existing low
NOK burners
Install and
continuously operate
SCR (or approved
tech)
Install and
continuously operate
SCR (or approved
tech)
0.1
0.1
0.1
12/31/2012
12/31/2003
12/31/2005
12/31/2006
12/31/2006
12/31/2003
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://www.epa.gov
/compliance/resour
ces/cases/civil/caa
/wepco.html
Appendix 3-3.3
-------
Company
and Plant
Oak Creek
Port
Washington
Valley
State
Wisconsin
Wisconsin
Wisconsin
Unit
Units 5 &
6
Unit/
Units
Units 1 -
4
Boilers 1
-4
Settlement Actions
Retire/Repower
Acซion
12/3 1/04 for
Units 1 -3.
""" eni'r"/
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)
Percent
Removal
or Rate
95% or 0.1
95% or 0.1
95% or 0.1
Effective
Date
12/31/2012
12/31/2012
12/31/2012
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)
Rate
0.1
0.1
0.1
Effective
Date
12/31/2012
12/31/2012
12/31/2012
Operate existing low
NOX burner
30 days
after entry
of consent
decree
PM or Mercury Control
Equipment Rate Eff^ve
Allowance
Retirement
Retirement
Allowance Restriction
Restriction **%
Reference
VEPCO
The Total Permissible NO*
will have a system wide em
Mount Storm
Chesterfield
Chesapeake
Energy
West
Virginia
Virginia
Virginia
Emissions in tons) from VEPCO system are: 104,000 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 there after. Beginning 1/1/201 3 they
ssion rate no greater then 0.15 Ib/MMBtu.
Units 1 -
3
Unit 4
Units
Unite
Units 3 &
4
Construct or
improve FGD
95% or
0.15
1/1/2005
Construct or
improve FGD
Construct or
improve FGD
95% or
0.13
95% or
0.13
10/12/2012
1/1/2010
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
1/1/2008
1/1/2013
1/1/2012
1/1/2011
1/1/2013
On or before March
31 of every year
beginning in 2013
and continuing
thereafter, VEPCO
shall surrender
45,000 SO2
allowances.
http://www.epa.gov
/compliance/resour
ces/cases/civil/caa
/vepco.html
Appendix 3-3.4
-------
Company
and Plant
Clover
Possum
Point
State
Virginia
Virginia
Unit
Units 1 &
2
Units 3 &
4
Settlement Actions
Retire/Repower
Action
Retire and
repower to 5/2/2003
natural gas
SOz control
Equipment
Improve FGD
Percent
Removal
or Rate
95% or
0.13
Effective
Date
9/1/2003
NOx Control
Equipment
Rate
Effective
Date
PM or Mercury Control
Equipment
Rate
Effective
Date
Allowance
Retirement
Retirement
Allowance Restriction
Restriction _
Reference
Santee Cooper
Santee Cooper shall comply with the following system wide averages for NOK 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. ForSO2 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.
Cross
Winyah
Grainger
South
Carolina
South
Carolina
South
Carolina
Unifl
Unit 2
Unifl
Unit 2
Units
Unit 4
Unit 1
Unit 2
Upgrade and
continuously
operate FGD
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
95%
87%
95%
95%
90%
90%
6/30/2006
6/30/2006
12/31/2008
12/31/2008
12/31/2008
12/31/2007
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
Install and
continuously operate
SCR
Operate lowNOx
burner or more
stringent technology
Operate low NOx
burner or more
stringent technology
0.1
0.11/0.1
0.11/0.1
0.12
0.14/0.12
0.13/0.12
5/31/2004
05/31/04
and
05/31/07
11/30/04
and
11/30/04
1 1/30/2004
1 1/30/2005
and
11/30/08
11/30/05
and
11/30/08
6/25/2004
5/1/2004
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.
httD://www.eoa.aov
/comoliance/resour
ces/cases/civil/caa
/sant eecoooer.htm
I
Appendix 3-3.5
-------
Company
Jeffries
State
Unit
Units 3, 4
Settlement Actions
Retire/Repower
Action EfDซeVe
SOz control
Equipment
Percent
Removal
or Rate
Effective
Date
NOx Control
Equipment
Operate low NOx
stringent technology
Rate
Effective
Date
6/25/2004
PM or Mercury Control
Equipment
Rate
Effective
Date
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
Effective
Date
Reference
Ohio Edison
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 Units 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.
No later than 8/11/2005, Ohio Edison shall install and operate low NO* burners on Sammis Units 1-7 and overtired air on Sammis Units 1,2,3,6, and 7. No later than 12/1/2005, Ohio Edison shall
NOK emissions from Samm
W.H.
Sammis
Plant
Ohio
s Units 1 -5.
Unifl
Unit 2
Units
Unit 4
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
50%
rem oval
Ib/MMBtu
50%
rem oval
1 1
Ib/MMBtu
50%
rem oval
or 1.1
Ib/MMBtu
12/31/2008
12/31/2008
12/31/2008
6/30/2009
Install SNCR
(or approved
alt. tech) &
operate
continuously
Operate
existing SNCR
continuously
Operate low NO,
burners and overfire
air by 12/1/05; install
(or approved
alt. tech) &
operate
continuously by
12/31/07
Install SNCR
(or approved
0.25
0.25
0.25
0.25
10/31/2007
2/15/2006
12/1/2005
and
10/31/2007
10/31/2007
nstall advanced combustion control optimization with software to minimize
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
forSO2. For
calendar year 2006
through 201 7, Ohio
Edison may
accumulate SO2
allowances for use at
the Sammis, Burger,
and Mansfield plants,
equipped with SO2
Emission Control
Standards.
Beginning in 2018,
Ohio Edison shall
surrender unused
restricted SO2
http://www.epa.gov
/compliance/resour
ces/cases/civil/caa
/oh ioedison.htm I
Appendix 3-3.6
-------
Company
Mansfield
Plant
State
Pennsylvani
Unit
Units
Unite
Unit/
Unit 1
Unit 2
Settlement Actions
Retire/Repower
Action
Effective
Date
SOz control
Equipment
approved equiv.
control tech)
Install Flash
Dryer Absorber
or ECO2 (or
approved equiv.
control tech) &
operate
continuously
Install FGD3 (or
approved equiv.
control tech) &
operate
continuously
Install FGD (or
approved equiv.
control tech) &
operate
continuously
Upgrade
existing FGD
Upgrade
existing FGD
P
Removal
or Rate
50%
rem oval
or 1.1
Ib/MMBtu
removal or
0.13
Ib/MMBtu
removal or
0.13
Ib/MMBtu
95%
95%
Effective
Date
6/29/2009
6/30/2011
6/30/2011
12/31/2005
12/31/2006
NOx Control
Equipment
alt. tech) &
operate
continuously
Install SNCR
(or approved
alt. tech) &
Operate
Continuously
Install SNCR
(or approved
alt. tech) &
operate
continuously
Operate
existing SNCR
Continuously
Rate
0.29
"Minimum
Extent
Practicable"
"Minimum
Extent
Practicable"
Effective
Date
3/31/2008
6/30/2005
8/1 1/2005
PM or Mercury Control
Equipment
Rate
Effective
Date
Operate
Existing
ESP
Continuously
Operate
Existing
ESP
Continuously
0.03
0.03
1/1/2010
1/1/2010
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
Effective
Date
Reference
Appendix 3-3.7
-------
Company
and Plant
Eastlake
Burger
State
Ohio
Ohio
Unit
Units
Units
Unit 4
Units
Settlement Actions
Retire/Repower
Action EffrSeVe
JthaMrast 12/31/2011
biomass
fuel, up to 12/31/2011
20% low
sulfur coal.
SOz control
Percent _
Equipment Removal Effeซlve
or Rate
Upgrade
95% 10/31/2007
existing FGD
NOx Control
Equipment
Rate
Effective
Date
Install low NO,
burners, over-fired
airandSNCRS
operate continuously
"Minimize
Emissions to
the
Extent
Practicable"
12/31/2006
PM or Mercury Control
Equipment
Rate
Effective
Date
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
Effective
Date
Reference
Mirantl1*
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 NO, 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. Beginn ng 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
Ib/MMBtuNO,.
Potom ac
River Plant
Virginia
Unifl
Unit 2
Units
Unit 4
Units
Install low NO,
burners (or more
effective tech) &
operate continuously
Install low NO,
burners (or more
effective tech) &
operate continuously
Install low NO,
burners (or more
effective tech) &
operate continuously
5/1/2004
5/1/2004
5/1/2004
http://www.epa.gov
/compliance/resour
ces/cases/civil/caa
/mirant.html
Appendix 3-3.8
-------
Company
and Plant
Morgan! own
Plant
Chalk Point
State
Maryland
Unit
Unifl
Unit 2
Unifl
Unit 2
Settlement Actions
Retire/Repower
Action
Effective
Date
SOz control
Equipment
P
Removal
or Rate
Effective
Date
Install and
continuously
operate FGD (or
equiv.
technology)
Install and
continuously
operate FGD (or
equiv.
technology)
95%
95%
6/1/2010
6/1/2010
NOx Control
Equipment
Install SCR
(or approved
alt. tech) &
operate continuously
Install SCR
(or approved
alt. tech) &
operate continuously
Rate
0.1
0.1
Effective
Date
5/1/2007
5/1/2008
PM or Mercury Control
Equipment
Rate
Effective
Date
Allowance
Retirement
Retirement
For each year after
Mirant commences
FGD operation at
Chalk Point, Mirant
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 than
the total amount of
SO2 emissions
allowed under this
Section XVIII.
Allowance Restriction
Restriction
Effective
Date
Reference
Illinois Power
System-wide NO, Emission Annual Caps: 15,000 to
201 3 onward.
bald win
Illinois
Units 1 &
2
Units
ns 2005; 14,000 tons 2006; 13,800 tons 2007 onward. System-wide SO2 Emiss on Annual Caps: 66,300 tons 2005 - 2006; 65,000 tons 2007; 62,000 tons 2008 - 2010; 57,000 tons 201 1; 49,500 tons 20
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
12/31/2011
12/31/2011
Operate O FA &
existing SCR
continuously
Operate OFA and/or
low NOi burners
0.1
0.12 until
12/30/12; 0.1
from 12/31/12
8/1 1/2005
08/11/05
and
12/31/12
Install &
continuously
operate Baghouse
Install &
continuously
operate Baghouse
0.015
0.015
12/31/2010
12/31/2010
By year end 2008,
Dynergy will
surrender 12,000
SO2 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
and each year
thereafter it will
surrender 30,000
allowances. Ifthe
2; 29,000 tons
http://www.epa.gov
/compliance/resour
ces/cases/civil/caa
/illinoispower.html
Appendix 3-3.9
-------
Company
and Plant
Havana
Hennepin
Vermilion
Wood River
Kentucky Uti
EW Brown
Generating
Station
State
Illinois
Illinois
Illinois
Illinois
Unit
Unite
Unifl
Unit 2
Units 1 &
2
Units 4 &
5
Settlement Actions
Retire/Repower
Action
Effective
Date
SOz control
Equipment
Install wet or dry
FGD (or
approved equiv.
alt. tech) &
operate
continuously
Percent
Removal
or Rate
1.2
Ib/MMBtu
until
12/30/2012
;0.1
Ib/MMBtu
from
12/31/2012
onward
1.2
1.2
1.2
1.2
Effective
Date
8/11/2005
and
12/31/2012
7/27/2005
7/27/2005
1/31/2007
7/27/2005
NOX Control
Equipment
Operate OFA and/or
low NOK burners &
operate existing
SCR continuously
Operate OFA
and/or lowNOK
burners
Operate OFA
and/or low NO,
burners
Operate OFA
and/or lowNOx
burners
Operate OFA
and/or lowNOK
burners
Rate
0.1
"Minimum
Extent
Practicable"
"Minimum
Extent
Practicable"
"Minimum
Extent
Practicable"
"Minimum
Extent
Practicable"
Effective
Date
8/1 1/2005
8/1 1/2005
8/1 1/2005
8/1 1/2005
8/1 1/2005
PM or Mercury Control
Equipment
Install &
continuously
operate Bag house,
then install ESP or
alt. PM equip
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
For Bag-
house:
0.015
Ib/MMBt
u; For
ESP:
0.03
Ib/MMBt
u
0.03
0.03
0.03
0.03
Effective
Date
For
Baghouse:
12/31/12;
For ESP:
12/31/05
12/31/2006
12/31/2006
12/31/2010
12/31/2005
Allowance
Retirement
Retirement
surrendered
allowances result in
nsufficient remaining
allowances allocated
to the units
comprising the DMG
system, DMG can
request to surrender
fewer SO2
allowances.
Allowance Restriction
Region ซEiซ
Reference
ities Company
Kentucky
Units
Install FGD
97% or
0.100
12/31/2010
Install and
continuously operate
SCR by 12/31/201 2,
continuously operate
low NO, boiler and
OFA.
0.07
12/31/2012
Continuously
operate ESP
0.03
12/31/2010
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.
SO2 and N OK
allowances may not
be used for
compliance, and
emissions
decreases for
purposes of
complying with the
Consent Decree do
not earn credits.
httD://www.eoa.aov
/comoliance/resour
ces/cases/civil/caa
/ku com oanv.html
Salt River Project Agricultural Improvement and Power District (SRP)
Appendix 3-3.10
-------
Company
and Plant
Generating
Station
State
Arizona
Unit
Unit 1 or
Unit 2
Unit 1 or
Unit 2
Settlement Actions
Retire/Repower
Acซion
SOz control
Equipment
Immediately
begin
continuous
operation of
existing FGDs
on both units,
install new FGD.
Install new FGD
Percent
Removal
or Rate
95% or
0.08
95% or
0.08
Effective
Date
New FGD
installed by
1/1/2012
1/1/2013
NOX Control
Equipment
Install and
continuously operate
low NOX burner and
SCR
Install and
continuously operate
low NOX burner
Rate
0.32 prior to
SCR
installation,
0.080 after
0.32
Effective
Date
LNBby
06/01/2009
, SCR by
06/01/2014
6/1/201 1
PM or Mercury Control
Equipment
Optimization and
continuous
operation of existing
ESPs.
Rate
0.03
Effective
Date
Optimization
begins
immediately,
rate limit
begins
01/01/12
(date of new
FGD
installation)
Optimization
begins
immediately,
rate limit
begins
01/01/13
(date of new
FGD
installation)
Allowance
Retirement
Retirement
Beginning in 2012, all
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.
Allowance Restriction
Restriction
SO2 and N Ox
allowances may not
be used for
compliance, and
emissions
decreases for
purposes of
complying with the
Consent Decree do
not earn credits.
Effective
Date
Reference
httD://www.eoa.aov
/comoliance/resour
ces/cases/civil/caa
/srp.html
American Electric Power
Eastern System-Wde
At least
600MW from
various units
West
Virginia
Indiana
Sporn
1-4
Clinch
River
1-3
Tanners
Creek
renter 12/31'2ฐ18
re-power
Annual Cap
(tons)
450,000
450,000
420,000
350,000
340,000
275,000
260,000
235,000
184,000
174,000
Year
2010
2011
2012
2013
2014
2015
2016
2017
2018
201 9 and
thereafter
Annual Cap
(tons)
96,000
92,500
92,500
85,000
85,000
85,000
75,000
72,000
Year
2009
2010
2011
2012
2013
2014
2015
201 6 and
thereafter
N Ox and SO2
allowances that
would have been
made available by
emission reductions
pursuant to the
Consent Decree
must be surrendered.
N Ox and 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
NOx allowances
relative to the CAIR
Allocations, and
restricts the use of
some. See par. 74-
79 for details.
Reducing emissions
below the Eastern
System -Wide
Annual Tonnage
Limitations for NOx
and SO2 earns
super compliance
allowances.
http://www.epa.gov
/compliance/resour
ces/cases/civil/caa
/americanelectricp
ower1007.html
Appendix 3-3.11
-------
Company
and Plant
Amos
Big Sandy
Cardinal
Clinch River
Conesville
State
West
Virginia
West
Virginia
Kentucky
Ohio
Virginia
Ohio
Unit
1-3
Kam m er
1-3
Unit 1
Unit 2
Units
Unifl
Unit 2
Unit 1
Unit 2
Units
Units 1 -
3
Unit 1
Unit 2
Settlement Actions
Retire/Repower
Action EffrSeVe
Retire,
retrofit, or a * ฐ
re-power y
Retire, Dgte Qf
re-power ^
SOz control
Equipment
Percent
Removal
or Rate
Effective
Date
Install and
continuously
operate FGD
Install and
continuously
operate FGD
Install and
continuously
operate FGD
Burn only coal
with no more
than 1.75
Ib/MMBtu
annual average
Install and
continuously
operate FGD
Install and
continuously
operate FGD
Install and
continuously
operate FGD
Install and
continuously
operate FGD
Plant-wide
annual cap:
21 ,700
tons from
2010 to
2014, then
16,300
after
1/1/2015
12/31/2009
12/31/2010
12/31/2009
Date of
entry
12/31/2015
12/31/2008
12/31/2008
12/31/2012
2010-
2014,2015
and
thereafter
NOx Control
Equipment
Rate
Effective
Date
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 low NO,
burners
1/1/2008
1/1/2009
1/1/2008
Date of
entry
1/1/2009
1/1/2009
1/1/2009
1/1/2009
Date of
entry
PM or Mercury Control
Equipment Rate
Effective
Date
Continuously
operate ESP ฐ'03
Continuously
operate ESP ฐ'03
12/31/2009
12/31/2009
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
Effective
Date
Reference
Appendix 3-3.12
-------
Company
and Plant
Gavin
Glen Lyn
Kam m er
Kanawha
River
Mitchell
Mountaineer
Muskingum
River
State
Ohio
Virginia
West
Virginia
West
Virginia
West
Virginia
West
Virginia
Ohio
Unit
Units
Unit 4
Units
Unite
Unifl
Unit 2
Units 5, 6
Units 1 -
3
Units 1,2
Unit 1
Unit 2
Unit 1
Units 1 -
4
Settlement Actions
Retire/Repower
Action EffrSeVe
Retire,
retrofit, or 12/31/2012
re-power
Retire,
retrofit, or 12/31/2015
re-power
SOz control
Equipment
Percent
Removal
or Rate
Effective
Date
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
Ib/MMBtu
annual average
Burn only coal
with no more
than 1.75
Ib/MMBtu
annual average
Install and
continuously
operate FGD
Install and
continuously
operate FGD
Install and
continuously
operate FGD
95%
95%
Plant-wide
annual cap:
35,000
12/31/2010
12/31/2009
12/31/2009
Date of
entry
Date of
entry
Date of
entry
1/1/2010
Date of
entry
12/31/2007
12/31/2007
12/31/2007
NOx Control
Equipment
Rate
Effective
Date
Install and
continuously operate
SCR
Continuously
operate low NO*
burners
Continuously
operate low NOK
burners
Install and
continuously operate
SCR
Install and
continuously operate
SCR
Continuously
operate low NO,
burners
Continuously
operate over-fire air
Continuously
operate low NO,
burners
Install and
continuously operate
SCR
Install and
continuously operate
SCR
Install and
continuously operate
SCR
12/31/2010
Date of
entry
Date of
entry
1/1/2009
1/1/2009
Date of
entry
Date of
entry
Date of
entry
1/1/2009
1/1/2009
1/1/2008
PM or Mercury Control
Equipment
Rate
Effective
Date
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
Effective
Date
Reference
Appendix 3-3.13
-------
Company
and Plant
Picway
Rockport
Sporn
Tanners
Creek
State
Ohio
Indiana
West
Virginia
Indiana
Unit
Units
Unit 9
Unifl
Unit 2
Units
Units 1 -
3
Unit 4
Settlement Actions
Retire/Repower
Action
Effective
Date
Retire,
retrofit, or
re-power
12/31/2013
SOz control
Equipment
Install and
continuously
operate FGD
Percent
Removal
or Rate
Effective
Date
12/31/2015
Install and
continuously
operate FGD
Install and
continuously
operate FGD
12/31/2017
12/31/2019
Burn only coal
with no more
than 1.2
Ib/MMBtu
annual average
Burn only coal
with no more
than 1.2% sulfur
content annual
average
Date of
entry
Date of
entry
NOX Control
Equipment
Install and
continuously operate
SCR
Continuously
operate low NO,
burners
Install and
continuously operate
SCR
Install and
continuously operate
SCR
Rate
Effective
Date
1/1/2008
Date of
entry
12/31/2017
12/31/2019
Continuously
operate low NOK
burners
Continuously
operate over-fire air
Date of
entry
Date of
entry
PM or Mercury Control
Equipment
Continuously
operate ESP
Rate
0.03
Effective
Date
12/31/2002
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
Effective
Date
Reference
-
-
-
-
-
-
East Kentucky Power Cooperative Inc.
By 12/31/2009, EKPC shall choose whether to: 1) install and continuously 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
System-wide 12-
month rolling
tonnage limits
apply
12-month
rolling limit
(tons)
57,000
40,000
28,000
Start of 12-
month cycle
10/1/2008
7/1/2011
1/1/2013
All units must
operate low NOK
boilers
12-month
rolling limit
(tons)
11,500
8,500
8,000
Start of 12-
month
cycle
1/1/2008
1/1/2013
1/1/2015
PM control devices
must be operated
continuously
system-wide, ESPs
must 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 N OK
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
NOX allowances
allocated to EKPC
must be used within
the EKPC system.
Allowances made
available due to
super compliance
maybe sold or
traded.
http://www.epa.gov
/compliance/resour
ces/cases/civil/caa
/n evadapower.htm I
Appendix 3-3.14
-------
Company
Spurlock
Dale Plant
Cooper
State
Kentucky
Kentucky
Kentucky
Unit
Unit 1
Unit 2
Unitl
Unit 2
Units
Unit 4
Unitl
Settlement Actions
Retire/Repower
Acซion ซ|Jฃป
EKPC may
choose to
retire Dale 3
and 4 in lieu 12/31/2012
of installing
controls in
Cooper 2
SOz control
Equipment
Install and
continuously
operate FGD
Install and
continuously
operate FGD by
10/1/2008
P
Removal
or Rate
95% or 0.1
95% or 0.1
Effective
Date
6/30/2011
1/1/2009
NOx Control
Equipment
Continuously
operate SCR
Continuously
operate SCR and
OFA
continuously operate
low NOX burners by
10/31/2007
Install and
continuously operate
low NOX burners by
10/31/2007
Rate
0.1 2 for Unitl
until
01/01/2013, at
which point the
unit limit drops
to 0.1. Prior to
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
0.46
0.46
Effective
Date
60 days
after entry
60 days
after entry
1/1/2008
1/1/2008
PM or Mercury Control
Equipment
Rate
Effective
Date
Allowance
Retirement
Retirement
surrender 1 ,000 NOX
allowances
immediately under
the ARP, and 3,107
under the NO, SIP
Call. EKPC must
15,311 SO2
allowances.
Allowance Restriction
Restriction
Effective
Date
Date of entry
Reference
http://www.epa.gov
/compliance/resour
ces/cases/civil/caa
/eastkentu ckypowe
r-dale0907.html
Appendix 3-3.15
-------
Company
and Plant
State
Unit
Unit 2
Settlement Actions
Retire/Repower
Acซion
SOz control
Equipment
IfEKPCoptsto
install controls
rather than
retiring Dale, it
must install and
continuously
operate FGD or
equiv.
technology
Percent
Removal
or Rate
95% or
0.10
Effective
Date
NOX Control
Equipment
If EKPC elects to
install controls, it
must continuously
operate SCR or
install equiv.
technology
Rate
0.08 (or 90% if
non-SCR
technology is
used)
Effective
Date
12/31/2012
PM or Mercury Control
Equipment
Rate
Effective
Date
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
Effective
Date
Reference
Nevada Power Company
Beginning 1/1/2010, comb ned NOX emissions from Units 5, 6, 7, and 8 must be no more than 360 tons per year.
Clark
Generating
Station
Nevada
Units
Unite
Unit/
Units
Units may only fire
natural gas
Increase water
injection
immediately, then
install and operate
ultra-low NO,
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
5ppm 1-hour
average
5ppm 1-hour
average
12/31/08
(ULNB
n stall at ion
, 01/30/09
(1-hour
average)
12/31/09
(ULNB
nstallation)
, 01/30/10
(1-hour
average)
12/31/09
(ULNB
nstallation)
, 01/30/10
(1-hour
average)
12/31/08
(ULNB
nstallation)
, 01/30/09
(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.
httD://www.eoa.aov
/compliance/resour
ces/cases/civil/caa
/nevadaoower.html
Dayton Power & Light
Non-EPA Settlement of 10/23/2008
Stuart
Generating
Station
Ohio
Station-
wide
Complete
installation of
FGDs on each
unit.
96% or
0.10
7/31/2009
Owners may not
purchase any new
catalyst with SO2 to
SO-j conversion rate
greater than 0.5%
0.17 station-
wide
0.17 station-
wide
30 days
after entry
60 days
after entry
date
0.030 Ib
per unit
7/31/2009
N Ox and SO2
allowances may not
be used to comply
with the monthly
rates specified in
the Consent
Decree.
Courtlink
document provided
by EPA in email
Appendix 3-3.16
-------
Company
and Plant
State
Unit
Settlement Actions
Retire/Repower
Action
Effective
Date
SOz control
Equipment
P
Removal
or Rate
82%
data from
periods of
malfunction
s
82%
including
data from
periods of
malfunction
s
Effective
Date
7/31/09
through
7/30/1 1
after
7/31/11
NOx Control
Equipment
Install control
technology on one
unit
Rate
0.10 on any
single unit
0.15 station-
wide
0.10 station-
wide
Effective
Date
12/31/2012
7/1/2012
12/31/2014
PM or Mercury Control
Equipment
Rate
Install
rigid-type
electro-
each
unit's
ESP
Effective
Date
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
Effective
Date
Reference
PSEG FOSSIL, Amended Consent Decree of November 2006
Kearny
Hudson
New Jersey
New Jersey
Unit 7
Units
Unit 2
Retire unit
Retire unit
1/1/2007
1/1/2007
Install Dry FGD
or approved alt.
technology) and
continually
operate
0.15
Annual Cap
(tons)
5,547
5,270
5,270
5,270
12/31/2010
Year
2007
2008
2009
2010
Install SCR (or
approved tech) and
continually operate
0.1
Annual Cap
(tons)
3,486
3,486
3,486
3,486
12/31/2010
Year
2007
2008
2009
2010
nstall Baghouse (or
approved
technology)
0.015
12/31/2010
Allowances allocated
to Kearny, Hudson,
and Mercer may only
be used for the
operational needs of
those units, and all
surplus allowances
must be surrendered.
Within 90 days of
amended Consent
Decree, PSEG must
surrender 1,230 NO*
Allowances and
8,568 SO2
Allowances not
already allocated to
or generated by the
units listed here.
Kearny allowances
must be surrendered
with the shutdown of
those units.
http://www.epa.gov
/compliance/resour
ces/decrees/amen
ded/psegfossil-
amended-cd.pdf
Appendix 3-3.17
-------
Company
and Plant
Mercer
State
New Jersey
Unit
Units 1 &
2
Settlement Actions
Retire/Repower
Action
Effective
Date
SOz control
Equipment
Install Dry FGD
(or approved alt.
technology) and
continually
operate
Percent
Removal
or Rate
0.15
Effective
Date
12/31/2010
NOx Control
Equipment
Install SCR (or
approved tech) and
continually operate
Rate
0.1
Effective
Date
1/1/2007
PM or Mercury Control
Equipment
Install Baghouse (or
approved
technology)
Rate
0.015
Effective
Date
12/31/2010
Allowance
Retirement
Retirement
Allowance Restriction
Restriction
Effective
Date
Reference
Westar Energy
Jeffrey
Energy
Center
Kansas
All units
Duke Energy
Gallagher
Indiana
Units 1 &
3
Units 2 &
4
Retire or
repower as
natural gas
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 install FGDs by
2011 and operate them continuously.
FGDs must ma ntain a 30-Day Rolling
Average Unit Removal Efficiency for SC>2 of
at least 97% or a 30-Day Rolling Average
Unit Emission Rate for SOs of no greater
than 0.070 Ib/MMBtu.
Units 1-3 must continuously operate Low NOX
Combustion Systems by 2012 and achieve and
maintain a 30-Day Rolling Average Unit Emission
Rate for NO* of no greater than 0.180 Ib/MMBtu.
One of the three units must install an SCR by 2015
and operate it continuously to mainta n a 30-Day
Rolling Average Unit Emission Rate for NO* of no
greater than 0.080 Ib/MMBtu.
By 201 3 Westar sha I elect to either (a) install a
second SCR on one of the other JEC Units by
2017 or (b) meet a 0.100 Ib/MMBtu Plant-Wide 12-
Month Rolling Average Emission Rate for NO,, by
2015
Units 1, 2, and 3 must operate each ESP and
FGD system continuously by 2011 and
maintain a 0.030 Ib/MMBtu PM Emissions
Rate.
Units 1 and 2's ESPs must be rebuilt by 2014
in order to meet a 0.030 Ib/MMBtu PM
Emissions Rate
1/1/2012
Install Dry
sorbent injection
technology
80%
1/1/2012
Notes:
1) This summary table describes New Source Review settlement actions as they are represented in EPA Base Case v.4.10. The settlement actions are simplified for representation in the model. This table is not intended to be a comprehensive description of all elements of the actual
settlement agreements.
2) Settlement actions for which the required emission limits will be effective by the time of the first mapped run year (before 1/1/2012) are built into the database of units used in EPA Base Case v.4.10 ("hardwired"). However, future actions are generally modeled as individual constraints on
emission rates in EPA Base Case v.4.10 allowing the modeled economic situation to dictate whether and when a unit would opt to install controls versus retire.
3) Some control installations that are required by these NSR settlements have already been taken by the affected companies, even if deadlines specified in their settlement haven't occurred yet. Any controls that are already in place are built into EPA Base Case v.4.10
4) If a settlement agreement requires installation of PM controls, then the controls are shown in this table and reflected in EPA Base Case v.4.10. If settlement requires optimization or upgrade of existing PM controls, those actions are not included in EPA Base Case v.4.10.
5) For units for which an FGD is modeled as an emissions constraint in EPA Base Case v.4.10, EPA used the assumptions on removal efficiencies that are shown in Table 5-4 of this documentation report.
6) For units for which an FGD is hardwired in EPA Base Case v.4.10, unless the type of FGD is specified in the settlement, EPA modeling assumes the most cost effective FGD (wet or dry) and a corresponding 98% removal efficiency for wet and 93% for dry.
7) For units for which an SCR is modeled as an emissions constraint or is hardwired in EPA Base Case v.4.10, EPA assumed an emissions rate equal to 10% of the unit's uncontrolled rate, with a floor of .06 Ib/MMBtu or used the emission limit if provided.
8) The applicable low NOX burner reduction efficiencies are shown in Table A 3-1:3 in the Base Case v.4.10 documentation materials.
9) EPA included in EPA Base Case v.4.10 the requirements of the settlements as they existed at the second quarter of 2010.
10) Some of the NSR settlements require the retirement of SC>2 allowances. For EPA Base Case v.4.10, EPA estimates the amount of allowances to be retired from these settlements and adjusted the total Title IV allowances accordingly.
Appendix 3-3.18
-------
Appendix 3-4 State Settlements in EPA Base Case v.4.10
Company and
Plant
State
Unit
State Enforcement Actions
Retire/Repower
Action
AES
Greenidge
Westover
Hickling
Jennison
New York
New York
New York
New York
Unit 4
Units
Units
Unit 7
Units 1 &
2
Units 1 &
2
Effective
Date
SO2 control
Equipment
Percent
Removal
or Rate
Effective
Date
NOX Contro
Equipment
Rate
Effective Date
PM Contro
Equipment
Rate
Effective
Date
Mercury Control
Equipment
Rate
Effective
Date
Install FGD
Install BACT
Install BACT
Install BACT
Install BACT
90%
90%
9/1/2007
12/31/2009
12/31/2010
12/31/2009
5/1/2007
5/1/2007
Install SCR
Install BACT
Install SCR
Install BACT
Install BACT
Install BACT
0.15
0.15
9/1/2007
12/31/2009
12/31/2010
12/31/2009
5/1/2007
5/1/2007
Niagara Mohawk Power
NRG shall comply with the below annual tonnage limitations for its Huntley and Dunkirk Stations: 2005 is 59,537 tons of SO2 and 1 0,777 tons of NOX, 2006 is 34,230 of SO2 and 6,772 of NOX, 2007 is 30,859 of SO2 and 6,21 1 of NOX, 2008 is
22,733 tons of SO2
Huntley
New York
Units 63
-66
Retire
Public Service Co. of NM
San Juan
New Mexico
Unitl
Unit 2
Units
Unit 4
Before
2008
State-of-the-art
technology
90%
10/31/2008
3/31/2009
4/30/2008
10/31/2007
State-of-the-art
technology
0.3
10/31/2008
3/31/2009
4/30/2008
10/31/2007
Operate
Baghouse and
demister
technology
0.02
12/31/2009
12/31/2009
4/30/2008
10/31/2007
Design
activated
carbon injection
technology (or
comparable
tech)
12/31/2009
12/31/2009
4/30/2008
10/31/2007
Public Service Co of Colorado
Comanche
Colorado
Units 1 &
2
Units
Install and
operate FGD
Install and
operate FGD
0.1
Ib/MMBtu
combined
average
0.1
Ib/MMBtu
7/1/2009
Install low-NOx
emission controls
Install and
operate SCR
0.15
Ib/MMBtu
combined
average
0.08
7/1/2009
Install and
operate a
fabric filter
dust collection
system
0.01
Install sorbent
injection
technology
Install sorbent
injection
technology
7/1/2009
Within 180
days of start-
up
Appendix 3-4.1
-------
Company and
Plant
State
Unit
State Enforcement Actions
Retire/Repower
Action
SO2 control
Equipment
Percent
Removal
or Rate
Effective
Date
NOX Control
Equipment
Rate
Effective Date
PM
Equipment
TVA
Bull Run
John Sevier
Kingston
Tennessee
Tennessee
Tennessee
Unitl
Unitl
Unit 2
Units
Unit 4
Unitl
Unit 2
Units
Unit 4
Units
Unite
Unit/
Units
Unit 9
Complete FGD
installation
Install FGD
Install FGD
0.15
Ib/MMBtu,
4,431 TRY
0.15
Ib/MMBtu,
1,023 TRY
0.15
Ib/MMBtu,
1,028 TRY
0.15
Ib/MMBtu,
1,081 TRY
0.15
Ib/MMBtu,
1,000 TRY
0.15
Ib/MMBtu,
794 TRY
0.15
Ib/MMBtu,
785 TRY
0.15
Ib/MMBtu,
822 TRY
0.15
Ib/MMBtu,
800 TRY
0.15
Ib/MMBtu,
1,021 TRY
0.15
Ib/MMBtu,
1,095 TRY
0.15
Ib/MMBtu,
1,040 TRY
0.15
Ib/MMBtu,
1,048 TRY
0.15
Ib/MMBtu,
1,01 2 TRY
FGD
already
active as of
date of
entry
27 months
from date
of entry
27 months
from date
of entry
Install SCR
Operate existing
SCR
0.08
Ib/MMBtu,
2,295 TRY
0.05
Ib/MMBtu,
372 TRY
0.05
Ib/MMBtu,
374 TRY
0.05
Ib/MMBtu,
389 TRY
0.05
Ib/MMBtu,
360 TRY
0.06
Ib/MMBtu,
323 TRY
0.06
Ib/MMBtu,
320 TRY
0.06
Ib/MMBtu,
335 TRY
0.06
Ib/MMBtu,
326 TRY
0.06
Ib/MMBtu,
41 6 TRY
0.05
Ib/MMBtu,
365 TRY
0.05
Ib/MMBtu,
347 TRY
0.05
Ib/MMBtu,
349 TRY
0.05
Ib/MMBtu,
337 TRY
21 months
from date of
entry
Control
Rate
Effective
Date
Mercury Control
Equipment Rate ^stive
uats
Appendix 3-4.2
-------
Company and
Plant
Widows Creek
State
Alabama
Unit
Unitl
Unit 2
Units
Unit 4
Units
Unite
Unit/
Units
State Enforcement Actions
Retire/Repower
Action
Effective
Date
SO2 control
Equipment
Install FGD
Percent
Removal
or Rate
0.15
Ib/MMBtu,
569 TPY
0.15
Ib/MMBtu,
608 TPY
0.15
Ib/MMBtu,
663 TPY
0.15
Ib/MMBtu,
602 TPY
0.15
Ib/MMBtu,
640 TPY
0.15
Ib/MMBtu,
626 TPY
0.56
Ib/MMBtu,
8950 TPY
0.30
Ib/MMBtu,
4,508 TPY
Effective
Date
27 months
from date
of entry
NOX Control
Equipment
Install SCR
Rate
0.06
Ib/MMBtu,
246 TPY
0.06
Ib/MMBtu,
263 TPY
0.06
Ib/MMBtu,
287 TPY
0.06
Ib/MMBtu,
261 TPY
0.06
Ib/MMBtu,
277 TPY
0.06
Ib/MMBtu,
271 TPY
0.06
Ib/MMBtu,
892 TPY
0.06
Ib/MMBtu,
860 TPY
Effective Date
21 months
from date of
entry
PM
Equipment
Control
Rate
Effective
Date
Mercury Control
Equipment Rate ^stive
uats
Rochester Gas & Electric
Russell Plant
New York
Units 1 -
4
Retire
all
units
Mirant New York
Lovett Plant
New York
Unitl
Unit 2
Retire
Retire
5/7/2007
4/30/2008
Appendix 3-4.3
-------
-------
Appendix 3-5 Citizen Settlements in EPA Base Case v.4.10
Company
and Plant
State
Unit
Citizen Suits Provided by DOJ
Retire/Repower
Action
Effective
Date
SO2 control
Equipment
Percent
Removal
or Rate
Effective
Date
NOX Control
Equipment
SWEPCO (AEP)
Welsh
Texas
Units 1-
3
Rate
Effective
Date
PM Control
Equipment
Rate
Effective
Date
Install and
operate CEMs
12/31/2010
Allegheny Energy
Hatfield's
Ferry
Pennsylvania
Units 1
-3
Install and
operate wet
FGD
6/30/2010
Install and
operate sulfur
trioxide injection
systems, improve
ESP
performance
0.1 Ib/MMBtu in
2006, then 0.075
Ibs per hour
(filterable) and 0.1
Ib/MMBtu for
particles less than
ten microns in 2010
2006 and
6/30/2010
Wisconsin Public Service Corp
Pulliam
Wisconsin
Units 3
&4
Retire
12/31/2007
University of Wisconsin
Charter
Street
Heating
Plant
Wisconsin
Repower to
burn 100%
biomass
12/31/2012
Appendix 3-5.1
-------
Company
and Plant
Citizen Suits Provided by DOJ
Retire/Repower
Action
Tucson Electric Power
Springerville
Plant
Arizona
Units 1
&2
Units
Future
Unit 4
Effective
Date
SO2 control
Equipment
Removal
or Rate
Effective
Date
NOX Control
Equipment
Rate
Effective
Date
PM Control
Equipment
Rate
Effective
Date
Dry FGD,
85%
reduction
required
0.27
Ib/MMBtu
12/31/2006
Four-unit
cap of
10,662
tons per
year once
units 3 and
operational
SCR, LNB
0.22
Ib/MMBtu
12/31/2006
Four-unit
cap of
8,940 tons
3 and 4 are
operational
Baghouse
0.03 Ib/MMBtu
1/1/2006
Appendix 3-5.2
-------
Appendix 3-6 Renewable Portfolio Standards in EPA Base Case v.4.10
NEMS
Region
CNV
ECAR
ERGOT
MAAC
MAIN
MAPP
NE
NWP
NY
RA
SPP
STV
IPM Regions Covered
CA-N and CA-S
MEGS, RFCO, RFCP, and
TVAK
ERCT
MACE, MACS, and MACW
COMD, GWAY, and WUMS
MRO
NENG
NWPE and PNW
DSNY, LILC, NYC, and
UPNY
AZNM, RMPA, and SNV
SPPN and SPPS
ENTG, SOU, TVA, VACA,
and VAPW
Units
%
%
%
/O
/O
%
/O
%
GWh
%
%
%
2012 2015 2020 2030 2ฐ3_5"
&UOU
15.7% 17.3% 20.0% 20.0% 20.0%
0.8% 3.0% 4.5% 5.7% 5.7%
3.9% 5.0% 5.0% 5.0% 5.0%
7.4% 10.1% 14.8% 15.4% 15.4%
5.6% 8.9% 13.2% 17.5% 17.5%
3.7% 4.6% 6.1% 7.2% 7.2%
7.4% 9.6% 13.4% 13.8% 13.8%
4.6% 7.3% 12.4% 13.7% 13.7%
4,838 5,233 5,097 5,236 5,369
3.0% 4.2% 6.0% 6.9% 6.9%
1.9% 1.9% 3.8% 3.8% 3.8%
0.5% 0.9% 1.7% 1.9% 1.9%
Notes:
The Renewable Portfolio Standard percentages are applied
projections.
The actual renewable portfolio standard targets in GWh are
the model.
to modeled electricity sale
implemented exactly as shown in
Appendix 3-6.1
-------
-------
Appendix 3-7 Capacity Deployment Limits for Advanced Coal with CCS and
New Nuclear in EPA Base Case v.4.10
Run
Year
2012
2015
2020
2030
2040
2050
Advanced
Coal with
CCS (MW)
0
2,000
New
Nuclear
(MW)
0
0
9,750 7,500
38,220 29,400
112,367 86,436
293,652 225,886
Note:
The 2020 through 2050 limits for 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 maximum amount of one technology is developed
in a given run year, zero MWof the other may be
developed. See the production possibility chart below.
250,000 -,
200,000 -
jjj 150,000 -
0
^
z
z 100,000 -
50,000 -
0-
C
Production Possibility Curves
(Incremental Capacity in MW by Run Year)
* * . ^
*
* ป . ^
* * . . 2050
'**ซ.%
" ^ , 2040 * ป ,
^*^ ***.,
. ^ 2030 "^.^ "--.^
202*0* ป . * ^ , * * .
^^^. * ^^. *
) 50,000 100,000 150,000 200,000 250,000 300,000
Advanced Coal with CCS
Appendix 3-7.1
-------
-------
Appendix 3-8 Nuclear Capacity Deployment Constraint in EPA Base Case v.4.10
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
2030
2040
2050
7,500 7,500
14,700 1.96 * 2020_Base_Capacity
28,812 1.96 * 2030_Base_Capacity
56,472 1.96 * 2040_Base_Capacity
0
+ 1.96 * 2020_lncremental_Capacity
+ 1.96 * 2030_lncremental_Capacity
+ 1.96 * 2040_lncremental_Capacity
7,500
1.96 * (2020_Base_Capacity + 2020_lncremental_Capacity)
1.96 * (2030_Base_Capacity + 2030_lncremental_Capacity)
1.96 * (2040_Base_Capacity + 2040_lncremental_Capacity)
Run
Year
2020
2030
2040
2050
Maximum Possible New Nuclear Capacity Deployment Allowed
Deployment Starts 2020
Incremental Cumulative
7,500 7,500
29,400 36,900
86,436 123,336
225,886 349,222
Deployment Starts 2030
Incremental Cumulative
0 0
14,700 14,700
57,624 72,324
169,415 241,739
Deployment Starts 2040
Incremental Cumulative
0 0
0 0
28,812 28,812
112,943 141,755
Deployment Starts 2050
Incremental Cumulative
0 0
0 0
0 0
56,472 56,472
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.
Appendix 3-8.1
-------
2050
Maximum Possible Cumulative New Nuclear Capacity Each Run Year
50,000
100,000
150,000 200,000
Capacity (MW)
250,000
300,000
350,000
I Deployment Starts 2020 Deployment Starts 2030 Deployment Starts 2040 Deployment Starts 2050
Appendix 3-8.2
-------
Appendix 3-9 Complete Availability Assumptions in EPA Base Case v.4.10
This is a small exerpt of the data in Appendix 3-9. The complete data set in spreadsheet format
can be downloaded via the link found at
www.epa.qov/airmarkets/proqsreqs/epa-ipm/BaseCasev410.html
Please see Table 3-7 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
_. . _ Winter
Pant Type . .. .....
yt^ Availability
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
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
Appendix 3-9.1
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4 Generating Resources
"Existing", "planned-committed", and "potential" are the three general types of generating units
modeled in EPA Base Case v.4.10. 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.4.10,
(2) Section 4.2 provides detailed information on existing non-nuclear generating units
modeled in EPA Base Case v.4.10,
(3) Section 4.3 provides detailed information pertaining to planned-committed units which are
assumed in EPA Base Case v.4.10,
(4) Section 4.4 provides detailed information pertaining to the IPM assumptions for potential
plants, and
(5) Section 4.5 describes the handling of existing and potential nuclear units in EPA Base
Case v.4.10
4.1 National Electric Energy Data System (NEEDS)
EPA Base Case v.4.10 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.4.10. The data sources for planned-committed units in NEEDS are
discussed below in Section 4.3. The population of existing units in NEEDS v4.10 represents
generating units that were in operation through the end of 2006. The population of planned-
committed includes any units online or scheduled to come online from 2007 to the end of 2011
(with two exceptions listed in the note under Table 4-2 below).
4.2 Existing Units
EPA Base Case v.4.10 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.4.10.
4.2.1 Population of Existing Units
The population of existing units was taken primarily from EIA 860 (2006) and EIA 767 (2005). 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 IPM. Table 4-2 below
summarizes the rules used in populating the NEEDS v.4.10 database.
4-1
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Table 4-1 Data Sources for NEEDS v.4.10 for EPA Base Case v.4.10
Data Source
Data Source Documentation
DOE's Form EIA-860
DOE's Form EIA-860 is an annual survey of utility power plants at the
generator level. It contains data such as summer, winter and
nameplate capacity, location (state and county), status, prime mover,
primary energy source and in-service year. NEEDS v.4.10 uses EIA
Form 860 (2006) data as one of the primary data inputs.
DOE's Form EIA-767
DOE's Form EIA-767 is an annual survey, "Steam-Electric Plant
Operation and Design Report", that contains data for utility nuclear and
fossil fuel steam boilers such as fuel quantity and quality; boiler
identification, location, status, and design information; and post-
combustion NOX control, FGD scrubber and particulate collector device
information. Note that boilers in plants with less than 10 MWdo not
report all data elements. The relationship between boilers and
generators is also provided, along with generator-level generation and
nameplate capacity. Note that boilers and generators are not
necessarily in a one-to-one correspondence. NEEDS v.4.10 uses EIA
Form 767 (2005) data as one of the primary data inputs.
NERC Electricity
Supply and Demand
(ES&D) database
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.4.10 uses NERC ES&D (2006) data as one of the primary
data inputs.
DOE's Annual Energy
Outlook (AEO)
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 such as heat rates, planned committed units,
nuclear unit capacities and uprates were used in NEEDS v.4.10.
Global Energy
Decisions New
Entrants database
Global Energy's New Entrants database has information on new power
plant builds, rerates and retirements. Information on committed units is
based on November 2009 dataset.
EPA's Emission
Tracking System
(ETS 2007)
The Emission Tracking System (ETS) database is updated quarterly. It
contains boiler-level information such as primary fuel, heat input, SO2
and NOX controls, and SO2 and NOX emissions.
Utility and RPO
(Regional Planning
Organizations)
Comments
Comments from selected U.S. utilities and RPOs regarding the
population in NEEDS as well as unit characteristics were used in
NEEDS v.4.10.
Note:
1 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 date were not
available for the indicated issued date or where there were methodological reasons for using
other vintages of the data.
4-2
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Table 4-2 Rules Used in Populating NEEDS v.4.10 for EPA Base Case v.4.10
Scope
Capacity
Status
Planned or Committed
Units
Firm/Non-firm Electric
Sales
Rule
Excluded units with reported nameplate, summer and winter capacity
of zero
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 generators)
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 201 1 ; one biomass and
one nuclear unit that are scheduled to come online after 201 1 were
also included
Excluded non-utility onsite generators that do not produce electricity
for sale to the grid.
Excluded all mobile and distributed generators
Note:
1The biomass unit is Mitchell, unit 3, and the nuclear unit is Watts Bar Nuclear Plant, unit 2.
As with previous versions of the database, NEEDS v.4.10 includes steam units at the boiler level
and non-steam units at the generator level. A unit in NEEDS v.4.10, 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.4.10 through
2006. EIA Form 860 (2006) and Form 767 (2005) is the starting point and largest component of
the existing unit population in NEEDS v.4.10 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 Global Energy's New Entrants database.
Table 4-3 Summary Population (through 2006) of Existing Units in NEEDSv.4.10 for EPA
Base Case v.4.10
Plant Type
Biomass
Coal Steam
Combined Cycle
Combustion Turbine
Fossil Waste
Geothermal
Hydro
IGCC
Landfill Gas
Municipal Solid Waste
Non-Fossil Waste
Nuclear
O/G Steam
Pumped Storage
Solar
Tires
Wind
Grand Total
Number of Units
134
1,235
1,532
5,386
20
196
3,754
4
698
176
45
104
682
150
19
3
330
14,468
Capacity (MW)
2,286
305,451
179,557
132,293
610
2,264
77,713
529
1,068
2,098
516
101,099
112,371
20,940
412
44
11,637
950,889
4-3
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4.2.2 Capacity
The NEEDS unit capacity values implemented in EPA Base Case v.4.10 reflect net summer
dependable capacity16, to the extent possible. Table 4-4 summarizes the hierarchy of primary
data sources used in compiling capacity data for NEEDS v.4.10.
Table 4-4 Hierarchy of Data Sources for Capacity in NEEDS v.4.10
Sources Presented in Hierarchy
Capacity from Utility Comments
2006 EIA 860 Summer Capacity
NERC ES&D 2006 Summer Capacity
2006 EIA 860 Winter Capacity
NERC ES&D 2006 Winter Capacity
2006 EIA 860 Nameplate Capacity
Notes:
Presented in hierarchical order that applies.
If capacity is zero, unit is not included.
As noted earlier, for steam units NEEDS v.4.10 includes boiler level data, while for non-steam
units NEEDS v.4.10 contains generator level data. Capacity data in EIA and NERC data sources
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.
The capacity-parsing algorithm used for steam units in NEEDS v.4.10 took into account boiler-
generator mapping. Fossil steam and nuclear 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 767, 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 767 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.4.10
Type of Boiler-Generator Links
For Boiler B1
to B/v linked to
Generators
G1 to G/v
One-to-One
MWB, =
MWG;
One-to-Many
MWB, =
I;MWG;
Many-to-One
MWB, =
(MFB,/r,MFs,)*MWG;
Many-to-Many
MWB, =
(MFB,/I,MFB,)*I;MWG;
Notes:
MFB, = maximum steam flow of boiler;
MWG; = electric generation capacity of generatory
16As 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.
4-4
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Since EPA Base Case v.4.10 uses net energy for load as demand, NEEDS v.4.10 only includes
generators that sell the majority of their power to the electric grid in order to be consistent with
demand. The generators that should be in NEEDS v.4.10. by this qualification are determined
from the 2005 EIA Form 906 non-utility source and disposition data set.
4.2.3 Plant Location
NEEDS v.4.10 uses state, county and model region data to represent the physical location of each
plant.
State and County
NEEDS v.4.10 used the state and county data in EIA 860 (2006)
Model Region
For each unit the associated model region was derived based on NERC regions and sub-regions
reported in NERC ES&D 2006 for that unit. For units with no NERC sub-region data, NERC
region and state were used to derive associated model regions. For units with no NERC region
data, state and county were used to derive associated model regions. Table 3-1 in Chapter 3
provides a summary of the mapping between NERC regions and EPA Base Case v.4.10 model
regions.
4.2.4 Online Year
The EPA Base Case v.4.10 uses online year to capture when the unit entered service. NEEDS
includes online years for all units in the database. In NEEDS v.4.10, online years for boilers, utility
and non-utility generators were primarily derived from reported in-service dates in EIA 767 2005
and EIA 860 2006 respectively.
EPA Base Case v.4.10 does not include any assumption about the retirement year for generating
units, except for existing nuclear units which must retire when they reach age 60. (See section
3.7 fora discussion of the nuclear lifetime assumption.) EPA Base Case v.4.10 does, however,
provide 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, an early retired plant ceases to incur FOM and VOM costs.
However, retired units do meet capital cost obligations for 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.4.10 drives model plant aggregation, modeling of pollution control options and
mercury emission modification factors. NEEDS v.4.10 contains information on the firing and
bottom type of coal steam boilers in the database. Great effort was taken to see that the inventory
of existing and committed controls represented in EPA Base Case v.4.10 was comprehensive and
as up-to-date as possible. The hierarchy of data sources used is shown in Table 4-6.
4.2.6 Model Plant Aggregation
While 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.4.10
aggregation scheme is designed so that each model plant only represents generating units from a
single state. This 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
4-5
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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 10 major categories
used for the aggregation scheme in EPA Base Case v.4.10 are the following:
(1) Model Region
(2) Unit Technology Type
(3) Fuel Demand Region
(4) Applicable Environmental Regulations
(5) State
(6) Unit Configuration
(7) Emission Rates
(8) Heat Rates
(9) Fuel
(10) Size
Table 4-6 Data Sources for Unit Configuration in NEEDS v.4.10 for EPA Base Case v.4.10
Unit
Component
Firing Type
Bottom Type
SO2 Pollution
Control
NOX Pollution
Control
Particulate
Matter
Control
Primary Data Source
Utility/RPO Comments
Utility/RPO Comments
NSR Settlement or
Utility/RPO Comments
NSR Settlement or
Utility/RPO Comments
NSR Settlement or
Utility/RPO Comments
Secondary Data
Source
2005 EIA 767
2005 EIA 767
EPA's Emission
Tracking System
(ETS) - 2006
EPA's Emission
Tracking System
(ETS) - 2006
EPA's Emission
Tracking System
(ETS) - 2006
Tertiary
Data
Source
~
~
2005 EIA
767
2005 EIA
767
2005 EIA
767
Other
Sources
~
~
See Note
See Note
1999Hg
ICR
Default
-
Dry
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: MclLVAINE Utility Upgrade Database, ICAC (Institute of Clean Air Companies), and web
sites of generating unit owners and operators.
Table 4-7 provides a crosswalk between actual plants and the aggregated "model plants" used in
the EPA Base Case v.4.10. 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.4.10.
17For readers interested in the intricacies of Table 4-7, here are several observations: (1)
Depending on its capacity and fuel types combusted, an existing coal steam model plant may be
provided with multiple scrubber and ACI retrofit options. As a result the total number of model
plants representing scrubber and ACI retrofits may exceed the total number of model plants
representing existing coal steam units. (See chapter 5 for a detailed description of the sulfur
dioxide (scrubber) and mercury (ACI) retrofit options.) (2) 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, the reverse timing, or both 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
Noncatalytic Reduction (SNCR)") have a "Number of of IPM Model Plants" that is a smaller than
4-6
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Table 4-7 Aggregation Profile of Model Plants as Provided at Set Up of EPA Base Case
v.4.10
Existing and Planned/Committed Units
Plant Type
Biomass
Coal Steam
Combined Cycle
Combustion Turbine
Fossil_Other
Fuel Cell
Geothermal
Hydro
Import
Integrated Gas Combined Cycle
Landfill Gas
Non Fossil_Other1
Nuclear2
Oil/Gas Steam
Pumped Storage
Solar
Wind
Total
Number of
Units
161
1,267
1,627
5,474
21
4
211
3,771
2
6
747
241
105
685
151
92
458
15,023
Number of IPM
Model Plants
71
913
610
2,225
14
4
8
99
2
5
59
73
105
435
21
37
57
4,738
New Units
Plant Type
New Biomass
New Coal with Carbon Capture
New Combined Cycle
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 SPC-DryFGD_SCR_ACI
New SPC-WetFGD_SCR
New Solar Thermal
New Solar PV
Number of
Units
-
-
-
-
-
Number of IPM
Model Plants
64
754
32
32
32
160
26
58
96
64
690
600
27
27
55
32
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 32 model regions and the
specific totals vary from technology to technology for several reasons. First, some technologies
have multiple vintages, 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, conventional pulverized coal is not provided as an
option in CA-N).
4-7
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Total
2,749
Retrofits
Plant Type
Retrofit Coal with Activated Carbon Injection (ACI)
Retrofit Coal with ACI + SCR
Retrofit Coal with ACI + SCR + Scrubber
Retrofit Coal with ACI + SCR + Scrubber + CCS
Retrofit Coal with ACI + SNCR + Scrubber
Retrofit Coal with ACI + SNCR
Retrofit Coal with ACI + SNCR + Scrubber + CCS
Retrofit Coal with ACI + Scrubber
Retrofit Coal with ACI + Scrubber + CCS
Retrofit Coal with Selective Catalytic Reduction (SCR)
Retrofit Coal with SCR + Scrubber
Retrofit Coal with SCR + Scrubber + CCS
Retrofit Coal with Selective Noncatalytic Reduction (SNCR)
Retrofit Coal with SNCR + Scrubber
Retrofit Coal with SNCR + Scrubber + CCS
Retrofit Coal with Scrubber
Retrofit Coal with Scrubber + CCS
Retrofit Coal with CCS
Retrofit Oil Gas with SCR
Total
Number of
Units
-
-
Number of IPM
Model Plants
427
1,076
1,575
1,708
357
447
161
1,570
1,372
360
2,281
2,065
141
544
112
587
1,078
14
281
16,156
Early Retirements
Plant Type
CC Early Retirement
Coal Early Retirement
CT Early Retirement
IGCC Early Retirement
Nuke Early Retirement
O/G Early Retirement
Total
Number of
Units
-
-
-
Number of IPM
Model Plants
610
6,178
2,225
5
105
435
9,558
[ Grand Total (Existing and Planned/Committed + New + Retrofits + Early Retirements): 33,201 |
Notes:
1Non Fossil_Other includes units whose fuel is municipal solid waste, tires, and other non-fossil waste.
2The 105 nuclear units include 104 currently operating units plus Watts Bar Nuclear Plant, Unit 2, which is
scheduled to come online in 2014. All are listed in Appendix 4-3.
4-8
-------
4.2.7 Cost and Performance Characteristics of Existing Units
In EPA Base Case v.4.10 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.4.10. 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. The section below contains a discussion of the cost and performance
assumptions for existing units used in the EPA Base Case v.4.10.
Variable Operating and Maintenance Cost (VOM)
VOM represents the non-fuel cost variable associated with producing a unit of 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.4.10. 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 (2007$) in EPA Base Case v.4.10
Capacity Type
Combined Cycle
Coal Steam
Conventional
Hydroelectric
Combined Turbine
Fuel Cell
Geothermal
IGCC
MSW/Landfill Gas
SO2 Control
~
Scrubbed - Dry
Scrubbed -
Wet
Unscrubbed
~
~
~
~
~
~
Hg Control
-
NoHg
AC I
NoHg
AC I
NoHg
AC I
-
NoHg
-
-
-
-
NOX Control
NoNOx
SCR
NoNOx
SCR
SNCR
NoNOx
SCR
SNCR
NoNOx
SCR
SNCR
NoNOx
SCR
SNCR
NoNOx
SCR
SNCR
NoNOx
SCR
SNCR
-
NoNOx
SCR
-
-
-
-
Variable O&M
Range
(mills/kWh)
2.63-7.67
2.75-7.79
3.66-5.05
4.34-5.73
4.73-6.12
4.62-6.02
5.30-6.69
5.70-7.09
2.48-3.87
3.16-4.55
3.55-4.94
3.44-4.83
4.12-5.51
4.51 -5.91
0.90-2.29
1.58-2.97
1.97-3.37
1.87-3.26
2.54-3.94
2.94-4.33
6.66
2.60-9.59
2.73-9.71
9.7
8.3
0 - 4.72
8.79
4-9
-------
Capacity Type
Oil/Gas Steam
Pumped Storage
Solar Photovoltaic
Solar Thermal
Wind
Wood/Biomass
SO2 Control
Scrubbed -
Wet
Unscrubbed
-
~
~
~
-
Hg Control
NoHg
NoHg
-
-
-
-
-
NOX Control
NoNOx
SNCR
NoNOx
SCR
SNCR
-
-
-
-
-
Variable O&M
Range
(mills/kWh)
0.94-5.07
1.49-5.62
0.94-5.07
1.06-5.19
1.49-5.62
8.37
2.09
2.78
3.18
6.98
Fixed Operation and Maintenance Cost (POM)
FOM represents the annual fixed cost of maintaining a unit. FOM costs are incurred independent
of achieved generation levels and signify the fixed cost of operating and maintaining the unit for
generation. Table 4-9 summarizes the FOM assumptions used in EPA Base Case v.4.10. Note
that FOM varies by the age of the unit. The values appearing in this table include the cost of
maintaining any associated pollution control equipment. The values in Table 4-9 are based on
FERC (Federal Energy Regulatory Commission) Form 1 data.
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.4.10 is discussed in Section 3.8.
Lifetimes
Unit lifetime assumptions in EPA Base Case v.4.10 are detailed in Sections 3.7 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.4.10.
4.2.8 Life Extension Costs for existing units
The usable modeling time horizon in previous EPA Base Cases typically extended out only as far
as 2030 and covered a period of roughly 20-25 years. In contrast, the modeling time horizon in
EPA Base Case 4.10 extends to 2050 covers a period of almost 40 years. Due to this longer time
horizon, provision had to be made in EPA Base Case v.4.10 for investments (beyond the routine
maintenance of the power plant) that would be required to extend the life of existing units over this
longer time horizon. 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 annual
capital expenditures over the last 10-15 years of the power plan.
4-10
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Table 4-9 FOM Assumptions Used in EPA Base Case v.4.10
Prime Mover
Type
Combined
Cycle
Conventional
Hydroelectric
Fuel Cell
Gas Turbine
Geothermal
IGCC
MSW/Landfill
Gas
Nuclear
Pumped
Storage
Solar
Photovoltaic
Solar Thermal
Steam Turbine
Primary
Fuel
Oil & Gas
Water
Natural
Gas
Oil & Gas
Earth
Coal
Landfill
Gas
Nuclear
Water
Sun
Sun
Coal
SO2 Control
-
-
-
-
-
-
-
-
-
-
-
Scrubbed -
Dry
Scrubbed -
Wet
Hg
Control
-
-
-
-
-
-
-
-
-
-
-
No Hg
ACI
NoHg
NOX
Control
-
-
-
-
-
-
-
-
-
-
-
NoNOx
SCR
SNCR
No NOX
SCR
SNCR
NoNOx
SCR
Age of Unit
All Years
All Years
All Years
>30 years
20-30 years
0-20 years
All Years
All Years
All Years
All Years
All Years
All Years
All Years
0 to 20 Years
20 to 30 Years
30 to 40 Years
Greater than 40 Years
0 to 20 Years
20 to 30 Years
30 to 40 Years
Greater than 40 Years
0 to 20 Years
20 to 30 Years
30 to 40 Years
Greater than 40 Years
0 to 20 Years
20 to 30 Years
30 to 40 Years
Greater than 40 Years
0 to 20 Years
20 to 30 Years
30 to 40 Years
Greater than 40 Years
0 to 20 Years
20 to 30 Years
30 to 40 Years
Greater than 40 Years
0 to 20 Years
20 to 30 Years
30 to 40 Years
Greater than 40 Years
0 to 20 Years
20 to 30 Years
FOM (2007$
/kW-Yr)
12.6
14.3
18.3
8.8
8.5
3.7
21.6
118.4
23.6
100.5
18.3
17.1
22.6
42.2
44.2
55.1
60.8
42.9
44.9
55.7
61.4
42.5
44.5
55.3
61.1
42.4
44.4
55.2
60.9
43.0
45.0
55.9
61.6
42.6
44.6
55.5
61.2
43.2
45.2
56.0
61.8
43.8
45.8
4-11
-------
Prime Mover
Type
Primary
Fuel
Oil & Gas
SO2 Control
Unscrubbed
-
Hg
Control
ACI
No Hg
ACI
-
NOX
Control
SNCR
No NOX
SCR
SNCR
NoNOx
SCR
SNCR
No NOX
SCR
SNCR
NoNOx
SCR
Age of Unit
30 to 40 Years
Greater than 40 Years
0 to 20 Years
20 to 30 Years
30 to 40 Years
Greater than 40 Years
0 to 20 Years
20 to 30 Years
30 to 40 Years
Greater than 40 Years
0 to 20 Years
20 to 30 Years
30 to 40 Years
Greater than 40 Years
0 to 20 Years
20 to 30 Years
30 to 40 Years
Greater than 40 Years
0 to 20 Years
20 to 30 Years
30 to 40 Years
Greater than 40 Years
0 to 20 Years
20 to 30 Years
30 to 40 Years
Greater than 40 Years
0 to 20 Years
20 to 30 Years
30 to 40 Years
Greater than 40 Years
0 to 20 Years
20 to 30 Years
30 to 40 Years
Greater than 40 Years
0 to 20 Years
20 to 30 Years
30 to 40 Years
Greater than 40 Years
0 to 20 Years
20 to 30 Years
30 to 40 Years
Greater than 40 Years
0 to 20 Years
20 to 30 Years
30 to 40 Years
Greater than 40 Years
0 to 20 Years
FOM (2007$
/kW-Yr)
56.7
62.4
43.5
45.5
56.3
62.0
43.3
45.3
56.2
61.9
44.0
46.0
56.8
62.6
43.6
45.6
56.5
62.2
32.9
34.9
45.8
51.5
33.6
35.6
46.4
52.2
33.2
35.2
46.1
51.8
33.1
35.1
45.9
51.7
33.7
35.7
46.6
52.3
33.3
35.3
46.2
51.9
18.4
21.0
22.3
28.4
19.3
4-12
-------
Prime Mover
Type
Wind
Wood/Biomass
Primary
Fuel
Wind
Biomass
SO2 Control
-
-
Hg
Control
-
-
NOX
Control
SNCR
-
-
Age of Unit
20 to 30 Years
30 to 40 Years
Greater than 40 Years
0 to 20 Years
20 to 30 Years
30 to 40 Years
Greater than 40 Years
All Years
All Years
FOM (2007$
/kW-Yr)
21.9
23.2
29.3
18.6
21.2
22.5
28.6
18.3
20.1
Table 4-10 Life Extension Cost Assumptions Used in EPA Base Case v.4.10
Plant Type
Coal Steam
Combined Cycle
Combustion Turbine &
1C Engine
Oil/Gas Steam
IGCC
Nuclear
Lifespan
without Life
Extension
Expenditures
40
30
30
40
40
40
Life Extension
Cost as
Proportion of
New Unit
Capital Cost
(%)
7.0
9.3
4.2
3.4
7.4
9.0
Capital
Cost of
New Unit
(2007$/kW)
2,918
976
698
2,699
3,265
4,621
Life
Extension
Cost
(2007$/kW)
204
91
30
91
242
416
Note:
Life extension expenditures double the lifespan of the unit.
4.3 Planned-Committed Units
EPA Base Case v.4.10 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 2012.
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.4.10 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.4.10 indicating its generating capacity by unit types.
Due to data confidentiality restrictions, NEEDS v.4.10 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.4.10.
4-13
-------
Table 4-11 Summary of Planned-Committed Units in NEEDS v.4.10 for EPA Base Case
v.4.10
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
Wind
Subtotal
495
3
302
91
279
35
235
40
687
26,295
28,462
2007-2012
2011
2007-2011
2007-2011
2007-2011
2007-2011
2011
2011
2007-2011
2007-2011
Fossil/Conventional
Coal Steam
Combined Cycle
Combustion Turbine
Fossil Waste
IGCC
Nuclear
O/G Steam
Subtotal
Grand Total
17,055
25,088
9,648
274
1,230
1,180
115
54,590
83,052
2007-2011
2007-2011
2007-2011
2011
2009-2011
2014
2008-2011
Table 4-12 Planned-Committed Units by Model Region in NEEDS v.4.10 for EPA Base Case
v.4.10
IPM Region
AZNM
CA-N
CA-S
Plant Type
Biomass
Coal Steam
Combined Cycle
Combustion Turbine
Geothermal
Solar
Wind
Combined Cycle
Combustion Turbine
Fuel Cell
Geothermal
Landfill Gas
Solar
Wind
Biomass
Combined Cycle
Combustion Turbine
Fuel Cell
Hydro
Landfill Gas
Capacity (MW)
24
400
94
593
95
20
130
1,279
603
1
25
17
249
2,533
2
1,293
454
2
5
8
4-14
-------
IPM Region
COMD
DSNY
ENTG
ERCT
FRCC
GWAY
LILC
MACE
MACS
MACW
MRO
Plant Type
Pumped Storage
Solar
Wind
Combined Cycle
Landfill Gas
Wind
Combined Cycle
Biomass
Coal Steam
Combined Cycle
Biomass
Coal Steam
Combined Cycle
Combustion Turbine
Fossil Waste
Landfill Gas
Non-Fossil Waste
Solar
Wind
Combined Cycle
Combustion Turbine
Landfill Gas
Municipal Solid Waste
Coal Steam
Landfill Gas
Wind
Combined Cycle
Combustion Turbine
Landfill Gas
O/G Steam
Solar
Combustion Turbine
Landfill Gas
O/G Steam
Biomass
Landfill Gas
Municipal Solid Waste
Wind
Landfill Gas
Wind
Biomass
Coal Steam
Combined Cycle
Combustion Turbine
Hydro
Landfill Gas
Municipal Solid Waste
Capacity (MW)
40
255
112
573
6
282
635
14
665
1,336
50
3,250
3,266
639
274
16
10
3
7,669
6,365
1,191
21
16
1,800
5
1,177
350
105
27
9
7
30
5
100
30
22
14
480
10
480
107
1,782
1,204
878
11
7
5
4-15
-------
IPM Region
NENG
NWPE
NYC
PNW
RFCO
RFCP
RMPA
SNV
SOU
Plant Type
Non-Fossil Waste
Wind
Biomass
Combined Cycle
Combustion Turbine
Hydro
Landfill Gas
O/G Steam
Solar
Wind
Biomass
Coal Steam
Combined Cycle
Geothermal
Hydro
Solar
Wind
Combustion Turbine
Biomass
Combined Cycle
Combustion Turbine
Hydro
Landfill Gas
Non-Fossil Waste
Solar
Wind
Combined Cycle
IGCC
Landfill Gas
Non-Fossil Waste
Wind
Coal Steam
Combined Cycle
Landfill Gas
Non-Fossil Waste
Wind
Coal Steam
Combustion Turbine
Hydro
Landfill Gas
Solar
Wind
Combustion Turbine
Solar
Wind
Biomass
Combined Cycle
Capacity (MW)
25
4,598
44
987
301
16
11
6
1
650
1
1,112
1,062
182
12
2
266
1
31
1,262
175
19
10
58
2
2,584
720
1,230
26
3
554
695
580
5
80
264
768
658
9
6
15
1,362
720
112
189
116
1,237
4-16
-------
IPM Region
SPPN
SPPS
TVAK
UPNY
VACA
VAPW
WUMS
Plant Type
Non-Fossil Waste
Coal Steam
Combustion Turbine
Wind
Coal Steam
Combined Cycle
Combustion Turbine
Non-Fossil Waste
Solar
Wind
Nuclear
Wind
Coal Steam
Combustion Turbine
Landfill Gas
Biomass
Hydro
Landfill Gas
Non-Fossil Waste
Wind
Coal Steam
Combustion Turbine
Hydro
Landfill Gas
Solar
Wind
Combined Cycle
Combustion Turbine
Landfill Gas
Solar
Biomass
Coal Steam
Combined Cycle
Landfill Gas
Wind
Capacity (MW)
18
1,172
845
651
660
1,080
939
35
8
943
1,180
111
1,018
200
5
25
13
14
7
826
1,980
779
6
18
12
38
1,190
537
31
1
50
1,753
575
8
396
Note:
Any unit that has an online year of 2007- 2011 was considered a Planned and Committed Unit
4.3.2 Capacity
The capacity of planned-committed units in NEEDS v.4.10 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.4.10 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.
4-17
-------
4.3.4 Online and Retirement Year
As noted above, planned-committed units included in NEEDS v.4.10 are only those units which
are likely to come on-line before 2012. All planned-committed units were given a default online
year of end of 2011 since this is the first analysis year in EPA Base Case v.4.10. The
assumptions in EPA Base Case v.4.10 do not include a lifetime for planned-committed units.
4.3.5 Unit Configuration and Cost-and-Performance
All planned-committed units in NEEDS v.4.10 assume the cost, performance, and unit
configuration characteristics of potential units that are available in 2012. A detailed description of
potential unit assumptions is provided below in Section 4.4.
4.4 Potential Units
The EPA Base Case v.4.10 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 MWare 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.4.10. The following sections describe the cost and
performance assumptions for the potential units represented in the EPA Base Case v.4.10.
4.4.1 Methodology Used to Derive the Cost and Performance Characteristics of
Conventional Potential Units
Cost and performance assumptions for potential units in previous EPA base cases were based
primarily on data from the latest available Annual Energy Outlook (AEO) published by the U.S.
Department of Energy's Energy Information Administration. However, an unprecedented run up in
the costs of new generating units over the preceding 5 years prompted EPA to analyze other
references in addition to the AEO for Base Case v.4.10. The cost escalation which was
particularly noticeable for base load electric generating units, was generally attributed to
international competition and, was increasingly seen as permanent. That is, there was a growing
consensus that costs were not going to settle back to pre-2010 levels.
With this in mind, the power sector engineering staff in EPA's Clean Air Markets Division
performed comparative cost analyses based on reports and discussions with government
agencies, national technical laboratories, industry, academia, and various non-governmental
organizations. The key sources reviewed included:
U.S. Energy Information Administration: Annual Energy Outlook 2008, 2009, 2010
National Energy Technology Laboratory, Fossil Energy Power Plant Desk Reference
(Bituminous Coal)19
18 U.S. Department of Energy, Energy Information Administration, Assumptions to the Annual
Energy Outlook 2008: Electric Market Module, DOE/EIA-0554(2008), June 2008.
www.eia.doe.gov/oiaf/archive/aeo08/assumption/electricity.html
U.S. Department of Energy, Energy Information Administration, Assumptions to the Annual
Energy Outlook 2009: Electric Market Module, DOE/EIA-0554(2009), March 2009.
www.eia.doe.gov/oiaf/archive/aeo09/assumption/electricitv.html
U.S. Department of Energy, Energy Information Administration, Assumptions to the Annual
Energy Outlook 2010: Electric Market Module, #:DOE/EIA-0554(2010), April 2010.
www.eia.doe.gov/oiaf/aeo/assumption/electricity.html.
19 U.S. Department of Energy, National Energy Technology Laboratory, Foss;7 Energy Power Plant
Desk Reference, Bituminous Coal and Natural Gas to Electricity Summary Sheets DOE/NETL-
4-18
-------
U.S. Environmental Protection Agency, Environmental Footprints and Costs of Coal-Based
Integrated Gasification Combined Cycle and Pulverized Coal Technologies20
EPRI (Electric Power Research Institute): "Economic Assessment of Advanced Coal-Based
Power Plants with CO2 Capture"21
Harvard University: "Realistic Costs of Carbon Capture"22
Massachusetts Institute of Technology: "Update on the Cost of Nuclear Power"23
Union of Concerned Scientists: Climate 2030 - A National Blueprint for a Clean Energy
Economy24
4.4.2 Cost and Performance for Potential Conventional Units
The comparative analyses described in the preceding section resulted in the cost and
performance characteristics shown in Table 4-13. They are based on EPA's engineering
assessments. As seen in Table 4-13, EPA Base Case v.4.10 includes cost and performance
characteristics for the following potential technologies: supercritical pulverized coal, advanced
combined cycle, advanced combustion turbines, integrated gasification combined cycle (IGCC),
advanced coal with carbon capture capabilities, and nuclear units. The cost and performance
assumptions are based on the size (i.e., 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 a
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.4.10 are discussed in Chapter 8 under financial
assumptions.
2007/1282, May 2007. http://www.netl.doe.qov/enerqv-
analvses/pubs/Cost%20and%20Performance%20Baseline-012908.pdf
20U.S. EPA, Environmental Footprints and Costs of Coal-Based Integrated Gasification Combined
Cycle and Pulverized Coal Technologies. EPA-430/R-06/2006, July 2006.
21Booras, G., Economic Assessment of Advanced Coal-Based Power Plants with CO2 Capture, a
presentation at EPRI (Electric Power Research Institute) MIT Carbon Sequestration Forum 1C,
September 16, 2008.
22AI-Juaied, M and A Whitmore, ""Realistic Costs of Carbon Capture" Harvard Kennedy School.
Belfer Center Discussion Paper 2009-08, July 2009.
http://belfercenter.ksq.harvard.edu/files/2009 AUuaied Whitmore Realistic Costs of Carbon C
apture web.pdf
23Du, Y., J.E. Parsons (2009). Update on the cost of nuclear power. MIT Center for Energy and
Environmental Policy Research (CEEPR) Working Paper 09-004, May 2009.
http://web.mit.edu/ceepr/www/publications/workinqpapers/2009-004.pdf
24Cleetus R., S. Clemmer, and D. Friedman, Climate 2030 - A National Blueprint for a Clean
Energy Economy, Union of Concerned Scientists, May 2009.
http://www.ucsusa.org/global warming/solutions/big picture solutions/climate-2030-
blueprint.html#Download the Climate 2030 Blueprint repo
4-19
-------
Table 4-13 Performance and Unit Cost Assumptions for Potential (New) Capacity from Conventional Technologies in EPA Base Case v4.10
Size (MW)
First Year
Available
Lead Time (Years)
Vintage #1
(years covered)
Availability
Advanced
Combined
Cycle
560
2015
3
2012-
2054
87%
Advanced
Combustion
Turbine
170
2012
2
201 2 - 2054
92%
Nuclear
1350
2017
6
2012-
2054
90%
Integrated
Gasification
Combined
Cycle -
Bituminous
600
2013
4
201 2 - 2054
85%
Integrated
Gasification
Combined Cycle
- Subbituminous
600
2013
4
201 2 - 2054
85%
Advanced
Coal with
Carbon
Capture-
Bituminous1
500
2015
4
2012-2054
85%
Advanced Coal
with Carbon
Capture -
Subbituminous1
500
2015
4
201 5 - 2054
85%
Supercritical
Pulverized
Coal - Wet
Bituminous
600
2013
4
2012-2054
85%
Supercritical
Pulverized
Coal - Dry
Sub-
Bituminous
600
2013
4
2012-2054
85%
Vintage #1
Heat Rate
(Btu/kWh)
Capital2
(2007$/kW)
Fixed O&M
(2007$/kW/yr)
Variable O&M
(2007$/MWh)
6,810
976
14.4
2.57
10,720
698
12.3
3.59
10,400
4,621
92.4
0.77
8,424
3,265
47.9
1.32
8,062
3,310
48.2
1.15
10,149
4,720
60.5
1.67
9,713
4,785
61.0
1.46
8,874
2,918
28.9
3.43
8,937
3,008
28.6
2.27
Notes:
1For The term "Advanced Coal with Carbon Capture" is used here and in the output files for EPA Base Case v.4.10 to represent a variety of
technologies that are expected to provide carbon capture capabilities. These include both supercritical steam generators with carbon capture and
integrated gasification combined cycle (IGCC) with carbon capture. Although IGCC with carbon capture was used to define the cost and
performance parameters that are implemented in EPA Base Case v.4.10, projections of "Advanced Coal with Carbon Capture" in EPA Base Case
v.4.10 are not limited to this technology.
2Capital cost represents overnight capital cost.
4-20
-------
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 kW per year. VOM represents the 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 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 3-11.
4.4.3 Short-Term Capital Cost Adder
Besides the capital costs shown in Table 4-13 and Table 4-16 EPA Base Case v.4.10 includes a
short-term capital cost adder that kicks in if the new capacity in a specific model run year exceeds
certain upper bounds. This 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 then market adjustments will have eliminated the short term scarcity experienced
in earlier years.
Here's how these short-term adders work in Base Case v.4.10: 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 2012 for coal steam potential units is 25,301 MW. If no more than this total new coal
steam capacity is built in 2012, only the capital cost shown in Table 4-13 is incurred. Between
25,301 and 42,168 MW (the sum of the Step 1 and Step 2 upper bounds, i.e., 25,301 MW+ 16,
867 MW = 42,168 MW), the Step 2 cost adder of $967/MW 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 25,301 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 42,168 MW, then the Step 3
capacity adder of $2,500/MW is incurred. To determine if the upper bounds for plant type "Coal
Steam" in Table 4-14 have been reached, one must sum the capacities added in a model run year
for plant types Supercritical Pulverized Coal - Wet Bituminous and Supercritical Pulverized Coal -
Dry Bituminous. The upper bound for "Coal Steam" applies to the sum of the capacity added in
the model run year for these two plant types.
The short-term capital cost adders shown in Table 4-14 were derived from AEO assumptions.
4-21
-------
4.4.4 Regional Cost Adjustment
The capital costs reported in Table 4-14 are generic. Before EPA implements these capital cost
values they are converted to region-specific costs. This is done through the application of regional
adjustment factors which capture regional differences in labor, material, and construction costs.
The regional adjustment factors used in EPA Base Case v.4.10 are shown in Table 4-15. They
were developed from AEO and are applied to both conventional technologies shown in Table 4-13
and to the renewable and non-conventional technologies shown in Table 4-16 below.
4-22
-------
Table 4-14 Short-Term Capital Cost Adders for New Power Plants in EPA Base Case v.4.10 (2007$)
ID
Number
1
2
3
4
5
6
7
8
9
10
11
Plant Type
Biomass
Coal Steam
Combined
Cycle
Combustion
Turbine
Fuel Cell
Geothermal
IGCCand
Advanced
Coal with
Carbon
Capture
Landfill Gas
Nuclear
Solar
Thermal
Solar PV
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 ($/kW)
Upper Bound (MW)
Adder ($/kW)
Upper Bound (MW)
Adder ($/kW)
Upper Bound (MW)
Adder ($/kW)
Upper Bound (MW)
Adder ($/kW)
2012
Step 1 Step 2 Step 3
600 400
1,410 3,646
8,434 5,622
967 2,500
46,469 30,979
310 801
24,098 16,066
213 551
600 400
1,987 5,138
315 210
1,981 5,123
2,400 1 ,600
1 ,072 2,774
600 400
1,135 2,936
1 1 ,230 7,487
1 ,579 4,083
106 70
1,608 4,158
54 36
1 ,733 4,483
2015
Step 1 Step 2 Step 3
1 ,800 1 ,200
1,410 3,646
25,301 16,867
967 2,500
139,406 92,937
310 801
72,295 48,197
213 551
1 ,800 1 ,200
1,987 5,138
946 630
1,981 5,123
7,200 4,800
1 ,072 2,774
1 ,800 1 ,200
1,135 2,936
33,690 22,460
1 ,579 4,083
317 211
1,608 4,158
54 36
1 ,733 4,483
2020
Step 1 Step 2 Step 3
3,000 2,000
1,410 3,646
42,168 28,112
967 2,500
232,344 154,896
310 801
120,492 80,328
213 551
3,000 2,000
1,987 5,138
1 ,576 1 ,051
1,981 5,123
12,000 8,000
1 ,072 2,774
3,000 2,000
1,135 2,936
56,151 37,434
1 ,579 4,083
528 352
1,608 4,158
90 60
1 ,733 4,483
2030
Step 1 Step 2 Step 3
6,000 4,000
1,410 3,646
84,336 56,224
967 2,500
464,687 309,791
310 801
240,984 160,656
213 551
6,000 4,000
1,987 5,138
3,152 2,102
1,981 5,123
24,000 16,000
1 ,072 2,774
6,000 4,000
1,135 2,936
112,301 74,867
1 ,579 4,083
1 ,056 704
1,608 4,158
180 120
1 ,733 4,483
4-23
-------
ID
Number
12
13
Plant Type
Onshore
Wind
Offshore
Wind
Upper Bound (MW)
Adder ($/kW)
Upper Bound (MW)
Adder ($/kW)
2012
Step 1 Step 2 Step 3
23,000 19,670
646 1 ,672
600 400
1 ,304 3,373
2015
Step 1 Step 2 Step 3
29,505 19,670
646 1 ,672
1 ,800 1 ,200
1 ,304 3,373
2020
Step 1 Step 2 Step 3
49,174 32,783
646 1 ,672
3,000 2,000
1 ,304 3,373
2030
Step 1 Step 2 Step 3
98,348 65,566
646 1 ,672
6,000 4,000
1 ,304 3,373
Note:
The term "Advanced Coal with Carbon Capture" is used here and in the output files for EPA Base Case v.4.10 to represent a variety of
technologies that are expected to provide carbon capture capabilities. These include both supercritical steam generators with carbon capture and
integrated gasification combined cycle (IGCC) with carbon capture. Although IGCC with carbon capture was used to define the cost and
performance parameters that are implemented in EPA Base Case v.4.10 and shown in Table 4-13, projections of "Advanced Coal with Carbon
Capture" in EPA Base Case v.4.10 are not limited to this technology.
4-24
-------
Table 4-15 Regional Cost Adjustment Factors for Conventional and Renewable Generating
Technologies in EPA Base Case v.4.10
Model
Region
AZNM
CA-N
CA-S
COMD
DSNY
ENTG
ERCT
FRCC
GWAY
LILC
MACE
MACS
MACW
MEGS
MRO
NENG
NWPE
NYC
PNW
RFCO
RFCP
RMPA
SNV
SOU
SPPN
SPPS
TVA
TVAK
UPNY
VACA
VAPW
WUMS
Region Description or Reliability Council Name
Western Electricity Coordinating Council - Arizona, New Mexico
Western Electricity Coordinating Council - California North
Western Electricity Coordinating Council - California South
Commonwealth Edison
Downstate New York
Entergy
Texas Regional Entity
Florida Reliability Coordinating Council
Gateway
Long Island Company
Legacy Mid-Atlantic Area Council - East
Legacy Mid-Atlantic Area Council - South
Legacy Mid-Atlantic Area Council - West
Michigan Electric Coordination System
Midwest Regional Planning Organization
New England Power Pool
Western Electricity Coordinating Council - Northwest Power Pool
East
New York City
Western Electricity Coordinating Council - Pacific Northwest
Reliability First Corporation - MISO
Reliability First Corporation - PJM
Western Electricity Coordinating Council - Rocky Mountain Power
Area
Western Electricity Coordinating Council - Southern Nevada
Southern Company
Southwest Power Pool - North
Southwest Power Pool - South
Tennessee Valley Authority
Tennessee Valley Authority - MISO-KY
Upstate New York
Virginia-Carolinas
Dominion Virginia Power
Wisconsin-Upper Michigan
Regional
Factor
1.003
1.058
1.058
1.004
1.043
0.960
0.986
0.961
1.004
1.879
0.996
0.996
0.996
1.004
1.004
1.145
1.026
1.989
1.026
1.004
1.004
1.003
1.003
0.960
0.997
0.997
0.960
1.004
1.043
0.960
0.960
1.004
4-25
-------
4.4.5 Cost and Performance for Potential Renewable Generating and Non-Conventional
Technologies
The renewable and non-conventional generating technologies included as potential units in the
EPA Base Case v.4.10 are conventional biomass boilers, biomass gasification combined cycle
(BGCC), onshore and offshore wind (shallow and deep), geothermal, fuel cells, solar photovoltaic,
solar thermal, and landfill gas. Table 4-16 summarizes the cost and performance assumptions in
EPA Base Case v.4.10 for these potential units. Except for biomass, the parameters shown in
Table 4-16 are based on AEO 2009. The size (MW) presented in 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 Table 4-16 are averages or ranges that
are discussed in further detailed in the following subsections. Also discussed below are additional
types of data from sources other than AEO 2009 that play a role in the representation of these
types of generation in EPA Base Case v.4.10.
4-26
-------
Table 4-16 Performance and Unit Cost Assumptions for Potential (New) Renewable and Non-Conventional Technology Capacity in EPA
Base Case v4.10
Size (MW)
First Year Available
Lead Time (Years)
Vintage #1
(years covered)
Vintage #2
(years covered)
Vintage #3
(years covered)
Availability
Generation Capability
Biomass
Conventional
Boiler
35
2013
3
2012-2054
85%
Biomass
Gasification
Combined
Cycle1
120
2019
4
2020 - 2054
85%
Fuel
Cells
10
2013
3
2012-
2054
87%
Geothermal
50
2014
4
201 2 - 2054
87%
Landfill Gas
LGHI
LGLo
LGVLo
30
2013
3
2012-
2019
2020-
2029
2030-
2054
2012-
2019
2020-
2029
2030-
2054
2012-
2019
2020-
2029
2030-
2054
90%
Economic Dispatch
Solar
Photovoltaic
5
2012
2
2012 - 2019
2020 - 2029
2030 - 2054
90%
Solar
Thermal
100
2013
3
2012-
2019
2020-
2029
2030-
2054
90%
Onshore
Wind
50
2013
3
2012-
2019
2020-
2029
2030-
2054
95%
Offshore
Wind
50
2013
3
2012-
2019
2020-
2029
2030-
2054
95%
Generation Profile
Vintage #1
Heat Rate (Btu/kWh)
Capital (2007$/kW)2
Fixed O&M (2007$/kW/yr)
Variable O&M (2007$/MWh)
13,500
4,698
85.2
1 1 .60
7,930
6,259
5.7
47.92
29,655 -
397,035
1 624 -
20,674
151 -219
0.00
13,648
2,596
114.3
0.01
13,648
3,270
114.3
0.01
13,648
5,035
114.3
0.01
0
5,765
11.7
0
0
5,156
56.8
0
0
1,954
30.3
0.00
0
3 852 -
5,085
89.5
0.00
Vintage #2
Heat Rate (Btu/kWh)
Capital (2007$/kW) 2
Fixed O&M (2007$/kW/yr)
Variable O&M (2007$/MWh)
9,800
4,071
48.3
8.83
-
-
-
-
-
-
-
-
13,648
2,505
114.3
0.01
13,648
3,156
114.3
0.01
13,648
4,859
114.3
0.01
0
5,350
11.7
0
0
4,641
56.8
0
0
1,912
30.3
0.00
0
3,621 -
4,780
89.5
0.00
Vintage #3
Heat Rate (Btu/kWh)
Capital (2007$/kW) 2
Fixed O&M (2007$/kW/yr)
Variable O&M (2007$/MWh)
-
-
-
-
-
-
-
-
-
-
-
-
13,648
2,019
114.3
0.01
13,648
2,544
114.3
0.01
13,648
3,916
114.3
0.01
0
3,777
11.7
0
0
4,383
56.8
0
0
1,580
30.3
0.00
0
2,809 -
3,708
89.5
0.00
Note:
1 The biomass generating technologies shown in this table represent new capacity designed to burn biomass only. Assumptions for biomass co-firing at existing coal plants can be
found in Table 5-14.
2Capital cost represents overnight capital cost.
4-27
-------
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 did to the conventional generation technologies
Biomass Electricity Generation
Two biomass generation technologies with separate vintage periods are offered as new (potential)
units in EPA Base Case v.4.10. Conventional direct fired biomass boilers are offered in vintage
period 1, i.e., 2012-2019. Based on engineering and market analysis that indicated that biomass
gas combined cycle (BGCC) units will become commercially available by 2020, BGCC with its
much more favorable heat rate and cost characteristics is provided as a potential unit from 2020
onward. Prepared by EPA's power sector engineering staff, the cost and performance
characteristics of these two technology options are shown in Table 4-16.
Wind Generation
Previous EPA base cases only represented onshore wind generation. In addition to onshore
wind, EPA Base Case v.4.10 includes 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: Wind resources are conventionally categorized into wind
quality classes, ranging from class 1 (designated to be the least productive and reliable class for
wind generation) to class 7 (designated to be the most productive and reliable class for wind
generation). Areas designated as wind class 3 or higher are generally suitable for commercial
wind turbine applications. Whereas previous EPA base cases only included wind classes 4, 5,
and 6, EPA Base Case v.4.10 also includes class 3 and 7.
EPA worked with the U.S. Department of Energy's (DOE) National Renewable Energy Laboratory
(NREL), on a complete update of the wind resource assumptions for use in EPA Base Case
v.4.10. The result is a complete representation of the potential onshore, offshore (shallow and
deep) wind generating capacity (in MW) broken into four cost 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.4.10.
4-28
-------
Table 4-17 Onshore Regional Potential Wind Capacity (MW) by Wind and Cost Class in
EPA Base Case v.4.10
IPM Region
AZNM
CA-N
CA-S
COMD
DSNY
ENTG
ERCT
GWAY
LILC
MACE
MACS
MACW
Wind Class
3
4
5
6
7
3
4
5
6
7
3
4
5
6
7
3
4
3
4
5
6
7
3
5
3
4
5
6
7
3
4
3
4
3
4
5
3
4
5
3
4
5
6
Cost Class
1
707
42
6
214
4
1,269
560
79
286
12
1,689
1,323
380
118
46
2
19
98
64
~
-
1
~
3,230
9,912
396
207
5
10
~
-
~
384
9
~
8
2
~
700
182
71
-
2
1,714
329
2,028 1
447
106
~
1 ,069 1
631
~
352
~
1 ,460 1
614
~
~
-
260
599
60
~
-
1
20
1
32,701 2
1,415
~
~
-
621
-
128
-
~
~
~
5
~
1 ,054 1
26
3
44
27
612
264
144
-
476
746
795
-
-
402
653
435
231
-
-
297
30
-
198
796
899
512
-
-
580
872
-
925
-
-
-
-
747
636
200
-
4
125,761
33,741
2,355
512
166
8,646
1,539
765
740
399
18,014
2,536
831
540
233
62,549
312
500
268
89
29
29
2
30
321,950
51,392
1,484
582
20
275,467
922
567
194
1,264
163
2
57
10
3
2,412
477
161
46
4-29
-------
IPM Region
MEGS
MRO
NENG
NWPE
PNW
RFCO
RFCP
RMPA
SNV
SOU
SPPN
Wind Class
3
4
5
3
4
5
6
3
4
5
6
7
3
4
5
6
7
3
4
5
6
7
3
4
3
4
5
6
7
3
4
5
6
7
3
4
5
6
3
3
4
5
Cost Class
1
3,571
17
7
2,052
1,310
1,768
737
364
28
147
1,913
1,891
353
122
205
216
69
11
34
18
12,199
196
82
44
41
2
1,327
3,222
2,546
3,149
619
9
1
1
1
1,933
2
11
103 163,
22,146 68,
1,985 1,
1,128
442
356
6,167 7,
1,058 3,
1,239 3,
1,517
902
322
86
87
116
22,865 8,
289 4,
354
24
4,769 8,
7,038 15,
8,000 11,
6,188 2,
-
~
9,618 37,
3
467
083
431
380
471
657
600
823
755
354
208
122
99
79
334
841
169
148
447
851
388
151
-
2
341
4
35,633
259
12
2,021,548
1,010,547
156,014
4,489
9,127
1,968
969
438
478
630,559
236,910
50,582
17,728
1,755
74,323
15,515
3,483
1,463
190
28,239
64
2,976
466
159
96
53
409,831
216,430
58,990
14,741
6,748
2,707
234
39
11
2
454,442
163,483
839
4-30
-------
IPM Region
SPPS
TVA
TVAK
UPNY
VACA
VAPW
WUMS
Wind Class
3
4
5
6
7
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
Cost Class
1
109
2,945
2,660
3
~
204
~
19
3
~
4
2
~
-
~
-
~
~
92
33
8
4
~
~
13
5
5
~
371
57
-
2
~
1 1 ,388 44
13,184
105
~
~
121
~
~
5
~
~
~
-
2,822 3
403
95
~
272
60
~
~
7
261
40
~
~
11
~
49
-
3
69
398
-
111
-
-
166
56
19
-
17
1
346
-
-
35
-
-
39
30
-
34
29
-
-
64
-
4
452,934
349,741
21,167
170
34
637
155
62
16
12
220
15
5
-
3,675
555
114
25
879
124
44
27
18
352
100
35
33
17
130,624
84
41
4-31
-------
Table 4-18 Offshore Shallow Regional Potential Wind Capacity (MW) by Wind and Cost
Class in EPA Base Case v.4.10
IPM Region
CA-N
CA-S
COMD
DSNY
ENTG
ERCT
FRCC
LILC
MACE
MACS
MACW
MECS
MRO
Wind Class
3
4
5
6
7
3
4
5
6
7
3
4
3
3
4
3
4
5
3
4
3
4
5
6
3
4
5
6
3
4
3
4
5
6
3
4
5
6
7
3
4
5
6
Cost Class
1
497
281
43
29
1
280
139
139
114
1
393
981
11
43,021
695
14,372
15,191
4,457
43,305
6,120
693
1,610
1,851
530
2,745
8,161
8,838
5,123
1,066
187
160
136
1,320
5
2,349
3,850
5,451
1,886
6
399
952
348
1
2
995
561
86
59
3
560
277
278
228
3
785
1,963
22
86,041
1,390
28,745
30,382
8,915
86,610
12,240
1,385
3,220
3,703
1,060
5,490
16,323
17,676
10,246
2,132
374
319
271
2,640
11
4,699
7,701
10,903
3,771
13
798
1,904
696
3
4
995
561
86
59
3
560
277
278
228
3
785
1,963
22
86,041
1,390
28,745
30,382
8,915
86,610
12,240
1,385
3,220
3,703
1,060
5,490
16,323
17,676
10,246
2,132
374
319
271
2,640
11
4,699
7,701
10,903
3,771
13
798
1,904
696
3
4-32
-------
IPM Region
NENG
NYC
PNW
RFCO
SOU
UPNY
VACA
VAPW
WUMS
Wind Class
3
4
5
6
7
3
4
5
3
4
5
6
7
3
4
5
6
3
4
5
3
4
5
3
4
5
6
3
4
5
6
3
4
5
6
Cost Class
1
2,326
3,134
2,989
6,157
334
99
253
3
716
1,651
1,310
204
112
686
2,298
5,664
1,963
8,466
4,903
311
884
859
659
6,229
12,064
13,709
3,209
1,990
3,422
3,886
3,660
2,272
2,902
1,832
680
2
4,652
6,269
5,978
12,314
667
198
506
5
1,432
3,303
2,620
407
224
1,371
4,595
1 1 ,328
3,925
16,933
9,806
621
1,768
1,718
1,318
12,458
24,129
27,418
6,419
3,981
6,843
7,772
7,321
4,544
5,805
3,664
1,360
4
4,652
6,269
5,978
12,314
667
198
506
5
1,432
3,303
2,620
407
224
1,371
4,595
1 1 ,328
3,925
16,933
9,806
621
1,768
1,718
1,318
12,458
24,129
27,418
6,419
3,981
6,843
7,772
7,321
4,544
5,805
3,664
1,360
4-33
-------
Table 4-19 Offshore Deep Regional Potential Wind
in EPA Base Case
Capacity (MW) by Wind and Cost Class
v.4.10
IPM Region
CA-N
CA-S
COMD
ENTG
ERCT
FRCC
LILC
MACE
MACS
MACW
MECS
MRO
NENG
Wind Class
3
4
5
6
7
3
4
5
6
7
4
5
6
3
4
4
5
3
4
5
4
5
6
7
3
4
5
6
4
4
5
3
4
5
6
7
3
4
5
6
3
4
5
6
7
Cost Class
1
4,039
25,846
9,947
21,282
19,318
10,721
9,247
14,402
10,140
169
1,028
1,100
950
13,473
10,730
10,501
6,548
28,019
53,858
1,109
501
431
15,589
5
11
140
1,049
22,490
7
29
557
220
701
7,710
33,394
45
354
4,882
3,283
1,535
144
1,754
3,683
59,338
1,762
2
8,077
51,693
19,894
42,565
38,636
21,441
18,494
28,805
20,280
339
2,055
2,200
1,900
26,945
21,461
21,003
13,096
56,037
107,715
2,219
1,002
861
31,178
10
22
280
2,099
44,979
14
58
1,114
439
1,403
15,420
66,787
90
707
9,765
6,566
3,070
287
3,508
7,366
118,676
3,524
4
8,077
51,693
19,894
42,565
38,636
21,441
18,494
28,805
20,280
339
2,055
2,200
1,900
26,945
21,461
21,003
13,096
56,037
107,715
2,219
1,002
861
31,178
10
22
280
2,099
44,979
14
58
1,114
439
1,403
15,420
66,787
90
707
9,765
6,566
3,070
287
3,508
7,366
118,676
3,524
4-34
-------
IPM Region
NYC
PNW
RFCO
SOU
UPNY
VACA
VAPW
WUMS
Wind Class
4
3
4
5
6
7
4
5
6
3
4
5
3
4
5
6
4
5
6
5
6
3
4
5
6
Cost Class
1
58
241
813
12,502
34,795
25,739
9
1,162
507
8,765
15,055
2,169
50
1,506
5,993
465
2
6,536
23,687
151
16,150
395
3,533
8,073
39,059
2
116
482
1,625
25,005
69,589
51,477
19
2,323
1,014
17,529
30,109
4,339
100
3,011
11,986
930
3
13,073
47,373
302
32,300
790
7,066
16,145
78,119
4
116
482
1,625
25,005
69,589
51,477
19
2,323
1,014
17,529
30,109
4,339
100
3,011
1 1 ,986
930
3
13,073
47,373
302
32,300
790
7,066
16,145
78,119
4-35
-------
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.4.10 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 Hourl 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 Appendix
4-1 shows the generation profile for onshore wind in model region CA-N.) In IPM the seasonal
average "kWh of generation per MW (shown in the last row of the example in Appendix 4-1) is
used to derive the generation from a particular wind class in a specific model region.
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.4.10 were obtained from
AEO 2010 and are shown in Table 4-20, Table 4-21, and. Table 4-22
Reserve Margin Contribution (also referred to as capacity credit): EPA Base Case v.4.10 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 all renewable resource technologies except wind and solar,
have 100 percent contribution towards reserve margin in the EPA Base Case v.4.10. (Note Hydro,
not considered a renewable technology, also has less than a 100% reserve margin contribution.)
Reserve margin contribution ratios are based on AEO 2010. Table 4-20, Table 4-21, and Table
4-22 present the reserve margin contributions apportioned to new wind plants in the EPA Base
Case v.4.10 as derived from AEO 2010. The tables show the onshore and offshore (shallow and
deep) reserve margins for each wind class in each model region.
4-36
-------
Table 4-20 Onshore Reserve Margin Contribution an Average Capacity Factor by Wind
Class and Model Region
IPM Model Region
AZNM
CA-N
CA-S
COMD
DSNY
ENTG
ERCT
GWAY
LILC
MACE
MACS
MACW
MEGS
MRO
NENG
NWPE
PNW
RFCO
RFCP
RMPA
SNV
SOU
SPPN
SPPS
TVA
TVAK
UPNY
VACA
VAPW
WUMS
Average Annual
Capacity Factor
Wind Class
3
22%
14%
14%
18%
18%
26%
19%
18%
18%
18%
18%
18%
22%
19%
15%
25%
25%
22%
22%
22%
22%
26%
24%
24%
26%
22%
18%
26%
26%
18%
29%
4
24%
16%
16%
20%
20%
21%
20%
20%
20%
20%
20%
25%
21%
16%
28%
28%
25%
25%
24%
24%
27%
27%
29%
25%
20%
29%
29%
20%
33%
5
29%
19%
19%
~
24%
35%
25%
~
24%
24%
24%
30%
26%
20%
33%
33%
~
30%
29%
29%
33%
33%
35%
30%
24%
35%
35%
24%
39%
6
34%
22%
22%
~
28%
29%
~
~
28%
~
30%
23%
39%
39%
~
35%
34%
34%
~
38%
41%
35%
28%
41%
41%
~
46%
7
37%
24%
24%
~
30%
32%
~
~
~
~
25%
42%
42%
~
38%
37%
~
~
42%
44%
~
44%
44%
~
50%
Table 4-21 Offshore Shallow Reserve Margin Contribution an Average Capacity Factor by
Wind Class and Model Region
IPM Model Region
CA-N
CA-S
COMD
DSNY
ENTG
ERCT
FRCC
LILC
Wind Class
3
15%
15%
19%
19%
27%
20%
19%
19%
4
17%
17%
21%
30%
22%
21%
21%
5
20%
20%
~
~
26%
25%
6
24%
24%
~
~
~
29%
7
25%
25%
~
~
~
~
4-37
-------
IPM Model Region
MACE
MACS
MACW
MEGS
MRO
NENG
NYC
PNW
RFCO
SOU
UPNY
VACA
VAPW
WUMS
Average Annual
Capacity Factor
Wind Class
3
19%
19%
19%
23%
20%
15%
19%
26%
23%
27%
19%
27%
27%
19%
31%
4
21%
21%
21%
26%
22%
17%
21%
29%
26%
30%
21%
30%
30%
21%
34%
5
25%
25%
31%
27%
21%
25%
35%
31%
36%
25%
36%
36%
25%
41%
6
30%
30%
37%
32%
24%
~
41%
37%
~
43%
43%
30%
48%
7
~
~
39%
26%
~
44%
~
~
~
~
52%
Table 4-22 Offshore Deep Reserve Margin Contribution an Average Capacity Factor by
Wind Class and Model Region
IPM Model Region
CA-N
CA-S
COMD
ENTG
ERCT
FRCC
LILC
MACE
MACS
MACW
MEGS
MRO
NENG
NYC
PNW
RFCO
SOU
UPNY
VACA
VAPW
WUMS
Average Annual
Capacity Factor
Wind Class
3
15%
15%
27%
~
18%
~
19%
~
23%
20%
15%
26%
~
27%
19%
~
19%
31%
4
17%
17%
21%
30%
22%
21%
21%
21%
21%
21%
26%
23%
17%
21%
29%
26%
30%
21%
30%
~
21%
35%
5
20%
20%
26%
~
26%
25%
25%
25%
25%
31%
27%
21%
35%
31%
36%
25%
36%
36%
26%
41%
6
24%
24%
30%
~
~
30%
30%
~
37%
32%
24%
41%
37%
30%
43%
43%
30%
49%
7
26%
26%
32%
-
40%
26%
45%
-
53%
4-38
-------
Capital cost calculation: EPA Base Case v.4.10 uses multipliers similar to the LT (long term)
multipliers from the Energy Information Administration's NEMS model25 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.
Four cost classes are used in EPA Base Case v.4.10 with class 1 having the lowest cost
adjustment factor (1) and class 4 having the highest adjustment factor (ranging from 2.48 to 2.67
depending on the model region and whether the wind resource is onshore, offshore shallow or
offshore deep), as shown in Table 4-23. To the obtain the capital cost for a particular new wind
model plant, the base capital costs shown in Table 4-16 are multiplied by the cost adjustment
factor for the wind cost class applicable to the new plant.
Table 4-23 Capital Cost Adjustment Factors for New Wind Plants in Base Case v.4.10
Onshore
Offshore Deep Water
Offshore Shallow Water
Cost Class
1
1
1
1
2 3
1.2 1.5
1 .35
1 .35
4
2.51
2.5
2.5
Note:
1The Cost Adjustment Factor for Cost Class 4 Onshore is 2.5 for the majority of regions.
Exceptions are as follows:
ERCT has a Cost Adjustment Factor for Cost Class 4 Onshore of 2.62
AZNM, RMPA, and SNV have a Cost Adjustment Factor for Cost Class 4 Onshore of 2.66
NWPE, PNW, SPPN, SPPS, and MRO have a Cost Adjustment Factor for Cost Class 4
Onshore of 2.67
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 4-24 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 7, cost class 2 in the CA-N model region in run year 2020.
25Revising the Long Term Multipliers in NEMS: Quantifying the Incremental Transmission Costs
Due to Wind Power, Report to EIA from Princeton Energy Resources International, LLC. May
2007.
4-39
-------
Table 4-24 Example Calculations Of Wind Generation Potential, Reserve Margin
Contribution, And Capital Cost For Onshore Wind In CA-N At Wind Class 7, Cost Class 2
Required Data
Table 4-1 7 Potential wind capacity (C) = 352 MW
Appendix 4-1 Winter average generation (Gw) per available MW per hour = 559 kWh/MW
Appendix 4-1 Summer average generation (Gs) per available MW per hour = 422 kWh/MW
Hours in Winter (Hw) season (October - April) = 5,088 hours
Hours in Summer (Hs)season (May - September) = 3,672 hours
Table 4-20 Reserve Margin Contribution (RM) CA-N, Wind Class 7 = 24 percent
Table 4-1 6 Capital Cost (Cap202o) in vintage range for year 2020 = $1 ,91 2/kW
Table 4-23 Capital Cost Adjustment Factor (CAF0N,c2) for onshore cost class 2 = 1 .2
Table 4-1 5 Regional Factor (RF) 1.058
Calculations
Generation Potential = Cx Gw x Hw + CxGsxHs
= 352MWx559kWh/MWx5088hours +
352 MW x 422 kWh/MWx 3672 hours
= l,546GWh
Reserve Margin Contribution = RM x C
= 24%x352MW
Capital Cost = Cap 2020 x CAFON C2 x RF x C
= $l,912/MWxl.2xl.058x3527WF
= $854 million dollars
Solar Generation
Solar Resource Potential: No explicit constraint limit is placed on solar electric capacity in EPA
Base Case v.4.10. However, since solar thermal is only feasible in areas with sufficient direct
isolation, EPA Base Case v.4.10 includes the assumption that new solar thermal plants can only
be built west of the Mississippi River. Solar photovoltaic is not limited to specific parts of the
country.
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.4.10 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 AEO
2010, which provided separate winter and summer generation profiles for solar thermal and
photovoltaic in each eligible IPM region. As an illustrative example, Appendix 4-2 shows the solar
thermal and solar photovoltaic winter and summer generation profiles in model region AZNM.
Reserve margin contribution: The procedure described above for calculating the reserve margin
contributions for wind generation was also used for solar generation. Table 4-25 presents the
winter and summer average capacity factors (CFs) and reserve margin contributions by model
4-40
-------
region for new solar thermal and photovoltaic units in EPA Base Case v.4.10. The region-specific
summer and winter capacity factors included in this table are metrics that provide a shorthand
depiction of the hourly specific generation profiles for each region. They are based on AEO 2010
data. The assumptions in EPA Base Case v.4.10 for capacity factors and reserve margin
contributions for existing units are also based on AEO 2010.
Table 4-25 Solar Reserve Margin Contribution and Average Capacity Factor by Model
Region
Model
Region
AZNM
CA-N
CA-S
COMD
DSNY
ENTG
ERCT
FRCC
GWAY
LILC
MACE
MACS
MACW
MEGS
MRO
NENG
NWPE
NYC
PNW
RFCO
RFCP
RMPA
SNV
SOU
SPPN
SPPS
TVA
TVAK
UPNY
VACA
VAPW
WUMS
Solar Thermal
Winter
Average
Capacity
Factor
30%
32%
32%
26%
18%
23%
23%
30%
30%
22%
22%
Summer
Average
Capacity
Factor
42%
51%
51%
35%
34%
41%
41%
42%
42%
35%
35%
Reserve
Margin
Contribution
43%
53%
53%
36%
36%
18%
18%
43%
43%
37%
37%
Solar Photovoltaic
Winter
Average
Capacity
Factor
25%
23%
23%
19%
17%
21%
22%
23%
19%
17%
18%
18%
18%
17%
20%
19%
18%
17%
18%
17%
17%
25%
25%
21%
22%
22%
21%
17%
17%
21%
21%
19%
Summer
Average
Capacity
Factor
28%
28%
28%
23%
22%
23%
24%
23%
23%
22%
22%
22%
22%
23%
23%
22%
25%
22%
25%
23%
23%
28%
28%
23%
24%
24%
23%
23%
22%
23%
23%
23%
Reserve
Margin
Contribution
28%
28%
28%
24%
22%
23%
25%
23%
24%
22%
23%
23%
23%
23%
24%
23%
16%
22%
16%
23%
23%
28%
28%
23%
25%
25%
23%
23%
22%
23%
23%
24%
Geothermal Generation
Geothermal Resource Potential: Six model regions in EPA Base Case v.4.10 have geothermal
potential. The potential capacity in each of these regions is shown in Table 4-26. The values are
based on AEO 2010 data.
4-41
-------
Table 4-26 Regional Assumptions on Potential Geothermal Electric Capacity
IPM Model Region
AZNM
CA-N
CA-S
NWPE
PNW
RMPA
Grand Total
Capacity (MW)
2,216
662
124
4,555
1,336
70
8,963
Note:
This data is a summary of the geothermal data used in EPA Base
Case v.4.10
Cost Calculation: EPA Base Case v.4.10 does not contain a single capital cost, but multiple
geographically-dependent capital costs for geothermal generation. The assumptions for
geothermal were developed using AEO 2010 cost and performance estimates for 88 known sites.
Both dual flash and binary cycle technologies26 were represented. In EPA Base Case v.4.10 the
88 sites were collapsed into 26 different options based on geographic location and cost and
performance characteristics of geothermal sites in each of the six eligible IPM regions where
geothermal generation opportunities exist. Table 4-27 shows the potential geothermal capacity
and cost characteristics for applicable model regions.
Table 4-27 Potential Geothermal Capacity and Cost Characteristics by Model Region
IPM Region /ป!,,ซซ
( MW)
1,404
196
AZNM 316
294
6
575
CA-N 7
80
71
CA-S 48
5
Capital Cost
(2007$)
4,002
4,675
5,650
7,744
9,199
1,624
2,873
4,214
4,957
5,679
6,817
FO&M
(2007$/kW-yr)
185.1
206.8
201.1
192.2
218.8
185.1
185.1
206.2
185.1
185.1
185.1
26ln dual flash systems, high temperature water (above 400ฐF) is sprayed into a tank held at a
much lower pressure than the fluid. This causes some of the fluid to "flash," i.e., rapidly vaporize
to steam. The steam is used to drive a turbine, which, in turn, drives a generator. In the binary
cycle technology, moderate temperature water (less than 400ฐF) vaporizes a secondary, working
fluid which drives a turbine and generator. Due to its use of more plentiful, lower temperature
geothermal fluids, these systems tend to be most cost effective and are expected to be the most
prevalent future geothermal technology.
4-42
-------
IPM Region
NWPE
PNW
RMPA
Capacity
(MW)
9
24
103
1,165
3,001
137
67
12
28
9
268
36
420
612
70
Capital Cost
(2007$)
6,255
8,337
9,776
1 1 ,465
20,674
4,523
5,380
3,428
4,594
8,210
3,890
4,782
5,211
5,625
5,820
FO&M
(2007$/kW-yr)
164.1
164.1
168.6
179.6
181.7
185.1
183.0
218.8
185.1
185.1
151.5
151.5
156.3
190.3
185.1
Landfill Gas Electricity Generation
Landfill Gas Resource Potential: Estimates of potential electric capacity from landfill gas are
based on the AEO 2010 inventory. EPA Base Case v.4.10 represents 3 categories of potential
landfill gas units; "hi", "low", and "very low". The categories refer to the amount and rate of
methane production from the existing landfill site. Table 4-28 summarizes potential electric
capacity from landfill gas used in EPA Base Case v.4.10.
There are several things to note about Table 4-28. Since the potential electric capacity from new
landfill gas units is based on AEO 2009, the limits listed in Table 4-28 apply to the NEMS
(National Energy Modeling System) regions indicated in column 1. In EPA Base Case v.4.10 the
sum of the new landfill gas electric capacity in the corresponding IPM regions shown in column 2
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 4-28 represent an upper bound on the amount of new landfill capacity
that can be added in each of the indicated model regions 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 Table 4-16.
Table 4-28 Regional Assumptions on Potential Electric Capacity from New Landfill Gas
Units (MW)
NEMS
Region
ECAR
ERGOT
MAAC
MAIN
MAPP
NY
NE
FL
IPM Region
RFCO, MEGS, RFCP, TVAK
ERCT
MACE, MACS, MACW
WUMS, COMD, GWAY
MRO
DSNY, LILC, NYC, UPNY
NENG
FRCC
Class
LGHI
72
12
93
83
43
54
62
14
LGLo
30
26
22
92
22
27
6
26
LGLVo
539
316
311
495
150
142
51
158
4-43
-------
NEMS
Region
STV
SPP
NWP
RA
CNV
US
IPM Region
SOU, TVA, ENG, VACA, VAPW
SPPN, SPPS
PNW, NWPE
AZNM, SNV, RMPA
NA-N, CA-S
Class
LGHI
68
5
27
-
131
664
LGLo
22
-
58
-
250
581
LGLVo
447
185
185
91
749
3,819
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 105 nuclear units in EPA Base Case v.4.10 are
represented by separate model plants. As noted in Table 4-7 the 105 nuclear units include 104
currently operating units plus Watts Bar Nuclear Plant, Unit 2, which is scheduled to come online
in 2014. All are listed in Appendix 4-3. The population characteristics, plant location, and unit
configuration data in NEEDS, v.4.10 were obtained primarily from EIA Form 860 and AEO 2010.
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.4.10 uses capacity
factor assumptions to define the upper bound on generation from nuclear units. Nuclear capacity
factor assumptions in EPA Base Case v.4.10 are based on an Annual Energy Outlook projection
algorithm. The nuclear capacity factor projection algorithm is described below:
For each reactor, the capacity factor overtime 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:
o Before 25 years: Performance increases by 0.5 percentage point per year;
o 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:
o Before 30 years: Performance increases by 0.7 percentage points per year;
o 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 historical
capacity factors above 90 percent, the projected capacity factors range from 89 percent to 93
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.4.10 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 2010, which
were used to characterize the cost and performance of existing nuclear units in EPA Base Case
v.4.10 are shown in Appendix 4-03.
4-44
-------
EPA Base Case v.4.10 also uses the nuclear capacity uprates from AEO 2010. These are shown
in Table 4-29.
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.4.10 are shown in Table 4-13 above. The cost assumptions were
updated as part of the comparative analysis performed by EPA's power sector engineering staff.
That update is described above in section 4.4.1.
Table 4-29 Nuclear Upratings (MW) as Incorporated in EPA Base Case v.4.10 from AEO
2010
Name
Arkansas Nuclear One
Arkansas Nuclear One
Brunswick
Brunswick
Byron Generating Station
Byron Generating Station
Catawba
Catawba
Duane Arnold
Fermi
Grand Gulf
Harris
Joseph M Farley
Joseph M Farley
Limerick
Limerick
McGuire
McGuire
Oconee
Oconee
Oconee
Peach Bottom
Peach Bottom
Perry
PSEG Salem Generation
PSEG Salem Generation
Quad Cities Generation
Quad Cities Generation
Sequoyah
Sequoyah
South Texas Project
South Texas Project
Surry
Surry
VC Summer
Waterford 3
Wolf Creek Generation
Watts Bar Nuclear Plant
Plant ID
8055
8055
6014
6014
6023
6023
6036
6036
1060
1729
6072
6015
6001
6001
6105
6105
6038
6038
3265
3265
3265
3166
3166
6020
2410
2410
880
880
6152
6152
6251
6251
3806
3806
6127
4270
210
7722
Unit ID
1
2
1
2
1
2
1
2
1
2
1
1
1
2
1
2
1
2
1
2
3
2
3
1
1
2
1
2
1
2
1
2
1
2
1
3
1
2
Year
2016
2016
2014
2014
2019
2019
2016
2016
2015
2016
2015
2017
2017
2017
2018
2018
2014
2014
2017
2017
2017
2014
2014
2016
2015
2015
2013
2013
2013
2013
2013
2013
2015
2015
2015
2016
2017
2014
Change in MWs
50.0
59.0
56.3
56.2
116.4
11.4
67.7
67.7
34.8
67.0
76.7
54.0
51.0
52.0
113.4
113.4
110.0
110.0
51.0
51.0
51.0
66.7
66.7
74.0
70.4
67.8
52.0
52.0
69.0
68.0
76.8
76.8
47.9
47.9
58.0
69.1
70.0
1,180
4-45
-------
-------
Appendix 4-1 Representative Wind Generation Profiles in EPA Base Case
v.4.10
Illustrative Hourly Wind Generation Profile (kWh of Generation per MW of Electricity)
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
Wind Class
3
268
268
269
263
253
243
236
233
230
227
225
226
226
228
227
228
231
240
250
259
267
271
271
268
246
4
361
359
355
345
326
310
297
291
282
276
276
280
283
287
288
289
289
296
309
325
339
350
357
360
314
5
492
488
483
464
430
396
374
372
371
372
374
376
376
381
385
390
394
405
423
444
464
479
488
491
421
6
504
503
498
483
454
424
402
395
391
389
391
394
396
400
402
404
406
415
433
453
473
488
498
502
437
7
635
633
629
613
580
544
518
514
511
510
510
508
505
507
511
517
524
538
558
580
601
618
629
633
559
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
Wind Class
3
380
374
366
350
326
299
282
292
320
348
368
381
388
393
393
390
384
377
375
374
378
382
384
382
362
4
410
402
391
368
334
295
261
256
270
296
320
340
354
365
372
371
358
340
331
335
354
381
401
409
346
5
456
444
422
387
337
286
250
248
269
298
320
331
334
341
350
361
369
371
378
386
402
424
444
455
361
6
591
583
566
535
489
433
389
384
408
442
466
480
484
489
496
501
501
496
496
500
518
546
572
586
498
7
555
546
523
479
413
344
295
293
316
348
368
373
370
372
383
398
414
421
431
440
464
498
529
547
422
Notes:
Based on
This is an
Onshore Wind in Model Region CA-N.
example of the wind data used in EPA Base Case v.4.10
Appendix 4-1.1
-------
-------
Appendix 4-2 Representative Solar Generation Profiles in EPA Base v.4.10
Illustrative Hourly Solar Generation Profile (kWh of Generation per MW of Electricity)
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
3
3
3
3
3
181
181
601
601
601
601
601
601
601
601
601
601
601
181
181
181
181
181
181
336
Solar
Photovoltaic
0
0
0
0
0
29
29
660
660
660
660
660
660
660
660
660
660
660
29
29
29
29
29
29
312
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
9
9
9
9
9
284
284
720
720
720
720
720
720
720
720
720
720
720
284
284
284
284
284
284
426
Solar
Photovoltaic
0
0
0
0
0
13
13
610
610
610
610
610
610
610
610
610
610
610
13
13
13
13
13
13
284
Notes:
Based on
This is an
model region AZNM.
example of the solar data used in EPA Base Case v.4.10
Appendix 4-2.1
-------
-------
Appendix 4-3 Characteristics of Existing Nuclear Units
Region
AZNM
CA-N
CA-S
COMD
DSNY
ENTG
State
Arizona
California
California
Illinois
New York
Arkansas
Louisiana
Mississippi
Plant Name
Palo Verde
Palo Verde
Palo Verde
Diablo Canyon
Diablo Canyon
San Onofre
San Onofre
Braidwood Generation Station
Braidwood Generation Station
Byron Generating Station
Byron Generating Station
LaSalle Generating Station
LaSalle Generating Station
Dresden Generating Station
Dresden Generating Station
Quad Cities Generating Station
Quad Cities Generating Station
Indian Point 2
Indian Point 3
Arkansas Nuclear One
Arkansas Nuclear One
Waterford 3
River Bend
Grand Gulf
ORIS
_ . .... On-Line Capacit Heat Rate
uoae_umt Yegr y(MW) (Btu/kWh)
6008_1 1986 1,311 10,427
6008_2 1986 1,352 10,427
6008_3 1988 1,283 10,427
6099_1 1985 1,122 10,427
6099_2 1986 1,118 10,427
360_2 1983 1,070 10,427
360_3 1984 1,080 10,427
6022_1 1988 1,178 10,427
6022_2 1988 1,152 10,427
6023_1 1985 1,164 10,427
6023_2 1987 1,136 10,427
6026_1 1984 1,118 10,427
6026_2 1984 1,120 10,427
869_2 1970 867 10,427
869_3 1971 867 10,427
880_1 1972 867 10,427
880_2 1972 867 10,427
2497_2 1973 1,020 10,427
8907_3 1976 1,025 10,427
8055_1 1974 836 10,427
8055_2 1980 988 10,427
4270_3 1985 1,152 10,427
6462_1 1986 967 10,427
6072_1 1985 1,266 10,427
FOM VOM
(2007$ (2007
/kW-yr) mills/kWh)
117.2 0.50
117.2 0.55
117.2 0.52
132.1 0.71
132.1 0.70
208.6 1.00
208.6 1.05
129.7 0.57
129.7 0.59
126.4 0.57
126.4 0.56
157.9 0.75
157.9 0.76
203.6 0.89
203.6 0.95
177.3 0.83
177.3 0.83
227.3 1.40
199.2 0.96
152.6 0.63
152.6 0.65
162.7 0.61
193.7 1.03
134.8 0.54
Appendix 4-3.1
-------
Region
ERCT
FRCC
GWAY
MACE
MACS
MACW
MECS
State
Texas
Florida
Illinois
Missouri
New Jersey
Pennsylvania
Maryland
Pennsylvania
Michigan
Plant Name
Comanche Peak
Comanche Peak
South Texas Project
South Texas Project
St Lucie
St Lucie
Turkey Point
Turkey Point
Crystal River
Clinton Power Station
Callaway
PSEG Salem Generating Station
PSEG Salem Generating Station
Oyster Creek
PSEG Hope Creek Generating Station
Limerick
Limerick
Calvert Cliffs Nuclear Power Plant
Calvert Cliffs Nuclear Power Plant
Peach Bottom
Peach Bottom
PPL Susquehanna
PPL Susquehanna
Three Mile Island
Fermi
Palisades
ORIS
P .... On-Line Capacit Heat Rate
oode_umt Yegr y (MW) (Btu/kWh)
6145_1 1990 1,202 10,240
6145_2 1993 1,202 10,317
6251_1 1988 1,280 10,427
6251_2 1989 1,280 10,427
6045_1 1976 839 10,427
6045_2 1983 714 10,427
621_3 1972 693 10,427
621_4 1973 693 10,427
628_3 1977 851 10,427
204_1 1987 1,043 10,427
6153_1 1984 1,190 10,427
241 0_1 1977 1,174 10,427
241 0_2 1981 1,130 10,427
2388_1 1969 619 10,427
6118_1 1986 1,196 10,427
6105_1 1986 1,134 10,427
6105_2 1990 1,134 10,427
601 1_1 1975 885 10,427
601 1_2 1977 874 10,427
3166_2 1974 1,112 10,427
3166_3 1974 1,112 10,427
6103_1 1983 1,283 10,427
6103_2 1985 1,288 10,427
801 1_1 1974 786 10,427
1729_2 1988 1,122 10,427
1715_1 1972 778 10,427
FOM VOM
(2007$ (2007
/kW-yr) mills/kWh)
120.0 0.61
120.0 0.63
121.6 0.59
121.6 0.58
142.3 0.64
142.3 0.71
146.8 0.67
146.8 0.66
181.5 0.81
200.1 0.97
139.7 0.74
159.9 0.77
159.9 0.79
255.1 1.17
147.5 0.84
127.6 0.55
127.6 0.54
155.2 0.75
155.2 0.72
172.7 0.81
172.7 0.80
172.1 0.89
172.1 0.88
170.9 0.82
155.9 0.80
197.2 1.14
Appendix 4-3.2
-------
Region
MRO
NENG
PNW
RFCO
RFCP
SOU
SPPN
State
Iowa
Minnesota
Nebraska
Connecticut
Massachusetts
New
Hampshire
Vermont
Washington
Michigan
Ohio
Pennsylvania
Alabama
Georgia
Kansas
Plant Name
Duane Arnold
Monticello
Prairie Island
Prairie Island
Fort Calhoun
Cooper
Millstone
Millstone
Pilgrim Nuclear Power Station
Seabrook
Vermont Yankee
Columbia Generating Station
Donald C Cook
Donald C Cook
Perry
Davis Besse
Beaver Valley
Beaver Valley
Joseph M Farley
Joseph M Farley
Edwin 1 Hatch
Edwin 1 Hatch
Vogtle
Vogtle
Wolf Creek Generating Station
ORIS
P .... On-Line Capacit Heat Rate
oode_umt Yegr y (MW) (Btu/kWh)
1060_1 1975 581 10,427
1922_1 1971 646 10,427
1925_1 1974 551 10,427
1925_2 1974 545 10,427
2289_1 1973 478 10,427
8036_1 1974 767 10,427
566_2 1975 882 10,427
566_3 1986 1,236 10,427
1590_1 1972 685 10,427
6115_1 1990 1,244 10,427
3751_1 1972 620 10,427
371_2 1984 1,131 10,427
6000_1 1975 1,029 10,942
6000_2 1978 1,077 10,848
6020_1 1987 1,231 11,000
6149_1 1977 887 11,000
6040_1 1976 887 10,962
6040_2 1987 887 10,946
6001_1 1977 851 11,794
6001_2 1981 860 11,650
6051_1 1975 876 10,427
6051_2 1979 883 10,427
649_1 1987 1,172 10,427
649_2 1989 1,169 10,427
210_1 1985 1,166 10,427
FOM VOM
(2007$ (2007
/kW-yr) mills/kWh)
208.4 1.11
187.8 1.02
162.3 0.82
162.3 0.83
219.4 1.19
223.6 1.29
205.4 no
192.2 1.02
241.6 1.06
1787 0.94
203.8 1.06
152.1 0.73
174.9 1.05
174.9 1.08
160.1 0.80
158.1 0.90
190.3 0.96
190.3 0.90
138.5 0.71
138.5 0.68
146.9 0.77
146.9 0.78
145.6 0.66
145.6 0.65
137.7 0.71
Appendix 4-3.3
-------
Region
TVA
UPNY
VACA
VAPW
State
Alabama
Tennessee
New York
North Carolina
South Carolina
Virginia
Plant Name
Browns Ferry
Browns Ferry
Browns Ferry
Sequoyah
Sequoyah
Watts Bar Nuclear Plant
Watts Bar Nuclear Plant
Nine Mile Point Nuclear Station
Nine Mile Point Nuclear Station
James A Fitzpatrick
R. E. Ginna Nuclear Power Plant
Brunswick
Brunswick
Harris
McGuire
McGuire
H B Robinson
Oconee
Oconee
Oconee
Catawba
Catawba
V C Summer
Surry
Surry
North Anna
North Anna
ORIS
P .... On-Line Capacit Heat Rate
oode_umt Yegr y (MW) (Btu/kWh)
46_1 1974 1,225 10,550
46_2 1975 1,286 10,215
46_3 1977 1,337 10,215
6152_1 1981 1,150 10,123
6152_2 1982 1,127 10,202
7722_1 1996 1,121 10,266
7722_2 2014 1,180 10,266
2589_1 1969 621 10,427
2589_2 1969 1,311 10,427
6110_1 1976 852 10,427
6122_1 1970 498 10,427
6014_1 1977 938 10,318
601 4_2 1975 937 10,397
601 5_1 1987 900 10,982
6038_1 1981 1,100 10,427
6038_2 1984 1,100 10,427
3251_2 1971 710 10,697
3265_1 1973 846 10,427
3265_2 1974 846 10,427
3265_3 1974 846 10,427
6036_1 1985 1,129 10,427
6036_2 1986 1,129 10,427
6127_1 1984 966 10,427
3806_1 1972 799 10,427
3806_2 1973 799 10,427
6168_1 1978 940 10,427
6168_2 1980 925 10,427
FOM VOM
(2007$ (2007
/kW-yr) mills/kWh)
99.9 0.40
99.9 0.42
99.9 0.40
115.4 0.48
115.4 0.45
139.1 0.64
92.4 0.49
193.5 0.98
188.9 0.97
203.0 0.90
205.8 0.92
110.6 0.46
110.6 0.46
131.3 0.60
119.6 0.48
119.6 0.50
119.8 0.59
139.6 0.73
139.6 0.65
139.6 0.72
134.0 0.64
134.0 0.64
143.5 0.80
120.7 0.58
120.7 0.57
98.7 0.47
98.7 0.50
Appendix 4-3.4
-------
Region
WUMS
State
Wisconsin
Plant Name
Point Beach
Point Beach
Kewaunee
ORIS
P .... On-Line Capacit Heat Rate
oode_umt Yegr y (MW) (Btu/kWh)
4046_1 1970 599 10,427
4046_2 1972 601 10,427
8024_1 1974 556 10,427
FOM VOM
(2007$ (2007
/kW-yr) mills/kWh)
202.3 0.97
202.3 1.00
151.5 0.85
Appendix 4-3.5
-------
-------
5 Emission Control Technologies
EPA Base Case v.4.10 includes a major update of emission control technology assumptions. For
this base case EPA contracted with engineering firm Sargent and Lundy to perform a complete
bottom-up engineering reassessment of the cost and performance assumptions for sulfur dioxide
(SO2) and nitrogen oxides (NOX) emission controls. In addition to the work by Sargent and Lundy,
Base Case v.4.10 includes two Activated Carbon Injections (ACI) options (Standard and Modified)
for mercury (Hg) control27. Capture and storage options for carbon dioxide (CO2) have also been
added in the new base case.
These emission control options are listed in Table 5-1. They are available in EPA Base Case
v.4.10 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.4.10 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.4.10
SO2 Control
Technology Options
Limestone Forced
Oxidation (LSFO)
Scrubber
Lime Spray Dryer
(LSD) Scrubber
NOX Control
Technology Options
Selective Catalytic
Reduction (SCR)
System
Selective Non-
Catalytic Reduction
(SNCR) System
Combustion Controls
Hg Control
Technology Options
Standard Activated
Carbon Injection (SPAC-
ACI) System
Modified Activated
Carbon Injection
(MPAC-ACI) System
SO2 and NOX Control
Technology Removal
Cobenefits
CO2 Control
Technology Options
CO2 Capture and
Sequestration
5.1 Sulfur Dioxide Control Technologies
Two commercially available Flue Gas Desulfurization (FGD) technology options for removing the
SO2 produced by coal-fired power plants are offered in EPA Base Case v.4.10: 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
3lb 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.4.10 when a unit
retrofits with an LSD SO2 scrubber, it loses the option of burning BG, BH, and LG coals due to
their high sulfur content.
In EPA Base Case v.4.10 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
27The mercury emission controls options and assumptions in EPA Base Case v.4.10 do not reflect
mercury control updates that are currently underway at EPA in support of the Utility MACT
initiative and do not make use of data collected under EPA's 2010 Information Collection Request
(ICR).
5-1
-------
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. Scrubber efficiencies
for existing units were derived from data reported in EIA Form 767. In transferring this data for
use in EPA Base Case v.4.10 the following changes were made. The maximum removal
efficiency was set at 98% for wet scrubbers and 93% for dry scrubber units. Existing units
reporting efficiencies above these levels in Form 767 were assigned the maximum removal
efficiency in NEEDS v.4.10 indicated in the previous sentence.
As shown in Table 5-2, existing units that are selected to be retrofitted by the model with
scrubbers are given the maximum removal efficiencies of 98% for LSFO and 93% for LSD. 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
Performance
Assumptions
Percent Removal
Capacity Penalty
Heat Rate Penalty
Cost (2007$)
Applicability
Sulfur Content
Applicability
Applicable Coal Types
Limestone Forced
Oxidation (LSFO)
98%
with a floor of 0.06 Ibs/MMBtu
Calculated based on
characteristics of the unit:
See Table 5-4 for examples
Units > 25 MW
BA, BB, BD, BE, BG, BH, SA,
SB, SD, LD, LE, and LG
Lime Spray Dryer (LSD)
93%
with a floor of 0.065 Ibs/MMBtu
Calculated based on
characteristics of the unit:
See Table 5-4 for examples
Units > 25 MW
Coals < 3 Ibs SGVMMBtu
BA, BB, BD, BE, SA, SB, SD,
LD, and LE
Potential (new) coal-fired units built by the model are also assumed to be constructed with a
scrubber achieving a removal efficiency of 98% for LSFO and 93% for LSD. In EPA Base Case
v.4.10 the costs of potential new coal units include the cost of scrubbers.
5.1.1 Methodology for Obtaining SO2 Controls Costs
The Sargent and Lundy update of SO2 and NOX control costs is notable on several counts. First, it
brought costs up to levels seen in the marketplace in 2009. Incorporating these costs into EPA's
base case carries an implicit assumption, not universally accepted, that the run up in costs seen
over the preceding 5 years and largely attributed to international competition, is permanent and
will not settle back to pre-2009 levels. Second, a revised methodology, based on Sargent and
Lundy's expert experience, was used to build up the capital, fixed and variable operating and
maintenance components of cost. That methodology, which employed an engineering build up of
each component of cost, is described here and in the following sections. Detailed example cost
calculation spreadsheets for both SO2 and NOX controls are included in Appendices 5-1 and 5-2
respectively. The Sargent and Lundy reports in which these spreadsheets appeared can be
downloaded via links to the Appendices 5-1 A, 5-1B, 5-2A, and 5-2B links found at
www.epa.gov/airmarkets/progsregs/epaipm/BaseCasev410.html.
Capital Costs: In building up capital costs three separate cost modules were included for LSD and
four for LSFO: absorber island, reagent preparation, waste handling (LSFO only), and everything
else (also called "balance of plant") with the latter constituting the largest cost module, consisting
of fans, new wet chimney, piping, ductwork, minor waste water treatment, and other costs
required for treatment. For each of the four modules the cost of foundations, buildings, electrical
equipment, installation, minor, physical and chemical wastewater treatment, and average retrofit
difficulty were taken into account.
5-2
-------
The governing cost variables for each module are indicated in Table 5-3. The major variables
affecting capital cost are unit size and the SO2 content of the fuel with the latter having the
greatest impact on the reagent and waste handling facilities. In addition, heat rate affects the
amount of flue gas produced and consequently the size of each of the modules. The quantity of
flue gas is also a function of coal rank since different coals have different typical heating values.
Table 5-3 Capital Cost Modules and Their Governing Variables for SO2 and NOX Emission
Controls
Module
Retrofit
Difficulty
(1 =
average)
Coal Rank
Factor
(Bi, = 1,
PRB = 1.05,
Lignite = 1.07)
Heat Rate
(Btu/kWh)
SO2 Rate
(Ib/MMBtu)
NOX Rate
(Ib/MMBtu)5
Unit
Size
(MW)
SO2 Emission Controls -Wet FGD and SDA FGD
Absorber
Island
Reagent
Preparation
Waste
Handling
Balance of
Plant1
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
NOX Emission Controls - SCR and SNCR
SCR/SNCR
Island2
Reagent
Preparation3
Air Heater
Modification4
Balance of
Plant5 - SCR
Balance of
Plant1 -
SNCR
X
X
X
X
X
X
X
X
X
X
X3
X
X
X
X
X
X
Notes:
1"Balance of plant" costs include such cost items as ID and booster fans, new wet chimneys,
piping, ductwork, minor waste water treatment, auxiliary power modifications, and other electrical
and site upgrades.
2The SCR island module includes the cost of inlet ductwork, reactor, and bypass. The SNCR
island module includes cost of injectors, blowers, distributed control system (DCS), and reagent
system.
3Only applies to SCR.
4On generating units that burn bituminous coal whose SO2 and content exceeds 3 Ibs/MMBtu, air
heater modifications used to control SO3 are needed in conjunction with the operation of SCR and
SNCR.
5For SCR, the NOX rate is frequently expressed through the calculated NOX removal efficiency.
5-3
-------
Once the key variables that figure in the cost of the four modules are identified, they are used to
derive costs for each base module in equations developed by Sargent and Lundy based on their
experience with multiple engineering projects. The base module costs are summed to obtain total
bare module costs. This total is increased by 30% to account for additional engineering and
construction fees. The resulting value is the capital, engineering, and construction cost (CECC)
subtotal. To obtain the total project cost (TPC), the CECC subtotal is increased by 5% to account
for owner's home office costs, i.e., owner's engineering, management, and procurement costs.
The resulting sum is then increased by another 10% to build in an Allowance for Funds used
During Construction (AFUDC) over the 3-year engineering and construction cycle. The resulting
value, expressed in $/kW, is the capital cost factor that is used in EPA Base Case v.4.10.
Variable Operating and Maintenance Costs (VOIVD: These are the costs incurred in running the
emission control device. They are proportional to the electrical energy produced and are
expressed in units of $ per MWh. For FGD, Sargent and Lundy identified four components of
VOM: (a) costs for reagent usage, (b) costs for waste generation, (c) make up water costs, and
(d) cost of additional power required to run the control (often called the "parasitic load"). For a
given coal rank and a pre-specified SO2 removal efficiency, each of these components of VOM
cost is a function of the generating unit's heat rate (Btu/kWh) and the sulfur content (Ib
SO2/MMBtu) of the coal (also referred to as the SO2 feed rate). For purposes of modeling, the
total VOM includes the first three of these component costs. The last component - cost of
additional power- is factored into IPM, not in the VOM value, but through a capacity and heat rate
penalty as described in the next paragraph. Due to the differences in the removal processes, the
per MWh cost for waste handling, makeup water, and auxiliary power tend to be higher for LSFO
while reagent usage cost and total VOM (excluding parasitic load) are higher for LSD.
Capacity and Heat Rate Penalty: The amount of electrical power required to operate the FGD
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 the FGD 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 rate28. 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). Unlike previous base cases, which assumed a generic heat
rate and capacity penalties for all installations, in EPA Base Case v.4.10 specific LSFO and LSD
heat rate and capacity penalties are calculated for each installation based on equations developed
by Sargent and Lundy that take into account the rank of coal burned, its SO2 rate, and the heat
rate of the model plant.
Fixed Operating and Maintenance Costs (FOM): These are the annual costs of maintaining a unit.
They represent expenses incurred regardless of the extent to which the emission control system
is run. They are expressed in units of $ per kW per year. In calculating FOM Sargent and Lundy
took into account labor and materials costs associated with operations, maintenance, and
administrative functions. The following assumptions were made:
28 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 -1
( Capacity Penalty ^
I 100 J
xlOO
5-4
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FOM for operations is based on the number of operators needed which is a function of the
size (i.e., MW capacity) of the generating unit and the type of FGD control. For LSFO 12
additional operators were assumed to be required for a 500 MW or smaller installation and 16
for a unit larger than 500 MW. For LSD 8 additional operators were assumed to be needed.
FOM for maintenance is a direct function of the FGD capital cost
FOM for administration is a function of the FOM for operations and maintenance.
Table 5-4 presents the capital, VOM, and FOM costs as well as the capacity and heat rate penalty
for the two SO2 emission control technologies (LSFO and LSD) included in EPA Base Case v.4.10
for an illustrative set of generating units with a representative range of capacities and heat rates.
5-5
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Table 5-4 Illustrative Scrubber Costs (2007$) for Representative Sizes and Heat Rates under the Assumptions in EPA Base Case v.4.10
Scrubber Type
LSFO
Minimum Cutoff:
>25MW
Maximum Cutoff:
None
Assuming 3
Ib/MMBtu SO2
Content
Bituminous Coal
LSD
Minimum Cutoff:
>25MW
Maximum Cutoff:
None
Assuming 2
Ib/MMBtu SO2
Content
Bituminous Coal
Heat Rate
(Btu/kWh)
9,000
10,000
1 1 ,000
9,000
10,000
1 1 ,000
Capacity
Penalty
-1.5
-1.67
-1.84
-1.18
-1.32
-1.45
Heat
Rate
Penalty
1.53
1.7
1.87
1.2
1.33
1.47
Variable
O&M
(mills/kWh)
1.66
1.84
2.03
2.13
2.36
2.60
Capacity (MW)
100
Capital
Cost
($/kW)
747
783
817
641
670
698
Fixed
O&M
($/kW-yr)
22.5
22.8
23.2
16.4
16.7
17.0
300
Capital Fixed
Cost O&M
($/kW) ($/kW-yr)
547 10.5
573 10.8
598 1 1 .0
469 8.1
491 8.3
511 8.5
500
Capital Fixed
Cost O&M
($/kW) ($/kW-yr)
473 7.8
496 8.0
517 8.2
406 6.1
424 6.3
442 6.5
700
C^tal Fixed O&M
($/kw> ($/kW-y)
430 7.2
451 7.4
470 7.6
385 5.3
403 5.5
420 5.7
1000
Capital Fixed
Cost O&M
($/kW) ($/kW-yr)
388 5.9
407 6.1
425 6.3
385 4.9
403 5.1
420 5.2
5-6
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5.2 Nitrogen Oxides Control Technology
The EPA Base Case v.4.10 includes two categories of NOX reduction technologies: combustion
and post-combustion controls. Combustion controls reduce NOX emissions during the combustion
process by regulating flame characteristics such as temperature and fuel-air mixing. Post-
combustion controls operate downstream of the combustion process and remove NOX emissions
from the flue gas. All the specific combustion and post-combustion technologies included in EPA
Base Case v.4.10 are commercially available and currently in use in numerous power plants.
5.2.1 Combustion Controls
The EPA Base Case v.4.10 representation of combustion controls uses equations that are tailored
to the boiler type, coal type, and combustion controls already in place and allow appropriate
additional combustion controls to be exogenously applied to generating units based on the NOX
emission limits they face. Characterizations of the emission reductions provided by combustion
controls are presented in Table 3-1.3 in Appendix 3-1. The EPA Base Case v.4.10 cost
assumptions for NOX Combustion Controls are summarized in Table 5-5. Table 5-6 provides a
mapping of existing coal unit configurations and incremental combustion controls applied in EPA
Base Case v.4.10 to achieve state-of-the-art combustion control configuration.
Table 5-5 Cost (2007$) 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
Capital O&M Variable O&M
($/kW) ($/kW- (mills/kWh)
yr)
45 0.3 0.07
61 0.4 0.09
24 0.2 0.00
33 0.2 0.03
38 0.3 0.03
29 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 = ($ forX MW Unit) = ($ for 300 MW Unit) x (300/X)0359
LNC1, LNC2 and LNC3 = ($ for XMW Unit) = ($ for 300 MW Unit) x (300/X)0359
Vertically-Fired = ($ for XMW Unit) = ($ for 300 MW Unit) x (300/X)0553
where
($ for 300 MW Unit) is the value obtained using the factors shown in the above table and
X is the
capacity (in MW) of the unit taking on combustion controls.
5-7
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Table 5-6 Incremental Combustion NOX Controls in EPA Base Case v.4.10
Boiler Type
Cell
Cyclone
Stoker/SPR
Tangential
Vertical
Wall
Existing NOX
Combustion Control
LNB
NCR
-
-
-
LA
LNB
LNB + OFA
LNC1
LNC2
OFA
ROFA
-
-
LA
LNB
LNF
OFA
Incremental Combustional Control
OFA
LNB AND OFA
OFA
OFA
LNC3
LNC3
CONVERSION
CONVERSION
CONVERSION
CONVERSION
LNC1
LNB
FROM LNC1 TO LNC3
FROM LNC1 TO LNC3
FROM LNC1 TO LNC3
FROM LNC2 TO LNC3
NOX Combustion Control - Vertically Fired Units
LNB AND OFA
LNB AND OFA
OFA
OFA
LNB
5.2.2 Post-combustion Controls
The EPA Base Case v.4.10 includes two post-combustion retrofit control technologies for existing
coal units: Selective Catalytic Reduction (SCR) and Selective Non-Catalytic Reduction (SNCR). In
EPA Base Case v.4.10 oil/gas steam units are eligible for SCR only. NOX reduction in an 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 ammonia
or urea, 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 to the presence of a catalyst, SCR can
achieve greater NOX reductions than SNCR. However, SCR costs are higher.
Table 5-7 summarizes the performance and applicability assumptions in EPA Base Case v.4.10
for each NOX post-combustion control technology and provides a cross reference to information on
cost assumptions.
Table 5-7 Summary of Retrofit NOX Emission Control Performance Assumptions
Control
Performance
Assumptions
Unit Type
Percent Removal
Size Applicability
Costs (2007$)
Selective Catalytic Reduction
(SCR)
Coal
90% down to 0.06
Ib/MMBtu
Units > 25 MW
See Table 5-8
Oil/Gas
80%
Units > 25 MW
See Table 5-9
Selective Non-Catalytic
Reduction
(SNCR)
Coal
Pulverized Coal: 35%
Fluidized Bed: 50%
Units > 25 MW
See Table 5-8
5-8
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Potential (new) coal-fired, combined cycle, and IGCC units are modeled to be constructed with
SCR systems and designed to have emission rates ranging between 0.01 and 0.06 Ib
NOx/MMBtu. EPA Base Case v.4.10 cost assumptions for these units include the cost of SCR
5.2.3 Methodology for Obtaining SCR Costs for Coal Units
As with the update of SO2 control costs, Sargent and Lundy employed an engineering build-up of
the capital, fixed and variable operating and maintenance components of cost to update post-
combustion NOX control costs. This section describes the approach used for SCR. The next
section treats SNCR. Detailed example cost calculation spreadsheets for both technologies can
be found in Appendix 5-2.
For cost calculation purposes the Sargent and Lundy methodology calculates plant specific NOX
removal efficiencies, i.e., the percent difference between the uncontrolled NOX rate29 for a model
plant and the cost calculation floor NOX rate corresponding to the predominant coal rank used at
the plant ( 0.07 Ib/MMBtu for bituminous and 0.05 Ib/MMBtu forsubbitumionus and lignite coals).
For example, a plant that burns subbitumionus coal with an uncontrolled NOX rate of 0.1667
Ib/MMBtu, and a cost calculation floor NOX rate of 0.05 Ib/MMBtu would have a removal efficiency
of 70%, i.e., (0.1667-0.05)/0.1667 = 0.1167/0.1667 = .70. The NOX removal efficiency so
obtained figures in the capital, VOM, and FOM components of SCR cost.
Capital Costs: In building up SCR capital costs, four separate cost modules were included: SCR
island (e.g., inlet ductwork, reactor, and bypass), reagent preparation, air pre-heater modification,
and balance of plan (e.g., ID or booster fans, piping, and auxiliary power modification). Air pre-
heater modification cost only applies for plants that burn bituminous coal whose SO2 content is 3
Ibs/MMBtu or greater, where SO3 control is necessary. Otherwise, there is no air pre-heat cost.
For each of the four modules the cost of foundations, buildings, electrical equipment, installation,
and average retrofit difficulty were taken into account.
The governing cost variables for each module are indicated in Table 5-3. All four capital cost
modules, except reagent preparation, are functions of retrofit difficulty, coal rank, heat rate, and
unit size. NOX rate (expressed via the NOX removal efficiency) affects the SCR and reagent
preparation cost modules. Not shown in Table 5-3, heat input (in Btu/hr) also impacts reagent
preparation costs. As noted above, the SO2 rate becomes a factor in SCR cost for plants that
combust bituminous coal with 3 Ibs SO2/MMBtu or greater, where air pre-heater modifications are
needed for SO3 control.
As with FGD capital costs, the base module costs for SCR are summed to obtain total bare
module costs. This total is increased by 30% to account for additional engineering and
construction fees. The resulting value is the capital, engineering, and construction cost (CECC)
subtotal. To obtain the total project cost (TPC) the CECC subtotal is increased by 5% to account
for owner's home office costs, i.e., owner's engineering, management, and procurement costs.
Whereas the resulting sum is then increased by another 10% for FGD, for SCR it is increased by
6% to factor in an Allowance for Funds used During Construction (AFUDC) over the 2-year
engineering and construction cycle (in contrast to the 3-year cycle assumed for FGD). The
resulting value, expressed in $/MW, is the capital cost factor that is used in EPA Base Case
v.4.10.
Variable Operating and Maintenance Costs (VOM): For SCR Sargent and Lundy identified four
components of VOM: (a) costs for the urea reagent, (b) costs of catalyst replacement and
disposal, (c) cost of required steam, and (d) cost of additional power required to run the control
29 More precisely, the uncontrolled NOX rate for a model plant in EPA Base Case v.4.10 is the
capacity weighted average of the Mode 1 NOX rates of the generating units comprising the model
plant. The meaning of "Mode 1 NOX rate" is discussed in section 3.9.2 and Appendix 3-1 ("NOX
Rate Development in EPA Base Case v.4.10).
5-9
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(i.e., the "parasitic load"). As was the case for FGD, the last component - cost of additional power
- is factored into IPM, not in the VOM value, but through a capacity and heat rate penalty as
described earlier. Of the first three of these component costs, reagent cost and catalyst
replacement are predominant while steam cost is much lower in magnitude. NOX rates and heat
rates are key determinates of reagent and steam costs, while NOX rate (via removal efficiency),
capacity factor, and coal rank are key drivers of catalyst replacement costs.
Capacity and Heat Rate Penalty:
Unlike previous base cases, which assumed a generic heat rate and capacity penalties for all
installations, in EPA Base Case v.4.10 specific SCR heat rate and capacity penalties are
calculated for each installation based on equations developed by Sargent and Lundy that take into
account the rank of coal burned, its SO2 rate, and the heat rate of the model plant.
Fixed Operating and Maintenance Costs (FOM): For SCR the following assumptions were made:
FOM for operations is based on the assumption that one additional operator working half-time
is required.
FOM for maintenance is assumed to $193,585 (in 2007$) for generating units less than 500
MWand $290,377 (in 2007$) for generating units 500 MW or greater
There was assumed to be no FOM for administration for SCR.
Table 5-8 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,
heat rates, and NOX removal efficiencies. The illustrations include and identify plants that do and
do not burn bituminous coal with 3 Ibs SO2/MMBtu or greater.
5-10
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Table 5-8 Illustrative Post Combustion NOX Controls for Coal Plants Costs (2007$) for Representative Sizes and Heat Rates under the
Assu Assumptions in EPA Base Case v.4.10
Control Type
SCR
Minimum Cutoff:
>25MW
Maximum Cutoff: None
Assuming Bituminous Coal
NOX rate: 0.5 Ib/MMBtu
SO2 rate: 2.0 Ib/MMBtu
SNCR - Non-FBC
Minimum Cutoff:
>25MW
Maximum Cutoff: None
Assuming Bituminous Coal
NOX rate: 0.5 Ib/MMBtu
SO2 rate: 2.0 Ib/MMBtu
SNCR - Fluidized Bed
Minimum Cutoff:
>25MW
Maximum Cutoff: None
Assuming Bituminous Coal
NOX rate: 0.5 Ib/MMBtu
SO2 rate: 2.0 Ib/MMBtu
Heat Rate
(Btu/kWh)
9,000
10,000
1 1 ,000
9,000
10,000
1 1 ,000
9,000
10,000
1 1 ,000
Capacity
Penalty
-0.54
-0.56
-0.58
-0.05
-0.05
Heat
Rate
Penalty
0.54
0.56
0.59
0.05
0.05
Variable
O&M
(mills/kWh)
1.15
1.24
1.33
0.88
0.98
1.08
0.88
0.98
1.08
Capacity (MW)
100
Capital '*e
/*/i IAI\ ($/kW-
(VKVV) *
yr)
221 2.5
240 2.5
258 2.5
45 1
47 1
48 1
34 0.9
35 0.9
36 0.9
300
Capital '*e
/*/i IAI\ ($/kW-
(VKVV) ป
yr)
177 0.8
193 0.8
209 0.8
500
Capital '*e
/*/i IAI\ ($/kW-
(VKVV) ป
yr)
163 0.7
178 0.7
193 0.7
700
Capital '*e
/*/i IAI\ ($/kW-
(VKVV) ป
yr)
155 0.5
169 0.5
184 0.5
1000
"ssf sa
\su3i /
-------
5.2.4 Methodology for Obtaining SCR Costs for Oil/Gas Steam units
The cost calculations for SCR described in section 5.2.3 apply to coal units. For SCR on oil/gas
steam units the cost calculation procedure employed in EPA's most recent previous base case
was used. However, capital costs were scaled up by 2.13 to account for increases in the
component costs that had occurred since the assumptions were incorporated in that base case.
All costs were expressed in constant 2007$ for consistency with the dollar year cost basis used
throughout EPA Base Case v4.10. Table 5-9 shows that resulting capital, FOM, and VOM cost
assumptions for SCR on oil/gas steam units. The scaling factor for capital and fixed operating and
maintenance costs, described in footnote 1, applies to all size units from 25 MW and up.
Table 5-9 Post-Combustion NCv Controls for Oil/Gas Steam Units in EPA Base Case v.4.10
Post-Combustion
Control Technology
SCR1
Capital
($/kW)
75
Fixed O&M
($/kW-yr)
1.08
Variable O&M
(mills/kWh)
0.12
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.
This data is used in the generation of EPA Base Case v.4.0
1 SCR Cost Equations:
SCR Capital Cost and Fixed O&M: (200/MW)035
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) = 75 * (200/275)035 = 67 $/kW
SCR FOM Cost ($/kW-yr) = 1.08 * (200/275)035 ~ 0.97 $/kW-yr
SCR VOM Cost (mills/kWh) = 0.12 mills/kWh
Reference:
Cosf Estimates for Selected Applications ofNOx Control Technologies on Stationary
Combustion Boilers, Bechtel Power Corporation for US EPA, June 1997
5.2.5 Methodology for Obtaining SNCR Costs
In the Sargent and Lundy 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).
Capital Costs: Due to the absence of a catalyst and, with it, the elimination of the need for more
extensive reagent preparation, the Sargent and Lundy engineering build up of SNCR capital costs
includes three rather than four separate cost modules: SNCR (injectors, blowers, distributive
control system, reagent system), air pre-heater modification, and balance of plan (e.g., ID or
booster fans, piping, and auxiliary power modification). For CFB units, the SNCR and balance of
plan module costs are 75% of what they are on other boiler types. The air pre-heater modification
cost module is the same as for SCR and there is no cost difference between CFB and other boiler
types. As with SCR the air heater modification cost only applies for plants that burn bituminous
coal whose SO2 content is 3 Ibs/MMBtu or greater, where SO3 control is necessary. Otherwise,
there is no air pre-heat cost. For each of the three modules the cost of foundations, buildings,
electrical equipment, installation, and average retrofit difficulty were taken into account.
The governing cost variables for each module are indicated in Table 5-3. Unit size affects all
three modules. Retrofit difficulty, coal rank, and heat rate impact the SNCR and air heater
modification modules. The SO2 rate impacts the air pre-heater modification module. NOX rate
5-12
-------
(expressed via the NOX removal efficiency) and heat input (not shown in Table 5-3) affect the
balance of plan module.
The base module costs for SNCR are summed to obtain total bare module costs. This total is
increased by 30% to account for additional engineering and construction fees. The resulting value
is the capital, engineering, and construction cost (CECC) subtotal. To obtain the total project cost
(TPC) the CECC subtotal is increased by 5% to account for owner's home office costs, i.e.,
owner's engineering, management, and procurement costs. Since SNCR projects are typically
completed in less than a year, there is no Allowance for Funds used During Construction
(AFUDC) in the SNCR capital cost factor that is used in EPA Base Case v.4.10.
Variable Operating and Maintenance Costs (VOM): Sargent and Lundy identified two components
of VOM for SNCR: (a) cost for the urea reagent and (b) the cost of dilution water. The magnitude
of the reagent cost predominates the VOM with the cost of dilution water at times near zero.
There is no capacity or heat rate penalty associated with SNCR since the only impact on power
are compressed air or blower required for urea injection and the reagent supply system.
Capacity and Heat Rate Penalty:
Unlike previous base cases, which assumed a generic heat rate and capacity penalties for all
installations, in EPA Base Case v.4.10 specific SNCR heat rate and capacity penalties are
calculated for each installation based on equations developed by Sargent and Lundy that take into
account the rank of coal burned, its SO2 rate, and the heat rate of the model plant.
Fixed Operating and Maintenance Costs (FOM): The assumptions for FOM for operations and
for administration are the same for SNCR as for SCR, i.e.,
FOM for operations is based on the assumption that one additional operator working half-time
is required.
There was assumed to be no FOM for administration for SCR.
FOM for maintenance materials and labor was assumed to be a direct function of base module
cost, specifically, 1.2% of those costs divided by the capacity of the generating unit expressed in
kilowatts.
Detailed example cost calculation spreadsheets for SNCR can be found in Appendix 5-2.
5.2.6 SO2 and NOX Controls for Units with Capacities from 25 MW to 100 MW (25 M <
capacity < 100 MW)
In EPA Base Case v.4.10 coal units with capacities between 25 MWand 100 MWare 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. This
assumption is 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 100 MW
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.30 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 fora 100 MWunit,
30 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.,
information on the project can be found at
qreenidqe.html.
5-13
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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.4.10, 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 retrofit with an
MPT.
Illustrative scrubber, SCR, and SNCR costs for 25-100 MWcoal units with a range heats rates
can be found by referring to the 100 MW "Capital Costs ($/kW)" and "Fixed O&M" columns in
Table 5-4 and Table 5-8. 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
Under most climate policies currently being discussed, biomass is treated as "carbon neutral," i.e.,
a zero contributor of CO2 to the atmosphere. The reasoning is that the CO2 emitted in the
combustion of biomass will be reabsorbed via photosynthesis in plants grown to replace the
biomass that was combusted. Consequently, if a power plant can co-fire biomass and thereby
replace a portion of fossil fuel, it reduces its CO2 emissions by approximately the same proportion,
although combustion efficiency losses may somewhat diminish the proportion of CO2 reduction.
Roughly speaking, by co-firing enough biomass to produce 10% of a coal plant's power output, a
co-fired plant can realize close to an effective 10% reduction in CO2 emitted.
Biomass co-firing is provided as a fuel choice for all coal-fired power plants in EPA Base Case
v.4.10. 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. 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.4.10 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 EPA Base Case v.4.10 "facility level" is defined as the set of
generating units which share the same ORIS code31 in NEEDS v.4.10.
The capital and FOM costs associated with biomass co-firing are summarized in Table 5-10.
Developed by EPA's power sector engineering staff32, they are on the same cost basis as the
31 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 under ownership changes.
32 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 A/Ox 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 Cofiring: 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) LauxS., J. Grusha, and D. Tillman, Co-firing of Biomass and Opportunity Fuels in Low NOx
5-14
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costs shown in Table 4-16 which resulted from EPA's comparative analysis of electricity sector
costs as described in Chapter 4.
Table 5-10 Biomass Cofiring for Coal Plants
Size of Biomass Unit (MW)
Capital Cost (2007$/kW From Biomass)
Fixed O&M (2007$/kW-yr)
5
488
24.2
10
411
16.2
15
371
11.7
20
345
9.4
25
327
8.0
30
312
11.1
35
300
9.9
40
290
8.9
45
282
8.1
50
275
7.5
The capital and FOM costs were implemented by ICF in EPA Base Case v.4.10 as a $/MMBtu
biomass fuel cost adder. The procedure followed to implement this was first to represent the
discrete costs shown in Table 5-10 as continuous exponential cost functions showing the FOM
and capital costs for all size coal generating units between 0 and 50 MW in size. Then, for every
coal generating unit represented in EPA Base Case 4.10, 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 an 11% capital charge rate. (This is the capital charge rate for
environmental retrofits found in Table 8-1 and discussed in Chapter 8.) 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 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 units co-fires biomass.
5.4 Mercury Control Technologies
As previously noted, the mercury emission controls options and assumptions in EPA Base Case
v.4.10 do not reflect mercury control updates that are currently underway at EPA in support of the
Utility MACT initiative and do not make use of data collected under EPA's 2010 Information
Collection Request (ICR). The following discussion is based on EPA's earlier work on mercury
controls.
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 emission policies that would require the installation of mercury
emission controls, mercury emission reductions below the mercury content of the fuel are strictly
due to characteristics of the combustion process and incidental removal resulting from non-
mercury control technologies, i.e., the SO2, NOX, and particulate controls. While the base case
itself does not include any federal mercury control policies, it does include some State mercury
reduction requirements. IPM has the capability to model mercury controls that might be installed
in response to such State mercury control policies. These same controls come into play in model
runs that analyze possible federal mercury policies relative to the base case. The technology
specifically designated for mercury control in such policy runs is Activated Carbon Injection (ACI)
downstream of the combustion process.
Burners, PowerGen 2000 - Orlando, FL,
www.fwc.com/publications/tech papers/powgen/pdfs/clrw bio.pdf.
Tillman, D. A., Cofiring Biomass for Greenhouse Gas Mitigation, presented at Power-Gen 99, New
Orleans, LA, November 30 - December 1, 1999.
(e) 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
5-15
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The following discussion is divided into three parts. Sections 5.4.1 and 5.4.2 treat the two factors
that figure into the unregulated mercury emissions resulting under EPA Base Case v.4.10.
Section 5.4.1 discusses how mercury content of fuel is modeled in EPA Base Case v.4.10.
Section 5.4.2 looks at the procedure used in the base case to capture the mercury reductions
resulting from different unit and (non-mercury) control configurations. Section 5.4.3 explains the
mercury emission control options that are available under EPA Base Case v.4.10. A major focus
is on the cost and performance features of Activated Carbon Injection. Each section indicates the
data sources and methodology used.
5.4.1 Mercury Content of Fuels
Coal: The assumptions in EPA Base Case v.4.10 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).33 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.
The ICR second component 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 in EPA Base Case v.4.10, these data points were
first grouped by IPM coal types and IPM coal supply regions. (IPM coal types divide bituminous,
sub-bituminous, and lignite coal into different grades based on sulfur content. See Table 5-11.)
Next, a clustering analysis was performed on the data using the SAS statistical software package.
Clustering analysis places objects into groups or clusters, such that data in a given cluster tend to
be similar to each other and dissimilar to data in other clusters. The clustering analysis involved
two steps. First, the number of clusters of mercury concentrations for each IPM coal type was
determined based on the range of mercury and SO2 concentrations for that coal type. Each coal
type used one, two or three clusters. To the greatest extent possible the total number of clusters
for each coal type was limited to keep the model size and run time within feasible limits. Second,
the clustering procedure was used to group each coal type within each IPM coal supply region into
the previously determined number of clusters and show the resulting mercury concentration for
each cluster. The average of each cluster is the mercury content of coal finally used in EPA Base
Case v.4.10 for estimating mercury emissions. IPM input files retain the mapping between
different coal type-supply region combinations and the mercury clusters. Table 5-11 below
provides a summary by coal type of the number of clusters and their mercury concentrations.
33Data from the ICR can be found at http://www.epa.gov/ttn/atw/combust/utiltox/mercury.html.
5-16
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Table 5-11 Mercury Clusters and Mercury Content of Coal by IPM Coal Types
Coal Type by Sulfur Grade
Low Sulfur Easter Bituminous (BA)
Low Sulfur Western Bituminous (BB)
Low Medium Sulfur Bituminous (BD)
Medium Sulfur Bituminous (BE)
High Sulfur Bituminous (BG)
High Sulfur Bituminous (BH)
Low Sulfur Subbituminous (SA)
Low Sulfur Subbituminous (SB)
Low Medium Sulfur Subbituminous (SD)
Low Medium Sulfur Lignite (LD)
Medium Sulfur Lignite (LE)
High Sulfur Lignite (LG)
Mercury Emission Factors by Coal Sulfur
Grades (Ibs/TBtu)
Cluster #1
3.19
1.82
5.38
19.53
7.10
7.38
4.24
6.44
4.43
7.51
13.55
14.88
Cluster #2
4.37
4.86
8.94
8.42
20.04
13.93
5.61
12.00
7.81
Cluster #3
21.67
14.31
34.71
-
-
Oil, natural gas, and waste fuels: The EPA Base Case v.4.10 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.34 Table 5-12 provides a summary of the
assumptions on the mercury content for oil, gas and waste fuels included in EPA Base Case
v.4.10.
Table 5-12 Assumptions on Mercury Concentration in Non-Coal Fuel in EPA Base Case
v.4.10
Fuel Type
Oil
Natural Gas
Petroleum Coke
Biomass
Municipal Solid
Waste
Geothermal
Resource
Mercury Concentration
0.48
O.OO1
23.18
0.57
71 85
2.97-3.7
(Ibs/TBtu)
Note:
1The 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
0.00014 Ibs/TBtu. Values for geothermal resources
represent a range.
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
34"Analysis of Emission Reduction Options for the Electric Power Industry," Office of Air and
Radiation, US EPA, March 1999.
5-17
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the inlet) during combustion and flue-gas treatment process is (1-EMF). The EMF varies by the
type of coal (bituminous, sub-bituminous, 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 representation 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 participants35 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 subbitumionus
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 improved understanding of mercury capture with SCRs was incorporated in EPA Base Case
v.4.10 mercury EMFs for unit configurations with SCR and wet scrubbers.
Table 5-13 below provides a summary of EMFs used in EPA Base Case v.4.10. Table 5-14
provides definitions of acronyms for existing controls that appear in Table 5-13. Table 5-15
provides a key to the burner type designations appearing in Table 5-13.
5.4.3 Mercury Control Capabilities
EPA Base Case v.4.10 offers two options for meeting mercury reduction requirements: (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.
35 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.gov/ttnatw01/utility/hgwhitepaperfinal.pdf.
5-18
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Table 5-13 Mercury Emission Modification Factors Used in EPA Base Case v.4.10
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
Particulate Control
Cold Side ESP
Cold Side ESP
Cold Side ESP
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 + 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
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
Fabric Filter
Fabric Filter
Fabric Filter
Hot Side ESP
Hot Side ESP
Hot Side ESP
Hot Side ESP
Hot Side ESP
Hot Side ESP
Post
Combustion
Control -
NOX
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
SNCR
SCR
SCR
SCR
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
SCR
SCR
SCR
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
Post
Combustion
Control -
SO2
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
Wet FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Bituminous
EMF
0.64
0.46
0.64
0.64
0.1
0.64
0.46
0.64
0.64
0.1
0.11
0.1
0.4
0.1
0.4
0.11
0.64
0.46
0.64
0.64
0.1
0.64
0.46
0.64
0.64
0.11
0.1
0.4
0.1
0.4
0.11
0.11
0.03
0.4
0.11
0.1
0.4
0.1
0.4
0.11
0.9
0.58
0.9
0.9
0.1
0.9
Subbitumionus
EMF
0.97
0.84
0.65
0.97
0.84
0.65
0.84
0.65
0.97
0.27
0.27
0.27
0.95
0.27
0.95
0.27
0.97
0.84
0.65
0.97
0.84
0.65
0.84
0.65
0.97
0.27
0.27
0.95
0.27
0.95
0.27
0.27
0.27
0.95
0.27
0.27
0.95
0.27
0.95
0.27
1
0.6
1
1
0.8
1
Lignite
EMF
0.93
0.58
0.93
0.93
0.58
0.93
0.58
0.93
0.93
0.58
1
0.58
0.91
0.58
0.91
1
0.93
0.58
0.93
0.93
0.58
0.93
0.58
0.93
0.93
1
0.58
0.91
0.58
0.91
1
1
0.58
0.91
1
0.58
0.91
0.58
0.91
1
1
1
1
1
1
1
5-19
-------
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
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
Participate Control
Hot Side ESP
Hot Side ESP
Hot Side ESP
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
Hot Side ESP + FGC
Hot Side ESP + FGC
No Control
No Control
No Control
No Control
No Control
No Control
No Control
No Control
No Control
PM Scrubber
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 + 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
Fabric Filter
Fabric Filter
Fabric Filter
Fabric Filter
Post
Combustion
Control -
NOX
None
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
None
SNCR
SNCR
SCR
None
None
None
SNCR
SNCR
None
None
SNCR
SNCR
SCR
None
None
None
SNCR
SNCR
None
None
SNCR
SNCR
SNCR
SCR
Post
Combustion
Control -
S02
Wet FGD
Dry FGD
None
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
None
Wet FGD
Wet FGD
Wet FGD
Dry FGD
None
None
Dry FGD
Dry FGD
None
None
Wet FGD
Wet FGD
Wet FGD
Dry FGD
None
None
Dry FGD
Dry FGD
None
None
Wet FGD
Dry FGD
None
Bituminous
EMF
0.58
0.9
0.9
0.11
0.9
0.58
0.9
0.9
0.1
0.9
0.58
0.9
0.9
1
0.45
1
1
0.1
1
0.45
1
1
0.8
0.65
0.65
0.1
0.65
0.45
0.65
0.05
0.05
0.05
0.05
0.65
0.65
0.1
0.65
0.45
0.65
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
Subbitumionus
EMF
0.6
1
1
0.27
1
0.6
1
1
0.8
1
0.6
1
1
1
0.6
1
1
0.7
1
0.6
1
1
1
0.65
0.65
0.84
0.65
0.45
0.65
0.43
0.43
0.43
0.43
0.65
0.65
0.84
0.65
0.45
0.65
0.43
0.43
0.43
0.43
0.43
0.43
0.43
0.43
Lignite
EMF
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0.62
0.62
0.62
0.62
1
0.62
0.43
0.43
0.43
0.43
0.62
0.62
0.62
0.62
1
0.62
0.43
0.43
0.43
0.43
0.43
0.43
0.43
0.43
5-20
-------
Burner
Type
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
FBC
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
Participate Control
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 + FGC
Hot Side ESP + FGC
Hot Side ESP + FGC
Hot Side ESP + FGC
No Control
No Control
No Control
No Control
No Control
No Control
No Control
No Control
No Control
Cold Side ESP
Cold Side ESP
Cold Side ESP
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 + 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
Post
Combustion
Control -
NOX
SCR
SCR
None
None
None
SNCR
SNCR
None
None
SNCR
SNCR
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
Post
Combustion
Control -
S02
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
Dry FGD
Dry FGD
None
None
Dry FGD
Dry FGD
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Bituminous
EMF
0.05
0.05
0.1
0.05
0.05
1
0.45
0.45
1
1
0.45
0.45
1
1
1
0.45
1
0.1
0.45
1
0.45
1
0.64
0.34
0.64
0.64
0.1
0.64
0.34
0.64
0.64
0.2
0.1
0.05
0.2
0.1
0.05
0.3
0.05
0.2
0.64
0.34
0.64
0.64
0.1
0.64
0.34
Subbitumionus
EMF
0.27
0.43
0.43
0.43
0.43
1
0.45
0.45
1
1
0.45
0.45
1
1
1
0.45
1
0.7
0.45
1
0.45
1
0.97
0.65
0.65
0.97
0.84
0.65
0.84
0.65
0.97
0.75
0.3
0.75
0.75
0.3
0.75
0.3
0.75
0.75
0.97
0.65
0.65
0.97
0.84
0.65
0.84
Lignite
EMF
0.43
0.43
0.43
0.43
0.43
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0.56
1
1
0.56
1
0.56
1
1
1
0.56
1
1
0.56
1
0.56
1
1
1
0.56
1
1
0.56
1
0.56
5-21
-------
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
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
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
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
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
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 + 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
Hot Side ESP + FGC
Hot Side ESP + FGC
Post
Combustion
Control -
NOX
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
Post
Combustion
Control -
S02
Dry FGD
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
Bituminous
EMF
0.64
0.64
0.2
0.1
0.05
0.2
0.1
0.05
0.3
0.05
0.2
0.11
0.03
0.05
0.11
0.1
0.05
0.1
0.05
0.11
0.9
0.58
0.6
0.9
0.1
0.6
0.58
0.6
0.9
0.11
0.03
0.05
0.11
0.1
0.05
0.03
0.05
0.11
0.9
0.58
0.6
0.9
0.1
0.6
0.58
0.6
0.9
Subbitumionus
EMF
0.65
0.97
0.75
0.3
0.75
0.75
0.3
0.75
0.3
0.75
0.75
0.27
0.27
0.75
0.27
0.27
0.75
0.27
0.75
0.27
0.9
0.75
0.85
0.9
0.8
0.85
0.8
0.85
0.94
0.27
0.27
0.75
0.27
0.15
0.75
0.27
0.75
0.27
0.9
0.75
0.85
0.9
0.8
0.85
0.8
0.85
0.94
Lignite
EMF
1
1
1
0.56
1
1
0.56
1
0.56
1
1
1
0.56
1
1
0.56
1
0.56
1
1
1
1
1
1
1
1
1
1
1
1
0.56
1
1
0.56
1
0.56
1
1
1
1
1
1
1
1
1
1
1
5-22
-------
Burner
Type
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Participate Control
Hot Side ESP + FGC + FF
Hot Side ESP + FGC + FF
Hot Side ESP + FGC + FF
Hot Side ESP + FGC + FF
Hot Side ESP + FGC + FF
Hot Side ESP + FGC + FF
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
No Control
No Control
No Control
PM Scrubber
PM Scrubber
PM Scrubber
Cold Side ESP
Cold Side ESP
Cold Side ESP
Cold Side ESP
Cold Side ESP
Cold Side ESP
Cold Side ESP
Cold Side ESP
Cold Side ESP
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
Cold Side ESP + FGC
Cold Side ESP + FGC
Fabric Filter
Fabric Filter
Fabric Filter
Fabric Filter
Fabric Filter
Fabric Filter
Fabric Filter
Fabric Filter
Post
Combustion
Control -
NOX
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
SNCR
SCR
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
Post
Combustion
Control -
S02
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
None
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
Bituminous
EMF
0.11
0.03
0.05
0.11
0.1
0.05
0.03
0.05
0.11
1
0.58
0.6
1
0.1
0.6
0.58
0.6
1
0.9
0.9
0.9
0.65
0.34
0.65
0.65
0.1
0.65
0.34
0.65
0.65
0.65
0.34
0.65
0.65
0.1
0.65
0.34
0.65
0.65
0.11
0.03
0.1
0.11
0.1
0.1
0.1
0.1
Subbitumionus
EMF
0.27
0.27
0.75
0.27
0.15
0.75
0.27
0.75
0.27
1
0.7
0.85
1
0.7
0.85
0.7
0.85
1
0.91
1
0.91
0.97
0.73
0.65
0.97
0.84
0.65
0.84
0.65
0.97
0.97
0.73
0.65
0.97
0.84
0.65
0.84
0.65
0.97
0.27
0.27
0.75
0.27
0.27
0.75
0.27
0.75
Lignite
EMF
1
0.56
1
1
0.56
1
0.56
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0.56
1
1
0.56
1
0.56
1
1
1
0.56
1
1
0.56
1
0.56
1
1
1
0.56
1
1
0.56
1
0.56
1
5-23
-------
Burner
Type
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Stoker
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Participate Control
Fabric Filter
Hot Side ESP
Hot Side ESP
Hot Side ESP
Hot Side ESP
Hot Side ESP
Hot Side ESP
Hot Side ESP
Hot Side ESP
Hot Side ESP
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
Hot Side ESP + FGC
Hot Side ESP + FGC
No Control
No Control
No Control
No Control
No Control
No Control
No Control
No Control
No Control
PM Scrubber
Cold Side ESP
Cold Side ESP
Cold Side ESP
Cold Side ESP
Cold Side ESP
Cold Side ESP
Cold Side ESP
Cold Side ESP
Cold Side ESP
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
Cold Side ESP + FGC
Cold Side ESP + FGC
Post
Combustion
Control -
NOX
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
Post
Combustion
Control -
S02
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
Bituminous
EMF
0.11
1
0.58
1
1
0.1
1
0.58
1
1
1
0.58
1
1
0.1
1
0.58
1
1
1
0.58
1
1
0.1
1
0.58
1
1
1
0.64
0.34
0.64
0.64
0.1
0.64
0.34
0.64
0.64
0.64
0.34
0.64
0.64
0.1
0.64
0.34
0.64
0.64
Subbitumionus
EMF
0.27
1
1
1
1
0.8
1
1
1
1
1
1
1
1
0.8
1
1
1
1
1
1
1
1
0.7
1
1
1
1
1
0.97
0.73
0.65
0.97
0.84
0.65
0.84
0.65
0.97
0.97
0.73
0.65
0.97
0.84
0.65
0.84
0.65
0.97
Lignite
EMF
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0.56
1
1
0.56
1
0.56
1
1
1
0.56
1
1
0.56
1
0.56
1
1
5-24
-------
Burner
Type
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Other
Participate Control
Fabric Filter
Fabric Filter
Fabric Filter
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
Hot Side ESP
Hot Side ESP
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
Hot Side ESP + FGC
Hot Side ESP + FGC
Hot Side ESP + FGC + FF
No Control
No Control
No Control
No Control
No Control
No Control
No Control
No Control
No Control
PM Scrubber
Post
Combustion
Control -
NOX
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
None
SNCR
SNCR
SNCR
SCR
SCR
SCR
None
None
None
None
Post
Combustion
Control -
S02
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
None
Wet FGD
Dry FGD
None
Wet FGD
Dry FGD
Wet FGD
Dry FGD
None
None
Bituminous
EMF
0.45
0.03
0.4
0.11
0.1
0.4
0.1
0.4
0.11
1
0.58
1
1
0.1
1
0.58
1
1
0.11
1
0.58
1
1
0.1
1
0.58
1
1
0.11
1
0.58
1
1
0.1
1
0.58
1
1
0.9
Subbitumionus
EMF
0.75
0.27
0.75
0.27
0.27
0.75
0.27
0.75
0.27
1
1
1
1
0.8
1
1
1
1
0.27
1
1
1
1
0.8
1
1
1
1
0.27
1
0.7
1
1
0.7
1
0.7
1
1
0.91
Lignite
EMF
1
0.56
1
1
0.56
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
1
1
1
1
1
1
1
1
1
1
5-25
-------
Table 5-14 Definition of Acronyms for Existing Controls
Acronym
Description
ESP Electro Static Precipitator - Cold Side
HESP Electro Static Precipitator - Hot Side
ESP/O Electro Static Precipitator - Other
FF Fabric Filter
FGD Flue Gas Desulfurization - Wet
DS Flue Gas Desulfurization - Dry
SCR Selective Catalytic Reduction
PMSCRUB Particulate Matter Scrubber
Table 5-15 Key to Burner Type Designations in Table 5-13
"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.
"Stoker" refers to stoker boilers where lump coal is fed continuously onto a moving grate or
chain which moves the coal into the combustion zone in which air is drawn through the grate
and ignition takes place. The carbon gradually burns off, leaving ash which drops off at the end
into a receptacle, from which it is removed for disposal.
"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.
"Other" refers to miscellaneous burner types including cell burners and arch-, roof-, and
vertically-fired burner configurations.
5-26
-------
Mercury Control through SO2 and NOX Retrofits
In EPA Base Case v.4.10, 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 the unregulated 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). These same EMFs would be
available in mercury policy runs to characterize the mercury reductions that can be achieved by
retrofitting a unit with SCR, SNCR, SO2 scrubbers and particulate controls. The absence of a
federal mercury emission reduction policy means that these controls appear in the base case in
response to SO2, NOX, or particulate limits or state-level mercury emission requirements.
However, in future model runs where mercury limits are present these same SO2 and NOX
controls could be deliberately installed for mercury control if they provide the least cost option for
meeting mercury policy limits.
Activated Carbon Injection (ACI)
The technology specifically designated for mercury control is Activated Carbon Injection (ACI)
downstream of the combustion process in coal fired units. A comprehensive ACI update, which
will incorporate the latest field experience through 2010, is being prepared by Sargent and Lundy
(the same engineering firm that developed the SO2 and NOX control assumptions used in EPA
Base Case v.4.10). It will be incorporated in a future EPA base case. The ACI assumptions in
the current base case release are the result of a 2007 internal EPA engineering study.
Based on this study, it is assume that 90% removal from the level of mercury in the coal is
achievable with the application of one of three alternative ACI configurations: Standard Powered
Activated Carbon (SPAC), Modified Powered Activated Carbon (MPAC), orSPAC in combination
with a fabric filter. The MPAC option exploits the discovery that by converting elemental mercury
to oxidized mercury, halogens (like chlorine, iodine, and bromine) can make activated carbon
more effective in capturing the mercury at the high temperatures found in industrial processes like
power generation. In the MPAC system, a small amount of bromine is chemically bonded to the
powdered carbon which is then injected into the flue gas stream either upstream of both the
particulate control device (ESP or fabric filter) and the air pre-heater (APH), between the APH and
the particulate control device, or downstream of both the pre-existing APH and particulate control
devices but ahead of a new dedicated pulsed-jet fabric filter. (The latter is known as the
TOXECON approach, an air pollution control process patented by EPRI.)
Table 5-16 presents the capital, FOM, and VOM costs as well as the capacity and heat rate
penalty for the five Hg emission control technologies included in EPA Base Case v.4.10 for an
illustrative set of generating units with a representative range of capacities.
5-27
-------
Table 5-16 Illustrative Activated Carbon Injection Costs (2007$) for Representative Sizes under the Assumptions in EPA Base Case
v.4.10
Control Type
MPAC_Baghouse
Minimum Cutoff: > 25 MW
Maximum Cutoff: None
Assuming Bituminous
Coal
MPAC_CESP
Minimum Cutoff: > 25 MW
Maximum Cutoff: None
Assuming Bituminous
Coal
SPAC_Baghouse
Minimum Cutoff: > 25 MW
Maximum Cutoff: None
Assuming Bituminous
Coal
SPAC_ESP
Minimum Cutoff: > 25 MW
Maximum Cutoff: None
Assuming Bituminous
Coal
SPAC_ESP+Toxecon
Minimum Cutoff: > 25 MW
Maximum Cutoff: None
Assuming Bituminous
Coal
Capacit
y
Penalty
(%)
-0.43
-0.43
-0.43
-0.43
-0.43
Heat
Rate
Penalty
(%)
0.43
0.43
0.43
0.43
0.43
Capacity (MW)
100
Capital ^ฃej Variable
Cost "*w O&M cost
($/kW) l* " (mills/kWh)
3 0.1 0.16
8 0.1 0.57
5 0.1 0.22
27 0.5 2.29
269 4.3 2.44
300
Capital ^ฃej Variable
Cost "*w O&M cost
($/kW) l _ " (mills/kWh)
2 0.05 0.17
6 0.1 0.61
4 0.1 0.23
21 0.3 2.46
202 2.5 2.61
500
Capital F*^ Variable
Cost T O&M cost
($/kW) ^ (mills/kWh)
2 0.04 0.17
5 0.1 0.61
3 0.1 0.23
18 0.3 2.44
176 2.1 2.59
700
Capital f*^ Variable
Cost "*w O&M cost
($/kW) l_'f: (mills/kWh)
2 0.03 0.16
5 0.1 0.59
3 0.1 0.23
17 0.3 2.39
161 2.0 2.54
5-28
-------
The applicable ACI option depends on the coal type burned, its SO2 content, the boiler and
participate control type and, in some instances, consideration of whether an SO2 scrubber (FGD)
system or SCR NOX post-combustion control are present. Table 5-17 shows the ACI assignment
scheme used in EPA Base Case v.4.10 to achieve 90% mercury removal.
Table 5-17 Assignment Scheme for Mercury Emissions Control Using Activated Carbon
Injection (ACI) in EPA Base Case v.4.10
Applicability of Activated Carbon Injection
Coal Type
Bit/Sub-bit/
Lig
Bit/Sub-bit/
Lig
Bit/Sub-
bit/Lig
Bit
Bit
Sub-bit/Lig
Sub-bit/Lig
Bit/Sub-bit/
Lig
Bit/Sub-bit/
Lig
Bit/Sub-bit/
Lig
Bit/Sub-bit/
Lig
Bit/Sub-bit/
Lig
Bit/Sub-bit/
Lig
Sub-bit/ Lig
Bit/Sub-
bit/Lig
SO2 in Coal Boiler
(Ib/MMBtu) Type
<1.6 Non-CFB
Non-CFB
CFB
<1.6 Non-CFB
>1.6 Non-CFB
>1.6 Non-CFB
>1.6 Non-CFB
Non-CFB
-
<1.6 Non-CFB
<1.6 Non-CFB
<1 6
<1.6
Particulate
Control Type
CS-ESP or BH
(no FGC)
CS-ESP or BH
(no FGC)
CS-ESP or BH
(no FGC)
CS-ESP
CS-ESP or BH
CS-ESP
BH
HESP
HESP or CS-
ESP (with FGC)
BH
CS-ESP
(no FGC)
No Control
BH
CS-ESP
(no FGC)
Cyclone
FGD
System
-
LSD
-
Non-LSD
-
-
-
No
No
Non-LSD
Non-LSD
SCR
System
No
-
-
Yes
-
-
-
Yes
Yes
Yes
Yes
Toxecon
Required?
No
No
No
No
No
Yes
No
Yes
Yes
No
No
Yes
No
Yes
Yes
ACI Type
With 90% Hg
Reduction
MPAC
MPAC
MPAC
SPAC
SPAC
SPAC
SPAC
SPAC
SPAC
MPAC
MPAC
SPAC
SPAC
SPAC
SPAC
Notes:
Legends:
ACI
BH
Bit
CFB
CS-ESP
FGC
HESP
Lig
MPAC
SPAC
Sub-bit
Activated carbon injection
Baghouse
Bituminous coal
Circulating fluidized-bed boiler
Cold side electrostatic
precipitator
Flue gas conditioning
Hot electrostatic precipitator
Lignite
Modified powdered activated
carbon
Standard powdered activated
carbon
Subbituminous coal
If the existing equipment provides 90% Hg removal, no ACI
system is required.
"" means that the category type has no effect on the ACI
application.
5-29
-------
-------
Appendix 5-1 Example Cost Calculation Worksheets for SC*2 Control
Technologies in EPA Base Case v.4.10
Ljuridy
IPM Model - Revisions to Cost and Performance for Project No. 12301-007
APC Technologies August 20. 2010
Wet FGD Cost Development Methodology Filial
Table 3. Example Complete Cost Estimate for tbe Wet TGD System (Costs are all based on 2009 dollars)
>x=
Variable
'. i ! -.'. i'. ' ,
:'! -i . "
Grass hfeai Rant
S->U i f^ate
T#w tit OxK
.i;-T 1 .X'nr
HHIII R&ff Ffr tijl
MED! Input
i in^nri= -*,n\R
'. -= t. r
AUXFOIAW
Uijl.-.^ '.','-)ป' ^.;i1ซ
'
Waste Deocsai cos
(UnPtHwrCcBt
1
. : -''
Designation
t
B
c
D
|
.
i.-.
11
K
L
i
N
P
Q
R
S
I
Unilt
Mr-. , ! w i .'*
I'.-T'V
^BlU'KiWt
iltfrftt-tu;
jBlulT)
iVin hil
ptonhn
(14)
i-inr,,-^ ,
(S'Tor-)
LVtOTil
iS.k'ATi |
cS.ltjCiJ'l
i :?. In
Value
MOl V
5TIQ
1
HSDO
3
!ป.ปป. *
I
3 t=
4 7iE-ttl
U
1 M
g
n
OS
i
bU
Calcualicn
' - '
. .- j,
UisriiipJl
User irt.J!
- ]\W . Lป3= i or
: 1x00
VC' 10CO
^i1 '7'fl*l.ซ*n.Vlllli
^ ' I'K
.: i.i ;_ : Shout) is* ซ$*d Tor *nod* mpul.
I^^T-TJ .L/A F '. nr
i msionetwo, b.tk)rซ3B, MuiKtoliwra sietinrai. mitt
O-|Br(iF'6i'Or5s-|y[V2><()M
1ซJWW'IB)'<(P1Cn>3ri*"07Wt
WUR t BMP ป BMW *
- FAfi'.v.1
ToUl Preftcl Coat
Al = l
CECC IS) Excludes Owtnf'i CosU - DM. A I
CECC ปltiW -EicluHn OwnWi toals-
TPC1 1 Jl - IncllWM QwlWa MSB CiCC * B1
TPC1 (t'kW) - Inclu** Owns's Cssls
TPC (S| . IhckidK Cwnrrt CMB and AFUCC CECC t Bt B2
lnckji>HOviTHTซCซts und tfUDC-
Eiamplt
I5JI3.MD
lrtfi.Td2.IXID
338
m
14,699.300
Z2T,MQ,(1QQ
250,303,000
EJtre waste tiordng rost
bow titiono? ol ofri
ID CM taeslef -brw new iwtrhimrwv aip*1^ tirivjoft n-rni ViV;~ -
Basa tfaslBU'cter Ircolmont tactiK rc>
-------
ii M.ly
IPM Model - Revisions to Cost and Performance for Project No. 12301-007
APC Technologies August 20, 2010
Wet FGD Cost Development Methodology - Final
'..)i|..-!jk
'A'aitoWTiEigr Trefsiirซnl
.
Gnx-5 Hfltit Rate
st'i! Rflie
Tvt* of Coal
. 1 -..'tM
. ' : -
Heal Input
Li'ri&slcrifr ^aifr
|S
,".'.>-: "'jwer
Mahem Wale* riaty
L-niFstcne Cosl
Waits Disposal <-OK
- 1.1
Makeup Wolff (Josl
cpefaiuia LBfict' Rale
Designation
A
B
C
0
E
F
.
hi
K
1
M
N
P
:j
R
|
T
Units
Nra- (it riti ,VJtn
.r-wi
iBtii'kW.*ii
^Ib'MWeMi
<3luhr'
(iDiiilin
(iDHitiri
W
HCODqphi
iS'trni
:';. lull
ftKkVhi
iS'iWOl
|S.'lYl
Val^p
1.-j- V
iUO
t
950(1
3
Himnumn V
1
.1 -
1 /'I: -.. '
1.
Lal-.-L 3.1 . i
Uset iniwi i;Grwt6Titi,^ KI(? r.trti
User Inpdti.An "jy- : ' "A ~ 1 Q|
- User Inpjt
- Ll?pf Inpji
~U&ei htfNt
3it=l. PRB=I D5 Uq=l OT
A'C'ICOJ
'7 5;*A'D'G22M
J-t .-rl 'ซ:
1.59 ' 6
t
60
i i - -
' \ij os.u ; j- 1
FOMO (tvw yn = i J MW-eoo treh r 6 aoiiiuul trains ots I : o|-eTaUfi!'?3Kn..;ft' icojt
FOLIA MlA1 vrt = 0 ป3-(FOMO*fl 4'FOMM|
FOWtS.tWyil-FaMO+FOMW-FaHA-FOMWW
VMMtatMGMl
VOHR(KVmil) = K1Py1A
VOMUV iS*tiVhl = L'Qi'A
VOMM (HMT.'mi = N'S'A
VOUTiVW (
Flrad OSM a3d tonal t(jปiaiioii lau.f .:ซt=
FiKQd C^M eปJrM?txvil mntnlisnnncfl (ngn^nal arvl intor costs
FntsdC&M aadtcnal ajtnnislralivt acor CMK
Flซc] OiM costs IM waalswoter Meannna teallty
it";
1M
tt.16
D 37 Vanasit- CI&M costs fijf Irn&steoe reegซnt
1 36 vanafile 04M costs For waib? dsposal
Vaiitmle 04M ccah fur actiibonal auxillorv po^ar required
oddiliinGl Ion power fRafsr to ALM ?cwar % abcve,!
D OB '/i-inailt- '."IAM COSlS fui IT Jkt-.it.' '.vJilw
Vanaiile 0AM costs ror H^&te^it^
Appendix 5-1.2
-------
Sargent: & Lundy'
IPM Model - Revisions to Cost and Performance for Project No. 12301-007
APC Teclinologie^ August 20, 2010
SDA FGD Cost Development Methodology - Final
Table 3. Example Complete Cost Estimate for the SDA FGD System (Costs are all based oil 2009 dollars)
Vai.iihjt
Una ^izซ rGioMi
^elrofll Fami
Otosi -fen r..)it
.
Type r>J Coป
^HrTTaHrx
:.-F.5-fol
Moat Inpul
LIITO AST*
/ , .1. r: i1ซ
AL.I PC-war
1. ... ,) . '. 1 i ,.
JFT-T >:.:.-rv
. , .!, 1." j .. 1
AMI piw*r i\-r,l
.; '
Operating Labor Rais
Detonation
A
ง
r
D
E
b
H
K
H
N
P
R
S
JnHs
rM'A':>
IJMK'. i.
.O.WBlu.
Itor.'hr)
HC+VIII 1
1 .1
nomaipin
ifnn..
l! !!!.
ll.vwni
U'l'JiXH
.Mil'
VUM
ปป
1
9100
2
Pft3 W
1 H^
lr.ft
(
4
I'T
136
17
15
in
006
1
53
Calculation
L...I li JMJT i'.-..ii-.'i lh.(n BPMWl
- - L jL-r ii , ' i erolll l-ds a factw = 1 D i
l.'j*r lufur
-. User Input ISDA FGD Esuiratlan only valm up to 3 IbltlMBaj SO2 Rats i
IJ-?Rr Input
Fii1=( PRP^I -i: | iii- 1 !/
i: iiPi.iCM
,'C-iaco
lO.CWitWKt ta'Pft-e.'jaM leased w 95^ SOS reirowll
inKIWlD'ii-ol HiT'DVA'0.2ซJO
!l'j;-t ;- in..' 4"'l -1 31-F'l.i ShcjH be used for rnodB! Input
i(i wsrii'iC'-lKn ':.;'. D--'r^ i i-A'F'.y mm
,
:, inaalla3ixi Uildfซjฃ fuunijall&is etedrlcoi and retrolt (fiflfculty
ion .A"J3ซIL1) il-.c
BMF II) = if(ป,>600 tier (Vซ9TOO) slw 30000D'(*.*I> 716)rfl'|D'6V>02
8MB (SI = IFiA-eDD ปien .A' 1299001 else 79BOaO'|Atl 71E.trB'(F'Gl"D 4
BM |4) = BMS * BMF ป BMW ป BMB
Total frajKl Cost
A I - l
CECCtil E>cludM Owner's Coslป-BM*A1ปA2ซA3
CCe |ปkWป - ExcliKId Oปwr-< Cซ*tซ
B1=5'>ioICECC
TPC' I)) lnc*ldea Owner's Costs * CfiCC * Bl
TPC- IJilW) - Intlwl.i aimtr-t Cotlt -
E2=1DMK(CECCปB1)
TPC (1) \nctuietOtmtft Costs ind AFUDC - CECC * B1
TPC |S*ซV.| - IncluMS Ownr-* Coad ind AFUDC
47,9S5,OOD
102.320,1X10
10,252.000
10,232. BOD
449
8,651,DOD
4N
13,967 .DOO
e M . 1. 1 ii : i : - islavj -.(
812
eaoen! pieaaialKjn arid waste retyde^andliig Oil
&nsซ rmdule adanc? erf plan U3S& including
ID w tooster fan? pipirig di(cr*oik. flledrcal. etc .
TuudI I'll':*; II KXIlllt LubL [I lUUUIXI I tlrutil rdLlLf'
BBW modute c^ssl pe^ kW
and Ccn&1nic4
-------
': "-.-M _!-i ir, .ii LLjndy1 "
IPM Model - Revisions to Cost and Performance for Project No. 12301-007
APC Technologies August 207 2010
SDA FGD Cost Development Methodology - Final
r Ur J OฃM Cost
FOMO (S'kw yr) = ia addinonai uparaBtsj'iM
FOซ(M iS.W/ yr) = BM'O 0 15.'(B'A' IflOCI
FOปW*)=KTW
VOMW (i'MVrti) = L-Q'A
'.'ana = !i
IJnil SlZ9 'XiTiss;-
I-:-': ' ! . !
( - -, ' - l>-
yjj' Kile
Type L/ i: o I'
'.
: '
Kg at lnp.il
,(.:
vVirilt Rate
AL* Purftr
L.|'>-'i[. \j -]!>.! K il_
: i i'.!
. i '< \ -i ; .. .. > :cr,l
AIJ* PrwerCosI
Vlafceup Water Coat
: >-i ii'M : 1 : .1 ,'-
Dnlgnrtlan
^
El
E
F
ii
H
K
L
M
i
F'
|
=1
s
f
Unrtป
.:M'/,-I
EVi. K^'.'li.
iit.Mt'Biu:
leiu'hn
(tor^'hrj
(tarvhrj
(%)
; liซ:iu nr.ni
;:;'<::ni
;>i.nni
[WtWh)
^S'laooj
H'tn)
UUlM
300
1
MM
2
Pflfl W
1 D5
;i [i'>
L : ''-.- ''
4
ID
1.J5
I?
94
30
O.M
1
Caieuistian
- -- f,,.r ',, ' :
- -. L'a-l !(:,! - I .t.-i- f|" !--t.- .!((( .;!' j :.|. !. : [) 1
', .'
UsBDnpui -L'A -:.[ rsiu .r:. -...h.i. M it- K"'.! r.iu s'.1.1 Rale)
--- L-=*i ''i(.-ui
Bil=' F=!f-
i.:,'llj:.[MI..
A'C'IBOO
l06702'(D^>i;--i i ,n;.
|0 601fi'(D''2>+3 1 .19 I7'D >'A' &2COD
IOMD547'! . ^ M ! : ShtLld tie used 'ui n-L'^l ftut.
lO&4&9e-'L . , i . : M|j
Lasor CK.: i! .'.; -skills
VOMW (S'MIVDI = M'S.'A
VOM IIilMWh) > VOMR VOMW < VOMP VOMM
5 12
0 16
137
0.96
a 06
2.4D
Fixed 13&M sdaiLtihal operating l&tor costs
Fined O&M ndclti:*nr>-3l mainleniMce' maleral wirj IntMr cosls
Fined OSM odditoral aaminislniilivs laoor cosls
Total Fixed oaM casts
v.it il--: >:^:' rr. .v. !-!( lit!!.- r-,^--f!
VairaWe OftW cosls tar waste disposal
VanaWe OftM cwls for orWitjongl aiixiMry power rwuw** uncluwno
ten power (Refer ID Aux Fewer % ฃjoป>a)
at*e O&IW cc&is Mi makeup walei
Appendix 5-1.4
-------
Appendix 5-2 Example Cost Calculation Worksheets forNOx Post-
Combustion Control Technologies in EPA Base Case v.4.10
IPM Model - Revisions to Cost and Performance for AFC
Technologies
' ~.-i. - i.-. i! .--. njncfy'
Project No. 12301-007
August 20,2010
SCR Cost Development Methodology -Final
Table 1, Example of The Capital CosTEstimnte Work Sheet.
V li.ilil,
1 1 * - .:
"tefrcfil Factor
-teat Rale
SO* Rate
502 Rai*
Type of Coat
loal Factor
^eal Kate Facto*
-faat IrfXJt
Cwecflv Factor
^ฃ" Removal EirUwri'' ,
H.-.-V h,snw-.il i .vrio'
1, - KI-W!
L .-.- :-V'k- -'/ ;
Steam Roquirod
1 > .< "::.;; ~~J~ : ป1 -' lin <-i
^atafysit Cost
i
Sin am Cost
: >|J. > il i | ..I.M -^Ifl
1 i.-.,.;|ll,r,i,M
A
3
C
O
E
F
G
H
[
J
R
L
M
rt
o
R
S
T
U
M..i^,
i.M'iV.i
i HI- .'k'/.-f ,
(lb.^MM6tu)
(ll>rtM^teflJ'l
(Btu'hr)
(%^
%
ibiTi
J^ib'j
I'S.'tmVi
>1 :..
V.^I.H-
nH
1
9?BO
ll^-t
1 71
ORB *
1 C6
B"^S
5.93E*-09
85
rn
o ฃ7Z
n ru *\\?
Wa
BBS
310
& \" i
0 :C
4
I,M
:,il. sjj ilinn
1.
; User Input '. (no
M-'- .--''-- ! -' '-' I/- -'-'
Wt 13
af>
r:i.i i ' L .!! 1 i
Costs are all based on 2009 dollars
i.apttal Cost Cxlciilatkm
inn >*:*?^ - Bi^iifn^^ii. lovaBsdon. DuUmgs. ftRffidfirtons. ซ4ซctdcat. and retrofii dintaAy.
DMR fS) - 16000O'fBnL)*D.2*fA*G*H)ISD.92
i BMP |() = J 1GQCC'' f M iftO JG
BfJIA (5|. - IFEi 3TMEM6&flOO'IBrtA-GTHrD.]re;EJ_SEO
BMB ;4; = iBCOCC-|B;-(ft-G-H^Q.Jl2
BM {&! = BMR~f BWF + SMS * BMB
Enm^y
S G5. t93 DCS
$ 1- 2id.Di>J
5
S 5666 000
S 73.093,000
CMnmartB
SCR llnlcl Ductrto-k Rractc-r. &,TซMj IsJand Gasl
BaEB Roagont Prnparation Cost
Air Heater Modification I SO3 Conlrd ! Eh luminous only S - dUntniBlul
ID or booster tzra ฃ. Auxiliary F"ovwr MoctfutiDn Costs
TlrtO fciVrt fi-'iO'lU'l-i '' i "-J III ' 'Ii1 1 :('
BM WKW> = 122 Bas* cost w< kW
A1 = lOtQfBWI
A2- 1O%idBM
A3= 1O%crfBM
S T.^Trt.nrci
5 7J09.DOQ
S 7 309,000
cngi iMMrlr*jfmi1'...i>ii*Jrn*l.Mi ManEWMn-?nr n>ซa
ContraOor praM and faos
CECT^i - CM- A' -.",VปA3
CECC (S/kWI -
B 1 - 5% or CECC
B2 = f%irfCECC+B1
S 'I1. 1 .- [Mi
158
5 i.T5t.OOO
1 S iBQ UOJ
.-..I--.-- ; - . -' i. :., i ; -I - '. ~ ' ,
. ..._: ji '.'".!-. j.-i,. .. .: JL- ..:'! '.". .-1 . i . . --'-
rruM^agcmant and pro c --ram ant acr.rtiflaj
cora&ucion cytlel
TPt (i) = CECL * B1 * Bi
s iu5,rs;.u&o
Tola project cast
i '.. ' i.i . .:-. 1 - .\
Appendix 5-2.1
-------
IPM Model - Revisions to Cost mid Performance for APC
Technologies
Project No. 12301-007
August 20,2010
SCR Cost Development Methodology - Final
Table :. Example of the Tiled and Variable O&M Estimate Work Sheet.
Vulijble
1
k :! - . '
-teat Rate
SOKRHte
SOi1 Rale
FvwofOjsi
Coal Factor
\--.y. ,_-.!* \ :,>::i<
h i i '
: i-. . .1.
SCM Removd Efficiency
N ' -V-.MII..I F;u lul
Vox Removal
Urea Rate (IKH>)
'_:4:> vi 1 ^-; ., t>:
': :!
UrwCosI SO1)* "t s*j7itr
^atalystCDSI
Aux Porter Goal
Storn C JXJl
'.';:...' ' . i -:,.^
Designation
A
B
v.
~
E
F
G
H
.1
K
L
M
M
C
P
R
S
T
u
V
Uniti
Wl;
(Elufk'iVM
lli't/MSr.
ili'l.ll/-il..i
fBlU'li')
(%)
%
bli
MbTl
ibซi-;
1%)
(Mcn(
(S'mJ)
i.tV'jUn
;s.t.ป:
1 Still
Vjlue
600
1
9860
n >i
1.^1
PF!B ป
1-05
1 .539
^ !^.--- : !
65
ro
" S75
H.MP^-IJ^
60S
6(39
D57
3111
8000
EOS
4
CO
LakLiljiicii
< I i nil
'. ' ."I 1 '1:1111 1 . i IK 1 . . :! :f ' .11
< User Input
1 .'^-r riout
< Usfii snout
Bป=1.0.PRB=l.[)5.Ug=I.Or
onuoo
.. ' . 1.1:
.'.'IM Inpui
ll'J
P'-i'lO-'S'K.i'llll
M'O-EZD'OMS'l.OI.'D.SS
N'1.13
, T:,- : Hr ; J ..... i . ~ , ..-rt-(. ;;n,t\\ :.'J.' c. , ,t. .
Ljb^ ctt-1 I .|M- 1 i. ... I : . .' ^
Costs are all based on 2009 dollars
MM ill JKMCOCI
FCMO (i'kW yr) = (1/Z operate lime as5umBd)'2000"W(A'1KKU
:.'Mr,'il .,\ ป!= I -..'.-.. , . ..CCO
5 0.10
t 0.50
Fixed OSM addiliQiial of^rsftng labor costs
i't: .<;.!' 3:: : :-'i3l i-ri.n il4r.ir :^ r-y^-.
and fabor costs
FOM [t'kW yn - rOMO FOMM
} U.6ซ
:::.-, F,*l :.'". OIK
Variable OKM E,n*l
' .f. F' .. . V.'.lp = '.'( ''". 1 "I'T
Ct.'v; ,.: t.-'.. i = : ::-;:r 'jrc .-.::. _ '.
' <':<.:<:. ; .1 .-.- >" . fiv
:. DJf
L 0.35
-:. D a i
;-i' --- = ' . '.I f :-,;-. 1.- ---
:y ?-. = 'I .: '.I :. : i::. 1: : :,:; , r "ri: :i: fiv4
'v - ' . '.1 ,- . -. i, i
1 _ disposal
KM (UMWhl - VOMR VOMW ; VOMM
t Ij.'j'i
Appendix 5-2.2
-------
Sar-osotS
IPM Model - Revisions to Cost and Performance for Project No. 12301-007
APC Technologies August 20, 2010
SN'C'R Cost Development Methodology Filial
Table 1. Example of the Capital C osr Estimate Work Sheet (for T-fiied boilers).
/arlabla
3o.l*r TYW
JntSi
3&Uyffl Facttw
-i i; I'jr.
.
Type Of C-WH
- -p.l KrLlS-r
,-.-*; (.!-(!.- i -i.-v.r
- tal Inpijl
floaty F ป!;:;-
i oj Removal Efcmency
OK Rorrc'/td
feaRaป(IOD%l
...:i !L quired
, -.-,ซ
Mli
rea Cost 50ftk At soutisn
w* Poww Cosi
:.iL [,.:>i V...:.-j: C:n:i
> i .- ; ' - >' -
Designation
A
B
C
n
E
E
f
G
II
[
J
K
L
M
N
o
p
Q
R
Unhs
I.MIAT,
iBUl^VsTi;
n-.r/'.i)...,
n>MMr-.!'j:
i Bluihr}
:',
%
ttth
ribftn i
illvUri
(%>
. i:QL',.;pr,i
|i.'ton;i
iSkWhl
. I '>.]-.!;
(ฃ
1.65E*02
717
6457
005
GTT
31 D
^,06
1
CalcutaUan
,:_-UsW U^iut
ซ... USDT htpi*
----- Iteet inoiACAn aversae'rieiiofithMafacWf = 1-0)
---ussf inpui
^-- t.>-,ftr inni--
'- t'aef tncui
= - : '.', I -.b 1 '.o L.-J 1 .r
. .1!
^C'lCDO
<.'--- Uaer Inpul
D"H'1C*-.-J.-1iX)
^"J
i. ., i , . - .
M1.. i,''H.i;Q
Labor cos! fflffl 1 1 i %;ts
Costs are all based on 2009 dollars
Capital Cast Calculation
EKOifiplH CprnmcritK
Include! Equipment. inalsJIabcn builri.nga Fou-d.ibccii etedncal. and nHrofH difficulty
3MS- Sl= 8"F.'L05'200OOO'lA'Gl"Q42
3M*iSl = - - .- 'H-- ::.'.'.! - .-.-., 'S. b 1 - L
. , - iu.i '-i i- ...
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ฃ A,' H"yi'- %-V'^ ill'- '.Ji'i -' ' ' - i , Si "3lbrtnfffiEul
t .' . '..III I - i tl -inr-.- - -. -" r "' Hi=* ;1 "H '' :'.l .iflfir-
- ..HI 1 1 .;.il ii- i . : r. : i
19 T!JW- n:st i.^-i k'ปV
ratal Pro|oci Coct
A2 = tO%O* SM
ฃ &J5.00D Erimii-...' ] -ji d ., |] j',-;uii '. . s -.'n>emccซ3t3
ฃ B36.000 _j.t.!i -J . ..-:,.'. .. :lni; . . n .>.i,. pel diet-, etc..
A.) = lC?%al9M :-. .-.ill'i. , : w-.v r*-,tr ,-ir.-. '--,-,
CECC (SI - Bปl^ft1ปAZ+&3
CECC (SAW) -
ฃ 6371,000 Capdal tr,yrimi\tig ma ccnKrucitoo ccsl sutrftital
23 Oocitfil. e>nr>ซซซnna and conetrucitcn coซl iyBoFS per t>Vt'
B1 -51!* of CECC
r 349000 Owoera ccata includug ah tion>&aff ce eoatu fov/iMris erigineeiing,
rnarUM^' &J i ir t. ;- LH;^'." .- r. ^^Uvp-jes;
TPC (SJ - CECC B1
TPC ^VW|-
$ 7.320,000 Total prqfecl cost
24 Idlrfl - : :,-' "-"i kVV
Appendix 5-2.3
-------
t Luncly
EPM Model - Revisions to Cost and Performance for Project No. 12301-007
APC Technologies August 20. 2010
SNC'R Cost Development Methodology - Final
Table 2. Example of the Fixed and Variable OA-M Cost Estimate Work Sheet (for T-fired boilers).
Variable
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"ixซd TiiM Ciwt
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I
S
0.74
ODD
074
'. 'arable OSM costs fbr Urea
Variable O8M costs for dlkitbn iwaler
Appendix 5-2.4
-------
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.4.10 are advanced
coal-fired units with CO2 capture (carbon capture).1 The cost and performance characteristics of
these units are shown in Table 4-13 and are discussed in Chapter 4.
Besides offering carbon capture capabilities on potential units that the model builds from scratch,
EPA Base Case v.4.10 also 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)
Incremental1 Capital Cost (2007 $/kW)
Incremental1 FOM (2007 $/kW-yr)
Incremental1 VOM (2007 (mills/kWh)
Capacity Penalty (%)
Heat Rate Penalty (%)
CO2 Removal (%)
450-750 MW
1,972
3.00
2.35
-25%
33%
90%
> 750 MW
1,599
1.98
2.35
-25%
33%
90%
Note:
Incremental costs are applied to the derated (after retrofit) MWsize.
The capital costs shown in Table 6-1 are based on the costs reported for Case 1 in a study2
performed for the U.S. Department of Energy's (DOE) National Energy Technology Laboratory
(NETL) by a team consisting of Alstom Power, Inc., American Electric Power (AEP), ABB Global,
and the Ohio Coal Development Office. For Case 1 this comprehensive engineering study,
conducted from 1999-2001, evaluated the impacts on plant performance and the required cost to
add facilities to capture greater than 90% of the CO2 emitted by AEP's Conesville Ohio Unit #5.
This is a 450 MWsubcritical3 pulverized bituminous coal plant with a lime based FGD, and an
electrostatic precipitator for particulate control. The carbon capture method that was evaluated
was an amine-based scrubber using the Kerr-McGee/ABB Lummus Global commercially available
monoethanolamine (MEA) process. In this system the flue gas leaves the FGD (which has been
modified to reduce the SO2 concentration as required by the MEA process) and is cooled and
ducted to the MEA system where more than 96% of the CO2 can be removed. For use in EPA
Base Case v.4.10 the capital cost was scaled to be applicable to the MW capacity sizes shown in
Table 6-1 and converted to constant 2007$ from the 2006$ costs reported in the NETL study.
1The 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, IGCC with carbon capture
was used in Table 4-13.
2 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.qov/enerqv-
analvses/pubs/CO2%20Retrofit%20From%20Existinq%20Plants%20Revised%20November%202
007.pdf. A summary of costs for each of the cases appears in Table 3-65 (p. 139).
3"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
-------
A capacity derating penalty of 25% was assumed, based on reported research and field
experience as of the summer 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.)
Since the fixed (FOM) and variable operating and maintenance (VOM) costs from the Conesville
study were given without documentation, another NETL study4 which fully documented these
costs was used to obtain the FOM and VOM values shown in Table 6-1. For FOM and VOM, the
cost differential was calculated between Case 9, a 550 MWsubcritical pulverized coal plant with
CO2 capture, and Case 10, a comparable unit but without CO2 capture. These differentials
provided the VOM and FOM costs for the "450-750 MW case in Table 6-1. For the "greater than
750 MW case these costs were scaled up by the ratio of a unit with an effective capacity of 750
MWto the effective capacity of the 450-750 MWcase raised to a power (k), where k reflects the
elasticity of the costs due to economies of scale. (The same approach was used to scale the
capital costs.) For capital, FOM, and VOM, the value of k was 0.65, 0.30, and 1 respectively.
6.2 CO2 Storage
The capacity and cost assumptions for CO2 storage in EPA Base Case v.4.10 are based on
GeoCAT (Geosequestration Cost Analysis Tool), a spreadsheet model developed for EPA by ICF
International in support of EPA's draft Federal Requirements Under the Underground Injection
Control (UIC) Program for Carbon Dioxide Geologic Storage Wells.5 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
4"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://www.netl.doe.gov/enerqy-
analyses/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).
5"Federal Requirements Under the 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.gov/fedrgstr/EPA-WATER/2008/July/Day-
25/w16626.htm and www.epa.gov/safewater/uic/wells_sequestration.html#regdevelopment.
6-2
-------
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,
enhanced shale gas, and
basalt
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"6, enhanced by ICF International 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. 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.7
For EPA Base Case v.4.10 GeoCAT identified storage opportunities in 33 of the lower 48
continental states and storage cost curves were developed for each of them.8 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
6"Carbon Sequestration Atlas of the United States and Canada", U.S. Department of Energy,
National Energy Technology Laboratory, Morgantown, VW, March, 2007.
7Detailed 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 technoloqyandcostanalvsis.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, Pages 4281-4288. Available online at www.sciencedirect.com.
8The states without identified storage opportunities in EPA Base Case v.4.10 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.
6-3
-------
cost curves. The result is a total of 37 storage cost curves which are shown in Appendix 6-1
("CO2 Storage Cost Curves in EPA Base Case").9
The cost curves shown in Appendix 6-1 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.
There are several additional things to note about the cost curves in Appendix 6-1. First, besides
electric sector demand for CO2 storage, there is expected to be demand from the industrial sector
as well. Therefore, before being incorporated into EPA Base Case v.4.10, the original CO2
storage capacity in each storage region was reduced by an estimate of the storage required for
CO2 generated by industrial sector sources. To do this, ICF first estimated the level of industrial
demand in each CO2 storage region expected at an allowance price of $150 per ton.10 (An
allowance price of $150/ton was chosen to provide a conservative estimate of the amount of
storage available to the electricity sector, since under most CO2 policies that would be analyzed
with EPA Base Case v.4.1.0 the allowance price is expected to be below $150/ton.) Then, for
each region ICF calculated the ratio of the industrial demand to total storage capacity available for
less than $10/ton. (An upper limit of $10/ton was chosen because the considerable amount
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 for 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/ton 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.4.10. Thus, the
values shown in Table 6-1 represent the storage available to the electric sector.
Second, price steps from region to region are the same. (That is, CO2STEP5 (column 2) has a
step cost value of $4.54/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. Third,
in any given region, the cost curves are the same for every year. Thus, the step cost, step bound,
and total storage capacity shown in columns 4 and 5 in Appendix 6-1 remain the same from year
to year. This feature implies the assumption that over the modeling time horizon, i.e., 2012-2050,
no new storage will need to be added to augment the storage that is in today's storage inventory.
This assumption is not meant to imply that additional storage is unavailable. It only implies that for
purposes of modeling the assumption will only be revisited if model runs requiring storage exhaust
key components in the storage inventory.
Finally, in each storage cost curve included in Appendix 6-1, CO2STEP1 through CO2STEP3
show a negative cost, and CO2STEP4 shows a zero cost. These steps in the cost curves
represent storage available from enhanced oil recovery (EOR) where oil producers either pay or
9For consistency across the emission costs represented in v.4.10, the costs shown in Appendices
9-1 and 9-2 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 $/ton values shown In Appendices 9-1
and 9-2 by 1.1023.
10The approach that ICF employed to estimate industrial demand for CO2 storage is described in
ICF International, "Methodology and Results for Initial Forecast of Industrial CCS Volumes,"
January 2009.
6-4
-------
offer free storage for CO2 which they inject into mature oil wells to enhance the amount of oil
recovered.11
6.3 CO2 Transport
Each of the 32 IPM model regions can send CO2 to the 37 regions represented by the storage
cost curves in Appendix 6-1. The associated transport costs (in 2007$/Ton) are shown in
Appendix 6-2 (CO2 Transportation Matrix in EPA Base Case v.4.0).
These costs were derived by ICF International by first calculating the pipeline distance from each
of the CO2 Production Regions to each of the CO2 Storage Regions listed in Appendix 6-2. (For
example, the distance from MACS to Louisiana Onshore was estimated as 997 miles.) Since
there are large economies of scale for pipelines, CO2 transportation costs would depend on how
many power plants and industrial CO2 sources could share a pipeline over a given distance.
Consequently, ICF's method assumes that the longer the distance from the source of the CO2 (in
our example MACS) to the sink for the CO2 (in our example Louisiana Onshore), the more chance
there is for other sources to share in the transportation costs with the pipeline diameter growing
with distance as more sources are fed into the same system. Cost components include pipeline
costs (in $/inch-mile) and cost of service (in $/ton per 75 miles). These cost components in turn
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. Table 6-2 illustrates the build-up of cost for the MACS to Louisiana Onshore example.
This example comes to $20.11 per ton of CO2 (in 2007$) for the overall miles pipeline distance
traveled. (This is the short ton equivalent to the $22.17 metric tonne value shown in Table 6-2.)
Table 6-2 CO2 Transport Cost Calculation Example - MACS to Louisiana Onshore
CARBON DIOXIDE PIPELINES
Outside
Dia.
Inches
12.75
16
24
30
36
42
Inside
Dia.
Inches
12.0
15.0
22.5
28.2
33.8
39.4
Wall
Thickness
Inches
0.39
0.49
0.73
0.92
1.10
1.28
Pipeline
Cost in
$/lnch-Mile
$ 75,000
$ 78,116
$ 84,119
$ 86,399
$ 88,678
$ 90,958
Service in $/metric
ton per 75 miles or
121 km
$4.36
$3.25
$2.02
$1.56
$1.27
$1.10
Capacity in
metric
tons/day
10,775
19,139
53,385
93,887
148,913
219,942
Flow Capacity in
million standard cubic
feet per day
(60 degrees F and
14.73 psi)
203
361
1,007
1,771
2,808
4,148
Number of 500
MW IGCC plants
accomodated
0.97
1.73
4.83
8.49
13.46
19.88
Note: 500 MW IGCC plant would produce 512 metric tonnes of CO2 per hour. Of this, 90% or 461 tonnes would be captured.
Maximum CO2 tranport needs would be 11, 064 tonnes per power plant per day. Cost of service based on 7 cents per kWh electricity.
Example Spaclal Assumptions
Single Power Plant Pipeline (12 inch, small gathering) distance in miles
Two Power Plant Pipeline (16 inch, large gathering) distance in miles
Eight Power Plant Pipeline (30 inch, mainline) distance in miles
Miles
$/Mile per Tonne
Cost per
Tonne
Annual Cost per
Power Plant @85
Utilization Rate
25 $0.058 $1.45 $4,986,315
25 $0.043 $1.08 $3,717,211
947 $0.021 $19.64 $67,400,166
Total Distance & Costs 997 $0.022 $22.17 $76,103,692
11There is also a market for CO2 injection in enhanced coal bed methane (ECBM) production.
ECBM is excluded from EPA's inventory as discussed earlier.
6-5
-------
-------
Appendix 6-1 COz Storage Cost Curves in EPA Base Case 4.10
Note: The curves for each region are applicable in each model run year 2012 - 2050.
CO2 Storage
Region
Alabama
Arizona
Arkansas
Step
Name
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
CO2 Storage
Step Cost
(2007$/Ton)
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
Annual Step Bound
(MMTons)
1
0
0
0
31
39
38
0
4
13
0
0
0
1
0
0
0
0
0
0
0
0
0
121
145
113
0
38
0
0
0
0
0
0
0
0
0
0
1
0
0
0
146
177
Total Storage Capacity
(MMTons)
45
0
0
6
1,568
1,967
1,895
9
186
639
7
14
0
68
0
14
0
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
62
0
0
0
7,297
8,863
Appendix 6-2.1
-------
CO2 Storage
Region
Atlantic Offshore
California
Onshore
Step
Name
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
CO2 Storage
Step Cost
(2007$/Ton)
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
Annual Step Bound
(MMTons)
142
1
51
3
0
1
0
1
0
1
0
0
0
0
0
0
0
1,832
2,211
1,706
0
0
569
0
0
0
0
0
0
0
0
0
19
0
0
2
1,227
1,966
367
11
70
30
0
16
0
21
Total Storage Capacity
(MMTons)
7,110
35
2,568
128
0
53
0
71
0
53
0
0
0
0
0
0
0
91,580
110,528
85,311
0
0
28,437
0
0
0
0
0
0
0
0
0
941
0
0
121
61,357
98,304
18,335
531
3,516
1,507
0
797
0
1,063
Appendix 6-2.2
-------
CO2 Storage
Region
Colorado
Florida
Georgia
Step
Name
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
CO2 Storage
Step Cost
(2007$/Ton)
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
Annual Step Bound
(MMTons)
0
16
0
0
0
3
0
0
0
13
16
16
1
7
1
0
0
0
1
0
0
0
0
0
2
0
0
0
456
550
426
0
143
1
0
0
0
1
0
0
0
0
0
0
0
0
Total Storage Capacity
(MMTons)
0
797
0
0
0
136
0
0
0
627
801
804
35
353
59
0
22
0
30
0
22
0
0
0
105
0
0
0
22,813
27,479
21,317
13
7,172
33
0
20
0
26
0
20
0
0
0
0
0
0
Appendix 6-2.3
-------
CO2 Storage St
Region Na
CO2 Storage
ep Step Cost
me (2007$/Ton)
STEP4 0.00
STEPS 4.54
STEP6 9.07
STEP7 13.61
STEPS 18.14
STEP9 22.68
STEP10 27.22
STEP11 31.75
STEP12 36.29
STEP13 40.82
STEP14 45.36
STEP15 49.90
STEP16 54.43
STEP17 58.97
STEP18 63.50
STEP19 68.04
STEP1 -13.61
STEP2 -9.07
STEPS -4.54
STEP4 0.00
STEPS 4.54
STEP6 9.07
STEP7 13.61
STEPS 18.14
STEP9 22.68
Illinois STEP10 27.22
STEP11 31.75
STEP12 36.29
STEP13 40.82
STEP14 45.36
STEP15 49.90
STEP16 54.43
STEP17 58.97
STEP18 63.50
STEP19 68.04
Indiana STEP1 -13.61
STEP2 -9.07
STEPS -4.54
STEP4 0.00
STEPS 4.54
STEP6 9.07
STEP7 13.61
STEPS 18.14
STEP9 22.68
STEP10 27.22
STEP11 31.75
Annual Step Bound
(MMTons)
0
42
51
40
0
0
13
0
0
0
0
0
0
0
0
0
3
0
0
0
309
373
303
1
108
4
0
2
0
3
0
2
0
0
0
0
0
0
0
164
198
167
0
56
0
0
Total Storage Capacity
(MMTons)
0
2,117
2,555
2,000
0
0
667
0
0
0
0
0
0
0
0
0
165
16
0
0
15,455
18,653
15,168
73
5,420
180
0
109
0
144
0
108
0
0
0
17
2
0
0
8,195
9,890
8,332
1
2,781
2
0
Appendix 6-2.4
-------
CO2 Storage
Region
Kansas
Kentucky
Step
Name
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
CO2 Storage
Step Cost
(2007$/Ton)
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
Annual Step Bound
(MMTons)
0
0
0
0
0
0
0
0
6
0
0
0
37
50
66
14
32
0
0
12
0
0
0
0
0
0
0
0
0
0
0
54
86
16
1
4
1
0
4
0
1
0
1
0
0
2
Total Storage Capacity
(MMTons)
1
0
1
0
1
0
0
0
287
0
0
0
1,863
2,513
3,323
685
1,620
0
0
620
0
0
0
0
0
0
0
7
0
0
0
2,694
4,310
808
26
208
64
0
182
0
52
0
39
0
0
86
Appendix 6-2.5
-------
CO2 Storage
Region
Louisiana
Onshore
Louisiana
Offshore
Michigan
Step
Name
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
CO2 Storage
Step Cost
(2007$/Ton)
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
Annual Step Bound
(MMTons)
20
0
3
0
918
1,127
949
7
47
334
0
8
0
26
3
11
0
0
8
23
0
0
0
0
0
661
2,535
0
677
2,208
992
20
1,695
0
1,338
0
0
1,159
1
0
0
0
339
409
323
0
Total Storage Capacity
(MMTons)
1,012
0
130
0
45,891
56,334
47,463
353
2,342
16,704
0
397
0
1,292
134
530
0
0
397
1,128
0
0
0
0
0
33,069
126,766
0
33,829
110,376
49,604
1,012
84,765
0
66,898
0
0
57,975
62
0
0
0
16,935
20,471
16,130
4
Appendix 6-2.6
-------
CO2 Storage
Region
Mississippi
Montana
Step
Name
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
CO2 Storage
Step Cost
(2007$/Ton)
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
Annual Step Bound
(MMTons)
108
0
0
0
0
0
0
0
0
0
0
2
0
0
0
552
668
522
1
4
178
0
1
0
3
0
2
0
0
1
4
0
0
0
1,608
1,941
1,505
8
513
23
0
8
0
13
0
10
Total Storage Capacity
(MMTons)
5,380
7
6
4
0
0
2
0
3
0
2
117
0
18
0
27,623
33,410
26,080
63
221
8,877
0
71
0
157
0
95
0
0
71
194
0
0
0
80,381
97,053
75,253
396
25,652
1,131
0
391
0
652
0
522
Appendix 6-2.7
-------
CO2 Storage
Region
North Dakota
Nebraska
Nevada
Step
Name
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
CO2 Storage
Step Cost
(2007$/Ton)
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
Annual Step Bound
(MMTons)
0
0
8
5
0
0
0
91
110
91
8
41
22
0
8
0
13
0
10
0
0
8
0
0
0
0
15
18
17
0
7
1
0
0
0
0
0
0
0
0
0
0
0
0
0
60
Total Storage Capacity
(MMTons)
0
0
391
241
0
0
0
4,549
5,499
4,538
376
2,068
1,110
0
384
0
640
0
512
0
0
384
11
0
0
0
734
881
859
11
337
25
0
15
0
20
0
15
0
0
0
0
0
0
0
3,024
Appendix 6-2.8
-------
CO2 Storage
Region
New Mexico
New York
Step
Name
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
CO2 Storage
Step Cost
(2007$/Ton)
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
Annual Step Bound
(MMTons)
73
56
0
19
0
0
0
0
0
0
0
0
0
0
13
0
0
0
36
67
103
6
59
21
0
6
0
8
0
6
0
0
0
0
0
0
0
0
0
1
0
1
0
0
0
0
Total Storage Capacity
(MMTons)
3,650
2,821
0
940
0
0
0
0
0
0
0
0
0
0
672
0
0
0
1,791
3,338
5,130
285
2,960
1,033
0
293
0
391
0
293
0
0
0
0
0
0
0
0
8
54
15
39
7
0
23
0
Appendix 6-2.9
-------
CO2 Storage
Region
Ohio
Oklahoma
Oregon
Step
Name
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
CO2 Storage
Step Cost
(2007$/Ton)
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
Annual Step Bound
(MMTons)
0
0
0
0
0
0
0
0
0
0
213
257
206
0
71
1
0
3
0
1
0
0
0
0
1
18
2
3
0
2
10
41
8
35
36
0
9
0
22
0
12
0
0
9
0
0
Total Storage Capacity
(MMTons)
0
0
0
0
0
0
0
0
0
0
10,634
12,835
10,320
13
3,551
33
0
130
0
26
0
20
0
0
66
898
116
154
0
117
502
2,070
387
1,767
1,779
0
436
0
1,116
0
581
0
0
436
0
0
Appendix 6-2.10
-------
CO2 Storage
Region
Pacific Offshore
Pennsylvania
Step
Name
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
CO2 Storage
Step Cost
(2007$/Ton)
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
Annual Step Bound
(MMTons)
0
0
171
206
161
0
54
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
309
331
573
0
0
198
331
265
0
2
0
2
222
0
0
0
0
52
84
19
1
5
2
Total Storage Capacity
(MMTons)
0
0
8,530
10,294
8,036
0
2,679
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
15,432
16,535
28,660
2
3
9,921
16,537
13,234
0
83
8
110
11,123
0
0
0
0
2,611
4,178
972
34
262
86
Appendix 6-2.11
-------
CO2 Storage
Region
South Carolina
South Dakota
Step
Name
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
CO2 Storage
Step Cost
(2007$/Ton)
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
Annual Step Bound
(MMTons)
0
4
0
1
0
1
0
0
2
0
0
0
0
43
51
40
0
13
0
0
0
0
0
0
0
0
0
0
0
0
0
0
219
264
206
0
69
0
0
0
0
0
0
0
0
0
Total Storage Capacity
(MMTons)
0
206
0
69
0
52
0
0
93
0
0
0
0
2,126
2,565
2,000
0
667
0
0
0
0
0
0
0
0
0
0
0
0
0
0
10,933
13,196
10,313
0
3,438
1
0
0
0
0
0
0
0
0
Appendix 6-2.12
-------
CO2 Storage
Region
Tennessee
Texas Onshore
Texas Offshore
Step
Name
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
CO2 Storage
Step Cost
(2007$/Ton)
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
Annual Step Bound
(MMTons)
0
0
0
0
0
21
33
6
0
0
0
0
0
0
0
0
0
0
0
0
113
0
14
0
1,800
2,195
1,913
25
228
690
0
38
0
81
0
38
0
0
0
0
0
0
0
0
0
397
Total Storage Capacity
(MMTons)
0
0
0
0
0
1,035
1,657
319
0
0
0
0
0
0
0
0
0
0
0
0
5,633
0
724
0
90,016
109,766
95,669
1,258
11,406
34,524
0
1,887
0
4,041
0
1,887
0
0
0
0
0
0
0
0
0
19,842
Appendix 6-2.13
-------
CO2 Storage St
Region Na
CO2 Storage
ep Step Cost
me (2007$/Ton)
STEPS 18.14
STEP9 22.68
STEP10 27.22
STEP11 31.75
STEP12 36.29
STEP13 40.82
STEP14 45.36
STEP15 49.90
STEP16 54.43
STEP17 58.97
STEP18 63.50
STEP19 68.04
STEP1 -13.61
STEP2 -9.07
STEPS -4.54
STEP4 0.00
STEPS 4.54
STEP6 9.07
STEP7 13.61
STEPS 18.14
STEP9 22.68
Utah STEP10 27.22
STEP11 31.75
STEP12 36.29
STEP13 40.82
STEP14 45.36
STEP15 49.90
STEP16 54.43
STEP17 58.97
STEP18 63.50
STEP19 68.04
Virginia STEP1 -13.61
STEP2 -9.07
STEPS -4.54
STEP4 0.00
STEPS 4.54
STEP6 9.07
STEP7 13.61
STEPS 18.14
STEP9 22.68
STEP10 27.22
STEP11 31.75
STEP12 36.29
STEP13 40.82
STEP14 45.36
STEP15 49.90
Annual Step Bound
(MMTons)
1,521
0
400
1,324
595
4
1,000
0
796
3
0
627
4
0
0
0
2
4
5
1
3
1
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1
0
0
0
0
0
0
Total Storage Capacity
(MMTons)
76,059
0
19,999
66,192
29,762
197
49,998
0
39,801
133
0
31,338
195
0
0
0
106
184
251
36
137
46
0
12
0
16
0
12
0
0
0
0
0
0
0
0
0
21
9
53
23
0
14
0
18
0
Appendix 6-2.14
-------
CO2 Storage
Region
Washington
West Virginia
Wyoming
Step
Name
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
STEPS
STEP6
STEP7
STEPS
STEP9
STEP10
STEP11
STEP12
STEP13
STEP14
STEP15
STEP16
STEP17
STEP18
STEP19
STEP1
STEP2
STEPS
STEP4
CO2 Storage
Step Cost
(2007$/Ton)
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
4.54
9.07
13.61
18.14
22.68
27.22
31.75
36.29
40.82
45.36
49.90
54.43
58.97
63.50
68.04
-13.61
-9.07
-4.54
0.00
Annual Step Bound
(MMTons)
0
0
0
0
0
0
0
0
162
196
155
0
52
0
0
0
0
0
0
0
0
0
0
0
0
0
0
47
75
14
1
5
2
0
1
0
2
0
1
0
0
0
6
0
0
0
Total Storage Capacity
(MMTons)
14
0
0
0
0
0
0
0
8,101
9,777
7,738
0
2,579
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2,351
3,761
721
38
227
94
0
73
0
75
0
57
0
0
10
324
0
0
0
Appendix 6-2.15
-------
CO2 Storage St
Region Na
CO2 Storage
ep Step Cost
me (2007$/Ton)
STEPS 4.54
STEP6 9.07
STEP7 13.61
STEPS 18.14
STEP9 22.68
STEP10 27.22
STEP11 31.75
STEP12 36.29
STEP13 40.82
STEP14 45.36
STEP15 49.90
STEP16 54.43
STEP17 58.97
STEP18 63.50
STEP19 68.04
Annual Step Bound
(MMTons)
2,644
3,198
2,486
2
836
10
0
1
0
7
0
2
0
0
1
Total Storage Capacity
(MMTons)
132,195
159,909
124,304
100
41,794
496
0
65
0
339
0
87
0
0
65
Appendix 6-2.16
-------
Appendix 6-2 CO2 Transportation Matrix in EPA Base Case v.4.10
CO2 Production Region
AZNM
CA-N
CO2 Storage Region
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Cost (2007$/Ton)
26.30
3.50
19.34
35.66
13.36
9.43
34.30
32.10
23.54
25.54
11.13
29.06
22.58
23.19
28.53
23.21
18.29
18.73
11.58
9.20
3.30
34.34
30.66
12.63
20.63
12.18
33.49
32.35
16.24
27.12
15.99
21.22
7.90
32.84
30.89
12.76
37.36
11.27
30.35
46.55
4.67
17.69
45.34
43.10
33.75
35.78
Appendix 6-2.1
-------
CO2 Production Region
CA-S
CO2 Storage Region
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
Cost (2007$/Ton)
21.53
39.54
33.61
34.04
37.98
34.28
22.73
23.59
19.92
5.18
13.42
43.93
40.66
23.52
14.68
5.49
43.47
43.30
22.18
37.87
26.74
31.95
12.50
43.36
41.28
18.13
33.45
7.46
26.55
42.90
6.99
15.09
41.31
39.32
30.57
32.59
18.18
36.20
29.58
29.90
35.22
30.34
21.82
22.54
17.41
4.60
9.72
Appendix 6-2.2
-------
CO2 Production Region
COMD
CO2 Storage Region
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Cost (2007$/Ton)
41.12
37.62
19.87
17.43
5.27
40.45
39.59
20.67
34.35
22.59
27.79
10.69
40.00
38.01
16.62
15.38
26.11
13.19
16.86
34.86
18.43
22.02
16.05
4.75
4.82
15.43
8.40
16.98
20.13
4.81
15.10
18.69
17.74
16.28
30.94
23.94
10.57
7.45
15.12
34.88
35.76
10.14
15.15
16.60
9.56
20.39
20.75
Appendix 6-2.3
-------
CO2 Production Region
DSNY
ENTG
CO2 Storage Region
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Cost (2007$/Ton)
23.86
11.68
9.22
19.55
20.59
39.27
23.19
13.07
48.11
31.74
22.09
16.20
16.14
14.22
28.47
11.74
24.54
27.30
11.58
22.44
30.66
29.63
29.57
44.25
37.07
5.72
8.97
27.58
47.39
48.99
6.18
14.74
29.17
14.78
30.61
28.92
37.14
9.36
9.81
32.53
7.84
21.51
3.44
16.70
31.99
17.06
16.30
Appendix 6-2.4
-------
CO2 Production Region
ERCT
CO2 Storage Region
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Cost (2007$/Ton)
13.09
8.81
9.87
11.85
11.53
6.63
9.61
15.04
5.45
22.95
22.36
16.04
27.84
19.32
19.12
14.70
9.24
35.90
31.01
17.17
13.34
19.94
8.76
10.31
9.93
22.29
14.87
13.49
20.78
11.70
17.85
6.89
22.16
28.61
16.48
19.08
18.02
15.08
16.40
11.44
18.11
7.38
7.88
21.40
8.61
24.73
24.42
16.44
Appendix 6-2.5
-------
CO2 Production Region
FRCC
CO2 Storage Region
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Cost (2007$/Ton)
24.59
15.94
25.74
21.33
8.37
34.69
26.55
23.80
18.68
21.63
15.19
4.33
6.27
20.59
21.28
20.06
21.08
7.71
33.74
14.94
8.78
44.39
29.83
4.12
5.33
16.83
15.92
24.61
13.10
11.59
12.45
20.06
10.73
34.81
34.07
28.72
40.31
31.64
20.09
16.78
21.91
48.66
42.80
17.31
6.76
31.99
11.23
19.12
Appendix 6-2.6
-------
CO2 Production Region
GWAY
LILC
CO2 Storage Region
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Cost (2007$/Ton)
14.75
35.06
12.94
13.74
33.33
12.18
23.91
9.40
16.05
33.36
17.01
19.59
14.19
3.25
4.03
13.08
7.95
13.27
16.40
8.25
11.47
19.47
18.64
15.15
29.31
21.68
13.25
9.20
12.12
34.74
33.66
12.01
13.61
16.90
7.49
16.70
16.94
22.59
11.76
9.55
19.15
20.91
40.31
23.89
12.75
49.26
32.87
21.86
Appendix 6-2.7
-------
CO2 Production Region
MACE
CO2 Storage Region
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Cost (2007$/Ton)
16.18
17.12
15.16
29.50
12.40
24.99
27.68
12.79
22.91
31.94
30.91
30.72
45.37
38.10
6.99
9.97
28.52
48.65
50.04
7.14
14.74
30.42
15.36
31.26
29.36
38.30
9.62
10.45
33.74
18.55
38.48
21.68
10.69
47.66
31.26
19.72
13.89
15.24
13.24
27.66
10.19
22.64
25.32
11.60
20.57
30.99
29.97
29.18
Appendix 6-2.8
-------
CO2 Production Region
MACS
CO2 Storage Region
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Cost (2007$/Ton)
43.73
36.26
6.45
8.24
26.53
47.58
48.24
5.49
12.45
29.27
13.07
29.00
27.02
36.75
7.30
8.23
32.43
16.44
36.43
19.46
9.47
45.76
29.37
18.22
12.14
13.21
11.19
25.61
7.98
20.47
23.18
10.24
18.39
29.61
28.61
27.33
41.79
34.20
6.22
6.46
24.39
46.05
46.19
4.10
10.68
27.73
10.85
26.78
Appendix 6-2.9
-------
CO2 Production Region
MACW
MECS
CO2 Storage Region
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Cost (2007$/Ton)
24.84
34.89
5.40
6.02
30.75
18.02
36.52
20.34
11.63
45.53
29.13
20.31
14.14
13.33
11.38
25.71
8.92
21.83
24.66
9.25
19.72
28.62
27.60
27.00
41.62
34.31
4.24
6.18
24.75
45.23
46.26
3.35
12.68
26.94
12.01
27.78
26.20
34.58
7.16
7.03
30.15
16.68
29.60
15.92
15.62
38.19
21.83
Appendix 6-2.10
-------
CO2 Production Region
MRO
CO2 Storage Region
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
Cost (2007$/Ton)
22.17
15.84
7.49
6.33
18.94
7.85
19.10
22.23
3.25
17.07
21.14
20.13
19.62
34.33
27.44
7.11
4.97
18.56
37.67
39.24
7.16
14.68
19.37
10.21
23.33
23.15
27.18
10.10
7.73
22.60
19.01
19.94
13.69
23.49
27.89
11.66
26.95
21.76
9.29
10.96
10.29
15.09
18.68
21.50
11.53
17.42
11.90
Appendix 6-2.11
-------
CO2 Production Region
NENG
CO2 Storage Region
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
Cost (2007$/Ton)
11.07
9.34
24.07
17.93
17.48
14.76
11.48
27.61
29.28
17.42
21.18
9.43
15.05
18.97
21.26
16.81
18.68
16.31
12.27
23.42
42.41
26.33
14.98
51.13
34.79
24.11
18.58
19.32
17.41
31.63
14.85
27.50
30.19
14.53
25.42
33.26
32.21
32.59
47.30
40.21
8.58
12.16
30.77
50.04
52.11
9.37
17.16
Appendix 6-2.12
-------
CO2 Production Region
NWPE
NYC
CO2 Storage Region
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Cost (2007$/Ton)
31.93
17.84
33.71
31.88
40.15
12.11
12.91
35.40
27.91
9.77
20.78
35.44
14.70
5.96
36.36
32.67
21.61
23.58
11.09
27.62
25.29
26.89
25.00
25.18
10.32
10.93
7.21
10.98
9.06
30.95
28.06
13.98
15.84
16.89
30.80
32.53
8.96
26.57
20.66
25.42
3.71
31.39
29.15
5.44
20.30
39.63
23.21
Appendix 6-2.13
-------
CO2 Production Region
PNW
CO2 Storage Region
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Cost (2007$/Ton)
12.36
48.61
32.22
21.44
15.67
16.43
14.47
28.82
11.72
24.35
27.05
12.18
22.27
31.39
30.36
30.08
44.72
37.42
6.46
9.29
27.83
48.09
49.37
6.46
14.22
29.83
14.69
30.58
28.72
37.65
9.02
9.77
33.13
42.14
20.11
35.04
48.98
13.81
20.04
50.59
46.59
34.78
36.61
25.36
40.75
39.59
41.10
36.69
Appendix 6-2.14
-------
CO2 Production Region
RFCO
CO2 Storage Region
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
Cost (2007$/Ton)
39.46
17.43
18.47
21.01
14.85
21.07
42.34
40.36
28.28
3.25
19.55
42.86
46.30
19.07
40.20
34.51
39.51
15.41
44.36
42.03
16.74
13.04
28.50
12.94
13.05
37.78
21.38
18.74
12.54
5.27
3.35
17.68
4.66
15.63
18.73
5.43
13.56
22.47
21.53
19.37
33.79
26.28
8.87
4.60
16.70
38.47
38.25
7.40
Appendix 6-2.15
-------
CO2 Production Region
RFCP
RMPA
CO2 Storage Region
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Cost (2007$/Ton)
11.52
20.26
6.58
20.46
19.79
26.91
7.97
5.45
23.00
13.89
32.04
15.58
10.62
41.38
24.98
17.85
11.42
8.80
6.79
21.22
4.32
17.34
20.29
6.87
15.22
25.71
24.74
22.97
37.39
29.81
6.63
3.25
20.08
41.93
41.80
4.25
10.11
23.65
7.49
23.05
21.68
30.52
5.46
3.25
26.52
23.85
9.55
Appendix 6-2.16
-------
CO2 Production Region
SNV
CO2 Storage Region
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Cost (2007$/Ton)
16.71
31.63
17.46
3.49
32.29
28.72
18.09
20.10
7.05
24.03
21.22
22.89
22.12
21.10
11.42
11.64
4.18
13.38
7.86
28.07
24.84
9.92
19.92
18.51
27.64
28.64
8.93
22.77
16.93
21.49
6.49
27.84
25.67
6.65
32.28
6.22
25.26
41.46
7.58
13.07
40.30
38.00
28.82
30.84
16.51
34.55
28.58
Appendix 6-2.17
-------
CO2 Production Region
SOU
CO2 Storage Region
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Cost (2007$/Ton)
29.13
33.30
29.20
19.63
20.35
15.37
3.47
8.34
39.22
35.81
18.42
16.35
7.40
38.63
38.20
18.48
32.81
21.87
27.10
8.50
38.36
36.31
14.43
4.18
27.42
8.43
10.90
37.87
22.64
11.34
7.18
9.70
9.30
17.56
8.20
7.81
10.55
14.28
5.77
27.31
26.58
21.36
33.74
25.23
16.41
12.17
15.13
Appendix 6-2.18
-------
CO2 Production Region
SPPN
CO2 Storage Region
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Cost (2007$/Ton)
41.36
36.88
13.91
7.47
24.49
5.17
14.74
12.18
28.01
10.43
9.83
25.93
13.64
18.28
7.41
20.61
28.02
11.97
22.01
17.82
7.70
9.68
7.49
13.26
12.47
15.15
13.35
11.49
16.91
16.32
10.49
23.89
16.05
18.80
14.87
6.58
30.49
28.03
17.68
17.65
13.92
11.76
12.94
14.83
17.50
17.08
15.04
Appendix 6-2.19
-------
CO2 Production Region
SPPS
TVA
CO2 Storage Region
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Cost (2007$/Ton)
15.10
11.20
17.67
4.43
20.65
28.28
14.16
19.48
16.93
11.33
12.87
8.86
15.21
8.21
10.25
17.63
8.21
21.41
20.99
13.59
24.13
15.52
22.34
18.01
5.82
32.92
27.08
20.64
17.26
18.31
12.63
7.79
9.48
19.01
18.71
17.18
18.39
8.35
27.00
9.27
11.57
37.00
21.01
14.92
9.38
5.89
Appendix 6-2.20
-------
CO2 Production Region
TVAK
CO2 Storage Region
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
Cost (2007$/Ton)
5.11
16.43
4.98
11.03
14.09
10.09
8.93
24.27
23.45
19.38
32.90
24.77
12.91
8.49
14.64
39.25
36.71
10.73
8.86
21.65
3.25
16.66
15.30
26.56
8.43
6.94
23.64
10.73
27.75
11.08
12.03
37.41
21.13
16.77
10.78
4.94
3.25
16.98
3.82
13.38
16.47
7.71
11.30
23.31
22.43
19.30
33.35
Appendix 6-2.21
-------
CO2 Production Region
UPNY
CO2 Storage Region
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Cost (2007$/Ton)
25.51
10.73
6.29
15.60
38.86
37.51
8.79
9.94
20.88
4.40
18.59
17.60
26.71
7.66
5.56
23.27
20.03
36.09
21.28
14.72
44.58
28.28
23.17
16.86
13.43
11.72
25.39
10.47
23.46
26.43
7.98
21.34
26.70
25.66
26.05
40.78
33.92
3.25
6.70
24.84
43.46
45.73
4.90
15.43
25.31
13.63
28.78
27.77
Appendix 6-2.22
-------
CO2 Production Region
VACA
VAPW
CO2 Storage Region
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Cost (2007$/Ton)
33.58
9.76
8.90
28.77
10.50
34.30
15.62
4.12
44.44
28.53
11.33
5.19
12.80
11.12
23.89
7.14
14.99
17.26
13.65
13.12
31.22
30.33
26.88
40.35
32.07
12.49
9.80
21.89
46.66
43.93
9.72
3.74
28.79
7.53
22.16
19.21
34.09
5.81
6.77
31.03
14.71
36.20
18.50
7.13
45.84
29.54
15.91
Appendix 6-2.23
-------
CO2 Production Region
WUMS
CO2 Storage Region
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Alabama
Arizona
Arkansas
Atlantic Offshore
California Onshore
Colorado
Florida
Georgia
Illinois
Indiana
Kansas
Kentucky
Louisiana Onshore
Louisiana Offshore
Michigan
Mississippi
Montana
North Dakota
Cost (2007$/Ton)
9.93
13.24
11.24
25.45
7.42
18.94
21.50
11.51
16.92
30.58
29.61
27.61
41.82
33.96
8.42
7.43
23.95
46.77
45.95
5.91
8.48
28.52
9.77
25.61
23.29
35.10
4.65
5.67
31.30
18.36
26.16
15.53
19.56
34.18
18.00
25.05
19.02
7.54
7.86
15.92
11.21
19.69
22.81
5.49
17.89
16.61
15.61
Appendix 6-2.24
-------
CO2 Production Region
CO2 Storage Region
Nebraska
Nevada
New Mexico
New York
Ohio
Oklahoma
Oregon
Pacific Offshore
Pennsylvania
South Carolina
South Dakota
Tennessee
Texas Onshore
Texas Offshore
Utah
Virginia
West Virginia
Wyoming
Cost (2007$/Ton)
15.69
30.42
24.08
11.28
9.37
16.23
33.18
35.61
11.68
18.07
14.90
12.58
22.36
23.26
23.14
14.13
11.73
18.28
Note:
Production Regions are equal to IPM model regions
Appendix 6-2.25
-------
-------
7 Set-up Parameters and Rules
The EPA Base Case v.4.10 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.4.10 extends from 2012 through 2054 with IPM
seeking the least cost solution that meets all constraints and minimizes net present values over
this 43-year period. The six 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.4.10
Run Year
2012
2015
2020
2030
2040
2050
Years Represented
2012-2013
2014-2016
2017-2024
2025 - 2034
2035 - 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 early. The decision to
retrofit or retire is endogenous to IPM and based on the least cost approach to meeting the
system and other operating constraints included in the EPA Base Case v.4.10. IPM is capable of
modeling retrofits and early retirements in two stages, enabling model plants to install two different
sets of retrofits incrementally at different points in time. 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.4.10 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 early retirement as an option in stage 1. Second
stage retrofit options are provided to coal-steam plants only.
Table 7-2 and Table 7-3 present the first and second stage retrofit options respectively. The costs
of multiple retrofits on the same model plant, whether installed in one or two stages, are assumed
to be additive. In linear programming models like IPM, projections of pollution control equipment
capacity and early retirements that can occur over the modeling time horizon are limited to those
retrofit and retirement options that have been pre-specified when setting up the modeled scenario.
While the model decides endogenously whether and how much of each retrofit option to install, it
cannot provide a retrofit that was not pre-specified before the modeling scenario was run. Table
7-2 and Table 7-3 show all the retrofit options available in EPA Base Case v.4.10.
7-1
-------
Table 7-2 First Stage Retrofit Assignment Scheme in EPA Base Case v.4.10
Plant Type
Coal Steam
Combined
Cycle
Combustion
Turbine
Nuclear
Oil and Gas
Steam
Retrofit Option 1st Stage
Coal Early Retirement
Coal Steam SCR
Coal Steam SNCR -
Cyclone Boilers
Coal Steam SNCR - Non
Cyclone Boilers and Non
FBC Boilers
Coal Steam SNCR - FBC
Boilers
LSD Scrubber
LSFO Scrubber
CO2 Capture and Storage
ACI - Hg Control Option
(MPAC/ SPAC/ SPAC+
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
CC Early Retirement
CT Early Retirement
Nuclear Early Retirement
Oil/Gas Early Retirement
Oil and Gas Steam SCR
Criteria
All coal steam boilers
All coal steam boilers that are 25 MW or larger and
do not possess an existing SCR control option
All cyclone 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 non cyclone and non FBC coal steam boilers
that are 25 MW or larger and smaller than 1 00 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 and non FBC coal steam boilers 25
MWor larger and burning less than 3 Ibs/MMBtu
SO2 coal
All unscrubbed and non FBC coal steam boilers 25
MWor larger
All scrubbed coal steam boilers 400 MWor larger
All coal steam boilers larger than 25 MWthat 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
All combined cycle units
All combustion turbine units
All nuclear power units
All O/G steam boilers
All O/G steam boilers 25 MW or larger that do not
possess an existing post combustion NOX control
option
7-2
-------
Table 7-3 Second Stage Retrofit Assignment Scheme in EPA Base Case v.4.10
Plant Type
Coal Steam
Retrofit Option 1st Stage
NOX Control Option1
SO2 Control Option2
Hg Control Option3
CO2 Control Option4
NOX Control Option1 + SO2 Control Option2
NOX Control Option1 + Hg Control Option3
SO2 Control Option2 + Hg Control Option3
NOX Control Option1 + SO2 Control Option2
+ Hg Control Option3
Retrofit Option 2nd Stage5
SO2 Control Option and/or Hg
Control Option and/or CO2 Control
Option
NOX Control Option and/or Hg
Control Option and/or CO2 Control
Option
CO2 Control Option
None
Hg Control Option
CO2 Control Option
CO2 Control Option
CO2 Control Option
Notes:
1"NOX Control Option" implies that a model plant may be retrofitted with one of the following NOX
control technologies:
SCR, SNCR - cyclone, SNCR - non-cyclone, or SNCR - FBC
2"SO2 Control Option" implies that a model plant may be retrofitted with one of the following SO2
control technologies:
LSFO scrubber or LSD scrubber
3"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:
MPAC, SPAC, or SPAC + Toxecon
4"CO2 Control Option" implies that a model plant may be retrofitted with carbon capture and
storage technology
5 Retrofits with multiple 2nd stage options may install any combination of the listed options.
7.3 Trading and Banking
Four regional or national environmental air regulations included in EPA Base Case v.4.10 involve
trading and banking of emission allowances47: NOX SIP Call program, the Title IV SO2 program,
the West Region Air Partnership's (WRAP) program regulating SO2 (as part of the federal
Regional Haze Rule), and the Regional Greenhouse Gas Initiative (RGGI) for CO2. Table 7-4
below summarizes the key parameters of these four trading and banking programs as
incorporated in EPA Base Case v.4.10. Trading and banking are modeled on a U.S. system-wide
basis for the Title IV SO2 program and on a regional basis for the other three programs. EPA
Base Case v.4.10 does not include any explicit assumptions on the allocation of emission
allowances among model plants under any of the four programs.
47For a detailed discussion of the assumptions of all the environmental air regulations included in
the EPA Base Case v.4.10, see chapter 3.
7-3
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Table 7-4 Trading and Banking Rules in EPA Base Case v.4.10
Coverage
Timing
Size of
Initial Bank
Total
Allowances
(MTons)
SIP Call -
Ozone
Seasons NOX
All fossil units
> 25 MW1
Ozone Season
(May-
September)
The bank
starting in 201 2
is assumed to
be zero
2012-2054:
527.5
Title IV - S02
All fossil units
>25MW
Annual
The bank starting
in 201 2 is
assumed to be 1 1
million tons
2012: 19,679
2013: 8,407
2014: 8,397
2015: 8,327
2016: 8,312
2017: 8,287
2018: 8,169
2019: 8,155
2020-2054:8,153
WRAP- S02
All fossil units
>25MW2
Annual
The bank
starting in 201 8
is assumed to
be zero
2018-2054:
144.7
RGGI - C02
All fossil units
>25MW3
Annual
The bank starting in
2012 is assumed to
be zero
2012-2014: 188,077
2015: 183,375
2016: 178,673
2017: 173,971
2018-2054: 169,269
Notes:
1 Alabama, Connecticut, Delaware, District of Columbia, Illinois, Indiana, Kentucky, Maryland,
Massachusetts, Michigan, Missouri, New Jersey, New York, North Carolina, Ohio,
Pennsylvania, Rhode Island, South Carolina, Tennessee, Virginia, West Virginia
2 Arizona, New Mexico, Oregon, Utah, Wyoming
3 Connecticut, Delaware, Maine, New Hampshire, New Jersey, New York, Vermont, Rhode
Island, Massachusetts, Maryland
7.4 Post-2030 Modeling Assumptions and Capabilities
Previous EPA base cases had at most a usable modeling time horizon out to year 2030. EPA
Base Case v.4.10 has the capability to model out to 2050. However, bottom up models like IPM,
which is used to build the EPA base case, require input data at the finest possible level of
granularity. Preferably, such data would be based on gathered information obtained through
regulatory submittals, surveys, and scientific, engineering, economic, and commercial
assessments specifically related to the particular characteristics of the issue being modeled. Past
2030 or 2035 such information is rarely available.
As a result, a two tiered approach was taken to the inputs used to build EPA Base Case v.4.10.
Prior to 2030 assumptions would be based to the greatest extent possible on verifiable empirical
data gathered from the best available sources vetted using cross-checks against alternative data
sources. Beyond 2030 a pragmatic approach was taken. Where credible empirical data was
available, it would be used. Where empirical data was not available, technically plausible,
explicitly articulated assumptions would be used to extrapolate pre-2030 assumptions out to 2050.
While perhaps not optimal, such an approach was seen as potentially valuable, if only because it
would focus attention on the long-range assumptions needed for bottom-up modeling and, in
doing so, elicit comments from the interested public and technical experts. This could lead to
future improvements in the long-range inputs with possible side benefits for all projections whether
based on bottom-up, top-down or hybrid modeling approaches.
A corollary of this two tiered approach to input assumptions is that the modeling results past 2030
should be viewed somewhat differently from those prior to 2030. The pre-2030 modeling results
7-4
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are expected to bear scrutiny at a fine level of granularity (answering questions like the plausibility
of a particular generating unit being retrofit with a dry SO2 scrubber and a SCR in a particular
model run year or of another generating unit being retired by IPM in a certain year).
The post-2030 modeling results are not intended to be examined at such a fine grain level.
Instead, the post-2030 modeling capability is designed to serve two purposes: The first purpose is
to ensure that EPA Base Case v.4.10 takes into account the potential impact of post-2030 policy
provisions on pre-2030 modeling results. For example, it would be useful to have the capability to
project the impact on pre-2030 modeling results of a provision in a Climate Change bill that takes
effect in 2042. The second purpose is to give a broad sense of directional trends beyond 2030.
For example, using current technology cost and performance assumptions, the long-range
modeling capability could provide a picture of the likely composition of the power sector in 2040 or
2050 with and without policy intervention. To take fuller advantage of this capability, five generic
placeholder future generation technologies have been included in EPA Base Case v.4.10. While
not playing a role in the base case itself, their presence allows a user to define their cost and
performance characteristics at a later time and to perform sensitivity analysis to see the possible
impact of new technologies on post-2030 trends.
Table 7-5 shows the underlying post-2030 modeling assumptions incorporated in EPA Base Case
v.4.10 for key modeling parameters.
Table 7-5 Post-2030 Assumptions in EPA Base Case v.4.10
Topic
Post-2030 Assumptions
POWER SYSTEM OPERATION
Model Regions
Electric Load Modeling
Electric Load Growth
Net Internal Demand (Peak Demand)
Load Duration Curves (LDCs)
Transmission
Interregional Transmission Capability
Transmission Link Wheeling Charge
Transmission Losses
International Imports
Mexico
Canada
Capacity, and Dispatch
Availability
Capacity Factor
Turndown
Reserve Margins
Power Plant Lifetimes
Existing Environmental Regulation
SO2 Regulations
Same as pre-2030
Post 2035 growth rate is based on AEO
2010 2025-2035 growth rate
Post 2035 growth rate is based on AEO
2010 2025-2035 growth rate
2007 load curves adjusted to post 2030
energy and peak load projections. LDCs
include six segments per season in run
years 2012, 2015, 2020, and 2030 and
four segments in 2040 and 2050.
Same as pre-2030
Same as pre-2030
Same as pre-2030
Same as 2030
Endogenously Modeled
Same as pre-2030 for all plant types
except nuclear
Same as 2030 for nuclear
Same as 2030
Same as pre-2030
Same as pre-2030
Same as pre-2030
Same as 2030
7-5
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Topic
NOX Regulations
State Specific Environmental Regulations
New Source Review (NSR)
Emission Assumptions for Potential (New) Units
Capacity Deployment Constraints
Post-2030 Assumptions
Same as 2030
Same as 2030
Same as 2030
Same as pre-2030
Run year specific
GENERATING RESOURCES
National Electric Energy Data System (NEEDS)
Existing Units and Planned/Committed Units
Population of Existing Units
Capacity
Plant Location
Online Year
Unit Configuration
Model Plant Aggregation
Cost and Performance of Existing Units
Heat Rates
NOX Rates
Potential Units
Cost and Performance of Potential Conventional
Technologies
Cost and Performance of Potential Renewable
Technologies
Biomass
Wind
Solar
Geothermal
Landfill Gas
Short Term Cost Adder
Regional Adjustment Factor
Nuclear Units
Existing Nuclear Units
VOM and FOM Cost Assumptions for
Nuclear Units
Nuclear Upratings (MW)
Nuclear Scheduled Retirements (MW)
Potential Nuclear Units
Same as pre-2030
Same as pre-2030
Same as pre-2030
Same as pre-2030
Same as pre-2030
Same as pre-2030
Same as pre-2030
Same as pre-2030
Same as pre-2030
Same as pre-2030
Same as pre-2030
Same as 2030
Same as 2030
Same as 2030
Same as pre-2030
Same as 2030
None
Same as pre-2030
Same as pre-2030 (adjusted for life
extension costs)
None
Retirement at age 60 years
Same as 2030
EMISSION CONTROL TECHNOLOGIES
Sulfur Dioxide Control Technologies
Limestone Forced Oxidation (LSFO)
Lime Spray Drying (LSD)
FGD Engineering Cost Equations
Nitrogen Oxides Control Technology
Combustion Controls
Post-combustion Controls
SCR and SNCR Engineering Cost Equations
Mercury Control Technologies
Mercury Content of Fuels
Same as pre-2030
Same as pre-2030
Same as pre-2030
Same as pre-2030
Same as pre-2030
Same as pre-2030
Same as pre-2030
7-6
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Topic
Post-2030 Assumptions
Mercury Emission Modification Factors
Mercury Control Capabilities
ACI Engineering Cost Equations
CO2 Sequestration
CO2 capture
CO2 transport
CO2 storage cost curves
Same as pre-2030
Same as pre-2030
Same as pre-2030
Same as pre-2030
Same as pre-2030
Same as pre-2030
SETUP PARAMETERS AND RULES
Run Year Mapping
Retrofit Assignments
Run year specific
Same as pre-2030
FINANCIAL ASSUMPTIONS
Methodology
Capital Charge Rates for Investments
Discount Rate for Capital and Non-Capital Costs
Same as 2030
Same as pre-2030
FUEL ASSUMPTIONS
Coal
Coal Markets
Coal Supply Curves
Coal Transportation Costs
Coal Assignments
Emission Factors
Natural Gas
Resources Data and Reservoir Description
Field Development and Production Forecast
Methodology
Lower 48 States U.S. Resources
Canada Resources
Treatment of Frontier Resources
Exploration and Production (E&P) Technology
Characterization
End Use Demand Characterization
Pipeline and Transport
Existing pipelines
Potential pipeline costs
Emission Factors
Fuel Oil
Prices
Emission Factors
Biomass
Biomass Supply Curves
Emission Factors
Nuclear Fuel Prices
Same as pre-2030
2030 cost-adjusted for labor productivity
2030 cost-adjusted for fuel price changes
Same as pre-2030
Same as pre-2030
Same as pre-2030
Same growth as pre-2030
Same growth as pre-2030
Alaska North Slope starts 2040
Same as 2030
Same growth as pre-2030
Same as pre-2030
Same growth as pre-2030
Same as pre-2030
Same as 2035
Same as pre-2030
Same as 2035
Same as pre-2030
Same as 2030
7-7
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8 Financial Assumptions
This chapter presents the financial assumptions used in EPA Base Case v.4.10. The first section
gives a summary of each of the key financial parameters. The remainder of the chapter presents
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.
8.1 Summary of Key Financial Parameters
8.1.1 Capital Charge Rate, Book Life, and Discount Rate for Capital Expenditures
EPA Base Case v.4.10 models a diverse set of generation and emission control technologies,
each of which requires financing.1 Table 8-1 presents the capital charge rate, discount rate, and
book life assumptions for the technologies in base case v.4.10. As will be discussed more fully
later in this chapter, the capital charge rate is used to convert the capital cost of a technology into
a stream of levelized annual payments that ensure capital recovery. The discount rate is used to
translate future cash flows into current dollars by taking into account factors (like inflation and the
ability to earn interest), which make one dollar tomorrow worth less than one dollar today. The
discount rate allows inter-temporal tradeoffs and represents the risk adjusted time value of money.
The book life is the payback period on an investment.
There are several things to note about Table 8-1. The technology differentiated capital charge
rates are used in v.4.10 to derive the associated capital charge rates shown in the table.
However, while the technology-differentiated discount rates appearing in the table were used in
deriving these capital charge rates, in EPA Base Case v.4.10 a single U.S. discount rate of 6.15%
is used across all technologies.
1 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.
8-1
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Table 8-1 U.S. Discount Rates and Capital Charge Rates in EPA Base Case v4.10
Investment Technology
Environmental Retrofits
Advanced Combined Cycle
Advanced Combustion Turbine
Supercritical Pulverized Coal and Integrated Gasification
Combined Cycle without Carbon Capture1
Advanced Coal with Carbon Capture
Nuclear without Production Tax Credit (PTC)
Nuclear with Production Tax Credit (PTC)2
Biomass with ARRA Loan Guarantees3
Biomass without ARRA Loan Guarantees
Wind and Landfill Gas with ARRA Loan Guarantees2
Wind and Landfill Gas without ARRA Loan Guarantees
Solar and Geothermal with ARRA Loan Guarantees2
Solar and Geothermal without ARRA Loan Guarantees
Capital
Charge Rate
1 1 .3%
12.1%
12.9%
14.1%
11.1%
10.8%
9.1%
9.3%
11.1%
10.1%
12.2%
10.1%
12.2%
Discount
Rate
5.5%
6.2%
6.9%
7.8%
5.5%
5.5%
5.5%
4.6%
6.2%
4.6%
6.2%
4.6%
6.2%
Book
Life
30
30
30
40
40
40
40
40
40
20
20
20
20
Notes:
The discount rates appearing in the table were used in deriving these capital charge rates.
However, as noted in the text, a single U.S. discount rate of 6.15% is used across all
technologies in EPA Base Case v.4.10.
1The capital charge rate for these technologies includes a 3% climate change uncertainty
adder. (See text.)
2The capital charge rate for this technology reflects the impact of the PTC provided under the
Energy Policy Act of 2005. (See text.)
3The capital charge rate for these technologies reflects the impact of ARRA loan guarantees.
(See text.)
Capital Cost Adder for Climate Change Uncertainty: Adopting the procedure followed in ElA's
Annual Energy Outlook 2010, the capital charge rates shown in Table 8-1 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 section 8.2.3 for discussion of debt and
equity). This capital cost adder reflects increased financing costs for investment decisions
involving coal plants without carbon capture caused by uncertainty surrounding possible future
climate change policies that could limit CO2 emissions from the power sector
ARRA Loan Guarantees for Renewables and Biofuels: The American Recovery and
Reinvestment Act (ARRA) of 2009 (Public Law 111-5) provides loan guarantees for renewables
and biofuels. Following the procedure implemented in AEO 2010, these loan guarantees are
reflected in a reduction of 2% in the cost of debt and equity for biomass, wind, landfill gas, solar,
and geothermal technologies. Capital charge rates with and without the 2% reduction appear in
Table 8-1 because the loan guarantees expires in 2016.
Energy Policy Act Production Tax Credit for Nuclear: 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 MWof new nuclear capacity. The financial impact of the credit is reflected in
the capital charge rate shown in Table 8-1 for "Nuclear with Production Tax Credit (PTC)."
8.1.2 ARRA Production and Investment Tax Credit (PTC and ITC) for Renewables
In addition to the loan guarantees that are reflected in the capital charge rates for renewables
shown in Table 8-1, ARRA 2009 (Division B, Title I, Sec. 1101, 1102, and 1603) also provides
extensions of the PTC and 30 percent ITC to renewables. These are represented in EPA Base
Case, v.4.10 as a 30% reduction in the capital cost of these technologies in 2012.
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8.1.3 Discount Rate for Non-Capital Expenditures
The discount rate for non-capital expenditures (e.g., annual fuel, variable operations and
maintenance, and fixed operations and maintenance costs) in EPA Base Case v.4.10 is assumed
to be 6.15%. This serves as the default discount rate for all non-capital expenditures.
8.1.4 Inter-temporal Allowance Price Calculation
Under a perfectly competitive cap-and-trade program that allows banking, 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.
The EPA Base Case v.4.10 uses the default discount rate of 6.15 percent in computing the
increase in allowance price for cap-and-trade programs when banking is engaged as a
compliance strategy.
8.1.5 Nominal and Real Dollars
EPA Base Case v.4.10 uses real 2007 dollars as its real dollar baseline. See Chapter 2 for further
discussion on how IPM uses the real dollars for inter-temporal analysis.
8.2 Development of the Financial Assumptions for EPA Base Case v.4.10
This section explains the method used to derive the capital charge rate and discount rate as well
as the assumptions underlying these financial parameters.
8.2.1 Introduction
As noted in section 8.1, the discount rate and the capital charge rate are the two parameters that
encapsulate the financing assumptions for an investment option in EPA Base Case, v.4.10. The
discount rate allows inter-temporal tradeoffs and represents the risk adjusted time value of money.
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.
Discount Rate
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.
Capital Charge Rate
The capital charge rate is a function of the parameters that overlap in part with the discount rate,
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
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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
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. The capital charge rate so calculated is defined as follows:
Capital Charge Rate = EBITDA/Total Investment
In other words, the capital charge rate is the rate of return required on invested capital, resulting
from pure operations.
8.2.2 Method for Deriving Discount Rate and Capital Charge Rate in EPA Base Case v 4.10
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 approximately 35 percent
to 40 percent of capacity being deregulated IPP (Independent Power Producer) capacity. For
example, merchant IPP's selling into spot market have more market risk than regulated plants or
IPP's 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 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.
Market Structure Risks
The power sector in North America can be divided into the traditional regulated sector (as known
as "cost of service" sector) and deregulated merchant sector (as 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. 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 are less
exposed to the market than deregulated investments, all else equal. In this report, we use the
term "utility financing" to refer 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.
Deregulated Merchant - In a deregulated merchant market structure, investments bear the
full or a very high degree of market risk as the price that they can sell electricity at 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
8-4
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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 to the sector. The operational cash flows
from investments in this sector are more volatile as compared to in the traditional regulated
sector, and hence, carry more business or market risk. In this report, we use the term
"merchant financing" to refer to this type of market structure.
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.
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 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.
Project finance, as this category of financing is often labeled, 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 it defaults on the loan, debtors have recourse only to the project itself and not
against the larger holdings of the project developer. This approach can be more risky than
corporate finance, all else being equal, because there is less diversification than the
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.
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 facel.
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 used 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 financing2 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 should be based on IPP and utility
corporate financing.
1 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
2Project Financing data is less observable as it's not explicitly traded. Also, often key financing
parameters are unavailable due to confidentiality reasons.
8-5
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Approach to Market Structure Risk
In EPA Base Case 4.10, a hybrid financing model is used, i.e., it is assumed that future
development activity would be roughly evenly split 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 contractsS. In this
approach, for modeling purposes, we assume that new units are financed as a weighted average
of utility and merchant financing parameters. For new units we assume that both utility and
merchant components get equal weights. For retrofits, we assume that utility component gets 2/3
and merchant component gets 1/3 weight4.
Example 1: The debt to equity capital structure of a combustion turbine is 55/45 under utility
financing and 30/70 under merchant financing. Under the assumption that utility and
merchant components get equal weights, the debt to equity ratio under hybrid financing is D =
(55 + 30)/2 = 42.5 / E = (45 + 70)/2 = 57.5.
Example 2: The debt to equity capital structure of a retrofit is 55/45 under utility financing and
45/55 under merchant financing. Under the assumption of a 2/3, 1/3, utility/merchant
weighting, the debt to equity ratio under hybrid financing is D = (55 * 2/3) + (45 * 1/3) = 51.6 /
E = (45 * 2/3) + (55 * 1/3) = 48.3. A full summary for all technologies appears in Table 8-2
below.
Capital Charge Rate - A More Detailed Description
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. The capital charge rate so calculated is defined as follows:
Tabl
e 8-2 Capital Structure Assumptions for EPA Base Case v4.10
Technology
Combustion Turbine
Combined Cycle
Coal & Nuclear
Renewables
Retrofits
Utility
55/45
55/45
55/45
55/45
55/45
Merchant
30/70
45/55
60/40
45/55
45/55
Hybrid
42.5/57.5
50/50
57.5/42.5
50/50
51.7/48.3
Capital Charge Rate = EBITDA/Total Investment
In other words, the capital charge rate is the rate of return required on invested capital, resulting
from pure operations.
3An 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 or 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 is extremely complex, a hybrid
approach is used.
4Retrofits are largely associated with coal fired plants and most coal fired plants are currently
owned and operated by utilities in a "utility financing" structure. Moreover, since the magnitude of
the retrofit investment is not as large as a plant investment, the financing of a retrofit is more likely
to happen from a firm's internal cash flows instead of external financing.
8-6
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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 equityS are calculated as follows:
Cash Flows to Equity = EBIT (1-tax rate)
- Interest (1-tax rate)
+ Depreciation
- Capital Expenditures
- Working Capital Change
- Principal Payments
+ New Debt Issued
Discount Rates and Capital Charge Rates
Based on the above approach, the discount rates and capital charge rates summarized in Table
8-1 above were obtained for investments in the U.S. The procedures and assumptions used to
calculate the rates in Table 8-1 are discussed in the sections below.
8.2.3 Calculation of the Hybrid Capital Charge Rates
ROE
The first step was the calculation of a return on equity (ROE) using an average ROE under utility
financing (10.3%) and merchant financing (15.2%) assuming a 50:50 debt/equity ratio. This
resulted in a ROE of 12.75%6. This ROE is kept the same across each technology? but the risk
differences across technologies are implemented through the capital structure. See the discussion
of capital structures in this subsection under "Debt Equity Share" and the discussion of "Debt and
Equity Shares and Technology Risk" in section 8.2.4.
Note that a 50:50 mix (corresponding to the hybrid capital structure for a combined cycle - see
Table 8-2) has been chosen. This is because we assumed that the overall IPP risk was on
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 companies8 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 was considered
appropriate to use the ROE corresponding to a combined cycle facility.
5An alternative definition of free cash flow to equity is as follows: Net Income + Depreciation -
capital expenditures -working capital change - Principal Payments + New Debt Issued
6The Pennsylvania-New Jersey-Maryland Interconnection (PJM) uses a 12% ROE for a combined
cycle at a 50:50 debt/equity ratio to calculate the cost of new entry (CONE) for their capacity
markets. Hence, the estimates are fairly close to those used by a major RTO.
7Even though ROE is kept the same across all technologies, it doesn't mean that the market risks
are considered the same for each technology. See capital structure discussion in the next
paragraph.
8Our merchant parameters are derived from market observations of five IPP companies - see
discussion on development of merchant financed parameters.
8-7
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Debt Equity Share
Second, the capital structures (D/E)9 for the various technology types were calculated using an
average of utility and merchant financing. 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. The merchant debt capacity is based on market risk where
a base load plant is likely to have a higher debt capacity than a combustion turbine plant. Table
8-2 presents the capital structure assumptions used in EPA Base Case v4.10.
The risk differences across technologies are implemented by varying the capital structure. As
shown in Table 8-2 and discussed above, a peaking unit such as a combustion turbine is
estimated to have a capital structure of 42.5/57.5 while a base load unit such as nuclear and coal
is assumed to have a capital structure of 57.5/42.5. This is based on the intuition that less risky
technologies can carry more leverage. As debt is less expensive than equity, this will
automatically translate into a lower capital charge rate (and a lower discount rate) for base load
technologies and a higher capital charge rate (and a higher discount rate) for peaking technology,
assuming other components of the capital charge rate calculation remain the same.
Cost of Debt
Third, the cost of debt was adjusted to reflect the average cost of debt for utility and merchant
financings for each technology. The utility cost of debt is assumed to be the same across all
technologies while the merchant cost of debt is higher than utility and is higher for a combustion
turbine unit than for a combined cycle or a coal plant. Table 8-3 summarizes the debt rates used
in EPA Base Case v4.10.
Table 8-3 Debt Rates for EPA Base Case v4.10
Technology
Combustion Turbine
Combined Cycle
Coal & Nuclear
Wind
Retrofits
Utility
6.25%
6.25%
6.25%
6.25%
6.25%
Merchant
9%
8%
8%
8%
8%
Hybrid
7.63%
7.13%
7.13%
7.13%
6.83%
These financing parameters were then combined with taxation assumptions and technology
specific assumptions on depreciation, book life and debt life to yield the capital charge rates
outlined in Table 8-1 above.
8.2.4 Development of Merchant Financing Parameters
Merchant ROE
The Independent Power Producer (IPP) return on equity parameter was estimated to be 15.2%10.
This was based on empirical analysis of stock price data of five pure play comparable merchant
generation companies, namely Reliant, NRG, Dynegy, Mirant, and Calpine. First, levered betas11
(a measure of total corporate risk which includes business and financial risk) for the five
companies were calculated using five years of historical stock price data. Second, unlevered
betas (a measure of business risk, i.e., those affected by a firm's investment decisions) were
9A 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.
10Merchant ROE, as additionally observed by EIA, have risen overtime.
11Levered beta is directly measured from the company's stock returns with no adjustment made
for the debt financing undertaken by the company. It is also known as equity beta. Hence, levered
beta incorporates both business and financing risk undertaken by the company.
8-8
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calculated using the estimated levered beta, the companies' market debt/equity ratio, and the
riskiness of debt. As most comparables historically had periods of financial distress, the
unlevering12 approach was modified to include the riskiness of debt, instead of purely using the
Hamada equation.13 The unlevered betas were then relevered14 at the target debt/equity ratio of
50/50 to get the relevered equity betas and return on equity. 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 Rate based on 20 year T bond rate: 4.9%15
Market Risk Premium 1926-200616 7.1%
Size Premium: 0.65%17
The estimation of the IPP ROE described here is fairly close to what EIA has published. EIA
estimates a 2010 ROE of roughly 14.8% at a D/E ratio of 45/55 and increasing to approximately
16% by 2012.18
Merchant Cost of Debt
The cost of debt for the merchant sector was computed assuming an average 3-month LIBOR
(London Interbank Offered Rate) of 4.9-5% and an average spread of 3% reflecting the low
medium grade or low grade nature of merchant bonds. An additional one percent spread was
assumed for combustion turbine units due to the high price risk for combustion turbine units.
Debt and Equity Shares and Technology Risk
The capitalization structure for merchant financings was estimated to be 45/55 based on empirical
analyses. This capitalization structure was assumed to be on average reflective of the combined
cycle for reasons discussed earlier in this document.
Each generation technology was considered to have its own risk profile. Some evidence indicated
that the greater the base load share, the lower the asset risk. This is consistent with having
revenues that are more related to variable cost advantages as well as the value of capacity as
opposed to peaking units which are more dependent on scarcity or capacity revenue, which, in
turn, has very high systemic risk.
There are two main mechanisms for reflecting the greater risk for peakers 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 peakers, and lower for base load. For example, an unlevered beta and
12The 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.
13The 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)."
14The 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
15Federal Reserve Statistical Release (H15 data), May 2007
16Source: Stocks, Bonds, Bills, and Inflation, 2007 Yearbook Valuation Edition,
Morningstar/lbbotson's Associates
17Source: Stocks, Bonds, Bills, and Inflation, 2007 Yearbook Valuation Edition,
Morningstar/lbbotson's Associates
18See Electricity Market Module of NEMS, EIA Annual Energy Outlook, May 2009
8-9
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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 was the
adopted approach. Thus, even though the leverage of peakers was lowered, the ROE was not
lowered. This raised the weighted average cost of capital and the resulting capital charge rate.
This effectively also raised the unlevered beta for peakers relative to combined cycle. For base
load, leverage was raised without raising ROE, effectively lowering the unlevered beta and the
cost of capital.
8.2.5 Development of Utility Financing Parameters
Utility ROE
The utility return on equity was calculated to be 10.3%. This was based on empirical analysis of
correlation of returns on the S&P utility Index vs. the broader S&P 500 market index for the last
five years to determine the levered beta and then unlevering and relevering based on a process
similar to that for merchant sector. The ROE is also consistent with what state commissions have
awarded the shareholder-owned electric utilities recently.19
Utility Cost of Debt
The cost of debt for the utility sector was estimated to be 6.25%. The utility bonds were
categorized into various credit rating rungs based on information obtained from the Edison Electric
Institute.20 Historical yields were analyzed for the various rungs based on data obtained from
Bloomberg. A weighted average cost of debt was then determined based on the historical yields
and percentages of utility credit rating classes. The estimated value was also corroborated against
the yield to maturity of Moody's average utility bond index.
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.
Technology Risks
For the utility financing, we assumed that the required returns for regulated utilities are
independent of technology. This assumption was a simplifying assumption, and further empirical
work may be warranted here.
8.2.6 Development of Other Parameters
Taxation and Insurance Costs
Corporate and State Income Taxes: The maximum US corporate income tax rate is 35%.21 State
taxes vary but on a national average basis, the state taxes are 6.50%.22 This yields a net effective
tax rate of 39.3%.
19See page 35, 2006 Financial Review, Annual Report of the U.S Shareholder Owned Electric
Utility Industry
202006 Financial Review, Annual Report of the U.S Shareholder Owned Electric Utility Industry
21 Internal Revenue Service, Publication 542.
22Population weighted average based on 2008 state taxes information available at Federation of
Tax Administrators, ttp://www.taxadmin.org/fta/rate/corp_inc.html.
8-10
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State Property Taxes: 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: Insurance costs are approximately 0.3%. This is based on estimates of
insurance costs on a national average basis.
Inflation
The inflation rate of 2.25% is based on an assessment of implied inflation from an analysis of
yields on 5 year and 10 year Treasury securities and Treasury Inflation Protected Securities
(TIPS).
Book life, Debt Life and Depreciation
Table 8-4 presents a summary of various assumed lives at the national level.
Table 8-4 Book Life, Debt Life and Depreciation Schedules for EPA Base Case v. 4.10
Technology
Combined Cycle
Combustion Turbine
Coal Steam and IGCC
Nuclear
Solar and Geothermal
Biomass
Wind and Landfill Gas
Retrofits
Book Life
(Years)
30
30
40
40
20
40
20
30
Debt Life
(Years)
20
15
20
20
20
20
20
20
US - MACRS
Depreciation Schedule
20
15
20
15
5
7
7
20
Book Life or Useful Life of Plant:
The book life or useful life of a plant was estimated based on researching financial statements of
utility and merchant generation companies. The financial statements23 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 years schedule except in the case of combustion
turbine where debt life is lower.
Depreciation Schedule:
The US MACRS24 depreciation schedules were obtained from IRS Publication 94625 that lists the
schedules based on asset classes. The document specifies a 5 years 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 at 15 years as well.
23SEC 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
24MACRS 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.
25IRS Publication 946, "How to Depreciate Property", Table B-2, Class Lives and Recovery
Periods.
8-11
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-------
9 Coal
The next three chapters cover the representation and underlying assumptions for fuels in EPA
Base Case v.4.10. 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.4.10. 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.4.10 and the
painstaking 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 84 coal supply curves that are implemented in EPA
Base Case v.4.10. Illustrative examples are included of the step-by-step approach employed in
developing a 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 September
2008, 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): PA Consulting Group
(coal transportation and team coordination), Wood Mackenzie (coal supply curve development),
Hellerworx (coal transportation and third party review), and ICF Consulting (representation in
IPM). The coal supply curves and transportation matrix implemented in EPA Base Case v.4.10
are included in appendices at the end of this chapter.
9.1 Coal Market Representation in EPA Base Case v.4.10
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.4.10. 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 power plant modeled is assigned to one of 151 coal demand regions. The demand
regions are defined to reflect the coal transportation options (rail, barge, truck, conveyer belt) that
are available to the plants that they serve. These demand regions are interconnected by a
transportation network to at least one of the 31 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.4.10 the endogenous demand for coal is generated by coal fired power
plants interacting with a set of exogenous supply curves (see Appendix 9-4 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 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
Appendix 9-3 for coal transportation matrix data) also factors into the final determination of
9-1
-------
delivered coal prices, given coal demand and supply. IPM derives the equilibrium coal
consumption and prices that result when all electric system 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 31 coal supply regions in EPA Base Case v.4.10, 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.4.10. 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
Central Appalachia
Central Appalachia
Central Appalachia
Central Appalachia
Dakota Lignite
Dakota Lignite
East Interior
East Interior
East Interior
East Interior
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
Western Montana
Western Montana
Western Wyoming
Wyoming Northern PRB
Wyoming Southern PRB
State
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
Kansas
Oklahoma
Montana, Bull Mountains
Montana, Powder River
Wyoming, Green River
Wyoming, Powder River Basin
Wyoming, Powder River Basin
Supply Region
KE
TN
VA
WS
ME
ND
IL
IN
KW
MS
LA
TX
MD
OH
PC
PW
WN
CG
CR
CU
UT
AL
AZ
NS
KS
OK
MT
MP
WG
WH
WL
9-2
-------
Figure 9-1 Map of the Coal Supply Regions in EPA Base Case v.4.10
WfeStern torthem
9.1.2 Coal Demand Regions
Coal demand regions are designed to reflect coal transportation options available to power plants.
Existing coal plants with similar transportation infrastructures (i.e., rail, barge, or truck/conveyor
belt), proximity to mine (i.e., mine mouth or not mine mouth), transportation competitiveness levels
(i.e., non-competitive, low-cost competitive, or high-cost competitive), and within the same
geographic area are grouped into a coal demand region. Table 9-2 below lists the 135 coal
demand regions used in EPA Base Case v.4.10 by code and descriptive name.
When IPM is run, it determines the amount and type of new generation capacity to add within
each of IPM's 32 model regions. These model regions reflect the administrative, operational, and
transmission geographic structure of the electricity grid. Since the coal demand regions do not
typically coincide or overlap with the IPM model regions, new coal plants that IPM "builds" in
specific model regions must be assigned to a particular coal demand region. The IPM-region-to-
coal-demand-region assignments for new coal generating capacity are indicated in column 3 of
Table 9-2. Also shown in the last column of Table 9-2 are instances where only one existing
power plant is contained in a coal demand region. Forty-seven of the coal demand regions contain
only one power plant.
Table 9-2 Coal Demand Regions in EPA Base Case
Coal
Demand
Region
Codes
ALR1
ALR2
ALR3
AMM1
Descriptive Name
Alabama High-Cost Competitive_Not
Mine Mouth Rail
Alabama Low-Cost Competitive_Not
Mine Mouth_Barge
Alabama Low-Cost Competitive_Not
Mine Mouth Rail
New Mexico High-Cost
Competitive Mine Mouth Rail
IPM Model
Regions with
Potential Plants
Assigned to this
Coal Demand
Region
~
~
~
-
Plant Name when
Coal Demand
Region Just
Includes One Plant
Greene County
Plant
E C Gaston Plant
9-3
-------
Coal
Demand
Region
Codes
AMM2
AMM4
AMM5
AMN1
AMN2
AMN3
CAM
CAI2
CAI3
CAR1
CAR2
CARS
CC1
CC2
CCS
CU1
CU2
CU4
DAL1
DAL2
DAL4
EIM1
EIM2
Descriptive Name
Arizona, New Mexico High-Cost
Competitive_Not Mine Mouth_Rail
New Mexico Low-Cost
Competitive_Mine
Mouth_Truck/Conveyor Belt
New Mexico Low-Cost Competitive_Not
Mine Mouth_Truck/Conveyor Belt
Arizona High-Cost Competitive_Not
Mine Mouth Rail
Arizona Low-Cost Competitive_Not Mine
Mouth Rail
Arizona Non-Competitive_Not Mine
Mouth Rail
Virginia High-Cost Competitive_Not
Mine Mouth Rail
Kentucky Low-Cost Competitive_Not
Mine Mouth Rail
Kentucky Low-Cost Competitive_Not
Mine Mouth_Truck/Conveyor Belt
North and South Carolina High-Cost
Competitive_Not Mine Mouth_Rail
North and South Carolina Low-Cost
Competitive_Not Mine Mouth_Rail
North and South Carolina Non-
Competitive_Not Mine Mouth_Rail
Colorado High-Cost Competitive_Not
Mine Mouth Rail
Colorado Low-Cost Competitive_Not
Mine Mouth_Truck/Conveyor Belt
Colorado Non-Competitive_Not Mine
Mouth Rail
Utah High-Cost Competitive_Not Mine
Mouth Rail
Utah Low-Cost Competitive_Mine
Mouth_Truck/Conveyor Belt
Utah Non-Competitive_Not Mine
Mouth Rail
North Dakota High-Cost
Competitive_Mine
Mouth_Truck/Conveyor Belt
Montana, North Dakota Low-Cost
Competitive_Mine
Mouth_Truck/Conveyor Belt
North Dakota Non-Competitive_Not
Mine Mouth Rail
Iowa, Missouri High-Cost
Competitive_Not Mine Mouth_Rail
Iowa Low-Cost Competitive_Not Mine
IPM Model
Regions with
Potential Plants
Assigned to this
Coal Demand
Region
~
~
~
~
~
AZNM
~
~
~
~
~
VACA
~
~
RMPA
~
~
~
~
~
~
~
~
Plant Name when
Coal Demand
Region Just
Includes One Plant
Navajo Plant
San Juan Plant
Raton Plant
Apache Station
H Wilson Sundt
Generating Station
Tyrone Plant
KUCC Plant
Huntington Plant
Milton R Young
Plant
Prairie Creek Plant
Fair Station Plant
9-4
-------
Coal
Demand
Region
Codes
EIM3
EIM4
EIM5
FL1
FL2
FL3
GAR1
GAR2
GFB1
GFB3
GFB4
GFR1
GFR2
GFR3
GWAY
IBB1
IBB2
IBB3
IBB4
1111
III2
III3
III4
Descriptive Name
Mouth_Barge
Iowa, Missouri Low-Cost
Competitive_Not Mine Mouth_Rail
Iowa Low-Cost Competitive_Not Mine
Mouth_Truck/Conveyor Belt
Iowa, Missouri Non-Competitive_Not
Mine Mouth Rail
Florida High-Cost Competitive_Not Mine
Mouth Rail
Florida Low-Cost Competitive_Not Mine
Mouth_Barge
Florida Low-Cost Competitive_Not Mine
Mouth Rail
Georgia, Mississippi Low-Cost
Competitive_Not Mine Mouth_Rail
Georgia Non-Competitive_Not Mine
Mouth Rail
Alabama Low Cost Competitive_Not
Mine Mouth Rail
Mississippi Low-Cost Competitive_Not
Mine Mouth_Barge
Mississippi Non-Competitive_Not Mine
Mouth Rail
Mississippi, Texas High-Cost
Competitive_Not Mine Mouth_Rail
Arkansas, Louisiana, Texas Low-Cost
Competitive_Not Mine Mouth_Rail
Arkansas, Louisiana, Texas Non-
Competitive_Not Mine Mouth_Rail
Illinois, Mine Mouth
Kentucky High-Cost Competitive_Not
Mine Mouth Rail
Kentucky Low Cost Competitive_Not
Mine Mouth Rail
Indiana, Kentucky Low-Cost
Competitive_Not Mine Mouth_Barge
Illinois, Indiana, Kentucky Low-Cost
Competitive_Not Mine Mouth_Rail
Illinois, Indiana High-Cost
Competitive_Not Mine Mouth_Rail
Kentucky High-Cost Competitive_Not
Mine Mouth_Truck/Conveyor Belt
Illinois, Indiana, Kentucky Low-Cost
Competitive_Not Mine Mouth_Barge
Illinois, Indiana Low-Cost
Competitive_Not Mine Mouth_Rail
IPM Model
Regions with
Potential Plants
Assigned to this
Coal Demand
Region
~
~
~
FRCC
~
~
~
SOU
~
~
~
ERCT
~
ENTG
GWAY
~
~
~
~
~
~
~
COMD & RFCO
Plant Name when
Coal Demand
Region Just
Includes One Plant
Pella Plant
Barry Plant
Jack Watson Plant
Victor J Daniel Jr
Plant
Cane Run Plant
Mill Creek Plant
Green River Plant
9-5
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Coal
Demand
Region
Codes
1115
1116
1117
IMB1
IMB2
IMB3
IMB4
MA-1
MA-2
MA-3
MAB1
MIB1
MIB2
MIB3
MIB4
MNR1
MNR2
MNR3
MNR5
MWR1
MWR2
MWR3
Descriptive Name
Illinois, Indiana, Kentucky Low-Cost
Competitive_Not Mine
Mouth_Truck/Conveyor Belt
Indiana Non-Competitive_Mine
Mouth_Truck/Conveyor Belt
Illinois, Indiana, Kentucky Non-
Competitive_Not Mine Mouth_Rail
Illinois, Iowa, Missouri High-Cost
Competitive_Not Mine Mouth_Rail
Iowa, Missouri Low-Cost
Competitive_Not Mine Mouth_Rail
Missouri Low-Cost Competitive_Not
Mine Mouth_Truck/Conveyor Belt
Iowa Non-Competitive_Not Mine
Mouth Rail
Maryland Low-Cost Competitive_Not
Mine Mouth Rail
Maryland Low-Cost Competitive_Not
Mine Mouth_Truck/Conveyor Belt
Maryland Non-Competitive_Not Mine
Mouth Rail
Maryland Low-Cost Competitive_Not
Mine Mouth Rail
Michigan High-Cost Competitive_Not
Mine Mouth Rail
Michigan, Wisconsin Low-Cost
Competitive Not Mine Mouth Barge
Michigan, Wisconsin Low-Cost
Competitive_Not Mine Mouth_Rail
Michigan Low-Cost Competitive_Not
Mine Mouth_Truck/Conveyor Belt
Minnesota, South Dakota High-Cost
Competitive_Not Mine Mouth_Rail
Minnesota Low-Cost Competitive_Not
Mine Mouth_Barge
Minnesota Low-Cost Competitive_Not
Mine Mouth Rail
Minnesota, South Dakota Non-
Competitive_Not Mine Mouth_Rail
Iowa, Kansas, Missouri, Nebraska,
Oklahoma High-Cost Competitive_Not
Mine Mouth Rail
Kansas, Missouri High-Cost
Competitive_Not Mine
Mouth_Truck/Conveyor Belt
Kansas, Missouri, Nebraska, Oklahoma
Low-Cost Competitive_Not Mine
Mouth Rail
IPM Model
Regions with
Potential Plants
Assigned to this
Coal Demand
Region
~
~
TVAK
MRO
~
~
~
~
~
MACS
~
~
~
MEGS
~
~
~
~
~
SPPN
~
SPPS
Plant Name when
Coal Demand
Region Just
Includes One Plant
Rank E Ratts Plant
Endicott Station
Silver Bay Power
Plant
9-6
-------
Coal
Demand
Region
Codes
MWR5
NAM
NAI2
NAI3
NAI4
NAI5
NAI6
NE1
NE2
NE3
NII1
NII2
NII3
NNR1
NOR1
NOR2
NOR3
NOR4
NOR5
NOR6
NU1
NU2
ORP1
Descriptive Name
Kansas, Missouri Non-Competitive_Not
Mine Mouth Rail
West Virginia High-Cost
Competitive Mine Mouth Rail
West Virginia High-Cost
Competitive_Not Mine Mouth_Rail
Pennsylvania, West Virginia Low-Cost
Competitive_Not Mine Mouth_Barge
West Virginia Low-Cost
Competitive_Not Mine Mouth_Rail
West Virginia Low-Cost
Competitive_Not Mine
Mouth_Truck/Conveyor Belt
Ohio Non-Competitive_Not Mine
Mouth Rail
Maine, Massachusetts, New Hampshire,
New Jersey High-Cost Competitive_Not
Mine Mouth Rail
Connecticut, Massachusetts, New
Hampshire, New Jersey Low-Cost
Competitive_Not Mine Mouth_Barge
Connecticut, New York Low-Cost
Competitive_Not Mine Mouth_Rail
Indiana High-Cost Competitive_Not
Mine Mouth Rail
Illinois Low-Cost Competitive_Not Mine
Mouth_Barge
Illinois, Indiana Low-Cost
Competitive_Not Mine Mouth_Rail
Nevada Non-Competitive_Not Mine
Mouth Rail
Ohio High-Cost Competitive_Not Mine
Mouth Rail
Ohio Low-Cost Competitive_Mine
Mouth_Truck/Conveyor Belt
Ohio Low-Cost Competitive_Not Mine
Mouth_Barge
Ohio Low-Cost Competitive_Not Mine
Mouth Rail
Ohio Low-Cost Competitive_Not Mine
Mouth_Truck/Conveyor Belt
Ohio Non-Competitive_Not Mine
Mouth Rail
New York High-Cost Competitive_Not
Mine Mouth Rail
New York Low-Cost Competitive_Not
Mine Mouth Rail
Ohio, Pennsylvania, West Virginia High-
IPM Model
Regions with
Potential Plants
Assigned to this
Coal Demand
Region
~
RFCP
~
~
~
~
~
~
~
DSNY
~
~
~
~
~
~
~
~
~
~
UPNY
~
~
Plant Name when
Coal Demand
Region Just
Includes One Plant
Mt Storm Plant
Willow Island Plant
Albright Plant
Muskingum River
Plant
North Valmy Plant
Conesville Plant
Hiles Plant
O H Hutchings Plant
AES Westover Plant
9-7
-------
Coal
Demand
Region
Codes
ORP2
ORP3
ORP4
PC1
PC2
PCS
PC4
PC6
PE1
PE2
PE3
PRB1
PRB3
PRB4
SNR1
TAB1
TAB2
TABS
TKI1
TKI2
TXL1
TXL2
Descriptive Name
Cost Competitive_Not Mine Mouth_Rail
Ohio, Pennsylvania, West Virginia Low
Cost Competitive Not Mine Mouth Rail
Ohio, West Virginia Low-Cost
Competitive Not Mine Mouth Barge
Ohio, Pennsylvania, West Virginia Low-
Cost Competitive Not Mine Mouth Rail
Pennsylvania High-Cost
Competitive_Not Mine Mouth_Rail
Pennsylvania High-Cost
Competitive_Not Mine
Mouth_Truck/Conveyor Belt
Pennsylvania Low-Cost
Competitive Not Mine Mouth Barge
Pennsylvania Low-Cost
Competitive_Not Mine Mouth_Rail
Pennsylvania Non-Competitive_Not
Mine Mouth Rail
New Jersey, Pennsylvania High-Cost
Competitive_Not Mine Mouth_Rail
Pennsylvania Low-Cost
Competitive_Not Mine
Mouth_Truck/Conveyor Belt
Delaware, New Jersey, Pennsylvania
Non-Competitive_Not Mine Mouth_Rail
Wyoming High-Cost Competitive_Mine
Mouth_Truck/Conveyor Belt
Montana Low-Cost Competitive_Not
Mine Mouth_Truck/Conveyor Belt
Wyoming Non-Competitive_Not Mine
Mouth Rail
Nevada Non-Competitive_Not Mine
Mouth Rail
Alabama High-Cost Competitive_Not
Mine Mouth Rail
Alabama Low Cost Competitive_Not
Mine Mouth Rail
Alabama, Tennessee Low-Cost
Competitive_Not Mine Mouth_Barge
Tennessee Low-Cost Competitive_Not
Mine Mouth Rail
Tennessee Non-Competitive_Not Mine
Mouth Rail
Mississippi, Texas High-Cost
Competitive_Mine Mouth_Rail
Texas High-Cost Competitive_Not Mine
Mouth Rail
IPM Model
Regions with
Potential Plants
Assigned to this
Coal Demand
Region
~
~
~
MACW
~
~
~
~
~
~
MACE
~
~
~
SNV
~
~
~
~
TVA
~
~
Plant Name when
Coal Demand
Region Just
Includes One Plant
Homer City Station
P H Glatfelter Plant
PPL Montour Plant
Shawville Plant
Colstrip Plant
Reid Gardner
Charles R Lowman
Widows Creek
9-8
-------
Coal
Demand
Region
Codes
TXL3
TXL4
TXL5
VAPW
VEP1
VEP2
WIR1
WIR2
WIR4
WOM1
WOM2
WON1
WON2
WON3
WYG1
WYG2
WYG3
WYG4
Descriptive Name
Texas High-Cost Competitive_Not Mine
Mouth_Truck/Conveyor Belt
Louisiana, Texas Low-Cost
Competitive_Mine
Mouth_Truck/Conveyor Belt
Texas Non-Competitive_Not Mine
Mouth Rail
Virginia, Mine Mouth
South Carolina, Virginia High-Cost
Competitive_Not Mine Mouth_Rail
Virginia Non-Competitive_Not Mine
Mouth Rail
Wisconsin High-Cost Competitive_Not
Mine Mouth Rail
Wisconsin Low-Cost Competitive_Not
Mine Mouth Rail
Wisconsin Non-Competitive_Not Mine
Mouth Rail
Michigan Low-Cost Competitive_Not
Mine Mouth Rail
Michigan Non-Competitive_Not Mine
Mouth Rail
California High-Cost Competitive_Not
Mine Mouth Rail
California Low-Cost Competitive_Not
Mine Mouth Rail
Montana, Oregon, Washington Non-
Competitive_Not Mine Mouth_Rail
Wyoming High-Cost Competitive_Mine
Mouth_Truck/Conveyor Belt
Wyoming High-Cost Competitive_Not
Mine Mouth Rail
Wyoming Low-Cost Competitive_Mine
Mouth_Truck/Conveyor Belt
Wyoming Non-Competitive_Mine
Mouth Rail
IPM Model
Regions with
Potential Plants
Assigned to this
Coal Demand
Region
~
~
~
VAPW
~
~
~
WUMS
~
~
~
~
~
PNW
NWPE
~
~
~
Plant Name when
Coal Demand
Region Just
Includes One Plant
Twin Oaks Power
One Plant
Gibbons Creek
Eckert Station
Erickson Station
ACE Cogeneration
Facility
Osage Plant
Jim Bridger
9.1.3 Coal Quality Characteristics
Coal varies by heat content, SO2 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, subbitumionus, 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.)
9-9
-------
Table 9-3 Coal Rank Heat Content Ranges
Coal Type
Bituminous
Sub-bituminous
Lignite
Heat Content (Btu/lb)
>1 0,260 -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
0.81
1.21
1.67
3.35
-0.80
-1.20
-1.66
-3.34
-5.00
>5.00
The assumptions in EPA Base Case v.4.10 on the heat, 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)1 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 and ash content of the coal used was
obtained along with mercury content.
The ICR resulted in more than 40,000 data points indicating the coal type, sulfur content, mercury
content, ash 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.4.10, 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, 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 resulting values are shown in Table 9-5.
Data from the ICR can be found at http://www.epa.gov/ttn/atw/combust/utiltox/mercury.html.
9-10
-------
Table 9-5 Coal Quality Characteristics by Supply Region and Coal Grade
Coal
Supply
Region
AL
AZ
CG
CR
CU
IL
IN
KE
KS
KW
LA
MD
ME
MP
MS
MT
ND
NS
Coal
Grade
BB
BD
BE
BB
BA
BB
BA
BD
BA
BB
BD
BE
BG
BH
BD
BE
BG
BH
BA
BB
BD
BE
BG
BG
BD
BE
BG
BH
LE
BB
BD
BE
BG
LD
SA
SD
LE
BB
LD
LE
BB
BD
Heat Content
(MMBtu/Ton)
24.82
24
23.82
24.64
21.49
22.01
25.5
22.2
23.8
23.22
23.21
23
23.01
22.19
22.62
23.43
23.37
23.41
25.32
25.79
25.33
25.14
24.09
25.32
24.23
24.45
23.93
22.84
14.09
24.64
26.32
24.85
23.26
13.36
18.9
17.23
13.19
21
13.7
13.46
26.4
18.1
SO2 Content
(Ibs/MMBtu)
1.1
1.4
2.7
1.1
0.7
0.9
0.7
1.4
0.7
0.9
1.3
2.2
4.6
5.6
1.4
2.3
4.3
6.1
0.7
1
1.4
2.1
3.8
4.8
1.6
2.8
4.5
5.7
2.5
1.1
1.6
2.8
3.6
1.4
0.6
1.5
2.8
1.1
1.5
2.3
1.1
1.6
Mercury
Content
(Ibs/TBtu)
4.2
7.3
12.6
5.3
3.1
4.1
3.5
7
2.6
4
3.1
6.5
6.5
5.4
3.8
5.2
7.2
7.1
3
4.8
6
7.9
12
4.1
5.6
7.1
6.9
8.2
7.3
5.3
7.8
15.6
16.6
8.6
4.2
4.5
12.4
5.3
6.4
8.3
5.3
5.5
Ash Content
(Ibs/MMBtu)
9.8
10.8
10.7
7.9
7.3
8.4
7
8.3
6.3
7.8
8.1
6.6
8.1
9.1
7.4
8
8.2
8.6
6.1
6.4
7.4
7.7
10.2
8.5
6.2
7.4
8
10.2
17.1
7.9
9.5
11.7
16.6
11.3
4
10.1
21.5
7.9
10.7
12.8
7.9
19.6
Cluster
Number
2
2
2
2
1
2
1
1
1
2
1
2
1
1
1
2
1
1
1
2
1
2
3
1
1
2
1
1
2
2
2
1
3
1
1
1
1
2
1
1
2
1
9-11
-------
Coal
Supply
Region
OH
OK
PC
PW
TN
TX
UT
VA
WG
WH
WL
WN
WS
Coal
Grade
BE
BB
BD
BE
BG
BH
BE
BD
BE
BG
BH
BD
BE
BG
BB
BD
BE
LD
LE
LG
BA
BB
BD
BE
BA
BB
BD
BE
BB
SD
SA
SB
SB
BD
BE
BG
BH
BA
BB
BD
BE
BG
Heat Content
(MMBtu/Ton)
18.1
24.68
25.55
25.24
24.34
23.92
22.15
25.06
25.66
25.33
23.39
24.26
26.22
25.86
24.18
23.91
26.75
13.06
13.22
12.27
23.68
23.23
23.05
25.06
22.7
25.97
25.76
26.03
21.67
18.5
17.43
17.43
17.15
25.01
25.67
26.03
25.15
26.2
24.73
24.64
24.38
25.64
SO2 Content
(Ibs/MMBtu)
1.8
1.1
1.4
3.1
4
6.4
2.7
1.4
2.6
3.8
6.3
1.6
2.5
3.7
1.1
1.3
2.1
1.6
3
3.9
0.7
0.9
1.4
2.3
0.7
1
1.4
2.1
1.1
1.3
0.6
0.9
0.9
1.5
2.5
4
6.1
0.7
1.1
1.3
1.9
4.7
Mercury
Content
(Ibs/TBtu)
8.2
5.7
6.4
18.7
18.5
13.9
25.8
21.7
18
21.5
34.7
11.2
8.4
8.6
3.8
6.3
8.4
12
14.7
14.9
4.4
3.9
4.4
9.2
3.5
4.6
5.7
8.4
1.8
4.3
5.6
6.4
6.4
10.3
10.3
9.3
8.8
3.5
5.7
8.1
8.8
7.1
Ash Content
(Ibs/MMBtu)
18.8
9.8
10.3
7.1
8
9.1
11.3
49.3
9.2
9.6
13.9
10
5.4
6.5
10.4
10.4
6.5
22.3
25.6
25.5
7.4
8.6
10.5
7.4
7
7
8
8.1
5.6
10
5.5
6.5
6.5
9.2
7.9
6.9
9.6
7
9.2
9.3
9.9
6.4
Cluster
Number
2
1
1
1
2
2
1
3
1
2
3
2
2
1
2
1
2
2
1
1
2
2
1
2
1
2
1
2
1
1
2
1
1
2
2
1
1
1
2
2
2
1
9-12
-------
Next, a clustering algorithm was used to further aggregate the data in EPA Base Case v.4.10 for
model size management purposes. The clustering analysis was performed on the mercury and
SO2 data shown in Table 9-5 using the SAS statistical software package. Clustering analysis
places objects into groups or clusters, such that data in a given cluster tend to be similar to each
other and dissimilar to data in other clusters. The clustering analysis involved two steps. (In the
following write-up BG coal is used to illustrate how the procedure worked.) First, the number of
clusters of mercury and SO2 concentrations for each IPM coal type was determined based on the
range in average mercury and SO2 concentrations across all coal supply regions for a specific
coal type. Each coal type used either one or two clusters. The total number of clusters for each
coal grade was limited to keep the model size and run time within feasible limits. (Two clusters
were used for BG coal.) Second, for each coal grade the clustering procedure was applied to all
the regional SO2 and mercury values shown in Table 9-5 for that coal grade. (In the BG coal
example there are 11 such regional SO2 and mercury values.) Using the SAS cluster procedure,
each of the constituent regional values was assigned to a cluster and the cluster average SO2 and
mercury values were recorded. The resulting values are shown in Table 9-6 and Table 9-7. (For
BG coal the Cluster #1 average SO2 and mercury values are 4.36 Ib/MMBtu and 7.10 Ib/TBtu
respectively. The Cluster #2 average SO2 and mercury values are 3.89 Ib/MMBtu and 20.04
Ib/TBtu respectively. The Cluster #3 average SO2 and mercury values are 3.68 Ib/MMBtu and
14.31 Ib/TBtu respectively.) Although not used in determining the clusters, ash and CO2 values
were calculated for each of the clusters. These values are shown in Table 9-8 and Table 9-9. (The
CO2 values were derived from data in the Energy Information Administration's Annual Energy
Outlook 2009 (AEO 2009), not from data collected in the ICR.)
IPM input files retain the mapping between different coal grade/supply region combinations and
the clusters. The mapping can be seen in the last column of Table 9-5 which shows the cluster
number associated with the coal grade/supply region combination indicated in the first and second
columns of this table. (For BG coal, the SAS cluster procedure mapped supply regions IL, IN, KS,
KW, PW, WN, and WS to Cluster #1, supply regions OH and PC to Cluster #2, and MD and KE to
Cluster #3. See Figure 9-2 for an illustration of this mapping.) Table 9-6 to Table 9-9 show the
mercury, SO2, ash, and CO2 values assigned to coal grades and regions based on this cluster
mapping. The values shown in Table 9-6 to Table 9-9 are used in EPA Base Case v.4.10 for
calculating emissions.
Table 9-6 SO2 Emission Factors of Coal Used in EPA Base Case v.4.10
Coal Type by Sulfur Grade
Low Sulfur Eastern Bituminous (BA)
Low Sulfur Western Bituminous (BB)
Low Medium Sulfur Bituminous (BD)
Medium Sulfur Bituminous (BE)
High Sulfur Bituminous (BG)
High Sulfur Bituminous (BH)
Low Sulfur Subbituminous (SA)
Low Sulfur Subbituminous (SB)
Low Medium Sulfur Subbituminous (SD)
Low Medium Sulfur Lignite (LD)
Medium Sulfur Lignite (LE)
High Sulfur Lignite (LG)
Sulfur Emission Factors (Ibs/MMBtu)
Cluster #1
0.7
1.13
1.43
2.78
4.36
5.89
0.62
0.94
1.41
1.46
2.88
3.91
Cluster #2
0.67
1.03
1.45
2.3
3.89
6.43
0.58
-
-
1.61
2.38
-
Cluster # 3
~
~
1.42
~
3.68
6.29
~
~
~
~
~
~
9-13
-------
Table 9-7 Mercury Emission Factors of Coal Used in EPA Base Case v.4.10
Coal Type by Sulfur Grade
Low Sulfur Eastern Bituminous (BA)
Low Sulfur Western Bituminous (BB)
Low Medium Sulfur Bituminous (BD)
Medium Sulfur Bituminous (BE)
High Sulfur Bituminous (BG)
High Sulfur Bituminous (BH)
Low Sulfur Subbituminous (SA)
Low Sulfur Subbituminous (SB)
Low Medium Sulfur Subbituminous (SD)
Low Medium Sulfur Lignite (LD)
Medium Sulfur Lignite (LE)
High Sulfur Lignite (LG)
Mercury Emission Factors (Ibs/TBtu)
Cluster #1
3.19
1.82
5.38
19.53
7.1
7.38
4.24
6.44
4.43
7.51
13.55
14.88
Cluster #2
4.37
4.86
8.94
8.42
20.04
13.93
5.61
-
-
12
7.81
-
Cluster #3
-
-
21.67
-
14.31
34.71
-
-
-
-
-
-
Table 9-8 Ash Emission Factors of Coal Used in EPA Base Case v.4.10
Coal Type by Sulfur Grade
Low Sulfur Eastern Bituminous (BA)
Low Sulfur Western Bituminous (BB)
Low Medium Sulfur Bituminous (BD)
Medium Sulfur Bituminous (BE)
High Sulfur Bituminous (BG)
High Sulfur Bituminous (BH)
Low Sulfur Subbituminous (SA)
Low Sulfur Subbituminous (SB)
Low Medium Sulfur Subbituminous (SD)
Low Medium Sulfur Lignite (LD)
Medium Sulfur Lignite (LE)
High Sulfur Lignite (LG)
Ash Emission Factors by Coal Sulfur
Grades (Ibs/MMBtu)
Cluster #1
6.77
5.59
9.64
9.84
7.51
9.38
3.98
6.5
10.08
11.01
23.58
25.51
Cluster #2
7.39
8.1
9.77
8.69
8.8
9.13
5.47
~
~
22.33
15
-
Cluster #3
~
-
49.31
~
13.41
13.89
-
~
~
-
~
-
9-14
-------
Table 9-9 CO2 Emission Factors of Coal Used in EPA Base Case v.4.10
Coal Type by Sulfur Grade
Low Sulfur Eastern Bituminous (BA)
Low Sulfur Western Bituminous (BB)
Low Medium Sulfur Bituminous (BD)
Medium Sulfur Bituminous (BE)
High Sulfur Bituminous (BG)
High Sulfur Bituminous (BH)
Low Sulfur Subbituminous (SA)
Low Sulfur Subbituminous (SB)
Low Medium Sulfur Subbituminous (SD)
Low Medium Sulfur Lignite (LD)
Medium Sulfur Lignite (LE)
High Sulfur Lignite (LG)
CO2 Emission Factors by Coal
Sulfur Grades (Ibs/MMBtu)
Cluster #1
205.4
205.8
206.6
206.3
205.2
205.2
213.1
212.7
213.1
217
214.8
213.5
Cluster #2
205.4
205.8
206.6
206.3
205.2
205.2
213.1
-
-
217
214.8
-
Cluster #3
-
~
206.6
~
205.2
205.2
~
~
-
~
~
-
Figure 9-2 Cluster Mapping Example BG Coal
IL-BG
Hg: 6.5 Ibs/TBtu
WS -BG
Hg: 7.1 Ibs/TBtu
OH -BG
Hg: 18.5 Ibs/TBtu
PC-BG
Hg: 21.5 Ibs/TBtu
IN -BG
SO2: 4.3 Ibs/MMBtu
Hg: 7.2 Ibs/TBtu
KS -BG
Hg: 4.1 Ibs/TBtu
BG-Cluster*!
S02: 4.36 Ibs/MMBtu
Hg: 7.10 Ibs/TBtu
BG-Clusters
S02: 3.89 Ibs/MMBtu
Hg: 20.04 Ibs/TBtu
BG- Cluster #3
S02: 3.68 Ibs/MMBtu
Hg: 14.31 Ibs/TBtu
KW-BG
SO2: 4.5 Ibs/MMBtu
Hg: 6.9 Ibs/TBtu
PW-BG
SO2: 3.7 Ibs/MMBtu
Hg: 8.6 Ibs/TBtu
WN-BG
3O2: 4.0 Ibs/MMBtu
Hg: 9.3 Ibs/TBtu
MD -BG
Hg: 16.6 Ibs/TBtu
KE-BG
Hg: 12.0 Ibs/TBtu
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.4.10 are shown in Table 9-10. Not all of the coal grades
9-15
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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 9-10 Example of Coal Assignments Made in EPA Base Case
Plant Name
Salem Harbor
Dickerson
Glen Lyn
Danskammer
Generating Station
R E Burger
Moutaineer
Big Brown
Black River
Generation
E D Edwards
R Gallagher
Unique ID
1626 B 1
1572 B 3
3776 B 51
2480_B_3
2864 B 5
6264_B_1
3497 B 1
10464_B_E0001
856_B_1
1008_B_1
SIPSO2
Limit
(Ibs/MMBtu)
1.2
2.8
1.75
1.1
9.02
1
3
3.8
4.71
4.71
Scrubber?
No
No
No
No
No
Yes
No
Yes
No
No
Fuels Allowed
BA,BB
BA,BB,BD,BE
BA,BB,BD
BA,BB
BA,BB,BD,BE,BG,BH
BA,BB,BD,BE,BG,BH,
SA,SB,SD
LD,LE,SA,SB,SD
BA,BB,BD,BE,BG,BH
BA,BB,BD,BE,BG,SA,
SB,SD
BA,BB,BD,BE,BG,SA,
SB,SD
9.2 Coal Supply Curves
9.2.1 Nature of Supply Curves Developed for EPA Base Case v.4.10
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.4.10. 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 31 coal supply regions (described above in sections 9.1.1) and 12
coal grades (described above in section 9.1.3). The combined code list is shown in Table 9-11
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 9-11) for forecast years 2012, 2015, 2020, 2030, and 2040.
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Table 9-11 Basin-Level Groupings Used in Preparing v.4.0 Coal Supply Curves
Coal Supply Regions and Coal Grades in EPA IPM, v.4.0
BITUMINOUS
SUB-BITUMINOUS
LIGNITE
Geo. Region Geo. Sub-Region
Appalachia Southern Appalachia
West Southwest"
West Rocky'Mounfain
West RockyM'ounfain
West Rocky'Mounfain
Interior East Interior (Illinois Basin)
Inferior Easf Interior (Illinois Basin)
Inferior _ Gulf" Lignite
Appalachia Northern Appalachia
West Dako"ta Lignite
Appalachia CenfralAppalachia
inferior We'sTlnTe'rlor"
Inferior Easf Interior (Illinois Basiri)
West We"sTe7n" Montana
coal code
Region Code
Gulf Coast Ugnife
Western Monfana
'p'akoTaTfgnlfe
"Southwest"
Northern Appalachia
West Interior
Northern Appalachia
Northern Appalachia
Gulf
West
West
West
Appalachia
Inferior
Appalachia
Appalachia
AppaTachTa"
Gulf GulfCoasf Ugnife
West Rocky'Mounfain
Appalachia CenfralAppalachia
West We"st"ern"\Afyomlng
Wesf Wyoming Powder River Basin
West Wyoming Powder River Basin
Appalachia _ Northern Appalachia _
Appalachia CenfralAppalachia _
BA BB BD BE BG BH
JII-
JII-
9.2.2 Procedure Employed in Determining Mining Costs
Wood Mackenzie estimates mine production costs on a mine-by-mine basis utilizing proprietary
bottom-up engineering cost models. A mine's cash costs are the sum of its direct operating costs
(DOCs), royalty tax, severance tax, property tax, reclamation tax and black lung fees. Using these
mine costing models, costs curves are developed by summing the individual and incremental
costs that make up mine cash-costs and assuming a built-in 10% discounted rate-of-return. As an
illustration of the break-down of costs included in the mine costing models, Figure 9-3 lists the
cost components included and calculations performed for a Powder River Basin mine supply
curve. Appendix 9-1 contains a more detailed illustration of the procedure used to derive a supply
curve from its constituent mine costing models.
9-17
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Figure 9-3 Cost Calculations Included When Developing Coal Supply Curves (based on a
Powder River Basin Mine Supply Curve Example)
10% [
)CFROR All cost curves assume mine operators are able to earn a minimum 10% discounted rate-of-return.
Cash Co;
it
Royalty = Revenue * Royalty %
Severance Tax = (Revenue - Royalty) * Sevr Tax Rate! * % Adjustment if needed
Property Tax = (Revenue - Royalty)* property tax rate
Reclamation Tax = Production * reclamation rate2
Black Lung = Production * (the lesser of 0.55, or 4.4% * sales price of coal)
DOCs (surface mines)
Labor = Production * (Wages + Benefits) / Productivity
Unit Removal Costs
= Cost per yard by equiprTlent type * Amount removed
Added coal haul = year-over-year mileage increase * haul rate * production
On-going reclamation = production * reclamation rate (as a function of coal depth)
< OR >
DOCs (deep mines)
Labor = Production * (Wages + Benefits) / Productivity
Materials & Supplies
Trucking costs = haul distance from mine to load-out * haul rate
Mine overhead = Cost associated with mine support
Division overhead = Company dependent costs for operations
Pension = company's portion of employee retirement
General Definitions:
Revenues = Tons coal produced * sale price/ton
Productivity (TPMH) = Tons coal produced / man hours worked in reporting period
Stripping Ratio = Overburden Yard / Coal Production
Production = Amount of coal removed from the mine in a given period
Cash cost: is the sum of a mine's Direct Operating Costs (DOCs), Royalty tax, Severance Tax, Property Tax,
Reclamation Tax and Black Lung fees.
! Severance Tax Rate is state specific
2 Reclamation Tax used was 0.15 for Deep Mines & 0.35 for Surface Mines
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.
Several methods are employed for cost estimation depending on the availability of information and
the diversity of mining operations. When possible, Wood Mackenzie analysts develop detailed lists
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 direct operating costs.
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Direct costs categories include: mine labor, salaries, material and supplies, and mine overhead.
The costs are estimated based on labor productivity and mining methods. 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. For surface
mines, material and supply costs are estimated based on the mining method (dragline, truck-
shovel and other) and the number of yards of overburden1 moved by each method. A cost per
yard moved is estimated for each mining method and mining region. Where coal is washed,
washing costs are based on the type of plant being used and the average washing cost per ton for
the mining region. Overhead costs are estimated based on mine size.
Labor costs 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. These preparation plants may be located at the mine site or a central
preparation plant that washes coal from a number of mines. If the coal is transported to an offsite
location for washing, transportation costs to the plant are included in the total costs.
Supply costs are adjusted annually to reflect movements in the price of steel, diesel, natural gas
and other commodities. Cost adjustments are averaged on an annual basis and analyzed to
ensure that anomalous spikes in commodity prices are not carried forward in the cost analysis.
Royalties, severance taxes, black lung fees, reclamation taxes and property taxes are estimated
using federal, state and local parameters.
In the Western United States, capital requirements are estimated for each mine and a life-of-mine
discounted cash flow analysis is used to determine the price required to yield a 10% DCFROR2,
including income taxes. In the Eastern United States, the required price is estimated based on
operating costs and production levels.
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. (This was done in the example shown in Figure 9-3 above.) 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
1 Overburden refers to the surface soil and rock that must be removed to uncover the coal.
2 DCFROR stands for discounted cash flow rate of return (also called "internal rate of return" (IRR)
and "rate of return"). It is the annualized effective coupounded return that can be earned on
invested capital.
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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. (Transport costs are taken into account using a separate
procedure which is described below in section 9.3.)
In cases where new mines are planned or recoverable reserves are available to support new
mines (see sections 9.2.6 and 9.2.7 below), Wood Mackenzie uses nearby mines with similar
geography and geology to estimate mine operating costs and productivity levels. Production levels
for new mines are estimated based on known reserves, historic precedent, and region specific
knowledge.
9.2.3 Supply Curve Development
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 9-4 and Figure 9-5 below.
Figure 9-4 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
1
J
Type
S
U
S
S
S
S
U
U
U
S
Cost
J 30
$ 20
$ 32
J 36
I 29
J 28
J 25
$ 23
J 27
$ 35
Production
2
4
1
0.5
2
2.5
5
4
3
0.25
J10 -
Mine Cost and Production Amis
Illlllll
s a
t
D E F O 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 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 9-6 for a stepped version of the supply curve example
shown in Figure 9-5. 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. (See Appendix 9-1 for a more
detailed example of how a supply curve is derived from constituent mine costing models.)
9-20
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Figure 9-5 Illustration of Final Step in Developing a Cumulative Coal Supply Curve
New 01
Existing? (V
E
E
E
E
N
E
N
N
N
N
Mine(V
B
H
G
1
F
E
A
C
J
D
JjffieHCostfi
U
u
U
u
s
s
s
s
s
s
J 20
J 23
J 25
J 27
} 28
} 23
} 30
} 32
} 35
} 36
Ulln
Production HProiluctiop
4
4
5
3
2.5
2
2
1
0.25
0.5
4
8
13
16
18.5
20.5
22.5
23.5
23.75
24.25
Smooth Supply Curve
5 10 15 20
Cumulative Production (Tons)
Figure 9-6 Example Coal Supply Curve in Stepped Format
Stepped Supply Curve
13 17
Cumulative Production
MINE NAME
New or ExistincQ
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
23
28
28
29
30
30
35
36
9.2.4 Data Sources Used to Build the Curves
For active mines, data relating to labor and productivity is taken from MSHA databases. MSHA
reports on individual mine production, number of employees and employee-hours worked.
Corporate financial statements of publicly traded companies are listed with the Securities and
Exchange Commission (SEC). Supplemental information on work schedules, equipment,
percentages of washed coal, trucking distances between mine and preparation plants is obtained
9-21
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in interviews performed for Wood Mackenzie's annually published county-by-county studies.
Information on recoverable reserves comes from several sources such as Environmental Impact
Statements (EIS), company annual reports, applications filed at state permitting offices or Lease
by Application (LBA) filings for mines on federal lands.
For areas where public information is not available or is incomplete, reserves are estimated using
geologic reports of nearby properties and some extrapolation by mining engineers and geologists.
9.2.5 Procedure Used In Determining Mine Productivity
Projected production and stripping ratios3 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.
These factors are not used directly but provide a backdrop for deriving productivity estimates. As
with surface mines Wood Mackenzie relies on MSHA data for its productivity estimates.
Productivity estimates for underground mines start with the MSHA estimates and are carried
forward into the forecast years without adjustment.
9.2.6 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
3 Stripping ratio is the amount of waste material (rock and/or soil) that must be removed to recover
one unit (commonly expressed in short tons) of coal. For example, a stripping ratio of 9.8 means
that to recover 1 ton of coal you must remove 9.8 tons of waste material. A lower stripping ratio
means that less waste has to be removed.
9-22
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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)4 estimates to ensure that they do not
exceed the DRB estimates.
9.2.7 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. 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.
9.2.8 Other Notable Procedures
Cost Rounding
For simplification, the estimated mine costs were rounded so that costs less than 20 $/Ton were
rounded to the nearest $0.25. Costs that fell between 20 and 50 $/Ton were rounded to the
nearest $0.50 and costs greater than $50 were rounded to the nearest $1.00.
<=$20, round to nearest $0.25
>$20 and <=$50, round to nearest $0.50
>$50, round to nearest $1.00
Future Cost Adjustments
For consistency with the cost basis used in EPA Base Case v.4.10, costs are converted to real
2007$. Wood Mackenzie has assumed that improved productivity will lead to cost reductions in all
regions except Central Appalachia where depleting reserves will lead to falling productivity and
increased costs. Costs for all regions except Central Appalachia have been reduced at a rate of
0.4%/year. Central Appalachian costs have been increased at a rate of 0.4%/year based on the
assumption that labor costs on average account for 40% of the Cost of Production. These regional
cost adjustments are derived from specific factors affecting costs in regions based on information
maintained by Wood Mackenzie and their on-going dialog with industry professionals.
9.2.9 Region Specific Assumptions and Outlooks
Powder River Basin (PRB)
Powder River Basin cost curves are based on cost models run for each of the identified projects in
Wood Mackenzie's coal supply database. These cost models are run on five year increments over
a 20 year mine life. These models assume that federal lease tracts are acquired as necessary to
achieve a 20 year mine life. In preparing the curves for EPA, it was assumed that existing mines
would operate at projected levels through 2011 and reserves were adjusted to reflect remaining
reserves at that time. Ten years additional reserves were then added to the remaining reserves
4Posted by the Energy Information Administration (EIA) in its January, 2007 Coal Production
Report.
9-23
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based on the assumption that additional reserves would be available for lease and the mines
would continue to operate. Costs for the added reserves were increased by $3.00/ton to reflect
increased coal leasing costs and increasing mining ratios in the PRB.
One existing mine, Decker, is expected to close prior to 2012 and was therefore not included in
the cost curves.
A MT region was added to accommodate two proposed mines in Montana that do not fit the
quality specifications for the ME or MP regions.
There is an annual limit of 612 million tons per year on Wyoming PRB coal production (i.e., coal
codes WH and WL in Table 9-11) based on expected maximum production from existing mines
plus potential production from four identified projects.
Western Bituminous Coalfields
The Western Bituminous Coalfields include the Colorado, Utah, southern Wyoming, New Mexico
and Arizona coalfields. Life-of-mine costs are used for all operating mines and identified projects.
Reserves have been reduced based on projected production through 2011 for existing mines and
mines that are expected to go into production before 2012. Unlike the PRB no additional reserves
have been added to the reserve base for existing mines.
Arizona mine costs are FOB5 mine.
In Utah all costs except Deer Creek's include transportation to a loadout facility. Deer Creek costs
are based on delivery to the Huntington Canyon power plant.
In New Mexico, all costs are FOB rail or FOB mine. It is assumed that the Navajo, San Juan
Underground and the proposed Navajo South/Desert Rock mine will serve their respective mine-
mouth power plants. One existing mine, McKinley, will be mined out by 2012. The proposed
Carrizozo mine in SE New Mexico is included in the curve.
In Colorado all costs are FOB mine. This includes the Deserado mine which currently ships all of
its production to the Bonanza power plant via a private railroad. A CR region has been added to
accommodate two proposed mines in or near the Raton Basin.
Louisiana (LA)/ Mississippi (MS)
Louisiana cost curves are based on Wood Mackenzie cost models for existing and planned mines
in Louisiana. Where a mine's reserves exceed production requirements over the forecast period, it
has been assumed that a second mine could be opened on the reserves. A high cost mine with
cost of $50/ton was added.
A Mississippi cost curve was added.
Montana Lignite (ME)
Montana Lignite curves are based on Wood Mackenzie cost estimates for GNP lignite properties.
All costs are FOB mine. Because lignite typically does not ship well, it is assumed that any new
mines will be developed to serve mine mouth customers.
5 FOB stands for "Free On Board" or "Freight on Board." It indicates the point at which
responsibility and costs for a goods is transferred from the seller (or shipper) to the buyer. "FOB
mine" implies that the price includes costs up to the mine and that the buyer assumes costs
beyond the mine. "FOB rail" implies the prices includes the cost of loading the coal onto a rail car.
9-24
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North Dakota Lignite (ND)
North Dakota curves are based on Wood Mackenzie cost estimates for the region. Where a
mine's reserves exceed production requirements over the forecast period, it has been assumed
that a second mine could be opened on the reserves. Costs for the new mines were increased by
$2.00/ton. A GNP project was added as a high cost new mine.
Oklahoma/Kansas (OK, KS)
The 2006 set of coal supply curves developed for EPA by Hill and Associates (now a unit of Wood
Mackenzie) was updated by increasing costs 30% and adding a high cost mine with a cost of
$100/ton.
Texas Lignite
Texas Lignite cost curves are based on cost models run for each of the existing mines and
identified projects in Wood Mackenzie's coal supply database. Big Brown was deleted for the
existing mines as its reserves will be depleted before 2011.
Illinois Basin (IL, IN, KW)
Illinois Basin cost curves are based on cost models run for each of the existing mines and
identified projects in Wood Mackenzie's coal supply database. Where additional reserves are
known to be available, additional next step mines were added based on information maintained by
Wood Mackenzie on the region.
Appalachia (AL, OH, PC, PW, TN, VA, WN & WS)
Appalachian cost curves are based on Wood Mackenzie's extensive database of existing and
planned mines. 2012 production and cost curves were prepared for each region and coal grade
using the regional model to estimate cost, production and reserve data for existing mines. To
protect the proprietary nature of the regional curves, mine data were aggregated to produce a
curve similar to the regional curve without disclosing specific mine data. Cost and production
estimates for each of the next step mines were prepared for each region and coal type based on
information maintained by Wood Mackenzie's knowledge for each region.
9.2.10 Explanation of Coal Supply Curve Extensions to 2040
Wood Mackenzie added additional reserves at increased costs on a mine-by-mine basis for each
region based on its extensive coal resource database and knowledge of the coal industry. A list of
the mines added by region and coal grade can be found in Appendix 9-2. For modeling purposes
the 2040 coal supply curves are used in 2050 as well.
9.3 Coal Transportation
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).
9-25
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In recent years, transportation rates (especially rail rates) 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 September 2008, when the coal transportation rate assumptions for EPA
Base Case v.4.10 were finalized. It is important to remember that these rates do not reflect rates
that transporters and coal-fired owners may currently be negotiating in the near-term (pre-2012).
Instead, these rates reflect expected long-term equilibrium levels, including the long-term market
dynamics that will drive these pricing levels.
All rates are represented in 2007 real dollars.
9.3.1 Coal Transportation Matrix Overview
Description
In order to model coal transportation rates within the EPA's modeling construct, a coal
transportation matrix was developed, which represents a matrix of all the coal demand regions
and coal supply regions modeled within the IPM model for EPA Base Case v.4.10. The matrix
includes the associated transportation costs between these supply and demand nodes. Each coal
demand region covers a set of coal plants having similar transportation infrastructure,
transportation competitiveness levels, and geographic location; in addition to these criteria, coal
demand regions are also classified as either "mine-mouth" or"non mine-mouth" regions. Coal
supply regions are represented by the major coal mining basins modeled in IPM; a more detailed
discussion on these regions can be found in previous sections.
Methodology
Each coal supply region and coal demand region is connected via a transportation link, which can
include multiple transportation modes. For each transportation link, cost estimates, in terms of
$/ton, were calculated utilizing mode-based transportation cost factors, analysis of the competitive
nature of the moves, and overall distance that the coal type must move over each applicable
mode. An example of the calculation methodology for movements including multiple transportation
modes is shown in Figure 9-7.
Figure 9-7 Calculation of Multi-Mode Transportation Costs (Example)
Rail Cost ($/ton) =
Rail Mill Rate (mills/ton-mile) x Rail
Mileage
Transloading
Cost ($/ton)
Barge Cost ($/ton) =
Loading Cost ($/ton) + Barge Mill Rate
(mills/ton-mile) x Barge Mileage
9.3.2 Calculation of Supply/Demand Region Distances
Definition of applicable supply/demand regions
Coal demand regions are linked to coal supply regions based on historical coal deliveries, as well
as based on the potential for new coal supplies to serve a demand region going forward. A
demand region may have transportation links with more than one supply region, depending on the
various coal types that can be physically delivered and burned by generators within a given coal
demand region.
9-26
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Figure 9-8 Coal Demand Region with Multiple Coal Supply Regions
Coal
Demand
Region
Coal Supply
Region #1
Coal Supply
Region #2
Coal Supply
Region #3
Transportation Links for Existing Coal-Fired Plants
Transportation routings forgiven coal supply regions and coal demand regions were developed
based on third-party software6 and other industry knowledge available to Hellerworx and PA
Consulting Group. Origins for each coal supply region were based on significant mines or other
significant delivery points within the supply region, and destinations for each coal demand region
were based on geographical points located near, and with similar key delivery transportation
characteristics, as the coal plants located within the given coal demand region. 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
Within each coal demand region, coal transportation links representative of the typical
transportation costs expected to be incurred by new coal plants within that region were developed.
For coal demand regions where new coal plant construction is not expected to include mine-
mouth plants, the transportation links for new plants are based on transportation links in the
existing coal demand region that are expected to have costs most similar to those incurred by new
plants. For coal demand regions where new coal plant construction is expected to consist
primarily of mine-mouth plants, new transportation links reflecting short-distance transportation of
local coal supplies were created as needed to properly represent the transportation costs incurred
by new plants. 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, between 2004 and 2008, the differential between rates at captive plants
and rates at competitively-served plants narrowed. For all of the coal supply regions except the
Rail routing and mileage calculations utilize ALK Technologies PC*Miler software.
9-27
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Powder River Basin (PRB), 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,
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 9-12 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).
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, 400-699
miles, and 700+ 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
2007 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).
9-28
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Table 9-13 Assumed Eastern Rail Rates (2007 mills/ton-mile)
Mileage Block
<200
200-299
300-399
400-699
700+
Captive
72
55
55
37
35
High-Cost Competitive
72
55
55
37
35
Low-Cost Competitive
58
43
43
30
28
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 9-14 Assumed Midwestern Rail Rates (2007 mills/ton-mile)
Mileage Block
<200
200-299
300-399
400-699
700+
Captive
72
55
55
36
34
High-Cost Competitive
72
55
55
36
34
Low-Cost Competitive
58
43
43
29
27
Rates applicable to Western moves
Rail moves within the Western U.S. are handled predominately by BNSF and UP. In addition to
these incumbent carriers, CP acquired the Dakota, Minnesota and Eastern Railroad (DM&E) in
October 2007, which increases the probability that DM&E's project to build a third rail line into the
PRB will be completed. The analysis assumes that DM&E's entry into the market will influence
transportation rates for PRB coal by 2012,7 and the rail rate forecast for PRB coal shipments to
competitively-served destinations reflects this expectation.
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 (with the possible
future entry of DM&E as a third competitor within this region), 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.
7 Note that this is not equivalent to assuming that DM&E's PRB project would be operational by
2012. Construction of the DM&E's PRB project is expected to be a three-year process. However,
in order to obtain financing and begin construction, DM&E would likely have to negotiate some rail
contracts for PRB coal shipments. Thus, DM&E's presence as a third competitor in the market for
PRB coal shipments might affect rail rates well before DM&E's additional rail line into the PRB
became operational
9-29
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Non-PRB coal moves
Table 9-15 Assumed Non-PRB Western Rail Rates (2007 mills/ton-mile)
Mileage Block Captive
< 300 43
300+ 25
High-Cost Competitive
43
21
Low-Cost Competitive
35
21
PRB moves confined to BNSF/UP rail lines
Table 9-16 Assumed PRB Western Rail Rates (2007 mills/ton-mile)
Mileage Block
<300
300+
Captive
43
23
High-Cost Competitive
43
14
Low-Cost Competitive
35
14
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 $2.16 per ton or 28 mills perton-mile (whichever is higher) is applied to the
portion of the movement that occurs on railroads other than BNSF and UP. (The $2.16 per ton
assumption is a minimum rate for short-distance movements of PRB coal on Eastern railroads.)
9.3.4 Truck rates
Truck rates include loading and transport components, and all trucking flows are considered
competitive because highway access is open to any trucking firm. The truck rates shown in Table
9-17 are expected long-term equilibrium levels reflective of current rates as of September 2008,
and expected changes in labor costs, fuel prices, and steel prices. The slightly higher truck rates
in Utah reflect market conditions specific to that market, which is relatively remote.
Table 9-17 Assumed Truck Rates (2007 Real Dollars)
Market
Outside of Utah Market
Utah Market
Loading Cost ($/ton)
1.03
1.54
Transport (mills/ton-mile)
134
134
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
9-18 are expected long-term equilibrium levels reflective of current rates as of September 2008,
and expected changes in labor costs, fuel prices, and steel prices.
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.
9-30
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Table 9-18 Assumed Barge Rates (2007 Real Dollars)
T * o iv
-------
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 9-20.
Table 9-20 Assumed Other Transportation Rates (2007 Real Dollars)
Coal Demand Region
Rail-to-Barge
Rail-to-Vessel
Rail-to- Rail
Truck-to-Barge
Conveyor
Rate ($/ton)
1.23
1.23
1.44
1.49
1.13
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 34% of the rail industry's operating costs in 2006, and fuel accounted for an
additional 19%. The remaining 47% of the rail industry's costs relate primarily to locomotive and
railcar ownership and maintenance, and track construction and maintenance.
The RCAF8 Unadjusted for Productivity (RCAF-U), which tracks operating expenses for the rail
industry, has increased at an annualized rate of 6.2%/year over the past five years, more than
double the increase of 2.8%/year in general inflation (GDP-IPD) over the same period. However,
this largely resulted from steep increases in diesel fuel prices. Excluding fuel, the rail industry's
operating costs (as measured by the All-inclusive Index Less Fuel, or AII-LF), increased by only
3.5%/year.
8 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.
9-32
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Figure 9-9 Rail Cost Indices Performance (2Q2003-2Q2008)
1.400
O
ฃ 0 900
0)
o
TJ 0.800
O
O
= 0.700
n
a:
Performance of Rail Cost Indices, 2Q2003-2Q2008
(annuallzed nominal S change)
RCAF
Unadjusted
for
Productivity
[RCAF.U)
6.2*
RCAF
Adjusted for
Productivity
(RCAF Uj
4.0S
All-Inclusive
Index Less
Fuel (flll-LFj
3.5%
Labor
Component
of RCAF-U
3.0%
GDP-IPD
2.8%
fj
o
ง
-RCAF-U
ง
RCAF-A
AII-LF
-GDP-IPD
n RCAF-U L a b o r C om portent
In addition to diesel fuel price increases, world prices for steel (which is a significant component of
locomotive, railcar, and track construction and maintenance costs) also increased steeply over the
past five years, rising from about $290/metric tonne as of June 2003 to about $650/metric tonne
as of June 2007, and over $1,000/metric tonne as of June 2008. However, during the previous five
years (2Q1998-2Q2003), when steel prices were less volatile, the AII-LF closely tracked general
inflation, rising at about 2.1 %/year compared with 2.0%/yearforthe GDP-IPD.
Additionally, over the past five years, the rate of increase in the rail industry's labor costs
(3.0%/year) has closely tracked the increase in the GDP-IPD (2.8%/year.)
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 show that, at 2006
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.
9-33
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Figure 9-10 Long-Run Marginal Cost Breakdown by Transportation Mode
100%
90%
80%
70%
60%
50%
40%
30%
20%
10%
0%
Rail
Barge
Truck
I Fuel D Other
9.3.9 Market Drivers Moving Forward
Diesel fuel prices
The Energy Information Administration's (ElA's) Annual Energy Outlook (AEO)9 forecast of long-
term equilibrium prices fordiesel fuel shows expected prices ranging from about $2.62/gallon in
2012 to about $2.77/gallon in 2030 (2007 real dollars). This range of prices is comparable to the
actual average on-highway diesel fuel price for 2006 which was $2.78/gallon (2007 real dollars).
The coal transportation rate forecast for EPA Base Case v.4.10 assumes that diesel fuel prices
will return to these long-run equilibrium levels by 2012.
Table 9-21 EIA AEO Diesel Fuel Forecast, 2012-2030 (2007 Real Dollars)
Year
2012
2015
2020
2025
2030
Annualized
% Change, 2025-2030
Rate ($/gallon)
2.62
2.49
2.57
2.61
2.77
1.10%
Source: EIA
9 As noted at the beginning of this section, the coal transportation rate assumptions for EPA Base
Case v.4.10 were finalized in September 2008. At that time, the Annual Energy Outlook 2008
forecast was the latest available.
9-34
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Iron ore prices
ABARE's10 forecast of iron ore prices shows an expectation that iron ore prices will return to late
2007/early 2008 levels (i.e., to the levels prevailing before the most recent price spike) by 2012,
and to decline by about 18% in real terms for their 5-year forecast period (2008-2013) as a whole.
Table 9-22 ABARE Forecast of Iron Ore Prices
ABARE Estimate of Average Price for Australian
Iron Ore Exports, Year Ending (YE) March 2008
ABARE Forecast for YE Mar 2009
ABARE Forecast for YE Mar 201 0
ABARE Forecast for YE Mar 201 1
ABARE Forecast for YE Mar 201 2
ABARE Forecast for YE Mar 201 3
Total Percent Change (2008-2013)
2007 $/metric tonne
67.72
98.68
91.19
73.73
61.84
55.52
-18.00%
Source: ABARE, Australian Commodities, vol. 15 no. 1 and 2, March and
June Quarters 2008
Labor costs
Labor costs for the rail industry are expected to continue to escalate at approximately the same
rate as overall inflation (i.e., labor costs are expected to be approximately flat in real terms). 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 likely to increase at rates similar to or slightly
slower than the increase in rail labor costs.
Productivity gains
The most recent data published by AAR (covering 2002-2006) shows that rail industry productivity
increased at an annualized rate of approximately 1.2% 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.
Long-Term Escalation of Coal Transportation Rates
Based on the foregoing discussion, the transportation rate forecast assumes flat real escalation of
rail and truck rates, and a 1% per year real decline in barge and lake vessel rates, which reflects
some pass-through of productivity gains in those highly competitive industries, over the 2012-2025
period.
However, ElA's forecast of diesel fuel prices, which is essentially flat in real terms during the
2012-2025 period, predicts a relatively steep rise in diesel fuel prices (annualized increase of
1.1%/year) between 2025 and 2030. Because of this, coal transportation rates are assumed to
escalate as follows during the 2026-2062 period:
Rail: 1.1% annual real increase in fuel prices x 20% fuel cost weighting = real rate increase of
0.2%/year.
Truck: 1.1% annual real increase in fuel prices x 50% fuel cost weighting = real rate increase
of0.5%/year.
10 ABARE 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 32% of total worldwide iron ore exports in 2007. See
www.abareconomics.com
9-35
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Barge and lake vessel: 1.1% annual real increase in fuel prices x 35% fuel cost weighting =
real input cost increase of 0.4%/year, less 1 % per year for pass-through of productivity gains
= real rate decline of 0.6%/year.
Conveyor: no change in real terms throughout the study period.
9.3.10 Other Considerations
Transportation constraints limiting the growth of PRB coal use
The rate at which coal shipments from the PRB (Montana and Wyoming) regions can be
increased is somewhat limited in the near-term by the capacity of the rail lines that transport the
coal from these regions. Hence, the following limits on the growth of PRB coal production are
implemented in IPM:
Wyoming PRB coal growth is limited to 15 million short tons additional production capacity
each year.
Montana coal growth is limited to 2 million short tons additional production capacity each year.
Table 9-23 Assumed Production Growth Rates
Coal Supply Source
Wyoming PRB
Montana
Growth/Year (MM short tons)
15
2
Other transportation constraints
This analysis does not consider the February 10, 2009 announcement by Norfolk Southern and
Canadian National Railway to share rail lines and enhance the efficiency of service out of the
Illinois Basin coal supply region (Mid-American Corridor). This announcement has the potential to
alleviate an existing bottleneck (both rate-based and logistical-based) that has historically
prevented large volumes of coal moving from the Illinois Basin to Southeastern coal-fired facilities,
although it is too early to know the full impact of this arrangement.
Global recession
The analysis underlying the coal transportation assumptions as described above was completed
prior to experiencing the full impact of the current global recession on the energy industry. In
addition to downward pressure on fuel and steel prices, the recession led to large declines in
industrial coal and electricity demand. Coal-fired plants, already faced with a glut of stockpiled
coal, saw excess supply further balloon due to relatively mild temperatures throughout 2009 and
historically low gas prices that led to some gas-fired facilities displacing more marginal, higher-
cost, coal-fired facilities. In the face of declining demand, coal transporters saw movements fall
dramatically as contracted tonnage was deferred and contracts were reworked. However, it
remains to be seen how, or if, transporters will adjust rates in the face of changing demand
dynamics. For example, railroads demonstrated little desire to lower rates in recent contract
negotiations even as coal volumes shipped by rail were off 9.3% from year-to-date 2008 levels as
of September 12, 2009.
9.4 Coal Exports, Imports, and Non-Electric Sectors Demand
The coal supply curves used in EPA Base Case v.4.10 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 2007 was used in electricity generation - non-electric 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, and non-electric sector coal demand are based on ElA's AEO
2010.
9-36
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In EPA Base Case v.4.10 coal exports and coal-serving residential, commercial and industrial
demand are designed to correspond as closely as possible to the projections in AEO 2010 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.4.10 are identified that are
contained in or overlap geographically with those EIA Coal Market Module (CMM) supply regions
and coal grades that are projected as serving exports and non-electric sector demand in AEO
2010. Next, coal for exports and non-electric demand are constrained by CMM supply region and
coal grade to meet the levels projected in AEO 2010. These levels are shown in Table 9-24 and
Table 9-25. (Since the AEO 2010 time horizon extends to 2035 and EPA Base Case v.4.10 to
2050, the AEO projected levels for 2035 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.4.10
than in AEO 2010 the specific regions and coal grades that serve export and non-electric sector
demand are not pre-specified but modeled.
Imported coal is assumed to cost 30.81 2007$/Ton, and is only available to plants in the eight
demand regions which are eligible to receive imported coal. The eight coal demand regions which
may receive imported coal, along with the cost of transporting this coal to the demand regions, are
summarized in Table 9-19. The total US imports of steam coal are limited as shown in Table 9-26.
Table 9-24 Coal Exports
Name
Rocky Mountains - Bituminous Low Sulfur
Central Appalachia - Bituminous Medium Sulfur
East Interior- Bituminous Medium Sulfur
Northern Appalachia - Bituminous Medium Sulfur
Wyoming Southern PRB - Subbituminous Low Sulfur
2012
1.24
6.69
6.46
4.57
0.03
2015
0.97
7.74
4.29
3.02
0.04
2020
0.45
7.4
0
0
0.05
2030
0.84
7.31
0
0
0.09
2040 -2050
1.08
6.96
0
0
0.12
9-37
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Table 9-25 Residential, Commercial, and Industrial Demand
Name
East Interior- Bituminous High Sulfur
Northern Appalachia - Bituminous High Sulfur
West Interior- Bituminous High Sulfur
Central Appalachia - Bituminous Low Sulfur
Southern Appalachia - Bituminous Low Sulfur
Rocky Mountain - Bituminous Low Sulfur
Arizona/New Mexico - Bituminous Low Sulfur
Central Appalachia - Bituminous Medium Sulfur
East Interior- Bituminous Medium Sulfur
Northern Appalachia - Bituminous Medium Sulfur
Southern Appalachia - Bituminous Medium Sulfur
Gulf Lignite- High Sulfur
Dakota Lignite - Medium Sulfur
Western Montana - Subbituminous Low Sulfur
Western Wyoming - Subbituminous Low Sulfur
Wyoming Northern PRB - Subbituminous Low Sulfur
Western Wyoming - Subbituminous Medium Sulfur
Arizona/New Mexico - Subbituminous Medium Sulfur
2012
6.84
1.12
1.59
4.8
0.21
3.78
0.41
13.3
0.82
4.02
1.36
2.46
5.26
0.43
0.92
3.85
1.03
0.1
2015
7.06
1.16
1.85
4.98
0.22
4.03
0.43
13.84
0.84
4.16
1.41
2.57
5.43
0.19
0.98
3.99
1.11
0.11
2020
7.1
1.16
1.99
5.01
0.22
4.1
0.44
13.93
0.84
4.17
1.42
2.59
5.46
0.03
1
4.01
1.14
0.11
2030
6.97
1.14
1.98
4.89
0.21
4.06
0.44
13.66
0.83
4.05
1.4
2.54
5.36
0
1
3.94
1.13
0.11
2040-
2050
6.88
1.12
1.95
4.8
0.21
3.97
0.43
13.42
0.82
3.97
1.37
2.49
5.3
0
0.98
3.88
1.1
0.11
Table 9-26 Coal Import Limits
Annual Coal Imports Cap (Million Short Tons)
2012
30.0
2015
28.9
2020
36.0
2030
36.2
2040-
2050
51.5
9-38
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Appendix 9-1. Illustrative Example of Wood Mackenzie Costing Procedure
Used in Developing EPA's Coal Supply Curves
To further demonstrate the procedures used in preparing Wood Mackenzie's cost tables, a sample
was prepared for the Colorado, Green River Basin, 0.81-1.20 Ibs. SO2/MMbtu coals. This region
was selected because it contains both surface and underground mines as well as existing (E) and
planned new mines (N).
The initial step was to prepare cost models for the selected mines. The mine names have been
replaced with mine step designations: E01, E02, EOS, N01, N02 and N03. Production and
productivity assumptions for the mines have been modified to mask the mines selected for this
sample procedure. Cost models were prepared for E01, E02, EOS, N02 and N03. N01 was not
modeled because it is a proposed replacement for EOS and is expected to have a cost structure
very similar to EOS. The cost model was run in 2008$ and used to solve for the sales price
required to return a 10% DCFROR for the mine.
In the following pages of this appendix individual cost models (in the form of a series of
spreadsheets) are provided for mines E01_S, EO2JJG, EO3JJG, NO2JJG, and NO3JJG,
Each mine's spreadsheet consists of 4 pages that capture the costs and cash flows for the mines
over the 2008 - 2035 time period. The first page in each spreadsheet model provides production
and productivity data for the mine. The second page shows its capital requirements. The third
page contains a summary of capital expenditures. The fourth page pulls together all costs and
cash flows and (in the third row from the top) derives the required sales price on the assumption of
a 10% rate of return.
The model results obtained for each mine were then loaded into the "EPA Cost Curve Worksheet,"
which appears on the last page of this appendix. (The "sales prices ($/ton)" from the mine costing
models can be seen in the 11th column ("Cost of Production (2008$)") of the cost curve worksheet.
This worksheet also contains EPA's coal region and coal type data as well as Wood Mackenzie
region and type codes. (The Wood Mackenzie codes were included to assist in the proper
assignment of costs for areas where cost data was prepared and grouped based on Wood
Mackenzie codes.) Additional data includes mine names, step names, codes for existing or new
mines, mine type (used for western mines), heat content, production rate and reserves.
In conjunction with transferring the costs generated for each mine to the "EPA Cost Curve
Worksheet," a number of adjustments were made to support their use in EPA's IPM electric sector
model:
(1) There are a number of differences in the values appearing in the 11th column and the
corresponding "sales price" values that appeared in the individual mine costing models. For
example, it was assumed the N01 production costs would be the same as the mine it is replacing
but additional transportation will be required to move the coal to the mine loadout and partial
washing would take place. To account for these additional costs $1.00/ton was added to the Cost
of Production of EOS to estimate the cost for N01. In the case of N03, it was assumed that
additional transportation from the mine mouth to the loadout will be required so an additional
$1.00/ton was added to the model results. This adjustment was based on a separate modeling
analysis that Wood Mackenzie performed to estimate the cost of production at N03. Because this
modeling contained mine specific and proprietary data, it could not be included in this appendix.
(2) Because the mine costing model estimates were prepared in 2008$, the costs were converted
(deflated) to constant 2007$, which is the cost basis used in EPA Base Case v.4.10. (This
conversion can be seen in the 11th ("Cost of Production (2008$)") and 12th ("Cost of Production
(2007$)") columns of the Cost Curve Worksheet.)
Appendix 9-1.1
-------
(3) In running the individual cost models for new mines, Wood Mackenzie makes certain
assumptions regarding the start-up date for the mine. In transferring the costs generated by the
cost models to the EPA Cost Curve Worksheet it is assumed that the new mines could be opened
by 2012 if demand exists and EPA's IPM model is allowed to determine when the mine will be
opened.
(4) Wood Mackenzie has assumed that labor productivity in all Producing Regions except Central
Appalachia will increase at a rate of 1% per year. Productivity in Central Appalachia is expected to
fall 1 % per year. These productivity assumptions affect future Cost of Production estimates. All
regions except Central Appalachia were deflated 0.4% per year while it was inflated by 0.4% per
year. The 0.4% adjustment is based on the assumption that labor costs on average account for
40% of the Cost of Production. In the EPA Cost Curve Worksheet the productivity adjustments
appear in the 13th ("deflator") and 14th ("deflated cost") columns. The 0.4% productivity growth
assumption means that in the 4 years between 2008 (the net present value year used in the mine
costing spreadsheets) and 2012 (the first model year in EPA's IPM base case) productivity would
increase by a factor of 1.02 (shown in the 13th column) and, consequently, the cost shown in the
12th column would have to be divided by this deflator (13th column) to obtain the deflated costs
shown in the 14th column
(5) Costs were then rounded by the procedure described above in section 9.3.8 to obtain the
"Final Cost" values shown in the 15th column.
Besides the adjustments described above and shown in the cost curve worksheet, other
adjustments to costs were made to meet EPA's need for cost and production data out to 2040 and
beyond. Wood Mackenzie's cost models are generally run for a maximum of 20 years even
though additional, higher cost reserves are known to exist. When production and reserve data
were pushed past reserve estimates typically used in the cost models, additional reserves were
added and costs were increased. Appendix 9-2 lists the new mines that were included in the 2040
curves. As a quality assurance check, if additional reserves were assigned to any coal region and
type, the resulting totals were tested against EIA Reserve Estimate - 2006 (Table 15_06) to
insure reserves were not overstated and to establish an upper geologic limit for reserves in any
area.
Appendix 9-1.2
-------
Appendix 9-1 (Cont'd) Illustrative Example
Mine:
Production Data
Year Tons
(000)
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
50,000
$/ton
In-Situ
DLYds T/SYds Total Yds Ratio
(000) (000) (000)
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
24,500
9.8
9.8
9.8
9.8
9.8
9.8
9.8
9.8
9.8
9.8
9.8
9.8
9.8
9.8
9.8
9.8
9.8
9.8
9.8
9.8
490,000 0 490,000 9.8
Effective
DL% DLYds T/SYds Total Yds Ratio
Rehandle (000) (000) (000)
10%
10%
10%
10%
10%
10%
10%
10%
10%
10%
10%
10%
10%
10%
10%
10%
10%
10%
10%
10%
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
26,950
10.8
10.8
10.8
10.8
10.8
10.8
10.8
10.8
10.8
10.8
10.8
10.8
10.8
10.8
10.8
10.8
10.8
10.8
10.8
10.8
539,000 0 539,000 10.8
Appendix 9-1.3
-------
Mine: E01_S
Capital Requirements ($ X 1000)
Capital Contingency: 0%
Miles of Rail spur: 0
Coal Storage: 10000
Year
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
Acqisition
0
0.00
Develop.
0
0
0.00
Rail
0
0
0.00
Facilities
15,878
15,878
0.32
Truck Shovel
Initial Repl
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
o
0
0
0
0
0
0
0
0
0
0 0
0.00 0.00
Dragline
Initial Repl
64,680
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
64,680 0
1.29 0.00
Coal Load & Haul
Initial Repl
9,720
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
4,082
0
0
0
0
0
0
0
0
0
9,720 4,082
0.19 0.08
Miscellaneous
Initial Repl
16,368
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
16,368
0
o
0
0
o
0
16,368
0
0
0
0
o
16,368 32,736
0.33 0.65
Total
Initial Repl
106,646
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
16,368
0
0
4,082
0
0
0
16,368
0
0
0
0
0
106,646 36,818
2.13 0.74
Appendix 9-1.4
-------
Mine: E01 S
Capital Expenditure Summary
Year
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
Acquisition
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Development
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Depreciable
Assets
106,646
0
0
0
0
0
0
16,368
0
0
4,082
0
0
0
16,368
0
0
0
0
0
143,464
Property Tax
Base
106,646
106,646
106,646
106,646
106,646
106,646
106,646
106,646
106,646
106,646
106,646
106,646
106,646
106,646
106,646
106,646
106,646
106,646
106,646
106,646
Depreciation
14,025
14,025
14,025
14,025
14,025
14,025
14,025
3,397
,397
,397
,980
,980
,980
,980
,980
2,921
2,921
2,338
2,338
2,338
141,126
Working
Capital
3,993
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-3,993
0
Total
Capital
110,639
0
0
0
0
0
0
16,368
0
0
4,082
0
0
0
16,368
0
0
0
0
-3,993
143,464
Appendix 9-1.5
-------
Mine: E01_S
Required Sales Price
Sales Price ($/ton): $20.716
Discount Rate: 10%
Net Present Value: $0
Cost Contingency Factors: 10%
Initial Labor Productivity (t/mh): 9
Average Coal Thickness (ft): 45
UMWA(YorN): N
Sev. Taxes:
Property Taxes
Income Taxes:
Royalty:
Rate ($/ton)
Adjustment
Mill Levy (in mills):
Assessment rate:
Federal
State
$0.54
0%
44
25%
34%
6%
12.5%
Year
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
Tons
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
2,500
50,000
Revenue
51,789
51,789
51,789
51,789
51,789
51,789
51,789
51,789
51,789
51,789
51,789
51,789
51,789
51,789
51,789
51,789
51,789
51,789
51,789
51,789
1,035,785
20.72
Direct
Operating
Cost
23,958
23,958
23,958
23,958
23,958
23,958
23,958
23,958
23,958
23,958
23,958
23,958
23,958
23,958
23,958
23,958
23,958
23,958
23,958
23,958
479,159
9.58
Royalty
6,474
6,474
6,474
6,474
6,474
6,474
6,474
6,474
6,474
6,474
6,474
6,474
6,474
6,474
6,474
6,474
6,474
6,474
6,474
6,474
129,473
2.59
Taxes (other than income)
Severance
702
702
702
702
702
702
702
702
702
702
702
702
702
702
702
702
702
702
702
702
14,040
0.28
Black
Lung
,375
,375
,375
,375
,375
,375
,375
,375
,375
,375
,375
,375
,375
,375
,375
,375
,375
,375
,375
,375
27,500
0.55
Reel.
875
875
875
875
875
875
875
875
875
875
875
875
875
875
875
875
875
875
875
875
17,500
0.35
Property
570
570
570
570
570
570
570
570
570
570
570
570
570
570
570
570
570
570
570
570
11,394
0.23
Development
Cost
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.00
Depreciation
14,025
14,025
14,025
14,025
14,025
14,025
14,025
,397
,397
,397
,980
,980
,980
,980
,980
2,921
2,921
2,338
2,338
2,338
141,126
2.82
Depletion
306
306
306
306
306
306
306
,625
,625
,625
,625
,625
,625
,625
,625
,625
,625
,625
,625
,625
49,271
0.99
Taxes
122
122
122
122
122
122
122
3,046
3,046
3,046
2,813
2,813
2,813
2,813
2,813
3,236
3,236
3,470
3,470
3,470
40,943
0.82
Net Income
184
184
184
184
184
184
184
4,569
4,569
4,569
4,219
4,219
4,219
4,219
4,219
4,855
4,855
5,205
5,205
5,205
61,414
1.23
Operating
Cash
Flow
14,515
14,515
14,515
14,515
14,515
14,515
14,515
11,591
11,591
11,591
11,825
11,825
11,825
11,825
11,825
11,401
11,401
11,168
11,168
11,168
251,811
5.04
Capital
Expenditures
110,639
0
0
0
0
0
0
16,368
0
0
4,082
0
0
0
16,368
0
0
0
0
-3,993
143,464
2.87
Annual
Cash
Flow
-96,124
14,515
14,515
14,515
14,515
14,515
14,515
-4,777
11,591
11,591
7,742
11,825
11,825
11,825
-4,543
11,401
11,401
11,168
11,168
15,161
108,347
2.17
Appendix 9-1.6
-------
Appendix 9-1.7
-------
Mine: E02 UG
Production & Productivity Data
% Washed 70%
Plant Recovery: 70%
Production by Equipment at Full Production
% Longwall Production: 80%
% CM Production: 20%
% CV Production: 0%
Year
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
$/ton
Clean
Tons
(000)
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
42,000
CVROM
Tons
(000)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
CM ROM
Tons
(000)
506
506
506
506
506
506
506
506
506
506
506
506
506
506
506
506
506
506
506
506
506
10,634
LWROM
Tons
(000)
2,026
2,026
2,026
2,026
2,026
2,026
2,026
2,026
2,026
2,026
2,026
2,026
2,026
2,026
2,026
2,026
2,026
2,026
2,026
2,026
2,026
42,538
Total ROM
Tons
(000)
2,532
2,532
2,532
2,532
2,532
2,532
2,532
2,532
2,532
2,532
2,532
2,532
2,532
2,532
2,532
2,532
2,532
2,532
2,532
2,532
2,532
53,172
Overall
Recovery
%
79%
79%
79%
79%
79%
79%
79%
79%
79%
79%
79%
79%
79%
79%
79%
79%
79%
79%
79%
79%
79%
79%
Haul
Distance
(miles)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Appendix 9-1.8
-------
Mine: E02_UG
Capital Requirements ($ X 1000)
Capital Contingency
Miles of Rail spur:
Coal Storage:
Depth to Shafts:
No. of Men/Supply Shafts
No. of Air Shafts
0
0
100
1
1
CV Mining Ht:
CM Mining Ht:
LW Mining Ht:
Capital Contingency:
Shafts:
if prod < 1000k, 1 M&S + 1 Air
if prod > 1000k, 2 M&S+1 Air
Year
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
Acqisition
0
0.00
Exploration
&
Engineering
1,920
1,920
0.05
Development
Labor
59,940
59,940
1.43
Shaft
Capital
Cost
13,774
13,774
0.33
Surface
Facilities
& Equip.
11,391
11,391
0.27
Prep Plant
18,990
18,990
Rail
0
0
0.00
Conventional Sections
Units Initial Repl
Required $ $
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0 0
0.00 0.00
Continuous Miners
Units Initial Repl
Required $ $
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
2
9,000
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
9,000
0
0
0
0
0
0
9,000
0
0
0
9,000 18,000
0.21 0.43
Longwalls
Units Initial Repl
Required $ $
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
37,500
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
37,500
0
0
0
0
0
0
37,500
0
0
0
37,500 75,000
0.89 1.79
Fixed U/G Equip.
Initial Repl
$ $
20,629
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
20,629
0
0
0
0
0
0
20,629
0
0
0
20,629 41,257
0.49 0.98
Total
Initial Repl
$ $
173,144
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
67,129
0
0
0
0
0
0
67,129
0
0
0
0
0
0
173,144 134,257
4.12 3.20
Appendix 9-1.9
-------
Mine: E02 UG
Capital Expenditure Summary
Year
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
Acquisition
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.00
Exploration
&
Engineering
1,920
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1,920
0.05
Depreciable Assets
7 Year Life 15 Year Life Total
67,129
0
0
0
0
0
0
67,129
0
0
0
0
0
0
67,129
0
0
0
0
0
0
104,095
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
171,224
0
0
0
0
0
0
67,129
0
0
0
0
0
0
67,129
0
0
0
0
0
0
201,386 104,095 305,481
4.79 2.48 7.27
Property Tax
Base
171,224
171,224
171,224
171,224
171,224
171,224
171,224
171,224
171,224
171,224
171,224
171,224
171,224
171,224
171,224
171,224
171,224
171,224
171,224
171,224
171,224
Depreciation
7 Year Life 1 5 Year Life Total
9,590
9,590
9,590
9,590
9,590
9,590
9,590
9,590
9,590
9,590
9,590
9,590
9,590
9,590
9,590
9,590
9,590
9,590
9,590
9,590
9,590
6,940
6,940
6,940
6,940
6,940
6,940
6,940
6,940
6,940
6,940
6,940
6,940
6,940
6,940
6,940
0
0
0
0
0
0
16,529
16,529
16,529
16,529
16,529
16,529
16,529
16,529
16,529
16,529
16,529
16,529
16,529
16,529
16,529
9,590
9,590
9,590
9,590
9,590
9,590
201,386 104,095 305,481
4.79 2.48 7.27
Working
Capital
5,789
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-5,789
0
0.00
Total
Capital
178,933
0
0
0
0
0
0
67,129
0
0
0
0
0
0
67,129
0
0
0
0
0
-5,789
307,401
7.32
Appendix 9-1.10
-------
Mine: E02_UG
Required Sales Price (S X 1000)
Sales Price ($/ton):
Discount Rate:
Net Present Value:
Cost Contingency Factors:
Average Coal Thickness (ft):
Tons/Man-hour
UMWA (Y or N):
Product (Steam or Met)
6
6.0
Y
S
Sev. Taxes: Rate
Adjustment
Prop. Taxes Tax Rate (in mills)
% of revenue basis for tax
Assessment rate:
Income Taxes Federal
State
Royalty
% of Reserve owned:
Year
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
Tons
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
2,000
42,000
Revenue
72,953
72,953
72,953
72,953
72,953
72,953
72,953
72,953
72,953
72,953
72,953
72,953
72,953
72,953
72,953
72,953
72,953
72,953
72,953
72,953
72,953
1,532,003
36.48
Direct
Operating
Cost
34,737
34,737
34,737
34,737
34,737
34,737
34,737
34,737
34,737
34,737
34,737
34,737
34,737
34,737
34,737
34,737
34,737
34,737
34,737
34,737
34,737
729,469
17.37
Royalty
5,836
5,836
5,836
5,836
5,836
5,836
5,836
5,836
5,836
5,836
5,836
5,836
5,836
5,836
5,836
5,836
5,836
5,836
5,836
5,836
5,836
122,560
2.92
Taxes (other than income)
Severance
216
216
216
216
216
216
216
216
216
216
216
216
216
216
216
216
216
216
216
216
216
4,536
0.11
Black
Lung
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
46,200
1.10
Reel.
300
300
300
300
300
300
300
300
300
300
300
300
300
300
300
300
300
300
300
300
300
6,300
0.15
Property
1,007
1,007
1,007
1,007
1,007
1,007
1,007
1,007
1,007
1,007
1,007
1,007
1,007
1,007
1,007
1,007
1,007
1,007
1,007
1,007
1,007
21,142
0.50
Corp G&A,
Selling &
Ace. Pen.
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
2,200
46,200
1.10
Development
Cost
1,920
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1,920
0.05
Depreciation
16,529
16,529
16,529
16,529
16,529
16,529
16,529
16,529
16,529
16,529
16,529
16,529
16,529
16,529
16,529
9,590
9,590
9,590
9,590
9,590
9,590
305,481
Depletion
4,004
4,964
4,964
4,964
4,964
4,964
4,964
4,964
4,964
4,964
4,964
4,964
4,964
4,964
4,964
5,369
5,369
5,369
5,369
5,369
5,369
105,712
2 52
Taxes
1,601
1,985
1,985
1,985
1,985
1,985
1,985
1,985
1,985
1,985
1,985
1,985
1,985
1,985
1,985
4,599
4,599
4,599
4,599
4,599
4,599
56,993
1.36
Net Income
2,402
2,978
2,978
2,978
2,978
2,978
2,978
2,978
2,978
2,978
2,978
2,978
2,978
2,978
2,978
6,899
6,899
6,899
6,899
6,899
6,899
85,490
2.04
Operating
Cash
Flow
22,935
24,471
24,471
24,471
24,471
24,471
24,471
24,471
24,471
24,471
24,471
24,471
24,471
24,471
24,471
21,858
21,858
21,858
21,858
21,858
21,858
496,683
11.83
Capital
Expenditures
177,013
0
0
0
0
0
0
67,129
0
0
0
0
0
0
67,129
0
0
0
0
0
-5,789
305,481
Annual
Cash
Flow
-154,078
24,471
24,471
24,471
24,471
24,471
24,471
-42,657
24,471
24,471
24,471
24,471
24,471
24,471
-42,657
21,858
21,858
21,858
21,858
21,858
27,647
191,202
4.55
Appendix 9-1.11
-------
Mine: E03 UG
Production & Productivity Data
% Washed 0%
Plant Recovery: 100%
Production by Equipment at Full Production
% Longwall Production: 80%
% CM Production: 20%
% CV Production: 0%
Year
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
$/ton
Clean
Tons
(000)
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
189,000
CVROM
Tons
(000)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
CM ROM
Tons
(000)
1,800
1,800
1,800
1,800
1,800
1,800
1,800
1,800
1,800
1,800
1,800
1,800
1,800
1,800
1,800
1,800
1,800
1,800
1,800
1,800
1,800
37,800
LWROM
Tons
(000)
7,200
7,200
7,200
7,200
7,200
7,200
7,200
7,200
7,200
7,200
7,200
7,200
7,200
7,200
7,200
7,200
7,200
7,200
7,200
7,200
7,200
151,200
Total ROM
Tons
(000)
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
189,000
Overall
Recovery
%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
Haul
Distance
(miles)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Appendix 9-1.12
-------
Mine: E03_UG
Capital Requirements ($ X 1000)
Capital Contingency:
Miles of Rail spur:
Coal Storage:
Depth to Shafts:
No. of Men/Supply Shafts
No. of Air Shafts
0
0
100
1
1
CV Mining Ht:
CM Mining Ht:
LW Mining Ht:
Capital Contingency:
Shafts:
if prod < 1000k, 1 M&S+ 1 Air
if prod > 1000k, 2 M&S + 1 Air
Year
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
Acqisition
0
0.00
Exploration
&
Engineering
2,590
2,590
0.01
Development
Labor
91,705
91,705
0.49
Shaft
Capital
Cost
9,183
9,183
0.05
Surface
Facilities
& Equip.
11,878
11,878
0.06
Prep Plant
0
0
Rail
0
0
0.00
Conventional Sections
Units Initial Repl
Required $ $
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0 0
0.00 0.00
Continuous Miners
Units Initial Repl
Required $ $
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
4
12,000
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
12,000
0
0
0
0
0
0
12,000
0
0
0
12,000 24,000
0.06 0.13
ongwall initial 1 00 million $
Longwalls
Units Initial Repl
Required $ $
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
100,000
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
100,000
0
0
0
0
0
0
100,000
0
0
0
100,000 200,000
0.53 1.06
Fixed U/G Equip.
Initial Repl
$ $
31,562
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
31,562
0
0
0
0
0
0
31,562
0
0
0
31,562 63,124
0.17 0.33
Total
Initial Repl
$ $
258,917
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
143,562
0
0
0
0
0
0
143,562
0
0
0
0
0
0
258,917 287,124
1.37 1.52
Appendix 9-1.13
-------
Mine: E03JJG
Capital Expenditure Summary
Year
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
Acquisition
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.00
Exploration
&
Engineering
2,590
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2,590
0.01
Depreciable Assets
7 Year Life 1 5 Year Life Total
143,562
0
0
0
0
0
0
143,562
0
0
0
0
0
0
143,562
0
0
0
0
0
0
112,766
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
256,327
0
0
0
0
0
0
143,562
0
0
0
0
0
0
143,562
0
0
0
0
0
0
430,685 112,766 543,451
2.28 0.60 2.88
Property Tax
Base
256,327
256,327
256,327
256,327
256,327
256,327
256,327
256,327
256,327
256,327
256,327
256,327
256,327
256,327
256,327
256,327
256,327
256,327
256,327
256,327
256,327
Depreciation
7 Year Life 1 5 Year Life Total
20,509
20,509
20,509
20,509
20,509
20,509
20,509
20,509
20,509
20,509
20,509
20,509
20,509
20,509
20,509
20,509
20,509
20,509
20,509
20,509
20,509
7,518
7,518
7,518
7,518
7,518
7,518
7,518
7,518
7,518
7,518
7,518
7,518
7,518
7,518
7,518
0
0
0
0
0
0
28,027
28,027
28,027
28,027
28,027
28,027
28,027
28,027
28,027
28,027
28,027
28,027
28,027
28,027
28,027
20,509
20,509
20,509
20,509
20,509
20,509
430,685 112,766 543,451
2.28 0.60 2.88
Working
Capital
19,092
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-19,092
0
0.00
Total
Capital
278,009
0
0
0
0
0
0
143,562
0
0
0
0
0
0
143,562
0
0
0
0
0
-19,092
546,041
2.89
Year
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
Appendix 9-1.14
-------
Mine: E03JJG
Required Sales Price (S X 1000)
Sales Price (S/ton):
Discount Rate:
Net Present Value:
Cost Contingency Factors:
Average Coal Thickness (ft):
Tons/Man-hour
UMWA (Y or N):
Product (Steam or Met)
Sev. Taxes: Rate
Adjustment
Prop. Taxes Tax Rate (in mills)
% of revenue basis for tax
Assessment rate:
Income Taxes Federal
State
Royalty
% of Reserve owned:
Year
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
Tons
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
9,000
189,000
Revenue
192,950
192,950
192,950
192,950
192,950
192,950
192,950
192,950
192,950
192,950
192,950
192,950
192,950
192,950
192,950
192,950
192,950
192,950
192,950
192,950
192,950
4,051,948
21.44
Direct
Operating
Cost
114,552
114,552
114,552
114,552
114,552
114,552
114,552
114,552
114,552
114,552
114,552
114,552
114,552
114,552
114,552
114,552
114,552
114,552
114,552
114,552
114,552
2,405,584
12.73
Royalty
15,436
15,436
15,436
15,436
15,436
15,436
15,436
15,436
15,436
15,436
15,436
15,436
15,436
15,436
15,436
15,436
15,436
15,436
15,436
15,436
15,436
324,156
1.72
Taxes (other than income)
Severance
2,106
2,106
2,106
2,106
2,106
2,106
2,106
2,106
2,106
2,106
2,106
2,106
2,106
2,106
2,106
2,106
2,106
2,106
2,106
2,106
2,106
44,226
0.23
Black
Lung
8,490
8,490
8,490
8,490
8,490
8,490
8,490
8,490
8,490
8,490
8,490
8,490
8,490
8,490
8,490
8,490
8,490
8,490
8,490
8,490
8,490
178,286
0.94
Reel.
,350
,350
,350
,350
,350
,350
,350
,350
,350
,350
,350
,350
,350
,350
,350
,350
,350
,350
,350
,350
,350
28,350
0.15
Property
2,663
2,663
2,663
2,663
2,663
2,663
2,663
2,663
2,663
2,663
2,663
2,663
2,663
2,663
2,663
2,663
2,663
2,663
2,663
2,663
2,663
55,917
0.30
Corp G&A,
Selling &
Ace. Pen.
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
92,400
0.49
Development
Cost
2,590
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2,590
0.01
Depreciation
28,027
28,027
28,027
28,027
28,027
28,027
28,027
28,027
28,027
28,027
28,027
28,027
28,027
28,027
28,027
20,509
20,509
20,509
20,509
20,509
20,509
543,451
2.88
Depletion
6,669
7,964
7,964
7,964
7,964
7,964
7,964
7,964
7,964
7,964
7,964
7,964
7,964
7,964
7,964
11,722
11,722
11,722
11,722
11,722
11,722
188,494
1.00
Taxes
2,667
3,185
3,185
3,185
3,185
3,185
3,185
3,185
3,185
3,185
3,185
3,185
3,185
3,185
3,185
4,689
4,689
4,689
4,689
4,689
4,689
75,398
0.40
Net Income
4,001
4,778
4,778
4,778
4,778
4,778
4,778
4,778
4,778
4,778
4,778
4,778
4,778
4,778
4,778
7,033
7,033
7,033
7,033
7,033
7,033
113,096
0.60
Operating
Cash
Flow
38,696
40,768
40,768
40,768
40,768
40,768
40,768
40,768
40,768
40,768
40,768
40,768
40,768
40,768
40,768
39,265
39,265
39,265
39,265
39,265
39,265
845,041
4.47
Capital
Expenditures
275,419
0
0
0
0
0
0
143,562
0
0
0
0
0
0
143,562
0
0
0
0
0
-19,092
543,451
2.88
Annual
Cash
Flow
-236,723
40,768
40,768
40,768
40,768
40,768
40,768
-102,793
40,768
40,768
40,768
40,768
40,768
40,768
-102,793
39,265
39,265
39,265
39,265
39,265
58,357
301,590
1.60
Appendix 9-1.15
-------
Mine: N02 UG
Production & Productivity Data
% Washed 0%
Plant Recovery: 100%
Production by Equipment at Full Production
% Longwall Production: 80%
% CM Production: 20%
% CV Production: 0%
Year
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
$/ton
Clean
Tons
(000)
500
3,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
98,500
CVROM
Tons
(000)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
CM ROM
Tons
(000)
500
600
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
20,100
LWROM
Tons
(000)
0
2,400
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
78,400
Total ROM
Tons
(000)
500
3,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
98,500
Overall
Recovery
%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
Haul
Distance
(miles)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Appendix 9-1.16
-------
Mine: N02_UG
Capital Requirements ($ X 1000)
Capital Contingency:
Miles of Rail spur:
Coal Storage:
Depth to Shafts:
No. of Men/Supply Shafts
No. of Air Shafts
0%
0
0
1000
1
1
CV Mining Ht:
CM Mining Ht:
LW Mining Ht:
Capital Contingency:
production
-75% < 500k
-50% 500k<= & < 750k
0% >750k
if prod < 1000k, 1 M&S+ 1 Air
if prod > 1000k, 2 M&S + 1 Air
Year
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
Acqisition
0
0.00
Exploration
&
Engineering
350
350
350
1,030
2,080
0.02
Development
Labor
0
0
0
30,085
30,085
0.31
Shaft
Capital
Cost
0
0
0
45,174
45,174
0.46
Surface
Facilities
& Equip.
6,777
6,777
0.07
Prep Plant
0
0
0
0
0
Rail
0
0
0
0
0
0.00
Conventional Sections
Units Initial Repl
Required $ $
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0 0
0.00 0.00
Continuous Miners
Units Initial Repl
Required $ $
0
0
0
0
2
2
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
0
0
0
0
6,000
0
3,000
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
6,000
0
3,000
0
0
0
0
9,000 9,000
0.09 0.09
Longwalls
Units Initial Repl
Required $ $
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
0
0
0
25,000
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
25,000
0
0
0
0
0
25,000 25,000
0.25 0.25
Fixed U/G Equip.
Initial Repl
$ $
1,109
0
0
0
1,631
6,798
816
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1,109
0
0
0
1,631
6,798
816
1,109
0
0
0
10,354 11,463
0.11 0.12
Total
Initial Repl
$ $
1,459
350
350
52,981
7,631
31,798
3,816
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1,109
0
0
0
7,631
31,798
3,816
1,109
0
0
0
0
0
0
0
0
0
0
98,384 45,463
1.00 0.46
Appendix 9-1.17
-------
Mine: N02_UG
Capital Expenditure Summary
Year
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
Acquisition
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.00
Exploration
&
Engineering
350
350
350
1,030
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2,080
0.02
Depreciable Assets
7 Year Life 15 Year Life Total
1,109
0
0
0
7,631
31,798
3,816
1,109
0
0
0
7,631
31,798
3,816
1,109
0
0
0
0
0
0
0
0
0
0
0
0
0
82,036
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1,109
0
0
82,036
7,631
31,798
3,816
1,109
0
0
0
7,631
31,798
3,816
1,109
0
0
0
0
0
0
0
0
0
0
89,816 82,036 171,852
0.91 0.83 1.74
Property Tax
Base
1,109
1,109
1,109
53,060
60,691
92,489
96,304
96,304
96,304
96,304
96,304
96,304
96,304
96,304
96,304
96,304
96,304
96,304
96,304
96,304
96,304
96,304
96,304
96,304
96,304
Depreciation
7 Year Life 15 Year Life Total
158
158
158
158
1,249
5,791
6,336
6,336
6,336
6,336
6,336
6,336
6,336
6,336
6,336
6,336
6,336
6,336
5,246
704
158
0
0
0
0
0
0
0
5,469
5,469
5,469
5,469
5,469
5,469
5,469
5,469
5,469
5,469
5,469
5,469
5,469
5,469
5,469
0
0
0
0
0
0
0
158
158
158
5,627
6,718
11,260
11,805
11,805
11,805
11,805
11,805
11,805
11,805
11,805
11,805
11,805
11,805
11,805
5,246
704
158
0
0
0
0
89,816 82,036 171,852
0.91 0.83 1.74
Working
Capital
0
0
0
0
1,015
4,840
3,903
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-9,759
0
0.00
Total
Capital
1,459
350
350
83,066
8,646
36,638
7,719
1,109
0
0
0
7,631
31,798
3,816
1,109
0
0
0
0
0
0
0
0
0
-9,759
173,932
1.77
Year
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
Appendix 9-1.18
-------
Mine: N02JJG
Required Sales Price (S X 1000)
Sales Price (S/ton):
Discount Rate:
Net Present Value:
Cost Contingency Factors:
Average Coal Thickness (ft):
Tons/Man-hour
UMWA(YorN):
Product (Steam or Met)
Sev. Taxes: Rate
Adjustment
Prop. Taxes Tax Rate (in mills)
% of revenue basis for tax
Assessment rate:
Income Taxes Federal
State
Royalty
% of Reserve owned:
Year
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
Tons
0
0
0
0
500
3,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
98,500
Revenue
0
0
0
0
10,003
60,021
100,035
100,035
100,035
100,035
100,035
100,035
100,035
100,035
100,035
100,035
100,035
100,035
100,035
100,035
100,035
100,035
100,035
100,035
100,035
1,970,686
20.01
Direct
Operating
Cost
0
0
0
0
6,089
35,131
58,551
58,551
58,551
58,551
58,551
58,551
58,551
58,551
58,551
58,551
58,551
58,551
58,551
58,551
58,551
58,551
58,551
58,551
58,551
1,153,690
11.71
Royalty
0
0
0
0
800
4,802
8,003
8,003
8,003
8,003
8,003
8,003
8,003
8,003
8,003
8,003
8,003
8,003
8,003
8,003
8,003
8,003
8,003
8,003
8,003
157,655
1.60
Taxes (other than income)
Severance
0
0
0
0
0
486
,026
,026
,026
,026
,026
,026
,026
,026
,026
,026
,026
,026
,026
,026
,026
,026
,026
,026
,026
19,980
0.20
Black
Lung
0
0
0
0
440
2,641
4,402
4,402
4,402
4,402
4,402
4,402
4,402
4,402
4,402
4,402
4,402
4,402
4,402
4,402
4,402
4,402
4,402
4,402
4,402
86,710
0.88
Reel.
0
0
0
0
75
450
750
750
750
750
750
750
750
750
750
750
750
750
750
750
750
750
750
750
750
14,775
0.15
Property
0
0
0
0
138
828
1,380
1,380
1,380
1,380
1,380
1,380
1,380
1,380
1,380
1,380
1,380
1,380
1,380
1,380
1,380
1,380
1,380
1,380
1,380
27,195
0.28
Corp G&A,
Selling &
Ace. Pen.
0
0
0
0
550
3,300
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
87,450
0.89
Development
Cost
350
350
350
1,030
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
2,080
0.02
Depreciation
158
158
158
5,627
6,718
11,260
11,805
11,805
11,805
11,805
11,805
11,805
11,805
11,805
11,805
11,805
11,805
11,805
5,246
704
158
0
0
0
0
171,852
1.74
Depletion
0
0
0
0
0
562
4,859
4,859
4,859
4,859
4,859
4,859
4,859
4,859
4,859
4,859
4,859
4,859
7,363
7,363
7,363
7,363
7,363
7,363
7,363
110,405
1.12
Taxes
-203
-203
-203
-2,663
-1,923
225
,944
,944
,944
,944
,944
,944
,944
,944
,944
,944
,944
,944
3,566
5,383
5,601
5,664
5,664
5,664
5,664
55,557
0.56
Net Income
-305
-305
-305
-3,994
-2,884
337
2,915
2,915
2,915
2,915
2,915
2,915
2,915
2,915
2,915
2,915
2,915
2,915
5,349
8,074
8,401
8,496
8,496
8,496
8,496
83,336
0.85
Operating
Cash
Flow
-147
-147
-147
1,633
3,834
12,159
19,579
19,579
19,579
19,579
19,579
19,579
19,579
19,579
19,579
19,579
19,579
19,579
17,957
16,140
15,922
15,859
15,859
15,859
15,859
365,593
3.71
Capital
Expenditures
1,109
0
0
82,036
8,646
36,638
7,719
1,109
0
0
0
7,631
31,798
3,816
1,109
0
0
0
0
0
0
0
0
0
-9,759
171,852
1.74
Annual
Cash
Flow
-1,256
-147
-147
-80,403
-4,812
-24,479
11,860
18,470
19,579
19,579
19,579
11,948
-12,218
15,764
18,470
19,579
19,579
19,579
17,957
16,140
15,922
15,859
15,859
15,859
25,617
193,741
1.97
Appendix 9-1.19
-------
Mine: N03 UG
Production & Productivity Data
% Washed 0%
Plant Recovery: 100%
Production by Equipment at Full Production
% Longwall Production: 80%
% CM Production: 20%
% CV Production: 0%
Year
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
$/ton
Clean
Tons
(000)
1,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
86,000
CVROM
Tons
(000)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
CM ROM
Tons
(000)
0
0
0
200
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
1,000
17,200
LWROM
Tons
(000)
0
0
0
800
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
4,000
68,800
Total ROM
Tons
(000)
0
0
0
1,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
86,000
Overall
Recovery
%
#DIV/0!
#DIV/0!
#DIV/0!
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
100%
Haul
Distance
(miles)
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
Appendix 9-1.20
-------
Mine: N03_UG
Capital Requirements ($ X 1000)
Capital Contingency:
Miles of Rail spur:
Coal Storage:
Depth to Shafts:
No. of Men/Supply Shafts
No. of Air Shafts
0%
0
0
100
1
1
CV Mining Ht:
CM Mining Ht:
LW Mining Ht:
Capital Contingency:
Shafts:
production
-75% < 500k
-50% 500k<= & < 750k
0% >750k
if prod < 1000k, 1 M&S + 1 Air
if prod > 1000k, 2 M&S + 1 Air
Year
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
Acqisition
0
0.00
Exploration
&
Engineering
350
350
350
350
350
350
1,530
3,630
0.04
Development
Labor
0
0
0
0
0
0
49,835
49,835
0.58
Shaft
Capital
Cost
0
0
0
0
0
0
9,183
9,183
0.11
Surface
Facilities
& Equip.
8,412
8,412
0.10
Prep Plant
0
0
0
0
0
0
0
0
Rail
0
0
0
0
0
0
0
0
0.00
Conventional Sections
Units Initial Repl
Required $ $
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0 0
0.00 0.00
Continuous Miners
Units Initial Repl
Required $ $
0
0
0
0
0
0
0
1
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
3
0
0
0
0
0
0
0
3,000
6,000
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3,000
6,000
0
0
9,000 9,000
0.10 0.10
Longwalls
Units Initial Repl
Required $ $
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
0
0
0
0
0
0
0
50,000
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
50,000
0
0
0
50,000 50,000
0.58 0.58
Fixed U/G Equip.
Initial Repl
$ $
1,109
0
0
0
0
0
0
14,411
1,631
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1,109
0
0
0
0
0
0
15,520
1,631
0
0
17,151 18,260
0.20 0.21
Total
Initial Repl
$ $
1,459
350
350
350
350
350
19,124
67,411
7,631
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1,109
0
0
0
0
0
0
68,520
7,631
0
0
0
0
0
0
0
0
0
97,375 77,260
1.13 0.90
Appendix 9-1.21
-------
Mine: N03 UG
Capital Expenditure Summary
Year
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
Acquisition
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0.00
Exploration
&
Engineering
350
350
350
350
350
350
1,530
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3,630
0.04
Depreciable Assets
7 Year Life 15 Year Life Total
1,109
0
0
0
0
0
0
68,520
7,631
0
0
0
0
0
68,520
7,631
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
67,429
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
1,109
0
0
0
0
0
67,429
68,520
7,631
0
0
0
0
0
68,520
7,631
0
0
0
0
0
0
0
0
0
153,411 67,429 220,841
1.78 0.78 2.57
Property Tax
Base
1,109
1,109
1,109
1,109
1,109
1,109
18,703
86,114
93,745
93,745
93,745
93,745
93,745
93,745
93,745
93,745
93,745
93,745
93,745
93,745
93,745
93,745
93,745
93,745
93,745
Depreciation
7 Year Life 15 Year Life Total
158
158
158
158
158
158
158
9,789
10,879
10,879
10,879
10,879
10,879
10,879
10,879
10,879
10,879
10,879
10,879
10,879
10,879
1,090
0
0
0
0
0
0
0
0
0
4,495
4,495
4,495
4,495
4,495
4,495
4,495
4,495
4,495
4,495
4,495
4,495
4,495
4,495
4,495
0
0
0
0
158
158
158
158
158
158
4,654
14,284
15,374
15,374
15,374
15,374
15,374
15,374
15,374
15,374
15,374
15,374
15,374
15,374
15,374
1,090
0
0
0
153,411 67,429 220,841
1.78 0.78 2.57
Working
Capital
0
0
0
0
0
0
0
1,745
6,982
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
-8,727
0
0.00
Total
Capital
1,459
350
350
350
350
350
68,959
70,265
14,613
0
0
0
0
0
68,520
7,631
0
0
0
0
0
0
0
0
-8,727
224,471
2.61
Appendix 9-1.22
-------
Mine: N03JJG
Required Sales Price ($ X 1000)
Sales Price (S/ton):
Discount Rate:
Net Present Value:
Cost Contingency Factors:
Average Coal Thickness (ft):
Tons/Man-hour
UMWA (Y or N):
Product (Steam or Met)
Sev. Taxes: Rate $0.27
Adjustment 100.0%
Prop. Taxes Tax Rate (in mills) 60
% of revenue basis for tax
Assessment rate: 25.0%
Income Taxes Federal 34.00%
State 6.00%
Royalty 8.0%
% of Reserve owned: 0%
Year
2007
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
Note: Mi
Tons
0
0
0
0
0
0
0
1,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
5,000
86,000
ne cost ($19. 67
Revenue
0
0
0
0
0
0
0
19,670
98,349
98,349
98,349
98,349
98,349
98,349
98,349
98,349
98,349
98,349
98,349
98,349
98,349
98,349
98,349
98,349
98,349
1,691,596
19.67
/ton) plus tran
Direct
Operating
Cost
0
0
0
0
0
0
0
10,473
52,364
52,364
52,364
52,364
52,364
52,364
52,364
52,364
52,364
52,364
52,364
52,364
52,364
52,364
52,364
52,364
52,364
900,654
10.47
portation and
Royalty
0
0
0
0
0
0
0
1,574
7,868
7,868
7,868
7,868
7,868
7,868
7,868
7,868
7,868
7,868
7,868
7,868
7,868
7,868
7,868
7,868
7,868
135,328
1.57
loadout cc
Taxes (other than income)
Severance
0
0
0
0
0
0
0
0
1,026
1,026
1,026
1,026
1,026
1,026
1,026
1,026
1,026
1,026
1,026
1,026
1,026
1,026
1,026
1,026
1,026
17,442
0.20
sts($1.00/ton) =
Black
Lung
0
0
0
0
0
0
0
865
4,327
4,327
4,327
4,327
4,327
4,327
4,327
4,327
4,327
4,327
4,327
4,327
4,327
4,327
4,327
4,327
4,327
74,430
0.87
Total F
Reel.
0
0
0
0
0
0
0
150
750
750
750
750
750
750
750
750
750
750
750
750
750
750
750
750
750
12,900
0.15
OB cost
Property
0
0
0
0
0
0
0
271
,357
,357
,357
,357
,357
,357
,357
,357
,357
,357
,357
,357
,357
,357
,357
,357
,357
23,344
0.27
$20.67/ton
Corp G&A,
Selling &
Ace. Pen.
0
0
0
0
0
0
0
990
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
4,400
75,790
0.88
)
Development
Cost
350
350
350
350
350
350
1,530
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
3,630
0.04
Depreciation
158
158
158
158
158
158
4,654
14,284
15,374
15,374
15,374
15,374
15,374
15,374
15,374
15,374
15,374
15,374
15,374
15,374
15,374
1,090
0
0
0
220,841
2.57
Depletion
0
0
0
0
0
0
0
0
5,441
5,441
5,441
5,441
5,441
5,441
5,441
5,441
5,441
5,441
5,441
5,441
5,441
7,238
7,238
7,238
7,238
99,690
1.16
Taxes
-203
-203
-203
-203
-203
-203
-2,473
-3,575
2,177
2,177
2,177
2,177
2,177
2,177
2,177
2,177
2,177
2,177
2,177
2,177
2,177
7,171
7,607
7,607
7,607
51,019
0.59
Net Income
-305
-305
-305
-305
-305
-305
-3,710
-5,362
3,265
3,265
,265
,265
,265
,265
,265
,265
,265
,265
,265
,265
,265
10,757
11,411
11,411
11,411
76,528
0.89
Operating
Cash
Flow
-147
-147
-147
-147
-147
-147
943
8,921
24,080
24,080
24,080
24,080
24,080
24,080
24,080
24,080
24,080
24,080
24,080
24,080
24,080
19,085
18,649
18,649
18,649
397,059
4.62
Capital
Expenditures
1,109
0
0
0
0
0
67,429
70,265
14,613
0
0
0
0
0
68,520
7,631
0
0
0
0
0
0
0
0
-8,727
220,841
2.57
Annual
Cash
Flow
-1,256
-147
-147
-147
-147
-147
-66,486
-61,344
9,467
24,080
24,080
24,080
24,080
24,080
-44,440
16,449
24,080
24,080
24,080
24,080
24,080
19,085
18,649
18,649
27,377
176,219
2.05
Appendix 9-1.23
-------
EPA CODES WM CODES deflator =- 0.004/yr for all reg
2012 Prob. Prod. 2012 Est Reserves
Year Abbrev CoalType_Gr CODER CODEF Mine Step Name Existing Mine Heat Content Cost of Cost of deflator deflated Final Cost Coal Cum Coal Reserves
ade or New Type (MMBtu/Ton) Production Production cost (Rounded) Production Production (Million Tons)
(2008$/Ton) (2007$/Ton) (Million
Tons/Year)
2012
2012
2012
2012
2012
2012
CG
CG
CG
CG
CG
CG
BB
BB
BB
BB
BB
BB
CGH
CGH
CGM
CGH
CGH
CGM
SCZ
SCZ
SCZ
SCZ
SCZ
SCZ
N02
N03
E01
EOS
N01
E02
N02
N03
E01
EOS
N01
E02
N
N
E
E
N
E
U
U
S
U
U
U
22.01
22.01
22.01
22.01
22.01
22.01
$20.01
$20.67
$20.72
$21.44
$22.44
$36.48
$19.59
$20.24
$20.29
$20.99
$21.97
$35.72
1.02
1.02
1.02
1.02
1.02
1.02
$19.21
$19.84
$19.89
$20.58
$21.54
$35.01
$19.25
$19.75
$20.00
$20.50
$21.50
$35.00
5.000
5.000
2.500
9.000
9.000
2.000
5.000
10.000
12.500
21.500
30.500
32.500
50.00
95.00
20.00
80.00
70.00
20.00
2012 Final Cost (Rounded)
$40 -,
$35 -
$30 -
$25 -
$20 -
$15 -
U) $10 -
re
O $5-
J2
5.0 10.0 12.5 21.5 30.5
Cumulative Production (Million Tons)
32.5
Appendix 9-1.24
-------
Appendix 9-2 New Mines Included in 2040 Curves
Year
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
Coal
Supply
Region
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AZ
CG
CG
CG
CG
CG
CG
CR
CR
CU
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
Coal
Grade
BB
BB
BB
BB
BD
BD
BD
BD
BE
BE
BE
BE
BB
BA
BA
BA
BB
BB
BB
BA
BD
BB
BE
BE
BE
BE
BE
BE
BE
BE
BE
BE
BE
BE
BE
BE
BE
BG
BG
BG
BG
BG
BG
BG
Step
Name
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N01
N02
N03
N01
N02
N03
N02
N01
N01
N01
N02
N03
N04
N05
N06
N07
N08
N09
N10
N11
N12
N13
N14
N15
N01
N02
N03
N04
N05
N06
N07
Heat Content
(MMBtu/Ton)
24.82
24.82
24.82
24.82
24
24
24
24
23.82
23.82
23.82
23.82
24.64
21.49
21.49
21.49
22.01
22.01
22.01
25.5
22.2
23.22
23
23
23
23
23
23
23
23
23
23
23
23
23
23
23
23.01
23.01
23.01
23.01
23.01
23.01
23.01
Cost of
Production
(2007$/Ton)
$39.50
$42.00
$44.50
$47.00
$47.00
$58.00
$70.00
$82.00
$63.00
$69.00
$75.00
$82.00
$16.75
$18.25
$29.00
$23.00
$19.25
$16.75
$17.75
$27.00
$27.00
$19.25
$32.50
$32.00
$33.50
$35.00
$37.00
$38.50
$40.50
$42.00
$44.00
$45.50
$47.00
$49.00
$51.00
$52.00
$86.00
$24.00
$27.00
$28.50
$37.50
$46.00
$28.50
$32.50
Coal
Production
(Million
Tons/Year)
4
0
4
0
2
2
2
2
0.5
0.5
0.5
0.5
5
12
1
3
9
5
5
3
0.3
8
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
5
2.5
3
4
0.5
4
4
Coal
Reserves
(Million Tons)
13
25
50
50
49
50
50
50
121
115
115
98
450
70
40
350
70
50
95
60
10
100
55
15
15
15
15
15
15
15
15
15
15
15
15
15
15
398
9.6
38
130
8
200
200
Appendix 9-2.1
-------
Year
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
Coal
Supply
Region
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
Coal
Grade
BG
BG
BG
BG
BG
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
BD
BD
BD
BD
BE
BE
BE
BE
BG
BG
BG
BG
BG
BG
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
Step
Name
N08
N09
N10
N11
N12
N01
N02
N03
N04
N05
N06
N07
N08
N09
N10
N11
N12
N13
N14
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N05
N06
N01
N02
N03
N04
N05
N06
N07
N08
N09
N10
N11
N12
Heat Content
(MMBtu/Ton)
23.01
23.01
23.01
23.01
23.01
22.19
22.19
22.19
22.19
22.19
22.19
22.19
22.19
22.19
22.19
22.19
22.19
22.19
22.19
22.62
22.62
22.62
22.62
23.43
23.43
23.43
23.43
23.37
23.37
23.37
23.37
23.37
23.37
23.41
23.41
23.41
23.41
23.41
23.41
23.41
23.41
23.41
23.41
23.41
23.41
Cost of
Production
(2007$/Ton)
$37.00
$41.00
$45.50
$54.00
$86.00
$24.00
$24.00
$24.00
$24.50
$24.00
$24.00
$27.50
$29.00
$31.50
$35.00
$38.50
$48.50
$53.00
$86.00
$30.00
$32.00
$34.50
$86.00
$24.00
$34.50
$37.00
$86.00
$27.50
$30.50
$33.00
$35.00
$38.00
$84.00
$31.00
$34.00
$49.50
$28.50
$29.50
$30.00
$31.00
$32.00
$33.00
$34.00
$35.00
$36.00
Coal
Production
(Million
Tons/Year)
4
4
4
4
4
5
5
5
3.7
3
3
7.8
0.5
2.2
0.2
1.9
0.8
0.5
5
0.5
0.5
0.5
0.5
0.1
1
1
1
1.5
1.5
0.5
1.6
1
1
1.5
0.2
0.8
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
Coal
Reserves
(Million Tons)
200
200
200
200
200
177.4
253.2
221.9
107.5
70
60
460
2
125
3
37.8
20
4
250
10
10
10
10
0.5
15
26
15
30
30
6
9.5
418.1
5
60
3
11
60
60
60
60
60
60
60
60
60
Appendix 9-2.2
-------
Year
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
Coal
Supply
Region
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
IN
KE
KE
KE
KE
KE
KE
KE
KE
KE
KE
KE
KE
KE
KE
KE
KE
KE
KE
KE
KE
KS
KS
KS
KS
KS
Coal
Grade
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
BA
BA
BA
BA
BB
BB
BB
BB
BD
BD
BD
BD
BE
BE
BE
BE
BG
BG
BG
BG
BG
BG
BG
BG
BG
Step
Name
N13
N14
N15
N16
N17
N18
N19
N20
N21
N22
N23
N24
N25
N26
N27
N28
N29
N30
N31
N32
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N05
Heat Content
(MMBtu/Ton)
23.41
23.41
23.41
23.41
23.41
23.41
23.41
23.41
23.41
23.41
23.41
23.41
23.41
23.41
23.41
23.41
23.41
23.41
23.41
23.41
25.32
25.32
25.32
25.32
25.79
25.79
25.79
25.79
25.33
25.33
25.33
25.33
25.14
25.14
25.14
25.14
24.09
24.09
24.09
24.09
25.32
25.32
25.32
25.32
25.32
Cost of
Production
(2007$/Ton)
$37.00
$38.00
$39.00
$40.00
$40.50
$41.50
$42.50
$43.50
$44.50
$45.50
$46.50
$47.50
$48.50
$49.50
$50.00
$51.00
$52.00
$53.00
$54.00
$86.00
$68.00
$88.00
$108.00
$128.00
$87.00
$99.00
$111.00
$123.00
$74.00
$87.00
$100.00
$114.00
$71.00
$91.00
$111.00
$130.00
$57.00
$87.00
$117.00
$148.00
$36.50
$44.50
$52.00
$59.00
$67.00
Coal
Production
(Million
Tons/Year)
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
1.5
0.3
0.3
0.3
0.3
0.5
0.5
0.5
0.5
4.1
3
2
1
4.1
3
2
1
0.3
0.3
0.3
0.3
0.1
0.1
0.1
0.1
0.1
Coal
Reserves
(Million Tons)
60
60
60
60
60
60
60
60
60
60
60
60
60
60
60
60
60
60
60
60
11.9
15
15
15
71.1
80
80
80
192.7
170
180
152
351.8
320
150
145
4
4
4
4
1.2
1.2
1.2
1.2
1.2
Appendix 9-2.3
-------
Year
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
Coal
Supply
Region
KS
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
KW
LA
LA
Coal
Grade
BG
BD
BD
BD
BE
BE
BE
BE
BE
BE
BE
BE
BE
BE
BE
BE
BE
BE
BE
BE
BE
BE
BE
BE
BG
BG
BG
BG
BG
BG
BG
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
BH
LE
LE
Step
Name
N06
N01
N02
N03
N01
N02
N03
N04
N05
N06
N07
N08
N09
N10
N11
N12
N13
N14
N15
N16
N17
N18
N19
N20
N01
N02
N03
N04
N05
N06
N07
N01
N02
N03
N04
N05
N06
N07
N08
N09
N10
N11
N12
N01
N02
Heat Content
(MMBtu/Ton)
25.32
24.23
24.23
24.23
24.45
24.45
24.45
24.45
24.45
24.45
24.45
24.45
24.45
24.45
24.45
24.45
24.45
24.45
24.45
24.45
24.45
24.45
24.45
24.45
23.93
23.93
23.93
23.93
23.93
23.93
23.93
22.84
22.84
22.84
22.84
22.84
22.84
22.84
22.84
22.84
22.84
22.84
22.84
14.09
14.09
Cost of
Production
(2007$/Ton)
$86.00
$59.00
$67.00
$86.00
$30.50
$33.50
$34.00
$34.50
$35.00
$35.50
$36.50
$37.00
$37.50
$38.00
$38.50
$39.00
$39.50
$40.00
$40.50
$41.50
$42.00
$42.50
$43.00
$86.00
$26.00
$30.00
$32.00
$36.50
$37.00
$50.00
$86.00
$29.50
$32.00
$34.00
$38.00
$53.00
$53.00
$53.00
$53.00
$53.00
$53.00
$54.00
$86.00
$19.00
$43.00
Coal
Production
(Million
Tons/Year)
0.1
0.7
0.5
0.5
2
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
3
3
3
4
2
3
3
5
1
2
1
1
2
2
2
2
2
2
2
2
2
Coal
Reserves
(Million Tons)
1.2
10
105
105
300
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
30
24.8
195
156.8
104.5
20
180
180
17
4
22
7.8
30
240
240
240
240
240
240
240
75
75
Appendix 9-2.4
-------
Year
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
Coal
Supply
Region
MD
MD
MD
MD
MD
MD
MD
MD
MD
MD
MD
MD
MD
MD
MD
MD
ME
ME
ME
ME
ME
ME
ME
ME
ME
MP
MP
MP
MP
MP
MP
MS
MS
MT
ND
ND
ND
ND
ND
ND
NS
NS
NS
NS
NS
Coal
Grade
BB
BB
BB
BB
BD
BD
BD
BD
BE
BE
BE
BE
BG
BG
BG
BG
LD
LD
LD
LD
LD
LD
LD
LD
LD
SA
SA
SA
SD
SD
SD
LE
LE
BB
LD
LD
LD
LE
LE
LE
BB
BD
BD
BE
BE
Step
Name
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N05
N06
N07
N08
N09
N01
N02
N03
N01
N02
N03
N01
N02
N01
N01
N02
N03
N01
N02
N03
N01
N01
N02
N01
N02
Heat Content
(MMBtu/Ton)
24.64
24.64
24.64
24.64
26.32
26.32
26.32
26.32
24.85
24.85
24.85
24.85
23.26
23.26
23.26
23.26
13
13.55
13.85
13.1
14.2
13
13.4
13.3
13.2
18.9
18.9
18.9
17.23
17.23
17.23
12.8
12.8
21
13.7
13.7
13.7
13.46
13.46
13.46
26.4
22
22
17
22
Cost of
Production
(2007$/Ton)
$71.00
$76.00
$80.00
$85.00
$65.00
$70.00
$76.00
$85.00
$44.00
$58.00
$73.00
$88.00
$55.00
$62.00
$69.00
$78.00
$11.75
$12.50
$14.75
$15.00
$15.50
$16.00
$17.00
$17.00
$24.00
$13.75
$14.75
$17.00
$14.25
$13.00
$15.25
$15.75
$43.00
$23.50
$15.75
$15.25
$13.75
$13.75
$17.00
$26.50
$43.00
$23.00
$43.00
$14.25
$43.00
Coal
Production
(Million
Tons/Year)
0.3
0.3
0.3
0.3
0.7
0.7
0.7
0.7
0.3
0.3
0.3
0.3
0.4
0.4
0.4
0.4
15
15
15
1
15
15
15
15
10
15
15
15
15
15
15
3
1
5
18
9
1
6
4
2
0.6
0.4
0.4
6
0.4
Coal
Reserves
(Million Tons)
5
5
5
5
2.5
7.5
8
7
3
3
3
3
15
15
15
15
550
550
400
50
3500
970
1400
455
215
450
450
450
450
450
450
96
40
450
500
565
512
589
500
51
22
16
20
180
20
Appendix 9-2.5
-------
Year
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
Coal
Supply
Region
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OH
OK
OK
OK
OK
OK
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PC
PW
PW
PW
PW
Coal
Grade
BB
BB
BB
BB
BD
BD
BD
BD
BE
BE
BE
BE
BG
BG
BG
BG
BH
BH
BH
BH
BE
BE
BE
BE
BE
BD
BD
BD
BD
BE
BE
BE
BE
BG
BG
BG
BG
BH
BH
BH
BH
BD
BD
BD
BD
Step
Name
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N05
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
Heat Content
(MMBtu/Ton)
24.68
24.68
24.68
24.68
25.55
25.55
25.55
25.55
25.24
25.24
25.24
25.24
24.34
24.34
24.34
24.34
23.92
23.92
23.92
23.92
22.15
22.15
22.15
22.15
22.15
25.06
25.06
25.06
25.06
25.66
25.66
25.66
25.66
25.33
25.33
25.33
25.33
23.39
23.39
23.39
23.39
24.26
24.26
24.26
24.26
Cost of
Production
(2007$/Ton)
$76.00
$83.00
$91.00
$100.00
$63.00
$69.00
$75.00
$82.00
$57.00
$69.00
$81.00
$94.00
$49.00
$60.00
$70.00
$82.00
$50.00
$60.00
$72.00
$86.00
$45.00
$48.00
$51.00
$55.00
$86.00
$64.00
$73.00
$83.00
$94.00
$39.50
$54.00
$69.00
$84.00
$51.00
$60.00
$68.00
$77.00
$51.00
$60.00
$68.00
$77.00
$38.50
$43.00
$47.00
$51.00
Coal
Production
(Million
Tons/Year)
1
1
1
1
0.3
0.3
0.3
0.3
0.5
0.5
0.5
0.5
4
4
4
4
4
4
4
4
0.3
0.3
0.3
0.3
0.3
0.5
0.5
0.5
0.5
1.5
1.5
1.5
1.5
1
1
1
1
0.5
0.5
0.5
0.5
0.8
0.8
0.8
0.8
Coal
Reserves
(Million Tons)
50
50
50
50
94
100
100
100
208
210
210
230
446
450
450
450
500
500
500
500
3.6
3.6
3.6
3.6
3.6
7.6
5
5
5
15
15
15
15
22
25
20
20
10
10
10
10
122
126
130
134
Appendix 9-2.6
-------
Year
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
Coal
Supply
Region
PW
PW
PW
PW
PW
PW
PW
PW
TN
TN
TN
TN
TN
TN
TN
TN
TN
TN
TN
TN
TX
TX
TX
TX
UT
UT
UT
UT
UT
UT
UT
UT
VA
VA
VA
VA
VA
VA
VA
VA
VA
VA
VA
VA
VA
Coal
Grade
BE
BE
BE
BE
BG
BG
BG
BG
BB
BB
BB
BB
BD
BD
BD
BD
BE
BE
BE
BE
LE
LE
LE
LE
BA
BA
BA
BB
BB
BD
BD
BE
BA
BA
BA
BA
BB
BB
BB
BB
BD
BD
BD
BD
BE
Step
Name
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N01
N02
N01
N02
N01
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
Heat Content
(MMBtu/Ton)
26.22
26.22
26.22
26.22
25.86
25.86
25.86
25.86
24.18
24.18
24.18
24.18
23.91
23.91
23.91
23.91
26.75
26.75
26.75
26.75
13.22
13.22
13.22
13.22
23.68
23.68
23.68
23.23
23.23
23.05
23.05
25.06
22.7
22.7
22.7
22.7
25.97
25.97
25.97
25.97
25.76
25.76
25.76
25.76
26.03
Cost of
Production
(2007$/Ton)
$37.00
$40.50
$44.00
$46.00
$37.00
$39.50
$42.50
$64.00
$101.00
$106.00
$112.00
$118.00
$101.00
$104.00
$107.00
$110.00
$85.00
$93.00
$101.00
$110.00
$11.50
$14.75
$15.75
$15.25
$20.00
$24.50
$24.50
$25.50
$21.50
$24.00
$41.00
$28.50
$103.00
$108.00
$115.00
$121.00
$94.00
$103.00
$112.00
$120.00
$85.00
$94.00
$103.00
$112.00
$68.00
Coal
Production
(Million
Tons/Year)
2
2
2
2
5
5
5
1
0.3
0.3
0.3
0.3
0.3
0.3
0.3
0.3
0.3
0.3
0.3
0.3
11
4
6
7
1
4
4
4
2
4
3
2
0.3
0.3
0.3
0.3
0.8
0.8
0.8
0.8
1.1
0.8
0.8
0.8
0.5
Coal
Reserves
(Million Tons)
744
784
824
864
567
667
767
767
3.8
3.8
3.8
3.8
4.5
4.5
4.5
4.2
6.3
6
6
6
219
150
127
114
10
80
25
50
22
45
50
40
44.4
40
40
39
87.2
85
85
84
68.4
50
50
42
40.6
Appendix 9-2.7
-------
Year
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
2040
Coal
Supply
Region
VA
VA
VA
WG
WG
WG
WG
WL
WL
WL
WL
WN
WN
WN
WN
WN
WN
WN
WN
WN
WN
WN
WN
WN
WN
WN
WN
WS
WS
WS
WS
WS
WS
WS
WS
WS
WS
WS
WS
WS
WS
WS
WS
WS
WS
Coal
Grade
BE
BE
BE
BB
BB
BB
SD
SB
SB
SB
SB
BD
BD
BD
BD
BE
BE
BE
BE
BG
BG
BG
BG
BH
BH
BH
BH
BA
BA
BA
BA
BB
BB
BB
BB
BD
BD
BD
BD
BE
BE
BE
BE
BG
BG
Step
Name
N02
N03
N04
N01
N02
N03
N01
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
N03
N04
N01
N02
Heat Content
(MMBtu/Ton)
26.03
26.03
26.03
21.67
21.67
21.67
18.5
17.15
17.15
17.15
17.15
25.01
25.01
25.01
25.01
25.67
25.67
25.67
25.67
26.03
26.03
26.03
26.03
25.15
25.15
25.15
25.15
26.2
26.2
26.2
26.2
24.73
24.73
24.73
24.73
24.64
24.64
24.64
24.64
24.38
24.38
24.38
24.38
25.64
25.64
Cost of
Production
(2007$/Ton)
$78.00
$89.00
$112.00
$24.50
$23.50
$22.50
$19.75
$17.75
$10.75
$11.75
$13.00
$45.50
$65.00
$85.00
$104.00
$29.00
$49.00
$69.00
$89.00
$32.50
$48.00
$64.00
$80.00
$34.00
$53.00
$72.00
$91.00
$98.00
$107.00
$112.00
$122.00
$90.00
$107.00
$114.00
$122.00
$82.00
$89.00
$120.00
$147.00
$69.00
$84.00
$99.00
$113.00
$69.00
$80.00
Coal
Production
(Million
Tons/Year)
0.5
0.5
0.5
0.5
6
3
1
15
15
15
15
0.4
0.4
0.4
0.4
2
2
2
2
6.5
5
5
5
5
5
5
5
0.3
0.3
0.3
0.3
0.5
0.5
0.5
0.5
1.5
1.5
1.5
1.5
1.4
1.3
1.3
1.3
0.8
0.8
Coal
Reserves
(Million Tons)
26
26
26
15
190
55
13
450
450
450
450
1.6
2
2
2
40
40
40
40
600
600
600
600
125
125
125
75
4.7
4.7
4.7
4.6
106.8
100
100
100
384.8
333
333
333
420.7
420
420
420
80
79
Appendix 9-2.8
-------
Year
2040
2040
Coal
Supply
Region
WS
ws
Coal
Grade
BG
BG
Step
Name
N03
N04
Heat Content
(MMBtu/Ton)
25.64
25.64
Cost of
Production
(2007$/Ton)
$92.00
$104.00
Coal
Production
(Million
Tons/Year)
0.8
0.8
Coal
Reserves
(Million Tons)
79
80
Appendix 9-2.9
-------
-------
Appendix 9-3 Coal Transportation Matrix in EPA Base Case v.4.10
This is a small excerpt of the data in Appendix 9-3. The complete data set in spreadsheet format
can be downloaded via the link found at www.epa.gov/airmarkets/proqsreqs/epa-
ipm/BaseCasev410.html
Coal Supply
Region -
Description
Arizona
New Mexico, San
Juan
West Virginia,
North
Wyoming,
Powder River
Basin (8400)
Louisiana
Wyoming,
Powder River
Basin (8400)
Wyoming,
Powder River
Basin (8800)
Wyoming,
Powder River
Basin (8800)
Montana, East
Wyoming,
Powder River
Basin (8400)
Wyoming,
Powder River
Basin (8400)
Wyoming,
Powder River
Basin (8400)
Wyoming,
Powder River
Basin (8800)
Wyoming,
Powder River
Basin (8800)
Alabama
Colorado, Green
River
Colorado, Uinta
Illinois
Indiana
Kentucky East
Coal
Demand
Region
AMM1
AMM1
NAI1
NAI1
TXL1
TXL1
NAI1
TXL1
DAL1
DAL1
PRB1
WYG1
DAL1
PRB1
ALR1
ALR1
ALR1
ALR1
ALR1
ALR1
Coal Demand Region Description
AMMM_High-Cost Competitive_Mine
Mouth Rail
AMMM_High-Cost Competitive_Mine
Mouth Rail
NAIN_High-Cost Competitive_Mine
Mouth Rail
NAIN_High-Cost Competitive_Mine
Mouth_Rail
TXLG_High-Cost Competitive_Mine
Mouth Rail
TXLGJHigh-Cost Competitive_Mine
Mouth_Rail
NAIN_High-Cost Competitive_Mine
Mouth_Rail
TXLGJHigh-Cost Competitive_Mine
Mouth_Rail
DALG_High-Cost Competitive_Mine
Mouth Truck/Conveyor Belt
DALG_High-Cost Competitive_Mine
Mouth_Truck/Conveyor Belt
PRBJHigh-Cost Competitive_Mine
Mouth_Truck/Conveyor Belt
WYGR_High-Cost Competitive_Mine
Mouth_Truck/Conveyor Belt
DALG_High-Cost Competitive_Mine
Mouth_Truck/Conveyor Belt
PRB_High-Cost Competitive_Mine
Mouth_Truck/Conveyor Belt
ALRL_High-Cost Competitive_Not
Mine Mouth Rail
ALRL_High-Cost Competitive_Not
Mine Mouth Rail
ALRL_High-Cost Competitive_Not
Mine Mouth Rail
ALRL_High-Cost Competitive_Not
Mine Mouth Rail
ALRL_High-Cost Competitive_Not
Mine Mouth Rail
ALRL_High-Cost Competitive_Not
Mine Mouth Rail
Total Cost
(2007$/Ton)
1.13
1.13
1.13
36.93
1.13
24.58
37.3
22.63
4.83
10.79
2.21
2.21
11.23
1.13
0
33.86
39.76
25.73
23.32
26.57
Escalation/
Year (2012-
2025)
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
1
Escalation/
Year (2026-
2054)
1
1
1
1.0021
1
1.0021
1.0021
1.0021
1.0042
1.002
1.0011
1.0011
1.002
1
1
1.0022
1.0022
1.0022
1.0022
1.0022
Appendix 9-3.1
-------
-------
Appendix 9-4 Coal Supply Curves in EPA Base Case v.4.10
This is a small excerpt of the data in Appendix 9-4. The complete data set in
spreadsheet format and complete set of graphs can be downloaded via the link found at
www.epa.gov/airmarkets/progsregs/epa-ipm/BaseCasev410.html
Year
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
Coal
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
Coal
Grade
BB
BB
BB
BB
BB
BB
BB
BB
BB
BD
BD
BD
BD
BD
BD
BD
BD
BD
BD
BD
BD
BD
BE
BE
BE
BE
BE
BE
BE
Step
Name
E01
N01
N02
E02
EOS
N03
E04
N04
EOS
E01
E02
EOS
E04
N01
EOS
E06
E07
N02
EOS
N03
E09
N04
E01
E02
EOS
E04
EOS
E06
N01
Heat Content
(MMBtu/Ton)
24.82
24.82
24.82
24.82
24.82
24.82
24.82
24.82
24.82
24
24
24
24
24
24
24
24
24
24
24
24
24
23.82
23.82
23.82
23.82
23.82
23.82
23.82
Cost of
Production
(2007$/Ton)
43.1
44.5
47.0
48.9
49.9
49.9
50.9
52.9
53.8
43.1
44.5
48.9
52.9
52.9
53.8
56.8
64.6
65.6
73.4
78.3
85.1
92.0
36.2
43.1
45.5
50.9
54.8
62.6
70.5
Coal
Production
(Million
Tons/Year)
1.0
4.0
0.0
0.9
5.6
4.0
1.0
0.0
0.8
0.4
0.3
0.4
0.9
2.0
0.3
0.7
0.4
2.0
0.1
2.0
0.5
2.0
1.8
0.4
0.1
0.4
0.9
0.2
0.5
Coal
Reserves
(Million
Tons)
111
13
25
51
73
50
5
50
22
233
9
16
10
49
1
26
24
50
6
50
26
50
93
14
0
10
16
5
121
Appendix 9-4.1
-------
Coal Supply Curve - WH_SA
100
200 300 400
Cumulative Production (MMTons)
500
600
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$20
Coal Supply Curve - WH_SB
$18
$16
$14
~ $12
ง $10
s.
8
<-> $8
$6
$4
$2
$0
10 20 30 40 50 60
Cumulative Production (MMTons)
70
80
2012 Curve 2015 Curve 2020 Curve 2030 Curve
90
100
-------
Coal Supply Curve - WL_SB
100
200 300 400
Cumulative Production (MMTons)
500
600
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - MP_SA
$20
$18
$16
_F
$14 J
~ $12
ง $10
S.
8
<-> $8
$6
$4
$2
$0
10 20 30 40 50 60
Cumulative Production (MMTons)
70
2012 Curve 2015 Curve 2020 Curve 2030 Curve
80
90
-------
$25
Coal Supply Curve - MP_SD
$20
~ $15
o
8
<-> $10
$5
$0
10 20 30 40 50 60
Cumulative Production (MMTons)
70
80
90
100
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$30
$25
$20
Coal Supply Curve - MT_BB
$15
8
o
$10
$5
$0
8 10 12
Cumulative Production (MMTons)
14
16
18
20
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$30
Coal Supply Curve - WG_BB
$25
$20
$15
S3
o
$10
$5
$0
456
Cumulative Production (MMTons)
10
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$30
$25
$20
Coal Supply Curve - WG_SD
$15
8
o
$10
$5
$0
6 8 10 12
Cumulative Production (MMTons)
14
2012 Curve 2015 Curve 2020 Curve 2030 Curve
16
18
-------
$120
Coal Supply Curve - KS_BG
$100
$80
$60
S3
o
$40
$20
$0^-
0.2
0.4 0.6 0.8
Cumulative Production (MMTons)
2012 Curve 2015 Curve 2020 Curve 2030 Curve
1.2
1.4
-------
$120
Coal Supply Curve - OK_BE
$100
$80
S3
o
$60
$40
$20
$0^-
0.5
1 1.5
Cumulative Production (MMTons)
2.5
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$60
$50
$40
Coal Supply Curve - NS_BB
$30
8
o
$20
$10
$0
0.2
0.4 0.6 0.8 1
Cumulative Production (MMTons)
2012 Curve 2015 Curve 2020 Curve 2030 Curve
1.2
1.4
-------
Coal Supply Curve - NS_BD
3456
Cumulative Production (MMTons)
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$60
$50
$40
Coal Supply Curve - NS_BE
$30
8
o
$20
$10
$0
10 15 20
Cumulative Production (MMTons)
25
2012 Curve 2015 Curve 2020 Curve 2030 Curve
30
-------
$20
Coal Supply Curve - AZ_BB
$18
$16
$14
~ $12
ง $10
s.
8
<-> $8
$6
$4
$2
$0
6 8
Cumulative Production (MMTons)
10
2012 Curve 2015 Curve 2020 Curve 2030 Curve
12
14
-------
Coal Supply Curve - CG_BA
$40
$35
$30
$25
$20
S3
o
$15
$10
$5
$0
10 15 20 25
Cumulative Production (MMTons)
30
2012 Curve 2015 Curve 2020 Curve 2030 Curve
35
40
-------
Coal Supply Curve - CG_BB
$40
$35
$30
$25
$10
$5
$0
10
20 30 40
Cumulative Production (MMTons)
50
2012 Curve 2015 Curve 2020 Curve 2030 Curve
60
-------
Coal Supply Curve - CR_BA
$35
$30
$25
P $20
ง $15
o
$10
$5
$0
0.5
1.5 2
Cumulative Production (MMTons)
2.5
3.5
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$30
$25
$20
Coal Supply Curve - CR_BD
$15
8
o
$10
$5
$0
0.05 0.1 0.15 0.2 0.25
Cumulative Production (MMTons)
2012 Curve 2015 Curve 2020 Curve 2030 Curve
0.3
0.35
-------
$30
Coal Supply Curve - CU_BA
$25
$20
$15
8
o
$10
$5
$0
6 8
Cumulative Production (MMTons)
10
2012 Curve 2015 Curve 2020 Curve 2030 Curve
12
14
-------
$30
Coal Supply Curve - CU_BB
$25
$20
$15
8
o
$10
$5
$0
6 8 10
Cumulative Production (MMTons)
12
2012 Curve 2015 Curve 2020 Curve 2030 Curve
14
16
-------
Coal Supply Curve - CU_BD
$16
$14
$12
$10
S3
o
$8
$6
$4
$2
$0
0.05 0.1 0.15 0.2 0.25
Cumulative Production (MMTons)
2012 Curve 2015 Curve 2020 Curve 2030 Curve
0.3
0.35
-------
Coal Supply Curve - UT_BA
$45
8
o
$10
$0
6 8 10 12
Cumulative Production (MMTons)
14
16
18
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - UT_BB
$45
$40
$35
$30
t $25
In $20
O
$15
$10
$5
$0
10 15 20 25 30
Cumulative Production (MMTons)
35
2012 Curve 2015 Curve 2020 Curve 2030 Curve
40
45
-------
$50
$45
Coal Supply Curve - UT_BD
$40
$35
~ $30
I
ง $25-r
8
<-> $20
$15
$10
$5
$0
10 15
Cumulative Production (MMTons)
20
2012 Curve 2015 Curve 2020 Curve 2030 Curve
25
-------
$40
Coal Supply Curve - UT_BE
$35
$30
$25
$20
S3
o
$15
$10
$5
$0
0.5
1.5 2 2.5 3
Cumulative Production (MMTons)
3.5
2012 Curve 2015 Curve 2020 Curve 2030 Curve
4.5
-------
Coal Supply Curve - PC_BD
$120
$100
$80
8
o
$60
$40
$20
$0^
234
Cumulative Production (MMTons)
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - PC_BE
$100
$90
$20
$10
$0^-
10 15
Cumulative Production (MMTons)
20
2012 Curve 2015 Curve 2020 Curve 2030 Curve
25
-------
Coal Supply Curve - PC_BG
$100
$90
$0^
3456
Cumulative Production (MMTons)
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$100
Coal Supply Curve - PC_BH
$90
$80
$70
~ $60
I
ง $50
S.
8
<-> $40
$30
$20
$10
$0^-
0.5
1 1.5
Cumulative Production (MMTons)
2012 Curve 2015 Curve 2020 Curve 2030 Curve
2.5
-------
Coal Supply Curve - PW_BD
$70
$60
$50
p $40
ง $30
o
$10
$0
468
Cumulative Production (MMTons)
10
2012 Curve 2015 Curve 2020 Curve 2030 Curve
12
-------
Coal Supply Curve - PW_BE
$70
$60
$50
p $40
ง $30
o
$20
$10
$0
10 15 20 25 30
Cumulative Production (MMTons)
35
2012 Curve 2015 Curve 2020 Curve 2030 Curve
40
45
-------
$80
Coal Supply Curve - PW_BG
$70
$60
$50
I
!-
O
O
S.
8
$40
f
$30-^-
$20
$10
$0
6 8 10 12
Cumulative Production (MMTons)
14
2012 Curve 2015 Curve 2020 Curve 2030 Curve
16
18
-------
Coal Supply Curve - OH_BB
$120
$100
$80
$60
S3
o
$40
$20
$0^-
0.5
1.5 2 2.5 3
Cumulative Production (MMTons)
3.5
2012 Curve 2015 Curve 2020 Curve 2030 Curve
4.5
-------
$100
Coal Supply Curve - OH_BD
$90
$80
$70
~ $60
I
ง $50
S.
8
<-> $40
$30
$20
$10
$0^-
0.2 0.4 0.6 0.8 1 1.2
Cumulative Production (MMTons)
1.4
2012 Curve 2015 Curve 2020 Curve 2030 Curve
1.6
1.8
-------
Coal Supply Curve - OH_BE
$120
$100
$80
8
o
$60
$40
$20
$0^
345
Cumulative Production (MMTons)
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - OH_BG
$100
$90
$0^
10
15 20 25 30
Cumulative Production (MMTons)
35
40
45
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$120
Coal Supply Curve - OH_BH
$100
$80
$60
S3
o
$40
$20
$0^-
6 8 10 12
Cumulative Production (MMTons)
14
2012 Curve 2015 Curve 2020 Curve 2030 Curve
16
18
-------
Coal Supply Curve - MD_BB
$100
$90
$80
$70
~ $60
I
ง $50
S.
8
<-> $40
$30
$20
$10
$0^-
0.2
0.4 0.6 0.8
Cumulative Production (MMTons)
2012 Curve 2015 Curve 2020 Curve 2030 Curve
1.2
1.4
-------
Coal Supply Curve - MD_BD
$100
$90
$80
$70
~ $60
I
ง $50
S.
8
<-> $40
$30
$20
$10
$0^-
0.5
1 1.5 2
Cumulative Production (MMTons)
2.5
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - MD_BE
$120
$100
$80
8
o
$60
$40
$20
$0^
0.5
1.5 2
Cumulative Production (MMTons)
2.5
3.5
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$100
Coal Supply Curve - MD_BG
$90
$80
$70
~ $60
I
ง $50
S.
8
<-> $40
$30
$20
$10
$0^-
0.2 0.4 0.6 0.8 1 1.2
Cumulative Production (MMTons)
1.4
2012 Curve 2015 Curve 2020 Curve 2030 Curve
1.6
1.8
-------
$140
Coal Supply Curve - WN_BD
$120
$100
F
o $80
ง $60
o
$40
$20
$0^-
468
Cumulative Production (MMTons)
10
2012 Curve 2015 Curve 2020 Curve 2030 Curve
12
-------
Coal Supply Curve - WN_BE
$120
$100
$80
8
o
$60
$40
$20
$0^
10 15 20
Cumulative Production (MMTons)
25
30
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$100
Coal Supply Curve - WN_BG
$90
$80
$70
~ $60
I
ง $50
S.
8
<-> $40
$30
$20
$10
$0^-
10
20 30 40
Cumulative Production (MMTons)
50
2012 Curve 2015 Curve 2020 Curve 2030 Curve
60
70
-------
$120
Coal Supply Curve - WN_BH
$100
$80
S3
o
$60
$40
$20
$0^-
10 15
Cumulative Production (MMTons)
20
25
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$25
Coal Supply Curve - TX_LD
$20
~ $15
o
8
<-> $10
$5
$0
456
Cumulative Production (MMTons)
10
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - TX_LE
10
20
30 40
Cumulative Production (MMTons)
50
60
70
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - TX_LG
$12
$10
$6
$4
$2
S3
o
$0
468
Cumulative Production (MMTons)
10
12
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$60
Coal Supply Curve - LA_LE
$50
$40
$30
8
o
$20
$10
$0
3456
Cumulative Production (MMTons)
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$120
Coal Supply Curve - KW_BD
$100
$80
$60
S3
o
$40
$20
$0^-
0.2 0.4 0.6 0.8 1 1.2
Cumulative Production (MMTons)
1.4
2012 Curve 2015 Curve 2020 Curve 2030 Curve
1.6
1.8
-------
$120
Coal Supply Curve - KW_BE
$100
$80
$60
$40
S3
o
$20
$0^-
6 8
Cumulative Production (MMTons)
10
2012 Curve 2015 Curve 2020 Curve 2030 Curve
12
14
-------
$120
Coal Supply Curve - KW_BG
$100
$80
$60
S3
o
$40
$20
$0^-
10
20 30 40
Cumulative Production (MMTons)
50
60
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - KW_BH
$120
$100
$80
8
o
$60
$40
$20
$0^
10
15 20 25 30
Cumulative Production (MMTons)
35
40
45
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - IL_BE
$120
$100
$80
$60
$40
$20
8
o
$0^
10 15 20
Cumulative Production (MMTons)
25
30
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$120
Coal Supply Curve - IL_BG
$100
$80
$60
S3
o
$40
$20
$0^-
10 20 30 40 50 60
Cumulative Production (MMTons)
70
2012 Curve 2015 Curve 2020 Curve 2030 Curve
80
90
-------
$120
Coal Supply Curve - IL_BH
$100
$80
$60
S3
o
$40
$20
$0^-
20
40 60 80
Cumulative Production (MMTons)
100
120
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$120
Coal Supply Curve - IN_BD
$100
$80
$60
S3
o
$40
$20
$0^-
3456
Cumulative Production (MMTons)
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$120
Coal Supply Curve - IN_BE
$100
$80
$60
S3
o
$40
$20
$0^-
3456
Cumulative Production (MMTons)
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - IN_BG
$100
$90
$0^
10 15
Cumulative Production (MMTons)
20
25
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - IN_BH
$120
$100
$80
8
o
$60
$40
$20
$0^
10
20
30 40 50
Cumulative Production (MMTons)
60
70
80
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$60
$50
$40
Coal Supply Curve - MS_LE
$30
8
o
$20
$10
$0
3456
Cumulative Production (MMTons)
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$18
Coal Supply Curve - ND_LD
$16
$14
$12
t $10
I
I
ง $8
o
$6
$4
$2
$0
10
20 30 40
Cumulative Production (MMTons)
2012 Curve 2015 Curve 2020 Curve 2030 Curve
50
60
-------
Coal Supply Curve - ND_LE
$30
$25
$20
$15
8
o
$5
$0
10 15
Cumulative Production (MMTons)
20
2012 Curve 2015 Curve 2020 Curve 2030 Curve
25
-------
Coal Supply Curve - ME_LD
$5
$0
20
40 60 80
Cumulative Production (MMTons)
100
120
140
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$140
Coal Supply Curve - WS_BA
$120
$100
o $80
$40
$20
$0^-
0.2 0.4 0.6 0.8 1 1.2
Cumulative Production (MMTons)
1.4
1.6
1.8
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - WS_BB
$140
$120
$0^
8 10 12
Cumulative Production (MMTons)
14
16
18
20
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - WS_BD
$160
$140
$120
$100
S3
o
$80
$60
$40-
$20
$0^
10
20 30 40
Cumulative Production (MMTons)
50
60
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$120
Coal Supply Curve - WS_BE
$100
$80
$60
S3
o
$40
$20
$0^-
234
Cumulative Production (MMTons)
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$120
Coal Supply Curve - WS_BG
$100
$80
$60
S3
o
$40
$20
$0^-
0.5
1.5 2
Cumulative Production (MMTons)
2.5
2012 Curve 2015 Curve 2020 Curve 2030 Curve
3.5
-------
Coal Supply Curve - VA_BA
$140
$120
$0^
0.2
0.4
0.6 0.8 1
Cumulative Production (MMTons)
1.2
1.4
1.6
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - VA_BB
$140
$120
$100
o $80
ง $60
o
$40
$20
$0^
0.5
1.5 2 2.5
Cumulative Production (MMTons)
3.5
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - VA_BD
$120
$100
$80
8
o
$60
$40
$20
$0^
6 8 10
Cumulative Production (MMTons)
12
14
16
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - VA_BE
$120
$100
$80
8
o
$60
$40
$20
$0^
0.5
1 1.5 2
Cumulative Production (MMTons)
2.5
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - KE_BA
$140
$120
$0^
0.5
1.5 2
Cumulative Production (MMTons)
2.5
3.5
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - KE_BB
$140
$120
$0^
468
Cumulative Production (MMTons)
10
12
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - KE_BD
$140
$120
$0^
10
20
30 40 50
Cumulative Production (MMTons)
60
70
80
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - KE_BE
$140
$120
$0^
10 15 20
Cumulative Production (MMTons)
25
30
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - KE_BG
$180
$160
O
$0^
0.5
1 1.5
Cumulative Production (MMTons)
2.5
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
Coal Supply Curve - TN_BB
$120
$100
$80
$60
S3
o
$40
$20
$0^-
0.2
0.4 0.6 0.8
Cumulative Production (MMTons)
2012 Curve 2015 Curve 2020 Curve 2030 Curve
1.2
-------
$120
Coal Supply Curve - TN_BD
$100
S3
o
$80
$60
$40
$20
$0^-
0.5
1.5 2 2.5
Cumulative Production (MMTons)
3.5
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$120
$100
$80
$60
Coal Supply Curve - TN_BE
8
o
$40
$20
$0^-
0.2
0.4 0.6 0.8
Cumulative Production (MMTons)
2012 Curve 2015 Curve 2020 Curve 2030 Curve
1.2
1.4
-------
$100
Coal Supply Curve - AL_BD
$90
$80
$70
~ $60
I
g $50
o
<-> $40 +
$30
$20
$10
$0^-
6 8
Cumulative Production (MMTons)
10
2012 Curve 2015 Curve 2020 Curve 2030 Curve
12
14
-------
Coal Supply Curve - AL_BE
$100
$90
$0^
3 4
Cumulative Production (MMTons)
2012 Curve 2015 Curve 2020 Curve 2030 Curve
-------
$60
$50
$40
Coal Supply Curve - AL_BB
$30
8
o
$20
$10
$0
8 10 12
Cumulative Production (MMTons)
14
16
2012 Curve 2015 Curve 2020 Curve 2030 Curve
18
20
-------
-------
10 Natural Gas
This chapter describes how natural gas supply, demand, and costing are modeled in EPA Base
Case v.4.10. Section 10.1 indicates that natural gas supply dynamics are directly (i.e.,
endogenously) modeled in the new base case. This contrasts to previous EPA base cases where
natural gas supply curves and related assumptions were developed outside of IPM and then
treated as an (exogenous) input to the base case. Section 10.2 gives an overview of the new
natural gas module. Section 3.9 treats in detail the specific components of the module that are
only briefly described in Section 10.2. Specifically, Sections 10.3 and 10.4 describe the very
detailed process-engineering model and data sources used to characterize North American
conventional, unconventional, and frontier 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 2012-2050 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 demand is represented. 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
report and proxy natural gas supply curves from the new integrated model based on results in
EPA Base Case v.4.10. The proxy curves are meant to provide a point of comparison with the
natural gas supply curves used in previous EPA IPM base case.
10.1 Overview of IPM's Natural Gas Module
In previous EPA base cases natural gas supply curves and related assumptions were developed
outside of IPM and provided in an iterative fashion as static inputs to the base case. Regional gas
price forecast, in the form of basis differentials1, was also provided as static inputs for delivered
gas price calculations. The iteration process began with a set of supply curves and basis
differentials generated from a series of runs using external stand-alone gas model. Results from
the IPM run such as power sector gas demand and heat rates were fed back to the gas model as
inputs for the next iteration. It was a time consuming process as it took several iterations to
converge and involving human interaction between iterations.
In EPA Base Case v.4.10 natural gas supply, demand, transportation, storage, and related costs
are modeled directly in IPM through the incorporation of a new natural gas module. In the new
system, 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. Integrating
natural gas modeling into IPM as illustrated in Figure 10-1 and Figure 10-2 has some advantages
over the previous modeling approach. The direct interaction between the electric and the gas
modules captures the overall gas supply and demand dynamic and requires no iteration. The
11n 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.
10-1
-------
model solves for gas price in each region, therefore, it does not need to import gas price basis
differentials as in the previous approach.
The result from a modeling standpoint is a new integrated natural gas module with a linear
programming (LP) structure that is fully consistent and compatible with that used in IPM. Natural
gas LP components, which include objective function parameters consistent in form with IPM's
cost minimization, a series of decision variables, and a set of constraints, have been added to the
original LP structure of the IPM electricity module. This integration makes the gas module a
working component of the IPM modeling framework.
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.
Figure 10-1 Modeling and Data Structure in EPA Base Case v.4.10.
Emission Control
Technologies
J Chapter 5
Sulfur Dioxide
Nitrogen Oxides
Mercury
Carbon Capture and Storage
Generation Resources
J Chanter 4
Existing EGUsf
P Ian net) EG Us t
Potential Hera E 6 Us
Future Placeholder Technologies
Conditioned by:
Short-term Caprtal Cost Adder
Regional Cost Adjustments
Capacity Deployment Constraints
Power System Operation
_; Chaptei 3 '_
Regional Configurations
Capacity. Generation, and Dispatch Assumptions
T ra nsmissi o n Assu mptio ns
Turndown Constraint
Reliability Constraints
Electricity Demand Growth
Env\ronmental Regulations
CO, Capture,
Transport, and
Storage
Chapter 6
Capture Technologies
Transportation
Storage Regions
Set-Up Rules and
Parameters
Chapter 7
Run Yea rs
Aggregation Schemes
R etrofit Assi gnm ents
Trading and Banking
P ost-2D30 Assu mptio ns
IPM Enginett
Chapter 2
Model Outputs
Emissions
Costs
C a pa cit/ Expansion and Generation
Retrofit Decisions
Fuel Consumption and Prices
Electricity Usage and Prices
Post-Processor
Financial Assumptions
J Chapter 8
Discount Rate
Capital Charge Rate
Book Life
Caprtal Cost Adder for Climate 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)
^ Chapter 10
North American Sup ply (from GMM
hrydrocarbon SupplyModel)
- Reserves and Resources
- Production Costs LNG Supply and Costs
Pipeline Netvuork
Storage
Non-EGU Demand (Residential, Commercial,
Industrial)
Pricing Mechanism
Parsina Outputs
IndMdual BoilerLey^l Data
Outputs for Air
Quality Modeling
C rite ri a Air Pollutants
N on- elite ria Air Pollutants
Toxi cs Aj r Po llutants
Point Source Locators
t Information on existing and planned electric gene rating units (EGUs) is contained in the National Electrical
Energy Data System (HEEDS) data base maintained for EPA by ICF International. Planned EGUs a re those
which were under construction or had obtained financing at the time that the EPA Base Case was finalized.
ine is the model structure described in Chapter2
10-2
-------
Figure 10-2 Natural Gas Module in EPA Base Case v.4.10.
MUHlGU
Supply Sub-Module
CatHvrtarwi
Noocorrป*nljonal
' t'_';! ?'
Economic Characterization
moon
P*W type, sas, S (Jeptti
Success rales
H'lllinj a olhe* COKS
OSM Factolt ConปซปHHj
Production casls
ProonwiQ plani co&tf
Uaซ snd plant giป Uw
Pipeline Transportal
Capacity & Rales
S*0 costs
OSH COStS
Natural Gป
Pipriinp
Model VปliatปiiCn
aacteattmg Exeretsa
Cahbfabora to hislarc
Improved success rates
fcnprovw) feamvTf pa well
Cost WdUcOom dxstftjrm, Onปng sic)
Economic *ve*ป
Qlorton
Natural Gn
Storago
LNO Sub-Modul*
aaion supp*y and
Regwderton capac*,1 intJcoป(
GM M refer s to ICF * GM Marks Model
E&D costs - exploration and rJewlcpn-ert! coete
O&M costs = operaStoos and maintenance coals
IMG i ijqudKKl nWuTSI gaป
10-3
-------
10.2 Key Components of the New IPM Natural Gas Module
The new 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 114 supply/demand/storage nodes and 14 LNG regasification 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 114 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 77 supply regions. "Resource Appreciation"2 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 77 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 excess of LNG regasification capacity already in
the system and a relatively low electricity demand growth assumption in the EPA Base Case
v.4.10, the regasification expansion feature is turned off. If future economic demands more LNG
capacity, it can be turned back on.
End use natural gas demand tor the non-power sectors (i.e. the residential, commercial, and
industrial sectors) is incorporated in the IPM LP structure 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.
2 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.
10-4
-------
Figure 10-3 Gas Transmission Network Map
Vf,-vM id* J'-'.H). [JKtB Bid LJr,u vmradd.Ai
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
Name
New England
Everett TRANS
Quebec
New York City
Niagara
Leidy
Cove Point TRANS
Georgia
Elba Is TRANS
South Florida
East Ohio
Maumee/Defiance
Lebanon
Indiana
South Illinois
North Illinois
Southeast Michigan
Tennessee/Kentucky
MD/DC/Northern VA
Wisconsin
Supply
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
Transit,
Import/
Export
X
X
X
Underground
Storage
X
X
X
X
X
X
X
X
Peakshaving
Storage
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
10-5
-------
Node
21
22
23
24
25
26
27
28
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
Name
Northern Missouri
Minnesota
Crystal Falls
Ventura
Emerson Imports
Nebraska
Great Plains
Kansas
East Colorado
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)
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
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
Transit,
Import/
Export
X
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
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
10-6
-------
Node
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
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
Name
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
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
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
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
Transit,
Import/
Export
X
X
X
X
X
X
X
X
Underground
Storage
X
X
X
X
X
X
X
X
X
X
X
Peakshaving
Storage
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
10-7
-------
Node
112
113
114
Name
Southeast Missouri
Uinta/Piceance
South MS/AL
Supply
X
X
X
Demand
X
X
X
Transit,
Import/
Export
Underground
Storage
X
X
X
Peakshaving
Storage
X
X
X
Figure 10-4 Gas Supply Regions Map
10-8
-------
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
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
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
39
41
45
47
48
49
50
54
55
56
57
58
59
60
61
62
Region Name
Niagara
Leidy
Florida
East Ohio
Maumee/ Defiance
Lebanon
Indiana
South Illinois
North Illinois
Southeast Michigan
Tennessee/Kentucky
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
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 S./ Desoto Canyon/Mississippi
Canyon
Henry Hub
North Louisiana Hub
Central and West Louisiana Shelf
10-1
-------
Supply
Region
Number
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
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
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
10-2
-------
Figure 10-5 Gas Demand Regions Map
Natural gas pipeline network is modeled by 343 transmission links or segments (excluding
pipeline connections with LNG 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.1 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
6-5
6-5
5-6
11 -6
11 -6
6-19
6-79
6-79
Pipeline
DOMINION TRANS (CNG)
COLUMBIA GAS TRANS CORP
NATIONAL FUEL GAS SUPPLY CO
DOMINION TRANS (CNG)
COLUMBIA GAS TRANS CORP
DOMINION TRANS (CNG)
TEXAS EASTERN TRANS CORP
TRANSCONTINENTAL GAS P L CO
1 In this context "load factor" refers to the percentage of the pipeline capacity that is utilized at a
given time.
10-3
-------
Link
6-79
80-6
80-6
96-8
96-10
80-11
17-12
98-12
14-13
98-14
16-15
16-20
16-98
78-17
99-17
18-80
18-92
79-19
19-79
19-79
92-19
23-99
106-23
41 -27
28-29
68-28
31 -30
31 -30
30-31
30-48
113-30
113-32
63-33
63-33
68-33
37-36
37-38
40-41
41 -83
73-43
46-45
46-48
66-51
51 -66
54-114
58-56
60-58
Pipeline
TENNESSEE GAS PIPELINE CO
COLUMBIA GAS TRANS CORP
EQUITRANS INC
SOUTHERN NATURAL GAS CO
FLORIDA GAS TRANS CO
COLUMBIA GAS TRANS CORP
ANR PIPELINE CO
ANR PIPELINE CO
PANHANDLE EASTERN P L CO
TRUNKLINE GAS CO
NAT GAS P L CO OF AMERICA
ANR PIPELINE CO
ANR PIPELINE CO
BLUEWATER PIPELINE CO
MICHCON
COLUMBIA GAS TRANS CORP
EAST TENNESSEE NAT GAS CO
EASTERN SHORE NAT GAS CO
TRANSCONTINENTAL GAS P L CO
COLUMBIA GAS TRANS CORP
COLUMBIA GAS TRANS CORP
GREAT LAKES GAS TRANS LTD
GREAT LAKES GAS TRANS LTD
WILLISTON BASIN P L CO
COLORADO INTERSTATE GAS
COLORADO INTERSTATE GAS
COLORADO INTERSTATE GAS
SOUTHERN STAR CENTRAL (WILLIAMS)
WYOMING INTERSTATE CO
NORTHWEST PIPELINE CORP
NORTHWEST PIPELINE CORP
NORTHWEST PIPELINE CORP
EL PASO NAT GAS CO
TRANSWESTERN PIPELINE CO
TRANSWESTERN PIPELINE CO
SOCAL GAS
PACIFIC GAS & ELECTRIC
NORTHWEST ENERGY
WILLISTON BASIN P L CO
TERASEN (BC GAS)
NORTHWEST PIPELINE CORP
NORTHWEST PIPELINE CORP
TENNESSEE GAS PIPELINE CO
TEXAS EASTERN TRANS CORP
TRANSCONTINENTAL GAS P L CO
GULF SOUTH (KOCH)
TRANSCONTINENTAL GAS P L CO
10-4
-------
Link
60-58
60-58
60-58
60-58
60-58
60-65
61 -107
64-63
64-63
65-63
66-63
68-63
63-68
63-97
65-64
65-64
108-68
108-68
68-108
106-78
102-84
99-98
99-98
101 -102
Pipeline
SOUTHERN NATURAL GAS CO
FLORIDA GAS TRANS CO
TENNESSEE GAS PIPELINE CO
TEXAS EASTERN TRANS CORP
GULF SOUTH (KOCH)
NAT GAS P L CO OF AMERICA
CENTERPOINT ENERGY (RELIANT)
TXU LONESTAR GAS PIPELINE
EPGT TEXAS PIPELINE (VALERO)
OASIS
EPGT TEXAS PIPELINE (VALERO)
TRANSWESTERN PIPELINE CO
EL PASO NAT GAS CO
EL PASO NAT GAS CO
TXU FUEL CO
TXU LONESTAR GAS PIPELINE
NAT GAS P L CO OF AMERICA
EL PASO NAT GAS CO
ANR PIPELINE CO
UNION GAS
BAJA NORTE
ANR PIPELINE CO
MICHIGAN GAS STORAGE
EL PASO NAT GAS CO
Natural gas storage is modeled by 180 underground and LNG peak shaving storage facilities
that are linked to individual nodes. The underground storage is grouped into three categories
based on storage "Days Service"3: (1) 20-day for high deliverability4 storage such as salt caverns,
(2) 80-day for depleted5 and aquifer6 reservoirs, and (3) over 80 days mainly for depleted
reservoirs. Figure 10-6 shows natural gas storage facility node map. The level of gas storage
withdrawals and injections are calculated within the supply and demand balance algorithm based
on working gas7 levels, gas prices, and extraction/injection rates and costs. Starting year of
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.
3 "Days Service" refers to the number of days required to completely withdraw the maximum
working gas inventory associated with an underground storage facility.
4 High deliverability storage is depleted reservoir storage facility or Salt Cavern storage whose
design allows a relatively quick turnover of the working gas capacity.
5 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.
6 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.
7 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
10-5
-------
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-2030 Input Assumptions
The time horizon of previous EPA IPM base cases extended no further than 2030. This made
possible a detailed bottom-up development of natural gas assumptions from available data
sources. To support analysis of climate change policies, which have a longer time horizon than
previously analyzed policies for conventional air pollutants, the time horizon of EPA's new Base
Case v.4.10 extends to 2050. The same detailed bottom-up approach that was employed
previously is employed out to 2030. Beyond 2030, where detailed data is not readily available,
various technically plausible simplifying assumptions were made. For example, natural gas
demand growth from 2030 to 2050 for the non-power sectors (i.e. residential, commercial, and
industrial) is assumed to be the same as the level of growth from 2020 to 2030. Resource growth
assumptions (for resource appreciation) that were applied for pre-2030 are extended beyond
2030. Post 2030 price projections for crude oil and natural gas liquid8 (NGL) are assumed to be
flat at 2030 price levels. The pre-2030 price projections were adapted from AEO 2010.
reservoir in order to maintain adequate pressure and deliverability rates throughout the withdrawal
season.
8 Those hydrocarbons in natural gas that are separated from the gas as liquids in gas processing
or cycling plants. Generally such liquids consist of propane and heavier hydrocarbons and are
commonly referred to as lease condensate, natural gasoline, and liquefied petroleum gases.
10-6
-------
Figure 10-6 Natural Gas Storage Facility Node Map
O 20-Day
80-Day
A Over 80 Days
Q LNG Peak Shaving
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.4.10 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 US 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 with which those resources can be proven9 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
9 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.
10-7
-------
of base year economically recoverable natural gas resources and remaining reserves as a
function of E&D cost for the 77 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.10
10.3.1 Resource and Reserves11 Assessment
Data sources: The HSM uses the U.S. Geological Survey (USGS), Minerals Management
Service (MMS), and Canadian Gas Potential Committee (CGPC) play-level12 resource
assessments as the starting point for the new field/new pool13 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 gas14, 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 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.15
10 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.
11 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.
12 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.
13 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.
14 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) "coalbed 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.
15 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,
10-8
-------
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.16
In Canada, gas composition data are obtained from provincial agencies. These data were used to
develop dry gas17 production/reserves by region and processing costs in the HSM and to
characterize ethane rejection18 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" equation19 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.
harmonic, and hyperbolic equations are typically used to represent the decline curve.
16 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.
17 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'.
18 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.
19 "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.
10-9
-------
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: The Enhanced Recovery Module (or ERM) within the HSM, 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.
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. Results from HSM simulation for the two frontier regions can be seen
in Table 10-4. It shows an undiscovered resource potential is 126.8 Tcf for Alaska North Slope
and 32.9 Tcf for Mackenzie Delta and remaining gas reserves of 25.5 Tcf and 0.4 Tcf for Alaska
North Slope and Mackenzie Delta, respectively. 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 gas to market
in order to realize the long-held goal of monetizing the Alaska North Slope and Mackenzie Delta
gas.
In developing the gas resource assumptions for EPA Base Case v.4.10, two gas pipeline projects
were identified for bringing the two frontier gas supply resources to the markets in the U.S. and
Canada. A diagnostic run was made with both potential pipeline projects turned on, letting the
model decide the starting year of the projects and subsequent pipeline capacity expansions.
Analysis of pipeline capacities and flows indicated that the Alaska gas pipeline project would be
feasible starting from 2035, but the Mackenzie Delta pipeline project would not be feasible at all
due to relatively low pipeline flows. These were the assumptions used for EPA Base Case v.4.10.
Table 10-4 U.S. and Canada Natural Gas Resources and Reserves
Region
Lower 48 Onshore Non
Associated
Conventional
Northeast
Gulf Coast
Midcontinent
End of Year 2008
Undiscovered
Dry Gas
Resource
(Tcf)
1,629.0
313.3
15.4
133.9
54.4
Dry Gas
Reserves
(Tcf)
208.5
50.1
3.8
16.4
11.2
End of Year 2010
Undiscovered
Dry Gas
Resource
(Tcf)
1,616.2
306.6
15.0
131.5
52.7
Dry Gas
Reserves
(Tcf)
208.0
50.0
3.8
16.4
11.2
10-10
-------
Region
Southwest
Rocky Mountain
West Coast
Shale Gas
Northeast
Gulf Coast
Mid continent
Southwest
Rocky Mountain
West Coast
Coalbed Methane
Northeast
Gulf Coast
Midcontinent
Southwest
Rocky Mountain
West Coast
Tight Gas
Northeast
Gulf Coast
Midcontinent
Southwest
Rocky Mountain
West Coast
Lower 48 Offshore Non
Associated
Lower 48 Associated-
Dissolved Gas
Total Lower 48
Alaska
Alaska North Slope
Alaska - Other
Total U.S.
Canada Non Associated
Conventional
Shale Gas
Coalbed Methane
Tight Gas
Canada Associated-
Dissolved Gas
Eastern Canada Offshore
MacKenzie Delta
Total Canada
End of Year 2008
Undiscovered
Dry Gas
Resource
(Tcf)
19.2
84.0
6.4
921.2
254.8
433.1
133.9
61.3
37.9
0.3
73.9
9.5
4.3
9.6
-
49.8
0.7
320.7
33.7
59.6
4.6
6.1
205.1
11.5
137.1
145.1
1,911.2
153.6
126.8
26.8
2,064.8
667.9
121.4
508.8
27.4
10.3
8.1
71.8
32.9
780.8
Dry Gas
Reserves
(Tcf)
5.6
10.7
2.4
38.5
3.5
13.5
10.9
10.7
-
-
20.5
2.0
1.2
2.2
-
15.1
-
99.5
6.6
28.9
7.5
15.2
41.2
-
10.5
17.9
237.0
35.2
25.2
9.9
272.1
56.7
43.6
0.5
12.5
-
2.7
2.5
0.4
62.3
End of Year 2010
Undiscovered
Dry Gas
Resource
(Tcf)
18.6
82.6
6.2
917.2
254.4
431.6
132.9
60.3
37.7
0.3
73.1
9.5
4.2
9.5
-
49.3
0.6
319.2
34.0
58.2
4.6
5.9
204.9
11.6
136.3
143.5
1,895.9
153.3
126.8
26.5
2,049.2
667.3
119.6
511.1
26.7
9.9
8.0
71.6
32.9
779.8
Dry Gas
Reserves
(Tcf)
5.6
10.7
2.3
38.4
3.5
13.4
10.8
10.6
-
-
20.4
2.0
1.2
2.2
-
15.0
-
99.2
6.6
28.9
7.5
15.1
41.1
-
10.5
17.9
236.3
35.2
25.2
9.9
271.5
56.5
43.5
0.5
12.5
-
2.7
2.5
0.4
62.1
10-11
-------
10.3.3 Use of the HSM resource and reserves data in EPA Base Case using IPM v.4.10
Natural Gas Module
The base year for the integrated gas-electricity module in EPA Base Case using IPM v.4.10 is
2012. 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
2011 to provide end of year (EOY) 2011 reserves and resources as the starting point for the
integrated run from 2012 onward. This in turn requires the reserves and resources data to be
provided for the EOY 2010. Since the data from the HSM are as of EOY 2008, a two-year
production forecast needs to be conducted to estimate the EOY 2010 gas resources and
reserves. This production forecast is done using the GMM with the EPA Base Case assumptions.
In the future if an IPM sensitivity analysis case is performed whose assumptions are likely to have
a significant impact on gas reserves and resources in the 2009-2010 timeframe, the HSM
projection of EOY 2010 gas resources and reserves may have to be re-run.
The last two columns in Table 10-4 give a snapshot of the starting natural gas resource and
reserve assumptions that were provided by HSM to EPA Base Case v.4.10 for EOY 2010. 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. The reserves are remaining dry gas volumes to be produced from
existing developed fields. For EPA Base Case the maximum wellhead price for the resource cost
curves is capped at around $14/MMBtu (in real 2007 dollars). The ultimate potential undiscovered
resources available are actually higher than those presented in Table 10-4 but it would cost more
than $14/MMBtu to recover them. (It is important to note that this price is for wet20 gas at the
wellhead in the production nodes and is found to be high enough to cover the range of wellhead
prices for EPA scenarios. The dry gas price at the receiving nodes can be higher than
$14/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.
Since the new 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 gas21 from oil fields. The unconventional gas is
subdivided into coalbed methane, shale gas, and tight gas. The U.S. and Canada natural gas
undiscovered resources and remaining reserves as of EOY 2008 and their estimates for the EOY
2010 are also shown in Table 10-4.
Figure 10-7 presents resource cost curves for the EOY 2010 initializing gas assumptions that the
HSM provides for EPA Base Case v.4.10. The cost curves show the recoverable resources at
different price levels. Separate resource cost curves are shown for key regions as well as for
conventional and unconventional gas. The recoverable resources shown at maximum wellhead
prices in these graphs are those tabulated in Table 10-4 under EOY 2010 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.
20 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.
21 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.
10-12
-------
Figure 10-7 Resource Cost Curves at the End of Year 2010
14 n
13
100 200 300 400 500 800 700 600
Undiscovered Dry Gas Resource (Tcf)
-h*QTlrieast -- Gulf Coast -*-Midocntinent
- Rocky Mountain -a- West Coast -ฑ- Gulf Offshore
-Alaska -a- Easlem Canada Onshore - MacKenzie Delta
Southwest
- Western Canada
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 EOY2010 undiscovered resources in Table 10-4 and Figure 10-7
include resource appreciation in 2009 and 2010.
10-13
-------
Figure 10-8 Exploration & Development and Production Processes and Costs to Bring
Undiscovered Resource into Reserves and Production
Production ^_^_^ Produ
(Wet) / (D
/
/
i
Rest
1 Processing '
- Dry gas share
- Lease and plant use
- Gas processing cost
\^
\ Production
- Reserves-to-production ratio
- Production cost
Undisc
\ Reso
\
\
\
\
\
Exploration & Development *
- Resource potential
- Resource discovery factor
- Exploration & Development drilling requirement
- Exploration & Development costs
ction
ry)
overed
urce
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 overtime 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
10-14
-------
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.
Figure 10-10 shows E&D cost needed to discover and develop 2.5%, 5%, and 7.5% of the
remaining undiscovered resource in 2011 by natural gas supply region.
Figure 10-9 E&D and Production Technology Improvement Factor
Figure
0.5
2010
2020
2030
2040
2050
2060
Onshore
Offshore Shelf
1 Offshore Deepw ater
10-10
10-15
-------
Incremental E&D Cost (EOY 2010) by Percentage of Resource Found
(114) South MS/AL
(113) Uinta/Piceance
(111) Northern Arkansas
(110) Southeastern Oklahoma
(109) Northeast Oklahoma
(108) Southwest Oklahoma
(107) Carthage
(99) Central Michigan
(98) Southwest Michigan
(96) Florida
(92) SWVirginia
(90) Arctic
(89) Northern Alaska
(87) Southern Alaska
(86) McKenzie Delta
(83) Wind River Basin
(80) West Virginia
(76) Saskatchewan
(74) Caroline
(72) North British Columbia
(71) Florida off-shore moratorium
(70) Green Canyon
(69) Garden Banks
(68) NWTX
(67) Offshore Texas
(66) S. TX
(65) E. TX (Katy)
(64) Dallas/Fort Worth
(63) Southw est Texas
(62) Central and West Louisiana Shelf
(61) North Louisiana Hub
(60) Henry Hub
(59) Viosca Knoll S./ Desoto
(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) SOCAL Area
(34) North Wyoming
(32) San Juan Basin
(30) Opal
(29) East Colorado
(28) Kansas
(21) Northern Missouri
(18) Tennessee/Kentucky
(16) North Illinois
(15) South Illinois
(14) Indiana
(11) East Ohio
(6) Leidy
(5) Niagara
0
4 6
Resource Cost at Wellhead
(2007$/MMBtu)
10
D2.5% B5.0% n7.5%
10-16
-------
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 4% of the remaining undiscovered
resource (column 4 in Table 10-5). The drilling requirement constraint (column 5 in Table 10-5) is
10,000 feet for every billion cubic feet of incremental resource discovered for onshore and 2,500
feet/Bcf for offshore.
Table 10-5 Exploration and Development Assumptions for EPA Base Case v.4.10
Region
(5) Niagara
(6) Leidy
(11) East Ohio
(14) Indiana
(15) South Illinois
(16) North Illinois
(18)
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 S./
Desoto
Canyon/Mississippi
Canyon
(60) Henry Hub
Fraction of
Hydrocarbons
that are
Natural Gas
Liquids
(NGLs)
(Fraction)
0.01
0.00
0.00
0.05
0.10
0.10
0.12
0.15
0.13
0.09
0.09
0.09
0.09
0.01
0.02
0.03
0.04
0.26
0.01
0.04
0.04
0.07
0.11
0.07
0.11
Fraction of
Hydrocarbons
that are Crude
Oil
(Fraction)
0.04
0.05
0.23
0.81
0.10
0.10
0.10
0.46
0.17
0.10
0.10
0.10
0.10
0.91
0.81
0.88
0.72
0.00
0.88
0.22
0.22
0.52
0.27
0.52
0.27
Max Share of
Resources
that can be
Developed
per Year
(Fraction)
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
Exploration,
Development
Drilling
Required
(Ft/Bcf)
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
2,500
10,000
2,500
2,500
10,000
2,500
10,000
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
10-17
-------
Region
(61) North Louisiana
Hub
(62) Central and West
Louisiana Shelf
(63) Southwest Texas
(64) Dallas/Fort Worth
(65) E. TX (Katy)
(66) S. TX
(67) Offshore Texas
(68) NW TX
(69) Garden Banks
(70) Green Canyon
(71) Florida off-shore
moratorium area
(72) North British
Columbia
(74) Caroline
(76) Saskatchewan
(80) West Virginia
(83) Wind River Basin
(86) McKenzie Delta
(87) Southern Alaska
(89) Northern Alaska
(90) Arctic
(92) SW Virginia
(96) Florida
(98) Southwest
Michigan
(99) Central Michigan
(107) Carthage
(108) Southwest
Oklahoma
(109) Northeast
Oklahoma
(110) Southeastern
Oklahoma
(111) Northern
Arkansas
(113) Uinta/Piceance
(114)SouthMS/AL
Fraction of
Hydrocarbons
that are
Natural Gas
Liquids
(NGLs)
(Fraction)
0.08
0.07
0.12
0.07
0.17
0.12
0.06
0.22
0.06
0.07
0.07
0.01
0.03
0.00
0.07
0.09
0.00
0.00
0.00
0.05
0.00
0.02
0.04
0.04
0.08
0.13
0.13
0.13
0.00
0.09
0.04
Fraction of
Hydrocarbons
that are Crude
Oil
(Fraction)
0.08
0.52
0.52
0.06
0.19
0.07
0.25
0.05
0.25
0.52
0.52
0.05
0.19
0.73
0.04
0.10
0.00
0.00
0.00
0.55
0.01
0.82
0.11
0.11
0.08
0.17
0.17
0.17
0.13
0.10
0.22
Max Share of
Resources
that can be
Developed
per Year
(Fraction)
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
0.04
Exploration,
Development
Drilling
Required
(Ft/Bcf)
10,000
2,500
10,000
10,000
10,000
10,000
2,500
10,000
2,500
2,500
2,500
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
10,000
Lease
and Plant
Use
(Fraction)
0.04
0.04
0.05
0.05
0.05
0.05
0.05
0.05
0.04
0.04
0.04
0.08
0.10
0.07
0.04
0.05
0.08
0.08
0.08
0.08
0.02
0.21
0.04
0.04
0.05
0.04
0.04
0.04
0.04
0.05
0.03
Other drilling constraints include rig capacity, rig retirement, rig growth, and drilling speed. Values
forthe 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 base year 2011. The initial rig counts are 3,798 rigs for onshore, 115
rigs for offshore shelf, and 115 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
10-18
-------
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).
Figure 10-11 Drilling Rig Speed Constraint
700
2000
2010
2020
2030 2040 2050 2060
Onshore
1 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 16 years of R/P). Coalbed methane gas has the lowest P/R ratio with average of 0.03
(or 32 years of R/P) or half of that of the tight and shale gas.
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 2011 is estimated to be
$0.51/MMBtu (in real 2007 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.
10-19
-------
Table 10-5 shows the shares of NGL (column 2) and crude oil (column 3) by supply region.
Associated gas from crude oil and NGL from wet gas are 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 2007
dollars) to $0.56/MMBtu with average of $0.22/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).
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 base year 2011 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.22 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 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 2011 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 2011 and 2050.
22 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.
10-20
-------
50
a 40
s.
30
01 20
10
Figure 10-12 North American LNG Supply Curves
Winter 2011
10 15 20
Max quantity LNG (Bcf/day)
25
30
Summer 2011
5 40 -
1
w 30
r-
g
0.
0 1n
Z 1U -
_l
0
V***'*
0 5 10 15 20 25 30
Max quantity LNG (Bcf/day)
Winter 2050
10 15 20
Max quantity LNG (Bcf/day)
25
30
Summer 2050
0 5 10 15 20 25 30
Max quantity LNG (Bcf/day)
10.5.2 Regasification Facilities
For the EPA Base Case, ten existing and four potentials North American LNG regasification
facilities are considered in the IPM natural gas module. Table 10-6 lists the 14 facilities (current
existing facilities are highlighted), the destination nodes where the LNG are delivered, and the
base year 2011 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. However, the electric generating units
that consume gas from the Penuelas LNG facilities are included in the IPM electric module. In
EPA Base Case v.4.10. 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
LNG Regasification
Facility
Cove Point
Elba Island
Everett
Node Location
(7) Cove Point TRANS
(9) Elba Is TRANS
(2) Everett TRANS
Base Year
(2011)
Regasification
Capacity
(Bcf/day)
1.50
2.10
0.70
10-21
-------
No
4
5
6
7
8
9
10
11
12
13
14
LNG Regasification
Facility
Gulf Gateway
Lake Charles
Altamira
Costa Azul
Cameron LNG
Freeport LNG
Golden Pass
Canaport
Sabine Pass
Gulf LNG Energy
LLC
Northeast Gateway
Node Location
(69) Garden Banks
(60) Henry Hub
(51) Reynosa Imp/Exp
(84) California Mexican Exports
(60) Henry Hub
(65) E. TX (Katy)
(65) E. TX (Katy)
(49) Eastern Canada Offshore
(60) Henry Hub
(56) North Mississippi
(1) New England
Base Year
(2011)
Regasification
Capacity
(Bcf/day)
0.50
2.10
1.00
2.00
1.50
1.50
2.00
1.00
2.60
1.00
0.80
Figure 10-13 North American LNG Regasification Facilities Map
'(11) Canaport
\0
\f W
-&) Everett
14) NE Gateway
(1) Cove Point
12) Sabin PassQ (2) Elba Island
O
(7) Costa Azul
(10) Golden Pass
O'
(9) Freeport LNG Q
(4) Gulf Gateway
O(13) Gulf LNG Energy
'(5) Lake Charles
O (6) Altamira
O Existing
O Potential
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.
10-22
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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 base year 2011 levelized
capital cost for capacity expansion (in real 2007 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 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.4.10. EPA scenario results show very low
total LNG utilizations, less than 15%, throughout the projection period which 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 curves23. 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 demand 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.
23 "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.
10-23
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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.
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 over time 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
10-24
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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.
10.6.2 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 4.10. For these purposes a U.S. annual GDP growth rate of 3.0%, a U.S. annual industrial
production growth rate of 2.3%, and a Canadian annual GDP growth rate of 2.5 % are assumed.
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.4.10,
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.4.10, 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.
10-25
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Table 10-7 Summer and Winter Load Segments in EPA Base Case v.4.10
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.
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.4.10. 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. It should be noted that firm gas
demand (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.4.10 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. Sensitivity runs with slight modifications to
the macroeconomic assumptions can still use the same curves if the gas demand forecast is
expected not to be much different than that from the base case. In this case, changes in the gas
demand solutions have minor effect to the long-term elasticity. However, a sensitivity run (e.g.
carbon policy run) with major changes in CO2 allowance prices should not use the same gas
demand curves because it will have higher impact to the long-term gas demand elasticity. A new
set of non-electric gas demand curves needs to be generated for this type of run.
Figure 10-14 Examples of Firm Demand Curves by Electric Load Segment
Gas Price
New England (Node 1), Winter 2011
35
30
25 -
f 20
* 15
5
0 -
I
1
1
1
. 1
1
1
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i
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t
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9
; (
( (
( (
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! <
! o
0.00 0.05 0.10 0.15 0.20 0.25 0.30
Firm Demand (Bcf)
* Needle Peak Near Peak A High Shoulder
o Middle Shoulder at Low Shoulder Base
Gas Price
New England (Node 1), Summer 2011
ฐ5
25
3
i 1-=
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0.00 0.01 0.02 0.03 0.04 0.05 0.06 0.07
Firm Demand (Bcf)
Needle Peak - Near Peak A High Shoulder
e Middle Shoulder 516 Low Shoulder Base
10-26
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Figure 10-15 Examples of Interruptible Demand Curves by Electric Load Segment
New England (Node 1), Winter 2011
10.00 15.00 20.00
Interruptible Demand (Bcf)
- Needle Peak
- Middle Shoulder
- Near Peak
- Low Shoulder
-High Shoulder
-Base
Gas Price
New England (Node 1), Summer 2011
9 -n
* 15
3- m
m
1
l
l
1
1
1
1
'
,
,
t *
II
u
U
U
u
1 1 ic
0.00 5.00 10.00 15.00 20.00 25.00 30.00
Interruptible Demand (Bcf)
ซ Needle Peak m Near Peak A High Shoulder
e Middle Shoulder * Low Shoulder Base
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 3431 gas pipeline corridors (including
bi-directional links) between the 114 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.2 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 10-16 shows the flow and capacity
of five pipeline corridors in New England in 2020. Gas flows into New England along three
pipeline corridors (indicated in Figure 10-16 by 3 of the 4 arrows that point into the region)
representing a total of seven pipeline systems (indicated by name labels in Figure 10-16). New
England also receives gas via the Everett LNG terminal (indicated in Figure 10-16 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 10-16 by the arrow that points away
from the region).
Excluding LNG import Terminal nodes and their pipeline connections.
2 See footnote #3 above for a definition of "load factor."
10-27
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Figure 10-16 New England Pipeline Corridors in 2020
Maritimes & Northeast
Portland Natural Gas
Granite State
Vermont Gas
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 basis3 (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 10-17 depicts the
base year 2011 discount curve for the pipeline corridor connecting nodes (61) North Louisiana
Hub and (18) Tennessee/Kentucky. Cost growth factors shown in Figure 10-18 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.
3 See footnote #1 above for a definition of "basis."
10-28
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Figure 10-17 Example Pipeline Discount Curve
N LAHub(61)toTN/KY(18)
1.00
0.00
40
60
80
100
Pipeline Utilization (%)
Figure 10-18 Pipeline Cost Growth Factor
1.30
1.25
1.20
1.15
1.10
1.05
1.00
2010
2020
2030
2040
2050
2060
10.7.3 Pipeline Capacity Expansion Logic
Base year pipeline capacity, derived from GMM, includes existing capacities and planned
capacities that are expected to be operational from the beginning of 2011. 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 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 infinity4 as their maximum capacity addition
requirement. Where this occurs, the pipeline expansion is only controlled by the pipeline capital
cost.
4ln 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.
10-29
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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.4.10, 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. Based on diagnostic run analysis discussed in Section 3, the Mackenzie
Delta pipeline project is not made available throughout the projection. Both capacity addition
constraints for Mackenzie delta are set to zero. Based on the same analysis, the Alaska pipeline
corridors (connecting nodes 89, 88, 87, and 72) are set to come online from 2035. The minimum
capacity constraint is set to zero throughout the projection. The maximum capacity constraint is
initially set to zero to restrict pipeline builds and then set to infinity from 2035.
Expansions in other pipeline corridors are not restricted. The model is allowed to build capacity to
any pipeline corridors at any time as long as it contributes to minimization of the objective function.
There is no reason for restricting the upper bound for capacity expansion since the IPM/Gas
model was designed to be used as a long-term policy tool rather than a pipeline analysis tool.
Having no restriction to the minimum capacity expansion, however, is a limitation of the model as
it may lead to unrealistic capacity expansions especially for large pipeline projects such as Alaska
and Mackenzie Delta. Without restricting the starting dates and the capacities, the model may
build unrealistically low incremental capacities throughout the projection. This was the reason for
conducting the diagnostic run for Alaska and Mackenzie Delta projects. Theoretically, it is
possible to add capability in the model to make decisions on minimum incremental pipeline
capacity expansions. However, it requires adding a lot more constraints to the LP which may
result in prohibitively large model. The workaround for ensuring reasonable capacity expansion
results is to perform diagnostic runs such as that for Alaska and Mackenzie Delta.
The base year 2011 levelized pipeline capital cost (in real 2007 dollars per MMBtu/Day of pipeline
capacity addition) is specified for each of the 343 pipeline links. The cost growth factors shown in
Figure 10-18 are applied to derive the cost increase overtime. The average levelized capital cost
for pipeline capacity expansion for 2011 is $154 per MMBtu/Day. The expected levelized capital
cost for North Alaska pipeline for 2035 is $305 per MMBtu/Day.
10.8 Gas Storage
The IPM natural gas module has 108 underground storage facilities that are linked to 48 nodes.
The underground storage is grouped into three categories based on storage "Days Service."5
"20-Day" high deliverability storage - 35 storage facilities
"80-Day" depleted/aquifer reservoirs - 38 storage facilities
"Over 80 Days" depleted/aquifer reservoirs - 35 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.
5 See footnote #5 above for a definition of "Days Service."
10-30
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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 108 such X's which correspond to the 108 underground
storage facilities noted in the previous paragraph. These 108 X's appear in 48 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) Leidy
(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) Tennessee/Kentucky
(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
Underground Storage
Facility
20-
Day
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
Over
80
Days
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
Potential
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
10-31
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Node
(46) NPC/PGT Hub
(47) North Nevada
(48) Idaho
(54) North Alabama
(56) North Mississippi
(58) Eastern Louisiana Hub
(60) Henry Hub
(61) North Louisiana Hub
(63) Southwest Texas
(64) Dallas/Ft Worth
(65) E. TX (Katy)
(66) S. TX
(68)NWTX
(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
(1 06) Toronto
(107) Carthage
(108) Southwest Oklahoma
(109) Northeast Oklahoma
(110) Southeastern Oklahoma
(111) Northern Arkansas
(112) Southeast Missouri
(113) Uinta/Piceance
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
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
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
X
X
10-32
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Node
(11 4) South MS/AL
Underground Storage
Facility
20-
Day
X
80-
Day
X
Over
80
Days
LNG Peakshaving
Facility
Existing
Potential
X
10.8.1 Storage Capacity and Injection/Withdrawal Constraints
Working gas capacity is initially allocated in the GMM to individual nodes based on historical data.
Since the base year in EPA Base Case using IPM v.4.10 gas module is 2011, a projection of
natural gas storage capacity at the end of 2010 is needed as a starting point. The expected
working gas capacity as of EOY 2010 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 EOY 2010 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 (i.e., totals and averages); the actual GMM EOY 2010 inputs to the
IPM gas module vary by location and storage type.
Table 10-9 Storage Capacity and Injection/Withdrawal Rates (EOY 2010)
Underground Storage
20 Day
80 Day
Over 80 Days
Total
LNG Peakshaving Storage
Working Gas
Capacity (Bcf)
458
3,353
944
4,755
84
Average Daily
Injection Rate
(Percent of WG
Capacity)
6.7
1.3
0.5
0.5
Average Daily
Withdrawal Rate
(Percent of WG
Capacity)
9.3
2.2
0.9
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 base year 2011 variable cost or commodity6 charge for underground storage
facilities is assumed to be 1.54 cents/MMBtu and is the same for all underground storage nodes
and types. The variable cost for LNG peakshaving facility is much higher at 36 cents/MMBtu as it
includes variable costs for gas liquefaction (in gas injection process) and LNG regasification (in
gas withdrawal process). The variable cost is assumed to be the same for all LNG peakshaving
nodes. A storage cost growth factor shown in Figure 10-19 is applied to the injection/withdrawal
cost to reflect cost increase over time. The cost is assumed to grow at an average rate of 0.5
percent per year.
6 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
10-33
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Figure 10-19 Storage Cost Growth Factor
1.30
1.25
1.20
1.15
1.10
1.05
1.00
2010
2020
2030
2040
2050
2060
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 10-20 shows projected maximum storage
expansion constraints for the "80-day" category storage facility in supply area Katy, Texas.
Figure 10-20 Example Maximum Storage Capacity Expansion
Storage category: "80-day"
Supply area: Katy, Texas
RD
50 -
4D -
*O Qf)
CQ ou
9n
m -
I
1
f
J
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,
10-34
-------
storage capacity expansion projects will compete with each other and even with other projects
such as LNG regasification capacity expansions, pipeline expansions, etc.
The base year 2011 levelized storage capital cost (in real 2007 dollars per MMBtu of storage
capacity addition) is specified for each of the 180 storage facilities. Table 10-10 lists the average
base year 2011 levelized storage capital cost for the four types of storage facility. Amongst the
underground storage facilities the higher capital costs represent more storage cycles7 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 20 percent and 50 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 10-19
are applied to the capital cost to derive the cost increase over time. The capital cost is assumed
to grow at an average rate of 0.5 percent per year.
Table 10-10 Base Year 2011 Average Levelized Storage Capital Cost
Storage Type
Underground Storage
20-Day
80-Day
Over 80 Days
LNG Peakshaving Storage
Average Levelized
Storage Capital Cost
(2007$/MMBtu)
1.09
0.86
0.72
5.13
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
10-21. These price projections were adapted from AEO 2009. No attempt was made to project
prices beyond 2030 other than to assume that prices remain at their 2030 levels. The projected
prices shown in Figure 10-21 are expressed in units of 2007$ per MMBtu. Using a crude oil Btu
content of 5.8 MMBtu/Bbl, the projected crude oil prices in Figure 10-21 can be translated into the
more familiar units of dollars per barrel (Bbl), in which case, prices in this figure are equivalent to
$62/Bbl in 2011, $97/Bbl in 2015, $114/Bbl in 2020, and constant at $124/Bbl from 2030 (in real
2007 dollars) onward.
7 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.
10-35
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Figure 10-21 Crude Oil and NGL Prices
25.00
20.00
15.00
~ 10.00
01
o
5.00
0.00
2000
2010 2020 2030 2040
2050 2060
Crude Oil
Natural Gas Liquids
10.9.2 Natural Gas Prices
Node-level natural gas prices are outputs of the model and are obtained from the optimal solution
of the combined IPM electric power sector and natural gas linear programming (LP) model. From
a technical modeling standpoint, the node gas prices are what are called "shadow prices" or "dual
variable values" associated with the node mass balance constraints at the optimal LP solution.
10.10 Outputs and Proxy Natural Gas Supply Curves
10.10.1 Outputs from the New IPM Natural Gas Module
Previous EPA IPM base cases reported natural gas consumption (in TBtu), Henry Hub and
delivered natural gas prices (in $/MMBtu). In addition to these reports, the new natural gas
module in EPA Base Case v.4.10 is capable of reporting natural gas supply (in Tcf), disposition (in
Tcf), prices (in $/MMBtu), production (in Tcf) by supply region, end-of-year reserves and annual
reserve additions (in Tcf), imports and exports (in Tcf), consumption by end-use sector and
census division (in Tcf), prices by census division (in $/MMBtu), and inter-regional pipeline flows
and LNG imports (in Bcf).
10.10.2 Proxy Natural Gas Supply Curves
In previous EPA IPM base cases a set of gas supply curves was generated outside of IPM (most
recently by ICF's NANGAS (North American Natural Gas Analysis System) model) and then used
in IPM as part of the base case input assumptions. (For a description of this approach see
Appendix 8-2.9 "Technical Background Paper on the Development of Natural Gas Supply Curves
for EPA Base Case 2004, v.2.1.9" in Standalone Documentation for EPA Base Case 2004
(V.2.1.9) Using the Integrated Planning Model EPA 430-R-05-011, September 2005. It is
available for viewing and downloading at www.epa.gov/airmarkets/progsregs/epa-
ipm/docs/bc8appendix.pdf.) The incorporation of the new fully integrated natural gas module into
IPM eliminates the use of explicit gas supply curves, replacing them with more dynamic and
responsive representation of an integrated natural gas supply chain and the U.S. power sector.
However, it is recognized that it would be useful to have a set of proxy natural gas supply curves
from the new integrated approach that could be compared to the natural gas supply curves used
in previous EPA Base Cases. The proxy curves would only represent a one-time snapshot of
supply/price relations resulting from the new integrated approach, but at least it would provide a
point of comparison with the natural gas supply curves used in previous EPA IPM base cases.
10-36
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Table 10-11 contains the proxy supply curves for the electric power sector for 2015 and 2020.
(These are years that would be directly comparable with supply curves from previous base cases.)
The curves were generated based on GMM supply elasticities and gas demand and price
solutions from the IPM/Gas model. The supply elasticity is calculated from GMM for each of the
IPM run years. The gas supply curve, for each IPM run year, is constructed by applying the
supply elasticity around the price/quantity solution of gas consumption in the power sector from
the IPM/Gas model (highlighted rows in
Table 10-11) varying the price from $3/MMBtu to $15/MMBtu (in real 2007 dollar). The supply
elasticity, in the same run year, is assumed to be constant within the price range.
The proxy supply curves below specify annual price and volume relationships at the Henry Hub.
For each listed step the price applies for all increments of supply greater than the value shown in
the preceding step up to and including the supply level indicated in the current step.
Table 10-11 Proxy Natural Gas Supply Curves for EPA Base Case v.4.10
2015
Gas Price
(2007$/MMBtu)
3.00
3.11
3.23
3.34
3.45
3.56
3.68
3.79
3.90
4.02
4.13
4.24
4.36
4.47
4.58
4.69
4.81
5.08
5.34
5.61
5.88
6.15
6.42
6.69
6.95
7.22
7.49
7.76
8.03
8.29
Gas Supply to
Electric Sector
(TBtu)
4,385
4,469
4,552
4,633
4,713
4,792
4,870
4,946
5,022
5,096
5,169
5,242
5,313
5,384
5,453
5,522
5,590
5,741
5,887
6,030
6,171
6,308
6,442
6,574
6,703
6,831
6,956
7,078
7,199
7,318
2020
Gas Price
(2007$/MMBtu)
3.00
3.08
3.16
3.23
3.31
3.39
3.47
3.55
3.63
3.70
3.78
3.86
3.94
4.02
4.09
4.17
4.25
4.53
4.82
5.10
5.38
5.66
5.95
6.23
6.51
6.80
7.08
7.36
7.64
7.93
Gas Supply to
Electric Sector
(TBtu)
5,688
5,762
5,836
5,909
5,981
6,052
6,123
6,192
6,261
6,329
6,397
6,464
6,530
6,595
6,660
6,724
6,788
7,000
7,205
7,405
7,601
7,791
7,977
8,159
8,337
8,511
8,682
8,850
9,014
9,176
10-37
-------
2015
Gas Price
(2007$/MMBtu)
8.56
8.83
9.10
9.37
9.64
9.90
10.17
10.44
10.71
10.98
11.25
11.51
11.78
12.05
12.32
12.59
12.85
13.12
13.39
13.66
13.93
14.20
14.46
14.73
15.00
Gas Supply to
Electric Sector
(TBtu)
7,435
7,551
7,665
7,777
7,888
7,997
8,105
8,212
8,317
8,421
8,524
8,626
8,726
8,826
8,924
9,022
9,118
9,214
9,308
9,402
9,495
9,587
9,678
9,768
9,859
2020
Gas Price
(2007$/MMBtu)
8.21
8.49
8.78
9.06
9.34
9.63
9.91
10.19
10.47
10.76
11.04
11.32
11.61
11.89
12.17
12.45
12.74
13.02
13.30
13.59
13.87
14.15
14.43
14.72
15.00
Gas Supply to
Electric Sector
(TBtu)
9,335
9,492
9,646
9,798
9,947
10,094
10,240
10,383
10,524
10,664
10,802
10,938
11,073
1 1 ,206
11,337
1 1 ,467
11,596
11,723
11,849
11,973
12,097
12,219
12,340
12,460
12,581
Glossary of Terms Used in this Section
For ease of reference Table 10-12 assembles in one table terms that have been defined in
footnotes throughout this chapter.
Table 10-12 Glossary of Natural Gas Terms Used in Documentation
Term
Definition
Arps-Roberts equation
"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.
Associated gas
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.
Basis
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.
10-38
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Term
Definition
Decline curve
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.
Depleted reservoir
storage
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.
Dry gas
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
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 and interruptible
demand
"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
High deliverability storage is depleted reservoir storage facility or Salt
Cavern storage whose design allows a relatively quick turnover of the
working gas capacity.
Lease and plant use
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.
Liquefied Natural Gas
(LNG)
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
facility
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.
10-39
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Term
Load factor
Natural gas liquid
(NGL)
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
Definition
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 propane and heavier hydrocarbons and are commonly
referred to as lease condensate, natural gasoline, and liquefied
petroleum gases.
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. A field 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 withdrawn from storage as per the rights and
obligations pertaining to a gas storage lease. Analogous to
commodity charges for gas pipeline service
10-40
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Term
Definition
Storage cycle
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.
Unconventional gas
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.
Underground storage
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.
Wet gas
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.
Working gas
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.
10-41
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-------
Appendix 10-1 EPA Base Case v.4.10 with AEO Gas Resource Assumptions
For purposes of comparison a variant of EPA Base Case v.4.10 was prepared with natural gas
resource assumptions that were set to approximate those in the Energy Information
Administration's Annual Energy Outlook 2010.
To set up this case, EPA asked ICF International, who had developed the natural gas module for
EPA Base Case v.4.10, to determine how best to represent the AEO 2010 resource assumptions
in IPM in view of structural differences between the two models. It should be noted that the only
change between the original EPA base case and this variant are the natural gas resource
assumptions. The base year proved reserves assumptions were not changed.1 The following is a
summary of the findings of ICF's comparison and the approach that was implemented in setting
up the AEO 2010 gas resource base case variant.
ICF's analysis of the AEO 2010 natural gas resource assumptions was based on the AEO 2010
assumptions document.2 ICF found that the gas resource base in AEO 2010 is defined as
technically recoverable resources (as of beginning of year 2008) without reference to economic
profitability, whereas the gas resource base in IPM is defined as the economically recoverable
resource (as of end of year 2010) which represents that portion of the original-gas-in-place that is
economic to develop at wellhead prices3 below $14/MMBtu (in 2007 dollars) given current
technologies and industry costs.
ICF made adjustments to convert the AEO technically recoverable gas resources so that it could
be used in the IPM Natural Gas Module. Their analysis found that the economically recoverable
gas resource as defined in the IPM natural gas module was about 15% to 30% lower than the
technically recoverable gas resource without economic consideration as used in AEO 2010.
However, since the resource base for conventional, tight gas, and coalbed methane gas in the
EPA base case was already 15% to 30% lower than the gas resources in the AEO 2010, ICF did
not change the gas resource base for these resource types.
On the other hand, ICF found that the shale gas resource in the EPA base case was much higher
than in AEO 2010. To quantify the difference in shale gas resource, ICF first calculated that a
20% reduction was needed in order both to translate the AEO technically recoverable shale gas
resource into the equivalent economically recoverable resource used in IPM and to account for
resource development between 2008 (base year for the AEO gas resources) and 2011 (base year
for the IPM gas resource). Once the two resource bases were expressed so they could be
compared, ICF found that the AEO shale gas resource assumption was about 31% of that used in
the EPA base case.
To implement this in the alternative base case, the total shale gas resource was set so it would be
31% of the shale gas resource base assumed in EPA Base Case v.4.10. No attempt was made
1 The base year proved reserves assumptions are described in section 10.3 of this chapter under
the header "Use of the HSM resource and reserves data in EPA Base Case using IPM v.4.10
Natural Gas Module."
2 Energy Information Administration, Assumptions to the Annual Energy Outlook 2010: Natural
Gas Transmission and Distribution Module, DOE/EIA-0554(2010), April 9, 2010.
www.eia.doe.gov/oiaf/aeo/assumption/nat gas.html
3 The wellhead price is the price required to cover total wellhead resource costs including capital
expenditures, cost of capital, operating costs, royalties, severance taxes and income taxes.
Wellhead economics are based upon standard discounted cash flow analysis. Costs include
drilling and completion, operating, geological and geophysical (G&G), and lease costs.
Completion costs include hydraulic fracturing, and such costs are based upon cost per fracture
stage and number of fracture stages. Drilling costs, well lateral length, number of fracture stages,
and cost per fracture stage are based on analysis and data from industry.
Appendix 10-1.1
-------
to adjust shale gas resources by supply region so that the regional shale gas resources in AEO
2010 and EPA's AEO Supply Case would match.
Table 10-1.1 shows the resulting shale gas resource base assumptions for AEO 2010, EPA Base
Case v.4.10, and the AEO Supply Case of the EPA base case. The location of the U.S. natural
gas supply regions listed in Table 10-1.1 are shown in the map in Figure 10-1.1.
Table 10-1.1 Shale Gas Resource Base in Tcf (does not include proved reserves)
U.S.
Northeast
Gulf Coast
Mid continent
Southwest
Rocky Mountain
West Coast
Canada
AEO2010(a)
(as of BOY 2008)
346.5
73.2
90.3
51.0
59.5
21.6
50.9
NA
EPA Base Case(b)
(as of EOY2010)
917.2
254.4
431.6
132.9
60.3
37.7
0.3
511.1
AEO Supply Case(b)
(as of EOY 2010)
284.9
79.0
134.1
41.3
18.7
11.7
0.1
158.7
Technically recoverable resources without reference to economic profitability.
Economically recoverable resources under wellhead gas price of$14/MMBtu (2007 dollars).
Figure 10-1.1 U.S. Supply Region
Pacific
Atlantic
Appendix 10-1.2
-------
11 Other Fuels and Fuel Emission Factor Assumptions
Besides coal (chapter 9) and natural gas (chapter 10) EPA Base Case v.4.10 also includes
assumptions for residual 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.4.10. 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 this fuel which currently powers about 45% of U.S. electric generating capacity. 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.4.10.
11.1 Fuel Oil
Two petroleum derived fuels are included in EPA Base Case v.4.10: 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.4.10 are from AEO 2010 and are shown in Table
11-1. They are regionally differentiated according to the NEMS (National Energy Modeling
System) regions used in AEO 2010 and are mapped to their corresponding IPM regions for use in
EPA Base Case v.4.10.
Table 11-1 Fuel Oil Prices by NEMS Region in EPA Base Case v.4.10
Residual
NEMS Region
ECAR
ERGOT
MAAC
MAIN
MAPP
NY
NE
FL
SERC
SPP
NWP
RA
CA
2012
16.40
20.00
9.85
91.20
17.14
9.63
9.80
10.50
10.96
17.36
19.56
19.68
21.63
Fuel Oil Prices (2007$/MMBtu)
2015
30.04
21.96
11.84
104.84
8.61
11.73
11.91
12.48
12.83
21.73
21.58
21.67
23.83
2020
41.07
23.40
13.63
115.87
8.61
13.59
13.77
13.92
14.28
23.15
23.06
23.14
25.10
2030
54.20
25.42
15.65
129.00
8.61
15.61
15.80
15.95
16.32
25.14
25.00
25.09
27.24
2040 - 2050
63.77
26.91
17.05
138.57
16.19
16.99
17.19
17.44
17.81
26.60
26.50
26.59
28.56
Distillate
NEMS Region
ECAR
ERGOT
MAAC
MAIN
MAPP
NY
NE
2012
14.8
14.75
14.82
14.86
14.88
14.87
15.07
Fuel Oil Prices (2007$/MMBtu)
2015
16.96
16.86
16.99
17.04
17.05
17.05
17.23
2020
19.87
19.71
19.9
19.94
19.95
19.98
20.13
2030
22.25
22.09
22.3
22.31
22.32
22.38
22.53
2040 - 2050
24.19
24.03
24.25
24.24
24.25
24.33
24.49
11-1
-------
Distillate
NEMS Region
FL
SERC
SPP
NWP
RA
CA
2012
14.67
14.65
14.8
15.84
15.59
16.21
Fuel Oil Prices (2007$/MMBtu)
2015
16.78
16.8
16.93
17.85
17.73
17.95
2020
19.65
19.69
19.8
20.29
20.6
19.99
2030
22.04
22.08
22.18
22.84
23.02
22.66
2040 - 2050
23.99
24.03
24.12
24.74
24.97
24.53
11.2 Biomass
Biomass is offered as a fuel for existing dedicated biomass power plants and potential (new)
biomass direct fired boilers (built by the model prior to 2020) and to potential (new) biomass
gasification combined cycle units built by the model from 2020 forward. (See chapter 4 for a
presentation of the cost and performance characteristics for these two technologies.) 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.4.10.) As noted in the discussion in chapter 5, the combustion of biomass fuel is
considered to have a net zero impact on atmospheric carbon dioxide levels since the emissions
released are equivalent in carbon content to the carbon absorbed during fuel crop growth1.
EPA Base Case v.4.10 uses biomass supply curves based on those in AEO 2010. There are
fourteen regional biomass fuel supply curves, one for each of the 14 NEMS coal demand regions
represented in AEO 2010. Plants demand biomass from the supply curve corresponding to the
NEMS coal demand region in which they are located. No inter-regional 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. The supply component of the curve
represents the aggregate supply in a region of four types of biomass fuels: forestry residue,
agricultural residue, urban wood waste, and mill residue and energy crops. The price component
of the curve includes transportation cost and represents the delivered fuel cost at the plant gate.
The original AEO 2010 supply curves contained 48 price steps, and are modeled as-is in EPA
Base Case v.4.10. Appendix 11-1 contains the 2012-2035 biomass supply curves.
The supply curves in Appendix 11-1 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 NEMS coal demand region based
on AEO 2010. The total national projection from AEO 2010 was scaled up to the projections
obtained from the Forest and Agricultural Sector Optimization Model (FASOM), a dynamic,
nonlinear programming model of the U.S. forest and agricultural sectors developed for EPA by
Bruce A. McCarl, Professor of Agricultural Economics at Texas A&M University. Table 11-2 shows
the non-electric sector demand by run year and NEMS region.
Table 11-2 Non-Electric Biomass Demand by NEMS Region in EPA Base Case v.4.10
Non-Electric Biomass Demand (TBtu)
NEMS Coal Demand Region
1
2
3
4
CT, MA, ME, NH, Rl, andVT
NY, PA, and NJ
VW, MD, DC, DE, VA, NC, and SC
GA and FL
2012 2015 2020 2030 2040-2050
17.1 15.7
0.0
19.4 126.7 336.1 354.1 324.2
12.7 80.3 201.7 202.4 185.3
1Hughes, E., Role of Renewables in Greenhouse Gas Reduction, Electric Power Research
Institute (EPRI): November, 1998. Report TR-111883, p. 28.
11-2
-------
Non-Electric Biomass
NEMS Coal Demand Region
5
6
7
8
9
10
11
12
13
14
OH
IN, IL, Ml.andWI
KY and TN
AL and MS
MN, IA, ND, SD, NE, MO, and KS
TX, LA, OK, and AR
MT, WY, and ID
CO, UT, and NV
AZ and NM
WA, OR, and CA
2012
~
~
~
131.8
0.9
0.4
0.3
0.3
0.2
Demand
2015
-
184.3
0.3
0.1
0.1
0.1
22.7
(TBtu)
2020
~
~
~
63.8
0.1
0.0
0.0
0.0
506.7
2030
~
~
~
48.0
0.1
13.2
11.8
9.0
467.6
2040 - 2050
0.0
0.0
0.0
0.0
43.9
0.1
12.1
10.8
8.2
428.1
Once the non-electric demand for biomass is factored in, biomass prices in EPA Base Case
v.4.10 are derived endogenously based on the aggregate power sector demand for biomass in
each region. The results are unique market-clearing prices for each supply region. All plants
using biomass from that supply region face the same market-clearing price.
11.3 Nuclear Fuel
The AEO 2009 price assumption for nuclear fuel is used as the nuclear fuel price assumption for
2012-2050 in EPA Base Case v.4.10. The 2012, 2015, 2020, and 2030 prices are 0.71, 0.75,
0.76, and 0.84 Ibs/MMBtu, respectively.
11.4 Waste Fuels
Among the "modeled fuels" shown for existing generating units in the NEEDS, v.4.10 (the
database which serves as the source of data on existing units for EPA Base Case v.4.10) are a
number of waste fuels, including waste coal, petroleum coke, fossil waste, non-fossil waste, tires,
and municipal solid waste (MSW). Table 11-3 describes these fuels, shows their extent of their
representation in NEEDS, and then indicates the assumptions adopted in EPA Base Case v.4.10
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.4.10. 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 is included under coal.
11-3
-------
Table 11-3 Waste Fuels in NEEDS, v.4.10 and EPA Base Case v.4.10
Modeled
Fuel in
NEEDS
Wastp
V V CIO It?
Coal
\U/l_/CII
Petroleum
Coke
Fossil
Waste
Non-Fossil
Waste
Tires
Municipal
Solid
Waste
Number
of Units
in NEEDS
3
29
28
66
3
183
Total
Capacity
in NEEDS
2,205 MW
3,442 MW
982 MW
874 MW
44 MW
2,197MW
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
unconventional 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.doe.gov/glossary/in
dex.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/in
dex.cfm
Supply and Cost
Modeled
By
Supply
Curve
Based
on AEO
2010
Price
Point
Price
Point
Price
Point
Price
Point
Price
Point
Assumed
Price
AEO 2010
$42. 247
MMBtu
0
0
0
0
11-4
-------
11.5 Fuel Emission Factors
Table 11-4 brings together all the fuel emission factor assumptions as implemented in EPA Base
Case v.4.10. For sulfur dioxide 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 detailed treatment of the topic. Nitrogen oxides (NOX) are not included in Table 11-4
because NOX levels are not primarily fuel based but are a factor of the combustion process.
Table 11-4 Fuel Emission Factor Assumptions in EPA Base Case v.4.10
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
Heat Content
(Btu/lb)1
>1 0,260 -13,000
>7,500- 10,260
< 7,500
-
~
~
6,175
14,150
~
~
~
Carbon
Dioxide
(Ibs/MMBtu)2
205.2 - 206.6
212.7-213.1
213.5-217.0
117.08
161.4
161.4-173.9
0
205.7
225.1
321.1
0
189.5
91.9
Sulfur
Dioxide
(Ibs/MMBtu)3
0.67-6.43
0.58-1.41
1.46-3.91
0
0
0.3-2.65
0.08
5.36
7.27
0.08
0
1.65
0.35
Mercury
(Ibs/TBtu)3
1.82-34.71
4.24 - 6.44
7.51 -14.88
0.00014
0.48
0.48
0.57
63.9
23.18
0
0
3.58
71.85
Notes:
1 Distillate and Residual Oils, Biomass, Fossil Waste, Non-Fossil Waste, Tires, and Municipal Solid
Waste (MSW) are priced at a $/MMBtu basis and hence heat content is not required for modeling.
2Also see Table 9-9
3Also see Table 9-6, and Table 9-7
Biomass fuel is considered to have a net zero impact on atmospheric carbon dioxide levels since
the emissions released are equivalent in carbon content to the carbon absorbed during fuel crop
growth. (See, for example, Hughes, E., Role of Renewables in Greenhouse Gas Reduction,
Electric Power Research Institute (EPRI): November, 1998. Report TR-111883, p. 28.)
Biomass Co-firing," Chapter 2 in Renewable Energy Technology Characterizations, U.S.
Department of Energy and Electric Power Research Institute (EPRI), 1997.
Analysis of Emissions Reduction Option for the Electric Power Industry, Office of Air and Radiation,
U.S. Environmental Protection Agency, March 1999.
11-5
-------
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Appendix 11-1 Biomass Supply Curves in EPA Base Case v.4.10
This is a small excerpt of the data in Appendix 11-1. The complete data set in spreadsheet format
can be downloaded via the link found at www.epa.gov/airmarkets/proqsreqs/epa-
ipm/BaseCasev410.html
Year Biomass Supply Region Step Name
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
2012
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
AL, MS
BM01
BM02
BM03
BM04
BM05
BM06
BM07
BM08
BM09
BM010
BM011
BM012
BM013
BM014
BM015
BM016
BM017
BM018
BM019
BM020
BM021
BM022
BM023
BM024
BM025
BM026
BM027
BM028
BM029
BM030
BM031
BM032
BM033
BM034
BM035
BM036
BM037
BM038
BM039
BM040
Cost of
Production
(2007$/MMBtu)
0.00
1.83
2.12
2.39
2.68
2.97
3.26
3.54
3.83
4.11
4.40
4.68
4.97
5.26
5.54
5.82
6.11
6.40
6.82
7.24
7.66
8.07
8.49
8.91
9.33
9.76
10.18
10.60
11.02
11.44
11.86
12.28
12.70
13.12
13.54
13.97
14.38
14.80
15.22
15.64
Biomass
Production
(TBtu/Year)
0
21.28
21.04
19.44
13.27
10.35
7.33
78
2.95
1.22
0.2
0
0
0
0
0
0
0
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
5
Appendix 11-1
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