Economic Impact Analysis of the Stationary
Combustion Turbines NSPS: Final Report
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EPA-452/R-06-001
February 2006
ECONOMIC IMPACT ANALYSIS (EIA) FOR THE STATIONARY COMBUSTION
TURBINES NSPS
U.S. Environmental Protection Agency
Office of Air Quality Planning and Standards
Health and Environmental Impacts Division
Air Benefits and Costs Group
Research Triangle Park, NC
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TABLE OF CONTENTS
Section Page
1 Introduction 1-1
1.1 Agency Requirements for an EIA 1-1
1.2 Scope and Purpose 1-2
1.3 Organization of the Report 1-2
2 Combustion Turbine Technologies and Costs 2-1
2.1 Simple-Cycle Combustion Turbine Technologies 2-1
2.2 Combined-Cycle Combustion Turbines Technologies 2-2
2.3 Capital and Installation Costs 2-4
2.4 O&M Costs Including Fuel 2-4
3 Background on Health Affects and Regulatory Alternatives 3-1
3.1 Background 3-1
iii
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3.1.1 Summary of Stationary Combustion Turbines
NSPS 3-1
3.2 Health Effects Associated with NOX and SO2 Emissions from
Stationary Combustion Turbines 3-7
3.2.1 Benefits of Reduced Nitrous Oxide Emissions 3-7
3.2.2 Benefits of Sulfur Dioxide Reductions 3-9
3.3 Emission Reductions from the NSPS 3-9
4 Projection of Units and Facilities in Affected Sectors 4-1
4.1 Profile of Existing Combustion Turbine Units 4-1
4.1.1 Distribution of Units and Facilities by Industry 4-1
4.1.2 Technical Characteristics 4-1
4.2 Projected Growth of Combustion Turbines 4-5
4.3 Projected Number of Affected Stationary Combustion Turbines 4-5
5 Profile of the Electric Utility Industry 5-1
5.1 Electric Utility Industry (NAICS 22111) 5-1
5.1.1 Market Structure of the Electric Power Industry 5-1
5.1.1.1 The Evolution of the Electric Power Industry 5-1
5.1.1.2 Structure of the Traditional Regulated Utility 5-3
5.1.1.3 Current Electric Power Supply Chain 5-5
5.1.1.4 Overview of Deregulation and the Potential Future
Structure of the Electricity Market 5-13
iv
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5.1.2 Electricity Generation 5-15
5.1.2.1 Growth in Generation Capacity 5-17
5.1.3 Electricity Consumption 5-19
Economic Analysis Methods 6-1
6.1 Agency Requirements for Conducting an EIA 6-1
6.2 Overview of Economic Modeling Approaches 6-2
6.2.1 Modeling Dimension 1: Scope of Economic
Decisionmaking 6-2
6.2.2 Modeling Dimension 2: Interaction Between Economic
Sectors 6-3
6.3 Selected Modeling Approach Used for Combustion Turbine
Analysis 6-4
6.3.1 Electricity Markets 6-7
6.3.2 Other Energy Markets 6-7
6.3.3 Supply and Demand Elasticities for Energy Markets 6-8
6.3.4 Final Product and Service Markets 6-11
6.3.4.1 Modeling the Impact on the Industrial and
Commercial Sectors 6-11
6.3.4.2 Impact on the Residential Sector and
Transportation Sectors 6-13
6.3.4.3 Impact on the Government Sector 6-13
6.4 Summary of the Economic Impact Model 6-13
6.4.1 Estimating Changes in Social Welfare 6-16
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7 Economic Impact Analysis 7-1
7.1 Engineering Control Cost Inputs 7-1
7.1.1 Computing Supply Shifts in the Electricity Market 7-1
7.2 Market-Level Results 7-2
7.3 Social Cost Estimates 7-6
7.4 Energy Impact Analysis 7-8
8 Small Entity Impacts 8-1
8.1 Identifying Small Businesses 8-2
8.2 Screening-Level Analysis 8-2
8.3 Assessment 8-2
References R-l
Appendix A Overview of the Market Model A-l
Appendix B Assumptions and Sensitivity Analysis B-l
VI
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LIST OF FIGURES
Number Page
2-1 Simple-Cycle Gas Turbine 2-2
2-2 Combined-Cycle Gas Turbine 2-3
4-1 Number of Units by MW Capacity 4-3
4-2 Number of Units by Annual MWh Output Equivalent 4-4
5-1 Traditional Electric Power Industry Structure 5-4
5-2 Electric Utility Industry 5-7
5-3 Utility and Nonutility Generation and Shares by Class, 1988 and 1998 5-9
5-4 Annual Electricity Sales by Sector 5-19
6-1 Links Between Energy and Final Product Markets 6-6
6-2 Electricity Market 6-8
6-3 Potential Market Effects of the NSPS on Petroleum, Natural Gas, or Coal . . . 6-9
6-4 Fuel Market Interactions with Facility-Level Production Decisions 6-12
6-5 Operationalizing the Estimation of Economic Impact 6-15
6-6 Changes in Economic Welfare with Regulation 6-17
7-1 Market for Baseload Electricity 7-4
Vll
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LIST OF TABLES
Number Page
2-1 Comparison of Emissions from Coal-Fired and Simple-Cycle Turbines and
Combined-Cycle Turbines 2-4
2-2 Overall Installation Costs 2-5
2-3 Comparison of Percentage of Costs 2-5
4-1 Facilities With Units Having Capacities Above 1 MW by Industry
Grouping and Government Sector 4-2
4-2 Stationary Combustion Turbine Projections 4-4
5-1 Total Expenditures in 1996 ($103) 5-6
5-2 Number of Electricity Suppliers in 1999 5-8
5-3 Top Power Marketing Companies, First Quarter 1999 5-12
5-4 Industry Capability by Energy Source, 2000 5-16
5-5 Installed Capacity at U.S. Nonutility Attributed to Major Industry Groups
and Census Division, 1995 through 1999 (MW) 5-16
5-6 Existing Capacity at U.S. Electric Utilities by Prime Mover and Energy
Source, as of January 1, 1998 5-18
5-7 Key Parameters in the Cases 5-20
5-8 Capacity Additions and Retirements at U. S. Electric Utilities by Energy
Source, 1997 5-21
5-9 Fossil-Fueled Existing Capacity and Planned Capacity Additions at
U.S. Electric Utilities by Prime Mover and Primary Energy Source,
as of January 1, 1998 5-22
5-10 U.S. Electric Utility Retail Sales of Electricity by Sector, 1989 Through
viii
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July 1999 (Million kWh) 5-23
6-1 Comparison of Modeling Approaches 6-3
6-2 Supply and Demand Elasticities 6-10
6-3 Fuel Price Elasticities 6-10
6-4 Supply and Demand Elasticities for Industrial and Commercial Sectors 6-14
7-1 Total Capital and Annual Cost of the NSPS in the Fifth Year 7-2
7-2 Summary of Turbine Cost Information and Supply Shifts 7-3
7-3 Market-Level Impacts of Stationary Combustion Turbines NSPS: 2010 .... 7-5
7-4 Changes in Market Shares for Electricity Suppliers 7-6
7-5 Distribution of Social Costs of Stationary Combustion Turbines NSPS: 2010 . 7-7
rx
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SELECT LIST OF ACRONYMS AND ABBREVIATIONS
CAA: Clean Air Act
CO: Carbon Monoxide
COPD: Chronic Obstructive Pulmonary Disease
CCCT: Combined-Cycle Combustion Turbine
C/S: Cost to Sales Ratio
DOE: Department o f Energy
EO: Executive Order
EPA: Environmental Protection Agency
EWG: Exempt Wholesale Generators
GW: Gigawatt
HAP: Hazardous Air Pollutant
ICCR: Industrial Combustion Coordinated Rulemaking
IPP: Independent Power Producer
kWh: Kilowatt Hour
Ib: Pound
mills/kWh: Mills per Kilowatt Hour
mmBTU: Millions of British Thermal Units
MACT: Maximum Achievable Control Technology
MW: Megawatts
Mwh: Megawatt Hours
NAAQS: National Ambient Air Quality Standards
NAICS: North American Industrial Classification System
NESHAP: National Emission Standards for Hazardous Air Pollutants
NPR: No tice o f Pro po sed Rulemaking
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NSPS: New Source Performance Standards
NSR: New Source Review
OMB: Office of Management and Budget
O&M: Operation and Maintenance
P/E: Partial Equilibrium
PM: Particulate Matter
ppbdv: Parts Per Billion, dry volume
ppm: Parts Per Million
PRA: Paperwork Reduction Act of 1995
RFA: Regulatory Flexibility Act
SAB: Science Advisory Board
SBA: Small Business Administration
SBREFA: Small Business Regulatory Enforcement Fairness Act of 1996
SCCT: Simple-Cycle Combustion Turbine
SIC: Standard Industrial Classification
SO A: Secondary Organic Aerosols
TAC: Total Annual Cost
tpd: Tons Per Day
tpy: Tons Per Year
UMRA: Unfimded Mandates Reform Act
VOCs: Volatile Organic Compounds
XI
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SECTION 1
INTRODUCTION
The U.S. Environmental Protection Agency (referred to as EPA or the Agency)
is developing regulations under Section 111 of the Clean Air Act (CAA) for new stationary
combustion turbines. The majority of stationary combustion turbines burn natural gas and
are used in the electric power and natural gas industries. The regulations are designed to
reduce emissions of nitrogen oxides (NOX) and sulfur dioxide (SO2) generated by the
combustion of fossil fuels in new combustion turbines. To inform this rulemaking, the Air
Benefits and Costs Group (ABCG) of EPA's Office of Air Quality Planning and Standards
(OAQPS) has developed an economic impact analysis (EIA) to estimate the potential social
costs of the regulation. This report presents the results of this analysis in which a market
model was used to analyze the impacts of the air pollution rule on society.
1.1 Agency Requirements for an EIA
Congress and the Executive Office have imposed statutory and administrative
requirements for conducting economic analyses to accompany regulatory actions. Section
317 of the CAA specifically requires estimation of the cost and economic impacts for
specific regulations and standards proposed under the authority of the Act. In addition,
Executive Order (EO) 12866 requires a more comprehensive analysis of benefits and costs
for significant regulatory actions.1 Other statutory and administrative requirements include
examination of the composition and distribution of benefits and costs. For example, the
Regulatory Flexibility Act (RFA), as amended by the Small Business Regulatory
Enforcement and Fairness Act of 1996 (SBREFA), requires EPA to consider the economic
impacts of regulatory actions on small entities. Also, Executive Order 13211 requires EPA to
consider for particular rules the impacts on energy markets.
1.2 Scope and Purpose
The CAA's purpose is to protect and enhance the quality of the nation's air
resources (Section 101(b)). Section 111 of the CAA establishes the authority of EPA to set
new source performance standards (NSPS) for criteria pollutants. This report evaluates the
economic impacts of pollution control requirements placed on stationary combustion
turbines under these amendments. These control requirements are designed to reduce
releases of NOX and SO2 from new sources into the atmosphere.
The regulation affects new stationary combustion turbines over 1 megawatt
(MW). To estimate the economic impacts associated with the regulation, new stationary
combustion turbines are projected through the fifth year after promulgation.
'Office of Management and Budget (OMB) guidance under EO 12866 stipulates that a full benefit-cost analysis
is required only when the regulatory action has an annual effect on the economy of $100 million or more.
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1.3 Organization of the Report
The remainder of this report is divided into six sections that describe the
methodology and present results of this analysis:
• Section 2 provides background information on combustion turbine technologies
and compares the equipment, installation, and operating costs of simple-cycle
combustion turbines (SCCTs) and combined-cycle combustion turbines (CCCTs).
• Section 3 provides background information on the regulatory alternatives
examined, information on the emission reductions associated with the rule, and
health effects from exposure to the NOX emitted by combustion turbines.
• Section 4 provides projections of new stationary combustion turbines through the
fifth year after promulgation. This section also profiles the population of existing
turbines.
• Section 5 profiles the electric service industry (NAICS 221).
• Section 6 presents the methodology for assessing the economic impacts of the
NSPS and describes the computerized market model used to estimate the social
cost impacts and to disaggregate impacts into changes in producer and consumer
surplus.
• Section 7 presents the economic impact estimates for the NSPS . This section
also discusses the regulation's impact on energy supply, distribution, and use.
• Section 8 provides the Agency's analysis of the regulation's impact on small
entities.
In addition to these sections, Appendix A details the market model approach used to predict
the economic impacts of the NSPS. Appendix B describes the limitations of the data and
market model and presents sensitivity analyses associated with key assumptions.
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SECTION 2
COMBUSTION TURBINE TECHNOLOGIES AND COSTS
This section provides background information on combustion turbine
technologies. Included is a discussion of simple-cycle combustion turbines (SCCTs) and
combined-cycle combustion turbines (CCCTs), along with a comparison of fuel efficiency
and capital costs between the two classes of turbines.
2.1 Simple-Cycle Combustion Turbine Technologies
Most stationary combustion turbines use natural gas to generate shaft power
that is converted into electricity.2 Combustion turbines have four basic components, as
shown in Figure 2-1.
1. The compressor raises the air pressure up to thirty times atmospheric.
2. A fuel compressor is used to pressurize the fuel.
3. The compressed air is heated in the combustion chamber at which point fuel is
added and ignited.
4. The hot, high pressure gases are then expanded through a power turbine,
producing shaft power, which is used to drive the air and fluid compressors and a
generator or other mechanical drive device. Approximately one-third of the
power developed by the power turbine can be required by the compressors.
Electric utilities primarily use simple-cycle combustion turbines as peaking or backup units.
Their relatively low capital costs and quick start-up capabilities make them ideal for partial
operation to generate power at periods of high demand or to provide ancillary services, such
as spinning reserves or black-start back-up capacity.3 The disadvantage of simple-cycle
2Combustion turbine technology used for aircraft engines is virtually the same except the energy is used to
generate thrust.
'Spinning reserves are unloaded generating capacity that is synchronized to the grid that can begin to respond
immediately to correct for generation/load imbalances caused by generation and transmission outages and
that is fully available within 10 minutes. Black-start capacity refers to generating capacity that can be made
fully available within 30 to 60 minutes to back up operating reserves and for commercial purposes.
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Gas Turtiines
Fuel
Fuel Compressor
Combustion
Chamber
(D
(Li
Q.
E
o
O
QJ
a
Turbine Shaft
Work
Output
Exhaust
Figure 2-1. Simple-Cycle Gas Turbine
Source: Hay, Nelson E., ed. 1988. Guide to Natural Gas Cogeneration. Lilburn, GA: The Fairmont Press,
Inc.
systems is that they are relatively inefficient, thus making them less attractive as base load
generating units.
2.2
Combined-Cycle Combustion Turbines Technologies
The combined-cycle system incorporates two simple-cycle systems into one
generation unit to maximize energy efficiency. Energy is produced in the first cycle using a
gas turbine; then the heat that remains is used to create steam, which is run through a steam
turbine. Thus, two single units, gas and steam, are put together to minimize lost potential
energy.
The second cycle is a steam turbine. In a CCCT, the waste heat remaining from
the gas turbine cycle is used in a boiler to produce steam. The steam is then put through a
steam turbine, producing power. The remaining steam is recondensed and either returned to
the boiler where it is sent through the process again or sold to a nearby industrial site to be
used in a production process. Figure 2-2 shows a gas-fired CCCT.
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Emissions
Combustion Gases
300-400 °F
Combined Cycle
Steam Generator
Combustion Gases
900-1000 °F
Steam
Steam Turbine
Shaft
Electric
Generator
GasTurbine
Fuel Air
Figure 2-2. Combined-Cycle Gas Turbine
Source: Siemens Westinghouse. August 31, 1999. Presentation.
There are significant efficiency gains in using a combined-cycle turbine
compared to simple-cycle systems. With SCCTs, adding a second stage allows for heat that
otherwise would have been emitted and completely wasted to be used to create additional
power or steam for industrial purposes. For example, a SCCT with an efficiency of 38.5
percent, adding a second stage increases the efficiency to 58 percent, a 20 percent increase in
efficiency (Siemens, 1999). General Electric (1999) has recently developed a 480 MW
system that will operate at 60 percent net combined-cycle efficiency.
In addition to energy efficiency gains, CCCTs also offer environmental
efficiency gains compared to existing coal plants. In addition, efficiency gains associated
with the CCCT lead to lower emissions compared to SCCTs. As Table 2-1 shows, the 58
percent efficiency turbine decreases NOX emissions by 14 percent over simple-cycle
combustion turbines and 89 percent over existing coal electricity generation plants. In
addition, CO2 emissions will be 5 percent lower than emissions from SCCTs and 64 percent
lower than existing coal plants.
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Table 2-1. Comparison of Emissions from Coal-Fired and Simple-Cycle Turbines and
Combined-Cycle Turbines
C02
(lb/MW-hr) (Ib/MW-hr)
Coal electricity generation 5.7 2,190
Simple-cycle turbines 0.7 825
Combined- cycle turbines 0.6 780
Source: Siemens Westinghouse. August 31, 1999. Presentation.
2.3 Capital and Installation Costs
CCCT capital and installation costs are approximately 30 percent less ($/MW)
than a conventional coal or oil steam power plant's capital and installation costs, and CCCT
costs are likely to decrease over the next 10 years. Gas turbine combined-cycle plants range
from approximately $300 per kW installed for very large utility-scale plants to $1,000 per
kW ($1998) for small industrial cogeneration installation (GTW Handbook, 1999). However,
the prices of construction can vary as a result of local labor market conditions and the
geographic conditions of the site (GTW Handbook, 1999). SCCTs are approximately half the
cost of CCCT units.
Table 2-2 breaks down the budgeted construction costs of a gas-fired 107 MW
combined-cycle cogenerating station at John F. Kennedy International Airport that was
installed several years ago. As shown in Table 2-2, the construction price can range
dramatically. This job finished near the top of the budget, close to $133,600,000. According
to Gas Turbine World, the typical budget price for a 168 MW plant is $80,600,000,
($480/kW) for a plant with net efficiency of 50.9 percent (GTW Handbook, 1999).
2.4 O&M Costs Including Fuel
Fuel accounts for one-half to two-thirds of total production costs (annualized
capital, operation and maintenance, fuel costs) associated with generating power using
combustion turbines. Table 2-3 compares the percentage of costs spent on annualized
capital, operation and maintenance, and fuel for both simple turbines and CCCTs.
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Table 2-2. Overall Installation Costs
Construction costs can vary dramatically. This table shows the budgeted cost for a gas-fired
107 MW combined-cycle cogenerating station at John F. Kennedy International Airport in
Brooklyn, New York. The power plant uses two 40 MW Stewart & Stevenson LM6000 gas
turbine generators each exhausting into a triple pressure heat recovery steam generator raising
steam for processes and to power a nominal 27 MW steam turbine generator. Budgeted prices are
in 1995-1996 U.S. dollars.
Budget Equipment Pricing $ Amount
Gas turbine generators $24,000,000
Heat recovery steam generators 10,000,000
Steam turbine generator set 4,000,000
Condenser 300,000
Cooling towers 800,000
Transformer and switchgear 8,000,000
Balance of plant equipment 7,500,000
Subtotal, equipment $54,600,000
Budget Services and Labor
Mechanical and electrical construction $20-75,000,000
Engineering 4,000,000
Subtotal, services $24-79,000,000
Total Capital Cost $78,600,000-133,600,000
Source: 1998-99 GTWHandbook. "Turnkey Combined Cycle Plant Budget Price Levels." Fairfield, CT:
Pequot Pub. Pgs. 16-26.
Table 2-3. Comparison of Percentage of Costs"
Simple Cycle Combined Cycle
% Capital costs 50 25
% Operation and maintenance 10 10
% Fuel 40 65
Based on a review of marketing information from turbine manufacturers and the GTW Handbook.
The fuel costs may vary depending on the plant's location. In areas where gas
costs are high, for a base-load CCCT power plant, fuel costs can account for up to 70 percent
of total plant costs—including acquisition, owning and operating costs, and debt service
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(GTW Handbook, 1999). General Electric's "H" design goals for future CCCT systems are
to reduce power plant operating costs by at least 10 percent compared to today's technology
as a direct result of using less fuel. The higher efficiency allows more power to be generated
with the same amount of fuel, resulting in a substantial fuel cost savings for the plant owner
(General Electric, 1999).
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SECTION 3
BACKGROUND ON HEALTH AFFECTS AND REGULATORY ALTERNATIVES
3.1 Background
Section 111 of the CAA requires EPA to establish NSPS for major and area
sources within various source categories.
3.1.1 Summary of the Stationary Combustion Turbines NSPS
Does the rule apply to me?
The standards would apply to new stationary combustion turbines with a heat
input at peak load greater than or equal to 10.7 GJ (10 MMBtu) per hour that commerce
construction, modification, or reconstruction after February 18, 2005. The applicability of
the rule is similar to that of existing 40 CFR part 60, subpart GG, except that the rule would
apply to new, modified, and reconstructed stationary combustion turbines, and their
associated heat recovery steam generators (HRSG) and duct burners. A new stationary
combustion turbine is defined as all equipment, including but not limited to the combustion
turbine, the fuel, air, lubrication and exhaust gas systems, control systems (except emissions
control equipment), heat recovery system, and any ancillary components and sub-
components comprising any simple cycle stationary combustion turbine, any
regenerative/recuperative cycle stationary combustion turbine, any combined cycle
combustion turbine, and any combined heat and power combustion turbine based system.
The new stationary combustion turbines subject to the standards are exempt from the
requirements of 40 CFR part 60, subpart GG. Heat recovery steam generators and duct
burners subject to subpart KKKK are exempt from the requirements of 40 CFR part 60,
subparts Da, Db, and DC.
What pollutants would be regulated?
The pollutants to be regulated by the standards are NOx and SO2.
What is the affected source?
The affected source for the stationary combustion turbine NSPS is each
stationary combustion turbine with a power output at peak load greater than or equal to 1
MW, that commences construction, modification, or reconstruction after proposal.
Integrated gasification combined cycle (IGCC) combustion turbine facilities covered by
subpart Da of 40 CFR part 60 (the Utility NSPS) are exempt from the requirements of the
rule.
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What emission limits must I meet?
The format of the standards for NO is allow the turbine owner or operator the
choice of a concentration-based or an output-based emission limit. The concentration-based
limit is in units of parts per million by volume (ppmv) at 15 percent oxygen. The output-
based emission limit is in in units of emissions mass per unit useful recovered energy,
nanograms/Joule (ng/J) or pounds per megawatt-hour (Ib/MW-hr). The Nox limits differ
based on the fuel input at peak load, fuel, application, and location of the turbine. The fuel
input of the turbine does not include any supplemental fuel input to the heat recovery system
and refers to the rating of the combustion turbine itself. The 50 mmBTU/hr category peak
heat input is based on the fuel input to a 23 percent efficient 3.5 MW combustion turbine.
The 850 mmBTU/hr category peak heat input is based on the fuel input to a 44 percent
efficient 110 MW combustion turbine. The 30 MW category for turbines located north of
the Arctic Circle, turbines operating at less than 75 percent of peak load, modified and
reconstructed offshore turbines, and turbines operating at temperatures less than 0 degress
Fahrenheit is based on the categories in the original NSPS for combustion turbines, subpart
GG. These are presented in Table 3-1.
Table 3-1. NO Emission Standards (ng/J)
Combustion Turbine Type
Combustion Turbine Heat Input
at Peak Load (HHV)
NOx Emission
Standard
New turbine firing natural
gas, electric generating
<= 50 mmBTU/hr
42ppmat 15
percent oxygen (02)
or 290 ng/J of useful
output (2.3 Ib/MWh)
New turbine firing natural
gas, mechanical drive
<= 50 mmBTU/hr
100 ppm at 15
percent O2 or 690
ng/J of useful output
(5.5 Ib/MWh)
New turbine firing natural gas
> 50 mmBTU/hr and <=850
mmBTU/hr
25 ppm at 15
percent oxygen (02)
or 150 ng/J of useful
output (0.43
Ib/MWh)
New turbine firing fuels other
than natural gas, electric
generating
<= 50 mmBTU/hr
96 ppm at 15
percent oxygen (02)
or 700 ng/J of useful
output (2.3 Ib/MWh)
3-2
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New turbine firing fuels other
than natural gas, mechanical
drive
<= 50 MMBTU/hr
150 ppm at 15
percent oxygen (02)
or 1,100 ng/J of
useful output (8.7
Ib/MWh)
New turbine firing fuels other
than natural gas
> 50 mmBTU/hr and <=850
mmBTU/hr
74ppmat 15
percent oxygen (02)
or 460 ng/J of useful
output (2.3 Ib/MWh)
New turbine firing natural
gas, electric generating
<= 50 mmBTU/hr
42ppmat 15
percent oxygen (02)
or 290 ng/J of useful
output (2.3 Ib/MWh)
New, modified, or
reconstructed turbine firing
fuels other than natural gas
> 850 mmBTU/hr
42ppmat 15
percent oxygen (02)
or 160 ng/J of useful
output (1.3 Ib/MWh)
Modified or reconstructed
turbines
<= 50 mmBTU/hr
150 ppm at 15
percent oxygen (02)
or 1,100 ng/J of
useful output (8.7
Ib/MWh)
Modified or reconstructed
turbine firing natural gas
> 50 mmBTU/hr and <= 850
mmBTU/hr
42ppmat 15
percent oxygen (02)
or 250 ng/J of useful
output (2.0 Ib/MWh)
Modified or reconstructed
turbine firing fuels other than
natural gas
>50 mmBTU/hr and <= 850
mmBTU/hr
96 ppm at 15
percent oxygen
or 590 ng/J of useful
output (4.7 Ib/MWh)
Turbines located north of the
Arctic Circle (latitude 66.5
north), turbines operating at
less than 75 percent of peak
load, modified and
reconstructed offshore
turbines, and turbines
operating at temperatures less
than 0 degree Fahrenheit
<= 30 MW output
150 ppm at 15
percent oxygen (02)
or 1,100 ng/J of
useful output (8.7
Ib/MWh)
3-3
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Turbines located north of the
Arctic Circle (latitude 66.5
north), turbines operating at
less than 75 percent of peak
load, modified and
reconstructed offshore
turbines, and turbines
operating at temperatures less
than 0 degree Fahrenheit
Heat recovery units operating
independent of the
combustion turbine
> 30 MW output
All sizes
96 ppm at 15
percent O2 or 590
ng/J of useful output
(4.7 Ib/MW-hr)
54 ppm at 15
percent O2 or 110
ng/J of useful output
(0.86 Ib/MW-hr)
We have determined that it is appropriate to exempt emergency combustion
turbines from the NO limit. We have defined these units as turbines that operate in
emergency situations. For example, turbines used to supply electric power when the local
utility service is interrupted are considered to fall under this definition. In addition, we are
proposing that combustion turbines used by manufacturers in research and development of
equipment for both combustion turbine emission control techniques and combustion turbine
efficiency improvements be exempted from the NOX limit. Given the small number of
turbines that are expected to fall under this category and since there is not one definition that
can provide an all-inclusive description of the type of research and development work that
qualifies for the exemption from the NOx limit, we have decided that it is appropriate to
make these exemption determinations on case by case basis only.
The proposed standard for SO2 is the same for all turbines regardless of size
and fuel type. You may not cause to be discharged into the atmosphere from the subject
stationary combustion turbine any gases which contain SO^ in excess of 110 ng/J (0.90
Ib/MW-hr) gross energy output for turbines located in continental areas, and 780 ng/J (6.2
Ib/MW-hr) gross energy output for turbines located elsewhere. You can choose to comply
with the SC>2 limit itself or with a limit on the sulfur content of the fuel. The fuel sulfur
content is 26 ng SO2/J (0.060 Ib SO2/mmBTU) heat input for turbines in continental areas
and 180 ng SO2/J (0.42 Ib SO2/mmBTU) heat input for turbines in noncontinental areas.
If I modify or reconstruct my existing, turbine, does the rule apply to me?
The standards apply to stationary combustion turbines that are modified or
reconstructed after proposal. The guidelines for determining whether a source is modified or
reconstructed are given in 40 CFR 60.14 and 60.15, respectively. A turbine that is overhauled
as part of a maintenance program is not considered a modification if there is no increase in
emissions.
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How do I demonstrate compliance?
In order to demonstrate compliance with the NO limit, an initial performance
test is required. If you are using water or steam injection, you must continuously monitor
your water or steam to fuel ratio in order to demonstrate compliance and you are not required
to perform annual stack testing to demonstrate compliance. If you are not using water or
steam injection, you would conduct performance tests annually following the initial
performance test in order to demonstrate compliance. Alternatively, you may choose to
demonstrate continuous compliance with the use of a continuous emission monitoring system
(CEMS) or parametric monitoring; if you choose this option, you are not required to conduct
subsequent annual performance tests.
If you are using a NO CEMS, the initial performance test required under 40
CFR 60.8 may, alternatively, coincide with the relative accuracy test audit (RATA). If you
choose this as your initial performance test, you must perform a minimum of nine reference
method runs, with a minimum time per run of 21 minutes, at a single load level, between 90
and 100 percent of peak (or the highest achievable) load. You must use the test data both to
demonstrate compliance with the applicable NOX emission limit and to provide the required
reference method data for the RATA of the CEMS.
What monitoring requirements must I meet?
If you are using water or steam injection to control NOX emissions, you must
install and operate a continuous monitoring system to monitor and record the fuel
consumption and the ratio of water or steam to fuel being fired in the turbine. Alternatively,
you could use a CEMS consisting of NOX and oxygen (02) or carbon dioxide (CO2)
monitors. During each full unit operating hour, each monitor would complete a minimum of
one cycle of operation for each 15-minute quadrant of the hour. For partial unit operating
hours, at least one valid data point would be obtained for each quadrant of the hour in which
the unit operates.
If you operate any new turbine which does not use water or steam injection to
control NOX emissions, you would have to perform annual stack testing to demonstrate
continuous compliance with the NOX limit. Alternatively, you could elect either to use a
NOX CEMS or perform continuous parameter monitoring as follows:
(1) For a diffusion flame turbine without add-on selective catalytic reduction
(SCR) controls, you would define at least four parameters indicative of the unit's NO
formation characteristics, and you would monitor these parameters continuously.
(2) For any lean premix stationary combustion turbine, you would continuously
monitor the appropriate parameters to determine whether the unit is operating in the lean
premixed combustion mode.
(3) For any turbine that uses SCR to reduce NOX emissions, you would
continuously monitor appropriate parameters to verify the proper operation of the emission
controls.
3-5
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(4) For affected units that are also regulated under part 75 of this chapter, if
you elect to monitor the NOX emission rate using the methodology in appendix E to part 75
of this chapter, or the low mass emissions methodology in 40 CFR 75. 19, the monitoring
requirements of the turbine NSPS may be met by performing the parametric monitoring
described in section 2.3 of appendix E of part 75 of this chapter or in 40 CFR
Alternatively, you could petition the Administrator for other acceptable
methods of monitoring your emissions. If you choose to use a CEMS or perform parameter
monitoring to demonstrate continuous compliance, annual stack testing is not required.
If you operate any stationary combustion turbine subject to the provisions of the
rule, and you choose not to comply with the SO^ stack limit, you would monitor the total
sulfur content of the fuel being fired in the turbine. There are several options for determining
the frequency of fuel sampling, consistent with appendix D to part 75 of this chapter for fuel
oil; and the sulfur content would be determined and recorded once per unit operating day for
gaseous fuel, unless a custom fuel sampling schedule is used. Alternatively, you could elect
not to monitor the total sulfur content of the fuel combusted in the turbine, if you
demonstrate that the fuel does not to exceed a total sulfur content of 300 ppmw. This
demonstration may be performed by using the fuel quality characteristics in a current, valid
purchase contract, tariff sheet, or transportation contract, or through representative fuel
sampling data which show that the sulfur content of the fuel does not exceed 300 ppmw.
If you choose to monitor combustion parameters or parameters indicative of
proper operation of NOX emission controls, the appropriate parameters would be
continuously monitored and recorded during each run of the initial performance test, to
establish acceptable operating ranges, for purposes of the parameter monitoring plan for the
affected unit.
If you are required to periodically determine the sulfur content of the fuel
combusted in the turbine, a minimum of three fuel samples would be collected during the
performance test. For liquid fuels, the samples for the total sulfur content of the fuel must be
analyzed using American Society of Testing and Materials (ASTM) methods D129-00,
D2622-98, D4294-02, D1266-98, D5453-00 or D 1552-01. For gaseous fuels, ASTM
D1072-90 (Reapproved 1999); D3246-96; D4468-85 (Reapproved 2000); or D6667-01 must
be used to analyze the total sulfur content of the fuel.
The applicable ranges of some ASTM methods mentioned above are not
adequate to measure the levels of sulfur in some fuel gases. Dilution of samples before
analysis (with verification of the dilution ratio) may be used, subject to the approval of the
Administrator.
What reports must I submit?
For each affected unit for which you continuously monitor parameters or
emissions, or periodically determine the fuel sulfur content under the rule, you would submit
reports of excess emissions and monitor downtime, in accordance with 40 CFR 60.7(c). For
simple cycle turbines, excess emissions must be reported for all 4-hour rolling average
3-6
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periods of unit operation, including startup, shutdown, and malfunctions where emissions
exceed the allowable emission limit or where one or more of the monitored process or
control parameters exceeds the acceptable range as determined in the monitoring plan.
Combined cycle and combined heat and power units use a 30 day rolling average to
determine excess emissions.
For each affected unit for which you perform an annual performance test, you
must submit an annual written report of the results of each performance test.
3.2 Health Effects Associated with NOX and SO2 Emissions from Stationary
Combustion Turbines
3.2.1 Benefits of Reduced Nitrous Oxide Emissions
Emissions of NOX produce a wide variety of health and welfare effects.
Nitrogen dioxide can irritate the lungs at high occupational levels and may lower resistance
to respiratory infection (such as influenza), although the research has been equivocal. NOX
emissions are an important precursor to acid rain and may affect both terrestrial and aquatic
ecosystems. Atmospheric deposition of nitrogen leads to excess nutrient enrichment
problems ("eutrophication") in the Chesapeake Bay and several nationally important
estuaries along the East and Gulf Coasts. Eutrophication can produce multiple adverse
effects on water quality and the aquatic environment, including increased algal blooms,
excessive phytoplankton growth, and low or no dissolved oxygen in bottom waters.
Eutrophication also reduces sunlight, causing losses in submerged aquatic vegetation critical
for healthy estuarine ecosystems. Deposition of nitrogen-containing compounds also affects
terrestrial ecosystems. Nitrogen fertilization can alter growth patterns and change the
balance of species in an ecosystem.
Nitrogen dioxide and airborne nitrate also contribute to pollutant haze (often
brown in color), which impairs visibility and can reduce residential property values and the
value placed on scenic views.
NOX in combination with volatile organic compounds (VOC) also serves as a
precursor to ozone. Based on a large number of recent studies, EPA has identified several
key health effects that maybe associated with exposure to elevated levels of ozone.
Exposures to high ambient ozone concentrations have been linked to increased hospital
admissions and emergency room visits for respiratory problems. Repeated exposure to
ozone may increase susceptibility to respiratory infection and lung inflammation and can
aggravate preexisting respiratory disease, such as asthma. Repeated prolonged exposures
(i.e., 6 to 8 hours) to ozone at levels between 0.08 and 0.12 ppb, over months to years may
lead to repeated inflammation of the lung, impairment of lung defense mechanisms, and
irreversible changes in lung structure, which could in turn lead to premature aging of the
lungs and/or chronic respiratory illnesses such as emphysema, chronic bronchitis, and
asthma.
3-7
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Children have the highest exposures to ozone because they typically are active
outside playing and exercising, during the summer when ozone levels are highest. Further,
children are more at risk than adults from the effects of ozone exposure because their
respiratory systems are still developing. Adults who are outdoors and moderately active
during the summer months, such as construction workers and other outdoor workers, also are
among those with the highest exposures. These individuals, as well as people with
respiratory illnesses such as asthma, especially children with asthma, experience reduced
lung function and increased respiratory symptoms, such as chest pain and cough, when
exposed to relatively low ozone levels during periods of moderate exertion. In addition to
human health effects, ozone adversely affects crop yield, vegetation and forest growth, and
the durability of materials. Ozone causes noticeable foliar damage in many crops, trees, and
ornamental plants (i.e., grass, flowers, shrubs, and trees) and causes reduced growth in
plants.
Particulate matter (PM) can also be formed from NOX emissions. Secondary
PM is formed in the atmosphere through a number of physical and chemical processes that
transform gases such as sulfur dioxide, NOX, and VOC into particles. Scientific studies have
linked PM (alone or in combination with other air pollutants) with a series of health effects
(see Chapter 8 for a detailed discussion of studies used to evaluate health impacts of PM
emissions). Coarse particles can accumulate in the respiratory system and aggravate health
problems such as asthma. Fine particles can penetrate deep into the lungs and are more
likely than coarse particles to contribute to a number of the health effects. These health
effects include decreased lung function and alterations in lung tissue and structure and in
respiratory tract defense mechanisms which may be manifest in increased respiratory
symptoms and disease or in more severe cases, increased hospital admissions and emergency
room visits or premature death. Children, the elderly, and people with cardiopulmonary
disease, such as asthma, are most at risk from these health effects.
PM also causes a number of adverse effects on the environment. Fine PM is the
major cause of reduced visibility in parts of the United States, including many of our national
parks and wilderness areas. Other environmental impacts occur when particles deposit onto
soil, plants, water, or materials. For example, particles containing nitrogen and sulfur that
deposit onto land or water bodies may change the nutrient balance and acidity of those
environments, leading to changes in species composition and buffering capacity.
Particles that are deposited directly onto leaves of plants can, depending on
their chemical composition, corrode leaf surfaces or interfere with plant metabolism.
Finally, PM causes soiling and erosion damage to materials.
Thus, reducing the emissions of NOX from stationary combustion turbines can
help to improve some of the effects mentioned above, either those directly related to NOX
emissions, or the effects of ozone and PM resulting from the combination of NOX with other
pollutants.
3-8
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3.2.2 Benefits of Sulfur Dioxide Reductions
Very high concentrations of sulfur dioxide (SO2) affect breathing and ambient
levels have been hypothesized to aggravate existing respiratory and cardiovascular disease.
Potentially sensitive populations include asthmatics, individuals with bronchitis or
emphysema, children and the elderly. SO2 is also a primary contributor to acid deposition, or
acid rain, which causes acidification of lakes and streams and can damage trees, crops,
historic buildings and statues. In addition, sulfur compounds in the air contribute to visibility
impairment in large parts of the country. This is especially noticeable in national parks.
PM can also be formed from SO2 emissions. Secondary PM is formed in the
atmosphere through a number of physical and chemical processes that transform gases, such
as SO2, into particles. Overall, emissions of SO2 can lead to some of the effects discussed in
this section—either those directly related to SO2 emissions, or the effects of ozone and PM
resulting from the combination of SO2 with other pollutants.
3.3 Emission Reductions from the NSPS
The reductions of NOx from this NSPS for new stationary combustion turbines
will essentially be zero because the new turbines that may need to install add-on controls to
meet the NOx emissions limits will already be required to install these add-on controls to
meet NOx reduction requirements under the Prevention of Significant Deterioration/New
Source Review (PSD/NSR) programs. Therefore, we conclude that the NOx reductions
resulting from the rule will essentially be zero. The expected SO2 reductions resulting from
the rule will be approximately 830 tons/year in the fifth year after promulgation of the
standards.
3-9
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SECTION 4
PROJECTION OF UNITS AND FACILITIES IN AFFECTED SECTORS
The regulation will affect new turbine units with capacity over 1 MW. As a
result, the economic impact estimates presented in Section 7 and the small entity screening
analysis presented in Section 8 are based on the population of existing units and the
projection of new combustion turbine units for the next 5 years. This section begins with a
review of the technical characteristics and industry distribution of existing combustion
turbines contained in the Agency's Inventory Database. It presents projected growth
estimates for combustion turbines greater than 1 MW and describes trends in the electric
utility industry. It also presents (in Section 4.3) the estimated number of new combustion
turbines that will be affected by this rule.
4.1 Profile of Existing Combustion Turbine Units
4.1.1 Distribution of Un its and Facilities by Industry
Table 4-1 presents the number of combustion turbines and facilities owning
turbines by NAICS code. Forty-seven percent of existing combustion turbines are in
Utilities (NAICS 221), 22 percent are in Pipeline Transportation, and 18 percent are in Oil
and Gas Extraction (NAICS 211). Section 4 presents industry profiles for the electric power,
natural gas pipelines, and oil and gas industries. The remaining units are primarily
distributed across the manufacturing sector and are concentrated in the chemical and
petroleum industries.
4.1.2 Technical Characteristics
This section characterizes the population of 2,072 units by MW capacity, fuel
type, hours of operation, annual MWh produced (or equivalent), and simple or combined
cycle.
• MW Capacity: Unit capacities in the population range between 1 and 368 MW.
Although some units have large capacities in excess of 100 MW, about half
(1,000 units) have capacities between 1 and 10 MW (see Figure 4-1). Only
approximately 13 percent (278 units) have capacities greater than 100 MW. The
total estimated capacity of all the units in the population is 79,909 MW.
4-1
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Table 4-1. Facilities With Units Having Capacities Above 1 MW by Industry Grouping
and Government Sector
NAICS
112
211
212
221
233
235
311
321
322
324
325
326
327
331
332
333
334
335
336
337
339
422
486
488
513
522
541
561
611
622
721
923
926
928
Unknown
Total
Description
Animal Production
Oil and Gas Extraction
Mining (Except Oil and Gas)
Utilities
Building, Developing, and General Contracting
Special Trade Contractors
Food Manufacturing
Wood Products Manufacturing
Paper Manufacturing
Petroleum and Coal Products Manufacturing
Chemical Manufacturing
Plastics and Rubber Products Manufacturing
Nonmetallic Mineral Product Manufacturing
Primary Metal Manufacturing
Fabricated Metal Product Manufacturing
Machinery Manufacturing
Computer and Electronic Product Manufacturing
Electrical Equipment, Appliance, and Component
Manufacturing
Transportation Equipment Manufacturing
Furniture and Related Product Manufacturing
Miscellaneous Manufacturing
Wholesale Trade, Nondurable Goods
Pipeline Transportation
Support Activities for Transportation
Broadcasting and Telecommunications
Credit Intermediation and Related Activities
Professional, Scientific, and Technical Services
Administrative and Support Services
Educational Services
Hospitals
Accommodation
Administration of Human Resource Programs
Administration of Economic Programs
National Security and International Affairs
Industry Classification Unknown
# Units
1
365
3
983
1
2
18
3
17
34
63
4
1
13
2
2
6
1
3
1
3
6
448
1
1
3
2
1
10
23
1
1
1
42
6
2,072
# Facilities
1
105
3
393
1
1
11
2
11
11
39
3
1
4
2
2
5
1
3
1
3
4
244
1
1
1
2
1
8
14
1
1
1
12
5
899
Source: Industrial Combustion Coordinated Rulemaking (ICCR). 1998. Data/Information Submitted to the
Coordinating Committee at the Final Meeting of the Industrial Combustion Coordinated Rulemaking
Federal Advisory Committee. EPA Docket Numbers A-94-63, II-K-4b2 through -4b5. Research
Triangle Park, North Carolina. September 16-17.
4-2
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900 -,
800 -
700 -
600 -
500 -
400 -
300 -
200 -
100 -
n
765
215
227
325
242 22 1
57
| |
ItoS 5 to 10 10 to 25 25 to 50 50 to 100 100 to 200 >200
MW Capacity Range
Figure 4-1. Number of Units by MW Capacity
Fuel type: To determine the breakdown of turbines by fuel type, the EPA Region
4 spreadsheet of national combustion turbines permitted in the past few years was
used. According to the spreadsheet, 41 percent of turbines were dual fuel, 3
percent fired distillate oil only, and the remaining 56 percent fired natural gas
only. Many dual fuel turbines are permitted to operate up to 10 percent of the
time on distillate oil, so for purposes of this estimate it was assumed that dual fuel
turbines would operate 10 percent of the time on distillate oil.
Hours of Operation: This EIA uses assumptions that new simple cycle stationary
combustion turbines typically operate at a 20 percent capacity factor (or 1,752
hours per year) and combined cycle turbines typically operate at a 60 percent
capacity factor (or 5,256 hours per year). These figures are based on information
submitted during the public comment period for the proposed Stationary
Combustion NESHAP. The same hours of operation are used in this analysis.
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Table 4-2. Stationary Combustion Turbine Projections
Total Number of New Units
Simple cycle
Combined cycle
Total in 5th year
Average per year
286
69
355
71
Annual MWh Equivalent: Figure 4-2 presents the distribution of units by the
estimated annual MWh equivalent produced by each unit. For units that are used
for compression or other functions, their likely MWh output was estimated using
their MW capacity and annual hours of operation. Annual MWh for 245 units
lacking annual hours of operation information was not calculated. Figure 4-3
includes data for the other 1,827 units, more than one-third of which have output
of between 10,000 and 50,000 MWh a year. 360 units have output of less than
5,000 MWh, and 217 units have output greater than 500,000 MWh.
700 -,
600 -
& 500 -
Z 400 H
o
I 300 H
200 -
100 -
0
624
228
132
294
149
217
<500 500 to 5,000
5,000 to
10,000
10,000 to
50,000
50,000 to
100,000
100,000 to
500,000
>500,000
Anniitil MWh Equivalent
Figure 4-2. Number of Units by Annual MWh Output Equivalent
Note: Excludes 245 units for which information on annual hours of operation was unavailable.
Simple vs. combined cycle: The Inventory Database did not distinguish between
simple and combined cycle turbines. In order to determine the breakdown
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between simple and combined cycle units, the EPA's RACT/BACT/LAER
Clearinghouse and the national list of combustion turbines maintained by EPA
Region 4 were consulted. Both of those sources showed that the vast majority of
turbines rated less than 30 MW are simple cycle. For turbines that are larger than
30 MW, approximately 40 percent were simple cycle and 60 percent were
combined cycle.
4.2 Projected Growth of Combustion Turbines
The Agency estimates there will be a total of 355 new stationary turbines over
the next 5 years (see Table 4-2). This projection is based on a survey of gas turbine orders
for the period of June 2002 to May 2003 in the October 2003 Diesel & Gas Turbine
Worldwide (D>W) Power Generation Order Survey. The breakdown of turbines
classified as simple and combined cycle was estimated by using EPA's RACT/BACT/LAER
Clearinghouse and the national list of combustion turbines maintained by EPA Region 4.
4.3 Projected Number of Affected Stationary Combustion Turbines
We estimate that 10 of the new simple-cycle turbines in the 30 to 120 MW
range will install selective catalytic reduction (SCR) to meet the NOX emission standard for
the Gas Turbine NSPS. It is possible that some units could install a heat recovery steam
generator (HRSG). Although a HRSG is more expensive than SCR, it has the benefit of
increased power output and therefore may be a more attractive option. However, for
purposes of this estimate, it was assumed that SCR would be used to comply with the rule.
Combined-cycle units and simple-cycle units less than 30 MW or greater than 120 MW will
not need to install a HRSG or SCR since turbines that do not exceed the NOX emissions
limits and meet the efficiency requirements are available. Existing sources are not required
to comply with emission requirements in the rule.
Based on the projected estimates of simple-cycle units in the 30 to 60 MW and
60 to 120 MW ranges, a total of 10 units are expected to install an SCR. Two 30 to 60 MW
units and eight 60 to 120 MW units are expected to install SCR.
It should be noted that these 10 new turbines will already be required to install
these add-on controls to meet NOx reduction requirements under the PSD/NSR programs.
Thus, we conclude that the control costs resulting from the proposed NSPS will be
essentially zero. These sources and other affected sources are expected to follow monitoring,
record keeping, and reporting requirements, conduct fuel sampling, and conduct initial
performance testing.
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4-6
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SECTION 5
PROFILE OF THE ELECTRIC UTILITY INDUSTRY
The Agency anticipates that all of the direct costs of the NSPS will be borne by
the electric services (NAICS 22111) sector. The Agency projects that growth in new
combustion turbines that will be affected by the regulation will also be concentrated in the
electric services. This section contains background information on this industry to help
inform the regulatory process.
5.1 Electric Utility Industry (NAICS 22111)
This profile of the U.S. electric power industry provides background
information on the evolution of the electricity industry, the composition of a traditional
regulated electric utility, the current market structure of the electric industry, and
deregulation trends and the potential future market structure of the electricity market. This
profile also discusses current industry characteristics and trends that will influence the future
generation and consumption of electricity.
5.1.1 Market Structure of the Electric Power Industry
The ongoing process of deregulation of wholesale and retail electric markets is
changing the structure of the electric power industry. Deregulation is leading to the
functional unbundling of generation, transmission, and distribution and to competition in the
generation segment of the industry. This section provides background on the current
structure of the industry and future deregulation trends. It begins with a brief overview of
the evolution of the electric power industry because the future market structure will, in large
part, be determined by the existing infrastructure and capital assets that have evolved over
the past decades.
5.1.1.1 The Evolution of the Electric Power Industry
The electric utility industry began as isolated local service systems with the first
electric companies evolving in densely populated metropolitan areas like New York and
Chicago. Prior to World War I, rural electrification was a piecemeal process. Only small,
isolated systems existed, typically serving a single town. The first high-voltage transmission
network was built in the Chicago area in 1911 (the Lake County experiment). This new
network connected the smaller systems surrounding Chicago and resulted in substantial
production economies, lower customer prices, and increased company profits.
5-1
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In light of the success of the Lake County experiment, the 1910s and 1920s saw
increased consolidation and rapid growth in electricity usage. During this period, efficiency
gains and demand growth provided the financing for system expansions. Even though the
capacity costs (fixed costs per peak kW demanded) were typically twice as large with the
consolidated/interconnected supply systems, the fixed costs per unit of energy production
(kWh) were comparable to those of the old single-city system. This was the case because of
load factor improvements, which resulted from aggregating customer demand.
Whereas the average fixed cost per customer was relatively unchanged as a
result of the move from single-city to consolidated supply systems, large savings were
realized from decreases in operating costs. In particular, fuel costs per kWh decreased
70 percent because of the improved combustion efficiency of larger plants and lower fuel
prices for purchases of large quantities. In addition, operation and maintenance costs
decreased 85 percent, primarily as a result of decreased labor intensity.
During the 1920s, only a small part of the efficiency gains were passed on to
customers in the form of lower prices. Producers retained the bulk of the productivity
increases as profits. These profits provided the internal capital to finance system expansions
and to buy out smaller suppliers. Industry expansion and consolidation led to the
development of large utility holding companies whose assets were shares of common stock
in many different operating utilities.
The speculative fever of the 1920s led to holding companies purchasing one
another, creating financial pyramids based on inflated estimates of company assets. With the
stock market crash in 1929, shareholders who had realized both real economic profits and
speculative gains lost large amounts of money. The financial collapse of the utility holding
companies led to new levels of utility regulation.
From the 1930s through the 1960s, the regulated mandate of electric utilities
was basically unchanged: to provide safe, adequate, and reliable service to all electricity
users. The majority of the state and federal laws regulating utilities in place during this era
had been written shortly after the Depression. The laws were primarily designed to prevent
"ruinous competition" through costly duplication of utility functions and to protect customers
against exploitation from a monopoly supplier.
During this period, most utilities were vertically integrated, controlling
everything from generation to distribution. Economies of scale in generation and the
inefficiency of duplicating transmission and distribution systems made the electric utility
industry a textbook example of a natural monopoly. Electricity was viewed as a
homogeneous good from which there were no product unbundling opportunities or unique
5-2
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product offerings on which competition could get a foothold. In addition, the industry was
extremely capital-intensive, providing a sizable barrier to entry even if the monopoly status
of the utilities had not been protected.
From the 1930s to the 1960s, the electric industry experienced almost
continuous growth in demand. In addition, there was a steady stream of technological
innovations in generation, transmission, and distribution operations. The increased
economies of scale, technological advances, and fast demand growth led to steadily declining
unit costs. However, in an environment of decreasing unit costs, there were few rate cases
and almost no pressure from customers to change the system. This period is often referred to
as the golden era for the electric utility industry.
5.1.1.2 Structure of the Traditional Regulated Utility
The utilities vary substantially in size, type, and function. Figure 5-1 illustrates
the typical structure of the electric utility market. Even with the technological and regulatory
changes in the 1970s and 1980s, at the beginning of the 1990s the structure of the electric
utility industry could still be characterized in terms of generation, transmission, and
distribution. Commercial and retail customers were in essence "captive," and rates and
service quality were primarily determined by public utility commissions.
The majority of utilities are interconnected and belong to a regional power pool.
Pooling arrangements enable facilities to coordinate the economic dispatch of generation
facilities and manage transmission congestion. In addition, pooling diverse loads can
increase load factors and decrease costs by sharing reserve capacity.
Generation. Coal-fired plants have historically accounted for the bulk of
electricity generation in the United States. With abundant national coal reserves and
advances in pollution abatement technology, such as advanced scrubbers for pulverized coal
and flue gas-desulfurization systems, coal will likely remain the fuel of choice for most
existing generating facilities over the near term.
Natural gas accounts for approximately 10 percent of current generation
capacity but is expected to grow; advances in natural gas exploration and extraction
technologies and new coal gasification have contributed to the use of natural gas for power
generation.
5-3
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Electricity
Generation
Power Plants
Trans-
mission
High Voltage Lines
Transformer
Distribution
Residential
Customers
Small C/l
Customers
Large C/l
Customers
Figure 5-1. Traditional Electric Power Industry Structure
Nuclear plants and renewable energy sources (e.g., hydroelectric, solar, wind)
provide approximately 20 percent and 10 percent of current generating capacity,
respectively. However, there are no plans for new nuclear facilities to be constructed, and
there is little additional growth forecasted in renewable energy.
5-4
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Transmission. Transmission refers to high voltage lines used to link generators
to substations where power is stepped down for local distribution. Transmission systems
have been traditionally characterized as a collection of independently operated networks or
grids interconnected by bulk transmission interfaces.
Within a well-defined service territory, the regulated utility has historically had
responsibility for all aspects of developing, maintaining, and operating transmissions. These
responsibilities included
• system planning and expanding,
• maintaining power quality and stability, and
• responding to failures.
Isolated systems were connected primarily to increase (and lower the cost of) power
reliability. Most utilities maintained sufficient generating capacity to meet customer needs,
and bulk transactions were initially used only to support extreme demands or equipment
outages.
Distribution. Low-voltage distribution systems that deliver electricity to
customers comprise integrated networks of smaller wires and substations that take the higher
voltage and step it down to lower levels to match customers' needs.
The distribution system is the classic example of a natural monopoly because it
is not practical to have more than one set of lines running through neighborhoods or from the
curb to the house.
5.1.1.3 Current Electric Power Supply Chain
This section provides background on existing activities and emerging
participants in the electric power supply chain.4 Because the restructuring plans and time
tables are made at the state level, the issues of asset ownership and control throughout the
current supply chain in the electric power industry vary from state to state. However, the
activities conducted throughout the supply chain are generally the same.
Table 5-1 shows costs by utility ownership and by segment of the supply chain.
Generation accounts for approximately 75 percent of the cost of delivered electric power.
4The electric power supply chain includes all generation, transmission, distribution, administrative, and market
activities needed to deliver electric power to consumers.
5-5
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Table 5-1. Total Expenditures in 1996 ($103)
Utility
Ownership Generation Transmission Distribution
Customer Administration
Accounts and General
and Sales Expenses
Investor-
owned
Publicly
owned
Federal
Cooperatives
80,891,644
12,495,324
3,685,719
15,105,404
112,178,091
75.6%
148,370,552
2,216,113
840,931
327,443
338,625
3,723,112
2.5%
6,124,443
1,017,646
1,435
1,133,984
8,277,508
5.6%
6,204,229
486,195
55,536
564,887
7,310,847
4.9%
13,820,059
1,360,111
443,809
1,257,015
16,880,994
11.4%
Sources: U.S. Department of Energy, Energy Information Administration (EIA). 1998a. Financial Statistics of
Major Publicly Owned Electric Utilities, 1997. Washington, DC: U.S. Department of Energy.
U.S. Department of Energy, Energy Information Administration (EIA). 1997. Financial Statistics of
Major U.S. Investor-Owned Electric Utilities, 1996. Washington, DC: U.S. Department of Energy.
Figure 5-2 provides an overview of the electric power supply chain,
highlighting a combination of activities and service providers. The activities/members of the
electric power supply chain are typically grouped into generation, transmission, and
distribution. These three segments are described in the following sections.
Generation. As part of deregulation, the transmission and distribution of
electricity are being separated from the business of generating electricity, and a new
competitive market in electricity generation is evolving. As power generators prepare for the
competitive market, the share of electricity generation attributed to nonutilities and utilities is
shifting.
More than 7,000 electricity suppliers currently operate in the U.S. market. As
shown in Table 5-2, approximately 42 percent of suppliers are utilities and 58 percent are
nonutilities. Utilities include investor-owned, cooperatives, and municipal systems. Of the
approximately 3,100 utilities operating in the United States, only about 700 generate electric
power. The majority of utilities distribute electricity that they have purchased from power
generators via their own distribution systems.
5-6
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Fuel Source: Coal, Natural Gas, Water, etc.
IPP Generation
Local Utility
Generation
Private
Lines
Se If-Generation
E/ec-tricity
Competing Utility
Generation
(outside service
territory)
/ntersystem
Bulk Transmission
* Surplus
Electricity
+ Purchased
System Reliability
and Control
Local Distribution
* Surplus
Electricity
+ Purchased
Waste Heat
Large C/l
Customers
Small C/l
Customers
Residential
Customers
Figure 5-2. Electric Utility Industry
Utility and nonutility generators produced a total of 3,369 billion kWh in 1995.
Although utilities generate the vast majority of electricity produced in the United States,
nonutility generators are quickly eroding utilities' shares of the market. Nonutility
generators include private entities that generate power for their own use or to sell to utilities
or other end users. Between 1985 and 1995, nonutility generation increased from 98 billion
kWh (3.8 percent of total generation) to 374 billion kWh (11.1 percent). Figure 5-3
illustrates this shift in the share of utility and nonutility generation.
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Table 5-2. Number of Electricity Suppliers in 1999
Electricity Suppliers Number Percent
Utilities 3,124 42%
Investor-owned utilities 222
Cooperatives 875
Municipal systems 1,885
Public power districts 73
State projects 55
Federal agencies 14
Nonutilities 4,247 58%
Nonutilities (excluding EWGs) 4,103
Exempt wholesale generators 144
Total 7,371 100%
Source: U.S. Department of Energy, Energy Information Administration (EIA). 1999g. The Changing
Structure of the Electric Power Industry 1999: Mergers and Other Corporate Combinations.
Washington, DC: U.S. Department of Energy.
Utilities. There are four categories of utilities: investor-owned utilities (lOUs),
publicly owned utilities, cooperative utilities, and federal utilities. Of the four, only lOUs
always generate electricity.
lOUs are increasingly selling off generation assets to nonutilities or converting
those assets into nonutilities (Haltmaier, 1998). To prepare for the competitive market, lOUs
have been lowering their operating costs, merging, and diversifying into nonutility
businesses.
In 1995, utilities generated 89 percent of electricity, a decrease from 96 percent
in 1985. lOUs generate the majority of the electricity produced in the United States. lOUs
are either individual corporations or a holding company, in which a parent company operates
one or more utilities integrated with one another. lOUs account for approximately three-
quarters of utility generation, a percentage that held constant between 1985 and 1995.
Utilities owned by the federal government accounted for about one-tenth of
generation in both 1985 and 1995. The federal government operated a small number of large
utilities in 1995 that supplied power to large industrial consumers or federal installations.
The Tennessee Valley Authority is an example of a federal utility.
5-8
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Utilities
Shares of Total
Utility Generation
1988 Generation
Utility 93%
Nonutility 7%
Shares of Total
Nonutility Generation
Investor-Owned
Nonutilities
Cooperative
Other Public
Federal
Investor-Owned
4%
1 0%
9%
Shares of Total
77% Utility Generation
1998 Generation
Utility 89%
Nonutility 11%
Cogen OF
SPP OF
Cogen Non-QF
Other Non-QF
Any
Combination
EWG
0%
Cogeri QF
EWG
SPP QF
Cogen Non-QF
Other Non-QF
Shares of Total
Nonutility Generation
12%
7%
" Includes facilities classified in more than one of the following FERC designated categories: cogenerator QF, small
power producer QF, or exempt wholesale generator.
Cogen = Cogenerator.
EWG = Exempt wholesale generator.
Other Non-QF = Nocogenerator Non-QF.
QF = Qualifying facility.
SPP = Small power producer.
Note: Sum of components may not equal total due to independent rounding. Classes for nonutility generation are
determined by the class of each generating unit.
Sources: Utility data: U.S. Department of Energy, Energy Information Administration (EIA). 1996b. Electric Power
Annuall995. Volumes I and II. DOE/EIA-0348(95)/1. Washington, DC: U.S. Department of Energy; Table i
(and previous issues); Nonutility data: Shares of generation estimated by EIA; total generation from Edison
Electric Institute (E El). 1998. Statistical Yearbook of the Electric Utility Industry 1998. November.
Washington, DC;
Figure 5-3. Utility and Nonutility Generation and Shares by Class, 1988 and 1998
Many states, municipalities, and other government organizations also own and
operate utilities, although the majority do not generate electricity. Those that do generate
electricity operate capacity to supply some or all of their customers' needs. They tend to be
small, localized outfits and can be found in 47 states. These publicly owned utilities
accounted for about one-tenth of utility generation in 1985 and 1995. In a deregulated
market, these generators may be in direct competition with other utilities to service their
market.
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Rural electric cooperatives are the fourth category of utilities. They are formed
and owned by groups of residents in rural areas to supply power to those areas. Cooperatives
generally purchase from other utilities the energy that they sell to customers, but some
generate their own power. Cooperatives only produced 5 percent of utility generation in
1985 and only 6 percent in 1995.
Nonutilities. Nonutilities are private entities that generate power for their own
use or to sell to utilities or other establishments. Nonutilities are usually operated at mines
and manufacturing facilities, such as chemical plants and paper mills, or are operated by
electric and gas service companies (DOE, EIA, 1998b). More than 4,200 nonutilities operate
in the United States.
Between 1988 and 1998, nonutility generators increased their share of
electricity generation from 7 percent to 11 percent (see Figure 5-3). In 1978, the Public
Utilities Regulatory Policies Act (PURPA) stipulated that electric utilities must interconnect
with and purchase capacity and energy offered by any qualifying nonutility. In 1996, FERC
issued Orders 888 and 889 that opened transmission access to nonutilities and required
utilities to share information about available transmission capacity. These moves established
wholesale competition, spurring nonutilities to increase generation and firms to invest in
nonutility generation.
Nonutilities are frequently categorized by their FERC classification and the type
of technology they employ. There are three categories of nonutilities: cogenerators, small
power producers (SPPs), and exempt wholesale generators (EWGs).
Cogenerators are nonutilities that sequentially or simultaneously produce
electricity and another form of energy (such as heat or steam) using the same fuel source. At
cogeneration facilities, steam is used to drive a turbine to generate electricity. The waste
heat and steam from driving the turbine is then used as an input in an industrial or
commercial process. For a cogenerator to qualify or interconnect with utilities, it must meet
certain ownership, operating, and efficiency criteria specified by FERC. In 1985, about
55 percent of nonutility generation was produced by cogenerators that qualified or met
FERC's specifications and sold power to utilities. By 1995 the percentage increased to
67 percent as the push for deregulation gathered momentum. At the same time, the
percentage that was produced by nonqualifying cogenerators decreased from 25 percent to
9 percent.
SPPs typically generate power using renewable resources, such as biomass,
solar energy, wind, or water. However, increasingly SPPs include companies that self-
generate power using combustion turbines and sell excess power back to the grid. As with
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cogenerators, SPPs must fulfill a series of FERC requirements to interconnect with utilities.
PURPA revisions enabled nonutility renewable electricity to grow significantly, and SPPs
have responded by improving technologies, decreasing costs, and increasing efficiency and
reliability (DOE, EIA, 1998b). Between 1985 and 1995, the percentage of SPP nonutility
generation nearly doubled to 13 percent.
EWGs produce electricity for the wholesale market. Also known as IPPs,
EWGs typically contract directly with large bulk customers, such as large industrial and
commercial facilities and utilities. They do not operate any transmission or distribution
facilities but pay tariffs to use facilities owned and operated by utilities. Unlike with
qualifying cogenerators and SPPs, utilities are not required to purchase energy produced by
EWGs, but they may do so at market-based prices. EWGs did not exist until the Energy
Policy Act created them in 1992, and by 1995 they generated about 2 percent of nonutility
electricity.
In 1995, about 4 percent of nonutility generation was produced by facilities that
were classified as any combination of cogenerator, SPP, and EWG. An additional 6 percent
was produced by facilities that generate electricity for their own consumption.
Transmission. Whereas the market for electricity generation is moving toward
a competitive structure, the transmission of electricity is currently (and will likely remain) a
regulated, monopoly operation. In areas where power markets are developing, generators
pay tariffs to distribute their electricity over established lines owned and maintained by
independent organizations. Independent service operators (ISOs) will most likely coordinate
transmission operations and generation dispatch over the bulk power system.
The bulk power transmission system consists of three large regional networks,
which also encompass smaller groups. The three networks are geographically defined: the
Eastern Interconnect in the eastern two-thirds of the nation; the Western Interconnect in the
western portion; and the Texas Interconnect, which encompasses the majority of Texas. The
western and eastern networks are each fully integrated with Canada. The western is also
integrated with Mexico. Within each network, the electricity producers are connected by
extra high-voltage connections that allow them to transfer electrical energy from one part of
the network to the other.
The bulk power system makes it possible for electric power producers to engage
in wholesale trade. In 1995, utilities sold 1,283 billion kWh to other utilities. The amount of
energy sold by nonutilities has increased dramatically from 40 billion kWh in 1986 to 222
billion kWh in 1995, an average annual increase of 21 percent (DOE, EIA, 1996a).
Distribution utilities and large industrial and commercial customers also have the option of
5-11
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purchasing electricity in bulk at market prices from their local utility, a nonutility, or another
utility. The process of transmitting electricity between suppliers via a third party is known as
wholesale wheeling.
The wholesale trade for electricity is increasingly handled by power marketers
(brokers). Power marketers act as independent middlemen that buy and sell wholesale
electricity at market prices (EEI, 1999). Customers include large commercial and industrial
facilities in addition to utilities. Power marketers emerged in response to increased
competition. Brokers do not own generation facilities, transmissions systems, or distribution
assets, but they may be affiliated with a holding company that operates generation facilities.
Currently, 570 power marketers operate in the United States. The amount of power sold by
marketers increased from 3 million MWh to 2.3 billion MWh between 1995 and 1998. This
is the equivalent of going from powering 1 million homes to powering 240 million homes
(EEI, 1999). Table 5-3 lists the top ten power marketers by sales for the first quarter of
1999.
Table 5-3. Top Power Marketing Companies, First Quarter 1999
Company Total MWh Sold
Enron Power Marketing, Inc. 78,002,931
Southern Company Energy Marketing, L.P. 38,367,107
Aquila Power Corp. 29,083,612
PG&E Energy Trading-Power, L.P. 28,463,487
Duke Energy Trading & Marketing, L.L.C. 22,276,608
LG&E Energy Marketing, Inc. 15,468,749
Entergy Power Marketing Corp. 12,670,520
PacifiCorp Power Marketing, Inc. 11,800,263
Tractebel Energy Marketing, Inc. 10,041,039
Nor Am Energy Services, Inc. 9,817,306
Source: Resource Data International. 1999. "PMA Online Top 25 Power Marketer Rankings." Power
Marketers Online Magazine, As obtained on
August 11, 1999.
Distribution. The local distribution system for electricity is expected to remain
a regulated monopoly operation. But power producers will soon be able to compete for retail
customers by paying tariffs to entities that distribute the power. Utilities may designate an
5-12
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ISO to operate the distribution system or continue to operate it themselves. If the utility
operates its own system, it is required by law to charge the same tariff to other power
producers that it charges producers within its own corporate umbrella. The sale of electricity
by a utility or other supplier to a customer in another utility's retail service territory is known
as retail wheeling.
Supporters of retail wheeling claim that it will help lower the average price paid
for electricity. The states with the highest average prices for electricity are expected to be
the first to permit retail wheeling; wholesale wheeling is already permitted nationwide. In
1996, California, New England, and the Mid-Atlantic States had the highest average prices
for electricity, paying 3 cents or more per kilowatt-hour than the national average of
6.9 cents (DOE, EIA, 1998b). Open access to the electricity supply, coupled with a
proliferation of electricity suppliers, should combine to create falling electricity prices and
increasing usage. By 2002, the nationwide average price for electricity is projected to be
11 percent lower than in 1995, an average annual decline of roughly 2 percent (Haltmaier,
1998).
The explosion in computer and other information technology usage in the
commercial sector is expected to offset energy efficiency gains in the residential and
industrial sectors and lead to a net increase in the demand for electricity. Retail wheeling has
the potential to allow customers to lower their costs per kilowatt-hour by purchasing
electricity from suppliers that best fit their usage profiles. Large commercial and industrial
customers engaged in self-generation or cogeneration will also be able to sell surplus
electricity in the wholesale market.
5.1.1.4 Overview of Deregulation and the Potential Future Structure of the Electricity
Market
Beginning in the latter part of the 19th century and continuing for about 100
years, the prevailing view of policymakers and the public was that the government should
use its power to require or prescribe the economic behavior of "natural monopolies" such as
electric utilities. The traditional argument is that it does not make economic sense for there
to be more than one supplier—running two sets of wires from generating facilities to end
users is more costly than one set. However, since monopoly supply is not generally regarded
as likely to provide a socially optimal allocation of resources, regulation of rates and other
economic variables was seen as a necessary feature of the system.
Beginning in the 1970s, the public policy view shifted against traditional
regulatory approaches and in favor of deregulation for many important industries including
5-13
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transportation, communications, finance, and energy. The major drivers for deregulation of
electric power included the following:
• existence of rate differentials across regions offering the promise of benefits from
more efficient use of existing generation resources if the power can be transmitted
across larger geographic areas than was typical in the era of industry regulation;
• the erosion of economies of scale in generation with advances in combustion
turbine technology;
• complexity of providing a regulated industry with the incentives to make socially
efficient investment choices;
• difficulty of providing a responsive regulatory process that can quickly adjust
rates and conditions of service in response to changing technological and market
conditions; and
• complexity of monitoring utilities' cost of service and establishing cost-based
rates for various customer classes that promote economic efficiency while at the
same time addressing equity concerns of regulatory commissions.
Viewed from one perspective, not much changes in the electric industry with
restructuring. The same functions are being performed, essentially the same resources are
being used, and in a broad sense the same reliability criteria are being met. In other ways,
the very nature of restructuring, the harnessing of competitive forces to perform a previously
regulated function, changes almost everything. Each provider and each function become
separate competitive entities that must be judged on their own.
This move to market-based provision of generation services is not matched on
the transmission and distribution side. Network interactions on AC transmission systems
have made it impossible to have separate transmission paths compete. Hence, transmission
and distribution remain regulated. Transmission and generation heavily interact, however,
and transmission congestion can prevent specific generation from getting to market.
Transmission expansion planning becomes an open process with many interested parties.
This open process, coupled with frequent public opposition to transmission expansion, slows
transmission enhancement. The net result is greatly increased pressure on the transmission
system.
Restructuring of the electric power industry could result in any one of several
possible market structures. In fact, different parts of the country will probably use different
structures, as the current trend indicates. The eventual structure may be dominated by a
power exchange, bilateral contracts, or a combination. A strong Regional Transmission
5-14
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Organization (RTO) may operate in the area, or a vertically integrated utility may continue to
operate a control area. In any case, several important characteristics will change:
• Commercial provision of generation-based services (e.g., energy, regulation, load
following, voltage control, contingency reserves, backup supply) will replace
regulated service provision. This drastically changes how the service provider is
assessed.
• Individual transactions will replace aggregated supply meeting aggregated
demand. It will be necessary to continuously assess each individual's
performance.
• Transaction sizes will shrink. Instead of dealing only in hundreds and thousands
of MW, it will be necessary to accommodate transactions of a few MW and less.
• Supply flexibility will greatly increase. Instead of services coming from a fixed
fleet of generators, service provision will change dynamically among many
potential suppliers as market conditions change.
5.1.2 Electricity Generation
Because of the uncertainties associated with the future course of deregulation,
forecasting deregulation's impact on generation trends, and hence growth in combustion
turbines, is difficult. However, most industry experts believe that deregulation will lead to
increased competition in the wholesale (and eventually retail) power markets, driving out
high cost producers of electricity, and that there will be an increased reliance on distributed
generation to compensate for growing demands on the transmission system.
In 2000, the United States relied on fossil fuels to produce almost 74 percent of
its electricity. Table 5-4 shows a breakdown of generation by energy source.5 Whereas
natural gas seems to play a relatively minor role among utility producers, it represents 30
percent of capacity among nonutility producers. This is because nonutilities use coal and
petroleum to the same extent as the larger, traditionally regulated utility power producers.
Among nonutility producers, manufacturing facilities contain the largest
electricity-generating capacity. Table 5-5 illustrates that, from 1995 through 1997,
manufacturing
'Nonutility power producers have approximately 10 percent of the capacity of utility power producers.
5-15
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Table 5-4. Industry Capacity by Energy Source, 2000
Energy Source
Fossil fuels
Coal
Natural gas
Petroleum
Duel-fired
Nuclear
Hydroelectric
Renewable/other
Total
Utility Generators
(MW)
424,218
259,059
38,964
26,250
99,945
85,519
91,590
1,050
602,377
Nonutility
Generators (MW)
173,320
56,190
58,668
13,003
45,549
12,038
7,478
16,322
209,248
Total (MW)
597,538
315,249
97,632
39,253
145,494
97,557
99,068
17,372
811,625
Sources: U.S. Department of Energy, Energy Information Administration. 2000a. Electric Power Annual,
1999, Volume II. DOE/EIA-0348(99)/2. Washington, DC: U.S. Department of Energy.
Table 5-5. Installed Capacity at U.S. Nonutility Attributed to Major Industry Groups
and Census Division, 1995 through 1999 (MW)
Year Manufacturing
1995
1996
1997
1998
1999
47,606
49,529
49,791
51,255
52,430
Transportation
and Public
Utilities
15,124a
16,050
16,559
24,527
78,419
Services
2,165
2,181
2,223
2,506
2,342
Other
Public Industry
Mining Administration Groups
3,428
3,313
3,306
3,275
5,123
544
542
616
534
536
l,388a
1,575
1,510
15,989
28,506
Total
70,254
73,189
74,004
98,085
167,357
" Revised data.
Notes: All data are for 1 MW and greater. Data for 1997 are preliminary; data for prior years are final. Totals
may not equal sum of components because of independent rounding.
Source: U.S. Department of Energy, Energy Information Administration (EIA). 2000a. Electric Power Annual
1999, Volume II. DOE/EIA-0348(99)/2. Washington, DC: U.S. Department of Energy.
5-16
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facilities consistently had the capacity to produce over two-thirds of nonutility electricity
generation. However, manufacturing share fell to less than one half of nonutility capacity in
1998/1999.
In 1997 cogenerators produced energy totaling 146 billion kWh for their own
use. Cogenerators are expected to continue to increase their generation capabilities at a
slightly slower rate than utilities.
Table 5-6 further disaggregates capacity by prime mover and energy source at
electric utilities. As the table shows, hydroelectric and steam are the two prime movers with
the most units, while steam and nuclear generators have the greatest total capacity.
Combustion turbines' (including the second stage of CCCTs) generation represents
approximately 10 percent of total U.S. capacity.
Figure 5-4 shows the annual electricity sales by sector from 1970 with
projections through 2020.
The literature suggests that electricity consumption is relatively price inelastic.
Consumers are generally unable or unwilling to forego a large amount of consumption as the
price increases. Numerous studies have investigated the short-run elasticity of demand for
electricity. Overall, the studies suggest that, for a 1 percent increase in the price of
electricity, demand will decrease by 0.15 percent. However, as Table 5-7 shows, elasticities
vary greatly, depending on the demand characteristics of end users and the price structure.
Demand elasticities are estimated to range from a-0.05 percent elasticity of demand for a
"flat rates" case (i.e., no time-of-use assumption) up to a-0.50 percent demand elasticity for
a "high consumer response" case (DOE, EIA, 1999b).
5.1.2.1 Growth in Generation Capacity
The electric industry is continuing to grow and change. Throughout the
country, electric utility capacity additions are slightly outpacing capacity retirements. The
trend goes beyond an increasing capacity but also shows that coal units are slowly being
replaced by newer, more efficient methods of producing energy. In 1997, 71 electric utility
units were closed, decreasing capacity by 2,127 MW. Of those, six were coal facilities and
43 were petroleum facilities. However, of the 62 facility additions (2,918 MW), none were
coal powered, while 24 use petroleum. Gas installations slightly outpaced petroleum ones,
totaling 25 new units at electric utilities in 1997. Table 5-8 outlines capacity additions and
retirements at U.S. electric utilities by energy source.
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Table 5-6. Existing Capacity at U.S. Electric Utilities by Prime Mover and Energy
Source, as of January 1,1998
Prime Mover Energy Source
U.S. Total
Steam
Coal only
Other solids"
Petroleum only
Gas only
Other solids/coal"
Solids/petroleum*
Solids/gas"
Solids/petroleum/gasb
Petroleum/gas
Internal Combustion
Petroleum only
Gas only
Petroleum/gas
Other solids only1
Combustion Turbine
Petroleum only
Gas only
Petroleum/gas
Second Stage of CCCTs
Petroleum only
Gas only
Coal/petroleum
Coal/gas
Petroleum/gas
Waste heat
Nuclear
Hydroelectric (conventional)
Hydroelectric (pumped storage)
Geothermal
Solar
Wind
Number of Units
10,421
2,117
911
15
137
117
1
72
232
1
624
2,892
1,799
48
1,044
1
1,549
625
179
745
202
11
29
1
1
100
60
107
3,352
141
27
11
19
Generator Nameplate Capacity (MW)
754,925
469,210
276,895
334
22,476
10,840
2
10,796
36,763
558
110,324
5,075
2,671
66
2,335
3
63,131
22,802
5,776
34,554
16,224
470
2,331
326
113
8,852
4,130
107,632
73,202
18,669
1,746
5
14
" Includes wood, wood waste, and nonwood waste.
b Includes coal, wood, wood waste, and nonwood waste.
Source: U.S. Department of Energy, Energy Information Administration (EIA). 1999c. Electric Power Annual
1998. Volumes I and II. Washington, DC: U.S. Department of Energy.
5-18
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Ft stiff ntiai
Cb iTJBwrc iol
Figure 5-4. Annual Electricity Sales by Sector
Planned additions indicate a strong trend towards gas-powered
turbine/stationary combustion units. Three-quarters of the gas turbine/stationary combustion
units are expected to be gas-powered with the remaining quarter petroleum-powered. Based
on 1998 planned additions, it is likely that all additional petroleum-fueled units in the near
future will be gas turbine/stationary combustion units, not steam. Table 5-9 shows planned
capacity additions by prime mover and energy source.
5.1.3
Electricity Consumption
This section analyzes the growth projections for electricity consumption as well
as the price elasticity of demand for electricity. Growth in electricity consumption has
traditionally paralleled GDP growth. However, improved energy efficiency of electrical
equipment, such as high-efficiency motors, has slowed demand growth over the past few
decades. The magnitude of the relationship has been decreasing over time, from growth of 7
percent per year in the 1960s down to 1 percent in the 1980s. As a result, determining what
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Table 5-7. Key Parameters in the Cases
Key Assumptions
Case Name
AEO97 Reference Case
No Competition
Flat Rates
(no time-of-use rates)
Moderate Consumer
Response
High Consumer Response
High Efficiency
No Capacity Additions
High Gas Price
Low Gas Price
High Value of Reliability
HalfO&M
Intense Competition
Cost Reduction
and Efficiency
Improvements
AEO97 Reference
Case
No change from
1995
AEO97 Reference
Case
AEO97 Reference
Case
AEO97 Reference
Case
Increased cost
savings and
efficiencies
AEO97 Reference
Case
AEO97 Reference
Case
AEO97 Reference
Case
AEO97 Reference
Case
AEO97 Reference
Case
AEO97 Reference
Case
Short-Run
Elasticity
of Demand
(Percent)
—
—
-0.05
-0.15
-0.50
-0.15
-0.15
-0.15
-0.15
-0.15
-0.15
-0.15
Natural Gas
Prices
AEO97 Reference
Case
AEO97 Reference
Case
AEO97 Reference
Case
AEO97 Reference
Case
AEO97 Reference
Case
AEO97 Reference
Case
AEO97 Low Oil
and Gas Supply
Technology Case
AEO97 High Oil
and Gas Supply
Technology Case
AEO97 Reference
Case
AEO97 Reference
Case
AEO97 Reference
Case
AEO97 Reference
Case
Capacity
Additions
As needed
to meet demand
As needed
to meet demand
As needed
to meet demand
As needed
to meet demand
As needed
to meet demand
As needed
to meet demand
Not allowed
As needed
to meet demand
As needed
to meet demand
As needed
to meet demand
As needed
to meet demand
As needed to meet
demand
— = not applicable.
Source: U.S. Department of Energy, Energy Information Administration, Office of Integrated Analysis and
Forecasting. "Competitive Electricity Price Projections."
. As obtained on November 15, 1999b.
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Table 5-8. Capacity Additions and Retirements at U.S. Electric Utilities by Energy
Source, 1997
Additions
Primary Energy
Source
U.S. total
Coal
Petroleum
Gas
Water
(pumped storage
hydroelectric)
Nuclear
Waste heat
Renewable"
Number
of Units
62
—
24
25
—
—
3
10
Generator
Nameplate
Capacity (MW)
2,918
—
199
2,475
—
—
171
73
Retirements
Number
of Units
71
6
43
18
—
2
—
2
Generator
Nameplate
Capacity (MW)
2127
281
445
405
—
995
—
1
a Includes conventional hydroelectric; geothermal; biomass (wood, wood waste, nonwood waste); solar; and
wind.
Note: Total may not equal the sum of components because of independent rounding.
Source: U.S. Department of Energy, Energy Information Administration (EIA). 1999c. Electric Power Annual
1998. Volumes I and II. Washington, DC: U.S. Department of Energy.
the future growth will be is difficult, although it is expected to be positive (DOE, EIA,
1999a). Table 5-10 shows consumption by sector of the economy over the past 10 years.
The table shows that since 1989 electricity sales have increased at least 10 percent in all four
sectors. The commercial sector has experienced the largest increase, followed by residential
consumption.
In the future, residential demand is expected to be at the forefront of increased
electricity consumption. Between 1997 and 2020, residential demand is expected to increase
at 1.6 percent annually. Commercial growth in demand is expected to be approximately 1.4
percent, while industry is expected to increase demand by 1.1 percent (DOE, EIA, 1999a).
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Table 5-9. Fossil-Fueled Existing Capacity and Planned Capacity Additions at U.S.
Electric Utilities by Prime Mover and Primary Energy Source, as of January 1,1998
Planned Additions"
Prime Mover Energy Generator Nameplate
Source Number of Units Capacity (MW)
U.S. Total
Steam
Coal
Petroleum
Gas
Gas Turbine/Internal
Combustion
Petroleum
Gas
272
45
8
—
37
226
52
174
50,184
18,518
2,559
—
15,959
31,663
1,444
30,219
Planned additions are for 1998 through 2007. Totals include one 2.9 MW fuel cell unit.
Notes: Total may not equal the sum of components because of independent rounding. The Form EIA-860
was revised during 1995 to collect data as of January 1 of the reporting year, where "reporting year" is
the calendar year in which the report is required to be filed with the Energy Information
Administration. These data reflect the status of electric plants/generators as of January 1; however,
dynamic data are based on occurrences in the previous calendar year (e.g., capabilities and energy
sources based on test and consumption in the previous year).
Source: U.S. Department of Energy, Energy Information Administration (EIA). 1999c. Electric Power
Annual 1998. Volumes land U. Washington, DC: U.S. Department of Energy.
5-22
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Table 5-10. U.S. Electric Utility Retail Sales of Electricity by Sector, 1989 Through
July 1999 (Million kWh)
Period
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
Percentage
change
1989-1998
Residential
905,525
924,019
955,417
935,939
994,781
1,008,482
1,042,501
1,082,491
1,075,767
1,124,004
19%
Commercial
725,861
751,027
765,664
761,271
794,573
820,269
862,685
887,425
928,440
948,904
24%
Industrial
925,659
945,522
946,583
972,714
977,164
1,007,981
1,012,693
1,030,356
1,032,653
1,047,346
12%
Other"
89,765
91,988
94,339
93,442
94,944
97,830
95,407
97,539
102,901
99,868
10%
All Sectors
2,646,809
2,712,555
2,762,003
2,763,365
2,861,462
2,934,563
3,013,287
3,097,810
3,139,761
3,220,121
18%
Includes public street and highway lighting, other sales to public authorities, sales to railroads and railways,
and interdepartmental sales.
Sources: U.S. Department of Energy, Energy Information Administration (EIA). 1999c. Electric Power
Annual 1998. Volumes land n. Washington, DC: U.S. Department of Energy.
U.S. Department of Energy, Energy Information Administration (EIA). 1996b. Electric Power
Annual 1995. Volumes land II. Washington, DC: U.S. Department of Energy.
5-23
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SECTION 6
ECONOMIC ANALYSIS METHODS
This section presents the methodology for analyzing the economic impacts of
the NSPS. Implementation of this methodology will provide the economic data and
supporting information needed by EPA to support its regulatory determination. This analysis
is based on microeconomic theory and the methods developed for earlier EPA studies to
operationalize this theory. These methods are tailored to and extended for this analysis, as
appropriate, to meet EPA's requirements for an economic impact analysis (EIA) of controls
placed on stationary combustion turbines.
This methodology section includes a description of the Agency requirements for
conducting an EIA, background information on typical economic modeling approaches, the
conceptual approach selected for this EIA, and an overview of the computerized market
model used in the analysis. The focus of this section is on the approach for modeling the
electricity market and its interactions with other energy markets and final product markets.
Appendix A contains additional detail on estimating changes is producer and consumer
surplus in the nonelectric utility markets included in the economic model.
6.1 Agency Requirements for Conducting an EIA
The CAA provides the statutory authority under which all air quality regulations
and standards are implemented by OAQPS. The 1990 CAA Amendments require that EPA
establish emission standards for sources releasing any of the listed HAPs.
Congress and the Executive Office have imposed requirements for conducting
economic analyses to accompany regulatory actions. The Agency has published its
guidelines for developing an EIA (EPA, 1999a). Section 312 of the CAA specifically
requires a comprehensive analysis that considers benefits, costs, and other effects associated
with compliance. On the benefits side, it requires consideration of all the economic, public
health, and environmental benefits of compliance. On the cost side, it requires consideration
of the effects on employment, productivity, cost of living, economic growth, and the overall
economy. These effects are evaluated by measures of facility- and company-level
production impacts and societal-level producer and consumer welfare impacts. The RFA and
SBREFA require regulatory agencies to consider the economic impacts of regulatory actions
on small entities. Executive Order 12866 requires regulatory agencies to conduct an analysis
of the economic benefits and costs of all proposed regulatory actions with projected impacts
6-1
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(costs plus benefits) greater than $100 million. Also, Executive Order 13211 requires EPA
to consider for particular rules the impacts on energy markets. The Agency's draft Economic
Analysis Guidelines provide detailed instructions and expectations for economic analyses
that support rulemaking (EPA, 1999a). The EIA provides the data and information needed to
comply with the federal regulation, the executive order, and the guidance manual.
6.2 Overview of Economic Modeling Approaches
In general, the EIA methodology needs to allow EPA to consider the effect of
the different regulatory alternatives. Several types of economic impact modeling approaches
have been developed to support regulatory development. These approaches can be viewed as
varying along two modeling dimensions:
• the scope of economic decisionmaking accounted for in the model and
• the scope of interaction between different segments of the economy.
Each of these dimensions was considered in recommending our approach. The advantages
and disadvantages of each are discussed below.
6.2.1 Modeling Dimension 1: Scope of Economic Decisionmaking
Models incorporating different levels of economic decisionmaking can
generally be categorized as with behavior responses and without behavior responses
(accounting approach). Table 6-1 provides a brief comparison of the two approaches. The
behavioral approach is grounded in economic theory related to producer and consumer
behavior in response to changes in market conditions. In essence, this approach models the
expected reallocation of society's resources in response to a regulation. The behavioral
approach explicitly models the changes in market prices and production. Resulting changes
in price and quantity are key inputs into the determination of a number of important
phenomena in an EIA, such as changes in producer surplus, changes in consumer surplus,
and net social welfare effects. For example, a large price increase may imply that consumers
bear a large share of the regulatory burden, thereby mitigating the impact on producers'
profits and plant closures.
In contrast, the nonbehavioral/accounting approach essentially holds fixed all
interaction between facility production and market forces. In this approach, a simplifying
assumption is made that the firm absorbs all control costs, and discounted cash flow analysis
is used to evaluate the burden of the control costs. Typically, engineering control costs are
weighted by the number of affected units to develop "engineering" estimates of the total
armualized costs. These costs are then compared to company or industry sales to evaluate
6-2
-------
Table 6-1. Comparison of Modeling Approaches
EIA With Behavioral Responses
Incorporates control costs into production function
Includes change in quantity produced
Includes change in market price
Estimates impacts for
• affected producers
• unaffected producers
• consumers
• foreign trade
EIA Without Behavioral Responses
• Assumes firm absorbs all control costs
• Typically uses discounted cash flow analysis to evaluate burden of control costs
• Includes depreciation schedules and corporate tax implications
• Does not adjust for changes in market price
• Does not adjust for changes in plant production
the regulation's impact.
6.2.2 Modeling Dimension 2: Interaction Between Economic Sectors
Because of the large number of markets potentially affected by the combustion
turbines regulation, an issue arises concerning the level of sectoral interaction to model. In
the broadest sense, all markets are directly or indirectly linked in the economy; thus, all
commodities and markets are to some extent affected by the regulation. For example, the
control costs on turbines may directly affect the market for aluminum if aluminum plants are
operating turbines for self-generation of electricity or generation of process steam. However,
control costs will also indirectly affect the market for aluminum because the cost of
electricity will increase. As a result, the increased price of aluminum production (due to
direct and indirect costs on the aluminum industry) may be passed onto consumers of
aluminum products.
The appropriate level of market interactions to be included in the EIA is
determined by the scope of the regulation across industries and the ability of affected firms to
pass along the regulatory costs in the form of higher prices. Alternative approaches for
modeling interactions between economic sectors can generally be divided in three groups:
6-3
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• Partial equilibrium mo del: Individual markets are modeled in isolation. The only
factor affecting the market is the cost of the regulation on facilities in the industry
being modeled.
• General equilibrium model: All sectors of the economy are modeled together.
General equilibrium models operationalize neoclassical microeconomic theory by
modeling not only the direct effects of control costs, but also potential input
substitution effects, changes in production levels associated with changes in
market prices across all sectors, and the associated changes in welfare
economywide. A disadvantage of general equilibrium modeling is that
substantial time and resources are required to develop a new model or tailor an
existing model for analyzing regulatory alternatives.
• Multiple-market partial equilibrium model: A subset of related markets are
modeled together, with intersectoral linkages explicitly specified. To account for
the relationships and links between different markets without employing a full
general equilibrium model, analysts can use an integrated partial equilibrium
model. In instances where separate markets are closely related and there are
strong interconnections, there are significant advantages to estimating market
adjustments in different markets simultaneously using an integrated market
modeling approach.
6.3 Selected Modeling Approach Used for Combustion Turbine Analysis
To conduct the analysis for the combustion turbine NSPS, the Agency used a
market modeling approach that incorporates behavioral responses in a multiple-market
partial equilibrium model as described above. The majority of the regulation's control costs
are projected to be associated with combustion turbines in the electricity market. These
control costs will increase the price of energy, affecting almost all sectors of the economy.
Because the elasticity of demand for energy varies across fuel types, it is important to use a
market modeling approach to estimate the share of the burden borne by producers and
consumers.
Multiple-market partial equilibrium analysis provides a manageable approach to
incorporate interactions between energy markets and final product markets into the EIA to
accurately estimate the impact of the regulation. The multiple-market partial equilibrium
approach represents an intermediate step between a simple, single-market partial equilibrium
approach and a full general equilibrium approach. This approach involves identifying and
modeling the most significant subset of market interactions using an integrated partial
equilibrium framework. In effect, the modeling technique is to link a series of standard
partial equilibrium models by specifying the interactions between supply functions and then
solving for all prices and quantities across all markets simultaneously.
6-4
-------
Figure 6-1 presents an overview of the key market linkages included in the
economic impact modeling approach used to analyze the combustion turbines NSPS. The
focus of the analysis is on the energy supply chain, including the extraction and distribution
of natural gas and oil, the generation of electricity, and the consumption of energy by
producers of final products and services. As shown in Figure 6-1, wholesale electricity
generators consume natural gas and petroleum products to generate electricity that is then
used in the production of final products and services. In addition, the final product and
service markets also use natural gas and petroleum products as an input into their production
process. This analysis explicitly models the linkages between these market segments.
The control costs associated with the regulation will directly affect the cost of
the generation of wholesale electricity using combustion turbines. In addition to the direct
impact of control costs on entities installing new combustion turbines, indirect impacts are
passed along the energy supply chain through changes in prices. For example, the price of
natural gas will increase because of two effects: the higher price of electricity used in the
natural gas industry and increased demand for natural gas generated by fuel switching from
electricity to natural gas. Similarly, production costs for manufacturers of final products will
change as a result of price of electricity and natural gas.
Also included in the impact model is feedback on changes in outputs in final
product markets to the demand for Btus in the fuel markets. The change in facility output is
determined by the size of the Btu cost increase (typically variable cost per output), the
facility's production function (slope of facility-level supply curve), and the characteristics of
the facility's downstream market (other market suppliers and market demanders). For
example, if consumers' demand for a product is not sensitive to price, then producers can
pass the cost of the regulation through to consumers and the facility output will not change.
However, if only a small number of facilities in a market are affected, then competition will
prevent a facility from raising its prices.
One possible feedback pathway not explicitly modeled is technical changes in
manufacturing processes. For example, if the cost of Btus increases, a facility may use
measures to increase manufacturing efficiency or capture waste heat. These facility-level
responses are a form of pollution prevention. However, directly incorporating these
responses into the model is beyond the scope of our analysis.6
'Technical changes are indirectly captured through the own-price and cross-price elasticities of demand used to
model fuel switching. These are discussed in Section 6.4.1.
6-5
-------
a\
Energy Consumption
Fuel Market!
Sifip]jr Danand
Exogenous Endogenous
Oil
Gas
Cod
V
_ demand
i demsnd
Industry A
Btu Manufacturing
Production *" Process
Hectricity
Electricity Market
i demsnd
T
Costs
Irdustiy B
Industry C
Figure 6-1. Links Between Energy and Final Product Markets
Intermediate or
Final Pro due t Markets
Endogenous
supply
PrcductA
-------
The major market segments included in the model and the intermarket linkages
connecting the fuel markets and final product and service markets are described below.
Because, as mentioned in Section 3, the overwhelming majority of combustion turbine units
are used to generate wholesale electric power, the discussion focuses on the electricity
market.
6.3.1 Electricity Markets
In this analysis, the market for base load energy and peak power are modeled
separately. As the industry deregulates, it is becoming increasingly common for separate
market prices to be determined for these two commodity attributes of electricity. In addition,
the growth of CCCTs is being driven primarily by growth in base load energy demand, and
the growth in SCCTs will be driven primarily by growth in peak demand. And because the
relative impact on the control costs is greater for SCCTs compared to CCCTs, economic
impacts will be different for base load energy and peak power.7
The base load energy and peak power market analyses compare the baseline
equilibrium (without the regulation) to the regulated market equilibrium Figure 6-2a
presents a generalized market for the base load electricity that includes the installation of
new turbines to meet demand growth for base load power.8 Existing source supply is
characterized by an up ward-sloping marginal cost (supply) curve. The supply of new base
load generation capacity is characterized by constant marginal costs and is modeled as a
horizontal supply curve through the current market price. Figure 6-2b shows that the control
costs associated with the rule will affect both existing and new sources of supply, shifting the
market supply curve and leading to an increase in price and decrease in quantity of base load
power consumed.
6.3.2 Other Energy Markets
The petroleum, natural gas, and coal markets are also included in the market
model. Because the overwhelming majority of the affected combustion turbines is projected
to be used in the electricity market, the other energy markets are assumed not to be directly
affected by the rule. However, these markets will be indirectly affected through changes in
'The same controls are required for SCCTs and for CCCTs. But the relative costs are higher for SCCTs because
their equipment and installation costs are approximately 40 percent less compared to CCCTs. Control costs
are discussed in Section 6.1.
8A similar figure and analysis apply for peak load power with the exception that peak load supply is generally
less responsive to price changes at the margin (i.e., base load elasticity of supply > peak load elasticity of
supply).
6-7
-------
Price
$/kWh
Price
AP
t
New
Quantity
Existing
Sources
New
Sources
a) Without Regulation
Figure 6-2. Electricity Market
AQ
b) With Control Costs
Quantity
(KWK)
input fuel prices (i.e., a supply shift) and changes in demand from final product and service
markets using these energy sources (i.e., a demand shift). The ultimate impact on market
price and quantities depends on the relative magnitudes of these shifts. Note the demand for
other fuels may increase (Figure 6-3a) as firms switch away from electricity to petroleum,
natural gas, or coal, or demand may decrease (Figure 6-3b) as the higher price for electricity
suppresses economic activity decreasing demand for all fuels.
6.3.3
Supply and Demand Elasticities for Energy Markets
The market model incorporates behavioral changes based on the price
elasticities of supply and demand. The price elasticities used to estimate the economic
impacts presented in Section 6.3 are given in Table 6-2. Appendix B contains the sensitivity
analysis for the key supply and demand elasticity assumptions.
Because most of the direct cost impacts fall on the combustion turbines in
electricity markets, the price elasticities of supply in the electricity markets are important
factors influencing the size and distribution of the economic impacts associated with the
combustion turbine regulation. The elasticities of supply are intended to represent the
behavioral
6-8
-------
AP
AQ
a) Demand Increase
Btu
AQ
b) Demand Dec:
Btu
Figure 6-3. Potential Market Effects of the NSPS on Petroleum, Natural Gas, or Coal
responses from existing sources.9 However, in general, there is no consensus on estimates of
the price elasticity of supply for electricity. Estimates of the elasticity of supply for electric
power were unavailable. This is in part because, under traditional regulation, the electric
utility industry had a mandate to serve all its customers. In addition, utilities were
compensated on a rate-based rate of return. As a result, the market concept of supply
elasticity was not the driving force in utilities' capital investment decisions. To
operationalize the model, a supply elasticity of 0.75 was assumed for the base load energy
market. We assumed that the peak power market was one-half of base load energy elasticity.
Given the uncertainty surrounding these parameters, the Agency conducted a sensitivity
analysis for this value. The results of this sensitivity analysis are reported in Appendix B.
In contrast, many studies have been conducted on the elasticity of demand for
electricity, and it is generally agreed that, in the short run, the demand for electricity is
relatively inelastic. Most residential, commercial, and industrial electricity consumers do not
significantly adjust short-run behavior in response to changes in the price of electricity. The
elasticity of demand for electricity is primarily driven by long-run decisions regarding
'The supply curve for new sources is assumed to be horizontal, reflecting a constant marginal cost of production
for new sources.
6-9
-------
equipment efficiency and fuel substitution. Table 6-3 shows the elasticities of demand used
for the commercial, residential, and transportation sectors.
6-10
-------
Table 6-2. Supply and Demand Elasticities
Energy
Sectors
Electricity:
baseload
energy
Electricity:
peak power
Natural gas
Petroleum
Coal
Elasticity of
Supply
0.75
0.375"
0.41C
0.58"
1.0e
Elasticity of Demand
Manufacturing Commercial" Transportation" Residential"
Derived demand Derived -0.24 -0.23
demand
Derived demand Derived -0.24 -0.23
demand
Derived demand Derived -0.47 -0.26
demand
Derived demand Derived -0.28 -0.28
demand
Derived demand Derived -0.28 -0.28
demand
U.S. Department of Energy, Energy Information Administration. 2000b. "Issues in Midterm Analysis and
Forecasting 1999—Table 1." . As obtained on May 8,
2000.
Assumed to be one-half of baseload energy elasticity.
Dahl, Carol A., and Thomas E. Duggan. 1996. "U.S. Energy Product Supply Elasticities: A Survey and
Application to the U.S. Oil Market."Resource and Energy Economics\S:243-263.
Hogman, William W. 1989. "World Oil Price Projections: A Sensitivity Analysis." Prepared pursuant to
the Harvard-Jap an World Oil Market Study. Cambridge, MA: Energy Environmental Policy Center, John F.
Kennedy School of Government, Harvard University.
Zimmerman, M.B. 1977. "Modeling Depletion in the Mineral Industry: The Case of Coal." The Bell
Journal of Economics 8(2):41-65.
Table 6-3. Fuel Price Elasticities
Own and Cross Elasticities in 2015
Inputs
Electricity
Natural Gas
Steam Coal
Residual
Distillate
Electricity
-0.074
0.496
0.021
0.236
0.247
Natural Gas
0.092
-0.229
0.061
0.036
0.002
Coal
0.605
1.087
-0.499
0.650
0.578
Residual
0.080
0.346
0.151
-0.587
0.044
Distillate
0.017
0.014
0.023
0.012
-0.055
Source: U.S. Department of Energy, Energy Information Administration (EIA). January 1998c. Model
Documentation Report: Industrial Sector Demand Module of the National Energy Modeling System.
DOE/EIA-M064(98). Washington, DC: U.S. Department of Energy.
6-11
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Additional elasticity of demand parameters for the commercial, residential, and
transportation sectors, by fuel type (natural gas, petroleum and coal), were obtained from the
Energy Information Administration. The elasticity of demand in the energy market for the
manufacturing sector is not specified because the model calculates the derived demand for
each of the five energy markets modeled. In effect, adjustments in the final product markets
due to changes in production levels and fuel switching are used to estimate changes in
demand, eliminating the need for demand elasticity parameters in the energy markets.
6.3.4 Final Product and Service Markets
Producers of final products and services are segmented into industrial,
commercial, transportation, and residential sectors. The industrial sector is further
partitioned into the 23 manufacturing, agricultural, and mining sectors. A partial equilibrium
analysis was conducted for each of these sectors. Changes in production levels and fuel
switching due to the regulation's impact on the price of electricity are then linked back into
the energy markets.
6.3.4.1 Modeling the Impact on the Industrial and Commercial Sectors
The impact of the regulation on these sectors was modeled using changes in the
cost of Btus used in production processes. In this context, Btus refer to the generic energy
requirements that are used to generate process heat, process steam, or shaft power. As shown
in Figure 6-4, the regulation will increase the cost of Btu production indirectly through
increases in the price of Btus due to control costs on wholesale electricity generators. The
effect is similar to placing a tax on certain types of energy sources (i.e., on Btus generated by
combustion turbines). The firms' reactions to the change in the cost of Btu production feeds
back into the energy markets in two ways (see Figure 6-4). The first feedback pathway is
through changing the fuel used in the production process. This can include fuel switching,
such as switching from gas turbines to power processes to diesel engines, and/or process
changes that increase energy efficiency and reduce the amount of Btus required per unit of
output. Fuel switching impacts are modeled using cross-price elasticities of demand between
energy sources and own-price elasticities.
EPA modeled fuel switching using secondary data developed by the U.S.
Department of Energy for the National Energy Modeling System (NEMS). Table 6-3
contains fuel price elasticities of demand for electricity, natural gas, petroleum products, and
coal. The diagonal elements in the table represent own-price elasticities. For example, the
table indicates that for steam coal, a 1 percent change in the price of coal will lead to a
0.499 percent decrease in the use of coal. The off diagonal elements are cross-price
elasticities and indicate fuel
6-12
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Compliance Costs
A $/Btu
Fuel
Markets
A
$/Btu
Btu Production
Decision
A $/Btu
Production
Decision
Output
Market
A Fuel Use
A Output
Figure 6-4. Fuel Market Interactions with Facility-Level Production Decisions
switching propensities. For example, for steam coal, the second column indicates that a
1 percent increase in the price of coal will lead to a 0.061 percent increase in the use of
natural gas.
The second feedback pathway to the energy markets is through the facility's
change in output. Because Btus are an input into the production process, price increases
(t $/Btu) lead to an upward shift in the industry supply curve. In a perfectly competitive
market, the point where supply equals demand determines the market price and quantity. A
shift in the industry supply curve leads to a change in the equilibrium market price and
quantity. EPA assumed constant returns to scale in production so that the percentage change
in the equilibrium market quantity in each final product and service market equals the
percentage change in Btus consumed by industries.
The change in equilibrium supply and demand in each final industrial and
commercial sector was modeled using a partial equilibrium approach. The size of the
regulation-induced shifts in the final product supply curves is a function of the indirect fuel
costs (determined by the change in fuel prices and the fuel intensity) relative to variable
production costs in each manufacturing industry.
It was assumed that the demand for final industrial and commercial pro ducts
and services is unchanged by the regulation. However, because the demand function
quantifies the change in quantity demanded in response to a change in price, the baseline
demand conditions are important in determining the regulation's impact. Because prices
changes are anticipated to be small, the key demand parameters are the elasticity of demand
6-13
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with respect to changes in the price of final products. Demand elasticities for each of the
sectors included in the analysis are reported in Table 6-4.
6.3.4.2 Impact on the Residential Sector and Transportation Sectors
The residential and transportation sector does not bear any direct costs
associated with the regulation because they do not own combustion turbines. However, they
bear indirect costs due to price increases. These sectors' change in energy demand in
response to changes in energy prices is modeled as a series of demand curves parameterized
by elasticity of demand parameters (see Table 6-2).
6.3.4.3 Impact on the Government Sector
All combustion turbines projected to be installed by government entities will be
for local generation of electricity. These municipal generators are grouped into the
electricity energy market; thus the government sector is not explicitly included in the model.
6.4 Summary of the Economic Impact Model
We summarize the linkages used to operationalize the estimation of economic
impacts associated with the compliance costs in Figure 6-5.
Control costs on new turbines used for generators will shift the supply curve for
wholesale electricity. The new equilibrium price and quantity in the electricity market will
determine the distribution of impacts between producers (electricity generators) and
consumers. Changes in wholesale electricity generators' demand for input fuels (due to
changes in the market quantity of electricity) feed back into the natural gas, coal, and
petroleum markets.
Finally, manufacturers experience supply curve shifts due to changes in prices
for natural gas, petroleum, electricity, and coal. The share of these costs borne by producers
(manufactures) and consumers is determined by the new equilibrium price and quantity in
the final product and service markets. Changes in manufacturers' Btu demands due to fuel
switching and changes in production levels feed back into the energy markets.
Adjustments in price and quantity in all energy and final product markets occur
simultaneously. A computer model was used to numerically simulate market adjustments by
iterating over commodity prices until equilibrium is reached (i.e., until supply equals demand
in all markets being modeled) and to estimate the economic impact of the regulation (change
in producer and consumer surplus) in the sectors of the economy being modeled.
6-14
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Table 6-4. Supply and Demand Elasticities for Industrial and Commercial Sectors
NAICS Description
Industrial Sectors
311 Food
312 Beverage and Tobacco Products
313 Textile Mills
314 Textile Product Mills
315 Apparel
316 Leather and Allied Products
321 Wood Products
322 Paper
323 Printing and Related Support
325 Chemicals
326 Plastics and Rubber Products
327 Nonmetallic Mineral Products
331 Primary M etals
332 Fabricated Metal Products
333 Machinery
334 Computer and Electronic Products
335 Electrical Equip., Appliances, and
Components
336 Transportation Equipment
337 Furniture and Related Products
339 Miscellaneous
1 1 Agricultural Sector
23 Construction Sector
21 Other Mining Sector
Commercial Sector (NAICS 42-45;51-56;61-72)
Supply
0.75
0.75
0.75
0.75
0.75
0.75
0.75
0.75
0.75
0.75
0.75
0.75
0.75
0.75
0.75
0.75
0.75
0.75
0.75
0.75
0.75
0.75
0.75
0.75
Demand
-1.00
-1.30
-1.50
-1.50
-1.10
-1.20
-1.00
-1.50
-1.80
-1.80
-1.80
-1.00
-1.00
-0.20
-0.50
-0.30
-0.50
-0.50
-1.80
-0.60
-1.80
-1.00
-0.30
-1.00
6-15
-------
Fuel Mar lets
Energy Consumption
Final Product Markets
Assume
01
GIB
Cod
j jdgmxnd
2-f dem and
Elsdriily
EfcrtrktyMirhet
2jdan and
hdustryA
Eta
ftocess
Product Price
FbelPrics
fcdustryB
Industy Z
Fbelfrices
kl Businesses
FbelPrice
Residmtkl Households
P = maAetprice offiia.1
output
Q = quaiitily sold of final
Figure 6-5. Operationalizing the Estimation of Economic Impact
-------
This model comprises a series of computer spreadsheet modules. The modules
integrate the engineering inputs and the market-level adjustment parameters to estimate the
regulation's impact on the price and quantity in each market being analyzed. At the heart of
the model is a market-clearing algorithm that compares the total quantity supplied to the total
quantity demanded for each market commodity. Appendix A describes the computer model
in more detail.
6.4.1 Estimating Changes in Social Welfare
The combustion turbine regulation will impact almost every sector of the
economy either directly through control costs or indirectly through changes in the price of
energy and final products. For example, a share of control costs that originate in the energy
markets are passed through the final product markets and are borne by both the producers
and consumers of final products. To estimate the total change in social welfare without
double-counting impacts across the linked partial equilibrium markets being modeled, EPA
quantified social welfare changes for the following categories:
• change in producer surplus in the energy markets,
• change in producer surplus in the final product and service markets,
• change in consumer surplus in the final product and service markets, residential
and transportation energy markets.
Figure 6-6 illustrates the change in producer and consumer surplus in the intermediate energy
market and the final product markets. For example, assume a simple world with only one
energy market, wholesale electricity, and one final product market, pulp and paper. If the
regulation increased the cost of generating wholesale electricity, then part of the cost of the
regulation will be borne by the electricity producers as decreased producer surplus and part
of the costs will be passed on to the pulp and paper manufacturers. In Figure 6-6a, the pulp
and paper manufacturers are the consumers of electricity, so the change in consumer surplus
is displayed. This change in consumer surplus in the energy market is captured by the final
product market (because the consumer is the pulp and paper industry in this case), where it is
split between consumer surplus and producer surplus in those markets. Figure 6-6b shows
the change in producer surplus in the energy market.
As shown in Figures 6-6c and 6-6d, the cost affects the pulp and paper industry
by shifting up the supply curve in the pulp and paper market. These higher electricity prices
therefore lead to costs in the pulp and paper industry that are distributed between producers
6-17
-------
and consumers of paper products in the form of lower producer surplus and lower consumer
surplus. Note that the change in consumer surplus in the intermediate energy market must
Q Q
(a) Change ill Consumer
touplus iii the Energy
Market
(b) Change m Pi ortucei Surplus
iii die Energy Market
p
p
Q Q.
(c) Change iii Consumer
Siup his in Final Produc t
Markets
Q Q. Q
(
-------
equal the total change in consumer and producer surplus in the final product market. Thus,
to avoid double-counting, the change in consumer surplus in the intermediate energy market
was not quantified; instead the total change in social welfare was calculated as
Change in Social Welfare = £APSE + £APSF + £ACSF + £ACSRT (6.1)
where
APSE = change in producer surplus in the energy markets,
APSF = change in producer surplus in the final pro duct markets,
ACSF = change in consumer surplus in the final pro duct markets, and
ACSRT = change in consumer surplus residential and transportation energy
markets.
Appendix A contains the detailed equations used to calculate the change in producer and
consumer surplus in the appropriate intermediate and final product markets.
6-19
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SECTION 7
ECONOMIC IMPACT ANALYSIS
Control measures implemented to comply with the NSPS will impose
regulatory costs on affected facilities in the energy, manufacturing, commercial, and
government sectors. These costs will be distributed between producers and consumers
through changes in energy prices and changes in prices of final products and services. This
section describes the compliance costs of the regulatory alternatives and presents the
economic impact estimates, including energy impacts, of the NSPS.
7.1 Engineering Control Cost Inputs
To calculate the total cost of the NOX emission standard by the fifth year after
promulgation, one calculated them based on the requirements of the NSPS. It has been noted
earlier in this EIA (Chapter 3) that the add-on controls that the ten new turbines would have
to apply to comply with this proposal will already be applied in response to Prevention of
Significant Deterioration/New Source Review (PSD/NSR) requirements. Thus, the total
capital cost of this proposal is essentially zero. The requirements of this NSPS are those for
inital performance testing, fuel sampling, monitoring and recordkeeping. Table 7-1 shows
the total annual cost associated with these requirements in the fifth year after promulgation
for each MW range. These annual costs total $3.4 million. As a result, the total annual cost
of the NSPS is $3.4 million (1998$).
7,1.1 Computing Supply Shifts in the Electricity Market
For the purpose of the market model, the electric services industry is broken
into two market sectors: base load energy and peak power. As shown in Section 4 (Table 4-
3), EPA estimates approximately two-thirds of new combustion turbine units are projected to
contribute to the base load energy market, and the remaining one-third are projected to
contribute to the peak power market. As a result, the control costs for the electricity are
distributed 67 percent to the electric base load energy market and 33 percent to the peak
power market. The relative shift in the supply curve for each segment is presented as the
percentage shift in the price of the marginal unit produced. The percentage shift is calculated
7-1
-------
Table 7-1. Total Capital and Annual Cost of the Proposed NSPS in the Fifth Year
Total Capital Cost
Control cost $0
Total Annual Cost
Control cost $0
Initial performance testing $369,200
Fuel sampling $206,681
Monitoring and recordkeeping $2,393,730
Reporting $440,519
Total $3,410,130
Source: Alpha-Gamma Technologies, Inc. January 30, 2005. "Cost Impact of Proposed NSPS for
Stationary Combustion Turbines." Memorandum to Jaime Pagan, EPA OAQPS BSD Combustion
Group from Melanie Taylor, Alpha-Gamma Technologies, Inc.
as the ratio of compliance costs to the revenue of the affected portion of the industry10 (see
Table 7-2). Affected sources with performance testing, fuel sampling, monitoring and
recordkeeping, and reporting have shifts of 0.1 percent for base and peak load. The
remaining segments are unaffected (i.e., supply shift equals zero).
Figure 7-1 illustrates the supply shifts and shows the with-regulation supply
curve S]. In this example, the regulation leads to an increased supply by unaffected units,
crowding out the new units with compliance costs.
7.2 Market-Level Results
The model projects the NSPS standard will increase base load electricity price
by 0.03 percent and peak power prices by 0.04 percent (see Table 7-3). Domestic production
declines by 0.005 and 0.011 percent, respectively.
Revenue in the electric utility industry was segmented into the base load and peak power markets assuming an
80/20 split, respectively. This ratio was estimated based on discussions with industry experts.
7-2
-------
Table 7-2. Summary of Turbine Cost Information and Supply Shifts
Share Units
of Market
Revenue" Control Supply Shift
($109) Costs" ($106) (%)
Base Load Energy
Existing 97.5% $173.29
New affected: initial performance 2.3% $4.17
testing, fuel sampling, monitoring and
recordkeeping, and reporting only
Total 100.0% $177.64
Peak Power
Existing 97.5% $43.32
New affected: initial performance 2.3% $1.04
testing, fuel sampling, monitoring and
recordkeeping, and reporting only
Total 100.0% $44.40
$2.2
$1.2
$3.4
0.0%
0.1%
0.0%
0.0%
0.1%
0.0%
"Revenues and costs are in 1 998$.
The analysis also shows the impact on distribution of electricity supply (see
Table 7-4). The increase in the price of electricity will make it profitable for unaffected
sources to increase supply, displacing approximately 0.1 percent of affected new supply.
This increase in supply implies that fewer older units may be retired as a result of the
regulation. The remaining change in quantity results from decreased consumer demand as
the prices of base load energy and peak power increase. However, all these effects are very
small.
In the natural gas and petroleum markets, both the price and quantity increase,
indicating that an increase in demand for the fuel (due to fuel switching) dominates the
upward shift in the supply curve (increased electricity costs as a fuel input). Price increases
in these markets are below 0.1 percent. Price and quantity decrease in the coal market,
reflecting the decreased demand for coal as electric utilities reduce output. Market-level
impacts on downstream product and service markets are essentially zero.
7-3
-------
Price
($;kWh)
D
(Projected
Demand)
-B-
kWh
-Projected new source growth -
B = Increase in supply from existing units
C = Decreased quantity demanded due to price increase
D = Affected supply that delays entry into the market until
demand sufficiently grows
a= Supply shift for affected new units
Figure 7-1. Market for Baseload Electricity
7.3
Social Cost Estimates
The social impact of a regulatory action is traditionally measured by the change
in economic welfare that it generates. The social costs of the rule will be distributed across
producers of energy and their customers. Producers experience welfare impacts resulting
from changes in profits corresponding with the changes in production levels and market
prices. Consumers experience welfare impacts due to changes in market prices and
7-4
-------
Table 7-3. Market-Level Impacts of Stationary Combustion Turbines NSPS Standard:
2010
Energy Markets
Petroleum
Natural Gas
Base Electricity
Peak Electricity
Coal
Industrial Sectors
NAICS Description Description
311 Food
312 Beverage and Tobacco Products
313 Textile Mills
314 Textile Product Mills
315 Apparel
316 Leather and Allied Products
321 Wood Products
322 Paper
323 Printing and Related Support
325 Chemicals
326 Plastics and Rubber Products
327 Nonmetallic Mineral Products
331 Primary Metals
332 Fabricated Metal Products
333 Machinery
334 Computer and Electronic Products
335 Electrical Equipment, Appliances, and
Components
336 Transportation Equipment
337 Furniture and Related Products
339 Miscellaneous
1 1 Agricultural Sector
23 Construction Sector
21 Other Mining Sector
Commercial Sector
Percent
Price
0.002
0.007
0.028
0.044
-0.001
Percent
Price
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.001
0.001
0.000
Change
Quantity
0.001
0.002
-0.005
-0.011
-0.001
Change
Quantity
0.000
0.000
-0.000
0.000
0.000
0.000
0.000
-0.000
0.000
-0.000
-0.000
-0.000
-0.000
0.000
0.000
0.000
0.000
0.000
0.000
0.000
-0.000
-0.001
0.000
0.000
"Actual value for all 0.000 entries for the various sectors is > -0.001 and< 0.
7-5
-------
consumption levels. However, it is important to emphasize that this measure does not
include benefits that occur outside the market, that is, the value of reduced levels of air
pollution with the regulation.
The national compliance cost estimates are often used to approximate the social
cost of the rule. The engineering analysis estimated annual costs of $3.4 million. In cases
where the engineering costs of compliance are used to estimate social cost, the burden of the
regulation is measured as falling solely on the affected producers, who experience a pro fit
loss exactly equal to these cost estimates. Thus, the entire loss is a change in producer
surplus with no change (by assumption) in consumer surplus, because no change in market
price is estimated. This is typically referred to as a "full-cost absorption" scenario in which
all factors of production are assumed to be fixed and firms are unable to adjust their output
levels when faced with additional costs.
Table 7-4. Changes in Market Shares for Electricity Suppliers
With Regulation Shares
Baseline Shares (%) (%)
Existing—unaffected 97.5 97.6
New—initial performance testing, 2.3 2.3
fuel sampling, monitoring and
recordkeeping, reporting only
New—controls, initial performance 0.1 0.0
testing, fuel sampling, monitoring and
recordkeeping, reporting
In contrast, the economic analysis conducted by the Agency accounts for
behavioral responses by producers and consumers to the regulation, as affected producers
shift costs to other economic agents. This approach results in a social cost estimate that may
differ from the engineering compliance cost estimate and also provides insights on how the
regulatory burden is distributed across stakeholders. As shown in Table 7-5, the economic
model estimates the total social cost of the rule to be $2 million. The social cost estimate is
slightly less than the estimated engineering costs as a result of behavioral changes of
producers and consumers. Therefore the social costs primarily reflect higher costs by
existing units to increase supply, and the deadweight loss to consumers as price increases and
quantity decreases. It should be noted that this social cost estimate does not account for the
benefits of emission reductions associated with this NSPS and hence is not net of these
impacts to society.
7-6
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Table 7-5. Distribution of Social Costs of Stationary Combustion Turbines NSPS: 2010
($1998 106)
Sectors/Markets
Energy Sector
Petroleum (NAICS 32411,4861)
Natural Gas (NAICS 21 11 1,4862, 2212)
Electricity (NAICS 221 11, 221 122, 221121)
Coal (NAICS 2121)
Subtotal:
Industrial Sector
NAICS Description
311 Food
312 Beverage and Tobacco Products
3 1 3 Textiles Mills
3 1 4 Textile Product Mills
315 Apparel
316 Leather and Allied Products
321 Wood Products
322 Paper
323 Printing and Related Support
325 Chemicals
326 Plastics and Rubber Products
327 Nonmetallic Mineral Products
331 Primary Metals
332 Fabricated Metal Products
333 Machinery
334 Computer and Electronic Products
335 Electrical Equipment, Appliances, and
Components
336 Transportation Equipment
337 Furniture and Related Products
339 Miscellaneous
1 1 Agricultural Sector
23 Construction Sector
21 Other Mining Sector
Industrial Sector Subtotal:
Commercial Sector
Residential Sector
Transportation Sector
Subtotal
Grand Total
Producer
Surplus
$7
$6
$68
-$1
$80
Producer
Surplus
-$1
$0
-$0
$0
$0
$0
$0
-$1
$0
-$2
-$1
-$1
-$2
$0
$0
$0
$0
-$1
$0
$0
-$1
-$8
$0
-$18
-$14
NA
NA
-32
$48
Change in:
Consumer
Surplus
NA
NA
NA
NA
NA
Change in:
Consumer
Surplus
-$0
$0
$0
$0
$0
$0
$0
-$0
$0
-$1
-$0
-$0
-$1
-$1
-$0
-$0
$0
-$0
$0
$0
-$1
-$6
$1
-$11
-$10
-$23
-$6
-$50
-$50
Social
Welfare
NA
NA
NA
NA
NA
Social
Welfare
-$1
$0
-$0
$0
$0
$0
-$0
-$1
-$0
-$3
-$1
-$1
-$3
-$1
-$0
-$0
-$0
-$1
$0
$0
-$2
-$14
-$1
-$29
-$24
-$26
-$6
-$82
-$2
7-7
-------
The analysis also shows important distributional impacts across stakeholders.
For example, the model projects consumers will bear a burden of $50 million, as a result of
higher energy prices. In contrast, producer surplus increases by $48 million as energy
producers, particularly the electricity industry, become more profitable with higher prices.
7.4 Energy Impact Analysis
Executive Order 13211, "Actions Concerning Regulations That Significantly
Affect Energy Supply, Distribution, or Use" (66 Fed. Reg. 28355 [May 22, 2001]), requires
EPA to prepare and submit a Statement of Energy Effects to the Administrator of the Office
of Information and Regulatory Affairs, Office of Management and Budget, for certain
actions identified as "significant energy actions." Section 4(b) of Executive Order 13211
defines "significant energy actions" as "any action by an agency (normally published in the
Federal Register) that promulgates or is expected to lead to the promulgation of a final rule
or regulation, including notices of inquiry, advance notices of proposed rulemaking, and
notices of proposed rulemaking:
• that is a significant regulatory action under Executive Order 12866 or any
successor order, and is likely to have a significant adverse effect on the supply,
distribution, or use of energy, or
• that is designated by the Administrator of the Office of Information and
Regulatory Affairs as a significant energy action."
Although the NSPS is considered to be a significant regulatory action under
Executive Order 12866, it is not a "significant energy action" because it is not likely to have
a significant adverse effect on the supply, distribution, or use of energy. No Statement of
Energy Effects is required for this rule, but the following energy impact estimates are
included for informational purposes.
Energy Price Effects. As described in the market-level results section,
electricity prices are projected to increase by less than 0.1 percent. Petroleum and natural
gas prices are all projected to increase by less than 0.1 percent. The price of coal is projected
to decrease slightly.
Impacts on Electricity Supply, Distribution, and Use. We project the increased
compliance costs for the electricity market will result in an annual production decline of
approximately 0.2 billion kWh. Note these effects have been mitigated to some degree since
sectors previously using electricity in the baseline will switch to other energy sources (see
below).
7-8
-------
Impacts on Petroleum, Natural Gas, and Coal Supply, Distribution, and Use.
The rule will lead to higher electricity prices relative to other fuel types, resulting in fuel
switching. The model projects increases in petroleum production/consumption of
approximately 300 barrels per day. Similarly, natural gas production/consumption is
projected to increase by 2 million cubic feet per day. The model also projects decreases in
coal production/consumption of approximately 30 short tons per year. We expect that there
will be no discernable impact on the import of foreign energy supplies, and no other adverse
outcomes are expected to occur with regards to energy supplies. Also, the increase in cost of
energy production should be minimal given the very small increase in fuel consumption
resulting from back pressure related to operation of add-on control devices, such as SCR
emission control devices. All of the estimates presented above account for some passthrough
of costs to consumers as well as the direct cost impact to producers.
7-9
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SECTION 8
SMALL ENTITY IMPACTS
The regulatory costs imposed on domestic producers and government entities to
reduce air emissions from combustion turbines will have a direct impact on owners of
the affected facilities. Firms or individuals that own the facilities with combustion turbines
are legal business entities that have the capacity to conduct business transactions and make
business decisions that affect the facility. The legal and financial responsibility for
compliance with a regulatory action ultimately rests with these owners, who must bear the
financial consequences of their decisions. Environmental regulations potentially affect all
sizes of businesses, but small businesses may have special problems relative to large
businesses in complying with such regulations.
The RFA of 1980 requires that special consideration be given to small entities
affected by federal regulations. The RFA was amended in 1996 by SBREFA to strengthen
the RFA's analytical and procedural requirements. Prior to enactment of SBREFA, EPA
exceeded the requirements of the RFA by requiring the preparation of a regulatory flexibility
analysis for every rule that would have any impact, no matter how minor, on any number, no
matter how small, of small entities. Under SBREFA, however, the Agency decided to
implement the RFA as written and to require a regulatory flexibility analysis only for rules
that will have a significant impact on a substantial number of small entities. In practical
terms, the amount of analysis of impacts to small entities has not changed, for SBREFA
required EPA to increase involvement of small entities in the rulemaking process.
This section investigates characteristics of businesses and government entities that
are likely to install new combustion turbines affected by this rule and provides a preliminary
screening-level analysis to assist in determining whether this rule is likely to impose a
significant impact on a substantial number of the small businesses within this industry.
The screening-level analysis employed here is a "sales test," which computes the
annualized compliance costs as a share of sales/revenue for existing companies/government
entities. Existing companies/government entities with combustion turbines are used to
provide insights into future companies/government entities that are likely to install new
turbines that are affected by the regulation.
8-1
-------
8.1 Identifying Small Businesses
As described in Section 3 of this report, the Agency has projected that approximately
355 new combustion turbines will begin operation during the next 5-years. Approximately
10 sources would be required to comply with the NOX emission standard for the Gas Turbine
NSPS by applying add-on controls, as mentioned earlier in this report (Chapter 3). However,
as also mentioned earlier in this report, these 10 new turbines will already be required to
install add-on controls to meet NOx reductions under the PSD/NSR programs. The only
requirements on them due to this NSPS will be initial performance testing, fuel sampling,
monitoring and recordkeeping, and reporting. No existing combustion turbines will be
affected by the regulation. However, because it is not possible to project specific companies
or government organizations that will purchase combustion turbines in the future, the small
entity screening analysis for the combustion turbine rule is based on the evaluation of
existing owners of combustion turbines. It is assumed that the existing size and ownership
distribution of combustion turbines contained in the Inventory Database is representative of
the future growth in new combustion turbines. The remainder of this section presents cost
and sales information on small companies and government organizations that own existing
combustion turbines of 1 MW or greater.
8.2 Screening-Level Analysis
Based on the Inventory Database and Small Business Administration (SBA)
definitions, 29 small entities own 51 units, which are located at 35 facilities.11 The 51 units
owned by small entities represent approximately 2.5 percent of the 2,072 units in the
Inventory Database with valid capacity information. This implies that approximately 1 out
of the 10 new affected units will be owned by a small entity. Based on our previous
research, the 29 small entities have an average revenue (sales) of approximately $80 million.
We compared the average unit compliance costs ($3.4/10 = $0.34 million) with the average
sales value and for a typical small entities and calculated the cost to sales ratio for the
potentially affected small entity is 0.3 percent.
"Public and private electric service providers are defined as small if their annual generation is less than 4
million kWh. Local government entities that own combustion turbines are defined as small if the city
population is fewer than 50,000. In the manufacturing sector, companies are defined as small if the total
employment of the parent company is fewer than 500.
8-1
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8.3 Assessment
The RFA generally requires an agency to prepare a regulatory flexibility analysis of
any rule subject to notice and comment rulemaking requirements under the Administrative
Procedure Act or any other statute unless the agency certifies that the rule will not have a
significant economic impact on a substantial number of small entities. Small entities include
small businesses, small organizations, and small governmental jurisdictions.
For purposes of assessing the impacts of today's rule on small entities, small entity is
defined as:
• a small business whose parent company has fewer than 100 or 1,000 employees,
depending on size definition for the affected NAICS code, or fewer than 4 billion
kW-hr per year of electricity usage;
• a small governmental jurisdiction that is a government of a city, county, town,
school district, or special district with a population of fewer than 50,000; and
• a small organization that is any not-for-profit enterprise, which is independently
owned and operated and is not dominant in its field.
It should be noted that small entities in one three-digit NAICS codes are affected by this rule,
and the small business definition applied to this industry by NAICS code is that listed in the
SBA size standards (13 CFR 121).
The economic impacts of the NSPS are expected to be insignificant. In addition,
since there is only one small entity affected by this rule, there is no significant impact
(economic) to a substantial number of small entities (or SISNOSE).
8-2
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REFERENCES
1998-99 GTWHandbook. "Turnkey Combined Cycle Plant Budget Price Levels." Fairfield,
CT: Pequot Pub. Pgs 19-26.
Alpha-Gamma Technologies, Inc. October 21, 2004. "Cost Impact of Proposed NSPS for
Stationary Combustion Turbines." Memorandum to Jaime Pagan, EPA OAQPS BSD
Combustion Group from Melanie Taylor, Alpha-Gamma Technologies, Inc.
Berger, Bill D. and Kenneth E. Anderson. 1978. Modern Petroleum: A Basic Primer of the
Industry. Tulsa, OK: The Petroleum Publishing Co.
Cliburn, J.K. 2001. "Local Governments Turn to Municipal Aggregation." Public Power
Magazine. (January-February).
Conces, Elaine. 2000. "Hoover's Online—Energy Industry Snapshot." As obtained on
April 18, 2000. .
Dahl, Carol A., and Thomas E. Duggan. 1996. "U.S. Energy Product Supply Elasticities: A
Survey and Application to the U.S. Oil Market." Resource and Application
Economics 18:243-263.
Edison Electric Institute (EEI). 1998. Statistical Yearbook of the Electric Utility Industry
1997. November. Washington, DC.
Edison Electric Institute (EEI). 1999. "The Rise of the Power Marketer."
. As obtained on August 11,
1999.
General Electric Corporation. GE Power Plants. . As obtained on
Novembers, 1999.
Haltmaier, Susan. 1998. "Electricity Production and Sales." In U.S. Industry & Trade
Outlook '98, DRI/McGraw-Hill, Standard & Poor's, and U.S. Department of
Commerce/international Trade Administration. New York: McGraw-Hill, pp. 5-1 to
5-9.
Hay, Nelson E., ed. 1988. Guide to Natural Gas Cogeneration. Lilburn, GA: The Fairmont
Press, Inc.
R-l
-------
Heil, Scott F., Ed. 1998. Ward's Business Directory of U.S. Private and Public Companies
1998, Volume 5. Detroit, MI: Gale Research Inc.
Hogman, William W. 1989. "World Oil Price Projections: A Sensitivity Analysis."
Prepared pursuant to the Harvard-Japan World Oil Market Study. Cambridge, MA:
Energy Environmental Policy Center, John F. Kennedy School of Government,
Harvard University.
Hoover's Incorporated. 1998. Hoover's Company Profiles. Austin, TX: Hoover's
Incorporated, .
Industrial Combustion Coordinated Rulemaking (ICCR). 1998. Data/Information Submitted
to the Coordinating Committee at the Final Meeting of the Industrial Combustion
Coordinated Rulemaking Federal Advisory Committee. EPA Docket Numbers
A-94-63, II-K-4b2 through -4b5. Research Triangle Park, North Carolina.
September 16-17.
Lillis, Kevin. 1998. "Crude Petroleum and Natural Gas." In U.S. Industry and Trade
Outlook '98. New York: DRI/McGraw-Hill, Standard & Poor's, and U.S.
Department of Commerce/International Trade Administration, pp. 3-1 to 3-8.
Natural Gas Supply Association (NGSA) et al. 2000a. "Transportation of Natural Gas."
. As obtained on March 22, 2000.
Natural Gas Supply Association (NGSA) et al. 2000b. "Storage of Natural Gas."
. As obtained on March 22, 2000.
Natural Gas Supply Association (NGSA) et al. 2000c. "Natural Gas Production."
. As obtained on March 22, 2000.
Office of Pipeline Safety (OPS), U.S. Department of Transportation. 2000. "Annual
Mileage Totals: Transmission & Distribution." . As obtained on March 22, 2000.
Resource Data International. 1999. "PMA Online Top 25 Power Marketer Rankings."
Power Marketers Online Magazine,
As obtained on August 11, 1999.
Reuters News Service. November 10, 1999. "EIA Sees Cheaper Power, Rising Carbon,
Less Nukes." Reuters News Service.
R-2
-------
Taylor, Melanie. May 17, 2000. Memorandum: Cost-Effectiveness Strategies of Above-
the-Floor MACT Options for Existing Stationary Combustion Turbines. To: Sinis
Roy, EPA/OAQPS/ESD/Combustion Group.
Seimens Westinghouse. August 31, 1999. Presentation.
Siemens. Fossil Power Generation. . As
obtained on November 3, 1999.
Tussing, Arlon R., and Bob Tippee. 1995. The Natural Gas Industry: Evolution, Structure,
and Economics. 2nd Edition. Tulsa, OK: Perm Well Publishing Company.
U.S. Department of Commerce, Bureau of the Census. 1995a. 1992 Census of Mineral
Industries, Industry Series: Crude Petroleum and Natural Gas. MIC92-I-13A.
Washington, DC: U.S. Department of Commerce.
U.S. Department of Commerce, Bureau of the Census. 1995b. 1992 Census of Mineral
Industries, Industry Series: Natural Gas Liquids. MIC92-I-13B. Washington, DC:
U.S. Department of Commerce.
U.S. Department of Commerce, Bureau of the Census. 1995c. 1992 Census of Mineral
Industries, Industry Series: Oil and Gas Field Services. MIC92-I-13C. Washington,
DC: U.S. Department of Commerce.
U.S. Department of Commerce, Bureau of the Census. 1999a. 1997 Economic Census,
Mining, Industry Series: Crude Petroleum and Natural Gas Extraction. EC97N-
2111A. Washington, DC: U.S. Department of Commerce.
U.S. Department of Commerce, Bureau of the Census. 1999b. 1997 Economic Census,
Mining, Industry Series: Natural Gas Liquid Extraction. EC97N-2111 b.
Washington, DC: U.S. Department of Commerce.
U.S. Department of Commerce, Bureau of the Census. 1999c. 1997 Economic Census,
Mining, Industry Series: Drilling Oil and Gas Wells. EC97N-2131A. Washington,
DC: U.S. Department of Commerce.
U.S. Department of Commerce, Bureau of the Census. 1999d. 1997 Economic Census,
Mining, Industry Series: Support Activities for Oil and Gas Operations. EC97N-
213 IB. Washington, DC: U.S. Department of Commerce.
R-3
-------
U.S. Department of Commerce, Bureau of the Census. 2000. 1997 Economic Census,
Transportation and Warehousing: Geographic Area Series. EC97T48A-US.
Washington, DC: Government Printing Office.
U.S. Department of Energy, Energy Information Administration (EIA). 1996a. The
Changing Structure of the Electric Power Industry: An Update. DOE/EIA-05 62(96).
Washington, DC: U.S. Department of Energy.
U.S. Department of Energy, Energy Information Administration (EIA). 1996b. Electric
Power Annual 1995. Volumes I and II. DOE/EIA-0348(95)/1. Washington, DC:
U.S. Department of Energy.
U.S. Department of Energy, Energy Information Administration (EIA). 1997. Financial
Statistics of Major U.S. Investor-Owned Electric Utilities, 1996. Washington, DC:
U.S. Department of Energy.
U.S. Department of Energy, Energy Information Administration (EIA). 1998a. Financial
Statistics of Major Publicly Owned Electric Utilities, 1997. Washington, DC: U.S.
Department of Energy.
U.S. Department of Energy, Energy Information Administration (EIA). 1998b. The
Changing Structure of the Electric Power Industry: Selected Issues, 1998.
DOE/EIA-0562(98). Washington, DC: U.S. Department of Energy.
U.S. Department of Energy, Energy Information Administration (EIA). January 1998c.
Model Documentation Report: Industrial Sector Demand Module of the National
Energy Modeling System. DOE/EIA-M064(98). Washington, DC: U.S. Department
of Energy.
U.S. Department of Energy, Energy Information Administration (EIA). "Annual Energy
Outlook 1999—Market Trend—Electricity." . As accessed November 15, 1999a.
U.S. Department of Energy, Energy Information Administration (EIA), Office of Integrated
Analysis and Forecasting. "Competitive Electricity Price Projections."
. As obtained on November 15,
1999b.
U.S. Department of Energy, Energy Information Administration (EIA). 1999c. Electric
Power Annual, 1998. Volumes I and II. Washington, DC: U.S. Department of
Energy.
R-4
-------
U.S. Department of Energy, Energy Information Administration (EIA). 1999d. Natural Gas
1998: Issues and Trends. Washington, DC: U.S. Department of Energy.
U.S. Department of Energy, Energy Information Administration (EIA). 1999e. Natural Gas
Annual 1998. Washington, DC: U.S. Department of Energy.
U.S. Department of Energy, Energy Information Administration (EIA). 1999f. Petroleum
Supply Annual 1998, Volume I. Washington DC: U.S. Department of Energy.
U.S. Department of Energy, Energy Information Administration (EIA). 1999g. The
Changing Structure of the Electric Power Industry 1999: Mergers and Other
Corporate Combinations. Washington, DC: U.S. Department of Energy.
U.S. Department of Energy, Energy Information Administration (EIA). 1999h. U.S. Crude
Oil, Natural Gas, and Natural Gas Liquids Reserves 1998 Annual Report.
Washington, DC: U.S. Department of Energy.
U.S. Department of Energy, Energy Information Administration (EIA). 2000a. Electric
Power Annual 1999, Volume II. DOE/EIA-0348(99)/2. Washington, DC: U.S.
Department of Energy.
U.S. Department of Energy, Energy Information Administration. 2000b. Issues in Midterm
Analysis and Forecasting 1999—Table 1.
. As obtained on May 8, 2000.
U.S. Department of Energy, Energy Information Administration (EIA). "Supplement Tables
to the AEO 2000." . As
obtained on June 20, 2001.
U.S. Environmental Protection Agency. 1999a. Economic Analysis Resource Document.
Research Triangle Park, NC: Office of Air Quality Planning and Standards.
U.S. Environmental Protection Agency. 1999b. EPA Office of Compliance Sector Notebook
Project: Profile of the Oil and Gas Extraction Industry. Washington, DC: U.S.
Environmental Protection Agency.
Whelan, Michael. 1998. "Improving Compressor Station Performance: Getting at the Heart
of the Matter." .
Zimmerman, M.B. 1977. "Modeling Depletion in the Mineral Industry: The Case of Coal."
The Bell Journal of Economics 8(2):41-65.
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APPENDIX A
OVERVIEW OF THE MARKET MODEL
To develop estimates of the economic impacts on society resulting from the
regulation, the Agency developed a computational model using a framework that is
consistent with economic analyses performed for other rules. This approach employs
standard microeconomic concepts to model behavioral responses expected to occur
with the regulation. This appendix describes the spreadsheet model in detail and
discusses how the Agency
• characterized the supply and demand in the energy markets,
• characterized supply and demand responses in industrial and commercial
markets,
• introduced a policy "shock" into the electricity market by using control
cost-induced shifts in the supply functions of affected supply segments
(new and existing sources),
• introduced indirect shifts in market supply functions resulting from
changes in energy prices
• used a solution algorithm to determine a new with-regulation equilibrium
in each market.
A.I Energy Markets
The operational model includes five energy markets: coal, electricity (base load
energy), electricity (peak power), natural gas, and petroleum. The following sections
describe supply and demand equations the Agency developed to characterize these
markets. The data source for the price and quantity data used to calibrate the model
is the Department of Energy's Supplemental Tables to the Annual Energy Outlook
2000 (DOE, EIA, 2001).
A. 1.1 Supply Side Modeling
The Agency modeled the existing market supply of energy markets (Qsi) using a
single representative supplier with an upward-sloping supply curve. The Cobb-
Douglas (CD) function specification is
A-7
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Qs.= Aj-
where
Qg. = the supply of energy product i,
Aj = a parameter that calibrates the supply equation to replicate the
estimated 2005 level of production (Btu),
Pi = the 2005 ($/Btu) market price for product i, and
c; = direct compliance costs (electricity markets only). Supply
shifts were computed and reported in Section 6, Table 6-2.
n
V ct-Ap. = indirect effects of changes in input prices, where a is the fuel
i= 1
share, i indexes the energy market. The fuel share is allowed
to vary using a fuel switching rule using cross-price elasticities
of demand between energy sources, as described in Section 5
of the report.
esi = the domestic supply elasticity for product i.
For the electricity markets, new supply sources are characterized with a constant
marginal cost (supply) curve. In baseline, these units are willing to supply their
generation capacity at the baseline market price (P0i). With regulation, affected
sources are willing to supply their generation capacity if the new price (P1;) exceeds
costs (baseline + direct + indirect):
n
pii * PV Ci + I ttsApJ (A.2)
A.1.2 Demand Side Modeling
Market demand in the energy markets (QDi) is expressed as the sum of the energy,
residential, transportation, industrial, and commercial sectors:
-------
QDi = I qDij , (A3)
j=i
where i indexes the energy market and j indexes the consuming sector. The Agency modeled
the residential, and transportation sectors as single representative demanders using a
simple Cobb Douglas specification:
qDi = AiPi^ , (A-4)
where p is the market price, r\ is an assumed demand elasticity (actual values are presented in
Section 5, Table 5-2), and A is a demand parameter. In contrast, the energy,
industrial and commercial sectors demand is modeled as a derived demand resulting
from the production/consumption choices in agricultural, energy, mining,
manufacturing, and service industries. Changes in energy demand for these
industries respond to changes in output and fuel switching that occurs in response to
changes in relative energy prices projected in the energy markets. For each sector,
energy demand is expressed as follows:
qDijl = (1 + %AQDj) • (qDijo) • FSW (A.5)
where % is demand for energy, QD is output in the final product or service market, FSW is a
factor generated by the iuel switching algorithm, i indexes the energy market, j
indexes the market. The subscripts 0 and 1 represent baseline and with regulation
conditions, respectively.
A.2 Industrial and Commercial Markets
Given data limitations associated with the scope of potentially affected industrial and
commercial markets, EPA used an alternative approach to estimate the relative
changes in price and quantities. These measures are used to compute change in
economic welfare as described in Section A.4.
A. 2.1 Compute Percentage Change in Market Price
First, we computed the change in production costs resulting from changes in the
market price of fuels (determined in the energy markets):
A-9
-------
n
%Ac: = y a-Ap. , (A.6)
J i=l
where a is the fuel share,12 i indexes the energy market, and j indexes the industrial or
commercial market. We use the results from equation A.6 and the market supply and
demand elasticities to compute the change in market price:
%APj = %ACj- —2— (A>7)
A.2.2 Compute Percentage Change in Market Quantity
Using the percentage change in the price calculated in Equation A.7 and assumptions
regarding the market demand elasticity, the relative change in quantity was
computed. For example, in a market where the demand elasticity is assumed to be -1
(i.e., unitary), a 1 percent increase in price results in a 1 percent decrease in quantity.
This change was then input into equation A. 5 to determine energy demand.
A.3 With-Regulation Market Equilibrium Determination
Market adjustments can be conceptualized as an interactive feedback process. Supply
segments face increased production costs as a result of the rule and are willing to
supply smaller quantities at the baseline price. This reduction in market supply leads
to an increase in the market price that all producers and consumers face, which leads
to further responses by producers and consumers and thus new market prices, and so
on. The new with-regulation equilibrium is the result of a series of iterations in
which price is adjusted and producers and consumers respond, until a set of stable
market prices arises where total market supply equals market demand (i.e., Qs = QD)
in each market. Market price adjustment takes place based on a price revision rule
that adjusts price upward (downward) by a given percentage in response to excess
demand (excess supply).
The algorithm for determining with-regulation equilibria can be summarized by
seven recursive steps:
12The fuel share is allowed to vary using a fuel switching rule using cross-price elasticities of demand between
energy sources, as described in Section 5.
A-10
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1. Impose the control costs on electricity supply segments, thereby affecting
their supply decisions.
2. Recalculate the market supply in the energy markets. Excess demand
exists.
3. Determine the new energy prices via a price revision rule.
4. Recalculate energy market supply.
5. Account for fuel switching given new energy prices. Solve for new
equilibrium in final product and service market.
6. Compute energy demand.
7. Compare supply and demand in energy markets. If equilibrium conditions
are not satisfied, go to Step 3, resulting in anew set of energy prices.
Repeat until equilibrium conditions are satisfied (i.e., the ratio of supply to
demand is arbitrarily close to one).
A.4 Computing Social Costs
In the energy markets, consumers(residential and transportation) and producer
surplus were calculated using standard methods based on the price and quantity
before and after regulation. In the industrial and commercial markets, however, there
is no easily defined price or quantity due to the wide variety of products that fall
under each sector (i.e. NAICs code). Therefore, methods of calculating consumer
and producer surplus are defined based on relative changes in price and quantity and
total industry sales rather than on the price and quantity directly. The following
sections describe how we derive welfare estimates for these markets.
A.4.1 Change in Consumer Surplus
If price and quantities were available, a linear approximation of the change in
consumer surplus can be calculated using the following formula:
ACS = -[(AP) Q0 -0.5(AQ) (AP)], (A.8)
where Q0 denotes the baseline quantity. Given the model only estimates relative changes in
price and quantity for each industrial/commercial market, changes in consumer
surplus were calculated using these data and total revenue by NAICS code as shown
below:
A-5
-------
ACS = -[(AP) Q, - 0.5 (AQ) (AP)] (P, (},)/(?, Q,)
ACS = -[%AP - 0.5 (%AP) (%AQ)] (P, Q,). (A.9)
A. 4.2 Change in Producer Surplus
If price and quantities were available, a linear approximation could also be used to
compute the change in producer surplus:
APS —[((CC/QO - AP)(Q! - AQ)]+ 0.5 [(CC/Q, - AP) (AQ)], (A. 10)
where CC/Q] equals the per-unit "cost-shifter" of the regulation. Again, we transform this
equation into one that relies only on percentage changes in price and quantity, total
revenue,13 and compliance costs:
APS = - [((CC/Q,) - AP)(Q1 - AQ)]+ 0.5 [((CC/Q,) - AP)(AQ)](P1 (},)/(?, Q,)
APS = - [(% cost shift - %AP)(1 - %AQ)+ 0.5 (% cost shift - %AP )(%AQ)][P1 Q,]
APS = - [% cost shift - %AP ][1 - 0.5(%AQ)][TR], (A. 11)
"Multiplying price and quantity in an industry yields total industry revenue. The U.S. Census Bureau provides
shipment data for the NAICs codes included in the economic model.
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APPENDIX B
ASSUMPTIONS AND SENSITIVITY ANALYSIS
In developing the economic model to estimate the impacts of the stationary
combustion turbine NSPS, several assumptions were necessary to make the model
operational. This appendix lists and explains the major model assumptions and
describes their potential impact on the analysis results. Sensitivity analyses are
presented for numeric assumptions.
Assumption: The domestic markets for energy are perfectly competitive.
Explanation: Assuming that the markets for energy are perfectly competitive implies that
individual producers are not capable of unilaterally affecting the prices they receive
for their products. Under perfect competition, firms that raise their price above the
competitive price are unable to sell at that higher price because they are a small share
of the market and consumers can easily buy from one of a multitude of other firms
that are selling at the competitive price level. Given the relatively homogeneous
nature of individual energy products (petroleum, coal, natural gas, electricity), the
assumption of perfect competition at the national level seems to be appropriate.
Possible Impact: If energy markets were in fact imperfectly competitive, implying that
individual producers can exercise market power and thus affect the prices they
receive for their products, then the economic model would understate possible
increases in the price of energy due to the regulation as well as the social costs of the
regulation. Under imperfect competition, energy producers would be able to pass
along more of the costs of the regulation to consumers; thus, consumer surplus losses
would be greater, and producer surplus losses would be smaller in the energy
markets.
Assumption: Base load energy and peak power represent 80 percent and 20 percent,
respectively, of the total cost of electricity production.
Explanation: With deregulation, it is increasingly common for base load energy and peak
power to be traded as different commodities. This economic model segments the
electricity market into these separate markets. However, no production cost or sales
data are currently available to partition the electricity market into base load and peak
B-l
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power markets. The 80/20 percent was obtained from discussions with industry
experts.
Sensitivity Analysis: Table B-l shows how estimated economic impacts change as the share
of base load versus peak power costs varies.
Table B-l. Sensitivity Analysis: Base Load and Peak Power Markets' Share of
Electricity Production Costs ($106)
Base Load = 70% Base Load = 80% Base Load = 90%
Peak = 30% Peak = 20% Peak = 10%
Change in producer
surplus
Change in consumer
surplus
Change in social welfare
213
-215
-2
208
-209
-2
203
-204
-2
Assumption: The elasticity of supply in the base load and peak power electricity
markets for existing sources is approximately 0.75 and 0.38, respectively.
Explanation: The price elasticity of supply in the electricity markets represents the
behavioral responses from existing sources to changes in the price of electricity.
However, there is no consensus on estimates of the price elasticity of supply for
electricity. This is in part because, under traditional regulation, the electric utility
industry had a mandate to serve all its customers and utilities were compensated on a
rate-based rate of return. As a result, the market concept of supply elasticity was not
the driving force in utilities' capital investment decisions. This has changed under
deregulation. The market price for electricity has become the determining factor in
decisions to retire older units or to make higher cost units available to the market.
Sensitivity Analysis: Table B-2 shows how the economic impact estimates vary as the
elasticity of supply in the electricity markets varies.
B-2
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Table B-2. Sensitivity Analysis: Elasticity of Supply in the Electricity Markets
Change in producer surplus
Change in consumer
surplus
Change in social welfare
ES = -25%
235
-237
-2
Base Case
208
-209
-2
ES = + 25%
185
-187
-2
Assumption: The domestic markets for final products and services are all
perfectly competitive.
Explanation: Assuming that these markets are perfectly competitive implies that the
producers of these products are unable to unilaterally affect the prices they receive for
their products. Because the industries used in this analysis are aggregated across a
large number of individual producers, it is a reasonable assumption that the individual
producers have a very small share of industry sales and cannot individually influence
the price of output from that industry.
Possible Impact: If these product markets were in fact imperfectly competitive, implying
that individual producers can exercise market power and thus affect the prices they
receive for their products, then the economic model would understate possible
increases in the price of final products due to the regulation as well as the social costs
of the regulation. Under imperfect competition, producers would be able to pass
along more of the costs of the regulation to consumers; thus, consumer surplus losses
would be greater, and producer surplus losses would be smaller in the final product
markets.
Assumption: The elasticity of supply in final product markets.
Explanation: The final product markets are modeled at the two-, and three-digit NAICS
codes level to operationalize the economic model. Because of the high level of
aggregation, elasticities of supply and demand estimates are not often available in the
literature. The elasticities of supply and demand in the final product markets
primarily determine the distribution of economic impacts between producers and
consumers.
Sensitivity Analysis: Table B-3 shows how the economic impact estimates vary as the
supply and demand elasticities in the final product markets vary.
B-3
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Table B-3. Sensitivity Analysis: Supply and Demand Elasticities in the Final Product
Markets
ES = -25% ES = Base Case ES = +25%
ED = +25% ED = Base Case ED = -25%
Change in producer surplus 185 208 231
Change in consumer surplus -187 -209 -233
Change in social welfare -2 -2 -2
B-4
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Assumption: The amount of energy (in terms of Btus) required to produce a unit of
output in the final product markets remains constant as output changes and
prices.
Explanation: The importance of this assumption is that when output in the final product
markets changes as a result of a change in energy prices, it is assumed that the
amount of fuel used changes in the same proportion as output, although the
distribution of fuel usage among fuel types may change due to fuel switching. This
change in the demand for fuels feeds into the energy markets and affects the
equilibrium price and quantity in the energy markets.
Possible Impact: For example, fuel usage per unit output may change if the price of energy
increases because of increased energy efficiency. National energy-efficiency trends
are included in the model through projected Btu consumption (i.e., Btu consumption
is projected to grow more slowly than output). However, if the regulation leads to
increased energy efficiency because of higher fuel prices, this will result in a smaller
economic impact than the model results presented in Section 6 indicate.
Assumption: Sensitivity to Fuel Switching.
Sensitivity Analysis: Table B-4 shows how the economic impact estimates vary as fuel-
switching is turned on or off in the model.
Table B-4. Sensitivity Analysis: Own- and Cross-Price Elasticities Used to Model Fuel
Switching
Base Case Without Fuel Switching
Change in producer surplus 208 207
Change in consumer surplus -209 -208
Change in social welfare -2 -2
B-5
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United States Office of Air Quality Planning and Standards Publication No. EPA-452/R-06-001
Environmental Protection Agency Health and Environmental Impacts Division February 2006
Research Triangle Park, NC
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