Report #:DOE/EIA-0554(2008)

Release date: June 2008

Next release date: March 2009

 Assumptions to the Annual Energy Outlook 2008

Introduction ........................................... 1

Macroeconomic Activity Module ................................ 13

International Energy Module .................................. 15

Residential Demand Module .................................. 21

Commercial Demand Module.................................. 31

Industrial Demand Module ................................... 43

Transportation Demand Module ................................ 59

Electricity Market Module .................................... 77

Oil and Gas Supply Module .................................. 97

Natural Gas Transmission and Distribution Module...................... 113

Petroleum Market Module ................................... 123

Coal Market Module ...................................... 135

Renewable Fuels Module ................................... 147

Appendix A: Handling of Federal and Selected State Legislation 

and Regulation In the Annual Energy Outlook ........................ 163

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 - DRAFT - 4/16/2008

 Contents

Introduction

This report presents the major assumptions of the National Energy Modeling System (NEMS) used to

generate the projections in the Annual Energy Outlook 20081 (AEO2008), including general features of the

model structure, assumptions concerning energy markets, and the key input data and parameters that are

the most significant in formulating the model results. Detailed documentation of the modeling system is

available in a series of documentation reports.2

The National Energy Modeling System

The projections in the AEO2008 were produced with the NEMS, which is developed and maintained by the

Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide

projections of domestic energy-economy markets in the long term and perform policy analyses requested by

decisionmakers in the White House, U.S. Congress, offices within the Department of Energy, including DOE

Program Offices, and other government agencies. The AEO projections are also used by analysts and

planners in other government agencies and outside organizations.

The time horizon of NEMS is approximately 25 years, the period in which the structure of the economy and

the nature of energy markets are sufficiently understood that it is possible to represent considerable

structural and regional detail. Because of the diverse nature of energy supply, demand, and conversion in

the United States, NEMS supports regional modeling and analysis in order to represent the regional

differences in energy markets, to provide policy impacts at the regional level, and to portray transportation

flows. The level of regional detail for the end-use demand modules is the nine Census divisions. Other

regional structures include production and consumption regions specific to oil, natural gas, and coal supply

and distribution, the North American Electric Reliability Council (NERC) regions and subregions for

electricity, and the Petroleum Administration for Defense Districts (PADDs) for refineries. Maps illustrating

the regional formats used in each module are included in this report. Only selected regional results are

presented in the AEO2008, which predominately focuses on the national results. Complete regional and

detailed results are available on the EIA Forecasts and Analyses Home Page.

(http://www.eia.doe.gov/oiaf/aeo/index.html) 

For each fuel and consuming sector, NEMS balances the energy supply and demand, accounting for the

economic competition between the various energy fuels and sources. NEMS is organized and implemented

as a modular system (Figure 1). The modules represent each of the fuel supply markets, conversion sectors, 

and end-use consumption sectors of the energy system. NEMS also includes a macroeconomic and an

international module. The primary flows of information between each of these modules are the delivered

prices of energy to the end user and the quantities consumed by product, region, and sector. The delivered

prices of fuel encompass all the activities necessary to produce, import, and transport fuels to the end user.

The information flows also include other data such as economic activity, domestic production, and

international petroleum supply availability. 

The integrating module of NEMS controls the execution of each of the component modules. To facilitate

modularity, the components do not pass information to each other directly but communicate through a

central data storage location. This modular design provides the capability to execute modules individually,

thus allowing decentralized development of the system and independent analysis and testing of individual

modules. This modularity allows use of the methodology and level of detail most appropriate for each energy

sector. NEMS solves by calling each supply, conversion, and end-use demand module in sequence until the

delivered prices of energy and the quantities demanded have converged within tolerance, thus achieving an

economic equilibrium of supply and demand in the consuming sectors. Solution is reached annually through

the projection horizon. Other variables are also evaluated for convergence such as petroleum product

imports, crude oil imports, and several macroeconomic indicators. 

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 1

Report #:DOE/EIA-0554(2008)

Release date: May 2008

Next release date: March 2009
Each NEMS component also represents the impact and cost of Federal legislation and regulation that affect

the sector and reports key emissions. NEMS generally reflects all current legislation and regulation that are

defined sufficiently to be modeled as of December 31, 2008, such as the Energy Independence and Security

Act of 2007, the Energy Policy Act of 2005, the Working Families Tax Relief Act of 2004, and the America

Jobs Creation Act of 2004, and the costs of compliance with regulations such as the Mobile Source Air

Toxics rule released by the Environmental Protection Agency on February 9, 2007 that establishes controls

on gasoline, passenger vehicles, and portable fuel containers designed to significantly reduce emissions of

benzene and other hazardous air pollutants. The NEMS components also reflect selected State legislation

and regulations where implementing regulations are clear. The potential impacts of pending or proposed

Federal and State legislation, regulations, or standards—or of sections of legislation that have been enacted

but that require funds or implementing regulations that have not been provided or specified—are not

reflected in NEMS. A list of the specific Federal and selected State legislation and regulations included in the

AEO, including how they are incorporated, is provided in Appendix A.

Component Modules

The component modules of NEMS represent the individual supply, demand, and conversion sectors of

domestic energy markets and also include international and macroeconomic modules. In general, the

modules interact through values representing the prices of energy delivered to the consuming sectors and

the quantities of end-use energy consumption. This section provides brief summaries of each of the

modules.

Macroeconomic Activity Module

The Macroeconomic Activity Module (MAM) provides a set of macroeconomic drivers to the energy

modules, and there is a macroeconomic feedback mechanism within NEMS. Key macroeconomic variables

used in the energy modules include gross domestic product (GDP), disposable income, value of industrial

shipments, new housing starts, new light-duty vehicle sales, interest rates, and employment. The module

uses the following models from Global Insight, Inc. (GII): Macroeconomic Model of the U.S. Economy,

National Industry Model, and National Employment Model. In addition, EIA has constructed a Regional

Economic and Industry Model to project regional economic drivers and a Commercial Floorspace Model to

project 13 floorspace types in 9 Census divisions. The accounting framework for industrial value of

shipments uses the North American Industry Classification System (NAICS).

2 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Oil and Gas

Supply Module

Natural Gas

Transmission

and Distribution 

Module

Coal Market

Module

Renewable

Fuels Module

Supply

Residential

Demand Module

Commercial

Demand

Module

Transportation

Demand Module

Industrial

Demand Module

Demand

Electricity

Market

Module

Petroleum

Market

Module

Conversion

Macroeconomic

Activity

Module

International

Energy

Module

Integrating

Module

Figure 1. National Energy Modeling System

Source: Energy Information Administration, Office of Integrated Analysis and Forecasting.
International Module

The International Module represents the response of world oil markets (supply and demand) to assumed

world oil prices. The results/outputs of the module are a set of crude oil and product supply curves that are

available to U.S. markets for each case/scenario analyzed. The petroleum import supply curves are made

available to U.S. markets through the Petroleum Market Module (PMM) of NEMS in the form of 5 categories

of imported crude oil and 17 international petroleum products, including supply curves for oxygenates and

unfinished oils. The supply-curve calculations are based on historical market data and a world oil

supply/demand balance, which is developed from reduced form models of international liquids supply and

demand (new to AEO2008), current investment trends in exploration and development, and long-term

resource economics for 221 countries/territories. The oil production estimates include both conventional and 

unconventional supply recovery technologies.

Residential and Commercial Demand Modules

The Residential Demand Module projects energy consumption in the residential sector by housing type and

end use, based on delivered energy prices, the menu of equipment available, the availability of renewable

sources of energy, and housing starts. The Commercial Demand Module projects energy consumption in

the commercial sector by building type and nonbuilding uses of energy and by category of end use, based on 

delivered prices of energy, availability of renewable sources of energy, and macroeconomic variables

representing interest rates and floorspace construction.

Both modules estimate the equipment stock for the major end-use services, incorporating assessments of

advanced technologies, including representations of renewable energy technologies and the effects of both

building shell and appliance standards, including the recently enacted provisions of the EISA2007. The

Commercial Demand Module incorporates combined heat and power (CHP) technology. The modules also

include projections of distributed generation. Both modules incorporate changes to “normal” heating and

cooling degree-days by Census division, based on a 10-year average and on State-level population

projections. The Residential Demand Module projects that the average square footage of both new

construction and existing structures increase based on trends in the size of new construction and the

remodeling of existing homes.

Industrial Demand Module

The Industrial Demand Module projects the consumption of energy for heat and power and for feedstocks

and raw materials in each of 21 industries, subject to the delivered prices of energy and macroeconomic

variables representing employment and the value of shipments for each industry. As noted in the description

of the Macroeconomic Activity Module, the value of shipments is based on NAICS. The industries are

classified into three groups—energy-intensive manufacturing, non-energy-intensive manufacturing, and

nonmanufacturing. Of the 8 energy-intensive industries, 7 are modeled in the Industrial Demand Module,

with components for boiler/steam/cogeneration, buildings, and process/assembly use of energy. Bulk

chemicals are further disaggregated to organic, inorganic, resins, and agricultural chemicals. A generalized

representation of cogeneration and a recycling component are also included. The use of energy for

petroleum refining is modeled in the PMM, and the projected consumption is included in the industrial totals.

Transportation Demand Module

The Transportation Demand Module projects consumption of fuels in the transportation sector, including

petroleum products, electricity, methanol, ethanol, compressed natural gas, and hydrogen, by transportation 

mode, vehicle vintage, and size class, subject to delivered prices of energy fuels and macroeconomic

variables representing disposable personal income, GDP, population, interest rates, and industrial

shipments. Fleet vehicles are represented separately to allow analysis of the Energy Policy Act of 1992

(EPACT1992) and other legislation and legislative proposals. EPACT2005 is used to assess the impact of

tax credits on the purchase of hybrid gas-electric, alternative-fuel, and fuel-cell vehicles. The module also

includes a component to assess the penetration of alternative-fuel vehicles. The CAFE and biofuel

representation in the module reflect the provisions in the EISA2007.

The air transportation component explicitly represents air travel in domestic and non U.S. markets and

includes the industry practice of parking aircraft in both domestic and international markets to reduce

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 3
operating costs and the movement of aircraft from passenger to cargo markets as aircraft ages.

3 For air

freight shipments, the model represents regional fuel use in narrow-body and wide-body aircraft. An

infrastructure constraint limits overall growth in passenger and freight air travel to levels commensurate with

industry-projected infrastructure expansion and capacity growth.

Electricity Market Module

The Electricity Market Module (EMM) represents generation, transmission, and pricing of electricity, subject

to delivered prices for coal, petroleum products, natural gas, and biofuels; costs of generation by all

generation plants, including capital costs; macroeconomic variables for costs of capital and domestic

investment; enforced environmental emissions laws and regulations; and electricity load shapes and

demand. There are three primary submodules—capacity planning, fuel dispatching, and finance and pricing.

Nonutility generation, distributed generation, and transmission and trade are modeled in the planning and

dispatching submodules. The levelized cost of uranium fuel for nuclear generation is incorporated directly in

the EMM.

All specifically identified CAAA90 compliance options that have been promulgated by the EPA are explicitly

represented in the capacity expansion and dispatch decisions; those that have not been promulgated (e.g.,

fine particulate proposals) are not incorporated. All financial incentives for power generation expansion and

dispatch specifically identified in EPACT2005 have been implemented. Several States, primarily in the

Northeast, have recently enacted air emission regulations that affect the electricity generation sector. Where 

firm State compliance plans have been announced, regulations are represented in AEO2008.

Renewable Fuels Module

The Renewable Fuels Module (RFM) includes submodules representing renewable resource supply and

technology input information for central-station, grid-connected electricity generation technologies, including 

conventional hydroelectricity, biomass (wood, energy crops, and biomass co-firing), geothermal, landfill gas, 

solar thermal electricity, solar photovoltaics (PV), and wind energy. The RFM contains renewable resource

supply estimates representing the regional opportunities for renewable energy development. Investment tax 

credits for renewable fuels are incorporated, as currently legislated in EPACT1992 and EPACT2005.

EPACT1992 provides a 10-percent tax credit for business investment in solar energy (thermal non-power

uses as well as power uses) and geothermal power; those credits have no expiration date. EPACT2005

increases the tax credit to 30 percent for solar energy systems installed before January 1, 2009.

Production tax credits for wind, geothermal, landfill gas, and some types of hydroelectric and biomass-fueled 

plants are also represented. They provide a tax credit of up to 1.9 cents per kilowatthour for electricity

produced in the first 10 years of plant operation. For AEO2008, new plants coming on line before January 1,

2009, are eligible to receive the credit.

Oil and Gas Supply Module

The Oil and Gas Supply Module (OGSM) represents domestic crude oil and natural gas supply within an

integrated framework that captures the interrelationships among the various sources of supply: onshore,

offshore, and Alaska by both conventional and unconventional techniques, including natural gas recovery

from coalbeds and low-permeability formations of sandstone and shale. The framework analyzes cash flow

and profitability to compute investment and drilling for each of the supply sources, based on the prices for

crude oil and natural gas, the domestic recoverable resource base, and the state of technology. Oil and gas

production functions are computed for 12 supply regions, including 3 offshore and 3 Alaskan regions. The

module also represents foreign sources of natural gas, including pipeline imports and exports to Canada and 

Mexico, and liquefied natural gas (LNG) imports and exports.

Crude oil production quantities are input to the Petroleum Market Module (PMM) in NEMS for conversion

and blending into refined petroleum products. Supply curves for natural gas are input to the Natural Gas

Transmission and Distribution Module (NGTDM) for use in determining natural gas prices and quantities.

International LNG supply sources and options for construction of new regasification terminals in Canada,

Mexico, and the United States as well as expansions of existing U.S. regasification terminals are

represented, based on the projected regional costs associated with international natural gas supply,

liquefaction, transportation, and regasification and world natural gas market conditions.

4 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008
Natural Gas Transmission and Distribution Module

The Natural Gas Transmission and Distribution Module (NGTDM) represents the transmission, distribution,

and pricing of natural gas, subject to end-use demand for natural gas and the availability of domestic natural

gas and natural gas traded on the international market. The module tracks the flows of natural gas and

determines the associated capacity expansion requirements in an aggregate pipeline network, connecting

the domestic and foreign supply regions with 12 demand regions. The flow of natural gas is determined for

both a peak and off-peak period in the year. Key components of pipeline and distributor tariffs are included in

separate pricing algorithms.

Petroleum Market Module

The Petroleum Market Module (PMM) projects prices of petroleum products, crude oil and product import

activity, and domestic refinery operations (including fuel consumption), subject to the demand for petroleum

products, the availability and price of imported petroleum, and the domestic production of crude oil, natural

gas liquids, and biofuels (ethanol, biodiesel, biobutanol, etc.). The module represents refining activities in

the five PADDs. It explicitly models the requirements of the EISA2007, the CAAA90, and the costs of

automotive fuels, such as conventional and reformulated gasoline, and includes biofuels production for

blending in gasoline and diesel

AEO2008 represents regulations that limit the sulfur content of all non-road and locomotive/marine diesel to

15 ppm by mid-2012. The module also reflects the renewable fuels standard (RFS) in the EISA2007 that

requires the use of 36 billion gallons per year of biofuels by 2022 with corn ethanol limited to 15 billon gallons

per year. Demand growth and regulatory changes necessitate capacity expansion for refinery processing

units. End-use prices are based on the marginal costs of production, plus markups representing product

marketing and distribution costs and State and Federal taxes.

4 Refinery capacity expansion at existing sites

is permitted in all five refining regions modeled.

Fuel ethanol and biodiesel are included in the PMM, because they are commonly blended into petroleum

products. The module allows ethanol blending into gasoline at 10 percent by volume or less (E10), as well as

E85, a blend of up to 85 percent ethanol by volume. Ethanol is produced primarily in the Midwest from corn or 

other starchy crops, and may also be produced from cellulosic material, such as switchgrass and poplar, in

the future. Biodiesel is produced from seed oil, imported palm oil, animal fats, or yellow grease (primarily,

recycled cooking oil).

Both domestic and imported ethanol count toward the RFS. Domestic ethanol production is modeled from

two feedstocks: corn and cellulosic materials. Corn-based ethanol plants are numerous (more than 100 in

operation, producing more than 5 billion gallons annually) and are based on a well-known technology that

converts sugar into ethanol. Ethanol from cellulosic sources is a new technology with no pilot plants in

operation. However, the U.S. Department of Energy has awarded grants (up to $385 million) in 2007 to

construct capacity totaling 147 million gallons per year. AEO2008 assumes that this capacity will be

operational in 2012. Imported ethanol may be produced from cane sugar or bagasse, the cellulosic

byproduct of sugar milling. The sources of ethanol are modeled to compete on an economic basis and to

meet the EISA2007 renewable fuels mandate.

Fuels produced by gasification and Fischer-Tropsch synthesis are modeled in the PMM, based on their

economics relative to competing feedstocks and products. The three processes modeled are coal-to-liquids 

(CTL), gas-to-liquids (GTL), and biomass-to-liquids (BTL). CTL facilities are likely to be built at locations

close to coal supply and water sources, where liquid products and surplus electricity could also be

distributed to nearby demand regions. GTL facilities may be built in Alaska but would compete with the

Alaska Natural Gas Transportation System for available natural gas resources. BTL facilities are likely to be

built where there are large supplies of biomass such as crop residue and forestry waste. Since the BTL

process uses cellulosic feedstocks, it is also modeled as a choice to meet the EISA2007 cellulosic biofuels

requirement.

Coal Market Module

The Coal Market Module (CMM) simulates mining, transportation, and pricing of coal, subject to end-use

demand for coal differentiated by heat and sulfur content. U.S. coal production is represented in the CMM by

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 5
40 separate supply curves—differentiated by region, mine type, coal rank, and sulfur content. The coal

supply curves include a response to capacity utilization of mines, mining capacity, labor productivity, and

factor input costs (mining equipment, mining labor, and fuel requirements). Projections of U.S. coal

distribution are determined by minimizing the cost of coal supplied, given coal demands by demand region

and sector, accounting for minemouth prices, transportation costs, existing coal supply contracts, and sulfur

and mercury allowance costs. Over the projection horizon, coal transportation costs in the CMM are

projected to vary in response to changes in railroad productivity and the cost of rail transportation equipment

and diesel fuel.

The CMM produces projections of U.S. steam and metallurgical coal exports and imports, in the context of

world coal trade. The CMM determines the pattern of world coal trade flows that minimizes the production

and transportation costs of meeting a specified set of regional world coal import demands, subject to

constraints on export capacities and trade flows. The international coal market component of the module

computes trade in 3 types of coal for 17 export and 20 import regions. U.S. coal production and distribution

are computed for 14 supply and 14 demand regions.

Cases for the Annual Energy Outlook 2008

In preparing projections for the AEO2008, EIA evaluated a wide range of trends and issues that could have

major implications for U.S. energy markets between now and 2030. Besides the reference case, the

AEO2008 presents detailed results for four alternative cases that differ from each other due to fundamental

assumptions concerning the domestic economy and world oil market conditions. These alternative cases

include the following:

• Economic Growth - In the reference case, real GDP grows at an average annual rate of 2.4 percent

from 2006 through 2030, supported by a 1.9 percent per year growth in productivity in nonfarm

business and a 0.9 percent per year growth in nonfarm employment. In the high economic growth

case, real GDP is projected to increase by 3.0 percent per year, with productivity and nonfarm

employment growing at 2.4 percent and 1.2 percent per year, respectively. In the low economic

growth case, the average annual growth in GDP, productivity and nonfarm employment is 1.8, 1.5

and 0.5 percent, respectively.

• Price Cases – For purposes of the AEO2008, the world oil price is defined by the price of light,

low-sulfur crude oil delivered in Cushing, Oklahoma. In the reference case, world oil prices decline

gradually from current levels to $57 per barrel in 2016 ($68 per barrel in nominal terms), as expanded

investment in exploration and development brings new supplies to world markets. After 2016, real

prices begin to rise as demand continues to grow and higher cost supplies are brought to market. In

2030, the average real price of crude oil is $70 per barrel in 2006 dollars, or about $113 per barrel in

nominal dollars. The reference case represents EIA’s current judgment about the most likely

behavior of key OPEC members in the mid term. In the projection, OPEC countries increase

production at a rate that keeps their market share of world liquids production at approximately 40

percent through 2030. The low and high price cases define a wide range of potential price paths,

which in 2030 span from $43 to $117 per barrel in real dollars. These cases reflect differences in the

assumptions about world energy resource availability, production costs, and changes in OPEC

behavior. The low price case assumes greater world crude oil and natural gas resources that are less

expensive to produce and a future market where all oil and natural gas production becomes more

competitive and plentiful than the reference case. The high price cases assumes that world crude oil

and natural gas resources, including OPEC’s, are lower and require greater cost to produce than

assumed in the reference case.

In addition tothesefour cases, and the reference case, 31 additionalalternativecasespresentedin Table1

that explore the impact of changing key assumptions on individual sectors.

6 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008
Many of the side cases were designed to examine the impacts of varying key assumptions for individual

modules or a subset of the NEMS modules, and thus the full market consequences, such as the

consumption or price impacts, are not captured. In a fully integrated run, the impacts would tend to narrow

the range of the differences from the reference case. For example, the best available technology side case in 

the residential demand assumes that all future equipment purchases are made from a selection of the most

efficient technologies available in a particular year. In a fully integrated NEMS run, the lower resulting fuel

consumption would have the effect of lowering the market prices of those fuels with the concomitant impact

of increasing economic growth, thus stimulating some additional consumption. The results of single model or 

partially integrated cases should be considered the maximum range of the impacts that could occur with the

assumptions defined for the case.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 7

Case name Description Integration

mode

Reference Baseline economic growth ( 2.4 percent per year from 2006-2030), 

world oil price, and technology assumptions. Fully integrated

Early Release Reference Released in 12/2007, excludes EISA2007 and other changes in

reference case.

 Fully integrated

Low Economic Growth Gross domestic product grows at an average annual rate of 1.8

percent from 2006 through 2030. Other assumptions are the

same as in the reference case.

 Fully integrated

High Economic Growth Gross domestic product grows at an average annual rate of 3.0

percent from 2006 through 2030. Other assumptions are the same 

as in the reference case. 

 Fully integrated

Low Price More optimistic assumptions for worldwide crude oil and natural

gas resources than in the reference case. World light, sweet crude 

oil prices are $43 per barrel in 2030, compared with $72 per barrel 

in the reference case (2006 dollars). Other assumptions are the

same as in the reference case.

Fully integrated

High Price More pessimistic assumptions for worldwide crude oil and natural

gas resources than in the reference case. World light, sweet crude 

oil prices are about $117 per barrel (2006 dollars) in 2030. Other

assumptions are the same as in the reference case.

 Fully integrated

Residential: 

2008 Technology

Future equipment purchases based on equipment available in

2008. Existing building shell efficiencies fixed at 2008 levels.

 With commercial

Residential: High 

Technology

Earlier availability, lower costs, and higher efficiencies assumed

for more advanced equipment. Building shell efficiencies for new

construction meet ENERGY STAR requirements after 2016.

 With commercial

Residential: Best 

Available Technology

Future equipment purchases and new building shells based on

most efficient technologies available by fuel. Building shell

efficiencies for new construction meet the criteria for most efficient

components after 2008.

 With commercial

Commercial: 

2008 Technology

Future equipment purchases based on equipment available in

2008. Building shell efficiencies fixed at 2008 levels.

 With residential

Commercial: 

HighTechnology

Earlier availability, lower costs, and higher efficiencies assumed

for more advanced equipment. Building shell efficiencies for new

and existing buildings increase by 8.75 and 6.25 percent,

respectively, from 2003 values by 2030.

With residential

Commercial Best 

Available Technology

Future equipment purchases based on most efficient technologies

available by fuel. Building shell efficiencies for new and existing

buildings increase by 10.5 and 7.5 percent, respectively, from

2003 values by 2030.

 With residential

Industrial: 2008 

Technology

Efficiency of plant and equipment fixed at 2008 levels. Standalone

Industrial:

High Technology

Earlier availability, lower costs, and higher efficiencies assumed

for more advanced equipment.

 Standalone

Transportation: 

High Technology

Reduced costs and improved efficiencies assumed for advanced

technologies. 

 Standalone

Table 1. Summary of AEO2008 Cases
8 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Case name Description Integration

mode

Electricity: Low Nuclear Cost New nuclear capacity assumed to have 10 percent lower capital

and operating costs in 2030 than in the reference case. 

 Fully Integrated

Electricity: High Nuclear Cost Costs for new nuclear technology are assumed not to improve

over time from 2006 levels in the reference case. 

 Fully Integrated

Electricity: Low Fossil 

Technology

Costs and efficiencies for advanced fossil-fired generating

technologies improve by 10 percent in 2030 from reference case 

values.

 Fully Integrated

Electricity: High Fossil 

Cost

New advanced fossil generating technologies assumed not to

improve over time from 2008. 

 Fully Integrated

Renewable Fuels: High

Renewable Cost

New renewable generating technologies assumed not to

improve over time from 2008.

Fully integrated

Renewable Fuels: Low

Renewable Cost

Levelized cost of energy for nonhydropower renewable 

generating technologies declines by 10 percent in 2030 from

reference case values.

Fully integrated

Oil and Gas: 

 Rapid Technology

Cost, finding rate, and success rate parameters adjusted 

for 50-percent more rapid improvement than in the

reference case. 

 Fully integrated

Oil and Gas: 

Slow Technology

Cost, finding rate, and success rate parameters adjusted 

for 50-percent slower improvement than in the reference 

case. 

 Fully integrated

Oil and Gas: High 

LNG Supply

LNG imports exogenously set to a factor times the 

reference case levels from 2010 forward, with remaining

assumptions from the reference case. The factor starts 

at 1.0 in 2010 and linearly increases to 3.0 by 2030. 

 Fully Integrated

Oil and Gas: Low 

LNG Supply

LNG imports help constant at 2009 levels, with remaining

assumptions from the reference case.

Fully Integrated

Oil and Gas: ANWR The Arctic National Wildlife Refuge in Alaska is opened to

Federal oil and natural gas leasing, with remaining 

assumptions from the reference case.

 Fully Integrated

Coal: Low Coal Cost Productivity for coal mining and coal transportation 

assumed to increase more rapidly than in the reference 

case. Coal mining wages, mine equipment, and coal

transportation equipment costs assumed to be lower 

than in the reference case.

 Fully Integrated

Coal: High Coal Cost Productivity for coal mining and coal transportation 

assumed to increase more slowly than in the reference 

case. Coal mining wages, mine equipment, and coal

transportation equipment costs assumed to be higher

than in the reference case.

 Fully integrated

Integrated 2008 

Technology

Combination of the residential, commercial, and industrial 

2008 technology cases, electricity high fossil cost case, 

high renewable cost case, and high nuclear cost case.

Fully integrated

Integrated High

Technology

Combination of the residential, commercial, industrial, and

transportation high technology cases, electricity low fossil 

cost case, low renewable cost case, and low nuclear cost 

case.

Fully integrated

Integrated Alternative

Weather Case

Assumes future weather resembles 30-year average, as

opposed to 10-year average.

Fully integrated

Low Energy Project Cost Recent cost increases are assumed to revert 

back to lower levels of a few years ago. Base costs for new

electric generating capacity decreases by 15 percent over 

ten years, then remain flat. Capital costs for oil and natural 

gas exploration and production fall back toward their pre-2003

levels over time. Refining costs are set to 2004 levels.

Fully integrated

Table 1. Summary of AEO2008 Cases (cont.)
Carbon Dioxide Emissions

Carbon dioxide emissions from energy use are dependent on the carbon content of the fossil fuel, the

fraction of the fuel consumed in combustion, and the consumption of that fuel. The product of the carbon

content at full combustion and the combustion fraction yields an adjusted carbon emission factor for each

fossil fuel. The emissions factors are expressed in millions of metric tons carbon dioxide emitted per

quadrillion Btu of energy use, or equivalently, in kilograms carbon dioxide per million Btu. The adjusted

emissions factors are multiplied by the energy consumption of the fossil fuel to arrive at the carbon dioxide

emissions projections.

For fuel uses of energy, the combustion fractions are assumed to be 1.00 in keeping with international

conventions.5 Previously, a small fraction of the carbon content of the fuel was assumed to remain

unoxidized. The carbon dioxide in nonfuel use of energy, such as for asphalt and petrochemical feedstocks,

is assumed to be sequestered in the product and not released to the atmosphere. For energy categories that 

are mixes of fuel and nonfuel uses, the combustion fractions are based on the proportion of fuel use. Any

carbon dioxide emitted by biogenic renewable sources, such as biomass and alcohols, is considered

balanced by the carbon dioxide sequestration that occurred in its creation. Therefore, following convention,

net emissions of carbon dioxide from biogenic renewable sources are taken as zero, and no emission

coefficient is reported. In calculating carbon dioxide emissions for motor gasoline, the direct emissions from

renewable blending stock (ethanol) is omitted. Similarly, direct emissions from biodiesel are omitted from

reported carbon dioxide emissions. Table 2 presents the assumed carbon dioxide coefficients at full

combustion, the combustion fractions, and the adjusted carbon dioxide emission factors used for AEO2008.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 9

Case name Description Integration

mode

High Energy Project Cost Recent cost increases are assumed to continue. Base costs for

new electric generating capacity increase throughout the

projection. Capital costs for oil and natural 

gas exploration and production activities remain at increased

levels as experienced since 2003. Refining costs increase 

from current costs.

Fully integrated

Limited Electricity 

Generation Supply

New coal plants are not built unless they include sequestration.

Other non-natural gas capacity sources are restricted to

reference case levels or assumed to have higher costs. Existing

nuclear units are assumed to have lower output than in the

reference.

Fully integrated

Limited Natural Gas

Supply

No Arctic natural gas pipelines are in operation by 2030. 

LNG import values are held constant at 2009 levels from 

2010 forward. Oil and natural gas resources are 15 

percent lower, and the technological progress is set to

half the rate of the reference case.

 Fully integrated

Combined Limited This case combines all the assumptions of the Limited

Electricity Generation Supply and Limited Natural

Natural Gas Supply cases.

 Fully integrated

Table 1. Summary of AEO2008 Cases (cont.)
10 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

 Fuel Type

Carbon Dioxide

 Coefficient 

at Full 

Combustion

Combustion

Fraction

Adjusted 

Emissions

Factor

Petroleum

Motor Gasoline (net of ethanol) 70.88 1.000 70.88

Liquefied Petroleum Gas

 Used as Fuel 63.03 1.000 62.72

 Used as Feedstock 61.64 0.200 12.31

Jet Fuel 70.88 1.000 70.88

Distillate Fuel (net of biodiesel) 73.15 1.000 73.15

Residual Fuel 78.80 1.000 78.80

Asphalt and Road Oil 75.61 0.000 0.00

Lubricants 74.21 0.500 37.11

Petrochemical Feedstocks 69.85 0.381 26.59

Kerosene 72.31 1.000 72.31

Petroleum Coke 102.12 0.860 87.82

Petroleum Still Gas 64.20 1.000 64.20

Other Industrial 74.43 1.000 74.43

Coal

Residential and Commercial 95.35 1.000 95.35

Metallurgical 93.71 1.000 93.71

Industrial Other 93.98 1.000 93.98

Electric Utility194.66 1.000 94.66

Natural Gas

Used as Fuel 53.06 1.000 53.06

Used as Feedstocks 53.06 0.517 27.44

Table 2. Carbon Dioxide Emission Factors

 (million metric tons carbon dioxide equivalent per quadrillion Btu)

1Emission factors for coal used for electricity generation are specified by coal supply region and types of coal, so the average carbon dioxide contents 

for coal varies throughout the projection. The 2006 average is 94.66.

Source: Energy Information Administration, Emissions of Greenhouse Gases in the United States 2006, DOE/EIA-0573(2006), (Washington, DC,

November 2006).
[1] Energy Information Administration, Annual Energy Outlook 2008 (AEO2008), DOE/EIA-0383(2008),

(Washington, DC, April 2008).

[2] NEMS documentation reports are available on the EIA Homepage (http://tonto.eia.doe.gov/reports/

reports_kindD.asp?type=model documentation). 

[3] Jet Information Services, Inc., World Jet Inventory Year-End 2006 (Utica, NY, March 2007); and personal 

communication from Stuart Miller (Jet Information Services). 

[4] For gasoline blended with ethanol, the tax credit of 51 cents (nominal) per gallon of ethanol is assumed to 

be available through 2010. It is assumed to expire after 2010 under current law.

[5] The Intergovernmental Panel on Climate Change 2006, 2006 IPCC Guidelines For National Greenhouse 

Gas Inventories, prepared by the National Greenhouse Gas Inventories Program, published: IGES, Japan,

2006.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 11

Notes and Sources

Macroeconomic Activity Module

The Macroeconomic Activity Module (MAM) represents the interaction between the U.S. economy as a

whole and energy markets. The rate of growth of the economy, measured by the growth in gross

domestic product (GDP) is a key determinant of the growth in demand for energy. Associated economic

factors, such as interest rates and disposable income, strongly influence various elements of the supply and

demand for energy. At the same time, reactions to energy markets by the aggregate economy, such as a

slowdown in economic growth resulting from increasing energy prices, are also reflected in this module. A

detailed description of the MAM is provided in the EIA publication, Model Documentation Report:

Macroeconomic Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065(2007),

(Washington, DC, January 2007).

Key Assumptions

The output of the U.S. economy, measured by GDP, is expected to increase by 2.4 percent between 2006

and 2030 in the reference case. Two key factors help explain the growth in GDP: the growth rate of nonfarm

employment and the rate of productivity change associated with employment. As Table 3 indicates, for the

Reference Case GDP growth slows from 2.5 percent between 2010 and 2020, to 2.4 percent between 2020

and 2030. In the near term from 2006 through 2010, the growth in nonfarm employment is low at 1.1percent

compared with 2.4 percent in the second half of the 1990s, while the economy is expected to experiencing 

productivity growth of 1.7 percent. Over the projection period, nonfarm employment is expected to grow by

0.9 percent per year. Nonfarm employment, a measure of demand for nonfarm labor, is generally more

volatile than the labor force, a measure of labor supply. The latter depends upon the projection of

population and labor force participation rate. The Census Bureau’s middle series population projection is 

used as a basis for population growth for the AEO2008. Total population is expected to grow by 0.8

percent per year between 2006 and 2030, and the share of population over 65 is expected to increase over

time. However, the share of the labor force in the population over 65 is also projected to increase in the

projection period. 

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 13

 Assumptions 2006-2010 2010-2020 2020-2030 2006-2010

GDP (Billion Chain-Weighted $2000)

 High Growth 3.1 3.0 2.9 3.0

 Reference 2.4 2.5 2.4 2.4

 Low Growth 1.7 2.0 1.7 1.8

Nonfarm Employment

 High Growth 2.0 1.2 1.0 1.2

 Reference 1.1 0.8 0.8 0.9

 Low Growth 0.2 0.4 0.6 0.5

Productivity

 High Growth 2.1 2.4 2.4 2.4

 Reference 1.7 2.0 1.9 1.9

 Low Growth 1.5 1.6 1.4 1.5

Table 3. Growth in Gross Domestic Product, Nonfarm Employmemt and Productivity

(Percent per Year)

Source: Energy Information Administration, AEO20068 National Energy Modeling System runs: AEO2008.d030208f;

hm2008.d031608a; and lm2008.d031608a.

Report #:DOE/EIA-0554(2008)

Release date:June 2008

Next release date: March 2009
To achieve the reference case’s long-run 2.4 percent economic growth, there is an anticipated steady

growth in labor productivity. The improvement in labor productivity reflects the positive effects of a growing

capital stock as well as technological change over time. Nonfarm labor productivity is expected to remain

between 1.9 and 2.0 percent for the remainder of the projection period from 2006 through 2030. Business

fixed investment as a share of nominal GDP is expected to grow over the last 10 years of the projection. The 

resulting growth in the capital stock and the technology base of that capital stock helps to sustain productivity 

growth of 1.9 percent from the 2005 to 2030.

To reflect the uncertainty in projection of economic growth, the AEO2007 uses high and low economic

growth cases along with the reference case to project the possible impacts on energy markets. The high

economic growth case incorporates higher population, labor force and productivity growth rates than the

reference case. Due to the higher productivity gains, inflation and interest rates are lower compared to the

reference case. Investment, disposable income, and industrial production are increased. Economic output

is projected to increase by 3.0 percent per year between 2006 and 2030. The low economic growth case

assumes lower population, labor force, and productivity gains, with resulting higher prices and interest rates

and lower industrial output growth. In the low economic growth case, economic output is expected to

increase by 1.8 percent per year over the projection horizon. 

14 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 
International Energy Module

The International Energy Module (IEM) performs two tasks in all NEMS runs. First, the module reads

exogenously global and U.S.A. petroleum liquids supply and demand curves (1 curve per year; 2008-2030;

approximated, isoelastic fit to previous NEMS results). These quantities are not modeled directly in NEMS. 

Previous versions of the IEM adjusted these quantities after reading in initial values. In an attempt to more

closely integrate the AEO2008 with IEO2007 and the STEO some functionality was removed from IEM while

a new algorithm was implemented. Based on the difference between U.S. total petroleum liquids production

(consumption) and the expected U.S. total liquids production (consumption) at the current WTI price, curves

for global petroleum liquids consumption (production) were adjusted for each year. According to previous

operations, a new WTI price path was generated. An exogenous oil supply module, Generate World Oil

Balances (GWOB), was also used in IEM to provide annual regional (country) level production detail for

conventional and unconventional liquids.

The second task of the IEM is to interact with the PMM module during runs to determine changes in the WTI

price and the supply prices of crude oils and petroleum products for import to the United States in response

to changes in U.S. import requirements. As a result of the interaction with PMM, this module also determines 

new values for oil production in the Middle East OPEC region, along with a report for crude oil, light and

heavy refined products imports by source. 

Key Assumptions

The level of oil production by countries in the Organization of Petroleum Exporting Countries (OPEC) is a key 

factor influencing the world oil price projections incorporated into AEO2008. Non-OPEC production,

worldwide regional economic growth rates and the associated regional demand for oil are additional factors

affecting the world oil price. 

The world oil price is the annual average U.S. cost of imported low-sulfur light crude oil in PADD2. For the

low, reference, and high oil price cases, prices reach $42, $70 and $118 per barrel in 2030, respectively, in

2006 dollars. The reference case assumes that OPEC producers will continue to demonstrate a disciplined

production approach. The low oil price case reflects a market where all oil production becomes more

competitive and plentiful. The high oil price case could result from a more cohesive and market-assertive

OPEC whose long-term goal might be to maintain a constant market share. The three price scenarios are

shown in Figure 2.

OPEC oil production is assumed to increase throughout the reference case projection, making OPEC the

primary source for satisfying the worldwide increase in oil consumption expected over the projection period

(Figure 3). OPEC is assumed to be the source of additional production because its member nations hold a

major portion of the world’s total reserves—exceeding 927 billion barrels, about 70 percent of the world’s

estimated total, at the end of 2006.1

The reference case values for OPEC production are shown in Figure 3. Ecuador is not included in OPEC in

AEO2008 because of the late announcement. Iraq oil production is assumed to not return to pre-conflict

volumes until 2010. By 2030, Iraq is expected to increase production capacity to more than 4.6 million

barrels per day with likely investment help from foreign sources. Non-OPEC liquids production is expected

to increase by 1.1 percent per year over the projection period, as advances in both exploration and extraction 

technologies result in an upward trend. The non-OPEC production path for the reference case is shown in

Figure 4.

The non-U.S. oil production projections in the AEO2008 begin with country-level assumptions regarding oil

resources. These resource estimates are taken in part from the USGS World Petroleum Assessment of

2000 as well as from PennWell Publishing Company Oil and Gas Journal, summary of which is shown in

Table 4.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 15

Report #:DOE/EIA-0554(2008)

Release date: June 2008

Next release date: March 2009
16 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 

0

25

50

75

100

125

1995 2000 2005 2010 2015 2020 2025 2030

High Low Reference Case

History Projections

Figure 2. World Oil Prices in Three Cases, 1995-2030

2006 Dollars per Barrel

Source: AEO2008 National Energy Modeling System runs AEO2008.D030208F, LP2008.D031608A, and

HP2008.D031808A.

0

10

20

30

40

50

1995 2000 2005 2010 2015 2020 2025 2030

History Projections

Figure 3. OPEC Total Liquids Production in the Reference Case, 1995-2030

Millions barrels per Day

OPEC = Organization of Petroleum Exporting Countries.

Source: Energy Information Administration. AEO2008 National Energy Modeling System run AEO2008.D030208F.
The reference case growth rates for GDP for various regions in the world are shown in Table 5. Except for

the United States, the GDP growth rate assumptions for non U.S. country/regions are taken from IEO2007. 

The values for growth in oil demand in the International Energy Module, which depend upon the oil price

levels as well as GDP growth rates, are shown in Table 6 for the reference case by regions.

Petroleum products imports are represented in the projections through a series of curves for each of the five

Petroleum Administration for Defense Districts (PADDs). Curves are provided for seventeen products:

traditional gasoline (including aviation), reformulated gasoline, conventional and reformulated gasoline

blending stocks for oxygenated blending (CBOB, RBOB), traditional distillate fuel, low-sulfur heating oil, ultra 

low-sulfur diesel fuel, high and low-sulfur residual fuel, jet fuel (including naphtha jet), liquefied petroleum

gases, petrochemical feedstocks, unfinished oils (resid, naphtha, heavy gas oil), methanol, MTBE, and other 

petroleum products. The curves are derived from AEO2007 curves and analysis of price differential

between marker crude oils and refined petroleum productions imported into the U.S. 

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 17

0

10

20

30

40

50

60

70

80

1995 2000 2005 2010 2015 2020 2025 2030

History Projections

Figure 4. Non-OPEC Total Liquids Production in the Reference Case, 1995-2030

Millions barrels per Day

OPEC = Organization of Petroleum Exporting Countries.

Source: Energy Information Administration. AEO2008 National Energy Modeling System run AEO2008.D030208F.
18 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 

 Region Proved Oil Reserves

Western Hemisphere 321.1 

Western‘Europe 13.2

Asia-Pacific 34.3

Eastern Europe and F.S.U. 100

Middle East 748.3

Africa 114.8

Total World 1331.7

Total OPEC 927.5

Table 4. Worldwide Oil Reserves as of January 1, 2008

(Billion Barrels)

Source: PennWell Corporation, Oil and Gas Journal, Vol 103, No 47 (Dec 19, 2005).

 Region Average Annual Percentage Change

OECD 2.3 

OECD North America 2.6

OECD Europe 2.3

OECD Asia 1.9

Non-OECD 5.3

Non-OECD Europe and Eurasia 4.3

Non-OECD Asia 5.8

Middle East 4.2

Africa 4.9

Central and South America 3.9

Total World 4.0

Table 5. Average Annual Real Gross Domestic Product Rates, 2004-2030 (2000 Purchasing PowerParity

 Weights and Prices)

Source: For the U.S., Energy Informatin Administration, National Energy Modeling System run AEO2008.D030208F; for other countries, Global

Insight, Inc., World Overview (Lexington, MA, January 2007)

 Region Oil Demand Growth

OECD 0.3% 

OECD North America 0.4%

OECD Europe 0.1%

OECD Asia 0.4%

Non-OECD 2.3%

Non-OECD Europe and Eurasia 1.1%

Non-OECD Asia 2.8%

Middle East 2.2%

Africa 2.2%

Central and South America 2.3%

Total World 1.2%

Table 6. Average Annual Growth Rates for Total Liquids Demand in the Reference Case, 2004-2030

(Percent per Year)

Source: Energy Information Administration, AEO2008 National Energy Modeling System run: AEO2008.D030208F; and IEO2007 System for the

Analysis of Global Energy Markets (2007).
[1] PennWell Corporation, Oil and Gas Journal, Vol. 103, No. 47 (December 19, 2005). 

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 19

Notes and Sources

Residential Demand Module

The NEMS Residential Demand Module projects future residential sector energy requirements based on

projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming

equipment. The Residential Demand Module projections begin with a base year estimate of the housing

stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy

consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds

new housing units to the stock, determines the equipment installed in new units, retires existing housing

units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts 

by type (single-family, multifamily and mobile homes) and Census Division and prices for each energy

source for each of the nine Census Divisions (see Figure 5). The Residential Demand Module also requires

projections of available equipment and their installed costs over the projection horizon. Over time,

equipment efficiency tends to increase because of general technological advances and also because of

Federal and/or state efficiency standards. As energy prices and available equipment changes over the

projection horizon, the module includes projected changes to the type and efficiency of equipment

purchased as well as projected changes in the usage intensity of the equipment stock.

The end-use services for which equipment stocks are modeled include space conditioning (heating and

cooling), water heating, refrigeration, freezers, dishwashers, clothes washers, lighting, furnace fans, color

televisions, personal computers, cooking, clothes drying, ceiling fans, coffee makers, spas, home security

systems, microwave ovens, set-top boxes, home audio equipment, rechargeable electronics, and

VCR/DVDs. In addition to the major equipment-driven end-uses, the average energy consumption per

household is projected for other electric and nonelectric appliances. The module’s output includes number

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 21

Pacific

East South Central

South Atlantic

Middle

Atlantic

New

England

West

South

Central

West

North

Central East

North

Central

Mountain

AK

WA

MT

ID WY

NV

UT

CO

AZ

NM

TX

OK

IA

KS MO

IL

IN

KY

TN

MS AL

FL

GA

SC

NC

WV

PA NJ

MD

DE

NY

CT

VT ME

RI

MA

NH

VA

WI

MI

OH

NE

SD

ND MN

AR

LA

OR

CA

HI

Middle Atlantic

New England

East North Central

West North Central

Pacific

West South Central

East South Central

South Atlantic

Mountain

Figure 5. United States Census Divisions

Source:Energy Information Administration,Office of Integrated Analysis and Forecasting.

Report #:DOE/EIA-0554(2008)

Release date: June 2008

Next release date: March 2009
of households, equipment stock, average equipment efficiencies, and energy consumed by service, fuel,

and geographic location. The fuels represented are distillate fuel oil, liquefied petroleum gas, natural gas,

kerosene, electricity, wood, geothermal, coal, and solar energy.

One of the implicit assumptions embodied in the Residential Demand Module is that, through 2030, there will 

be no radical changes in technology or consumer behavior. No new regulations of efficiency beyond those

currently embodied in law or new government programs fostering efficiency improvements are assumed.

Technologies which have not gained widespread acceptance today will generally not achieve significant

penetration by 2030. Currently available technologies will evolve in both efficiency and cost. In general, at

the same efficiency level, future technologies will be less expensive than those available today in real dollar

terms. When choosing new or replacement technologies, consumers will behave similarly to the way they

now behave. The intensity of end-uses will change moderately in response to price changes. Electric end

uses will continue to expand, but at a decreasing rate.1

Key Assumptions

Housing Stock Submodule

An important determinant of future energy consumption is the projected number of households. Base year

estimates for 2005 are derived from the Energy Information Administration’s (EIA) Residential Energy

Consumption Survey (RECS) (Table 7). The projection for occupied households is done separately for each 

Census Division. It is based on the combination of the previous year’s surviving stock with projected housing 

starts provided by the NEMS Macroeconomic Activity Module. The housing stock submodule assumes a

constant survival rate (the percentage of households which are present in the current projection year, which

were also present in the preceding year) for each type of housing unit; 99.6 percent for single-family units,

99.9 percent for multifamily units, and 97.6 percent for mobile home units. Projected fuel consumption is

dependent not only on the projected number of housing units, but also on the type and geographic

distribution of the houses. The intensity of space heating energy use varies greatly across the various

climate zones in the United States. Also, fuel prevalence varies across the country—oil (distillate) is more

frequently used as a heating fuel in the New England and Middle Atlantic Census Divisions than in the rest of 

the country, while natural gas dominates in the Midwest. An example of differences by housing type is the

more prevalent use of liquefied petroleum gas in mobile homes relative to other housing types. 

Technology Choice Submodule

The key inputs for the Technology Choice Submodule are fuel prices by Census Division and characteristics

of available equipment (installed cost, maintenance cost, efficiency, and equipment life). Fuel prices are

determined by an equilibrium process which considers energy supplies and demands and are passed to this 

submodule from the integrating module of NEMS. Energy price, combined with equipment UEC (which is a

function of efficiency), determines the operating costs of equipment. Equipment characteristics are

22 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Census Division Single-family Units Multiple family Units Mobile Home Total Units

New England 3,392,944 1,899,981 173,072 5,465,996

Mid Atlantic 10,077,231 4,784,686 254,610 15,116,527

East North Central 14,091,216 3,233,929 424,271 17,749,416

West North Central 6,107,582 1,406,214 340,759 7,854,555

South Atlantic 14,823,560 4,910,592 1,962,563 21,696,715

East South Central 5,438,660 729,591 724,503 6,892,754

West South Central 8,892,255 2,120,675 1,109,901 12,122,831

Mountain 5,680,398 951,482 922,976 7,554,856

Pacific 11,150,078 4,456,348 1,030,541 16,636,967

United States 79,653.923 24,493,498 6,943,196 111,090,617

Table 7. 2005 Households

Source: U.S. Department of Energy, Energy Information Administration, 2005 Residential Energy Consumption Survey (preliminary data).
exogenous to the model and are modified to reflect both Federal standards and anticipated changes in the

market place. Table 8 lists capital cost and efficiency for selected residential appliances for the years 2007

and 2020.

Table 9 provides the cost and performance parameters for representative distributed generation

technologies. The AEO2008 model also incorporates endogenous “learning” for the residential distributed

generation technologies, allowing for declining technology costs as shipments increase. For fuel cell and

photovoltaic systems, learning parameter assumptions for the AEO2008 reference case result in a 13

percent reduction in capital costs each time the number of units shipped to the buildings sectors (residential

and commercial) doubles.

The Residential Demand Module projects equipment purchases based on a nested choice methodology.

The first stage of the choice methodology determines the fuel and technology to be used, the second stage

determines the efficiency of the selected equipment type. The equipment choices for cooling, water heating, 

and cooking are linked to the space heating choice for new construction. Technology and fuel choice for

replacement equipment uses a nested methodology similar to that for new construction, but includes (in

addition to the capital and installation costs of the equipment) explicit costs for technology switching (e.g.,

costs for installing gas lines if switching from electricity or oil to gas, or costs for adding ductwork if switching

from electric resistance heat to central heating types). Also, for replacements, there is no linking of fuel

choice for water heating and cooking as is done for new construction. Technology switching upon

replacement is allowed for space heating, air conditioning, water heating, cooking and clothes drying. 

Once the fuel and technology choice for a particular end use is determined, the second stage of the choice

methodology determines efficiency. In any given year, there are several available prototypes of varying

efficiency (minimum standard, medium low, medium high and highest efficiency). Efficiency choice is based 

on a functional form and coefficients which give greater or lesser importance to the installed capital cost (first 

cost) versus the operating cost. Generally, within a technology class, the higher the first cost, the lower the

operating cost. For new construction, efficiency choices are made based on the costs of both the heating

and cooling equipment and the building shell characteristics.

The parameters for the second stage efficiency choice are calibrated to the most recently available shipment 

data for the major residential appliances. Shipment efficiency data are obtained from industry associations

which monitor shipments such as the Association of Home Appliance Manufacturers. Because of this

calibration procedure, the model allows the relative importance of first cost versus operating cost to vary by

general technology and fuel type (e.g., natural gas furnace, electric heat pump, electric central air

conditioner, etc.). Once the model is calibrated, it is possible to calculate (approximately) the apparent

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 23

 

Equipment Type

Relative

Performance1

2007

Installed Cost

 ($2007)2

 

Efficiency3

2020 

Installed Cost 

 ($2004)2 Efficiency3

 Approximate

 Hurdle

 Rate

Electric Heat Pump Minimum

Best

$3,800

$7,500

13.0

17.0

$3,800

$6,700

13.0

20.0

15% 

Natural Gas Furnace Minimum

Best

$1,500

$3,050

0.80

0.96

$1,500

$2,700

0.80

0.96

15%

Room Air Conditioner Minimum

Best

$310

$925

9.8

11.7

$310

$875

9.8

12.0

140%

Central Air Conditioner Minimum

Best

$3,000

$5,700

13.0

21.0

$3,000

$5,750

13.0

23.0

15%

Refrigerator (23.9 cubic ft

 in adjusted volume)

Minimum

Best

$550

$950

510

417

$550

$1000

510

417

19%

Electric Water Heater Minimum

Best

$400

$1,530

0.90

2.4

$400

$1,700

0.90

2.4

30%

Solar Water Heater N/A $3,500 2.0 $4,500 2.0 30%

Table 8. Installed Cost and Efficiency Ratings of Selected Equipment

1Minimum performance refers to the lowest efficiency equipment available. Best refers to the highest efficiency equipment available.

2

Installed costs are given in 2007 dollars in the original source document.

3Efficiency measurements vary by equipment type. Electric heat pumps and central air conditioners are rated for cooling performance using the

Seasonal Energy Efficiency Ratio (SEER); natural gas furnaces are based on Annual Fuel Utilization Efficiency; room air conditioners are based on 

Energy Efficiency Ratio (EER); refrigerators are based on kilowatt-hours per year; and water heaters are based on Energy Factor (delivered Btu

divided by input Btu).

Source: Navigant Consulting, EIA Technology Forecast Updates, Reference Number 20070831.1September 2007.
discount rates based on the relative weight given to the operating cost savings versus the weight given to the 

higher cost of more efficient equipment. Hurdle rates in excess of 30 percent are common in the Residential

Demand Module. The prevalence of such high apparent hurdle rates by consumers has led to the notion of

the “efficiency gap” that is, there are many investments that could be made that provide rates of return in

excess of residential borrowing rates (15 to 20 percent for example). There are several studies which

document instances of apparent high discount rates.2 Once equipment efficiencies for a technology and fuel 

are determined, the installed efficiency for its entire stock is calculated.

Appliance Stock Submodule

The Appliance Stock Submodule is an accounting framework which tracks the quantity and average

efficiency of equipment by end use, technology, and fuel. It separately tracks equipment requirements for

new construction and existing housing units. For existing units, this module calculates equipment which

survives from previous years, allows certain end uses to further penetrate into the existing housing stock and 

calculates the total number of units required for replacement and further penetration. Air conditioning and

clothes drying are the two end uses not considered to be “fully penetrated.” 

Once a piece of equipment enters into the stock, an accounting of its remaining life is begun. It is assumed

that all appliances survive a minimum number of years after installation. A fraction of appliances are

removed from the stock once they have survived for the minimum number of years. Between the minimum

and maximum life expectancy, all appliances retire based on a linear decay function. For example, if an

appliance has a minimum life of 5 years and a maximum life of 15 years, one tenth of the units (1 divided by

15 minus 5) are retired in each of years 6 through 15. It is further assumed that, when a house is retired from

the stock, all of the equipment contained in that house retires as well; i.e., there is no secondhand market for

this equipment. The assumptions concerning equipment lives are given in Table 10.

24 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Technology Type Year of

 Introduction

Average

Generating

 Capacity

 (kW)

Electrical

Efficiency

Combined

Efficiency

 (Elec. +

 Thermal)

Installed

 Capital

 Cost

 ($2005 per

 KW of

 Capacity)1

Service

Life

 Years

Solar Photovoltaic

2007 2.0 0.16 N/A $6,924 30

2010 2.5 0.18 N/A $6,944 30

2015 3.0 0.20 N/A $5,310 30

2020 3.0 0.22 N/A $4,627 30

2030 4.0 0.25 N/A $3,840 30

Fuel Cell 2007 10 0.308 0.697 $8,897 20

2010 10 0.320 0.699 $7,802 20

2015 10 0.335 0.705 $6,160 20

2020 10 0.350 0.712 $4,517 20

2030 10 0.360 0.723 $2,669 20

Table 9. Capital Cost and Performance Parameters of Selected Residential Distributed Generation 

 Technologies

1

Installed costs are given in 2005 dollars in the original source document.

Source: Solar Technology Specifications: Solar Energy Industries Association, Our Solar Power Future - The U.S. Photovoltaic Industry Roadmap

through 2030 and Beyond (SEIA, September 2004). Fuel cells: Discovery Insights, LLC, "Installed Costs for Small CHP Systems - Estimates and

Projections" (April 2005). 
Fuel Consumption Submodule

Energy consumption is calculated by multiplying the vintage equipment stocks by their respective UECs.

The UECs include adjustments for the average efficiency of the stock vintages, short term price elasticity of

demand and “rebound” effects on usage (see discussion below), the size of new construction relative to the

existing stock, people per household and shell efficiency and weather effects (space heating and cooling).

The various levels of aggregated consumption (consumption by fuel, by service, etc.) are derived from these 

detailed equipment-specific calculations.

Equipment Efficiency

The average energy consumption of a particular technology is initially based on estimates derived from

RECS 2001. Appliance efficiency is either derived from a long history of shipment data (e.g., the efficiency of 

conventional air-source heat pumps) or assumed based on engineering information concerning typical

installed equipment (e.g., the efficiency of ground-source heat pumps). When the average efficiency is

computed from shipment data, shipments going back as far as 20 to 30 years are combined with

assumptions concerning equipment lifetimes. This allows for not only an average efficiency to be

calculated, but also for equipment retirements to be vintaged—older equipment tends to be lower in

efficiency and also tends to get retired before newer, more efficient equipment. Once equipment is retired,

the Appliance Stock and Technology Choice Modules determine the efficiency of the replacement

equipment. It is often the case that the retired equipment is replaced by substantially more efficient

equipment.

As the stock efficiency changes over the simulation interval, energy consumption decreases in inverse

proportion to efficiency. Also, as efficiency increases, the efficiency rebound effect (discussed below) will

offset some of the reductions in energy consumption by increased demand for the end-use service. For

example, if the stock average for electric heat pumps is now 10 percent more efficient than in 2001, then all

else constant (weather, real energy prices, shell efficiency, etc.), energy consumption per heat pump would

average about only 9 percent less. 

Adjusting for the Size of Housing Units

Information derived from RECS 2001 indicates that new construction (post-1990) is on average roughly 26

percent larger than the existing stock of housing. Estimates for the size of each new home built in the

projection period vary by type and region, and are determined by a log-trend projection based on historical

data from the Bureau of the Census.3 For existing structures, it is assumed that about 1 percent of

households that existed in 2005 add about 600 square feet to the heated floor space in each year of the

projection period.4 The energy consumption for space heating, air conditioning, and lighting is assumed to

increase with the square footage of the structure. This results in an increase in the average size of the

housing stock from 1,802 to 2,046 square feet from 2005 through 2030.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 25

 Equipment Minimum Life Maximum Life

Heat Pumps 7 21

Central Forced-Air Furnaces 10 25

Hydronic Space Heaters 20 30

Room Air Conditioners 8 16

Central Air Conditioners 7 21

Gas Water Heaters 4 14

Electric Water Heaters 5 22

Cooking Stoves 16 21

Clothes Dryers 11 20

Refrigerators 7 26

Freezers 11 31

Table 10. Minimum and Maximum Life Expectancies of Equipment

Source: Lawrence Berkeley Laboratory, Baseline Data for the Residential Sector and Development of a Residential Forecasting Database, May

1994, and analysis of RECS 2001 data.
Adjusting for Weather and Climate

Weather in any given year always includes short-term deviations from the expected longer-term average (or

climate). Recognition of the effect of weather on space heating and air conditioning is necessary to avoid

inadvertently projecting abnormal weather conditions into the future. In the residential module, adjustments

are made to space heating and air conditioning UECs by Census Division by their respective heating and

cooling degree-days (HDD and CDD). A 10 percent increase in HDD would increase space heating

consumption by 18 percent over what it would have otherwise been. Over the projection period, the

residential module uses a 10-year average for heating and cooling degree - days by Census Division,

adjusted by projections in state population shifts.

Short-Term Price Effect and Efficiency Rebound

It is assumed that energy consumption for a given end-use service is affected by the marginal cost of

providing that service. That is, all else equal, a change in the price of a fuel will have an opposite, but less

than proportional, effect on fuel consumption. The current value for the short-term elasticity parameter is

-0.15.5 This value implies that for a 1 percent increase in the price of a fuel, there will be a corresponding

decrease in energy consumption of -0.15 percent. Another way of affecting the marginal cost of providing a

service is through altered equipment efficiency. For example, a 10 percent increase in efficiency will reduce

the cost of providing the end-use service by 10 percent. Based on the short-term efficiency rebound

parameter, the demand for the service will rise by 1.5 percent (-10 percent multiplied by -0.15). Only space

heating and cooling are assumed to be affected by both elasticities and the efficiency rebound effect. 

Shell Efficiency

The shell integrity of the building envelope is an important determinant of the heating and cooling load for

each type of household. In the NEMS Residential Demand Module, the shell integrity is represented by an

index, which changes over time to reflect improvements in the building shell. The shell integrity index is

dimensioned by vintage of house, type of house, fuel type, service (heating and cooling), and Census

Division. The age, type, location, and type of heating fuel are important factors in determining the level of

shell integrity. Housing units which heat with electricity tend to have less air infiltration rates than homes that

use other fuels. The age of homes are classified by new (post-2005) and existing. Existing homes are

characterized by the RECS 2005 survey and are assigned a shell index value based on the mix of homes

that exist in the base year (2005). The improvement over time in the shell integrity of these homes is a

function of two factors—an assumed annual efficiency improvement and improvements made when real fuel 

prices increase (no price-related adjustment is made when fuel prices fall). For new construction, building

shell efficiency is determined by the relative costs and energy bill savings for several levels of heating and

cooling equipment, in conjunction with the building shell attributes. The packages represented in NEMS

range from homes that meet the International Energy Conservation Code (IECC)6 to homes that exceed the

IECC by 50 percent. Shell efficiency in new homes would increase over time if energy prices rise, or the cost

of more efficient equipment falls.

Legislation and Regulations

Energy Independence and Security Act of 2007 (EISA 2007)

EISA 2007 contains several provisions that impact projections of residential energy use. Standards for

general service incandescent light bulbs are phased-in over 2012-2014, with a more restrictive standard

specified in 2020. It is estimated that these standards require 29 percent less watts per bulb in the first

phase-in, increasing to 67 percent in 2020. EISA also updates the dehumidifier standard specified in

EPACT 2005, resulting in 7 percent increase in electricity savings, relative to the EPACT 2005 requirement. 

New efficiency standards for external power supplies are set for July 1, 2008, reducing electricity use in both

the active and no-load modes. Standards are also set for boilers (September 2012) and dishwashers

(January 2010). Lastly, DOE is instructed to create standards for manufactured housing, requiring

compliance to the latest International Energy Conservation Code (IECC) by the end of 2011.

26 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008
Energy Policy Act of 2005 (EPACT05)

The passage of the EPACT05 in August 2005 provides additional minimum efficiency standards for

residential equipment and provides tax credits to producers and purchasers of energy efficient equipment

and builders of energy efficient homes. The standards contained in EPACT05 include: 190 watt maximum

for torchiere lamps in 2006; Dehumidifier standards for 2007 and 2012; and ceiling fan light kit standards in

2007. Manufactured homes that are 30 percent better than the latest code, a $1000 tax credit can be

claimed in 2006 and 2007. Likewise, builders of homes that are 50 percent better than code can claim a

$2000 credit over the same period. The builder tax credits and production tax credits are assumed to be

passed through to the consumer in the form of lower purchase cost. EPACT05 includes production tax

credits for energy efficient refrigerators, dishwashers, and clothes washers in 2006 and 2007, with dollar

amounts varying by type of appliance and level of efficiency met, subject to annual caps. Consumers can

claim a 10 percent tax credit in 2006 and 2007 for several types of appliances specified by EPACT05,

including: Energy efficient gas, propane, or oil furnaces or boilers, energy efficient central air conditioners,

air and ground source heat pumps, hot water heaters, and windows. Lastly, consumers can claim a 30

percent tax credit in 2006 and 2007 for purchases of solar PV, solar water heaters, and fuel cells, subject to a 

cap.

National Appliance Energy Conservation Act of 1987

The Technology Choice Submodule incorporates equipment standards established by the National

Appliance Energy Conservation Act of 1987 (NAECA). Some of the NAECA standards implemented in the

module include: a Seasonal Energy Efficiency Rating (SEER) of 13.0 for central air conditioners and heat

pumps; an Annual Fuel Utilization Efficiency (energy output over energy input) of 0.78 for oil and gas

furnaces; an Efficiency Factor of 0.90 for electric water heaters; and refrigerator standards that set

consumption limits to 510 kilowatt-hours per year in 2002.

Residential Alternative Cases

Technology Cases

In addition to the AEO2008 reference case, three side cases were developed to examine the effect of

equipment and building standards on residential energy use—a 2008 technology case, a best available

technology case, and a high technology case. These side cases were analyzed in stand-alone (not

integrated with the supply modules) NEMS runs and thus do not include supply-responses to the altered

residential consumption patterns of the two cases. AEO2008 also analyzed integrated2008 technology and

high technology cases. The integrated 2008 technology case combines the 2008 technology cases of the

four end-use demand sectors, the electricity low fossil technology case, and the assumption of renewable

technologies fixed at 2008 levels. The integratedhigh technology case uses the same approach, but for high 

technology.

The 2008 technology case assumes that all future equipment purchases are made based only on equipment 

available in 2008. This case further assumes that existing building shell efficiencies will not improve beyond

2008 levels. 

The high technology case assumes earlier availability, lower costs, and/or higher efficiencies for more

advanced equipment than the reference case. Equipment assumptions were developed by engineering

technology experts, considering the potential impact on technology given increased research and

development into more advanced technologies.7 In the high technology case. All new construction is

assumed to meet Energy Star specifications after 2016.

The best available technology case assumes that all equipment purchases from 2009 forward are based on

the highest available efficiency in the high technology case in a particular simulation year, disregarding the

economic costs of such a case. This case is designed to show how much the choice of the highest-efficiency 

equipment could affect energy consumption. In this case, all new construction is built to the most efficient

specifications after 2008.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 27
Residential "Normal" Weather Sensitivity Case

The projections presented in AEO2008 assume that future “normal” weather is represented by the average

of the last 10 years (1997-2006). Prior to AEO2008, “normal” weather, in the form of heating and cooling

degree-days, was represented as the average of the past 30 years, as published by the National Oceanic

and Atmospheric Administration (NOAA). In order to gauge the importance of this change, a weather

sensitivity case was created using the NOAA 30-year average heating and cooling degree-days as a proxy

for future “normal” weather. Because the 10-year average weather assumed in the AEO2008 reference case 

is warmer in both summer and winter relative to the 30-year average, the sensitivity case reduces future

needs for air conditioning, and increases the need for space heating, relative to the AEO2008 reference

case.

28 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008
[1] The Model Documentation Report contains additional details concerning model structure and operation. 

Refer to Energy Information Administration, Model Documentation Report: Residential Sector Demand

Module of the National Energy Modeling System, DOE/EIA-M065(2006), (March 2007).

[2] Among the explanations often mentioned for observed high average implicit discount rates are: market

failures, (i.e., cases where incentives are not properly aligned for markets to result in purchases based on 

energy economics alone); unmeasured technology costs (i.e., extra costs of adoption which are not included 

or difficult to measure like employee down-time); characteristics of efficient technologies viewed as less

desirable than their less efficient alternatives (such as equipment noise levels or lighting quality

characteristics); and the risk inherent in making irreversible investment decisions. Examples of market

failures/barriers include: decision makers having less than complete information, cases where energy

equipment decisions are made by parties not responsible for energy bills (e.g., landlord/tenants,

builders/home buyers), discount horizons which are truncated (which might be caused by mean occupancy

times that are less than the simple payback time and that could possibly be classified as an information

failure), and lack of appropriate credit vehicles for making efficiency investments, to name a few. The use of

high implicit discount rates in NEMS merely recognizes that such rates are typically found to apply to

energy-efficiency investments.

[3] U.S. Bureau of Census, Series C25 Data from various years of publications.

[4] Sources: U.S. Bureau of Census, Annual Housing Survey 2001 and Professional Remodler, 2002 Home

Remodeling Study.

[5] See DAHL, CAROL, A Survey of Energy Demand Elasticities in Support of the Development of the

NEMS, October 1993.

[6] The IECC established guidelines for builders to meet specific targets concerning energy efficiency with

respect to heating and cooling load.

[7] The high technology assumptions are based on Energy Information Administration, Technology Forecast 

Updates-Residential and Commercial Building technologies-Advanced Adoption Case (Navigant

Consulting, September 2007).

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 29

Notes and Sources

Commercial Demand Module

The NEMS Commercial Sector Demand Module generates projections of commercial sector energy

demand through 2030. The definition of the commercial sector is consistent with EIA’s State Energy Data

System (SEDS). That is, the commercial sector includes business establishments that are not engaged in

transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or

construction). The bulk of commercial sector energy is consumed within buildings; however, street lights,

pumps, bridges, and public services are also included if the establishment operating them is considered

commercial. Since most of commercial energy consumption occurs in buildings, the commercial module

relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for

characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to

provide end use services.

1

The commercial module projects consumption by fuel2 at the Census division level using prices from the

NEMS energy supply modules, and macroeconomic variables from the NEMS Macroeconomic Activity

Module (MAM), as well as external data sources (technology characterizations, for example). Energy

demands are projected for ten end-use services3 for eleven building categories4 in each of the nine Census

divisions (see Figure 5). The model begins by developing projections of floorspace for the 99 building

category and Census division combinations. Next, the ten end-use service demands required for the

projected floorspace are developed. The electricity generation and water and space heating supplied by

distributed generation and combined heat and power technologies are projected. Technologies are then

chosen to meet the projected service demands for the seven major end uses.5 Once technologies are

chosen, the energy consumed by the equipment stock (both existing and purchased equipment) is

developed to meet the projected end-use service demands.6

Key Assumptions

The key assumptions made by the commercial module are presented in terms of the flow of the calculations

described above. The sections below summarize the assumptions in each of the commercial module

submodules: floorspace, service demand, distributed generation, technology choice, and end-use

consumption. The submodules are executed sequentially in the order presented, and the outputs of each

submodule become the inputs to subsequently executed submodules. As a result, key projection drivers for

the floorspace submodule are also key drivers for the service demand submodule, and so on.

Floorspace Submodule

Floorspace is projected by starting with the previous year's stock of floorspace and eliminating a portion to

represent the age-related removal of buildings. Total floorspace is the sum of the surviving floorspace plus

new additions to the stock derived from the MAM floorspace growth projection.7

Existing Floorspace and Attrition

Existing floorspace is based on the estimated floorspace reported in the 2003 Commercial Buildings Energy

Consumption Survey (Table 11). Over time, the 2003 stock is projected to decline as buildings are removed

from service (floorspace attrition). Floorspace attrition is estimated by a logistic decay function, the shape of

which is dependent upon the values of two parameters: average building lifetime and gamma. The average

building lifetime refers to the median expected lifetime of a particular building type. The gamma parameter

corresponds to the rate at which buildings retire near their median expected lifetime. The current values for

the average building lifetime and gamma vary by building type as presented in Table 12.

8

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 31

Report #:DOE/EIA-0554(2008)

Release date: June 2008

Next release date: March 2009
New Construction Additions to Floorspace 

The commercial module develops estimates of projected commercial floorspace additions by combining the

surviving floorspace estimates with the total floorspace projection from MAM. A total NEMS floorspace

projection is calculated by applying the MAM assumed floorspace growth rate within each Census division

and MAM building type to the corresponding NEMS Commercial Demand Module’s building types based on

the CBECS building type shares. The NEMS surviving floorspace from the previous year is then subtracted

from the total NEMS floorspace projection for the current year to yield new floorspace additions.9

Service Demand Submodule

Once the building stock is projected, the Commercial Demand module develops a projection of demand for

energy-consuming services required for the projected floorspace. The module projects service demands for

the following explicit end-use services: space heating, space cooling, ventilation, water heating, lighting,

cooking, refrigeration, personal computer office equipment, and other office equipment.10 The service

demand intensity (SDI) is measured in thousand Btu of end-use service demand per square foot and differs

across service, Census division and building type. The SDIs are based on a hybrid engineering and

statistical approach of CBECS consumption data.

11 Projected service demand is the product of square feet

and SDI for all end uses across the eleven building categories with adjustments for changes in shell

efficiency for space heating and cooling.

32 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Assembly EducationFood

Sales

Food

Service

Health

Care Lodging Large

Office

Small

Office

Merc/

Service

Warehouse Other Total

New England 431 299 75 45 48 374 282 320 819 411 351 3,452

Middle 

 Atlantic 1,243 1,384 163 127 310 797 1,523 1,065 1,641 1,112 1,177 10,543

East North 

 Central 1,355 1,990 218 248 316 549 1,297 1,129 2,148 2,023 1,152 12,424

West North 

 Central 772 552 102 206 123 595 219 704 1,045 994 369 5,680

South 

 Atlantic 1,161 2,445 223 433 469 939 1,173 1,065 3,391 1,836 865 13,999

East South 

 Central 546 341 67 99 134 368 195 371 985 390 223 3,719

West South 

 Central 965 1,198 197 232 235 387 916 501 2,076 1,740 575 9,022

Mountain 411 640 64 32 94 438 230 535 1,087 506 168 4,207

Pacific 809 1,027 146 232 176 649 1,028 915 2,051 1,066 515 8,613

United

 States 7,693 9,874 1,255 1,654 1,905 5,096 6,861 6,605 15,242 10,078 5,395 71,658

Table 11. 2003 Total Floorspace by Census Division and Principal Building Activity

 (Millions of Square Feet)

Note: Totals may not equal sum of components due to independent rounding. 

Source: Energy Information Administration, 2003 Commercial Buildings Energy Consumption Survey Public Use Data

Assembly EducationFood

Sales

Food

Service

Health

Care Lodging

Large

Office

Small

Office

Merc/

Service

Warehouse Other

Median Expected

 Lifetime (years) 80 80 65 65 65 69 73 73 65 80 75

gamma 1.8 2.6 2.5 2.5 2.3 2.0 2.0 2.0 1.8 1.6 2.5

Table 12. Floorspace Attrition Parameters

Sources: Energy Information Administration, Commercial Buildings Energy Consumption Survey 1999, 1995, 1992, and 1989 Public Use Data, 1986

Nonresidential Buildings Energy Consumption Survey, McGraw-Hill Construction Dodge Annual Starts - non residential building starts, and Journal of

Business and Economic Statistics, April 1986, Vol. 4, No. 2.
Shell Efficiency

The shell integrity of the building envelope is an important determinant of the heating and cooling loads for

each type of building. In the NEMS Commercial Demand Module, the shell efficiency is represented by an

index, which changes over time to reflect improvements in the building shell. This index is dimensioned by

building type and Census division and applies directly to heating. For cooling, the effects are computed from

the index, but differ from heating effects, because of different marginal effects of shell integrity and because

of internal building loads. In the AEO2008 reference case, shell improvements for new buildings are up to 21

percent more efficient than the 2003 stock of similar buildings. Over the projection horizon, new building

shells improve in efficiency by 7 percent relative to their efficiency in 2003. For existing buildings, efficiency is 

assumed to increase by 5 percent over the 2003 stock average. The shell efficiency index affects the space

heating and cooling service demand intensities causing changes in fuel consumed for these services as the

shell integrity improves.

Distributed Generation and Combined Heat and Power

Nonutility power production applications within the commercial sector are currently concentrated in

education, health care, office and warehouse buildings. Program driven installations of solar photovoltaic

systems are based on information from DOE’s Photovoltaic and Million Solar Roofs programs as well as

DOE and industry news releases and the National Renewable Energy Laboratory’s Renewable Electric

Plant Information System. Historical data from Form EIA-860, Annual Electric Generator Report, are used to 

derive electricity generation for 2004 through 2006 by Census division, building type and fuel. A projection of 

distributed generation and combined heat and power (CHP) of electricity is developed based on the

economic returns projected for distributed generation and CHP technologies. The model uses a detailed

cash-flow approach to estimate the internal rate of return for an investment. Penetration assumptions for

distributed generation and CHP technologies are a function of the estimated internall rate of return relative to 

purchased electricity. Table 13 provides the cost and performance parameters for representative distributed

generation and CHP technologies.

The model also incorporates endogenous “learning” for new distributed generation and CHP technologies,

allowing for declining technology costs as shipments increase. For fuel cell and photovoltaic systems,

parameter assumptions for the AEO2005 reference case result in a 13 percent reduction in capital costs

each time the number of units shipped to the buildings sectors (residential and commercial) doubles. 

Doubling the number of microturbines shipped results in a 10 percent reduction in capital costs and doubling

the number of distributed wind systems shipped results in a 3 percent reduction.

Technology Choice Submodule

The technology choice submodule develops projections of the results of the capital purchase decisions for

equipment fueled by the three major fuels (electricity, natural gas, and distillate fuel). Capital purchase

decisions are driven by assumptions concerning behavioral rule proportions and time preferences,

described below, as well as projected fuel prices, average utilization of equipment (the capacity factors),

relative technology capital costs, and operating and maintenance (O&M) costs. 

Decision Types

In each projection year, equipment is potentially purchased for three “decision types”. Equipment must be

purchased for newly added floorspace and to replace the portion of equipment in existing floorspace that is

projected to wear out.12 Equipment is also potentially purchased for retrofitting equipment that has become

economically obsolete. The purchase of retrofit equipment occurs only if the annual operating costs of a

current technology exceed the annualized capital and operating costs of a technology available as a retrofit

candidate.

Behavioral Rules

The commercial module allows the use of three alternate assumptions about equipment choice behavior.

These assumptions constrain the equipment selections to three choice sets, which are progressively more

restrictive. The choice sets vary by decision type and building type:

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 33
• Unrestricted Choice Behavior - This rule assumes that commercial consumers consider all types of 

equipment that meet a given service, across all fuels, when faced with a capital purchase decision. 

• Same Fuel Behavior - This rule restricts the capital purchase decision to the set of technologies that

consume the same fuel that currently meets the decision maker’s service demand. 

34 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Technology Type Year 

Average

Generating

Capacity

(kW)

Electrical

Efficiency

Combined

Efficiency

(Elec.+Thermal)

Installed Capital

Cost ($2005 per

 kW of Capacity)*

Service

 Life

 (Years)

Solar Photovoltaic 2005

2010

30

32

0.16

0.18

N/A

N/A

$6,115

$4,458

30

30

2015

2020

2025

35

40

40

0.20

0.22

0.22

N/A

N/A

N/A

$4,292

$3,856

$3,528

30

30

30

2030 45 0.25 N/A $3,200 30

Fuel Cell 2005 200 0.36 0.72 $7,162 20

2010 200 0.44 0.66 $6,219 20

2015

2020

2025

2030

200

200

200

200

0.45

0.47

0.48

0.49

0.67

0.69

0.70

0.72

$5,203

$4,187

$3,647

$3,108

20

20

20

20

Natural Gas Engine 2005

2010

2015

2020

2025

2030

300

300

300

300

300

300

0.31

0.32

0.32

0.33

0.33

0.34

0.77

0.78

0.78

0.78

0.79

0.80

$2,132

$1,878

$1,714

$1,551

$1,343

$1,134

20

20

20

20

20

20

Oil-Fired Engine 2005

2010

2015

2020

2025

2030

300

300

300

300

300

300

0.34

0.34

0.35

0.35

0.36

0.36

0.73

0.74

0.74

0.74

0.78

0.82

$2,575

$2,268

$2.071

$1,873

$1,622

$1,370

20

20

20

20

20

20

Natural Gas Turbine 2005

2010

2015

2020

2025

2030

1000

1000

1000

1000

1000

1000

0.22

0.23

0.24

0.24

0.25

0.26

0.68

0.68

0.68

0.69

0.69

0.70

$2,000

$1,775

$1,684

$1,593

$1,511

$1,429

20

20

20

20

20

20

Natural Gas Micro

 Turbine

2005

2010

2015

2020

2025

2030

200

200

200

200

200

200

0.29

0.29

0.31

0.33

0.34

0.36

0.60

0.60

0.61

0.61

0.62

0.63

$2,856

$2,328

$1,981

$1,634

$1,343

$1,052

20

20

20

20

20

20

Wind

2005

2010

2015

2020

2025

2030

30

32

35

40

40

50

0.13

0.13

0.13

0.13

0.13

0.13

N/A

N/A

N/A

N/A

N/A

N/A

$4,000

$3,735

$3,720

$3,609

$3,497

$3,417

30

30

30

30

30

30

Table 13. Capital Cost and Performance Parameters of Selected Commercial Distributed Generation

 Technologies

*Installed costs are given in 2005 dollars in the original source document. Costs for solar photovoltaic, fuel cell, microturbine, and wind technologies

include learning effects.

Sources: Energy Information Administration, Commercial and Industrial CHP Technology Cost and Performance Data Analysis for EIA's NEMS,

Decision Analysis Corporation and Discovery Insights LLC., February 2006, National Renewable Energy Laboratory, Gas-Fired Distributed Energy

Resource Technology Characterizations: Reference Number NREL/TP-620-34783, November 2003, Discovery Insights, LLC, "Installed Costs for

Small CHP Systems - Estimates and Projections" (April 2005), and Solar Energy Industries Association, Our Solar Power Future - The U.S.

Photovoltaic Industry Roadmap through 2030 and Beyond, (SEIA, September 2004).
• Same Technology Behavior - Under this rule, commercial consumers consider only the available

models of the same technology and fuel that currently meet service demand, when facing a capital

stock decision. 

Under any of the above three behavior rules, equipment that meets the service at the lowest annualized

lifecycle cost is chosen. Table 14 illustrates the proportions of floorspace subject to the different behavior

rules for space heating technology choices in large office buildings.

Time Preferences

Commercial building owners' time preferences regarding current versus future expenditures are assumed to 

be distributed among seven alternate time preference premiums (Table 15). Adding the risk-adjusted time

preference premiums to the 10-year Treasury Bill rate from MAM results in implicit discount rates, also

known as hurdle rates, applicable to the assumed proportions of commercial floorspace. The effect of the

use of this distribution of discount rates is to prevent a single technology from dominating purchase

decisions in the lifecycle cost comparisons. The distribution used for AEO2008 assigns some floorspace a

very high discount or hurdle rate to simulate floorspace which will never retrofit existing equipment and which 

will only purchase equipment with the lowest capital cost. Discount rates for the remaining six segments of

the distribution get progressively lower, simulating increased sensitivity to the fuel costs of the equipment

that is purchased. The proportion of floorspace assumed for the 0.0 time preference premium represents an

estimate of the Federally owned commercial floorspace that is subject to purchase decisions in a given year. 

The Federal sector is expected to purchase energy-efficient equipment to meet the Federal buildings

performance standards of the Energy Policy Act of 2005 and the Energy Independence and Security Act of

2007 whenever cost effective. For Federal purchase decisions relating to energy conservation, cost

effectiveness is determined using a discount rate based on long-term Treasury bond rates, approximated in

the commercial module by the 10-year Treasury Bill rate. For lighting, the proportion of floorspace assumed

for the 0.0 time preference premium is increased to include all Federal floorspace starting in 2009 to

represent the EISA 2007 provision that all Federal buildings be equipped with energy efficient lighting

fixtures and bulbs to the maximum extent feasible, including when replacing bulbs in existing fixtures. 

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 35

Proportion of Floorspace-All

Proportion of Floorspace-Lighting

(2009 and later) Time Preference Premium

Services (Except Lighting 2009 

and later)

27.0 27.0 1000.0

25.4 25.4 152.9

20.4 20.4 55.4

16.2 16.2 30.9

10.0 7.9 19.9

0.8 0.6 13.6

0.2 2.5 0.0

100.0 100.0 --

Table 15. Assumed Distribution of Risk-adjusted Time Preference Premiums

(Percent)

Source: Energy Information Administration, Model Documentation Report: Commercial Sector Demand Module of the National Energy Modeling

System, DOE/EIA-M066(2008) (June 2008).

Unrestricted Same Fuel Same Technology Total

New Equipment Decision 21 30 49 100

Replacement Decision 8 35 57 100

Retrofit Decision 0 5 95 100

Table 14. Assumed Behavior Rules for Choosing Space Heating Equipment in Large Office Buildings

(Percent)

Source: Energy Information Administration, Model Documentation Report: Commercial Sector Demand Module of the National Energy Modeling

System, DOE/EIA-M066(2008) (June 2008).
The distribution of hurdle rates used in the commercial module is also affected by changes in fuel prices. If a

fuel’s price rises relative to its price in the base year (2003), the nonfinancial portion of each hurdle rate in the 

distribution decreases to reflect an increase in the relative importance of fuel costs, expected in an

environment of rising prices. Parameter assumptions for AEO2008 result in a 30 percent reduction in the

nonfinancial portion of a hurdle rate if the fuel price doubles. If the risk-adjusted time preference premium

input by the model user results in a hurdle rate below the assumed financial discount rate for the commercial

sector, 15 percent, with base year fuel prices (such as the rate given in Table 15 for the Federal sector), no

response to increasing fuel prices is assumed.

Technology Characterization Database

The technology characterization database organizes all relevant technology data by end use, fuel, and

Census division. Equipment is identified in the database by a technology index as well as a vintage index,

the index of the fuel it consumes, the index of the service it provides, its initial market share, the Census

division index for which the entry under consideration applies, its efficiency (or coefficient of performance or

efficacy in the case of lighting equipment), installed capital cost per unit of service demand satisfied,

operating and maintenance cost per unit of service demand satisfied, average service life, year of initial

availability, and last year available for purchase. Equipment may only be selected to satisfy service demand

if the year in which the decision is made falls within the window of availability. Equipment acquired prior to

the lapse of its availability continues to be treated as part of the existing stock and is subject to replacement

or retrofitting. This flexibility in limiting equipment availability allows the direct modeling of equipment

efficiency standards. Table 16 provides a sample of the technology data for space heating in the New

England Census division.

An option to allow endogenous price-induced technological change has been included in the determination

of equipment costs and availability for the menu of equipment. This concept allows future technologies

faster diffusion into the market place if fuel prices increase markedly for a sustained period of time. The

option was not exercised for the AEO2008 model runs.

End-Use Consumption Submodule

The end-use consumption submodule calculates the consumption of each of the three major fuels for the ten

end-use services plus fuel consumption for combined heat and power and district services. For the ten

end-use services, energy consumption is calculated as the end-use service demand met by a particular type

of equipment divided by its efficiency and summed over all existing equipment types. This calculation

includes dimensions for Census division, building type, and fuel. Consumption of the five minor fuels is

projected based on historical trends.

Equipment Efficiency

The average energy consumption of a particular appliance is based initially on estimates derived from the

2003 CBECS. As the stock efficiency changes over the model simulation, energy consumption decreases

nearly, but not quite proportionally to the efficiency increase. The difference is due to the calculation of

efficiency using the harmonic average and also the efficiency rebound effect discussed below. For example, 

if on average, electric heat pumps are now 10 percent more efficient than in 2003, then all else constant

(weather, real energy prices, shell efficiency, etc.), energy consumption per heat pump would now average

about 9 percent less. The Service Demand and Technology Choice Submodules together determine the

average efficiency of the stocks used in adjusting the initial average energy consumption.

Adjusting for Weather and Climate

Weather in any given year always includes short-term deviations from the expected longer-term average (or

climate). Recognition of the effect of weather on space heating and air conditioning is necessary to avoid

projecting abnormal weather conditions into the future. In the commercial module, proportionate

adjustments are made to space heating and air conditioning demand by Census division. These

adjustments are based on National Oceanic and Atmospheric Administration (NOAA) data for Heating

Degree Days (HDD) and Cooling Degree Days (CDD). A 10 percent increase in HDD would increase space

heating consumption by 10 percent over what it would have been otherwise. The commercial module uses a 

10-year average for HDD and CDD by Census division, adjusted over the projection period by projections for 

state population shifts.

36 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008
Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 37

 

Equipment Type Vintage Efficiency2

Capital Cost

($2007 per

Mbtu/hour) 3

Maintenance Cost

($2007 per

Mbtu/hour) 3

Service

Life

(Years)

Electric Rooftop Heat Pump 2007- typical 3.2 $72.78 $1.39 15 

2007- high efficiency 3.4 $96.67 $1.39 15 

2010 - typical (standard) 3.3 $76.67 $1.39 15 

2010 - high efficiency 3.4 $96.67 $1.39 15 

2020 - typical 3.3 $76.67 $1.39 15 

2020 - high efficiency 3.4 $96.67 $1.39 15 

Ground-Source Heat Pump 2007- typical 3.5 $140.00 $16.80 20

2007- high efficiency 4.9 $170.00 $16.80 20

2010- typical 3.5 $140.00 $16.80 20

2010 - high efficiency 4.9 $170.00 $16.80 20

2020 - typical 4.0 $140.00 $16.80 20

2020 - high efficiency 4.9 $170.00 $16.80 20

Electric Boiler Current typical 0.98 $17.53 $0.58 21 

Packaged Electric Typical 0.96 $16.87 $3.95 18 

Natural Gas Furnace Current Standard 0.80 $9.35 $0.97 20 

2007 - high efficiency 0.82 $9.90 $0.94 20 

2020 - typical 0.81 $9.23 $0.96 20 

2020 - high efficiency 0.90 $11.57 $0.86 20 

2030 - typical 0.82 $9.12 $0.94 20 

2030 - high efficiency 0.91 $11.44 $0.85 20 

Natural Gas Boiler Current Standard 0.80 $22.42 $0.50 25 

2007 - mid efficiency 0.85 $25.57 $0.47 25 

2007 - high efficiency 0.96 $39.96 $0.52 25 

2020 - typical 0.82 $21.84 $0.49 25 

Natural Gas Heat Pump 2007 - absorption 1.4 $158.33 $2.50 15 

2010 - absorption 1.4 $158.33 $2.50 15

2020 - absorption 1.4 $158.33 $2.50 15

Distillate Oil Furnace Current Standard 0.81 $11.14 $0.96 20 

2020 - typical 0.81 $11.14 $0.96 20 

Distillate Oil Boiler Current Standard 0.83 $17.63 $0.15 20 

2007 - high efficiency 0.89 $19.84 $0.14 20 

2020 - typical 0.83 $17.63 $015 20 

Table 16. Capital Cost and Efficiency Ratings of Selected Commercial Space Heating Equipment1

1Equipment listed is for the New England Census division, but is also representative of the technology data for the rest of the U.S. See the source

referenced below for the complete set of technology data..

2Efficiency measurements vary by equipment type. Electric rooftop air-source heat pumps, ground source and natural gas heat pumps are rated for

heating performance using coefficient of performance; natural gas and distillate furnaces are based on Thermal Efficiency; and boilers are based on

combustion efficiency.

3Capital and maintenance costs are given in 2007 dollars.

Source: Energy Information Administration, “EIA - Technology Forecast Updates - Residential and Commercial Building Technologies - Reference

Case Second Edition (Revised)”, Navigant Consulting, Inc., Reference Number 20070831.1, September 2007.
Short-Term Price Effect and Efficiency Rebound

It is assumed that energy consumption for a given end-use service is affected by the marginal cost of

providing that service. That is, all else equal, a change in the price of a fuel will have an inverse, but less than 

proportional, effect on fuel consumption. The current value for the short-term price elasticity parameter is

-0.25 for all major end uses except refrigeration. A value of -0.1 is currently used for commercial

refrigeration. A value of -0.05 is currently used for PC and non-PC office equipment and other minor uses of

electricity. For example, for lighting this value implies that for a 1 percent increase in the price of a fuel, there

will be a corresponding decrease in energy consumption of 0.25 percent. Another way of affecting the

marginal cost of providing a service is through equipment efficiency. As equipment efficiency changes

overtime, so will the marginal cost of providing the end-use service. For example, a 10 percent increase in

efficiency will reduce the cost of providing the service by 10 percent. The short-term elasticity parameter for

efficiency rebound effects is -0.15 for affected end uses; therefore, the demand for the service will rise by 1.5

percent (-10 percent x -0.15). Currently, all services are affected by the short-term price effect and services

affected by efficiency rebound are space heating and cooling, water heating, ventilation and lighting. 

 Legislation and Regulations

Energy Independence and Security Act of 2007 (EISA07)

The EISA07 legislation passed in December 2007 provides standards for the following explicitly modeled

commercial equipment. The EISA07 requires specific energy efficiency measures in commercial walk-in

coolers and walk-in freezers effective January 1, 2009. Incandescent and halogen lamps must meet

standards for maximum allowable wattage based on lumen output starting in 2012 and metal halide lamp

fixtures using lamps between 150 and 500 watts are required to have a minimum ballast efficiency ranging

from 88 to 94 percent, depending on ballast type, effective January 1, 2009.

The EISA07 requirement for Federal buildings to use energy efficient lighting fixtures and bulbs to the

maximum extent possible is represented by adjusting the proportion of the commercial sector assumed to

use the 10-year Treasury Bill rate as an implicit discount or hurdle rate for lighting.

Energy Policy Act of 2005 (EPACT05)

The passage of the EPACT05 in August 2005 provides additional minimum efficiency standards for

commercial equipment. Some of the standards for explicitly modeled equipment, effective January 1, 2010,

include: an Energy Efficiency Rating (EER) ranging from 10.8 to 11.2 for small package air conditioning and

heating equipment; daily electricity consumption limits by volume for commercial refrigerators, freezers, and

refrigerator-freezers; and electricity consumption limits per 100 pounds of ice produced based on equipment 

type and capacity for automatic ice makers. The EPACT05 adds standards for medium base compact

fluorescent lamps effective January 1, 2006, for ballasts for Energy Saver fluorescent lamps effective in

2009 and 2010, and bans the manufacture or import of mercury vapor lamp ballasts effective January 1,

2008.

Several efficiency standards in the EPACT05 pertain to equipment not explicitly represented in the NEMS

Commercial Demand Module. For low voltage dry-type transformers, effects of the standard are included in

estimating the share of projected miscellaneous electricity use attributable to transformer losses. For

illuminated exit signs, traffic signals, and commercial prerinse spray valves, assumed energy reductions are 

calculated based on per-unit savings relative to a baseline unit and the estimated share of installed units and

sales that already meet the standard. Total projected reductions are phased in over time to account for stock

turnover. Under the EPACT05 standards, illuminated exit signs and traffic signal modules must meet

ENERGY STAR program requirements as of January 1, 2006. The requirements limit input power demand

to 5 watts or less per face for exit signs. Nominal wattages for traffic signal modules are limited to 8 to 15

watts, based on module type. Effective January 1, 2007, low voltage dry-type distribution transformers are

required to meet the National Electrical Manufacturers Association Class I Efficiency Levels with minimum

efficiency levels ranging from 97 percent to 98.9 percent based on output. Commercial prerinse spray

valves13 must have a maximum flow rate of 1.6 gallons per minute, effective January 1, 2006 with energy

reductions attributed to hot water use.

38 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008
The EPACT05 expands the Business Investment Tax Credit to 30 percent for solar property installed in 2006 

and 2007. Business Investment Tax Credits of 30 percent for fuel cells and 10 percent for microturbine

power plants are also available for property installed in 2006 and 2007. The EPACT05 tax credit provisions

were extended in December 2006 to cover equipment installed in 2008. These credits are directly

incorporated into the cash-flow approach for distributed generation systems and factored into the installed

capital cost assumptions for solar hot water heaters.

Energy Policy Act of 1992 (EPACT92)

A key assumption incorporated in the technology selection process is that the equipment efficiency

standards described in the EPACT92 constrain minimum equipment efficiencies. The effects of standards

are modeled by modifying the technology database to eliminate equipment that no longer meets minimum

efficiency requirements. For standards effective January 1, 1994, affected equipment includes electric heat

pumps—minimum heating system performance factor of 6.8, gas and oil-fired boilers—minimum

combustion efficiency of 0.8 and 0.83, respectively, gas and oil-fired furnaces—minimum thermal efficiency

of 0.8 and 0.81, respectively, fluorescent lighting—minimum efficacy of 75 lumens per watt, incandescent

lighting—minimum efficacy of 16.9 lumens per watt, air-cooled air conditioners—minimum energy efficiency

ratio of 8.9, electric water heaters—minimum energy factor of 0.85, and gas and oil water heaters—minimum 

thermal efficiency of 0.78. Updated standards are effective October 29, 2003 for gas water

heaters—minimum thermal efficiency of 0.8. An additional standard affecting fluorescent lamp ballasts is

effective April 1, 2005. The standard mandates electronic ballasts with a minimum ballast efficacy factor of

1.17 for 4-foot, 2-lamp ballasts and 0.63 for 8-foot, 2-lamp ballasts.

The 10 percent Business Investment Tax Credit for solar energy property included in EPACT92 is directly

incorporated into the cash-flow approach for projecting distributed generation by commercial photovoltaic

systems. For solar hot water heaters, the tax credit is factored into the installed capital cost assumptions

used in the technology choice submodule.

Energy Efficiency Programs

Several energy efficiency programs affect the commercial sector. These programs are designed to stimulate 

investment in more efficient building shells and equipment for heating, cooling, lighting, and other end uses. 

The commercial module includes several features that allow projected efficiency to increase in response to

voluntary programs (e.g., the distribution of risk-adjusted time preference premiums and shell efficiency

parameters). Retrofits of equipment for space heating, air conditioning and lighting are incorporated in the

distribution of premiums given in Table 14. Also the shell efficiency of new and existing buildings is assumed 

to increase from 2003 through 2030. Shells for new buildings increase in efficiency by 7 percent over this

period, while shells for existing buildings increase in efficiency by 5 percent. 

Commercial Alternative Cases

Technology Cases

In addition to the AEO2008 reference case, three side cases were developed to examine the effect of

equipment and building standards on commercial energy use—a 2008 technology case, a high technology

case, and a best available technology case. These side cases were analyzed in stand-alone (not integrated

with the NEMS demand and supply modules) buildings (residential and commercial) modules runs and thus

do not include supply-responses to the altered commercial consumption patterns of the three cases. 

AEO2008 also analyzed an integrated high technology case, which combines the high technology cases of

the four end-use demand sectors, the electricity high fossil technology case, the low nuclear cost case, and

the low renewable cost case, and an integrated 2008 technology case, which combines the 2008 technology 

cases of the end-use demand sectors, the electricity low fossil technology case, and the high renewable cost 

case.

The 2008 technology case assumes that all future equipment purchases are made based only on equipment 

available in 2008. This case assumes building shell efficiency to be fixed at 2008 levels. In the reference

case, existing building shells are allowed to increase in efficiency by 5 percent over 2003 levels, and new

building shells improve by 7 percent by 2030 relative to new buildings in 2003. 

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 39
The high technology case assumes earlier availability, lower costs, and/or higher efficiencies for more

advanced equipment than the reference case. Equipment assumptions were developed by engineering

technology experts, considering the potential impact on technology given increased research and

development into more advanced technologies. In the high technology case, building shell efficiencies are

assumed to improve 25 percent more than in the reference case after 2008. Existing building shells,

therefore, increase by 6.25 percent relative to 2003 levels and new building shells by 8.75 percent relative to

their efficiency in 2003 by 2030.

The best available technology case assumes that all equipment purchases after 2008 are based on the

highest available efficiency in the high technology case in a particular simulation year, disregarding the

economic costs of such a case. It is designed to show how much the choice of the highest-efficiency

equipment could affect energy consumption. Shell efficiencies in this case are assumed to improve 50

percent more than in the reference case after 2008, i.e., existing shells increase by 7.5 percent relative to

2003 levels and new building shells by 10.5 percent relative to their efficiency in 2003 by 2030.

Fuel shares, where appropriate for a given end use, are allowed to change in the technology cases as the

available technologies from each technology type compete to serve certain segments of the commercial

floorspace market. For example, in the best available technology case, the most efficient gas furnace

technology competes with the most efficient electric heat pump technology. This contrasts with the

reference case, in which, a greater number of technologies for each fuel with varying efficiencies all 

compete to serve the heating end use. In general, the fuel choice will be affected as the available choices

are constrained or expanded, and will thus differ across the cases.

Two sensitivities that focus on electricity generation incorporate alternative assumptions for non-hydro

renewable energy technologies in the power sector, the industrial sector, and the buildings sectors, including 

residential and commercial photovoltaic systems. In each of these cases, assumptions regarding

non-renewable technologies are not changed from the reference case.

The high renewable cost case assumes that the cost and performance characteristics for residential and

commercial photovoltaic systems remain fixed at 2008 levels through the projection horizon.

The low renewable cost case assumes that costs for residential and commercial photovoltaic systems are

10 percent lower than reference case cost estimates by 2030.

40 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008
[1] Energy Information Administration, 2003 Commercial Buildings Energy Consumption Survey (CBECS)

Public Use Files, web site www.eia.doe.gov/emeu/cbecs/cbecs2003/public_use_2003/cbecs_pubdata

2003. html.

[2] The fuels accounted for by the commercial module are electricity, natural gas, distillate fuel oil, residual

fuel oil, liquefied petroleum gas (LPG), coal, motor gasoline, and kerosene. Current commercial use of

biomass (wood, Municipal solid waste) is also included. In addition to these fuels the use of solar energy is

projected based on an exogenous estimate of projected solar photovoltaic system installations under the

Million Solar Roofs program, State and local incentive programs, and the potential endogenous penetration

of solar photovoltaic systems and solar thermal water heaters.

[3] The end-use services in the commercial module are heating, cooling, water heating, ventilation, cooking,

lighting, refrigeration, PC and non-PC office equipment and a category denoted other to account for all other

minor end uses.

[4] The 11 building categories are assembly, education, food sales, food services, health care, lodging,

large offices, small offices, mercantile/services, warehouse and other.

[5] Minor end uses are modeled based on penetration rates and efficiency trends.

[6] The detailed documentation of the commercial module contains additional details concerning model

structure and operation. Refer to Energy Information Administration, Model Documentation Report: 

Commercial Sector Demand Module of the National Energy Modeling System, DOE/EIA M066(2008), (June

2008).

[7] The commercial floorspace equations of the Macroeconomic Activity Model are estimated using the F.W. 

Dodge Statistics and Forecasts Group database of historical floorspace estimates. The F.W. Dodge

estimate for commercial floorspace in the U.S. is approximately 16 percent lower than the estimate obtained

from the CBECS used for the Commercial module. See F.W. Dodge, Building Stock Database Methodology

and 1991 Results, Construction Statistics and Forecasts, F.W. Dodge, McGraw-Hill.

[8] The commercial module performs attrition for 9 vintages of floorspace developed using stock estimates

from the previous 5 CBECS and historical floorspace additions data from F.W. Dodge data.

[9] In the event that the computation of additions produce a negative value for a specific building type, it is

assumed to be zero.

[10] “Other office equipment” includes copiers, fax machines, typewriters, cash registers, server computers,

and other miscellaneous office equipment. A tenth category denoted other includes equipment such as

elevators, medical, and other laboratory equipment, communications equipment, security equipment, 

transformers and miscellaneous electrical appliances. Commercial energy consumed outside of buildings

and for combined heat and power is also included in the “other” category.

[11] Based on updated estimates using 2003 CBECS building-level consumption data and CBECS 1995

end-use-level consumption data and the methodology described in Estimation of Energy End-Use

Intensities, web site www.eia.doe.gov/emeu/cbecs/tech_end_use.html.

[12] The proportion of equipment retiring is inversely related to the equipment life.

[13] Commercial prerinse spray valves are handheld devices used to remove food residue from dishes and

flatware before cleaning.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 41

Notes and Sources

Industrial Demand Module

The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and

feedstocks) for 21 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are

further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive

manufacturing industries. The manufacturing industries are modeled through the use of a detailed process

flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with

substantially less detail (Table 17). The Industrial Demand Module projects energy consumption at the four

Census region level (see Figure 5); energy consumption at the Census Division level is estimated by

allocating the Census region projection using the SEDS1 data.

The energy-intensive industries (food products, paper and allied products, bulk chemicals, glass and glass

products, cement, iron and steel, and aluminum) are modeled in considerable detail. Each industry is

modeled as three separate but interrelated components consisting of the Process Assembly (PA)

Component, the Buildings Component (BLD), and the Boiler/Steam/Cogeneration (BSC) Component. The

BSC Component satisfies the steam demand from the PA and BLD Components. In some industries, the PA 

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 43

Energy-Intensive 

Manufacturing

Nonenergy-Intensive 

Manufacturing

Nonmanufacturing 

Industries

Food Products (NAICS 311) Metal-Based Durables Agricultural

Production -Crops (NAICS 111)

 Fabricated Metal Products (NAICS 332)

 Machinery (NAICS 333)

 Computer and Electronic

 Products (NAICS 334)

 Electrical Equipment (NAICS 335)

 Transportation Equipment (NAICS 336)

Paper and Allied

 Products (NAICS 322) Other Non-Intensive Manufacturing Other Agriculture

Including

 Livestock

(NAICS 112-

115)

 Wood Products (NAICS 321)

 Plastic Products (NAICS 326)

 Balance of Manufacturing (all remaining

 NAICS)

Bulk Chemicals Coal Mining (NAICS 2121)

 Inorganic

(NAICS 32512

 to

 32518)

 Organic (NAICS 32511,

 32519)

 Resins (NAICS 3252)

 Agricultural (NAICS 3253

Glass and Glass

 Products (NAICS 3272) Oil and Gas

 Extraction (NAICS 211)

Cement (NAICS 32731)

Metal and Other

Nonmetallic

Mining

(NAICS 2122-

 2123)

Iron and Steel (NAICS 3311-3312) Construction (NAICS

 233-235)

Aluminum (NAICS 3313)

Table 17. Industry Categories

NAICS = North American Industry Classification System.

Source: Office of Management and Budget, North American Industry Classification System (NAICS) - United States (Springfield, VA, National

Technical Information Service).

Report #:DOE/EIA-0554(2008)

Release date: June 2008

Next release date: March 2009
Component produces byproducts that are consumed in the BSC Component. For the manufacturing

industries, the PA Component is separated into the major production processes or end uses. 

Petroleum refining (North American Industry Classification System 32411) is modeled in detail in the

Petroleum Market Module of NEMS, and the projected energy consumption is included in the manufacturing

total. projections of refining energy use, and lease and plant fuel and fuels consumed in cogeneration in the

oil and gas extraction industry (North American Industry Classification System 211) are exogenous to the

Industrial Demand Module, but endogenous to the NEMS modeling system.

Key Assumptions

The NEMS Industrial Demand Module primarily uses a bottom-up process modeling approach. An energy

accounting framework traces energy flows from fuels to the industry’s output. An important assumption in

the development of this system is the use of 2002 baseline Unit Energy Consumption (UEC) estimates

based on analysis of the Manufacturing Energy Consumption Survey (MECS) 2002.2 The UECs represent

the energy required to produce one unit of the industry’s output. The output may be defined in terms of

physical units (e.g., tons of steel) or in terms of the dollar value of shipments.

The module depicts the manufacturing industries (apart from petroleum refining, which is modeled in the

Petroleum Market Module of NEMS) with a detailed process flow or end use approach. The dominant

process technologies are characterized by a combination of unit energy consumption estimates and

“technology possibility curves.” The technology possibility curves indicate the energy intensity of new and

existing stock relative to the 2002 stock over time. Rates of energy efficiency improvement assumed for new 

and existing plants vary by industry and process. These assumed rates were developed using professional

engineering judgments regarding the energy characteristics, year of availability, and rate of market adoption

of new process technologies.

Process/Assembly Component

The PA Component models each major manufacturing production step or end use for the manufacturing

industries. The throughput production for each process step is computed as well as the energy required to

produce it.

Within this component, the UECs are adjusted based on the technology possibility curves for each step. For

example, state-of-the-art additions to waste fiber pulping capacity in 2002 are assumed to require only 94

percent as much energy as does the average existing plant (Table 18). The technology possibility curve is a

means of embodying assumptions regarding new technology adoption in the manufacturing industry and the 

associated increased energy efficiency of capital without characterizing individual technologies. To some

extent, all industries will increase the energy efficiency of their process and assembly steps. The reasons for 

the increased efficiency are not likely to be directly attributable to changing energy prices but due to other

exogenous factors. Since the exact nature of the technology improvement is too uncertain to model in detail, 

the module employs a technology possibility curve to characterize the bundle of technologies available for

each process step.

Byproducts produced in the PA Component serve as fuels for the BSC Component. In the industrial module,

byproducts are assumed to be consumed before purchased fuel.

44 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 
Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 45

Industry/Process Unit

Existing Facilities New Facilities

REI 20301TPC2 REI 20023 REI 20304TPC2

Food Products

 Process Heating

 Process Cooling

 Other

0.900

0.875

0.914

-0.0038

-0.0048

-0.0032

0.900

0.850

0.915

0.800

0.750

0.810

-0.0042

-0.0045

-0.0043

Paper & Allied Products

 Wood Preparation

 Waste Pulping

 Mechanical Pulping

 Semi-chemical

 Kraft, Sulfite, misc. Chemicals

 Bleaching

 Paper Making

0.792

0.936

0.816

0.954

0.870

0.798

0.869

-0.0083

-0.0024

-0.0072

-0.0017

-0.0049

-0.0080

-0.0050

0.882

0.936

0.931

0.971

0.914

0.878

0.885

0.701

0.936

0.701

0.937

0.827

0.719

0.852

-0.0082

-0.0000

-0.0101

-0.0013

-0.0036

-0.0071

-0.0014

Bulk Chemicals

 Process Heating

 Process Cooling

 Electro-Chemical

 Other

0.900

0.875

0.980

0.914

-0.0038

-0.0048

-0.0007

-0.0032

0.900

0.850

0.950

0.915

0.800

0.750

0.850

0.810

-0.0042

-0.0045

-0.0040

-0.0043

Glass & Glass Products5

 Batch Preparation

 Melting/Refining

 Forming

 Post-Forming

0.941

0.934

0.984

0.978

 -0.0022 

-0.0024

-0.0006

-0.0008

0.882

0.900

0.982

0.968

0.882

0.868

0.968

0.955

0.0000

-0.0013

-0.0005

-0.0005

Cement

 Dry Process

 Wet Process6

 Finish Grinding

0.905

0.951

0.975

-0.0036

-0.0018

-0.0009

0.900

NA

0.950

0.810

NA

0.950

-0.0038

 NA

 0.0000

Iron and Steel

 Coke Oven6

 BF/BOF

 EAF

 Ingot Casting/Primary Rolling6

 Continuous Casting7

 Hot Rolling7

 Cold Rolling7

0.935

0.994

0.955

1.000

1.000

0.826

0.737

-0.0024

-0.0002

-0.0028

 0.0000

 0.0000

-0.0068

-0.0108

0.902

0.987

0.990

NA

1.000

0.800

0.924

0.869

0.987

0.849

NA

1.000

0.652

0.474

-0.0013

 0.0000

0.0055

 NA

0.0000

-0.0073

-0.0236

Aluminum

 Alumina Refining

 Primary Smelting

 Secondary

 Semi-Fabrication, Sheet

 Semi-Fabrication, Other

0.930

0.900

0.875

0.900

0.925

-0.0026

-0.0038

-0.0048

-0.0038

-0.0028

0.900

0.950

0.850

0.900

0.950

0.860

0.800

0.750

0.800

0.850

-0.0016

-0.0061

-0.0045

-0.0042

-0.0040

Metal-Based Durables

Fabricated Metals

 Process Heating

 Process Cooling

 Other

 

0.728

0.669

0.763

-0.0113

-0.0143

-0.0096

0.675

0.638

0.686

0.420

0.385

0.420

-0.0168

-0.0178

-0.0174

Table 18. Coefficients for Technology Possibility Curve
Machine drive electricity consumption in the food, bulk chemicals, metal-based durables, and balance of

manufacturing sectors is calculated by a motor stock model. The beginning stock of motors is modified over

the projection horizon as motors are added to accommodate growth in shipments for each sector, as motors

are retired and replaced, and as failed motors are rewound. When an old motor fails, an economic choice is

made on whether to repair or replace the motor. When a new motor is added, either to accommodate growth 

or as a replacement, the motor must meet the premium efficiency standard minimum for efficiency or a

premium efficiency motor. Table 19 provides the beginning stock efficiency for seven motor size groups in

each of the four industries, as well as efficiencies for EPACT minimum and premium motors. 3 As the motor

stock changes over the projection horizon, the overall efficiency of the motor population changes as well.

46 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 

Industry/Process Unit

Existing Facilities New Facilities

REI 20301TPC2 REI 20023 REI 20304TPC2

Machinery

 Process Heating 

 Process Cooling

 Other

0.728

0.669

0.763

-0.0113

-0.0143

-0.0096

0.675

0.638

0.686

0.330

0.298

0.328

-0.0252

-0.0268

-0.0261

Computers and Electronics

 Process Heating

 Process Cooling

 Other

0.900

0.875

0.914

-0.0075

-0.0095

-0.0064

0.720

0.880

0.732

0.569

0.529

0.573

-0.0084

-0.0089

-0.0087

Electrical Equipment

 Process Heating

 Process Cooling

 Other

0.900

0.875

0.914

-0.0075

-0.0085

-0.0064

0.720

0.880

0.732

0.569

0.529

0.573

-0.0084

-0.0089

-0.0087

Transportation Equipment

 Process Heating

 Process Cooling

 Other

0.863

0.829

0.882

-0.0053

-0.0067

-0.0045

0.765

0.723

0.778

0.633

0.591

0.640

-0.0067

-0.0071

-0.0069

Other Non-Intensive Manufacturing

Wood Products

 Process Heating

 Process Cooling

 Other

0.728

0.669

0.763

-0.0113

-0.0143

-0.0096

0.630

0.595

0.641

0.392

0.359

0.392

-0.0168

-0.0178

-0.0174

Plastic Products

 Process Heating

 Process Cooling

 Other

0.854

0.818

0.874

-0.0075

-0.0095

-0.0064

0.675

0.638

0.686

0.533

0.496

0.538

-0.0084

-0.0089

-0.0084

Balance of Manufacturing

 Process Heating

 Process Cooling

 Other

0.728

0.669

0.763

-0.0131

-0.0167

-0.0112

0.675

0.638

0.686

0.373

0.339

0.371

-0.0210

-0.0143

-0.0217

Table 18. Coefficients for Technology Possiblity Curves (Continued)

 

1REI 2030 Existing Facilities = Ratio of 2030 energy intensity to average 2002 energy intensity for existing facilities.

 

2

TPC = annual rate of change between 2002 and 2030. 

 3REI 2002 New Facilities = For new facilities, the ratio of state-of-the-art energy intensity to average 2002 energy intensity for existing

facilities. 

 

4REI 2030 New Facilities = Ratio of 2030 energy intensity for a new state-of-the-art facility to the average 2002 intensity for existing

facilities.

 

5REIs and TPCs apply to virgin and recycled materials.

 

6No new plants are likely to be built with these technologies. 

 

7Net shape casting is projected to reduce the energy requirements for hot and cold rolling rather than for the continuous casting step. 

 NA = Not applicable.

 BF = Blast furnace.

 BOF = Basic oxygen furnace.

 EAF = Electric arc furnace.

Source: Energy Information Administration, Model Documentation Report, Industrial Sector Demand Module of the National Energy Modeling System,

DOE/EIA-M064(2008) (Washington, DC, 2008).
Buildings Component

The total buildings energy demand by industry for each region is a function of regional industrial employment 

and output. Building energy consumption was estimated for building lighting, hvac (heating,ventilation, and

air conditioning), facility support, and onsite transportation. Space heating was further divided to estimate

the amount provided by direct combustion of fossil fuels and that provided by steam (Table 20). Energy

consumption in the BLD Component for an industry is estimated based on regional employment and output

growth for that industry.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 47

Industrial Sector

 Horsepower Range 2002 Stock

 Efficiency (%)

Premium

 Efficiency (%)

Premium

Cost

 (2002$)

Food

 1 - 5 hp 81.3 89.2 607

 6 - 20 hp 87.1 92.5 1,352

 21 - 50 hp 90.1 93.8 2,612

 51 - 100 hp 92.7 95.3 6,354

 101 - 200 hp 93.5 95.2 11,548

 201 - 500 hp 93.8 95.4 30,299

 > 500 hp 93.0 96.2 36,187

Bulk Chemicals

 1 - 5 hp 82.0 89.4 607

 6 - 20 hp 87.4 92.6 1,352

 21 - 50 hp 90.4 93.9 2,612

 51 - 100 hp 92.4 95.4 6,354

 101 - 200 hp 93.5 95.3 11,548

 201 - 500 hp 93.3 95.5 30,299

 > 500 hp 93.2 96.2 36,187

Metal-Based Durables1

 1 - 5 hp 81.9 89.2 607

 6 - 20 hp 89.9 92.5 1,352

 21 - 50 hp 89.9 93.9 2,612

 51 - 100 hp 92.0 95.3 6,354

 101 - 200 hp 93.5 95.2 11,548

 201 - 500 hp 93.7 95.4 30,299

 > 500 hp 93.0 96.2 36,187

Other Non-Intensive

 Manufacturing2

 1 - 5 hp 83.0 89.2 607

 6 - 20 hp 88.3 92.5 1,352

 21 - 50 hp 90.3 93.9 2,612

 51 - 100 hp 92.7 95.3 6,354

 101 - 200 hp 94.3 95.2 11,548

 201 - 500 hp 94.3 95.4 30,299

 > 500 hp 92.9 96.2 36,187

Table 19. Cost and Performance Parameters for Industrial Motor Choice Model

1

 The Metal-Based Durables group includes five sectors that are modeled separately: Fabricated Metal Products; Machinery; Computer and

Electronic Products; Electrical Equipment, Appliances, and Components; and Transportation Equipment

2 The Other Non-Intensive Manufacturing group includes three sectors that are modeled separately: Wood Products; Plastics and Rubber Products; 

and Balance of Manufacturing.

Source: Energy Information Administration, Model Documentation Report, Industrial Sector Demand Module of the National Energy Modeling

System, DOE/EIA-M064(2008) (Washington, DC, 2008).

Note: The efficiencies listed in this table are operating efficiencies based on average part-loads. Because the average part-load is not the same

for all industries, the listed efficiencies for the different motor sizes vary across industries.
Boiler/Steam/Combined Heat and Power Component

The steam demand and byproducts from the PA and BLD Components are passed to the BSC Component,

which applies a heat rate and a fuel share equation (Table 21) to the boiler steam requirements to compute

the required energy consumption. 

The boiler fuel shares apply only to the fuels that are used in non-combined heat and power (CHP) boilers. 

The portion of the steam demand that is met with cogenerated steam reduces the amount of boiler fuel that

would otherwise be required. The non-CHP boiler fuel shares are calculated using a logit formulation. The

equation is calibrated to 2002 so that the actual boiler fuel shares are produced for the relative prices that

prevailed in 2002.

The byproduct fuels are consumed before the quantity of purchased fuels is estimated. The boiler fuel

shares are based on the 2002 MECS.4

Combined Heat and Power

Combined heat and power (CHP) plants, which are designed to produce electricity and useful heat, have

been used in the industrial sector for many years. The CHP estimates in the module are based on the

assumption that the historical relationship between industrial steam demand and CHP will continue in the

future. 

The energy intensity of the new capital stock relative to 2002 capital stock is reflected in the parameter of the

technology possibility curve estimated for the major production steps for each of the energy-intensive

industries. These curves are based on engineering judgment of the likely future path of energy intensity

changes (Table 20). The energy intensity of the existing capital stock also is assumed to decrease over

time, but not as rapidly as new capital stock. The net effect is that over time the amount of energy required to

produce a unit of output declines. Although total energy consumption in the industrial sector is projected to

increase, overall energy intensity is projected to decrease.

48 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 
Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 49

Industry Region

Lighting

Electricity

Consumption

Building Use and Energy Source

Facility

 Support

 Total

 Consumptiion

Onsite 

Transportation 

Total

Consumption

HVAC

Electricity

Consumption

HVAC

Natural Gas

Consumption

HVAC

Steam

Consumption

Food Products 1

2

3

4

1.6

7.2

5.8

2.5

1.7

7.7

6.2

2.7

4.0

16.9

12.1

7.5

2.0

4.4

6.0

3.7

0.6

2.2

1.6

1.0

0.9

0.8

1.8

1.6

Paper & Allied

 Products

1

2

3

4

1.9

3.5

7.1

2.9

2.0

3.7

7.5

3.1

3.6

6.4

14.0

3.4

0.0

0.0

0.0

0.0

0.2

0.2

0.5

0.1

0.8

1.1

2.5

0.7

Bulk Chemicals 1

2

3

4

1.4

3.1

13.0

0.9

1.7

3.7

15.7

1.1

1.3

2.3

16.4

1.1

0.0

0.0

0.0

0.0

0.3

0.5

3.3

0.2

0.8

0.8

5.3

0.1

Glass & Glass

 Products

1

2

3

4

0.3

0.6

0.8

0.2

0.5

0.9

1.3

0.4

2.2

2.1

3.3

0.9

0.0

0.0

0.0

0.0

0.5

0.1

0.8

0.1

0.5

0.1

0.8

0.1

Cement 1

2

3

4

0.1

0.2

0.4

0.2

0.1

0.2

0.4

0.2

0.1

0.4

0.6

0.3

0.0

0.0

0.0

0.0

0.1

0.1

0.2

0.1

0.7

1.4

1.4

1.4

Iron & Steel 1

2

3

4

0.6

2.1

2.0

0.4

0.7

2.6

2.5

0.4

3.4

8.1

3.2

0.3

0.0

0.0

0.0

0.0

0.5

1.1

0.5

0.0

0.8

6.4

0.8

0.0

Aluminum 1

2

3

4

0.3

0.8

1.5

0.3

0.4

1.1

2.1

0.4

0.7

1.6

3.7

0.5

0.0

0.0

0.0

0.0

0.1

0.3

0.7

0.1

0.1

0.1

1.1

0.0

Metal-Based Durables

Fabricated Metal Products 1

2

3

4

2.2

7.3

5.2

1.4

2.4

7.8

5.6

1.5

7.4

25.1

15.2

3.4

2.1

7.1

4.3

1.0

0.2

0.6

0.4

0.1

0.1

0.8

1.3

0.0

Machinery 

 

1

2

3

4

1.9

5.8

3.7

1.0

2.6

7.7

5.0

1.4

4.7

18.7

6.9

2.3

2.4

9.4

3.5

1.2

0.2

0.7

0.2

0.1

0.0

0.7

0.3

0.0

Computers & Electronic

 Products

 

1

2

3

4

5.2

2.5

4.2

5.9

11.3

5.3

9.2

12.8

7.1

4.1

2.7

8.0

8.9

5.1

3.3

10.0

0.5

0.3

0.1

0.4

0.1

0.2

0.0

0.1

Table 20. 2002 Building Component Energy Consumption

(Trillion Btu)
50 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 

Industry Region

Lighting

Electricity

Consumption

Building Use and Energy Source

Facility

 Support

 Total

 Consumptiion

Onsite 

Transportation 

Total

Consumption

HVAC

Electricity

Consumption

HVAC

Natural Gas

Consumption

HVAC

Steam

Consumption

Electrical Equipmentt

 

1

2

3

4

0.9

2.3

2.8

0.4

1.2

3.0

3.7

0.5

3.0

5.7

5.5

1.6

1.3

2.4

2.3

0.7

0.1

0.1

0.2

0.1

0.1

0.1

0.8

0.1

Transportation Equipment 

 

1

2

3

4

2.2

14.6

7.5

2.5

2.8

18.6

9.5

3.2

6.6

36.9

14.5

5.8

0.9

5.2

2.0

0.8

0.4

1.4

0.6

0.2

0.0

1.0

0.8

0.0

Other Non-Intensive

 Manufacturing

Wood Products

 

1

2

3

4

0.3

0.8

2.9

1.3

0.3

0.8

2.9

1.3

0.7

2.1

3.7

2.2

1.1

3.3

5.8

3.5

0.2

0.3

0.6

0.4

1.7

1.1

3.5

2.4

Plastic Products

 

1

2

3

4

2.1

5.5

6.0

1.2

2.6

6.7

7.3

1.5

3.1

10.0

12.4

1.8

0.0

0.0

0.0

0.0

0.2

0.5

0.7

0.1

0.8

0.9

1.0

0.0

Balance of Manufacturing

 

1

2

3

4

6.9

16.0

26.2

7.8

9.7

22.4

36.8

10.9

7.0

31.3

62.4

16.7

0.0

0.0

0.0

0.0

0.8

1.9

3.2

0.8

0.8

1.8

3.1

0.8

Table 20. 2002 Building Component Energy Consumption (cont.)

(Trillion Btu)

HVAC = Heating, Ventilation, Air Conditioning.

Source: Energy Information Administration, Model Documentation Report: Industrial Demand Module of the National Energy Modeling System,

DOE/EIA-M064(2008), (Washington, DC, 2008).
Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 51

Industry Region Alpha Natural Gas Coal Oil Renewables

Food Products 1

2

3

4

-2.0

-2.0

-2.0

-2.0

 28

125

 86

 53

 2

154

 10

 13

5

4

3

4

 2

15

33

 6

Paper & Allied Products 1

2

3

4

-2.0

-2.0

-2.0

-2.0

56

64

157

48

 28

75

97

14

25

13

61

 4

 87

103

864

164

Bulk Chemicals 1

2

3

4

-2.0

-2.0

-2.0

-2.0

 43

 98

685

 50

 3

 34

194

 1

 56

 46

271

 3

 0

 0

 0

 0

Glass & Glass Products 1

2

3

4

-2.0

-2.0

-2.0

-2.0

 0

 1

 1

 0

 0

 0

 0

 0

 6

 0

 9

 0

 2

 1

 1

 0

Cement 1

2

3

4

-2.0

-2.0

-2.0

-2.0

 0

 0

 0

 0

 1

 2

 3

 2

 0

 0

 0

 0

 0

 0

 0

 0

Iron & Steel 1

2

3

4

-2.0

-2.0

-2.0

-2.0

 10

24

 9

 1

 7

 1

 0

 0

 4

 67

 22

 10

0

0

0

0

Aluminum 1

2

3

4

-2.0

-2.0

-2.0

-2.0

 2

 5

 10

 2

 0

 0

 0

 0

 0

 0

 0

 0

 1

 0

 8

 0

 Fabricated Metal Products 1

2

3

4

-2.0

-2.0

-2.0

-2.0

2

7

5

1

0

0

0

0

0

1

0

0

2

2

0

0

 Machinery 1

2

3

4

-2.0

-2.0

-2.0

-2.0

2

9

3

1

0

1

0

0

0

0

0

0

1

1

0

0

Table 21. 2002 Boiler Fuel Consumption and Logit Parameter

(trilliion Btu)
The projection for additions to fossil-fueled cogeneration is based on assessing capacity that could be added 

to generate the industrial steam requirements that are not already met by existing CHP. The technical

potential for onsite CHP is primarily based on supplying thermal requirements. Capacity additions are then

determined by the interaction of payback periods and market penetration rates. Installed cost for the

cogeneration systems is given in Table 22.

Technology

The amount of energy consumption reported by the industrial module is also a function of the vintage of the

capital stock that produces the output. It is assumed that new vintage stock will consist of state-of-the-art

technologies that are more energy efficient than the average efficiency of the existing capital stock.

Consequently, the amount of energy required to produce a unit of output using new capital stock is less than

that required by the existing capital stock. Capital stock is grouped into three vintages: old, middle, and new.

The old vintage consists of capital added in 2002 and earlier and is assumed to retire at a fixed rate each

year (Table 23). Middle vintage capital is that which is added after 2002 but not including the year of the

projection. New production capacity is built in the projection years when the capacity of the existing stock of

capital in the industrial model cannot produce the output projected by the NEMS Regional Macroeconomic

Model. Capital additions during the projection horizon are retired in subsequent years at the same rate as

the pre-2003 capital stock.

52 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 

Industry Region Alpha Natural Gas Coal Oil Renewables

 Computers and Electronic

 Products

1

2

3

4

-2.0

-2.0

-2.0

-2.0

10

5

4

11

0

0

0

0

2

0

0

0

0

0

0

0

 Electrical Equipment 1

2

3

4

-2.0

-2.0

-2.0

-2.0

1

2

2

1

0

0

0

0

0

0

0

0

0

0

0

0

 Transportation Equipment 1

2

3

4

-2.0

-2.0

-2.0

-2.0

 5

 31

12

 5

 8

0

2

 0

 3

1

2

 0

 8

 11

 2

 1

 Wood Products 1

2

3

4

-2.0

-2.0

-2.0

-2.0

1

4

7

4

0

0

1

0

0

0

1

0

11

20

142

56

 Plastic Products 1

2

3

4

-2.0

-2.0

-2.0

-2.0

6

21

24

 4

2

20

0

0

2

1

4

0

1

1

2

0

 Balance of Manufacturing 1

2

3

4

-2.0

-2.0

-2.0

-2.0

15

68

137

 35

9

50

54

7

43

16

54

1

8

3

7

2

Table 21. 2002 Boiler Fuel Consumption and Logit Parameter (cont.)

(trilliion Btu)

Alpha: User-specified.

Source: Energy Information Administration, Model Documentation Report: Industrial Sector Demand Module of the National Energy Modeling

System, DOE/EIA-064(2008), (Washington, DC, 2008).
Legislation and Regulations

The Energy Indpendence and Security Act of 2007

The EPAct of 1992 motor efficiency standards are superseded for purchase made after 2011. Section 313

increases or creates minimum efficiency standards for newly manufactured, general purpose electric motors 

that must be met within three years of enactment. The efficiency standards are raised for general purpose,

integral-horsepower induction motors with the exception of fire pump motors. Minimum standards were

created for seven types of poly-phase, integral-horsepower induction motors and NEMA design "B" 201-500

hp motors that were not previously covered by EPAct 1992 standards. After 2011, the industrial model

requires that new motors meet the EISA2007 efficiency standards.

Energy Policy Act of 1992 (EPACT)

EPACT contains several implications for the industrial module. These implications concern efficiency

standards for boilers, furnaces, and electric motors. The industrial module uses heat rates of 1.25 (80

percent efficiency) and 1.22 (82 percent efficiency) for gas and oil burners respectively. These efficiencies

meet the EPACT standards. EPACT mandates minimum efficiencies for all motors up to 200 horsepower

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 53

Size Installed Cost

($2005 per kilowatt)1

System (kilowatts) 2005 2030

1 Engine 1000 1,373 989

2 Engine 3000 1,089 929

3 Gas Turbine 3000 1,530 1,265

4 Gas Turbine 5000 1,180 979

5 Gas Turbine 10000 1,104 959

6 Gas Turbine 25000 930 813

7 Gas Turbine 40000 808 743

8 Combined Cycle 100000 846 787

Table 22. Cost Characteristics of Industrial CHP Systems

1Costs are given in 2005 dollars in original source document.

Source: Energy Information Administration, Model Documentation Report: Industrial Sector Demand Module of the National Energy Modeling System,

DOE/EIA-MO64(2008) (Washington, DC, 2008).

 Industry

Retirement Rate 

(percent)

 

 Industry

Retirement Rate

 (percent)

Food Products 

Pulp and Paper

Bulk Chemicals

Iron & Steel

 Blast Furnace and Basic Stell Products

 Electric Arc Furnace

 Coke Ovens

 Other Stell

1.7

2.3

1.7

1.5

1.5

2.5

2.9

Glass and Glass Products 

Cement 

Aluminum

Metal-Based Durables

Other Non-Intensive Manufacturing

1.3

1.2

1.3

1.3

Table 23. Retirement Rates

Note: Except for the Blast Furnace and Basic Steel Products Industry, the retirement rate is the same for each process step or

end-use within an industry. 

Source: Energy Information Administration, Model Documentation Report: Industrial Sector Demand Module of the National

Energy Modeling System, DOE/EIA-MO64(2008), (Washington, DC, 2008).
purchased after 1998. The choices offered in the motor model are all at least as efficient as the EPACT

minimums.

Clean Air Act Amendments of 1990 (CAAA90)

The CAAA90 contains numerous provisions that affect industrial facilities. Three major categories of such

provisions are as follows: process emissions, emissions related to hazardous or toxic substances, and SO2

emissions.

Process emissions requirements were specified for numerous industries and/or activities (40 CFR 60). 

Similarly, 40 CFR 63 requires limitations on almost 200 specific hazardous or toxic substances. These

specific requirements are not explicitly represented in the NEMS industrial model because they are not

directly related to energy consumption projections.

Section 406 of the CAAA90 requires the Environmental Protection Agency (EPA) to regulate industrial SO2

emissions at such time that total industrial SO2 emissions exceed 5.6 million tons per year (42 USC 7651). 

Since industrial coal use, the main source of SO2 emissions, has been declining, EPA does not anticipate

that specific industrial SO2 regulations will be required (Environmental Protection Agency, National Air

Pollutant Emission Trends: 1990-1998, EPA-454/R-00-002, March 2000, Chapter 4). Further, since

industrial coal use is not projected to increase, the industrial cap is not expected be a factor in industrial

energy consumption projections.5

Industrial Alternative Cases 

Technology Cases

The high technology case assumes earlier availability, lower costs, and higher efficiency for more advanced

equipment. (Tables 24 and 25)6 The high technology case also assumes that the rate at which biomass

byproducts will be recovered from industrial processes increases from 0.1 percent per year to 0.7 percent

per year. The availability of additional biomass leads to an increase in biomass-based cogeneration.

Changes in aggregate energy intensity result both from changing equipment and production efficiency and

from changes in the composition of industrial output. Since the composition of industrial output remains the

same as in the reference case, delivered energy intensity declines by 1.1 (this number need to revised when 

a num is available) percent annually compared with the reference case, in which delivered energy intensity is 

projected to decline 0.9 (this number need to revised when a num is available) percent annually.

The 2008 technology case holds the energy efficiency of plant and equipment constant at the 2008 level over 

the projection. Both cases were run with only the Industrial Demand Module rather than as a fully integrated

NEMS run, (i.e., the other demand models and the supply models of NEMS were not executed).

Consequently, no potential feedback effects from energy market interactions were captured.

AEO2008 also analyzed an integrated high technology case (consumption high technology), which

combines the high technology cases of the four end-use demand sectors, the electricity high fossil

technology case, the advanced nuclear case, and the high renewables case.

The high renewables case assumes that the rate at which biomass byproducts will be recovered from

industrial processes increases from 0.1 percent per year to 0.7 percent per year. The availability of

additional biomass leads to an increase in biomass-based CHP.

54 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 
Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 55

Industry/Process Unit

Existing Facilities New Faciliies

 REI 20301TPC2 REI 20303TPC2

Food Products

 Process Heating

 Process Cooling

 Other

0.889

0.889

0.889

-0.004

-0.004

-0.004

0.702

0.702

0.702

-0.009

-0.009

-0.009

Paper & Allied Products

 Wood Preparation

 Waste Pulping

 Mechanical Pulping

 Semi-chemical

 Kraft, Sulfite, misc. Chemicals (a)

 Bleaching

 Paper Making

0.747

0.898

0.771

0.948

0.827

0.758

0.766

-0.010

-0.004

-0.009

-0.002

-0.007

-0.010

-0.009

0.532

0.800

0.580

0.777

0.549

0.627

0.451

-0.018

-0.006

-0.017

-0.008

-0.018

-0.012

-0.024

Bulk Chemicals

 Process Heating

 Process Cooling

 Electro-Chemical

 Other

0.893

0.893

0.893

0.893

-0.004

-0.004

-0.004

-0.004

0.710

0.710

0.710

0.710

-0.009

-0.009

-0.009

-0.009

Glass & Glass Products4

 Batch Preparation

 Melting/Refining

 Forming

 Post-Forming

0.941

0.822

0.965

0.971

 -0.002 

-0.007

-0.001

-0.001

0.819

0.449

0.826

0.865

-0.003

-0.025

-0.006

-0.004

Cement

 Dry Process

 Wet Process6

 Finish Grinding

0.800

0.894

0.850

-0.008

-0.004

-0.006

0.531

NA

0.600

-0.019

NA

-0.016

Iron & Steel

 Coke Oven5

 BF/BOF

 EAF

 Ingot Casting/Primary Rolling5

 Continuous Casting6

 Hot Rolling6

 Cold Rolling6

0.845

0.950

0.845

1.000

1.000

0.761

0.706

-0.006

-0.002

-0.006

-0.000

-0.000

-0.010

-0.012

0.637

0.785

0.655

NA

1.000

0.337

0.400

-0.012

-0.008

-0.015

NA

0.000

-0.030

-0.029

Aluminum

 Alumina Refining

 Primary Smelting

 Secondary

 Semi-Fabrication, Sheet/plate/foil

 Semi-Fabrication, Other

0.915

0.800

0.825

0.750

0.825

-0.003

-0.008

-0.007

-0.010

-0.007

0.576

0.522

0.376

0.457

0.467

-0.016

-0.021

-0.029

-0.024

-0.025

Metal-Based Durables

Fabricated Metals

 Process Heating

 Process Cooling

 Other

0.704

0.647

0.741

-0.0124

-0.0155

-0.0106

0.380

0.369

0.386

-0.0203

-0.0193

-0.0203

Table 24. Coefficients for Technology Possibility Curves, High Technology Case
56 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 

Industry/Process Unit

Existing Facilities New Facilities

REI 20301TPC2 REI 20304TPC2

Machinery

 Process Heating

 Process Cooling

 Other

0.704

0.647

0.738

-0.0124

-0.0155

-0.0108

0.284

0.280

0.281

-0.0305

-0.0290

-0.0314

Computers and Electronics

 Process Heating

 Process Cooling

 Other

0.792

0.748

0.817

-0.0083

-0.0103

-0.0072

0.541

0.503

0.545

-0.0102

-0.0107

-0.0105

Electrical Equipment

 Process Heating

 Process Cooling

 Other

0.890

0.865

0.905

-0.0083

-0.0103

-0.0072

0.780

0.742

0.793

-0.0102

-0.0107

-0.0105

Transportation Equipment

 Process Heating

 Process Cooling

 Other

0.849

0.817

0.870

-0.0058

-0.0072

-0.0050

0.609

0.581

0.619

-0.0081

-0.0077

-0.0051

Other Non-Intensive

 Manufacturing

Wood Products

 Process Heating

 Process Cooling

 Other

0.705

0.647

0.742

-0.0124

-0.0154

-0.0106

0.356

0.341

0.354

-0.0202

-0.0196

-0.0209

Plastic Products

 Process Heating

 Process Cooling

 Other

0.793

0.749

0.817

-0.0083

-0.0103

-0.0072

0.508

0.473

0.512

-0.0253

-0.0266

-0.0260

Balance of Manufacturing

 Process Heating

 Process Cooling

 Other

0.665

0.602

0.702

-0.0145

-0.0180

-0.0126

0.330

0.300

0.328

-0.0253

-0.0266

-0.0260

Table 24. Coefficients for Technology Possibility Curves, High Technology Case (Continued)

 ,1REI 2030 Existing Facilities = Ratio of 2030 energy intensity to average 2002 energy intensity for existing facilities. 

 

2

TPC = annual rate of change between 2002 and 2030. 

 

3REI 2030 New Facilities = Ratio of 2030 energy intensity for a new State-of-the-art facility to the average 2002 intensity for existing

facilities.

 

4

 REIs and TPCs apply to virgin and recycled materials. 

 

5No new plants are likely to be built with these technologies.

 

6Net shape casting is projected to reduce the energy requirements for hot and cold rolling rather than for the continuous casting step. 

 NA = Not applicable.

 BF = Blast furnace.

 BOF = Basic oxygen furnace.

 EAF = Electric arc furnace.

Source: Energy Information Administration, Model Documentation Report, Industrial Sector Demand Module of the National Energy Modeling System,

DOE/EIA-M064(2008) (Washington, DC, 2008).
Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 57

Size Installed Cost

($2005 per kilowatt)1

System (kilowatts) 2005 2030

1 Engine 1000 1,373 927

2 Engine 3000 1,089 918

3 Gas Turbine 3000 1,530 1036

4 Gas Turbine 5000 1,180 903

5 Gas Turbine 10000 1,104 895

6 Gas Turbine 25000 930 779

7 Gas Turbine 40000 808 728

8 Combined Cycle 100000 846 768

Table 25. Cost Characteristics of Industrial CHP Systems, High Technology Case

1Costs are given in 2005 dollars in original source document.

Source: Energy Information Administration, Model Documentation Report: Industrial Sector Demand Module of the National Energy Modeling System,

DOE/EIA-MO64(2008) (Washington, DC, 2008).
[1] Energy Information Administration, State Energy Data System, 2004, www.eia.doe.gov/emeu/

_seds.html

[2] Energy Information Administration, Manufacturing Energy Consumption Survey, web site

www.eia.doe.gov/emeu/mecs/mecs2002/data02/shelltables.html.

[3] U.S., Department of Energy (2005). Motor Master+ 4.0 software database; available online:

http://www1.eere.energy.gov/industry/bestpractices/software.html#mm.

[4] Energy Information Administration, Manufacturing Energy Consumption Survey, web site

www.eia.doe.gov/emeu/mecs/mecs2002/data02/shelltables.html.

[5] Emissions due to coal-to-liquids plants are included with the electric power sector because these are

also large electricity generating plants.

[6] These assumptions are based in part on Energy Information Administration, Industrial Technology and

Data Analysis Supporting the NEMS Industrial Model (Focis Associates, October 2005).

58 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 

Notes and Sources
Transportation Demand Module

The NEMS Transportation Demand Module estimates energy consumption across the nine Census

Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific

technology attributes applicable by transportation mode. Total transportation energy consumption is the

sum of energy use in eight transport modes: light-duty vehicles (cars and light trucks), commercial light

trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), freight and

passenger aircraft, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty 

vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

Key Assumptions

Light-Duty Vehicle Assumptions

The light duty vehicle Manufacturers Technology Choice Model (MTCM) includes 63 fuel saving

technologies with data specific to cars and light trucks (Tables 26 and 27) including incremental fuel

efficiency improvement, incremental cost, first year of introduction, and fractional horsepower change.

These assumed technology characterizations are scaled up or down to approximate the differences in each

attribute for 6 Environmental Protection Administration (EPA) size classes of cars and light trucks.

The vehicle sales share module holds the share of vehicle sales by import and domestic manufacturers

constant within a vehicle size class at 1999 levels based on National Highway Traffic and Safety

Administration data.

1

EPA size class sales shares are projected as a function of income per capita, fuel prices, and average

predicted vehicle prices based on endogenous calculations within the MTCM.2

The MTCM utiizes 63 new technologies for each size class and origin of manufacturer (domestic or foreign)

based on the cost-effectiveness of each technology and an initial availability year. The discounted stream of

fuel savings is compared to the marginal cost of each technology. The fuel economy module assumes the

following:

• All fuel saving technologies have a 3-year payback period.

• The real discount rate remains steady at 15 percent.

• For cars, the fuel economy standards are not attribute based, but apply to both the manufacturer's

domestic and imported fleet. For cars, the fuel economy standard increases from 27.5 mpg in 2010 to

41.0 mpg in 2020 in AEO2008. For light trucks, the footprint based average fleet fuel economy

standard increases from 24.0 mpg in 2011 to 31.0 mpg in 2020. In AEO2008, the light duty vehicle

fuel economy standards are assumed to remain at the 2020 level.

• Expected future fuel prices are calculated based on an extrapolation of the growth rate between a five

year moving average of fuel price 3 years and 4 years prior to the present year. This assumption is

founded upon an assumed lead time of 3 to 4 years to significantly modify the vehicles offered by a

manufacturer.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 59

Report #:DOE/EIA-0554(2008)

Release date: June 2008

Next release date: March 2009
60 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Fractional

 Fuel

 Efficiency

 Change

Incremental 

Cost 

(1990$)

Incremental

 Cost 

($/Unit Wt.)

Incremental

Weight

 (Lbs.)

Incremental

Weight

 (Lbs./Uni

t Wt.)

Introduction

 Year

Fractional

 Horsepower 

Change

Unit Body Construction 4 100 0 0 -6 1980 0

Material Substitution II 3.3 0 0.4 0 -5 1990 0

Material Substitution III 6.6 0 0.6 0 -10 1998 0

Material Substitution IV 9.9 0 0.9 0 -15 2006 0

Material Substitution V 13.2 0 1.2 0 -20 2014 0

Drag Reduction II 2.3 40 0 0 0 1988 0

Drag Reduction III 4.4 85 0 0 0.2 1992 0

Drag Reduction IV 6.3 145 0 0 0.5 2000 0

Drag Reduction V 8 225 0 0 1 2010 0

Roll-Over Technology -1.5 100 0 0 2.2 2004 0

Side Impact Technology -1.5 100 0 0 2.2 2004 0

Adv Low Loss Torque

 Converter

2 25 0 0 0 1999 0

Early Torque Converter

 Lockup

0.5 8 0 0 0 2002 0

Aggressive Shift Logic 2 60 0 0 0 1999 0

4-Speed Automatic 4.5 285 0 10 0 1980 0

5-Speed Automatic 6.5 435 0 20 0 1995 0

6-Speed Automatic 8 570 0 30 0 2003 0

6-Speed Manual 2 100 0 20 0 1995 0

CVT 10.5 615 0 -25 0 1998 0

Automated Manual Trans 8 100 0 0 0 2004 0

Roller Cam 2 16 0 0 0 1980 0

OHC/AdvOHV-4 Cylinder 3 80 0 0 0 1980 10

OHC/AdvOHV-6 Cylinder 3 100 0 0 0 1987 10

OHC/AdvOHV-8 Cylinder 3 120 0 0 0 1986 10

4-Valve/4-Cylinder 8 205 0 10 0 1988 17

4-Valve/6-Cylinder 8 280 0 15 0 1992 17

4 Valve/8-Cylinder 8 320 0 20 0 1994 17

5 Valve/6-Cylinder 8 300 0 18 0 1998 20

VVT-4 Cylinder 2.5 45 0 10 0 1994 5

VVT-6 Cylinder 2.5 115 0 20 0 1993 5

VVT-8 Cylinder 2.5 115 0 20 0 1993 5

VVL-4 Cylinder 4 170 0 25 0 1997 10

VVL-6 Cylinder 4 260 0 40 0 2000 10

VVL-8 Cylinder 4 330 0 50 0 2000 10

Camless Valve Actuation-4cyl 7.5 450 0 35 0 2009 13

Camless Valve Actuation-6cyl 7.5 600 0 55 0 2008 13

Camless Valve Actuation-8cyl 7.5 750 0 75 0 2007 13

Cylinder Deactivation 4.5 250 0 10 0 2004 0

Turbocharging/

 Supercharging

6 650 0 -100 0 1980 15

Engine Friction Reduction I 2 25 0 0 0 1992 3

Engine Friction Reduction II 3.5 63 0 0 0 2000 5

Engine Friction Reduction III 5 114 0 0 0 2008 7

Engine Friction Reduction IV 6.5 177 0 0 0 2016 9

Stoichiometric GDI/4-Cylinder 7 300 0 20 0 2006 10

Stoichiometric GDI/6-Cylinder 7 450 0 30 0 2006 10

Lean Burn GDI 5 250 0 20 0 2006 0

5W-30 Engine Oil 1 22.5 0 0 0 1998 0

5W-20 Engine Oil 2 37.5 0 0 0 2003 0

OW-20 Engine Oil 3.1 150 0 0 0 2030 0

Electric Power Steering 2 140 0 0 0 2004 0

Improved Alternator 0.3 15 0 0 0 2005 0

Improved Oil/Water Pump 0.5 10 0 0 0 2000 0

Electric Oil/Water Pump 1 50 0 0 0 2007 0

Tires II 2 30 0 -8 0 1995 0

Tires III 4 75 0 -12 0 2005 0

Tires IV 6 135 0 -16 0 2015 0

Front Wheel Drive 6 250 0 0 -6 1980 0

Four Wheel Drive

 Improvements

2 100 0 0 -1 2000 0

42V-Launch Assist and

 Regen

3 600 0 80 0 2005 -5

42V-Engine Off at Idle 4.5 800 0 45 0 2005 0

Tier 2 Emissions Technology -1 120 0 20 0 2006 0

Increased Size/Weight -1.7 0 0 0 2.55 2003 0

Variable Compression Ratio 4 450 0 25 0 2015 0

Table 26. Standard Technology Matrix For Cars1

1

 Fractional changes refer to the percentage change from the 1990 values.

Sources: Energy and Environment Analysis, Documentation of Technology included in the NEMS Fuel Economy Model for Passenger Cars and Light Trucks 

(September, 2002). National Research Council, Effectiveness and Impact of Corporate Average Fuel Economy (CAFE) Standards (Copyright 2002).
Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 61

Fractional

 Fuel

 Efficiency

 Change

Incremental 

Cost 

(1990$)

Incremental

 Cost 

($/UnitWt.)

Incremental

Weight (Lbs.)

Incremental

Weight

 (Lbs./UnitWt.)

Introduction

 Year

Fractional

 Horsepower 

Change

Unit Body Construction 4 100 0 0 -6 1980 0

Material Substitution II 3.3 0 0.4 0 -5 1994 0

Material Substitution III 6.6 0 0.6 0 -10 2002 0

Material Substitution IV 9.9 0 0.9 0 -15 2010 0

Material Substitution V 13.2 0 1.2 0 -20 2018 0

Drag Reduction II 2.3 40 0 0 0 1992 0

Drag Reduction III 4.4 85 0 0 0.2 1998 0

Drag Reduction IV 6.3 145 0 0 0.5 2006 0

Drag Reduction V 8 225 0 0 1 2014 0

Roll-Over Technology -1.5 100 0 0 2.2 2006 0

Side Impact Technology -1.5 100 0 0 2.2 2006 0

Adv Low Loss Torque Converter 2 25 0 0 0 2005 0

Early Torque Converter Lockup 0.5 8 0 0 0 2003 0

Aggressive Shift Logic 2 60 0 0 0 2003 0

4-Speed Automatic 4.5 285 0 10 0 1980 0

5-Speed Automatic 6.5 435 0 20 0 1999 0

6-Speed Automatic 8 570 0 30 0 2003 0

6-Speed Manual 2 100 0 20 0 2000 0

CVT 10.5 615 0 -25 0 2004 0

Automated Manual Trans 8 100 0 0 0 2004 0

Roller Cam 2 16 0 0 0 1985 0

OHC/AdvOHV-4 Cylinder 3 80 0 0 0 1980 10

OHC/AdvOHV-6 Cylinder 3 100 0 0 0 1990 10

OHC/AdvOHV-8 Cylinder 3 120 0 0 0 1990 10

4-Valve/4-Cylinder 7 205 0 10 0 1998 17

4-Valve/6-Cylinder 7 280 0 15 0 2000 17

4 Valve/8-Cylinder 7 320 0 20 0 2000 17

5 Valve/6-Cylinder 7 300 0 18 0 2010 20

VVT-4 Cylinder 2.5 45 0 10 0 1998 5

VVT-6 Cylinder 2.5 115 0 20 0 1997 5

VVT-8 Cylinder 2.5 115 0 20 0 1997 5

VVL-4 Cylinder 4 170 0 25 0 2002 10

VVL-6 Cylinder 4 260 0 40 0 2001 10

VVL-8 Cylinder 4 330 0 50 0 2006 10

Camless Valve Actuation-4cyl 7.5 450 0 35 0 2014 13

Camless Valve Actuation-6cyl 7.5 600 0 55 0 2012 13

Camless Valve Actuation-8cyl 7.5 750 0 75 0 2011 13

Cylinder Deactivation 4.5 250 0 10 0 2004 0

Turbocharging/Supercharging 6 650 0 -100 0 1987 15

Engine Friction Reduction I 2 25 0 0 0 1992 3

Engine Friction Reduction II 3.5 63 0 0 0 2000 5

Engine Friction Reduction III 5 114 0 0 0 2010 7

Engine Friction Reduction IV 6.5 177 0 0 0 2016 9

Stoichiometric GDI/4-Cylinder 7 300 0 20 0 2008 10

Stoichiometric GDI/6-Cylinder 7 450 0 30 0 2010 10

Lean Burn GDI 5 250 0 20 0 2010 0

5W-30 Engine Oil 1 22.5 0 0 0 1998 0

5W-20 Engine Oil 2 37.5 0 0 0 2003 0

OW-20 Engine Oil 3.1 150 0 0 0 2030 0

Electric Power Steering 2 140 0 0 0 2005 0

Improved Alternator 0.3 15 0 0 0 2005 0

Improved Oil/Water Pump 0.5 10 0 0 0 2000 0

Electric Oil/Water Pump 1 50 0 0 0 2008 0

Tires II 2 30 0 -8 0 1995 0

Tires III 4 75 0 -12 0 2005 0

Tires IV 6 135 0 -16 0 2015 0

Front Wheel Drive 2 250 0 0 -3 1984 0

Four Wheel Drive

 Improvements

2 100 0 0 -1 2000 0

42V-Launch Assist and Regen 3 600 0 80 0 2005 -5

42V-Engine Off at Idle 4.5 800 0 45 0 2005 0

Tier 2 Emissions Technology -1 160 0 20 0 2006 0

Increased Size/Weight -2.5 0 0 0 3.75 2003 0

Variable Compression Ratio 4 450 0 25 0 2015 0

Table 27. Standard Technology Matrix For Light Trucks1

1

Fractional changes refer to the percentage change from the 1990 values.

Sources: Energy and Environment Analysis, Documentation of Technology included in the NEMS Fuel Economy Model for Passenger Cars and Light Trucks

(September, 2002). National Research Council, Effectiveness and Impact of Corporate Average Fuel Economy (CAFE) Standards (Copyright 2002).
Degradation factors (Table 28) used to convert Environmental Protection Agency-rated fuel economy to

actual “on the road” fuel economy are based on table values. Baseline degradation factors are tapplication

of a logistic curve to the projections of three factors: increases in city/highway driving, increashen adjusted

to reflect the percentage of reformulated gasoline consumed.

The vehicle miles traveled (VMT) module forecasts VMT as a function of the cost of driving per mile, and

disposable personal income per capita. Coefficients were re-estimated for AEO2008. Based on output from 

the model, the fuel price elasticity rises to a maximum of -0.13 as fuel prices rise above reference case levels 

in each year.

Commercial Light Duty Fleet Assumptions

With the current focus of transportation legislation on commercial fleets and their composition, the

Transportation Demand Module is designed to divide commercial light-duty fleets into three types: business, 

government, and utility. Based on this classification, commercial light-duty fleet vehicles vary in survival

rates and duration in fleet use before being sold for use as personal vehicles (Table 29). The average length

of time vehicles are kept before being sold for personal use is 4 years for business use, 5 years for

government use, and 6 years for utility use. While the total number of vehicles sold to fleets can vary over

time, the share of total fleet sales by fleet type is held constant at 2003 levels in the Transportation Demand

Module. Of total automobile sales to fleets, 84.8 percent are used in business fleets, 6.5 percent in

government fleets, and 8.7 percent in utility fleets. Of total light truck sales to fleets, 58.4 percent are used in

business fleets, 7.1 percent in government fleets, and 34.5 percent in utility fleets.3 Both the automobile and

light truck shares by fleet type are held constant from 2004 through 2030. In 2003, 19.1 percent of all

automobiles sold and 12.2 percent of all light trucks sold were for fleet use. The share of total automobile and 

light truck sales to fleet remains constant at these levels over the entire forecast period.

Alternative-fuel shares of fleet sales by fleet type are held constant at year 2005 levels. Size class sales

shares of vehicles are held constant at anticipated levels (Table 30).4 Individual sales shares of

alternative-fuel fleet vehicles by technology type are assumed to remain constant for utility, government, and 

for business fleets5(Table 31).

Annual VMT per vehicle by fleet type stays constant over the forecast period based on the Oak Ridge

National Laboratory fleet data. 

Fleet fuel economy for both conventional and alternative-fuel vehicles is assumed to be the same as the

personal new vehicle fuel economy and is subdivided into six EPA size classes for cars and light trucks.

62 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

2000 2005 2010 2015 2020 2030

Cars 79.1 81.3 81.8 82.3 82.8 83.8

Light Trucks 81.0 80.3 80.8 81.3 81.8 82.8

Table 28. Car and Light Truck Degradation Factors

Source: Energy Information Administration, Transportation Sector Model of the National Energy Modeling System, Model Documentation 2007,

DOE/EIA-M070(2007), (Washington, DC, 2007).

 Mini Subcompact Compact Midsize Large 2-Seater

Car 

 Business 0.00 10.52 10.73 42.68 36.07 0.00

 Government 0.00 2.80 39.98 2.84 54.39 0.00

 Utility 0.00 7.86 34.74 12.32 45.08 0.00

5 Pk Pk 5 Van 1 Van 5 Util 1 Util

Light Truck 

 Business 7.94 35.14 7.89 26.76 5.46 16.81

 Government 6.75 50.81 28.41 4.60 1.62 7.81

 Utility 8.22 52.06 5.99 32.69 0.32 0.72

Table 29. 2005 Percent of fleet Alternative Fuel Vehicles by Fleet Type by Size class

Source: CNEAF Alternatives to Traditional Transportation Fuels 2005 (Part II - User and Fuel Data). 

http://www.eia.doe.gov/cneaf/alternate/page/aftables/afvtransfuel_II.html #in use
The Light Commercial Truck Model 

The Light Commercial Truck Module of the NEMS Transportation Model is constructed to represent light

trucks that weigh 8,501 to 10,000 pounds gross vehicle weight (Class 2B vehicles). These vehicles are

assumed to be used primarily for commercial purposes. 

The module implements a twenty-year stock model that estimates vehicle stocks, travel, fuel efficiency, and

energy use by vintage. Historic vehicle sales and stock data, which constitute the baseline from which the

forecast is made, are taken from a recent Oak Ridge National Laboratory study.6 The distribution of vehicles

by vintage, and vehicle scrappage rates is derived from R.L. Polk company registration data.7,

8 Vehicle

travel by vintage was constructed using vintage distribution curves and estimates of average annual travel

by vehicle.9,

10

Because the commercial fleet model operates on three fleet type representations (business, government,

and utility), the federal and state mandates are weighted by fleet vehicle stocks to create a composite 

The vehiclesales modulecompares thelegislatively mandatedsales totheresults from theconsumerdriven 

sales shares. If the consumer driven sales shares are less than the legislatively mandated sales The

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 63

 Fleet Type by Size Class Automobiles Light Trucks

Business Fleet

 Mini 3.12 2.46

 Subcompact 23.42 8.41

 Compact 26.62 23.26

 Midsize 36.15 8.12

 Large 9.90 14.15

 2-seater 0.78 43.60

Government Fleet

 Minl 0.19 6.67

 Subcompact 4.58 43.60

 Compact 20.55 10.44

 Midsize 28.64 17.10

 Large 45.99 3.82

 2-seater 0.05 18.37

Utility Fleet

 Mini 1.50 7.26

 Subcompact 12.47 38.71

 Compact 10.01 11.79

 Midsize 59.23 18.91

 Large 16.42 7.19

 2-seater 0.38 16.15

Table 30. Commercial Fleet Size Class Shares by Fleet and Vehicle Type

(Percentage)

Source: Oak Ridge National Laboratory, Fleet Characteristics and Data Issues, Stacy Davis and Lorena Truett, final report prepared for the

Department of Energy, Energy Information Administration, Office of Integrated Analysis and Forecasting, (Oak Ridge, TN, January 2003).

 Technology Business Government Utility

Ethanol 72.6 54.0 26.8

Methanol 0.0 0.0 0.0

Electric 1.1 3.0 1.1

CNG 4.6 8.5 17.3

LPG 21.7 34.5 54.7

Table 31. Purchases of Alternative-Fuel Vehicles by Fleet Type and Technology Type

(Percentage)

Sources: CNEAF Alternatives to Traditional Transportation Fuels 2005 (part II - User and Fuel Data).

http://www.eia.doe.gov/cneaf/alternate/page/aftables/afvtransfuel_II.html #in use.
The growth in light commercial truck VMT is a function of industrial output for agriculture, mining,

construction, trade, utilities, and personal travel. These industrial groupings were chosen for their

correspondence with output measures being forecast by NEMS. The overall growth in VMT reflects a

weighted average based upon the distribution to total light commercial truck VMT by sector. Forecasted fuel

efficiencies are assumed to increase at the same annual growth rate as light-duty trucks (<8,500 pounds

gross vehicle weight). 

Consumer Vehicle Choice Assumptions 

The Consumer Vehicle Choice Module (CVCM) utilizes a nested multinomial logit (NMNL) model that 

predicts sales shares based on relevant vehicle and fuel attributes. The nesting structure first predicts the 

probability of fuel choice for multi-fuel vehicles within a technology set. The second level nesting predicts 

penetration among similar technologies within a technology set (i.e., gasoline versus diesel hybrids). The 

third level choice determines market share among the different technology sets.11 The technology sets 

include:

• Conventional fuel capable (gasoline, diesel, bi-fuel and flex-fuel),

• Hybrid (gasoline and diesel),

• Dedicated alternative fuel (CNG, LPG, methanol, and ethanol),

• Fuel cell (gasoline, methanol, and hydrogen), and

• Electric battery powered (lead acid, nickel-metal hydride,lithium polymer)12

The vehicle attributes considered in the choice algorithm include: price, maintenance cost, battery

replacement cost, range, multi-fuel capability, home refueling capability, fuel economy, acceleration and

luggage space. With the exception of maintenance cost, battery replacement cost, and luggage space,

vehicle attributes are determined endogenously.13 The fuel attributes used in market share estimation

include availability and price. Vehicle attributes vary by six EPA size classes for cars and light trucks and fuel

availability varies by Census division. The NMNL model coefficients were developed to reflect purchase

decisions for cars and light trucks separately. 

Where applicable, CVCM fuel efficient technology attributes are calculated relative to conventional gasoline

miles per gallon. It is assumed that many fuel efficiency improvements in conventional vehicles will be

transferred to alternative-fuel vehicles. Specific individual alternative-fuel technological improvements are

also dependent upon the CVCM technology type, cost, research and development, and availability over

time. Make and model availability estimates are assumed according to a logistic curve based on the initial

technology introduction date and current offerings. Coefficients summarizing consumer valuation of vehicle

attributes were derived from assumed economic valuation compared to vehicle price elasticities. Initial

CVCM vehicle stocks are set according to EIA surveys.14 A fuel switching algorithm based on the relative

fuel prices for alternative fuels compared to gasoline is used to determine the percentage of total VMT

represented by alternative fuels in bi-fuel and flex-fuel alcohol vehicles.

Freight Truck Assumptions 

The freight truck module estimates vehicle stocks, travel, fuel efficiency, and energy use of three size

classes: light medium (Class 3), heavy medium (Classes 4 -6), and heavy (Classes 7-8). Within the size

classes, the stock model structure is designed to cover twenty vehicle vintages and estimate energy use by

four fuel types: diesel, gasoline, LPG, and CNG. Fuel consumption estimates are reported regionally (by

Census Division) according to the distillate fuel shares from the State Energy Data Report.

15 The technology 

input data specific to the different types of trucks including the year of introduction, incremental fuel efficiency 

improvement, and capital cost of introducing the new technologies, is shown in Table 32.

64 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008
Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 65

Medium Light Trucks Medium Heavy Trucks Heavy Trucks

Technology 

Type

Intro ductio n 

Year

Capital

 Cost

Incr. 

Fuel 

Econ. 

Improvement

Introduction

 Year

Capital 

Cost

Incr. 

Fuel 

Econ. 

Improvement

Introduction

 Year

Capital

 Cost

Incr. 

Fuel 

Econ. 

Improvement

Areo dynamic I: Cab top

deflector,

sloping hood and cab

side flares

2002 600.00 0.023 0 750.00 0.023 0 750.00 0.018

Closing/covering of gap

between tractor and

trailer, aero dynamic

bumper, underside air

baffles, wheel well

covers

N/A N/A 0.000 2004 800.00 0.036 2005 1500.00 0.023

Trailer leading and

trailing edge curvatures

N/A N/A 0.000 2005 400.00 0.009 2005 500.00 0.012

Aero Dynamics IV:

pneumatic blowing

N/A N/A 0.000 N/A N/A 0.000 2010 2500.00 0.045

Tires I: radials 0 40.00 0.018 0 180.00 0.018 0 300.00 0.014

Tires II: low rolling

resistance 

2004 180.00 0.023 2005 280.00 0.023 2005 550.00 0.027

Tires III: super singles N/A N/A 0.000 N/A N/A 0.000 2008 700.00 0.018

Tires IV: reduced rolling

resistance from

pneumatic blowing

N/A N/A 0.000 N/A N/A 0.000 2015 500.00 0.011

Transmission: lock-up,

electronic controls,

reduced friction

2005 750.00 0.018 2005 900.00 0.018 2005 1000.00 0.020

Diesel Engine I:

turbocharged, direct

injection with better

thermal management

2003 700.00 0.045 2004 1000.00 0.072 N/A N/A 0.000

Diesel Engine II:

integrated

starter/alternator with

idle off and limited

regenerative breaking

2005 1500.00 0.045 2005 1200.00 0.045 N/A N/A 0.000

Diesel Engine III:

improved engine iwth

lower friction, better

injectors, and efficient

combustion

2012 2000.00 0.090 2008 2000.00 0.072 N/A 300.00 0.000

Diesel Engine IV: hybrid

electric powertrain

2010 6000.00 0.360 2010 8000.00 0.360 N/A N/A 0.000

Diesel Engine V: internal 

friction reduction -

iimproved lubricants and

bearings

N/A N/A 0.000 N/A N/A 0.000 2005 500.00 0.020

Diesel Engine VI:

increased peak cylinder

pressure

N/A NA 0.000 N/A N/A 0.000 2006 1000.00 0.040

Diesel Engine VII:

improved injectors and

more efficient

combustion

N/A N/A 0.000 N/A N/A 0.000 2007 N/A 0.060

Diesel Engine VIII:

reduce waste heat

improved thermal

management

N/A N/A 0.000 N/A N/A 0.000 2010 N/A 0.000

Table 32. Standard Technology Matrix for Freight Trucks
66 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Medium Light Trucks Medium Heavy Trucks Heavy Trucks

Technology 

Type Introduction 

Year

Capital

 Cost

Incr. 

Fuel 

Econ. 

Improvement

Introduction

 Year

Capital 

Cost

Incr. 

Fuel 

Econ. 

Improvement

Introduction

 Year

Capital

 Cost

Incr. 

Fuel 

Econ. 

Improvement

Gasoline Engine I:

electronic fuel

injection, DOHC,

multiple values

2003 700.00 0.045 2003 1000.00 0.045 N/A N/A 0.000

Gasoline Engine II:

integrated

starter/alternator with

idle off and limited

regenerative breaking

2005 1000.00 0.045 2005 1200.00 0.072 N/A N/A 0.000

Gasoline Engine III:

direct injection (GDI)

2008 700.00 0.108 2008 1000.00 0.108 N/A N/A 0.000

Gasoline Engine IV;

hybrid electric

powertrain

2010 6000.00 0.405 2010 8000.00 0.405 N/A N/A 0.000

Weight Reduction I:

high strength

lightweight materials

2010 1300.00 0.045 2007 2000.00 0.045 2005 2000.00 0.100

Diesel Emission-NOx

I: exhaust

recirculation, timing

retard, selective

catalytic reduction

2002 250.00 -0.040 2003 400.00 -0.040 2003 500.00 -0.040

Diesel Emissions-NOx

II: nitrogen enriched

combustion air

2003 500.00 -0.005 2003 700.00 -0.005 2003 750.00 -0.005

Diesel Emissions-NOx

III: non-thermal

plasma catalyst

2007 1000.00 -0.015 2006 1200.00 -0.015 2007 1250.00 -0.015

Diesel Emissions-NOx

IV: NOx absorber

system

2007 1500.00 -0.030 2006 2000.00 -0.030 2007 2500.00 -0.030

Diesel Emission-PM I: 

oxidation catalyst

2002 150.00 -0.005 2002 200.00 -0.005 2002 250.00 -0.005

Diesel Emission-PM

II: catalytic particulate 

filter

2006 1000.00 -0.015 2006 1250.00 -0.025 2006 1500.00 -0.015

Diesel EmissionHC/CO I: oxidation

catalyst

2002 150.00 -0.005 2002 200.00 -0.005 2002 250.00 -0.005

Diesl EmissionHC/CO II: closed

crankcase system

2005 50.00 0.000 2005 65.00 0.000 2005 75.00 0.000

Gasoline EmissionPM I: Improved

oxidation catalyst

2005 250.00 -0.003 2005 350.00 -0.003 N/A N/A 0.000

Gasoline

Emission-NOx I: 

EGR/spark retard

2002 25.00 -0.015 2002 25.00 -0.015 N/A N/A 0.000

Gasoline

Emission-NOx II: 

oxygen sensors 

2003 75.00 0.000 2003 75.00 0.000 N/A N/A 0.000

Gasoline

Emission-NOx III:

secondary air/closed

loop system

2008 50.00 0.000 2008 50.00 0.000 N/A N/A 0.000

Table 32. Standard Technology Matrix for Freight Trucks (cont.)
The freight module uses projections of dollars of industrial output to estimate growth in freight truck travel.

The industrial output is converted to an equivalent measure of volume output using freight adjustment

coefficients. 16,

17 These freight adjustment coefficients vary by North American Industrial Classification

System (NAICS) code with the deviation diminishing gradually over time toward parity. Freight truck

load-factors (ton-miles per truck) by NAICS code are constants formulated from historical data. 18

Fuel economy of new freight trucks is dependent on the market penetration of various emission control

technologies and advanced technology components.19 For the advanced technology components, market

penetration is determined as a function of technology type, cost effectiveness, and introduction year. Cost

effectiveness is calculated as a function of fuel price, vehicle travel, fuel economy improvement, and

incremental capital cost. Emissions control equipment is assumed to enter the market to meet regulated

emission standards. 

Heavy truck freight travel is estimated by class size and fuel type based on matching projected freight travel

demand (measured by industrial output) to the travel supplied by the current fleet. Travel by vintage and size

class is then adjusted so that total travel meets total demand. Initial heavy vehicle travel, by vintage and size

class, is derived using Vehicle Inventory and Use Survey (VIUS) data.20

Initial freight truck stocks by vintage are obtained from R. L. Polk Co. and are distributed by fuel type using

VIUS data.21 Vehicle scrappage rates are also estimated using R. L. Polk Co. data.22

Freight and Transit Rail Assumptions

The freight rail module uses the industrial output by NAICS code measured in real 1987 dollars and converts

these dollars into an adjusted volume equivalent. Coal production from the NEMS Coal Market Module is

used to adjust coal rail travel. Freight rail adjustment coefficients (used to convert dollars to volume

equivalents) are based on historical data and remain constant.23,

24 Initial freight rail efficiencies are based

on the freight model from Argonne National Laboratory.25 The distribution of rail fuel consumption by fuel

type is also based on historical data and remains constant.26 Regional freight rail consumption estimates are 

distributed according to the State Energy Data Report.

27

Domestic and International Shipping Assumptions

As done in the previous sub-module, the domestic freight shipping module uses the industrial output by

NAICS code measured in real 1987 dollars and converts these dollars into an adjusted volume equivalent. 

The freight adjustment coefficients (used to convert dollars to volume equivalents) are based on historical

data. Domestic shipping efficiencies are based on the model developed by Argonne National Laboratory.

The energy consumption in the international shipping module is a function of the total level of imports and

exports. The distribution of domestic and international shipping fuel consumption by fuel type is based on

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 67

Medium Light Trucks Medium Heavy Trucks Heavy Trucks

Technology 

Type

Introduction 

Year

Capital

 Cost

Incr. 

Fuel 

Econ. 

Improvement

Introduction

 Year

Capital 

Cost

Incr. 

Fuel 

Econ. 

Improvement

Introduction

 Year

Capital

 Cost

Incr. 

Fuel 

Econ. 

Improvement

Gasoline EmissionHC/CO I: oxygen

sensors 2003 75.00 0.000 2003 75.00 0.000 N/A N/A 0.000

Gasoline EmissionHC/CO II: evap.

canister w/improved

vaccum, materials,

and connectors

2003 50.00 0.000 2003 50.00 0.000 N/A N/A 0.000

Gasoline EmissionHC/CO III: oxidation

catalyst

2005 250.00 -0.003 2005 350.00 -0.003 N/A N/A 0.000

1. Payback period is same for the three modes.

Table 32. Standard Technology Matrix for Freight Trucks (cont.)
historical data and remains constant throughout the forecast. 28 Regional domestic shipping consumption

estimates are distributed according to the residual oil regional shares in the State Energy Data Report. 

29

Air Travel Demand Assumptions

The air travel demand module calculates the domestic and international ticket prices for travel as a function

of fuel cost. The ticket price is constrained to be no lower than the current lowest cost per mile provider,

adjusted by load factor. Domestic and international revenue passenger miles are based on historic data,30

per capita income, and ticket price. The revenue ton miles of air freight are based on merchandise exports,

gross domestic product, and fuel cost.31

Airport capacity constraints based on the FAA’s Airport Capacity Benchmark Report 2004 are incorporated

into the air travel demand module using airport capacity measures.32 Airport capacity is defined by the

maximum number of flights per hour airports can routinely handle, the amount of time airports operate at

optimal capacity, and passenger load factors. Capacity is expected to increase over time due to planned

infrastructure improvements. If the projected demand in air travel exceeds the capacity constraint, demand

is reduced to match the constraint.

Aircraft Stock/Efficiency Assumptions

The aircraft stock and efficiency module consists of a world, US and Non-US, stock model of wide body,

narrow body, and regional jets by vintage. Total aircraft supply for a given year is based on the initial supply

of aircraft for model year 2003, new passenger sales, and the survival rate by vintage (Table 33).33 New

passenger sales are a function of revenue passenger miles and gross domestic product. 

68 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Age of Aircraft (years)

Aircraft Type New 1-10 11-20 21-30 >30 Total

Passenger

 Narrow Body 135 1,578 1,405 537 308 3,963

 Wide Body 9 303 255 124 36 727

 Regional Jets 94 1,863 70 7 12 2,046

Cargo

 Narrow Body 1 21 67 156 329 574

 Wide Body 8 127 177 26 196 769

 Regional Jets 0 0 4 23 13 40

Survival Curve

 (fraction) New 5 10 20 30

 Narrow Body 1.0000 0.9998 0.9992 0.9911 0.9256

 Wide Body 1.0000 0.9980 0.9954 0.9754 0.8892

 Regional Jets 1.0000 0.9967 0.9942 0.9816 0.9447

Table 33. 2006 USA Passenger and Cargo Aircraft Supply and Survival Rate

Source: Jet Information Services, 2006 World Jet Inventory, data tables (2006).
Older planes, wide and narrow body planes over 25 years of age are placed as cargo jets according to a

cargo percentage varying from 50 percent of 25 year old planes to 100 percent of those aircraft 30 years and

older. The available seat-miles per plane, which measure the carrying capacity of the airplanes by aircraft

type, vary over time, with wide bodies remaining constant and narrow bodies increasing.34 The difference

between the seat-miles demanded and the available seat-miles represents potential newly purchased

aircraft. If demand is less than supply, then passenger aircraft is either parked or exported, starting with

twenty nine year old aircraft, at a pre-defined rate. Aircraft continues to be parked until equilibrium is

reached. If supply is less than demand planes are either imported or unparked and brought back into

service. 

Technological availability, economic viability, and efficiency characteristics of new aircraft are assumed to

grow at a fixed rate. Fuel efficiency of new aircraft acquisitions represents, at a minimum, a 5-percent

improvement over the stock efficiency of surviving airplanes. Maximum growth rates of fuel efficiency for

new aircraft are based on a fixed growth rate. Regional shares of all types of aircraft fuel use are assumed to

be constant and are consistent with the State Energy Data Report estimate of regional jet fuel shares.

Legislation and Regulations

Energy Independence and Security Act of 2007 (EISA2007)

The EISA2007 legislation requires the development of fuel economy standards for work trucks (8,500 lbs. to

less than 10,000 lbs GVWR) and commercial medium- and heavy-duty on-highway vehicles (10,000 lbs or

more GVWR). The new fuel economy standards require consideration of vehicle attributes and duty

requirements and can prescribe standards for different classes of vehicles, such as buses used in urban

operation or semi-trucks used primarily in highway operation. The Act provides a minimum of 4 full model

years lead time before the new fuel economy standard is adopted and 3 full model years after the new fuel

economy standard has been established before the fuel economy standards for work trucks can be

modified. Because these fuel economy standards are pending and NEMS does not currently model fuel

economy regulation for work trucks or commercial medium- and heavy- duty vehicles, this aspect of the Act

is not included in AEO2008.

A fuel economy credit trading program is established based on EISA2007. Currently, CAFE credits earned

by manufacturers can be banked for up to 3 years and can only be applied to the fleet (car or light truck) from

which the credit was earned. Starting in model year 2011 the credit trading program will allow manufacturers

whose automobiles exceed the minimum fuel economy standards to earn credits that can be sold to other

manufacturers whose automobiles fail to achieve the prescribed standards. The credit trading program is

designed to ensure that the total oil savings associated with manufacturers that exceed the prescribed

standards are preserved when credits are sold to manufacturers that fail to achieve the prescribed

standards. While the credit trading program begins in 2011, EISA2007 allows manufacturers to apply credits

earned to any of the 3 model years prior to the model year the credits are earned, and to any of the 5 model

years after the credits are earned. The transfer of credits within a manufacturer’s fleet is limited to specific

maximums. For model years 2011 through 2013, the maximum transfer is 1.0 mpg; for model years 2014

through 2017, the maximum transfer is 1.5 mpg; and for model years 2018 and later, the maximum credit

transfer is 2.0 mpg. NEMS currently has a switch that allows for sensitivity analysis of CAFE credit banking

by manufacturer fleet, but does not model the trading of credits across manufacturers. The AEO2008 does

not consider trading of credits since this would require significant modifications to NEMS and detailed

technology cost and efficiency data by manufacturer, which is not readily available. 

The CAFE credits specified under the Alternative Motor Fuels Act (AMFA) through 2019 is extended. Prior to 

passage of this Act, the CAFE credits under AMFA were scheduled to expire after model year 2010.

Currently, 1.2 mpg is the maximum CAFE credit that can be earned from selling alternative fueled vehicles.

EISA2007 extends the 1.2 mpg credit maximum through 2014 and reduces the maximum by 0.2 mpg for

each following year until it is phased out by model year 2020. NEMS does not model CAFE credits earned

from alternative fuel vehicles sales because manufacturer specific data would be required and although

some manufacturer detail is represented for light trucks, there is no manufacturer detail currently

represented for cars. In addition, an algorithm that counts credits earned from the sale of alternative fueled

vehicles would need to be added to NEMS, which would require significant modification to the model

structure. AEO2008 does not consider this section of the Act.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 69
The Energy Policy Act of 2005

The Energy Policy Act of 2005 provides tax credits for the purchase of vehicles that have a lean burn engine

or employ a hybrid or fuel cell propulsion system. The amount of the credit received for a vehicle is based the 

vehicle’s inertia weight, improvement in city tested fuel economy relative to an equivalent 2002 base year

value, emissions classification, and type of propulsion system. The tax credit is also sales limited by

manufacturer for vehicles with lean burn engines or hybrid propulsion systems. After December 31, 2005,

the first calendar quarter a manufacturer’s sales of lean burn or hybrid vehicles reaches 60,000 units, the

phase out period begins. Reduction of credits begins in the second calendar quarter following the initial

quarter the sales maximum was reached. For that quarter and the following quarter, the applicable tax credit 

will be reduced by 50 percent. For the subsequent third and fourth calendar quarters, the applicable tax

credit is reduced to 25 percent of the original value. These tax credits are included in the AEO2008.

Energy Policy Act of 1992 (EPACT)

Fleet alternative-fuel vehicle sales necessary to meet the EPACT regulations are derived based on the 

mandates as they currently stand and the Commercial Fleet Vehicle Module calculations. Total projected 

AFV sales are divided into fleets by government, business, and fuel providers (Table 34). 

Because the commercial fleet model operates on three fleet type representations (business, government,

and utility), the federal and state mandates are weighted by fleet vehicle stocks to create a composite

mandate for both. The same combining methodology is used to create a composite mandate for electric

utilities and fuel providers based on fleet vehicle stocks.35

Low Emission Vehicle Program (LEVP)

The LEVP was originally passed into legislation in 1990 in the State of California. It began as the

implementation of a voluntary opt-in pilot program under the purview of Clean Air Act Amendments of 1990

(CAAA90), which included a provision that other States could opt in to the California program to achieve

lower emissions levels than would otherwise be achieved through CAAA90. Twelve states have elected to

adopt the California LEVP.

The LEVP is an emissions-based policy, setting sales mandates for 6 categories of low-emission vehicles:

low-emission vehicles (LEVs), ultra-low-emission vehicles (ULEVs), super-ultra low emission vehicles

(SULEVs), partial zero-emission vehicles (PZEVs), advanced technology partial zero emission vehicles

(AT-PZEVs), and zero-emission vehicles (ZEVs). The LEVP requires that in 2005 10 percent of a

manufacturer’s sales are ZEVs or equivalent ZEV earned credits, increasing to 11 percent in 2009, 12

percent in 2012, 14 percent in 2015, and 16 percent in 2018 where it remains constant thereafter. In August

2004, CARB enacted further amendments to the LEVP that place a greater emphasis on emissions

reductions from PZEVs and AT-PZEVs and requires that manufacturers produce a minimum number of fuel

cell and electric vehicles. In addition, manufacturers are allowed to adopt alternative compliance

requirements for ZEV sales that are based on cumulative fuel cell vehicle sales targets for vehicles sold in all

States participating in California’s LEVP. Under the alternative compliance requirements, ZEV credits can

also be earned by selling battery electric vehicles. Currently, all manufacturers have opted to adhere to the

alternative compliance requirements. The mandate still includes phase-in multipliers for pure ZEVs and

allows 20 percent ofthe sales requirementto be met with AT-PZEVs and 60 percent ofthe requirementto be

met with PZEVs. AT-PZEVs and PZEVs are allowed 0.2 credits per vehicle. EIA assumes that credit

allowances for PZEVs will be met with conventional vehicle technology, hybrid vehicles will be sold to meet

the AT-PZEV allowances, and that hydrogen fuel cell vehicles will be sold to meet the pure ZEV

requirements under the alternative compliance path.

70 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

 Year Federal State Fuel Providers Electric Utilities

2005 75 75 70 90

Table 34. EPACT Legislative Mandates for AFV Purchases by Fleet Type and Year

(Percent)

Source: EIA, Energy Efficiency and Renewable Energy (Washington, DC, 2005), http://www1.eere.energy.gov/femp/about/fleet-requirements.html,

http://www1.eere.energy.gov/vehicles and fuels/epact/state/state-gov.html.
vehicle sales module compares the legislatively mandated sales to the results from the consumer driven

sales shares. If the consumer driven sales shares are less than the legislatively mandated sales

requirements, then the legislative requirements serve as a minimum constraint for the hybrid, electric, and

fuel cell vehicle sales. 

Transportation Alternative Cases

High Technology Case

In the high technology case, the conventional fuel saving technology characteristics came from a study by

the American Council for an Energy Efficient Economy.36 Tables 35 and 36 summarize the High Technology 

matrix for cars and light trucks. High technology case assumptions for heavy trucks reflect the optimistic

values, with respect to efficiency improvement, for advanced engine and emission control technologies as

reported by ANL.37

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 71
72 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Fractional

 Fuel

Efficiency

 Change

Incremental 

Cost 

(1990$)

Incremental 

Cost 

($/Unit Wt.)

Incremental

 Weight

 (Lbs.)

Incremental 

Weight

 (Lbs./Unit

 Wt.)

Introduction

 Year

Fractional

 Horsepower

 Change

Unit Body Construction 4 100 0 0 -6 1980 0

Material Substitution II 3.3 0 0.4 0 -5 1990 0

Material Substitution III 6.6 0 0.5 0 -10 1998 0

Material Substitution IV 9.9 0 0.5 0 -15 2006 0

Material Substitution V 13.2 0 1.1 0 -20 2014 0

Drag Reduction II 1.6 0 0 0 0 1988 0

Drag Reduction III 3.2 0 0 0 0.2 1992 0

Drag Reduction IV 6.3 145 0 0 0.5 2000 0

Drag Reduction V 8 225 0 0 1 2010 0

Roll-Over Technology -1.5 100 0 0 2.2 2004 0

Side Impact Technology -1.5 100 0 0 2.2 2004 0

Adv Low Loss Torque Converter 2 25 0 0 0 1999 0

Early Torque Converter Lockup 1 8 0 0 0 2002 0

Aggressive Shift Logic 3.5 65 0 0 0 1999 0

4-Speed Automatic 4.5 285 0 10 0 1980 0

5-Speed Automatic 8 410 0 20 0 1995 0

6-Speed Automatic 9.5 495 0 30 0 2003 0

6-Speed Manual 2 80 0 20 0 1995 0

CVT 11.5 365 0 -25 0 1998 0

Automated Manual Trans 8 100 0 0 0 2004 0

Roller Cam 2 16 0 0 0 1980 0

OHC/AdvOHV-4 Cylinder 3 60 0 0 0 1980 10

OHC/AdvOHV-6 Cylinder 3 80 0 0 0 1987 10

OHC/AdvOHV-8 Cylinder 3 100 0 0 0 1986 10

4-Valve/4-Cylinder 8.8 185 0 10 0 1988 17

4-Valve/6-Cylinder 8.8 260 0 15 0 1992 17

4 Valve/8-Cylinder 8.8 320 0 20 0 1994 17

5 Valve/6-Cylinder 9 300 0 18 0 1998 20

VVT-4 Cylinder 2.5 30 0 10 0 1994 5

VVT-6 Cylinder 2.5 90 0 20 0 1993 5

VVT-8 Cylinder 2.5 90 0 20 0 1993 5

VVL-4 Cylinder 7.5 150 0 25 0 1997 10

VVL-6 Cylinder 7.5 205 0 40 0 2000 10

VVL-8 Cylinder 7.5 290 0 50 0 2000 10

Camless Valve Actuation-4cyl 12 450 0 35 0 2009 13

Camless Valve Actuation-6cyl 12 600 0 55 0 2008 13

Camless Valve Actuation-8cyl 12 750 0 75 0 2007 13

Cylinder Deactivation 9 250 0 10 0 2004 0

Turbocharging/ Supercharging 5 475 0 -100 0 1980 15

Engine Friction Reduction I 2 25 0 0 0 1992 3

Engine Friction Reduction II 3.5 63 0 0 0 2000 5

Engine Friction Reduction III 5 114 0 0 0 2008 7

Engine Friction Reduction IV 6.5 177 0 0 0 2016 9

Stoichiometric GDI/4-Cylinder 7 300 0 20 0 2006 10

Stoichiometric GDI/6-Cylinder 7 450 0 30 0 2006 10

Lean Burn GDI 6 250 0 20 0 2006 0

5W-30 Engine Oil 1 10.5 0 0 0 1998 0

5W-20 Engine Oil 2 20 0 0 0 2003 0

OW-20 Engine Oil 3.1 80 0 0 0 2030 0

Electric Power Steering 2 50 0 0 0 2004 0

Improved Alternator 0.3 15 0 0 0 2005 0

Improved Oil/Water Pump 0.5 10 0 0 0 2000 0

Electric Oil/Water Pump 1 50 0 0 0 2007 0

Tires II 1.5 15 0 -8 0 1995 0

Tires III 3 35 0 -12 0 2005 0

Tires IV 6 90 0 -16 0 2015 0

Front Wheel Drive 6 250 0 0 -6 1980 0

Four Wheel Drive Improvements 2 100 0 0 -1 2000 0

42V-Launch Assist and Regen 5 400 0 80 0 2005 -5

42V-Engine Off at Idle 6 500 0 45 0 2005 0

Tier 2 Emissions Technology -1 120 0 20 0 2006 0

Increased Size/Weight -1.7 0 0 0 2.55 2003 0

Variable Compression Ratio 4 350 0 25 0 2015 0

Table 35. High Technology Matrix For Cars

Source: Energy and Environmental Analysis, Documentation of Technology included in the NEMS Fuel Economy Model for Passenger Cars and Light

Trucks (September, 2002). National Research Council, Effectiveness and Impact of Corporate Average Fuel Economy (CAFE) Standards (Copyright

2002).
Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 73

Fractional

 Fuel

 Efficiency

 Change Incremental 

Cost (1990$)

Incremental

Cost ($/Unit

 Wt.)

Incremenal

Weight

 (Lbs.)

Incremental

Weight

 (Lbs./Unit

 Wt.)

Introduction

 Year

Fractional

 Horsepower

 Change

Unit Body Construction 4 100 0 0 -6 1980 0

Material Substitution II 3.3 0 0.4 0 -5 1994 0

Material Substitution III 6.6 0 0.5 0 -10 2002 0

Material Substitution IV 9.9 0 0.5 0 -15 2010 0

Material Substitution V 13.2 0 1.1 0 -20 2018 0

Drag Reduction II 1.6 0 0 0 0 1992 0

Drag Reduction III 3.2 0 0 0 0.2 1998 0

Drag Reduction IV 6.3 145 0 0 0.5 2006 0

Drag Reduction V 8 225 0 0 1 2014 0

Roll-Over Technology -1.5 100 0 0 2.2 2006 0

Side Impact Technology -1.5 100 0 0 2.2 2006 0

Adv Low Loss Torque

 Converter

2 25 0 0 0 2005 0

Early Torque Converter

 Lockup

1 8 0 0 0 2003 0

Aggressive Shift Logic 3.5 65 0 0 0 2003 0

4-Speed Automatic 4.5 285 0 10 0 1980 0

5-Speed Automatic 8 410 0 20 0 1999 0

6-Speed Automatic 9.5 495 0 30 0 2003 0

6-Speed Manual 2 80 0 20 0 2000 0

CVT 11.5 365 0 -25 0 2004 0

Automated Manual Trans 8 100 0 0 0 2004 0

Roller Cam 2 16 0 0 0 1985 0

OHC/AdvOHV-4 Cylinder 3 60 0 0 0 1980 10

OHC/AdvOHV-6 Cylinder 3 80 0 0 0 1990 10

OHC/AdvOHV-8 Cylinder 3 100 0 0 0 1990 10

4-Valve/4-Cylinder 8.8 185 0 10 0 1998 17

4-Valve/6-Cylinder 8.8 260 0 15 0 2000 17

4 Valve/8-Cylinder 8.8 320 0 20 0 2000 17

5 Valve/6-Cylinder 9 300 0 18 0 2010 20

VVT-4 Cylinder 2.5 30 0 10 0 1998 5

VVT-6 Cylinder 2.5 90 0 20 0 1997 5

VVT-8 Cylinder 2.5 90 0 20 0 1997 5

VVL-4 Cylinder 7.5 150 0 25 0 2002 10

VVL-6 Cylinder 7.5 205 0 40 0 2001 10

VVL-8 Cylinder 7.5 290 0 50 0 2006 10

Camless Valve

 Actuation-4cyl

12 450 0 35 0 2014 13

Camless Valve

 Actuation-6cyl

12 600 0 55 0 2012 13

Camless Valve

 Actuation-8cyl

12 750 0 75 0 2011 13

Cylinder Deactivation 9 250 0 10 0 2004 0

Turbocharging/Supercharging 5 475 0 -100 0 1987 15

Engine Friction Reduction I 2 25 0 0 0 1992 3

Engine Friction Reduction II 3.5 63 0 0 0 2000 5

Engine Friction Reduction III 5 114 0 0 0 2010 7

Engine Friction Reduction IV 6.5 177 0 0 0 2016 9

Stoichiometric GDI/4-Cylinder 7 300 0 20 0 2008 10

Stoichiometric GDI/6-Cylinder 7 450 0 30 0 2010 10

Lean Burn GDI 6 250 0 20 0 2010 0

5W-30 Engine Oil 1 10.5 0 0 0 1998 0

5W-20 Engine Oil 2 20 0 0 0 2003 0

OW-20 Engine Oil 3.1 80 0 0 0 2030 0

Electric Power Steering 2 50 0 0 0 2005 0

Improved Alternator 0.3 15 0 0 0 2005 0

Improved Oil/Water Pump 0.5 10 0 0 0 2000 0

Electric Oil/Water Pump 1 50 0 0 0 2008 0

Tires II 1.5 15 0 -8 0 1995 0

Tires III 3 35 0 -12 0 2005 0

Tires IV 6 90 0 -16 0 2015 0

Front Wheel Drive 6 250 0 0 -3 1984 0

Four Wheel Drive

 Improvements

2 100 0 0 -1 2000 0

42V-Launch Assist and Regen 5 400 0 80 0 2005 -5

42V-Engine Off at Idle 6 500 0 45 0 2005 0

Tier 2 EmissionsTechnology -1 120 0 20 0 2006 0

Increased Size/Weight -1.7 0 0 0 3.75 2003 0

Variable Compression Ratio 4 350 0 25 0 2015 0

Table 36. High Technology Matrix For Light Trucks

Source: Energy and Enviromental Analysis, Documentation of Technology included in the NEMS Fuel Economy Model for Passenger Cars and Light

Trucks (September, 2002). National Research Council, Effectiveness and Impact of Corporate Average Fuel Economy (CAFE) Standards (Copyright

2002).
[1] U.S. Department of Transportation, National Highway Traffic and Safety Administration, “Summary of

Fuel Economy Performance”, (Washington, DC, March 2004). 

[2] Goldberg, Pinelopi Koujianou, “Product Differentiation and Oligopoly In International Markets: The Case

of The U.S. Automobile Industry,” Econometrica, Vol. 63, No.4 (July, 1995), 891-951. 

[3] Oak Ridge National Laboratory, “Fleet Characteristics And Data Issues,” Davis, Stacy C, Lorena Truett,

Oak Ridge National Laboratory, (Oak Ridge, TN, january 2003). 

[4] Bobit Publishing Company, The Fleet Fact Book, various issues (Redondo Beech, California). 

[5] Bobit Publishing Company, Note 4. 

[6] Davis, Stacy C., Lorena F. Truett, “Investigation of Class 2B Trucks (Vehicles of 8,500 to 10,000 LBS

GVWR),” Oak Ridge National Laboratory, ORNL/TM-2002/49, March 2002. 

[7] Davis, Stacy C., Lorena F. Truett, op.cit., Note 6. 

[8] Greenspan, Alan, and Darrel Cohen, “Motor Vehicle Stocks, Scrappage, and Sales,” Federal Reserve

Board (Washington, DC, October 30, 1996). 

[9] Oak Ridge National Laboratory, Transportation Energy Data Book: 26 and Annual (Oak Ridge, TN,

2007). 

[10] Davis, Stacy C., Lorena F. Truett, op.cit., Note 6. 

[11] Greene, David L. and S.M. Chin, “Alternative Fuels and Vehicles (AFV) Model Changes,” Center for

Transportation Analysis, Oak Ridge National Laboratory, (Oak Ridge, TN, November 14, 2000). 

[12] U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, prepared by

Interlaboratory Working Group, Scenarios of U.S. Carbon Reductions: Potential Impacts of Energy

Technologies by 2010 and Beyond, (Washington, DC, 1998). 

[13] Energy and Environmental Analysis, Inc., Updates to the Fuel Economy Model (FEM) and Advanced

Technology Vehicle (ATV) Module of the National Energy Modeling System (NEMS) Transportation Model,

Prepared for the Energy Information Administration (EIA), (Arlington, VA, October 23, 2000).

[14] Energy Information Administration, Alternatives to Traditional Transportation Fuels 2005,

hhttp://www.eia.doe.gov/cneaf/alternate/page/aftables/afvtransfuel_II.html #in use.

[15] Energy Information Administration, State Energy Data 2005 Consumption,

http://www.eia.doe.gov/emeu/states/_Seds.html. 

[16] Decision Analysis Corporation of Virginia, “Re-estimation of Freight Adjustment Coefficients,” Report

prepared for the Energy Information Administration (EIA), February 28, 1995). 

[17] Reebie Associates, TRANSEARCH Freight Commodity Flow Database, (Greenwich, CT, 1992). 

[18] U.S. Department of Commerce, Bureau of Census, Vehicle Inventory and Use Survey, EC97TV,

(Washington, DC, October 1999). 

[19] Vyas, A., C. Saricks, and F. Stodolsky, “The Potential Effect of Future Energy Efficiency and 

Emissions Improving Technology on Fuel Consumption of Heavy Trucks,” Argonne National Laboratory,

(Argonne, IL, 2002). 

[20] Davis, Stacy C., “Memorandum on the Distribution of Trucks by Age and Weight: 2000 Truck

Population,” Oak Ridge National Laboratory, (Oak Ridge, TN, November 2001) 

74 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Notes and Sources
[21] Davis, Stacy C., op. cit., Note 20. 

[22] Schmoyer, Rick, “Scrappage of Heavy Trucks - Estimates for the Year 2000,” Oak Ridge National

Laboratory, DRAFT, (Oak Ridge, TN, June 2001). 

[23] Decision Analysis Corporation of Virginia, op. cit. Note 19. 

[24] Reebie Associates, op. cit., Note 17. 

[25] Argonne National Laboratory, Transportation Energy Demand Through 2010, (Argonne, IL, 1992). 

[26] U.S. Department of Transportation, Federal Railroad Administration, “1989 Carload Waybill 

Statistics; Territorial Distribution, Traffic and Revenue by Commodity Classes,” (September 1991 and Prior

issues). 

[27] Energy Information Administration, op. cit., Note 15. 

[28] Army Corps of Engineers, Waterborne Commerce of the United States, (Waterborne Statistics Center:

New Orleans, LA, 1993). 

[29] Energy Information Administration, op. cit., Note 15. 

[30] Bureau of Transportation Statistics, Office of Airline Information, Air Carrier Summary Data (Form 41,

Schedules T-1 and T-2), (2006). http://www.transtats.bts.gov/DataIndex.asp; link: Air Carrier Summary Data 

(Form 41 and 298C Summary Data). 

[31] Bureau of Transportation Statistics, op. cit., Note 30. 

[32] U.S. Department of Transportation, Federal Aviation Administration, Airport Capacity Benchmark

Report, 2004 (2004). 

[33] Jet Information Services Inc., World Jet Inventory: Year-End 2006, (December 2006). 

[34] Bureau of Transportation Statistics, op. cit., Note 30.

[35] Energy Information Administration, op. cit. Note 14 

[36] Energy and Environmental Analysis, Inc., “Documentation of Technologies Included in the NEMS Fuel

Economy Model for Passenger Cars and Light Trucks,” Prepared for the Energy Information Administration,

(Arlington, VA, September 30, 2002). 

[37] Vyas, A., C. Saricks, and F. Stodolsky, “Projected Effect of Future Efficiency and Emissions 

Improving Technologies on Fuel Consumption of Heavy Trucks,” Argonne National Laboratory, (Argonne,

IL, 2001).

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 75

Notes and Sources

Electricity Market Module

The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of

electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load 

and demand electricity, and electricity finance and pricing. It includes nonutility capacity and generation, and 

electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication,

Electricity Market Module of the National Energy Modeling System 2008, DOE/EIA-M068(2008).

Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM

determines the most economical way to supply electricity, within environmental and operational constraints.

There are assumptions about the operations of the electricity sector and the costs of various options in each

of the EMM submodules. This section describes the model parameters and assumptions used in EMM. It

includes a discussion of legislation and regulations that are incorporated in EMM as well as information

about the climate change action plan. The various electricity and technology cases are also described.

EMM Regions

The supply regions used in EMM are based on the North American Electric Reliability Council regions and

subregions shown in Figure 6 (region definitions as of 2004).

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 77

11

13

12

5

2

10

8

9

4

1

3

6

7

Figure 6. Electricity Market Model Supply Regions

 1 East Central Area Reliability Coordination Agreement (ECAR) 8 Florida Reliability Coordinating Council (FL)

 2 Electric Reliability Council of Texas (ERCOT) 9 Southeastern Electric Reliability Council (SERC)

 3 Mid-Atlantic Area Council (MAAC) 10 Southwest Power Pool (SPP)

 4 Mid-America Interconnected Network (MAIN) 11 Northwest Power Pool (NWP)

 5 Mid-Continent Area Power Pool (MAPP) 12. Rocky Mountain Power Area, Arizona, New Mexico, and

 6. New York (NY) Southern Nevada (RA)

 7. New England (NE) 13 California (CA)

Report #:DOE/EIA-0554(2008)

Release date: June 2008

Next release date: March 2009
Model Parameters and Assumptions

Generating Capacity Types

The capacity types represented in the EMM are shown in Table 37.

New Generating Plant Characteristics

The cost and performance characteristics of new generating technologies are inputs to the electricity

capacity planning submodule (Table 38). These characteristics are used in combination with fuel prices from 

the NEMS fuel supply modules and foresight on fuel prices, to compare options when new capacity is

needed. Heat rates for fossil-fueled technologies are assumed to decline linearly through 2025.

The overnight costs shown in Table 38 are the cost estimates to build a plant in a typical region of the

country. Differences in plant costs due to regional distinctions are calculated by applying regional multipliers 

that represent variations in the cost of labor. The base overnight cost is multiplied by a project contingency

factor and a technological optimism factor (described later in this chapter), resulting in the total construction

cost for the first-of-a-kind unit used for the capacity choice decision.

78 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 

Capacity Type

Existing coal steam plants1

High Sulfur Pulverized Coal with Wet Flue Gas Desulfurization

Advanced Coal - Integrated Coal Gasification Combined Cycle

Advanced Coal with carbon sequestration

Oil/Gas Steam - Oil/Gas Steam Turbine

Combined Cycle - Conventional Gas/Oil Combined Cycle Combustion Turbine

Advanced Combined Cycle - Advanced Gas/Oil Combined Cycle Combustion Turbine

Advanced Combined Cycle with carbon sequestration

Combustion Turbine - Conventional Combustion Turbine

Advanced Combustion Turbine - Steam Injected Gas Turbine

Molten Carbonate Fuel Cell

 Conventional Nuclear

Advanced Nuclear - Advanced Light Water Reactor

Generic Distributed Generation - Baseload

Generic Distributed Generation - Peak

Conventional Hydropower - Hydraulic Turbine

Pumped Storage - Hydraulic Turbine Reversible

Geothermal

Municipal Solid Waste

Biomass - Integrated Gasification Combined-Cycle

Solar Thermal - Central Receiver

Solar Photovoltaic - Single Axis Flat Plate 

Wind

Wind Offshore

Table 37. Generating Capacity Types Represented in the Electricity Market Module

1

The EMM represents 32 different types of existing coal steam plants, based on the different possible configuration of Nox,

particulate and SO2 emission control devices, as well as future options for controlling mercury.

Source: Energy Information Administration, Office of Integrated Analysis and Forecasting.
Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 79

Technology

Online 

Year1

Size 

(mW)

Leadtime

(Years)

Base

Overnight

 Cost

in 2007

($2006/kW)

Contingency Factors

 

 Project Technological

 Contingency Optimism

 Factor2 Factor3

Total

Overnight

 Cost

 in 20074

(2006 $/kW)

Variable

O&M5

 ($2006

 mills/kWh)

Fixed 

O&M5

($2006/kW)

Heatrate6

in

 2007

(Btu/kWhr)

Heatrate

 nth-of-

 a-kind

(Btu/kWr)

Scrubbed Coal New7

2011 600 4 1,434 1.07 1.00 1,534 4.46 26.79 9,200 8,740

Integrated Coal-Gasification

 Combined Cycle (IGCC)7

2011 550 4 1,657 1.07 1.00 1,773 2.84 37.62 8,765 7,450

IGCC with Carbon

 Sequestration 2011 380 4 2,302 1.07 1.03 2,537 4.32 44.27 10,781 8,307

Conv Gas/Oil Comb Cycle 2010 250 3 683 1.05 1.00 717 2.01 12.14 7,196 6,800

Adv Gas/Oil Comb Cycle (CC) 2010 400 3 654 1.08 1.00 706 1.95 11.38 6,752 6,333

ADV CC with Carbon

 Sequestration 2010 400 3

 

 1,254 1.08 1.04 1,409 2.86 19.36 8,613 7,493

Conv Combustion Turbine8

2009 160 2 476 1.05 1.00 500 3.47 11.78 10,833 10,450

Adv Combustion Turbine 2009 230 2 450 1.05 1.00 473 3.08 10.24 9,289 8,550

Fuel Cells 2010 10 3 4,653 1.05 1.10 5,374 46.62 5.50 7,930 6,960

Advanced Nuclear 2016 1350 6 2,143 1.10 1.05 2,475 0.48 66.05 10,400 10,400

Distributed Generation -Base 2009 5 2 972 1.05 1.00 1,021 6.93 15.59 9,200 8,900

Distributed Generation -Peak 2010 2 3 1,168 1.05 1.00 1,227 6.93 15.59 10,257 9,880

Biomass 2011 80 4 2,490 1.07 1.05 2,809 6.53 62.70 8,911 8,911

MSW - Landfill Gas 2010 30 3 1,773 1.07 1.00 1,897 0.01 111.15 13,648 13,648

Geothermal 7,9 2011 50 4 1,057 1.05 1.00 1,110 0.00 160.18 35,376 33,729

Conventional Hydropower9

2011 500 4 1,410 1.10 1.00 1,551 3.41 13.59 10,022 10,022

Wind 2010 50 3 1,340 1.07 1.00 1,434 0.00 29.48 10,022 10,022

Wind Offshore 2011 100 4 2,547 1.10 1.03 2,872 0.00 87.05 10,022 10,022

Solar Thermal7

2010 100 3 3,499 1.07 1.00 3,744 0.00 55.24 10,022 10,022

Photovoltaic7

2009 5 2 5,380 1.05 1.00 5,649 0.00 11.37 10,022 10,022

Table 38. Cost and Performance Characteristics of New Central Station Electricity Generating Technologies

1Online year represents the first year that a new unit could be completed, given an order date of 2007.

2A contingency allowance is defined by the American Association of Cost Engineers as the "specific provision for unforeseeable

elements if costs within a defined project scope; particularly important where previous experience has shown that unforeseeable

events which will increase costs are likely to occur."

3

The technological optimism factor is applied to the first four units of a new, unproven design. It reflects the demonstrated tendency

to underestimate actual costs for a first-of-a-kind unit.

4Overnight capital cost including contingency factors, excluding regional multipliers and learning effects. Interest charges are also

excluded. These represent costs of new projects initiated in 2007.

5O&M = Operations and maintenance.

6

For hydro, wind, and solar technologies, the heatrate shown represents the average heatrate for conventional thermal generation

as of 2006. This is used for purposes of calculating primary energy consumption displaced for these resources, and does not imply

an estimate of their actual energy conversion efficiency.

7Capital costs are shown before investment tax credits are applied.

8Combustion turbine units can be built by the model prior to 2009 if necessary to meet a given region's reserve margin.

9Because geothermal and hydro cost and performance characteristics are specific for each site, the table entries represent the cost

of the least expensive plant that could be built in the Northwest Power Pool region, where most of the proposed sites are located.

Sources: The values shown in this table are developed by the Energy Information Administration, Office of Integrated Analysis and

Forecasting, from analysis of reports and discussions with various sources from industry, government, and the Department of

Energy Fuel Offices and National Laboratories. They are not based on any specific technology model, but rather, are meant to

represent the cost and performance of typical plants under normal operating conditions for each plant type. Key sources reviewed

are listed in the ‘Notes and Sources’ section at the end of the chapter. 
Technological Optimism and Learning 

Overnight costs for each technology are calculated as a function of regional construction parameters, project 

contingency, and technological optimism and learning factors. 

The technological optimism factor represents the demonstrated tendency to underestimate actual costs for a 

first-of-a-kind, unproven technology. As experience is gained (after building 4 units) the technological

optimism factor is gradually reduced to 1.0.

The learning function in NEMS is determined at a component level. Each new technology is broken into its

major components, and each component is identified as revolutionary, evolutionary or mature. Different

learning rates are assumed for each component, based on the level of experience with the design

component (Table 39). Where technologies use similar components, these components learn at the same

rate as these units are built. For example, it is assumed that the underlying turbine generator for a

combustion turbine, combined cycle and integrated coal-gasification combined cycle unit is basically the

same. Therefore construction of any of these technologies would contribute to learning reductions for the

turbine component. 

The learning function has the nonlinear form:

OC(C) = a*C-b,

where C is the cumulative capacity for the technology component.

80 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 

Period 1 Period 2 Period 3 Period 1 Period 2 Minimum Total

Technology Component Learning 

Rate

Learning

 Rate

Learning

 Rate

Doublings Doublings Learning by 2025

Pulverized Coal - - 1% - - 5%

Combustion Turbine - conventional - - 1% - - 5%

Combustion Turbine - advanced - 10% 1% - 5 10%

HRSG1- - 1% - - 5%

Gasifier - 10% 1% - 5 10%

Carbon Capture/Sequestration 20% 10% 1% 3 5 20%

Balance of Plant - IGCC - - 1% - - 5%

Balance of Plant - Turbine - - 1% - - 5%

Balance of Plant - Combined Cycle - - 1% - - 5%

Fuel Cell 10% 5% 1% 3 5 10%

Advanced Nuclear 5% 3% 1% 3 5 10%

Fuel prep - Biomass IGCC 20% 10% 1% 3 5 20%

Distributed Generation - Base - 5% 1% - 5 10%

Distributed Generation - Peak - 5% 1% - 5 10%

Geothermal - 8% 1% - 5 10%

Municipal Solid Waste - - 1% - - 5%

Hydropower - - 1% - - 5%

Wind - - 1% - - 1%

Wind Offshore 20% 10% 1% 3 5 20%

Solar Thermal 20% 10% 1% 3 5 20%

Solar PV 15% 8% 1% 3 5 20%

Table 39. Learning Parameters for New Generating Technology Components

1HRSG = Heat Recovery Steam Generator

Note: Please see the text for a description of the methodology for learning in the Electricity Market Module.

Source: Energy Information Administration, Office of Integrated Analysis and Forecasting.
The progress ratio (pr) is defined by speed of learning (e.g., how much costs decline for every doubling of

capacity). The reduction in capital cost for every doubling of cumulative capacity (f) is an exogenous

parameter input for each component (Table 39). Consequently, the progress ratio and f are related by:

pr = 2-b = (1 - f)

The parameter “b” is calculated by (b =-(ln(1-f)/ln(2)). The parameter “a” can be found from initial conditions. 

That is,

a =OC(C0)/C0-b

where C0 is the cumulative initial capacity. Thus, once the rates of learning (f) and the cumulative capacity

(C0) are known for each interval, the corresponding parameters (a and b) of the nonlinear function are

known. Three learning steps were developed, to reflect different stages of learning as a new design is

introduced to the market. New designs with a significant amount of untested technology will see high rates of 

learning initially, while more conventional designs will not have as much learning potential. All design

components receive a minimal amount of learning, even if new capacity additions are not projected. This 

represents cost reductions due to future international development or increased research and development.

Once the learning rate by component is calculated, a weighted average learning factor is calculated for each

technology. The weights are based on the share of the initial cost estimate that is attributable to each

component (Table 40). For technologies that do not share components, this weighted average learning rate

is calculated exogenously, and input as a single component. These technologies may still have a mix of

revolutionary components and more mature components, but it is not necessary to include this detail in the

model unless capacity from multiple technologies would contribute to the component learning. 

Table 41 shows the capacity credit toward component learning for the various technologies. It was assumed

that for all combined-cycle technologies, the turbine unit contributed two-thirds of the capacity, and the

steam unit one-third. Therefore, building one gigawatt of gas combined cycle would contribute 0.67

gigawatts toward turbine learning, and 0.33 gigawatts toward steam learning. All non-capacity components,

such as the balance of plant category, contribute 100 percent toward the component learning.

International Learning. In AEO2008, capital costs for all new electricity generating technologies (fossil,

nuclear, and renewable) decrease in response to foreign and domestic experience. Foreign units of new

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 81

Technology

Combustion

 Turbine-

 conventional

Combustion

 Turbine-

 advanced HRSG Gasifier

Carbon

 Capture/

Sequestration

Balance

 of Plant-

 IGCC

Balance of 

PlantTurbine

Balance of

 Plant-

 Combined

 Cycle

Fuelprep 

Biomass 

IGCC

Integrated

 Coal_Gasification Comb

 Cycle (IGCC)

0% 15% 20% 41% 0% 24% 0% 0% 0%

IGCC with carbon 

 sequestration

0% 10% 15% 30% 30% 15% 0% 0% 0%

Conv Gas/Oil Comb Cycle 30% 0% 40% 0% 0% 0% 0% 30% 0%

Adv Gas/Oil Comb Cycle

 (CC)

0% 30% 40% 0% 0% 0% 0% 30% 0%

Adv CC with carbon

 sequestration

0% 20% 25% 0% 40% 0% 0% 15% 0%

Conv Comb Turbine 50% 0% 0% 0% 0% 0% 50% 0% 0%

Adv Comb Turbine 0% 50% 0% 0% 0% 0% 50% 0% 0%

Biomass 0% 12% 16% 33% 0% 20% 0% 0% 19%

Table 40. Component Cost Weights for New Technologies

Note: All unlisted technologies have a 100% weight with the corresponding component. Components are not broken out for all

technologies unless there is overlap with other technologies.

HRSG = Heat Recovery Steam Generator.

Source: Market Based Advanced Coal Power Systems, May 1999, DOE/FE-0400
technologies are assumed to contribute to reductions in capital costs for units that are installed in the United

States to the extent that (1) the technology characteristics are similar to those used in U.S. markets, (2) the

design and construction firms and key personnel compete in the U.S. market, (3) the owning and operating

firm competes actively in the U.S. market, and (4) there exists relatively complete information about the

status of the associated facility. If the new foreign units do not satisfy one or more of these requirements,

they are given a reduced weight or not included in the domestic learning effects calculation. 

AEO2008 includes 5,000 megawatts of advanced coal gasification combined-cycle capacity, 5,244

megawatts of advanced combined-cycle natural gas capacity, 11 megawatts of biomass capacity and 47

megawatts each of traditional wind and offshore wind capacity to be built outside the United States from

2000 through 2003. The learning function also includes 7,200 megawatts of advanced nuclear capacity,

representing two completed units and four additional units under construction in Asia.

Distributed Generation

Distributed generation is modeled in the end-use sectors as well as in the EMM, which is described in the

appropriate chapters. This section describes the representation of distributed generation in the EMM only.

Two generic distributed technologies are modeled. The first technology represents peaking capacity

(capacity that has relatively high operating costs and is operated when demand levels are at their highest). 

The second generic technology for distributed generation represents base load capacity (capacity that is

operated on a continuous basis under a variety of demand levels). See Table 38 for costs and performance

assumptions. It is assumed that these plants reduce the costs of transmission upgrades that would

otherwise be needed.

Representation of Electricity Demand

The annual electricity demand projections from the NEMS demand modules are converted into load duration 

curves for each of the EMM regions (based on North American Electric Reliability Council regions and

subregions) using historical hourly load data. The load duration curve in the EMM is made up of 9 time

slices. First, the load data is split into three seasons, (winter - December through March, summer - June

through September, and fall/spring). Within each season the load data is sorted from high to low, and three

load segments are created - a peak segment representing the top 1 percent of the load, and then two

off-peak segments representing the next 33 percent and 66 percent, respectively. The seasons were

defined to account for seasonal variation in supply availability. 

82 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 

Technology

Combustion

 Turbine-

 conventional

Combustion

 Turbine-

 advanced HRSG Gasifier

Carbon

 Capture/

Sequestration

Balance

 of Plant-

 IGCC

Balance of 

PlantTurbine

Balance of

 Plant-

 Combined

 Cycle

Fuelprep 

Biomass 

IGCC

Integrated

 Coal_Gasification Comb

 Cycle (IGCC)

0% 67% 33% 100% 0% 100% 0% 0% 0%

IGCC with carbon 

 sequestration

0% 67% 33% 100% 100% 100% 0% 0% 0%

Conv Gas/Oil Comb Cycle 67% 0% 33% 0% 0% 0% 0% 100% 0%

Adv Gas/Oil Comb Cycle

 (CC)

0% 67% 33% 0% 0% 0% 0% 100% 0%

Adv CC with carbon

 sequestration

0% 67% 33% 0% 100% 0% 0% 100% 0%

Conv Comb Turbine 100% 0% 0% 0% 0% 0% 100% 0% 0%

Adv Comb Turbine 0% 100% 0% 0% 0% 0% 100% 0% 0%

Biomass 0% 67% 33% 100% 0% 100% 0% 0% 100%

Table 41. Component Capacity Weights for New Technologies

HRSG = Heat Recovery Steam Generator.

Source: Energy Information Administration, Office of Integrated Analysis and Forecasting.
Reserve margins—the percentage of capacity required in excess of peak demand needed for unforeseeable 

outages—are determined within the model through an interative approach comparing the marginal cost of

capacity and the cost of unserved energy. The target reserve margin is adjusted each model cycle until the

two costs converge. The resulting reserve margins from the AEO2008 reference case range from 10 to 14

percent.

Fossil Fuel-Fired and Nuclear Steam Plant Retirement

Fossil-fired steam plant retirements and nuclear retirements are calculated endogenously within the model.

Plants are assumed to retire when it is no longer economical to continue running them. Each year, the model 

determines whether the market price of electricity is sufficient to support the continued operation of existing

plants. If the expected revenues from these plants are not sufficient to cover the annual going forward costs,

the plant is assumed to retire if the overall cost of producing electricity can be lowered by building new

replacement capacity. The going-forward costs include fuel, operations and maintenance costs and annual

capital additions, which are plant specific based on historical data. The average capital additions for existing

plants are $8 per kilowatt (kW) for oil and gas steam plants, $16 per kW for coal plants and $20 per kW for

nuclear plants (in 2006 dollars). These costs are added to existing plants regardless of their age. Beyond 30

years of age an additional $6 per kW capital charge for fossil plants, and $30 per kW charge for nuclear

plants is included in the retirement decision to reflect further investment to address impacts of aging. Age

related cost increases are due to capital expenditures for major repairs or retrofits, decreases in plant

performance, and/or increased maintenance costs to mitigate the effects of aging.

Biomass Co-firing

Coal-fired power plants are allowed to co-fire with biomass fuel if it is economical. Co-firing requires a capital 

investment for boiler modifications and fuel handling. This expenditure ranges from about $115 to $265 per

kilowatt of biomass capacity, depending on the type and size of the boiler. A coal-fired unit modified to allow

co-firing can generate up to 15 percent of the total output using biomass fuel, assuming sufficient residue

supplies are available. Larger units are required to pay additional transportation costs as the level of co-firing 

increases, due to the concentrated use of the regional supply.

New Nuclear Plant Orders

A new nuclear technology competes with other fossil-fired and renewable technologies as new generating

capacity is needed to meet increasing demand, or replace retiring capacity, throughout the projection period. 

The cost assumptions for new nuclear units are based on an analysis of recent cost estimates for nuclear

designs available in the United States and worldwide. The capital cost assumptions in the reference case

represent the expense of building a new single unit nuclear plant of approximately 1,000 megawatts at a new 

“Greenfield” site. Since no new nuclear plants have been built in the US in many years, there is a great deal

of uncertainty about the true costs of a new unit. The estimate used for AEO2008 is an average of the

construction costs incurred in completed advanced reactor builds in Asia, adjusting for expected learning

from other units still under construction. 

Nuclear Uprates 

The AEO2008 nuclear power projection also assumes capacity increases at existing units. Nuclear plant

operators can increase the rated capacity at plants through power uprates, which are license amendments

that must be approved by the U.S. Nuclear Regulatory Commission (NRC). Uprates can vary from small

(less than 2 percent) increases in capacity, which require very little capital investment or plant modifications,

to extended uprates of 15-20 percent, requiring significant modifications. Historically, most uprates were

small, and the AEO projections accounted for them only after they were implemented and reported, but

recent surveys by the NRC and EIA have indicated that more extended power uprates are expected in the

near future. AEO2008 assumes that all of those uprates approved, pending or expected by the NRC will be

implemented, for a capacity increase of 2.7 gigawatts between 2007 and 2030. Table 42 provides a

summary of projected uprate capacity additions by region. In cases where the NRC did not specifically

identify the unit expected to uprate, EIA assumed the units with the lowest operating costs would be the next

likely candidates for power increases.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 83
Interregional Electricity Trade

Both firm and economy electricity transactions among utilities in different regions are represented within the

EMM. In general, firm power transactions involve the trading of capacity and energy to help another region

satisfy its reserve margin requirement, while economy transactions involve energy transactions motivated

by the marginal generation costs of different regions. The flow of power from region to region is constrained

by the existing and planned capacity limits as reported in the National Electric Reliability Council and

Western Electric Coordinating Council Summer and Winter Assessment of Reliability of Bulk Electricity

Supply in North America. Known firm power contracts are obtained from NERC’s Electricity Supply and

Demand Database 2004. They are locked in for the term of the contract. Contracts that are scheduled to

expire by 2013 are assumed not to be renewed. Because there is no information available about expiration

dates for contracts that go beyond 2013, they are assumed to be phased out by 2022. In addition, in certain

regions where data show an established commitment to build plants to serve another region, new plants are

permitted to be built to serve the other region’s needs. This option is available to compete with other

resource options.

Economy transactions are determined in the dispatching submodule by comparing the marginal generating

costs of adjacent regions in each time slice. If one region has less expensive generating resources available 

in a given time period (adjusting for transmission losses and transmission capacity limits) than another

region, the regions are allowed to exchange power. 

84 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 

Region

East Central Area Reliability Coordination Agreement 0.1

Electric Reliability Council of Texas 0.4

Mid-Atlantic Area Council 0.1

Mid-America Interconnected Network 0.1

Mid-Continent Area Power Pool 0.0

New York 0.1

New England 0.0

Florida Reliability Coordinating Council 0.0

Southeastern Electric Reliability Council 1.8

Southwest Power Pool 0.0

Northwest Power Pool 0.0

Rocky Mountain Power Area, Arizona, New Mexico, and Southern Nevada 0.1

California 0.1

Total 2.7

Table 42. Nuclear Upratres by EMM Region

(gigawatts)

Source: Energy Information Administration, Office of Integrated Analysis and Forecasting, based on 

Nuclear Regulatory Commission survey, http://www.nrc.gov/reactors/operating/licensing/

power-uprates.html
International Electricity Trade

Two components of international firm power trade are represented in the EMM—existing and planned

transactions, and unplanned transactions. Existing and planned transactions are obtained from the North

American Electric Reliability Council’s Electricity Supply and Demand Database 2004. Unplanned firm

power trade is represented by competing Canadian supply with U.S. domestic supply options. Canadian

supply is represented via supply curves using cost data from the Department of Energy report Northern

Lights: The Economic and Practical Potential of Imported Power from Canada, (DOE/PE-0079).

International economy trade is determined endogenously based on surplus energy expected to be available

from Canada by region in each time slice. Canadian surplus energy is determined using Canadian electricity 

supply and demand projections from the MAPLE-C model developed for Natural Resources Canada.

Electricity Pricing

The reference case assumes a transition to full competitive pricing in New York, Mid-Atlantic Area Council,

and Texas, and a 95 percent transition to competitive pricing in New England (Vermont being the only

fully-regulated State in that region). California returned to almost fully regulated pricing in 2002, after

beginning a transition to competition in 1998. In addition electricity prices in the East Central Area Reliability

Council, the Mid-American Interconnected Network, the Southeastern Electric Reliability Council, the

Southwest Power Pool, the Northwest Power Pool, and the Rocky Mountain Power Area/Arizona are a mix

of both competitive and regulated prices. Since some States in each of these regions have not taken action

to deregulate their pricing of electricity, prices in those States are assumed to continue to be based on

traditional cost-of-service pricing. The price for mixed regions is a load-weighted average of the competitive

price and the regulated price, with the weight based on the percent of electricity load in the region that has

taken action to deregulate. The reference case assumes that State-mandated price freezes or reductions

during a specified transition period will occur based on the terms of the legislation. In general, the transition

period is assumed to occur over a ten-year period from the effective date of restructuring, with a gradual shift

to marginal cost pricing. In regions where none of the states in the region have introduced

competition—Florida Reliability Coordinating Council and Mid-Continent Area Power Pool—electricity

prices are assumed to remain regulated and the cost-of-service calculation is used to determine electricity

prices.

The price of electricity to the consumer is comprised of the price of generation, transmission, and distribution

including applicable taxes. Transmission and distribution are considered to remain regulated in the AEO;

that is, the price of transmission and distribution is based on the average cost. In competitive regions, an

algorithm in place allows customers to compete for better rates among rate classes as long as the overall

average cost is met. The price of electricity in the regulated regions consists of the average cost of

generation, transmission, and distribution for each customer class. In the competitive regions, the

generation component of price is based on marginal cost, which is defined as the cost of the last (or most

expensive) unit dispatched. The marginal cost includes fuel, operation and maintenance, taxes, and a

reliability price adjustment, which represents the value of capacity in periods of high demand. The price of

electricity in the regions with a competitive generation market consists of the marginal cost of generation

summed with the average costs of transmission and distribution. 

In recent years, the move towards competition in the electricity business has led utilities to make efforts to

reduce costs to improve their market position. These cost reduction efforts are reflected in utility operating

data reported to the Federal Energy Regulatory Commission (FERC) and these trends have been

incorporated in the AEO2008. Both General and Administrative (G&A) expenses and Operations and

Maintenance (O&M) expenses have shown declines in recent years. The O&M declines show variation

based on the plant type. A regression analysis of recent data was done to determine the trend, and the

resulting function was used to project declines throughout the projection. The analysis of G&A costs used

data from 1992 through 2001, which had a 15 percent overall decline in G&A costs, and a 1.8 percent

average annual decline rate. The AEO2008 projection assumes a further decline of 18 percent by 2025

based on the results of the regression analysis. The O&M cost data was available from 1990 through 2001,

and showed average annual declines of 2.1 percent for all steam units, 1.8 percent for combined cycle and

1.5 percent for nuclear. The AEO2008 assumes further declines in O&M expenses for these plant types, for

a total decline through 2025 of 17 percent for combined cycle, 15 percent for steam and 8 percent for

nuclear.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 85
There have been ongoing changes to pricing structures for ratepayers in competitive States since the

inception of retail competition. The AEO has incorporated these changes as they have been incorporated

into utility tariffs. These have included transition period rate reductions and freezes instituted by various

States, and surcharges in California relating to the 2000-2001 energy crisis there. Since price freezes for

most customers have ended or will end in the next year or two, a large survey of utility tariffs found that many

costs related to the transition to competition were now explicitly added to the distribution portion, and

sometimes the transmission portion of the customer bill regardless of whether or not the customer bought

generation service from a competitive or regulated supplier. There are some unexpected costs relating to

unforeseen events. For instance, as a result of volatile fuel markets, State regulators have had a hard time

enticing retail suppliers to offer competitive supply to residential and smaller commercial and industrial

customers. They have often resorted to procuring the energy themselves through auction or competitive

bids or have allowed distribution utilities to procure the energy on the open market for their customers for a

fee. For AEO2008, typical charges that all customers must pay on the distribution portion of their bill

(depending on where they reside) include: transition charges (including persistent stranded costs), public

benefits charges (usually for efficiency and renewable energy programs), administrative costs of energy

procurement, and nuclear decommissioning costs. Costs added to the transmission portion of the bill

include the Federally Mandated Congestion Charges (FMCC), a bill pass-through associated with the

Federal Energy Regulatory Commission passage of Standard Market Design (SMD) to enhance reliability of

the transmission grid and control congestion. 

Transmission costs for the AEO are traditionally projected based on regressions of historical spending per

non-coincident peak time electricity use to ensure that the model builds enough transmission infrastructure

to accommodate growth in peak electricity demand. However, since spending decreased throughout the

1990s we have had to add in extra spending on transmission. Our additions were based on several large

studies, such as the Department of Energy’s National Transmission Grid Study, which set out to document

how much spending would be needed to keep the national grid operating efficiently. Transmission spending

has in fact been increasing very recently. We will be monitoring transmission spending closely over the next

several years and updates will be made as new information becomes available.

Fuel Price Expectations

Capacity planning decisions in the EMM are based on a life cycle cost analysis over a 20-year period. This

requires foresight assumptions for fuel prices. Expected prices for coal, natural gas and oil are derived using 

rational expectations, or ‘perfect foresight’. In this approach, expectations for future years are defined by the

realized solution values for these years in a prior run. The expectations for the world oil price and natural gas

wellhead price are set using the resulting prices from a prior run. The markups to the delivered fuel prices are 

calculated based on the markups from the previous year within a NEMS run. Coal prices are determined

using the same coal supply curves developed in the Coal Market Module. The supply curves produce prices

at different levels of coal production, as a function of labor productivity, and costs and utilization of mines.

Expectations for each supply curve are developed in the EMM based on the actual demand changes from

the prior run throughout the projection horizon, resulting in updated mining utilization and different supply

curves.

The perfect foresight approach generates an internally consistent scenario for which the formation of

expectations is consistent with the projections realized in the model. The NEMS model involves iterative

cycling of runs until the expected values and realized values for variables converge between cycles.

Legislation and Regulations

Clean Air Act Amendments of 1990 (CAAA90) and Clean Air Interstate Rule (CAIR)

It is assumed that electricity producers comply with the CAIR, which mandates limits on sulfur dioxide (SO2)

and /or nitrogen oxide (NOx) in 28 eastern states and the District of Columbia. The annual limits for SO2

emissions are 3.6 million tons beginning in 2010 and 2.5 million tons starting in 2015. The corresponding

limits of NOx emissions are 1.5 million tons in 2009 and 1.3 million tons in 2015.

Prior to the implementation of these targets, generators are still required to comply with the SO2 and NOx

limits specified by the CAAA90. The western states not covered by the CAIR are assumed to comply with

the CAAA90 throughout the projection period. By 2010, the CAAA90 assigns an annual limit of 1.7 million

86 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 
tons for SO2 in these areas. Utilities are assumed to satisfy the limits on sulfur emissions by retrofitting units

with flue gas desulfurization (FGD) equipment, transferring or purchasing sulfur emission allowances,

operating high-sulfur coal units at a lower capacity utilization rate, or switching to low-sulfur fuels. It is

assumed that the market for trading emission allowances is allowed to operate without regulation and that

the States do not further regulate the selection of coal too be used.

As specified in the CAAA90, EPA has developed a two-phase nitrogen oxide (NOx) program, with the first set 

of standards for existing coal plants applied in 1996 while the second set was implemented in 2000. Dry

bottom wall-fired, and tangential fired boilers, the most common boiler types, referred to as Group 1 Boilers,

were required to make significant reductions beginning in 1996 and further reductions in 2000. Relative to

their uncontrolled emission rates, which range roughly between 0.6 and 1.0 pounds per million Btu, they are

required to make reductions between 25 and 50 percent to meet the Phase I limits and further reductions to

meet their Phase II limits. The EPA did not impose limits on existing oil and gas plants, but some states have 

additional NOx regulations. All new fossil units are required to meet standards. In pounds per million Btu,

these limits are 0.11 for conventional coal, 0.02 for advanced coal, 0.02 for combined cycle, and 0.08 for

combustion turbines. These NOx limits are incorporated in EMM.

In addition, the EPA has issued rules to limit the emissions of NOx, specifically calling for capping emissions

during the summer season in 22 Eastern and Midwestern states. After an initial challenge, these rules have

been upheld, and emissions limits have been finalized for 19 states and the District of Columbia (Table 43).

Within EMM, electric generators in these 19 states must comply with the limit either by reducing their own

emissions or purchasing allowances from others who have more than they need.

The costs of adding flue gas desulfurization equipment (FGD) to remove sulfur dioxide (SO2) and selective

catalytic reduction (SCR) equipment to remove nitrogen oxides (NOx) are given below for 300, 500, and

700-megawatt coal plants. FGD units are assumed to remove 95 percent of the SO2, while SCR units are

assumed to remove 90 percent of the NOx. The costs per megawatt of capacity decline with plant size and

are shown in Table 44.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 87

State Emissions Cap

Alabama 29.02

Connecticut 2.65

Delaware 5.25

District of Columbia 0.21

Illinois 32.37

Indiana 47.73

Kentucky 36.50

Maryland 14.66

Massachusetts 15.15

Michigan 32.23

New Jersey 10.25

New York 31.04

North Carolina 31.82

Ohio 48.99

Pennsylvania 47.47

Rhode Island 1.00

South Carolina 16.77

Tennessee 25.81

Virginia 17.19

West Virginia 26.86

Table 43. Summer Season NOx Emissions Budgets for 2004 and Beyond

(Thousand tons per season)

Source: U.S. Environmental Protection Agency, Federal Register, Vol. 65, number 42 (March 2, 2002) pages 11222-11231.
Clean Air Mercury Rule (CAMR)1

The CAMR establishes a cap-and-trade program with a two-phase implementation. The regulation specifies 

a limit of 38 tons beginning in 2010 and 15 tons starting in 2018. To reduce mercury, power companies can

change their fuels, redispatch their units, change the configuration of their units or add mercury specific

controls. To represent this, the EMM allows plants to alter their configuration by adding equipment, such as

an SCR to remove NOx or an SO2 scrubber. They can also add activated carbon injection systems

specifically designed to remove mercury. Activated carbon can be injected in front of existing particulate

control devices or a supplemental fabric filter can be added with activated carbon injection capability.

The equipment to inject activated carbon in front of an existing particulate control device is assumed to cost

approximately $5 (2006 dollars) per kilowatt of capacity, while the cost of a supplemental fabric filter with

activated carbon injection (often referred as a COPAC unit) is approximately $64 per kilowatt of capacity.2

The amount of activated carbon required to meet a given percentage removal target is given by the following

equations.3

For a unit with a CSE, using subbituminous coal, and simple activated carbon injection:

• Hg Removal (%) = 65 – (65.286 / (ACI + 1.026))

For a unit with a CSE, using bituminous coal, and simple activated carbon injection:

• Hg Removal (%) = 100 – (469.379 / (ACI + 7.169))

For a unit with a CSE, and a supplemental fabric filter with activated carbon injection:

• Hg Removal (%) = 100 – (28.049 / (ACI + 0.428))

For a unit with a HSE/Other, and a supplemental fabric filter with activated carbon injection:

• Hg Removal (%) = 100 – (43.068 / (ACI + 0.421))

ACI = activated carbon injected in pounds per million actual cubic feet.

Power Plant Mercury Emissions Assumptions

The Electricity Market Module (EMM) of the National Energy Modeling System (NEMS) represents 35 coal

plant configurations and assigns a mercury emissions modification factor (EMF) to each configuration Each

configuration represents different combinations of boiler types, particulate control devices, sulfur dioxide

(SO2) control devices, nitrogen oxide (NOx) control devices, and mercury control devices. An EMF

represents the amount of mercury that was in the fuel that remains after passing through all the plant’s

systems. For example, an EMF of 0.60 means that 40 percent of the mercury that was in the fuel is removed

by various parts of the plant. Table 45 provides the assumed EMFs for existing coal plant configurations

without mercury specific controls.

88 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 

Coal Plant Size (MW) FGD Capital Costs ($/KW) SCR Capital Costs ($/KW)

300 301 124

500 230 108

700 190 98

Table 44. Coal Plant Retrofit Costs

(2006 Dollars)

Note: The model was run for each individual plant assuming a 1.3 retrofit factor for FGDs and 1.6 factor for SCRs.

Source: CUECOST3.xls model (as updated 2/9/2000) developed for the Environmental Protection Agency by Raytheon Engineers

and Constructors, Inc. EPA Contract number 68-D7-0001.
Planned SO2 Scrubber and NOx Control Equipment Additions

In recent years, in response to state emission reduction programs and compliance agreements with the

Environmental Protection Agency, some companies have announced plans to add scrubbers to their plants

to reduce sulfur dioxide and particulate emissions. Where firm commitments appear to have been made

these plans have been represented in NEMS. Based on EIA analysis of announced plans, 46.9 gigawatts of

capacity are assumed to add these controls (Table 46). The greatest number of retrofits is expected to occur 

in the Midwestern States, where there is a large base of coal capacity impacted by the SO2 limit in CAIR, as

well as in the Southeastern Electric Reliability Council because of the Clean Smokestacks bill passed by the

North Carolina General Assembly.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 89

Configuration EIA EMFs EPA EMFs

SO2

Control

Particulate

 Control

NOx

Control

Bit

Coal

Sub

 Coal

Lignite

 Coal

Bit

 Coal

Sub

 Coal

Lignite

 Coal

None BH — 0.11 0.27 0.27 0.11 0.26 1.00

Wet BH None 0.05 0.27 0.27 0.03 0.27 1.00

Wet BH SCR 0.10 0.27 0.27 0.10 0.15 0.56

Dry BH —- 0.05 0.75 0.75 0.05 0.75 1.00

None CSE —- 0.64 0.97 0.97 0.64 0.97 1.00

Wet CSE None 0.34 0.73 0.73 0.34 0.84 0.56

Wet CSE SCR 0.10 0.73 0.73 0.10 0.34 0.56

Dry CSE —- 0.64 0.65 0.65 0.64 0.65 1.00

None HSE/Oth —- 0.90 0.94 0.94 0.90 0.94 1.00

Wet HSE/Oth None 0.58 0.80 0.80 0.58 0.80 1.00

Wet HSE/Oth SCR 0.42 0.76 0.76 0.10 0.75 1.00

Dry HSE/Oth —- 0.60 0.85 0.85 0.60 0.85 1.00

Table 45. Mercury Emission Modification Factors

Notes: SO2 Controls - Wet = Wet Scrubber and Dry = Dry Scrubber, Particulate Controls, BH - fabric filter/baghouse. CSE = cold

side electrostatic precipitator, HSE = hot side electrostatic precipitator, NOx Controls, SCR = selective catalytic reduction, — = not

applicable, Bit = bituminous coal, Sub = subbituminous coal. The NOx control system is not assumed to enhance mercury removal

unless a wet scrubber is present, so it is left blank in such configurations. 

Sources: EPA, EMFs. http://www.epa.gov/clearskies/technical.html EIA EMFs not from EPA: Lignite EMFs, Mercury Control

Technologies for Coal-Fired Power Plants, presented by the Office of Fossil Energy on July 8, 2003. Bituminous coal mercury

removal for a Wet/HSE/Oth/SCR configured plant, Table EMF1, Analysis of Mercury Control Cost and Performance, Office of

Fossil Energy & National Energy Technology Laboratory, U.S. Department of Energy, January 2003, Washington, DC.
Companies are also announcing plans to retrofit units with controls to reduce NOx emissions to comply with

emission limits in certain states. In the reference case planned post-combustion control equipment amounts

to 35.5 gigawatts of selective catalytic reduction (SCR) and another 1.6 gigawatts of selective non-catalytic

reduction (SNCR) equipment. 

Energy Policy Acts of 1992 (EPACT92) and 2005 (EPACT05)

The provisions of the EPACT92 include revised licensing procedures for nuclear plants and the creation of

exempt wholesale generators (EWGs). The EPACT05 provides a 20-percent investment tax credit for

Integrated Coal-Gasification Combined Cycle capacity and a 15-percent investment tax credit for other

advanced coal technologies. These credits are limited to 3 gigawatts in both cases. It also contains a

production tax credit (PTC) of 1.8 cents (nominal) per kilowatthour for new nuclear capacity beginning

operation by 2020. This PTC is specified for the first 8 years of operation, is limited to $125 million (per

gigawatt) annually, and is limited to 6 gigawatts of new capacity. However, this credit may be shared to

additional units if more than 6 gigawatts are under construction by January 1, 2014. In the AEO2008

Reference case it is projected that 8 gigawatts of new nuclear capacity will be built by 2020, each receiving a

credit worth 1.35 cents per kilowatthour. EPACT05 extended the PTC for qualifying renewable facilities by 2

years, or December 31, 2007. It also repealed the Public Utility Holding Company Act (PUHCA).

FERC Orders 888 and 889

FERC has issued two related rules (Orders 888 and 889) designed to bring low cost power to consumers

through competition, ensure continued reliability in the industry, and provide for open and equitable

transmission services by owners of these facilities. Specifically, Order 888 requires open access to the

transmission grid currently owned and operated by utilities. The transmission owners must file

nondiscriminatory tariffs that offer other suppliers the same services that the owners provide for themselves.

Order 888 also allows these utilities to recover stranded costs (investments in generating assets that are

unrecoverable due to consumers selecting another supplier). Order 889 requires utilities to implement

standards of conduct and an Open Access Same-Time Information System (OASIS) through which utilities

and non-utilities can receive information regarding the transmission system. Consequently, utilities are

expected to functionally or physically unbundle their marketing functions from their transmission functions.

These orders are represented in EMM by assuming that all generators in a given region are able to satisfy

load requirements anywhere within the region. Similarly, it is assumed that transactions between regions

will occur if the cost differentials between them make it economic to do so.

90 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 

Region Capacity (Gigawatts)

East Central Area Reliability Coordination Agreement 20.1

Electric Reliability Council of Texas 0.0

Mid-Atlantic Area Council 4.1

Mid-America Interconnected Network 1.7

Mid-Continent Area Power Pool 1.1

New York 0.0

New England 0.0

Florida Reliability Coordinating Council 0.0

Southeastern Electric Reliability Council 19.2

Southwest Power Pool 0.0

Northwest Power Pool 0.0

Rocky Mountain Power Area, Arizona, New Mexico, and Southern Nevada 0.7

California 0.0

Total 46.9

Table 46. Planned SO2 Scrubber Additions Represented by Region

Source: Energy Information Administration, Office of Integrated Analysis and Forecasting, based on public announcements

and reports to Form EIA-767, "Annual Steam-Electric Plant Operation and Design Data".
Electricity Alternative Cases

Low and High Cost Fossil Cases

The high cost fossil case assumes that the costs of advanced fossil generating technologies (integrated

coal- gasification combined-cycle, advanced natural gas combined-cycle and turbines) will remain at current 

costs during the projection period, that is, no learning reductions are applied to the cost. Operating

efficiencies for advanced technologies are assumed to be constant at 2008 levels. Capital costs of

conventional generating technologies are the same as those assumed in the reference case (Table 47). 

In the low cost fossil case, capital costs, heat rates and operating costs for the advanced coal and gas

technologies are assumed to be ten percent lower than Reference case levels in 2030. Since learning

occurs in the Reference case, costs and performance in the high case are reduced from initial levels by more 

than ten percent. Heat rates for advanced fossil technologies, in the high fossil case, fall to 16 to 31 percent

below initial levels, while capital costs are reduced by 19 percent to 25 percent between 2008 and 2030.

The low and high cost fossil cases are fully-integrated runs, allowing feedback from the end-use demand

and fuel supply modules. 

Nuclear Cost Cases

For nuclear power plants, two nuclear cost cases analyze the sensitivity of the projections to lower and

higher costs for new plants. The cost assumptions for the low nuclear cost case reflect a ten percent

reduction in the capital and operating cost for the advanced nuclear technology in 2030, relative to the

reference case. Since the reference case assumes some learning occurs regardless of new orders and

construction, the reference case already projects a 18 percent reduction in capital costs between 2008 and

2030. The low nuclear cost case therefore assumes a 26 percent reduction between 2008 and 2030. The

high nuclear cost case assumes that capital costs for the advanced nuclear technology do not decline from

2008 levels (Table 48). Cost and performance characteristics for all other technologies are as assumed in

the reference case.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 91
92 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 

Total Overnight Cost1

 

 Heat Rate

Total

 Overnight

 Cost

in 2007

Reference

(2006 $/kW) Reference

(2006 $/kW)

High Cost Fossil

(2006 $/kW)

Low Cost Fossil

(2006 $/kW)

Heatrate in

 2007

(Reference)

Btu/kWhr

Reference

BTU/kWhr

High Cost Fossil

Btu/kWhr

Low cost Fossil

Btu/kWhr

 Pulverized Coal 1534 9200

 2015 1504 1504 1504 9069 9069 9069

 2020 1477 1472 1483 8904 8904 8904

 2025 1453 1450 1462 8740 8740 8740

 2030 1432 1429 1440 8740 8740 8740

 Advanced Coal 1773 8765

 2015 1719 1774 1658 8389 8765 8176

 2020 1681 1774 1574 7920 8765 7441

 2025 1635 1774 1493 7450 8765 6705

 2030 1566 1774 1409 7450 8765 6705

 Advanced Coal

 with Sequestration 2537 10781

 2015 2423 2537 2343 10074 10781 9837

 2020 2342 2537 2205 9191 10781 8656

 2025 2254 2537 2067 8307 10781 7476

 2030 2142 2537 1927 8307 10781 7476

Conventional

 Combined Cycle 717 7196

 2015 703 703 703 7064 7064 7064

 2020 693 693 693 6932 6932 6932

 2025 683 683 683 6800 6800 6800

 2030 673 673 673 6800 6800 6800

Advanced Gas 706 6752

 2015 688 707 662 6612 6752 6401

 2020 675 707 633 6473 6752 6051

 2025 657 707 602 6333 6752 5700

 2030 634 707 571 6333 6752 5700

 Advanced Gas

 with Sequestration 1409 8613

 2015 1343 1271 1336 8240 8613 7990

 2020 1296 1271 1255 7866 8613 7367

 2025 1241 1271 1175 7493 8613 6744

 2030 1181 1450 1094 7493 8613 6744

Conventional

 CombustionTurbine 500 10833

 2015 490 490 490 10675 10675 10675

 2020 483 483 483 10563 10563 10563

 2025 476 476 476 10450 10450 10450

 2030 469 469 469 10450 10450 10450

Advanced

 CombustionTurbine 473 9289

 2015 459 473 440 9012 9289 8691

 2020 449 473 416 8781 9289 8193

 2025 433 473 395 8550 9289 7695

 2030 412 473 371 8550 9289 7695

Table 47. Cost and Performance Characteristics for Fossil-Fueled Generating Technologies: Three Cases

1

Total overnight cost (including project contingency, technological optimism and learning factors, but excluding regional multipliers), 

for projects online in the given year.

Source: AEO2008 National Energy Modeling System runs: AEO2008.D030208F, HCFOSS08.D030308A, LCFOSS08.D030308A.
Low and High Energy Project Cost Cases

The AEO2008 Issues in Focus article, “Impacts of Uncertainties in Energy Project Costs”, examines two

scenarios that vary cost assumptions in the power sector as well as the oil and gas and petroleum

submodules. This section will discuss the assumptions used in the EMM for these two cases. Additional

assumptions for these integrated cases can be found in the relevant oil and natural gas chapters of this

document. 

The reference case assumes that investment costs are based on the latest cost data, including any

commodity price increases over the past few years, and that they will remain at these levels throughout the

forecast. The base costs for all technologies in the reference case were increased by 15 percent relative to

AEO2007 to reflect recent cost increases.

The high energy project cost case assumes that the factor costs continue to rise, leading to increasing

investment costs in the energy industry. In the power sector, it is assumed that the base costs of new

generating construction increase by 2.5 percent per year from 2007 through 2030, a rate based on the

construction cost growth of the past five years. Although changes in learning rates can also impact the cost

projections, in general, costs for most technologies in 2030 are about 75 percent higher in the high energy

project cost case than in the reference case.

The low energy project cost case assumes that the underlying factor cost markets gradually see cost

declines back to the levels of the early 2000’s, before the spikes. In the power sector, it is assumed that the

base costs of new generating construction decline by 15 percent over the next ten years. 

Limited Electricity Generation Supply and Limited Natural Gas Supply Cases

The AEO2008 Issues in Focus article, “Limited Electricity Generation Supply and Limited Natural Gas

Supply Cases”, examines cases where severe pressure is put on the natural gas industry. Three cases were 

developed to analyze the uncertainties surrounding the availability of non-natural gas-fired power plants and 

the potential for new natural gas supplies. This section describes the assumptions used in the case

restricting electricity technologies. The assumptions for the second case can be found in the natural gas

chapter of this document. A combined case was also run for the article, and uses the assumptions from both

the electricity and natural gas models.

The limited electricity generation supply case focuses on the potential challenges in the power sector facing

non-natural gas-fired technologies. This case assumes that no new coal plants will be built unless they

include carbon sequestration, due to uncertainty surrounding future environmental requirements. This case

also assumes that new builds of nuclear, wind and biomass will be restricted to reference case levels. New

non-natural gas-fired capacity, including sequestration and other renewables, is assumed to cost 25 percent 

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 93

 Total Overnight Cost1

Advanced

 Nuclear

Technology

Overnight Cost

in 2006 

(Reference)

(2006$/kW)

Reference Case

(2006$/kW)

High

 Nuclear Cost

(2006$/KW)

Low 

Nuclear Cost

(2006$/kW)

2475

2015 2378 2474 2270

2020 2262 2474 2123

2025 2098 2474 1976

2030 2033 2474 1829

Table 48. Cost Characteristics for Advanced Nuclear Technology: Two Cases

1

Total overnight cost (including project contingency, technological optimism and learning factors, but excluding regional

multipliers), for projects online in the given year.

Source: AEO2008 National Energy Modeling System runs: AEO2008.D030208F, HCNUC08.D030308A, LCNUC08.D030308A.
more than in the reference case. Output from existing nuclear capacity is also assumed to decline after

plants reach 40 years of age due to uncertainties surrounding the ability of older plants to maintain high

capacity factors.

94 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 
[1] On February 8, 2008, the U.S Court of Appeals found CAMR to be unlawful and voided it, ruling that

the EPA had not proven that mercury was a pollutant eligible for regulation under a less stringent portion

of the Clean Air Act; however, EIA did not have time to revise AEO2008 before publication to remove the

impact of CAMR.

[2] These costs were developed using the National Energy Technology Laboratory Mercury Control

Performance and Cost Model, 1998.

[3] U.S. Department of Energy, Analysis of Mercury Control Cost and Performance, Office of Fossil

Energy & National Energy Technology Laboratory, January 2003.

Sources referenced in Table 38.

Fossil technology cost and performance characteristics were developed utilizing reviews performed by

A2H Energy Services and Booz Allen Hamilton (BAH) in May 2004. A2H and BAH reviewed the

parameters utilized in the Annual Energy Outlook 2004 (AEO2004) and provided recommended changes

where needed. The averages of the AE2004 values and the recommended values were used.

Aiken, Richard, Booz Allen Hamilton, Review of Fossil Energy Cost and Performance Assumptions in the

Electricity Market Module of the National Energy Modeling System, May 2004.

DeLallo, Michael, Independent Expert (PEER) Review Program for the Energy Information Administration, 

May 17, 2004.

McGraw-Hill Companies, Top Plants, Power Magazine, Vol. 146, No. 5, August 2002. 

A Roadmap to Deploy New Nuclear Power Plants in the United States by 2010 (RDNN), available at the

following link: http://www.nuclear.gov/Nuclear2010/NucPwr2010_PI.html.

“New Fuel for the CANDU - And a new CANDU, too!”; NUKEM Market Report, June 2002.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 95

Notes and Sources

Oil and Gas Supply Module

The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to

analyze oil and gas supply on a regional basis (Figure 7). A detailed description of the OGSM is provided in

the EIA publication, Model Documentation Report: The Oil and Gas Supply Module (OGSM),

DOE/EIA-M063(2007), (Washington, DC, 2007). The OGSM provides crude oil and natural gas short-term

supply parameters to both the Natural Gas Transmission and Distribution Module and the Petroleum Market

Module. The OGSM simulates the activity of numerous firms that produce oil and natural gas from domestic

fields throughout the United States.

OGSM encompasses domestic crude oil and natural gas supply by both conventional and nonconventional

recovery techniques. Nonconventional recovery includes unconventional gas recovery from low

permeability formations of sandstone and shale, and coalbeds. 

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 97

Figure 7. Oil and Gas Supply Model Regions

Source: Energy Information Administration, Office of Integrated Analysis and Forecasting.

Report #:DOE/EIA-0554(2008)

Release date: June 2008

Next release date: March 2009
Primary inputs for the module are varied. One set of key assumptions concerns estimates of domestic

technically recoverable oil and gas resources. Other factors affecting the projection include the assumed

rates of technological progress, supplemental gas supplies over time, and natural gas import and export

capacities.

Key Assumptions

Domestic Oil and Gas Technically Recoverable Resources 

Domestic oil and gas technically recoverable resources1 consist of proved reserves,2 inferred reserves,3

and undiscovered technically recoverable resources.4 OGSM resource assumptions are based on

estimates of technically recoverable resources from the United States Geological Survey (USGS) and the

Minerals Management Service (MMS) of the Department of the Interior.5 Supplemental adjustments to the

USGS nonconventional gas resources are made by Advanced Resources International (ARI), an

independent consulting firm. Based on estimates from the Reserves and Production Division of the EIA

Office of Oil and Gas, 16.1 billion barrels6 are added to US. inferred reserves to reflect a revised assessment 

of the potential of enhanced oil recovery to increase the recoverability of remaining in-place resources. 

While undiscovered resources for Alaska are based on USGS estimates, estimates of recoverable

resources are obtained on a field-by-field basis from a variety of sources including trade press. Published

estimates in Tables 49 and 50 reflect the removal of intervening reserve additions between the date of the

latest available assessment and January 1, 2006.

Lower 48 Offshore

Most of the Lower 48 offshore oil and gas production comes from the deepwater of the Gulf of Mexico

(GOM). Production from current producing fields and industry announced discoveries largely determine the

short-term oil and natural gas production projection. 

For currently producing fields, a 20-percent exponential decline is assumed for production except for natural

gas production from fields in shallow water, which uses a 30-percent exponential decline. Fields that began

production after 2001 are assumed to remain at their peak production level for 2 years before declining. 

The assumed field size and year of initial production of the major announced deepwater discoveries that

were not brought into production by 2007 are shown in Table 51. A field that is announced as an oil field is

assumed to be 100 percent oil and a field that is announced as a gas field is assumed to be 100 percent gas. 

If a field is expected to produce both oil and gas, 70 percent is assumed to be oil and 30 percent is assumed

to be gas. Production is assumed to 

• ramp up to a peak level in 2 to 4 years depending on the size of the field, 

• remain at the peak level until the ratio of cumulative production to initial resource reaches 20 percent

for oil and 30 percent for natural gas, 

• and then decline at an exponential rate of 20-30 percent.

The discovery of new fields (based on MMS’s field size distribution) is assumed to follow historical patterns. 

Production from these fields is assumed to follow the same profile as the announced discoveries (as

described in the previous paragraph).

98 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008
Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 99

Crude Oil Resource Category As of January 1, 2006

Undiscovered 49.86

 Onshore 20.55

 Northeast 1.17

 Gulf Coast 5.23

 Midcontinent 1.12

 Southwest 2.95

 Rocky Moutain 7.77

 West Coast 2.32

 Offshore 29.31

 Deep (>200 meters Water Depth) 27.24

 Shallow (0-200 meters Water Depth) 2.07

Inferred Reserves 62.15

 Onshore 50.69

 Northeast 1.00

 Gulf Coast 5.28

 Midcontinent 6.88

 Southwest 17.24

 Rocky Mountain 11.75

 West Coast 8.54

 Offshore 11.46

 Deep (>200 meters Water Depth) 6.61

 Shallow (0-200 meters Water Depth) 4.85

Total Lower 48 States Unproved 112.01

Alaska 30.64

Total U.S. Unproved 142.65

Proved Reserves 23.02

Total Crude Oil 165.67

Table 49. Crude Oil Technically Recoverable Resources

(Billion barrels)

Note: Resources in areas where drilling is officially prohibited are not included in this table. The 

Alaska value is not explicitly utilized in the OGSM, but is included here to complete the table. The

Alaska value does not include resources from the Arctic Offshore Outer Continental shelf. 

Source: Conventional Onshore, State Offshore, and Alaska - U.S. Geological Survey (USGS);

Federal (Outer Continental Shelf) Offshore - Minerals Management Service (MMS); Proved

Reserves - EIA, Office of Oil and Gas. Table values reflect removal of intervening reserve additions

between the date of the latest available assessment and January 1, 2006.
100 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Natural Gas Resource Category As of January 1, 2006

Lower 48 Nonassociated Conventional Gas 499.96

Undiscovered 273.30

 Onshore 115.51

 Northeast 4.53

 Gulf Coast 64.86

 Midcontinent 14.32

 Southwest 11.15

 Rocky Mountain 14.31

 West Coast 6.33

 Offshore 157.79

 Deep (>200 meters water depth) 100.95

 Shallow (0-200 meters water depth) 56.84

Inferred Reserves 226.66

Onshore 170.89

 Northeast 0.55

 Gulf Coast 79.45

 Midcontinent 56.68

 Southwest 16.84

 Rocky Mountain 16.73

 West Coast 0.64

 Offshore 55.77

 Deep (>200 meters water depth) 9.07

 Shallow (0-200 (meters water depth) 46.71

Unconventional Gas Recovery 499.92

• Tight Gas 304.21

 Northeast 55.98

 Gulf Coast 46.20

 Midcontinent 17.52

 Southwest 13.82

 Rocky Mountain 164.22

 West Coast 6.48

• Shale 124.98

 Northeast 27.73

 Gulf Coast 0.00

 Midcontinent 44.98

 Southwest 38.01

 Rocky Mountain 14.26

 West Coast 0.00

• Coalbed 70.73

 Northeast 5.13

 Gulf Coast 3.66

 Midcontinent 6..01

 Southwest 0.00

 Rocky Mountain 55.92

 West Coast 0.00

Associated-Dissolved Gas 129.61

Total Lower 48 Unproved 1129.49

 Alaska 30.74

Total U.S. Unproved 1160.23

 Proved Reserves 204.39

Total Natural Gas 1364.61

Table 50. Natural Gas Technically Recoverable Resources

(trillion cubic feet)

Sources and Notes for this table are listed in the 'Notes and Sources' section at the end of chapter.
Oil Shale Liquids Production

Projections for oil shale liquids production are based on underground mining and surface retorting

technology and costs. The facility parameter values and cost estimates assumed in the projection are based

on information reported for the Paraho Oil Shale Project, with the costs converted into 2004 dollars.7 Oil

shale rock mining costs, however, are based on current Rocky Mountain underground coal mining costs,

which are representative oil shale rock mining costs. Oil shale facility investment and operating costs are

assumed to decline by 1 percent per year. The construction of commercial oil shale production facilities is not 

permitted prior to 2017, based on the current status of petroleum company research, development and

demonstration (RD&D) programs. 

Although the petroleum company oil shale RD&D programs are focused on the in-situ production of oil shale

liquids, the underground mining and surface retorting process shares many similarities with the in-situ

process. Moreover, because the in-situ process is still at the experimental stage, there are no publicly

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 101

Field/Project

Name Block

Water

Depth

(feet)

Year of

Discovery

Field

Size

Class

Field

Size

(MMBOE)

Start

Year of

Production

Neptune AT575 6220 1995 13 182 2008

Tahiti GC640 4292 2002 15 691 2008

Mirage MC941 4457 1998 12 89 2008

Telemark AT063 3927 2000 12 89 2009

GC238/GC282 GC238 4457 2001 13 182 2009

Shenzi GC653 2386 2002 14 372 2009

Puma GC823 4238 2002 14 372 2009

Blind Faith MC696 4129 2003 14 372 2009

Thunder Hawk MC734 6989 2001 13 182 2009

Thunder Horse MC778 5724 2004 17 2954 2009

Great White AC857 5993 1999 14 372 2010

Trident AC903 9743 2001 13 182 2010

Sturgis AT182 3710 2003 12 89 2010

Entrada GC379 4690 2000 14 372 2010

Hornet MC751 3878 2001 13 182 2010

Goose MC766 1624 2002 12 89 2010

Thunder Horse North MC726 5660 2000 15 691 2010

Cascade WR206 8143 2002 14 372 2010

Chinook WR469 8831 2003 14 372 2010

Knotty Head GC512 3557 2005 14 372 2011

Ringo MC546 2460 2006 14 372 2011

Tubular Bells MC726 4334 2003 12 89 2011

Pony GC468 3497 2006 13 182 2012

La Femme MC427 5800 2004 12 89 2012

Stones WR508 9556 2005 12 89 2012

Tiger AC818 9004 2004 12 89 2013

Norman GB434 5000 2006 15 691 2013

Jack WR759 6963 2004 14 372 2013

Grand Cayman GB517 5000 2006 13 182 2014

St. Malo WR678 7036 2003 14 372 2014

Kaskida KC292 5860 2006 15 691 2015

Egmont MC413 2500 2006 13 182 2015

Big Foot WR029 5235 2006 12 89 2015

Table 51. Assumed Size and Initial Production Year of Major Announced Deepwater Discoveries
available estimates as to the in-situ process capital and operating costs required to produce a barrel of oil

shale liquids at a commercial scale. Consequently, the underground mining and surface retorting costs, in

conjunction with the 1 percent per year cost decline, are intended to be a surrogate for the in-situ process

costs.

Oil shale production facilities are assumed to be built when the net present value of the discounted cash flow

exceeds zero. The discounted cash flow calculation uses a calculated discount rate that takes into

consideration the financial risk associated with building oil shale facilities. Oil shale facilities take 5 years to

construct, with an additional 5 years required to bring an in-situ facility into full production. An assumed

technology penetration rate specifies that 5 years must pass from the time the first facility begins

construction before the second facility can begin construction. Subsequent facilities are permitted to begin

construction 3 years, 2 years, and then every year after a prior facility begins construction. Oil shale liquids

production is not resource constrained, because approximately 400 billion barrels of petroleum liquids exist

in oil shale rock with at least 30 gallons per ton of rock.

Because the in-situ process is still at the experimental stage, and because the underground mining and

surface retorting process is unlikely to be environmentally acceptable, the oil shale liquids production

projections should be considered highly uncertain.

Alaska Crude Oil Production

Projected Alaska oil production includes both existing producing fields and undiscovered fields that are

expected to exist, based upon the region’s geology. The existing fields category includes the expansion

fields around the Prudhoe Bay and Alpine Fields for which companies have already announced

development schedules. The initial production from these fields occurs in the first few years of the projection, 

with the projected oil production and the date of commencement based on the most current petroleum

company announcements. Alaska crude oil production from the undiscovered fields is determined by the

estimates of available resources in undeveloped areas and the net present value of the cash flow calculated

for these undiscovered fields based on the expected capital and operating costs, and on the projected oil

prices. Based on the latest U.S. Geological Survey resource assessments, the remaining North Slope fields

are expected to be primarily small and mid-size oil fields that are smaller than the Alpine Field.

Oil and gas exploration and production currently are not permitted in the Alaska National Wildlife Refuge.

The projections for Alaska oil and gas production assume that this prohibition remains in effect throughout

the projection period.

The greatest uncertainty associated with the Alaska oil projections is whether the heavy oil deposits located

on the North Slope, which exceed 20 billion barrels of oil-in-place, will be producible in the foreseeable future 

at recovery rates exceeding a few percent.

Supplemental Natural Gas

The projection for supplemental gas supply is identified for three separate categories: synthetic natural gas

(SNG) from liquids, SNG from coal, and other supplemental supplies (propane-air, coke oven gas, refinery

gas, biomass air, air injected for Btu stabilization, and manufactured gas commingled and distributed with

natural gas). SNG from the currently operating Great Plains Coal Gasification Plant is assumed to continue

through the projection period, at an average historical level of 50.9 billion cubic feet per year.8 Other

supplemental supplies are held at a constant level of 10.7 billion cubic feet per year throughout the projection 

because this level is consistent with historical data and it is not believed to change significantly in the context

of a reference case. Synthetic natural gas from liquid hydrocarbons in Hawaii is assumed to continue over

the projection at the average historical level of 2.7 billion cubic feet per year.

102 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008
Legislation and Regulations

The Outer Continental Shelf Deep Water Royalty Act (Public Law 104-58) gave the Secretary of Interior the

authority to suspend royalty requirements on new production from qualifying leases and required that royalty 

payments be waived automatically on new leases sold in the 5 years following its November 28, 1995,

enactment. The volume of production on which no royalties were due for the 5 years was assumed to be

17.5 million barrels of oil equivalent (BOE) in water depths of 200 to 400 meters, 52.5 million BOE in water

depths of 400 to 800 meters, and 87.5 million BOE in water depths greater than 800 meters. In any year

during which the arithmetic average of the closing prices on the New York Mercantile Exchange for light

sweet crude oil exceeded $28 per barrel or for natural gas exceeded $3.50 per million Btu, any production of

crude oil or natural gas was subject to royalties at the lease stipulated royalty rate. Although automatic relief

expired on November 28, 2000, the act provided the MMS the authority to include royalty suspensions as a

feature of leases sold in the future. In September 2000, the MMS issued a set of proposed rules and

regulations that provide a framework for continuing deep water royalty relief on a lease by lease basis. In the 

model it is assumed that relief will be granted roughly the same levels as provided during the first 5 years of

the act.

Section 345 of the Energy Policy Act of 2005 provides royalty relief for oil and gas production in water depths

greater than 400 meters in the Gulf of Mexico from any oil or gas lease sale occurring within 5 years after

enactment. The minimum volume of production with suspended royalty payments are: 

(1) 5,000,000 barrels of oil equivalent (BOE) for each lease in water depths of 400 to 800 meters; 

(2) 9,000,000 BOE for each lease in water depths of 800 to 1,600 meters; 

(3) 12,000,000 BOE for each lease in water depths of 1,600 to 2,000 meters; and 

(4) 16,000,000 BOE for each lease in water depths greater than 2,000 meters. 

The water depth categories specified in Section 345 were adjusted to be consistent with the depth

categories in the Offshore Oil and Gas Supply Submodule. The suspension volumes are 5,000,000 BOE for

leases in water depths 400 to 800 meters; 9,000,000 BOE for leases in water depths of 800 to 1,600 meters;

12,000,000 BOE for leases in water depth of 1,600 to 2,400 meters; and 16,000,000 for leases in water

depths greater than 2,400 meters. Examination of the resources available at 2,000 to 2,400 meters showed

that the differences between the depths used in the model and those specified in the bill would not materially

affect the model result. 

The Minerals Management Service published its final rule on the “Oil and Gas and Sulphur Operations in the

Outer Continental Shelf–Relief or Reduction in Royalty Rates–Deep Gas Provisions” on January 26, 2004,

effective March 1, 2004. The rule grants royalty relief for natural gas production from wells drilled to 15,000

feet or deeper on leases issued before January 1, 2001, in the shallow waters (less than 200 meters) of the

Gulf of Mexico. Production of gas from the completed deep well must begin before 5 years after the effective

date of the final rule. The minimum volume of production with suspended royalty payments is 15 billion cubic 

feet for wells drilled to at least 15,000 feet and 25 billion cubic feet for wells drilled to more than 18,000 feet.

In addition, unsuccessful wells drilled to a depth of at least 18,000 feet would receive a royalty credit for 5

billion cubic feet of natural gas. The ruling also grants royalty suspension for volumes of not less than 35

billion cubic feet from ultra-deep wells on leases issued before January 1, 2001.

Section 354 of the energy Policy Act of 2005 established a competitive program to provide grants for

cost-shared projects to enhance oil and natural gas recovery through CO2 injection, while at the same time

sequestering CO2 produced from the combustion of fossil fuels in power plants and large industrial

processes. 

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 103
Oil and Gas Supply Alternative Cases

Rapid and Slow Technology Cases

Two alternative cases were created to assess the sensitivity of the projections to changes in the assumed

rates of progress in oil and natural gas supply technologies. To create these cases a number of parameters

representing technological penetration in the reference case were adjusted to reflect a more rapid and a

slower penetration rate. In the reference case, the underlying assumption is that technology will continue to

penetrate at historically observed rates. Since technologies are represented somewhat differently in

different submodules of the Oil and Gas Supply Module, the approach for representing rapid and slow

technology penetration varied as well. For instance, the effects of technological progress on conventional oil 

and natural gas parameters in the reference case, such as finding rates, drilling, lease equipment and

operating costs, and success rates, were adjusted upward and downward by 50 percent (Table 52), for the

rapid and slow technology cases, respectively. The approach taken in unconventional natural gas is

discussed below. 

In the Canadian supply submodule, successful natural gas wells and production levels in the Western

Canadian Sedimentary Basin (WCSB) are assumed to be progressively greater in the rapid technology case 

and lesser in the slow technology case across the projection horizon. By 2030, the number of successful

natural gas wells associated with conventional and tight formations are approximately 16 percent higher and

lower in the rapid and slow technology cases than in the reference case due to differences in assumed

technological improvements. The resource base levels for the WCSB were assumed not to vary across

technology cases. The technology growth parameter on production from coal bed natural gas wells is

adjusted upward and downward by 75 percent under the rapid and slow technology cases, resulting in

production levels approximately 26 percent higher or lower due to assumed technological differences.

Finally, the minimum supply prices deemed necessary to trigger the Alaska and MacKenzie Delta natural

gas pipelines are progressively decreased or increased over the projection in the rapid and slow technology

cases, respectively, downward or upward from 0.0 to 12.5 percent by 2030. All other parameters in the

model were kept at their reference case values, including technology parameters for other modules,

parameters affecting foreign oil supply, and assumptions about imports and exports of LNG and natural gas

trade between the United States and Mexico. Production costs in the MacKenzie Delta vary across the

projection period based on the estimated change in drilling costs in the lower 48 states, indirectly capturing

the impact of different assumptions about technological improvement.

The Unconventional Gas Recovery Supply Submodule (UGRSS) relies on Technology Impacts and Timing

functions to capture the effects of technological progress on costs and productivity in the development of gas 

from deposits of coalbed methane, gas shales, and tight sands. The numerous research and technology

initiatives are combined into 11 specific “technology groups,” that encompass the full spectrum of key

disciplines — geology, engineering, operations, and the environment. The technology groups utilized for the 

Annual Energy Outlook 2008 are characterized for three distinct technology cases — Slow Technological

Progress, Reference Case, and Rapid Technological Progress — that capture three different futures for

technology progress. The 11 technology groups are listed in Table 53. Table 54 provides a description of

their treatment under the different technology cases.

Arctic National Wildlife Refuge (ANWR) Case

The Arctic National Wildlife Refuge (ANWR) case assumes that Congressional legislation opening the

Federal 1002 Area to Federal oil and gas leasing would be enacted in 2008.

The ANWR case is solely focused on the potential for ANWR to produce crude oil. The ANWR case

assumes that any gas found within ANWR would be re-injected into ANWR oil reservoirs to maintain

reservoir pressure and that any Alaskan gas pipeline built during the projection period would rely on the

natural gas reserves and resources found within the State lands located in the Central North Slope.

The ANWR case assumes that the opening of the Federal 1002 Area would also open the Native lands and

State offshore region to oil exploration. The Federal, State, and Native lands are referred to collectively as

104 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008
Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 105

 

Category Slow Reference Rapid

Lower 48 Onshore

Costs

 Drilling 0.25 0.50 0.75

 Lease Equipment 0.28 0.55 0.83

 Operating 0.19 0.39 0.58

Finding Rates

 New Field Discoveries 0.00 0.00 0.00

 Known Fields 0.50 1.00 2.00

Success Rates

 Exploratory 0.25 0.50 0.75

 Developmental 0.25 0.50 0.75

Lower 48 Offshore

Exploration success rates 0.50 1.00 1.50

Delay to commence first exploration and between 

 exploration (years)

0.25 0.50 1.00

Exploration and Development drilling costs 0.50 1.00 1.50

Operating costs 0.50 1.00 1.50

Time to construct production facility (years) 0.25 0.50 1.00

Production facility construction costs 0.50 1.00 1.50

Initial constant production rate 0.25 0.50 1.00

Production Decline rate 0.00 0.00 0.00

Alaska

 Costs

 Drilling 0.50 1.00 1.50

 Lease Equipment 0.50 1.00 1.50

 Operating 0.50 1.00 1.50

Finding Rates 1.50 3.00 4.50

Table 52. Assumed Annual Rates of Technological Progress for Conventional Crude Oil and Natural Gas

 Sources

(percent/year)

Source: The values shown in this table are developed by the Energy Information Administration, Office of Integrated Analysis and

Forecasting from econometric analysis for onshore costs and discussions with various industry and government sources for

offshore and Alaska costs. Onshore drilling cost data are based on the American Petroleum Institute's Joint Association Survey on

Drilling Costs. Onshore lease equipment and operating costs are based on the Energy Information Administration's Costs and

Indices for Domestic Oil & Gas Field Equipment and Production Operations.
106 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Technology 

Group

Technology Type Impact

1 Basin assessments Increase the available resource base by a) accelerating the time that hypothetical plays in

currently unassessed areas become available for development and b) increasing the play

probability for hypothetical plays – that portion of a given area that is likely to be productive.

2 Play specific, extended

reservoir characterizations

Increase the pace of new development by accelerating the pace of development of emerging 

plays, where projects are assumed to require extra years for full development compared to

plays currently under development.

3 Advanced well performance

diagnostics and remediation

Expand the resource base by increasing reserve growth for already existing reserves.

4 Advanced exploration and

natural fracture detection R&D

Increases the success of development by a) improving exploration/development drilling

success rates for all plays and b) improving the ability to find the best prospects and areas.

5 Geology technology modeling

and matching

Matches the “best available technology” to a given play with the result that the expected

ultimate recovery (EUR) per well is increased.

6 More effective, lower damage

well completion and stimulation

technology

Improves fracture length and conductivity, resulting in increased EUR’s per well.

7 Targeted drilling and hydraulic

fracturing R&D

Results in more efficient drilling and stimulation which lowers well drilling and stimulation

costs.

8 New practices and technology

for gas and water treatment

Result in more efficient gas separation and water disposal which lowers water and gas

treatment operation and maintenance costs.

9 Advanced well completion

technologies, such as

cavitation, horizontal drilling,

and multi-lateral wells:

Defines applicable plays, thereby accelerating the date such technologies are available and

introduces and improved version of the particular technology, which increases EUR per well.

10 Other unconventional gas

technologies, such as

enhanced coalbed methane

and enhanced gas shales

recovery

Introduce dramatically new recovery methods that a) increase EUR per well and b) become

available at dates accelerated by increase R&D, with c) increased operation and

maintenance costs (in the case of coalbed methane) for the incremental gas produced.

11 Mitigation of environmental

constraints

Removes development constraints in environmentally sensitive basins, resulting in an

increase in basin areas available for development.

Table 53. Technology Types and Impacts

Source: Advanced Resources International.
Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 107

Technology Case

Technology

 Group Item Type of Deposit Slow Reference Rapid

1 Year Hypothetical Plays Become Available All Types-Non DOE

All Types-DOE

NA

NA

NA

2016

NA

2009

2 Decrease in Extended Portion of Development

Schedule for Emerging Plays (per year)

Coalbed Methane and

 Tight Sands - Non DOE

Gas Shales-Non DOE

All Types - DOE

0.83%

1.25%

1.25%

1.67%

2.50%

2.50%

2.50%

3.75%

3.75%

3 Expansion of Existing Reserves (per year

 -declining 0.1% per year; eg., 3.0, 2.0...)

Tight Sands

Coalbed Methane &

 Gas Shales

1.0%

2.0%

2.0%

4.0%

3.0%

6.0%

4 Increase in Percentage of Wells Drilled

 Successfully (per year)

All Types 0.1% 0.2% 0.3%

Year that Best 30 Percent of Basin is Fully

 Identified

All Types 2100 2044 2031

5 Increase in EUR per Well (per year) All Types 0.13% 0.25% 0.38%

6 Increase in EUR per Well (per year) All Types 0.13% 0.25% 0.38%

7 Decrease in Drilling and Stimulation Costs per

Well (per year)

All Types NA NA NA

8 Decrease in Water and Gas Treatment O&M

Costs per Well (per year)

All Types NA NA NA

9 Year Advanced Well Completion

Technologies Become Available

Coalbed Methane

Tight Sands &Gas

Shales

NA

NA

NA

2016

NA

2009

Increase in EUR per well (total increase) Coalbed Methane NA NA NA

Tight Sands NA 10% 15%

Gas Shales NA 20% 30%

10 Year Advanced Recovery Technologies

 Become Available

Coalbed Methane &

Tight Sands

Gas Shales

NA

NA

NA

NA

2023

NA

Increase in EUR per well (total increase) Coalbed Methane NA NA 45%

Tight Sands NA NA 15%

Gas Shales NA NA NA

Increase in Costs ($1996/Mcf) for Incremental

 CBM production

Coalbed Methane

Tight Sands

NA

NA

NA

NA

1.75

0.75

GasShales NA NA NA

11 Proportion of Areas Current Restricted that

 become Available for Development (per year)

All Types - Non DOE

All Types - DOE

0.5%

0.25%

1.0%

0.5%

1.5%

0.75%

Table 54. Assumed Rates of Technological Progress for Unconventional Gas Recovery

EUR = Estimated Ultimate Recovery.

O&M = Operation & Maintenance.

CBM = Coalbed Methane.

NA = Not applicable.

DOE = Those plays in the Rocky Mountain basins assessed as part of Department of Energy sponsored basin studies.

Source: Reference Technology Case, Advanced Resources, International; Slow and Rapid Technology Cases, Energy Information

Administration, Office of Integrated Analysis and Forecasting.
the ANWR Coastal Plain. The ANWR case assumes that the size of the oil fields discovered within the

coastal plain is based on the mean U.S. Geological Survey (USGS) estimate of 10.4 billion barrels of

technically recoverable crude oil9 that the USGS10 estimated for the Federal, State, and Native lands in or

adjacent to ANWR. 

The ANWR case assumes first production from the ANWR area would occur 10 years after the 2008

enactment of legislation opening ANWR to oil and gas leasing. So first ANWR oil production would occur in

2018, based on the following timeline:

• 2 to 3 years to obtain U.S. Bureau of Land Management (BLM) leases.

• 2 to 3 years to drill a single exploratory well, due to the limited winter drilling season.

• 1 to 2 years to develop a production development plan and obtain BLM approval for that plan.

• 3 to 4 years to construct the necessary infrastructure and to drill and complete development wells.

The 10-year timeline for developing ANWR petroleum resources assumes that there are no protracted legal

battles regarding the leasing and development of ANWR oil resources.

The ANWR case assumes that much of the oil resources in ANWR, like the other oil resources on Alaska’s

North Slope, could be profitably developed given the current levels of technology and at current and

projected oil prices. This analysis also assumes that new fields in ANWR will begin development 2 years

after a prior ANWR field begins oil production.

108 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008
The ANWR case uses the USGS mean oil resource estimate of potential field sizes in the coastal plain area. 

Because the larger fields are generally easier to find and cheaper to develop, the ANWR case assumes that

the largest oil fields are developed first. Based on the 2-year time lag assumption between the development

of successive oil fields and the USGS field size distribution, the ANWR case assumes the following oil field

development schedule:

Potential production from ANWR fields is based on the size of the field discovered and the production

profiles of other fields of the same size in Alaska with similar geological characteristics. In general, fields are

assumed to take 3 to 4 years to reach peak production, maintain peak production for 3 to 4 years, and then

decline until they are no longer profitable and are closed.

Natural Gas Supply Assumptions for the Limited Natural Gas Supply Case and for

the Combined Limited Alternatives Case

The combined limited alternatives case includes all the same assumptions regarding natural gas supply, but

with additional assumptions regarding the electric power sector.

Two large natural gas pipelines are under consideration for development in the Arctic region of North

America, which collectively would significantly add to lower 48 gas supply - a Mackenzie Delta gas pipeline in 

Canada and an Alaska gas pipeline.11 In the reference case, the building of these pipelines is based on the

prevailing economics of each pipeline; that is, the lower-48 natural gas price relative to the cost of building

and operating each pipeline. In the limited natural gas supply case, neither Arctic pipeline is allowed to be

built through 2030.

In the limited natural gas supply case, gross domestic LNG imports are held constant at 1.0 trillion cubic feet

starting in 2009 and extending through 2030. This LNG supply assumption is identical to that used in the low

LNG case.

The reference case oil and gas production projections are based on the U.S. Geological Survey (USGS) and

U.S. Minerals Management Service (MMS) mean estimates of the technically recoverable domestic oil and

gas resource base. The limited natural gas supply case assumes that the U.S. undiscovered oil and gas

resource base is 15 percent less than the mean USGS and MMS estimates that are used in the reference

case. The Canadian undiscovered natural gas resource base is also assumed to be 15 percent less in this

case. This low oil and gas resource base assumption is identical to that assumed in the high price case.

Technological progress generally reduces the cost of finding, developing, and producing natural gas

resources. In the limited natural gas supply case, the future rate of technological progress proceeds at half

the rate embodied in the reference case, for both oil and gas in the United States and for natural gas in

Canada. This assumption is the same as that used in the low oil and gas technology case.

In the limited natural gas supply case, coal-to-gas technology is assumed to be unavailable as a means for

providing domestic natural gas supply.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 109

Year In Which Field Begins Production ANWR Case Field Size

(million barrels)

2018 1,370

2020 700

2022 700

2024 360

2026 360

2028 360

2030 360

Total 4,210

Source: Energy Information Administration, Office of Integrated Analysis and Forecasting.
Oil and Natural Gas Cost Assumptions for the Low and High Project Cost Cases

High Project Cost Case Assumptions for Oil and Natural Gas

In the high commodity cost case, it is assumed that the oil and gas wells and construction materials costs

continue to rise beyond current levels.

In the oil and gas supply module, the oil and gas well drilling costs escalate from 2007 through 2010 to twice

the reference case level in 2010. After 2010, oil and gas well drilling costs are held constant at twice the

reference case level though 2030. This cost escalation is partly offset by an annual technology improvement

factor. Pipeline construction costs are increased over the reference case by one percent per year for both

Lower 48 pipeline construction and for the Alaska and Mackenzie Delta pipelines. 

LNG liquefaction costs match the reference case increase through 2008. In 2009, LNG liquefaction costs are 

set to be 20 percent higher than those in 2008. LNG liquefaction costs remain constant at the 2009 through

2030. LNG regasification facilities construction costs are increased by 15 percent above the reference case

in 2008 and held constant through 2030. LNG shipping costs are increased by seven percent through 2008

above the reference case level and then held constant through 2030. 

In the refining sector, construction costs are increased above the reference case level by a factor equal to

the percentage difference between the 2004 and 2006 Nelson-Farrar index and held constant from 2008

through 2030. Construction costs for corn and cellulosic ethanol plants are treated similarly using the

Chemical Engineering Plant Cost Index (CEPCI).

Low Project Cost Case Assumptions for Oil and Natural Gas

In the low project cost case it is generally assumed that commodity prices will gradually decline back to price

levels seen 5 years ago.

In the oil and gas supply module, the oil and gas well drilling costs decline from 2007 through 2010 to half the

reference case level in 2010. After 2010, oil and gas well drilling costs are held constant at half the reference

case level though 2030. Pipeline construction costs are decreased below the reference case by one percent

per year. The increase applied to LNG liquefaction facility construction costs in the reference case is phased

back down to the 2006 cost level by 2015 and is held constant thereafter. The 15 percent and 7 percent

increases applied to the LNG regasification construction and shipping costs in the reference case are

phased out starting in 2009 and ending in 2018. 

The recent run-up in refinery construction costs is assumed to be a temporary aberration with construction

costs returning to historic levels through the addition of new commodity supplies and/or a reduction in

demand for those commodities. The Nelson-Farrar index and CEPCI are used to scale refinery and ethanol

plant construction costs, respectively, down to their 2004 levels. These costs are then held constant through 

2030.

110 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008
[1] Technically recoverable resources are resources in accumulations producible using current recovery

technology but without reference to economic profitability.

[2] Proved reserves are the estimated quantities that analysis of geological and engineering data

demonstrate with reasonable certainty to be recoverable in future years from known reservoirs under

existing economic and operating conditions.

[3] Inferred reserves are that part of expected ultimate recovery from known fields in excess of

cumulative production plus current reserves.

[4] Undiscovered resources are located outside oil and gas fields in which the presence of resources has

been confirmed by exploratory drilling; they include resources from undiscovered pools within confirmed

fields when they occur as unrelated accumulations controlled by distinctly separate structural features or

stratigraphic conditions.

[5] Donald L. Gautier and others, U.S. Department of Interior, U.S. Geological Survey, 1995 National

Assessment of the United States Oil and Gas Resources, (Washington, D.C., 1995); U.S. Department of

Interior, Minerals Management Service, Report to Congress: Comprehensive Inventory of U.S. OCS Oil 

and Natural Gas Resources, (February 2006); and 2003 estimates of conventionally recoverable

hydrocarbon resources of the Gulf of Mexico and Atlantic Outer Continental Shelf as of January 1, 2003.

[6] The amounts added (in billion barrels) among the various OGSM regions are as follows: Northeast

0.4, Gulf Coast 5.0, Midcontinent 3.8, Southwest 4.1, Rocky Mountain 1.5, and West Coast 1.3.

[7] Source: Noyes Data Corporation, Oil Shale Technical Data Handbook, edited by Perry Nowacki, Park 

Ridge, New Jersey, 1981, pages 89-97. The Paraho Oil Shale Project design had a maximum production 

rate of 100,000 syncrude barrels per day, which is used in the OSSS as the standard oil shale facility

size.

[8] The potential for the introduction of new coal-to-gas capacity was not considered for AEO2008, but

will be incorporated in AEO2009 projections.

[9] Technically recoverable resources are resources that can be produced using current technology.

[10] U.S. Department of Interior, U.S. Geological Survey, The Oil and Gas Resource Potential of the

Arctic National Wildlife Refuge 1002 Area, Alaska, Open File Report 98-34, 1999; U.S. Geological

Survey, USGS Fact Sheet FS-028-01, April 2001; and, Oil and Gas Resources of the Arctic Alaska

Petroleum Province, by David W. Houseknecht and Kenneth J. Bird, U.S. Geological Survey Professional

Paper 1732–A, 2005.

[11] The National Energy Modeling System assumes that Canadian and Alaska gas pipelines would be

interconnected to U.S. lower 48 natural gas markets. The no Arctic pipelines assumption also precludes

the building of a natural gas pipeline from the Alaska North Slope to South-Central Alaska, where the gas

would be converted to liquefied natural gas (LNG) and then shipped to foreign and domestic LNG

customers. However, this assumption does not preclude the conversion of Alaska North Slope gas into

petroleum liquids, which would then be shipped through the existing Alyeska Oil Pipeline (also known as

the TransAlaska Pipeline System).

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 111

Notes and Sources
Notes and Sources for Table 50

Note: Resources in areas where drilling is officially prohibited are not included in this table. Also, the

Associated-Dissolved Gas and the Alaska values are not explicitly utilized in the OGSM, but are included

here to complete the table. The Alaska value does not include stranded Arctic gas. 

Source: Onshore, State Offshore, and Alaska - U.S. Geological Survey (USGS) with adjustments to

Unconventional Gas Recovery resources by Advanced Resources, International; Federal (Outer

Continental Shelf) Offshore - Minerals Management Service (MMS); Proved Reserves -- EIA, Office of

Oil and Gas. Table values reflect removal of intervening reserve additions between the date of the latest

available assessment and January 1, 2006.

112 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Notes and Sources
Natural Gas Transmission and Distribution

Module

The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas

production, wellhead and border prices, end-use prices, and flows of natural gas through the regional

interstate network, for both a peak (December through March) and off peak period during each projection

year. These are derived by solving for the market equilibrium across the three main components of the

natural gas market: the supply component, the demand component, and the transmission and distribution

network that links them. Natural gas flow patterns are a function of the pattern in the previous year, coupled

with the relative prices of the supply options available to bring gas to market centers within each of the

NGTDM regions (Figure 8). The major assumptions used within the NGTDM are grouped into five general

categories. They relate to (1) structural components of the model, (2) capacity expansion and pricing of

transmission and distribution services, (3) Arctic pipelines, and (4) imports and exports. A complete listing of 

NGTDM assumptions and in-depth methodology descriptions are presented in Model Documentation:

Natural Gas Transmission and Distribution Model of the National Energy Modeling System, Model

Documentation 2007, DOE/EIA-M062(2007) (Washington, DC, 2007). 

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 113

Pacific

(9)

Mountain

(8)

CA

(12)

AZ/NM

(11)

W. North Central

(4)

W. South Central

(7)

E. South

Central

(6)

E. North

Central

(3)

S. Atlantic

(5)

FL

(10)

Mid.

Atlantic

(2)

New

Engl.

(1)

W. Canada

E. Canada

MacKenzie

Alaska Canada

Offshore

and LNG

Mexico

Bahamas

Primary Flows

Secondary Flows

Pipeline Border Crossing

Specific LNG Terminals

Generic LNG Terminals

Pacific

(9)

Mountain

(8)

CA

(12)

AZ/NM

(11)

W. North Central

(4)

W. South Central

(7)

E. South

Central

(6)

E. North

Central

(3)

S. Atlantic

(5)

FL

(10)

Mid.

Atlantic

(2)

New

Engl.

(1)

W. Canada

E. Canada

MacKenzie

Alaska Canada

Offshore

and LNG

Mexico

Bahamas

Primary Flows

Secondary Flows

Pipeline Border Crossing

Specific LNG Terminals

Generic LNG Terminals

Figure 8. Natural Gas Transmission and Distribution Model Regions

Source: Energy Information Administration, Office of Integrated Analysis and Forecasting

Report #:DOE/EIA-0554(2008)

Release date: June 2008

Next release date: March 2009
Key Assumptions

Structural Components

The primary and secondary region-to-region flows represented in the model are shown in Figure 8. Primary

flows are determined, along with nonassociated gas production levels, as the model equilibrates supply and

demand. Associated-dissolved gas production is determined in the Oil and Gas Supply Module (OGSM). 

Secondary flows are established before the equilibration process and are generally set exogenously. 

Liquefied natural gas (LNG) imports are also not directly part of the equilibration process, but our set at the

beginning of each NEMS iteration in response to the price from the previous iteration. Flows and production

levels are determined for each season, linked by seasonal storage. When required, annual quantities (e.g.,

consumption levels) are split into peak and offpeak values based on historical averages. When multiple

regions are contained in a Census Division, regional end-use consumption levels are approximated using

historical average shares. Pipeline and storage capacity are added as warranted by the relative volumes

and prices. Regional pipeline fuel and lease and plant fuel consumption are established by applying an

historically based factor to the flow of gas through a region and the production in a region, respectively. 

Prices within the network, including at the borders and the wellhead, are largely determined during the

equilibration process. Delivered prices for each sector are set by adding an endogenously estimated

markup (generally a distributor tariff) to the regional representative citygate price. Supply curves and electric 

generator gas consumption are provided by other NEMS modules for subregions of the NGTDM regions,

reflective of how their internal regions overlap with the NGTDM regions.

Capacity Expansion and Pricing of Transmission and Distribution Services

For the first 2 projection years, announced pipeline and storage capacity expansions (that are deemed

highly likely to occur) are used to establish limits on flows and seasonal storage in the model. Subsequently,

pipeline and storage capacity is added when increases in consumption, coupled with an anticipated price

increase, warrant such additions (i.e., flow is allowed to exceed current capacity if the demand still exists

given an assumed increased tariff). Once it is determined that an expansion will occur, the associated

capital costs are applied in the revenue requirement calculations in future years. Capital costs are assumed

based on average costs of recent comparable expansions for compressors, looping, and new pipeline.

It is assumed that pipeline and local distribution companies build and subscribe to a portfolio of interstate

pipeline and storage capacity to serve a region-specific colder-than-normal winter demand level, currently

set at 30 percent above the daily average. Maximum pipeline capacity utilization in the peak period is set at

99 percent. In the off-peak period, the maximum is assumed to vary between 75 and 99 percent of the

design capacity. The overall level and profile of consumption, as well as the availability and price of supplies, 

generally cause realized pipeline utilization levels to be lower than the maximum.

Pricing of Services

While transportation tariffs for interstate pipeline services are initially based on a regulated cost-of-service

calculation, an adjustment to the tariffs is applied which is dependent on the realized utilization rate, to reflect 

a market-based differential. Transportation rates for interstate pipeline services (both between NGTDM

regions and within a region) are calculated assuming that the costs of new pipeline capacity will be rolled into 

the existing rate base.

Delivered prices by sector and season are derived by adding a markup to the average regional market price

of natural gas in both peak and off-peak periods. (Prices are reported on an annual basis and represent

quantity-weighted averages of the two seasons.) These markups include the cost of service provided by

intraregional interstate pipelines, intrastate pipelines, and local distributors. The intrastate tariffs are

accounted for endogenously through historical model benchmarking. Distributor tariffs represent the

difference between the regional delivered and citygate price, independent of whether or not a customer class 

typically purchases gas through a local distributor. 

The distribution tariffs are projected using econometrically estimated equations, primarily in response to

changes in consumption levels. An assumed differential is used to divide the industrial price into one for

114 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 
noncore customers (refineries and industrial boiler users) and one for core customers who have less

alternative fuel options. 

The vehicle natural gas (VNG) sector is divided into fleet and non-fleet vehicles. In general, the distributor

tariffs for natural gas to vehicles are set to EIA’s Natural Gas Annual historical end-use prices minus citygate 

prices plus Federal and State VNG taxes (held constant in nominal dollars) plus an assumed dispensing

cost. Dispensing costs are assumed to be $3.82 and $2.23 (2006 dollars per mcf) for non-fleet and fleet

vehicles, respectively. The price to non-fleet vehicles is set to 75 percent of the equivalent motor gasoline

price, if it would have been lower otherwise.

Pipelines from Arctic Areas into Alberta 

The outlook for natural gas production from the North Slope of Alaska is affected strongly by the unique

circumstances regarding its transport to market. Unlike virtually all other identified deposits of natural gas in

the United States, North Slope gas lacks a means of economic transport to major commercial markets. The

lack of viable marketing potential at present has led to the use of Prudhoe Bay gas to maximize crude oil

recovery in that field. Recent high natural gas prices seemingly raised the potential economic viability of

such a project, although expected costs have increased as well. Setbacks in negotiations between the

primary producers and the Alaska government have further delayed the project. The primary assumptions

associated with estimating the cost of North Slope Alaskan gas in Alberta, as well as for MacKenzie Delta

gas into Alberta, are shown in Table 55. A calculation is performed to estimate a regulated, levelized, tariff

for each pipeline. Additional items are added to account for the wellhead price, treatment costs, pipeline fuel 

costs, and a risk premium to reflect the potential impact on the market price once the pipeline comes on line. 

For the Alaska pipeline the uncertainty associated with the initial capitalization is captured by applying a

value that is 20 percent higher than the expected value. For comparison purposes, a price differential of

$0.68 (2006 dollars per Mcf) is assumed between the price in Alberta and the average lower 48 price. The

resulting cost of Alaska gas, relative to the lower 48 wellhead price, is approximately $4.37 (2006 dollars per

Mcf), with some variation across the projection due to changes in gross domestic product. Construction of

an Alaska-to-Alberta pipeline is projected to commence if the assumed total costs for Alaska gas in the lower 

48 States exceeds the average lower 48 gas price in each of the previous 2 years, on average over the

previous 5 years (with greater weight applied to more recent years), and as expected to average over the

next 3 years. An adjustment is made if prices were declining over the previous 5 years. Once the assumed

4-year construction period is complete, expansion can occur if the price exceeds the initial trigger price by

$1.94 (2006 dollars per Mcf). When the Alaska to Alberta pipeline is built in the model, additional pipeline

capacity is added to bring the gas across the border into the United States. For accounting purposes, the

model assumes that all of the Alaska gas will be consumed in the United States and that sufficient

economical supplies are available at the North Slope to fill the pipeline over the depreciation period.

Natural gas production from the MacKenzie Delta is assumed to be sufficient to fill a pipeline over the

projection period should one be built connecting the area to markets in the south. The basic methodology

used to represent the decision to build a MacKenzie pipeline is similar to the process used for an

Alaska-to-lower 48 pipeline, using the primary assumed parameters listed in Table 56. One exception is that 

wellhead costs are assumed to change across the projection period with estimated changes to drilling costs

for the lower 48 States.

Natural Gas Imports and Exports

U.S. natural gas trade with Mexico is determined endogenously based on various assumptions about the

natural gas market in Mexico. U.S. natural gas exports from the United States to Canada are set

exogenously in NEMS starting at 365 billion cubic feet per year in 2007 and increasing to 519 tcf by 2030.

Canadian production and U.S. import flows from Canada are determined endogenously within the model. 

Growth rates for consumption in Mexico are set exogenously based on projections from the International

Energy Outlook 2007 and are provided on Table 57, along with initially assumed growth rates for production

in Mexico from the same source. Adjustments are made endogenously within the model to reflect a

response to price fluctuations within the market. Domestic production is assumed to be supplemented by

LNG from receiving terminals constructed on both the east and west coasts of Mexico that serve only the 

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 115
116 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 

Alaska to Alberta MacKenzie Delta to Alberta

Initial flow into Alberta 3.9 Bcf per day 1.1 Bcf per day

Expansion potential 22 percent 58 percent

Initial capitalization 20.9 billion (2006 dollars) $10.0 billion (2006 dollars)

Cost of Debt (premium over AA bond

rate) 0.0 percent 1.0 percent

Cost of equity (premium over AA bond

rate) 5.0 percent 8.0 percent

Debt fraction 80 percent 70 percent

Depreciation period 15 years 15 years

Minimum wellhead price (including $1.61 (2006 dollars per Mcf) $2.94 (2006 dollars per Mcf)

 treatment and fuel costs)

Risk Premium $0.34 (2006 dollars per Mcf) $0.06 (2006 dollars per Mcf)

Additional cost for expansion $1.94 (2006 dollars per Mcf) $0.34 (2006 dollars per Mcf)

Construction period 4 years 3 years

Planning period 5 years 2 years

Earliest start year 2020 2014

Table 55. Primary Assumptions for Natural Gas Pipelines from Alaska and MacKenzie Delta into Alberta, 

Canada

Note: The potential for capital cost overruns is represented by using an initial capitalization that is 20 percent greater than the

expected estimate. The minimum wellhead price for Alaska accounts for Alaska's 2007 Oil and Gas Production Tax.

Source: Energy Information Administration, Office of Integrated Analysis and Forecasting. Alaska pipeline data are partially

based on information from British Petroleum/ExxonMobil/Conoco Phillips and reflect an assumed impact on Alaska pipeline

finances as a result of the American Jobs Creation Act of 2004 and the Military Construction Appropriations Act, 2004. 

National Energy Board of Canada, “Mackenzie Gas Project – Hearing Order GH-1-2004, Supplemental Information – Project

Update 2007,” dated May 15, 2007;

National Energy Board of Canada, “Mackenzie Gas Project – Project Cost Estimate and Schedule Update,” dated March 12,

2007;

Canada Revenue Agency, “T2 Corporation Income Tax Guide 2006,” T4012(E) Rev. 07.

Indian and Northern Affairs Canada, “Oil and Gas in Canada’s North,” website address

http://www.ainc-inac.gc.ca/ps/ecd/env/nor_e.html.

National Energy Board of Canada, “Application for Approval of the Development Plan for Taglu Field - Project Description,”

submitted by Imperial Oil Resources Ltd., TDPA-P1, August 2004;

National Energy Board of Canada, “Application for Approval of the Development Plan for Niglintgak Field - Project Description,”

submitted by Shell Canada Ltd., NDPA-P1, August 2004; and

National Energy Board of Canada, “Application for Approval of the Development Plan for Parsons Lake Field - Project

Description,” submitted by ConocoPhillips Canada (North) Ltd., PLDPA-P1, August 2004.

Consumption Production

2007 - 2010 7.0 3.0

2011- 2015 3.5 2.1

2016 - 2020 2.2 3.7

2021 - 2025 1.9 1.6

2026 - 2030 2.2 2.9

Table 56. Assumed Annual Growth Rates for Mexico (percent)

Source: EIA, International Energy Outlook 2007, DOE/EIA-0484(2007) and Energy Information Administration, Office of

Integrated Analysis and Forecasting. 
Mexico market. Receiving terminal(s) in Baja California, Mexico, that serve both Mexico and the United

States can be constructed if the market price at the tailgate exceeds a trigger price, based on the cost of

bringing LNG to the region and the market price of LNG. The difference between production and

consumption in any year is assumed to be either imported from, or exported to, the United States.

Canadian consumption and production in Eastern Canada are set exogenously in the model and are shown

in Table 58. Production in the Western Canadian Sedimentary Basin (WCSB) is calculated endogenously to

the model using annual supply curves based on beginning-of-year proved reserves and an expected

production-to-reserve ratio. Reserve additions are set equal to the product of successful natural gas wells

(based on an econometric estimation) and a finding rate (set as a function of the remaining economically

recoverable resource base). The initial coalbed methane and conventional WCSB economically

recoverable resource base estimates assumed in the model for the beginning of 2004 are 70 trillion cubic

feet and 92 trillion cubic feet, respectively.1 Potential production from tight formations was approximated by

increasing the conventional resource level by 1.5 percent annually. Production from coalbed sources is

established based on an assumed production path which varies in response to the level of remaining

resources and the solution price in the previous projection year. To temporarily approximate the impact of

the 2007 average increase in the Alberta royalty rate, starting in 2009, the price drivers on western Canada

supply in the model were assumed to be 5 percent less than they would have been otherwise.

Annual U.S. exports of liquefied natural gas (LNG) to Japan are assumed to phase down from 2006 levels of

61 billion cubic feet per year through March of 2009, when the export license expires, and 0.0 through the

remainder of the projection. LNG imports are determined endogenously within the model. The model

provides for the construction of new facilities should gas prices be high enough to make construction

economic — the prices (including regasification) that are needed to initially trigger new LNG construction in

the United States and the Bahamas vary by region and, at the beginning of the forecast, range from $3.39 to

$5.02/Mcf (2005 dollars).

Currently there are five LNG facilities in operation, located at Everett, Massachusetts; Lake Charles,

Louisiana; Cove Point, Maryland; Elba Island, Georgia; and off the coast of Louisiana (Gulfport Energy

Bridge). These five facilities including expansions currently in progress have a combined design capacity of

2,125 million cubic feet per day (2.1 trillion cubic feet per year). Further expansion is triggered when the

regional LNG tailgate2 price meets or exceeds a trigger price as determined in the model.

The model also has a provision for the construction of new facilities in all United States coastal regions, in

eastern and western Canada and in Mexico. Mexico currently has one terminal at Altameria, in operation as

of 2006. Supplies from a Baja California, Mexico, facility are assumed to enter the United States as pipeline

imports from Mexico destined for Southwestern markets. A 1 Bcf per day facility, currently under

construction, is assumed to come online in 2008 with one-half of its supplies available to the United States. 

As with expansion of existing facilities, construction of additional facilities is triggered when the regional LNG 

tailgate price meets or exceeds a trigger price. The trigger price for additional Baja California, Mexico, LNG

facilities starts at $5.43/Mcf (2006 dollars). LNG is represented similarly in eastern Canada. A 1 Bcf/day

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 117

Year Consumption Production 

Eastern Canada

2005 3,300 151

2010 4,000 240

2015 4,200 530

2020 4,600 670

2025 4,900 820

2030 5,200 710

Table 57. Exogenously Specified Canadian Production and Consumption

(billion cubic feet per year)

Source: Consumption - EIA, International Energy Outlook 2007, DOE/EIA-0484(2007); Production - Energy Informatiion

Administration, Office of Integrated Analysis and Forecasting.
facility, currently under construction, is assumed to come online in 2008. No assumption regarding the

amount destined for the United States is made. The supply is simply added to the supply in eastern Canada. 

The trigger price for additional capacity in eastern Canada starts at $4.07/Mcf (2006 dollars). The trigger

price for initial construction in western Canada is $5.48/Mcf (2006 dollars). These trigger prices are

increased by a market price adjustment factor representing the difference between the world market price

for LNG and the cost to bring it to the U.S. market. This factor is specified based on the assumed growth in

world natural gas consumption from the International Energy Outlook 2007 and the annual change in the

world oil price.

Since LNG does not compete directly with wellhead prices, trigger prices are compared with regional prices

in the vicinity of the LNG facility (i.e., the tailgate price) rather than with wellhead prices. With the exception of 

the Canada and Baja facilities, the individual trigger prices represent the least cost feasible combination of

production, liquefaction, and transportation costs to the facility plus the regasification cost at the facility, plus

the market price adjustment factor. Regasification costs at new facilities include capital costs for

construction of the facility. A range of cost components used in determining trigger prices at new facilities is

shown in Table 58. Regional risk premiums are determined based on regional specific factors that include

proposal and site identification activity, population density, housing values, income values, and availability of 

deepwater ports.

The production costs reflect assumed market prices entering the liquefaction facility for various stranded

gas3 locations and average about $1.00 Mcf (2006 dollars). Different supply factors are estimated based on

the existing and potential upstream projects for each supply source, and are applied to the average supply

cost to arrive at the production cost by source.4

Liquefaction costs are revised to account for recent escalations of liquefaction plant costs around the world. 

The revised costs are estimated to have increased at least 50 percent over the average liquefaction cost

estimated by EIA in 2006 and are assumed based on a generally declining liquefaction capital cost function

for one train (3.9 million metric tons of LNG or 186 Bcf per year) starting at $500 per ton of plant capacity in

2006. The capital cost is to be amortized over a 20-year period with a 18 percent average cost of equity, 60

percent debt fraction, and 30 percent corporate tax rate. The cost of debt is assumed to equal the AA utility

bond rate. These liquefaction costs are adjusted to account for individual plant factors such as the plant’s

age and location. The liquefaction plant utilization rate is assumed to be 93 percent.

LNG shipment costs from a supply source to a receiving terminal are a function of the distance between

these two locations, an average per unit-mile shipment cost, and a port cost. The per unit-mile shipment cost 

is computed as a function of the return on invested capital for the tanker, number of round trips per year,

distance between a supply source and an LNG terminal, average tanker capacity, estimated fuel cost, and

administrative and general expenses for the tanker serving that route. Taxes are embedded in the

administrative and general expenses.

118 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 

Low High

2005 Production $0.39 Nigeria $1.75 Norway

2005 Liquefaction $2.39 All facilities $2.39 All facilities

Shipping $0.40 Venezuala to the Bahamas $2.21 Qatar to Gulf Mexico

Regasification $0.40 Gulf of Mexico $1.11 New England

Risk Premium $0.63 West South Central $2.00 East South Central

Table 58. LNG Cost Components

 (2006 dollars per mcf)

Source: Energy Information Administration, Office of Integrated Analysis and Forecasting. Gas supply costs are 

based on a March 31, 2003 report produced under contract to EIA by the Gas Technology Institute (GTI), using

a conversion factor of 1,100 Btus/cf. Regasification costs are based on Project Technical Liaison, Inc.

estimates. Shipping costs are based on various sources, including www.dataloy.com for transportation

distances, the GTI Report, and EIA judgement. Liquefaction costs are based on data from Wood MacKenzie. 

Liquefaction, shipping, and regasification costs are determined endogenously in the NGTDM.
Shipment costs are based on distances, an assumed average per unit capital cost for all the newly built

tankers ($1,247 per cubic-meter capacity in 2006 dollars), an average rate of return on the invested capital,

tanker fuel costs, administrative and general expenses, an assumed average tanker capacity per trip

(159,000 cubic meters), and the assumed number of round trips per year for a tanker serving a particular

route. The estimated shipment costs, in 2006 dollars/Mcf, were divided by the route distances to arrive at

initial transportation costs. On average these calculations provide a result of $0.00022/Mcf-mile in 2006

dollars (i.e., roughly $0.22/Mcf per 1,000 nautical miles, based on a one-way trip). Finally, an assumed

$0.05/Mcf port cost is added to each of these transportation costs to arrive at the final shipment costs.

Regasification costs include a fixed and variable component. Variable costs include administrative and

general expenses, operating and maintenance expenses, taxes and insurance, electric power costs, and

fuel usage and loss. The fixed costs reflect the expected annual return on capital and are based on the

assumed capital cost, a 60 percent debt fraction, the cost of debt and equity, a 38 percent corporate tax rate,

and a 20-year economic life. The capital costs are based on the cost of storage tanks, vaporizer units,

marine facilities, site improvements and roads, buildings and services, installation, engineering and project

management, land, contingency, and the capacity of the plant. The cost of debt is tied to the AA utility bond

rate and the cost of equity is tied to the 10-year treasury note yield plus a 10-percent risk premium. A per-unit 

regasification charge for a given size facility is obtained by dividing total costs by an assumed annual

throughput. Regional specific factors are applied to account for differences in costs associated with land

purchase, labor, site specific permitting, special land and waterway preparation and/or acquisition, and other 

general construction and operating cost differences.

It is assumed that LNG facilities are developed with an initial design capacity along with a capability for future 

expansion. For existing terminals, original capital expenditures are considered sunk costs. Costs were

additionally determined for expansion beyond currently announced expansion plans at all existing facilities,

with the exception of Everett (where room for expansion is limited), under the assumption that if prices

reached sustained levels at which new facilities would be constructed, additional expansion at existing

facilities would likely be considered. The costs of expansion at existing facilities within a region are in

general lower that those for the construction of new facilities. If market prices warrant, additional capacity

can be added in a region either through expansion or construction of new facilities.

Legislation and Regulations

The methodology for setting reservation fees for transportation services is initially based on a regulated rate

calculation, but is ultimately consistent with FERC’s alternative ratemaking and capacity release position in

that it allows some flexibility in the rates pipelines ultimately charge. The methodology is market-based in

that rates for transportation services will respond positively to increased demand for services while rates will

decline (reflecting discounts to retain customers) should the demand for services decline. 

A number of legislative actions have been taken to provide a more favorable environment for the introduction 

of new liquefied natural gas (LNG) regasification facilities in the United States. In December 2002 under the

Hackberry Decision, FERC terminated open access requirements for new onshore LNG terminals, placing

them on an equal footing with offshore terminals regulated under provisions of the Maritime Security Act of

2002. The Maritime Security Act, signed into law in November 2002, also amended the Deepwater Port Act

of 1974 to include offshore natural gas facilities, transferring jurisdiction for these facilities from the FERC to

the Maritime Administration and the U.S. Coast Guard. The result should be to streamline the permitting

process and relax regulator requirements. More recently an EPACT2005 provision clarified the role of the

FERC as the final decision making body on issues concerning onshore LNG facilities. While none of these

legislative/regulatory actions is explicitly represented in the modeling framework, these provisions are

indirectly reflected in selected model parameters.

Section 116 of the Military Construction Appropriations and Emergency Hurricane Supplemental

Appropriations Act, 2004 (H.R.4837) gives the Secretary of Energy the authority to issue Federal loan

guarantees for an Alaska natural gas transportation project, including the Canadian portion, that would carry

natural gas from northern Alaska, through the Canadian border south of 68 degrees north latitude, into

Canada, and to the lower-48 States. This authority would expire 2 years after the final certificate of public

convenience and necessity is issued. In aggregate the loan guarantee would not exceed: (1) 80 percent of

total capital costs (including interest during construction); (2) $18 billion dollars (indexed for inflation at the

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 119
time of enactment); or (3) a term of 30 years. The Act also promotes streamlined permitting and

environmental review, an expedited court review process, and protection of rights-of-way for the pipeline.

The loan guarantee is represented in the model by assuming the cost of debt at a percentage point lower

than what would have been assumed otherwise and by assuming a debt fraction of 80 percent, instead of 70

percent.

Section 706 of the American Jobs Creation Act of 2004 (H.R.4520) provided a 7-year cost-of-investment

recovery period for the Alaska natural gas pipeline, as opposed to the previously allowed 15-year recovery

period, for tax purposes. The provision is effective for property placed in service after 2013 (or treated as

such) and is represented in the model by using a cost of equity that is 3 percentage points lower than would

have been assumed otherwise. 

Section 707 of the American Jobs Creation Act extended the 15-percent tax credit previously applied to

costs related to enhanced oil recovery to construction costs for a gas treatment plant that supplies natural

gas to a 2 trillion Btu per day pipeline, lies in Northern Alaska, and produces carbon dioxide for injection into

hydrocarbon-bearing geological formations. A gas treatment plan on the North Slope that feeds gas into an

Alaska pipeline to Canada is expected to satisfy this requirement. The provision is effective for costs

incurred after 2004 and is represented in the model by assuming a charge for natural gas treatment that is

$0.05 per Mcf less than what would have been assumed otherwise.

Section 1113 of the Safe, Accountable, Flexible, Efficient Transportation Equity Act: A Legacy for Users

(SAFETEA-LU) raised the federal motor fuels tax for compressed natural gas vehicles (CNG) from 48.54

cents per Mcf to 18.3 cents per gasoline gallon equivalent (or about $1.46 per Mcf), all in nominal dollars. 

The same section also allows for a motor fuels excise tax credit of $0.50 per gasoline gallon equivalent to the 

seller through September 30, 2009. For AEO2007, the tax rate was changed accordingly and assumed

constant in nominal terms throughout the projection. Similarly the tax credit was subtracted from the CNG

cost estimates through the time period indicated, also in nominal terms.

Section 312 of the Energy Policy Act of 2005 authorizes the Federal Energy Regulatory Commission (FERC) 

to allow natural gas storage facilities to charge market-based rates if it was believed that they would not exert 

market power. In the AEO2007 storage rates were allowed to vary from regulation-based rates, depending

on market conditions.

Natural Gas Transmission and Distribution Alternative Cases

High and Low Liquefied Natural Gas Import Cases

Two cases were created to assess the impact of a range of liquefied natural gas (LNG) imports on the

domestic natural gas market. The future level of LNG imports into the United States is highly uncertain. The

levels will depend on such things as the ability and motivation of companies to site regasification facilities

domestically, the ability and motivation of companies to site liquefaction facilities throughout the world, the

world market for natural gas shipped via pipeline and in liquid form, the relative need for consuming the

available natural gas in other parts of the world, the potential other uses for the gas (e.g., its conversion into

liquid fuel), and finally the price of LNG on the world market, which in turn is impacted by the cost of

producing, liquefying, shipping, and regasifying the gas. These cases are intended to highlight the impact if

LNG imports were actually much different than under the reference case, for whatever reason. For the high

liquefied natural gas import case, starting in 2011, LNG imports are increased above the reference case

levels by 10 percent per year. Specifically, LNG imports are 10 percent above 2011 reference case levels in

2011, 20 percent above 2012 reference case levels in 2012, and 200 percent above 2030 reference case

levels in 2030. For the low liquefied natural gas case, LNG import levels are held constant at 2009 reference

case levels from 2010 forward.

120 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 
[1] For unconventional (i.e., coalbed) -- Average undiscovered resources under the National Energy Board's

Supply Push and Techno-vert scenarios in "Canada's Energy Future, Scenarios for Supply and Demand to

2025," 2003. For conventional -- "Canada's Conventional Natural Gas Resources -- A Status Report," April

2004.

[2] Tailgate LNG prices represents the price when natural gas exists the regasification facility.

[3] Gas reserves that have been located but are isolated from potential markets, commonly referred to as

“stranded” gas, are likely to provide most of the natural gas for LNG in the future. Reserves that can be

linked to sources of demand via pipeline are unlikely candidates to be developed for LNG.

[4] Largely based on information from Gas Technology Institute, “Liquefied Natural Gas (LNG) Methodology

Enhancements in NEMS,” Report submitted to Energy Information Administration, March 31, 2003.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 121

Notes and Sources

Petroleum Market Module

The NEMS Petroleum Market Module (PMM) projects petroleum product prices and sources of supply for

meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), 

petroleum product imports, unfinished oil imports, other refinery inputs (including alcohols, ethers, bioesters, 

corn, biomass, and coal), natural gas plant liquids production, and refinery processing gain. In addition, the

PMM projects capacity expansion and fuel consumption at domestic refineries.

The PMM contains a linear programming (LP) representation of U.S. refining activities in the five Petroleum

Area Defense Districts (PADDs) (Figure 9). The LP model is created by aggregating individual refineries

within a PADD into two types of representative refineries, and linking all five PADD's via crude and product

transit links. This representation provides the marginal costs of production for a number of conventional and

new petroleum products. In order to interact with other NEMS modules with different regional

representations, certain PMM inputs and outputs are converted from PADD regions to other regional

structures and vice versa. The linear programming results are used to determine end-use product prices for

each Census Division (shown in Figure 5) using the assumptions and methods described below.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 123

AK

WA

NV

AZ

OR

CA

HI

V

MT

WY

ID

UT

CO

IV

OK

IA

KS

MO

IL

IN

KY

TN

WI

MI

OH

NE

SD

ND MN

II

NM

TX

MS

AL AR

LA III

NJ

CT

VT ME

RI

MA

NH

FL

GA

SC

NC

WV

MD

DE VA

NY

PA I

Figure 9. Petroleum Administration for Defense Districts

Source:Energy Information Administration,Office of Integrated Analysis and Forecasting.

Report #:DOE/EIA-0554(2008)

Release date: June 2008

Next release date: March 2009
Key Assumptions

Product Types and Specifications

The PMM models refinery production of the products shown in Table 59.

The costs of producing different formulations of gasoline and diesel fuel that are required by State and

Federal regulations are determined within the linear programming representation by incorporating

specifications and demands for these fuels. The PMM assumes that the specifications for these fuels will

remain the same as currently specified, with a few exceptions: the sulfur content, which will be phased down

to reflect EPA regulations for all gasoline and diesel fuels; and, benzene will be reduced in gasoline

beginning in 2011.

Motor Gasoline Specifications and Market Shares

The PMM models the production and distribution of three different types of gasoline: conventional,

oxygenated, and reformulated (Phase 2). The following specifications are included in the PMM to

differentiate between conventional and reformulated gasoline blends (Table 60): Reid vapor pressure (Rvp), 

benzene content, aromatic content, sulfur content, olefins content, and the percent evaporated at 200 and

300 degrees Fahrenheit (E200 and E300). The sulfur content specification for gasoline is reduced annually

through 2007 to reflect recent regulations requiring the average annual sulfur content of all gasoline used in

the United States to be phased-down to 30 parts per million (ppm) between 2004 and 2007.1 PMM assumes

that RFG has an average annual sulfur content of 135 ppm in 2000 and meets the 30 ppm requirement in

2004. Regional assumptions for phasing-down the sulfur in conventional gasoline account for less stringent

sulfur requirements for small refineries and refineries in the Rocky Mountain region. The 30 ppm annual

average standard is not fully realized in conventional gasoline until 2008 due to allowances for small

refineries. The sulfur specifications assumed for each region and type of gasoline are provided in Table 61.

Conventional gasoline must comply with antidumping requirements aimed at preventing the quality of

conventional gasoline from eroding as the reformulated gasoline program is implemented. Conventional

gasoline must meet the Complex Model II compliance standards which cannot exceed average 1990 levels

of toxic and nitrogen oxide emissions.2

Oxygenated gasoline is assumed to have specifications identical to conventional gasoline, with the

exception of a higher oxygen requirement, specifically 2.7 percent oxygen by weight. Some areas that

require oxygenated gasoline will also require reformulated gasoline. For the sake of simplicity, the areas of

overlap are assumed to require gasoline meeting the reformulated specifications.

Cellulosic biomass feedstock supplies and costs are taken from the NEMS Renewable Fuels Model. Initial

capital costs for biomass cellulosic ethanol were obtained from a research project reviewing cost estimates

from multiple sources.3 Operating costs and credits for excess electricity generated at biomass ethanol

plants were obtained from a National Renewable Energy Laboratory report4 and the USDA Agricultural

Baseline Projections to 2015.5

124 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Product Category Specific Products

 Motor Gasoline Conventional Unleaded, Oxygenated, Reformulated

 Jet Fuel Kerosene-type

 Distillates Kerosene, Heating Oil, Low-Sulfur-Diesel, Ultra-Low-Sulfur-Diesel

 Residual Fuels Low Sulfur, High Sulfur

 Liquefied Petroleum Gases Propane, Liquefied Petroleum Gases Mixed

 Petrochemical Feedstocks Petrochemical Naptha, Petrochemical Gas Oil, Propylene, Aromatics

 Others Lubricating Products and Waxes, Asphalt/Road Oil, Still Gas

Petroleum Coke, Special Naphthas, Aviation Gasoline

Table 59. Petroleum Product Categories

Source: Energy Information Administration, Office of Integrated Analysis and Forecasting.
Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 125

PADD

Reid 

Vapor

 Pressure

(Max PSI)

Aromatics

Volume 

Percent 

(Max)

Benzene

Volume

 Percent

 (Max)

2007

Sulfur

PPM

 (Max)

Olefin

Volume

Percent

(Max)

Percent

 Evaporated

 at

200o

Percent

 Evaluated

at

300o

Conventional

 PADD I 9.6 26.0 1.1 41.7 11.6 47.1 82.0

 PADD II 10.2 26.1 1.1 32.2 11.6 47.1 81.9

 PADD III 9.9 26.1 1.1 32.4 11.6 47.1 81.9

 PADD IV 10.8 26.1 1.1 44.2 11.6 47.1 81.9

 PADD V 9.2 26.7 1.1 33.7 11.7 45.7 81.4

Reformulated

 PADD I 8.5 20.7 0.6 30.0 11.9 50.2 84.6

 PADD II 9.5 18.5 0.8 30.0 7.1 50.8 85.2

 PADD III 8.6 19.8 0.6 30.0 11.2 51.6 83.9

 PADD IV 8.6 19.8 0.6 30.0 11.2 51.6 83.9

 PADD V

 Nonattainment 7.9 22.0 0.70 20.0 6.0 49.0 90.0

 CARB (attainment) 7.9 22.0 0.70 20.0 6.0 49.0 90.0

Table 60. Year Round Gasoline Specifications by Petroleum Administration for Defense Districts

(PADD)

Max = Maximum.

PADD = Petroleum Administration for Defense District.

PPM = Parts per Million by Weight.

PSI = Pounds per Square Inch.

Source: Energy Information Administration, Office of Integrated Analysis and Forecasting. Derived using U.S. EPA’s

Complex Model, and updated with U.S. EPA's 2005 gasoline projection survey

(http://www.epa.gov/otaq/regs/fuels/rfg/properf/rfgperf.htm).

2004 2005 2006 2007 2008-2030

Conventional

 PADD I 143.4 90.0 43.4 41.7 30

PADD II 111.6 60.0 32.2 32.2 30

 PADD III 114.5 60.0 32.4 32.4 30

 PADD IV 140.0 90.0 44.2 44.2 30

PADD V 122.8 70.0 33.7 33.7 30

Reformulated

PADD I-IV 30 30 30 30 30

PADD V 20 20 20 20 20

Table 61. Gasoline Sulfur Content Assumptions, by Region and Gasoline Type, Parts per Million (PPM)

Source: Energy Information Administration, Office of Integrated Analysis and Forecasting. Derived from Form EI-810

“Monthly Refinery Report” and U.S. Environmental Protection Agency, “Tier 2” Motor Vehicle Emissions Standards and

Gasoline Sulfur Control requirements, February 2000, (Washington, DC).
Corn supply prices are estimated from the USDA baseline projections to 2017.6 The capital cost of a

50-million-gallon-per-year corn ethanol plant was assumed to be $69 million (2006 $). Operating costs of

corn ethanol plants are obtained from USDA survey of ethanol plant costs7. Energy requirements are

obtained from a study of carbon dioxide emissions associated with ethanol production.8

Reformulated gasoline has been required in many areas in the United States since January 1995. In 1998,

the EPA began certifying reformulated gasoline using the “Complex Model,” which allows refiners to specify

reformulated gasoline based on emissions reductions from their companies' respective 1990 baselines or

the EPA’s 1990 baseline. The PMM reflects “Phase 2” reformulated gasoline requirements which began in

2000. The PMM uses a set of specifications that meet the “complex Model” requirements, but it does not

attempt to determine the optimal specifications that meet the “Complex Model.” (Table 62).

AEO2008 assumes MTBE will be phased out by the end of 2006 as a result of decisions made by the

petroleum industry to discontinue MTBE blending with gasoline. Ethanol is assumed to be used in areas

where reformulated or oxygenated gasoline is required. Federal reformulated gasoline (RFG) is blended

with 10% ethanol; oxygenated gasoline is blended with 10% ethanol; and California Air Resources Board

(CARB) RFG is blended with 5.77% ethanol. Ethanol is also allowed to blend into conventional gasoline at

up to 10 percent by volume, depending on its blending value and relative cost competitiveness with other

gasoline blending components. EISA2007 defines a requirements schedule for having renewable fuels

blended into transportation fuels by 2022. 

Reid Vapor Pressure (RVP) limitations are effective during summer months, which are defined differently by

consuming regions. In addition, different RVP specifications apply within each refining region, or PADD.

The PMM assumes that these variations in RVP are captured in the annual average specifications, which

are based on summertime RVP limits, wintertime estimates, and seasonal weights.

Within the PMM, total gasoline demand is disaggregated into demand for conventional, oxygenated, and

reformulated gasoline by applying assumptions about the annual market shares for each type. The shares

are allowed to change over time based on assumptions regarding the market penetration of new fuels. In

AEO2008, however, the annual market shares for each region reflect actual 2006 market shares and are

held constant throughout the projection. (See Table 63 for AEO2008 market share assumptions.)

Diesel Fuel Specifications and Market Shares

In order to account for diesel desulphurization regulations related to Clean Air Act Amendment of 1990

(CAAA90), low-sulfur diesel is differentiated from other distillates. In NEMS, Census Division 9 is required to 

meet CARB standards. Both Federal and CARB standards currently limit sulfur to 15 ppm.

AEO2008 incorporates the “ultra-low-sulfur diesel” (ULSD) regulation finalized in December 2000. ULSD is

highway diesel that contains no more than 15 ppm sulfur at the pump. The ULSD regulation includes a

phase-in period under the “80/20” rule, that requires the production of a minimum 80 percent ULSD for

highway use between June 2006 and June 2010, and a 100 percent requirement for ULSD thereafter. As

NEMS produces annual average results, only a portion of the production of highway diesel in 2006 is subject

to the 80/20 rule and the 100 percent requirement does not cover all highway diesel until 2011.

126 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Gasoline

Type/Year

New England Middle

 Atlantic

East

 North 

Central

West

 North 

Central

South 

Atlantic

East 

South 

Central

West 

South 

Central

Mountain Pacific

Conventional Gasoline 20 43 79 66 82 95 73 70 32

Oxygenated Gasoline

 (2.7% oxygen) 0 0 0 26 0 0 1 14 2

Reformulated Gasoline 80 57 21 8 17 5 27 15 76*

Table 62. Market Share for Gasoline Types by Census Division

*Note: 61 percent is assumed to comply with the Federal RFG requirement, 15 percent is the result of State requirements.

Source: Energy Information Administration, Office of Integrated Analysis and Forecasting. Derived from EIA-782C, “Monthly

Report of Prime Supplier Sales of Petroleum Products Sold for Local Consumption,” January-December 2006.
NEMS models ULSD as containing 7.5 ppm sulfur at the refinery gate in 2006, phasing down to 7ppm sulfur

by 2011. This lower sulfur limit at the refinery reflects the general consensus that refiners will need to

produce diesel with a sulfur content below 10 ppm to allow for contamination during the distribution process.

It is assumed that revamping (retrofitting) existing refinery units to produce ULSD will be undertaken by

refineries representing two-thirds of highway diesel production and that the remaining refineries will build

new units. The capital cost of revamping is assumed to be 50 percent of the cost of adding a new unit.

The amount of ULSD downgraded to a lower value product because of sulfur contamination in the

distribution system is assumed to be 7.8 percent at the start of the program, declining to 2.2 percent at full

implementation. The decline reflects the expectation that the distribution system will become more efficient

at handling ULSD with experience.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 127

Sector/Product

Census Division

New 

England

Middle

Atlantic

East 

North

Central

West

 North

Central

South

Atlantic

East 

South 

Central

West

 South

 Central Mountain Pacific

Residential Sector

 Distillate Fuel Oil 0.40 0.46 0.31 0.24 0.45 0.41 0.27 0.22 0.31

 Kerosene 0.1 0.30 0.10 0.15 0.07 0.07 0.05 0.21 0.14

 Liquefied Petroleum Gases 0.91 0.92 0.55 0.35 0.87 0.76 0.81 0.65 0.85

Commercial Sector

 Distillate Fuel Oil 0.14 0.14 0.06 0.03 0.07 0.04 0.07 0.00 0.10

 Gasoline 0.10 0.15 0.14 0.1 0.08 0.12 0.12 0.14 0.15

 Kerosene 0.1 0.27 0.09 0.15 0.09 0.07 0.00 0.20 0.13

 Liquefied Petroleum Gases 0.47 0.57 0.41 0.41 0.50 0.48 0.52 0.51 0.46

 Low-Sulfur Residual Fuel Oil 0.32 0.00 0.59 0.4 0.03 0.72 0.10 0.00 0.79

Utility Sector

 Distillate Fuel Oil -0.23 0.06 -0.10 -0.09 0.00 -0.02 -0.15 0.01 -0.06

 High-Sulfur Residual Fuel Oil1-0.07 -0.10 0.00 -0.10 0.00 -0.06 0.00 0.00 0.01

 Low-Sulfur Residual Fuel Oil1-0.07 -0.10 0.00 -0.10 0.00 -0.06 0.00 0.00 0.01

Transportation Sector

 Distillate Fuel Oil 0.26 0.20 0.16 0.12 0.15 0.16 0.15 0.13 0.22

 E8520.13 0.17 0.14 0.14 0.11 0.12 0.09 0.14 0.15

 Gasoline 0.13 0.17 0.14 0.14 0.1 0.12 0.09 0.14 0.15

 High-Sulfur Residual Fuel Oil1-0.01 -0.03 0.15 0.1 0.00 0.23 0.19 0.00 0.29

 Jet Fuel 0.03 0.00 -0.01 -0.01 0.07 0.00 -0.03 0.00 0.02

 Liquefied Petroleum Gases 0.46 0.48 0.66 0.66 0.53 0.65 0.65 0.60 0.59

Industrial Sector

 Asphalt and Road Oil 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

 Distillate Fuel Oil 0.14 0.11 0.20 0.15 0.12 0.13 0.14 0.03 0.14

 Gasoline 0.13 0.16 0.14 0.13 0.11 0.13 0.10 0.14 0.16

 Kerosene -0.01 0.01 0.01 -0.01 0.00 0.05 0.20 0.07 0.00

 Liquefied Petroleum Gases 0.46 0.34 0.34 0.34 0.41 0.30 0.10 0.48 0.51

 Low-Sulfur Residual Fuel Oil 0.11 0.00 0.20 0.09 0.06 0.21 0.21 -0.19 0.10 

Table 63. Petroleum Product End-Use Markups by Sector and Census Division

(2005 dollars per gallon)

1Negative values indicate that average end-use sales prices were less than wholesale prices. This often occurs with residual fuel

which is produced as a byproduct when crude oil is refined to make higher value products like gasoline and heating oil.

2

74 percent ethanol and 26 percent gasoline.

Sources: Markups based on data from Energy Information Administration (EIA), Form EIA-782A, Refiners’/Gas Plant Operators’

Monthly Petroleum Product Sales Report; EIA, Form EIA-782B, Resellers’/Retailers’ Monthly Petroleum Report Product Sales

Report; EIA, Form FERC-423, Monthly Report of Cost and Quality of Fuels for Electric Plants; EIA, Form EIA-759 Monthly Power

Plant Report; EIA, State Energy Data Report 2006, Consumption (October 2007); EIA, State Energy Data 2006: Prices and

Expenditures (October 2007).
A revenue loss is assumed to occur when a portion of ULSD that is put into the distribution system is

contaminated and must be sold as a lower value product. The amount of the revenue loss is estimated

offline based on earlier NEMS results and is included in the AEO2008 ULSD price projections as a

distribution cost. The revenue loss associated with the 7.8 percent downgrade assumption for 2008 is 0.7

cents per gallon. The revenue loss estimate declines to 0.2 cents per gallon after 2010 to reflect the

assumed decline to 2.2 percent.

The capital and operating costs associated with ULSD distribution are based on assumptions used by the

EPA in the Regulatory Impact Analysis (RIA) of the rule.9 Capital costs of 0.7 cents per gallon are assumed

for additional storage tanks needed to handle ULSD during the transition period. These capital expenditures 

are assumed to be fully amortized by 2011. Additional operating costs for distribution of highway diesel of

0.2 cents per gallon are assumed over the entire projection period. Another 0.2 cent cost per gallon is

assumed for lubricity additives. Lubricity additives are needed to compensate for the reduction of aromatics

and high-molecular-weight hydrocarbons stripped away by the severe hydrotreating used in the

desulphurization process.

Demand for highway-grade diesel, both 500 ppm and ULSD combined, is assumed to be equivalent to the

total transportation distillate demand. Historically, highway-grade diesel supplies have nearly matched total

transportation distillate sales, although some highway-grade diesel has gone to nontransportation uses

such as construction and agriculture.

The energy content of ULSD is assumed to decline from that of 500 ppm diesel by 0.5 percent because

undercutting and severe desulphurization will result in a lighter stream composition than that for 500 ppm

diesel.

AEO2008 incorporates the “nonroad, locomotive, and marine” (NRLM) diesel regulation finalized in May

2004. The PMM model has been revised to reflect the nonroad rule and re-calibrated for market shares of

highway, NRLM diesel, and other distillate (mostly heating oil, but excluding jet fuel and kerosene). The

NRLM diesel rule follows the highway diesel rule closely and represents an incremental tightening of the

entire diesel pool. The demand for high sulfur distillate is expected to diminish over time, while the demand

for ULSD (both highway and NRLM) is expected to increase over time.

The final NRLM rule is implemented in multiple steps and requires sulfur content for all NRLM diesel fuel

produced by refiners to be reduced to 500 ppm starting mid-2007. It also establishes a new ultra-low-sulfur

diesel (ULSD) limit of 15 ppm for nonroad diesel by mid-2010. For locomotive and marine diesel, the rule

establishes an ULSD limit of 15 ppm in mid-2012.

End-Use Product Prices

End-use petroleum product prices are based on marginal costs of production plus production-related fixed

costs plus distribution costs and taxes. The marginal costs of production are determined within the LP and

represent variable costs of production, including additional costs for meeting reformulated fuels provisions of 

the CAAA90. Environmental costs associated with controlling pollution at refineries are implicitly assumed

in the annual update of the refinery investment costs for the processing units.

The costs of distributing and marketing petroleum products are represented by adding product-specific

distribution costs to the marginal refinery production costs (product wholesale prices). The distribution costs 

are derived from a set of base distribution markups (Table 64).

128 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008
State and Federal taxes are also added to transportation fuels to determine final end-use prices (Tables 65

and 66). Recent tax trend analysis indicates that State taxes increase at the rate of inflation, therefore, State

taxes are held constant in real terms throughout the projection. This assumption is extended to local taxes

which are assumed to average 2 cents per gallon.10 Federal taxes are assumed to remain at current levels in 

accordance with the overall AEO2008 assumption of current laws and regulations. Federal taxes are

deflated as follows:

Federal Tax product, year = Current Federal Tax product / GDP Deflator year

Crude Oil Quality

In the PMM, the quality of crude oil is characterized by average gravity and sulfur levels. Both domestic and

imported crude oil are divided into five categories as defined by the ranges of gravity and sulfur shown in

Table 66.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 129

Year/Product

Census Division

New

England

Middle

 Atlantic

East

 North

 Central

West

 North 

Central

South

 Atlantic

East

 South 

Central

West

 South 

Central

Mountain Pacific

 Gasoline10.23 0.24 0.22 0.20 0.18 0.19 0.20 0.21 0.21

 Diesel 0.24 0.28 0.23 0.21 0.20 0.18 0.19 0.23 0.21

 Liquefied Petroleum Gases 0.12 0.12 0.17 0.19 0.18 0.17 0.13 0.14 0.06

 E8520.23 0.24 0.23 0.20 0.18 0.19 0.20 0.21 0.21

 Jet Fuel 0.05 0.05 0.00 0.04 0.05 0.05 0.02 0.04 0.03

Table 64. State and Local Taxes on Petroleum Transportation Fuels by Census Division

(2005 dollars per gallon)

1

Tax also applies to gasoline consumed in the commercial and industrial sectors.

2 74 percent ethanol and 26 percent gasoline.

Source: "Compilation of United States Fuel Taxes, Inspection, Fees and Environmental Taxes and Fees," Defense energy

support Center, Editions 2006-12, August 17, 2006. Gasoline, diesel and E85 aggregated from Petroleum Marketing Monthly

DE/EIA-0380(2005/09), Table EN1, (Washington, DC, September 2005). LPG aggregated from Federal Highway

Administration, Tax Rates on Motor Fuel, Jet fuel from EIA, Office of Oil and Gas.

Product Tax

Gasoline 0.18

Diesel 0.24

Jet Fuel 0.04

Liquefied Petroleum Gases30.43

M8510.09

E8520.19

Table 65. Federal Taxes

(Nominal dollars per gallon)

1

85 percent methanol and 15 percent gasoline.

2

74 percent ethanol and 26 percent gasoline.

3

2010 data-based on EPACT05: excise tax is 4.3 cents/gal after 9-30-2011 and 18.3 cents/gal prior to that. A credit of 50

cents/gal is also applied between 10-1-06 and 9-30-09.

Sources: Omnibus Budget Reconciliation Act of 1993 (H.R. 2264); Tax Payer Relief Act of 1997 (PL 105-34), Clean Fuels

Report (Washington, DC, April 1998) and Energy Policy Act of 2005 (PL 109-58).
A “composite” crude oil with the appropriate yields and qualities is developed for each category by averaging

the characteristics of specific crude oil streams in the category. While the domestic and foreign categories

are the same, the composite crudes for each category may differ because different crude streams make up

the composites. For domestic crude oil, estimates of total regional production are made first, then shared out 

to each of the five categories based on historical data. For imported crude oil, a separate supply curve is

provided for each of the five categories. 

Capacity Expansion 

PMM allows for capacity expansion of all processing units including distillation, vacuum distillation,

hydrotreating, coking, fluid catalytic cracking, hydrocracking, and alkylation manufacturing. Capacity

expansion occurs by processing unit, starting from base year capacities established by PADD using

historical data.

Expansion occurs in NEMS when the value received from the additional product sales exceeds the

investment and operating costs of the new unit. The investment costs assume a financing ratio of 60 percent 

equity and 40 percent debt, with a hurdle rate and an after-tax return on investment of about 9 percent.

Capacity expansion plans are determined every 3 years. For example, the PMM looks ahead in 2008 and

determines the optimal capacities given the estimated demands and prices expected in the 2011 projection

year. The PMM then allows any of that capacity to be built in each of the projection years 2009, 2010, and

2011. At the end of 2011 the cycle begins anew, looking ahead to 2014. ACU capacity under construction

that is expected to begin operating during by 2010. is added to existing capacities in their respective start

year. Capacity expansion is also modeled for corn and cellulosic ethanol, coal-to-liquids, and

biomass-to-liquids production. 

Biofuels Supply 

The PMM provides supply functions on an annual basis through 2030 for ethanol produced from both corn

and cellulosic biomass to produce transportation fuel. It also assumes that small amounts of vegetable oil

and animal fats are processed into biodiesel, a blend of methyl esters suitable for fueling diesel engines.

• Corn feedstock supplies and costs are provided exogenously to NEMS. Feedstock costs reflect

credits for co-products (livestock feed, corn oil, etc.). Feedstock supplies and costs reflect the

competition between corn and its co-products and alternative crops, such as soybeans and their

co-products.

• Cellulosic (biomass) feedstock supply and costs are provided by the Renewable Fuels Module in

NEMS. Cellulosic ethanol production and biomass-to-liquids (BTL) production compete for this

feedstock.

• The Federal motor fuels excise tax credit for ethanol is 51 cents per gallon of ethanol (5.1 cents per

gallon credit to gasohol at a 10-percent volumetric blending portion) is applied within the model. The

tax credit is held constant in nominal terms, decreasing with inflation throughout the projection. It is

assumed that the credit expires after 2010.

130 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Crude Oil Categories Sulfur

(percent)

Gravity

(degrees API)

Low Sulfur Light 0 - 0.5 25 - 60

Medium Sulfur Heavy 0.35 - 1.1 26 - 40

High Sulfur Light > 1.1 >32

High Sulfur Heavy > 1.1 24 - 33

High Sulfur Very Heavy > 0.9 < 23

Table 66. Crude Oil Specifications

Source: Energy Information Administration, Office of Integrated Analysis and Forecasting. Derived from EI-810, “Monthly

Refinery Report” data.
To model the new Renewable Fuels Standard in EISA07, several assumptions were required. In addition to

using the text of the Bill it was also assumed that rules promulgated under the RFS in EPACT05 would

govern the administration of the EISA07 RFS.

• The penetration of cellulosic ethanol into the market is limited before 2012 to the projects

cosponsored by DOE grants currently scheduled to produce approximately 150 million gallons per

year.

• Biomass-to-Liquid (Fischer-Tropsch) diesel fuel production contributes 1.5 credits towards the

cellulosic mandate.

• Imported cane ethanol counts toward the advanced renewables mandate. In addition, a limited

supply of cellulosic ethanol would be available for import and would count toward the cellulosic

mandate.

• The cellulosic biofuel waiver, when activated, reduces the cellulosic, advanced, and total requirement 

by that amount in all future years. In years beyond 2022, the last year specified in the EISA, the RFS

mandate levels are held constant.

• It is assumed that biodiesel and BTL diesel may be consumed in diesel without significant

infrastructure modification (either vehicles or delivery infrastructure).

• Ethanol is assumed to be consumed as either E10 or E85, with no intermediate blends. The cost of

placing E85 pumps at the most economic stations is spread over all transportation fuels. Using this

assumption, the E10 blending market is assumed to be saturated and the E85 market consumes

additional ethanol after 2014.

• To accommodate the ethanol requirements in particular, transportation modes are expanded or

upgraded for both E10 and E85, and it is assumed that most ethanol originates from the Midwest, with 

transportation costs ranging from a low of 1.7 cents per gallon for expanded distribution in the

Midwest, to as high as 2.6 cents per gallon for the Southeast and West Coast.

• For E85 dispensing stations, it is assumed the average cost of a retrofit and new station is about

$45,000 per station, which translates into an incremental cost per gallon ranging from 26 cents in

2013 to 4.4 cents by 2020, depending on the average sales per dispenser.

• The total projected incremental infrastructure cost (transportation, distribution, dispensing) for E85

varies from 27 cents per gallon in 2013 to 6 cents per gallon in 2020.

Interregional transportation is assumed to be by rail, ship, barge, and truck, and the associated costs are

included in PMM. A subsidy is offered by the Department of Agriculture’s Commodity Credit Corporation for

the production of biodiesel. In addition, the American Jobs Creation Act of 2004 provides an additional tax

credit of $1 per gallon of soybean oil for biodiesel and 50 cents per gallon for yellow grease biodiesel until

2006, and EPACT05 extends the credit again to 2008.

Gas-To-Liquids, Coal-To-Liquids, Biomass-To-Liquids, and Gasification

Technologies

Gas-to-liquids (GTL) facilities convert natural gas into distillates, and are assumed to be built if the prices for

lower sulfur distillates reach a high enough level to make it economic. In the PMM, gas-to-liquids facilities are 

assumed to be built only on the North Slope of Alaska, where the distillate product is transported on the

Trans-Alaskan Pipeline System (TAPS) to Valdez and shipped to markets in the lower 48 States. Given

estimates showing that GTL technology is a less profitable means for monetizing the natural gas on the

North Slope relative to an Alaska pipeline to the lower-48 states, the earliest start date for a GTL facility is set

at 2015. Also, the source of feedstock gas to any GTL facility in Alaska is assumed to be from undiscovered,

non-associated resources which will be more costly than the current, largely associated proved reserves on

the North Slope (assumed dedicated to the pipeline). The GTL facilities are built incrementally, with output

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 131
volumes of 50,000 barrels per day, at a cost of $49,100 per barrel of daily capacity (2006 dollars). Operating

costs are assumed to be $4.55 per barrel (2006 dollars). The transportation cost to ship the GTL product

from the North Slope to Valdez along the TAPS is assumed to be the price set to move oil (i.e. the TAPS

revenue recovery rate). This rate is a function of allowable costs, profit, and flow, and can change over the

projection.

It is also assumed that coal-to-liquids (CTL) facil i ties will be built when low-sulfur dis til late prices are high

enough to make them economic. One CTL facil ity is capa ble of pro cess ing 21,800 tons of bitu mi nous coal

per day, with a pro duc tion capac ity of 50,000 bar rels of syn thetic fuels per day and 200 mega watts of

capac ity for elec tric ity cogeneration sold to the grid.11 A CTL facility of this size is assumed to cost over $3.6

billion in initial capital investment (2006 dollars). CTL facil i ties could be built near exist ing refin er ies. For the

East Coast, poten tial CTL facil i ties could be built near the Del a ware River basin; for the Cen tral region, near

the Illi nois River basin or near Bill ings, Montana; and for the West Coast, in the vicin ity of Puget Sound in

Wash ing ton State. The CTL yields are assumed to be sim i lar to those from a GTL facil ity, because both

involve the Fischer-Tropsch pro cess to con vert syngas (CO + H2) to liq uid hydro car bons. The pri mary yields

would be dis til late and ker o sene, with addi tional yields of naphthas and liq ue fied petro leum gases.

Petro leum prod ucts from CTL facil i ties are assumed to be com pet i tive when dis til late prices rise above the

cost of CTL pro duc tion (adjusted for cred its from the sale of cogenerated elec tric ity). It is assumed that CTL

facilities can only be built after 2010.

Gasification of petroleum coke (petcoke) and heavy oil (asphalt, vacuum resid, etc.) is represented in

AEO2008. The PMM assumes petcoke to be the primary feedstock for gasification, which in turn could be

converted to either combined heat and power (CHP) or hydrogen production based on refinery economics. 

A typical gasification facility is assumed to have a capacity of 2,000 ton-per-day (TPD) which includes the

main gasifier and other integrated units in the refinery such as air separation unit (ASU), syngas clean-up,

sulfur recovery unit (SRU), and two downstream process options - CHP or hydrogen production. Currently,

there is more than 5,000 TPD gasification capacity in the Nation, producing CHP and hydrogen. Additional

gasification capacity is projected to be built in the AEO2008 projection, primarily for CHP production.

Combined Heat and Power (CHP) 

Electricity consumption in the refinery is a function of the throughput of each unit. Sources of electricity

consist of refinery power generation, utility purchases, refinery CHP, and merchant CHP. Power generators

and CHP plants are modeled in the PMM linear program as separate units which are allowed to compete

along with purchased electricity. Both the refinery and merchant CHP units provide estimates of capacity,

fuel consumption, and electricity sales to the grid based on historical parameters.

Refinery sales to the grid are estimated using the following percentages which are based on 2005 data:

The PMM sells electricity back to the grid in these percentages at a price equal to the average wholesale

price of electricity in each PMM region.

Merchant CHP plants are defined as non-refiner owned facilities located near refineries to provide energy to

the open market and to the neighboring refinery. These sales occur at a price equal to the average

wholesale price of electricity in each PMM region. Electricity prices are obtained from the Electricity Market

Model.

132 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Region Percent Sold To Grid

PADD I 67.0

PADD II 0.9

PADD III 2.2

PADD IV 0.9

PADDV 45.4

Source: Energy Information Administration, Office of Integrated Analysis and Forecasting. Derived using EIA-860B, “Annual

Electric Generators Report-Nonutility”.
Short-term Methodology

Petroleum balance and price information for 2007 are projected at the U.S. level in the Short-term Energy

Outlook, (STEO). The PMM adopts the STEO results for 2007, using regional estimates derived from the

national STEO projections.

Legislation and Regulations

The Tax Payer Relief Act of 1997 reduced excise taxes on liquefied petroleum gases and methanol

produced from natural gas. The reductions set taxes on these products equal to the Federal gasoline tax on

a Btu basis.

Title II of CAAA90 established regulations for oxygenated and reformulated gasoline and reduced-sulfur

(500 ppm) on-highway diesel fuel. These are explicitly modeled in the PMM. Reformulated gasoline

represented in the PMM meets the requirements of phase 2 of the Complex Model, except in the Pacific

region where it meets CARB 3 specifications. 

AEO2008 reflects “Tier 2" Motor Vehicle Emissions Standards and Gasoline Sulfur Control Requirements

finalized by EPA in February 2000. This regulation requires that the average annual sulfur content of all

gasoline used in the United States be phased-down to 30 ppm between the years 2004 and 2007. The 30

ppm annual average standard is not fully realized in conventional gasoline until 2008 due to allowances for

small refineries.

AEO2008 reflects Heavy-Duty Engine and Vehicle Standards and Highway Diesel Fuel Sulfur Control

Requirements finalized by the EPA in December 2000. Between June 2006 and June 2010, this regulation

requires that 80 percent of highway diesel supplies contain no more than 15 ppm sulfur while the remaining

20 percent of highway diesel supplies contain no more than 500 ppm sulfur. After June 2010, all highway

diesel is required to contain no more than 15 ppm sulfur at the pump.

AEO2008 reflects nonroad locomotive and marine (NRLM) diesel requirements finalized by the EPA in May

2004. Between June 2007 and June 2010, this regulation requires that nonroad diesel supplies contain no

more than 15 ppm sulfur. For locomotive and marine diesel, the action establishes a NRLM limit of 15 ppm in 

mid-2012.

AEO2008 incorporates the American Jobs Creation Act of 2004 to extend the Federal tax credit of 51 cents

per gallon of ethanol blended into gasoline through 2010.

AEO2008 represents major provisions in the Energy Policy Act of 2005 concerning the petroleum industry,

including: 1) removal of oxygenate requirement in RFG; and 2) extension of tax credit of $1 per gallon for

soybean oil biodiesel and $0.50 per gallon for yellow grease biodiesel through 2008.

AEO2008 includes provisions outlined in the Energy Independence and Security Act of 2007 concerning the

petroleum industry, including a renewable Fuels Standard increasing total U.S. consumption of renewable

fuels. Although the statute calls for higher levels, due to uncertainty about wheter the new RFS schedule can 

be achieved and the stated mechanisms for reducing the cellulosic biofuel schedule the final schedules in

PMM were assumed to be: 1) 32.5 billion gallons in 2022 for all fuels; 2) 17.5 billion gallons in 2022 for

advanced biofuels; 3) 12.5 billion gallons in 2022 for cellulosic biofuel; 4) 1 billion gallons of biodiesel by

2022.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 133
[1] U.S. Environmental Protection Agency, “Tier 2” Motor Vehicle Emissions Standards and Gasoline 

Sulfur Control Requirements, February 2000, (Washington, DC).

[2] Federal Register, Environmental Protection Agency, 40 CFR Part 80, Regulation of Fuels and Fuel 

Additives: Standards for Reformulated and Conventional Gasoline, Rules and Regulations, p. 7800, 

(Washington, DC, February 1994).

[3] Marano, John, "Alternative Fuels Technology Profile: Cellulosic Ethanol", March 2008.

[4] McAloon, Andrew; Taylor, Frank; Yee, Winnie; Ibsen, Kelly; and Wooley, Robert. "Determining the

Cost of Producing Ethanol from Corn Starch and Lignocellulosic Feedstocks," October 2000.

[5] U.S. Department of Agriculture, "USDA Agricultural Baseline Projections to 2017," February 2008,

http://www.ers.usda.gov/publications/oce081.

[6] Ibid

[7] Shapouri Hosein; Gallagher, Paul; and Graboski, Mike. USDA's 1998 Ethanol Cost-of-Production

Survey. January 2002.

[8] Marland, G. and A.F. Turhollow. 1991. "CO2 Emissions from the Production and Combusion of Fuel

Ethanol from Corn." Energy, 16(11/12):1307-1316.

[9] U.S. Environmental Protection Agency, Regulatory Impact Analysis: Heavy-Duty Engine and Vehicle

Standards and Highway Diesel Fuel Sulfur Requirements, EPA420-R-00-026 (Washington, DC,

December 2000).

[10] American Petroleum Institute, How Much We Pay for Gasoline: 1996 Annual Review, May 1997.

[11] Marano, John, "Alternative Fuels Technology Profile: Coal to Liquids", March 2008.

134 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Notes and Sources
Coal Market Module

The NEMS Coal Market Module (CMM) provides projections of U.S. coal production, consumption, exports,

imports, distribution, and prices. The CMM comprises three functional areas: coal production, coal

distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal

Market Module of the National Energy Modeling System 2008, DOE/EIA-M060(2008) (Washington, DC,

2008).

Key Assumptions

Coal Production

The coal production submodule of the CMM generates a different set of supply curves for the CMM for each

year of the projection. Forty separate supply curves are developed for each of 14 supply regions, nine coal

types (unique combinations of thermal grade and sulfur content), and two mine types (underground and

surface). Supply curves are constructed using an econometric formulation that relates the minemouth prices 

of coal for the supply regions and coal types to a set of independent variables. The independent variables

include: capacity utilization of mines, mining capacity, labor productivity, the user cost of capital of mining

equipment, and the cost of factor inputs (labor and fuel).

The key assumptions underlying the coal production modeling are:

• As capacity utilization increases, higher minemouth prices for a given supply curve are projected. 

The opportunity to add capacity is allowed within the modeling framework if capacity utilization rises

to a pre-determined level, typically in the 80 percent range. Likewise, if capacity utilization falls,

mining capacity may be retired. The amount of capacity that can be added or retired in a given year

depends on the level of capacity utilization, the supply region, and the mining process (underground

or surface). The volume of capacity expansion permitted in a projection year is based upon historical

patterns of capacity additions.

• Between 1980 and 1999, U.S. coal mining productivity increased at an average rate of 6.7 percent

per year from 1.93 to 6.61 tons per miner per hour. The major factors underlying these gains were

interfuel price competition, structural change in the industry, and technological improvements in coal

mining.1 Since 1999, however, growth in overall U.S. coal mining productivity has slowed

substantially, decreasing at a rate of 0.8 percent per year to 6.26 tons per miner hour in 2006. By

region, productivity in most of the coal producing basins represented in the CMM has remained

essentially constant during the past 5 years. In the Central Appalachian coal basin, which has been

mined extensively, productivity declined by a significant 28 percent between 1999 and 2006,

corresponding to an average decline of 4.6 percent per year. 

Over the projection period, labor productivity is expected to remain near current levels in most coal

supply regions, reflecting the trend of the previous five years. Higher stripping ratios and the added

labor needed to maintain more extensive underground mines offset productivity gains achieved from

improved equipment, automation, and technology. Productivity in some areas of the East is projected 

to decline as operations move from mature coalfields to marginal reserve areas. Regulatory

restrictions on surface mines and fragmentation of underground reserves limit the benefits that can

be achieved by Appalachian producers from economies of scale. 

In the CMM, different rates of productivity improvement are assumed for each of the 40 coal supply

curves used to represent U.S. coal supply. These estimates are based on recent historical data and

expectations regarding the penetration and impact of new coal mining technologies.2 Data on labor

productivity are provided on a quarterly and annual basis by individual coal mines and preparation

plants on the U.S. Mine Safety and Health Administration’s Form 7000-2, “Quarterly Mine

Employment and Coal Production Report” and the Energy Information Administration’s Form EIA-7A, 

Coal Production Report. In the reference case, overall U.S. coal mining labor productivity increases

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 135

Report #:DOE/EIA-0554(2008)

Release date: June 2008

Next release date: March 2009
at rate of 0.6 percent a year between 2006 and 2030. Reference case projections of coal mining

productivity by region are provided in Table 67. 

• In the AEO2008 scenarios, both the wage rate for U.S. coal miners and mine equipment costs are

assumed to remain constant in 2006 dollars (i.e., increase at the general rate of inflation) over the

projection period. This assumption primarily reflects the recent trends in these cost variables. 

Coal Distribution

The coal distribution submodule of the CMM determines the least-cost (minemouth price plus transportation 

cost) supplies of coal by supply region for a given set of coal demands in each demand sector using a linear

programming algorithm. Production and distribution are computed for 14 supply (Figure 10) and 14 demand

regions (Figure 11) for 49 demand subsectors.

The projected levels of coal-to-liquids, industrial steam, coking, and residential/commercial coal demand are 

provided by the petroleum market, industrial, commercial, and residential demand modules, respectively;

electricity coal demands are projected by the EMM; coal imports and coal exports are projected by the CMM

based on non-U.S. coal supply availability, endogenously determined U.S. import demand, and

exogenously determined world coal demand (non-U.S.).

136 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Supply Region 2006 2010 2015 2020 2025 2030

Average

 Annual

 Growth

 06-30

Northern

 Appalachia

4.02 3.86 4.00 4.07 4.10 4.12 0.1%

Central

 Appalachia 2.89 2.65 2.61 2.48 2.40 2.31 -0.9%

Southern

 Appalachia 2.02 1.91 1.80 1.70 1.64 1.59 -1.0%

Eastern Interior 4.17 4.22 4.32 4.35 4.38 4.37 0.2%

Western Interior 3.35 3.35 3.35 3.35 3.35 3.35 0.0%

Gulf Lignite 9.67 9.51 9.27 9.04 8.82 8.60 -0.5%

Dakota Lignite 17.00 17.26 17.69 18.14 18.60 19.07 0.5%

Western

 Montana 22.05 22.11 22.67 23.25 19.42 18.69 -0.7%

Wyoming,

 Northern 

 Power River Basin

38.38 36.26 36.85 37.25 37.59 37.78 -0.1%

Wyoming,

 Southern 

 Power River Basin

40.99 38.53 38.23 37.77 37.17 36.43 -0.5%

Western

 Wyoming 8.76 7.95 8.03 8.31 8.44 8.62 -0.1%

Rocky Mountain 7.06 6.70 6.84 6.96 7.07 7.15 0.1%

Arizona/New

 Mexico 8.38 8.46 8.57 8.65 8.71 8.76 0.2%

Alaska/

 Washington 2.69 2.69 2.69 2.69 2.69 2.69 0.0%

U.S. Average 6.26 6.08 6.71 6.99 7.18 7.25 0.6%

Table 67. Coal Mining Productivity by Region

(Short Tons per Miner Hour)

Source: Energy Information Administration, AEO2008 National Energy Modeling System run AEO2008.D030208f.
Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 137

WA

OR ID

CA

NV

UT

TX

OK

AR

MO

LA

MS

AL

GA

FL

TN

SC

NC

KY VA

WV

WY

CO

SD

ND

MI

MN

WI

IL

IN

OH

MD

PA

NJ

DE

CT

MA

NH

VT

NY

ME

RI

MT

NE

IA

KS

MI

AZ

NM

500 0

SCALE IN MILES

APPALACHIA

Northern Appalachia

Central Appalachia

Southern Appalachia

INTERIOR

NORTHERN GREAT PLAINS

Eastern Interior

Western Interior

Gulf Lignite

Dakota Lignite

Western Montana

Wyoming, Northern Powder River Basin

Wyoming, Southern Powder River Basin

Western Wyoming

OTHER WEST

Rocky Mountain

Southwest

Northwest

KY

AK

1000 0

SCALE IN MILES

Figure 10. Coal Supply Regions

Source: Energy Information Administration, Office of Integrated Analysis and Forecasting
The key assumptions underlying the coal distribution modeling are:

• Base-year (2006) transportation costs are estimates of average transportation costs for each

origin-destination pair without differentiation by transportation mode (rail, truck, barge, and

conveyor). These costs are computed as the difference between the average delivered price for a

demand region (by sector and for export) and the average minemouth price for a supply curve.

Delivered price data are from Form EIA-3, Quarterly Coal Consumption Report-Manufacturing

Plants, Form EIA-5, Quarterly Coke Consumption and Quality Report, Coke Plants, Form EIA-423,

Monthly Cost and Quality of Fuels for Electric Plants Report, Federal Energy Regulatory Commission 

(FERC) Form 423, Monthly Report of Cost and Quality of Fuels for Electric Plants, and the U.S.

Bureau of the Census’ Monthly Report EM-545. Minemouth price data are from Form EIA-7A, Coal

Production Report.

• For the electricity sector only, a two-tier transportation rate structure is used for those regions which,

in response to rising demands or changes in demands, may expand their market share beyond

historical levels. The first-tier rate is representative of the historical average transportation rate. The

138 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

CT,MA,ME,NH,RI,VT

IN,IL,MI,WI

1. NE

2. YP

3. SA

4. GF

5. OH

6. EN

7. KT

AL,MS

MN,IA,ND,SD,NE,MO,KS

TX,LA,OK,AR

MT,WY,ID

CO,UT,NV

AZ,NM

AK,HI,WA,OR,CA

8. AM

9. CW

10. WS

11. MT

12. CU

13. ZN

14. PC

WV,MD,DC,DE,VA,NC,SC

Region Code Region Content

NY,PA,NJ

GA,FL

OH

KY,TN

Region Code Region Content

12. CU

11. MT

14. PC

13. ZN

10. WS

9. CW

8. AM 4. GF

7. KT

3. SA

6. EN

5. OH

2. YP

1. NE

Figure 11. Coal Demand Regions

Source: Energy Information Administration, Office of Integrated Analysis and Forecasting.
second-tier transportation rate is used to capture the higher cost of expanded shipping distances in

large demand regions. The second tier is also used to capture costs associated with the use of

subbituminous coal at units that were not originally designed for its use. This cost is estimated at

$0.10 per million Btu (2000 dollars).3

• Coal transportation costs, both first- and second-tier rates, are modified over time by two regional

(east and west) transportation indices. The indices are measures of the change in average

transportation rates, on a tonnage basis, that occurs between successive years for rail and

multi-mode coal shipments. An east index is used for coal originating from eastern supply regions

while a west index is used for coal originating from western supply regions. The indices are

calculated econometrically as a function of railroad productivity, the user cost of capital of railroad

equipment, average contract duration, and average distance (west only). Although the indices are

derived from railroad information, they are universally applied to all domestic coal transportation

movements within the CMM. In the AEO2008 reference case, eastern coal transportation rates are

projected to be 1 percent higher in 2030 and western rates are projected to be 2 percent higher in

2030 compared to 2006. 

Railroad productivity, measured in freight ton-miles per employee per year,is expected to increase at

an average rate of 2.9 percent per year for the east and 1.8 percent per year for the west from 2006. 

The user cost of capital for railroad equipment is calculated from the PPI for railroad equipment,

projected exogenously to remain flat in real terms, and accounts for the opportunity cost of money

used to purchase equipment, depreciation occurring as a result of use of the equipment (assumed at

10 percent), less any capital gain associated with the worth of the equipment. Contract duration is

held constant at 2001 levels over the projection reflecting the assumption that new contracts will

continue to be, on average, less than 5 years in length. For the west, distance is held constant over

the projection reflecting that distance is already implicitly accounted for in the model by using the

origin-destination pair transportation rate structure. The transportation rate indices for seven

AEO2008 cases are shown in Table 68.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 139

Scenario Region: 2006 2010 2015 2020 2025 2030

Reference Case

East 1.000 1.0450 1.0308 1.0183 1.0094 1.0055

West 1.000 1.0396 1.0311 1.0242 1.0194 1.0180

High Resource Price

East 1.000 1.0477 1.0308 1.0194 1.0146 1.0116

West 1.000 1.0415 1.0311 1.0250 1.0233 1.0226

Low Resource Price

East 1.000 1.0437 1.0306 1.0178 1.0067 1.0023

West 1.000 1.0386 1.0309 1.0238 1.0174 1.0156

High Economic Growth

East 1.000 1.0448 1.0337 1.0265 1.0219 1.0223

West 1.000 1.0394 1.0332 1.0303 1.0287 1.0306

Low Economic Growth East 1.000 1.0451 1.0279 1.0111 0.9985 0.9910

West 1.000 1.0396 1.0289 1.0188 1.0112 1.0071

High Coal Cost

East 1.000 1.0439 1.0484 1.0548 1.0642 1.0796

West 1.000 1.0393 1.0454 1.0534 1.0630 1.0767

Low Coal Cost

East 1.000 1.0452 1.0127 0.9830 0.9573 0.9360

West 1.000 1.0391 1.0163 0.9958 0.9776 0.9622

Table 68. Transportation Rate Multipliers

 (Constant Dollar Index, 2006=1.000)

Source: Projections: Energy Information Administration, National Energy Modeling System runs AEO2008.D030208f,

HP2008.D031809a, LP2008.D031608a, HM2008.D031608a, LM2008.D031608a, HCCST08.D030508a, and

LCCST08.D030508a. Based on methodology described in Coal Market Module of the National Energy Modeling System,

Model Documentation 2008, DOE/EIA-060(2008), (Washington, DC, 2008).
• Major coal rail carriers have implemented fuel surcharge programs in which higher transportation fuel 

costs have been passed on to shippers. While the programs vary in their design, the Surface

Transportation Board (STB), the regulatory body with limited authority to oversee rate disputes, has

recommended that the railroads agree to develop some consistencies among their disparate

programs and has likewise recommended closely linking the charges to actual fuel use. The STB has 

cited the use of a mileage-based program as one means to more closely estimate actual fuel

expenses. 

For AEO2008, representation of a fuel surcharge program is included in the coal transportation costs. 

For the west, the methodology is based on BNSF Railway Company's mileage-based program. The

surcharge becomes effective when the projected nominal distillate price to the transportation sector

exceeds $1.25 per gallon. For every $0.06 per gallon increase above $1.25, a $0.01 per carload mile

is charged. For the east, the methodology is based on CSX Transportation's mileage-based

program. The surcharge becomes effective when the projected nominal distillate price to the

transportation sector exceeds $2.00 per gallon. For every $0.04 per gallon increase above $2.00, a

$0.01 per carload mile is charged. The number of tons per carload and the number of miles vary with

each supply and demand region combination and are a pre-determined model input. The final

calculated surcharge (in constant dollars per ton) is added to the escalator-adjusted transportation

rate. For every projection year, it is assumed that 100 percent of all coal shipments are subject to the

surcharge program.

• Coal contracts in the CMM represent a minimum quantity of a specific electricity coal demand that

must be met by a unique coal supply source prior to consideration of any alternative sources of

supply. Base-year (2006) coal contracts between coal producers and electricity generators are

estimated on the basis of receipts data reported by electric utilities on FERC Form 423, Monthly

Report of Cost and Quality of Fuels for Electric Plants, and by nonutility generators on Form EIA-423,

Monthly Cost and Quality of Fuels for Electric Plants Report. Coal contracts are specified by CMM

supply region, coal type, demand region, and whether or not a unit has flue gas desulfurization

equipment. Coal contract quantities are reduced over time on the basis of contract duration data

reported by electric utilities on FERC Form 580, “Interrogatory on Fuel and Energy Purchase

Practices,” historical patterns of coal use, and information obtained from various coal and electric

power industry publications and reports. 

• Electric generation demand received by the CMM is subdivided into “coal groups” representing

demands for different sulfur and thermal heat content categories. This process allows the CMM to

determine the economically optimal blend of different coals to minimize delivered cost, while meeting

emissions requirements. Similarly, nongeneration demands are subdivided into subsectors with their

own coal groups to ensure that, for example, lignite is not used to meet a coking coal demand.

• Coal-to-liquids (CTL) facilities are assumed to be economic when low-sulfur distillate prices reach

high enough levels. These plants are assumed to be co-production facilities with generation capacity 

of 652 MW and the capability of producing 50,000 barrels of liquid fuel per day. The technology

assumed is similar to an integrated gasification combined cycle, first converting the coal feedstock to

gas, and then subsequently converting the syngas to liquid hydrocarbons using the Fisher-Tropsch

process. Of the total amount of coal consumed at each plant, 46 percent of the energy input is

retained in the product with the remaining energy used for conversion (38 percent) and for the

production of power sold to the grid (17 percent). 

Coal Imports and Exports

Coal imports and exports are modeled as part of the CMM’s linear program that provides annual projections

of U.S. steam and metallurgical coal exports, in the context of world coal trade. The linear program

determines the pattern of world coal trade flows that minimize the production and transportation costs of

meeting U.S. import demand and a pre-specified set of regional world coal import demands. It does this

subject to constraints on export capacity and trade flows.

140 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008
The key assumptions underlying coal export modeling are:

• The coal market is competitive. In other words, no large suppliers or groups of producers are able to

influence the price through adjusting their output. Producers’ decisions on how much and who they

supply are driven by their costs, rather than prices being set by perceptions of what the market can

bear. In this situation, the buyer gains the full consumer surplus.

• Coal buyers (importing regions) tend to spread their purchases among several suppliers in order to

reduce the impact of potential supply disruptions, even though this may add to their purchase costs.

Similarly, producers choose not to rely on any one buyer and instead endeavor to diversify their sales.

• Coking coal is treated as homogeneous. The model does not address quality parameters that define

coking coals. The values of these quality parameters are defined within small ranges and affect world 

coking coal flows very little.

Data inputs for coal trade modeling:

• U.S. coal exports are determined, in part, by the projected level of world coal import demand. World

steam and metallurgical coal import demands for the AEO2008 cases are shown in Tables 69 and 70.

• Step-function coal export supply curves for all non-U.S. supply regions. The curves provide

estimates of export prices per metric ton, inclusive of minemouth and inland freight costs, as well as

the capacities for each of the supply steps.

• Ocean transportation rates (in dollars per metric ton) for feasible coal shipments between

international supply regions and international demand regions. The rates take into account

maximum vessel sizes that can be handled at export and import piers and through canals and reflect

route distances in thousands of nautical miles.

Coal Quality

Each year the values of base year coal production, heat, sulfur and mercury (Hg) content and carbon dioxide 

emissions for each coal source in CMM are calibrated to survey data. Surveys used for this purpose are the

FERC Form 423, a survey of the origin, cost and quality of fossil fuels delivered to electric utilities, the Form

EIA 423, a survey of the origin, cost and quality of fossil fuels delivered to non-utility generating facilities, the

Form EIA-5 which records the origin, cost, and quality of coal receipts at domestic coke plants, and the Form 

EIA 3, which records the origin, cost and quality of coal delivered to domestic industrial consumers. 

Estimates of coal quality for the export and residential/commercial sectors are made using the survey data

for coal delivered to coking coal and industrial steam coal consumers. Hg content data for coal by supply

region and coal type, in units of pounds of Hg per trillion Btu, shown in Table 71, were derived from

shipment-level data reported by electricity generators to the Environmental Protection Agency in its 1999

Information Collection Request. The database included approximately 40,500 Hg samples reported for

1,143 generating units located at 464 coal-fired facilities. Carbon dioxide emission factors for each coal type

are shown in Table 71 in pounds of carbon dioxide emitted per million Btu.4

The CMM projects steam and metallurgical coal trade flows from 17 coal-exporting regions of the world to 20

import regions for three coal types (coking, bituminous steam, and subbituminous). It includes five U.S.

export regions and four U.S. import regions.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 141
142 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Import Regions1 20062

2010 2015 2020 2025 2030

The Americas 56.1 60.5 62.2 95.8 107.4 126.1

 United States3

27.4 29.9 33.8 65.2 75.7 93.0

 Canada 14.0 13.6 9.7 9.1 9.9 10.3

 Mexico 5.7 7.1 8.5 9.4 9.4 9.4

 South America 9.0 9.9 10.2 12.1 12.4 13.4

Europe 169.2 168.8 166.5 164.1 159.1 154.7

 Scandinavia 10.8 10.1 7.8 6.4 5.7 4.9

 U.K/Ireland 41.7 34.2 33.0 32.2 31.7 30.8

 Germany/Austria 26.5 26.5 27.8 27.5 26.6 25.6

 Other NW Europe 23.7 19.6 17.7 16.7 14.7 13.8

 Iberia 23.2 22.5 21.2 20.1 18.8 17.3

 Italy 14.2 23.0 24.8 26.6 26.6 26.6

 Med/E Europe 29.1 32.9 34.2 34.6 35.0 35.7

Asia 283.9 320.7 350.0 386.3 409.7 429.9

 Japan 87.8 86.0 86.0 86.0 86.0 86.0

 East Asia 104.2 103.2 110.4 121.8 128.5 139.5

 China/Hong Kong 40.8 64.9 74.6 87.4 92.9 94.7

 ASEAN 24.1 31.7 39.8 48.5 57.2 63.2

 Indian Sub 27.0 34.9 39.2 42.6 45.1 46.5

Total 509.2 550.0 578.7 646.2 676.2 710.7

Table 69. World Steam Coal Import Demand by Import Region

(Million metric tons of coal equivalent)

1

Import Regions: South America: Argentina, Brazil, Chile, Puerto Rico; Scandinavia: Denmark, Finland, Norway, Sweden; Other

NW Europe: Belgium, France, Luxembourg, Netherlands; Iberia: Portugal, Spain; Med/E Europe: Algeria, Bulgaria, Croatia,

Egypt, Greece, Israel, Malta, Morocco, Romania, Tunisia, Turkey; East Asia: North Korea, South Korea, Taiwan; ASEAN:

Malaysia, Philippines, Thailand; Indian Sub: Bangladesh, India, Iran, Pakistan, Sri Lanka.

2

The base year of the world trade projection for coal is 2006.

3Excludes imports to Puerto Rico and the U.S. Virgin Islands.

Notes: One “metric ton of coal equivalent” contains 27.78 million Btu. Totals may not equal sum of components due

to independent rounding.
Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 143

Import Regions1200622010 2015 2020 2025 2030

The Americas 20.8 25.5 27.4 28.9 31.7 36.1

 United States 1.3 1.3 1.3 1.3 1.3 1.3

 Canada 4.6 3.6 3.5 3.3 3.2 3.0

 Mexico 1.0 1.1 2.3 2.3 3.4 3.4

 South America 13.9 19.5 20.3 21.9 23.8 28.4

Europe 57.7 52.1 49.5 53.0 54.2 55.8

 Scandinavia 2.9 2.5 2.0 1.9 1.6 1.3

 U.K/Ireland 8.8 7.2 7.2 7.2 7.2 7.2

 Germany/Austria 9.0 7.5 6.5 6.5 6.5 6.5

 Other NW Europe 14.5 14.2 13.1 12.0 11.5 11.6

 Iberia 4.4 3.9 3.8 3.8 3.8 3.8

 Italy 8.3 6.2 5.6 5.6 5.6 5.6

 Med/E Europe 9.8 10.6 11.3 16.0 18.0 19.8

Asia 124.3 143.6 160.3 170.2 180.5 190.8

 Japan 74.5 84.5 84.0 81.1 78.9 78.1

 East Asia 27.3 27.7 27.8 29.1 32.2 33.2

 China/Hong Kong 3.5 6.1 19.2 27.6 34.5 42.2

 ASEAN 0.0 0.0 0.0 0.0 0.0 0.0

 Indian Sub 19.0 25.3 29.3 32.4 34.9 37.3

Total 202.8 221.2 237.2 252.1 266.4 282.7

Table 70. World Metallurgical Coal Import Demand by Import Region

(Million metric tons of coal equivalent)

1

Import Regions: South America: Argentina, Brazil, Chile, Puerto Rico; Scandinavia: Denmark, Finland, Norway, Sweden; Other

NW Europe: Belgium, France, Luxembourg, Netherlands; Iberia: Portugal, Spain; Med/E Europe: Algeria, Bulgaria, Croatia,

Egypt, Greece, Israel, Malta, Morocco, Romania, Tunisia, Turkey; East Asia: North Korea, South Korea, Taiwan; ASEAN:

Malaysia, Philippines, Thailand; Indian Sub: Bangladesh, India, Iran, Pakistan, Sri Lanka.

2 The base year of the world trade projection for coal is 2006.

Notes: One “metric ton of coal equivalent” contains 27.78 million Btu. Totals may not equal sum of components due to

independent rounding.

Source: Projections: Energy Information Administration, Office of Integrated Analysis and Forecasting.
144 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Coal Supply 

 Region

Coal Rank and

 Sulfur Level Mine Type

2006

Production

(Million

Short

tons)

Heat

Content

(Million

 Btu per

 Short

Ton)

Sulfur

Content 

(Pounds

Per

Million

Btu)

Mercury 

Content 

(Pounds

Per

Trillion 

Btu)

CO2

(Pounds

Per

Million

Btu)

Northern

 Appalachia

Metallurgical

Mid-Sulfur Bituminous

High-Sulfur Bituminous

Waste Coal (Gob and

 Culm)

Underground

All

All

Surface

3.4

66.8

66.2

13.6

26.27

25.24

24.84

12.70

0.68

1.28

2.49

2.82

N/A

11.17

11.67

63.9

207.5

207.5

205.7

205.7

Central

 Appalachia

Metallurgical

Low-Sulfur Bituminous

Mid-Sulfur Bituminous

Underground

All

All

38.3

44.9

153.4

26.27

24.84

24.74

0.62

0.55

0.86

N/A

5.61

7.58

205.9

205.9

205.9

Southern

Appalachia

Metallurgical

Low-Sulfur Bituminous

Mid-Sulfur Bituminous

Underground

All

All

7.4

0.2

11.4

26.27

24.84

24.85

0.51

0.50

1.21

N/A

3.87

10.15

205.4

205.4

205.4

 East Interior Mid-Sulfur Bituminous

High-Sulfur Bituminous

Mid-Sulfur Lignite

All

All

Surface

26.4

68.7

3.8

22.26

22.85

10.23

1.06

2.67

0.94

5.6

6.35

14.11

204.9

204.7

213.5

 West Interior High-Sulfur Bituminous Surface 2.8 22.66 2.42 21.55 204.4

 Gulf Lignite Mid-Sulfur Lignite

High-Sulfur Lignite

Surface

Surface

33.4

16.3

13.38

12.57

1.29

2.40

14.11

15.28

213.5

213.5

 Dakota Lignite Mid-Sulfur Lignite Surface 30.8 13.26 1.07 8.38 218.8

Western 

 Montana

Low-Sulfur Subbituminous

Low-Sulfur Subbituminous

Mid-Sulfur Subbituminous

Underground

Surface

Surface

0.3

22.5

18.7

20.03

18.72

17.19

0.58

0.37

0.79

5.06

5.06

5.47

209.6

213.5

213.5

Northern

 Wyoming

Low-Sulfur Subbituminous

 Mid-Sulfur Subbituminous

Surface

Surface

172.0

4.0

16.88

16.27

0.39

0.83

7.08

7.55

212.7

212.7

Southern

 Wyoming Low-Sulfur Subbituminous Surface 255.1 17.66 0.31 5.22 212.7

Western

 Wyoming

Low-Sulfur Subbituminous

 Low-Sulfur Subbituminous

 Mid-Sulfur Subbituminous

Underground

 Surface

 Surface

 0.5

 

 3.2

11.9

18.53

 

 18.88

19.00

0.63

0.50

0.77

2.19

4.06

4.35

206.5

212.7

212.7

Rocky

Mountain

Low-Sulfur Bituminous

Low-Sulfur Subbituminous

Underground

Surface

52.7

9.7

22.95

20.70

0.51

0.41

3.82

2.04

205.1

212.7

Southwest Low-Sulfur Bituminous

Mid-Sulfur Subbituminous

Mid-Sulfur Bituminous

Surface

Surface

Underground

13.0

14.1

7.0

20.89

18.09

19.52

0.47

0.95

0.70

4.66

7.18

7.18

207.5

208.8

208.8

 Northwest Mid-Sulfur Subbituminous Surface 4.0 15.61 0.95 6.99 210.0

Table 71. Production, Heat Content, and Sulfur, Mercury and Carbon Dioxide Emission Factors by Coal

Type and Region

N/A = not available.

Source: Energy Infor ma tion Admin is tra tion, Form EIA-3, “Quar terly Coal Con sump tion Report—Man u fac turing Plants”; Form EIA-5, “Quarterly Coal

Consumption and Quality Report, Coke Plants"; Form EIA-6A, “Coal Dis tri bu tion Report—Annual”; Form EIA-7A, “Coal Pro duc tion Report", and Form

EIA-423, "Monthly Cost and Quality of Fuels for Electric Plants Report.” Fed eral Energy Reg u la tory Com mis sion, Form 423, “Monthly Report of Cost

and Qual ity of Fuels for Elec tric Plants.” U.S. Depart ment of Com merce, Bureau of the Cen sus, “Monthly Report EM-545.” U.S. Envi ron men tal

Pro tec tion Agency, Emis sion Stan dards Divi sion, Infor ma tion Col lec tion Request for Elec tric Util ity Steam Gen er ating Unit, Mer cury Emis sions

Infor ma tion Col lec tion Effort (Research Tri an gle Park, NC, 1999). B.D. Hong and E.R. Slatick, “Car bon Diox ide Emis sion Fac tors for Coal,” in Energy

Infor ma tion Admin is tra tion, Quar terly Coal Report, Jan u ary-March 1994, DOE/EIA-0121 (94/Q1) (Wash ing ton, DC, August 1995).
Legislation and Regulations

The AEO2008 reference case incorporates provisions of the Clean Air Act Amendments of 1990 as they

apply to sulfur dioxide and nitrogen oxide emissions. EPA finalized the Clean Air Interstate Rule (CAIR) and

the Clean Air Mercury Rule (CAMR) in March 2005, and both are represented in the reference case. For

affected states, CAIR further restricts emissions of sulfur dioxide beginning in 2010 to 3.6 million tons and

nitrogen oxides beginning in 2009 to 1.5 million tons. Beginning in 2015, for affected states, tighter emission

limits for sulfur dioxide (2.5 million tons) and nitrogen oxides (1.3 million tons) are required in Phase 2 of

CAIR. A nationwide cap for mercury of 38 tons per year beginning in 2010 and then 15 tons per year

beginning in 2018 are specified in CAMR. The reference case excludes any potential environmental actions

not currently mandated such as carbon dioxide reductions or other rules or regulations not finalized.

Coal Alternative Cases

Coal Cost Cases

In the reference case, coal mine labor productivity is assumed to increase on average by 0.6 percent per

year through 2030 while miner wage rates and mine equipment costs remain constant in 2006 dollars. 

Eastern and western railroad productivity is assumed to grow at an average rate of 2.9 and 1.8 percent

respectively from 2006. Railroad equipment costs are assumed to remain flat in real terms from 2006 levels. 

In two alternative coal cost cases, productivity, average miner wages, and equipment cost assumptions

were modified for 2009 through 2030 in order to examine the impacts on U.S. coal supply, demand,

distribution and prices. 

In the low mining cost case, coal mine labor productivity is assumed to increase at an average rate of 3.7

percent per year through 2030. Miner wages are assumed to decline in constant dollars by 1.0 percent per

year. Mine equipment costs and railroad equipment costs are projected to fall by 1.0 percent. In the low

mining cost case, eastern and western railroad productivity is assumed to grow at an average rate of 5.3 and

4.2 percent, respectively from 2006. 

In the high mining cost case, coal mine labor productivity is assumed to decline at an average rate of 3.0

percent per year through 2030. Miner wages are assumed to increase in constant dollars by 1.0 percent per

year. Mine equipment costs and railroad equipment costs are projected to increase by 1.0 percent. In the

high mining cost case, eastern railroad productivity is assumed to increase by 0.5 percent per year and

western railroad productivity is assumed to decrease by 0.6 percent per year from 2006. 

For the coal cost cases, adjustments to the reference case coal mining and railroad productivity

assumptions were based on variations in growth rates observed in the data for these industries since 1980. 

The low and high coal cost cases represent fully integrated NEMS runs, with feedback from the

Macroeconomic Activity, International, supply, conversion, and end-use demand modules.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 145
[1] Energy Information Administration, The U.S. Coal Industry, 1970-1990: Two Decades of Change,

DOE/EIA-0559, (Washington, DC, November 1992).

[2] Stanley C. Suboleski, et.al., Central Appalachia: Coal Mine Productivity and Expansion, Electric

Power Research Institute, EPRI IE-7117, (September 1991).

[3] The estimated cost of switching to subbituminous coal, $0.10 per million Btu (2000 dollars), was

derived by Energy Ventures Analysis, Inc. and was recommended for use in the CMM as part of an

Independent Expert Review of the Annual Energy Outlook 2002's Powder River Basin production and

transportation rates. Barbaro, Ralph and Seth Schwartz. Review of the Annual Energy Outlook 2002

Reference Case Forecast for PRB Coal, prepared for the Energy Information Administration (Arlington,

VA: Energy Ventures Analysis, Inc., August 2002)

[4] Hong, B.D. and Slatick, E.R. “Carbon Dioxide Emission Factors for Coal,” Energy Information 

Administration, Quarterly Coal Report, January-March 1994, DOE/EIA-121 (94/Q1) (Washington, DC,

August 1995).

146 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

Notes and Sources
Renewable Fuels Module

The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input

information for projections of new central-station U.S. electricity generating capacity using renewable

energy resources. The RFM has seven submodules representing various renewable energy sources,

biomass, geothermal, conventional hydroelectricity, landfill gas, solar thermal, solar photovoltaics, and

wind1.

Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass

materials, are fuels in the conventional sense of the word, while others, such as water, wind, and solar

radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable

technologies cover the gamut of commercial market penetration, from hydroelectric power, which was one of 

the first electric generation technologies, to newer power systems using biomass, geothermal, LFG, solar,

and wind energy. In some cases, they require technological innovation to become cost effective or have

inherent characteristics, such as intermittency, which make their penetration into the electricity grid

dependent upon new methods for integration within utility system plans or upon the availability of low-cost

energy storage systems.

The submodules of the RFM interact primarily with the Electricity Market Module (EMM). Because of the

high level of integration with the EMM, the final outputs (levels of consumption and market penetration over

time) for renewable energy technologies are largely dependent upon the EMM. 

Projections for residential and commercial grid-connected photovoltaic systems are developed in the

end-use demand modules and not in the RFM; see the Distributed Generation and Combined Heat and

Power descriptions in the “Commercial Demand Module” section of the report.

Key Assumptions

Nonelectric Renewable Energy Uses

In addition to projections for renewable energy used in central station electricity generation, the AEO2008

contains projections of nonelectric renewable energy uses for industrial and residential wood consumption,

solar residential and commercial hot water heating, biofuels blending in transportation fuels, and residential

and commercial geothermal (ground-source) heat pumps. Assumptions for their projections are found in the

residential, commercial, industrial, and petroleum marketing sections of this report. Additional minor

renewable energy applications occurring outside energy markets, such as direct solar thermal industrial

applications or direct lighting, off-grid electricity generation, and heat from geothermal resources used

directly (e.g., district heating and greenhouses) are not included in the projections.

Electric Power Generation

The RFM considers only grid-connected central station electricity generation systems. The RFM

submodules that interact with the EMM are the central station grid-connected biomass, geothermal,

conventional hydroelectricity, landfill gas, solar (thermal and photovoltaic), and wind submodules, which

provide specific data or estimates that characterize that resource. A set of technology cost and performance 

values is provided directly to the EMM and are central to the build and dispatch decisions of the EMM. The

technology cost and performance values are summarized in Table 38 in the chapter discussing the EMM.

Overnight capital costs are presented in Table 72 and the assumed capacity factors for new plants in Table

73.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 147

Report #:DOE/EIA-0554(2008)

Release date: June 2008

Next release date: March 2009
148 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 

Technology Reference High Cost Renewable1 Year Low Cost Renewable

Geothermal2 2010 1,126 1,149 1,093

 2020 3,231 3,511 3,031

 2030 3,122 3,647 2,808

Hydroelectric2, 2010 1,769 1,784 1,716

2020 1,644 1,782 1,631

2030 1,575 1,782 1,475

 Landfill Gas 2010 1,881 1,897 1,881

2020 1,828 1,897 1,828

2030 1,776 1,897 1,776

 Photovoltaic3 2010 4,915 5,084 4,825

2020 4,331 5,084 4,077

2030 3,681 5,084 3,397

 Solar Thermal3 2010 3.004 3,370 2,941

2020 2,524 3,370 2,337

2030 2,149 3,370 1,888

 Biomass4 2010 2,758 2,783 2,698

2020 2,482 2,647 2,301

2030 2,224 2,487 1,929

 Offshore Wind 2010 2,812 2,872 2,808

2020 2,641 2,872 2,621

2030 2,473 2,872 2,452

 Onshore Wind 2010 1,707 1,721 1,702

2020 1,693 1,721 1,669

2030 1,683 1,721 1,656

Table 72. Overnight Capital Cost Characteristics for Renewable Energy Generating Technologies in Three 

 Cases (2006$/kW)

1Overnight capital cost (that is, excluding interest charges), plus contingency, learning, and technological optimism factors,

excluding regional multipliers. A contingency allowance is defined by the American Association of Cost Engineers as the specific

provision for unforeseeable elements of costs within a defined project scope. This is particularly important where previous

experience has shown that unforeseeable events which will increase costs are likely to occur.

2Geothermal and Hydroelectric costs are specific for each site. The table entries represent the least cost unit available in the

specified year in the Northwest Power Pool region. In the 2006 Renewables cases, costs vary as different sites continue to be

developed.

3Costs decline slightly in the Low Renewable case for photovoltaic and solar thermal technologies as technological optimism is

factored into initial costs (see pg. 72 in the chapter discussing the EMM). However, there is no learning-by-doing assumed once the

optimism factor has been removed.

4Biomass plants share significant components with similar coal-fired plants, these components continue to decline in cost in the Low 

Renewables case, although biomass-specific components (especially fuel handling components) do not see cost declines beyond

2005.

Source: AEO2008 National Energy Modeling System runs AEO2008.D030208F, HIRENCST.D030408A, and

LORENCST.D030408A.
Capital Costs

Capital costs for renewable technologies are affected by several factors. Capital costs for technology to

exploit some resources, especially geothermal, hydroelectric, and wind power resources, are assumed to be 

dependent on the quality, accessibility, and/or other site-specific factors in the areas with exploitable

resources. These factors can include additional costs associated with reduced resource quality; need to

build or upgrade transmission capacity from remote resource areas to load centers; or local impediments to

permitting, equipment transport, and construction in good resource areas due to siting issues, inadequate

infrastructure, or rough terrain.

Short-term cost adjustment factors increase technology capital costs as a result of a rapid U.S. buildup in a

single year, reflecting limitations on the infrastructure (for example, limits on manufacturing, resource

assessment, and construction expertise) to accommodate unexpected demand growth. These factors,

which are applied to all new electric generation capacity, are a function of past production rates and are

further described in The Electricity Market Module of the National Energy Modeling System: Model

Documentation Report, available at http://www.eia.doe.gov/bookshelf/docs.html.

Independent of the other two factors, capital costs for all electric generation technologies, including

renewable technologies, are assumed to decline as a function of growth in installed capacity for each

technology.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 149

Technology Year Reference High Renewable Cost Low Renewable Cost

Geothermal2

2010 0.90 0.90 0.90

2020 0.90 0.90 0.90

2030 0.90 0.90 0.90

 Hydrolectric2

2010 0.64 0.64 0.64

2020 0.50 0.51 0.57

2030 0.49 0.51 0.54

Landfill Gas 2010 0.90 0.90 0.90

2020 0.90 0.90 0.90

2030 0.90 0.90 0.90

Photovoltaic 2010 0.21 0.21 0.21

2020 0.21 0.21 0.21

2030 0.21 0.21 0.21

Solar Thermal 2010 0.31 0.31 0.31

2020 0.31 0.31 0.31

2030 0.31 0.31 0.31

Biomass 2010 0.83 0.83 0.83

2020 0.83 0.83 0.83

2030 0.83 0.83 0.83

Offshore Wind3

2010 0.40 0.40 0.46

2020 0.40 0.40 0.46

2030 0.40 0.40 0.46

Onshore Wind3

2010 0.43 0.42 0.44

2020 0.45 0.42 0.48

2030 0.45 0.42 0.50

Table 73. Capacity Factors1 for Renewable Energy Generating Technologies in Three Cases

1Capacity factor for units available to be built in specified year. Capacity factor represents maximum expected

annual power output as a fraction of theoretical output if plant were operated at rated capacity for a full year.

2Hydroelectric capacity factors are specific for each site. The table entries represent the least-cost unit available in 

the specified year in the Northwest Power Pool region.

3Wind capacity factors are based on regional resource availability and generation characteristics. The table

entries represent the least-cost resource available in the specified year in the Northwest Power Pool region.

Source: AEO2008 National Energy Modeling System runs: AEO2008.D030208F, HIRENCST.D030408A, and

LORENCST.D030408A.
For a description of NEMS algorithms lowering generating technologies’ capital costs as more units enter

service (learning), see “Technological Optimism and Learning” in the EMM chapter of this report. A detailed

description of the RFM is provided in the EIA publication, Renewable Fuels Module of the National Energy

Modeling System, Model Documentation 2005, DOE/EIA-M069(2005) (Washington, DC, 2005).

Solar Electric Submodule

Background

The Solar Electric Submodule currently includes both concentrating solar power (thermal) and

photovoltaics, including two solar technologies: 50 megawatt central receiver (power tower) solar thermal

(ST) and 5 megawatt single axis tracking-flat plate photovoltaic (PV) technologies. PV is assumed available

in all thirteen EMM regions, while ST is available only in the six Western regions where direct normal solar

insolation is sufficient. Capital costs for both technologies are determined by EIA using multiple sources,

including public reports of recent solar thermal capcity additions. Most other cost and performance

characteristics for ST are obtained or derived from the August 6, 1993, California Energy Commission

memorandum, Technology Characterization for ER 94; and, for PV, from the Electric Power Research

Institute, Technical Assessment Guide (TAG) 1993. In addition, capacity factors are obtained from

information provided by the National Renewable Energy Laboratory (NREL).

Assumptions

• Capacity factors for solar technologies are assumed to vary by time of day and season of the year,

such that nine separate capacity factors are provided for each modeled region, three for time of day

and for each of three broad seasonal groups (summer, winter, and spring/fall). Regional capacity

factors vary from national averages. The current reference case solar thermal annual capacity factor

for California, for example, is assumed to average 40 percent; California’s current reference case PV

capacity factor is assumed to average 24.6 percent.

• Because solar technologies are more expensive than other utility grid-connected technologies, early

penetration will be driven by broader economic decisions such as the desire to become familiar with a 

new technology, environmental considerations, and the availability of limited Federal subsidies. 

Minimal early years’ penetration is included by EIA as “floor” additions to new generating capacity

(see “Supplemental and Floor Capacity Additions” below).

• Solar resources are well in excess of conceivable demand for new capacity; energy supplies are

considered unlimited within regions (at specified daily, seasonal, and regional capacity factors).

Therefore, solar resources are not estimated in NEMS. In the seven regions where ST technology is

not modeled, the level of direct, normal insolation (the kind needed for that technology) is insufficient

to make that technology commercially viable through 2030.

• NEMS represents the Energy Policy Act of 1992 (EPACT92) permanent 10-percent investment tax

credit (ITC) for solar electric power generation by tax-paying entities. The current 30-percent ITC is

scheduled to expire at the end of 2008.

Wind-Electric Power Submodule

Background

Because of limits to windy land areas, wind is considered a finite resource, so the submodule calculates

maximum available capacity by Electricity Market Module Supply Regions. The minimum economically

viable average wind speed is about 14 mph, and wind speeds are categorized by annual average wind

speed based on a classification system from the Pacific Northwest Laboratory. The RFM tracks wind

capacity (megawatts) by resource quality, distance to transmission, and other resource costs within a region

and moves to the next best wind resource when one category is exhausted. For AEO2008, wind resource

data on the amount and quality of wind per EMM region come from the National Renewable Energy

Laboratory2 The technological performance, cost, and other wind data used in NEMS are derived by EIA

from available data and from available literature.3 Maximum wind capacity, capacity factors, and incentives

are provided to the EMM for capacity planning and dispatch decisions. These form the basis on which the

150 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 
EMM decides how much power generation capacity is available from wind energy. The fossil-fuel heat rate

equivalents for wind are used for energy consumption calculation purposes only. 

Assumptions

• Only grid-connected (utility and nonutility) generation is included. Projections for distributed wind

generation are included in the commercial and residential modules. 

• In the wind submodule, wind supply costs are affected by three modeling measures: addressing (1)

average wind speed, (2) distance from existing transmission lines, and (3) resource degradation,

transmission network upgrade costs, and market factors. 

• Available wind resource is reduced by excluding all windy lands not suited for the installation of wind

turbines because of: excessive terrain slope (greater than 20 percent); reservation of land for

non-intrusive uses (such as National Parks, wildlife refuges, and so forth); inherent incompatibility

with existing land uses (such as urban areas, areas surrounding airports and water bodies, including

offshore locations); insufficient continguous windy land to support a viable wind plant (less than 5

square kilometers of windy land in a 100 square kilometer area). Half of the wind resource located on

military reservations, U.S. Forest Service land, state forested land, and all non-ridge-crest forest

areas are excluded from the available resource base to account for the uncertain ability to site

projects at such locations. These assumptions are detailed in the Draft Final Report to EIA on 

Incorporation of Existing Validated Wind Data into NEMS, November 2003.

• Capital costs for wind technologies are assumed to increase in response to (1) declining natural

resource quality, such as terrain slope, terrain roughness, terrain accessibility, wind turbulence, wind 

variability, or other natural resource factors, (2) increasing cost of upgrading existing local and

network distribution and transmission lines to accommodate growing quantities of intermittent wind

power, and (3) market conditions, such as the increasing costs of alternative land uses, including 

aesthetic or environmental reasons. Capital costs are left unchanged for some initial share, then

increased 20, 50, 100 percent, and finally 200 percent, to represent the aggregation of these factors. 

• Proportions of total wind resources in each category vary by EMM region. For all thirteen EMM

regions combined, 1.3 percent of windy land is available with no cost increase, 5.4 percent is

available with a 20 percent cost increase, 11.2 percent is available with a 50 percent cost increase,

27.3 percent is available with a 100 percent cost increase, and almost 54.8 percent of windy land is

assumed to be available with a 200 percent cost increase.

• Depending on the EMM region, the cost of competing fuels, and other factors, wind plants can be built 

to meet system capacity requirements or as a “fuel saver” to displace generation from existing

capacity. For wind to penetrate as a fuel saver, its total capital and fixed operations and maintenance

costs minus applicable subsidies must be less than the variable operating costs, including fuel, of the

existing (non-wind) capacity. When competing in the new capacity market, wind is assigned a

capacity credit that declines based on its estimated contribution to regional reliability requirements. 

• Because of downwind turbulence and other aerodynamic effects, the model assumes an average

spacing between turbine rows of 5 rotor diameters and a lateral spacing between turbines of 10 rotor

diameters. This spacing requirement determines the amount of power that can be generated from

wind resources, about 6.5 megawatts per square kilometer of windy land, and is factored into

requests for generating capacity by the EMM. 

• Capacity factors are assumed to increase to a national average of 44 percent in the best wind class

resulting from taller towers, more reliable equipment, and advanced technologies. Capacity factors

for each wind class are calculated as a function of overall wind market growth. The capacity factors

are assumed to be limited to about 48 percent for an average Class 6 site. As better wind resources

are depleted, capacity factors are assumed to go down. 

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 151
• AEO2008 does not allow plants constructed after 2008 to claim the Federal Production Tax Credit

(PTC), a 2 cent per kilowatt-hour tax incentive that is set to expire on December 31, 2008. Wind

plants are assumed to depreciate capital expenses using the Modified Accelerated Cost Recovery

Schedule with a 5-year tax life. 

Offshore wind resources are represented as a separate technology from onshore wind resources. Offshore

resources are modeled with a similar model structure as onshore wind. However, because of the unique

challenges of offshore construction and the somewhat different resource quality, the assumptions with

regard to capital cost, learning-by-doing cost reductions, and variation of resource exploitation costs and

performance differ significantly from onshore wind.

• Like onshore resources, offshore resources are assumed to have an upwardly sloping supply curve,

in part influenced by the same factors that determine the onshore supply curve (such as distance to

load centers, environmental or aesthetic concerns, variable terrain/seabed) but also explicitly by

water depth.

• Because of the more difficult maintenance challenge offshore, performance for given annual average 

wind power density level is assumed to be somewhat reduced by reduced turbine availability. 

Offsetting this, however, is the availability of resource areas with higher overall power density than is

assumed available onshore. Capacity factors for offshore are limited to be about 50 percent for a

Class 7 site.

• Cost reductions in the offshore technology result in part from learning reductions in onshore wind

technology as well as from cost reductions unique to offshore installations, such as foundation design 

and construction techniques. Because offshore technology is significantly less mature than onshore

wind technology, offshore-specific technology learning occurs at a somewhat faster rate than

on-shore technology.

Geothermal-Electric Power Submodule

Background

The Geothermal-Electric Submodule (GES) estimates the generating capacity and output potential of 89

hydrothermal sites in the Western United States. This estimation is based on two studies: New Geothermal

Site Identification and Qualification, prepared by GeothermEx, Inc for the California Public Utility

Commission, and Western Governors’ Association Geothermal Task Force Report, which was co-authored

by several geothermal experts from the public and private sectors. These studies focus on geothermal

resources with confirmed temperatures greater than 100 Celsius, which is generally considered the

threshold for economically feasible conventional development. While EIA had previously distinguished

between binary and dual flash technologies, this is no longer an essential component of cost estimates. 

Instead, these studies incorporate expected power plant cost and performance based on each confirmed

resource temperature. This enables greater projection precision relative to a static choice between two

technologies. All plants are assumed to operate at 90 percent capacity factor. Enhanced Geothermal

Systems (EGS), such as hot dry rock, are not included as potential resources since this technology is still in

development and is not expected to be in significant commercial use within the projection horizon.

The two studies off of which EIA estimates are based maintain separate capital cost components for each

site’s development. The GeothermEx study divided individual site costs into four components: exploration,

confirmation, development, and transmission. Site exploration is a small component of aggregate costs,

oftentimes being zero. Confirmation and transmission costs may be significant, however the vast majority of

capital costs are classified under site development which includes power plant construction. The WGA

report, which was used to estimate geothermal potential outside of the GeothermEx database region, did not 

provide site specific, separate capital cost components. However, it did provide some sites with two levels of 

capital costs, meaning a portion of the resource could be developed at a lower cost than the remaining

potential. Therefore, EIA maintained two categories of site specific capital development costs, with a cost

premium placed on some sites beyond their most economic resource. Site specific operation and

maintenance costs are also included in the submodule. As a result of revised supply estimations, the annual

site build limit has been relaxed but still remains. Geothermal development is limited to 25 MW of generating

capacity until 2010, when the 50 MW limit goes into effect for the remainder of the projection period. 

152 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 
Assumptions

• Existing and identified planned capacity data are obtained directly by the EMM from Forms EIA-860A

(utilities) and EIA-860B (nonutilities) and from supplemental additions (See Below). 

• The permanent investment tax credit of 10 percent available in all projection years based on the

EPACT applies to all geothermal capital costs, except through 2008 when the 1.9 cent production tax

credit is available to this technology and is assumed chosen instead.

• Plants are not assumed to retire unless their retirement is reported to EIA. Geysers units are not

assumed to retire but instead are assigned the 35 percent capacity factors reported to EIA reflecting

their reduced performance in recent years.

• Capital and operating costs vary by site and year; values shown in Table 39 in the EMM chapter are

indicative of those used by EMM for geothermal build and dispatch decisions. 

Biomass Electric Power Submodule

Background

Biomass consumed for electricity generation is modeled in two parts in NEMS. Capacity in the wood

products and paper industries, the so-called captive capacity, is included in the industrial sector module as

cogeneration. Generation by the electricity sector is represented in the EMM, with capital and operating

costs and capacity factors as shown in Table 38 in the EMM chapter, as well as fuel costs, being passed to

the EMM where it competes with other sources. Fuel costs are provided in sets of regional supply

schedules. Projections for ethanol are produced by the Petroleum Market Module (PMM), with the quantities 

of biomass consumed for ethanol decremented from, and prices obtained from, the EMM regional supply

schedules.

Assumptions

• Existing and planned capacity data are obtained from Form EIA-860.

• The conversion technology represented, upon which the costs in Table 39 in the EMM chapter are

based, is an advanced gasification-combined cycle plant that is similar to a coal-fired gasifier. Costs

in the reference case were developed by EIA to be consistent with coal gasifier costs. Short-term

cost adjustment factors are used.

• Biomass cofiring can occur up to a maximum of 15 percent of fuel used in coal-fired generating

plants. 

Fuel supply schedules are a composite of four fuel types: forestry materials, wood residues, agricultural

residues and energy crops. Energy crop data are presented in yearly schedules from 2010 to 2030 in

combination with the other material types for each region. The forestry materials component is made up of

logging residues, rough rotten salvageable dead wood, and excess small pole trees.4 The wood residue

component consists of primary mill residues, silvicultural trimmings, and urban wood such as pallets,

construction waste, and demolition debris that are not otherwise used.5 Agricultural residues are wheat

straw, corn stover, and a number of other major agricultural crops.6 Energy crop data are for hybrid poplar,

willow, and switchgrass grown on crop land, pasture land, or on Conservation Reserve Program lands.7

The maximum amount of resources in each supply category is shown in Table 74.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 153
Landfill-Gas-to-Electricity Submodule

Background

Landfill-gas-to-electricity capacity competes with other technologies using supply curves that are based on

the amount of “high”, “low”, and “very low” methane producing landfills located in each EMM region. An

average cost-of-electricity for each type of landfill is calculated using gas collection system and electricity

generator costs and characteristics developed by EPA’s “Energy Project Landfill Gas Utilization Software”

(E-PLUS).8

Assumptions

• Gross domestic product (GDP) and population are used as the drivers in an econometric equation

that establishes the supply of landfill gas.

• Recycling is assumed to account for 35 percent of the total waste stream by 2005 and 50 percent by

2010 (consistent with EPA’s recycling goals).

• The waste stream is characterized into three categories: readily, moderately, and slowly

decomposable material.

• Emission parameters are the same as those used in calculating historical methane emissions in the

EIA’s Emissions of Greenhouse Gases in the United States 2003.9

154 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 

Coal Demand

Region States AgriculturalResidue

Energy

 Crops Forestry Residue

Urban Wood

 Waste/Mill

 Residue

Total1

1. NE CT, MA, ME, NH, RI, VT 0 17 70 15 102

2..YP NY, PA, NJ 22 95 45 59 221

3. SA WV, MD, DC, DE, VA, NC, SC 72 272 429 56 829

4. GF GA, FL 4 115 158 47 325

5. OH OH 97 86 167 17 366

6. EN IN, IL, MI, WI 726 286 426 47 1,485

7. KT KY, TN 27 385 265 30 706

8. AM AL, MS 0 281 37 19 338

9. CW MN, IA, ND, SD, NE, MO, KS 1085 1,231 190 28 2,534

10. WS TX, LA, OK, AR 14 632 152 57 855

11. MT MT, WY, ID 26 20 326 25 397

12. CU CO, UT, NV 53 1 155 7 215

13. ZN AZ, NM 17 0 378 7 403

14. PC AK, HI, WA, OR, CA 76 0 100 83 259

Total U.S. 2,218 3,422 2,898 497 9,034

Table 74. 2020 Maximum U.S. Biomass Resources, by Coal Demand Region and Type

(Trillion Btu)

1May include rounding error.

Sources: Urban Wood Wastes: Antares Group Inc., Biomass Residue Supply Curves for the U.S (updated), prepared for the

National Renewable Energy Laboratory, June 1999; Agricultural residues, energy crops, and forestry residues from the

University of Tennessee Department of Agricultural Economics POLYSIS model, 2007.
• The ratio of “high”, “low”, and “very low” methane production sites to total methane production is

calculated from data obtained for 156 operating landfills contained in the Government Advisory

Associates METH2000 database.10

• Cost-of-electricity for each site was calculated by assuming each site to be a 100-acre by 50-foot

deep landfill and by applying methane emission factors for “high”, “low”, and “very low” methane

emitting wastes.

Conventional Hydroelectricity

The conventional hydroelectricity submodule represents U.S. potential for new conventional hydroelectric

capacity 1 megawatt or greater from new dams, existing dams without hydroelectricity, and from adding

capacity at existing hydroelectric dams. Summary hydroelectric potential is derived from reported lists of

potential new sites assembled from Federal Energy Regulatory Commission (FERC) license applications

and other survey information, plus estimates of capital and other costs prepared by the Idaho National

Engineering and Environmental Laboratory (INEEL).11 Annual performance estimates (capacity factors)

were taken from the generally lower but site specific FERC estimates rather than from the general estimates

prepared by INEEL, and only sites with estimated costs 10 cents per kilowatthour or lower are included in the 

supply. Pumped storage hydro, considered a nonrenewable storage medium for fossil and nuclear power, is

not included in the supply; moreover, the supply does not consider offshore or in-stream hydro, efficiency or

operational improvements without capital additions, or additional potential from refurbishing existing

hydroelectric capacity.

In the hydroelectricity submodule, sites are first arrayed by NEMS region from least to highest cost per

kilowatthour. For any year’s capacity decisions, only those hydroelectric sites whose estimated levelized

costs per kilowatthour are equal to or less than an EMM determined avoided cost (the least cost of other

technology choices determined in the previous decision cycle) are submitted. Next, the array of

below-avoided cost sites is parceled into three increasing cost groups, with each group characterized by the

average capacity-weighted cost and performance of its component sites. Finally, the EMM receives from the

conventional hydroelectricity submodule the three increasing-cost quantities of potential capacity for each

region, providing the number of megawatts potential along with their capacity-weighted average overnight

capital cost, operations and maintenance cost, and average capacity factor. After choosing from the supply,

the EMM informs the hydroelectricity submodule, which decrements available regional potential in

preparation for the next capacity decision cycle.

Legislation and Regulations

Energy Policy Act of 1992 (EPACT92) and 2005 (EPACT05)

The RFM includes the investment and energy production tax credits codified in the Energy Policy Act of 1992 

(EPACT 92) as amended. The investment tax credit established by EPACT 92 provides a credit to Federal

income tax liability worth 10 percent of initial investment cost for a solar, geothermal, or qualifying biomass

facility. This credit was temporarily raised to 30 percent for some solar projects and extended to residential

projects. This change is reflected in the commercial and residential modules, but is not reflected for

utility-scale installations, where impacts are expected to be minimal and not in a timeframe to impact the

multi-year capacity planning process being modeled. The production tax credit, as established by EPACT

92, applied to wind and certain biomass facilities. As amended, it provides a 2 cent tax credit for every

kilowatt-hour of electricity produced for the first 10 years of operation for a facility constructed by December

31, 2007. The value of the credit, originally 1.5 cents, is adjusted annually for inflation. With the various

amendments, the production tax credit is available for electricity produced from qualifying geothermal,

animal waste, certain small-scale hydroelectric, landfill gas, municipal solid waste, and additional biomass

resources. Poultry litter and geothermal resources receive a 2 cent tax credit for the first 10 years of facility

operations. All other renewable resources receive a 1 cent tax credit for the first 10 years of facility

operations. The investment and production tax credits are exclusive of one another, and may not both be

claimed for the same facility.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 155
Alternative Renewable Cases

Renewable Technology Cases

Two cases examine the effect on energy supply using alternative assumptions for cost and performance of

non-hyrdo, non-landfill gas renewable energy technologies. The High Renewable Cost case examines the

effect if technology costs were to remain at current levels. The Low Renewable Cost case examines the

effect if technology energy costs were reduced by 2030 to 10 percent below Reference case values. 

The High Renewable Cost case does not allow “learning-by-doing” effects to reduce the capital cost of

biomass, geothermal, solar, or wind technologies or to improve wind capacity factor beyond 2008 levels. 

The construction of the first four units of biomass integrated gasification combined cycle units are still

assumed to reduce the technological optimism factor associated with this technology. All other parameters

remain the same as in the Reference case.

The Low Renewable Cost case assumes that the non-hydro, non-landfill gas renewable technologies are

able to reduce their overall cost-of-energy produced in 2030 by 10 percent from the Reference case. 

Because the cost of supply of renewable resources is assumed to increase with increasing utilization (that is, 

the renewable resource supply curves are upwardly sloping), the cost reduction is achieved by targeting the

reduction on the “marginal” unit of supply for each technology in 2030 for the Reference case (that is, the

next resource available to be utilized in the Reference case in 2030). This has the effect of reducing costs for 

the entire supply (that is, shifting the supply curve downward by 10 percent). As a result of the overall

reduction in costs, more supply may be utilized, and a unit from higher on the supply curve may result in

being the marginal unit of supply. Thus the actual market-clearing cost-of-energy for a given renewable

technology may not differ by much from the Reference case, although that resource contributes more energy 

supply than in the Reference case. These cost reductions are achieved gradually through

“learning-by-doing”, and are only fully realized by 2030.

For biomass, geothermal, and solar technologies, this cost reduction is achieved by a reduction in overnight

capital costs sufficient to achieve the 10 percent targeted reduction in cost-of-energy. As a result, the supply 

of biomass fuel is increased by 10 percent at every price level. For geothermal, the capital cost of the

lowest-cost site available in the year 2005 is reduced such that if it were available for construction in 2030, it

would have a 10 percent lower cost-of-energy in the High Renewable case than the cost-of-energy it would

have in 2030 were it available for construction in the Reference case. For solar technologies (both

photovoltaic and solar thermal power), the resource is assumed to be unlimited and the reductions in

cost-of-energy are achieved strictly through capital cost reduction.

Observation of wind energy markets indicates that improvements in performance (as measured by capacity

factor) have, in recent years, dominated reductions in capital cost as a means of reducing cost-of-energy. 

Therefore, in the Low Renewable Cost case, the reduction in wind levelized cost comes from both modestly

reduced capital cost and improved capacity factor. Other assumptions within NEMS are unchanged from

the Reference case.

For the Low Renewable Cost case, demand-side improvements are also assumed in the renewable energy

technology portions of residential and commercial buildings, industrial processes, and refinery fuels

modules. Details on these assumptions can be found in the corresponding sections of this report.

State RPS Programs

Starting with AEO 2008, EIA represents various state-level policies generally referred to as Renewable

Portfolio Standards (RPS). These policies vary significantly among states, but typically require the addition

of renewable generation to meet a specified share of state-wide generation. Any non-discretionary

limitations on meeting the generation or capacity target are modeled to the extent possible. However,

because of the complexity of the various requirements, the regional target aggregation (described below),

and nature of some of the limitations (also described below), measurement of compliance is assumed to be

approximate.

156 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 
For the AEO2008, regional renewable generation targets were estimated using the renewable generation

targets in each state within the region. In many cases, regional boundaries intersect state boundaries; in

these cases states were assigned to be within a single region, based on EIA expert judgment of factors such

as predominant load locations and location of renewable resources eligible for that state’s RPS program. 

Using state-level RPS compliance schedules and preliminary estimates of projected sales growth, EIA

estimated the amount of renewable generation required in each state within a region. Required generation

in each state was then summed to the regional level for each year, and a regional renewable generation

share of total sales was determined, as shown in Table 75.

Only targets with established enforcement provisions or established state funding mechanisms were

included in the calculation; goals, provisional RPS requirements, or requirements lacking established

funding were not included. The California and New York programs require state funding, and these

programs are assumed to be complied with only to the extent that state funding allows. Compliance

enforcement provisions vary significantly among states and most states have established procedures for

waiving compliance through the use of “alternative compliance” payments, penalty payments, discretionary

regulatory waivers, or retail price impact limits. Because of the variety of mechanisms, even within a given

electricity market region, these limits are not modeled.

Supplemental and Floor Capacity Additions 

For AEO2008, EIA has continued its tradition of supplemental and floor renewable capacity additions. All

specific project listings in Table 76 have been independently verified by EIA, with the exception of landfill gas

listings that were obtained through EPA. In total, 6.4 gigawatts of capacity are represented in these listings. 

For 2008 and beyond, the capacity additions are a preview of the limited data EIA currently has on new

projects. Listings additional for these years should not be viewed as comprehensive. This list of projects

does not represent renewable capacity that will be induced by State RPS programs beyond 2007.

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 157

Region12015 2025 2030

ECAR 0% 0% 0%

ERCOT 5% 5% 5%

MAAC 9% 13% 13%

MAIN 6% 12% 12%

MAPP 9% 11% 11%

NY2

* * *

NE 8% 12% 12%

FL 0% 0% 0%

STV 1% 2% 2%

SPP 0% 0% 0%

NWP 7% 12% 12%

RA 4% 7% 7%

CNV3

* * *

Table 75. Aggregate Regional RPS Requirements

1 See chapter on the electricity Market Module for a map of the electricity regions

2New York is not projected to meet RPS targets because of funding limitations. EIA projects that currently authorized funds will

support 2.5 billion kilowatthours of new renewable generation by 2015.

3California is not projected to meet RPS targets because of funding limitations. EIA projects that currently authorized funds will

support the addition of 700 MW of additional renewable capacity through 2011.
158 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 

Technology Plant Identification State

Net

Summer

Capability

(Megawatts)

On-Line

Years

Biomass Okeelanta Cogeneration FL 40 2007

Fibrominn Biomass Power Plant MN 55 2007

Sierra Pacific Burlington Facility WA 25 2007

Plant Carl Project GA 20 2007

MN Poultry Litter MN 55 2007

Rough and Ready Lumber Biomas Project OR 1.7 2007

Lincoln Paper & Tissue ME 10 2007

Snowflake White Mountain Power Plant AZ 24 2008

Geothermal Galena Unit 2 NV 4.5 2007

Raft River Geothermal Power Plant ID 9.8 2007

Salt Wells Geothermal NV 11 2007

Stillwater Addition NV 15 2007

Steamboat Hills NV 4 2007

Blundell Expansion (Roosevelt Hot Springs) UT 11 2007

Galena Unit 3 NV 12.8 2008

Landfill Gas (including mass-burn waste) C& E Electric MI 2.3 2007

Ocean County Landfill NJ 9.6 2007

Seven Mile Creek LFG WI 0.8 2007

Horry Land Fill Gas Site SC 1.1 2007

Tullytown Land Fill PA 2.2 2007

Coventry LFG VT 1.6 2007

GROWS Land Fill PA 2.5 2007

Seccra Land Fill PA 0.8 2007

Rumpke/Pendleton County Land Fill KY 3.2 2007

Sauk County Land Fill WI 0.4 2007

Cape May County Land Fill NNJ 0.3 2007

Newland Park Land Fill MD 3.1 2007

Dry Creek Landfill OR 3.2 2007

Lee County Solid Waste Energy FL 16 2007

Lee County Landfill SC 1.9 2008

Central Station Photovoltaics (PV) SunE Alamosa CO 8 2007

Springerville Expansion 2008 C AZ 1 2008

Springerville Expansion 2009 C AZ 1 2009

Springerville Expansion 2010 C AZ 1 2010

Solar Thermal Eldorado Solar Thermal NV 66.5 2007

Solargenix Solar Thermal Project NV 64 2007

Conventional Hydro Gross Hydro Plant CO 7.8 2007

Manitou Springs CO 0.5 2007

Lower St. Anthony Falls MN 9 2008

Castle Creek Hyrdoplant CO 1 2009

Table 76. Planned U.S. Central Station Generating Capacity Using Renewable Resources for 2004 and

 Beyond1
Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 159

Technology Plant Identification State

Net

Summer

Capability

(Megawatts)

On-Line

Years

Wind Alta Mesca Phase IV CA 40 2007

Sweetwater Wind Phase IV TX 241 2007

Twin Groves Wind Farm Phase I IL 198 2007

Cedar Creek Wind CO 300 2007

Sweetwater Wind5 TX 81 2007

Pakini Nui Wind Farm HI 21 2007

Top of Iowa Windfarm III IA 29.4 2007

Lone Star Wind Farm (frmly

 Cross Timbers) TX 200 2007

Wildorado Wind Ranch TX 161 2007

Mars Hill Wind Farm Project ME 42 2007

Allegheny Ridge Wind Farm PA 80 2007

MinnDakota Wind SD 150 2007

Twin Buttes Wind Farm CO 75 2007

Klondike Windpower Phase III OR 221 2007

Locust Ridge PA 26 2007

Sand Bluff TX 90 2007

Post Oak Wind LLC TX 200 2007

Biglow Canyon Wind Farm OR 125.4 2007

Smoky Hills Windfarm KS 100.8 2007

Mount Storm Wind Project WV 164 2007

Pomeroy Wind IA 123 2007

Scurry County Wind TX 130.5 2007

Cow Branch Wind Power MO 50.4 2007

CR Cleaning House Wind MO 50.4 2007

Loess Hills Wind Farm MO 5 2007

Bluegrass Ridge Wind Phase I MO 33.4 2007

Peetz Wind Farm CO 400 2007

Steel Winds Wind Farm NY 20 2007

Snyder Wind Farm TX 63 2007

Langdon Wind Farm ND 159 2007

Old Trail Wind Farm IL 198 2007

Fenton Wind Energy MN 205 2007

Consent Decree Wind Phase I OH 3.7 2007

Diamond Willow Wind MT 20 2007

Elkoorn Valley Wind OR 101 2007

Endeavor Wind Project IA 100 2007

Table 76. Planned U.S. Central Station Generating Capacity Using Renewable Resources for 2004 and

 Beyond1 (cont)
160 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 

Technology Plant Identification State

Net

Summer

Capability

(Megawatts)

On-Line

Years

Good Know Windfarm WA 94 2007

Prairie Star Wind Farm MN 100 2007

Cedar Ridge Wind WI 68 2008

Top of Iowa Windfarm II IA 80 2008

Blue Sky Green Field Wind Projcet WI 145 2008

Marengo Wind Plant WA 140.4 2008

White Creek Wind Farm WA 204 2008

Oliver Wind Phase II ND 48 2008

Champion Wind Farm TX 126.5 2008

Roscoe Wind Farm TX 209 2008

Clinton Wind Farm NY 100.5 2008

Ellenurg Wind Farm NY 81 2008

Bliss Windpark Phase II NY 100.5 2008

Harvest Wind Farm MI 53 2008

Taconite Ridge Energy Center MN 25 2008

Tehachapi Wind I CA 0.6 2009

Tehachapi Wind Resource II CA 15.3 2009

North Dakota Wind Expansion ND 100 2009

Consent Decree Wind Phase Ii OH 19.3 2009

Table 76. Planned U.S. Central Station Generating Capacity Using Renewable Resources for 2004 and

 Beyond1 (Cont.)

1Includes reported information and EIA estimates for goals, mandates, renewable portfolio standards (RPS), and California

Assembly Bill 1890 required renewables.

2Regional estimates developed by EIA.

Source: Energy Information Administration, Office of Integrated Analysis and Forecasting, based on publicly available information

about specific projects, state renewable portfolio standards, mandates, goals, and commercial and other plans.
[1] For a comprehensive description of each submodule, see Energy Information Administration, Office of

Integrated Analysis and Forecasting, Model Documentation, Renewable Fuels Module of the National

Energy Modeling System, DOE/EIA-M069(2005), (Washington, DC, March 2005).

[2] Revising the Long Term Multipliers in NEMS: Quantifying the Incremental Transmission Costs Due to

Wind Power, Report to EIA from Princeton Energy Resources International, LLC. May 2007.

[3] Wiser, Ryan and Mark Bollinger. Annual Report on U.S. Wind Power Installation, Cost, and

Performance Trends: 2006. U.S. Department of Energy, Office of Energy Efficiency and Reneweable

Energy. May 2007.

[4] United States Department of Agriculture, U.S. Forest Service, "Forest Resources of the United States, 

1992", General Technical Report RM-234, (Fort Collins CO, June 1994).

[5] Antares Group Inc., "Biomass Residue Supply Curves for the U.S (updated)", prepared for the

National Renewable Energy Laboratory, June 1999.

[6] Walsh, M.E., et.al., Oak Ridge National Laboratory, "The Economic Impacts of Bioenergy Crop

Production on U.S. Agriculture", (Oak Ridge, TN, May 2000), http://bioenergy.ornl.gov/papers/wagin/

index.html.

[7] Graham, R.L., et.al., Oak Ridge National Laboratory, “The Oak Ridge Energy Crop County Level

Database”, (Oak Ridge TN, December, 1996).

[8] U.S. Environmental Protection Agency, Atmospheric Pollution Prevention Division, Energy Project

Landfill Gas Utilization Software (E-PLUS) Version 1.0, EPA-430-B-97-006 (Washington, DC, January

1997).

[9] Energy Information Administration, "Emissions of Greenhouse Gases in the United States 2003",

DOE/EIA-0573(2003) (Washington, DC, December 2004).

[10] Governmental Advisory Associates, Inc., METH2000 Database, Westport, CT, January 25, 2000.

[11] Douglas G. Hall, Richard T. Hunt, Kelly S. Reeves, and Greg R. Carroll, Idaho National Engineering and

Environmental Laboratory, "Estimation of Economic Parameters of U.S. Hydropower Resources"

INEEL/EXT-03-00662 (Idaho Falls, Idaho, June 2003).

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 161

Notes and Sources

Appendix A: Handling of Federal and

Selected State Legislation and

Regulation in the Annual Energy Outlook
164 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

AppendixA: Handling of Federal and Selected State Legislation and Regulation in the Annual Energy Outlook

Legislation Brief Description AEO Handling Basis

Residential Sector

A. National Appliance Energy

 Conservation Act of 1987

Requires Secretary of Energy to

set minimum efficiency

standards for 10 appliance

categories.

Included for categories

represented in the AEO

residential sector forecast.

 a. Room Air Conditioners Current standard of 9.8 EER Federal Register Notice of Final

Rulemaking.

 b. Other Air Conditioners

 (<5.4 tons)

Current standard 10 SEET for

central air conditioners and heat

pumps, increasing to 13 SEER

in 2006.

Federal Register Notice of Final

Rulemaking.

 c. Water Heaters Electric: Current standard .90

EF. Gas: Current standard .59

EF.

Federal Register Notice of Final

Rulemaking.

 d. Refrigerators/Freezers

 kWh/yr

Current standard of .51 Federal Register Notice of Final

Rulemaking.

 e. Dishwashers Current standard of .46 EF. Federal Register Notice of Final

Rulemaking.

 f. Fluorescent Lamp

 Ballasts

Current standard of .90 power

factor

Federal Register Notice of Final

Rulemaking.

 g. Clothes Washe rs Current standard of 1.18 EF,

increasing to 1.04 MEF in 2004,

further increasing to 1.26 MEF

in 2007.

Federal Register Notice of Final

Rulemaking.

 h. Furnaces Standard set at 78 AFUE for

gas and oil furnaces.

Federal Register Notice of Final

Rulemaking.

 i. Clothes Dryers Gas: Current standard 2.67 EF.

Electric: Current standard 3.01

EF. The increase in MEF for

clothes washers further

increases the de facto standard

for clothes dryers due to better

extraction of water from clothes

in washing process.

Federal Register Notice of Final

Rulemaking.

B. Energy Policy Act of 1992 (EPACT92)

 a. Building Codes For the IECC 2006, specifies

whole house efficiency

minimums.

Assumes that all States adopt

the IECC 2006 code by 2017.

Trend of States adoption to

codes, allowing for lead times

for enforcement and builder

compliance.

 b. Energy-Efficient

 Mortgages

Allow homeowners to qualify for

higher loan amounts if the home

is energy-efficient, as scored by

HERS.

Efficiency of equipment

represented in technology

choice parameters. Efficiency

of shell represented in HVAC

choice.

No way to separate out these

purchases from others.

Assumes historical effect in the

forecast, with cost-reducing

learning in the shell portion of

HVAC choice.

C. Energy Policy Act of 2005 (EPACT05)

 a. Torchiere Lamp

 Standard

Sets 190 watt bulb limit in 2006. EPACT05.

 b. Ceiling Fan Light Kit

 Standard

Ceiling fans must be shipped

with compact fluorescent bulbs

or use no more than 190 watts

per fixture in 2007.

Reduce lighting electricity

consumption by appropriate

amount.

Number of ceiling fan shipments

and estimated kWh savings per

unit determine overall savings.
Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 165

Legislation Brief Description AEO Handling Basis

 c. Dehumidifier Standard Sets standard for dehumidifiers

in 2007 and 2012.

Reduce miscellaneous

electricity consumption by

appropriate amount.

Number of dehumidifier

shipments and estimated kWh

savings per unit determine

overall savings.

 d. Energy-Efficient

 Equipment Tax Credit

Purchasers of certain energyefficient equipment can claim

tax credits in 2006 and 2007.

Reduce cost of applicable

equipment by specified amount.

EPACT05.

 e. New Home Tax Credit Builders receive $1000 or

$2000 tax credit if they build

homes 30 or 50 percent better

than code in 2006 and 2007.

Reduce shell package cost for

these homes by specified

amount.

Cost reductions to consumers

are assumed to be 100 percent

of the builder’s tax credit.

 f. Energy-Efficient

 Appliance Tax Credit

Producers of energy-efficient

refrigerators, dishwashers, and

clothes washers receive tax

credits for each unit they

produce that meets certain

efficiency specifications.

Assume the cost savings are

passed on to the consumer,

reducing the price of the

appliance by the specified

amount.

Cost reductions to consumers

are assumed to be 100 percent

of the producer’s tax credit.

D. Energy Independence and Security Act of 2007

 a. General Service

 Incandescent Lamp

 Standard

Require less wattage for bulbs

in 2012-2014 and 2020.

reduce wattage for new bulbs by

28 percent in 2013 and 67

percent in 2020.

EISA 2007

 b. Dehumidifier Standard Updates EPACT 2005 standard. Reduce miscellaneous

electricity consumption by

appropriate amount.

Increase savings estimated for

EPACT 2005 by appropriate

amount.

 c. Boiler Standard Sets standards for boilers in

2013.

Require new purchases of

boilers to meet the standard.

EISA 2007

 d. Dishwasher Standard Sets standards for dishwashers

in 2010.

Require new purchases of

dishwashers to meet the

standard by 2010.

EISA 2007

 e. External Power Supply

 Standard

Sets standards for external

power supplies in 2008

Reduce miscellaneous

electricity consumption by

appropriate amount.

Number of shipments and

estimated kWh savings per unit

determine overall savings.

 f. Manufactured Housing

 Code

Require manufactured homes to

meet latest IECC in 2011.

Require that all manufactured

homes shipped after 2011 meet

the IECC 2006

EISA 2007

Commercial Sector

A. National Appliance Energy

 Conservation Act of 1987

Requires Secretary of Energy to

set minimum efficiency

standards for 10 appliance

categories.

Included for categories

represented in the AEO

commercial sector forecast.

 a. Room Air Conditioners Current standard of 9.8 EER Federal Register Notice of Final

Rulemaking.

 b. Other Reside ntial-size Air

 Conditioners (<5.4 tons)

Current standard 10 SEER for

central air conditioning and heat

pumps, increasing to 13 SEER

in 2006.

Federal Register Notice of Final

Rulemaking.

 c. Fluorescent Lamp

 Ballasts

Current standard if .90 power

factor and minimum efficacy

factor for F40 and F96 lamps

based on lamp size and

wattage, increasing to higher

efficacy factor in 2005 that limits

purchases to electronic ballasts.

Federal Register Notice of Final

Rulemaking.
Legislation Brief Description AEO Handling Basis

166 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

B. Energy Policy Act of 1992 (EPACT92)

 a. Buildings Codes Incorporated in commercial

building shell assump tions. 

Efficiency of new relative to

existing she ll represente d in

shell efficiency indices. 

Assume shell efficiency

improves 5 and 7 percent by

2030 for existing buildings and

new construction, respe ctively.

Based on Arthur D. Little

commercial shell indices

developed for EIA in 1998,

updated to 1999 CBECS

building stock. 

 b. Window labeling Designed to help co nsumers

determine which windows are

more energy efficient.

Incorporated in commercial

building shell assump tions. 

Efficiency of new relative to

existing shell represented I

shell efficiency indices. 

Assume shell efficiency

improves 5 and 7 percent by

2030 for existing buildings and

new construction, respe ctively.

Based on Arthur D. Little

commercial shell indices

developed for EIA in 1998,

updated to 1999 CBECS

building stock.

 c. Commercial Furnaces

 and Boilers

Gas-fired furnaces a nd boilers: 

Current standard is 0.80

thermal ef ficiency. Oil

furnaces and boilers: Current

standard is 0.81 thermal

efficiency for furnaces, 0.83

thermal efficiency for boilers.

Public Law 102-486:

EPACT92. Federal Register

Notice of Final Rulemaking.

 d. Commerc ial Air 

 Conditioners and Heat

 Pumps 

Air-cooled air conditioners and

heat pumps less than 135,000

Btu: Current standard of 8.9

EER. Air-c ooled air

conditioners and heat pumps

greater than 135,000 Btu:

Current standard of 8.5 EER.

Public Law 102-486:

EPACT92. 

 e. Commercial Water

 Heaters

Natural gas and oil: EPACT

standard .78 thermal efficiency

increasing to .80 thermal

efficiency for gas units in 2003 . 

Public Law 102-486:

EPACT92. Federal Register

Notice of Final Rulemaking.

 f. Lamps Incandescent: Current

standard 16.9 lum ens per watt. 

Fluorescent: Current sta ndard

75 and 80 lumens per watt for

4 and 8 foot lamps,

respectively.

 g. Electric Motors Specifies minimum efficiency

levels for a variety of motor

types and sizes.

End-use services modeled at

the equipment lev el. Motors

contained in new equipment

must meet the standards.

Public Law 102-486:

EPACT92. 

 h. Federal Energy

 Management

Requires Federal agen cies to

reduce energy consumption 20

percent by 2000 relative to

1985.

Superseded by Executive

Order 13123 and EPACT05.

Superseded by Executive

Order 13123.

 I. Business Investment

 Energy Cred it

Provides a permanent 10

percent inv estmen t tax credit

for solar property.

Tax credit incorporated in cash

flow for solar generation

systems. Investment cost

reduced 10 percent for solar

water heaters.

Public Law 102-486:

EPACT92.

C. Executive Order 13123,

 “Greening the Government

 Through Efficient Energy

 Management

Requires Federal agen cies to

reduce energy consumption 30

percent by 2005 and 35

percent by 2010 relative to

1985 through life-cycle cos teffective energy measures.

Superseded by EPACT05 and

EISA07.

Superseded by EPACT05 and

EISA07.
Legislation Brief Description AEO Handling Basis

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 167

D. Energy Policy Act of 2005 (EPACT05)

 a. Comm ercial Pack age Air

 Conditioners and Heat

 Pumps

Sets min imum e fficiency lev els

in 2010.

Air-cooled air conditioners/heat

pumps less tha n 135,000 Btu: 

standard of 11.2/11.0 EER and

heating COP of 3.3 . Aircooled air conditioners/heat

pumps greater than 135,000

Btu: standard of 11.0 /10/6

EER and heating COP of 3.2.

Public Law 109-58: EPACT05.

 b. Commercial

 Refrigerators, Freezers,

 and Autom atic

 Icemakers

Sets min imum e fficiency lev els

in 2010 based on volume.

Set standard by level of

improvement above stock

average efficiency in 2003.

Public Law 109-58: EPACT05.

 c. Lamp Ballasts Bans manufacture or import of

mercury v apor lamp ballasts in

2008. Sets minimum efficacy

levels fir T12 energy saver

ballasts in 2009 and 2010

based on application.

Remove mercury vapor

lighting system from

technolog y choice m enu in

2008. Set minimum efficacy of

T12 ballasts at specified

standard levels.

Public Law 109-58: EPACT05.

 d. Compact Fluores cent 

 Lamps

Sets standard for medium

base lamps at Energy Star

requirements in 2006.

Set efficacy level of compact

fluorescent lamps at required

level. 

Public Law 109-58: EPACT05.

 e. Illuminated Exit Signs

 and Traffic S ignals

Set standards at Energy Star

requirements in 2006.

Reduce miscellaneous

electricity consumption by

appropriate amou nt.

Number of shipments, share of

shipments that currently meet

standard, and estimated kWh

savings per unit determine

overall savings.

 f. Distribution Transformers Sets standard as National

Electrical Manufactu rers

Association Class I Efficiency

levels in 2007.

Effects of the stand ard are

included in estimating the

share of miscellaneous

electricity consumption

attributable to transformer

losses.

Public Law 109-58: EPACT05.

 g. Prerinse Spray Valves Sets maximu m flow rate to 1.6

gallons per minute in 2006.

Reduce energy use for water

heating by appropriate am ount.

Number of shipments, share of

shipments that currently meet

standard, and estimated kWh

savings per unit determine

overall savings.

 h. Federal Energy

 Management

Requires Federal agen cies to

reduce energy consumption 20

percent by 2015 relative to

2003 through life-cycle cos teffective energy measures.

The Federal “share” of the

commercial sector uses the 10

year treasury bond rate as a

discount rate in equipment

purchase decisions as

opposed to adding risk

premiums to the 10 year

treasury bond rate to develop

discount rates for other

commercial decisions.

Public Law 109-58: EPA CT05. 

Superseded by EISA07.

 I. Business Investment Tax

 Credit for Fuel Cells and

 Microturbines

Provides a 30 percent

investment tax credit for fuel

cells and a 10 percent

investment tax credit for

microturbines installed in 2006

through 2008.

Tax credit incorporated in cash

flow for fuel cells and

microturbines. 

Public Law 109-58: EPA CT05. 

Extended through 2008 by

Public Law 109-432

 j. Business Solar

 Investm ent Tax Cre dit

Provides a 30 percent

investment tax credit for solar

property installed in 2006

through 2008.

Tax credit incorporated in cash

flow for solar generation

systems, investment cost

reduced 30 percent for solar

water heaters.

Public Law 109-58: EPA CT05. 

Extended through 2008 by

Public Law 109-432.
Legislation Brief Description AEO Handling Basis

168 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

E. Energy Independence and Security Act of 2007 (EISA07)

 a. Comm ercial W alk-in

 Coolers and Walk-in

 Freezers

Requires u se of spec ific

energy effic iency me asures in

equipment manufactured in or

after 2009.

Set standard by equivalent

level of improvement above

stock av erage efficie ncy in

2003.

Public Law 110-140: EISA97.

 b. Incandescent and

 Halogen lamps

Sets ma ximum a llowable

wattage based on lumen

output starting in 2012.

Remove incandescent and

halogen general service

lighting systems that do not

meet standard from technology

choice menu in 2012.

Public Law 110-140: EISA97.

 c. Metal Halide Lamp

 Ballasts

Sets min imum e fficiency lev els

for metal halide lamp ba llasts

starting in 2009.

Remove metal halide lighting

systems that do not meet

standard from technology

choice menu in 2009. Set

minimum s ystem efficiency to

include specified standa rd

levels for ballasts - ranging

from 88 to 94 percent based

on ballast type.

Public Law 110-140: EISA97.

 d. Federal Use of Energy

 Efficient Lighting

Requires use of energy

efficient lighting fixtures and

bulbs in Federal buildings to

the maxim um exten t possible

starting in 2009.

Increase proportion of sector

using 10 year treasury bond

rate for lighting purchase

decisions to represen t all

existing and new Federal

floorspace in 2009.

Public Law 110-140: EISA97.

 e. Federal Energy

 Management

Requires Federal agen cies to

reduce energy consumption

per square foot 30 percent by

2015 relative to 2003 through

life-cycle cost-effective energy

measures.

The Federal “share” of the

commercial sector uses the 10

year treasury bond rate as a

discount rate in equipment

purchase decisions as

opposed to adding risk

premiums to the 10 year

treasury bond rate to develop

discount rates for other

commercial decisions.

Public Law 110-140: EISA97.

Industrial Sector

A. Energy Policy Act of 1992 (EPACT92)

 a. Motor Efficiency

 Standards

Specifies minimum efficiency

levels for a variety of motor

types and sizes.

New motors must meet the

standards.

Standard specified in

EPACT92. 10 CFR 431.

 b. Boiler Efficiency 

 Standards

Specifies minimum combustion

efficiency for package b oilers

larger than 300,000 Btu /hr. 

Natural Gas boilers: 80

percent, oil boilers: 83 percent.

All package boilers are

assumed to meet the efficiency

standards. While the

standards do not apply to fielderected boilers, which are

typically used in steamintensive industries, we

assume they meet the

standard in the AEO.

Standard specified in

EPACT92. 10 CFR 431.

B. Clean Air Act Amendments (CCCA90)

 a. Process Emissions Numerous process emissions

requirements for specified

industries and/or activities.

Not modeled be cause they are

not directly related to energy

projections.

CAAA90, 40 CFR 60.

 b. Emissions related to

 hazardous/toxic 

 substances

Numerous emissions

requirements relative to

hazardous and/or toxic

substances.

Not modeled be cause they are

not directly related to energy

projections.

CAAA90, 40 CFR 60.

 c. Industrial SO2

 emissions

Sets annual limit for industrial

SO2 emissions at 5.6 million

tons. If limit is reached,

specific regulations could be

implemented.

Industrial SO2 em issions are

not projec ted to reac h the limit

(Source: E PA, Nation al Air

Pollutant Emissions Trends:

1990-1998, EPA-454/R-00-

002, March 200 0, p. 4-3.)

CAAA90, Section 406 (42 USC

7651)
Legislation Brief Description AEO Handling Basis

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 169

 d. Industrial boiler

 hazardous air pollutants

Requires industrial boilers and

process heaters to meet

emissions limits on HAPs to

comply with the Maximum

Achievable Control Technology

(MACT) floor. 

Not explicitly modeled because

new boilers are expected to

meet the standards in the

absence of the rule an d retrofit

costs sh ould be relativ ely

small. 

Environmental Protection

Agency, National Emissions

Standard s for Hazardo us Air

Pollutants f or Industria l,

Commercial, and Institutional

Boilers and Process Heatrates,

40 CFR Part 63. 

 e. Emissions from

 stationary diesel

 engines

Requires engine

manufacturers to meet the

same emission standards as

nonroad d iesel engine s. Fully

effective in 2011.

New stationary engines meet

the standards.

40 CFR Parts 60, 85, 89, 94,

1039, 1065, and 1068.

C. Energy Policy Act of 2005 (EPACT 05)

 a. Physical Energy

 Intensity

Voluntary comm itments to

reduce physical energy

intensity by 2.5 percent

annually for 2007-2016.

Not modeled because

participation is voluntary;

actual reductions will depend

on future, u nknown

commitments.

EPACT2005, Section 106 (42

USC 15811)

 b. Mineral components of

 cement of conc rete

Increase in mineral component

of Federally procured cement

or concrete.

Not mod eled beca use spec ific

proportion will be specified in

the future.

EPACT2005, Section 108 (42

USC 6966).

 c. Tax credits for coke 

 oven

Provides a tax credit of $3.00

per barrel oil equivalent,

limited to 4000 barrels per day

average. Applies to most

producers of coal coke or coke

gas.

Not modeled because no

impact on U.S. coke plant

activity is anticipated.

EPACT2005, Section 1321 (29

USC 29).

 d. Emissions from stationary

 diesel engines

Requires engine manufactures

to meet the same emission

standards as nonroad diesel

engines. F ully effective in

2011.

New stationary engines meet

the standards

40 CFR Parts 60, 85, 89, 94,

1039, 1065, and 1068

D. The Energy Independence and Security Act of 2007

Motor Efficiency Standards Supersedes EPAct1992

Efficiency Standards no later

than 2011

Motor purchases must meet

the EPAct1992 standards

through 2010; afterwards

purchases must meet the

EISA2007 standards

EISA2007

Transportation Sector

A. Energy Policy Act of 1992

 (EPACT92)

Increases the number of

alternative fuel vehicles and

alternative fuel use in Fe deral,

State, and fuel provided fleets.

Assumes Federal, State and

fuel provider fleets meet the

mandated sales requirements.

Energy Policy Act of 1992,

Public Law 102-486-Oct. 24,

1992.

B. Low Em ission Veh icle

 Program (LEVP)

The Clean Air Act provides

California the authority to set

vehicle criteria emission

standards that exceed Federal

standards. Apart of that

program mandates the sale of

zero emission vehicles by

manufacturers, other

nonattainment. S tates are

given the option of op ting into

the Federa l or California

emission standards.

Incorporates the LEVP

program as amended on

August 4, 2005. Assumes

California, Connecticut, Maine,

Massachu setts, New Jersey,

New York, Rhode island,

Vermont, Oregon, and

Washington adopt the LEVP

program as amended August

4, 2005 and that the proposed

sales requirements for hybrid,

electric, and fuel cell vehicles

are met.

Section 17 7 of the Clea n Air

Act, 42 U.S.C. sec. 7507

(1976) and CARB, C alifornia

Exhaust Emissions Standards

and Test Procedures for

Passenger Ca rs, Light-Duty

Trucks, and M edium-Duty

Vehicles, August 4, 2005.

C. Light Vehicle GHG

 Emission Standards

California has enacted light

vehicle GHG emission

standards as part of the Low

Emission Vehicle Program

(A.B. 1493), which requires

that GHG emissions from new

light vehicle s be signific antly

reduced from 2009 to 2016.

AEO2008 does not

incorporate. EPA has denied

the California claim.

The alliance of Autom obile

Manufacturers and Several

California auto dealerships

filed suit against A.B. 1493 on

December 7, 2004.
Legislation Brief Description AEO Handling Basis

170 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

D. Corporate Average Fuel

 Economy (CA FÉ) 

 Standard

Requires manu facturers to

produce vehicles whose

average fuel economy meets a

minimum Fe deral standard. 

Cars and light trucks are

regulated separately.

The current CAFÉ standard for

cars is 27.5 mpg. The car

standard is unchange through

2011. The current CAFÉ

standard for light trucks is 22 .5

mpg, incr easing to 2 3.1 mpg in

2009, 23.5 mpg in 2010 and

24.0 mpg in 2011. The

assumed standard increases

to 41.0 mpg for ca rs and 30.5

mpg for light trucks in 2020.

Energy Policy Conservation

Act of 1975; Title 49 United

States Code, Chapter 329;

Federal Register, Vol. 68, No.

66, Monday, April 7, 2003; and

Federal Register, Vol. 71, No.

66, April 6, 2006. For 2011

and beyond, EISA 2007, Title I,

Section 102.

E. Electric, Hybrid, and

 Alternative Fuel Vehic le

 Tax Incentives

Federal tax incentives a re

provided to encourage the

purchase of electric, hy brid

and or alternative fuel

vehicles. For example, tax

incentives for hybrid vehicles

in the form of a $2,000 income

tax deduction.

Incorporates the Federal tax

incentives for hybrid and

electric vehicles.

IRS Technical Publication 535;

Business Expenses

F. The Working Families Tax

 Relief Act of 2004

The Act repeals the phase out

of the credits which were

allowed for qua lified electric

and clean fuel vehicles for

property acquired in 2004 and

2005. The credit is reduced by

75 percent for vehicles

acquired in 2 006. This will

provide an incentiv e to

purchase electric and clean

fuel vehicles.

The federal tax incentives are

embodie d in the cod e. This

will provide an incentive to

purchase electric and clean

fuel vehic les but little im pact is

realized on projections of total

highway energy use.

Sections 318 and 319 of the

Working families Tax Relief

Act of 2004.

G. State Electric, Hybrid, and

 Alternative Fuel Vehic le

 Tax and other incentives

Approximately 20 States

provide tax and other

incentives to encourage the

purchase of electric, hy brid

and or alternative fuel

vehicles. The tax incentives

are in the form of income

reductions, tax credits, and

exemptions. Other incentives

include use of HOV lanes and

exemptions from emissions

inspections from emissions

inspections and licens ing fees. 

The incentives offered and the

mix varies by state. For

example, Georgia offers a tax

credit of $5, 000 for elec tric

vehicles and O klahoma offers

a tax credit o f $1,500 fo r hybrid

and alternative fuel vehicles.

Does not incorporate State tax

and other incentives for hybrid,

electric, and other alternative

fuel vehicle.

State laws in Arizona,

Arkansas, California, Colorado,

Delaware, Florida, Georgia,

Iowa, Kansas, Louisiana,

Maine, Maryland, Michigan,

New Hampshire, New York,

Oklahoma, Pennsylvania,

Utah, Virginia, and

Washing ton. 

H. Energy Policy Act of 2005 Provides tax credits for the

purchase of vehicles that have

a lean burn engine or em ploy a

hybrid or fuel cell propulsion

system. The amount of the

credit receiv ed for a ve hicle is

based on the vehic le’s inertia

weight, improvem ent in city

tested fuel econom y relative to

an equivalent 2002 base year

value, emissions classification,

type of propulsion system, and

number of vehicles sold.

Incorporates the Federal tax

incentives for hybrid and fuel

cell vehicles.

Title XIII, Section 1341 of the

Energy Policy Act of 2005.
Legislation Brief Description AEO Handling Basis

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 171

Electric Power Generation

A. Clean Air Act Amendment

 of 1990

Established a national limit on

electricity generator emissions

of sulfur dioxide to be achieved

through a cap and trade

program.

Sulfur dioxide cap and trade

program is explicitly modeled,

choosing the optimal mix of

options for meeting the

national emissions c ap. 

Clean Air Act Amendments of

1990, Title IV, Sections 401

through 406, Sulfur Dioxide

Reduction Program, 42 U.S.C.

7651a through 7651e.

Set boiler typ e specific

nitrogen oxide emission s limits

for electricity generators.

Assum es each b oiler installs

the options neces sary to

comply with their nitrogen

oxide emissions limit.

Clean Air Act Amendments of

1990, Title IV, Sections 407,

Nitrogen Oxide Emission

Reduction Program, 42 U.S.C.

7651f.

Under section 126, Northeast

states petitioned the EPA

arguing tha t generator s in

other states contributed to the

nitrogen oxide emissions

problems in their states. EPA

established a summer season

nitrogen oxide emission cap

and trade program covering 22

states (three were removed by

the courts) to start in May 2003

(delayed until May 2004).

The 19-state summer season

nitrogen oxide cap and trade

program is explicitly modeled,

allowing electricity generators

to choose the optimal mix of

control options to meet the

emission cap.

Section 126 Rule: Revised

Deadlines, Federal Reg ister: 

April 30, 2002 (volume 67,

Number 83). Rules and

Regulations, Pages 21521-

21530.

Requires the EPA to establish

national ambient air quality

standards. In 1997, EPA set

new standards for ground level

ozone and fine particulates. 

EPA is currently determining

which areas of the coun try are

not in compliance with the new

standards. Area designations

will be made in December

2004. States will then have

until Decem ber 2007 to submit

their compliance plans, and

until 2009-2 014 to bring all

areas into compliance.

Because stat implementation

plans have not been

established, these revised

standards are not curre ntly

represented.

Clean Air Act Amendment of

1990, Title I, Sections 108 and

109, Nation al Ambien t Air

Quality Standards for Ozone,

40 CFR Part 50, Federal

Register, Vol 68, No 3,

January 8, 2003. National

Ambient Air Quality Standards

for Particulate Matter, 40 CFR

Part 50, Fe deral Regis ter, Vol.

62, No. 138, July 18, 1997.

B. Clean A ir Interstate R ule

 (CAIR)

CAIR imposes a two-phased

limit on emissions of sulfur

dioxide and/or nitrogen oxide

from electric generators in 28

states and the District of

Columbia

Cap and trade programs for

SO2

 and NOx

 are modeled

explicitly, allowing the model to

choose the best method for

meeting the emission caps.

Federal Register, Vol. 70, No.

91 (May 12, 2005), 40 CFR

Parts 51, 72, 73, 74, 77, 78

and 96.

C. Clean A ir Mercury R ule

 (CAMR)

Establishes a national cap on

mercury e missions from coa lfired power plants through a

cap and trade program,

implemented in two phases

with a banking provision.

The cap a nd trade pro gram is

modeled explicitly.

Modifies Section 112 of Clean

Air Act Amendment of 1990,

Federal Register, Vol. 70, No.

95 (May 18, 2005), 40 CFR

Parts.

D. Energy Policy Act of 1992

 (EPACT92)

Created a class of ge nerators

referred to as exempt

wholesale generators (EW Gs),

exempt from PUCHA as long

as they sell wholesale power.

Represents the development

of Exemp t Who lesale

Generators (EWGs) or what

are now referred to as

independent power prod ucers

(IPPs) in all regions.

Energy Policy Act of 1992,

Title VII, Electricity, Subtitle A,

Exempt Whole sale

Generators.

Created a permanent

investment tax credit (ITC) for

solar and geotherm al facilities. 

The ITCs for renewables a re

explicitly mod eled as sta ted in

the law.

Energy Policy Act of 1992,

Title XII, Renewable Energy,

Section 1212, Renewable.
Legislation Brief Description AEO Handling Basis

172 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

E. The Public Utility Holding 

 Company Act of 1935

 (PUCHA)

PUCHA is a US federal statue

which was enacted to legislate

against ab usive pra ctices in

the utility industry. The act

grants power to the US

Securities and Exchange

Commission (SEC) to oversee

and outlaw large holding

companies which might

otherwise control the provision

of electrical service to large

regions of the country. It gives

the SEC power to approve or

deny mergers and acquisitions

and, if necessary, force utility

companies to dispose of

assets or change business

practices if the com pany’s

structure of activities are not

deemed to be in the p ublic

interest.

It is assumed that holding

compa nies act co mpetitive ly

and do not use their regulated

power businesses to crosssubsidize their unregulated

businesses.

Public Utility Holding Company

Act of 1936.

F. FERC Orders 888 and 889 FERC has issues two related

rules Orders 888 and 889

designed to bring low cost

power to consumers through

competition, ensure continued

reliability in the industry, and

provide fo r open and equitable

transmission services by

owners of these facilities. 

Specifically, Order 888

requires open access to the

transmis sion grid cu rrently

owned and operated by

utilities. The transmission

owners mu st file

nondiscriminatory tariffs that

offer other suppliers the same

services that the owne rs

provide for themselves. Order

888 also allows these utilities

to recover strande d costs

(investments in generating

assets th at are unrec overable

due to consumers selecting

another supplier). Order 889

requires utilities to implement

standards of conduct and a

Open Access Same-time

Information System (OASIS)

through which utilities and nonutilities can receive information

regarding the transmission

system. Consequently, utilities

are expected to functionally or

physically un bundle the ir

marketin g functions from their

transmission functions.

These orders are represented

in the forecast by assuming

that all generators in a given

region are able to satisfy load

requireme nts anywhere within

the region. S imilarly, it is

assumed that transactions

between reg ions will occur if

the cost differentials between

them make it economic to do

so.

Promotin g Who lesale

Competition Through Open

Access, Non -discriminatory

Transmission Services by

Public Utilities; Public Utilities

and Transmitting Utilities,

ORDER NO. 888 (Is sued Apr il

24, 1996), 18 CFR Parts 35

and 385, Docket Nos. RM95-8-

000 and RM94-7-001. Open

Access Same-Time

Informatio n System (formerly

Real-Time Information

Networks) and Standards of

Conduct, ORDER NO. 889,

(Issued April 24, 1996), 18

CFR Part 37, Dock et No. 

RM95-9-000.

G. New Source Review (NSR) On August 28m 2003, the EPA

issued a final rule defining

certain power plant and

industrial facility activities as

routine ma intenance , repair

and replaceme nt, which are

not subject to new source

review (NSR). As stated by

EPA, these changes provide a

category of equipment

replacement ac tivities that are

not subject to Major NSR

requirements under the routine

It is assumed tha t coal plants

will be able to incre ase their

output as electricity demand

increases. Their maximum

capacity factor is set at 84

percent. No increases in the

capacity o f existing plan ts is

assum ed. If further a nalysis

shows that capacity uprates

may result from the NSR rule,

they will be incorp orated in

future AEO s. Howeve r, at this

time, the NSR rile is being

contested in the courts.

EPA, 40 CFR Parts 51 and 52,

Prevention of Significant

Deterioration (PSD) and NonAttainment New Source

Review (NSR): Equipment

Replacement Provision of the

Routine M aintenanc e, Repair

and Replacement Exclusion;

Final Rule, Federal Register,

Vol. 68, No. 207, page 61248,

October 27, 2003.
Legislation Brief Description AEO Handling Basis

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 173

maintenance, repair and

replacement (RMRR)

exclusion.[ 1] Essen tially this

means that power plants and

industrial fac ilities engagin g in

RMRR activities will not have

to get preconstruction approval

from the S tate or EPA and will

not have to install best

available emissions control

technologies that might be

required if NSR were triggered. 

H. State RPS laws, mandates,

and goals

Several States have enacted

laws requiring th at a certain

percentage of their generation

come from qualifying

renewable sources. 

The AEO reference case does

not repres ent the widely

varying state requirements for

renewable energy capac ity

because of unc ertainty

regarding policy design and

enforcem ent. A sce nario is

presented in the AEO 2007

that exam ines these laws

assuming full compliance.

The 23 states with RPS or

other mandates providing

quantified projections are

detailed in the Legislation and

Regulation s section o f this

report.

I. State En vironme ntal Laws Several Sates have enacted

laws requiring emissions

reductions from their

generating plants.

Where compliance plans have

been announced, they have

been incorporated. In total 22

gigawatts of planned SO2

scrubbers, 27 gigawatts of

planned s elective c atalytic

reduction (SCR) and 3

gigawatts of planned selective

non-catalytic reduction (SNCR)

are represented.

North Carolina’s Clean Smoke

Stacks Act, Session Law 2002-

4, Senate Bill 1078, An A ct to

Improve Air Quality in the

State by Imposing Limits on

the Emis sion of Cert ain

Pollutants f rom Certa in

Facilities that Burn Coal to

Generate Electricity and to

Provide for Recovery by

Electric Utilities of the Costs of

Achieving Com pliance with

those Limits.

J. Energy Policy Act of 2005 Extends P roduction T ax Credit

(PTC) for ce rtain renewab le

generation through December

31, 2007. The PTC was

created by EPACT 1992, and

originally applied to wind and

some biomass fuels. It was

subsequently am ended to

extend the eligibility period and

add additional qualifying fuels. 

EPAC2005 further extends the

eligibility period, and adds

certain hydroelectric facilities

as qualifying fuels.

EPACT2005 also adds a PTC

for up to 6,000 megawatts of

new nuclear capacity and a

$1.3 billion investment tax

credit for new or repowered

coal-fired power projects.

The tax credits for renewables,

nuclear and coal proje cts are

explicitly modeled as specified

in the law.

Energy Policy Act of 2005,

Sections 1301, 1306, and

1307.

Oil and Gas Su pply

A. The Outer Continental

 Shelf Deep W ater Royalty

 Relief Act (DWRRA)

Mandates that all tracts offered

by Novem ber 22, 200 0, in

deep water in certain areas of

the Gulf of Mexico must be

offered under the new bidding

system permitted by the

DWRRA. The Secretary of

Interior must offer such tracts

with a specific minimum royalty

suspension volume based on

water depth.

Incorporates royalty rates

based on water depth.

43 U.S.C. SS 1331-1356

(2002).

B. Energy Policy and 

 Conservation Act

 Amendments of 2000

Required the USG S to

inventory oil and gas

resources beneath Federal

lands.

To date, the Rocky M ountain

oil and gas resource inv entory

has been completed by the

USGS. T he results o f this

Scientific Inventory of O nshore

Federal Lands: Oil and Gas

Resources and Reserves and

the Extent and Nature of
Legislation Brief Description AEO Handling Basis

174 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

inventory have been

incorporate d in the tech nically

recoverable oil and gas

resource volumes used for the

Rocky Mountain region.

Restrictions or Imped iments to

their Development: The

Paradox/San Juan,

Uinta/Piceance, Greater Green

River, and Powder River

Basins and the Montana

Thrust Belt. Prepared by the

Departments o f Interior,

Agriculture and Energy,

January 2003.

C. Hackberry Decision Terminated open access

requirements for new on shore

LNG terminals and authorized

them to charge market-based

rather than cost-of-service

rates.

This is reflected in lower risk

premiums for new terminal

construction.

Docket No. PL02-9, Natural

Gas Markets Conference

(2002).

D. Maritime Security Act of

 2002 Amendments to the 

 Deepwater Port Act of

 1974 

Transfers jurisdiction over

offshore LNG facilities from

FERC to the Maritime

Administration (MARAD) and

the Coast Guard, both under

the Department of

Transportation (DOT), provides

these fac ilities with a new,

streamlined application

process, and relaxes

regulatory requirements

(offshore LNG facilities are no

longer required to operate as

common carriers or to provide

open acc ess as th ey did while

under FERC jurisdiction ).

This is reflected in lower risk

premiums for new terminal

construction.

P.L. 107-295.

E. Section 29 Tax Credit for

 Nonconv entional Fue ls

The Alternative Fuel

Production Credit (Section 29

of the IRC) applies to qualified

nonconventional fuels from

wells drilled or facilities placed

in service between January 1,

1980, and Dece mber 31, 1992. 

Gas production from qualifying

wells could receive a 3 dollar

(1979 constant dollars) per

barrel of oil equ ivalent cre dit

on volumes produced through

December 31, 2002. The

qualified fuels are: oil

produced from shale and tar

sands; gas from

geopressurized brine,

Devonian shale, coal seams,

tight formations, and biomass;

liquid, gaseo us, or solid

synthetic fuels produced from

coal; fuel from qualified

processed formations or

biomass; and steam from

agricultural products.

The Sect ion 29 Tax C redit

expired on December 31,

2002, and it not consid ered in

new production decisions . 

However, the effect of these

credits is im plicitly included in

the parameters th at are

derived from historica l data

reflecting such credits.

Alternative Fuel Production

Credit (Section 29 of the

Internal Revenue C ode),

initially established in the

Windfall Profit Tax of 1980.

F. Energy Policy Act of 2005 Established a program to

provide g rants to en hance oil

and gas recovery through CO2

injection.

Additional oil resources were

added to account for increased

use of CO2-enhance d oil

recovery.

Title III, Section 354 of the

Energy Policy Act of 2005.

Natural Gas Transmission

and Distribution

A. Alaska Natural Gas

 Pipeline Act, Sections 

 101-116 of the Military

Disallows approval for a

pipeline to en ter Canada via

Alaska north of 68 degrees

Assumes the pipeline

construction cost estimate for

the “southern”Alaska pipeline

route in projecting when an

P.L. 108-324.
Legislation Brief Description AEO Handling Basis

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 175

 Construction Hurricane

 Supplemental

 Appropriations Act, 2005.

latitude. Also, provides

Federal guarantees for loans

and other debt obligations

assigned to infrastruc ture in

the United States or Canada

related to any natural gas

pipeline system that carries

Alaska natural gas to the

border between Alaska and

Canada south of 68 degrees

north latitude. This authority

Alaska gas pipeline would be

profitable to build. Also, when

calculating the tariff associated

with the Alaska pipeline, the

return on debt was lowered by

1 percentage point and the

percentage of capital financed

by debt was increased by 10,

to account for the impact of the

loan guarantee.

would expire 2 years after the

final certificate of public

conven ience and necessity is

issued. The guarantee will not

exceed 1) 80 percent of the

total capital costs (including

interest during construction), 2)

$18 billion dollars (indexed for

inflation at the time of

enactment), or 3) a term of 30

years.

B. American Jobs Creation

 Act of 2004, Sections 706

 and 707.

Provides a 70yea r cost-ofinvestment recovery period for

the Alaska natural gas

pipeline, as opposed to the

currently allowed 15-year

recovery period, for tax

purposes . The prov ision would

be effective for property placed

in service after 2013, or

treated as such. Effe ctively

extends the 15-percent tax

credit currently applied to costs

related to en hanced o il

recovery to cons truction costs

for a gas treatment plant on

the on the North Slope that

would feed gas into an Alaska

pipeline to Canada.

When c alculating the tariff

associated with the Alaska

pipeline, the return on equity

was lowered by 3 percentage

points. Also, the charge

associated with removing

liquids from natural gas at the

gas processing plant for the

Alaska natural gas pipeline

was decreased by $0.05 per

Mcf.

P.L. 108-357.

C. Pipeline Safety

 Improvement Act of 2002

Imposes a stricter regime on

pipeline operators designe d to

prevent leaks and ruptures.

Costs associate d with

implementing the new safety

features are assumed to be a

small percentage of total

pipeline cos ts and are p artially

offset by benefits gained

through reducing pipeline

leakage. It is assumed that

the Act accelerates the

schedule of repair work that

would have been done

otherwise.

P.L. 107-355, 116 Stat. 2985.

D. FERC O rder 436 (Is sued in

 1985)

Order 436 changed gas

transmission from a merchant

business, wherein the pipeline

buys the gas commodity at the

inlet and sold the gas

commod ity at the delivery

point, to being a transportation

business wherein the pipeline

does not take title to the ga s. 

Order 436 permitted pipelines

to apply for blanket

transporta tion certificat es, in

Natural gas is priced at the

wellhead at a competitive rate

determined by the m arket. 

The flow of gas in the system

is a function of the relative

costs and is set to balance

supply, dem and, and p rices in

the market. Transportation

costs are based on a regulated

rate calculation

50 F. R. 42408, FERC Statutes

and Regulations Paragraph

30,665 (1985).
Legislation Brief Description AEO Handling Basis

176 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

return for becoming nondiscriminatory, open-access

transporters. Order 436 also

allocated gas pipeline cap acity

on a first-com, first-serve

basis, allowed pipelines to

discount below the maximum

rate, allowed local gas

distributors to convert to

transportation only contracts,

and created optional expedited

certificates for the construction

of new facilities.

E. FERC O rder 636 (Is sued in

 1992)

FERC Order 636 completed

the separation of pipeline

merchant services from

pipeline transportation

services, requiring pipelines to

offer separate tariffs for firm

transporta tion, interrupt ible

transportation, and storage

services. Order 636 also

permitted pipelines to re sell

unused firm capacity as

interruptible transportation,

gave shippers the right to first

refusal at th e expiration o f their

firm transportation contracts,

adopted Straight-FixedVariable rate method ology,

and created a mechanism for

pipelines to recover the costs

incurred by prior take-or-pay

contracts.

A straight-fixed-variable rate

design is used to establish

regulated rates. To reflect

some of the flexibility built into

the system, the ac tual tariffs

charged are allowed to va ry

from the regulated rates as a

function of the utilization of the

pipeline. End-use prices a re

set separately for firm and

interruptible customers for the

industrial and electric

generation sectors.

57 F.R. 13267, FERC Statutes

and Regulations Paragraph

30,939 (1992)

F. Energy Policy Act of 2005 Allowed natural gas storage

facilities to charge marke tbased rates if it was believed

they would not exert market

power.

Storage rates are allowed to

vary from regulation-based

rates depending on market

conditions.

Title III, Section 312 of the

Energy Policy Act of 2005.

Petroleum Refining

A. Ultra-Low-Sulfur Diesel

 (ULSD) regulations under

 the Clean Air Act

 Amendment of 1990

80 percent of highway diesel

pool must contain 15 ppm

sulfur or less starting in fall

2006. By m id-2010, all

highway diesel must be 15

ppm or less. All nonroad,

locomotive, and marine diesel

fuel produc ed must contain

less than 500 ppm starting

mid-2007. By mid-2010

nonroad d iesel mus t contain

less than 15 ppm. Locomotive

and marine diesel must

contain less than 15 ppm by

mid-2012.

Reflected in diesel

specifications

40 CFR Parts 69, 80, 86, 89,

94, 1039, 1048, 1065, and

1068

B. Mobile Source Air Toxics

 (MSAT) controls under the

 Clean Air Act Amendment

 of 1990

Establishes a list of 21

substances emitted from motor

vehicles and known to cause

serious human health effects,

particularly benzene,

formaldehyde, 1.3 butadiene,

acetaldehyde, diesel exhaust

organic gases, and diesel

particulate matter. Establishes

anti-backs liding and an tidumping rules for gasoline.

Modeled by updating gasoline

specifications to most current

EPA gasoline su rvey data

(2005) repre senting an tibacksliding requirements.

40 CFR Parts 60 and 86.
Legislation Brief Description AEO Handling Basis

Energy Information Administration/Assumptions to the Annual Energy Outlook 2008 177

C. Low-Sulfur Gasoline 

 Regulations under the 

 Clean Air Act Amendment

 of 1990

Gasoline must contain an

average of 30 ppm sulfur or

less by 2006. Sm all refiners

may be permitted to delay

compliance until 2008.

Reflected in gasoline

specifications.

40 CFR Parts 80, 85 and 86

D. MTBE Bans in 25 States 23 States ban the use of

MTBE in gasoline by 2007

Ethanol assumed to be the

oxygenate of choice in RFG

where MTBE is banned.

State laws in Arizona,

California, Colorado,

Connecticut, Illinois, Indiana,

Iowa, Kansas, Ken tucky,

Maine, Michigan, Minnesota,

Missouri, Montana, Nebraska,

New Hampshire, N ew Jersey,

New York, North Carolina,

Ohio, Rhode Island , South

Dakota, Vermont, Washington,

and Wisconsin.

E. Regiona l clean fuel 

 formulations under the 

 Clean Air Act Ame ndments

 of 1990

States with air quality problems

can specify alternative

gasoline or diesel formulations

with EPA’s permission. 

California has long had

authority to set its own fuel

standards.

Reflected in PADD-level

gasoline and diesel

specifications.

State implementation plans

required by the Clean Air Act

Amendments of 1990, as

approved by EPA.

F. Federal M otor Fuels

 Excise Taxes

Taxes are levied on each

gallon of transportation fuels to

fund infrastructure and general

revenue. These taxes are set

to expire at v arious time s in

the future but are expec ted to

be renewed, as they have

been in the past.

Gasoline, diesel, and ethanol

blend tax rate s are includ ed in

end-use prices and are

assumed to be extended

indefinitely at current nominal

rates.

26 USC 4041 Extended by

American Jobs Creation Act of

2004

G. State Motor Fuel Taxes Taxes are levied on each

gallon of transportation fuels. 

The assump tion that State

taxes will increase at the rate

of inflation supports an implied

need for additional highway

revenues as driving increases.

Gasoline and diese l rates are

included in end-use prices and

are assumed to be extended

indefinitely in real terms (to

keep pace with inflation).

Determined by review of

existing State laws performed

semi-annually by EIA’s Office

of Oil and Gas.

H. Diesel Excise Taxes Phases out the 4 .3 cents

excise tax on railroads

between 2005 and 2007.

Modeled by phas ing out. American Jobs Creation Act of

2004, Section 241.

I. Energy Policy Act of 2005 (EPACT05)

a. Ethanol/biodiesel Tax

 Credit

Petroleum produc t blenders

may claim tax credits for

blending ethanol into gasoline

and for blending biodiesel into

diesel fuel or heating oil. The

credits may be claimed against

the Federal motor fuels excise

tax or the income tax. The tax

credits are 51 per gallon of

nonvirgin biodiesel, and $1.00

per gallon of virgin biodiesel. 

The ethanol tax credit expires

in 2010. The biodiesel tax

credits expire after 2008.

The tax credits are applied

against the production costs of

the products into which they

are blended. Ethanol is used

in gasoline a nd E85. V irgin

biodiesel is assumed to be

blended into highway diese l,

and nonv irgin biodiese l is

assumed to b e blended into

nonroad d iesel or heat ing oil.

26 USC 40, 4041 and

American Jobs Creation Act of

2004. Biodiesel tax credits

extended to 2008 under

Energy Policy Act of 2005.

b. Renewab le Fuels

 Standard (RFS)

This section has largely been

redefined by EISA07 (see

below) however EPA

rulemakin g comple ted for this

law was assum ed to conta in

guiding principles for the rules

and administration of EISA07.

Energy Policy Act of 2005,

Section 1501.
Legislation Brief Description AEO Handling Basis

178 Energy Information Administration/Assumptions to the Annual Energy Outlook 2008

c. Elimination of Oxygen 

 Content Re quiremen t in

 Reformulated Gasoline

Within 270 days of enactment

of the Act, e xcept for Ca lifornia

where it is effective

immediately.

Oxygena te waiver alrea dy in

option of the model. M TBE is

assumed to phase out in 2006

resulting from the petroleum

industry’’s decision to

discontinue use. AEO

projection may still show use

of ethanol in gasoline based

on the economics between

ethanol and other gasoline

blending components.

Energy Policy Act of 2005,

Section 1504.

 d. Coal Gasification

 Provisions

Investment tax credit program

for qualifying advanced clean

coal projects including C oal to

Liquids Projects.

Two CTL units are ava ilable to

build with lower capital costs

reflecting the provision’s

funding.

Energy Policy Act of 2005,

Section 1307.

J. Energy Independence and Security Act of 2007 (EISA07)

 a. Renewab le Fuels

 Standard (RFS)

Requires the use of 36 billion

gallons of ethanol per year by

2022, with corn ethanol limited

to 15 billion gallons. Any other

biofuel ma y be used to fulfill

the balance of the mandate,

but the balance must include

16 billion gallons per year of

cellulosic biofuel by 2022 and

1 billion gallons per year of

biodiesel by 2012.

The RFS is included in

AEO20 08, howev er it is

assumed that the schedule for

cellulosic biofuel is adjusted

downward consistent with

waiver prov isions con tained in

the law.

Source: Energy Information Administration, Office of Integrated Analysis and Forecasting.

Abbreviations:

AEO: Annual Energy Outlook

AFUE: Average Fuel Use Efficiency

Btu: British Thermal Unit

CAF...: Corporate Average Fuel Economy

CBECS: Commercial Building Energy Consumption Survey

CFR: Code of Federal Regulations

DOE: Department of Energy

DOT: Department of Transportation

DWRRA: Deep Water Royalty Relief Act

EER: Energy Efficient Ratio

EF: Energy Efficiency

EIA: Energy Information Administration

EPA: Environmental Protection Agency

EPACT92: Energy Policy Act of 1992

EPACT05: Energy Policy Act of 2005

EWGs: Exempt Whole sale Generators

FERC: Federal Energy Regulatory Commission

HERS: Home Energy Efficiency Rating

HVAC: Heating, Ventilation, and Air Conditioning IECC: International Energy

Conservation Code ITC: Investment Tax Credit

kWh: Kilowatthour

LBNL: Lawrence Berkeley National Laboratory

LEVP: Low Emission Vehicle Program

LNG: Liquified Natural Gas

MARAD: Maritime Administration

MEF: Modified Energy Factor

MSAT: Mobile Source Air Toxics MTBE: Methyl-Tertiary-Butyl-Ether

OASIS: Open Access Same-Time Information System

PADD: Petroleum Administration for Defense Districts

P.L.: Public Law

PPM: Parts Per Million

PTC: Production Tax Credit

PUCHA: Public Utility Holding Company Act of 1935

RECS: Residential Energy Consumption Survey

RPS: Renewable Portfolio Standard

SCR: Selective Catalytic Reduction

SEER: Seasonal Energy Efficiency Rating

SO2: Sulfur Dioxide

SNCR: Selective Non-Cata lytic Reduction

ULSD: Ultra-Low Sulfur Dioxide

U.S.C.: United States Code

USGS: United States Geological Survey

ZEV: Zero Emission Vehicle