Assumptions to the Annual 

Energy Outlook 2013

May 2013

Independent Statistics & Analysis

www.eia.gov

U.S. Department of Energy

Washington, DC 20585
This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and 

analytical agency within the U.S. Department of Energy. By law, EIA’s data, analyses, and forecasts are 

independent of approval by any other officer or employee of the United States Government. The views 

in this report therefore should not be construed as representing those of the Department of Energy or 

other Federal agencies.
Table of Contents

Introduction ..................................................................................................................................................3

Macroeconomic Activity Module................................................................................................................17

International Energy Module......................................................................................................................21

Residential Demand Module ......................................................................................................................27

Commercial Demand Module.....................................................................................................................39

Industrial Demand Module.........................................................................................................................53

Transportation Demand Module ................................................................................................................75

Electricity Market Module ........................................................................................................................101

Oil and Gas Supply Module.......................................................................................................................119

National Gas Transmission and Distribution Module ...............................................................................135

Liquid Fuels Market Module .....................................................................................................................145

Coal Market Module .................................................................................................................................161

Renewable Fuels Module..........................................................................................................................175

Appendix A: Handling of Federal and Selected state Legislation and Regulation in the AEO .................187
Introduction
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U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 3

Introduction

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

in the Annual Energy Outlook 2013 [1] (AEO2013), 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

Projections in the AEO2013 are generated using the NEMS, developed and maintained by the Office of Energy Analysis of the U.S. 

Energy Information Administration (EIA). In addition to its use in developing the Annual Energy Outlook (AEO) projections, NEMS 

is also used to complete analytical studies for the U.S. Congress, the Executive Office of the President, other offices within the 

U.S. Department of Energy, and other Federal agencies. NEMS is also used by other nongovernment groups, such as the Electric 

Power Research Institute, Duke University, and Georgia Institute of Technology. In addition, the AEO projections are used by 

analysts and planners in other government agencies and nongovernment organizations.

The projections in NEMS are developed with the use of a market-based approach, subject to regulations and standards. For each 

fuel and consuming sector, NEMS balances energy supply and demand, accounting for economic competition among the various 

energy fuels and sources. The time horizon of NEMS extends to 2040. To represent regional differences in energy markets, the 

component modules of NEMS function at the regional level: the 9 Census divisions for the end-use demand modules; production 

regions specific to oil, natural gas, and coal supply and distribution; 22 regions and subregions of the North American Electric 

Reliability Corporation for electricity; and 8 refining regions that are a subset of the 5 Petroleum Administration for Defense 

Districts (PADDs). Maps illustrating the regional formats used in each module are included in this report. Only selected regional 

results are presented in AEO2013, which predominantly focus on the national results. Complete regional and detailed results are 

available on the EIA Analyses and Projections Home Page (www.eia.gov/analysis/).

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. The modular design also permits the use of the 

methodology and level of detail most appropriate for each energy sector. NEMS executes each of the component modules to 

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

fuel prices encompass all the activities necessary to produce, import, and transport fuels to end users. The information flows 

also include other data on such areas as economic activity, domestic production, and international petroleum supply. NEMS 

calls 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. A solution is reached for each year from 2012 through 2040. Other variables, such as petroleum product imports, crude 

oil imports, and several macroeconomic indicators, also are evaluated for convergence. Each NEMS component represents the 

impacts and costs of legislation and environmental regulations that affect that sector. NEMS accounts for all combustion-related 

carbon dioxide (CO2) emissions, as well as emissions of sulfur dioxide (SO2), nitrogen oxides (NOx), and mercury from the 

electricity generation sector.

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.

The version of NEMS used for AEO2013 generally represents current legislation and environmental regulations, including recent 

government actions for which implementing regulations were available as of September 30, 2012, such as: the new light-duty 

vehicle (LDV) greenhouse gas (GHG) and corporate average fuel economy (CAFE) standards for model years 2017 to 2025 [3] 

released in October 2012; the Clean Air Interstate Rule (CAIR), which was reinstated as binding legislation after the Cross- State 

Air Pollution Rule (CSAPR) [4] was vacated on August 21, 2012; updated handling of the U.S. Environmental Protection Agency’s 

(EPA) National Emissions Standards for Hazardous Air Pollutants for industrial boilers and process heaters [5] based on 

regulations released in March 2011; the Mercury and Air Toxics Standards [6] issued by the EPA in December 2011; California’s 

cap-and-trade program authorized by Assembly Bill 32 (AB 32), the Global Warming Solutions Act of 2006 [7], issued in 

September 2006; and the California Low Carbon Fuel Standard (LCFS) [8] finalized in January 2010. 
4 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Introduction

The potential impacts of proposed federal and state legislation, regulations, or standards—or of sections of legislation that have 

been enacted but require funds or implementing regulations that have not been provided or specified—are not reflected in NEMS. 

Many of the pending provisions, however, are examined in alternative cases included in AEO2013 or in other analysis completed 

by EIA. 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 prices 

or expenditures for 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 receives 

energy-related indicators from the NEMS energy components as part of the 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, sales of new LDVs, interest rates, and employment. Key energy indicators 

fed back to the MAM include aggregate energy prices and costs. The MAM uses the following models from IHS Global Insight: 

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). 

Source: U.S. Energy Information Administration, Office of Energy Analysis.

Figure 1. National Energy Modeling System
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 5

Introduction

International Energy Module

The International Energy Module (IEM) uses assumptions of economic growth and expectations of future U.S. and world 

petroleum and other liquids production and consumption, by year, to project the interaction of U.S. and international 

petroleum and other liquids markets. The IEM computes Brent and West Texas Intermediate (WTI) prices, provides a world 

crude-like liquids supply curve, and generates a worldwide oil supply/demand balance for each year of the projection period. 

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 petroleum and other liquids supply and demand, current investment trends in 

exploration and development, and long-term resource economics by country and territory. The oil production estimates 

include both petroleum and other liquids supply recovery technologies. The IEM also provides, for each year of the projection 

period, endogenous and exogenous assumptions for petroleum products for import and export in the United States. In 

interacting with the rest of NEMS, the IEM changes Brent and WTI prices in response to changes in expected production and 

consumption of crude oil and other liquids in the United States.

Residential and Commercial Demand Modules

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

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

and changes in the housing stock. The Commercial Demand Module projects energy consumption in the commercial sector 

by Census division, building type, and category of end use, based on delivered prices of energy, availability of renewable 

sources of energy, and changes in commercial floorspace. 

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

technologies, representations of renewable energy technologies, and the effects of both building shell and appliance 

standards. The modules also include projections of distributed generation. The Commercial Demand Module also 

incorporates combined heat and power (CHP) technology. Both modules incorporate changes to “normal” heating and 

cooling degree-days by Census division, based on a 30-year historical trend and on state-level population projections. 

The Residential Demand Module projects an increase in the average square footage of both new construction and existing 

structures, based on trends in new construction and remodeling.

Industrial Demand Module

The Industrial Demand Module (IDM) projects the consumption of energy for heat and power, as well as the consumption 

of feedstocks and raw materials in each of 21 industry groups, subject to the delivered prices of energy and macroeconomic 

estimates of employment and the value of shipments for each industry. As noted in the description of the MAM, the 

representation of industrial activity in NEMS is based on the NAICS. The industries are classified into three groups—energyintensive manufacturing, non-energy-intensive manufacturing, and nonmanufacturing. Seven of eight energy-intensive 

manufacturing industries are modeled in the IDM, including energy-consuming components for boiler/steam/cogeneration, 

buildings, and process/assembly use of energy. Energy demand for petroleum and other liquids refining (the eighth energyintensive manufacturing industry) is modeled in the Liquid Fuels Market Module (LFMM) as described below, but the 

projected consumption is reported under the industrial totals. 

There are several updates and upgrades in the representations of select industries. AEO2013 includes an upgraded 

representation for the aluminum industry. Instead of assuming that technological development for a particular process occurs 

on a predetermined or exogenous path based on engineering judgment, these upgrades allow IDM technological change to 

be modeled endogenously, while using more detailed process representation. The upgrade allows for explicit technological 

change, and therefore energy intensity, to respond to economic, regulatory, and other conditions. The combined cement 

and lime industry was upgraded in the Annual Energy Outlook 2012 (AEO2012). For subsequent AEOs other energy-intensive 

industries will be similarly upgraded. 

The bulk chemicals model has been enhanced in several respects: baseline natural gas liquids (NGL) feedstock data were 

aligned with Manufacturing Energy Consumption Survey 2006 data; an updated propane pricing mechanism reflecting 

natural gas price influences was used to allow for price competition between liquid petroleum gases feedstock and 

petroleum-based (naphtha) feedstock; and propylene supplied by the refining industry is now specifically accounted for in the 

LFMM. 

Nonmanufacturing models were significantly revised as well. The construction and mining models were augmented to better 

reflect NEMS assumptions regarding energy efficiencies in (off-road) vehicles and buildings, as well as coal, oil, and natural 

gas extraction productivity. The agriculture model was similarly augmented in AEO2012. The IDM also includes a generalized 

representation of CHP. The methodology for CHP systems simulates the utilization of installed CHP systems based on 

historical utilization rates and is driven by end-use electricity demand. To evaluate the economic benefits of additional CHP 

capacity, the model also includes an appraisal incorporating historical capacity factors and regional acceptance rates for new 

CHP facilities.
6 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Introduction

There are also enhancements to the IDM to account for regulatory changes. This includes California’s AB 32 that allows for 

representation of a cap-and-trade program developed as part of California’s GHG reduction goals for 2020. Another regulatory 

update is included for the handling of National Emissions Standards for Hazardous Air Pollutants for industrial boilers, to address 

the maximum degree of emission reduction using maximum achievable control technology.

Transportation Demand Module

The Transportation Demand Module projects consumption of energy by mode and fuel—including petroleum products, electricity, 

methanol, ethanol, compressed natural gas (CNG), liquefied natural gas (LNG), and hydrogen—in the transportation sector, 

subject to delivered energy prices, macroeconomic variables such as GDP, and other factors such as technology adoption. The 

Transportation Demand Module includes legislation and regulations, such as the Energy Policy Act of 2005 (EPACT2005), 

the Energy Improvement and Extension Act of 2008 (EIEA2008), and the American Recovery and Reinvestment Act of 2009 

(ARRA2009), which contain tax credits for the purchase of alternatively fueled vehicles. Representations of LDV CAFE and GHG 

emissions standards, HDV fuel consumption and GHG emissions standards, and biofuels consumption reflect standards enacted 

by NHTSA and the EPA, as well as provisions in the Energy Independence and Security Act of 2007 (EISA2007). 

The air transportation component of the Transportation Demand Module represents air travel in domestic and foreign markets 

and includes the industry practice of parking aircraft in both domestic and international markets to reduce operating costs, as well 

as the movement of aging aircraft from passenger to cargo markets. For passenger travel and air freight shipments, the module 

represents regional fuel use and travel demand for three aircraft types: regional, narrow-body, and wide-body. An infrastructure 

constraint, which is also modeled, can potentially limit overall growth in passenger and freight air travel to levels commensurate 

with industry-projected infrastructure expansion and capacity growth. 

The Transportation Demand Module projects energy consumption for freight and passenger rail and marine vessels by mode and 

fuel, subject to macroeconomic variables such as the value and type of industrial shipments.

Electricity Market Module

There are three primary submodules of the Electricity Market Module (EMM)—capacity planning, fuel dispatching, and finance 

and pricing. The capacity expansion submodule uses the stock of existing generation capacity, the cost and performance of 

future generation capacity, expected fuel prices, expected financial parameters, expected electricity demand, and expected 

environmental regulations to project the optimal mix of new generation capacity that should be added in future years. The fuel 

dispatching submodule uses the existing stock of generation equipment types, their operation and maintenance costs and 

performance, fuel prices to the electricity sector, electricity demand, and all applicable environmental regulations to determine 

the least-cost way to meet that demand. The submodule also determines transmission and pricing of electricity. The finance and 

pricing submodule uses capital costs, fuel costs, macroeconomic parameters, environmental regulations, and load shapes to 

estimate generation costs for each technology. 

All specifically identified options promulgated by the EPA for compliance with the Clean Air Act Amendments of 1990 are 

explicitly represented in the capacity expansion and dispatch decisions. All financial incentives for power generation expansion 

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

enacted air emission regulations for CO2 that affect the electricity generation sector, and those regulations are represented in 

AEO2013. The AEO2013 Reference case also imposes a limit on CO2 emissions for specific covered sectors, including the electric 

power sector, in California, as represented in California’s AB 32. The AEO2013 Reference case reinstates the CAIR after the court 

vacated CSAPR in August 2012. CAIR incorporates a cap and trade program for annual emissions of SO2 and annual and seasonal 

emissions of NOx from fossil power plants. Reductions in mercury emissions from coal- and oil-fired power plants also are 

reflected through the inclusion of the Mercury and Air Toxics Standards for power plants, finalized by the EPA on December 16, 

2011. 

Although currently there is no Federal legislation in place that restricts GHG emissions, regulators and the investment community 

have continued to push energy companies to invest in technologies that are less GHG-intensive. The trend is captured in the 

AEO2013 Reference case through a 3-percentage-point increase in the cost of capital, when evaluating investments in new coalfired power plants, new coal-to-liquids (CTL) plants without carbon capture and storage, and pollution control retrofits.

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 (dedicated biomass plants and co-firing in existing coal plants), geothermal, landfill gas, solar thermal electricity, solar 

photovoltaics, and both onshore and offshore wind energy. The RFM contains renewable resource supply estimates representing 

the regional opportunities for renewable energy development. Investment tax credits (ITCs) for renewable fuels are incorporated, 

as currently enacted, including a permanent 10-percent ITC for business investment in solar energy (thermal nonpower uses
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 7

Introduction

as well as power uses) and geothermal power (available only to those projects not accepting the production tax credit [PTC] 

for geothermal power). In addition, the module reflects the increase in the ITC to 30 percent for solar energy systems installed 

before January 1, 2017. The extension of the credit to individual homeowners under EIEA2008 is reflected in the Residential and 

Commercial Demand Modules. 

PTCs for wind, geothermal, landfill gas, and some types of hydroelectric and biomass-fueled plants also are represented, based 

on the laws in effect on October 31, 2012. They provide a credit of up to 2.2 cents per kilowatthour for electricity produced in the 

first 10 years of plant operation. For AEO2013, new wind plants coming on line before January 1, 2013, are eligible to receive the 

PTC; other eligible plants must be in service before January 1, 2014. The law has subsequently been amended to extend the PTC 

for wind by an additional year. Furthermore, eligible plants of any type will qualify if construction begins prior to the expiration 

date, regardless of when the plant enters commercial service. This change was made after the completion of AEO2013 and is 

not reflected in the analysis. As part of ARRA2009, plants eligible for the PTC may instead elect to receive a 30-percent ITC or 

an equivalent direct grant. AEO2013 also accounts for new renewable energy capacity resulting from state renewable portfolio 

standard programs, mandates, and goals.

Oil and Gas Supply Module

The Oil and Gas Supply Module 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 all production 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 natural gas production activities are 

modeled for 12 supply regions, including 6 onshore, 3 offshore, and 3 Alaskan regions. 

The Onshore Lower 48 Oil and Gas Supply Submodule evaluates the economics of future exploration and development projects 

for crude oil and natural gas at the play level. Crude oil resources include conventional, structurally reservoired resources as well 

as highly fractured continuous zones, such as the Austin chalk and Bakken shale formations. Production potential from advanced 

secondary recovery techniques (such as infill drilling, horizontal continuity, and horizontal profile) and enhanced oil recovery (such 

as CO2 flooding, steam flooding, polymer flooding, and profile modification) are explicitly represented. Natural gas resources 

include high-permeability carbonate and sandstone, tight gas, shale gas, and coalbed methane. 

Domestic crude oil production quantities are used as inputs to the LFMM in NEMS for conversion and blending into refined 

petroleum products. Supply curves for natural gas are used as inputs to the Natural Gas Transmission and Distribution Module 

(NGTDM) for determining natural gas wellhead prices and domestic production.

Natural Gas Transmission and Distribution Module

The 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 Lower 48 U.S. demand regions. 

The 12 Lower 48 regions align with the 9 Census divisions, with three subdivided, and Alaska handled separately. The flow of 

natural gas is determined for both a peak and off-peak period in the year, assuming a historically based seasonal distribution of 

natural gas demand. Key components of pipeline and distributor tariffs are included in separate pricing algorithms. An algorithm 

is included to project the addition of CNG retail fueling capability. The module also accounts for foreign sources of natural gas, 

including pipeline imports and exports to Canada and Mexico, as well as LNG imports and exports.

Liquids Fuels Market Module

The LFMM projects prices of petroleum products, crude oil and product import activity, as well as domestic refinery operations, 

subject to demand for petroleum products, availability and price of imported petroleum, and domestic production of crude oil, 

NGL, and biofuels—ethanol, biodiesel, biomass-to-liquids (BTL), CTL, gas-to-liquids (GTL), and coal-and-biomass-to-liquids 

(CBTL). Costs, performance, and first dates of commercial availability for the advanced liquid fuels technologies [9] are reviewed 

and updated annually. 

The module represents refining activities in eight domestic U.S. regions, and a Maritime Canada/Caribbean refining region 

(created to represent short-haul international refineries that predominantly serve U.S. markets). In order to better represent policy, 

import/export patterns, and biofuels production, the eight U.S. regions were defined by subdividing three of the five U.S. PADDs. 

All nine refining regions are defined below:

Region 1. PADD I – East Coast 

Region 2. PADD II – Interior 

Region 3. PADD II – Great Lakes
8 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Introduction

Region 4. PADD III – Gulf Coast 

Region 5. PADD III – Interior 

Region 6. PADD IV – Mountain 

Region 7. PADD V – California 

Region 8. PADD V – Other 

Region 9. Maritime Canada/Caribbean 

The capacity expansion submodule uses the stock of existing generation capacity, the cost and performance of future 

generation capacity, expected fuel prices, expected financial parameters, expected electricity demand, and expected 

environmental regulations to project the optimal mix of new generation capacity that should be added in future years. 

The LFMM models the costs of automotive fuels, such as conventional and reformulated gasoline, and includes production of 

biofuels for blending in gasoline and diesel. Fuel ethanol and biodiesel are included in the LFMM, because they are commonly 

blended into petroleum products. The module allows ethanol blending into gasoline at 10 percent by volume, 15 percent by 

volume (E15) in states that lack explicit language capping ethanol volume or oxygen content, and up to 85 percent by volume 

(E85) for use in flex-fuel vehicles. Crude and refinery product imports are represented by supply curves defined by the NEMS 

IEM. Products also can be imported from refining region 9 (Maritime Canada/Caribbean). Refinery product exports are provided 

by the IEM. 

Capacity expansion of refinery process units and nonpetroleum liquid fuels production facilities is also modeled in the LFMM. 

The model uses current liquid fuels production capacity, the cost and performance of each production unit, expected fuel and 

feedstock costs, expected financial parameters, expected liquid fuels demand, and relevant environmental policies to project the 

optimal mix of new capacity that should be added in the future. 

The LFMM includes representation of the renewable fuels standard (RFS) specified in EISA2007, which mandates the use of 

36 billion gallons of ethanol equivalent renewable fuel by 2022. Both domestic and imported biofuels count toward the RFS. 

Domestic ethanol production is modeled for three feedstock categories: corn, cellulosic plant materials, and advanced feedstock 

materials. Starch-based ethanol plants are numerous (more than 190 are now in operation, with a total maximum sustainable 

nameplate capacity of more than 14 billion gallons annually), and they are based on a well-known technology that converts 

starch and sugar into ethanol. Ethanol from cellulosic sources is a new technology with only a few small pilot plants in operation. 

Ethanol from advanced feedstocks—produced at ethanol refineries that ferment and distill grains other than corn, and reduce 

GHG emissions by at least 50 percent—is also a new technology modeled in the LFMM. 

Fuels produced by Fischer-Tropsch synthesis and through a pyrolysis process are also modeled in the LFMM, based on their 

economics relative to competing feedstocks and products. The five processes modeled are CTL, CBTL, GTL, BTL, and pyrolysis. 

Two California-specific policies are also represented in the LFMM: the LCFS and the AB 32 cap-and-trade program. The 

LCFS requires the carbon intensity (amount of GHG per unit of energy) of transportation fuels sold for use in California to 

decrease according to a schedule published by the California Air Resources Board. California’s AB 32 cap-and-trade program 

is established to help California achieve its goal of reducing CO2 emissions to 1990 levels by 2020. Working with other NEMS 

modules (IDM, EMM and Emissions Policy Module), the LFMM provides emissions allowances and actual emissions of CO2

from California refineries, and NEMS provides the mechanism (carbon price) to trade allowances such that the total CO2

emissions cap is met.

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 41 separate supply curves— 

differentiated by region, mine type, coal rank, and sulfur content. The coal supply curves respond 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 region and 

sector; environmental restrictions; and accounting for minemouth prices, transportation costs, and coal supply contracts. Over 

the projection period, coal transportation costs in the CMM vary in response to changes in the cost of rail investments.

The CMM produces projections of U.S. steam and metallurgical coal exports an dimports in the context of world coal trade, 

determining the pattern of world coal trade flows that minimizes production and transportation costs while 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 regions and 20 import regions U.S. coal 

production and distribution are computed for 14 supply regions and 16 demand regions.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 9

Introduction

Annual Energy Outlook 2013 cases

In preparing projections for AEO2013, EIA evaluated a wide range of trends and issues that could have major implications for U.S. 

energy markets between now and 2040. Besides the Reference case, AEO2013 presents detailed results for five 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, population grows by 0.9 percent per year, nonfarm employment by 1.0 percent per year, and labor 

productivity by 1.9 percent per year from 2011 to 2040. Economic output as measured by real GDP increases by 2.5 percent 

per year from 2011 through 2040, and growth in real disposable income per capita averages 1.4 percent per year. 

•	 The Low Economic Growth case assumes lower growth rates for population (0.8 percent per year) and labor productivity (1.4 

percent per year), resulting in lower nonfarm employment (0.8 percent per year), higher prices and interest rates, and lower 

growth in industrial output. In the Low Economic Growth case, economic output as measured by real GDP increases by 1.9 

percent per year from 2011 through 2040, and growth in real disposable income per capita averages 1.2 percent per year. 

•	 The High Economic Growth case assumes higher growth rates for population (1.0 percent per year) and labor productivity 

(2.1 percent per year), resulting in higher nonfarm employment (1.1 percent per year). With higher productivity gains and 

employment growth, inflation and interest rates are lower than in the Reference case, and consequently economic output 

grows at a higher rate (2.9 percent per year) than in the Reference case (2.5 percent). Disposable income per capita grows by 

1.6 percent per year, compared with 1.4 percent in the Reference case. 

Price Cases – For AEO2013, the benchmark oil price is being re-characterized to represent Brent crude oil instead of WTI crude 

oil. This change, which is being made to better reflect the marginal price refineries pay for imported light, sweet crude oil, used 

to produce petroleum product for consumers.. EIA will continue to report the WTI price, as it is a critical reference point for 

evaluation of the growing production in the mid-continent. EIA will also continue to report the Imported Refiner Acquisition Cost 

(IRAC). 

The historical record shows substantial variability in oil prices, and there is arguably even more uncertainty about future prices in 

the long term. AEO2013 considers three oil price cases (Reference, Low Oil Price, and High Oil Price) to allow an assessment of 

alternative views on the future course of oil prices. 

The Low and High Oil Price cases reflect a wide range of potential price paths, resulting from variation in demand by countries 

outside the Organization for Economic Cooperation and Development (OECD) for petroleum and other liquid fuels due to different 

levels of economic growth. The Low and High Oil Price cases also reflect different assumptions about decisions by members of 

the Organization of the Petroleum Exporting Countries (OPEC) regarding the preferred rate of oil production and about the future 

finding and development costs and accessibility to conventional structurally reservoired oil resources outside the United States.

•	 In the Reference case, real oil prices (in 2011 dollars) rise from $109 per barrel in 2011 to $163 per barrel in 2040. The 

Reference case represents EIA’s current judgment regarding exploration and development costs and accessibility of 

oil resources. It also assumes that OPEC producers will choose to maintain their share of the market and will schedule 

investments in incremental production capacity so that OPEC’s oil production will represent between 40 and 43 percent of 

the world’s total petroleum and other liquids production over the projection period. 

•	 In the Low Oil Price case, crude oil prices are $75 per barrel (2011 dollars) in 2040. The low price results from lower demand 

for petroleum and other liquid fuels in the non-OECD nations. Lower demand is derived from lower economic growth relative 

to the Reference case. In this case, GDP growth in the non-OECD countries is lower on average relative to the Reference 

case in each projection year, beginning in 2013. The OECD projections are affected only by the price impact. On the supply 

side, OPEC countries increase their oil production to obtain a 49-percent share of total world petroleum and other liquids 

production in 2040, and oil resources outside the United States are more accessible and/or less costly to produce (as a result 

of technology advances, more attractive fiscal regimes, or both) than in the Reference case. 

•	 In the High Oil Price case, oil prices reach about $237 per barrel (2011 dollars) in 2040. The high prices result from higher 

demand for petroleum and other liquid fuels in the non-OECD nations. Higher demand is measured by higher economic 

growth relative to the Reference case. In this case, GDP growth in the non-OECD countries is higher on average relative to the 

Reference case in each projection year, beginning in 2013. The OECD projections are affected only by the price impact. On the 

supply side, OPEC countries reduce their market share to between 37 and 40 percent and oil resources outside the United 

States are less accessible and/or more costly to produce than in the Reference case.

In addition to these cases, 22 additional alternative cases presented in Table 1.1 explore the impact of changing key assumptions 

on individual sectors.
10 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Introduction

Table 1.1. Summary of AEO2013 cases

Case name Description

Reference Real GDP grows at an average annual rate of 2.5 percent from 2011 to 2040. Crude oil price 

rise to about $163 per barrel (2011 dollars) in 2040.

Low Economic Growth Real GDP grows at an average annual rate of 1.9 percent from 2011 to 2040. Other energy 

market assumptions are the same as in the Reference case.

High Economic Growth Real GDP grows at an average annual rate of 2.9 percent from 2011 to 2040. Other energy 

market assumptions are the same as in the Reference case.

Low Oil Price Low prices result from a combination of low demand for petroleum and other liquid fuels in the 

non-OECD nations and higher global supply. Lower demand is measured by lower economic 

growth relative to the Reference case. On the supply side, OPEC increases its market share 

to 49 percent, and the costs of other liquids production technologies are lower than in the 

Reference case. Crude oil prices fall to $75 per barrel in 2040.

High Oil Price High prices result from a combination of higher demand for petroleum and other liquids in the 

non-OECD nations and lower global supply. Higher demand is measured by higher economic 

growth relative to the Reference case. Non-OPEC petroleum production expands more slowly 

in the short and middle term relative to the Reference case. Crude oil price rises to $237 per 

barrel (2011 dollars) in 2040.

No Sunset Begins with the Reference case and assumes extension of all existing energy policies and 

legislation that contain sunset provisions, except those requiring additional funding (e.g.,

loan guarantee programs) and those that involve extensive regulatory analysis, such as CAFE

improvements and periodic updates of efficiency standards.

Extended Policies Begins with the No Sunset case and assumes an increase in the capacity limitations on the ITC 

and extension of the program. The case includes additional rounds of efficiency standards for 

residential and commercial products, as well as new standards for products not yet covered; 

adds multiple rounds of national building codes by 2026; and increases LDV fuel economy 

standards in the transportation sector to 57.7 miles per gallon in 2040.

Electricity: Low Nuclear Assumes that all nuclear plants are limited to a 60-year life (45 gigawatts of retirements), 

uprates are limited to the 1.3 gigawatt that has been reported to EIA, and planned additions are 

the same as in the Reference case.. 

Electricity: High Nuclear Assumes that all nuclear plants are life-extended beyond 60 years (except for one announced 

retirement) and uprates are the same as in the Reference case. New plants include those under 

construction and plants that have a scheduled U.S. Nuclear Regulatory Commission or Atomic 

Safety and Licensing Board hearing.

Electricity: Small Modular Reactor Assumes that the characteristics of the new advanced nuclear technology are based on a small 

modular design rather that the AP1000.

Renewable Fuels: Low Renewable 

Technology Cost

Costs for new nonhydropower renewable generating technologies are 20 percent lower than 

in the Reference case through 2040. Capital costs for new BTL technologies and biodiesel 

production technologies are reduced by 20 percent relative to the Reference case through 

2040.

Oil and Gas: Low Oil and Gas Resource Estimated ultimate recovery (EUR) per shale gas, tight gas, and tight oil well is 50 percent 

lower than in the Reference case.

Oil and Gas: High Oil and Gas Resource Shale gas, tight gas, and tight oil well EURs are 100 percent higher than in the Reference 

case, and the maximum well spacing is assumed to be 40 acres. Also includes kerogen 

development, tight oil resources in Alaska, and 50 percent higher undiscovered resources in 

lower 48 offshore and Alaska than in the Reference case.

Liquids Market: Low/No Net Import Uses AEO2013 Reference case oil price, with assumed greater improvement in vehicle efficiency 

and lower vehicle technology costs; post-2025 increase in CAFE standards by 1.4 percent per 

year through 2040; lower vehicle miles traveled (VMT); expanded market availability of LNG/

CNG in heavy-duty trucks, rail, and marine; higher GTL market penetration; optimistic battery 

case (AEO2012) assumptions for electric drivetrain vehicles costs; and greater availability 

of domestic petroleum supply (consistent with the High Oil and Gas Resource case). Also 

assumes increased market penetration of biomass pyrolysis oils, CTL, and BTL production. 

Also, initial assumptions associated with E85 availability and maximum penetration of E15 are 

set to be more optimistic.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 11

Introduction

Table 1.1. Summary of AEO2013 cases (cont.)

Case name Description

Liquids Market: High Net Imports Uses AEO2013 Reference case oil price, with assumed lower improvement in vehicle efficiency 

(driven by limits on technology improvement and non-enforcement of CAFE standards), higher 

VMT, no change in LNG/CNG market availability, no change in GTL penetration, no change in 

biofuel market penetration from the Reference case, and lower availability of domestic petroleum 

supply (consistent with the Low Oil and Gas Resource case).

Coal: Low Coal Cost Regional productivity growth rates for coal mining are approximately 2.5 percent per year higher 

than in the Reference case, and coal mining wages, mine equipment, and coal transportation rates 

in 2040 are lower than in the Reference case.

Coal: High Coal Cost Regional productivity growth rates for coal mining are approximately 2.5 percent per year lower 

than in the Reference case, and coal mining wages, mine equipment, and coal transportation rates 

in 2040 are higher than in the Reference case.

Integrated 2012 Demand Technology Referred to in text as “2012 Demand Technology.” Assumes future equipment purchases in the 

residential and commercial sectors are based only on the range of equipment available in 2012. 

Building shell efficiency is held constant at 2012 levels. Energy efficiency of new industrial plant 

and equipment held constant at the 2013 level over the projection period.

Integrated Best Available

Demand Technology

Referred to in the text as “Best Available Demand Technology.” Assumes that all future equipment 

purchases in the residential and commercial sectors are made from a menu of technologies that 

includes only the most efficient models available in a particular year, regardless of cost. Residential 

building shells for new construction are built to the most efficient specifications after 2012, and 

existing residential shells have twice the improvement of the Reference case. New and existing 

commercial building shell efficiencies improve 50 percent more than in the Reference case by 

2040. Industrial and transportation sector assumptions are the same as in the Reference case.

Integrated High Demand

Technology

Referred to in the text as “High Demand Technology.” Assumes earlier availability, lower costs, and 

higher efficiencies for more advanced residential and commercial equipment. For new residential 

construction, building shell efficiencies are assumed to meet ENERGY STAR requirements after 

2016. Existing residential shells exhibit 50 percent more improvement than in the Reference case 

after 2012. New and existing commercial building shells are assumed to improve 25 percent more 

than in the Reference case by 2040. For the industrial sector, assumes earlier availability, lower 

costs, and higher efficiency for more advanced equipment and a more rapid rate of improvement 

in the recovery of biomass byproducts from industrial processes. In the transportation sector, 

the characteristics of conventional and alternative-fuel LDVs reflect more optimistic assumptions 

about incremental improvements in fuel economy and costs. Freight trucks are assumed to see 

more rapid improvement in fuel efficiency for engine and emissions control technologies. More 

optimistic assumptions for fuel efficiency improvements are also made for the air, rail, and shipping 

sectors.

No GHG Concern No GHG emissions reduction policy is enacted, and market investment decisions are not altered in 

anticipation of such a policy.

GHG10 Applies a price for CO2 emissions throughout the economy, starting at $10 per metric ton in 2014 

and rising by 5 percent per year through 2040.

GHG15 Applies a fee for CO2 emissions throughout the economy, starting at $15 per metric ton in 2014 and 

rising by 5 percent per year through 2040.

GHG25 Applies a fee for CO2 emissions throughout the economy, starting at $25 per metric ton in 2014 

and rising by 5 percent per year through 2040.

GHG10 and Low Gas Prices Combines GHG10 and High Oil and Gas Resource cases.

GHG15 and Low Gas Prices Combines GHG15 and High Oil and Gas Resource cases.

GHG25 and Low Gas Prices Combines GHG25 and High Oil and Gas Resource cases.
12 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Introduction

Carbon dioxide emissions 

CO2 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 CO2 factor for each fossil fuel. The emissions factors are expressed in millions of metric tons of 

carbon dioxide emitted per quadrillion Btu of energy use, or equivalently, in kilograms of CO2 per million Btu. The adjusted 

emissions factors are multiplied by the energy consumption of the fossil fuel to arrive at the CO2 emissions projections.

For fuel uses of energy, all of the carbon is assumed to be oxidized, so the combustion fraction is equal to 1.0 (in keeping with 

international conventions). Previously, a small fraction of the carbon content of the fuel was assumed to remain unoxidized. The 

carbon 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. In calculating CO2 emissions for motor gasoline, the direct emissions from renewable 

blending stock (ethanol) is omitted. Similarly, direct emissions from biodiesel are omitted from reported CO2 emissions.

Any CO2 emitted by biogenic renewable sources, such as biomass and alcohols, is considered balanced by the CO2 

sequestration that occurred in its creation. Therefore, following convention, net emissions of CO2 from biogenic renewable 

sources are assumed to be zero in reporting energy-related CO2 emissions; however, to illustrate the potential for these 

emissions in the absence of any offsetting sequestration, as might occur under related land use change, the CO2 emissions 

from biogenic fuel use are calculated and reported separately.

Table 1.2 presents the assumed CO2 coefficients at full combustion, the combustion fractions, and the adjusted CO2 emission 

factors used for AEO2013.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 13

Introduction

Table 1.2. Carbon dioxide emission factors

million metric tons carbon dioxide equivalent per quadrillion Btu

Fuel Type

Carbon Dioxide 

Coefficient at

Full Combustion

Combustion

Fraction

Adjusted 

Emission 

Factor

Petroleum

Gasoline (net of ethanol) 71.26 1.0000 71.26

Liquefied Petroleum Gas

 Used as Fuel 62.48 1.0000 62.48

 Used as Feedstock 61.60 0.2000 12.32

Jet Fuel 70.88 1.0000 70.88

Distillate Fuel (net of biodiesel) 73.15 1.0000 73.15

Residual Fuel 78.80 1.0000 78.80

Asphalt and Road Oil 75.61 0.0000 0.00

Lubricants 74.21 0.5000 37.11

Petrochemical Feedstocks 71.02 0.4099 29.11

Kerosene 72.31 1.0000 72.31

Petroleum Coke 102.12 0.9557 97.60

Petroleum Still Gas 64.20 1.0000 64.20

Other Industrial 74.54 1.0000 74.54

Coal

Residential and Commercial 95.35 1.0000 95.35

Metallurgical 93.71 1.0000 93.71

Coke 117.81 1.0000 117.81

Industrial Other 93.88 1.0000 93.98

Electric Utility1 95.52 1.0000 95.52

Natural Gas

Used as Fuel 53.06 1.0000 53.06

Used as Feedstocks 53.06 0.4374 23.21

Biogenic Energy Sources

Biomass 88.45 1.0000 88.45

Biogenic Waste 90.65 1.0000 90.65

Biofuels Heats and Coproducts 88.45 1.0000 88.45

Ethanol 65.88 1.0000 65.88

Biodiesel 73.88 1.0000 73.88

Liquids from Biomass 73.15 1.0000 73.15

Green Liquids 73.15 1.0000 73.15

1

Emission factors for coal used for electricity generation are specified by coal supply region and types of coal, so the average CO2 content for coal varies 

throughout the projection. The 2009 average was 95.52.

Source: U.S. Energy Information Administration, Emissions of Greenhouse Gases in the United States 2009, DOE/EIA-0573(2009), (Washington, DC, 

February 2010).
14 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Introduction

Notes and sources

[1] Energy Information Administration, Annual Energy Outlook 2013 (AEO2013), DOE/EIA-0383(2013), (Washington, DC, April 

2013).

[2] NEMS documentation reports are available on the EIA Homepage (www.eia.gov/analysis/model-documentation.cfm).

[3] U.S. Environmental Protection Agency and National Highway Traffic Safety Administration, “2017 and Later Model Year 

Light- Duty Vehicle Greenhouse Gas Emissions and Corporate Average Fuel Economy Standards,” Federal Register, Vol. 77, No. 

199, 40 CFR Parts 85, 86, and 600, and 49 CFR Parts 523, 531, 533, et al. (Washington, DC: October 15, 2012), website www. 

gpo. gov/fdsys/pkg/FR-2012-10-15/html/2012-21972.htm.

[4] U.S. Environmental Protection Agency, “Cross-State Air Pollution Rule (CSAPR)” (Washington, DC: January 14, 2013), 

website http://epa.gov/airtransport. CSAPR was scheduled to begin on January 1, 2012; however, the U.S. Court of Appeals for 

the D.C. Circuit issued a stay delaying implementation while it addresses legal challenges to the rule that have been raised by 

several power companies and States. CSAPR is included in AEO2013 despite the stay, because the Court of Appeals had not 

made a final ruling at the time AEO2013 was published.

[5] U.S. Congress, “Clean Air Act: Chapter 85—Air Pollution Prevention and Control,” 42 U.S.C. 7412 (2011), website www.gpo.

gov/fdsys/pkg/USCODE-2011-title42/pdf/USCODE-2011-title42-chap85.pdf.

[6] U.S. Environmental Protection Agency, “Mercury and Air Toxics Standards (MATS)” (Washington, DC: March 27, 

2012),website www.epa.gov/mats.

[7] California Environmental Protection Agency, Air Resources Board, “Assembly Bill No. 32: Global Warming Solutions Act” 

(Sacramento, CA: September 27, 2006), website www.arb.ca.gov/cc/ab32/ab32.htm.

[8] California Environmental Protection Agency, Air Resources Board, “Low Carbon Fuel Standard Program” (Sacramento, CA: 

January 11, 2013), website www.arb.ca.gov/fuels/lcfs/lcfs.htm. U.S. Environmental Protection Agency, “Mercury and Air Toxics 

Standards,” website www.epa.gov/mats.

[9] Alternative other liquids technologies include all biofuels technologies plus CTL and GTL.
Macroeconomic Activity Module
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U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 17

Macroeconomic Activity Module

The Macroeconomic Activity Module (MAM) represents interactions between the U.S. economy and energy markets. The 

rate of growth of the economy, measured by the growth in gross domestic product (GDP), is a key determinant of growth in 

the 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, (2012), (Washington, DC, October 2012).

Key assumptions

The output of the U.S. economy, measured by GDP, is expected to increase by 2.5 percent between 2011 and 2040 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 2.1 indicates, in the Reference case, real GDP grows by 2.5 percent 

for the next ten years and 2.4 percent growth for the final fifteen years of the projection. Both the high and low macroeconomic 

growth cases show roughly 0.5 percentage point differences in growth as compared to the Reference case. Non-farm 

employment shows higher growth in the first five years of the projection period and then returns to its long-run trend growth. In 

the Reference case, nonfarm employment grows by 1.0 percent from 2011 to 2040 as compared to 1.2 percent and 0.8 percent 

in the High Growth and Low Growth cases, respectively. In the Reference case, productivity (measured as output per hour in 

nonfarm businesses) grows by 1.9 percent from 2011 to 2040; showing slower growth than the 2.0 percent growth experienced 

during the previous 30 years. 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 2011 to 2040.

The Census Bureau’s middle series population projection is used as a basis for population growth in the AEO2013. Total 

population is expected to grow by 0.9 percent per year between 2011 and 2040, 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. 

To achieve the Reference case’s long-run 2.5 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 1.7 and 2.2 percent for the remainder 

of the projection period from 2015 through 2040.

Table 2.1. Growth in gross domestic product, nonfarm employment and productivity

Assumptions 2011-2015 2015-2025 2025-2040 2011-2040 

Real GDP (Billion Chain-Weighted $2005)

 High Growth 2.7% 3.2% 2.7% 2.9%

 Reference 2.5% 2.6% 2.4% 2.5% 

 Low Growth 2.0% 1.7% 2.1% 1.9% 

Nonfarm Employment

 High Growth 1.7% 1.3% 0.9% 1.1%

 Reference 1.6% 0.9% 0.8% 1.0% 

 Low Growth 1.3% 0.9% 0.7% 0.8% 

Productivity

 High Growth 1.0% 2.2% 2.2% 2.1%

 Reference 0.9% 2.0% 2.0% 1.9%

 Low Growth 0.6% 1.4% 1.7% 1.4%

Source: U.S. Energy Information Administration, AEO2013 National Energy Modeling system runs: AEO2013.d102312A, LM2013.d110912A, and HM2013.

d110912A.
18 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Macroeconomic Activity Module

To reflect uncertainty in the projection of U.S. economic growth, the AEO2013 uses High and Low Economic Growth cases to 

project the possible impacts of alternative economic growth assumptions 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 than the Reference case. Investment, disposable income and industrial production are 

greater. Economic output is projected to increase by 2.9 percent per year between 2011 and 2040. 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 1.9 percent per year over 

the projection horizon.
International Energy Module
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U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 21

International Energy Module

The LFMM International Energy Module (IEM) simulates the interaction between U.S. and global petroleum markets. It uses 

assumptions of economic growth and expectations of future U.S. and world crude-like liquids production and consumption to 

estimate the effects of changes in U.S. liquid fuels markets on the international petroleum market. For each year of the forecast, 

the LFMM IEM computes BRENT and WTI prices, provides a supply curve of world crude-like liquids, and generates a worldwide 

oil supply- demand balance with regional detail. The IEM also provides, for each year of the projection period, endogenous and 

exogenous assumptions for petroleum products for import and export in the United States.

Changes in the oil price (BRENT) are computed in response to:

1. The difference between projected U.S. total crude-like liquids production and the expected U.S. total crude-like liquids 

production at the current oil price (estimated using the current oil price and the exogenous U.S. total crude-like liquids 

supply curve for each year). 

and

2. The difference between projected U.S. total crude-like liquids consumption and the expected U.S. total crude-like liquids 

consumption at the current oil price (estimated using the current oil price and the exogenous U.S. total crude-like liquids 

demand curve).

Key assumptions

The level of oil production by OPEC is a key factor influencing the oil price projections incorporated into AEO2013. Non-OPEC 

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

the world oil price.

In the Reference case, real oil prices rise from a $109 per barrel (2011 dollars) in 2012 to $163 per barrel in 2040. The Reference 

case represents EIA’s current judgment regarding exploration and development costs and accessibility of oil resources. It also 

assumes that OPEC producers will choose to maintain their share of the market and will schedule investments in incremental 

production capacity so that OPEC’s oil production will represent about 42 percent of the world’s total petroleum and other 

liquids production over the projection period. In the Low Oil Price case, crude oil prices are $75 per barrel (2011 dollars) in 2040. 

In the Low Oil Price case, the low price results from lower demand for petroleum and other liquid fuels in the non-OECD nations. 

Lower demand is derived from lower economic growth relative to the Reference case. In this case, GDP growth in the non-OECD 

countries is 1.1 lower on average relative to Reference case in each projection year, beginning in 2013. The OECD projections are 

affected only by the price impact. On the supply side, OPEC countries increase their oil production to obtain a 43-percent share 

of total world petroleum and other liquids production, and oil resources outside the United States are more accessible and/or 

less costly to produce (as a result of technology advances, more attractive fiscal regimes, or both) than in the Reference case. In 

the High Oil Price case, oil prices reach about $237 per barrel (2011 dollars) in 2040. In the High Oil Price case, the high prices 

result from higher demand for petroleum and other liquid fuels in the non-OECD nations. Higher demand is measured by higher 

economic growth relative to the Reference case. In this case, GDP growth in the non-OECD countries is 0.6 percent higher on 

average relative to Reference case in each projection year, beginning in 2013. The OECD projections are affected only by the 

price impact. On the supply side, OPEC countries are assumed to reduce their market share slightly, and oil resources outside 

the United States are assumed to be less accessible and/or more costly to produce than in the Reference case.

OPEC oil production in the Reference case is assumed to increase throughout the projection (Figure 3), at a rate that enables 

the organization to maintain an approximately constant market share over the projection period. OPEC is assumed to be an 

important source of additional production because its member nations hold a major portion of the world’s total reserves— 

exceeding 1200 billion barrels, about 73 percent of the world’s estimated total, at the beginning of 2012. [1] Despite investment 

from foreign sources, Iraq’s oil production is not assumed to maintain steady growth until after 2015 as infrastructure limitations 

as well as security and legislative issues are assumed to slow development for the next five years.

Non-U.S., non-OPEC oil production projections in the AEO2013 are developed in two stages. Projections of liquids production 

before 2015 are based largely on a project-by-project assessment of major fields, including volumes and expected schedules, 

with consideration given to the decline rates of active projects, planned exploration and development activity, and countryspecific geopolitical situations and fiscal regimes. Incremental production estimates from existing and new fields after 2015 are 

estimated based on country-specific consideration of economics and ultimate technically recoverable resource estimates. The 

non-OPEC production path for the Reference case is shown in Figure 4.
22 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

International Energy Module

Figure 2. World oil prices in five cases, 1995-2040

2011 dollars per barrel

Source: U.S. Energy Information Administration. AEO2013, National Energy Modeling System runs REF2013. 

D102312A, HIGHPRICE.D110912A, LOWPRNOGTL.D112012A

Figure 3. OPEC total liquids production in the Reference case, 1995-2040

million barrels per day

OPEC = Organization of Petroleum Exporting Countries.

Source: U.S. Energy Information Administration. AEO2013 National Energy Modeling System run REF2013. 

D102312A.

0

25

50

75

100

125

150

175

200

225

250

1995 2000 2005 2010 2015 2020 2025 2030 2035 2040

Reference Case High Price Case

Low Price Case

History Projections
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 23

International Energy Module

Figure 4 Non-OPEC total liquids production in the Reference case, 1995-2040

million barrels per day

OPEC = Organization of Petroleum Exporting Countries.

Source: U.S. Energy Information Administration. AEO2013 National Energiy Modeling System run REF2013. 

D102312A

.

The non-U.S. oil production projections in the AEO2013 are limited by country-level assumptions regarding technically 

recoverable oil resources. Inputs to these resource estimates include the USGS World Petroleum Assessment of 2000 and oil 

reserves published in the Oil & Gas Journal by PennWell Publishing Company, a summary of which is shown in Table 3.1.

The Reference case growth rates for GDP for various regions in the world are shown in Table 3.2. The GDP growth rate 

assumptions for non-U.S. countries/regions are taken from Oxford Economic Model (August 2012).

The values for growth in total liquids demand in the International Energy Module, which depend upon the oil price levels as well 

as GDP growth rates, are shown in Table 3.3 for the Reference case by regions.

Table 3.1. Worldwide oil reserves as of January 1, 2012

billion barrels

Region Proved Oil Reserves

 Western Hemisphere 530.0

 Western Europe 10.9

 Asia-Pacific 47.2

 Eastern Europe and Former Soviet Union (F.S.U.) 120.0

 Middle East 802.2

 Africa 127.6

 Total World 1,637.9

 Total OPEC 1,204.7

Source: Pennwell Corporation, Oil and Gas Journal, Vol 110. 12 (Dec. 3, 2012).
24 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

International Energy Module

Table 3.2. Average annual real gross domestic product rates, 2010-2040 

2005 purchasing power parity weights and prices

Region Average Annual Percentage Change

 OECD 2.17%

 OECD Americas 2.58%

 OECD Europe 1.91%

 OECD Asia 1.58%

 Non-OECD 4.46%

 Non-OECD Europe and Eurasia 3.44%

 Non-OECD Asia 4.97%

 Middle East 2.10%

 Africa 4.63%

 Central and South America 3.37%

 Total World 3.41%

Source: U.S. Energy Information Administration, National Energy Modeling System run REF2013.d102312A.

Table 3.3. Average annual growth rates for total liquids demand in the Reference case, 2010-2040

billion barrels

Region Oil Demand Growth

 OECD 0.05%

 OECD Americas 0.03%

 OECD Europe 0.00%

 OECD Asia 0.19%

 Non-OECD 1.05%

 Non-OECD Europe and Eurasia 1.32%

 Non-OECD Asia 2.23%

 Middle East 1.03%

 Africa 1.75%

 Central and South America 1.09%

 Total World 0.87%

Source: U.S. Energy Information Administration, National Energy Modeling System run REF2013.d102312A; and World Energy Projection system Plus

(2012), run AEO2013_reference_annual2012.09.11_095710.

Notes and sources

[1] PennWell Corporation, Oil and Gas Journal, Vol. 110.12 (December 3, 2012).
Residential Demand Module
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U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 27

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 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” (UEC) by appliance (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 by 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 change 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.

Figure 5. United States Census Divisions

Source: U.S. Energy Information Administration, Office of Energy Analysis.

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
28 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Residential Demand Module

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, dehumidifiers, external power supplies, 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 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, coal, geothermal, and solar energy.

One of the implicit assumptions embodied in the Residential Demand Module is that, through 2040, there will be no radical 

changes in technology or consumer behavior. With the exception of efficiency levels described in consensus agreements among 

equipment manufacturers and efficiency advocates, 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 2040. Currently available technologies will evolve in both 

efficiency and cost. In general, at the same efficiency level, future technologies will be less expensive, in real dollar terms, than 

those available today. 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 4.1). 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.

Table 4.1. 2005 Households

Census Single-Family Units Multifamily Units Mobile Homes Total Units 

New England 3,382,964 1,899,961 173,072 5,465,996 

Middle Atlantic 10,077,231 4,794,686 254,610 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 14,823,660 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

Source: U.S. Energy Information Administration, 2005 Residential Energy Consumption Survey.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 29

Residential Demand Module

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). The Integrating Module of NEMS estimates fuel 

prices through an equilibrium simulation that balances supply and demand and passes the prices to the Residential submodule.

Prices combined with equipment UEC (a function of efficiency) determine the operating costs of equipment. Equipment 

characteristics are exogenous to the model and are modified to reflect both Federal standards and anticipated changes in the 

market place. Table 4.2 lists capital costs and efficiency for selected residential appliances for the years 2010 and 2020.

Table 4.2. Installed cost and efficiency ratings of selected equipment

Equipment Type

Relative 

Performance1

2010 Installed 

Cost (2010$)2

2010 

Efficiency3

2020 

Installed 

Cost 

(2010$)2

2020 

Efficiency3

Approximate 

Hurdle Rate

Minimum $4,800 7.7 $4,950 8.2

Electric Heat Pump (heating component) Best $6,708 10.7 $8,125 10.8 25%

Minimum $2,500 0.78 $2,750 0.90

Natural Gas Furnace4 Best $2,625 0.98 $3,750 0.98 15%

Minimum $275 9.8 $295 11.0

Room Air Conditioner Best $455 12.0 $515 13.0 42%

Minimum $3,200 13.7 $3,550 14.0

Central Air Conditioner Best $4,500 21.0 $5,750 24.0 25%

Minimum $500 511 $525 408

Refrigerator5 Best $850 342 $1,250 327 10%

Minimum $600 0.90 $675 0.95

Electric Water Heater Best $1,370 2.35 $2,050 2.35 50%

Solar Water Heater6 N/A $5,320 N/A $7,300 N/A 30%

1

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

2

Installed costs are given in 2010 dollars in the original source document.

3

Efficiency measurements vary by equipment type. Electric heat pumps are based on Heating Seasonal Performance Factor (HSPF); natural gas furnaces 

are based on Annual Fuel Utilization Efficiency (AFUE); central air conditioners are based on Seasonal Energy Efficiency Ratio (SEER); 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).

4Values are for Northern regions of U.S.

5 Reflects refrigerator with top mounted freezer with 20.6 cubic feet nominal volume.

6

Values are for Southern regions of U.S.

Source: EIA Technology Forecast Updates, (Navigant Consulting , 2010).

Table 4.3 provides the cost and performance parameters for representative distributed generation technologies. The 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 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. Capital costs for small wind, a relatively mature technology, only decline three percent with each doubling 

of shipments.

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 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 fuel or 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 across fuels upon 

replacement is allowed for space heating, air conditioning, water heating, cooking and clothes drying. 
30 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Residential Demand Module

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, some 

intermediate levels, 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 obtain calculations for the apparent discount 

rates based on the relative weight given to the operating cost savings versus the weight given to the higher initial 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 (10 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 the number of units which survive 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 major end uses not considered to be “fully penetrated.”

Table 4.3. Capital cost and performance parameters of selected residential distributed generation technologies

Technology Type

Year of 

Introduction

Average 

Generating 

Capacity (kWDC)

Electrical 

Efficiency

 Combined 

Efficiency 

(Elec. + 

Thermal 

Installed 

Capital Cost 

(2009 $ per 

kWDC)1

Service 

Life (Years)

Solar Photovoltaic

2010 3.5 0.150 N/A $7,200 30

2015 4.0 0.175 N/A $4,965 30

2025 5.0 0.197 N/A $3,664 30

2035 5.0 0.200 N/A $3,462 30

Fuel Cell

2010 10 0.364 0.893 $14,837 20

2015 10 0.429 0.859 $14,837 20

2025 10 0.456 0.842 $14,837 20

2035 10 0.479 0.828 $14,837 20

Wind

2010 2 0.13 N/A $7,802 30

2015 3 0.13 N/A $6,983 30

2025 3 0.13 N/A $6,234 30

2035 4 0.13 N/A $5,903 30

1

The original source documents presented solar photovoltaic costs in 2008 dollars, fuel cell and wind costs in 2010 dollars.

Source: Solar photovoltaic: Photovoltaic (PV) Cost and Performance Characteristics for Residential and Commercial Applications (ICF International, 2010). 

Fuel cell: Commercial and Industrial CHP Technology Cost and Performance Data Analysis for EIA (SENTECH Incorporated, 2010). Wind: The Cost and 

Performance of Distributed Wind Turbines, 2010-35 (ICF International, 2010).
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 31

Residential Demand Module

Once a piece of equipment enters into the stock, an accounting of its remaining life begins. The decay function is based on Weibull 

distribution shape parameters that approximate linear decay functions. The estimated maximum and minimum equipment 

lifetimes used to inform the Weibull shape parameters are shown in Table 4.4. Weibull shapes allow some retirement before the 

listed minimum lifetime, as well as allow some equipment to survive beyond its listed maximum lifetime. It is 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 second-hand market 

for this equipment.

Table 4.4. Minimum and maximum life expectancies of equipment

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

Source: Lawrence Berkeley National Laboratory. Baseline Data for the Residential Sector and Development of a Residential Forecasting Database, May 1994, 

and analysis of RECS 2001 data.

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, 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 for most technology types is initially based on estimates derived from RECS 2005. 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 to be vintaged and retirements to be projected by vintage and efficiency, as older equipment tends to be lower 

in efficiency and also tends to be 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 ten 

percent more efficient than in 2005, then all else constant (weather, real energy prices, shell efficiency, etc.), energy consumption 

per heat pump would average about only nine percent less.

Adjusting for the size of housing units

Information derived from RECS 2005 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 one 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 a housing unit from 1,618 to 1,767 square 

feet from 2005 through 2040.
32 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Residential Demand Module

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. The residential module adjusts space heating and air conditioning UECs by Census Division 

using data on heating and cooling degree-days (HDD and CDD). Short-term projections are informed by the National Oceanic 

and Atmospheric Administration’s (NOAA) 15-month outlook from their Climate Prediction Center[5], which often encompasses 

the first forecast year (2013 in the case of AEO2013). Projections of degree days beyond that are informed by a 30-year linear 

trend of each state’s degree days, which are then population-weighted to the Census division level. In this way, the projection 

accounts for projected population migrations across the nation and continues any realized historical changes in degree days at 

the state level.

A ten-percent increase in HDD would increase space heating consumption by ten percent over what it would have otherwise 

been, while a ten-percent increase in CDD would increase cooling consumption by about 12.5 percent.

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 for non-electric fuels is -0.15 [6]. 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. Changes in 

equipment efficiency also affect the marginal cost of providing a service. 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, cooling, and lighting are 

assumed to be affected by both elasticities

and the efficiency rebound effect. For electricity, the short-term elasticity parameter is set to -0.30 to account for successful 

deployment of smart grid projects funded under the American Recovery and Reinvestment Act of 2009 (ARRA09).

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 heated with electricity tend to have less air infiltration rates than homes that 

use other fuels. Homes are classified by age as new (post-2005) or existing. Existing homes are represented 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) [7] to homes that are built with the most efficient shell components. Shell efficiency in new homes 

increases over time when energy prices rise, or the cost of more efficient equipment falls, all else equal.

Legislation and regulations

American Recovery and Reinvestment Act of 2009 (ARRA09)

The ARRA09 legislation passed in February 2009 provides energy efficiency funding for Federal agencies, State Energy Programs, 

and block grants, as well as a sizable increase in funding for weatherization. To account for the impact of this funding, it is 

assumed that the total funding is aimed at increasing the efficiency of the existing housing stock. The assumptions regarding the 

energy savings for heating and cooling are based on evaluations of the impact of weatherization programs over time. Further, 

it is assumed each house requires a $2,600 investment to achieve the heating and cooling energy savings cited in [8] and that 

the efficiency measures last approximately 20 years. Assumptions for funding amounts and timing were revised downward and 

further into the future based on analysis of the weatherization program by the Inspector General of the Department of Energy 

[9].

The ARRA09 provisions remove the cap on the 30-percent tax credit for ground-source heat pumps, solar PV, solar thermal water 

heaters, and small wind turbines through 2016. Additionally, the cap for the tax credits for other energy efficiency improvements, 

such as windows and efficient furnaces, was increased to $1,500 through the end of 2010. Several tax credits were extended 
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 33

Residential Demand Module

at reduced credit levels through the end of 2011 as part of the Tax Relief, Unemployment Insurance Reauthorization, and Job 

Creation Act of 2010. These tax credits were further extended through the end of 2013 as part of the American Taxpayer Relief 

Act of 2012, but this legislation was passed too late to be included in AEO2013.

Successful deployment of smart grid projects based on ARRA09 funding could stimulate more rapid investment in smart grid 

technologies, especially smart meters on buildings and homes, which would make consumers more responsive to electricity 

price changes. To represent this, the price elasticity of demand for residential electricity was increased for the services that have 

the ability to alter energy intensity (e.g., lighting)

Energy Improvement and Extension Act of 2008 (EIEA 2008)

EIEA 2008 extends and amends many of the tax credits that were made available to residential consumers in EPACT 2005. The 

tax credits for energy-efficient equipment can now be claimed through 2016, while the $2,000 cap for solar technologies has 

been removed. Additionally, the tax credit for ground-source (geothermal) heat pumps was increased to $2,000. The production 

tax credits for dishwashers, clothes washers, and refrigerators were extended by one to two years, depending on the efficiency 

level and product. See the EPACT 2005 section below for more details about product coverage

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 a seven-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.

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. For manufactured homes that are 30 percent better than the latest 

code, a $1,000 tax credit can be claimed in 2006 and 2007. Likewise, builders of homes that are 50 percent better than code 

can claim a $2,000 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.

Residential alternative cases

Technology cases

In addition to the Reference case, the Residential Demand Module contributes alternate assumptions to five side cases 

developed to examine the effect of different assumptions of technology and policy on energy use. Three cases are devoted 

to technology assumptions in the demand sectors: the 2012 Technology case, a High Technology case, and a Best Available 

Technology case. Two cases, the Integrated Low Technology and High Technology cases, combine demand sector technology 

assumptions with alternative technology assumptions for renewable and fossil fuel electricity generation technologies. Two 

cases examine policy continuation impacts: the No Sunset case and the Extended Policies case.

The 2012 Technology assumptions specify that all future equipment purchases are made based only on equipment available 

in 2012. These cases further assume that existing building shell efficiencies will not improve beyond 2012 levels. The 2012 

Technology assumptions are implemented in the 2012 Integrated Demand Technology case.

The High Technology assumptions include earlier availability, lower costs, and/or higher efficiencies for more advanced 

equipment than the Reference case. Equipment assumptions developed by engineering technology experts reflect the potential 

impact on technology given increased research and development into more advanced technologies [10]. In the High Technology 

cases, all new construction is assumed to meet Energy Star specifications after 2016. In addition, consumers are assumed 

to evaluate energy efficiency investments at a discount rate of seven percent real. The High Technology assumptions are 

implemented in the Integrated High Demand Technology case.
34 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Residential Demand Module

The Best Available Demand Technology case assumptions require that all equipment purchases from 2013 forward are based on 

the highest available efficiency in the High Technology case in a particular modeled 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 2012. In addition, consumers are assumed to 

evaluate energy efficiency investments at a discount rate of seven percent real.

Policy cases

The No Sunset case assumes the extension of all existing energy policies and legislation that contain sunset provisions. For the 

residential sector, this primarily involves tax credits for distributed generation and efficient end-use equipment. The Extended 

Policy case assumes additional rounds of appliance standards for most end-use equipment while maintaining the No Sunset tax 

credit assumptions for distributed generation, solar water heaters, and geothermal heat pumps. Standard levels are established 

based on current Energy Star guidelines. The Extended Policy case also adds multiple rounds of building codes by 2026.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 35

Residential Demand Module

Notes and sources

[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-M067(2012), (December 2012). http://www.eia.gov/forecasts/nemsdoc/

residential/pdf/m067%282012%29.pdf

[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. 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 Remodeler, 2002 Home Remodeling

Study.

[5] National Oceanic and Atmospheric Administration, National Weather Service, Experimental Monthly Degree Day 

Forecast, http://www.cpc.ncep.noaa.gov/pacdir/DDdir/ddforecast.txt. Explanation of forecast available at http://www.

cpc.ncep.noaa.gov/pacdir/DDdir/N1.html.

[6] See Dahl, Carol, A Survey of Energy Demand Elasticities in Support of the Development of the NEMS, October 1993. 

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

heating and cooling load.

[8] Oak Ridge National Laboratory, Estimating the National Effects of the U.S. Department of Energy’s Weatherization

Assistance Program with State-Level Data: A Metaevaluation Using Studies from 1993 to 2005, September 2005.

[9] U.S. Department of Energy, Office of Inspector General, Office of Audit Services, Special Report: Progress in 

Implementing the Department of Energy’s Weatherization Assistance Program under the American Recovery and 

Reinvestment Act, February 2010.

[10] The high technology assumptions are based on Energy Information Administration, Technology Forecast UpdatesResidential and Commercial Building Technologies-Advanced Adoption Case (Navigant Consulting, September 2011).
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Commercial Demand Module
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U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 39

Commercial Demand Module

The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2040. 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 fuel [2] 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 services [3] for 

eleven building categories [4] 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 agerelated 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 5.1). 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 5.2 [8].

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.
40 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Commercial Demand Module

Table 5.1. 2003 Total floorspace by Census Division and principal building activity 

millions of square feet

Assembly Education

Food

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 5,580

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

Total 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

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

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

Table 5.2. Floorspace attrition parameters

Assembly Education

Food

Sales

Food

Service

Health

Care Lodging

Large

Office

Small

Office

Merc/

Service Warehouse Other

Median Expected 

Lifetime (years) 55 62 55 50 55 53 65 58 50 58 60

Gamma 2.2 2.1 2.3 2.0 2.5 2.1 2.0 2.0 2.2 2.0 2.3

Source: U.S. Energy Information Administration, Commercial Buildings Energy Consumption Survey 2003, 1999, 1995, 1992, and 1989 Public Use Data, 

1986 Nonresidential Buildings Energy Consumption Survey, McGraw-Hill Construction Dodge Annual Starts - non-residential building starts, Northwest 

Energy Efficiency Alliance, Assessment of the Commercial Building Stock in the Pacific Northwest, KEMA-XENERGY, Inc., March 2004, and public 

information on demolitions.

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 separate building shell heating and cooling 

factors which change over time to reflect improvements in the building shell. The factors, dimensioned by building type and 

Census division, affect the space heating and cooling service demand intensities causing changes in fuel consumed for these 

services as the shell integrity improves. In the AEO2013 Reference case building shells for new construction built in 2003 are up 

to 49 percent more efficient with respect to heating and up to 30 percent more efficient with respect to cooling relative to the 

average shell for existing buildings of the same type. Over the projection horizon, new building shells improve in efficiency by 

15.0 percent relative to their efficiency in 2003. For existing buildings, efficiency is assumed to increase by 6.9 percent over the 

2003 stock average. 

Distributed generation and combined heat and power

Program-driven installations of solar photovoltaic systems are based primarily on information from the Interstate Renewable 

Energy Council’s annual report on U.S. solar market trends. Historical data from Form EIA-860, Annual Electric Generator Report, 

are used to derive electricity generation for 2004 through 2009 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 internal rate of return relative to purchased electricity. Table 5.3 provides the cost and performance parameters for 

representative distributed generation and CHP technologies.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 41

Commercial Demand Module

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 

AEO2013 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:

• 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.

• 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 5.4 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. Adding the risk-adjusted time preference premiums to the 10-year Treasury 

note 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 AEO2013 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 share of 

floorspace assigned to each rate in the distribution varies by end-use service. Table 5.5 illustrates the distribution of time 

preference premiums for space heating and lighting in 2015. 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 note 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.
42 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Commercial Demand Module

Table 5.3. Capital cost and performance parameters of selected commercial distributed generation technologies

Technology Type

Year of 

Introduction

Average 

Generating 

Capacity

 (kWDC)

Electrical 

Efficiency

 Combined 

Efficiency 

(Elec. + 

Thermal)

Installed 

Capital Cost

 (2009 $ per 

kWDC)*

Service 

Life

(Years)

Solar Photovoltaic 2010 30 0.15 N/A $6,410 30

2015 35 0.18 N/A $4,475 30

2025 40 0.20 N/A $3,340 30

2035 45 0.20 N/A $3,151 30

Fuel Cell 2010 300 0.42 0.65 $7,404 20

2015 300 0.49 0.66 $5,019 20

2025 300 0.51 0.69 $4,016 20

2035 300 0.54 0.73 $3,180 20

Natural Gas Engine 2010 334 0.30 0.82 $1,780 20

2015 334 0.31 0.85 $1,630 20

2025 334 0.30 0.87 $1,251 20

2035 334 0.30 0.91 $831 20

Oil-fired Engine 2010 300 0.34 0.73 $1,784 20

2015 300 0.34 0.74 $1,746 20

2025 300 0.35 0.80 $1,669 20

2035 300 0.36 0.78 $1,592 20

Natural Gas Turbine 2010 3510 0.25 0.76 $1,884 20

2015 3510 0.25 0.77 $1,858 20

2025 3510 0.25 0.80 $1,760 20

2035 3510 0.25 0.82 $1,645 20

Natural Gas Microturbine 2010 200 0.32 0.61 $2,414 20

2015 200 0.34 0.67 $2,098 20

2025 200 0.37 0.73 $1,467 20

2035 200 0.41 0.80 $836 20

Wind 2010 32 0.13 N/A $5,243 30

2015 35 0.13 N/A $4,715 30

2025 40 0.13 N/A $3,973 30

2035 50 0.13 N/A $3,627 30

*The original source documents presented solar photovoltaic costs in 2008 dollars, all other technologies in 2010 dollars. Costs for solar photovoltaic, fuel cell, 

microturbine, and wind technologies include learning effects. 

Sources: U.S. Energy Information Administration, Commercial and Industrial CHP Technology Cost and Performance Data Analysis for EIA SENTECH, Inc., 

and SAIC, Inc., June 2010, U.S. Energy Information Administration, Photovoltaic (PV) Cost and Performance Characteristics for Residential and Commercial 

Applications Final Report, ICF International, August 2010, and U.S. Energy Information Administration, The Cost and Performance of Distributed Wind Turbines, 

2010-35 Final Report, ICF International, August 2010.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 43

Commercial Demand Module

Table 5.4. Assumed behavior rules for choosing space heating equipment in large office buildings

percent

Unrestricted Same Fuel Same Technology Total

New Equipment Decision 21 30 49 100

Replacement Decision 7 31 62 100

Retrofit Decision 1 4 95 100

Source: U.S. Energy Information Administration, Model Documentation Report: Commercial Sector Demand Module of the National Energy Modeling System,

DOE/EIA-M066(2012) (August 2012).

Table 5.5. Assumed distribution of risk-adjusted time preference premiums for space heating and lighting equipment in 

2015

percent

Time Preference Premium Proportion of Floorspace-Space Heating (2015) Proportion of Floorspace-Lighting (2015)

1000.0 27.0 27.0

100.0 23.0 23.0

45.0 19.0 18.6

25.0 18.6 18.6

15.0 10.7 8.8

6.5 1.5 1.5

0.0 0.2 2.5

-- 100.0 100.0

Source: U.S. Energy Information Administration, Model Documentation Report: Commercial Sector Demand Module of the National Energy Modeling System, 

DOE/EIA-M066(2012) (August 2012).

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 

AEO2013 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 0.0 rate given in Table 5.5), 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 5.6 provides a sample of the technology data for 

space heating in the New England Census division.

An option has been included to allow endogenous price-induced technological change 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 AEO2013 model runs.
44 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Commercial Demand Module

Table 5.6. Capital cost and efficiency ratings of selected commercial space heating equipment1

Equipment Type Vintage Efficiency2

Capital Cost 

(2010$ per Mbtu/

hour)3

Maintenance Cost 

(2007$ per Mbtu/

hour)3

Service Life 

(Years)

Rooftop Air-Source Heat 

Pump 2003 installed base 3.10 $63.89 $1.39 15

2010 current standard/typical 3.30 $76.67 $1.39 15

2010 high 3.40 $96.67 $1.39 15

2020 typical 3.30 $76.67 $1.39 15

2020 high 3.40 $96/67 $1.39 15

Ground-Source Heat Pump 2003 installed base 3.40 $140.00 $16.80 20

2010 typical 3.50 $140.00 $16.80 20

2007-10 high 4.90 $170.00 $16.80 20

2020 typical 3.50 $140.00 $16.80 20

2020 high 4.90 $170.00 $16.80 20

Electric Boiler 2003 installed base 0.94 $15.64 $0.24 15

2010 typical 0.94 $15.64 $0.24 15

Electric Resistance Heater 2003 installed base 0.98 $21.76 $0.01 18

Natural Gas Heat Pump 2003 installed base (residential type) 1.30 $158.33 $2.50 15

2010 typical (engine-driven rooftop) 1.40 $312.50 $4.58 30

2020 typical (engine-driven rooftop) 1.40 $212.50 $4.58 30

2030 typical (engine-driven rooftop) 1.40 $129.17 $4.58 30

Natural Gas Furnace 2003 installed base 0.71 $9.85 $1.06 17.5

2010 current standard/typical 0.78 $9.84 $0.97 17.5

2010 high 0.80 $10.30 $0.94 17.5

2020 typical 0.78 $9.84 $0.97 17.5

2020 high 0.88 $10.67 $0.66 17.5

2030 typical 0.78 $9.84 $0.97 17.5

2030 high 0.89 $11.88 $0.85 17.5

2035 high 0.91 $12.25 $0.83 17.5

Natural Gas Boiler 2003 installed base 0.73 $20.55 $0.77 25

2010 current standard/typical 0.78 $25.64 $0.72 25

2012 standard 0.80 $21.02 $0.47 25

2012 mid-range 0.89 $28.79 $0.63 25

2010 high 0.97 $38.02 $0.58 25

2020 typical 0.80 $25.00 $0.70 25

2020 high 0.97 $38.02 $0.58 25

2030 typical 0.80 $25.00 $0.70 25

Distillate Oil furnace 2003 installed base 0.76 $13.56 $0.99 18.5

2010 typical 0.80 $13.28 $0.94 18.5

2020 typical 0.80 $13.28 $0.94 18.5

Distillate Oil Boiler 2003 installed base 0.76 $17.54 $0.17 25

2010 current standard 0.81 $18.21 $0.16 25

2010-12 standard 0.82 $18.10 $0.16 25

2010 high 0.87 $25.05 $0.13 25

2020 typical 0.82 $18.10 $0.16 25

2020 high 0.87 $25.05 $0.13 25 *

Equipment 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 reference 

below for the complete set of technology data.

2

Efficiency 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 and boilers are based on Thermal Efficiency.

Source: U.S. Energy Information Administration, “EIA - Technology Forecast Updates - Residential and Commercial Building Technologies - Reference Case”, 

Navigant Consulting, Inc., October 2011.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 45

Commercial Demand Module

End-Use Consumption Submodule

The end-use consumption submodule calculates the consumption of each of the three major fuels (electricity, natural gas, 

and distillate fuel oil) 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 (residual fuel oil, liquefied petroleum gas, motor 

gasoline, kerosene, and coal) 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 as much as, 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). Short-term projections are informed by the 

National Oceanic and Atmospheric Administration’s (NOAA) 15-month outlook from their Climate Prediction Center[13], 

which often encompasses the first forecast year. Projections of degree days beyond that are informed by a 30-year linear 

trend of each state’s degree days, which are then population-weighted to the Census division level. In this way, the projection 

accounts for projected population migrations across the nation and continues any realized historical changes in degree days 

at the state level. A 10-percent increase in HDD would increase space heating consumption by 10 percent over what it would 

have been, while a ten-percent increase in CDD would increase cooling consumption by about 12.5 percent.

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 over 

time, 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

American Recovery and Reinvestment Act of 2009 (ARRA09)

The ARRA09 legislation passed in February 2009 provides energy efficiency funding for federal agencies, State Energy 

Programs, and block grants. To account for the impact of this funding, states are assumed to adopt and enforce the ASHRAE 

90.1-2007 standard by 2018 for building shell measures, and all Public buildings (federal, state, and local) are assumed to 

use the 10-year Treasury note rate for purchase decisions related to both new construction and replacement equipment while 

stimulus funding is available. A percentage of the State Energy Program and Conservation Block Grant funding is assumed 

to be used for solar photovoltaic and small wind turbine installations. Additional stimulus funding is applied to fuel cell 

installations.

The ARRA09 provisions remove the cap on the 30-percent Business Investment Tax Credit for wind turbines. The Investment 

Tax Credit is still available for systems installed through 2016. These credits are directly incorporated into the cash-flow 

approach for distributed generation systems. 
46 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Commercial Demand Module

Energy Imropovement and Extension Act of 2008 (EIEA08)

The EIEA08 legislation passed in October 2008 extends the Business Investment Tax Credit provisions of the Energy Policy Act 

of 2005 and expands the credit to include additional technologies. The Business Investment Tax Credits of 30 percent for solar 

energy systems and fuel cells and 10 percent for microturbines are extended through 2016. The cap on the fuel cell credit has 

been increased from $500 to $1,500 per half kilowatt of capacity. The EIEA08 provisions expand the Investment Tax Credit to 

include a 10-percent credit for CHP systems and ground-source heat pumps and a 30-percent credit for wind turbines with the 

wind credit capped at $4,000. The expanded credits are available for systems installed through 2016. These credits are directly 

incorporated into the cash-flow approach for distributed generation systems, including CHP, and factored into the installed capital 

cost assumptions for solar hot water heaters and ground-source heat pumps.

Energy Independence and Security Act of 2007 (EISA07)

The EISA07 legislation passed in December 2007 provides standards for specific 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 note 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 premise 

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 drytype 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 pre-rinse spray valves [14] must 

have a maximum flow rate of 1.6 gallons per minute, effective January 1, 2006 with energy reductions attributed to hot water use.

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. Some of the EPACT92 standards implemented 

in the module include: gas and oil-fired boilers—minimum combustion efficiency of 0.80 and 0.83, respectively, amended to 

minimum thermal efficiency of 0.80 and 0.81, respectively, in 2012; gas and oil-fired furnaces—minimum thermal efficiency of 
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 47

Commercial Demand Module

0.80 and 0.81, respectively; electric water heaters—minimum energy factor of 0.85; and gas and oil water heaters—minimum 

thermal efficiency of 0.80 and 0.78, respectively. A fluorescent lamp ballast standard effective in 2005 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. 

Fluorescent lamps and incandescent reflector lamb bulbs must meet amended standard levels for minimum average lamp 

efficacy in 2012. Recent updates for commercial refrigeration equipment include maximum energy consumption standards for 

refrigerated vending machines and display cases based on volume.

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 riskadjusted 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 5.5. Also the shell efficiency of new and existing 

buildings is assumed to increase from 2003 through 2040. Shells for new buildings increase in efficiency by 15.0 percent over 

this period, while shells for existing buildings increase in efficiency by 6.9 percent.

Commercial alternative cases

Technology cases

In addition to the AEO2013 Reference case, three side cases were developed to examine the effect of equipment and building 

standards on commercial energy use—a 2012 Demand Technology case, a High Demand Technology case, and a Best Available 

Demand Technology case. These side cases were analyzed in integrated runs with the NEMS demand and supply modules and 

thus include supply responses to the altered commercial consumption patterns of the three cases. AEO2013 also analyzed a 

Low Renewable Technology Cost case.

The 2012 Demand Technology case assumes that all future equipment purchases are made based only on equipment available 

in 2012. This case assumes building shell efficiency to be fixed at 2012 levels. In the High Demand Technology case, depending 

on technology or end use, equipment costs are lower, efficiencies are higher, and equipment is available sooner than in the 

Reference case. Energy efficiency investments are evaluated at 7 percent real rather than the distribution of hurdle rates 

assumed for 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 addition to 

equipment improvements, building shell efficiencies are assumed to improve 25 percent more than in the Reference case after 

2012. Existing building shells, therefore, increase by 8.6 percent relative to 2003 levels and new building shells by 18.8 percent 

relative to their efficiency in 2003 by 2040.

The Best Available Demand Technology case assumes that all equipment purchases after 2012 are based on the highest 

available efficiency for each type of technology in the High Demand 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 2012, i.e., existing shells increase by 10.4 percent relative to 2003 levels and new building shells by 22.5 

percent relative to their efficiency in 2003 by 2040.

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.

The Low Renewable Cost case, which focuses on electricity generation, incorporates alternative assumptions for non-hydro 

renewable energy technologies in the power sector, the industrial sector, and the buildings sectors, including residential and 

commercial photovoltaic and wind systems. In this case, assumptions regarding non-renewable technologies are not changed 

from the Reference case. It assumes that costs for residential and commercial photovoltaic and wind systems are 20 percent 

below Reference case assumptions beginning in 2013 and continuing through the projection period.
48 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Commercial Demand Module

Analysis cases

Two integrated analysis cases were completed for the AEO2013: the No Sunset and Extended Policies cases. Both cases are 

based upon Reference case assumptions, with additional changes made to extend existing tax credits and policies beyond those 

prescribed by current law.

In the No Sunset case, the 30-percent solar photovoltaic investment tax credit (ITC) that is scheduled to revert to a 10-percent 

credit in 2016 is, instead, assumed to be extended indefinitely at 30 percent. Additional tax credits for the purchase of other 

renewable and combined heat and power equipment, such as ground-source heat pumps and fuel cells, are also assumed to be 

extended indefinitely as opposed to expiring in 2016.

The Extended Policies case adopts the same assumptions as the No Sunset case and includes additional changes. For instance, 

federal equipment efficiency standards are updated at particular intervals consistent with the provisions in the existing law, 

with the levels based on ENERGY STAR specifications, or Federal Energy Management Program (FEMP) purchasing guidelines 

for federal agencies. Standards are also introduced for products that currently are not subject to federal efficiency standards. 

Updated national building energy codes reach 30-percent improvement in 2020 relative to the American Society of Heating, 

Refrigerating and Air-Conditioning Engineers (ASHRAE) Building Energy Code 90.1-2004 in the commercial sector. Two 

subsequent rounds in 2023 and 2026 each add an assumed 5-percent incremental improvement to building energy codes.

The equipment standards and building codes assumed for the Extended Policies case are meant to illustrate the potential effects 

of these polices on energy consumption for buildings. No cost-benefit analysis or evaluation of impacts on consumer welfare was 

completed in developing the assumptions. Likewise, no technical feasibility analysis was conducted, although standards were not 

allowed to exceed “maximum technologically feasible” levels described in DOE’s technical support documents.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 49

Commercial Demand Module

Notes and sources

[1] U.S. Energy Information Administration, 2003 Commercial Buildings Energy Consumption Survey (CBECS) Public Use

Files, web site www.eia.gov/emeu/cbecs/cbecs2003/public_use_2003/cbecs_pudata2003.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 existing solar photovoltaic system installations, projected installations due to state and local incentive 

programs, and the potential endogenous penetration of solar photovoltaic systems and solar thermal water heaters. The 

use of wind energy is projected based on an estimate of existing distributed wind turbines and the potential endogenous 

penetration of wind turbines in the commercial sector.

[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 U.S. Energy Information Administration, Model Documentation Report: Commercial Sector Demand 

Module of the National Energy Modeling System, DOE/EIA M066(2012), (August 2012).

[7] The commercial floorspace equations of the Macroeconomic Activity Model are estimated using the McGraw-Hill 

Construction Research & Analytics database of historical floorspace estimates. The McGraw-Hill Construction 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 McGraw-Hill Construction data.

[9] In the event that the computation of additions produces 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, escalators, 

medical, and other laboratory equipment, laundry, 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 2003 CBECS end-use-level consumption data developed using 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] National Oceanic and Atmospheric Administration, National Weather Service, Experimental Monthly Degree Day 

Forecast, http://www.cpc.ncep.noaa.gov/pacdir/DDdir/ddforecast.txt. Explanation of forecast available at http://www.

cpc.ncep.noaa.gov/pacdir/DDdir/N1.html.

[14] Commercial pre-rinse spray valves are handheld devices used to remove food residue from dishes and flatware 

before cleaning.
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Industrial Demand Module
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U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 53

Industrial Demand Module

The NEMS Industrial Demand Module (IDM) estimates energy consumption by energy source (fuels and feedstocks) 

for 15 manufacturing and 6 non-manufacturing industries. The manufacturing industries are subdivided further into 

the energy- intensive manufacturing industries and non-energy-intensive manufacturing industries (Table 6.1). The 

manufacturing industries are modeled through the use of a detailed process-flow or end-use accounting procedure. The 

non-manufacturing industries are modeled with less detail because processes are simpler and there is less available data. 

The petroleum refining industry is not included in the Industrial Demand Module, as it is simulated separately in the Liquid 

Fuels Market Module (LFMM) of NEMS. The IDM calculates energy consumption for the four Census Regions (see Figure 

5) and disaggregates regional energy consumption to the nine Census Divisions based on fixed shares from the U.S. Energy 

Information Administration (EIA) State Energy Data System [1].

Table 6.1. Industry categories and NAICS codes

Energy-Intensive Manufacturing Non-energy-Intensive Manufacturing Non-Manufacturing

Food products (NAICS 311) Metal-based durables Agricultural crop 

Paper and allied products (NAICS 322) Fabricated metal products (NAICS 332) production (NAICS 111)

Bulk chemicals Machinery (NAICS 333)

 Inorganic (NAICS 32512-

32518)

 Computer and electronic 

 products

(NAICS 334) Other agricultural 

production

(NAICS 112, 

113, 115)

 Organic (NAICS 32511, 

32519)

 Electrical equipment and 

 appliances

(NAICS 335) Coal mining (NAICS 

2121)

 Resins (NAICS 3252) Transportation equipment (NAICS 336)

Oil and gas 

extraction (NAICS 211)

 Agricultural Chemicals (NAICS 3253) Other Metal and other 

non-metallic 

mining

(NAICS 

2122-2123)

Glass and glass products (NAICS 3272) Wood products (NAICS 321)

Cement and Lime

(NAICS 32731, 

32741)

 Plastic and rubber 

 products

(NAICS 326) Construction (NAICS 23)

Iron and steel (NAICS 3311-

3312)

 Balance of manufacturing (NAICS 31-33 

not already 

classified)

Aluminum (NAICS 3313)

NAICS = North American Industry Classification System (2007).

Source: Office of Management and Budget, North American Industry Classification system (NAICS) - United States (Springfield, VA. National 

Technical Information Service).

The energy-intensive manufacturing industries, consisting of food products, paper and allied products, bulk chemicals, glass 

and glass products, cement and lime, iron and steel, and aluminum, are modeled in considerable detail. Each industry is 

modeled as three separate but interrelated components: the Process and Assembly (PA) Component, the Buildings (BLD) 

Component, and the Boiler, Steam, and Cogeneration (BSC) Component. The BSC Component satisfies the steam demand 

from the PA and BLD Components. In some industries, the PA 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 (NAICS 32411) is modeled in detail in the LFMM of NEMS, and the projected energy 

consumption is reported in the manufacturing total.

Projections of refining energy use, lease and plant fuel, and fuels consumed in cogeneration in the oil and gas extraction 

industry (NAICS 211) are exogenous to the Industrial Demand Module, but endogenous to the NEMS modeling system.

Key assumptions - manufacturing 

The NEMS Industrial Demand Module primarily uses a bottom-up 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 2006 baseline Unit Energy Consumption (UEC) estimates based on analysis and interpretations of the 2006 

Manufacturing Energy Consumption Survey (MECS) which is conducted by the EIA on a four-year survey cycle [2]. The 

UECs represent the energy required to produce one unit of the industry’s output. A unit of output may be defined in terms of 

physical units (e.g., tons of steel) or in dollar value of shipments. 
54 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Industrial Demand Module

The Industrial Demand Module depicts the manufacturing industries, except for petroleum refining, 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 (TPC). With the exception of the cement and lime industries and the aluminum 

industry, the technology possibility curve is an exponential growth trend corresponding to a given average annual rate of change, 

or TPC. The TPC depicts the assumed average annual rate of change in energy intensity of a process step or an energy end use 

(e.g., heating or cooling). The TPCs for new and existing plants vary by industry, vintage and process. These assumed rates were 

developed using professional engineering judgments regarding the energy characteristics, year of availability, and rate of market 

adoptions of new process technologies.

For the aluminum industry and combined cement and lime industry, energy projections are endogenously derived based on 

data obtained from the technology estimates (e.g., expenditures, energy coefficients, utility needs) in the Consolidated Impacts 

Modeling System (CIMS) database prepared by the Pacific Northwest National Laboratory, as calibrated using inputs from the 

U.S. Geological Survey (USGS) of the U.S. Department of the Interior, Portland Cement Association and MECS 2006 released by 

EIA [3,4,5].

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. The unit energy 

coefficient (UEC) is defined as the amount of energy to produce a unit of output; it measures the energy intensity of the process 

or end use. 

The module distinguishes the UECs by three vintages of capital stock. The amount of energy consumption reflects the 

assumption that new vintage stock will consist of state-of-the-art technologies that have different efficiencies from the existing 

capital stock. Consequently, the amount of energy required to produce a unit of output using new capital stock is often less than 

that required by the existing capital stock. The old vintage consists of capital existing in 2006 and surviving after adjusting 

for assumed retirements each year (Table 6.2). New production capacity is assumed to be added in a given projection year 

such that sufficient surviving and new capacity is available to meet the level of an industry’s output as determined in the NEMS 

Regional Macroeconomic Module. Middle vintage capital is that which is added after 2006 up through the year prior to the 

current projection year. 

To simulate technological progress and adoption of more-efficient energy technologies, the UECs are adjusted each projection 

year based on the assumed TPC for each step. The TPCs are derived from assumptions about the relative energy intensity (REI) 

of productive capacity by vintage (new capacity relative to existing stock in a given year) or over time (new or surviving capacity 

in 2040 relative to the 2006 stock). For example, state-of-the-art additions to steel hot rolling capacity in 2006 are assumedto 

require only 80 percent as much energy as does the average existing plant, so the REI for new capacity in 2006 is 0.80 (see 

Table 6.3). Over time, the UECs for new capacity change, and the rate of change is given by the TPC. The UECs of the surviving 

2006 capital stock are also assumed to change over time, but not as rapidly as for new capital stock because of retrofitting. For 

example, with hot rolling, the TPC for new facilities is -0.008, while the TPC for existing facilities is -0.007. Table 6.3 provides 

more examples, including alternative assumptions used to reflect an advanced, “high tech” case. 

Table 6.2. Retirement rates

Industry

Retirement Rate 

(percent) Industry

Retirement Rate 

(percent)

Iron and Steel

 Blast Furnace and Basic Steel Products 1.5 Glass and Glass Products 1.3

 Electric Arc Furnace 1.5 Food Products 1.7

Coke Oven 2.5 Pulp and Paper 2.3

Other Steel 2.9 Metal-Based Durables 1.3

Bulk Chemicals 1.7 Other Non-intensive Manufacturing 1.3

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, 

(publication pending), (Washington, DC, 2013).
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 55

Industrial Demand Module

For the new submodules cement and lime and aluminum, baseline capacity baseline capacity (as of year 2008) is assumed 

to retire at a linear rate over a fixed period of time (20 years). Incremental, or added, capacity after 2008 is assumed 

to retire according to a logistic survival function. In addition, for the cement industry, retirement of existing wet process 

kiln technology is assumed to be permanent; only dry process kilns can be added to replace retired wet kilns or to satisfy 

needed additional capacity.

The concepts of REI and TPCs are a means of embodying assumptions regarding new technology adoption in the 

manufacturing industry and the associated change in energy consumption of capital without characterizing individual 

technologies in detail. The approach reflects the assumption that industrial plants will change energy consumption as 

owners replace old equipment with new, sometimes more-efficient equipment, add new capacity, add new products, 

or upgrade their energy management practices. The reasons for the increased efficiency are not likely to be directly 

attributable to technology choice decisions, changing energy prices, or other factors readily subject to modeling. Instead, 

the module uses the REI and TPC concepts to characterize intensity trends for bundles of technologies available for major 

process steps or end use.

There are two exceptions to the general approach in the PA component. The first is for electric motor technology 

choice implemented for 9 industries to simulate their electric machine drive energy end use. Machine drive electricity 

consumption in the food industry, the five metal-based durables industries, and the three non-intensive manufacturing 

industries 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 minimum 

efficiency standard and a premium efficiency motor is also available. Table 6.4 provides the beginning stock efficiency for 

seven motor size groups in each of the three industry groups, as well as efficiencies for EPACT minimum and premium 

motors [7]. As the motor stock changes over the projection horizon, the overall efficiency of the motor population changes 

as well.

The second exception in the PA component is the Cement and Lime and Aluminum submodules. The methodology is 

described below.

The addition of the cement and lime submodule and aluminum submodule are the first two of several enhancements of 

the energy-intensive industries within the Industrial Demand Module. Instead of the aggregate energy intensity evolving 

according to TPCs curves for both new and vintage equipment for the process flows, the new submodules utilize detailed 

technology choice for each process flows. The new modules calculate surviving capacity based on retirement and needed 

capacity based on shipments and surviving capacity. Existing capital equipment retires linearly and new capital equipment 

retires according to an non-linear “S” curve over the useful life of the equipment. The exact shape of the “S” curve can be 

obtained by parameters adjusted by the user, New capital equipment information (capital and operating costs, energy use, 

and emissions) were obtained from the Consolidated Impacts Modeling System (CIMS) database. Each step of the process 

flow allows for multiple technology choices whose fuel type and efficiency are known at the national level, as regional fuel 

breakouts are fixed using available EIA data. 

Combined cement and lime industry

For the cement process flow, each step (raw material grinding, kiln – both rotation and burner, finished grinding) allows for 

multiple technology choices whose fuel type and efficiency are known at the national level, as regional fuel breakouts are 

fixed using available EIA data.

Cement has both dry and wet mill processes. Some technologies are available to both processes, while others are available 

to only one process. The technology choices within each group are:

1. Raw materials grinding: ball mill, roller mill

2. Kilns (rotators): rotary long with preheat, precalcining, and computer control (dry process only), rotary preheat 

with high-efficiency cooler (dry only), rotary preheat, precalcine with efficient cooler (dry process only), rotary wet 

standard with waste heat recovery boiler and cogeneration (wet process only)

3. Kilns (burners): standard fired by natural gas, efficient fired by natural gas, standard fired by oil, efficient fired by 

oil, standard fired by coal, standard fired by petroleum coke, standard fired by hazardous waste, standard fired by 

residue- derived fuel

4. Finished grinders: standard ball mill, finishing ball mill with high-efficiency separator, standard roller mill, finishing 

roller mill with high-efficiency separator

The technology slate in each of these process steps evolves over time and depends on the relative cost of equipment, cost 

of fuel, and fuel efficiency.
56 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Industrial Demand Module

The base year technology slate is determined from the latest CIMS database and calibrated for the base year 2008 with dry 

and wet mill capacity cement fuel use data from the Portland Cement Association, the USGS, and the 2006 MECS. All new 

cement capacity, both for replacement and increased production, is assumed to be dry cement capacity. Existing wet capacity 

is assumed to retire at a linear rate over 20 years with no replacement. Imported clinker, additives, and fly-ash are assumed 

to make constant percentage contributions to the finished product and thus “displace” a certain amount of domestic clinker 

production, and therefore energy use.

Lime shipments are estimated using a fixed percentage of stone, clay and glass shipments. Lime shipments, plus cement 

shipments, are presented together as the consolidated cement and lime output. Energy consumption and technology evolution in 

the lime industry are driven by the same methods implemented for cement, with different, industry-specific equipment choices.

Process/assembly component for Aluminum industry

For the aluminum process flow, each step (alumina production, anode production, and electrolysis for primary aluminum 

production, and melting for secondary production), allows for multiple technology choices whose fuel type and efficiency are 

known, as well as other operating characteristics. Technology shares are known at the national level, with regional fuel breakouts 

based on fixed allocations using available EIA data.

The aluminum industry has both primary and secondary production processes, which vary greatly in their energy demands. 

As such, the extents of these processes are based on the aluminum industry’s projected production and its historical share 

of production processes attenuated by relevant regional energy prices. Therefore, the fraction of total throughput from each 

aluminum production process varies over the model projections. 

Some technologies are available to both processes, while others are available to only one process. The technology choices within 

each production processing group are:

1. Primary smelting (Hall-Heroult electrolysis cell) is represented as smelting in four pre-bake anode technologies that 

denote standard and retrofitted choices and one inert anode wetted cathode choice.

2. Anode production, used in primary production only, is represented by three natural gas-fired furnaces under various 

configurations in forming and baking pre-bake anodes and the formation of Söderberg anodes. Note that anodes are a 

major requirement for the Hall-Heroult process.

3. Alumina production (Bayer Process) is used in primary production only and selects between existing natural gas facilities 

and those with retrofits.

4. Secondary production selects between two natural gas-fired melters – i.e., a standard and a melter with high efficiency: 

The technology slate in each of these process steps evolves over time and depends on the relative cost of equipment, cost of fuel, 

and fuel efficiency. The base year technology slate is determined from the latest CIMS database and calibrated for the base year 

2006 MECS and the USGS. All new capacities for aluminum production, both for replacement and increased production needs, 

are now assumed to be either pre-existing primary production or new secondary production, based on historical trend data and 

projected energy prices. Similar to the energy-intensive technology of the cement industry, the assumed lifespan of existing and 

new production capacity is assumed to be 20 and 30 years, respectively. In addition, production that has been idled is allowed to 

re-enter production before new equipment is built.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 57

Industrial Demand Module

Table 6.3. Coefficients for technology possibility curve for manufacturing industries and all industrial scenarios

applies to all fuels unless specified

Industry/Process Unit

Existing Facilities New Facillities

Reference 

REI20401

High 

Tech REI 

20401

Reference 

TPC%2

High 

Tech 

TPC%2

REI 

20063

Reference 

REI20404

High 

Tech REI 

20404

Reference 

TPC%2

High Tech 

TPC%2

Food Products

Process Heating 0.865 0.985 -0.426 -0.045 0.900 0.765 0.872 -0.477 -0.094

Process Heating-Steam 0.747 0.940 -0.853 -0.182 0.900 0.650 0.792 -0.953 -0.375

Process Cooling-Electricity 0.832 0.981 -0.540 -0.057 0.850 0.715 0.822 -0.506 -0.100

Process Cooling-Natural Gas 0.865 0.985 -0.426 -0.045 0.900 0.765 0.872 -0.477 -0.094

Other-Electricity 0.883 0.987 -0.364 -0.039 0.915 0.773 0.885 -0.493 -0.097

Other-Natural Gas 0.865 0.985 -0.426 -0.045 0.900 0.765 0.872 -0.477 -0.094

Paper & Allied Products

Wood Preparation 0.760 0.989 -0.802 -0.033 0.882 0.674 1.006 -0.790 -0.386

Waste Pulping-Electricity 0.925 0.947 -0.228 -0.161 0.936 0.936 0.866 0.000 -0.228

Waste Pulping-Steam 0.856 0.896 -0.456 -0.322 0.936 0.936 0.801 0.000 -0.456

Mechanical Pulping-Electricity 0.770 1.007 -0.767 0.021 0.931 0.580 1.259 -1.380 0.893

Mechanical Pulping-Steam 0.591 1.015 -1.533 0.043 0.931 0.359 1.699 -2.760 1.787

Semi-Chemical-Electricity 0.943 0.991 -0.173 -0.025 0.971 0.923 0.954 -0.149 -0.052

Semi-Chemical-Steam 0.889 0.983 -0.346 -0.051 0.971 0.877 0.937 -0.297 -0.105

Kraft, Sulfite, Misc. Chemicals 0.838 0.919 -0.519 -0.249 0.914 0.793 0.770 -0.415 -0.502

Kraft, Sulfite, Misc ChemicalsSteam 0.701 0.844 -1.037 -0.498 0.914 0.688 0.648 -0.830 -1.004

Bleaching-Electricity 0.747 0.918 -0.853 -0.252 0.878 0.651 0.918 -0.878 0.129

Bleaching-Steam 0.557 0.842 -1.706 -0.504 0.878 0.481 0.959 -1.756 0.259

Paper Making 0.848 0.802 -0.485 -0.621 0.885 0.846 0.553 -0.132 -1.376

Paper Making-Steam 0.944 0.809 -0.969 -0.621 0.885 0.809 0.553 -0.264 -1.376

Bulk Chemicals

Process Heating 0.877 0.960 -0.385 -0.120 0.905 0.770 0.860 -0.476 -0.149

Process Heating-Steam 0.590 0.721 -1.541 -0.957 0.724 0.377 0.481 -1.904 -1.194

Process Heating-Natural Gas 0.769 0.922 -0.770 -0.239 0.724 0.523 0.654 -0.952 -0.298

Process Cooling-Electricity 0.832 0.945 -0.540 -0.168 0.850 0.715 0.805 -0.506 -0.159

Process Cooling-Natural Gas 0.877 0.960 -0.385 -0.120 0.905 0.770 0.860 -0.476 -0.149

Electro-Chemicals 0.972 0.991 -0.082 -0.025 0.950 0.815 0.905 -0.450 -0.141

Other 0.877 0.960 -0.385 -0.120 0.905 0.770 0.860 -0.476 -0.149

Other-Electricity 0.883 0.962 -0.364 -0.113 0.915 0.773 0.868 -0.493 -0.155

Other-Natural Gas 0.769 0.922 -0.770 -0.239 0.724 0.523 0.654 -0.952 -0.298

Glass and Glass Products5

Batch Preparation-Electricity 0.931 1.000 -0.209 0.000 0.882 0.882 0.882 0.000 0.000

Melting/Refining 0.923 0.822 -0.235 -0.576 0.900 0.863 0.561 -0.125 -1.381

Melting/Refining-Steam 0.852 0.675 -0.470 -0.151 0.900 0.827 0.347 -0.250 -2.761

Forming 0.981 0.971 -0.056 -0.085 0.982 0.966 0.925 -0.048 -0.175

Forming-Steam 0.963 0.944 -0.111 -0.170 0.982 0.950 0.871 -0.096 -0.350

Post-Forming 0.974 0.989 -0.078 -0.034 0.968 0.953 0.945 -0.045 -0.069

Post-Forming-Steam 0.948 0.977 -0.157 -0.067 0.968 0.938 0.923 -0.090 -0.139

Iron and Steel

Coke Oven 0.924 0.864 -0.233 -0.429 0.902 0.863 0.624 -0.128 -1.076

Coke Oven-Steam 0.853 0.746 -0.467 -0.858 0.902 0.826 0.431 -0.257 -2.152

BF/BPF 0.992 0.943 -0.022 -0.172 0.987 0.987 0.869 0.000 -0.375

BF/BOF-Stem 0.985 0.889 -0.045 -0.345 0.987 0.987 0.764 0.000 -0.751
58 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Industrial Demand Module

Table 6.3. Coefficients for technology possibility curve for industries and all industrial scenarios (cont.)

applies to all fuels unless specified

Industry/Process Unit

Existing Facilities New Facillities

Reference 

REI20401

High 

Tech REI 

20401

Reference 

TPC%2

High 

Tech 

TPC%2

REI 

20063

Reference 

REI20404

High 

Tech REI 

20404

Reference 

TPC%2

High 

Tech 

TPC%2

Iron and Steel

EAF 0.901 0.889 -0.308 -0.346 0.990 0.805 0.750 -0.606 -0.813

Ingot Casting/Primary Rolling 1.000 1.000 0.000 0.000 NA NA NA NA NA

Continuous Casting 1.000 1.000 0.000 0.000 1.000 1.000 1.000 0.000 0.000

Hot Rolling7 0.788 0.890 -0.699 -0.344 0.800 0.608 0.573 0.804 -0.978

Hot Rolling-Steam7 0.620 0.791 -1.397 -0.687 0.800 0.461 0.409 -1.608 -1.956

Cold Rolling7 0.677 0.940 -1.141 -1.183 0.924 0.380 0.842 -2.580 -0.273

Cold Rolling-Steam7 0.456 0.883 -2.281 -0.365 0.924 0.153 0.767 -5.160 -0.546

Metal-Based Durables

Fabricated Metals

Process Heating 0.613 0.605 -1.427 -1.468 0.675 0.366 0.299 -1.784 -2.370

Process Cooling-Electricity 0.680 0.536 -1.127 -1.820 0.638 0.332 0.270 -1.903 -2.493

Process Cooling-Natural Gas 0.680 0.605 -1.127 -1.468 0.675 0.380 0.299 -1.679 -2.370

Other 0.680 0.605 -1.127 -1.468 0.675 0.380 0.299 -1.679 -2.370

Other-Electricity 0.680 0.647 -1.127 -1.274 0.686 0.366 0.296 -1.834 -2.439

Machinery

Process Heating 0.613 0.605 -1.427 -1.468 0.675 0.366 0.299 -1.784 -2.370

Process Cooling-Electricity 0.680 0.536 -1.127 -1.820 0.638 0.332 0.270 -1.903 -2.493

Process Cooling-Natural Gas 0.680 0.605 -1.127 -1.468 0.675 0.380 0.299 -1.679 -2.370

Other 0.680 0.605 -1.127 -1.468 0.675 0.380 0.299 -1.679 -2.370

Other-Electricity 0.680 0.647 -1.127 -1.274 0.686 0.366 0.296 -1.834 -2.439

Computers and Electronics

Process Heating 0.722 0.716 -0.952 -0.979 0.720 0.531 0.480 -0.892 -1.185

Process Cooling-Electricity 0.774 0.660 -0.751 -1.213 0.680 0.491 0.444 -0.952 -1.247

Process Cooling-Natural Gas 0.774 0.716 -0.751 -0.979 0.720 0.541 0.480 -0.840 -1.185

Other 0.774 0.716 -0.751 -0.979 0.720 0.541 0.480 -0.840 -1.185

Other-Electricity 0.774 0.748 -0.751 -0.850 0.732 0.535 0.482 -0.917 -1.219

Electrical Equipment

Process Heating 0.722 0.716 -0.952 -0.979 0.720 0.531 0.480 -0.892 -1.185

Process Heating-Steam NA NA -1.502 -3.914 NA NA NA -1.679 -4.740

Process Cooling-Electricity 0.774 0.660 -0.751 -1.213 0.680 0.491 0.444 -0.952 -1.247

Process Cooling-Natural Gas 0.774 0.716 -0.751 -0.979 0.720 0.541 0.480 -0.840 -1.185

Other 0.774 0.716 -0.751 -0.979 0.720 0.541 0.480 -0.840 -1.185

Other-Electricity 0.774 0.748 -0.751 -0.850 0.732 0.535 0.482 -0.917 -1.219

Transportation Equipment

Processing Heating 0.797 0.608 -0.666 -0.685 0.765 0.600 0.553 -0.714 -0.948

Processing Heating-Steam 0.698 0.386 -1.052 -2.740 0.765 0.483 0.389 -1.343 -3.792

Process Cooling-Electricity 0.836 0.539 -0.526 -0.849 0.723 0.557 0.514 -0.761 -0.997

Process Cooling-Natural Gas 0.836 0.608 -0.526 -0.685 0.765 0.608 0.553 -0.672 -0.948

Other 0.836 0.647 -0.526 -0.685 0.765 0.608 0.553 -0.672 -0.948

Other-Electricity 0.836 0.860 -0.526 -0.595 0.778 0.606 0.557 -0.734 -0.975
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 59

Industrial Demand Module

Table 6.3. Coefficients for Technology Possibility Curve for all Industrial Scenarios (cont.)

applies to all fuels unless specified

Industry/Process Unit

Existing Facilities New Facillities

Reference 

REI20401

High 

Tech REI 

20401

Reference 

TPC%2

High 

Tech 

TPC%2

REI 

20063

Reference 

REI20404

High 

Tech REI 

20404

Reference 

TPC%2

High 

Tech 

TPC%2

Other Non-Intensive 

 Manufacturing

Wood Products

Process Heating 0.613 0.654 -1.427 -1.452 0.630 0.342 0.342 -1.784 -2.358

Process Heating-Steam 0.720 0.426 -2.253 -5.807 0.630 0.386 0.386 -3.358 -9.432

Process Cooling-Electricity 0.680 0.590 -1.127 -1.804 0.595 0.310 0.310 -1.903 -2.481

Process Cooling-Natural Gas 0.680 0.654 -1.127 -1.452 0.630 0.354 0.354 -1.679 -2.358

Other 0.680 0.690 -1.127 -1.272 0.630 0.354 0.354 -1.679 -2.209

Other-Electricity 0.683 0.879 -1.115 -0.443 0.641 0.373 0.340 -1.845 -2.388

Plastic Products

Process Heating 0.722 0.718 -0.952 -0.968 0.675 0.498 0.451 -0.892 -1.179

Process Heating-Steam 0.598 0.380 -1.502 -3.871 0.675 0.380 0.380 -1.679 -4.716

Process Cooling-Electricity 0.774 0.663 -0.751 -1.203 0.638 0.461 0.417 -0.952 -1.241

Process Cooling-Natural Gas 0.774 0.718 -0.751 -0.968 0.675 0.507 0.451 -0.840 -1.179

Other 0.774 0.749 -0.751 -0.848 0.675 0.507 0.463 -0.840 -1.104

Other-Electricity 0.776 0.904 -0.743 -0.295 0.686 0.501 0.456 -0.922 -1.194

Balance of Manufacturing

Process Heating 0.784 0.781 -0.714 -0.726 0.675 0.529 0.489 -0.714 -0.943

Process Heating-Steam 0.903 0.589 -0.600 -1.546 0.900 0.762 0.348 -0.980 -2.753

Process Cooling-Electricity 0.825 0.735 -0.563 -0.902 0.638 0.492 0.454 -0.761 -0.992

Process Cooling-Natural Gas NA NA -0.563 -0.726 NA NA NA -0.672 -0.943

Other Natural Gas 0.825 0.805 -0.563 -0.636 0.675 0.537 0.499 -0.672 -0.883 1

REI 2040 Existing Facilities = Ratio of 2040 energy intensity to average 2006 energy intensity for existing facilities.

2

TPC = annual rate of change between 2006 and 2035.

3

REI 2006 New Facilities = For new facilities, the ratio of state-of-the-art energy intensity to average 2006 energy intensity for existing facilities.

4REI 2040 New Facilities = Ratio of 2040 energy intensity for a new state-of-the-art facility to the average 2006 intensity for existing facilities.

5

REI’s and TPCs apply to virgin and recycled materials.

6

No new plants are likely to be built with these technologies.

7

Net 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: U.S. Energy Information Administration, Model Documentation Report, Industrial Sector Demand Module of the National Energy Modeling System, 

(publication pending) (Washington, DC, 2013).
60 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Industrial Demand Module

Table 6.4. Cost and performance parameters for industrial motor choice model

Industrial Sector 

Horsepower Range

Base Stock 

Efficiency (%)

Premium 

Efficiency (%)

Premium

Cost

(2002$) 

Food

1-5 hp 81.3 89.2 601

6 - 20 hp 87.1 92.5 1,338

21 - 50 hp 90.1 93.8 2,585

51 - 100 hp 92.7 95.3 6,290

101 - 200 hp 93.5 95.2 11,430

201 - 500 hp 93.8 95.4 29,991

> 500 hp 93.0 96.2 36,176

Metal-Based Durables1

1-5 hp 86.7 89.2 601

6-20 hp 91.3 92.5 1,338

21-50 hp 93.0 93.9 2,585

51-100 hp 94.0 95.3 6,290

101-200 hp 94.6 95.2 11,430

201-500 hp 93.7 95.4 29,991

>500 hp 94.1 96.2 36,176

Other Non-Intensive Manufacturing2

1-5 hp 86.7 89.2 601

6-20 hp 91.3 92.5 1,338

21-50 hp 93.0 93.9 2,585

51-100 hp 94.0 95.3 6,290

101-200 hp 94.6 95.2 11,430

201-500 hp 93.7 95.4 11,430

>500 hp 94.1 96.2 36,176

1

The Metal-Based Durables group includes five industries 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: U.S. Energy Information Administration, Model Documentation Report, Industrial Sector Demand Module of the National Energy Modeling System, 

(publication pending) (Washington, DC, 2013). 

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.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 61

Industrial Demand Module

Petrochemical feedstock requirement

This subroutine estimates feedstock requirements for the major petrochemical intermediates such as ethylene, propylene, 

and butadiene. The primary feedstocks used to produce these chemicals are natural gas liquids (NGL) (ethane, propane, 

butane) and petrochemical (oil-based) feedstocks (gas oil, naphtha) [6]. Biomass is a potential raw material source, but it 

is assumed that there will be no biomass-based capacity over the projection period because of economic barriers. The type 

of feedstock not only determines the source of feedstock but also the energy for heat and power requirements to produce 

the chemicals.

To determine the relative amounts of feedstock (NGL or oil-based) baseline intensities, feedstock consumption intensities 

are derived from the 2006 MECS. Feedstock consumption of both types grows or declines with organic chemicals shipment 

value. It should be noted that there is no change in the feedstock intensity over time, i.e., all feedstock TPCs are assumed to 

be zero. Unlike most other processes represented in manufacturing PA components, chemical yields are governed by basic 

chemical stoichiometry which allows for specific yields under set conditions of pressure and temperature. For the projected 

LPG feedstock quantities, a further subdivision is made into refinery-produced propylene and ethane. All ethane produced 

by the NEMS Oil and Gas Supply Module is absorbed by the chemical model. The remaining balance of LPG feedstock 

requirement is a mixture of pentanes plus, butane, and propane.

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 on-site transportation. Space heating was further divided to estimate the amount provided by direct 

combustion of fossil fuels and that provided by steam (Table 6.5). Energy consumption in the BLD Component for an 

industry is estimated based on regional employment and output growth for that industry using the 2006 MECS as a basis. 

Boiler, steam, and cogeneration 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 6.6) to the boiler steam requirements to compute the required energy 

consumption.

The boiler fuel shares apply only to the fuels that are used in boilers for steam-only applications. Fuel use for the portion of 

the steam demand associated with combined heat and power (CHP) is described in the next section. Some fuel switching 

for the remainder of the boiler fuel use is assumed and is calculated with a logit-sharing equation where fuels shares are a 

function of fuel prices. The equation is calibrated to 2006 so that the 2006 fuel shares are produced for the relative prices 

that prevailed in

2006.

The byproduct fuels, production of which is estimated in the PA Component, are assumed to be consumed without regard 

to price, independent of purchased fuels. The boiler fuel share equations and calculations are based on the 2006 MECS and 

information from the Council of Industrial Boiler Owners. [8]

Combined heat and power

CHP plants, which are designed to produce both 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, and that the rate of additional CHP penetration will depend on the 

economics of retrofitting CHP plants to replace steam generated from existing non-CHP boilers. The technical potential 

for CHP is primarily based on supplying thermal requirements (i.e., matching thermal loads). Capacity additions are then 

determined by the interaction of CHP investment payback periods (with the time-value of money included) derived using 

operating hours reported in EIA’s published statistics, market penetration rates for investments with those payback 

periods, and regional deployment for these systems as characterized by the “collaboration coefficients” in Table 6.8. 

Assumed installed costs for the CHP systems are given in Table 6.7.
62 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Industrial Demand Module

Table 6.5. 2006 Building component energy consumption 

trillion Btu

Industry

Building Use and Energy Source

Region

Lighting 

Electricity 

Consumption

HVAC 

Electricity 

Consumption

HVAC 

Natural Gas 

Consumption

HVAC

Steam 

Consumption

Facility

Support

Total

Consumption

Onsite 

Transportation 

Total 

Consumption

Food Products 1 1.5 1.7 1.7 1.2 1.0 0.6

2 8.3 9.1 14.9 5.3 7.0 1.2

3 6.5 7.1 8.7 6.0 4.6 1.3

4 3.5 3.9 7.0 4.8 3.3 1.5

Paper & Allied Products 1 1.6 1.8 2.6 0.0 0.7 1.8

2 3.7 4.1 2.9 0.0 1.2 1.3

3 8.7 9.8 9.5 0.0 3.0 4.2

4 3.9 4.4 2.9 0.0 1.3 1.8

Bulk Chemicals 1 1.0 1.3 1.6 0.0 1.1 1.9

2 2.9 3.8 4.2 0.0 3.1 4.1

3 11.1 14.5 11.5 0.0 10.6 6.8

4 1.1 1.5 1.7 0.0 1.3 2.0

Glass & Glass Products 1 0.4 0.3 3.4 0.0 2.2 2.5

2 1.2 1.0 5.8 0.0 2.7 2.8

3 1.1 0.9 6.1 0.0 2.7 2.7

4 0.3 0.3 3.1 0.0 2.1 2.5

Cement 1 0.2 0.4 0.7 0.0 0.6 0.7

2 0.5 0.8 0.7 0.0 1.0 1.4

3 0.7 1.1 0.8 0.0 1.1 2.3

4 0.5 0.7 0.6 0.0 0.9 1.4

Iron and Steel 1 1.0 0.8 2.6 0.0 0.8 0.7

2 2.8 2.0 8.8 0.0 1.5 1.9

3 2.7 2.0 3.6 0.0 1.1 1.2

4 0.4 0.3 1.3 0.0 0.6 0.7

Aluminum 1 0.4 0.2 0.6 0.0 0.4 0.2

2 0.5 0.3 1.1 0.0 0.5 0.2

3 1.9 1.2 2.8 0.0 1.6 0.7

4 0.3 0.2 0.4 0.0 0.3 0.2

Metal-Based Durables Fabricated

 Products 1 1.8 1.8 4.7 4.0 0.7 0.4

2 5.9 5.9 18.7 15.9 2.5 2.0

3 4.7 4.7 11.9 10.0 1.9 2.3

4 1.8 1.8 2.5 2.1 0.6 0.5

Machinery 1 2.5 1.8 4.7 4.0 0.7 0.4

2 9.5 5.9 18.7 15.9 2.5 2.0

3 3.7 4.7 11.9 10.0 1.9 2.3

4 0.7 1.8 2.5 2.1 0.6 0.5

Computers & Electronic Products 1 2.0 4.8 4.4 3.9 1.7 0.6

2 1.7 4.0 4.6 4.0 1.5 0.6

3 3.1 7.3 4.2 3.6 2.3 0.6

4 4.3 10.2 7.2 6.5 3.0 0.6

Transportation Equipment 1 3.5 4.5 11.6 0.9 1.3 0.4

2 15.2 19.9 56.2 4.2 5.8 2.1

3 10.4 14.1 14.1 1.1 2.6 1.2

4 2.7 3.5 6.0 0.4 0.9 0.5

Electrical Equipment 1 0.6 0.7 0.7 0.5 0.2 0.3

2 1.7 2.1 2.4 1.9 0.8 0.5

3 2.5 3.0 4.8 3.7 1.2 0.6

4 0.2 0.3 0.5 0.4 0.1 0.3

Other Non-Intensive Manufacturing 

 Wood Products 1 0.5 0.3 0.5 0.9 0.1 0.9

2 2.1 1.5 3.0 5.8 0.6 4.2

3 3.3 2.3 1.9 3.7 0.7 5.0

4 1.4 1.0 1.7 3.3 0.4 4.2
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 63

Industrial Demand Module

Table 6.5. 2006 Building component energy consumption (cont.) 

trillion Btu

Industry

Building Use and Energy Source

Region

Lighting 

Electricity 

Consumption

HVAC 

Electricity 

Consumption

HVAC

Natural Gas 

Consumption

HVAC

Steam 

Consumption

Facility

Support

Total

Consumption

Onsite 

Transportation 

Total 

Consumption

Plastic Products 1 2.0 2.5 4.3 0.0 1.2 1.3

2 7.0 8.7 9.6 0.0 3.1 1.0

3 5.9 7.4 11.2 0.0 2.9 1.0

4 1.1 1.4 0.8 0.0 0.5 0.3

Balance of Manufacturing 1 5.7 8.8 14.9 0.0 2.3 1.9

2 16.7 25.8 23.1 0.0 6.1 1.3

3 21.4 33.0 43.7 0.0 8.3 2.1

4 4.0 6.1 11.1 0.0 1.7 0.9

HVAC = Heating, Ventilation, Air Conditioning.

Source: U.S. Energy Information Administration, Model Documentation Report, Industral Sector Demand Module of the National Energy Modeling System, 

(publication pending) (Washington, DC 2013).
64 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Industrial Demand Module

Table 6.6. 2006 Boiler fuel component and logit parameter 

trillion Btu

Region Alpha Natural Gas Coal Oil Renewables

Food Products 1 -2.0 19 0 4 1

2 -2.0 168 109 12 22

3 -2.0 96 11 12 52

4 -2.0 76 14 4 4

Paper & Allied Products 1 -2.0 41 40 16 80

2 -2.0 48 60 12 90

3 -2.0 159 91 64 998

4 -2.0 53 13 4 97

Bulk Chemicals 1 -2.0 13 0 56 0

2 -2.0 97 37 18 0

3 -2.0 605 31 384 0

4 -2.0 20 21 6 0

Glass & Glass Products 1 -2.0 2 0 3 10

2 -2.0 6 0 3 1

3 -2.0 6 0 3 2

4 -2.0 1 0 3 1

Cement 1 -2.0 0 0 1 1

2 -2.0 1 0 1 5

3 -2.0 0 0 1 3

4 -2.0 0 0 1 3

Iron & Steel 1 -2.0 4 6 20 0

2 -2.0 16 1 66 0

3 -2.0 6 0 7 0

4 -2.0 1 0 1 0

Aluminum 1 -2.0 2 0 0 0

2 -2.0 4 0 0 0

3 -2.0 11 0 0 0

4 -2.0 1 0 0 0

Metal-Based Durables 

 Fabricated Metal Products 1 -2.0 5 0 0 0

2 -2.0 19 0 0 2

3 -2.0 12 0 1 0

4 -2.0 3 0 0 0

Machinery 1 -2.0 3 0 1 0

2 -2.0 12 1 0 1

3 -2.0 5 0 0 0

4 -2.0 1 0 0 0

Computers & electronic Products 1 -2.0 4 0 1 0

2 -2.0 5 0 1 0

3 -2.0 4 0 1 0

4 -2.0 8 0 1 1

Electrical Equipment 1 -2.0 5 8 3 7

2 -2.0 27 -3 1 5

3 -2.0 7 1 3 4

4 -2.0 3 0 0 0
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 65

Industrial Demand Module

Table 6.6. 2006 Boiler fuel component and logit parameter (cont.) 

trillion Btu

Region Alpha Natural Gas Coal Oil Renewables

Transportation Equipment 1 -2.0 1 0 0 0

2 -2.0 2 0 0 0

3 -2.0 4 0 0 0

4 -2.0 0 0 0 0

Other Non-Intensive 

 Manufacturing Wood Products 1 -2.0 2 0 0 11

2 -2.0 12 1 1 40

3 -2.0 7 0 1 123

4 -2.0 5 0 2 48

 Plastic Products 1 -2.0 10 0 2 0

2 -2.0 23 0 0 0

3 -2.0 25 10 6 0

4 -2.0 2 0 0 0

 Balance of Manufacturing 1 -2.0 41 -11 18 1

2 -2.0 64 51 28 2

3 -2.0 121 58 31 22

4 -2.0 31 8 15 0

Alpha: User-specified.

Source: U.S. Energy Information Administration, Model Documentation Report, Industral Sector Demand Module of the National Energy Modeling 

System, (publication pending) (Washington, DC 2013).

Table 6.7. Cost characteristics of industrial CHP systems

System

Size Kilowatts 

(KW)

Installed Cost 

(2005$ per KWh)1

Reference 2010 Reference 2040 High Tech 2040

Engine 100 1440 576 535

200 1260 396 354

Gas turbine 3510 1719 1496 1450

5670 1152 1023 1006

14990 982 869 869

25000 987 860 860

40000 875 830 830

Combined cycle 100000 723 684 668

1

Costs are given in 2005 dollars in original source document.

Source: U.S. Energy Information Administration, Model Documentation Report, Industral Sector Demand Module of the National Energy Modeling 

System, (publication pending) (Washington, DC 2013).

Table 6.8. Regional collaboration coefficients for CHP deployment

Census Region Collaboration Coefficient

Northeast 1.46

Midwest 1.34

South 0.33

West 1.06

Source: American Council for an Energy-Efficient Economy, “Challenges Facing Combined 

Heat and Power Today: A State-by-State Assessment,” September 2011, website: www.

aceee.org/research-report/ie111 and Energy Information Administration, Office of Energy 

Analysis.
66 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Industrial Demand Module

Key assumptions - non-manufacturing

The non-manufacturing sector consists of three industries: agriculture, mining and construction. These industries all use 

electricity, natural gas, diesel fuel, and gasoline. The mining industry also uses coal, NGL, and residual fuel oil, and the 

construction industry also uses other petroleum in the form of asphalt and road oil. Except for oil and gas extraction, almost all 

of the energy use in the nonmanufacturing sector takes place in the process and assembly step. Oil and gas extraction uses a 

significant amount of residual fuel in the BSC component. Table 6.9 shows the baseline unit energy consumption values for the 

nonmanufacturing subsectors in 2006.

Table 6.9 2006 UECs for nonmanufacturing 

Unit Energy Consumption (UEC) in thousand Btu/2005$)

Industry/Process UEC 2006 

Agriculture

 Crop Production

 Buildings 1.54

 Vehicles 1.87

 Irrigation 0.59

 Other Agricultural Production

 Buildings 0.80

 Vehicles 1.26

 Irrigation 0.33

Construction 2.02

Mining

 Coal 4.17

 Oil & Gas Extraction 1.45

 Metal/Non-metal 8.63

Unlike the manufacturing sector, the non-manufacturing sector does not have a single source of data for energy consumption 

estimates. Instead, UECs for the non-manufacturing sector are derived from various sources of data collected by a number 

of government agencies. Furthermore, unlike the majority of manufacturing industries displayed in Table 6.3, the TPCs for 

non-manufacturing are not “fixed” in that they are dynamic and evolve over time. This evolution depends on output from other 

modules such as building and transportation equipment efficiencies which are employed in the agriculture and construction 

models as well as oil & gas well and coal mine productivity which is employed in the mining model. 

Agriculture

U.S. agriculture consists of three major sub-sectors: 

•	 crop production, which is dependent primarily on regional environments and crops demanded; 

•	 animal production, which is largely dependent on food demands and feed accessibility; 

•	 and all remaining agricultural activities, which is primarily composed of forestry and logging. 

These sub-industries have historically been tightly coupled due to competing use of land area. For example, crops produced for 

animal feed cannot be consumed by humans; forests provide the feedstock of the paper and wood industries but in turn do not 

allow the growth of crops or limit or prevent grazing of animals.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 67

Industrial Demand Module

However, energy consumption in these industries is tied to specialized equipment, which often determines the fuel requirement 

with little flexibility. Within each of these sub-industries the key energy-using equipment can be broken into three major 

categories: off-road vehicles, buildings, and other equipment, which is primarily irrigation equipment for crop production. 

Agriculture TPCs are calculated within the NEMS model by further subdividing consumption in each sub-industry based on 

the equipment in which the energy is used: off-road vehicles, which are trucks, tractors, and other specialty vehicles; buildings, 

which require lighting and temperature control; and other equipment, which covers a variety of both common (e.g., pumps) 

and specialty (for example cotton gins) equipment used in all the various types of agricultural production. Thus, changes in 

efficiencies in heavy and medium-duty vehicles from the Transportation Sector Module and changes in lighting and heating 

efficiencies from the Commercial Sector Demand Module are used to dynamically modify the agriculture TPCs.

Baseline energy consumption data for the two agriculture sectors (crops and other agriculture) is based on data from the Census 

of Agriculture and a special tabulation from the National Agricultural Statistics Service (USDA-NASS). Expenditures for four 

energy sources are collected from crop farms and livestock farms as part of the Agricultural Resource Management Survey 

(ARMS). These data are converted from dollar expenditures to energy quantities using fuel prices from NASS and EIA.

Mining

The mining sector is comprised of three sectors: coal mining, and metal and nonmetal mining, and oil and gas extraction, Energy 

use is based on what equipment is used at the mine and onsite vehicles used. All mines use extraction equipment and lighting, 

but only coal and metal and nonmetal mines use grinding and ventilation. As with the agriculture module described above, TPCs 

are influenced by efficiency changes in buildings and transportation equipment. 

Coal mining production is obtained from Coal Market Module (CMM). Currently, it is assumed that 70 percent of the coal is 

mined at the surface and the rest is mined underground. As these shares evolve, however, so does the energy consumed since 

surface mines use less energy overall than underground mining. Moreover, the energy consumed for coal mining depends on coal 

mine productivity which is also obtained from the CMM. Diesel and electricity are the predominant fuels used in coal mining. 

Electricity used for coal grinding is calculated using the raw grinding process step from the cement submodule. In metal and 

non-metal mining, energy use is similar to coal mining. Output used for metal and non-metal mining is derived from the Macro 

Analysis Module’s (MAM) variable for “other” mining which also provides the shares of each. 

For oil and natural gas extraction, production is derived from the OGSM module. Energy use depends upon the fuel extracted 

as well as whether the well is conventional, or unconventional, e.g. extraction from tight and shale formations, percentage of dry 

wells, and well depth. 

Construction

Construction uses diesel fuel, gasoline, asphalt and road oil, as well as electricity and natural gas. Asphalt and road oil are tied 

to state and local government real investment in highways and streets, and this investment is derived from the MAM. TPCs 

for diesel and gasoline fuels are directly tied to the Transportation Sector Module’s heavy and medium duty vehicle efficiency 

projections. For non-vehicular construction equipment, TPCs are a weighted average of vehicular TPCs and highway investment.

Legislation and regulations

Energy Improvement and Extension Act of 2008

Under EIEA2008 Title I, “Energy Production Incentives,” Section 103 provides an Investment Tax Credit (ITC) for qualifying 

Combined Heat and Power (CHP) systems placed in service before January 1, 2017. Systems with up to 15 megawatts of electrical 

capacity qualify for an ITC up to 10 percent of the installed cost. For systems between 15 and 50 megawatts, the percentage 

tax credit declines linearly with the capacity, from 10 percent to 3 percent. To qualify, systems must exceed 60-percent fuel 

efficiency, with a minimum of 20 percent each for useful thermal and electrical energy produced. The provision was modeled in 

AEO2012 by adjusting the assumed capital cost of industrial CHP systems to reflect the applicable credit.

The Energy Independence and Security Act of 2007

Under EISA2007, the motor efficiency standards established under the Energy Policy Act of 1992 (EPACT) are superseded 

for purchases made after 2011. Section 313 of EISA2007 increases or creates minimum efficiency standards for newly 

manufactured, general purpose electric motors. 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” motors (201-500 horsepower) that were not previously covered 

by EPACT standards. The industrial module’s motor efficiency assumptions reflect the EISA2007 efficiency standards for new 

motors added after 2011.
68 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Industrial Demand Module

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 at least 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 purchased after 1998. The choices offered in the 

motor efficiency assumptions 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. (Emissions due to coal-to-liquids CHP plants are included with 

the electric power sector because they are subject to the separate emission limits of large electricity generating plants.) 

The Energy Independence and Security Act of 2007

Under EISA2007, the motor efficiency standards established under the Energy Policy Act of 1992 (EPACT) are 

superseded for purchases made after 2011. Section 313 of EISA2007 increases or creates minimum efficiency standards 

for newly manufactured, general purpose electric motors. 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” motors (201-500 horsepower) 

that were not previously covered by EPACT standards. The industrial module’s motor efficiency assumptions reflect the 

EISA2007 efficiency standards for new motors added after 2011.

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 at least 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 purchased after 1998. The choices offered in the 

motor efficiency assumptions 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.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 69

Industrial Demand Module

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, EPA454/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. (Emissions due to coal-to-liquids CHP 

plants are included with the electric power sector because they are subject to the separate emission limits of large 

electricity generating plants.)

Maximum Achievable Control Technology for Industrial Boilers (Boiler MACT)

Section 112 of the Clean Air Act (CAA) requires the regulation of air toxics through implementation of the National 

Standards for Hazardous Air Pollutants (NESHAP) for industrial, commercial, and institutional boilers. The final 

regulations, known as Boiler MACT, are modeled in the AEO2013. Pollutants covered by Boiler MACT include the 

hazardous air pollutants (HAP), hydrogen chloride (HCI), mercury (HG), dioxin/furan, carbon monoxide (CO), 

and particulate matter (PM). Generally, industries comply with the Boiler MACT regulations by including regular 

maintenance and tune-ups for smaller facilities and emission limits and performance tests for larger facilities. Boiler 

MACT is modeled as an upgrade cost in the Macroeconomic Activity Module (MAM). These upgrade costs are 

classified as “nonproductive costs” which are not associated with efficiency improvements. The effect of these costs in 

the MAM is a reduction in shipments coming into the Industrial Demand Module.

California Assembly Bill 32: Emissions cap-and-trade as part of the Global Warming Solutions Act of 2006 (AB32)

AB32 established a comprehensive, multi-year program to reduce Green House Gas (GHG) emissions in California, 

including a cap-and-trade program. In addition to the cap-and-trade program, AB32 also authorizes the low carbon fuel 

standard (LCFS); energy efficiency goals and programs in transportation, buildings; and industry; combined heat and 

power goals; and renewable portfolio standards.

For AEO2013, the cap-and-trade provisions were modeled for industrial facilities, refineries, and fuel providers. GHG 

emissions include both non-CO2 and specific non-CO2 GHG emissions. The allowance price, representing the 

incremental cost of complying with AB32 cap-and-trade, is modeled in the NEMS Electricity Market Module via a region 

specific emissions constraint. This allowance price, when added to market fuel prices, results in higher effective fuel 

prices in the demand sectors. Limited banking and borrowing, as well as a price containment reserve and offsets, have 

been modeled in the NEMS. AB32 is not modeled explicitly in the Industrial Module, but enters the module implicitly 

through higher effective fuel prices and macroeconomic effects of higher prices, all of which affect energy demand and 

emissions.

Industrial alternative cases

Technology cases

The Integrated High Demand Technology case inputs assume earlier availability, lower costs, and higher efficiency of 

more advanced equipment, based on engineering judgments and research compiled by Focis Associates in a 2005 study 

for EIA (Tables 6.3 and 6.7) [9]. The Integrated High Demand Technology case inputs also assume that the rate at which 

biomass byproducts will be recovered from industrial processes 0.7 percent per year, as opposed to 0.4 percent per 

year in the Reference case. The availability of additional biomass leads to an increase in biomass-based cogeneration. 

Changes in aggregate energy intensity can result both from changing equipment and production efficiency and from 

changes in the composition of industrial output.

The Integrated 2012 Demand Technology case inputs hold the energy efficiency of industrial plant and equipment 

constant at the 2013 level over the projection period.

The IDM is used as part of the Low Renewable Technology Cost case. In this case, costs for non-hydropower renewable 

generating technologies are 20 percent lower than Reference case levels through 2040. 
70 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Industrial Demand Module

Resource Cases

Two resource cases are used in AEO2013. The Industrial High Resource Case is a combination of High Economic Growth, 

High Oil & Gas Resource, and Industrial High Technology cases. The Industrial Low Resource Case is a combination of 

Low Economic Growth and Low Oil & Gas Resource cases. The intent is to examine the impact on industrial output, the 

mix of production, and energy consumption of changes in the level of oil and natural gas. 

In the Industrial High Resource Case, Higher oil and natural gas production drive more rapid growth in industrial output 

and change in mix of production by industry when compared with the Reference case. The impact of the greater oil and 

natural gas production are wide-spread and increase the probability of realizing the higher level of economic growth 

reflected in the High Economic Growth case and of achieving the technological advancements of the High Industrial 

Technology case.

In the Industrial Low Resource case oil and natural gas production is lower and prices higher than in the Reference Case, 

resulting in slower growth in industrial output. The lower oil and natural gas production levels result in a slower advance 

in the U.S. economy when compared with the Reference Case.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 71

Industrial Demand Module

Notes and sources

[1] U.S. Energy Information Administration, State Energy Data System, based on energy consumption by State 

through 2009, as downloaded in August, 2011, from www.eia.gov/state/seds/. 

[2] U. S. Energy Information Administration, Manufacturing Energy Consumption Survey, website www.eia.doe.

gov/ emeu/mecs/. 

[3] Roop, Joseph M. “The Industrial Sector in CIMS-US,” Pacific Northwest National Laboratory, 28th Industrial Energy 

Technology Conference, May, 2006.

[4] Portland Cement Association, U.S. and Canadian Portland Cement Industry Plant Information Summary, cement 

data was made available under a non-disclosure agreement, website www.cement.org/.

[5] U.S. Department of the Interior, U.S. Geological Survey, Minerals Yearbook, cement data was made available under 

a non-disclosure agreement, website www.minerals.usgs.gov/minerals/pubs/commodity/cement/.

[6] In NEMS, NGLs are reported as Liquefied Petroleum Gas (LPG).

[7] U.S., Department of Energy(2007). Motor Master+ 4.0 software database; available at updated link www1.eere.

energy.gov/manufacturing/tech_deployment/software_motormaster.html. 

[8] Personal correspondence with the Council of Industrial Boiler Owners.

[9] U.S. Energy Information Administration, Industrial Technology and Data Analysis Supporting the NEMS Industrial 

Model (Focis Associates, October 2005).
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Transportation Demand 
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U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 75

Transportation Demand Module

The NEMS Transportation Demand Module estimates transportation energy consumption across the nine Census 

Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific and associated 

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), buses, freight and passenger aircraft, freight 

and passenger rail, freight shipping, and miscellaneous transport such as recreational boating. 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 Component (MTCC) includes 86 advanced technology input 

assumptions specific to cars and light trucks (Tables 7.1 and 7.2) that include incremental fuel economy improvement, 

incremental cost, incremental weight change, first year of introduction, and fractional horsepower change.

The vehicle sales share module holds the share of vehicle sales by manufacturers constant within a vehicle size class at 

2008 levels based on National Highway Traffic and Safety Administration (NHTSA) data [1]. Environmental Protection 

Agency (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 MTCC [2].

The MTCC utilizes 86 technologies for each size class and manufacturer 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 to determine cost effectiveness and market penetration. The fuel economy module assumes the following: 

•	 The financial parameters used to determine technology economic effectiveness are evaluated based on the need to 

improve fuel economy to meet CAFE standards versus consumer willingness to pay for fuel economy improvement 

beyond those minimum requirements.

•	 Fuel economy standards for light duty vehicles reflect current law through model year 2025, according to NHTSA 

model year2011 final rulemaking, joint EPA and NHTSA rulemaking for 2012 through 2016, and joint EPA and NHTSA 

rulemaking for 2017 through 2025. CAFE standards enacted for model years 2022 through 2025 will undergo a 

midterm evaluation by NHTSA and could be subject to change. For model years 2026 through 2040, fuel economy 

standards are held constant at model year 2025 levels with fuel economy improvements still possible based on 

continued improvements in economic effectiveness.

•	 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.
76 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Transportation Demand Module

Table 7.1. Standard technology matrix for cars1

Fuel

Efficiency

Change %

Incremental 

Cost $2000

Incremental Cost

($/UnitWt.)

Absolute 

Incremental Weight 

(Lbs.)

Per Unit 

Incremental 

Weight (Lbs./

UnitWt.)

Introduction Year

Horse 

power

Change %

Unit Body Construction 4.0 99.91 0.00 0 -6 1980 0

Mass Reduction I 1.0 0.00 0.06 0 -1.5 2005 0

Mass Reduction II 2.6 0.00 0.14 0 -3.5 2009 0

Mass Reduction III 5.4 0.00 0.42 0 -10 2011 0

Mass Reduction IV 8.4 0.00 0.62 0 -15 2099 0

Mass Reduction V 11.6 0.00 0.72 0 -20 2099 0

Aerodynamics I 2.4 48.17 0.00 0 0.5 2000 0

Aerodynamics II 4.9 203.29 0.00 0 1 2011 0

6 Speed Manual 2.2 255.59 0.00 20 0 1995 0

Aggressive Shift Logic I 2.5 32.44 0.00 0 0 1999 0

Aggressive Shift Logic II 6.7 27.18 0.00 0 0 2017 0

Early Torque Converter Lockup 0.5 29.49 0.00 0 0 2002 0

High Efficiency Gearbox 1.6 200.63 0.00 0 0 2017 0

5 Speed Automatic 1.4 103.91 0.00 20 0 1995 0

6 Speed Automatic 2.2 270.05 0.00 30 0 2003 0

7 Speed Automatic 5.1 401.04 0.00 40 0 2009 0

8 Speed Automatic 8.0 532.83 0.00 50 0 2010 0

Dual Clutch Automated Manual 5.5 56.75 0.00 -10 0 2004 0

CVT 8.4 250.98 0.00 -25 0 1998 0

Low Friction Lubricants 0.7 3.20 0.00 0 0 2003 0

Engine Friction Reduction I-4 cyl 2.0 47.16 0.00 0 0 2000 1.25

Engine Friction Reduction I-6 cyl 2.6 71.14 0.00 0 0 2000 1.25

Engine Friction Reduction I-8 cyl 2.8 94.32 0.00 0 0 2000 1.25

Engine Friction Reduction II-4 cyl 3.6 100.71 0.00 0 0 2017 2.25

Engine Friction Reduction II-6 cyl 4.7 147.87 0.00 0 0 2017 2.25

Engine Friction Reduction II-8 cyl 5.1 195.03 0.00 0 0 2017 2.25

Cylinder Deactivation-6 cyl 6.5 187.06 0.00 10 0 2004 0

Cylinder Deactivation-8 cyl 6.9 209.97 0.00 10 0 2004 0

VVT I-OHV Intake Cam Phasing-6 cyl 2.6 43.90 0.00 20 0 2051 1.25

VVT I-OHV Intake Cam Phasing-8 cyl 2.7 43.90 0.00 30 0 2051 1.25

VVT I-OHC Intake Cam Phasing-4 cyl 2.1 43.90 0.00 10 0 1993 1.25

VVT I-OHC Intake Cam Phasing-6 cyl 2.6 88.76 0.00 20 0 1993 1.25

VVT I-OHC Intake Cam Phasing-8 cyl 2.7 88.76 0.00 30 0 1993 1.25

VVT II-OHV Coupled Cam Phasing-6 cyl 5.4 43.90 0.00 20 0 2009 1.25

VVT II-OHV Coupled Cam Phasing-8 cyl 5.8 43.90 0.00 30 0 2009 1.25

VVT II-OHC Coupled Cam Phasing-4 cyl 4.3 43.90 0.00 10 0 2009 1.25

VVT II-OHC Coupled Cam Phasing-6 cyl 5.4 88.76 0.00 20 0 2009 1.25

VVT II-OHC Coupled Cam Phasing-8 cyl 5.8 88.76 0.00 30 0 2009 1.25

VVT III-OHV Dual Cam Phasing-6 cyl 5.4 99.26 0.00 25 0 2051 1.56

VVT III-OHV Dual Cam Phasing-8 cyl 5.8 99.26 0.00 37.5 0 2051 1.56

VVT III-OHC Dual Cam Phasing-4 cyl 4.3 90.67 0.00 12.5 0 2009 1.56

VVT III-OHC Dual Cam Phasing-6 cyl 5.4 195.65 0.00 25 0 2009 1.56

VVT III-OHC Dual Cam Phasing-8 cyl 5.8 195.65 0.00 37.5 0 2009 1.56

VVL I-OHV Discrete-6 cyl 5.5 225.24 0.00 40 0 2000 2.5

VVL I-OHV Discrete-8 cyl 5.9 322.59 0.00 50 0 2000 2.5

VVL I-OHC Discrete-4 cyl 4.3 155.57 0.00 25 0 2000 2.5

VVL I-OHC Discrete-6 cyl 5.5 225.24 0.00 40 0 2000 2.5

VVL I-OHC Discrete-8 cyl 5.9 322.59 0.00 50 0 2000 2.5

VVL II-OHV Continuous-6 cyl 7.0 1150.07 0.00 40 0 2011 2.5

VVL II-OHV Continuous-8 cyl 7.5 1256.96 0.00 50 0 2011 2.5

VVL II-OHC Continuous-4 cyl 5.4 232.88 0.00 25 0 2011 2.5

VVL II-OHC Continuous-6 cyl 7.0 427.58 0.00 40 0 2011 2.5

VVL II-OHC Continuous-8 cyl 7.5 466.71 0.00 50 0 2011 2.5

Stoichiometric GDI-4 cyl 1.5 264.37 0.00 20 0 2006 2.5

Stoichiometric GDI-6 cyl 1.5 397.99 0.00 30 0 2006 2.5

Stoichiometric GDI-8 cyl 1.5 478.16 0.00 40 0 2006 2.5

OHV to DOHC TBDS-I4 21.6 1383.90 0.00 -100 0 2009 3.75

OHV to DOHC TBDS I-V6 20.2 2096.84 0.00 -100 0 2009 3.75

SOHC to DOHC TBDS I-I4 21.6 827.47 0.00 -100 0 2009 3.75

SOHC to DOHC TBDS I-V6 20.2 1605.80 0.00 -100 0 2009 3.75

DOHC TBDS I-I3 17.5 915.28 0.00 -100 0 2009 3.75

DOHC TBDS I-I4 21.6 747.30 0.00 -100 0 2009 3.75

DOHC TBDS I-V6 20.2 1530.88 0.00 -100 0 2009 3.75
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 77

Transportation Demand Module

Table 7.1. Standard technology matrix for cars1 (cont.)

Fuel

Efficiency

Change %

Incremental 

Cost $2000

Incremental Cost

($/UnitWt.)

Absolute 

Incremental Weight 

(Lbs.)

Per Unit 

Incremental 

Weight (Lbs./

UnitWt.)

Introduction Year

Horse 

power

Change %

OHV to DOHC TBDS II-I4 26.3 1586.36 0.00 -100 0 2012 3.75

OHV to DOHC TBDS II-V6 24.5 2445.33 0.00 -100 0 2012 3.75

SOHC to DOHC TBDS II-I4 26.3 1046.15 0.00 -100 0 2012 3.75

SOHC to DOHC TBDS II-V6 24.5 1968.59 0.00 -100 0 2012 3.75

DOHC TBDS II-I3 21.2 1130.47 0.00 -100 0 2012 3.75

DOHC TBDS II-I4 26.3 968.31 0.00 -100 0 2012 3.75

DOHC TBDS II-V6 24.5 1895.85 0.00 -100 0 2012 3.75

OHV to DOHC TBDS III-I4 (from V6) 32.6 2031.83 0.00 -100 0 2017 3.75

OHV to DOHC TBDS III-I4 (from V8) 30.7 1601.81 0.00 -200 0 2017 3.75

SOHC to DOHC TBDS III-I4 (from V6) 32.6 1565.84 0.00 -100 0 2017 3.75

SOHC to DOHC TBDS III-I4 (from V8) 30.7 1380.40 0.00 -200 0 2017 3.75

DOHC TBDS III-I3 (from I4) 27.1 1634.58 0.00 -100 0 2017 3.75

DOHC TBDS III-I4 (from V6) 32.6 1498.70 0.00 -100 0 2017 3.75

DOHC TBDS III-I4 (from V8) 30.7 1302.07 0.00 -200 0 2017 3.75

Electric Power Steering 1.3 107.15 0.00 0 0 2004 0

Improved Accessories I 0.7 87.49 0.00 0 0 2005 0

12V Micro Hybrid w/EPS and IACC 7.0 640.24 0.00 45 0 2005 0

Improved Accessories II 2.5 128.69 0.00 0 0 2012 0

Mild Hybrid w/EPS and IACC II 11.0 2902.00 0.00 80 0 2012 -2.5

Tires I 2.0 5.60 0.00 -12 0 2005 0

Tires II 4.0 58.35 0.00 -15 0 2017 0

Low Drag Brakes 0.8 59.15 0.00 0 0 2000 0

Secondary Axle Disconnect 1.3 96.34 0.00 0 -1 2012 0 1 Fractional changes refer to the percentage change from the base technology.

Sources: U.S. Energy Information Administration, 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). 

National Highway Traffic Safety Administration, Corporate Average Fuel Economy for MY 2011-2015 Passenger Cars and Light Trucks (April 2008). U.S. 

Environmental Protection Agency, Interim Report: New Powertrain Technologies and Their Projected Costs (October 2005).

Environmental Protection Agency and Department of Transportation National Highway Traffic Safety Administration, “2017 and Later Model Year LightDuty Vehicle Greenhouse Gas Emissions and Corporate Average Fuel Economy Standards; Final Rule,” Federal Register Vol. 77, No. 199, October 15, 2012. 

40 CFR Parts 85, 86, 600, 49 CFR Parts 523, 531, 533, et al. and 600.
78 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Transportation Demand Module

Table 7.2. Standard technology matrix for light trucks1

Fuel

Efficiency

Change %

Incremental 

Cost $2000

Incremental Cost

($/UnitWt.)

Absolute 

Incremental Weight 

(Lbs.)

Per Unit 

Incremental Weight

(Lbs./

UnitWt.)

Introduction YearHorse power

Change %

Unit Body Construction 4.0 100.00 0.00 0 -6 1980 0

Mass Reduction I 1.0 0.00 0.06 0 -1.5 2005 0

Mass Reduction II 2.6 0.00 0.14 0 -7.5 2009 0

Mass Reduction III 5.4 0.00 0.42 0 -10 2011 0

Mass Reduction IV 8.4 0.00 0.62 0 -15 2016 0

Mass Reduction V 11.6 0.00 0.72 0 -20 2020 0

Aerodynamics I 2.4 48.17 0.00 0 0.5 2000 0

Aerodynamics II 4.9 203.29 0.00 0 1 2011 0

6 Speed Manual 2.0 255.59 0.00 20 0 1995 0

Aggressive Shift Logic I 2.3 32.44 0.00 0 0 1999 0

Aggressive Shift Logic II 6.3 27.18 0.00 0 0 2017 0

Early Torque Converter Lockup 0.5 29.49 0.00 0 0 2002 0

High Efficiency Gearbox 1.6 200.63 0.00 0 0 2017 0

5 Speed Automatic 1.3 103.91 0.00 20 0 1995 0

6 Speed Automatic 2.0 270.05 0.00 30 0 2003 0

7 Speed Automatic 5.0 401.04 0.00 40 0 2009 0

8 Speed Automatic 8.0 532.83 0.00 50 0 2014 0

Dual Clutch Automated Manual 4.9 182.24 0.00 -10 0 2004 0

CVT 7.8 250.98 0.00 -25 0 1998 0

Low Friction Lubricants 0.7 3.20 0.00 0 0 2003 0

Engine Friction Reduction I-4 cyl 2.0 47.16 0.00 0 0 2000 1.25

Engine Friction Reduction I-6 cyl 2.6 71.14 0.00 0 0 2000 1.25

Engine Friction Reduction I-8 cyl 2.5 94.32 0.00 0 0 2000 1.25

Engine Friction Reduction II-4 cyl 3.6 100.71 0.00 0 0 2017 2.25

Engine Friction Reduction II-6 cyl 4.7 147.87 0.00 0 0 2017 2.25

Engine Friction Reduction II-8 cyl 4.4 195.03 0.00 0 0 2017 2.25

Cylinder Deactivation-6 cyl 6.4 187.06 0.00 10 0 2004 0

Cylinder Deactivation-8 cyl 6.0 209.97 0.00 10 0 2004 0

VVT I-OHV Intake Cam Phasing-6 cyl 2.6 43.90 0.00 20 0 2051 1.25

VVT I-OHV Intake Cam Phasing-8 cyl 2.5 43.90 0.00 30 0 2051 1.25

VVT I-OHC Intake Cam Phasing-4 cyl 2.1 43.90 0.00 10 0 1993 1.25

VVT I-OHC Intake Cam Phasing-6 cyl 2.6 88.76 0.00 20 0 1993 1.25

VVT I-OHC Intake Cam Phasing-8 cyl 2.5 88.76 0.00 30 0 1993 1.25

VVT II-OHV Coupled Cam Phasing-6 cyl 5.4 43.90 0.00 20 0 2009 1.25

VVT II-OHV Coupled Cam Phasing-8 cyl 5.1 43.90 0.00 30 0 2009 1.25

VVT II-OHC Coupled Cam Phasing-4 cyl 4.3 43.90 0.00 10 0 2009 1.25

VVT II-OHC Coupled Cam Phasing-6 cyl 5.4 88.76 0.00 20 0 2009 1.25

VVT II-OHC Coupled Cam Phasing-8 cyl 5.1 88.76 0.00 30 0 2009 1.25

VVT III-OHV Dual Cam Phasing-6 cyl 5.4 99.26 0.00 25 0 2051 1.56

VVT III-OHV Dual Cam Phasing-8 cyl 5.1 99.26 0.00 37.5 0 2051 1.56

VVT III-OHC Dual Cam Phasing-4 cyl 4.3 90.67 0.00 12.5 0 2009 1.56

VVT III-OHC Dual Cam Phasing-6 cyl 5.4 195.65 0.00 25 0 2009 1.56

VVT III-OHC Dual Cam Phasing-8 cyl 5.1 195.65 0.00 37.5 0 2009 1.56

VVL I-OHV Discrete-6 cyl 5.5 225.24 0.00 40 0 2000 2.5

VVL I-OHV Discrete-8 cyl 5.2 322.59 0.00 50 0 2000 2.5

VVL I-OHC Discrete-4 cyl 4.2 155.57 0.00 25 0 2000 2.5

VVL I-OHC Discrete-6 cyl 5.5 225.24 0.00 40 0 2000 2.5

VVL I-OHC Discrete-8 cyl 5.2 322.59 0.00 50 0 2000 2.5

VVL II-OHV Continuous-6 cyl 7.0 1150.07 0.00 40 0 2011 2.5

VVL II-OHV Continuous-8 cyl 6.5 1256.96 0.00 50 0 2011 2.5

VVL II-OHC Continuous-4 cyl 5.3 232.88 0.00 25 0 2011 2.5

VVL II-OHC Continuous-6 cyl 7.0 427.58 0.00 40 0 2011 2.5

VVL II-OHC Continuous-8 cyl 6.5 466.71 0.00 50 0 2011 2.5

Stoichiometric GDI-4 cyl 1.5 264.37 0.00 20 0 2006 2.5

Stoichiometric GDI-6 cyl 1.5 397.99 0.00 30 0 2006 2.5

Stoichiometric GDI-8 cyl 1.5 478.16 0.00 40 0 2006 2.5

OHV to DOHC TBDS-I4 21.6 1383.90 0.00 -100 0 2009 3.75

OHV to DOHC TBDS I-V6 20.2 2096.84 0.00 -100 0 2009 3.75

SOHC to DOHC TBDS I-I4 21.6 827.47 0.00 -100 0 2009 3.75

SOHC to DOHC TBDS I-V6 20.2 1605.80 0.00 -100 0 2009 3.75

DOHC TBDS I-I3 17.5 915.28 0.00 -100 0 2009 3.75

DOHC TBDS I-I4 21.6 747.30 0.00 -100 0 2009 3.75

DOHC TBDS I-V6 20.2 1530.88 0.00 -100 0 2009 3.75
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 79

Transportation Demand Module

Table 7.2. Standard technology matrix for light trucks1 (cont.)

Fuel

Efficiency

Change %

Incremental 

Cost $2000

Incremental Cost

($/UnitWt.)

Absolute 

Incremental Weight 

(Lbs.)

Per Unit 

Incremental Weight

(Lbs./

UnitWt.)

Introduction YearHorse power

Change %

OHV to DOHC TBDS II-I4 26.3 1586.36 0.00 -100 0 2012 3.75

OHV to DOHC TBDS II-V6 24.5 2445.33 0.00 -100 0 2012 3.75

SOHC to DOHC TBDS II-I4 26.3 1046.15 0.00 -100 0 2012 3.75

SOHC to DOHC TBDS II-V6 24.5 1968.59 0.00 -100 0 2012 3.75

DOHC TBDS II-I3 21.2 1130.47 0.00 -100 0 2012 3.75

DOHC TBDS II-I4 26.3 968.31 0.00 -100 0 2012 3.75

DOHC TBDS II-V6 24.5 1895.85 0.00 -100 0 2012 3.75

OHV to DOHC TBDS III-I4 (from V6) 32.6 2031.83 0.00 -100 0 2017 3.75

OHV to DOHC TBDS III-I4 (from V8) 30.7 1601.81 0.00 -200 0 2017 3.75

SOHC to DOHC TBDS III-I4 (from V6) 32.6 1565.84 0.00 -100 0 2017 3.75

SOHC to DOHC TBDS III-I4 (from V8) 30.7 1380.40 0.00 -200 0 2017 3.75

DOHC TBDS III-I3 (from I4) 27.1 1634.58 0.00 -100 0 2017 3.75

DOHC TBDS III-I4 (from V6) 32.6 1498.70 0.00 -100 0 2017 3.75

DOHC TBDS III-I4 (from V8) 30.7 1302.07 0.00 -200 0 2017 3.75

Electric Power Steering 1.0 107.15 0.00 0 0 2004 0

Improved Accessories I 0.7 87.49 0.00 0 0 2005 0

12V Micro Hybrid w/EPS and IACC 6.7 697.79 0.00 45 0 2005 0

Improved Accessories II 2.4 128.69 0.00 0 0 2012 0

Mild Hybrid w/EPS and IACC II 10.6 2902.00 0.00 80 0 2012 -2.5

Tires I 2.0 5.60 0.00 -12 0 2005 0

Tires II 4.0 58.35 0.00 -15 0 2017 0

Low Drag Brakes 0.8 59.15 0.00 0 0 2000 0

Secondary Axle Disconnect 1.4 96.34 0.00 0 -1 2012 0 1

Fractional changes refer to the percentage change from the base technology.

Sources: U.S. Energy Information Administration. 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). 

National Highway Traffic Safety Administration, Corporate Average Fuel Economy for MY 2011-2015 Passenger Cars and Light Trucks (April 2008). U.S. 

Environmental Protection Agency, Interim Report: New Powertrain Technologies and Their Projected Costs (October 2005).

Environmental Protection Agency and Department of Transportation National Highway Traffic Safety Administration, “2017 and Later Model Year Light-Duty 

Vehicle Greenhouse Gas Emissions and Corporate Average Fuel Economy Standards; Final Rule,” Federal Register Vol. 77, No. 199, October 15, 2012. 40 CFR Parts 

85, 86, 600, 49 CFR Parts 523, 531, 533, et al. and 600.
80 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Transportation Demand Module

Degradation factors are used to convert new vehicle tested fuel economy values to “on-road” fuel economy values (Table 7.3). 

The degradation factors represent adjustments made to tested fuel economy values to account for the difference between fuel 

economy performance realized in the CAFE test procedure and fuel economy realized under normal driving conditions.

Table 7.3. Car and light truck degradation factors

2005 2010 2015 2020 2030 2040

Cars 79.8 81.7 81.7 81.7 81.7 81.7

Light Trucks 80.6 80.0 80.0 80.0 80.0 80.0

Source: U.S. Energy Information Administration, Transportation Sector Modules of the National Energy Modeling System, Model Documentation 2011, 

DOE/EIA-M070(2011), (Washington, DC, 2012).

Commercial light duty fleet assumptions 

The Transportation Demand Module divides 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 of in-fleet use before sale for 

use as personal vehicles. The average length of time passenger cars are kept before being sold for personal use is 3 years for 

business use, 6 years for government use, and 5 years for utility use. Of total automobile sales to fleets in 2009, 75.1 percent 

are used in business fleets, 9.6 percent in government fleets, and 15.3 percent in utility fleets. Of total light truck sales to fleets 

in 2009, 47.3 percent are used in business fleets, 15.1 percent in government fleets, and 37.6 percent in utility fleets [3]. Both 

the automobile and light truck shares by fleet type are held constant from 2009 through 2040. In 2009, 18.2 percent of all 

automobiles sold and 16.9 percent of all light trucks sold were for fleet use. The share of total automobile and light truck sales 

slowly declines over the forecast period based on historic trends.

Table 7.4. Percent of fleet alternative fuel vehicles by fleet type by size class, 2005

Mini Subcompact Compact Midsize Large 2-Seater

Car

Business 0.0 10.5 10.7 42.7 36.1 0.0

Government 0.0 2.8 40.0 2.8 54.4 0.0

Utility 0.0 7.9 34.7 12.3 45.1 0.0

SM Pk LG Pk SM Van LG Van SM Util LG Util

Light Truck

Business 7.9 35.1 7.9 26.8 5.5 16.8

Government 6.7 50.8 28.4 4.6 1.6 7.8

Utility 8.2 52.1 6.0 32.7 0.3 0.7

Source: U.S. Energy Information Administration, “Archive--Alternative Transportation Fuels (ATF) and Alternative Fueled Vehicles (AFV),” http://

www.eia.doe.gov/cneaf/alternate/page/aftables/afvtransfuel_II.html #in use.

Alternative-fuel shares of fleet vehicle sales by fleet type are held constant at 2005 levels (Table 7.4). Size class sales shares of 

vehicles are also held constant at 2005 levels (Table 7.5) [4]. Individual sales shares of new vehicles purchased by technology 

type are assumed to remain relatively constant for utility, government, and for business fleets using the previous 5-year average 

(Table 7.6) [5].

Annual vehicle miles traveled (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.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 81

Transportation Demand Module

Table 7.5. Commercial fleet size class shares by fleet and vehicle type, 2005

percentage

Fleet Type by Size Class Automobiles Light Trucks

Business Fleet

Mini 3.1 2.5

Subcompact 23.4 8.4

Compact 26.6 23.3

Midsize 36.2 8.1

Large 9.9 14.2

2-seater 0.8 43.6

Government Fleet

Mini 0.2 6.7

Subcompact 4.6 43.6

Compact 20.6 10.4

Midsize 28.6 17.1

Large 46.0 3.8

2-seater 0.0 18.4

Utility Fleet

Mini 1.5 7.3

Subcompact 12.5 38.7

Compact 10.0 11.8

Midsize 59.2 18.9

Large 16.4 7.2

2-seater 0.4 16.1

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 Energy Analysis, (Oak Ridge, Tn, January 2003). 

Table 7.6. Share of new vehicle purchases by fleet type and technology type, 2009

percentage

Technology Business Government Utility

Cars

Gasoline 99.10 72.78 95.52

Ethanol Flex 0.46 26.20 2.11

Electric 0.00 0.02 0.07

CNG/LNG Bi-Fuel 0.14 0.56 1.08

LPG Bi-Fuel 0.16 0.11 0.40

CNG/LNG 0.08 0.33 0.63

LPG 0.08 0.01 0.19

Light Trucks

Gasoline 71.71 59.46 98.22

Ethanol Flex 16.29 35.09 0.49

Electric 0.04 0.07 0.05

CNG/LNG Bi-Fuel 1.28 2.29 0.51

LPG Bi-Fuel 7.93 2.55 0.31

CNG/LNG 1.54 0.49 0.24

LPG 1.22 0.05 0.18

Sources: U.S. Energy Information Administration, Archive - Alternative Transportation Fuels (ATF) and Alternative Fueled Vehicles (AFV), http://

www.eia.gov/renewable/afv/archive/index.cfm.
82 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Transportation Demand Module

The light commercial truck model

The Light Commercial Truck Module of the NEMS Transportation Model represents light trucks that have a 8,501 to 10,000 

pound gross vehicle weight rating (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 economy, and energy 

use by vintage. Historic vehicle sales and stock data, which constitute the baseline from which the projection is made, are 

taken from an Oak Ridge National Laboratory study [6]. The distribution of vehicles by vintage, and vehicle scrappage rates 

are derived from R.L. Polk & Co. registration data [7],[8]. Vehicle travel by vintage was constructed using vintage distribution 

curves and estimates of average annual travel by vehicle [9],[10]. 

The growth in light commercial truck VMT is a function of industrial output for agriculture, mining, construction, total 

manufacturing, utilities, and personal travel. These groupings were chosen for their correspondence with output measures 

being forecast by NEMS. The overall growth in VMT reflects a weighted average based on the distribution of total light 

commercial truck VMT by sector. Projected fuel efficiencies are assumed to increase at the same annual growth rate as 

conventional gasoline light-duty trucks (<8,500 pounds gross vehicle weight).

Consumer vehicle choice assumptions

The Consumer Vehicle Choice Component (CVCC) 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, compressed natural gas (CNG) and liquefied natural gas (LNG), liquefied 

petroleum gas (LPG), and flex-fuel),

•	 Hybrid (gasoline and diesel),

•	 Plug-in hybrid (10 mile all-electric range and 40 mile all-electric range)

•	 Dedicated alternative fuel (CNG, LNG, and LPG),

•	 Fuel cell (gasoline, methanol, and hydrogen), and

•	 Electric battery powered (100 mile range and 200 mile range) [12]

The vehicle attributes considered in the choice algorithm include: vehicle price, maintenance cost, battery replacement cost, 

range, multi-fuel capability, home refueling capability, fuel economy, acceleration and luggage space. With the exceptions of 

maintenance cost, battery replacement cost, and luggage space, vehicle attributes are determined endogenously [13]. Battery 

costs for plug-in hybrid electric and all-electric vehicles are based on a production based function over several technology 

phase periods. 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, CVCC 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 CVCC 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 CVCC 

vehicle stocks are set according to the EIA survey EIA-886 [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 bifuel and flex-fuel alcohol vehicles.

Freight truck assumptions

The freight truck module estimates vehicle stocks, travel, fuel efficiency, and energy use for three size classes of trucks: lightmedium (Class 3), heavy-medium (Classes 4-6), and heavy (Classes 7-8). The three size classes are further broken down into 

13 subclasses for fuel economy classification purposes (Table 7.7). These subclasses include two breakouts for light-medium 

size class, including pickup/van and vocational, one breakout for heavy-medium, including vocational, and ten breakouts 

for heavy. The ten subclasses for heavy include parceling the class into class 7 or class 8, day cab or sleeper cab, and low, 

mid or high roof. Within the size classes, the stock model structure is designed to cover 34 vehicle vintages and to estimate 

energy use by four fuel types: diesel, gasoline, LPG, and natural gas (CNG and LNG). Fuel consumption estimates are reported 

regionally (by Census Division) according to the distillate fuel shares from the State Energy Data System [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, are shown in Table 7.8.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 83

Transportation Demand Module

Table 7.7. Vehicle technology category for technology matrix for freight trucks

Vehicle category Class Type Roof1

1 3 Pickup and Van -

2 3 Vocational -

3 4-6 Vocational -

4 7-8 Vocational -

5 7 Tractor - day cab low

6 7 Tractor - day cab mid

7 7 Tractor - day cab high

8 8 Tractor - day cab low

9 8 Tractor - day cab mid

10 8 Tractor - day cab high

11 8 Tractor - sleeper cab low

12 8 Tractor - sleeper cab mid

13 8 Tractor - sleeper cab high

1

Applies to Class 7 and 8 day and sleeper cabs only.

Table 7.8. Standard technology matrix for freight trucks

Technology Type

Vehicle 

Category

Introduction 

Year

Capital Costs

(2009$)

Incremental Fuel 

Economy 

Improvement 

(%)

Aerodynamics I: streamlined bumper, grill, windshield, roof 1 2010 58 1.5

Aerodynamics I: conventional features; general aerodynamic shape, removal of

classic non-aerodynamic features 5,8,11 1995 1000 4.1

Aerodynamics I 7,10,13 1995 1000 4.6

Aerodynamics II: SmartWay features; streamlined shape, bumper grill, hood,

mirrors, side fuel tank and roof fairings, side gap extenders 

5, 8 2004 1126 1.5

Aerodynamics II 7,10 2004 1126 3.1

Aerodynamics II 11 2004 1155 4.2

Aerodynamics II 13 2004 1506 4.2

Aerodynamics III: underbody airflow, down exhaust, lowered ride height 7 2014 2303 4.2

Aerodynamics III 10 2014 0 0

Aerodynamics III 13 2014 2675 5.8

Aerodynamics IV: skirts, boat tails, nose cone, vortex stabilizer, pneumatic

blowing 5-13 1995 5500 13.0

Tires I: low rolling resistance 1 2010 7 1.5

Tires I 2,3 2010 162 2.6

Tires I 4, 8-13 2010 194 2.0

Tires I 5-7 2010 130 2.0

Tires II: super singles 5-13 2000 150 5.3

Tires III: single wide tires on trailer 5-13 2000 800 3.1

Weight Reduction I 1 2010 127 1.6

Weight Reduction I: aluminum dual tires or super singles 5-13 2010 650 1.0

Weight Reduction II: weight reduction 15% 3-13 2018 6200 3.0

Weight Reduction III: weight reduction 20% 3-13 2022 11000 3.5

Accessories I: Electric/electrohydraulic improvements; electric power steering or

electrohydraulic power steering 1 2010 115 1.5

Accessories II: Improved accessories; electrified water, oil, fuel injection, power

steering pump, aircompressor 1 2010 93 1.5

Accessories III: Auxiliary Power Unit 11-13 2000 5400 5.8

Transmission I: 8-speed Automatic from 6-speed automatic 1 2000 280 1.7

Transmission II: 6-Manual from 4-speed automatic 1 1995 150 1.0

Transmission III: Automated Manual Transmission 2-13 2000 5000 3.5

Diesel Engine I: aftertreatment improvements 1 2010 119 4.0

Diesel Engine I 2 2010 117 2.6

Diesel Engine II: low friction lubricants 1-13 2005 4 0.5

Diesel Engine III: variable valve actuation 2 2010 0 1.0

Diesel Engine III 3-13 2005 300 1.0

Diesel Engine IV: engine friction reduction, low tension piston rings, roller cam

followers, piston skirt design, improved crankshaft design and bearings; coating 1-2 2010 116 1.0
84 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Transportation Demand Module

Table 7.8. Standard technology matrix for freight trucks (cont.)

Technology Type

Vehicle 

Category

Introduction 

Year

Capital Costs

(2009$)

Incremental Fuel 

Economy 

Improvement 

(%)

Diesel Engine IV: engine friction reduction, improved bearings to allow lower 

viscosity oil 3-13 2010 250 1.0

Diesel Engine V: improved turbo efficiency 2-13 2010 18 1.5

Diesel Engine VI: improved water, oil, fuel pump; pistons; valve train friction 

reduction 2 2010 213 1.3

Diesel Engine VI 3, 5-8 2010 186 1.3

Diesel Engine VI: improved water, oil, and fuel pump; pistons 4, 9-13 2010 150 1.3

Diesel Engine VII: improved cylinder head, fuel rail and injector, EGR cooler 2 2010 42 4.7

Diesel Engine VII 3-13 2010 31 4.7

Diesel Engine VIII: turbo mechanical compounding 5-13 2017 1000 3.9

Diesel Engine IX: low temperature EGR, improved turbochargers 1 2010 184 5.0

Diesel Engine X: sequential downsizing/turbocharging 5-13 2010 1200 2.5

Diesel Engine XI: waste heat recovery, Organic Rankine Cycle (bottoming cycle) 3-13 2019 10000 8.0

Diesel Engine XII: electric turbo compounding 4-13 2020 8000 7.6

Gasoline Engine I: low friction lubricants 1-13 2010 4 0.5

Gasoline Engine II: coupled cam phasing 2-4 2010 46 2.6

Gasoline Engine III: engine friction reduction; low tension piston rings, roller cam 

followers, piston skirt design, improved crankshaft design and bearings; coating 1-2 2010 116 2.0

Gasoline III 3-4 2010 95 2.0

Gasoline Engine IV: stoichiometric gasoline direct injection V8 1 2006 481 1.5

Gasoline Engine IV 2 2010 481 1.5

Gasoline Engine IV 3-4 2014 450 1.5

Gasoline Engine V: turbocharging and downsizing SGDI V8 to V6 1-4 2006 1743 2.1 

Gasoline Engine VI: lean burn GDI 1-4 2020 750 13.0 

Gasoline Engine VII: HCCI 1-4 2030 685 12.0 

Hybrid System I: 42V engine off at idle 1-2 2005 1500 7.0 

Hybrid System I 3-4 2005 1500 4.5 

Hybrid System II: dual mode hybrid 1-2 2008 12000 25.0 

Hybrid System II: electric, ePTO, or hydraulic 3-4 2009 26667 30.0 

Hybrid System II: 4 kWh battery, 50 kW motor generator 5-13 2012 26000 5.5 

Source: Greenhouse Gas Emissions Standards and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles, U.S. Environmental Protection 

Agency and U.S. Department of Transportation, Final Rules, Federal Register, Vol. 76, No. 179, (September 2011). Final Rulemaking to Establish Greenhouse 

Gas Emissions Standards and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles, Regulatory Impact Analysis,

U.S. Environmental Protection Agency and U.S. Department of Transportation, (August 2011). Reducing Heavy-Duty Long Haul Combination Truck Fuel 

Consumption and CO2 Emissions, Final Report, TIAX, LLC. (October 2009). Update of Technology Information for Forecasting Heavy-Duty On-Road Vehicle 

Fuel Economy, Final Report, ICF International, Prepared for the U.S. Energy Information Administration, (August 2010). Technologies and Approaches to 

Reducing the Fuel Consumption of Medium- and Heavy-Duty Vehicles, National Research Council of the National Academy of Sciences, (2010).

The freight module uses projections 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 Industry 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 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.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 85

Transportation Demand Module

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 by the U.S. Energy Information Administration 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. Vehicle scrappage rates are also estimated by the U.S. Energy Information Administration 

using R. L. Polk & Co. data.

Freight rail assumptions

The freight rail module uses the industrial output by NAICS code measured in real 2005 dollars and converts these dollars into an 

adjusted volume equivalent. Coal production from the NEMS Coal Market Module is used to adjust coal-based rail travel. Freight 

rail adjustment coefficients (used to convert dollars to volume equivalents) are based on historical data and remain constant 

[21],[22]. Initial freight rail efficiencies are based on historic data taken from the Transportation Energy Data Book [23]. The 

distribution of rail fuel consumption by fuel type is also based on historical data and remains constant over the projection [24]. 

Regional freight rail consumption estimates are distributed according to the State Energy Data System [25].

Domestic and international shipping assumptions

Similar to the previous sub-module, the domestic freight shipping module uses the industrial output by NAICS code measured in 

real 2005 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 historical data and remains constant throughout the projection [26]. Regional domestic 

shipping consumption estimates are distributed according to the residual oil regional shares in the State Energy Data System [27]. 

The air model

The air model is a thirteen region world demand and supply model (Table 7.9). For each region, demand is computed for domestic 

travel (both takeoff and landing occur in the same region) and international travel (either takeoff or landing is in the region but not 

both). Once the demand for aircraft is determined, the stock efficiency module moves aircraft between regions to satisfy the 

demand.

Table 7.9. Thirteen regions for the world model

Region Number Region Major Countries in Region

1 United States United States

2 Canada Canada

3 Central America Mexico

4 South America Brazil

5 Europe France, Germany

6 Africa S. Africa

7 Middle East Egypt

8 Russia Russia

9 China China

10 Northeast Asia Japan, Korea

11 Southeast Asia Vietnam

12 Southwest Asia India

13 Oceania Australia, New Zealand

Source: Jet Information Services, 2009 World Jet Inventory, data tables (2009)

Air travel demand assumptions

The air travel demand module calculates the domestic and international per-capita revenue passenger miles (RPM-PC) for each 

region. Domestic and international revenue passenger miles are based on the historical data in Table 7.10, [28] per capita income 

for the United States, per-capita GDP for the non-U.S. regions, and ticket prices. The revenue ton miles of air freight for the United 

States are based on merchandise exports, gross domestic product, and fuel cost. For the non-U.S. regions, revenue ton miles are 

based on GDP growth in the region [29].
86 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Transportation Demand Module

Airport capacity constraints based on the Federal Aviation Administration (FAA) Airport Capacity Benchmark Report 2004 

are incorporated into the air travel demand module using airport capacity measures [30]. 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 expansion is expected to be delayed due to the economic environment and fuel costs.

Aircraft stock/efficiency assumptions

The aircraft stock and efficiency module consists of a world regional 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 2009, new passenger sales, 

and the survival rate by vintage (Table 7.11) [31]. New passenger sales are a function of revenue passenger miles and gross 

domestic product.

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 increase gradually over time. Domestic and international travel are 

combined into a single regional demand for seat-miles and passed to the Aircraft Fleet Efficiency Component, which adjusts the 

initial aircraft stock to meet that demand. For each region, starting with the United States, the initial stock is adjusted by moving 

aircraft between regions.

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 an improvement over the stock efficiency of surviving airplanes. A generic set of 

new technologies (Table 7.12) are introduced in different years and with a set of improved efficiencies over the base year (2007). 

Regional shares of all types of aircraft fuel use are assumed to be constant and are consistent with the State Energy Data System 

estimate of regional jet fuel shares.

Table 7.10. 2010 Regional population, gdp, per capita gdp, domestic and international rpm and per-capita rpm

Region

Population

(million) GDP (2006$) GDP_PC

United States 310.8 13,088 42,106.0

Canada 34.1 1,239 36,383.8

Central America 197.3 2,025 10,262.7

South America 393.1 3,993 10,158.3

Europe 607.9 15,367 25,280.1

Africa 931.9 2,636 2,829.1

Middle East 298.7 3,083 10,318.7

Russia 278.6 2,843 10,203.4

China 1,347.3 9,577 7,108.2

Northeast Asia 200.6 5,024 25,045.1

Southeast Asia 627.9 3,752 5,975.7

Southwest Asia 1,629.3 4,971 3,015.2

Oceania 27.9 909 32,641.2

Region RPM (billion) RPM_PC (thousand)

Domestic

United States 564.8 1,816.9

Canada 27.1 795.0

Central America 20.1 101.8

South America 70.7 179.9

Europe 399.4 657.0

Africa 31.0 33.2

Middle East 47.8 159.9

Russia 32.8 117.9

China 208.0 154.4

Northeast Asia 44.5 221.8

Southeast Asia 81.0 129.0

Southwest Asia 30.4 18.7

Oceania 50.0 1,795.2
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 87

Transportation Demand Module

Table 7.10. 2010 Regional population, gdp, per capita gdp, domestic and international rpm and per-capita rpm (cont.)

Region

RPM

(billion) RPM_PC (thousand)

International

United States 244.2 785.7

Canada 53.1 1,559.8

Central America 63.7 322.9

South America 49.8 126.7

Europe 378.3 622.4

Africa 59.2 63.5

Middle East 113.5 380.0

Russia 31.0 111.1

China 90.9 67.5

Northeast Asia 93.0 463.5

Southeast Asia 132.9 211.6

Southwest Asia 49.5 30.4

Oceania 44.0 1,579.9

Source: Global Insight 2006 chained weighted dollars, Boeing Current Market Outlook 2009.

Table 7.11. 2010 Regional passenger and cargo aircraft supply

Aircraft Type New

Age of Aircraft (years)

1-10 11-20 21-30 >30 Total

Passenger

Narrow Body

United States 98 1456 1397 680 185 3816 

Canada 5 144 80 17 13 259 

Central America 12 173 46 74 58 363 

South America 42 279 138 146 109 714 

Europe 204 1630 953 191 20 2998 

Africa 22 148 149 162 106 587 

Middle East 60 215 160 58 36 529 

Russia 14 202 372 283 215 1086 

China 168 847 282 11 1 1309 

Northeast Asia 22 149 109 7 4 291 

Southeast Asia 83 239 201 120 28 671 

Southwest Asia 27 224 46 43 7 347 

Oceania 14 165 49 2 0 230 

Wide Body

United States 9 201 294 129 18 651 

Canada 0 30 32 22 0 84 

Central America 0 9 7 8 0 24 

South America 3 43 43 6 2 97 

Europe 36 345 368 53 9 811 

Africa 2 57 43 35 12 149 

Middle East 36 236 145 70 11 498 

Russia 4 20 83 51 0 158 

China 22 132 11 3 4 0 271 

Northeast Asia 17 146 158 23 0 344 

Southeast Asia 21 204 166 18 7 416 

Southwest Asia 3 51 32 23 4 113 

Oceania 7 56 55 8 0 126 

Regional Jets

United States 35 1774 487 49 9 2354 

Canada 8 132 118 72 25 355 

Central America 5 85 61 18 0 169 

South America 32 94 11 3 31 3 273 

Europe 84 669 638 106 0 1497 

Africa 24 106 124 59 13 326 

Middle East 15 86 83 10 3 197 

Russia 1 73 79 71 3 227
88 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Transportation Demand Module

Table 7.11. 2009 Regional passenger and cargo aircraft supply (cont.)

Age of Aircraft (years)

Aircraft Type New 1-10 11-20 21-30 >30 Total

China 18 112 15 1 0 146 

Northeast Asia 8 56 5 0 0 69 

Southeast Asia 18 78 90 41 7 234 

Southwest Asia 7 53 27 5 3 95 

Oceania 6 98 91 42 0 237 

Cargo

Narrow Body

United States 0 0 76 106 218 400 

Canada 0 0 4 8 21 33

Central America 0 2 2 5 8 17

South America 0 0 3 17 42 62

Europe 0 0 24 68 10 102

Africa 0 0 4 13 57 74

Middle East 0 0 2 5 6 13

Russia 0 5 2 2 8 17

China 0 2 20 16 1 39 

Northeast Asia 0 0 0 0 0 0 

Southeast Asia 0 0 0 8 14 23

Southwest Asia 0 0 2 10 5 17

Oceania 0 0 0 10 3 13

Wide Body

United States 14 86 227 184 102 613 

Canada 0 0 0 3 4 7 

Central America 0 2 1 3 4 10 

South America 0 8 2 7 7 24 

Europe 5 32 52 54 8 151 

Africa 0 0 2 1 1 4 

Middle East 4 10 18 18 5 55 

Russia 0 5 9 5 0 19 

China 9 35 36 11 0 91 

Northeast Asia 0 30 19 4 0 53 

Southeast Asia 0 32 18 4 0 54 

Southwest Asia 0 0 5 4 1 10 

Oceania 0 0 0 0 0 0 

Regional Jets

United States 0 0 22 3 0 25 

Canada 0 0 0 7 0 7

Central America 0 0 4 1 0 5 

South America 0 0 0 4 0 4 

Europe 0 2 55 40 0 97 

Africa 0 0 0 5 1 6 

Middle East 0 0 0 0 0 0 

Russia 0 0 1 0 0 1 

China 0 0 0 0 0 0 

Northeast Asia 0 0 0 0 0 0 

Southeast Asia 0 0 2 3 0 5 

Southwest Asia 0 0 1 0 0 1 

Oceania 0 0 1 3 0 4 

Survival Curve (fraction) New 5 10 20 40

Narrow Body 1.000 0.9998 0.9994 0.9970 0.8000 

Wide Body 1.000 0.9984 0.9961 0.9870 0.7900 

Regional Jets 1.000 0.9971 0.9950 0.9830 0.7800 

Source: Jet Information Services, 2009 World Jet Inventory (2009).
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 89

Transportation Demand Module

Table 7.12. Standard technology matrix for air travel

Technology Introduction Year Fractional Efficiency Improvement Jet Fuel Trigger Price (1987$/per gallon)

Technology #1 2008 0.03 1.34

Technology #2 2014 0.07 1.34

Technology #3 2020 0.11 1.34

Technology #4 2025 0.15 1.34

Technology #5 2018 0.20 1.34

Technology #6 2018 0.00 1.34

Source: Jet Information Services, 2009 World Jet Inventory, data tables (2009)

Legislation and regulations

Light Duty Vehicle Combined Corporate Average Fuel Economy (CAFE) Standards

The AEO2013 Reference case includes the attribute-based CAFE standards for LDVs for Model Year (MY) 2011, the joint 

attribute-based CAFE and vehicle GHG emissions standards for MY 2012 through MY 2016 and for MY 2017 through 

2025. CAFE standards are then held constant in subsequent model years, although the fuel economy of new LDVs 

continues to rise modestly over time.

Heavy Duty Vehicle Combined Corporate Average Fuel Economy Standards

On September 15, 2011, the EPA and NHTSA jointly announced a final rule, called the HD National Program [32], which for 

the first time establishes greenhouse gas (GHG) emissions and fuel consumption standards for on-road heavy-duty trucks 

and their engines. The AEO2013 Reference case incorporates the new standards for heavy-duty vehicles (HDVs) with gross 

vehicle weight rating (GVWR) above 8,500 pounds (Classes 2b through 8). The HD National Program standards begin for 

MY 2014 vehicles and engines and are fully phased in by MY 2018. AEO2013 models standard compliance among 13 HDV 

regulatory classifications that represent the discrete vehicle categories set forth in the rule.

Energy Independence and Security Act of 2007 (EISA2007)

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 allows for sensitivity analysis of CAFE credit banking by 

manufacturer fleet, but does not model the trading of credits across manufacturers. The AEO2013 does not consider 

trading of credits since this would require significant modifications to the NEMS and detailed technology cost and 

efficiency data by manufacturer, which are not readily available.

The CAFE credits specified under the Alternative Motor Fuels Act (AMFA) through 2019 are 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 model CAFE credits earned from alternative fuel vehicles sales.

American Recovery and Reinvestment Act of 2009 and Energy Improvement and Extension Act of 2008

ARRA Title I, Section 1141, modified the EIEA2008 Title II, Section 205, tax credit for the purchase of new, qualified plugin electric drive motor vehicles. According to the legislation, a qualified plug-in electric drive motor vehicle must draw 

propulsion from a traction battery with at least 4 kilowatthours of capacity and be propelled to a significant extent by 

an electric motor which draws electricity from a battery that is capable of being recharged from an external source of 

electricity.
90 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Transportation Demand Module

The tax credit for the purchase of a plug-in electric vehicle is $2,500, plus, starting at a battery capacity of 5 kilowatthours, an 

additional $417 per kilowatthour battery credit up to a maximum of $7,500 per vehicle. The tax credit eligibility and phaseout are specific to an individual vehicle manufacturer. The credits are phased out once a manufacturer’s cumulative sales of 

qualified vehicles reach 200,000. The phaseout period begins two calendar quarters after the first date in which a

manufacturer’s sales reach the cumulative sales maximum after December 31, 2009. The credit is reduced to 50 percent of the 

total value for the first two calendar quarters of the phase-out period and then to 25 percent for the third and fourth calendar 

quarters before being phased out entirely thereafter. The credit applies to vehicles with a gross vehicle weight rating of less 

than 14,000 pounds.

ARRA also allows a tax credit of 10 percent against the cost of a qualified electric vehicle with a battery capacity of at least 4 

kilowatthours subject to the same phase out rules as above. The tax credits for qualified plug-in electric drive motor vehicles 

and electric vehicles are included in AEO2013.

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 7.13).

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 [33].

Table 7.13. EPACT legislative mandates for AFV purchases by fleet type and year

percent

Year Federal State Fuel Providers Electric Utilities

2005 75 75 70 90

Source: U.S. Energy Information Administraiton, Energy Efficiency and Renewable Energy (Washington, DC, 2005), www1.eere.energy.gov/vehicles and 

fuels/epact/state/statutes_regulations.,html.

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. Fourteen 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 ATPZEVs 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 

of the sales requirement to be met with AT-PZEVs and 60 percent of the requirement to 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.

Transportation alternative case

Integrated High Technology case

In the Integrated High Technology case for cars and light trucks, the conventional fuel saving technology characteristics are 

based on NHTSA and EPA values [34]. Tables 7.14 and 7.15, summarize the high technology matrices for cars and light trucks. 

Table 7.16 reflects the high technology case assumptions for freight trucks. These reflect optimistic values, with respect to 

efficiency improvement and capital cost, for advanced technologies [35-38]. For the air module, the Integrated High Technology case reflects earlier introduction years for the new aircraft technologies and a greater penetration share, Table 7.17.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 91

Transportation Demand Module

Table 7.14. High technology matrix for cars

Fuel 

Efficiency 

Change %

Incremental 

Cost $2000

Incremental 

Cost ($/

UnitWt.)

Absolute 

Incremental 

Weight 

(Lbs.)

Per Unit 

Incremental 

Weight 

(Lbs./

UnitWt.)

Introduction 

Year

Horsepower 

Change %

Unit Body Construction 4.4 89.92 0.00 0 -6 1980 0

Mass Reduction I 1.1 0.00 0.06 0 -1.5 2005 0

Mass Reduction II 2.9 0.00 0.13 0 -3.5 2009 0

Mass Reduction III 5.9 0.00 0.37 0 -10 2011 0

Mass Reduction IV 9.2 0.00 0.56 0 -15 2099 0

Mass Reduction V 12.8 0.00 0.65 0 -20 2099 0

Aerodynamics I 2.6 43.35 0.00 0 0.5 2000 0

Aerodynamics II 5.4 182.96 0.00 0 1 2011 0

6 Speed Manual 2.4 230.03 0.00 20 0 1995 0

Aggressive Shift Logic I 2.8 29.20 0.00 0 0 1999 0

Aggressive Shift Logic II 7.4 24.46 0.00 0 0 2017 0

Early Torque Converter Lockup 0.6 26.54 0.00 0 0 2002 0

High Efficiency Gearbox 1.8 180.56 0.00 0 0 2017 0

5 Speed Automatic 1.5 93.52 0.00 20 0 1995 0

6 Speed Automatic 2.4 243.05 0.00 30 0 2003 0

7 Speed Automatic 5.6 360.93 0.00 40 0 2009 0

8 Speed Automatic 8.8 479.55 0.00 50 0 2010 0

Dual Clutch Automated Manual 6.1 51.08 0.00 -10 0 2004 0

CVT 9.2 225.88 0.00 -25 0 1998 0

Low Friction Lubricants 0.8 2.88 0.00 0 0 2003 0

Engine Friction Reduction I-4 cyl 2.2 42.44 0.00 0 0 2000 1.25

Engine Friction Reduction I-6 cyl 2.9 64.02 0.00 0 0 2000 1.25

Engine Friction Reduction I-8 cyl 3.1 84.89 0.00 0 0 2000 1.25

Engine Friction Reduction II-4 cyl 4.0 90.64 0.00 0 0 2017 2.25

Engine Friction Reduction II-6 cyl 5.2 133.08 0.00 0 0 2017 2.25

Engine Friction Reduction II-8 cyl 5.6 175.53 0.00 0 0 2017 2.25

Cylinder Deactivation-6 cyl 7.2 168.36 0.00 10 0 2004 0

Cylinder Deactivation-8 cyl 7.6 188.97 0.00 10 0 2004 0

VVT I-OHV Intake Cam Phasing-6 cyl 2.9 39.51 0.00 20 0 2051 1.25

VVT I-OHV Intake Cam Phasing-8 cyl 3.0 39.51 0.00 30 0 2051 1.25

VVT I-OHC Intake Cam Phasing-4 cyl 2.3 39.51 0.00 10 0 1993 1.25

VVT I-OHC Intake Cam Phasing-6 cyl 2.9 79.88 0.00 20 0 1993 1.25

VVT I-OHC Intake Cam Phasing-8 cyl 3.0 79.88 0.00 30 0 1993 1.25

VVT II-OHV Coupled Cam Phasing-6 cyl 5.9 39.51 0.00 20 0 2009 1.25

VVT II-OHV Coupled Cam Phasing-8 cyl 6.4 39.51 0.00 30 0 2009 1.25

VVT II-OHC Coupled Cam Phasing-4 cyl 4.7 39.51 0.00 10 0 2009 1.25

VVT II-OHC Coupled Cam Phasing-6 cyl 5.9 79.88 0.00 20 0 2009 1.25

VVT II-OHC Coupled Cam Phasing-8 cyl 6.4 79.88 0.00 30 0 2009 1.25

VVT III-OHV Dual Cam Phasing-6 cyl 5.9 89.33 0.00 25 0 2051 1.56

VVT III-OHV Dual Cam Phasing-8 cyl 6.4 89.33 0.00 37.5 0 2051 1.56

VVT III-OHC Dual Cam Phasing-4 cyl 4.7 81.60 0.00 12.5 0 2009 1.56

VVT III-OHC Dual Cam Phasing-6 cyl 5.9 176.09 0.00 25 0 2009 1.56

VVT III-OHC Dual Cam Phasing-8 cyl 6.4 176.09 0.00 37.5 0 2009 1.56

VVL I-OHV Discrete-6 cyl 6.1 202.72 0.00 40 0 2000 2.5

VVL I-OHV Discrete-8 cyl 6.5 290.33 0.00 50 0 2000 2.5

VVL I-OHC Discrete-4 cyl 4.7 140.01 0.00 25 0 2000 2.5

VVL I-OHC Discrete-6 cyl 6.1 202.72 0.00 40 0 2000 2.5

VVL I-OHC Discrete-8 cyl 6.5 290.33 0.00 50 0 2000 2.5

VVL II-OHV Continuous-6 cyl 7.7 1035.06 0.00 40 0 2011 2.5

VVL II-OHV Continuous-8 cyl 8.3 1131.26 0.00 50 0 2011 2.5

VVL II-OHC Continuous-4 cyl 5.9 209.59 0.00 25 0 2011 2.5

VVL II-OHC Continuous-6 cyl 7.7 384.82 0.00 40 0 2011 2.5

VVL II-OHC Continuous-8 cyl 8.3 420.04 0.00 50 0 2011 2.5

Stoichiometric GDI-4 cyl 1.7 237.93 0.00 20 0 2006 2.5

Stoichiometric GDI-6 cyl 1.7 358.19 0.00 30 0 2006 2.5

Stoichiometric GDI-8 cyl 1.7 430.34 0.00 40 0 2006 2.5

OHV to DOHC TBDS-I4 23.8 1245.51 0.00 -100 0 2009 3.75

OHV to DOHC TBDS I-V6 22.2 1887.16 0.00 -100 0 2009 3.75

SOHC to DOHC TBDS I-I4 23.8 744.73 0.00 -100 0 2009 3.75

SOHC to DOHC TBDS I-V6 22.2 1445.22 0.00 -100 0 2009 3.75

DOHC TBDS I-I3 19.3 823.75 0.00 -100 0 2009 3.75

DOHC TBDS I-I4 23.8 672.57 0.00 -100 0 2009 3.75

DOHC TBDS I-V6 22.2 1377.79 0.00 -100 0 2009 3.75
92 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Transportation Demand Module

Table 7.14. High technology matrix for cars (cont.)

Fuel 

Efficiency 

Change %

Incremental 

Cost $2000

Incremental 

Cost ($/

UnitWt.)

Absolute 

Incremental 

Weight 

(Lbs.)

Per Unit 

Incremental 

Weight 

(Lbs./

UnitWt.)

Introduction 

Year

Horsepower 

Change %

OHV to DOHC TBDS II-I4 28.9 1427.73 0.00 -100 0 2012 3.75

OHV to DOHC TBDS II-V6 27.0 2200.80 0.00 -100 0 2012 3.75

SOHC to DOHC TBDS II-I4 28.9 941.53 0.00 -100 0 2012 3.75

SOHC to DOHC TBDS II-V6 27.0 1771.73 0.00 -100 0 2012 3.75

DOHC TBDS II-I3 23.3 1017.42 0.00 -100 0 2012 3.75

DOHC TBDS II-I4 28.9 871.48 0.00 -100 0 2012 3.75

DOHC TBDS II-V6 27.0 1706.27 0.00 -100 0 2012 3.75

OHV to DOHC TBDS III-I4 (from V6) 35.9 1828.65 0.00 -100 0 2017 3.75

OHV to DOHC TBDS III-I4 (from V8) 33.8 1441.63 0.00 -200 0 2017 3.75

SOHC to DOHC TBDS III-I4 (from V6) 35.9 1409.25 0.00 -100 0 2017 3.75

SOHC to DOHC TBDS III-I4 (from V8) 33.8 1242.36 0.00 -200 0 2017 3.75

DOHC TBDS III-I3 (from I4) 29.8 1471.12 0.00 -100 0 2017 3.75

DOHC TBDS III-I4 (from V6) 35.9 1348.83 0.00 -100 0 2017 3.75

DOHC TBDS III-I4 (from V8) 33.8 1171.86 0.00 -200 0 2017 3.75

Electric Power Steering 1.4 96.44 0.00 0 0 2004 0

Improved Accessories I 0.8 78.74 0.00 0 0 2005 0

12V Micro Hybrid w/EPS and IACC 7.7 576.22 0.00 45 0 2005 0

Improved Accessories II 2.8 115.82 0.00 0 0 2012 0

Mild Hybrid w/EPS and IACC II 12.1 2611.80 0.00 80 0 2012 -2.5

Tires I 2.2 5.04 0.00 -12 0 2005 0

Tires II 4.4 52.51 0.00 -15 0 2017 0

Low Drag Brakes 0.9 53.23 0.00 0 0 2000 0

Secondary Axle Disconnect 1.4 86.70 0.00 0 -1 2012 0

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). National 

Highway Traffic Safety Administration, Corporate Average Fuel Economy for MY 2011-2015 Passenger Cars and Light Trucks (April 2008). U.S. Environmental 

Protection Agency, Interim Report: New Powertrain Technologies and Their Projected Costs (October 2005).

Environmental Protection Agency and Department of Transportation National Highway Traffic Safety Administration, “2017 and Later Model Year Light-Duty 

Vehicle Greenhouse Gas Emissions and Corporate Average Fuel Economy Standards; Final Rule,” Federal Register Vol. 77, No. 199, October 15, 2012. 40 CFR 

Parts 85, 86, 600, 49 CFR Parts 523, 531, 533, et al. and 600.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 93

Transportation Demand Module

Table 7.15. High technology matrix for light trucks

Fuel 

Efficiency 

Change %

Incremental 

Cost $2000

Incremental 

Cost ($/

UnitWt.)

Absolute 

Incremental 

Weight 

(Lbs.)

Per Unit 

Incremental 

Weight 

(Lbs./

UnitWt.)

Introduction 

Year

Horsepower 

Change %

Unit Body Construction 4.4 90.00 0.00 0 -6 1980 0

Mass Reduction I 1.1 0.00 0.06 0 -1.5 2005 0

Mass Reduction II 2.9 0.00 0.13 0 -7.5 2009 0

Mass Reduction III 5.9 0.00 0.37 0 -10 2011 0

Mass Reduction IV 9.2 0.00 0.56 0 -15 2016 0

Mass Reduction V 12.8 0.00 0.65 0 -20 2020 0

Aerodynamics I 2.6 43.35 0.00 0 0.5 2000 0

Aerodynamics II 5.4 182.96 0.00 0 1 2011 0

6 Speed Manual 2.2 230.03 0.00 20 0 1995 0

Aggressive Shift Logic I 2.5 29.20 0.00 0 0 1999 0

Aggressive Shift Logic II 6.9 24.46 0.00 0 0 2017 0

Early Torque Converter Lockup 0.6 26.54 0.00 0 0 2002 0

High Efficiency Gearbox 1.8 180.56 0.00 0 0 2017 0

5 Speed Automatic 1.5 93.52 0.00 20 0 1995 0

6 Speed Automatic 2.2 243.05 0.00 30 0 2003 0

7 Speed Automatic 5.5 360.93 0.00 40 0 2009 0

8 Speed Automatic 8.8 479.55 0.00 50 0 2014 0

Dual Clutch Automated Manual 5.4 164.02 0.00 -10 0 2004 0

CVT 8.6 225.88 0.00 -25 0 1998 0

Low Friction Lubricants 0.8 2.88 0.00 0 0 2003 0

Engine Friction Reduction I-4 cyl 2.2 42.44 0.00 0 0 2000 1.25

Engine Friction Reduction I-6 cyl 2.9 64.02 0.00 0 0 2000 1.25

Engine Friction Reduction I-8 cyl 2.8 84.89 0.00 0 0 2000 1.25

Engine Friction Reduction II-4 cyl 4.0 90.64 0.00 0 0 2017 2.25

Engine Friction Reduction II-6 cyl 5.2 133.08 0.00 0 0 2017 2.25

Engine Friction Reduction II-8 cyl 4.8 175.53 0.00 0 0 2017 2.25

Cylinder Deactivation-6 cyl 7.0 168.36 0.00 10 0 2004 0

Cylinder Deactivation-8 cyl 6.6 188.97 0.00 10 0 2004 0

VVT I-OHV Intake Cam Phasing-6 cyl 2.9 39.51 0.00 20 0 2051 1.25

VVT I-OHV Intake Cam Phasing-8 cyl 2.8 39.51 0.00 30 0 2051 1.25

VVT I-OHC Intake Cam Phasing-4 cyl 2.3 39.51 0.00 10 0 1993 1.25

VVT I-OHC Intake Cam Phasing-6 cyl 2.9 79.88 0.00 20 0 1993 1.25

VVT I-OHC Intake Cam Phasing-8 cyl 2.8 79.88 0.00 30 0 1993 1.25

VVT II-OHV Coupled Cam Phasing-6 cyl 5.9 39.51 0.00 20 0 2009 1.25

VVT II-OHV Coupled Cam Phasing-8 cyl 5.6 39.51 0.00 30 0 2009 1.25

VVT II-OHC Coupled Cam Phasing-4 cyl 4.7 39.51 0.00 10 0 2009 1.25

VVT II-OHC Coupled Cam Phasing-6 cyl 5.9 79.88 0.00 20 0 2009 1.25

VVT II-OHC Coupled Cam Phasing-8 cyl 5.6 79.88 0.00 30 0 2009 1.25

VVT III-OHV Dual Cam Phasing-6 cyl 5.9 89.33 0.00 25 0 2051 1.56

VVT III-OHV Dual Cam Phasing-8 cyl 5.6 89.33 0.00 37.5 0 2051 1.56

VVT III-OHC Dual Cam Phasing-4 cyl 4.7 81.60 0.00 12.5 0 2009 1.56

VVT III-OHC Dual Cam Phasing-6 cyl 5.9 176.09 0.00 25 0 2009 1.56

VVT III-OHC Dual Cam Phasing-8 cyl 5.6 176.09 0.00 37.5 0 2009 1.56

VVL I-OHV Discrete-6 cyl 6.1 202.72 0.00 40 0 2000 2.5

VVL I-OHV Discrete-8 cyl 5.7 290.33 0.00 50 0 2000 2.5

VVL I-OHC Discrete-4 cyl 4.6 140.01 0.00 25 0 2000 2.5

VVL I-OHC Discrete-6 cyl 6.1 202.72 0.00 40 0 2000 2.5

VVL I-OHC Discrete-8 cyl 5.7 290.33 0.00 50 0 2000 2.5

VVL II-OHV Continuous-6 cyl 7.7 1035.06 0.00 40 0 2011 2.5

VVL II-OHV Continuous-8 cyl 7.2 1131.26 0.00 50 0 2011 2.5

VVL II-OHC Continuous-4 cyl 5.8 209.59 0.00 25 0 2011 2.5

VVL II-OHC Continuous-6 cyl 7.7 384.82 0.00 40 0 2011 2.5

VVL II-OHC Continuous-8 cyl 7.2 420.04 0.00 50 0 2011 2.5

Stoichiometric GDI-4 cyl 1.7 237.93 0.00 20 0 2006 2.5

Stoichiometric GDI-6 cyl 1.7 358.19 0.00 30 0 2006 2.5

Stoichiometric GDI-8 cyl 1.7 430.34 0.00 40 0 2006 2.5

OHV to DOHC TBDS-I4 23.8 1245.51 0.00 -100 0 2009 3.75

OHV to DOHC TBDS I-V6 22.2 1887.16 0.00 -100 0 2009 3.75

SOHC to DOHC TBDS I-I4 23.8 744.73 0.00 -100 0 2009 3.75

SOHC to DOHC TBDS I-V6 22.2 1445.22 0.00 -100 0 2009 3.75

DOHC TBDS I-I3 19.3 823.75 0.00 -100 0 2009 3.75

DOHC TBDS I-I4 23.8 672.57 0.00 -100 0 2009 3.75

DOHC TBDS I-V6 22.2 1377.79 0.00 -100 0 2009 3.75
94 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Transportation Demand Module

Table 7.15. High technology matrix for light trucks (cont.)

Fuel 

Efficiency 

Change %

Incremental 

Cost $2000

Incremental 

Cost ($/

UnitWt.)

Absolute 

Incremental 

Weight 

(Lbs.)

Per Unit 

Incremental 

Weight 

(Lbs./

UnitWt.)

Introduction 

Year

Horsepower 

Change %

OHV to DOHC TBDS II-I4 28.9 1427.73 0.00 -100 0 2012 3.75

OHV to DOHC TBDS II-V6 27.0 2200.80 0.00 -100 0 2012 3.75

SOHC to DOHC TBDS II-I4 28.9 941.53 0.00 -100 0 2012 3.75

SOHC to DOHC TBDS II-V6 27.0 1771.73 0.00 -100 0 2012 3.75

DOHC TBDS II-I3 23.3 1017.42 0.00 -100 0 2012 3.75

DOHC TBDS II-I4 28.9 871.48 0.00 -100 0 2012 3.75

DOHC TBDS II-V6 27.0 1706.27 0.00 -100 0 2012 3.75

OHV to DOHC TBDS III-I4 (from V6) 35.9 1828.65 0.00 -100 0 2017 3.75

OHV to DOHC TBDS III-I4 (from V8) 33.8 1441.63 0.00 -200 0 2017 3.75

SOHC to DOHC TBDS III-I4 (from V6) 35.9 1409.25 0.00 -100 0 2017 3.75

SOHC to DOHC TBDS III-I4 (from V8) 33.8 1242.36 0.00 -200 0 2017 3.75

DOHC TBDS III-I3 (from I4) 29.8 1471.12 0.00 -100 0 2017 3.75

DOHC TBDS III-I4 (from V6) 35.9 1348.83 0.00 -100 0 2017 3.75

DOHC TBDS III-I4 (from V8) 33.8 1171.86 0.00 -200 0 2017 3.75

Electric Power Steering 1.1 96.44 0.00 0 0 2004 0

Improved Accessories I 0.8 78.74 0.00 0 0 2005 0

12V Micro Hybrid w/EPS and IACC 7.4 628.01 0.00 45 0 2005 0

Improved Accessories II 2.6 115.82 0.00 0 0 2012 0

Mild Hybrid w/EPS and IACC II 11.7 2611.80 0.00 80 0 2012 -2.5

Tires I 2.2 5.04 0.00 -12 0 2005 0

Tires II 4.4 52.51 0.00 -15 0 2017 0

Low Drag Brakes 0.9 53.23 0.00 0 0 2000 0

Secondary Axle Disconnect 1.5 86.70 0.00 0 -1 2012 0

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). National 

Highway Traffic Safety Administration, Corporate Average Fuel Economy for MY 2011-2015 Passenger Cars and Light Trucks (April 2008). U.S. Environmental 

Protection Agency, Interim Report: New Powertrain Technologies and Their Projected Costs (October 2005).

Environmental Protection Agency and Department of Transportation National Highway Traffic Safety Administration, “2017 and Later Model Year Light-Duty 

Vehicle Greenhouse Gas Emissions and Corporate Average Fuel Economy Standards; Final Rule,” Federal Register Vol. 77, No. 199, October 15, 2012. 40 CFR 

Parts 85, 86, 600, 49 CFR Parts 523, 531, 533, et al. and 600.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 95

Transportation Demand Module

Table 7.16. High technology matrix for freight trucks

Technology Type

Vehicle 

Category

Capital 

Costs

(2009$)

Incremental Fuel 

Economy 

Improvement 

(%)

Aerodynamics I: streamlined bumper, grill, windshield, roof 1 53 2.0 

Aerodynamics I: conventional features; general aerodynamic shape, removal of classic non-aerodynamic features 5, 8, 11 900 4.5 

Aerodynamics I 7,10, 13 900 5.1 

Aerodynamics II: SmartWay features; streamlined shape, bumper grill, hood, mirrors, side fuel tank and roof fairings, 

side gap extenders 5, 8 997 2.0 

Aerodynamics II 7,10 997 4.0 

Aerodynamics II 11 1040 5.0 

Aerodynamics II 13 1355 5.0 

Aerodynamics III: underbody airflow, down exhaust, lowered ride height 7 1552 5.0

Aerodynamics III 13 1803 7.0

Aerodynamics IV: skirts, boat tails, nose cone, vortex stabilizer, pneumatic blowing 5-13 4950 14.0

Tires I: low rolling resistance 1 6 2.0

Tires I 2,3 110 3.0

Tires I 4 131 2.2

Tires I 5-7 114 2.2

Tires I 8-13 172 2.2

Tires II: super singles 5-13 140 6.2

Tires III: single wide tires on trailer 5-13 720 3.4

Weight Reduction I 1 116 1.8

Weight Reduction I: aluminum dual tires or super singles 5-13 580 1.1

Weight Reduction II: weight reduction 15% 3-13 5580 3.3

Weight Reduction III: weight reduction 20% 3-13 9900 3.9

Accessories I: Electric/electrohydraulic improvements; electric power steering or electrohydraulic power steering 1 105 2.0

Accessories II: Improved accessories; electrified water, oil, fuel injection, power steering pump, aircompressor 1 85 2.0

Accessories III: Auxiliary Power Unit 11-13 4834 6.4

Transmission I: 8-speed Automatic from 6-speed automatic 1 248 1.9

Transmission II: 6-Manual from 4-speed automatic 1 135 1.1

Transmission III: Automated Manual Transmission 2-13 4500 3.9

Diesel Engine I: aftertreatment improvements 1 109 5.0

Diesel Engine I 2 109 4.0

Diesel Engine II: low friction lubricants 1-13 3 1.0

Diesel Engine III: variable valve actuation 2 0 1.1

Diesel Engine III 3-13 270 1.1

Diesel Engine IV: engine friction reduction, low tension piston rings, roller cam followers, piston skirt design, 

improved crankshaft design and bearings; coating 1-2 111 2.0

Diesel Engine IV: engine friction reduction, improved bearings to allow lower viscosity oil 3-13 225 2.0

Diesel Engine V: improved turbo efficiency 2-13 15 2.0

Diesel Engine VI: improved water, oil, fuel pump; pistons; valve train friction reduction 2 192 2.0

Diesel Engine VI 3, 5-7 167 2.0 

Diesel Engine VI: improved water, oil, fuel pump; pistons 4, 8-13 135 2.0

Diesel Engine VII: improved cylinder head, fuel rail and injector, EGR cooler 2 36 7.0

Diesel Engine VII 3-13 26 7.0

Diesel Engine VIII: turbo mechanical compounding 5-13 900 5.0

Diesel Engine IX: low temperature EGR, improved turbochargers 1 166 6.0

Diesel Engine X: sequential downsizing/turbocharging 5-13 1080 2.8

Diesel Engine XI: waste heat recovery, Organic Ranking Cycle (bottoming cycle) 3-13 9000 8.8

Diesel Engine XII: electric turbo compounding 4-13 7200 10.0

Gasoline Engine I: low friction lubricants 1-13 3 0.6

Gasoline Engine II: coupled cam phasing 2-4 43 4.0

Gasoline Engine III: engine friction reduction; low tension piston rings, roller cam followers, piston skirt design, 

improved crankshaft design and bearings; coating 1 111 3.0

Gasoline III 2 104 3.0

Gasoline III 3-4 86 3.0

Gasoline Engine IV: stoichiometric gasoline direct injection V8 1-2 425 2.0

Gasoline Engine IV 3-4 430 2.0

Gasoline Engine V: turbocharging and downsizing SGDI V8 to V6 1-4 1569 2.2

Gasoline Engine VI: lean burn GDI 1-4 675 14.0

Gasoline Engine VII: HCCI 1-4 617 14.0

Hybrid System I: 42V engine off at idle 1-2 1350 7.7

Hybrid System I 3-4 1350 5.0

Hybrid System II: dual mode hybrid 1-2 10800 27.5

Hybrid System II: electric, ePTO, or hydraulic 3-4 24000 33.0

Hybrid System II: 4 kWh battery, 50 kW motor generator 5-13 24000 6.0

Source: Greenhouse Gas Emissions Standards and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and Vehicles, U.S. Environmental Protection Agency and U.S. Department of Transportation, 

Final Rules, Federal Register, Vol. 76, No. 179, (September 2011). Final Rulemaking to Establish Greenhouse Gas Emissions Standards and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and 

Vehicles, Regulatory Impact Analysis, U.S. Environmental Protection Agency and U.S. Department of Transportation, (August 2011). Reducing Heavy-Duty Long Haul Combination Truck Fuel Consumption and 

CO2 Emissions, Final Report, TIAX, LLC. (October 2009). Update of Technology Information for Forecasting Heavy-Duty On-Road Vehicle Fuel Economy, Final Report, ICF International, Prepared for the U.S. 

Energy Information Administration, (August 2010). Technologies and Approaches to Reducing the Fuel Consumption of Medium- and Heavy-Duty Vehicles, National Research Council of the National Academy 

of Sciences, (2010).
96 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Transportation Demand Module

Table 7.17. High technology matrix for air travel

Technology Introduction Year Fractional Efficiency Improvement Jet Fuel Trigger Price (1987$ per gallon)

Technology #1 2008 0.03 1.34

Technology #2 2014 0.07 1.34

Technology #3 2020 0.11 1.34

Technology #4 2025 0.15 1.34

Technology #5 2018 0.22 1.34

Technology #6 2018 0.10 1.34

Technology #7 2025 0.04 1.00

Technology #8 2020 0.05 1.34

Source: Jet Information Services, 2009 World Jet Inventory, data tables (2009). Energy Information Administration, Transportation Sector Model of the 

National Energy Modeling System, Model Documentation 2010, DOE/EIA-M070(2010), (Washington, DC, 2010).
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 97

Transportation Demand Module

Notes and sources

[1] U.S. Department of Transportation, National Highway Traffic and Safety Administration, “Summary of Fuel Economy 

Performance”, (Washington, DC, December 2009). 

[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,” Stacy Davis and Lorena Truett, final report 

prepared for the Department of Energy, Energy Information Administration, Office of Energy Analysis, (Oak Ridge, Tn, 

January 2003). 

[4] Bobit Publishing Company, The Fleet Fact Book, various issues (Redondo Beach, 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: 30th Edition (Oak Ridge, TN, 2011). 

[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] U.S. Energy Information Administration, Archive - Alternative Transportation Fuels (ATF) and Alternative Fueled 

Vehicles (AFV), http://www.eia.gov/renewable/afv/archive/index.cfm.

[15] U.S. Energy Information Administration, State Energy Data System 2009.

[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, ECO2TV, (Washington, DC, 

December 2004).

[19] Greenhouse Gas Emissions Standards and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and

Vehicles, U.S. Environmental Protection Agency and U.S. Department of Transportation, Final Rules, Federal Register, Vol.

76, No. 179, (September 2011).

[20] U.S. Department of Commerce, Bureau of the Census, “Vehicle Inventory and U.S. Survey,” ECO2TV (Washington, 

DC, December 2009).

[21] Decision Analysis Corporation of Virginia, op. cit. Note 19. 

[22] Reebie Associates, op. cit., Note 17.

[23] Oak Ridge National Laboratory, Op. cit. Note 9.

[24] 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). 

[25] U.S. Energy Information Administration, op. cit., Note 15.
98 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Transportation Demand Module

Notes and sources

[26] U.S. Army Corps of Engineers, Waterborne Commerce of the United States, (Waterborne Statistics Center: New

Orleans, LA, 1993).

[27] U.S. Energy Information Administration, op. cit., Note 15. 

[28] U.S. Department of Transportation, Research and Innovative Technology Administration, Bureau of Transportation 

Statistics, Air Carrier Summary Data (Form 41, Schedules T-1 and T-2), (2011). http://www.transtats.bts.gov/DataIndex. 

asp; link: Air Carrier Summary Data (Form 41 and 298C Summary Data). 

[29] U.S. Department of Transportation, Research and Innovative Technology Administration, Bureau of Transportation

Statistics, op. cit., Note 28. 

[30] U.S. Department of Transportation, Federal Aviation Administration, Airport Capacity Benchmark Report, 2004 

(2004).

[31] Jet Information Services Inc., World Jet Inventory: Year-End 2009, (December 2009). 

[32] Greenhouse Gas Emissions Standards and Fuel Efficiency Standards for Medium- and Heavy-Duty Engines and

Vehicles, U.S. Environmental Protection Agency and U.S. Department of Transportation, Final Rules, Federal Register, Vol.

76, No. 179, (September 2011).

[33] Energy Information Administration, op. cit. Note 14. 

[34] Energy and Environmental Analysis, Inc., “Documentation of Technologies Included in the NEMS Fuel Economy 

Model for Passenger Cars and Light Trucks,” Prepared for the U.S. Energy Information Administration, (Arlington, VA, 

September 30, 2002). 

[35] Final Rulemaking to Establish Greenhouse Gas Emissions Standards and Fuel Efficiency Standards for Mediumand Heavy-Duty Engines and Vehicles, Regulatory Impact Analysis, U.S. Environmental Protection Agency and U.S. 

Department of Transportation, (August 2011). 

[36] Reducing Heavy-Duty Long Haul Combination Truck Fuel Consumption and CO2 Emissions, Final Report, TIAX, LLC. 

(October 2009).

[37] Update of Technology Information for Forecasting Heavy-Duty On-Road Vehicle Fuel Economy, Final Report, ICF 

International, Prepared for the U.S. Energy Information Administration, (August 2010).

[38] Technologies and Approaches to Reducing the Fuel Consumption of Medium- and Heavy-Duty Vehicles, National

Research Council of the National Academy of Sciences, (2010).
Electricity Market Module
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U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 101

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, electricity load and demand, 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 

2013, DOE/EIA-M068(2013).

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 side cases are also described.

EMM regions 

The supply regions used in EMM are based on the North American Electric Reliability Corporation regions and subregions 

shown in Figure 6.

Figure 6. Electricity Market Model Supply Regions
102 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Electricity Market Module

Model parameters and assumptions 

Generating capacity types 

The capacity types represented in the EMM are shown in Table 8.1.

Table 8.1. Generating capacity types represented in the Electricity Market Module

Capacity Type

Existing coal steam plants1

High Sulfur Pulverized Coal with Wet Flue Gas Desulfurization

Advanced Coal - Integrated Coal Gasification Combined Cycle

Pulverized 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 - Fluidized Bed

Solar Thermal - Central Tower

Solar Photovoltaic - Fixed Tilt

Wind

Wind Offshore

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 and carbon.

Source: U.S. Energy Information Administration.

New generating plant characteristics 

The cost and performance characteristics of new generating technologies are inputs to the electricity capacity planning 

submodule (Table 8.2). 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 new fossil-fueled technologies are 

assumed to decline linearly through 2025.

For the AEO2013, EIA commissioned an external consultant to update current cost estimates for utility-scale electric generating 

plants [1]. This report used a consistent methodology, similar to the one used to develop the estimates for AEO2011 and 

AEO2012, but accounted for more recent data and experience. A cost adjustment factor, based on the producer price index for 

metals and metal products, allows the overnight costs to fall in the future if this index drops, or rise further if it increases.

The overnight costs shown in Table 8.2 represent the estimated cost of building a plant in a typical region of the country. 

Differences in plant costs due to regional distinctions are calculated by applying regional multipliers. Regional multipliers by 

technology are also based on regional cost estimates developed by the consultant. The regional variations account for multiple 

factors, such as differences in terrain, weather, population, and labor wages. 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.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 103

Electricity Market Module

Table 8.2. Cost and performance characteristics of new central station electricity generating technologies

Technology

Online

Year1

Size

(mW)

Lead 

time

(years)

Base 

Overnight 

Cost in 

2012

(2011 $/

kW)

Contingency Factors Total 

Overnight

Cost in 

20124

(2011 $/

kW)

Variable

O&M5

(2011 $/

mWh)

Fixed

O&M

(2011$/

kW)

Heatrate6

in 2012

(Btu/

kWh)

nth-of-akind

Heatrate

(Btu/

kWh)

Project 

Contingency

Factor2

Technological

Optimism

Factor3

Scrubbed Coal 

New7 2016 1300 4 2,694 1.07 1.00 2,883 4.39 30.64 8,800 8,740 

Integrated CoalGasification Comb 

Cycle (IGCC)7 2016 1200 4 3,475 1.07 1.00 3,718 7.09 50.49 8,700 7,450 

Pulverized Coal with 

Carbon sequestion 2017 650 4 4,662 1.07 1.03 5,138 4.37 65.31 12,000 9,316

Conv Gas/Oil Comb 

Cycle 2015 620 3 858 1.05 1.00 901 3.54 12.94 7,050 6,800 

Adv Gas/Oil Comb 

Cycle (CC) 2015 400 3 931 1.08 1.00 1,006 3.21 15.10 6,430 6,333 

Adv CC with carbon 

sequestration 2017 340 3 1,833 1.08 1.04 2,059 6.66 31.23 7,525 7,493 

Conv Comb 

Turbine8 2014 85 2 910 1.05 1.00 956 15.18 7.21 10,850 10,450 

Adv Comb Turbine 2014 210 2 632 1.05 1.00 664 10.19 6.92 9,750 8,550 

Fuel Cells 2015 10 3 6,045 1.05 1.10 6,982 0.00 357.47 9,500 6,960 

Adv Nuclear 2018 2236 6 4,700 1.10 1.05 5,429 2.10 91.65 10,452 10,452

Distributed 

Generation - Base 2015 2 3 1,395 1.05 1.00 1,465 7.62 17.14 9,038 8,900 

Distributed 

Generation - Peak 2015 1 2 1,675 1.05 1.00 1,759 7.62 17.14 10,042 9,880 

Biomass 2016 50 4 3,685 1.07 1.02 4,041 5.17 103.79 13,500 13,500 

Geothermal7,9 2013 50 4 2,444 1.05 1.00 2,567 0.00 110.94 9,756 9,756

MSW - Landfill Gas 2013 50 3 7,858 1.07 1.00 8,408 8.51 381.74 13,648 13,648

Conventional 

Hydropower9 2016 500 4 2,179 1.10 1.00 2,397 2.60 14.57 9,756 9,756

Wind 2013 100 3 2,032 1.07 1.00 2,175 0.00 38.86 9,756 9,756

Wind Offshore 2016 400 4 4,452 1.10 1.25 6,121 0.00 72.71 9,756 9,756

Solar Thermal7 2015 100 3 4,653 1.07 1.00 4,979 0.00 66.09 9,756 9,756

Photovoltaic7,10 2014 150 2 3,624 1.05 1.00 3,805 0.00 21.37 9,756 9,756 1

Online year represents the first year that a new unit could be completed, given an order date of 2012. For wind, geothermal and landfill gas, the online 

year was moved earlier to acknowledge the significant market activity already occurring in anticipation of the expiration of the Production Tax Credit.

2

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; 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.

4 Overnight capital cost including contingency factors, excluding regional multipliers and learning effects. Interest charges are also excluded. These 

represent costs of new projects initiated in 2012. 

5

O&M = Operations and maintenance.

6

For hydro, wind, solar and geothermal technologies, the heatrate shown represents the average heatrate for conventional thermal generation as of 

2011.  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.

7

Capital costs are shown before investment tax credits are applied. 

8

Combustion turbine units can be built by the model prior to 2014 if necessary to meet a given region’s reserve margin. 

9

Because 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.

10Costs and capacities are expressed in terms of net AC power available to the grid for the installed capacity. 

Sources: For the AEO2013, EIA updated cost estimates for utility-scale electric generating plants, based on a draft report provided by external consultants. 

The final report can be found at www.eia.gov/forecasts/capitalcost/. Site specific costs for geothermal were provided by the National Energy Renewable 

Laboratory, “Updated U.S. Geothermal Supply Curve”, February 2010.
104 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Electricity Market Module

Table 8.3. Learning parameters for new generating technology components

Technology Component

Period 1

Learning Rate 

(LR1)

Period 2

Learning 

Rate(LR2)

Period 3

Learning 

Rate (LR3)

Period 1

Doublings

Period 2

Doublings

Minimum Total

Learning by 2035

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 20% 10% 1% 3 5 20%

Advanced Nuclear 5% 3% 1% 3 5 10%

Fuel prep - Biomass - 10% 1% - 5 10%

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% - - 5%

Wind Offshore 20% 10% 1% 3 5 20%

Solar Thermal 20% 10% 1% 3 5 10%

Solar PV - Module - 10% 1% - 5 10%

Balance of Plant - Solar PV - 10% 1% - 5 10% 1

HRSG = Heat Recovery Steam Generator

Note: Please see the text for a description of the methodology for learning in the Electricity Market Module.

Source: U.S. Energy Information Administration, Office of Electricity, Coal, Nuclear and Renewables Analysis.

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 8.3). 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.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 105

Electricity Market Module

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 (LR) is an exogenous parameter input for each component 

(Table 8.3). The progress ratio and LR are related by: 

pr = 2-b = (1 - LR) 

The parameter “b” is calculated from the second equality above (b =-(ln(1-LR)/ln(2)). The parameter “a” is computed from 

initial conditions, i.e. 

a =OC(C0)/CO

-b

where C0 is the initial cumulative capacity. Once the rates of learning (LR) and the cumulative capacity (C0) are known for each 

interval, the parameters (a and b) can be computed. Three learning steps were developed to reflect different stages of learning 

as a new design is introduced into 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. Costs of all design components 

are adjusted to reflect 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 rates by component are 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 8.4). 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. In the 

case of the solar PV technology, it is assumed that the module component accounts for 50 percent of the cost, and that the 

balance of system components accounts for the remaining 50 percent. Because the amount of end-use PV capacity (existing 

and projected) is significant relative to total solar PV capacity, and because the technology of the module component is 

common across the end-use and electric power sectors, the calculation of the learning factor for the PV module component also 

takes into account capacity built in the residential and commercial sectors.

Table 8.5 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. Components that do not contribute to the capacity of the plant, such as the balance of plant category, 

receive 100 percent capacity credit for any capacity built with that component. For example, when calculating capacity for 

the “Balance of plant - CC” component, all combined cycle capacity would be counted 100 percent, both conventional and 

advanced.

Table 8.4. Component cost weights for new technologies

Technology

Pulverized 

Coal

Combustion

Turbineconventional

Combustion

Turbineadvanced HRSG Gasifier

Carbon

Capture/

Sequestration

Balance

of PlantIGCC

Balance 

of

PlantTurbine

Balance 

of

PlantCombined

Cycle

Fuel Prep

Biomass

Integrated

Coal-Gasification 

Comb Cycle (IGCC) 0% 0% 15% 20% 41% 0% 24% 0% 0% 0%

Pulverized Coal with 

carbon sequestration 70% 0% 0% 0% 0% 30% 0% 0% 0% 0%

Conv Gas/Oil Comb 

Cycle 0% 30% 0% 40% 0% 0% 0% 0% 30% 0%

Adv Gas/Oil Comb 

Cycle (CC) 0% 0% 30% 40% 0% 0% 0% 0% 30% 0%

Adv CC with carbon 

sequestration 0% 0% 20% 25% 0% 40% 0% 0% 15% 0%

Conv Comb Turbine 0% 50% 0% 0% 0% 0% 0% 50% 0% 0%

Adv Comb Turbine 0% 0% 50% 0% 0% 0% 0% 50% 0% 0%

Biomass 50% 0% 0% 0% 0% 0% 0% 0% 0% 50%

Note: All unlisted technologies have a 100 percent 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.
106 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Electricity Market Module

Table 8.5. Component capacity weights for new technologies

Technology

Pulverized 

Coal

Combustion

Turbineconventional

Combustion

Turbineadvanced HRSG Gasifier

Carbon

Capture/

Sequestration

Balance

of PlantIGCC

Balance 

of PlantTurbine

Balance of

PlantCombined

Cycle

Fuel 

Prep

Biomass

Integrated

Coal-Gasification 

Comb Cycle (IGCC) 0% 0% 67% 33% 100% 0% 100% 0% 0% 0%

Pulverized Coal with 

Carbon sequestration 100% 0% 0% 0% 0% 100% 0% 0% 0% 0%

Conv Gas/Oil Comb 

Cycle 0% 67% 0% 33% 0% 0% 0% 0% 100% 0%

Adv Gas/Oil Comb 

Cycle (CC) 0% 0% 67% 33% 0% 0% 0% 0% 100% 0%

Adv CC with carbon 

sequestration 0% 0% 67% 33% 0% 100% 0% 0% 100% 0%

Conv Comb Turbine 0% 100% 0% 0% 0% 0% 0% 100% 0% 0%

Adv Comb Turbine 0% 0% 100% 0% 0% 0% 0% 100% 0% 0%

Biomass 50% 0% 0% 0% 0% 0% 0% 0% 0% 100%

HRSG = Heat Recovery Steam Generator.

Source: U.S. Energy Information Administration, Office of Electricity, Coal, Nuclear and Renewables Analysis.

Distributed generation 

Distributed generation is modeled in the end-use sectors (as described in the appropriate chapters) as well as in the EMM. 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 8.2 for costs and performance assumptions. It is 

assumed that these plants reduce the costs of transmission upgrades that would otherwise be needed. 

Demand storage 

The electricity model includes the option to build a new demand storage technology to simulate load shifting, through programs 

such as smart meters. This is modeled as a new technology build, but with operating characteristics similar to pumped storage. The 

technology is able to decrease the load in peak slices, but must generate to replace that demand in other time slices. There is an 

input factor that identifies the amount of replacement generation needed, where a factor of less than 1.0 can be used to represent 

peak shaving rather than purely shifting the load to other time periods. This plant type is limited to operating only in the peak load 

slices, and for AEO2013, it is assumed that this capacity is limited to 3.5 percent of peak demand on average in 2040, with limits 

varying from 2.2 percent to 6.8 percent of peak across the regions.

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 Corporation 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 49 percent and 50 percent, respectively. The seasons were defined to account for seasonal variation in supply 

availability.

Reserve margins—the percentage of capacity required in excess of peak demand needed for unforeseeable outages—are determined 

within the model through an iterative approach comparing the marginal cost of capacity and the cost of unserved energy. The target 

reserve margin is adjusted for each model cycle until the two costs converge. The resulting reserve margins from the AEO2013

Reference case range from 8 to 21 percent.

Fossil fuel-fired and nuclear steam plant retirement 

Fossil-fired steam plant retirements and nuclear retirements are calculated endogenously within the model. Generating units 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 plant generators. A generating unit is assumed to
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 107

Electricity Market Module

retire if the expected revenues from the generator are not sufficient to cover the annual going-forward costs and 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 unit-specific and based on historical data. The 

average capital additions for existing plants are $8 per kilowatt (kW) for oil and gas steam plants, $17 per kW for coal plants 

and $22 per kW for nuclear plants (in 2011 dollars). These costs are added to the estimated costs at existing plants regardless 

of their age. Beyond 30 years of age an additional $7 per kW capital charge for fossil plants, and $33 per kW charge for nuclear 

plants is included in the retirement decision to reflect further investment to address the impacts of aging. Age-related cost 

increases are attributed to capital expenditures for major repairs or retrofits, decreases in plant performance, and/or increases in 

maintenance costs to mitigate the effects of aging.

EIA assumes all retirements reported as planned during the next ten years on the Form EIA-860 will occur. Additionally, 

the AEO2013 nuclear projection assumes an additional 6.5 gigawatts of nuclear capacity retirements by 2040 based on the 

uncertainty related to resolving issues associated with long-term operations and aging management.

Biomass co-firing 

Coal-fired power plants are assumed to co-fire with biomass fuel if it is economical. Co-firing requires a capital investment for 

boiler modifications and fuel handling. This expenditure is assumed to be $280 per kW of biomass capacity. 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.

Nuclear uprates 

The AEO2013 nuclear power projection 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 modification, 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. AEO2013

assumes that all of those uprates reported to EIA as planned modifications on the Form EIA-860 will take place, representing 1.5 

gigawatts of additional capacity. EIA also assumes an additional 6.5 gigawatts of nuclear power uprates will be completed over 

the projection period, based on interactions with industry stakeholders and the NRC. Table 8.6 provides a summary of projected 

uprate capacity additions by region.

Table 8.6. Nuclear uprates by EMM region

gigawatts

Texas Reliability Entity 0.25

Florida Reliability Coordinating Council 1.12

Midwest Reliability Council - East 0.00

Midwest Reliability Council - West 0.55

Northeast Power Coordinating Council/New England 0.25

Northeast Power Coordinating Council/NYC-Westchester 0.00

Northeast Power Coordinating Council/Long Island 0.00

Northeast Power Coordinating Council/Upstate 0.50

ReliabilityFirst Corporation/East 0.82

ReliabilityFirst Corporation/Michigan 0.25

ReliabilityFirst Corporation/West 0.99

SERC Reliability Corporation/Delta 0.43

SERC Reliability Corporation/Gateway 0.00

SERC Reliability Corporation/Southeastern 0.25

SERC Reliability Corporation/Central 0.75

SERC Reliability Corporation/Virginia-Carolina 1.06

Southwest Power Pool/North 0.00

Southwest Power Pool/South 0.00

Western Electricity Coordinating Council/Southwest 0.25

Western Electricity Coordinating Council/California 0.55

Western Electricity Coordinating Council/Northwest Power Pool Area 0.00

Western Electricity Coordinating Council/Rockies 0.00

Total 8.02

Source: U.S. Energy Information Administration, Office of Electricity, Coal, Nuclear and Renewables Analysis, based on Nuclear Regulatory 

Commission survey www.nrc.gov/reactors/operating/licensing/power-updates.html.
108 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Electricity Market Module

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 North American 

Electric Reliability Corporation and Western Electricity 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 2007 and information provided in the 2012 Summer and Winter Assessments. They are locked in for the term of 

the contract. Contracts that are scheduled to expire by 2016 are assumed not to be renewed. Because there is no information 

available about expiration dates for contracts that go beyond 2016, they are assumed to be phased out by 2025. The EMM 

includes an option to add interregional transmission capacity. In some cases it may be more economic to build generating 

capacity in a neighboring region, but additional costs to expand the transmission grid will be incurred as well. Explicitly expanding 

the interregional transmission capacity may also make the transmission line available for additional economy trade.

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 assumed to exchange power. 

International electricity trade 

Two components of international firm power trade are represented in the EMM—existing and planned transactions, and 

unplanned transactions. Data on existing and planned transactions are obtained from the North American Electric Reliability 

Corporation’s Electricity Supply and Demand Database 2007. 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

Electricity pricing is projected for 22 electricity market regions in AEO2013 for fully competitive, partially competitive and 

fully regulated supply regions. The price of electricity to the consumer comprises 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 to build, operate and maintain these systems. In competitive 

regions, an algorithm 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 competitive generation price includes the marginal cost (fuel 

and variable operations and maintenance costs), taxes, and a reliability price adjustment, which represents what customers 

are willing to pay for added capacity to avoid outages in periods of high demand. For the AEO2013, the difference between EIA’s 

reliability costs and the historical Independent System Operator capacity, ancillary service, and uplift charges was added to 

the competitive generation price. The price of electricity in the regions with a competitive generation market consists of the 

competitive cost of generation summed with the average costs of transmission and distribution. The price for mixed regions 

reflects a load-weighted average of the competitive price and the regulated price, based on the percent of electricity load in the 

region subject to deregulation. In competitively supplied regions, a transition period is assumed to occur (usually over a ten-year 

period) from the effective date of restructuring, with a gradual shift to marginal cost pricing.

The Reference case assumes a transition to full competitive pricing in the three New York regions and in the ReliabilityFirst

Corporation/ East region, and a 97-percent transition to competitive pricing in New England (Vermont being the only fullyregulated state in that region). Six regions fully regulate their electricity supply, including the Florida Reliability Coordinating 

Council, three of the SERC Reliability Corporation subregions - Southeastern (SRSE), Central (SRCE) and Virginia-Carolina (SRVC) 

- Southwest Power Pool Regional Entity/North (SPNO), and the Western Electricity Coordinating Council / Rockies (RMPA). The 

Texas Reliability Entity, which in the past was considered fully competitive by 2010, is now only 88-percent competitive, since 

many cooperatives have declined to become competitive or allow competitive energy to be sold to their customers. California 

returned to almost fully regulated pricing in 2002, after beginning a transition to competition in 1998, with only 7 percent 

competitive supply sold currently in the Western Electricity Coordinating Council (WECC)/ California region. All other regions 

reflect a mix of both competitive and regulated prices.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 109

Electricity Market Module

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 in the state. 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 AEO2013, 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. Additional costs not included in historical data sets have been added in adjustment factors to 

the transmission and distribution operations and maintenance costs, which impact the cost of both competitive and regulated 

electricity supply. Since most of these costs, such as transition costs, are temporary in nature, they are gradually phased out 

throughout the projection. Regions found to have these added costs include the Northeast Power Coordinating Council/ New 

England and New York regions, the ReliabilityFirst Corporation/ East and West regions, and the WECC/ California region.

Fuel price expectations 

Capacity planning decisions in the EMM are based on a life cycle cost analysis over a 30-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.

Nuclear fuel prices 

Nuclear fuel prices are calculated through an offline analysis which determines the delivered price to generators in mills per 

kilowatthour. To produce reactor grade uranium, the uranium (U308) must first be mined, and then sent through a conversion 

process to prepare for enrichment. The enrichment process takes the fuel to a given purity of U-235, typically 3-5 percent for 

commercial reactors in the United States. Finally, the fabrication process prepares the enriched uranium for use in a specific type 

of reactor core. The price of each of the processes is determined, and the prices are summed to get the final price of the delivered 

fuel. The one mill per kilowatthour charge that is assessed on nuclear generation to go to the DOE’s Nuclear Waste Fund is also 

included in the final nuclear price. The analysis uses forecasts from Energy Resources International for the underlying uranium 

prices.

Legislation and regulations

Clean Air Act Amendments of 1990 (CAAA90) and Clean Air Interstate Rule (CAIR) 

Currently, regulation of SO2 and NOX emissions is administered under the Clean Air Interstate Rule (CAIR), and the AEO2013

assumes that CAIR remains a binding regulation throughout the projection period. CAIR was initially promulgated in 2005, but 

has been challenged in court several times. The Cross-State Air Pollution Rule (CSAPR) was released by EPA in July 2011 and 

was intended to replace CAIR, but it was vacated by the U.S. Court of Appeals for the District of Columbia Circuit, and CAIR was 

reinstated. 
110 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Electricity Market Module

CAIR covers all fossil fueled power plants greater than 25 megawatts in 27 states and the District of Columbia. There are annual 

emissions caps for SO2 and NOX and different states fall under each cap, as shown in the map in Figure 7, although all are in the 

eastern half of the United States. The caps for SO2 and NOX were set to allow states to achieve their National Ambient Air Quality 

Standards (NAAQS) for particulate matter (impacted by SO2 levels) and ground level ozone (impacted by NOX). Allowances can 

be traded amongst all participants in the CAAA90 Title IV program, not just those in CAIR states, however allowances are traded 

at a discount in non-CAIR states. AEO2013 represents emissions trading in both the CAIR and non-CAIR regions, as specified by 

the regulation, and includes banking of allowances consistent with CAIR’s provisions.

As specified in the CAAA90, EPA 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 the Phase II limits. The EPA did not impose limits on existing oil and gas plants, but some states have 

instituted additional NOx regulations. All new fossil units are required to meet current 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.

Sample 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 100, 300, 500, and 700-megawatt coal plants. In the 

EMM, plant-specific costs are calculated based on the size of the unit and other operating characteristics. FGD units are assumed 

to remove 95 percent of the SO2, while SCR units are assumed to remove 90 percent of the NOx. The EMM also includes an 

option to install a dry sorbent injection (DSI) system, which is assumed to remove 70 percent of the SO2. However, the DSI option 

is only available under the mercury and air toxics rule discussed in the next section, as its primary benefit is for reducing hydrogen 

chloride (HCl). The costs per megawatt of capacity decline with plant size and are shown in Table 8.7.

Figure 7. States covered by the Clean Air Interstate Rule

Source: U.S. Environmental Protection Agency, Clean Air Interstate Rule—Where You Live (Washington, DC, July 31, 2012), 

website http://www.epa.gov/cair/where.html.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 111

Electricity Market Module

Table 8.7. Coal plant retrofit costs

2011 dollars

Coal Plant Size (MW) FGD Capital Costs ($/kW) SCR Capital Costs ($/kW) DSI Capital Costs ($/kW)

100 695 280 128

300 538 213 58

500 454 191 41

700 395 179 32

Documentation for EPA Base Case v4.10 using the Integrated Planning Model, August 2010, EPA Contract EP-W-08-018.

Mercury regulation

The Mercury and Air Toxics Standards (MATS) were finalized in December 2011 to fulfill EPA’s requirement to regulate 

mercury emissions from power plants. MATS also regulates other hazardous air pollutants (HAPS) such as hydrogen chloride 

(HCl) and fine particulate matter (PM2.5). MATS applies to coal- and oil-fired power plants with a nameplate capacity greater 

than 25 megawatts. The standards are scheduled to take effect in 2015, but allow for a one year waiver to comply, and require 

that all qualifying units achieve the maximum achievable control technology (MACT) for each of the three covered pollutants. 

For AEO2013, EIA assumes that all coal-fired generating units with a capacity greater than 25 megawatts will comply with the 

rule beginning in 2016, due to the large number of plants requesting the one year extension. All power plants are required to 

reduce their mercury emissions to 90 percent below their uncontrolled emissions levels.

Because the EMM does not explicitly model HCl or PM2.5, specific control technologies are assumed to be used to achieve 

compliance. In order to meet the HCl requirement, units must have either flue gas desulfurization (FGD) scrubbers or dry 

sorbent injection (DSI) systems in order to continue operating. A full fabric filter is also required to meet the PM2.5 limits and 

to improve the effectiveness of the DSI technology. When plants alter their configuration by adding equipment such as an SCR 

to remove NOx or an SO2 scrubber, removal of mercury is often a resulting cobenefit. The EMM considers all combinations 

of controls and may choose to add NOX or SO2 controls purely to lower mercury if it is economic to do so. Plants 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 

$6 (2011 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 $153 (2011 dollars) 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 cold side electrostatic precipitator (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 hot side electrostatic precipitator (HSE) or other particulate control, and a supplemental fabric filter with 

activated carbon injection: 

• Hg Removal (%) = 100 - (43.068 / (ACI + 0.421)) 

ACI = activated carbon injection rate in pounds per million actual cubic feet of flue gas. 
112 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Electricity Market Module

Power plant mercury emissions assumptions 

The EMM 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 8.8 provides the assumed EMFs for existing coal plant 

configurations without mercury-specific controls.

Table 8.8. Mercury emission modification factors

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 0.50 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

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. 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.

Planned SO2 Scrubber and NOx control equipment additions

EIA assumes that all planned retrofits, as reported on the Form EIA-860, will occur as currently scheduled. For AEO2013, this 

includes 17.7 gigawatts of planned SO2 scrubbers (Table 8.9) and 9.5 gigawatts of planned selective catalytic reduction (SCR).

Carbon capture and sequestration retrofits 

Although a Federal greenhouse gas program is not assumed in the AEO2013 Reference case, the EMM includes the option of 

retrofitting existing coal plants for carbon capture and sequestration (CCS). This option is important when considering alternate 

scenarios that do constrain carbon emissions. The modeling structure for CCS retrofits within the EMM was developed by the 

National Energy Technology Laboratory[4] and uses a generic model of retrofit costs as a function of basic plant characteristics 

(such as heatrate). The costs have been adjusted to be consistent with costs of new CCS technologies. The CCS retrofits are 

assumed to remove 90 percent of the carbon input. The addition of the CCS equipment results in a capacity derate of around 30 

percent and reduced efficiency of 43 percent at the existing coal plant. The costs depend on the size and efficiency of the plant, with 

the capital costs ranging from $1,250 to $1,650 per kilowatt. It was assumed that only plants greater than 500 megawatts and with 

heat rates below 12,000 BTU per kilowatthour would be considered for CCS retrofits.

State Air Emissions Regulation

AEO2013 continues to model the Northeast Regional Greenhouse Gas Initiative (RGGI), which applies to fossil-fuel powered plants 

over 25 megawatts in the Northeastern United States. The State of New Jersey withdrew from the program at the end of 2011, 

leaving nine states in the accord. The rule caps CO2 emissions from covered electricity generating facilities and requires that they 

account for each ton of CO2 emitted with an allowance purchased at auction. Because the baseline and projected emissions were 

calculated before the economic recession that began in 2008, the actual emissions in the first years of the program have been less 

than the cap, leading to excess allowances and allowance prices at the floor price.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 113

Electricity Market Module

The California Assembly Bill 32 (AB 32), the Global Warming Solutions Act of 2006, authorized the California Air Resources Board 

(CARB) to set California’s GHG reduction goals for 2020 and establish a comprehensive, multi-year program to reduce GHG 

emissions in California. As one of the major initiatives for AB 32, CARB designed a cap-and-trade program that started on January 

1, 2012, with the enforceable compliance obligations beginning in 2013 for the electric power sector and industrial facilities. Fuel 

providers must comply starting in 2015. The AB32 cap-and-trade provisions are incorporated in AEO2013 through an emission 

constraint in the EMM that also accounts for the emissions determined by the other sectors. An allowance price is calculated and 

added to fuel prices for the affected sectors. Limited banking and borrowing of allowances as well as an allowance reserve and 

offsets have been modeled, as specified in the Bill, providing some compliance flexibility and cost containment.

Table 8.9. Planned SO2 scrubber additions by EMM region

gigawatts

Texas Reliability Entity 0.0

Florida Reliability Coordinating Council 0.0

Midwest Reliability Council - East 0.0

Midwest Reliability Council - West 1.2

Northeast Power Coordinating Council/New England 0.5

Northeast Power Coordinating Council/NYC-Westchester 0.0

Northeast Power Coordinating Council/Long Island 0.0

Northeast Power Coordinating Council/Upstate 1.0

ReliabilityFirst Corporation/East 0.0

ReliabilityFirst Corporation/Michigan 1.4

ReliabilityFirst Corporation/West 6.1

SERC Reliability Corporation/Delta 0.0

SERC Reliability Corporation/Gateway 3.0

SERC Reliability Corporation/Southeastern 2.5

SERC Reliability Corporation/Central 0.2

SERC Reliability Corporation/Virginia-Carolina 0.0

Southwest Power Pool/North 1.4

Southwest Power Pool/South 0.0

Western Electricity Coordinating Council/Southwest 0.4

Western Electricity Coordinating Council/California 0.0

Western Electricity Coordinating Council/Northwest Power Pool Area 0.0

Western Electricity Coordinating Council/Rockies 0.0

Total 17.7

Source: U.S. Energy Information Administration, Form EIA-860, “Annual Electric Generator Report.”

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 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. 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).

Energy Improvement and Extension Act 2008 (EIEA2008) 

EIEA2008 extended the investment tax credit of 30 percent through 2016 for solar and fuel cell facilities.

American Recovery and Reinvestment Act (ARRA) 

Updated tax credits for Renewables 

ARRA extended the expiration date for the PTC to January 1, 2013, for wind and January 1, 2014, for all other eligible renewable 

resources. In addition, ARRA allows companies to choose an investment tax credit (ITC) of 30 percent in lieu of the PTC and allows 

for a grant in lieu of this credit to be funded by the U.S. Treasury. For some technologies, such as wind, the full PTC would appear to 

be more valuable than the 30 percent ITC; however, the difference can be small. Qualitative factors, such as the lack of partners with 

sufficient tax liability, may cause companies to favor the ITC grant option. AEO2013 generally assumes that renewable electricity 

projects will claim the more favorable tax credit or grant option available to them.
114 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Electricity Market Module

Loan guarantees for renewables

ARRA provided $6 billion to pay the cost of guarantees for loans authorized by the Energy Policy Act of 2005. While most 

renewable projects which started construction prior to September 30, 2011 are potentially eligible for these loan guarantees, the 

application and approval of guarantees for specific projects is a highly discretionary process, and has thus far been limited. While 

AEO2013 includes projects that have received loan guarantees under this authority, it does not assume automatic award of the loans 

to potentially eligible technologies. 

Support for CCS

ARRA provided $3.4 billion for additional research and development on fossil energy technologies. A portion of this funding is 

expected to be used to fund projects under the Clean Coal Power Initiative program, focusing on projects that capture and sequester 

greenhouse gases. To reflect the impact of this provision, AEO2013 Reference case assumes that an additional 1 gigawatt of coal 

capacity with CCS will be stimulated by 2018.

Smart grid expenditures 

ARRA provides $4.5 billion for smart grid demonstration projects. While somewhat difficult to define, smart grid technologies 

generally include a wide array of measurement, communications, and control equipment employed throughout the transmission 

and distribution system that will enable real-time monitoring of the production, flow, and use of power from the generator to the 

consumer. Among other things, these smart grid technologies are expected to enable more efficient use of the transmission and 

distribution grid, lower line losses, facilitate greater use of renewables, and provide information to utilities and their customers that 

will lead to greater investment in energy efficiency and reduced peak load demands. The funds provided will not fund a widespread 

implementation of smart grid technologies, but could stimulate more rapid investment than would otherwise occur.

Several changes were made throughout the NEMS to represent the impacts of the smart grid funding provided in ARRA. In the 

electricity module, it was assumed that line losses would fall slightly, peak loads would fall as customers shifted their usage 

patterns, and customers would be more responsive to pricing signals. Historically, line losses, expressed as the percentage of 

electricity lost, have been falling for many years as utilities make investments to replace aging or failing equipment.

Smart grid technologies also have the potential to reduce peak demand through the increased deployment of demand response 

programs. In AEO2013, it is assumed that the Federal expenditures on smart grid technologies will stimulate efforts that reduce 

peak demand from what they otherwise would be, with the amount of total peak load reduction growing from 2.2 percent initially 

to 3.5 percent by 2040, although the shifts vary by region. Load is shifted to offpeak hours, so net energy consumed remains largely 

constant.

FERC Orders 888 and 889

FERC 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 SameTime Information System (OASIS) through which utilities and non-utilities can receive information regarding the transmission 

system. As a result, utilities have functionally or physically unbundled 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 such transactions economical. 

Electricity alternative cases 

Nuclear Alternative cases

For AEO2013, three alternate cases were run for nuclear power plants to address uncertainties about the operating lives of existing 

reactors, the potential for new nuclear capacity, and capacity uprates at existing plants. These scenarios are discussed in the Issues 

in Focus article, “Nuclear Power in AEO2013” in the full AEO2013 report.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 115

Electricity Market Module

• The Low Nuclear case assumes that all existing reactors will not receive a second license renewal and are retired within 60 

years of operation. The reported retirement at Oyster Creek occurs as currently planned, at the end of 2019. Kewaunee is also 

retired in this case, at the end of 2014, based on an announcement by Dominion Resources in late 2012. Additionally, two units 

that are currently out of service are assumed to be permanently shut down in the Low Nuclear case. San Onofre 2 and Crystal 

River 3 are not currently operating, but are assumed to be returned to service in 2015 in the Reference case. In the Low Nuclear 

Case both units are assumed to retire in 2013. In the Reference case, existing plants are assumed to run as long as they continue 

to be economic, implicitly assuming that a second 20-year license renewal will be obtained for most plants reaching 60 years 

of age before 2040. The Low Nuclear case was run to analyze the impact of additional nuclear retirements, which could occur 

if the oldest plants do not receive a second license extension. In this case, 45 gigawatts of nuclear capacity are assumed to 

be retired by 2040. This case assumes that no new nuclear capacity will be added throughout the projection, excluding the 

capacity already planned and under construction. The case also assumes that only those capacity uprates reported to EIA will be 

completed. In contrast, the Reference case assumes additional uprates based on Nuclear Regulatory Commission (NRC) surveys 

and industry reports.

• The High Nuclear case assumes that all existing nuclear units will receive a second license renewal and operate beyond 60 years 

(excluding one announced retirement). In the Reference case, beyond the announced retirement of Oyster Creek, an additional 

6.5 gigawatts of nuclear capacity is assumed to be retired through 2040, reflecting uncertainty surrounding future aging impacts 

and/or costs. This case was run to provide a more optimistic outlook where all licenses are renewed and all plants are assumed 

to find it economic to continue operating beyond 60 years. The High Nuclear case also assumes additional planned nuclear 

capacity is completed based on combined license (COL) applications with the NRC. The Reference case assumes 5.5 gigawatts 

of planned capacity are added, while the High Nuclear case includes 13.3 gigawatts of planned capacity additions.

• The Small Modular Reactor case assumes that new advanced nuclear plants built in the forecast will be based on a smaller 

modular design rather than the larger AP1000 design used in the Reference case. The overnight costs are assumed to be the 

same as in the Reference case, but the construction lead time is reduced from six years to three years for the smaller design. The 

fixed operating and maintenance costs are assumed to be higher for the smaller design. To account for the necessary time for 

design certification, the first available online date for the small reactors is assumed to be 2025.
116 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Electricity Market Module

Notes and sources

[1] Review of Power Plant Cost and Performance Assumptions for NEMS, Science Applications International Corporation, 

April 2013. The costs shown Table 8.2 and used for the AEO2013 were based on a draft report provided in September 

2012 and may vary slightly from the published final report.

[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.

[4] Retrofitting Coal-Fired Power Plants for Carbon Dioxide Capture and Sequestration - Exploratory Testing of NEMS for

Integrated Assessments, DOE/NETL-2008/1309, P.A. Geisbrecht, January 18, 2009.
Oil and Gas Supply Module
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U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 119

Oil and Gas Supply Module

The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze crude oil and 

natural gas exploration and development on a regional basis (Figure 8). The OGSM is organized into 4 submodules: Onshore 

Lower 48 Oil and Gas Supply Submodule, Offshore Oil and Gas Supply Submodule, Oil Shale Supply Submodule[1], and Alaska 

Oil and Gas Supply Submodule. 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(2011), (Washington, DC, 2011). 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.

Figure 8. Oil and Gas Supply Model regions

Source: U.S. Energy Information Administration, Office of Energy Analysis.

Rocky Mountain - 5

Rocky Mountains

West Coast

Midcontinent

Northeast

Gulf Coast

Southwest

Atlantic

Shallow Gulf of Mexico

Deep Gulf of Mexico
120 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Oil and Gas Supply Module

OGSM encompasses domestic crude oil and natural gas supply by several recovery techniques and sources. Crude oil recovery 

includes improved oil recovery processes such as water fl ooding, infi ll drilling, and horizontal drilling, as well as enhanced oil 

recovery processes such as CO2 fl ooding, steam fl ooding, and polymer fl ooding. Recovery from highly fractured, continuous 

zones (e.g. Austin chalk and Bakken shale formations) is also included. Natural gas supply includes resources from lowpermeability tight sand formations, shale formations, coalbed methane, and other sources.

Key assumptions

Domestic oil and natural gas technically recoverable resources

The outlook for domestic crude oil production is highly dependent on upon the production profi le of individual wells over time, 

the cost of drilling and operating those wells, and the revenues generated by those wells. Every year EIA re-estimates initial 

production (IP) rates and production decline curves, which determine estimated ultimate recovery (EUR) per well and total 

technically recoverable resources (TRR) [2]. 

A common measure of the long-term viability of U.S. domestic crude oil and natural gas as an energy source is the remaining 

technically recoverable resource that consist of proved reserves [3] and unproved resources [4]. Estimates of TRR are highly 

uncertain, particularly in emerging plays where few wells have been drilled. Early estimates tend to vary and shift signifi cantly 

over time as new geological information is gained through additional drilling, as long-term productivity is clarifi ed for existing 

wells, and as the productivity of new wells increases with technology improvements and better management practices. TRR 

estimates used by EIA for each AEO are based on the latest available well production data and on information from other Federal

and State governmental agencies, industry, and academia. Published estimates in Tables 9.1 and 9.2 refl ect the removal of 

intervening reserve additions and production between the date of the latest available assessment and January 1, 2011.

Table 9.1. Technically recoverable U.S. crude oil resources as of January 1, 2011

billion barrels

Proved Reserves Unproved Resources

Total Technically 

Recoverable Resources

Lower 48 Onshore 17 125 142

 Northeast 03 3

 Gulf Coast 2 27 29

 Midcontinent 2 15 16

 Southwest 6 32 38

 Rocky Mountain 4 25 30

 West Coast 3 24 26

Lower 48 Off shore 5 49 54

 Gulf (currently available) 4 37 41

 Eastern/Central Gulf (unavailable until 2022) 04 4

 Pacifi c 17 7

 Atlantic 01 1

Alaska (Onshore and Off shore) 4 34 38

Total U.S. 25 208 233

Note: Crude oil resources include lease condensates but do not include natural gas plant liquids or kerogen (oil shale). Resources in areas 

where drilling is offi cially prohibited are not included in this table. The estimate of 7.3 billion barrels of crude oil resources in the Northern

Atlantic, Northern and Central Pacifi c, and within a 50-mile buff er off the Mid and Southern Atlantic OCS is also excluded from the 

technically recoverable volumes because leasing is not expected in these areas by 2040.

Source: Onshore, State Off shore, and Alaska - U.S. Geological Survey (USGS); Federal (Outer Continental Shelf) Off shore - Bureau of Ocean 

Energy Management (formerly the Minerals Management Service); Proved Reserves - U.S. Energy Information Administration. Table values 

refl ect removal of intervening reserve additions between the date of the latest available assessment and January 1, 2011.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 121

Oil and Gas Supply Module

Table 9.2. Technically recoverable U.S. natural gas resources as of January 1, 2011

trillion cubic feet

Proved 

Reserves

Unproved 

Resources

Total Technically 

Recoverable 

Resources

Lower 48 Onshore Non Associated Natural Gas 261 1,321 1,582

 Tight Gas 81 435 517

 Northeast 3 34 37

 Gulf Coast 18 181 199

 Midcontinent 5 22 27

 Southwest 3 12 15

 Rocky Mountain 52 179 232

 West Coast 0 8 8

 Shale Gas 94 543 637

 Northeast 16 239 255

 Gulf Coast 25 143 168

 Midcontinent 22 53 75

 Southwest 31 58 89

 Rocky Mountain 0 38 38

 West Coast -- 12 12

 Coalbed Methane 17 121 139

 Northeast 2 4 6

 Gulf Coast 1 2 3

 Midcontinent 1 38 39

 Southwest 1 6 6

 Rocky Mountain 13 60 73

 West Coast -- 10 10

 Other 68 222 289

 Northeast 10 29 39

 Gulf Coast 14 105 119

 Midcontinent 22 23 45

 Southwest 12 24 36

 Rocky Mountain 9 27 36

 West Coast 0 13 13

Lower 48 Onshore Associated-Dissolved Gas 21 179 200

 Northeast 0 2 2

 Gulf Coast 2 43 45

 Midcontinent 2 13 15

 Southwest 10 48 57

 Rocky Mountain 5 50 55

 West Coast 2 23 25

Lower 48 Offshore 14 258 272

 Gulf (currently available) 13 214 227

 Eastern/Central Gulf (unavailable until 2022) -- 21 21

 Pacific 1 10 11

 Atlantic -- 12 12

Alaska (Onshore and Offshore) 9 273 282

Total U.S. 305 2,031 2,335

Note: Resources in other areas where drilling is officially prohibited are not included. The estimate of 32.9 trillion cubic feet of natural gas 

resources in the Northern Atlantic, Northern and Central Pacific, and within a 50-mile buffer off the Mid and Southern Atlantic OCS is also 

excluded from the technically recoverable volumes because leasing is not expected in these areas by 2040. 

Source: Onshore, State Offshore, and Alaska - U.S. Geological Survey (USGS) with adjustments to tight gas, shale gas, and coalbed methane

resources; Federal (Outer Continental Shelf) Offshore - Bureau of Ocean Energy Management (formerly the Minerals Management 

Service); Proved Reserves - U.S. Energy Information Administration. Table values reflect removal of intervening reserve additions between 

the date of the latest available assessment and January 1, 2011
122 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Oil and Gas Supply Module

The remaining unproved TRR for a continuous-type shale gas or tight oil area is the product of (1) land area, (2) well spacing (wells 

per square mile), (3) percentage of area untested, (4) percentage of area with potential, and (5) EUR per well. The play-level 

unproved technically recoverable resource assumptions for tight oil, shale gas, tight gas, and coalbed methane are summarized 

in Tables 9.3-9.4. The model uses a distribution of EUR per well in each play and often in sub-play areas. Table 9.5 provides an 

example of the distribution of EUR per well for each of the Bakken areas. The Bakken is subdivided into three areas: Montana, 

North Dakota Core, and North Dakota Extension. The North Dakota Core represents the portion that is considered to be the 

“sweet spot” and has the highest well production rates, while the “Extension” area refers to the bulk of North Dakota that has less 

productive wells. Because of the significant variation in well productivity within an area, the wells in each Bakken area are further 

delineated into three well productivity categories: top 15%, middle 70%, and bottom 15%. This level of detail is provided for select 

plays in Appendix 2.C of the AEO2013 Documentation for the OGSM. The USGS periodically publishes tight and shale resource 

assessments that are used as a guide for selection of key parameters in the calculation of the TRR used in the AEO. The USGS 

seeks to assess the recoverability of shale gas and tight oil based on the wells drilled and technologies deployed at the time of the 

assessment. 

The AEO TRRs incorporate current drilling, completion, and recovery techniques, requiring adjustments to the USGS estimates, as 

well as the inclusion of shale gas and tight oil resources not yet assessed by USGS. When USGS assessments and underlying data 

become publicly available, the USGS assumptions for land area, well spacing, and percentage of area with potential typically are 

used by EIA to develop the AEO TRR estimates. EIA may revise the well spacing assumptions in future AEOs to reflect evolving 

drilling practices. If well production data are available, EIA analyzes the decline curve of producing wells to calculate the expected 

EUR per well from future drilling.

The underlying resource for the Reference case is uncertain particularly as exploration and development of tight oil continues to 

move into areas with little to no production history. Many wells drilled in tight or shale formations using the latest technologies 

have less than two years of production history so the impact of recent technological advancement on the estimate of future 

recovery cannot be fully ascertained. Uncertainty also extends to areal extent of formations and the number of layers that could be 

drilled within formations. Two alternative resource cases are discussed at the end of this chapter. 

Lower 48 onshore

The Onshore Lower 48 Oil and Gas Supply Submodule (OLOGSS) is a play-level model used to analyze crude oil and natural 

gas supply from onshore lower 48 sources. The methodology includes a comprehensive assessment method for determining 

the relative economics of various prospects based on financial considerations, the nature of the resource, and the available 

technologies. The general methodology relies on a detailed economic analysis of potential projects in known fields, enhanced oil 

recovery projects, and undiscovered resources. The projects which are economically viable are developed subject to the availability 

of resource development constraints which simulate the existing and expected infrastructure of the oil and gas industries. For 

crude oil projects, advanced secondary or improved oil recovery techniques (e.g. infill drilling and horizontal drilling) and enhanced 

oil recovery (e.g. CO2 flooding, steam flooding, and polymer flooding) processes are explicitly represented. For natural gas projects, 

the OLOGSS represents supply from shale formations, tight sands formations, coalbed methane, and other sources.

The OLOGSS evaluates the economics of future crude oil and natural gas exploration and development from the perspective of 

an operator making an investment decision. An important aspect of the economic calculation concerns the tax treatment. Tax 

provisions vary with the type of producer (major, large independent, or small independent). For AEO2013, the economics of 

potential projects reflect the tax treatment provided by current laws for large independent producers. Relevant tax provisions are 

assumed unchanged over the life of the investment. Costs are assumed constant over the investment life but vary across region, 

fuel, and process type. Operating losses incurred in the initial investment period are carried forward and used against revenues 

generated by the project in later years.

Technology advances, including improved drilling and completion practices, as well as advanced production and processing 

operations, are explicitly modeled to determine the direct impacts on supply, reserves, and various economic parameters. The 

success of the technology program is measured by estimating the probability that the technology development program will be 

successfully completed. It reflects the pace at which technology performance improves and the probability that the technology 

project will meet the program goals. There are four possible curves which represent the adoption of the technology: convex, 

concave, sigmoid/logistic and linear. The convex curve corresponds to rapid initial market penetration followed by slow market 

penetration. The concave curve corresponds to slow initial market penetration followed by rapid market penetration. The sigmoid/

logistic curve represents a slow initial adoption rate followed by rapid increase in adoption and then slow adoption again as the 

market becomes saturated. The linear curve represents a constant rate of market penetration, and may be used when no other 

predictions can be made.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 123

Oil and Gas Supply Module

Table 9.3. U.S. unproved technically recoverable tight/shale oil and gas resources by play (as of January 1, 2011)

Average EUR TRR

Region Basin Play

Area 

(mi2)

Well Spacing 

(wells/mi2)

% of Area 

Untested1

% of 

Area with 

Potential2

Crude Oil 

(MMbls/well)

Natural Gas 

(Bcf/well)

Crude Oil 

(MMbls)

Natural Gas 

(Bcf)

Tight/Shale Oil

1-Northeast Appalachian Utica Oil-Core 3,400 2.6 100.0% 80.0% 0.086 0.086 599 599

1-Northeast Appalachian Utica Oil-Extension 19,492 2.6 100.0% 20.0% 0.034 0.034 339 339

2-Gulf Coast Western Gulf Austin Chalk-Giddings 4,685 8.0 99.1% 52.9% 0.084 0.108 1,644 2,114

2-Gulf Coast Western Gulf Austin Chalk-Outlying 14,079 7.7 99.1% 52.8% 0.101 0.312 5,755 17,741

2-Gulf Coast Western Gulf Eagle Ford-Oil 5,046 5.4 90.9% 81.4% 0.258 0.293 5,177 5,876

3-Midcontinent Anadarko Cana Woodford-Oil 3,957 5.1 100.0% 85.5% 0.024 0.170 414 2,915

4-Southwest Permian Bone Spring 2,332 4.0 96.2% 88.0% 0.253 0.234 1,999 1,844

4-Southwest Permian Spraberry 1,091 6.4 99.9% 67.8% 0.278 0.650 1,310 3,065

4-Southwest Permian Wolfcamp 9,270 4.0 99.1% 34.5% 0.153 0.201 1,941 2,549

5-Rocky Mounttain Denver Niobrara 7,724 5.0 100.0% 97.2% 0.012 0.073 440 2,728

5-Rocky Mounttain Greater Green River All Plays 1,361 5.8 100.0% 100.0% 0.112 0.015 888 116

5-Rocky Mounttain Montana Thrust Belt All Plays 2,400 2.3 100.0% 100.0% 0.111 0.075 602 410

5-Rocky Mounttain Paradox Fractured Interbed 2,771 1.6 100.0% 42.3% 0.543 0.434 1,001 801

5-Rocky Mounttain Powder River All Plays 19,684 3.0 100.0% 100.0% 0.035 0.040 2,062 2,364

5-Rocky Mounttain Southwestern Wyoming All Plays 1,661 5.8 100.0% 100.0% 0.111 0.015 1,084 142

5-Rocky Mounttain Uinta-Piceance All Plays 85 16.0 100.0% 100.0% 0.050 0.111 68 152

5-Rocky Mounttain Williston Bakken MT 15,790 3.9 97% 27.3% 0.093 0.064 1,519 1,049

5-Rocky Mounttain Williston Bakken ND Core 4,012 2.0 75.8% 85.0% 0.372 0.132 1,925 681

5-Rocky Mounttain Williston Bakken ND Extension 26,080 2.0 91.5% 45.5% 0.211 0.244 4,593 5,308

6-West Coast San Joaquin/Los Angeles Monterey/Santos 1,770 16.0 100.0% 97.3% 0.497 0.553 13,709 15,244

Tight/Shale Oil Total 47,067 66,037

Shale Gas

1-Northeast Appalachian Devonian Big Sandy 10,669 6.0 82.3% 20.0% 0.000 0.498 -- 5,231

1-Northeast Appalachian Devonian Greater Siltstone Area 22,914 6.0 95.5% 20.0% 0.000 0.330 -- 8,620

1-Northeast Appalachian Devonian Low Thermal Maturity 45,844 6.0 98.7% 10.0% 0.000 0.500 -- 13,545

1-Northeast Appalachian Marcellus Foldbelt 19,064 4.3 100.0% 4.6% 0.000 0.205 -- 774

1-Northeast Appalachian Marcellus Interior 45,161 4.3 98.2% 37.0% 0.013 2.065 898 145,645

1-Northeast Appalachian Marcellus Western 39,843 5.5 99.5% 7.2% 0.000 0.127 -- 1,991

1-Northeast Appalachian Utica Gas 49,725 4.3 100.0% 51.8% 0.000 0.339 -- 37,257

1-Northeast Cincinatti Arch Northwestern Ohio 6,000 4.0 100.0% 50.0% 0.000 0.220 -- 2,641

1-Northeast Illinois New Albany 1,600 8.0 99.0% 50.0% 0.000 1.722 -- 10,909

1-Northeast Michigan Antrim 12,000 8.0 91.2% 60.0% 0.000 0.240 -- 12,586

2-Gulf Coast Black Warrior Floyd-Neal/Conasauga 2,429 2.0 100.0% 65.0% 0.000 1.559 -- 4,922

2-Gulf Coast Louisiana-Mississippi Salt Haynesville/Bossier 9,320 6.2 94.4% 32.7% 0.001 4.160 16 74,661

2-Gulf Coast Western Gulf Pearsall 1,420 6.0 99.9% 85.0% 0.000 1.200 -- 8,652

2-Gulf Coast Western Gulf Eagle Ford-Dry Gas 2,200 6.0 99.4% 45.0% 0.087 1.946 514 11,456

2-Gulf Coast Western Gulf Eagle Ford-Wet Gas 5,400 6.0 99.5% 80.0% 0.196 1.695 5,046 43,583

3-Midcontinent Anadarko Cana Woodford-Dry 1,720 4.0 98.0% 52.8% 0.019 2.492 66 8,870

3-Midcontinent Anadarko Cana Woodford-Wet 1,590 4.0 97.5% 66.7% 0.291 2.488 1,204 10,297

3-Midcontinent Arkoma Caney 2,890 4.0 99.9% 29.1% 0.000 0.337 -- 1,132

3-Midcontinent Arkoma Fayetteville-Central 3,451 8.0 85.0% 21.9% 0.000 2.155 -- 11,075

3-Midcontinent Arkoma Fayetteville-West 2,402 8.0 99.7% 25.4% 0.000 0.928 -- 4,517

3-Midcontinent Arkoma Woodford 3,000 8.0 94.2% 23.2% 0.011 2.868 60 15,043

3-Midcontinent Black Warrior Chattanooga 696 8.0 100.0% 29.4% 0.000 0.990 -- 1,620

4-Southwest Fort Worth Barnett 9,895 8.0 50.0% 46.9% 0.011 1.588 211 29,454

4-Southwest Permian Barnett-Woodford 2,691 4.0 99.8% 95.0% 0.000 2.769 -- 28,259

5-Rocky Mountain Greater Green River Hillard-Baxter-Mancos 17,911 8.0 99.9% 25.0% 0.000 0.372 -- 13,302

5-Rocky Mountain San Juan Lewis 1,557 3.0 99.9% 95.0% 0.000 2.202 -- 9,778

5-Rocky Mountain Uinta-Piceance lMancos 3,880 8.0 99.7% 40.0% 0.000 0.903 -- 11,288

5-Rocky Mountain Williston Gammon 4,207 2.0 100.0% 91.2% 0.000 0.455 -- 3,491

6-West Coast Columbia Basin Central 1,245 8.0 100.0% 87.7% 0.000 1.400 -- 12,220

Shale Gas Total 8,085 542,821

Tight Gas

1-Northeast Appalachian Clinton Medina 42,054 10.4 9.3% 63.9% 0.000 0.059 -- 12,421

1-Northeast Appalachian Tuscarora 42,495 8.0 100.0% 0.6% 0.000 0.686 -- 1,399

1-Northeast Appalachian Upper Devonian High 12,775 10.0 57.8% 67.1% 0.000 0.212 -- 10,514

1-Northeast Appalachian Upper Devonian Moderate/Low 29,808 10.0 81.5% 37.0% 0.000 0.061 -- 5,510

1-Northeast Michigan Berea Sandstone 51,863 8.0 98.2% 18.0% 0.000 0.011 33 799

2-Gulf Coast Louisiana-Mississippi Salt Cotton Valley/Bossier 14,794 12.1 90.2% 29.4% 0.016 2.892 755 136,843

2-Gulf Coast Western Gulf Olmos 8,233 4.0 91.6% 56.3% 0.020 1.923 347 32,652

2-Gulf Coast Western Gulf Vicksburg 3,667 8.0 91.6% 10.7% 0.030 1.474 88 4,238

2-Gulf Coast Western Gulf Wilcox Lobo 2,982 8.0 72.0% 41.2% 0.006 1.022 42 7,232
124 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Oil and Gas Supply Module

Table 9.3. U.S. unproved technically recoverable tight/shale oil and gas resources by play (as of January 1, 2011) (cont.)

Average EUR TRR

Region Basin Play

Area 

(mi2)

Well Spacing 

(wells/mi2)

% of Area 

Untested1

% of 

Area with 

Potential2

Crude Oil 

(MMbls/well)

Natural Gas 

(Bcf/well)

Crude Oil 

(MMbls)

Natural 

Gas 

(Bcf)

Tight Gas

1-Northeast Appalachian Clinton Medina 42,054 10.4 9.3% 63.9% 0.000 0.059 -- 12,421

1-Northeast Appalachian Tuscarora 42,495 8.0 100.0% 0.6% 0.000 0.686 -- 1,399

1-Northeast Appalachian Upper Devonian High 12,775 10.0 57.8% 67.1% 0.000 0.212 -- 10,514

1-Northeast Appalachian Upper Devonian Moderate/Low 29,808 10.0 81.5% 37.0% 0.000 0.061 -- 5,510

1-Northeast Michigan Berea Sandstone 51,863 8.0 98.2% 18.0% 0.000 0.011 33 799

2-Gulf Coast Louisiana-Mississippi Salt Cotton Valley/Bossier 14,794 12.1 90.2% 29.4% 0.016 2.892 755 136,843

2-Gulf Coast Western Gulf Olmos 8,233 4.0 91.6% 56.3% 0.020 1.923 347 32,652

2-Gulf Coast Western Gulf Vicksburg 3,667 8.0 91.6% 10.7% 0.030 1.474 88 4,238

2-Gulf Coast Western Gulf Wilcox Lobo 2,982 8.0 72.0% 41.2% 0.006 1.022 42 7,232

3-Midcontinent Anadarko Cherokee/Redfork 1,978 4.0 72.5% 29.9% 0.009 0.920 16 1,577

3-Midcontinent Anadarko Cleveland 2,562 4.0 97.1% 45.1% 0.043 0.892 192 4,003

3-Midcontinent Anadarko Granite Wash/Atoka 7,790 4.0 96.1% 28.2% 0.075 1.679 635 14,182

3-Midcontinent Arkoma Arkoma 1,000 8.0 69.3% 32.2% 0.000 1.297 -- 2,317

4-Southwest Permian Abo 1,578 8.0 56.9% 78.9% 0.037 0.713 400 4,038

4-Southwest Permian Canyon 9,602 8.0 60.3% 75.2% 0.007 0.228 368 7,938

5-Rocky Mountain Denver Denver/jules 4,500 16.0 87.8% 86.1% 0.000 0.244 -- 13,254

5-Rocky Mountain North Central Montana High Potential 2,000 4.0 77.0% 88.9% 0.000 0.612 -- 3,350

5-Rocky Mountain North Central Montana Low Potential 3,000 4.0 99.3% 74.7% 0.000 0.212 -- 1,889

5-Rocky Mountain North Central Montana Moderate Potential 2,000 4.0 97.5% 79.3% 0.000 0.335 -- 2,075

5-Rocky Mountain Piceance

South Basin Williams Fork/

Mesaverde 272 32.0 98.6% 83.7% 0.000 1.091 -- 7,849

5-Rocky Mountain San Juan Dakota 3,918 8.0 74.9% 99.1% 0.002 0.300 41 6,980

5-Rocky Mountain San Juan Mesaverde 3,689 8.0 71.2% 47.4% 0.003 0.345 26 3,432

5-Rocky Mountain San Juan Pictured Cliffs 3,958 4.0 67.8% 0.7% 0.000 0.203 -- 15

5-Rocky Mountain Southwestern Wyoming Deep Mesaverde 16,416 4.0 99.8% 10.9% 0.000 0.414 -- 2,955

5-Rocky Mountain Southwestern Wyoming Fort Union/Fox Hills 3,858 8.0 99.9% 4.9% 0.000 0.702 -- 1,060

5-Rocky Mountain Southwestern Wyoming Frontier (Deep) 16,619 4.0 100.0% 6.7% 0.000 2.581 -- 10,803

5-Rocky Mountain Southwestern Wyoming Frontier Moxa Arch 2,334 8.0 84.2% 15.5% 0.000 1.198 -- 2,920

5-Rocky Mountain Southwestern Wyoming Lance 5,500 8.0 90.7% 8.6% 0.000 6.605 -- 22,675

5-Rocky Mountain Southwestern Wyoming Lewis 5.172 8.0 99.2% 36.8% 0.003 0.460 42 6,955

5-Rocky Mountain Southwestern Wyoming Shallow Mesaverde (1) 5,239 4.0 95.0% 50.1% 0.000 1.250 -- 12,472

5-Rocky Mountain Southwestern Wyoming Shallow Mesaverde (2) 6,814 8.0 100.0% 49.0% 0.000 0.671 -- 17,914

5-Rocky Mountain Uinta-Piceance Basin Flank Mesaverde 1,708 8.0 99.8% 42.8% 0.000 0.988 -- 5,767

5-Rocky Mountain Uinta-Piceance Deep Synclinal Mesaverde 2,893 8.0 100.0% 14.4% 0.000 0.989 -- 3,297

5-Rocky Mountain Uinta-Piceance Iles/Mesaverde 1,172 8.0 99.1% 94.3% 0.000 0.730 -- 6,395

5-Rocky Mountain Uinta-Piceance

North Basin Williams Fork/

Mesaverde 908 8.0 100.0% 90.2% 0.000 0.654 -- 4,286

5-Rocky Mountain Uinta-Piceance

South Basin Williams Fork/

Mesaverde 636 32.0 98.6% 83.7% 0.000 0.467 -- 7,834

5-Rocky Mountain Uinta-Piceance Tertiary East 1,600 16.0 96.4% 32.9% 0.000 0.578 -- 4,693

5-Rocky Mountain Uinta-Piceance Tertiary West 1,603 8.0 100.0% 21.0% 0.000 4.066 -- 10,949

5-Rocky Mountain Wind River Fort Union/Lance Deep 2,500 4.0 99.9% 79.6% 0.000 0.537 -- 4,267

5-Rocky Mountain Wind River Fort Union/Lance Shallow 1,500 8.0 99.5% 94.8% 0.000 1.167 -- 13,212

5-Rocky Mountain Wind River Mesaverde/Frontier Deep 250 4.0 97.7% 45.0% 0.000 1.992 -- 876

5-Rocky Mountain Wind River Mesaverde/Frontier Shallow 250 4.0 90.6% 91.6% 0.000 1.252 -- 1,039

6-West Coast Columbia Basin Centered 1,500 8.0 100.0% 49.9% 0.000 1.257 -- 7,528

Tight Gas Total 2,985 435,405

Grand Total 58,066 1,044,263

EUR = estimated ultimate recovery; TRR = technically recoverable resource.

1

 Percent of total wells (area times well spacing) left to be drilled.

2

 Percent of area that is expected to have technically recoverable resources.

Source: U.S. Energy Information Administration, Office of Energy Analysis.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 125

Oil and Gas Supply Module

Table 9.4. U.S. unproved technically recoverable coalbed methane resources by play (as of January 1, 2011)

Average EUR TRR

Region Basin Play

Area 

(mi2)

Well Spacing 

(wells/mi2)

% of Area 

Untested1

% of 

Area with 

Potential2

Crude Oil 

(MMbls/

well)

Naturall Gas 

(Bcf/well)

Crude Oil 

(MMbls)

Natural 

Gas (Bcf)

1-Northwest Appalachian Central Basin 3,870 8 97.8% 34.0% 0 0.176 0 1,812

1-Northwest Appalachian North High 3,817 12 100.0% 9.4% 0 0.125 0 540

1-Northwest Appalachian North Mod/Low 8,906 12 100.0% 5.5% 0 0.080 0 474

1-Northwest Illinois Central Basin 1,714 8 100.0% 74.5% 0 0.120 0 1,226

2-Gulf Coast Black Warrior Extention Area 700 8 99.9% 21.1% 0 0.080 0 95

2-Gulf Coast Black Warrior Main Area 1,000 12 71.0% 97.1% 0 0.206 0 1,717

2-Gulf Coast Cahaba Cahaba Coal Field 387 8 93.4% 73.1% 0 0.179 0 379

3-Midcontinent Forest City Central Basin 23,769 8 100.0% 97.2% 0 0.172 0 31,781

3-Midcontinent Midcontinent Arkoma 2,998 8 97.8% 92.7% 0 0.216 0 4,703

3-Midcontinent Midcontinent Cherokee 3,550 8 100.0% 96.8% 0 0.065 0 1,798

4-Southwest Raton Southern 2,028 8 99.8% 95.1% 0 0.375 0 5,782

5-Rocky Mountain Greater Green River Deep 3,600 4 100.0% 45.0% 0 0.600 0 3,886

5-Rocky Mountain Greater Green River Shallow 720 8 99.7% 89.7% 0 0.204 0 1,052

5-Rocky Mountain Piceance Deep 2,000 4 100.0% 76.7% 0 0.600 0 3,680

5-Rocky Mountain Piceance Divide Creek 144 8 99.0% 94.9% 0 0.179 0 194

5-Rocky Mountain Piceance Shallow 2,000 4 99.2% 94.0% 0 0.299 0 2,234

5-Rocky Mountain Piceance White River Dome 216 8 98.7% 94.3% 0 0.410 0 658

5-Rocky Mountain Powder River Big George/Lower Fort Union 2,880 16 100.0% 54.5% 0 0.260 0 6,519

5-Rocky Mountain Powder River Wasatch 216 8 99.8% 95.3% 0 0.056 0 92

5-Rocky Mountain Powder River Wyodak/Upper Fort Union 6,600 20 98.9% 94.4% 0 0.136 0 16,772

5-Rocky Mountain Raton Northern 470 8 99.7% 73.2% 0 0.350 0 959

5-Rocky Mountain Raton Purgatoire River 360 8 97.2% 49.6% 0 0.311 0 431

5-Rocky Mountain San Juan Fairway NM 670 4 50.0% 50.5% 0 1,142 0 773

5-Rocky Mountain San Juan North Basin 2,060 4 83.8% 78.4% 0 0,280 0 1,513

5-Rocky Mountain San Juan North Basin CO 1,980 4 86.2% 98.0% 0 1,515 0 10,134

5-Rocky Mountain San Juan South Basin 1,190 4 93.8% 92.3% 0 0,199 0 821

5-Rocky Mountain San Juan South Menefee NM 7,454 5 100.0% 5.0% 0 0.095 0 294

5-Rocky Mountain Uinta Blackhawk 1,186 8 99.6% 97.1% 0 0.155 0 1,426

5-Rocky Mountain Uinta Ferron 400 8 96.9% 58.6% 0 0.776 0 1,410

5-Rocky Mountain Uinta Sego 534 4 99.9% 63.9% 0 0.306 0 418

5-Rocky Mountain Wind River Mesaverde 418 2 100.0% 100.0% 0 2,051 0 1,713

5-Rocky Mountain Wyoming Thrust Belt 5,200 2 100.0% 100.0% 0 0.454 0 5,418

6-West Coast Western Washington Bellingham 441 2 100.0% 100.0% 0 2,391 0 2,109

6-West Coast Western Washington Southern Puget Lowlands 1,102 2 100.0% 100.0% 0 0.687 0 1,514

6-West Coast Western Washington Western Cascade Mountains 2,174 2 100.0% 99.0% 0 1.559 0 6,710

Total Coalbed Methane 0 120,944

EUR = estimated ultimate recovery; TRR = technically recoverable resource.

1

 Percent of total wells (area times well spacing) left to be drilled. 

2

 Percent of area that is expected to have technically recoverable resources. 

Source: U.S. Energy Information Administration, Office of Energy Analysis.

Table 9.5. Distribution of EURs in the Bakken

Number of 

Potential Wells

EUR (mbbls/well)

Well Category

Average 

EUR

Top 

15%

Middle 

70%

Bottom 

15%

Bakken MT 16,324 154 87 18 93

Bakken ND Core 5,157 765 349 89 372

Bakken ND Extension 21,767 476 189 48 211

Source: U.S. Energy Information Administration, Office of Energy Analysis.
126 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

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The market penetration curve is a function of the relative economic attractiveness of the technology instead of being a timedependent function. A technology will not be implemented unless the benefits through increased production or cost reductions 

are greater than the cost to apply the technology. As a result, the market penetration curve provides a limiting value on 

commercialization instead of a specific penetration path. In addition to the curve, the implementation probability captures the 

fact that not all technologies that have been proven in the lab are able to be successfully implemented in the field.

CO2 enhanced oil recovery

For CO2 miscible flooding, the OLOGSS incorporates both industrial and natural sources of CO2. The industrial sources of CO2

are:

•	 Hydrogen plants

•	 Ammonia plants

•	 Ethanol plants

•	 Cement plants

•	 Refineries (hydrogen)

•	 Fossil fuel power plants

•	 Natural gas processing

•	 Coal/biomass to liquids (CBTL)

Technology and market constraints prevent the total volumes of CO2 (Table 9.6) from becoming immediately available. The 

development of the CO2 market is divided into 2 periods: 1) development phase and 2) market acceptance phase. During the 

development phase, the required capture equipment is developed, pipelines and compressors are constructed, and no CO2 is 

available. During the market acceptance phase, the capture technology is being widely implemented and volumes of CO2 first 

become available. The number of years in each development period is shown in Table 9.7. CO2 is available from planned Carbon 

Sequestration and Storage (CCS) power plants funded by American Recovery and Reinvestment Act of 2009 (ARRA) starting 

in 2016.

Table 9.6. Maximum volume of CO2 available

OGSM Region Natural Hydrogen Ammonia Ethanol Cement

Refineries 

(hydrogen) Power Plants

Natural Gas 

Processing

East Coast 0 3 0 52 94 17 12980 23

Gulf Coast 292 0 78 0 86 114 3930 114

Midcontinent 16 0 0 175 48 1 752 0

southwest 657 0 0 68 74 0 0 0

Rocky Mountains 80 0 3 23 35 62 2907 12

West Coast 0 0 0 4 48 93 1134 40

Northern Great Plains 0 0 0 9 3 16 60 6

Source: U.S. Energy Information Administration, Office of Energy Analysis.

The cost of CO2 from natural sources is a function of the oil price. For industrial sources of CO2, the cost to the producer 

includes the cost to capture, compress to pipeline pressure, and transport to the project site via pipeline within the region 

(Table 9.8). Inter-regional transportation costs add $0.40 per Mcf for every region crossed.

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 currently producing fields and industry-announced discoveries largely determines 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 2008 are assumed 

to remain at their peak production level for 2 years before declining.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 127

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Table 9.7. CO2 availability assumptions

Source Type Development Phase (years) Market Acceptance Phase (years) Ultimate Market Acceptance

Natural 1 10 100%

Hydrogen 4 10 100%

Ammonia 2 10 100%

Ethanol 4 10 100%

Cement 7 10 100%

Refineries (hydrogen) 4 10 100%

Power Plants 12 10 100%

Natural Gas Processing 2 10 100%

Source: U.S. Energy Information Administration, Office of Energy Analysis.

Table 9.8. Industrial CO2 capture & transportation costs by region

$/Mcf

OGSM Region Hydrogen Ammonia Ethanol Cement

Refineries 

(hydrogen) Power Plants

Natural Gas 

Processing CBTL

East Coast $2.44 $2.10 $2.23 $4.29 $2.44 $5.96 $1.92 $1.91

Gulf Coast $1.94 $2.10 $2.23 $4.29 $1.94 $5.96 $1.92 $1.91

Midcontinent $2.07 $2.10 $2.23 $4.29 $2.07 $5.96 $1.92 $1.91

Southwest $2.02 $2.10 $2.23 $4.29 $2.02 $5.96 $1.92 $1.91

Rocky Mountains $2.03 $2.10 $2.23 $4.29 $2.03 $5.96 $1.92 $1.91

West Coast $2.01 $2.10 $2.23 $4.29 $2.01 $5.96 $1.92 $1.91

Northern Great Plains $2.05 $2.10 $2.23 $4.29 $2.05 $5.96 $1.92 $1.91

Source: U.S. Energy Information Administration. Office of Energy Analysis.

The assumed field size and year of initial production of the major announced deepwater discoveries that were not brought into 

production by 2011 are shown in Table 9.9. 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 BOEM’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). 

Advances in technology for the various activities associated with crude oil and natural gas exploration, development, and 

production can have a profound impact on the costs associated with these activities. The specific technology levers and values 

for the offshore are presented in Table 9.10.

Leasing is assumed to be available in 2018 in the Mid and South Atlantic, in 2023 in the South Pacific, and after 2035 in the 

North Atlantic, Florida straits, Pacific Northwest, and North and Central California.

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. Projected North Slope oil production also includes 

the initiation of oil production in the Point Thomson Field in 2016. 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 prices.

The discovery of new Alaskan oil fields is determined by the number of new wildcat exploration wells drilled each year and by 

the average wildcat success rate. The North Slope and South-Central wildcat well success rates are based on the success rates 

reported to the Alaska Oil and Gas Conservation Commission for the period of 1977 through 2008.
128 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Oil and Gas Supply Module

Table 9.9. Assumed size and initial production year of major announced deepwater discoveries

Field/Project Name Block

Water Depth 

(feet) Year of Discovery Field Size Class

Field Size 

(MMBoe)

Start Year of 

Production

Anduin West MC754 2,696 2008 11 46 2012

Bushwood GB463 2,700 2009 13 182 2012

Caesar GC683 4,457 2006 11 45 2012

Cascade WR206 8,143 2002 14 372 2012

Cheyenne East LL400 9,200 2010 9 12 2012

Chinook WR469 8,831 2003 14 372 2012

Clipper GC299 3,452 2005 11 45 2012

Galapogos MC519 6,526 2009 11 45 2012

Goose MC751 1,624 2003 11 45 2012

Isabella MC562 6,535 2007 11 45 2012

Mandy MC199 2,478 2010 13 182 2012

MC241 MC285 2,427 2006 11 45 2012

Ozona GB515 3,000 2008 11 45 2012

Pyrenees GB293 2,100 2009 12 89 2012

Silvertip AC815 9,226 2004 12 372 2012

West Tonga GC726 4,674 2007 12 89 2012

Wide Berth GC490 3,700 2009 12 89 2012

Axe DC004 5,831 2010 12 89 2013

Big Foot WR029 5,235 2005 12 89 2013

Dalmatian DC048 5,876 2008 12 89 2013

Knotty Head GC512 3,557 2005 14 372 2013

Jack WR759 6,963 2004 14 372 2014

Lucius KC875 7,168 2009 13 182 2014

St. Malo WR678 7,036 2003 14 372 2014

Tubular Bells MC725 4,334 2003 12 89 2014

Freedom MC948 6,095 2008 15 691 2015

Heidelberg GC859 5,000 2009 13 182 2015

Kodiak MC771 4,986 2008 13 182 2015

Pony GC468 3,497 2006 14 372 2015

Samurai GC432 3,400 2009 12 89 2015

Winter GB605 3,400 2009 11 45 2015

Kaskida KC292 5,860 2006 15 691 2016

Mission Deep GC955 7,300 1999 13 182 2016

Stones WR508 9,556 2005 12 89 2016

Tiber KC102 4,132 2009 15 691 2016

Vito MC984 4,038 2009 13 182 2016

Shenandoah WR052 5,750 2009 13 182 2017
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 129

Oil and Gas Supply Module

Table 9.9. Assumed size and initial production year of major announced deepwater discoveries (cont.)

Field/Project Name Block

Water Depth 

(feet) Year of Discovery Field Size Class

Field Size 

(MMBoe)

Start Year of 

Production

Buckskin KC872 6,920 2009 13 182 2018

Diamond LL370 9,975 2008 11 45 2018

Julia WR627 7,087 2007 12 89 2018

Appomattox MC392 7,217 2009 15 691 2019

Hadrian South KC964 7,586 2009 13 182 2019

Hal WR848 7,657 2008 11 45 2019

Vicksburg DC353 7,457 2009 14 372 2019

Cardamom GB427 2,720 2010 13 182 2020

Hadrian North KC919 7,000 2010 14 372 2020

Source: U.S. Energy Information Administration. Office of Energy Analysis.

New wildcat exploration drilling rates are determined differently for the North Slope and South-Central Alaska. North Slope wildcat 

well drilling rates were found to be reasonably well correlated with prevailing West Texas Intermediate crude oil prices. Consequently, 

an ordinary least squares statistical regression was employed to develop an equation that specifies North Slope wildcat exploration 

well drilling rates as a function of prevailing West Texas Intermediate crude oil prices. In contrast, South- Central wildcat well drilling 

rates were found to be uncorrelated to crude oil prices or any other criterion. However, South- Central wildcat well drilling rates on 

average equaled just over 3 wells per year during the 1977 through 2008 period, so 3 South- Central wildcat exploration wells are 

assumed to be drilled every year in the future.

Table 9.10. Offshore exploration and production technology levels

Technology Level

Total Improvement over 30 

years (percent)

Exploration success rates 30

Delay to commence first exploration and between 15

Exploration & development drilling costs 30

Operating cost 30

Time to construct production facility 15

Production facility construction costs 30

Initial constant production rate 15

Decline rate 0

Source: U.S. Energy Information Administration, Office of Energy Analysis.

On the North Slope, the proportion of wildcat exploration wells drilled onshore relative to those drilled offshore is assumed to change 

over time. Initially, only a small proportion of all the North Slope wildcat exploration wells are drilled offshore. However, over time, 

the offshore proportion increases linearly, so that after 20 years, 50 percent of the North Slope wildcat wells are drilled onshore and 

50 percent are drilled offshore. The 50/50 onshore/offshore wildcat well apportionment remains constant through the remainder of 

the projection in recognition of the fact that offshore North Slope wells and fields are considerably more expensive to drill and develop, 

thereby providing an incentive to continue drilling onshore wildcat wells even though the expected onshore field size is considerably 

smaller than the oil fields expected to be discovered offshore.
130 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

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The size of the new oil fields discovered by wildcat exploration drilling is based on the expected field sizes of the undiscovered 

Alaska oil resource base, as determined by the U.S. Geological Survey for the onshore and State offshore regions of Alaska, 

and by the Bureau of Ocean Energy Management (BOEM) (formerly known as the U.S. Minerals Management Service) for the 

Federal offshore regions of Alaska. It is assumed that the largest undiscovered oil fields will be found and developed first and in 

preference to the small and midsize undiscovered fields. As the exploration and discovery process proceeds and as the largest oil 

fields are discovered and developed, the discovery and development process proceeds to find and develop the next largest set of 

oil fields. This large to small discovery and development process is predicated on the fact that developing new infrastructure in 

Alaska, particularly on the North Slope, is an expensive undertaking and that the largest fields enjoy economies of scale, which 

ake them more profitable and less risky to develop than the smaller fields.

Oil and gas exploration and production currently are not permitted in the Arctic National Wildlife Refuge. The projections for 

Alaska oil and gas production assume that this prohibition remains in effect throughout the projection period.

Three uncertainties are associated with the Alaska oil projections. First, 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. Second, the oil production potential of the North Slope shale formations is unknown at this time. Third, the North 

Slope offshore oil resource potential, especially in the Chukchi Sea, is untested.

In June 2011, Alyeska Pipeline Service Company released a report regarding potential operational problems that might occur as 

Trans-Alaska Pipeline System (TAPS) throughput declines from the current production levels.[6] Although the onset of TAPS 

low flow problems could begin at around 550,000 barrels per day, absent any mitigation, the severity of the TAPS operational 

problems is expected to increase significantly as throughput declines. As the types and severity of problems multiplies, 

the investment required to mitigate those problems is expected to increase significantly. Because of the many and diverse 

operational problems expected to occur below 350,000 barrels per day of throughput, considerable investment might be 

required to keep the pipeline operational below this threshold. Thus, North Slope fields are assumed to be shut down, plugged, 

and abandoned when the following 2 conditions are simultaneously satisfied: 1) TAPS throughput would have to be at or below 

350,000 barrels per day and 2) total North Slope oil production revenues would have to be at or below $5.0 billion per year. 

Legislation and regulations

The Outer Continental Shelf Deep Water Royalty Act (Public Law 104-58) gave the Secretary of the 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 Minerals Management Service (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 at 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 volumes 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 of 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 depths 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.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 131

Oil and Gas Supply Module

The MMS 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 

roduction 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.

From 1982 through 2008, Congress did not appropriate funds needed by the MMS to conduct leasing activities on portions of 

the Federal Outer Continental Shelf (OCS) and thus effectively prohibited leasing. Further, a separate Executive ban in effect since 

1990 prohibited leasing through 2012 on the OCS, with the exception of the Western Gulf of Mexico and portions of the Central 

and Eastern Gulf of Mexico. When combined, these actions prohibited drilling in most offshore regions, including areas along the 

Atlantic and Pacific coasts, the eastern Gulf of Mexico, and portions of the central Gulf of Mexico. In 2006, the Gulf of Mexico 

Energy Security Act imposed yet a third ban on drilling through 2022 on tracts in the Eastern Gulf of Mexico that are within 125 

miles of Florida, east of a dividing line known as the Military Mission Line, and in the Central Gulf of Mexico within 100 miles of 

Florida.

On July 14, 2008, President Bush lifted the Executive ban and urged Congress to remove the Congressional ban. On September 

30, 2008, Congress allowed the Congressional ban to expire. Although the ban through 2022 on areas in the Eastern and Central 

Gulf of Mexico remains in place, the lifting of the Executive and Congressional bans removed regulatory obstacles to development 

of the Atlantic and Pacific OCS.

Oil and gas supply alternative cases

Tight Oil and Shale Gas Resource cases

Estimates of technically recoverable tight/shale crude oil and natural gas resources are particularly uncertain and change over 

time as new information is gained through drilling, production, and technology experimentation. Over the last decade, as more 

tight/shale formations have gone into production, the estimate of technically recoverable tight oil and shale gas resources has 

increased. However, these increases in technically recoverable resources embody many assumptions that might not prove to be 

true over the long term and over the entire tight/shale formation. For example, these resource estimates assume that crude oil 

and natural gas production rates achieved in a limited portion of the formation are representative of the entire formation, even 

though neighboring well production rates can vary by as much as a factor of three within the same play. Moreover, the tight/

shale formation can vary significantly across the petroleum basin with respect to depth, thickness, porosity, carbon content, pore 

pressure, clay content, thermal maturity, and water content. Additionally, technological improvements and innovations may allow 

development of crude oil and natural gas resources that have not been identified yet so are not included in the Reference case. 

Two cases were developed with alternate crude oil and natural gas resource assumptions. These cases do not represent an upper 

and lower bound on future domestic oil and natural gas supply but rather provide a framework to examine the impact of higher 

and lower domestic supply on energy demand, imports, and prices (see ‘Issues in Focus’ articles).

High Oil and Gas Resource case. This case is designed to address what might happen if domestic crude oil production continued 

to increase through the projection period, reaching over 10 million barrels per day. This case includes (1) 100 percent higher 

estimated ultimate recovery (EUR) per tight oil, tight gas, and shale gas well than in the reference case and a maximum well 

spacing of 40 acres to reflect the possibility that additional layers of low permeability zones are identified and developed, 

compared with well spacing that ranges from 20 to 406 acres with an average of 100 acres in the Reference case; (2) kerogen 

development reaching 135,000 barrels per day by 2025; (3) tight oil development in Alaska increasing the total Alaska TRR by 

1.9 billion barrels; and (4) 50 percent higher technically recoverable undiscovered resources in Alaska and the offshore lower 

48 states than in the Reference case. A few offshore Alaska fields are assumed to be discovered and thus developed earlier 

than in the Reference case. The total unproved technically recoverable resources are 557 billion barrels of crude oil and 6,771 

trillion cubic feet compared to 197 billion barrels of crude oil and 2,022 trillion cubic feet of dry natural gas in the Reference case. 

Proved reserves of oil and natural gas are the same in all three cases; 25 billion barrels of crude oil and 305 trillion cubic feet of 

dry natural gas. Additionally, given the higher natural gas resource in this case, the maximum penetration rate for gas-to-liquids 

(GTL) was increased to 10 percent per year from a nominal rate of 5 percent per year in the Reference case.
132 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Oil and Gas Supply Module

Low Oil and Gas Resource case. In this case, the EUR per tight oil, tight gas, and shale gas well is assumed to be 50 percent lower 

than in the Reference case, increasing the per-unit cost of developing the resource. The total unproved technically recoverable 

crude oil resource is decreased to 168 billion barrels and the natural gas resource is decreased to 1500 trillion cubic feet, 

compared to 197 billion barrels of crude oil and 2,022 trillion cubic feet of natural gas assumed in the Reference case.

Notes and sources

[1] The current development of tight oil plays has shifted industry focus and investment away from the development of U.S. oil 

shale (kerogen) resources. Considerable technological development is required prior to the large-scale in-situ production of 

oil shale being economically feasible. Consequently, the Oil Shale Supply Submodule assumes that large- scale in-situ oil shale 

production is not commercially feasible prior to 2040.

[2] Technically recoverable resources are resources in accumulations producible using current recovery technology but without 

reference to economic profitability.

[3] 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.

[4] Unproved resources include resources that have been confirmed by exploratory drilling and undiscovered resources, which 

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 the Interior, U.S. Geological Survey, 1995 National Assessment of the United 

States Oil and Gas Resources, (Washington, D.C., 1995); U.S. Department of the 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] Alyeska Pipeline Service Company, Low Flow Impact Study, Final Report, June 15, 2011, Anchorage, Alaska, at www.alyeskapipe.com/Inthenews/LowFlow/LoFIS_Summary_Report_P6%2027_FullReport.pdf
Natural Gas Transmission and 

Distribution Module
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U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 135

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 a regional interstate representative pipeline 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 9). The major assumptions used within the NGTDM are grouped into four 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 2013, DOE/EIA-M062(2013) (Washington, DC, 2013).

Figure 9. Natural Gas Transmission and Distribution Module Regions
136 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Natural Gas Transmission and Distribution Module

Key assumptions

Structural components

The primary and secondary region-to-region flows represented in the model are shown in Figure 9. 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 and exports of domestically produced natural 

gas are also not directly part of the equilibration process, but are set at the beginning of each NEMS iteration in response to 

the price from the previous iteration and projected future prices, respectively. LNGre-exports are set exogenously to the model. 

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 off-peak 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

For the first two 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. 

Reservation and operation 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. Historically based differentials are used to establish separate prices for energy-intensive and non-energyintensive industrial customers.

The transportation or natural gas vehicle sector is segregated into compressed natural gas (CNG) and liquefied natural gas 

(LNG) at private refueling stations (fleets) and at public retail stations. The distributor markup for natural gas delivered via 

pipeline to a CNG station is based off historical data for the sector. A retail markup and motor fuel (excise) taxes are added to set 

the final retail price. The excise taxes applied and the value and assumptions behind the retail markups assumed are shown in 

Table 10.1. The price for delivered dry natural gas to a liquefaction plant is approximated by using the price to electric generators. 

The price for LNG is therefore set to the price to electric generators, plus the assumed price to liquefy and transport the LNG, the 

retail price markup at the station, and the excise taxes.The values for these components and the primary assumptions behind 

them are shown in Table 10.1. The table shows the national average State excise tax, while in the model these taxes vary by 

region.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 137

Natural Gas Transmission and Distribution Module

Table 10.1. Assumptions related to CNG and LNG fuel prices

Year CNG CNG LNG LNG

fl eet retail fl eet retail

Retail markup after dry gas pipeline delivery, with no excise tax (2010$/dge) 0.80 0.93 1.39 1.58

 Capacity (dge/day) 1600 1100 4000 4000

 Usage (percent of capacity) 80 60 80 60

 Capital cost (million 2010$) 0.80 0.5 1.0 1.0

 Capital recovery (years) 5 10 5 10

 Weighted average cost of capital (rate) 0.10 0.15 0.10 0.15

 Operating cost (2010$/dge) 0.34 0.51 0.41 0.59

 Charge for liquefying and delivering LNG (2010$/dge -- -- 0.75 0.75

Federal excise tax (nominal$/dge) 0.21 0.21 0.42 0.42

State excise tax (nominal$/dge) 0.15 0.15 0.24 0.24

Fuel loss for liquefying and delivering LNG (percent of input volumes) -- -- 10 10

Fuel loss at station (percent of input volumes) 0 0.5 1.0 2.0

Source: U.S. Energy Information Administration, U.S. Tax Code and State Tax Codes.

Note: dge is diesel-gallon equivalent

Pipelines from arctic areas into Alberta

The outlook for natural gas production from the North Slope of Alaska is aff ected strongly by its extreme distance from 

the necessary infrastructure to transport it to major commercial markets. At present there are three basic options for 

commercializing the natural gas that has been produced in association with the Prudhoe Bay oil fi elds and reinjected, and is 

therefore relatively low-cost to recover: build a pipeline to the lower 48 states via Alberta, produce and transport the natural 

gas as liquid fuel in a gas-to-liquid (GTL) plant, or pipe the natural gas to a seaport, liquefy and ship it overseas. The GTL option 

was not considered for AEO2013. Which, if any, of the other two options that is determined within the model to be economically 

viable fi rst is assumed to have primary access to the proved, low-cost, reserves on the North Slope and preclude the economic 

viability of the other option. The assumptions associated with the LNG option are provided in a later section. 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 10.2. 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 refl ect the potential 

impact on the market price if the pipeline comes on line.

To assess the market value of Alaskan and Mackenzie Valley gas against the lower 48 market, a price diff erential of $0.75 (2011 

dollars per Mcf) is assumed between the price in Alberta and the average lower 48 wellhead price. The resulting cost of Alaska 

gas, relative to the lower 48 wellhead price, is approximately $6.30 (2011 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 exceed the average lower 48 gas price in each of the previous two

years, on average over the previous fi ve years (with greater weight applied to more recent years), and as expected to average 

over the next three years. An adjustment is made if prices were declining over the previous fi ve years. Once the assumed fouryear construction period is complete, expansion can occur if the price exceeds the initial trigger price by $6.87 (2011 dollars

per Mcf). Supplies to fi ll an expanded pipeline are assumed to require new gas wells. 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 suffi cient economical 

supplies are available at the North Slope to fi ll the pipeline over the depreciation period.

Natural gas production from the Mackenzie Delta is assumed to be suffi cient to fi ll 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 10.2.
138 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Natural Gas Transmission and Distribution Module

Table 10.2. Primary assumptions for natural gas pipelines from Alaska and Mackenzie delta into Alberta, 

Canada

Alaska to Alberta Mackenzie Delta to Alberta

Initial flow into Alberta 3.8 billion cubic feet per day 1.1 billion cubic feet per day

Expansion potential 22 percent 58 percent

Initial capitalization $37.0 billion (2011 dollars) $11.0 billion (2011 dollars)

Cost of Debt (premium over 10-year treasury note yield) 0.75 percent 0.0 percent

Cost of equity (premium over 10-year treasury note yield) 6.5 percent 7.5 percent

Debt fraction 70 percent 60 percent

Depreciation period 20 years 20 years

Minimum wellhead price (including treatment and fuel costs) $1.76 (2011 dollars per Mcf) $3.22 (2011 dollars per Mcf)

Expected price reduction $1.04 (2011 dollars per Mcf) $0.06 (2011 dollars per Mcf)

Additional cost for expansion $6.87 (2011 dollars per Mcf)* $0.37 (2011 dollars per Mcf)

Construction period 4 years 4 years

Planning period 5 years 2 years

Earliest start year 2021 2018

*Includes added cost to explore for and produce natural gas beyond what has already been proven.

Source: U.S. Energy Information Administration, Office of Energy Analysis. Alaska pipeline cost data are based on Federal Energy Regulatory 

Commission, Docket PF09-11-001, “Open Season Plan Documents Submitted in Connection with Request for Commission Approval of 

Detailed Plan for Conducting an Open Season,” submitted by TransCanada Alaska Company LLC on January 29, 2010, Volume III of III, 

Appendix C, Exhibit J – Recourse Rate Output, various pages. Note that the capital cost figure is the arithmetic average of the two $30.7 and 

$40.4 billion capital cost estimates that include the mainline gas pipeline and the gas treatment plant, but which exclude the gas field line 

from Point Thomson to the gas treatment plant. 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 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,”

Supplemental natural gas

The projection for supplemental gas supply is identified for three separate categories: pipeline quality synthetic natural gas 

(SNG) from coal or coal-to-gas (CTG), SNG from liquids, 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). The third 

category, other supplemental supplies, are held at a constant level of 6.6 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. SNG from liquid hydrocarbons in Hawaii is assumed to continue over the projection at the average historical level of 

2.6 billion cubic feet per year. SNG production from coal at the currently operating Great Plains Coal Gasification Plant is also 

assumed to continue through the projection period at an average historical level of 52.2 billion cubic feet per year. It is assumed 

that additional CTG facilities will be built if and when natural gas prices are high enough to make them economic. One CTG 

facility is assumed capable of processing 6,040 tons of bituminous coal per day, with a production capacity of 0.1 billion cubic 

feet per day of synthetic fuel and approximately 100 megawatts of capacity for electricity cogeneration sold to the grid. A CTG 

facility of this size is assumed to cost nearly $1 billion in initial capital investment (2011 dollars). CTG facilities are assumed to be 

built near existing coal mines. All NGTDM regions are considered potential locations for CTG facilities except for New England. 

Synthetic gas products from CTG facilities are assumed to be competitive when natural gas prices rise above the cost of CTG 

production (adjusted for credits from the sale of cogenerated electricity). It is assumed that CTG facilities will not be built before 

2012.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 139

Natural Gas Transmission and Distribution Module

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. Natural gas consumption levels in Mexico are set exogenously based on projections from the International Energy 

Outlook 2011 and are provided in Table 10.3, along with initially assumed Mexico natural gas production and LNG import levels 

targeted for markets in Mexico. Adjustments to production 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. Maximum LNG import volumes targeted for markets in Mexico are 

set exogenously and will be realized if endogenously determined LNG imports into North America are sufficient. The difference 

between production plus LNG imports and consumption in Mexico in any year is assumed to be either imported from, or 

exported to, the United States.

Similarly to Mexico, Canada is modeled through a combination of exogenously and endogenously specified components. Natural 

gas exports from the United States to Canada are set exogenously in NEMS starting at 737 billion cubic feet per year in 2011 

and increasing to 1,433 billion cubic feet by 2040. Canadian production and U.S. import flows from Canada are determined 

endogenously within the model. Canadian natural gas production in Eastern Canada and consumption are set exogenously in 

the model and are shown in Table 10.4. Production from conventional and tight formations 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 estimated production-to-reserve ratio. Reserve additions are set equal to the product of successful natural gas wells 

and a finding rate (both based on an econometric estimation). The initial coalbed methane, shale gas, and conventional WCSB 

economically recoverable unproved resource base estimates assumed in the model are 45 trillion cubic feet, 90 trillion cubic 

feet, and 127 trillion cubic feet, respectively, all as of 2011. [1] Potential production from tight formations was approximately by 

increasing the conventional resource level by 2.3 percent annually. Production from coalbed and shale 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. LNG imports to and exports from Canada are set in conjunction with the LNG import and export 

volumes for the lower 48 states.

Table 10.3. Exogenously specified Mexico natural gas consumption and supply

billion cubic feet per year

Consumption Initial Dry Production Initial LNG Imports

2015 2,590 1.710 3

2020 3,132 1,536 501

2025 3,884 1,478 976

2030 4,564 1,612 1,231

2035 5,263 1,895 1,366

2040 5,957 2,167 1,366

Source: Consumption - U.S. Energy Information Administration. International Energy Outlook 2011 DOE/EIA-0484(2011) and U.S. Energy 

Information Administration, Office of petroleum, Gas, and Biofuels Analysis; Production - U.S. Energy Information Administration, Office of 

Petroleum, Gas, and Biofuels Analysis. LNG imports - U.S. Energy Information Administration, International Energy Outlook 2011, DOE/EIA0484(2011).

Note: Excludes LNG imported to Mexico for export to the United States.

Table 10.4. Exogenously specified Canada natural gas consumption and supply

billion cubic feet per year

Year Consumption Production Eastern Canada

2010 2,936 119

2015 3,507 127

2020 3,742 98

2025 4,175 81

2030 4,558 68

2035 5,041 58

2040 5,355 40

Source: Consumption - U.S. Energy Information Administration. International Energy Outlook 2011, DOE/EIA-0484(2011); Production - Energy

Information Administration, Office of Petroleum, Gas, and Biofuels Analysis.
140 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Natural Gas Transmission and Distribution Module

LNG imports to the United States and Canada are determined endogenously within the model using Atlantic/Pacific and peak/

off-peak supply curves derived from model results generated by EIA’s International Natural Gas Model (INGM). Prices from 

the previous model iteration are used to establish the total level of U.S./Canada LNG imports in the peak and off-peak period 

and in the Atlantic and Pacific regions. First, assumed LNG imports which are consumed in Mexico are subtracted (presuming 

the volumes are sufficient). Then, the remaining levels are allocated to the model regions based on last year’s import levels, the 

available regasification capacity, and the relative prices. Regasification capacity is limited to facilities currently in existence and 

those already under Annual U.S. exports of liquefied natural gas (LNG) to Japan via Alaska’s existing Kenai facility are assumed 

to cease in 2012. LNG re-exports are assumed to stay at 30 billion cubic feet per year throughout the projection period, close 

to current historical levels. LNG exports of domestically produced natural gas from the lower 48 States, Canada, and Alaska are 

set endogenously to the model. The model assesses the relative economics of a generic project (consisting of two trains, with 

total annual capacity of 400 billion cubic feet) in operation over the next 20 years in each viable coastal region by comparing 

a model generated estimate of the expected market price in Europe and Asia over the next 20 years against the expected price 

of natural gas in each coastal region plus assumed charges for liquefaction, shipping, and regasification (shown in Table 10.5). 

A present value of the differential is set using a discount rate of 10 percent. The model limits the annual builds to one train a 

year. The region, showing the greatest positive economic potential is selected each year, if any, with the exception that Western 

Canada always takes precedence (used to address a convergence issue). Once a facility is built it is assumed to operate at 

its design capacity throughout the projection period. The addition of a third and fourth train is assumed to be economically 

advantageous over a greenfield facility and is represented with a $0.50 per Mcf (2010 dollars) discounted cost. Other accounting 

and constraining assumptions such as earliest start year and maximum export volumes are shown below. Any existing facilities 

or ones under construction are set exogenously to the model, which for AEO2013 include the two trains under construction at 

Sabine Pass (at 1.1 Bcf per day starting in mid-2016).The projected market price of LNG in Europe (National Balancing Point) and 

Asia (Japan) is based on the assumed values shown in Table 10.6, projected Brent oil prices, and the level of North American 

LNG exports.

Table 10.5. Charges related to LNG exports and other supporting assumptions

2010 dollars per million Btu

S. Atlantic W.S. Central WA/OR W. Canada Alaska

Liquefaction & Pipe Fee 3.30 3.00 4.10 4.40 7.00

Shipping to Europe 0.98 1.28 3.86 3.84 3.65

Shipping to Asia 2.63 2.55 1.15 1.13 0.90

Regasification 0.10 0.10 0.10 0.10 0.10

Earliest start year 2019 2018 2019 2018 2023

Maximum exports (Bcf) 9999 9999 9999 800 800

Fuel charge (percent)* 15 15 15 15 15

*Percent increase in market price of natural gas charged by liquefaction facility to cover fuel related expenses, largely fuel used in the 

liquefaction process. 

Source: Energy Information Administration, Office of Petroleum, Gas, and Biofuels Analysis.

Table 10.6. International natural gas volume drivers for world LNG Europe and Asia market price 

projections

billion cubic feet

Flexible 

LNG*

Consumption Production

OECD Europe Japan S. Korea China China

2010 2,301 19,915 3,718 1,515 3,769 3,334

2015 3,609 18,184 3,976 1,737 7,001 4,606

2020 4,732 18,735 3,976 1,858 8,983 5,206

2025 5,834 19,194 4,191 2,020 11,361 6,206

2030 6,854 20,204 4,298 2,154 13,474 7,506

2035 7,902 21,306 4,298 2,240 15,192 8,806

2040 8,922 22,227 4,407 2,332 16,351 10,264

*Flexible LNG is a baseline projection of the volumes of LNG sold in the spot market or effectively available for sale at flexible 

destinations. Source: Consumption and Production – U.S. Energy Information Administration. International Energy Outlook 2011, DOE/

EIA-0484(2011) and Energy Information Administration, Office of Petroleum, Gas, and Biofuels Analysis. Flexible LNG–PFC Energy and 

Energy Information Administration, Office of Petroleum, Gas, and Biofuels Analysis
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 141

Natural Gas Transmission and Distribution Module

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 should the demand for services decline.

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 (indexed for inflation at the 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 assumed costs of borrowing money for the pipeline were reduced to reflect the 

decreased risk as a result of the loan guarantee.

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 assumed to have minimal impact on the decision to 

build the pipeline.

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. The impact of this tax credit is assumed to be factored into the cost estimates 

filed by the participating companies.

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. Storage rates are 

allowed to vary in the model from regulation-based rates, depending on market conditions.

Notes and sources

[1] Coalbed, shale gas, and tight sands unproved resource based on the National Energy Board of Canada’s “Canada’s Energy 

Future: Energy supply and demand projections to 2035,” November 2011.
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Liquid Fuels Market Module
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U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 145

Liquid Fuels Market Module

The NEMS Liquid Fuels Market Module (LFMM) 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, esters, corn, biomass, and coal), natural gas plant liquids 

production, and refinery processing gain. In addition, the LFMM projects capacity expansion and fuel consumption at domestic 

refineries.

The LFMM contains a linear programming (LP) representation of U.S. petroleum refining activities, biofuels production 

activities, and other non-petroleum liquid fuels production activity in eight domestic U.S. regions and refining activity in a new 

Maritime Canada/Caribbean refining region (created to represent short-haul international refineries that predominantly serve 

U.S. markets). In order to better represent policy, import/export patterns, and biofuels production, the eight U.S. regions were 

defined by subdividing three of the five Petroleum Administration for Defense Districts (PADDs) (Figure 10). The LP model also 

represents crude import supply curves, gasoline import supply curves from Europe, advanced ethanol import supply curves from 

Brazil, and exogenously defined imports and exports for selected products. The nine LFMM regions and import/export curves 

are connected in the LP via crude and product transit links. In order to interact with other NEMS modules with different regional 

representations, certain LFMM inputs and outputs are converted from sub-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.

Figure 10. Liquid Fuels Market Module Regions

Source: U.S. Energy Information Administration, Office of Energy Analysis.
146 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Liquid Fuels Market Module

Key assumptions

Product types and specifications

The LFMM models refinery production of the products shown in Table 11.1.

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 (LP) representation of refineries by incorporating the specifications and demands for 

these fuels. The LFMM assumes that the specifications for these fuels will remain the same as currently specified.

Table 11.1. Petroleum product categories

Product Category Specific Products

Motor Gasoline Conventional, Reformulated (including CARB gasoline)

Jet Fuel Kerosene-type

Distillates Kerosene, Heating Oil, Low-Sulfur, Ultra-Low-Sulfur and CARB Diesel

Residual Fuels Low Sulfur, High Sulfur

Liquefied Petroleum Gases Ethane, Propane, Propylene, normal- and iso-Butane

Petrochemical Feedstock Petrochemical Naphtha, Petrochemical Gas Oil, Aromatics

Others

Lubricating Products and Waxes, Asphalt/Road Oil, Still Gas

Petroleum Coke, Special Naphthas, Aviation Gasoline

Source: U.S. Energy Information Administration, Office of Energy Analysis.

Motor gasoline specifications and market shares

The LFMM models the production and distribution of two different types of gasoline: conventional and reformulated (Phase 

2). The following specifications are included in the LFMM to differentiate between conventional and reformulated gasoline 

blends (Table 11.2): 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). 

Conventional gasoline must meet the Complex Model II compliance standards which cannot exceed average 1990 levels of toxic 

and nitrogen oxide emissions [2].

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 survey of literature [4] and the USDA 

Agricultural Baseline Projections to 2019 [5].

Corn supply prices are estimated from the USDA baseline projections to 2019 [6]. The capital cost of a 50-million-gallon- peryear corn ethanol plant was assumed to be $84 million (2008 $). Operating costs of corn ethanol plants are obtained from USDA 

survey of ethanol plant costs [7]. 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 LFMM reflects “Phase 2” 

reformulated gasoline requirements which began in 2000. The LFMM 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 11.3).
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 147

Liquid Fuels Market Module

Table 11.2. Year-round gasoline specifications by Petroleum Administration for Defense Districts (PADD), as of 2011

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

Evaporated

at 300o

Conventional

PADD I 9.6 26.0 1.1 30.0 11.6 47.1 82.0

PADD II 10.2 26.1 1.1 30.0 11.6 47.1 81.9

PADD III 9.9 26.1 1.1 30.0 11.6 47.1 81.9

PADD IV 10.8 26.1 1.1 30.0 11.6 47.1 81.9

PADD V 9.2 26.7 1.1 30.0 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

Max = Maximum.

PADD = Petroleum Administration for Defense District. PPM = parts per million by weight.

PSI = pounds per square inch.

Benzene volume percent changed to 0.6 for all regions and type in 2011 to meet the MSAT2 ruling.

Source: U.S. Energy Information Administration, Office of Energy Analysis. Derived using U.S. EPA’s Complex Model, and updated with U.S. EPA’s gasoline 

projection survey “Fuel Trends Report: Gasoline 1995-2005”, January 2008, EPA420-R-08-002. (http://www.epa.gov/otaq/regs/fuels/fueltrends.htm).

Table 11.3. Market share for gasoline types by Census Division

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 18 41 81 88 81 95 72 86 25

Reformulated Gasoline 82 59 19 12 19 5 28 14 75

Source: U.S. Energy Information Administration, Office of Energy Analysis. Derived from EIA-782C, “Monthly

Report of Prime Supplier Sales of Petroleum Products Sold for Local Consumption,” January-December 2010.

As of January 2007, Oxygenated Gasoline is included within Conventional Gasoline.

AEO2013 assumes a minimum 10 percent blend of ethanol in domestically consumed motor gasoline. Federal reformulated 

gasoline (RFG) and conventional gasoline can be blended with up to 15 percent ethanol in light-duty vehicles of model year 

2001 and newer, but actual levels will depend on ethanol’s blending value and relative cost competitiveness with other gasoline 

blending components. In addition, current state regulation along with marketplace constraints limit the full penetration of 

E15 in the early part of the projection. 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 LFMM 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.
148 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Liquid Fuels Market Module

Within the LFMM, total gasoline demand is disaggregated into demand for conventional and reformulated gasoline by applying 

assumptions about the annual market shares for each type. In AEO2013 the annual market shares for each region reflect actual 2010 

market shares and are held constant throughout the projection. (See Table 11.3 for AEO2013 market share assumptions.)

Diesel fuel specifications and market shares

In order to account for ultra-low-sulfur diesel (ULSD) regulations related to Clean Air Act Amendments of 1990 (CAAA90), ultralow-sulfur diesel is differentiated from other distillates. In NEMS, the California portion of the Pacific Region (Census Division 9) is 

required to meet CARB standards. Both Federal and CARB standards currently limit sulfur to 15 ppm.

AEO2013 incorporates the ULSD regulation finalized in December 2000. ULSD is highway diesel that contains no more than 15 ppm 

sulfur at the pump.

Demand for highway-grade diesel is assumed to be equivalent to the total transportation distillate demand. Historically, highwaygrade diesel supplies have nearly matched total transportation distillate sales, although some highway-grade diesel has gone to nontransportation uses such as construction and agriculture.

AEO2013 incorporates the “nonroad, locomotive, and marine” (NRLM) diesel regulation finalized in May 2004. 

The final NRLM rule established a new ULSD limit of 15 ppm for nonroad diesel by mid-2010. For locomotive and marine diesel, the 

rule established 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 11.4).

State and Federal taxes are also added to transportation fuels to determine final end-use prices (Tables 11.5 and 11.6). 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 AEO2013 assumption of current laws and regulations. Federal 

taxes are not held constant but deflated as follows:

Federal Tax product, year = Current Federal Tax product /GDP Deflator year

Crude oil quality

In the LFMM, the quality of crude oil is characterized by average gravity and sulfur levels. Both domestic and imported crude oil are 

divided into nine categories as defined by the ranges of gravity and sulfur shown in Table 11.7.

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. In the LFMM, the domestic and foreign categories are the same, and the composite crudes 

for each category are derived from both domestic and foreign crude characteristics. For domestic crude oil, estimates of total regional 

production are made first, then shared out to each of the nine categories based on their API gravity and sulfur content. For imported 

crude oil, a separate supply curve is provided for each category.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 149

Liquid Fuels Market Module

Table 11.4. Petroleum product end-use markups by sector and Census Division

2010 dollars per gallon

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 0.66 0.77 0.42 0.33 0.65 0.40 0.37 0.33 0.48

Kerosene 0.18 0.42 0.17 0.31 0.29 0.23 0.34 0.65 1.39

Liquefied Petroleum Gases 0.08 1.57 1.00 0.68 1.41 1.26 1.02 1.09 1.23

Commercial Sector

Distillate Fuel Oil 0.40 0.26 0.15 0.05 0.15 0.14 0.13 0.12 0.12

Gasoline 0.16 0.16 0.15 0.13 0.14 0.16 0.14 0.18 0.19

Kerosene 0.18 0.40 0.13 0.31 0.28 0.29 0.30 0.60 1.39

Liquefied Petroleum Gases 0.69 0.86 0.70 0.70 0.78 0.82 0.76 0.83 0.70

Low-Sulfur Residual Fuel Oil 0.15 0.06 0.06 0.57 0.17 -0.10 0.06 1.12 1.40

Utility Sector

Distillate Fuel Oil 0.10 -0.01 0.07 0.01 0.17 0.13 -0.39 0.22 -0.14

Residual Fuel Oil1 -0.41 -0.21 -0.13 0.90 0.36 1.51 0.24 1.67 1.51

Transportation Sector

Distillate Fuel Oil 0.36 0.25 0.17 0.15 0.18 0.15 0.14 0.16 0.25

E852 0.15 0.14 0.12 0.11 0.12 0.12 0.09 0.16 0.15

Gasoline 0.18 0.18 0.15 0.14 0.14 0.16 0.12 0.20 0.19

High-Sulfur Residual Fuel Oil1 0.04 -0.18 1.09 -0.13 0.15 0.19 -0.50 0.00 0.47

Jet Fuel 0.01 0.02 0.01 0.01 0.01 0.01 0.01 0.00 0.02

Liquefied Petroleum Gases 0.60 0.84 1.10 1.11 0.84 1.12 1.01 1.00 1.00

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 0.24 0.25 0.22 0.17 0.28 0.22 0.16 0.17 0.17

Gasoline 0.18 0.17 0.15 0.14 0.14 0.16 0.14 0.19 0.19

Kerosene 0.00 0.06 0.02 -0.02 0.01 0.09 0.01 0.56 1.26

Liquefied Petroleum Gases 0.92 0.94 0.60 0.60 0.72 0.49 0.24 0.52 0.86

Low-Sulfur Residual Fuel Oil 0.07 -0.08 0.90 0.75 0.35 -0.01 0.08 -0.09 0.21

1

Negative 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

E85 refers to a blend of 85 percent ethanol (renewable) and 15 percent motor gasoline (non-renewable). To address cold starting issues, the percentage of

ethanol varies seasonally. The annual average ethanol content of 74 percent is used.

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 2010, Consumption (June 2011); EIA, State Energy Data 

2010: Prices and Expenditures (June 2011).
150 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Liquid Fuels Market Module

Table 11.5. State and local taxes on petroleum transportation fuels by Census Division, as of May 2011

2011 dollars per gallon

Year/Product

Census Division

New

England

Middle

Atlantic

East

North

Central

West

North

Central

South

Atlantic

East

South

Central

West

South

Central Mountain Pacific

Gasoline1 0.31 0.27 0.25 0.25 0.21 0.22 0.22 0.24 0.24

Diesel 0.28 0.32 0.23 0.22 0.22 0.19 0.19 0.23 0.32

Liquefied Petroleum Gases 0.13 0.13 0.19 0.21 0.20 0.19 0.15 0.15 0.06

E852 0.22 0.23 0.18 0.17 0.14 0.15 0.15 0.16 0.27

Jet Fuel 0.07 0.05 0.00 0.04 0.08 0.08 0.03 0.04 0.03

1

Tax also applies to gasoline consumed in the commercial and industrial sectors.

2

E85refers to a blend of 85 percent ethanol (renewable) and 15 percent motor gasoline (non-renewable). To address cold starting issues, the percentage of 

ethanol varies seasonally. The annual average ethanol content of 74 percent is used.

Source: “Compilation of United States Fuel Taxes, Inspection, Fees and Environmental Taxes and Fees,” Defense Energy Support Center, Editions 2011-09, 

May 18, 2011).

Table 11.6 Federal taxes, as of October 2011

nominal dollars per gallon

Product Tax

Gasoline 0.18

Diesel 0.24

Jet Fuel 0.04

Liquefied Petroleum Gases3 0.043

M851 0.09

E852 0.20

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 was 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). IRS Internal Revenue Bulletin 2006-43 available on the web at www.irs.gov/pub/irs-irbs/irb06-43.pdf

Table 11.7. Crude oil specifications

Crude Oil Categories

Sulfur

(percent)

Gravity

(degrees API)

Light Sweet <0.3 >35

Light Sour 0.3-1.1 >35

Medium Medium Sour 0.3-1.1 27-35

Medium Sour 1.1-2.6 27-35

Heavy Sweet 0.3-1.1 <27

Heavy Sour >2.6 <27

California 1.1-2.6 <27

Syncrude <0.3 27-35

DilBit/SynBit >2.6 <27

Source: Memorandum “Composite Crude Oils for the LFMM”, March 22, 2011, to Less Goudarzi, OnLocation, Inc, from Dave Hirshfeld, MathPro Inc. 

submitted to U.S. Energy Information Administration, Office of Energy Analysis, under contract number DT0001767, Oil and Gas Supply Module Development. 

Converted to ranges by OnLocation, Inc and EIA, 2011.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 151

Liquid Fuels Market Module

Capacity expansion

The LFMM allows for capacity expansion of all processing unit types including atmospheric distillation, vacuum distillation, 

hydrotreating, coking, fluid catalytic cracking, hydrocracking, and alkylation; however, atmospheric distillation expansion is not 

allowed in AEO2013. Capacity expansion occurs by processing unit, starting from regional capacities established using historical 

data.

Expansion occurs in LFMM 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 nine percent. The LFMM models capacity expansion using a new three-period planning 

approach similar to that used in the NEM Electricity Market Module (EMM). The first two periods contain a single planning 

year (current year and next year, respectively), and the third period represents a net present value of the next 19 years in the 

projection. The second and third planning periods work together to establish an economic plan for capacity expansion for the next 

NEM model year. In period 2, product demands and legislative requirements must be met exactly. Period 3 acts like a leverage in 

the capacity expansion decision for period 2, and is controlled by the discount rate assumptions. Larger discount rates increase 

the relative impacts from early periods and decrease the impacts of the later periods. The LFMM has the option to use multiple 

discount rates for the NPV calculation to represent various categories of risk. For AEO2013, the LFMM uses an 18 percent discount 

rate. Atmospheric Crude Unit (ACU) capacity, as well as downstream process unit capacity, under construction that is expected 

to begin operating in the future is added to existing capacities in their respective start year. Capacity expansion is also modeled 

for production of corn and cellulosic ethanol, biomass pyrolysis oil, biodiesel, renewable diesel, coal-to-liquids, gas-to-liquids, 

and biomass-to-liquids. The retirement and replacement of existing refining capacity due to economics or life is not currently 

represented in the LFMM.

Non-petroleum fuel technology characteristics

The LFMM explicitly models a number of liquid fuels technologies that do not require petroleum feedstock. These technologies 

produce both fuel-grade products for blending with traditional petroleum products, and alternative feedstock for the traditional 

petroleum refinery (Table 11.8).

Estimates of capital costs, operating cost, and process yield for these technologies are shown in Table 11.9. Costs are defined for 

2010 and are escalated in the LFMM using the GDP deflator. Owner’s Capital Cost is defined as the anticipated cost for a fully 

continuous, commercial scale plant. However, some of the technologies have not yet been proven at a commercial scale. As a 

result, a technology optimism factor is applied to the owner’s capital cost for the first plant of those technologies. For the next four 

plants, the capital cost decreases linearly such that the fifth plant is built at the owner’s capital cost defined in the table. Following 

this phase, capital cost is decreased at a rate corresponding to the maturity of the components that make up the technology, 

reflecting the principle of learning by doing. This principle is implemented in the LFMM in the same way as it is in the Electricity 

Market Module. Model parameters are shown in Table 11.10.

Table 11.8 Alternative fuel technology product type

Technology Product Type

Biochemical

Corn Ethanol Fuel Grade

Advanced Grain Ethanol Fuel Grade

Cellulosic Ethanol Fuel Grade

Thermocatalytic

Biomass-to-Liquids Fuel Grade/Refinery Feed

Pyrolysis Fuel Grade

Methyl Ester Biodiesel Fuel Grade

Nonester Renewable Diesel Fuel Grade

Coal/Biomass-to-Liquids (CBTL) Fuel Grade/Refinery Feed

Gas-to-Liquids (GTL) Fuel Grade/Refinery Feed

Coal-to-Liquids (CTL) Fuel Grade/Refinery Feed

Source: U.S. Energy Information Administration, Office of Energy Analysis.
152 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Liquid Fuels Market Module

Table 11.9. Non-petroleum fuel technology characteristics1

United States Gulf Coast

AEO2011 2020 Basis 

(2011$)

Online 

Year

Nameplate 

Capacity2

Base 

Overnight 

Capital

Contingency

 Factors3,4

Total 

Overnight 

Capital5

Total 

Variable 

Cost6

Fixed 

O&M7

Thermal 

Efficiency8

barrels/day $/daily barrel Project Optimism $/daily barrel $/barrel $/barrel

Energy 

Percent

Biochemical

Corn Ethanol - 6,523 $24,147 5% 0% $27,591 $68.83 - 54%

Advanced Grain Ethanol 2011 4,240 $26,562 5% 0% $30,350 $78.41 - 49%

Cellulosic Ethanol (1st plant) 2012 3,700 $99,948 5% 25% $142,755 $49.39 $12.41 28%

Cellulosic Ethanol (50th plant) - 3,700 $99,948 5% 25% $82,428 $49.39 $12.41 28%

Thermocatalytic

Coal/Biomass-to-Liquids 

(CBTL) 2015 30,000 $136,731 10% 2.5% $151,014 $12.46 $21.74 45%

Biomass–to-Liquids (1st plant) 2012 3,143 $242,560 10% 25% $326,703 $15.65 $39.11 47% 

Biomass–to-Liquids (50th 

plant) - 3,143 $242,560 10% 25% $246,608 $15.65 $39.11 47%

Pyrolysis (1st plant) 2014 687 $56,450 10% 25% $78,726 $31.12 $24.56 52% 

Pyrolysis (50th plant) 2014 687 $56,450 10% 25% $54,770 $31.12 $24.56 52% 

Coal–to-Liquids (CTL) 2015 50,000 $136,856 10% 0% $147,465 $12.68 $20.18 43%

Gas–to-Liquids (GTL)9 2017 34,000 $68,448 10% 0% $73,923 $48.36 $10.37 59% 

Methyl Ester Biodiesel (FAME) - 1,305 $26,747 5% 0% $28,085 $132.24 - 36% 

Nonester Renewable Diesel 

(NERD) 2010 2,000 $10,761 5% 2.5% $11,471 $129.81 $1.80 38%

1

This table is based on the AEO2011 Reference case projections for year 2020. 2

For all processes except corn ethanol and FAME biodiesel, annual capacity refers to the capacity of one plant as defined in the Petrolem Market Module of

NEMS. For corn ethanol and FAME biodiesel, annual capacity is the most common plant size as of 2008.

3

Contingency is defined by the American Association of Cost Engineers as a “specific provision for unforeseeable elements in costs within a defined project 

scope; particularly important where previous experience has shown that unforeseeable events which will increase costs are likely to occur.”

4The technology optimism factor is applied to the first four units of an unproven design, reflecting a demonstrated tendency to underestimate costs for a firstof-a-kind unit.

5

Total Overnight cost including contingency factors, excluding regional multipliers, learning effects, and interest charges.

6

Variable Operating and Maintenance costs (O&M) include sales of electricity to the grid and coproduct value where applicable.

7

For Corn Ethanol, Advanced Ethanol, and Biodiesel, fixed costs are included in Variable Operating Cost.

8

A soybean oil mass yield of 20% is assumed in the crush facility in order to compute yield. Efficiency is defined as the heat content of the liquid products 

divided by the heat content of the feedstock.

9

While these costs are for a Gulf Coast facility, the costs in other regions, particularly Alaska, are expected to be much higher.

Sources: The values shown in this table are developed by the Energy Information Administration, Office of Electricity, Coal, Nuclear, and Renewables 

Analysis, from analysis of reports and discussions with various sources from industry, government, and the Department of Energy Fuel Offices and National 

Laboratories. They are meant to represent the cost and performance of typical plants under normal operating conditions for each technology. Key sources 

reviewed are listed in “Notes and Sources” at the end of the chapter.

Variable operating cost includes the cost of feedstock, utility requirements, coproduct credit, and other costs that depend 

on capacity utilization, and they represent the expected costs to operate a fully continuous, commercial-scale plant for each 

technology. The breakdown is shown in Table 11.11.

Non-petroleum fuels market dynamics

In the LFMM, overnight capital costs are amortized and then added to variable and fixed costs in order to provide a cost of 

production [11]. As a result of this inclusion of capital cost in the cost of production, a given technology’s production cost has the 

potential to become more or less attractive relative to other technologies as plants are built.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 153

Liquid Fuels Market Module

While cost of production defines a basis for comparison, market competition is often defined by the required feedstock. For 

example, technologies requiring greases and oils (biodiesel and renewable diesel) compete with each other for that feedstock, 

limiting the overall market share of each technology. As a consequence of this and the Renewable Fuels Standard, cellulosic 

ethanol and Biomass to Liquids (BTL) technologies, which include Fischer-Tropsch and Pyrolysis, compete directly with each 

other. By contrast, technologies like Gas-to-Liquids and Coal-to-Liquids compete more directly with petroleum fuels, since their 

feedstock are more similar to petroleum and their fuels are not required by the RFS.

Table 11.10. Non-petroleum fuel technology learning parameters

Plants Built 1st of a Kind 5th of a Kind 32nd of a Kind

Cellulosic Ethanol

Mature 0% 33% 67% 0% 100%

Decline Factor 0.079 0.415 0.014 0.152 0.072

Cumulative Capacity 1.25 0.708 0.754 0.288 0.75

Biomass-to-Liquids (BTL)

Plant % 0% 0% 100% 0% 100%

Decline Factor 0.079 0.415% 0.014 0.152 0.072

Cumulative Capacity 1.250 1.128 1.126 0.000 1.126

Pyrolysis

Plant % 0% 18% 82% 0% 100%

Decline Factor 0.079 0.418 0.014 0.152 0.072

Cumulative Capacity 1.28 0.386 0.923 0.155 0.923

Source: U.S. Energy Information Administration.

Table 11.11. Non-petroleum fuel technology variable costs1

AEO2011 2020 Basis 

(Real 2011 $/barrel)Technology Total Feedstock Cost Net Utility Cost2 Coproduct Credit Other Variable3

Biochemical - - - - -

Corn Ethanol $68.83 $70.69 $10.91 $19.78 $7.01

Advanced Grain Ethanol $78.41 $89.73 -$3.99 $14.34 $7.01

Cellulosic Ethanol $49.39 $23.64 -$16.83 - $42.58

Thermocatalytic - - - - -

Coal/Biomass-to-Liquids 

(CBTL) $12.46 $18.16 $9.57 - $3.76

Biomass-to-Liquids (BTL) $15.65 $22.42 -$11.16 - $4.39

Pyrolysis $31.12 $20.54 $0.00 $3.64 $14.21

Coal-to-Liquids (CTL) $12.68 $18.39 -$9.57 - $3.86

Gas-to-Liquids (GTL) $48.36 $47.11 $0.00 - $1.25

Methyl Ester Biodiesel (FAME) $132.24 $124.87 $1.61 $0.74 $6.50

Nonester Renewable Diesel 

(NERD) $129.81 $127.27 $0.11 - $2.43

1

This table is based on the AEO2011 Reference case projections for year 2020. 2

Sales of electricity to the Grid from cogeneration are included in net utility costs.

3

These costs are specific to each technology. Often cooling water, catalyst, and chemicals are applied here. For cellulosic ethanol, this includes enzyme costs 

and therefore is expected to decrease over time.

Source: U.S. Energy Information Administration, Office of Electricity, Coal, Nuclear, and Renewables Analysis.
154 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Liquid Fuels Market Module

Biofuels supply

The LFMM provides supply functions on an annual basis through 2040 for ethanol produced from corn, non-corn grain, and 

cellulosic biomass to produce transportation fuel. The LFMM provides supply functions on an annual basis though 2040 for soy 

oil, other seed-based oils, and grease used as feedstock for biodiesel and renewable diiesel.

•	 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.

To model the Renewable Fuels Standard in EISA2007, several assumptions were required.

•	 The penetration of cellulosic ethanol into the market is limited before 2016 to several planned projects with aggregate 

nameplace capacity of approximately 250 million gallons per year. Planned capacity through 2016 for Pyrolysis and Biomass-toLiquids processes is not allowed to exceed 95 million gallons.

•	 Methyl ester biodiesel production contributes 1.5 credits towards the advanced mandate.

•	 Renewable diesel fuel, including that from Pyrolysis oil, and Fischer-Tropsch diesel contribute 1.7 credits toward the cellulosic 

mandate.

•	 Cellulosic drop-in gasoline contributes 1.54 credits toward the cellulosic mandate.

•	 Imported Brazilian sugarcane ethanol counts towards the advanced renewable mandate. Supply curves for sugarcane ethanol 

imports allow for substantial penetration by 2022 into the U.S. advanced fuel supply pool, after which sugarcane ethanol 

remains competitive due to its relatively low production cost, availability, and the expiration of the 54 cents/ gallon import tariff 

on Jan. 1, 2012. 

•	 Separate biofuel waivers can be activated by the EPA for each of the four RFS fuel categories. In years beyond 2022, the RFS 

mandate levels continue to increase toward 36 billion gallons

•	 It is assumed that biodiesel and BTL diesel may be consumed in diesel engines without significant infrastructure modification 

(either vehicles or delivery infrastructure).

•	 Ethanol is assumed to be consumed as E10, E15 or E85, with no intermediate blends. The cost of placing E85 pumps at the most 

economic stations is spread over diesel and gasoline.

•	 To accommodate the ethanol requirements in particular, transportation modes are expanded or upgraded for E10, E15 and E85, 

and it is assumed that most ethanol originates from the Midwest, with nominal transportation costs of a few cents per gallon. 

•	 For E85 dispensing stations, it is assumed the average cost of a retrofit and new station is about $45,000 per station.

Interregional transportation is assumed to be by rail, ship, barge, and truck, and the associated costs are included in LFMM.

Non-petroleum fossil fuel supply

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 them economic. The earliest start date for a GTL facility is set at 2018. 

It is also assumed that coal-to-liquids (CTL) facilities will be built when low-sulfur distillate prices are high enough to make them 

economic. Additionally, a process which allows co-firing of coal with biomass (CBTL) is modeled in the LFMM, but not made 

available for AEO2013. A 50,000-barrel-per-day CTL facility is assumed to cost about $7 billion in initial capital investment (2009 

dollars) while a 30,000-barrel-per-day CBTL facility is expected to cost about $4.4 billion. These facilities could be built near 

existing refineries. For the East Coast, potential CTL facilities could be built near the Delaware River basin; for the Central region, 

near the Illinois River basin or near Billings, Montana; and for the West Coast, in the vicinity of Puget Sound in Washington State. It 

is further assumed that CTL facilities can only be built after 2017.

Combined heat and power (CHP)

Electricity consumption at the refinery and other liquid fuels production facilities is a function of the throughput of each unit. 

Sources of electricity consist of refinery power generation, utility purchases, and CHP from other liquid fuels producers (including 

cellulosic/advanced ethanol, coal and biomass to liquids). Power generators and CHP plants are modeled in the LFMM linear 

program as separate units, and are allowed to compete along with purchased electricity. Operating characteristics for these 

electricity producers are based on historical parameters and available data. Sales to the grid or own use decisions are made on 

an economic basis within the LP solution. The price for electricity sales to the grid is set to the marginal energy price for baseload 

generation (provided by the EMM).
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 155

Liquid Fuels Market Module

Short-term methodology

Petroleum balance and price information for 2012 and 2013 are projected at the U.S. level in the Short-Term Energy Outlook, 

(STEO). The LFMM adopts the STEO results for 2012 and 2013, using regional estimates derived from the national STEO 

projections.

Legislation and regulation

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 on-highway diesel fuel. These are 

explicitly modeled in the LFMM. Reformulated gasoline represented in the LFMM meets the requirements of phase 2 of the 

Complex Model, except in the Pacific region where it meets CARB 3 specifications.

AEO2013 reflects “Tier 2” Motor Vehicle Emissions Standards and Gasoline Sulfur Control Requirements requires that the average 

annual sulfur content of all gasoline used in the United States be 30 ppm annual average.

AEO2013 reflects Heavy-Duty Engine and Vehicle Standards and Highway Diesel Fuel Sulfur Control Requirements. All highway 

diesel is required to contain no more than 15 ppm sulfur at the pump.

AEO2013 reflects nonroad locomotive and marine (NRLM) diesel requirements 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.

AEO2013 represents major provisions in the Energy Policy Act of 2005 (EPACT05) concerning the petroleum industry, including 

removal of the oxygenate requirement in RFG.

AEO2013 includes provisions outlined in the Energy Independence and Security Act of 2007 (EISA2007) concerning the 

petroleum industry, including a Renewable Fuels Standard (RFS) increasing total U.S. consumption of renewable fuels. In order to 

account for the possibility that RFS targets might be unattainable at reasonable cost, LFMM includes a provision for purchase of 

waivers. In essence, the LFMM RFS waivers function as maximum allowed RIN prices

AEO2013 includes the EPA Mobil Source Air Toxics (MSAT 2) rule which includes the requirement that all gasoline products 

(including reformulated and conventional gasoline) produced at a refinery during a calendar year will need to contain no more than 

0.62 percent benzene by volume. This does not include gasoline produced or sold in California, which is already covered by the 

current California Phase 3 Reformulated Gasoline Program.

AEO2013 includes California’s Low Carbon Fuel Standard which aims to reduce the Carbon Intensity (CI) of gasoline and diesel 

fuels in that State by about 10% respectively from 2012 through 2020. 

AEO2013 incorporates the cap-and-trade program within the California Assembly Bill (AB 32), the Global Warming Solutions Act 

of 2006. The program started January 1, 2012, with enforceable compliance obligations beginning in 2013. Petroleum refineries 

are given allowances (calculated in the LFMM) in the cap-and-trade system based on the volumetric output of aviation gasoline, 

motor gasoline, kerosene-type jet fuel, distillate fuel oil, renewable liquid fuels and asphalt. Suppliers of RBOB and Distillate Fuel 

Oil #1 and #2 are required to comply starting in 2015 if the emissions from full combustion of these products are greater than or 

equal to 25,000 MTCO2e in any year 2011-2014.

AEO2013 does not include mandates passed in 2010 by Connecticut, Maine, New York, and New Jersey that aim to lower the sulfur 

content of all heating oil to ultra-low-sulfur diesel over different time schedules. Nor does it include transition to a 2% biodiesel 

content in the case of Maine and Connecticut. These will be added next AEO cycle.

Due to the uncertainty surrounding compliance options, AEO2013 did not include any explicit modeling treatment of the 

International Maritime Organization’s “MARPOL Annex 6” rule covering cleaner marine fuels and ocean ship engine emissions.

Liquids fuels alternative cases

Low/no net imports case

In the reference case, maximum market penetration for gas-to-liquids (GTL) and coal-to-liquids (CTL) was defined at a nominal 

5 percent per year. Given the expectation for high net exports in this case, this maximum penetration rate was increased to 10 

percent per year. Capacity expansion of biomass pyrolysis production was also allowed to increase beyond the base build level, 

but at a higher investment cost. In addition, assumptions associated with E85 availability and E15 market penetration were more 

optimistic, such that E85 availability was nearly three times the reference case level in 2040, and E15 penetration was about 15% 

higher than the reference case in 2040. Additional changes were made in two NEMS models (OGSM and TDM) resulting in higher 

domestic crude and natural gas production (described in section “Oil and gas supply alternative cases”, High resource
156 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Liquid Fuels Market Module

case), and lower liquid fuels demand. As described in the “Transportation demand alternative cases” section in the TDM chapter, 

the methodology used to achieve lower demands includes the use of more optimistic assumptions about improvements in LDV 

fuel economy and reductions in LDV technology costs, lower vehicle miles traveled (VMT) due to changes in consumer behavior, 

an extension of the LDV CAFE standards beyond 2025 at an average annual rate of 1.4 percent through 2040, expanded market 

availability of LNG/CNG in heavy-duty trucks, rail and marine, and use of assumptions from the optimistic battery case (AEO2012) 

for electric vehicle battery and drivetrain costs.

High net imports case

No changes were made to the LFMM for this scenario. Changes were made in two NEMS models (OGSM and TDM) such that 

domestic crude production was lowered (described in section “Oil and gas supply alternative cases”, Low resource case), and the 

domestic liquid fuels demand was increased, as compared to the AEO2013 reference case. As described in the “Transportation 

demand alternative cases” section in the TDM chapter, an increase in domestic liquids fuels demand was achieve by assuming 

lower improvement in vehicle efficiency (driven by limits on technology improvement and non-enforcement of CAFE standards), 

and higher VMT.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 157

Liquid Fuels Market Module

Notes and sources

[1] U.S. Environmental Protection Agency, “Tier 2” Motor Vehicle Emissions Standards and Gasoline Sulfur Control 

Requirements, February 2000 (Washington, DC).

[2] Federal Register, U.S. 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] Ibid.

[5] U.S. Department of Agriculture, “USDA Agricultural Baseline Projections to 2019,” February 2009, www.ers.usda.

gov/publications/oce091.

[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 Combustion 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] Economic lifetime is 15 years for cellulosic ethanol, biomass Fischer-Tropsch, and Pyrolysis Oil. It is 20 years for all 

others. Required rate of return is calculated using a 60:40 debt to equity ratio and the capital asset pricing model for the 

cost of equity.

[12] www.agrievolution.com/atti/brasile_02.ppt.
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Coal Market Module
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U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 161

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 2013, DOE/EIA-M060(2013) (Washington, DC, 2013).

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. Combinations of 14 supply regions, nine coal types (unique groupings of thermal grade and sulfur content), and two 

mine types (underground and surface), result in 41 separate supply curves. 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, the cost of factor inputs (labor and fuel), and other mine supply costs.

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 2000, U.S. coal mining productivity increased at an average rate of 6.6 percent per year, from 1.93 to 6.99 

short tons per miner per hour. The major factors underlying these gains were inter-fuel price competition, structural change 

in the industry, and technological improvements in coal mining. Since 2000, however, growth in overall U.S. coal mining 

productivity has been negative, declining at a rate of 2.7 percent per year to 5.19 short tons per miner-hour in 2011. By region, 

productivity in all of the coal producing basins represented in the NEMS Coal Market Module has declined some during the 

past decade. In the Central Appalachian coal basin, which has been mined extensively, productivity declined by 50 percent 

between 2000 and 2011, corresponding to an average decline of 6.1 percent per year. While productivity declines have been 

more moderate at the highly productive mines in Wyoming’s Powder River Basin, overall coal mining productivity still fell by 

27 percent between 2000 and 2011, corresponding to an average rate of decline of 2.8percent per year.

•	 Over the projection period, labor productivity is expected to decline in a number of coal supply regions, reflecting the trend 

of the previous decade. 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 41 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 U.S. Energy Information Administration’s Form EIA-7A, “Coal Production 

and Preparation Report”. In the Reference case, overall U.S. coal mining labor productivity declines at rate of 1.4 percent per 

year between 2011 and 2040. Reference case projections of coal mining productivity by region are provided in Table 12.1.

•	 In the AEO2013 Reference case, the wage rate for U.S. coal miners increases by 1.0 percent per year and mine equipment 

costs are assumed to remain constant in 2011 dollars (i.e., increase at the general rate of inflation) over the projection period.

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 11) and 16 demand regions (Figure 12) for 49 demand subsectors. 

The projected levels of coal-to-liquids, industrial steam, coking, and residential/commercial coal demand are provided by the 

liquid fuel 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. supply availability, endogenously 

determined U.S. import demand, and exogenously determined world coal import demands (non-U.S.).
162 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Coal Market Module

Table 12.1. Coal mining productivity by region

short tons per miner hour

Supply Region 2011 2020 2025 2030 2035 2040

Average Annual 

Growth 11-40

Northern Appalachia 3.24 2.76 2.61 2.47 2.38 2.29 -1.2%

Central Appalachia 2.09 1.26 1.06 0.90 0.80 0.73 -3.6%

Southern Appalachia 1.68 1.18 1.04 0.91 0.85 0.79 -2.6%

Eastern Interior 4.04 3.81 3.67 3.53 3.44 3.36 -0.6%

Western Interior 2.38 1.96 1.85 1.75 1.72 1.68 -1.2%

Gulf Lignite 7.23 5.33 4.74 4.22 3.92 3.63 -2.3%

Dakota Lignite 12.14 10.75 10.27 9.82 9.53 9.24 -0.9%

Western Montana 16.41 12.48 11.46 10.87 10.31 9.94 -1.7%

Wyoming, Northern Powder River Basin 30.92 24.82 22.78 20.91 19.78 18.72 -1.7%

Wyoming, Southern Powder River Basin 34.50 27.69 25.41 23.33 22.07 20.88 -1.7%

Western Wyoming 6.25 5.18 4.90 4.88 4.94 4.77 -0.9%

Rocky Mountain 5.31 4.19 3.82 3.49 3.27 3.08 -1.9%

Arizona/New Mexico 8.39 7.13 6.99 6.19 5.90 5.65 -1.4%

Alaska/Washington 6.48 5.32 4.93 4.57 4.35 4.13 -1.5%

U.S. Average 5.19 4.43 4.05 3.76 3.60 3.47 -1.4%

Source: U.S. Energy Information Administration, AEO2013 National Energy Modeling System run REF2013.D102312A.

The key assumptions underlying the coal distribution modeling are:

•	 Base-year (2011) 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-923, “Power Plant Operations Report”, and the 

U.S. Bureau of the Census’ “Monthly Report EM-545”. Minemouth price data are from Form EIA-7A, “Coal Production and 

Preparation 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 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, calculated econometrically, are measures of the change in average transportation rates 

for coal shipments on a tonnage basis, which occurs between successive years for 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 

east index is a function of railroad productivity, the user cost of capital for railroad equipment, and national average diesel fuel 

price. The user cost of capital for railroad equipment is calculated from the producer price index (PPI) for railroad equipment, 

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. In calculating the 

user cost of capital, three percentage points are added to the cost of borrowing in order to account for the possibility that 

greenhouse gas emissions may be regulated in the future. The west index is a function of railroad productivity, investment, 

and the western share of national coal consumption. The indices are universally applied to all domestic coal transportation 

movements within the CMM. In the AEO2013 Reference case, eastern coal transportation rates are projected to be 3 percent 

higher by 2020 but then return to 2011 levels after 2025. Western rates fall slightly early in the projection but are 1 percent 

higher than 2011 in 2040.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 163

Coal Market Module

Figure 11. Coal Supply Regions

Source: U.S. Energy Information Administration, Office of Energy Analysis
164 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Coal Market Module

•	 For the projection period, the explanatory variables are assumed to have varying impacts on the calculation of the indices.

For the west, investment is the analogous variable to the user cost of capital of railroad equipment. The investment value 

and the PPI for rail equipment, which is used to derive the user cost of capital increase with an increase in national ton-miles 

(total tons of coal shipped multiplied by the average distance). Increases in investment (west) or the user cost of capital 

for railroad equipment (east) cause projected transportation rates to increase. For both the east and the west, any related 

financial savings due to productivity improvements are assumed to be retained by the railroads and are not passed on to 

shippers in the form of lower transportation rates. For that reason, productivity is held flat for the projection period for both 

regions. For the east for the projection period, diesel fuel is removed from the equation in order to avoid double-counting 

the influence of diesel fuel costs with the impact of the fuel surcharge program. The transportation rate indices for seven 

AEO2013 cases are shown in Table 12.2.

Figure 12. Coal Demand Regions

Source: U.S. Energy Information Administration, Office of Energy Analysis
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 165

Coal Market Module

Table 12.2. Transportation rate multipliers

constant dollar index, 2011=1.000

Scenario Region: 2011 2020 2025 2030 2035 2040

Reference Case East 1.000 1.0275 1.0087 1.0031 1.0039 1.0033

West 1.000 0.9895 1.0071 1.0160 1.0194 1.0131

High Oil Price East 1.000 1.0420 1.0137 1.0097 1.0111 1.0133

West 1.000 0.9836 0.9997 1.0056 1.0058 0.9941

Low Oil Price East 1.000 1.0178 1.0019 1.0029 1.0014 0.9978

West 1.000 0.9984 1.0120 1.0228 1.0330 1.0363

High Economic Growth East 1.000 1.0287 0.9990 0.9950 0.9944 0.9910

West 1.000 1.0045 1.0215 1.0322 1.0307 1.0264

Low Economic Growth East 1.000 1.0392 1.0269 1.0192 1.0198 1.0159

West 1.000 0.9707 0.9862 0.9887 0.9946 0.9930

High Coal Cost East 1.000 1.0700 1.1200 1.1600 1.2000 1.2400

West 1.000 1.0600 1.1200 1.1800 1.2300 1.2700

Low Coal Cost East 1.000 0.9500 0.8900 0.8400 0.8000 0.7500

West 1.000 0.9200 0.8900 0.8500 0.8100 0.7600

Source: Projections: U.S. Energy Information Administration, National Energy Modeling System runs REF2013.D102312A, HIGHPRICE.D110912A, 

LOWPRNOGTL. D112012A, HIGHMACRO.D110912A, LOWMACRO.D110912A, HCCST13.D112112A, LCCST13.D112112A. Based on methodology described in 

Coal Market Module of the National Energy Modeling System 2013, DOE/EIA-M066(2013) (Washington, DC, 2013).

•	 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, recommended that the railroads agree to develop some consistencies among 

their disparate programs and likewise recommended closely linking the charges to actual fuel use. The STB cited the use of a 

mileage-based program as one means to more closely estimate actual fuel expenses.

•	 For AEO2013, 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 (2011) coal contracts between coal 

producers and electricity generators are estimated on the basis of receipts data reported by generators on the EIA-923, “Power 

Plant Operations 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 from information reported on the Form EIA-923, “Power Plant Operations Report”, historical patterns of coal use, and 

information obtained from various coal and electric power industry publications and reports.
166 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Coal Market Module

•	 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 845 MW (300 MW for the grid and 

545 MW to support the conversion process) and the capability of producing 50,000 barrels of liquid fuels 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 and for the production of power sold to the grid. For AEO2013, coal-biomass-to-liquids (CBTL) are not modeled. 

CTL facilities produce paraffinic naptha used in plastics production and blendable naptha used in motor gasoline (together 

about 43 percent of the total by volume) and distillate fuel oil (about 57 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 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. 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. 

The key assumptions underlying coal export modeling are:

•	 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. 

The data inputs for coal trade modeling are:

•	 World steam and metallurgical coal import demands for the AEO2013 cases are shown in Tables 12.3 and 12.4. U.S. coal 

exports are determined, in part, by these estimates of world coal import demand. 

•	 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 typical vessel sizes and route distances in thousands of nautical 

miles between supply and demand regions.

Coal quality

Each year the values of base year coal production, heat, sulfur and mercury content and carbon dioxide emissions for each coal 

source in CMM are calibrated to survey data. Surveys used for this purpose are the Form EIA-923, a survey of the origin, cost and 

quality of fossil fuels delivered to generating facilities, the Form EIA-3, which records the origin, cost, and quality of coal delivered 

to U.S. manufacturers, transformation and processing plants, and commercial and institutional users, and the Form EIA-5, 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. Mercury content data for coal 

by supply region and coal type, in units of pounds of mercury per trillion Btu, shown in Table 71, were derived from shipmentlevel data reported by electricity generators to the Environmental Protection Agency in its 1999 Information Collection Request. 

Carbon dioxide emission factors for each coal type are shown in Table 12.5 in pounds of carbon dioxide emitted per million Btu 

[4].
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 167

Coal Market Module

Table 12.3. World steam coal import demand by import region

million metric tons of coal equivalent

2011 2020 2025 2030 2035 2040

The Americas 33.1 26.1 31.3 35.6 58.0 78.6

 United States3 9.6 0.0 3.0 3.1 16.8 28.5

 Canada 3.7 3.0 2.8 2.8 2.8 2.8

 Mexico 4.8 5.8 6.5 7.2 10.0 12.9

 South America 15.0 17.3 19.0 22.5 28.4 34.4

Europe 148.8 177.7 176.4 174.9 174.6 174.7

 Scandinavia 13.3 6.5 5.8 5.0 4.5 4.1

 U.K./Ireland 27.0 29.0 29.0 30.4 31.7 33.1

 Germany/Austria 22.0 38.6 37.6 36.6 35.6 34.7

 Other NW Europe 28.9 22.1 20.9 20.0 19.2 18.4

 Iberia 13.2 18.1 18.0 17.7 16.3 15.0

 Italy 11.9 25.4 27.2 27.2 27.2 27.2

 Med/E Europe 32.5 38.0 37.9 38.0 40.1 42.2

Asia 478.9 563.2 604.9 658.8 706.0 749.7

 Japan 88.8 82.7 79.4 79.2 76.3 73.5

 East Asia 128.9 129.0 131.2 139.7 149.4 155.3

 China/Hong Kong 137.4 183.6 207.0 228.8 242.8 256.8

 ASEAN 41.9 52.1 61.0 68.4 76.8 85.3

 Indian Sub 81.9 115.8 126.3 142.7 160.7 178.8

TOTAL 660.8 767.0 812.6 869.3 938.6 1,003.0

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 2011.

3

Excludes imports to Puerto Rico and the U.S. Virgin Islands.

Notes: One “metric ton of coal equivalent” equals 27.78 million Btu. Totals may not equal sum of components due to independent rounding. 
168 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Coal Market Module

Table 12.4. World metallurgical coal import demand by import region

million metric tons of coal equivalent

2011 2020 2025 2030 2035 2040

The Americas 21.1 35.8 43.9 54.4 67.8 81.3

 United States 1.3 1.3 1.3 1.3 1.3 1.3

 Canada 4.0 3.5 3.5 3.4 3.3 3.2

 Mexico 1.6 1.0 1.0 1.0 1.0 1.0

 South America 14.2 29.9 38.1 48.7 62.2 75.8

Europe 61.9 61.7 61.4 61.5 61.4 61.4

 Scandinavia 3.2 2.7 2.7 2.7 2.7 2.7

 U.K./Ireland 8.2 7.3 7.3 7.3 7.3 7.4

 Germany/Austria 10.6 11.4 11.3 11.3 11.3 11.3

 Other NW Europe 13.6 14.7 14.5 14.4 14.3 14.1

 Iberia 2.9 3.9 3.8 3.8 3.6 3.5

 Italy 9.7 7.4 7.3 7.3 7.3 7.3

 Med/E Europe 13.7 14.3 14.5 14.7 14.9 15.1

Asia 171.0 232.2 245.4 249.6 256.9 264.2

 Japan 72.1 74.8 70.9 64.1 61.2 58.3

 East Asia 38.7 37.3 38.5 39.6 40.8 42.0

 China/Hong Kong 27.2 60.9 62.9 65.0 67.2 69.4

 ASEAN4 0.0 0.0 0.0 0.0 0.0 0.0

 Indian Sub 33.0 59.2 73.1 80.9 87.7 94.5

TOTAL 265.6 292.8 311.7 333.3 347.9 368.4

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 2011. 

3

 Excludes imports to Puerto Rico and the U.S. Virgin Islands. 

4 Malaysia, Phillipines, and Thailand are not expected to import significant amounts of metallurgical coal in the projection. 

Notes: One “metric ton of coal equivalent” equals 27.78 million Btu. Totals may not equal sum of components due to independent rounding. 

Legislation and regulations

The AEO2013 is based on current laws and regulations in effect before October 31, 2012. The Mercury Air Toxics Standard 

MATS), finalized in December 2011, is included in the AEO2013 Reference case as well as the Clean Air Interstate Rule (CAIR).

MATS sets emissions limits for mercury, other heavy metals, and acid gases from coal and oil power plants that are 25 MW or 

greater. Since generators are expected to request one-year extensions for compliance, MATS is assumed to be fully in place by 

2016 rather than 2015 as stated in the regulation.

CAIR is a cap and trade program that regulates sulfur dioxide and nitrous oxide emissions from fossil fueled power plants with 

a nameplate capacity greater than 25 megawatts in 27 States and the District of Columbia. Initial implementation of CAIR for 

NOX occurred in 2009 and for SO2, in 2010, and both caps will be subject to further tightening in 2015. The AEO2013 includes 

trading and banking of allowances consistent with CAIR’s provisions. States covered by CAIR can trade allowances amongst 

themselves or with non-CAIR states participating in the Clean Air Act Amendment Title IV program. Non-CAIR state allowances 

are considered less valuable than CAIR state allowances and are traded at a discounted rate. For a more complete description of 

the CAIR program refer to the Legislation and Regulations section. 
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 169

Coal Market Module

Table 12.5. Production, heat content, sulfur, mercury and carbon dioxide emission factors by coal type and region

Coal Supply Region States

Coal Rank and Sulfur 

Level Mine Type

2011 

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

PA, OH, MD, 

WV (North) Metallurgical Underground 18.2 26.30 0.88 N/A 204.7

Mid-Sulfur 

Bituminous All 36.7 25.21 1.40 11.17 204.7

High-Sulfur 

Bituminous All 78.0 24.68 2.71 11.67 204.7

Waste Coal (Gob 

and Culm) Surface 12.5 11.60 3.57 63.9 204.7

Central Appalachia

KY (East), WV 

(South), VA, TN 

(North) Metallurgical Underground 61.7 26.30 0.66 N/A 206.4

Low-Sulfur 

Bituminous All 14.0 24.72 0.54 5.61 206.4

Mid-Sulfur 

Bituminous All 109.3 24.64 0.92 7.58 206.4

Southern Appalachia AL, TN (South) Metallurgical Underground 10.2 26.30 0.59 N/A 204.7

Low-Sulfur 

Bituminous All 0.4 25.58 0.49 3.87 204.7

Mid-Sulfur 

Bituminous All 8.7 24.37 1.32 10.15 204.7

East Interior

IL, IN, KY(West), 

MS

Mid-Sulfur 

Bituminous All 23.3 23.00 1.16 5.6 203.1

High-Sulfur 

Bituminous All 93.2 22.82 2.60 6.35 203.1

Mid-Sulfur Lignite Surface 2.7 10.49 0.91 14.11 216.5

West Interior

IA, MO, KS, AR, 

OK, TX (Bit)

High-Sulfur 

Bituminous Surface 1.8 20.95 1.71 21.55 202.8

Gulf Lignite TX (Lig), LA Mid-Sulfur Lignite Surface 38.9 13.41 1.17 14.11 212.6

High-Sulfur Lignite Surface 10.8 12.31 2.81 15.28 212.6

Dakota Lignite ND, MT (Lig) Mid-Sulfur Lignite Surface 28.6 13.22 1.22 8.38 219.3

Western Montana MT (Sub)

Low-Sulfur 

Subbituminous Underground 5.1 20.54 0.67 5.06 215.5

Low-Sulfur 

Subbituminous Surface 19.2 17.88 0.36 5.06 215.5

Mid-Sulfur 

Subbituminous Surface 17.3 17.02 0.79 5.47 215.5

Northern Wyoming

WY (Northern 

Powder River 

Basin)

Low-Sulfur 

Subbituminous Surface 172.6 16.79 0.37 7.08 214.3

Mid-Sulfur 

Subbituminous Surface 2.4 16.26 0.77 7.55 214.3

Southern Wyoming

WY (Southern 

Powder River 

Basin

Low-Sulfur 

Subbituminous Surface 251.1 17.63 0.29 5.22 214.3
170 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Coal Market Module

Table 12.5. Production, heat content, sulfur, mercury and carbon dioxide emission factors by coal type and region (cont)

Coal Supply Region States

Coal Rank and Sulfur 

Level Mine Type

2011 

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)

Western Wyoming

WY (Other 

basins, excluding 

Powder River 

Basin

Low-Sulfur 

Subbituminous Underground 3.0 18.51 0.64 2.19 214.3

Low-Sulfur 

Subbituminous Surface 3.7 19.12 0.48 4.06 214.3

Mid-Sulfur 

Subbituminous Surface 5.9 19.12 0.82 4.35 214.3

Rocky Mountain CO, UT Metallurgical Underground * 26.30 0.43 N/A 209.6

Low-Sulfur 

Bituminous Underground 41.1 21.86 0.47 3.82 209.6

Low-Sulfur 

Subbituminous Surface 5.4 19.81 0.49 2.04 212.8

Southwest AZ, NM

Low-Sulfur 

Bituminous Surface 8.0 21.56 0.59 4.66 207.1

Mid-Sulfur 

Subbituminous Surface 18.1 18.26

 

1.00 7.18 209.2

Mid-Sulfur 

Bituminous Underground 4.0 19.22 0.71 7.18 207.1

Northwest WA, AK

Low-Sulfur 

Subbituminous Surface 2.1 15.76 0.25 6.99 216.1

*indicates less than 50,000 tons of production in 2011. N/A = not available.

Source: U.S. Energy Information Administration, Form EIA-3, “Quarterly Coal Consumption and Quality Report Manufacturing and Transformation/Processing Coal 

Plants and Commercial and Institutional Coal Users”; Form EIA-5, “Quarterly Coal Consumption and Quality Report, Coke Plants”; Form EIA-7A, “Coal Production 

and Preparation Report”, and Form EIA-923, “Power Plant Operations Report”. U.S. Department of Commerce, Bureau of the Census, “Monthly Report EM-545.” 

U.S. Environmental Protection Agency, Emission Standards Division, Information Collection Request for Electric Utility Steam Generating Unit,

Mercury Emissions Information Collection Effort (Research Triangle Park, NC, 1999). U.S. Environmental Protection Agency, “ANNEX 2 Methodology and Data for 

Estimating CO2 Emissions from Fossil Fuel Combustion”, Table A-38, web site http://epa.gov/climatechange/emissions/downloads11/US-GHG-Inventory-2011- 

Annex-2.pdf.

The Energy Improvement and Extension Act of 2008 (EIEA) and Title IV, under Energy and Water Development, of the American 

Recovery and Revitalization Act of 2009 (ARRA), together, are assumed to result in about 1 gigawatt of advanced coal-fired 

capacity with carbon capture and sequestration by 2017.

EIEA was passed in October 2008 as part of the Emergency Economic Stabilization Act of 2008. Subtitle B provides investment 

tax credits for various projects sequestering CO2. Subtitle B, which extends the phase-out of payments by coal producers to the 

Black Lung Disability Trust Fund from 2013 to 2018, is also modeled in the AEO2013.

Title IV under ARRA provides $3.4 billion for additional research and development on fossil energy technologies. This includes 

$800 million to fund projects under the Clean Coal Power Initiative (CCPI) program, focusing on projects that capture and 

sequester greenhouse gases or use captured carbon dioxide for enhanced oil recovery (EOR). The Hydrogen Energy California 

Project and a new plant to be built by Summit Texas Clean Energy in Texas both include efforts to use captured carbon dioxide for 

EOR.

Title XVII of the Energy Policy Act of 2005 authorizes loan guarantees for projects that avoid, reduce, or sequester greenhouse 

gasses. For AEO2013, the 1 gigawatt of advanced coal-fired capacity with carbon capture and sequestration assumed for EIEA and 

ARRA are also assumed to benefit from these loan guarantees.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 171

Coal Market Module

Beginning in 2008, electricity generating units of 25 megawatts or greater were required to hold an allowance for each ton of CO2

emitted in nine Northeastern States as part of the Regional Greenhouse Gas Initiative (RGGI). The States currently participating in 

RGGI include Connecticut, Maine, Maryland, Massachusetts, Rhode Island, Vermont, New York, New Hampshire, and Delaware. 

RGGI is modeled in AEO2013 as an emissions reduction program for the Central Atlantic region.

AEO2013 includes representation of California Assembly Bill 32 (AB32), the Global Warming Solution Act of 2006. As modeled, 

AB32 imposes a limit on power sector CO2 emissions for electricity sector power plants serving California beginning in 2012 and 

declining at a uniform annual rate through 2020.

Coal alternative cases

Coal Cost cases

In the Reference case, coal mine labor productivity is assumed to decline on average by 1.4 percent per year through 2040. Miner 

wage rates increase by about 0.9 percent per year, and mine equipment costs remain constant in 2011 dollars. Eastern coal 

transportation rates are projected to be similar to 2011 levels in 2040. Western rates are 1 percent higher in 2040 than in 2011. 

In two alternative coal cost cases, productivity, average miner wages, equipment cost, and transportation rate assumptions were 

modified for 2013 through 2040 in order to examine the impacts on U.S. coal supply, demand, distribution and prices.

In the Low Coal Cost case, coal mine labor productivity is assumed to increase at an average rate of 0.9 percent per year through 

2040. Coal mining wages, mine equipment costs, and other mine supply costs all are assumed to be about 25 percent lower in 

2040 in real terms in the Low Coal Cost case than in the Reference case. Coal transportation rates, excluding the impact of fuel 

surcharges, are assumed to be 25 percent lower by 2040.

In the High Coal Cost case, coal mine labor productivity is assumed to decline at an average rate of 4.3 percent per year through 

2040. Coal mining wages, mine equipment costs, and other mine supply costs all are assumed to be about 32 percent higher in 

2040 in real terms in the High Coal Cost case than in the Reference case. Compared to the Reference case, coal transportation 

rates are assumed to be 25 percent higher by 2040. 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.

No Greenhouse Gas Concern case

In the Reference case, to reflect the market reaction to potential future GHG regulation, a 3-percentage-point increase in the cost 

of capital for investments in new coal-fired power plants without carbon capture and sequestration technology is assumed. These 

assumptions affect cost evaluations for the construction of new capacity but not the actual operating costs for new existing plants. 

This adjustment was first implemented for AEO2009. Beginning with AEO2012, a 3-percentage-point increase in the cost of 

capital for investments in retrofits at existing coal plants is also applied for emission control equipment (excluding CCS).

The No GHG concern case excludes the 3-percentage point increase in the cost of capital.
172 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Coal Market Module

Notes and sources

[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] U.S. Environmental Protection Agency, “Climate Change—Regulatory Initiative: Greenhouse Gas Reporting Program”, 

website www.epa.gov/climatechange/emissions/
Renewable Fuels Module
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U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 175

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 wind [1].

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. Commercial market penetration of renewable technologies varies widely. Hydroelectric 

power, one of the oldest electric generation technologies, accounted for roughly 8 percent of electric power generation in 2011; 

newer power systems using biomass, geothermal, LFG, solar, or wind energy contribute a combined 5 percent.

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. Because some types of biomass fuel can be used for either electricity 

generation or for the production of liquid fuels, such as ethanol, there is also some interaction with the Petroleum Market 

Module (PMM), which contains additional representation of some biomass feedstocks that are used primarily for liquid fuels 

production.

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 description in the “Commercial Demand 

Module” and “Residential Demand Module” sections of the report. Descriptions for biomass energy production in industrial 

settings, such as the pulp and paper industries can be found in the “Industrial 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, AEO2013 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 these projections are found in the residential, commercial, industrial, and petroleum marketing module 

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 the respective resource. A 

set of technology cost and performance values is provided directly to the EMM and is central to the build and dispatch decisions 

of the EMM. The technology cost and performance values are summarized in Table 8.2 in the chapter discussing the EMM. 
176 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Renewable Fuels Module

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 www.eia.gov/analysis/model-documentation.cfm.

Also assumed to affect all new capacity types are costs associated with construction commodities. Through much of the period 

from 2000 to 2008, the installed cost for most new plants was observed to increase. Although several factors contributed to this 

cost escalation, some of which may be more or less important to specific types of new capacity, much of the overall cost increase 

was correlated with increases in the cost of construction materials, such as bulk metals, specialty metals, and concrete. Capital 

costs are specifically linked to the projections for the metals producer price index found in the Macroeconomic Module of NEMS. 

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.

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 2011, DOE/ 

EIA-M069(2011) (Washington, DC, 2011).

Solar Electric Submodule

Background

The Solar Electric Submodule currently includes both solar thermal (also referred to as “concentrating solar power” or CSP) and 

photovoltaic (PV), technologies. The representative solar thermal technology assumed for cost estimation is a 100-megawatt 

central-receiver tower without integrated energy storage, while the representative solar PV technology is a 150-megawatt 

array of flat plate PV modules using single-axis tracking. PV is assumed available in all EMM regions, while CSP is available 

only in the Western regions with the arid atmospheric conditions that result in the most cost-effective capture of direct 

sunlight. Cost estimates for both technologies are based on a forthcoming report by SAIC to be published in early 2013, see: 

the “Documentations & Assumptions” section of www.eia.gov/forecasts/aeo/er/index.cfm). Technology- specific performance 

characteristics are obtained from information provided by the National Renewable Energy Laboratory (NREL). 

Assumptions 

• 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. In addition, the current 30-percent ITC, scheduled to expire at the end of 2016, is also 

represented to qualifying new capacity installations.

• Existing capacity and planned capacity additions are based on EIA survey data from the Form EIA-860, “Annual Electric 

Generator Report” and Form EIA-860M, “Monthly Update to the Annual Electric Generator Report”. Planned capacity additions 

under construction or having all regulatory approvals and having an expected completion date prior to the expiration of the 

30-percent ITC were included in the model’s planned capacity additions, according to respondents’ planned completion dates.

• 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 based on climate and latitude. 

• 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 regions where CSP technology is not modeled, the level of direct, normal insolation (the kind needed for that technology) is 

assumed to be insufficient to make that technology commercially viable through the projection horizon. 
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 177

Renewable Fuels Module

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 15 mph 

at a hub-height of 80 m, and wind speeds are categorized by annual average wind speed based on a classification system 

originally from the Pacific Northwest Laboratory (see http://rredc.nrel.gov/wind/pubs/atlas/tables/1-1T.html). The RFM tracks 

wind capacity (megawatts) by resource quality and costs within a region, and moves to the next best wind resource when 

one category is exhausted. Wind resource data on the amount and quality of wind per EMM region come from the National 

Renewable Energy Laboratory [2]. The technological performance, cost, and other wind data used in NEMS are based on a 

forthcoming report by SAIC to be published in early 2013, see: the “Documentations & Assumptions” section of www.eia.gov/

forecasts/aeo/er/index.cfm). 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 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 contiguous 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 titled, “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, as 

the best sites are utilized, (2) increasing cost of upgrading existing local and network distribution and transmission lines to 

accommodate growing quantities of remote 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 by 10, 25, 50 percent, and finally 100 percent, to represent the aggregation of these factors

• Proportions of total wind resources in each category vary by EMM region. For all EMM regions combined, about 1 percent of 

windy land (107 GW of 11,600 GW in total resource) is available with no cost increase, 3.4 percent (390 GW) is available with 

a 10 percent cost increase, 2 percent (240 GW) is available with a 25-percent cost increase, and over 90 percent is available 

with a 50- or 100-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 for each wind class are calculated as a function of overall wind market growth. The capacity factors are 

assumed to be limited to about 50 percent for a typical Class 6 site. As better wind resources are depleted, capacity factors 

are assumed to go down, corresponding with the use of less desirable sites. By 2040, the typical wind plant build will have 

a somewhat lower capacity factor than those found in the best wind resource areas. Capacity factors in the Reference case 

increase to about 45 percent in the best wind class resulting from taller towers, more reliable equipment, and advanced 

technologies, although, as noted, these may not represent the best available sites because of other site-specific factors.
178 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Renewable Fuels Module

• AEO2013 does not allow plants constructed after 2012 to claim the federal Production Tax Credit (PTC), a 2.2-cent-per-kilowatt- hour tax 

incentive for wind that wasset to expire on December 31, 2012 for wind only. After completion of this case, the law was changed to allow 

wind plants under construction by December 31, 2013 to qualify for the PTC. 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 a 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. A technological optimism factor (see EMM documentation: www.eia.gov/ analysis/modeldocumentation.cfm) is included for offshore wind to account for the substantial cost of establishing the unique construction 

infrastructure required for this technology.

Geothermal-Electric Power Submodule

Background

Beginning in AEO2011, all geothermal supply curve data came from the National Renewable Energy Laboratory’s updated U.S. 

geothermal supply curve assessment. The report, released in February 2010, assigns cost estimates to the U.S. Geological Survey’s 

(USGS) 2008 geothermal resource assessment. Some data from the 2006 report, “The Future of Geothermal Energy,” prepared 

by the Massachusetts Institute of Technology, was also incorporated into the NREL report; however, this would be more relevant 

to deep, dry, and unknown geothermal resources, something which EIA did not include in its supply curve. NREL took the USGS 

data and used the Geothermal Electricity Technology Evaluation Model (GETEM), an Excel-based techno-economic systems 

analysis tool, to estimate the costs [3]. Only resources with temperatures above 110 degrees Celsius were considered. There are 

approximately 125 of these known, hydrothermal resources which EIA used in its supply curve. Each of these sites also has what 

NREL classified as “near-field enhanced geothermal energy system potential” which are in areas around the identified site that lack 

the permeability of fluids that are present in the hydrothermal potential. Therefore, there are 250 total points on the supply curve 

since each of the 125 hydrothermal sites has corresponding enhanced geothermal system (EGS) potential.

In the past, EIA cost estimates were broken down into cost-specific components. Unfortunately, this level of detail was not available 

in the NREL data. A site-specific capital cost and fixed operations and maintenance cost were provided. Both types of technology, 

both flash and binary, are also included with capacity factors ranging from 90 to 95 percent. While the source of the data was 

changed beginning in AEO2011, the site-by-site matrix input that acts as the supply curve has been retained.

Assumptions 

• Existing and identified planned capacity data are obtained directly by the EMM from Form EIA-860 and Form EIA-860m. 

• 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 December 2013 when the 2.2-cent production tax credit is available to this technology and is 

assumed chosen instead. Projects that have begun construction and are beyond the exploratory drilling phase by that date are 

eligible for this production tax credit. 

• Plants are not assumed to retire unless their retirement is reported to EIA. The 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. 
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 179

Renewable Fuels Module

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 in the electricity 

sector is represented in the EMM. Fuel costs are calculated in NEMS and passed to EMM, while capital and operating costs and 

performance characteristics are assumed as shown in Table 8.2. 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 and Form EIA-860m. 

• The conversion technology represented is an 80-MW dedicated combustion plant. The cost estimates for this technology are 

based on a forthcoming report by SAIC to be published in early 2013, see: the “Documentations & Assumptions” section of 

www.eia.gov/forecasts/aeo/er/index.cfm).

• Biomass co-firing 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. Feedstock potential from agricultural residues and dedicated energy crops are calculated from a version of the Policy 

Analysis (POLYSYS) agricultural model that uses the same oil prices as the rest of NEMS. Forestry residues are calculated from 

inventories conducted by the U.S. Forest Service and Oak Ridge National Laboratory. 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 existing cropland. POLYSYS 

assumes that the additional cropland needed for energy crops will displace existing pasturelands. The lands in the Conservation 

Reserve Program are preserved [7]. The maximum amount of resources in each coal region is shown in Table 13.1.

Table 13.1. Maximum U.S. biomass resources, by coal demand region and type in 2035

trillion Btu

Coal Demand 

Region States Agricultural Sector Forestry Residue

Urban Wood 

Waste/Mill 

Residue

1 (NE) CT, MA, ME, NH, RI, VT 6 115 40

2 (YP) NY, PA, NJ 164 162 88

3 (S1) WV, MD, DC, DE 174 91 37

4 (S2) VA, NC, SC 167 364 58

5 (GF) GA, FL 104 358 87

6 (OH) OH 266 60 37

7 (EN) IN, IL, MI, WI 1323 155 81

8 (KT) KY, TN 353 167 43

9 (AM) AL, MS 194 332 43

10 (C1) MN, ND, SD 279 57 31

11 (C2) IA, NE, MO, KS 2183 77 45

12 (WS) TX, LA, OK, AR 689 269 86

13 (MT) MT, WY, ID 78 61 26

14 (CU) CO, UT, NV 32 59 51

15 (ZN) AZ, NM 12 73 41

16 (PC) AK, HI, WA, OR, CA 84 239 122

Sources: U.S. Billion-Ton Update (Oak Ridge National Lab, 2011) and the Policy Analysis (POLYSYS) model developed by the 

University of Tennessee’s Department of Agricultural Economics.
180 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Renewable Fuels Module

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 50 percent of the waste stream in 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 EIA’s Emissions of Greenhouse 

Gases in the United States 2003 [9].

• 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 of 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 of 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 

Renewable electricity tax credits 

The RFM includes the investment and energy production tax credits codified in the Energy Policy Act of 1992 (EPACT92) as 

amended. The investment tax credit established by EPACT92 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 raised to 30 percent through 

2016 for some solar projects and extended to residential projects. This change is reflected in the RFM, commercial demand, and 

residential demand modules. The production tax credit, as established by EPACT92, applied to wind and certain biomass facilities. 

As amended, it provides a 2.2-cent tax credit for every kilowatthour of electricity produced for the first 10 years of operation for 

a wind facility constructed by December 31, 2012 or by December 31, 2013 for other eligible facilities. 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. Wind, poultry litter, geothermal, and “closed loop” [12] biomass resources receive a 
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 181

Renewable Fuels Module

2.2-cent tax credit for the first 10 years of facility operations. All other renewable resources receive a 1.1 cent (that is, one-half the 

value of the credit for other resources) tax credit for the first 10 years of facility operations. EIA assumes that biomass facilities 

obtaining the PTC will use “open-loop” fuels, as “closed-loop” fuels are assumed to be unavailable and/or too expensive for 

widespread use during the period that the tax credit is available. The investment and production tax credits are exclusive of one 

another, and may not both be claimed for the same geothermal facility (which is eligible to receive either.

The American Taxpayer Relief Act passed in January of 2012 extends the wind PTC expiration date until December 31, 2013. 

In addition, it modifies the requirement for all fuels that plants be operational by the expiration date to allow any plant under 

construction by the expiration date to qualify. However, due to the timing of the legislation, this update is not included in the 

AEO2013 Reference case.

State RPS programs 

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, and nature of some of the 

limitations, the measurement of compliance is assumed to be approximate.

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 State requirements were divided among relevant 

regions based on sales. 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 13.2.

Only targets with established enforcement provisions or established State funding mechanisms were included in the calculation; 

Non-enforceable goals were not included.. 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.

Alternative renewable case 

Low Renewable Cost case 

The Low Renewable Cost case examines the effect of reducing renewable technology capital costs by 20 percent below Reference 

case values throughout the projection period.

For wind, biomass, LFG, geothermal, and solar technologies, this cost reduction is achieved by a applying a 20% reduction in the 

base overnight capital costs assumed in the Reference case. For geothermal and hydro, the capital cost of each individual site that 

is modeled is reduced by 20% compared to the Reference case. Biomass prices are also assumed to be reduced 20 percent for a 

given quantity of fuel supplied. 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 options of 

residential demand, commercial demand, industrial demand, and PMM modules. Details on these assumptions can be found in 

the corresponding sections of this report.
182 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Renewable Fuels Module

Table 13.2. Aggregate regional renewable portfolio standard requirements (percentage share of total values)

Region1 2020 2030 2040

Texas Reliability Entity 4.4% 4.4% 4.4%

Midwest Reliability Council - East 10.0% 10.0% 10.0%

Midwest Reliability Council - West 10.3% 11.4% 11.4%

Northeast Power Coordinating Council - Northeast 14.3% 14.6% 14.6%

Northeast Power Coordinating Council - NYC/Westchester 24.6% 24.6% 24.6%

Northeast Power Coordinating Council - Long Island 24.6% 24.6% 24.6%

Northeast Power Coordinating Council - Upstate NY 24.4% 24.5% 24.5%

Reliability First Corporation - East 13.6% 14.8% 14.8%

Reliability First Corporation - Michigan 10.0% 10.0% 10.0%

Reliability First Corporation - West 7.1% 9.3% 9.3%

SERC Reliability Corporation - Delta 0.6% 0.6% 0.6%

SERC Reliability Corporation - Gateway 11.2% 15.8% 15.8%

SERC Reliability Corporation - Virginia/Carolina 0.0% 0.1% 0.1%

SERC Reliability Corporation - Virginia/Carolina 5.0% 5.6% 5.5%

Southwest Power Pool - North 11.9% 13.2% 13.2%

Southwest Power Pool - South 2.1% 2.2% 2.2%

Western Electricity Coordinating Council - Southwest 9.4% 11.1% 11.1%

Western Electricity Coordinating Council - California 33.0% 33.0% 33.0%

Western Electricity Coordinating Council - Northwest 10.1% 11.0% 11.0%

Western Electricity Coordinating Council - Rockies 15.5% 15.5% 15.5%

1

 See chapter on the Electricity Market Module for a map of the electricity market module supply regions.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 183

Renewable Fuels Module

Notes and sources

[1] For a comprehensive description of each submodule, see U. S. Energy Information Administration, Office of Integrated 

Analysis and Forecasting, Model Documentation, Renewable Fuels Module of the National Energy Modeling System, 

DOE/EIA-M069(2011), (Washington, DC, August 2011).

[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] The one exception applies to the Salton Sea resource area. For that site, EIA used cost estimates provided by R.W. 

Beck, Inc. rather than NREL.

[4] U.S. Department of Energy. U.S. Billion-Ton Update: Biomass Supply for a Bioenergy and Bioproducts Industry. 

August 2011. 

[5] U.S. Department of Energy. U.S. Billion-Ton Update: Biomass Supply for a Bioenergy and Bioproducts Industry. 

August 2011. 

[6] De la Torre Ugarte, D. “Biomass and bioenergy applications of the POLYSYS modeling framework” Biomass and 

Bioenergy 18 (2000): 291-308. 

[7] De la Torre Ugarte, D. “Biomass and bioenergy applications of the POLYSYS modeling framework” Biomass and 

Bioenergy 18 (2000): 291-308. 

[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] U.S. Energy Information Administration, “Emissions of Greenhouse Gases in the United States 2003”, DOE/EIA0573(2003) (Washington, DC, December 2004), www.eia.gov/oiaf/1605/archive/gg04rpt/index.html. [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), //hydropower.inel. gov/resourceassessment/index.html.

[12] Closed-loop biomass are crops produced explicitly for energy production. Open-loop biomass are generally wastes 

or residues that are a byproduct of some other process, such as crops grown for food, forestry, landscaping, or wood 

milling.
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Appendix A: Handling of federal 

and selected state legislation and 

regulation in the AEO
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U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 187

Appendix A: Handling of federal and selected state legislation and regulation in the AEO

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 with periodic 

updates

Included for categories 

represented in the AEO 

residential sector forecast.

Public Law 100-12.

 a. Room air conditioners Sets standards for room air 

conditioners in 2014.

Require new purchases of 

room air conditioners to meet 

the standard.

Federal Register Notice 

of Final Rulemaking.

 b. Central air conditioners and heat

 pumps

Sets standards for central air 

conditioners in 2015.

Require new purchases of 

other air conditioners to meet 

the standard.

Federal Register Notice 

of Final Rulemaking.

 c. Water heaters Sets standards for water 

heaters in 2015.

Require new purchases of 

water heaters to meet the 

standard.

Federal Register Notice 

of Final Rulemaking.

 d. Refrigerators and freezers Sets standards for refrigerators 

and freezers in 2014.

Require new purchases of 

refrigerators/freezers to meet 

the standard.

Federal Register Notice 

of Final Rulemaking.

 e. Dishwashers Sets standards for dishwasher 

in 2010.

Require new purchases of 

dishwashers to meet the 

standard.

Federal Register Notice 

of Final Rulemaking.

 f. Fluorescent lamp ballasts Sets standards for fluorescent 

lamp ballasts in 2005.

Require new purchases of 

fluorescent lamp ballasts to 

meet the standard.

Federal Register Notice 

of Final Rulemaking.

 g. Clothes washers Sets standards for clothes 

washers in 2011.

Require new purchases of 

clothes washers to meet the 

standard.

Federal Register Notice 

of Final Rulemaking.

 h. Furnaces Sets standards for furnaces in 

2013.

Require new purchases of 

furnaces to meet the standard.

Federal Register Notice 

of Final Rulemaking.

 i. Clothes dryers Sets standards for clothes 

dryers in 2015.

Require new purchases of 

clothes dryers to meet the 

standard.

Federal Register Notice 

of Final Rulemaking.

 j. Boilers Sets standards for boilers in 

2012.

Require new purchases of 

boilers to meet the standard.

Federal Register Notice 

of Final Rulemaking.

B. Energy Policy Act of 1992 (EPACT1992) Public Law 102-486

 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. Various lighting types Sets standards for various 

lightig types in 2012.

Require new purchases of 

various lighting types to meet 

the standards.

Federal Register Notice 

of Final Rulemaking.

C. Energy Policy Act of 2005 (EPACT2005) Public Law 109-58.

 a. Torchiere lamp standard Sets standard for torchiere 

lamps in 2006.

Requires new purchases of 

torchiere bulbs to meet the 

standard.

Federal Register Notice 

of Final Rulemaking.

 b. Compact fluorescent lamp standard Sets standard for fluorescent 

lamps in 20006.

Requires new purchases of 

compact fluorescent bulbs to 

meet the standard.

Federal Register Notice 

of Final Rulemaking.
188 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Appendix A: Handling of federal and selected state legislation and regulation in the AEO

Legislation Brief description AEO handling Basis

 c. Ceiling fan light kit standard Sets standard for ceiling 

fans and ceiling fan light 

kits in 2007.

Reduce lighting electricity 

consumption by appropriate 

amount.

Number of ceiling fan 

shipments and estimated 

kWh savings per unit 

determine overall savings.

 d. Dehumidifier standard Sets standard for 

dehumidifiers in 2012.

Reduce dehumidfier 

electricity consumption by 

appropriate amount.

Number of dehumidifier

shipments and estimated 

kWh savings per unit 

determine overall savings.

 e. Energy-efficient equipment tax credit Purchasers of certain 

energy-efficient equipment 

can claim tax credits in 

2006 and 2007.

Reduce cost of applicable

equipment by specified 

amount.

 f. 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.

 g. Energy-efficient appliance tax credit Producers of energyefficient 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 (EISA 2007) Public Law 110-140.

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.

Federal Register Notice of 

Final Rulemaking.

b. External power supply standard Sets standards for external 

power supplies in 2008.

Reduce external power 

supply electricity 

consumption by

appropriate amount.

Number of shipments and

estimated kWh savings 

per unit determine overall 

savings.

c. 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.

E. Energy Improvement and Extension Act of 2008 (EIEA 2008) Public Law 110-343.

a. Energy-efficient equipment tax credit Purchasers of certain 

energy-efficient equipment 

can claim tax credits 

through 2016.

Reduce the cost of 

applicable equipment by 

specified amount.

EIEA 2008.

b. Energy-efficient appliance tax credit Producers of energyefficient refrigerators, 

clothes washers, and 

dishwashers receive tax 

credits for each unit they 

produce that meets certain 

efficiency specifications, 

subject to an annual cap.

Assume the cost savings are 

passed on to the consumer, 

reducing the price of the 

appliance by the specified

amount.

Cost reductions to consumer 

are assumed to be 100 

percent of the producer’s tax 

credit.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 189

Appendix A: Handling of federal and selected state legislation and regulation in the AEO

Legislation Brief description AEO handling Basis

F. American Recovery and Reinvestment Act of 2009 Public Law 111-5.

 a. Energy-efficient equip-

 ment tax credit

Increases cap to $1500 of energyefficient equipment specified 

under Section C(d) above. 

Removes cap for PV, wind, and 

ground-source heat pumps

Reduce the cost of applicable

equipment by specified amount.

EPACT 2005 and ARRA 

2009.

 b. Weatherization and State

 Energy Programs

Increases funding for 

weatherization and other 

programs to increase the energy 

efficiency of existing housing 

stock.

Apply annual funding amount to

existing housing retrofits. Savings for 

heating and cooling based on $2600 

per home investment as specified in 

weatherization program

evaluation.

ARRA 2009.

G. Tax Relief, Unemployment Insurance Reauthorization, and Job Creation Act of 2010 Public Law 111-312.

 a. Energy-efficient 

 equipment tax credit

Extends tax credits for some 

energy-efficient equipment, 

generally to EISA 2007 amounts.

Reduce the cost of applicable 

equipment by specified amount.

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 

increasing to 10.9 CEER in 2014.

Federal Register Notice of 

Final Rulemaking.

 b. Other residential-size 

 air conditioners (<5.4 

 tons)

10 SEER before 2006 for central air 

conditioning and heat pumps; 13 

SEER in 2006; 14 SEER in 2015.

Federal Register Notice of 

Final Rulemaking.

 c. Fluorescent lamp 

 ballasts

Current standard of 0.90 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.

B. Energy Policy Act of 1992 (EPACT92)

 a. Building codes Incorporated in commercial building 

shell assumptions. Efficiency of new 

relative to existing shell represented 

in shell efficiency indices. Assumes 

shell efficiency improves 6.9 and 

15.0 percent by 2040 for existing 

buildings and new construction, 

respectively.

Based on Science 

Applications International 

Corporation commercial 

shell indices for 2003 

developed for EIA in 2008 

and 2011.

 b. Window labeling Designed to help consumers 

determine which windows are 

more energy efficient.

Incorporated in commercial building 

shell assumptions. Efficiency of new 

relative to existing shell represented 

by shell efficiency indices. Assume 

shell efficiency improves 6.9 and 

15.0 percent by 2040 for existing 

buildings and new construction, 

respectively.

Based on Science 

Applications International 

Corporation commercial 

shell indices for 2003 

developed for EIA in 2008 

and 2011.

 c. Commercial furnaces 

 and boilers

Gas-fired furnaces and boilers: 

Current standard is 0.80% thermal 

efficiency. 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.
190 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Appendix A: Handling of federal and selected state legislation and regulation in the AEO

Legislation Brief description AEO handling Basis

 d. Commercial air 

 conditioners and heat 

 pumps

Air-cooled air conditioners and heat 

pumps less than 135,000 

Btu: 2001 standard of 8.9 EER. 

Air-cooled air conditioners and heat 

pumps greater than 135,000 Btu: 

2001 standard of 8.5 EER.

Public Law 102-486: 

EPACT92.

 e. Commercial water heaters Natural gas and oil: EPACT 

standard 0.78-percent thermal 

efficiency increasing to 80-percent 

thermal efficiency for gas units in 

2003.

Public Law 102-486: 

EPACT92. Federal Register 

Notice of Final Rulemaking.

 f. Lamps Incandescent: 16.9 lumens per 

watt. Fluorescent 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 level. Motors 

contained in new equipment 

must meet the standards.

Public Law 102-486: 

EPACT92.

 h. Federal energy management Requires federal agencies to 

reduce energy consumption 

20 percent by 2000 relative 

to 1995.

Superseded by Executive Order 

13123, EPACT05, and EISA07.

Superseded by Executive 

Order 13123.

 i. Business investment energy 

 credit

Provides a permanent 

10-percent investment 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 agencies to 

reduce energy consumption 

30 percent by 2005 and 35 

percent by 2010 relative to 

1985 through life-cycle costeffective energy measures.

Superseded by EPACT05 and 

EISA07.

Superseded by EPACT05 and 

EISA07.

D. Energy Policy Act of 2005 (EPACT05)

 a. Commercial package air 

 conditioners and heat 

 pumps

Sets minimum efficiency 

levels in 2010.

Air-cooled air conditioners/heat 

pumps less than 135,000 Btu: 

standard of 11.2/11.0 EER and 

heating COP of 3.3. Air-cooled 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 automatic 

 icemakers

Sets minimum efficiency 

levels in 2010.

Set standard by level of 

improvement above stock average 

efficiency in 2003.

Public Law 190-58: EPACT05.

 c. Lamp ballasts Bans manufacture or import 

of mercury vapor lamp 

ballasts in 2008. Sets 

minimum efficacy level for 

T12 energy saver ballasts in 

2009 and 2010 based on 

application.

Remove mercury vapor lighting 

system from technology choice 

menu in 2008. Set minimum 

efficacy of T12 ballasts at 

specified standard levels.

Public Law 102-58: EPACT05.

 d. Compact fluorescent 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.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 191

Appendix A: Handling of federal and selected state legislation and regulation in the AEO

Legislation Brief description AEO handling Basis

 e. Illuminated exit signs and 

 traffic signals

Set standards at ENERGY 

STAR requirements in 2006.

Reduce miscellaneous electricity 

consumption by appropriate 

amount.

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 Manufacturers 

Association Class I Efficiency 

levels in 2007.

Effects of the standard are 

included in estimating the share 

of miscellaneous electricity 

consumption attributable to 

transformer losses.

Public Law 109-58: EPACT05.

 g. Pre-rinse spray valves Sets maximum flow rate to 1.6 

gallons per minute in 2006.

Reduce energy use for water 

heating by appropriate amount.

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 agencies to 

reduce energy consumption 

20 percent by 2015 relative to 

2003 through life-cycle costeffective energy measures.

The federal “share” of the 

commercial sector uses the 

10-year Treasury note rate as 

a discount rate in equipment 

purchase decisions as opposed 

to adding risk premiums to the 

10-year Treasury note rate to 

develop discount rates for other 

commercial decisions

Public law 109-58: EPACT05. 

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: EPACT05. 

Extended through 2008 by 

Public Law 109-432. Extended 

through 2016 by EIEA08.

 j. Business solar investment tax 

 credit

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: EPACT05. 

Extended through 2008 by 

Public Law 109-432. Extended 

through 2016 by EIEA08.

E. Energy Independence and Security Act of 2007 (EISA07)

 a. Commercial walk-in coolers 

 and walk-in freezers

Requires use of specific 

energy efficiency measures in 

equipment manufactured in or 

after 2009.

Set standard by equivalent level of 

improvement above stock average 

efficiency in 2003.

Public Law 110-140: EISA07.

 b. Incandescent and halogen 

 lamps

Sets maximum allowable 

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: EISA07.

 c. Metal halide lamp ballasts Sets minimum efficiency levels 

for metal halide lamp ballasts 

starting in 2009.

Remove metal halide lighting 

systems that do not meet 

standard fromtechnology choice 

menu in 2009. Set minimum 

system efficiency to include 

specified standard levels for 

ballasts -ranging from 88 to 94 

percent based on ballast type.

Public Law 110-140: EISA07.

d. Federal use of energy-efficient 

 lighting

Requires use of energyefficient lighting fixtures and 

bulbs in federal buildings to 

the maximum extent possible 

starting in 2009.

Increase proportion of sector 

using 10 year treasury note rate 

for lighting purchase decisions 

to represent all existing and new 

federal floorspace in 2009.

Public Law 110-140: EISA07.
192 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Appendix A: Handling of federal and selected state legislation and regulation in the AEO

Legislation Brief description AEO handling Basis

e. Federal energy 

 management

Requires federal agencies 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 note 

rate as a discount rate in equipment 

purchase decisions as opposed to 

adding risk premiums to the 10-year 

Treasury note rate to develop discount 

rates for other commercial decisions.

Public Law 110-140: 

EISA07.

F. Energy Improvement and Extension Act of 2008 (EIEA08)

a. Business solar 

 investment tax credit

Extends the EPACT05 30-percent 

investment tax credit for solar 

property through 2016.

Tax credit incorporated in cash flow for 

solar generation systems. Investment 

cost reduced 30 percent for solar water 

heaters.

Public Law 110-343: 

EIEA08.

b. Business investment tax 

 credit for fuel cells and 

 microturbines

Extends the EPACT05 30-percent 

investment tax credit for fuel cells 

and 10-percent investment tax 

credit for microturbines through 

2016.

Tax credit incorporated in cash flow for 

fuel cells and microturbines.

Public Law 110-343: 

EIEA08

c. Business investment tax 

 credit for CHP systems

Provides a 10-percent investment 

tax credit for CHP systems 

installed in 2009 through 2016

Tax credit incorporated in cash flow for 

CHP systems.

Public Law 110-343: 

EIEA08.

d. Business investment tax 

 credit for small wind 

 turbines

Provides a 30-percent investment 

tax credit for wind turbines 

installed in 2009 through 2016.

Tax credit incorporated in cash flow for 

wind turbine generation systems.

Public Law 110-343: 

EIEA08.

e. Business investment tax 

 credit for geothermal 

 heat pumps

Provides a 10-percent investment 

tax credit for geothermal heat 

pump systems installed in 2009 

through 2016.

Investment cost for geothermal heat 

pump systems reduced 10 percent.

Public Law 110-343: 

EIEA08.

G. American Recovery and Reinvestment Act of 2009 (ARRA09)

a. Business investment tax 

 credit for small wind 

 turbines

Removes the cap on the EIEA08 

30-percent investment tax credit 

for wind turbines through 2016.

Tax credit incorporated in cash flow for 

wind turbine generation systems.

Public Law 111-5: ARRA09.

b. Stimulus funding to 

 federal agencies

Provides funding for efficiency 

improvement in federal 

buildings and facilities.

Increase the proportion of sector using 

the 10-year Treasury note rate for 

purchase decisions to include all existing 

and new federal floorspace in years 

stimulus funding is available to account 

for new, replacement, and retrofit 

projects. Assume some funding is used 

for solar generation, small wind turbine, 

and fuel cell installations.

Public Law 111-5: ARRA09.

c. State Energy Program 

 funding and energy 

 efficiency and 

 conservation block 

 grants

Provides grants for state and local 

governments for energy efficiency 

and renewable energy purposes. 

State Energy Program funding 

conditioned on enactment of new 

building codes.

Increase the proportion of sector using 

the 10-year Treasury note rate for 

purchase decisions to include all public 

buildings in years stimulus funding is 

available. Increase new building shell 

efficiency to 10 percent better than 

2003 by 2018 for improved building 

codes. Assume some funding is used 

for solar generation and small wind 

turbine systems.

Public Law 111-5: ARRA09.

d. Funding for smart grid 

 projects

Provides funding for smart grid 

demonstration projects.

Assume smart grid technologies cause 

consumers to become more responsive 

to electricity price changes by increasing 

the price elasticity of demand for certain 

end uses.

Public Law 111-5; ARRA09.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 193

Appendix A: Handling of federal and selected state legislation and regulation in the AEO

Legislation Brief description AEO handling Basis

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 boilers 

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 field-erected boilers, which are 

typically used in steam-intensive 

industries, we assume they meet 

the standard in the AEO.

Standard specified in

EPACT92. 10 CFR 431.

B. Clean Air Act Amendments (CAAA90)

 a. Process emissions Numerous process emissions

requirements for specified

industries and/or activities.

Not modeled because 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 because 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 emissions 

are not projected to reach 

the limit (Source: EPA, 

National Air Pollutant 

Emissions Trends:1990-1998, 

EPA-454/R-00-002, March 

2000, p. 4-3.)

CAAA90, Section 406 (42 

USC 7651)

 d. Industrial boiler hazardous air 

 pollutants

Requires industrial boilers and 

process heaters to conduct 

periodic tune-ups or meet 

emissions limits on HAPs to 

comply with the Maximum 

Achieveable Control 

Technology (MACT) Floor. 

Regulations finalized December 

2012.

Costs of compliance that are not 

offset by efficiency gains (nonrecoverable costs) modeled as 

an additional capital cost in the 

Macroeconomic Activity Module 

(MAM) based on proposed 

regulations as of September 2012.

U.S. Environmental Protection 

Agency, National Emissions 

Standards for Hazardous 

Air Pollutants for Industrial, 

Commercial, and Institutional 

Boilers, Major Source (40 CFR 

63, Subpart DDDDD) and 

Area Source (40 CFR 63 Part 

JJJJJJ)

 e. Emissions from stationary diesel

 engines

Requires engine

manufacturers to meet the

same emission standards as

nonroad diesel engines. 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 (EPACT05)

 a. Physical energy intensity Voluntary commitments 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, unknown

commitments.

EPACT2005, Section 106 

(42 USC 15811)

 b. Mineral components of cement of 

 concrete

Increase in mineral component 

of federally procured cement or 

concrete.

Not modeled. EPACT2005, Section 108 

(42 USC 6966).

 c. Tax credits for coke oven Provides a tax credit of $3.00

per barrel oil equuivalent, 

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).
194 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Appendix A: Handling of federal and selected state legislation and regulation in the AEO

Legislation Brief description AEO handling Basis

D. The Energy Independence and Security Act of 2007 (EISA2007)

 a. 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

E. The Energy Improvement and Extension Act of 2008 (EISA2008)

 a. Combined heat and power 

 tax incentive

Provides an investment tax credit for 

up to 15 megawatts of capacity in 

combined heat and power systems of 50 

megawatts or less through 2016

Costs of systems adjusted to 

reflect the credit.

EIEA2008, Title I, Sec. 103

Transportation sector

A. Energy Policy Act of 1992 

(EPACT92)

Increases the number of alternative 

fuel vehicles and alternative fuel use in 

federal, state, and fuel provided fleets.

Assumes federal, state and 

fuel provided fleets meet the 

mandated sales requirements.

Energy Policy Act of 1992, 

Public Law 102-486-Oct. 

24, 1992.

B. Low Emission Vehicle 

Program (LEVP)

The Clean Air Act provides California 

the authority to set vehicle criteria 

emission standards that exceed federal 

standards. A part of that program 

mandates the sale of zero-emission 

vehicles by manufacturers, other 

nonattainment states are given the 

option of opting into the federal or 

California emission standards.

Incorporates the LEVP program 

as amended on August 4, 2005. 

Assumes California, Connecticut, 

Maine, Massachusetts, 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 177 of the Clean 

Air Act, 42 U.S.C. sec. 

7507 (1976) and CARB, 

California Exhaust 

Emissions Standards 

and Test Procedures for 

Passenger Cars, Light-Duty 

Trucks, and Medium-Duty 

Vehicles, August 4, 2005.

C. Corporate Average Fuel 

Economy (CAFE) Standard for 

Light Duty Vehicles

Requires manufacturers to produce 

vehicles that meet a minimum federal 

average fuel economy standard, 

promulgated jointly for model years 

2012-2016 and 2017-2025 with an 

average greenhouse emissions standard; 

cars and light trucks are regulated 

separately.

CAFE standards are increased 

for model years 2011 through 

2016 to meet the final CAFE 

rulemakings for model year 2011 

and 2012 to 2016, respectively. 

CAFE standards are increased for 

model years 2017 to 2025 to meet 

final CAFE joint rulemakings for 

model year 2017 to 2022 and to 

meet augural CAFE standards for 

model year 2023 to 2025, which 

will undergo a midterm evaluation 

to finalize. CAFE standards are 

held constant through the end of 

the projection.

Energy Policy 

Conservation Act of 

1975; Title 49 United 

States code, Chapter 329; 

Energy Independence 

and Security Act of 2007, 

Title 1, Section 102; 

Average Fuel Economy 

Standards Passenger 

Cars and Light Trucks 

Model Year 2011; Federal 

Register, Vol. 74, No. 59, 

March 2009; Light-Duty 

Vehicle Greenhouse Gas 

Emission Standards and 

Corporate Average Fuel 

Economy Standards, Final 

Rule, Federal Register, 

Vol. 75, No. 88, May 

2010; 2017 and Later 

Model Year Light-Duty 

Vehicle Greenhouse Gas 

Emissions and Corporate 

Average Fuel Economy 

Standards Federal Register, 

Vol. 77, No. 199, October 

2012.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 195

Appendix A: Handling of federal and selected state legislation and regulation in the AEO

Legislation Brief description AEO handling Basis

D. Electric, Hybrid, and 

Alternative Fuel Vehicle Tax 

Incentives

Federal tax incentives are provided 

to encourage the purchase of electric, 

hybrid 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.

E. Plug-in Hybrid Vehicle Tax 

Credit

EIEA2008 grants a tax credit of $2,500 

for PHEVs with at least 4kWh of 

battery capacity, with larger batteries 

earning an additional $417 per kWh up to 

a maximum of $7,500 for light-duty 

PHEVs. The credit will apply until 250,000 

eligible PHEVs are sold or until 2015, 

whichever comes first.

Incorporates the federal tax 

credits for PHEVs.

Energy Improvement and

Extension Act of 2008, H.R.6049.

F. State Electric, Hybrid, and 

Alternative Fuel Vehicle 

Tax and Other Incentives

Approximately 20 states provide tax 

and other incentives to encourage 

the purchase of electric, hybrid 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 and licensing fees. The 

incentives offered and the mix varies by 

state. For example, Georgia offers a tax 

credit of $5,000 for electric vehicles and 

Oklahoma offers a tax credit of $1,500 for 

hybrid and alternative fuel vehicles.

Does not incorporate state 

tax and other incentives for 

hybrid, electric, and other 

alternative fuel vehicles.

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 Washington.

G. HD National Program; 

Greenhouse Gas Emissions 

and Fuel Consumption 

Standards for Heavy-Duty 

Vehicles

Requires on-road heavy-duty vehicle 

manufacturers to produce vehicles 

that meet a minimum federal average 

greenhouse gas emission standard, 

issued by the EPA, for model years 2014-

2018. NHTSA established voluntary fuel 

consumption standards for MY 2014-

2015, and mandatory fuel consumption 

standards for MY 2016 and beyond for onroad heavy-duty trucks and their engines; 

vocational and combination engines are 

regulated separately.

HD National program 

standards begin for MY 2014 

as set by the GHG emissions 

portion of the rule with the 

assumption that the vehicles 

comply with the voluntary 

portion of the rule for fuel 

consumption. The model 

allows for both the engine 

and chassis technologies to 

meet the standards.

Section 202 of the Clean Air 

Act; Title 49 United States 

code, Chapter 32902[k]; Energy 

Independence and Security Act 

of 2007, Title 1, Section 102; 

Federal Register, Vol. 76, No. 179, 

September 2011.

Electric power generation

A. Clean Air Act Amendments 

of 1990 (CAAA90)

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 cap.

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-type-specific nitrogen oxide 

emissions limits for electricity generators.

Assumes each boiler installs 

the options necessary 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.
196 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Appendix A: Handling of federal and selected state legislation and regulation in the AEO

Legislation Brief description AEO handling Basis

Requires the EPA to establish national 

ambient air quality standards 

(NAAQS). In 1997, EPA set new 

standards for ground level ozone and 

fine particulates. EPA is currently 

determining which areas of the ountry 

are not in compliance with the new 

standards. Area designations were 

made in December 2004. States 

submitted their compliance plans, and 

have until 2009-2014 to bring all areas 

into compliance.

These standards are not 

explicitly represented, but the 

Clean Air Interstate Rule is 

incorporated (described below) 

and was developed to help 

states meet their NAAQS.

Clean Air Act Amendment of 

1990, Title I, Sections 108 and 

109, National Ambient 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, Federal Register, Vol. 62, No. 

138, July 18, 1997.

B. Clean Air Interstate Rule 

(CAIR)

CAIR imposes a two-phased limit on 

emissions of sulfur dioxide and/or 

nitrogen oxide from electric generators 

in 27 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. Mercury and Air Toxics 

Standards (MATS)

MATS sets standards to reduce air 

pollution from coal and oil-fired power 

plants greater than 25 megawatts. 

The rule requires plants achieve 

the maximum achievable control 

technology for mercury, hydrogen 

chloride (HCl) and fine particulate 

matter (PM 2.5).

The EMM assumes that all 

coal-fired generating plants 

above 25 megawatts will comply 

beginning in 2016. Plants are 

assumed to reduce mercury 

emissions by 90 percent relative 

to uncontrolled levels. Because 

the EMM does not model HCl or 

PM 2.5 explicitly, to meet those 

requirements, coal plants are 

required to install either an FGD 

or a dry sorbent injection system 

including a full fabric filter.

Environmental Protection 

Agency, “Mercury and Air Toxics 

Standards,” website epa.gov/mats.

D. Energy Policy Act of 1992 

(EPACT92)

Created a class of generators referred 

to as exempt wholesale generators 

(EWGs), exempt from PUHCA as long 

as they sell wholesale power.

Represents the development 

of Exempt Wholesale 

Generators (EWGs) or what 

are now referred to as 

independent power producers 

(IPPs) in all regions.

Energy Policy Act of 1992, Title 

VII, Electricity, Subtitle A, Exempt 

Wholesale Generators.

E. The Public Utility Holding 

Company Act of 1935 

(PUHCA)

PUHCA is a federal statue which was 

enacted to legislate against abusive 

practices in the utility industry. The 

act grants power to the U.S. 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 company’s structure of 

activities are not deemed to be in the 

public interest.

It is assumed that holding 

companies act competitively 

and do not use their regulated 

power businesses to crosssubsidize their unregulated 

businesses.

Public Utility Holding Company

Act of 1936.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 197

Appendix A: Handling of federal and selected state legislation and regulation in the AEO

Legislation Brief description AEO handling Basis

F. 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 a 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 

the forecast 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.

Promoting Wholesale Competition 

Through Open Access, NonDiscriminatory Transmission 

Services by Public Utilities; Public 

Utilities and Transmitting Utilities, 

ORDER NO. 888 (Issued April 

24, 1996), 18 CFR Parts 35 and 

385, Docket Nos. RM95-8-000 

and RM94-7-001. Open Access 

Same-Time Information System 

(formerly Real-Time Information 

Networks) and Standards of 

Conduct, ORDER NO. 889, 

(Issued April 24, 1996), 18 CFR 

Part 37, Docket No. RM95-9-000.

G. New Source Review (NSR) On August 28, 2003, the EPA issued 

a final rule defining certain power 

plant and industrial facility activities 

as routine maintenance, repair and 

replacement, which are not subject to 

new source review (NSR). As stated 

by EPA, these changes provide a 

category of equipment replacement 

activities that are not subject to Major 

NSR requirements under the routine 

maintenance, repair and replacement 

(RMRR) exclusion.[1] Essentially this 

means that power plants and industrial 

facilities engaging in RMRR activities 

will not have to get preconstruction 

approval from the state or EPA and 

will not have to install best available 

emissions control technologies 

that might be required if NSR were 

triggered.

It is assumed that coal plants will 

be able to increase their output 

as electricity demand increases. 

Their maximum capacity factor 

is set at 75 percent. No increases 

in the capacity of existing plants 

is assumed. If further analysis 

shows that capacity uprates may 

result from the NSR rule, they 

will be incorporated in future 

AEOs. However, at this time, 

the NSR rule is being contested 

in the courts.

EPA, 40 CFR Parts 51 and 

52, Deterioration (PSD) and 

Non-Replacement Provision 

of the Vol. 68, No. 207, page 

61248, Prevention of Significant 

Attainment New Source Review 

(NSR): Equipment Routine 

Maintenance, Repair and 

Replacement Exclusion; Final 

Rule, Federal Register, October 27, 

2003.

H. State RPS Laws, Mandates,

and Goals

Several states have enacted laws 

requiring that a certain percentage 

of their generation come from 

qualifying renewable sources.

The AEO reference case 

represents the Renewable 

Portfolio Standard (RPS) or

substantively similar laws from 

30 states and the District of 

Columbia. As described in the

The 30 states with RPS or other 

mandates providing quantified 

projections are detailed in the 

Legislation and Regulations 

section of this report.
198 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Appendix A: Handling of federal and selected state legislation and regulation in the AEO

Legislation Brief description AEO handling Basis

Renewable Fuels Module 

chapter of this document,

mandatory targets from 

the various states are 

aggregated at the regional 

level, and achievement of 

nondiscretionary compliance 

criteria is evaluated for each 

region.

I. Regional and State Air 

Emissions Regulations

The Northeast Regional Greenhouse 

Gas Initiative (RGGI) applies to 

fossil-fueled power plants over 25 

megawatts in the Northeastern 

United States. The state of NJ 

withdrew in 2011, leaving 9 states 

in the program. The rule caps CO2

emissions and requires they account 

for CO2 emitted with allowances 

purchased at auction.

The impact of RGGI is 

included in the EMM, making 

adjustments when needed to 

estimate the emissions caps 

at the regional level used in 

NEMS.

Regional Greenhouse Gas Initiative 

Model rule, www.rggi.org

The California Assembly Bill 32 

(AB32) sets GHG reduction goals for 

2020 for California. A cap-and-trade 

program was designed to enforce the 

caps. The cap-and-trade program 

applies to multiple economic sectors 

including electric power plants, 

large industrial facilities, suppliers 

of transportation fuel and suppliers 

of natural gas. Emissions resulting 

from electricity generated outside 

California but consumed in the state 

are also subject to the cap.

The EMM models the capand-trade program explicitly 

for CO2 for California through 

an emission constraint that 

accounts for emissions from the 

other sectors. Limited banking 

and borrowing of allowances 

as well as an allowance reserve 

and offsets are incorporated as 

specified in the Bill.

California Code of Regulations, 

Subchapter 10 Climate Change, 

Article 5, Sections 95800 to 

96023, Title 17, “California Cap 

on Greenhouse Gas Emissions 

and Market-Based Compliance 

Mechanisms,” (Sacramento, CA: 

July 2011).

J. Energy Policy Act of 2005 Extended and substantially 

expanded and modified the 

Production Tax Credit, originally 

created by EPACT1992.

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 projects are 

explicitly modeled as specified 

in the law and subsequent 

amendments.

Energy Policy Act of 2005, 

Sections 1301, 1306, and 1307

K. American Recovery and

Reinvestment Act of 2009

Extends the Production Tax Credit 

(PTC) to wind facilities constructed 

by December 31, 2012 and to other 

eligible renewable facilities

constructed by December 31, 2013. 

Allows PTC-eligible facilities to 

claim a 30-percent investment tax 

credit (ITC) instead of the PTC. 

Projects starting construction by 

the end of 2010 (subsequently 

extended to the end of 2011) may 

elect to take a cash grant equal to 

the value of the 30-percent ITC 

instead of either tax credit.

The extensions of the PTC 

and 30-percent ITC are 

represented in the AEO

reference case as specified 

in the law. The AEO does not 

distinguish between the 

effects of the 30-percent ITC 

and the equivalent cash grant, 

and the cash grant is not 

specifically modeled.

American Recovery and 

Reinvestment Act of 2009, 

Division B, Title I, Sec. 1101, 1102, 

and 1603.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 199

Appendix A: Handling of federal and selected state legislation and regulation in the AEO

Legislation Brief description AEO handling Basis

ARRA provided $6 billion to pay 

the cost of guarantees for loans 

authorized by the Energy Policy 

Act of 2005. The purpose of these 

loan guarantees is to stimulate the 

deployment of conventional renewable 

and transmission technologies and 

innovative biofuels technologies. 

However, to qualify, eligible projects 

must be under construction by 

September 30, 2011.

AEO2013 includes projects that 

have received loan guarantees 

under this authority, but does 

not assume automatic award of 

the loans to potentially eligible 

technologies.

American Recovery and 

Reinvestment Act of 2009, 

Title IV, “Energy and Water 

Development”, Section 406.

ARRA provides $4.5 billion for smart 

grid demonstration projects. These 

generally include a wide array of 

measurement, communications, and 

control equipment employed throughout the transmission and distribution 

system that will enable real-time 

monitoring of the production, flow, 

and use of power from generator to 

consumer.

In the electricity module, it was

assumed that line losses would

fall slightly, peak loads would

fall as customers shifted their

usage patterns, and customers

would be more responsive to

pricing signals.

American Recovery and 

Reinvestment Act of 2009, 

Title IV, “Energy and Water 

Development”, Section 405.

ARRA provides $800 million to fund 

projects under the Clean Coal Power 

Initiative program focusing on capture 

and sequestration of greenhouse gases.

It was assumed that one gigawatt 

of new coal with sequestration 

capacity would come online by 

2018.

American Recovery and 

Reinvestment Act of 2009, 

Title IV, “Energy and Water

Development”

L. American Taxpayer Relief 

Act of 2012 (ATRA)

ATRA was passed on January 1, 

2013 and included several provisions 

extending tax credits to the energy 

sector. Most significantly, it extended 

the PTC for wind by one year, and 

redefined the criteria for all qualifying 

projects to be based on ‘under 

construction’ by December 31, 2013 

rather than in service by that same date, 

thus extending the credit for length of 

the typical construction period.

ATRA was passed too late to 

be incorporated in the AEO2013

Reference case, but a special 

case was prepared to analyze 

key provisions, including the 

renewable PTC extension. Results 

are presented in the AEO2013

Issues in Focus section.

American Taxpayer Relief Act of 

2012, P.L. 112-240, Sections 401 

through 412.

M. Nuclear Waste Confidence 

Rule

The U.S. Nuclear Regulatory 

Commission (NRC) Waste Confidence 

Rule originally determined that spent 

nuclear fuel can be safely stored 

onsite for 30 years without significant 

environmental impacts. A 2010 

update amended this part of the rule 

to extend to 60 years. In June 2012, 

the U.S. Court of Appeals for the 

District of Columbia Circuit struck 

down the 2010 amendment, and the 

NRC subsequently issued an order 

that suspended actions related to 

issuance of operating licenses and 

renewals until the rule is revised.

Plants that have not yet submitted 

license renewal applications 

or new units that have not yet 

received an operating license 

may be delayed by the 2012 

order. However, because the NRC 

expects to resolve the issues 

with the rule within two years, 

the AEO2013 assumes that the 

issuance of new operating licenses 

or license renewals will not be 

affected, as they occur further out 

in the forecast.

Federal Register, Vol. 49, No. 171

(1984), Vol. 55, No. 181 (1990), 

Vol. 75, No. 246 (2010), U.S. 

Nuclear Regulatory Commission, 

“CLI-12-16, Memorandum and 

Order” (August 7, 2012).
200 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Appendix A: Handling of federal and selected state legislation and regulation in the AEO

Oil and gas supply

A. The Outer Continental Shelf 

Deep Water Royalty Relief 

Act (DWRRA)

Mandates that all tracts offered by 

November 22, 2000, 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 the 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 USGS to inventory oil and 

gas resources beneath federal lands.

To date, the Rocky Mountain oil 

and gas resource inventory has 

been completed by the USGS. 

The results of this inventory 

have been incorporated in the 

technically recoverable oil and 

gas resource volumes used for the 

Rocky Mountain region.

Scientific Inventory of Onshore 

Federal Lands: Oil and Gas 

Resources and Reserves and 

the Extent and Nature of 

Restrictions or Impediments 

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 of Interior, 

Agriculture and Energy, January 

2003.

C. Section 29 Tax Credit for

Nonconventional Fuels

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 

December 31, 1992. Gas production 

from qualifying wells could receive a $3 

(1979 constant dollars) per barrel of oil 

equivalent credit 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, gaseous, or solid 

synthetic fuels produced from coal; fuel 

from qualified processed formations or 

biomass; and steam from agricultural 

products.

The Section 29 Tax Credit 

expired on December 31, 2002, 

and it is not considered in new 

production decisions. However, 

the effect of these credits 

is implicitly included in the 

parameters that are derived from 

historical data reflecting such 

credits.

Alternative Fuel Production 

Credit (Section 29 of the 

Internal Revenue Code), initially 

established in the Windfall Profit 

Tax of 1980.

D. Energy Policy Act of 2005. Established a program to provide 

grants to enhance oil and gas 

recovery through CO2 injection.

Additional oil resources were 

added to account for increased 

use of CO2-enhanced 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 

Construction Hurricane 

Supplemental 

Appropriations Act, 2005.

Disallows approval for a pipeline to

enter Canada via Alaska north of 68 

degrees latitude. Also, provides 

federal guarantees for loans and other 

debt obligations assigned to infrastructure in the United States or Canada 

related to any natural gas pipeline 

Assumes the pipeline 

construction cost estimate for the 

“southern”Alaska pipeline route 

in projecting when an Alaska gas 

pipeline would be profitable to 

build. With recent increased in cost 

estimates, well beyond $18 billion, 

the loan guarantee is assumed to 

have a minimal impact on the build 

decision.

P.L. 108-324.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 201

Appendix A: Handling of federal and selected state legislation and regulation in the AEO

Legislation Brief description AEO handling Basis

system that carries Alaska natural gas 

to the border between Alaska and

Canada south of 68 degrees north 

latitude. This authority would expire 2 

years after the final certificate of public 

convenience and necessity is issued. The 

guarantee will not exceed 1) 80 percent 

of the total capital costs (including 

interest during construction), 2) $18 

billion (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 7-year cost-of-investment 

recovery period for the Alaska natural 

gas pipeline, as opposed to the currently 

allowed 15-year recovery period, for 

tax purposes. The provision would be 

effective for property placed in service 

after 2013, or treated as such. Effectively 

extends the 15-percent tax credit 

currently applied to costs related to 

enhanced oil recovery to construction 

costs for a gas treatment plant on the 

North Slope that would feed gas into an 

Alaska pipeline to Canada.

The change in the recovery 

period is assumed to have a 

minimal impact on the decision 

to build the pipeline. The 

assumed treatment costs are 

based on company estimates 

made after these tax provisions 

were enacted.

P.L. 108-357.

C. Pipeline Safety, Regulatory 

Certainty, and Job Creation 

Act of 2011 and other 

previous laws and regulations 

on pipeline safety.

Provides for enhanced safety, reliability 

and environmental protection in the 

transportation of energy products by 

pipeline.

Costs associated with previously 

imposed pipeline safety laws are 

assumed to already be reflected 

in historical capital and operating 

cost data used in the model. 

Any additional costs associated 

with more recent legislation are 

assumed to be a small percentage 

of total pipeline costs and are 

partially offset by benefits gained 

through reducing pipeline leakage.

P.L. 112-90, 125 Stat. 1904

D. Energy Policy Act of 2005. Allowed natural gas storage

facilities to charge market-based

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.

E. Federal Motor Fuels Excise 

Taxes for Compressed 

Natural Gas and Liquefied 

Natural Gas in Vehicles

Taxes are levied on each gallon or 

gasoline-gallon equivalent of natural gas.

Federal motor fuels excise taxes 

on natural gas fuel for vehicles 

are included in retail prices and 

are assumed to be extended 

indefinitely at current nominal 

rates.

26 USC 4041.

F. State Motor Fuels Taxes for 

Compressed Natural Gas 

and Liquefied Natural Gas 

in Vehicles

Taxes are levied on each gallon, gasolinegallon equivalent, or diesel-gallon 

equivalent of natural gas.

State motor fuels excise taxes 

on natural gas fuel for vehicles 

are included in retail prices and 

are assumed to be extended 

indefinitely at current nominal 

rates.

Determined by review of existing 

state laws.
202 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Appendix A: Handling of federal and selected state legislation and regulation in the AEO

Liquid Fuels Market

Legislation Brief description AEO handling Basics

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 mid-2010, all highway diesel 

must be 15 ppm or less. All nonroad, 

locomotive, and marine diesel fuel 

produced must contain less than 500 ppm 

starting mid-2007. By mid-2010 nonroad 

diesel must 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-backsliding and antidumping rules for gasoline.

Modeled by updating gasoline 

specifications to most current 

EPA gasoline survey data (2005) 

representing anti-backsliding 

requirements.

40 CFR Parts 60 and 86.

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. Small 

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, Kentucky,

Maine, Michigan, Minnesota,

Missouri, Montana, Nebraska,

New Hampshire, New Jersey,

New York, North Carolina,

Ohio, Rhode Island, South

Dakota, Vermont, Washington,

and Wisconsin.

E. Regional Clean Fuel 

Formulations

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 Motor 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 various times in the future but 

are expected to be renewed, as they have 

been in the past.

Gasoline, diesel, and ethanol blend 

tax rates are included 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 assumption 

that state taxes will increase at the rate 

of inflation supports an implied need for 

additional highway revenues as driving 

increases.

Gasoline and diesel 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 semiannually by EIA’s Office of Energy 

Statistics.

H. Diesel Excise Taxes Phases out the 4.3 cents excise tax 

on railroads between 2005 and 2007.

Modeled by phasing out. American Jobs Creation Act of 

2004, Section 241.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 203

Appendix A: Handling of federal and selected state legislation and regulation in the AEO

Legislation Brief description AEO handling Basis

I. Energy Policy Act of 2005 (EPACT05)

 a. Ethanol/biodiesel tax

 credit

Petroleum product 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 and E85. Virgin 

biodiesel is assumed to be blended 

into highway diesel, and nonvirgin 

biodiesel is assumed to be blended 

into nonroad diesel or heating 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. Renewable Fuels Standard

 (RFS)

This section has largely been 

redefined by EISA07 (see below); 

however, EPA rulemaking completed 

for this law was assumed to contain 

guiding principles of the rules and 

administration of EISA07.

Energy Policy Act of 2005, 

Section 1501.

 c. Elimination of oxygen 

 content requirement in 

 reformulated gasoline 

Within 270 days of enactment of the 

Act, except for California where it is 

effective immediately.

Oxygenate waiver already an option 

of the model. MTBE 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 Coal-to- Liquids 

Projects.

Two CTL units are available 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. Renewable 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 may 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 AEO2013, 

however it is assumed that the 

schedule for cellulosic biofuel is 

adjusted downward consistent with 

waiver provisions contained in the 

law.

K. State Heating Oil Mandates A number of Northeastern states 

passed legislation that reduces the 

maximum sulfur content of heating 

oil to between 15 and 50 ppm in 

different phases through 2016.

Due to time constraints, this was 

not incorporated in the LFMM for 

AEO2013, but will be included for 

AEO2014 and beyond.

Connecticut State Senate 

Bill 382, Maine State 

Legislature HP1160, NJ State 

Department of Environmental 

Protection, Amendment 

N.J.A.C. 7:27-9.2, New York 

State Senate Bill S1145C.

L. California Low Carbon Fuel 

Standard (LCFS)

California passed legislation which 

is designed to reduce the Carbon 

Intensity (CI) of motor gasoline and 

diesel fuels sold in California by 10 

percent between 2012 and 2020 

through the increased sale of 

alternative “low-carbon” fuels.

The LCFS is included in AEO2013

as legislated for gasoline and 

diesel fuel sold in California, and

for other regulated fuels. 

California Air Resources 

Board, “Final Regulation 

Order: Subarticle 7. Low 

Carbon Fuel Standard.”
204 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Appendix A: Handling of federal and selected state legislation and regulation in the AEO

Legislation Brief description AEO handling Basis

M. California Assembly Bill 32 (AB32) The California Assembly Bill 32 

(AB32), the Global Warming 

Solutions Act of 2006, authorized 

the California Air Resources Board 

(CARB) to set GHG reduction 

goals for 2020 for California. A 

cap-and-trade program was 

designed to enforce the caps. The 

cap-and-trade program applies 

to multiple economic sectors 

including electric power plants, 

large industrial facilities, suppliers 

of transportation fuel and suppliers 

of natural gas. Emissions resulting 

from electricity generated outside 

California but consumed in the 

State are also subject to the cap.

The AB32 cap-and-trade was 

more fully implemented in 

AEO2013, adding industrial 

facilities, refineries, fuel 

providers, and non-CO2 GHG 

emissions to the representation 

already in the electrical power 

sector of NEMS. Also, limited 

banking and borrowing, as well 

as an allowance reserve and 

offset purchases, were modeled, 

providing some compliance 

flexibility and cost containment.

California Code of Regulations, 

Subchapter 10 Climate Change, 

Article 5, Sections 95800 to 

96023, Title 17, “California Cap 

on Greenhouse Gas Emissions 

and Market-Based Compliance 

Mechanisms,” (Sacramento, CA: 

July 2011).

N. EPA ETS Waiver EPA approved two waivers for 

the use of ethanol motor 

gasoline blends of up to 15 

percent in vehicles 2001 and 

newer.

These two waivers were 

included and modeled in 

AEO2013 based on forecasted 

vehicle fleets and potential 

infrastructure and liability 

setbacks.

EPA–HQ–OAR–2009–0211; 

FRL–9215–5, EPA–HQ–OAR–

2009–0211; FRL–9258–6.

Source: U.S. Energy Information Administration, Office of Energy Analysis.
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 205

Appendix A: Handling of federal and selected state legislation and regulation in the AEO

Abbreviations:

AB: Assembly Bill

AB32: California Assembly Bill 32

ACI: Activated carbon injection

AEO: Annual Energy Outlook

AEO2012: Annual Energy Outlook 2012 

AFUE: Average Fuel Use Efficiency

ANWR: Artic National Wildlife Refuge

ARRA2009: American Recovery and Reinvestment Act of 2009

ASHRAE: American Society of Heating Refrigerating, and Air-Conditioning Engineers

Blue Chip: Blue Chip Consensus

BTL: Biomass-to-liquids

Btu: British Thermal Unit

CAFE: Corporate Average Fuel Economy

CAIR: Clean Air Interstate Rule

CARB: California Air Resources Board

CBECS: Commercial Building Energy Consumption Survey

CBO: Congressional Budget Office

CBTL: Coal- and biomass-to-liquids

CCS: Carbon capture and storage

CFR: Code of Federal Regulations

CHP: Combined heat and power

CI: Carbon intensity

CMM: Coal Market Module

CNG: Compressed natural gas

CO2: Carbon dioxide

CO

2-EOR: Carbon dioxide-enhanced oil recovery

CSAPR: Cross-State Air Pollution Rule

CTL: Coal-to-liquids

DG: Distributed generation 

DGE: Diesel gallon equivalent

DOE: U.S. Department of Energy

DOT: Department of Transportation

DSI: Direct sorbent injection

DWRRA: Deep Water Royalty Relief Act

E10: Motor gasoline blend containing up to 10 percent ethanol

E15: Motor gasoline blend containing up to 15 percent ethanol

E85: Motor fuel containing up to 85 percent ethanol

EERE: Energy Efficiency and Renewable Energy

EER: Energy Efficient Ratio

EIA: U.S. Energy Information Administration

EIEA2008: Energy Improvement and Extension Act of 2008

EISA2007: Energy Independence and Security Act of 2007

EOR: Enhanced oil recovery

EPA: U.S. Environmental Protection Agency

EPACT92: Energy Polic y Act of 1992

EPACT05: Energy Policy Act of 2005

EUR: Estimated ultimate recovery

EV: Electric vehicle

EVA: Energy Ventures Analysis

EWGs: Exempt Wholesale Generators

FFV: Flex-fuel vehicle

FEMP: Federal Energy Management Program

FERC: Federal Energy Regulatory Commission

FGD: Flue gas desulfurization

HDV: Heavy-duty Vehicles

HERS: Home Energy System Rating

HVAC: Heating, Ventilation, and Air Conditioning 

GDP: Gross domestic procduct

GHG: Greenhouse Gases
206 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013

Appendix A: Handling of federal and selected state legislation and regulation in the AEO

Abbreviations:

GTL: Gas-to-liquids

GVWR: Gross vehicle weight rating

HAP: Hazardous air pollutant

HB: House Bill

HCI: Hydrogen chloride

HD: Heavy-duty

HDV: Heavy-duty vehicle

HERS: Home Energy System Rating

HEV: Hybrid electric vehicle

Hg: Mercury

HVAC: Heating Ventilation, and Air Conditioning

ICE: Internal combustion engine

IDM: Industrial Demand Module

IEA: International Energy Agency

IECC2006: 2006 International Energy Conversion Code

IEM: International Energy Module

IHSGI: IHS Global Insight

INFORUM: Interindustry Forecasting Project at the University of Maryland

IOU: Investor-owned utility

IREC: Interstate Renewable Energy Council

ITC: Investment Tax Credit

kWh: Kilowatthour

LBNL: Lawrence Berkeley National Laboratory

LCFS: Low Carbon Fuel Standard

LDV: Light-duty vehicle

LED: Light-emitting diode

LFMM: Liquid Fuels Market Module

LNG: Liquefied natural gas

MARAD: Maritime Administration

MATS: Mercury and Air Toxics Standards

MAM: Macroeconomic Activity Module

MCF: Thousand Cubic Feet

MEF: Modified Energy Factor

mmt: Million metric tons

MMTCO2e: Million metric tons carbon dioxide equivalent

mpg: Miles per gallon

MSAT: Mobile Source Air Toxics

MSRP: Manufacturer’s suggested retail price

MTBE: Methyl Tertiary-Butyl Ether

MY: Model year

NAICS: North American Industry Classification System

NEMS: National Energy Modeling System

NERC: North American Electric Reliability Corportion

NGL: Natural gas liquids

NGPL: Natural gas plant liquids

NGTDM: Natural Gas Transmission and Distribution Module

NGV: Natural gas vehicle

NHTSA: National Highway Traffic Safety Administration

NOx: Nitrogen oxides

NRC: U.S. Nuclear Regulatory Commission

OASIS: Open Access Same-Time Information System

OECD: Organization for Economic Cooperation and Development

OMB: Office of Management and Budget

OPEC: Organization of the Petroleum Exporting Countries

P&G: Purvin & Gertz

PADD: Petroleum Administration for Defense District

PCs: Personal computers

PHEV: Plug-in Hybrid Electric Vehicles
U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 207

Appendix A: Handling of federal and selected state legislation and regulation in the AEO

Abbreviations:

P.L.: Public Law

PM: Particulate matter

PM25: Particulate matter less than 2.5 microns diameter

PMM: Petroleum Market Module

PPM: Parts Per Million

PTC: Production tax credit

PUHCA: Public Utility Holding Company Act of 1935

PV: Solar photovoltaic

RAC: U.S. Refiner Acquisition Cost

RECS: Residential Enegy Consumption Survey

RFM: Renewable Fuels Module

RFS: Renewable fuel standard

RGGI: Regional Greenhouse Gas Initiative

RPS: Renewable portfolio standard

SB: Senate Bill

SCR: Selective catalytic reduction

SEER: Strategic Energy and Economic Research, Inc.

SEIA: Solar Energy Industries Association

SNCR: Selective noncatalytic reduction

SO2: Sulfur dioxide

STEO: Short-Term Energy Outlook

TAPS: Trans-Alaska Pipeline System

TRR: Technically recoverable resource

UEC: Unit energy consumption

USLD: Ultra-Low-Sulfur Diesel

U.S.C.: United States Code

UPS: Uninterruptible power supply

USGS: United States Geological’s Survey

VIUS: Vehicle Inventory and Use Survey

VMT: Vehicle miles traveled

WTI: West Texas Intermediate

ZEV: Zero Emission Vehicle