The National Energy Modeling System
Integrating Module of the National Energy Modeling
System (INT)
Description
The National Energy Modeling System (NEMS) is an energy-economy modeling
system of U.S. energy markets used for mid-term projections through 2030,
as well as for energy and environmental policy analysis. NEMS projects
the production, imports, conversion, consumption, and prices of energy,
subject to macroeconomic and financial factors, world energy markets,
resource availability and costs, behavioral and technological choice criteria,
cost and performance characteristics of energy technologies, and demographics.
The model reflects market economics, industry structure, and energy policies
and regulations that influence market behavior.
The integrating module of the National Energy Modeling System controls
the solution algorithm, manages the global data, and implements greenhouse
gas emissions accounting and associated policy options.
This section addresses some aspects of NEMS common to all of the component
modules, including computing and archive information.
Last Model Update
October 2005
Part of Another Model
Part of the National Energy Modeling System
Model Interfaces
NEMS comprises the following modules with model contacts
as indicated.
|
Integrating Module
|
Dan Skelly (202) 586-1722 |
| Residential Sector Demand Module |
John Cymbalsky (202) 586-4815
|
|
Commercial Sector Demand Module
|
Erin Boedecker (202) 586-4791
|
|
Transportation Sector Demand Module
|
John Maples (202) 586-1757
|
|
Industrial Demand Module
|
Crawford Honeycutt (202) 586-1420
|
|
Macroeconomic Activity Module
|
Ronald Earley (202) 586-1398
|
|
International Energy Module
|
Dan Butler (202) 586-9503
|
|
Coal Market Module
|
Diane Kearney (202) 586-2415
|
|
Renewable Fuels Module
|
Christopher Namovicz (202) 586-7120
|
|
Electricity Market Module
|
Jeffrey Jones (202) 586-2038
|
|
Natural Gas Transmission and Distribution Module
|
Joseph Benneche (202) 586-6132
|
|
Oil and Gas Supply Module
|
Ted McCallister (202) 586-4820
|
|
Petroleum Market Module
|
Willaim Brown (202) 586-8181
|
Sponsor
- Office: Office of Integrated Analysis and Forecasting
- Division: Energy Demand and Integration Division
- Model Contact: Dan Skelly
- Telephone: (202) 586-1722
- E-Mail Address: dskelly@eia.doe.gov
Documentation
Archive Media and Installation Manual(s)
NEMS has been archived for the reference case published in the Annual
Energy Outlook 2006, DOE/EIA-0581 (2006). The NEMS archive contains all
of the nonproprietary modules of NEMS as used in the reference case.
The NEMS archive is available on an as-is basis (ftp://eia.doe.gov/pub/oiaf/aeo/aeo2006.zip).
The purpose of the archive is to disclose the source code and inputs used,
as well as to demonstrate that the published results from the AEO reference
case can be reproduced by re-running the model. The archive does not include
the executable model, although it can be generated from the source code
of the model with the appropriate software, some of which is proprietary.
While there is no Installation Manual, brief instructions for compiling
the source code, setting up a run, and replicating
the AEO reference case are included in a file named “readme.txt”
that is included with the archive.
Coverage
- Geographic: Nine Bureau of Census Divisions. Some component
analytical modules represent energy production or conversion at different
levels of regional detail
- Time Unit/Frequency: Annual through 2030
- Product(s): Natural gas, electricity, coal, steam coal, metallurgical
coal, distillate fuel oil, residual fuel oil, motor gasoline, jet fuel,
liquefied petroleum gases, petrochemical feedstocks, kerosene, other
petroleum products, methanol, ethanol, nuclear power, hydropower, and
other renewable sources
- Economic Sector(s): Residential, commercial, industrial, and
transportation end-use consumption; coal supply; oil and gas production
and natural gas markets; utility and nonutility capacity, and generation
of electricity; oil product pricing
Modeling Features
- Model Structure: NEMS is structured as a set of quasi-independent
modules, executed iteratively in a convergence algorithm designed to
simulate annual energy market equilibria over the projection horizon.
- Modeling Technique: NEMS is a simulation of the impacts of
present and planned energy market conditions and regulations on the
supplies of and demands for energy products. Different techniques are
applied in different sectors, as appropriate.
- Special Features: The primary design feature of NEMS is its
modularity. That is, the model is organized by fuel production —
oil, natural gas, coal, and electricity — and by end-use consumption
sector. The modularity allows any single module or group of modules
to be run independently as a debugging aid or for stand-alone analysis.
Furthermore, modularity also allows the flexibility for each sector
to be represented in the most appropriate way, highlighting the particular
issues important for the sector, including the most appropriate regional
structure.
Non-DOE Data Input Sources
All data sources are listed under the appropriate modules of NEMS, which
are listed in the Model Interfaces section.
DOE Data Input Sources
All data sources are listed under the appropriate modules of NEMS, which
are listed in the Model Interfaces section.
Computing Environment
- Hardware Used: Personal computer workstations
- Operating System: Windows XP
- Language/Software Used:
The parts of NEMS using OML are the Electricity Market Module, the
Coal Market Module, the Petroleum Market Module, and the Natural Gas
Transmission and Distribution Module. While the OML libraries are
in the archive, the OML software will not run unless the user licenses
the OML software with KMS Optimization Products and obtains a key.
NEMS can be executed without the Global Insight model, however this
holds all macroeconomic results constant at the reference case levels.
- Memory Requirement (image size): 1 to 2 gigabyte RAM
- Storage Requirement: The archive zip file is 70 megabytes.
The extracted files are about 450 megabytes. Compiling and linking the
model requires about 1.5 gigabytes. Each integrated NEMS run requires
2 to 5 gigabytes of storage.
- Estimated Run Time: Integrated NEMS runs (AEO2006 version)
take about 6 hours each with all modules on. Usually three to six runs
are executed in sequence, or “cycled,” to achieve convergence.
Return to Contents
Coal Market Module (CMM)
Description
The Coal Market Module (CMM) is one of the four energy supply modules
included in the NEMS modeling framework. The CMM simulates mining, transportation,
and pricing of coal, subject to the end-use demand for coal differentiated
by heat and sulfur content. U.S. coal production is represented in the
CMM using 40 separate supply curves — differentiated by region, mine
type, coal rank, and sulfur content. Projections of U.S. coal distribution
are determined in the CMM through the use of a linear programming algorithm
that determines the least-cost supplies of coal for a given set of coal
demands by demand region and sector, accounting for minemouth prices,
transportation costs, existing coal supply contracts, and sulfur and mercury
allowance costs. Over the forecast horizon, coal transportation costs
in the CMM are projected to vary in response to changes in railroad productivity
and the user cost of rail transportation equipment. The CMM produces projections
of U.S. steam and metallurgical coal exports and imports, in the context
of world coal trade. The CMM’s linear programming algorithm determines
the pattern of world coal trade flows that minimizes the production and
transportation costs of meeting a set of regional world coal import demands,
subject to constraints on export capacities and trade flows.
The CMM consists of two submodules: Coal Production Submodule (CPS),
and Coal Distribution Submodule (CDS). The CDS consists of two components:
a domestic component representing the U.S. coal market, and an international
component representing world coal trade.
The Coal Production Submodule (CPS) — The CPS produces
supply-price relationships for 14 coal producing regions, nine coal types
(unique combinations of thermal grade and sulfur content) and two mine
types (underground and surface) addressing the relationship between the
minemouth price of coal and corresponding levels of capacity utilization
at coal mines, annual productive capacity, labor productivity, and the
cost of factor inputs (mine labor, mining equipment, and fuel). The CPS
generates regional, mid-term (to 2030) coal supply curves for input to
the National Energy Modeling System’s (NEMS’s) Coal Distribution,
Electricity Capacity Planning (ECP) and Electricity Fuel Dispatch (EFD)
Submodules.
Coal Distribution Submodule (CDS), Domestic Component
— The domestic component of the Coal Distribution Submodule (CDS)
forecasts coal distribution from 14 U.S. coal supply regions to 14 domestic
demand regions. The model consists of a linear program with constraints
representing environmental, technical and service/reliability constraints
on delivered coal price minimization by consumers. Coal supply curves
are input from the CPS, while coal demands are received from the Residential,
Commercial, Industrial and Electric Power components of NEMS, with export
and import demands being provided by the international component of the
CDS.
Coal Distribution Submodule (CDS), International Component
— The international component of the CDS projects coal trade flows
from 16 coal-exporting regions (five of which are in the United States)
to 20 demand or importing regions (four of which are in the United States)
for three coal types — premium bituminous, low-sulfur bituminous,
and subbituminous. The model consists of supply, demand, trade and transportation
components. The major coal exporting countries represented include: United
States, Australia, South Africa, Canada, Indonesia, China, Colombia, Venezuela,
Poland, and the countries of the Former Soviet Union. The model is used
to forecast international coal trade. It provides projections of U.S.
coal exports and imports to the domestic component of the Coal Distribution
Submodule.
Last Model Update
November 2005
Part of Another Model
Part of the National Energy Modeling System (NEMS)
Sponsor
- Office: Office of Integrated Analysis and Forecasting
- Division: Coal and Electric Power Division
- Model Contact: Diane Kearney
- Telephone: (202) 586-2415
- E-Mail Address: Diane.Kearney@eia.doe.gov
Documentation
- Coal Production Submodule (CPS)
- Energy Information Administration, Model Documentation, Coal Market
Module of the National Energy Modeling System, Part I, DOE/EIA-M060
(2005) (Washington, DC, April 2005)
- Coal Distribution Submodule (CDS), Domestic Component
- Energy Information Administration, EIA Model Documentation, Coal
Market Module of the National Energy Modeling System, Part II-A,
DOE/EIA-M060(2005) (Washington, DC, April 2005)
- Coal Distribution Submodule (CDS), International Component
- Energy Information Administration, EIA Model Documentation, Coal
Market Module of the National Energy Modeling System, Part II-B,
DOE/EIA-M060(2005) (Washington, DC, April 2005), web site http://www.eia.doe.gov/bookshelf/docs.html
Archive Media and Installation Manual(s)
See Integrating Module for the National Energy Modeling System (NEMS)
Coverage
Coal Production Submodule (CPS)
- Geographic: Supply curves for 14 geographic regions
- Time Unit/Frequency: 1990 through 2030
- Product(s): Nine coal types
- Economic Sector(s): Coal producers and importers
Coal Distribution Submodule (CDS), Domestic Component
- Geographic: 14 geographic demand regions representing the
U.S. domestic coal market (regions include the continental United States,
Hawaii, Puerto Rico, U.S. Virgin Islands)
- Time Unit/Frequency: Annual forecasts for 1990-2030
- Product(s): Bituminous, subbituminous, lignite and waste coals
in steam and metallurgical coal markets
- Economic Sector(s): Forecasts coal supply to two Residential/Commercial,
three Industrial, two domestic metallurgical, one Coal-to-liquids, six
Export, and 35 Electricity subsectors
Coal Distribution Submodule (CDS), International Component
- Geographic: 16 export regions (five of which are in the United
States) and 20 import regions (four of which are in the United States)
- Time Unit/Frequency: Each run represents a single forecast
year. Model can be run for any forecast year for which input data are
available
- Product(s): Coking, low-sulfur bituminous coal, and subbituminous
coal
- Economic Sector(s): Coking and steam
Modeling Features
Coal Production Submodule (CPS)
- Model Structure: The CPS employs a regression model to estimate
price–supply relationships for underground and surface coal mines
by region and coal type, using projected levels of capacity utilization
at coal mines, annual productive capacity, productivity, miner wages,
capital costs of mining equipment, and fuel prices.
- Modeling Technique: Three main steps are involved in the construction
of the coal supply curves:
- Calibrate the regression model to base-year production and price
levels by region, mine type (underground and surface), and coal
type
- Convert the regression equation into supply curves
- Construct step–function supply curves for input to the CDS,
ECP, and EFD
Coal Distribution Submodule (CDS), Domestic Component
- Model Structure:The CDS uses 40 coal supply sources representing
12 types of coal produced in 14 supply regions. In the CDS, coal types
are defined as unique combinations of thermal grade, sulfur content
and mine type. The definition of coal types in the CDS differs slightly
from the NEMS CPS, where coal types are defined as unique combinations
of thermal grade and sulfur content. Coal shipments to consumers are
represented by transportation rates specific to NEMS sector and supply
curve/demand region pair, based on historical differences between minemouth
and delivered prices for such coal movements. In principle there are
27,440 such rates for any forecast year; in practice there are less
since many rates are economically infeasible and a unique transportation
rate is not derived for each of the 35 electricity sectors. Coal supplies
are delivered to up to 49 demand subsectors in each of the 14 demand
regions. Currently the NEMS system provides projections of U.S. coal
demand through 2030.
- Modeling Technique: The model utilizes a linear programming
that minimizes delivered cost to all demand sectors.
- Special Features:
- The NEMS residential, commercial, and industrial models provide
demands for those sectors, while the NEMS Petroleum Market Module
provides demands for the coal-to-liquids sector and the NEMS Electricity
Market Module provides demands for the electricity generation sectors.
The CDS provides coal production, Btu conversion factors, minemouth,
transportation and delivered costs for coal supplies to meet these
demands to the NEMS system.
- The CDS interfaces with the international component of the CDS
to determine quantities of U.S. coal export and imports.
- The CDS interfaces with the Coal Market Module’s Coal Production
Submodule to receive supply curves that specify the minemouth price
in relation to the quantity demanded. In turn, the CPS receives
production quantities from the CDS that are used to revise its prices,
if necessary, for subsequent iterations
Coal Distribution Submodule (CDS), International Component
- Model Structure: Satisfies coal import demands at the lowest
cost based on specified supply and transportation costs, and subject
to projected overall levels of available coal export capacities by region
and by coal type.
- Modeling Technique: The model is a Linear Program (LP), which
satisfies demands at all points at the minimum overall “world””coal
cost plus transportation cost and is embedded within the Coal Market
Module.
Non-DOE Data Input Sources
Coal Production Submodule (CPS)
Coal Distribution Submodule (CDS), Domestic Component
- U.S. Department of Commerce
- Monthly Report EM 545
- Monthly Report EM 145
- Association of American Railroads
- Railroad Facts, 2002 Edition (Washington, DC, October
2002), and previous editions
- U.S. Department of Labor, Bureau of Labor Statistics
- PPI for Railroad Equipment, Series ID: WPU144
- Global Insight
These non-DOE sources are used to derive the following inputs for the
domestic component of the CDS:
- U.S. coal import and export quantities by region
- Labor productivity for rail freight shipments
- Term representing the average annual user cost of capital for railroad
equipment
Coal Distribution Submodule (CDS), International Component
DOE Data Input Sources
Coal Production Submodule (CPS)
Coal Distribution Submodule (CDS), Domestic Component
Coal Distribution Submodule (CDS), International Component
None
Computing Environment
See Integrating Module of the National Energy Modeling System
Return to Contents
Commercial Sector Demand Module (CSDM)
Description
The NEMS Commercial Sector Demand Module is a simulation tool based upon
economic and engineering relationships that models commercial sector energy
demands at the nine Census Division level of detail for 11 distinct categories
of commercial buildings. Commercial equipment selections are performed
for the major fuels of electricity, natural gas, and distillate fuel,
for the major services of space heating, space cooling, water heating,
ventilation, cooking, refrigeration, and lighting. The market segment
level of detail is modeled using a constrained life-cycle cost minimization
algorithm that considers commercial sector consumer behavior and time
preference premiums. The algorithm also models the minor fuels of residual
oil, liquefied petroleum gas, steam coal, motor gasoline, and kerosene,
the renewable fuel sources of wood and municipal solid waste; and the
minor services of office equipment (with a separate breakout of personal
computers), and “other” in less detail than the major fuels
and services. Distributed generation and combined heat and power are represented
using a detailed cumulative positive cash flow approach to model penetration
of distributed resources. Numerous specialized considerations are incorporated,
including the effects of changing building shell efficiencies and consumption
to provide district services.
Last Model Update
October 2005
Part of Another Model
National Energy Modeling System (NEMS)
Sponsor
- Office: Office of Integrated Analysis and Forecasting
- Division: Energy Demand and Integration Division
- Model Contact: Erin Boedecker
- Telephone: (202) 586-4791
- E-Mail Address: Erin.Boedecker@eia.doe.gov
Documentation
Energy Information Administration, U.S. Department of Energy, Model Documentation
Report: Commercial Sector Demand Model of the National Energy Modeling
System, DOE/EIA-M066 (2006) (Washington, DC, February 2006).
http://tonto.eia.doe.gov/FTPROOT/modeldoc/m066(2006).pdf
Archive Media and Installation Manual(s)
See Integrating Module of the National Energy Modeling System (NEMS)
Coverage
- Geographic: Nine Census Divisions: New England, Mid Atlantic,
East North Central, West North Central, South Atlantic, East South Central,
West South Central, Mountain, Pacific
- Time Unit/Frequency: Annual through 2025
- Product(s): Electricity, natural gas, distillate, residual
oil, liquefied petroleum gas, steam coal, motor gasoline, kerosene,
wood, municipal solid waste
- Economic Sector(s): Eleven building categories: assembly,
education, food sales, food services, healthcare, lodging, large office,
small office, mercantile and service, warehouse, other. Ten services:
space heating, space cooling, water heating, ventilation, cooking, lighting,
refrigeration, PC-related office equipment, non-PC-related office equipment,
and other
Modeling Features
- Model Structure: Sequential calculation of forecasted commercial
floorspace, service demand, distributed resources penetration, technology
choice, and end-use consumption.
- Modeling Technique: Simulation of technology choice by decision
type, within a service, within a building and Census division, for the
current year of the forecast. Commercial Buildings Energy Consumption
Survey 1995 and 1999 data are used for initial floorspace, market shares,
fuel shares, district service shares. Engineering analyses are used
for initial efficiency estimates.
- Special Features: Technology choice database and simulation
technique is capable of accommodating an extensive range of policy analyses,
including but not limited to demand-side management capital incentives,
tax credits, and equipment efficiency standards.
Non-DOE Data Input Sources
- F.W. Dodge
- Non-residential building construction starts for development
of building survival parameters
- Description of floorspace categorization to enable mapping to
DOE sources
- Arthur D. Little Technical Reports, EPRI Technical Assessment Guide,
GRI Baseline Data Book, Navigant Consulting, Inc. Technical Reports,
ONSITE SYCOM CHP report (references provided in Appendix C to the model
documentation)
- Commercial sector existing equipment characteristics, including
typical equipment capacity, installed capital cost, operating and
maintenance (O&M) cost, expected physical lifetime based on
data from the years 1990–2004
- Equipment research and development (R&D) advances and projected
dates of model introduction, projections for technology availability
encompassing the years 2005–2030
DOE Data Input Sources
- Commercial Building Energy Consumption Survey (CBECS), 1999 characteristics
and building-level consumption, 1995 end-use energy consumption
- Base year floorspace by Census division, building type, building
age cohort, energy-consuming characteristics
- Base year district service consumption totals and relative shares
- Base year Energy Use Intensity (EUI) by Census division, building
type, and energy service
- Base year equipment stock characteristics by Census division and
energy service
- Base year energy consumption for calculation of nonbuilding consumption
to benchmark
- Form EIA-860B, Annual Electric Generator Report — Nonutility,
forms for year 2000
- Historical commercial sector quantities of electricity generated
by Census division, generating fuel, and building type
- Annual consumption of fuels for combined heat and power by Census
division and building type
- Current status of commercial sector generating facilities
- Form EIA-860, Annual Electric Generator Report forms for years 2001–2004
- Historical commercial sector quantities of electricity generated
by Census division, generating fuel, and building type
- Annual consumption of fuels for combined heat and power by Census
division and building type
- Current status of commercial sector generating facilities
- National Renewable Energy Laboratory (NREL) Interlaboratory Documentation,
1990
- Forecasted commercial sector renewable energy demand, by renewable
source and energy service
Computing Environment
See Integrating Module of the National Energy Modeling System (NEMS)
Return to Contents
Electricity Market Module (EMM)
Description
The NEMS Electricity Market Module (EMM) provides a major link in the
NEMS framework. In each model year, the EMM receives electricity demand
from the NEMS demand modules, fuel prices from the NEMS fuel supply modules,
expectations from the NEMS system module, and macroeconomic parameters
from the NEMS macroeconomic module and then estimates the actions taken
by electric utilities and nonutilities to meet demand in the most economical
manner. The EMM then outputs electricity prices to the demand modules,
fuel consumption to the fuel supply modules, emissions to the system module,
and capital requirements to the macroeconomic module. The model is iterated
until a solution is reached for that model year. The EMM consists of four
submodules: Electricity Capacity Planning (ECP), Electricity Fuel Dispatch
(EFD), Electricity Finance and Pricing (EFP), and Electricity Load and
Demand (ELD).
Electricity Capacity Planning Submodule (ECP)
The purpose of the ECP is to determine how the electric power industry
will change its mix of generating capacity over the forecast horizon.
It evaluates retirement decisions for fossil and nuclear plants and captures
responses to environmental regulations, such as the CAAA or limits on
carbon emissions. It includes traditional and nontraditional sources of
supply. The ECP also represents changes in the competitive structure (i.e.,
deregulation). Due to competition, no distinction is made between utilities
and nonutilities as owners of new capacity.
Electricity Fuel Dispatch Submodule (EFD)
The objective of the EFD is to represent the economic, operational, and
environmental considerations in electricity dispatching and trade. The
EFD allocates available generating capacity to meet the demand for electricity
on a minimum cost basis, subject to engineering constraints and to restrictions
on emissions such as SO2, NOx, mercury, and carbon.
Electricity Finance and Pricing Submodule (EFP)
The EFP forecasts financial information for electric utilities on an
annual basis given a set of inputs and assumptions concerning forecast
capacity expansion plans, operating costs, regulatory environment, and
financial data. The outputs of the model include electricity prices by
end use sectors for North American Electric Reliability (NERC) and Census
regions, financial statements, revenue requirements, and financial ratios
for each state of production (generation, transmission, and distribution).
Electricity Load and Demand Submodule (ELD)
Broadly speaking, the ELD submodule has been designed to perform two
major functions:
- Translate total electricity consumption forecasts into system load
shapes
- Translate census division demand data into NERC region data, and
vice versa
Emissions
The EMM tracks emission levels for sulfur dioxide (SO2), nitrogen oxides
(NOx), and mercury (hg). Facility development, retrofitting, and dispatch
are constrained to comply with the constraints to the Clean Air Act Amendments
of 1990 (CAAA90), the Clean Air Interstate Rule (CAIR), and the Clean
Air Mercury Rule (CAMR). An innovative feature of this legislation is
a system of trading emissions allowances. The trading system allows a
utility with a relatively low cost of compliance to sell its excess compliance
(i.e., the degree to which its emissions per unit of power generated are
below maximum allowable levels) to utilities with a relatively high cost
of compliance. The trading of emissions allowances does not change the
national aggregate emissions level set by CAAA90, but it does tend to
minimize the overall cost of compliance.
Last Model Update
September 2005
Part of Another Model
Part of the National Energy Modeling System (NEMS)
Sponsor
- Office: Office of Integrated Analysis and Forecasting
- Division: Coal and Electric Power Division
- Model Contact: Jeffrey Jones
- Telephone: (202) 586-2038
- E-Mail Address: Jeffrey.Jones@eia.doe.gov
Documentation
Energy Information Administration, Model Documentation Report: The Electricity
Market Module of the National Energy Modeling System, DOE/EIA-M068 (Washington,
DC, March 2006) http://tonto.eia.doe.gov/FTPROOT/modeldoc/m068(2006).pdf
Archive Media and Installation Manual(s)
See Integrating Module of the National Energy Modeling System
Coverage
- Geographic: 13 North American Electric Reliability Council
(NERC) Regions and Subregions, called EMM regions
- Time Unit/Frequency: Annually through 2030
- Product(s):
- Electricity prices and price components
- Fuel demands
- Capacity additions
- Capital requirements
- Emissions
- Renewable capacity
- Avoided costs
- Economic Sector(s): Electric utilities and non-utilities.
Modeling Features
- Model Structure:
- ECP — The ECP is executed once a year to determine
planning decisions that must be initiated in the current forecast
year and completed within the planning horizon. The ECP uses a linear
programming (LP) formulation to compete options for meeting future
demands for electricity and complying with environmental regulations.
It selects the strategies that minimize the total present value
of the investment and operating costs over a pre-specified period,
subject to certain conditions. These conditions include requirements
that demands for electricity (accounting for seasonal and daily
fluctuations variations and transmission/distributions losses) are
met, minimum reliability requirements are satisfied, and emissions
limits are not exceeded.
- EFD —The EFD addresses utility and
nonutility supplies endogenously; i.e., the EFD dispatches new nonutility
sources together with utility fossil-fuel, geothermal, biomass,
and nuclear generating capacity. However, existing nonutility supply,
along with nontraditional cogenerators, are considered “must
run:” units and are placed such that they are always dispatched.
Most of these facilities have contracts with utilities to purchase
power, so this treatment ensures that the model output reflects
actual usage. Traditional cogeneration and intermittent renewable
technologies are represented exogenously with the load curve adjusted
prior to dispatching other generating technologies.
- EFP — The EFP is an accounting system that
models regulatory and competitive markets and is completely deterministic.
It has solution algorithms for the generation, transmission, and
distribution stages of production. Pricing mechanisms are implemented
for the generation and transmission stages of production to enhance
the model’s flexibility in simulating emerging pricing techniques
used in the electric power industry.
- ELD — The ELD submodule is designed to be a
fully integrated part of the NEMS framework. The primary functions
of the ELD submodule are to develop regional system load duration
curves from demand estimates for the ECP and EFD modules and to
translate the nine Census division electricity demand estimates
into the 13 NERC regions and subregions that the EMM requires.
- Modeling Technique:
- ECP — The ECP uses a linear programming (LP)
formulation to determine planning decisions for the electric power
industry. The ECP contains a representation of planning and dispatching
in order to examine the tradeoff between capital and operating costs.
It simulates least-cost planning and competitive markets by selecting
strategies for meeting expected demands and complying with environmental
restrictions that minimize the discounted, present value of investment
and operating costs. The ECP explicitly incorporates current emissions
restrictions and provides the flexibility to examine potential regulations
such as emissions taxes and carbon stabilization.
- EFD — The EFD uses a linear programming algorithm
to provide a least-cost solution to allocating (dispatching) capacity
to meet demand. Dispatching involves deciding what generating capacity
should be operated to meet the demand for electricity, which is
subject to seasonal, daily, and hourly fluctuations. The objective
of the EFD is to provide an economic/environmental dispatching procedure.
In an economic (least-cost) dispatch, the marginal source of electricity
is selected to react to each change in load. In environmental dispatching,
the demand for electricity must be satisfied without violating certain
emissions restrictions. The EFD integrates the cost-minimizing solution
with environmental compliance options to produce the least-cost
solution that satisfies electricity demand and restricts emissions
to be within specified limits.
- EFP — The EFP is an accounting system that
models regulatory practice and is completely deterministic. It also
determines prices in a competitive market. It has solution algorithms
for the generation, transmission, and distribution stages of production.
Pricing mechanisms are implemented for the generation and transmission
stages of production to enhance the model’s flexibility in
simulating emerging pricing techniques used in the electric power
industry. There are many pricing mechanisms that could be used for
this purpose. The regulated price uses the traditional cost of service
method based on average costs. The competitive price utilizes marginal
cost pricing. The modular design of this submodule will allow the
user to plug in additional pricing methods as they are needed in
the future.
- ELD — The basic algorithm can be thought of
as an end-use building block approach. The system demand is divided
into a set of components called end-uses. The hourly loads for each
end-use are forecast. Next, the hourly loads of each end-use are
summed to yield the forecast of system load at the customers’
meters (i.e., hourly system sales). The final step is to simulate
transmission and distribution losses. The regional hourly loads
are calculated as the sum of hourly system sales and transmission
and distribution losses.
Non-DOE Data Input Sources
- North American Electric Reliability Council (NERC)
- Reliability Assessments Reports
- Electricity Supply and Demand Database
- Pacific Gas and Electric, Hydro-Quebec, Manitoba Hydro, and British
Columbia Hydro
- Environmental Protection Agency (EPA)
- Allowance Tracking System (ATS)
- NOx Allowance Tracking System (NATS)
- “Analyzing Electric Power Generators Under the CAAA, Appendix
5” (Washington, DC, March 1998)
- Continuous Emissions Monitoring System (CEMS)
- ICF, Incorporated
- A survey of Canadian taxes
- Oak Ridge National Laboratories, Energy Economic Database (EEDB),
various program phases
DOE Data Input Sources
Forms and Publications
- Energy Information Administration, Form EIA-860, Annual Generator
Report
- Capacity and fuel source information
- Energy Information Administration, Form EIA-867, Annual Nonutility
Power Producer Report
- Installed capacity, energy consumption, generation and electric
energy sales to electric utilities and other nonutilities by facility
- Energy Information Administration, Form EIA-767, Steam Electric Plant
Operation and Design Report
- Plant operations and equipment design (including boiler, generator,
cooling system, flue gas desulfurization, flue gas particulate collectors,
and stack data)
- Energy Information Administration, Form EIA-759, Monthly Power Plant
Report
- Monthly data on net generation, consumption of coal, petroleum,
and natural gas; and end-of-the-month stocks of petroleum and coal
for each plant by prime mover and fuel type combination
- Energy Information Administration, Form EIA-411, Coordinated Regional
Bulk Power Supply Program Report
- Actual energy and peak demand for the preceding year and 10 additional
years; existing and future generating capacity; scheduled capacity
transfers; projections of capacity, demand, purchases, sales, and
scheduled maintenance; assessment of adequacy; generating capacity
unavailability; bulk power system maps; near term transmission adequacy;
future critical bulk power facilities that may not be in service
when required; and system evaluation criteria
- F ederal Energy Regulatory Commission (FERC), FERC Form 1, Annual
Electric Utility Report
- Income and earnings, taxes, depreciation and amortization, salaries
and wages, operating revenues, and operating and maintenance costs
- Federal Energy Regulatory Commission, Form FERC-423, Monthly Report
of Cost and Quality of Cost and Quality of Fuels for Electric Plants
- Cost and performance data for both existing and future units
- Distributed Utility Associates, Assessing Market Acceptance and Penetration
for Distributed Generation in the United States, Spring 1999, prepared
for EIA. This report contains cost and performance characteristics for
modeling distributed generation in the Electricity Market Module.
Models and Other
- Energy Information Administration, Office of Integrated Analysis
and Forecasting, Cost and Performance Database for New Generating Technologies
- A database of current costs and performance characteristics
- U.S. Department of Energy, Northern Lights: The Economic and Practical
Potential of Imported Power from Canada, DOE/PE-0079 (Washington,
DC, December 1987)
- Capital costs to build
- Variable and fixed operating and maintenance costs
- Transmission costs
- Various publications on Canadian energy supply cited in the Northern
Lights bibliography
System Modules
- Cogeneration and other electricity production, Commercial and Industrial
Demand Modules
- Generation from renewable sources
- Renewables Fuels Module
- Fossil fuel prices — Fuel Supply Modules of NEMS
- SO2 and mercury emissions — Coal Market Module
- Bond rates — Macroeconomic Activity Module
- Capacity utilization by technology — Renewable Fuels Module
- Electricity consumption by sector and region, traditional cogeneration
Demand Modules
- Fuel and variable O&M costs, fixed O&M costs, SO2 allowance
costs, RPS allowance costs, trade results and nonutility generation
— EFD
- Sectoral consumption by time period — ELD
- New plant capital costs, plant type, ownership type, and retrofit
decisions — ECP
Return to Contents
Industrial Demand Module (IDM)
Description
The Industrial Demand Module is based upon economic and engineering relationships
that model industrial sector energy consumption at the nine Census Division
level of detail. The seven most energy-intensive industries are modeled
at the detailed process step level and eight other industries are modeled
at a less detailed level. The Industrial Demand Module incorporates three
components: buildings; process and assembly; and boiler, steam, and cogeneration.
Last Model Update
October 2004
Part of Another Model
Part of the National Energy Modeling System (NEMS)
Sponsor
- Office: Office of Integrated Analysis and Forecasting
- Division: Demand and Integration Division
- Model Contact: T. Crawford Honeycutt
- Telephone: (202) 586-1420
- E-Mail Address: Crawford.Honeycutt@eia.doe.gov
Documentation
Energy Information Administration, Model Documentation Report: Industrial
Sector of the National Energy Modeling System, DOE/EIA-M064
(Washington, DC, May 2005) http://tonto.eia.doe.gov/FTPROOT/modeldoc/m064(2005).pdf.
Archive Media and Installation Manual(s)
See Integrating Module of the National Energy Modeling System.
Coverage
- Geographic: Nine Census divisions: New England, Mid-Atlantic,
East North Central, West North Central, South Atlantic, East South Central,
West South Central, Mountain, Pacific
- Time Unit/Frequency: Annual through 2025.
Modeling Features
- Model Structure: Nine manufacturing and six nonmanufacturing
industries. The manufacturing industries are further subdivided into
the energy-intensive and nonenergy-intensive industries
- Each industry is modeled as three separate but interrelated components
consisting of the process/assembly component (PA), the buildings
component (BLD), and the boiler/steam/cogeneration component (BSC)
- Modeling Technique: The energy-intensive industries are modeled
through the use of a detailed process flow accounting procedure. The
remaining industries use the same general procedure but do not include
a detailed process flow.
Non-DOE Data Input Sources
- National Energy Accounts
- Historical dollar value of output in the industrial sector
DOE Input Sources
- Form EI-867, Survey of Independent Power Producers
- Electricity generation, total and by prime mover
- Electricity generation for own use and sales
- Capacity utilization
- Manufacturing Energy Consumption Survey 1998, December 2000
- State Energy Data System 2001, August 2004
Computing Environment
See Integrating Module of the National Energy Modeling System
Return to Contents
International Energy Module (IEM)
Description:
IEM is a recursive model of world petroleum supply and demand by region
derived from EIA’s Oil Market Simulation (OMS-PC) Model (retired)
with enhanced detail on U.S. market conditions from the NEMS Petroleum
Market Model (PMM). IEM determines PAD District-level import supply schedules
by refined product type and crude oil grade consistent with estimated
world oil price. IEM outputs include forecasted world oil price, non-OPEC
oil production and oil consumption by region, and OPEC oil production
and capacity utilization.
Last Model Update
September 2005
Part of Another Model
National Energy Modeling System (NEMS)
Sponsor
- Office: Office of Integrated Analysis and Forecasting
- Division: International, Economic, and Greenhouse Gases Division
- Model Contact: Dan Butler
- Telephone: (202) 586-9503
- E-Mail Address: george.butler@eia.doe.gov
Documentation
Energy Information Administration, Model Documentation Report: NEMS
International Energy Module, DOE/EIA-M071 (2005) (Washington, DC,
May 2005) http://tonto.eia.doe.gov/FTPROOT/modeldoc/m07199.pdf.
Archive Media and Installation Manual(s)
See the Integrating Module of the National Energy Modeling System
Coverage
- Geographic:
- Demand Regions: United States, U.S. Territories,
Canada, Mexico, Western Europe, Japan, Australia and New Zealand,
Former Soviet Union, Eastern Europe, China, India, South Korea,
Other Asia, Middle East, Africa, South and Central America
- Supply Regions: United States, Canada, Mexico,
Western Europe, Japan, Australia and New Zealand, Russia, Caspian
& Other Former Soviet Union, Eastern Europe, China, Other Asia,
Middle East, Africa, South and Central America, OPEC Asia, OPEC
Middle East, OPEC North Africa, OPEC West Africa, OPEC South America
- U.S. Detail: PAD District-level import supply
curves
- Time Unit/Frequency: Annual through 2030
- Product(s): Five grades of crude oil, 14 refined products,
two oxygenates (methanol and MTBE), and four intermediate streams
- Economic Sector(s): Major oil-consuming countries, regionalized
above.
Modeling Features
- Model Structure: The model includes three subcomponents: The
World Oil Market (WOM); Petroleum Product Supply (PPS); and Oxygenates
Supply (OS). The structure of the WOM component is based on the OMS
model (now retired), with greater U.S. detail from NEMS PMM.
- Modeling Technique: Recursive simulation (search for equilibrium
oil price), linear programming (derive import supply curves), econometrics
(estimate parameters of OPEC price reaction curve and rest of world
crude demand/supply curves)
- Special Features: None
Non-DOE Data Input Sources
None
DOE Data Input Sources
- Energy Information Administration, Annual Energy Review, Monthly
Energy Review, International Energy Annual, and International
Petroleum Statistics Report (Washington, DC, annually)
- U.S. crude oil supply and demand from PMM, reference demand and
supply for rest of world (ROW) regions, initial (unadjusted) import
supply curves from WORLD LP model
Computing Environment
See Integrating Module of the National Energy Modeling System
Return to Contents
Macroeconomic Activity Module (MAM)
Description
MAM is comprised of three submodules: Macroeconomic, Industry, and Regional.
The Macroeconomic Submodule is the Global Insight Model
of the U.S. Economy and is the same model used by Global Insight Inc.
to generate the economic forecasts behind the company’s monthly assessment
of the U.S. economy. The model is a 1,700-equation specification of the
U.S. economy that forecasts macroeconomic driver variables at the national
level of detail.
The Industry Submodule is a derivative of Global Insight’s
industry and employment models. The models have been tailored in order
to provide the industry and employment detail required by the NEMS modeling
system.
The Regional Submodule was developed by EIA and is comprised
of the Regional Macroeconomic Model, Regional Industry and Employment
Model, and the Regional Commercial Floorspace Model. The first two models
were developed during 2004 for use in the preparation of the Annual
Energy Outlook (AEO) 2005 and the third was re-estimated for AEO2006.
Last Model Update
October 2005
Part of Another Model
National Energy Modeling System (NEMS)
Sponsor
- Office: Office of Integrated Analysis and Forecasting
- Division: International, Economic, and Greenhouse Gases Division
- Model Contact: Ronald Earley
- Telephone: (202) 586-1398
- E-Mail Address: Ronald.Earley@eia.doe.gov
Documentation
Energy Information Administration, Model Documentation Report: Macroeconomic
Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065
(2006) (Washington, DC, January 2006)
http://tonto.eia.doe.gov/FTPROOT/modeldoc/m065(2006).pdf
Archive Media and Installation Manual(s)
See Integrating Module of the National Energy Modeling System
Coverage
- Geographic: Nine Census Divisions
- Time Unit/Frequency: Annual through 2030 (for AEO2006)
- Product(s): Forecasts of domestic macroeconomic driver variables,
at the national, interindustry, and nine Census Division levels of detail
- Economic Sector(s): National and regional economic activity
Modeling Features
- Model Structure: MAM is comprised of three submodules: Macroeconomic,
Industry, and Regional. The Macroeconomic and the Industry submodules
are acquired from Global Insight, Inc. while the Regional submodule
was developed within EIA.
- Modeling Technique: The Macroeconomic and Regional submodules
are statistically estimated models of economic activity. The Industry
submodule employs both an Input-Output structure as well as statistical
estimation techniques.
- Special Features: None
Non-DOE Data Input Sources
Procurement of proprietary models from Global Insight, Inc.:
- Global Insight Model of the U.S. Economy
- Global Insight Industry and Employment Models
Additional data is acquired from non-DOE Federal government sources to
estimate the Regional Model plus acquisition of commercial floorspace
data from McGraw-Hill Construction.
DOE Data Input Sources
Before the MAM executes its models, over 70 energy prices and quantities
are extracted from the output of a NEMS simulation. These represent consumption
of fuels and the prices paid for each fuel plus domestic production of
energy commodities and constitute exogenous inputs to MAM.
Computing Environment
See Integrating Module of the National Energy Modeling System.
Return to Contents
Natural Gas Transmission and Distribution Model
(NGTDM)
Description
The Natural Gas Transmission and Distribution Model (NGTDM) is the component
of the National Energy Modeling System (NEMS) that represents the mid-term
natural gas market. The purpose of the NGTDM is to derive natural gas
supply and end-use prices and flow patterns for movements of natural gas
through the regional interstate network. The prices and flow patterns
are derived by obtaining a 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.
Last Model Update
November 2005
Part of Another Model
Yes, the National Energy Modeling System (NEMS)
Sponsor
- Office: Office of Integrated Analysis and Forecasting
- Division: Oil and Gas Division
- Model Contact: Joseph Benneche
- Telephone: (202) 586-6132
- E-Mail Address: Joseph.Benneche@eia.doe.gov
Documentation
Archive Media and Installation Manual(s)
See Integrating Module of the National Energy Modeling System
Coverage
- Geographic: Demand regions are the 12 NGTDM regions, which
are based on the nine Census Divisions with Census Division 5 split
further into South Atlantic and Florida, Census Division 8 split further
into Mountain and Arizona/New Mexico, and Census Division 9 split further
into California and Pacific, with Alaska and Hawaii handled separately.
Production is represented in the lower 48 at 17 onshore and three offshore
regions. Import/export border crossings include three at the Mexican
border, seven at the Canadian border, at the four existing liquefied
natural gas onshore import terminals and at seven coastal points for
potential new liquified natural gas terminals. Canada is subdivided
into an eastern and western region.
- Time Unit/Frequency: Annual through 2030
- Product(s): Natural gas
- Economic Sector(s): Residential, commercial, industrial, electric
generators, and transportation
Modeling Features
- Model Structure: Modular; three major components: the Interstate
Transmission Submodule (ITS), the Pipeline Tariff Submodule (PTS), and
the Distributor Tariff Submodule (DTS).
- ITS: Integrating module of the NGTDM. Simulates
the natural gas price determination process by bringing together
all major economic factors that influence regional natural gas trade
in the United States. Determines natural gas flows, prices, and
pipeline capacity expansion for a simplified network representing
the interstate natural gas pipeline system.
- PTS: Develops parameters for setting tariffs in
the ITS for storage and for transportation services provided by
interstate pipeline companies
- DTS: Develops markups for distribution services
provided by local distribution companies and intrastate pipeline
companies.
- Modeling Technique:
- ITS: Heuristic algorithm, operates iteratively
until supply/demand convergence is realized across the network
- PTS: Econometric estimation and accounting algorithm
- DTS: Econometric estimation
Non-DOE Data Input Sources
- Information Resources, Inc., Octane Week
- Federal vehicle natural gas (VNG) taxes
- Canadian Association Petroleum Producers Statistical Handbook
- Historical Canadian supply and consumption data
- Mineral Management Service, Federal Offshore Statistics 1995
- Alabama and Louisiana State and Federal offshore production before
1990
- Mineral Management Service
- Revenues and volumes for offshore production in Texas, California,
and Louisiana
- Foster Pipeline Financial Cost Data
- Alaska Department of Natural Resources
- State of Alaska north to south historical natural gas consumption
ratio
- Data Resources Inc., U.S. Quarterly Model
- Yield on AA utility bonds
- Board of Governors of the Federal Reserve System Statistical Release,
Selected Interest Rates and Bond Prices
- Real average yield on 10-year U.S. government bonds
- Oil and Gas Journal, �Pipeline Economics�
- Pipeline annual capitalization and operating revenues
- National Energy Board, “Canada’s Energy Future: Scenarios
for Supply and Demand to 2025,” 2003.
- Basis for setting forecasts for Canadian consuption, unconventional production and offshore production
- Internal Gas Technology Institute report produced for EIA, March 31,
2003
- LNG supply, liquefaction, and shipping, costs
- Internal Project Technical Liaison, Inc report produced for EIA
- Fundamentals of the Global LNG Industry 2001
- Natural gas liquefaction costs
- www.dataloy.com
- Hart Energy Network’s Motor Fuels Information Center at www.hartenergynetwork.com/motorfuels/state/doc/glance/glnctax.htm
- compressed natural gas vehicle taxes by state
DOE Data Input Sources
Forms and Publications
- Energy Information Administration, Form EIA-23, Annual Survey of
Domestic Oil and Gas Reserves
- Annual estimate of gas reserves by type and State
- Energy Information Administration, Form EIA-176, Annual Report of
Natural and Supplemental Gas Supply and Disposition
- Annual natural gas sources of supply, consumption, and flows
on the interstate pipeline network
- Energy Information Administration, Form EIA-857, Monthly Report of
Natural Gas Purchases and Deliveries to Consumers
- Monthly natural gas price and volume data on deliveries to end
users
- Energy Information Administration, Form EIA-895, Monthly Quantity
of Natural Gas Report
- Monthly natural gas production
- Energy Information Administration, Form EIA-860, Annual Electric
Generator Report
- Electric generators plant type and code information, used in
the classification of power plants as core or noncore customers.
Data from this report are also used in the derivation of historical
prices and markups for core and noncore service.
- Energy Information Administration, Form EIA-767, A Steam-Electric
Plant Operation and Design Report
- Electric generators plant type and boiler information, by month,
used in the classification of power plants as core or noncore customers.
Data from this report are also used in the derivation of historical
prices and markups for core and noncore service.
- Energy Information Administration, Form EIA-759, Monthly Power Plant
Report
- Natural gas consumption by plant code and month, used in the
classification of power plants as core or noncore customers. Data
from this report are also used in the derivation of historical prices
and markups for core and noncore services.
- Annual Energy Review, DOE/EIA-0384
- Gross domestic product and implicit price deflator
- Federal Energy Regulatory Commission, Form FERC-2, Annual Report
of Major Natural Gas Companies
- Financial statistics of major interstate natural gas pipelines
- Annual purchases/sales by pipeline (volume and price)
- Federal Energy Regulatory Commission, Form FERC-567, Annual Flow
Diagram
- Pipeline capacity and flow information
- Energy Information Administration, Form EIA-191, Underground Gas
Storage Report
- Base gas and working gas storage capacity and monthly storage
injection and withdrawal levels by region and pipeline company
- Energy Information Administration, Form EIA-846, Manufacturing Energy
Consumption Survey
- Base year average annual industrial end-use prices for natural gas
- Energy Information Administration, Short-Term Energy Outlook,
DOE/EIA-0131
- National forecast targets for first two forecast years beyond
history
- Federal Energy Regulatory Commission, Form 423, Cost and Quality
of Fuels for Electric Utility Plants, DOE/EIA-0191
- Natural gas prices to electric generators
- Department of Energy, Natural Gas Imports and Exports, Office
of Fossil Energy
- Import volumes by crossing in the most recent historical year
Models and Other
- Energy Information Administration, National Energy Modeling System
(NEMS)
- Domestic supply, imports, and demand representations are provided
as inputs to the NGTDM from other NEMS modules.
Computing Environment
See Integrating Module of the National Energy Modeling System
Return to Contents
Oil and Gas Supply Module (OGSM)
Description:
OGSM is used by the Oil and Gas Division in the Office of Integrated
Analysis and Forecasting as an analytic aid to support preparation of
projections of reserves and production of crude oil and natural gas at
the regional and national levels. The annual projections and associated
analyses appear in the Annual Energy Outlook (DOE/EIA-0383) of the Energy
Information Administration. The projections also are provided as a service
to other branches of the U.S. Department of Energy, the Federal Government,
and non-Federal public and private institutions concerned with the crude
oil and natural gas industry.
OGSM projects the following aspects of the crude oil and natural gas
supply industry:
- production
- reserves
- drilling activity
- natural gas imports and exports
Last Model Update
October 2005
Part of Another Model
National Energy Modeling System (NEMS)
Sponsor
- Office: Office of Integrated Analysis and Forecasting
- Division: Oil and Gas Division
- Model Contact: Ted McCallister
- Telephone: (202) 586-4820
- E-Mail Address: Ted.McCallister@eia.doe.gov
Documentation
Energy Information Administration, Documentation of the Oil and Gas
Supply Module (OGSM), DOE/EIA-M063
(Washington, DC, May 2005) http://tonto.eia.doe.gov/FTPROOT/modeldoc/m063(2005).pdf.
Coverage
- Geographic: Six lower 48 onshore supply regions, three lower
48 offshore regions, and three Alaskan regions
- Time Unit/Frequency: Annually through 2030
- Product(s): Crude oil and natural gas
- Economic Sector(s): Oil and gas field production activities
and foreign natural gas trade
Modeling Features
- Model Structure: Modular, containing five major components
- Lower 48 Onshore Supply Submodule
- Unconventional Gas Recovery Supply Submodule
- Offshore Supply Submodule
- Foreign Natural Gas Supply Submodule
- Alaska Oil and Gas Supply Submodule
- Modeling Technique: The OGSM is a hybrid econometric/discovery
process model. Drilling activities in the United States are determined
by the discounted cash flow that measures the expected present value
profits for the proposed effort and other key economic variables. LNG
imports are projected on the basis of unit supply costs for gas delivered
into the lower 48 pipeline network.
- Special Features: Can run stand-alone or within the NEMS.
Integrated NEMS runs employ short-term natural gas supply functions
for efficient market equilibration.
Non-DOE Data Input Sources
- Alaskan Oil and Gas Field Size Distributions, U.S. Geological Survey
- Alaska Facility Cost by Oil Field Size, U.S. Geological Survey
- Alaska Operating Cost, U.S. Geological Survey
- Basin Differential Prices, Natural Gas Week, Washington, DC.
- State Corporate Tax Rate, Commerce Clearing House, Inc., State
Tax Guide
- State Severance Tax Rate, Commerce Clearing House, Inc., State
Tax Guide
- Federal Corporate Tax Rate, Royalty Rate, U.S. Tax Code
- Onshore Drilling Costs — (1) American Petroleum Institute,
Joint Association Survey of Drilling Costs (1970-2003), Washington,
DC.; (2) Additional unconventional gas recovery drilling and operating
cost data from operating companies
- Offshore Lease Equipment and Operating costs, Department of Interior.
Minerals Management Service (correspondence from Gulf of Mexico and
Pacific OCS regional offices)
- Offshore Technically Recoverable Oil and Gas Undiscovered Resources,
Department of Interior. Minerals Management Service (correspondence
from Gulf of Mexico and Pacific OCS regional offices)
- Offshore Exploration, Drilling, Platform, and Production Costs, American
Petroleum Institute, Joint Association Survey of Drilling Costs (2002),
ICF Resource Incorporated (2002), Oil and Gas Journals
- Canadian Wells Drilled, Reserves, and Production Canadian Associationof
Petroleum Producers, Statistical Handbook
- Canadian Unconventional Recoverable Resource Base, National Energy
Board, Canada’s Energy Future, Scenarios for Supply and Demand
to 2025, 2003, Table A6.1
- Canadian Conventional Natural Gas Resources, National Energy Board,
Canada’s Conventional Natural Gas Resources, A Status Report,
April 2004, Table 1.1A
- Unconventional Gas Resource Data — (1) USGS 1995 National Assessment
of United States Oil and Natural Gas Resources; (2) Additional unconventional
gas data from operating companies
- Unconventional Gas Technology Parameters — (1) Advanced Resources
International Internal studies; (2) Data gathered from operating companies.
DOE Data Input Sources
- Onshore Lease Equipment Cost, Energy Information Administration.
Costs and Indexes for Domestic Oil and Gas Field Equipment and Production
Operations (1980-2003), DOE/EIA-0185 (80-03)
- Onshore Operating Cost, Energy Information Administration. Costs
and Indexes for Domestic Oil and Gas Field Equipment and Production
Operations (1980-2003), DOE/EIA-0185 (80-03)
- Emissions Factors, Energy Information Administration
- Oil and Gas Well Initial Flow Rates, Energy Information Administration,
Office of Oil and Gas
- Wells Drilled, Energy Information Administration, Office of Oil and
Gas
- Expected Recovery of Oil and Gas Per Well, Energy Information Administration,
Office of Oil and Gas
- Undiscovered Recoverable Resource Base, Energy Information Administration,
The Domestic Oil and Gas Recoverable Resource Base: Supporting Analysis
for the National Energy Strategy, SR/NES/92-05
- Oil and Gas Reserves, Energy Information Administration. U.S.
Crude Oil, Natural Gas, and Natural Gas Liquids Reserves (1977-2003),
DOE/EIA-0216 (77-03)
Computing Environment
See Integrating Module of the National Energy Modeling System
Return to Contents
Petroleum Market Model (PMM)
Description
The Petroleum Market Model is a simulation of the U.S. petroleum industry.
It includes 12 domestic crude oil production regions, five refining centers
with full processing representations and capacity expansion capability
and gas plant liquid production, and nine marketing regions. The heart
of the model is a linear program optimization which ensures a rational
economic simulation of decisions of petroleum sourcing, resource allocations,
and the calculation of marginal price basis for the products. Eighteen
refined products are manufactured, imported, and marketed. Seven of these
products are specification blended, while the remaining 11 are recipe
blended. Capacitated transportation systems are included to represent
existing intra-U.S. crude oil and product shipments (liquefied petroleum
gas, clean, dirty) via pipeline, marine tanker, barge, and truck/rail
tankers. The export and import of crude oil and refined products are also
simulated. All imports are purchased in accordance with import supply
curves. Domestic manufacture of methanol and ethanol are represented as
though the processing plants are merchant facilities. Transportation is
allowed for ethanol shipments to the demand region terminals for splash
blending. The program is written in FORTRAN, which includes callable subroutines
allowing full communication with the LP portion of the model, which is
in the form of an MPS resident file.
Last Model Update
January 2006
Part of Another Model
National Energy Modeling System (NEMS)
Sponsor
- Office: Office of Integrated Analysis and Forecasting
- Division: Oil and Gas Division
- Model Contact: William Brown
- Telephone: (202) 586-8181
- E-Mail Address: wbrown@eia.doe.gov
Documentation
Archive Media and Installation Manual(s)
See Integrating Module of the National Energy Modeling System.
Coverage
- Geographic: Twelve domestic crude oil production regions (East
Coast, Gulf Coast, Mid-Continent, Permian Basin, Rocky Mountain, West
Coast, Atlantic Offshore, Gulf Offshore(2), Pacific Offshore, Alaska
North, and Alaska Offshore); five refining regions (Petrolum Area Defense
Districts I-V); nine market demand regions, the Census divisions (New
England, Mid Atlantic, East North Central, West North Central, South
Atlantic, East South Central, West South Central, Mountain, Pacific)
- Time Unit/Frequency: Annual through 2030
- Product(s): LPG, conventional motor gasoline, conventional
high-oxygen motor gasoline, reformulated motor gasoline, California
Air Resources Board (CARB) gasoline, E85, jet fuel, distillate fuel
oil, highway diesel, ultra-low sulfur highway diesel, low-sulfur residual
fuel oil, high-sulfur residual fuel oil, petrochemical feedstocks, asphalt/road
oil, marketable coke, still gas, and other
- Refinery Processes: crude distillation, vacuum
distillation, delayed coker, fluid coker, visbreaker, fluid catalytic
cracker, thermal cracker, hydrocracker-dist, hydrocracker-resid,
solvent deasphalter, resid desulfurizer, FCC feed hydrofiner, distillate
HDS, naphtha hydrotreater, catalytic reformer-450 psi, catalytic
reformer-200 psi, alkylation plants (sulfuric and hydrofluoric),
catalytic polymerization, pen/hex isomerization, butane isomerization,
etherification, butanes splitter, dimersol, butylene isomerization,
total recycle isomerization, naphtha splitter, C2-C5 dehydrogenator,
cyclar unit hydrogen plant, sulfur plant, aromatics recovery plant,
lube + wax plants, FCC gasoline splitter, gas/H2 splitter, stream
transfers, fuel system, steam production, power generation.
- Crude Oil: Alaska low sulfur light, Alaska mid
sulfur heavy, domestic low sulfur light, domestic midsulfur heavy,
domestic high sulfur light, domestic high sulfur heavy, domestic
high sulfur very heavy, imported low sulfur light, imported mid
sulfur heavy, imported high sulfur light, imported high sulfur heavy,
imported high sulfur very heavy.
- Transportation Modes: Jones Act dirty marine tanker,
Jones Act clean marine tanker, LPG marine tanker, import tankers,
clean barge, dirty barge, LPG pipeline, clean pipelines, dirty pipelines,
rail/truck tankers. These cover all significant U.S. links.
Modeling Features
- Model Structure: FORTRAN callable subroutines, which update
the linear programming matrix, re-optimize, extract and post-process
the solution results, update system variables, and produce reports.
- Modeling Technique: Optimization of linear programming representation
of refinery processing and transportation which relates the various
economic parameters and structural capabilities with resource constraints
to produce the required product at minimum cost, thereby producing the
marginal product prices in a manner that accounts for the major factors
applicable in a market economy.
- Special Features: Choice of imports or domestic production
of products is modeled, capacity expansion is determined endogenously,
product prices include fixed and environmental costs, oxygenated and
reformulated gasolines and low-sulfur diesel fuel are explicitly modeled.
Non-DOE Data Input Sources
Information Resources Inc. (IRI), WORLD Model data; National Petroleum
Council; ICF Resources, Oil and Gas Journal, Jacobs Consultants
DOE Data Input Sources
- EIA-14, Refiners' Monthly Cost Report
- EIA-182, Domestic Crude Oil First Purchase Report
- EIA-782A, Refiners'/Gas Plant Operators' Monthly Petroleum Product
Sales Report
- EIA-782B, Reseller/Retailer's Monthly Petroleum Product Sales
Report
- EIA-782C, Monthly Report of Prime Supplier Sales of Petroleum
Products Sold for Local Consumption
- EIA-759, Monthly Power Plant Report
- EIA-810, Monthly Refinery Report
- EIA-811, Monthly Bulk Terminal Report
- EIA-812, Monthly Product Pipeline Report
- EIA-813, Monthly Crude Oil Report
- EIA-814, Monthly Imports Report
- EIA-817, Monthly Tanker and Barge Movement Report
- EIA-820, Annual Refinery Report
- EIA-826, Monthly Electric Utility Sales and Revenue Report with
State Distributions
- EIA-856, Monthly Foreign Crude Oil Acquisition Report
- EIA-860B, Electric Generation Report — Nonutility
- FERC-423, Monthly Report of Cost and Quality of Fuels for Electric
Plants
- In addition to the above, information is obtained from several Energy
Information Administration formal publications:
Petroleum Supply Annual, Petroleum Supply Monthly, Petroleum Marketing
Annual, Petroleum Marketing Monthly, Fuel Oil and Kerosene Sales, Natural
Gas Annual, Natural Gas Monthly, Annual Energy Review, Monthly Energy
Review, State Energy Data Report, and State Energy Price
and Expenditure Report.
Computing Environment
See Integrating Module of the National Energy Modeling System
Return to Contents
Renewable Fuels Module (RFM)
Description
The RFM consists of five analytical submodules that represent major renewable
energy resources — landfill gas, wind energy, solar, biomass, and
geothermal electric.
The purpose of the RFM is to define the technological, cost and resource
size characteristics of renewable energy technologies. They are provided
to the Electricity Market Module (EMM) for grid-connected
electricity capacity planning decisions. The characteristics include available
energy capacity, capital costs, fixed operating costs, variable operating
costs, capacity factor, heat rate, construction lead time, and fuel product
price.
The Landfill Gas Submodule (LFG) provides the NEMS Electricity
Market Module with annual regional projections of energy produced from
landfill gas. The submodule provides regional forecasts of electric capacity
to be decremented from electric utility capacity requirements, as well
as capital and operating costs for the calculation of electricity prices.
The purpose of the Wind Energy Submodule (WES) is to project
the cost, performance, and availability of wind-generated electricity,
and provide this information to the Electricity Capacity Planning (ECP)
component of the Electric Market Module (EMM) for building the new capacity
in competition with other sources of electricity generation.
The purpose of the NEMS Solar Submodule (SOLAR) is to define
the costs and performance characteristics of central station Solar Thermal
(ST) and Photovoltaic (PV) electricity generating technologies and to
pass them to the EMM for capacity planning decisions.
The Biomass Submodule passes to the EMM cost and performance
characteristics by EMM regions and years. The fuel component of the cost
characteristics is determined from the regional biomass supply schedules
and then converted to a variable O&M cost.
The purpose of the Geothermal Electric Submodule (GES)
is to provide the Electricity Capacity Planning (ECP) module the amounts
of available geothermal generating capacity and its cost and performance
characteristics for competition in the ECP for new regional electricity
supply in the Western United States.
Last Model Update
February 2001
Part of Another Model
National Energy Modeling System (NEMS)
Sponsor
- Office: Office of Integrated Analysis and Forecasting
- Division: Coal and Electric Power Division
- Model Contact: Christopher Namovicz
- Telephone: (202) 586-7120
- E-Mail Address: cnamovicz@eia.doe.gov
Documentation
Energy Information Administration, Model Documentation Report, Renewable
Fuels Module of the National Energy Modeling System, DOE/EIA-M069
(2001) (Washington, DC, February 2001)
http://tonto.eia.doe.gov/FTPROOT/modeldoc/m0692001.pdf.
Archive Media and Installation Manual(s)
See Integrating Module of the National Energy Modeling System.
Coverage
Landfill Gas Submodule
- Geographic: 13 modified EMM regions
- Time Unit/Frequency: Annual through 2030
- Product(s): Generating capacity
- Economic Sector(s): Electric utility sector
Wind Energy Submodule
- Geographic: 13 EMM Regions: East Central, Texas, Mid-Atlantic,
Mid-America, Mid-Continent, Northeast, New England, Florida, Southeastern,
Southwest, Western, Rocky Mountain, California, South Nevada
- Time Unit/Frequency: Annual through 2030
- Product(s): Electricity
- Economic Sector(s): Electric utility sector, nonutility generators
(NUGS).
Solar Submodule
- Geographic: For PV 13 EMM Regions: East Central, Texas,
Mid-Atlantic, Mid-America, Mid-Continent, Northeast, New England, Florida,
Southeastern, Southwest, Western, Rocky Mountain and Arizona, California
and South Nevada. For solar thermal: Western, Rocky Mountain,
California, South Nevada.
- Time Unit/Frequency: Annual through 2030
- Product(s): Electricity.
Biomass Submodule
- Geographic: 13 EMM Regions
- Time/Unit Frequency: Annual through 2030
- Product(s): Electricity.
Geothermal Electric Submodule
- Geographic: EMM Regions 11, 12, 13
- Time Unit/Frequency: Annual through 2030
- Product(s): Electricity
- Economic Sector(s): Electric generators.
Modeling Features
Landfill Gas Submodule
- Model Structure: Sequential calculation of landfill gas to
electricity generation, followed by derivation of regional and sector
energy shares based on estimates of the percentage of landfill gas combusted
- Modeling Technique: Econometric estimation of municipal solid
waste generation, coupled with an energy share allocation algorithm
for deriving electric generation capacity and energy quantities by sector
and region
- Special Features: Allows for the modeling of regional and
national resource recovery efforts.
Wind Energy Submodule
- Model Structure: Sequential calculation of available wind
capacity by EMM Region, wind class and year, with a deduction of that
year's installed capacity from the remaining available capacity
- Modeling Technique: Accounting function of available windy
land area and conversion of land area to swept rotor area and then to
available generation capacity
- Special Features: Accounting for policy and/or production
incentives.
Solar Submodule
- Model Stucture: Read input file for time-of-day and seasonal
capacity factors by region
- Modeling Technique: None
- Special Features: None.
Biomass Submodule
- Model Structure: Data from nine Census divisions are restructured
into 13 EMM supply regions
- Modeling Technique: None
- Special Features: Accounting for production tax incentives.
Geothermal Electric Submodule
- Model Structure: The model operates at the level of individual
geothermal sites aggregated to segmented EMM regional averages.
- Modeling Technique: Levelized electricity costs from each
supply segment of each site in each region are arrayed in increasing
cost order, then aggregated into three increasing average-cost segments
in each iteration in each year, along with attendant quantities (megawatts)
and average heat rates and capacity factors. Incorporates short-term
cost elasticities of supply, technological optimism, and learning.
Non-DOE Data Input Sources
Landfill Gas Submodule
- Franklin Associates, data prepared for the Environmental Protection
Agency
- National annual quantity of municipal solid waste generated
- Current annual percentages of municipal solid waste combusted
and landfilled
- Government Advisory Associates, Resource Recovery Database,
and Resource Recovery Yearbook
- Plant-specific electricity generation, Btu energy content of
MSW
- Plant locations and energy-consuming sectors
- Electric Power Research Institute, TAG Technical Assessment Guide
- Capital cost; fixed and variable operation and maintenance costs
- Plant capacity factor.
Wind Energy Submodule
- Princeton Economic Research, Incorporated (PERI)
- WNDSLICE preprocessing program
- Electric Power Research Institute and U.S. Department of Energy,
Office of Energy Efficiency and Renewable Energy
- Renewable Energy Technology Characterizations (EPRI TR-109496,
December 1997).
Solar Submodule
- California Energy Commission
- Cost and performance characteristics, solar thermal technology
- Electric Power Research Institute and U.S. Department of Energy,
Office of Energy Efficiency and Renewable Energy
- Renewable Energy Technology Characterizations (EPRI TR-109496,
December 1997)
- Electric Power Research Institute
- Cost and performance characteristics, PV technology
- IRS Tax Code
- 10-percent investment tax credit
- National Solar Radiation Database
Biomass Submodule
None
Geothermal Electric Submodule
DynCorp I&ET, "Geothermal Supply and Cost Performance Characteristics,"
contract deliverable for Purchase Order #36727 for the Energy Information
Administration, Coal and Electric Power Division, Office of Integrated
Analysis and Forecasting, June 30, 2000.
DOE Data Input Sources
Landfill Gas Submodule
- Source reduction factor
- Waste stream adjustment factor
- Landfill gas-fueled capacity
- Projected shares of MSW combusted and landfilled
- Heat content of MSW
- Current capacities for MSW and landfill gas-fueled units.
Wind Energy Submodule
- Energy Information Administration, Annual Energy Review 1991,
DOE/EIA-0384(91) (Washington, DC, June 1992)
- Pacific Northwest Laboratory
- Reports PNL-7789, DOE/CH10093-4, and PNL-3195
- DOE/EPRI, Turbine Verification Program — "TVP Project-at-a-Glance"
Series.
Solar Submodule
- Electric Power Research Institute and U.S. Department of Energy,
Office of Energy Efficiency and Renewable Energy, "Technology Characterizations,"
EPRI (TR-109496, December 1997).
Biomass Submodule
None
Geothermal Electric Submodule
None
Computing Environment
See Integrating Module of the National Energy Modeling System
Return to Contents
Residential Sector Demand Module (RSDM)
Description
The NEMS Residential Sector Demand Module is an integrated dynamic modeling
system that projects residential energy demand by service, fuel, and Census
Division. The modeling methodology is based on accounting principles and
considers important issues related to consumer behavior. Housing and equipment
stocks are tracked over the forecast period for ten major services. The
major services considered are space heating, space cooling, clothes washing,
dish washing, water heating, cooking, clothes drying, lighting, refrigeration,
and freezers. A logit function is used to estimate market shares of each
equipment technology within each major service based on either the installed
capital and operating costs or the life-cycle cost. Miscellaneous appliance
consumption is calculated as a function of Unit Energy Consumption (UEC),
a measure of energy intensity developed from the Residential Energy Consumption
Survey (RECS) database.
Last Model Update
October 2005
Part of Another Model
The Residential Sector Demand Module is designed, executed, and maintained
as part of the National Energy Modeling System (NEMS)
Sponsor
- Office: Office of Integrated Analysis and Forecasting
- Division: Energy Demand and Integration Division
- Model Contact: John Cymbalsky
- Telephone: (202) 586-4815
- E-Mail Address: John.Cymbalsky@eia.doe.gov
Documentation
Energy Information Administration, Model Documentation Report: Residential
Sector Demand Model of the National Energy Modeling System, DOE/EIA-M067
(2005) (Washington, DC, April 2005). http://tonto.eia.doe.gov/FTPROOT/modeldoc/m067(2005).pdf
Archive Media and Installation Manual(s)
See Integrating Module of the National Energy Modeling System
Coverage
- Geographic: Nine Census Divisions: New England, Middle Atlantic,
East North Central, West North Central, South Atlantic, East South Central,
West South Central, Mountain, Pacific
- Time Unit/Frequency: Annual through 2030
- Product(s): Fuel consumption including: electricity, natural
gas, distillate, liquefied petroleum gas, kerosene, geothermal, wood,
solar, and coal; energy consumption per household; equipment stock and
efficiency.
- Economic Sector(s): Domestic residential sector
- Services: Space heating, space cooling, clothes
washers, dishwashers, water heating, cooking, clothes drying, refrigeration,
freezers, lighting, color televisions, furnace fans, personal computers,
electric appliances, other appliances, secondary space heating
- Housing Types: Single-family, multifamily, mobile
homes
Modeling Features
- Model Structure: Sequential algorithm composed of housing
and equipment stock flow algorithms, technology choice algorithm, housing
shell integrity algorithm, end-use consumption, and emissions calculations
- Modeling Technique: Housing and equipment stock turnover are
modeled using linear decay functions. Market shares for each type of
equipment choice are based on a logit function employing installed capital
costs and operating costs. Unit energy consumption estimates, fuel prices,
and equipment market shares are user inputs that drive the calculation
of final end-use consumption
- Special Features: Technology choice logit function has the
ability to use installed capital, and operating costs or life-cycle
costs to determine new market shares
Non-DOE Data Input Sources
- American Home Appliance Manufacturers Association
- Shipment-weighted efficiency ratings for refrigerators, clothes
washers, dishwashers, freezers, room air conditioners
- U.S. Bureau of the Census, Current Construction Report-Series–C25
Characteristics of New Housing: 2004(Washington, DC, 2005)
- New housing and base year market shares for some services and
equipment types
- Gas Appliance Manufactures Association, Consumers' Directory for
Certified Efficiency Ratings, 2004
- Lawrence Berkeley Laboratory, Energy Data Sourcebook for the U.S.
Residential Sector, 1997
- Residential equipment technical characterization data
- Expected minimum and maximum appliance lifetimes
- Expected lifetimes of housing types
- Navigant Consulting, EIA Technology Forecast Updates — Residential
and Commercial Buildings, 2004
- Arthur D. Little, Electricity Consumption by Small End Uses in
Residential Buildings, 1998
DOE Data Input Sources
- U.S. Department of Energy, Energy Information Administration, A
Look at Residential Energy Consumption in 2001
- Base-year market shares for services and equipment types
- Base-year housing stock
- Unit energy consumption values (UECs).
Computing Environment
See Integrating Module of the National Energy Modeling System.
Return to Contents
Transportation Sector Module (TRAN)
Description
The Transportation Sector Module incorporates an integrated modular design
based upon economic, engineering, and demographic relationships that model
transportation sector energy demand at the nine Census Division level
of detail. The Transportation Sector Module comprises the following components:
Light Duty Vehicles, Light Duty Fleet Vehicles, Commercial Light Trucks,
Freight Transport (truck, rail, and marine), Aircraft, and Miscellaneous
Transport (military, mass transit, and recreational boats). The model
provides sales and stock estimates for conventional and alternative fuel/advanced
technology light duty vehicles, heavy duty vehicles, and aircraft. Energy
consumption and travel demand is estimated for all transportation modes
and is disaggregated by fuel type and market segment.
Last Model Update
September 2005
Part of Another Model
Yes, part of the National Energy Modeling System (NEMS)
Sponsor
- Office: Office of Integrated Analysis and Forecasting
- Division: Energy Demand and Integration Division
- Model Contact: John Maples
- Telephone: (202) 586-1757
- E-Mail Address: John.Maples@eia.doe.gov
Documentation
Energy Information Administration, Model Documentation Report: Transportation
Sector Model of the National Energy Modeling System, DOE/EIA-M070 (2005)
(Washington, DC, June 2005). http://tonto.eia.doe.gov/FTPROOT/modeldoc/m070(2005).pdf
Archive Media and Installation Manual(s)
See Integrating Module of the National Energy Module System
Coverage
- Geographic: Nine Census Divisions: New England, Mid Atlantic,
East North Central, West North Central, South Atlantic, East South Central,
West South Central, Mountain, Pacific
- Time Unit/Frequency: Annual through 2030
- Product(s): Motor gasoline, aviation gasoline, diesel/distillate,
residual oil, electricity, jet fuel, LPG, CNG, methanol, ethanol, hydrogen,
lubricants, pipeline fuel natural gas
- Economic Sector(s): Forecasts are produced for personal and
commercial travel, freight trucks, railroads, domestic and international
marine, domestic and international aviation, mass transit, military
use
Modeling Features
- Model Structure: Light-duty vehicles are classified according
to the six EPA size classes for cars and light trucks. Freight trucks
are divided into three weight classes: Class 3, Classes 4 through 6,
and Classes 7 and 8. Buses are disaggregated into commuter, intercity,
and school classifications. The air transport module addresses domestic
and international passenger and freight travel by regional, narrow body,
and wide body aircraft. Rail transportation is composed of freight rail
and three modes of personal rail travel: commuter, intercity and transit.
Water borne freight is divided into domestic and international categories.
- Modeling Technique: The modeling techniques employed in the
Transportation Sector Module vary by module: economet rics for passenger
travel, freight travel, and new vehicle market shares; economic and
engineering based for technology adoption in the light duty vehicle,
heavy duty vehicle, and aircraft models; and structural for light-duty
vehicle, heavy duty vehicle, and aircraft capital stock estimations.
- Special Features: The Transportation Sector Module has been
designed to allow the user to examine changes in energy demand based
on changes in various demand drivers and policy. The range of policy
issues that the transportation model can evaluate are: fuel taxes and
subsidies, fuel economy levels by size class, CAFE levels, vehicle pricing
policies by size class, demand for performance within size classes;
fleet vehicle sales by technology type, alternative fuel/advanced technology
light duty vehicle sales shares, the Energy Policy Act, travel reduction,
criteria emission standards, and greenhouse gas emissions.
Non-DOE Data Input Sources
- National Energy Accounts
- U.S. Department of Transportation, Federal Highway Administration,
Highway Statistics
- U.S. Environmental Protection Agency, Office of Transportation and
Air Quality, Light-Duty Automotive Technology and Fuel Economy Trends:
1975 Through 2004, EPA420-S-04-002, April 2004
- National Highway Traffic and Safety Administration, Mid-Year Fuel
Economy Report, 2004
- Oak Ridge National Laboratory, Transportation Energy Data Book
Edition 24, ORNL-6973, December 2004
- Oak Ridge National Laboratory, Fleet Characteristics and Data
Issues, January 2003
- Department of Commerce, Bureau of the Census, Truck Inventory and
Use Survey Data 1997
- State of California, California Air Resources Board, California LEV
Regulations with Amendments Effective August 14, 2004
- U.S. Department of Transportation, Bureau of Transportation Statistics,
Office of Airline Information, Air Carrier Summary Data
- Mitre Corporation for U.S. Department of Transportation, Federal
Aviation Administration, Airport Capacity Benchmark Report 2004, September
2004
- Jet Information Services Inc., World Jet Inventory: Year-End 2004,
December 2004
- Boeing Company, Current Market Outlook 2004, December 2004
DOE Data Input Sources
- State Energy Data System (SEDS), DOE/EIA-0214 (99), May 2001
- Short-Term Energy Outlook (STEO), DOE/EIA-0202 (October 2005)
Computing Environment
See Integrating Module of the National Energy Modeling System
Return to Contents
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