Models of the National Energy
Modeling System

Description:

The National Energy Modeling System (NEMS) represents a general equilibrium solution of the interactions between the U.S. energy markets and the economy. The model achieves a supply-and-demand balance in the end-use demand regions, defined as the nine Census Divisions, by solving for the prices of each energy type so that the quantities producers are willing to supply equal the quantities consumers wish to consume. The system reflects market economics, industry structure, and energy policies and regulations that influence market behavior.

Last Model Update:

October 2000

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	Daniel Skelly (202) 586-1722
Residential Sector Demand Module	John H. Cymbalsky (202) 586-4815
Commercial Sector Demand Module	Erin Bodecker (202) 586-4791
Transportation Sector Demand Module	John Maples (202) 586-1757
Industrial Demand Module	Crawford Honeycutt (202) 586-1420
Macroeconomic Activity Module	Ron Earley (202) 586-1398
International Energy Module	Dan Butler (202) 586-9503
Coal Market Module	Mike Mellish (202) 586-2136
Renewable Fuels Module	Tom Petersik (202) 586-6582
Electricity Market Module	Robert Eynon (202) 586-2315
Natural Gas Transmission and Distribution Module	Joseph Benneche (202) 586-6132
Oil and Gas Supply Module	Ted McCallister (202) 586-4820
Petroleum Market Module	Han-Lin Lee (202) 586-4247
DRI Model of the U.S. Economy	Ron Earley (202) 586-1398
World Oil Refining, Logistics, and Demand Model	Dan Butler (202) 586-9503

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:

• Energy Information Administration, I ntegrating Module of the National Energy Modeling System: Model Documentation, DOE/EIA-M057 (2001) (Washington, DC, December 2000)
  http://www.eia.gov/FTPROOT/modeldoc/m057(2001).pdf
  
• Energy Information Administration, National Energy Modeling System: An Overview 2000, DOE/EIA-0581(2000) (Washington, DC, March 2000)
  http://www.eia.gov/FTPROOT/forecasting/05812000.pdf.

Archive Media and Installation Manual(s):

Archived for the reference case published in the Annual Energy Outlook, 2001, DOE/EIA-0383 (2001). The archive contains all of the modules of NEMS as used in the reference case. The archives containing source code, inputs and outputs, is stored at ftp://eia.doe.gov/pub/temp/aeo/aeo2001.exe as a self-extracting zip file. The archive does not contain an executable for NEMS. Preparing an executable requires Compaq Visual Fortran (http://www.compaq.com/fortran/index.html) and the Optimization Modeling Library from Ketron Management Science (http://ketronms.com).

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 2020
• 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 provides an equilibrium framework in which the economic forces of supply and demand can be simulated. Its modular structure allows each individual module to be represented in a different fashion if desired.
• Modeling Technique: NEMS is a simulation of the impacts of present and planned energy market conditions upon 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 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: A multiuser environment is implemented using two networked Compaq Proliant Servers, model 5500R, each with four 550 mhz Pentium III Xeon processors, 2.5 gigabytes RAM, 54 gigabytes hard disk space; supplemented by a distributed computer sharing system using 8 Dell workstations (model Precision 410), each with two 500mhz Pentium III processors, 512 megabyte RAM, and 18 gigabytes hard disk space.
• Operating System: Windows NT 4
• Language/Software Used: Compaq Visual FORTRAN 6.1; Ketron Management Science's Optimization Modeling Library; MKS Toolkit
• Memory Requirement (image size): 305 megabytes
• Storage Requirement: 2 gigabytes
• Estimated Run Time: 2.5-3 hours CPU time for a single run with all modules on. Often, 3 runs are executed in sequence, or "cycled," to improve convergence. Such 3-cycle runs take between 7.5 and 9 hours.

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Description:

The CMM has three submodules. The Coal Production Submodule produces supply-price relationships for 12 coal types and 11 producing regions, addressing the relationship between the minemouth price of coal and corresponding levels of coal production, labor productivity, and the cost of factor inputs (mine labor, mining equipment, and fuel). The model serves as a major component in the National Energy Modeling System (NEMS). The purpose of the model is to produce annual domestic coal supply curves for the mid-term (to 2020) for the Coal Distribution Submodule of the Coal Market Module of NEMS

Coal Distribution Submodule — United States coal production, national and international coal transportation industries. The model is used to forecast annual coal supply and distribution to domestic markets

Coal Distribution Submodule (International Coal Flows) — 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, Columbia, Venezuela, Poland, and the countries of the Former Soviet Union. The model is used to forecast international coal trade. It provides U.S. coal export forecasts to the domestic component of the Coal Distribution Submodule.

Last Model Update:

November 2000

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: Michael Mellish
• Telephone: (202) 586-2136
• E-Mail Address: Michael.Mellish@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 (01) (Washington, DC, January 2001)
• Coal Distribution Submodule (CDS):
  • Energy Information Administration, EIA Model Documentation, Coal Market Module of the National Energy Modeling System, Part II-A, DOE/EIA-M060 (01) (Washington, DC, January 2001)
• Coal Distribution Submodule (CDS) (International Coal Trade):
  • Energy Information Administration, Model Documentation, Coal Market Module of the National Energy Modeling System, Part II-B, DOE/EIA-M060 (01) (Washington, DC, January 2001
    http://www.eia.gov/FTPROOT/modeldoc/m060(2001).pdf.

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 11 geographic regions
• Time Unit/Frequency: 1990 through 2020
• Product(s): 12 coal types
• Economic Sector(s): Coal producers and importers.

Coal Distribution Submodule (CDS):

• Geographic: United States, including Hawaii, Puerto Rico, and the U.S. Virgin Islands
• Time Unit/Frequency: Annual forecasts for 1990-2020
• Product(s): Bituminous, subbituminous and lignite coals in steam and metallurgical coal markets
• Economic Sector(s): Forecasts coal supply to 2 residential/commercial, 3 industrial, 2 domestic metallurgical, 4 export, and 7 electric utility subsectors (a synthetic fuel subsector is present but not operational in the CDS) to 13 domestic demand regions.

Coal Distribution Submodule (CDS) (International Coal Flows):

• Geographic: 16 export regions (5 of which are in the United States) and 20 import regions (4 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 production, 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

Coal Distribution Submodule (CDS):

• Model Structure: The CDS uses 35 coal supply sources representing 12 types of coal produced in 11 supply regions. 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 8,190 such rates for any forecast year; in practice there are less since many rates are economically infeasible. Coal supplies are delivered to up to 18 demand sectors in each of the 13 demand regions. A single model run represents a single year, but up to 31 consecutive years (1990-2020) may be run in an iterative fashion. Currently, the NEMS system provides demand input for the 1990-2020 period
• Modeling Technique: The model utilizes a linear programming that minimizes delivered cost to all demand sectors
• Special Features:
  • All demands are exogeneous to the CDS
  • Supply curves (there are 35 supply sources) depicting the U.S. coal reserve base are exogenous to CDS and are reported in the CDS from 11 coal supply regions
  • CDS currently contains no descriptive detail on coal transportation by different modes and routes. Transportation modeling consists only of sector-specific rates between demand regions and supply curves that are adjusted annually for changes in factor input cost changes, the producer price index for transportation equipment, and a time trend
  • CDS output includes tables of aggregated output for NEMS system and approximately 20 single-year reports providing greater regional and sectoral detail on demands, production distribution patterns, and rates charged.
  • Coal imports are treated as a static input that is subtracted from demand before solving the CDS. Imports are reported to NEMS and detailed in some single-year reports
  • CDS reports minemouth, transport, and delivered coal prices, coal shipment origins and destinations (by region and economic sub-sector), and energy and sulfur content of coal

Coal Distribution Submodule (CDS) (International Coal Trade):

• 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
• Special Features: The model is designed for the analysis of legislation concerned with SO2 emissions and trade of nonconventional coals (subbituminous coals).

Non-DOE Input Sources:

Coal Production Submodule (CPS):

• U.S. Department of Labor, Bureau of Labor Statistics
  • Average Hourly Earnings of Production Workers (Coal Mining), Series ID: EEU10120006
  • PPI for Mining Machinery and Equipment, Series ID: PCU3532#
• DRI/McGraw Hill
  • Yield on Utility Bonds

Coal Distribution Submodule (CDS):

• U.S. Department of Commerce
  • Form EM-545
• U.S. Department of Commerce
  • Form IM-145
• Association of American Railroads (Washington, DC, quarterly)
  • AAR Railroad Cost Indices
• Rand McNally and Co. (Chicago, IL, 1988)
  • Handy Railroad Atlas of the United States
• Caplan, Abby, et al, eds. (Washington, DC, 1996)
  • 1996-1997 Fieldston Coal Transportation Manual

Coal Distribution Submodule (CDS) (International Coal Flows):

• SSY Consultancy and Research, McClosky Coal Information, Ltd., and the International Energy Agency. Published trade and business journal articles, including Coal Week International, Energy Publishing, LLC's International Coal Trade, Financial Times International Coal Report, and World Coal
  • Coal Import Demands
  • Coal Supply Curves
  • Diversity Constraints
  • Ocean Freight Rates
  • Sulfur Emission Constraints
  • Subbituminous and High-Sulfur Coal Constraints.

DOE Data Input Sources:

Coal Production Submodule (CPS):

• Energy Information Administration, Forms EIA-3, EIA-3A, EIA-5, EIA-5A, EIA-6A, and EIA-7A
  • Historical data for the regression model used for estimating coal supply curves
  • Base year values for U.S. coal production, productivity, and prices
  • Heat and sulfur content averages, and carbon emission factors by supply curve
• Energy Information Administration, Electric Power Annual 1998, Volume II (DOE/EIA-0348(99) (Washington, DC, October 1999)
  • Base year electricity prices and wages
• Energy Information Administration, State Energy Price and Expenditure Report 1997 (DOE/EIA-0214(97) (Washington, DC, September 1999).
  • Historical electricity prices for the regression model used for estimating coal supply curves.
• Federal Energy Regulatory Commission
  • FERC Form-423 database

Coal Distribution Submodule (CDS):

• Data Sources:
  • Form EIA-3, Quarterly Coal Consumption Report, Manufacturing Plants
  • Form EIA-5, Coke Plant Report Quarterly
  • Form EIA-6A, Coal Distribution Report
  • Form EIA-7A, Coal Production Report
  • FERC Form 423, Monthly Report of Cost and Quality of Fuels for Electric Plants
  • FERC Form 580, Interrogatory on Fuel and Energy Purchase Practices
• Physical: Forecasts of annual coal supply tonnages (and trillion Btu) by economic sector and subsector, coal supply region, coal Btu, sulfur content, and demand region
  • Demand shares by sector and region: (1) residential/commercial (trillion Btu); (2) industrial steam coal (trillion Btu); (3) industrial metallurgical coal (trillion Btu); (4) import supplies (millions of short tons)
  • Coal supply/transportation contracts: (1) coal supply regions; (2) coal demand regions; (3) coal quality (Btu and sulfur content); (4) contract annual volumes (trillion Btu); (5) contract expiration dates (forecast year)
  • Coal quality data for supply curves: (1) million Btu per short ton: (2) lbs. sulfur per million Btu
  • Coal quality specifications for regional subsectoral demands on electricity generation and other sectors
• Economic: Forecasts of annual minemouth, transportation, and delivered coal prices by coal type, economic sector, coal demand, and supply regions
  • Supply curves relating minemouth prices to cumulative production levels
  • Transportation rates: (1) 1987 dollars per short ton; (2) specified by subsector, differ by sector; (3) differ also by supply and demand region pair
  • Transportation rate escalation factors: (1) exogenous; (2) based on estimates of factor input costs (labor, fuel, etc.); (3) used to adjust for productivity change
  • Minemouth price adjustments: (1) can be made by supply region and forecast year; (2) currently used only by forecast year; (3) used to escalate and de-escalate transportation rates for forecast year
  • Transportation rate adjustments: (1) can be used by demand sector and demand region; (2) derived from off-line program that subtracts base year minemouth costs from delivered costs reported in Forms EIA-3 and -5, and FERC Form 423 to produce transport rate, calculates ratio between model rate and rate from forms, preserve ratio as model parameter; (3) used to calibrate rates in model

Coal Distribution Submodule (CDS) (International Coal Trade):

None.

Computing Environment:

See Integrating Module of the National Energy Modeling System.

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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 cogeneration 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:

December 2000

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:

U.S. Department of Energy, Energy Information Administration, Model Documentation Report: Commercial Sector Demand Model of the National Energy Modeling System, DOE/EIA-M066 (2001) (Washington, DC, December 2000)
http://www.eia.gov/FTPROOT/modeldoc/m066(2001).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, and Pacific
• Time Unit/Frequency: Annual through 2020
• 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 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 data base 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 Input Sources:

• Data Resources Inc. (DRI), F.W. Dodge
  • Commercial sector floorspace growth by Census division and building type
  • Description of floorspace categorization to enable mapping to DOE sources
• Arthur D. Little Technical Reports, EPRI Technical Assessment Guide, GRI Baseline Data Book (references provided in Appendix C to the report)
  • 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 1990-1998
  • Equipment research and development (R&D) advances and projected dates of model introduction, projections for technology availability encompassing the years 1999-2015
• Onsite Energy commercial combined heat and power report
  • Current and projected distributed generation technology cost and performance.

DOE Data Input Sources:

• Form EIA-871, Commercial Buildings Energy Consumption Survey 1995 (CBECS 1995)
  • 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 years 1995-1998
  • Historical commercial sector quantities of cogenerated electricity by Census division, generating fuel, and building type
  • Annual consumption of fuels for cogeneration 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).

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Description:

The DRI Model represents national economic production and income corresponding to the National Income and Product Accounts published by the Department of Commerce. These forecasts of national activity extend 25 years and serve as the basis for EIA macroeconomic forecasts. EIA alters the DRI forecasts so that the energy variables included in the macro- economic model correspond to EIA energy price forecasts.

Last Model Update:

August 2000

Part of Another Model?

No

Sponsor:

• Office: Office of Integrated Analysis and Forecasting
• Division: International, Economic, and Greenhouse Gases Division
• Model Contact: Kay A. Smith
• Telephone: (202) 586-1455
• E-Mail Address: Kay.Smith@eia.doe.gov

Documentation:

Energy Information Administration, Documentation of the DRI Model of the U.S. Economy, DOE/EIA-M061
(Washington, DC, December 1993)
http://www.eia.gov/FTPROOT/modeldoc/m061.pdf.

Archive Media and Installation Manual(s):

See Integrating Module of the National Energy Modeling System.

Coverage:

• Geographic: Quarterly forecasts for 25 years at a national level
• Time Unit/Frequency: Quarterly
• Product(s): Personal consumption expenditures, producers durable equipment investment, nonresidential construction, residential construction and nondefense Federal Government expenditures, Federal defense expenditures, exports, imports, inventory change in final goods, and inventory change in materials and work-in-process
• Economic Sector(s): Domestic spending, domestic income, tax policy, international, financial, inflation, simulated supply potential, expectations.

Modeling Features:

• Model Structure: The DRI Model forecasts roughly 1,200 concepts encompassing final demands, aggregate supply, prices, incomes, interest rates, industrial detail, and international trade. There are eight blocks to the model: Domestic spending, domestic income, tax sector, prices, financial, international trade, expectations, and aggregate supply. The domestic spending, income and tax blocks correspond to the National Income and Product Accounts. The rest of the blocks interact with the blocks describing domestic activity
• Modeling Technique: Econometric simulation modeling techniques
• Special Features: None.

Non-DOE Input Sources:

• U.S. Department of Commerce (Washington, DC)
  • Consumption
  • Investment
  • Residential construction
  • Exports
  • Imports
  • Inventory change
  • Defense spending.

DOE Data Input Sources:

None.

Computing Environment:

See Integrating Module of the National Energy Modeling System.

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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 Load and Demand-Side Management (LDSM).

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 is intended to consider investment decisions for both demand- and supply-side options. However, consumer responses are assumed to be represented in the end-use demand modules, so the structure for demand-side management (DSM) options is not utilized within the ECP. 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).

Load and Demand-Side Management Submodule (LDSM):

Broadly speaking, the LDSM submodule has been designed to perform four major functions:

• Translate total electricity consumption forecasts into system load shapes
• Develop utility DSM programs for potential inclusion in future utility capacity expansion plans
• Translate census division demand data into NERC region data, and vice versa
• Report DSM impact on regional system demand.

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) and other pollution constraints. 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 2001

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, February 2001)
http://www.eia.gov/FTPROOT/modeldoc/m0682001.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 2020
• 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 practice 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
  • LDSM — The LDSM submodule is designed to be a fully integrated part of the NEMS framework. The submodule models the impact of DSM activities in terms of changes in load shapes. To do this, the LDSM submodule has a database of end-use load shapes for each of the thirteen EMM regions, being modeled in the NEMS framework. The LDSM also uses a technologies database develops jointly with the demand modules. Individual DSM options then match a base technology ("FROM" technology) to a more efficient DSM technology ("TO" technology). The energy changes and the resulting changes in load shapes (delta load shapes) are computed for each option. These constitute the unit level impact of DSM options. To compute the system level impacts, the DSM options must first be penetrated over time, and then aggregated to a form that can be completed against supply-side options. Details of these processes are given in the sections that follow. The three primary functions of the LDSM submodule are to (a) develop regional system load duration curves from demand estimates for the ECP and EFD modules, (b) screen potential DSM options for analysis by the EMM Capacity Planning module, and (c) supply the demand modules with feedback from the ECP concerning the shifts in end-use technology resulting from the optimal choice of DSM options. In addition to these three functions, the LDSM also translates 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 emissions restrictions imposed by the CAAA90 and provides the flexibility to examine potential regulations such as emissions taxes and carbon stabilization
  • EFD — The EFD uses an heuristic approach 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 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 one that has been included initially in this submodule is the traditional cost of service method. The modular design of this submodule will allow the user to plug in additional pricing methods as they are needed in the future
  • LDSM — The basic algorithm can be thought of as 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 Input Sources:

• The EPA 1985 National Utility Reference File (NURF), 1989. NURF data were submitted to the 10 EPA regions for review of the following key elements: 1985 SO2 emissions and emissions rate, 1985 total heat input, and 1985 SO2 emission limits and associated variables
• Data Resources/McGraw-Hill, Inc., Energy Review, Winter 1986-1987
• ICF, Incorporated
  • A survey of Canadian taxes
• New England Power Pool, New York Power Pool, and Western Area Power Administration
• NERC Mid-Atlantic Area Council and Northeast Power Coordinating Council
  • Reliability data
  • Electricity prices are calculated by use of a traditional cost of service discounting method for regulated regions, marginal cost calculations for competitive regions, and a hint of both methods when warrented. Accounting also takes into consideration regulatory nuances among regions
• Pacific Gas and Electric, Hydro-Quebec, Manitoba Hydro, and British Columbia Hydro
• Environmental Protection Agency: The National Allowance Data Base, Version 2.11, March 1993
  • Data base elements on utility combustion sources
• 1985 National Emissions Data System (NEDS) submittals
• EPRI, Technical Assessment Guide (TAG) Electricity Supply, 1989
• Oak Ridge National Laboratories, Energy Economic Database (EEDB), various program phases
• Electric Power Research Institute, Technical Assessment Guide (EPRI-TAG1993)
  • Photovoltatic cost and performance data
• EPRI, 1991: United Engineers and Constructors, Technical Feasibility and Costs of Selective Catalytic Reduction NOx Control, GS-7276
• EPRI, 1991: United Engineers and constructors, Economic Evaluation of Flue Gas Desulfurization Systems, GS-7193
• Vatabuk, Estimating Costs of Air Pollution Controls, Louis Publishers, 1990.

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
• EIA, Electric Plant Cost and Power Production Expenses, 1990
• 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
• 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
• 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

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
• Energy Information Administration, Annual Outlook for U.S. Electric Power, 1987
  • EIA survey data
• 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 — LDSM
• New plant capital costs, plant type, ownership type, and retrofit decisions — ECP
• EIA, Advanced Reactor Sourcebook.

  Return to Contents

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:

September 2000

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, December 2000)
http://www.eia.gov/FTPROOT/modeldoc/m064(2001).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, and Pacific
• Time Unit/Frequency: Annual through 2020.

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 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 1994, December 1997
• State Energy Data System 1997, September 1999.

Computing Environment:

See Integrating Module of the National Energy Modeling System.

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Description:

IEM is a recursive model of world petroleum supply and demand by region derived from EIA's Oil Market Simulation (OMS-PC) Model 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:

February 1999

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 (99) (Washington, DC, February 1999)
http://www.eia.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 (50 States and territories), Canada, Mexico, Japan, Australia and New Zealand, OECD Europe, Other Central and South America, Pacific Rim, Other Developing Countries, Former Soviet Union, Eastern Europe, China, OPEC
  • Supply Regions: United States (50 States and territories), Canada, Mexico, Japan, Australia and New Zealand, OECD Europe, Other Central and South America, Pacific Rim, Other Developing Countries, Former Soviet Union, Eastern Europe, China, OPEC
  • U.S. Detail: PAD District-level import supply curves
• Time Unit/Frequency: Annual through 2020
• Product(s): 5 grades of crude oil, 10 refined products, and 2 oxygenates (methanol and MTBE)
• 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, 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 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.

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Description:

MAM is comprised of four submodules: National, Employment, Interindustry, and Regional. The National Submodule is a kernel regression approximation of the proprietary U.S. Quarterly Macroeconomic Model developed by Data Resources/McGraw-Hill, Inc. (DRI). The U.S. Quarterly Model is a 1,200 equation econometric specification that forecasts macroeconomic driver variables at the national level of detail.

The Interindustry Submodule is a response surface approximation of the DRI Personal Computer Input-Output (PCIO) Model. The DRI PCIO model is a detailed input-output representation of interindustry linkages that works in tandem with the full DRI U.S. Quarterly Model.

The Employment Submodule is a response surface approximation of the DRI Econometric Model of Employment by Industry. The DRI Econometric Model of Employment by Industry, on which the response surface Employment Submodule is based, uses interindustry gross output from DRI's Personal Computer Input-Output (PCIO) Model as its major input when determining employment.

The Regional Submodule consists of a set of shares at the nine Census Division level of detail developed from simulations of DRI's U.S. Quarterly Macroeconomic Model, PCIO Model, Employment Model, and Regional Model. The regional shares included as the Regional Submodule of MAM are used to disaggregate the national results generated by the National, Interindustry, and Employment Submodules of MAM to the nine Census Division level of detail.

Last Model Update:

December 2000

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: Ron 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 (2001) (Washington, DC, December 2000)
http://www.eia.gov/FTPROOT/modeldoc/m065(2001).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 2020
• Product(s): Forecasts of domestic macroeconomic driver variables, at the national, interindustry, and nine Census Division levels of detail
• Economic Sector(s): National macroeconomic activity.

Modeling Features:

• Model Structure: MAM is composed of four Submodules: National, Interindustry, Employment, and Regional. The four submodules are executed sequentially in the order presented, and subsequent submodules build upon the results of previously executed submodules
• Modeling Technique: The National Submodule is a kernel regression representation, and the Employment and Inter-industry Submodules of MAM are econometric response surface representations of large proprietary econometric models. The Regional Submodule of MAM is composed of shares developed from simulations of large econometric macroeconomic, interindustry, employment, and regional models
• Special Features: None.

Non-DOE Input Sources:

DRI input data from the DRI U.S. Quarterly Macroeconomic Model, the DRI PCIO Model, the DRI Employment Model, and the DRI Regional Model.

DOE Data Input Sources:

MAM relies upon the DRI input data to generate the baseline growth path. Alternative growth paths are developed based on alternative economic driver variable growth path assumptions. DOE data are not used to develop the MAM.

Computing Environment:

See Integrating Module of the National Energy Modeling System.

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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:

October 2000

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:

• Energy Information Administration, Model Documentation of the Natural Gas Transmission and Distribution Model (NGTDM) of the National Energy Modeling System (NEMS), DOE/EIA-M062 (Washington, DC, February 2001)
  http://www.eia.gov/FTPROOT/modeldoc/m0622001.pdf.

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 9 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 3 offshore regions. Import/export border crossings include 3 at the Mexican border, 7 at the Canadian border, and 4 liquefied natural gas import terminals. A simplified Canadian representation is subdivided into an eastern and western region
• Time Unit/Frequency: Annual through 2020
• 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 Module (ITM), the Pipeline Tariff Module (PTM), and the Distributor Tariff Module (DTM)
  • ITM: Integrating module of the NGTDM. Simulates the natural gas price determination process by bringing together all major economic and technological factors that influence regional natural gas trade in the United States. Determines natural gas flows and prices, and pipeline and storage capacity expansion and utilization for a simplified network representing the interstate natural gas pipeline system
  • PTM: Develops parameters for setting tariffs in the ITM for transportation and storage services provided by interstate pipeline companies
  • DTM: Develops markups for distribution services provided by local distribution companies and intrastate pipeline companies
• Modeling Technique:
  • ITM: Heuristic algorithm, operates iteratively until supply/demand convergence is realized across the network
  • PTM: Econometric estimation and accounting algorithm
  • DTM: Empirical process
• Special Features:
  • Represents interregional flows of gas and pipeline capacity constraints for two seasonal periods
  • Represents regional supplies
  • Determines the amount and the location of pipeline and storage facility capacity expansion on a regional basis
  • Captures the economic tradeoffs between pipeline capacity additions and increases in regional storage capability
  • Distinguishes end-use customers by type (core and noncore).

Non-DOE Input Sources:

• Information Resources, Inc., Octane Week
  • Federal vehicle natural gas (VNG) taxes
• Canadian Petroleum Association 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
  • Pipeline financial 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.

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 firm interruptible 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 firm/interruptible 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 firm/interruptible services.
• Rate case filings under Section 4 of the Natural Gas Policy Act, as submitted to FERC by each pipeline company
  • Contract demand data and cost allocation by pipeline company
• 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 core industrial end-use prices
• Capacity and Service on the Interstate Natural Gas Pipeline System 1990, DOE/EIA-0556
  • Pipeline capacity and capacity reservations by customer
• Federal Energy Regulatory Commission, NGA Section 7(c) Filings, "Applications for Certification of Public Convenience and Necessity"
  • Planned pipeline capacity additions
• 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, www.afdc.doe.gov
  • Compressed natural gas vehicle taxes by state
• Department of Energy, Natural Gas Imports and Exports, Office of Fossil Energy
  • Import volumes by crossing in the most recent historical year
• Department of Energy, The Climate Change Action Plan Technical Supplement
  • Estimated savings from fugitive emissions

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.

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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:

January 2001

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, January 2001)
http://www.eia.gov/FTPROOT/modeldoc/m063(2001).pdf.

Coverage:

• Geographic: Six lower 48 onshore supply regions, three lower 48 offshore regions, and three Alaskan regions.
• Time Unit/Frequency: Annually through 2020
• 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 six major components
  • Lower 48 Onshore Supply Submodule
  • Unconventional Gas Recovery Supply Submodule
  • Offshore Supply Submodule
  • Foreign Natural Gas Supply Submodule
  • Enhanced Oil Recovery 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 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 (1970-1998), Washington, DC.; (2) Additional unconventional gas recovery drilling and operating cost data from operating companies
• Shallow Offshore Drilling Costs, American Petroleum Institute, Joint Association Survey of Drilling Costs (1970-1998), Washington, DC
• Shallow Offshore Lease Equipment and Operating costs, Department of Interior. Minerals Management Service (correspondence from Gulf of Mexico and Pacific OCS regional offices)
• Shallow Offshore Wells Drilled per Project, Department of Interior. Minerals Management Service (correspondence from Gulf of Mexico and Pacific OCS regional offices
• Shallow and Deep Offshore Technically Recoverable Oil and Gas Undiscovered Resources, Department of Interior. Minerals Management Service (correspondence from Gulf of Mexico and Pacific OCS regional offices)
• Deep Offshore Exploration, Drilling, Platform, and Production Costs, American Petroleum Institute, Joint Association Survey of Drilling Costs (1995), ICF Resource Incorporated (1994), Oil and Gas Journals
• Canadian Royalty Rate, Corporate Tax Rate, Provincial Corporate Tax Rate, Energy Mines and Resources Canada. Petroleum Fiscal Systems in Canada (Third Edition, 1988)
• Canadian Wells Drilled, Canadian Petroleum Association, Statistical Handbook (1976-1993)
• Canadian Lease Equipment and Operating Costs, Sproule Associates Limited, The Future Natural Gas Supply Capability of the Western Canadian Sedimentary Basin (report prepared for TransCanada Pipelines Limited, January 1990)
• Canadian Recoverable Resource Base, National Energy Board, Canadian Energy Supply and Demand 1990-2010, June 1991
• Canadian Reserves, Canadian Petroleum Association, Statistical Handbook (1976-1993)
• 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 (1980-1998), DOE/EIA-0815 (80-98)
• Onshore Operating Cost, Energy Information Administration. Costs and Indexes for Domestic Oil and Gas Field Equipment and Production Operations (1980-1998), DOE/EIA-0815 (80-98)
• 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 (1977-1998), DOE/EIA-0216 (77-98).

Computing Environment:

See Integrating Module of the National Energy Modeling System.

Return to Contents

Description:

The Petroleum Market Model is a simulation of the U.S. petroleum industry. It includes 12 domestic crude oil production regions, three 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 simu- lation 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 is represented as though the processing plants were a part of the refinery complexes, whereas ethanol sources are treated as merchant. 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:

February 2001

Part of Another Model?

National Energy Modeling System (NEMS)

Sponsor:

• Office: Office of Integrated Analysis and Forecasting
• Division: Oil and Gas Division
• Model Contact: Han-Lin Lee
• Telephone: (202) 586-4247
• E-Mail Address: HLee@eia.doe.gov

Documentation:

• Energy Information Administration, EIA Model Documentation: Petroleum Market Model of the National Energy Modeling System (NEMS), DOE/EIA-M059 (2001) (Washington, DC, February 2001)
  http://www.eia.gov/FTPROOT/modeldoc/m0592001.pdf.

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, Pacific Offshore, Alaska South, Alaska North, and Alaska Offshore); three refining regions (PAD District I, an aggregate of PAD Districts II-IV, and PAD District V); nine market regions, the Census divisions (New England, Mid Atlantic, East North Central, West North Central, South Atlantic, East South Central, West South Central, Mountain, and Pacific).
• Time Unit/Frequency: Annual through 2020
• Product(s): LPG, conventional motor gasoline, conventional high-oxygen motor gasoline, reformulated motor gasoline, California Air Resources Board (CARB) gasoline, M85, E85, jet fuel, distillate fuel oil, highway diesel, low-sulfur residual fuel oil, high-sulfur residual fuel oil, petrochemical feedstocks, asphalt/road oil, marketable coke, still gas, 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 plant, 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 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 Input Sources:

Information Resources Inc. (IRI), WORLD Model data; National Petroleum Council; ICF Resources, Oil and Gas Journal.

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.

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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: Zia Haq
• Telephone: (202) 586-2869
• E-Mail Address: Zia.Haq@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://www.eia.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: Thirteen modified EMM regions
• Time Unit/Frequency: Annual through 2020
• 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 and South Nevada
• Time Unit/Frequency: Annual through 2020
• 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, and South Nevada.
• Time Unit/Frequency: Annual through 2020
• Product(s): Electricity.

Biomass Submodule:

• Geographic: 13 EMM Regions
• Time/Unit Frequency: Annual through 2020
• Product(s): Electricity.

Geothermal Electric Submodule:

• Geographic: EMM Regions 11, 12, 13
• Time Unit/Frequency: Annual through 2020
• 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 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
  • Regional Insulation.

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.

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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) data base.

Last Model Update:

December 2000

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 H. 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 (2001) (Washington, DC, December 2000)
http://www.eia.gov/FTPROOT/modeldoc/m0672001.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, and Pacific
• Time Unit/Frequency: Annual through 2020
• Product(s): Fuel consumption including: electricity, natural gas, distillate, liquefied petroleum gas, kerosene, geothermal, wood, solar thermal, 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, other color televisions, furnace fans, personal computers, electric appliances, other appliances, and secondary space heating
  • Housing Types: Single-Family, Multifamily, and 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 Input Sources:

• American Home Appliance Manufacturers Association
  • Shipment-weighted efficiency ratings for refrigerators, clothes washers, dishwashers, freezers, and room air conditioners
• U.S. Bureau of the Census, Current Construction Report-Series C25 Characteristics of New Housing: 1996 (Washington, DC, 1998)
  • New housing and base year market shares for some services and equipment types
• Gas Appliance Manufactures Association, Consumers' Directory for Certified Efficiency Ratings, 1994
• 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
• Arthur D. Little, EIA Technology Forecast Updates — Residential and Commercial Buildings, 1998
• 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 1997
  • 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.

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Description:

The Transportation Sector Module incorporates an integrated modular design which is based upon economic, engineering, and demographic relationships that model transportation sector energy consumption 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 estimates of 2 conventional and alternative fuel/advanced technology light duty vehicles, and consumption estimates of 12 main fuels.

Last Model Update:

February 2001

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 (2001) (Washington, DC, February 2001)
http://www.eia.gov/FTPROOT/modeldoc/m0702001.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, and Pacific
• Time Unit/Frequency: Annual through 2020
• 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, aviation, mass transit, and 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 medium-duty and heavy-duty size classes. Buses are subdivided into commuter, intercity, and school buses. The air transport module contains both wide- and narrow-body aircraft. Rail transportation is composed of freight rail and three modes of personal rail travel: commuter, intercity and transit. Shipping is divided into domestic and international categories
• Modeling Technique: The modeling techniques employed in the Transportation Sector Module vary by module: econometrics for passenger travel, aviation, and new vehicle market shares; exogenous engineering and judgement for MPG, aircraft efficiency, and various freight characteristics; and structural for light-duty vehicle and aircraft capital stock estimations
• Special Features: The Transportation Sector Module has been created to allow the user to change various exogenous and endogenous input levels. 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; Low Emission Vehicle Program, VMT reduction, and greenhouse gas.

Non-DOE Input Sources:

• National Energy Accounts
• Federal Highway Administration, Highway Statistics, FHWA-PL-017, November 1999
• Department of Transportation Air Travel Statistics
• U.S. Department of Transportation, Bureau of Transportation Statistics, Air Carrier Traffic Statistics Monthly,
  December 1997/1996
• National Highway Traffic and Safety Administration, Mid-Year Fuel Economy Report, 1999
• Oak Ridge National Laboratory, Energy Data Book 20, ORNL-6959, October 2000
• Oak Ridge National Laboratory, Fleet Vehicles in the U.S., 1992
• Federal Aviation Administration, FAA Aviation Forecasts: Fiscal Years 1993-2004, February 1998
• Department of Commerce, Bureau of the Census, Truck Inventory and Use Survey, 1992
• California Air Resources Board, Proposed Regulations for Low-Emission Vehicles and Clean Fuels, Staff Report,
  August 13, 1990.

DOE Data Input Sources:

• State Energy Data System (SEDS), DOE/EIA-0214 (97), September 1999
• Short-Term Energy Outlook (STEO), DOE/EIA-0202 (00/3Q).

Computing Environment:

See Integrating Module of the National Energy Modeling System.

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Description:

The WORLD model is a linear programming model which simulates the operation of the worldwide petroleum industry based on user-specified assumptions regarding the time horizon and scenario of interest. The WORLD model simulates regional effects. Insights at the level of individual countries or refinery type can be obtained, but only where the model has been appropriately disaggregated.

Last Model Update:

December 2000

Part of Another Model?

No

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, WORLD Oil Refining Logistics Demand Model, DOE/EIA-M058
(Washington, DC, March 1994)
http://www.eia.gov/FTPROOT/modeldoc/m05894.pdf.

Archive Media and Installation Manual(s):

See Integrating Module of the National Energy Modeling System.

Coverage:

• Geographic: Regional Disaggregation
  • Representation of the world's major regions with flexibility to redefine regions to meet specific needs
  • Flexibility to create refining subregions, e.g., to distinguish different classes of refiners
• Time Unit/Frequency: Annual through 2020
• Product(s): Crude oils and refined products
• Economic Sector(s): Petroleum refining and transportation.

Modeling Features:

• Model Structure: WORLD is a linear programming model which simulates the operation of the world-wide petroleum industry based on user-specified assumptions regarding the time horizon and scenario of interest
• Modeling Technique: Linear programming
• Special Features: None.

Non-DOE Input Sources:

Various industry sources for refinery processes, crude oil assays, and refined product specifications.

• Oil and Gas Journal
• IEA/OECD, Quarterly and annual statistics on OECD Nations but also numerous other countries
• UN, mainly for third world countries
  • Crude supply and product demand data
• Hydrocarbon Processing
• NPRA, API, and NPC data.

DOE Data Input Sources:

Energy Information Administration, International Energy Annual, DOE/EIA-0219 (Washington, DC, annually)

• Petroleum Supply Annual
• International Energy Annual, Annual Energy Outlook, International Energy Outlook
  • Crude supply and product demand data.

Computing Environment:

See Integrating Module of the National Energy Modeling System.

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