Powered by Deep Web Technologies
Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


1

Assumptions to the Annual Energy Outlook - Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module Assumption to the Annual Energy Outlook Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for forecasts of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has five submodules representing various renewable energy sources, biomass, geothermal, landfill gas, solar, and wind; a sixth renewable, conventional hydroelectric power, is represented in the Electricity Market Module (EMM).109 Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as wind and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was an original source of electricity generation, to newer power systems using biomass, geothermal, LFG, solar, and wind energy. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittency, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon low-cost energy storage.

2

Assumptions to the Annual Energy Outlook 2002 - Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for forecasts of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has five submodules representing various renewable energy sources, biomass, geothermal, landfill gas, solar, and wind; a sixth renewable, conventional hydroelectric power, is represented in the Electricity Market Module (EMM).117 Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as wind and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration,

3

Assumptions to the Annual Energy Outlook 2001 - Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for forecasts of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has five submodules representing various renewable energy sources, biomass, geothermal, landfill gas, solar, and wind; a sixth renewable, conventional hydroelectric power, is represented in the Electricity Market Module (EMM).112 Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as wind and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration,

4

Assumptions to the Annual Energy Outlook 2000 - Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module (RFM) consists of five distinct submodules that represent the major renewable energy technologies. Although it is described here, conventional hydroelectric is included in the Electricity Market Module (EMM) and is not part of the RFM. Similarly, ethanol modeling is included in the Petroleum Market Module (PMM). Some renewables, such as municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as wind and solar radiation, are energy sources that do not require the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was an original source of electricity generation, to newer power systems using wind, solar, and geothermal energy. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittency, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon low-cost energy storage.

5

Assumptions to the Annual Energy Outlook 1999 - Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

renewable.gif (4875 bytes) renewable.gif (4875 bytes) The NEMS Renewable Fuels Module (RFM) consists of five distinct submodules that represent the major renewable energy technologies. Although it is described here, conventional hydroelectric is included in the Electricity Market Module (EMM) and is not part of the RFM. Similarly, ethanol modeling is included in the Petroleum Market Module (PMM). Some renewables, such as municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as wind and solar radiation, are energy sources that do not require the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was an original source of electricity generation, to newer power systems using wind, solar, and geothermal energy. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittence, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon low-cost energy storage.

6

EIA-Assumptions to the Annual Energy Outlook - Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module Assumptions to the Annual Energy Outlook 2007 Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for forecasts of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has seven submodules representing various renewable energy sources, biomass, geothermal, conventional hydroelectricity, landfill gas, solar thermal, solar photovoltaics, and wind.112 Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as water, wind, and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was one of the first electric generation technologies, to newer power systems using biomass, geothermal, LFG, solar, and wind energy. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittency, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon the availability of low-cost energy storage systems.

7

Assumptions to the Annual Energy Outlook - Household Expenditures Module  

Gasoline and Diesel Fuel Update (EIA)

Household Expenditures Module Household Expenditures Module Assumption to the Annual Energy Outlook Household Expenditures Module Figure 5. United States Census Divisions. Having problems, call our National Energy Information Center at 202-586-8800 for help. The Household Expenditures Module (HEM) constructs household energy expenditure profiles using historical survey data on household income, population and demographic characteristics, and consumption and expenditures for fuels for various end-uses. These data are combined with NEMS forecasts of household disposable income, fuel consumption, and fuel expenditures by end-use and household type. The HEM disaggregation algorithm uses these combined results to forecast household fuel consumption and expenditures by income quintile and Census Division (see

8

Assumptions to the Annual Energy Outlook - Transportation Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module Assumption to the Annual Energy Outlook Transportation Demand Module The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars, light trucks, sport utility vehicles and vans), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), freight and passenger airplanes, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

9

EIA - Assumptions to the Annual Energy Outlook 2009 - Renewable Fuels  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module Assumptions to the Annual Energy Outlook 2009 Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for projections of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has seven submodules representing various renewable energy sources, biomass, geothermal, conventional hydroelectricity, landfill gas, solar thermal, solar photovoltaics, and wind1. Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as water, wind, and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was one of the first electric generation technologies, to newer power systems using biomass, geothermal, LFG, solar, and wind energy.

10

Assumptions to the Annual Energy Outlook - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module Assumption to the Annual Energy Outlook Petroleum Market Module Figure 8. Petroleum Administration for Defense Districts. Having problems, call our National Energy Information Center at 202-586-8800 for help. The NEMS Petroleum Market Module (PMM) forecasts petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, other refinery inputs including alcohols, ethers, and bioesters natural gas plant liquids production, and refinery processing gain. In addition, the PMM estimates capacity expansion and fuel consumption of domestic refineries. The PMM contains a linear programming representation of U.S. refining

11

Assumptions to the Annual Energy Outlook - Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumption to the Annual Energy Outlook Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2004, DOE/EIA- M068(2004). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

12

Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Tools Tools Printable Version Share this resource Send a link to Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and Methodology to someone by E-mail Share Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and Methodology on Facebook Tweet about Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and Methodology on Twitter Bookmark Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and Methodology on Google Bookmark Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and Methodology on Delicious Rank Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and Methodology on Digg Find More places to share Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and Methodology on AddThis.com...

13

Assumptions to the Annual Energy Outlook - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module Assumption to the Annual Energy Outlook Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, imports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2004, DOE/EIA-M060(2004) (Washington, DC, 2004). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves addresses the relationship between the minemouth price of coal and corresponding levels of capacity utilization of mines, mining capacity, labor productivity, and the cost of factor inputs (mining equipment, mine labor, and fuel requirements).

14

EIA - Assumptions to the Annual Energy Outlook 2008 - Renewable Fuels  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module Assumptions to the Annual Energy Outlook 2008 Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for projections of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has seven submodules representing various renewable energy sources, biomass, geothermal, conventional hydroelectricity, landfill gas, solar thermal, solar photovoltaics, and wind1. Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as water, wind, and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was one of the first electric generation technologies, to newer power systems using biomass, geothermal, LFG, solar, and wind energy. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittency, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon the availability of low-cost energy storage systems.

15

Liquid Fuels Market Module  

U.S. Energy Information Administration (EIA) Indexed Site

Liquid Fuels Market Module Liquid Fuels Market Module This page inTenTionally lefT blank 145 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Liquid Fuels Market Module The NEMS Liquid Fuels Market Module (LFMM) projects petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, unfinished oil imports, other refinery inputs (including alcohols, ethers, esters, corn, biomass, and coal), natural gas plant liquids production, and refinery processing gain. In addition, the LFMM projects capacity expansion and fuel consumption at domestic refineries. The LFMM contains a linear programming (LP) representation of U.S. petroleum refining

16

Renewable Fuels Module This  

U.S. Energy Information Administration (EIA) Indexed Site

Fuels Module Fuels Module This page inTenTionally lefT blank 175 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for projections of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has seven submodules representing various renewable energy sources: biomass, geothermal, conventional hydroelectricity, landfill gas, solar thermal, solar photovoltaics, and wind [1]. Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as water, wind, and solar radiation, are energy sources that do not involve

17

Assumptions to the Annual Energy Outlook 1999 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

coal.gif (4423 bytes) coal.gif (4423 bytes) The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Model Documentation: Coal Market Module of the National Energy Modeling System, DOE/EIA-MO60. Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions, and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves addresses the relationship between the minemouth price of coal and corresponding levels of coal production, labor productivity, and the cost of factor inputs (mining equipment, mine labor, and fuel requirements).

18

Assumptions  

Gasoline and Diesel Fuel Update (EIA)

1 1 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Commercial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 47 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 67 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 82 Natural Gas Transmission and Distribution Module . . . . . . . . . . . . . . . . . . . . . . . . . . . 92 Petroleum Market Module. . . . . . . . . . . . .

19

Assumptions to the Annual Energy Outlook 2000 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2000, DOE/EIA-M060(2000) January 2000. The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2000, DOE/EIA-M060(2000) January 2000. Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions, and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves addresses the relationship between the minemouth price of coal and corresponding levels of coal production, labor productivity, and the cost of factor inputs (mining equipment, mine labor, and fuel requirements).

20

Assumptions to the Annual Energy Outlook 1999 - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

petroleum.gif (4999 bytes) petroleum.gif (4999 bytes) The NEMS Petroleum Market Module (PMM) forecasts petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, other refinery inputs including alcohol and ethers, natural gas plant liquids production, and refinery processing gain. In addition, the PMM estimates capacity expansion and fuel consumption of domestic refineries. The PMM contains a linear programming representation of refining activities in three U.S. regions. This representation provides the marginal costs of production for a number of traditional and new petroleum products. The linear programming results are used to determine end-use product prices for each Census Division using the assumptions and methods described below. 75

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


21

Assumptions to the Annual Energy Outlook 2000 - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module (PMM) forecasts petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, other refinery inputs including alcohol and ethers, natural gas plant liquids production, and refinery processing gain. In addition, the PMM estimates capacity expansion and fuel consumption of domestic refineries. Petroleum Market Module (PMM) forecasts petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, other refinery inputs including alcohol and ethers, natural gas plant liquids production, and refinery processing gain. In addition, the PMM estimates capacity expansion and fuel consumption of domestic refineries. The PMM contains a linear programming representation of refining activities in three U.S. regions. This representation provides the marginal costs of production for a number of traditional and new petroleum products. The linear programming results are used to determine end-use product prices for each Census Division using the assumptions and methods described below.100

22

Assumptions  

Gasoline and Diesel Fuel Update (EIA)

to the to the Annual Energy Outlook 1998 December 1997 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Household Expenditures Module. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Commercial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 65 Oil and Gas Supply Module

23

Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

page intentionally left blank page intentionally left blank 167 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for projections of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has seven submodules representing various renewable energy sources: biomass, geothermal, conventional hydroelectricity, landfill gas, solar thermal, solar photovoltaics, and wind [1]. Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as water, wind, and solar radiation, are energy sources that do not involve the

24

Assumptions to the Annual Energy Outlook 2002 - Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2002, DOE/EIA- M068(2002) January 2002. Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are

25

Assumptions to the Annual Energy Outlook 2001 - Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2001, DOE/EIA- M068(2001) January 2001. Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are

26

Assumptions to the Annual Energy Outlook 2002 - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 9 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The distinction between the two sets of manufacturing industries pertains to the level of modeling. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 19). The Industrial Demand Module forecasts energy consumption at the four Census region levels; energy consumption at the Census Division level is allocated

27

EIA-Assumptions to the Annual Energy Outlook - Transportation Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module Assumptions to the Annual Energy Outlook 2007 Transportation Demand Module The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption isthe sum of energy use in eight transport modes: light-duty vehicles (cars and light trucks), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), freight and passenger aircraft, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

28

Assumptions to the Annual Energy Outlook 2001 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2001, DOE/EIA-M060(2001) January 2001. Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions, and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves

29

Assumptions to the Annual Energy Outlook 2002 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2002, DOE/EIA-M060(2002) (Washington, DC, January 2002). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves

30

Assumptions to the Annual Energy Outlook - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumption to the Annual Energy Outlook Residential Demand Module The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions (see Figure 5). The Residential Demand Module also requires projections of available equipment and their installed costs over the forecast horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the forecast horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

31

Assumptions to the Annual Energy Outlook - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module Assumption to the Annual Energy Outlook Industrial Demand Module Table 17. Industry Categories Printer Friendly Version Energy-Intensive Manufacturing Nonenergy-Intensive Manufacturing Nonmanufacturing Industries Food and Kindred Products (NAICS 311) Metals-Based Durables (NAICS 332-336) Agricultural Production -Crops (NAICS 111) Paper and Allied Products (NAICS 322) Balance of Manufacturing (all remaining manufacturing NAICS) Other Agriculture Including Livestock (NAICS112- 115) Bulk Chemicals (NAICS 32B) Coal Mining (NAICS 2121) Glass and Glass Products (NAICS 3272) Oil and Gas Extraction (NAICS 211) Hydraulic Cement (NAICS 32731) Metal and Other Nonmetallic Mining (NAICS 2122- 2123) Blast Furnaces and Basic Steel (NAICS 331111) Construction (NAICS233-235)

32

Assumptions to the Annual Energy Outlook - International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module International Energy Module Assumption to the Annual Energy Outlook International Energy Module Figure 2. World Oil Prices in three Cases, 1970-2025. Having problems, call our National Energy Information Center at 202-586-8800 for help. Figure Data Figure 3. OPEC Oil Production in the Reference Case, 1970-2025. Having problems, call our National Energy Information Center at 202-586-8800 for help. Figure Data Figure 4. Non-OPEC Production in the Reference Case, 1970-2025. Having problems, call our National Energy Information Center at 202-586-8800 for help. Figure Data Table 4. Worldwide Oil Reserves as of January 1, 2002 (Billion Barrels) Printer Friendly Version Region Proved Oil Reserves Western Hemisphere 313.6 Western‘Europe 18.1 Asia-Pacific 38.7

33

EIA-Assumptions to the Annual Energy Outlook - Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumptions to the Annual Energy Outlook 2007 Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules-electricity capacity planning, electricity fuel dispatching, load and demand electricity, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2007, DOE/EIA- M068(2007). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

34

Assumptions to the Annual Energy Outlook 2001 - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module The NEMS Petroleum Market Module (PMM) forecasts petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, other refinery inputs including alcohol and ethers, natural gas plant liquids production, and refinery processing gain. In addition, the PMM estimates capacity expansion and fuel consumption of domestic refineries. The PMM contains a linear programming representation of refining activities in three U.S. regions. This representation provides the marginal costs of production for a number of traditional and new petroleum products. The linear programming results are used to determine end-use product prices for

35

Assumptions to the Annual Energy Outlook 2002 - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module The NEMS Petroleum Market Module (PMM) forecasts petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, other refinery inputs including alcohol and ethers, natural gas plant liquids production, and refinery processing gain. In addition, the PMM estimates capacity expansion and fuel consumption of domestic refineries. The PMM contains a linear programming representation of refining activities in three U.S. regions. This representation provides the marginal costs of production for a number of traditional and new petroleum products. The linear programming results are used to determine end-use product prices for

36

EIA-Assumptions to the Annual Energy Outlook - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module Assumptions to the Annual Energy Outlook 2007 Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 21 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 17). The Industrial Demand Module forecasts energy consumption at the four Census region level (see Figure 5); energy consumption at the Census Division level is estimated by allocating the Census region forecast using the SEDS25 data.

37

EIA-Assumptions to the Annual Energy Outlook - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2007 Commercial Demand Module The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2030. The definition of the commercial sector is consistent with EIA's State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.12

38

Assumptions to the Annual Energy Outlook 1999 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

commercial.gif (5196 bytes) commercial.gif (5196 bytes) The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2020. The definition of the commercial sector is consistent with EIA’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings, however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.12

39

Assumptions to the Annual Energy Outlook 2001 - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Comleted Copy in PDF Format Comleted Copy in PDF Format Related Links Annual Energy Outlook 2001 Supplemental Data to the AEO 2001 NEMS Conference To Forecasting Home Page EIA Homepage Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 9 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The distinction between the two sets of manufacturing industries pertains to the level of modeling. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 19). The

40

Assumptions to the Annual Energy Outlook 2000 - Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 9 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The distinction between the two sets of manufacturing industries pertains to the level of modeling. The energy-intensive industries are modeled through the use of a detailed process flow accounting procedure, whereas the nonenergy-intensive and the nonmanufacturing industries are modeled with substantially less detail (Table 14). The Industrial Demand Module forecasts energy consumption at the four Census region levels; energy consumption at the Census Division level is allocated by using the SEDS24 data.

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


41

EIA-Assumptions to the Annual Energy Outlook - Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module Assumptions to the Annual Energy Outlook 2007 Petroleum Market Module Figure 9. Petroleum Administration for Defense Districts. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Petroleum Market Module (PMM) forecasts petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, unfinished oil imports, other refinery inputs (including alcohols, ethers, and bioesters), natural gas plant liquids production, and refinery processing gain. In addition, the PMM projects capacity expansion and fuel consumption at domestic refineries. The PMM contains a linear programming (LP) representation of U.S. refining

42

EIA - Assumptions to the Annual Energy Outlook 2008 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module Assumptions to the Annual Energy Outlook 2008 Coal Market Module The NEMS Coal Market Module (CMM) provides projections of U.S. coal production, consumption, exports, imports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2008, DOE/EIA-M060(2008) (Washington, DC, 2008). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the projection. Forty separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations of thermal grade and sulfur content), and two mine types (underground and surface). Supply curves are constructed using an econometric formulation that relates the minemouth prices of coal for the supply regions and coal types to a set of independent variables. The independent variables include: capacity utilization of mines, mining capacity, labor productivity, the user cost of capital of mining equipment, and the cost of factor inputs (labor and fuel).

43

EIA-Assumptions to the Annual Energy Outlook - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module Assumptions to the Annual Energy Outlook 2007 Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, imports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2007, DOE/EIA-M060(2007) (Washington, DC, 2007). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Forty separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations of thermal grade and sulfur content), and two mine types (underground and surface). Supply curves are constructed using an econometric formulation that relates the minemouth prices of coal for the supply regions and coal types to a set of independent variables. The independent variables include: capacity utilization of mines, mining capacity, labor productivity, the user cost of capital of mining equipment, and the cost of factor inputs (labor and fuel).

44

EIA - Assumptions to the Annual Energy Outlook 2010 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module Assumptions to the Annual Energy Outlook 2010 Coal Market Module The NEMS Coal Market Module (CMM) provides projections of U.S. coal production, consumption, exports, imports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2010, DOE/EIA-M060(2010) (Washington, DC, 2010). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the projection. Forty separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations of thermal grade and sulfur content), and two mine types (underground and surface). Supply curves are constructed using an econometric formulation that relates the minemouth prices of coal for the supply regions and coal types to a set of independent variables. The independent variables include: capacity utilization of mines, mining capacity, labor productivity, the user cost of capital of mining equipment, the cost of factor inputs (labor and fuel), and other mine supply costs.

45

Renewable Fuels Module  

Reports and Publications (EIA)

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the Annual Energy Outlook forecasts.

Chris Namovicz

2013-07-03T23:59:59.000Z

46

Assumptions to the Annual Energy Outlook 2002 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and

47

Assumptions to the Annual Energy Outlook 2001 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and

48

Assumptions to the Annual Energy Outlook 2000 - International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module determines changes in the world oil price and the supply prices of crude oils and petroleum products for import to the United States in response to changes in U.S. import requirements. A market clearing method is used to determine the price at which worldwide demand for oil is equal to the worldwide supply. The module determines new values for oil production and demand for regions outside the United States, along with a new world oil price that balances supply and demand in the international oil market. A detailed description of the International Energy Module is provided in the EIA publication, Model Documentation Report: The International Energy Module of the National Energy Modeling System, DOE/EIA-M071(99), (Washington, DC, February 1999).

49

Assumptions to the Annual Energy Outlook 2001 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2020. The definition of the commercial sector is consistent with EIA’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for

50

Assumptions to the Annual Energy Outlook 2002 - Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2020. The definition of the commercial sector is consistent with EIA’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for

51

Assumptions to the Annual Energy Outlook 2000 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions. The Residential Demand Module also requires projections of available equipment over the forecast horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the forecast horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

52

Assumptions to the Annual Energy Outlook 1999 - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

residential.gif (5487 bytes) residential.gif (5487 bytes) The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions. The Residential Demand Module also requires projections of available equipment over the forecast horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the forecast horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

53

EIA-Assumptions to the Annual Energy Outlook - International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module International Energy Module Assumptions to the Annual Energy Outlook 2007 International Energy Module The International Energy Module (IEM) performs two tasks in all NEMS runs. First, the module reads exogenously derived supply curves, initial price paths and international regional supply and demand levels into NEMS. These quantities are not modeled directly in NEMS because NEMS is not an international model. Previous versions of the IEM adjusted these quantities after reading in initial values. In an attempt to more closely integrate the AEO2007 with the IEO2006 and the STEO some functionality was removed from the IEM. More analyst time was devoted to analyzing price relationships between marker crude oils and refined products. A new exogenous oil supply model, Generate World Oil Balances (GWOB), was also developed to incorporate actual investment occurring in the international oil market through 2015 and resource assumptions through 2030. The GWOB model provides annual country level oil production detail for eight conventional and unconventional oils.

54

EIA-Assumptions to the Annual Energy Outlook - Oil and Gas Supply Module  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module Assumptions to the Annual Energy Outlook 2007 Oil and Gas Supply Module Figure 7. Oil and Gas Supply Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze oil and gas supply on a regional basis (Figure 7). A detailed description of the OGSM is provided in the EIA publication, Model Documentation Report: The Oil and Gas Supply Module (OGSM), DOE/EIA-M063(2006), (Washington, DC, 2006). The OGSM provides crude oil and natural gas short-term supply parameters to both the Natural Gas Transmission and Distribution Module and the Petroleum Market Module. The OGSM simulates the activity of numerous firms that produce oil and natural

55

AEO Assumptions  

Gasoline and Diesel Fuel Update (EIA)

for the for the Annual Energy Outlook 1997 December 1996 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 Energy Information Administration/Assumptions for the Annual Energy Outlook 1997 Contents Page Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Commercial Demand Module . . . . . . . . . . . . . . . . . .

56

EIA-Assumptions to the Annual Energy Outlook - Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumptions to the Annual Energy Outlook 2007 Residential Demand Module Figure 5. United States Census Divisions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimate of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the "unit energy consumption" by appliance (or UEC-in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new

57

Assumptions to the Annual Energy Outlook - Oil and Gas Supply Module  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module Assumption to the Annual Energy Outlook Oil and Gas Supply Module Figure 7. Oil and Gas Supply Model Regions. Having problems, call our National Energy Information Center at 202-586-8800 for help. Table 50. Crude Oil Technically Recoverable Resources (Billion barrels) Printer Friendly Version Crude Oil Resource Category As of January 1, 2002 Undiscovered 56.02 Onshore 19.33 Northeast 1.47 Gulf Coast 4.76 Midcontinent 1.12 Southwest 3.25 Rocky Moutain 5.73 West Coast 3.00 Offshore 36.69 Deep (>200 meter W.D.) 35.01 Shallow (0-200 meter W.D.) 1.69 Inferred Reserves 49.14 Onshore 37.78 Northeast 0.79 Gulf Coast 0.80 Midcontinent 3.73 Southwest 14.61 Rocky Mountain 9.91 West Coast 7.94

58

EIA - Assumptions to the Annual Energy Outlook 2010  

Gasoline and Diesel Fuel Update (EIA)

Assumptions to the Annual Energy Outlook 2010 This report summarizes the major assumptions used in the NEMS to generate the AEO2010 projections. Introduction Macroeconomic Activity Module International Energy Module Residential Demand Module Commercial Demand Module Industrial Demand Module Transportation Demand Module Electricity Market Module Oil and Gas Supply Module Natural Gas Transmission and Distribution Module Petroleum Market Module Coal Market Module Renewable Fuels Module PDF (GIF) Appendix A: Handling of Federal and Selected State Legislation and Regulation In the Annual Energy Outlook Past Assumptions Editions Download the Report Assumptions to the Annual Energy Outlook 2010 Report Cover. Need help, contact the National Energy Information Center at 202-586-8800.

59

Model documentation: Electricity Market Module, Electricity Fuel Dispatch Submodule  

SciTech Connect

This report documents the objectives, analytical approach and development of the National Energy Modeling System Electricity Fuel Dispatch Submodule (EFD), a submodule of the Electricity Market Module (EMM). The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components.

Not Available

1994-04-08T23:59:59.000Z

60

EIA - Assumptions to the Annual Energy Outlook 2009  

Gasoline and Diesel Fuel Update (EIA)

Assumptions to the Annual Energy Outlook 2009 The Early Release for next year's Annual Energy Outlook will be presented at the John Hopkins Kenney Auditorium on December 14th This report summarizes the major assumptions used in the NEMS to generate the AEO2009 projections. Introduction Macroeconomic Activity Module International Energy Module Residential Demand Module Commercial Demand Module Industrial Demand Module Transportation Demand Module Electricity Market Module Oil and Gas Supply Module Natural Gas Transmission and Distribution Module Petroleum Market Module Coal Market Module Renewable Fuels Module PDF (GIF) Appendix A: Handling of Federal and Selected State Legislation and Regulation In the Annual Energy Outlook Past Assumptions Editions

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


61

Design assumptions and bases for small D-T-fueled spherical tokamak (ST) fusion core  

SciTech Connect

Recent progress in defining the assumptions and clarifying the bases for a small D-T-fueled ST fusion core are presented. The paper covers several issues in the physics of ST plasmas, the technology of neutral beam injection, the engineering design configuration, and the center leg material under intense neutron irradiation. This progress was driven by the exciting data from pioneering ST experiments, a heightened interest in proof-of-principle experiments at the MA level in plasma current, and the initiation of the first conceptual design study of the small ST fusion core. The needs recently identified for a restructured fusion energy sciences program have provided a timely impetus for examining the subject of this paper. Our results, though preliminary in nature, strengthen the case for the potential realism and attractiveness of the ST approach.

Peng, Yueng Kay Martin [ORNL; Haines, J.R. [Oak Ridge National Laboratory (ORNL)

1996-01-01T23:59:59.000Z

62

Assumptions to the Annual Energy Outlook 2002 - Oil and Gas Supply Module  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze oil and gas supply. A detailed description of the OGSM is provided in the EIA publication, Model Documentation Report: The Oil and Gas Supply Module (OGSM), DOE/EIA-M063(2002), (Washington, DC, January 2002). The OGSM provides crude oil and natural gas short-term supply parameters to both the Natural Gas Transmission and Distribution Module and the Petroleum Market Module. The OGSM simulates the activity of numerous firms that produce oil and natural gas from domestic fields throughout the United States, acquire natural gas from foreign producers for resale in the United States, or sell U.S. gas to foreign consumers. OGSM encompasses domestic crude oil and natural gas supply by both

63

Assumptions to the Annual Energy Outlook 2001 - Oil and Gas Supply Module  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze oil and gas supply. A detailed description of the OGSM is provided in the EIA publication, Model Documentation Report: The Oil and Gas Supply Module (OGSM), DOE/EIA-M063(2001), (Washington, DC, January 2001). The OGSM provides crude oil and natural gas short-term supply parameters to both the Natural Gas Transmission and Distribution Module and the Petroleum Market Module. The OGSM simulates the activity of numerous firms that produce oil and natural gas from domestic fields throughout the United States, acquire natural gas from foreign producers for resale in the United States, or sell U.S. gas to foreign consumers. OGSM encompasses domestic crude oil and natural gas supply by both

64

Assumptions to the Annual Energy Outlook 1999 - Oil and Gas Supply Module  

Gasoline and Diesel Fuel Update (EIA)

oil.gif (4836 bytes) oil.gif (4836 bytes) The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze oil and gas supply. A detailed description of the OGSM is provided in the EIA publication, Model Documentation Report: The Oil and Gas Supply Module (OGSM), DOE/EIA-M063(99), (Washington, DC, January 1999). The OGSM provides crude oil and natural gas short-term supply parameters to both the Natural Gas Transmission and Distribution Module and the Petroleum Market Module. The OGSM simulates the activity of numerous firms that produce oil and natural gas from domestic fields throughout the United States, acquire natural gas from foreign producers for resale in the United States, or sell U.S. gas to foreign consumers. OGSM encompasses domestic crude oil and natural gas supply by both conventional and nonconventional recovery techniques. Nonconventional recovery includes enhanced oil recovery and unconventional gas recovery from tight gas formations, gas shale, and coalbeds. Foreign gas transactions may occur via either pipeline (Canada or Mexico) or transport ships as liquefied natural gas (LNG).

65

Sensitivity of economic performance of the nuclear fuel cycle to simulation modeling assumptions  

E-Print Network (OSTI)

Comparing different nuclear fuel cycles and assessing their implications require a fuel cycle simulation model as complete and realistic as possible. In this thesis, methodological implications of modeling choices are ...

Bonnet, Nicphore

2007-01-01T23:59:59.000Z

66

MODELING ASSUMPTIONS FOR THE ADVANCED TEST REACTOR FRESH FUEL SHIPPING CONTAINER  

SciTech Connect

The Advanced Test Reactor Fresh Fuel Shipping Container (ATR FFSC) is currently licensed per 10 CFR 71 to transport a fresh fuel element for either the Advanced Test Reactor, the University of Missouri Research Reactor (MURR), or the Massachusetts Institute of Technology Research Reactor (MITR-II). During the licensing process, the Nuclear Regulatory Commission (NRC) raised a number of issues relating to the criticality analysis, namely (1) lack of a tolerance study on the fuel and packaging, (2) moderation conditions during normal conditions of transport (NCT), (3) treatment of minor hydrogenous packaging materials, and (4) treatment of potential fuel damage under hypothetical accident conditions (HAC). These concerns were adequately addressed by modifying the criticality analysis. A tolerance study was added for both the packaging and fuel elements, full-moderation was included in the NCT models, minor hydrogenous packaging materials were included, and fuel element damage was considered for the MURR and MITR-II fuel types.

Rick J. Migliore

2009-09-01T23:59:59.000Z

67

Model documentation Renewable Fuels Module of the National Energy Modeling System  

DOE Green Energy (OSTI)

This report documents the objectives, analaytical approach and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1996 Annual Energy Outlook forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described.

NONE

1996-01-01T23:59:59.000Z

68

Electricity market module: Electricity fuel dispatch submodule  

Science Conference Proceedings (OSTI)

In previous Annual Energy Outlooks (AEO), international electricity trade was represented in the National Energy Modeling System (NEMS) Electricity Market Module (EMM) modeling framework as an exogenous input. The exception to this exogenous treatment was for firm power projections, i.e., new Canadian hydroelectric model builds. The AEO95 implementation of EMM allowed Canadian hydroelectric projects to be selected in the Electricity Capacity Planning (ECP) submodule on an annual basis and otherwise addressed as any other purchased power commitments. This technical memorandum addresses modifications to the Electricity Fuel Dispatch Submodule implemented in AEO96 to enhance the treatment of international electricity trade through the representation of economy imports from Canada.

NONE

1996-06-01T23:59:59.000Z

69

EIA model documentation: Electricity market module - electricity fuel dispatch  

Science Conference Proceedings (OSTI)

This report documents the National Energy Modeling System Electricity Fuel Dispatch Submodule (EFD), a submodule of the Electricity Market Module (EMM) as it was used for EIA`s Annual Energy Outlook 1997. It replaces previous documentation dated March 1994 and subsequent yearly update revisions. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. This document serves four purposes. First, it is a reference document providing a detailed description of the model for reviewers and potential users of the EFD including energy experts at the Energy Information Administration (EIA), other Federal agencies, state energy agencies, private firms such as utilities and consulting firms, and non-profit groups such as consumer and environmental groups. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its statistical and forecast reports. Third, it facilitates continuity in model development by providing documentation which details model enhancements that were undertaken for AE097 and since the previous documentation. Last, because the major use of the EFD is to develop forecasts, this documentation explains the calculations, major inputs and assumptions which were used to generate the AE097.

NONE

1997-01-01T23:59:59.000Z

70

Renewable Fuels Module, Appendix - Model Performance, Model Documentation  

Reports and Publications (EIA)

This appendix discusses performance aspects of the Renewable Fuels Module (RFM). It is intended to present the pattern of response of the RFM to typical changes in its major inputs from other NEMS modules.

Perry M. Lindstrom

1995-06-01T23:59:59.000Z

71

Solid oxide fuel cell matrix and modules  

DOE Patents (OSTI)

Porous refractory ceramic blocks arranged in an abutting, stacked configuration and forming a three dimensional array provide a support structure and coupling means for a plurality of solid oxide fuel cells (SOFCs). Each of the blocks includes a square center channel which forms a vertical shaft when the blocks are arranged in a stacked array. Positioned within the channel is a SOFC unit cell such that a plurality of such SOFC units disposed within a vertical shaft form a string of SOFC units coupled in series. A first pair of facing inner walls of each of the blocks each include an interconnecting channel hole cut horizontally and vertically into the block walls to form gas exit channels. A second pair of facing lateral walls of each block further include a pair of inner half circular grooves which form sleeves to accommodate anode fuel and cathode air tubes. The stack of ceramic blocks is self-supporting, with a plurality of such stacked arrays forming a matrix enclosed in an insulating refractory brick structure having an outer steel layer. The necessary connections for air, fuel, burnt gas, and anode and cathode connections are provided through the brick and steel outer shell. The ceramic blocks are so designed with respect to the strings of modules that by simple and logical design the strings could be replaced by hot reloading if one should fail. The hot reloading concept has not been included in any previous designs.

Riley, Brian (Willimantic, CT)

1990-01-01T23:59:59.000Z

72

Assumptions to the Annual Energy Outlook 2013  

U.S. Energy Information Administration (EIA) Indexed Site

Energy Module Energy Module This page inTenTionally lefT blank 21 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 International Energy Module The LFMM International Energy Module (IEM) simulates the interaction between U.S. and global petroleum markets. It uses assumptions of economic growth and expectations of future U.S. and world crude-like liquids production and consumption to estimate the effects of changes in U.S. liquid fuels markets on the international petroleum market. For each year of the forecast, the LFMM IEM computes BRENT and WTI prices, provides a supply curve of world crude-like liquids, and generates a worldwide oil supply- demand balance with regional detail. The IEM also provides, for each year of the projection period, endogenous and

73

Assumptions to the Annual Energy Outlook 2008  

Gasoline and Diesel Fuel Update (EIA)

8) 8) Release date: June 2008 Next release date: March 2009 Assumptions to the Annual Energy Outlook 2008 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 Commercial Demand Module. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 77 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 Natural Gas Transmission and Distribution Module. . . . . . . . . . . . . . . . . . . . . . 113 Petroleum Market Module

74

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 21 Commercial Demand Module. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 69 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 Natural Gas Transmission and Distribution Module . . . . . . . . . . . . . . . . . . . . . . 99 Petroleum Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Coal Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 117 Renewable Fuels Module . . . . . . . . . . .

75

System for fuel rod removal from a reactor module  

DOE Patents (OSTI)

A robotic system for remote underwater withdrawal of the fuel rods from fuel modules of a light water breeder reactor includes a collet/grapple assembly for gripping and removing fuel rods in each module, which is positioned by use of a winch and a radial support means attached to a vertical support tube which is mounted over the fuel module. A programmable logic controller in conjunction with a microcomputer, provides control for the accurate positioning and pulling force of the rod grapple assembly. Closed circuit television cameras are provided which aid in operator interface with the robotic system.

Matchett, Richard L. (Bethel Park, PA); Roof, David R. (North Huntingdon, PA); Kikta, Thomas J. (Pittsburgh, PA); Wilczynski, Rosemarie (McKees Rocks, PA); Nilsen, Roy J. (Pittsburgh, PA); Bacvinskas, William S. (Bethel Park, PA); Fodor, George (Pittsburgh, PA)

1990-01-01T23:59:59.000Z

76

System for fuel rod removal from a reactor module  

DOE Patents (OSTI)

A robotic system for remote underwater withdrawal of the fuel rods from fuel modules of a light water breeder reactor includes a collet/grapple assembly for gripping and removing fuel rods in each module, which is positioned by use of a winch and a radial support means attached to a vertical support tube which is mounted over the fuel module. A programmable logic controller in conjunction with a microcomputer, provides control for the accurate positioning and pulling force of the rod grapple assembly. Closed circuit television cameras are provided which aid in operator interface with the robotic system. 7 figs.

Matchett, R.L.; Fodor, G.; Kikta, T.J.; Bacvinsicas, W.S.; Roof, D.R.; Nilsen, R.J.; Wilczynski, R.

1988-07-28T23:59:59.000Z

77

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2003, DOE/EIA-M068(2003) April 2003. Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

78

Assumptions to the Annual Energy Outlook 2002 - Table of Contents  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Oil and Gas Supply Module Renewable Fuels Module Natural Gas Transmission and Distribution Module Coal Market Module Coal Market Module Petroleum...

79

Assumptions to the Annual Energy Outlook 2013  

U.S. Energy Information Administration (EIA) Indexed Site

Industrial Demand Module Industrial Demand Module This page inTenTionally lefT blank 53 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Industrial Demand Module The NEMS Industrial Demand Module (IDM) estimates energy consumption by energy source (fuels and feedstocks) for 15 manufacturing and 6 non-manufacturing industries. The manufacturing industries are subdivided further into the energy- intensive manufacturing industries and non-energy-intensive manufacturing industries (Table 6.1). The manufacturing industries are modeled through the use of a detailed process-flow or end-use accounting procedure. The non-manufacturing industries are modeled with less detail because processes are simpler and there is less available data. The petroleum refining

80

EIA - Assumptions to the Annual Energy Outlook 2009 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module Assumptions to the Annual Energy Outlook 2009 Transportation Demand Module The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars and light trucks), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), freight and passenger aircraft, freight, rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


81

EIA - Assumptions to the Annual Energy Outlook 2008 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module Assumptions to the Annual Energy Outlook 2008 Transportation Demand Module The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars and light trucks), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), freight and passenger aircraft, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

82

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Household Expenditures Module Household Expenditures Module The Household Expenditures Module (HEM) constructs household energy expenditure profiles using historical survey data on household income, population and demographic characteristics, and consumption and expenditures for fuels for various end-uses. These data are combined with NEMS forecasts of household disposable income, fuel consumption, and fuel expenditures by end-use and household type. The HEM disaggregation algorithm uses these combined results to forecast household fuel consumption and expenditures by income quintile and Census Division. Key Assumptions The historical input data used to develop the HEM version for the AEO2003 consists of recent household survey responses, aggregated to the desired level of detail. Two surveys performed by the Energy Information Administration are included in the AEO2003 HEM database, and together these input data are used to develop a set of baseline household consumption profiles for the direct fuel expenditure analysis. These surveys are the 1997 Residential Energy Consumption Survey (RECS) and the 1991 Residential Transportation Energy Consumption Survey (RTECS).

83

Assumptions and Criteria for Performing a Feasability Study of the Conversion of the High Flux Isotope Reactor Core to Use Low-Enriched Uranium Fuel  

SciTech Connect

A computational study will be initiated during fiscal year 2006 to examine the feasibility of converting the High Flux Isotope Reactor from highly enriched uranium fuel to low-enriched uranium. The study will be limited to steady-state, nominal operation, reactor physics and thermal-hydraulic analyses of a uranium-molybdenum alloy that would be substituted for the current fuel powder--U{sub 3}O{sub 8} mixed with aluminum. The purposes of this document are to (1) define the scope of studies to be conducted, (2) define the methodologies to be used to conduct the studies, (3) define the assumptions that serve as input to the methodologies, (4) provide an efficient means for communication with the Department of Energy and American research reactor operators, and (5) expedite review and commentary by those parties.

Primm, R.T., III; Ellis, R.J.; Gehin, J.C.; Moses, D.L.; Binder, J.L.; Xoubi, N. (U. of Cincinnati)

2006-02-01T23:59:59.000Z

84

EIA - Assumptions to the Annual Energy Outlook 2009 - Electricity Market  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumptions to the Annual Energy Outlook 2009 Electricity Market Module figure 6. Electricity Market Model Supply Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand electricity, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2009, DOE/EIA-M068(2009). Based on fuel prices and electricity demands provided by the other modules

85

Development of Fuel Shuffling Module for PHISICS  

SciTech Connect

PHISICS (Parallel and Highly Innovative Simulation for the INL Code System) [4] code toolkit has been in development at the Idaho National Laboratory. This package is intended to provide a modern analysis tool for reactor physics investigation. It is designed with the mindset to maximize accuracy for a given availability of computational resources and to give state of the art tools to the modern nuclear engineer. This is obtained by implementing several different algorithms and meshing approaches among which the user will be able to choose, in order to optimize his computational resources and accuracy needs. The software is completely modular in order to simplify the independent development of modules by different teams and future maintenance. The package is coupled with the thermo-hydraulic code RELAP5-3D [3]. In the following the structure of the different PHISICS modules is briefly recalled, focusing on the new shuffling module (SHUFFLE), object of this paper.

Allan Mabe; Andrea Alfonsi; Cristian Rabiti; Aaron Epiney; Michael Lineberry

2013-06-01T23:59:59.000Z

86

Axially staggered seed-blanket reactor fuel module construction  

DOE Patents (OSTI)

A heterogeneous nuclear reactor of the seed-blanket type is provided wher the fissile (seed) and fertile (blanket) nuclear fuels are segregated axially within each fuel element such that fissile and fertile regions occur in an alternating pattern along the length of the fuel element. Further, different axial stacking patterns are used for the fuel elements of at least two module types such that when modules of different types are positioned adjacent to one another, the fertile regions of the modules are offset or staggered. Thus, when a module of one type is surrounded by modules of the second type the fertile regions thereof will be surrounded on all sides by fissile material. This provides enhanced neutron communication both radially and axially, thereby resulting in greater power oscillation stability than other axial arrangements. The arrangements of the fissile and fertile regions in an alternating axial manner minimizes the radial power peaking factors and provides a more optional thermal-hydraulic design than is afforded by radial arrangements.

Cowell, Gary K. (Monroeville, PA); DiGuiseppe, Carl P. (West Mifflin, PA)

1985-01-01T23:59:59.000Z

87

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module The NEMS Petroleum Market Module (PMM) forecasts petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, other refinery inputs including alcohol and ethers, natural gas plant liquids production, and refinery processing gain. In addition, the PMM estimates capacity expansion and fuel consumption of domestic refineries. The PMM contains a linear programming representation of refining activities in three U.S. regions. This representation provides the marginal costs of production for a number of traditional and new petroleum products. The linear programming results are used to determine end-use product prices for each Census Division using the assumptions and methods described below.106

88

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module Assumptions to the Annual Energy Outlook 2006 The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption isthe sum of energy use in eight transport modes: light-duty vehicles (cars and light trucks), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), freight and passenger aircraft, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

89

Assumptions to the Annual Energy Outlook 2001 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars, light trucks, industry sport utility vehicles and vans), commercial light trucks (8501-10,000 lbs), freight trucks (>10,000 lbs), freight and passenger airplanes, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption. Key Assumptions Macroeconomic Sector Inputs

90

Assumptions to the Annual Energy Outlook - Macroeconomic Activity...  

Annual Energy Outlook 2012 (EIA)

Macroeconomic Activity Module Assumption to the Annual Energy Outlook Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) represents the interaction between the...

91

EIA - Assumptions to the Annual Energy Outlook 2008 - Electricity Market  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumptions to the Annual Energy Outlook 2008 Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand electricity, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2008, DOE/EIA-M068(2008). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

92

Model documentation renewable fuels module of the National Energy Modeling System  

Science Conference Proceedings (OSTI)

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1995 Annual Energy Outlook (AEO95) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. The RFM consists of six analytical submodules that represent each of the major renewable energy resources--wood, municipal solid waste (MSW), solar energy, wind energy, geothermal energy, and alcohol fuels. The RFM also reads in hydroelectric facility capacities and capacity factors from a data file for use by the NEMS Electricity Market Module (EMM). The purpose of the RFM is to define the technological, cost and resource size characteristics of renewable energy technologies. These characteristics are used to compute a levelized cost to be competed against other similarly derived costs from other energy sources and technologies. The competition of these energy sources over the NEMS time horizon determines the market penetration of these renewable energy technologies. 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.

NONE

1995-06-01T23:59:59.000Z

93

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

7) 7) Release date: April 2007 Next release date: March 2008 Assumptions to the Annual Energy Outlook 2007 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Commercial Demand Module. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 57 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 75 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 93 Natural Gas Transmission and Distribution Module. . . . . . . . . . . . . . . . . . . . . . 107 Petroleum Market Module

94

Model documentation, Renewable Fuels Module of the National Energy Modeling System  

DOE Green Energy (OSTI)

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the Annual Energy Outlook 1998 (AEO98) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. For AEO98, the RFM was modified in three principal ways, introducing capital cost elasticities of supply for new renewable energy technologies, modifying biomass supply curves, and revising assumptions for use of landfill gas from municipal solid waste (MSW). In addition, the RFM was modified in general to accommodate projections beyond 2015 through 2020. Two supply elasticities were introduced, the first reflecting short-term (annual) cost increases from manufacturing, siting, and installation bottlenecks incurred under conditions of rapid growth, and the second reflecting longer term natural resource, transmission and distribution upgrade, and market limitations increasing costs as more and more of the overall resource is used. Biomass supply curves were also modified, basing forest products supplies on production rather than on inventory, and expanding energy crop estimates to include states west of the Mississippi River using information developed by the Oak Ridge National Laboratory. Finally, for MSW, several assumptions for the use of landfill gas were revised and extended.

NONE

1998-01-01T23:59:59.000Z

95

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module Electricity Market Module Assumptions to the Annual Energy Outlook 2006 The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules—electricity capacity planning, electricity fuel dispatching, load and demand electricity, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2006, DOE/EIA- M068(2006). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described.

96

Assumptions to the Annual Energy Outlook 2000 - Household Expenditures  

Gasoline and Diesel Fuel Update (EIA)

Key Assumptions Key Assumptions The historical input data used to develop the HEM version for the AEO2000 consists of recent household survey responses, aggregated to the desired level of detail. Two surveys performed by the Energy Information Administration are included in the AEO2000 HEM database, and together these input data are used to develop a set of baseline household consumption profiles for the direct fuel expenditure analysis. These surveys are the 1997 Residential Energy Consumption Survey (RECS) and the 1991 Residential Transportation Energy Consumption Survey (RTECS). HEM uses the consumption forecast by NEMS for the residential and transportation sectors as inputs to the disaggregation algorithm that results in the direct fuel expenditure analysis. Household end-use and personal transportation service consumption are obtained by HEM from the NEMS Residential and Transportation Demand Modules. Household disposable income is adjusted with forecasts of total disposable income from the NEMS Macroeconomic Activity Module.

97

Model documentation renewable fuels module of the National Energy Modeling System  

DOE Green Energy (OSTI)

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it relates to the production of the 1997 Annual Energy Outlook forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs. and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. This documentation report serves three purposes. First, it is a reference document for model analysts, model users, and the public interested in the construction and application of the RFM. Second, it meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. Finally, such documentation facilitates continuity in EIA model development by providing information sufficient to perform model enhancements and data updates as part of EIA`s ongoing mission to provide analytical and forecasting information systems.

NONE

1997-04-01T23:59:59.000Z

98

Model documentation: Renewable Fuels Module of the National Energy Modeling System  

SciTech Connect

This report documents the objectives, analytical approach, and design of the National Energy Modeling System (NEMS) Renewable Fuels Module (RFM) as it related to the production of the 1994 Annual Energy Outlook (AEO94) forecasts. The report catalogues and describes modeling assumptions, computational methodologies, data inputs, and parameter estimation techniques. A number of offline analyses used in lieu of RFM modeling components are also described. This documentation report serves two purposes. First, it is a reference document for model analysts, model users, and the public interested in the construction and application of the RFM. Second, it meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. The RFM consists of six analytical submodules that represent each of the major renewable energy resources -- wood, municipal solid waste (MSW), solar energy, wind energy, geothermal energy, and alcohol fuels. Of these six, four are documented in the following chapters: municipal solid waste, wind, solar and biofuels. Geothermal and wood are not currently working components of NEMS. The purpose of the RFM is to define the technological and cost characteristics of renewable energy technologies, and to pass these characteristics to other NEMS modules for the determination of mid-term forecasted renewable energy demand.

Not Available

1994-04-01T23:59:59.000Z

99

EIA - Assumptions to the Annual Energy Outlook 2009 - Commercial Demand  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2009 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2030. The definition of the commercial sector is consistent with EIA’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.1

100

EIA - Assumptions to the Annual Energy Outlook 2010 - Commercial Demand  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2009 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2035. The definition of the commercial sector is consistent with EIA’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services [1].

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


101

EIA - Assumptions to the Annual Energy Outlook 2008 - Industrial Demand  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module Assumptions to the Annual Energy Outlook 2008 Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 21 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 17). The Industrial Demand Module projects energy consumption at the four Census region level (see Figure 5); energy consumption at the Census Division level is estimated by allocating the Census region projection using the SEDS1 data.

102

EIA - Assumptions to the Annual Energy Outlook 2008 - Commercial Demand  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2008 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2030. The definition of the commercial sector is consistent with EIA’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.1

103

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module Coal Market Module The NEMS Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2003, DOE/EIA-M060(2003) (Washington, DC, January 2003). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Separate supply curves are developed for each of 11 supply regions and 12 coal types (unique combinations of thermal grade, sulfur content, and mine type). The modeling approach used to construct regional coal supply curves addresses the relationship between the minemouth price of coal and corresponding levels of capacity utilization of mines, mining capacity, labor productivity, and the cost of factor inputs (mining equipment, mine labor, and fuel requirements).

104

Purge gas protected transportable pressurized fuel cell modules and their operation in a power plant  

DOE Patents (OSTI)

A fuel cell generator apparatus and method of its operation involves: passing pressurized oxidant gas, (O) and pressurized fuel gas, (F), into fuel cell modules, (10 and 12), containing fuel cells, where the modules are each enclosed by a module housing (18), surrounded by an axially elongated pressure vessel (64), where there is a purge gas volume, (62), between the module housing and pressure vessel; passing pressurized purge gas, (P), through the purge gas volume, (62), to dilute any unreacted fuel gas from the modules; and passing exhaust gas, (82), and circulated purge gas and any unreacted fuel gas out of the pressure vessel; where the fuel cell generator apparatus is transpatable when the pressure vessel (64) is horizontally disposed, providing a low center of gravity.

Zafred, Paolo R. (Pittsburgh, PA); Dederer, Jeffrey T. (Valencia, PA); Gillett, James E. (Greensburg, PA); Basel, Richard A. (Plub Borough, PA); Antenucci, Annette B. (Pittsburgh, PA)

1996-01-01T23:59:59.000Z

105

Assumptions to the Annual Energy Outlook 2000 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module estimates energy consumption across the nine Census Divisions and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars, light trucks, industry sport utility vehicles and vans), commercial light trucks (8501-10,000 lbs), freight trucks (>10,000 lbs), freight and passenger airplanes, freight rail, freight shipping, mass transit, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption. Transportation Demand Module estimates energy consumption across the nine Census Divisions and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars, light trucks, industry sport utility vehicles and vans), commercial light trucks (8501-10,000 lbs), freight trucks (>10,000 lbs), freight and passenger airplanes, freight rail, freight shipping, mass transit, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption. Key Assumptions Macroeconomic Sector Inputs

106

Annual Energy Outlook 96 Assumptions  

Gasoline and Diesel Fuel Update (EIA)

for for the Annual Energy Outlook 1996 January 1996 Energy Information Administration Office of Integrated Analysis and Forecasting U.S. Department of Energy Washington, DC 20585 Introduction This paper presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 1996 (AEO96). In this context, assumptions include general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports listed in the Appendix. 1 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview. The National Energy Modeling System The projections

107

Purge gas protected transportable pressurized fuel cell modules and their operation in a power plant  

DOE Patents (OSTI)

A fuel cell generator apparatus and method of its operation involves: passing pressurized oxidant gas and pressurized fuel gas into modules containing fuel cells, where the modules are each enclosed by a module housing surrounded by an axially elongated pressure vessel, and where there is a purge gas volume between the module housing and pressure vessel; passing pressurized purge gas through the purge gas volume to dilute any unreacted fuel gas from the modules; and passing exhaust gas and circulated purge gas and any unreacted fuel gas out of the pressure vessel; where the fuel cell generator apparatus is transportable when the pressure vessel is horizontally disposed, providing a low center of gravity. 11 figs.

Zafred, P.R.; Dederer, J.T.; Gillett, J.E.; Basel, R.A.; Antenucci, A.B.

1996-11-12T23:59:59.000Z

108

EIA - Assumptions to the Annual Energy Outlook 2010 - Petroleum Market  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module Assumptions to the Annual Energy Outlook 2010 Petroleum Market Module The NEMS Petroleum Market Module (PMM) projects petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, unfinished oil imports, other refinery inputs (including alcohols, ethers, bioesters, corn, biomass, and coal), natural gas plant liquids production, and refinery processing gain. In addition, the PMM projects capacity expansion and fuel consumption at domestic refineries. Figure 9. Petroleum Administration for Defense Districts. The PMM contains a linear programming (LP) representation of U.S. refining activities in the five Petroleum Area Defense Districts (PADDs) (Figure 9),

109

EIA - Assumptions to the Annual Energy Outlook 2009 - Industrial Demand  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module Assumptions to the Annual Energy Outlook 2009 Industrial Demand Module Table 6.1. Industry Categories. Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version Table 6.2.Retirement Rates. Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 15 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries (Table 6.1). The manufacturing industries are modeled through the use of a detailed process flow or end use accounting

110

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module Assumptions to the Annual Energy Outlook 2006 The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 12 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 17). The Industrial Demand Module forecasts energy consumption at the four Census region level (see Figure 5); energy consumption at the Census Division level is estimated by allocating the Census region forecast using the SEDS27 data.

111

EIA - Assumptions to the Annual Energy Outlook 2008 - Petroleum Market  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module Assumptions to the Annual Energy Outlook 2008 Petroleum Market Module Figure 9. Petroleum Administration for Defense Districts. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Petroleum Market Module (PMM) projects petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, unfinished oil imports, other refinery inputs (including alcohols, ethers, bioesters, corn, biomass, and coal), natural gas plant liquids production, and refinery processing gain. In addition, the PMM projects capacity expansion and fuel consumption at domestic refineries. The PMM contains a linear programming (LP) representation of U.S. refining

112

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Commercial Demand Module Commercial Demand Module Assumptions to the Annual Energy Outlook 2006 The NEMS Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2030. The definition of the commercial sector is consistent with EIA’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.14

113

Assumptions to the Annual Energy Outlook 2000 - Electricity Market Demand  

Gasoline and Diesel Fuel Update (EIA)

Electricity Market Module (EMM) represents the planning, operations, and pricing of electricity in the United States. It is composed of four primary submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. In addition, nonutility generation and supply and electricity transmission and trade are represented in the planning and dispatching submodules. Electricity Market Module (EMM) represents the planning, operations, and pricing of electricity in the United States. It is composed of four primary submodules—electricity capacity planning, electricity fuel dispatching, load and demand-side management, and electricity finance and pricing. In addition, nonutility generation and supply and electricity transmission and trade are represented in the planning and dispatching submodules. Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. The major assumptions are summarized below.

114

Modules for estimating solid waste from fossil-fuel technologies  

SciTech Connect

Solid waste has become a subject of increasing concern to energy industries for several reasons. Increasingly stringent air and water pollution regulations result in a larger fraction of residuals in the form of solid wastes. Control technologies, particularly flue gas desulfurization, can multiply the amount of waste. With the renewed emphasis on coal utilization and the likelihood of oil shale development, increased amounts of solid waste will be produced. In the past, solid waste residuals used for environmental assessment have tended only to include total quantities generated. To look at environmental impacts, however, data on the composition of the solid wastes are required. Computer modules for calculating the quantities and composition of solid waste from major fossil fuel technologies were therefore developed and are described in this report. Six modules have been produced covering physical coal cleaning, conventional coal combustion with flue gas desulfurization, atmospheric fluidized-bed combustion, coal gasification using the Lurgi process, coal liquefaction using the SRC-II process, and oil shale retorting. Total quantities of each solid waste stream are computed together with the major components and a number of trace elements and radionuclides.

Crowther, M.A.; Thode, H.C. Jr.; Morris, S.C.

1980-10-01T23:59:59.000Z

115

Assumptions to the Annual Energy Outlook - Contacts  

Gasoline and Diesel Fuel Update (EIA)

Contacts Contacts Assumption to the Annual Energy Outlook Contacts Specific questions about the information in this report may be directed to: Introduction Paul D. Holtberg 202/586-1284 Macroeconomic Activity Module Ronald F. Earley Yvonne Taylor 202/586-1398 202/586-1398 International Energy Module G. Daniel Butler 202/586-9503 Household Expenditures Module/ Residential Demand Module John H. Cymbalsky 202/586-4815 Commercial Demand Module Erin E. Boedecker 202/586-4791 Industrial Demand Module T. Crawford Honeycutt 202/586-1420 Transportation Demand Module John D. Maples 202/586-1757 Electricity Market Module Laura Martin 202/586-1494 Oil and Gas Supply Module/Natural Gas Transmission and Distribution Module Joseph Benneche 202/586-6132 Petroleum Market Module Bill Brown 202/586-8181

116

EIA - Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

7 7 Assumptions to the Annual Energy Outlook 2007 This report summarizes the major assumptions used in the NEMS to generate the AEO2007 projections. Contents (Complete Report) Download complete Report. Need help, contact the National Energy Information Center at 202-586-8800. Introduction Introduction Section to the Assumptions to the Annual Energy Outlook 2007 Report. Need help, contact the National Energy Information Center at 202-586-8800. Introduction Section to the Assumptions to the Annual Energy Outlook 2007 Report. Need help, contact the National Energy Information Center at 202-586-8800. Macroeconomic Activity Module Macroeconomic Activity Module Section to the Assumptions to the Annual Energy Outlook 2007 Report. Need help, contact the National Energy Information Center at 202-586-8800.

117

Assumptions and criteria for performing a feasibility study of the conversion of the high flux isotope reactor core to use low-enriched uranium fuel  

SciTech Connect

This paper provides a preliminary estimate of the operating power for the High Flux Isotope Reactor when fuelled with low enriched uranium (LEU). Uncertainties in the fuel fabrication and inspection processes are reviewed for the current fuel cycle [highly enriched uranium (HEU)] and the impact of these uncertainties on the proposed LEU fuel cycle operating power is discussed. These studies indicate that for the power distribution presented in a companion paper in these proceedings, the operating power for an LEU cycle would be close to the current operating power. (authors)

Primm Iii, R. T. [Oak Ridge National Laboratory, P. O. Box 2008, Oak Ridge, TN 37831-6399 (United States); Ellis, R. J.; Gehin, J. C. [Oak Ridge National Laboratory, P. O. Box 2008, Oak Ridge, TN 37831-6172 (United States); Moses, D. L. [Oak Ridge National Laboratory, P. O. Box 2008, Oak Ridge, TN 37831-6050 (United States); Binder, J. L. [Oak Ridge National Laboratory, P. O. Box 2008, Oak Ridge, TN 37831-6162 (United States); Xoubi, N. [Univ. of Cincinnati, Rhodes Hall, ML 72, PO Box 210072, Cincinnati, OH 45221-0072 (United States)

2006-07-01T23:59:59.000Z

118

Single module pressurized fuel cell turbine generator system  

DOE Patents (OSTI)

A pressurized fuel cell system (10), operates within a common pressure vessel (12) where the system contains fuel cells (22), a turbine (26) and a generator (98) where preferably, associated oxidant inlet valve (52), fuel inlet valve (56) and fuel cell exhaust valve (42) are outside the pressure vessel.

George, Raymond A. (Pittsburgh, PA); Veyo, Stephen E. (Murrysville, PA); Dederer, Jeffrey T. (Valencia, PA)

2001-01-01T23:59:59.000Z

119

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

7, DOE/EIA- 7, DOE/EIA- M068(2007). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described. EMM Regions The supply regions used in EMM are based on the North American Electric Reliability Council regions and

120

D:\assumptions_2001\assumptions2002\currentassump\demand.vp  

Gasoline and Diesel Fuel Update (EIA)

2 2 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Commercial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 Natural Gas Transmission and Distribution Module . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 Petroleum Market Module. . . . . . . . . . . . .

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


121

EIA - Assumptions to the Annual Energy Outlook 2009 - Coal Market...  

Annual Energy Outlook 2012 (EIA)

of mining equipment, the cost of factor inputs (labor and fuel), and other mine supply costs. The key assumptions underlying the coal production modeling are: As capacity...

122

Generator module architecture for a large solid oxide fuel cell power plant  

DOE Patents (OSTI)

A solid oxide fuel cell module contains a plurality of integral bundle assemblies, the module containing a top portion with an inlet fuel plenum and a bottom portion receiving air inlet feed and containing a base support, the base supports dense, ceramic exhaust manifolds which are below and connect to air feed tubes located in a recuperator zone, the air feed tubes passing into the center of inverted, tubular, elongated, hollow electrically connected solid oxide fuel cells having an open end above a combustion zone into which the air feed tubes pass and a closed end near the inlet fuel plenum, where the fuel cells comprise a fuel cell stack bundle all surrounded within an outer module enclosure having top power leads to provide electrical output from the stack bundle, where the fuel cells operate in the fuel cell mode and where the base support and bottom ceramic air exhaust manifolds carry from 85% to all 100% of the weight of the stack, and each bundle assembly has its own control for vertical and horizontal thermal expansion control.

Gillett, James E.; Zafred, Paolo R.; Riggle, Matthew W.; Litzinger, Kevin P.

2013-06-11T23:59:59.000Z

123

Trade Study on Aggregation of Multiple 10-KW Solid Ozide Fuel Cell Power Modules  

DOE Green Energy (OSTI)

According to the Solid State Energy Conversion Alliance (SECA) program guidelines, solid oxide fuel cells (SOFC) will be produced in the form of 3-10 kW modules for residential use. In addition to residential use, these modules can also be used in apartment buildings, hospitals, etc., where a higher power rating would be required. For example, a hospital might require a 250 kW power generating capacity. To provide this power using the SECA SOFC modules, 25 of the 10 kW modules would be required. These modules can be aggregated in different architectures to yield the necessary power. This report will show different approaches for aggregating numerous SOFC modules and will evaluate and compare each one with respect to cost, control complexity, ease of modularity, and fault tolerance.

Ozpineci, B.

2004-12-03T23:59:59.000Z

124

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, imports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2006, DOE/EIA-M060(2006) (Washington, DC, 2006). Coal Market Module (CMM) provides forecasts of U.S. coal production, consumption, exports, imports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2006, DOE/EIA-M060(2006) (Washington, DC, 2006). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Forty separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations of thermal grade and sulfur content), and two mine types (underground and surface). Supply curves are constructed using an econometric formulation that relates the minemouth prices of coal for the supply regions and coal types to a set of independent variables. The independent variables include: capacity utilization of mines, mining capacity, labor productivity, the user cost of capital of mining equipment, and the cost of factor inputs (labor and fuel).

125

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Transportation Demand Module Transportation Demand Module The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars, light trucks, sport utility vehicles and vans), commercial light trucks (8501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), freight and passenger airplanes, freight rail, freight shipping, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

126

Assumptions to the Annual Energy Outlook 2013  

U.S. Energy Information Administration (EIA) Indexed Site

Demand Module Demand Module This page inTenTionally lefT blank 27 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Residential Demand Module The NEMS Residential Demand Module projects future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimate of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the "unit energy consumption" (UEC) by appliance (in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing

127

Electricity Market Module  

U.S. Energy Information Administration (EIA) Indexed Site

Market Module Market Module This page inTenTionally lefT blank 101 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules-electricity capacity planning, electricity fuel dispatching, electricity load and demand, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2013, DOE/EIA-M068(2013). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most

128

Assumptions to the Annual Energy Outlook 2001 - Household Expenditures  

Gasoline and Diesel Fuel Update (EIA)

Completed Copy in PDF Format Completed Copy in PDF Format Related Links Annual Energy Outlook2001 Supplemental Data to the AEO2001 NEMS Conference To Forecasting Home Page EIA Homepage Household Expenditures Module Key Assumptions The historical input data used to develop the HEM version for the AEO2001 consists of recent household survey responses, aggregated to the desired level of detail. Two surveys performed by the Energy Information Administration are included in the AEO2001 HEM database, and together these input data are used to develop a set of baseline household consumption profiles for the direct fuel expenditure analysis. These surveys are the 1997 Residential Energy Consumption Survey (RECS) and the 1991 Residential Transportation Energy Consumption Survey (RTECS). HEM uses the consumption forecast by NEMS for the residential and

129

Assumptions to the Annual Energy Outlook 2013  

U.S. Energy Information Administration (EIA) Indexed Site

Demand Module Demand Module This page inTenTionally lefT blank 39 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2040. The definition of the commercial sector is consistent with EIA's State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial.

130

Assumptions to the Annual Energy Outlook 2013  

U.S. Energy Information Administration (EIA) Indexed Site

Macroeconomic Activity Module Macroeconomic Activity Module This page inTenTionally lefT blank 17 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) represents interactions between the U.S. economy and energy markets. The rate of growth of the economy, measured by the growth in gross domestic product (GDP), is a key determinant of growth in the demand for energy. Associated economic factors, such as interest rates and disposable income, strongly influence various elements of the supply and demand for energy. At the same time, reactions to energy markets by the aggregate economy, such as a slowdown in economic growth resulting from increasing energy prices, are also reflected

131

Appendix model performance - model documentation renewable fuels module of the National Energy Modeling System  

DOE Green Energy (OSTI)

This appendix discusses performance aspects of the Renewable Fuels Module (RFM). It is intended to present the pattern of response of the RFM to typical changes in its major inputs from other NEMS modules. The overall approach of this document, with the particular statistics presented, is designed to be comparable with similar analyses conducted for all of the modules of NEMS. While not always applicable, the overall approach has been to produce analyses and statistics that are as comparable as possible with model developer`s reports for other NEMS modules. Those areas where the analysis is somewhat limited or constrained are discussed. Because the RFM consists of independent submodules, this appendix is broken down by submodule.

Not Available

1994-09-01T23:59:59.000Z

132

Materials and Modules for Low Cost, High Performance Fuel Cell Humidifiers  

NLE Websites -- All DOE Office Websites (Extended Search)

Kick-off Meeting, Kick-off Meeting, Wash. D.C - 10/01/2009 Materials and Modules for Low Cost, High Performance Fuel Cell Humidifiers Prime Contractor: W. L. Gore & Associates Elkton, MD Principal Investigator: William B. Johnson Sub-Contractor: dPoint Technologies Vancouver, BC W. L. Gore & Associates, Inc. DOE Kick-off Meeting, Wash. D.C - 10/01/2009 Ahluwalia, et. al, ibid. Mirza, Z. DOE Hydrogen Program Review, June 9-13, 2008; Washington, DC Background W. L. Gore & Associates, Inc. DOE Kick-off Meeting, Wash. D.C - 10/01/2009 Objective and Technical Barriers Addressed More efficient, low-cost humidifiers can increase fuel cell inlet humidity: Reduce system cost and size of balance of plant; Improve fuel cell performance; Improve fuel cell durability. OBJECTIVE: Demonstrate a durable, high performance water

133

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module Renewable Fuels Module The NEMS Renewable Fuels Module (RFM) provides natural resources supply and technology input information for forecasts of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has five submodules representing various renewable energy sources, biomass, geothermal, landfill gas, solar, and wind; a sixth renewable, conventional hydroelectric power, is represented in the Electricity Market Module (EMM).119 Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as wind and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was an original source of electricity generation, to newer power systems using biomass, geothermal, LFG, solar, and wind energy. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittency, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon low-cost energy storage.

134

Assumptions to the Annual Energy Outlook 1999 - Industrial Demand...  

Gasoline and Diesel Fuel Update (EIA)

industrial.gif (5205 bytes) The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 9 manufacturing and 6 nonmanufacturing...

135

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

6 6 Assumptions to the Annual Energy Outlook 2006 This report presents major assumptions of NEMS that are used to generate the projections in the AEO2006. Contents (Complete Report) Download complete Report. Need help, contact the National Energy Information Center at 202-586-8800. Introduction Introduction Section to the Assumptions to the Annual Energy Outlook 2006 Report. Need help, contact the National Energy Information Center at 202-586-8800. Introduction Section to the Assumptions to the Annual Energy Outlook 2006 Report. Need help, contact the National Energy Information Center at 202-586-8800. Macroeconomic Activity Module Macroeconomic Activity Module Section to the Assumptions to the Annual Energy Outlook 2006 Report. Need help, contact the National Energy Information Center at 202-586-8800.

136

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution network that links them. In addition, natural gas flow patterns are a function of the pattern in the previous year, coupled with the relative prices of gas supply options as translated to the represented market “hubs.” The major assumptions used within the NGTDM are grouped into five general categories. They relate to (1) the classification of demand into core and noncore transportation service classes, (2) the pricing of transmission and distribution services, (3) pipeline and storage capacity expansion and utilization, and (4) the implementation of recent regulatory reform. A complete listing of NGTDM assumptions and in-depth methodology descriptions are presented in Model Documentation: Natural Gas Transmission and Distribution Model of the National Energy Modeling System, Model Documentation 2003, DOE/EIA- M062(2003) (Washington, DC, January 2003).

137

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Energy Module Oil and Gas Supply Module Household Expenditures Module Natural Gas Transmission and Distribution Module Residential Demand Module Petroleum Market Module...

138

Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 95 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules-electricity capacity planning, electricity fuel dispatching, electricity load and demand, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2011, DOE/EIA-M068(2011). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most

139

Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

This page inTenTionally lefT blank 91 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2012 Electricity Market Module The NEMS Electricity Market Module (EMM) represents the capacity planning, dispatching, and pricing of electricity. It is composed of four submodules-electricity capacity planning, electricity fuel dispatching, electricity load and demand, and electricity finance and pricing. It includes nonutility capacity and generation, and electricity transmission and trade. A detailed description of the EMM is provided in the EIA publication, Electricity Market Module of the National Energy Modeling System 2012, DOE/EIA-M068(2012). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most

140

Development of a Hybrid Compressor/Expander Module for Automotive Fuel Cell Applications  

DOE Green Energy (OSTI)

In this program TIAX LLC conducted the development of an advanced technology compressor/expander for supplying compressed air to Proton Exchange Membrane (PEM) fuel cells in transportation applications. The overall objective of this program was to develop a hybrid compressor/expander module, based on both scroll and high-speed turbomachinery technologies, which will combine the strengths of each technology to create a concept with superior performance at minimal size and cost. The resulting system was expected to have efficiency and pressure delivery capability comparable to that of a scroll-only machine, at significantly reduced system size and weight when compared to scroll-only designs. Based on the results of detailed designs and analyses of the critical system elements, the Hybrid Compressor/Expander Module concept was projected to deliver significant improvements in weight, volume and manufacturing cost relative to previous generation systems.

McTaggart, Paul

2004-12-31T23:59:59.000Z

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


141

Assumptions to the Annual Energy Outlook - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction Assumption to the Annual Energy Outlook Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 20041 (AEO2004), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview3, which is updated once every two years. The National Energy Modeling System The projections in the AEO2004 were produced with the National Energy Modeling System. NEMS is developed and maintained by the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projections of domestic energy-economy markets in the midterm time period and perform policy analyses requested by decisionmakers in the U.S. Congress, the Administration, including DOE Program Offices, and other government agencies.

142

Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 51 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 15 manufacturing and 6 non-manufacturing industries. The manufacturing industries are further subdivided into the energy- intensive manufacturing industries and nonenergy-intensive manufacturing industries (Table 6.1). The manufacturing industries are modeled through the use of a detailed process-flow or end-use accounting procedure, whereas the non- manufacturing industries are modeled with substantially less detail. The petroleum refining industry is not included in the Industrial Module, as it is simulated separately in the Petroleum Market Module of NEMS. The Industrial Module calculates

143

Assumptions to the Annual Energy Outlook 2006  

Gasoline and Diesel Fuel Update (EIA)

6) 6) Release date: March 2006 Next release date: March 2007 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 International Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Commercial Demand Module. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 71 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 Natural Gas Transmission and Distribution Module. . . . . . . . . . . . . . . . . . . . . . 101 Petroleum Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 109 Coal Market Module

144

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 20031 (AEO2003), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview.3 The National Energy Modeling System The projections in the AEO2003 were produced with the National Energy Modeling System. NEMS is developed and maintained by the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projections of domestic energy-economy markets in the midterm time period and perform policy analyses requested by decisionmakers and analysts in the U.S. Congress, the Department of Energy’s Office of Policy and International Affairs, other DOE offices, and other government agencies.

145

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Industrial Demand Module Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 9 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 20). The Industrial Demand Module forecasts energy consumption at the four Census region levels; energy consumption at the Census Division level is allocated by using the SEDS24 data. The energy-intensive industries (food and kindred products, paper and allied products, bulk chemicals, glass and glass products, hydraulic cement, blast furnace and basic steel products, and aluminum) are modeled in considerable detail. Each industry is modeled as three separate but interrelated components consisting of the Process Assembly (PA) Component, the Buildings Component (BLD), and the Boiler/Steam/Cogenera- tion (BSC) Component. The BSC Component satisfies the steam demand from the PA and BLD Components. In some industries, the PA Component produces byproducts that are consumed in the BSC Component. For the manufacturing industries, the PA Component is separated into the major production processes or end uses.

146

International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 23 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 International Energy Module The NEMS International Energy Module (IEM) simulates the interaction between U.S. and global petroleum markets. It uses assumptions of economic growth and expectations of future U.S. and world crude-like liquids production and consumption to estimate the effects of changes in U.S. liquid fuels markets on the international petroleum market. For each year of the forecast, the NEMS IEM computes world oil prices, provides a supply curve of world crude-like liquids, generates a worldwide oil supply- demand balance with regional detail, and computes quantities of crude oil and light and heavy petroleum products imported into

147

EIA-Assumptions to the Annual Energy Outlook - Macroeconomic Activity  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module Macroeconomic Activity Module Assumptions to the Annual Energy Outlook 2007 Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) represents the interaction between the U.S. economy as a whole and energy markets. The rate of growth of the economy, measured by the growth in gross domestic product (GDP) is a key determinant of the growth in demand for energy. Associated economic factors, such as interest rates and disposable income, strongly influence various elements of the supply and demand for energy. At the same time, reactions to energy markets by the aggregate economy, such as a slowdown in economic growth resulting from increasing energy prices, are also reflected in this module. A detailed description of the MAM is provided in the EIA publication, Model Documentation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065(2007), (Washington, DC, January 2007).

148

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module International Energy Module Assumptions to the Annual Energy Outlook 2006 The International Energy Module determines changes in the world oil price and the supply prices of crude oils and petroleum products for import to the United States in response to changes in U.S. import requirements. A market clearing method is used to determine the price at which worldwide demand for oil is equal to the worldwide supply. The module determines new values for oil production and demand for regions outside the United States, along with a new world oil price that balances supply and demand in the international oil market. A detailed description of the International Energy Module is provided in the EIA publication, Model Documentation Report: The International Energy Module of the National Energy Modeling System, DOE/EIA-M071(06), (Washington, DC, February 2006).

149

EIA - Assumptions to the Annual Energy Outlook 2009 - Macroeconomic  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module Macroeconomic Activity Module Assumptions to the Annual Energy Outlook 2010 Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) represents the interaction between the U.S. economy as a whole and energy markets. The rate of growth of the economy, measured by the growth in gross domestic product (GDP) is a key determinant of the growth in demand for energy. Associated economic factors, such as interest rates and disposable income, strongly influence various elements of the supply and demand for energy. At the same time, reactions to energy markets by the aggregate economy, such as a slowdown in economic growth resulting from increasing energy prices, are also reflected in this module. A detailed description of the MAM is provided in the EIA publication, Model Document>ation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065(2009), (Washington, DC, January 2009).

150

EIA - Assumptions to the Annual Energy Outlook 2008 - Macroeconomic  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module Macroeconomic Activity Module Assumptions to the Annual Energy Outlook 2008 Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) represents the interaction between the U.S. economy as a whole and energy markets. The rate of growth of the economy, measured by the growth in gross domestic product (GDP) is a key determinant of the growth in demand for energy. Associated economic factors, such as interest rates and disposable income, strongly influence various elements of the supply and demand for energy. At the same time, reactions to energy markets by the aggregate economy, such as a slowdown in economic growth resulting from increasing energy prices, are also reflected in this module. A detailed description of the MAM is provided in the EIA publication, Model Documentation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065(2007), (Washington, DC, January 2007).

151

EIA - Assumptions to the Annual Energy Outlook 2009 - Macroeconomic  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module Macroeconomic Activity Module Assumptions to the Annual Energy Outlook 2009 Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) represents the interaction between the U.S. economy as a whole and energy markets. The rate of growth of the economy, measured by the growth in gross domestic product (GDP) is a key determinant of the growth in demand for energy. Associated economic factors, such as interest rates and disposable income, strongly influence various elements of the supply and demand for energy. At the same time, reactions to energy markets by the aggregate economy, such as a slowdown in economic growth resulting from increasing energy prices, are also reflected in this module. A detailed description of the MAM is provided in the EIA publication, Model Documentation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065(2008), (Washington, DC, January 2008).

152

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module Assumptions to the Annual Energy Outlook 2006 Figure 7. Oil and Gas Supply Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze oil and gas supply on a regional basis (Figure 7). A detailed description of the OGSM is provided in the EIA publication, Model Documentation Report: The Oil and Gas Supply Module (OGSM), DOE/EIA-M063(2006), (Washington, DC, 2006). The OGSM provides crude oil and natural gas short-term supply parameters to both the Natural Gas Transmission and Distribution Module and the Petroleum Market Module. The OGSM simulates the activity of numerous firms that produce oil and natural

153

EIA - Assumptions to the Annual Energy Outlook 2009 - Petroleum Market  

Gasoline and Diesel Fuel Update (EIA)

Petroleum Market Module Petroleum Market Module Assumptions to the Annual Energy Outlook 2009 Petroleum Market Module Figure 9., Petroleum Administration for Defense Districts. Need help, contact the National Energy Information Center at 202-586-8800. Table 11.1. Petroleum Product Categories. Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version Table 11.2. Year Round Gasoline Specifications by Petroleum Administration for Defense Districts. Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version Table 11.3. Gasolline Sulfur Content Assumptions, by Region and Gasoline Type, Parts per Million (PPM). Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version

154

Assumptions to the Annual Energy Outlook 2000 - Errata  

Gasoline and Diesel Fuel Update (EIA)

Assumptions to the Annual Energy Outlook 2000 Assumptions to the Annual Energy Outlook 2000 as of 4/4/2000 1. On table 20 "the fractional fuel efficiency change for 4-Speed Automatic" should be .045 instead of .030. On table 20 "the fractional fuel efficiency change for 5-Speed Automatic" should be .065 instead of .045. (Change made on 3/6/2000) 2. Table 28 should be labeled: "Alternative-Fuel Vehicle Attribute Inputs for Compact Cars for Two Stage Logit Model". (Change made on 3/6/2000) 3. The capital costs in Table 29 should read 1998 dollars not 1988 dollars. (Change made on 3/6/2000) 4. Table 37 changed the label "Year Available" to "First Year Completed." Changed the second sentence of Footnote 1 to read "these estimates are costs of new projects

155

EIA - Assumptions to the Annual Energy Outlook 2009 - International Energy  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module International Energy Module Assumptions to the Annual Energy Outlook 2009 International Energy Module Figure 2. World Oil Prices in three Cases, 1995-2030 (2006 dollars per barrel). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 3. OPEC Total Liquids Production in the Reference Case, 1995-2030 (million barrels per day). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 4. Non-OPEC Total Liquids Production in the Reference Case, 1995-2030 (million barrels per day). Need help, contact the National Energy Information Center at 202-586-8800. figure data The International Energy Module (IEM) performs two tasks in all NEMS runs. First, the module reads exogenously global and U.S.A. petroleum liquids

156

EIA - Assumptions to the Annual Energy Outlook 2010 - Residential Demand  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumptions to the Annual Energy Outlook 2010 Residential Demand Module Figure 5. United States Census Divisions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Residential Demand Module projects future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimate of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the "unit energy consumption" by appliance (or UEC-in million Btu per household per year). The projection process adds new housing units to the stock,

157

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

States. States. OGSM encompasses domestic crude oil and natural gas supply by both conventional and nonconventional recovery techniques. Nonconventional recovery includes unconventional gas recovery from low permeability formations of sandstone and shale, and coalbeds. Energy Information Administration/Assumptions to the Annual Energy Outlook 2007 93 Figure 7. Oil and Gas Supply Model Regions Source: Energy Information Administration, Office of Integrated Analysis and Forecasting. Report #:DOE/EIA-0554(2007) Release date: April 2007 Next release date: March 2008 Primary inputs for the module are varied. One set of key assumptions concerns estimates of domestic technically recoverable oil and gas resources. Other factors affecting the projection include the assumed

158

The disciplined use of simplifying assumptions  

Science Conference Proceedings (OSTI)

Simplifying assumptions --- everyone uses them but no one's programming tool explicitly supports them. In programming, as in other kinds of engineering design, simplifying assumptions are an important method for dealing with complexity. Given a complex ...

Charles Rich; Richard C. Waters

1982-04-01T23:59:59.000Z

159

High-bandwidth Modulation of H2/Syngas Fuel to Control Combustion Dynamics in Micro-Mixing Lean Premix Systems  

SciTech Connect

The goal of this program was to develop and demonstrate fuel injection technologies that will facilitate the development of cost-effective turbine engines for Integrated Gasification Combined Cycle (IGCC) power plants, while improving efficiency and reducing emissions. The program involved developing a next-generation multi-point injector with enhanced stability performance for lean premix turbine systems that burn hydrogen (H2) or synthesis gas (syngas) fuels. A previously developed injector that demonstrated superior emissions performance was improved to enhance static flame stability through zone staging and pilot sheltering. In addition, piezo valve technology was implemented to investigate the potential for enhanced dynamic stability through high-bandwidth modulation of the fuel supply. Prototype injector and valve hardware were tested in an atmospheric combustion facility. The program was successful in meeting its objectives. Specifically, the following was accomplished: Demonstrated improvement of lean operability of the Parker multi-point injector through staging of fuel flow and primary zone sheltering; Developed a piezo valve capable of proportional and high-bandwidth modulation of gaseous fuel flow at frequencies as high as 500 Hz; The valve was shown to be capable of effecting changes to flame dynamics, heat release, and acoustic signature of an atmospheric combustor. The latter achievement indicates the viability of the Parker piezo valve technology for use in future adaptively controlled systems for the mitigation of combustion instabilities, particularly for attenuating combustion dynamics under ultra-lean conditions.

Jeff Melzak; Tim Lieuwen; Adel Mansour

2012-01-31T23:59:59.000Z

160

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction Assumptions to the Annual Energy Outlook 2006 Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 20061 (AEO2006), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview3, which is updated once every few years. The National Energy Modeling System

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


161

Assumptions to the Annual Energy Outlook 1999 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

link.gif (1946 bytes) link.gif (1946 bytes) bullet1.gif (843 bytes) Assumptions to the AEO99 bullet1.gif (843 bytes) Supplemental Tables to the AEO99 bullet1.gif (843 bytes) To Forecasting Home Page bullet1.gif (843 bytes) EIA Homepage introduction.gif (4117 bytes) This paper presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 19991 (AEO99), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview.3

162

EIA - Assumptions to the Annual Energy Outlook 2010 - Natural Gas  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module Assumptions to the Annual Energy Outlook 2010 Natural Gas Transmission and Distribution Module Figure 8. Natural Gas Transmission and distribution Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each projection year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and

163

EIA - Assumptions to the Annual Energy Outlook 2008 - Natural Gas  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module Assumptions to the Annual Energy Outlook 2008 Natural Gas Transmission and Distribution Module Figure 8. Natural Gas Transmission and Distribution Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each projection year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution

164

EIA - Assumptions to the Annual Energy Outlook 2009 - Natural Gas  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module Assumptions to the Annual Energy Outlook 2009 Natural Gas Transmission and Distribution Module Figure 8. Natural Gas Transmission and distribution Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each projection year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution

165

Assumptions to the Annual Energy Outlook - Natural Gas Transmission and  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module Assumption to the Annual Energy Outlook Natural Gas Transmission and Distribution Module Figure 8. Natural Gas Transmission and Distribution Model Regions. Having problems, call our National Energy Information Center at 202-586-8800 for help. The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution

166

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumptions to the Annual Energy Outlook 2006 Figure 5. United States Census Divisions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimate of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment

167

High-silicon {sup 238}PuO{sub 2} fuel characterization study: Half module impact tests  

SciTech Connect

The General-Purpose Heat Source (GPHS) provides power for space missions by transmitting the heat of [sup 238]Pu decay to an array of thermoelectric elements. The modular GPHS design was developed to address both survivability during launch abort and return from orbit. Previous testing conducted in support of the Galileo and Ulysses missions documented the response of GPHSs to a variety of fragment- impact, aging, atmospheric reentry, and Earth-impact conditions. The evaluations documented in this report are part of an ongoing program to determine the effect of fuel impurities on the response of the heat source to conditions baselined during the Galileo/Ulysses test program. In the first two tests in this series, encapsulated GPHS fuel pellets containing high levels of silicon were aged, loaded into GPHS module halves, and impacted against steel plates. The results show no significant differences between the response of these capsules and the behavior of relatively low-silicon fuel pellets tested previously.

Reimus, M.A.H.

1997-01-01T23:59:59.000Z

168

EIA - Assumptions to the Annual Energy Outlook 2009 - Residential Demand  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module Assumptions to the Annual Energy Outlook 2009 Residential Demand Module The NEMS Residential Demand Module projects future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimate of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions (see Figure 5). The Residential Demand Module also requires projections of available equipment and their installed costs over the projection horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the projection horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

169

Residential Sector End-Use Forecasting with EPRI-REEPS 2.1: Summary Input Assumptions and Results  

E-Print Network (OSTI)

A comparison of national energy consumption by fuel typeenergy consumption in homes under differing assumptions, scenarios, and policies. At the national

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

170

Electricity Market Module  

Gasoline and Diesel Fuel Update (EIA)

6, DOE/EIA- 6, DOE/EIA- M068(2006). Based on fuel prices and electricity demands provided by the other modules of the NEMS, the EMM determines the most economical way to supply electricity, within environmental and operational constraints. There are assumptions about the operations of the electricity sector and the costs of various options in each of the EMM submodules. This section describes the model parameters and assumptions used in EMM. It includes a discussion of legislation and regulations that are incorporated in EMM as well as information about the climate change action plan. The various electricity and technology cases are also described. EMM Regions The supply regions used in EMM are based on the North American Electric Reliability Council regions and

171

Assumptions to the Annual Energy Outlook 2012  

U.S. Energy Information Administration (EIA)

Assumptions to the Annual Energy Outlook 2012 August 2012 www.eia.gov U.S. Department of Energy Washington, DC 20585

172

EIA - Assumptions to the Annual Energy Outlook 2010 - International Energy  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module International Energy Module Assumptions to the Annual Energy Outlook 2010 International Energy Module Figure 2. World Oil Prices in Three Cases, 1995-2035 Figure 2. World Oil Prices in three Cases, 1995-2035 (2008 dollars per barrel). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 3. OPEC Total Liquids Production in the Reference Case, 1980-2035 Figure 3. OPEC Total Liquids Production in the Reference Case, 1995-2030 (million barrels per day). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 4. Non-OPEC Total Liquids Production in the Reference Case, 1980-2035 Figure 4. Non-OPEC Total Liquids Production in the Reference Case, 1995-2030 (million barrels per day). Need help, contact the National Energy Information Center at 202-586-8800.

173

Macroeconomic Activity Module  

Annual Energy Outlook 2012 (EIA)

d022412A. U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2012 18 Macroeconomic Activity Module To reflect uncertainty in the projection of...

174

EIA - Assumptions to the Annual Energy Outlook 2008 - International Energy  

Gasoline and Diesel Fuel Update (EIA)

International Energy Module International Energy Module Assumptions to the Annual Energy Outlook 2008 International Energy Module The International Energy Module (IEM) performs two tasks in all NEMS runs. First, the module reads exogenously global and U.S.A. petroleum liquids supply and demand curves (1 curve per year; 2008-2030; approximated, isoelastic fit to previous NEMS results). These quantities are not modeled directly in NEMS. Previous versions of the IEM adjusted these quantities after reading in initial values. In an attempt to more closely integrate the AEO2008 with IEO2007 and the STEO some functionality was removed from IEM while a new algorithm was implemented. Based on the difference between U.S. total petroleum liquids production (consumption) and the expected U.S. total liquids production (consumption) at the current WTI price, curves for global petroleum liquids consumption (production) were adjusted for each year. According to previous operations, a new WTI price path was generated. An exogenous oil supply module, Generate World Oil Balances (GWOB), was also used in IEM to provide annual regional (country) level production detail for conventional and unconventional liquids.

175

International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

2 2 International Energy Module The NEMS International Energy Module (IEM) simulates the interaction between U.S. and global petroleum markets. It uses assumptions of economic growth and expectations of future U.S. and world crude-like liquids production and consumption to estimate the effects of changes in U.S. liquid fuels markets on the international petroleum market. For each year of the forecast, the NEMS IEM computes oil prices, provides a supply curve of world crude-like liquids, generates a worldwide oil supply- demand balance with regional detail, and computes quantities of crude oil and light and heavy petroleum products imported into the United States by export region. Changes in the oil price (WTI), which is defined as the price of light, low-sulfur crude oil delivered to Cushing, Oklahoma in

176

Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 137 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 Petroleum Market Module The NEMS Petroleum Market Module (PMM) projects petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, unfinished oil imports, other refinery inputs (including alcohols, ethers, bioesters, corn, biomass, and coal), natural gas plant liquids production, and refinery processing gain. In addition, the PMM projects capacity expansion and fuel consumption at domestic refineries. The PMM contains a linear programming (LP) representation of U.S. refining activities in the five Petroleum Administration for

177

Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

This page inTenTionally lefT blank 135 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2012 Petroleum Market Module The NEMS Petroleum Market Module (PMM) projects petroleum product prices and sources of supply for meeting petroleum product demand. The sources of supply include crude oil (both domestic and imported), petroleum product imports, unfinished oil imports, other refinery inputs (including alcohols, ethers, esters, corn, biomass, and coal), natural gas plant liquids production, and refinery processing gain. In addition, the PMM projects capacity expansion and fuel consumption at domestic refineries. The PMM contains a linear programming (LP) representation of U.S. refining activities in the five Petroleum Administration for

178

Climate Action Planning Tool Formulas and Assumptions  

NLE Websites -- All DOE Office Websites (Extended Search)

CLIMATE ACTION PLANNING TOOL FORMULAS AND ASSUMPTIONS Climate Action Planning Tool Formulas and Assumptions The Climate Action Planning Tool calculations use the following formulas and assumptions to generate the business-as-usual scenario and the greenhouse gas emissions reduction goals for the technology options. Business-as-Usual Scenario All Scope 1 (gas, oil, coal, fleet, and electricity) and Scope 2 calculations increase at a rate equal to the building growth rate. Scope 3 calculations (commuters and business travel) increase at a rate equal to the population growth rate. Assumptions New buildings will consume energy at the same rate (energy use intensity) as existing campus buildings. Fleet operations will be proportional to total building area.

179

Hierarchy of Mesoscale Flow Assumptions and Equations  

Science Conference Proceedings (OSTI)

The present research proposes a standard nomenclature for mesoscale meteorological concepts and integrates existing concepts of atmospheric space scales, flow assumptions, governing equations, and resulting motions into a hierarchy useful in ...

P. Thunis; R. Bornstein

1996-02-01T23:59:59.000Z

180

Assumptions to the Annual Energy Outlook 2002 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 20021 (AEO2002), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview.3 The National Energy Modeling System The projections in the AEO2002 were produced with the National Energy Modeling System. NEMS is developed and maintained by the Office of

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


181

Assumptions to the Annual Energy Outlook 2001 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Outlook2001 Outlook2001 Supplemental Data to the AEO2001 NEMS Conference To Forecasting Home Page EIA Homepage Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 20011 (AEO2001), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview.3 The National Energy Modeling System The projections in the AEO2001 were produced with the National Energy

182

Assumptions to the Annual Energy Outlook 1999 - Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

transportation.gif (5318 bytes) transportation.gif (5318 bytes) The NEMS Transportation Demand Module estimates energy consumption across the nine Census Divisions and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars, light trucks, industry sport utility vehicles and vans), commercial light trucks (8501-10,000 lbs), freight trucks (>10,000 lbs), freight and passenger airplanes, freight rail, freight shipping, mass transit, and miscellaneous transport such as mass transit. Light-duty vehicle fuel consumption is further subdivided into personal usage and commercial fleet consumption.

183

EIA - Assumptions to the Annual Energy Outlook 2008  

Annual Energy Outlook 2012 (EIA)

Module Commercial Demand Module Industrial Demand Module Transportation Demand Module Electricity Market Module Oil and Gas Supply Module Natural Gas Transmission and...

184

Requirements for a Dynamic Solvent Extraction Module to Support Development of Advanced Technologies for the Recycle of Used Nuclear Fuel  

Science Conference Proceedings (OSTI)

The Department of Energy's Nuclear Energy Advanced Modeling and Simulation (NEAMS) Program has been established to create and deploy next generation, verified and validated nuclear energy modeling and simulation capabilities for the design, implementation, and operation of future nuclear energy systems to improve the U.S. energy security. As part of the NEAMS program, Integrated Performance and Safety Codes (IPSC's) are being produced to significantly advance the status of modeling and simulation of energy systems beyond what is currently available to the extent that the new codes be readily functional in the short term and extensible in the longer term. The four IPSC areas include Safeguards and Separations, Reactors, Fuels, and Waste Forms. As part of the Safeguards and Separations (SafeSeps) IPSC effort, interoperable process models are being developed that enable dynamic simulation of an advanced separations plant. A SafeSepss IPSC 'toolkit' is in development to enable the integration of separation process modules and safeguards tools into the design process by providing an environment to compose, verify and validate a simulation application to be used for analysis of various plant configurations and operating conditions. The modules of this toolkit will be implemented on a modern, expandable architecture with the flexibility to explore and evaluate a wide range of process options while preserving their stand-alone usability. Modules implemented at the plant-level will initially incorporate relatively simple representations for each process through a reduced modeling approach. Final versions will incorporate the capability to bridge to subscale models to provide required fidelity in chemical and physical processes. A dynamic solvent extraction model and its module implementation are needed to support the development of this integrated plant model. As a stand-alone application, it will also support solvent development of extraction flowsheets and integrated safeguards approaches within the Fuel Cycle Research and Development (FCR&D) Program. The purpose of this document is to identify the requirements for this dynamic solvent extraction model to guide process modelers and code developers to produce a computational module that meets anticipated future needs.

Jack Law; Veronica Rutledge; Candido Pereira; Jackie Copple; Kurt Frey; John Krebs; Laura Maggos; Kevin Nichols; Kent Wardle; Pratap Sadasivan; Valmor DeAlmieda; David Depaoli

2011-06-01T23:59:59.000Z

185

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

T T he NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 21 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 17). The Industrial Demand Module forecasts energy consumption at the four Census region level (see Figure 5); energy consumption at the Census Division level is estimated by allocating the Census region forecast using the SEDS 25 data.

186

High-Bandwidth Modulation of H2/Syngas Fuel to Control Combustion Dynamics in Micro-Mixing Lean Premix - Parker Hannifin  

NLE Websites -- All DOE Office Websites (Extended Search)

Bandwidth Modulation of H Bandwidth Modulation of H 2 /Syngas Fuel to Control Combustion Dynamics in Micro-Mixing Lean Premix-Parker Hannifin Background In this congressionally directed project, Parker Hannifin Corporation (Parker), in cooperation with Georgia Institute of Technology (Georgia Tech), will enhance its micro-mixing injector platform to improve combustion operability in lean premix turbine systems by attenuating the combustion dynamics. This will be accomplished

187

Assumptions to the Annual Energy Outlook 2013  

U.S. Energy Information Administration (EIA) Indexed Site

Introduction Introduction This page inTenTionally lefT blank 3 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 2013 [1] (AEO2013), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports [2]. The National Energy Modeling System Projections in the AEO2013 are generated using the NEMS, developed and maintained by the Office of Energy Analysis of the U.S.

188

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze oil and gas supply. A detailed description of the OGSM is provided in the EIA publication, Model Documentation Report: The Oil and Gas Supply Module (OGSM), DOE/EIA-M063(2003), (Washington, DC, February 2003). The OGSM provides crude oil and natural gas short-term supply parameters to both the Natural Gas Transmission and Distribution Module and the Petroleum Market Module. The OGSM simulates the activity of numerous firms that produce oil and natural gas from domestic fields throughout the United States, acquire natural gas from foreign producers for resale in the United States, or sell U.S. gas to foreign consumers.

189

Assumptions to the Annual Energy Outlook 2013  

U.S. Energy Information Administration (EIA) Indexed Site

Assumptions to the Annual Assumptions to the Annual Energy Outlook 2013 May 2013 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any other officer or employee of the United States Government. The views in this report therefore should not be construed as representing those of the Department of Energy or other Federal agencies. Table of Contents Introduction .................................................................................................................................................. 3

190

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) represents the interaction between the U.S. economy as a whole and energy markets. The rate of growth of the economy, measured by the growth in gross domestic product (GDP) is a key determinant of the growth in demand for energy. Associated economic factors, such as interest rates and disposable income, strongly influence various elements of the supply and demand for energy. At the same time, reactions to energy markets by the aggregate economy, such as a slowdown in economic growth resulting from increasing energy prices, are also reflected in this module. A detailed description of the MAM is provided in the EIA publication, Model Documentation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065(2003), (Washington, DC, January 2003).

191

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

2 2 The commercial module forecasts consumption by fuel 13 at the Census division level using prices from the NEMS energy supply modules, and macroeconomic variables from the NEMS Macroeconomic Activity Module (MAM), as well as external data sources (technology characterizations, for example). Energy demands are forecast for ten end-use services 14 for eleven building categories 15 in each of the nine Census divisions (see Figure 5). The model begins by developing forecasts of floorspace for the 99 building category and Census division combinations. Next, the ten end-use service demands required for the projected floorspace are developed. The electricity generation and water and space heating supplied by distributed generation and combined heat and power technologies are projected. Technologies are then

192

Energy Information Administration (EIA) - Assumptions to the Annual Energy  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuels Module (RFM) provides natural resources supply and technology input information for forecasts of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has seven submodules representing various renewable energy sources, biomass, geothermal, conventional hydroelectricity, landfill gas, solar thermal, solar photovoltaics, and wind108. Renewable Fuels Module (RFM) provides natural resources supply and technology input information for forecasts of new central-station U.S. electricity generating capacity using renewable energy resources. The RFM has seven submodules representing various renewable energy sources, biomass, geothermal, conventional hydroelectricity, landfill gas, solar thermal, solar photovoltaics, and wind108. Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as water, wind, and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was one of the first electric generation technologies, to newer power systems using biomass, geothermal, LFG, solar, and wind energy. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittency, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon the availability of low-cost energy storage systems.

193

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

6 and 27) including incremental fuel 6 and 27) including incremental fuel efficiency improvement, incremental cost, first year of introduction, and fractional horsepower change. These assumed technology characterizations are scaled up or down to approximate the differences in each attribute for 6 Environmental Protection Administration (EPA) size classes of cars and light trucks. The vehicle sales share module holds the share of vehicle sales by import and domestic manufacturers constant within a vehicle size class at 1999 levels based on National Highway Traffic and Safety Administration data. 32 EPA size class sales shares are projected as a function of income per capita, fuel prices, and average predicted vehicle prices based on endogenous calculations within the MTCM

194

EIA - Assumptions to the Annual Energy Outlook 2008 - Oil and Gas Supply  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module Assumptions to the Annual Energy Outlook 2008 Oil and Gas Supply Module Figure 7. Oil and Gas Supply Module. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze oil and gas supply on a regional basis (Figure 7). A detailed description of the OGSM is provided in the EIA publication, Model Documentation Report: The Oil and Gas Supply Module (OGSM), DOE/EIA-M063(2007), (Washington, DC, 2007). The OGSM provides crude oil and natural gas short-term supply parameters to both the Natural Gas Transmission and Distribution Module and the Petroleum Market Module. The OGSM simulates the activity of numerous firms that produce oil and natural

195

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Residential Demand Module Residential Demand Module The NEMS Residential Demand Module forecasts future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of use of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimates of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the “unit energy consumption” by appliance (or UEC—in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type (single-family, multifamily and mobile homes) and Census Division and prices for each energy source for each of the nine Census Divisions. The Residential Demand Module also requires projections of available equipment over the forecast horizon. Over time, equipment efficiency tends to increase because of general technological advances and also because of Federal and/or state efficiency standards. As energy prices and available equipment changes over the forecast horizon, the module includes projected changes to the type and efficiency of equipment purchased as well as projected changes in the usage intensity of the equipment stock.

196

Assumptions to the Annual Energy Outlook  

Gasoline and Diesel Fuel Update (EIA)

Assumptions to the Annual Energy Outlook 2004 Assumptions to the Annual Energy Outlook 2004 143 Appendix A: Handling of Federal and Selected State Legislation and Regulation in the Annual Energy Outlook Legislation Brief Description AEO Handling Basis Residential Sector A. National Appliance Energy Conservation Act of 1987 Requires Secretary of Energy to set minimum efficiency standards for 10 appliance categories a. Room Air Conditioners Current standard of 8.82 EER Federal Register Notice of Final Rulemaking, b. Other Air Conditioners (<5.4 tons) Current standard 10 SEER for central air conditioner and heat pumps, increasing to 12 SEER in 2006. Federal Register Notice of Final Rulemaking, c. Water Heaters Electric: Current standard .86 EF, incr easing to .90 EF in 2004. Gas: Curren

197

Fuels  

NLE Websites -- All DOE Office Websites (Extended Search)

Goals > Fuels Goals > Fuels XMAT for nuclear fuels XMAT is ideally suited to explore all of the radiation processes experienced by nuclear fuels.The high energy, heavy ion accleration capability (e.g., 250 MeV U) can produce bulk damage deep in the sample, achieving neutron type depths (~10 microns), beyond the range of surface sputtering effects. The APS X-rays are well matched to the ion beams, and are able to probe individual grains at similar penetrations depths. Damage rates to 25 displacements per atom per hour (DPA/hr), and doses >2500 DPA can be achieved. MORE» Fuels in LWRs are subjected to ~1 DPA per day High burn-up fuel can experience >2000 DPA. Traditional reactor tests by neutron irradiation require 3 years in a reactor and 1 year cool down. Conventional accelerators (>1 MeV/ion) are limited to <200-400 DPAs, and

198

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

clothes drying, ceiling fans, coffee makers, spas, home security clothes drying, ceiling fans, coffee makers, spas, home security systems, microwave ovens, set-top boxes, home audio equipment, rechargeable electronics, and VCR/DVDs. In addition to the major equipment-driven end-uses, the average energy consumption per household is projected for other electric and nonelectric appliances. The module's output includes number Energy Information Administration/Assumptions to the Annual Energy Outlook 2007 19 Pacific East South Central South Atlantic Middle Atlantic New England West South Central West North Central East North Central Mountain AK WA MT WY ID NV UT CO AZ NM TX OK IA KS MO IL IN KY TN MS AL FL GA SC NC WV PA NJ MD DE NY CT VT ME RI MA NH VA WI MI OH NE SD MN ND AR LA OR CA HI Middle Atlantic New England East North Central West North Central Pacific West South Central East South Central

199

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

7 7 1 (AEO2007), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant to formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports. 2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview 3 , which is updated once every few years. The National Energy Modeling System The projections in the AEO2007 were produced with the National Energy Modeling System. NEMS is developed and maintained by the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projections of domestic energy-economy markets in the long term and

200

Assumptions to Annual Energy Outlook - Energy Information Administrati...  

Annual Energy Outlook 2012 (EIA)

Assumptions to AEO2013 Release Date: May 14, 2013 | Next Release Date: May 2014 | full report Introduction This report presents the major assumptions of the National Energy...

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


201

Assumptions to the Annual Energy Outlook - Table 41  

Annual Energy Outlook 2012 (EIA)

> Forecasts >Assumptions to the Annual Energy Outlook> Download Report Assumption to the Annual Energy Outlook Adobe Acrobat Reader Logo Adobe Acrobat Reader is required for PDF...

202

Assumptions to the Annual Energy Outlook 2000 - Natural Gas Transmission  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution network that links them. In addition, natural gas flow patterns are a function of the pattern in the previous year, coupled with the relative prices of gas supply options as translated to the represented market “hubs.” The major assumptions used within the NGTDM are grouped into five general categories. They relate to (1) the classification of demand into core and noncore transportation service classes, (2) the pricing of transmission and distribution services, (3) pipeline and storage capacity expansion and utilization, (4) the implementation of recent regulatory reform, and (5) the implementation of provisions of the Climate Change Action Plan (CCAP). A complete listing of NGTDM assumptions and in-depth methodology descriptions are presented in Model Documentation: Natural Gas Transmission and Distribution Model of the National Energy Modeling System, Model Documentation 2000, DOE/EIA-M062(2000), January 2000.

203

Assumptions to the Annual Energy Outlook 2000 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction This paper presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 20001 (AEO2000), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 A synopsis of NEMS, the model components, and the interrelationships of the modules is presented in The National Energy Modeling System: An Overview.3 The National Energy Modeling System The projections in the AEO2000 were produced with the National Energy Modeling System. NEMS is developed and maintained by the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projections of domestic energy-economy markets in the midterm time period and perform policy analyses requested by decisionmakers and analysts in the U.S. Congress, the Department of Energy’s Office of Policy, other DOE offices, and other government agencies.

204

Assumptions to the Annual Energy Outlook 1999 - Natural Gas Transmission  

Gasoline and Diesel Fuel Update (EIA)

The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by obtaining 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. In addition, natural gas flow patterns are a function of the pattern in the previous year, coupled with the relative prices of gas supply options as translated to the represented market “hubs.” The major assumptions used within the NGTDM are grouped into five general categories. They relate to (1) the classification of demand into core and noncore transportation service classes, (2) the pricing of transmission and distribution services, (3) pipeline and storage capacity expansion and utilization, (4) the implementation of recent regulatory reform, and (5) the implementation of provisions of the Climate Change Action Plan (CCAP). A complete listing of NGTDM assumptions and in-depth methodology descriptions are presented in Model Documentation Report: Natural Gas Transmission and Distribution Model of the National Energy Modeling System, DOE/EIA-MO62/1, January 1999.

205

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

7, DOE/EIA-M060(2007) (Washington, 7, DOE/EIA-M060(2007) (Washington, DC, 2007). Key Assumptions Coal Production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the forecast. Forty separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations of thermal grade and sulfur content), and two mine types (underground and surface). Supply curves are constructed using an econometric formulation that relates the minemouth prices of coal for the supply regions and coal types to a set of independent variables. The independent variables include: capacity utilization of mines, mining capacity, labor productivity, the user cost of capital of mining equipment, and the cost of factor inputs (labor and fuel).

206

Cost and Performance Assumptions for Modeling Electricity Generation Technologies  

Science Conference Proceedings (OSTI)

The goal of this project was to compare and contrast utility scale power plant characteristics used in data sets that support energy market models. Characteristics include both technology cost and technology performance projections to the year 2050. Cost parameters include installed capital costs and operation and maintenance (O&M) costs. Performance parameters include plant size, heat rate, capacity factor or availability factor, and plant lifetime. Conventional, renewable, and emerging electricity generating technologies were considered. Six data sets, each associated with a different model, were selected. Two of the data sets represent modeled results, not direct model inputs. These two data sets include cost and performance improvements that result from increased deployment as well as resulting capacity factors estimated from particular model runs; other data sets represent model input data. For the technologies contained in each data set, the levelized cost of energy (LCOE) was also evaluated, according to published cost, performance, and fuel assumptions.

Tidball, R.; Bluestein, J.; Rodriguez, N.; Knoke, S.

2010-11-01T23:59:59.000Z

207

EIA - Assumptions to the Annual Energy Outlook 2010  

Annual Energy Outlook 2012 (EIA)

image Electricity Market Module pdf image Oil and Gas Supply Module pdf image Natural Gas Transmission and Distribution Module pdf image Petroleum Market Module pdf image Coal...

208

EIA - Assumptions to the Annual Energy Outlook 2009  

Annual Energy Outlook 2012 (EIA)

image Electricity Market Module pdf image Oil and Gas Supply Module pdf image Natural Gas Transmission and Distribution Module pdf image Petroleum Market Module pdf image Coal...

209

EIA - Assumptions to the Annual Energy Outlook 2008  

Gasoline and Diesel Fuel Update (EIA)

image Electricity Market Module pdf image Oil and Gas Supply Module pdf image Natural Gas Transmission and Distribution Module pdf image Petroleum Market Module pdf image Coal...

210

Assumptions to the Annual Energy Outlook 2000 - Household Expenditures  

Gasoline and Diesel Fuel Update (EIA)

Commercial Sector Demand Module generates forecasts of commercial sector energy demand through 2020. The definition of the commercial sector is consistent with EIA’s State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial. Since most of commercial energy consumption occurs in buildings, the commercial module relies on the data from the EIA Commercial Buildings Energy Consumption Survey (CBECS) for characterizing the commercial sector activity mix as well as the equipment stock and fuels consumed to provide end use services.12

211

Alternative Fuels Data Center: Petroleum Reduction Planning Tool  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Tools Tools Printable Version Share this resource Send a link to Alternative Fuels Data Center: Petroleum Reduction Planning Tool Assumptions and Methodology to someone by E-mail Share Alternative Fuels Data Center: Petroleum Reduction Planning Tool Assumptions and Methodology on Facebook Tweet about Alternative Fuels Data Center: Petroleum Reduction Planning Tool Assumptions and Methodology on Twitter Bookmark Alternative Fuels Data Center: Petroleum Reduction Planning Tool Assumptions and Methodology on Google Bookmark Alternative Fuels Data Center: Petroleum Reduction Planning Tool Assumptions and Methodology on Delicious Rank Alternative Fuels Data Center: Petroleum Reduction Planning Tool Assumptions and Methodology on Digg Find More places to share Alternative Fuels Data Center: Petroleum

212

Fuel  

E-Print Network (OSTI)

heavy-water-moderated, light-water-moderated and liquid-metal cooled fast breeder reactors fueled with natural or low-enriched uranium and containing thorium mixed with the uranium or in separate target channels. U-232 decays with a 69-year half-life through 1.9-year half-life Th-228 to Tl-208, which emits a 2.6 MeV gamma ray upon decay. We find that pressurized light-water-reactors fueled with LEU-thorium fuel at high burnup (70 MWd/kg) produce U-233 with U-232 contamination levels of about 0.4 percent. At this contamination level, a 5 kg sphere of U-233 would produce a gammaray dose rate of 13 and 38 rem/hr at 1 meter one and ten years after chemical purification respectively. The associated plutonium contains 7.5 percent of the undesirable heat-generating 88-year half-life isotope Pu-238. However, just as it is possible to produce weapon-grade plutonium in low-burnup fuel, it is also practical to use heavy-water reactors to produce U-233 containing only a few ppm of U-232 if the thorium is segregated in target channels and discharged a few times more frequently than the natural-uranium driver fuel. The dose rate from a 5-kg solid sphere of U-233 containing 5 ppm U-232 could be reduced by a further factor of 30, to about 2 mrem/hr, with a close-fitting lead sphere weighing about 100 kg. Thus the proliferation resistance of thorium fuel cycles depends very much upon how they are implemented. The original version of this manuscript was received by Science & Global Security on

Jungmin Kang A

2001-01-01T23:59:59.000Z

213

Residential Sector Demand Module  

Reports and Publications (EIA)

Model Documentation - Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

Owen Comstock

2012-12-19T23:59:59.000Z

214

Industrial Demand Module  

Reports and Publications (EIA)

Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Industrial Demand Module. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code.

Kelly Perl

2013-05-14T23:59:59.000Z

215

Industrial Demand Module  

Reports and Publications (EIA)

Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Industrial Demand Module. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code.

Kelly Perl

2013-09-30T23:59:59.000Z

216

Residential Sector Demand Module  

Reports and Publications (EIA)

Model Documentation - Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

Owen Comstock

2013-11-05T23:59:59.000Z

217

Engineering Development of Advanced Physical Fine Coal Cleaning for Premium Fuel Applications: Task 9 - Selective agglomeration Module Testing and Evaluation.  

SciTech Connect

The primary goal of this project was the engineering development of two advanced physical fine coal cleaning processes, column flotation and selective agglomeration, for premium fuel applications. The project scope included laboratory research and bench-scale testing of both processes on six coals to optimize the processes, followed by the design, construction, and operation of a 2 t/hr process development unit (PDU). The project began in October, 1992, and is scheduled for completion by September 1997. This report summarizes the findings of all the selective agglomeration (SA) test work performed with emphasis on the results of the PDU SA Module testing. Two light hydrocarbons, heptane and pentane, were tested as agglomerants in the laboratory research program which investigated two reactor design concepts: a conventional two-stage agglomeration circuit and a unitized reactor that combined the high- and low-shear operations in one vessel. The results were used to design and build a 25 lb/hr bench-scale unit with two-stage agglomeration. The unit also included a steam stripping and condensation circuit for recovery and recycle of heptane. It was tested on six coals to determine the optimum grind and other process conditions that resulted in the recovery of about 99% of the energy while producing low ash (1-2 lb/MBtu) products. The fineness of the grind was the most important variable with the D80 (80% passing size) varying in the 12 to 68 micron range. All the clean coals could be formulated into coal-water-slurry-fuels with acceptable properties. The bench-scale results were used for the conceptual and detailed design of the PDU SA Module which was integrated with the existing grinding and dewatering circuits. The PDU was operated for about 9 months. During the first three months, the shakedown testing was performed to fine tune the operation and control of various equipment. This was followed by parametric testing, optimization/confirmatory testing, and finally a 72-hour round the clock production run for each of the three project coals (Hiawatha, Taggart, and Indiana VII). The parametric testing results confirmed that the Taggart coal ground to a D80 of 30 microns could be cleaned to 1 lb ash/MBtu, whereas the Hiawatha and Indiana Vil coals had to be ground to D80s of 40 and 20 microns, respectively, to be cleaned to 2 lb ash/MBtu. The percent solids, residence time, shear intensity (impeller tip speed and energy input per unit volume), and heptane dosage were the main variables that affected successful operation (phase inversion or microagglomerate formation in the high-shear reactor and their growth to 2-3 mm in size during low shear). Downward inclination of the vibrating screen and adequate spray water helped produce the low ash products. Btu recoveries were consistently greater than 98%. Two-stage steam stripping achieved about 99% heptane recovery for recycle to the process. Residual hydrocarbon concentrations were in the 3000 to 5000 ppm range on a dry solids basis.

Moro, N.` Jha, M.C.

1997-09-29T23:59:59.000Z

218

EIA - Assumptions to the Annual Energy Outlook 2010 - Oil and Gas Supply  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module Assumptions to the Annual Energy Outlook 2010 Oil and Gas Supply Module Figure 8. Natural Gas Transmission and Distribution Model Regions. The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze oil and gas natural gas exploration and development on a regional basis (Figure 7). The OGSM is organized into 4 submodules: Onshore Lower 48 Oil and Gas Supply Submodule, Offshore Oil and Gas Supply Submodule, Oil Shale Supply submodule, and Alaska Oil and Gas Supply Submodule. A detailed description of the OGSM is provided in the EIA publication, Model Documentation Report: The Oil and Gas Supply Module (OGSM), DOE/EIA-M063(2010), (Washington, DC, 2010). The OGSM provides crude oil and natural gas short-term supply parameters to both the Natural

219

Renewable Fuels Module  

Annual Energy Outlook 2012 (EIA)

The RFM has seven submodules representing various renewable energy sources, biomass, geothermal, conventional hydroelectricity, landfill gas, solar thermal, solar photovoltaics,...

220

Renewable Fuels Module This  

Gasoline and Diesel Fuel Update (EIA)

The RFM has seven submodules representing various renewable energy sources: biomass, geothermal, conventional hydroelectricity, landfill gas, solar thermal, solar photovoltaics,...

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


221

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

unfinished oil imports, other refinery inputs (including alcohols, unfinished oil imports, other refinery inputs (including alcohols, ethers, and bioesters), natural gas plant liquids production, and refinery processing gain. In addition, the PMM projects capacity expansion and fuel consumption at domestic refineries. The PMM contains a linear programming (LP) representation of U.S. refining activities in the five Petroleum Area Defense Districts (PADDs) (Figure 9). The LP model is created by aggregating individual refineries within a PADD into one representative refinery, and linking all five PADD's via crude and product transit links. This representation provides the marginal costs of production for a number of conventional and new petroleum products. In order to interact with other NEMS modules with different regional representations,

222

Annual Energy Outlook 2001-Appendix G: Major Assumptions for the Forecasts  

Gasoline and Diesel Fuel Update (EIA)

Forecasts Forecasts Summary of the AEO2001 Cases/ Scenarios - Appendix Table G1 bullet1.gif (843 bytes) Model Results (Formats - PDF, ZIP) - Appendix Tables - Reference Case - 1998 to 2020 bullet1.gif (843 bytes) Download Report - Entire AEO2001 (PDF) - AEO2001 by Chapters (PDF) bullet1.gif (843 bytes) Acronyms bullet1.gif (843 bytes) Contacts Related Links bullet1.gif (843 bytes) Assumptions to the AEO2001 bullet1.gif (843 bytes) Supplemental Data to the AEO2001 (Only available on the Web) - Regional and more detailed AEO 2001 Reference Case Results - 1998, 2000 to 2020 bullet1.gif (843 bytes) NEMS Conference bullet1.gif (843 bytes) Forecast Homepage bullet1.gif (843 bytes) EIA Homepage Appendix G Major Assumptions for the Forecasts Component Modules Major Assumptions for the Annual Energy Outlook 2001

223

Macroeconomic Activity Module  

Reports and Publications (EIA)

Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Macroeconomic Activity Module (MAM) used to develop the Annual Energy Outlook for 2013 (AEO2013). The report catalogues and describes the module assumptions, computations, methodology, parameter estimation techniques, and mainframe source code

2013-04-10T23:59:59.000Z

224

EIA-Assumptions to the Annual Energy Outlook - National Gas Transmission  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module Assumptions to the Annual Energy Outlook 2007 National Gas Transmission and Distribution Module Figure 8. Natural Gas Transmission and Distribution Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution

225

Model documentation report: Commercial Sector Demand Module of the National Energy Modeling System  

Science Conference Proceedings (OSTI)

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. 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 eleven 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 algorithm also models demand for 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. Section 2 of this report discusses the purpose of the model, detailing its objectives, primary input and output quantities, and the relationship of the Commercial Module to the other modules of the NEMS system. Section 3 of the report describes the rationale behind the model design, providing insights into further assumptions utilized in the model development process to this point. Section 3 also reviews alternative commercial sector modeling methodologies drawn from existing literature, providing a comparison to the chosen approach. Section 4 details the model structure, using graphics and text to illustrate model flows and key computations.

NONE

1998-01-01T23:59:59.000Z

226

Petroleum Market Module - Energy Information Administration  

U.S. Energy Information Administration (EIA)

U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2012 137 Petroleum Market Module Table 11.2. Year-round gasoline ...

227

BWR fuel design options for self-sustainable Th-{sup 233}U fuel cycle  

SciTech Connect

In this work, we investigate a number of fuel assembly design options for a BWR core operating in a closed self-sustainable Th-{sup 233}U fuel cycle. The designs rely on axially heterogeneous fuel assembly structure in order to improve fertile to fissile conversion ratio. One of the main assumptions of the current study was to restrict the fuel assembly geometry to a single axial fissile zone 'sandwiched' between two fertile blanket zones. The main objective was to study the effect of the most important design parameters, such as dimensions of fissile and fertile zones and average void fraction, on the net breeding of {sup 233}U. The main design challenge in this respect is that the fuel breeding potential is at odds with axial power peaking and therefore limits the maximum achievable core power rating. The calculations were performed with BGCore system, which consists of MCNP code coupled with fuel depletion and thermo-hydraulic feedback modules. A single 3-dimensional fuel assembly with reflective radial boundaries was modeled applying simplified restrictions on maximum central line fuel temperature and Critical Power Ratio. It was found that axially heterogeneous fuel assembly design with single fissile zone can potentially achieve net breeding. In this case however, the achievable core power density is roughly one third of the reference BWR core. (authors)

Shaposhnik, Y.; Shwageraus, E. [Ben-Gurion Univ. of the Negev, Dept. of Nuclear Engineering, P. O. B. 653, Beer-Sheva 84105 (Israel); Elias, E. [Faculty of Mechanical Engineering, Technion - Israel Inst. of Technology, Technion city, 32000 Haifa (Israel)

2012-07-01T23:59:59.000Z

228

Assumptions to the Annual Energy Outlook 2002 - Household Expenditures...  

Annual Energy Outlook 2012 (EIA)

Expenditures Module The Household Expenditures Module (HEM) constructs household energy expenditure profiles using historical survey data on household income, population and...

229

General-purpose heat source: Research and development program. High-siliocon fuel characterization study: Half module impact tests 1 and 2  

SciTech Connect

The General-Purpose Heat Source (GPHS) provides power for space missions by transmitting the heat of {sup 238}Pu decay to an array of thermoelectric elements. Because any space mission could experience a launch abort or return from orbit, the heat source must be designed and constructed to survive credible accident environments. Previous testing conducted in support of the Galileo and Ulysses missions documented the response of GPHSs to a variety of fragment-impact, aging, atmospheric reentry, and earth-impact conditions. The evaluations documented in this report are part of an ongoing program to determine the effect of fuel impurities on the response of the heat source to conditions baselined during the Galileo/Ulysses test program. In the first two tests in this series, encapsulated GPHS fuel pellets containing high levels of silicon were aged, loaded into GPHS module halves, and impacted against steel plates. The results show no significant differences between the response of these capsules and the behavior of relatively low-silicon fuel pellets tested previously.

Reimus, M.A.H.; George, T.G.

1996-03-01T23:59:59.000Z

230

Assumption-Commitment Support for CSP Model Checking  

E-Print Network (OSTI)

AVoCS 2006 Assumption-Commitment Support for CSP Model Checking Nick Moffat1 Systems Assurance using CSP. In our formulation, an assumption-commitment style property of a process SYS takes the form-Guarantee, CSP, Model Checking, Compositional Reasoning 1 Introduction The principle of compositional program

Paris-Sud XI, Université de

231

EIA - Assumptions to the Annual Energy Outlook 2009 - Oil and Gas Supply  

Gasoline and Diesel Fuel Update (EIA)

Oil and Gas Supply Module Oil and Gas Supply Module Assumptions to the Annual Energy Outlook 2009 Oil and Gas Supply Module Figure 7. Oil and Gas Supply Model Regions. Need help, contact the National Energy Information Center at 202-586-8800. Table 9.1. Crude Oil Technically Recoverable Resources. Need help, contact the Naitonal Energy Information Center at 202-586-8800. printer-friendly version Table 9.2. Natural Gas Technically Recoverable Resources. Need help, contact the National Energy Information Center at 202-586-8800. Table 9.2. Continued printer-friendly version Table 9.3. Assumed Size and Initial Production year of Major Announced Deepwater Discoveries. Need help, contact the National Energy Information Center at 202-586-8800. printer-friendly version Table 9.4. Assumed Annual Rates of Technological Progress for Conventional Crude Oil and Natural Gas Sources. Need help, contact the National Energy Information Center at 202-586-8800.

232

Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

LBL-34045 UC-1600 Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting-uses include Heating, Ventilation and Air Conditioning (HVAC). Our analysis uses the modeling framework provided by the HVAC module in the Residential End-Use Energy Planning System (REEPS), which was developed

233

Hydrogen Fuel Cell Engines  

E-Print Network (OSTI)

#12;#12;Hydrogen Fuel Cell Engines MODULE 11:GLOSSARY AND CONVERSIONS CONTENTS 11.1 GLOSSARY Cell Engines MODULE 11:GLOSSARY AND CONVERSIONS OBJECTIVES This module is for reference only. Hydrogen MODULE 11: GLOSSARY AND CONVERSIONS PAGE 11-1 11.1 Glossary This glossary covers words, phrases

234

Assumptions to Annual Energy Outlook - Energy Information Administration  

U.S. Energy Information Administration (EIA) Indexed Site

Assumptions to AEO2013 Assumptions to AEO2013 Release Date: May 14, 2013 | Next Release Date: May 2014 | full report Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 2013 [1] (AEO2013), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports [2]. The National Energy Modeling System Projections in the AEO2013 are generated using the NEMS, developed and maintained by the Office of Energy Analysis of the U.S. Energy Information Administration (EIA). In addition to its use in developing the Annual

235

Assumptions to Annual Energy Outlook - Energy Information Administration  

Gasoline and Diesel Fuel Update (EIA)

Assumptions to AEO2012 Assumptions to AEO2012 Release Date: August 2, 2012 | Next Release Date: August 2013 | Full report Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 2012 [1] (AEO2012), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports [2]. The National Energy Modeling System The projections in AEO2012 are generated using the NEMS, developed and maintained by the Office of Energy Analysis (OEA) of the U.S. Energy Information Administration (EIA). In addition to its use in developing the

236

Notes 01. The fundamental assumptions and equations of lubrication theory  

E-Print Network (OSTI)

The fundamental assumption in Lubrication Theory. Derivation of thin film flow equations from Navier-Stokes equations. Importance of fluid inertia effects in thin film flows. Some fluid physical properties

San Andres, Luis

2009-01-01T23:59:59.000Z

237

Prognostic Evaluation of Assumptions Used by Cumulus Parameterizations  

Science Conference Proceedings (OSTI)

Using a spectral-type cumulus parameterization that includes moist downdrafts within a three-dimensional mesoscale model, various disparate closure assumptions are systematically tested within the generalized framework of dynamic control, static ...

Georg A. Grell

1993-03-01T23:59:59.000Z

238

Computational soundness for standard assumptions of formal cryptography  

E-Print Network (OSTI)

This implementation is conceptually simple, and relies only on general assumptions. Specifically, it can be thought of as a 'self-referential' variation on a well-known encryption scheme. 4. Lastly, we show how the ...

Herzog, Jonathan, 1975-

2004-01-01T23:59:59.000Z

239

LBL-34045 UC-1600 Residential HVAC Data, Assumptions and Methodology  

NLE Websites -- All DOE Office Websites (Extended Search)

5 UC-1600 Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1 Francis X. Johnson, Richard E. Brown, James W. Hanford, Alan H. Sanstad and...

240

Assumptions to the Annual Energy Outlook 1999 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

bullet1.gif (843 bytes) Feedback link.gif (1946 bytes) bullet1.gif (843 bytes) Assumptions to the AEO99 bullet1.gif (843 bytes) Interactive Data Queries to the AEO99 bullet1.gif...

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


241

Idaho National Engineering Laboratory installation roadmap assumptions document. Revision 1  

SciTech Connect

This document is a composite of roadmap assumptions developed for the Idaho National Engineering Laboratory (INEL) by the US Department of Energy Idaho Field Office and subcontractor personnel as a key element in the implementation of the Roadmap Methodology for the INEL Site. The development and identification of these assumptions in an important factor in planning basis development and establishes the planning baseline for all subsequent roadmap analysis at the INEL.

Not Available

1993-05-01T23:59:59.000Z

242

Fuel Cell Power Plants Renewable and Waste Fuels  

NLE Websites -- All DOE Office Websites (Extended Search)

Power Plants Power Plants Fuel Cell Power Plants Renewable and Waste Fuels DOE-DOD Workshop Washington, DC. January 13, 2011 reliable, efficient, ultra-clean FuelCell Energy, Inc. * Premier developer of stationary fuel Premier developer of stationary fuel cell technology - founded in 1969 * Over 50 installations in North America, Europe, and Asia * Industrial, commercial, utility products products * 300 KW to 50 MW and beyond FuelCell Energy, the FuelCell Energy logo, Direct FuelCell and "DFC" are all registered trademarks (®) of FuelCell Energy, Inc. g Product Line Based on Stack Building Block Cell Package and Stack Four-Stack Module DFC3000 Two 4-Stack Modules 2.8 MW Single-Stack Module Single Stack Module DFC1500 One 4-Stack Module 1.4 MW DFC300

243

Commercial Sector Demand Module  

Reports and Publications (EIA)

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components.

Kevin Jarzomski

2012-11-15T23:59:59.000Z

244

Coal Market Module  

Reports and Publications (EIA)

Documents the objectives and the conceptual and methodological approach used in the development of the National Energy Modeling System's (NEMS) Coal Market Module (CMM) used to develop the Annual Energy Outlook 2013 (AEO2013). This report catalogues and describes the assumptions, methodology, estimation techniques, and source code of CMM's two submodules. These are the Coal Production Submodule (CPS) and the Coal Distribution Submodule (CDS).

Michael Mellish

2013-07-17T23:59:59.000Z

245

Commercial Sector Demand Module  

Reports and Publications (EIA)

Documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components.

Kevin Jarzomski

2013-10-10T23:59:59.000Z

246

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

equilibrates supply and demand. Associated-dissolved gas production is determined in the Oil and Gas Supply Module (OGSM). Secondary flows are established before the equilibration...

247

Assumptions to the Annual Energy Outlook 1999 - Commercial Demand...  

Annual Energy Outlook 2012 (EIA)

household.gif (5637 bytes) The Household Expenditures Module (HEM) constructs household energy expenditure profiles using historical survey data on household income, population and...

248

Life-cycle analysis of alternative aviation fuels in GREET  

SciTech Connect

The Greenhouse gases, Regulated Emissions, and Energy use in Transportation (GREET) model, developed at Argonne National Laboratory, has been expanded to include well-to-wake (WTWa) analysis of aviation fuels and aircraft. This report documents the key WTWa stages and assumptions for fuels that represent alternatives to petroleum jet fuel. The aviation module in GREET consists of three spreadsheets that present detailed characterizations of well-to-pump and pump-to-wake parameters and WTWa results. By using the expanded GREET version (GREET1{_}2011), we estimate WTWa results for energy use (total, fossil, and petroleum energy) and greenhouse gas (GHG) emissions (carbon dioxide, methane, and nitrous oxide) for (1) each unit of energy (lower heating value) consumed by the aircraft or (2) each unit of distance traveled/ payload carried by the aircraft. The fuel pathways considered in this analysis include petroleum-based jet fuel from conventional and unconventional sources (i.e., oil sands); Fisher-Tropsch (FT) jet fuel from natural gas, coal, and biomass; bio-jet fuel from fast pyrolysis of cellulosic biomass; and bio-jet fuel from vegetable and algal oils, which falls under the American Society for Testing and Materials category of hydroprocessed esters and fatty acids. For aircraft operation, we considered six passenger aircraft classes and four freight aircraft classes in this analysis. Our analysis revealed that, depending on the feedstock source, the fuel conversion technology, and the allocation or displacement credit methodology applied to co-products, alternative bio-jet fuel pathways have the potential to reduce life-cycle GHG emissions by 55-85 percent compared with conventional (petroleum-based) jet fuel. Although producing FT jet fuel from fossil feedstock sources - such as natural gas and coal - could greatly reduce dependence on crude oil, production from such sources (especially coal) produces greater WTWa GHG emissions compared with petroleum jet fuel production unless carbon management practices, such as carbon capture and storage, are used.

Elgowainy, A.; Han, J.; Wang, M.; Carter, N.; Stratton, R.; Hileman, J.; Malwitz, A.; Balasubramanian, S. (Energy Systems)

2012-07-23T23:59:59.000Z

249

A Comparison of the Free Ride and CISK Assumptions  

Science Conference Proceedings (OSTI)

In a recent paper Fraedrich and McBride have studied the relation between the free ride and CISK (conditional instability of the second kind) assumptions in a well-known two-layer model. Here the comparison is extended to a more general case. ...

Torben Strunge Pedersen

1991-08-01T23:59:59.000Z

250

Assumptions to the Annual Energy Outlook 2001 - Macroeconomic Activity  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) represents the interaction between the U.S. economy as a whole and energy markets. The rate of growth of the economy, measured by the growth in gross domestic product (GDP) is a key determinant of the growth in demand for energy. Associated economic factors, such as interest rates and disposable income, strongly influence various elements of the supply and demand for energy. At the same time, reactions to energy markets by the aggregate economy, such as a slowdown in economic growth resulting from increasing energy prices, are also reflected in this module. A detailed description of the MAM is provided in the EIA publication, Model Documentation Report: Macroeconomic Activity Module

251

Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

page intentionally left blank page intentionally left blank 153 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 Coal Market Module The NEMS Coal Market Module (CMM) provides projections of U.S. coal production, consumption, exports, imports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2011, DOE/EIA-M060(2011) (Washington, DC, 2011). Key assumptions Coal production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the projection. Forty-one separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations

252

Coal Market Module This  

Gasoline and Diesel Fuel Update (EIA)

51 51 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2012 Coal Market Module The NEMS Coal Market Module (CMM) provides projections of U.S. coal production, consumption, exports, imports, distribution, and prices. The CMM comprises three functional areas: coal production, coal distribution, and coal exports. A detailed description of the CMM is provided in the EIA publication, Coal Market Module of the National Energy Modeling System 2012, DOE/EIA-M060(2012) (Washington, DC, 2012). Key assumptions Coal production The coal production submodule of the CMM generates a different set of supply curves for the CMM for each year of the projection. Forty-one separate supply curves are developed for each of 14 supply regions, nine coal types (unique combinations

253

EIA Renewable Energy- Shipments of Photovoltaic Cells and Modules ...  

U.S. Energy Information Administration (EIA)

Renewables and Alternate Fuels > Solar Photovoltaic Cell/Module Annual Report > Annual Shipments of Photovoltaic Cells and Modules by Source: Shipments of ...

254

Assumption Parish, Louisiana: Energy Resources | Open Energy Information  

Open Energy Info (EERE)

Assumption Parish, Louisiana: Energy Resources Assumption Parish, Louisiana: Energy Resources Jump to: navigation, search Equivalent URI DBpedia Coordinates 29.9232544°, -91.09694° Loading map... {"minzoom":false,"mappingservice":"googlemaps3","type":"ROADMAP","zoom":14,"types":["ROADMAP","SATELLITE","HYBRID","TERRAIN"],"geoservice":"google","maxzoom":false,"width":"600px","height":"350px","centre":false,"title":"","label":"","icon":"","visitedicon":"","lines":[],"polygons":[],"circles":[],"rectangles":[],"copycoords":false,"static":false,"wmsoverlay":"","layers":[],"controls":["pan","zoom","type","scale","streetview"],"zoomstyle":"DEFAULT","typestyle":"DEFAULT","autoinfowindows":false,"kml":[],"gkml":[],"fusiontables":[],"resizable":false,"tilt":0,"kmlrezoom":false,"poi":true,"imageoverlays":[],"markercluster":false,"searchmarkers":"","locations":[{"text":"","title":"","link":null,"lat":29.9232544,"lon":-91.09694,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

255

PROJECT MANGEMENT PLAN EXAMPLES Policy & Operational Decisions, Assumptions  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Policy & Operational Decisions, Assumptions Policy & Operational Decisions, Assumptions and Strategies Examples 1 & 2 Example 1 1.0 Summary The 322-M Metallurgical Laboratory is currently categorized as a Radiological Facility. It is inactive with no future DOE mission. In May of 1998 it was ranked Number 45 in the Inactive Facilities Risk Ranking database which the Facilities Decommissioning Division maintains. A short-term surveillance and maintenance program is in-place while the facility awaits final deactivation. Completion of the end points described in this deactivation project plan will place the 322-M facility into an End State that can be described as "cold and dark". The facility will be made passively safe requiring minimal surveillance and no scheduled maintenance.

256

Cost and Performance Assumptions for Modeling Electricity Generation Technologies  

NLE Websites -- All DOE Office Websites (Extended Search)

Cost and Performance Cost and Performance Assumptions for Modeling Electricity Generation Technologies Rick Tidball, Joel Bluestein, Nick Rodriguez, and Stu Knoke ICF International Fairfax, Virginia Subcontract Report NREL/SR-6A20-48595 November 2010 NREL is a national laboratory of the U.S. Department of Energy, Office of Energy Efficiency & Renewable Energy, operated by the Alliance for Sustainable Energy, LLC. National Renewable Energy Laboratory 1617 Cole Boulevard Golden, Colorado 80401 303-275-3000 * www.nrel.gov Contract No. DE-AC36-08GO28308 Cost and Performance Assumptions for Modeling Electricity Generation Technologies Rick Tidball, Joel Bluestein, Nick Rodriguez, and Stu Knoke ICF International Fairfax, Virginia NREL Technical Monitor: Jordan Macknick

257

Effects of internal gain assumptions in building energy calculations  

DOE Green Energy (OSTI)

The utilization of direct solar gains in buildings can be affected by operating profiles, such as schedules for internal gains, thermostat controls, and ventilation rates. Building energy analysis methods use various assumptions about these profiles. The effects of typical internal gain assumptions in energy calculations are described. Heating and cooling loads from simulations using the DOE 2.1 computer code are compared for various internal-gain inputs: typical hourly profiles, constant average profiles, and zero gain profiles. Prototype single-family-detached and multi-family-attached residential units are studied with various levels of insulation and infiltration. Small detached commercial buildings and attached zones in large commercial buildings are studied with various levels of internal gains. The results of this study indicate that calculations of annual heating and cooling loads are sensitive to internal gains, but in most cases are relatively insensitive to hourly variations in internal gains.

Christensen, C.; Perkins, R.

1981-01-01T23:59:59.000Z

258

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

The International Energy Module (IEM) performs two tasks in all NEMS runs. First, the module reads The International Energy Module (IEM) performs two tasks in all NEMS runs. First, the module reads exogenously derived supply curves, initial price paths and international regional supply and demand levels into NEMS. These quantities are not modeled directly in NEMS because NEMS is not an international model. Previous versions of the IEM adjusted these quantities after reading in initial values. In an attempt to more closely integrate the AEO2007 with the IEO2006 and the STEO some functionality was removed from the IEM. More analyst time was devoted to analyzing price relationships between marker crude oils and refined products. A new exogenous oil supply model, Generate World Oil Balances (GWOB), was also developed to incorporate actual investment occurring in the international oil market through 2015

259

Assumptions to the Annual Energy Outlook 2002 - Macroeconomic Activity  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) represents the interaction between the U.S. economy as a whole and energy markets. The rate of growth of the economy, measured by the growth in gross domestic product (GDP) is a key determinant of the growth in demand for energy. Associated economic factors, such as interest rates and disposable income, strongly influence various elements of the supply and demand for energy. At the same time, reactions to energy markets by the aggregate economy, such as a slowdown in economic growth resulting from increasing energy prices, are also reflected in this module. A detailed description of the MAM is provided in the EIA publication, Model Documentation Report: Macroeconomic Activity Module

260

Assumptions to the Annual Energy Outlook 2000 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Macroeconomic Activity Module (MAM) represents the interaction between the U.S. economy as a whole and energy markets. The rate of growth of the economy, measured by the growth in gross domestic product (GDP) is a key determinant of the growth in demand for energy. Associated economic factors, such as interest rates and disposable income, strongly influence various elements of the supply and demand for energy. At the same time, reactions to energy markets by the aggregate economy, such as a slowdown in economic growth resulting from increasing energy prices, are also reflected in this module. A detailed description of the MAM is provided in the EIA publication, Model Documentation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065, (Washington, DC, February 1994), plus Macroeconomic Activity Module (MAM): Kernel Regression Documentation of the National Energy Modeling System 1999, DOE/EIA-M065(99), Washington, DC, 1999).

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


261

EIA - Assumptions to the Annual Energy Outlook 2009 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction Assumptions to the Annual Energy Outlook 2009 Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 2009 (AEO2009),1 including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 The National Energy Modeling System The projections in the AEO2009 were produced with the NEMS, which is developed and maintained by the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projections of domestic energy-economy markets in the long term and perform policy analyses requested by decisionmakers in the White House, U.S. Congress, offices within the Department of Energy, including DOE Program Offices, and other government agencies. The Annual Energy Outlook (AEO) projections are also used by analysts and planners in other government agencies and outside organizations.

262

EIA - Assumptions to the Annual Energy Outlook 2010 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction Assumptions to the Annual Energy Outlook 2010 Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 2010 [1] (AEO2010), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports [2]. The National Energy Modeling System The projections in the AEO2010 were produced with the NEMS, which is developed and maintained by the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projections of domestic energy-economy markets in the long term and perform policy analyses requested by decisionmakers in the White House, U.S. Congress, offices within the Department of Energy, including DOE Program Offices, and other government agencies. The Annual Energy Outlook (AEO) projections are also used by analysts and planners in other government agencies and outside organizations.

263

EIA - Assumptions to the Annual Energy Outlook 2008 - Introduction  

Gasoline and Diesel Fuel Update (EIA)

Introduction Introduction Assumptions to the Annual Energy Outlook 2008 Introduction This report presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook 20081 (AEO2008), including general features of the model structure, assumptions concerning energy markets, and the key input data and parameters that are the most significant in formulating the model results. Detailed documentation of the modeling system is available in a series of documentation reports.2 The National Energy Modeling System The projections in the AEO2008 were produced with the NEMS, which is developed and maintained by the Office of Integrated Analysis and Forecasting of the Energy Information Administration (EIA) to provide projections of domestic energy-economy markets in the long term and perform policy analyses requested by decisionmakers in the White House, U.S. Congress, offices within the Department of Energy, including DOE Program Offices, and other government agencies. The AEO projections are also used by analysts and planners in other government agencies and outside organizations.

264

Assumptions to the Annual Energy Outlook 2002 - Transportation...  

Annual Energy Outlook 2012 (EIA)

no on-board fuel reformers), or if the vehicle has ZEV-like equipment on-board such as regenerative braking, advanced batteries, or an advanced electric drivetrain. An emission...

265

Assumptions to the Annual Energy Outlook 1999 - Table 2  

Gasoline and Diesel Fuel Update (EIA)

Carbon Emission Factors (Kilograms-carbon per million Btu) Carbon Emission Factors (Kilograms-carbon per million Btu) Fuel Type Carbon Coefficient at Full Combustion Combustion Fraction Adjusted Emissions Factor Petroleum Motor Gasoline 19.35 0.990 19.16 Liquefied Petroleum Gas Used as Fuel 16.87 0.995 16.79 Used as Feedstock 17.11 0.200 3.42 Jet Fuel 19.33 0.990 19.14 Distillate Fuel 19.95 0.990 19.75 Residual Fuel 21.49 0.990 21.28 Asphalt and Road Oil 20.62 0.000 0.00 Lubricants 20.24 0.600 12.14 Petrochemical Feedstocks 19.37 0.200 3.87 Kerosene 19.72 0.990 19.52 Petroleum Coke 27.85 0.500 13.93 Petroleum Still Gas 17.51 0.995 17.42 Other Industrial 20.31 0.990 20.11 Coal Residential and Commercial 25.92 0.990 25.74 Metallurgical 25.55 0.990 25.28 Industrial Other 25.61 0.990 25.38 Electric Utility1 25.74 0.990 25.48 Natural Gas Used as Fuel

266

Model documentation report: Residential sector demand module of the national energy modeling system  

SciTech Connect

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This reference document provides a detailed description for energy analysts, other users, and the public. The NEMS Residential Sector Demand Module is currently used for mid-term forecasting purposes and energy policy analysis over the forecast horizon of 1993 through 2020. The model generates forecasts of energy demand for the residential sector by service, fuel, and Census Division. Policy impacts resulting from new technologies, market incentives, and regulatory changes can be estimated using the module. 26 refs., 6 figs., 5 tabs.

NONE

1998-01-01T23:59:59.000Z

267

Assessment and Suggestions to Improve the Commercial Building Module of EIA-NEMS  

E-Print Network (OSTI)

The National Energy Modeling System (NEMS) is a comprehensive, computer-based, energy-economy modeling system developed and maintained by the Department of Energy's Energy Information Administration (EIA). NEMS forecasts the national production, imports, conversion, consumption, and prices of energy out to 2015, subject to macroeconomic assumptions, world energy markets, resource availability and costs, technological developments, and behavioral and technological choice criteria. NEMS has nine program modules of which the Commercial Sector Demand (CSD) module is one. Currently the CSD module uses a matrix of Energy Use Intensities (EUls) gleaned from the 1989 CBECS database to model service demand per major fuel type for eight different geographic census divisions and eleven different building types.

O'Neal, D. L.

1996-01-01T23:59:59.000Z

268

Assumptions to the Annual Energy Outlook 2001 - Natural Gas Transmission  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution network that links them. In addition, natural gas flow patterns are a function of the pattern in the previous year, coupled with the relative prices of gas supply options as translated to the represented market

269

Assumptions to the Annual Energy Outlook 1999 - Macroeconomic Activity  

Gasoline and Diesel Fuel Update (EIA)

macroeconomic.gif (5367 bytes) macroeconomic.gif (5367 bytes) The Macroeconomic Activity Module (MAM) represents the interaction between the U.S. economy as a whole and energy markets. The rate of growth of the economy, measured by the growth in gross domestic product (GDP) is a key determinant of the growth in demand for energy. Associated economic factors, such as interest rates and disposable income, strongly influence various elements of the supply and demand for energy. At the same time, reactions to energy markets by the aggregate economy, such as a slowdown in economic growth resulting from increasing energy prices, are also reflected in this module. A detailed description of the MAM is provided in the EIA publication, Model Documentation Report: Macroeconomic Activity Module (MAM) of the National Energy Modeling System, DOE/EIA-M065, (Washington, DC, February 1994).

270

Assumptions to the Annual Energy Outlook 2002 - Natural Gas Transmission  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Transmission and Distribution Module Natural Gas Transmission and Distribution Module The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each forecast year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution network that links them. In addition, natural gas flow patterns are a function of the pattern in the previous year, coupled with the relative prices of gas supply options as translated to the represented market

271

Residential Sector Demand Module 2000, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

John H. Cymbalsky

1999-12-01T23:59:59.000Z

272

Residential Sector Demand Module 2004, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

John H. Cymbalsky

2004-02-01T23:59:59.000Z

273

Residential Sector Demand Module 2001, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

John H. Cymbalsky

2000-12-01T23:59:59.000Z

274

Residential Sector Demand Module 2002, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

John H. Cymbalsky

2001-12-01T23:59:59.000Z

275

Residential Sector Demand Module 2005, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

John H. Cymbalsky

2005-04-01T23:59:59.000Z

276

Residential Sector Demand Module 2003, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

John H. Cymbalsky

2003-01-01T23:59:59.000Z

277

Residential Sector Demand Module 2008, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

John H. Cymbalsky

2008-10-10T23:59:59.000Z

278

Residential Sector Demand Module 2006, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

John H. Cymbalsky

2006-03-01T23:59:59.000Z

279

Residential Sector Demand Module 2009, Model Documentation  

Reports and Publications (EIA)

Model Documentation - Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

John H. Cymbalsky

2009-05-01T23:59:59.000Z

280

Residential Sector Demand Module 2007, Model Documentation  

Reports and Publications (EIA)

Documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code.

John H. Cymbalsky

2007-04-26T23:59:59.000Z

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


281

Fuel Cell Power PlantsFuel Cell Power Plants Renewable and Waste Fuels  

E-Print Network (OSTI)

for Safety and Grid Interface Direct Fuel Cell Module: FuelCell Energy, the FuelCell Energy logo, Direct Fuel generation of combined heat andcombined heat and power ­Clean Power with natural gas f lfuel ­Renewable Power with biofuels ·Grid connected power generationgeneration ­High Efficiency Grid support

282

Biennial Assessment of the Fifth Power Plan Interim Report on Fuel Price Assumptions  

E-Print Network (OSTI)

The Fifth Power Plan includes price forecasts for natural gas, oil, and coal. Natural gas prices have by far and natural gas prices have put some pressure on coal prices as well, although they remain lower capacity to deliver the coal and higher oil prices increased the delivery costs as well. Both natural gas

283

Assumptions to the Annual Energy Outlook 1999 - Table 1  

Gasoline and Diesel Fuel Update (EIA)

Summary of AEO99 Cases Summary of AEO99 Cases Case Name Description Integration mode Reference Baseline economic growth, world oil price, and technology assumptions Fully Integrated Low Economic Growth Gross Domestic product grows at an average annual rate of 1.5 percent, compared to the reference case growth of 2.1 percent. Fully Integrated High Economic Growth Gross domestic product grows at an average annual rate of 2.6 percent, compared to the reference case growth of 2.1 percent. Fully Integrated Low World Oil Price World oil prices are $14.57 per barrel in 2020, compared to $22.73 per barrel in the reference case. Partially Integrated High World Oil Price World oil prices are $29.35 per barrel in 2020, compared to $22.73 per barrel in the reference case. Partially Integrated Residential: 1999 Technology

284

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

7), 7), (Washington, DC, January 2007). Key Assumptions The output of the U.S. economy, measured by GDP, is expected to increase by 2.9 percent between 2005 and 2030 in the reference case. Two key factors help explain the growth in GDP: the growth rate of nonfarm employment and the rate of productivity change associated with employment. As Table 3 indicates, for the Reference Case GDP growth slows down in each of the periods identified, from 3.0 percent between 2005 and 2010, to 2.9 percent between 2010 and 2020, to 2.8 percent in the between 2020 and 2030. In the near term from 2005 through 2010, the growth in nonfarm employment is low at 1.2 percent compared with 2.4 percent in the second half of the 1990s, while the economy is expected to experiencing relatively strong

285

Assumptions to the Annual Energy Outlook 2007 Report  

Gasoline and Diesel Fuel Update (EIA)

12 12 . Some renewables, such as landfill gas (LFG) from municipal solid waste (MSW) and other biomass materials, are fuels in the conventional sense of the word, while others, such as water, wind, and solar radiation, are energy sources that do not involve the production or consumption of a fuel. Renewable technologies cover the gamut of commercial market penetration, from hydroelectric power, which was one of the first electric generation technologies, to newer power systems using biomass, geothermal, LFG, solar, and wind energy. In some cases, they require technological innovation to become cost effective or have inherent characteristics, such as intermittency, which make their penetration into the electricity grid dependent upon new methods for integration within utility system plans or upon the availability of low-cost

286

Electricity Market Module  

Reports and Publications (EIA)

Documents the Electricity Market Module as it was used for the Annual Energy Outlook 2013. The Electricity Market Module (EMM) is the electricity supply component of the National Energy Modeling System (NEMS). The EMM represents the generation, transmission, and pricing of electricity. It consists of four submodules: the Electricity Capacity Planning (ECP) Submodule, the Electricity Fuel Dispatch (EFD) Submodule, the Electricity Finance and Pricing (EFP) Submodule, and the Electricity Load and Demand (ELD) Submodule.

Jeff Jones

2013-07-24T23:59:59.000Z

287

Thermal breeder fuel enrichment zoning  

DOE Patents (OSTI)

A method and apparatus for improving the performance of a thermal breeder reactor having regions of higher than average moderator concentration are disclosed. The fuel modules of the reactor core contain at least two different types of fuel elements, a high enrichment fuel element and a low enrichment fuel element. The two types of fuel elements are arranged in the fuel module with the low enrichment fuel elements located between the high moderator regions and the high enrichment fuel elements. Preferably, shim rods made of a fertile material are provided in selective regions for controlling the reactivity of the reactor by movement of the shim rods into and out of the reactor core. The moderation of neutrons adjacent the high enrichment fuel elements is preferably minimized as by reducing the spacing of the high enrichment fuel elements and/or using a moderator having a reduced moderating effect.

Capossela, Harry J. (Schenectady, NY); Dwyer, Joseph R. (Albany, NY); Luce, Robert G. (Schenectady, NY); McCoy, Daniel F. (Latham, NY); Merriman, Floyd C. (Rotterdam, NY)

1992-01-01T23:59:59.000Z

288

Transportation Sector Module 1997, Model Documentation  

Reports and Publications (EIA)

Over the past year, several modifications have been made to the NEMS Transportation Model,incorporating greater levels of detail and analysis in modules previously represented in the aggregate or under a profusion of simplifying assumptions. This document is intended to amend those sections of the Model Documentation Report (MDR) which describe these superseded modules.

John Maples

1997-02-01T23:59:59.000Z

289

CRITICAL ASSUMPTIONS IN THE F-TANK FARM CLOSURE OPERATIONAL DOCUMENTATION REGARDING WASTE TANK INTERNAL CONFIGURATIONS  

SciTech Connect

The intent of this document is to provide clarification of critical assumptions regarding the internal configurations of liquid waste tanks at operational closure, with respect to F-Tank Farm (FTF) closure documentation. For the purposes of this document, FTF closure documentation includes: (1) Performance Assessment for the F-Tank Farm at the Savannah River Site (hereafter referred to as the FTF PA) (SRS-REG-2007-00002), (2) Basis for Section 3116 Determination for Closure of F-Tank Farm at the Savannah River Site (DOE/SRS-WD-2012-001), (3) Tier 1 Closure Plan for the F-Area Waste Tank Systems at the Savannah River Site (SRR-CWDA-2010-00147), (4) F-Tank Farm Tanks 18 and 19 DOE Manual 435.1-1 Tier 2 Closure Plan Savannah River Site (SRR-CWDA-2011-00015), (5) Industrial Wastewater Closure Module for the Liquid Waste Tanks 18 and 19 (SRRCWDA-2010-00003), and (6) Tank 18/Tank 19 Special Analysis for the Performance Assessment for the F-Tank Farm at the Savannah River Site (hereafter referred to as the Tank 18/Tank 19 Special Analysis) (SRR-CWDA-2010-00124). Note that the first three FTF closure documents listed apply to the entire FTF, whereas the last three FTF closure documents listed are specific to Tanks 18 and 19. These two waste tanks are expected to be the first two tanks to be grouted and operationally closed under the current suite of FTF closure documents and many of the assumptions and approaches that apply to these two tanks are also applicable to the other FTF waste tanks and operational closure processes.

Hommel, S.; Fountain, D.

2012-03-28T23:59:59.000Z

290

Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

2 2 Industrial Demand Module The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 15 manufacturing and 6 non-manufacturing industries. The manufacturing industries are further subdivided into the energy- intensive manufacturing industries and non-energy-intensive manufacturing industries (Table 6.1). The manufacturing industries are modeled through the use of a detailed process-flow or end-use accounting procedure, whereas the non- manufacturing industries are modeled with substantially less detail. The petroleum refining industry is not included in the Industrial Demand Module, as it is simulated separately in the Petroleum Market Module of NEMS. The Industrial Demand Module calculates energy consumption for the four Census Regions (see Figure 5) and disaggregates the energy consumption

291

Hydrogen Fuel Cell Engines  

E-Print Network (OSTI)

the batteries, and to power accessories like the air condi- tioner and heater. Hybrid electric cars can exceed#12;#12;Hydrogen Fuel Cell Engines MODULE 8: FUEL CELL HYBRID ELECTRIC VEHICLES CONTENTS 8.1 HYBRID ELECTRIC VEHICLES .................................................................................. 8-1 8

292

Assumptions to the Annual Energy Outlook 1999 - Acronyms  

Gasoline and Diesel Fuel Update (EIA)

acronyms.gif (3143 bytes) acronyms.gif (3143 bytes) AEO Annual Energy Outlook AEO98 Annual Energy Outlook 1998 AEO99 Annual Energy Outlook 1999 AFV AFV Alternative-Fuel Vehicle AGA American Gas Association ANGTS Alaskan Natural Gas Transportation System BEA Bureau of Economic Analysis BSC Boiler/Steam/Cogeneration BTU British Thermal Unit CAAA90 Clean Air Act Amendments of 1990 CBECS Commercial Buildings Energy Consumption Surveys CCAP Climate Change Action Plan CDD Cooling Degree-Days CNG Compressed natural gas DOE U.S. Department of Energy DRB Demonstrated Reserve Base DRI Data Resources, Inc./McGraw Hill EER Energy Efficiency Ratio EIA Energy Information Administration EIS Environmental Impact Statement EPA U.S. Environmental Protection Agency EPACT Energy Policy Act of 1992 EWG Exempt Wholesale Generator FAA Federal Aviation Administration

293

Macroeconomic Activity Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 19 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook2011 Macroeconomic Activity Module The Macroeconomic Activity Module (MAM) represents the interaction between the U.S. economy as a whole and energy markets. The rate of growth of the economy, measured by the growth in gross domestic product (GDP) is a key determinant of the growth in demand for energy. Associated economic factors, such as interest rates and disposable income, strongly influence various elements of the supply and demand for energy. At the same time, reactions to energy markets by the aggregate economy, such as a slowdown in economic growth resulting from increasing energy prices, are also reflected in this module.

294

A Statistical Analysis of the Dependency of Closure Assumptions in Cumulus Parameterization on the Horizontal Resolution  

Science Conference Proceedings (OSTI)

Simulated data from the UCLA cumulus ensemble model are used to investigate the quasi-universal validity of closure assumptions used in existing cumulus parameterizations. A closure assumption is quasi-universally valid if it is sensitive neither ...

Kuan-Man Xu

1994-12-01T23:59:59.000Z

295

Industrial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and The NEMS Industrial Demand Module estimates energy consumption by energy source (fuels and feedstocks) for 12 manufacturing and 6 nonmanufacturing industries. The manufacturing industries are further subdivided into the energy-intensive manufacturing industries and nonenergy-intensive manufacturing industries. The manufacturing industries are modeled through the use of a detailed process flow or end use accounting procedure, whereas the nonmanufacturing industries are modeled with substantially less detail (Table 17). The Industrial Demand Module forecasts energy consumption at the four Census region level (see Figure 5); energy consumption at the Census Division level is estimated by allocating the Census region forecast using the SEDS 27 data.

296

World Energy Projection System Plus (WEPS+): Global Activity Module  

Reports and Publications (EIA)

World Energy Projection System Plus Model Documentation: Global Activity Module Documents the objectives, analytical approach, and development of the World Energy Projection Plus (WEPS+) Global Activity Module (GAM) used to develop the International Energy Outlook for 2013 (IEO2013). The report catalogues and describes the module assumptions, computations, methodology, parameter estimation techniques, and mainframe source code

Vipin Arora

2013-10-23T23:59:59.000Z

297

Demonstration of zinc/air fuel battery to enhance the range and mission of fleet electric vehicles: Preliminary results in the refueling of a multicell module  

DOE Green Energy (OSTI)

We report progress in an effort to develop and demonstrate a refuelable zinc/air battery for fleet electric vehicle applications. A refuelable module consisting of twelve bipolar cells with internal flow system has been refueled at rates of nearly 4 cells per minute refueling time of 10 minutes for a 15 kW, 55 kWh battery. The module is refueled by entrainment of 0.5-mm particles in rapidly flowing electrolyte, which delivers the particles into hoppers above each cell in a parallel-flow hydraulic circuit. The concept of user-recovery is presented as an alternative to centralized service infrastructure during market entry.

Cooper, J.F.; Fleming, D.; Keene, L.; Maimoni, A.; Peterman, K.; Koopman, R.

1994-08-08T23:59:59.000Z

298

Oil and Gas Supply Module  

U.S. Energy Information Administration (EIA) Indexed Site

Oil and Gas Supply Module Oil and Gas Supply Module This page inTenTionally lefT blank 119 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Oil and Gas Supply Module The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze crude oil and natural gas exploration and development on a regional basis (Figure 8). The OGSM is organized into 4 submodules: Onshore Lower 48 Oil and Gas Supply Submodule, Offshore Oil and Gas Supply Submodule, Oil Shale Supply Submodule[1], and Alaska Oil and Gas Supply Submodule. A detailed description of the OGSM is provided in the EIA publication, Model Documentation Report: The Oil and Gas Supply Module (OGSM), DOE/EIA-M063(2011), (Washington, DC, 2011). The OGSM provides

299

PDSF Modules  

NLE Websites -- All DOE Office Websites (Extended Search)

Modules Modules Modules Modules Approach to Managing The Environment Modules is a system which you can use to specify what software you want to use. If you want to use a particular software package loading its module will take care of the details of modifying your environment as necessary. The advantage of the modules approach is that the you are not required to explicitly specify paths for different executable versions and try to keep their related man paths and environment variables coordinated. Instead you simply "load" and "unload" specific modules to control your environment. Getting Started with Modules If you're using the standard startup files on PDSF then you're already setup for using modules. If the "module" command is not available, please

300

Alternative Fuels Data Center: Hybrid and Plug-In Electric Vehicle  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Electricity Electricity Printable Version Share this resource Send a link to Alternative Fuels Data Center: Hybrid and Plug-In Electric Vehicle Emissions Data Sources and Assumptions to someone by E-mail Share Alternative Fuels Data Center: Hybrid and Plug-In Electric Vehicle Emissions Data Sources and Assumptions on Facebook Tweet about Alternative Fuels Data Center: Hybrid and Plug-In Electric Vehicle Emissions Data Sources and Assumptions on Twitter Bookmark Alternative Fuels Data Center: Hybrid and Plug-In Electric Vehicle Emissions Data Sources and Assumptions on Google Bookmark Alternative Fuels Data Center: Hybrid and Plug-In Electric Vehicle Emissions Data Sources and Assumptions on Delicious Rank Alternative Fuels Data Center: Hybrid and Plug-In Electric Vehicle Emissions Data Sources and Assumptions on Digg

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


301

Alternative fuels and vehicles choice model  

DOE Green Energy (OSTI)

This report describes the theory and implementation of a model of alternative fuel and vehicle choice (AFVC), designed for use with the US Department of Energy`s Alternative Fuels Trade Model (AFTM). The AFTM is a static equilibrium model of the world supply and demand for liquid fuels, encompassing resource production, conversion processes, transportation, and consumption. The AFTM also includes fuel-switching behavior by incorporating multinomial logit-type equations for choice of alternative fuel vehicles and alternative fuels. This allows the model to solve for market shares of vehicles and fuels, as well as for fuel prices and quantities. The AFVC model includes fuel-flexible, bi-fuel, and dedicated fuel vehicles. For multi-fuel vehicles, the choice of fuel is subsumed within the vehicle choice framework, resulting in a nested multinomial logit design. The nesting is shown to be required by the different price elasticities of fuel and vehicle choice. A unique feature of the AFVC is that its parameters are derived directly from the characteristics of alternative fuels and vehicle technologies, together with a few key assumptions about consumer behavior. This not only establishes a direct link between assumptions and model predictions, but facilitates sensitivity testing, as well. The implementation of the AFVC model as a spreadsheet is also described.

Greene, D.L. [Oak Ridge National Lab., TN (United States). Center for Transportation Analysis

1994-10-01T23:59:59.000Z

302

Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

This page intentionally left blank This page intentionally left blank 39 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 Commercial Demand Module The NEMS Commercial Sector Demand Module generates projections of commercial sector energy demand through 2035. The definition of the commercial sector is consistent with EIA's State Energy Data System (SEDS). That is, the commercial sector includes business establishments that are not engaged in transportation or in manufacturing or other types of industrial activity (e.g., agriculture, mining or construction). The bulk of commercial sector energy is consumed within buildings; however, street lights, pumps, bridges, and public services are also included if the establishment operating them is considered commercial.

303

A Review of Electric Vehicle Cost Studies: Assumptions, Methodologies, and Results  

E-Print Network (OSTI)

assumptions Battery costs and capacities: Lead acid batteryElectricity cost Battery cost and capacity: Lead acidElectricity cost Battery cost and capacity: N i C d

Lipman, Timothy

1999-01-01T23:59:59.000Z

304

Oil and Gas Supply Module  

Gasoline and Diesel Fuel Update (EIA)

1 1 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2012 Oil and Gas Supply Module The NEMS Oil and Gas Supply Module (OGSM) constitutes a comprehensive framework with which to analyze crude oil and natural gas exploration and development on a regional basis (Figure 8). The OGSM is organized into 4 submodules: Onshore Lower 48 Oil and Gas Supply Submodule, Offshore Oil and Gas Supply Submodule, Oil Shale Supply Submodule[1], and Alaska Oil and Gas Supply Submodule. A detailed description of the OGSM is provided in the EIA publication, Model Documentation Report: The Oil and Gas Supply Module (OGSM), DOE/EIA-M063(2011), (Washington, DC, 2011). The OGSM provides crude oil and natural gas short-term supply parameters to both the Natural Gas Transmission and Distribution Module and the Petroleum

305

Neural network control of air-to-fuel ratio in a bi-fuel engine  

Science Conference Proceedings (OSTI)

In this paper, a neural network-based control system is proposed for fine control of the intake air/fuel ratio in a bi-fuel engine. This control system is an add-on module for an existing vehicle manufacturer's electronic control units (ECUs). Typically ... Keywords: Artificial neural networks, bi-fuel engines, compressed natural gas (CNG), fuel injection control

G. Gnanam; S. R. Habibi; R. T. Burton; M. T. Sulatisky

2006-09-01T23:59:59.000Z

306

Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

4 4 The commercial module forecasts consumption by fuel 15 at the Census division level using prices from the NEMS energy supply modules, and macroeconomic variables from the NEMS Macroeconomic Activity Module (MAM), as well as external data sources (technology characterizations, for example). Energy demands are forecast for ten end-use services 16 for eleven building categories 17 in each of the nine Census divisions (see Figure 5). The model begins by developing forecasts of floorspace for the 99 building category and Census division combinations. Next, the ten end-use service demands required for the projected floorspace are developed. The electricity generation and water and space heating supplied by distributed generation and combined heat and power technologies are projected. Technologies are then

307

Development of Hydrogen Selective Membranes/Modules as Reactors/Separators for Distributed Hydrogen Production - DOE Hydrogen and Fuel Cells Program FY 2012 Annual Progress Report  

NLE Websites -- All DOE Office Websites (Extended Search)

3 3 FY 2012 Annual Progress Report DOE Hydrogen and Fuel Cells Program Paul KT Liu Media and Process Technology Inc. (M&P) 1155 William Pitt Way Pittsburgh, PA 15238 Phone: (412) 826-3711 Email: pliu@mediaandprocess.com DOE Managers HQ: Sara Dillich Phone: (202) 586-7925 Email: Sara.Dillich@ee.doe.gov GO: Katie Randolph Phone: (720) 356-1759 Email: Katie.Randolph@go.doe.gov Contract Number: DE-FG36-05GO15092 Subcontractor: University of Southern California Project Start Date: July 1, 2005 Projected End Date: December 31, 2012 Fiscal Year (FY) 2012 Objectives The water-gas shift (WGS) reaction becomes less efficient when high CO conversion is required, such as for distributed hydrogen production applications. Our project

308

Advanced Fuel Cycle Cost Basis  

SciTech Connect

This report, commissioned by the U.S. Department of Energy (DOE), provides a comprehensive set of cost data supporting a cost analysis for the relative economic comparison of options for use in the Advanced Fuel Cycle Initiative (AFCI) Program. The report describes the AFCI cost basis development process, reference information on AFCI cost modules, a procedure for estimating fuel cycle costs, economic evaluation guidelines, and a discussion on the integration of cost data into economic computer models. This report contains reference cost data for 25 cost modules23 fuel cycle cost modules and 2 reactor modules. The cost modules were developed in the areas of natural uranium mining and milling, conversion, enrichment, depleted uranium disposition, fuel fabrication, interim spent fuel storage, reprocessing, waste conditioning, spent nuclear fuel (SNF) packaging, long-term monitored retrievable storage, near surface disposal of low-level waste (LLW), geologic repository and other disposal concepts, and transportation processes for nuclear fuel, LLW, SNF, transuranic, and high-level waste.

D. E. Shropshire; K. A. Williams; W. B. Boore; J. D. Smith; B. W. Dixon; M. Dunzik-Gougar; R. D. Adams; D. Gombert; E. Schneider

2008-03-01T23:59:59.000Z

309

Advanced Fuel Cycle Cost Basis  

SciTech Connect

This report, commissioned by the U.S. Department of Energy (DOE), provides a comprehensive set of cost data supporting a cost analysis for the relative economic comparison of options for use in the Advanced Fuel Cycle Initiative (AFCI) Program. The report describes the AFCI cost basis development process, reference information on AFCI cost modules, a procedure for estimating fuel cycle costs, economic evaluation guidelines, and a discussion on the integration of cost data into economic computer models. This report contains reference cost data for 26 cost modules24 fuel cycle cost modules and 2 reactor modules. The cost modules were developed in the areas of natural uranium mining and milling, conversion, enrichment, depleted uranium disposition, fuel fabrication, interim spent fuel storage, reprocessing, waste conditioning, spent nuclear fuel (SNF) packaging, long-term monitored retrievable storage, near surface disposal of low-level waste (LLW), geologic repository and other disposal concepts, and transportation processes for nuclear fuel, LLW, SNF, and high-level waste.

D. E. Shropshire; K. A. Williams; W. B. Boore; J. D. Smith; B. W. Dixon; M. Dunzik-Gougar; R. D. Adams; D. Gombert

2007-04-01T23:59:59.000Z

310

Advanced Fuel Cycle Cost Basis  

SciTech Connect

This report, commissioned by the U.S. Department of Energy (DOE), provides a comprehensive set of cost data supporting a cost analysis for the relative economic comparison of options for use in the Advanced Fuel Cycle Initiative (AFCI) Program. The report describes the AFCI cost basis development process, reference information on AFCI cost modules, a procedure for estimating fuel cycle costs, economic evaluation guidelines, and a discussion on the integration of cost data into economic computer models. This report contains reference cost data for 25 cost modules23 fuel cycle cost modules and 2 reactor modules. The cost modules were developed in the areas of natural uranium mining and milling, conversion, enrichment, depleted uranium disposition, fuel fabrication, interim spent fuel storage, reprocessing, waste conditioning, spent nuclear fuel (SNF) packaging, long-term monitored retrievable storage, near surface disposal of low-level waste (LLW), geologic repository and other disposal concepts, and transportation processes for nuclear fuel, LLW, SNF, transuranic, and high-level waste.

D. E. Shropshire; K. A. Williams; W. B. Boore; J. D. Smith; B. W. Dixon; M. Dunzik-Gougar; R. D. Adams; D. Gombert; E. Schneider

2009-12-01T23:59:59.000Z

311

Module Configuration  

SciTech Connect

A stand alone battery module including: (a) a mechanical configuration; (b) a thermal management configuration; (c) an electrical connection configuration; and (d) an electronics configuration. Such a module is fully interchangeable in a battery pack assembly, mechanically, from the thermal management point of view, and electrically. With the same hardware, the module can accommodate different cell sizes and, therefore, can easily have different capacities. The module structure is designed to accommodate the electronics monitoring, protection, and printed wiring assembly boards (PWAs), as well as to allow airflow through the module. A plurality of modules may easily be connected together to form a battery pack. The parts of the module are designed to facilitate their manufacture and assembly.

Oweis, Salah (Ellicott City, MD); D' Ussel, Louis (Bordeaux, FR); Chagnon, Guy (Cockeysville, MD); Zuhowski, Michael (Annapolis, MD); Sack, Tim (Cockeysville, MD); Laucournet, Gaullume (Paris, FR); Jackson, Edward J. (Taneytown, MD)

2002-06-04T23:59:59.000Z

312

Heterogeneous Correlation Modeling Based on the Wavelet Diagonal Assumption and on the Diffusion Operator  

Science Conference Proceedings (OSTI)

This article discusses several models for background error correlation matrices using the wavelet diagonal assumption and the diffusion operator. The most general properties of filtering local correlation functions, with wavelet formulations, are ...

Olivier Pannekoucke

2009-09-01T23:59:59.000Z

313

Microwave Properties of Ice-Phase Hydrometeors for Radar and Radiometers: Sensitivity to Model Assumptions  

Science Conference Proceedings (OSTI)

A simplified framework is presented for assessing the qualitative sensitivities of computed microwave properties, satellite brightness temperatures, and radar reflectivities to assumptions concerning the physical properties of ice-phase ...

Benjamin T. Johnson; Grant W. Petty; Gail Skofronick-Jackson

2012-12-01T23:59:59.000Z

314

NGNP: High Temperature Gas-Cooled Reactor Key Definitions, Plant Capabilities, and Assumptions  

SciTech Connect

This document provides key definitions, plant capabilities, and inputs and assumptions related to the Next Generation Nuclear Plant to be used in ongoing efforts related to the licensing and deployment of a high temperature gas-cooled reactor. These definitions, capabilities, and assumptions were extracted from a number of NGNP Project sources such as licensing related white papers, previously issued requirement documents, and preapplication interactions with the Nuclear Regulatory Commission (NRC).

Wayne Moe

2013-05-01T23:59:59.000Z

315

Fossil fuels -- future fuels  

Science Conference Proceedings (OSTI)

Fossil fuels -- coal, oil, and natural gas -- built America`s historic economic strength. Today, coal supplies more than 55% of the electricity, oil more than 97% of the transportation needs, and natural gas 24% of the primary energy used in the US. Even taking into account increased use of renewable fuels and vastly improved powerplant efficiencies, 90% of national energy needs will still be met by fossil fuels in 2020. If advanced technologies that boost efficiency and environmental performance can be successfully developed and deployed, the US can continue to depend upon its rich resources of fossil fuels.

NONE

1998-03-01T23:59:59.000Z

316

Module Handbook Specialisation Photovoltaics  

E-Print Network (OSTI)

#12;Specialisation Photovoltaics, University of Northumbria Module 1/Photovoltaics: PHOTOVOLTAIC CELL AND MODULE TECHNOLOGY Module name: PHOTOVOLTAIC CELL AND MODULE TECHNOLOGY Section EUREC · Chemistry · Physics Target learning outcomes The module Photovoltaic Cell and Module Technology teaches

Habel, Annegret

317

Alternative Fuels Data Center: Alternative Fuel and Fueling Infrastructure  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuel and Fuel and Fueling Infrastructure Incentives to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel and Fueling Infrastructure Incentives on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel and Fueling Infrastructure Incentives on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel and Fueling Infrastructure Incentives on Google Bookmark Alternative Fuels Data Center: Alternative Fuel and Fueling Infrastructure Incentives on Delicious Rank Alternative Fuels Data Center: Alternative Fuel and Fueling Infrastructure Incentives on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel and Fueling Infrastructure Incentives on AddThis.com... More in this section... Federal State Advanced Search

318

Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuel Fuel Vehicle (AFV) and Fueling Infrastructure Loans to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Loans on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Loans on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Loans on Google Bookmark Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Loans on Delicious Rank Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Loans on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Loans on AddThis.com...

319

Hardware Materials in Carbonate Fuel Cell - Programmaster.org  

Science Conference Proceedings (OSTI)

Metallic materials are extensively utilized in fuel-cell module hardware (current ... A Study on the Hot Corrosion Resistance of Metal-cemet-glass Coating on...

320

On-farm use of biomass fuels: market penetration potential during normal and fuel-emergency conditions  

Science Conference Proceedings (OSTI)

The potential for biomass fuels produced in decentralized facilities to replace the centrally produced fuels currently used in agriculture is examined. Two issues are examined. Will biomass fuels become cost-competitive relative to central fuels. And, what is the potential for biomass fuels to replace central fuels during emergency conditions when central fuels are unavailable. To answer these questions, descriptions of a range of currently available biomass technologies have been prepared and estimates made of current and projected agricultural fuel needs and biomass-feedstock availabilities. A variety of assumptions about future conditions have been adopted, the most important of which is that central fuel prices escalate at 7.5% annually relative to the commodities and inputs used to produce biomass fuel products. Under these assumptions, a number of biomass fuels will become cost-competitive during the 1980s, but most will do so late in the decade. Moreover, once these fuels become cost-competitive, penetration will occur gradually. Market forces thus will not markedly reduce the vulnerability of agriculture to energy-supply interruptions during this period. Biomass fuels could, however, play an important role during a fuel emergency. Estimates indicate they could replace up to about 60% of annual agricultural-sector fuel consumption by 1990, during the course of a fuel emergency of one year's duration.

Bjornstad, D.J.; Hillsman, E.L.; Tepel, R.C.; Mills, J.B.; CHester, C.V.; Klepper, O.H.; Borkowski, R.J.; Nichols, J.; Rainey, J.A.

1982-12-01T23:59:59.000Z

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


321

Alternative Fuels Data Center: Alternative Fuel Use and Alternative Fuel  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuel Use Fuel Use and Alternative Fuel Vehicle (AFV) Acquisition Requirements to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel Use and Alternative Fuel Vehicle (AFV) Acquisition Requirements on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel Use and Alternative Fuel Vehicle (AFV) Acquisition Requirements on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel Use and Alternative Fuel Vehicle (AFV) Acquisition Requirements on Google Bookmark Alternative Fuels Data Center: Alternative Fuel Use and Alternative Fuel Vehicle (AFV) Acquisition Requirements on Delicious Rank Alternative Fuels Data Center: Alternative Fuel Use and Alternative Fuel Vehicle (AFV) Acquisition Requirements on Digg Find More places to share Alternative Fuels Data Center: Alternative

322

Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuel Fuel Vehicle (AFV) and Fueling Infrastructure Grants and Loans to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Grants and Loans on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Grants and Loans on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Grants and Loans on Google Bookmark Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Grants and Loans on Delicious Rank Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Grants and Loans on Digg Find More places to share Alternative Fuels Data Center: Alternative

323

On the use of the parabolic concentration profile assumption for a rotary desiccant dehumidifier  

SciTech Connect

The current work describes a model for a desiccant dehumidifier which uses a parabolic concentration profile assumption to model the diffusion resistance inside the desiccant particle. The relative merits of the parabolic concentration profile model compared with widely utilized rotary desiccant wheel models are discussed. The periodic steady-state parabolic concentration profile model developed is efficient and can accommodate a variety of materials. These features make it an excellent tool for design studies requiring repetitive desiccant wheel simulations. A quartic concentration profile assumption was also investigated which yielded a 2.8 percent average improvement in prediction error over the parabolic model.

Chant, E.E. [Univ. of Turabo, Gurabo (Puerto Rico); Jeter, S.M. [Georgia Inst. of Technology, Atlanta, GA (United States). George W. Woodruff School of Mechanical Engineering

1995-02-01T23:59:59.000Z

324

Sensitivity of Rooftop PV Projections in the SunShot Vision Study to Market Assumptions  

Science Conference Proceedings (OSTI)

The SunShot Vision Study explored the potential growth of solar markets if solar prices decreased by about 75% from 2010 to 2020. The SolarDS model was used to simulate rooftop PV demand for this study, based on several PV market assumptions--future electricity rates, customer access to financing, and others--in addition to the SunShot PV price projections. This paper finds that modeled PV demand is highly sensitive to several non-price market assumptions, particularly PV financing parameters.

Drury, E.; Denholm, P.; Margolis, R.

2013-01-01T23:59:59.000Z

325

Fuel Cell Technologies Office: Fuel Cells  

NLE Websites -- All DOE Office Websites (Extended Search)

Cells Search Search Help Fuel Cells EERE Fuel Cell Technologies Office Fuel Cells Printable Version Share this resource Send a link to Fuel Cell Technologies Office: Fuel...

326

Fuel cell system  

DOE Patents (OSTI)

A fuel cell system is comprised of a fuel cell module including sub-stacks of series-connected fuel cells, the sub-stacks being held together in a stacked arrangement with cold plates of a cooling means located between the sub-stacks to function as electrical terminals. The anode and cathode terminals of the sub-stacks are connected in parallel by means of the coolant manifolds which electrically connect selected cold plates. The system may comprise a plurality of the fuel cell modules connected in series. The sub-stacks are designed to provide a voltage output equivalent to the desired voltage demand of a low voltage, high current DC load such as an electrolytic cell to be driven by the fuel cell system. This arrangement in conjunction with switching means can be used to drive a DC electrical load with a total voltage output selected to match that of the load being driven. This arrangement eliminates the need for expensive voltage regulation equipment.

Early, Jack (Perth Amboy, NJ); Kaufman, Arthur (West Orange, NJ); Stawsky, Alfred (Teaneck, NJ)

1982-01-01T23:59:59.000Z

327

The Role Of Modeling Assumptions And Policy Instruments in Evaluating The Global Implications Of U.S. Biofuel Policies  

Science Conference Proceedings (OSTI)

The primary objective of current U.S. biofuel law the Energy Independence and Security Act of 2007 (EISA) is to reduce dependence on imported oil, but the law also requires biofuels to meet carbon emission reduction thresholds relative to petroleum fuels. EISA created a renewable fuel standard with annual targets for U.S. biofuel use that climb gradually from 9 billion gallons per year in 2008 to 36 billion gallons (or about 136 billion liters) of biofuels per year by 2022. The most controversial aspects of the biofuel policy have centered on the global social and environmental implications of its potential land use effects. In particular, there is an ongoing debate about whether indirect land use change (ILUC) make biofuels a net source, rather sink, of carbon emissions. However, estimates of ILUC induced by biofuel production and use can only be inferred through modeling. This paper evaluates how model structure, underlying assumptions, and the representation of policy instruments influence the results of U.S. biofuel policy simulations. The analysis shows that differences in these factors can lead to divergent model estimates of land use and economic effects. Estimates of the net conversion of forests and grasslands induced by U.S. biofuel policy range from 0.09 ha/1000 gallons described in this paper to 0.73 ha/1000 gallons from early studies in the ILUC change debate. We note that several important factors governing LUC change remain to be examined. Challenges that must be addressed to improve global land use change modeling are highlighted.

Oladosu, Gbadebo A [ORNL; Kline, Keith L [ORNL

2010-01-01T23:59:59.000Z

328

Biennial Assessment of the Fifth Power Plan Gas Turbine Power Plant Planning Assumptions  

E-Print Network (OSTI)

Biennial Assessment of the Fifth Power Plan Gas Turbine Power Plant Planning Assumptions October 17, 2006 Simple- and combined-cycle gas turbine power plants fuelled by natural gas are among the bulk-emission and efficient gas turbine technology made combined-cycle gas turbine power plants the "resource of choice

329

External review of the thermal energy storage (TES) cogeneration study assumptions. Final report  

DOE Green Energy (OSTI)

This report is to provide a detailed review of the basic assumptions made in the design, sizing, performance, and economic models used in the thermal energy storage (TES)/cogeneration feasibility studies conducted by Pacific Northwest Laboratory (PNL) staff. This report is the deliverable required under the contract.

Lai, B.Y.; Poirier, R.N. [Chicago Bridge and Iron Technical Services Co., Plainfield, IL (United States)

1996-08-01T23:59:59.000Z

330

New EPA Fuel Economy and Environment Label - Gasoline Vehicles  

NLE Websites -- All DOE Office Websites (Extended Search)

Gasoline Vehicles Gasoline Vehicles Gasoline Vehicles Fuel Economy In addition to the MPG estimates displayed on previous labels, combined city/highway fuel use is also given in terms of gallons per 100 miles. New! Fuel Economy & Greenhouse Gas Rating Use this scale to compare vehicles based on tailpipe greenhouse gas emissions, which contribute to climate change. New! Smog Rating You can now compare vehicles based on tailpipe emissions of smog-forming air pollutants. New! Five-Year Fuel Savings This compares the five-year fuel cost of the vehicle to that of an average gasoline vehicle. The assumptions used to calculate these costs are listed at the bottom of the label. Annual Fuel Cost This cost is based on the combined city/highway MPG estimate and assumptions about driving and fuel prices listed at the bottom of the

331

Fuel pin  

DOE Patents (OSTI)

A fuel pin for a liquid metal nuclear reactor is provided. The fuel pin includes a generally cylindrical cladding member with metallic fuel material disposed therein. At least a portion of the fuel material extends radially outwardly to the inner diameter of the cladding member to promote efficient transfer of heat to the reactor coolant system. The fuel material defines at least one void space therein to facilitate swelling of the fuel material during fission.

Christiansen, D.W.; Karnesky, R.A.; Leggett, R.D.; Baker, R.B.

1987-11-24T23:59:59.000Z

332

Assessment of Gasification-Based Biorefining at Kraft Pulp and Paper Mills in the United States, Part A: Background and Assumptions  

Science Conference Proceedings (OSTI)

Commercialization of black liquor and biomass gasification technologies is anticipated in the 2010-2015 time frame, and synthesis gas from gasifiers can be converted into liquid fuels using catalytic synthesis technologies that are already commercially established in the gas-to-liquids or coal-to-liquids industries. This set of two papers describes key results from a major assessment of the prospective energy, environmental, and financial performance of commercial gasification-based biorefineries integrated with kraft pulp and paper mills [1]. Seven detailed biorefinery designs were developed for a reference mill in the southeastern United States, together with the associated mass/energy balances, air emissions estimates, and capital investment requirements. The biorefineries provide chemical recovery services and co-produce process steam for the mill, some electricity, and one of three liquid fuels: a Fischer-Tropsch synthetic crude oil (which could be refined to vehicle fuels at an existing petroleum refinery), dimethyl ether (a diesel engine fuel or propane substitute), or an ethanol-rich mixed-alcohol product. This paper describes the key assumptions that underlie the biorefinery designs. Part B will present analytical results.

Larson, E. D.; Consonni, S.; Katofsky, R. E.; Iisa, K.; Frederick, W. J., Jr.

2008-11-01T23:59:59.000Z

333

Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

and Fueling Infrastructure Funding and Technical Assistance and Fueling Infrastructure Funding and Technical Assistance to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Funding and Technical Assistance on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Funding and Technical Assistance on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Funding and Technical Assistance on Google Bookmark Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Funding and Technical Assistance on Delicious Rank Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Funding and Technical Assistance on Digg

334

Thermionic modules  

DOE Patents (OSTI)

Modules of assembled microminiature thermionic converters (MTCs) having high energy-conversion efficiencies and variable operating temperatures manufactured using MEMS manufacturing techniques including chemical vapor deposition. The MTCs incorporate cathode to anode spacing of about 1 micron or less and use cathode and anode materials having work functions ranging from about 1 eV to about 3 eV. The MTCs also exhibit maximum efficiencies of just under 30%, and thousands of the devices and modules can be fabricated at modest costs.

King, Donald B. (Albuquerque, NM); Sadwick, Laurence P. (Salt Lake City, UT); Wernsman, Bernard R. (Clairton, PA)

2002-06-18T23:59:59.000Z

335

Fuel cells for the '90s  

SciTech Connect

Nontraditional power plants may be needed to help utilities meet the need for additional generating capacity in the late 1980s. Fuel cell power plants can be built in small factory-assembled modules and installed in just 2 or 3 years. Because the fuel cell converts fuel-oil, gas, even coal distillates and other synthetic fuels-directly to electricity without combustion, it has almost no sulfur and nitrogen oxide emissions. With no harmful emissions, fuel cells can be sited in populated areas. And because there is no combustion cycle to waste much of the fuel's energy, fuel cells have potentially higher efficiencies than thermal power plants. As a result of 12 years of intensive development by EPRI, DOE, utilities, manufacturers, and a fuel cell users group, the fuel cell technology will be ready when it is needed.

Lihach, N.; Fickett, A.; Gillis, E.

1984-09-01T23:59:59.000Z

336

New concept for coal wettability evaluation and modulation. Technical progress report, April 1, 1993--June 30, 1993  

SciTech Connect

This project is concerned with the new concept for coal surface wettability evaluation and modulation. The objective of the work is to study the fundamental surface chemistry features about the evaluation of the surface wettability of coal and pyrite and establish a new separation strategy which could contribute to the advanced coal-cleaning for premium fuel application. In the past quarter report, the capillary rise test results of three coal and mineral pyrite samples in distilled water, kerosene, and salt solution indicated that there are good agreements between the experimental observations and theoretical assumption. In this quarter, the further capillary rise tests were conducted for coal, pyrite and coal pyrite in distilled water, kerosene and benzene. The test results shown that surface wettability of coal, mineral pyrite, and coal pyrite have good correlation with the theoretical predictions.

Hu, W.

1993-09-01T23:59:59.000Z

337

Fuels Technology - Capabilities - FEERC  

NLE Websites -- All DOE Office Websites (Extended Search)

Research Capabilities Fuels Technology Advanced petroleum-based fuels Fuel-borne reductants On-board reforming Alternative fuels...

338

Alternative Fuels Data Center: Alternative Fuel and Special Fuel  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuel and Fuel and Special Fuel Definitions to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel and Special Fuel Definitions on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel and Special Fuel Definitions on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel and Special Fuel Definitions on Google Bookmark Alternative Fuels Data Center: Alternative Fuel and Special Fuel Definitions on Delicious Rank Alternative Fuels Data Center: Alternative Fuel and Special Fuel Definitions on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel and Special Fuel Definitions on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuel and Special Fuel Definitions

339

Alternative Fuels Data Center: Alternative Fuel Motor Carrier Fuel Tax  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuel Motor Fuel Motor Carrier Fuel Tax to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel Motor Carrier Fuel Tax on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel Motor Carrier Fuel Tax on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel Motor Carrier Fuel Tax on Google Bookmark Alternative Fuels Data Center: Alternative Fuel Motor Carrier Fuel Tax on Delicious Rank Alternative Fuels Data Center: Alternative Fuel Motor Carrier Fuel Tax on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel Motor Carrier Fuel Tax on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuel Motor Carrier Fuel Tax Effective January 1, 2014, a person who operates a commercial motor vehicle

340

Paducah DUF6 Conversion Final EIS - Chapter 4: Environmental Impact Assessment Approach, Assumptions, and Methodology  

NLE Websites -- All DOE Office Websites (Extended Search)

Paducah DUF Paducah DUF 6 Conversion Final EIS 4 ENVIRONMENTAL IMPACT ASSESSMENT APPROACH, ASSUMPTIONS, AND METHODOLOGY This EIS evaluates potential impacts on human health and the natural environment from building and operating a DUF 6 conversion facility at three alternative locations at the Paducah site and for a no action alternative. These impacts might be positive, in that they would improve conditions in the human or natural environment, or negative, in that they would cause a decline in those conditions. This chapter provides an overview of the methods used to estimate the potential impacts associated with the EIS alternatives, summarizes the major assumptions that formed the basis of the evaluation, and provides some background information on human health

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


341

NGNP: High Temperature Gas-Cooled Reactor Key Definitions, Plant Capabilities, and Assumptions  

SciTech Connect

This document is intended to provide a Next Generation Nuclear Plant (NGNP) Project tool in which to collect and identify key definitions, plant capabilities, and inputs and assumptions to be used in ongoing efforts related to the licensing and deployment of a high temperature gas-cooled reactor (HTGR). These definitions, capabilities, and assumptions are extracted from a number of sources, including NGNP Project documents such as licensing related white papers [References 1-11] and previously issued requirement documents [References 13-15]. Also included is information agreed upon by the NGNP Regulatory Affairs group's Licensing Working Group and Configuration Council. The NGNP Project approach to licensing an HTGR plant via a combined license (COL) is defined within the referenced white papers and reference [12], and is not duplicated here.

Phillip Mills

2012-02-01T23:59:59.000Z

342

GRI baseline projection: Methodology and assumptions 1996 edition. Topical report, January-December 1995  

Science Conference Proceedings (OSTI)

The report documents the methodology employed in producing the 1996 Edition of the GRI Baseline Projection. DRI/McGraw-Hill`s Energy Group (DRI) maintains an energy modeling system for the Gas Research Institute (GRI) that is used to produce an annual projection of the supply and demand for energy by regions in the United States. The 1996 Edition of the GRI Baseline Projection is produced using several different models. The models analyze various pieces of the U.S. energy markets and their solutions are based on a framework of exogenous assumptions provided by GRI. The report describes the integration and solution procedures of the models and the assumptions used to produce the final projection results.

Rhodes, M.R.; Baxter, R.P.; Nottingham, R.P.

1996-04-01T23:59:59.000Z

343

GRI baseline projection: Methodology and assumptions 1995 edition. Topical report, January-December 1994  

SciTech Connect

The report documents the methodology employed in producing the 1995 Edition of the GRI Baseline Projection. DRI/McGraw-Hill`s Energy Group (DRI) maintains an energy modeling system for the Gas Research Institute (GRI) that is used to produce an annual projection of the supply and demand for energy by regions in the United States. The 1995 Edition of the GRI Baseline Projection is produced using several different models. The models analyze various pieces of the U.S. energy markets and their solutions are based on a framework of exogeneous assumptions provided by GRI. The report describes the integration and solution procedures of the models and the assumptions used to produce the final projection results.

Baxter, R.P.; Silveira, T.S.; Harshbarger, S.L.

1995-02-01T23:59:59.000Z

344

Alternative Fuels Data Center: Alternative Fuel Promotion  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Alternative Fuel Alternative Fuel Promotion to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel Promotion on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel Promotion on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel Promotion on Google Bookmark Alternative Fuels Data Center: Alternative Fuel Promotion on Delicious Rank Alternative Fuels Data Center: Alternative Fuel Promotion on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel Promotion on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuel Promotion The Missouri Alternative Fuels Commission (Commission) promotes the continued production and use of alternative transportation fuels in

345

Alternative Fuels Data Center: Alternative Fuel Definition  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuel Fuel Definition to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel Definition on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel Definition on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel Definition on Google Bookmark Alternative Fuels Data Center: Alternative Fuel Definition on Delicious Rank Alternative Fuels Data Center: Alternative Fuel Definition on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel Definition on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuel Definition The definition of an alternative fuel includes natural gas, liquefied petroleum gas, electricity, hydrogen, fuel mixtures containing not less

346

Alternative Fuels Data Center: Ethanol Fueling Stations  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fueling Fueling Stations to someone by E-mail Share Alternative Fuels Data Center: Ethanol Fueling Stations on Facebook Tweet about Alternative Fuels Data Center: Ethanol Fueling Stations on Twitter Bookmark Alternative Fuels Data Center: Ethanol Fueling Stations on Google Bookmark Alternative Fuels Data Center: Ethanol Fueling Stations on Delicious Rank Alternative Fuels Data Center: Ethanol Fueling Stations on Digg Find More places to share Alternative Fuels Data Center: Ethanol Fueling Stations on AddThis.com... More in this section... Ethanol Basics Benefits & Considerations Stations Locations Infrastructure Development Vehicles Laws & Incentives Ethanol Fueling Stations Photo of an ethanol fueling station. Thousands of ethanol fueling stations are available in the United States.

347

Alternative Fuels Data Center: Hydrogen Fueling Stations  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fueling Fueling Stations to someone by E-mail Share Alternative Fuels Data Center: Hydrogen Fueling Stations on Facebook Tweet about Alternative Fuels Data Center: Hydrogen Fueling Stations on Twitter Bookmark Alternative Fuels Data Center: Hydrogen Fueling Stations on Google Bookmark Alternative Fuels Data Center: Hydrogen Fueling Stations on Delicious Rank Alternative Fuels Data Center: Hydrogen Fueling Stations on Digg Find More places to share Alternative Fuels Data Center: Hydrogen Fueling Stations on AddThis.com... More in this section... Hydrogen Basics Benefits & Considerations Stations Locations Infrastructure Development Vehicles Laws & Incentives Hydrogen Fueling Stations Photo of a hydrogen fueling station. A handful of hydrogen fueling stations are available in the United States

348

Alternative Fuels Data Center: Biodiesel Fueling Stations  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fueling Fueling Stations to someone by E-mail Share Alternative Fuels Data Center: Biodiesel Fueling Stations on Facebook Tweet about Alternative Fuels Data Center: Biodiesel Fueling Stations on Twitter Bookmark Alternative Fuels Data Center: Biodiesel Fueling Stations on Google Bookmark Alternative Fuels Data Center: Biodiesel Fueling Stations on Delicious Rank Alternative Fuels Data Center: Biodiesel Fueling Stations on Digg Find More places to share Alternative Fuels Data Center: Biodiesel Fueling Stations on AddThis.com... More in this section... Biodiesel Basics Benefits & Considerations Stations Locations Infrastructure Development Vehicles Laws & Incentives Biodiesel Fueling Stations Photo of a biodiesel fueling station. Hundreds of biodiesel fueling stations are available in the United States.

349

An advanced fuel cell simulator  

E-Print Network (OSTI)

Fuel cell power generation systems provide a clean alternative to the conventional fossil fuel based systems. Fuel cell systems have a high e?ciency and use easily available hydrocarbons like methane. Moreover, since the by-product is water, they have a very low environmental impact. The fuel cell system consists of several subsystems requiring a lot of e?ort from engineers in diverse areas. Fuel cell simulators can provide a convenient and economic alternative for testing the electrical subsystems such as converters and inverters. This thesis proposes a low-cost and an easy-to-use fuel cell simulator using a programmable DC supply along with a control module written in LabVIEW. This simulator reproduces the electrical characteristics of a 5kW solid oxide fuel cell (SOFC) stack under various operating conditions. The experimental results indicate that the proposed simulator closely matches the voltage-current characteristic of the SOFC system under varying load conditions. E?ects of non-electrical parameters like hydrogen ?ow rate are also modeled and these parameters are taken as dynamic inputs from the user. The simulator is customizable through a graphical user interface and allows the user to model other types of fuel cells with the respective voltage-current data. The simulator provides an inexpensive and accurate representation of a solid oxide fuel cell under steady state and transient conditions and can replace an actual fuel cell during testing of power conditioning equipment.

Acharya, Prabha Ramchandra

2004-08-01T23:59:59.000Z

350

Assumptions to the Annual Energy Outlook 2000-Table 2. Carbon Emission  

Gasoline and Diesel Fuel Update (EIA)

Carbon Emission Factors Carbon Emission Factors (Kilograms-carbon per million Btu) Fuel Type Carbon Coefficient at Full Combustion Combustion Fraction Adjusted Emissions Factor Petroleum Motor Gasoline 19.33 0.990 19.14 Liquefied Petroleum Gas Used as Fuel 17.20 0.995 17.11 Used as Feedstock 16.87 0.200 3.37 Jet Fuel 19.33 0.990 19.14 Distillate Fuel 19.95 0.990 19.75 Residual Fuel 21.49 0.990 21.28 Asphalt and Road Oil 20.62 0.000 0.00 Lubricants 20.24 0.600 12.14 Petrochemical Feedstocks 19.37 0.200 3.87 Kerosene 19.72 0.990 19.52 Petroleum Coke 27.85 0.500 13.93 Petroleum Still Gas 17.51 0.995 17.42 Other Industrial 20.31 0.990 20.11 Coal Residential and Commercial 25.92 0.990 25.66 Metallurgical 25.55 0.990 25.29 Industrial Other 25.61 0.990 25.39 Electric Utility1 25.74 0.990 24.486 Natural Gas Used as Fuel

351

Fuel cell system with coolant flow reversal  

DOE Patents (OSTI)

Method and apparatus for cooling electrochemical fuel cell system components. Periodic reversal of the direction of flow of cooling fluid through a fuel cell stack provides greater uniformity and cell operational temperatures. Flow direction through a recirculating coolant fluid circuit is reversed through a two position valve, without requiring modulation of the pumping component.

Kothmann, Richard E. (Pittsburgh, PA)

1986-01-01T23:59:59.000Z

352

Residential Sector End-Use Forecasting with EPRI-REEPS 2.1: Summary Input Assumptions and Results  

E-Print Network (OSTI)

G. Koomey. 1994. Residential Appliance Data, Assumptions andunits) Table A 3 : Number of Appliances in Existing Homes (sector, including appliances and heating, ventilation, and

Koomey, Jonathan G.

2010-01-01T23:59:59.000Z

353

Fuel Cell Technologies Office: Fuel Cells  

Office of Energy Efficiency and Renewable Energy (EERE) Indexed Site

Efficiency and Renewable Energy EERE Home | Programs & Offices | Consumer Information Fuel Cells Search Search Help Fuel Cells EERE Fuel Cell Technologies Office Fuel Cells...

354

Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Alternative Fuel Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Loans to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Loans on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Loans on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Loans on Google Bookmark Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Loans on Delicious Rank Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Loans on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Loans on AddThis.com...

355

Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Alternative Fuel Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Grants to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Grants on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Grants on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Grants on Google Bookmark Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Grants on Delicious Rank Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Grants on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Grants on AddThis.com...

356

Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Alternative Fuel Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Tax Credit to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Tax Credit on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Tax Credit on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Tax Credit on Google Bookmark Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Tax Credit on Delicious Rank Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Tax Credit on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Tax Credit on AddThis.com...

357

Alternative Fuels Data Center: Alternative Fuel and Alternative Fuel  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Alternative Fuel and Alternative Fuel and Alternative Fuel Vehicle (AFV) Fund to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel and Alternative Fuel Vehicle (AFV) Fund on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel and Alternative Fuel Vehicle (AFV) Fund on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel and Alternative Fuel Vehicle (AFV) Fund on Google Bookmark Alternative Fuels Data Center: Alternative Fuel and Alternative Fuel Vehicle (AFV) Fund on Delicious Rank Alternative Fuels Data Center: Alternative Fuel and Alternative Fuel Vehicle (AFV) Fund on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel and Alternative Fuel Vehicle (AFV) Fund on AddThis.com... More in this section...

358

Alternative Fuels Data Center: Alternative Fuel and Alternative Fuel  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuel and Fuel and Alternative Fuel Vehicle (AFV) Tax Exemption to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel and Alternative Fuel Vehicle (AFV) Tax Exemption on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel and Alternative Fuel Vehicle (AFV) Tax Exemption on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel and Alternative Fuel Vehicle (AFV) Tax Exemption on Google Bookmark Alternative Fuels Data Center: Alternative Fuel and Alternative Fuel Vehicle (AFV) Tax Exemption on Delicious Rank Alternative Fuels Data Center: Alternative Fuel and Alternative Fuel Vehicle (AFV) Tax Exemption on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel and Alternative Fuel Vehicle (AFV) Tax Exemption on AddThis.com...

359

Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

Central Air, Fuels = Oil and Gas, Other = LPG and Misc. (3)Central Air, Fuels = Oil and Gas, LPG and Misc. (3) Sources:Central Air, Fuels = Oil and Gas, Other = LPG and Misc. (3)

Johnson, F.X.

2010-01-01T23:59:59.000Z

360

Petroleum Market Module  

Gasoline and Diesel Fuel Update (EIA)

other refinery inputs including alcohols, ethers, bioesters, other refinery inputs including alcohols, ethers, bioesters, natural gas plant liquids production, and refinery processing gain. In addition, the PMM estimates capacity expansion and fuel consumption of domestic refineries. The PMM contains a linear programming representation of U.S. refining activities in the five Petroleum Area Defense Districts (PADDs) (Figure 9). The model is created by aggregating individual refineries into one linear programmming representation for each PADD. This representation provides the marginal costs of production for a number of conventional and new petroleum products. In order to interact with other NEMS modules with different regional representations, certain PMM inputs and outputs are converted from PADD regions to other regional structures and vice versa. The linear programming results are used to determine

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


361

Photovoltaic module and module arrays  

DOE Patents (OSTI)

A photovoltaic (PV) module including a PV device and a frame. The PV device has a PV laminate defining a perimeter and a major plane. The frame is assembled to and encases the laminate perimeter, and includes leading, trailing, and side frame members, and an arm that forms a support face opposite the laminate. The support face is adapted for placement against a horizontal installation surface, to support and orient the laminate in a non-parallel or tilted arrangement. Upon final assembly, the laminate and the frame combine to define a unitary structure. The frame can orient the laminate at an angle in the range of 3.degree.-7.degree. from horizontal, and can be entirely formed of a polymeric material. Optionally, the arm incorporates integral feature(s) that facilitate interconnection with corresponding features of a second, identically formed PV module.

Botkin, Jonathan (El Cerrito, CA); Graves, Simon (Berkeley, CA); Lenox, Carl J. S. (Oakland, CA); Culligan, Matthew (Berkeley, CA); Danning, Matt (Oakland, CA)

2012-07-17T23:59:59.000Z

362

Assumptions to the Annual Energy Outlook 2001 - Table 2. Carbon Dioxide  

Gasoline and Diesel Fuel Update (EIA)

Carbon Dioxide Emission Factors Carbon Dioxide Emission Factors (Kilograms-carbon equivalent per million Btu) Fuel Type Carbon Dioxide Coefficient at Full Combustion Combustion Fraction Adjusted Emissions Factor Petroleum Motor Gasoline 19.36 0.990 19.17 Liquefied Petroleum Gas Used as Fuel 17.18 0.995 17.09 Used as Feedstock 16.88 0.200 3.38 Jet Fuel 19.33 0.990 19.14 Distillate Fuel 19.95 0.990 19.75 Residual Fuel 21.49 0.990 21.28 Asphalt and Road Oil 20.62 0.000 0.00 Lubricants 20.24 0.600 12.14 Petrochemical Feedstocks 19.37 0.200 3.87 Kerosene 19.72 0.990 19.52 Petroleum Coke 27.85 0.500 13.93 Petroleum Still Gas 17.51 0.995 17.42 Other Industrial 20.31 0.990 20.11 Coal Residential and Commercial 26.00 0.990 25.74 Metallurgical 25.56 0.990 25.30 Industrial Other 25.63 0.990 25.38 Electric Utility1 25.76 0.990 25.50 Natural Gas

363

Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fueling Infrastructure Grants to someone by E-mail Fueling Infrastructure Grants to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Grants on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Grants on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Grants on Google Bookmark Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Grants on Delicious Rank Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Grants on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) and Fueling Infrastructure Grants on AddThis.com...

364

Bases, Assumptions, and Results of the Flowsheet Calculations for the Decision Phase Salt Disposition Alternatives  

SciTech Connect

The High Level Waste (HLW) Salt Disposition Systems Engineering Team was formed on March 13, 1998, and chartered to identify options, evaluate alternatives, and recommend a selected alternative(s) for processing HLW salt to a permitted wasteform. This requirement arises because the existing In-Tank Precipitation process at the Savannah River Site, as currently configured, cannot simultaneously meet the HLW production and Authorization Basis safety requirements. This engineering study was performed in four phases. This document provides the technical bases, assumptions, and results of this engineering study.

Dimenna, R.A.; Jacobs, R.A.; Taylor, G.A.; Durate, O.E.; Paul, P.K.; Elder, H.H.; Pike, J.A.; Fowler, J.R.; Rutland, P.L.; Gregory, M.V.; Smith III, F.G.; Hang, T.; Subosits, S.G.; Campbell, S.G.

2001-03-26T23:59:59.000Z

365

Science with the Square Kilometer Array: Motivation, Key Science Projects, Standards and Assumptions  

E-Print Network (OSTI)

The Square Kilometer Array (SKA) represents the next major, and natural, step in radio astronomical facilities, providing two orders of magnitude increase in collecting area over existing telescopes. In a series of meetings, starting in Groningen, the Netherlands (August 2002) and culminating in a `science retreat' in Leiden (November 2003), the SKA International Science Advisory Committee (ISAC), conceived of, and carried-out, a complete revision of the SKA science case (to appear in New Astronomy Reviews). This preface includes: (i) general introductory material, (ii) summaries of the key science programs, and (iii) a detailed listing of standards and assumptions used in the revised science case.

C. Carilli; S. Rawlings

2004-09-12T23:59:59.000Z

366

Hydrogen Fuel  

NLE Websites -- All DOE Office Websites (Extended Search)

explored as a fuel for passenger vehicles. It can be used in fuel cells to power electric motors or burned in internal combustion engines (ICEs). It is an environmentally...

367

International Stationary Fuel Cell Demonstration  

NLE Websites -- All DOE Office Websites (Extended Search)

STATIONARY FUEL CELL DEMONSTRATION STATIONARY FUEL CELL DEMONSTRATION John Vogel, Plug Power Inc. Yu-Min Tsou, PEMEAS E-TEK 14 February, 2007 Clean, Reliable On-site Energy SAFE HARBOR STATEMENT This presentation contains forward-looking statements, including statements regarding the company's future plans and expectations regarding the development and commercialization of fuel cell technology. All forward-looking statements are subject to risks, uncertainties and assumptions that could cause actual results to differ materially from those projected. The forward-looking statements speak only as of the date of this presentation. The company expressly disclaims any obligation or undertaking to release publicly any updates or revisions to any such statements to reflect any change in the company's expectations or any change in

368

Residential Appliance Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

LBL-34046 UC-350 Residential Appliance Data, Assumptions and Methodology for End-Use Forecasting. DE-AC03-76SF00098 #12;i ABSTRACT This report details the data, assumptions and methodology for end-use provided by the Appliance Model in the Residential End-Use Energy Planning System (REEPS), which

369

Model documentation coal market module of the National Energy Modeling System  

SciTech Connect

This report documents the approaches used in developing the Annual Energy Outlook 1995 (AEO95). This report catalogues and describes the assumptions, methodology, estimation techniques, and source code of the coal market module`s three submodules. These are the Coal Production Submodule (CPS), the Coal Export Submodule (CES), the Coal Expert Submodule (CES), and the Coal Distribution Submodule (CDS).

1995-03-01T23:59:59.000Z

370

Assumptions to the Annual Energy Outlook 2001 - Table 3. Coal-Related  

Gasoline and Diesel Fuel Update (EIA)

Coal-Related Methane Assumptions Coal-Related Methane Assumptions Northern Appalachia Central Appalachia Southern Appalachia Eastern Interior Western Fraction of underground coal production at: Gassy mines 0.885 0.368 0.971 0.876 0.681 Nongassy mines 0.115 0.632 0.029 0.124 0.319 Production from mines with degasification systems (fraction of underground production) 0.541 0.074 0.810 0.067 0.056 Emission factors (kilograms methane per short ton of coal produced) Underground Mining Gassy mines 6.047 5.641 27.346 2.988 6.027 Nongassy mines 0.362 0.076 15.959 0.285 0.245 Degassified mines 4.085 37.724 22.025 0.310 0.000 Surface Mining 0.706 0.706 0.706 0.706 0.706 Post-Mining, underground-mined 1.505 1.505 1.505 1.505 1.505 Post-Mining, surface-mined 0.061 0.061 0.061 0.061 0.061 Methane recovery at active coal mines

371

EFFECT OF FUEL IMPURITIES ON FUEL CELL PERFORMANCE AND DURABILITY  

DOE Green Energy (OSTI)

A fuel cell is an electrochemical energy conversion device that produces electricity during the combination of hydrogen and oxygen to produce water. Proton exchange membranes fuel cells are favored for portable applications as well as stationary ones due to their high power density, low operating temperature, and low corrosion of components. In real life operation, the use of pure fuel and oxidant gases results in an impractical system. A more realistic and cost efficient approach is the use of air as an oxidant gas and hydrogen from hydrogen carriers (i.e., ammonia, hydrocarbons, hydrides). However, trace impurities arising from different hydrogen sources and production increases the degradation of the fuel cell. These impurities include carbon monoxide, ammonia, sulfur, hydrocarbons, and halogen compounds. The International Organization for Standardization (ISO) has set maximum limits for trace impurities in the hydrogen stream; however fuel cell data is needed to validate the assumption that at those levels the impurities will cause no degradation. This report summarizes the effect of selected contaminants tested at SRNL at ISO levels. Runs at ISO proposed concentration levels show that model hydrocarbon compound such as tetrahydrofuran can cause serious degradation. However, the degradation is only temporary as when the impurity is removed from the hydrogen stream the performance completely recovers. Other molecules at the ISO concentration levels such as ammonia don't show effects on the fuel cell performance. On the other hand carbon monoxide and perchloroethylene shows major degradation and the system can only be recovered by following recovery procedures.

Colon-Mercado, H.

2010-09-28T23:59:59.000Z

372

Technical evaluation and assessment of CNG/LPG bi-fuel and flex-fuel vehicle viability  

DOE Green Energy (OSTI)

This report compares vehicles using compressed natural gas (CNG), liquefied petroleum gas (LPG), and combinations of the two in bi-fuel or flex-fuel configurations. Evidence shows that environmental and energy advantages can be gained by replacing two-fuel CNG/gasoline vehicles with two-fuel or flex-fuel systems to be economically competitive, it is necessary to develop a universal CNG/LPG pressure-regulator-injector and engine control module to switch from one tank to the other. For flex-fuel CNG/LPG designs, appropriate composition sensors, refueling pumps, fuel tanks, and vaporizers are necessary.

Sinor, J E [Sinor (J.E.) Consultants, Inc., Niwot, CO (United States)

1994-05-01T23:59:59.000Z

373

Alternative Fuels Data Center: Alternative Fueling Infrastructure  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Alternative Fueling Alternative Fueling Infrastructure Development to someone by E-mail Share Alternative Fuels Data Center: Alternative Fueling Infrastructure Development on Facebook Tweet about Alternative Fuels Data Center: Alternative Fueling Infrastructure Development on Twitter Bookmark Alternative Fuels Data Center: Alternative Fueling Infrastructure Development on Google Bookmark Alternative Fuels Data Center: Alternative Fueling Infrastructure Development on Delicious Rank Alternative Fuels Data Center: Alternative Fueling Infrastructure Development on Digg Find More places to share Alternative Fuels Data Center: Alternative Fueling Infrastructure Development on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type

374

Fuel Cell Technologies Office: Fuel Cell Animation  

NLE Websites -- All DOE Office Websites (Extended Search)

Fuel Cell Animation to someone by E-mail Share Fuel Cell Technologies Office: Fuel Cell Animation on Facebook Tweet about Fuel Cell Technologies Office: Fuel Cell Animation on...

375

Alternative Fuels Data Center: Emerging Fuels  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Emerging Fuels Emerging Fuels Printable Version Share this resource Send a link to Alternative Fuels Data Center: Emerging Fuels to someone by E-mail Share Alternative Fuels Data Center: Emerging Fuels on Facebook Tweet about Alternative Fuels Data Center: Emerging Fuels on Twitter Bookmark Alternative Fuels Data Center: Emerging Fuels on Google Bookmark Alternative Fuels Data Center: Emerging Fuels on Delicious Rank Alternative Fuels Data Center: Emerging Fuels on Digg Find More places to share Alternative Fuels Data Center: Emerging Fuels on AddThis.com... More in this section... Biobutanol Drop-In Biofuels Methanol P-Series Renewable Natural Gas xTL Fuels Emerging Alternative Fuels Several emerging alternative fuels are under development or already developed and may be available in the United States. These fuels may

376

Fuel Cells  

NLE Websites -- All DOE Office Websites (Extended Search)

Fuel Cells Fuel Cells Converting chemical energy of hydrogenated fuels into electricity Project Description Invented in 1839, fuels cells powered the Gemini and Apollo space missions, as well as the space shuttle. Although fuel cells have been successfully used in such applications, they have proven difficult to make more cost-effective and durable for commercial applications, particularly for the rigors of daily transportation. Since the 1970s, scientists at Los Alamos have managed to make various scientific breakthroughs that have contributed to the development of modern fuel cell systems. Specific efforts include the following: * Finding alternative and more cost-effective catalysts than platinum. * Enhancing the durability of fuel cells by developing advanced materials and

377

Journal of Power Sources 140 (2005) 331339 Numerical study of a flat-tube high power density solid oxide fuel cell  

E-Print Network (OSTI)

· Research and development in MCFC, SOFC, PEM and Fuels #12;FuelCell Energy, the FuelCell Energy logo, Direct Electrolyte Anode Cathode Electrolyte FCE SOFC Systems Background SOFC MW Module FCE utilizes VPS (Versa Power Systems) fuel cell technology in FCEs SOFC stack modules and systems. FCE/VPS team is engaged

378

Comparison of risk-dominant scenario assumptions for several TRU waste facilities in the DOE complex  

Science Conference Proceedings (OSTI)

In order to gain a risk management perspective, the DOE Rocky Flats Field Office (RFFO) initiated a survey of other DOE sites regarding risks from potential accidents associated with transuranic (TRU) storage and/or processing facilities. Recently-approved authorization basis documents at the Rocky Flats Environmental Technology Site (RFETS) have been based on the DOE Standard 3011 risk assessment methodology with three qualitative estimates of frequency of occurrence and quantitative estimates of radiological consequences to the collocated worker and the public binned into three severity levels. Risk Class 1 and 2 events after application of controls to prevent or mitigate the accident are designated as risk-dominant scenarios. Accident Evaluation Guidelines for selection of Technical Safety Requirements (TSRs) are based on the frequency and consequence bin assignments to identify controls that can be credited to reduce risk to Risk Class 3 or 4, or that are credited for Risk Class 1 and 2 scenarios that cannot be further reduced. This methodology resulted in several risk-dominant scenarios for either the collocated worker or the public that warranted consideration on whether additional controls should be implemented. RFFO requested the survey because of these high estimates of risks that are primarily due to design characteristics of RFETS TRU waste facilities (i.e., Butler-type buildings without a ventilation and filtration system, and a relatively short distance to the Site boundary). Accident analysis methodologies and key assumptions are being compared for the DOE sites responding to the survey. This includes type of accidents that are risk dominant (e.g., drum explosion, material handling breach, fires, natural phenomena, external events, etc.), source term evaluation (e.g., radionuclide material-at-risk, chemical and physical form, damage ratio, airborne release fraction, respirable fraction, leakpath factors), dispersion analysis (e.g., meteorological assumptions, distance to receptors, plume meander, deposition, and other factors affecting the calculated {chi}/Q), dose assessments (specific activities, inhalation dose conversion factors, breathing rates), designated frequency of occurrence, and risk assignment per the DOE Standard 3011 methodology. Information from the sites is being recorded on a spreadsheet to facilitate comparisons. The first response from Westinghouse Safety Management Solutions for the Savannah River Site (SRS) also provided a detailed analysis of the major differences in methods and assumptions between RFETS and SRS, which forms much of the basis for this paper. Other sites responding to the survey include the Idaho National Engineering and Environmental Laboratory (INEEL), Hanford, and the Los Alamos National Laboratory (LANL).

Foppe, T.L. [Foppe and Associates, Inc., Golden, CO (United States); Marx, D.R. [Westinghouse Safety Management Solutions, Inc., Aiken, SC (United States)

1999-06-01T23:59:59.000Z

379

Photovoltaic module energy rating procedure. Final subcontract report  

DOE Green Energy (OSTI)

This document describes testing and computation procedures used to generate a photovoltaic Module Energy Rating (MER). The MER consists of 10 estimates of the amount of energy a single module of a particular type (make and model) will produce in one day. Module energy values are calculated for each of five different sets of weather conditions (defined by location and date) and two load types. Because reproduction of these exact testing conditions in the field or laboratory is not feasible, limited testing and modeling procedures and assumptions are specified.

Whitaker, C.M.; Newmiller, J.D. [Endecon Engineering (United States)

1998-01-01T23:59:59.000Z

380

Assumptions to the Annual Energy Outlook 2000-Table 1. Summary of the  

Gasoline and Diesel Fuel Update (EIA)

0 Cases 0 Cases Case Name Description Integration mode Reference Baseline economic growth, world oil price, and technology assumptions Fully Integrated Low Economic Growth Gross Domestic product grows at an average annual rate of 1.7 percent, compared to the reference case growth of 2.2 percent. Fully Integrated High Economic Growth Gross domestic product grows at an average annual rate of 2.6 percent, compared to the reference case growth of 2.2 percent. Fully Integrated Low World Oil Price World oil prices are $14.90 per barrel in 2020, compared to $22.04 per barrel in the reference case. Fully Integrated High World Oil Price World oil prices are $28.04 per barrel in 2020, compared to $22.04 per barrel in the reference case. Fully Integrated Residential: 2000 Technology

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


381

Assumptions to the Annual Energy Outlook 2001 - Table 1. Summary of AEO2001  

Gasoline and Diesel Fuel Update (EIA)

1 Cases 1 Cases Case name Description Integration mode Reference Baseline economic growth, world oil price, and technology assumptions Fully integrated Low Economic Growth Gross domestic product grows at an average annual rate of 2.5 percent, compared to the reference case growth of 3.0 percent. Fully integrated High Economic Growth Gross domestic product grows at an average annual rate of 3.5 percent, compared to the reference case growth of 3.0 percent. Fully integrated Low World Oil Price World oil prices are $15.10 per barrel in 2020, compared to $22.41 per barrel in the reference case. Fully integrated High World Oil Price World oil prices are $28.42 per barrel in 2020, compared to $22.41 per barrel in the reference case. Fully integrated Residential: 2001 Technology

382

Washington International Renewable Energy Conference 2008 Pledges: Methodology and Assumptions Summary  

Science Conference Proceedings (OSTI)

The 2008 Washington International Renewable Energy Conference (WIREC) was held in Washington, D.C., from March 4-6, 2008, and involved nearly 9,000 people from 125 countries. The event brought together worldwide leaders in renewable energy (RE) from governments, international organizations, nongovernmental organizations, and the private sector to discuss the role that renewables can play in alleviating poverty, growing economies, and passing on a healthy planet to future generations. The conference concluded with more than 140 governments, international organizations, and private-sector representatives pledging to advance the uptake of renewable energy. The U.S. government authorized the National Renewable Energy Laboratory (NREL) to estimate the carbon dioxide (CO2) savings that would result from the pledges made at the 2008 conference. This report describes the methodology and assumptions used by NREL in quantifying the potential CO2 reductions derived from those pledges.

Babiuch, B.; Bilello, D. E.; Cowlin, S. C.; Mann, M.; Wise, A.

2008-08-01T23:59:59.000Z

383

TOB Module Assembly  

NLE Websites -- All DOE Office Websites (Extended Search)

SiTracker Home Page Participating Institutions and Principal Contacts Useful Links Notes Images TOB Module Assembly and Testing Project TOB Integration Data Tracker Offline DQM LHC Fluence Calculator Total US Modules Tested Graph Total US Modules Tested Graph Total US Modules Tested Total US Modules Tested US Modules Tested Graph US Modules Tested Graph US Modules Tested US Modules Tested Rod Assembly TOB Modules on a Rod TOB Rod Insertion Installation of a TOB Rod Completed TOB Completed Tracker Outer Barrel TOB Module Assembly and Testing Project All 5208 modules of the CMS Tracker Outer Barrel were assembled and tested at two production sites in the US: the Fermi National Accelerator Laboratory and the University of California at Santa Barbara. The modules were delivered to CERN in the form of rods, with the last shipment taking

384

Fuel Cells  

NLE Websites -- All DOE Office Websites (Extended Search)

Materials Science » Materials Science » Fuel Cells Fuel Cells Research into alternative forms of energy, especially energy security, is one of the major national security imperatives of this century. Get Expertise Melissa Fox Applied Energy Email Catherine Padro Sensors & Electrochemical Devices Email Fernando Garzon Sensors & Electrochemical Devices Email Piotr Zelenay Sensors & Electrochemical Devices Email Rod Borup Sensors & Electrochemical Devices Email Karen E. Kippen Experimental Physical Sciences Email Like a battery, a fuel cell consists of two electrodes separated by an electrolyte-in polymer electrolyte fuel cells, the separator is made of a thin polymeric membrane. Unlike a battery, a fuel cell does not need recharging-it continues to produce electricity as long as fuel flows

385

Fuel Cells  

NLE Websites -- All DOE Office Websites (Extended Search)

Fuel Cells Fuel Cells The Solid State Energy Conversion Alliance (SECA) program is responsible for coordinating Federal efforts to facilitate development of a commercially relevant and robust solid oxide fuel cell (SOFC) system. Specific objectives include achieving an efficiency of greater than 60 percent, meeting a stack cost target of $175 per kW, and demonstrating lifetime performance degradation of less than 0.2 percent per

386

Alternative Fuels Data Center: Fuel Prices  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Vehicles Vehicles Printable Version Share this resource Send a link to Alternative Fuels Data Center: Fuel Prices to someone by E-mail Share Alternative Fuels Data Center: Fuel Prices on Facebook Tweet about Alternative Fuels Data Center: Fuel Prices on Twitter Bookmark Alternative Fuels Data Center: Fuel Prices on Google Bookmark Alternative Fuels Data Center: Fuel Prices on Delicious Rank Alternative Fuels Data Center: Fuel Prices on Digg Find More places to share Alternative Fuels Data Center: Fuel Prices on AddThis.com... Fuel Prices As gasoline prices increase, alternative fuels appeal more to vehicle fleet managers and consumers. Like gasoline, alternative fuel prices can fluctuate based on location, time of year, and political climate. Alternative Fuel Price Report

387

Alternative Fuels Data Center: Alternative Fuel License  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuel Fuel License to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel License on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel License on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel License on Google Bookmark Alternative Fuels Data Center: Alternative Fuel License on Delicious Rank Alternative Fuels Data Center: Alternative Fuel License on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel License on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuel License Any person acting as an alternative fuels dealer must hold a valid alternative fuel license and certificate from the Wisconsin Department of Administration. Except for alternative fuels that a dealer delivers into a

388

Alternative Fuels Data Center: Alternative Fuel License  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuel Fuel License to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel License on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel License on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel License on Google Bookmark Alternative Fuels Data Center: Alternative Fuel License on Delicious Rank Alternative Fuels Data Center: Alternative Fuel License on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel License on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuel License Alternative fuel providers, bulk users, and retailers, or any person who fuels an alternative fuel vehicle from a private source that does not pay

389

Novel Fuel  

Science Conference Proceedings (OSTI)

About this Abstract. Meeting, Materials Science & Technology 2009. Symposium, Energy Materials. Presentation Title, Novel Fuel. Author(s), Naum Gosin, Igor...

390

Fuel Cells  

Energy.gov (U.S. Department of Energy (DOE))

Fuel cells are an emerging technology that can provide heat and electricity for buildings and electrical power for vehicles and electronic devices.

391

Alternative Fuels Data Center: Electricity Fuel Basics  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Electricity Fuel Electricity Fuel Basics to someone by E-mail Share Alternative Fuels Data Center: Electricity Fuel Basics on Facebook Tweet about Alternative Fuels Data Center: Electricity Fuel Basics on Twitter Bookmark Alternative Fuels Data Center: Electricity Fuel Basics on Google Bookmark Alternative Fuels Data Center: Electricity Fuel Basics on Delicious Rank Alternative Fuels Data Center: Electricity Fuel Basics on Digg Find More places to share Alternative Fuels Data Center: Electricity Fuel Basics on AddThis.com... More in this section... Electricity Basics Production & Distribution Research & Development Related Links Benefits & Considerations Stations Vehicles Laws & Incentives Electricity Fuel Basics Photo of a plug-in hybrid vehicle fueling. Electricity is considered an alternative fuel under the Energy Policy Act

392

Alternative Fuels Data Center: Alternative Fuel Definition  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Alternative Fuel Alternative Fuel Definition to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel Definition on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel Definition on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel Definition on Google Bookmark Alternative Fuels Data Center: Alternative Fuel Definition on Delicious Rank Alternative Fuels Data Center: Alternative Fuel Definition on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel Definition on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuel Definition The following fuels are defined as alternative fuels by the Energy Policy Act (EPAct) of 1992: pure methanol, ethanol, and other alcohols; blends of

393

Alternative Fuels Data Center: Alternative Fuels Tax  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuels Tax Fuels Tax to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuels Tax on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuels Tax on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuels Tax on Google Bookmark Alternative Fuels Data Center: Alternative Fuels Tax on Delicious Rank Alternative Fuels Data Center: Alternative Fuels Tax on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuels Tax on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuels Tax A state excise tax is imposed on the use of alternative fuels. Alternative fuels include liquefied petroleum gas (LPG or propane), compressed natural gas (CNG), and liquefied natural gas (LNG). The current tax rates are as

394

Alternative Fuels Data Center: Renewable Fuel Standard  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Renewable Fuel Renewable Fuel Standard to someone by E-mail Share Alternative Fuels Data Center: Renewable Fuel Standard on Facebook Tweet about Alternative Fuels Data Center: Renewable Fuel Standard on Twitter Bookmark Alternative Fuels Data Center: Renewable Fuel Standard on Google Bookmark Alternative Fuels Data Center: Renewable Fuel Standard on Delicious Rank Alternative Fuels Data Center: Renewable Fuel Standard on Digg Find More places to share Alternative Fuels Data Center: Renewable Fuel Standard on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Renewable Fuel Standard RFS Volumes by Year Enlarge illustration The Renewable Fuel Standard (RFS) is a federal program that requires transportation fuel sold in the U.S. to contain a minimum volume of

395

Alternative Fuels Data Center: Alternative Fuels Tax  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Alternative Fuels Tax Alternative Fuels Tax to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuels Tax on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuels Tax on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuels Tax on Google Bookmark Alternative Fuels Data Center: Alternative Fuels Tax on Delicious Rank Alternative Fuels Data Center: Alternative Fuels Tax on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuels Tax on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuels Tax Excise taxes on alternative fuels are imposed on a gasoline gallon equivalent basis. The tax rate for each alternative fuel type is based on the number of motor vehicles licensed in the state that use the specific

396

Alternative Fuels Data Center: Alternative Fuel Loans  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuel Loans Fuel Loans to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel Loans on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel Loans on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel Loans on Google Bookmark Alternative Fuels Data Center: Alternative Fuel Loans on Delicious Rank Alternative Fuels Data Center: Alternative Fuel Loans on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel Loans on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuel Loans The Oregon Department of Energy administers the State Energy Loan Program (SELP) which offers low-interest loans for qualified projects. Eligible alternative fuel projects include fuel production facilities, dedicated

397

Alternative Fuels Data Center: Alternative Fuels Tax  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuels Tax Fuels Tax to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuels Tax on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuels Tax on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuels Tax on Google Bookmark Alternative Fuels Data Center: Alternative Fuels Tax on Delicious Rank Alternative Fuels Data Center: Alternative Fuels Tax on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuels Tax on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuels Tax Alternative fuels are subject to an excise tax at a rate of $0.205 per gasoline gallon equivalent, with a variable component equal to at least 5% of the average wholesale price of the fuel. (Reference Senate Bill 454,

398

Alternative Fuels Data Center: Alternative Fuels Tax  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuels Tax Fuels Tax to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuels Tax on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuels Tax on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuels Tax on Google Bookmark Alternative Fuels Data Center: Alternative Fuels Tax on Delicious Rank Alternative Fuels Data Center: Alternative Fuels Tax on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuels Tax on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuels Tax The excise tax imposed on an alternative fuel distributed in New Mexico is $0.12 per gallon. Alternative fuels subject to the excise tax include liquefied petroleum gas (or propane), compressed natural gas, and liquefied

399

Alternative Fuels Data Center: Alternative Fuel Tax  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Alternative Fuel Tax Alternative Fuel Tax to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel Tax on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel Tax on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel Tax on Google Bookmark Alternative Fuels Data Center: Alternative Fuel Tax on Delicious Rank Alternative Fuels Data Center: Alternative Fuel Tax on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel Tax on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuel Tax The Minnesota Department of Revenue imposes an excise tax on the first licensed distributor that receives E85 fuel products in the state and on distributors, special fuel dealers, or bulk purchasers of other alternative

400

Residential HVAC Data, Assumptions and Methodology for End-Use Forecasting with EPRI-REEPS 2.1  

E-Print Network (OSTI)

oil hydronic, electric room, and electric (air source) heatFuels = Oil and Gas, LPG and Misc. (3) Sources: 1990 RECS (Fuels = Oil and Gas, Other = LPG and Misc. (3) Sources: 1990

Johnson, F.X.

2010-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


401

50-year-old assumptions about strength muscled aside | Argonne National  

NLE Websites -- All DOE Office Websites (Extended Search)

C. David Williams with an X-ray diffraction apparatus used to measure lattice spacing of filaments in moth wing muscle samples. To view a larger version of the image, click on it. Credit: A. Kidder/University of Washington. C. David Williams with an X-ray diffraction apparatus used to measure lattice spacing of filaments in moth wing muscle samples. To view a larger version of the image, click on it. Credit: A. Kidder/University of Washington. C. David Williams with an X-ray diffraction apparatus used to measure lattice spacing of filaments in moth wing muscle samples. To view a larger version of the image, click on it. Credit: A. Kidder/University of Washington. To view a larger, downloadable version of the image, click on it. To view a larger, downloadable version of the image, click on it. 50-year-old assumptions about strength muscled aside July 11, 2013 Tweet EmailPrint LEMONT, Ill. - Doctors have a new way of thinking about how to treat heart and skeletal muscle diseases. Body builders have a new way of

402

Standard assumptions and methods for solar heating and cooling systems analysis  

DOE Green Energy (OSTI)

A set of inputs, assumptions, analytical methods, and a reporting format is presented to help compare the results of residential and commercial solar system analyses being performed by different investigators. By the common use of load data, meteorological data, economic parameters, and reporting format, researchers examining, for example, two types of collectors may more easily compare their results. For residential heating and cooling systems, three locations were selected. The weather data chosen to characterize these cities are the Typical Meteorological Year (TMY). A house for each location was defined that is typical of new construction in that locale. Hourly loads for each location were calculated using a computerized load model that interacts with the system specified inputs characterizing each house. Four locations for commercial cooling analyses were selected from among the existing sites for which TMYs were available. A light commercial (nominal 25-ton cooling load) office building was defined and is used in all four locations. Hourly cooling and heating loads were computed for each city and are available on magnetic tape from the Solar Energy Research Insititute (SERI).

Leboeuf, C.M.

1980-01-01T23:59:59.000Z

403

SHARP Physics Modules Updated | Department of Energy  

Energy.gov (U.S. Department of Energy (DOE)) Indexed Site

Physics Modules Updated Physics Modules Updated SHARP Physics Modules Updated January 29, 2013 - 12:37pm Addthis PROTEUS Development The SHARP neutronics module, PROTEUS, includes neutron and gamma transport solvers, cross-section processing tools, and tools for depletion and fuel cycle analysis. Efforts in the second quarter focused on three major priorities: multi-physics integration, intermediate-fidelity tool development, and demonstrations of applicability. Integration of the second-order, discrete ordinates (Sn method) solver of PROTEUS with the latest version of the MOAB framework (which represents and evaluates mesh data) was initiated to enable its use for multi-physics analysis. With these updates, PROTEUS can obtain the mesh specification from the MOAB framework and store its data on the MOAB mesh representation so that MOAB

404

Ballasted photovoltaic module and module arrays  

DOE Patents (OSTI)

A photovoltaic (PV) module assembly including a PV module and a ballast tray. The PV module includes a PV device and a frame. A PV laminate is assembled to the frame, and the frame includes an arm. The ballast tray is adapted for containing ballast and is removably associated with the PV module in a ballasting state where the tray is vertically under the PV laminate and vertically over the arm to impede overt displacement of the PV module. The PV module assembly can be installed to a flat commercial rooftop, with the PV module and the ballast tray both resting upon the rooftop. In some embodiments, the ballasting state includes corresponding surfaces of the arm and the tray being spaced from one another under normal (low or no wind) conditions, such that the frame is not continuously subjected to a weight of the tray.

Botkin, Jonathan (El Cerrito, CA); Graves, Simon (Berkeley, CA); Danning, Matt (Oakland, CA)

2011-11-29T23:59:59.000Z

405

EIA - The National Energy Modeling System: An Overview 2003-Renewable Fuels  

Gasoline and Diesel Fuel Update (EIA)

Renewable Fuelsl Module Renewable Fuelsl Module The National Energy Modeling System: An Overview 2003 Renewable Fuels Module Figure 11. Renewable Fuels Module Structure. Need help, contact the National Energy Information Center at 202-586-8800. Renewable Fuels Module Table. Need help, contact the National Energy Information Center at 202-586-8800. The renewable fuels module (RFM) represents renewable energy resoures and large–scale technologies used for grid-connected U.S. electricity supply (Figure 11). Since most renewables (biomass, conventional hydroelectricity, geothermal, landfill gas, solar photovoltaics, solar thermal, and wind) are used to generate electricity, the RFM primarily interacts with the electricity market module (EMM). New renewable energy generating capacity is either model–determined or

406

Alternative Fuels Data Center: Alternative Fuel Tax  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuel Tax Fuel Tax to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel Tax on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel Tax on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel Tax on Google Bookmark Alternative Fuels Data Center: Alternative Fuel Tax on Delicious Rank Alternative Fuels Data Center: Alternative Fuel Tax on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel Tax on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuel Tax Special fuels, including biodiesel, biodiesel blends, biomass-based diesel, biomass-based diesel blends, and liquefied natural gas, have a reduced tax rate of $0.27 per gallon. Liquefied petroleum gas (LPG or propane) and

407

Alternative Fuels Data Center: Special Fuel Tax  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Special Fuel Tax to Special Fuel Tax to someone by E-mail Share Alternative Fuels Data Center: Special Fuel Tax on Facebook Tweet about Alternative Fuels Data Center: Special Fuel Tax on Twitter Bookmark Alternative Fuels Data Center: Special Fuel Tax on Google Bookmark Alternative Fuels Data Center: Special Fuel Tax on Delicious Rank Alternative Fuels Data Center: Special Fuel Tax on Digg Find More places to share Alternative Fuels Data Center: Special Fuel Tax on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Special Fuel Tax Effective January 1, 2014, certain special fuels sold or used to propel motor vehicles are subject to a license tax. Liquefied natural gas is subject to a tax of $0.16 per diesel gallon equivalent. Compressed natural

408

Alternative Fuels Data Center: Renewable Fuels Assessment  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Renewable Fuels Renewable Fuels Assessment to someone by E-mail Share Alternative Fuels Data Center: Renewable Fuels Assessment on Facebook Tweet about Alternative Fuels Data Center: Renewable Fuels Assessment on Twitter Bookmark Alternative Fuels Data Center: Renewable Fuels Assessment on Google Bookmark Alternative Fuels Data Center: Renewable Fuels Assessment on Delicious Rank Alternative Fuels Data Center: Renewable Fuels Assessment on Digg Find More places to share Alternative Fuels Data Center: Renewable Fuels Assessment on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Renewable Fuels Assessment The U.S. Department of Defense (DOD) prepared a report, Opportunities for DOD Use of Alternative and Renewable Fuels, on the use and potential use of

409

Alternative Fuels Data Center: Biodiesel Fuel Basics  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuel Basics Fuel Basics to someone by E-mail Share Alternative Fuels Data Center: Biodiesel Fuel Basics on Facebook Tweet about Alternative Fuels Data Center: Biodiesel Fuel Basics on Twitter Bookmark Alternative Fuels Data Center: Biodiesel Fuel Basics on Google Bookmark Alternative Fuels Data Center: Biodiesel Fuel Basics on Delicious Rank Alternative Fuels Data Center: Biodiesel Fuel Basics on Digg Find More places to share Alternative Fuels Data Center: Biodiesel Fuel Basics on AddThis.com... More in this section... Biodiesel Basics Blends Production & Distribution Specifications Related Links Benefits & Considerations Stations Vehicles Laws & Incentives Biodiesel Fuel Basics Related Information National Biofuels Action Plan Biodiesel is a domestically produced, renewable fuel that can be

410

Alternative Fuels Data Center: Renewable Fuel Standard  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Renewable Fuel Renewable Fuel Standard to someone by E-mail Share Alternative Fuels Data Center: Renewable Fuel Standard on Facebook Tweet about Alternative Fuels Data Center: Renewable Fuel Standard on Twitter Bookmark Alternative Fuels Data Center: Renewable Fuel Standard on Google Bookmark Alternative Fuels Data Center: Renewable Fuel Standard on Delicious Rank Alternative Fuels Data Center: Renewable Fuel Standard on Digg Find More places to share Alternative Fuels Data Center: Renewable Fuel Standard on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Renewable Fuel Standard At least 2% of all diesel fuel sold in Washington must be biodiesel or renewable diesel. This requirement will increase to 5% 180 days after the

411

Alternative Fuels Data Center: Biodiesel Fuel Use  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Biodiesel Fuel Use to Biodiesel Fuel Use to someone by E-mail Share Alternative Fuels Data Center: Biodiesel Fuel Use on Facebook Tweet about Alternative Fuels Data Center: Biodiesel Fuel Use on Twitter Bookmark Alternative Fuels Data Center: Biodiesel Fuel Use on Google Bookmark Alternative Fuels Data Center: Biodiesel Fuel Use on Delicious Rank Alternative Fuels Data Center: Biodiesel Fuel Use on Digg Find More places to share Alternative Fuels Data Center: Biodiesel Fuel Use on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Biodiesel Fuel Use The Iowa Department of Transportation (IDOT) may purchase biodiesel for use in IDOT vehicles through the biodiesel fuel revolving fund created in the state treasury. The fund consists of money received from the sale of Energy

412

Alternative Fuels Data Center: Ethanol Fuel Basics  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuel Basics to Fuel Basics to someone by E-mail Share Alternative Fuels Data Center: Ethanol Fuel Basics on Facebook Tweet about Alternative Fuels Data Center: Ethanol Fuel Basics on Twitter Bookmark Alternative Fuels Data Center: Ethanol Fuel Basics on Google Bookmark Alternative Fuels Data Center: Ethanol Fuel Basics on Delicious Rank Alternative Fuels Data Center: Ethanol Fuel Basics on Digg Find More places to share Alternative Fuels Data Center: Ethanol Fuel Basics on AddThis.com... More in this section... Ethanol Basics Blends Specifications Production & Distribution Feedstocks Related Links Benefits & Considerations Stations Vehicles Laws & Incentives Ethanol Fuel Basics Related Information National Biofuels Action Plan Ethanol is a renewable fuel made from various plant materials collectively

413

Alternative Fuels Data Center: Biodiesel Fuel Use  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuel Use to Fuel Use to someone by E-mail Share Alternative Fuels Data Center: Biodiesel Fuel Use on Facebook Tweet about Alternative Fuels Data Center: Biodiesel Fuel Use on Twitter Bookmark Alternative Fuels Data Center: Biodiesel Fuel Use on Google Bookmark Alternative Fuels Data Center: Biodiesel Fuel Use on Delicious Rank Alternative Fuels Data Center: Biodiesel Fuel Use on Digg Find More places to share Alternative Fuels Data Center: Biodiesel Fuel Use on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Biodiesel Fuel Use The South Dakota Department of Transportation and employees using state diesel vehicles must stock and use fuel blends containing a minimum of 2% biodiesel (B2) that meets or exceeds the most current ASTM specification

414

Alternative Fuels Data Center: Hydrogen Fuel Specifications  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Hydrogen Fuel Hydrogen Fuel Specifications to someone by E-mail Share Alternative Fuels Data Center: Hydrogen Fuel Specifications on Facebook Tweet about Alternative Fuels Data Center: Hydrogen Fuel Specifications on Twitter Bookmark Alternative Fuels Data Center: Hydrogen Fuel Specifications on Google Bookmark Alternative Fuels Data Center: Hydrogen Fuel Specifications on Delicious Rank Alternative Fuels Data Center: Hydrogen Fuel Specifications on Digg Find More places to share Alternative Fuels Data Center: Hydrogen Fuel Specifications on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Hydrogen Fuel Specifications The California Department of Food and Agriculture, Division of Measurement Standards (DMS) established interim specifications for hydrogen fuels for

415

Alternative Fuels Data Center: Flexible Fuel Vehicles  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Ethanol Ethanol Printable Version Share this resource Send a link to Alternative Fuels Data Center: Flexible Fuel Vehicles to someone by E-mail Share Alternative Fuels Data Center: Flexible Fuel Vehicles on Facebook Tweet about Alternative Fuels Data Center: Flexible Fuel Vehicles on Twitter Bookmark Alternative Fuels Data Center: Flexible Fuel Vehicles on Google Bookmark Alternative Fuels Data Center: Flexible Fuel Vehicles on Delicious Rank Alternative Fuels Data Center: Flexible Fuel Vehicles on Digg Find More places to share Alternative Fuels Data Center: Flexible Fuel Vehicles on AddThis.com... More in this section... Ethanol Basics Benefits & Considerations Stations Vehicles Availability Conversions Emissions Laws & Incentives Flexible Fuel Vehicles Photo of a flexible fuel vehicle.

416

Alternative Fuels Data Center: Alternative Fuel Use  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuel Use Fuel Use to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel Use on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel Use on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel Use on Google Bookmark Alternative Fuels Data Center: Alternative Fuel Use on Delicious Rank Alternative Fuels Data Center: Alternative Fuel Use on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel Use on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuel Use All state employees operating flexible fuel or diesel vehicles as part of the state fleet must use E85 or biodiesel blends whenever reasonably available. Additionally, the Nebraska Transportation Services Bureau and

417

Alternative Fuels Data Center: Alternative Fuels Tax  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuels Tax Fuels Tax to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuels Tax on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuels Tax on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuels Tax on Google Bookmark Alternative Fuels Data Center: Alternative Fuels Tax on Delicious Rank Alternative Fuels Data Center: Alternative Fuels Tax on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuels Tax on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuels Tax Alternative fuels used to propel vehicles of any kind on public highways are taxed at a rate determined on a gasoline gallon equivalent basis. The tax rates are posted in the Pennsylvania Bulletin. (Reference Title 75

418

Liquid Fuels Market Model (LFMM) Unveiling LFMM  

Gasoline and Diesel Fuel Update (EIA)

Implementation of the Renewable Fuel Implementation of the Renewable Fuel Standard (RFS) in the Liquid Fuels Market Module (LFMM) of NEMS Michael H. Cole, PhD, PE michael.cole@eia.gov August 1, 2012 | Washington, DC LFMM / NEMS overview 2 M. Cole, EIA Advanced Biofuels Workshop August 1, 2012 | Washington, DC * LFMM is a mathematical representation of the U.S. liquid fuels market (motor gasoline, diesel, biofuels, etc.). EIA analysts use LFMM to project motor fuel prices and production approaches through 2040. * LFMM is a cost-minimization linear program (LP). For a given set of fuel demands, LFMM will find the least-cost means of satisfying those demands, subject to various constraints (such as the RFS). * LFMM is part of the National Energy Modeling System (NEMS), which is a computer model of the U.S. energy economy. EIA uses

419

Connections for solid oxide fuel cells  

DOE Patents (OSTI)

A connection for fuel cell assemblies is disclosed. The connection includes compliant members connected to individual fuel cells and a rigid member connected to the compliant members. Adjacent bundles or modules of fuel cells are connected together by mechanically joining their rigid members. The compliant/rigid connection permits construction of generator fuel cell stacks from basic modular groups of cells of any desired size. The connections can be made prior to installation of the fuel cells in a generator, thereby eliminating the need for in-situ completion of the connections. In addition to allowing pre-fabrication, the compliant/rigid connections also simplify removal and replacement of sections of a generator fuel cell stack.

Collie, Jeffrey C. (Pittsburgh, PA)

1999-01-01T23:59:59.000Z

420

Alternative Fuels Data Center: Alternative Fuel Infrastructure...  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Type Alternative Fuel Infrastructure Development Program The Tennessee Department of Environment and Conservation provides funding for alternative fueling infrastructure...

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


421

Fuel Chemistry Preprints  

Science Conference Proceedings (OSTI)

Papers are presented under the following symposia titles: advances in fuel cell research; biorefineries - renewable fuels and chemicals; chemistry of fuels and emerging fuel technologies; fuel processing for hydrogen production; membranes for energy and fuel applications; new progress in C1 chemistry; research challenges for the hydrogen economy, hydrogen storage; SciMix fuel chemistry; and ultraclean transportation fuels.

NONE

2005-09-30T23:59:59.000Z

422

NERSC Modules Software Environment  

NLE Websites -- All DOE Office Websites (Extended Search)

Environment » Modules Environment Environment » Modules Environment Modules Software Environment NERSC uses the module utility to manage nearly all software. There are two huge advantages of the module approach: NERSC can provide many different versions and/or installations of a single software package on a given machine, including a default version as well as several older and newer versions; and Users can easily switch to different versions or installations without having to explicitly specify different paths. With modules, the MANPATH and related environment variables are automatically managed. Users simply ``load'' and ``unload'' modules to control their environment. The module utility consists of two parts: the module command itself and the modulefiles on which it operates. Module Command

423

Assumptions to the Annual Energy Outlook 2001 - Table 4. Coefficients of  

Gasoline and Diesel Fuel Update (EIA)

Coefficients of Linear Equations for Natural Gas- and Coefficients of Linear Equations for Natural Gas- and Oil-Related Methane Emissions Emissions Sources Intercept Variable Name and Units Coefficient Variable Name and Units Coefficient Natural Gas -38.77 Time trend (calendar year) .02003 Dry gas production (thousand cubic feet .02186 Natural Gas Processing -0.9454 Natural gas liquids production (million barrels per day) .9350 Not applicable Natural Gas Transmission and Storage 2.503 Pipeline fuel use (thousand cubic feet) 1.249 Dry gas production (thousand cubic feet) -0.06614 Natural Gas Distribution -58.16 Time trend (calendar year) .0297 Natural gas consumption (quadrillion Btu) .0196 Oil production, Refining, and Transport 0.03190 Oil consumption (quadrillion Btu) .002764 Not applicable Source: Derived from data used in Energy Information Administration, Emissions of Greenhouse Gases in the United States 1999, DOE/EIA-0573(99), (Washington, DC, October 2000).

424

FUEL ELEMENT  

DOE Patents (OSTI)

A ceramic fuel element for a nuclear reactor that has improved structural stability as well as improved cooling and fission product retention characteristics is presented. The fuel element includes a plurality of stacked hollow ceramic moderator blocks arranged along a tubular raetallic shroud that encloses a series of axially apertured moderator cylinders spaced inwardly of the shroud. A plurality of ceramic nuclear fuel rods are arranged in the annular space between the shroud and cylinders of moderator and appropriate support means and means for directing gas coolant through the annular space are also provided. (AEC)

Bean, R.W.

1963-11-19T23:59:59.000Z

425

Alternative Fuels Data Center: Fuel Quality Standards  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuel Quality Standards Fuel Quality Standards to someone by E-mail Share Alternative Fuels Data Center: Fuel Quality Standards on Facebook Tweet about Alternative Fuels Data Center: Fuel Quality Standards on Twitter Bookmark Alternative Fuels Data Center: Fuel Quality Standards on Google Bookmark Alternative Fuels Data Center: Fuel Quality Standards on Delicious Rank Alternative Fuels Data Center: Fuel Quality Standards on Digg Find More places to share Alternative Fuels Data Center: Fuel Quality Standards on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Fuel Quality Standards The South Dakota Department of Public Safety may promulgate rules establishing: Standards for the maximum volume percentages of ethanol and methanol

426

Alternative Fuels Data Center: Renewable Fuels Mandate  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Renewable Fuels Renewable Fuels Mandate to someone by E-mail Share Alternative Fuels Data Center: Renewable Fuels Mandate on Facebook Tweet about Alternative Fuels Data Center: Renewable Fuels Mandate on Twitter Bookmark Alternative Fuels Data Center: Renewable Fuels Mandate on Google Bookmark Alternative Fuels Data Center: Renewable Fuels Mandate on Delicious Rank Alternative Fuels Data Center: Renewable Fuels Mandate on Digg Find More places to share Alternative Fuels Data Center: Renewable Fuels Mandate on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Renewable Fuels Mandate One year after in-state production has reached 350 million gallons of cellulosic ethanol and sustained this volume for three months, all gasoline

427

Alternative Fuels Data Center: Renewable Fuels Mandate  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Renewable Fuels Renewable Fuels Mandate to someone by E-mail Share Alternative Fuels Data Center: Renewable Fuels Mandate on Facebook Tweet about Alternative Fuels Data Center: Renewable Fuels Mandate on Twitter Bookmark Alternative Fuels Data Center: Renewable Fuels Mandate on Google Bookmark Alternative Fuels Data Center: Renewable Fuels Mandate on Delicious Rank Alternative Fuels Data Center: Renewable Fuels Mandate on Digg Find More places to share Alternative Fuels Data Center: Renewable Fuels Mandate on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Renewable Fuels Mandate All gasoline sold in the state must be blended with 10% ethanol (E10). Gasoline with an octane rating of 91 or above is exempt from this mandate,

428

Alternative Fuels Data Center: Renewable Fuels Promotion  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Renewable Fuels Renewable Fuels Promotion to someone by E-mail Share Alternative Fuels Data Center: Renewable Fuels Promotion on Facebook Tweet about Alternative Fuels Data Center: Renewable Fuels Promotion on Twitter Bookmark Alternative Fuels Data Center: Renewable Fuels Promotion on Google Bookmark Alternative Fuels Data Center: Renewable Fuels Promotion on Delicious Rank Alternative Fuels Data Center: Renewable Fuels Promotion on Digg Find More places to share Alternative Fuels Data Center: Renewable Fuels Promotion on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Renewable Fuels Promotion Recognizing that biofuels such as ethanol and biodiesel will be an important part of the state's energy economy and advanced research in

429

Alternative Fuels Data Center: Alternative Fuels Promotion  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Alternative Fuels Alternative Fuels Promotion to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuels Promotion on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuels Promotion on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuels Promotion on Google Bookmark Alternative Fuels Data Center: Alternative Fuels Promotion on Delicious Rank Alternative Fuels Data Center: Alternative Fuels Promotion on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuels Promotion on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuels Promotion The state of Hawaii has signed a memorandum of understanding (MOU) with the U.S. Department of Energy to collaborate to produce 70% of the state's

430

Alternative Fuels Data Center: Alternative Fuel Tax  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Alternative Fuel Tax Alternative Fuel Tax to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel Tax on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel Tax on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel Tax on Google Bookmark Alternative Fuels Data Center: Alternative Fuel Tax on Delicious Rank Alternative Fuels Data Center: Alternative Fuel Tax on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel Tax on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuel Tax The excise tax imposed on compressed natural gas (CNG), liquefied natural gas (LNG), and liquefied petroleum gas (LPG or propane) used to operate a vehicle can be paid through an annual flat rate sticker tax based on the

431

Alternative Fuels Data Center: Renewable Fuel Promotion  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Renewable Fuel Renewable Fuel Promotion to someone by E-mail Share Alternative Fuels Data Center: Renewable Fuel Promotion on Facebook Tweet about Alternative Fuels Data Center: Renewable Fuel Promotion on Twitter Bookmark Alternative Fuels Data Center: Renewable Fuel Promotion on Google Bookmark Alternative Fuels Data Center: Renewable Fuel Promotion on Delicious Rank Alternative Fuels Data Center: Renewable Fuel Promotion on Digg Find More places to share Alternative Fuels Data Center: Renewable Fuel Promotion on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Renewable Fuel Promotion The Texas Bioenergy Policy Council and the Texas Bioenergy Research Committee were established to promote the goal of making biofuels a

432

Alternative Fuels Data Center: Renewable Fuel Standard  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Renewable Fuel Renewable Fuel Standard to someone by E-mail Share Alternative Fuels Data Center: Renewable Fuel Standard on Facebook Tweet about Alternative Fuels Data Center: Renewable Fuel Standard on Twitter Bookmark Alternative Fuels Data Center: Renewable Fuel Standard on Google Bookmark Alternative Fuels Data Center: Renewable Fuel Standard on Delicious Rank Alternative Fuels Data Center: Renewable Fuel Standard on Digg Find More places to share Alternative Fuels Data Center: Renewable Fuel Standard on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Renewable Fuel Standard Within six months following the point at which monthly production of denatured ethanol produced in Louisiana equals or exceeds a minimum annualized production volume of 50 million gallons, at least 2% of the

433

Alternative Fuels Data Center: Alternative Fuel Tax  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Fuel Tax Fuel Tax to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel Tax on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel Tax on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel Tax on Google Bookmark Alternative Fuels Data Center: Alternative Fuel Tax on Delicious Rank Alternative Fuels Data Center: Alternative Fuel Tax on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel Tax on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuel Tax The state road tax for vehicles that operate on propane (liquefied petroleum gas, or LPG) or natural gas is paid through the purchase of an annual flat fee sticker, and the amount is based on the vehicle's gross

434

Alternative Fuels Data Center: Propane Fueling Stations  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Stations to someone by E-mail Stations to someone by E-mail Share Alternative Fuels Data Center: Propane Fueling Stations on Facebook Tweet about Alternative Fuels Data Center: Propane Fueling Stations on Twitter Bookmark Alternative Fuels Data Center: Propane Fueling Stations on Google Bookmark Alternative Fuels Data Center: Propane Fueling Stations on Delicious Rank Alternative Fuels Data Center: Propane Fueling Stations on Digg Find More places to share Alternative Fuels Data Center: Propane Fueling Stations on AddThis.com... More in this section... Propane Basics Benefits & Considerations Stations Locations Infrastructure Development Vehicles Laws & Incentives Propane Fueling Stations Photo of a liquefied petroleum gas fueling station. Thousands of liquefied petroleum gas (propane) fueling stations are

435

Alternative Fuels Data Center: Alternative Fuel Study  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Alternative Fuel Study Alternative Fuel Study to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel Study on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel Study on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel Study on Google Bookmark Alternative Fuels Data Center: Alternative Fuel Study on Delicious Rank Alternative Fuels Data Center: Alternative Fuel Study on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel Study on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuel Study As directed by the Nevada Legislature, the Legislative Commission (Commission) conducted an interim study in 2011 concerning the production and use of energy in the state. The study included information on the use

436

Fuels - Biodiesel  

NLE Websites -- All DOE Office Websites (Extended Search)

* Biodiesel * Biodiesel * Butanol * Ethanol * Hydrogen * Natural Gas * Fischer-Tropsch Batteries Cross-Cutting Assessments Engines GREET Hybrid Electric Vehicles Hydrogen & Fuel Cells Materials Modeling, Simulation & Software Plug-In Hybrid Electric Vehicles PSAT Smart Grid Student Competitions Transportation Research and Analysis Computing Center Working With Argonne Contact TTRDC Clean Diesel Fuels Background Reducing our country's dependence on foreign oil and the rising costs of crude oil are primary reasons for a renewed interest in alternative fuels for the transportation sector. Stringent emissions regulations and public concern about mobile sources of air pollution provide additional incentives to develop fuels that generate fewer emissions, potentially reducing the need for sophisticated, expensive exhaust after-treatment devices.

437

Hydrogen Fuel  

Energy.gov (U.S. Department of Energy (DOE))

Hydrogen is a clean fuel that, when consumed, produces only water. Hydrogen can be produced from a variety of domestic sources, such as coal, natural gas, nuclear power, and renewable power. These...

438

Fuel Economy  

NLE Websites -- All DOE Office Websites (Extended Search)

Selling your car? Advertise its fuel economy with our Used Car Label tool. Download a label for on-line ads. Print a label to attach to your car. Did you know? You can purchase...

439

Certification of alternative aviation fuels and blend components  

SciTech Connect

Aviation turbine engine fuel specifications are governed by ASTM International, formerly known as the American Society for Testing and Materials (ASTM) International, and the British Ministry of Defence (MOD). ASTM D1655 Standard Specification for Aviation Turbine Fuels and MOD Defence Standard 91-91 are the guiding specifications for this fuel throughout most of the world. Both of these documents rely heavily on the vast amount of experience in production and use of turbine engine fuels from conventional sources, such as crude oil, natural gas condensates, heavy oil, shale oil, and oil sands. Turbine engine fuel derived from these resources and meeting the above specifications has properties that are generally considered acceptable for fuels to be used in turbine engines. Alternative and synthetic fuel components are approved for use to blend with conventional turbine engine fuels after considerable testing. ASTM has established a specification for fuels containing synthesized hydrocarbons under D7566, and the MOD has included additional requirements for fuels containing synthetic components under Annex D of DS91-91. New turbine engine fuel additives and blend components need to be evaluated using ASTM D4054, Standard Practice for Qualification and Approval of New Aviation Turbine Fuels and Fuel Additives. This paper discusses these specifications and testing requirements in light of recent literature claiming that some biomass-derived blend components, which have been used to blend in conventional aviation fuel, meet the requirements for aviation turbine fuels as specified by ASTM and the MOD. The 'Table 1' requirements listed in both D1655 and DS91-91 are predicated on the assumption that the feedstocks used to make fuels meeting these requirements are from approved sources. Recent papers have implied that commercial jet fuel can be blended with renewable components that are not hydrocarbons (such as fatty acid methyl esters). These are not allowed blend components for turbine engine fuels as discussed in this paper.

Wilson III, George R. (Southwest Research Institute, 6220 Culebra Road, San Antonio, Texas 78238 (United States)); Edwards, Tim; Corporan, Edwin (United States Air Force Research Laboratory, Wright-Patterson Air Force Base, Ohio 45433 (United States)); Freerks, Robert L. (Rentech, Incorporated, 1331 17th Street, Denver, Colorado 80202 (United States))

2013-01-15T23:59:59.000Z

440

Natural Gas Transmission and Distribution Module  

Gasoline and Diesel Fuel Update (EIA)

page intentionally left blank page intentionally left blank 129 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 Natural Gas Transmission and Distribution Module The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through the regional interstate network, for both a peak (December through March) and off peak period during each projection year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution network that links them. Natural gas flow patterns are a function of the pattern in the previous year, coupled

Note: This page contains sample records for the topic "fuels module assumptions" from the National Library of EnergyBeta (NLEBeta).
While these samples are representative of the content of NLEBeta,
they are not comprehensive nor are they the most current set.
We encourage you to perform a real-time search of NLEBeta
to obtain the most current and comprehensive results.


441

Natural Gas Transmission and Distribution Module This  

Gasoline and Diesel Fuel Update (EIA)

This This page inTenTionally lefT blank 127 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2012 Natural Gas Transmission and Distribution Module The NEMS Natural Gas Transmission and Distribution Module (NGTDM) derives domestic natural gas production, wellhead and border prices, end-use prices, and flows of natural gas through a regional interstate representative pipeline network, for both a peak (December through March) and off-peak period during each projection year. These are derived by solving for the market equilibrium across the three main components of the natural gas market: the supply component, the demand component, and the transmission and distribution network that links them. Natural gas flow patterns are a function of the

442

Alternative Fuels Data Center: Alternative Fuel Definition  

Alternative Fuels and Advanced Vehicles Data Center (EERE)

Definition to someone by E-mail Definition to someone by E-mail Share Alternative Fuels Data Center: Alternative Fuel Definition on Facebook Tweet about Alternative Fuels Data Center: Alternative Fuel Definition on Twitter Bookmark Alternative Fuels Data Center: Alternative Fuel Definition on Google Bookmark Alternative Fuels Data Center: Alternative Fuel Definition on Delicious Rank Alternative Fuels Data Center: Alternative Fuel Definition on Digg Find More places to share Alternative Fuels Data Center: Alternative Fuel Definition on AddThis.com... More in this section... Federal State Advanced Search All Laws & Incentives Sorted by Type Alternative Fuel Definition Alternative fuel is defined as compressed natural gas, propane, ethanol, or any mixture containing 85% or more ethanol (E85) with gasoline or other

443

Conversion to Dual Fuel Capability in Combustion Turbine Plants: Addition of Distillate Oil Firing for Combined Cycles  

Science Conference Proceedings (OSTI)

During development of combined cycle projects, key assumptions and estimates regarding markets and technology on which the project is based may change. With fuel costs of combined cycle plants representing over 90 percent of annual operating cost, sudden changes in fuel pricing demand attention and re-evaluation. Conversion from natural gas fuel only to dual fuel capability with the addition of distillate oil firing systems is a technical response to market conditions that may have long-term as well as s...

2001-09-26T23:59:59.000Z

444

Manifold, bus support and coupling arrangement for solid oxide fuel cells  

DOE Patents (OSTI)

Individual, tubular solid oxide fuel cells (SOFCs) are assembled into bundles called a module within a housing, with a plurality of modules arranged end-to-end in a linear, stacked configuration called a string. A common set of piping comprised of a suitable high temperture resistant material (1) provides fuel and air to each module housing, (2) serves as electrically conducting buses, and (3) provides structural support for a string of SOFC modules. The piping thus forms a manfold for directing fuel and air to each module in a string and makes electrical contact with the module's anode and cathode to conduct the DC power generated by the SOFC. The piping also provides structureal support for each individual module and maintains each string of modules as a structurally integral unit for ensuring high strength in a large 3-dimensional array of SOFC modules. Ceramic collars are used to connect fuel and air inlet piping to each of the electrodes in an SOFC module and provide (1) electrical insulation for the current carrying bus bars and gas manifolds, (2) damping for the fuel and air inlet piping, and (3) proper spacing between the fuel and air inlet piping to prevent contact between these tubes and possible damage to the SOFC.

Parry, Gareth W. (East Windsor, CT)

1989-01-01T23:59:59.000Z

445

Manifold, bus support and coupling arrangement for solid oxide fuel cells  

DOE Patents (OSTI)

Individual, tubular solid oxide fuel cells (SOFCs) are assembled into bundles called a module within a housing, with a plurality of modules arranged end-to-end in a linear, stacked configuration called a string. A common set of piping comprised of a suitable high temperature resistant material (1) provides fuel and air to each module housing, (2) serves as electrically conducting buses, and (3) provides structural support for a string of SOFC modules. Ceramic collars are used to connect fuel and air inlet piping to each of the electrodes in an SOFC module and provide (1) electrical insulation for the current carrying bus bars and gas manifolds, (2) damping for the fuel and air inlet piping, and (3) proper spacing between the fuel and air inlet piping to prevent contact between these tubes and possible damage to the SOFC. 11 figs.

Parry, G.W.

1988-04-21T23:59:59.000Z

446

Preliminary Review of Models, Assumptions, and Key Data used in Performance Assessments and Composite Analysis at the Idaho National Laboratory  

SciTech Connect

This document is in response to a request by Ming Zhu, DOE-EM to provide a preliminary review of existing models and data used in completed or soon to be completed Performance Assessments and Composite Analyses (PA/CA) documents, to identify codes, methodologies, main assumptions, and key data se