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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

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.

9

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.

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

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

13

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

14

Alternative Fuels Data Center: Vehicle Cost Calculator Assumptions and  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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...

15

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.

16

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).

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

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

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 assumption" 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)

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. . . . . . . . . . . . .

23

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

24

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.

25

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

26

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

27

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

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

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.

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

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)

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 - 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

37

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.

38

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

39

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.

40

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

Note: This page contains sample records for the topic "fuels module assumption" 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 - 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).

43

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.

44

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).

45

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

46

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

47

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

48

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

49

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).

50

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.

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

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.

53

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

54

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

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 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.

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 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

59

Module 5: Fuel Cell Systems  

Broader source: Energy.gov [DOE]

This course covers the systems required to operate a fuel cell engine, the components and functionality of each fuel cell system

60

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

Note: This page contains sample records for the topic "fuels module assumption" 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

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

62

Model documentation Renewable Fuels Module of the National Energy Modeling System  

SciTech Connect (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

63

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

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

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). 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. 11 figs.

Riley, B.

1988-04-22T23:59:59.000Z

66

EIA model documentation: Electricity market module - electricity fuel dispatch  

SciTech Connect (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

67

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

68

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

69

Module 10: Maintenance and Fueling Guidelines  

Broader source: Energy.gov [DOE]

This course covers safety guidelines for hydrogen, safe maintenance facilities, safety guidelines for hydrogen fueling facilities

70

Module 6: Fuel Cell Engine Safety  

Broader source: Energy.gov [DOE]

This course will cover the hazards and safety provisions associated with hydrogen and fuel cell engine systems

71

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

72

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 . . . . . . . . . . .

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

Modeling a Proton Exchange Membrane Fuel Cell using Non-Equilibrium Thermodynamics: A Second Law analysis of assumptions and parameters:.  

E-Print Network [OSTI]

??In this work, a model derived from Non-Equilibrium Thermodynamics, for the Proton Exchange Membrane Fuel Cell, was utilized in order to explore the effect of (more)

Garcia Navarro, J.C.

2014-01-01T23:59:59.000Z

75

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.

76

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.

77

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.

78

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

79

Model documentation renewable fuels module of the National Energy Modeling System  

SciTech Connect (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

80

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).

Note: This page contains sample records for the topic "fuels module assumption" 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 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

82

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

SciTech Connect (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

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 (OSTI)

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

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.

85

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

86

Model documentation renewable fuels module of the National Energy Modeling System  

SciTech Connect (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

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

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

SciTech Connect (OSTI)

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

89

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.

90

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

91

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.

92

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.

93

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.

94

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

95

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

96

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].

97

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

98

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).

99

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.

100

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

Note: This page contains sample records for the topic "fuels module assumption" 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

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

102

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),

103

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

104

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.

105

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

106

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

107

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.

108

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

109

Integrating Multiple Solid Oxide Fuel Cell Modules* Burak Ozpineci1  

E-Print Network [OSTI]

than traditional generators even though they still have an important level of greenhouse gas (CO2 for more than a century. Today, as conventional fossil energy supplies, such as oil, coal and natural gas of Energy's Solid-State Energy Conversion Alliance (SECA) program [3] is targeting solid oxide fuel cell

Tolbert, Leon M.

110

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. . . . . . . . . . . . .

111

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

112

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

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

113

Key Assumptions Policy Issues  

E-Print Network [OSTI]

11/13/2014 1 Key Assumptions and Policy Issues RAAC Steering Committee November 17, 2014 Portland Supply Limitations 8 Withi h B l i8. Within-hour Balancing 9. Capacity and Energy Values for Wind/Solar t b it d d li d· Thermal: must be sited and licensed · Wind/solar: must be sited and licensed · EE

114

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).

115

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.

116

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

117

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

118

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

119

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

120

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

SciTech Connect (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 assumption" 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

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.

122

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

123

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.

124

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

125

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.

126

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).

127

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

128

Section 25: Future State Assumptions  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

the Compliance Certification Application (CCA), Chapter 6.0, Section 6.2 and Appendices SCR and MASS (U.S. DOE 1996). Many of these future state assumptions were derived from the...

129

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

SciTech Connect (OSTI)

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

130

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

Broader source: Energy.gov [DOE]

Presented at the Department of Energy Fuel Cell Projects Kickoff Meeting, September 1 October 1, 2009

131

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.

132

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

133

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.

134

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).

135

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).

136

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).

137

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).

138

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).

139

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

140

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.

Note: This page contains sample records for the topic "fuels module assumption" 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

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

142

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

143

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

144

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

145

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,

146

NEMS Freight Transportation Module Improvement Study  

Reports and Publications (EIA)

The U.S. Energy Information Administration (EIA) contracted with IHS Global, Inc. (IHS) to analyze the relationship between the value of industrial output, physical output, and freight movement in the United States for use in updating analytic assumptions and modeling structure within the National Energy Modeling System (NEMS) freight transportation module, including forecasting methodologies and processes to identify possible alternative approaches that would improve multi-modal freight flow and fuel consumption estimation.

2015-01-01T23:59:59.000Z

147

Microsoft PowerPoint - Module 7a - TRISO Fuel Design, Properties...  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

HTGRs The TRISO-coated Fuel Particle is Fundamental to HTGRs Pyrolytic Carbon Silicon Carbide (SiC) y o yt c Ca bo Kernel Porous Carbon Buffer But different HTGRs have different...

148

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

SciTech Connect (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

149

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

150

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

151

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

152

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

153

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

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

154

Fuels  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

155

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

156

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

157

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

158

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

159

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

160

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

Note: This page contains sample records for the topic "fuels module assumption" 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

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

162

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.

163

Fuel-optimal Earth-Mars trajectories using low-thrust exhaust-modulated plasma propulsion  

E-Print Network [OSTI]

relerence frames Lx', y', r'I are different for the Earth and Mars references. The substitutions for the second-order derivatives required in the 27 differential equations are given by 2 VIM ISI CCS M + RM RM RM (2. 64) V V sin AM + RM cosltlM ( RM.... Characteristics of the Plasma Propulsion. . Equations of Motion. III NECESSARY CONDITIONS OF OPTIMALITY?. . . 14 15 16 30 Optimal Control Theory. Necessary Conditions of a Fuel-Optimal Earth-Mars Trajectory with Low-Thrust Plasma Propulsion...

Nah, Ren Sang

2012-06-07T23:59:59.000Z

164

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.

165

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.

166

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.

167

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

168

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

169

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.

170

Climate Action Planning Tool Formulas and Assumptions  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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.

171

Diversion assumptions for high-powered research reactors  

SciTech Connect (OSTI)

This study deals with diversion assumptions for high-powered research reactors -- specifically, MTR fuel; pool- or tank-type research reactors with light-water moderator; and water, beryllium, or graphite reflectors, and which have a power level of 25 MW(t) or more. The objective is to provide assistance to the IAEA in documentation of criteria and inspection observables related to undeclared plutonium production in the reactors described above, including: criteria for undeclared plutonium production, necessary design information for implementation of these criteria, verification guidelines including neutron physics and heat transfer, and safeguards measures to facilitate the detection of undeclared plutonium production at large research reactors.

Binford, F.T.

1984-01-01T23:59:59.000Z

172

Alternative Fuels Data Center: Petroleum Reduction Planning Tool  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

173

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

174

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

175

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.

176

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

177

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.

178

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.

179

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

180

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).

Note: This page contains sample records for the topic "fuels module assumption" 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

Renewable Fuels Module This  

Gasoline and Diesel Fuel Update (EIA)

or other natural resource factors, as the best sites are utilized, (2) increasing cost of upgrading existing local and network distribution and transmission lines to accommodate...

182

Liquid Fuels Market Module  

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

In order to account for ultra-low-sulfur diesel (ULSD) regulations related to Clean Air Act Amendments of 1990 (CAAA90), ultra- low-sulfur diesel is differentiated from other...

183

Preliminary Assumptions for Natural Gas Peaking  

E-Print Network [OSTI]

Preliminary Assumptions for Natural Gas Peaking Technologies Gillian Charles and Steve Simmons GRAC, Reciprocating Engines Next steps 2 #12;Definitions Baseload Energy: power generated (or conserved) across a period of time to serve system demands for electricity Peaking Capacity: capability of power generating

184

Preliminary Assumptions for Natural Gas Peaking  

E-Print Network [OSTI]

Preliminary Assumptions for Natural Gas Peaking Technologies Gillian Charles GRAC 2/27/14 #12;Today Vernon, WA PSE Klamath Generation Peakers June 2002 (2) 54 MW P&W FT8 Twin- pac 95 MW Klamath, OR IPP; winter-only PPA w/ PSE Dave Gates Generating Station Jan 2011 (3) P&W SWIFTPAC 150 MW Anaconda, MT North

185

Empirically Revisiting the Test Independence Assumption  

E-Print Network [OSTI]

Empirically Revisiting the Test Independence Assumption Sai Zhang, Darioush Jalali, Jochen Wuttke}@cs.washington.edu ABSTRACT In a test suite, all the test cases should be independent: no test should affect any other test's result, and running the tests in any order should produce the same test results. Techniques such as test

Ernst, Michael

186

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.

187

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

188

Hydrogen Fuel Cell Engines and Related Technologies Course Manual...  

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

Module 10: Maintenance and Fueling Facility Guidelines Module 11: Glossary and Conversions Home About the Fuel Cell Technologies Office Hydrogen Production Hydrogen Delivery...

189

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

190

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

191

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

192

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

SciTech Connect (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

193

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).

194

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.

195

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.

196

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.

197

Integrated Module Heat Exchanger | Department of Energy  

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

Module Heat Exchanger Integrated Module Heat Exchanger 2012 DOE Hydrogen and Fuel Cells Program and Vehicle Technologies Program Annual Merit Review and Peer Evaluation Meeting...

198

Nuclear fuel scoping: implementation of a four node per assembly algorithm as the neutronic module for microscope  

E-Print Network [OSTI]

, . APPENDIX B INPUT FOR TEST CASES . SAMPLE INPUT FOR ONE NODE PER ASSEMBLY. . . . SAMPLE INPUT FOR FOUR NODES PER ASSEMBLY. . . APPENDIX C OUTPUT FOR TEST CASES SAMPLE OUTPUT FOR ONE NODE PER ASSEMBLY. . . SAMPLE OUTPUT FOR FOUR NODES PER ASSEMBLY... on which to simulate and test out some of his ideas or intuitions regarding ways of enhancing fuel procurement and bumup. It allows him to easily and cheaply experiment with the decision variables associated with fuel procurement and burnup, and to see...

Shofolu, Babatunde Olayemi

2012-06-07T23:59:59.000Z

199

Thermal Modeling Studies for Active Storage Modules in the Calvert Cliffs ISFSI  

SciTech Connect (OSTI)

Temperature measurements obtained for two storage modules in the Calvert Cliffs Nuclear Power Stations Independent Spent Fuel Storage Installation (ISFSI) as part of the Used Fuel Disposition Campaign of the Department of Energy (DOE) were used to perform validation and sensitivity studies on detailed computational fluid dynamics (CFD) models of the concrete storage modules, including the dry storage canister within the modules. The storage modules in the Calvert Cliffs Nuclear Power Stations ISFSI are a site-specific version of the standard NUHOMS HSM. The two modules inspected each contained a 24P DSC loaded with 24 CE 14x14 spent fuel assemblies. The thermal analysis was performed using the STAR-CCM+ package, and the models developed for the specific ISFSI modules yielded temperature predictions in actual storage conditions for the concrete structure, the DSC and its contents, including preliminary estimates of fuel cladding temperatures for the used nuclear fuel. The results of this work demonstrate that existing CFD modeling tools can be used to obtain reasonable and accurate detailed representations of spent fuel storage systems with realistic decay heat loadings when the model omits specific conservatisms and bounding assumptions normally used in design-basis and safety-basis calculations. This paper presents sensitivity studies on modeling detail (for the storage module and the DSC), boundary conditions, and decay heat load, to evaluate the effect of the modeling approach on predicted temperatures and temperature distributions. Because nearly all degradation mechanisms for materials and structures comprising dry storage and transportation systems are dependent on temperature, accurate characterization of local temperatures and temperature gradients that the various components of these systems will experience over the entire storage period has been identified as a primary requirement for evaluation of very long term storage of used nuclear fuel.

Adkins, Harold E.; Fort, James A.; Suffield, Sarah R.; Cuta, Judith M.; Collins, Brian A.

2013-06-14T23:59:59.000Z

200

Natural Gas Transmission and Distribution Module  

Gasoline and Diesel Fuel Update (EIA)

U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Natural Gas Transmission and Distribution Module The NEMS Natural Gas Transmission and...

Note: This page contains sample records for the topic "fuels module assumption" 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

Natural Gas Transmission and Distribution Module  

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

31, 2012, Washington, DC Major assumption changes for AEO2013 Oil and Gas Working Group Natural Gas Transmission and Distribution Module DRAFT WORKING GROUP PRESENTATION DO NOT...

202

LES and experimental studies of cold and reacting flow in a swirled partially premixed burner with and without fuel modulation  

SciTech Connect (OSTI)

In devices where air and fuel are injected separately, combustion processes are influenced by oscillations of the air flow rate but may also be sensitive to fluctuations of the fuel flow rate entering the chamber. This paper describes a joint experimental and numerical study of the mechanisms controlling the response of a swirled complex-geometry combustor burning natural gas and air. The flow is first characterized without combustion and LDV results are compared to large eddy simulation (LES) data. The nonpulsated reacting regime is then studied and characterized in terms of the heat release field. Finally the fuel flow rate is pulsated at several amplitudes and the response of the chamber is analyzed using phase-locked averaging and acoustic analysis. Results show that LES and acoustic analysis predict the flame dynamics in this complex configuration with accuracy when heat losses (radiation and convection) are accounted for. (author)

Sengissen, A.X. [CERFACS, 42 Avenue G. Coriolis, 31057 Toulouse cedex (France); Van Kampen, J.F.; Huls, R.A.; Stoffels, G.G.M.; Kok, J.B.W. [University of Twente, Faculty of Engineering, 7500 AE Enschede (Netherlands); Poinsot, T.J. [CERFACS, 42 Avenue G. Coriolis, 31057 Toulouse cedex (France); IMFT, Avenue C. Soula, 31400 Toulouse (France)

2007-07-15T23:59:59.000Z

203

Manufacturing Energy and Carbon Footprint Definitions and Assumptions, October 2012  

Broader source: Energy.gov [DOE]

Definitions of parameters and table of assumptions for the Manufacturing Energy and Carbon Footprint

204

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

205

Preliminary Thermal Modeling of HI-STORM 100 Storage Modules at Diablo Canyon Power Plant ISFSI  

SciTech Connect (OSTI)

Thermal analysis is being undertaken at Pacific Northwest National Laboratory (PNNL) in support of inspections of selected storage modules at various locations around the United States, as part of the Used Fuel Disposition Campaign of the U.S. Department of Energy, Office of Nuclear Energy (DOE-NE) Fuel Cycle Research and Development. This report documents pre-inspection predictions of temperatures for two modules at the Diablo Canyon Power Plant ISFSI identified as candidates for inspection. These are HI-STORM 100 modules of a site-specific design for storing PWR 17x17 fuel in MPC-32 canisters. The temperature predictions reported in this document were obtained with detailed COBRA-SFS models of these storage systems, with the following boundary conditions and assumptions. storage module overpack configuration based on FSAR documentation of HI-STORM100S-218, Version B; due to unavailability of site-specific design data for Diablo Canyon ISFSI modules Individual assembly and total decay heat loadings for each canister, based on at-loading values provided by PG&E, aged to time of inspection using ORIGEN modeling o Special Note: there is an inherent conservatism of unquantified magnitude informally estimated as up to approximately 20% -- in the utility-supplied values for at-loading assembly decay heat values Axial decay heat distributions based on a bounding generic profile for PWR fuel. Axial location of beginning of fuel assumed same as WE 17x17 OFA fuel, due to unavailability of specific data for WE17x17 STD and WE 17x17 Vantage 5 fuel designs Ambient conditions of still air at 50F (10C) assumed for base-case evaluations o Wind conditions at the Diablo Canyon site are unquantified, due to unavailability of site meteorological data o additional still-air evaluations performed at 70F (21C), 60F (16C), and 40F (4C), to cover a range of possible conditions at the time of the inspection. (Calculations were also performed at 80F (27C), for comparison with design basis assumptions.) All calculations are for steady-state conditions, on the assumption that the surfaces of the module that are accessible for temperature measurements during the inspection will tend to follow ambient temperature changes relatively closely. Comparisons to the results of the inspections, and post-inspection evaluations of temperature measurements obtained in the specific modules, will be documented in a separate follow-on report, to be issued in a timely manner after the inspection has been performed.

Cuta, Judith M.; Adkins, Harold E.

2014-04-17T23:59:59.000Z

206

Fuel Cell Power Plants Renewable and Waste Fuels  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

207

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,

208

2010 Manufacturing Energy and Carbon Footprints: Definitions and Assumptions  

Broader source: Energy.gov [DOE]

This 13-page document provides definitions and assumptions used in the Manufacturing Energy and Carbon Footprints (MECS 2010)

209

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

210

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

211

Life-cycle analysis of alternative aviation fuels in GREET  

SciTech Connect (OSTI)

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

212

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.

213

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

214

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

215

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

216

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

217

MONITORED GEOLOGIC REPOSITORY LIFE CYCLE COST ESTIMATE ASSUMPTIONS DOCUMENT  

SciTech Connect (OSTI)

The purpose of this assumptions document is to provide general scope, strategy, technical basis, schedule and cost assumptions for the Monitored Geologic Repository (MGR) life cycle cost (LCC) estimate and schedule update incorporating information from the Viability Assessment (VA) , License Application Design Selection (LADS), 1999 Update to the Total System Life Cycle Cost (TSLCC) estimate and from other related and updated information. This document is intended to generally follow the assumptions outlined in the previous MGR cost estimates and as further prescribed by DOE guidance.

R.E. Sweeney

2001-02-08T23:59:59.000Z

218

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

219

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

220

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

Note: This page contains sample records for the topic "fuels module assumption" 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

Diversion assumptions for high-powered research reactors. ISPO C-50 Phase 1  

SciTech Connect (OSTI)

This study deals with diversion assumptions for high-powered research reactors -- specifically, MTR fuel; pool- or tank-type research reactors with light-water moderator; and water, beryllium, or graphite reflectors, and which have a power level of 25 MW(t) or more. The objective is to provide assistance to the IAEA in documentation of criteria and inspection observables related to undeclared plutonium production in the reactors described above, including: criteria for undeclared plutonium production, necessary design information for implementation of these criteria, verification guidelines including neutron physics and heat transfer, and safeguards measures to facilitate the detection of undeclared plutonium production at large research reactors.

Binford, F.T.

1984-01-01T23:59:59.000Z

222

Idaho National Engineering Laboratory installation roadmap assumptions document. Revision 1  

SciTech Connect (OSTI)

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

223

Manufacturing Energy and Carbon Footprint Definitions and Assumptions...  

Energy Savers [EERE]

The age of the boiler, boiler size, maintenance practices, and fuel type are important factors. Power generation losses vary depending on whether cogeneration is employed (systems...

224

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

225

COMPARING ALASKA'S OIL PRODUCTION TAXES: INCENTIVES AND ASSUMPTIONS1  

E-Print Network [OSTI]

1 COMPARING ALASKA'S OIL PRODUCTION TAXES: INCENTIVES AND ASSUMPTIONS1 Matthew Berman In a recent analysis comparing the current oil production tax, More Alaska Production Act (MAPA, also known as SB 21 oil prices, production rates, and costs. He noted that comparative revenues are highly sensitive

Pantaleone, Jim

226

Reasoning by Assumption: Formalisation and Analysis of Human Reasoning Traces  

E-Print Network [OSTI]

for the traces acquired in experiments undertaken. 1 Introduction Practical reasoning processes are often not limited to single reasoning steps, but extend to traces or trajectories of a number of interrelated by assumption'. This (non-deductive) practical reasoning pattern in- volves a number of interrelated reasoning

Treur, Jan

227

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

228

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

229

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).

230

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

231

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

Annual Energy Outlook 2013 [U.S. Energy Information Administration (EIA)]

by the U.S. Environmental Protection Agency (EPA) in December 2011; the Cross-State Air Pollution Rule (CSAPR) 4 as finalized by the EPA in July 2011; the new fuel...

232

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.

233

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

234

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":""}]}

235

PROJECT MANGEMENT PLAN EXAMPLES Policy & Operational Decisions, Assumptions  

Broader source: Energy.gov (indexed) [DOE]

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.

236

Cost and Performance Assumptions for Modeling Electricity Generation Technologies  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

237

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.

238

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.

239

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.

240

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.

Note: This page contains sample records for the topic "fuels module assumption" 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

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).

242

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

243

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

244

Ecological Modelling 180 (2004) 135151 Simulating forest fuel and fire risk dynamics across  

E-Print Network [OSTI]

fuel module tracks fine fuel, coarse fuel and live fuel for each cell on a landscape. Fine fuel age (the oldest age cohorts) in combination with disturbance history. Live fuels, also called canopyEcological Modelling 180 (2004) 135­151 Simulating forest fuel and fire risk dynamics across

He, Hong S.

245

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

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

246

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

247

PDSF Modules  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

248

The contour method cutting assumption: error minimization and correction  

SciTech Connect (OSTI)

The recently developed contour method can measure 2-D, cross-sectional residual-stress map. A part is cut in two using a precise and low-stress cutting technique such as electric discharge machining. The contours of the new surfaces created by the cut, which will not be flat if residual stresses are relaxed by the cutting, are then measured and used to calculate the original residual stresses. The precise nature of the assumption about the cut is presented theoretically and is evaluated experimentally. Simply assuming a flat cut is overly restrictive and misleading. The critical assumption is that the width of the cut, when measured in the original, undeformed configuration of the body is constant. Stresses at the cut tip during cutting cause the material to deform, which causes errors. The effect of such cutting errors on the measured stresses is presented. The important parameters are quantified. Experimental procedures for minimizing these errors are presented. An iterative finite element procedure to correct for the errors is also presented. The correction procedure is demonstrated on experimental data from a steel beam that was plastically bent to put in a known profile of residual stresses.

Prime, Michael B [Los Alamos National Laboratory; Kastengren, Alan L [ANL

2010-01-01T23:59:59.000Z

249

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

250

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

251

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

252

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.

253

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

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

254

What fuel for a rocket?  

E-Print Network [OSTI]

Elementary concepts from general physics and thermodynamics have been used to analyze rocket propulsion. Making some reasonable assumptions, an expression for the exit velocity of the gases is found. From that expression one can conclude what are the desired properties for a rocket fuel.

E. N. Miranda

2012-08-13T23:59:59.000Z

255

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

256

SOLID OXIDE PLANAR AND TUBULAR SOLID OXIDE FUEL  

E-Print Network [OSTI]

SOLID OXIDE PLANAR AND TUBULAR SOLID OXIDE FUEL CELLS Dynamic Simulation Approach Modular Approach · Parallel planes: PSOFC · Other: combustor, reformer Solid Oxide Fuel Cell Electrochemistry Cell Reactions · Slow pressure transients #12;Fuel Cell Assumptions · H2 electrochemically oxidized only · CO consumed

Mease, Kenneth D.

257

FULL FUEL CYCLE ASSESSMENT WELL TO WHEELS ENERGY INPUTS,  

E-Print Network [OSTI]

, greenhouse gas (GHG) emissions, criteria pollutant emissions, air toxics emissions, and multimedia impacts on a full fuel cycle basis for alternative-fueled vehicles is important when assessing the overall control, and assumptions regarding feedstock sources and fuel production conversion efficiency

258

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

259

1. What are positive economical impacts of improving the fuel mileage standards? 2. What is the current fuel mileage standard for the United States?  

E-Print Network [OSTI]

Bowen's money saved = $1091 * 0.90 = $982 A4. Assumptions: Fuel Price is $2.00 per gallon Fuel cost1. What are positive economical impacts of improving the fuel mileage standards? 2. What is the current fuel mileage standard for the United States? 3. If Dr Bowen rides his bike 90% of the year, how

Bowen, James D.

260

Alternative Fuels Data Center: Alternative Fuel and Fueling Infrastructure  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

Note: This page contains sample records for the topic "fuels module assumption" 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

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

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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...

262

Diesel and Biodiesel Fuel Spray Simulations  

Science Journals Connector (OSTI)

Diesel and Biodiesel Fuel Spray Simulations ... That deviates from general assumptions and is probably the consequence of the large nozzle diameter. ... Numerous trials gave the best results for the pretuned C1, C2, and C3 values using following parameters and appropriate coefficients in the following expressions: where ?f is fuel density [kg/m3], ?f is fuel viscosity [mPa s], ?f is fuel surface tension [N/mm], tinj stands for injection time [ms], pave is average injection pressure [MPa], sq = pave/pmax (squarness), Qc represents fueling [mm3/cycle], and n is pump speed [1/min]. ...

Primoz Pogorevc; Breda Kegl; Leopold Skerget

2008-01-12T23:59:59.000Z

263

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

264

Module Configuration  

DOE Patents [OSTI]

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

265

On the self-similarity assumption in dynamic models for large eddy simulations  

E-Print Network [OSTI]

that the present formulation of the DP is usually incompatible with its under- lying self-similarity assumption SSAOn the self-similarity assumption in dynamic models for large eddy simulations Daniele Carati eddy simulations and their underlying self-similarity assumption is discussed. The interpretation

Van Den Eijnden, Eric

266

Alternative Fuels Data Center: Alternative Fuel Use and Alternative Fuel  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

267

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

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

268

Uniqueness of magnetotomography for fuel cells and fuel cell stacks  

Science Journals Connector (OSTI)

The criterion for the applicability of any tomographic method is its ability to construct the desired inner structure of a system from external measurements, i.e. to solve the inverse problem. Magnetotomography applied to fuel cells and fuel cell stacks aims at determining the inner current densities from measurements of the external magnetic field. This is an interesting idea since in those systems the inner electric current densities are large, several hundred mA per cm2and therefore relatively high external magnetic fields can be expected. Still the question remains how uniquely the inverse problem can be solved. Here we present a proof that by exploiting Maxwell's equations extensively the inverse problem of magnetotomography becomes unique under rather mild assumptions and we show that these assumptions are fulfilled in fuel cells and fuel cell stacks. Moreover, our proof holds true for any other device fulfilling the assumptions listed here. Admittedly, our proof has one caveat: it does not contain an estimate of the precision requirements the measurements need to fulfil for enabling reconstruction of the inner current densities from external magnetic fields.

H Lustfeld; J Hirschfeld; M Reiel; B Steffen

2009-01-01T23:59:59.000Z

269

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

270

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

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

271

Fuel System and Fuel Measurement  

Science Journals Connector (OSTI)

Fuel management provides optimal solutions to reduce fuel consumption. Merchant vessels, such as container ships, drive at a reduced speed to save fuel since the reduction of the speed from...?1 lowers consumption

Michael Palocz-Andresen

2013-01-01T23:59:59.000Z

272

New EPA Fuel Economy and Environment Label - Gasoline Vehicles  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

273

Alternative Fuels Data Center: Alternative Fuel and Special Fuel  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

274

Alternative Fuels Data Center: Alternative Fuel Motor Carrier Fuel Tax  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

275

Microstructured Hydrogen Fuel Cells  

Science Journals Connector (OSTI)

Micro fuel cells ; Polymer electrolyte membrane fuel cells ; Proton exchange membrane fuel cells ...

Luc G. Frechette

2014-05-01T23:59:59.000Z

276

Alternative Fuels Data Center: Alternative Fuel Definition  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

277

Alternative Fuels Data Center: Ethanol Fueling Stations  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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.

278

Alternative Fuels Data Center: Alternative Fuel Promotion  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

279

Alternative Fuels Data Center: Hydrogen Fueling Stations  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

280

Alternative Fuels Data Center: Biodiesel Fueling Stations  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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.

Note: This page contains sample records for the topic "fuels module assumption" 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

Hydrogen Consumption Measurement Research Platform for Fuel Cell Vehicles  

Science Journals Connector (OSTI)

Hydrogen consumption measurement research platform is designed for fuel economy test of the proton exchange membrane fuel cell vehicle (PEM FCV). Hardware is constructed with industrial PC (IPC), field bus data acquisition module and device control module. ... Keywords: Hydrogen Consumption Measuremen, LabVIEW, Data Acquisition

Fang Maodong; Chen Mingjie; Lu Qingchun; Jin Zhenhua

2010-06-01T23:59:59.000Z

282

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

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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...

283

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

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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...

284

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

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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...

285

Alternative Fuels Data Center: Alternative Fuel and Alternative Fuel  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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...

286

Alternative Fuels Data Center: Alternative Fuel and Alternative Fuel  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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...

287

OIKOS 101: 499504, 2003 Do seedlings in gaps interact? A field test of assumptions in ESS  

E-Print Network [OSTI]

OIKOS 101: 499­504, 2003 Do seedlings in gaps interact? A field test of assumptions in ESS seed seedlings in gaps interact? A field test of assumptions in ESS seed size models. ­ Oikos 101: 499­504. ESS for the occupancy of `safe sites' or vegetation gaps. If mortality rates are high and/or frequency-independent, ESS

Silvertown, Jonathan

288

Granular Matter 4(3) (2002) How good is the equipartition assumption for the transport  

E-Print Network [OSTI]

Granular Matter 4(3) (2002) How good is the equipartition assumption for the transport properties of a granular mixture? Meheboob Alam (1) , Stefan Luding (1;2) ? Abstract Kinetic-theory, with the assumption of equipar- tition of granular energy, suggests that the pressure and viscosity of a granular mixture vary

Luding, Stefan

289

Impact of assumption of log-normal distribution on monthly rainfall estimation from TMI  

E-Print Network [OSTI]

The log-normal assumption for the distribution of the rain rates used for the estimation of monthly rain totals proposed in Wilheit et al 1991 was examined. Since the log-normal assumption was originally used for the SSM/I, it is now necessary to re...

Lee, Dong Heon

2012-06-07T23:59:59.000Z

290

A new scenario framework for climate change research: The concept of Shared Climate Policy Assumptions  

SciTech Connect (OSTI)

The paper presents the concept of shared climate policy assumptions as an important element of the new scenario framework. Shared climate policy assumptions capture key climate policy dimensions such as the type and scale of mitigation and adaptation measures. They are not specified in the socio-economic reference pathways, and therefore introduce an important third dimension to the scenario matrix architecture. Climate policy assumptions will have to be made in any climate policy scenario, and can have a significant impact on the scenario description. We conclude that a meaningful set of shared climate policy assumptions is useful for grouping individual climate policy analyses and facilitating their comparison. Shared climate policy assumptions should be designed to be policy relevant, and as a set to be broad enough to allow a comprehensive exploration of the climate change scenario space.

Kriegler, Elmar; Edmonds, James A.; Hallegatte, Stephane; Ebi, Kristie L.; Kram, Tom; Riahi, Keywan; Winkler, Harald; Van Vuuren, Detlef

2014-04-01T23:59:59.000Z

291

GIZ Sourcebook Module 7a: Gender and Urban Transport: Smart and...  

Open Energy Info (EERE)

Global Related Tools Key Mobility Challenges in Indian Cities Alternative Fueling Station Locator GIZ Sourcebook Module 4c: Two and Three Wheelers ... further results Find...

292

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

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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...

293

Synthetic Fuel  

ScienceCinema (OSTI)

Two global energy priorities today are finding environmentally friendly alternatives to fossil fuels, and reducing greenhouse gass Two global energy priorities today are finding environmentally friendly alternatives to fossil fuels, and reducing greenhous

Idaho National Laboratory - Steve Herring, Jim O'Brien, Carl Stoots

2010-01-08T23:59:59.000Z

294

Moldy Assumptions  

E-Print Network [OSTI]

sustainability movements. 2 Despite these noble intentions, using human responsibility as a base for architecture

Heully, Gustave Paul

2012-01-01T23:59:59.000Z

295

Letter to the editor The bio-fuel debate and fossil energy use in palm oil  

E-Print Network [OSTI]

Letter to the editor The bio-fuel debate and fossil energy use in palm oil production: a critique-fuels based on palm oil to re- duce greenhouse gas emissions, due account should be taken of carbon emissions fuel use in palm oil pro- duction, making a number of assumptions that I believe to be incorrect

296

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

SciTech Connect (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

297

Alternative Fuels Data Center: Alternative Fueling Infrastructure  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

298

Alternative Fuels Data Center: Emerging Fuels  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

299

Fuel Cells  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

300

International Stationary Fuel Cell Demonstration  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

Note: This page contains sample records for the topic "fuels module assumption" 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

EFFECT OF FUEL IMPURITIES ON FUEL CELL PERFORMANCE AND DURABILITY  

SciTech Connect (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

302

CBE UFAD cost analysis tool: Life cycle cost model, issues and assumptions  

E-Print Network [OSTI]

Building Maintenance and Repair Cost Reference. WhitestoneJ. Wallis and H. Lin. 2008. CBE UFAD Cost Analysis Tool:UFAD First Cost Model, Issues and Assumptions. Center for

Webster, Tom; Benedek, Corinne; Bauman, Fred

2008-01-01T23:59:59.000Z

303

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

Science Journals Connector (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

304

Behavioral Assumptions Underlying California Residential Sector Energy Efficiency Programs (2009 CIEE Report)  

Broader source: Energy.gov [DOE]

This paper examines the behavioral assumptions that underlie Californias residential sector energy efficiency programs and recommends improvements that will help to advance the states ambitious greenhouse gas reduction goals.

305

Length measurement of a moving rod by a single observer without assumptions concerning its magnitude  

E-Print Network [OSTI]

We extend the results presented by Weinstein concerning the measurement of the length of a moving rod by a single observer, without making assumptions concerning the distance between the moving rod and the observer who measures its length.

Bernhard Rothenstein; Ioan Damian

2005-07-03T23:59:59.000Z

306

Assumptions about the U.S., the EU, NATO, and their Impact on the Transatlantic Agenda  

Science Journals Connector (OSTI)

I propose in this paper to discuss, from an American perspective, the assumptions and assertions that influence the way that I look at foreign policy events at the end of this decade. I will conclude with a fe...

Stanley Sloan

2000-01-01T23:59:59.000Z

307

A REVIEW OF ASSUMPTIONS AND ANALYSIS IN EPRI EA-3409, "HOUSEHOLD APPLIANCE CHOICE: REVISION OF REEPS BEHAVIORAL MODELS"  

E-Print Network [OSTI]

construction costs and fuel prices were used to translatethe model to the data. Fuel Price Expectations EPRl's modelswere based on the actual fuel prices faced by the consumer

Wood, D.J.

2010-01-01T23:59:59.000Z

308

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

E-Print Network [OSTI]

stock, household size, fuel prices and household income.needed by the model. Fuel price projections are implementedand Exogenous Drivers Fuel Prices Income Household Size

Johnson, F.X.

2010-01-01T23:59:59.000Z

309

Low Temperature Fuel Cell and Electrolyzer Balance-of-Plant Manufactur...  

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

(fairly standard) * Batteries or UCs (fairly standard) Fuel Cell Power Module BOP Air Delivery System * Blower Compressor * Currently use off the shelf blowers from a...

310

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

311

Fuel Cells  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

312

Alternative Fuels Data Center: Fuel Prices  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

313

Alternative Fuels Data Center: Alternative Fuel License  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

314

Alternative Fuels Data Center: Alternative Fuel License  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

315

Fuel Cells  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

316

Alternative fuels  

SciTech Connect (OSTI)

This paper presents the preliminary results of a review, of the experiences of Brazil, Canada, and New Zealand, which have implemented programs to encourage the use of alternative motor fuels. It will also discuss the results of a separate completed review of the Department of Energy's (DOE) progress in implementing the Alternative Motor Fuels Act of 1988. The act calls for, among other things, the federal government to use alternative-fueled vehicles in its fleet. The Persian Gulf War, environmental concerns, and the administration's National Energy Strategy have greatly heightened interest in the use of alternative fuels in this country.

Not Available

1991-07-01T23:59:59.000Z

317

Fuel Cells  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

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...

318

DOE Hydrogen and Fuel Cells Program Record 11007: Hydrogen Threshold Cost Calculation  

Broader source: Energy.gov [DOE]

Record 11007 from the U.S. Department of Energy Hydrogen and Fuel Cells Program documents the methodology and assumptions used to calculate the hydrogen threshold cost of $2.00 to $4.00 per gasoline gallon equivalent.

319

Alternative Fuels Data Center: Electricity Fuel Basics  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

320

Alternative Fuels Data Center: Alternative Fuel Definition  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

Note: This page contains sample records for the topic "fuels module assumption" 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 Fuels Tax  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

322

Alternative Fuels Data Center: Renewable Fuel Standard  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

323

Alternative Fuels Data Center: Alternative Fuels Tax  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

324

Alternative Fuels Data Center: Alternative Fuel Loans  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

325

Alternative Fuels Data Center: Alternative Fuels Tax  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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,

326

Alternative Fuels Data Center: Alternative Fuels Tax  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

327

Alternative Fuels Data Center: Alternative Fuel Tax  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

328

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

SciTech Connect (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

329

Fuel Research  

Science Journals Connector (OSTI)

... FUEL research was discussed by Sir Harry McGowan, who succeeds Sir William Larke as president of the Institute of Fuel, in ... has a ragged front, and new knowledge is continually changing relative national positions. Sir Harry McGowan referred to the domestic use of raw coal, which is still preferred to ...

1934-11-24T23:59:59.000Z

330

Model documentation coal market module of the National Energy Modeling System  

SciTech Connect (OSTI)

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).

NONE

1995-03-01T23:59:59.000Z

331

Alternative Fuels Data Center: Renewable Fuels Assessment  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

332

Alternative Fuels Data Center: Biodiesel Fuel Basics  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

333

Alternative Fuels Data Center: Renewable Fuel Standard  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

334

Alternative Fuels Data Center: Biodiesel Fuel Use  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

335

Alternative Fuels Data Center: Alternative Fuel Tax  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

336

Alternative Fuels Data Center: Special Fuel Tax  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

337

Alternative Fuels Data Center: Ethanol Fuel Basics  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

338

Alternative Fuels Data Center: Biodiesel Fuel Use  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

339

Alternative Fuels Data Center: Hydrogen Fuel Specifications  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

340

Alternative Fuels Data Center: Flexible Fuel Vehicles  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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.

Note: This page contains sample records for the topic "fuels module assumption" 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

Alternative Fuels Data Center: Alternative Fuel Use  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

342

Alternative Fuels Data Center: Alternative Fuels Tax  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

343

FUEL CELLS SOLID OXIDE FUEL CELLS | Gas Distribution  

Science Journals Connector (OSTI)

A uniform distribution of the reactants over the total available electrode surfaces in solid oxide fuel cells (SOFCs) is a prerequisite for the proper operation of the fuel cell. The gas distribution plays a dominant role not only in the current density distribution but also in the temperature distribution over the cell areas and in the stack and modules. Several transport mechanisms for mass transport occurring in the SOFC are introduced and discussed. General flow configurations and structures for the gas distribution at three different levels, i.e., stack/module, cell/tube, and electrode/electrolyte, are discussed for both tubular and planar type cells and illustrated with examples of concentration and temperature profiles.

L.G.J. de Haart; M. Spiller

2009-01-01T23:59:59.000Z

344

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

SciTech Connect (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

345

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

346

California Fuel Cell Partnership: Alternative Fuels Research  

Broader source: Energy.gov [DOE]

This presentation by Chris White of the California Fuel Cell Partnership provides information about alternative fuels research.

347

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

348

Fuel Processing Valri Lightner  

E-Print Network [OSTI]

, ORNL, NETL #12;Accomplishments · Demonstrated in the lab an advanced fuel flexible fuel processor

349

TOB Module Assembly  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

350

Fuel cell based battery-less ups system  

E-Print Network [OSTI]

emerged as one of the most promising sources for both portable and stationary applications. In this thesis, a new battery less UPS system configuration powered by fuel cell is discussed. The proposed topology utilizes a standard offline UPS module...

Venkatagiri Chellappan, Mirunalini

2008-10-10T23:59:59.000Z

351

Alternative Fuels Data Center: Renewable Fuels Mandate  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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,

352

Alternative Fuels Data Center: Renewable Fuels Promotion  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

353

Alternative Fuels Data Center: Fuel Quality Standards  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

354

Alternative Fuels Data Center: Renewable Fuels Mandate  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

355

Alternative Fuels Data Center: Alternative Fuels Promotion  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

356

Alternative Fuels Data Center: Alternative Fuel Tax  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

357

Alternative Fuels Data Center: Renewable Fuel Promotion  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

358

Alternative Fuels Data Center: Renewable Fuel Standard  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

359

Alternative Fuels Data Center: Alternative Fuel Tax  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

360

Alternative Fuels Data Center: Propane Fueling Stations  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

Note: This page contains sample records for the topic "fuels module assumption" 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

Alternative Fuels Data Center: Alternative Fuel Study  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

362

Campus Recreation at Sonoma State University RELEASE OF LIABILITY -PROMISE NOT TO SUE ASSUMPTION OF  

E-Print Network [OSTI]

Campus Recreation at Sonoma State University RELEASE OF LIABILITY - PROMISE NOT TO SUE ASSUMPTION OF RISK - AGREEMENT TO PAY CLAIMS PERMISSION TO USE VISUAL LIKENESS Activities: a) USE OF SSU RECREATION RECREATION PROGRAMS. Effective Locations and Time Periods: a) RECREATION CENTER: DURING HOURS OF OPERATION

Ravikumar, B.

363

Cognitive Assessment Models with Few Assumptions, and Connections with Nonparametric IRT  

E-Print Network [OSTI]

Cognitive Assessment Models with Few Assumptions, and Connections with Nonparametric IRT Brian of the monotonicity conditions discussed in Section 4. #12;Abstract In recent years, as cognitive theories of learning" on student achievement relative to theory-driven lists of examinee skills, beliefs and other cognitive

Junker, Brian

364

Draft -F. Nicoud 1 About the zero Mach number assumption in  

E-Print Network [OSTI]

Draft - F. Nicoud 1 About the zero Mach number assumption in the calculation of thermoacoustic as the the flame forcing ('Rayleigh') term. Besides, the net effect of the non zero Mach number terms the frequency of oscillation and growth rate are modified when the Mach number is not zero. It is demonstrated

Nicoud, Franck

365

Models of transcription factor binding: Sensitivity of activation functions to model assumptions  

E-Print Network [OSTI]

on statistical physics, a Markov-chain model and a computational simulation. Comparison of these models suggests for cooperativity. The simulation model suggests that direct interactions between TFs are unlikely to be the main in this contribution, the assumption of the cell being a well stirred reactor makes a qualitative difference

Kent, University of

366

Fuels - Biodiesel  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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.

367

Nuclear Fuels  

Science Journals Connector (OSTI)

The core of a nuclear reactor is composed of a controlled critical configuration of a fissile material, which in strict a sense is the fuel. This fissile material is contained in a matrix, normally a ceramic c...

Rudy J. M. Konings; Thierry Wiss

2011-01-01T23:59:59.000Z

368

Fuel economizer  

SciTech Connect (OSTI)

A fuel economizer device for use with an internal combustion engine fitted with a carburetor is disclosed. The fuel economizer includes a plate member which is mounted between the carburetor and the intake portion of the intake manifold. The plate member further has at least one aperture formed therein. One tube is inserted through the at least one aperture in the plate member. The one tube extends longitudinally in the passage of the intake manifold from the intake portion toward the exit portion thereof. The one tube concentrates the mixture of fuel and air from the carburetor and conveys the mixture of fuel and air to a point adjacent but spaced away from the inlet port of the internal combustion engine.

Zwierzelewski, V.F.

1984-06-26T23:59:59.000Z

369

Alternative Fuels Data Center: Alternative Fuel Definition  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (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

370

SHARP Physics Modules Updated | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

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

371

Certification of alternative aviation fuels and blend components  

SciTech Connect (OSTI)

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

372

Stationary Fuel Cells: Overview of Hydrogen and Fuel Cell Activities...  

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

Stationary Fuel Cells: Overview of Hydrogen and Fuel Cell Activities Stationary Fuel Cells: Overview of Hydrogen and Fuel Cell Activities Presentation covers stationary fuel cells...

373

Fuel Cell Technologies Overview: 2011 Fuel Cell Seminar | Department...  

Broader source: Energy.gov (indexed) [DOE]

Fuel Cell Technologies Overview: 2011 Fuel Cell Seminar Fuel Cell Technologies Overview: 2011 Fuel Cell Seminar Presentation by Sunita Satyapal at the Fuel Cell Seminar on November...

374

Fuel Cell Technologies Overview: 2011 Fuel Cell Seminar | Department...  

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

Overview: 2011 Fuel Cell Seminar Fuel Cell Technologies Overview: 2011 Fuel Cell Seminar Presentation by Sunita Satyapal at the Fuel Cell Seminar on November 1, 2011. Fuel Cell...

375

Fuel Processing Valri Lightner  

E-Print Network [OSTI]

of Hydrogen · Fuel Processors for PEM Fuel Cells Nuvera Fuel Cells, Inc. GE Catalytica ANL PNNL University-Board Fuel Processing Barriers $35/kW Fuel Processor $10/kW Fuel Cell Power Systems $45/kW by 2010 BARRIERS · Fuel processor start-up/ transient operation · Durability · Cost · Emissions and environmental issues

376

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

377

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

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

378

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

SciTech Connect (OSTI)

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

379

Alkaline regenerative fuel cell systems for energy storage  

SciTech Connect (OSTI)

This paper presents the results of a preliminary design study of a Regenerative Fuel Cell Energy Storage system for application to future low-earth orbit space missions. This high energy density storage system is based on state-of-the-art alkaline electrolyte cell technology and incorporates dedicated fuel cell and electrolysis cell modules. 11 refs.

Schubert, F.H.; Reid, M.A.; Martin, R.E.

1981-01-01T23:59:59.000Z

380

Unsaturated flow modeling in performance assessments for the Yucca Mountain disposal system for spent nuclear fuel and high-level radioactive waste  

Science Journals Connector (OSTI)

Abstract This paper summarizes the progression of modeling efforts of infiltration, percolation, and seepage conducted between 1984 and 2008 to evaluate feasibility, viability, and assess compliance of a repository in the unsaturated zone for spent nuclear fuel and high-level radioactive waste at Yucca Mountain, Nevada. Scientific understanding of infiltration in a desert environment, unsaturated percolation flux in fractures and matrix of the volcanic tuff, and seepage into an open drift in a thermally perturbed environment was initially lacking in 1984. As understanding of the Yucca Mountain disposal system increased through site characterization and in situ testing, modeling of infiltration, percolation, and seepage evolved from simple assumptions in a single model in 1984 to three modeling modules each based on several detailed process models in 2008. Uncertainty in percolation flux through Yucca Mountain was usually important in explaining the observed uncertainty in performance measures:cumulative release in assessments prior to 1995 and individual dose, thereafter.

Rob P. Rechard; Jens T. Birkholzer; Yu-Shu Wu; Joshua S. Stein; James E. Houseworth

2014-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "fuels module assumption" 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

Reforming of fuel inside fuel cell generator  

DOE Patents [OSTI]

Disclosed is an improved method of reforming a gaseous reformable fuel within a solid oxide fuel cell generator, wherein the solid oxide fuel cell generator has a plurality of individual fuel cells in a refractory container, the fuel cells generating a partially spent fuel stream and a partially spent oxidant stream. The partially spent fuel stream is divided into two streams, spent fuel stream I and spent fuel stream II. Spent fuel stream I is burned with the partially spent oxidant stream inside the refractory container to produce an exhaust stream. The exhaust stream is divided into two streams, exhaust stream I and exhaust stream II, and exhaust stream I is vented. Exhaust stream II is mixed with spent fuel stream II to form a recycle stream. The recycle stream is mixed with the gaseous reformable fuel within the refractory container to form a fuel stream which is supplied to the fuel cells. Also disclosed is an improved apparatus which permits the reforming of a reformable gaseous fuel within such a solid oxide fuel cell generator. The apparatus comprises a mixing chamber within the refractory container, means for diverting a portion of the partially spent fuel stream to the mixing chamber, means for diverting a portion of exhaust gas to the mixing chamber where it is mixed with the portion of the partially spent fuel stream to form a recycle stream, means for injecting the reformable gaseous fuel into the recycle stream, and means for circulating the recycle stream back to the fuel cells.

Grimble, Ralph E. (Finleyville, PA)

1988-01-01T23:59:59.000Z

382

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

motor fuel containing at least 10% alcohol) or alternative fuels whenever feasible and cost effective. DOA must place a list of gasohol and alternative fueling station locations...

383

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

special fuels. Special fuels include compressed and liquefied natural gas, liquefied petroleum gas (propane), hydrogen, and fuel suitable for use in diesel engines. In addition,...

384

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

alternative fuel vehicles (AFVs) capable of operating on natural gas or liquefied petroleum gas (propane), or bi-fuel vehicles capable of operating on conventional fuel or...

385

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Use and Fuel-Efficient Vehicle Requirements State-owned vehicle fleets must implement petroleum displacement plans to increase the use of alternative fuels and fuel-efficient...

386

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

and Special Fuel Definitions The definition of alternative fuel includes liquefied petroleum gas (propane). Special fuel is defined as all combustible gases and liquids that are...

387

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Renewable Fuel Labeling Requirement Biodiesel, biobutanol, and ethanol blend dispensers must be affixed with decals identifying the type of fuel blend. If fuel blends containing...

388

Saving Fuel, Reducing Emissions  

E-Print Network [OSTI]

would in turn lower PHEV fuel costs and make them morestretches from fossil-fuel- powered conventional vehiclesbraking, as do Saving Fuel, Reducing Emissions Making Plug-

Kammen, Daniel M.; Arons, Samuel M.; Lemoine, Derek M.; Hummel, Holmes

2009-01-01T23:59:59.000Z

389

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

and alternative fuel vehicles; promotes the development, sale, distribution, and consumption of alternative fuels; promotes the development and use of alternative fuel vehicles...

390

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

providers to install biofuel fueling facilities. Fueling facilities include storage tanks and fuel pumps dedicated to dispensing E85 and biodiesel blends of 20% (B20). TDOT...

391

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

interest in the qualified property. Renewable fuel is defined as a fuel produced from biomass that is used to replace or reduce conventional fuel use. (Reference Florida Statutes...

392

Alternative Fuel Vehicle Resources  

Broader source: Energy.gov [DOE]

Alternative fuel vehicles use fuel types other than petroleum and include such fuels as electricity, ethanol, biodiesel, natural gas, hydrogen, and propane. Compared to petroleum, these...

393

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Alternative Fuel Grants and Rebates The Arkansas Alternative Fuels Development Program (Program) provides grants to alternative fuel producers, feedstock processors, and...

394

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Fuel Exclusivity Contract Regulation Motor fuel franchise dealers may obtain alternative fuels from a supplier other than a franchise distributor. Any franchise provision that...

395

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Hydrogen Production and Retail Requirements All hydrogen fuel produced and sold in Michigan must meet state fuel quality requirements. Any retailer offering hydrogen fuel for sale...

396

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

that operate using at least 90% alternative fuel. Eligible alternative fuels include electricity, propane, natural gas, or hydrogen fuel. Medium-duty hybrid electric vehicles also...

397

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Fuels Promotion and Information The Center for Alternative Fuels (Center) promotes alternative fuels as viable energy sources in the state. The Center must assess the...

398

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

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 85%...

399

Low Carbon Fuel Standards  

E-Print Network [OSTI]

in 1990. These many alternative-fuel initiatives failed tolow-cost, low-carbon alternative fuels would thrive. Theto introduce low-carbon alternative fuels. Former Federal

Sperling, Dan; Yeh, Sonia

2009-01-01T23:59:59.000Z

400

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Alternative Fuels Labeling Requirement Retailers must display ratings on fueling pumps that are consistent with the percentage by volume of the alternative fuel being dispensed....

Note: This page contains sample records for the topic "fuels module assumption" 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

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

is defined as a renewable transportation fuel, transportation fuel additive, heating oil, or jet fuel that meets the definition of either biodiesel or non-ester renewable...

402

Criticality Calculations for Step?2 GPHS Modules  

Science Journals Connector (OSTI)

The Multi?Mission Radioisotope Thermoelectric Generator (MMRTG) will use an improved version of the General Purpose Heat Source (GPHS) module as its source of thermal power. This new version referred to as the Step?2 GPHS Module has additional and thicker layers of carbon fiber material (Fine Weaved Pierced Fabric) for increased strength over the original GPHS module. The GPHS uses alpha decay of 238 Pu in the oxide form as the primary source of heat and small amounts of other actinides are also present in the oxide fuel. Criticality calculations have been performed by previous researchers on the original version of the GPHS module (Step 0). This paper presents criticality calculations for the present Step?2 version. The Monte Carlo N?Particle eXtended code (MCNPX) was used for these calculations. Numerous configurations of GPHS module arrays surrounded by wet sand and other materials (to reflect the neutrons back into the stack with minimal absorption) were modeled. For geometries with eight GPHS modules (from a single MMRTG) surrounded by wet sand the configuration is extremely sub?critical; k eff is about 0.3. It requires about 1000 GPHS modules (from 125 MMRTGs) in a close?spaced stack to approach criticality ( k eff ?=?1.0) when surrounded by wet sand. The effect of beryllium in the MMRTG was found to be relatively small.

Ronald J. Lipinski; Danielle L. Hensen

2008-01-01T23:59:59.000Z

403

Criticality Calculations for Step-2 GPHS Modules  

SciTech Connect (OSTI)

The Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) will use an improved version of the General Purpose Heat Source (GPHS) module as its source of thermal power. This new version, referred to as the Step-2 GPHS Module, has additional and thicker layers of carbon fiber material (Fine Weaved Pierced Fabric) for increased strength over the original GPHS module. The GPHS uses alpha decay of {sup 238}Pu in the oxide form as the primary source of heat, and small amounts of other actinides are also present in the oxide fuel. Criticality calculations have been performed by previous researchers on the original version of the GPHS module (Step 0). This paper presents criticality calculations for the present Step-2 version. The Monte Carlo N-Particle eXtended code (MCNPX) was used for these calculations. Numerous configurations of GPHS module arrays surrounded by wet sand and other materials (to reflect the neutrons back into the stack with minimal absorption) were modeled. For geometries with eight GPHS modules (from a single MMRTG) surrounded by wet sand, the configuration is extremely sub-critical; k{sub eff} is about 0.3. It requires about 1000 GPHS modules (from 125 MMRTGs) in a close-spaced stack to approach criticality (k{sub eff} = 1.0) when surrounded by wet sand. The effect of beryllium in the MMRTG was found to be relatively small.

Lipinski, Ronald J. [Advanced Nuclear Concepts Department, Sandia National Laboratories, P.O Box 5800, Albuquerque, NM 87185 (United States); Hensen, Danielle L. [Risk and Reliability Department Sandia National Laboratories, P.O Box 5800, Albuquerque, NM 87185 (United States)

2008-01-21T23:59:59.000Z

404

Criticality calculations for Step-2 GPHS modules.  

SciTech Connect (OSTI)

The Multi-Mission Radioisotope Thermoelectric Generator (MMRTG) will use an improved version of the General Purpose Heat Source (GPHS) module as its source of thermal power. This new version, referred to as the Step-2 GPHS Module, has additional and thicker layers of carbon fiber material (Fine Weaved Pierced Fabric) for increased strength over the original GPHS module. The GPHS uses alpha decay of {sup 238}Pu in the oxide form as the primary source of heat, and small amounts of other actinides are also present in the oxide fuel. Criticality calculations have been performed by previous researchers on the original version of the GPHS module (Step 0). This paper presents criticality calculations for the present Step-2 version. The Monte Carlo N-Particle eXtended code (MCNPX) was used for these calculations. Numerous configurations of GPHS module arrays surrounded by wet sand and other materials (to reflect the neutrons back into the stack with minimal absorption) were modeled. For geometries with eight GPHS modules (from a single MMRTG) surrounded by wet sand, the configuration is extremely sub-critical; k{sub eff} is about 0.3. It requires about 1000 GPHS modules (from 125 MMRTGs) in a close-spaced stack to approach criticality (k{sub eff} = 1.0) when surrounded by wet sand. The effect of beryllium in the MMRTG was found to be relatively small.

Hensen, Danielle Lynn; Lipinski, Ronald J.

2007-08-01T23:59:59.000Z

405

Alternative Fuels Data Center: Alternative Fuel Vehicle Acquisition and  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

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

406

Update of the Used Fuel Disposition Campaign Implementation Plan  

SciTech Connect (OSTI)

This Campaign Implementation Plan provides summary level detail describing how the Used Fuel Disposition Campaign (UFDC) supports achievement of the overarching mission and objectives of the Department of Energy Office of Nuclear Energy Fuel Cycle Technologies Program The implementation plan begins with the assumption of target dates that are set out in the January 2013 DOE Strategy for the Management and Disposal of Used Nuclear Fuel and High-Level Radioactive Waste (http://energy.gov/downloads/strategy-management-and-disposal-used-nuclear-fuel-and-high-level-radioactive-waste). These target dates and goals are summarized in section III. This implementation plan will be maintained as a living document and will be updated as needed in response to progress in the Used Fuel Disposition Campaign and the Fuel Cycle Technologies Program.

Jens Birkholzer; Robert MacKinnon; Kevin McMahon; Sylvia Saltzstein; Ken Sorenson; Peter Swift

2014-09-01T23:59:59.000Z

407

NERSC Modules Software Environment  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (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

408

Fuel Cells & Alternative Fuels | Department of Energy  

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

Cells & Alternative Fuels Fuel Cells & Alternative Fuels Presentation given at DEER 2006, August 20-24, 2006, Detroit, Michigan. Sponsored by the U.S. DOE's EERE FreedomCar and...

409

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

410

World nuclear fuel cycle requirements 1990  

SciTech Connect (OSTI)

This analysis report presents the projected requirements for uranium concentrate and uranium enrichment services to fuel the nuclear power plants expected to be operating under three nuclear supply scenarios. Two of these scenarios, the Lower Reference and Upper Reference cases, apply to the United States, Canada, Europe, the Far East, and other countries with free market economies (FME countries). A No New Orders scenario is presented only for the United States. These nuclear supply scenarios are described in Commercial Nuclear Power 1990: Prospects for the United States and the World (DOE/EIA-0438(90)). This report contains an analysis of the sensitivities of the nuclear fuel cycle projections to different levels and types of projected nuclear capacity, different enrichment tails assays, higher and lower capacity factors, changes in nuclear fuel burnup levels, and other exogenous assumptions. The projections for the United States generally extend through the year 2020, and the FME projections, which include the United States, are provided through 2010. The report also presents annual projections of spent nuclear fuel discharges and inventories of spent fuel. Appendix D includes domestic spent fuel projections through the year 2030 for the Lower and Upper Reference cases and through 2040, the last year in which spent fuel is discharged, for the No New Orders case. These disaggregated projections are provided at the request of the Department of Energy's Office of Civilian Radioactive Waste Management.

Not Available

1990-10-26T23:59:59.000Z

411

High Temperature Fuel Cell (Phosphoric Acid) Manufacturing R&D  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

TEMPERATURE FUEL CELL TEMPERATURE FUEL CELL (PHOSPHORIC ACID) MANUFACTURING R&D Sridhar Kanuri Manager, Phosphoric acid fuel cells & fuel processing August 10 th , 2011 PAFC MANUFACTURING R&D Agenda PAFC cost challenge Manufacturing Cost reduction opportunities Summary PAFC SYSTEM OVERVIEW Overview Heaters Reactant manifolds Manifold adaptors Axial load system Pressure Plates Power take-off Coolant manifolds Insulation H frame Coolant hoses Cell stack Assembly Fuel Processing System Thermal Management System / Water Treatment System Power Supply System (CSA's) Electrical System Module Blower Skid Powerplant modules Cost reduction is being accomplished by incremental changes in technology and manufacturing Closing commercialization gap Continuous manufacturing

412

Modulational effects in accelerators  

SciTech Connect (OSTI)

We discuss effects of field modulations in accelerators, specifically those that can be used for operational beam diagnostics and beam halo control. In transverse beam dynamics, combined effects of nonlinear resonances and tune modulations influence diffusion rates with applied tune modulation has been demonstrated. In the longitudinal domain, applied RF phase and voltage modulations provide mechanisms for parasitic halo transport, useful in slow crystal extraction. Experimental experiences with transverse tune and RF modulations are also discussed.

Satogata, T.

1997-12-01T23:59:59.000Z

413

Configuration adjustment potential of the Very High Temperature Reactor prismatic cores with advanced actinide fuels  

E-Print Network [OSTI]

?.????????????????????............................. 102 APPENDIX C?.???????????????????????????. 104 VITA????????????????????????????????.111 viii LIST OF FIGURES FIGURE Page 1 Flow Chart of the CSAS6 Control Module????????????.? 12 2 Fuel Graphite Block... for the Annular Core Configuration with UO2 and MA fuel loadings???.??. 75 x LIST OF TABLES TABLE Page I Design Specifications for the HTTR????????..???????. 17 II Fuel Graphite Block Properties??????????????...??? 22 III...

Ames, David E, II

2006-10-30T23:59:59.000Z

414

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Diesel Fuel Blend Tax Exemption The biodiesel or ethanol portion of blended fuel containing taxable diesel is exempt from the diesel fuel tax. The biodiesel or ethanol fuel blend...

415

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

fuels include liquid non-petroleum based fuel that can be placed in motor vehicle fuel tanks and used to operate on-road vehicles, including all forms of fuel commonly or...

416

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

fuel blends of at least 20% biodiesel fuel or that mix fuel from separate storage tanks and allow the user to select the percentage of renewable fuel. The maximum credit...

417

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

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 the alternative fuels tax...

418

Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) Acquisition,  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

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

419

Fuel reforming for fuel cell application.  

E-Print Network [OSTI]

??Fossil fuels, such as natural gas, petroleum, and coal are currently the primary source of energy that drives the world economy. However, fossil fuel is (more)

Hung, Tak Cheong

2006-01-01T23:59:59.000Z

420

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

SciTech Connect (OSTI)

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

Note: This page contains sample records for the topic "fuels module assumption" 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

A Study of Fast Reactor Fuel Transmutation in a Candidate Dispersion Fuel Design  

SciTech Connect (OSTI)

Dispersion fuels represent a significant departure from typical ceramic fuels to address swelling and radiation damage in high burnup fuel. Such fuels use a manufacturing process in which fuel particles are encapsulated within a non-fuel matrix. Dispersion fuels have been studied since 1997 as part of an international effort to develop and test very high density fuel types for the Reduced Enrichment for Research and Test Reactors (RERTR) program.[1] The Idaho National Laboratory is performing research in the development of an innovative dispersion fuel concept that will meet the challenges of transuranic (TRU) transmutation by providing an integral fission gas plenum within the fuel itself, to eliminate the swelling that accompanies the irradiation of TRU. In this process, a metal TRU vector produced in a separations process is atomized into solid microspheres. The dispersion fuel process overcoats the microspheres with a mixture of resin and hollow carbon microspheres to create a TRUC. The foam may then be heated and mixed with a metal power (e.g., Zr, Ti, or Si) and resin to form a matrix metal carbide, that may be compacted and extruded into fuel elements. In this paper, we perform reactor physics calculations for a core loaded with the conceptual fuel design. We will assume a typical TRU vector and a reference matrix density. We will employ a fuel and core design based on the Advanced Burner Test Reactor (ABTR) design.[2] Using the CSAS6 and TRITON modules of the SCALE system [3] for preliminary scoping studies, we will demonstrate the feasibility of reactor operations. This paper will describe the results of these analyses.

Mark DeHart; Hongbin Zhang; Eric Shaber; Matthew Jesse

2010-11-01T23:59:59.000Z

422

FEAT Equations for CO, HC and NO. G. A. Bishop Last updated June 2011. ASSUMPTIONS  

E-Print Network [OSTI]

:H ratio is 2 and non-oxygenated. Applies to gasoline and diesel in general. Fuel is approximated make the math simpler we have chosen for the exhaust HC to be a multiple of the input HC are correct for diesel vehicles) and assume an 8cm path length. For a direct tailpipe comparison for diesel

Denver, University of

423

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

424

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

425

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

426

Coal based fuels, fuel systems and alternative fuels  

SciTech Connect (OSTI)

The introduction of coal based fuel systems such as coal/air and coal water mixtures was an attempt to minimize the use of heavy fuel oils in large scale power generation processes. This need was based on forecasts of fuel reserves and future pricing of fuel oils, therefore economic considerations predominated over environmental benefits, if any, which could result from widespread use of these fuels. Coal continued as the major fuel used in the power generation industry and combustion systems were developed to minimize gaseous emissions, such as NOx. Increasing availability of natural gas led to consideration of its use in combination with coal in fuel systems involving combined cycle or topping cycle operations. Dual fuel coal natural gas operations also offered the possibility of improved performance in comparison to 100% coal based fuel systems. Economic considerations have more recently looked at emulsification of heavy residual liquid fuels for consumption in power generation boiler and Orimulsion has emerged as a prime example of this alternative fuel technology. The paper will discuss some aspects of the burner technology related to the application of these various coal based fuels, fuel systems and alternative fuels in the power generation industry.

Allen, J.W.; Beal, P.R.

1998-07-01T23:59:59.000Z

427

Coal based fuels, fuel systems and alternative fuels  

SciTech Connect (OSTI)

The introduction of coal based fuel systems such as coal/air and coal water mixtures was an attempt to minimise the use of heavy fuel oils in large scale power generation processes. This need was based on forecasts of fuel reserves and future pricing of fuel oils, therefore economic considerations predominated over environmental benefits, if any, which could result from widespread use of these fuels. Coal continued as the major fuel used in the power generation industry and combustion systems were developed to minimise gaseous emissions, such as NO{sub x}. Increasing availability of natural gas led to consideration of its use in combination with coal in fuel systems involving combined cycle or topping cycle operations. Dual fuel coal natural gas operations also offered the possibility of improved performance in comparison to 100% coal based fuel systems. Economic considerations have more recently looked at emulsification of heavy residual liquid fuels for consumption in power generation boiler and Orimulsion has emerged as a prime example of this alternative fuel technology. The next sections of the paper will discuss some aspects of the burner technology related to the application of these various coal based fuels, fuel systems and alternative fuels in the power generation industry.

Allen, J.W.; Beal, P.R. [ABB Combustion Services Limited, Derby (United Kingdom)

1998-04-01T23:59:59.000Z

428

module 4 | Department of Energy  

Broader source: Energy.gov (indexed) [DOE]

module 4 module 4 HR5 TRANSITION BRIEFING module 4 More Documents & Publications Microsoft Word - Rev5functionalaccountabilityimplementationplan..doc Management (WFP) DEPARTMENT OF...

429

[Gas cooled fuel cell systems technology development program  

SciTech Connect (OSTI)

Objective is the development of a gas-cooled phosphoric acid fuel cell for electric utility power plant application. Primary objectives are to: demonstrate performance endurance in 10-cell stacks at 70 psia, 190 C, and 267 mA/cm[sup 2]; improve cell degradation rate to less than 8 mV/1000 hours; develop cost effective criteria, processes, and design configurations for stack components; design multiple stack unit and a single 100 kW fuel cell stack; design a 375 kW fuel cell module and demonstrate average cell beginning-of-use performance; manufacture four 375-kW fuel cell modules and establish characteristics of 1.5 MW pilot power plant. The work is broken into program management, systems engineering, fuel cell development and test, facilities development.

Not Available

1988-03-01T23:59:59.000Z

430

Alternative Fuels Data Center  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

Tools Tools Printable Version Share this resource Send a link to Alternative Fuels Data Center to someone by E-mail Share Alternative Fuels Data Center on Facebook Tweet about Alternative Fuels Data Center on Twitter Bookmark Alternative Fuels Data Center on Google Bookmark Alternative Fuels Data Center on Delicious Rank Alternative Fuels Data Center on Digg Find More places to share Alternative Fuels Data Center on AddThis.com... Fuel Properties Search Fuel Properties Comparison Create a custom chart comparing fuel properties and characteristics for multiple fuels. Select the fuel and properties of interest. Select Fuels Clear all All Fuels Gasoline Diesel (No. 2) Biodiesel Compressed Natural Gas (CNG) Electricity Ethanol Hydrogen Liquefied Natural Gas (LNG) Propane (LPG)

431

Fuel cell generating plant  

SciTech Connect (OSTI)

This paper discusses a fuel cell generating plant. It comprises a compressed fuel supply; a fuel cell system including fuel conditioning apparatus and fuel cells; a main fuel conduit for conveying fuel from the fuel supply to the fuel cell system; a turbo compressor having a turbine receiving exhaust products from the fuel cell system and a compressor for compressing air; a main air conduit for conveying air from the compressor to the fuel cell system; an auxiliary burner having a primary burner and a pilot; an auxiliary air conduit for conveying air from the compressed fuel supply to the auxiliary burner; an auxiliary exhaust conduit for conveying exhaust products from the auxiliary burner to the turbine; a check valve located between the fuel supply and the pilot; and a gas accumulator in the auxiliary fuel conduit located between the check valve and the pilot.

Sanderson, R.A.

1990-11-27T23:59:59.000Z

432

Development of an External Fuel Processor for a Solid Oxide Fuel Cell  

SciTech Connect (OSTI)

A 250 kW External Fuel Processor was developed and tested that will supply the gases needed by a pipeline natural gas fueled, solid oxide fuel cell during all modes of operation. The fuel processor consists of three major subsystems--a desulfurizer to remove fuel sulfur to an acceptable level, a synthesis gas generator to support plant heat-up and low load fuel cell operations, and a start gas generator to supply a non-flammable, reducing gas to the fuel cell during startup and shutdown operations. The desulfurization subsystem uses a selective catalytic sulfur oxidation process that was developed for operation at elevated pressure and removes the fuel sulfur to a total sulfur content of less than 80 ppbv. The synthesis gas generation subsystem uses a waterless, catalytic partial oxidation reactor to produce a hydrogen-rich mixture from the natural gas and air. An operating window was defined that allows carbon-free operation while maintaining catalyst temperatures that will ensure long-life of the reactor. The start gas subsystem generates an oxygen-free, reducing gas from the pipeline natural gas using a low-temperature combustion technique. These physically and thermally integrated subsystems comprise the 250 kW External Fuel Processor. The 250 kW External Fuel Processor was tested at the Rolls-Royce facility in North Canton, Ohio to verify process performance and for comparison with design specifications. A step wise operation of the automatic controls through the startup, normal operation and shutdown sequences allowed the control system to be tuned and verified. A fully automated system was achieved that brings the fuel processor through its startup procedure, and then await commands from the fuel cell generator module for fuel supply and shutdown. The fuel processor performance met all design specifications. The 250 kW External Fuel Processor was shipped to an American Electric Power site where it will be tested with a Rolls-Royce solid oxide fuel cell generator module.

Daniel Birmingham; Crispin Debellis; Mark Perna; Anant Upadhyayula

2008-02-28T23:59:59.000Z

433

Advanced silicon photonic modulators  

E-Print Network [OSTI]

Various electrical and optical schemes used in Mach-Zehnder (MZ) silicon plasma dispersion effect modulators are explored. A rib waveguide reverse biased silicon diode modulator is designed, tested and found to operate at ...

Sorace, Cheryl M

2010-01-01T23:59:59.000Z

434

LMFBR fuel component costs  

SciTech Connect (OSTI)

A significant portion of the cost of fabricating LMFBR fuels is in the non-fuel components such as fuel pin cladding, fuel assembly ducts and end fittings. The contribution of these to fuel fabrication costs, based on FFTF experience and extrapolated to large LMFBR fuel loadings, is discussed. The extrapolation considers the expected effects of LMFBR development programs in progress on non-fuel component costs.

Epperson, E.M.; Borisch, R.R.; Rice, L.H.

1981-10-29T23:59:59.000Z

435

Alternative Fuels Data Center: Flexible Fuel Vehicle Conversions  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Conversions to someone by E-mail Share Alternative Fuels Data Center: Flexible Fuel Vehicle Conversions on Facebook Tweet about Alternative Fuels Data Center: Flexible Fuel Vehicle...

436

Vehicle Certification Test Fuel and Ethanol Flex Fuel Quality...  

Broader source: Energy.gov (indexed) [DOE]

Vehicle Certification Test Fuel and Ethanol Flex Fuel Quality Vehicle Certification Test Fuel and Ethanol Flex Fuel Quality Breakout Session 2: Frontiers and Horizons Session 2-B:...

437

Texas Hydrogen Highway - Fuel Cell Hybrid Bus and Fueling Infrastructu...  

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

Texas Hydrogen Highway - Fuel Cell Hybrid Bus and Fueling Infrastructure Technology Showcase Texas Hydrogen Highway - Fuel Cell Hybrid Bus and Fueling Infrastructure Technology...

438

Light Duty Fuel Cell Electric Vehicle Hydrogen Fueling Protocol...  

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

Light Duty Fuel Cell Electric Vehicle Hydrogen Fueling Protocol Light Duty Fuel Cell Electric Vehicle Hydrogen Fueling Protocol Download the webinar slides from the U.S. Department...

439

Hydrogen and Fuel Cell Technologies Update: 2010 Fuel Cell Seminar...  

Broader source: Energy.gov (indexed) [DOE]

Hydrogen and Fuel Cell Technologies Update: 2010 Fuel Cell Seminar and Exposition Hydrogen and Fuel Cell Technologies Update: 2010 Fuel Cell Seminar and Exposition Presentation by...

440

Flexible Fuel Vehicles: Providing a Renewable Fuel Choice, Vehicle...  

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

Flexible Fuel Vehicles: Providing a Renewable Fuel Choice, Vehicle Technologies Program (VTP) (Fact Sheet) Flexible Fuel Vehicles: Providing a Renewable Fuel Choice, Vehicle...

Note: This page contains sample records for the topic "fuels module assumption" 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

DOE Fuel Cell Technologies Office: 2013 Fuel Cell Seminar and...  

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

DOE Fuel Cell Technologies Office: 2013 Fuel Cell Seminar and Energy Exposition DOE Fuel Cell Technologies Office: 2013 Fuel Cell Seminar and Energy Exposition Overview of DOE's...

442

DOE Fuel Cell Technologies Office Record 13012: Fuel Cell System...  

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

Fuel Cell Technologies Office Record 13012: Fuel Cell System Cost - 2013 DOE Fuel Cell Technologies Office Record 13012: Fuel Cell System Cost - 2013 This program record from the...

443

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

SciTech Connect (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

444

FUEL-FLEXIBLE GASIFICATION-COMBUSTION TECHNOLOGY FOR PRODUCTION OF H2 AND SEQUESTRATION-READY CO2  

SciTech Connect (OSTI)

It is expected that in the 21st century the Nation will continue to rely on fossil fuels for electricity, transportation, and chemicals. It will be necessary to improve both the process efficiency and environmental impact performance of fossil fuel utilization. GE Global Research (GEGR) has developed an innovative fuel-flexible Unmixed Fuel Processor (UFP) technology to produce H{sub 2}, power, and sequestration-ready CO{sub 2} from coal and other solid fuels. The UFP module offers the potential for reduced cost, increased process efficiency relative to conventional gasification and combustion systems, and near-zero pollutant emissions including NO{sub x}. GEGR (prime contractor) was awarded a Vision 21 program from U.S. DOE NETL to develop the UFP technology. Work on this Phase I program started on October 1, 2000. The project team includes GEGR, Southern Illinois University at Carbondale (SIU-C), California Energy Commission (CEC), and T. R. Miles, Technical Consultants, Inc. In the UFP technology, coal/opportunity fuels and air are simultaneously converted into separate streams of (1) pure hydrogen that can be utilized in fuel cells, (2) sequestration-ready CO{sub 2}, and (3) high temperature/pressure oxygen-depleted air to produce electricity in a gas turbine. The process produces near-zero emissions and, based on process modeling with best-case scenario assumptions, has an estimated process efficiency of 68%, based on electrical and H{sub 2} energy outputs relative to the higher heating value of coal, and an estimated equivalent electrical efficiency of 60%. The Phase I R&D program will determine the operating conditions that maximize separation of CO{sub 2} and pollutants from the vent gas, while simultaneously maximizing coal conversion efficiency and hydrogen production. The program integrates lab-, bench- and pilot-scale studies to demonstrate the UFP technology. This is the eleventh quarterly technical progress report for the Vision 21 UFP program supported by U.S. DOE NETL (Contract No. DE-FC26-00FT40974). This report summarizes program accomplishments for the period starting April 1, 2003 and ending June 30, 2003. The report includes an introduction summarizing the UFP technology, main program tasks, and program objectives; it also provides a summary of program activities and accomplishments covering progress in tasks including lab-scale experimental testing, pilot-scale assembly, and program management.

George Rizeq; Janice West; Arnaldo Frydman; Raul Subia; Vladimir Zamansky; Hana Loreth; Lubor Stonawski; Tomasz Wiltowski; Edwin Hippo; Shashi Lalvani

2003-07-01T23:59:59.000Z

445

Modulating lignin in plants  

SciTech Connect (OSTI)

Materials and methods for modulating (e.g., increasing or decreasing) lignin content in plants are disclosed. For example, nucleic acids encoding lignin-modulating polypeptides are disclosed as well as methods for using such nucleic acids to generate transgenic plants having a modulated lignin content.

Apuya, Nestor; Bobzin, Steven Craig; Okamuro, Jack; Zhang, Ke

2013-01-29T23:59:59.000Z

446

Smart Integrated Power Module  

Broader source: Energy.gov [DOE]

2012 DOE Hydrogen and Fuel Cells Program and Vehicle Technologies Program Annual Merit Review and Peer Evaluation Meeting

447

Integrated Power Module Cooling  

Broader source: Energy.gov [DOE]

2013 DOE Hydrogen and Fuel Cells Program and Vehicle Technologies Program Annual Merit Review and Peer Evaluation Meeting

448

Hydrogen storage and integrated fuel cell assembly  

DOE Patents [OSTI]

Hydrogen is stored in materials that absorb and desorb hydrogen with temperature dependent rates. A housing is provided that allows for the storage of one or more types of hydrogen-storage materials in close thermal proximity to a fuel cell stack. This arrangement, which includes alternating fuel cell stack and hydrogen-storage units, allows for close thermal matching of the hydrogen storage material and the fuel cell stack. Also, the present invention allows for tailoring of the hydrogen delivery by mixing different materials in one unit. Thermal insulation alternatively allows for a highly efficient unit. Individual power modules including one fuel cell stack surrounded by a pair of hydrogen-storage units allows for distribution of power throughout a vehicle or other electric power consuming devices.

Gross, Karl J. (Fremont, CA)

2010-08-24T23:59:59.000Z

449

Assessment of California reformulated gasoline impact on vehicle fuel economy  

SciTech Connect (OSTI)

Fuel economy data contained in the 1996 California Air Resources Board (CAROB) report with respect to the introduction of California Reformulated Gasoline (CaRFG) has been examined and reanalyzed by two additional statistical methodologies. Additional data has also been analyzed by these two statistical approaches. Within the assumptions of the analysis, point estimates for the reduction in fuel economy using CaRFG as compared to conventional, non-reformulated gasoline were 2-4 %, with a 95% upper confidence bound of 6 %. Substantial variations in fuel economy are routine and inevitable due to additional factors which affect mileage, even if there is no change in fuel reformulation. This additional analysis confirms the conclusion reached by CAROB with respect to the impact of CaRFG on fuel economy.

Aceves, S.; Glaser, R.; Richardson, J.

1997-01-01T23:59:59.000Z

450

Assessment of California reformulated gasoline impact on vehicle fuel economy  

SciTech Connect (OSTI)

Fuel economy data contained in the 1996 California Air Resources Board (CARB) report with respect to the introduction of California Reformulated Gasoline (CaRFG) has been examined and reanalyzed by two additional statistical methodologies. Additional data has also been analyzed by these two statistical approaches. Within the assumptions of the analysis, point estimates for the reduction in fuel economy using CaRFG as compared to conventional, non-reformulated gasoline were 2-4%, with a 95% upper confidence bound of 6%. Substantial variations in fuel economy are routine and inevitable due to additional factors which affect mileage, even if there is no change in fuel reformulation. This additional analysis confirms the conclusion reached by CARB with respect to the impact of CaRFG on fuel economy.

Aceves, S., LLNL

1997-01-01T23:59:59.000Z

451

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

452

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

453

Chemical Kinetic Modeling of Fuels  

Broader source: Energy.gov (indexed) [DOE]

petroleum based fuels * Non-petroleum based fuels: - Biodiesel and new generation biofuels - Fischer-Tropsch (F-T) fuels - Oil sand derived fuels Reduce mechanisms for...

454

Fuel Cell Links  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

Fuel Cell Links Fuel Cell Links The links below are provided as additional resources for fuel-cell-related information. Most of the linked sites are not part of, nor affiliated with, fueleconomy.gov. We do not endorse or vouch for the accuracy of the information found on such sites. Fuel Cell Vehicles and Manufacturers Chevrolet General Motors press release about the Chevrolet Fuel Cell Equinox Ford Ford overview of their hydrogen fuel cell vehicles Honda FCX Clarity official site Hyundai Hyundai press release announcing the upcoming Tucson Fuel Cell Mercedes-Benz Ener-G-Force Fuel-cell-powered concept SUV Nissan Nissan TeRRA concept SUV Toyota Overview of Toyota fuel cell technology Hydrogen- and Fuel-Cell-Related Information and Tools Fuel Cell Vehicles Brief overview of fuel cell vehicles provided by DOE's Alternative Fuels Data Center (AFDC)

455

Fuel Guide Economy  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

1 1 MODEL YEAR 2000 FUEL ECONOMY LEADERS IN POPULAR VEHICLE CLASSES Listed below are the vehicles with the highest fuel economy for the most popular classes, including both automatic and manual transmissions and gasoline and diesel vehicles. Please be aware that many of these vehicles come in a range of engine sizes and trim lines, resulting in different fuel economy values. Check the fuel economy guide or the fuel economy sticker on new vehicles to find the values for a particular version of a vehicle. CONTENTS MODEL YEAR 2000 FUEL ECONOMY LEADERS ................. 1 HOW TO USE THIS GUIDE ..................................................... 2 FUEL ECONOMY AND YOUR ANNUAL FUEL COSTS .......... 3 WHY FUEL ECONOMY IS IMPORTANT .................................

456

Fuels options conference  

SciTech Connect (OSTI)

The proceedings of the Fuels Options Conference held May 9-10, 1995 in Atlanta, Georgia are presented. Twenty-three papers were presented at the conference that dealt with fuels outlook; unconventional fuels; fuel specification, purchasing, and contracting; and waste fuels applications. A separate abstract was prepared for each paper for inclusion in the Energy Science and Technology Database.

NONE

1995-09-01T23:59:59.000Z

457

Chapter 3 - Fuels for Fuel Cells  

Science Journals Connector (OSTI)

Publisher Summary This chapter deals with various types of liquid fuels and the relevant chemical and physical properties of these fuels as a means of comparison to the fuels of the future. It gives an overview of the manufacture and properties of the common fuels as well as a description of various biofuels. A fuel mixture usually contains a wide range of organic compounds (usually hydrocarbons). The specific mixture of hydrocarbons gives a fuel its characteristic properties, such as boiling point, melting point, density, viscosity, and a host of other properties. Depending on the application (stationary, central power, remote, auxiliary, transportation, military, etc.), there are a wide range of conventional fuels, such as natural gas, liquefied petroleum gas, light distillates, methanol, ethanol, dimethyl ether, naphtha, gasoline, kerosene, jet fuels, diesel, and biodiesel, that could be used in reforming processes to produce hydrogen (or hydrogen-rich synthesis gas) to power fuel cells. Fossils fuels include gaseous fuels, gasoline, kerosene, diesel fuel, and jet fuels. Gaseous fuels include natural gas and liquefied petroleum gas. Types of gasoline include automotive gasoline, aviation gasoline, and gasohol. Some additives added into gasoline are antioxidants, corrosion inhibitors, demulsifiers, anti-icing, dyes and markers, drag reducers, and oxygenates.

James G. Speight

2011-01-01T23:59:59.000Z

458

DOE Hydrogen and Fuel Cells Program Record #13007: Industry Deployed Fuel Cell Backup Power (BuP)  

Broader source: All U.S. Department of Energy (DOE) Office Webpages (Extended Search)

7 Date: 09/05/2013 7 Date: 09/05/2013 Title: Industry Deployed Fuel Cell Backup Power (BuP) Originators: Pete Devlin, Jim Alkire, Sara Dillich, Dimitrios Papageorgopoulos Approved by: Rick Farmer and Sunita Satyapal Date: 09/09/13 Item: Table 1: Number of fuel cells deployments (current and planned) for applications in backup power. The funding of 903 Department of Energy (DOE) fuel cell backup power systems has led to over 3,500 industry installations and on-order backup power units with no DOE funding. Data/Assumptions/Calculations: The manufacturers providing the fuel cells for the deployments (current and planned) mentioned in Table 1 above are: Altergy Ballard / Ida Tech Hydrogenics ReliOn, Inc. Total DOE American Recovery and Reinvestment Act (ARRA) investment for these fuel cell

459

Thermoelectrics Partnership: Automotive Thermoelectric Modules...  

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

Solution for Automotive Thermoelectric Modules Application Thermoelectrics Partnership: Automotive Thermoelectric Modules with Scalable Thermo- and Electro-Mechanical Interfaces...

460

Alternative Fuels Data Center: Alternative Fueling Infrastructure Grants  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

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

Note: This page contains sample records for the topic "fuels module assumption" 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.


461

Alternative Fuels Data Center: Alternative Fuel Vehicle Replacement Grants  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

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

462

Alternative Fuels Data Center: Alternative Fuel Vehicle (AFV) Conversion  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

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

463

Alternative Fuels Data Center: Alternative Fueling Infrastructure Tax  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

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

464

Alternative Fuels Data Center: Alternative Fuel Vehicle Labeling  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

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

465

Alternative Fuels Data Center: Biofuel Fueling Infrastructure Tax Credit  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

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

466

Alternative Fuels Data Center: Alternative Fuels Promotion and Information  

Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

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

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