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


1

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

2

Commercial Demand Module  

Gasoline and Diesel Fuel Update (EIA)

2 2 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

3

Residential Sector Demand Module  

Reports and Publications (EIA)

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

Owen Comstock

2012-12-19T23:59:59.000Z

4

Industrial Demand Module  

Reports and Publications (EIA)

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

Kelly Perl

2013-05-14T23:59:59.000Z

5

Industrial Demand Module  

Reports and Publications (EIA)

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

Kelly Perl

2013-09-30T23:59:59.000Z

6

Residential Sector Demand Module  

Reports and Publications (EIA)

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

Owen Comstock

2013-11-05T23:59:59.000Z

7

Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

2 2 Residential Demand Module The NEMS Residential Demand Module projects future residential sector energy requirements based on projections of the number of households and the stock, efficiency, and intensity of energy-consuming equipment. The Residential Demand Module projections begin with a base year estimate of the housing stock, the types and numbers of energy-consuming appliances servicing the stock, and the "unit energy consumption" (UEC) by appliance (in million Btu per household per year). The projection process adds new housing units to the stock, determines the equipment installed in new units, retires existing housing units, and retires and replaces appliances. The primary exogenous drivers for the module are housing starts by type

8

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

9

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.

10

Commercial Sector Demand Module  

Reports and Publications (EIA)

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

Kevin Jarzomski

2012-11-15T23:59:59.000Z

11

Commercial Sector Demand Module  

Reports and Publications (EIA)

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

Kevin Jarzomski

2013-10-10T23:59:59.000Z

12

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.

13

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

14

Residential Sector Demand Module 2000, Model Documentation  

Reports and Publications (EIA)

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

John H. Cymbalsky

1999-12-01T23:59:59.000Z

15

Residential Sector Demand Module 2004, Model Documentation  

Reports and Publications (EIA)

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

John H. Cymbalsky

2004-02-01T23:59:59.000Z

16

Residential Sector Demand Module 2001, Model Documentation  

Reports and Publications (EIA)

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

John H. Cymbalsky

2000-12-01T23:59:59.000Z

17

Residential Sector Demand Module 2002, Model Documentation  

Reports and Publications (EIA)

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

John H. Cymbalsky

2001-12-01T23:59:59.000Z

18

Residential Sector Demand Module 2005, Model Documentation  

Reports and Publications (EIA)

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

John H. Cymbalsky

2005-04-01T23:59:59.000Z

19

Residential Sector Demand Module 2003, Model Documentation  

Reports and Publications (EIA)

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

John H. Cymbalsky

2003-01-01T23:59:59.000Z

20

Residential Sector Demand Module 2008, Model Documentation  

Reports and Publications (EIA)

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

John H. Cymbalsky

2008-10-10T23:59:59.000Z

Note: This page contains sample records for the topic "demand module structure" 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

Residential Sector Demand Module 2006, Model Documentation  

Reports and Publications (EIA)

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

John H. Cymbalsky

2006-03-01T23:59:59.000Z

22

Residential Sector Demand Module 2009, Model Documentation  

Reports and Publications (EIA)

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

John H. Cymbalsky

2009-05-01T23:59:59.000Z

23

Residential Sector Demand Module 1999, Model Documentation  

Reports and Publications (EIA)

This is the fifth edition of the Model Documentation Report: Residential Sector DemandModule of the National Energy Modeling System (NEMS). It reflects changes made to themodule over the past year for the Annual Energy Outlook 1999.

John H. Cymbalsky

1998-12-01T23:59:59.000Z

24

Residential Sector Demand Module 2007, Model Documentation  

Reports and Publications (EIA)

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

John H. Cymbalsky

2007-04-26T23:59:59.000Z

25

Residential Sector Demand Module 1998, Model Documentation  

Reports and Publications (EIA)

This is the fourth edition of the Model Documentation Report: Residential Sector DemandModule of the National Energy Modeling System (NEMS). It reflects changes made to themodule over the past year for the Annual Energy Outlook 1998. Since last year, severalnew end-use services were added to the module, including: Clothes washers,dishwashers, furnace fans, color televisions, and personal computers. Also, as with allNEMS modules, the forecast horizon has been extended to the year 2020.

John H. Cymbalsky

1998-01-01T23:59:59.000Z

26

Residential Demand Module of the National Energy Modeling ...  

U.S. Energy Information Administration (EIA)

Residential Demand Module of the National Energy Modeling System: Model Documentation 2013 November 2013 Independent Statistics & Analysis ...

27

Industrial Demand Module (IDM) - 2002 EIA Models Directory  

U.S. Energy Information Administration (EIA)

The Industrial Demand Module incorporates three components: buildings; process and assembly; and boiler, steam, and cogeneration. Last Model Update:

28

Residential Sector Demand Module 1997, Model Documentation  

Reports and Publications (EIA)

This is the third edition of the Model Documentation Report: Residential Sector DemandModule of the National Energy Modeling System. It reflects changes made to the moduleover the past year for the Annual Energy Outlook 1997. Since last year, a subroutinewas added to the model which allows technology and fuel switching when space heaters,heat pump air conditioners, water heaters, stoves, and clothes dryers are retired in bothpre-1994 and post-1993 single-family homes. Also, a time-dependant function forcomputing the installed capital cost of equipment in new construction and the retail costof replacement equipment in existing housing was added.

John H. Cymbalsky

1997-01-01T23:59:59.000Z

29

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

30

Commercial Demand Module of the National Energy Modeling System ...  

U.S. Energy Information Administration (EIA)

Commercial Demand Module of the National Energy Modeling System: Model Documentation 2012 November 2012 . Independent Statistics & Analysis . www.eia.gov

31

Residential Sector Demand Module 1995, Model Documentation  

Reports and Publications (EIA)

This updated version of the NEMS Residential Module Documentation includes changesmade to the residential module for the production of the Annual Energy Outlook 1995.

John H. Cymbalsky

1995-03-01T23:59:59.000Z

32

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

33

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

34

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.

35

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

36

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.

37

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

38

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)

39

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.

40

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.

Note: This page contains sample records for the topic "demand module structure" 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

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.

42

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

43

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

44

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

Science Conference Proceedings (OSTI)

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) Commercial Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, model source code, and forecast results generated through the synthesis and scenario development based on these components. The NEMS Commercial Sector Demand Module is a simulation tool based upon economic and engineering relationships that models commercial sector energy demands at the nine Census Division level of detail for eleven distinct categories of commercial buildings. Commercial equipment selections are performed for the major fuels of electricity, natural gas, and distillate fuel, for the major services of space heating, space cooling, water heating, ventilation, cooking, refrigeration, and lighting. The algorithm also models demand for the minor fuels of residual oil, liquefied petroleum gas, steam coal, motor gasoline, and kerosene, the renewable fuel sources of wood and municipal solid waste, and the minor services of office equipment. Section 2 of this report discusses the purpose of the model, detailing its objectives, primary input and output quantities, and the relationship of the Commercial Module to the other modules of the NEMS system. Section 3 of the report describes the rationale behind the model design, providing insights into further assumptions utilized in the model development process to this point. Section 3 also reviews alternative commercial sector modeling methodologies drawn from existing literature, providing a comparison to the chosen approach. Section 4 details the model structure, using graphics and text to illustrate model flows and key computations.

NONE

1998-01-01T23:59:59.000Z

45

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

46

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

47

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.

48

Model Documentation Report: Residential Demand Module of the ...  

U.S. Energy Information Administration (EIA)

rebates used in demand-side management programs), can be modified at the equipment level. Housing ... Residential retired equipment efficiencies of 2005 stock

49

Industrial Demand Module 1999, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. Crawford Honeycutt

1999-01-01T23:59:59.000Z

50

Industrial Demand Module 2005, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. C. Honeycutt

2005-05-01T23:59:59.000Z

51

Industrial Demand Module 2006, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. C. Honeycutt

2006-07-01T23:59:59.000Z

52

Industrial Demand Module 2009, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. C. Honeycutt

2009-05-20T23:59:59.000Z

53

Industrial Demand Module 2003, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. Crawford Honeycutt

2003-12-01T23:59:59.000Z

54

Industrial Demand Module 2007, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. C. Honeycutt

2007-03-21T23:59:59.000Z

55

Industrial Demand Module 2002, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. Crawford Honeycutt

2001-12-01T23:59:59.000Z

56

Industrial Demand Module 2001, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. Crawford Honeycutt

2000-12-01T23:59:59.000Z

57

Industrial Demand Module 2008, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. C. Honeycutt

2008-06-01T23:59:59.000Z

58

Industrial Demand Module 2000, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. Crawford Honeycutt

2000-01-01T23:59:59.000Z

59

Industrial Demand Module 2004, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

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

T. Crawford Honeycutt

2004-02-01T23:59:59.000Z

60

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.

Note: This page contains sample records for the topic "demand module structure" 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

A Structural Model of Demand for Apprentices ?  

E-Print Network (OSTI)

It is a widely held opinion that apprenticeship training represents a net investment for training firms, and that therefore firms only train if they have the possibility to recoup these investments after the training period. A recent study using a new firm-level dataset for Switzerland showed, however, that for 60 percent of the firms, the apprenticeship training itself does not result in net cost. In this context it seems important to examine the question whether the potential net cost of training (during the training period) are a major determinant for the demand for apprentices. Different count data models, in particular hurdle models, are used to estimate the effect of net cost on the demand for apprentices. The results show that the net cost have a significant impact on the training decision but no significant influence on the demand for apprentices, once the firm has decided to train. For policy purposes, these results indicate that subsidies for firms that already train apprentices would not boost the demand for apprentices. JEL Classification: J24, C25

Samuel Mhlemann; Jrg Schweri; Rainer Winkelmann; Stefan C. Wolter

2005-01-01T23:59:59.000Z

62

Industrial Demand Module 1998, National Energy Modeling System (NEMS)  

Reports and Publications (EIA)

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Industrial Demand Model. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code. This document serves three purposes. First, it is a reference document providing a detailed description ofthe NEMS Industrial Model for model analysts, users, and the public. Second, this report meets the legal requirement of the Energy Information Administration (EIA) to provide adequate documentation in supportof its models (Public Law 94-385, section 57.b2). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.

T. Crawford Honeycutt

1998-01-01T23:59:59.000Z

63

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

SciTech Connect

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

NONE

1998-01-01T23:59:59.000Z

64

ColorPower: A Structured Approach to Demand Response  

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

ColorPower: A Structured Approach to Demand Response Speaker(s): Steven Florek Date: August 31, 2012 - 12:00pm Location: 90-3122 Seminar HostPoint of Contact: Janie Page...

65

Modeling Structural Changes in Market Demand and Supply  

E-Print Network (OSTI)

Economic events may cause structural changes in markets. To know the effect of the economic event we should analyze the structural changes in the market demand and supply. The purpose of this dissertation is to analyze the effect of selected economic events on market demand and supply using econometric models. Structural changes can be modeled according to the types of changes. For an abrupt and instantaneous break, a dummy variable model can be used. For a smooth and gradual movement, proxy variables which represent the event can be applied, if we know the variables. If we don?t know the appropriate proxy variables, a smooth transition regression model can be employed. The BSE (Bovine Spongiform Encephalopathy) outbreak in the U.S. in 2003 is assumed to make abrupt and instantaneous changes in Korean meat consumption. To analyze the effect on Korean meat consumption, the Korean demands of beef, pork, chicken, and U.S. beef are estimated using an LA/AIDS (Linear Approximate Almost Ideal Demand System) model with the dummy variable specifying the time before and after the BSE. From the results we can confirm that food safety concerns caused by the BSE case changed Korean meat consumption structure. Korean beef and U.S. beef became less elastic, and pork and chicken got more elastic to budget. Korean beef became less price elastic, but pork and U.S. beef got more price elastic. The changes of U.S. natural gas supply caused by technology development and depletion in reserves are analyzed using a smooth transition regression model. From the results, we can confirm that the productivity improvement by technology development is greater than the labor cost increase by depletion, but not greater than the capital cost increase by depletion in mid-2000s. The effects of posting the winning bid in a repeated Vickrey auction are examined using a proxy variable. By applying an unobserved effect Tobit model to the experimental auction done by Corrigan and Rousu (2006) for a candy bar, we can confirm that the changes of bidding behavior are significant, especially when the winning bid is high. By extracting the bid affiliation effects, we showed that true willingness to pay can be estimated.

Park, Beom Su

2010-08-01T23:59:59.000Z

66

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

SciTech Connect

This report documents the objectives, analytical approach and development of the National Energy Modeling System (NEMS) 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. This report serves three purposes. First, it is a reference document providing a detailed description for model analysts, users, and the public. 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 (Public Law 93-275, section 57(b)(1)). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.

NONE

1995-02-01T23:59:59.000Z

67

Model documentation report: Residential sector demand module of the National Energy Modeling System  

SciTech Connect

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This document serves three purposes. First, it is a reference document providing a detailed description for energy analysts, other users, and the public. 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 according to Public Law 93-275, section 57(b)(1). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements.

NONE

1995-03-01T23:59:59.000Z

68

Model documentation report: Residential sector demand module of the National Energy Modeling System  

Science Conference Proceedings (OSTI)

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Residential Sector Demand Module. The report catalogues and describes the model assumptions, computational methodology, parameter estimation techniques, and FORTRAN source code. This document serves three purposes. First, it is a reference document that provides a detailed description for energy analysts, other users, and the public. 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 according to Public Law 93-275, section 57(b)(1). Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements.

NONE

1997-01-01T23:59:59.000Z

69

Property:FlatDemandStructure | Open Energy Information  

Open Energy Info (EERE)

Property Property Edit with form History Facebook icon Twitter icon » Property:FlatDemandStructure Jump to: navigation, search This is a property of type Page. Pages using the property "FlatDemandStructure" Showing 25 pages using this property. (previous 25) (next 25) 0 0000827d-84d0-453d-b659-b86869323897 + 0000827d-84d0-453d-b659-b86869323897 + 000e60f7-120d-48ab-a1f9-9c195329c628 + 000e60f7-120d-48ab-a1f9-9c195329c628 + 00101108-073b-4503-9cd4-01769611c26f + 00101108-073b-4503-9cd4-01769611c26f + 001361ca-50d2-49bc-b331-08755a2c7c7d + 001361ca-50d2-49bc-b331-08755a2c7c7d + 0016f771-cda9-4312-afc2-63f10c8d8bf5 + 0016f771-cda9-4312-afc2-63f10c8d8bf5 + 00178d3d-17cb-46ed-8a58-24c816ddce96 + 00178d3d-17cb-46ed-8a58-24c816ddce96 + 001d1952-955c-411b-8ce4-3d146852a75e + 001d1952-955c-411b-8ce4-3d146852a75e +

70

Transportation Demand This  

Annual Energy Outlook 2012 (EIA)

69 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2012 Transportation Demand Module The NEMS Transportation Demand Module estimates...

71

Hazard consistent structural demands and in-structure design response spectra  

Science Conference Proceedings (OSTI)

Current analysis methodology for the Soil Structure Interaction (SSI) analysis of nuclear facilities is specified in ASCE Standard 4. This methodology is based on the use of deterministic procedures with the intention that enough conservatism is included in the specified procedures to achieve an 80% probability of non-exceedance in the computed response of a Structure, System. or Component for given a mean seismic design input. Recently developed standards are aimed at achieving performance-based, risk consistent seismic designs that meet specified target performance goals. These design approaches rely upon accurately characterizing the probability (hazard) level of system demands due to seismic loads consistent with Probabilistic Seismic Hazard Analyses. This paper examines the adequacy of the deterministic SSI procedures described in ASCE 4-98 to achieve an 80th percentile of Non-Exceedance Probability (NEP) in structural demand, given a mean seismic input motion. The study demonstrates that the deterministic procedures provide computed in-structure response spectra that are near or greater than the target 80th percentile NEP for site profiles other than those resulting in high levels of radiation damping. The deterministic procedures do not appear to be as robust in predicting peak accelerations, which correlate to structural demands within the structure.

Houston, Thomas W [Los Alamos National Laboratory; Costantino, Michael C [Los Alamos National Laboratory; Costantino, Carl J [Los Alamos National Laboratory

2009-01-01T23:59:59.000Z

72

Q:\asufinal_0107_demand.vp  

Gasoline and Diesel Fuel Update (EIA)

00 00 (AEO2000) Assumptions to the January 2000 With Projections to 2020 DOE/EIA-0554(2000) Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 Macroeconomic Activity Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13 International Energy Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Household Expenditures Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 Residential Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Commercial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Industrial Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Transportation Demand Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 46 Electricity Market Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 66 Oil and Gas Supply Module . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 80 Natural Gas Transmission and Distribution

73

A statistical analysis of structural differences in minority household electricity demand  

SciTech Connect

In this paper, the structures for electricity demand in non-Latino Black and White households are compared. Electricity demand will be analyzed within the context of a complete demand system, and statistical tests for structural differences will be systematically conducted in the hope of pinpointing the location of differences within the context of this model. Structural differences in demand are defined as statistically significant differences in a parameter or group of parameters that identify the quantitative relationship between explanatory variables and electricity consumption. Along with population taste differences, which might emanate from historical and cultural population differences, structural differences might also occur because of differences in housing and geographic patterns and as a result of differences in access to markets and information. As a consequence, energy consumption decisions will differ, and the level and composition of energy consumption are likely to vary. In practice, it is nearly impossible to untangle the causes contributing to structural differences, but it is reasonably easy to test for statistical differences. The superficial evidence indicates there is a strong likelihood that structural differences do exist in electricity demand between White and Black households. The null hypothesis, which states that there exist no differences in the structures for electricity demand for Black and White households, is tested.

Poyer, D.A.; Earl, E.

1994-09-01T23:59:59.000Z

74

Electronic spectra of strongly modulated aperiodic structures  

Science Conference Proceedings (OSTI)

We consider the tight-binding Hamiltonian on strongly modulated aperiodic chains (e.g., quasiperiodic, self-similar, random). The site energies are distributed according to a given binary sequence ([ital V][sub [ital n

Barache, D. (Laboratoire de Physique Theorique et Mathematique, Universite Paris 7, Denis Diderot, 2 place Jussieu, 75251 Paris Cedex 05 (France)); Luck, J.M. (Service de Physique Theorique, Centre d'Etudes de Saclay, 91191 Gif-sur-Yvette Cedex (France))

1994-06-01T23:59:59.000Z

75

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

SciTech Connect

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) Industrial Demand Model. The report catalogues and describes model assumptions, computational methodology, parameter estimation techniques, and model source code. This document serves three purposes. First, it is a reference document providing a detailed description of the NEMS Industrial Model for model analysts, users, and the public. Second, this report meets the legal requirements of the Energy Information Administration (EIA) to provide adequate documentation in support of its model. Third, it facilitates continuity in model development by providing documentation from which energy analysts can undertake model enhancements, data updates, and parameter refinements as future projects.

NONE

1998-01-01T23:59:59.000Z

76

Single, stretched membrane, structural module experiments  

DOE Green Energy (OSTI)

This report describes tests done on stretched-membrane heliostats used to reflect solar radiation onto a central receiver. The tests were used to validate prior analysis and mathematical models developed to describe module performance. The modules tested were three meters in diameter and had reflective polymer film laminated to the membrane. The frames were supported at three points equally spaced around the ring. Three modules were pneumatically attached with their weight suspended at the bottom support, two were pneumatically attached with their weight suspended from the upper mounts, and one was rigidly attached with its weight suspended at the bottom mount. By varying the membrane tension we could simulate a uniform wind loading normal to the mirror's surface. A video camera 15+ meters away from the mirror recorded the virtual image of a target grid as reflected by the mirrors' surface. The image was digitized and stored on a microcomputer. Using the law of reflection and analytic geometry, we computed the surface slopes of a sampling of points on the surface. The dominant module response was consistent with prior SERI analyses. The simple analytical model is quite adequate for designing and sizing single-membrane modules if the initial imperfections and their amplification are appropriately controlled. To avoid potential problems resulting from the fundamentally n = 2 deformation phenomena, we advise using either relatively stiffer ring frames or more than three support points.

Wood, R.L.

1986-02-01T23:59:59.000Z

77

STATISTICAL ANALYSIS AND STRUCTURE OPTIMIZATION OF LARGE PHOTOVOLTAIC MODULE  

E-Print Network (OSTI)

on the output power of large Photovoltaic (PV) module by modeling each PV cell as a current source whose short. Photovoltaic (PV) is a simple and elegant method of harnessing the sun's energy. PV devices (solar cellsSTATISTICAL ANALYSIS AND STRUCTURE OPTIMIZATION OF LARGE PHOTOVOLTAIC MODULE RATHEESH R

Qiu, Qinru

78

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

79

Virasoro Module Structure of Local Martingales of SLE Variants  

E-Print Network (OSTI)

Martingales often play an important role in computations with Schramm-Loewner evolutions (SLEs). The purpose of this article is to provide a straightforward approach to the Virasoro module structure of the space of local martingales for variants of SLEs. In the case of ordinary chordal SLE, it has been shown in Bauer & Bernard: Phys.Lett.B 557 that polynomial local martingales form a Virasoro module. We will show for more general variants that the module of local martingales has a natural submodule M that has the same interpretation as the module of polynomial local martingales of chordal SLE, but it is in many cases easy to find more local martingales than that. We discuss the surprisingly rich structure of the Virasoro module M and construction of the ``SLE state'' or ``martingale generating function'' by Coulomb gas formalism. In addition, Coulomb gas or Feigin-Fuchs integrals will be shown to transparently produce candidates for multiple SLE pure geometries.

Kalle Kytl

2006-04-20T23:59:59.000Z

80

Residential Demand Module  

Gasoline and Diesel Fuel Update (EIA)

and clothes drying. In addition to the major equipment-driven and clothes drying. In addition to the major equipment-driven end-uses, the average energy consumption per household is projected for other electric and nonelectric Energy Information Administration/Assumptions to the Annual Energy Outlook 2006 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 South Atlantic Mountain Figure 5. United States Census Divisions Source:Energy Information Administration,Office of Integrated Analysis and Forecasting. Report #:DOE/EIA-0554(2006) Release date: March 2006

Note: This page contains sample records for the topic "demand module structure" 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

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

E-Print Network (OSTI)

analytical agency within the U.S. Department of Energy. By law, EIAs 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

unknown authors

2013-01-01T23:59:59.000Z

82

Transportation Demand Module  

Gasoline and Diesel Fuel Update (EIA)

NA NA 0.000 Diesel Engine II: integrated starteralternator with idle off and limited regenerative breaking 2005 1500.00 0.050 2005 1200.00 0.050 NA NA 0.000 Diesel Engine...

83

Property:OpenEI/UtilityRate/DemandRateStructure/Tier6Adjustment | Open  

Open Energy Info (EERE)

Property Property Edit with form History Facebook icon Twitter icon » Property:OpenEI/UtilityRate/DemandRateStructure/Tier6Adjustment Jump to: navigation, search This is a property of type Number. Pages using the property "OpenEI/UtilityRate/DemandRateStructure/Tier6Adjustment" Showing 13 pages using this property. 4 4b524791-bef2-49b1-850b-458730755203 + 8 + 4b524791-bef2-49b1-850b-458730755203 + 8 +, 9 +, 67 +, ... 4b524791-bef2-49b1-850b-458730755203 + 9 + 4b524791-bef2-49b1-850b-458730755203 + 2 + 4b524791-bef2-49b1-850b-458730755203 + 67 + 4b524791-bef2-49b1-850b-458730755203 + 2 + 4b524791-bef2-49b1-850b-458730755203 + 89 + 4b524791-bef2-49b1-850b-458730755203 + 3 + 4b524791-bef2-49b1-850b-458730755203 + 3 + 4b524791-bef2-49b1-850b-458730755203 + 3 +

84

Transportation Demand  

Gasoline and Diesel Fuel Update (EIA)

page intentionally left blank page intentionally left blank 69 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2011 Transportation Demand Module The NEMS Transportation Demand Module estimates transportation energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars and light trucks), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), buses, freight and passenger aircraft, freight and passenger rail, freight shipping, and miscellaneous

85

Property:OpenEI/UtilityRate/DemandRateStructure/Tier4Rate | Open Energy  

Open Energy Info (EERE)

Rate" Rate" Showing 13 pages using this property. 4 4b524791-bef2-49b1-850b-458730755203 + 5 +, 6 +, 3 +, ... 4b524791-bef2-49b1-850b-458730755203 + 6 + 4b524791-bef2-49b1-850b-458730755203 + 3 + 4b524791-bef2-49b1-850b-458730755203 + 7 + 4b524791-bef2-49b1-850b-458730755203 + 5 + 4b524791-bef2-49b1-850b-458730755203 + 8 + 4b524791-bef2-49b1-850b-458730755203 + 5 + 4b524791-bef2-49b1-850b-458730755203 + 5 + 4b524791-bef2-49b1-850b-458730755203 + 6 + 4b524791-bef2-49b1-850b-458730755203 + 6 + E E40880ac-c27b-4cbf-a011-b0d7d6e10fe9 + 1 + E40880ac-c27b-4cbf-a011-b0d7d6e10fe9 + 1 + E40880ac-c27b-4cbf-a011-b0d7d6e10fe9 + 1 + Retrieved from "http://en.openei.org/w/index.php?title=Property:OpenEI/UtilityRate/DemandRateStructure/Tier4Rate&oldid=53975

86

Property:OpenEI/UtilityRate/DemandRateStructure/Tier3Max | Open Energy  

Open Energy Info (EERE)

Max" Max" Showing 13 pages using this property. 4 4b524791-bef2-49b1-850b-458730755203 + 5 + 4b524791-bef2-49b1-850b-458730755203 + 5 + 4b524791-bef2-49b1-850b-458730755203 + 6 + 4b524791-bef2-49b1-850b-458730755203 + 7 + 4b524791-bef2-49b1-850b-458730755203 + 3 +, 4 +, 5 +, ... 4b524791-bef2-49b1-850b-458730755203 + 9 + 4b524791-bef2-49b1-850b-458730755203 + 3 + 4b524791-bef2-49b1-850b-458730755203 + 30 + 4b524791-bef2-49b1-850b-458730755203 + 4 + 4b524791-bef2-49b1-850b-458730755203 + 36 + E E40880ac-c27b-4cbf-a011-b0d7d6e10fe9 + 200 + E40880ac-c27b-4cbf-a011-b0d7d6e10fe9 + 200 + E40880ac-c27b-4cbf-a011-b0d7d6e10fe9 + 200 + Retrieved from "http://en.openei.org/w/index.php?title=Property:OpenEI/UtilityRate/DemandRateStructure/Tier3Max&oldid=539747

87

Property:OpenEI/UtilityRate/DemandRateStructure/Period | Open Energy  

Open Energy Info (EERE)

Period Period Jump to: navigation, search This is a property of type Number. The allowed values for this property are: 1 2 3 4 5 6 7 8 9 Pages using the property "OpenEI/UtilityRate/DemandRateStructure/Period" Showing 25 pages using this property. (previous 25) (next 25) 0 000e60f7-120d-48ab-a1f9-9c195329c628 + 1 + 000e60f7-120d-48ab-a1f9-9c195329c628 + 1 + 001361ca-50d2-49bc-b331-08755a2c7c7d + 1 + 001361ca-50d2-49bc-b331-08755a2c7c7d + 1 + 0016f771-cda9-4312-afc2-63f10c8d8bf5 + 1 + 0016f771-cda9-4312-afc2-63f10c8d8bf5 + 1 + 00178d3d-17cb-46ed-8a58-24c816ddce96 + 1 + 00178d3d-17cb-46ed-8a58-24c816ddce96 + 1 + 001d1952-955c-411b-8ce4-3d146852a75e + 1 + 001d1952-955c-411b-8ce4-3d146852a75e + 1 + 0022e9a5-942c-4e97-94d7-600f5d315ce8 + 1 + 0022e9a5-942c-4e97-94d7-600f5d315ce8 + 1 +

88

Economic development and the structure of the demand for commerial energy  

E-Print Network (OSTI)

To deepen the understanding of the relation between economic development and energy demand, this study estimates the Engel curves that relate per-capita energy consumption in major economic sectors to per-capita GDP. Panel ...

Judson, Ruth A.

89

Economic development and the structure of the demand for commerial energy  

E-Print Network (OSTI)

To deepen understanding of the relation between economic development and energy demand, this study estimates the Engel curves that relate per-capita energy consumption in major economic sectors to per-capita GDP. Panel ...

Judson, Ruth A.; Schmalensee, Richard.; Stoker, Thomas M.

90

Structural changes between models of fossil-fuel demand by steam-electric power plants  

SciTech Connect

A consumption function for multi-fuel steam-electric power plants is used to investigate fossil-fuel demand behavior. The input consumption equations for a plant's primary and alternate fossil fuels are derived by Shepard's lemma from a generalized Cobb-Douglas cost function reflecting average variable cost minimization constrained by technology and the demand for electricity. These equations are estimated by primary and alternate fuel subsets with ordinary least squares and seemingly unrelated regression techniques for 1974, 1977, and 1980. The results of the regression analysis show the importance of consumer demand in the fossil fuel consumption decision; it has the only significant parameter in all of the estimated equations. The estimated own- and cross-price elasticities are small, when they are statistically significant. The results for the primary fuel equations are better than those for the alternate fuel equations in all of the fuel pair subsets.

Gerring, L.F.

1984-01-01T23:59:59.000Z

91

Structuring energy supply and demand networks in a general equilibrium model to simulate global warming control strategies  

Science Conference Proceedings (OSTI)

Global warming control strategies which mandate stringent caps on emissions of greenhouse forcing gases can substantially alter a country's demand, production, and imports of energy products. Although there is a large degree of uncertainty when attempting to estimate the potential impact of these strategies, insights into the problem can be acquired through computer model simulations. This paper presents one method of structuring a general equilibrium model, the ENergy and Power Evaluation Program/Global Climate Change (ENPEP/GCC), to simulate changes in a country's energy supply and demand balance in response to global warming control strategies. The equilibrium model presented in this study is based on the principle of decomposition, whereby a large complex problem is divided into a number of smaller submodules. Submodules simulate energy activities and conversion processes such as electricity production. These submodules are linked together to form an energy supply and demand network. Linkages identify energy and fuel flows among various activities. Since global warming control strategies can have wide reaching effects, a complex network was constructed. The network represents all energy production, conversion, transportation, distribution, and utilization activities. The structure of the network depicts interdependencies within and across economic sectors and was constructed such that energy prices and demand responses can be simulated. Global warming control alternatives represented in the network include: (1) conservation measures through increased efficiency; and (2) substitution of fuels that have high greenhouse gas emission rates with fuels that have lower emission rates. 6 refs., 4 figs., 4 tabs.

Hamilton, S.; Veselka, T.D.; Cirillo, R.R.

1991-01-01T23:59:59.000Z

92

Impact of the Demand-Side Management (DSM) Program structure on the cost-effectiveness of energy efficiency projects  

SciTech Connect

Pacific Northwest Laboratory (PNL) analyzed the cost-effective energy efficiency potential of Fort Drum, a customer of the Niagara Mohawk Power Corporation (NMPC) in Watertown, New York. Significant cost-effective investments were identified, even without any demand-side management (DSM) incentives from NMPC. Three NMPC DSM programs were then examined to determine the impact of participation on the cost-effective efficiency potential at the Fort. The following three utility programs were analyzed: (1) utility rebates to be paid back through surcharges, (2) a demand reduction program offered in conjunction with an energy services company, and (3) utility financing. Ultimately, utility rebates and financing were found to be the best programs for the Fort. This paper examines the influence that specific characteristics of the DSM programs had on the decision-making process of one customer. Fort Drum represents a significant demand-side resource, whose decisions regarding energy efficiency investments are based on life-cycle cost analysis subject to stringent capital constraints. The structures of the DSM programs offered by NMPC affect the cost-effectiveness of potential efficiency investments and the ability of the Fort to obtain sufficient capital to implement the projects. This paper compares the magnitude of the cost-effective resource available under each program, and the resulting level of energy and demand savings. The results of this analysis can be used to examine how DSM program structures impact the decision-making process of federal and large commercial customers.

Stucky, D.J.; Shankle, S.A.; Dixon, D.R.; Elliott, D.B.

1994-12-01T23:59:59.000Z

93

Demand Response  

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

Peak load diagram Demand Response Demand Response (DR) is a set of time-dependent activities that reduce or shift electricity use to improve electric grid reliability, manage...

94

Demand Response  

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

Peak load diagram Demand Response Demand response (DR) is a set of time-dependent activities that reduce or shift electricity use to improve electric grid reliability, manage...

95

The National Energy Modeling System: An Overview 1998 - Commercial Demand  

Gasoline and Diesel Fuel Update (EIA)

COMMERCIAL DEMAND MODULE COMMERCIAL DEMAND MODULE blueball.gif (205 bytes) Floorspace Submodule blueball.gif (205 bytes) Energy Service Demand Submodule blueball.gif (205 bytes) Equipment Choice Submodule blueball.gif (205 bytes) Energy Consumption Submodule The commercial demand module (CDM) forecasts energy consumption by Census division for eight marketed energy sources plus solar thermal energy. For the three major commercial sector fuels, electricity, natural gas and distillate oil, the CDM is a "structural" model and its forecasts are built up from projections of the commercial floorspace stock and of the energy-consuming equipment contained therein. For the remaining five marketed "minor fuels," simple econometric projections are made. The commercial sector encompasses business establishments that are not

96

Transportation Demand This  

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

Transportation Demand Transportation Demand This page inTenTionally lefT blank 75 U.S. Energy Information Administration | Assumptions to the Annual Energy Outlook 2013 Transportation Demand Module The NEMS Transportation Demand Module estimates transportation energy consumption across the nine Census Divisions (see Figure 5) and over ten fuel types. Each fuel type is modeled according to fuel-specific and associated technology attributes applicable by transportation mode. Total transportation energy consumption is the sum of energy use in eight transport modes: light-duty vehicles (cars and light trucks), commercial light trucks (8,501-10,000 lbs gross vehicle weight), freight trucks (>10,000 lbs gross vehicle weight), buses, freight and passenger aircraft, freight

97

Addressing Energy Demand through Demand Response: International...  

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

Energy Demand through Demand Response: International Experiences and Practices Title Addressing Energy Demand through Demand Response: International Experiences and Practices...

98

Addressing Energy Demand through Demand Response: International...  

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

Addressing Energy Demand through Demand Response: International Experiences and Practices Title Addressing Energy Demand through Demand Response: International Experiences and...

99

Fabrication of nano-structural arrays by channeling pulsed atomic beams through an intensity-modulated  

E-Print Network (OSTI)

Fabrication of nano-structural arrays by channeling pulsed atomic beams through an intensity-dimensional nano-structure arrays by passing a pulsed atomic beam through an intensity-modulated continuous of ``cooling'' along the longitudinal direction. This enables fabrication of vertically heterogeneous nano

Zhu, Xiangdong

100

Structure of a fibronectin type III-like module from Clostridium thermocellum  

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

878 878 doi:10.1107/S1744309110022529 Acta Cryst. (2010). F66, 878-880 Acta Crystallographica Section F Structural Biology and Crystallization Communications ISSN 1744-3091 Structure of a fibronectin type III-like module from Clostridium thermocellum Markus Alahuhta, Qi Xu, Roman Brunecky, William S. Adney, Shi-You Ding, Michael E. Himmel and Vladimir V. Lunin* BioSciences Center, National Renewable Energy Laboratory, 1617 Cole Boulevard, Golden, Colorado 80401-3305, USA Correspondence e-mail: vladimir.lunin@nrel.gov Received 29 April 2010 Accepted 11 June 2010 PDB Reference: fibronectin type III-like module, 3mpc. The 1.6 A ˚ resolution structure of a fibronectin type III-like module from Clostridium thermocellum (PDB code 3mpc) with two molecules in the asymmetric unit is reported. The crystals used for data collection belonged to space group P2 1 2 1 2 1 , with

Note: This page contains sample records for the topic "demand module structure" 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

The National Energy Modeling System: An Overview 1998 - Residential Demand  

Gasoline and Diesel Fuel Update (EIA)

RESIDENTIAL DEMAND MODULE RESIDENTIAL DEMAND MODULE blueball.gif (205 bytes) Housing Stock Submodule blueball.gif (205 bytes) Appliance Stock Submodule blueball.gif (205 bytes) Technology Choice Submodule blueball.gif (205 bytes) Shell Integrity Submodule blueball.gif (205 bytes) Fuel Consumption Submodule The residential demand module (RDM) forecasts energy consumption by Census division for seven marketed energy sources plus solar thermal and geothermal energy. The RDM is a structural model and its forecasts are built up from projections of the residential housing stock and of the energy-consuming equipment contained therein. The components of the RDM and its interactions with the NEMS system are shown in Figure 5. NEMS provides forecasts of residential energy prices, population, and housing starts,

102

Solar in Demand | Department of Energy  

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

in Demand Solar in Demand June 15, 2012 - 10:23am Addthis Kyle Travis, left and Jon Jackson, with Lighthouse Solar, install microcrystalline PV modules on top of Kevin Donovan's...

103

Self-modulation oscillation regimes in fibre lasers with microoptomechanical resonance structures  

Science Conference Proceedings (OSTI)

Self-modulation oscillation regimes are studied in erbium fibre lasers with intracavity microoptomechanical structures (microoscillators) of different types, namely, based on silicon structures and consisting of special waveguide segments. Optical excitation of acoustomechanical vibrations of microoscillators is accomplished using photothermal effect or light pressure. Under the conditions of resonance interaction, i.e., when the eigenfrequencies of microoscillators coincide with the frequencies of relaxation oscillations or with those of intermode beats, the dependences of self-oscillation characteristics on the system parameters are found and the stability of the self-modulation frequency within 10{sup -4} - 10{sup -6} is obtained at relatively low (40 - 300) Q-factors of microoscillators. The possibility to construct multivariate (multichannel) fibreoptical sensors of physical quantities with frequency division of measurement channels is demonstrated. (optical fibres, lasers and amplifiers. properties and applications)

Egorov, F A; Potapov, V T [V.A.Kotel'nikov Institute of Radio Engineering and Electronics, Fryazino Branch, Russian Academy of Sciences, Fryazino, Moscow Region (Russian Federation)

2012-09-30T23:59:59.000Z

104

Electricity Demand and Energy Consumption Management System  

E-Print Network (OSTI)

This project describes the electricity demand and energy consumption management system and its application to the Smelter Plant of Southern Peru. It is composted of an hourly demand-forecasting module and of a simulation component for a plant electrical system. The first module was done using dynamic neural networks, with backpropagation training algorithm; it is used to predict the electric power demanded every hour, with an error percentage below of 1%. This information allows management the peak demand before this happen, distributing the raise of electric load to other hours or improving those equipments that increase the demand. The simulation module is based in advanced estimation techniques, such as: parametric estimation, neural network modeling, statistic regression and previously developed models, which simulates the electric behavior of the smelter plant. These modules allow the proper planning because it allows knowing the behavior of the hourly demand and the consumption patterns of the plant, in...

Sarmiento, Juan Ojeda

2008-01-01T23:59:59.000Z

105

NEMS integrating module documentation report  

Science Conference Proceedings (OSTI)

The National Energy Modeling System (NEMS) is a computer modeling system that produces a general equilibrium solution for energy supply and demand in the US energy markets. The model achieves a supply and demand balance in the end-use demand regions, defined as the nine Census Divisions, by solving for the prices of each energy type such that the quantities producers are willing to supply equal the quantities consumers wish to consume. The system reflects market economics, industry structure, and energy policies and regulations that influence market behavior. The NEMS Integrating Module is the central integrating component of a complex modeling system. As such, a thorough understanding of its role in the modeling process can only be achieved by placing it in the proper context with respect to the other modules. To that end, this document provides an overview of the complete NEMS model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Not Available

1993-12-14T23:59:59.000Z

106

Structural design considerations for stretched-membrane heliostat reflector modules with stability and initial imperfection considerations  

Science Conference Proceedings (OSTI)

This report extends the work of several previous reports that present the background leading to the development of stretched-membrane modules and analysis methods to study the structural response of the stretched-membrane module. Specifically, this report presents and discusses the design implications based on our analysis of single- or double-membrane concepts, and the amplification of initial imperfections and deflections caused by loading, which results from stability considerations. In this document, we present analysis results for both single- and double-membrane concepts corresponding to a range of design and loading conditions. Further, we show that stretched-membrane/frame combinations respond quite differently to external loads than can be inferred by studying the decoupled frame and membrane independently. Thus the coupled membrane/frame problem should be considered to assure an accurate description of its response. For idealized configurations and loadings, we discuss the relative merits of various design features for both of these designs. In addition, we studied the structural stability (i.e., the tendency of structural deformation to grow with little increase in applied load) of the tensioned-membrane, compressed-frame combination. Moreover, we demonstrate how stability considerations are important in determining the amplification of both initial displacement imperfection and the deformations caused by wind and weight loading on the structure.

Murphy, L.M.; Simms, D.; Sallis, D.V.

1986-10-01T23:59:59.000Z

107

The National Energy Modeling System: An Overview 2000 - Industrial Demand  

Gasoline and Diesel Fuel Update (EIA)

industrial demand module (IDM) forecasts energy consumption for fuels and feedstocks for nine manufacturing industries and six nonmanufactur- ing industries, subject to delivered prices of energy and macroeconomic variables representing the value of output for each industry. The module includes industrial cogeneration of electricity that is either used in the industrial sector or sold to the electricity grid. The IDM structure is shown in Figure 7. industrial demand module (IDM) forecasts energy consumption for fuels and feedstocks for nine manufacturing industries and six nonmanufactur- ing industries, subject to delivered prices of energy and macroeconomic variables representing the value of output for each industry. The module includes industrial cogeneration of electricity that is either used in the industrial sector or sold to the electricity grid. The IDM structure is shown in Figure 7. Figure 7. Industrial Demand Module Structure Industrial energy demand is projected as a combination of “bottom up” characterizations of the energy-using technology and “top down” econometric estimates of behavior. The influence of energy prices on industrial energy consumption is modeled in terms of the efficiency of use of existing capital, the efficiency of new capital acquisitions, and the mix of fuels utilized, given existing capital stocks. Energy conservation from technological change is represented over time by trend-based “technology possibility curves.” These curves represent the aggregate efficiency of all new technologies that are likely to penetrate the future markets as well as the aggregate improvement in efficiency of 1994 technology.

108

Modulated structure of [beta]-brass CuZn compressed to 90 GPa  

Science Conference Proceedings (OSTI)

Cu-Zn is a classic example of an alloy system displaying a sequence of phases along an alloy composition, called Hume-Rothery phases. The crystal structure of these phases is determined by valence electron concentration (that is the average number of valence electrons per atom), and the lowering of the electronic energy is considered the key factor for the structure stabilization. Using powder x-ray diffraction, we study the {beta}-phase of an equiatomic CuZn alloy in its body-centered cubic (bcc) phase in the pressure range up to 90 GPa and find a transformation to a modulated trigonal structure at around 40 GPa. We analyze the structural distortion of bcc CuZn by looking at the configuration of the Brillouin zone of the bcc and the trigonal structures and their interaction with the Fermi surface. We demonstrate that the stabilization of the complex high-pressure structure can be explained with the Hume-Rothery effect.

Degtyareva, Olga; Degtyareva, Valentina F. (Edinburgh); (CIW)

2010-05-21T23:59:59.000Z

109

Demand Response  

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

Assessment for Eastern Interconnection Youngsun Baek, Stanton W. Hadley, Rocio Martinez, Gbadebo Oladosu, Alexander M. Smith, Fran Li, Paul Leiby and Russell Lee Prepared for FY12 DOE-CERTS Transmission Reliability R&D Internal Program Review September 20, 2012 2 Managed by UT-Battelle for the U.S. Department of Energy DOE National Laboratory Studies Funded to Support FOA 63 * DOE set aside $20 million from transmission funding for national laboratory studies. * DOE identified four areas of interest: 1. Transmission Reliability 2. Demand Side Issues 3. Water and Energy 4. Other Topics * Argonne, NREL, and ORNL support for EIPC/SSC/EISPC and the EISPC Energy Zone is funded through Area 4. * Area 2 covers LBNL and NREL work in WECC and

110

High Temperatures & Electricity Demand  

E-Print Network (OSTI)

High Temperatures & Electricity Demand An Assessment of Supply Adequacy in California Trends.......................................................................................................1 HIGH TEMPERATURES AND ELECTRICITY DEMAND.....................................................................................................................7 SECTION I: HIGH TEMPERATURES AND ELECTRICITY DEMAND ..........................9 BACKGROUND

111

Module Configuration  

SciTech Connect

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

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

2002-06-04T23:59:59.000Z

112

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

Gasoline and Diesel Fuel Update (EIA)

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

113

Advanced Demand Responsive Lighting  

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

Demand Demand Responsive Lighting Host: Francis Rubinstein Demand Response Research Center Technical Advisory Group Meeting August 31, 2007 10:30 AM - Noon Meeting Agenda * Introductions (10 minutes) * Main Presentation (~ 1 hour) * Questions, comments from panel (15 minutes) Project History * Lighting Scoping Study (completed January 2007) - Identified potential for energy and demand savings using demand responsive lighting systems - Importance of dimming - New wireless controls technologies * Advanced Demand Responsive Lighting (commenced March 2007) Objectives * Provide up-to-date information on the reliability, predictability of dimmable lighting as a demand resource under realistic operating load conditions * Identify potential negative impacts of DR lighting on lighting quality Potential of Demand Responsive Lighting Control

114

Demand Response Spinning Reserve  

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

Demand Response Spinning Reserve Title Demand Response Spinning Reserve Publication Type Report Year of Publication 2007 Authors Eto, Joseph H., Janine Nelson-Hoffman, Carlos...

115

Addressing Energy Demand  

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

Addressing Energy Demand through Demand Response: International Experiences and Practices Bo Shen, Girish Ghatikar, Chun Chun Ni, and Junqiao Dudley Environmental Energy...

116

Propane Sector Demand Shares  

U.S. Energy Information Administration (EIA)

... agricultural demand does not impact regional propane markets except when unusually high and late demand for propane for crop drying combines with early cold ...

117

International Energy Module  

Gasoline and Diesel Fuel Update (EIA)

he International Energy Module determines changes in the world oil price and the supply prices of crude he 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).

118

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.

119

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,

120

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

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


121

EIA - Assumptions to the Annual Energy Outlook 2009 - 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

122

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].

123

Demand Response and Open Automated Demand Response Opportunities...  

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

Demand Response and Open Automated Demand Response Opportunities for Data Centers Title Demand Response and Open Automated Demand Response Opportunities for Data Centers...

124

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network (OSTI)

of integrating demand response and energy efficiencyand D. Kathan (2009), Demand Response in U.S. ElectricityFRAMEWORKS THAT PROMOTE DEMAND RESPONSE 3.1. Demand Response

Shen, Bo

2013-01-01T23:59:59.000Z

125

Demand Trading: Building Liquidity  

Science Conference Proceedings (OSTI)

Demand trading holds substantial promise as a mechanism for efficiently integrating demand-response resources into regional power markets. However, regulatory uncertainty, the lack of proper price signals, limited progress toward standardization, problems in supply-side markets, and other factors have produced illiquidity in demand-trading markets and stalled the expansion of demand-response resources. This report shows how key obstacles to demand trading can be overcome, including how to remove the unce...

2002-11-27T23:59:59.000Z

126

Solar in Demand | Department of Energy  

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

Solar in Demand Solar in Demand Solar in Demand June 15, 2012 - 10:23am Addthis Kyle Travis, left and Jon Jackson, with Lighthouse Solar, install microcrystalline PV modules on top of Kevin Donovan's town home. | Credit: Dennis Schroeder. Kyle Travis, left and Jon Jackson, with Lighthouse Solar, install microcrystalline PV modules on top of Kevin Donovan's town home. | Credit: Dennis Schroeder. April Saylor April Saylor Former Digital Outreach Strategist, Office of Public Affairs What does this mean for me? A new study says U.S. developers are likely to install about 3,300 megawatts of solar panels in 2012 -- almost twice the amount installed last year. In case you missed it... This week, the Wall Street Journal published an article, "U.S. Solar-Panel Demand Expected to Double," highlighting the successes of

127

Electricity Market Module  

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

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

128

Demonstration of Demand Control Ventilation Technology  

Science Conference Proceedings (OSTI)

Demand Control Ventilation (DCV) is one of the control strategies that can be used modulate the amount of ventilation air for space conditioning in commercial buildings. DCV modulates the amount of ventilation air introduced into the heating, ventilation and air conditioning (HVAC) system based on carbon dioxide levels sensed in the areas served. The carbon dioxide level is a proxy for the number of people within the space, from which the required quantity of ventilation air is determined. By using this ...

2011-12-30T23:59:59.000Z

129

The National Energy Modeling System: An Overview 2000 - Residential Demand  

Gasoline and Diesel Fuel Update (EIA)

residential demand module (RDM) forecasts energy consumption by Census division for seven marketed energy sources plus solar and geothermal energy. RDM is a structural model and its forecasts are built up from projections of the residential housing stock and of the energy-consuming equipment contained therein. The components of RDM and its interactions with the NEMS system are shown in Figure 5. NEMS provides forecasts of residential energy prices, population, and housing starts, which are used by RDM to develop forecasts of energy consumption by fuel and Census division. residential demand module (RDM) forecasts energy consumption by Census division for seven marketed energy sources plus solar and geothermal energy. RDM is a structural model and its forecasts are built up from projections of the residential housing stock and of the energy-consuming equipment contained therein. The components of RDM and its interactions with the NEMS system are shown in Figure 5. NEMS provides forecasts of residential energy prices, population, and housing starts, which are used by RDM to develop forecasts of energy consumption by fuel and Census division. Figure 5. Residential Demand Module Structure RDM incorporates the effects of four broadly-defined determinants of energy consumption: economic and demographic effects, structural effects, technology turnover and advancement effects, and energy market effects. Economic and demographic effects include the number, dwelling type (single-family, multi-family or mobile homes), occupants per household, and location of housing units. Structural effects include increasing average dwelling size and changes in the mix of desired end-use services provided by energy (new end uses and/or increasing penetration of current end uses, such as the increasing popularity of electronic equipment and computers). Technology effects include changes in the stock of installed equipment caused by normal turnover of old, worn out equipment with newer versions which tend to be more energy efficient, the integrated effects of equipment and building shell (insulation level) in new construction, and in the projected availability of even more energy-efficient equipment in the future. Energy market effects include the short-run effects of energy prices on energy demands, the longer-run effects of energy prices on the efficiency of purchased equipment and the efficiency of building shells, and limitations on minimum levels of efficiency imposed by legislated efficiency standards.

130

Mass Market Demand Response  

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

Mass Market Demand Response Mass Market Demand Response Speaker(s): Karen Herter Date: July 24, 2002 - 12:00pm Location: Bldg. 90 Demand response programs are often quickly and poorly crafted in reaction to an energy crisis and disappear once the crisis subsides, ensuring that the electricity system will be unprepared when the next crisis hits. In this paper, we propose to eliminate the event-driven nature of demand response programs by considering demand responsiveness a component of the utility obligation to serve. As such, demand response can be required as a condition of service, and the offering of demand response rates becomes a requirement of utilities as an element of customer service. Using this foundation, we explore the costs and benefits of a smart thermostat-based demand response system capable of two types of programs: (1) a mandatory,

131

Demand Impacted by Weather  

U.S. Energy Information Administration (EIA)

When you look at demand, its also interesting to note the weather. The weather has a big impact on the demand of heating fuels, if its cold, consumers will use ...

132

Demand Trading Toolkit  

Science Conference Proceedings (OSTI)

Download report 1006017 for FREE. The global movement toward competitive markets is paving the way for a variety of market mechanisms that promise to increase market efficiency and expand customer choice options. Demand trading offers customers, energy service providers, and other participants in power markets the opportunity to buy and sell demand-response resources, just as they now buy and sell blocks of power. EPRI's Demand Trading Toolkit (DTT) describes the principles and practice of demand trading...

2001-12-10T23:59:59.000Z

133

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.

134

New Structural-Dynamics Module for Offshore Multimember Substructures within the Wind Turbine Computer-Aided Engineering Tool FAST: Preprint  

DOE Green Energy (OSTI)

FAST, developed by the National Renewable Energy Laboratory (NREL), is a computer-aided engineering (CAE) tool for aero-hydro-servo-elastic analysis of land-based and offshore wind turbines. This paper discusses recent upgrades made to FAST to enable loads simulations of offshore wind turbines with fixed-bottom, multimember support structures (e.g., jackets and tripods, which are commonly used in transitional-depth waters). The main theory and strategies for the implementation of the multimember substructure dynamics module (SubDyn) within the new FAST modularization framework are introduced. SubDyn relies on two main engineering schematizations: 1) a linear frame finite-element beam (LFEB) model and 2) a dynamics system reduction via Craig-Bampton's method. A jacket support structure and an offshore system consisting of a turbine atop a jacket substructure were simulated to test the SubDyn module and to preliminarily assess results against results from a commercial finite-element code.

Song, H.; Damiani, R.; Robertson, A.; Jonkman, J.

2013-08-01T23:59:59.000Z

135

Demand Response and Open Automated Demand Response Opportunities...  

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

Response and Open Automated Demand Response Opportunities for Data Centers Title Demand Response and Open Automated Demand Response Opportunities for Data Centers Publication Type...

136

Electrical Demand Management  

E-Print Network (OSTI)

The Demand Management Plan set forth in this paper has proven to be a viable action to reduce a 3 million per year electric bill at the Columbus Works location of Western Electric. Measures are outlined which have reduced the peak demand 5% below the previous year's level and yielded $150,000 annual savings. These measures include rescheduling of selected operations and demand limiting techniques such as fuel switching to alternate power sources during periods of high peak demand. For example, by rescheduling the startup of five heat treat annealing ovens to second shift, 950 kW of load was shifted off peak. Also, retired, non-productive steam turbine chillers and a diesel air compressor have been effectively operated to displaced 1330 kW during peak periods each day. Installed metering devices have enabled the recognition of critical demand periods. The paper concludes with a brief look at future plans and long range objectives of the Demand Management Plan.

Fetters, J. L.; Teets, S. J.

1983-01-01T23:59:59.000Z

137

Structure Determination of Two Modulated g-Brass Structures in the Zn-Pd System through a (3+1)-Dimensional Space Description  

Science Conference Proceedings (OSTI)

The structure determination of two composite compounds in the Zn-Pd system with close relationships to the cubic g-brass structure Zn11-dPd2+d is reported. Their structures have been solved from single crystal X-ray diffraction data within a (3 + 1)-dimensional [(3 + 1)D] formalism. Zn75.7(7)Pd24.3 and Zn78.8(7)Pd21.2 crystallize with orthorhombic symmetry, super space group Xmmm(00g)0s0 X=[(1/2,1/2,0,0);(0,1/2,1/2,1/2); (1/2,0,1/2,1/2)], with the following lattice parameters, respectively: as = 12.929(3) , bs = 9.112(4) , cs = 2.5631(7) , q = 8/13 c* and Vs = 302.1(3) A3 and as = 12.909(3) , bs = 9.115(3) , cs = 2.6052(6) , q = 11/18 c* and Vs = 306.4(2) A3. Their structures may be considered as commensurate because they can be refined in the conventional 3D space groups (Cmcm and Cmce, respectively) using super cells, but they also refined within the (3 + 1)D formalism to residual factors R = 3.22% for 139 parameters and 1184 independent reflections for Zn75.7(7)Pd24.3 and R = 3.46% for 197 parameters and 1804 independent reflections for Zn78.8(7)Pd21.2. The use of the (3 + 1)D formalism improves the results of the refinement and leads to a better understanding of the complexity of the atomic arrangement through the various modulations (occupation waves and displacive waves). Our refinements emphasize a unique Pd/Zn occupation modulation at the center of the icosahedra which is correlated with the distortion of the sites.

Gourdon, Olivier [ORNL; Izaola, Zunbeltz [Hahn-Meitner Institut, Berlin, Germany; Elcoro, Luis [University of Pais Vasco; Petricek, Vaclav [Institute of Physics, Czech Republic; Miller, Gordon J. [Iowa State University

2009-01-01T23:59:59.000Z

138

Demand Dispatch-Intelligent  

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

and energy efficiency throughout the value chain resulting in the most economical price for electricity. Having adequate quantities and capacities of demand resources is a...

139

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.

140

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

Gasoline and Diesel Fuel Update (EIA)

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

Note: This page contains sample records for the topic "demand module structure" 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

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

142

The Vertical Structure of TOGA COARE Convection. Part II: Modulating Influences and Implications for Diabatic Heating  

Science Conference Proceedings (OSTI)

The temporal variability of western Pacific warm pool convection, especially its vertical structure, is examined in this study. Distributions of convective echo top heights and 30-dBZ contour heights have been produced from shipboard radar data ...

Charlotte A. DeMott; Steven A. Rutledge

1998-09-01T23:59:59.000Z

143

Demand Response Valuation Frameworks Paper  

E-Print Network (OSTI)

xxxv Option Value of Electricity Demand Response, Osmanelasticity in aggregate electricity demand. With these newii) reduction in electricity demand during peak periods (

Heffner, Grayson

2010-01-01T23:59:59.000Z

144

U.S. Propane Demand  

U.S. Energy Information Administration (EIA)

Demand is higher in 1999 due to higher petrochemical demand and a strong economy. We are also seeing strong demand in the first quarter of 2000; however, ...

145

Automated Demand Response and Commissioning  

E-Print Network (OSTI)

Fully-Automated Demand Response Test in Large Facilities14in DR systems. Demand Response using HVAC in Commercialof Fully Automated Demand Response in Large Facilities

Piette, Mary Ann; Watson, David S.; Motegi, Naoya; Bourassa, Norman

2005-01-01T23:59:59.000Z

146

Demand Response Spinning Reserve Demonstration  

E-Print Network (OSTI)

F) Enhanced ACP Date RAA ACP Demand Response SpinningReserve Demonstration Demand Response Spinning Reservesupply spinning reserve. Demand Response Spinning Reserve

2007-01-01T23:59:59.000Z

147

A 1.5 A resolution X-ray structure of the catalytic module of Caldicellulosiruptor bescii family 3 pectate lyase  

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

1498 1498 doi:10.1107/S1744309111038449 Acta Cryst. (2011). F67, 1498-1500 Acta Crystallographica Section F Structural Biology and Crystallization Communications ISSN 1744-3091 A 1.5 A ˚ resolution X-ray structure of the catalytic module of Caldicellulosiruptor bescii family 3 pectate lyase Markus Alahuhta, a Puja Chandrayan, b Irina Kataeva, b Michael W. W. Adams, b Michael E. Himmel a and Vladimir V. Lunin a * a BioSciences Center, National Renewable Energy Laboratory, 1617 Cole Boulevard, Golden, CO 80401, USA, and b Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA 30602-7229, USA Correspondence e-mail: vladimir.lunin@nrel.gov Received 17 August 2011 Accepted 19 September 2011 PDB Reference: family 3 pectate lyase catalytic module, 3t9g. A 1.5 A ˚ resolution X-ray structure of the catalytic module of Caldicellulosi- ruptor bescii

148

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

149

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

150

CONSULTANT REPORT DEMAND FORECAST EXPERT  

E-Print Network (OSTI)

CONSULTANT REPORT DEMAND FORECAST EXPERT PANEL INITIAL forecast, end-use demand modeling, econometric modeling, hybrid demand modeling, energyMahon, Carl Linvill 2012. Demand Forecast Expert Panel Initial Assessment. California Energy

151

International Energy Module  

Reports and Publications (EIA)

Summarizes the overall structure of the International Energy Model and its interface with other NEMS modules, mathematical specifications of behavioral relationships, and data sources and estimation methods.

Adrian Geagla

2012-11-05T23:59:59.000Z

152

International Energy Module  

Reports and Publications (EIA)

Summarizes the overall structure of the International Energy Model and its interface with other NEMS modules, mathematical specifications of behavioral relationships, and data sources and estimation methods.

Adrian Geagla

2013-10-22T23:59:59.000Z

153

Automated Demand Response and Commissioning  

E-Print Network (OSTI)

internal conditions. Maximum Demand Saving Intensity [W/ft2]automated electric demand sheds. The maximum electric shed

Piette, Mary Ann; Watson, David S.; Motegi, Naoya; Bourassa, Norman

2005-01-01T23:59:59.000Z

154

Electricity Market Module  

Reports and Publications (EIA)

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

Jeff Jones

2013-07-24T23:59:59.000Z

155

Behavioral Aspects in Simulating the Future US Building Energy Demand  

E-Print Network (OSTI)

USA, and published in the Conference Proceedings Structure of SBEAM Floor-space forecast to 2050 Gross demandUSA, and published in the Conference Proceedings Structure of SBEAM Floor-space forecast to 2050 Gross demandUSA, and published in the Conference Proceedings Relative Importance Total off- site energy demand (

Stadler, Michael

2011-01-01T23:59:59.000Z

156

Modulating the phase structure of black D6 branes in canonical ensemble  

E-Print Network (OSTI)

There exists a dramatic difference in phase structure between charged black Dp-branes with $p liquid-gas type. However, when the two are combined to form D0/D6, the resulting phase diagram finally gets changed dramatically to the wanted one, containing now the above liquid-gas type. This change arises from the interaction between D6 and the delocalized D0.

J. X. Lu; Ran Wei

2013-01-09T23:59:59.000Z

157

demand | OpenEI  

Open Energy Info (EERE)

demand demand Dataset Summary Description This dataset contains hourly load profile data for 16 commercial building types (based off the DOE commercial reference building models) and residential buildings (based off the Building America House Simulation Protocols). This dataset also includes the Residential Energy Consumption Survey (RECS) for statistical references of building types by location. Source Commercial and Residential Reference Building Models Date Released April 18th, 2013 (9 months ago) Date Updated July 02nd, 2013 (7 months ago) Keywords building building demand building load Commercial data demand Energy Consumption energy data hourly kWh load profiles Residential Data Quality Metrics Level of Review Some Review Comment Temporal and Spatial Coverage Frequency Annually

158

Demand Response Database & Demo  

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

Demand Response Database & Demo Speaker(s): Mike Graveley William M. Smith Date: June 7, 2005 - 12:00pm Location: Bldg. 90 Seminar HostPoint of Contact: Mary Ann Piette Infotility...

159

Tankless Demand Water Heaters  

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

Demand (tankless or instantaneous) water heaters have heating devices that are activated by the flow of water, so they provide hot water only as needed and without the use of a storage tank. They...

160

Automated Demand Response Tests  

Science Conference Proceedings (OSTI)

This report includes assessments and test results of four end-use technologies, representing products in the residential, commercial, and industrial sectors, each configured to automatically receive real-time pricing information and critical peak pricing (CPP) demand response (DR) event notifications. Four different vendors were asked to follow the interface requirements set forth in the Open Automated Demand Response (OpenADR) standard that was introduced to the public in 2008 and currently used in two ...

2008-12-22T23:59:59.000Z

Note: This page contains sample records for the topic "demand module structure" 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

Automated Demand Response Tests  

Science Conference Proceedings (OSTI)

This report, which is an update to EPRI Report 1016082, includes assessments and test results of four end-use vendor technologies. These technologies represent products in the residential, commercial, and industrial sectors, each configured to automatically receive real-time pricing information and critical peak pricing (CPP) demand response (DR) event notifications. Four different vendors were asked to follow the interface requirements set forth in the Open Automated Demand Response (OpenADR) Communicat...

2009-03-30T23:59:59.000Z

162

Modular Communication Interface Specification for Demand Response  

Science Conference Proceedings (OSTI)

This report contains a technical specification for a modular interface for residential appliances that enables them to be compatible with any utility communication system through the use of customer-installable plug-in communication modules. This specification is the result of collaboration between utilities, appliance makers, communication system providers, demand response service providers, and trade organizations. The specification details the mechanical, electrical, and logical characteristics of a s...

2011-08-31T23:59:59.000Z

163

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network (OSTI)

time. 4 Reducing this peak demand through DR programs meansthat a 5% reduction in peak demand would have resulted insame 5% reduction in the peak demand of the US as a whole.

Shen, Bo

2013-01-01T23:59:59.000Z

164

Demand and Price Volatility: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

shift in the short-run price elasticity of gasoline demand.A meta-analysis of the price elasticity of gasoline demand.2007. Consumer demand un- der price uncertainty: Empirical

Scott, K. Rebecca

2011-01-01T23:59:59.000Z

165

California Independent System Operator demand response & proxy demand resources  

Science Conference Proceedings (OSTI)

Demand response programs are designed to allow end use customers to contribute to energy load reduction individually or through a demand response provider. One form of demand response can occur when an end use customer reduces their electrical usage ...

John Goodin

2012-01-01T23:59:59.000Z

166

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.

167

Demand Response In California  

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

Energy Efficiency & Energy Efficiency & Demand Response Programs Dian M. Grueneich, Commissioner Dian M. Grueneich, Commissioner California Public Utilities Commission California Public Utilities Commission FUPWG 2006 Fall Meeting November 2, 2006 Commissioner Dian M. Grueneich November 2, 2006 1 Highest Priority Resource Energy Efficiency is California's highest priority resource to: Meet energy needs in a low cost manner Aggressively reduce GHG emissions November 2, 2006 2 Commissioner Dian M. Grueneich November 2, 2006 3 http://www.cpuc.ca.gov/PUBLISHED/REPORT/51604.htm Commissioner Dian M. Grueneich November 2, 2006 4 Energy Action Plan II Loading order continued "Pursue all cost-effective energy efficiency, first." Strong demand response and advanced metering

168

Travel Demand Modeling  

SciTech Connect

This chapter describes the principal types of both passenger and freight demand models in use today, providing a brief history of model development supported by references to a number of popular texts on the subject, and directing the reader to papers covering some of the more recent technical developments in the area. Over the past half century a variety of methods have been used to estimate and forecast travel demands, drawing concepts from economic/utility maximization theory, transportation system optimization and spatial interaction theory, using and often combining solution techniques as varied as Box-Jenkins methods, non-linear multivariate regression, non-linear mathematical programming, and agent-based microsimulation.

Southworth, Frank [ORNL; Garrow, Dr. Laurie [Georgia Institute of Technology

2011-01-01T23:59:59.000Z

169

Automated Demand Response Today  

Science Conference Proceedings (OSTI)

Demand response (DR) has progressed over recent years beyond manual and semi-automated DR to include growing implementation and experience with fully automated demand response (AutoDR). AutoDR has been shown to be of great value over manual and semi-automated DR because it reduces the need for human interactions and decisions, and it increases the speed and reliability of the response. AutoDR, in turn, has evolved into the specification known as OpenADR v1.0 (California Energy Commission, PIER Program, C...

2012-03-29T23:59:59.000Z

170

United States lubricant demand  

Science Conference Proceedings (OSTI)

This paper examines United States Lubricant Demand for Automotive and Industrial Lubricants by year from 1978 to 1992 and 1997. Projected total United States Lubricant Demand for 1988 is 2,725 million (or MM) gallons. Automotive oils are expected to account for 1,469MM gallons or (53.9%), greases 59MM gallons (or 2.2%), and Industrial oils will account for the remaining 1,197MM gallons (or 43.9%) in 1988. This proportional relationship between Automotive and Industrial is projected to remain relatively constant until 1992 and out to 1997. Projections for individual years between 1978 to 1992 and 1997 are summarized.

Solomon, L.K.; Pruitt, P.R.

1988-01-01T23:59:59.000Z

171

Demand Response Valuation Frameworks Paper  

E-Print Network (OSTI)

No. ER06-615-000 CAISO Demand Response Resource User Guide -8 2.1. Demand Response Provides a Range of Benefits to8 2.2. Demand Response Benefits can be Quantified in Several

Heffner, Grayson

2010-01-01T23:59:59.000Z

172

On Demand Guarantees in Iran.  

E-Print Network (OSTI)

??On Demand Guarantees in Iran This thesis examines on demand guarantees in Iran concentrating on bid bonds and performance guarantees. The main guarantee types and (more)

Ahvenainen, Laura

2009-01-01T23:59:59.000Z

173

Transportation Demand Management Plan  

E-Print Network (OSTI)

Transportation Demand Management Plan FALL 2009 #12;T r a n s p o r t a t i o n D e m a n d M a n the transportation impacts the expanded enrollment will have. Purpose and Goal The primary goal of the TDM plan is to ensure that adequate measures are undertaken and maintained to minimize the transportation impacts

174

Band gap tunability of molecular beam epitaxy grown lateral composition modulated GaInP structures by controlling V/III flux ratio  

Science Conference Proceedings (OSTI)

Lateral composition modulated (LCM) GaInP structures were grown on (001) GaAs substrate by molecular beam epitaxy with different V/III flux ratios. Band gap of LCM structures could be tuned from 1.93 eV to 1.83 eV by decreasing flux ratio while maintaining the same photoluminescence intensity, enhanced light absorption, and widened absorption spectrum. It is shown that for band gap tuning of LCM structures, flux ratio adjustment is a more viable method compared to growth temperature adjustment.

Park, K. W. [School of Information and Communications, Gwangju Institute of Science and Technology, Gwangju 500-712 (Korea, Republic of); Park, C. Y. [Micro Systems Laboratory, Samsung Advanced Institute of Technology, Yongin 446-712 (Korea, Republic of); Lee, Y. T. [School of Information and Communications, Gwangju Institute of Science and Technology, Gwangju 500-712 (Korea, Republic of); Department of Nanobio Materials and Electronics, Gwangju Institute of Science and Technology, Gwangju 500-712 (Korea, Republic of); Department of Photonics and Applied Physics, Gwangju Institute of Science and Technology, Gwangju 500-712 (Korea, Republic of)

2012-07-30T23:59:59.000Z

175

An Integrated Architecture for Demand Response Communications and Control  

E-Print Network (OSTI)

and produced a maximum demand reduction Proceedings of the 41st Hawaii International Conference on SystemAn Integrated Architecture for Demand Response Communications and Control Michael LeMay, Rajesh,gross,cgunter}@uiuc.edu Abstract In the competitive electricity structure, demand re- sponse programs

Gross, George

176

Structure and Function of the Clostridium thermocellum Cellobiohydrolase A X1-Module Repeat: Enhancement Through Stabilization of the CbhA Complex  

DOE Green Energy (OSTI)

The efficient deconstruction of lignocellulosic biomass remains a significant barrier to the commercialization of biofuels. Whereas most commercial plant cell-wall-degrading enzyme preparations used today are derived from fungi, the cellulosomal enzyme system from Clostridium thermocellum is an equally effective catalyst, yet of considerably different structure. A key difference between fungal enzyme systems and cellulosomal enzyme systems is that cellulosomal enzyme systems utilize self-assembled scaffolded multimodule enzymes to deconstruct biomass. Here, the possible function of the X1 modules in the complex multimodular enzyme system cellobiohydrolase A (CbhA) from C. thermocellum is explored. The crystal structures of the two X1 modules from C. thermocellum CbhA have been solved individually and together as one construct. The role that calcium may play in the stability of the X1 modules has also been investigated, as well as the possibility that they interact with each other. Furthermore, the results show that whereas the X1 modules do not seem to act as cellulose disruptors, they do aid in the thermostability of the CbhA complex, effectively allowing it to deconstruct cellulose at a higher temperature.

Brunecky, R.; Alahuhta, M.; Bomble, Y. J.; Xu, Q.; Baker, J. O.; Ding, S. Y.; Himmel, M. E.; Lunin, V. V.

2012-03-01T23:59:59.000Z

177

Photovoltaic module and module arrays  

DOE Patents (OSTI)

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

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

2012-07-17T23:59:59.000Z

178

On Demand Paging Using  

E-Print Network (OSTI)

The power consumption of the network interface plays a major role in determining the total operating lifetime of wireless handheld devices. On demand paging has been proposed earlier to reduce power consumption in cellular networks. In this scheme, a low power secondary radio is used to wake up the higher power radio, allowing the latter to sleep or remain off for longer periods of time. In this paper we present use of Bluetooth radios to serve as a paging channel for the 802.11 wireless LAN. We have implemented an on-demand paging scheme on a WLAN consisting of iPAQ PDAs equipped with Bluetooth radios and Cisco Aironet wireless networking cards. Our results show power saving ranging from 19% to 46% over the present 802.11b standard operating modes with negligible impact on performance.

Bluetooth Radios On; Yuvraj Agarwal; Rajesh K. Gupta

2003-01-01T23:59:59.000Z

179

ENERGY DEMAND FORECAST METHODS REPORT  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report to the California Energy Demand 2006-2016 Staff Energy Demand Forecast Report STAFFREPORT June 2005 CEC-400 .......................................................................................................................................1-1 ENERGY DEMAND FORECASTING AT THE CALIFORNIA ENERGY COMMISSION: AN OVERVIEW

180

Demand Forecast INTRODUCTION AND SUMMARY  

E-Print Network (OSTI)

Demand Forecast INTRODUCTION AND SUMMARY A 20-year forecast of electricity demand is a required of any forecast of electricity demand and developing ways to reduce the risk of planning errors that could arise from this and other uncertainties in the planning process. Electricity demand is forecast

Note: This page contains sample records for the topic "demand module structure" 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

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

182

Net Demand3 Production  

E-Print Network (OSTI)

Contract Number: DE-FE0004002 (Subcontract: S013-JTH-PPM4002 MOD 00) Summary The US DOE has identified a number of materials that are both used by clean energy technologies and are at risk of supply disruptions in the short term. Several of these materials, especially the rare earth elements (REEs) yttrium, cerium, and lanthanum were identified by DOE as critical (USDOE 2010) and are crucial to the function and performance of solid oxide fuel cells (SOFCs) 1. In addition, US DOE has issued a second Request For Information regarding uses of and markets for these critical materials (RFI;(USDOE 2011)). This report examines how critical materials demand for SOFC applications could impact markets for these materials and vice versa, addressing categories 1,2,5, and 6 in the RFI. Category 1 REE Content of SOFC Yttria (yttrium oxide) is the only critical material (as defined for the timeframe of interest for SOFC) used in SOFC 2. Yttrium is used as a dopant in the SOFCs core ceramic cells.. In addition, continuing developments in SOFC technology will likely further reduce REE demand for SOFC, providing credible scope for at least an additional 50 % reduction in REE use if desirable. Category 2 Supply Chain and Market Demand SOFC developers expect to purchase

J. Thijssen Llc

2011-01-01T23:59:59.000Z

183

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

184

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

Natural Gas Demands..xi Annual natural gas demand for each alternativeused in natural gas demand projections. 34

McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

2008-01-01T23:59:59.000Z

185

Coherent terahertz radiation from high-harmonic component of modulated free-electron beam in a tapered two-asymmetric grating structure  

SciTech Connect

Based on the mechanism of incoherent diffraction radiation excited by an electron bunch in a waveguide with periodic structure, this paper presents the concept of coherent terahertz (THz) radiation from the high-harmonic component of a modulated free-electron beam in a tapered two-asymmetric grating structure. The results show that in this mechanism 0.43 THz radiation can be generated with 10 A/cm{sup 2} current density, and the efficiency can reach 0.5%. Because of the low required current density and relative high efficiency, this concept shows the application potential for electron-beam-driven terahertz sources.

Zhang Yaxin; Zhou Yucong; Dong Liang; Liu Shenggang [Terahertz Science and Technology Research Center, University of Electronic Science and Technology of China, Chengdu 610054 (China)

2012-09-17T23:59:59.000Z

186

PDSF Modules  

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

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

187

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

Minimum demand and Maximum demand incorporate assumptionslevels, or very minor Maximum demand household size, growthvehicles in Increasing Maximum demand 23 mpg truck share

McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

2008-01-01T23:59:59.000Z

188

Photovoltaic Modules: Effect of Tilt Angle on Soiling.  

E-Print Network (OSTI)

??Photovoltaic (PV) systems are one of the next generation's renewable energy sources for our world energy demand. PV modules are highly reliable. However, in polluted (more)

Cano, Jose

2011-01-01T23:59:59.000Z

189

Dividends with Demand Response  

SciTech Connect

To assist facility managers in assessing whether and to what extent they should participate in demand response programs offered by ISOs, we introduce a systematic process by which a curtailment supply curve can be developed that integrates costs and other program provisions and features. This curtailment supply curve functions as bid curve, which allows the facility manager to incrementally offer load to the market under terms and conditions acceptable to the customer. We applied this load curtailment assessment process to a stylized example of an office building, using programs offered by NYISO to provide detail and realism.

Kintner-Meyer, Michael CW; Goldman, Charles; Sezgen, O.; Pratt, D.

2003-10-31T23:59:59.000Z

190

Chinese demand drives global deforestation Chinese demand drives global deforestation  

E-Print Network (OSTI)

Chinese demand drives global deforestation Chinese demand drives global deforestation By Tansa Musa zones and do not respect size limits in their quest for maximum financial returns. "I lack words economy. China's demand for hardwood drives illegal logging says "Both illegal and authorized

191

Estimating a Demand System with Nonnegativity Constraints: Mexican Meat Demand  

E-Print Network (OSTI)

: Properties of the AIDS Generalized Maximum Entropy Estimator 24 #12;Estimating a Demand SystemEstimating a Demand System with Nonnegativity Constraints: Mexican Meat Demand Amos Golan* Jeffrey with nonnegativity constraints is presented. This approach, called generalized maximum entropy (GME), is more

Perloff, Jeffrey M.

192

CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST Demand Forecast report is the product of the efforts of many current and former California Energy Commission staff. Staff contributors to the current forecast are: Project Management and Technical Direction

193

Demand Response | Department of Energy  

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

Demand Response Demand Response Demand Response Demand Response Demand response provides an opportunity for consumers to play a significant role in the operation of the electric grid by reducing or shifting their electricity usage during peak periods in response to time-based rates or other forms of financial incentives. Demand response programs are being used by electric system planners and operators as resource options for balancing supply and demand. Such programs can lower the cost of electricity in wholesale markets, and in turn, lead to lower retail rates. Methods of engaging customers in demand response efforts include offering time-based rates such as time-of-use pricing, critical peak pricing, variable peak pricing, real time pricing, and critical peak rebates. It also includes direct load control programs which provide the

194

ELECTRICITY DEMAND FORECAST COMPARISON REPORT  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION ELECTRICITY DEMAND FORECAST COMPARISON REPORT STAFFREPORT June 2005 ..............................................................................3 Residential Forecast Comparison ..............................................................................................5 Nonresidential Forecast Comparisons

195

Overview of Demand Response  

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

08 PJM 08 PJM www.pjm.com ©2003 PJM Overview of Demand Response PJM ©2008 PJM www.pjm.com ©2003 PJM Growth, Statistics, and Current Footprint AEP, Dayton, ComEd, & DUQ Dominion Generating Units 1,200 + Generation Capacity 165,000 MW Peak Load 144,644 MW Transmission Miles 56,070 Area (Square Miles) 164,250 Members 500 + Population Served 51 Million Area Served 13 States and DC Generating Units 1,200 + Generation Capacity 165,000 MW Peak Load 144,644 MW Transmission Miles 56,070 Area (Square Miles) 164,250 Members 500 + Population Served 51 Million Area Served 13 States and DC Current PJM RTO Statistics Current PJM RTO Statistics PJM Mid-Atlantic Integrations completed as of May 1 st , 2005 ©2008 PJM

196

New and Underutilized Technology: Carbon Dioxide Demand Ventilation Control  

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

Carbon Dioxide Demand Ventilation Carbon Dioxide Demand Ventilation Control New and Underutilized Technology: Carbon Dioxide Demand Ventilation Control October 4, 2013 - 4:23pm Addthis The following information outlines key deployment considerations for carbon dioxide (CO2) demand ventilation control within the Federal sector. Benefits Demand ventilation control systems modulate ventilation levels based on current building occupancy, saving energy while still maintaining proper indoor air quality (IAQ). CO2 sensors are commonly used, but a multiple-parameter approach using total volatile organic compounds (TVOC), particulate matter (PM), formaldehyde, and relative humidity (RH) levels can also be used. CO2 sensors control the outside air damper to reduce the amount of outside air that needs to be conditioned and supplied to the building when

197

Transmaterialization: technology and materials demand cycles  

SciTech Connect

Recently concern has risen worldwide regarding the issue of declining materials demand which has been termed dematerialization. A summary of the issues involved appears in the proceedings of the recent conference on metals demand published in Materials and Society (1986). Dematerialization refers to the constant decline in use of materials as a percentage of total production. Dematerialization implies a structural change in an economy, indicating a reduced demand for materials and, therefore, a decline in overall industrial growth. This paper proposes that, instead of dematerialization in the US material markets, the demand change that has been occurring can be more aptly described as transmaterialization. Transmaterialization implies a recurring industrial transformation in the way that economic societies use materials, a process that has occurred regularly or cyclically throughout history. Instead of a once and for all structural change as implied by dematerialization, transmaterialization suggests that minerals demand experiences phases in which old, lower-quality materials linked to mature industries undergo replacement periodically by higher-quality or technologically-more-appropriate materials. The latter, as of recent, tend to be lighter materials with more robust technical properties than those being replaced.

Waddell, L.M.; Labys, W.C.

1988-01-01T23:59:59.000Z

198

Oxygenate Supply/Demand Balances  

Gasoline and Diesel Fuel Update (EIA)

Oxygenate Supply/Demand Oxygenate Supply/Demand Balances in the Short-Term Integrated Forecasting Model By Tancred C.M. Lidderdale This article first appeared in the Short-Term Energy Outlook Annual Supplement 1995, Energy Information Administration, DOE/EIA-0202(95) (Washington, DC, July 1995), pp. 33-42, 83-85. The regression results and historical data for production, inventories, and imports have been updated in this presentation. Contents * Introduction o Table 1. Oxygenate production capacity and demand * Oxygenate demand o Table 2. Estimated RFG demand share - mandated RFG areas, January 1998 * Fuel ethanol supply and demand balance o Table 3. Fuel ethanol annual statistics * MTBE supply and demand balance o Table 4. EIA MTBE annual statistics * Refinery balances

199

Commercial Demand Module of the National Energy Modeling ...  

U.S. Energy Information Administration (EIA)

Commercial Buildings Energy Consumption Survey ... space cooling, water heating, ventilation, cooking, refrigeration, and lighting. The market segment ...

200

Model Documentation Report: Residential Demand Module of the ...  

U.S. Energy Information Administration (EIA)

New home heating technology choice model log-linear parameter ?. ... Percent of homes meeting ENERGY STAR Home criteria or better by heating technology

Note: This page contains sample records for the topic "demand module structure" 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

Demand Response Programs, 6. edition  

Science Conference Proceedings (OSTI)

The report provides a look at the past, present, and future state of the market for demand/load response based upon market price signals. It is intended to provide significant value to individuals and companies who are considering participating in demand response programs, energy providers and ISOs interested in offering demand response programs, and consultants and analysts looking for detailed information on demand response technology, applications, and participants. The report offers a look at the current Demand Response environment in the energy industry by: defining what demand response programs are; detailing the evolution of program types over the last 30 years; discussing the key drivers of current initiatives; identifying barriers and keys to success for the programs; discussing the argument against subsidization of demand response; describing the different types of programs that exist including:direct load control, interruptible load, curtailable load, time-of-use, real time pricing, and demand bidding/buyback; providing examples of the different types of programs; examining the enablers of demand response programs; and, providing a look at major demand response programs.

NONE

2007-10-15T23:59:59.000Z

202

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network (OSTI)

2007 EMCS EPACT ERCOT FCM FERC FRCC demand side managementEnergy Regulatory Commission (FERC). EPAct began the processin wholesale markets, which FERC Order 888 furthered by

Shen, Bo

2013-01-01T23:59:59.000Z

203

J. Plasma Fusion Res. SERIES, Vol. 8 (2009) Structures Formation in Inhomogeneous Plasma Excited by Thin Modulated Electron Beam  

E-Print Network (OSTI)

Interaction of a thin modulated electron beam with inhomogeneous non-isothermal plasma is studied using 2D PIC electrostatic simulation. On the early stage of the interaction intensive HF oscillations of the electric field are observed in the local plasma resonance region. The ponderomotive force of these oscillations disturbs the initial profile of plasma density. On the later stage of the interaction a ring-like pulse of the plasma density propagates out of the resonance region. Velocity of this pulse depends on its intensity and exceeds the ion sound velocity. This fact demonstrates the nonlinear nature of the pulse.

Taras Eu. Litoshenko; Ihor O. Anisimov

2008-01-01T23:59:59.000Z

204

electricity demand | OpenEI  

Open Energy Info (EERE)

demand demand Dataset Summary Description The New Zealand Ministry of Economic Development publishes energy data including many datasets related to electricity. Included here are three electricity consumption and demand datasets, specifically: annual observed electricity consumption by sector (1974 to 2009); observed percentage of consumers by sector (2002 - 2009); and regional electricity demand, as a percentage of total demand (2009). Source New Zealand Ministry of Economic Development Date Released Unknown Date Updated July 03rd, 2009 (5 years ago) Keywords Electricity Consumption electricity demand energy use by sector New Zealand Data application/vnd.ms-excel icon Electricity Consumption by Sector (1974 - 2009) (xls, 46.1 KiB) application/vnd.ms-excel icon Percentage of Consumers by Sector (2002 - 2009) (xls, 43.5 KiB)

205

Annual World Oil Demand Growth  

Gasoline and Diesel Fuel Update (EIA)

6 6 Notes: Following relatively small increases of 1.3 million barrels per day in 1999 and 0.9 million barrels per day in 2000, EIA is estimating world demand may grow by 1.6 million barrels per day in 2001. Of this increase, about 3/5 comes from non-OECD countries, while U.S. oil demand growth represents more than half of the growth projected in OECD countries. Demand in Asia grew steadily during most of the 1990s, with 1991-1997 average growth per year at just above 0.8 million barrels per day. However, in 1998, demand dropped by 0.3 million barrels per day as a result of the Asian economic crisis that year. Since 1998, annual growth in oil demand has rebounded, but has not yet reached the average growth seen during 1991-1997. In the Former Soviet Union, oil demand plummeted during most of the

206

Demand Response Valuation Frameworks Paper  

E-Print Network (OSTI)

lvi Southern California Edison filed its SmartConnectinfrastructure (e.g. , Edison Electric Institute, DemandSouthern California Edison Standard Practice Manual

Heffner, Grayson

2010-01-01T23:59:59.000Z

207

Automated Demand Response and Commissioning  

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

and Commissioning Title Automated Demand Response and Commissioning Publication Type Conference Paper LBNL Report Number LBNL-57384 Year of Publication 2005 Authors Piette, Mary...

208

Demand Uncertainty and Price Dispersion.  

E-Print Network (OSTI)

??Demand uncertainty has been recognized as one factor that may cause price dispersion in perfectly competitive markets with costly and perishable capacity. With the persistence (more)

Li, Suxi

2007-01-01T23:59:59.000Z

209

1995 Demand-Side Managment  

U.S. Energy Information Administration (EIA)

U.S. Electric Utility Demand-Side Management 1995 January 1997 Energy Information Administration Office of Coal, Nuclear, Electric and Alternate Fuels

210

Critical infrastructure security curriculum modules  

Science Conference Proceedings (OSTI)

Critical infrastructures have succumbed to the demands of greater connectivity. Although the scheme of connecting these critical equipment and devices to cyberspace has brought us tremendous convenience, it also enabled certain unimaginable risks and ... Keywords: SCADA, control systems, course modules, critical infrastructures, cybersecurity, programmable logic controllers, security, vulnerability

Guillermo A. Francia, III

2011-09-01T23:59:59.000Z

211

Demand Responsive Lighting: A Scoping Study  

E-Print Network (OSTI)

8 Figure 7: Maximum Demands Savings Intensity due toaddressed in this report. Maximum Demand Savings Intensity (Echelon Figure 7: Maximum Demands Savings Intensity due to

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

212

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

energy efficiency and demand response programs and tariffs.energy efficiency and demand response program and tariffenergy efficiency and demand response programs and tariffs.

Goldman, Charles

2010-01-01T23:59:59.000Z

213

Wireless Demand Response Controls for HVAC Systems  

E-Print Network (OSTI)

Strategies Linking Demand Response and Energy Efficiency,Fully Automated Demand Response Tests in Large Facilities,technical support from the Demand Response Research Center (

Federspiel, Clifford

2010-01-01T23:59:59.000Z

214

Demand Response Quick Assessment Tool (DRQAT)  

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

Demand Response Quick Assessment Tool (DRQAT) The opportunities for demand reduction and cost saving with building demand responsive control vary tremendously with building type...

215

Demand Responsive Lighting: A Scoping Study  

E-Print Network (OSTI)

2 2.0 Demand ResponseFully Automated Demand Response Tests in Large Facilities,was coordinated by the Demand Response Research Center and

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

216

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network (OSTI)

8.4 Demand Response Integration . . . . . . . . . . .for each day type for the demand response study - moderatefor each day type for the demand response study - moderate

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

217

Installation and Commissioning Automated Demand Response Systems  

E-Print Network (OSTI)

their partnership in demand response automation research andand Techniques for Demand Response. LBNL Report 59975. Mayof Fully Automated Demand Response in Large Facilities.

Kiliccote, Sila; Global Energy Partners; Pacific Gas and Electric Company

2008-01-01T23:59:59.000Z

218

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

and D. Kathan (2009). Demand Response in U.S. ElectricityEnergy Financial Group. Demand Response Research Center [2008). Assessment of Demand Response and Advanced Metering.

Goldman, Charles

2010-01-01T23:59:59.000Z

219

Strategies for Demand Response in Commercial Buildings  

E-Print Network (OSTI)

Fully Automated Demand Response Tests in Large Facilitiesof Fully Automated Demand Response in Large Facilities,was coordinated by the Demand Response Research Center and

Watson, David S.; Kiliccote, Sila; Motegi, Naoya; Piette, Mary Ann

2006-01-01T23:59:59.000Z

220

Retail Demand Response in Southwest Power Pool  

E-Print Network (OSTI)

23 ii Retail Demand Response in SPP List of Figures and10 Figure 3. Demand Response Resources by11 Figure 4. Existing Demand Response Resources by Type of

Bharvirkar, Ranjit

2009-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "demand module structure" 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

Option Value of Electricity Demand Response  

E-Print Network (OSTI)

Table 1. Economic demand response and real time pricing (Implications of Demand Response Programs in CompetitiveAdvanced Metering, and Demand Response in Electricity

Sezgen, Osman; Goldman, Charles; Krishnarao, P.

2005-01-01T23:59:59.000Z

222

Role of context-awareness for demand response mechanisms  

Science Conference Proceedings (OSTI)

Recently due to major changes in the structure of electricity industry and the rising costs of power generation, many countries have realized the potential and benefits of smart metering systems and demand response programs in balancing between the supply ... Keywords: context-awareness, demand response, smart energy management

Pari Delir Haghighi; Shonali Krishnaswamy

2011-08-01T23:59:59.000Z

223

China, India demand cushions prices  

SciTech Connect

Despite the hopes of coal consumers, coal prices did not plummet in 2006 as demand stayed firm. China and India's growing economies, coupled with solid supply-demand fundamentals in North America and Europe, and highly volatile prices for alternatives are likely to keep physical coal prices from wide swings in the coming year.

Boyle, M.

2006-11-15T23:59:59.000Z

224

Harnessing the power of demand  

Science Conference Proceedings (OSTI)

Demand response can provide a series of economic services to the market and also provide ''insurance value'' under low-likelihood, but high-impact circumstances in which grid reliablity is enhanced. Here is how ISOs and RTOs are fostering demand response within wholesale electricity markets. (author)

Sheffrin, Anjali; Yoshimura, Henry; LaPlante, David; Neenan, Bernard

2008-03-15T23:59:59.000Z

225

Demand Response for Ancillary Services  

Science Conference Proceedings (OSTI)

Many demand response resources are technically capable of providing ancillary services. In some cases, they can provide superior response to generators, as the curtailment of load is typically much faster than ramping thermal and hydropower plants. Analysis and quantification of demand response resources providing ancillary services is necessary to understand the resources economic value and impact on the power system. Methodologies used to study grid integration of variable generation can be adapted to the study of demand response. In the present work, we describe and illustrate a methodology to construct detailed temporal and spatial representations of the demand response resource and to examine how to incorporate those resources into power system models. In addition, the paper outlines ways to evaluate barriers to implementation. We demonstrate how the combination of these three analyses can be used to translate the technical potential for demand response providing ancillary services into a realizable potential.

Alkadi, Nasr E [ORNL; Starke, Michael R [ORNL

2013-01-01T23:59:59.000Z

226

Strategies for Demand Response in Commercial Buildings  

E-Print Network (OSTI)

the average and maximum peak demand savings. The electricity1: Average and Maximum Peak Electric Demand Savings during

Watson, David S.; Kiliccote, Sila; Motegi, Naoya; Piette, Mary Ann

2006-01-01T23:59:59.000Z

227

Demand Response Opportunities in Industrial Refrigerated Warehouses...  

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

Demand Response Opportunities in Industrial Refrigerated Warehouses in California Title Demand Response Opportunities in Industrial Refrigerated Warehouses in California...

228

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

Model of the Global Crude Oil Market and the U.S. RetailNoureddine. 2002. World crude oil and natural gas: a demandanalysis of the demand for oil in the Middle East. Energy

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

229

Demand and Price Volatility: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

A Joint Model of the Global Crude Oil Market and the U.S.Noureddine. 2002. World crude oil and natural gas: a demandelasticity of demand for crude oil, not gasoline. Results

Scott, K. Rebecca

2011-01-01T23:59:59.000Z

230

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

A Joint Model of the Global Crude Oil Market and the U.S.Noureddine. 2002. World crude oil and natural gas: a demandelasticity of demand for crude oil, not gasoline. Results

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

231

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network (OSTI)

global gasoline and diesel price and income elasticities.shift in the short-run price elasticity of gasoline demand.Habits and Uncertain Relative Prices: Simulating Petrol Con-

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

232

Modeling the residential demand for energy  

Science Conference Proceedings (OSTI)

Demand for energy is derived from the demand for services that appliances and energy together provide. This raises a number of serious econometric issues when estimating energy-demand functions: delineation of short-run and long-run household responses, specification of the price variable and in particular, the assumption that the model is recursive, or in other words, that the appliance choice equation and the energy consumption equation are uncorrelated. The dissertation utilizes a structural model of energy use whose theoretical underpinnings derive from the conditional logit model and an extension of that model to the joint-discrete/continuous case by Dubin and McFadden (1980). It uses the 1978 to 1979 National Interim Energy Comsumption Survey. Three appliance portfolio choices are analyzed; choice of water and space heating and central air-conditioning; choice of room air conditioners; and choice of clothes dryers, either as multinomial logit or binary probit choices. Results varied widely across the appliance choice considered; use of Hausman's test led to acceptance of the null hypothesis of orthogonality in some cases but not in others. Demand for electricity and natural gas tended to be price inelastic; however, estimated own-price effects differed considerably when disaggregated by appliance categories and across methods of estimation.

Kirby, S.N.

1983-01-01T23:59:59.000Z

233

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

234

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

235

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

236

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

237

Structure and function of the Clostridium thermocellum cellobiohydrolase A X1-module repeat: enhancement through stabilization of the CbhA complex  

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

292 292 doi:10.1107/S0907444912001680 Acta Cryst. (2012). D68, 292-299 Acta Crystallographica Section D Biological Crystallography ISSN 0907-4449 Structure and function of the Clostridium thermocellum cellobiohydrolase A X1-module repeat: enhancement through stabilization of the CbhA complex Roman Brunecky, Markus Alahuhta, Yannick J. Bomble, Qi Xu, John O. Baker, Shi-You Ding, Michael E. Himmel and Vladimir V. Lunin* Biosciences Center, National Renewable Energy Laboratory, 1617 Cole Boulevard, Golden, CO 80401, USA Correspondence e-mail: vladimir.lunin@nrel.gov # 2012 International Union of Crystallography Printed in Singapore - all rights reserved The efficient deconstruction of lignocellulosic biomass remains a significant barrier to the commercialization of biofuels. Whereas most commercial plant cell-wall-degrading enzyme preparations used today

238

Effects of the drought on California electricity supply and demand  

E-Print Network (OSTI)

Acknowledgments SUMMARY Electricity Demand ElectricityAdverse Impacts ELECTRICITY DEMAND . . . .Demand forElectricity Sales Electricity Demand by Major Utility

Benenson, P.

2010-01-01T23:59:59.000Z

239

Module Handbook Specialisation Photovoltaics  

E-Print Network (OSTI)

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

Habel, Annegret

240

building demand | OpenEI  

Open Energy Info (EERE)

demand demand Dataset Summary Description This dataset contains hourly load profile data for 16 commercial building types (based off the DOE commercial reference building models) and residential buildings (based off the Building America House Simulation Protocols). This dataset also includes the Residential Energy Consumption Survey (RECS) for statistical references of building types by location. Source Commercial and Residential Reference Building Models Date Released April 18th, 2013 (9 months ago) Date Updated July 02nd, 2013 (7 months ago) Keywords building building demand building load Commercial data demand Energy Consumption energy data hourly kWh load profiles Residential Data Quality Metrics Level of Review Some Review Comment Temporal and Spatial Coverage Frequency Annually

Note: This page contains sample records for the topic "demand module structure" 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

Demand Response Research in Spain  

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

Demand Response Research in Spain Demand Response Research in Spain Speaker(s): Iñigo Cobelo Date: August 22, 2007 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Mary Ann Piette The Spanish power system is becoming increasingly difficult to operate. The peak load grows every year, and the permission to build new transmission and distribution infrastructures is difficult to obtain. In this scenario Demand Response can play an important role, and become a resource that could help network operators. The present deployment of demand response measures is small, but this situation however may change in the short term. The two main Spanish utilities and the transmission network operator are designing research projects in this field. All customer segments are targeted, and the research will lead to pilot installations and tests.

242

EIA - AEO2010 - Electricity Demand  

Gasoline and Diesel Fuel Update (EIA)

Electricity Demand Electricity Demand Annual Energy Outlook 2010 with Projections to 2035 Electricity Demand Figure 69. U.S. electricity demand growth 1950-2035 Click to enlarge » Figure source and data excel logo Figure 60. Average annual U.S. retail electricity prices in three cases, 1970-2035 Click to enlarge » Figure source and data excel logo Figure 61. Electricity generation by fuel in three cases, 2008 and 2035 Click to enlarge » Figure source and data excel logo Figure 62. Electricity generation capacity additions by fuel type, 2008-2035 Click to enlarge » Figure source and data excel logo Figure 63. Levelized electricity costs for new power plants, 2020 and 2035 Click to enlarge » Figure source and data excel logo Figure 64. Electricity generating capacity at U.S. nuclear power plants in three cases, 2008, 2020, and 2035

243

Winter Demand Impacted by Weather  

Gasoline and Diesel Fuel Update (EIA)

8 Notes: Heating oil demand is strongly influenced by weather. The "normal" numbers are the expected values for winter 2000-2001 used in EIA's Short-Term Energy Outlook. The chart...

244

Demand for money in China .  

E-Print Network (OSTI)

??This research investigates the long-run equilibrium relationship between money demand and its determinants in China over the period 1952-2004 for three definitions of money (more)

Zhang, Qing

2006-01-01T23:59:59.000Z

245

Thermal Mass and Demand Response  

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

Thermal Mass and Demand Response Speaker(s): Gregor Henze Phil C. Bomrad Date: November 2, 2011 - 12:00pm Location: 90-4133 Seminar HostPoint of Contact: Janie Page The topic of...

246

Automated Demand Response and Commissioning  

E-Print Network (OSTI)

Conference on Building Commissioning: May 4-6, 2005 Motegi,National Conference on Building Commissioning: May 4-6, 2005Demand Response and Commissioning Mary Ann Piette, David S.

Piette, Mary Ann; Watson, David S.; Motegi, Naoya; Bourassa, Norman

2005-01-01T23:59:59.000Z

247

Distillate Demand Strong Last Winter  

Gasoline and Diesel Fuel Update (EIA)

4 Notes: Well, distillate fuel demand wasn't the reason that stocks increased in January 2001 and kept prices from going higher. As you will hear shortly, natural gas prices spiked...

248

Leslie Mancebo (7234) Transportation Demand &  

E-Print Network (OSTI)

Leslie Mancebo (7234) Transportation Demand & Marketing Coordinator 1 FTE, 1 HC Administrative Vice Chancellor Transportation and Parking Services Clifford A. Contreras (0245) Director 30.10 FTE Alternative Transportation & Marketing Reconciliation Lourdes Lupercio (4723) Michelle McArdle (7512) Parking

Hammock, Bruce D.

249

STEO December 2012 - coal demand  

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

coal demand seen below 1 billion tons in 2012 for fourth year in a row Coal consumption by U.S. power plants to generate electricity is expected to fall below 1 billion tons in...

250

Demand Response Spinning Reserve Demonstration  

Science Conference Proceedings (OSTI)

The Demand Response Spinning Reserve project is a pioneeringdemonstration of how existing utility load-management assets can providean important electricity system reliability resource known as spinningreserve. Using aggregated demand-side resources to provide spinningreserve will give grid operators at the California Independent SystemOperator (CAISO) and Southern California Edison (SCE) a powerful, newtool to improve system reliability, prevent rolling blackouts, and lowersystem operating costs.

Eto, Joseph H.; Nelson-Hoffman, Janine; Torres, Carlos; Hirth,Scott; Yinger, Bob; Kueck, John; Kirby, Brendan; Bernier, Clark; Wright,Roger; Barat, A.; Watson, David S.

2007-05-01T23:59:59.000Z

251

Application on demand system over the Internet  

E-Print Network (OSTI)

This paper describes the design and implementation of the ASP-NG system. The main modules of the ASP-NG system are the AoD service and the Web Portal. The ASP-NG Portal is a portal for providing the user with the necessary interface in order to access an Application on Demand (AoD) service. The ASP-NG portal is responsible for the interaction with the user of the AoD service. Using the AoD service the user rents an application for a limited time period at a fraction of the actual cost of the application. The AoD service is responsible for downloading the appropriate parts of the application according to the user's actions, while enforcing the mutually agreed frame between the user and the Application Service Provider (ASP). The implementation of the ASP-NG portal is based on the Web Services of the Java 2, Enterprise Edition platform and the implementation of the AoD module is based on CCCprogramming language. The ASP-NG portal offers to its users the capability to select and customize the language of the user interface in order to present information in their preferred language. Moreover the ASP-NG portal offers to the portal administrator the capability to customise the look and feel of the ASP-NG portal.

Ch Bouras Gkamas; Ch. Bouras A; A. Gkamas A; I. Nave B; D. Primpas A; A. Shani B; O. Sheory B; K. Stamos A; Y. Tzruya C

2004-01-01T23:59:59.000Z

252

National Action Plan on Demand Response  

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

Action Plan on Demand National Action Plan on Demand Action Plan on Demand National Action Plan on Demand Response Response Federal Utilities Partnership Working Group Federal Utilities Partnership Working Group November 18, 2008 November 18, 2008 Daniel Gore Daniel Gore Office of Energy Market Regulation Office of Energy Market Regulation Federal Energy Regulatory Commission Federal Energy Regulatory Commission The author's views do not necessarily represent the views of the Federal Energy Regulatory Commission Presentation Contents Presentation Contents Statutory Requirements Statutory Requirements National Assessment [Study] of Demand Response National Assessment [Study] of Demand Response National Action Plan on Demand Response National Action Plan on Demand Response General Discussion on Demand Response and Energy Outlook

253

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.

254

Demand Response and Open Automated Demand Response Opportunities for Data Centers  

E-Print Network (OSTI)

Standardized Automated Demand Response Signals. Presented atand Automated Demand Response in Industrial RefrigeratedActions for Industrial Demand Response in California. LBNL-

Mares, K.C.

2010-01-01T23:59:59.000Z

255

Open Automated Demand Response Communications in Demand Response for Wholesale Ancillary Services  

E-Print Network (OSTI)

A. Barat, D. Watson. 2006 Demand Response Spinning ReserveKueck, and B. Kirby 2008. Demand Response Spinning ReserveReport 2009. Open Automated Demand Response Communications

Kiliccote, Sila

2010-01-01T23:59:59.000Z

256

Definition: Demand | Open Energy Information  

Open Energy Info (EERE)

form form View source History View New Pages Recent Changes All Special Pages Semantic Search/Querying Get Involved Help Apps Datasets Community Login | Sign Up Search Definition Edit with form History Facebook icon Twitter icon » Definition: Demand Jump to: navigation, search Dictionary.png Demand The rate at which electric energy is delivered to or by a system or part of a system, generally expressed in kilowatts or megawatts, at a given instant or averaged over any designated interval of time., The rate at which energy is being used by the customer.[1] Related Terms energy, electricity generation References ↑ Glossary of Terms Used in Reliability Standards An i Like Like You like this.Sign Up to see what your friends like. nline Glossary Definition Retrieved from "http://en.openei.org/w/index.php?title=Definition:Demand&oldid=480555"

257

Successful demand-side management  

Science Conference Proceedings (OSTI)

This article is a brief summary of a series of case studies of five publicly-owned utilities that are noted for their success with demand-side management. These utilities are: (1) city of Austin, Texas, (2) Burlington Electric Department in Vermont, (3) Sacramento Municipal Utility District in California, (4) Seattle City Light, and (5) Waverly Light and Power in Iowa. From these case studies, the authors identified a number of traits associated with a successful demand-side management program. These traits are: (1) high rates, (2) economic factors, (3) environmental awareness, (4) state emphasis on integrated resource planning/demand side management, (5) local political support, (6) large-sized utilities, and (7) presence of a champion.

Hadley, S. [Oak Ridge National Laboratory, TN (United States); Flanigan, T. [Results Center, Aspen, CO (United States)

1995-05-01T23:59:59.000Z

258

Winter Demand Impacted by Weather  

Gasoline and Diesel Fuel Update (EIA)

8 8 Notes: Heating oil demand is strongly influenced by weather. The "normal" numbers are the expected values for winter 2000-2001 used in EIA's Short-Term Energy Outlook. The chart indicates the extent to which the last winter exhibited below-normal heating degree-days (and thus below-normal heating demand). Temperatures were consistently warmer than normal throughout the 1999-2000 heating season. This was particularly true in November 1999, February 2001 and March 2001. For the heating season as a whole (October through March), the 1999-2000 winter yielded total HDDs 10.7% below normal. Normal temperatures this coming winter would, then, be expected to bring about 11% higher heating demand than we saw last year. Relative to normal, the 1999-2000 heating season was the warmest in

259

Turkey's energy demand and supply  

SciTech Connect

The aim of the present article is to investigate Turkey's energy demand and the contribution of domestic energy sources to energy consumption. Turkey, the 17th largest economy in the world, is an emerging country with a buoyant economy challenged by a growing demand for energy. Turkey's energy consumption has grown and will continue to grow along with its economy. Turkey's energy consumption is high, but its domestic primary energy sources are oil and natural gas reserves and their production is low. Total primary energy production met about 27% of the total primary energy demand in 2005. Oil has the biggest share in total primary energy consumption. Lignite has the biggest share in Turkey's primary energy production at 45%. Domestic production should be to be nearly doubled by 2010, mainly in coal (lignite), which, at present, accounts for almost half of the total energy production. The hydropower should also increase two-fold over the same period.

Balat, M. [Sila Science, Trabzon (Turkey)

2009-07-01T23:59:59.000Z

260

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

residential electricity consumption, the flattening of the demand curves (except Maximum demand) reflects decreasing population growth ratesresidential electricity demand are described in Table 11. For simplicity, end use-specific UEC and saturation rates

McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

2008-01-01T23:59:59.000Z

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


261

EIA projections of coal supply and demand  

SciTech Connect

Contents of this report include: EIA projections of coal supply and demand which covers forecasted coal supply and transportation, forecasted coal demand by consuming sector, and forecasted coal demand by the electric utility sector; and policy discussion.

Klein, D.E.

1989-10-23T23:59:59.000Z

262

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

percent of 2008 summer peak demand (FERC, 2008). Moreover,138,000 MW (14 percent of peak demand) by 2019 (FERC, 2009).non-coincident summer peak demand by 157 GW by 2030, or 14

Goldman, Charles

2010-01-01T23:59:59.000Z

263

Retail Demand Response in Southwest Power Pool  

E-Print Network (OSTI)

pricing tariffs have a peak demand reduction potential ofneed to reduce summer peak demand that is used to set demandcustomers and a system peak demand of over 43,000 MW. SPPs

Bharvirkar, Ranjit

2009-01-01T23:59:59.000Z

264

Demand Responsive Lighting: A Scoping Study  

E-Print Network (OSTI)

with total Statewide peak demand and on peak days isto examine the electric peak demand related to lighting inDaily) - TOU Savings - Peak Demand Charges - Grid Peak -Low

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

265

Tankless Demand Water Heaters | Department of Energy  

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

Demand Water Heaters Tankless Demand Water Heaters August 19, 2013 - 2:57pm Addthis Illustration of an electric demand water heater. At the top of the image, the heating unit is...

266

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand.Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product to the contributing authors listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad

267

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST Volume 2: Electricity Demand The demand forecast is the combined product of the hard work and expertise of numerous California Energy previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped prepare

268

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand Robert P. Oglesby Executive Director #12;i ACKNOWLEDGEMENTS The demand forecast is the combined prepared the commercial sector forecast. Mehrzad Soltani Nia helped prepare the industrial forecast

269

Electric Utility Demand-Side Management 1997  

U.S. Energy Information Administration (EIA)

Electric Utility Demand-Side Management 1997 Executive Summary Background Demand-side management (DSM) programs consist of the planning, implementing, and monitoring ...

270

Equity Capital Flows and Demand for REITs  

Science Conference Proceedings (OSTI)

This paper examines the shape of the market demand curve for ... Our results do not support a downward demand curve for ... Charleston, IL 61920, USA e-mail:...

271

Home Network Technologies and Automating Demand Response  

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

electricity generation capacity to meet unrestrained future demand. To address peak electricity use Demand Response (DR) systems are being proposed to motivate reductions in...

272

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

California Long-term Energy Efficiency Strategic Plan. B-2 Coordination of Energy Efficiency and Demand Response> B-4 Coordination of Energy Efficiency and Demand Response

Goldman, Charles

2010-01-01T23:59:59.000Z

273

Installation and Commissioning Automated Demand Response Systems  

E-Print Network (OSTI)

al: Installation and Commissioning Automated Demand ResponseConference on Building Commissioning: April 22 24, 2008al: Installation and Commissioning Automated Demand Response

Kiliccote, Sila; Global Energy Partners; Pacific Gas and Electric Company

2008-01-01T23:59:59.000Z

274

EIA - Annual Energy Outlook 2009 - Electricity Demand  

Gasoline and Diesel Fuel Update (EIA)

data Rate of Electricity Demand Growth Slows, Following the Historical Trend Electricity demand fluctuates in the short term in response to business cycles, weather conditions,...

275

Demand Response as a System Reliability Resource  

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

Demand Response as a System Reliability Resource Title Demand Response as a System Reliability Resource Publication Type Report Year of Publication 2012 Authors Eto, Joseph H.,...

276

Option Value of Electricity Demand Response  

E-Print Network (OSTI)

Oakland CA, December. PJM Demand Side Response WorkingPrice Response Program a PJM Economic Load Response ProgramLoad Response Statistics PJM Demand Response Working Group

Sezgen, Osman; Goldman, Charles; Krishnarao, P.

2005-01-01T23:59:59.000Z

277

Retail Demand Response in Southwest Power Pool  

E-Print Network (OSTI)

Regulatory Commission (FERC) 2006. Assessment of DemandRegulatory Commission (FERC) 2007. Assessment of DemandRegulatory Commission (FERC) 2008a. Wholesale Competition

Bharvirkar, Ranjit

2009-01-01T23:59:59.000Z

278

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

29 5.6. Peak and hourly demand43 6.6. Peak and seasonal demandthe average percent of peak demand) significantly impact the

McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

2008-01-01T23:59:59.000Z

279

Water demand management in Kuwait  

E-Print Network (OSTI)

Kuwait is an arid country located in the Middle East, with limited access to water resources. Yet water demand per capita is much higher than in other countries in the world, estimated to be around 450 L/capita/day. There ...

Milutinovic, Milan, M. Eng. Massachusetts Institute of Technology

2006-01-01T23:59:59.000Z

280

Demand-Side Management Glossary  

Science Conference Proceedings (OSTI)

In recent years, demand-side management (DSM) programs have grown in significance within the U.S. electric power industry. Such rapid growth has resulted in new terms, standards, and vocabulary used by DSM professionals. This report is a first attempt to provide a consistent set of definitions for the expanding DSM terminology.

1992-11-01T23:59:59.000Z

Note: This page contains sample records for the topic "demand module structure" 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

Demand Dispatch Intelligent Demand for a More Efficient Grid  

E-Print Network (OSTI)

This report was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor any agency thereof, nor any of their employees, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness of any information, apparatus, product, or process disclosed, or represents that its use would not infringe privately owned rights. Reference therein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof. The views and opinions of authors expressed therein do not necessarily state or reflect those of the United States Government or any agency thereof. Demand Dispatch: Intelligent Demand for a More Efficient Grid

Keith Dodrill

2011-01-01T23:59:59.000Z

282

The alchemy of demand response: turning demand into supply  

Science Conference Proceedings (OSTI)

Paying customers to refrain from purchasing products they want seems to run counter to the normal operation of markets. Demand response should be interpreted not as a supply-side resource but as a secondary market that attempts to correct the misallocation of electricity among electric users caused by regulated average rate tariffs. In a world with costless metering, the DR solution results in inefficiency as measured by deadweight losses. (author)

Rochlin, Cliff

2009-11-15T23:59:59.000Z

283

US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier  

E-Print Network (OSTI)

US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier Approach Massimo www.cepe.ethz.ch #12;US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier Approach Page 1 of 25 US Residential Energy Demand and Energy Efficiency: A Stochastic Demand Frontier

284

Thermionic modules  

DOE Patents (OSTI)

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

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

2002-06-18T23:59:59.000Z

285

Sensor-based demand controlled ventilation  

SciTech Connect

In most buildings, occupancy and indoor pollutant emission rates vary with time. With sensor-based demand-controlled ventilation (SBDCV), the rate of ventilation (i.e., rate of outside air supply) also varies with time to compensate for the changes in pollutant generation. In other words, SBDCV involves the application of sensing, feedback and control to modulate ventilation. Compared to ventilation without feedback, SBDCV offers two potential advantages: (1) better control of indoor pollutant concentrations; and (2) lower energy use and peak energy demand. SBDCV has the potential to improve indoor air quality by increasing the rate of ventilation when indoor pollutant generation rates are high and occupants are present. SBDCV can also save energy by decreasing the rate of ventilation when indoor pollutant generation rates are low or occupants are absent. After providing background information on indoor air quality and ventilation, this report provides a relatively comprehensive discussion of SBDCV. Topics covered in the report include basic principles of SBDCV, sensor technologies, technologies for controlling air flow rates, case studies of SBDCV, application of SBDCV to laboratory buildings, and research needs. SBDCV appears to be an increasingly attractive technology option. Based on the review of literature and theoretical considerations, the application of SBDCV has the potential to be cost-effective in applications with the following characteristics: (a) a single or small number of dominant pollutants, so that ventilation sufficient to control the concentration of the dominant pollutants provides effective control of all other pollutants; (b) large buildings or rooms with unpredictable temporally variable occupancy or pollutant emission; and (c) climates with high heating or cooling loads or locations with expensive energy.

De Almeida, A.T. [Universidade de Coimbra (Portugal). Dep. Eng. Electrotecnica; Fisk, W.J. [Lawrence Berkeley National Lab., CA (United States)

1997-07-01T23:59:59.000Z

286

Evaluation Framework for Sustainable Demand Response Implementations: A Framework for Evaluating Demand Response Implementation Alte rnatives for Sustainability  

Science Conference Proceedings (OSTI)

This report presents a framework for evaluating demand response (DR) implementation options with the goal of achieving long-term sustainability. Effective implementation of DR can help reduce energy price volatility and maintain or improve service reliability. The DR evaluation framework provides a structured, systematic approach to help utility personnel and other stakeholders in planning and comparing demand response options, toward the goal of implementing sustainable DR programs that support utility ...

2011-12-30T23:59:59.000Z

287

Energy Demand | Open Energy Information  

Open Energy Info (EERE)

Energy Demand Energy Demand Jump to: navigation, search Click to return to AEO2011 page AEO2011 Data Figure 55 From AEO2011 report . Market Trends Growth in energy use is linked to population growth through increases in housing, commercial floorspace, transportation, and goods and services. These changes affect not only the level of energy use, but also the mix of fuels used. Energy consumption per capita declined from 337 million Btu in 2007 to 308 million Btu in 2009, the lowest level since 1967. In the AEO2011 Reference case, energy use per capita increases slightly through 2013, as the economy recovers from the 2008-2009 economic downturn. After 2013, energy use per capita declines by 0.3 percent per year on average, to 293 million Btu in 2035, as higher efficiency standards for vehicles and

288

Demand Response and Risk Management  

Science Conference Proceedings (OSTI)

For several decades, power companies have deployed various types of demand response (DR), such as interruptible contracts, and there is substantial ongoing research and development on sophisticated mechanisms for triggering DR. In this white paper, EPRI discusses the increasing use of electricity DR in the power industry and how this will affect the practice of energy risk management. This paper outlines 1) characteristics of a common approach to energy risk management, 2) the variety of types of DR impl...

2008-12-18T23:59:59.000Z

289

Building Technologies Office: Integrated Predictive Demand Response  

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

Integrated Predictive Integrated Predictive Demand Response Controller Research Project to someone by E-mail Share Building Technologies Office: Integrated Predictive Demand Response Controller Research Project on Facebook Tweet about Building Technologies Office: Integrated Predictive Demand Response Controller Research Project on Twitter Bookmark Building Technologies Office: Integrated Predictive Demand Response Controller Research Project on Google Bookmark Building Technologies Office: Integrated Predictive Demand Response Controller Research Project on Delicious Rank Building Technologies Office: Integrated Predictive Demand Response Controller Research Project on Digg Find More places to share Building Technologies Office: Integrated Predictive Demand Response Controller Research Project on AddThis.com...

290

Integrating Module of the National Energy Modeling System ...  

U.S. Energy Information Administration (EIA)

Chapter 3 describes the NEMS global data structure, used for inter-module communication, ... technologies, representations of renewable energy technologies, ...

291

Demand Trading: Measurement, Verification, and Settlement (MVS)  

Science Conference Proceedings (OSTI)

With this report, EPRI's trilogy of publications on demand trading is complete. The first report (1006015), the "Demand Trading Toolkit," documented how to conduct demand trading based on price. The second report (1001635), "Demand Trading: Building Liquidity," focused on the problem of liquidity in the energy industry and developed the Demand Response Resource Bank concept for governing electricity markets based on reliability. The present report focuses on the emerging price/risk partnerships in electr...

2004-03-18T23:59:59.000Z

292

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

293

A dynamic model of industrial energy demand in Kenya  

Science Conference Proceedings (OSTI)

This paper analyses the effects of input price movements, technology changes, capacity utilization and dynamic mechanisms on energy demand structures in the Kenyan industry. This is done with the help of a variant of the second generation dynamic factor demand (econometric) model. This interrelated disequilibrium dynamic input demand econometric model is based on a long-term cost function representing production function possibilities and takes into account the asymmetry between variable inputs (electricity, other-fuels and Tabour) and quasi-fixed input (capital) by imposing restrictions on the adjustment process. Variations in capacity utilization and slow substitution process invoked by the relative input price movement justifies the nature of input demand disequilibrium. The model is estimated on two ISIS digit Kenyan industry time series data (1961 - 1988) using the Iterative Zellner generalized least square method. 31 refs., 8 tabs.

Haji, S.H.H. [Gothenburg Univ. (Sweden)

1994-12-31T23:59:59.000Z

294

Automated Demand Response Opportunities in Wastewater Treatment Facilities  

E-Print Network (OSTI)

Interoperable Automated Demand Response Infrastructure,study of automated demand response in wastewater treatmentopportunities for demand response control strategies in

Thompson, Lisa

2008-01-01T23:59:59.000Z

295

Opportunities, Barriers and Actions for Industrial Demand Response in California  

E-Print Network (OSTI)

and Techniques for Demand Response, report for theand Reliability Demand Response Programs: Final Report.Demand Response

McKane, Aimee T.

2009-01-01T23:59:59.000Z

296

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network (OSTI)

Report 2009. Open Automated Demand Response Communicationsand Techniques for Demand Response. California Energyand S. Kiliccote. Estimating Demand Response Load Impacts:

Kiliccote, Sila

2010-01-01T23:59:59.000Z

297

Effects of the drought on California electricity supply and demand  

E-Print Network (OSTI)

DEMAND . . . .Demand for Electricity and Power PeakDemand . . . . ELECTRICITY REQUIREMENTS FOR AGRICULTUREResults . . Coriclusions ELECTRICITY SUPPLY Hydroelectric

Benenson, P.

2010-01-01T23:59:59.000Z

298

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network (OSTI)

14 Peak Demand Baselinewinter morning electric peak demand in commercial buildings.California to reduce peak demand during summer afternoons,

Kiliccote, Sila

2010-01-01T23:59:59.000Z

299

Price-elastic demand in deregulated electricity markets  

E-Print Network (OSTI)

by the amount of electricity demand that is settled forward.unresponsive demand side, electricity demand has to be metxed percentage of overall electricity demand. The ISO, thus,

Siddiqui, Afzal S.

2003-01-01T23:59:59.000Z

300

Building Energy Software Tools Directory : Demand Response Quick...  

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

Demand Response Quick Assessment Tool Back to Tool Demand response quick assessment tool screenshot Demand response quick assessment tool screenshot Demand response quick...

Note: This page contains sample records for the topic "demand module structure" 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

Automated Demand Response Strategies and Commissioning Commercial Building Controls  

E-Print Network (OSTI)

Braun (Purdue). 2004. Peak demand reduction from pre-coolingthe average and maximum peak demand savings. The electricityuse charges, demand ratchets, peak demand charges, and other

Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila; Linkugel, Eric

2006-01-01T23:59:59.000Z

302

Demand Response Valuation Frameworks Paper  

Science Conference Proceedings (OSTI)

While there is general agreement that demand response (DR) is a valued component in a utility resource plan, there is a lack of consensus regarding how to value DR. Establishing the value of DR is a prerequisite to determining how much and what types of DR should be implemented, to which customers DR should be targeted, and a key determinant that drives the development of economically viable DR consumer technology. Most approaches for quantifying the value of DR focus on changes in utility system revenue requirements based on resource plans with and without DR. This ''utility centric'' approach does not assign any value to DR impacts that lower energy and capacity prices, improve reliability, lower system and network operating costs, produce better air quality, and provide improved customer choice and control. Proper valuation of these benefits requires a different basis for monetization. The review concludes that no single methodology today adequately captures the wide range of benefits and value potentially attributed to DR. To provide a more comprehensive valuation approach, current methods such as the Standard Practice Method (SPM) will most likely have to be supplemented with one or more alternative benefit-valuation approaches. This report provides an updated perspective on the DR valuation framework. It includes an introduction and four chapters that address the key elements of demand response valuation, a comprehensive literature review, and specific research recommendations.

Heffner, Grayson

2009-02-01T23:59:59.000Z

303

Demand Side Bidding. Final Report  

SciTech Connect

This document sets forth the final report for a financial assistance award for the National Association of Regulatory Utility Commissioners (NARUC) to enhance coordination between the building operators and power system operators in terms of demand-side responses to Location Based Marginal Pricing (LBMP). Potential benefits of this project include improved power system reliability, enhanced environmental quality, mitigation of high locational prices within congested areas, and the reduction of market barriers for demand-side market participants. NARUC, led by its Committee on Energy Resources and the Environment (ERE), actively works to promote the development and use of energy efficiency and clean distributive energy policies within the framework of a dynamic regulatory environment. Electric industry restructuring, energy shortages in California, and energy market transformation intensifies the need for reliable information and strategies regarding electric reliability policy and practice. NARUC promotes clean distributive generation and increased energy efficiency in the context of the energy sector restructuring process. NARUC, through ERE's Subcommittee on Energy Efficiency, strives to improve energy efficiency by creating working markets. Market transformation seeks opportunities where small amounts of investment can create sustainable markets for more efficient products, services, and design practices.

Spahn, Andrew

2003-12-31T23:59:59.000Z

304

Rack assembly for mounting solar modules  

SciTech Connect

A rack assembly is provided for mounting solar modules over an underlying body. The rack assembly may include a plurality of rail structures that are arrangeable over the underlying body to form an overall perimeter for the rack assembly. One or more retention structures may be provided with the plurality of rail structures, where each retention structure is configured to support one or more solar modules at a given height above the underlying body. At least some of the plurality of rail structures are adapted to enable individual rail structures to be sealed over the underlying body so as to constrain air flow underneath the solar modules. Additionally, at least one of (i) one or more of the rail structures, or (ii) the one or more retention structures are adjustable so as to adapt the rack assembly to accommodate solar modules of varying forms or dimensions.

Plaisted, Joshua Reed; West, Brian

2012-09-04T23:59:59.000Z

305

Rack assembly for mounting solar modules  

SciTech Connect

A rack assembly is provided for mounting solar modules over an underlying body. The rack assembly may include a plurality of rail structures that are arrangeable over the underlying body to form an overall perimeter for the rack assembly. One or more retention structures may be provided with the plurality of rail structures, where each retention structure is configured to support one or more solar modules at a given height above the underlying body. At least some of the plurality of rail structures are adapted to enable individual rail structures o be sealed over the underlying body so as to constrain air flow underneath the solar modules. Additionally, at least one of (i) one or more of the rail structures, or (ii) the one or more retention structures are adjustable so as to adapt the rack assembly to accommodate solar modules of varying forms or dimensions.

Plaisted, Joshua Reed (Oakland, CA); West, Brian (San Francisco, CA)

2010-12-28T23:59:59.000Z

306

1 Modules and exactness  

E-Print Network (OSTI)

Suppose that R is an associative ring with 1. In most commutative cases, R is either the integers Z or some field k. Example: Suppose that k is a field and G is a group. The group-algebra k(G) over k is the direct sum k(G) = ? k, g?G with elements written as finite sums ? g?G ?g g, with ?g ? k and all but finitely many ?g = 0. The rule (?g g)(?h h) = (?g?h) (gh) defines the algebra structure on k(G), with multiplicative identity 1 = 1 e, where e is the identity element of G. A k(G)-module M is a k-vector space M, with bilinear map ? : k(G) M ? M with (r, m) ? ? r?m, such that r?(s?m) = (rs)? m and 1 ? m = m, or equivalently M is a k-vector 1 space equipped with a group homomorphism G ? Autk(M). k(G)-modules are often called G-modules for that reason. Not even that is the most enlightened way to describe a k(G)-module. A group G can be thought of as a category (actually a groupoid) with one object ? and a morphism ? g ? ? ? for every g ? G. Then a k(G)-module is a functor M: G ? k ? Mod which takes values in the category of k-vector spaces. NB: Ive only based these notions on fields k and their vector spaces to make them seem real. The object k could be a ring; then k(G) is a k-algebra still and a k(G)-module is a k-module M equipped with a group homomorphism G ? Autk(M). Now we recall some basic definitions and facts about R-modules. Suppose that f: M ? N is an R-module homomorphism. Then the kernel ker(f) of f is defined by ker(f) = {all x ? M such that f(x) = 0}. ker(f) is plainly a submodule of M. The image 2 im(f) of f is the submodule of N consisting of all y ? N such that y = f(x) for some x ? M. The cokernel of f cok(f) is defined to be the quotient A sequence cok(f) = N / im(f). M f ? ? M ? g ? ? M of R-module homomorphisms is said to be exact if ker(g) = im(f). Equivalently, the sequence is exact if g f = 0 and for all y ? M ? with g(y) = 0 there is an x ? M such that f(x) = y. A sequence M1 ? M2 ? ? Mn of R-module homomorphisms is said to be exact if ker = im everywhere. Example 1.1. The sequence 0 ? ker(f) ? M f ? ? N ? cok(f) ? 0 is exact for all R-module homomorphisms f. Note that 0 ? M f ? ? N is exact if and only if f is a monomorphism (injective), and that

unknown authors

2009-01-01T23:59:59.000Z

307

Solar cell module lamination process  

DOE Patents (OSTI)

A solar cell module lamination process using fluoropolymers to provide protection from adverse environmental conditions and thus enable more extended use of solar cells, particularly in space applications. A laminate of fluoropolymer material provides a hermetically sealed solar cell module structure that is flexible and very durable. The laminate is virtually chemically inert, highly transmissive in the visible spectrum, dimensionally stable at temperatures up to about 200.degree. C. highly abrasion resistant, and exhibits very little ultra-violet degradation.

Carey, Paul G. (Mountain View, CA); Thompson, Jesse B. (Brentwood, CA); Aceves, Randy C. (Tracy, CA)

2002-01-01T23:59:59.000Z

308

Demand Response For Power System Reliability: FAQ  

SciTech Connect

Demand response is the most underutilized power system reliability resource in North America. Technological advances now make it possible to tap this resource to both reduce costs and improve. Misconceptions concerning response capabilities tend to force loads to provide responses that they are less able to provide and often prohibit them from providing the most valuable reliability services. Fortunately this is beginning to change with some ISOs making more extensive use of load response. This report is structured as a series of short questions and answers that address load response capabilities and power system reliability needs. Its objective is to further the use of responsive load as a bulk power system reliability resource in providing the fastest and most valuable ancillary services.

Kirby, Brendan J [ORNL

2006-12-01T23:59:59.000Z

309

Residential demand response using reinforcement learning  

E-Print Network (OSTI)

Abstract We present a novel energy management system for residential demand response. The algorithm, named CAES, reduces residential energy costs and smooths energy usage. CAES is an online learning application that implicitly estimates the impact of future energy prices and of consumer decisions on long term costs and schedules residential device usage. CAES models both energy prices and residential device usage as Markov, but does not assume knowledge of the structure or transition probabilities of these Markov chains. CAES learns continuously and adapts to individual consumer preferences and pricing modifications over time. In numerical simulations CAES reduced average end-user financial costs from 16 % to 40 % with respect to a price-unaware energy allocation. I.

Marco Levorato; Andrea Goldsmith; Urbashi Mitra

2010-01-01T23:59:59.000Z

310

Definition: Peak Demand | Open Energy Information  

Open Energy Info (EERE)

Peak Demand Peak Demand Jump to: navigation, search Dictionary.png Peak Demand The highest hourly integrated Net Energy For Load within a Balancing Authority Area occurring within a given period (e.g., day, month, season, or year)., The highest instantaneous demand within the Balancing Authority Area.[1] View on Wikipedia Wikipedia Definition Peak demand is used to refer to a historically high point in the sales record of a particular product. In terms of energy use, peak demand describes a period of strong consumer demand. Related Terms Balancing Authority Area, energy, demand, balancing authority, smart grid References ↑ Glossary of Terms Used in Reliability Standards An inli LikeLike UnlikeLike You like this.Sign Up to see what your friends like. ne Glossary Definition Retrieved from

311

Distillate Demand Strong in December 1999  

Gasoline and Diesel Fuel Update (EIA)

5% higher than in the prior year, due mainly to diesel demand growth, since warm weather kept heating oil demand from growing much. Last December, when stocks dropped below...

312

Demand Response - Policy | Department of Energy  

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

over the last 11 years when interest in demand response increased. Demand response is an electricity tariff or program established to motivate changes in electric use by end-use...

313

Energy Basics: Tankless Demand Water Heaters  

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

only as needed and without the use of a storage tank. They don't produce the standby energy losses associated with storage water heaters. How Demand Water Heaters Work Demand...

314

Propane Demand by Sector - Energy Information Administration  

U.S. Energy Information Administration (EIA)

In order to understand markets you also have to look at supply and demand. First, demand or who uses propane. For the most part, the major components of propane ...

315

Travel Behavior and Demand Analysis and Prediction  

E-Print Network (OSTI)

and Demand Analysis and Prediction Konstadinos G. Goulias University of California Santa Barbara, Santa Barbara, CA, USA

Goulias, Konstadinos G

2007-01-01T23:59:59.000Z

316

Forecasting the demand for commercial telecommunications satellites  

Science Conference Proceedings (OSTI)

This paper summarizes the key elements of a forecast methodology for predicting demand for commercial satellite services and the resulting demand for satellite hardware and launches. The paper discusses the characterization of satellite services into more than a dozen applications (including emerging satellite Internet applications) used by Futron Corporation in its forecasts. The paper discusses the relationship between demand for satellite services and demand for satellite hardware

Carissa Bryce Christensen; Carie A. Mullins; Linda A. Williams

2001-01-01T23:59:59.000Z

317

Forecasting Uncertain Hotel Room Demand  

E-Print Network (OSTI)

Economic systems are characterized by increasing uncertainty in their dynamics. This increasing uncertainty is likely to incur bad decisions that can be costly in financial terms. This makes forecasting of uncertain economic variables an instrumental activity in any organization. This paper takes the hotel industry as a practical application of forecasting using the Holt-Winters method. The problem here is to forecast the uncertain demand for rooms at a hotel for each arrival day. Forecasting is part of hotel revenue management system whose objective is to maximize the revenue by making decisions regarding when to make rooms available for customers and at what price. The forecast approach discussed in this paper is based on quantitative models and does not incorporate management expertise. Even though, forecast results are found to be satisfactory for certain days, this is not the case for other arrival days. It is believed that human judgment is important when dealing with ...

Mihir Rajopadhye Mounir; Mounir Ben Ghaliay; Paul P. Wang; Timothy Baker; Craig V. Eister

2001-01-01T23:59:59.000Z

318

Forecasting demand of commodities after natural disasters  

Science Conference Proceedings (OSTI)

Demand forecasting after natural disasters is especially important in emergency management. However, since the time series of commodities demand after natural disasters usually has a great deal of nonlinearity and irregularity, it has poor prediction ... Keywords: ARIMA, Demand forecasting, EMD, Emergency management, Natural disaster

Xiaoyan Xu; Yuqing Qi; Zhongsheng Hua

2010-06-01T23:59:59.000Z

319

Leveraging gamification in demand dispatch systems  

Science Conference Proceedings (OSTI)

Modern demand-side management techniques are an integral part of the envisioned smart grid paradigm. They require an active involvement of the consumer for an optimization of the grid's efficiency and a better utilization of renewable energy sources. ... Keywords: demand response, demand side management, direct load control, gamification, smart grid, sustainability

Benjamin Gnauk; Lars Dannecker; Martin Hahmann

2012-03-01T23:59:59.000Z

320

CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 2014­2024 FINAL FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work to the contributing authors listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad

Note: This page contains sample records for the topic "demand module structure" 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

CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 2014­2024 REVISED FORECAST Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The demand forecast is the combined product of the hard work listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped

322

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network (OSTI)

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work and expertise of numerous, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped prepare

323

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022  

E-Print Network (OSTI)

REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand in this report. #12;i ACKNOWLEDGEMENTS The staff demand forecast is the combined product of the hard work listed previously, Mohsen Abrishami prepared the commercial sector forecast. Mehrzad Soltani Nia helped

324

FINAL STAFF FORECAST OF 2008 PEAK DEMAND  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION FINAL STAFF FORECAST OF 2008 PEAK DEMAND STAFFREPORT June 2007 CEC-200 of the information in this paper. #12;Abstract This document describes staff's final forecast of 2008 peak demand demand forecasts for the respective territories of the state's three investor-owned utilities (IOUs

325

Ups and downs of demand limiting  

SciTech Connect

Electric power load management by limiting power demand can be used for energy conservation. Methods for affecting demand limiting, reducing peak usage in buildings, particularly usage for heating and ventilating systems, and power pricing to encourage demand limiting are discussed. (LCL)

Pannkoke, T.

1976-12-01T23:59:59.000Z

326

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).

327

Microsoft PowerPoint - FinalModule2.ppt  

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

2: Work Breakdown Structure 2: Work Breakdown Structure Prepared by: Module 2 - Work Breakdown Structure 1 Prepared by: Booz Allen Hamilton Module 2: Work Breakdown Structure Welcome to Module 2. The objective of this module is to introduce you to Work Breakdown Structure (WBS) and other supporting documents. This module will include defining and illustrating the following topics: * Work Breakdown Structure * WBS dictionary * Organizational Breakdown Structure (OBS) * Responsibility Assignment Matrix (RAM) Module 2 - Work Breakdown Structure 2 Prepared by: Booz Allen Hamilton What is a Work Breakdown Structure? Planning a project using earned value management is no different than the initial planning necessary to implement any given project. There are basic items that you need to know and understand as a project manager:

328

Measurement and Verification for Demand Response  

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

Measurement and Verification for Measurement and Verification for Demand Response Prepared for the National Forum on the National Action Plan on Demand Response: Measurement and Verification Working Group AUTHORS: Miriam L. Goldberg & G. Kennedy Agnew-DNV KEMA Energy and Sustainability National Forum of the National Action Plan on Demand Response Measurement and Verification for Demand Response was developed to fulfill part of the Implementation Proposal for The National Action Plan on Demand Response, a report to Congress jointly issued by the U.S. Department of Energy (DOE) and the Federal Energy Regulatory Commission (FERC) in June 2011. Part of that implementation proposal called for a "National Forum" on demand response to be conducted by DOE and FERC. Given that demand response has matured, DOE and FERC decided that a "virtual" project

329

Are they equal yet. [Demand side management  

Science Conference Proceedings (OSTI)

Demand-side management (DSM) is considered an important tool in meeting the load growth of many utilities. Northwest regional and utility resource plans forecast demand-side resources to meet from one-half to two-thirds of additional electrical energy needs over the next 10 years. Numerous sources have stated that barriers, both regulatory and financial, exist to utility acquisition of demand-side resources. Regulatory actions are being implemented in Oregon to make demand-side investments competitive with supply-side investments. In 1989, the Oregon Public Utility Commission (PUC) took two actions regarding demand-side investments. The PUC's Order 89-1700 directed utilities to capitalize demand-side investments to properly match amortization expense with the multiyear benefits provided by DSM. The PUC also began an informal investigation concerning incentives for Oregon's regulated electric utilities to acquire demand-side resources.

Irwin, K.; Phillips-Israel, K.; Busch, E.

1994-05-15T23:59:59.000Z

330

Design, Synthesis, and Estrogenic Activity of a Novel Estrogen Receptor ModulatorsA Hybrid Structure of 17 -Estradiol and Vitamin E in Hippocampal Neurons  

E-Print Network (OSTI)

Design, Synthesis, and Estrogenic Activity of a Novel Estrogen Receptor ModulatorsA Hybrid receptor (ER)-dependent proliferation in reproductive tissues, functions as an estrogenic agonist . In Vitro analyses demonstrated that 2 was neuroprotective and effective in activating molecular mechanisms

Brinton, Roberta Diaz

331

TOB Module Assembly  

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

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

332

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

333

Discrete pulse modulation strategies for high-frequency inverter systems  

SciTech Connect

High-performance high-frequency inverter systems for UPS applications represent a demanding application that cannot be easily realized using conventional hard-switched PWM inverter topologies. Adoption of typical soft-switched inverters such as the resonant dc link inverter require the use of discrete pulse modulation strategies. New controller structures are necessary to cope with stringent voltage regulation and distortion constraints in the presence of unbalanced and nonlinear loads. This paper presents a controller that utilizes load current feed-forward strategy with a cost function current regulator to achieve excellent transient performance characteristics. Voltage regulation is ensured using a synchronous frame regulator. Detailed simulation and experimental results verifying the concepts are presented. Although this paper focuses on soft-switching inverters, the control concepts can be applied to conventional hard-switching inverters as well.

Venkataramanan, G. (Montana State Univ., Bozeman, MT (United States). Dept. of Electrical Engineering); Divan, D.M. (Univ. of Wisconsin, Madison, WI (United States). Dept. of Electrical and Computer Engineering); Jahns, T.M. (General Electric Co., Schenectady, NY (United States))

1993-07-01T23:59:59.000Z

334

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

335

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

336

Definition: Demand Side Management | Open Energy Information  

Open Energy Info (EERE)

Side Management Side Management Jump to: navigation, search Dictionary.png Demand Side Management The term for all activities or programs undertaken by Load-Serving Entity or its customers to influence the amount or timing of electricity they use.[1] View on Wikipedia Wikipedia Definition Energy demand management, also known as demand side management (DSM), is the modification of consumer demand for energy through various methods such as financial incentives and education. Usually, the goal of demand side management is to encourage the consumer to use less energy during peak hours, or to move the time of energy use to off-peak times such as nighttime and weekends. Peak demand management does not necessarily decrease total energy consumption, but could be expected to reduce the need

337

Distributed Intelligent Automated Demand Response (DIADR) Building  

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

Distributed Intelligent Automated Demand Distributed Intelligent Automated Demand Response (DIADR) Building Management System Distributed Intelligent Automated Demand Response (DIADR) Building Management System The U.S. Department of Energy (DOE) is currently conducting research into distributed intelligent-automated demand response (DIADR) building management systems. Project Description This project aims to develop a DIADR building management system with intelligent optimization and control algorithms for demand management, taking into account a multitude of factors affecting cost including: Comfort Heating, ventilating, and air conditioning (HVAC) Lighting Other building systems Climate Usage and occupancy patterns. The key challenge is to provide the demand response the ability to address more and more complex building systems that include a variety of loads,

338

Retail Demand Response in Southwest Power Pool  

SciTech Connect

In 2007, the Southwest Power Pool (SPP) formed the Customer Response Task Force (CRTF) to identify barriers to deploying demand response (DR) resources in wholesale markets and develop policies to overcome these barriers. One of the initiatives of this Task Force was to develop more detailed information on existing retail DR programs and dynamic pricing tariffs, program rules, and utility operating practices. This report describes the results of a comprehensive survey conducted by LBNL in support of the Customer Response Task Force and discusses policy implications for integrating legacy retail DR programs and dynamic pricing tariffs into wholesale markets in the SPP region. LBNL conducted a detailed survey of existing DR programs and dynamic pricing tariffs administered by SPP's member utilities. Survey respondents were asked to provide information on advance notice requirements to customers, operational triggers used to call events (e.g. system emergencies, market conditions, local emergencies), use of these DR resources to meet planning reserves requirements, DR resource availability (e.g. seasonal, annual), participant incentive structures, and monitoring and verification (M&V) protocols. Nearly all of the 30 load-serving entities in SPP responded to the survey. Of this group, fourteen SPP member utilities administer 36 DR programs, five dynamic pricing tariffs, and six voluntary customer response initiatives. These existing DR programs and dynamic pricing tariffs have a peak demand reduction potential of 1,552 MW. Other major findings of this study are: o About 81percent of available DR is from interruptible rate tariffs offered to large commercial and industrial customers, while direct load control (DLC) programs account for ~;;14percent. o Arkansas accounts for ~;;50percent of the DR resources in the SPP footprint; these DR resources are primarily managed by cooperatives. o Publicly-owned cooperatives accounted for 54percent of the existing DR resources among SPP members. For these entities, investment in DR is often driven by the need to reduce summer peak demand that is used to set demand charges for each distribution cooperative. o About 65-70percent of the interruptible/curtailable tariffs and DLC programs are routinely triggered based on market conditions, not just for system emergencies. Approximately, 53percent of the DR resources are available with less than two hours advance notice and 447 MW can be dispatched with less than thirty minutes notice. o Most legacy DR programs offered a reservation payment ($/kW) for participation; incentive payment levels ranged from $0.40 to $8.30/kW-month for interruptible rate tariffs and $0.30 to $4.60/kW-month for DLC programs. A few interruptible programs offered incentive payments which were explicitly linkedto actual load reductions during events; payments ranged from 2 to 40 cents/kWh for load curtailed.

Bharvirkar, Ranjit; Heffner, Grayson; Goldman, Charles

2009-01-30T23:59:59.000Z

339

Transportation Demand Management (TDM) Encyclopedia | Open Energy  

Open Energy Info (EERE)

Transportation Demand Management (TDM) Encyclopedia Transportation Demand Management (TDM) Encyclopedia Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Transportation Demand Management (TDM) Encyclopedia Agency/Company /Organization: Victoria Transport Policy Institute Sector: Energy Focus Area: Transportation Topics: Implementation Resource Type: Guide/manual Website: www.vtpi.org/tdm/tdm12.htm Cost: Free Language: English References: Victoria Transport Policy Institute[1] "The Online TDM Encyclopedia is the world's most comprehensive information resource concerning innovative transportation management strategies. It describes dozens of Transportation Demand Management (TDM) strategies and contains information on TDM planning, evaluation and implementation. It has thousands of hyperlinks that provide instant access

340

Marketing & Driving Demand: Social Media Tools & Strategies ...  

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

Marketing & Driving Demand: Social Media Tools & Strategies January 16, 2011 Maryanne Fuller (MF): Hi there. This is Maryanne Fuller from Lawrence Berkeley National Laboratory....

Note: This page contains sample records for the topic "demand module structure" 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

Northwest Open Automated Demand Response Technology Demonstration...  

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

morning and summer afternoon peak electricity demand in commercial buildings the Seattle area. LBNL performed this demonstration for the Bonneville Power Administration (BPA)...

342

Integration of Demand Side Management, Distributed Generation...  

Open Energy Info (EERE)

Page Edit with form History Facebook icon Twitter icon Integration of Demand Side Management, Distributed Generation, Renewable Energy Sources, and Energy Storages:...

343

Electric Utility Demand-Side Management  

U.S. Energy Information Administration (EIA)

Demand side management (DSM) activities in the electric power industry. The report presents a general discussion of DSM, its history, current issues, and a ...

344

Capitalize on Existing Assets with Demand Response  

E-Print Network (OSTI)

Industrial facilities universally struggle with escalating energy costs. EnerNOC will demonstrate how commercial, industrial, and institutional end-users can capitalize on their existing assetsat no cost and no risk. Demand response, the voluntary reduction of electric demand in response to grid instability, provides financial incentives to participating facilities that agree to conserve energy. With demand response, facilities also receive advance notice of potential blackouts and can proactively protect their equipment and machinery from sudden losses of power. A detailed case study, focusing on a sample industrial customers participation in demand response, will support the presentation.

Collins, J.

2008-01-01T23:59:59.000Z

345

Optimization of Demand Response Through Peak Shaving  

E-Print Network (OSTI)

Jul 5, 2013 ... Optimization of Demand Response Through Peak Shaving. G. Zakeri(g.zakeri *** at*** auckland.ac.nz) D. Craigie(David.Craigie ***at***...

346

Automated Demand Response Technology Demonstration Project for...  

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

Demonstration Project for Small and Medium Commercial Buildings Title Automated Demand Response Technology Demonstration Project for Small and Medium Commercial Buildings...

347

Demand response participation in PJM wholesale markets  

Science Conference Proceedings (OSTI)

This paper provides an overview of demand response resource participation in PJM wholesale ancillary service markets which include: Day Ahead Scheduling Reserves, Synchronized Reserves and Regulation.

Peter L. Langbein

2012-01-01T23:59:59.000Z

348

Demand Responsive Lighting: A Scoping Study  

E-Print Network (OSTI)

3 3.0 Previous Experience with Demand Responsive Lighting11 4.3. Prevalence of Lighting13 4.4. Impact of Title 24 on Lighting

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

349

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

for the most natural gas usage (33% and 51% of total demanddependence in natural gas usage, and consequently, Januarygas demand exhibits a strong winter peak in residential usage

McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

2008-01-01T23:59:59.000Z

350

Wireless Demand Response Controls for HVAC Systems  

E-Print Network (OSTI)

Response Controls for HVAC Systems Clifford Federspiel,tests. Figure 5: Specific HVAC electric power consumptioncontrol, demand response, HVAC, wireless Executive Summary

Federspiel, Clifford

2010-01-01T23:59:59.000Z

351

Home Network Technologies and Automating Demand Response  

E-Print Network (OSTI)

networks_in_the_home_the_new_growth_market.htm [12] NationalHome Network Technologies and Automating Demand Responsethe University of California. Home Network Technologies and

McParland, Charles

2010-01-01T23:59:59.000Z

352

Distillate Demand Strong in December 1999  

U.S. Energy Information Administration (EIA)

Total distillate demand includes both diesel and heating oil. These are similar products. Physically, diesel can be used in the heating oil market, but low sulfur ...

353

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

California Energy Demand Scenario Projections to 2050 RyanResearch Program California Energy Commission November 7,Chris Kavalec. California Energy Commission. CEC (2003a)

McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

2008-01-01T23:59:59.000Z

354

Discrete Choice Analysis: Hydrogen FCV Demand Potential  

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

Choice Analysis: H 2 FCV Demand Potential Cory Welch H 2 Scenario Analysis Workshop Washington, D.C. , January 31, 2007 2 Overview * Motivation for work * Methodology * Relative...

355

California Energy Demand Scenario Projections to 2050  

E-Print Network (OSTI)

In Maximum demand, year 2050 electricity consumption reachesefficiency, year 2050 electricity consumption is 357 TWh,capita electricity consumption increases from 7,421 kWh/year

McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

2008-01-01T23:59:59.000Z

356

Electric Utility Demand-Side Management 1997  

U.S. Energy Information Administration (EIA)

DOE/EIA-0589(97) Distribution Category UC-950 U.S. Electric Utility Demand-Side Management 1997 December 1998 Energy Information Administration Office of Coal ...

357

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

358

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

55. Sample distribution of vehicle electricity demand forand distribution facilities that supply electricity demand.55. Sample distribution of vehicle electricity demand for

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

359

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network (OSTI)

5. Average, minimum, and maximum demand reduction at eachshow the minimum and maximum demand reduction during the7. Average, minimum, and maximum demand reduction at each

Kiliccote, Sila

2010-01-01T23:59:59.000Z

360

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network (OSTI)

Figure 16 Annual peak electricity demand by sector. Tableincludes an hourly electricity demand (i.e. power) profileof aggregating sectoral electricity demands into a statewide

McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "demand module structure" 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

Residential Electricity Demand in China -- Can Efficiency Reverse the Growth?  

E-Print Network (OSTI)

with Residential Electricity Demand in India's Future - How2008). The Boom of Electricity Demand in the residential2005). Forecasting Electricity Demand in Developing

Letschert, Virginie

2010-01-01T23:59:59.000Z

362

Climate, extreme heat, and electricity demand in California  

E-Print Network (OSTI)

warming and electricity demand: A study of California.Extreme Heat, and Electricity Demand in California Norman L.high temperature and electricity demand for air-conditioned

Miller, N.L.

2008-01-01T23:59:59.000Z

363

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

Statewide California Electricity Demand. [accessed June 22,fuel efficiency and electricity demand assumptions used into added vehicle electricity demand in the BAU (no IGCC)

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

364

U.S. Propane Demand - Energy Information Administration  

U.S. Energy Information Administration (EIA)

Demand is higher in 1999 due to higher petrochemical demand and a strong economy. We are also seeing strong demand in the first quarter of 2000; however, ...

365

Demand Response in U.S. Electricity Markets: Empirical Evidence  

E-Print Network (OSTI)

Reliability Corporation. Demand response data task force:Energy. Benefits of demand response in electricity marketsAssessment of demand response & advanced metering, staff

Cappers, Peter

2009-01-01T23:59:59.000Z

366

Demand Response Opportunities in Industrial Refrigerated Warehouses in California  

E-Print Network (OSTI)

and Open Automated Demand Response. In Grid Interop Forum.work was sponsored by the Demand Response Research Center (load-management.php. Demand Response Research Center (2009).

Goli, Sasank

2012-01-01T23:59:59.000Z

367

Results and commissioning issues from an automated demand response pilot  

E-Print Network (OSTI)

of Fully Automated Demand Response in Large Facilities"Management and Demand Response in Commercial Buildings", L Band Commissioning Issues from an Automated Demand Response.

Piette, Mary Ann; Watson, Dave; Sezgen, Osman; Motegi, Naoya

2004-01-01T23:59:59.000Z

368

Open Automated Demand Response for Small Commerical Buildings  

E-Print Network (OSTI)

ofFullyAutomatedDemand ResponseinLargeFacilities. FullyAutomatedDemandResponseTestsinLargeFacilities. OpenAutomated DemandResponseCommunicationStandards:

Dudley, June Han

2009-01-01T23:59:59.000Z

369

Rates and technologies for mass-market demand response  

E-Print Network (OSTI)

Roger. 2002. Using Demand Response to Link Wholesale andfor advanced metering, demand response, and dynamic pricing.EPRI. 2001. Managing Demand-Response To Achieve Multiple

Herter, Karen; Levy, Roger; Wilson, John; Rosenfeld, Arthur

2002-01-01T23:59:59.000Z

370

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network (OSTI)

Goodin. 2009. Open Automated Demand Response Communicationsin Demand Response for Wholesale Ancillary Services. InOpen Automated Demand Response Demonstration Project. LBNL-

Ghatikar, Girish

2010-01-01T23:59:59.000Z

371

Coordination of Retail Demand Response with Midwest ISO Markets  

E-Print Network (OSTI)

Robinson, Michael, 2008, "Demand Response in Midwest ISOPresentation at MISO Demand Response Working Group Meeting,Coordination of Retail Demand Response with Midwest ISO

Bharvirkar, Ranjit

2008-01-01T23:59:59.000Z

372

Direct versus Facility Centric Load Control for Automated Demand Response  

E-Print Network (OSTI)

Interoperable Automated Demand Response Infrastructure.and Techniques for Demand Response. LBNL Report 59975. Mayand Communications for Demand Response and Energy Efficiency

Piette, Mary Ann

2010-01-01T23:59:59.000Z

373

Linking Continuous Energy Management and Open Automated Demand Response  

E-Print Network (OSTI)

A. Barat, D. Watson. Demand Response Spinning ReserveOpen Automated Demand Response Communication Standards:Dynamic Controls for Demand Response in a New Commercial

Piette, Mary Ann

2009-01-01T23:59:59.000Z

374

Scenarios for Consuming Standardized Automated Demand Response Signals  

E-Print Network (OSTI)

of Fully Automated Demand Response in Large Facilities.Fully Automated Demand Response Tests in Large Facilities.Interoperable Automated Demand Response Infrastructure.

Koch, Ed

2009-01-01T23:59:59.000Z

375

Dynamic Pricing, Advanced Metering, and Demand Response in Electricity Markets  

E-Print Network (OSTI)

the New England ISO Demand Response Collaborative, a NYSERDACEC Staff. Selected Demand Response Pilots in California:New Principles for Demand Response Planning, Electric Power

Borenstein, Severin; Jaske, Michael; Rosenfeld, Arthur

2002-01-01T23:59:59.000Z

376

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network (OSTI)

reliability signals for demand response GTA HTTPS HVAC IT kWand Commissioning Automated Demand Response Systems. and Techniques for Demand Response. California Energy

Kiliccote, Sila

2010-01-01T23:59:59.000Z

377

Measurement and evaluation techniques for automated demand response demonstration  

E-Print Network (OSTI)

Development for Demand Response Calculation Findings andManagement and Demand Response in Commercial Buildings. of Fully Automated Demand Response in Large Facilities.

Motegi, Naoya; Piette, Mary Ann; Watson, David S.; Sezgen, Osman; ten Hope, Laurie

2004-01-01T23:59:59.000Z

378

Open Automated Demand Response Communications Specification (Version 1.0)  

E-Print Network (OSTI)

and Techniques for Demand Response. May 2007. LBNL-59975.tofacilitateautomating demandresponseactionsattheInteroperable Automated Demand Response Infrastructure,

Piette, Mary Ann

2009-01-01T23:59:59.000Z

379

A Model of Household Demand for Activity Participation and Mobility  

E-Print Network (OSTI)

household car ownership, car usage, and travel by differentownership demand, and car usage demand. Modal travel demand,mode), car ownership, and car usage for spatial aggregations

Golob, Thomas F.

1996-01-01T23:59:59.000Z

380

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network (OSTI)

Table 22. Agricultural natural gas demand by planning area.23. Other sector natural gas demand by planning area.Projections Monthly natural gas demands are depicted in

McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

2008-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "demand module structure" 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

Microgrid Dispatch for Macrogrid Peak-Demand Mitigation  

E-Print Network (OSTI)

Dispatch for Macrogrid Peak- Demand Mitigation NicholasDispatch for Macrogrid Peak-Demand Mitigation Nicholasdetermine whether the peak demand on the substation feeder

DeForest, Nicholas

2013-01-01T23:59:59.000Z

382

Effects of the drought on California electricity supply and demand  

E-Print Network (OSTI)

for Electricity and Power Peak Demand . . . . ELECTRICITYby Major Utility Service Area Projected Peak Demand for1977 Historical Peak Demand by Utility Service Area Weather-

Benenson, P.

2010-01-01T23:59:59.000Z

383

Climate, extreme heat, and electricity demand in California  

E-Print Network (OSTI)

projected extreme heat and peak demand for electricity areadequately kept up with peak demand, and electricity supplytrend in aggregate peak demand in California is expected to

Miller, N.L.

2008-01-01T23:59:59.000Z

384

FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007  

E-Print Network (OSTI)

CALIFORNIA ENERGY COMMISSION FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007 INTEGRATED Table of Contents General Instructions for Demand Forecast Submittals.............................................................................. 4 Protocols for Submitted Demand Forecasts

385

Energy Demands and Efficiency Strategies in Data Center Buildings  

E-Print Network (OSTI)

Total Annual Energy Usage Peak Electric Demand Power UsageSetpoint (C) Peak Electric Demand Power Usage Effective-Total Annual Energy Usage Peak Electric Demand Scenario

Shehabi, Arman

2010-01-01T23:59:59.000Z

386

Robust Dynamic Traffic Assignment under Demand and Capacity Uncertainty  

E-Print Network (OSTI)

Assignment under Demand and Capacity Uncertainty ? Giuseppeworst-case sce- nario of demand and capacity con?gurations.uncertain demands and capacities are modeled as unknown-but-

Calafiore, Giuseppe; El Ghaoui, Laurent

2008-01-01T23:59:59.000Z

387

Rising Asian demand drives global coal consumption growth ...  

U.S. Energy Information Administration (EIA)

Global coal demand has almost doubled since 1980, driven by increases in Asia, where demand is up over 400% from 1980-2010. In turn, Asian demand is ...

388

Photovoltaic module mounting system  

SciTech Connect

A solar array mounting system having unique installation, load distribution, and grounding features, and which is adaptable for mounting solar panels having no external frame. The solar array mounting system includes flexible, pedestal-style feet and structural links connected in a grid formation on the mounting surface. The photovoltaic modules are secured in place via the use of attachment clamps that grip the edge of the typically glass substrate. The panel mounting clamps are then held in place by tilt brackets and/or mid-link brackets that provide fixation for the clamps and align the solar panels at a tilt to the horizontal mounting surface. The tilt brackets are held in place atop the flexible feet and connected link members thus creating a complete mounting structure.

Miros, Robert H. J. (Fairfax, CA); Mittan, Margaret Birmingham (Oakland, CA); Seery, Martin N. (San Rafael, CA); Holland, Rodney H. (Novato, CA)

2012-04-17T23:59:59.000Z

389

Photovoltaic module mounting system  

SciTech Connect

A solar array mounting system having unique installation, load distribution, and grounding features, and which is adaptable for mounting solar panels having no external frame. The solar array mounting system includes flexible, pedestal-style feet and structural links connected in a grid formation on the mounting surface. The photovoltaic modules are secured in place via the use of attachment clamps that grip the edge of the typically glass substrate. The panel mounting clamps are then held in place by tilt brackets and/or mid-link brackets that provide fixation for the clamps and align the solar panels at a tilt to the horizontal mounting surface. The tilt brackets are held in place atop the flexible feet and connected link members thus creating a complete mounting structure.

Miros, Robert H. J.; Mittan, Margaret Birmingham; Seery, Martin N; Holland, Rodney H

2012-09-18T23:59:59.000Z

390

Ballasted photovoltaic module and module arrays  

DOE Patents (OSTI)

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

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

2011-11-29T23:59:59.000Z

391

On-demand photoinitiated polymerization  

SciTech Connect

Compositions and methods for adjustable lenses are provided. In some embodiments, the lenses contain a lens matrix material, a masking compound, and a prepolymer. The lens matrix material provides structure to the lens. The masking compound is capable of blocking polymerization or crosslinking of the prepolymer, until photoisomerization of the compound is triggered, and the compound is converted from a first isomer to a second isomer having a different absorption profile. The prepolymer is a composition that can undergo a polymerization or crosslinking reaction upon photoinitiation to alter one or more of the properties of the lenses.

Boydston, Andrew J; Grubbs, Robert H; Daeffler, Chris; Momcilovic, Nebojsa

2013-12-10T23:59:59.000Z

392

Providing Reliability Services through Demand Response: A Prelimnary Evaluation of the Demand Response Capabilities of Alcoa Inc.  

Science Conference Proceedings (OSTI)

Demand response is the largest underutilized reliability resource in North America. Historic demand response programs have focused on reducing overall electricity consumption (increasing efficiency) and shaving peaks but have not typically been used for immediate reliability response. Many of these programs have been successful but demand response remains a limited resource. The Federal Energy Regulatory Commission (FERC) report, 'Assessment of Demand Response and Advanced Metering' (FERC 2006) found that only five percent of customers are on some form of demand response program. Collectively they represent an estimated 37,000 MW of response potential. These programs reduce overall energy consumption, lower green house gas emissions by allowing fossil fuel generators to operate at increased efficiency and reduce stress on the power system during periods of peak loading. As the country continues to restructure energy markets with sophisticated marginal cost models that attempt to minimize total energy costs, the ability of demand response to create meaningful shifts in the supply and demand equations is critical to creating a sustainable and balanced economic response to energy issues. Restructured energy market prices are set by the cost of the next incremental unit of energy, so that as additional generation is brought into the market, the cost for the entire market increases. The benefit of demand response is that it reduces overall demand and shifts the entire market to a lower pricing level. This can be very effective in mitigating price volatility or scarcity pricing as the power system responds to changing demand schedules, loss of large generators, or loss of transmission. As a global producer of alumina, primary aluminum, and fabricated aluminum products, Alcoa Inc., has the capability to provide demand response services through its manufacturing facilities and uniquely through its aluminum smelting facilities. For a typical aluminum smelter, electric power accounts for 30% to 40% of the factory cost of producing primary aluminum. In the continental United States, Alcoa Inc. currently owns and/or operates ten aluminum smelters and many associated fabricating facilities with a combined average load of over 2,600 MW. This presents Alcoa Inc. with a significant opportunity to respond in areas where economic opportunities exist to help mitigate rising energy costs by supplying demand response services into the energy system. This report is organized into seven chapters. The first chapter is the introduction and discusses the intention of this report. The second chapter contains the background. In this chapter, topics include: the motivation for Alcoa to provide demand response; ancillary service definitions; the basics behind aluminum smelting; and a discussion of suggested ancillary services that would be particularly useful for Alcoa to supply. Chapter 3 is concerned with the independent system operator, the Midwest ISO. Here the discussion examines the evolving Midwest ISO market structure including specific definitions, requirements, and necessary components to provide ancillary services. This section is followed by information concerning the Midwest ISO's classifications of demand response parties. Chapter 4 investigates the available opportunities at Alcoa's Warrick facility. Chapter 5 involves an in-depth discussion of the regulation service that Alcoa's Warrick facility can provide and the current interactions with Midwest ISO. Chapter 6 reviews future plans and expectations for Alcoa providing ancillary services into the market. Last, chapter 7, details the conclusion and recommendations of this paper.

Starke, Michael R [ORNL; Kirby, Brendan J [ORNL; Kueck, John D [ORNL; Todd, Duane [Alcoa; Caulfield, Michael [Alcoa; Helms, Brian [Alcoa

2009-02-01T23:59:59.000Z

393

Microsoft PowerPoint - FinalModule8.ppt  

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

8: Reporting 8: Reporting Prepared by: Module 8 - Reporting 1 Prepared by: Booz Allen Hamilton Module 8: Government Required Reports Welcome to Module 8. The objective of this module is to introduce you to Government required reports. The Topics that will be addressed in this Module include: * Define Cost Performance Report (CPR) * Define Cost/Schedule Status Report (C/SSR) Module 8 - Reporting 2 Prepared by: Booz Allen Hamilton Review of Previous Modules In the previous seven modules, we discussed the framework needed to perform Earned Value and develop an Earned Value Management System (EVMS). * In Module 1 we introduced you to earned value and the requirements for properly implementing an earned value management system (EVMS) * In Module 2 we discussed the development of the work breakdown structure

394

INTEGRATION OF PV IN DEMAND RESPONSE  

E-Print Network (OSTI)

of the baseline defining a customer's load profile, and (2) PVs cannot be turned on at will for scheduled tests customers to curtail demand when needed to reduce risk of grid failure during times of peak loading load. The value of this credit may reach or exceed $100/kW/year [1] Demand response is typically

Perez, Richard R.

395

A distributed approach to taming peak demand  

Science Conference Proceedings (OSTI)

A significant portion of all energy capacity is wasted in over-provisioning to meet peak demand. The current state-of-the-art in reducing peak demand requires central authorities to limit device usage directly, and are generally reactive. We apply techniques ...

Michael Sabolish; Ahmed Amer; Thomas M. Kroeger

2012-06-01T23:59:59.000Z

396

Designing presentations for on-demand viewing  

Science Conference Proceedings (OSTI)

Increasingly often, presentations are given before a live audience, while simultaneously being viewed remotely and recorded for subsequent viewing on-demand over the Web. How should video presentations be designed for web access? How is video accessed ... Keywords: digital library, streaming media, video on-demand

Liwei He; Jonathan Grudin; Anoop Gupta

2000-12-01T23:59:59.000Z

397

Note: The Newsvendor Model with Endogenous Demand  

Science Conference Proceedings (OSTI)

This paper considers a firm's price and inventory policy when it faces uncertain demand that depends on both price and inventory level. The authors extend the classic newsvendor model by assuming that expected utility maximizing consumers choose between ... Keywords: Demand Uncertainty, Fill Rate Competition, Inventory, Newsvendor Model, Pricing, Service Levels, Service Rate Competition

James D. Dana; Nicholas C. Petruzzi

2001-11-01T23:59:59.000Z

398

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST  

E-Print Network (OSTI)

CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 1: Statewide Electricity forecast is the combined product of the hard work and expertise of numerous staff members in the Demand the commercial sector forecast. Mehrzad Soltani Nia helped prepare the industrial forecast. Miguel Garcia

399

Forecasting Electricity Demand by Time Series Models  

Science Conference Proceedings (OSTI)

Electricity demand is one of the most important variables required for estimating the amount of additional capacity required to ensure a sufficient supply of energy. Demand and technological losses forecasts can be used to control the generation and distribution of electricity more efficiently. The aim of this paper is to utilize time series model

E. Stoimenova; K. Prodanova; R. Prodanova

2007-01-01T23:59:59.000Z

400

Residential sector: the demand for energy services  

Science Conference Proceedings (OSTI)

The purpose of this report is to project the demand for residential services, and, thereby, the demand for energy into the future. The service demands which best represent a complete breakdown of residential energy consumption is identified and estimates of the amount of energy, by fuel type, used to satisfy each service demand for an initial base year (1978) are detailed. These estimates are reported for both gross (or input) energy use and net or useful energy use, in the residential sector. The various factors which affect the consumption level for each type of energy and each identified service demand are discussed. These factors include number of households, appliance penetration, choice of fuel type, technical conversion efficiency of energy using devices, and relative energy efficiency of the building shell (extent of insulation, resistance to air infiltration, etc.). These factors are discussed relative to both the present and expected future values, for the purpose of projections. The importance of the housing stock to service demand estimation and projection and trends in housing in Illinois are discussed. How the housing stock is projected based on population and household projections is explained. The housing projections to the year 2000 are detailed. The projections of energy consumption by service demand and fuel type are contrasted with the various energy demand projections in Illinois Energy Consumption Trends: 1960 to 2000 and explains how and why the two approaches differ. (MCW)

Not Available

1981-01-01T23:59:59.000Z

Note: This page contains sample records for the topic "demand module structure" 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

Solar in Demand | Department of Energy  

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

Lighthouse Solar, install microcrystalline PV modules on top of Kevin Donovan's town home. | Credit: Dennis Schroeder. Kyle Travis, left and Jon Jackson, with Lighthouse Solar,...

402

Coordination of Energy Efficiency and Demand Response  

Science Conference Proceedings (OSTI)

This paper reviews the relationship between energy efficiency and demand response and discusses approaches and barriers to coordinating energy efficiency and demand response. The paper is intended to support the 10 implementation goals of the National Action Plan for Energy Efficiency's Vision to achieve all cost-effective energy efficiency by 2025. Improving energy efficiency in our homes, businesses, schools, governments, and industries - which consume more than 70 percent of the nation's natural gas and electricity - is one of the most constructive, cost-effective ways to address the challenges of high energy prices, energy security and independence, air pollution, and global climate change. While energy efficiency is an increasingly prominent component of efforts to supply affordable, reliable, secure, and clean electric power, demand response is becoming a valuable tool in utility and regional resource plans. The Federal Energy Regulatory Commission (FERC) estimated the contribution from existing U.S. demand response resources at about 41,000 megawatts (MW), about 5.8 percent of 2008 summer peak demand (FERC, 2008). Moreover, FERC recently estimated nationwide achievable demand response potential at 138,000 MW (14 percent of peak demand) by 2019 (FERC, 2009).2 A recent Electric Power Research Institute study estimates that 'the combination of demand response and energy efficiency programs has the potential to reduce non-coincident summer peak demand by 157 GW' by 2030, or 14-20 percent below projected levels (EPRI, 2009a). This paper supports the Action Plan's effort to coordinate energy efficiency and demand response programs to maximize value to customers. For information on the full suite of policy and programmatic options for removing barriers to energy efficiency, see the Vision for 2025 and the various other Action Plan papers and guides available at www.epa.gov/eeactionplan.

Goldman, Charles; Reid, Michael; Levy, Roger; Silverstein, Alison

2010-01-29T23:59:59.000Z

403

CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST  

E-Print Network (OSTI)

the entire forecast period, primarily because both weather-adjusted peak and electricity consumption were forecast. Keywords Electricity demand, electricity consumption, demand forecast, weather normalization, annual peak demand, natural gas demand, self-generation, conservation, California Solar Initiative. #12

404

OECD Crude Oil v Product Demand Seasonal Patterns  

Gasoline and Diesel Fuel Update (EIA)

6 Notes: The answer lies in separating crude oil demand from product demand. Crude oil demand should be a better indicator of pressures on crude oil price than product demand....

405

Demand Response in U.S. Electricity Markets: Empirical Evidence  

E-Print Network (OSTI)

concerns during system peak demand conditions, and failurerelative to national peak demand, was about 5.0% in 2006 [2]to a regions summer peak demand (see Fig. 2). Demand

Cappers, Peter

2009-01-01T23:59:59.000Z

406

NERSC Modules Software Environment  

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

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

407

Definition: PV module | Open Energy Information  

Open Energy Info (EERE)

Definition Definition Edit with form History Facebook icon Twitter icon » Definition: PV module Jump to: navigation, search Dictionary.png PV module A unit comprised of several PV cells, and the principal unit of a PV array; it is intended to generate direct current power under un-concentrated sunlight.[1][2] View on Wikipedia Wikipedia Definition A solar panel is a set of solar photovoltaic modules electrically connected and mounted on a supporting structure. A photovoltaic module is a packaged, connected assembly of photovoltaic cells. The solar module can be used as a component of a larger photovoltaic system to generate and supply electricity in commercial and residential applications. Each module is rated by its DC output power under standard test conditions (STC), and

408

Coordination of Retail Demand Response with Midwest ISO Markets  

E-Print Network (OSTI)

load and customer maximum demand are most commonly used as1) minimum and maximum amounts of demand reduction; (2)

Bharvirkar, Ranjit

2008-01-01T23:59:59.000Z

409

U.S. Regional Demand Forecasts Using NEMS and GIS  

E-Print Network (OSTI)

residential and commercial electricity demand forecasts. The23 Electricity Demandand commercial electricity demand per census division from

Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

2005-01-01T23:59:59.000Z

410

Coordination of Energy Efficiency and Demand Response  

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

Coordination of Energy Efficiency and Demand Response Coordination of Energy Efficiency and Demand Response Title Coordination of Energy Efficiency and Demand Response Publication Type Report Refereed Designation Unknown Year of Publication 2010 Authors Goldman, Charles A., Michael Reid, Roger Levy, and Alison Silverstein Pagination 74 Date Published 01/2010 Publisher LBNL City Berkeley Keywords electricity markets and policy group, energy analysis and environmental impacts department Abstract This paper reviews the relationship between energy efficiency and demand response and discusses approaches and barriers to coordinating energy efficiency and demand response. The paper is intended to support the 10 implementation goals of the National Action Plan for Energy Efficiency's Vision to achieve all cost-effective energy efficiency by 2025.1 Improving energy efficiency in our homes, businesses, schools, governments, and industries-which consume more than 70 percent of the nation's natural gas and electricity-is one of the most constructive, cost-effective ways to address the challenges of high energy prices, energy security and independence, air pollution, and global climate change. While energy efficiency is an increasingly prominent component of efforts to supply affordable, reliable, secure, and clean electric power, demand response is becoming a valuable tool in utility and regional resource plans. The Federal Energy Regulatory Commission (FERC) estimated the contribution from existing U.S. demand response resources at about 41,000 megawatts (MW), about 5.8 percent of 2008 summer peak demand (FERC, 2008). Moreover, FERC recently estimated nationwide achievable demand response potential at 138,000 MW (14 percent of peak demand) by 2019 (FERC, 2009).2 A recent Electric Power Research Institute study estimates that "the combination of demand response and energy efficiency programs has the potential to reduce non-coincident summer peak demand by 157 GW" by 2030, or 14-20 percent below projected levels (EPRI, 2009a). This paper supports the Action Plan's effort to coordinate energy efficiency and demand response programs to maximize value to customers. For information on the full suite of policy and programmatic options for removing barriers to energy efficiency, see the Vision for 2025 and the various other Action Plan papers and guides available at www.epa.gov/eeactionplan.

411

? Market Simulation Activities ? Registration Process Overview ? Agreements ? Intro to Demand Response Provider Software ? Resource Data Template ? Pre-Market Meter Data Submission  

E-Print Network (OSTI)

By the end of this module, you will be able to: ? Describe the purpose of the Proxy Demand Resource project ? Identify the tabs in the Demand Response Provider software ? Identify three components of the Generator Resource Data Template and describe how they are used. ISO PUBLIC- 2010 CAISO 3

Jenny Pedersen; Senior Client Trainer; Iso Public Caiso

2010-01-01T23:59:59.000Z

412

Review of Self-direct Demand Side Management (DSM) Programs  

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

Review of Self-direct Demand Side Management (DSM) Programs Review of Self-direct Demand Side Management (DSM) Programs Title Review of Self-direct Demand Side Management (DSM) Programs Publication Type Presentation Year of Publication 2012 Authors Borgeson, Merrian Keywords demand side resources: policy, electricity markets, electricity markets and policy group, energy analysis and environmental impacts department, energy efficiency, self direct programs, technical assistance Full Text LBNL recently provided technical assistance funded by DOE to the Public Utilities Commission of Ohio to inform their decision-making about changes to their existing self-direct program for commercial and industrial customers. Self-direct programs are usually targeted at large industrial customers with specialized needs or strong in-house energy engineering capacity. These programs are found in at least 24 states, and there is significant variety in how these programs are structured - with important implications for the additionality and reliability of the energy savings that result. LBNL reviewed existing programs and compared key elements of self-direct program design. For additional questions about this work, please contact Merrian Borgeson.

413

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.

414

FERC sees huge potential for demand response  

Science Conference Proceedings (OSTI)

The FERC study concludes that U.S. peak demand can be reduced by as much as 188 GW -- roughly 20 percent -- under the most aggressive scenario. More moderate -- and realistic -- scenarios produce smaller but still significant reductions in peak demand. The FERC report is quick to point out that these are estimates of the potential, not projections of what could actually be achieved. The main varieties of demand response programs include interruptible tariffs, direct load control (DLC), and a number of pricing schemes.

NONE

2010-04-15T23:59:59.000Z

415

Integrating Module of the National Energy Modeling System  

Reports and Publications (EIA)

Provides an overview of the complete National Energy Modeling System (NEMS) model, and includes brief descriptions of the modules with which the Integrating Module interacts. The emphasis and focus, however, is on the structure and function of the Integrating Module of NEMS.

Dan Skelly

2010-06-01T23:59:59.000Z

416

Experimental Observation of Energy Modulation in Electron Beams...  

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

OBSERVATION OF ENERGY MODULATION IN ELECTRON BEAMS PASSING THROUGH TERAHERTZ DIELECTRIC WAKEFIELD STRUCTURES* S. Antipov , C. Jing, P. Schoessow, and A. Kanareykin, Euclid...

417

The fluorite related modulated structures of the Gd{sub 2}(Zr{sub 2-x}Ce{sub x})O{sub 7} solid solution: An analogue for Pu disposition  

Science Conference Proceedings (OSTI)

We present an overview of the Gd{sub 2}(Zr{sub 2-x}Ce{sub x})O{sub 7} phase diagram, of interest as a model system for ceramic disposition of Pu (with Ce as a Pu surrogate). The fluorite related structures of this solid solution were determined using a modulated structure approach, to identify the underlying cation and vacancy ordering mechanisms from analysis of key satellite reflections in selected zone axis electron diffraction patterns. This revealed the formation of four structure types: pyrochlore for x1.50. X-ray absorption (XAS) and electron energy loss (EELS) spectra confirmed the presence of Ce{sup 4+} as the dominant species in compositions across this system, remaining analogous to Pu{sup 4+}. - Graphical abstract: Electron diffraction reveals the cation vacancy ordering mechanisms leading to fluorite related superstructures in the Gd{sub 2}(Zr{sub 2-x}Ce{sub x})O{sub 7} solid solution. Highlights: Black-Right-Pointing-Pointer The fluorite related solid solution Gd{sub 2}(Zr{sub 1-x}Ce{sub x})O{sub 7} was prepared by solid state synthesis. Black-Right-Pointing-Pointer Ce L{sub 3} edge XAS and Ce M{sub 4,5} EELS measurements show Ce substitutes as Ce{sup 4+}. Black-Right-Pointing-Pointer Cation and oxygen vacancy ordering results in four fluorite related structures.

Reid, D.P. [Immobilisation Science Laboratory, Department of Materials Science and Engineering, University of Sheffield, Mappin Street, Sheffield S1 3JD (United Kingdom); Stennett, M.C., E-mail: m.c.stennett@sheffield.ac.uk [Immobilisation Science Laboratory, Department of Materials Science and Engineering, University of Sheffield, Mappin Street, Sheffield S1 3JD (United Kingdom); Hyatt, N.C., E-mail: n.c.hyatt@sheffield.ac.uk [Immobilisation Science Laboratory, Department of Materials Science and Engineering, University of Sheffield, Mappin Street, Sheffield S1 3JD (United Kingdom)

2012-07-15T23:59:59.000Z

418

Operations Landscape for Integrating Demand Response in Wholesale Environments: A Primer on the Wholesale Operations Landscape for I ntegrating Retail Demand Response  

Science Conference Proceedings (OSTI)

The report depicts the electric power industry operations landscape, including the functions, systems, and information exchanges that support wholesale operations. It frames industry stakeholders and their respective uses for retail demand response (DR) in a structured fashion. It also elucidates opportunities, challenges, and strategies employed when integrating DR in wholesale environments.The project approach considers diverse functions, systems, and roles for demand-side resources ...

2012-12-31T23:59:59.000Z

419

NCEP_Demand_Response_Draft_111208.indd  

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

National Council on Electricity Policy: Electric Transmission Series for State Offi National Council on Electricity Policy: Electric Transmission Series for State Offi cials Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Offi cials Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Offi cials Prepared by the U.S. Demand Response Coordinating Committee for The National Council on Electricity Policy Fall 2008 i National Council on Electricity Policy: Electric Transmission Series for State Offi cials Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Offi cials The National Council on Electricity Policy is funded by the U.S. Department of Energy and the U.S. Environmental Protection Agency. The views and opinions expressed herein are strictly those of the

420

National Action Plan on Demand Response  

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

David Kathan, Ph.D David Kathan, Ph.D Federal Energy Regulatory Commission U.S. DOE Electricity Advisory Committee October 29, 2010 Demand Response as Power System Resources The author's views do not necessarily represent the views of the Federal Energy Regulatory Commission 2 Demand Response * FERC (Order 719) defines demand response as: - A reduction in the consumption of electric energy by customers from their expected consumption in response to an increase in the price of electric energy or to in incentive payments designed to induce lower consumption of electric energy. * The National Action Plan on Demand Response released by FERC staff broadens this definition to include - Consumer actions that can change any part of the load profile of a utility or region, not just the period of peak usage

Note: This page contains sample records for the topic "demand module structure" 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

EIA - Annual Energy Outlook 2008 - Electricity Demand  

Gasoline and Diesel Fuel Update (EIA)

Electricity Demand Electricity Demand Annual Energy Outlook 2008 with Projections to 2030 Electricity Demand Figure 60. Annual electricity sales by sector, 1980-2030 (billion kilowatthours). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 61. Electricity generation by fuel, 2006 and 2030 (billion kilowatthours). Need help, contact the National Energy Information Center at 202-586-8800. figure data Residential and Commercial Sectors Dominate Electricity Demand Growth Total electricity sales increase by 29 percent in the AEO2008 reference case, from 3,659 billion kilowatthours in 2006 to 4,705 billion in 2030, at an average rate of 1.1 percent per year. The relatively slow growth follows the historical trend, with the growth rate slowing in each succeeding

422

Demand Controlled Ventilation and Classroom Ventilation  

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

3 3 Authors Fisk, William J., Mark J. Mendell, Molly Davies, Ekaterina Eliseeva, David Faulkner, Tienzen Hong, and Douglas P. Sullivan Publisher Lawrence Berkeley National Laboratory City Berkeley Keywords absence, building s, carbon dioxide, demand - controlled ventilation, energy, indoor air quality, schools, ventilation Abstract This document summarizes a research effort on demand controlled ventilation and classroom ventilation. The research on demand controlled ventilation included field studies and building energy modeling. Major findings included:  The single-location carbon dioxide sensors widely used for demand controlled ventilation frequently have large errors and will fail to effectively control ventilation rates (VRs).  Multi-location carbon dioxide measurement systems with more expensive sensors connected to multi-location sampling systems may measure carbon dioxide more accurately.

423

China End-Use Energy Demand Modeling  

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

China End-Use Energy Demand Modeling China End-Use Energy Demand Modeling Speaker(s): Nan Zhou Date: October 8, 2009 (All day) Location: 90-3122 As a consequence of soaring energy demand due to the staggering pace of its economic growth, China overtook the United States in 2007 to become the world's biggest contributor to CO2 emissions (IEA, 2007). Since China is still in an early stage of industrialization and urbanization, economic development promises to keep China's energy demand growing strongly. Furthermore, China's reliance on fossil fuel is unlikely to change in the long term, and increased needs will only heighten concerns about energy security and climate change. In response, the Chinese government has developed a series of policies and targets aimed at improving energy efficiency, including both short-term targets and long-term strategic

424

Integrated Predictive Demand Response Controller Research Project |  

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

Predictive Demand Response Predictive Demand Response Controller Research Project Integrated Predictive Demand Response Controller Research Project The U.S. Department of Energy (DOE) is currently conducting research into integrated predictive demand response (IPDR) controllers. The project team will attempt to design an IPDR controller so that it can be used in new or existing buildings or in collections of buildings. In the case of collections of buildings, they may be colocated on a single campus or remotely located as long as they are served by a single utility or independent service operator. Project Description This project seeks to perform the necessary applied research, development, and testing to provide a communications interface using industry standard open protocols and emerging National Institute of Standards and Technology

425

Software demonstration: Demand Response Quick Assessment Tool  

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

Software demonstration: Demand Response Quick Assessment Tool Software demonstration: Demand Response Quick Assessment Tool Speaker(s): Peng Xu Date: February 4, 2008 - 12:00pm Location: 90-3122 The potential for utilizing building thermal mass for load shifting and peak demand reduction has been demonstrated in a number of simulation, laboratory, and field studies. The Demand Response Quick Assessment Tools developed at LBNL will be demonstrated. The tool is built on EnergyPlus simulation and is able to evaluate and compare different DR strategies, such as global temperature reset, chiller cycling, supply air temperature reset, etc. A separate EnergyPlus plotting tool will also be demonstrated during this seminar. Users can use the tool to test EnergyPlus models, conduct parametric analysis, or compare multiple EnergyPlus simulation

426

Better Buildings Neighborhood Program: Driving Demand  

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

even know they have. This section explains how you can use effective marketing to drive demand for energy upgrades in your community. Following the lead of many Better Buildings...

427

EIA - Annual Energy Outlook 2009 - Energy Demand  

Gasoline and Diesel Fuel Update (EIA)

demand for renewable fuels increasing the fastestincluding E85 and biodiesel fuels for light-duty vehicles, biomass for co-firing at coal-fired electric power plants, and...

428

Demand response-enabled residential thermostat controls  

E-Print Network (OSTI)

from the utility. The electricity rates were generated basedat the different electricity rates and the users discomfortrates. Demand response measures have the effect of adding elasticity to the electricity

Chen, Xue; Jang, Jaehwi; Auslander, David; Peffer, Therese; Arens, Edward

2008-01-01T23:59:59.000Z

429

A residential energy demand system for Spain  

E-Print Network (OSTI)

Sharp price fluctuations and increasing environmental and distributional concerns, among other issues, have led to a renewed academic interest in energy demand. In this paper we estimate, for the first time in Spain, an ...

Labandeira Villot, Xavier

2005-01-01T23:59:59.000Z

430

Demand Response Enabled Appliance Development at GE  

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

Demand Response Enabled Appliance Development at GE Speaker(s): David Najewicz Date: June 12, 2009 - 12:00pm Location: 90-3122 Dave Najewicz of GE Consumer and Appliances will...

431

Automated Demand Response for Critical Peak Pricing  

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

Automated Demand Response for Critical Peak Pricing Speaker(s): Naoya Motegi Date: June 9, 2005 - 12:00pm Location: Bldg. 90 California utilities have been exploring the use of...

432

Wireless Demand Response Controls for HVAC  

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

Wireless Demand Response Controls for HVAC Speaker(s): Clifford Federspiel Date: June 22, 2006 - 12:00pm Location: 90-3148 Seminar HostPoint of Contact: Richard Diamond Peng Xu We...

433

Geographically Based Hydrogen Demand & Infrastructure Analysis (Presentation)  

DOE Green Energy (OSTI)

Presentation given at the 2006 DOE Hydrogen, Fuel Cells & Infrastructure Technologies Program Annual Merit Review in Washington, D.C., May 16-19, 2006, discusses potential future hydrogen demand and the infrastructure needed to support hydrogen vehicles.

Melendez, M.

2006-05-18T23:59:59.000Z

434

Software demonstration: Demand Response Quick Assessment Tool  

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

Software demonstration: Demand Response Quick Assessment Tool Speaker(s): Peng Xu Date: February 4, 2008 - 12:00pm Location: 90-3122 The potential for utilizing building thermal...

435

Volatile coal prices reflect supply, demand uncertainties  

SciTech Connect

Coal mine owners and investors say that supply and demand are now finally in balance. But coal consumers find that both spot tonnage and new contract coal come at a much higher price.

Ryan, M.

2004-12-15T23:59:59.000Z

436

Demand response-enabled residential thermostat controls.  

E-Print Network (OSTI)

from the utility. The electricity rates were generated basedat the different electricity rates and the users discomfortrates. Demand response measures have the effect of adding elasticity to the electricity

Chen, Xue; Jang, Jaehwi; Auslander, David M.; Peffer, Therese; Arens, Edward A

2008-01-01T23:59:59.000Z

437

Essays on exchange rates and electricity demand  

E-Print Network (OSTI)

This thesis examines two important issues in economic development: exchange rates and electricity demand and addresses methodological issues of using time series and panel data analysis to investigate important policy ...

Li, Xiangming, 1966-

1999-01-01T23:59:59.000Z

438

Micro economics for demand-side management  

E-Print Network (OSTI)

This paper aims to interpret Demand-Side Management (DSM) activity and to point out its problems, adopting microeconomics as an analytical tool. Two major findings follow. first, the cost-benefit analysis currently in use ...

Kibune, Hisao

1991-01-01T23:59:59.000Z

439

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

Regulatory Commission [FERC] (2008). Assessment of DemandRegulatory Commission [FERC] (2009). A National AssessmentEIS EMCS EMS EPA ESCO ESPC FERC GE HVAC ISO ISO-NE kW kWh MW

Goldman, Charles

2010-01-01T23:59:59.000Z

440

Proceedings: Demand-Side Management Incentive Regulation  

Science Conference Proceedings (OSTI)

These proceedings provide background information on proposed regulatory incentive mechanisms to encourage utilities to develop demand-side management programs. Attendees discussed and analyzed various proposals and techniques and developed lists of key attributes that incentive mechanisms should have.

None

1990-05-01T23:59:59.000Z

Note: This page contains sample records for the topic "demand module structure" 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

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network (OSTI)

function of real-time electricity prices (left) and windinflexible) demand and real-time prices. The case study inas a special case. The real-time price process is modeled as

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

442

Rapid increases in electricity demand challenge both ...  

U.S. Energy Information Administration (EIA)

... on April 1 was the steepest so far this year in SPP. The rate of increase in electricity demand peaked at 12.4% between 6 a.m. and 7 a.m. ...

443

Marketing & Driving Demand Collaborative - Social Media Tools...  

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

for Marketing and Demand Creation (1.5 hr video) - EarthAid & Efficiency 2.0 Facebook Social Plug-ins YouTube Google Tools - Adwords & Web Optimizer *...

444

Coordination of Energy Efficiency and Demand Response  

E-Print Network (OSTI)

and Demand Response Duke Energy is using the name Save-a-Energy Efficiency Division. Duke Energy describes all of itsPresident, and C.E.O. Duke Energy Kateri Callahan President

Goldman, Charles

2010-01-01T23:59:59.000Z

445

Macroeconomic Activity Module (Mam) 1998 (Kernel Regression), Model Documentation  

Reports and Publications (EIA)

The Macroeconomic Activity Module (MAM) serves two functions within the National Energy Modeling System (NEMS). First, it provides consistent sets of baselines macroeconomic variables (GDP and components, aggregate prices, interest rates, industrial output, housing starts, commercial floorspace, newcar sales, etc.) which are used by the supply, demand and conversion modules in reaching an energy market equilibrium. Second, it is designed to provide a feedback mechanism that alters the baseline variables during the course of an integrated NEMS run.

Ron Earley

1998-10-01T23:59:59.000Z

446

Climate policy implications for agricultural water demand  

SciTech Connect

Energy, water and land are scarce resources, critical to humans. Developments in each affect the availability and cost of the others, and consequently human prosperity. Measures to limit greenhouse gas concentrations will inevitably exact dramatic changes on energy and land systems and in turn alter the character, magnitude and geographic distribution of human claims on water resources. We employ the Global Change Assessment Model (GCAM), an integrated assessment model to explore the interactions of energy, land and water systems in the context of alternative policies to limit climate change to three alternative levels: 2.5 Wm-2 (445 ppm CO2-e), 3.5 Wm-2 (535 ppm CO2-e) and 4.5 Wm-2 (645 ppm CO2-e). We explore the effects of two alternative land-use emissions mitigation policy optionsone which taxes terrestrial carbon emissions equally with fossil fuel and industrial emissions, and an alternative which only taxes fossil fuel and industrial emissions but places no penalty on land-use change emissions. We find that increasing populations and economic growth could be anticipated to almost triple demand for water for agricultural systems across the century even in the absence of climate policy. In general policies to mitigate climate change increase agricultural demands for water still further, though the largest changes occur in the second half of the century, under both policy regimes. The two policies examined profoundly affected both the sources and magnitudes of the increase in irrigation water demands. The largest increases in agricultural irrigation water demand occurred in scenarios where only fossil fuel emissions were priced (but not land-use change emission) and were primarily driven by rapid expansion in bioenergy production. In these scenarios water demands were large relative to present-day total available water, calling into question whether it would be physically possible to produce the associated biomass energy. We explored the potential of improved water delivery and irrigation system efficiencies. These could potentially reduce demands substantially. However, overall demands remained high under our fossil-fuel-only tax policy. In contrast, when all carbon was priced, increases in agricultural water demands were smaller than under the fossil-fuel-only policy and were driven primarily by increased demands for water by non-biomass crops such as rice. Finally we estimate the geospatial pattern of water demands and find that regions such as China, India and other countries in south and east Asia might be expected to experience greatest increases in water demands.?

Chaturvedi, Vaibhav; Hejazi, Mohamad I.; Edmonds, James A.; Clarke, Leon E.; Kyle, G. Page; Davies, Evan; Wise, Marshall A.; Calvin, Katherine V.

2013-03-28T23:59:59.000Z

447

Measuring the capacity impacts of demand response  

Science Conference Proceedings (OSTI)

Critical peak pricing and peak time rebate programs offer benefits by increasing system reliability, and therefore, reducing capacity needs of the electric power system. These benefits, however, decrease substantially as the size of the programs grows relative to the system size. More flexible schemes for deployment of demand response can help address the decreasing returns to scale in capacity value, but more flexible demand response has decreasing returns to scale as well. (author)

Earle, Robert; Kahn, Edward P.; Macan, Edo

2009-07-15T23:59:59.000Z

448

Tri-State Demand Response Framework  

Science Conference Proceedings (OSTI)

This report provides the results of a demand response framework development project of Tri-State Generation and Transmission, a wholesale provider to a number of rural electric associations in the Rocky Mountain west. Tri-State has developed an assortment of planned demand response and energy shaping products and services designed to both shave peak and shift consumption to off-peak hours. The applications, networks, and devices that will be needed to support these needs will involve many ...

2013-03-28T23:59:59.000Z

449

Enhanced heat transfer for thermionic power modules  

DOE Green Energy (OSTI)

The thermionic power module is capable of operating at very high heat fluxes, which in turn serve to reduce capital costs. The most efficient operation also requires uniform heat fluxes. The development of enhanced heat transfer systems is required to meet the demand for high heat fluxes (>20 w/cm/sup 2/) at high temperatures (>1500K) which advanced thermionic power modules place upon combustion systems. Energy transfer from the hot combustion gases may take place by convection, radiation, or a combination of radiation and convection. Enhanced convective heat transfer with a jet impingement system has been demonstrated in a thermionic converter. The recently-developed cellular ceramic radiative heat transfer system has also been applied to a thermionic converter. By comparing the jet impingement and cellular ceramic radiative heat transfer systems, an appropriate system may be selected for utilization in advanced thermionic power modules. Results are reported.

Johnson, D.C.

1981-07-01T23:59:59.000Z

450

Ethanol Demand in United States Gasoline Production  

SciTech Connect

The Oak Ridge National Laboratory (OWL) Refinery Yield Model (RYM) has been used to estimate the demand for ethanol in U.S. gasoline production in year 2010. Study cases examine ethanol demand with variations in world oil price, cost of competing oxygenate, ethanol value, and gasoline specifications. For combined-regions outside California summer ethanol demand is dominated by conventional gasoline (CG) because the premised share of reformulated gasoline (RFG) production is relatively low and because CG offers greater flexibility for blending high vapor pressure components like ethanol. Vapor pressure advantages disappear for winter CG, but total ethanol used in winter RFG remains low because of the low RFG production share. In California, relatively less ethanol is used in CG because the RFG production share is very high. During the winter in California, there is a significant increase in use of ethanol in RFG, as ethanol displaces lower-vapor-pressure ethers. Estimated U.S. ethanol demand is a function of the refiner value of ethanol. For example, ethanol demand for reference conditions in year 2010 is 2 billion gallons per year (BGY) at a refiner value of $1.00 per gallon (1996 dollars), and 9 BGY at a refiner value of $0.60 per gallon. Ethanol demand could be increased with higher oil prices, or by changes in gasoline specifications for oxygen content, sulfur content, emissions of volatile organic compounds (VOCS), and octane numbers.

Hadder, G.R.

1998-11-24T23:59:59.000Z

451

On demand responsiveness in additive cost sharing  

E-Print Network (OSTI)

Abstract. We propose two new axioms of demand responsiveness for additive cost sharing with variable demands. Group Monotonicity requires that if a group of agents increase their demands, not all of them pay less. Solidarity says that if agent i demands more, j should not pay more if k pays less. Both axioms are compatible in the partial responsibility theory postulating Strong Ranking, i.e., the ranking of cost shares should never contradict that of demands. The combination of Strong Ranking, Solidarity and Monotonicity characterizes the quasi-proportional methods, under which cost shares are proportional to rescaled demands. The alternative full responsibility theory is based on Separability, ruling out cross-subsidization when costs are additively separable. Neither the Aumann-Shapley nor the Shapley-Shubik method is group monotonic. On the other hand, convex combinations of nearby xed-path methods are group-monotonic: the subsidy-free serial method is the main example. No separable method meets Solidarity, yet restricting the axiom to submodular (or supermodular) cost functions leads to a characterization of the xed-ow methods, containing the Shapley-Shubik and serial methods. JEL Classication numbers: C 71, D 63.

Herv Moulin; Yves Sprumont

2005-01-01T23:59:59.000Z

452

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

453

Chilled Water Thermal Storage System and Demand Response at the University of California at Merced  

E-Print Network (OSTI)

University of California at Merced is a unique campus that has benefited from intensive efforts to maximize energy efficiency, and has participated in a demand response program for the past two years. Campus demand response evaluations are often difficult because of the complexities introduced by central heating and cooling, non-coincident and diverse building loads, and existence of a single electrical meter for the entire campus. At the University of California at Merced, a two million gallon chilled water storage system is charged daily during off-peak price periods and used to flatten the load profile during peak demand periods, further complicating demand response scenarios. The goal of this research is to study demand response savings in the presence of storage systems in a campus setting. First, University of California at Merced is described and its participation in a demand response event during 2008 is detailed. Second, a set of demand response strategies were pre-programmed into the campus control system to enable semi-automated demand response during a 2009 event, which is also evaluated. Finally, demand savings results are applied to the utilitys DR incentives structure to calculate the financial savings under various DR programs and tariffs.

Granderson, J.; Dudley, J. H.; Kiliccote, S.; Piette, M. A.

2009-11-01T23:59:59.000Z

454

Demand-Side Management (DSM) Opportunities as Real-Options  

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

Demand-Side Management (DSM) Opportunities as Real-Options Demand-Side Management (DSM) Opportunities as Real-Options Speaker(s): Osman Sezgen Date: August 1, 2002 - 12:00pm Location: Bldg. 90 Seminar Host/Point of Contact: Kristina LaCommare As some end-users of energy and aggregators are choosing to be exposed to real-time prices and energy price volatility, they are coming across new DSM opportunities that would not be feasible under typical utility rate structures. Effective evaluation of such opportunities requires a good understanding of the wholesale energy markets and the use of models based on recent financial techniques for option pricing. The speaker will give examples of such modeling approaches based on his experience in the retail-energy industry. Specific examples will include evaluation of distributed generation, load curtailment, dual-fuel cooling, and energy

455

The Role of Demand Resources In Regional Transmission Expansion Planning and Reliable Operations  

Science Conference Proceedings (OSTI)

Investigating the role of demand resources in regional transmission planning has provided mixed results. On one hand there are only a few projects where demand response has been used as an explicit alternative to transmission enhancement. On the other hand there is a fair amount of demand response in the form of energy efficiency, peak reduction, emergency load shedding, and (recently) demand providing ancillary services. All of this demand response reduces the need for transmission enhancements. Demand response capability is typically (but not always) factored into transmission planning as a reduction in the load which must be served. In that sense demand response is utilized as an alternative to transmission expansion. Much more demand response is used (involuntarily) as load shedding under extreme conditions to prevent cascading blackouts. The amount of additional transmission and generation that would be required to provide the current level of reliability if load shedding were not available is difficult to imagine and would be impractical to build. In a very real sense demand response solutions are equitably treated in every region - when proposed, demand response projects are evaluated against existing reliability and economic criteria. The regional councils, RTOs, and ISOs identify needs. Others propose transmission, generation, or responsive load based solutions. Few demand response projects get included in transmission enhancement plans because few are proposed. But this is only part of the story. Several factors are responsible for the current very low use of demand response as a transmission enhancement alternative. First, while the generation, transmission, and load business sectors each deal with essentially the same amount of electric power, generation and transmission companies are explicitly in the electric power business but electricity is not the primary business focus of most loads. This changes the institutional focus of each sector. Second, market and reliability rules have, understandably, been written around the capabilities and limitations of generators, the historic reliability resources. Responsive load limitations and capabilities are often not accommodated in markets or reliability criteria. Third, because of the institutional structure, demand response alternatives are treated as temporary solutions that can delay but not replace transmission enhancement. Financing has to be based on a three to five year project life as opposed to the twenty to fifty year life of transmission facilities. More can be done to integrate demand response options into transmission expansion planning. Given the societal benefits it may be appropriate for independent transmission planning organizations to take a more proactive role in drawing demand response alternatives into the resource mix. Existing demand response programs provide a technical basis to build from. Regulatory and market obstacles will have to be overcome if demand response alternatives are to be routinely considered in transmission expansion planning.

Kirby, Brendan J [ORNL

2006-07-01T23:59:59.000Z

456

Econometric Analyses of Public Water Demand in the United States  

E-Print Network (OSTI)

Two broad surveys of community- level water consumption and pricing behavior are used to answer questions about water demand in a more flexible and dynamic context than is provided in the literature. Central themes of price representation, aggregation, and dynamic adjustment tie together three econometric demand analyses. The centerpiece of each analysis is an exogenous weighted price representation. A model in first-differences is estimated by ordinary least squares using data from a personally-conducted survey of Texas urban water suppliers. Annual price elasticity is found to vary with weather and income, with a value of -0.127 at the data mean. The dynamic model becomes a periodic error correction model when the residuals of 12 static monthly models are inserted into the difference model. Distinct residential, commercial, and industrial variables and historical climatic conditions are added to the integrated model, using new national data. Quantity demanded is found to be periodically integrated with a common stochastic root. Because of this, the structural monthly models must be cointegrated to be consistent, which they appear to be. The error correction coefficient is estimated at -0.187. Demand is found to be seasonal and slow to adjust to shocks, with little or no adjustment in a single year and 90% adjustment taking a decade or more. Residential and commercial demand parameters are found to be indistinguishable. The sources of price endogeneity and historical fixes are reviewed. Ideal properties of a weighted price index are identified. For schedules containing exactly two rates, weighting is equivalent to a distribution function in consumption. This property is exploited to derive empirical weights from the national data, using values from a nonparametric generalization of the structural demand model and a nonparametric cumulative density function. The result is a generalization of the price difference metric to a weighted level-price index. The validity of a uniform weighting is not rejected. The weighted price index is data intensive, but the payoff is increased depth and precision for the economist and accessibility for the practitioner.

Bell, David

2011-12-01T23:59:59.000Z

457

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

458

Modulating lignin in plants  

DOE Patents (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

459

DemandDirect | Open Energy Information  

Open Energy Info (EERE)

DemandDirect DemandDirect Jump to: navigation, search Name DemandDirect Place Woodbury, Connecticut Zip 6798 Sector Efficiency, Renewable Energy, Services Product DemandDirect provides demand response, energy efficiency, load management, and distributed generation services to end-use electricity customers in order to reduce electricity consumption, improve grid reliability, and promote renewable energy. Coordinates 44.440496°, -72.414991° 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":44.440496,"lon":-72.414991,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

460

U.S. Coal Supply and Demand  

Gasoline and Diesel Fuel Update (EIA)

U.S. Coal Supply and Demand > U.S. Coal Supply and Demand U.S. Coal Supply and Demand > U.S. Coal Supply and Demand U.S. Coal Supply and Demand 2010 Review (entire report also available in printer-friendly format ) Previous Editions 2009 Review 2008 Review 2007 Review 2006 Review 2005 Review 2004 Review 2003 Review 2002 Review 2001 Review 2000 Review 1999 Review Data for: 2010 Released: May 2011 Next Release Date: April 2012 Table 3. Electric Power Sector Net Generation, 2009-2010 (Million Kilowatthours) New England Coal 14,378 14,244 -0.9 Hydroelectric 7,759 6,861 -11.6 Natural Gas 48,007 54,680 13.9 Nuclear 36,231 38,361 5.9 Other (1) 9,186 9,063 -1.3 Total 115,559 123,210 6.6 Middle Atlantic Coal 121,873 129,935 6.6 Hydroelectric 28,793 26,463 -8.1 Natural Gas 89,808 104,341 16.2 Nuclear 155,140 152,469 -1.7

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461

Changing fuel formulations will boost hydrogen demand  

SciTech Connect

Refinery demand in the U.S. for on-purpose hydrogen will continue to increase by 5-10 %/year, depending on the extent of implementation of the 1990 U.S. Clean Air Act Amendments (CAAA) and other proposed environmental legislation. Although the debate on the economic wisdom of the legislation still rages, it is evident that refiners likely will see a large upswing in hydrogen demand while existing hydrogen production may decline. To better understand the potential impact various reformulation scenarios may have on the refining industry, and specifically, on the demand for hydrogen, Texaco analyzed the hydrogen supply/demand scenario in great detail. Two cases were studied in this analysis: mild and severe reformulation. The mild reformulation case is based on current CAAA legislation along with minor modifications to automobile hardware. The severe case is based on a nationwide implementation of Phase 2 of the CAAA and California's proposed reformulated fuels. The paper discusses the current capacity balance; growth in demand; reformulated gasoline; steam methane reforming; and partial oxidation technology.

Simonsen, K.A.; O' Keefe, L.F. (Texaco Inc., White Plains, N.Y. (United States)); Fong, W.F. (Texaco Development Corp., White Plains, N.Y. (United States))

1993-03-22T23:59:59.000Z

462

Environmental issues of material input in CDTE-module manufacturing  

DOE Green Energy (OSTI)

The goal of a low-cost and high-volume photovoltaic (PV) module fabrication demands an optimized process sequence to guarantee product quality and module stability on a long-term basis. Nevertheless, large-scale module manufacturing uses several input and auxiliary materials and generates waste from processing output materials. The mining and refining of the PV manufacturing material consumes input and auxiliary material and also creates waste. Therefore, investigations into these materials were conducted with respect to their risk potential for environment and health.

Steinberger, H.; Hochwimmer, R.; Schmid, H. [Fraunhofer Inst. fuer Festkoerpertechnologie, Muenchen (Germany); Thumm, W.; Kettrup, A. [GSF, Oberschleissheim (Germany). Inst. fuer Oekologische Chemie; Moskowitz, P. [Brookhaven National Lab., Upton, NY (United States). Biomedical and Environmental Assessment Group

1995-12-31T23:59:59.000Z

463

Electric-Field Modulation of Curie Temperature in (Ga, Mn)As Field-Effect Transistor Structures with Varying Channel Thickness and Mn Compositions  

SciTech Connect

We have investigated the change of T{sub C} of ferromagnetic semiconductor (Ga, Mn)As by changing hole concentration p. The field effect transistor structure was utilized to change p. The relation T{sub C}propor top{sup 0.2} is obtained for three samples, despite the difference of their Mn composition and thickness, indicating that the relation holds over 2 decades of p.

Nishitani, Y.; Endo, M. [Laboratory for Nanoelectronics and Spintronics, Research Institute of Electrical Communication, Tohoku University, Katahira 2-1-1, Aoba-ku, Sendai 980-8577 (Japan); Chiba, D. [Semiconductor Spintronics Project, Exploratory Research for Advanced Technology, Japan Science and Technology Agency, Sanban-cho 5, Chiyoda-ku, Tokyo 102-0075 (Japan); Laboratory for Nanoelectronics and Spintronics, Research Institute of Electrical Communication, Tohoku University, Katahira 2-1-1, Aoba-ku, Sendai 980-8577 (Japan); Matsukura, F.; Ohno, H. [Laboratory for Nanoelectronics and Spintronics, Research Institute of Electrical Communication, Tohoku University, Katahira 2-1-1, Aoba-ku, Sendai 980-8577 (Japan); Semiconductor Spintronics Project, Exploratory Research for Advanced Technology, Japan Science and Technology Agency, Sanban-cho 5, Chiyoda-ku, Tokyo 102-0075 (Japan)

2010-01-04T23:59:59.000Z

464

EIA - AEO2010 - Natural Gas Demand  

Gasoline and Diesel Fuel Update (EIA)

Gas Demand Gas Demand Annual Energy Outlook 2010 with Projections to 2035 Natural Gas Demand Figure 68. Regional growth in nonhydroelectric renewable electricity capacity including end-use capacity, 2008-2035 Click to enlarge » Figure source and data excel logo Figure 69. Annual average lower 48 wellhead and Henry Hub spot market prices for natural gas, 1990-2035. Click to enlarge » Figure source and data excel logo Figure 70. Ratio of low-sulfur light crude oil price to Henry Hub natural gas price on an energy equivalent basis, 1990-2035 Click to enlarge » Figure source and data excel logo Figure 71. Annual average lower 48 wellhead prices for natural gas in three technology cases, 1990-2035. Click to enlarge » Figure source and data excel logo Figure 72. Annual average lower 48 wellhead prices for natural gas in three oil price cases, 1990-2035

465

Production Will Meet Demand Increase This Summer  

Gasoline and Diesel Fuel Update (EIA)

5 5 Notes: Production must meet increases in demand this year. Last year, increased imports met most of the summer demand increase, and increases in stock draws met almost all of the remainder. Production did not increase much. But this year, inventories will not be available, and increased imports seem unlikely. Thus, increases in production will be needed to meet increased demand. Imports availability is uncertain this summer. Imports in 1999 were high, and with Phase II RFG product requirements, maintaining this level could be challenging since not all refineries exporting to the U.S. will be able to meet the new gasoline specifications. Stocks will also contribute little supply this summer. Last year's high gasoline stocks allowed for a stock draw that was 58 MB/D higher than

466

EIA - Annual Energy Outlook 2008 - Energy Demand  

Gasoline and Diesel Fuel Update (EIA)

Energy Demand Energy Demand Annual Energy Outlook 2008 with Projections to 2030 Energy Demand Figure 40. Energy use per capita and per dollar of gross domestic product, 1980-2030 (index, 1980 = 1). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 41. Primary energy use by fuel, 2006-2030 (quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800. figure data Average Energy Use per Person Levels Off Through 2030 Because energy use for housing, services, and travel in the United States is closely linked to population levels, energy use per capita is relatively stable (Figure 40). In addition, the economy is becoming less dependent on energy in general. Energy intensity (energy use per 2000 dollar of GDP) declines by an average

467

Demand Management Institute (DMI) | Open Energy Information  

Open Energy Info (EERE)

Demand Management Institute (DMI) Demand Management Institute (DMI) Jump to: navigation, search Name Demand Management Institute (DMI) Address 35 Walnut Street Place Wellesley, Massachusetts Zip 02481 Sector Buildings Product Provides analysis for buildings on reducing energy use Website http://www.dmiinc.com/ Coordinates 42.3256508°, -71.2530294° 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":42.3256508,"lon":-71.2530294,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

468

Wireless Demand Response Controls for HVAC Systems  

Science Conference Proceedings (OSTI)

The objectives of this scoping study were to develop and test control software and wireless hardware that could enable closed-loop, zone-temperature-based demand response in buildings that have either pneumatic controls or legacy digital controls that cannot be used as part of a demand response automation system. We designed a SOAP client that is compatible with the Demand Response Automation Server (DRAS) being used by the IOUs in California for their CPP program, design the DR control software, investigated the use of cellular routers for connecting to the DRAS, and tested the wireless DR system with an emulator running a calibrated model of a working building. The results show that the wireless DR system can shed approximately 1.5 Watts per design CFM on the design day in a hot, inland climate in California while keeping temperatures within the limits of ASHRAE Standard 55: Thermal Environmental Conditions for Human Occupancy.

Federspiel, Clifford

2009-06-30T23:59:59.000Z

469

Centralized and Decentralized Control for Demand Response  

Science Conference Proceedings (OSTI)

Demand response has been recognized as an essential element of the smart grid. Frequency response, regulation and contingency reserve functions performed traditionally by generation resources are now starting to involve demand side resources. Additional benefits from demand response include peak reduction and load shifting, which will defer new infrastructure investment and improve generator operation efficiency. Technical approaches designed to realize these functionalities can be categorized into centralized control and decentralized control, depending on where the response decision is made. This paper discusses these two control philosophies and compares their relative advantages and disadvantages in terms of delay time, predictability, complexity, and reliability. A distribution system model with detailed household loads and controls is built to demonstrate the characteristics of the two approaches. The conclusion is that the promptness and reliability of decentralized control should be combined with the predictability and simplicity of centralized control to achieve the best performance of the smart grid.

Lu, Shuai; Samaan, Nader A.; Diao, Ruisheng; Elizondo, Marcelo A.; Jin, Chunlian; Mayhorn, Ebony T.; Zhang, Yu; Kirkham, Harold

2011-04-29T23:59:59.000Z

470

Supply and demand of lube oils  

Science Conference Proceedings (OSTI)

Lube oil consumption in the world has reached about 40 million tonnes per year, of which 24 million tonnes is used outside the communist areas. There are large regional differences in annual consumption per head from one kilogramme (kg) in India to 35 kg in North America. A statistical analysis of historical data over twenty years in about ninety countries has lead to the conclusion that national income, measured as GDP per head, is the key determinant of total lube oil consumption per head. The functional relationship, however, is different in different countries. Starting from GDP projections until the year 2000, regional forecasts of lube oil demand have been made which show that the share of developing nations outside the communist area in world demand will grow. This will increase the regional imbalance between base oil capacity and demand.

Vlemmings, J.M.L.M.

1988-01-01T23:59:59.000Z

471

China's Coal: Demand, Constraints, and Externalities  

Science Conference Proceedings (OSTI)

This study analyzes China's coal industry by focusing on four related areas. First, data are reviewed to identify the major drivers of historical and future coal demand. Second, resource constraints and transport bottlenecks are analyzed to evaluate demand and growth scenarios. The third area assesses the physical requirements of substituting coal demand growth with other primary energy forms. Finally, the study examines the carbon- and environmental implications of China's past and future coal consumption. There are three sections that address these areas by identifying particular characteristics of China's coal industry, quantifying factors driving demand, and analyzing supply scenarios: (1) reviews the range of Chinese and international estimates of remaining coal reserves and resources as well as key characteristics of China's coal industry including historical production, resource requirements, and prices; (2) quantifies the largest drivers of coal usage to produce a bottom-up reference projection of 2025 coal demand; and (3) analyzes coal supply constraints, substitution options, and environmental externalities. Finally, the last section presents conclusions on the role of coal in China's ongoing energy and economic development. China has been, is, and will continue to be a coal-powered economy. In 2007 Chinese coal production contained more energy than total Middle Eastern oil production. The rapid growth of coal demand after 2001 created supply strains and bottlenecks that raise questions about sustainability. Urbanization, heavy industrial growth, and increasing per-capita income are the primary interrelated drivers of rising coal usage. In 2007, the power sector, iron and steel, and cement production accounted for 66% of coal consumption. Power generation is becoming more efficient, but even extensive roll-out of the highest efficiency units would save only 14% of projected 2025 coal demand for the power sector. A new wedge of future coal consumption is likely to come from the burgeoning coal-liquefaction and chemicals industries. If coal to chemicals capacity reaches 70 million tonnes and coal-to-liquids capacity reaches 60 million tonnes, coal feedstock requirements would add an additional 450 million tonnes by 2025. Even with more efficient growth among these drivers, China's annual coal demand is expected to reach 3.9 to 4.3 billion tonnes by 2025. Central government support for nuclear and renewable energy has not reversed China's growing dependence on coal for primary energy. Substitution is a matter of scale: offsetting one year of recent coal demand growth of 200 million tonnes would require 107 billion cubic meters of natural gas (compared to 2007 growth of 13 BCM), 48 GW of nuclear (compared to 2007 growth of 2 GW), or 86 GW of hydropower capacity (compared to 2007 growth of 16 GW). Ongoing dependence on coal reduces China's ability to mitigate carbon dioxide emissions growth. If coal demand remains on a high growth path, carbon dioxide emissions from coal combustion alone would exceed total US energy-related carbon emissions by 2010. Within China's coal-dominated energy system, domestic transportation has emerged as the largest bottleneck for coal industry growth and is likely to remain a constraint to further expansion. China has a low proportion of high-quality reserves, but is producing its best coal first. Declining quality will further strain production and transport capacity. Furthermore, transporting coal to users has overloaded the train system and dramatically increased truck use, raising transportation oil demand. Growing international imports have helped to offset domestic transport bottlenecks. In the long term, import demand is likely to exceed 200 million tonnes by 2025, significantly impacting regional markets.

Aden, Nathaniel; Fridley, David; Zheng, Nina

2009-07-01T23:59:59.000Z

472

Demand Responsive Lighting: A Scoping Study  

SciTech Connect

The objective of this scoping study is: (1) to identify current market drivers and technology trends that can improve the demand responsiveness of commercial building lighting systems and (2) to quantify the energy, demand and environmental benefits of implementing lighting demand response and energy-saving controls strategies Statewide. Lighting systems in California commercial buildings consume 30 GWh. Lighting systems in commercial buildings often waste energy and unnecessarily stress the electrical grid because lighting controls, especially dimming, are not widely used. But dimmable lighting equipment, especially the dimming ballast, costs more than non-dimming lighting and is expensive to retrofit into existing buildings because of the cost of adding control wiring. Advances in lighting industry capabilities coupled with the pervasiveness of the Internet and wireless technologies have led to new opportunities to realize significant energy saving and reliable demand reduction using intelligent lighting controls. Manufacturers are starting to produce electronic equipment--lighting-application specific controllers (LAS controllers)--that are wirelessly accessible and can control dimmable or multilevel lighting systems obeying different industry-accepted protocols. Some companies make controllers that are inexpensive to install in existing buildings and allow the power consumed by bi-level lighting circuits to be selectively reduced during demand response curtailments. By intelligently limiting the demand from bi-level lighting in California commercial buildings, the utilities would now have an enormous 1 GW demand shed capability at hand. By adding occupancy and light sensors to the remotely controllable lighting circuits, automatic controls could harvest an additional 1 BkWh/yr savings above and beyond the savings that have already been achieved. The lighting industry's adoption of DALI as the principal wired digital control protocol for dimming ballasts and increased awareness of the need to standardize on emerging wireless technologies are evidence of this transformation. In addition to increased standardization of digital control protocols controller capabilities, the lighting industry has improved the performance of dimming lighting systems over the last two years. The system efficacy of today's current dimming ballasts is approaching that of non-dimming program start ballasts. The study finds that the benefits of applying digital controls technologies to California's unique commercial buildings market are enormous. If California were to embark on an concerted 20 year program to improve the demand responsiveness and energy efficiency of commercial building lighting systems, the State could avoid adding generation capacity, improve the elasticity of the grid, save Californians billion of dollars in avoided energy charges and significantly reduce greenhouse gas emissions.

Rubinstein, Francis; Kiliccote, Sila

2007-01-03T23:59:59.000Z

473

Demand Responsive Lighting: A Scoping Study  

SciTech Connect

The objective of this scoping study is: (1) to identify current market drivers and technology trends that can improve the demand responsiveness of commercial building lighting systems and (2) to quantify the energy, demand and environmental benefits of implementing lighting demand response and energy-saving controls strategies Statewide. Lighting systems in California commercial buildings consume 30 GWh. Lighting systems in commercial buildings often waste energy and unnecessarily stress the electrical grid because lighting controls, especially dimming, are not widely used. But dimmable lighting equipment, especially the dimming ballast, costs more than non-dimming lighting and is expensive to retrofit into existing buildings because of the cost of adding control wiring. Advances in lighting industry capabilities coupled with the pervasiveness of the Internet and wireless technologies have led to new opportunities to realize significant energy saving and reliable demand reduction using intelligent lighting controls. Manufacturers are starting to produce electronic equipment--lighting-application specific controllers (LAS controllers)--that are wirelessly accessible and can control dimmable or multilevel lighting systems obeying different industry-accepted protocols. Some companies make controllers that are inexpensive to install in existing buildings and allow the power consumed by bi-level lighting circuits to be selectively reduced during demand response curtailments. By intelligently limiting the demand from bi-level lighting in California commercial buildings, the utilities would now have an enormous 1 GW demand shed capability at hand. By adding occupancy and light sensors to the remotely controllable lighting circuits, automatic controls could harvest an additional 1 BkWh/yr savings above and beyond the savings that have already been achieved. The lighting industry's adoption of DALI as the principal wired digital control protocol for dimming ballasts and increased awareness of the need to standardize on emerging wireless technologies are evidence of this transformation. In addition to increased standardization of digital control protocols controller capabilities, the lighting industry has improved the performance of dimming lighting systems over the last two years. The system efficacy of today's current dimming ballasts is approaching that of non-dimming program start ballasts. The study finds that the benefits of applying digital controls technologies to California's unique commercial buildings market are enormous. If California were to embark on an concerted 20 year program to improve the demand responsiveness and energy efficiency of commercial building lighting systems, the State could avoid adding generation capacity, improve the elasticity of the grid, save Californians billion of dollars in avoided energy charges and significantly reduce greenhouse gas emissions.

Rubinstein, Francis; Kiliccote, Sila

2007-01-03T23:59:59.000Z

474

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network (OSTI)

as 15-minute minimum and maximum demand values are provided.8. Hourly average and maximum demand savings of McKinstry on9. Hourly average and maximum demand savings of McKinstry on

Kiliccote, Sila

2010-01-01T23:59:59.000Z

475

Open Automated Demand Response Dynamic Pricing Technologies and Demonstration  

E-Print Network (OSTI)

if the customers maximum demand has exceeded 999 kilowattswhose meter indicates a maximum demand of 200 kW or greater2) the customer's maximum billing demand has exceeded 499

Ghatikar, Girish

2010-01-01T23:59:59.000Z

476

Open Automated Demand Response for Small Commerical Buildings  

E-Print Network (OSTI)

theaverage,minimumandmaximumdemandreductionforeachAverage, Minimum and Maximum Demand Reduction Based on 3/1016 Average, Minimum and Maximum Demand Reduction Based on

Dudley, June Han

2009-01-01T23:59:59.000Z

477

Automated Demand Response Strategies and Commissioning Commercial Building Controls  

E-Print Network (OSTI)

4 9 . Piette et at Automated Demand Response Strategies andDynamic Controls for Demand Response in New and ExistingFully Automated Demand Response Tests in Large Facilities"

Piette, Mary Ann; Watson, David; Motegi, Naoya; Kiliccote, Sila; Linkugel, Eric

2006-01-01T23:59:59.000Z

478

Behavioral Aspects in Simulating the Future US Building Energy Demand  

E-Print Network (OSTI)

off- site energy demand (2030) 20% decrease to parameter 20%off-site energy demand (2030) 20% decrease to parameter 20%off-site energy demand (2030) 20% decrease to parameter 20%

Stadler, Michael

2011-01-01T23:59:59.000Z

479

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

Non-vehicle demand load factor Natural gas price Carbon tax89). They increase with demand (and gross natural gas-firedelectricity demand and by changing natural gas price and CO

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

480

Univariate Modeling and Forecasting of Monthly Energy Demand Time Series  

E-Print Network (OSTI)

in this report. #12;i ABSTRACT These electricity demand forms and instructions ask load-serving entities and Instructions for Electricity Demand Forecasts. California Energy Commission, Electricity Supply Analysis.................................................................................................................................7 Form 1 Historic and Forecast Electricity Demand

Abdel-Aal, Radwan E.

Note: This page contains sample records for the topic "demand module structure" 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.


481

Open Automated Demand Response for Small Commerical Buildings  

E-Print Network (OSTI)

ofthesmallcommercialpeakdemand. Themajorityofthelessthan200kWofpeakdemand,makeup20?25%of peakthesmallcommercial peakdemand. Atenpercentreduction

Dudley, June Han

2009-01-01T23:59:59.000Z

482

Assessing Vehicle Electricity Demand Impacts on California Electricity Supply  

E-Print Network (OSTI)

serves to partially fill off-peak demand troughs. If passivehigher before or after the peak demand hour when hydro powerare highest during off-peak demand hours, and are low at

McCarthy, Ryan W.

2009-01-01T23:59:59.000Z

483

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network (OSTI)

by Sector Residential Peak Demand (MW) Commercial IndustrialTable 16. Non-coincident peak demand by sector. growth Avg.IEPR Projected non-coincident peak demand (MW) 3.1.2. Hourly

McCarthy, Ryan; Yang, Christopher; Ogden, Joan M.

2008-01-01T23:59:59.000Z

484

Automated Demand Response Opportunities in Wastewater Treatment Facilities  

E-Print Network (OSTI)

power generators during peak demand periods. 13 Onsite powerit can be used during peak-demand periods. 15 Implementingtreatment loads from peak demand hours to off-peak hours is

Thompson, Lisa

2008-01-01T23:59:59.000Z

485

Linking Continuous Energy Management and Open Automated Demand Response  

E-Print Network (OSTI)

minimization Monthly peak demand management Daily time-of-Some tariff designs have peak demand charges that apply tothat may result in a peak demand that occurs in one month to

Piette, Mary Ann

2009-01-01T23:59:59.000Z

486

2012 Portland General Electric. All rights reserved. Planning for Demand  

E-Print Network (OSTI)

2/13/2013 1 © 2012 Portland General Electric. All rights reserved. Planning for Demand Response their usage. Demand Response ­ PGE Current Status 10 Automated Demand R

487

Laboratory Testing of Demand-Response Enabled Household Appliances  

SciTech Connect

With the advent of the Advanced Metering Infrastructure (AMI) systems capable of two-way communications between the utility's grid and the building, there has been significant effort in the Automated Home Energy Management (AHEM) industry to develop capabilities that allow residential building systems to respond to utility demand events by temporarily reducing their electricity usage. Major appliance manufacturers are following suit by developing Home Area Network (HAN)-tied appliance suites that can take signals from the home's 'smart meter,' a.k.a. AMI meter, and adjust their run cycles accordingly. There are numerous strategies that can be employed by household appliances to respond to demand-side management opportunities, and they could result in substantial reductions in electricity bills for the residents depending on the pricing structures used by the utilities to incent these types of responses.The first step to quantifying these end effects is to test these systems and their responses in simulated demand-response (DR) conditions while monitoring energy use and overall system performance.

Sparn, B.; Jin, X.; Earle, L.

2013-10-01T23:59:59.000Z

488

Installation and Commissioning Automated Demand Response Systems  

Science Conference Proceedings (OSTI)

Demand Response (DR) can be defined as actions taken to reduce electric loads when contingencies, such as emergencies and congestion, occur that threaten supply-demand balance, or market conditions raise supply costs. California utilities have offered price and reliability DR based programs to customers to help reduce electric peak demand. The lack of knowledge about the DR programs and how to develop and implement DR control strategies is a barrier to participation in DR programs, as is the lack of automation of DR systems. Most DR activities are manual and require people to first receive notifications, and then act on the information to execute DR strategies. Levels of automation in DR can be defined as follows. Manual Demand Response involves a labor-intensive approach such as manually turning off or changing comfort set points at each equipment switch or controller. Semi-Automated Demand Response involves a pre-programmed demand response strategy initiated by a person via centralized control system. Fully-Automated Demand Response does not involve human intervention, but is initiated at a home, building, or facility through receipt of an external communications signal. The receipt of the external signal initiates pre-programmed demand response strategies. We refer to this as Auto-DR (Piette et. al. 2005). Auto-DR for commercial and industrial facilities can be defined as fully automated DR initiated by a signal from a utility or other appropriate entity and that provides fully-automated connectivity to customer end-use control strategies. One important concept in Auto-DR is that a homeowner or facility manager should be able to 'opt out' or 'override' a DR event if the event comes at time when the reduction in end-use services is not desirable. Therefore, Auto-DR is not handing over total control of the equipment or the facility to the utility but simply allowing the utility to pass on grid related information which then triggers facility defined and programmed strategies if convenient to the facility. From 2003 through 2006 Lawrence Berkeley National Laboratory (LBNL) and the Demand Response Research Center (DRRC) developed and tested a series of demand response automation communications technologies known as Automated Demand Response (Auto-DR). In 2007, LBNL worked with three investor-owned utilities to commercialize and implement Auto-DR programs in their territories. This paper summarizes the history of technology development for Auto-DR, and describes the DR technologies and control strategies utilized at many of the facilities. It outlines early experience in commercializing Auto-DR systems within PG&E DR programs, including the steps to configure the automation technology. The paper also describes the DR sheds derived using three different baseline methodologies. Emphasis is given to the lessons learned from installation and commissioning of Auto-DR systems, with a detailed description of the technical coordination roles and responsibilities, and costs.

Global Energy Partners; Pacific Gas and Electric Company; Kiliccote, Sila; Kiliccote, Sila; Piette, Mary Ann; Wikler, Greg; Prijyanonda, Joe; Chiu, Albert

2008-04-21T23:59:59.000Z

489

Units: Cool Modules for HOT Languages  

E-Print Network (OSTI)

A module system ought to enable assembly-line programming using separate compilation and an expressive linking language. Separate compilation allows programmers to develop parts of a program independently. A linking language gives programmers precise control over the assembly of parts into a whole. This paper presents models of program units, MzScheme's module language for assembly-line programming. Units support separate compilation, independent module reuse, cyclic dependencies, hierarchical structuring, and dynamic linking. The models explain how to integrate units with untyped and typed languages such as Scheme and ML.

Matthew Flatt; Matthias Felleisen

1998-01-01T23:59:59.000Z

490

Patterns of crude demand: Future patterns of demand for crude oil as a func-  

E-Print Network (OSTI)

from the perspective of `peak oil', that is from the pers- pective of the supply of crude, and price#12;2 #12;Patterns of crude demand: Future patterns of demand for crude oil as a func- tion is given on the problems within the value chain, with an explanation of the reasons why the price of oil

Langendoen, Koen

491

Polycrystalline thin-film module and system performance  

DOE Green Energy (OSTI)

The Module and System Performance and Engineering Project at the National Renewable Energy Laboratory (NREL) conducts in-situ technical evaluations of photovoltaic (PV) modules and systems (arrays). These evaluations on module/array performance and stability are conducted at the NREL Photovoltaic Outdoor Test Facility (OTF) in Golden, CO. The modules and arrays are located at 39.7{degree}N latitude, 105.2{degree}W longitude, and at 1,782 meters elevation. Currently, two polycrystalline thin-film technologies are the focus of the research presented here. The module structures are copper indium diselenide (CIS) from Siemens Solar Industries and cadmium telluride (CdTe) from Solar Cells, Inc. The research team is attempting to correlate individual module performance with array performance for these two polycrystalline thin-film technologies. This is done by looking at module and array performance over time. Also, temperature coefficients are determined at both the module and array level. Results are discussed.

Strand, T.; Kroposki, B.; Hansen, R.; Mrig, L.

1995-11-01T23:59:59.000Z

492

Chilled Water Thermal Storage System and Demand Response at the University of California at Merced  

Science Conference Proceedings (OSTI)

The University of California at Merced is a unique campus that has benefited from intensive efforts to maximize energy efficiency, and has participated in a demand response program for the past two years. Campus demand response evaluations are often difficult because of the complexities introduced by central heating and cooling, non-coincident and diverse building loads, and existence of a single electrical meter for the entire campus. At the University of California at Merced, a two million gallon chilled water storage system is charged daily during off-peak price periods and used to flatten the load profile during peak demand periods. This makes demand response more subtle and challenges typical evaluation protocols. The goal of this research is to study demand response savings in the presence of storage systems in a campus setting. First, University of California at Merced summer electric loads are characterized; second, its participation in two demand response events is detailed. In each event a set of strategies were pre-programmed into the campus control system to enable semi-automated response. Finally, demand savings results are applied to the utility's DR incentives structure to calculate the financial savings under various DR programs and tariffs. A key conclusion to this research is that there is significant demand reduction using a zone temperature set point change event with the full off peak storage cooling in use.

Granderson, Jessica; Dudley, Junqiao Han; Kiliccote, Sila; Piette, Mary Ann

2009-10-08T23:59:59.000Z

493

Structure  

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

Structure Structure functions 1 NOTE: THE FIGURES IN THIS SECTION ARE INTENDED TO SHOW THE REPRESENTATIVE DATA. THEY ARE NOT MEANT TO BE COMPLETE COMPILATIONS OF ALL THE WORLD'S RELIABLE DATA. Q 2 (GeV 2 ) F 2 (x,Q 2 ) * 2 i x H1 ZEUS BCDMS E665 NMC SLAC 10 -3 10 -2 10 -1 1 10 10 2 10 3 10 4 10 5 10 6 10 7 10 8 10 9 10 -1 1 10 10 2 10 3 10 4 10 5 10 6 Figure 16.6: The proton structure function F p 2 measured in electromagnetic scattering of positrons on protons (collider experiments ZEUS and H1), in the kinematic domain of the HERA data, for x > 0.00006 (cf. Fig. 16.9 for data at smaller x and Q 2 ), and for electrons (SLAC) and muons (BCDMS, E665, NMC) on a fixed target. Statistical and systematic errors added in quadrature are shown. The data are plotted as a function of Q 2 in bins of fixed x. Some points have been slightly offset in Q 2 for clarity. The ZEUS binning in x is used in this plot; all other data are rebinned to the x values of

494

ENERGY DEMAND AND CONSERVATION IN KENYA: INITIAL APPRAISAL  

E-Print Network (OSTI)

of Statistics d) Nairobi, Kenya. See also Estimates ofDEMAND AND CONSERVATION IN KENYA: INITIAL APPRAISAL LeeDemand and Conservation in Kenya: Initial Appraisal Lee

Schipper, Lee

2013-01-01T23:59:59.000Z

495

Demand-Responsive and Efficient Building Systems as a Resource...  

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

Demand-Responsive and Efficient Building Systems as a Resource for Electricity Reliability Title Demand-Responsive and Efficient Building Systems as a Resource for Electricity...

496

U.S. Electric Utility Demand-Side Management 1999  

U.S. Energy Information Administration (EIA)

Electric Utility Demand-Side Management 1999 Executive Summary Background Demand-side management (DSM) programs consist of the planning, implementing, and monitoring ...

497

Forecasting the Demand of Woodfuels in Ghana - The Process Analysis...  

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

conducted to cover various categories of households to determine their basic energy demand for cooking, which is used to make more reliable projections in the future demand of...

498

Transportation Demand Management in Beijing - Mitigation of emissions...  

Open Energy Info (EERE)

the implementation of transport demand management measures. Appropriate Transport Demand Management (TDM) strategies and measures can affect travel behaviour and therefore reduce...

499

Demand Response Program Design and Implementation Case Study...  

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

Delurey, Dan, and J. Schwartz Date Published 022013 Keywords demand response research, demand side resources: policy, electricity markets, electricity markets and policy group,...

500

Rapid increases in electricity demand challenge both generating ...  

U.S. Energy Information Administration (EIA)

Because supply and demand for electricity must balance in real-time, rapid changes in demand create operational challenges for the electric system and generating unit ...