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


1

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

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

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

4

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.

5

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

6

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

7

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.

8

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

9

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.

10

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

11

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

12

California Energy Demand Scenario Projections to 2050  

E-Print Network [OSTI]

annual per-capita electricity consumption by demand15 California electricity consumption projections by demandannual per-capita electricity consumption by demand

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

2008-01-01T23:59:59.000Z

13

California Energy Demand Scenario Projections to 2050  

E-Print Network [OSTI]

California Energy Demand Scenario Projections to 2050 RyanCEC (2003a) California energy demand 2003-2013 forecast.CEC (2005a) California energy demand 2006-2016: Staff energy

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

2008-01-01T23:59:59.000Z

14

Demand Response Projects: Technical and Market Demonstrations  

E-Print Network [OSTI]

Demand Response Projects: Technical and Market Demonstrations Philip D. Lusk Deputy Director Energy Analyst #12;PLACE CAPTION HERE. #12;#12;#12;#12;City of Port Angeles Demand Response History energy charges · Demand charges during peak period only ­ Reduced demand charges for demand response

15

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.

16

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.

17

Integrated Predictive Demand Response Controller Research Project |  

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

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

18

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

19

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

20

Hawaiian Electric Company Demand Response Roadmap Project  

E-Print Network [OSTI]

of control. Water heater demand response options are notcurrent water heater and air conditioning demand responsecustomer response Demand response water heater participation

Levy, Roger

2014-01-01T23:59:59.000Z

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

Hawaiian Electric Company Demand Response Roadmap Project  

E-Print Network [OSTI]

Like HECO actual utility demand response implementations canindustry-wide utility demand response applications tend toobjective. Figure 4. Demand Response Objectives 17

Levy, Roger

2014-01-01T23:59:59.000Z

22

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

23

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.

24

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

25

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

26

California Energy Demand Scenario Projections to 2050  

E-Print Network [OSTI]

Vehicle Conventional and Alternative Fuel Response Simulatormodified to include alternative fuel demand scenarios (whichvehicle adoption and alternative fuel demand) later in the

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

2008-01-01T23:59:59.000Z

27

Date: June 12, 2007 To: Pacific Northwest Demand Response Project  

E-Print Network [OSTI]

Date: June 12, 2007 To: Pacific Northwest Demand Response Project From: Rich Sedano/RAP and Chuck, 2007 meeting of the Pacific Northwest Demand Response Project, we agreed to form three Working Groups for the evaluation of cost-effectiveness of Demand Response resources. One potential outcome would be for state

28

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)

29

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

30

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.

31

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

32

Assisting Mexico in Developing Energy Supply and Demand Projections | Open  

Open Energy Info (EERE)

Assisting Mexico in Developing Energy Supply and Demand Projections Assisting Mexico in Developing Energy Supply and Demand Projections Jump to: navigation, search Name Assisting Mexico in Developing Energy Supply and Demand Projections Agency/Company /Organization Argonne National Laboratory Sector Energy Topics GHG inventory, Background analysis Resource Type Software/modeling tools Website http://www.dis.anl.gov/news/Me Country Mexico UN Region Latin America and the Caribbean References Assisting Mexico in Developing Energy Supply and Demand Projections[1] "CEEESA and the team of experts from Mexico analyzed the country's entire energy supply and demand system using CEEESA's latest version of the popular ENPEP-BALANCE software. The team developed a system representation, a so-called energy network, using ENPEP's powerful graphical user

33

Project Execution Plan Review Module (RM)  

Broader source: Energy.gov [DOE]

The Project Execution Plan (PEP) Review Module (RM) is a tool that assists DOE federal project review teams in evaluating the adequacy of the PEP development and maintenance for projects of any...

34

Airline Pilot Demand Projections What this is-  

E-Print Network [OSTI]

sources of fleet projections Utilized Boeing Fleet assumptions to try and fill in Gaps (1.4% annual fleet growth) Aircraft Orders 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 Boeing 737 Max 8/9 0 0 0 0 1 7 7 7 7 7 Boeing 737 700 0 0 0 0 0 0 0 0 0 0 Boeing 737 800 0 0 0 0 0 0 0 0 0 0 Boeing 737 900 9 6 6 6

Bustamante, Fabián E.

35

Module Title: Project Module Code: OPTO6005  

E-Print Network [OSTI]

Ibsen, Dr Ping Hua, Prof James Wilkinson Contact (email ID) sm@orc.soton.ac.uk, mi@orc.soton.ac.uk, ph2@orc.soton.ac.uk, jsw@orc.soton.ac.uk Is the module subject to external accreditation? No If yes and optical labs of the ORC 3. Train in technical and hands-on research skills to gain technical insight

Anderson, Jim

36

Energy Demand Modelling Introduction to the PhD project  

E-Print Network [OSTI]

Energy Demand Modelling Introduction to the PhD project Erika Zvingilaite Risø DTU System Analysis for optimization of energy systems Environmental effects Global externalities cost of CO2 Future scenarios for the Nordic energy systems 2010, 2020, 2030, 2040, 2050 (energy-production, consumption, emissions, net costs

37

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

38

Automated Demand Response Technology Demonstration Project for Small and  

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

Technology Demonstration Project for Small and Technology Demonstration Project for Small and Medium Commercial Buildings Title Automated Demand Response Technology Demonstration Project for Small and Medium Commercial Buildings Publication Type Report LBNL Report Number LBNL-4982E Year of Publication 2011 Authors Page, Janie, Sila Kiliccote, Junqiao Han Dudley, Mary Ann Piette, Albert K. Chiu, Bashar Kellow, Edward Koch, and Paul Lipkin Date Published 07/2011 Publisher CEC/LBNL Keywords demand response, emerging technologies, market sectors, medium commercial business, openadr, small commercial, small commercial business, technologies Abstract Small and medium commercial customers in California make up about 20-25% of electric peak load in California. With the roll out of smart meters to this customer group, which enable granular measurement of electricity consumption, the investor-owned utilities will offer dynamic prices as default tariffs by the end of 2011. Pacific Gas and Electric Company, which successfully deployed Automated Demand Response (AutoDR) Programs to its large commercial and industrial customers, started investigating the same infrastructures application to the small and medium commercial customers. This project aims to identify available technologies suitable for automating demand response for small-medium commercial buildings; to validate the extent to which that technology does what it claims to be able to do; and determine the extent to which customers find the technology useful for DR purpose. Ten sites, enabled by eight vendors, participated in at least four test AutoDR events per site in the summer of 2010. The results showed that while existing technology can reliably receive OpenADR signals and translate them into pre-programmed response strategies, it is likely that better levels of load sheds could be obtained than what is reported here if better understanding of the building systems were developed and the DR response strategies had been carefully designed and optimized for each site.

39

Math 115 Excel Group Project 3 Worksheet Price Elasticity of Demand: U.S. Demand for Gasoline  

E-Print Network [OSTI]

Math 115 Excel Group Project 3 Worksheet Price Elasticity of Demand: U.S. Demand for Gasoline 1 for Gasoline 2 4. Consider the two price-demand graphs below. The labels give the x-value. Which graph for Gasoline 3 6. Jewelry This quote is from the article "Americans Snap Up Gold Jewelry as Metal's Price Sinks

Newberger, Florence

40

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

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


41

EIA-Assumptions to the Annual Energy Outlook - 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.

42

Demand response medium sized industry consumers (Smart Grid Project) | Open  

Open Energy Info (EERE)

response medium sized industry consumers (Smart Grid Project) response medium sized industry consumers (Smart Grid Project) Jump to: navigation, search Project Name Demand response medium sized industry consumers Country Denmark Headquarters Location Aarhus, Denmark Coordinates 56.162937°, 10.203921° 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":56.162937,"lon":10.203921,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

43

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

44

Northwest Open Automated Demand Response Technology Demonstration Project  

SciTech Connect (OSTI)

The Lawrence Berkeley National Laboratory (LBNL) Demand Response Research Center (DRRC) demonstrated and evaluated open automated demand response (OpenADR) communication infrastructure to reduce winter morning and summer afternoon peak electricity demand in commercial buildings the Seattle area. LBNL performed this demonstration for the Bonneville Power Administration (BPA) in the Seattle City Light (SCL) service territory at five sites: Seattle Municipal Tower, Seattle University, McKinstry, and two Target stores. This report describes the process and results of the demonstration. OpenADR is an information exchange model that uses a client-server architecture to automate demand-response (DR) programs. These field tests evaluated the feasibility of deploying fully automated DR during both winter and summer peak periods. DR savings were evaluated for several building systems and control strategies. This project studied DR during hot summer afternoons and cold winter mornings, both periods when electricity demand is typically high. This is the DRRC project team's first experience using automation for year-round DR resources and evaluating the flexibility of commercial buildings end-use loads to participate in DR in dual-peaking climates. The lessons learned contribute to understanding end-use loads that are suitable for dispatch at different times of the year. The project was funded by BPA and SCL. BPA is a U.S. Department of Energy agency headquartered in Portland, Oregon and serving the Pacific Northwest. BPA operates an electricity transmission system and markets wholesale electrical power at cost from federal dams, one non-federal nuclear plant, and other non-federal hydroelectric and wind energy generation facilities. Created by the citizens of Seattle in 1902, SCL is the second-largest municipal utility in America. SCL purchases approximately 40% of its electricity and the majority of its transmission from BPA through a preference contract. SCL also provides ancillary services within its own balancing authority. The relationship between BPA and SCL creates a unique opportunity to create DR programs that address both BPA's and SCL's markets simultaneously. Although simultaneously addressing both market could significantly increase the value of DR programs for BPA, SCL, and the end user, establishing program parameters that maximize this value is challenging because of complex contractual arrangements and the absence of a central Independent System Operator or Regional Transmission Organization in the northwest.

Kiliccote, Sila; Piette, Mary Ann; Dudley, Junqiao

2010-03-17T23:59:59.000Z

45

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

SciTech Connect (OSTI)

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

46

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

SciTech Connect (OSTI)

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

1994-08-01T23:59:59.000Z

47

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.

48

ADB-Methods and Tools for Energy Demand Projection | Open Energy  

Open Energy Info (EERE)

ADB-Methods and Tools for Energy Demand Projection ADB-Methods and Tools for Energy Demand Projection Jump to: navigation, search Tool Summary Name: Methods and Tools for Energy Demand Projection Agency/Company /Organization: Asian Development Bank Sector: Energy Topics: Pathways analysis Resource Type: Presentation, Software/modeling tools Website: cdm-mongolia.com/files/2_Methods_Hoseok_16May2010.pdf Cost: Free Methods and Tools for Energy Demand Projection Screenshot References: Methods and Tools for Energy Demand Projection[1] This article is a stub. You can help OpenEI by expanding it. References ↑ "Methods and Tools for Energy Demand Projection" Retrieved from "http://en.openei.org/w/index.php?title=ADB-Methods_and_Tools_for_Energy_Demand_Projection&oldid=398945" Categories:

49

Projecting household energy consumption within a conditional demand framework  

SciTech Connect (OSTI)

Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

Teotia, A.; Poyer, D.

1991-12-31T23:59:59.000Z

50

Projecting household energy consumption within a conditional demand framework  

SciTech Connect (OSTI)

Few models attempt to assess and project household energy consumption and expenditure by taking into account differential household choices correlated with such variables as race, ethnicity, income, and geographic location. The Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory (ANL) for the US Department of Energy (DOE), provides a framework to forecast the energy consumption and expenditure of majority, black, Hispanic, poor, and nonpoor households. Among other variables, household energy demand for each of these population groups in MEAM is affected by housing factors (such as home age, home ownership, home type, type of heating fuel, and installed central air conditioning unit), demographic factors (such as household members and urban/rural location), and climate factors (such as heating degree days and cooling degree days). The welfare implications of the revealed consumption patterns by households are also forecast. The paper provides an overview of the model methodology and its application in projecting household energy consumption under alternative energy scenarios developed by Data Resources, Inc., (DRI).

Teotia, A.; Poyer, D.

1991-01-01T23:59:59.000Z

51

Name of Module: Next Generation Network Project 2  

E-Print Network [OSTI]

) 30 Total 270 8. Module Examination and Grading Procedures The project will be examined at the beginning of the module. 11. Enrolment Procedures To participate to the lectures/seminars/projectsName of Module: Next Generation Network ­ Project 2 CP (ECTS): 9 Short Name: MINF-KS-AV/PJ2.W12

Wichmann, Felix

52

Name of Module: Next Generation Network Project 1  

E-Print Network [OSTI]

) 30 Total 270 8. Module Examination and Grading Procedures The project will be examined at the beginning of the module. 11. Enrolment Procedures To participate to the lectures/seminars/projectsName of Module: Next Generation Network ­ Project 1 CP (ECTS): 9 Short Name: MINF-KS-AV/PJ1.W12

Wichmann, Felix

53

ELECTRICITY DEMAND AND SUPPLY PROJECTIONS IN IEA WORLD ENERGY SCENARIOS: HOW MUCH, HOW CLEAN?  

Science Journals Connector (OSTI)

Abstract (40-Word Limit): The presentation will highlight and discuss projections for electricity demand up to 2050 based on the recent publication Energy Technology Perspectives 2012:...

Frankl, Paolo

54

Projective module description of embedded noncommutative spaces  

E-Print Network [OSTI]

An algebraic formulation is given for the embedded noncommutative spaces over the Moyal algebra developed in a geometric framework in \\cite{CTZZ}. We explicitly construct the projective modules corresponding to the tangent bundles of the embedded noncommutative spaces, and recover from this algebraic formulation the metric, Levi-Civita connection and related curvatures, which were introduced geometrically in \\cite{CTZZ}. Transformation rules for connections and curvatures under general coordinate changes are given. A bar involution on the Moyal algebra is discovered, and its consequences on the noncommutative differential geometry are described.

R. B. Zhang; Xiao Zhang

2008-10-14T23:59:59.000Z

55

Pacific Northwest Demand Response Project Lee Hall, BPA Smart Grid Program Manager  

E-Print Network [OSTI]

Pacific Northwest Demand Response Project Lee Hall, BPA Smart Grid Program Manager February 14 utilities to invest in DR Regional situational analysis � issues to address #12;Nationally � Demand ResponseSource: FERC Demand Response & Advanced Metering Report, February 2011 Peak DR 65,000 MW 1,062 MW Peak DR

56

Power System Equipment Module Test Project  

SciTech Connect (OSTI)

The technology of electric power generation when applying the binary process to hydrothermal resources had not yet been demonstrated in the United States. Accordingly, on November 10, 1977, the Electric Power Research Institute and the Department of Energy, acting through the Lawrence Berkeley Laboratory, agreed to cofund the Power System Equipment Module Test Project. The Power System Equipment Module Test Project consisted of a field test program to accomplish the objectives listed below while heating hydrocarbon fluids to above their critical points, expanding these fluids, and subsequently, condensing them below their critical points: (1) Verify the performance of state-of-the-art heat exchangers in geothermal service; (2) Verify the heat exchangers' performance heating either selected pure light hydrocarbons or selected mixtures of light hydrocarbons in the vicinity of their respective critical pressures and temperatures; (3) Establish overall heat transfer coefficients that might be used for design of commercial-size geothermal power plants using the same geothermal brine and light hydrocarbon working fluids; (4) Perform and investigate the above under representative fluid operating conditions during which the production wells would be pumped. The project was accomplished by diverting approximately 200 gpm of the flow from one of Magma Power Company's geothermal wells in the East Mesa Geothermal Field. After the heat was removed from the geothermal brine flow, the cooled flow was returned to Magma Power Company and recombined with the main brine stream for disposal by reinjection. Approximately five thermal megawatts was transferred from geothermal brine to hydrocarbon working fluids in a closed system. This heat was removed from the working fluids in a condenser and subsequently rejected to the environment by a wet cooling tower. The thermodynamic performance of both the working fluids and the system components was measured during the test program to achieve the project's objectives.

Schilling, J.R.

1980-12-01T23:59:59.000Z

57

Project Information Form Project Title White Paper on the Future of Passenger Travel Demand in the United  

E-Print Network [OSTI]

each agency or organization) Caltrans $26,383 Total Project Cost $26,383 Agency ID or Contract NumberProject Information Form Project Title White Paper on the Future of Passenger Travel Demand DTRT13-G-UTC29 Start and End Dates September 2014 to June 2015 Brief Description of Research Project

California at Davis, University of

58

Project Information Form Project Title White Paper on the Future of Passenger Travel Demand in the United  

E-Print Network [OSTI]

each agency or organization) DOT $26,383.66 Total Project Cost $26,383.66 Agency ID or Contract NumberProject Information Form Project Title White Paper on the Future of Passenger Travel Demand Project This white paper will summarize recent research findings pertaining to future passenger travel

California at Davis, University of

59

Project Information Form Project Title White Paper on the Effectiveness of Land Use and Demand Strategies in  

E-Print Network [OSTI]

DOT $12,000 Cal Trans Total Project Cost $42,533 Agency ID or Contract Number DTRT13-G-UTC29 StartProject Information Form Project Title White Paper on the Effectiveness of Land Use and Demand and End Dates June 30, 2014 to January 30, 2015 Brief Description of Research Project Reducing vehicle

California at Davis, University of

60

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

SciTech Connect (OSTI)

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

NONE

1998-01-01T23:59:59.000Z

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

Electricity demand and supply projections for Indian economy  

Science Journals Connector (OSTI)

The present paper deals with an econometric model to forecast future electricity requirements for various sectors of Indian economy. Following the analysis of time series of sectoral GDPs, number of consumers in various sectors and price indices of electricity, a logarithmic linear regression model has been developed to forecast long-term demand of electricity up to the year 2045. Using the historical GDP growth in various sectors and the corresponding electricity consumption for the period 1971-2005, it is predicted that the total electricity demand will be 5000 billion kWh, against a supply of 1500 billion kWh in the year 2045. This may lead to a disastrous situation for the country unless drastic policy measures are taken to improve the supply side as well as to reduce demand.

Subhash Mallah; N.K. Bansal

2009-01-01T23:59:59.000Z

62

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network [OSTI]

Power Administration (BPA) in the Seattle City Light (SCL)times of the year. The project was funded by BPA and SCL.BPA is a U.S. Department of Energy agency headquartered in

Kiliccote, Sila

2010-01-01T23:59:59.000Z

63

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network [OSTI]

Bonneville Power Administration (BPA) in Seattle City Lightproject was funded by BPA and SCL. This report summarizesPower Administration (BPA) and Seattle City Light (SCL) DR

Kiliccote, Sila

2010-01-01T23:59:59.000Z

64

Energy Management Using Storage Batteries in Large Commercial Facilities Based on Projection of Power Demand  

Science Journals Connector (OSTI)

This study provides three methods for projection of power demand of large commercial facilities planned for construction, ... the operation algorithm of storage batteries to manage energy and minimize power costs...

Kentaro Kaji; Jing Zhang; Kenji Tanaka

2013-01-01T23:59:59.000Z

65

Automation systems for Demand Response, ForskEL (Smart Grid Project) | Open  

Open Energy Info (EERE)

systems for Demand Response, ForskEL (Smart Grid Project) systems for Demand Response, ForskEL (Smart Grid Project) Jump to: navigation, search Project Name Automation systems for Demand Response, ForskEL Country Denmark Coordinates 56.26392°, 9.501785° 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":56.26392,"lon":9.501785,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

66

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

SciTech Connect (OSTI)

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) 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 requirement of the Energy Information Administration (EIA) to provide adequate documentation in support of its models. 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. The NEMS Industrial Demand Model is a dynamic accounting model, bringing together the disparate industries and uses of energy in those industries, and putting them together in an understandable and cohesive framework. The Industrial Model generates mid-term (up to the year 2015) forecasts of industrial sector energy demand as a component of the NEMS integrated forecasting system. From the NEMS system, the Industrial Model receives fuel prices, employment data, and the value of industrial output. Based on the values of these variables, the Industrial Model passes back to the NEMS system estimates of consumption by fuel types.

NONE

1997-01-01T23:59:59.000Z

67

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

SciTech Connect (OSTI)

This report documents the objectives, analytical approach, and development of the National Energy Modeling System (NEMS) 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

Flexible system development strategies for the Chuo Shinkansen Maglev Project : dealing with uncertain demand and R&D outcomes  

E-Print Network [OSTI]

As a large-scale, long-term transportation project, the Chuo Shinkansen Maglev Project in Japan includes various uncertainties. Among them, two major uncertainties are identified in this thesis: the uncertainty of demand ...

Ishii, Masaki, S.M. Massachusetts Institute of Technology

2007-01-01T23:59:59.000Z

69

Projections up for total energy demand by IEA nations in 1990  

SciTech Connect (OSTI)

The author reviews the most recent IEA projections for energy demand to the year 2000 in IEA countries. These show that the expectations for 1990 are now higher than estimates made last year. Production of solid fuels is expected to increase from 814 million toe in 1983 to 1044 million toe in 1990 and 1345 million toe by 2000. Nearly all the increase is expected in the US, Canada and Australia.

Vielvoye, R.

1985-06-17T23:59:59.000Z

70

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

E-Print Network [OSTI]

2010AssessmentofDemandResponseand AdvancedMetering:DevelopmentforDemandResponse Calculation?FindingsandEnergy Efficiencyand DemandResponsewithCommunicating

Page, Janie

2012-01-01T23:59:59.000Z

71

Low Dose Ionizing Radiation Modulates Immune Function New Project Overview  

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

Modulates Immune Function New Project Overview Modulates Immune Function New Project Overview Gregory Nelson Loma Linda University Abstract The immune system provides the first line of defense for exposures to environmental hazards. Protective immunity mechanisms using innate or adaptive responses are employed to mitigate acute challenges or amplify the readiness of the system to respond to future challenges. Some stimuli lead to amplified inflammatory reactions such as delayed hypersensitivity which is required for immunity to parasites and can also lead to adverse consequences such as contact dermatitis. Radiation exposure has the potential to aggravate hypersensitivity reactions as well as to suppress protective immunity. Ionizing radiation at high doses has long been recognized as highly effective in destroying cells of the immune system,

72

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.

73

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,

74

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

75

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

76

Final Report on DOE Project entitled Dynamic Optimized Advanced Scheduling of Bandwidth Demands for Large-Scale Science Applications  

SciTech Connect (OSTI)

In this project, developed scheduling frameworks for dynamic bandwidth demands for large-scale science applications. In particular, we developed scheduling algorithms for dynamic bandwidth demands in this project. Apart from theoretical approaches such as Integer Linear Programming, Tabu Search and Genetic Algorithm heuristics, we have utilized practical data from ESnet OSCARS project (from our DOE lab partners) to conduct realistic simulations of our approaches. We have disseminated our work through conference paper presentations and journal papers and a book chapter. In this project we addressed the problem of scheduling of lightpaths over optical wavelength division multiplexed (WDM) networks. We published several conference papers and journal papers on this topic. We also addressed the problems of joint allocation of computing, storage and networking resources in Grid/Cloud networks and proposed energy-efficient mechanisms for operatin optical WDM networks.

Ramamurthy, Byravamurthy [University of Nebraska-Lincoln

2014-05-05T23:59:59.000Z

77

Projection of Chinese motor vehicle growth, oil demand, and CO{sub 2}emissions through 2050.  

SciTech Connect (OSTI)

As the vehicle population in China increases, oil consumption and carbon dioxide (CO{sub 2}) emissions associated with on-road transportation are rising dramatically. During this study, we developed a methodology to project trends in the growth of the vehicle population, oil demand, and CO{sub 2} emissions associated with on-road transportation in China. By using this methodology, we projected--separately--the number of highway vehicles, motorcycles, and rural vehicles in China through 2050. We used three scenarios of highway vehicle growth (high-, mid-, and low-growth) to reflect patterns of motor vehicle growth that have occurred in different parts of the world (i.e., Europe and Asia). All are essentially business-as-usual scenarios in that almost none of the countries we examined has made concerted efforts to manage vehicle growth or to offer serious alternative transportation means to satisfy people's mobility needs. With this caveat, our projections showed that by 2030, China could have more highway vehicles than the United States has today, and by 2035, it could have the largest number of highway vehicles in the world. By 2050, China could have 486-662 million highway vehicles, 44 million motorcycles, and 28 million rural vehicles. These numbers, which assume essentially unmanaged vehicle growth, would result in potentially disastrous effects on the urban infrastructure, resources, and other social and ecological aspects of life in China. We designed three fuel economy scenarios, from conservative to aggressive, on the basis of current policy efforts and expectations of near-future policies in China and in developed countries. It should be noted that these current and near-future policies have not taken into consideration the significant potential for further fuel economy improvements offered by advanced technologies such as electric drive technologies (e.g., hybrid electric vehicles and fuel-cell vehicles). By using vehicle growth projections and potential vehicle fuel economy, we projected that China's on-road vehicles could consume approximately 614-1016 million metric tons of oil per year (12.4-20.6 million barrels per day) and could emit 1.9-3.2 billion metric tons of CO{sub 2} per year in 2050, which will put tremendous pressure on the balance of the Chinese and world oil supply and demand and could have significant implications on climate change. Our analysis shows that, while improvements in vehicle fuel economy are crucial for reducing transportation energy use, containing the growth of the vehicle population could have an even more profound effect on oil use and CO{sub 2} emissions. This benefit is in addition to other societal and environmental benefits--such as reduced congestion, land use, and urban air pollution--that will result from containing vehicle population growth. Developing public transportation systems for personal travel and rail and other modes for freight transportation will be important for containing the growth of motor vehicles in China. Although the population of passenger cars will far exceed that of all truck types in China in the future, our analysis shows that oil use by and CO{sub 2} emissions from the Chinese truck fleet will be far larger than those related to Chinese passenger cars because trucks are very use intensive (more vehicle miles traveled per year) and energy intensive (lower fuel economy). Unfortunately, the potential for improving fuel economy and reducing air pollutant emissions for trucks has not been fully explored; such efforts are needed. Considering the rapid depletion of the world's oil reserve, the heightened global interest in addressing greenhouse gas emissions, and the geopolitical complications of global oil supply and demand, the study results suggest that unmanaged vehicle growth and limited improvements in vehicle fuel efficiency will lead to an unsustainable and unstable transportation system in China. In other words, while our projections do not definitively indicate what will happen in the Chinese transportation sector by 2050, they do demonstrate

Wang, M.; Huo, H.; Johnson, L.; He, D.

2006-12-20T23:59:59.000Z

78

Projection of Chinese motor vehicle growth, oil demand, and Co{sub 2} emissions through 2050.  

SciTech Connect (OSTI)

As the vehicle population in China increases, oil consumption and carbon dioxide (CO{sub 2}) emissions associated with on-road transportation are rising dramatically. During this study, we developed a methodology to project trends in the growth of the vehicle population, oil demand, and CO{sub 2} emissions associated with on-road transportation in China. By using this methodology, we projected separately the number of highway vehicles, motorcycles, and rural vehicles in China through 2050. We used three scenarios of highway vehicle growth (high-, mid-, and low-growth) to reflect patterns of motor vehicle growth that have occurred in different parts of the world (i.e., Europe and Asia). All are essentially business-as-usual scenarios in that almost none of the countries we examined has made concerted efforts to manage vehicle growth or to offer serious alternative transportation means to satisfy people's mobility needs. With this caveat, our projections showed that by 2030, China could have more highway vehicles than the United States has today, and by 2035, it could have the largest number of highway vehicles in the world. By 2050, China could have 486-662 million highway vehicles, 44 million motorcycles, and 28 million rural vehicles. These numbers, which assume essentially unmanaged vehicle growth, would result in potentially disastrous effects on the urban infrastructure, resources, and other social and ecological aspects of life in China. We designed three fuel economy scenarios, from conservative to aggressive, on the basis of current policy efforts and expectations of near-future policies in China and in developed countries. It should be noted that these current and near-future policies have not taken into consideration the significant potential for further fuel economy improvements offered by advanced technologies such as electric drive technologies (e.g., hybrid electric vehicles and fuel-cell vehicles). By using vehicle growth projections and potential vehicle fuel economy, we projected that China's on-road vehicles could consume approximately 614-1016 million metric tons of oil per year (12.4-20.6 million barrels per day) and could emit 1.9-3.2 billion metric tons of CO{sub 2} per year in 2050, which will put tremendous pressure on the balance of the Chinese and world oil supply and demand and could have significant implications on climate change. Our analysis shows that, while improvements in vehicle fuel economy are crucial for reducing transportation energy use, containing the growth of the vehicle population could have an even more profound effect on oil use and CO{sub 2} emissions. This benefit is in addition to other societal and environmental benefits--such as reduced congestion, land use, and urban air pollution--that will result from containing vehicle population growth. Developing public transportation systems for personal travel and rail and other modes for freight transportation will be important for containing the growth of motor vehicles in China. Although the population of passenger cars will far exceed that of all truck types in China in the future, our analysis shows that oil use by and CO{sub 2} emissions from the Chinese truck fleet will be far larger than those related to Chinese passenger cars because trucks are very use intensive (more vehicle miles traveled per year) and energy intensive (lower fuel economy). Unfortunately, the potential for improving fuel economy and reducing air pollutant emissions for trucks has not been fully explored; such efforts are needed. Considering the rapid depletion of the world's oil reserve, the heightened global interest in addressing greenhouse gas emissions, and the geopolitical complications of global oil supply and demand, the study results suggest that unmanaged vehicle growth and limited improvements in vehicle fuel efficiency will lead to an unsustainable and unstable transportation system in China. In other words, while our projections do not definitively indicate what will happen in the Chinese transportation sector by 2050, they do demonstrate th

Huo, H.; Wang, M.; Johnson, L.; He, D.; Energy Systems; Energy Foundation

2007-01-01T23:59:59.000Z

79

DOE special projects: PLACE3S GIS MODULE [Final report  

SciTech Connect (OSTI)

PLACE3S (PLAnning for Community Energy, Economic and Environmental Sustainability) energy option matching module.

NONE

2002-07-31T23:59:59.000Z

80

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.

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

Projections of highway vehicle population, energy demand, and CO{sub 2} emissions in India through 2040.  

SciTech Connect (OSTI)

This paper presents projections of motor vehicles, oil demand, and carbon dioxide (CO{sub 2}) emissions for India through the year 2040. The populations of highway vehicles and two-wheelers are projected under three different scenarios on the basis of economic growth and average household size in India. The results show that by 2040, the number of highway vehicles in India would be 206-309 million. The oil demand projections for the Indian transportation sector are based on a set of nine scenarios arising out of three vehicle-growth and three fuel-economy scenarios. The combined effects of vehicle-growth and fuel-economy scenarios, together with the change in annual vehicle usage, result in a projected demand in 2040 by the transportation sector in India of 404-719 million metric tons (8.5-15.1 million barrels per day). The corresponding annual CO{sub 2} emissions are projected to be 1.2-2.2 billion metric tons.

Arora, S.; Vyas, A.; Johnson, L.; Energy Systems

2011-02-22T23:59:59.000Z

82

Using Compressed Air Efficiency Projects to Reduce Peak Industrial Electric Demands: Lessons Learned  

E-Print Network [OSTI]

"To help customers respond to the wildly fluctuating energy markets in California, Pacific Gas & Electric (PG&E) initiated an emergency electric demand reduction program in October 2000 to cut electric use during peak periods. One component...

Skelton, J.

83

Annual Energy Outlook with Projections to 2025  

Gasoline and Diesel Fuel Update (EIA)

Assumptions to the nnual Energy Outlook Assumptions to the nnual Energy Outlook EIA Glossary Assumptions to the Annual Energy Outlook 2004 Report #: DOE/EIA-0554(2004) Release date: February 2004 Next release date:February 2005 The Assumptions to the Annual Energy Outlook presents the major assumptions of the National Energy Modeling System (NEMS) used to generate the projections in the Annual Energy Outlook. Table of Contents Introduction Macroeconomic Activity Module International Energy Module Household Expenditures Module Residential Demand Module Commercial Demand Module Industrial Demand Module Transportation Demand Module Electricity Market Module Oil and Gas Supply Module Natural Gas Transmission and Distribution Module Petroleum Market Module Coal Market Module Renewable Fuels Module Appendix A Adobe Acrobat Logo

84

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

85

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

86

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].

87

Project Profile: Sensible Heat, Direct, Dual-Media Thermal Energy Storage Module  

Broader source: Energy.gov [DOE]

Acciona Solar, under the Thermal Storage FOA, plans to develop a prototype thermal energy storage (TES) module with high efficiency. This project is looking at a packed or structured bed TES tank with molten salt flowing through it.

88

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

SciTech Connect (OSTI)

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

89

Impact of the demand-side management (DSM) Program structure on the cost-effectiveness of energy efficiency projects  

SciTech Connect (OSTI)

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 DMS 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.

1995-06-01T23:59:59.000Z

90

Influence of Attic Radiant Barrier Systems on Air Conditioning Demand in an Utility Pilot Project  

E-Print Network [OSTI]

by Oak Ridge National Laboratory showed space heating reductions in Miami, Orlando and Atlanta (Wilkes, 1991). Also, detailed measurements by ORNL showed heating demand and energy reductions in monitored Tennessee homes (Levins and Karnitz, 1987...- 11 and R-30 Insulation, ORNL/CON-226, Oak Ridge National Laboratories, Oak Ridge, TN. Levins, W. P. and Karnitz, M. A. and Hall, J.A., 1990. Cooling Season Energy Measurements of Dust and Ventilation Effects on Radiant Barriers, ORNL/CON-271...

Parker, D. S.; Sherwin, J. R.

2002-01-01T23:59:59.000Z

91

Residential Demand Module  

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

for EIA (SENTECH Incorporated, 2010). Wind: The Cost and Performance of Distributed Wind Turbines, 2010-35 (ICF International, 2010). 33 U.S. Energy Information Administration |...

92

Chapter 10, Peak Demand and Time-Differentiated Energy Savings Cross-Cutting Protocols: The Uniform Methods Project: Methods for Determining Energy Efficiency Savings for Specific Measures  

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

0: Peak Demand and 0: Peak Demand and Time-Differentiated Energy Savings Cross-Cutting Protocols Frank Stern, Navigant Consulting Subcontract Report NREL/SR-7A30-53827 April 2013 The Uniform Methods Project: Methods for Determining Energy Efficiency Savings for Specific Measures 10 - 1 Chapter 10 - Table of Contents 1 Introduction .............................................................................................................................2 2 Purpose of Peak Demand and Time-differentiated Energy Savings .......................................3 3 Key Concepts ..........................................................................................................................5 4 Methods of Determining Peak Demand and Time-Differentiated Energy Impacts ...............7

93

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

94

Advanced Demand Responsive Lighting  

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

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

Design, Implementation, and Formal Verification of On-demand Connection Establishment Scheme for TCP Module of MPICH2 Library  

E-Print Network [OSTI]

developed at Argonne National Laboratory. The scalability of MPI implementations is very important for building high performance parallel computing applications. The initial TCP (Transmission Control Protocol) network module developed for Nemesis...

Muthukrishnan, Sankara Subbiah

2012-10-19T23:59:59.000Z

97

Minutes of February 14, 2013 meeting of the Pacific Northwest Demand Response Project (PNDRP) Presentations are linked in the meeting agenda at www.nwcouncil.org/energy/dr/meetings/2013_02/  

E-Print Network [OSTI]

1 Minutes of February 14, 2013 meeting of the Pacific Northwest Demand Response Project (PNDRP be working on demand response issues but in other areas including wind integration, the development PGE's treatment of demand response in their integrated resource plan (www.nwcouncil.org/media/4476948

98

Building Technologies Office: Integrated Predictive Demand Response  

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

99

Approved Module Information for EE2EDP, 2014/5 Module Title/Name: Electronics Design Project Module Code: EE2EDP  

E-Print Network [OSTI]

Code: EE2EDP School: Engineering and Applied Science Module Type: Standard Module New Module? No Module Engineering Systems. BEng Electrical and Electronic Engineering. BEng Electronic Engineering and Computer competition among the groups to produce a 'best' system. * Students will be required to use creativity

Neirotti, Juan Pablo

100

Demand Reduction  

Broader source: Energy.gov [DOE]

Grantees may use funds to coordinate with electricity supply companies and utilities to reduce energy demands on their power systems. These demand reduction programs are usually coordinated through...

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

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

103

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

104

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

105

World Energy Use Trends in Demand  

Science Journals Connector (OSTI)

In order to provide adequate energy supplies in the future, trends in energy demand must be evaluated and projections of future demand developed. World energy use is far from static, and an understanding of the demand

Randy Hudson

1996-01-01T23:59:59.000Z

106

Assessment of Demand Response Resource  

E-Print Network [OSTI]

Assessment of Demand Response Resource Potentials for PGE and Pacific Power Prepared for: Portland January 15, 2004 K:\\Projects\\2003-53 (PGE,PC) Assess Demand Response\\Report\\Revised Report_011504.doc #12;#12;quantec Assessment of Demand Response Resource Potentials for I-1 PGE and Pacific Power I. Introduction

107

Energy demand  

Science Journals Connector (OSTI)

The basic forces pushing up energy demand are population increase and economic growth. From ... of these it is possible to estimate future energy requirements.

Geoffrey Greenhalgh

1980-01-01T23:59:59.000Z

108

Microsoft Word - APRIL 2009 PMCDP Module CHRIS ESS Tutorial_MAINTAIN_PROJECT_HISTORY.doc  

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

MAINTIN PROJECT HISTORY MAINTIN PROJECT HISTORY REV: APRIL 2009 1 1. To update your project history, click on the "PMCDP Menu" and choose "Maintain project history." Maintain Project History ESS Tutorial, Project Management Career Development Program MAINTIN PROJECT HISTORY REV: APRIL 2009 2 2. A screen with the header "PMCDP Profile for [Your Name]" will appear titled "Step 3: Maintain project history." Options: Delete: This will delete all information for the selected project as currently showing in the table. Update: This will bring you back to the original input screen for project information. View Description: This will bring up a text box that will allow you to see the description previously entered. Sort: Project history information is presented in date-order, with the most recent position

109

Energy Demand Staff Scientist  

E-Print Network [OSTI]

Energy Demand in China Lynn Price Staff Scientist February 2, 2010 #12;Founded in 1988 Focused on End-Use Energy Efficiency ~ 40 Current Projects in China Collaborations with ~50 Institutions in China Researcher #12;Talk OutlineTalk Outline · Overview · China's energy use and CO2 emission trends · Energy

Eisen, Michael

110

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

111

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

112

Western Interconnection Synchrophasor Project  

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

Project Western Interconnection Synchrophasor Project Resources & Links Demand Response Energy Efficiency Emerging Technologies Synchrophasor measurements are a type of...

113

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.

114

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

115

Basic Theory of Demand-Side Management  

Science Journals Connector (OSTI)

Demand-Side Management (DSM) is pivotal in Integrated Resource ... to realize sustainable development, and advanced energy management activity. A project can be implemented only...

Zhaoguang Hu; Xinyang Han; Quan Wen

2013-01-01T23:59:59.000Z

116

Demand response at the Naval Postgraduate School .  

E-Print Network [OSTI]

??The purpose of this MBA project is to assist the Naval Postgraduate School's Public Works department to assimilate into a Demand Response program that will (more)

Stouffer, Dean

2008-01-01T23:59:59.000Z

117

Microsoft PowerPoint - Project DE_FE0000032 Student Modules.pptx  

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

and and Research and Research 2011 Yearly Review Meeting P j t DE FE0002111 Project DE-FE0002111 Title: A Modular Curriculum for Training University Students in Industry Standard CO2 Sequestration and Enhanced Oil Recovery q y Methodologies University of Texas of the Permian Basin y Presenter: Dr. Robert Trentham, Director Center for Energy and Economic Diversification February 23, 2011 Project Participants Project Participants * Dr Robert C. Trentham, Co-PI (Geology, CO2) , ( gy, ) * Dr Emily Stoudt, Co-PI (Geology) * Mr Robert Kiker (Production Engineering, Plant ) Visits) * Mr Steve Melzer (Reservoir Engineering, CO2) M T i M G i (L d M t) * Ms Teri McGuigan (Land Management) * Mr EMr. Emmanuel Ede, student * Ms Ibukun Bode (IBK)

118

Demand Response  

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

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

119

Demand Response and Open Automated Demand Response  

E-Print Network [OSTI]

LBNL-3047E Demand Response and Open Automated Demand Response Opportunities for Data Centers G described in this report was coordinated by the Demand Response Research Center and funded by the California. Demand Response and Open Automated Demand Response Opportunities for Data Centers. California Energy

120

Demand Response Resources in Pacific Northwest  

E-Print Network [OSTI]

Demand Response Resources in Pacific Northwest Chuck Goldman Lawrence Berkeley National Laboratory cagoldman@lbl.gov Pacific Northwest Demand Response Project Portland OR May 2, 2007 #12;Overview · Typology Annual Reports ­ Journal articles/Technical reports #12;Demand Response Resources · Incentive

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

Commercial & Industrial Demand Response  

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

Resources News & Events Expand News & Events Skip navigation links Smart Grid Demand Response Agricultural Residential Demand Response Commercial & Industrial Demand Response...

122

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

123

Demand Response Spinning Reserve Demonstration  

SciTech Connect (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

124

Electricity demand as frequency controlled reserves, ENS (Smart...  

Open Energy Info (EERE)

ENS (Smart Grid Project) Jump to: navigation, search Project Name Electricity demand as frequency controlled reserves, ENS Country Denmark Coordinates 56.26392, 9.501785...

125

Electricity demand as frequency controlled reserves, ForskEL...  

Open Energy Info (EERE)

ForskEL (Smart Grid Project) Jump to: navigation, search Project Name Electricity demand as frequency controlled reserves, ForskEL Country Denmark Coordinates 56.26392,...

126

TOB Module Assembly  

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

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

127

The National Energy Modeling System: An Overview 2000 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

coal market module (CMM) represents the mining, transportation, and pricing of coal, subject to end-use demand. Coal supplies are differentiated by heat and sulfur content. CMM also determines the minimum cost pattern of coal supply to meet exogenously defined U.S. coal export demands as a part of the world coal market. Coal supply is projected on a cost-minimizing basis, constrained by existing contracts. Twelve different coal types are differentiated with respect to thermal grade, sulfur content, and underground or surface mining. The domestic production and distribution of coal is forecast for 13 demand regions and 11 supply regions (Figures 19 and 20). coal market module (CMM) represents the mining, transportation, and pricing of coal, subject to end-use demand. Coal supplies are differentiated by heat and sulfur content. CMM also determines the minimum cost pattern of coal supply to meet exogenously defined U.S. coal export demands as a part of the world coal market. Coal supply is projected on a cost-minimizing basis, constrained by existing contracts. Twelve different coal types are differentiated with respect to thermal grade, sulfur content, and underground or surface mining. The domestic production and distribution of coal is forecast for 13 demand regions and 11 supply regions (Figures 19 and 20). Figure 19. Coal Market Module Demand Regions Figure 20. Coal Market Module Supply Regions

128

The Value of Computational Thinking across Grade Levels 9-12 Project VCTAL is developing a set of instructional modules and mini-modules for use in high  

E-Print Network [OSTI]

create Sample Module Questions · Is an electric car an economical choice? · Where should you install new whether it's time to buy an electric car by examining its cost to own and convenience to operate

129

The Integration of Energy Efficiency, Renewable Energy, Demand Response and Climate Change: Challenges and Opportunities for Evaluators and Planners  

E-Print Network [OSTI]

to inform projected energy and demand reductions in regionaldown to reflect energy and demand savings due to spillover (market and estimate the energy and demand savings associated

Vine, Edward

2007-01-01T23:59:59.000Z

130

Demand Response Research in Spain  

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

131

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

132

The Value of Computational Thinking across Grade Levels 9-12 Project VCTAL is developing a set of instructional modules and mini-modules for use in high  

E-Print Network [OSTI]

create Sample Module Questions · Is an electric car an economical choice? · Where should you install new explores whether it's time to buy an electric car by examining its cost to own and convenience to operate the cost of owning an electric car relative to a traditional hybrid or a gasoline-powered car. Students

133

Distributed Intelligent Automated Demand Response (DIADR) Building  

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

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,

134

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.

135

Addressing Energy Demand through Demand Response: International Experiences and Practices  

E-Print Network [OSTI]

Addressing Energy Demand through Demand Response:both the avoided energy costs (and demand charges) as wellCoordination of Energy Efficiency and Demand Response,

Shen, Bo

2013-01-01T23:59:59.000Z

136

Measurement and Verification for Demand Response  

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

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

137

Global Energy: Supply, Demand, Consequences, Opportunities  

SciTech Connect (OSTI)

July 29, 2008 Berkeley Lab lecture: Arun Majumdar, Director of the Environmental Energy Technologies Division, discusses current and future projections of economic growth, population, and global energy demand and supply, and explores the implications of these trends for the environment.

Arun Majumdar

2008-08-14T23:59:59.000Z

138

Global Energy: Supply, Demand, Consequences, Opportunities  

ScienceCinema (OSTI)

July 29, 2008 Berkeley Lab lecture: Arun Majumdar, Director of the Environmental Energy Technologies Division, discusses current and future projections of economic growth, population, and global energy demand and supply, and explores the implications of these trends for the environment.

Arun Majumdar

2010-01-08T23:59:59.000Z

139

Solar in Demand | Department of Energy  

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

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

140

Demand Response Valuation Frameworks Paper  

E-Print Network [OSTI]

benefits of Demand Side Management (DSM) are insufficient toefficiency, demand side management (DSM) cost effectivenessResearch Center Demand Side Management Demand Side Resources

Heffner, Grayson

2010-01-01T23:59:59.000Z

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

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).

142

Uranium 2009 resources, production and demand  

E-Print Network [OSTI]

With several countries currently building nuclear power plants and planning the construction of more to meet long-term increases in electricity demand, uranium resources, production and demand remain topics of notable interest. In response to the projected growth in demand for uranium and declining inventories, the uranium industry the first critical link in the fuel supply chain for nuclear reactors is boosting production and developing plans for further increases in the near future. Strong market conditions will, however, be necessary to trigger the investments required to meet projected demand. The "Red Book", jointly prepared by the OECD Nuclear Energy Agency and the International Atomic Energy Agency, is a recognised world reference on uranium. It is based on information compiled in 40 countries, including those that are major producers and consumers of uranium. This 23rd edition provides a comprehensive review of world uranium supply and demand as of 1 January 2009, as well as data on global ur...

Organisation for Economic Cooperation and Development. Paris

2010-01-01T23:59:59.000Z

143

Pacific Northwest Smart Grid Demonstration Project  

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

Project Western Interconnection Synchrophasor Project Resources & Links Demand Response Energy Efficiency Emerging Technologies BPA has joined 11 utilities, a major...

144

Mass Market Demand Response  

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

145

Demand Response Assessment INTRODUCTION  

E-Print Network [OSTI]

Demand Response Assessment INTRODUCTION This appendix provides more detail on some of the topics raised in Chapter 4, "Demand Response" of the body of the Plan. These topics include 1. The features, advantages and disadvantages of the main options for stimulating demand response (price mechanisms

146

Residential Energy Demand Reduction Analysis and Monitoring Platform - REDRAMP  

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

Dramatic Peak Residential Dramatic Peak Residential Demand Reduction in the Desert Southwest Yahia Baghzouz Center for Energy Research University of Nevada, Las Vegas Golden, CO Overview * Project description * Subdivision energy efficiency features * Home energy monitoring * Demand side management * Feeder loading * Battery Energy Storage System * Future Work Team Members Project Objective and Methodology * The main objective is to reduce peak power demand of a housing subdivision by 65% (compared to housing development that is built to conventional code). * This objective will be achieved by - Energy efficient home construction with roof- integrated PV system - Demand Side Management - Battery Energy Storage System Project schematic Diagram Project Physical Location: Las Vegas, NV Red Rock Hotel/Casino

147

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

148

Demand Activated Manufacturing Architecture  

SciTech Connect (OSTI)

Honeywell Federal Manufacturing & Technologies (FM&T) engineers John Zimmerman and Tom Bender directed separate projects within this CRADA. This Project Accomplishments Summary contains their reports independently. Zimmerman: In 1998 Honeywell FM&T partnered with the Demand Activated Manufacturing Architecture (DAMA) Cooperative Business Management Program to pilot the Supply Chain Integration Planning Prototype (SCIP). At the time, FM&T was developing an enterprise-wide supply chain management prototype called the Integrated Programmatic Scheduling System (IPSS) to improve the DOE's Nuclear Weapons Complex (NWC) supply chain. In the CRADA partnership, FM&T provided the IPSS technical and business infrastructure as a test bed for SCIP technology, and this would provide FM&T the opportunity to evaluate SCIP as the central schedule engine and decision support tool for IPSS. FM&T agreed to do the bulk of the work for piloting SCIP. In support of that aim, DAMA needed specific DOE Defense Programs opportunities to prove the value of its supply chain architecture and tools. In this partnership, FM&T teamed with Sandia National Labs (SNL), Division 6534, the other DAMA partner and developer of SCIP. FM&T tested SCIP in 1998 and 1999. Testing ended in 1999 when DAMA CRADA funding for FM&T ceased. Before entering the partnership, FM&T discovered that the DAMA SCIP technology had an array of applications in strategic, tactical, and operational planning and scheduling. At the time, FM&T planned to improve its supply chain performance by modernizing the NWC-wide planning and scheduling business processes and tools. The modernization took the form of a distributed client-server planning and scheduling system (IPSS) for planners and schedulers to use throughout the NWC on desktops through an off-the-shelf WEB browser. The planning and scheduling process within the NWC then, and today, is a labor-intensive paper-based method that plans and schedules more than 8,000 shipped parts per month based on more than 50 manually-created document types. The fact that DAMA and FM&T desired to move from paper-based manual architectures to digitally based computer architectures gave further incentive for the partnership to grow. FM&T's greatest strength was its knowledge of NWC-wide scheduling and planning with its role as the NWC leader in manufacturing logistics. DAMA's asset was its new knowledge gained in the research and development of advanced architectures and tools for supply chain management in the textiles industry. These complimentary strengths allowed the two parties to provide both the context and the tools for the pilot. Bender: Honeywell FM&T participated in a four-site supply chain project, also referred to as an Inter-Enterprise Pipeline Evaluation. The MSAD project was selected because it involves four NWC sites: FM&T, Pantex, Los Alamos National Laboratory (LANL), and Lawrence Livermore National Laboratory (LLNL). FM&T had previously participated with Los Alamos National Laboratory in FY98 to model a two-site supply chain project, between FM&T and LANL. Evaluation of a Supply Chain Methodology is a subset of the DAMA project for the AMTEX consortium. LANL organization TSA-7, Enterprise Modeling and Simulation, has been involved in AMTEX and DAMA through development of process models and simulations for LANL, the NWC, and others. The FY 1998 and this FY 1999 projects directly involved collaboration between Honeywell and the Enterprise Modeling and Simulation (TSA-7) and Detonation Science and Technology (DX1) organizations at LANL.

Bender, T.R.; Zimmerman, J.J.

2001-02-07T23:59:59.000Z

149

The National Energy Modeling System: An Overview 1998 - Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

COAL MARKET MODULE COAL MARKET MODULE blueball.gif (205 bytes) Coal Production Submodule blueball.gif (205 bytes) Coal Distribution Submodule blueball.gif (205 bytes) Coal Export Component The coal market module (CMM) represents the mining, transportation, and pricing of coal, subject to end-use demand. Coal supplies are differentiated by heat and sulfur content. The CMM also determines the minimum cost pattern of coal supply to meet exogenously defined U.S. coal export demands as a part of the world coal market. Coal supply is projected on a cost-minimizing basis, constrained by existing contracts. Twelve different coal types are differentiated with respect to thermal grade, sulfur content, and underground or surface mining. The domestic production and distribution of coal is forecast for 13 demand regions and 11 supply

150

Project  

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

Exploring the Standard Model Exploring the Standard Model       You've heard a lot about the Standard Model and the pieces are hopefully beginning to fall into place. However, even a thorough understanding of the Standard Model is not the end of the story but the beginning. By exploring the structure and details of the Standard Model we encounter new questions. Why do the most fundamental particles have the particular masses we observe? Why aren't they all symmetric? How is the mass of a particle related to the masses of its constituents? Is there any other way of organizing the Standard Model? The activities in this project will elucidate but not answer our questions. The Standard Model tells us how particles behave but not necessarily why they do so. The conversation is only beginning. . . .

151

Examining Synergies between Energy Management and Demand Response: A  

E-Print Network [OSTI]

LBNL-5719E Examining Synergies between Energy Management and Demand Response: A Case Study at Two Summary #12;Introduction Energy Management · · · · · · · · · · #12;Demand Response #12;#12;Bentley Prince-Project Personnel Changes #12;Enablement of Demand Response Capabilities due to Energy Management Improvement

152

EnerNOC Inc. Commercial & Industrial Demand Response  

E-Print Network [OSTI]

© EnerNOC Inc. Commercial & Industrial Demand Response: An Overview of the Utility/Aggregator Business Model Pacific Northwest Demand Response Project April 28, 2011 #12;22 Agenda Introduction Ener #12;77 Whos EnerNOC? Market Leader in C&I Demand Response and Industrial Energy Efficiency More than

153

Hawaiian Electric Company Demand Response Roadmap Project  

E-Print Network [OSTI]

widely differing control technologies, notification options,Electric Reliability Technology, LBNL, Joseph Eto E. Availability F. Technology Proposed Residential Large

Levy, Roger

2014-01-01T23:59:59.000Z

154

California Energy Demand Scenario Projections to 2050  

E-Print Network [OSTI]

energy scenarios to explore alternative energy pathways indo not include the alternative energy pathways (such asmodeling to investigate alternative energy supply strategies

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

2008-01-01T23:59:59.000Z

155

California Energy Demand Scenario Projections to 2050  

E-Print Network [OSTI]

CalCARS CEC DOF DWR EIA EMFAC EUI FE GBN GETF GSP GWh HHIndustrial Electricity EUI Agricultural CEC, 2003aOther Natural gas EUI All Shipments CEC, 2005a Electricity

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

2008-01-01T23:59:59.000Z

156

Hawaiian Electric Company Demand Response Roadmap Project  

E-Print Network [OSTI]

implementation of advanced metering and rapidly expanding development of wind, solar, and clean energy

Levy, Roger

2014-01-01T23:59:59.000Z

157

Hawaiian Electric Company Demand Response Roadmap Project  

E-Print Network [OSTI]

Smart Grid implementations may provide current, relevant information for calibrating potential renewable, outage management, and system operational benefits.

Levy, Roger

2014-01-01T23:59:59.000Z

158

Hawaiian Electric Company Demand Response Roadmap Project  

E-Print Network [OSTI]

with residential electric resistance water heater solar system backup electric resistance water heaters. Anheaters require electric resistance backup water heaters.

Levy, Roger

2014-01-01T23:59:59.000Z

159

Demand response enabling technology development  

E-Print Network [OSTI]

Demand Response Enabling Technology Development Phase IEfficiency and Demand Response Programs for 2005/2006,Application to Demand Response Energy Pricing SenSys 2003,

2006-01-01T23:59:59.000Z

160

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

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

Cross-sector Demand Response  

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

Resources News & Events Expand News & Events Skip navigation links Smart Grid Demand Response Agricultural Residential Demand Response Commercial & Industrial Demand Response...

162

Demand Response Programs for Oregon  

E-Print Network [OSTI]

Demand Response Programs for Oregon Utilities Public Utility Commission May 2003 Public Utility ....................................................................................................................... 1 Types of Demand Response Programs............................................................................ 3 Demand Response Programs in Oregon

163

Demand response enabling technology development  

E-Print Network [OSTI]

behavior in developing a demand response future. Phase_II_Demand Response Enabling Technology Development Phase IIYi Yuan The goal of the Demand Response Enabling Technology

Arens, Edward; Auslander, David; Huizenga, Charlie

2008-01-01T23:59:59.000Z

164

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

165

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.

166

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.

167

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

168

Demand Response In California  

Broader source: Energy.gov [DOE]

Presentation covers the demand response in California and is given at the FUPWG 2006 Fall meeting, held on November 1-2, 2006 in San Francisco, California.

169

Energy Demand Forecasting  

Science Journals Connector (OSTI)

This chapter presents alternative approaches used in forecasting energy demand and discusses their pros and cons. It... Chaps. 3 and 4 ...

S. C. Bhattacharyya

2011-01-01T23:59:59.000Z

170

Global energy demand to 2060  

SciTech Connect (OSTI)

The projection of global energy demand to the year 2060 is of particular interest because of its relevance to the current greenhouse concerns. The long-term growth of global energy demand in the time scale of climatic change has received relatively little attention in the public discussion of national policy alternatives. The sociological, political, and economic issues have rarely been mentioned in this context. This study emphasizes that the two major driving forces are global population growth and economic growth (gross national product per capita), as would be expected. The modest annual increases assumed in this study result in a year 2060 annual energy use of >4 times the total global current use (year 1986) if present trends continue, and >2 times with extreme efficiency improvements in energy use. Even assuming a zero per capita growth for energy and economics, the population increase by the year 2060 results in a 1.5 times increase in total annual energy use.

Starr, C. (Electric Power Research Institute, Palo Alto, CA (USA))

1989-01-01T23:59:59.000Z

171

Interoperability of Demand Response Resources Demonstration in NY  

SciTech Connect (OSTI)

The Interoperability of Demand Response Resources Demonstration in NY (Interoperability Project) was awarded to Con Edison in 2009. The objective of the project was to develop and demonstrate methodologies to enhance the ability of customer sited Demand Response resources to integrate more effectively with electric delivery companies and regional transmission organizations.

Wellington, Andre

2014-03-31T23:59:59.000Z

172

TIP #: Project Name  

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

Customers **Cost sharing partners. Project Synopsis Evaluate the performance and demand response (DR) of the Gen II GE GeoSpring(tm) HPWH under a number of operating...

173

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

174

RTP Customer Demand Response  

Science Journals Connector (OSTI)

This paper provides new evidence on customer demand response to hourly pricing from the largest and...real-time pricing...(RTP) program in the United States. RTP creates value by inducing load reductions at times...

Steven Braithwait; Michael OSheasy

2002-01-01T23:59:59.000Z

175

World Energy Demand  

Science Journals Connector (OSTI)

A reliable forecast of energy resources, energy consumption, and population in the future is a ... So, instead of absolute figures about future energy demand and sources worldwide, which would become...3.1 correl...

Giovanni Petrecca

2014-01-01T23:59:59.000Z

176

Natural Gas Transmission and Distribution Module  

Gasoline and Diesel Fuel Update (EIA)

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

177

Natural Gas Transmission and Distribution Module This  

Gasoline and Diesel Fuel Update (EIA)

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

178

Coordination of Energy Efficiency and Demand Response  

SciTech Connect (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

179

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

180

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

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

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

182

Demand and Price Volatility: Rational Habits in International Gasoline Demand  

E-Print Network [OSTI]

analysis of the demand for oil in the Middle East. EnergyEstimates elasticity of demand for crude oil, not gasoline.World crude oil and natural gas: a demand and supply model.

Scott, K. Rebecca

2011-01-01T23:59:59.000Z

183

Demand and Price Uncertainty: Rational Habits in International Gasoline Demand  

E-Print Network [OSTI]

analysis of the demand for oil in the Middle East. EnergyEstimates elasticity of demand for crude oil, not gasoline.World crude oil and natural gas: a demand and supply model.

Scott, K. Rebecca

2013-01-01T23:59:59.000Z

184

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

185

Changing Energy Demand Behavior: Potential of Demand-Side Management  

Science Journals Connector (OSTI)

There is a great theoretical potential to save resources by managing our demand for energy. However, demand-side management (DSM) programs targeting behavioral patterns of...

Dr. Sylvia Breukers; Dr. Ruth Mourik

2013-01-01T23:59:59.000Z

186

Japan's Long-term Energy Demand and Supply Scenario to 2050 - Estimation for the Potential of Massive CO2 Mitigation  

E-Print Network [OSTI]

No.4 Japan's Long-term Energy Demand and Supply Scenario towe projected Japan's energy demand/supply and energy-relatedcrises (to cut primary energy demand per GDP ( T P E S / G D

Komiyama, Ryoichi

2010-01-01T23:59:59.000Z

187

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

188

Demand Response In California  

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

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

189

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

190

Coordination of Energy Efficiency and Demand Response  

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

191

Memorandum: Cost-effectiveness valuation framework for Demand Response Resources: Guidelines and Suggestions (DRAFT)  

E-Print Network [OSTI]

Memorandum: Cost-effectiveness valuation framework for Demand Response Resources: Guidelines and Suggestions (DRAFT) To: Pacific Northwest Demand Response Project Cost-Effectiveness Working Group From: Chuck Northwest Demand Response Project agreed to form three Working Groups to explore DR issues in more detail

192

Energy Demand Modeling  

Science Journals Connector (OSTI)

From the end of World War II until the early 1970s there was a strong and steady increase in the demand for energy. The abundant supplies of fossil and other ... an actual fall in the real price of energy of abou...

S. L. Schwartz

1980-01-01T23:59:59.000Z

193

Demand Side Bidding. Final Report  

SciTech Connect (OSTI)

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

194

A Privacy-Aware Architecture For Demand Response Systems Stephen Wicker, Robert Thomas  

E-Print Network [OSTI]

A Privacy-Aware Architecture For Demand Response Systems Stephen Wicker, Robert Thomas School architectures that realize the benefits of demand response without requiring that AMI data be centrally-based demand response efforts in the face of public outcry. We also show that Trusted Platform Modules can

Wicker, Stephen

195

A Hierarchical Demand Response Framework for Data Center Power Cost Optimization Under Real-World Electricity Pricing  

E-Print Network [OSTI]

1 A Hierarchical Demand Response Framework for Data Center Power Cost Optimization Under Real bills. Our focus is on a subset of this work that carries out demand response (DR) by modulating

Urgaonkar, Bhuvan

196

ENABLING ENERGY DEMAND RESPONSE WITH VEHICULAR MESH NETWORKS  

E-Print Network [OSTI]

ENABLING ENERGY DEMAND RESPONSE WITH VEHICULAR MESH NETWORKS Howard CheHao Chang1, Haining Du2. Using VMesh to connect disjoint sensor networks One of our expectations for VMesh is to enable demand response (DR) [1] for automatic utility usage retrievals and price dispatching. DR is a project in- itiated

Chuah, Chen-Nee

197

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

198

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.

199

DOE DEMANDS SOLAR PATENTS  

Science Journals Connector (OSTI)

THE DEPARTMENT of Energy is claiming ownership of three patents awarded to Evergreen Solar and plans to prevent them from being sold to non-U.S. ... Even with the innovation, Evergreenlike U.S. solar firms Solyndra and SpectraWatt, which recently both declared bankruptcycould not compete with lower cost crystalline solar modules made in China. ...

MELODY BOMGARDNER

2011-10-17T23:59:59.000Z

200

Driving change : evaluating strategies to control automotive energy demand growth in China  

E-Print Network [OSTI]

As the number of vehicles in China has relentlessly grown in the past decade, the energy demand, fuel demand and greenhouse gas emissions associated with these vehicles have kept pace. This thesis presents a model to project ...

Bonde kerlind, Ingrid Gudrun

2013-01-01T23:59:59.000Z

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

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

202

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

203

Utility Sector Impacts of Reduced Electricity Demand  

SciTech Connect (OSTI)

This report presents a new approach to estimating the marginal utility sector impacts associated with electricity demand reductions. The method uses publicly available data and provides results in the form of time series of impact factors. The input data are taken from the Energy Information Agency's Annual Energy Outlook (AEO) projections of how the electric system might evolve in the reference case, and in a number of side cases that incorporate different effciency and other policy assumptions. The data published with the AEO are used to define quantitative relationships between demand-side electricity reductions by end use and supply-side changes to capacity by plant type, generation by fuel type and emissions of CO2, Hg, NOx and SO2. The impact factors define the change in each of these quantities per unit reduction in site electricity demand. We find that the relative variation in these impacts by end use is small, but the time variation can be significant.

Coughlin, Katie

2014-12-01T23:59:59.000Z

204

Uranium 2014 resources, production and demand  

E-Print Network [OSTI]

Published every other year, Uranium Resources, Production, and Demand, or the "Red Book" as it is commonly known, is jointly prepared by the OECD Nuclear Energy Agency and the International Atomic Energy Agency. It is the recognised world reference on uranium and is based on official information received from 43 countries. It presents the results of a thorough review of world uranium supplies and demand and provides a statistical profile of the world uranium industry in the areas of exploration, resource estimates, production and reactor-related requirements. It provides substantial new information from all major uranium production centres in Africa, Australia, Central Asia, Eastern Europe and North America. Long-term projections of nuclear generating capacity and reactor-related uranium requirements are provided as well as a discussion of long-term uranium supply and demand issues. This edition focuses on recent price and production increases that could signal major changes in the industry.

Organisation for Economic Cooperation and Development. Paris

2014-01-01T23:59:59.000Z

205

Managing Energy Demand With Standards and Information  

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

Managing Energy Demand With Standards and Information Managing Energy Demand With Standards and Information Speaker(s): Sebastien Houde Date: September 13, 2012 - 12:00pm Location: 90-3122 Seminar Host/Point of Contact: Christopher Payne The goal of this talk is to discuss two interrelated research projects that aim to assess the welfare effects of energy policies that rely on standards and information. The first project focuses on the Energy Star certification program. Using unique micro-data on the US refrigerator market, I first show that consumers respond to certification in different ways. Some consumers appear to rely heavily on Energy Star and pay little attention to electricity costs, others are the reverse, and still others appear to be insensitive to both electricity costs and Energy Star. I then develop a

206

Is Demand-Side Management Economically Justified?  

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

7 7 Is Demand-Side Management Economically Justified? With billions of dollars being spent on demand-side management programs in the U.S. every year, the rationale for and performance of these programs are coming under increasing scrutiny. Three projects in the Energy Analysis Program are making significant contributions to the DSM debate. *Total Resource Cost Test Ratio = ratio of utility avoided costs (i.e., benefits) divided by total cost of program (i.e., Administrative Cost + Incentive Cost + Consumer Cost) In May, Joe Eto, Ed Vine, Leslie Shown, Chris Payne, and I released the first in a series of reports we authored from the Database on Energy Efficiency Programs (DEEP) project. The objective of DEEP is to document the measured cost and performance of utility-sponsored energy-efficiency

207

World oil demands shift toward faster growing and less price-responsive products and regions  

Science Journals Connector (OSTI)

Using data for 19712008, we estimate the effects of changes in price and income on world oil demand, disaggregated by product transport oil, fuel oil (residual and heating oil), and other oil for six groups of countries. Most of the demand reductions since 197374 were due to fuel-switching away from fuel oil, especially in the OECD; in addition, the collapse of the Former Soviet Union (FSU) reduced their oil consumption substantially. Demand for transport and other oil was much less price-responsive, and has grown almost as rapidly as income, especially outside the OECD and FSU. World oil demand has shifted toward products and regions that are faster growing and less price-responsive. In contrast to projections to 2030 of declining per-capita demand for the world as a whole by the U.S. Department of Energy (DOE), International Energy Agency (IEA) and OPEC we project modest growth. Our projections for total world demand in 2030 are at least 20% higher than projections by those three institutions, using similar assumptions about income growth and oil prices, because we project rest-of-world growth that is consistent with historical patterns, in contrast to the dramatic slowdowns which they project.

Joyce M. Dargay; Dermot Gately

2010-01-01T23:59:59.000Z

208

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

Gasoline and Diesel Fuel Update (EIA)

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

209

DOE Hydrogen Analysis Repository: Hydrogen Demand and Infrastructure  

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

Hydrogen Demand and Infrastructure Deployment Hydrogen Demand and Infrastructure Deployment Project Summary Full Title: Geographically-Based Hydrogen Demand and Infrastructure Deployment Scenario Analysis Project ID: 189 Principal Investigator: Margo Melendez Keywords: Hydrogen fueling; infrastructure; fuel cell vehicles (FCV) Purpose This analysis estimates the spatial distribution of hydrogen fueling stations necessary to support the 5 million fuel cell vehicle scenario, based on demographic demand patterns for hydrogen fuel cell vehicles and strategy of focusing development on specific regions of the U.S. that may have high hydrogen demand. Performer Principal Investigator: Margo Melendez Organization: National Renewable Energy Laboratory (NREL) Address: 1617 Cole Blvd. Golden, CO 80401-3393 Telephone: 303-275-4479

210

New and Underutilized Technology: Carbon Dioxide Demand Ventilation Control  

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

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

211

Demand Response | Department of Energy  

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

212

Understanding and Analysing Energy Demand  

Science Journals Connector (OSTI)

This chapter introduces the concept of energy demand using basic micro-economics and presents the three-stage decision making process of energy demand. It then provides a set of simple ... (such as price and inco...

Subhes C. Bhattacharyya

2011-01-01T23:59:59.000Z

213

Demand Response: Load Management Programs  

E-Print Network [OSTI]

CenterPoint Load Management Programs CATEE Conference October, 2012 Agenda Outline I. General Demand Response Definition II. General Demand Response Program Rules III. CenterPoint Commercial Program IV. CenterPoint Residential Programs... V. Residential Discussion Points Demand Response Definition of load management per energy efficiency rule 25.181: ? Load control activities that result in a reduction in peak demand, or a shifting of energy usage from a peak to an off...

Simon, J.

2012-01-01T23:59:59.000Z

214

Marketing Demand-Side Management  

E-Print Network [OSTI]

they the only game in town, enjoying a captive market. Demand-side management (DSM) again surfaced as a method for increasing customer value and meeting these competitive challenges. In designing and implementing demand-side management (DSM) programs we... have learned a great deal about what it takes to market and sell DSM. This paper focuses on how to successfully market demand-side management. KEY STEPS TO MARKETING DEMAND-SIDE MANAGEMENT Management Commitment The first key element in marketing...

O'Neill, M. L.

1988-01-01T23:59:59.000Z

215

Demand Charges | Open Energy Information  

Open Energy Info (EERE)

Charges Jump to: navigation, search Retrieved from "http:en.openei.orgwindex.php?titleDemandCharges&oldid488967"...

216

ERCOT Demand Response Paul Wattles  

E-Print Network [OSTI]

ERCOT Demand Response Paul Wattles Senior Analyst, Market Design & Development, ERCOT Whitacre;Definitions of Demand Response · `The short-term adjustment of energy use by consumers in response to price to market or reliability conditions.' (NAESB) #12;Definitions of Demand Response · The common threads

Mohsenian-Rad, Hamed

217

Pricing data center demand response  

Science Journals Connector (OSTI)

Demand response is crucial for the incorporation of renewable energy into the grid. In this paper, we focus on a particularly promising industry for demand response: data centers. We use simulations to show that, not only are data centers large loads, ... Keywords: data center, demand response, power network, prediction based pricing

Zhenhua Liu; Iris Liu; Steven Low; Adam Wierman

2014-06-01T23:59:59.000Z

218

Integrated Project Team RM  

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

Integrated Project Team (IPT) Review Module Integrated Project Team (IPT) Review Module March 2010 CD-0 This R O 0 Review Modul OFFICE OF Inte C CD-1 le was piloted F ENVIRO Standard R grated P Rev Critical Decis CD-2 M at the OR U 23 incorporated ONMENTAL Review Plan Project Te view Module sion (CD) Ap CD March 2010 33 Disposition in the Review L MANAGE n (SRP) eam (IPT e pplicability D-3 Project in 200 Module. EMENT T) CD-4 09. Lessons lea Post Ope arned have been eration n Standard Review Plan, 2 nd Edition, March 2010 i FOREWORD The Standard Review Plan (SRP) 1 provides a consistent, predictable corporate review framework to ensure that issues and risks that could challenge the success of Office of Environmental Management (EM) projects are identified early and addressed proactively. The internal EM

219

Overview of Demand Response  

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

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

220

China's Coal: Demand, Constraints, and Externalities  

SciTech Connect (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

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

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

222

Project Title  

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

Advanced Resources International, Inc. Advanced Resources International, Inc. U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Building the Infrastructure for CO 2 Storage August 21-23, 2012 2 Presentation Outline * Benefit to the Program * Project Overview * Technical Status * Accomplishments to Date * Summary * Appendix 3 Benefit to the Program * Program goal being addressed: - Develop technologies that will support industries' ability to predict CO 2 storage capacity in geologic formations to within ±30 percent. * Project benefits statement: - This research seeks to develop a set of robust mathematical modules to predict how coal and shale permeability and

223

DEMAND CONTROLLED VENTILATION AND CLASSROOM VENTILATION  

SciTech Connect (OSTI)

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.? Currently-available optical people counting systems work well much of the time but have large counting errors in some situations. ? In meeting rooms, measurements of carbon dioxide at return-air grilles appear to be a better choice than wall-mounted sensors.? In California, demand controlled ventilation in general office spaces is projected to save significant energy and be cost effective only if typical VRs without demand controlled ventilation are very high relative to VRs in codes. Based on the research, several recommendations were developed for demand controlled ventilation specifications in the California Title 24 Building Energy Efficiency Standards.The research on classroom ventilation collected data over two years on California elementary school classrooms to investigate associations between VRs and student illness absence (IA). Major findings included: ? Median classroom VRs in all studied climate zones were below the California guideline, and 40percent lower in portable than permanent buildings.? Overall, one additional L/s per person of VR was associated with 1.6percent less IA. ? Increasing average VRs in California K-12 classrooms from the current average to the required level is estimated to decrease IA by 3.4percent, increasing State attendance-based funding to school districts by $33M, with $6.2 M in increased energy costs. Further VR increases would provide additional benefits.? Confirming these findings in intervention studies is recommended. ? Energy costs of heating/cooling unoccupied classrooms statewide are modest, but a large portion occurs in relatively few classrooms.

Fisk, William J.; Mendell, Mark J.; Davies, Molly; Eliseeva, Ekaterina; Faulkner, David; Hong, Tienzen; Sullivan, Douglas P.

2014-01-06T23:59:59.000Z

224

Microsoft PowerPoint - FinalModule3.ppt  

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

3: Project Scheduling 3: Project Scheduling Prepared by: Module 3 - Project Scheduling 1 Prepared by: Booz Allen Hamilton Module 3: Project Scheduling Welcome to Module 3. The objective of this module is to introduce you to Project Scheduling. The Topics that will be addressed in this Module include: * Define Planning vs. Scheduling * Define and Illustrate Basic Scheduling Concepts * Define Logic Relationships and Critical Path * Define and Illustrate Different Schedule Formats Module 3 - Project Scheduling 2 Prepared by: Booz Allen Hamilton Review of Previous Modules Let's quickly review what has been covered in the previous modules. * 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

225

Demand Response Programs, 6. edition  

SciTech Connect (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

226

Project Title  

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

Micro-Structured Sapphire Fiber Sensors for Micro-Structured Sapphire Fiber Sensors for Simultaneous Measurements of High-T and Dynamic Gas Pressure in Harsh Environments DE-FE0001127 Investigators: Hai Xiao, Hai-Lung Tsai, Missouri University of Science and Technology Junhang Dong, University of Cincinnati Program Manager: Norm Popkie, Gasification Division, NETL DOE Project Kickoff Meeting in the NETL Pittsburgh December 15, 2009 Outline * Background * Objectives * Project Elements * Management Plan * Research Plan and Approaches * Risk Management * Summary Background * Demands: High-performance, reliable, in situ sensors are highly demanded for advanced process control and lifecycle management in existing and future advanced power and fuel systems - Improved efficiency/safety/reliability/availability/maintainability

227

PDSF Modules  

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

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

228

Demo Abstract: Toward Data-driven Demand-Response Optimization in a Campus Microgrid  

E-Print Network [OSTI]

Demo Abstract: Toward Data-driven Demand-Response Optimization in a Campus Microgrid Yogesh Simmhan-driven demand response optimization (DR) in the USC campus microgrid, as part of the Los An- geles Smart Grid of this project is to investigate techniques for demand-response optimization (DR) ­ cur- tailing the electricity

Prasanna, Viktor K.

229

Design and Valuation of Demand Response Mechanisms and Instruments for Integrating  

E-Print Network [OSTI]

Design and Valuation of Demand Response Mechanisms and Instruments for Integrating Renewable) research project titled "Design and Valuation of Demand Response Mechanisms and Instruments for Integrating resources. The increased reserve requirement can be met using the so-called demand response resources (DRRs

230

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

231

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

232

Barrier Immune Radio Communications for Demand Response  

E-Print Network [OSTI]

of Fully Automated Demand Response in Large Facilities,Fully Automated Demand Response Tests in Large Facilities.for Automated Demand Response. Technical Document to

Rubinstein, Francis

2010-01-01T23:59:59.000Z

233

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

234

Home Network Technologies and Automating Demand Response  

E-Print Network [OSTI]

and Automating Demand Response Charles McParland, Lawrenceand Automating Demand Response Charles McParland, LBNLCommercial and Residential Demand Response Overview of the

McParland, Charles

2010-01-01T23:59:59.000Z

235

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

236

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

237

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

238

Demand Responsive Lighting: A Scoping Study  

E-Print Network [OSTI]

3 2.1 Demand-Side Managementbuildings. The demand side management framework is discussedIssues 2.1 Demand-Side Management Framework Forecasting

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

239

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

of Energy demand-side management energy information systemdemand response. Demand-side management (DSM) program goalsa goal for demand-side management (DSM) coordination and

Goldman, Charles

2010-01-01T23:59:59.000Z

240

China's Coal: Demand, Constraints, and Externalities  

E-Print Network [OSTI]

raising transportation oil demand. Growing internationalcoal by wire could reduce oil demand by stemming coal roadEastern oil production. The rapid growth of coal demand

Aden, Nathaniel

2010-01-01T23:59:59.000Z

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

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network [OSTI]

World: Renewable Energy and Demand Response Proliferation intogether the renewable energy and demand response communityimpacts of renewable energy and demand response integration

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

242

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

District Small Business Summer Solutions: Energy and DemandSummer Solutions: Energy and Demand Impacts Monthly Energy> B-2 Coordination of Energy Efficiency and Demand Response

Goldman, Charles

2010-01-01T23:59:59.000Z

243

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)

244

China-Transportation Demand Management in Beijing: Mitigation of Emissions  

Open Energy Info (EERE)

China-Transportation Demand Management in Beijing: Mitigation of Emissions China-Transportation Demand Management in Beijing: Mitigation of Emissions in Urban Transport Jump to: navigation, search Name Transportation Demand Management in Beijing - Mitigation of emissions in urban transport Agency/Company /Organization Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH Sector Climate Focus Area Transportation Topics Low emission development planning, -LEDS, -NAMA Website http://www.tdm-beijing.org/ Program Start 2011 Program End 2014 Country China Eastern Asia References Transport Management in Beijing[1] Program Overview The project aims to improve transport demand management (TDM) in Beijing in order to manage the steadily increasing traffic density. The project provides capacity building for decision-makers and transport planners in

245

Automated Demand Response Technologies and Demonstration in New York City  

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

Technologies and Demonstration in New York City Technologies and Demonstration in New York City using OpenADR Title Automated Demand Response Technologies and Demonstration in New York City using OpenADR Publication Type Report LBNL Report Number LBNL-6470E Year of Publication 2013 Authors Kim, Joyce Jihyun, Sila Kiliccote, and Rongxin Yin Date Published 09/2013 Publisher LBNL/NYSERDA Abstract Demand response (DR) - allowing customers to respond to reliability requests and market prices by changing electricity use from their normal consumption pattern - continues to be seen as an attractive means of demand-side management and a fundamental smart-grid improvement that links supply and demand. Since October 2011, the Demand Response Research Center at Lawrence Berkeley National Laboratory and New York State Energy Research and Development Authority have conducted a demonstration project enabling Automated Demand Response (Auto-DR) in large commercial buildings located in New York City using Open Automated Demand Response (OpenADR) communication protocols. In particular, this project focuses on demonstrating how OpenADR can automate and simplify interactions between buildings and various stakeholders in New York State including the independent system operator, utilities, retail energy providers, and curtailment service providers. In this paper, we present methods to automate control strategies via building management systems to provide event-driven demand response, price response and demand management based on OpenADR signals. We also present cost control opportunities under day-ahead hourly pricing for large customers and Auto-DR control strategies developed for demonstration buildings. Lastly, we discuss the communication architecture and Auto-DR system designed for the demonstration project to automate price response and DR participation.

246

Harnessing the power of demand  

SciTech Connect (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

247

China, India demand cushions prices  

SciTech Connect (OSTI)

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

248

Honeywell Demonstrates Automated Demand Response Benefits for...  

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

Honeywell Demonstrates Automated Demand Response Benefits for Utility, Commercial, and Industrial Customers Honeywell Demonstrates Automated Demand Response Benefits for Utility,...

249

Retail Demand Response in Southwest Power Pool  

E-Print Network [OSTI]

Data Collection for Demand-side Management for QualifyingPrepared by Demand-side Management Task Force of the

Bharvirkar, Ranjit

2009-01-01T23:59:59.000Z

250

Project Management and Analysis Project Conception and Execution  

E-Print Network [OSTI]

by the World Bank at a cost of $ 600,000. The objectives of the project are: Analyze the supply and demandTD 608 Project Management and Analysis Part I Project Conception and Execution Milind Sohoni Discussion () January 29, 2008 1 / 3 #12;The K-East Ward Water Project Proceed to the web location: www

Sohoni, Milind

251

Automated Demand Response and Commissioning  

SciTech Connect (OSTI)

This paper describes the results from the second season of research to develop and evaluate the performance of new Automated Demand Response (Auto-DR) hardware and software technology in large facilities. Demand Response (DR) is a set of activities to reduce or shift electricity use to improve the electric grid reliability and manage electricity costs. 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. We refer to this as Auto-DR. The evaluation of the control and communications must be properly configured and pass through a set of test stages: Readiness, Approval, Price Client/Price Server Communication, Internet Gateway/Internet Relay Communication, Control of Equipment, and DR Shed Effectiveness. New commissioning tests are needed for such systems to improve connecting demand responsive building systems to the electric grid demand response systems.

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

2005-04-01T23:59:59.000Z

252

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

253

Photovoltaic concentrator module improvements study  

SciTech Connect (OSTI)

This report presents results of a project to design and fabricate an improved photovoltaic concentrator module. Using previous work as a baseline, this study conducted analyses and testing to select major module components and design features. The lens parquet and concentrator solar cell were selected from the highest performing, available components. A single 185X point-focus module was fabricated by the project team and tested at Sandia. Major module characteristics include a 6 by 4 compression-molded acrylic lens parquet (0.737 m{sup 2} area), twenty-four 0.2 ohms-cm, FZ, p-Si solar cells (1.56 cm{sup 2} area) soldered to ceramic substrates and copper heat spreaders, and an aluminized steel housing with corrugated bottom. This project marked the first attempt to use prismatic covers on solar cells in a high-concentration, point-focus application. Cells with 15 percent metallization were obtained, but problems with the fabrication and placement of prismatic covers on these cells lead to the decision not to use covers in the prototype module. Cell assembly fabrication, module fabrication, and module optical design activities are presented here. Test results are also presented for bare cells, cell assemblies, and module. At operating conditions of 981 watts/m{sup 2} DNI and an estimated cell temperature of 65{degrees}C, the module demonstrated an efficiency of 13.9 percent prior to stressed environmental exposure. 12 refs., 56 figs., 7 tabs.

Levy, S.L.; Kerschen, K.A. (Black and Veatch, Kansas City, MO (United States)); Hutchison, G. (Solar Kinetics, Inc., Dallas, TX (United States)); Nowlan, M.J. (Spire Corp., Bedford, MA (United States))

1991-08-01T23:59:59.000Z

254

Coal Market Module This  

Gasoline and Diesel Fuel Update (EIA)

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

255

Coal Market Module  

Gasoline and Diesel Fuel Update (EIA)

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

256

Project Execution Plan RM  

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

Project Execution Plan (PEP) Review Module Project Execution Plan (PEP) Review Module March 2010 CD-0 O 0 OFFICE OF P C CD-1 F ENVIRO Standard R Project E Rev Critical Decis CD-2 M ONMENTAL Review Plan Execution view Module sion (CD) Ap CD March 2010 L MANAGE n (SRP) n Plan e pplicability D-3 EMENT CD-4 Post Ope eration Standard Review Plan, 2 nd Edition, March 2010 i FOREWORD The Standard Review Plan (SRP) 1 provides a consistent, predictable corporate review framework to ensure that issues and risks that could challenge the success of Office of Environmental Management (EM) projects are identified early and addressed proactively. The internal EM project review process encompasses key milestones established by DOE O 413.3A, Change 1, Program and Project Management for the Acquisition of Capital Assets, DOE-STD-1189-2008,

257

Renewable Fuels Module This  

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

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

258

Low Cost Solar Array Project cell and module formation research area. Process research of non-CZ silicon material. Final report, November 26, 1980-September 30, 1983  

SciTech Connect (OSTI)

The primary objective of the work reported was to investigate high-risk, high-payoff research areas associated with the Westinghouse process for producing photovoltaic modules using non-Czochralski sheet material. These tasks were addressed: technical feasibility study of forming front and back junctions using liquid dopant techniques, liquid diffusion mask feasibility study, application studies of antireflective material using a meniscus coater, ion implantation compatibility/feasibility study, and cost analysis. (LEW)

Campbell, R.B.

1983-01-01T23:59:59.000Z

259

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

260

Full Rank Rational Demand Systems  

E-Print Network [OSTI]

as a nominal income full rank QES. R EFERENCES (A.84)S. G. Donald. Inferring the Rank of a Matrix. Journal of97-102. . A Demand System Rank Theorem. Econometrica 57 (

LaFrance, Jeffrey T; Pope, Rulon D.

2006-01-01T23:59:59.000Z

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

Demand Forecasting of New Products  

E-Print Network [OSTI]

Keeping Unit or SKU) employing attribute analysis techniques. The objective of this thesis is to improve Abstract This thesis is a study into the demand forecasting of new products (also referred to as Stock

Sun, Yu

262

Demand Response and Energy Efficiency  

E-Print Network [OSTI]

Demand Response & Energy Efficiency International Conference for Enhanced Building Operations ESL-IC-09-11-05 Proceedings of the Ninth International Conference for Enhanced Building Operations, Austin, Texas, November 17 - 19, 2009 2 ?Less than 5..., 2009 4 An Innovative Solution to Get the Ball Rolling ? Demand Response (DR) ? Monitoring Based Commissioning (MBCx) EnerNOC has a solution involving two complementary offerings. ESL-IC-09-11-05 Proceedings of the Ninth International Conference...

263

Construction Project Safety and Health Plan RM  

Broader source: Energy.gov [DOE]

The Construction Project Safety and Health Plan (CPSHP) Review Module is a tool that assists DOE federal project review teams in evaluating the technical sufficiency of the project readiness in...

264

National Action Plan on Demand Response  

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

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

265

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

266

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

267

Module Configuration  

DOE Patents [OSTI]

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

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

2002-06-04T23:59:59.000Z

268

MODELING THE DEMAND FOR E85 IN THE UNITED STATES  

SciTech Connect (OSTI)

How demand for E85 might evolve in the future in response to changing economics and policies is an important subject to include in the National Energy Modeling System (NEMS). This report summarizes a study to develop an E85 choice model for NEMS. Using the most recent data from the states of Minnesota, North Dakota, and Iowa, this study estimates a logit model that represents E85 choice as a function of prices of E10 and E85, as well as fuel availability of E85 relative to gasoline. Using more recent data than previous studies allows a better estimation of non-fleet demand and indicates that the price elasticity of E85 choice appears to be higher than previously estimated. Based on the results of the econometric analysis, a model for projecting E85 demand at the regional level is specified. In testing, the model produced plausible predictions of US E85 demand to 2040.

Liu, Changzheng [ORNL; Greene, David L [ORNL

2013-10-01T23:59:59.000Z

269

Electricity demand as frequency controlled reserves, ENS (Smart Grid  

Open Energy Info (EERE)

Electricity demand as frequency controlled reserves, ENS (Smart Grid Electricity demand as frequency controlled reserves, ENS (Smart Grid Project) Jump to: navigation, search Project Name Electricity demand as frequency controlled reserves, ENS Country Denmark Coordinates 56.26392°, 9.501785° 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":56.26392,"lon":9.501785,"alt":0,"address":"","icon":"","group":"","inlineLabel":"","visitedicon":""}]}

270

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.

271

Project Title  

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

MVA Tools MVA Tools Sam Clegg, Kristy Nowak-Lovato, Ron Martinez, Julianna Fessenden, Thom Rahn, & Lianjie Huang Los Alamos National Laboratory U.S. Department of Energy National Energy Technology Laboratory Carbon Storage R&D Project Review Meeting Developing the Technologies and Infrastructure for CCS August 20-22, 2013 2 Presentation Outline * Benefit to the Program * Project Overview - Goals and Objectives * Technical Status * Accomplishments to Date * Summary * Appendix - Organization Chart - Bibliography 3 Project Overview: Goals and Objectives * Surface MVA - Frequency Modulated Spectroscopy - Quantitatively identify CO2, H2S and CH4 seepage from geologic sequestration sites - Distinguish anthropogenic CO2 from natural CO2 emissions * CO2 carbon stable isotope measurements

272

Facilitating Renewable Integration by Demand Response  

Science Journals Connector (OSTI)

Demand response is seen as one of the resources ... expected to incentivize small consumers to participate in demand response. This chapter models the involvement of small consumers in demand response programs wi...

Juan M. Morales; Antonio J. Conejo

2014-01-01T23:59:59.000Z

273

Demand Response as a System Reliability Resource  

E-Print Network [OSTI]

Barat, and D. Watson. 2007. Demand Response Spinning ReserveKueck, and B. Kirby. 2009. Demand Response Spinning ReserveFormat of 2009-2011 Demand Response Activity Applications.

Joseph, Eto

2014-01-01T23:59:59.000Z

274

Demand response-enabled residential thermostat controls.  

E-Print Network [OSTI]

human dimension of demand response technology from a caseArens, E. , et al. 2008. Demand Response Enabling TechnologyArens, E. , et al. 2006. Demand Response Enabling Technology

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

2008-01-01T23:59:59.000Z

275

Value of Demand Response -Introduction Klaus Skytte  

E-Print Network [OSTI]

Value of Demand Response - Introduction Klaus Skytte Systems Analysis Department February 7, 2006 Energinet.dk, Ballerup #12;What is Demand Response? Demand response (DR) is the short-term response

276

Balancing of Energy Supply and Residential Demand  

Science Journals Connector (OSTI)

Power demand of private households shows daily fluctuations and ... (BEV) and heat pumps. This additional demand, especially when it remains unmanaged, will ... to an increase in fluctuations. To balance demand,

Martin Bock; Grit Walther

2014-01-01T23:59:59.000Z

277

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

278

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

279

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"

280

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

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

Turkey's energy demand and supply  

SciTech Connect (OSTI)

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

282

International Oil Supplies and Demands  

SciTech Connect (OSTI)

The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--90 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world's dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group's thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

Not Available

1991-09-01T23:59:59.000Z

283

International Oil Supplies and Demands  

SciTech Connect (OSTI)

The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--1990 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world's dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group's thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

Not Available

1992-04-01T23:59:59.000Z

284

The impact of future energy demand on renewable energy production Case of Norway  

Science Journals Connector (OSTI)

Abstract Projections of energy demand are an important part of analyses of policies to promote conservation, efficiency, technology implementation and renewable energy production. The development of energy demand is a key driver of the future energy system. This paper presents long-term projections of the Norwegian energy demand as a two-step methodology of first using activities and intensities to calculate a demand of energy services, and secondly use this as input to the energy system model TIMES-Norway to optimize the Norwegian energy system. Long-term energy demand projections are uncertain and the purpose of this paper is to illustrate the impact of different projections on the energy system. The results of the analyses show that decreased energy demand results in a higher renewable fraction compared to an increased demand, and the renewable energy production increases with increased energy demand. The most profitable solution to cover increased demand is to increase the use of bio energy and to implement energy efficiency measures. To increase the wind power production, an increased renewable target or higher electricity export prices have to be fulfilled, in combination with more electricity export.

Eva Rosenberg; Arne Lind; Kari Aamodt Espegren

2013-01-01T23:59:59.000Z

285

Demand Response as a System Reliability Resource  

E-Print Network [OSTI]

for Demand Response Technology Development The objective ofin planning demand response technology RD&D by conductingNew and Emerging Technologies into the California Smart Grid

Joseph, Eto

2014-01-01T23:59:59.000Z

286

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

287

Demand Response - Policy | Department of Energy  

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

Demand Response - Policy Demand Response - Policy Since its inception, the Office of Electricity Delivery and Energy Reliability (OE) has been committed to modernizing the nation's...

288

Sandia National Laboratories: demand response inverter  

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

demand response inverter ECIS-Princeton Power Systems, Inc.: Demand Response Inverter On March 19, 2013, in DETL, Distribution Grid Integration, Energy, Energy Surety, Facilities,...

289

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

and Demand Response A pilot program from NSTAR in Massachusetts,Massachusetts, aiming to test whether an intensive program of energy efficiency and demand response

Goldman, Charles

2010-01-01T23:59:59.000Z

290

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

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

Demand: Social Media Tools & Strategies - January 16, 2011 Marketing & Driving Demand: Social Media Tools & Strategies - January 16, 2011 January 16, 2011 Conference Call...

291

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

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

Demand Collaborative - Social Media Tools & Strategies Marketing & Driving Demand Collaborative - Social Media Tools & Strategies Presentation slides from the BetterBuildings...

292

Reducing Energy Demand in Buildings Through State Energy Codes  

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

Codes Assistance Project Codes Assistance Project Maureen Guttman, AIA Executive Director, BCAP Alliance to Save Energy 202-530-2211 mguttman@ase.org Tuesday, April 2, 2013 - Thursday, April 4, 2013 Reducing Energy Demand in Buildings Through State Energy Codes - Providing Technical Support and Assistance to States - 2 | Building Technologies Office eere.energy.gov Purpose & Objectives Problem Statement: Buildings = largest sector of energy consumption in America * Energy codes are a ready-made regulatory mechanism * States need support for implementation Impact of Project:

293

Reducing Energy Demand in Buildings Through State Energy Codes  

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

Codes Assistance Project Codes Assistance Project Maureen Guttman, AIA Executive Director, BCAP Alliance to Save Energy 202-530-2211 mguttman@ase.org Tuesday, April 2, 2013 - Thursday, April 4, 2013 Reducing Energy Demand in Buildings Through State Energy Codes - Providing Technical Support and Assistance to States - 2 | Building Technologies Office eere.energy.gov Purpose & Objectives Problem Statement: Buildings = largest sector of energy consumption in America * Energy codes are a ready-made regulatory mechanism * States need support for implementation Impact of Project:

294

EIA - International Energy Outlook 2009-World Energy Demand and Economic  

Gasoline and Diesel Fuel Update (EIA)

World Energy and Economic Outlook World Energy and Economic Outlook International Energy Outlook 2009 Chapter 1 - World Energy Demand and Economic Outlook In the IEO2009 projections, total world consumption of marketed energy is projected to increase by 44 percent from 2006 to 2030. The largest projected increase in energy demand is for the non-OECD economies. Figure 10. World Marketed Energy Consumption, 1980-2030 (Quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 11. World Marketed Energy Consumption: OECD and Non-OECD, 1980-2030 (Quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 12. Marketed Energy Use by Region, 1990-2030 (Quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800.

295

EIA - International Energy Outlook 2008-World Energy Demand and Economic  

Gasoline and Diesel Fuel Update (EIA)

World Energy and Economic Outlook World Energy and Economic Outlook International Energy Outlook 2008 Chapter 1 - World Energy Demand and Economic Outlook In the IEO2008 projections, total world consumption of marketed energy is projected to increase by 50 percent from 2005 to 2030. The largest projected increase in energy demand is for the non-OECD economies. Figure 9. World Marketed EnergyConsumption, 1980-2030 (Quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 10. World Marketed Energy Consumption: OECD and Non-OECD, 1980-2030 (Quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800. Figure Data Figure 11. Marketed Energy Use in the Non-OECD Economies by Region, 1990-2030 (Quadrillion Btu). Need help, contact the National Energy Information Center at 202-586-8800.

296

LNG demand, shipping will expand through 2010  

SciTech Connect (OSTI)

The 1990s, especially the middle years, have witnessed a dramatic turnaround in the growth of liquefied-natural-gas demand which has tracked equally strong natural-gas demand growth. This trend was underscored late last year by several annual studies of world LNG demand and shipping. As 1998 began, however, economic turmoil in Asian financial markets has clouded near-term prospects for LNG in particular and all energy in general. But the extent of damage to energy markets is so far unclear. A study by US-based Institute of Gas Technology, Des Plaines, IL, reveals that LNG imports worldwide have climbed nearly 8%/year since 1980 and account for 25% of all natural gas traded internationally. In the mid-1970s, the share was only 5%. In 1996, the most recent year for which complete data are available, world LNG trade rose 7.7% to a record 92 billion cu m, outpacing the overall consumption for natural gas which increased 4.7% in 1996. By 2015, says the IGT study, natural-gas use would surpass coal as the world`s second most widely used fuel, after petroleum. Much of this growth will occur in the developing countries of Asia where gas use, before the current economic crisis began, was projected to grow 8%/year through 2015. Similar trends are reflected in another study of LNG trade released at year end 1997, this from Ocean Shipping Consultants Ltd., Surrey, U.K. The study was done too early, however, to consider the effects of the financial problems roiling Asia.

True, W.R.

1998-02-09T23:59:59.000Z

297

Smart Buildings and Demand Response  

Science Journals Connector (OSTI)

Advances in communications and control technology the strengthening of the Internet and the growing appreciation of the urgency to reduce demand side energy use are motivating the development of improvements in both energy efficiency and demand response (DR) systems in buildings. This paper provides a framework linking continuous energy management and continuous communications for automated demand response (Auto?DR) in various times scales. We provide a set of concepts for monitoring and controls linked to standards and procedures such as Open Automation Demand Response Communication Standards (OpenADR). Basic building energy science and control issues in this approach begin with key building components systems end?uses and whole building energy performance metrics. The paper presents a framework about when energy is used levels of services by energy using systems granularity of control and speed of telemetry. DR when defined as a discrete event requires a different set of building service levels than daily operations. We provide examples of lessons from DR case studies and links to energy efficiency.

2011-01-01T23:59:59.000Z

298

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

299

Industrial demand side management status report: Synopsis  

SciTech Connect (OSTI)

Industrial demand side management (DSM) programs, though not as developed or widely implemented as residential and commercial programs, hold the promise of significant energy savings-savings that will benefit industrial firms, utilities and the environment. This paper is a synopsis of a larger research report, Industrial Demand Side Management. A Status Report, prepared for the US Department of Energy. The report provides an overview of and rationale for DSM programs. Benefits and barriers are described, and data from the Manufacturing Energy Consumption Survey are used to estimate potential electricity savings from industrial energy efficiency measures. Overcoming difficulties to effective program implementation is worthwhile, since rough estimates indicate a substantial potential for electricity savings. The report categorizes types of DSM programs, presents several examples of each type, and explores elements of successful programs. Two in-depth case studies (of Boise Cascade and of Eli Lilly and Company) illustrate two types of effective DSM programs. Interviews with staff from state public utility commissions indicate the current thinking about the status and future of industrial DSM programs. Finally, the research report also includes a comprehensive bibliography, a description of technical assistance programs, and an example of a methodology for evaluating potential or actual savings from projects.

Hopkins, M.E.F.; Conger, R.L.; Foley, T.J.; Parker, J.W.; Placet, M.; Sandahl, L.J.; Spanner, G.E.; Woodruff, M.G.; Norland, D.

1995-08-01T23:59:59.000Z

300

Industrial demand side management: A status report  

SciTech Connect (OSTI)

This report provides an overview of and rationale for industrial demand side management (DSM) programs. Benefits and barriers are described, and data from the Manufacturing Energy Consumption Survey are used to estimate potential energy savings in kilowatt hours. The report presents types and examples of programs and explores elements of successful programs. Two in-depth case studies (from Boise Cascade and Eli Lilly and Company) illustrate two types of effective DSM programs. Interviews with staff from state public utility commissions indicate the current thinking about the status and future of industrial DSM programs. A comprehensive bibliography is included, technical assistance programs are listed and described, and a methodology for evaluating potential or actual savings from projects is delineated.

Hopkins, M.F.; Conger, R.L.; Foley, T.J. [and others

1995-05-01T23:59:59.000Z

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

The alchemy of demand response: turning demand into supply  

SciTech Connect (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

302

Is Cumulative Fossil Energy Demand a Useful Indicator for the Environmental Performance of Products?  

Science Journals Connector (OSTI)

Is Cumulative Fossil Energy Demand a Useful Indicator for the Environmental Performance of Products? ... The Ecoinvent database v1.2 (4), containing life-cycle information for many products consumed in the western economy, has been used to derive cumulative fossil energy demands and life-cycle impact scores. ... The project work proved to be demanding in terms of co-ordination efforts required and consent identification. ...

Mark A. J. Huijbregts; Linda J. A. Rombouts; Stefanie Hellweg; Rolf Frischknecht; A. Jan Hendriks; Dik van de Meent; Ad M. J. Ragas; Lucas Reijnders; Jaap Struijs

2005-12-27T23:59:59.000Z

303

Demand Response in Quebec's CI Buildings: Potentioal and Strategies  

E-Print Network [OSTI]

1 October 10th 2013 ? ICEBO2013 Demand response in Quebec?s CI buildings: potential and strategies Team: Ahmed Daoud, Ph.D, project manager Marie-Andr?e Leduc, MSc., ing, task manager Jean Baribeault, ing, researcher Karine Lavigne, MSc...-10-20 Proceedings of the 13th International Conference for Enhanced Building Operations, Montreal, Quebec, October 8-11, 2013 4 Demand response in CI buildings ESL-IC-13-10-20 Proceedings of the 13th International Conference for Enhanced Building Operations...

Daoud, A.; Leduc, M. A.; Baribeault, J.; Lavigne, K.; Chenard, S.; Poulin, A.; Martel, S.; Bendaoud, A.

2013-01-01T23:59:59.000Z

304

Assessment of Demand Response and Advanced Metering  

E-Print Network [OSTI]

#12;#12;2008 Assessment of Demand Response and Advanced Metering Staff Report Federal Energy metering penetration and potential peak load reduction from demand response have increased since 2006. Significant activity to promote demand response or to remove barriers to demand response occurred at the state

Tesfatsion, Leigh

305

INTEGRATION OF PV IN DEMAND RESPONSE  

E-Print Network [OSTI]

INTEGRATION OF PV IN DEMAND RESPONSE PROGRAMS Prepared by Richard Perez et al. NREL subcontract response programs. This is because PV generation acts as a catalyst to demand response, markedly enhancing by solid evidence from three utility case studies. BACKGROUND Demand Response: demand response (DR

Perez, Richard R.

306

Demand Side Management in Rangan Banerjee  

E-Print Network [OSTI]

Demand Side Management in Industry Rangan Banerjee Talk at Baroda in Birla Corporate Seminar August 31,2007 #12;Demand Side Management Indian utilities ­ energy shortage and peak power shortage. Supply for Options ­ Demand Side Management (DSM) & Load Management #12;DSM Concept Demand Side Management (DSM) - co

Banerjee, Rangan

307

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network [OSTI]

with hydro power and wind integration, more DR may be neededload growth, wind power integration, and fish operations are

Kiliccote, Sila

2010-01-01T23:59:59.000Z

308

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network [OSTI]

meters are required for measurement and verification of DRare required for measurement and verification of DR

Kiliccote, Sila

2010-01-01T23:59:59.000Z

309

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network [OSTI]

Facility Technician) Automated Logic Corporation: Ivanembedded in the Targets Automated Logic Corporation (ALC)

Kiliccote, Sila

2010-01-01T23:59:59.000Z

310

Northwest Open Automated Demand Response Technology Demonstration Project  

E-Print Network [OSTI]

Air Volume VFD Variable Frequency Drive XML Extensiblepressure reset, variable frequency drive (VFD) position

Kiliccote, Sila

2010-01-01T23:59:59.000Z

311

Incorporating Demand Response into Western Interconnection Transmission Planning  

E-Print Network [OSTI]

Aggregator Programs. Demand Response Measurement andIncorporating Demand Response into Western Interconnection13 Demand Response Dispatch

Satchwell, Andrew

2014-01-01T23:59:59.000Z

312

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

313

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

314

Regional Differences in Corn Ethanol Production: Profitability and Potential Water Demands  

E-Print Network [OSTI]

Through the use of a stochastic simulation model this project analyzes both the impacts of the expanding biofuels sector on water demand in selected regions of the United States and variations in the profitability of ethanol production due...

Higgins, Lindsey M.

2010-07-14T23:59:59.000Z

315

Toward data-driven demand-response optimization in a campus microgrid  

Science Journals Connector (OSTI)

We describe and demonstrate a prototype software architecture to support data-driven demand response optimization (DR) in the USC campus microgrid, as part of the Los Angeles Smart Grid Demonstration Project. The architecture includes a semantic ...

Yogesh Simmhan; Viktor Prasanna; Saima Aman; Sreedhar Natarajan; Wei Yin; Qunzhi Zhou

2011-11-01T23:59:59.000Z

316

Honeywell Demonstrates Automated Demand Response Benefits for Utility, Commercial, and Industrial Customers  

Broader source: Energy.gov [DOE]

Honeywells Smart Grid Investment Grant (SGIG) project demonstrates utility-scale performance of a hardware/software platform for automated demand response (ADR) for utility, commercial, and industrial customers. The case study is now available for downloading.

317

The BeyWatch Conceptual Model for Demand-Side Management  

Science Journals Connector (OSTI)

The BeyWatch project designs, develops and evaluates an innovative, energy-aware and user-centric solution, able to provide intelligent energy monitoring/control and power demand balancing at home/building and la...

Menelaos Perdikeas; Theodore Zahariadis

2011-01-01T23:59:59.000Z

318

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

319

Project Year Project Title  

E-Print Network [OSTI]

the cost of the project to labor only. The efficacy of the examples will be assessed through their useProject Year 2012-2013 Project Title Sight-Reading at the Piano Project Team Ken Johansen, Peabody) Faculty Statement The goal of this project is to create a bank of practice exercises that student pianists

Gray, Jeffrey J.

320

Project Year Project Team  

E-Print Network [OSTI]

design goals for this project include low cost (less than $30 per paddle) and robustness. The projectProject Year 2001 Project Team Faculty: Allison Okamura, Mechanical Engineering, Whiting School Project Title Haptic Display of Dynamic Systems Audience 30 to 40 students per year, enrolled

Gray, Jeffrey J.

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

Project Year Project Team  

E-Print Network [OSTI]

-year section of the summer project will cost $1344.) This project will be measured by the CER surveys conductedProject Year 2005 Project Team Sean Greenberg, Faculty, Philosophy Department, Krieger School of Arts & Sciences; Kevin Clark, Student, Philosophy Department, Krieger School of Arts & Sciences Project

Gray, Jeffrey J.

322

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

SciTech Connect (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

323

Project Information Form Project Title Integrating Management of Truck and Rail Systems in Los Angeles  

E-Print Network [OSTI]

Project Information Form Project Title Integrating Management of Truck and Rail Systems in Los or organization) Volvo Research and Educational Foundation- $79,604.00 Total Project Cost $79,604.00 Agency ID of Research Project This project will develop models to optimize the balance of freight demand across rail

California at Davis, University of

324

Incentives for demand-side management  

SciTech Connect (OSTI)

This report is the first product of an ongoing project to monitor the efforts of states to remove regulatory barriers to, and provide financial incentives for, utility investment in demand-side management (DSM) resources. The project was commissioned by the National Association of Regulatory Utility Commissioners (NARUC) in response to growing interest among regulators for a comprehensive survey of developments in this area. Each state report beings with an overview of the state`s progress toward removing regulatory barriers and providing incentives for DSM. Information is organized under five headings: status; IRP regulations and practice; current treatment of DSM, directions and trends; commission contact person. Where applicable, each overview is followed by one or more sections that report on specific incentive proposals or mechanisms within the state. Information on each proposal or mechanism is organized under eight headings. A notation on each page identifies the utility or other group associated with the proposal or mechanism. The eight headings are as follows: status; background; treatment of cost recovery; treatment of lost revenues/decoupling; treatment of profitability; other features; issues, and additional observations.

Reid, M.W.; Brown, J.B. [Barakat and Chamberlin, Inc., Oakland, CA (United States)] [Barakat and Chamberlin, Inc., Oakland, CA (United States)

1992-01-01T23:59:59.000Z

325

Incentives for demand-side management  

SciTech Connect (OSTI)

This report is the first product of an ongoing project to monitor the efforts of states to remove regulatory barriers to, and provide financial incentives for, utility investment in demand-side management (DSM) resources. The project was commissioned by the National Association of Regulatory Utility Commissioners (NARUC) in response to growing interest among regulators for a comprehensive survey of developments in this area. Each state report beings with an overview of the state's progress toward removing regulatory barriers and providing incentives for DSM. Information is organized under five headings: status; IRP regulations and practice; current treatment of DSM, directions and trends; commission contact person. Where applicable, each overview is followed by one or more sections that report on specific incentive proposals or mechanisms within the state. Information on each proposal or mechanism is organized under eight headings. A notation on each page identifies the utility or other group associated with the proposal or mechanism. The eight headings are as follows: status; background; treatment of cost recovery; treatment of lost revenues/decoupling; treatment of profitability; other features; issues, and additional observations.

Reid, M.W.; Brown, J.B. (Barakat and Chamberlin, Inc., Oakland, CA (United States)) [Barakat and Chamberlin, Inc., Oakland, CA (United States)

1992-01-01T23:59:59.000Z

326

EIA - Annual Energy Outlook 2008 - Natural Gas Demand  

Gasoline and Diesel Fuel Update (EIA)

Natural Gas Demand Natural Gas Demand Annual Energy Outlook 2008 with Projections to 2030 Natural Gas Demand Figure 72. Natural gas consumption by sector, 1990-2030 (trillion cubic feet). Need help, contact the National Energy Information Center at 202-586-8800. figure data Figure 73. Total natural gas consumption, 1990-2030 (trillion cubic feet). Need help, contact the National Energy Information Center at 202-586-8800. figure data Fastest Increase in Natural Gas Use Is Expected for the Buildings Sectors In the reference case, total natural gas consumption increases from 21.7 trillion cubic feet in 2006 to a peak value of 23.8 trillion cubic feet in 2016, followed by a decline to 22.7 trillion cubic feet in 2030. The natural gas share of total energy consumption drops from 22 percent in 2006

327

Project Year Project Team  

E-Print Network [OSTI]

Project Year 2002 Project Team Faculty: Louise Pasternack, Chemistry Department, Krieger School, Krieger School of Arts & Sciences Project Title Introductory Chemistry Lab Demonstrations Audience an interactive virtual lab manual that will facilitate understanding of the procedures and techniques required

Gray, Jeffrey J.

328

Project Year Project Team  

E-Print Network [OSTI]

(Karl) Zhang, Undergraduate Student, Biomedical Engineering, Whiting School of Engineering; Cheryl Kim Audio, Digital Video Project Abstract The goal of this project is to develop online modular units

Gray, Jeffrey J.

329

Line Projects  

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

(PDCI) Upgrade Project Whistling Ridge Energy Project Line Rebuild, Relocation and Substation Projects Wind Projects Line Projects BPA identifies critical infrastructure and...

330

Climate, extreme heat, and electricity demand in California  

SciTech Connect (OSTI)

Climate projections from three atmosphere-ocean climate models with a range of low to mid-high temperature sensitivity forced by the Intergovernmental Panel for Climate Change SRES higher, middle, and lower emission scenarios indicate that, over the 21st century, extreme heat events for major cities in heavily air-conditioned California will increase rapidly. These increases in temperature extremes are projected to exceed the rate of increase in mean temperature, along with increased variance. Extreme heat is defined here as the 90 percent exceedance probability (T90) of the local warmest summer days under the current climate. The number of extreme heat days in Los Angeles, where T90 is currently 95 F (32 C), may increase from 12 days to as many as 96 days per year by 2100, implying current-day heat wave conditions may last for the entire summer, with earlier onset. Overall, projected increases in extreme heat under the higher A1fi emission scenario by 2070-2099 tend to be 20-30 percent higher than those projected under the lower B1 emission scenario, ranging from approximately double the historical number of days for inland California cities (e.g. Sacramento and Fresno), up to four times for previously temperate coastal cities (e.g. Los Angeles, San Diego). These findings, combined with observed relationships between high temperature and electricity demand for air-conditioned regions, suggest potential shortfalls in transmission and supply during T90 peak electricity demand periods. When the projected extreme heat and peak demand for electricity are mapped onto current availability, maintaining technology and population constant only for demand side calculations, we find the potential for electricity deficits as high as 17 percent. Similar increases in extreme heat days are suggested for other locations across the U.S. southwest, as well as for developing nations with rapidly increasing electricity demands. Electricity response to recent extreme heat events, such as the July 2006 heat wave in California, suggests that peak electricity demand will challenge current supply, as well as future planned supply capacities when population and income growth are taken into account.

Miller, N.L.; Hayhoe, K.; Jin, J.; Auffhammer, M.

2008-04-01T23:59:59.000Z

331

Transportation Demand Management in Beijing - Mitigation of emissions in  

Open Energy Info (EERE)

Beijing - Mitigation of emissions in Beijing - Mitigation of emissions in urban transport Jump to: navigation, search Name Transportation Demand Management in Beijing - Mitigation of emissions in urban transport Agency/Company /Organization Deutsche Gesellschaft für Internationale Zusammenarbeit (GIZ) GmbH Sector Climate Focus Area Transportation Topics Low emission development planning, -LEDS, -NAMA Website http://www.tdm-beijing.org/ Program Start 2011 Program End 2014 Country China Eastern Asia References Transport Management in Beijing[1] Program Overview The project aims to improve transport demand management (TDM) in Beijing in order to manage the steadily increasing traffic density. The project provides capacity building for decision-makers and transport planners in Beijing to enable them to calculate baselines and assess reduction

332

New coal plant technologies will demand more water  

SciTech Connect (OSTI)

Population shifts, growing electricity demand, and greater competition for water resources have heightened interest in the link between energy and water. The US Energy Information Administration projects a 22% increase in US installed generating capacity by 2030. Of the 259 GE of new capacity expected to have come on-line by then, more than 192 GW will be thermoelectric and thus require some water for cooling. Our challenge will become balancing people's needs for power and for water. 1 ref., 7 figs.

Peltier, R.; Shuster, E.; McNemar, A.; Stiegel, G.J.; Murphy, J.

2008-04-15T23:59:59.000Z

333

Regulatory risks paralyzing power industry while demand grows  

SciTech Connect (OSTI)

2008 will be the year the US generation industry grapples with CO{sub 2} emission. Project developers are suddenly coal-shy, mostly flirting with new nuclear plants waiting impatiently in line for equipment manufacturers to catch up with the demand for wind turbines, and finding gas more attractive again. With no proven greenhouse gas sequestration technology on the horizon, utilities will be playing it safe with energy-efficiency ploys rather than rushing to contract for much-needed new generation.

Maize, K.; Peltier, R.

2008-01-15T23:59:59.000Z

334

Project Year Project Title  

E-Print Network [OSTI]

that incorporate video taped procedures for student preview. Solution This project will create videos for more to study the procedure and techniques before coming to class. Our previous fellowship project addressedProject Year 2009 Project Title Enhancing Biology Laboratory Preparation through Video

Gray, Jeffrey J.

335

Project Year Project Team  

E-Print Network [OSTI]

, there is no resource available to view the procedure before class. Solution The purpose of this project is to capture available to view the procedure before class. The purpose #12;of this project is to capture variousProject Year 2007 Project Team Kristina Obom, Faculty, Advanced Academic Programs, Krieger School

Gray, Jeffrey J.

336

Project Year Project Title  

E-Print Network [OSTI]

Project Year 2013-2014 Project Title German Online Placement Exam Project Team Deborah Mifflin to increased cost. As well, it lacked listening comprehension, writing and speaking components providing support, we will use Blackboard for this project. The creation will require numerous steps

Gray, Jeffrey J.

337

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

338

Demand Response Programs Oregon Public Utility Commission  

E-Print Network [OSTI]

Demand Response Programs Oregon Public Utility Commission January 6, 2005 Mike Koszalka Director;Demand Response Results, 2004 Load Control ­ Cool Keeper ­ ID Irrigation Load Control Price Responsive

339

Industrial Equipment Demand and Duty Factors  

E-Print Network [OSTI]

Demand and duty factors have been measured for selected equipment (air compressors, electric furnaces, injection molding machines, centrifugal loads, and others) in industrial plants. Demand factors for heavily loaded air compressors were near 100...

Dooley, E. S.; Heffington, W. M.

340

ConservationandDemand ManagementPlan  

E-Print Network [OSTI]

; Introduction Ontario Regulation 397/11 under the Green Energy Act 2009 requires public agencies and implement energy Conservation and Demand Management (CDM) plans starting in 2014. Requirementsofthe ConservationandDemand ManagementPlan 2014-2019 #12

Abolmaesumi, Purang

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

Energy Demand Analysis at a Disaggregated Level  

Science Journals Connector (OSTI)

The purpose of this chapter is to consider energy demand at the fuel level or at the ... . This chapter first presents the disaggregation of energy demand, discusses the information issues and introduces framewor...

Subhes C. Bhattacharyya

2011-01-01T23:59:59.000Z

342

Seasonal temperature variations and energy demand  

Science Journals Connector (OSTI)

This paper presents an empirical study of the relationship between residential energy demand and temperature. Unlike previous studies in this ... different regions and to the contrasting effects on energy demand ...

Enrica De Cian; Elisa Lanzi; Roberto Roson

2013-02-01T23:59:59.000Z

343

Project 143  

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

George Rizeq George Rizeq Principal Investigator GE Global Research 18A Mason Irvine, CA 92618 949-330-8973 rizeq@research.ge.com FUEL-FLEXIBLE GASIFICATION-COMBUSTION TECHNOLOGY FOR PRODUCTION OF HYDROGEN AND SEQUESTRATION-READY CARBON DIOXIDE Description Projections of increased demands for energy worldwide, coupled with increasing environmental concerns have given rise to the need for new and innovative technologies for coal-based energy plants. Incremental improvements in existing plants will likely fall short of meeting future capacity and environmental needs economically. Thus, the implementation of new technologies at large scale is vital. In order to prepare for this inevitable paradigm shift, it is necessary to have viable alternatives that have been proven both theoretically and experimentally

344

Decentralized demand management for water distribution  

E-Print Network [OSTI]

. Actual Daily Demand for Model 2 . . 26 4 Predicted vs. Actual Peak Hourly Demand for Model 1 27 5 Predicted vs. Actual Peak Hourly Demand for Model 2 28 6 Cumulative Hourly Demand Distribution 7 Bryan Distribution Network 8 Typical Summer Diurnal... locating and controlling water that has not been accounted for. The Ford Meter Box Company (1987) advises the testing and recalibration of existing water meters. Because operating costs in a distribution network can be quite substantial, a significant...

Zabolio, Dow Joseph

2012-06-07T23:59:59.000Z

345

Demand Responsive Lighting: A Scoping Study  

E-Print Network [OSTI]

LBNL-62226 Demand Responsive Lighting: A Scoping Study F. Rubinstein, S. Kiliccote Energy Environmental Technologies Division January 2007 #12;LBNL-62226 Demand Responsive Lighting: A Scoping Study in this report was coordinated by the Demand Response Research Center and funded by the California Energy

346

Leveraging gamification in demand dispatch systems  

Science Journals Connector (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

347

Demand Response and Ancillary Services September 2008  

E-Print Network [OSTI]

Demand Response and Ancillary Services September 2008 #12;© 2008 EnerNOC, Inc. All Rights Reserved programs The purpose of this presentation is to offer insight into the mechanics of demand response and industrial demand response resources across North America in both regulated and restructured markets As of 6

348

THE STATE OF DEMAND RESPONSE IN CALIFORNIA  

E-Print Network [OSTI]

THE STATE OF DEMAND RESPONSE IN CALIFORNIA Prepared For: California Energy in this report. #12; ABSTRACT By reducing system loads during criticalpeak times, demand response can help reduce the threat of planned rotational outages. Demand response is also widely regarded as having

349

THE STATE OF DEMAND RESPONSE IN CALIFORNIA  

E-Print Network [OSTI]

THE STATE OF DEMAND RESPONSE IN CALIFORNIA Prepared For: California Energy in this report. #12; ABSTRACT By reducing system loads during criticalpeak times, demand response (DR) can.S. and internationally and lay out ideas that could help move California forward. KEY WORDS demand response, peak

350

Modeling Energy Demand Aggregators for Residential Consumers  

E-Print Network [OSTI]

The current world-wide increase of energy demand cannot be matched by energy production and power grid updateModeling Energy Demand Aggregators for Residential Consumers G. Di Bella, L. Giarr`e, M. Ippolito, A. Jean-Marie, G. Neglia and I. Tinnirello § January 2, 2014 Abstract Energy demand aggregators

Paris-Sud XI, Université de

351

Response to changes in demand/supply  

E-Print Network [OSTI]

Response to changes in demand/supply through improved marketing 21.2 #12;#12;111 Impacts of changes log demand in 1995. The composites board mills operating in Korea took advantage of flexibility environment changes on the production mix, some economic indications, statistics of demand and supply of wood

352

Response to changes in demand/supply  

E-Print Network [OSTI]

Response to changes in demand/supply through improved marketing 21.2 http with the mill consuming 450 000 m3 , amounting to 30% of total plywood log demand in 1995. The composites board, statistics of demand and supply of wood, costs and competitiveness were analysed. The reactions

353

Energy demand forecasting: industry practices and challenges  

Science Journals Connector (OSTI)

Accurate forecasting of energy demand plays a key role for utility companies, network operators, producers and suppliers of energy. Demand forecasts are utilized for unit commitment, market bidding, network operation and maintenance, integration of renewable ... Keywords: analytics, energy demand forecasting, machine learning, renewable energy sources, smart grids, smart meters

Mathieu Sinn

2014-06-01T23:59:59.000Z

354

Smart Buildings Using Demand Response March 6, 2011  

E-Print Network [OSTI]

Smart Buildings Using Demand Response March 6, 2011 Sila Kiliccote Deputy, Demand Response Division Lawrence Berkeley National Laboratory Demand Response Research Center 1 #12;Presentation Outline Demand Response Research Center ­ DRRC Vision and Research Portfolio Introduction to Demand

Kammen, Daniel M.

355

Multifamily Projects  

Broader source: Energy.gov [DOE]

Presents Energy Smart Colorado's approach to driving demand for multifamily residential energy efficiency upgrades.

356

Renewable Fuels Module  

Gasoline and Diesel Fuel Update (EIA)

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

357

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

358

Energy demand and population changes  

SciTech Connect (OSTI)

Since World War II, US energy demand has grown more rapidly than population, so that per capita consumption of energy was about 60% higher in 1978 than in 1947. Population growth and the expansion of per capita real incomes have led to a greater use of energy. The aging of the US population is expected to increase per capita energy consumption, despite the increase in the proportion of persons over 65, who consume less energy than employed persons. The sharp decline in the population under 18 has led to an expansion in the relative proportion of population in the prime-labor-force age groups. Employed persons are heavy users of energy. The growth of the work force and GNP is largely attributable to the growing participation of females. Another important consequence of female employment is the growth in ownership of personal automobiles. A third factor pushing up labor-force growth is the steady influx of illegal aliens.

Allen, E.L.; Edmonds, J.A.

1980-12-01T23:59:59.000Z

359

Assessing the impact of energy saving measures on the future energy demand and related GHG (greenhouse gas) emission reduction of Croatia  

Science Journals Connector (OSTI)

Abstract In the light of European energy-climate package and its measures for increasing security of supply, decreasing the impact on environment and stimulating sustainability, Croatia as a new EU (European Union) member state needs to reconsider and develop new energy policy towards energy efficiency and renewable energy sources. Croatian long-term energy demand and its effect on the future national GHG (greenhouse gas) emissions are analysed in this paper. For that purpose the NeD model was constructed (National energy demand model). The model is comprised out of six modules, each representing one sector: industry, transport, households, services, agriculture and construction. The model is based on bottom up approach. The analysis has shown that energy policy measures, identified through this paper, can potentially achieve energy savings up to 157PJ in the year 2050, which presents a 40% decrease to referent (frozen efficiency) scenario. Results obtained in this paper were also compared to the Croatian National Energy Strategy for the years 2020 and 2030. It was shown that if already implemented policies were properly taken into account the actual final energy demand for the year 2030 would be 43% lower than projected by the Croatian National Energy Strategy.

Tomislav Pukec; Brian Vad Mathiesen; Tomislav Novosel; Neven Dui?

2014-01-01T23:59:59.000Z

360

Electricity demand analysis - unconstrained vs constrained scenarios  

Science Journals Connector (OSTI)

In India, the electricity systems are chronically constrained by shortage of both capital and energy resources. These result in rationing and interruptions of supply with a severely disrupted electricity usage pattern. From this background, we try to analyse the demand patterns with and without resource constraints. Accordingly, it is necessary to model appropriately the dynamic nature of electricity demand, which cannot be captured by methods like annual load duration curves. Therefore, we use the concept - Representative Load Curves (RLCs) - to model the temporal and structural variations in demand. As a case study, the electricity system of the state of Karnataka in India is used. Four years demand data, two unconstrained and two constrained, are used and RLCs are developed using multiple discriminant analysis. It is found that these RLCs adequately model the variations in demand and bring out distinctions between unconstrained and constrained demand patterns. The demand analysis attempted here helped to study the differences in demand patterns with and without constraints, and the success of rationing measures in reducing demand levels as well as greatly disrupting the electricity usage patterns. Multifactor ANOVA analyses are performed to find out the statistical significance of the ability of logically obtained factors in explaining overall variations in demand. The results showed that the factors that are taken into consideration accounted for maximum variations in demand at very high significance levels.

P. Balachandra; V. Chandru; M.H. Bala Subrahmanya

2003-01-01T23:59:59.000Z

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

Projectivities and Projective Embeddings  

Science Journals Connector (OSTI)

In this chapter, we aim to prove some of the main achievements in the theory of generalized polygons. First, we want to show what the little projective group and the groups of projectivities of some Moufang po...

Hendrik van Maldeghem

1998-01-01T23:59:59.000Z

362

Secure Demand Shaping for Smart Grid On constructing probabilistic demand response schemes  

E-Print Network [OSTI]

Secure Demand Shaping for Smart Grid On constructing probabilistic demand response schemes. Developing novel schemes for demand response in smart electric gird is an increasingly active research area/SCADA for demand response in smart infrastructures face the following dilemma: On one hand, in order to increase

Sastry, S. Shankar

363

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

E-Print Network [OSTI]

that energy intensity is not necessarily a good indicator of energy efficiency, whereas by controllingUS 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

364

Project Overview  

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

Questions Keeler-Pennwalt Wood Pole Removal Line Projects Line Rebuild, Relocation and Substation Projects Spacer Damper Replacement Program Wind Projects Project Overview BPA...

365

Project Year Project Title  

E-Print Network [OSTI]

operators, matrix indexing, vector computations, loops, functions, and plotting graphs, among others basic arithmetic operators, matrix indexing, and vector computations in MATLAB. After creatingProject Year 2011-2012 Project Title Online Tutorial for MATLAB Project Team Eileen Haase, Whiting

Gray, Jeffrey J.

366

Project Year Project Team  

E-Print Network [OSTI]

Project Year 2005 Project Team Krysia Hudson, Faculty, School of Nursing, Undergraduate Instruction for Educational Resources Project Title Enhanced Web-based Learning Environments for Beginning Nursing Students (e.g., demonstrations of procedures or tasks) into the WBL systems, it will be possible to increase

Gray, Jeffrey J.

367

Project Year Project Team  

E-Print Network [OSTI]

Project Year 2002 Project Team Faculty: Michael McCloskey, Cognitive Science/Neuroscience, Krieger of Arts & Sciences Project Title Cognitive Neuropsychology Audience The initial audience to access. The current procedure calls for individual students or researchers to contact the faculty member

Gray, Jeffrey J.

368

Project Year Project Title  

E-Print Network [OSTI]

Project Year 2011-2012 Project Title Using M-Health and GIS Technology in the Field to Improve into teams and having each team use a different m-health data collection tool (e.g., cellular phones, smart health patterns. The Tech Fellow, Jacqueline Ferguson, will assist in creating an m-health project

Gray, Jeffrey J.

369

Project Year Project Team  

E-Print Network [OSTI]

Project Year 2002 Project Team Faculty: Gregory Hager, Computer Science, Whiting School of Engineering Fellow: Alan Chen, Biomedical Engineering, Whiting School of Engineering Project Title Robotics is complicated, time-consuming, and costly, making a robot for an introductory-level class is not practical

Gray, Jeffrey J.

370

Project Proposal Project Logistics  

E-Print Network [OSTI]

Project Proposal · Project Logistics: ­ 2-3 person teams ­ Significant implementation, worth 55 and anticipated cost of copying to/from host memory. IV. Intellectual Challenges - Generally, what makes this computation worthy of a project? - Point to any difficulties you anticipate at present in achieving high

Hall, Mary W.

371

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

372

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).

373

U.S. oil, natural gas demand still climbing  

SciTech Connect (OSTI)

Steady economic growth and slightly lower prices will boost demand for petroleum and natural gas in the US again this year. Economic growth will lag behind last year`s level but will remain strong. Increased worldwide petroleum production should lower oil prices and encourage fuel-switching, which will suppress natural gas prices. In the US, total energy consumption will grow less rapidly than economic activity due to continuing improvement in energy efficiency. US petroleum product demand will move up to 1.5% in 1997 to average 18.45 million b/d. And natural gas consumption will be up 0.7% at 22.05 tcf. Despite the oil price increases of 1996, US crude oil production will continue to slide in 1997; Oil and Gas Journal projects a drop of 1.1%. US production has been falling since 1985, except for a modest increase in 1991 related to the Persian Gulf War. The rate of decline has diminished in the past 2 years, but US crude oil production has still fall at an average rate of about 226,000 b/d/year since 1985. The paper discusses the economy, total energy consumption, the oil supply, imports, stocks, refining, refining margins and prices, demand for motor gasoline, jet fuel, distillate fuel, residual fuel oil, and other petroleum products, and natural gas demand and supply.

Beck, R.J.

1997-01-27T23:59:59.000Z

374

Pacific Northwest Smart Grid Demonstration Project SUCCESS STORIES  

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

advanced proven technologies and tested emerging technologies. Smart meters and demand response Before the project, more than 12,000, or nearly half, of Lower Valley's members...

375

Development of a demand defrost controller. Final report  

SciTech Connect (OSTI)

The purpose of this project was to develop and commercialize a demand defrost controller that initiates defrosts of refrigeration systems only when required. The standard method of control is a time clock that usually defrosts too often, which wastes energy. The controller developed by this project uses an algorithm based on the temperature difference between the discharge and return of the display case air curtain along with several time settings to defrost only when needed. This controller was field tested in a supermarket where it controlled defrost of the low-temperature display cases. According to test results the controller could reduce annual energy consumption by 20,000 and 62,000 kWh for hot gas and electric defrost, respectively. The controller saves electric demand as well as energy, is adaptable to ambient air conditions, and provides valuable savings throughout the year. The savings are greatest for low-temperature systems that use the most energy. A less tangible benefit of the demand controller is the improvement in food quality that results from fewer defrosts.

Borton, D.N. [Power Kinetics, Troy, NY (United States); Walker, D.H. [Foster-Miller, Inc., Waltham, MA (United States)

1993-10-01T23:59:59.000Z

376

Final report: Efficient thyratron modulator project  

SciTech Connect (OSTI)

The purpose of this program was to examine methods of increasing the efficiency of producing pulses to drive Klystrons in the 150 MW range. This may include 2 Klystrons in the 75 MW range. Specific methods of interest to improve the pulse efficiency were the use of a circuit to add energy to the tail of the pulse, the use of a bipyrimidal transformer, and the use of gas insulation as a means of improving the pulse shape. These methods were investigated using both thyratron and IGBT switching. The low cost designs developed in this work consisted of low voltage designs which don't require the oil immersion. These designs can be ''hot tuned'' based on the use of simple, tunable inductors.

R. J. Adler; R. J. Richter-Sand; C. W. Gregg

1999-11-26T23:59:59.000Z

377

OUTDOOR RECREATION DEMAND AND EXPENDITURES: LOWER SNAKE RIVER RESERVOIRS  

E-Print Network [OSTI]

i OUTDOOR RECREATION DEMAND AND EXPENDITURES: LOWER SNAKE RIVER RESERVOIRS John R. Mc . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . v SECTION ONE - OUTDOOR RECREATION DEMAND . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Recreation Demand Methods

O'Laughlin, Jay

378

LEED Demand Response Credit: A Plan for Research towards Implementation  

E-Print Network [OSTI]

C. McParland, Open Automated Demand Response Communicationsand Open Automated Demand Response", Grid Interop Forum,Testing of Automated Demand Response for Integration of

Kiliccote, Sila

2014-01-01T23:59:59.000Z

379

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

380

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

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

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

382

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

383

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

384

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

385

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

386

Modeling, Analysis, and Control of Demand Response Resources  

E-Print Network [OSTI]

advanced metering and demand response in electricityGoldman, and D. Kathan. Demand response in U.S. electricity29] DOE. Benefits of demand response in electricity markets

Mathieu, Johanna L.

2012-01-01T23:59:59.000Z

387

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

388

Opportunities, Barriers and Actions for Industrial Demand Response in California  

E-Print Network [OSTI]

13 Table 2. Demand Side Management Framework for IndustrialDR Strategies The demand-side management (DSM) frameworkpresented in Table 2. Demand Side Management Framework for

McKane, Aimee T.

2009-01-01T23:59:59.000Z

389

The Role of Demand Response in Default Service Pricing  

E-Print Network [OSTI]

THE ROLE OF DEMAND RESPONSE IN DEFAULT SERVICE PRICING Galenfor providing much-needed demand response in electricitycompetitive retail markets, demand response often appears to

Barbose, Galen; Goldman, Chuck; Neenan, Bernie

2006-01-01T23:59:59.000Z

390

The Role of Demand Response in Default Service Pricing  

E-Print Network [OSTI]

and coordinated by the Demand Response Research Center onThe Role of Demand Response in Default Service Pricing Galenfor providing much-needed demand response in electricity

Barbose, Galen; Goldman, Charles; Neenan, Bernie

2008-01-01T23:59:59.000Z

391

Linking Continuous Energy Management and Open Automated Demand Response  

E-Print Network [OSTI]

description of six energy and demand management concepts.how quickly it can modify energy demand. This is not a newimprovements in both energy efficiency and demand response (

Piette, Mary Ann

2009-01-01T23:59:59.000Z

392

India Energy Outlook: End Use Demand in India to 2020  

E-Print Network [OSTI]

Institute, Curbing Global Energy Demand Growth: The Energyup Assessment of Energy Demand in India Transportationa profound effect on energy demand. Policy analysts wishing

de la Rue du Can, Stephane

2009-01-01T23:59:59.000Z

393

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

394

Photovoltaic Energy Technology Module | Open Energy Information  

Open Energy Info (EERE)

Photovoltaic Energy Technology Module Photovoltaic Energy Technology Module Jump to: navigation, search Tool Summary Name: Photovoltaic Energy Technology Module Agency/Company /Organization: World Bank Sector: Energy Focus Area: Renewable Energy, Solar Topics: Technology characterizations Website: web.worldbank.org/WBSITE/EXTERNAL/TOPICS/EXTENERGY2/EXTRENENERGYTK/0,, References: Photovoltaic Energy Technology Module[1] Resources Portable Solar Photovoltaic Lanterns: Performance and Certification Specification, and Type Approval, ESMAP TECHNICAL PAPER 078 Testing of Storage Batteries used in Stand Alone Photovoltaic Power Systems, Test procedures and examples of test results Technical Specifications for Solar Home Systems (SHS), Rural Electrification and Renewable Energy Development (PV Component) Project

395

Transportation Energy Futures Series: Freight Transportation Demand: Energy-Efficient Scenarios for a Low-Carbon Future  

SciTech Connect (OSTI)

Freight transportation demand is projected to grow to 27.5 billion tons in 2040, and to nearly 30.2 billion tons in 2050. This report describes the current and future demand for freight transportation in terms of tons and ton-miles of commodities moved by truck, rail, water, pipeline, and air freight carriers. It outlines the economic, logistics, transportation, and policy and regulatory factors that shape freight demand, the trends and 2050 outlook for these factors, and their anticipated effect on freight demand. After describing federal policy actions that could influence future freight demand, the report then summarizes the capabilities of available analytical models for forecasting freight demand. This is one in a series of reports produced as a result of the Transportation Energy Futures project, a Department of Energy-sponsored multi-agency effort to pinpoint underexplored strategies for reducing GHGs and petroleum dependence related to transportation.

Grenzeback, L. R.; Brown, A.; Fischer, M. J.; Hutson, N.; Lamm, C. R.; Pei, Y. L.; Vimmerstedt, L.; Vyas, A. D.; Winebrake, J. J.

2013-03-01T23:59:59.000Z

396

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

397

The Retail Planning Problem under Demand Uncertainty.  

E-Print Network [OSTI]

and Rajaram K. , (2000), Accurate Retail Testing of FashionThe Retail Planning Problem Under Demand Uncertainty GeorgeAbstract We consider the Retail Planning Problem in which

Georgiadis, G.; Rajaram, K.

2012-01-01T23:59:59.000Z

398

Retail Demand Response in Southwest Power Pool  

E-Print Network [OSTI]

17 6. Barriers to Retail23 ii Retail Demand Response in SPP List of Figures and6 Table 3. SPP Retail DR Survey

Bharvirkar, Ranjit

2009-01-01T23:59:59.000Z

399

Coordination of Energy Efficiency and Demand Response  

E-Print Network [OSTI]

water heaters with embedded demand responsive controls can be designed to automatically provide day-ahead and real-time response

Goldman, Charles

2010-01-01T23:59:59.000Z

400

Distributed Automated Demand Response - Energy Innovation Portal  

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

Transmission Find More Like This Return to Search Distributed Automated Demand Response Lawrence Livermore National Laboratory Contact LLNL About This Technology...

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

Demand Response (transactional control) - Energy Innovation Portal  

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

Transmission Electricity Transmission Find More Like This Return to Search Demand Response (transactional control) Pacific Northwest National Laboratory Contact PNNL About...

402

Regulation Services with Demand Response - Energy Innovation...  

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

Regulation Services with Demand Response Pacific Northwest National Laboratory Contact PNNL About This Technology Using grid frequency information, researchers have created...

403

Topics in Residential Electric Demand Response.  

E-Print Network [OSTI]

??Demand response and dynamic pricing are touted as ways to empower consumers, save consumers money, and capitalize on the smart grid and expensive advanced meter (more)

Horowitz, Shira R.

2012-01-01T23:59:59.000Z

404

Maximum-Demand Rectangular Location Problem  

E-Print Network [OSTI]

Oct 1, 2014 ... Demand and service can be defined in the most general sense. ... Industrial and Systems Engineering, Texas A&M University, September 2014.

Manish Bansal

2014-10-01T23:59:59.000Z

405

Coupling Renewable Energy Supply with Deferrable Demand  

E-Print Network [OSTI]

in the presence of renewable resources and on the amount ofprimarily from renewable resources, and to a limited extentintegration of renewable resources and deferrable demand. We

Papavasiliou, Anthony

2011-01-01T23:59:59.000Z

406

Demand response exchange in a deregulated environment .  

E-Print Network [OSTI]

??This thesis presents the development of a new and separate market for trading Demand Response (DR) in a deregulated power system. This market is termed (more)

Nguyen, DT

2012-01-01T23:59:59.000Z

407

Demand response exchange in a deregulated environment.  

E-Print Network [OSTI]

??This thesis presents the development of a new and separate market for trading Demand Response (DR) in a deregulated power system. This market is termed (more)

Nguyen, DT

2012-01-01T23:59:59.000Z

408

Geographically Based Hydrogen Demand and Infrastructure Rollout...  

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

Rollout Scenario Analysis Geographically Based Hydrogen Demand and Infrastructure Rollout Scenario Analysis Presentation by Margo Melendez at the 2010-2025 Scenario Analysis for...

409

DOE Hydrogen Analysis Repository: HyDRA: Hydrogen Demand and Resource  

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

HyDRA: Hydrogen Demand and Resource Analysis Tool HyDRA: Hydrogen Demand and Resource Analysis Tool Project Summary Full Title: HyDRA: Hydrogen Demand and Resource Analysis Tool Project ID: 220 Principal Investigator: Johanna Levene Brief Description: HyDRA has evolved from a basic display of spatial data to a repository of over 100 datasets with dynamic data, querying, and interoperability with other models and spatial data repositories and over 350 registered users. Keywords: Hydrogen infrastructure; wind; solar; biomass; coal; natural gas Purpose Facilitate regional and geographical analyses of resources, demand, and infrastructure relevant to the implementation of hydrogen production, delivery, and dispensing. Performer Principal Investigator: Johanna Levene Organization: National Renewable Energy Laboratory (NREL)

410

The National Transport Code Collaboration Module Library  

Science Journals Connector (OSTI)

This paper reports on the progress in developing a library of code modules under the auspices of the National Transport Code Collaboration (NTCC). Code modules are high quality, fully documented software packages with a clearly defined interface. The modules provide a variety of functions, such as implementing numerical physics models; performing ancillary functions such as I/O or graphics; or providing tools for dealing with common issues in scientific programming such as portability of Fortran codes. Researchers in the plasma community submit code modules, and a review procedure is followed to insure adherence to programming and documentation standards. The review process is designed to provide added confidence with regard to the use of the modules and to allow users and independent reviews to validate the claims of the modules' authors. All modules include source code; clear instructions for compilation of binaries on a variety of target architectures; and test cases with well-documented input and output. All the NTCC modules and ancillary information, such as current standards and documentation, are available from the NTCC Module Library Website http://w3.pppl.gov/NTCC. The goal of the project is to develop a resource of value to builders of integrated modeling codes and to plasma physics researchers generally. Currently, there are more than 40 modules in the module library.

A.H. Kritz; G. Bateman; J. Kinsey; A. Pankin; T. Onjun; A. Redd; D. McCune; C. Ludescher; A. Pletzer; R. Andre; L. Zakharov; L. Lodestro; L.D. Pearlstein; R. Jong; W. Houlberg; P. Strand; J. Wiley; P. Valanju; H.St. John; R. Waltz; J. Mandrekas; T.K. Mau; J. Carlsson; B. Braams

2004-01-01T23:59:59.000Z

411

Economy and Electricity Demand Growth Linked but ƒƒƒ.  

Gasoline and Diesel Fuel Update (EIA)

Economy and Electricity Demand Economy and Electricity Demand Growth Linked but ... for International Utility Conference, Demand Trends Panel March 12, 2013 | London, UK by Adam Sieminski, Administrator U. S. electricity use and economic growth, 1950-2040 Adam Sieminski, EEI Demand Trends, March 12, 2013 2 -2% 0% 2% 4% 6% 8% 10% 12% 14% 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 Percent growth, 3-year rolling average Source: EIA, Annual Energy Outlook 2013 Early Release History Projections 2011 Electricity Use GDP 2.4% 0.9% 2011 - 2040 average Annual energy use of a new refrigerator, 1950-2008 Adam Sieminski, EEI Demand Trends, March 12, 2013 3 Kilowatthours per year Source: DOE / EERE - Building Technologies Office 0 200 400 600 800 1,000 1,200 1,400 1,600 1,800

412

A National Forum on Demand Response: Results on What Remains to Be Done to  

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

Cost-Effectiveness Working Group Cost-Effectiveness Working Group A National Forum on Demand Response: Results on What Remains to Be Done to Achieve Its Potential - Cost-Effectiveness Working Group In July 2011, the Federal Energy Regulatory Commission's (FERC) staff and the Department of Energy (DOE) jointly submitted to Congress a required "Implementation Proposal for the National Action Plan on Demand Response." The Implementation Proposal was for FERC's June 2010 National Action Plan for Demand Response. Part of the July 2011 Implementation Proposal called for a "National Forum" on demand response to be conducted by DOE and FERC. Given the rapid development of the demand response industry, DOE and FERC decided that a "virtual" project, in which state officials, industry

413

A National Forum on Demand Response: Results on What Remains to Be Done to  

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

Measurement and Verification Working Group Measurement and Verification Working Group A National Forum on Demand Response: Results on What Remains to Be Done to Achieve Its Potential - Measurement and Verification Working Group In July 2011, the Federal Energy Regulatory Commission's (FERC) staff and the Department of Energy (DOE) jointly submitted to Congress a required "Implementation Proposal for the National Action Plan on Demand Response." The Implementation Proposal was for FERC's June 2010 National Action Plan for Demand Response. Part of the July 2011 Implementation Proposal called for a "National Forum" on demand response to be conducted by DOE and FERC. Given the rapid development of the demand response industry, DOE and FERC decided that a "virtual" project, in which state officials, industry

414

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

415

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

416

FINAL DEMAND FORECAST FORMS AND INSTRUCTIONS FOR THE 2007  

E-Print Network [OSTI]

......................................................................... 11 3. Demand Side Management (DSM) Program Impacts................................... 13 4. Demand Sylvia Bender Manager DEMAND ANALYSIS OFFICE Scott W. Matthews Chief Deputy Director B.B. Blevins Forecast Methods and Models ....................................................... 14 5. Demand-Side

417

Introduction Due to the demand for efficiency in turbomachinery, the clearance between the casing and the blades  

E-Print Network [OSTI]

Introduction Due to the demand for efficiency in turbomachinery, the clearance between the casing of Turbomachinery Wear Simulations SURE 2011 Project by Grégoire Martin, supervised by Dr. Christophe Pierre and Dr

Barthelat, Francois

418

Development and Validation of Aggregated Models for Thermostatic Controlled Loads with Demand Response  

SciTech Connect (OSTI)

Demand response is playing an increasingly important role in smart grid research and technologies being examined in recently undertaken demonstration projects. The behavior of load as it is affected by various load control strategies is important to understanding the degree to which different classes of end-use load can contribute to demand response programs at various times. This paper focuses on developing aggregated control models for a population of thermostatically controlled loads. The effects of demand response on the load population dynamics are investigated.

Kalsi, Karanjit; Elizondo, Marcelo A.; Fuller, Jason C.; Lu, Shuai; Chassin, David P.

2012-01-04T23:59:59.000Z

419

Demand Response and Electric Grid Reliability  

E-Print Network [OSTI]

Demand Response and Electric Grid Reliability Paul Wattles Senior Analyst, Market Design & Development, ERCOT CATEE Conference, Galveston October 10, 2012 2 North American Bulk Power Grids CATEE Conference October 10, 2012 ? The ERCOT... adequacy ? ?Achieving more DR participation would . . . displace some generation investments, but would achieve the same level of reliability... ? ?Achieving this ideal requires widespread demand response and market structures that enable loads...

Wattles, P.

2012-01-01T23:59:59.000Z

420

DEMAND SIMULATION FOR DYNAMIC TRAFFIC ASSIGNMENT  

E-Print Network [OSTI]

of the response of travelers to real-time pre- trip information. The demand simulator is an extension of dynamicDEMAND SIMULATION FOR DYNAMIC TRAFFIC ASSIGNMENT Constantinos Antoniou, Moshe Ben-Akiva, Michel Bierlaire, and Rabi Mishalani Massachusetts Institute of Technology, Cambridge, MA 02139 Abstract

Bierlaire, Michel

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


421

A Vision of Demand Response - 2016  

SciTech Connect (OSTI)

Envision a journey about 10 years into a future where demand response is actually integrated into the policies, standards, and operating practices of electric utilities. Here's a bottom-up view of how demand response actually works, as seen through the eyes of typical customers, system operators, utilities, and regulators. (author)

Levy, Roger

2006-10-15T23:59:59.000Z

422

SUMMER 2007 ELECTRICITY SUPPLY AND DEMAND OUTLOOK  

E-Print Network [OSTI]

CALIFORNIA ENERGY COMMISSION SUMMER 2007 ELECTRICITY SUPPLY AND DEMAND OUTLOOK DRAFTSTAFFREPORT May ELECTRICITY ANALYSIS OFFICE Sylvia Bender Acting Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION B. B assessment of the capability of the physical electricity system to provide power to meet electricity demand

423

Incorporating Demand Response into Western Interconnection Transmission Planning  

E-Print Network [OSTI]

response DSM Demand Side Management EE energy efficiencywith the development of demand-side management (DSM)-related

Satchwell, Andrew

2014-01-01T23:59:59.000Z

424

Strategies for Demand Response in Commercial Buildings  

SciTech Connect (OSTI)

This paper describes strategies that can be used in commercial buildings to temporarily reduce electric load in response to electric grid emergencies in which supplies are limited or in response to high prices that would be incurred if these strategies were not employed. The demand response strategies discussed herein are based on the results of three years of automated demand response field tests in which 28 commercial facilities with an occupied area totaling over 11 million ft{sup 2} were tested. Although the demand response events in the field tests were initiated remotely and performed automatically, the strategies used could also be initiated by on-site building operators and performed manually, if desired. While energy efficiency measures can be used during normal building operations, demand response measures are transient; they are employed to produce a temporary reduction in demand. Demand response strategies achieve reductions in electric demand by temporarily reducing the level of service in facilities. Heating ventilating and air conditioning (HVAC) and lighting are the systems most commonly adjusted for demand response in commercial buildings. The goal of demand response strategies is to meet the electric shed savings targets while minimizing any negative impacts on the occupants of the buildings or the processes that they perform. Occupant complaints were minimal in the field tests. In some cases, ''reductions'' in service level actually improved occupant comfort or productivity. In other cases, permanent improvements in efficiency were discovered through the planning and implementation of ''temporary'' demand response strategies. The DR strategies that are available to a given facility are based on factors such as the type of HVAC, lighting and energy management and control systems (EMCS) installed at the site.

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

2006-06-20T23:59:59.000Z

425

Encryption-on-Demand, [EOD-g8516] Page #-1 Encryption-On-Demand  

E-Print Network [OSTI]

Encryption-on-Demand, [EOD-g8516] Page #-1 Encryption-On-Demand: Practical and Theoretical be served by an 'encryption-on-demand' (EoD) service which will enable them to communicate securely with no prior preparations, and no after effects. We delineate a possible EoD service, and describe some of its

426

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

427

Advanced Control Technologies and Strategies Linking DemandResponse and Energy Efficiency  

SciTech Connect (OSTI)

This paper presents a preliminary framework to describe how advanced controls can support multiple modes of operations including both energy efficiency and demand response (DR). A general description of DR, its benefits, and nationwide status is outlined. The role of energy management and control systems for DR is described. Building systems such as HVAC and lighting that utilize control technologies and strategies for energy efficiency are mapped on to DR and demand shedding strategies are developed. Past research projects are presented to provide a context for the current projects. The economic case for implementing DR from a building owner perspective is also explored.

Kiliccote, Sila; Piette, Mary Ann

2005-09-02T23:59:59.000Z

428

Demand Response This is the first of the Council's power plans to treat demand response as a resource.1  

E-Print Network [OSTI]

Demand Response This is the first of the Council's power plans to treat demand response the resource and describes some of the potential advantages and problems of the development of demand response. WHAT IS DEMAND RESPONSE? Demand response is a change in customers' demand for electricity corresponding

429

Project Year Project Team  

E-Print Network [OSTI]

; Ian Sims, Student, Electrical and Computer Engineering, Whiting School of Engineering Project Title and Jazz Theory/Keyboard I & II. Technologies Used Digital Audio, Digital Video, Graphic Design, HTML

Gray, Jeffrey J.

430

Health Care Demand, Empirical Determinants of  

Science Journals Connector (OSTI)

Abstract Economic theory provides a powerful but incomplete guide to the empirical determinants of health care demand. This article seeks to provide guidance on the selection and interpretation of demand determinants in empirical models. The author begins by introducing some general rules of thumb derived from economic and statistical principles. A brief review of the recent empirical literature next describes the range of current practices. Finally, a representative example of health care demand is developed to illustrate the selection, use, and interpretation of empirical determinants.

S.H. Zuvekas

2014-01-01T23:59:59.000Z

431

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.

432

Microsoft PowerPoint - FinalModule2.ppt  

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

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:

433

Demand Responsive Lighting: A Scoping Study  

E-Print Network [OSTI]

reduce greenhouse gas emissions. If advanced lightinggreenhouse gas emissions. ii Projected Impact of Wireless Lighting

Rubinstein, Francis; Kiliccote, Sila

2007-01-01T23:59:59.000Z

434

NCEP_Demand_Response_Draft_111208.indd  

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

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

435

National Action Plan on Demand Response  

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

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

436

Demand Controlled Ventilation and Classroom Ventilation  

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

437

China End-Use Energy Demand Modeling  

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

438

Software demonstration: Demand Response Quick Assessment Tool  

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

439

Power Consumption Analysis of Architecture on Demand  

Science Journals Connector (OSTI)

Abstract (40-Word Limit): Recently proposed Architecture on Demand (AoD) node shows considerable flexibility benefits against traditional ROADMs. We study the power consumption of AoD...

Garrich, Miquel; Amaya, Norberto; Zervas, Georgios; Giaccone, Paolo; Simeonidou, Dimitra

440

Integration of Demand Side Management, Distributed Generation...  

Open Energy Info (EERE)

States. Annex 8 provides a list of software tools for analysing various aspects of demand response, distributed generation, smart grid and energy storage. Annex 9 is a list of...

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

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...

Collins, J.

2008-01-01T23:59:59.000Z

442

SAN ANTONIO SPURS DEMAND FOR ENERGY EFFICIENCY  

Broader source: Energy.gov [DOE]

As a city that experiences seasonal spikes in energy demand and accompanying energy bills, San Antonio, Texas, wanted to help homeowners and businesses reduce their energy use and save on energy...

443

Volatile coal prices reflect supply, demand uncertainties  

SciTech Connect (OSTI)

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

444

Demand Controlled Ventilation and Classroom Ventilation  

E-Print Network [OSTI]

columnsindicatetheenergyandcostsavingsfor demandclasssize. (Theenergycosts ofclassroomventilationTotal Increase in Energy Costs ($) Increased State Revenue

Fisk, William J.

2014-01-01T23:59:59.000Z

445

Transportation energy demand: Model development and use  

Science Journals Connector (OSTI)

This paper describes work undertaken and sponsored by the Energy Commission to improve transportation energy demand forecasting and policy analysis for California. Two ... , the paper discusses some of the import...

Chris Kavalec

1998-06-01T23:59:59.000Z

446

Measuring the capacity impacts of demand response  

SciTech Connect (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

447

Real-Time Demand Side Energy Management  

E-Print Network [OSTI]

Real-Time Demand Side Energy Management Annelize Victor Michael Brodkorb Sr. Business Consultant Business Development Manager Aspen Technology, Inc. Aspen Technology Espaa, S.A. Houston, TX Barcelona, Spain ABSTRACT To remain... competitive, manufacturers must capture opportunities to increase bottom-line profitability. The goal of this paper is to present a new methodology for reducing energy costs Demand-Side Energy Management. Learn how process manufacturers assess energy...

Victor, A.; Brodkorb, M.

2006-01-01T23:59:59.000Z

448

Electric Utility Demand-Side Evaluation Methodologies  

E-Print Network [OSTI]

"::. ELECTRIC UTILITY DEMAND-SIDE EVALUATION METHODOLOGIES* Nat Treadway Public Utility Commission of Texas Austin, Texas ABSTRACT The electric. util ity industry's demand-side management programs can be analyzed ?from various points... of view using a standard benefit-cost methodology. The methodology now in use by several. electric utilities and the Public Utility Commlsslon of Texas includes measures of efficiency and equity. The nonparticipant test as a measure of equity...

Treadway, N.

449

Aviation fuel demand development in China  

Science Journals Connector (OSTI)

Abstract This paper analyzes the core factors and the impact path of aviation fuel demand in China and conducts a structural decomposition analysis of the aviation fuel cost changes and increase of the main aviation enterprises business profits. Through the establishment of an integrated forecast model for Chinas aviation fuel demand, this paper confirms that the significant rise in Chinas aviation fuel demand because of increasing air services demand is more than offset by higher aviation fuel efficiency. There are few studies which use a predictive method to decompose, estimate and analyze future aviation fuel demand. Based on a structural decomposition with indirect prediction, aviation fuel demand is decomposed into efficiency and total amount (aviation fuel efficiency and air transport total turnover). The core influencing factors for these two indexes are selected using path analysis. Then, univariate and multivariate models (ETS/ARIMA model and Bayesian multivariate regression) are used to analyze and predict both aviation fuel efficiency and air transport total turnover. At last, by integrating results, future aviation fuel demand is forecast. The results show that the aviation fuel efficiency goes up by 0.8% as the passenger load factor increases 1%; the air transport total turnover goes up by 3.8% and 0.4% as the urbanization rate and the per capita GDP increase 1%, respectively. By the end of 2015, Chinas aviation fuel demand will have increased to 28 million tonnes, and is expected to be 50 million tonnes by 2020. With this in mind, increases in the main aviation enterprises business profits must be achieved through the further promotion of air transport.

Jian Chai; Zhong-Yu Zhang; Shou-Yang Wang; Kin Keung Lai; John Liu

2014-01-01T23:59:59.000Z

450

2012 CERTS LAAR Program Peer Review - Frequency Response Demand - Jeff Dagle, PNNL  

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

Frequency Responsive Demand Frequency Responsive Demand Jeff Dagle, PE Chief Electrical Engineer Advanced Power & Energy Systems Pacific Northwest National Laboratory (509) 375-3629 jeff.dagle@pnl.gov CERTS Project Meeting Berkeley, CA September 20, 2012 Acknowledgements Montana Tech University MK Donnelly DJ Turdnowski S Mattix 2 Project Objective This project is evaluating the utilization of large numbers of small loads to provide spinning reserve The specific scope of this project is comparing the ability of load to provide equivalent primary frequency response that would be available from conventional generation 3 Utilizing Small Loads for Frequency Responsive Reserves in a Large System Model Objectives: Credible analysis of the feasibility of using load as a frequency responsive

451

Ethanol Demand in United States Gasoline Production  

SciTech Connect (OSTI)

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

452

Performance analysis of demand planning approaches for aggregating, forecasting and disaggregating interrelated demands  

Science Journals Connector (OSTI)

A synchronized and responsive flow of materials, information, funds, processes and services is the goal of supply chain planning. Demand planning, which is the very first step of supply chain planning, determines the effectiveness of manufacturing and logistic operations in the chain. Propagation and magnification of the uncertainty of demand signals through the supply chain, referred to as the bullwhip effect, is the major cause of ineffective operation plans. Therefore, a flexible and robust supply chain forecasting system is necessary for industrial planners to quickly respond to the volatile demand. Appropriate demand aggregation and statistical forecasting approaches are known to be effective in managing the demand variability. This paper uses the bivariate VAR(1) time series model as a study vehicle to investigate the effects of aggregating, forecasting and disaggregating two interrelated demands. Through theoretical development and systematic analysis, guidelines are provided to select proper demand planning approaches. A very important finding of this research is that disaggregation of a forecasted aggregated demand should be employed when the aggregated demand is very predictable through its positive autocorrelation. Moreover, the large positive correlation between demands can enhance the predictability and thus result in more accurate forecasts when statistical forecasting methods are used.

Argon Chen; Jakey Blue

2010-01-01T23:59:59.000Z

453

Project Fact Sheet Project Brief  

E-Print Network [OSTI]

Project Fact Sheet Project Brief: Construction Project Team: Project Facts & Figures: Budget: £1.1M Funding Source: Departmental Construction Project Programme: Start on Site: November 2010 End Date : March 2011 Occupation Date: March 2011 For further information contact Project Manager as listed above

454

Project Fact Sheet Project Update  

E-Print Network [OSTI]

Project Fact Sheet Project Update: Project Brief: The works cover the refurbishment of floors 4, 5 operating theatre. The Bionanotechnology Centre is one of the projects funded from the UK Government's £20.imperial.ac.uk/biomedeng Construction Project Team: Project Facts & Figures: Budget: £13,095,963 Funding Source: SRIF II and Capital

455

Project Fact Sheet Project Brief  

E-Print Network [OSTI]

Project Fact Sheet Project Brief: This project refurbished half of the 5th and 7th floors on the Faculty of Medicine, please visit: http://www1.imperial.ac.uk/medicine/ Construction Project Team: Project Facts & Figures: Budget: £3,500,000 Funding Source: SRIF III Construction Project Programme: Start

456

An Operational Model for Optimal NonDispatchable Demand Response  

E-Print Network [OSTI]

An Operational Model for Optimal NonDispatchable Demand Response for Continuous PowerintensiveFACTS, $ Demand Response Energy Storage HVDC Industrial Customer PEV Renewable Energy Source: U.S.-Canada Power: To balance supply and demand of a power system, one can manipulate both: supply and demand demand response

Grossmann, Ignacio E.

457

Project Year Project Team  

E-Print Network [OSTI]

An Engineer's Guide to the Structures of Baltimore Audience Students from the Krieger School of Arts City, interfaced through a course website, the team will integrate descriptions of structural behavior format. Technologies Used HTML/Web Design, MySQL Project Abstract Structural analysis is typically taught

Gray, Jeffrey J.

458

Project Year Project Team  

E-Print Network [OSTI]

information systems (GIS) tools to design maps that integrate data for visualizing geographic concepts School of Engineering Project Title GIS & Introductory Geography Audience Undergraduate students on how to use the Internet for geographic research, and an interactive introduction to GIS through online

Gray, Jeffrey J.

459

Project Management Project Managment  

E-Print Network [OSTI]

­ Inspired by agile methods #12;Background · Large-scale software development & IT projects, plagued relations #12;One Agile Approach to Scheduling · The creative nature of game development resist heavy up Problems ­incompatible platforms, 3rd party etc. #12;Is Games Development Similar? · Yes & No

Stephenson, Ben

460

Findings from the 2004 Fully Automated Demand Response Tests in Large  

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

the 2004 Fully Automated Demand Response Tests in Large the 2004 Fully Automated Demand Response Tests in Large Facilities Title Findings from the 2004 Fully Automated Demand Response Tests in Large Facilities Publication Type Report LBNL Report Number LBNL-58178 Year of Publication 2005 Authors Piette, Mary Ann, David S. Watson, Naoya Motegi, and Norman Bourassa Date Published 10/18/2005 Keywords market sectors, technologies Abstract This report describes the results of the second season of research to develop and evaluate the performance of new Automated Demand Response (Auto-DR) hardware and software technology in large facilities. Demand Response (DR) is a set of time dependant activities that reduce or shift electricity use to improve electric grid reliability, manage electricity costs, and provide systems that encourage load shifting or shedding during times when the electric grid is near its capacity or electric prices are high. Demand Response is a subset of demand side management, which also includes energy efficiency and conservation. The overall goal of this research project was to support increased penetration of DR in large facilities through the use of automation and better understanding of DR technologies and strategies in large facilities. To achieve this goal, a set of field tests were designed and conducted. These tests examined the performance of Auto-DR systems that covered a diverse set of building systems, ownership and management structures, climate zones, weather patterns, and control and communication configurations.

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


461

Standard Review Plan (SRP) Modules | Department of Energy  

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

Quality Assurance » Standard Quality Assurance » Standard Review Plan (SRP) Modules Standard Review Plan (SRP) Modules Standard Review Plan - Critical Decision Handbook Overview Project Management Project Execution Plan Review Module (RM) Risk Management RM Integrated Project Team RM Earned Value Management System RM Acquisition Strategy RM Decommissioning Plan RM Site Transition Guidance Engineering and Design Conceptual Design RM Preliminary Design RM Final Design RM Construction Readiness RM Checkout, Testing, and Commissioning Plan RM Readiness Review RM Seismic Design Expectations Report Technology Readiness Assessment Report External Technical Review Report Preparation for Facility Operations RM Safety Safety Design Strategy RM Conceptual Safety Design RM Preliminary Safety Design RM Facility Disposition Safety Strategy RM

462

Informedia Experience-on-Demand: Capturing, Integrating and Communicating Experiences across People, Time and Space  

E-Print Network [OSTI]

an initial prototype of the EOD system. KEYWORDS Multimedia information systems; audio, video and location content analysis INTRODUCTION The Informedia Experience-on-Demand Project (EOD) develops tools, techniques information systems in operational situations to remote crisis managers in coordinating roles. Personal EOD

Wactlar, Howard D.

463

An Upload Bandwidth Threshold for Peer-to-Peer Video-on-Demand Scalability  

E-Print Network [OSTI]

.perino@orange-ftgroup.com Laurent Viennot INRIA Project-Team "GANG" between INRIA and LIAFA, France. laurent a static allocation of m = (n) videos into the boxes such that any adversarial sequence of video demands Author manuscript, published in "23rd IEEE International Parallel and Distributed Processing Symposium

Paris-Sud XI, Université de

464

Public Interest Energy Research (PIER) Program FINAL PROJECT REPORT  

E-Print Network [OSTI]

, and project oversight. Integrated Combined Heat and Power Systems Corporation, Gearoid Foley for the Combined Heat and Power project (Contr INTEGRATED COOLING, HEATING AND ENGINE POWER MODULE FEBRUARY 2010 CEC5002009098 Prepared for: California

465

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":""}]}

466

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

467

Coordination of Retail Demand Response with Midwest ISO Markets  

E-Print Network [OSTI]

LABORATORY Coordination of Retail Demand Response withXXXXX Coordination of Retail Demand Response with MidwestAC02-05CH11231. Coordination of Retail Demand Response with

Bharvirkar, Ranjit

2008-01-01T23:59:59.000Z

468

Analysis of Open Automated Demand Response Deployments in California  

E-Print Network [OSTI]

LBNL-6560E Analysis of Open Automated Demand Response Deployments in California and Guidelines The work described in this report was coordinated by the Demand Response Research. #12; #12;Abstract This report reviews the Open Automated Demand Response

469

PIER: Demand Response Research Center Director, Mary Ann Piette  

E-Print Network [OSTI]

1 PIER: Demand Response Research Center Director, Mary Ann Piette Program Development and Outreach Response Research Plan #12;2 Demand Response Research Center Objective Scope Stakeholders Develop, prioritize, conduct and disseminate multi- institutional research to facilitate Demand Response. Technologies

470

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

471

Demand Response Enabling Technologies and Approaches for Industrial Facilities  

E-Print Network [OSTI]

, there are also huge opportunities for demand response in the industrial sector. This paper describes some of the demand response initiatives that are currently active in New York State, explaining applicability of industrial facilities. Next, we discuss demand...

Epstein, G.; D'Antonio, M.; Schmidt, C.; Seryak, J.; Smith, C.

2005-01-01T23:59:59.000Z

472

LEED Demand Response Credit: A Plan for Research towards Implementation  

E-Print Network [OSTI]

DRs growing role in demand-side management activities andhow DR fits with demand-side management activities, DRemissions rates The demand-side management (DSM) framework

Kiliccote, Sila

2014-01-01T23:59:59.000Z

473

Coordination of Retail Demand Response with Midwest ISO Markets  

E-Print Network [OSTI]

Data Collection for Demand-side Management for QualifyingPrepared by Demand-side Management Task Force of the4. Status of Demand Side Management in Midwest ISO 5.

Bharvirkar, Ranjit

2008-01-01T23:59:59.000Z

474

A Survey on Privacy in Residential Demand Side Management Applications  

Science Journals Connector (OSTI)

Demand Side Management (DSM) is an auspicious concept for ... on privacy energy issues and potential solutions in Demand Response systems. For this we give an ... the BSI and indicate three technical types of Demand

Markus Karwe; Jens Strker

2014-01-01T23:59:59.000Z

475

Demand-Side Management and Energy Efficiency Revisited  

E-Print Network [OSTI]

EPRI). 1984. Demand Side Management. Vol. 1:Overview of Key1993. Industrial Demand-Side Management Programs: WhatsJ. Kulick. 2004. Demand side management and energy e?ciency

Auffhammer, Maximilian; Blumstein, Carl; Fowlie, Meredith

2007-01-01T23:59:59.000Z

476

Commercial Fleet Demand for Alternative-Fuel Vehicles in California  

E-Print Network [OSTI]

Precursors of demand for alternative-fuel vehicles: resultsFLEET DEMAND FOR ALTERNATIVE-FUEL VEHICLES IN CALIFORNIA*AbstractFleet demand for alternative-fuel vehicles (AFVs

Golob, Thomas F; Torous, Jane; Bradley, Mark; Brownstone, David; Crane, Soheila Soltani; Bunch, David S

1996-01-01T23:59:59.000Z

477

California Baseline Energy Demands to 2050 for Advanced Energy Pathways  

E-Print Network [OSTI]

ED2, September. CEC (2005b) Energy demand forecast methodsCalifornia Baseline Energy Demands to 2050 for Advancedof a baseline scenario for energy demand in California for a

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

2008-01-01T23:59:59.000Z

478

Behavioral Aspects in Simulating the Future US Building Energy Demand  

E-Print Network [OSTI]

Importance Total off- site energy demand (2030) 20% decreaseImportance Total off-site energy demand (2030) 20% decreaseImportance Total off-site energy demand (2030) 20% decrease

Stadler, Michael

2011-01-01T23:59:59.000Z

479

Energy Demands and Efficiency Strategies in Data Center Buildings  

E-Print Network [OSTI]

iv Chapter 5: National energy demand and potential energyAs Figure 1-2 shows, HVAC energy demand is comparable to thefor reducing this high energy demand reaches beyond

Shehabi, Arman

2010-01-01T23:59:59.000Z

480

Project Accounts  

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

» Project Accounts » Project Accounts Project Accounts Overview Project accounts are designed to facilitate collaborative computing by allowing multiple users to use the same account. All actions performed by the project account are traceable back to the individual who used the project account to perform those actions via gsisshd accounting logs. Requesting a Project Account PI's, PI proxies and project managers are allowed to request a project account. In NIM do "Actions->Request a Project Account" and fill in the form. Select the repository that the Project Account is to use from the drop-down menu, "Sponsoring Repository". Enter the name you want for the account (8 characters maximum) and a description of what you will use the account for and then click on the "Request Project Account" button. You

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

NERSC Modules Software Environment  

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

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

482

Construction Project Safety and Health Plan RM  

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

Construction Project Safety and Construction Project Safety and Health Plan Review Module March 2010 CD-0 Co 0 Le OFFICE O onstructi CD-1 This Review ssons learned f OF ENVIRO Standard ion Proje Rev Critical D CD-2 M w Module has b from the pilot h ONMENTA Review Pla ect Safety view Modul Decision (CD CD March 2010 been piloted at have been inco AL MANAG an (SRP) y and He le D) Applicabili D-3 the INL IWTU orporated in Re GEMENT alth Plan ity CD-4 U Project. eview Module. n Post Ope eration Standard Review Plan, 2 nd Edition, March 2010 i FOREWORD The Standard Review Plan (SRP) 1 provides a consistent, predictable corporate review framework to ensure that issues and risks that could challenge the success of Office of Environmental Management (EM) projects are identified early and addressed proactively. The internal EM

483

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

484

International Oil Supplies and Demands. Volume 1  

SciTech Connect (OSTI)

The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--90 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world`s dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group`s thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

Not Available

1991-09-01T23:59:59.000Z

485

Energy demand simulation for East European countries  

Science Journals Connector (OSTI)

The analysis and created statistical models of energy consumption tendencies in the European Union (EU25), including new countries in transition, are presented. The EU15 market economy countries and countries in transition are classified into six clusters by relative indicators of Gross Domestic Product (GDP/P) and energy demand (W/P) per capita. The specified statistical models of energy intensity W/GDP non-linear stochastic tendencies have been discovered with respect to the clusters of classified countries. The new energy demand simulation models have been developed for the demand management in time??territory hierarchy in various scenarios of short-term and long-term perspective on the basis of comparative analysis methodology. The non-linear statistical models were modified to GDP, W/P and electricity (E/P) final consumption long-term forecasts for new associated East European countries and, as an example, for the Baltic Countries, including Lithuania.

Jonas Algirdas Kugelevicius; Algirdas Kuprys; Jonas Kugelevicius

2007-01-01T23:59:59.000Z

486

International Oil Supplies and Demands. Volume 2  

SciTech Connect (OSTI)

The eleventh Energy Modeling Forum (EMF) working group met four times over the 1989--1990 period to compare alternative perspectives on international oil supplies and demands through 2010 and to discuss how alternative supply and demand trends influence the world`s dependence upon Middle Eastern oil. Proprietors of eleven economic models of the world oil market used their respective models to simulate a dozen scenarios using standardized assumptions. From its inception, the study was not designed to focus on the short-run impacts of disruptions on oil markets. Nor did the working group attempt to provide a forecast or just a single view of the likely future path for oil prices. The model results guided the group`s thinking about many important longer-run market relationships and helped to identify differences of opinion about future oil supplies, demands, and dependence.

Not Available

1992-04-01T23:59:59.000Z

487

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":""}]}

488

Enhanced heat transfer for thermionic power modules  

SciTech Connect (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

489

Project Fact Sheet Project Update  

E-Print Network [OSTI]

Project Fact Sheet Project Update: Project Brief: A state of the art facility, at Hammersmith information visit the Faculty of Medicine web pages http://www1.imperial.ac.uk/medicine/ Construction Project Team: Project Facts & Figures: Budget: £60 000 000 Funding Source: SRIF II (Imperial College), GSK, MRC

490

Project Fact Sheet Project Update  

E-Print Network [OSTI]

Project Fact Sheet Project Update: Project Brief: The refurbishment of the instrumentation equipment. This project encompasses refurbishment work on over 1,150m2 of laboratory space across four, the completed project will allow researchers to expand their work in satellite instrumentation, the fabrication

491

Project Fact Sheet Project Brief  

E-Print Network [OSTI]

Project Fact Sheet Project Brief: In the first phase of the Union Building re.union.ic.ac.uk/marketing/building Construction Project Team: Project Facts & Figures: Budget: £1,400,000 Funding Source: Capital Plan and Imperial College Union reserves Construction Project Programme: Start on Site: August 2006 End Date: March

492

Modulational effects in accelerators  

SciTech Connect (OSTI)

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

Satogata, T.

1997-12-01T23:59:59.000Z

493

Volume Project  

E-Print Network [OSTI]

Math 13900. Volume Project. For the following project, you may use any materials. This must be your own original creation. Construct a right pyramid with a base...

rroames

2010-01-12T23:59:59.000Z

494

Rice Supply, Demand and Related Government Programs.  

E-Print Network [OSTI]

, 1930-55 Year Weighted Year Weighted beginning average price beginning average price August per cwt. August per cwt. Dollars Dollars 'Includes an allowance for unredeemed loans. response to the strengthening of foreign demand, rice prices by 1952... 91 percent of the average parity price during 1935-54, with !he 4 years of World War I1 omitted. The elasticity of demand was assumed to be about -.2. The annually derived price based on the assumed elasticity and the percentage change in price...

Kincannon, John A.

1957-01-01T23:59:59.000Z

495

Demand Response Initiatives at CPS Energy  

E-Print Network [OSTI]

Demand Response Initiatives at CPS Energy Clean Air Through Energy Efficiency (CATEE) Conference December 17, 2013 ESL-KT-13-12-53 CATEE 2013: Clean Air Through Energy Efficiency Conference, San Antonio, Texas Dec. 16-18 CPSEs DR Program DR... than the military bases and Toyota combined. Schools & Universities contributed 6 MWs of Demand Response in 2013. 2013 DR Participants Trinity University - $5,654 Fort Sam ISD - $18,860 Judson ISD - $45,540 Alamo Colleges - $98,222 UTSA - $168...

Luna, R.

2013-01-01T23:59:59.000Z

496

Demand Response and Smart Metering Policy Actions Since the Energy...  

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

Demand Response and Smart Metering Policy Actions Since the Energy Policy Act of 2005: A Summary for State Officials Demand Response and Smart Metering Policy Actions Since the...

497

Overview of Demand Side Response | Department of Energy  

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

and Energy Officials Need to Know High Electric Demand Days: Clean Energy Strategies for Improving Air Quality Demand Response in U.S. Electricity Markets: Empirical Evidence...

498

Robust Unit Commitment Problem with Demand Response and ...  

E-Print Network [OSTI]

Oct 29, 2010 ... sion, both Demand Response (DR) strategy and intermittent renewable ... Key Words: unit commitment, demand response, wind energy, robust...

2010-10-31T23:59:59.000Z

499

National Action Plan on Demand Response | Department of Energy  

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

National Action Plan on Demand Response National Action Plan on Demand Response Presentation-given at the Federal Utility Partnership Working Group (FUPWG) Fall 2008...

500

ASSESSMENT OF VARIABLE EFFECTS OF SYSTEMS WITH DEMAND RESPONSE RESOURCES  

E-Print Network [OSTI]

ASSESSMENT OF VARIABLE EFFECTS OF SYSTEMS WITH DEMAND RESPONSE RESOURCES BY ANUPAMA SUNIL KOWLI B of consumers - called demand response resources (DRRs) - whose role has become increasingly important

Gross, George