National Library of Energy BETA

Sample records for demand ten end-use

  1. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    N ATIONAL L ABORATORY India Energy Outlook: End Use DemandTables Figures Figure 1. India Primary Energy Supply by fuel33 Table 15. India Industry Energy Intensities (GJ/

  2. India Energy Outlook: End Use Demand in India to 2020

    SciTech Connect (OSTI)

    de la Rue du Can, Stephane; McNeil, Michael; Sathaye, Jayant

    2009-03-30

    Integrated economic models have been used to project both baseline and mitigation greenhouse gas emissions scenarios at the country and the global level. Results of these scenarios are typically presented at the sectoral level such as industry, transport, and buildings without further disaggregation. Recently, a keen interest has emerged on constructing bottom up scenarios where technical energy saving potentials can be displayed in detail (IEA, 2006b; IPCC, 2007; McKinsey, 2007). Analysts interested in particular technologies and policies, require detailed information to understand specific mitigation options in relation to business-as-usual trends. However, the limit of information available for developing countries often poses a problem. In this report, we have focus on analyzing energy use in India in greater detail. Results shown for the residential and transport sectors are taken from a previous report (de la Rue du Can, 2008). A complete picture of energy use with disaggregated levels is drawn to understand how energy is used in India and to offer the possibility to put in perspective the different sources of end use energy consumption. For each sector, drivers of energy and technology are indentified. Trends are then analyzed and used to project future growth. Results of this report provide valuable inputs to the elaboration of realistic energy efficiency scenarios.

  3. Renewable Electricity Futures Study Volume 3: End-Use Electricity Demand

    Broader source: Energy.gov [DOE]

    This volume details the end-use electricity demand and efficiency assumptions. The projection of electricity demand is an important consideration in determining the extent to which a predominantly renewable electricity future is feasible. Any scenario regarding future electricity use must consider many factors, including technological, sociological, demographic, political, and economic changes (e.g., the introduction of new energy-using devices; gains in energy efficiency and process improvements; changes in energy prices, income, and user behavior; population growth; and the potential for carbon mitigation).

  4. Energy Demand: Limits on the Response to Higher Energy Prices in the End-Use Sectors (released in AEO2007)

    Reports and Publications (EIA)

    2007-01-01

    Energy consumption in the end-use demand sectorsresidential, commercial, industrial, and transportationgenerally shows only limited change when energy prices increase. Several factors that limit the sensitivity of end-use energy demand to price signals are common across the end-use sectors. For example, because energy generally is consumed in long-lived capital equipment, short-run consumer responses to changes in energy prices are limited to reductions in the use of energy services or, in a few cases, fuel switching; and because energy services affect such critical lifestyle areas as personal comfort, medical services, and travel, end-use consumers often are willing to absorb price increases rather than cut back on energy use, especially when they are uncertain whether price increases will be long-lasting. Manufacturers, on the other hand, often are able to pass along higher energy costs, especially in cases where energy inputs are a relatively minor component of production costs. In economic terms, short-run energy demand typically is inelastic, and long-run energy demand is less inelastic or moderately elastic at best.

  5. Evaluation of consumer demand for selected end-use markets for cotton 

    E-Print Network [OSTI]

    Viator, Catherine Longman

    2000-01-01

    The U.S. cotton industry is facing a rapidly diminishing share of the domestic and foreign textile markets. To become more competitive in these markets, the textile industry should know where consumer demand is being directed. The objectives...

  6. Renewable Electricity Futures Study. Volume 3. End-Use Electricity Demand

    SciTech Connect (OSTI)

    Hostick, Donna; Belzer, David B.; Hadley, Stanton W.; Markel, Tony; Marnay, Chris; Kintner-Meyer, Michael

    2012-06-15

    The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a future through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%–90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT). Learn more at the RE Futures website. http://www.nrel.gov/analysis/re_futures/

  7. Renewable Electricity Futures Study. Volume 3: End-Use Electricity Demand

    SciTech Connect (OSTI)

    Hostick, D.; Belzer, D.B.; Hadley, S.W.; Markel, T.; Marnay, C.; Kintner-Meyer, M.

    2012-06-01

    The Renewable Electricity Futures (RE Futures) Study investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. The analysis focused on the sufficiency of the geographically diverse U.S. renewable resources to meet electricity demand over future decades, the hourly operational characteristics of the U.S. grid with high levels of variable wind and solar generation, and the potential implications of deploying high levels of renewables in the future. RE Futures focused on technical aspects of high penetration of renewable electricity; it did not focus on how to achieve such a future through policy or other measures. Given the inherent uncertainties involved with analyzing alternative long-term energy futures as well as the multiple pathways that might be taken to achieve higher levels of renewable electricity supply, RE Futures explored a range of scenarios to investigate and compare the impacts of renewable electricity penetration levels (30%-90%), future technology performance improvements, potential constraints to renewable electricity development, and future electricity demand growth assumptions. RE Futures was led by the National Renewable Energy Laboratory (NREL) and the Massachusetts Institute of Technology (MIT).

  8. Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity;

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963Residential Consumers (Number of33 2,297 809 245 15504 End Uses of

  9. End Use and Fuel Certification

    Broader source: Energy.gov [DOE]

    Breakout Session 2: Frontiers and Horizons Session 2–B: End Use and Fuel Certification John Eichberger, Vice President of Government Relations, National Association for Convenience Stores

  10. End-Use Sector Flowchart

    Broader source: Energy.gov [DOE]

    This system of energy intensity indicators for total energy covers the economy as a whole and each of the major end-use sectors—transportation, industry, commercial and residential—identified in Figure 1. By clicking on any of the boxes with the word "Sector" in the title will reveal the more detailed structure within that sector.

  11. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    2006. “All India Electricity Statistics, General Review2005, “Industrial Statistics of India: Status and Issues”,is reported in India’s national statistics for this sector,

  12. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    Past Trend and Future Outlook",LBNL forthcoming. de la Rue2006. “Building up India: Outlook for India’s real estate”,2006a. “World Energy Outlook”, IEA/OECD, Paris, France.

  13. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    rural, k=Kerosene m=rural, k=biogas m =urban, k=LPG m=urban,k=LPG k=wood k=kerosene k=biogas k=electricity k=electricity

  14. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    of oil use for the need of LPG and kerosene for cooking andSector PJ Fuel Oil Diesel Oil LPG Electricity Source: CEA,PJ) PJ fuel oil diesel LPG electricity Energy consumption is

  15. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    Tables Figures Figure 1. India Primary Energy Supply by fuel7 Figure 2. Final and Primary Energy (including biomass) by19 Figure 10. Final and Primary Energy Consumption in the

  16. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    Efficiency in Electricity Consumption", HWWA Discussionelectricity includes electricity consumption plus thedistribution. Total electricity consumption represents 1,654

  17. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    Crises & Climate Challenges - 30 Years of Energy Use in IEACountries”, IEA/OECD, Paris, France. International Energy2006a. “World Energy Outlook”, IEA/OECD, Paris, France.

  18. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    Technology for Indian Pulp and Paper Industry” Newsletter ofwith 13% and the pulp and paper industry with 9%. Similarly,and Paper The Indian pulp and paper industry is the sixth

  19. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    for cooking and lighting. Biomass energy consumption willused in an economy, biomass energy consumption is certainlyby a large share of biomass energy use representing 50% of

  20. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    7 Figure 3. Energy Consumption in the Agriculture Sector (13 Figure 6. Energy Consumption in the ServiceFinal and Primary Energy Consumption in the Industry Sector,

  1. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    Statistics and Programme Implementation published a condensed version of statics related to energy production and consumption (

  2. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    2002, “TEDDY: TERI’s energy data directory and yearbook2006. “TEDDY: TERI’s energy data directory and yearbookU.S. DOE, 2006, “Buildings Energy Data Book 2006”, September

  3. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    Petroleum pricing in India: balancing efficiency andand Tables Figures Figure 1. India Primary Energy Supply by28 Table 13. India, US and France Farm Machinery

  4. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    same activities that require energy today will continue toaccounting of how energy is consumed today. For each sector,

  5. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    2005a. “Statistics of the Indian Paper Industry: Directoryof Indian Paper Industry”. Volume II. Saharanpur, India. de2005. “The Indian Paper Industry: Towards Sustainability”,

  6. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    and 6 million diesel irrigation pump sets in operation (rural areas, pump sets are installed to provide irrigation

  7. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    5% of its reserve is coking coal used by the steel industry.imports around 70% of coking coal annually. More recently,

  8. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    Diesel, 18% Primary Electricity Diesel, 49% Electricty,51% Electricty Data Adjustment Electricity consumption from

  9. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    gas oil nuclear hydro Energy output Own Uses Transmissiongas oil nuclear hydro Energy output Own Uses Transmissionenergy equivalence of electricity generated from hydro or

  10. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    photovoltaic water pumping systems since 1993- 94. About 7,000 pump set were installed with a capacity

  11. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    of 43% of total oil consumption. The residential sectorrepresenting 63% and oil consumption representing the rest.the diesel and fuel oil consumption are included, the total

  12. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    pumps in India”, Renewable and Sustainable Energy Reviews,Renewable Energy (MNES), 2008. “Annual Report 2007-08”. Government of India.

  13. India Energy Outlook: End Use Demand in India to 2020

    E-Print Network [OSTI]

    de la Rue du Can, Stephane

    2009-01-01

    first electricity distribution and transmission (T&D)Own Uses Transmission and distribution losses ElectricityOwn Uses Transmission and distribution loses Electricity

  14. End-use taxes: Current EIA practices

    SciTech Connect (OSTI)

    Not Available

    1994-08-17

    There are inconsistencies in the EIA published end-use price data with respect to Federal, state, and local government sales and excise taxes; some publications include end-use taxes and others do not. The reason for including these taxes in end-use energy prices is to provide consistent and accurate information on the total cost of energy purchased by the final consumer. Preliminary estimates are made of the effect on prices (bias) reported in SEPER (State Energy Price and Expenditure Report) resulting from the inconsistent treatment of taxes. EIA has undertaken several actions to enhance the reporting of end-use energy prices.

  15. Healthcare Energy End-Use Monitoring

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

    Healthcare Energy End-Use Monitoring Michael Sheppy, Shanti Pless, and Feitau Kung National Renewable Energy Laboratory Technical Report NRELTP-5500-61064 August 2014 NREL is a...

  16. Alabama Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"OmahaEnergy Sources and End Uses Topics: Energy Sources and End Uses End-UseA 6 J 9 U B u o f l53DecadeVehicle

  17. Alaska Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"OmahaEnergy Sources and End Uses Topics: Energy Sources and End Uses End-UseA 6 J 9 U BEstimatedSales (Billion342,261

  18. Arizona Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"OmahaEnergy Sources and End Uses Topics: Energy Sources and End Uses End-UseA 6 J 9Cubic Feet) Oil1369,739 330,914

  19. Arkansas Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"OmahaEnergy Sources and End Uses Topics: Energy Sources and End Uses End-UseA 6 J 9CubicFeet)

  20. Preliminary CBECS End-Use Estimates

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

    For the past three CBECS (1989, 1992, and 1995), we used a statistically-adjusted engineering (SAE) methodology to estimate end-use consumption. The core of the SAE methodology...

  1. Energy end-use intensities in commercial buildings

    SciTech Connect (OSTI)

    Not Available

    1994-09-01

    This report examines energy intensities in commercial buildings for nine end uses: space heating, cooling, ventilation, lighting, water heating, cooking, refrigeration, office equipment, and other. The objective of this analysis was to increase understanding of how energy is used in commercial buildings and to identify targets for greater energy efficiency which could moderate future growth in demand. The source of data for the analysis is the 1989 Commercial Buildings Energy Consumption survey (CBECS), which collected detailed data on energy-related characteristics and energy consumption for a nationally representative sample of approximately 6,000 commercial buildings. The analysis used 1989 CBECS data because the 1992 CBECS data were not yet available at the time the study was initiated. The CBECS data were fed into the Facility Energy Decision Screening (FEDS) system, a building energy simulation program developed by the US Department of Energy`s Pacific Northwest Laboratory, to derive engineering estimates of end-use consumption for each building in the sample. The FEDS estimates were then statistically adjusted to match the total energy consumption for each building. This is the Energy Information Administration`s (EIA) first report on energy end-use consumption in commercial buildings. This report is part of an effort to address customer requests for more information on how energy is used in buildings, which was an overall theme of the 1992 user needs study. The end-use data presented in this report were not available for publication in Commercial Buildings Energy Consumption and Expenditures 1989 (DOE/EIA-0318(89), Washington, DC, April 1992). However, subsequent reports on end-use energy consumption will be part of the Commercial Buildings Energy Consumption and Expenditures series, beginning with a 1992 data report to be published in early 1995.

  2. Healthcare Energy End-Use Monitoring

    Office of Energy Efficiency and Renewable Energy (EERE)

    This report describes the NREL partnership with two hospitals (MGH and SUNY UMU) to collect data on the energy used for multiple thermal and electrical end-use categories, which can be used to more effectively prioritize and refine the scope of investments in new metering and energy audits.

  3. Biomass Resource Allocation among Competing End Uses

    SciTech Connect (OSTI)

    Newes, E.; Bush, B.; Inman, D.; Lin, Y.; Mai, T.; Martinez, A.; Mulcahy, D.; Short, W.; Simpkins, T.; Uriarte, C.; Peck, C.

    2012-05-01

    The Biomass Scenario Model (BSM) is a system dynamics model developed by the U.S. Department of Energy as a tool to better understand the interaction of complex policies and their potential effects on the biofuels industry in the United States. However, it does not currently have the capability to account for allocation of biomass resources among the various end uses, which limits its utilization in analysis of policies that target biomass uses outside the biofuels industry. This report provides a more holistic understanding of the dynamics surrounding the allocation of biomass among uses that include traditional use, wood pellet exports, bio-based products and bioproducts, biopower, and biofuels by (1) highlighting the methods used in existing models' treatments of competition for biomass resources; (2) identifying coverage and gaps in industry data regarding the competing end uses; and (3) exploring options for developing models of biomass allocation that could be integrated with the BSM to actively exchange and incorporate relevant information.

  4. Detailed End Use Load Modeling for Distribution System Analysis

    SciTech Connect (OSTI)

    Schneider, Kevin P.; Fuller, Jason C.

    2010-04-09

    The field of distribution system analysis has made significant advances in the past ten years. It is now standard practice when performing a power flow simulation to use an algorithm that is capable of unbalanced per-phase analysis. Recent work has also focused on examining the need for time-series simulations instead of examining a single time period, i.e., peak loading. One area that still requires a significant amount of work is the proper modeling of end use loads. Currently it is common practice to use a simple load model consisting of a combination of constant power, constant impedance, and constant current elements. While this simple form of end use load modeling is sufficient for a single point in time, the exact model values are difficult to determine and it is inadequate for some time-series simulations. This paper will examine how to improve simple time invariant load models as well as develop multi-state time variant models.

  5. Healthcare Energy End-Use Monitoring

    SciTech Connect (OSTI)

    Sheppy, M.; Pless, S.; Kung, F.

    2014-08-01

    NREL partnered with two hospitals (MGH and SUNY UMU) to collect data on the energy used for multiple thermal and electrical end-use categories, including preheat, heating, and reheat; humidification; service water heating; cooling; fans; pumps; lighting; and select plug and process loads. Additional data from medical office buildings were provided for an analysis focused on plug loads. Facility managers, energy managers, and engineers in the healthcare sector will be able to use these results to more effectively prioritize and refine the scope of investments in new metering and energy audits.

  6. " Row: End Uses;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of34 End3.

  7. " Row: End Uses;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of34 End3.7

  8. " Row: End Uses;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of34 End3.78

  9. " Row: End Uses;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of34

  10. " Row: End Uses;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of348 End

  11. " Row: End Uses;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of348 End7

  12. " Row: End Uses;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of348 End78

  13. Office Buildings - End-Use Equipment

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal, Nuclear,DecadeYear Jan FebElements)Feet) Decade8 45YearYearEnd-Use

  14. Realizing Building End-Use Efficiency with Ermerging Technologies

    Office of Energy Efficiency and Renewable Energy (EERE)

    Information about the implementation of emerging technologies to maximize end-use efficiency in buildings.

  15. GridLAB-D Technical Support Document: Residential End-Use Module Version 1.0

    SciTech Connect (OSTI)

    Taylor, Zachary T.; Gowri, Krishnan; Katipamula, Srinivas

    2008-07-31

    1.0 Introduction The residential module implements the following end uses and characteristics to simulate the power demand in a single family home: • Water heater • Lights • Dishwasher • Range • Microwave • Refrigerator • Internal gains (plug loads) • House (heating/cooling loads) The house model considers the following four major heat gains/losses that contribute to the building heating/cooling load: 1. Conduction through exterior walls, roof and fenestration (based on envelope UA) 2. Air infiltration (based on specified air change rate) 3. Solar radiation (based on CLTD model and using tmy data) 4. Internal gains from lighting, people, equipment and other end use objects. The Equivalent Thermal Parameter (ETP) approach is used to model the residential loads and energy consumption. The following sections describe the modeling assumptions for each of the above end uses and the details of power demand calculations in the residential module.

  16. Utah Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal,Demand Module of theCubicEstimation Results forExtensions44 1,045Year

  17. Vermont Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal,Demand Module of theCubicEstimation ResultsYear JanYearDay)Year Jan Feb

  18. Virginia Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal,Demand Module of theCubicEstimation ResultsYearYear JanSalesYear Jan

  19. Washington Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal,Demand Module of theCubicEstimation10,428 285,726 264,589 264,540 318,292

  20. Wisconsin Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal,Demand Module of6,090 7,163 10,532 14,881 23,209DecadeFeet)087,066

  1. Monitoring of Electrical End-Use Loads in Commercial Buildings 

    E-Print Network [OSTI]

    Martinez, M.; Alereza, T.; Mort, D.

    1988-01-01

    custom-designed to facilitate collection and validation of the end-use load data. For example, the Load Profile Viewer is a PC-based software program for reviewing and validating the end-use load data....

  2. Engineer End Uses for Maximum Efficiency; Industrial Technologies...

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

    specified by the manufacturer, and the air going to all end uses should be free of condensate to maximize tool life and effectiveness. 6 End uses having similar air requirements...

  3. Energy End-Use Intensities in Commercial Buildings1992 -- Overview/End-Use

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun Jul1998,(Million CubicEnd1995 End-Use

  4. Energy End-Use Intensities in Commercial Buildings

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

    Estimates The end-use estimates had two main sources: the 1989 Commercial Buildings Energy Consumption Survey (CBECS) and the Facility Energy Decision Screening (FEDS) system....

  5. Opportunities for Energy Efficiency and Demand Response in the California Cement Industry

    E-Print Network [OSTI]

    Olsen, Daniel

    2012-01-01

    Opportunities for Energy  Efficiency and Demand Response in Agricultural/Water End?Use Energy Efficiency Program.    i 1   4.0   Energy Efficiency and Demand Response 

  6. Energy End-Use Intensities in Commercial Buildings

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

    as buildings of the 1980's. In this section, intensities are based upon the entire building stock, not just those buildings using a particular fuel for a given end use. This...

  7. United States Industrial Sector Energy End Use Analysis

    E-Print Network [OSTI]

    Shehabi, Arman

    2014-01-01

    by end uses (e.g. , boilers, process, electric drives,MECS 2002, and MECS 1998 data. Indirect Uses-Boiler FuelConventional Boiler Use CHP and/or Cogeneration Process

  8. Residential Behavioral Savings: An Analysis of Principal Electricity End Uses in British Columbia

    E-Print Network [OSTI]

    Tiedemann, Kenneth Mr.

    2013-01-01

    of residential end use electricity consumption for Britishresidential electricity consumption by end use Apply theresidential end use electricity consumption using a

  9. 2 Large CO2 reductions via offshore wind power matched to inherent 3 storage in energy end-uses

    E-Print Network [OSTI]

    Firestone, Jeremy

    2 Large CO2 reductions via offshore wind power matched to inherent 3 storage in energy end-uses 4 by matching the winds of the 14 Middle-Atlantic Bight (MAB) to energy demand in the 15 adjacent states] We develop methods for assessing offshore wind 9 resources, using a model of the vertical structure

  10. Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity;

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963Residential Consumers (Number of33 2,297 809 245 1550473 Number

  11. Level: National and Regional Data; Row: End Uses; Column: Energy Sources, including Net Demand for Electricity;

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963Residential Consumers (Number of33 2,297 809 245 1550473 Number Next

  12. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3 End Uses

  13. Refining and End Use Study of Coal Liquids

    SciTech Connect (OSTI)

    1997-10-01

    This report summarizes revisions to the design basis for the linear programing refining model that is being used in the Refining and End Use Study of Coal Liquids. This revision primarily reflects the addition of data for the upgrading of direct coal liquids.

  14. Industrial Steam Power Cycles Final End-Use Classification 

    E-Print Network [OSTI]

    Waterland, A. F.

    1983-01-01

    Final end uses of steam include two major classifications: those uses that condense the steam against heat transfer surfaces to provide heat to an item of process or service equipment; and those that require a mass flow of steam for stripping...

  15. REFINING AND END USE STUDY OF COAL LIQUIDS

    SciTech Connect (OSTI)

    Unknown

    2002-01-01

    This document summarizes all of the work conducted as part of the Refining and End Use Study of Coal Liquids. There were several distinct objectives set, as the study developed over time: (1) Demonstration of a Refinery Accepting Coal Liquids; (2) Emissions Screening of Indirect Diesel; (3) Biomass Gasification F-T Modeling; and (4) Updated Gas to Liquids (GTL) Baseline Design/Economic Study.

  16. Healthcare Energy: Using End-Use Data to Inform Decisions | Department...

    Energy Savers [EERE]

    Using End-Use Data to Inform Decisions Healthcare Energy: Using End-Use Data to Inform Decisions The Building Technologies Office conducted a healthcare energy end-use monitoring...

  17. United States Industrial Sector Energy End Use Analysis

    SciTech Connect (OSTI)

    Shehabi, Arman; Morrow, William R.; Masanet, Eric

    2012-05-11

    The United States Department of Energy’s (DOE) Energy Information Administration (EIA) conducts the Manufacturing Energy Consumption Survey (MECS) to provide detailed data on energy consumption in the manufacturing sector. The survey is a sample of approximately 15,000 manufacturing establishments selected from the Economic Census - Manufacturing Sector. MECS provides statistics on the consumption of energy by end uses (e.g., boilers, process, electric drives, etc.) disaggregated by North American Industry Classification System (NAICS) categories. The manufacturing sector (NAICS Sector 31-33) consists of all manufacturing establishments in the 50 States and the District of Columbia. According to the NAICS, the manufacturing sector comprises establishments engaged in the mechanical, physical, or chemical transformation of materials, substances, or components into new products. The establishments are physical facilities such as plants, factories, or mills. For many of the sectors in the MECS datasets, information is missing because the reported energy use is less than 0.5 units or BTUs, or is withheld to avoid disclosing data for individual establishments, or is withheld because the standard error is greater than 50%. We infer what the missing information likely are using several approximations techniques. First, much of the missing data can be easily calculated by adding or subtracting other values reported by MECS. If this is not possible (e.g. two data are missing), we look at historic MECS reports to help identify the breakdown of energy use in the past and assume it remained the same for the current MECS. Lastly, if historic data is also missing, we assume that 3 digit NAICS classifications predict energy use in their 4, 5, or 6 digit NAICS sub-classifications, or vice versa. Along with addressing data gaps, end use energy is disaggregated beyond the specified MECS allocations using additional industry specific energy consumption data. The result is a completed table of energy end use by sector with mechanical drives broken down by pumps, fans, compressed air, and drives.

  18. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of Fuel

  19. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of Fuel3.

  20. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of Fuel3.4.

  1. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of Fuel3.4.1

  2. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of

  3. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3 End

  4. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3 End1 End

  5. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3 End1

  6. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3 End13

  7. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3 End134

  8. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3 End1341

  9. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3 End13412

  10. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3

  11. " Row: End Uses within NAICS Codes;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of34 End

  12. Table 5.3 End Uses of Fuel Consumption, 2010;

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)Decade Year-0 Year-1 Year-2Feet)Thousand7,Year Jan995 1555.3 End Uses of Fuel

  13. Table 5.4 End Uses of Fuel Consumption, 2010;

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)Decade Year-0 Year-1 Year-2Feet)Thousand7,Year Jan995 1555.3 End Uses of

  14. Table 5.5 End Uses of Fuel Consumption, 2010;

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)Decade Year-0 Year-1 Year-2Feet)Thousand7,Year Jan995 1555.3 End Uses of5 End

  15. Table 5.6 End Uses of Fuel Consumption, 2010;

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)Decade Year-0 Year-1 Year-2Feet)Thousand7,Year Jan995 1555.3 End Uses of5

  16. Table 5.7 End Uses of Fuel Consumption, 2010;

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)Decade Year-0 Year-1 Year-2Feet)Thousand7,Year Jan995 1555.3 End Uses of57

  17. Table 5.8 End Uses of Fuel Consumption, 2010;

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)Decade Year-0 Year-1 Year-2Feet)Thousand7,Year Jan995 1555.3 End Uses of578

  18. Energy End-Use Intensities in Commercial Buildings 1989 -- Executive

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun Jul1998,(Million CubicEnd Use:‹Home

  19. The Role of Demand Response Policy Forum Series

    E-Print Network [OSTI]

    California at Davis, University of

    The Role of Demand Response Policy Forum Series Beyond 33 Percent: California's Renewable Future and Demand Response #12;Historic focus on Seasonal Grid Stress PG&E Demand Bid Test Day 0 2000 4000 6000 8000 Communication Latency #12;Bottom Up Review of End-Use Loads for Demand Response 5 Commercial Residential

  20. Demand Reduction

    Office of Energy Efficiency and Renewable Energy (EERE)

    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...

  1. Residential sector end-use forecasting with EPRI-Reeps 2.1: Summary input assumptions and results

    SciTech Connect (OSTI)

    Koomey, J.G.; Brown, R.E.; Richey, R.

    1995-12-01

    This paper describes current and projected future energy use by end-use and fuel for the U.S. residential sector, and assesses which end-uses are growing most rapidly over time. The inputs to this forecast are based on a multi-year data compilation effort funded by the U.S. Department of Energy. We use the Electric Power Research Institute`s (EPRI`s) REEPS model, as reconfigured to reflect the latest end-use technology data. Residential primary energy use is expected to grow 0.3% per year between 1995 and 2010, while electricity demand is projected to grow at about 0.7% per year over this period. The number of households is expected to grow at about 0.8% per year, which implies that the overall primary energy intensity per household of the residential sector is declining, and the electricity intensity per household is remaining roughly constant over the forecast period. These relatively low growth rates are dependent on the assumed growth rate for miscellaneous electricity, which is the single largest contributor to demand growth in many recent forecasts.

  2. Modeling of End-Use Energy Profile: An Appliance-Data-Driven Stochastic Approach

    E-Print Network [OSTI]

    Kang, Zhaoyi; Jin, Ming; Spanos, Costas J

    2014-01-01

    Demand side management: Demand response, intelligent energydesigning building demand-response system [5]. The Bottom-up

  3. West Virginia Natural Gas Consumption by End Use

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames5 Tables July 1996 Energy Information Administration Office of Coal,Demand Module of theCubicEstimation10,428 (Million20Decade Year-009,652

  4. Opportunities, Barriers and Actions for Industrial Demand Response in

    E-Print Network [OSTI]

    LBNL-1335E Opportunities, Barriers and Actions for Industrial Demand Response in California A.T. Mc of Global Energy Partners. This work described in this report was coordinated by the Demand Response Demand Response in California. PIER Industrial/Agricultural/Water EndUse Energy Efficiency Program. CEC

  5. Residential Behavioral Savings: An Analysis of Principal Electricity End Uses in British Columbia

    E-Print Network [OSTI]

    Tiedemann, Kenneth Mr.

    2013-01-01

    Fowlie. 2007. Demand-Side Management and Energy Efficiencyand building shells. Demand side management programs have

  6. The Value of End-Use Energy Efficiency in Mitigation of U.S. Carbon Emissions

    SciTech Connect (OSTI)

    Kyle, G. Page; Smith, Steven J.; Clarke, Leon E.; Kim, Son H.; Wise, Marshall A.

    2007-11-27

    This report documents a scenario analysis exploring the value of advanced technologies in the U.S. buildings, industrial, and transportation sectors in stabilizing atmospheric greenhouse gas concentrations. The analysis was conducted by staff members of Pacific Northwest National Laboratory (PNNL), working at the Joint Global Change Research Institute (JGCRI) in support of the strategic planning process of the U.S. Department of Energy (U.S. DOE) Office of Energy Efficiency and Renewable Energy (EERE). The conceptual framework for the analysis is an integration of detailed buildings, industrial, and transportation modules into MiniCAM, a global integrated assessment model. The analysis is based on three technology scenarios, which differ in their assumed rates of deployment of new or presently available energy-saving technologies in the end-use sectors. These technology scenarios are explored with no carbon policy, and under two CO2 stabilization policies, in which an economic price on carbon is applied such that emissions follow prescribed trajectories leading to long-term stabilization of CO2 at roughly 450 and 550 parts per million by volume (ppmv). The costs of meeting the emissions targets prescribed by these policies are examined, and compared between technology scenarios. Relative to the reference technology scenario, advanced technologies in all three sectors reduce costs by 50% and 85% for the 450 and 550 ppmv policies, respectively. The 450 ppmv policy is more stringent and imposes higher costs than the 550 ppmv policy; as a result, the magnitude of the economic value of energy efficiency is four times greater for the 450 ppmv policy than the 550 ppmv policy. While they substantially reduce the costs of meeting emissions requirements, advanced end-use technologies do not lead to greenhouse gas stabilization without a carbon policy. This is due mostly to the effects of increasing service demands over time, the high consumption of fossil fuels in the electricity sector, and the use of unconventional feedstocks in the liquid fuel refining sector. Of the three end-use sectors, advanced transportation technologies have the greatest potential to reduce costs of meeting carbon policy requirements. Services in the buildings and industrial sectors can often be supplied by technologies that consume low-emissions fuels such as biomass or, in policy cases, electricity. Passenger transportation, in contrast, is especially unresponsive to climate policies, as the fuel costs are small compared to the time value of transportation and vehicle capital and operating costs. Delaying the transition from reference to advanced technologies by 15 years increases the costs of meeting 450 ppmv stabilization emissions requirements by 21%, but the costs are still 39% lower than the costs assuming reference technology. The report provides a detailed description of the end-use technology scenarios and provides a thorough analysis of the results. Assumptions are documented in the Appendix.

  7. Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Demand for Electricity;

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963Residential Consumers (Number of33 2,297 809 245 1550

  8. Letter Report on Testing of Distributed Energy Resource, Microgrid, and End-Use

    E-Print Network [OSTI]

    Letter Report on Testing of Distributed Energy Resource, Microgrid, and End-Use Efficiency of Distributed Energy Resource, Microgrid, and End Use Efficiency Technologies (Task 8) This completes Under Cooperative Agreement No. DE-FC26-06NT42847 Hawai`i Distributed Energy Resource Technologies

  9. Utility Sector Impacts of Reduced Electricity Demand

    SciTech Connect (OSTI)

    Coughlin, Katie

    2014-12-01

    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.

  10. Investigation of structural changes in residential electricity demand

    SciTech Connect (OSTI)

    Chern, W.S.; Bouis, H.E.

    1982-09-23

    The purpose of this study was to investigate the stability of aggregate national residential electricity demand coefficients over time. The hypothesis is maintained that the aggregate residential demand is the sum of various end-use demand components. Since the end-use composition changes over time, the demand relationship may change as well. Since the end-use composition differs among regions, the results obtained from this study can be used for making inferences about regional differences in electricity demand relationships. There are two additional sources for a possible structural change. One is that consumers may react differently to declining and rising prices, secondly, the impact of the 1973 oil embargo may have shifted demand preferences. The electricity demand model used for this study is presented. A moving regression method was employed to investigate changes in residential electricity demand over time. The statistical results show a strikingly consistent pattern of change for most of the structural variables. The most important finding of this study is that the estimated structure of residential electricity demand changes systematically over time as a result of changes in the characteristics (both durability and saturation level) of the stock of appliances. Furthermore, there is not strong evidence that the structural changes in demand occurred due to either the reversal of the declining trend of electricity prices or the impact of the 1973 oil embarge. (LCL)

  11. InDemandInDemandInDemand Energize Your Career

    E-Print Network [OSTI]

    Wolberg, George

    InDemandInDemandInDemand Energize Your Career You can join the next generation of workers who in Energy #12;#12;In Demand | 1 No, this isn't a quiz...but if you answered yes to any or all and Training Administration wants you to have this publication, In Demand: Careers in Energy. It will let you

  12. VideoonDemandVideoonDemandVideoonDemand Video on Demand Testbed

    E-Print Network [OSTI]

    Eleftheriadis, Alexandros

    VideoonDemandVideoonDemandVideoonDemand Columbia's Video on Demand Testbed and Interoperability Experiment Columbia's Video on Demand Testbed and Interoperability Experiment S.-F. Chang and A Columbia UniversityColumbia University www.www.ctrctr..columbiacolumbia..eduedu/advent/advent #12;VideoonDemandVideoonDemandVideoonDemand

  13. VideoonDemandVideoonDemandVideoonDemand Video on Demand Testbed

    E-Print Network [OSTI]

    Eleftheriadis, Alexandros

    #12;VideoonDemandVideoonDemandVideoonDemand Columbia's Video on Demand Testbed and Interoperability Experiment Columbia's Video on Demand Testbed and Interoperability Experiment H.H. KalvaKalva, A.www.eeee..columbiacolumbia..eduedu/advent/advent #12;VideoonDemandVideoonDemandVideoonDemand VoD Testbed ArchitectureVoD Testbed Architecture Video

  14. Efficient Multi-Level Modeling and Monitoring of End-use Energy Profile in Commercial Buildings

    E-Print Network [OSTI]

    Kang, Zhaoyi

    2015-01-01

    buildings”. In: Energy Efficiency 5.2 (2012), pp. 149–162. [Sys- tems for Energy-Efficiency in Buildings. ACM. 2011, pp.Efficient Multi-Level Modeling and Monitoring of End-use

  15. Estimates of Energy Consumption by Building Type and End Use at U.S. Army Installations

    E-Print Network [OSTI]

    Konopacki, S.J.

    2010-01-01

    4. Figure 5-5. 1993 Electricity Consumption Estimates by EndkWh/ft ) 1993 Electricity Consumption Estimates by End Useof Total) 1993 Electricity Consumption Estimates by End Use

  16. ,"U.S. Distillate Fuel Oil and Kerosene Sales by End Use"

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

    Distillate Fuel Oil and Kerosene Sales by End Use" ,"Click worksheet name or tab at bottom for data" ,"Worksheet Name","Description"," Of Series","Frequency","Latest Data for"...

  17. 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

  18. Alternative Proofs of Ten Inequalities

    E-Print Network [OSTI]

    Adilsultan Lepes

    2014-12-06

    This article offers different proofs of ten inequalities from those already published. So that the readers can see for themselves, the tasks specified in the condition of the source and classical inequalities which used in previously published proofs.

  19. Greening Multi-Tenant Data Center Demand Response Niangjun Chen

    E-Print Network [OSTI]

    Ren, Shaolei

    Greening Multi-Tenant Data Center Demand Response Niangjun Chen , Xiaoqi Ren , Shaolei Ren , Adam resources for emergency demand response (EDR). However, currently, data centers typically participate in EDR. In this paper, we focus on "greening" demand response in multi-tenant data centers by incentivizing ten- ants

  20. Projecting Electricity Demand in 2050

    SciTech Connect (OSTI)

    Hostick, Donna J.; Belzer, David B.; Hadley, Stanton W.; Markel, Tony; Marnay, Chris; Kintner-Meyer, Michael CW

    2014-07-01

    This paper describes the development of end-use electricity projections and load curves that were developed for the Renewable Electricity (RE) Futures Study (hereafter RE Futures), which explored the prospect of higher percentages (30% ? 90%) of total electricity generation that could be supplied by renewable sources in the United States. As input to RE Futures, two projections of electricity demand were produced representing reasonable upper and lower bounds of electricity demand out to 2050. The electric sector models used in RE Futures required underlying load profiles, so RE Futures also produced load profile data in two formats: 8760 hourly data for the year 2050 for the GridView model, and in 2-year increments for 17 time slices as input to the Regional Energy Deployment System (ReEDS) model. The process for developing demand projections and load profiles involved three steps: discussion regarding the scenario approach and general assumptions, literature reviews to determine readily available data, and development of the demand curves and load profiles.

  1. 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

  2. Impacts of Temperature Variation on Energy Demand in Buildings (released in AEO2005)

    Reports and Publications (EIA)

    2005-01-01

    In the residential and commercial sectors, heating and cooling account for more than 40% of end-use energy demand. As a result, energy consumption in those sectors can vary significantly from year to year, depending on yearly average temperatures.

  3. ,"South Carolina Natural Gas Consumption by End Use"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008Wellhead PriceConsumption by End Use" ,"ClickConsumption by End Use"

  4. ,"South Dakota Natural Gas Consumption by End Use"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008Wellhead PriceConsumption by End Use"Summary"Consumption by End Use"

  5. Advanced Demand Responsive Lighting

    E-Print Network [OSTI]

    Advanced Demand Responsive Lighting Host: Francis Rubinstein Demand Response Research Center demand responsive lighting systems ­ Importance of dimming ­ New wireless controls technologies · Advanced Demand Responsive Lighting (commenced March 2007) #12;Objectives · Provide up-to-date information

  6. Ten Year Site Plans | Department of Energy

    Energy Savers [EERE]

    Ten Year Site Plans Ten Year Site Plans A Ten Year Site Plan (TYSP) is the essential planning document linking a site's real property requirements to its mission in support of the...

  7. Addressing Energy Demand through Demand Response. International Experiences and Practices

    SciTech Connect (OSTI)

    Shen, Bo; Ghatikar, Girish; Ni, Chun Chun; Dudley, Junqiao; Martin, Phil; Wikler, Greg

    2012-06-01

    Demand response (DR) is a load management tool which provides a cost-effective alternative to traditional supply-side solutions to address the growing demand during times of peak electrical load. According to the US Department of Energy (DOE), demand response reflects “changes in electric usage by end-use customers from their normal consumption patterns in response to changes in the price of electricity over time, or to incentive payments designed to induce lower electricity use at times of high wholesale market prices or when system reliability is jeopardized.” 1 The California Energy Commission (CEC) defines DR as “a reduction in customers’ electricity consumption over a given time interval relative to what would otherwise occur in response to a price signal, other financial incentives, or a reliability signal.” 2 This latter definition is perhaps most reflective of how DR is understood and implemented today in countries such as the US, Canada, and Australia where DR is primarily a dispatchable resource responding to signals from utilities, grid operators, and/or load aggregators (or DR providers).

  8. A functional analysis of electrical load curve modelling for some households specific electricity end-uses

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    domestic end-uses, the development of plug-in hybrid and electric vehicles, the increase of heat pumps heating systems such as heat pumps in new building or which will replace old installed fossil fuels based influences: · best building insulation which will reduce the energy needs for heating and cooling; · new

  9. Wood stove use in the end-use load and consumer assessment program residential base sample

    SciTech Connect (OSTI)

    LeBaron, B.A.

    1988-11-01

    This report examines wood heating in the End-Use Load and Consumer Assessment Program (ELCAP) Residential Base Sample during the 1985/1986 heating season. The goals of this study were to assess the frequency of wood burning in homes having wood burning equipment and to estimate the quantity of electrical space heat displaced by it use. 15 refs., 18 figs., 6 tabs.

  10. Electricity end-use efficiency: Experience with technologies, markets, and policies throughout the world

    SciTech Connect (OSTI)

    Levine, M.D.; Koomey, J.; Price, L. [Lawrence Berkeley Lab., CA (United States); Geller, H.; Nadel, S. [American Council for an Energy-Efficient Economy, Washington, DC (United States)

    1992-03-01

    In its August meeting in Geneva, the Energy and Industry Subcommittee (EIS) of the Policy Response Panel of the Intergovernmental Panel on Climate Change (IPCC) identified a series of reports to be produced. One of these reports was to be a synthesis of available information on global electricity end-use efficiency, with emphasis on developing nations. The report will be reviewed by the IPCC and approved prior to the UN Conference on Environment and Development (UNCED), Brazil, June 1992. A draft outline for the report was submitted for review at the November 1991 meeting of the EIS. This outline, which was accepted by the EIS, identified three main topics to be addressed in the report: status of available technologies for increasing electricity end-use efficiency; review of factors currently limiting application of end-use efficiency technologies; and review of policies available to increase electricity end-use efficiency. The United States delegation to the EIS agreed to make arrangements for the writing of the report.

  11. Ten-dimensional Supergravity Revisited

    SciTech Connect (OSTI)

    Bergshoeff, Eric; Roo, Mees de; Kerstan, Sven [Centre for Theoretical Physics, University of Groningen, Nijenborgh 4, 9747 AG Groningen (Netherlands); Riccioni, Fabio [DAMTP, Centre for Mathematical Sciences, University of Cambridge, Wilberforce Road, Cambridge CB3 0WA (United Kingdom)

    2006-06-19

    We show that the exisiting supergravity theories in ten dimensions can be extended with extra gauge fields whose rank is equal to the spacetime dimension. These gauge fields have vanishing field strength but nevertheless play an important role in the coupling of supergravity to spacetime filling branes.We discuss the role of these gauge fields in the construction of string theories with sixteen supercharges and mention their relation with a conjectured hyperbolic symmetry underlying string theory and M theory.

  12. INTERNATIONAL RESIDENTIAL ENERGY END USE DATA: ANALYSIS OF HISTORICAL AND PRESENT DAY STRUCTURE AND DYNAMICS

    E-Print Network [OSTI]

    Schipper, Lee

    2013-01-01

    growth in the residential demand for energy, particularlydemand for energy. In Griffinps epic study (1) the author was forced to model residential

  13. China's energy and emissions outlook to 2050: Perspectives from bottom-up energy end-use model

    E-Print Network [OSTI]

    Zhou, Nan

    2014-01-01

    demand-side Total electricity demand efficiency programs608 GW in 2050 Total electricity demand reaches 7,764 TWh innearly one-third of all electricity demand. Under AIS, the

  14. Energy Conservation: Policy Issues and End-Use Scenarios of Savings Potential -- Part 3, Policy Barriers and Investment Decisions in Industry

    E-Print Network [OSTI]

    Benenson, Peter

    2011-01-01

    CONAES) and FEA End Use Energy Consumption Data Base: 1978).and FEA End Use Energy Consumption Data Base: 1978). (3)CONAES) and FEA End Use Energy Consumption Data Base: 1978).

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

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01

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

  16. " Row: End Uses;" " Column: Energy Sources, including Net Electricity;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of348

  17. " Row: End Uses;" " Column: Energy Sources, including Net Electricity;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3482. End

  18. " Row: End Uses;" " Column: Energy Sources, including Net Electricity;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3482. End5

  19. " Row: End Uses;" " Column: Energy Sources, including Net Electricity;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3482.

  20. " Row: End Uses;" " Column: Energy Sources, including Net Electricity;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3482.5 End

  1. " Row: End Uses;" " Column: Energy Sources, including Net Electricity;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3482.5

  2. " Row: End Uses;" " Column: Energy Sources, including Net Electricity;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3482.55

  3. " Row: End Uses;" " Column: Energy Sources, including Net Electricity;"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page|Monthly","10/2015","1/15/1981" ,"DataWorking17.2 116.9 107.6 104.9612. End Uses of3482.556

  4. ,"Massachusetts Natural Gas Consumption by End Use"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008 © OECD/IEA - 2008LNGUndergroundDryAnnual",2014Consumption by End Use"

  5. ,"Ohio Natural Gas Consumption by End Use"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008Wellhead Price (Dollars per Thousand Cubic Feet)"Consumption by End Use"

  6. ,"Rhode Island Natural Gas Consumption by End Use"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008Wellhead PriceConsumption by End Use" ,"Click worksheet name or tab at

  7. ,"West Virginia Natural Gas Consumption by End Use"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA -Annual",2014Proved Reserves, WetGas,Consumption by End Use" ,"Click

  8. ,"Colorado Natural Gas Consumption by End Use"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008 © OECD/IEA - 2008LNG Storage NetConsumption by End Use" ,"Click worksheet

  9. ,"Connecticut Natural Gas Consumption by End Use"

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home PageMonthly","10/2015"4,"Ames City of",6,1,"Omaha Public PowerOECD/IEA - 2008 © OECD/IEA - 2008LNG Storage NetConsumptionConsumption by End Use"

  10. Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity;

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963Residential Consumers (Number of33 2,297 809 245 15504 End Uses of1

  11. Level: National Data; Row: End Uses within NAICS Codes; Column: Energy Sources, including Net Electricity;

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet) Wyoming963Residential Consumers (Number of33 2,297 809 245 15504 End Uses of12

  12. Energy End-Use Intensities in Commercial Buildings 1989 data -- Publication

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun Jul1998,(Million CubicEnd Use:‹Homeand

  13. Energy End-Use Intensities in Commercial Buildings 1995 - Index Page

    Gasoline and Diesel Fuel Update (EIA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of Natural GasAdjustments (Billion Cubic Feet)DecadeYear Jan Feb Mar Apr May Jun Jul1998,(Million CubicEnd1995 End-Use Data

  14. Demand Response Valuation Frameworks Paper

    E-Print Network [OSTI]

    Heffner, Grayson

    2010-01-01

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

  15. Solar Decathlon Turns Ten | Department of Energy

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

    Solar Decathlon Turns Ten Solar Decathlon Turns Ten September 28, 2012 - 2:22pm Addthis For the past 10 years, the Solar Decathlon has educated consumers about affordable clean...

  16. Large CO2 reductions via offshore wind power matched to inherent storage in energy end-uses

    E-Print Network [OSTI]

    Large CO2 reductions via offshore wind power matched to inherent storage in energy end-uses Willett develop methods for assessing offshore wind resources, using a model of the vertical structure offshore wind power matched to inherent storage in energy end- uses, Geophys. Res. Lett., 34, L02817, doi

  17. Residential Demand Sector Data, Commercial Demand Sector Data, Industrial Demand Sector Data - Annual Energy Outlook 2006

    SciTech Connect (OSTI)

    2009-01-18

    Tables describing consumption and prices by sector and census division for 2006 - includes residential demand, commercial demand, and industrial demand

  18. Residential Lighting End-Use Consumption Study: Estimation Framework and Initial Estimates

    SciTech Connect (OSTI)

    Gifford, Will R.; Goldberg, Miriam L.; Tanimoto, Paulo M.; Celnicker, Dane R.; Poplawski, Michael E.

    2012-12-01

    The U.S. DOE Residential Lighting End-Use Consumption Study is an initiative of the U.S. Department of Energy’s (DOE’s) Solid-State Lighting Program that aims to improve the understanding of lighting energy usage in residential dwellings. The study has developed a regional estimation framework within a national sample design that allows for the estimation of lamp usage and energy consumption 1) nationally and by region of the United States, 2) by certain household characteristics, 3) by location within the home, 4) by certain lamp characteristics, and 5) by certain categorical cross-classifications (e.g., by dwelling type AND lamp type or fixture type AND control type).

  19. Technology data characterizing water heating in commercial buildings: Application to end-use forecasting

    SciTech Connect (OSTI)

    Sezgen, O.; Koomey, J.G.

    1995-12-01

    Commercial-sector conservation analyses have traditionally focused on lighting and space conditioning because of their relatively-large shares of electricity and fuel consumption in commercial buildings. In this report we focus on water heating, which is one of the neglected end uses in the commercial sector. The share of the water-heating end use in commercial-sector electricity consumption is 3%, which corresponds to 0.3 quadrillion Btu (quads) of primary energy consumption. Water heating accounts for 15% of commercial-sector fuel use, which corresponds to 1.6 quads of primary energy consumption. Although smaller in absolute size than the savings associated with lighting and space conditioning, the potential cost-effective energy savings from water heaters are large enough in percentage terms to warrant closer attention. In addition, water heating is much more important in particular building types than in the commercial sector as a whole. Fuel consumption for water heating is highest in lodging establishments, hospitals, and restaurants (0.27, 0.22, and 0.19 quads, respectively); water heating`s share of fuel consumption for these building types is 35%, 18% and 32%, respectively. At the Lawrence Berkeley National Laboratory, we have developed and refined a base-year data set characterizing water heating technologies in commercial buildings as well as a modeling framework. We present the data and modeling framework in this report. The present commercial floorstock is characterized in terms of water heating requirements and technology saturations. Cost-efficiency data for water heating technologies are also developed. These data are intended to support models used for forecasting energy use of water heating in the commercial sector.

  20. DEMAND INTERPROCEDURAL PROGRAM ANALYSIS

    E-Print Network [OSTI]

    Reps, Thomas W.

    1 DEMAND INTERPROCEDURAL PROGRAM ANALYSIS USING LOGIC DATABASES Thomas W. Reps Computer Sciences@cs.wisc.edu ABSTRACT This paper describes how algorithms for demand versions of inerprocedural program­ analysis for all elements of the program. This paper concerns the solution of demand versions of interprocedural

  1. Capacity Demand Power (GW)

    E-Print Network [OSTI]

    California at Davis, University of

    Capacity Demand Power (GW) Hour of the Day The "Dip" Electricity Demand in Electricity Demand Every weekday, Japan's electricity use dips about 6 GW at 12 but it also shows that: · Behavior affects naHonal electricity use in unexpected ways

  2. 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

  3. July 11 Public Meeting: Physical Characterization of Grid-Connected Commercial And Residential Building End-Use Equipment And Appliances

    Broader source: Energy.gov [DOE]

    These documents contain the three slide decks presented at the public meeting on the Physical Characterization of Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances, held on July 11, 2014 in Washington, DC.

  4. Residential applliance data, assumptions and methodology for end-use forecasting with EPRI-REEPS 2.1

    SciTech Connect (OSTI)

    Hwang, R.J,; Johnson, F.X.; Brown, R.E.; Hanford, J.W.; Kommey, J.G.

    1994-05-01

    This report details the data, assumptions and methodology for end-use forecasting of appliance energy use in the US residential sector. Our analysis uses the modeling framework provided by the Appliance Model in the Residential End-Use Energy Planning System (REEPS), which was developed by the Electric Power Research Institute. In this modeling framework, appliances include essentially all residential end-uses other than space conditioning end-uses. We have defined a distinct appliance model for each end-use based on a common modeling framework provided in the REEPS software. This report details our development of the following appliance models: refrigerator, freezer, dryer, water heater, clothes washer, dishwasher, lighting, cooking and miscellaneous. Taken together, appliances account for approximately 70% of electricity consumption and 30% of natural gas consumption in the US residential sector. Appliances are thus important to those residential sector policies or programs aimed at improving the efficiency of electricity and natural gas consumption. This report is primarily methodological in nature, taking the reader through the entire process of developing the baseline for residential appliance end-uses. Analysis steps documented in this report include: gathering technology and market data for each appliance end-use and specific technologies within those end-uses, developing cost data for the various technologies, and specifying decision models to forecast future purchase decisions by households. Our implementation of the REEPS 2.1 modeling framework draws on the extensive technology, cost and market data assembled by LBL for the purpose of analyzing federal energy conservation standards. The resulting residential appliance forecasting model offers a flexible and accurate tool for analyzing the effect of policies at the national level.

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

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01

    DECC aggregator managed portfolio automated demand responseaggregator designs their own programs, and offers demand responseaggregator is responsible for designing and implementing their own demand response

  6. Automated Demand Response and Commissioning

    E-Print Network [OSTI]

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

    2005-01-01

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

  7. Demand Response Spinning Reserve Demonstration

    E-Print Network [OSTI]

    2007-01-01

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

  8. 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

  9. Exponential Demand Simulation Tool

    E-Print Network [OSTI]

    Reed, Derek D.

    2015-05-15

    Operant behavioral economics investigates the relation between environmental constraint and reinforcer consumption. The standard approach to quantifying this relation is through the use of behavioral economic demand curves. ...

  10. Managing Increased Charging Demand

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

    Managing Increased Charging Demand Carrie Giles ICF International, Supporting the Workplace Charging Challenge Workplace Charging Challenge Do you already own an EV? Are you...

  11. Public Health Benefits of End-Use Electrical Energy Efficiency in California: An Exploratory Study

    SciTech Connect (OSTI)

    McKone, Thomas E.; Lobscheid, A.B.

    2006-06-01

    This study assesses for California how increasing end-use electrical energy efficiency from installing residential insulation impacts exposures and disease burden from power-plant pollutant emissions. Installation of fiberglass attic insulation in the nearly 3 million electricity-heated homes throughout California is used as a case study. The pollutants nitrous oxides (NO{sub x}), sulfur dioxide (SO{sub 2}), fine particulate matter (PM2.5), benzo(a)pyrene, benzene, and naphthalene are selected for the assessment. Exposure is characterized separately for rural and urban environments using the CalTOX model, which is a key input to the US Environmental Protection Agency (EPA) Tool for the Reduction and Assessment of Chemicals and other environmental Impacts (TRACI). The output of CalTOX provides for urban and rural populations emissions-to-intake factors, which are expressed as an individual intake fraction (iFi). The typical iFi from power plant emissions are on the order of 10{sup -13} (g intake per g emitted) in urban and rural regions. The cumulative (rural and urban) product of emissions, population, and iFi is combined with toxic effects factors to determine human damage factors (HDFs). HDF are expressed as disability adjusted life years (DALYs) per kilogram pollutant emitted. The HDF approach is applied to the insulation case study. Upgrading existing residential insulation to US Department of Energy (DOE) recommended levels eliminates over the assmned 50-year lifetime of the insulation an estimated 1000 DALYs from power-plant emissions per million tonne (Mt) of insulation installed, mostly from the elimination of PM2.5 emissions. In comparison, the estimated burden from the manufacture of this insulation in DALYs per Mt is roughly four orders of magnitude lower than that avoided.

  12. Detailed Modeling and Response of Demand Response Enabled Appliances

    SciTech Connect (OSTI)

    Vyakaranam, Bharat; Fuller, Jason C.

    2014-04-14

    Proper modeling of end use loads is very important in order to predict their behavior, and how they interact with the power system, including voltage and temperature dependencies, power system and load control functions, and the complex interactions that occur between devices in such an interconnected system. This paper develops multi-state time variant residential appliance models with demand response enabled capabilities in the GridLAB-DTM simulation environment. These models represent not only the baseline instantaneous power demand and energy consumption, but the control systems developed by GE Appliances to enable response to demand response signals and the change in behavior of the appliance in response to the signal. These DR enabled appliances are simulated to estimate their capability to reduce peak demand and energy consumption.

  13. Installation and Commissioning Automated Demand Response Systems

    SciTech Connect (OSTI)

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

    2008-04-21

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

  14. Electrical Demand Management 

    E-Print Network [OSTI]

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

    1983-01-01

    The Demand Management Plan set forth in this paper has proven to be a viable action to reduce a 3 million per year electric bill at the Columbus Works location of Western Electric. Measures are outlined which have reduced the peak demand 5% below...

  15. Open Automated Demand Response for Small Commerical Buildings

    SciTech Connect (OSTI)

    Dudley, June Han; Piette, Mary Ann; Koch, Ed; Hennage, Dan

    2009-05-01

    This report characterizes small commercial buildings by market segments, systems and end-uses; develops a framework for identifying demand response (DR) enabling technologies and communication means; and reports on the design and development of a low-cost OpenADR enabling technology that delivers demand reductions as a percentage of the total predicted building peak electric demand. The results show that small offices, restaurants and retail buildings are the major contributors making up over one third of the small commercial peak demand. The majority of the small commercial buildings in California are located in southern inland areas and the central valley. Single-zone packaged units with manual and programmable thermostat controls make up the majority of heating ventilation and air conditioning (HVAC) systems for small commercial buildings with less than 200 kW peak electric demand. Fluorescent tubes with magnetic ballast and manual controls dominate this customer group's lighting systems. There are various ways, each with its pros and cons for a particular application, to communicate with these systems and three methods to enable automated DR in small commercial buildings using the Open Automated Demand Response (or OpenADR) communications infrastructure. Development of DR strategies must consider building characteristics, such as weather sensitivity and load variability, as well as system design (i.e. under-sizing, under-lighting, over-sizing, etc). Finally, field tests show that requesting demand reductions as a percentage of the total building predicted peak electric demand is feasible using the OpenADR infrastructure.

  16. THE PHILOSOPHY OF INFORMATION: TEN YEARS LATER

    E-Print Network [OSTI]

    Floridi, Luciano

    with the new ethical chal- lenges posed by information and communication technologies, to list some issue. Keywords: information ethics, levels of abstraction, philosophy of information, semanticTHE PHILOSOPHY OF INFORMATION: TEN YEARS LATER LUCIANO FLORIDI Abstract: This article provides

  17. A methodology for determining the relationship between air transportation demand and the level of service

    E-Print Network [OSTI]

    Eriksen, Steven Edward

    1976-01-01

    Introduction: Within the last ten years significant advances in the state-of-the art in air travel demand analysis stimulated researchers in the domestic air transportation field. Among these advances, researchers in ...

  18. 2 Large CO2 reductions via offshore wind power matched to inherent 3 storage in energy end-uses

    E-Print Network [OSTI]

    Firestone, Jeremy

    2 Large CO2 reductions via offshore wind power matched to inherent 3 storage in energy end-uses 4] We develop methods for assessing offshore wind 9 resources, using a model of the vertical structure. Dhanju, R. W. 26 Garvine, and M. Z. Jacobson (2007), Large CO2 reductions via 27 offshore wind power

  19. Demand Dispatch-Intelligent

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

    such as wind, solar, and electric vehicles as well as dispatchable loads and microgrids. Many of these resources will be "behind-the-meter" (i.e., demand resources) and...

  20. Demand and Price Uncertainty: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2013-01-01

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

  1. Demand and Price Volatility: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2011-01-01

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

  2. Demand and Price Volatility: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2011-01-01

    H. , and James M. Gri¢ n. 1983. Gasoline demand in the OECDof dynamic demand for gasoline. Journal of Econometrics 77(An empirical analysis of gasoline demand in Denmark using

  3. Demand and Price Volatility: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2011-01-01

    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

  4. Open Automated Demand Response Communications Specification (Version 1.0)

    SciTech Connect (OSTI)

    Piette, Mary Ann; Ghatikar, Girish; Kiliccote, Sila; Koch, Ed; Hennage, Dan; Palensky, Peter; McParland, Charles

    2009-02-28

    The development of the Open Automated Demand Response Communications Specification, also known as OpenADR or Open Auto-DR, began in 2002 following the California electricity crisis. The work has been carried out by the Demand Response Research Center (DRRC), which is managed by Lawrence Berkeley National Laboratory. This specification describes an open standards-based communications data model designed to facilitate sending and receiving demand response price and reliability signals from a utility or Independent System Operator to electric customers. OpenADR is one element of the Smart Grid information and communications technologies that are being developed to improve optimization between electric supply and demand. The intention of the open automated demand response communications data model is to provide interoperable signals to building and industrial control systems that are preprogrammed to take action based on a demand response signal, enabling a demand response event to be fully automated, with no manual intervention. The OpenADR specification is a flexible infrastructure to facilitate common information exchange between the utility or Independent System Operator and end-use participants. The concept of an open specification is intended to allow anyone to implement the signaling systems, the automation server or the automation clients.

  5. Analysis of Residential Demand Response and Double-Auction Markets

    SciTech Connect (OSTI)

    Fuller, Jason C.; Schneider, Kevin P.; Chassin, David P.

    2011-10-10

    Demand response and dynamic pricing programs are expected to play increasing roles in the modern Smart Grid environment. While direct load control of end-use loads has existed for decades, price driven response programs are only beginning to be explored at the distribution level. These programs utilize a price signal as a means to control demand. Active markets allow customers to respond to fluctuations in wholesale electrical costs, but may not allow the utility to control demand. Transactive markets, utilizing distributed controllers and a centralized auction can be used to create an interactive system which can limit demand at key times on a distribution system, decreasing congestion. With the current proliferation of computing and communication resources, the ability now exists to create transactive demand response programs at the residential level. With the combination of automated bidding and response strategies coupled with education programs and customer response, emerging demand response programs have the ability to reduce utility demand and congestion in a more controlled manner. This paper will explore the effects of a residential double-auction market, utilizing transactive controllers, on the operation of an electric power distribution system.

  6. End-use load control for power system dynamic stability enhancement

    SciTech Connect (OSTI)

    Dagle, J.E.; Winiarski, D.W.; Donnelly, M.K.

    1997-02-01

    Faced with the prospect of increasing utilization of the transmission and distribution infrastructure without significant upgrade, the domestic electric power utility industry is investing heavily in technologies to improve network dynamic performance through a program loosely referred to as Flexible AC Transmission System (FACTS). Devices exploiting recent advances in power electronics are being installed in the power system to offset the need to construct new transmission lines. These devices collectively represent investment potential of several billion dollars over the next decade. A similar development, designed to curtail the peak loads and thus defer new transmission, distribution, and generation investment, falls under a category of technologies referred to as demand side management (DSM). A subset of broader conservation measures, DSM acts directly on the load to reduce peak consumption. DSM techniques include direct load control, in which a utility has the ability to curtail specific loads as conditions warrant. A novel approach has been conceived by Pacific Northwest National Laboratory (PNNL) to combine the objectives of FACTS and the technologies inherent in DSM to provide a distributed power system dynamic controller. This technology has the potential to dramatically offset major investments in FACTS devices by using direct load control to achieve dynamic stability objectives. The potential value of distributed versus centralized grid modulation has been examined by simulating the western power grid under extreme loading conditions. In these simulations, a scenario is analyzed in which active grid stabilization enables power imports into the southern California region to be increased several hundred megawatts beyond present limitations. Modeling results show distributed load control is up to 30 percent more effective than traditional centralized control schemes in achieving grid stability.

  7. Demand and Price Uncertainty: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2013-01-01

    Sterner. 1991. Analysing gasoline demand elasticities: A2011. Measuring global gasoline and diesel price and incomeMutairi. 1995. Demand for gasoline in Kuwait: An empirical

  8. Demand Response Valuation Frameworks Paper

    E-Print Network [OSTI]

    Heffner, Grayson

    2010-01-01

    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

  9. Optimal Demand Response Libin Jiang

    E-Print Network [OSTI]

    Optimal Demand Response Libin Jiang Steven Low Computing + Math Sciences Electrical Engineering Caltech Oct 2011 #12;Outline Caltech smart grid research Optimal demand response #12;Global trends 1

  10. ENERGY DEMAND FORECAST METHODS REPORT

    E-Print Network [OSTI]

    ....................................................................................................1-16 Energy Consumption Data...............................................1-15 Data Sources for Energy Demand Forecasting ModelsCALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report

  11. Ten Questions Concerning Generative Computer Art

    E-Print Network [OSTI]

    McCormack, Jon

    Ten Questions Concerning Generative Computer Art Jon McCormack, Oliver Bown, Alan Dorin, Jonathan), Centre for Electronic Media Art, Faculty of Information Technology, Monash University, Caulfield East, Australia, Email: Jonathan McCabe (generative artist), Faculty of Arts and Design

  12. Chapter Ten Control System Theory Overview

    E-Print Network [OSTI]

    Gajic, Zoran

    Chapter Ten Control System Theory Overview In this book we have presented results mostly for continuous-time, time-invariant, deterministic control systems. We have also, to some extent, given the corre- sponding results for discrete-time, time-invariant, deterministic control systems. However, in control

  13. Estimating a Demand System with Nonnegativity Constraints: Mexican Meat Demand

    E-Print Network [OSTI]

    Carlini, David

    Estimating a Demand System with Nonnegativity Constraints: Mexican Meat Demand Amos Golan* Jeffrey an almost ideal demand system for five types of meat using cross-sectional data from Mexico, where most households did not buy at least one type of meat during the survey week. The system of demands is shown

  14. Peer-Assisted On-Demand Streaming: Characterizing Demands and

    E-Print Network [OSTI]

    Li, Baochun

    Peer-Assisted On-Demand Streaming: Characterizing Demands and Optimizing Supplies Fangming Liu Abstract--Nowadays, there has been significant deployment of peer-assisted on-demand streaming services over the Internet. Two of the most unique and salient features in a peer-assisted on-demand streaming

  15. Energy Demand Staff Scientist

    E-Print Network [OSTI]

    Eisen, Michael

    #12;Sources: China National Bureau of Statistics; U.S. Energy Information Administration, Annual Energy Outlook. Overview:Overview: Energy Use in China and the U.S.Energy Use in China and the U.S. 5 0Energy Demand in China Lynn Price Staff Scientist February 2, 2010 #12;Founded in 1988 Focused

  16. Agenda for Public Meeting on the Physical Characterization of Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances

    Broader source: Energy.gov [DOE]

    Download the agenda below for the July 11 Public Meeting on the Physical Characterization of Grid-Connected Commercial and  Residential Buildings End-Use Equipment and Appliances.

  17. California Energy Demand Scenario Projections to 2050

    E-Print Network [OSTI]

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

    2008-01-01

    fraction of residential and commercial demands, leading16 Residential electricity demand endspecific residential electricity demands into electricity

  18. Demand Forecast INTRODUCTION AND SUMMARY

    E-Print Network [OSTI]

    Demand Forecast INTRODUCTION AND SUMMARY A 20-year forecast of electricity demand is a required in electricity demand is, of course, crucial to determining the need for new electricity resources and helping of any forecast of electricity demand and developing ways to reduce the risk of planning errors

  19. Design and Implementation of an Open, Interoperable AutomatedDemand Response Infrastructure

    SciTech Connect (OSTI)

    Piette, Mary Ann; Kiliccote, Sila; Ghatikar, Girish

    2007-10-01

    This paper describes the concept for and lessons from the development and field-testing of an open, interoperable communications infrastructure to support automating demand response (DR). Automating DR allows greater levels of participation and improved reliability and repeatability of the demand response and customer facilities. Automated DR systems have been deployed for critical peak pricing and demand bidding and are being designed for real time pricing. The system is designed to generate, manage, and track DR signals between utilities and Independent System Operators (ISOs) to aggregators and end-use customers and their control systems.

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

    SciTech Connect (OSTI)

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

    2012-01-04

    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.

  1. Ten Year Site Plans | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative FuelsofProgram: Report15 MeetingDevelopment TechnologyTechnology-to-MarketNational Ten

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

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01

    retail regulatory authority prohibit such activity. Demand response integration into US wholesale power marketsretail or wholesale level. 17 While demand response began participating at scale in wholesale power markets

  3. TenKsolar Inc | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page| Open Energy Information Serbia-EnhancingEt Al., 2013) | Opensource History View NewsourceUsa, 1980-1994TenKsolar Inc

  4. Bos ten AG | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental JumpInformationBio-GasIllinois:EnergyIdaho |InformationBorrego SolarBos ten

  5. Demand Dispatch-Intelligent

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantityBonneville Power Administration would like submit theCovalent Bonding Low-Cost2DepartmentDelta Dental Claim Form PDF iconDemand

  6. Revelation on Demand Nicolas Anciaux

    E-Print Network [OSTI]

    Revelation on Demand Nicolas Anciaux 1 · Mehdi Benzine1,2 · Luc Bouganim1 · Philippe Pucheral1 "revelation on demand". Keywords: Confidentiality and privacy, Secure device, Data warehousing, Indexing model

  7. by popular demand: Addiction II

    E-Print Network [OSTI]

    Niv, Yael

    by popular demand: Addiction II PSY/NEU338:Animal learning and decision making: Psychological, size of other non-drug rewards, and cost (but ultimately the demand is inelastic, or at least

  8. Demand Response: Load Management Programs 

    E-Print Network [OSTI]

    Simon, J.

    2012-01-01

    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-peak period or from high-price periods...

  9. Chord on Demand Alberto Montresor

    E-Print Network [OSTI]

    Jelasity, Márk

    Chord on Demand Alberto Montresor University of Bologna, Italy montresor@cs.unibo.it M´ark Jelasity to solve a specific task on demand. We introduce T- CHORD, that can build a Chord network efficiently to solve a specific task on demand. Existing join protocols are not designed to handle the massive

  10. Supply Chain Supernetworks Random Demands

    E-Print Network [OSTI]

    Nagurney, Anna

    Supply Chain Supernetworks with Random Demands June Dong and Ding Zhang Department of Marketing of three tiers of decision-makers: the manufacturers, the distributors, and the retailers, with the demands equilibrium model with electronic commerce and with random demands for which modeling, qualitative analysis

  11. Chord on Demand Alberto Montresor

    E-Print Network [OSTI]

    Chord on Demand Alberto Montresor University of Bologna, Italy montresor@cs.unibo.it Mark Jelasity to solve a specific task on demand. We introduce T- CHORD, that can build a Chord network efficiently on demand. Existing join protocols are not designed to handle the massive concurrency involved in a jump

  12. ERCOT Demand Response Paul Wattles

    E-Print Network [OSTI]

    Mohsenian-Rad, Hamed

    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

  13. 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

  14. The evolution of carbon dioxide emissions from energy use in industrialized countries: an end-use analysis

    SciTech Connect (OSTI)

    Schipper, L.; Ting, M.; Khrushch, M.; Unander, F.; Monahan, P.; Golove, W.

    1996-08-01

    There has been much attention drawn to plans for reductions or restraint in future C02 emissions, yet little analysis of the recent history of those emissions by end use or economic activity. Understanding the components of C02 emissions, particularly those related to combustion of fossil fuels, is important for judging the likely success of plans for dealing with future emissions. Knowing how fuel switching, changes in economic activity and its structure, or changes in energy-use efficiency affected emissions in the past, we can better judge both the realism of national proposals to restrain future emissions and the outcome as well. This study presents a first step in that analysis. The organization of this paper is as follows. We present a brief background and summarize previous work analyzing changes in energy use using the factorial method. We then describe our data sources and method. We then present a series of summary results, including a comparison of C02 emissions in 1991 by end use or sector. We show both aggregate change and change broken down by factor, highlighting briefly the main components of change. We then present detailed results, sector by sector. Next we highlight recent trends. Finally, we integrate our results, discussing -the most important factors driving change - evolution in economic structure, changes in energy intensities, and shifts in the fuel mix. We discuss briefly some of the likely causes of these changes - long- term technological changes, effects of rising incomes, the impact of overall changes in energy prices, as well as changes in the relative prices of energy forms.

  15. Ten themes of viscous liquid dynamics

    E-Print Network [OSTI]

    Jeppe C. Dyre

    2006-12-06

    Ten "themes" of viscous liquid physics are discussed with a focus on how they point to a general description of equilibrium viscous liquid dynamics (i.e., fluctuations) at a given temperature. This description is based on standard time-dependent Ginzburg-Landau equations for the density fields, stress tensor fields, potential energy density field, and fields quantifying molecular orientations. One characteristic aspect of the theory is that density has the appearance of a non-conserved field. Another characteristic feature is long-wavelength dominance of the dynamics, which not only simplifies the theory by allowing for an ultra-local Hamiltonian (free energy), but also explains the observed general independence of chemistry. Whereas there are no long-ranged static (i.e., equal-time) correlations in the model, there are important long-ranged dynamic correlations on the alpha time scale.

  16. 2014-04-30 Public Meeting Agenda: Physical Characterization of Smart and Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances

    Broader source: Energy.gov [DOE]

    This document is the agenda for the Physical Characterization of Smart and Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances public meeting being held on April 30, 2014.

  17. 2014-04-30 Public Meeting Presentation Slides: Physical Characterization of Smart and Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances

    Broader source: Energy.gov [DOE]

    These documents contain slide decks presented at the Physical Characterization of Smart and Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances public meeting held on April 30, 2014.

  18. Demand Response Programs, 6. edition

    SciTech Connect (OSTI)

    2007-10-15

    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.

  19. Generating Demand for Multifamily Building Upgrades | Department...

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

    Demand for Multifamily Building Upgrades Generating Demand for Multifamily Building Upgrades Better Buildings Residential Network Peer Exchange Call Series: Generating Demand for...

  20. China's Coal: Demand, Constraints, and Externalities

    E-Print Network [OSTI]

    Aden, Nathaniel

    2010-01-01

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

  1. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

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

  2. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01

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

  3. Home Network Technologies and Automating Demand Response

    E-Print Network [OSTI]

    McParland, Charles

    2010-01-01

    LBNL Commercial and Residential Demand Response Overview ofmarket [5]. Residential demand reduction programs have beenin the domain of residential demand response. There are a

  4. Installation and Commissioning Automated Demand Response Systems

    E-Print Network [OSTI]

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

    2008-01-01

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

  5. Coupling Renewable Energy Supply with Deferrable Demand

    E-Print Network [OSTI]

    Papavasiliou, Anthony

    2011-01-01

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

  6. Strategies for Demand Response in Commercial Buildings

    E-Print Network [OSTI]

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

    2006-01-01

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

  7. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01

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

  8. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

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

  9. Hawaiian Electric Company Demand Response Roadmap Project

    E-Print Network [OSTI]

    Levy, Roger

    2014-01-01

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

  10. Retail Demand Response in Southwest Power Pool

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2009-01-01

    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

  11. Demand Response - Policy | Department of Energy

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

    Coordination of Energy Efficiency and Demand Response Demand Response in U.S. Electricity Markets: Empirical Evidence 2009 Retail Demand Response in Southwest Power Pool (January...

  12. Demand Response as a System Reliability Resource

    E-Print Network [OSTI]

    Joseph, Eto

    2014-01-01

    Barat, and D. Watson. 2007. Demand Response Spinning ReserveKueck, and B. Kirby. 2009. Demand Response Spinning Reserveand B. Kirby. 2012. The Demand Response Spinning Reserve

  13. California Energy Demand Scenario Projections to 2050

    E-Print Network [OSTI]

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

    2008-01-01

    duty fuel demand in alternate scenarios. ..for light-duty fuel demand in alternate scenarios. Minimum52 Heavy-duty vehicle fuel demand for each alternate

  14. California Energy Demand Scenario Projections to 2050

    E-Print Network [OSTI]

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

    2008-01-01

    2006-2016: Staff energy demand forecast (Revised SeptemberCEC (2005b) Energy demand forecast methods report.California energy demand 2003-2013 forecast. California

  15. Scenario Analysis of Peak Demand Savings for Commercial Buildings with Thermal Mass in California

    SciTech Connect (OSTI)

    Yin, Rongxin; Kiliccote, Sila; Piette, Mary Ann; Parrish, Kristen

    2010-05-14

    This paper reports on the potential impact of demand response (DR) strategies in commercial buildings in California based on the Demand Response Quick Assessment Tool (DRQAT), which uses EnergyPlus simulation prototypes for office and retail buildings. The study describes the potential impact of building size, thermal mass, climate, and DR strategies on demand savings in commercial buildings. Sensitivity analyses are performed to evaluate how these factors influence the demand shift and shed during the peak period. The whole-building peak demand of a commercial building with high thermal mass in a hot climate zone can be reduced by 30percent using an optimized demand response strategy. Results are summarized for various simulation scenarios designed to help owners and managers understand the potential savings for demand response deployment. Simulated demand savings under various scenarios were compared to field-measured data in numerous climate zones, allowing calibration of the prototype models. The simulation results are compared to the peak demand data from the Commercial End-Use Survey for commercial buildings in California. On the economic side, a set of electricity rates are used to evaluate the impact of the DR strategies on economic savings for different thermal mass and climate conditions. Our comparison of recent simulation to field test results provides an understanding of the DR potential in commercial buildings.

  16. Advective Accretion Flows: Ten Years Later

    E-Print Network [OSTI]

    S. K. Chakrabarti

    2000-07-18

    Ten years have passed since the global solutions of advective accretion disks around black holes and neutron stars were first discovered. Since then they are enjoying support from observers almost on a daily basis, more so in recent days with the launching of very high resolution satellites. This review presents the development of the subject of advective accretion in last twenty five years leading to the global solutions and their applications. It also shows that apart from the standard Keplerian disk features in most part of the accretion flow, future models must incorporate the essential features of the advective disks, such as the advection of energy and entropy by the flow, centrifugal barrier supported boundary layer of a black hole, steady and non-steady shocks, the bulk motion Comptonization of matter close to the black hole, outflows from the centrifugal barrier etc. Since black holes are `black', methods of their identification must be indirect, and therefore, the solutions must be known very accurately. On the horizon, matter moves supersonically, but just before that it is subsonic due to centrifugal pressure dominated boundary layer or CENBOL where much of the infall energy is released and outflows are generated. In this review, we show that advective flow models treat accretion and winds onto black holes and neutron stars in the same footing. Similarly treated are the steady and time-dependent behaviour of the boundary layers of neutron stars and the black holes!

  17. Demand Response Technology Roadmap A

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

    meetings and workshops convened to develop content for the Demand Response Technology Roadmap. The project team has developed this companion document in the interest of providing...

  18. Financing end-use solar technologies in a restructured electricity industry: Comparing the cost of public policies

    SciTech Connect (OSTI)

    Jones, E.; Eto, J.

    1997-09-01

    Renewable energy technologies are capital intensive. Successful public policies for promoting renewable energy must address the significant resources needed to finance them. Public policies to support financing for renewable energy technologies must pay special attention to interactions with federal, state, and local taxes. These interactions are important because they can dramatically increase or decrease the effectiveness of a policy, and they determine the total cost of a policy to society as a whole. This report describes a comparative analysis of the cost of public policies to support financing for two end-use solar technologies: residential solar domestic hot water heating (SDHW) and residential rooftop photovoltaic (PV) systems. The analysis focuses on the cost of the technologies under five different ownership and financing scenarios. Four scenarios involve leasing the technologies to homeowners in return for a payment that is determined by the financing requirements of each form of ownership. For each scenario, the authors examine nine public policies that might be used to lower the cost of these technologies: investment tax credits (federal and state), production tax credits (federal and state), production incentives, low-interest loans, grants (taxable and two types of nontaxable), direct customer payments, property and sales tax reductions, and accelerated depreciation.

  19. Scenarios of Global Municipal Water-Use Demand Projections over the 21st Century

    SciTech Connect (OSTI)

    Hejazi, Mohamad I.; Edmonds, James A.; Chaturvedi, Vaibhav; Davies, Evan; Eom, Jiyong

    2013-03-06

    This paper establishes three future projections of global municipal water use to the end of the 21st century: A reference business-as usual (BAU) scenario, a High Technological Improvement (High Tech) scenario and a Low Technological Improvement (Low Tech) scenario. A global municipal water demand model is constructed using global water use statistics at the country-scale, calibrated to the base year of 2005, and simulated to the end of the 21st century. Since the constructed water demand model hinges on socioeconomic variables (population, income), water price, and end-use technology and efficiency improvement rates, projections of those input variables are adopted to characterize the uncertainty in future water demand estimates. The water demand model is linked to the Global Change Assessment Model (GCAM), a global change integrated assessment model. Under the reference scenario, the global total water withdrawal increases from 466 km3/year in 2005 to 941 km3/year in 2100,while withdrawals in the high and low tech scenarios are 321 km3/ year and 2000 km3/ year, respectively. This wide range (321-2000 km3/ year) indicates the level of uncertainty associated with such projections. The simulated global municipal demand projections are most sensitive to population and income projections, then to end-use technology and efficiency projections, and finally to water price. Thus, using water price alone as a policy measure to reduce municipal water use may substantiate the share of municipal water price of people’s annual incomes.

  20. Scoping Study for Demand Respose DFT II Project in Morgantown, WV

    SciTech Connect (OSTI)

    Lu, Shuai; Kintner-Meyer, Michael CW

    2008-06-06

    This scoping study describes the underlying data resources and an analysis tool for a demand response assessment specifically tailored toward the needs of the Modern Grid Initiatives Demonstration Field Test in Phase II in Morgantown, WV. To develop demand response strategies as part of more general distribution automation, automated islanding and feeder reconfiguration schemes, an assessment of the demand response resource potential is required. This report provides the data for the resource assessment for residential customers and describes a tool that allows the analyst to estimate demand response in kW for each hour of the day, by end-use, season, day type (weekday versus weekend) with specific saturation rates of residential appliances valid for the Morgantown, WV area.

  1. Supply Chain Supernetworks With Random Demands

    E-Print Network [OSTI]

    Nagurney, Anna

    Supply Chain Supernetworks With Random Demands June Dong Ding Zhang School of Business State Field Warehouses: stocking points Customers, demand centers sinks Production/ purchase costs Inventory Customer Demand Customer Demand Retailer OrdersRetailer Orders Distributor OrdersDistributor Orders

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

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

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

  3. Retail Demand Response in Southwest Power Pool

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2009-01-01

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

  4. Honeywell Demonstrates Automated Demand Response Benefits for...

    Office of Environmental Management (EM)

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

  5. Effects of the drought on California electricity supply and demand

    E-Print Network [OSTI]

    Benenson, P.

    2010-01-01

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

  6. Demand Response for Ancillary Services

    SciTech Connect (OSTI)

    Alkadi, Nasr E; Starke, Michael R

    2013-01-01

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

  7. The use of negotiated agreements to improve efficiency of end-use appliances: First results from the European experience

    SciTech Connect (OSTI)

    Bertoldi, P.; Bowie, R.; Hagen, L.

    1998-07-01

    The European Union is pursuing measures to improve end-use equipment efficiency through a variety of policy instruments, in particular for domestic appliances. One of the most effective methods to achieve market transformation is through minimum efficiency performance standards (MEPS). However, after the difficulties and controversy following the adoption of legislation for MEPS for domestic refrigerators/freezers, a new policy instrument, i.e. negotiated agreements by manufacturers, has been investigated and tested for two type of appliances: domestic washing machines and TVs and VCRs. Based on the positive experience of the above two agreements, other products (e.g. dryers, dishwasher, electric water heaters, etc.) will be the subject of future negotiated agreements. Based on the results of the two negotiated agreements, this paper describes the energy efficiency potential, the procedures, and the advantages and disadvantages of negotiated agreements compared to legislated mandatory for MEPS, as developed in the European context. The paper concludes that negotiated agreements are a viable policy option, which allow flexibility in the implementation of the efficiency targets and therefore the adoption of cost-effective solutions for manufacturers. In addition, negotiated agreements can be implemented more quickly compared to mandatory MEPS and they allow a closer monitoring of the results. The main question asked in the paper is whether the negotiated agreements can deliver the results in the long term compared to what could be achieved through legislation. The European experience indicates that this instrument can deliver the results and that it offer a number of advantages compared to MEPS.

  8. Northwest Open Automated Demand Response Technology Demonstration Project

    SciTech Connect (OSTI)

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

    2010-03-17

    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.

  9. Ten Steps for Career Success Ready Reference A-4

    E-Print Network [OSTI]

    Ten Steps for Career Success Ready Reference A-4 College of Engineering, Architecture & Technology Career Services Oklahoma State University College of Engineering, Architecture & Technology Career

  10. Water Sampling At Valley Of Ten Thousand Smokes Region Area ...

    Open Energy Info (EERE)

    Water Sampling At Valley Of Ten Thousand Smokes Region Area (Keith, Et Al., 1992) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration Activity: Water Sampling...

  11. Ten New Mexico small businesses recognized at Innovation Celebration...

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

    NM small businesses recognized at Innovation Celebration Ten New Mexico small businesses recognized at Innovation Celebration April 3 Small businesses participating in projects...

  12. Data Acquisition-Manipulation At Valley Of Ten Thousand Smokes...

    Open Energy Info (EERE)

    Data Acquisition-Manipulation At Valley Of Ten Thousand Smokes Region Area (Kodosky & Keith, 1993) Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Exploration...

  13. Final Environmental Impact Report: North Brawley Ten Megawatt...

    Open Energy Info (EERE)

    Final Environmental Impact Report: North Brawley Ten Megawatt Geothermal Demonstration Facility Jump to: navigation, search OpenEI Reference LibraryAdd to library Report: Final...

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

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.; Zhou, Nan

    2009-05-18

    The time when energy-related carbon emissions come overwhelmingly from developed countries is coming to a close. China has already overtaken the United States as the world's leading emitter of greenhouse gas emissions. The economic growth that China has experienced is not expected to slow down significantly in the long term, which implies continued massive growth in energy demand. This paper draws on the extensive expertise from the China Energy Group at LBNL on forecasting energy consumption in China, but adds to it by exploring the dynamics of demand growth for electricity in the residential sector -- and the realistic potential for coping with it through efficiency. This paper forecasts ownership growth of each product using econometric modeling, in combination with historical trends in China. The products considered (refrigerators, air conditioners, fans, washing machines, lighting, standby power, space heaters, and water heating) account for 90percent of household electricity consumption in China. Using this method, we determine the trend and dynamics of demandgrowth and its dependence on macroeconomic drivers at a level of detail not accessible by models of a more aggregate nature. In addition, we present scenarios for reducing residential consumption through efficiency measures defined at the product level. The research takes advantage of an analytical framework developed by LBNL (BUENAS) which integrates end use technology parameters into demand forecasting and stock accounting to produce detailed efficiency scenarios, thus allowing for a technologically realistic assessment of efficiency opportunities specifically in the Chinese context.

  15. Demand and Price Volatility: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2011-01-01

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

  16. Demand and Price Uncertainty: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2013-01-01

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

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

    E-Print Network [OSTI]

    Shen, Bo

    2013-01-01

    electricity. In this manner, demand side management is directly integrated into the wholesale capacity marketcapacity market U.S. Federal Energy Regulatory Commission Florida Reliability Coordinating Council incremental auctions independent electricity

  18. Demand and Price Uncertainty: Rational Habits in International Gasoline Demand

    E-Print Network [OSTI]

    Scott, K. Rebecca

    2013-01-01

    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-

  19. California Baseline Energy Demands to 2050 for Advanced Energy Pathways

    E-Print Network [OSTI]

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

    2008-01-01

    demands. Residential and commercial demand has a significantDemand by Sector Residential Peak Demand (MW) Commercialwe convert residential electricity demand based upon climate

  20. Demand Response for Ancillary Services

    Broader source: Energy.gov [DOE]

    Methodologies used to study grid integration of variable generation can be adapted to the study of demand response. In the present work, we describe and implement a methodology to construct detailed temporal and spatial representations of demand response resources and to incorporate those resources into power system models. In addition, the paper outlines ways to evaluate barriers to implementation. We demonstrate how the combination of these three analyses can be used to assess economic value of the realizable potential of demand response for ancillary services.

  1. Physically-based demand modeling 

    E-Print Network [OSTI]

    Calloway, Terry Marshall

    1980-01-01

    nts on the demand. Of course the demand of a real a1r cond1t1oner has lower and upper bounds equal to 0 and 0 , respec- u tively. A constra1ned system can be simulated numerically, but there 1s no explicit system response formula s1m11ar... sect1on. It may now be instruct1ve to relate this model to that of Jones and Bri ce [5] . The average demand pred1 cted by their model is the expected value of the product of a load response factor 0 and a U sw1tching process H(t), which depends...

  2. Seasonality in air transportation demand

    E-Print Network [OSTI]

    Reichard Megwinoff, H?tor Nicolas

    1988-01-01

    This thesis investigates the seasonality of demand in air transportation. It presents three methods for computing seasonal indices. One of these methods, the Periodic Average Method, is selected as the most appropriate for ...

  3. Demand response enabling technology development

    E-Print Network [OSTI]

    2006-01-01

    Monitoring in an Agent-Based Smart Home, Proceedings of theConference on Smart Homes and Health Telematics, September,Smart Meter Motion sensors Figure 1: Schematic of the Demand Response Electrical Appliance Manager in a Home.

  4. Full Rank Rational Demand Systems

    E-Print Network [OSTI]

    LaFrance, Jeffrey T; Pope, Rulon D.

    2006-01-01

    Dover Publications 1972. Barnett, W.A. and Y.W. Lee. “TheEconometrica 53 (1985): 1421- Barnett, W.A. , Lee, Y.W. ,Laurent demand systems (Barnett and Lee 1985; Barnett, Lee,

  5. Residential Demand Module - NEMS Documentation

    Reports and Publications (EIA)

    2014-01-01

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

  6. Marketing Demand-Side Management 

    E-Print Network [OSTI]

    O'Neill, M. L.

    1988-01-01

    Demand-Side Management is an organizational tool that has proven successful in various realms of the ever changing business world in the past few years. It combines the multi-faceted desires of the customers with the increasingly important...

  7. Demand Response Spinning Reserve Demonstration

    SciTech Connect (OSTI)

    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.

    2007-05-01

    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.

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

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01

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

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

    E-Print Network [OSTI]

    Mares, K.C.

    2010-01-01

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

  10. Optimal Demand Response and Power Flow

    E-Print Network [OSTI]

    Willett, Rebecca

    Optimal Demand Response and Power Flow Steven Low Computing + Math Sciences Electrical Engineering #12;Outline Optimal demand response n With L. Chen, L. Jiang, N. Li Optimal power flow n With S. Bose;Optimal demand response Model Results n Uncorrelated demand: distributed alg n Correlated demand

  11. Aggregated Modeling of Thermostatic Loads in Demand Response: A Systems and Control Perspective

    SciTech Connect (OSTI)

    Kalsi, Karanjit; Chassin, Forrest S.; Chassin, David P.

    2011-12-12

    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 models for a homogeneous population of thermostatically controlled loads. The different types of loads considered in this paper include, but are not limited to, water heaters and HVAC units. The effects of demand response and user over-ride on the load population dynamics are investigated. The controllability of the developed lumped models is validated which forms the basis for designing different control strategies.

  12. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    relatively high economic/demographic growth, relatively low electricity and natural gas rates REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand Bill Junker Manager DEMAND ANALYSIS OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS

  13. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

    high economic/demographic growth, relatively low electricity and natural gas rates, and relatively low CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand Manager DEMAND ANALYSIS OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION

  14. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    relatively high economic/demographic growth, relatively low electricity and natural gas rates CALIFORNIA ENERGY DEMAND 2014­2024 FINAL FORECAST Volume 1: Statewide Electricity Demand Gough Office Manager DEMAND ANALYSIS OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS

  15. Demand Response as a System Reliability Resource

    E-Print Network [OSTI]

    Joseph, Eto

    2014-01-01

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

  16. Exponential Communication Ine ciency of Demand Queries

    E-Print Network [OSTI]

    Sandholm, Tuomas W.

    FORECAST COMBINATION IN REVENUE MANAGEMENT DEMAND FORECASTING SILVIA RIEDEL A thesissubmitted Combination in RevenueManagement Demand Forecasting Abstract The domain of multi level forecastcombination

  17. Generating Demand for Multifamily Building Upgrades | Department...

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

    Generating Demand for Multifamily Building Upgrades Generating Demand for Multifamily Building Upgrades Better Buildings Residential Network Peer Exchange Call Series: Generating...

  18. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

    demand response: ? Distribution utility ? ISO ? Aggregator (demand response less obstructive and inconvenient for the customer (particularly if DR resources are aggregated by a load aggregator).

  19. California Energy Demand Scenario Projections to 2050

    E-Print Network [OSTI]

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

    2008-01-01

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

  20. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

    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

  1. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

    Energy Efficiency, Demand Response, and Peak Load Managementdemand response, and load management programs in the Ebefore they undertake load management and demand response

  2. Supply chain planning decisions under demand uncertainty

    E-Print Network [OSTI]

    Huang, Yanfeng Anna

    2008-01-01

    Sales and operational planning that incorporates unconstrained demand forecasts has been expected to improve long term corporate profitability. Companies are considering such unconstrained demand forecasts in their decisions ...

  3. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

    > B-2 Coordination of Energy Efficiency and Demand Response> B-4 Coordination of Energy Efficiency and Demand Responseand integration is: Energy efficiency, energy conservation,

  4. Generating Demand for Multifamily Building Upgrades | Department...

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

    Generating Demand for Multifamily Building Upgrades Generating Demand for Multifamily Building Upgrades May 14, 2015 12:30PM to 2:00PM EDT Learn more...

  5. 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

  6. Turkey's energy demand and supply

    SciTech Connect (OSTI)

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

    2009-07-01

    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.

  7. International Oil Supplies and Demands

    SciTech Connect (OSTI)

    Not Available

    1992-04-01

    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.

  8. International Oil Supplies and Demands

    SciTech Connect (OSTI)

    Not Available

    1991-09-01

    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.

  9. Demand Response and Energy Efficiency 

    E-Print Network [OSTI]

    2009-01-01

    stream_source_info ESL-IC-09-11-05.pdf.txt stream_content_type text/plain stream_size 14615 Content-Encoding ISO-8859-1 stream_name ESL-IC-09-11-05.pdf.txt Content-Type text/plain; charset=ISO-8859-1 Demand Response... 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...

  10. Implications of maximizing China's technical potential for residential end-use energy efficiency: A 2030 outlook from the bottom-up

    E-Print Network [OSTI]

    Khanna, Nina

    2014-01-01

    Levine. 2012. “China's Energy and Emissions Outlook to 2050:on China’s Future Energy and Emissions Outlook. LBNL-4032E.Energy Demand Outlook

  11. Schneider Electric Boasts Ten Facilities Certified to Superior...

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

    ten facilities certified to the Superior Energy Performance (SEP(tm)) program and to ISO 50001 in the United States, Canada, and Mexico. This is the most SEP certifications...

  12. IIA/IIB Supergravity and Ten-forms

    E-Print Network [OSTI]

    E. A. Bergshoeff; J. Hartong; P. S. Howe; T. Ortin; F. Riccioni

    2010-04-08

    We perform a careful investigation of which p-form fields can be introduced consistently with the supersymmetry algebra of IIA and/or IIB ten-dimensional supergravity. In particular the ten-forms, also known as "top-forms", require a careful analysis since in this case, as we will show, closure of the supersymmetry algebra at the linear level does not imply closure at the non-linear level. Consequently, some of the (IIA and IIB) ten-form potentials introduced in earlier work of some of us are discarded. At the same time we show that new ten-form potentials, consistent with the full non-linear supersymmetry algebra can be introduced. We give a superspace explanation of our work. All of our results are precisely in line with the predictions of the E(11) algebra.

  13. Revelation on Demand Nicolas Anciaux

    E-Print Network [OSTI]

    is willing to reveal the aggregate response (according to his company's policy) to the customer dataRevelation on Demand Nicolas Anciaux 1 · Mehdi Benzine1,2 · Luc Bouganim1 · Philippe Pucheral1 time to support epidemiological studies. In these and many other situations, aggregate data or partial

  14. Demand Response Providing Ancillary Services

    E-Print Network [OSTI]

    1 Demand Response Providing Ancillary Services: A Comparison of Opportunities and Challenges in US to operate (likely price takers) ­ Statistical reliability (property of large aggregations of small resources size based on Mid-Atlantic Reserve Zone #12;Market Rules: Resource Size Min. Size (MW) Aggregation

  15. Water demand management in Kuwait

    E-Print Network [OSTI]

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

    2006-01-01

    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 ...

  16. On-demand data broadcasting 

    E-Print Network [OSTI]

    Kothandaraman, Kannan

    1998-01-01

    related to on-demand data broadcasting. We look at the problem of data broadcasting in an environment where clients make explicit requests to the server. The server broadcasts requested data items to all the clients, including those who have not requested...

  17. Promising Technology: Demand Control Ventilation

    Broader source: Energy.gov [DOE]

    Demand control ventilation (DCV) measures carbon dioxide concentrations in return air or other strategies to measure occupancy, and accurately matches the ventilation requirement. This system reduces ventilation when spaces are vacant or at lower than peak occupancy. When ventilation is reduced, energy savings are accrued because it is not necessary to heat, cool, or dehumidify as much outside air.

  18. April 30 Public Meeting: Physical Characterization of Smart and Grid-Connected Commercial and Residential Building End-Use Equipment and Appliances

    Broader source: Energy.gov [DOE]

    These documents contain slide decks presented at the Physical Characterization of Smart and Grid-Connected Commercial and Residential Buildings End-Use Equipment and Appliances public meeting held on April 30, 2014. The first document includes the first presentation from the meeting: DOE Vision and Objectives. The second document includes all other presentations from the meeting: Terminology and Definitions; End-User and Grid Services; Physical Characterization Framework; Value, Benefits & Metrics.

  19. Effects of the drought on California electricity supply and demand

    E-Print Network [OSTI]

    Benenson, P.

    2010-01-01

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

  20. Automated Demand Response Opportunities in Wastewater Treatment Facilities

    E-Print Network [OSTI]

    Thompson, Lisa

    2008-01-01

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

  1. Northwest Open Automated Demand Response Technology Demonstration Project

    E-Print Network [OSTI]

    Kiliccote, Sila

    2010-01-01

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

  2. Opportunities, Barriers and Actions for Industrial Demand Response in California

    E-Print Network [OSTI]

    McKane, Aimee T.

    2009-01-01

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

  3. Incorporating Demand Response into Western Interconnection Transmission Planning

    E-Print Network [OSTI]

    Satchwell, Andrew

    2014-01-01

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

  4. Upply Chain Supernetworks with Random Demands

    E-Print Network [OSTI]

    Nagurney, Anna

    Upply Chain Supernetworks with Random Demands June Dong & Ding Zhang School of Business State Warehouses: stocking points Field Warehouses: stocking points Customers, demand centers sinks Production Commerce and Value Chain Management, 1998 Customer Demand Customer Demand Retailer OrdersRetailer Orders

  5. Assessment of Demand Response and Advanced Metering

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    #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

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

    SciTech Connect (OSTI)

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

    2009-02-01

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

  7. The alchemy of demand response: turning demand into supply

    SciTech Connect (OSTI)

    Rochlin, Cliff

    2009-11-15

    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)

  8. California Baseline Energy Demands to 2050 for Advanced Energy Pathways

    E-Print Network [OSTI]

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

    2008-01-01

    End use energy consumption per square-foot and floorspaceof floorspace and energy consumption per square-foot, for 10

  9. Japan's Residential Energy Demand Outlook to 2030 Considering Energy Efficiency Standards"Top-Runner Approach"

    SciTech Connect (OSTI)

    Lacommare, Kristina S H; Komiyama, Ryoichi; Marnay, Chris

    2008-05-15

    As one of the measures to achieve the reduction in greenhouse gas emissions agreed to in the"Kyoto Protocol," an institutional scheme for determining energy efficiency standards for energy-consuming appliances, called the"Top-Runner Approach," was developed by the Japanese government. Its goal is to strengthen the legal underpinnings of various energy conservation measures. Particularly in Japan's residential sector, where energy demand has grown vigorously so far, this efficiency standard is expected to play a key role in mitigating both energy demand growth and the associated CO2 emissions. This paper presents an outlook of Japan's residential energy demand, developed by a stochastic econometric model for the purpose of analyzing the impacts of the Japan's energy efficiency standards, as well as the future stochastic behavior of income growth, demography, energy prices, and climate on the future energy demand growth to 2030. In this analysis, we attempt to explicitly take into consideration more than 30 kinds of electricity uses, heating, cooling and hot water appliances in order to comprehensively capture the progress of energy efficiency in residential energy end-use equipment. Since electricity demand, is projected to exhibit astonishing growth in Japan's residential sector due to universal increasing ownership of electric and other appliances, it is important to implement an elaborate efficiency standards policy for these appliances.

  10. BUILDINGS SECTOR DEMAND-SIDE EFFICIENCY TECHNOLOGY SUMMARIES

    E-Print Network [OSTI]

    ........................................................................... 59 End-Use: Water Heating Sector: Residential Author: Jim Lutz VIII. Heat Pump Water Heaters) ................................................................ 5 End-Use: Lighting, HVAC Sector: Commercial, Industrial, Residential Author: Kristin Heinemeier II End-Use: Interior Lighting Sector: Commercial, Industrial Author: Ellen Franconi III. Compact

  11. 1980 survey and evaluation of utility conservation, load management, and solar end-use projects. Volume 3: utility load management projects. Final report

    SciTech Connect (OSTI)

    Not Available

    1982-01-01

    The results of the 1980 survey of electric utility-sponsored energy conservation, load management, and end-use solar energy conversion projects are described. The work is an expansion of a previous survey and evaluation and has been jointly sponsored by EPRI and DOE through the Oak Ridge National Laboratory. There are three volumes and a summary document. Each volume presents the results of an extensive survey to determine electric utility involvement in customer-side projects related to the particular technology (i.e., conservation, solar, or load management), selected descriptions of utility projects and results, and first-level technical and economic evaluations.

  12. PATTERNS OF UNITED STATES MORTALITY FOR TEN SELECTED CAUSES OF DEATH

    E-Print Network [OSTI]

    Selvin, S.

    2013-01-01

    variables) for the ten selected causes of death. Figure 7.for the ten selected causes of death for males. Figure 8.for the ten selected causes of death for females. Figure 9.

  13. STEO December 2012 - coal demand

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home RoomPreservation of Fe(II) byMultidayAlumni > The2/01/12 Page 1NEWSSupportcoal demand seen below

  14. Export Controls "Top Ten" List Considerations for All University Employees

    E-Print Network [OSTI]

    Massachusetts at Amherst, University of

    Export Controls "Top Ten" List Considerations for All University Employees 1. Export control laws various aspects of export controls: · Department of Commerce for civilian and "dual-use" technologies sanctions. 3. There are two kinds of exports: · Physical shipments of technology and equipment to a foreign

  15. Technical descriptions of ten irrigation technologies for conserving energy

    SciTech Connect (OSTI)

    Harrer, B.J.; Wilfert, G.L.

    1983-05-01

    Technical description of ten technologies which were researched to save energy in irrigated agriculture are presented. These technologies are: well design and development ground water supply system optimization, column and pump redesign, variable-speed pumping, pipe network optimization, reduced-pressure center-pivot systems, low-energy precision application, automated gated-pipe system, computerized irrigation scheduling, and instrumented irrigation scheduling. (MHR)

  16. Scaling Microblogging Services with Divergent Traffic Demands

    E-Print Network [OSTI]

    Fu, Xiaoming

    Scaling Microblogging Services with Divergent Traffic Demands Tianyin Xu, Yang Chen, Lei Jiao, Ben-server architecture has not scaled with user demands, lead- ing to server overload and significant impairment

  17. Michel Meulpolder Managing Supply and Demand of

    E-Print Network [OSTI]

    Michel Meulpolder Managing Supply and Demand of Bandwidth in Peer-to-Peer Communities #12;#12;Managing Supply and Demand of Bandwidth in Peer-to-Peer Communities Proefschrift ter verkrijging van de

  18. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    relatively high economic/demographic growth, relatively low electricity and natural gas rates REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION Robert P

  19. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    /demographic growth, relatively low electricity and natural gas rates, and relatively low efficiency program CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 1: Statewide Electricity Manager Bill Junker Manager DEMAND ANALYSIS OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY

  20. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    incorporates relatively high economic/demographic growth, relatively low electricity and natural gas rates CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST Volume 2: Electricity Demand Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION Robert P. Oglesby Executive

  1. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    incorporates relatively high economic/demographic growth, relatively low electricity and natural gas rates CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand OFFICE Sylvia Bender Deputy Director ELECTRICITY SUPPLY ANALYSIS DIVISION Robert P

  2. Solar in Demand | Department of Energy

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

    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...

  3. Demand Effects in Productivity and Efficiency Analysis 

    E-Print Network [OSTI]

    Lee, Chia-Yen

    2012-07-16

    Demand fluctuations will bias the measurement of productivity and efficiency. This dissertation described three ways to characterize the effect of demand fluctuations. First, a two-dimensional efficiency decomposition (2DED) of profitability...

  4. Industrial Equipment Demand and Duty Factors 

    E-Print Network [OSTI]

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

    1998-01-01

    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 ...

  5. Coordination of Energy Efficiency and Demand Response

    SciTech Connect (OSTI)

    none,

    2010-01-01

    Summarizes existing research and discusses current practices, opportunities, and barriers to coordinating energy efficiency and demand response programs.

  6. Decentralized demand management for water distribution 

    E-Print Network [OSTI]

    Zabolio, Dow Joseph

    1989-01-01

    OF THE DEMAND CURVE 30 31 35 39 Model Development Results 39 45 VI CONTROLLER DESIGN AND COSTS 49 Description of Controller Production and Installation Costs 49 50 VII SYSTEM EVALUATION AND ECONOMICS 53 System Response and Degree of Control... Patterns 9 Typical Winter Diurnal Patterns 10 Trace of Marginal Pump Efficiency and Hourly Demand 11 Original Demand Distribution and Possible Redistributions 33 34 40 41 43 46 12 Typical Nodal Responses to Demand Change 54 ix LIST OF TABLES...

  7. Demand Response Valuation Frameworks Paper

    SciTech Connect (OSTI)

    Heffner, Grayson

    2009-02-01

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

  8. Demand Queries with Preprocessing Uriel Feige

    E-Print Network [OSTI]

    Demand Queries with Preprocessing Uriel Feige and Shlomo Jozeph May 1, 2014 )>IJH=?J Given a set of items and a submodular set-function f that determines the value of every subset of items, a demand query, the value of S minus its price. The use of demand queries is well motivated in the context of com

  9. DemandDriven Pointer Analysis Nevin Heintze

    E-Print Network [OSTI]

    Tardieu, Olivier

    Demand­Driven Pointer Analysis Nevin Heintze Research, Agere Systems (formerly Lucent Technologies analysis of a pro­ gram or program component. In this paper we introduce a demand­driven approach for pointer analysis. Specifically, we describe a demand­driven flow­insensitive, subset­based, context

  10. APPLICATION-FORM DEMANDED'ADMISSION

    E-Print Network [OSTI]

    Opportunities and Challenges for Data Center Demand Response Adam Wierman Zhenhua Liu Iris Liu of renewable energy into the grid as well as electric power peak-load shaving: data center demand response. Data center demand response sits at the intersection of two growing fields: energy efficient data

  11. Airline Pilot Demand Projections What this is-

    E-Print Network [OSTI]

    Bustamante, Fabián E.

    60 Mobile applications constantly demand additional memory, and traditional designs increase but also e-mail, Internet access, digital camera features, and video on demand. With feature expansion demanding additional storage and memory in all com- puting devices, DRAM and flash memory densities

  12. Algorithms Demands and Bounds Applications of Flow

    E-Print Network [OSTI]

    Kabanets, Valentine

    2/28/2014 1 Algorithms ­ Demands and Bounds Applications of Flow Networks Design and Analysis of Algorithms Andrei Bulatov Algorithms ­ Demands and Bounds 12-2 Lower Bounds The problem can be generalized) capacities (ii) demands (iii) lower bounds A circulation f is feasible if (Capacity condition) For each e E

  13. Adapton: Composable, Demand-Driven Incremental Computation

    E-Print Network [OSTI]

    Hicks, Michael

    Adapton: Composable, Demand-Driven Incremental Computation CS-TR-5027 -- July 12, 2013 Matthew A demands on the program output; that is, if a program input changes, all depen- dencies will be recomputed. To address these problems, we present cdd ic , a core calculus that applies a demand-driven seman- tics

  14. Pricing Cloud Bandwidth Reservations under Demand Uncertainty

    E-Print Network [OSTI]

    Li, Baochun

    Heap Assumptions on Demand Andreas Podelski1 , Andrey Rybalchenko2 , and Thomas Wies1 1 University analysis produces heap assumptions on demand to eliminate counterexamples, i.e., non-terminating abstract of a non-terminating abstract computation, i.e., it applies shape analysis on demand. The shape analysis

  15. Demand And Response Transportation Rider's Guide

    E-Print Network [OSTI]

    Acton, Scott

    Demand And Response Transportation Rider's Guide http://www.virginia.edu/parking/disabilities/dart Version 14.5 (8/13/14) Welcome DART Rider: The Demand and Response Transportation (DART) Service rides: #12;Demand And Response Transportation Rider's Guide http

  16. Scaling Microblogging Services with Divergent Traffic Demands

    E-Print Network [OSTI]

    Almeroth, Kevin C.

    Scaling Microblogging Services with Divergent Traffic Demands Tianyin Xu1 , Yang Chen1 , Lei Jiao1 client-server architecture has not scaled with user demands, leading to server overload and significant #12;Scaling Microblogging Services with Divergent Traffic Demands 21 producing effective predictions

  17. Demande de diplmes NOM,Prnom : ......................................................................................................................

    E-Print Network [OSTI]

    Chamroukhi, Faicel

    Optimal demand response: problem formulation and deterministic case Lijun Chen, Na Li, Libin Jiang load through real-time demand response and purchases balancing power on the spot market to meet the aggregate demand. Hence optimal supply procurement by the LSE and the consumption decisions by the users

  18. Precision On Demand: An Improvement in Probabilistic

    E-Print Network [OSTI]

    Precision On Demand: An Improvement in Probabilistic Hashing Igor Melatti, Robert Palmer approach Precision on Demand or POD). #12;This paper provides a scientific evaluation of the pros and cons time likely to increase by a factor of 1.8 or less. #12;Precision On Demand: An Improvement

  19. ADAPTON: Composable, Demand-Driven Incremental Computation

    E-Print Network [OSTI]

    Hicks, Michael

    ADAPTON: Composable, Demand- Driven Incremental Computation Abstract Many researchers have proposed important drawbacks. First, recomputation is oblivious to specific demands on the program output; that is ic , a core calculus that applies a demand-driven semantics to incremental computa- tion, tracking

  20. Constructing Speculative Demand Functions in Equilibrium Markets

    E-Print Network [OSTI]

    On the Convergence of Statistical Techniques for Inferring Network Traffic Demands Alberto Medina1 of traffic demands in a communication net- work enables or enhances a variety of traffic engineering and net set of these demands is prohibitively expensive because of the huge amounts of data that must

  1. Heap Assumptions on Demand Andreas Podelski1

    E-Print Network [OSTI]

    Wies, Thomas

    Heap Assumptions on Demand Andreas Podelski1 , Andrey Rybalchenko2 , and Thomas Wies1 1 University checker and shape analysis. The shape analysis pro- duces heap assumptions on demand to eliminate.e., it applies shape analysis on demand. The shape analysis produces a heap assumption, which is an assertion

  2. Appeld'offrespublic Demanded'approvisionnement

    E-Print Network [OSTI]

    Montréal, Université de

    ATM for Video and Audio on Demand David Greaves. University of Cambridge and ATM Ltd. email: djg fast, particularly for video- on-demand. These digital streams require constant-rate digi- tal channels of the Cambridge Digital Interactive Television Trial, where Video and Audio on demand are transported to the Home

  3. Precision On Demand: An Improvement in Probabilistic

    E-Print Network [OSTI]

    Precision On Demand: An Improvement in Probabilistic Hashing Igor Melatti, Robert Palmer approach Precision on Demand or POD). #12; This paper provides a scientific evaluation of the pros and cons time likely to increase by a factor of 1.8 or less. #12; Precision On Demand: An Improvement

  4. FORECAST COMBINATION IN REVENUE MANAGEMENT DEMAND FORECASTING

    E-Print Network [OSTI]

    Fernandez, Thomas

    Demandness in Rewriting and Narrowing Sergio Antoy1 and Salvador Lucas2 1 Computer Science by a strategy to compute a step. The notion of demandness provides a suitable framework for pre- senting that the notion of demandness is both atomic and fundamental to the study of strategies. 1 Introduction Modern

  5. Resolution on Demand Bianka BuschbeckWolf

    E-Print Network [OSTI]

    Reyle, Uwe

    Resolution on Demand Bianka Buschbeck­Wolf Universit¨at Stuttgart Report 196 May 1997 #12; May 1997¨ur den Inhalt dieser Arbeit liegt bei der Autorin. #12; Resolution on Demand Abstract Following the strategy of resolution on demand, the transfer component triggers inference processes in analysis

  6. Heap Assumptions on Demand Andreas Podelski1

    E-Print Network [OSTI]

    Wies, Thomas

    PROTOTYPE IMPLEMENTATION OF A DEMAND DRIVEN NETWORK MONITORING ARCHITECTURE Augusto Ciuffoletti for demand driven monitoring, named gd2, that can be potentially integrated in the gLite framework. We capable of managing the scalability challenge offered by a Grid environment: i) demand driven

  7. Pricing Cloud Bandwidth Reservations under Demand Uncertainty

    E-Print Network [OSTI]

    Li, Baochun

    Pricing Cloud Bandwidth Reservations under Demand Uncertainty Di Niu, Chen Feng, Baochun Li's utility depends not only on its bandwidth usage, but more importantly on the portion of its demand that can be made by all tenants and the cloud provider, even with the presence of demand uncertainty

  8. Transportation Energy: Supply, Demand and the Future

    E-Print Network [OSTI]

    Saldin, Dilano

    trends in China, India, Eastern Europe and other developing areas. China oil demand +104% by 2030, India 2000 2020 2040 2060 Supply demand Energy UWM-CUTS 14 U.S. DOE viewpoint, source:http://tonto.eia.doe.gov/FTPROOT/features/longterm.pdf#search='oilTransportation Energy: Supply, Demand and the Future http://www.uwm.edu/Dept/CUTS//2050/energy05

  9. Modeling Energy Demand Aggregators for Residential Consumers

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Modeling 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- response paradigm. When the energy provider needs to reduce the current energy demand on the grid, it can

  10. INTEGRATION OF PV IN DEMAND RESPONSE

    E-Print Network [OSTI]

    Perez, Richard R.

    INTEGRATION OF PV IN DEMAND RESPONSE PROGRAMS Prepared by Richard Perez et al. NREL subcontract the case that distributed PV generation deserves a substantial portion of the credit allotted to demand response programs. This is because PV generation acts as a catalyst to demand response, markedly enhancing

  11. Demand Response for Computing Jerey S. Chase

    E-Print Network [OSTI]

    Chase, Jeffrey S.

    Chapter 1 Demand Response for Computing Centers Jerey S. Chase Duke University 1.1 Introduction ............................................................... 3 1.2 Demand Response in the Emerging Smart Grid .......................... 5 1.2.1 Importance of Demand Response for Energy E ciency .......... 6 1.2.2 The Role of Renewable Energy

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. Barrier Immune Radio Communications for Demand Response

    E-Print Network [OSTI]

    LBNL-2294E Barrier Immune Radio Communications for Demand Response F. Rubinstein, G. Ghatikar, J Ann Piette of Lawrence Berkeley National Laboratory's (LBNL) Demand Response Research Center (DRRC and Environment's (CIEE) Demand Response Emerging Technologies Development (DRETD) Program, under Work for Others

  19. 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

  20. 3-D Characterization of the Structure of Paper and Paperboard and Their Application to Optimize Drying and Water Removal Processes and End-Use Applications

    SciTech Connect (OSTI)

    Shri Ramaswamy, University of Minnesota; B.V. Ramarao, State University of New York

    2004-08-29

    The three dimensional structure of paper materials plays a critical role in the paper manufacturing process especially via its impact on the transport properties for fluids. Dewatering of the wet web, pressing and drying will benefit from knowledge of the relationships between the web structure and its transport coefficients. The structure of the pore space within a paper sheet is imaged in serial sections using x-ray micro computed tomography. The three dimensional structure is reconstructed from these sections using digital image processing techniques. The structure is then analyzed by measuring traditional descriptors for the pore space such as specific surface area and porosity. A sequence of microtomographs was imaged at approximately 2 ?m intervals and the three-dimensional pore-fiber structure was reconstructed. The pore size distributions for both in-plane as well as transverse pores were measured. Significant differences in the in-plane (XY) and the transverse directions in pore characteristics are found and may help partly explain the different liquid and vapor transport properties in the in-plane and transverse directions. Results with varying sheet structures compare favorably with conventional mercury intrusion porosimetry data. Interestingly, the transverse pore structure appears to be more open with larger pore size distribution compared to the in plane pore structure. This may help explain the differences in liquid and vapor transport through the in plane and transverse structures during the paper manufacturing process and during end-use application. Comparison of Z-directional structural details of hand sheet and commercially made fine paper samples show a distinct difference in pore size distribution both in the in-plane and transverse direction. Method presented here may provide a useful tool to the papermaker to truly engineer the structure of paper and board tailored to specific end-use applications. The difference in surface structure between the top and bottom sides of the porous material, i.e. "two-sidedness" due to processing and raw material characteristics may lead to differences in end-use performance. The measurements of surface structure characteristics include thickness distribution, surface volume distribution, contact fraction distribution and surface pit distribution. This complements our earlier method to analyze the bulk structure and Z-D structure of porous materials. As one would expect, the surface structure characteristics will be critically dependent on the quality and resolution of the images. This presents a useful tool to characterize and engineer the surface structure of porous materials such as paper and board tailored to specific end-use applications. This will also help troubleshoot problems related to manufacturing and end-use applications. This study attempted to identify the optimal resolution through a comparison between 3D images obtained by monochromatic synchrotron radiation X-?CT in phase contrast mode (resolution ? 1 ?m) and polychromatic radiation X-?CT in absorption mode (res. ? 5 ?m). It was found that both resolutions have the ability to show the expected trends when comparing different paper samples. The low resolution technique shows fewer details resulting in lower specific surface area, larger pore channels, characterized as hydraulic radii, and lower tortuosities, where differences between samples and principal directions are more difficult to detect. The disadvantages of the high resolution images are high cost and limited availability of hard x-ray beam time as well as the small size of the sample volumes imaged. The results show that the low resolution images can be used for comparative studies, whereas the high resolution images may be better suited for fundamental research on the paper structure and its influence on paper properties, as one gets more accurate physical measurements. In addition, pore space diffusion model has been developed to simulate simultaneous diffusion in heterogeneous porous materials such as paper containing cellu

  1. Energy demand and population changes

    SciTech Connect (OSTI)

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

    1980-12-01

    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.

  2. Demande de casier 20142015 1. Demande ( remplir par l'lve)

    E-Print Network [OSTI]

    Demande de casier 20142015 1. Demande (à remplir par l'élève) Nom : . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . Demande l'attribution d'un casier pour y déposer) : . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . En cas d'acceptation de ma demande, je retirerai ma clé contre un chèque de caution d'un montant de

  3. DEMANDE DE CONGE Cette demande doit tre effectue un mois avant le dbut du semestre.

    E-Print Network [OSTI]

    Halazonetis, Thanos

    DEMANDE DE CONGE Cette demande doit être effectuée un mois avant le début du semestre. Date de la demande .......................................................... NOM-mail .......................................................................................................................................................................... @etu.unige.ch Demande à être mis au bénéfice d'un congé pour le(s) semestre(s) suivant(s) (2 semestres

  4. Risk Management for Video-on-Demand Servers leveraging Demand Forecast

    E-Print Network [OSTI]

    Li, Baochun

    Risk Management for Video-on-Demand Servers leveraging Demand Forecast Di Niu, Hong Xu, Baochun Li}@eecg.toronto.edu Shuqiao Zhao Multimedia Development Group UUSee, Inc. shuqiao.zhao@gmail.com ABSTRACT Video-on-demand (VoD) servers are usually over-provisioned for peak demands, incurring a low average resource effi- ciency

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

    E-Print Network [OSTI]

    Sastry, S. Shankar

    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

  6. Real-time Pricing Demand Response in Operations

    SciTech Connect (OSTI)

    Widergren, Steven E.; Marinovici, Maria C.; Berliner, Teri; Graves, Alan

    2012-07-26

    Abstract—Dynamic pricing schemes have been implemented in commercial and industrial application settings, and recently they are getting attention for application to residential customers. Time-of-use and critical-peak-pricing rates are in place in various regions and are being piloted in many more. These programs are proving themselves useful for balancing energy during peak periods; however, real-time (5 minute) pricing signals combined with automation in end-use systems have the potential to deliver even more benefits to operators and consumers. Besides system peak shaving, a real-time pricing system can contribute demand response based on the locational marginal price of electricity, reduce load in response to a generator outage, and respond to local distribution system capacity limiting situations. The US Department of Energy (DOE) is teaming with a mid-west electricity service provider to run a distribution feeder-based retail electricity market that negotiates with residential automation equipment and clears every 5 minutes, thus providing a signal for lowering or raising electric consumption based on operational objectives of economic efficiency and reliability. This paper outlines the capability of the real-time pricing system and the operational scenarios being tested as the system is rolled-out starting in the first half of 2012.

  7. Opportunities, Barriers and Actions for Industrial Demand Response in California

    E-Print Network [OSTI]

    McKane, Aimee T.

    2009-01-01

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

  8. Direct versus Facility Centric Load Control for Automated Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2010-01-01

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

  9. Open Automated Demand Response for Small Commerical Buildings

    E-Print Network [OSTI]

    Dudley, June Han

    2009-01-01

    of Fully Automated Demand  Response in Large Facilities.  Fully Automated Demand Response Tests in Large Facilities.  Open Automated  Demand Response Communication Standards: 

  10. Climate, extreme heat, and electricity demand in California

    E-Print Network [OSTI]

    Miller, N.L.

    2008-01-01

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

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

    E-Print Network [OSTI]

    Letschert, Virginie

    2010-01-01

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

  12. California Baseline Energy Demands to 2050 for Advanced Energy Pathways

    E-Print Network [OSTI]

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

    2008-01-01

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

  13. Assessing Vehicle Electricity Demand Impacts on California Electricity Supply

    E-Print Network [OSTI]

    McCarthy, Ryan W.

    2009-01-01

    fuel efficiency and electricity demand assumptions used into added vehicle electricity demand in the BAU (no IGCC)to added vehicle electricity demand in the Mixed technology

  14. SAN ANTONIO SPURS DEMAND FOR ENERGY EFFICIENCY | Department of...

    Energy Savers [EERE]

    SAN ANTONIO SPURS DEMAND FOR ENERGY EFFICIENCY SAN ANTONIO SPURS DEMAND FOR ENERGY EFFICIENCY SAN ANTONIO SPURS DEMAND FOR ENERGY EFFICIENCY As a city that experiences seasonal...

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

    E-Print Network [OSTI]

    Letschert, Virginie

    2010-01-01

    2007). Coping with Residential Electricity Demand in India'sResidential Electricity Demand in China –Can EfficiencyBoom of Electricity Demand in the residential sector in the

  16. Climate, extreme heat, and electricity demand in California

    E-Print Network [OSTI]

    Miller, N.L.

    2008-01-01

    Peirson. 1998. Residential energy demand and the interactionresponse of residential cooling energy demand to climaterise in residential and commercial electricity demand can be

  17. Coordination of Retail Demand Response with Midwest ISO Markets

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2008-01-01

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

  18. Rates and technologies for mass-market demand response

    E-Print Network [OSTI]

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

    2002-01-01

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

  19. Open Automated Demand Response Dynamic Pricing Technologies and Demonstration

    E-Print Network [OSTI]

    Ghatikar, Girish

    2010-01-01

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

  20. Linking Continuous Energy Management and Open Automated Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01

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

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

    E-Print Network [OSTI]

    Cappers, Peter

    2009-01-01

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

  2. LEED Demand Response Credit: A Plan for Research towards Implementation

    E-Print Network [OSTI]

    Kiliccote, Sila

    2014-01-01

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

  3. Open Automated Demand Response Communications Specification (Version 1.0)

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01

    and Techniques for Demand Response. May 2007. LBNL-59975.to facilitate automating  demand response actions at the Interoperable Automated Demand Response Infrastructure,

  4. Demand Response Opportunities in Industrial Refrigerated Warehouses in California

    E-Print Network [OSTI]

    Goli, Sasank

    2012-01-01

    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).

  5. Results and commissioning issues from an automated demand response pilot

    E-Print Network [OSTI]

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

    2004-01-01

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

  6. California Baseline Energy Demands to 2050 for Advanced Energy Pathways

    E-Print Network [OSTI]

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

    2008-01-01

    CEC (2005b) Energy demand forecast methods report.growth in California energy demands forecast in the baseline2006-2016: Staff energy demand forecast (Revised September

  7. National Action Plan on Demand Response | Department of Energy

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

    Working Group (FUPWG) Fall 2008 meeting-discusses the National Assessment of Demand Response study, the National Action Plan for Demand Response, and demand response as...

  8. Trends in End-Use Industries to Shape Growth in Global Forest Products Market, According to a New Report by Global Industry Analysts

    E-Print Network [OSTI]

    , such as origin of raw materials, and manufacturing process. Globalization offers several benefits to the industry technologically improved products. Globalization has also brought about a gradual change, with sourcing of raw materials shifting to emerging forest producing regions. Demand for forest products is also determined

  9. Electricity Demand and Energy Consumption Management System

    E-Print Network [OSTI]

    Sarmiento, Juan Ojeda

    2008-01-01

    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...

  10. Electric Utility Demand-Side Evaluation Methodologies 

    E-Print Network [OSTI]

    Treadway, N.

    1986-01-01

    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... cost and certification proceedings. A s~andard benefit-cost methodology analyzes demand-slde management programs from various ~oints of view. The benefit-cost methodology now ln use by several electric utilities and the * The views presented...

  11. Opportunities, Barriers and Actions for Industrial Demand Response in California

    SciTech Connect (OSTI)

    McKane, Aimee T.; Piette, Mary Ann; Faulkner, David; Ghatikar, Girish; Radspieler Jr., Anthony; Adesola, Bunmi; Murtishaw, Scott; Kiliccote, Sila

    2008-01-31

    In 2006 the Demand Response Research Center (DRRC) formed an Industrial Demand Response Team to investigate opportunities and barriers to implementation of Automated Demand Response (Auto-DR) systems in California industries. Auto-DR is an open, interoperable communications and technology platform designed to: Provide customers with automated, electronic price and reliability signals; Provide customers with capability to automate customized DR strategies; Automate DR, providing utilities with dispatchable operational capability similar to conventional generation resources. This research began with a review of previous Auto-DR research on the commercial sector. Implementing Auto-DR in industry presents a number of challenges, both practical and perceived. Some of these include: the variation in loads and processes across and within sectors, resource-dependent loading patterns that are driven by outside factors such as customer orders or time-critical processing (e.g. tomato canning), the perceived lack of control inherent in the term 'Auto-DR', and aversion to risk, especially unscheduled downtime. While industry has demonstrated a willingness to temporarily provide large sheds and shifts to maintain grid reliability and be a good corporate citizen, the drivers for widespread Auto-DR will likely differ. Ultimately, most industrial facilities will balance the real and perceived risks associated with Auto-DR against the potential for economic gain through favorable pricing or incentives. Auto-DR, as with any ongoing industrial activity, will need to function effectively within market structures. The goal of the industrial research is to facilitate deployment of industrial Auto-DR that is economically attractive and technologically feasible. Automation will make DR: More visible by providing greater transparency through two-way end-to-end communication of DR signals from end-use customers; More repeatable, reliable, and persistent because the automated controls strategies that are 'hardened' and pre-programmed into facility's software and hardware; More affordable because automation can help reduce labor costs associated with manual DR strategies initiated by facility staff and can be used for long-term.

  12. Demand Responsive Lighting: A Scoping Study

    E-Print Network [OSTI]

    Rubinstein, Francis; Kiliccote, Sila

    2007-01-01

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

  13. 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...

  14. Geographically Based Hydrogen Demand and Infrastructure Analysis...

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

    Analysis Geographically Based Hydrogen Demand and Infrastructure Analysis Presentation by NREL's Margo Melendez at the 2010 - 2025 Scenario Analysis for Hydrogen Fuel Cell Vehicles...

  15. Operationalizing demand forecasts in the warehouse

    E-Print Network [OSTI]

    Li, Dan, Ph. D. University of Rochester

    2015-01-01

    Demand planning affects the subsequent business activities including distribution center operational planning and management. Today's competitive environment requires distribution centers to rapidly respond to changes in ...

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

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

    January 16, 2011 Conference Call transcript: "Marketing & Driving Demand: Social Media Tools & Strategies," from the U.S. Department of Energy. Conference call transcript More...

  17. Integration of Demand Side Management, Distributed Generation...

    Open Energy Info (EERE)

    Integration of Demand Side Management, Distributed Generation, Renewable Energy Sources, and Energy Storages: State-of-the-Art Report, Volume 1, Main Report Jump to: navigation,...

  18. Optimization of Demand Response Through Peak Shaving

    E-Print Network [OSTI]

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

  19. Coordination of Energy Efficiency and Demand Response

    E-Print Network [OSTI]

    Goldman, Charles

    2010-01-01

    National Action Plan for Energy Efficiency Energy efficiency programson energy efficiency program types, see National Action PlanNational Action Plan for Energy Efficiency Most demand response programs

  20. Demand Response in the ERCOT Markets

    SciTech Connect (OSTI)

    Patterson, Mark

    2011-10-25

    ERCOT grid serves 85% of Texas load over 40K+ miles transmission line. Demand response: voluntary load response, load resources, controllable load resources, and emergency interruptible load service.

  1. Hawaiian Electric Company Demand Response Roadmap Project

    E-Print Network [OSTI]

    Levy, Roger

    2014-01-01

    Demand  Response  Roadmap  Project   Final  Report  39   5.   Developing a Roadmap Actionproject was to develop a “roadmap” to guide the Hawaiian

  2. Optimization of Demand Response Through Peak Shaving

    E-Print Network [OSTI]

    2013-06-19

    Jun 19, 2013 ... efficient linear programming formulation for the demand response of such a consumer who could be a price taker, industrial or commercial user ...

  3. BPA, Energy Northwest launch demand response pilot

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

    BPA-Energy-Northwest-launch-demand-response-pilot Sign In About | Careers | Contact | Investors | bpa.gov Search News & Us Expand News & Us Projects & Initiatives Expand...

  4. Wireless Demand Response Controls for HVAC Systems

    E-Print Network [OSTI]

    Federspiel, Clifford

    2010-01-01

    conditioning. Figure 2: Wireless discharge air temperatureWireless Demand Response Controls for HVAC Systems Cliffordcontrol software and wireless hardware that could enable

  5. California Energy Demand Scenario Projections to 2050

    E-Print Network [OSTI]

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

    2008-01-01

    Forecasts of California transportation energy demand, 2005-alternative transportation energy pathways on California’salternative transportation energy pathways on California’s

  6. Reducing Logistics Footprints and Replenishment Demands: Nano...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: Reducing Logistics Footprints and Replenishment Demands: Nano-engineered Silica Aerogels a Proven Method for Water Treatment Citation Details In-Document Search...

  7. Ten Projects Awarded NERSC Allocations under DOE's ALCC Program

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home RoomPreservationBio-Inspired Solar FuelTechnologyTel: Name: Rm. Tel: Location: Rm. OctTen Projects

  8. Ten local businesses to receive Venture Acceleration Fund awards

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity ofkandz-cm11 Outreach Home RoomPreservationBio-Inspired Solar FuelTechnologyTel: Name: Rm. Tel: Location: Rm. OctTenVenture

  9. TopTen Energy Efficient Products Website | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on QA:QA J-E-1 SECTION JEnvironmental Jump to:EA EISTJThin Film Solar TechnologiesCFRTopTen Energy Efficient Products

  10. Ten-Year Site Plans (TYSP) | National Nuclear Security Administration

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Homesum_a_epg0_fpd_mmcf_m.xls" ,"Available from WebQuantity of NaturalDukeWakefield Municipal Gas &SCE-SessionsSouthReport forRetirement PlanSupplemental Directives |Ten-Year Site

  11. Resource Allocation With Non-Deterministic Demands and Profits

    E-Print Network [OSTI]

    Preece, Alun

    100000$ Appeld'offrespublic 1 Demanded'approvisionnement 25000$àDemanded'approvisionnementet Appeld'offresurinvitationou 3soumissions 2 5000$àDemanded'approvisionnementet Appeld services reliés Services de professionnels 3000$àDemanded'approvisionnementet 1soumission 2 4

  12. 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

  13. Strategies for Aligning Program Demand with Contractor's Seasonal...

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

    Aligning Program Demand with Contractor's Seasonal Fluctuations Strategies for Aligning Program Demand with Contractor's Seasonal Fluctuations Better Buildings Neighborhood Program...

  14. Opportunities for Demand Response in California Agricultural Irrigation: A Scoping Study

    SciTech Connect (OSTI)

    Marks, Gary; Wilcox, Edmund; Olsen, Daniel; Goli, Sasank

    2013-01-02

    California agricultural irrigation consumes more than ten billion kilowatt hours of electricity annually and has significant potential for contributing to a reduction of stress on the grid through demand response, permanent load shifting, and energy efficiency measures. To understand this potential, a scoping study was initiated for the purpose of determining the associated opportunities, potential, and adoption challenges in California agricultural irrigation. The primary research for this study was conducted in two ways. First, data was gathered and parsed from published sources that shed light on where the best opportunities for load shifting and demand response lie within the agricultural irrigation sector. Secondly, a small limited survey was conducted as informal face-to-face interviews with several different California growers to get an idea of their ability and willingness to participate in permanent load shifting and/or demand response programs. Analysis of the data obtained from published sources and the survey reveal demand response and permanent load shifting opportunities by growing region, irrigation source, irrigation method, grower size, and utility coverage. The study examines some solutions for demand response and permanent load shifting in agricultural irrigation, which include adequate irrigation system capacity, automatic controls, variable frequency drives, and the contribution from energy efficiency measures. The study further examines the potential and challenges for grower acceptance of demand response and permanent load shifting in California agricultural irrigation. As part of the examination, the study considers to what extent permanent load shifting, which is already somewhat accepted within the agricultural sector, mitigates the need or benefit of demand response for agricultural irrigation. Recommendations for further study include studies on how to gain grower acceptance of demand response as well as other related studies such as conducting a more comprehensive survey of California growers.

  15. Linking Continuous Energy Management and Open Automated Demand Response

    E-Print Network [OSTI]

    Piette, Mary Ann

    2009-01-01

    end-uses and whole building energy performance metrics. Theperformance metrics associated with each of the domains. For example, whole-building energy

  16. THE PERFORMANCE OF QUEUING THEORETIC VIDEO ON DEMAND ALGORITHMS

    E-Print Network [OSTI]

    THE PERFORMANCE OF QUEUING THEORETIC VIDEO ON DEMAND ALGORITHMS BOURAS C.(1)(2), GAROFALAKIS J.(1,Greece KEYWORDS Video On Demand (VOD), Performance of Algorithms, Simulation, Modeling ABSTRACT Video On Demand on state-of-the-art technologies is Video On Demand (VOD). A Video On Demand System provides on demand

  17. 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

  18. Demand response in adjustment markets for electricity

    E-Print Network [OSTI]

    : electricity consumption, adjustment market, demand response, information asymmetry JEL codes: D11, D21, Q41 in the consumption of electric energy by retail customers from their expected consumption inDemand response in adjustment markets for electricity Claude Crampes and Thomas-Olivier Léautier

  19. MODELLING WOODLAND RECREATION DEMAND USING GEOGRAPHICAL

    E-Print Network [OSTI]

    Bateman, Ian J.

    MODELLING WOODLAND RECREATION DEMAND USING GEOGRAPHICAL INFORMATION SYSTEMS: A BENEFIT TRANSFER;MODELLING WOODLAND RECREATION DEMAND USING GEOGRAPHICAL INFORMATION SYSTEMS: A BENEFIT TRANSFER STUDY by Ian Research Promotion Fund. ISSN 0967-8875 #12;Abstract This paper utilizes geographical information systems

  20. Optimal Trading Strategy Supply/Demand Dynamics

    E-Print Network [OSTI]

    Gabrieli, John

    prices through the changes in their supply/demand.2 Thus, to study how market participants trade can have interesting implications on the observed behavior of intraday volume, volatility and prices: November 15, 2004. This Draft: April 8, 2006 Abstract The supply/demand of a security in the market

  1. Value of Demand Response -Introduction Klaus Skytte

    E-Print Network [OSTI]

    -of-supply and DR 15 minutes DaysHoursSeconds Adjustments of planned production Prognosis errors Excess capacity in demand to prices. Similar to Least-cost planning and demand-side management. DR differs by using prices: Curtailment of load, Direct load control, e.g. central control of electric comfort heating. Reservation prices

  2. Uranium 2009 resources, production and demand

    E-Print Network [OSTI]

    Organisation for Economic Cooperation and Development. Paris

    2010-01-01

    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...

  3. Coordination of Energy Efficiency and Demand Response

    SciTech Connect (OSTI)

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

    2010-01-29

    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.

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

    E-Print Network [OSTI]

    Langendoen, Koen

    #12;2 #12;Patterns of crude demand: Future patterns of demand for crude oil as a func- tion;5 Summary The crude oil market is actually experiencing dramatic changes on a world wide scale. Most schemes, and/or change quality of the feedstock (crude). Demand for crude oil is growing, especially

  5. The Future of Food Demand: Understanding Differences in Global Economic Models

    SciTech Connect (OSTI)

    Valin, Hugo; Sands, Ronald; van der Mensbrugghe, Dominique; Nelson, Gerald; Ahammad, Helal; Blanc, Elodie; Bodirsky, Benjamin; Fujimori, Shinichiro; Hasegawa, Tomoko; Havlik, Petr; Heyhoe, Edwina; Kyle, G. Page; Mason d'Croz, Daniel; Paltsev, S.; Rolinski, Susanne; Tabeau, Andrzej; van Meijl, Hans; von Lampe, Martin; Willenbockel, Dirk

    2014-01-01

    Understanding the capacity of agricultural systems to feed the world population under climate change requires a good prospective vision on the future development of food demand. This paper reviews modeling approaches from ten global economic models participating to the AgMIP project, in particular the demand function chosen and the set of parameters used. We compare food demand projections at the horizon 2050 for various regions and agricultural products under harmonized scenarios. Depending on models, we find for a business as usual scenario (SSP2) an increase in food demand of 59-98% by 2050, slightly higher than FAO projection (54%). The prospective for animal calories is particularly uncertain with a range of 61-144%, whereas FAO anticipates an increase by 76%. The projections reveal more sensitive to socio-economic assumptions than to climate change conditions or bioenergy development. When considering a higher population lower economic growth world (SSP3), consumption per capita drops by 9% for crops and 18% for livestock. Various assumptions on climate change in this exercise do not lead to world calorie losses greater than 6%. Divergences across models are however notable, due to differences in demand system, income elasticities specification, and response to price change in the baseline.

  6. Ten Low Mass Companions from the Keck Precision Velocity Survey

    E-Print Network [OSTI]

    Steven S. Vogt; R. Paul Butler; Geoffrey W. Marcy; Debra A. Fischer; Dimitri Pourbaix; Kevin Apps; Gregory Laughlin

    2001-10-16

    Ten new low mass companions have emerged from the Keck precision Doppler velocity survey, with minimum (msini) masses ranging from 0.8 mjup to 0.34 msun. Five of these are planet candidates with msini < 12 mjup, two are brown dwarf candidates with msini ~30 mjup, and three are low mass stellar companions. Hipparcos astrometry reveals the orbital inclinations and masses for three of the (more massive) companions, and it provides upper limits to the masses for the rest. A new class of extrasolar planet is emerging, characterized by nearly circular orbits and orbital radii greater than 1 AU. The planet HD 4208b appears to be a member of this new class. The mass distribution of extrasolar planets continues to exhibit a rapid rise from 10 mjup toward the lowest detectable masses near 1 msat.

  7. Ten Low Mass Companions from the Keck Precision Velocity Survey

    E-Print Network [OSTI]

    Vogt, S S; Marcy, G W; Fischer, D A; Pourbaix, D; Apps, K; Laughlin, G; Vogt, Steven S.; Marcy, Geoffrey W.; Fischer, Debra A.; Pourbaix, Dimitri; Apps, Kevin; Laughlin, Gregory

    2002-01-01

    Ten new low mass companions have emerged from the Keck precision Doppler velocity survey, with minimum (msini) masses ranging from 0.8 mjup to 0.34 msun. Five of these are planet candidates with msini < 12 mjup, two are brown dwarf candidates with msini ~30 mjup, and three are low mass stellar companions. Hipparcos astrometry reveals the orbital inclinations and masses for three of the (more massive) companions, and it provides upper limits to the masses for the rest. A new class of extrasolar planet is emerging, characterized by nearly circular orbits and orbital radii greater than 1 AU. The planet HD 4208b appears to be a member of this new class. The mass distribution of extrasolar planets continues to exhibit a rapid rise from 10 mjup toward the lowest detectable masses near 1 msat.

  8. Aggregated Modeling and Control of Air Conditioning Loads for Demand Response

    SciTech Connect (OSTI)

    Zhang, Wei; Lian, Jianming; Chang, Chin-Yao; Kalsi, Karanjit

    2013-06-21

    Demand response is playing an increasingly important role in the efficient and reliable operation of the electric grid. Modeling the dynamic behavior of a large population of responsive loads is especially important to evaluate the effectiveness of various demand response strategies. In this paper, a highly-accurate aggregated model is developed for a population of air conditioning loads. The model effectively includes statistical information of the population, systematically deals with load heterogeneity, and accounts for second-order dynamics necessary to accurately capture the transient dynamics in the collective response. Based on the model, a novel aggregated control strategy is designed for the load population under realistic conditions. The proposed controller is fully responsive and achieves the control objective without sacrificing end-use performance. The proposed aggregated modeling and control strategies are validated through realistic simulations using GridLAB-D. Extensive simulation results indicate that the proposed approach can effectively manage a large number of air conditioning systems to provide various demand response services, such as frequency regulation and peak load reduction.

  9. Northwest Open Automated Demand Response Technology Demonstration Project

    SciTech Connect (OSTI)

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

    2009-08-01

    Lawrence Berkeley National Laboratory (LBNL) and the Demand Response Research Center (DRRC) performed a technology demonstration and evaluation for Bonneville Power Administration (BPA) in Seattle City Light's (SCL) service territory. This report summarizes the process and results of deploying open automated demand response (OpenADR) in Seattle area with winter morning peaking commercial buildings. The field tests were designed to evaluate the feasibility of deploying fully automated demand response (DR) in four to six sites in the winter and the savings from various building systems. The project started in November of 2008 and lasted 6 months. The methodology for the study included site recruitment, control strategy development, automation system deployment and enhancements, and evaluation of sites participation in DR test events. LBNL subcontracted McKinstry and Akuacom for this project. McKinstry assisted with recruitment, site survey collection, strategy development and overall participant and control vendor management. Akuacom established a new server and enhanced its operations to allow for scheduling winter morning day-of and day-ahead events. Each site signed a Memorandum of Agreement with SCL. SCL offered each site $3,000 for agreeing to participate in the study and an additional $1,000 for each event they participated. Each facility and their control vendor worked with LBNL and McKinstry to select and implement control strategies for DR and developed their automation based on the existing Internet connectivity and building control system. Once the DR strategies were programmed, McKinstry commissioned them before actual test events. McKinstry worked with LBNL to identify control points that can be archived at each facility. For each site LBNL collected meter data and trend logs from the energy management and control system. The communication system allowed the sites to receive day-ahead as well as day-of DR test event signals. Measurement of DR was conducted using three different baseline models for estimation peak load reductions. One was three-in-ten baseline, which is based on the site electricity consumption from 7 am to 10 am for the three days with the highest consumption of the previous ten business days. The second model, the LBNL outside air temperature (OAT) regression baseline model, is based on OAT data and site electricity consumption from the previous ten days, adjusted using weather regressions from the fifteen-minute electric load data during each DR test event for each site. A third baseline that simply averages the available load data was used for sites less with less than 10 days of historical meter data. The evaluation also included surveying sites regarding any problems or issues that arose during the DR test events. Question covered occupant comfort, control issues and other potential problems.

  10. Fact #775: April 15, 2013 Top Ten Urban Areas for Fuel Wasted...

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

    5: April 15, 2013 Top Ten Urban Areas for Fuel Wasted due to Traffic Congestion, 2011 Fact 775: April 15, 2013 Top Ten Urban Areas for Fuel Wasted due to Traffic Congestion, 2011...

  11. The Top Ten Things I Learned at the Ambassador Retreat | Department...

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

    The Top Ten Things I Learned at the Ambassador Retreat The Top Ten Things I Learned at the Ambassador Retreat September 4, 2014 - 1:36pm Addthis Britt Ide President, Ide Law &...

  12. Automated Demand Response: The Missing Link in the Electricity Value Chain

    SciTech Connect (OSTI)

    McKane, Aimee; Rhyne, Ivin; Lekov, Alex; Thompson, Lisa; Piette, MaryAnn

    2009-08-01

    In 2006, the Public Interest Energy Research Program (PIER) Demand Response Research Center (DRRC) at Lawrence Berkeley National Laboratory initiated research into Automated Demand Response (OpenADR) applications in California industry. The goal is to improve electric grid reliability and lower electricity use during periods of peak demand. The purpose of this research is to begin to define the relationship among a portfolio of actions that industrial facilities can undertake relative to their electricity use. This ?electricity value chain? defines energy management and demand response (DR) at six levels of service, distinguished by the magnitude, type, and rapidity of response. One element in the electricity supply chain is OpenADR, an open-standards based communications system to send signals to customers to allow them to manage their electric demand in response to supply conditions, such as prices or reliability, through a set of standard, open communications. Initial DRRC research suggests that industrial facilities that have undertaken energy efficiency measures are probably more, not less, likely to initiate other actions within this value chain such as daily load management and demand response. Moreover, OpenADR appears to afford some facilities the opportunity to develop the supporting control structure and to"demo" potential reductions in energy use that can later be applied to either more effective load management or a permanent reduction in use via energy efficiency. Under the right conditions, some types of industrial facilities can shift or shed loads, without any, or minimal disruption to operations, to protect their energy supply reliability and to take advantage of financial incentives.1 In 2007 and 2008, 35 industrial facilities agreed to implement OpenADR, representing a total capacity of nearly 40 MW. This paper describes how integrated or centralized demand management and system-level network controls are linked to OpenADR systems. Case studies of refrigerated warehouses and wastewater treatment facilities are used to illustrate OpenADR load reduction potential. Typical shed and shift strategies include: turning off or operating compressors, aerator blowers and pumps at reduced capacity, increasing temperature set-points or pre-cooling cold storage areas and over-oxygenating stored wastewater prior to a DR event. This study concludes that understanding industrial end-use processes and control capabilities is a key to support reduced service during DR events and these capabilities, if DR enabled, hold significant promise in reducing the electricity demand of the industrial sector during utility peak periods.

  13. Automated Demand Response: The Missing Link in the Electricity Value Chain

    SciTech Connect (OSTI)

    McKane, Aimee; Rhyne, Ivin; Piette, Mary Ann; Thompson, Lisa; Lekov, Alex

    2008-08-01

    In 2006, the Public Interest Energy Research Program (PIER) Demand Response Research Center (DRRC) at Lawrence Berkeley National Laboratory initiated research into Automated Demand Response (OpenADR) applications in California industry. The goal is to improve electric grid reliability and lower electricity use during periods of peak demand. The purpose of this research is to begin to define the relationship among a portfolio of actions that industrial facilities can undertake relative to their electricity use. This 'electricity value chain' defines energy management and demand response (DR) at six levels of service, distinguished by the magnitude, type, and rapidity of response. One element in the electricity supply chain is OpenADR, an open-standards based communications system to send signals to customers to allow them to manage their electric demand in response to supply conditions, such as prices or reliability, through a set of standard, open communications. Initial DRRC research suggests that industrial facilities that have undertaken energy efficiency measures are probably more, not less, likely to initiate other actions within this value chain such as daily load management and demand response. Moreover, OpenADR appears to afford some facilities the opportunity to develop the supporting control structure and to 'demo' potential reductions in energy use that can later be applied to either more effective load management or a permanent reduction in use via energy efficiency. Under the right conditions, some types of industrial facilities can shift or shed loads, without any, or minimal disruption to operations, to protect their energy supply reliability and to take advantage of financial incentives. In 2007 and 2008, 35 industrial facilities agreed to implement OpenADR, representing a total capacity of nearly 40 MW. This paper describes how integrated or centralized demand management and system-level network controls are linked to OpenADR systems. Case studies of refrigerated warehouses and wastewater treatment facilities are used to illustrate OpenADR load reduction potential. Typical shed and shift strategies include: turning off or operating compressors, aerator blowers and pumps at reduced capacity, increasing temperature set-points or pre-cooling cold storage areas and over-oxygenating stored wastewater prior to a DR event. This study concludes that understanding industrial end-use processes and control capabilities is a key to support reduced service during DR events and these capabilities, if DR enabled, hold significant promise in reducing the electricity demand of the industrial sector during utility peak periods.

  14. Autonomous Demand Response for Primary Frequency Regulation

    SciTech Connect (OSTI)

    Donnelly, Matt; Trudnowski, Daniel J.; Mattix, S.; Dagle, Jeffery E.

    2012-02-28

    The research documented within this report examines the use of autonomous demand response to provide primary frequency response in an interconnected power grid. The work builds on previous studies in several key areas: it uses a large realistic model (i.e., the interconnection of the western United States and Canada); it establishes a set of metrics that can be used to assess the effectiveness of autonomous demand response; and it independently adjusts various parameters associated with using autonomous demand response to assess effectiveness and to examine possible threats or vulnerabilities associated with the technology.

  15. FERC sees huge potential for demand response

    SciTech Connect (OSTI)

    2010-04-15

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

  16. The Economics of Energy (and Electricity) Demand

    E-Print Network [OSTI]

    Platchkov, Laura M.; Pollitt, Michael G.

    25 3.3.2 Electrification of personal transport New sources of electricity demand may emerge which substantially change the total demand for electricity and the way electricity is consumed by the household. The Tesla Roadster12 stores 53 k... substantial battery storage capacity to the electricity grid, both when stationary at home and when at work. They may thus be very useful in providing short term back-up at system demand peaks or for dumping electricity to the batteries when supply is at a...

  17. Coal supply/demand, 1980 to 2000. Task 3. Resource applications industrialization system data base. Final review draft. [USA; forecasting 1980 to 2000; sector and regional analysis

    SciTech Connect (OSTI)

    Fournier, W.M.; Hasson, V.

    1980-10-10

    This report is a compilation of data and forecasts resulting from an analysis of the coal market and the factors influencing supply and demand. The analyses performed for the forecasts were made on an end-use-sector basis. The sectors analyzed are electric utility, industry demand for steam coal, industry demand for metallurgical coal, residential/commercial, coal demand for synfuel production, and exports. The purpose is to provide coal production and consumption forecasts that can be used to perform detailed, railroad company-specific coal transportation analyses. To make the data applicable for the subsequent transportation analyses, the forecasts have been made for each end-use sector on a regional basis. The supply regions are: Appalachia, East Interior, West Interior and Gulf, Northern Great Plains, and Mountain. The demand regions are the same as the nine Census Bureau regions. Coal production and consumption in the United States are projected to increase dramatically in the next 20 years due to increasing requirements for energy and the unavailability of other sources of energy to supply a substantial portion of this increase. Coal comprises 85 percent of the US recoverable fossil energy reserves and could be mined to supply the increasing energy demands of the US. The NTPSC study found that the additional traffic demands by 1985 may be met by the railways by the way of improved signalization, shorter block sections, centralized traffic control, and other modernization methods without providing for heavy line capacity works. But by 2000 the incremental traffic on some of the major corridors was projected to increase very significantly and is likely to call for special line capacity works involving heavy investment.

  18. Direct versus Facility Centric Load Control for Automated Demand Response

    SciTech Connect (OSTI)

    Koch, Ed; Piette, Mary Ann

    2009-11-06

    Direct load control (DLC) refers to the scenario where third party entities outside the home or facility are responsible for deciding how and when specific customer loads will be controlled in response to Demand Response (DR) events on the electric grid. Examples of third parties responsible for performing DLC may be Utilities, Independent System Operators (ISO), Aggregators, or third party control companies. DLC can be contrasted with facility centric load control (FCLC) where the decisions for how loads are controlled are made entirely within the facility or enterprise control systems. In FCLC the facility owner has more freedom of choice in how to respond to DR events on the grid. Both approaches are in use today in automation of DR and both will continue to be used in future market segments including industrial, commercial and residential facilities. This paper will present a framework which can be used to differentiate between DLC and FCLC based upon where decisions are made on how specific loads are controlled in response to DR events. This differentiation is then used to compare and contrast the differences between DLC and FCLC to identify the impact each has on:(1)Utility/ISO and third party systems for managing demand response, (2)Facility systems for implementing load control, (3)Communications networks for interacting with the facility and (4)Facility operators and managers. Finally a survey of some of the existing DR related specifications and communications standards is given and their applicability to DLC or FCLC. In general FCLC adds more cost and responsibilities to the facilities whereas DLC represents higher costs and complexity for the Utility/ISO. This difference is primarily due to where the DR Logic is implemented and the consequences that creates. DLC may be more certain than FCLC because it is more predictable - however as more loads have the capability to respond to DR signals, people may prefer to have their own control of end-use loads and FCLC systems. Research is needed to understand the predictability of FCLC which is related to the perceived value of the DR from the facility manager or home owner's perspective.

  19. Global Energy: Supply, Demand, Consequences, Opportunities

    ScienceCinema (OSTI)

    Majumdar, Arun

    2010-01-08

    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.

  20. Demand Controlled Ventilation and Classroom Ventilation

    E-Print Network [OSTI]

    Fisk, William J.

    2014-01-01

    columns indicate the energy and cost savings for  demand class size.   (The energy costs  of classroom ventilation $6.2 M in increased energy costs.   Further VR  increases 

  1. Essays on exchange rates and electricity demand

    E-Print Network [OSTI]

    Li, Xiangming, 1966-

    1999-01-01

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

  2. Demand Response and Energy Storage Integration Study

    Broader source: Energy.gov [DOE]

    This study is a multi-national laboratory effort to assess the potential value of demand response and energy storage to electricity systems with different penetration levels of variable renewable...

  3. Capitalize on Existing Assets with Demand Response 

    E-Print Network [OSTI]

    Collins, J.

    2008-01-01

    Industrial facilities universally struggle with escalating energy costs. EnerNOC will demonstrate how commercial, industrial, and institutional end-users can capitalize on their existing assets—at no cost and no risk. Demand response, the voluntary...

  4. Integration of Demand Side Management, Distributed Generation...

    Open Energy Info (EERE)

    United 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...

  5. CALIFORNIA ENERGY DEMAND 2014-2024 PRELIMINARY

    E-Print Network [OSTI]

    supervised data preparation. Steven Mac and Keith O'Brien prepared the historical energy consumption data. Nahid Movassagh forecasted consumption for the agriculture and water pumping CALIFORNIA ENERGY DEMAND 2014-2024 PRELIMINARY FORECAST Volume 1

  6. Hawaiian Electric Company Demand Response Roadmap Project

    E-Print Network [OSTI]

    Levy, Roger

    2014-01-01

    and technology options should have general application across systems. However, MECO has unprecedented levels of wind energywind, solar, and clean energy initiatives have introduced many changes and created uncertainties that complicate utility demand response technology

  7. Retail Demand Response in Southwest Power Pool

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2009-01-01

    and Retails Electricity Markets in SPP The Southwest Powerand Retails Electricity Markets in SPP.3 2.1 Wholesale Markets in the Southwest PowerRetail Demand Response in SPP Wholesale Markets in the Southwest Power

  8. China's Coal: Demand, Constraints, and Externalities

    E-Print Network [OSTI]

    Aden, Nathaniel

    2010-01-01

    unit water requirement of coal-fired electricity generationin electricity demand. Coal-fired power generation accounted12, the absolute amount of coal-fired capacity grew at an

  9. Global Climate Change and Demand for Energy

    E-Print Network [OSTI]

    Subramanian, Venkat

    1 Global Climate Change and Demand for Energy Tyson Research Center and International Center et al. Climate Variability and Climate Change: The New Climate Dice http://data, 2012 Tyson Research Center International Center for Advanced Research and Sustainability (I

  10. Micro economics for demand-side management

    E-Print Network [OSTI]

    Kibune, Hisao

    1991-01-01

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

  11. Volatile coal prices reflect supply, demand uncertainties

    SciTech Connect (OSTI)

    Ryan, M.

    2004-12-15

    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.

  12. Climate policy implications for agricultural water demand

    SciTech Connect (OSTI)

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

    2013-03-28

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

  13. Measuring the capacity impacts of demand response

    SciTech Connect (OSTI)

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

    2009-07-15

    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)

  14. Demand Response and Electric Grid Reliability 

    E-Print Network [OSTI]

    Wattles, P.

    2012-01-01

    and Regional Transmission Organizations are the ?air traffic controllers? of the bulk electric power grids 4 Power supply (generation) must match load (demand) CATEE Conference October 10, 2012 ? The fundamental concept behind ERCOT operations... changes or incentives.? (FERC) ? ?Changes in electric use by demand-side resources from their normal consumption patterns in response to changes in the price of electricity, or to incentive payments designed to induce lower electricity use at times...

  15. Ethanol Demand in United States Gasoline Production

    SciTech Connect (OSTI)

    Hadder, G.R.

    1998-11-24

    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.

  16. An Operational Model for Optimal NonDispatchable Demand Response

    E-Print Network [OSTI]

    Grossmann, Ignacio E.

    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

  17. A critical comparison of ten disposable cup LCAs

    SciTech Connect (OSTI)

    Harst, Eugenie van der, E-mail: eugenie.vanderharst@wur.nl [Environmental Systems Analysis Group, Wageningen University, P.O. Box 47, NL-6700 AA Wageningen (Netherlands); Potting, José, E-mail: jose.potting@wur.nl [Environmental Systems Analysis Group, Wageningen University, P.O. Box 47, NL-6700 AA Wageningen (Netherlands) [Environmental Systems Analysis Group, Wageningen University, P.O. Box 47, NL-6700 AA Wageningen (Netherlands); Environmental Strategies Research (fms), KTH Royal Institute of Technology, SE-110 44 Stockholm (Sweden)

    2013-11-15

    Disposable cups can be made from conventional petro-plastics, bioplastics, or paperboard (coated with petro-plastics or bioplastics). This study compared ten life cycle assessment (LCA) studies of disposable cups with the aim to evaluate the robustness of their results. The selected studies have only one impact category in common, namely climate change with global warming potential (GWP) as its category indicator. Quantitative GWP results of the studies were closer examined. GWPs within and across each study show none of the cup materials to be consistently better than the others. Comparison of the absolute GWPs (after correction for the cup volume) also shows no consistent better or worse cup material. An evaluation of the methodological choices and the data sets used in the studies revealed their influence on the GWP. The differences in GWP can be attributed to a multitude of factors, i.e., cup material and weight, production processes, waste processes, allocation options, and data used. These factors basically represent different types of uncertainty. Sensitivity and scenario analyses provided only the influence of one factor at once. A systematic and simultaneous use of sensitivity and scenario analyses could, in a next research, result in more robust outcomes. -- Highlights: • Conflicting results from life cycle assessment (LCA) on disposable cups • GWP results of LCAs did not point to a best or worst cup material. • Differences in GWP results are due to methodological choices and data sets used. • Standardized LCA: transparency of LCA studies, but still different in approaches.

  18. Development and evaluation of fully automated demand response in large facilities

    SciTech Connect (OSTI)

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

    2004-03-30

    This report describes the results of a research project 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 electric grid reliability, manage electricity costs, and ensure that customers receive signals that encourage load reduction during times when the electric grid is near its capacity. The two main drivers for widespread demand responsiveness are the prevention of future electricity crises and the reduction of electricity prices. Additional goals for price responsiveness include equity through cost of service pricing, and customer control of electricity usage and bills. The technology developed and evaluated in this report could be used to support numerous forms of DR programs and tariffs. For the purpose of this report, we have defined three levels of Demand Response automation. Manual Demand Response involves manually turning off lights or equipment; this can be a labor-intensive approach. Semi-Automated Response involves the use of building energy management control systems for load shedding, where a preprogrammed load shedding strategy is initiated by facilities staff. Fully-Automated Demand Response is initiated at a building or facility through receipt of an external communications signal--facility staff set up a pre-programmed load shedding strategy which is automatically initiated by the system without the need for human intervention. We have defined this approach to be Auto-DR. An important concept in Auto-DR is that a facility manager is able to ''opt out'' or ''override'' an individual DR event if it occurs at a time when the reduction in end-use services is not desirable. This project sought to improve the feasibility and nature of Auto-DR strategies in large facilities. The research focused on technology development, testing, characterization, and evaluation relating to Auto-DR. This evaluation also included the related decisionmaking perspectives of the facility owners and managers. Another goal of this project was to develop and test a real-time signal for automated demand response that provided a common communication infrastructure for diverse facilities. The six facilities recruited for this project were selected from the facilities that received CEC funds for new DR technology during California's 2000-2001 electricity crises (AB970 and SB-5X).

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

    E-Print Network [OSTI]

    . WHAT IS DEMAND RESPONSE? Demand response is a change in customers' demand for electricity corresponding. Demand response as defined here does not include involuntary curtailment imposed on electricity users to conditions in wholesale power markets, its electricity demand is not. This situation has a number of adverse

  20. Washington: Sustainability Training for Realtors in High Demand...

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

    Sustainability Training for Realtors in High Demand Washington: Sustainability Training for Realtors in High Demand March 6, 2014 - 5:50pm Addthis Demand has been high for a free...

  1. Forecasting Market Demand for New Telecommunications Services: An Introduction

    E-Print Network [OSTI]

    Parsons, Simon

    Forecasting Market Demand for New Telecommunications Services: An Introduction Peter Mc in demand forecasting for new communication services. Acknowledgments: The writing of this paper commenced employers or consultancy clients. KEYWORDS: Demand Forecasting, New Product Marketing, Telecommunica- tions

  2. A Methodology for Estimating Interdomain Web Traffic Demand

    E-Print Network [OSTI]

    Maggs, Bruce M.

    A Methodology for Estimating Interdomain Web Traffic Demand Anja Feldmann , Nils Kammenhuber-varying) interdomain HTTP traffic demand matrix pairing several hundred thousand blocks of client IP addresses, Traffic demand, Interdomain, Es- timation 1. INTRODUCTION The reliable estimation and prediction

  3. Demand-Side Management and Energy Efficiency Revisited

    E-Print Network [OSTI]

    Auffhammer, Maximilian; Blumstein, Carl; Fowlie, Meredith

    2007-01-01

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

  4. Coordination of Retail Demand Response with Midwest ISO Markets

    E-Print Network [OSTI]

    Bharvirkar, Ranjit

    2008-01-01

    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.

  5. Demand Response Enabling Technologies and Approaches for Industrial Facilities 

    E-Print Network [OSTI]

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

    2005-01-01

    , 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...

  6. Demand Control Utilizing Energy Management Systems - Report of Field Tests 

    E-Print Network [OSTI]

    Russell, B. D.; Heller, R. P.; Perry, L. W.

    1984-01-01

    Energy Management systems and particularly demand controllers are becoming more popular as commercial and light industrial operations attempt to reduce their electrical usage and demand. Numerous techniques are used to control energy use and demand...

  7. Automated Demand Response Strategies and Commissioning Commercial Building Controls

    E-Print Network [OSTI]

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

    2006-01-01

    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"

  8. Learning Energy Demand Domain Knowledge via Feature Transformation

    E-Print Network [OSTI]

    Povinelli, Richard J.

    -- Domain knowledge is an essential factor for forecasting energy demand. This paper introduces a method knowledge substantially improves energy demand forecasting accuracy. However, domain knowledge may differ. The first stage automatically captures energy demand forecasting domain knowledge through nonlinear

  9. Behavioral Aspects in Simulating the Future US Building Energy Demand

    E-Print Network [OSTI]

    Stadler, Michael

    2011-01-01

    Floor-space forecast to 2050 Gross demand for energy Macro-Floor-space forecast to 2050 Gross demand for energy Macro-Floor-space forecast to 2050 Gross demand for energy Macro-

  10. 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

  11. 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

  12. Agreement Template for Energy Conservation and Demand Side Management...

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

    Agreement Template for Energy Conservation and Demand Side Management Services Agreement Template for Energy Conservation and Demand Side Management Services Template agreement...

  13. Structuring Rebate and Incentive Programs for Sustainable Demand...

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

    Structuring Rebate and Incentive Programs for Sustainable Demand Structuring Rebate and Incentive Programs for Sustainable Demand Better Buildings Neighborhood Program Peer...

  14. Using Mobile Applications to Generate Customer Demand | Department...

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

    Using Mobile Applications to Generate Customer Demand Using Mobile Applications to Generate Customer Demand Better Buildings Residential Network Peer Exchange Call Series: Using...

  15. Reducing Energy Demand in Buildings Through State Energy Codes...

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

    Reducing Energy Demand in Buildings Through State Energy Codes Reducing Energy Demand in Buildings Through State Energy Codes Building Codes Project for the 2013 Building...

  16. Estimating Costs and Efficiency of Storage, Demand, and Heat...

    Energy Savers [EERE]

    Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters A water heater's energy...

  17. Response to several FOIA requests - Renewable Energy. Demand...

    Energy Savers [EERE]

    Response to several FOIA requests - Renewable Energy. Demand for Fossil Fuels Response to several FOIA requests - Renewable Energy. Demand for Fossil Fuels Response to several FOIA...

  18. Using Wind and Solar to Reliably Meet Electricity Demand, Greening...

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

    and wind generation technologies. A variety of approaches can be deployed, including demand response, which can be used to shift demand to periods of greater renewable output,...

  19. Strategies for Marketing and Driving Demand for Commercial Financing...

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

    Strategies for Marketing and Driving Demand for Commercial Financing Products Strategies for Marketing and Driving Demand for Commercial Financing Products Better Buildings...

  20. Agreement for Energy Conservation and Demand Side Management...

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

    Agreement for Energy Conservation and Demand Side Management Services Template Agreement for Energy Conservation and Demand Side Management Services Template Document features a...

  1. Tool Improves Electricity Demand Predictions to Make More Room...

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

    Tool Improves Electricity Demand Predictions to Make More Room for Renewables Tool Improves Electricity Demand Predictions to Make More Room for Renewables October 3, 2011 -...

  2. FERC Presendation: Demand Response as Power System Resources...

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

    Federal Energy Regulatory Commission (FERC) presentation on demand response as power system resources before the Electicity Advisory Committee, October 29, 2010 Demand Response as...

  3. Implementation Proposal for the National Action Plan on Demand...

    Energy Savers [EERE]

    Implementation Proposal for the National Action Plan on Demand Response - July 2011 Implementation Proposal for the National Action Plan on Demand Response - July 2011 Report to...

  4. SGDP Report Now Available: Interoperability of Demand Response...

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

    SGDP Report Now Available: Interoperability of Demand Response Resources Demonstration in NY (February 2015) SGDP Report Now Available: Interoperability of Demand Response...

  5. Estimating Costs and Efficiency of Storage, Demand, and Heat...

    Office of Environmental Management (EM)

    Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters A water heater's...

  6. Can Automotive Battery Recycling Help Meet Lithium Demand? |...

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

    Can Automotive Battery Recycling Help Meet Lithium Demand? Title Can Automotive Battery Recycling Help Meet Lithium Demand? Publication Type Presentation Year of Publication 2013...

  7. Automated Demand Response Strategies and Commissioning Commercial Building Controls

    E-Print Network [OSTI]

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

    2006-01-01

    efficiency, daily peak load management and demand response.Loads Efficiency, Daily Load Management and Demand ResponseOperations Peak Load Management (Daily) - TOU Savings - Peak

  8. Robust Unit Commitment Problem with Demand Response and ...

    E-Print Network [OSTI]

    2010-10-31

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

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

    Office of Environmental Management (EM)

    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...

  10. China-Transportation Demand Management in Beijing: Mitigation...

    Open Energy Info (EERE)

    China-Transportation Demand Management in Beijing: Mitigation of Emissions in Urban Transport Jump to: navigation, search Name Transportation Demand Management in Beijing -...

  11. Estimating Costs and Efficiency of Storage, Demand, and Heat...

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

    Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters Estimating Costs and Efficiency of Storage, Demand, and Heat Pump Water Heaters March 10, 2015 -...

  12. Demand Response and Energy Storage Integration Study - Past Workshops...

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

    Demand Response and Energy Storage Integration Study - Past Workshops Demand Response and Energy Storage Integration Study - Past Workshops The project was initiated and informed...

  13. SGDP Report: Interoperability of Demand Response Resources Demonstrati...

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

    Report: Interoperability of Demand Response Resources Demonstration in NY (February 2015) SGDP Report: Interoperability of Demand Response Resources Demonstration in NY (February...

  14. ASSESSMENT OF VARIABLE EFFECTS OF SYSTEMS WITH DEMAND RESPONSE RESOURCES

    E-Print Network [OSTI]

    Gross, George

    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

  15. SGDP Report Now Available: Interoperability of Demand Response...

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

    Report Now Available: Interoperability of Demand Response Resources Demonstration in NY (February 2015) SGDP Report Now Available: Interoperability of Demand Response Resources...

  16. International Oil Supplies and Demands. Volume 1

    SciTech Connect (OSTI)

    Not Available

    1991-09-01

    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.

  17. International Oil Supplies and Demands. Volume 2

    SciTech Connect (OSTI)

    Not Available

    1992-04-01

    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.

  18. Wireless Demand Response Controls for HVAC Systems

    SciTech Connect (OSTI)

    Federspiel, Clifford

    2009-06-30

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

  19. China's Coal: Demand, Constraints, and Externalities

    SciTech Connect (OSTI)

    Aden, Nathaniel; Fridley, David; Zheng, Nina

    2009-07-01

    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.

  20. Centralized and Decentralized Control for Demand Response

    SciTech Connect (OSTI)

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

    2011-04-29

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