National Library of Energy BETA

Sample records for forecasts energy consumption

  1. Energy consumption and expenditure projections by population group on the basis of the annual energy outlook 1999 forecast

    SciTech Connect

    Poyer, D.A.; Balsley, J.H.

    2000-01-07

    This report presents an analysis of the relative impact of the base-case scenario used in Annual Energy Outlook 1999 on different population groups. Projections of energy consumption and expenditures, as well as energy expenditure as a share of income, from 1996 to 2020 are given. The projected consumption of electricty, natural gas, distillate fuel, and liquefied petroleum gas during this period is also reported for each population group. In addition, this report compares the findings of the Annual Energy Outlook 1999 report with the 1998 report. Changes in certain indicators and information affect energy use forecasts, and these effects are analyzed and discussed.

  2. probabilistic energy production forecasts

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    energy production forecasts - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary ...

  3. Transportation sector energy consumption

    Annual Energy Outlook

    Chapter 8 Transportation sector energy consumption Overview In the International Energy Outlook 2016 (IEO2016) Reference case, transportation sector delivered energy consumption ...

  4. Solar Energy Market Forecast | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Market Forecast Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Solar Energy Market Forecast AgencyCompany Organization: United States Department of Energy Sector:...

  5. Acquisition Forecast | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Acquisition Forecast Acquisition Forecast Acquisition Forecast It is the policy of the U.S. Department of Energy (DOE) to provide timely information to the public regarding DOE's forecast of future prime contracting opportunities and subcontracting opportunities which are available via the Department's major site and facilities management contractors. This forecast has been expanded to also provide timely status information for ongoing prime contracting actions that are valued in excess of the

  6. Manufacturing Consumption of Energy 1991--Combined Consumption...

    Energy Information Administration (EIA) (indexed site)

    call 202-586-8800 for help. Return to Energy Information Administration Home Page. Home > Energy Users > Manufacturing > Consumption and Fuel Switching Manufacturing Consumption of...

  7. National Lighting Energy Consumption

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Lighting Energy National Lighting Energy Consumption Consumption 390 Billion kWh used for lighting in all 390 Billion kWh used for lighting in all commercial buildings in commercial buildings in 2001 2001 LED (<.1% ) Incandescent 40% HID 22% Fluorescent 38% Lighting Energy Consumption by Lighting Energy Consumption by Breakdown of Lighting Energy Breakdown of Lighting Energy Major Sector and Light Source Type Major Sector and Light Source Type Source: Navigant Consulting, Inc., U.S. Lighting

  8. Office Buildings - Energy Consumption

    Energy Information Administration (EIA) (indexed site)

    Energy Consumption Office buildings consumed more than 17 percent of the total energy used by the commercial buildings sector (Table 4). At least half of total energy, electricity,...

  9. Manufacturing Consumption of Energy 1994

    Energy Information Administration (EIA) (indexed site)

    (MECS) > MECS 1994 Combined Consumption and Fuel Switching Manufacturing Energy Consumption Survey 1994 (Combined Consumption and Fuel Switching) Manufacturing Energy Consumption...

  10. DOE Releases Latest Report on Energy Savings Forecast of Solid...

    Energy.gov [DOE] (indexed site)

    The sixth iteration of the Energy Savings Forecast of Solid-State Lighting in General Illumination Applications compares the annual lighting energy consumption in the U.S. with and ...

  11. Industrial sector energy consumption

    Annual Energy Outlook

    Chapter 7 Industrial sector energy consumption Overview The industrial sector uses more delivered energy 294 than any other end-use sector, consuming about 54% of the world's total ...

  12. Forecast Energy | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    Zip: 94965 Region: Bay Area Sector: Services Product: Intelligent Monitoring and Forecasting Services Year Founded: 2010 Website: www.forecastenergy.net Coordinates:...

  13. Commercial Buildings Energy Consumption and Expenditures 1992...

    Energy Information Administration (EIA) (indexed site)

    Consumption and Expenditures Electricity Consumption Natural Gas Consumption Wood and Solar Energy Consumption Fuel Oil and District Heat Consumption Energy Consumption in...

  14. Energy Information Administration - Transportation Energy Consumption...

    Energy Information Administration (EIA) (indexed site)

    Energy Consumption Transportation Energy Consumption Surveys energy used by vehicles EIA conducts numerous energy-related surveys and other information programs. In general, the...

  15. " Column: Energy-Consumption Ratios;"

    Energy Information Administration (EIA) (indexed site)

    3 Consumption Ratios of Fuel, 2010;" " Level: National Data; " " Row: Values of Shipments within NAICS Codes;" " Column: Energy-Consumption Ratios;" " Unit: Varies." ...

  16. Manufacturing Consumption of Energy 1994

    Energy Information Administration (EIA) (indexed site)

    Detailed Tables 28 Energy Information AdministrationManufacturing Consumption of Energy 1994 1. In previous MECS, the term "primary energy" was used to denote the "first use" of...

  17. Energy Information Administration - Commercial Energy Consumption...

    Annual Energy Outlook

    5A. Fuel Oil Consumption and Conditional Energy Intensity by Census Region for All Buildings, 2003 Total Fuel Oil Consumption (million gallons) Total Floorspace of Buildings Using...

  18. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update

    A. Consumption and Gross Energy Intensity by Year Constructed for Sum of Major Fuels for All Buildings, 2003 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace of...

  19. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update

    2A. Natural Gas Consumption and Conditional Energy Intensity by Year Constructed for All Buildings, 2003 Total Natural Gas Consumption (billion cubic feet) Total Floorspace of...

  20. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update

    5A. Natural Gas Consumption and Conditional Energy Intensity by Census Region for All Buildings, 2003 Total Natural Gas Consumption (billion cubic feet) Total Floorspace of...

  1. Energy Information Administration - Commercial Energy Consumption...

    Annual Energy Outlook

    0A. Electricity Consumption and Conditional Energy Intensity by Climate Zonea for All Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings...

  2. Energy Information Administration - Commercial Energy Consumption...

    Annual Energy Outlook

    0A. Natural Gas Consumption and Conditional Energy Intensity by Climate Zonea for All Buildings, 2003 Total Natural Gas Consumption (billion cubic feet) Total Floorspace of...

  3. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update

    8A. Natural Gas Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 2 Total Natural Gas Consumption (billion cubic feet) Total Floorspace...

  4. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update

    A. Consumption and Gross Energy Intensity by Climate Zonea for All Buildings, 2003 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace of Buildings (million square feet)...

  5. Energy Information Administration - Commercial Energy Consumption...

    Annual Energy Outlook

    9A. Natural Gas Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 3 Total Natural Gas Consumption (billion cubic feet) Total Floorspace...

  6. Energy Information Administration - Commercial Energy Consumption...

    Annual Energy Outlook

    9A. Electricity Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 3 Total Electricity Consumption (billion kWh) Total Floorspace of...

  7. Energy Information Administration - Commercial Energy Consumption...

    Annual Energy Outlook

    2A. Electricity Consumption and Conditional Energy Intensity by Year Constructed for All Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings...

  8. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update

    8A. Electricity Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 2 Total Electricity Consumption (billion kWh) Total Floorspace of...

  9. Energy Information Administration - Commercial Energy Consumption...

    Annual Energy Outlook

    5A. Electricity Consumption and Conditional Energy Intensity by Census Region for All Buildings, 2003 Total Electricity Consumption (billion kWh) Total Floorspace of Buildings...

  10. Household Vehicles Energy Consumption 1991

    Energy Information Administration (EIA) (indexed site)

    or commercial trucks (See Table 1). Energy Information AdministrationHousehold Vehicles Energy Consumption 1991 5 The 1991 RTECS count includes vehicles that were owned or used...

  11. Manufacturing Consumption of Energy 1994

    Energy Information Administration (EIA) (indexed site)

    Natural Gas to Residual Fuel Oil, by Industry Group and Selected Industries, 1994 369 Energy Information AdministrationManufacturing Consumption of Energy 1994 SIC Residual...

  12. energy data + forecasting | OpenEI Community

    OpenEI (Open Energy Information) [EERE & EIA]

    energy data + forecasting Home FRED Description: Free Energy Database Tool on OpenEI This is an open source platform for assisting energy decision makers and policy makers in...

  13. Energy Preview: Residential Transportation Energy Consumption...

    Annual Energy Outlook

    t 7 Energy Preview: Residential Transportation Energy Consumption Survey, Preliminary Estimates, 1991 (See Page 1) This publication and other Energy Information Administration...

  14. Residential Energy Consumption Survey:

    Annual Energy Outlook

    ... ...*...,,.<,<,...,,.,,.,,. 97 Table 6. Residential Fuel Oil and Kerosene Consumption and Expenditures April 1979 Through March 1980 Northeast...

  15. 2014 Manufacturing Energy Consumption Survey

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    U S C E N S U S B U R E A U 2014 Manufacturing Energy Consumption Survey Sponsored by the Energy Information Administration U.S. Department of Energy Administered and Compiled by ...

  16. Manufacturing Consumption of Energy 1994

    Energy Information Administration (EIA) (indexed site)

    2(94) Distribution Category UC-950 Manufacturing Consumption of Energy 1994 December 1997 Energy Information Administration Office of Energy Markets and End Use U.S. Department of...

  17. Manufacturing consumption of energy 1991

    SciTech Connect

    Not Available

    1994-12-01

    This report provides estimates on energy consumption in the manufacturing sector of the US economy. These estimates are based on data from the 1991 Manufacturing Energy Consumption Survey (MECS). This survey--administered by the Energy End Use and Integrated Statistics Division, Office of Energy Markets and End Use, Energy Information Administration (EIA)--is the most comprehensive source of national-level data on energy-related information for the manufacturing industries.

  18. Short-Term Energy Outlook Model Documentation: Motor Gasoline Consumption Model

    Reports and Publications

    2011-01-01

    The motor gasoline consumption module of the Short-Term Energy Outlook (STEO) model is designed to provide forecasts of total U.S. consumption of motor gasolien based on estimates of vehicle miles traveled and average vehicle fuel economy.

  19. Household Vehicles Energy Consumption 1991

    Energy Information Administration (EIA) (indexed site)

    of vehicles in the residential sector. Data are from the 1991 Residential Transportation Energy Consumption Survey. The "Glossary" contains the definitions of terms used in the...

  20. Household Vehicles Energy Consumption 1991

    Energy Information Administration (EIA) (indexed site)

    logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Consumption 1991 December 1993 Release Next Update: August 1997. Based on the 1991...

  1. DOE/EIA-0321/HRIf Residential Energy Consumption Survey. Consumption

    Annual Energy Outlook

    purchase diaries from a subset of respondents composing a Household Transportation Panel and is reported separately. Residential Energy Consumption Survey: Consumption and...

  2. Household Vehicles Energy Consumption 1991

    Energy Information Administration (EIA) (indexed site)

    16.8 17.4 18.6 18.9 1.7 2.2 0.6 1.5 Energy Information AdministrationHousehold Vehicles Energy Consumption 1991 15 Vehicle Miles Traveled per Vehicle (Thousand) . . . . . . . . ....

  3. Energy Information Administration - Commercial Energy Consumption...

    Annual Energy Outlook

    A. Consumption and Gross Energy Intensity by Census Region for Sum of Major Fuels for All Buildings, 2003 Sum of Major Fuel Consumption (trillion Btu) Total Floorspace of Buildings...

  4. Energy Intensity Indicators: Commercial Source Energy Consumption

    Energy.gov [DOE]

    Figure C1 below reports as index numbers over the period 1970 through 2011: 1) commercial building floor space, 2) energy use based on source energy consumption, 3) energy intensity, and 4) the...

  5. Transportation Energy Consumption Surveys

    Energy Information Administration (EIA) (indexed site)

    Electricity Hydropower Biofuels: Ethanol & Biodiesel Wind Geothermal Solar Energy in Brief How much U.S. electricity is generated from renewable energy?...

  6. Household Vehicles Energy Consumption 1991

    Energy Information Administration (EIA) (indexed site)

    for 1994, will continue the 3-year cycle. The RTECS, a subsample of the Residential Energy Consumption Survey (RECS), is an integral part of a series of surveys designed by...

  7. Forecast of transportation energy demand through the year 2010

    SciTech Connect

    Mintz, M.M.; Vyas, A.D.

    1991-04-01

    Since 1979, the Center for Transportation Research (CTR) at Argonne National Laboratory (ANL) has produced baseline projections of US transportation activity and energy demand. These projections and the methodologies used to compute them are documented in a series of reports and research papers. As the lastest in this series of projections, this report documents the assumptions, methodologies, and results of the most recent projection -- termed ANL-90N -- and compares those results with other forecasts from the current literature, as well as with the selection of earlier Argonne forecasts. This current forecast may be used as a baseline against which to analyze trends and evaluate existing and proposed energy conservation programs and as an illustration of how the Transportation Energy and Emission Modeling System (TEEMS) works. (TEEMS links disaggregate models to produce an aggregate forecast of transportation activity, energy use, and emissions). This report and the projections it contains were developed for the US Department of Energy's Office of Transportation Technologies (OTT). The projections are not completely comprehensive. Time and modeling effort have been focused on the major energy consumers -- automobiles, trucks, commercial aircraft, rail and waterborne freight carriers, and pipelines. Because buses, rail passengers services, and general aviation consume relatively little energy, they are projected in the aggregate, as other'' modes, and used primarily as scaling factors. These projections are also limited to direct energy consumption. Projections of indirect energy consumption, such as energy consumed in vehicle and equipment manufacturing, infrastructure, fuel refining, etc., were judged outside the scope of this effort. The document is organized into two complementary sections -- one discussing passenger transportation modes, and the other discussing freight transportation modes. 99 refs., 10 figs., 43 tabs.

  8. 2009 Energy Consumption Per Person | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    2009 Energy Consumption Per Person 2009 Energy Consumption Per Person 2009 Energy Consumption Per Person Per capita energy consumption across all sectors of the economy. Click on a state for more information.

  9. 1999 Commercial Buildings Energy Consumption Survey Detailed...

    Energy Information Administration (EIA) (indexed site)

    Consumption and Expenditures Tables Table C1. Total Energy Consumption by Major Fuel ...... 124 Table C2. Total Energy Expenditures by ...

  10. Building Energy Consumption Analysis

    Energy Science and Technology Software Center

    2005-03-02

    DOE2.1E-121SUNOS is a set of modules for energy analysis in buildings. Modules are included to calculate the heating and cooling loads for each space in a building for each hour of a year (LOADS), to simulate the operation and response of the equipment and systems that control temperature and humidity and distribute heating, cooling and ventilation to the building (SYSTEMS), to model energy conversion equipment that uses fuel or electricity to provide the required heating,more » cooling and electricity (PLANT), and to compute the cost of energy and building operation based on utility rate schedule and economic parameters (ECONOMICS).« less

  11. Building Energy Consumption Analysis

    Energy Science and Technology Software Center

    2005-01-24

    DOE2.1E-121 is a set of modules for energy analysis in buildings. Modules are included to calculate the heating and cooling loads for each space in a building for each hour of a year (LOADS), to simulate the operation and response of the equipment and systems that control temperature and humidity and distribute heating, cooling and ventilation to the building (SYSTEMS), to model energy conversion equipment that uses fuel or electricity to provide the required heating,more » cooling and electricity (PLANT), and to compute the cost of energy and building operation based on utility rate schedule and economic parameters (ECONOMICS). DOE2.1E-121 contains modifications to DOE2.1E which allows 1000 zones to be modeled.« less

  12. Community Energy Consumption Analysis

    Energy Science and Technology Software Center

    1992-02-21

    The TDIST3 program performs an analysis of large integrated community total energy systems (TES) supplying thermal and electrical energy from one or more power stations. The program models the time-dependent energy demands of a group of representative building types, distributes the thermal demands within a thermal utility system (TUS), simulates the dynamic response of a group of power stations in meeting the TUS demands, and designs an optimal base-loaded (electrically) power plant and thermal energymore » storage reservoir combination. The capital cost of the TES is evaluated. The program was developed primarily to analyze thermal utility systems supplied with high temperature water (HTW) from more than one power plant. The TUS consists of a transmission loop and secondary loops with a heat exchanger linking each secondary loop to the transmission loop. The power stations electrical output supplies all community buildings and the HTW supplies the thermal demand of the buildings connected through the TUS, a piping network. Basic components of the TES model are one or more power stations connected to the transmission loop. These may be dual-purpose, producing electricity and HTW, or just heating plants producing HTW. A thermal storage reservoir is located at one power station. The secondary loops may have heating plants connected to them. The transmission loop delivers HTW to local districts; the secondary loops deliver the energy to the individual buildings in a district.« less

  13. Manufacturing consumption of energy 1994

    SciTech Connect

    1997-12-01

    This report provides estimates on energy consumption in the manufacturing sector of the U.S. economy based on data from the Manufacturing Energy Consumption Survey. The sample used in this report represented about 250,000 of the largest manufacturing establishments which account for approximately 98 percent of U.S. economic output from manufacturing, and an expected similar proportion of manufacturing energy use. The amount of energy use was collected for all operations of each establishment surveyed. Highlights of the report include profiles for the four major energy-consuming industries (petroleum refining, chemical, paper, and primary metal industries), and an analysis of the effects of changes in the natural gas and electricity markets on the manufacturing sector. Seven appendices are included to provide detailed background information. 10 figs., 51 tabs.

  14. Energy Intensity Indicators: Residential Source Energy Consumption

    Energy.gov [DOE]

    Figure R1 below reports as index numbers over the period 1970 through 2011: 1) the number of U.S. households, 2) the average size of those housing units, 3) residential source energy consumption, 4...

  15. Vehicle Energy Consumption and Performance Analysis | Argonne...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Consumption and Performance Analysis Vehicle Energy Consumption and Performance Analysis Argonne researchers have applied their expertise in modeling, simulation and control to ...

  16. Visualization of United States Energy Consumption | Open Energy...

    OpenEI (Open Energy Information) [EERE & EIA]

    Energy Consumption Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Visualization of United States Energy Consumption AgencyCompany Organization: Energy Information...

  17. Household vehicles energy consumption 1994

    SciTech Connect

    1997-08-01

    Household Vehicles Energy Consumption 1994 reports on the results of the 1994 Residential Transportation Energy Consumption Survey (RTECS). The RTECS is a national sample survey that has been conducted every 3 years since 1985. For the 1994 survey, more than 3,000 households that own or use some 6,000 vehicles provided information to describe vehicle stock, vehicle-miles traveled, energy end-use consumption, and energy expenditures for personal vehicles. The survey results represent the characteristics of the 84.9 million households that used or had access to vehicles in 1994 nationwide. (An additional 12 million households neither owned or had access to vehicles during the survey year.) To be included in then RTECS survey, vehicles must be either owned or used by household members on a regular basis for personal transportation, or owned by a company rather than a household, but kept at home, regularly available for the use of household members. Most vehicles included in the RTECS are classified as {open_quotes}light-duty vehicles{close_quotes} (weighing less than 8,500 pounds). However, the RTECS also includes a very small number of {open_quotes}other{close_quotes} vehicles, such as motor homes and larger trucks that are available for personal use.

  18. Energy Information Administration (EIA)- Manufacturing Energy Consumption

    Gasoline and Diesel Fuel Update

    Survey (MECS) Steel Analysis Brief Chemical Industry Analysis Brief Change Topic: Steel | Chemical JUMP TO: Introduction | Energy Consumption | Energy Expenditures | Producer Prices and Production | Energy Intensity | Energy Management Activities | Fuel Switching Capacity Introduction The chemical industries are a cornerstone of the U.S. economy, converting raw materials such as oil, natural gas, air, water, metals, and minerals into thousands of various products. Chemicals are key materials

  19. Energy Information Administration (EIA)- Manufacturing Energy Consumption

    Gasoline and Diesel Fuel Update

    Survey (MECS) Steel Analysis Brief Steel Industry Analysis Brief Change Topic: Steel | Chemical JUMP TO: Introduction | Energy Consumption | Energy Expenditures | Producer Prices and Production | Energy Intensity | Energy Management Activities Introduction The steel industry is critical to the U.S. economy. Steel is the material of choice for many elements of construction, transportation, manufacturing, and a variety of consumer products. It is the backbone of bridges, skyscrapers,

  20. Energy consumption in thermomechanical pulping

    SciTech Connect

    Marton, R.; Tsujimoto, N.; Eskelinen, E.

    1981-08-01

    Various components of refining energy were determined experimentally and compared with those calculated on the basis of the dimensions of morphological elements of wood. The experimentally determined fiberization energy of spruce was 6 to 60 times larger than the calculated value and that of birch 3 to 15 times larger. The energy consumed in reducing the Canadian standard freeness of isolated fibers from 500 to 150 ml was found to be approximately 1/3 of the total fiber development energy for both spruce and birch TMP. Chip size affected the refining energy consumption; the total energy dropped by approximately 30% when chip size was reduced from 16 mm to 3 mm in the case of spruce and approximately 40% for birch. 6 refs.

  1. Commercial Buildings Energy Consumption and Expenditures 1992

    Energy Information Administration (EIA) (indexed site)

    Distribution Category UC-950 Commercial Buildings Energy Consumption and Expenditures 1992 April 1995 Energy Information Adminstration Office of Energy Markets and End Use U.S....

  2. Issues in International Energy Consumption Analysis: Canadian...

    Energy Information Administration (EIA) (indexed site)

    Issues in International Energy Consumption Analysis: Canadian Energy Demand June 2015 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 ...

  3. Residential Energy Consumption Survey (RECS) - Analysis & Projections...

    Gasoline and Diesel Fuel Update

    EIA has conducted the Residential Energy Consumption Survey (RECS) since 1978 to provide data on home energy characteristics, end uses of energy, and expenses for the four Census ...

  4. Household energy consumption and expenditures, 1990

    SciTech Connect

    Not Available

    1993-03-02

    This report, Household Energy Consumption and Expenditures 1990, is based upon data from the 1990 Residential Energy Consumption Survey (RECS). Focusing on energy end-use consumption and expenditures of households, the 1990 RECS is the eighth in a series conducted since 1978 by the Energy Information Administration (EIA). Over 5,000 households were surveyed, providing information on their housing units, housing characteristics, energy consumption and expenditures, stock of energy-consuming appliances, and energy-related behavior. The information provided represents the characteristics and energy consumption of 94 million households nationwide.

  5. Projecting household energy consumption within a conditional demand framework

    SciTech Connect

    Teotia, A.; Poyer, D.

    1991-01-01

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

  6. Projecting household energy consumption within a conditional demand framework

    SciTech Connect

    Teotia, A.; Poyer, D.

    1991-12-31

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

  7. DOE Taking Wind Forecasting to New Heights | Department of Energy

    Energy Saver

    Taking Wind Forecasting to New Heights DOE Taking Wind Forecasting to New Heights May 18, 2015 - 3:24pm Addthis A 2013 study conducted for the U.S. Department of Energy (DOE) by ...

  8. State energy data report 1992: Consumption estimates

    SciTech Connect

    Not Available

    1994-05-01

    This is a report of energy consumption by state for the years 1960 to 1992. The report contains summaries of energy consumption for the US and by state, consumption by source, comparisons to other energy use reports, consumption by energy use sector, and describes the estimation methodologies used in the preparation of the report. Some years are not listed specifically although they are included in the summary of data.

  9. Household energy consumption and expenditures, 1987

    SciTech Connect

    Not Available

    1989-10-10

    Household Energy Consumption and Expenditures 1987, Part 1: National Data is the second publication in a series from the 1987 Residential Energy Consumption Survey (RECS). It is prepared by the Energy End Use Division (EEUD) of the Office of Energy Markets and End Use (EMEU), Energy Information Administration (EIA). The EIA collects and publishes comprehensive data on energy consumption in occupied housing units in the residential sector through the RECS. 15 figs., 50 tabs.

  10. Commercial Buildings Energy Consumption and Expenditures 1992

    Energy Information Administration (EIA) (indexed site)

    Appendix A How the Survey Was Conducted Introduction The Commercial Buildings Energy Consumption Survey (CBECS) is conducted by the Energy Information Administration (EIA) on a...

  11. Issues in International Energy Consumption Analysis: Electricity...

    Energy Information Administration (EIA) (indexed site)

    Energy Consumption Analysis: Electricity Usage in India's Housing Sector November 2014 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC ...

  12. Manufacturing Energy Consumption Survey (MECS) - Analysis & Projection...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    That increase in supply has in turn lowered the price of natural gas to manufacturers Manufacturing Energy Consumption Data Show Large Reductions in Both Manufacturing Energy Use ...

  13. Residential Energy Consumption Survey (RECS) - Analysis & Projections...

    Gasoline and Diesel Fuel Update

    This rise has occurred while Federal energy efficiency standards were enacted on every major appliance, overall household energy consumption actually decreased from 10.58 quads to ...

  14. Electrical appliance energy consumption control methods and electrical energy consumption systems

    DOEpatents

    Donnelly, Matthew K.; Chassin, David P.; Dagle, Jeffery E.; Kintner-Meyer, Michael; Winiarski, David W.; Pratt, Robert G.; Boberly-Bartis, Anne Marie

    2008-09-02

    Electrical appliance energy consumption control methods and electrical energy consumption systems are described. In one aspect, an electrical appliance energy consumption control method includes providing an electrical appliance coupled with a power distribution system, receiving electrical energy within the appliance from the power distribution system, consuming the received electrical energy using a plurality of loads of the appliance, monitoring electrical energy of the power distribution system, and adjusting an amount of consumption of the received electrical energy via one of the loads of the appliance from an initial level of consumption to an other level of consumption different than the initial level of consumption responsive to the monitoring.

  15. Electrical appliance energy consumption control methods and electrical energy consumption systems

    DOEpatents

    Donnelly, Matthew K.; Chassin, David P.; Dagle, Jeffery E.; Kintner-Meyer, Michael; Winiarski, David W.; Pratt, Robert G.; Boberly-Bartis, Anne Marie

    2006-03-07

    Electrical appliance energy consumption control methods and electrical energy consumption systems are described. In one aspect, an electrical appliance energy consumption control method includes providing an electrical appliance coupled with a power distribution system, receiving electrical energy within the appliance from the power distribution system, consuming the received electrical energy using a plurality of loads of the appliance, monitoring electrical energy of the power distribution system, and adjusting an amount of consumption of the received electrical energy via one of the loads of the appliance from an initial level of consumption to an other level of consumption different than the initial level of consumption responsive to the monitoring.

  16. State Energy Data System 2014 Consumption Technical Notes

    Annual Energy Outlook

    Consumption Technical Notes U.S. Energy Information Administration | State Energy Data 2014: Consumption 3 Purpose All of the estimates contained in the state energy consumption ...

  17. Trends in Commercial Buildings--Trends in Energy Consumption...

    Energy Information Administration (EIA) (indexed site)

    2 Part 1. Energy Consumption Data Tables Total Energy Intensity Intensity by Energy Source Background: Site and Primary Energy Trends in Energy Consumption and Energy Sources Part...

  18. Household energy consumption and expenditures 1993

    SciTech Connect

    1995-10-05

    This presents information about household end-use consumption of energy and expenditures for that energy. These data were collected in the 1993 Residential Energy Consumption Survey; more than 7,000 households were surveyed for information on their housing units, energy consumption and expenditures, stock of energy-consuming appliances, and energy-related behavior. The information represents all households nationwide (97 million). Key findings: National residential energy consumption was 10.0 quadrillion Btu in 1993, a 9% increase over 1990. Weather has a significant effect on energy consumption. Consumption of electricity for appliances is increasing. Houses that use electricity for space heating have lower overall energy expenditures than households that heat with other fuels. RECS collected data for the 4 most populous states: CA, FL, NY, TX.

  19. Acquisition Forecast Download | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Acquisition Forecast Download Acquisition Forecast Download Click on the link to download a copy of the DOE HQ Acquisition Forecast. Acquisition-Forecast-2016-11-10.xlsx (70.03 KB) More Documents & Publications National Nuclear Security Administration - Juliana Heynes Small Business Program Manager Directory EA-1900: Notice of Availability of a Draft Environmental Assessment

  20. Today's Forecast: Improved Wind Predictions | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions July 20, 2011 - 6:30pm Addthis Stan Calvert Wind Systems Integration Team Lead, Wind & Water Power Program What does this project do? It will increase the accuracy of weather forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical

  1. Optimization Based Data Mining Approah for Forecasting Real-Time Energy Demand

    SciTech Connect

    Omitaomu, Olufemi A; Li, Xueping; Zhou, Shengchao

    2015-01-01

    The worldwide concern over environmental degradation, increasing pressure on electric utility companies to meet peak energy demand, and the requirement to avoid purchasing power from the real-time energy market are motivating the utility companies to explore new approaches for forecasting energy demand. Until now, most approaches for forecasting energy demand rely on monthly electrical consumption data. The emergence of smart meters data is changing the data space for electric utility companies, and creating opportunities for utility companies to collect and analyze energy consumption data at a much finer temporal resolution of at least 15-minutes interval. While the data granularity provided by smart meters is important, there are still other challenges in forecasting energy demand; these challenges include lack of information about appliances usage and occupants behavior. Consequently, in this paper, we develop an optimization based data mining approach for forecasting real-time energy demand using smart meters data. The objective of our approach is to develop a robust estimation of energy demand without access to these other building and behavior data. Specifically, the forecasting problem is formulated as a quadratic programming problem and solved using the so-called support vector machine (SVM) technique in an online setting. The parameters of the SVM technique are optimized using simulated annealing approach. The proposed approach is applied to hourly smart meters data for several residential customers over several days.

  2. 2016 Solar Forecasting Workshop | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Solar Forecasting Workshop 2016 Solar Forecasting Workshop On August 3, 2016, the SunShot Initiative's systems integration subprogram hosted the Solar Forecasting Workshop to convene experts in the areas of bulk power system operations, distribution system operations, weather and solar irradiance forecasting, and photovoltaic system operation and modeling. The goal was to identify the technical challenges and opportunities in solar forecasting as a capability that can significantly reduce the

  3. Manufacturing Energy Consumption Survey (MECS) - U.S. Energy Information

    Energy Information Administration (EIA) (indexed site)

    Administration (EIA) ‹ Consumption & Efficiency Manufacturing Energy Consumption Survey (MECS) Glossary › FAQS › Overview Data 2010 2006 2002 1998 1994 1991 Archive Analysis & Projections Preliminary estimates show that U.S. manufacturing energy consumption increased between 2010 and 2014 Graph showing manufacturing energy consumption has increased for the first time since 2002 Source: U.S. Energy Information Administration, Manufacturing Energy Consumption Survey (MECS) 2010

  4. Manufacturing Energy Consumption Survey (MECS) - U.S. Energy Information

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Administration (EIA) ‹ Consumption & Efficiency Manufacturing Energy Consumption Survey (MECS) Glossary › FAQS › Overview Data 2010 2006 2002 1998 1994 1991 Archive Analysis & Projections Preliminary estimates show that U.S. manufacturing energy consumption increased between 2010 and 2014 Graph showing manufacturing energy consumption has increased for the first time since 2002 Source: U.S. Energy Information Administration, Manufacturing Energy Consumption Survey (MECS) 2010

  5. Short-Term Energy Outlook Model Documentation: Other Petroleum Products Consumption Model

    Reports and Publications

    2011-01-01

    The other petroleum product consumption module of the Short-Term Energy Outlook (STEO) model is designed to provide U.S. consumption forecasts for 6 petroleum product categories: asphalt and road oil, petrochemical feedstocks, petroleum coke, refinery still gas, unfinished oils, and other miscvellaneous products

  6. Residential Energy Consumption Survey (RECS) - Energy Information

    Energy Information Administration (EIA) (indexed site)

    Administration U.S. Energy Information Administration - EIA - Independent Statistics and Analysis Sources & Uses Petroleum & Other Liquids Crude oil, gasoline, heating oil, diesel, propane, and other liquids including biofuels and natural gas liquids. Natural Gas Exploration and reserves, storage, imports and exports, production, prices, sales. Electricity Sales, revenue and prices, power plants, fuel use, stocks, generation, trade, demand & emissions. Consumption &

  7. NREL: Energy Analysis - Energy Forecasting and Modeling Staff

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Energy Forecasting and Modeling The following includes summary bios of staff expertise and interests in analysis relating to energy economics, energy system planning, risk and uncertainty modeling, and energy infrastructure planning. Team Lead: Nate Blair Administrative Support: Elizabeth Torres Clayton Barrows Dave Bielen Aaron Bloom Greg Brinkman Brian W Bush Stuart Cohen Wesley Cole Paul Denholm Nicholas DiOrio Aron Dobos Kelly Eurek Janine Freeman Bethany Frew Pieter Gagnon Elaine Hale

  8. DOE Publishes New Forecast of Energy Savings from LED Lighting...

    Office of Environmental Management (EM)

    Addthis Related Articles DOE Releases Latest Report on Energy Savings Forecast of Solid-State Lighting DOE Publishes Pricing and Efficacy Trend Analysis for Utility Program ...

  9. Consumption

    Energy Information Administration (EIA) (indexed site)

    . Electricity Consumption and Conditional Energy Intensity by Climate Zonea for Non-Mall Buildings, 2003" ,"Total Electricity Consumption (billion kWh)",,,,,"Total Floorspace of...

  10. Consumption

    Energy Information Administration (EIA) (indexed site)

    A. Electricity Consumption and Conditional Energy Intensity by Climate Zonea for All Buildings, 2003" ,"Total Electricity Consumption (billion kWh)",,,,,"Total Floorspace of...

  11. Consumption

    Energy Information Administration (EIA) (indexed site)

    A. Electricity Consumption and Conditional Energy Intensity by Building Size for All Buildings, 2003" ,"Total Electricity Consumption (billion kWh)",,,"Total Floorspace of...

  12. Consumption

    Energy Information Administration (EIA) (indexed site)

    3. Electricity Consumption and Conditional Energy Intensity, 1999" ,"Total Electricity Consumption (billion kWh)",,,"Total Floorspace of Buildings Using Electricity (million square...

  13. Consumption

    Energy Information Administration (EIA) (indexed site)

    A. Electricity Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 1" ,"Total Electricity Consumption (billion kWh)",,,"Total Floorspace...

  14. Consumption

    Energy Information Administration (EIA) (indexed site)

    . Electricity Consumption and Conditional Energy Intensity by Building Size for Non-Mall Buildings, 2003" ,"Total Electricity Consumption (billion kWh)",,,"Total Floorspace of...

  15. Consumption

    Energy Information Administration (EIA) (indexed site)

    . Electricity Consumption and Conditional Energy Intensity by Census Division for Non-Mall Buildings, 2003: Part 1" ,"Total Electricity Consumption (billion kWh)",,,"Total...

  16. Consumption

    Energy Information Administration (EIA) (indexed site)

    . Electricity Consumption and Conditional Energy Intensity by Census Division for Non-Mall Buildings, 2003: Part 2" ,"Total Electricity Consumption (billion kWh)",,,"Total...

  17. Consumption

    Energy Information Administration (EIA) (indexed site)

    9A. Electricity Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 3" ,"Total Electricity Consumption (billion kWh)",,,"Total Floorspace...

  18. Consumption

    Energy Information Administration (EIA) (indexed site)

    Electricity Consumption and Conditional Energy Intensity by Census Region, 1999" ,"Total Electricity Consumption (billion kWh)",,,,"Total Floorspace of Buildings Using Electricity...

  19. Consumption

    Energy Information Administration (EIA) (indexed site)

    . Electricity Consumption and Conditional Energy Intensity by Census Region for Non-Mall Buildings, 2003" ,"Total Electricity Consumption (billion kWh)",,,,"Total Floorspace of...

  20. Consumption

    Energy Information Administration (EIA) (indexed site)

    A. Electricity Consumption and Conditional Energy Intensity by Census Region for All Buildings, 2003" ,"Total Electricity Consumption (billion kWh)",,,,"Total Floorspace of...

  1. Consumption

    Energy Information Administration (EIA) (indexed site)

    . Electricity Consumption and Conditional Energy Intensity by Year Constructed for Non-Mall Buildings, 2003" ,"Total Electricity Consumption (billion kWh)",,,"Total Floorspace of...

  2. Consumption

    Energy Information Administration (EIA) (indexed site)

    4. Electricity Consumption and Conditional Energy Intensity by Year Constructed, 1999" ,"Total Electricity Consumption (billion kWh)",,,"Total Floorspace of Buildings Using...

  3. Consumption

    Energy Information Administration (EIA) (indexed site)

    A. Electricity Consumption and Conditional Energy Intensity by Census Division for All Buildings, 2003: Part 2" ,"Total Electricity Consumption (billion kWh)",,,"Total Floorspace...

  4. Consumption

    Energy Information Administration (EIA) (indexed site)

    A. Electricity Consumption and Conditional Energy Intensity by Year Constructed for All Buildings, 2003" ,"Total Electricity Consumption (billion kWh)",,,"Total Floorspace of...

  5. Consumption

    Energy Information Administration (EIA) (indexed site)

    . Electricity Consumption and Conditional Energy Intensity by Census Division for Non-Mall Buildings, 2003: Part 3" ,"Total Electricity Consumption (billion kWh)",,,"Total...

  6. Consumption

    Energy Information Administration (EIA) (indexed site)

    5. Fuel Oil Consumption and Conditional Energy Intensity by Census Region for Non-Mall Buildings, 2003" ,"Total Fuel Oil Consumption (million gallons)",,,,"Total Floorspace of...

  7. Consumption

    Energy Information Administration (EIA) (indexed site)

    3. Fuel Oil Consumption and Conditional Energy Intensity by Census Region, 1999" ,"Total Fuel Oil Consumption (million gallons)",,,,"Total Floorspace of Buildings Using Fuel Oil...

  8. Consumption

    Energy Information Administration (EIA) (indexed site)

    A. Fuel Oil Consumption and Conditional Energy Intensity by Census Region for All Buildings, 2003" ,"Total Fuel Oil Consumption (million gallons)",,,,"Total Floorspace of Buildings...

  9. Wind Forecasting Improvement Project | Department of Energy

    Energy Saver

    Forecasting Improvement Project Wind Forecasting Improvement Project October 3, 2011 - 12:12pm Addthis This is an excerpt from the Third Quarter 2011 edition of the Wind Program ...

  10. State energy data report 1993: Consumption estimates

    SciTech Connect

    1995-07-01

    The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public; and (2) to provide the historical series necessary for EIA`s energy models.

  11. State Energy Data Report, 1991: Consumption estimates

    SciTech Connect

    Not Available

    1993-05-01

    The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to the Government, policy makers, and the public; and (2) to provide the historical series necessary for EIA`s energy models.

  12. Commercial Buildings Energy Consumption and Expenditures 1992

    Energy Information Administration (EIA) (indexed site)

    Appendix I Related EIA Publications on Energy Consumption For information about how to obtain these publi- cations, see the inside cover of this report. Please note that the...

  13. Commercial Buildings Energy Consumption and Expenditures 1992

    Energy Information Administration (EIA) (indexed site)

    in this report were based on monthly billing records submitted by the buildings' energy suppliers. The section, "Annual Consumption and Expenditures" provide a detailed...

  14. ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; GREENHOUSES...

    Office of Scientific and Technical Information (OSTI)

    fuel-fired peak heating for geothermal greenhouses Rafferty, K. 32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION; GREENHOUSES; AUXILIARY HEATING; CAPITALIZED COST; OPERATING...

  15. Derived Annual Estimates of Manufacturing Energy Consumption...

    Energy Information Administration (EIA) (indexed site)

    > Derived Annual Estimates - Executive Summary Derived Annual Estimates of Manufacturing Energy Consumption, 1974-1988 Figure showing Derived Estimates Executive Summary This...

  16. Household Vehicles Energy Consumption 1994 - Appendix C

    Energy Information Administration (EIA) (indexed site)

    discusses several issues relating to the quality of the Residential Transportation Energy Consumption Survey (RTECS) data and to the interpretation of conclusions based on...

  17. Commercial Miscellaneous Electric Loads Report: Energy Consumption...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Commercial Miscellaneous Electric Loads Report: Energy Consumption Characterization and Savings Potential in 2008 by Building Type Commercial Miscellaneous Electric Loads Report: ...

  18. State energy data report 1994: Consumption estimates

    SciTech Connect

    1996-10-01

    This document provides annual time series estimates of State-level energy consumption by major economic sector. The estimates are developed in the State Energy Data System (SEDS), operated by EIA. SEDS provides State energy consumption estimates to members of Congress, Federal and State agencies, and the general public, and provides the historical series needed for EIA`s energy models. Division is made for each energy type and end use sector. Nuclear electric power is included.

  19. Energy Information Administration - Commercial Energy Consumption...

    Annual Energy Outlook

    4A. Electricity Consumption and Expenditure Intensities for All Buildings, 2003 Electricity Consumption Electricity Expenditures per Building (thousand kWh) per Square Foot (kWh)...

  20. Energy Information Administration - Commercial Energy Consumption...

    Annual Energy Outlook

    3A. Total Electricity Consumption and Expenditures for All Buildings, 2003 All Buildings Using Electricity Electricity Consumption Electricity Expenditures Number of Buildings...

  1. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update

    4A. Fuel Oil Consumption and Expenditure Intensities for All Buildings, 2003 Fuel Oil Consumption Fuel Oil Expenditures per Building (gallons) per Square Foot (gallons) per...

  2. Energy Information Administration - Commercial Energy Consumption...

    Annual Energy Outlook

    3A. Total Fuel Oil Consumption and Expenditures for All Buildings, 2003 All Buildings Using Fuel Oil Fuel Oil Consumption Fuel Oil Expenditures Number of Buildings (thousand)...

  3. State energy data report 1996: Consumption estimates

    SciTech Connect

    1999-02-01

    The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sectors. The estimates are developed in the Combined State Energy Data System (CSEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining CSEDS is to create historical time series of energy consumption by State that are defined as consistently as possible over time and across sectors. CSEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public and (2) to provide the historical series necessary for EIA`s energy models. To the degree possible, energy consumption has been assigned to five sectors: residential, commercial, industrial, transportation, and electric utility sectors. Fuels covered are coal, natural gas, petroleum, nuclear electric power, hydroelectric power, biomass, and other, defined as electric power generated from geothermal, wind, photovoltaic, and solar thermal energy. 322 tabs.

  4. Residential Energy Consumption Survey (RECS) - Analysis & Projections...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Where does RECS square footage data come from? July 11, 2012 RECS data show decreased energy consumption per household June 6, 2012 The impact of increasing home size on energy ...

  5. Appliance Energy Consumption in Australia | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    ?viewPublicatio Equivalent URI: cleanenergysolutions.orgcontentappliance-energy-consumption-australi DeploymentPrograms: Industry Codes & Standards Regulations:...

  6. Residential Energy Consumption Survey: Quality Profile

    SciTech Connect

    1996-03-01

    The Residential Energy Consumption Survey (RECS) is a periodic national survey that provides timely information about energy consumption and expenditures of U.S. households and about energy-related characteristics of housing units. The survey was first conducted in 1978 as the National Interim Energy Consumption Survey (NIECS), and the 1979 survey was called the Household Screener Survey. From 1980 through 1982 RECS was conducted annually. The next RECS was fielded in 1984, and since then, the survey has been undertaken at 3-year intervals. The most recent RECS was conducted in 1993.

  7. Changes in Natural Gas Monthly Consumption Data Collection and the Short-Term Energy Outlook

    Reports and Publications

    2010-01-01

    Beginning with the December 2010 issue of the Short-Term Energy Outlook (STEO), the Energy Information Administration (EIA) will present natural gas consumption forecasts for the residential and commercial sectors that are consistent with recent changes to the Form EIA-857 monthly natural gas survey.

  8. Estimates of US biomass energy consumption 1992

    SciTech Connect

    Not Available

    1994-05-06

    This report is the seventh in a series of publications developed by the Energy Information Administration (EIA) to quantify the biomass-derived primary energy used by the US economy. It presents estimates of 1991 and 1992 consumption. The objective of this report is to provide updated estimates of biomass energy consumption for use by Congress, Federal and State agencies, biomass producers and end-use sectors, and the public at large.

  9. Commercial Miscellaneous Electric Loads Report: Energy Consumption

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Characterization and Savings Potential in 2008 by Building Type | Department of Energy Commercial Miscellaneous Electric Loads Report: Energy Consumption Characterization and Savings Potential in 2008 by Building Type Commercial Miscellaneous Electric Loads Report: Energy Consumption Characterization and Savings Potential in 2008 by Building Type Commercial miscellaneous electric loads (MELs) are generally defined as all electric loads except those related to main systems for heating,

  10. 1991 Manufacturing Consumption of Energy 1991 Executive Summary

    Energy Information Administration (EIA) (indexed site)

    Summary The Manufacturing Consumption of Energy 1991 report presents statistics about the energy consumption of the manufacturing sector, based on the 1991 Manufacturing Energy...

  11. The Wind Forecast Improvement Project (WFIP). A Public-Private Partnership Addressing Wind Energy Forecast Needs

    SciTech Connect

    Wilczak, James M.; Finley, Cathy; Freedman, Jeff; Cline, Joel; Bianco, L.; Olson, J.; Djalaova, I.; Sheridan, L.; Ahlstrom, M.; Manobianco, J.; Zack, J.; Carley, J.; Benjamin, S.; Coulter, R. L.; Berg, Larry K.; Mirocha, Jeff D.; Clawson, K.; Natenberg, E.; Marquis, M.

    2015-10-30

    The Wind Forecast Improvement Project (WFIP) is a public-private research program, the goals of which are to improve the accuracy of short-term (0-6 hr) wind power forecasts for the wind energy industry and then to quantify the economic savings that accrue from more efficient integration of wind energy into the electrical grid. WFIP was sponsored by the U.S. Department of Energy (DOE), with partners that include the National Oceanic and Atmospheric Administration (NOAA), private forecasting companies (WindLogics and AWS Truepower), DOE national laboratories, grid operators, and universities. WFIP employed two avenues for improving wind power forecasts: first, through the collection of special observations to be assimilated into forecast models to improve model initial conditions; and second, by upgrading NWP forecast models and ensembles. The new observations were collected during concurrent year-long field campaigns in two high wind energy resource areas of the U.S. (the upper Great Plains, and Texas), and included 12 wind profiling radars, 12 sodars, 184 instrumented tall towers and over 400 nacelle anemometers (provided by private industry), lidar, and several surface flux stations. Results demonstrate that a substantial improvement of up to 14% relative reduction in power root mean square error (RMSE) was achieved from the combination of improved NOAA numerical weather prediction (NWP) models and assimilation of the new observations. Data denial experiments run over select periods of time demonstrate that up to a 6% relative improvement came from the new observations. The use of ensemble forecasts produced even larger forecast improvements. Based on the success of WFIP, DOE is planning follow-on field programs.

  12. State energy data report 1995 - consumption estimates

    SciTech Connect

    1997-12-01

    The State Energy Data Report (SEDR) provides annual time series estimates of State-level energy consumption by major economic sectors. The estimates are developed in the State Energy Data System (SEDS), which is maintained and operated by the Energy Information Administration (EIA). The goal in maintaining SEDS exists for two principal reasons: (1) to provide State energy consumption estimates to Members of Congress, Federal and State agencies, and the general public, and (2) to provide the historical series necessary for EIA`s energy models.

  13. Energy Department Forecasts Geothermal Achievements in 2015 | Department of

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Energy Forecasts Geothermal Achievements in 2015 Energy Department Forecasts Geothermal Achievements in 2015 The 40th annual Stanford Geothermal Workshop in January featured speakers in the geothermal sector, including Jay Nathwani, Acting Director of the Energy Department's Geothermal Technologies Office. Nathwani shared achievements and challenges in the program's technical portfolio. The 40th annual Stanford Geothermal Workshop in January featured speakers in the geothermal sector,

  14. Manufacturing Consumption of Energy 1994

    Energy Information Administration (EIA) (indexed site)

    A24. Total Inputs of Energy for Heat, Power, and Electricity Generation by Program Sponsorship, Industry Group, Selected Industries, and Type of Energy- Management Program, 1994:...

  15. Consumption & Efficiency - U.S. Energy Information Administration (EIA)

    Energy Information Administration (EIA) (indexed site)

    Consumption & Efficiency Glossary › FAQS › Overview Data Residential Energy Consumption Survey data Commercial Energy Consumption Survey data Manufacturing Energy Consumption Survey data Vehicle Energy Consumption Survey data Energy intensity Consumption summaries Average cost of fossil-fuels for electricity generation All consumption & efficiency data reports Analysis & Projections Major Topics Most popular All sectors Commercial buildings Efficiency Manufacturing Projections

  16. Energy Information Administration - Commercial Energy Consumption...

    Energy Information Administration (EIA) (indexed site)

    Gas Consumption Natural Gas Expenditures per Building (thousand cubic feet) per Square Foot (cubic feet) Distribution of Building-Level Intensities (cubic feetsquare foot) 25th...

  17. Consumption

    Energy Information Administration (EIA) (indexed site)

    . Consumption and Gross Energy Intensity by Building Size for Sum of Major Fuels for Non-Mall Buildings, 2003" ,"Sum of Major Fuel Consumption (trillion Btu)",,,"Total Floorspace...

  18. Energy Consumption of Die Casting Operations

    SciTech Connect

    Jerald Brevick; clark Mount-Campbell; Carroll Mobley

    2004-03-15

    Molten metal processing is inherently energy intensive and roughly 25% of the cost of die-cast products can be traced to some form of energy consumption [1]. The obvious major energy requirements are for melting and holding molten alloy in preparation for casting. The proper selection and maintenance of melting and holding equipment are clearly important factors in minimizing energy consumption in die-casting operations [2]. In addition to energy consumption, furnace selection also influences metal loss due to oxidation, metal quality, and maintenance requirements. Other important factors influencing energy consumption in a die-casting facility include geographic location, alloy(s) cast, starting form of alloy (solid or liquid), overall process flow, casting yield, scrap rate, cycle times, number of shifts per day, days of operation per month, type and size of die-casting form of alloy (solid or liquid), overall process flow, casting yield, scrap rate, cycle times, number of shifts per day, days of operation per month, type and size of die-casting machine, related equipment (robots, trim presses), and downstream processing (machining, plating, assembly, etc.). Each of these factors also may influence the casting quality and productivity of a die-casting enterprise. In a die-casting enterprise, decisions regarding these issues are made frequently and are based on a large number of factors. Therefore, it is not surprising that energy consumption can vary significantly from one die-casting enterprise to the next, and within a single enterprise as function of time.

  19. Wind Energy Technology Trends: Comparing and Contrasting Recent Cost and Performance Forecasts (Poster)

    SciTech Connect

    Lantz, E.; Hand, M.

    2010-05-01

    Poster depicts wind energy technology trends, comparing and contrasting recent cost and performance forecasts.

  20. Household Vehicles Energy Consumption 1991

    Energy Information Administration (EIA) (indexed site)

    selected tabulations were produced using two different software programs, Table Producing Language (TPL) and Statistical Analysis System (SAS). Energy Information Administration...

  1. Manufacturing Consumption of Energy 1994

    Energy Information Administration (EIA) (indexed site)

    in hydro- power. During that time period, there was an unusual number of hydropower projects up for license renewal by the Federal Energy Regulatory Commission; hydropower...

  2. Manufacturing Consumption of Energy 1994

    Energy Information Administration (EIA) (indexed site)

    energy data used in this report do not reflect adjustments for losses in electricity generation or transmission. 1 The manufacturing sector is composed of establishments classified...

  3. Manufacturing Energy Consumption Survey (MECS) - Data - U.S....

    Energy Information Administration (EIA) (indexed site)

    Data Methodology & Forms + EXPAND ALL Consumption of Energy for All Purposes (First Use) Total Primary Consumption of Energy for All Purposes by Census Region, Industry Group, and ...

  4. Manufacturing Energy Consumption Survey (MECS) - Data - U.S....

    Energy Information Administration (EIA) (indexed site)

    Data Methodology & Forms + EXPAND ALL Consumption of Energy for All Purposes (First Use) Total First Use (formerly Primary Consumption) of Energy for All Purposes by Census Region, ...

  5. ,"Total Fuel Oil Consumption (trillion Btu)",,,,,"Fuel Oil Energy...

    Energy Information Administration (EIA) (indexed site)

    A. Fuel Oil Consumption (Btu) and Energy Intensities by End Use for All Buildings, 2003" ,"Total Fuel Oil Consumption (trillion Btu)",,,,,"Fuel Oil Energy Intensity (thousand Btu...

  6. 2002 Manufacturing Energy Consumption Survey - User Needs Survey

    Energy Information Administration (EIA) (indexed site)

    2002 Manufacturing Energy Consumption Survey: User-Needs Survey View current results. We need your help in designing the next Energy Consumption Survey (MECS) As our valued...

  7. Smart Meters Help Balance Energy Consumption at Solar Decathlon...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Smart Meters Help Balance Energy Consumption at Solar Decathlon Smart Meters Help Balance Energy Consumption at Solar Decathlon September 28, 2011 - 10:57am Addthis The Team...

  8. Power to the Plug: An Introduction to Energy, Electricity, Consumption...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    to the Plug: An Introduction to Energy, Electricity, Consumption, and Efficiency Power to the Plug: An Introduction to Energy, Electricity, Consumption, and Efficiency Below is...

  9. Appliance Standby Power and Energy Consumption in South African...

    OpenEI (Open Energy Information) [EERE & EIA]

    Standby Power and Energy Consumption in South African Households Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Appliance Standby Power and Energy Consumption in South...

  10. Energy Information Agency's 2003 Commercial Building Energy Consumption Survey Tables

    Office of Energy Efficiency and Renewable Energy (EERE)

    Energy use intensities in commercial buildings vary widely and depend on activity and climate, as shown in this data table, which was derived from the Energy Information Agency's 2003 Commercial Building Energy Consumption Survey.

  11. Making Wind Energy Predictable: New Profilers Provide Hourly Forecasts |

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Department of Energy Wind Energy Predictable: New Profilers Provide Hourly Forecasts Making Wind Energy Predictable: New Profilers Provide Hourly Forecasts May 11, 2016 - 6:48pm Addthis Balancing the power grid is an art-or at least a scientific study in chaos-and the Energy Department is hoping wind energy can take a greater role in the act. Yet, the intermittency of wind-sometimes it's blowing, sometimes it's not-makes adding it smoothly to the nation's electrical grid a challenge. If wind

  12. Energy consumption series: Lighting in commercial buildings

    SciTech Connect

    Not Available

    1992-03-11

    Lighting represents a substantial fraction of commercial electricity consumption. A wide range of initiatives in the Department of Energy`s (DOE) National Energy Strategy have focused on commercial lighting as a potential source of energy conservation. This report provides a statistical profile of commercial lighting, to examine the potential for lighting energy conservation in commercial buildings. The principal conclusion from this analysis is that energy use for lighting could be reduced by as much as a factor of four using currently available technology. The analysis is based primarily on the Energy Information Administration`s (EIA) 1986 Commercial Buildings Energy Consumption Survey (CBECS). The more recent 1989 survey had less detail on lighting, for budget reasons. While changes have occurred in the commercial building stock since 1986, the relationships identified by this analysis are expected to remain generally valid. In addition, the analytic approach developed here can be applied to the data that will be collected in the 1992 CBECS.

  13. Trends in Renewable Energy Consumption and Electricity - Energy...

    Gasoline and Diesel Fuel Update

    Overview Data Summary Biomass Geothermal Hydropower Solar Wind Alternative transportation ... Wind was the source of 11 percent of total renewable energy consumption, and solar and ...

  14. Manufacturing Consumption of Energy 1994

    Energy Information Administration (EIA) (indexed site)

    A9. Total Inputs of Energy for Heat, Power, and Electricity Generation by Fuel Type, Census Region, and End Use, 1994: Part 1 (Estimates in Btu or Physical Units) See footnotes at...

  15. Manufacturing Consumption of Energy 1994

    Energy Information Administration (EIA) (indexed site)

    , X Y X X M. Hansen, W. Hurwitz, and W. Madlow, "Sample and Survey Methods and Theory, Volume I" (New York: John Wiley & Sons, Inc., 1953), 49 p. 166. 440 Energy...

  16. Commercial Buildings Energy Consumption Survey - Office Buildings

    Reports and Publications

    2010-01-01

    Provides an in-depth look at this building type as reported in the 2003 Commercial Buildings Energy Consumption Survey. Office buildings are the most common type of commercial building and they consumed more than 17% of all energy in the commercial buildings sector in 2003. This special report provides characteristics and energy consumption data by type of office building (e.g. administrative office, government office, medical office) and information on some of the types of equipment found in office buildings: heating and cooling equipment, computers, servers, printers, and photocopiers.

  17. Household energy consumption and expenditures 1987

    SciTech Connect

    Not Available

    1990-01-22

    This report is the third in the series of reports presenting data from the 1987 Residential Energy Consumption Survey (RECS). The 1987 RECS, seventh in a series of national surveys of households and their energy suppliers, provides baseline information on household energy use in the United States. Data from the seven RECS and its companion survey, the Residential Transportation Energy Consumption Survey (RTECS), are made available to the public in published reports such as this one, and on public use data files. This report presents data for the four Census regions and nine Census divisions on the consumption of and expenditures for electricity, natural gas, fuel oil and kerosene (as a single category), and liquefied petroleum gas (LPG). Data are also presented on consumption of wood at the Census region level. The emphasis in this report is on graphic depiction of the data. Data from previous RECS surveys are provided in the graphics, which indicate the regional trends in consumption, expenditures, and uses of energy. These graphs present data for the United States and each Census division. 12 figs., 71 tabs.

  18. International Energy Outlook 2016-Transportation sector energy consumption

    Gasoline and Diesel Fuel Update

    - Energy Information Administration 8. Transportation sector energy consumption print version Overview In the International Energy Outlook 2016 (IEO2016) Reference case, transportation sector delivered energy consumption increases at an annual average rate of 1.4%, from 104 quadrillion British thermal units (Btu) in 2012 to 155 quadrillion Btu in 2040. Transportation energy demand growth occurs almost entirely in regions outside of the Organization for Economic Cooperation and Development

  19. Visualization of United States Renewable Consumption | Open Energy...

    OpenEI (Open Energy Information) [EERE & EIA]

    Visualization of United States Renewable Consumption AgencyCompany Organization: Energy Information Administration Sector: Energy Resource Type: Softwaremodeling tools User...

  20. The impact of forecasted energy price increases on low-income consumers

    SciTech Connect

    Eisenberg, Joel F.

    2005-10-31

    The Department of Energy’s Energy Information Administration (EIA) recently released its short term forecast for residential energy prices for the winter of 2005-2006. The forecast indicates significant increases in fuel costs, particularly for natural gas, propane, and home heating oil, for the year ahead. In the following analysis, the Oak Ridge National Laboratory has integrated the EIA price projections with the Residential Energy Consumption Survey (RECS) for 2001 in order to project the impact of these price increases on the nation’s low-income households by primary heating fuel type, nationally and by Census Region. The statistics are intended for the use of policymakers in the Department of Energy’s Weatherization Assistance Program and elsewhere who are trying to gauge the nature and severity of the problems that will be faced by eligible low-income households during the 2006 fiscal year.

  1. Household Energy Consumption Segmentation Using Hourly Data

    SciTech Connect

    Kwac, J; Flora, J; Rajagopal, R

    2014-01-01

    The increasing US deployment of residential advanced metering infrastructure (AMI) has made hourly energy consumption data widely available. Using CA smart meter data, we investigate a household electricity segmentation methodology that uses an encoding system with a pre-processed load shape dictionary. Structured approaches using features derived from the encoded data drive five sample program and policy relevant energy lifestyle segmentation strategies. We also ensure that the methodologies developed scale to large data sets.

  2. Issues in International Energy Consumption Analysis: Canadian Energy Demand

    Reports and Publications

    2015-01-01

    The residential sector is one of the main end-use sectors in Canada accounting for 16.7% of total end-use site energy consumption in 2009 (computed from NRCan 2012. pp, 4-5). In this year, the residential sector accounted for 54.5% of buildings total site energy consumption. Between 1990 and 2009, Canadian household energy consumption grew by less than 11%. Nonetheless, households contributed to 14.6% of total energy-related greenhouse gas emissions in Canada in 2009 (computed from NRCan 2012). This is the U.S. Energy Information Administrations second study to help provide a better understanding of the factors impacting residential energy consumption and intensity in North America (mainly the United States and Canada) by using similar methodology for analyses in both countries.

  3. Short-Term Energy Outlook Model Documentation: Macro Bridge Procedure to Update Regional Macroeconomic Forecasts with National Macroeconomic Forecasts

    Reports and Publications

    2010-01-01

    The Regional Short-Term Energy Model (RSTEM) uses macroeconomic variables such as income, employment, industrial production and consumer prices at both the national and regional1 levels as explanatory variables in the generation of the Short-Term Energy Outlook (STEO). This documentation explains how national macroeconomic forecasts are used to update regional macroeconomic forecasts through the RSTEM Macro Bridge procedure.

  4. DOETEIAO32l/2 Residential Energy Consumption Survey; Consumption

    Annual Energy Outlook

    purchase diaries from a subset of respondents comprising a Household Transportation Panel and is reported separately. * Wood used for heating. Although wood consumption data...

  5. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update

    (million square feet) Energy Intensity for Sum of Major Fuels (thousand Btu square foot) New England Middle Atlantic East North Central New England Middle Atlantic East North...

  6. Energy Information Administration - Commercial Energy Consumption...

    Annual Energy Outlook

    Using Electricity (million square feet) Electricity Energy Intensity (kWhsquare foot) New England Middle Atlantic East North Central New England Middle Atlantic East North...

  7. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update

    Natural Gas (million square feet) Natural Gas Energy Intensity (cubic feetsquare foot) New England Middle Atlantic East North Central New England Middle Atlantic East North...

  8. Electrical energy consumption control apparatuses and electrical energy consumption control methods

    DOEpatents

    Hammerstrom, Donald J.

    2012-09-04

    Electrical energy consumption control apparatuses and electrical energy consumption control methods are described. According to one aspect, an electrical energy consumption control apparatus includes processing circuitry configured to receive a signal which is indicative of current of electrical energy which is consumed by a plurality of loads at a site, to compare the signal which is indicative of current of electrical energy which is consumed by the plurality of loads at the site with a desired substantially sinusoidal waveform of current of electrical energy which is received at the site from an electrical power system, and to use the comparison to control an amount of the electrical energy which is consumed by at least one of the loads of the site.

  9. Housing characteristics, 1987: Residential Energy Consumption Survey

    SciTech Connect

    Not Available

    1989-05-26

    This report is the first of a series of reports based on data from the 1987 RECS. The 1987 RECS is the seventh in the series of national surveys of households and their energy suppliers. These surveys provide baseline information on how households in the United States use energy. A cross section of housing types such as single-family detached homes, townhouses, large and small apartment buildings, condominiums, and mobile homes were included in the survey. Data from the RECS and a companion survey, the Residential Transportation Energy Consumption Survey (RTECS), are available to the public in published reports such as this one and on public use tapes. 10 figs., 69 tabs.

  10. Energy Information Administration - Commercial Energy Consumption...

    Annual Energy Outlook

    Q 16.4 19.1 Buildings without Cooling ... Q 8 4 3,308 1,832 1,241 5.7 4.4 2.9 Water-Heating Energy Sources Electricity ... 51 216...

  11. User-needs study for the 1992 Commercial Buildings Energy Consumption Survey. [Energy Consumption Series

    SciTech Connect

    Not Available

    1992-09-01

    The Commercial Buildings Energy Consumption Survey (CBECS) that is conducted by the Energy Information Administration (EIA) is the primary source of energy data for commercial buildings in the United States. The survey began in 1979 and has subsequently been conducted in 1983, 1986, and 1989. The next survey will cover energy consumption during the year 1992. The building characteristic data will be collected between August 1992 and early December 1992. Requests for energy consumption data are mailed to the energy suppliers in January 1993, with data due by March 1993. Before each survey is sent into the field, the data users' needs are thoroughly assessed. The purpose of this report is to document the findings of that user-needs assessment for the 1992 survey.

  12. OpenEI Community - energy data + forecasting

    OpenEI (Open Energy Information) [EERE & EIA]

  13. DOE Releases Latest Report on Energy Savings Forecast of Solid-State Lighting

    Energy.gov [DOE]

    DOE has published a new report forecasting the energy savings of LED white-light sources compared with conventional white-light sources. The sixth iteration of the Energy Savings Forecast of Solid...

  14. Solar Forecast Improvement Project | Department of Energy

    Energy Saver

    Energy Systems Integration » Solar Energy Grid Integration Systems-Advanced Concepts Solar Energy Grid Integration Systems-Advanced Concepts On September 1, 2011, DOE announced $25.9 million to fund eight solar projects that are targeting ways to develop power electronics and build smarter, more interactive systems and components so that solar energy can be integrated into the electric power distribution and transmission grid at higher levels. Part of the SunShot Systems Integration

  15. Household energy consumption and expenditures, 1990. [Contains Glossary

    SciTech Connect

    Not Available

    1993-03-02

    This report, Household Energy Consumption and Expenditures 1990, is based upon data from the 1990 Residential Energy Consumption Survey (RECS). Focusing on energy end-use consumption and expenditures of households, the 1990 RECS is the eighth in a series conducted since 1978 by the Energy Information Administration (EIA). Over 5,000 households were surveyed, providing information on their housing units, housing characteristics, energy consumption and expenditures, stock of energy-consuming appliances, and energy-related behavior. The information provided represents the characteristics and energy consumption of 94 million households nationwide.

  16. Energy Intensity Indicators: Transportation Energy Consumption

    Energy.gov [DOE]

    This section contains an overview of the aggregate transportation sector, combining both passenger and freight segments of this sector. The specific energy intensity indicators for passenger and freight can be obtained from the links, passenger transportation, or freight transportation. For further detail within the transportation sector, download the appropriate Trend Data worksheet containing detailed data and graphics for specific transportation modes.

  17. International Energy Outlook 2016-Industrial sector energy consumption -

    Gasoline and Diesel Fuel Update

    Energy Information Administration 7. Industrial sector energy consumption print version Overview The industrial sector uses more delivered energy [294] than any other end-use sector, consuming about 54% of the world's total delivered energy. The industrial sector can be categorized by three distinct industry types: energy-intensive manufacturing, nonenergy-intensive manufacturing, and nonmanufacturing (Table 7-1). The mix and intensity of fuels consumed in the industrial sector vary across

  18. Trends in Commercial Buildings--Energy Sources Consumption Tables

    Energy Information Administration (EIA) (indexed site)

    ** estimates adjusted to match the 1995 CBECS definition of target population Energy Information Administration Commercial Buildings Energy Consumption Survey Table 2....

  19. Manufacturing Energy Consumption Survey (MECS) - Data - U.S....

    Energy Information Administration (EIA) (indexed site)

    Data Methodology & Forms 2006 Data Tables Manufacturing Energy Consumption Survey (MECS) - Data - U.S. Energy Information Administration (EIA) Revision notice (November 2009): ...

  20. Power to the Plug: An Introduction to Energy, Electricity, Consumption...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Grades: All Topics: Biomass, Wind Energy, Hydropower, Solar, Geothermal Owner: The NEED Project Power to the Plug: An Introduction to Energy, Electricity, Consumption, and...

  1. Commercial Buildings Energy Consumption Survey 2003 - Detailed Tables

    Reports and Publications

    2008-01-01

    The tables contain information about energy consumption and expenditures in U.S. commercial buildings and information about energy-related characteristics of these buildings.

  2. Fossil Fuel-Generated Energy Consumption Reduction for New Federal...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Buildings Fossil Fuel-Generated Energy Consumption Reduction for New Federal Buildings and Major Renovations of Federal Buildings Document details Fossil Fuel-Generated Energy ...

  3. Review of Wind Energy Forecasting Methods for Modeling Ramping Events

    SciTech Connect

    Wharton, S; Lundquist, J K; Marjanovic, N; Williams, J L; Rhodes, M; Chow, T K; Maxwell, R

    2011-03-28

    Tall onshore wind turbines, with hub heights between 80 m and 100 m, can extract large amounts of energy from the atmosphere since they generally encounter higher wind speeds, but they face challenges given the complexity of boundary layer flows. This complexity of the lowest layers of the atmosphere, where wind turbines reside, has made conventional modeling efforts less than ideal. To meet the nation's goal of increasing wind power into the U.S. electrical grid, the accuracy of wind power forecasts must be improved. In this report, the Lawrence Livermore National Laboratory, in collaboration with the University of Colorado at Boulder, University of California at Berkeley, and Colorado School of Mines, evaluates innovative approaches to forecasting sudden changes in wind speed or 'ramping events' at an onshore, multimegawatt wind farm. The forecast simulations are compared to observations of wind speed and direction from tall meteorological towers and a remote-sensing Sound Detection and Ranging (SODAR) instrument. Ramping events, i.e., sudden increases or decreases in wind speed and hence, power generated by a turbine, are especially problematic for wind farm operators. Sudden changes in wind speed or direction can lead to large power generation differences across a wind farm and are very difficult to predict with current forecasting tools. Here, we quantify the ability of three models, mesoscale WRF, WRF-LES, and PF.WRF, which vary in sophistication and required user expertise, to predict three ramping events at a North American wind farm.

  4. Weather forecast-based optimization of integrated energy systems.

    SciTech Connect

    Zavala, V. M.; Constantinescu, E. M.; Krause, T.; Anitescu, M.

    2009-03-01

    In this work, we establish an on-line optimization framework to exploit detailed weather forecast information in the operation of integrated energy systems, such as buildings and photovoltaic/wind hybrid systems. We first discuss how the use of traditional reactive operation strategies that neglect the future evolution of the ambient conditions can translate in high operating costs. To overcome this problem, we propose the use of a supervisory dynamic optimization strategy that can lead to more proactive and cost-effective operations. The strategy is based on the solution of a receding-horizon stochastic dynamic optimization problem. This permits the direct incorporation of economic objectives, statistical forecast information, and operational constraints. To obtain the weather forecast information, we employ a state-of-the-art forecasting model initialized with real meteorological data. The statistical ambient information is obtained from a set of realizations generated by the weather model executed in an operational setting. We present proof-of-concept simulation studies to demonstrate that the proposed framework can lead to significant savings (more than 18% reduction) in operating costs.

  5. Commercial Buildings Energy Consumption and Expenditures 1992...

    Energy Information Administration (EIA) (indexed site)

    1992 Consumption and Expenditures 1992 Consumption & Expenditures Overview Full Report Tables National estimates of electricity, natural gas, fuel oil, and district heat...

  6. LED Lighting Forecast | Department of Energy

    Energy Saver

    Research & Development » Technology Application R&D » LED Lighting Facts LED Lighting Facts LED lighting facts - A Program of the U.S. DOE DOE's LED Lighting Facts® program showcases LED products for general illumination from manufacturers who commit to testing products and reporting performance results according to industry standards. For lighting buyers, designers, and energy efficiency programs, the program provides information essential to evaluating SSL products. Central to the

  7. PIA - Form EIA-475 A/G Residential Energy Consumption Survey...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Form EIA-475 AG Residential Energy Consumption Survey PIA - Form EIA-475 AG Residential Energy Consumption Survey PIA - Form EIA-475 AG Residential Energy Consumption Survey PIA ...

  8. Residential Energy Consumption Survey (RECS) - Analysis & Projections -

    Gasoline and Diesel Fuel Update

    U.S. Energy Information Administration (EIA) RECS data show decreased energy consumption per household RECS 2009 - Release date: June 6, 2012 Total United States energy consumption in homes has remained relatively stable for many years as increased energy efficiency has offset the increase in the number and average size of housing units, according to the newly released data from the Residential Energy Consumption Survey (RECS). The average household consumed 90 million British thermal units

  9. User-needs study for the 1993 residential energy consumption survey

    SciTech Connect

    Not Available

    1993-09-24

    During 1992, the Energy Information Administration (EIA) conducted a user-needs study for the 1993 Residential Energy Consumption Survey (RECS). Every 3 years, the RECS collects information on energy consumption and expenditures for various classes of households and residential buildings. The RECS is the only source of such information within EIA, and one of only a few sources of such information anywhere. EIA sent letters to more than 750 persons, received responses from 56, and held 15 meetings with users. Written responses were also solicited by notices published in the April 14, 1992 Federal Register and in several energy-related publications. To ensure that the 1993 RECS meets current information needs, EIA made a specific effort to get input from policy makers and persons needing data for forecasting efforts. These particular needs relate mainly to development of the National Energy Modeling System and new energy legislation being considered at the time of the user needs survey.

  10. Beyond "Partly Sunny": A Better Solar Forecast | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    "Partly Sunny": A Better Solar Forecast Beyond "Partly Sunny": A Better Solar Forecast December 7, 2012 - 10:00am Addthis The Energy Department is investing in better solar forecasting techniques to improve the reliability and stability of solar power plants during periods of cloud coverage. | Photo by Dennis Schroeder/NREL. The Energy Department is investing in better solar forecasting techniques to improve the reliability and stability of solar power plants during periods

  11. Residential Lighting End-Use Consumption | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Information Resources » Publications » Market Studies » Residential Lighting End-Use Consumption Residential Lighting End-Use Consumption The U.S. DOE Residential Lighting End-Use Consumption Study aims to improve the understanding of lighting energy usage in U.S. residential dwellings using a regional estimation framework. The framework 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)

  12. Impact of Extended Daylight Saving Time on National Energy Consumption,

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Report to Congress | Department of Energy Report to Congress Impact of Extended Daylight Saving Time on National Energy Consumption, Report to Congress This report presents the detailed results, data, and analytical methods used in the DOE Report to Congress on the impacts of Extended Daylight Saving Time on the U.S. national energy consumption. Report to Congress (285 KB) More Documents & Publications Impact of Extended Daylight Saving Time on National Energy Consumption, Technical

  13. Commercial Buildings Energy Consumption Survey (CBECS) - How Was Energy

    Gasoline and Diesel Fuel Update

    Usage Information Collected in the 2012 CBECS? Energy Usage Information Collected in the 2012 CBECS? CBECS 2012 - Release date: March 18, 2016 The Commercial Buildings Energy Consumption Survey (CBECS) project cycle spans at least four years, beginning with development of the sample frame and survey questionnaire and ending with release of data to the public. This set of three methodology documents provides details about each of the three major stages of the 2012 CBECS survey process. * How

  14. Energy for 500 Million Homes: Drivers and Outlook for Residential Energy Consumption in China

    SciTech Connect

    Zhou, Nan; McNeil, Michael A.; Levine, Mark

    2009-06-01

    China's rapid economic expansion has propelled it to the rank of the largest energy consuming nation in the world, with energy demand growth continuing at a pace commensurate with its economic growth. The urban population is expected to grow by 20 million every year, accompanied by construction of 2 billion square meters of buildings every year through 2020. Thus residential energy use is very likely to continue its very rapid growth. Understanding the underlying drivers of this growth helps to identify the key areas to analyze energy efficiency potential, appropriate policies to reduce energy use, as well as to understand future energy in the building sector. This paper provides a detailed, bottom-up analysis of residential building energy consumption in China using data from a wide variety of sources and a modelling effort that relies on a very detailed characterization of China's energy demand. It assesses the current energy situation with consideration of end use, intensity, and efficiency etc, and forecast the future outlook for the critical period extending to 2020, based on assumptions of likely patterns of economic activity, availability of energy services, technology improvement and energy intensities. From this analysis, we can conclude that Chinese residential energy consumption will more than double by 2020, from 6.6 EJ in 2000 to 15.9 EJ in 2020. This increase will be driven primarily by urbanization, in combination with increases in living standards. In the urban and higher income Chinese households of the future, most major appliances will be common, and heated and cooled areas will grow on average. These shifts will offset the relatively modest efficiency gains expected according to current government plans and policies already in place. Therefore, levelling and reduction of growth in residential energy demand in China will require a new set of more aggressive efficiency policies.

  15. Residential Energy Consumption Survey (RECS) - U.S. Energy Information

    Gasoline and Diesel Fuel Update

    Administration (EIA) ‹ Consumption & Efficiency Residential Energy Consumption Survey (RECS) Glossary › FAQS › Overview Data 2009 2005 2001 1997 1993 Previous Analysis & Projections RECS Terminology A B C D E F G H I J K L M N O P Q R S T U V W XYZ A Account Classification: The method in which suppliers of electricity, natural gas, or fuel oil classify and bill their customers. Commonly used account classifications are "Commercial," "Industrial,"

  16. Manufacturing-Industrial Energy Consumption Survey(MECS) Historical...

    Energy Information Administration (EIA) (indexed site)

    reports, data tables and questionnaires Released: May 2008 The Manufacturing Energy Consumption Survey (MECS) is a periodic national sample survey devoted to measuring...

  17. Impact of Extended Daylight Saving Time on National Energy Consumption...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Report to Congress Impact of Extended Daylight Saving Time on National Energy Consumption, Report to Congress This report presents the detailed results, data, and analytical ...

  18. Commercial Buildings Energy Consumption Survey (CBECS) - U.S...

    Gasoline and Diesel Fuel Update

    Relationship of CBECS Coverage to EIA Supply Surveys The primary purpose of the CBECS is to collect accurate statistics of energy consumption by individual buildings. EIA also ...

  19. Comparison of Real World Energy Consumption to Models and DOE...

    Energy.gov [DOE] (indexed site)

    It first identifies and prioritizes the appliances to be evaluated. Then, the study determines whether real world energy consumption differed substantially from predictions and ...

  20. Fossil Fuel-Generated Energy Consumption Reduction for New Federal...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Buildings OIRA Comparison Document Fossil Fuel-Generated Energy Consumption Reduction for New Federal Buildings and Major Renovations of Federal Buildings OIRA Comparison Document ...

  1. Impact of Extended Daylight Saving Time on National Energy Consumption...

    Office of Environmental Management (EM)

    Technical Documentation Impact of Extended Daylight Saving Time on National Energy Consumption, Technical Documentation This report presents the detailed results, data, and ...

  2. Commercial Buildings Energy Consumption and Expenditures 1995...

    Energy Information Administration (EIA) (indexed site)

    fuel oil, and district heat consumption and expenditures for commercial buildings by building characteristics. Previous Page Arrow Separater Bar File Last Modified: January 29,...

  3. Commercial Buildings Energy Consumption Survey (CBECS) - U.S. Energy

    Gasoline and Diesel Fuel Update

    Information Administration (EIA) Building Type Definitions In the Commercial Buildings Energy Consumption Survey (CBECS), buildings are classified according to principal activity, which is the primary business, commerce, or function carried on within each building. Buildings used for more than one of the activities described below are assigned to the activity occupying the most floorspace. A building assigned to a particular principal activity category may be used for other activities in a

  4. Energy Savings Forecast of Solid-State Lighting in General Illuminatio...

    Energy Saver

    (1.54 MB) More Documents & Publications Energy Savings Potential of Solid-State Lighting in General Illumination Applications - Report 2016 SSL Forecast Report LED ADOPTION REPORT

  5. Residential Energy Consumption Survey (RECS) - Analysis & Projections -

    Gasoline and Diesel Fuel Update

    U.S. Energy Information Administration (EIA) How does EIA estimate energy consumption and end uses in U.S. homes? RECS 2009 - Release date: March 28, 2011 EIA administers the Residential Energy Consumption Survey (RECS) to a nationally representative sample of housing units. Specially trained interviewers collect energy characteristics on the housing unit, usage patterns, and household demographics. This information is combined with data from energy suppliers to these homes to estimate

  6. Buildings Energy Data Book: 4.4 Legislation Affecting Energy Consumption of Federal Buildings and Facilities

    Buildings Energy Data Book

    1 Energy Policy Act of 2005, Provisions Affecting Energy Consumption in Federal Buildings Source(s): Energy Management Requirements - Amended reduction goals set by the National Energy Conservation Policy Act, and requires increasing percentage reductions in energy consumption through FY 2015, with a final energy consumption reduction goal of 20 percent savings in FY 2015, as compared to the baseline energy consumption of Federal buildings in FY 2003. (These goals were superseded by Section 431

  7. Energy consumption series: Development of the 1991 Manufacturing Energy Consumption Survey

    SciTech Connect

    Not Available

    1992-05-18

    The implementation and results of the proceedings concerning the Energy Information Administration assessment of the Manufacturing Energy Consumption Survey (MECS) are documented in this report. The text and Appendices C, D, and E summarize the background of the MECS data system, the events that led to the MECS redesign, the major issues address during the review process, and the eventual 1991 MECS design that resulted. For many readers, the most useful part of the report may be Appendices A and B, which contain overall summaries of the users' groups and the industrial roundtables. These appendices capture the rationale for additional data needs as provided by the users. Also, they are a rich source of information on how manufacturers deal with energy use day-to-day, how they have addressed the need for energy efficiency improvement in the past, and the opportunities and problems associated with future efforts to improve efficiency. (VC)

  8. Energy consumption series: Development of the 1991 Manufacturing Energy Consumption Survey

    SciTech Connect

    Not Available

    1992-05-18

    The implementation and results of the proceedings concerning the Energy Information Administration assessment of the Manufacturing Energy Consumption Survey (MECS) are documented in this report. The text and Appendices C, D, and E summarize the background of the MECS data system, the events that led to the MECS redesign, the major issues address during the review process, and the eventual 1991 MECS design that resulted. For many readers, the most useful part of the report may be Appendices A and B, which contain overall summaries of the users` groups and the industrial roundtables. These appendices capture the rationale for additional data needs as provided by the users. Also, they are a rich source of information on how manufacturers deal with energy use day-to-day, how they have addressed the need for energy efficiency improvement in the past, and the opportunities and problems associated with future efforts to improve efficiency. (VC)

  9. Manufacturing Energy Consumption Survey (MECS) - Data - U.S....

    Energy Information Administration (EIA) (indexed site)

    Data Methodology & Forms + EXPAND ALL Consumption of Energy for All Purposes (First Use) Values SIC RSE Number of Establishments by First Use of Energy for All Purposes (Fuel and ...

  10. Manufacturing Energy Consumption Survey (MECS) - Data - U.S....

    Energy Information Administration (EIA) (indexed site)

    Data Methodology & Forms all tables + EXPAND ALL Consumption of Energy for All Purposes ... Table 1.4 Number of Establishments Using Energy Consumed for All Purpose XLSPDF Table 1.5 ...

  11. Manufacturing Energy Consumption Survey (MECS) - Data - U.S....

    Energy Information Administration (EIA) (indexed site)

    Data Methodology & Forms + EXPAND ALL Consumption of Energy for All Purposes (First Use) ... XLS PDF Table 1.4 Number of Establishments Using Energy Consumed for All Purpose XLS PDF ...

  12. Estimates of U.S. Biomass Energy Consumption 1992

    Reports and Publications

    1994-01-01

    This report is the seventh in a series of publications developed by the Energy Information Administration (EIA) to quantify the biomass derived primary energy used by the U.S. economy. It presents estimates of 1991 and 1992 consumption.

  13. ANL Software Improves Wind Power Forecasting | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    ANL Software Improves Wind Power Forecasting ANL Software Improves Wind Power Forecasting May 1, 2012 - 3:19pm Addthis This is an excerpt from the Second Quarter 2012 edition of the Wind Program R&D Newsletter. Since 2008, Argonne National Laboratory and INESC TEC (formerly INESC Porto) have conducted a research project to improve wind power forecasting and better use of forecasting in electricity markets. One of the main results from the project is ARGUS PRIMA (PRediction Intelligent

  14. " Column: Energy-Consumption Ratios;"

    Energy Information Administration (EIA) (indexed site)

    3 Consumption Ratios of Fuel, 2002;" " Level: National Data; " " Row: Values of Shipments within NAICS Codes;" " Column: Energy-Consumption Ratios;" " Unit: Varies." " "," ",,,"Consumption"," " " "," ",,"Consumption","per Dollar" " "," ","Consumption","per Dollar","of Value","RSE" "NAICS",,"per

  15. " Column: Energy-Consumption Ratios;"

    Energy Information Administration (EIA) (indexed site)

    3 Consumption Ratios of Fuel, 2006;" " Level: National Data; " " Row: Values of Shipments within NAICS Codes;" " Column: Energy-Consumption Ratios;" " Unit: Varies." ,,,,"Consumption" ,,,"Consumption","per Dollar" ,,"Consumption","per Dollar","of Value" "NAICS",,"per Employee","of Value Added","of Shipments" "Code(a)","Economic

  16. Commercial Buildings Energy Consumption Survey (CBECS) - U.S. Energy

    Gasoline and Diesel Fuel Update

    Information Administration (EIA) CBECS Terminology NOTE: This glossary is specific to the 1999, 2003 and 2012Commercial Buildings Energy Consumption Surveys (CBECS). CBECS glossaries for prior years can be found in the appendices of past CBECS reports. A B C D E F G H I J K L M N O P Q R S T U V W X Y Z Account Classification: The method in which suppliers of electricity, natural gas, or fuel oil classify and bill their customers. Commonly used account classifications are

  17. Manufacturing Energy Consumption Survey (MECS) - Analysis & Projection...

    Energy Information Administration (EIA) (indexed site)

    Residential - RECS Transportation DOE Uses MECS Data Manufacturing Energy and Carbon Footprints Associated Analysis Manufacturing Energy Sankey Diagrams Manufacturing Energy Flows ...

  18. Impact of Extended Daylight Saving Time on National Energy Consumption,

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Technical Documentation | Department of Energy Technical Documentation Impact of Extended Daylight Saving Time on National Energy Consumption, Technical Documentation This report presents the detailed results, data, and analytical methods used in the DOE Report to Congress on the impacts of Extended Daylight Saving Time on the national energy consumption in the United States. Technical Documentation for Report to Congress (3.65 MB) More Documents & Publications Impact of Extended

  19. Commercial Buildings Energy Consumption Survey (CBECS) - Analysis &

    Gasoline and Diesel Fuel Update

    Projections - U.S. Energy Information Administration (EIA) 2012 CBECS Preliminary Results What is a commercial building? The CBECS includes buildings greater than 1,000 square feet that devote more than half of their floorspace to activity that is neither residential, manufacturing, industrial, nor agricultural. When will energy consumption estimates be available? Energy consumption and expenditures data will be available beginning in spring 2015. CBECS data collection is currently in its

  20. Energy Consumption Series: Assessment of energy use in multibuilding facilities

    SciTech Connect

    Not Available

    1993-08-01

    This study originally had two primary objectives: (1) to improve EIA`s estimates of district heat consumption for commercial buildings in the CBECS sample that lacked individual metering and (2) to provide a basis for estimating primary fuel consumption by central plants serving commercial buildings. These objectives were expanded to include additional questions relating to these central plants. Background information is provided on the CBECS and on district heating and cooling, which is the most important type of energy-related service provided by multibuilding facilities with central physical plants. Chapters 2 and 3 present data results on multibuilding facilities from the 1989 CBECS and the pilot Facility Survey. Chapter 2 presents the characteristics of multibuilding facilities and the individual buildings located on these facilities. Chapter 3 provides estimates of energy inputs and outputs of multibuilding facilities with central physical plants. Chapter 4 assesses the quality of the pilot Facility Survey and includes recommendations for future work in this area. The appendices provide more detailed information on the Facility Survey itself, in particular the limitations on the use of these results. Appendix B, ``Data Quality``, provides detailed information relating to the limitations of the data and the conclusions presented in this report. As a pilot study, the 1989 Facility Survey has some serious flaws and limitations which are recognized in this report.

  1. Fact #792: August 12, 2013 Energy Consumption by Sector and Energy Source, 1982 and 2012

    Office of Energy Efficiency and Renewable Energy (EERE)

    In the last 30 years, overall energy consumption has grown by about 22 quadrillion Btu. The share of energy consumption by the transportation sector has seen modest growth in that time – from about...

  2. Fact #792: August 12, 2013 Energy Consumption by Sector and Energy...

    Energy.gov [DOE] (indexed site)

    In the last 30 years, overall energy consumption has grown by about 22 quadrillion Btu. The share of energy consumption by the transportation sector has seen modest growth in that ...

  3. Residential energy consumption survey: consumption and expenditures, April 1982-March 1983. Part 1, national data

    SciTech Connect

    Thompson, W.

    1984-11-01

    This report presents data on the US consumption and expenditures for residential use of natural gas, electricity, fuel oil or kerosene, and liquefied petroleum gas (LPG) from April 1982 through March 1983. Data on the consumption of wood for this period are also presented. The consumption and expenditures data are based on actual household bills, obtained, with the permission of the household. from the companies supplying energy to the household. Data on wood consumption are based on respondent recall of the amount of wood burned during the winter and are subject to memory errors and other reporting errors described in the report. These data come from the 1982 Residential Energy Consumption Survey (RECS), the fifth in a series of comparable surveys beginning in 1978. The 1982 survey is the first survey to include, as part of its sample, a portion of the same households interviewed in the 1980 survey. A separate report is planned to report these longitudinal data. This summary gives the highlights of a comparison of the findings for the 5 years of RECS data. The data cover all types of housing units in the 50 states and the District of Columbia including single-family units, apartments, and mobile homes. For households with indirect energy costs, such as costs that are included in the rent or paid by third parties, the sonsumption and expenditures data are estimated and included in the figures reported here. The average household consumption of natural gas, electricity, fuel oil or kerosene, and LPG dropped in 1982 from the previous year, hitting a 5-year low since the first Residential Energy Consumption Survey (RECS) was conducted in 1978. The average consumption was 103 (+-3) million Btu per household in 1982, down from 114 (+-) million Btu in 1981. The weather was the main contributing factor. 8 figures, 46 tables.

  4. Wind Energy Forecasting: A Collaboration of the National Center for Atmospheric Research (NCAR) and Xcel Energy

    SciTech Connect

    Parks, K.; Wan, Y. H.; Wiener, G.; Liu, Y.

    2011-10-01

    The focus of this report is the wind forecasting system developed during this contract period with results of performance through the end of 2010. The report is intentionally high-level, with technical details disseminated at various conferences and academic papers. At the end of 2010, Xcel Energy managed the output of 3372 megawatts of installed wind energy. The wind plants span three operating companies1, serving customers in eight states2, and three market structures3. The great majority of the wind energy is contracted through power purchase agreements (PPAs). The remainder is utility owned, Qualifying Facilities (QF), distributed resources (i.e., 'behind the meter'), or merchant entities within Xcel Energy's Balancing Authority footprints. Regardless of the contractual or ownership arrangements, the output of the wind energy is balanced by Xcel Energy's generation resources that include fossil, nuclear, and hydro based facilities that are owned or contracted via PPAs. These facilities are committed and dispatched or bid into day-ahead and real-time markets by Xcel Energy's Commercial Operations department. Wind energy complicates the short and long-term planning goals of least-cost, reliable operations. Due to the uncertainty of wind energy production, inherent suboptimal commitment and dispatch associated with imperfect wind forecasts drives up costs. For example, a gas combined cycle unit may be turned on, or committed, in anticipation of low winds. The reality is winds stayed high, forcing this unit and others to run, or be dispatched, to sub-optimal loading positions. In addition, commitment decisions are frequently irreversible due to minimum up and down time constraints. That is, a dispatcher lives with inefficient decisions made in prior periods. In general, uncertainty contributes to conservative operations - committing more units and keeping them on longer than may have been necessary for purposes of maintaining reliability. The downside is costs are

  5. Commercial Buildings Energy Consumption and Expenditures 1992...

    Energy Information Administration (EIA) (indexed site)

    with the national average of 81 thousand Btu per square foot), while buildings using solar energy or passive solar features used the major energy sources more intensively...

  6. Commercial Buildings Energy Consumption and Expenditures 1992

    Energy Information Administration (EIA) (indexed site)

    schedules and the number of workers across all shifts as well as the main shift. * Energy Management Characteristics - Energy management questions were expanded to ask whether...

  7. Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types, Notice of Data Availability

    Energy.gov [DOE]

    Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types, Notice of Data Availability

  8. New York: Weatherizing Westbeth Reduces Energy Consumption

    Energy.gov [DOE]

    Project provides energy savings and the improved health and safety of the residents within the building.

  9. Impact of Extended Daylight Saving Time on national energy consumption

    SciTech Connect

    Belzer, David B.; Hadley, Stanton W.; Chin, Shih -Miao

    2008-10-01

    This report presents the detailed results, data, and analytical methods used in the DOE Report to Congress on the impacts of Extended Daylight Saving Time on the U.S. national energy consumption.

  10. Impact of Extended Daylight Saving Time on national energy consumption

    SciTech Connect

    Belzer, David B.; Hadley, Stanton W.; Chin, Shih -Miao

    2008-10-01

    This report presents the detailed results, data, and analytical methods used in the DOE Report to Congress on the impacts of Extended Daylight Saving Time on the national energy consumption.

  11. New Water Booster Pump System Reduces Energy Consumption by 80...

    Energy.gov [DOE] (indexed site)

    As a result, the company reduced pumping system energy consumption by 80 percent (225,100 kWh per year), saving an annual 11,255 in pumping costs. With a capital investment of ...

  12. Smart Meters Help Balance Energy Consumption at Solar Decathlon

    Office of Energy Efficiency and Renewable Energy (EERE)

    Clouds, rain, thunderstorms… at Solar Decathlon Village? Oh my, you may say. But less-than-ideal weather conditions are no match for this year's teams, thanks to smart grid technology that is helping them monitor their energy consumption.

  13. New Water Booster Pump System Reduces Energy Consumption by 80...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    This case study outlines how General Motors (GM) developed a highly efficient pumping ... As a result, the company reduced pumping system energy consumption by 80 percent (225,100 ...

  14. Issues in International Energy Consumption Analysis: Electricity Usage in

    Energy Information Administration (EIA) (indexed site)

    India's Housing Sector - Energy Information Administration Canadian Energy Demand Electricity Usage in India's Housing Sector SERIES: Issues in International Energy Consumption Analysis Canadian Energy Demand Release date: June 2, 2015 The residential sector is one of the main end-use sectors in Canada accounting for 16.7% of total end-use site energy consumption in 2009 (computed from NRCan 2012. pp, 4-5). In this year, the residential sector accounted for 54.5% of buildings total site

  15. Assessment of Vehicle Sizing, Energy Consumption and Cost through Large

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Scale Simulation of Advanced Vehicle Technologies | Argonne National Laboratory Assessment of Vehicle Sizing, Energy Consumption and Cost through Large Scale Simulation of Advanced Vehicle Technologies Title Assessment of Vehicle Sizing, Energy Consumption and Cost through Large Scale Simulation of Advanced Vehicle Technologies Publication Type Report Year of Publication 2016 Authors Moawad, A, Kim, N, Shidore, N, Rousseau, A Institution Argonne National Laboratory City Argonne, IL USA

  16. Commercial Buildings Energy Consumption and Expenditures 1992

    Energy Information Administration (EIA) (indexed site)

    at the national level as well as State level in several EIA reports, including State Energy Data Report (SEDR) and the Monthly Energy Review (MER). When comparing the CBECS totals...

  17. Commercial Buildings Energy Consumption and Expenditures 1992

    Energy Information Administration (EIA) (indexed site)

    in CBECS. In addition, the same customer may be classified differently by each of its energy suppliers. Activities with Large Amounts of Hot Water: One of the energy-related space...

  18. Delivered Energy Consumption Projections by Industry in the Annual Energy Outlook 2002

    Reports and Publications

    2002-01-01

    This paper presents delivered energy consumption and intensity projections for the industries included in the industrial sector of the National Energy Modeling System.

  19. Energy Department Announces $2.5 Million to Improve Wind Forecasting |

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Department of Energy Improve Wind Forecasting Energy Department Announces $2.5 Million to Improve Wind Forecasting January 8, 2015 - 12:00pm Addthis The Energy Department today announced $2.5 million for a new project to research the atmospheric processes that generate wind in mountain-valley regions. This in-depth research, conducted by Vaisala of Louisville, Colorado, will be used to improve the wind industry's weather models for short-term wind forecasts, especially for those issued less

  20. Manufacturing Energy Consumption Survey (MECS) - Analysis & Projection...

    Gasoline and Diesel Fuel Update

    iron and steel, paper, wood products, and food, as well as less energy-intensive industries such as textiles, leather, apparel, furniture, machinery, and electrical equipment. ...

  1. Commercial Buildings Energy Consumption and Expenditures 1992

    Energy Information Administration (EIA) (indexed site)

    the sponsor the government, utility or sponsored in-house. Energy Management and Control System Heating or cooling system monitored or controlled by a computerized building...

  2. DOE/EIA-0318/1 Nonresidential Buildings Energy Consumption Survey...

    Energy Information Administration (EIA) (indexed site)

    Nonresidential Buildings Energy Consumption Survey: 1979 Consumption and Expenditures D Part I: Natural Gas and Electricity March 1983 Energy Information Administration ...

  3. Table 1.3 Primary Energy Consumption Estimates by Source, 1949...

    Gasoline and Diesel Fuel Update

    ... hydroelectric power, geothermal, solar thermal, photovoltaic, and wind. ... Notes: * See "Primary Energy Consumption" in Glossary. * See Table E1 for estimated energy consumption ...

  4. Electricity in US energy consumption. [Percentages for 1973 to 1982

    SciTech Connect

    Studness, C.M.

    1984-09-13

    The share of US energy consumption devoted to electric generation rose sharply again in 1983. Of 70.573 quadrillion Btu consumed nationally last year, 35.4% or 24.975 quadrillion Btu were used for electric generation. This represented an increase from 34.3% in 1982. Significantly, the share of the nation's energy consumption accounted for by electric generation has risen just as rapidly during the ten years since the Arab oil embargo in 1973 as it did during the decade leading up to the embargo. Electricity's share of energy consumption rose 7.3 percentage points from only 19.5% in 1963 to 26.8% in 1973 and another 8.6 percentage points during the last ten years to 35.4% in 1983. Moreover, electricity's share of energy consumption has grown in each of the ten years since the embargo. The nation's energy consumption actually fell 0.4% in 1983, and it declined 4.9% or roughly 0.4% per year during 1973 to 1983. By contrast, energy consumed in electric generation rose 2.9% last year and grew 2.3% per year during the last decade.

  5. Energy Forecasting Framework and Emissions Consensus Tool (EFFECT...

    OpenEI (Open Energy Information) [EERE & EIA]

    Tool (EFFECT) EFFECT is an open, Excel-based modeling tool used to forecast greenhouse gas emissions from a range of development scenarios at the regional and national levels....

  6. Current Status and Future Scenarios of Residential Building Energy Consumption in China

    SciTech Connect

    Zhou, Nan; Nishida, Masaru; Gao, Weijun

    2008-12-01

    China's rapid economic expansion has propelled it into the ranks of the largest energy consuming nation in the world, with energy demand growth continuing at a pace commensurate with its economic growth. Even though the rapid growth is largely attributable to heavy industry, this in turn is driven by rapid urbanization process, by construction materials and equipment produced for use in buildings. Residential energy is mostly used in urban areas, where rising incomes have allowed acquisition of home appliances, as well as increased use of heating in southern China. The urban population is expected to grow by 20 million every year, accompanied by construction of 2 billion square meters of buildings every year through 2020. Thus residential energy use is very likely to continue its very rapid growth. Understanding the underlying drivers of this growth helps to identify the key areas to analyze energy efficiency potential, appropriate policies to reduce energy use, as well as to understand future energy in the building sector. This paper provides a detailed, bottom-up analysis of residential building energy consumption in China using data from a wide variety of sources and a modeling effort that relies on a very detailed characterization of China's energy demand. It assesses the current energy situation with consideration of end use, intensity, and efficiency etc, and forecast the future outlook for the critical period extending to 2020, based on assumptions of likely patterns of economic activity, availability of energy services, technology improvement and energy intensities.

  7. New York: Weatherizing Westbeth Reduces Energy Consumption |...

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    ... 517.8 Million in Weatherization Funding and Energy Efficiency Grants for New York One Sky Homes, San Jose, CA, Custom Builder, Grand Award Winner. | California prides itself on ...

  8. Residential Energy Consumption Survey: Housing Characteristics...

    Gasoline and Diesel Fuel Update

    either air or liquid as the working fluid. It does not refer :<: passive collection of solar thermal energy. Fuel Oil Paid by Household: The household paid directly to the fuel...

  9. Energy Savings Forecast of Solid-State Lighting in General Illumination Applications

    Office of Energy Efficiency and Renewable Energy (EERE)

    Report forecasting the U.S. energy savings of LED white-light sources compared to conventional white-light sources (i.e., incandescent, halogen, fluorescent, and high-intensity discharge) over the...

  10. "Table A48. Selected Energy Operating Ratios for Total Energy Consumption for"

    Energy Information Administration (EIA) (indexed site)

    8. Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Census Region, Census Division, and Economic" " Characteristics of the Establishment, 1994" ,,,"Consumption","Major" " "," ","Consumption","per Dollar","Byproducts(b)","Fuel Oil(c)"," " " ","Consumption","per Dollar","of

  11. "Table A50. Selected Energy Operating Ratios for Total Energy Consumption for"

    Energy Information Administration (EIA) (indexed site)

    0. Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Industry Group," " Selected Industries, and Economic Characteristics of the" " Establishment, 1991 (Continued)" ,,,,,"Major" ,,,"Consumption","Consumption per","Byproducts(c)","Fuel Oil(d)" ,,"Consumption","per Dollar","Dollar of Value","as a Percent

  12. Energy consumption series: Lighting in commercial buildings. [Contains glossary

    SciTech Connect

    Not Available

    1992-03-11

    Lighting represents a substantial fraction of commercial electricity consumption. A wide range of initiatives in the Department of Energy's (DOE) National Energy Strategy have focused on commercial lighting as a potential source of energy conservation. This report provides a statistical profile of commercial lighting, to examine the potential for lighting energy conservation in commercial buildings. The principal conclusion from this analysis is that energy use for lighting could be reduced by as much as a factor of four using currently available technology. The analysis is based primarily on the Energy Information Administration's (EIA) 1986 Commercial Buildings Energy Consumption Survey (CBECS). The more recent 1989 survey had less detail on lighting, for budget reasons. While changes have occurred in the commercial building stock since 1986, the relationships identified by this analysis are expected to remain generally valid. In addition, the analytic approach developed here can be applied to the data that will be collected in the 1992 CBECS.

  13. Solar energy conversion: Technological forecasting. (Latest citations from the Aerospace database). Published Search

    SciTech Connect

    Not Available

    1993-12-01

    The bibliography contains citations concerning current forecasting of Earth surface-bound solar energy conversion technology. Topics consider research, development and utilization of this technology in relation to electric power generation, heat pumps, bioconversion, process heat and the production of renewable gaseous, liquid, and solid fuels for industrial, commercial, and domestic applications. Some citations concern forecasts which compare solar technology with other energy technologies. (Contains 250 citations and includes a subject term index and title list.)

  14. Solar energy conversion: Technological forecasting. (Latest citations from the Aerospace database). Published Search

    SciTech Connect

    1995-01-01

    The bibliography contains citations concerning current forecasting of Earth surface-bound solar energy conversion technology. Topics consider research, development and utilization of this technology in relation to electric power generation, heat pumps, bioconversion, process heat and the production of renewable gaseous, liquid, and solid fuels for industrial, commercial, and domestic applications. Some citations concern forecasts which compare solar technology with other energy technologies. (Contains 250 citations and includes a subject term index and title list.)

  15. US industrial process heating energy consumption: 1985

    SciTech Connect

    McDermott, H.; Chapman, M.A.

    1988-02-01

    The objective of this report was to refine and update energy-use estimates for US industrial process heating based on categories defined in an earlier study sponsored by Gas Research Institute (GRI) (Report No. GRI--84/0187. 154 refs., 77 tabs.

  16. Select Results from the Energy Assessor Experiment in the 2012 Commercial Buildings Energy Consumption Survey

    Energy Information Administration (EIA) (indexed site)

    Select Results from the Energy Assessor Experiment in the 2012 Commercial Buildings Energy Consumption Survey December 2015 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | Select Results from the Energy Assessor Experiment in the 2012 Commercial Buildings Energy Consumption Survey i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the

  17. Residential Energy Consumption Survey (RECS) - Analysis & Projections -

    Gasoline and Diesel Fuel Update

    U.S. Energy Information Administration (EIA) Where does RECS square footage data come from? RECS 2009 - Release date: July 11, 2012 The size of a home is a fixed characteristic strongly associated with the amount of energy consumed within it, particularly for space heating, air conditioning, lighting, and other appliances. As a part of the Residential Energy Consumption Survey (RECS), trained interviewers measure the square footage of each housing unit. RECS square footage data allow

  18. Determinants of measured energy consumption in public housing

    SciTech Connect

    Greely, K.M.; Mills, E.; Goldman, C.A.; Ritschard, R.L. )

    1988-01-01

    In this study, the authors used a two-part methodology to analyze metered energy use patterns in 91 public housing projects. Their goal was to develop a technique that could be used by the U.S. Department of Housing and Urban Development (HUD) and public housing authorities (PHAs) to derive reasonable energy use guidelines for different segments of the public housing stock. In the authors' approach, actual energy use was first normalized to consumption in a year with ''typical'' weather and then used in a multiple regression analysis of different cross-sectional variables. The regression model explained 80% of the variation in energy use, with the type of account and the management practices of PHAs emerging as important explanatory factors. As compared to previous engineering estimates of public housing consumption, the projects in this study used 8% (per square foot) to 16% (per apartment) less fuel and electricity, but consumption was still significantly higher (43%) than that of privately owned multifamily housing. They conclude that this methodology could be used to help HUD and PHAs increase their understanding of energy use patterns and appropriate consumption levels in public housing.

  19. EIA Energy Efficiency-Table 1d. Nonfuel Consumption (Site Energy...

    Annual Energy Outlook

    d Page Last Modified: May 2010 Table 1d. Nonfuel Consumption (Site Energy) for Selected Industries, 1998, 2002, and 2006 (Trillion Btu) MECS Survey Years NAICS Subsector and...

  20. Analysis of federal incentives used to stimulate energy consumption

    SciTech Connect

    Cole, R.J.; Cone, B.W.; Emery, J.C.; Huelshoff, M.; Lenerz, D.E.; Marcus, A.; Morris, F.A.; Sheppard, W.J.; Sommers, P.

    1981-08-01

    The purpose of the analysis is to identify and quantify Federal incentives that have increased the consumption of coal, oil, natural gas, and electricity. The introductory chapter is intended as a device for presenting the policy questions about the incentives that can be used to stimulate desired levels of energy development. In the theoretical chapter federal incentives were identified for the consumption of energy as Federal government actions whose major intent or result is to stimulate energy consumption. The stimulus comes through changing values of variables included in energy demand functions, thereby inducing energy consumers to move along the function in the direction of greater quantity of energy demanded, or through inducing a shift of the function to a position where more energy will be demanded at a given price. The demand variables fall into one of six categories: price of the energy form, price of complements, price of substitutes, preferences, income, and technology. The government can provide such incentives using six different policy instruments: taxation, disbursements, requirements, nontraditional services, traditional services, and market activity. The four major energy forms were examined. Six energy-consuming sectors were examined: residential, commercial, industrial, agricultural, transportation, and public. Two types of analyses of incentive actions are presented in this volume. The generic chapter focused on actions taken in 1978 across all energy forms. The subsequent chapters traced the patterns of incentive actions, energy form by energy form, from the beginning of the 20th century, to the present. The summary chapter includes the results of the previous chapters presented by energy form, incentive type, and user group. Finally, the implications of these results for solar policy are presented in the last chapter. (MCW)

  1. A method for evaluating transport energy consumption in suburban areas

    SciTech Connect

    Marique, Anne-Francoise Reiter, Sigrid

    2012-02-15

    Urban sprawl is a major issue for sustainable development. It represents a significant contribution to energy consumption of a territory especially due to transportation requirements. However, transport energy consumption is rarely taken into account when the sustainability of suburban structures is studied. In this context, the paper presents a method to estimate transport energy consumption in residential suburban areas. The study aimed, on this basis, at highlighting the most efficient strategies needed to promote awareness and to give practical hints on how to reduce transport energy consumption linked to urban sprawl in existing and future suburban neighborhoods. The method uses data collected by using empirical surveys and GIS. An application of this method is presented concerning the comparison of four suburban districts located in Belgium to demonstrate the advantages of the approach. The influence of several parameters, such as distance to work places and services, use of public transport and performance of the vehicles, are then discussed to allow a range of different development situations to be explored. The results of the case studies highlight that traveled distances, and thus a good mix between activities at the living area scale, are of primordial importance for the energy performance, whereas means of transport used is only of little impact. Improving the performance of the vehicles and favoring home-work give also significant energy savings. The method can be used when planning new areas or retrofitting existing ones, as well as promoting more sustainable lifestyles regarding transport habits. - Highlights: Black-Right-Pointing-Pointer The method allows to assess transport energy consumption in suburban areas and highlight the best strategies to reduce it. Black-Right-Pointing-Pointer Home-to-work travels represent the most important part of calculated transport energy consumption. Black-Right-Pointing-Pointer Energy savings can be achieved by

  2. U.S. Department of Energy Workshop Report: Solar Resources and Forecasting

    SciTech Connect

    Stoffel, T.

    2012-06-01

    This report summarizes the technical presentations, outlines the core research recommendations, and augments the information of the Solar Resources and Forecasting Workshop held June 20-22, 2011, in Golden, Colorado. The workshop brought together notable specialists in atmospheric science, solar resource assessment, solar energy conversion, and various stakeholders from industry and academia to review recent developments and provide input for planning future research in solar resource characterization, including measurement, modeling, and forecasting.

  3. Final Report on California Regional Wind Energy Forecasting Project:Application of NARAC Wind Prediction System

    SciTech Connect

    Chin, H S

    2005-07-26

    Wind power is the fastest growing renewable energy technology and electric power source (AWEA, 2004a). This renewable energy has demonstrated its readiness to become a more significant contributor to the electricity supply in the western U.S. and help ease the power shortage (AWEA, 2000). The practical exercise of this alternative energy supply also showed its function in stabilizing electricity prices and reducing the emissions of pollution and greenhouse gases from other natural gas-fired power plants. According to the U.S. Department of Energy (DOE), the world's winds could theoretically supply the equivalent of 5800 quadrillion BTUs of energy each year, which is 15 times current world energy demand (AWEA, 2004b). Archer and Jacobson (2005) also reported an estimation of the global wind energy potential with the magnitude near half of DOE's quote. Wind energy has been widely used in Europe; it currently supplies 20% and 6% of Denmark's and Germany's electric power, respectively, while less than 1% of U.S. electricity is generated from wind (AWEA, 2004a). The production of wind energy in California ({approx}1.2% of total power) is slightly higher than the national average (CEC & EPRI, 2003). With the recently enacted Renewable Portfolio Standards calling for 20% of renewables in California's power generation mix by 2010, the growth of wind energy would become an important resource on the electricity network. Based on recent wind energy research (Roulston et al., 2003), accurate weather forecasting has been recognized as an important factor to further improve the wind energy forecast for effective power management. To this end, UC-Davis (UCD) and LLNL proposed a joint effort through the use of UCD's wind tunnel facility and LLNL's real-time weather forecasting capability to develop an improved regional wind energy forecasting system. The current effort of UC-Davis is aimed at developing a database of wind turbine power curves as a function of wind speed and

  4. Manufacturing Energy Consumption Survey (MECS) - Analysis & Projections -

    Gasoline and Diesel Fuel Update

    U.S. Energy Information Administration (EIA) Manufacturing Energy Consumption Survey (MECS) Glossary › FAQS › Overview Data 2010 2006 2002 1998 1994 1991 Archive Analysis & Projections MECS Industry Analysis Briefs Steel Industry Analysis The steel industry is critical to the U.S. economy. Steel is the material of choice for many elements of construction, transportation, manufacturing, and a variety of consumer products. It is the backbone of bridges, skyscrapers, railroads,

  5. Building and occupant characteristics as determinants of residential energy consumption

    SciTech Connect

    Nieves, L.A.; Nieves, A.L.

    1981-10-01

    The major goals of the research are to gain insight into the probable effects of building energy performance standards on energy consumption; to obtain observations of actual residential energy consumption that could affirm or disaffirm comsumption estimates of the DOE 2.0A simulation model; and to investigate home owner's conservation investments and home purchase decisions. The first chapter covers the investigation of determinants of household energy consumption. The presentation begins with the underlying economic theory and its implications, and continues with a description of the data collection procedures, the formulation of variables, and then of data analysis and findings. In the second chapter the assumptions and limitations of the energy use projections generated by the DOE 2.0A model are discussed. Actual electricity data for the houses are then compared with results of the simulation. The third chapter contains information regarding households' willingness to make energy conserving investments and their ranking of various conservation features. In the final chapter conclusions and recommendations are presented with an emphasis on the policy implications of this study. (MCW)

  6. Derived annual estimates of manufacturing energy consumption, 1974--1988

    SciTech Connect

    Not Available

    1992-08-05

    This report presents a complete series of annual estimates of purchased energy used by the manufacturing sector of the US economy, for the years 1974 to 1988. These estimates interpolate over gaps in the actual data collections, by deriving estimates for the missing years 1982--1984 and 1986--1987. For the purposes of this report, ``purchased`` energy is energy brought from offsite for use at manufacturing establishments, whether the energy is purchased from an energy vendor or procured from some other source. The actual data on purchased energy comes from two sources, the US Department of Commerce Bureau of the Census`s Annual Survey of Manufactures (ASM) and EIA`s Manufacturing Energy Consumption Survey (MECS). The ASM provides annual estimates for the years 1974 to 1981. However, in 1982 (and subsequent years) the scope of the ASM energy data was reduced to collect only electricity consumption and expenditures and total expenditures for other purchased energy. In 1985, EIA initiated the triennial MECS collecting complete energy data. The series equivalent to the ASM is referred to in the MECS as ``offsite-produced fuels.``

  7. Buildings Energy Data Book: 3.1 Commercial Sector Energy Consumption

    Buildings Energy Data Book

    0 2003 Commercial Primary Energy Consumption Intensities, by Principal Building Type Consumption Percent of Total | Consumption Percent of Total Building Type (thousand Btu/SF) Consumption | Building Type (thousand Btu/SF) Consumption Health Care 345.9 8% | Education 159.0 11% Inpatient 438.8 6% | Service 151.6 4% Outpatient 205.9 2% | Food Service 522.4 6% Food Sales 535.5 5% | Religious Worship 77.0 2% Lodging 193.1 7% | Public Order and Safety 221.1 2% Office 211.7 19% | Warehouse and Storage

  8. An analysis of residential energy consumption in a temperate climate

    SciTech Connect

    Clark, Y.Y.; Vincent, W.

    1987-06-01

    Electrical energy consumption data have been recorded for several hundred submetered residential structures in Middle Tennessee. All houses were constructed with a common energy package.'' Specifically, daily cooling usage data have been collected for 130 houses for the 1985 and 1986 cooling seasons, and monthly heating usage data for 186 houses have been recorded by occupant participation over a seven-year period. Cooling data have been analyzed using an SPSSx multiple regression analysis and results are compared to several cooling models. Heating, base, and total energy usage are also analyzed and regression correlation coefficients are determined as a function of several house parameters.

  9. Manufacturing Energy Consumption Survey (MECS) - U.S. Energy...

    Annual Energy Outlook

    Biomass: Organic nonfossil material of biological origin constituting a renewable energy ... It is commonly used as a fuel within the steel works. An energy source to produce heat ...

  10. Residential Energy Consumption Survey (RECS) - Data - U.S. Energy

    Energy Information Administration (EIA) (indexed site)

    Information Administration (EIA) 1997 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous Housing characteristics Consumption & expenditures Microdata Methodology Housing Characteristics Tables Table Titles (Released: February 2004) Entire Section Percents Tables: HC1 Housing Unit Characteristics, Million U.S. Households PDF PDF NOTE: As of 10/31/01, numbers in the "Housing Units" TABLES section for stub item: "Number of Floors in Apartment Buildings" were

  11. Residential Energy Consumption Survey (RECS) - Data - U.S. Energy

    Energy Information Administration (EIA) (indexed site)

    Information Administration (EIA) 5 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous Housing characteristics Consumption & expenditures Microdata Housing Characteristics Tables + EXPAND ALL Floorspace - Housing Characteristics PDF (all tables) Total Floorspace All, Heated, and Cooled Floorspace (HC1.1.1) PDF XLS Average Floorspace All Housing Units (HC1.1.2) PDF XLS Single Family and Mobile Homes (HC1.1.3) PDF XLS Apartments (HC1.1.4) PDF XLS Usage Indicators Heated Floorspace

  12. "Table A45. Selected Energy Operating Ratios for Total Energy Consumption"

    Energy Information Administration (EIA) (indexed site)

    5. Selected Energy Operating Ratios for Total Energy Consumption" " for Heat, Power, and Electricity Generation by Industry Group," " Selected Industries, and Value of Shipment Categories, 1994" ,,,,,"Major" ,,,"Consumption","Consumption per","Byproducts(c)","Fuel Oil(d)" ,,"Consumption","per Dollar","Dollar of Value","as a Percent","as a Percent","RSE"

  13. "Table A46. Selected Energy Operating Ratios for Total Energy Consumption"

    Energy Information Administration (EIA) (indexed site)

    Selected Energy Operating Ratios for Total Energy Consumption" " for Heat, Power, and Electricity Generation by Industry Group," " Selected Industries, and Employment Size Categories, 1994" ,,,,,"Major" ,,,"Consumption","Consumption per","Byproducts(c)","Fuel Oil(d)" ,,"Consumption","per Dollar","Dollar of Value","as a Percent","as a Percent","RSE"

  14. "Table A47. Selected Energy Operating Ratios for Total Energy Consumption for"

    Energy Information Administration (EIA) (indexed site)

    7. Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Census Region, Census Division, Industry Group, and" " Selected Industries, 1994" ,,,,,"Major" ,,,,"Consumption","Byproducts(b)" ,,,"Consumption","per Dollar","as a","Fuel Oil(c) as" ,,"Consumption","per Dollar","of Value","Percent of","a

  15. "Table A51. Selected Energy Operating Ratios for Total Energy Consumption for"

    Energy Information Administration (EIA) (indexed site)

    1. Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Census Region and Economic" " Characteristics of the Establishment, 1991 " ,,,,,"Major" ,,,"Consumption","Consumption per","Byproducts(c)","Fuel Oil(d)" ,,"Consumption","per Dollar","Dollar of Value","as a Percent","as a Percent","RSE"

  16. "Table A8. Selected Energy Operating Ratios for Total Energy Consumption for"

    Energy Information Administration (EIA) (indexed site)

    A8. Selected Energy Operating Ratios for Total Energy Consumption for" " Heat, Power, and Electricity Generation by Census Region, Industry Group, and" " Selected Industries, 1991" ,,,,,"Major" ,,,,"Consumption","Byproducts(b)" ,,,"Consumption","per Dollar","as a","Fuel Oil(c) as" ,,"Consumption","per Dollar","of Value","Percent of","a Percent

  17. Buildings Energy Data Book: 3.1 Commercial Sector Energy Consumption

    Buildings Energy Data Book

    1 2003 Commercial Delivered Energy Consumption Intensities, by Ownership of Unit (1) Ownership Nongovernment Owned 85.1 72% Owner-Occupied 87.3 35% Nonowner-Occupied 88.4 36% Government Owned 105.3 28% 100% Note(s): Source(s): Consumption (thousand Btu/SF) 1) Mall buildings are no longer included in most CBECs tables; therefore, some data is not directly comparable to past CBECs. EIA, 2003 Commercial Buildings Energy Consumption and Expenditures: Consumption and Expenditures Tables, June 2006,

  18. Buildings Energy Data Book: 3.1 Commercial Sector Energy Consumption

    Buildings Energy Data Book

    8 Commercial Delivered Energy Consumption Intensities, by Vintage Consumption per Year Constructed Square Foot (thousand Btu/SF) Prior to 1960 84.4 23% 1960 to 1969 91.5 12% 1970 to 1979 97.0 18% 1980 to 1989 100.0 19% 1990 to 1999 90.3 19% 2000 to 2003 81.6 8% Average 91.0 Source(s): EIA, 2003 Commercial Buildings Energy Consumption and Expenditures: Consumption and Expenditures Tables, Oct. 2006, Table C1a

  19. International Energy Outlook 2016-Buildings sector energy consumption -

    Gasoline and Diesel Fuel Update

    484(2016) I May 2016 International Energy Outlook 2016 ~ Independent Statistics & Ana[ysis e~ ~* a~ 1 U.S. ~~ergy. Information Administration Contacts The International Energy Outlook 2016 was prepared by the U.S. Energy Information Administration (EIA) under the direction of John Conti, Assistant Administrator for Energy Analysis (john.conti@eia.gov, 202-586-2222); Paul Holtberg, Team Leader, Analysis Integration Team (paul.holtberg@eia.gov, 202-586-1284); Jim Diefenderfer, Director, Office

  20. Residential Energy Consumption Survey (RECS) - U.S. Energy Information

    Gasoline and Diesel Fuel Update

    U.S. Energy Information Administration (EIA) State fact sheets on household energy use RECS 2009 - Release date: August 13, 2013 (Correction) The RECS gathers information through personal interviews with a nationwide sample of homes and energy suppliers. The 2009 survey was the largest RECS to date and the larger sample size allowed for the release of data for 16 individual states, in addition to national, regional, and division-level estimates. See a closer look at residential energy

  1. Residential Energy Consumption Survey (RECS) - Data - U.S. Energy

    Energy Information Administration (EIA) (indexed site)

    Information Administration (EIA) 9 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous Housing characteristics Consumption & expenditures Microdata Methodology Housing characteristics tables + EXPAND ALL Fuels used & end uses Preliminary release date: March 28, 2011 Final release date: May 6, 2013 ZIP (all tables) by Type of housing unit (HC1.1) XLS by Owner-renter (HC1.2) XLS by Year of construction (HC1.3) XLS by Number of household members (HC1.4) XLS by Household income

  2. Buildings Energy Data Book: 4.1 Federal Buildings Energy Consumption

    Buildings Energy Data Book

    1 FY 2007 Federal Primary Energy Consumption (Quadrillion Btu) Buildings and Facilities 0.88 Vehicles/Equipment 0.69 (mostly jet fuel and diesel) Total Federal Government Consumption 1.57 Source(s): DOE/FEMP, Annual Report to Congress on FEMP FY 2007, Jan. 2010, Table A-1, p. 90 for total consumption and Table A-7, p. 95 for vehicle and equipment operations

  3. Residential Energy Consumption Survey (RECS) - Analysis & Projections -

    Gasoline and Diesel Fuel Update

    U.S. Energy Information Administration (EIA) Air conditioning in nearly 100 million U.S. homes RECS 2009 - Release date: August 19, 2011 line chart:air conditioning in U.S. figure dataExcept in the temperate climate regions along the West coast, air conditioners (AC) are now standard equipment in most U.S. homes (Figure 1). As recently as 1993, only 68% of all occupied housing units had AC. The latest results from the 2009 Residential Energy Consumption Survey (RECS) show that 87 percent of

  4. January 2013 Short-Term Energy Outlook (STEO)

    Gasoline and Diesel Fuel Update

    flat gasoline and jet fuel consumption. ... EIA expects the Henry Hub natural gas spot price... below this forecast. U.S. Energy Information Administration | Short-Term Energy ...

  5. Buildings Energy Data Book: 3.1 Commercial Sector Energy Consumption

    Buildings Energy Data Book

    3 Commercial Delivered and Primary Energy Consumption Intensities, by Year Percent Delivered Energy Consumption Primary Energy Consumption Floorspace Post-2000 Total Consumption per Total Consumption per (million SF) Floorspace (1) (10^15 Btu) SF (thousand Btu/SF) (10^15 Btu) SF (thousand Btu/SF) 1980 50.9 N.A. 5.99 117.7 10.57 207.7 1990 64.3 N.A. 6.74 104.8 13.30 207.0 2000 (2) 68.5 N.A. 8.20 119.7 17.15 250.3 2010 81.1 26% 8.74 107.7 18.22 224.6 2015 84.1 34% 8.88 105.5 18.19 216.2 2020 89.1

  6. Short and Long-Term Perspectives: The Impact on Low-Income Consumers of Forecasted Energy Price Increases in 2008 and A Cap & Trade Carbon Policy in 2030

    SciTech Connect

    Eisenberg, Joel Fred

    2008-01-01

    The Department of Energy's Energy Information Administration (EIA) recently released its short-term forecast for residential energy prices for the winter of 2007-2008. The forecast indicates increases in costs for low-income consumers in the year ahead, particularly for those using fuel oil to heat their homes. In the following analysis, the Oak Ridge National Laboratory has integrated the EIA price projections with the Residential Energy Consumption Survey (RECS) for 2001 in order to project the impact of these price increases on the nation's low-income households by primary heating fuel type, nationally and by Census Region. The report provides an update of bill estimates provided in a previous study, "The Impact Of Forecasted Energy Price Increases On Low-Income Consumers" (Eisenberg, 2005). The statistics are intended for use by policymakers in the Department of Energy's Weatherization Assistance Program and elsewhere who are trying to gauge the nature and severity of the problems that will be faced by eligible low-income households during the 2008 fiscal year. In addition to providing expenditure forecasts for the year immediately ahead, this analysis uses a similar methodology to give policy makers some insight into one of the major policy debates that will impact low-income energy expenditures well into the middle decades of this century and beyond. There is now considerable discussion of employing a cap-and-trade mechanism to first limit and then reduce U.S. emissions of carbon into the atmosphere in order to combat the long-range threat of human-induced climate change. The Energy Information Administration has provided an analysis of projected energy prices in the years 2020 and 2030 for one such cap-and-trade carbon reduction proposal that, when integrated with the RECS 2001 database, provides estimates of how low-income households will be impacted over the long term by such a carbon reduction policy.

  7. Controlled cooling of an electronic system for reduced energy consumption

    DOEpatents

    David, Milnes P.; Iyengar, Madhusudan K.; Schmidt, Roger R.

    2016-08-09

    Energy efficient control of a cooling system cooling an electronic system is provided. The control includes automatically determining at least one adjusted control setting for at least one adjustable cooling component of a cooling system cooling the electronic system. The automatically determining is based, at least in part, on power being consumed by the cooling system and temperature of a heat sink to which heat extracted by the cooling system is rejected. The automatically determining operates to reduce power consumption of the cooling system and/or the electronic system while ensuring that at least one targeted temperature associated with the cooling system or the electronic system is within a desired range. The automatically determining may be based, at least in part, on one or more experimentally obtained models relating the targeted temperature and power consumption of the one or more adjustable cooling components of the cooling system.

  8. " Row: Energy Sources;" " Column: Consumption Potential;"

    Energy Information Administration (EIA) (indexed site)

    Nonswitchable Minimum and Maximum Consumption, 2010; " " Level: National and Regional Data;" " Row: Energy Sources;" " Column: Consumption Potential;" " Unit: Physical Units." ,"Actual","Minimum","Maximum" "Energy Sources","Consumption","Consumption(a)","Consumption(b)" ,"Total United States" "Electricity Receipts(c) (million kilowatthours)",745247,727194,770790

  9. Residential Energy Consumption Survey (RECS) - U.S. Energy Information

    Gasoline and Diesel Fuel Update

    Administration (EIA) About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports Has your home been selected for the RECS? State fact sheets Arizona household graph See state fact sheets › 2009 RECS Features Heating and cooling no longer majority of U.S. home energy use March 7, 2013 Newer U.S. homes are 30% larger but consume about as much energy as older homes February 12, 2013 Where does RECS square footage data come from? July 11, 2012 RECS data show decreased energy

  10. Consumption

    Energy Information Administration (EIA) (indexed site)

    Using Natural Gas (million square feet)",,,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"North- east","Mid- west","South","West","North- east","Mid-...

  11. Consumption

    Energy Information Administration (EIA) (indexed site)

    Using Natural Gas (million square feet)",,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"West South Central","Moun- tain","Pacific","West South Central","Moun-...

  12. Consumption

    Energy Information Administration (EIA) (indexed site)

    (million square feet)",,,"Energy Intensity for Sum of Major Fuels (thousand Btu square foot)" ,"West North Central","South Atlantic","East South Central","West North...

  13. Consumption

    Energy Information Administration (EIA) (indexed site)

    (million square feet)",,,,"Energy Intensity for Sum of Major Fuels (thousand Btu square foot)" ,"North- east","Mid- west","South","West","North- east","Mid-...

  14. Consumption

    Energy Information Administration (EIA) (indexed site)

    Using Natural Gas (million square feet)",,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"New England","Middle Atlantic","East North Central","New England","Middle...

  15. Consumption

    Energy Information Administration (EIA) (indexed site)

    Using Natural Gas (million square feet)",,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"West North Central","South Atlantic","East South Central","West North...

  16. Consumption

    Energy Information Administration (EIA) (indexed site)

    (million square feet)",,,"Energy Intensity for Sum of Major Fuels (thousand Btu square foot)" ,"West South Central","Moun- tain","Pacific","West South Central","Moun-...

  17. Consumption

    Energy Information Administration (EIA) (indexed site)

    (million square feet)",,,,"Energy Intensity for Sum of Major Fuels (thousand Btusquare foot)" ,"North- east","Mid- west","South","West","North- east","Mid-...

  18. The Wind Forecast Improvement Project (WFIP). A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations -- the Northern Study Area

    SciTech Connect

    Finley, Cathy

    2014-04-30

    This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements in wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the

  19. Hawaii Energy Strategy: Program guide. [Contains special sections on analytical energy forecasting, renewable energy resource assessment, demand-side energy management, energy vulnerability assessment, and energy strategy integration

    SciTech Connect

    Not Available

    1992-09-01

    The Hawaii Energy Strategy program, or HES, is a set of seven projects which will produce an integrated energy strategy for the State of Hawaii. It will include a comprehensive energy vulnerability assessment with recommended courses of action to decrease Hawaii's energy vulnerability and to better prepare for an effective response to any energy emergency or supply disruption. The seven projects are designed to increase understanding of Hawaii's energy situation and to produce recommendations to achieve the State energy objectives of: Dependable, efficient, and economical state-wide energy systems capable of supporting the needs of the people, and increased energy self-sufficiency. The seven projects under the Hawaii Energy Strategy program include: Project 1: Develop Analytical Energy Forecasting Model for the State of Hawaii. Project 2: Fossil Energy Review and Analysis. Project 3: Renewable Energy Resource Assessment and Development Program. Project 4: Demand-Side Management Program. Project 5: Transportation Energy Strategy. Project 6: Energy Vulnerability Assessment Report and Contingency Planning. Project 7: Energy Strategy Integration and Evaluation System.

  20. Annual Energy Consumption Analysis Report for Richland Middle School

    SciTech Connect

    Liu, Bing

    2003-12-18

    Richland Middle School is a single story, 90,000 square feet new school located in Richland, WA. The design team proposed four HVAC system options to serve the building. The proposed HVAC systems are listed as following: (1) 4-pipe fan coil units served by electrical chiller and gas-fired boilers, (2) Ground-source closed water loop heat pumps with water loop heat pumps with boiler and cooling tower, and (3) VAV system served by electrical chiller and gas-fired boiler. This analysis estimates the annual energy consumptions and costs of each system option, in order to provide the design team with a reasonable basis for determining which system is most life-cycle cost effective. eQuest (version 3.37), a computer-based energy simulation program that uses the DOE-2 simulation engine, was used to estimate the annual energy costs.

  1. Trends in energy use in commercial buildings -- Sixteen years of EIA's commercial buildings energy consumption survey

    SciTech Connect

    Davis, J.; Swenson, A.

    1998-07-01

    The Commercial Buildings Energy Consumption Survey (CBECS) collects basic statistical information on energy consumption and energy-related characteristics of commercial buildings in the US. The first CBECS was conducted in 1979 and the most recent was completed in 1995. Over that period, the number of commercial bindings and total amount of floorspace increased, total consumption remained flat, and total energy intensity declined. By 1995, there were 4.6 million commercial buildings and 58.8 billion square feet of floorspace. The buildings consumed a total of 5.3 quadrillion Btu (site energy), with a total intensity of 90.5 thousand Btu per square foot per year. Electricity consumption exceeded natural gas consumption (2.6 quadrillion and 1.9 quadrillion Btu, respectively). In 1995, the two major users of energy were space heating (1.7 quadrillion Btu) and lighting (1.2 quadrillion Btu). Over the period 1979 to 1995, natural gas intensity declined from 71.4 thousand to 51.0 thousand Btu per square foot per year. Electricity intensity did not show a similar decline (44.2 thousand Btu per square foot in 1979 and 45.7 thousand Btu per square foot in 1995). Two types of commercial buildings, office buildings and mercantile and service buildings, were the largest consumers of energy in 1995 (2.0 quadrillion Btu, 38% of total consumption). Three building types, health care, food service, and food sales, had significantly higher energy intensities. Buildings constructed since 1970 accounted for half of total consumption and a majority (59%) of total electricity consumption.

  2. Buildings Energy Data Book: 4.4 Legislation Affecting Energy Consumption of Federal Buildings and Facilities

    Buildings Energy Data Book

    3 Energy Independence and Security Act of 2007, Provisions Affecting Energy Consumption in Federal Buildings Source(s): Standard Relating to Solar Hot Water - Requires new Federal buildings, or Federal buildings undergoing major renovations, to meet at least 30 percent of hot water demand through the use of solar hot water heaters, if cost-effective. [Section 523] Federally-Procured Appliances with Standby Power - Requires all Federal agencies to procure appliances with standby power consumption

  3. Understanding Energy Consumption, One Candy Corn at a Time | Department of

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Energy Understanding Energy Consumption, One Candy Corn at a Time Understanding Energy Consumption, One Candy Corn at a Time October 21, 2016 - 5:50pm Addthis Understanding Energy Consumption, One Candy Corn at a Time Daniel Wood Daniel Wood Data Visualization and Cartographic Specialist, Office of Public Affairs Click here to see the calculator in action! To commemorate National Energy Action Month, we're featuring some scarily effective ways to save energy at home. As cooler weather lurks

  4. Sample design for the residential energy consumption survey

    SciTech Connect

    Not Available

    1994-08-01

    The purpose of this report is to provide detailed information about the multistage area-probability sample design used for the Residential Energy Consumption Survey (RECS). It is intended as a technical report, for use by statisticians, to better understand the theory and procedures followed in the creation of the RECS sample frame. For a more cursory overview of the RECS sample design, refer to the appendix entitled ``How the Survey was Conducted,`` which is included in the statistical reports produced for each RECS survey year.

  5. Consumption

    Energy Information Administration (EIA) (indexed site)

    Using Natural Gas (million square feet)",,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"1959 or Before","1960 to 1989","1990 to 2003","1959 or Before","1960 to...

  6. Consumption

    Energy Information Administration (EIA) (indexed site)

    Using Natural Gas (million square feet)",,,,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"Zone 1","Zone 2","Zone 3","Zone 4","Zone 5","Zone 1","Zone 2","Zone 3","Zone...

  7. Consumption

    Energy Information Administration (EIA) (indexed site)

    (million square feet)",,,"Energy Intensity for Sum of Major Fuels (thousand Btusquare foot)" ,"1959 or Before","1960 to 1989","1990 to 2003","1959 or Before","1960 to...

  8. Consumption

    Energy Information Administration (EIA) (indexed site)

    (million square feet)",,,"Energy Intensity for Sum of Major Fuels (thousand Btusquare foot)" ,"1,001 to 10,000 Square Feet","10,001 to 100,000 Square Feet","Over 100,000...

  9. Consumption

    Energy Information Administration (EIA) (indexed site)

    Using Natural Gas (million square feet)",,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"1,001 to 10,000 Square Feet","10,001 to 100,000 Square Feet","Over 100,000...

  10. Consumption

    Energy Information Administration (EIA) (indexed site)

    (million square feet)",,,"Energy Intensity for Sum of Major Fuels (thousand Btu square foot)" ,"New England","Middle Atlantic","East North Central","New England","Middle...

  11. Consumption

    Energy Information Administration (EIA) (indexed site)

    (million square feet)",,,"Energy Intensity for Sum of Major Fuels (thousand Btu square foot)" ,"1,001 to 10,000 Square Feet","10,001 to 100,000 Square Feet","Over 100,000...

  12. Consumption

    Energy Information Administration (EIA) (indexed site)

    (million square feet)",,,,,"Energy Intensity for Sum of Major Fuels (thousand Btu square foot)" ,"Zone 1","Zone 2","Zone 3","Zone 4","Zone 5","Zone 1","Zone 2","Zone 3","Zone...

  13. Consumption

    Energy Information Administration (EIA) (indexed site)

    Using Natural Gas (million square feet)",,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"1959 or Before","1960 to 1989","1990 to 1999","1959 or Before","1960 to...

  14. Consumption

    Energy Information Administration (EIA) (indexed site)

    (million square feet)",,,"Energy Intensity for Sum of Major Fuels (thousand Btusquare foot)" ,"1959 or Before","1960 to 1989","1990 to 1999","1959 or Before","1960 to...

  15. TV Energy Consumption Trends and Energy-Efficiency Improvement Options

    SciTech Connect

    Park, Won Young; Phadke, Amol; Shah, Nihar; Letschert, Virginie

    2011-07-01

    The SEAD initiative aims to transform the global market by increasing the penetration of highly efficient equipment and appliances. SEAD is a government initiative whose activities and projects engage the private sector to realize the large global energy savings potential from improved appliance and equipment efficiency. SEAD seeks to enable high-level global action by informing the Clean Energy Ministerial dialogue as one of the initiatives in the Global Energy Efficiency Challenge. In keeping with its goal of achieving global energy savings through efficiency, SEAD was approved as a task within the International Partnership for Energy Efficiency Cooperation (IPEEC) in January 2010. SEAD partners work together in voluntary activities to: (1) ?raise the efficiency ceiling? by pulling super-efficient appliances and equipment into the market through cooperation on measures like incentives, procurement, awards, and research and development (R&D) investments; (2) ?raise the efficiency floor? by working together to bolster national or regional policies like minimum efficiency standards; and (3) ?strengthen the efficiency foundations? of programs by coordinating technical work to support these activities. Although not all SEAD partners may decide to participate in every SEAD activity, SEAD partners have agreed to engage actively in their particular areas of interest through commitment of financing, staff, consultant experts, and other resources. In addition, all SEAD partners are committed to share information, e.g., on implementation schedules for and the technical detail of minimum efficiency standards and other efficiency programs. Information collected and created through SEAD activities will be shared among all SEAD partners and, to the extent appropriate, with the global public.As of April 2011, the governments participating in SEAD are: Australia, Brazil, Canada, the European Commission, France, Germany, India, Japan, Korea, Mexico, Russia, South Africa, Sweden

  16. New Forecasting Tools Enhance Wind Energy Integration In Idaho and Oregon

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    New Forecasting Tools Enhance Wind Energy Integration in Idaho and Oregon Page 1 Under the American Recovery and Reinvestment Act of 2009, the U.S. Department of Energy and the electricity industry have jointly invested over $7.9 billion in 99 cost-shared Smart Grid Investment Grant projects to modernize the electric grid, strengthen cybersecurity, improve interoperability, and collect an unprecedented level of data on smart grid and customer operations. 1. Summary Idaho Power Company (IPC)

  17. Short-Term Energy Carbon Dioxide Emissions Forecasts August 2009

    Reports and Publications

    2009-01-01

    Supplement to the Short-Term Energy Outlook. Short-term projections for U.S. carbon dioxide emissions of the three fossil fuels: coal, natural gas, and petroleum.

  18. RECENT TRENDS IN EMERGING TRANSPORTATION FUELS AND ENERGY CONSUMPTION

    SciTech Connect

    Bunting, Bruce G

    2012-01-01

    Abundance of energy can be improved both by developing new sources of fuel and by improving efficiency of energy utilization, although we really need to pursue both paths to improve energy accessibility in the future. Currently, 2.7 billion people or 38% of the world s population do not have access to modern cooking fuel and depend on wood or dung and 1.4 billion people or 20% do not have access to electricity. It is estimated that correcting these deficiencies will require an investment of $36 billion dollars annually through 2030. In growing economies, energy use and economic growth are strongly linked, but energy use generally grows at a lower rate due to increased access to modern fuels and adaptation of modern, more efficient technology. Reducing environmental impacts of increased energy consumption such as global warming or regional emissions will require improved technology, renewable fuels, and CO2 reuse or sequestration. The increase in energy utilization will probably result in increased transportation fuel diversity as fuels are shaped by availability of local resources, world trade, and governmental, environmental, and economic policies. The purpose of this paper is to outline some of the recently emerging trends, but not to suggest winners. This paper will focus on liquid transportation fuels, which provide the highest energy density and best match with existing vehicles and infrastructure. Data is taken from a variety of US, European, and other sources without an attempt to normalize or combine the various data sources. Liquid transportation fuels can be derived from conventional hydrocarbon resources (crude oil), unconventional hydrocarbon resources (oil sands or oil shale), and biological feedstocks through a variety of biochemical or thermo chemical processes, or by converting natural gas or coal to liquids.

  19. Buildings Energy Data Book: 4.4 Legislation Affecting Energy Consumption of Federal Buildings and Facilities

    Buildings Energy Data Book

    2 Executive Order 13423, Provisions Affecting Energy Consumption in Federal Buildings Source(s): -- Requires Federal agencies to improve energy efficiency and reduce greenhouse gas emissions by either 3 percent annual reductions through FY 2015, or by 30 percent by 2015, as compared to FY 2003. -- Requires Federal agencies to obtain at least half of required renewable energy from new renewable sources. Executive Order 13423, Strengthening Federal Environmental, Energy, and Transportation

  20. Nonresidential buildings energy consumption survey: 1979 consumption and expenditures. Part 2. Steam, fuel oil, LPG, and all fuels

    SciTech Connect

    Patinkin, L.

    1983-12-01

    This report presents data on square footage and on total energy consumption and expenditures for commercial buildings in the contiguous United States. Also included are detailed consumption and expenditures tables for fuel oil or kerosene, liquid petroleum gas (LPG), and purchased steam. Commercial buildings include all nonresidential buildings with the exception of those where industrial activities occupy more of the total square footage than any other type of activity. 7 figures, 23 tables.

  1. Report Summary: Energy Savings Forecast of SSL in General Illumination

    Energy Saver

    No. U.S. Department of Eney Release Date: WR-B-95-06 Office of Inspector General May 5, 1995 Report on Audit of Construction of Protective Force Training Faciliti at the Pantex Plant This report can be obtained from the U.S. Department of Energy Office of Scientific and Technical Information P.O. Box 62 Oak Ridge, Tennessee 37831 S tPrined wth soy ink n recycled pper U.S. DEPARTMENT OF ENERGY OFFICE OF INSPECTOR GENERAL AUDIT OF CONSTRUCTION OF PROTECTIVE FORCE TRAINING FACILITIES AT THE PANTEX

  2. Comfort, Indoor Air Quality, and Energy Consumption in Low Energy Homes

    SciTech Connect

    Englemann, P.; Roth, K.; Tiefenbeck, V.

    2013-01-01

    This report documents the results of an in-depth evaluation of energy consumption and thermal comfort for two potential net zero-energy homes (NZEHs) in Massachusetts, as well as an indoor air quality (IAQ) evaluation performed in conjunction with Lawrence Berkeley National Laboratory (LBNL).

  3. Biodiesel Supply and Consumption in the Short-Term Energy Outlook

    Reports and Publications

    2009-01-01

    The historical biodiesel consumption data published in the Energy Information Administration's Monthly Energy Review March 2009 edition were revised to account for imports and exports. Table 10.4 of the Monthly Energy Review was expanded to display biodiesel imports, exports, stocks, stock change, and consumption. Similar revisions were made in the April 2009 edition of the Short-Term Energy Outlook (STEO).

  4. Short-Term Energy Outlook - U.S. Energy Information Administration...

    Annual Energy Outlook

    Data Figures Tables Custom Table Builder Real Prices Viewer Forecast Changes (PDF) Special ... Power Producer (IPP) consumption. c Renewable energy includes minor components of ...

  5. Webinar: Forecasting Wind Energy Costs and Cost Drivers | Department of

    Energy Saver

    | Department of Energy Assistance Program (WAP) Closeout Frequently Asked Questions Weatherization Assistance Program (WAP) Closeout Frequently Asked Questions This document provides a list of frequently asked questions in regards to the Weatherization Assistance Program (WAP) Closeout procedures. wap_closeout_faqs.pdf (379.35 KB) More Documents & Publications WPN 12-3: Closeout Procedures for Recovery Act Grants Under the Weatherization Assistance Program CLOSEOUT PROCEDURES FOR

  6. Table 16. Total Energy Consumption, Projected vs. Actual

    Energy Information Administration (EIA) (indexed site)

    Total Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",88.02,89.53,90.72,91.73,92.71,93.61,94.56,95.73,96.69,97.69,98.89,100,100.79,101.7,102.7,103.6,104.3,105.23 "AEO 1995",,89.21,89.98,90.57,91.91,92.98,93.84,94.61,95.3,96.19,97.18,98.38,99.37,100.3,101.2,102.1,102.9,103.88 "AEO

  7. Energy Savings Forecast of Solid-State Lighting in General Illumination Applications

    SciTech Connect

    none,

    2014-08-29

    With declining production costs and increasing technical capabilities, LED adoption has recently gained momentum in general illumination applications. This is a positive development for our energy infrastructure, as LEDs use significantly less electricity per lumen produced than many traditional lighting technologies. The U.S. Department of Energy’s Energy Savings Forecast of Solid-State Lighting in General Illumination Applications examines the expected market penetration and resulting energy savings of light-emitting diode, or LED, lamps and luminaires from today through 2030.

  8. End use energy consumption data base: transportation sector

    SciTech Connect

    Hooker, J.N.; Rose, A.B.; Greene, D.L.

    1980-02-01

    The transportation fuel and energy use estimates developed a Oak Ridge National Laboratory (ORNL) for the End Use Energy Consumption Data Base are documented. The total data base contains estimates of energy use in the United States broken down into many categories within all sectors of the economy: agriculture, mining, construction, manufacturing, commerce, the household, electric utilities, and transportation. The transportation data provided by ORNL generally cover each of the 10 years from 1967 through 1976 (occasionally 1977 and 1978), with omissions in some models. The estimtes are broken down by mode of transport, fuel, region and State, sector of the economy providing transportation, and by the use to which it is put, and, in the case of automobile and bus travel, by the income of the traveler. Fuel types include natural gas, motor and aviation gasoline, residual and diesel oil, liuqefied propane, liquefied butane, and naphtha- and kerosene-type jet engine fuels. Electricity use is also estimated. The mode, fuel, sector, and use categories themselves subsume one, two, or three levels of subcategories, resulting in a very detailed categorization and definitive accounting.

  9. Canada's Fuel Consumption Guide Website | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    URI: cleanenergysolutions.orgcontentcanadas-fuel-consumption-guide-websit Language: English Policies: Regulations Regulations: Fuel Efficiency Standards This website...

  10. Ocean thermal energy conversion: Historical highlights, status, and forecast

    SciTech Connect

    Dugger, G.L.; Avery, W.H.; Francis, E.J.; Richards, D.

    1983-07-01

    In 1881, d'Arsonval conceived the closed-Rankine-cycle ocean thermal energy conversion (OTEC) system in which a working fluid is vaporized by heat exchange with cold water drawn from a 700-1200 m depth. In 1930, Claude demonstrated an open-cycle process in Cuba. Surface water was flash-vaporized at 3 kPa to drive a turbine directly (no secondary working fluid) and then was condensed by direct contact with water drawn from a 700-m depth through a 1.6m-diam, 1.75-km-long cold-water pipe (CWP). From a delta T of 14/sup 0/C his undersized turbine generated 22 kW. In 1956 a French team designed a 3.5-MW (net) open-cycle plant for installation off Abidjan on the Ivory Coast of Africa and demonstrated the necessary CWP deployment. The at-sea demonstrations by Mini-OTEC and OTEC-1 and other recent advances in OTEC technology summarized herein represent great progress. All of the types of plants proposed for the DOE's PON program may be worthy of development; certainly work on a grazing plant is needed. Our estimates indicate that the U.S. goals established by Public Law 96-310 leading to 10 GW of OTEC power and energy product equivalents by 1999 are achievable, provided that adequate federal financial incentives are retained to assure the building of the first few plants.

  11. An Integrated Geovisual Analytics Framework for Analysis of Energy Consumption Data and Renewable Energy Potentials

    SciTech Connect

    Omitaomu, Olufemi A; Maness, Christopher S; Kramer, Ian S; Kodysh, Jeffrey B; Bhaduri, Budhendra L; Steed, Chad A; Karthik, Rajasekar; Nugent, Philip J; Myers, Aaron T

    2012-01-01

    We present an integrated geovisual analytics framework for utility consumers to interactively analyze and benchmark their energy consumption. The framework uses energy and property data already available with the utility companies and county governments respectively. The motivation for the developed framework is the need for citizens to go beyond the conventional utility bills in understanding the patterns in their energy consumption. There is also a need for citizens to go beyond one-time improvements that are often not monitored and measured over time. Some of the features of the framework include the ability for citizens to visualize their historical energy consumption data along with weather data in their location. The quantity of historical energy data available is significantly more than what is available from utility bills. An overlay of the weather data provides users with a visual correlation between weather patterns and their energy consumption patterns. Another feature of the framework is the ability for citizens to compare their consumption on an aggregated basis to that of their peers other citizens living in houses of similar size and age and within the same or different geographical boundaries, such as subdivision, zip code, or county. The users could also compare their consumption to others based on the size of their family and other attributes. This feature could help citizens determine if they are among the best in class . The framework can also be used by the utility companies to better understand their customers and to plan their services. To make the framework easily accessible, it is developed to be compatible with mobile consumer electronics devices.

  12. Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption

    Buildings Energy Data Book

    4 Ownership (1) Owned 54.9 104.5 40.3 78% Rented 77.4 71.7 28.4 22% Public Housing 75.7 62.7 28.7 2% Not Public Housing 77.7 73.0 28.4 19% 100% Note(s): Source(s): 1) Energy consumption per square foot was calculated using estimates of average heated floor space per household. According to the 2005 Residential Energy Consumption Survey (RECS), the average heated floor space per household in the U.S. was 1,618 square feet. Average total floor space, which includes garages, attics and unfinished

  13. Drivers of U.S. Household Energy Consumption, 1980-2009

    Energy Information Administration (EIA) (indexed site)

    Drivers of U.S. Household Energy Consumption, 1980-2009 February 2015 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy ...

  14. Potential for the Use of Energy Savings Performance Contracts to Reduce Energy Consumption and Provide Energy and Cost Savings in Non-Building Applications

    Energy.gov [DOE]

    Document provides information on the use of energy savings performance contracts to reduce energy consumption and provide energy and cost savings in non-building applications.

  15. Table 11.1 Carbon Dioxide Emissions From Energy Consumption by...

    Energy Information Administration (EIA) (indexed site)

    ... minus denaturant. 5Distillate fuel oil, excluding biodiesel. RRevised. PPreliminary. ... Notes: * Data are estimates for carbon dioxide emissions from energy consumption, ...

  16. Table 11.2e Carbon Dioxide Emissions From Energy Consumption...

    Energy Information Administration (EIA) (indexed site)

    ... from energy consumption. * See "Carbon Dioxide" in Glossary. * Totals may not equal sum of components due to independent rounding. 4Distillate fuel oil, excluding biodiesel. ...

  17. Table 11.2c Carbon Dioxide Emissions From Energy Consumption...

    Energy Information Administration (EIA) (indexed site)

    ... minus denaturant. 4Distillate fuel oil, excluding biodiesel. RRevised. PPreliminary. ... Notes: * Data are estimates for carbon dioxide emissions from energy consumption, ...

  18. Table 11.2a Carbon Dioxide Emissions From Energy Consumption...

    Energy Information Administration (EIA) (indexed site)

    ... from energy consumption. * See "Carbon Dioxide" in Glossary. * Totals may not equal sum of components due to independent rounding. 4Distillate fuel oil, excluding biodiesel. ...

  19. Table 11.2b Carbon Dioxide Emissions From Energy Consumption...

    Energy Information Administration (EIA) (indexed site)

    ... minus denaturant. 4Distillate fuel oil, excluding biodiesel. RRevised. PPreliminary. ... Notes: * Data are estimates for carbon dioxide emissions from energy consumption. * See ...

  20. Table A13. Total Consumption of Offsite-Produced Energy for...

    Energy Information Administration (EIA) (indexed site)

    ... Statistics Division, Form EIA-846, '1991" "Manufacturing Energy Consumption Survey,' and Bureau of the Census, Industry" "Division, data files for the '1991 Annual Survey of

  1. DOE/EIA-0272/S The National Interim Energy Consumption Survey...

    Energy Information Administration (EIA) (indexed site)

    Exploring the Variability in Energy Consumption, (DOEEIA-0272). A discussion on the theory behind the particular form of the models chosen and the choice of the independent...

  2. 3TIER Environmental Forecast Group Inc 3TIER | Open Energy Information

    OpenEI (Open Energy Information) [EERE & EIA]

    TIER Environmental Forecast Group Inc 3TIER Jump to: navigation, search Name: 3TIER Environmental Forecast Group Inc (3TIER) Place: Seattle, Washington Zip: 98121 Sector: Renewable...

  3. Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption

    Buildings Energy Data Book

    7 Range 10 4 48 Clothes Dryer 359 (2) 4 49 Water Heating Water Heater-Family of 4 40 64 (3) 26 294 Water Heater-Family of 2 40 32 (3) 12 140 Note(s): Source(s): 1) $1.139/therm. 2) Cycles/year. 3) Gallons/day. A.D. Little, EIA-Technology Forecast Updates - Residential and Commercial Building Technologies - Reference Case, Sept. 2, 1998, p. 30 for range and clothes dryer; LBNL, Energy Data Sourcebook for the U.S. Residential Sector, LBNL-40297, Sept. 1997, p. 62-67 for water heating; GAMA,

  4. Survey Consumption

    Annual Energy Outlook

    purchase diaries from a subset of respondents composing a Household Transportation Panel and is reported separately. Residential Energy Consumption Survey: Consumption and...

  5. Table 16. Total Energy Consumption, Projected vs. Actual Projected

    Energy Information Administration (EIA) (indexed site)

    Total Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 88.0 89.5 90.7 91.7 92.7 93.6 94.6 95.7 96.7 97.7 98.9 100.0 100.8 101.7 102.7 103.6 104.3 105.2 AEO 1995 89.2 90.0 90.6 91.9 93.0 93.8 94.6 95.3 96.2 97.2 98.4 99.4 100.3 101.2 102.1 102.9 103.9 AEO 1996 90.6 91.3 92.5 93.5 94.3 95.1 95.9 96.9 98.0 99.2 100.4 101.4 102.1 103.1 103.8 104.7 105.5 106.5 107.2

  6. Table 17. Total Delivered Residential Energy Consumption, Projected vs. Actual

    Energy Information Administration (EIA) (indexed site)

    Total Delivered Residential Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 10.3 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.4 10.5 10.5 10.5 10.5 10.5 10.6 10.6 AEO 1995 11.0 10.8 10.8 10.8 10.8 10.8 10.8 10.7 10.7 10.7 10.7 10.7 10.7 10.7 10.8 10.8 10.9 AEO 1996 10.4 10.7 10.7 10.7 10.8 10.8 10.9 10.9 11.0 11.2 11.2 11.3 11.4 11.5 11.6 11.7 11.8 12.0 12.1

  7. Table 18. Total Delivered Commercial Energy Consumption, Projected vs. Actual

    Energy Information Administration (EIA) (indexed site)

    Total Delivered Commercial Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 6.8 6.9 6.9 7.0 7.1 7.1 7.2 7.2 7.3 7.3 7.4 7.4 7.4 7.5 7.5 7.5 7.5 7.6 AEO 1995 6.9 6.9 7.0 7.0 7.0 7.1 7.1 7.1 7.1 7.1 7.2 7.2 7.2 7.2 7.3 7.3 7.3 AEO 1996 7.1 7.2 7.2 7.3 7.3 7.4 7.4 7.5 7.6 7.6 7.7 7.7 7.8 7.9 8.0 8.0 8.1 8.2 8.2 AEO 1997 7.4 7.4 7.4 7.5 7.5 7.6 7.7 7.7 7.8 7.8 7.9 7.9

  8. Table 19. Total Delivered Industrial Energy Consumption, Projected vs. Actual

    Energy Information Administration (EIA) (indexed site)

    Total Delivered Industrial Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 25.4 25.9 26.3 26.7 27.0 27.1 26.8 26.6 26.9 27.2 27.7 28.1 28.3 28.7 29.1 29.4 29.7 30.0 AEO 1995 26.2 26.3 26.5 27.0 27.3 26.9 26.6 26.8 27.1 27.5 27.9 28.2 28.4 28.7 29.0 29.3 29.6 AEO 1996 26.5 26.6 27.3 27.5 26.9 26.5 26.7 26.9 27.2 27.6 27.9 28.2 28.3 28.5 28.7 28.9 29.2 29.4 29.6

  9. Table 20. Total Delivered Transportation Energy Consumption, Projected vs. Actual

    Energy Information Administration (EIA) (indexed site)

    Total Delivered Transportation Energy Consumption, Projected vs. Actual Projected (quadrillion Btu) 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 AEO 1994 23.6 24.1 24.5 24.7 25.1 25.4 25.7 26.2 26.5 26.9 27.2 27.6 27.9 28.3 28.6 28.9 29.2 29.5 AEO 1995 23.3 24.0 24.2 24.7 25.1 25.5 25.9 26.2 26.5 26.9 27.3 27.7 28.0 28.3 28.5 28.7 28.9 AEO 1996 23.9 24.1 24.5 24.8 25.3 25.7 26.0 26.4 26.7 27.1 27.5 27.8 28.1 28.4 28.6 28.9 29.1 29.3

  10. Buildings Energy Data Book: 4.1 Federal Buildings Energy Consumption

    Buildings Energy Data Book

    2 FY 2007 Federal Building Energy Use Shares, by Fuel Type and Agency Site Primary | Primary | FY 2007 Fuel Type Percent Percent | Agency Percent | (10^15 Btu) Electricity 49.4% 77.3% | DOD 53.8% | Total Delivered Natural Gas 33.5% 14.9% | USPS 9.8% | Energy Consumption = 0.39 Fuel Oil 7.3% 3.3% | DOE 8.2% | Total Primary Coal 5.2% 2.3% | VA 6.4% | Energy Consumption = 0.88 Other 4.9% 2.2% | GSA 5.1% | Total 100% 100% | Other 16.8% | Total 100% Note(s): Source(s): See Table 2.3.1 for floorspace.

  11. Buildings Energy Data Book: 4.1 Federal Buildings Energy Consumption

    Buildings Energy Data Book

    3 Federal Building Delivered Energy Consumption Intensities, by Year (1) Year Year FY 1985 123.0 FY 1997 111.9 FY 1986 131.3 FY 1998 107.7 FY 1987 136.9 FY 1999 106.7 FY 1988 136.3 FY 2000 104.8 FY 1989 132.6 FY 2001 105.9 FY 1990 128.6 FY 2002 104.6 FY 1991 122.9 FY 2003 105.2 FY 1992 125.5 FY 2004 104.9 FY 1993 122.3 FY 2005 98.2 FY 1994 120.2 FY 2006 (2) 113.9 FY 1995 117.3 FY 2007 (3) 112.9 FY 1996 115.0 FY 2015 (4) 89.5 Note(s): Source(s): Consumption per Gross Consumption per Gross Square

  12. Notice of Intent to Issue Solar Forecasting 2 | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Solar Forecasting 2 Notice of Intent to Issue Solar Forecasting 2 Subprogram: Systems Integration Funding Number: DE-FOA-0001658 Funding Amount: $10,000,000 The SunShot Initiative intends to release a funding opportunity announcement (FOA) to support advancements in solar forecasting to enable higher penetration of solar power in the electric grid. The Solar Forecasting 2 FOA will focus on improving solar forecasting skills, especially during challenging conditions, such as partly cloudy weather

  13. EIA Energy Efficiency-Table 1a. Table 1a. Consumption of Site...

    Annual Energy Outlook

    a Page Last Modified: May 2010 Table 1a. Consumption of Energy (Site Energy) for All Purposes (First Use) for Selected Industries, 1998, 2002, and 2006 (Trillion Btu) MECS Survey...

  14. How can we compare or add up our energy consumption?

    Reports and Publications

    2012-01-01

    Energy in Brief article on the use of energy conversion factors to compare energy usage from different fuels.

  15. Table 2.10 Commercial Buildings Energy Consumption and Expenditure Indicators, Selected Years, 1979-2003

    Energy Information Administration (EIA) (indexed site)

    0 Commercial Buildings Energy Consumption and Expenditure Indicators, Selected Years, 1979-2003 Energy Source and Year Building Characteristics Energy Consumption Energy Expenditures Number of Buildings Total Square Feet Square Feet per Building Total Per Building Per Square Foot Per Employee Total Per Building Per Square Foot Per Million Btu Thousands Millions Thousands Trillion Btu Million Btu Thousand Btu Million Btu Million Dollars 1 Thousand Dollars 1 Dollars 1 Dollars 1 Major Sources 2

  16. Comparison of Real World Energy Consumption to Models and DOE Test

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Procedures | Department of Energy Comparison of Real World Energy Consumption to Models and DOE Test Procedures Comparison of Real World Energy Consumption to Models and DOE Test Procedures This study investigates the real-world energy performance of appliances and equipment as it compares with models and test procedures. The study looked to determine whether DOE and industry test procedures actually replicate real world conditions, whether performance degrades over time, and whether

  17. Novel Ultra-Low-Energy Consumption Ultrasonic Clothes Dryer | Department of

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Energy Novel Ultra-Low-Energy Consumption Ultrasonic Clothes Dryer Novel Ultra-Low-Energy Consumption Ultrasonic Clothes Dryer With support from the Energy Department's Building Technologies Office, Oak Ridge National Laboratory and GE Appliances are changing the way Americans do laundry with their ultrasonic drying technology that uses vibrations, not heat, to dry fabric. Oak Ridge National Lab's Ayyoub Momen demonstrates ultrasonic clothes dryer technology for David Danielson, Assistant

  18. Comparison of Real World Energy Consumption to Models and Department of Energy Test Procedures

    SciTech Connect

    Goetzler, William; Sutherland, Timothy; Kar, Rahul; Foley, Kevin

    2011-09-01

    This study investigated the real-world energy performance of appliances and equipment as it compared with models and test procedures. The study looked to determine whether the U.S. Department of Energy and industry test procedures actually replicate real world conditions, whether performance degrades over time, and whether installation patterns and procedures differ from the ideal procedures. The study first identified and prioritized appliances to be evaluated. Then, the study determined whether real world energy consumption differed substantially from predictions and also assessed whether performance degrades over time. Finally, the study recommended test procedure modifications and areas for future research.

  19. The Reality and Future Scenarios of Commercial Building Energy Consumption in China

    SciTech Connect

    Zhou, Nan; Lin, Jiang

    2007-08-01

    While China's 11th Five Year Plan called for a reduction of energy intensity by 2010, whether and how the energy consumption trend can be changed in a short time has been hotly debated. This research intends to evaluate the impact of a variety of scenarios of GDP growth, energy elasticity and energy efficiency improvement on energy consumption in commercial buildings in China using a detailed China End-use Energy Model. China's official energy statistics have limited information on energy demand by end use. This is a particularly pertinent issue for building energy consumption. The authors have applied reasoned judgments, based on experience of working on Chinese efficiency standards and energy related programs, to present a realistic interpretation of the current energy data. The bottom-up approach allows detailed consideration of end use intensity, equipment efficiency, etc., thus facilitating assessment of potential impacts of specific policy and technology changes on building energy use. The results suggest that: (1) commercial energy consumption in China's current statistics is underestimated by about 44%, and the fuel mix is misleading; (2) energy efficiency improvements will not be sufficient to offset the strong increase in end-use penetration and intensity in commercial buildings; (3) energy intensity (particularly electricity) in commercial buildings will increase; (4) different GDP growth and elasticity scenarios could lead to a wide range of floor area growth trajectories , and therefore, significantly impact energy consumption in commercial buildings.

  20. ,"Total Fuel Oil Consumption (trillion Btu)",,,,,"Fuel Oil Energy...

    Energy Information Administration (EIA) (indexed site)

    in this table do not include enclosed malls and strip malls. In the 1999 CBECS, total fuel oil consumption in malls was not statistically significant. (*)Value rounds to zero...

  1. ENERGY USE AND DOMESTIC HOT WATER CONSUMPTION Final Report

    Office of Scientific and Technical Information (OSTI)

    USE AND DOMESTIC HOT WATER CONSUMPTION Final Report Phase 1 Prepared for THE N E W YORK ... operating data on combined domestic hot water @HW) and heating systems to be used in ...

  2. Hydraulic HEV Fuel Consumption Potential | Department of Energy

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Hydraulic HEV Fuel Consumption Potential Hydraulic HEV Fuel Consumption Potential 2012 DOE Hydrogen and Fuel Cells Program and Vehicle Technologies Program Annual Merit Review and Peer Evaluation Meeting vss071_rousseau_2012_o.pdf (1.07 MB) More Documents & Publications Evaluation of Powertrain Options and Component Sizing for MD and HD Applications on Real World Drive Cycles Roadmap and Technical White Papers for 21st Century Truck Partnership Fuel Displacement & Cost Potential of CNG,

  3. Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption

    Buildings Energy Data Book

    1 Type (1) Single-Family: 55.4 106.6 39.4 80.5% Detached 55.0 108.4 39.8 73.9% Attached 60.5 89.3 36.1 6.6% Multi-Family: 78.3 64.1 29.7 14.9% 2 to 4 units 94.3 85.0 35.2 6.3% 5 or more units 69.8 54.4 26.7 8.6% Mobile Homes 74.6 70.4 28.5 4.6% All Housing Types 58.7 95.0 37.0 100% Note(s): Source(s): 1) Energy consumption per square foot was calculated using estimates of average heated floor space per household. According to the 2005 Residential Energy Consumption Survey (RECS), the average

  4. Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption

    Buildings Energy Data Book

    2 Year Built (1) Prior to 1950 74.5 114.9 46.8 24% 1950 to 1969 66.0 96.6 38.1 23% 1970 to 1979 59.4 83.4 33.5 15% 1980 to 1989 51.9 81.4 32.3 14% 1990 to 1999 48.2 94.4 33.7 16% 2000 to 2005 44.7 94.7 34.3 8% Average 58.7 95.0 40.0 Note(s): Source(s): 1) Energy consumption per square foot was calculated using estimates of average heated floor space per household. According to the 2005 Residential Energy Consumption Survey (RECS), the average heated floor space per household in the U.S. was

  5. Short-Term Energy Outlook Model Documentation: Coal Supply, Demand, and Prices

    Reports and Publications

    2016-01-01

    The coal module of the Short-Term Energy Outlook (STEO) model is designed to provide forecasts of U.S. production, consumption, imports, exports, inventories, and prices.

  6. Waste-to-Energy Biomass Digester with Decreased Water Consumption - Energy

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Innovation Portal Biomass and Biofuels Biomass and Biofuels Find More Like This Return to Search Waste-to-Energy Biomass Digester with Decreased Water Consumption Colorado State University Contact CSU About This Technology Publications: PDF Document Publication Preliminary Market Report (334 KB) PDF Document Publication Anaerobic Digester Summary (251 KB) Technology Marketing SummaryThe enormous amount of biomass waste created by animal feeding operations releases methane, a valuable fuel

  7. Commercial Buildings Energy Consumption Survey (CBECS) - Data - U.S. Energy

    Gasoline and Diesel Fuel Update

    Information Administration (EIA) What is an RSE? The estimates in the Commercial Buildings Energy Consumption Survey (CBECS) are based on data reported by representatives of a statistically-designed subset of the entire commercial building population in the United States, or a "sample." Consequently, the estimates differ from the true population values. However, the sample design permits us to estimate the sampling error in each value. It is important to understand: CBECS estimates

  8. Transportation Energy Futures: Combining Strategies for Deep Reductions in Energy Consumption and GHG Emissions (Brochure)

    SciTech Connect

    Not Available

    2013-03-01

    This fact sheet summarizes actions in the areas of light-duty vehicle, non-light-duty vehicle, fuel, and transportation demand that show promise for deep reductions in energy use. Energy efficient transportation strategies have the potential to simultaneously reduce oil consumption and greenhouse gas (GHG) emissions. The Transportation Energy Futures (TEF) project examined how the combination of multiple strategies could achieve deep reductions in GHG emissions and petroleum use on the order of 80%. Led by NREL, in collaboration with Argonne National Laboratory, the project's primary goal was to help inform domestic decisions about transportation energy strategies, priorities, and investments, with an emphasis on underexplored opportunities. TEF findings reveal three strategies with the potential to displace most transportation-related petroleum use and GHG emissions: 1) Stabilizing energy use in the transportation sector through efficiency and demand-side approaches. 2) Using additional advanced biofuels. 3) Expanding electric drivetrain technologies.

  9. Reduction in Energy Consumption & Variability in Steel Foundry Operations

    SciTech Connect

    Frank Peters

    2005-05-04

    large process variation. This indicates the need for ongoing monitoring of the process and system to quantify the effort being expended. A system to measure the grinding effort was investigated but did not prove to be successful. A weld wire counting system was shown to be very successful in tracking casting quality by monitoring the quantity of weld wire being expended on a per casting basis. Further use of such systems is highly recommended. The field studies showed that the visual inspection process for the casting surface was a potentially large source of process variation. Measurement system analysis studies were conducted at three steel casting producers. The tests measured the consistency of the inspectors in identifying the same surface anomalies. The repeatability (variation of the same operator inspecting the same casting) was found to be relatively consistent across the companies at about 60-70%. However, this is still are very large amount of variation. Reproducibility (variation of different operators inspecting the same casting) was worse, ranging between 20 to 80% at the three locations. This large amount of variation shows that there is a great opportunity for improvement. Falsely identifying anomalies for reworking will cause increased expense and energy consumption. This is particularly true if a weld repair and repeated heat treatment is required. However, not identifying an anomaly could also result in future rework processing, a customer return, or scrap. To help alleviate this problem, casting surface comparator plates were developed and distributed to the industry. These plates are very inexpensive which enables them to be provided to all those involved with casting surface quality, such as operators, inspectors, sales, and management.

  10. Crude oil and alternate energy production forecasts for the twenty-first century: The end of the hydrocarbon era

    SciTech Connect

    Edwards, J.D.

    1997-08-01

    Predictions of production rates and ultimate recovery of crude oil are needed for intelligent planning and timely action to ensure the continuous flow of energy required by the world`s increasing population and expanding economies. Crude oil will be able to supply increasing demand until peak world production is reached. The energy gap caused by declining conventional oil production must then be filled by expanding production of coal, heavy oil and oil shales, nuclear and hydroelectric power, and renewable energy sources (solar, wind, and geothermal). Declining oil production forecasts are based on current estimated ultimate recoverable conventional crude oil resources of 329 billion barrels for the United States and close to 3 trillion barrels for the world. Peak world crude oil production is forecast to occur in 2020 at 90 million barrels per day. Conventional crude oil production in the United States is forecast to terminate by about 2090, and world production will be close to exhaustion by 2100.

  11. The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations. The Southern Study Area, Final Report

    SciTech Connect

    Freedman, Jeffrey M.; Manobianco, John; Schroeder, John; Ancell, Brian; Brewster, Keith; Basu, Sukanta; Banunarayanan, Venkat; Hodge, Bri-Mathias; Flores, Isabel

    2014-04-30

    This Final Report presents a comprehensive description, findings, and conclusions for the Wind Forecast Improvement Project (WFIP) -- Southern Study Area (SSA) work led by AWS Truepower (AWST). This multi-year effort, sponsored by the Department of Energy (DOE) and National Oceanographic and Atmospheric Administration (NOAA), focused on improving short-term (15-minute - 6 hour) wind power production forecasts through the deployment of an enhanced observation network of surface and remote sensing instrumentation and the use of a state-of-the-art forecast modeling system. Key findings from the SSA modeling and forecast effort include: 1. The AWST WFIP modeling system produced an overall 10 - 20% improvement in wind power production forecasts over the existing Baseline system, especially during the first three forecast hours; 2. Improvements in ramp forecast skill, particularly for larger up and down ramps; 3. The AWST WFIP data denial experiments showed mixed results in the forecasts incorporating the experimental network instrumentation; however, ramp forecasts showed significant benefit from the additional observations, indicating that the enhanced observations were key to the model systems’ ability to capture phenomena responsible for producing large short-term excursions in power production; 4. The OU CAPS ARPS simulations showed that the additional WFIP instrument data had a small impact on their 3-km forecasts that lasted for the first 5-6 hours, and increasing the vertical model resolution in the boundary layer had a greater impact, also in the first 5 hours; and 5. The TTU simulations were inconclusive as to which assimilation scheme (3DVAR versus EnKF) provided better forecasts, and the additional observations resulted in some improvement to the forecasts in the first 1 - 3 hours.

  12. Power to the Plug: An Introduction to Energy, Electricity, Consumption, and Efficiency

    Education - Teach & Learn

    The NEED Project and the U.S. Department of Energy have collaborated to bring you this educational four-page guide to energy, electricity, consumption and efficiency. It includes, on the last page, a home energy survey to help you analyze your home energy use.

  13. Power to the Plug: An Introduction to Energy, Electricity, Consumption and Efficiency

    SciTech Connect

    DOE / EERE / NEED Project

    2011-06-07

    The NEED Project and the U.S. Department of Energy have collaborated to bring you this educational four-page guide to energy, electricity, consumption and efficiency. It includes, on the last page, a home energy survey to help you analyze your home energy use.

  14. A look at commercial buildings in 1995: Characteristics, energy consumption, and energy expenditures

    SciTech Connect

    1998-10-01

    The commercial sector consists of business establishments and other organizations that provide services. The sector includes service businesses, such as retail and wholesale stores, hotels and motels, restaurants, and hospitals, as well as a wide range of facilities that would not be considered commercial in a traditional economic sense, such as public schools, correctional institutions, and religious and fraternal organizations. Nearly all energy use in the commercial sector takes place in, or is associated with, the buildings that house these commercial activities. Analysis of the structures, activities, and equipment associated with different types of buildings is the clearest way to evaluate commercial sector energy use. The Commercial Buildings Energy Consumption Survey (CBECS) is a national-level sample survey of commercial buildings and their energy suppliers conducted quadrennially (previously triennially) by the Energy Information Administration (EIA). The target population for the 1995 CBECS consisted of all commercial buildings in the US with more than 1,000 square feet of floorspace. Decision makers, businesses, and other organizations that are concerned with the use of energy--building owners and managers, regulators, legislative bodies and executive agencies at all levels of government, utilities and other energy suppliers--are confronted with a buildings sector that is complex. Data on major characteristics (e.g., type of building, size, year constructed, location) collected from the buildings, along with the amount and types of energy the buildings consume, help answer fundamental questions about the use of energy in commercial buildings.

  15. Manufacturing Consumption of Energy 1994 - Derived measures of...

    Energy Information Administration (EIA) (indexed site)

    eialogo Calculation of MECS Energy Measures Reported energy values were used to construct several derived values, which, in turn, were used to prepare the estimates appearing in...

  16. Impact of Extended Daylight Saving Time on National Energy Consumption Report to Congress

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Impact of Extended Daylight Saving Time on National Energy Consumption Report to Congress Energy Policy Act of 2005, Section 110 October 2008 U.S. Department of Energy Energy Efficiency and Renewable Energy Acknowledgements The Department of Energy (DOE) acknowledges the important contributions made to this study by the principal investigators and primary authors-David B. Belzer, Ph.D (Pacific Northwest National Laboratory), Stanton W. Hadley (Oak Ridge National Laboratory), and Shih-Miao Chin,

  17. Household and environmental characteristics related to household energy-consumption change: A human ecological approach

    SciTech Connect

    Guerin, D.A.

    1988-01-01

    This study focused on the family household as an organism and on its interaction with the three environments of the human ecosystem (natural, behavioral, and constructed) as these influence energy consumption and energy-consumption change. A secondary statistical analysis of data from the US Department of Energy Residential Energy Consumption Surveys (RECS) was completed. The 1980 and 1983 RECS were used as the data base. Longitudinal data, including household, environmental, and energy-consumption measures, were available for over 800 households. The households were selected from a national sample of owner-occupied housing units surveyed in both years. Results showed a significant( p = <.05) relationship between the dependent-variable energy-consumption change and the predictor variables heating degree days, addition of insulation, addition of a wood-burning stove, year the housing unit was built, and weighted number of appliances. A significant (p = <.05) relationship was found between the criterion variable energy-consumption change and the discriminating variables of age of the head of the household, cooling degree days, heating degree days, year the housing unit was built, and number of stories in the housing unit.

  18. Impact of Extended Daylight Saving Time on national energy consumption: Report to Congress

    SciTech Connect

    None, None

    2008-10-01

    This report presents the detailed results, data, and analytical methods used in the DOE Report to Congress on the impacts of Extended Daylight Saving Time on the U.S. national energy consumption.

  19. EIA Energy Efficiency-Table 1b. Fuel Consumption for Selected...

    Gasoline and Diesel Fuel Update

    b Page Last Modified: May 2010 Table 1b. End Uses of Fuel Consumption (Site Energy) for Selected Industries, 1998, 2002, and 2006 (Trillion Btu) MECS Survey Years NAICS Subsector...

  20. EIA Energy Efficiency-Table 2b. Primary Fuel Consumption for...

    Gasoline and Diesel Fuel Update

    b Page Last Modified: May 2010 Table 2b. End Uses of Fuel Consumption (Primary 1 Energy) for Selected Industries, 1998, 2002, and 2006 (Trillion Btu) MECS Survey Years NAICS...

  1. "PART 1: ENERGY/WATER CONSUMPTION AND COST DATA"

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Adjustment Data Report for Fiscal Years Prior to 2008" ,,,"FY","20XX" "Agency:","Department of X",,,"Prepared by:" "Date:",,,,"Phone:" "PART 1: ENERGY/WATER CONSUMPTION AND COST DATA" "1-1. NECPA/E.O. 13423 Goal Subject Buildings" "Energy Type","Consumption Units","Annual Consumption","Annual Cost (Thou. $)","Unit Cost ($)",,"Site-Delivered Btu

  2. Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption

    Buildings Energy Data Book

    1 Delivered Energy Consumption Intensities of Public Multi-Family Buildings, by Fuel and Region (Thousand Btu/SF) Region Electricity Natural Gas Fuel Oil Total Northeast 27.7 45.9 39.9 71.5 Midwest 22.5 49.9 N.A. 70.3 South 53.5 27.9 N.A. 65.9 West 22.0 25.3 N.A. 46.2 National Average 33.0 43.4 68.3

  3. Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption

    Buildings Energy Data Book

    2 Delivered Energy Consumption Intensities of Public Multi-Family Buildings, by Fuel and Region (Million Btu/Household) Region Electricity Natural Gas Fuel Oil Total Northeast 21.2 34.9 36.2 54.7 Midwest 16.6 36.6 N.A. 51.8 South 39.4 20.0 N.A. 48.5 West 16.6 19.3 N.A. 34.8 National Average 24.6 32.2 51.0

  4. User-needs study for the 1992 Commercial Buildings Energy Consumption Survey

    SciTech Connect

    Not Available

    1992-09-01

    The Commercial Buildings Energy Consumption Survey (CBECS) that is conducted by the Energy Information Administration (EIA) is the primary source of energy data for commercial buildings in the United States. The survey began in 1979 and has subsequently been conducted in 1983, 1986, and 1989. The next survey will cover energy consumption during the year 1992. The building characteristic data will be collected between August 1992 and early December 1992. Requests for energy consumption data are mailed to the energy suppliers in January 1993, with data due by March 1993. Before each survey is sent into the field, the data users` needs are thoroughly assessed. The purpose of this report is to document the findings of that user-needs assessment for the 1992 survey.

  5. Trends in Commercial Buildings--Trends in Energy Consumption...

    Energy Information Administration (EIA) (indexed site)

    the use of the four major sources and other energy sources (e.g., district chilled water, solar, wood). Energy consumed in commercial buildings is a significant fraction of that...

  6. AEO2011: Energy Consumption by Sector and Source - Mountain ...

    OpenEI (Open Energy Information) [EERE & EIA]

    comes from the Energy Information Administration (EIA), and is part of the 2011 Annual Energy Outlook Report (AEO2011). This dataset is table 8, and contains only the reference...

  7. OSTIblog Articles in the energy consumption Topic | OSTI, US...

    Office of Scientific and Technical Information (OSTI)

    Our earth has an immense reservoir of geothermal energy that has helped to create this amazing landscape. Geothermal energy is the heat contained within the earth-a clean, ...

  8. U.S. Lighting Market Characterization Volume I: National Lighting Inventory and Energy Consumption Estimate Final Report

    SciTech Connect

    None, None

    2002-09-01

    Multiyear study to evaluate light sources and identify opportunities for saving energy. This report estimates energy consumption for residential, commercial, industrial, and outdoor stationary.

  9. Energy Consumption: Costs and the Annual Efficiency Index

    SciTech Connect

    2004-01-01

    This document explains to municipal workers how they can measure and reduce the energy usage of their buildings.

  10. Video game console usage and US national energy consumption: Results from a field-metering study

    DOE PAGES [OSTI]

    Desroches, Louis-Benoit; Greenblatt, Jeffery B.; Pratt, Stacy; Willem, Henry; Claybaugh, Erin; Beraki, Bereket; Nagaraju, Mythri; Price, Sarah K.; Young, Scott J.; Donovan, Sally M.; et al

    2014-10-23

    There has been an increased in attention placed on the energy consumption of miscellaneous electronic loads in buildings by energy analysts and policymakers in recent years. The share of electricity consumed by consumer electronics in US households has increased in the last decade. Many devices, however, lack robust energy use data, making energy consumption estimates difficult and uncertain. Video game consoles are high-performance machines present in approximately half of all households and can consume a considerable amount of power. The precise usage of game consoles has significant uncertainty, however, leading to a wide range of recent national energy consumption estimates.more » We present here an analysis based on field-metered usage data, collected as part of a larger field metering study in the USA. This larger study collected data from 880 households in 2012 on a variety of devices, including 113 game consoles (the majority of which are Generation 7 consoles). From our metering, we find that although some consoles are left on nearly 24 h/day, the overall average usage is lower than many other studies have assumed, leading to a US national energy consumption estimate of 7.1 TWh in 2012. Nevertheless, there is an opportunity to reduce energy use with proper game console power management, as a substantial amount of game console usage occurs with the television turned off. The emergence of Generation 8 consoles may increase national energy consumption.« less

  11. Video game console usage and US national energy consumption: Results from a field-metering study

    SciTech Connect

    Desroches, Louis-Benoit; Greenblatt, Jeffery B.; Pratt, Stacy; Willem, Henry; Claybaugh, Erin; Beraki, Bereket; Nagaraju, Mythri; Price, Sarah K.; Young, Scott J.; Donovan, Sally M.; Ganeshalingam, Mohan

    2014-10-23

    There has been an increased in attention placed on the energy consumption of miscellaneous electronic loads in buildings by energy analysts and policymakers in recent years. The share of electricity consumed by consumer electronics in US households has increased in the last decade. Many devices, however, lack robust energy use data, making energy consumption estimates difficult and uncertain. Video game consoles are high-performance machines present in approximately half of all households and can consume a considerable amount of power. The precise usage of game consoles has significant uncertainty, however, leading to a wide range of recent national energy consumption estimates. We present here an analysis based on field-metered usage data, collected as part of a larger field metering study in the USA. This larger study collected data from 880 households in 2012 on a variety of devices, including 113 game consoles (the majority of which are Generation 7 consoles). From our metering, we find that although some consoles are left on nearly 24 h/day, the overall average usage is lower than many other studies have assumed, leading to a US national energy consumption estimate of 7.1 TWh in 2012. Nevertheless, there is an opportunity to reduce energy use with proper game console power management, as a substantial amount of game console usage occurs with the television turned off. The emergence of Generation 8 consoles may increase national energy consumption.

  12. An investigation of cointegration and causality between energy consumption and economic growth

    SciTech Connect

    Cheng, B.S.

    1995-12-31

    This paper reexamines the causality between energy consumption and economic growth with both bivariate and multivariate models by applying the recently developed methods of cointegration and Hsiao`s version of the Granger causality to transformed U.S. data for the period 1947-1990. The Phillips-Perron (PP) tests reveal that the original series are not stationary and, therefore, a first differencing is performed to secure stationarity. The study finds no causal linkages between energy consumption and economic growth. Energy and gross national product (GNP) each live a life of its own. The results of this article are consistent with some of the past studies that find no relationship between energy and GNP but are contrary to some other studies that find GNP unidirectionally causes energy consumption. Both the bivariate and trivariate models produce the similar results. We also find that there is no causal relationship between energy consumption and industrial production. The United States is basically a service-oriented economy and changes in energy consumption can cause little or no changes in GNP. In other words, an implementation of energy conservation policy may not impair economic growth. 27 refs., 5 tabs.

  13. Numerical prediction of energy consumption in buildings with controlled interior temperature

    SciTech Connect

    Jarošová, P.; Št’astník, S.

    2015-03-10

    New European directives bring strong requirement to the energy consumption of building objects, supporting the renewable energy sources. Whereas in the case of family and similar houses this can lead up to absurd consequences, for building objects with controlled interior temperature the optimization of energy demand is really needed. The paper demonstrates the system approach to the modelling of thermal insulation and accumulation abilities of such objetcs, incorporating the significant influence of additional physical processes, as surface heat radiation and moisture-driven deterioration of insulation layers. An illustrative example shows the numerical prediction of energy consumption of a freezing plant in one Central European climatic year.

  14. Modeling energy consumption of residential furnaces and boilers in U.S. homes

    SciTech Connect

    Lutz, James; Dunham-Whitehead, Camilla; Lekov, Alex; McMahon, James

    2004-02-01

    In 2001, DOE initiated a rulemaking process to consider whether to amend the existing energy efficiency standards for furnaces and boilers. A key factor in DOE's consideration of new standards is their cost-effectiveness to consumers. Determining cost-effectiveness requires an appropriate comparison of the additional first cost of energy efficiency design options with the savings in operating costs. This report describes calculation of equipment energy consumption (fuel and electricity) based on estimated conditions in a sample of homes that are representative of expected furnace and boiler installations. To represent actual houses with furnaces and boilers in the United States, we used a set of houses from the Residential Energy Consumption Survey of 1997 conducted by the Energy Information Administration. Our calculation methodology estimates the energy consumption of alternative (more-efficient) furnaces, if they were to be used in each house in place of the existing equipment. We developed the method of calculation described in this report for non-weatherized gas furnaces. We generalized the energy consumption calculation for this product class to the other furnace product classes. Fuel consumption calculations for boilers are similar to those for the other furnace product classes. The electricity calculations for boilers are simpler than for furnaces, because boilers do not provide thermal distribution for space cooling as furnaces often do.

  15. Residential Energy Consumption Survey (RECS) - Analysis & Projections -

    Gasoline and Diesel Fuel Update

    U.S. Energy Information Administration (EIA) The impact of increasing home size on energy demand RECS 2009 - Release date: April 19, 2012 Homes built since 1990 are on average 27% larger than homes built in earlier decades, a significant trend because most energy end-uses are correlated with the size of the home. As square footage increases, the burden on heating and cooling equipment rises, lighting requirements increase, and the likelihood that the household uses more than one refrigerator

  16. Buildings Energy Data Book: 1.2 Residential Sector Energy Consumption

    Buildings Energy Data Book

    Residential Sector Energy Consumption March 2012 1.2.9 Implicit Price Deflators (2005 = 1.00) Year Year Year 1980 0.48 1990 0.72 2000 0.89 1981 0.52 1991 0.75 2001 0.91 1982 0.55 1992 0.77 2002 0.92 1983 0.58 1993 0.78 2003 0.94 1984 0.60 1994 0.80 2004 0.97 1985 0.62 1995 0.82 2005 1.00 1986 0.63 1996 0.83 2006 1.03 1987 0.65 1997 0.85 2007 1.06 1988 0.67 1998 0.86 2008 1.09 1989 0.70 1999 0.87 2009 1.10 2010 1.11 Source(s): EIA, Annual Energy Review 2010, August 2011, Appendix D, p. 353.

  17. Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption

    Buildings Energy Data Book

    9 Northeast Midwest South West National Space Heating 70.3 56.6 20.4 23.8 38.7 Space Cooling 3.6 5.6 13.9 4.0 7.9 Water Heating 21.1 20.4 15.8 21.2 19.0 Refrigerator 5.4 7.0 6.6 5.7 6.3 Other Appliances & Lighting 23.0 25.9 25.0 24.1 24.7 Total (1) 79.9 77.4 95.0 Note(s): Source(s): 2005 Delivered Energy End-Uses for an Average Household, by Region (Million Btu per Household) 122.2 113.5 1) Due to rounding, sums do not add up to totals. EIA, 2005 Residential Energy Consumption Survey, Oct.

  18. Assessment of Vehicle Sizing, Energy Consumption and Cost through...

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Technologies Office (VTO) supports new technologies to increase energy security in the transportation sector at a critical time for global petroleum supply, demand, and pricing. ...

  19. Manufacturing Energy Consumption Survey (MECS) - Data - U.S....

    Energy Information Administration (EIA) (indexed site)

    Archive MECS Survey Data 2010 | 2006 | 2002 | 1998 | 1994 | 1991 | Archive Special Reports (click on table headings to sort) Title Release Year Cycle Year Format Energy-Related...

  20. Novel Ultra-Low-Energy Consumption Ultrasonic Clothes Dryer ...

    Office of Environmental Management (EM)

    ... More Documents & Publications A new thermoelectric clothes dryer being developed by Oak ... Credit: Oak Ridge National Laboratory. Novel Energy-Efficient Thermoelectric Clothes Dryer ...

  1. Machine Learning Based Multi-Physical-Model Blending for Enhancing Renewable Energy Forecast -- Improvement via Situation Dependent Error Correction

    SciTech Connect

    Lu, Siyuan; Hwang, Youngdeok; Khabibrakhmanov, Ildar; Marianno, Fernando J.; Shao, Xiaoyan; Zhang, Jie; Hodge, Bri-Mathias; Hamann, Hendrik F.

    2015-07-15

    With increasing penetration of solar and wind energy to the total energy supply mix, the pressing need for accurate energy forecasting has become well-recognized. Here we report the development of a machine-learning based model blending approach for statistically combining multiple meteorological models for improving the accuracy of solar/wind power forecast. Importantly, we demonstrate that in addition to parameters to be predicted (such as solar irradiance and power), including additional atmospheric state parameters which collectively define weather situations as machine learning input provides further enhanced accuracy for the blended result. Functional analysis of variance shows that the error of individual model has substantial dependence on the weather situation. The machine-learning approach effectively reduces such situation dependent error thus produces more accurate results compared to conventional multi-model ensemble approaches based on simplistic equally or unequally weighted model averaging. Validation over an extended period of time results show over 30% improvement in solar irradiance/power forecast accuracy compared to forecasts based on the best individual model.

  2. Estimating Total Energy Consumption and Emissions of China's Commercial and Office Buildings

    SciTech Connect

    Fridley, David; Fridley, David G.; Zheng, Nina; Zhou, Nan

    2008-03-01

    Buildings represent an increasingly important component of China's total energy consumption mix. However, accurately assessing the total volume of energy consumed in buildings is difficult owing to deficiencies in China's statistical collection system and a lack of national surveys. Official statistics suggest that buildings account for about 19% of China's total energy consumption, while others estimate the proportion at 23%, rising to 30% over the next few years. In addition to operational energy, buildings embody the energy used in the in the mining, extraction, harvesting, processing, manufacturing and transport of building materials as well as the energy used in the construction and decommissioning of buildings. This embodied energy, along with a building's operational energy, constitutes the building's life-cycle energy and emissions footprint. This report first provides a review of international studies on commercial building life-cycle energy use from which data are derived to develop an assessment of Chinese commercial building life-cycle energy use, then examines in detail two cases for the development of office building operational energy consumption to 2020. Finally, the energy and emissions implications of the two cases are presented.

  3. Residential Energy Consumption Survey (RECS) - Analysis & Projections -

    Energy Information Administration (EIA) (indexed site)

    U.S. Energy Information Administration (EIA) About the RECS RECS Survey Forms RECS Maps RECS Terminology Archived Reports Has your home been selected for the RECS? State fact sheets Arizona household graph See state fact sheets › 2009 RECS Features Heating and cooling no longer majority of U.S. home energy use March 7, 2013 Newer U.S. homes are 30% larger but consume about as much energy as older homes February 12, 2013 Where does RECS square footage data come from? July 11, 2012 RECS data

  4. 2016 Bioenergizeme Infographic Challenge: US Energy Consumption By Source

    Energy.gov [DOE]

    This infographic was created by students from High Tech Early College in Denver, CO, as part of the U.S. Department of Energy-BioenergizeME Infographic Challenge. The BioenergizeME Infographic...

  5. Potential for the Use of Energy Savings Performance Contracts to Reduce Energy Consumption and Provide Energy and Cost Savings in Non-Building Applications

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    for the Use of Energy Savings Performance Contracts to Reduce Energy Consumption and Provide Energy and Cost Savings in Non-Building Applications A Joint Study by the United States Secretaries of Energy and Defense Authorized in the Energy Independence and Security Act 2007 by Congress Prepared by US Department of Energy Office of Energy Efficiency and Renewable Energy, Federal Energy Management Program For questions and comments please contact: Schuyler Schell Federal Energy Management Program

  6. Federal Government’s Energy Consumption Lowest in Almost 40 Years

    Energy.gov [DOE]

    While the U.S. federal government continues to be one of the largest energy consumers in the world, its consumption has been steadily declining for nearly four decades, and now stands at less than 1 quadrillion British thermal units, the lowest since 1975, when data collection began. Find out how our Federal Energy Management Program helped agencies achieve this milestone.

  7. Buildings Energy Data Book: 1.1 Buildings Sector Energy Consumption

    Buildings Energy Data Book

    3 Buildings Share of U.S. Primary Energy Consumption (Percent) Total Consumption Total Industry Transportation Total (quads) 1980(1) 20.1% 13.5% | 33.7% 41.1% 25.2% 100% | 78.1 1981 20.0% 13.9% | 33.9% 40.4% 25.6% 100% | 76.1 1982 21.2% 14.8% | 36.0% 37.9% 26.1% 100% | 73.1 1983 21.1% 15.0% | 36.1% 37.7% 26.3% 100% | 72.9 1984 20.8% 14.9% | 35.7% 38.7% 25.7% 100% | 76.6 1985 21.0% 15.0% | 35.9% 37.8% 26.3% 100% | 76.5 1986 20.8% 15.1% | 35.9% 37.0% 27.1% 100% | 76.6 1987 20.5% 15.1% | 35.6%

  8. Analysis of changes in residential energy consumption, 1973-1980

    SciTech Connect

    King, M.J.; Belzer, D.B.; Callaway, J.M.; Adams, R.C.

    1982-09-01

    The progress of energy conservation in the residential sector since the 1973 to 1974 Arab oil embargo is assessed. To accomplish this goal, the reduction in residential energy use per household since 1973 is disaggregated into six possible factors. The factors considered were: (1) building shell efficiencies, (2) geographic distribution of households, (3) appliance efficiency, (4) size of dwelling units, (5) fuel switching, and (6) consumer attitudes. The most important factor identified was improved building shell efficiency, although the impact of appliance efficiency is growing rapidly. Due to data limitations, PNL was not able to quantify the effects of two factors (size of dwelling units and fuel switching) within the framework of this study. The total amount of the energy reduction explained ranged from 18 to 46% over the years 1974 to 1980.

  9. Buildings Energy Data Book: 3.1 Commercial Sector Energy Consumption

    Buildings Energy Data Book

    2 Commercial Site Renewable Energy Consumption (Quadrillion Btu) (1) Growth Rate Wood (2) Solar Thermal (3) Solar PV (3) GHP Total 2010-Year 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 0.110 0.035 0.010 N.A. 0.155 0.4% 0.110 0.035 0.009 N.A. 0.154 0.4% 0.110 0.035 0.009 N.A. 0.153 0.4% 0.110

  10. Buildings Energy Data Book: 3.1 Commercial Sector Energy Consumption

    Buildings Energy Data Book

    9 2003 Commercial Delivered Energy Consumption Intensities, by Principal Building Type and Vintage (1) | Building Type Pre-1959 1960-1989 1990-2003 | Building Type Pre-1959 1960-1989 1990-2003 Health Care 178.1 216.0 135.7 | Education 77.7 88.3 80.6 Inpatient 230.3 255.3 253.8 | Service 62.4 86.0 74.8 Outpatient 91.6 110.4 84.4 | Food Service 145.2 290.1 361.2 Food Sales 205.8 197.6 198.3 | Religious Worship 46.6 39.9 43.3 Lodging 88.2 111.5 88.1 | Public Order & Safety N.A. 101.3 110.6

  11. China's transportation energy consumption and CO2 emissions from a global perspective

    SciTech Connect

    Yin, Xiang; Chen, Wenying; Eom, Jiyong; Clarke, Leon E.; Kim, Son H.; Patel, Pralit L.; Yu, Sha; Kyle, G. Page

    2015-07-01

    ABSTRACT Rapidly growing energy demand from China's transportation sector in the last two decades have raised concerns over national energy security, local air pollution, and carbon dioxide (CO2) emissions, and there is broad consensus that China's transportation sector will continue to grow in the coming decades. This paper explores the future development of China's transportation sector in terms of service demands, final energy consumption, and CO2 emissions, and their interactions with global climate policy. This study develops a detailed China transportation energy model that is nested in an integrated assessment model—Global Change Assessment Model (GCAM)—to evaluate the long-term energy consumption and CO2 emissions of China's transportation sector from a global perspective. The analysis suggests that, without major policy intervention, future transportation energy consumption and CO2 emissions will continue to rapidly increase and the transportation sector will remain heavily reliant on fossil fuels. Although carbon price policies may significantly reduce the sector's energy consumption and CO2 emissions, the associated changes in service demands and modal split will be modest, particularly in the passenger transport sector. The analysis also suggests that it is more difficult to decarbonize the transportation sector than other sectors of the economy, primarily owing to its heavy reliance on petroleum products.

  12. Buildings Energy Data Book: 1.1 Buildings Sector Energy Consumption

    Buildings Energy Data Book

    3 World Primary Energy Consumption and Population, by Country/Region 1990-2000 2000-2010 Region/Country 1990 2000 2010 1990 2000 2010 Energy Pop. Energy Pop. United States 85.0 99.8 97.8 18.7% 250 282 311 4.6% 1.6% 1.2% -0.2% 1.0% China 27.0 36.4 104.6 20.0% 1,148 1,264 1,343 20.0% 3.0% 1.0% 11.1% 0.6% OECD Europe 69.9 76.8 79.6 15.2% 402 522 550 8.2% 0.9% 2.6% 0.4% 0.5% Other Non-OECD Asia 12.5 20.6 31.3 6.0% 781 1,014 1,086 16.2% 5.1% 2.6% 4.2% 0.7% Russia (1) 61.0 27.2 29.9 5.7% 288 147 140

  13. 1980 annual report to Congress: Volume three, Forecasts: Summary

    SciTech Connect

    Not Available

    1981-05-27

    This report presents an overview of forecasts of domestic energy consumption, production, and prices for the year 1990. These results are selected from more detailed projections prepared and published in Volume 3 of the Energy Information Administration 1980 Annual Report to Congress. This report focuses specifically upon the 1980's and concentrates upon similarities and differences in the domestic energy system, as forecast, compared to the national experience in the years immediately following the 1973--1974 oil embargo. Interest in the 1980's stems not only from its immediacy in time, but also from its importance as a time in which certain adjustments to higher energy prices are expected to take place. The forecasts presented do not attempt to account for all of this wide range of potentially important forces that could conceivably alter the energy situation. Instead, the projections are based on a particular set of assumptions that seems reasonable in light of what is currently known. 9 figs., 25 tabs.

  14. Commercial Buildings Energy Consumption Survey (CBECS) - Analysis &

    Gasoline and Diesel Fuel Update

    Projections - U.S. Energy Information Administration (EIA) All Reports & Publications Search By: Go Pick a date range: From: To: Go Commercial Buildings Available formats PDF Updated Buildings Sector Appliance and Equipment Costs and Efficiency Released: November 9, 2016 EIA works with technology experts to project the cost and efficiency of future HVAC, lighting, and other major end-use equipment rather than developing residential and commercial technology projections in-house. These

  15. Determinants of automobile use and energy consumption in OECD countries

    SciTech Connect

    Schipper, L.

    1995-11-01

    Energy use is associated with environmental problems and other externalities arising from personal transportation. In this article, the author reviews trends in the use of the car and other modes of personal transportation in 10 OECD countries from 1970 to 1992. He analyzes changes in energy use for these activities and discuss underlying components of, and causes for, these changes. He compares differences between the US and the European countries studied, concluding that most of the variations arise because of differences in total transport activity and modal choice, not because of the energy efficiency of each mode. He analyzes more closely differences in activity, which is dominated by the automobile, relating automobile use to differences in fuel prices and car taxation, in patterns of mobility, in demographic patterns, and in geographical factors like land use or place of residence. He concludes with a focus on one externality of transportation, the carbon dioxide emissions from travel. He notes that these emissions are rising in all the countries studied. He suggests that policies aimed at stemming this rise must be integrated with other policies related to other problems of transportation, many of which are perceived to be more important than that of CO{sub 2} alone. 121 refs., 28 figs., 2 tabs.

  16. Constraining Energy Consumption of China's Largest IndustrialEnterprises Through the Top-1000 Energy-Consuming EnterpriseProgram

    SciTech Connect

    Price, Lynn; Wang, Xuejun

    2007-06-01

    Between 1980 and 2000, China's energy efficiency policiesresulted in a decoupling of the traditionally linked relationship betweenenergy use and gross domestic product (GDP) growth, realizing a four-foldincrease in GDP with only a doubling of energy use. However, during Chinas transition to a market-based economy in the 1990s, many of thecountry's energy efficiency programs were dismantled and between 2001 and2005 China's energy use increased significantly, growing at about thesame rate as GDP. Continuation of this one-to-one ratio of energyconsumption to GDP given China's stated goal of again quadrupling GDPbetween 2000 and 2020 will lead to significant demand for energy, most ofwhich is coal-based. The resulting local, national, and globalenvironmental impacts could be substantial.In 2005, realizing thesignificance of this situation, the Chinese government announced anambitious goal of reducing energy consumption per unit of GDP by 20percent between 2005 and 2010. One of the key initiatives for realizingthis goal is the Top-1000 Energy-Consuming Enterprises program. Thecomprehensive energy consumption of these 1000 enterprises accounted for33 percent of national and 47 percent of industrial energy usage in 2004.Under the Top-1000 program, 2010 energy consumption targets wereannounced for each enterprise. Activities to be undertaken includebenchmarking, energy audits, development of energy saving action plans,information and training workshops, and annual reporting of energyconsumption. This paper will describe the program in detail, includingthe types of enterprises included and the program activities, and willprovide an analysis of the progress and lessons learned todate.

  17. Residential Energy Consumption Survey (RECS) - Analysis & Projections -

    Gasoline and Diesel Fuel Update

    U.S. Energy Information Administration (EIA) All Reports & Publications Search By: Go Pick a date range: From: To: Go Residential heating oil and propane prices at levels similar to last winter's low prices November 17, 2016 U.S. residential electricity prices decline for the first time in many years October 6, 2016 Total U.S. electricity sales projected to grow slowly as electricity intensity declines June 15, 2016 All 72 related articles › Residential Available formats PDF Primary

  18. Future Air Conditioning Energy Consumption in Developing Countriesand what can be done about it: The Potential of Efficiency in theResidential Sector

    SciTech Connect

    McNeil, Michael A.; Letschert, Virginie E.

    2007-05-01

    The dynamics of air conditioning are of particular interestto energy analysts, both because of the high energy consumption of thisproduct, but also its disproportionate impact on peak load. This paperaddresses the special role of this end use as a driver of residentialelectricity consumption in rapidly developing economies. Recent historyhas shown that air conditioner ownership can grow grows more rapidly thaneconomic growth in warm-climate countries. In 1990, less than a percentof urban Chinese households owned an air conditioner; by 2003 this numberrose to 62 percent. The evidence suggests a similar explosion of airconditioner use in many other countries is not far behind. Room airconditioner purchases in India are currently growing at 20 percent peryear, with about half of these purchases attributed to the residentialsector. This paper draws on two distinct methodological elements toassess future residential air conditioner 'business as usual' electricityconsumption by country/region and to consider specific alternative 'highefficiency' scenarios. The first component is an econometric ownershipand use model based on household income, climate and demographicparameters. The second combines ownership forecasts and stock accountingwith geographically specific efficiency scenarios within a uniqueanalysis framework (BUENAS) developed by LBNL. The efficiency scenariomodule considers current efficiency baselines, available technologies,and achievable timelines for development of market transformationprograms, such as minimum efficiency performance standards (MEPS) andlabeling programs. The result is a detailed set of consumption andemissions scenarios for residential air conditioning.

  19. Ramping Effect on Forecast Use: Integrated Ramping as a Mitigation Strategy; NREL (National Renewable Energy Laboratory)

    SciTech Connect

    Diakov, Victor; Barrows, Clayton; Brinkman, Gregory; Bloom, Aaron; Denholm, Paul

    2015-06-23

    Power generation ramping between forecasted (net) load set-points shift the generation (MWh) from its scheduled values. The Integrated Ramping is described as a method that mitigates this problem.

  20. Building Technologies Office: R&D Opportunities to Reduce Energy Consumption in Miscellaneous Electric Loads (MELs)

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Office: R&D Opportunities to Reduce Energy Consumption in Miscellaneous Electric Loads (MELs) Pat Phelan (patrick.phelan@ee.doe.gov) BTO Emerging Technologies June 3, 2016 2 Why Do We Care About MELs? Problem: Fraction of energy consumption due to MELs is rising as other building technologies become more efficient. DOE Quadrennial Technology Review (2015)  60% of remaining energy consumption after 2020 R&D targets are achieved, the majority of which are MELs. FY16 Activities: * Panel

  1. Solar Forecasting Technical Workshop

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Forecasting Technical Workshop August 3, 2016 901 D St SW, Suite #930, Washington, DC Agenda 8:00-8:30 Check-in 8:30-8:45 Welcome & Opening remarks Guohui Yuan, DOE 8:45-9:15 Overview of Motivation and Techniques for Solar Forecasting Jan Kleissl, UCSD 9:15-9:45 Collaborative Research on Solar Power Forecasting: Challenges, Methods, and Assessment Tara Jensen, NCAR 9:45-10:00 Break 10:00-10:30 Machine-learning Based Enhancements for Renewable Energy Forecasting: From Research to Applications

  2. Fossil Fuel-Generated Energy Consumption Reduction for New Federal Buildings and Major Renovations of Federal Buildings

    Energy.gov [DOE]

    Document details Fossil Fuel-Generated Energy Consumption Reduction for New Federal Buildings and Major Renovations of Federal Buildings in a Supplemental Notice of Proposed Rulemaking.

  3. Fossil Fuel-Generated Energy Consumption Reduction for New Federal Buildings and Major Renovations of Federal Buildings OIRA Comparison Document

    Office of Energy Efficiency and Renewable Energy (EERE)

    Document details the Fossil Fuel-Generated Energy Consumption Reduction for New Federal Buildings and Major Renovations of Federal Buildings in an OIRA Comparison Document.

  4. Wind Energy Management System EMS Integration Project: Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations

    SciTech Connect

    Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

    2010-01-01

    The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind and solar power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation), and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind/solar forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. To improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter

  5. Impact of Energy Policy Act of 2005 Section 206 Rebates on Consumers and Renewable Energy Consumption, With Projections to 2010

    Reports and Publications

    2006-01-01

    The Energy Information Administration (EIA), with the agreement of the Department, interpreted section 206(d) as calling for a listing of the types of renewable fuels available today, and a listing of those that will be available in the future based on the incentives provided in section 206(d). This report provides that information, and also provides information concerning renewable energy equipment and renewable energy consumption.

  6. Future U.S. water consumption : The role of energy production.

    SciTech Connect

    Elcock, D.; Environmental Science Division

    2010-06-01

    This study investigates how meeting domestic energy production targets for both fossil and renewable fuels may affect future water demand. It combines projections of energy production developed by the U.S. Department of Energy with estimates of water consumption on a per-unit basis (water-consumption coefficients) for coal, oil, gas, and biofuels production, to estimate and compare the domestic freshwater consumed. Although total domestic freshwater consumption is expected to increase by nearly 7% between 2005 and 2030, water consumed for energy production is expected to increase by nearly 70%, and water consumed for biofuels (biodiesel and ethanol) production is expected to increase by almost 250%. By 2030, water consumed in the production of biofuels is projected to account for nearly half of the total amount of water consumed in the production of all energy fuels. Most of this is for irrigation, and the West North Central Region is projected to consume most of this water in 2030. These findings identify an important potential future conflict between renewable energy production and water availability that warrants further investigation and action to ensure that future domestic energy demand can be met in an economically efficient and environmentally sustainable manner.

  7. Impact of Extended Daylight Saving Time on National Energy Consumption Report to Congress

    SciTech Connect

    Belzer, D. B.; Hadley, S. W.; Chin, S-M.

    2008-10-01

    The Energy Policy Act of 2005 (Pub. L. No. 109-58; EPAct 2005) amended the Uniform Time Act of 1966 (Pub. L. No. 89-387) to increase the portion of the year that is subject to Daylight Saving Time. (15 U.S.C. 260a note) EPAct 2005 extended the duration of Daylight Saving Time in the spring by changing its start date from the first Sunday in April to the second Sunday in March, and in the fall by changing its end date from the last Sunday in October to the first Sunday in November. (15 U.S.C. 260a note) EPAct 2005 also called for the Department of Energy to evaluate the impact of Extended Daylight Saving Time on energy consumption in the United States and to submit a report to Congress. (15 U.S.C. 260a note) This report presents the results of impacts of Extended Daylight Saving Time on the national energy consumption in the United States. The key findings are: (1) The total electricity savings of Extended Daylight Saving Time were about 1.3 Tera Watt-hour (TWh). This corresponds to 0.5 percent per each day of Extended Daylight Saving Time, or 0.03 percent of electricity consumption over the year. In reference, the total 2007 electricity consumption in the United States was 3,900 TWh. (2) In terms of national primary energy consumption, the electricity savings translate to a reduction of 17 Trillion Btu (TBtu) over the spring and fall Extended Daylight Saving Time periods, or roughly 0.02 percent of total U.S. energy consumption during 2007 of 101,000 TBtu. (3) During Extended Daylight Saving Time, electricity savings generally occurred over a three- to five-hour period in the evening with small increases in usage during the early-morning hours. On a daily percentage basis, electricity savings were slightly greater during the March (spring) extension of Extended Daylight Saving Time than the November (fall) extension. On a regional basis, some southern portions of the United States exhibited slightly smaller impacts of Extended Daylight Saving Time on energy savings

  8. Table A20. Total First Use (formerly Primary Consumption) of Energy for All P

    Energy Information Administration (EIA) (indexed site)

    Total First Use (formerly Primary Consumption) of Energy for All Purposes by Census" " Region, Census Division, and Economic Characteristics of the Establishment, 1994" " (Estimates in Btu or Physical Units)" ,,,,,,,,"Coke",,"Shipments" " "," ","Net","Residual","Distillate","Natural Gas(e)"," ","Coal","and Breeze"," ","of Energy

  9. All Consumption Tables.vp

    Energy Information Administration (EIA) (indexed site)

    4) June 2007 State Energy Consumption Estimates 1960 Through 2004 2004 Consumption Summary Tables Table S1. Energy Consumption Estimates by Source and End-Use Sector, 2004...

  10. ,"Total Fuel Oil Consumption

    Energy Information Administration (EIA) (indexed site)

    0. Fuel Oil Consumption (gallons) and Energy Intensities by End Use for Non-Mall Buildings, 2003" ,"Total Fuel Oil Consumption (million gallons)",,,,,"Fuel Oil Energy Intensity...

  11. ,"Total Fuel Oil Consumption

    Energy Information Administration (EIA) (indexed site)

    A. Fuel Oil Consumption (gallons) and Energy Intensities by End Use for All Buildings, 2003" ,"Total Fuel Oil Consumption (million gallons)",,,,,"Fuel Oil Energy Intensity...

  12. Buildings Energy Data Book: 1.1 Buildings Sector Energy Consumption

    Buildings Energy Data Book

    U.S. Residential and Commercial Buildings Total Primary Energy Consumption (Quadrillion Btu and Percent of Total) Electricity Growth Rate Natural Gas Petroleum (1) Coal Renewable(2) Sales Losses Total TOTAL (2) 2010-Year 1980 7.42 28.2% 3.04 11.5% 0.15 0.6% 0.87 3.3% 4.35 10.47 14.82 56.4% 26.29 100% - 1981 7.11 27.5% 2.63 10.2% 0.17 0.6% 0.89 3.5% 4.50 10.54 15.03 58.2% 25.84 100% - 1982 7.32 27.8% 2.45 9.3% 0.19 0.7% 0.99 3.8% 4.57 10.80 15.37 58.4% 26.31 100% - 1983 6.93 26.4% 2.50 9.5% 0.19

  13. Buildings Energy Data Book: 3.1 Commercial Sector Energy Consumption

    Buildings Energy Data Book

    Commercial Primary Energy Consumption, by Year and Fuel Type (Quadrillion Btu and Percent of Total) Electricity Growth Rate Natural Gas Petroleum (1) Coal Renewable(2) Sales Losses Total Total(3) 2010-Year 1980 2.63 24.9% 1.31 12.4% 0.12 1.1% 0.02 0.2% 1.91 4.58 6.49 61.4% 1981 2.54 23.9% 1.12 10.5% 0.14 1.3% 0.02 0.2% 2.03 4.76 6.80 64.1% 1982 2.64 24.3% 1.03 9.5% 0.16 1.4% 0.02 0.2% 2.08 4.91 6.99 64.5% 1983 2.48 22.7% 1.16 10.7% 0.16 1.5% 0.02 0.2% 2.12 4.98 7.09 65.0% 1984 2.57 22.5% 1.22

  14. Buildings Energy Data Book: 1.1 Buildings Sector Energy Consumption

    Buildings Energy Data Book

    2 U.S. Buildings Site Renewable Energy Consumption (Quadrillion Btu) (1) Growth Rate Wood (2) Solar Thermal (3) Solar PV (3) GSHP (4) Total 2010-Year 1980 0.867 0.000 N.A. 0.000 0.867 - 1981 0.894 0.000 N.A. 0.000 0.894 - 1982 0.993 0.000 N.A. 0.000 0.993 - 1983 0.992 0.000 N.A. 0.000 0.992 - 1984 1.002 0.000 N.A. 0.000 1.002 - 1985 1.034 0.000 N.A. 0.000 1.034 - 1986 0.947 0.000 N.A. 0.000 0.947 - 1987 0.882 0.000 N.A. 0.000 0.882 - 1988 0.942 0.000 N.A. 0.000 0.942 - 1989 1.018 0.052 N.A.

  15. Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption

    Buildings Energy Data Book

    0 Region (1) Northeast 73.5 122.2 47.7 24% New England 77.0 129.4 55.3 7% Middle Atlantic 72.2 119.7 45.3 17% Midwest 58.9 113.5 46.0 28% East North Central 61.1 117.7 47.3 20% West North Central 54.0 104.1 42.9 8% South 51.5 79.8 31.6 31% South Atlantic 47.4 76.1 30.4 16% East South Central 56.6 87.3 36.1 6% West South Central 56.6 82.4 31.4 9% West 56.6 77.4 28.1 18% Mountain 54.4 89.8 33.7 6% Pacific 58.0 71.8 25.7 11% U.S. Average 58.7 94.9 37.0 100% Note(s): Source(s): 1) Energy consumption

  16. Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption

    Buildings Energy Data Book

    3 Building Type Pre-1995 1995-2005 Pre-1995 1995-2005 Pre-1995 1995-2005 Single-Family 38.4 44.9 102.7 106.2 38.5 35.5 Detached 37.9 44.7 104.5 107.8 38.8 35.4 Attached 43.8 55.5 86.9 85.1 34.2 37.6 Multi-Family 63.8 58.7 58.3 49.2 27.2 24.3 2 to 4 units 69.0 55.1 70.7 59.4 29.5 25.0 5 or more units 61.5 59.6 53.6 47.2 26.3 24.2 Mobile Homes 82.4 57.1 69.6 74.5 29.7 25.2 Note(s): Source(s): 2005 Residential Delivered Energy Consumption Intensities, by Principal Building Type and Vintage Per

  17. Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption

    Buildings Energy Data Book

    4 Primary Energy Consumption Total Per Household 1980 79.6 N.A. 123.5 15.72 197.4 1981 82.8 N.A. 114.2 15.23 184.0 1982 83.7 N.A. 114.6 15.48 184.9 1983 84.6 N.A. 110.6 15.38 181.9 1984 86.3 N.A. 113.9 15.90 184.2 1985 87.9 N.A. 111.7 16.02 182.3 1986 89.1 N.A. 108.4 15.94 178.8 1987 90.5 N.A. 108.2 16.21 179.1 1988 92.0 N.A. 112.7 17.12 186.0 1989 93.5 N.A. 113.7 17.76 190.0 1990 94.2 N.A. 102.7 16.92 179.5 1991 95.3 N.A. 104.6 17.38 182.4 1992 96.4 N.A. 104.7 17.31 179.6 1993 97.7 N.A. 107.5

  18. Derived annual estimates of manufacturing energy consumption, 1974--1988. [Contains glossary

    SciTech Connect

    Not Available

    1992-08-05

    This report presents a complete series of annual estimates of purchased energy used by the manufacturing sector of the US economy, for the years 1974 to 1988. These estimates interpolate over gaps in the actual data collections, by deriving estimates for the missing years 1982--1984 and 1986--1987. For the purposes of this report, purchased'' energy is energy brought from offsite for use at manufacturing establishments, whether the energy is purchased from an energy vendor or procured from some other source. The actual data on purchased energy comes from two sources, the US Department of Commerce Bureau of the Census's Annual Survey of Manufactures (ASM) and EIA's Manufacturing Energy Consumption Survey (MECS). The ASM provides annual estimates for the years 1974 to 1981. However, in 1982 (and subsequent years) the scope of the ASM energy data was reduced to collect only electricity consumption and expenditures and total expenditures for other purchased energy. In 1985, EIA initiated the triennial MECS collecting complete energy data. The series equivalent to the ASM is referred to in the MECS as offsite-produced fuels.''

  19. China's Top-1000 Energy-Consuming Enterprises Program:Reducing Energy Consumption of the 1000 Largest Industrial Enterprises in China

    SciTech Connect

    Price, Lynn; Price, Lynn; Wang, Xuejun; Yun, Jiang

    2008-06-02

    In 2005, the Chinese government announced an ambitious goal of reducing energy consumption per unit of GDP by 20% between 2005 and 2010. One of the key initiatives for realizing this goal is the Top-1000 Energy-Consuming Enterprises program. The energy consumption of these 1000 enterprises accounted for 33% of national and 47% of industrial energy usage in 2004. Under the Top-1000 program, 2010 energy consumption targets were determined for each enterprise. The objective of this paper is to evaluate the program design and initial results, given limited information and data, in order to understand the possible implications of its success in terms of energy and carbon dioxide emissions reductions and to recommend future program modifications based on international experience with similar target-setting agreement programs. Even though the Top-1000 Program was designed and implemented rapidly, it appears that--depending upon the GDP growth rate--it could contribute to somewhere between approximately 10% and 25% of the savings required to support China's efforts to meet a 20% reduction in energy use per unit of GDP by 2010.

  20. Nonresidential-building energy-consumption survey, 1979. Final report, Part II and Part III

    SciTech Connect

    Not Available

    1981-06-01

    The Utility Survey component of the Nonresidential Building Energy Consumption Survey was designed to provide data on the quantity and costs of energy consumed during 1979 by each building represented in the Building Survey data. To this end, 13,386 consumption and cost reporting forms were mailed to 1509 companies/organizations/agencies who supplied some type of energy to the 6222 buildings represented in the data from the earlier Building Survey. Part II, Section 2 discusses the step-by-step process of building the computer and manual files that were needed in order to conduct the Utility Survey. How the files were actually used in order to implement, control, and manage the Utility Survey was also discussed. Section 3 discusses the reporting forms and the accompanying instructional material used to collect data from the energy suppliers and Section 4 discusses the various operations for implementing the data collection task. The proessing of the data is described in Section 5 and the method of keeping the data confidential is described in Section 6. Part III, Section 7 presents several analyses of the costs associated with the Interim Nonresidential Building Energy Consumption Survey. Tables included reflect costs incurred through April 25, 1981. Administrative correspondence, record sheets, and explanatory notes are included in appendices. (MCW)

  1. Wind Energy Management System Integration Project Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations

    SciTech Connect

    Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

    2010-09-01

    The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation) and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. In order to improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively, by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique

  2. USING TIME VARIANT VOLTAGE TO CALCULATE ENERGY CONSUMPTION AND POWER USE OF BUILDING SYSTEMS

    SciTech Connect

    Makhmalbaf, Atefe; Augenbroe , Godfried

    2015-12-09

    Buildings are the main consumers of electricity across the world. However, in the research and studies related to building performance assessment, the focus has been on evaluating the energy efficiency of buildings whereas the instantaneous power efficiency has been overlooked as an important aspect of total energy consumption. As a result, we never developed adequate models that capture both thermal and electrical characteristics (e.g., voltage) of building systems to assess the impact of variations in the power system and emerging technologies of the smart grid on buildings energy and power performance and vice versa. This paper argues that the power performance of buildings as a function of electrical parameters should be evaluated in addition to systems’ mechanical and thermal behavior. The main advantage of capturing electrical behavior of building load is to better understand instantaneous power consumption and more importantly to control it. Voltage is one of the electrical parameters that can be used to describe load. Hence, voltage dependent power models are constructed in this work and they are coupled with existing thermal energy models. Lack of models that describe electrical behavior of systems also adds to the uncertainty of energy consumption calculations carried out in building energy simulation tools such as EnergyPlus, a common building energy modeling and simulation tool. To integrate voltage-dependent power models with thermal models, the thermal cycle (operation mode) of each system was fed into the voltage-based electrical model. Energy consumption of systems used in this study were simulated using EnergyPlus. Simulated results were then compared with estimated and measured power data. The mean square error (MSE) between simulated, estimated, and measured values were calculated. Results indicate that estimated power has lower MSE when compared with measured data than simulated results. Results discussed in this paper will illustrate the

  3. 2016 SSL Forecast Report

    Energy.gov [DOE]

    The DOE report, Energy Savings Forecast of Solid-State Lighting in General Illumination Applications, is a biannual report which models the adoption of LEDs in the U.S. general-lighting market,...

  4. SSL Forecast Report

    Energy.gov [DOE]

    The DOE report, Energy Savings Forecast of Solid-State Lighting in General Illumination Applications, is the latest edition of a biannual report which models the adoption of LEDs in the U.S....

  5. Buildings Energy Data Book: 1.1 Buildings Sector Energy Consumption

    Buildings Energy Data Book

    1 Buildings Share of U.S. Petroleum Consumption (Percent) U.S. Petroleum Site Consumption Primary Consumption Total Buildings Industry Electric Gen. Transportation Buildings Industry Transportation (quads) 1980 9% 28% 8% 56% | 14% 31% 56% 34.2 1981 8% 26% 7% 59% | 12% 29% 59% 31.9 1982 8% 26% 5% 61% | 11% 28% 61% 30.2 1983 8% 25% 5% 62% | 12% 27% 62% 30.1 1984 9% 26% 4% 61% | 11% 27% 61% 31.1 1985 8% 25% 4% 63% | 11% 26% 63% 30.9 1986 8% 24% 5% 63% | 11% 26% 63% 32.2 1987 8% 25% 4% 63% | 11% 26%

  6. Buildings Energy Data Book: 3.1 Commercial Sector Energy Consumption

    Buildings Energy Data Book

    4 Commercial Buildings Share of U.S. Natural Gas Consumption (Percent) Site Consumption Primary Consumption Total Commercial Industry Electric Gen. Transportation Commercial Industry Transportation (quads) 1980 13% 41% 19% 3% | 18% 49% 3% 20.22 1981 13% 42% 19% 3% | 18% 49% 3% 19.74 1982 14% 39% 18% 3% | 20% 45% 3% 18.36 1983 14% 39% 17% 3% | 19% 46% 3% 17.20 1984 14% 40% 17% 3% | 19% 47% 3% 18.38 1985 14% 40% 18% 3% | 19% 46% 3% 17.70 1986 14% 40% 16% 3% | 19% 46% 3% 16.59 1987 14% 41% 17% 3% |

  7. Buildings Energy Data Book: 3.1 Commercial Sector Energy Consumption

    Buildings Energy Data Book

    5 Commercial Buildings Share of U.S. Petroleum Consumption (Percent) Site Consumption Primary Consumption Total Commercial Industry Electric Gen. Transportation Commercial Industry Transportation (quads) 1980 4% 28% 8% 56% | 6% 31% 56% 34.2 1981 4% 26% 7% 59% | 5% 29% 59% 31.9 1982 3% 26% 5% 61% | 5% 28% 61% 30.2 1983 4% 25% 5% 62% | 5% 27% 62% 30.1 1984 4% 26% 4% 61% | 5% 27% 61% 31.1 1985 3% 25% 4% 63% | 5% 26% 63% 30.9 1986 4% 24% 5% 63% | 5% 26% 63% 32.2 1987 3% 25% 4% 63% | 5% 26% 63% 32.9

  8. An analysis of residential energy consumption in a temperate climate. Volume 2

    SciTech Connect

    Clark, Y.Y.; Vincent, W.

    1987-06-01

    Electrical energy consumption data have been recorded for several hundred submetered residential structures in Middle Tennessee. All houses were constructed with a common ``energy package.`` Specifically, daily cooling usage data have been collected for 130 houses for the 1985 and 1986 cooling seasons, and monthly heating usage data for 186 houses have been recorded by occupant participation over a seven-year period. Cooling data have been analyzed using an SPSSx multiple regression analysis and results are compared to several cooling models. Heating, base, and total energy usage are also analyzed and regression correlation coefficients are determined as a function of several house parameters.

  9. Benchmarking the energy efficiency of Dutch industry: An assessment of the expected effect on energy consumption and CO2 emissions

    SciTech Connect

    Phylipsen, Dian; Blok, Kornelis; Worrell, Ernst; De Beer, Jeroen

    2002-06-01

    As part of its energy and climate policy the Dutch government has reached an agreement with the Dutch energy-intensive industry that is explicitly based on industry's relative energy efficiency performance. The energy efficiency of the Dutch industry is benchmarked against that of comparable industries in countries world-wide. In the agreement, industry is required to belong to the top-of-the-world in terms of energy efficiency. In return, the government refrains from implementing additional climate policies.This article assesses the potential effects of this agreement on energy consumption and CO2 emissions by comparing the current level of energy efficiency of the Dutch industry - including electricity production - to that of the most efficient countries and regions. At the current structure achieving the regional best practice level for the selected energy-intensive industries would result in a 5plus or minus 2 percent lower current primary energy consumption than the actual level. Most of the savings are expected in the petrochemical industry and in electricity generation. Avoided CO2 emissions would amount to 4 Mt CO2. A first estimate of the effect of the benchmarking agreement in 2012 suggests primary energy savings of 50-130 PJ or 5-10 Mt CO2 avoided compared to the estimated Business as Usual development (5-15 percent). This saving is smaller than what a continuation of the existing policies of Long Term Agreements would probably deliver.

  10. Computer usage and national energy consumption: Results from a field-metering study

    SciTech Connect

    Desroches, Louis-Benoit; Fuchs, Heidi; Greenblatt, Jeffery; Pratt, Stacy; Willem, Henry; Claybaugh, Erin; Beraki, Bereket; Nagaraju, Mythri; Price, Sarah; Young, Scott

    2014-12-01

    The electricity consumption of miscellaneous electronic loads (MELs) in the home has grown in recent years, and is expected to continue rising. Consumer electronics, in particular, are characterized by swift technological innovation, with varying impacts on energy use. Desktop and laptop computers make up a significant share of MELs electricity consumption, but their national energy use is difficult to estimate, given uncertainties around shifting user behavior. This report analyzes usage data from 64 computers (45 desktop, 11 laptop, and 8 unknown) collected in 2012 as part of a larger field monitoring effort of 880 households in the San Francisco Bay Area, and compares our results to recent values from the literature. We find that desktop computers are used for an average of 7.3 hours per day (median = 4.2 h/d), while laptops are used for a mean 4.8 hours per day (median = 2.1 h/d). The results for laptops are likely underestimated since they can be charged in other, unmetered outlets. Average unit annual energy consumption (AEC) for desktops is estimated to be 194 kWh/yr (median = 125 kWh/yr), and for laptops 75 kWh/yr (median = 31 kWh/yr). We estimate national annual energy consumption for desktop computers to be 20 TWh. National annual energy use for laptops is estimated to be 11 TWh, markedly higher than previous estimates, likely reflective of laptops drawing more power in On mode in addition to greater market penetration. This result for laptops, however, carries relatively higher uncertainty compared to desktops. Different study methodologies and definitions, changing usage patterns, and uncertainty about how consumers use computers must be considered when interpreting our results with respect to existing analyses. Finally, as energy consumption in On mode is predominant, we outline several energy savings opportunities: improved power management (defaulting to low-power modes after periods of inactivity as well as power scaling), matching the rated power

  11. Table A17. Total First Use (formerly Primary Consumption) of Energy for All P

    Energy Information Administration (EIA) (indexed site)

    Total First Use (formerly Primary Consumption) of Energy for All Purposes" " by Employment Size Categories, Industry Group, and Selected Industries, 1994" " (Estimates in Trillion Btu)" ,,,," "," Employment Size(b)" ,,,,,,,,,"RSE" "SIC"," "," "," "," "," "," "," ",1000,"Row" "Code(a)","Industry Group and

  12. Table A32. Total Consumption of Offsite-Produced Energy for Heat, Power, and

    Energy Information Administration (EIA) (indexed site)

    Consumption of Offsite-Produced Energy for Heat, Power, and" " Electricity Generation by Value of Shipment Categories, Industry Group, and" " Selected Industries, 1991" " (Estimates in Trillion Btu)" ,,,,"Value of Shipments and Receipts(b)" ,,,," (million dollars)" ,," ","-","-","-","-","-","-","RSE" ," "," ","

  13. Reduced Energy Consumption through the Development of Fuel-Flexible Gas Turbines

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    Development of Fuel-Flexible Combustion Systems Utilizing Opportunity Fuels in Gas Turbines ADVANCED MANUFACTURING OFFICE Reduced Energy Consumption through the Development of Fuel-Flexible Gas Turbines Introduction Gas turbines-heat engines that use high-temperature and high-pressure gas as the combustible fuel-are used extensively throughout U.S. industry to power industrial processes. The majority of turbines are operated using natural gas because of its availability, low cost, and

  14. New Water Booster Pump System Reduces Energy Consumption by 80% and Increases Reliability

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    BENEFITS A Motor Challeng NEW WATER BOOSTER PUMP SYSTEM REDUCES ENERGY CONSUMPTION BY 80 PERCENT AND INCREASES RELIABILITY Summary Due to major renovations at their Pontiac Operations Complex, General Motors (GM) needed to relocate the facility's city water booster pumping system. Using a systems approach and careful forethought, a highly efficient pumping system appropriate for current plant requirements was developed. Because of a sizeable decrease in the workforce and production at this

  15. Seismic energy data analysis of Merapi volcano to test the eruption time prediction using materials failure forecast method (FFM)

    SciTech Connect

    Anggraeni, Novia Antika

    2015-04-24

    The test of eruption time prediction is an effort to prepare volcanic disaster mitigation, especially in the volcano’s inhabited slope area, such as Merapi Volcano. The test can be conducted by observing the increase of volcanic activity, such as seismicity degree, deformation and SO2 gas emission. One of methods that can be used to predict the time of eruption is Materials Failure Forecast Method (FFM). Materials Failure Forecast Method (FFM) is a predictive method to determine the time of volcanic eruption which was introduced by Voight (1988). This method requires an increase in the rate of change, or acceleration of the observed volcanic activity parameters. The parameter used in this study is the seismic energy value of Merapi Volcano from 1990 – 2012. The data was plotted in form of graphs of seismic energy rate inverse versus time with FFM graphical technique approach uses simple linear regression. The data quality control used to increase the time precision employs the data correlation coefficient value of the seismic energy rate inverse versus time. From the results of graph analysis, the precision of prediction time toward the real time of eruption vary between −2.86 up to 5.49 days.

  16. Impact of conservation measures on Pacific Northwest residential energy consumption. Final report

    SciTech Connect

    Moe, R.J.; Owzarski, S.L.; Streit, L.P.

    1983-04-01

    The objective of this study was to estimate the relationship between residential space conditioning energy use and building conservation programs in the Pacific Northwest. The study was divided into two primary tasks. In the first, the thermal relationship between space conditioning energy consumption under controlled conditions and the physical characteristics of the residence was estimated. In this task, behavioral characteristics such as occupant schedules and thermostat settings were controlled in order to isolate the physical relationships. In the second task, work from the first task was used to calculate the thermal efficiency of a residence's shell. Thermal efficiency was defined as the ability of a shell to prevent escapement of heat generated within a building. The relationship between actual space conditioning energy consumption and the shell thermal efficiency was then estimated. Separate thermal equations for mobile homes, single-family residences, and multi-family residences are presented. Estimates of the relationship between winter electricity consumption for heating and the building's thermal shell efficiency are presented for each of the three building categories.

  17. Department of Energy Announces Funding to Help Consumers Better Manage Their Energy Consumption

    Energy.gov [DOE]

    New Funding Opportunity Provides More Knowledge to Consumers about their Energy Use; Could Lead to Lower Energy Bills for Consumers

  18. New Water Booster Pump System Reduces Energy Consumption by 80 Percent and Increases Reliability

    Office of Energy Efficiency and Renewable Energy (EERE)

    This case study outlines how General Motors (GM) developed a highly efficient pumping system for their Pontiac Operations Complex in Pontiac, Michigan. In short, GM was able to replace five original 60- to 100-hp pumps with three 15-hp pumps whose speed could be adjusted to meet plant requirements. As a result, the company reduced pumping system energy consumption by 80 percent (225,100 kWh per year), saving an annual $11,255 in pumping costs. With a capital investment of $44,966 in the energy efficiency portion of their new system, GM projected a simple payback of 4 years.

  19. Table 2.2 Manufacturing Energy Consumption for All Purposes, 2006 (Trillion Btu )

    Energy Information Administration (EIA) (indexed site)

    Manufacturing Energy Consumption for All Purposes, 2006 (Trillion Btu ) NAICS 1 Code Manufacturing Group Coal Coal Coke and Breeze 2 Natural Gas Distillate Fuel Oil LPG 3 and NGL 4 Residual Fuel Oil Net Electricity 5 Other 6 Shipments of Energy Sources 7 Total 8 311 Food 147 1 638 16 3 26 251 105 (s) 1,186 312 Beverage and Tobacco Products 20 0 41 1 1 3 30 11 -0 107 313 Textile Mills 32 0 65 (s) (s) 2 66 12 -0 178 314 Textile Product Mills 3 0 46 (s) 1 Q 20 (s) -0 72 315 Apparel 0 0 7 (s) (s)

  20. Whole house fenestration energy consumption as a function of variable window air leakage rates

    SciTech Connect

    Kehrli, D.

    1995-09-01

    Residential building energy consumption is dependent on many variables. The heat loss or gain attributable to fenestration products can be a significant portion of the whole building load. The fenestration industry is current developing and implementing new test methods and rating procedures to more accurately account for fenestration energy transfer. One of the tools being developed by the National Fenestration Rating Council (NFRC) is a PC-based program called Residential Fenestration (RESFEN) heating and cooling load use and costs. This paper will provide a review of the energy and cost impacts that variable air leakage rates of several types of window products can have on overall window energy usage as modeled in four typical building designs located in the US. The analysis was performed with the RESFEN software as part of an NFRC sensitivity study on this issue.

  1. Minority energy assessment report

    SciTech Connect

    Teotia, A.P.S.; Poyer, D.A.; Lampley, L.; Anderson, J.L.

    1992-12-01

    The purpose of this research is to project household energy consumption, energy expenditure, and energy expenditure as share of income for five population groups from 1991 to 2009. The approach uses the Minority Energy Assessment Model (MEAM), developed by Argonne National Laboratory for the US Department of Energy's Office of Minority Economic Impact. The MEAM provides a framework that can be used to forecast regional energy consumption and energy expenditure for majority, black, Hispanic, poor, and nonpoor households. The forecasts of key macroeconomic and energy variables used as exogenous variables in the MEAM were obtained from the Data Resources, Inc., Macromodel and Energy Model. Generally, the projections of household energy consumption, expenditure, and energy expenditure as share of income vary across population groups and census regions.

  2. A Method for Modeling Household Occupant Behavior to Simulate Residential Energy Consumption

    SciTech Connect

    Johnson, Brandon J; Starke, Michael R; Abdelaziz, Omar; Jackson, Roderick K; Tolbert, Leon M

    2014-01-01

    This paper presents a statistical method for modeling the behavior of household occupants to estimate residential energy consumption. Using data gathered by the U.S. Census Bureau in the American Time Use Survey (ATUS), actions carried out by survey respondents are categorized into ten distinct activities. These activities are defined to correspond to the major energy consuming loads commonly found within the residential sector. Next, time varying minute resolution Markov chain based statistical models of different occupant types are developed. Using these behavioral models, individual occupants are simulated to show how an occupant interacts with the major residential energy consuming loads throughout the day. From these simulations, the minimum number of occupants, and consequently the minimum number of multiple occupant households, needing to be simulated to produce a statistically accurate representation of aggregate residential behavior can be determined. Finally, future work will involve the use of these occupant models along side residential load models to produce a high-resolution energy consumption profile and estimate the potential for demand response from residential loads.

  3. Drivers of U.S. Household Energy Consumption, 1980-2009 - Energy...

    Annual Energy Outlook

    with the decomposition of energy changes into separate effects. 5Factors such as conservation effort and consumer responses to change in energy prices may also influence changes ...

  4. Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption

    Buildings Energy Data Book

    20 Site Consumption Primary Consumption Total Residential Industry Electric Gen. Transportation Residential Industry Transportation (quads) 1980 5% 28% 8% 56% | 8% 31% 56% 34.2 1981 5% 26% 7% 59% | 7% 29% 59% 31.9 1982 5% 26% 5% 61% | 6% 28% 61% 30.2 1983 4% 25% 5% 62% | 6% 27% 62% 30.1 1984 5% 26% 4% 61% | 6% 27% 61% 31.1 1985 5% 25% 4% 63% | 6% 26% 63% 30.9 1986 5% 24% 5% 63% | 6% 26% 63% 32.2 1987 5% 25% 4% 63% | 6% 26% 63% 32.9 1988 5% 24% 5% 63% | 6% 26% 63% 34.2 1989 5% 24% 5% 63% | 7% 25%

  5. S U M M A R I E S U.S. Energy Information Administration | State Energy Data 2014: Consumption

    Gasoline and Diesel Fuel Update

    3 Table C1. Energy Consumption Overview: Estimates by Energy Source and End-Use Sector, 2014 (Trillion Btu) State Total Energy b Sources End-Use Sectors a Fossil Fuels Nuclear Electric Power Renewable Energy e Net Interstate Flow of Electricity f Net Electricity Imports g Residential Commercial Industrial b Transportation Coal Natural Gas c Petroleum d Total Alabama 1,958.2 575.9 651.5 497.4 1,724.9 431.4 277.0 -475.0 0.0 378.7 262.4 848.4 468.7 Alaska 603.1 18.2 329.6 233.6 581.4 0.0 21.8 0.0

  6. Direct and indirect effect of changes in family structure and lifestyle upon energy consumption, 1950-1080

    SciTech Connect

    Stever, C.J.

    1985-01-01

    This research project examines both the direct and indirect influence of changes in family structure and lifestyle dimensions upon residential energy consumption patterns from 1950 to 1980. These relationships are investigated on a macro level using three national energy surveys administered from 1974 to 1980 and the Census Bureau and other government sources of documenting changes in social characteristics and energy consumption levels over thirty years. Stage I looks at changes in residential consumption from 1950 to 1980 and conservation behavior from 1965 to 1980. The objective of Stage II is to identify those family structure and lifestyle characteristics that constrain conservation measures in which a household engages. Stage III examines the commonly held assumption that investment in conservation equipment will result in reduced consumption. Stage IV explores the potential influence that changes in structural and lifestyle characteristics of householders may have upon average consumption levels from 1950 to 1980. The primary implications of this study are: (1) in order to obtain a complete picture of the current energy situation, it is necessary to examine consumption and conservation behavior both before and after the 1973 oil embargo, and (2) changes in social structural and lifestyle of households over time appear to have contributed as much, if not more, to reduce consumption in the late 1970s as did conscious conservation efforts by householders.

  7. Table A14. Total First Use (formerly Primary Consumption) of Energy for All P

    Energy Information Administration (EIA) (indexed site)

    4. Total First Use (formerly Primary Consumption) of Energy for All Purposes" " by Value of Shipment Categories, Industry Group, and Selected Industries, 1994" " (Estimates in Trillion Btu)" ,,,," Value of Shipments and Receipts(b)" ,,,," "," (million dollars)" ,,,,,,,,,"RSE" "SIC"," "," "," "," "," "," "," ",500,"Row"," ","

  8. Table A30. Total Primary Consumption of Energy for All Purposes by Value of

    Energy Information Administration (EIA) (indexed site)

    0. Total Primary Consumption of Energy for All Purposes by Value of" "Shipment Categories, Industry Group, and Selected Industries, 1991" " (Estimates in Trillion Btu)" ,,,," Value of Shipments and Receipts(b)" ,,,," ","(million dollars)" ,,,"-","-","-","-","-","-","RSE" "SIC"," "," "," "," "," ","

  9. Table A33. Total Primary Consumption of Energy for All Purposes by Employment

    Energy Information Administration (EIA) (indexed site)

    Primary Consumption of Energy for All Purposes by Employment" " Size Categories, Industry Group, and Selected Industries, 1991 (Continued)" " (Estimates in Trillion Btu)" ,,,,,"Employment Size" ,,,"-","-","-","-","-","-","RSE" "SIC"," "," "," "," "," "," ",,500,"Row" "Code(a)","Industry Groups and

  10. Table A9. Total Primary Consumption of Energy for All Purposes by Census

    Energy Information Administration (EIA) (indexed site)

    A9. Total Primary Consumption of Energy for All Purposes by Census" " Region and Economic Characteristics of the Establishment, 1991" " (Estimates in Btu or Physical Units)" ,,,,,,,,"Coke" " "," ","Net","Residual","Distillate","Natural Gas(d)"," ","Coal","and Breeze"," ","RSE" " ","Total","Electricity(b)","Fuel

  11. "Table 19. Total Delivered Industrial Energy Consumption, Projected vs. Actual"

    Energy Information Administration (EIA) (indexed site)

    Total Delivered Industrial Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",25.43,25.904,26.303,26.659,26.974,27.062,26.755,26.598,26.908,27.228,27.668,28.068,28.348,28.668,29.068,29.398,29.688,30.008 "AEO

  12. Buildings Energy Data Book: 8.1 Buildings Sector Water Consumption

    Buildings Energy Data Book

    1 Buildings Sector Water Consumption March 2012 8.1.2 Average Energy Intensity of Public Water Supplies by Location (kWh per Million Gallons) Location United States (2) 627 437 1,363 United States (3) 65 (6) 1,649 Northern California Indoor 111 1,272 1,911 Northern California Outdoor 111 1,272 0 Southern California Indoor (5) 111 1,272 1,911 Southern California Outdoor 111 1,272 0 Iowa (6) 380 1,570 Massachusetts (6) (6) 1,750 Wisconsin Class AB (4) - - Wisconsin Class C (4) - - Wisconsin Class

  13. DOE/EIA-0555(95)/2 Energy Consumption Series Measuring Energy...

    Energy Information Administration (EIA) (indexed site)

    is possible to separate the effects unrelated to energy efficiency. This approach can be thought of as a "top-down" approach. It is like peeling away all the effects until energy...

  14. U.S. gasoline consumption highest in 8 years

    Energy Information Administration (EIA) (indexed site)

    U.S. gasoline consumption highest in 8 years U.S. gasoline consumption this year is expected to be at the highest level since the record fuel demand seen back in 2007 as lower gasoline prices and more people finding jobs means more sales at the gasoline pump. In its new monthly forecast, the U.S. Energy Information Administration said gasoline consumption increased by 2.7% during the first eight months of 2015 and should rise by an average of 190,000 barrels per day this year to 9.1 million

  15. Department of Energy award DE-SC0004164 Climate and National Security: Securing Better Forecasts

    SciTech Connect

    Reno Harnish

    2011-08-16

    The Climate and National Security: Securing Better Forecasts symposium was attended by senior policy makers and distinguished scientists. The juxtaposition of these communities was creative and fruitful. They acknowledged they were speaking past each other. Scientists were urged to tell policy makers about even improbable outcomes while articulating clearly the uncertainties around the outcomes. As one policy maker put it, we are accustomed to making these types of decisions. These points were captured clearly in an article that appeared on the New York Times website and can be found with other conference materials most easily on our website, www.scripps.ucsd.edu/cens/. The symposium, generously supported by the NOAA/JIMO, benefitted the public by promoting scientifically informed decision making and by the transmission of objective information regarding climate change and national security.

  16. U.S. primary energy consumption by source and sector, 2015

    Energy Information Administration (EIA) (indexed site)

    33 35 24 9 53 100 14 9 <1 91 28 72 23 4 1 92 3 5 44 39 7 11 76 1 9 1 26 37 13 22 petroleum 1 35.4 (36%) sector natural gas 2 28.3 (29%) coal 3 15.7 (16%) renewable energy 4 9.7 (10%) nuclear electric power 8.3 (9%) source percent of sources percent of sectors industrial 5 21.2 (22%) residential and commercial 6 10.6 (11%) electric power 7 38.2 (39%) 15 transportation 27.6 (28%) U.S. primary energy consumption by source and sector, 2015 Total = 97.7 quadrillion British thermal units (Btu) 1

  17. EIA lowers forecast for summer gasoline prices

    Energy Information Administration (EIA) (indexed site)

    EIA lowers forecast for summer gasoline prices U.S. gasoline prices are expected to be ... according to the new monthly forecast from the U.S. Energy Information Administration. ...

  18. Plant Wide Assessment of Energy Usage Utilizing SitEModelling as a Tool for Optimizing Energy Consumption

    SciTech Connect

    Ralf Janowsky, Ph.D.; Tracey Mole, Ph.D.

    2007-12-31

    The Evonik Degussa Corporation is the global market leader in the specialty chemicals industry. Innovative products and system solutions make an indispensable contribution to our customers' success. We refer to this as "creating essentials". In fiscal 2004, Degussa's 45,000 employees worldwide generated sales of 11.2 billion euros and operating profits (EBIT) of 965 million euros. Evonik Degussa Corporation has performed a plant wide energy usage assessment at the Mapleton, Illinois facility, which consumed 1,182,330 MMBTU in 2003. The purpose of this study was to identify opportunities for improvement regarding the plant’s utility requirements specific to their operation. The production is based mainly on natural gas usage for steam, process heating and hydrogen production. The current high price for natural gas in the US is not very competitive compared to other countries. Therefore, all efforts must be taken to minimize the utility consumption in order to maximize market position and minimize fixed cost increases due to the rising costs of energy. The main objective of this plant wide assessment was to use a methodology called Site Energy Modelling (SitE Modelling) to identify areas of potential improvement for energy savings, either in implementing a single process change or in changing the way different processes interact with each other. The overall goal was to achieve energy savings of more than 10% compared to the 2003 energy figures of the Mapleton site. The final savings breakdown is provided below: - 4.1% savings for steam generation and delivery These savings were accomplished through better control schemes, more constant and optimized loading of the boilers and increased boiler efficiency through an advanced control schemes. - 1.6% savings for plant chemical processing These saving were accomplished through optimized processing heating efficiency and batch recipes, as well as an optimized production schedule to help equalize the boiler load (e

  19. Buildings Energy Data Book: 1.1 Buildings Sector Energy Consumption

    Buildings Energy Data Book

    0 Buildings Share of U.S. Natural Gas Consumption (Percent) Total Buildings Industry Electric Gen. Transportation Buildings Industry Transportation 1980 37% 41% 19% 3% | 48% 49% 3% 20.22 1981 36% 42% 19% 3% | 48% 49% 3% 19.74 1982 40% 39% 18% 3% | 51% 45% 3% 18.36 1983 40% 39% 17% 3% | 51% 46% 3% 17.20 1984 39% 40% 17% 3% | 50% 47% 3% 18.38 1985 39% 40% 18% 3% | 51% 46% 3% 17.70 1986 41% 40% 16% 3% | 51% 46% 3% 16.59 1987 39% 41% 17% 3% | 50% 47% 3% 17.63 1988 40% 42% 15% 3% | 50% 47% 3% 18.44

  20. Buildings Energy Data Book: 1.1 Buildings Sector Energy Consumption

    Buildings Energy Data Book

    9 Buildings Share of U.S. Electricity Consumption (Percent) Total Industry Transportation Total | (quads) 1980 34% 27% | 61% 39% 0% 100% | 7.15 1981 34% 28% | 61% 38% 0% 100% | 7.33 1982 35% 29% | 64% 36% 0% 100% | 7.12 1983 35% 29% | 64% 36% 0% 100% | 7.34 1984 34% 29% | 63% 37% 0% 100% | 7.80 1985 34% 30% | 64% 36% 0% 100% | 7.93 1986 35% 30% | 65% 35% 0% 100% | 8.08 1987 35% 30% | 65% 35% 0% 100% | 8.38 1988 35% 30% | 65% 35% 0% 100% | 8.80 1989 34% 31% | 65% 35% 0% 100% | 9.03 1990 34% 31% |

  1. Buildings Energy Data Book: 2.1 Residential Sector Energy Consumption

    Buildings Energy Data Book

    8 2009 Annual Natural Gas Consumption per Appliance by Census Division Census Division New England Middle Atlantic East North Central West North Central South Atlantic East South Central West South Central Mountain Pacific United States Average Total Source(s): 515,657 208,173 43,648 42,723 90,171 American Gas Association, Residential Natural Gas Market Survey, Jan. 2011, Table 10-1. 61,928 23,005 5,238 5,135 10,270 44,675 20,232 3,286 3,286 29,064 33,891 24,648 3,595 3,081 5,135 58,334 26,702

  2. Buildings Energy Data Book: 6.1 Electric Utility Energy Consumption

    Buildings Energy Data Book

    1 Buildings Share of U.S. Electricity Consumption/Sales (Percent) Buildings Delivered Total | Total Industry Transportation Total (10^15 Btu) 1980 | 60.9% 38.9% 0.2% 100% | 7.15 1981 | 61.4% 38.5% 0.1% 100% | 7.33 1982 | 64.1% 35.7% 0.2% 100% | 7.12 1983 | 63.8% 36.1% 0.2% 100% | 7.34 1984 | 63.2% 36.7% 0.2% 100% | 7.80 1985 | 63.8% 36.0% 0.2% 100% | 7.93 1986 | 64.8% 35.1% 0.2% 100% | 8.08 1987 | 64.9% 34.9% 0.2% 100% | 8.38 1988 | 65.0% 34.8% 0.2% 100% | 8.80 1989 | 64.8% 35.0% 0.2% 100% |

  3. The Value of Wind Power Forecasting

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Wind Power Forecasting Preprint Debra Lew and Michael Milligan National Renewable Energy Laboratory Gary Jordan and Richard Piwko GE Energy Presented at the 91 st American ...

  4. A survey on wind power ramp forecasting.

    SciTech Connect

    Ferreira, C.; Gama, J.; Matias, L.; Botterud, A.; Wang, J.

    2011-02-23

    The increasing use of wind power as a source of electricity poses new challenges with regard to both power production and load balance in the electricity grid. This new source of energy is volatile and highly variable. The only way to integrate such power into the grid is to develop reliable and accurate wind power forecasting systems. Electricity generated from wind power can be highly variable at several different timescales: sub-hourly, hourly, daily, and seasonally. Wind energy, like other electricity sources, must be scheduled. Although wind power forecasting methods are used, the ability to predict wind plant output remains relatively low for short-term operation. Because instantaneous electrical generation and consumption must remain in balance to maintain grid stability, wind power's variability can present substantial challenges when large amounts of wind power are incorporated into a grid system. A critical issue is ramp events, which are sudden and large changes (increases or decreases) in wind power. This report presents an overview of current ramp definitions and state-of-the-art approaches in ramp event forecasting.

  5. July 2016 Systems Integration Solar Forecasting:

    Office of Energy Efficiency and Renewable Energy (EERE) (indexed site)

    2016 Systems Integration Solar Forecasting: Maximizing its value for grid integration Introduction The forecasting of power generated by variable energy resources such as wind and solar has been the focus of academic and industrial research and development for as long as significant amounts of these renewable energy resources have been connected to the electric grid. The progress of forecasting capabilities has largely followed the penetration of the respective resources, with wind forecasting

  6. U.S. Energy Information Administration | State Energy Data 2014: Consumption

    Gasoline and Diesel Fuel Update

    5 The real gross domestic product (GDP) data used in the U.S. Energy Information Administration State Energy Data System (SEDS) to calculate total energy consumed per chained (2009) dollar of output are shown in Tables D1 and D2. The data are the U.S. Department of Commerce, Bureau of Economic Analysis (BEA), real GDP estimates by state, beginning in 1997. The estimates are released in June of each year. For the United States, the national real GDP series from the National In- come and Product

  7. Reducing Idle Power Consumption in Office Spaces Saves U.S. Navy in Energy Costs (Fact Sheet), NREL (National Renewable Energy Laboratory)

    U.S. Department of Energy (DOE) - all webpages (Extended Search)

    Reducing Idle Power Consumption in Office Spaces Saves U.S. Navy in Energy Costs As part of a two-year project to demonstrate energy efficiency measures, renewable energy generation, and energy systems integration, the National Renewable Energy Laboratory (NREL) has identified advanced plug load controls as a promising technology for reducing energy use and related costs in the U.S. Navy's Naval Facilities Engineering Command (NAVFAC) office spaces. The demonstration was one of eight

  8. Solar Forecasting

    Energy.gov [DOE]

    On December 7, 2012, DOE announced $8 million to fund two solar projects that are helping utilities and grid operators better forecast when, where, and how much solar power will be produced at U.S....

  9. DOE Announces Webinars on Real Time Energy Management, Solar Forecasting Metrics, and More

    Energy.gov [DOE]

    EERE offers webinars to the public on a range of subjects, from adopting the latest energy efficiency and renewable energy technologies to training for the clean energy workforce. Webinars are free; however, advanced registration is typically required. You can also watch archived webinars and browse previously aired videos, slides, and transcripts.

  10. TRANSPORTATION ENERGY FUTURES - Combining Strategies for Deep Reductions in Energy Consumption and GHG Emissions

    SciTech Connect

    Anya Breitenbach

    2013-03-15

    This fact sheet summarizes actions in the areas of light-duty vehicle, non-light-duty vehicle, fuel, and transportation demand that show promise for deep reductions in energy use.

  11. U.S. Energy Information Administration | State Energy Data 2014: Consumption

    Gasoline and Diesel Fuel Update

    Destination State ____________________________________________________________________________________________________ 1 U.S. Energy Information Administration | Quarterly Coal Distribution Report 1st Quarter 2013 Alabama _____________________________________________________________________________________________________________________________________ Table DS-1. Domestic Coal Distribution, by Destination State, 1st Quarter 2013 Destination: Alabama (thousand short tons) Coal Origin State

  12. Impacts of Climate Change on Energy Consumption and Peak Demand in Buildings: A Detailed Regional Approach

    SciTech Connect

    Dirks, James A.; Gorrissen, Willy J.; Hathaway, John E.; Skorski, Daniel C.; Scott, Michael J.; Pulsipher, Trenton C.; Huang, Maoyi; Liu, Ying; Rice, Jennie S.

    2015-01-01

    This paper presents the results of numerous commercial and residential building simulations, with the purpose of examining the impact of climate change on peak and annual building energy consumption over the portion of the Eastern Interconnection (EIC) located in the United States. The climate change scenario considered (IPCC A2 scenario as downscaled from the CASCaDE data set) has changes in mean climate characteristics as well as changes in the frequency and duration of intense weather events. This investigation examines building energy demand for three annual periods representative of climate trends in the CASCaDE data set at the beginning, middle, and end of the century--2004, 2052, and 2089. Simulations were performed using the Building ENergy Demand (BEND) model which is a detailed simulation platform built around EnergyPlus. BEND was developed in collaboration with the Platform for Regional Integrated Modeling and Analysis (PRIMA), a modeling framework designed to simulate the complex interactions among climate, energy, water, and land at decision-relevant spatial scales. Over 26,000 building configurations of different types, sizes, vintages, and, characteristics which represent the population of buildings within the EIC, are modeled across the 3 EIC time zones using the future climate from 100 locations within the target region, resulting in nearly 180,000 spatially relevant simulated demand profiles for each of the 3 years. In this study, the building stock characteristics are held constant based on the 2005 building stock in order to isolate and present results that highlight the impact of the climate signal on commercial and residential energy demand. Results of this analysis compare well with other analyses at their finest level of specificity. This approach, however, provides a heretofore unprecedented level of specificity across multiple spectrums including spatial, temporal, and building characteristics. This capability enables the ability to

  13. Energy-consumption and carbon-emission analysis of vehicle and component manufacturing.

    SciTech Connect

    Sullivan, J. L.; Burnham, A.; Wang, M.; Energy Systems

    2010-10-12

    A model is presented for calculating the environmental burdens of the part manufacturing and vehicle assembly (VMA) stage of the vehicle life cycle. The approach is bottom-up, with a special focus on energy consumption and CO{sub 2} emissions. The model is applied to both conventional and advanced vehicles, the latter of which include aluminum-intensive, hybrid electric, plug-in hybrid electric and all-electric vehicles. An important component of the model, a weight-based distribution function of materials and associated transformation processes (casting, stamping, etc.), is developed from the United States Council for Automotive Research Generic Vehicle Life Cycle Inventory Study. As the approach is bottom-up, numerous transformation process data and plant operational data were extracted from the literature for use in representing the many operations included in the model. When the model was applied to conventional vehicles, reliable estimates of cumulative energy consumption (34 GJ/vehicle) and CO{sub 2} emission (2 tonnes/vehicle) were computed for the VMA life-cycle stage. The numerous data sets taken from the literature permitted the development of some statistics on model results. Because the model explicitly includes a greater coverage of relevant manufacturing processes than many earlier studies, our energy estimates are on the higher end of previously published values. Limitations of the model are also discussed. Because the material compositions of conventional vehicles within specific classes (cars, light duty trucks, etc.) are sensibly constant on a percent-by-weight basis, the model can be reduced to a simple linear form for each class dependent only on vehicle weight. For advanced vehicles, the material/transformation process distribution developed above needs to be adjusted for different materials and components. This is particularly so for aluminum-intensive and electric-drive vehicles. In fact, because of their comparatively high manufacturing

  14. Buildings Energy Data Book: 1.1 Buildings Sector Energy Consumption

    Buildings Energy Data Book

    2 Buildings Share of U.S. Petroleum Consumption (Million Barrels per Day) Buildings Residential Commercial Total Industry Transportation Total 1980 2.62 2.01 l 4.63 10.55 19.01 34.19 1981 2.26 1.73 l 3.98 9.13 18.81 31.93 1982 1.96 1.49 l 3.45 8.35 18.42 30.23 1983 1.87 1.61 l 3.48 7.97 18.60 30.05 1984 1.95 1.60 l 3.55 8.48 19.02 31.05 1985 1.92 1.40 l 3.32 8.13 19.47 30.92 1986 2.03 1.60 l 3.62 8.39 20.18 32.20 1987 2.04 1.51 l 3.54 8.50 20.82 32.86 1988 2.20 1.57 l 3.77 8.88 21.57 34.22 1989

  15. Buildings Energy Data Book: 6.1 Electric Utility Energy Consumption

    Buildings Energy Data Book

    3 U.S. Electricity Generation Input Fuel Consumption (Quadrillion Btu) Renewables Growth Rate Hydro. Oth(2) Total Nuclear Other (3) Total 2010-Year 1980 2.87 0.06 2.92 2.74 (1) 24.32 1981 2.72 0.06 2.79 3.01 (1) 24.49 1982 3.23 0.05 3.29 3.13 (1) 23.95 1983 3.49 0.07 3.56 3.20 (1) 24.60 1984 3.35 0.09 3.44 3.55 (1) 25.59 1985 2.94 0.11 3.05 4.08 (1) 26.09 1986 3.04 0.12 3.16 4.38 (1) 26.22 1987 2.60 0.13 2.73 4.75 (1) 26.94 1988 2.30 0.12 2.43 5.59 (1) 28.27 1989 2.81 0.41 3.22 5.60 (1) 29.88

  16. Transportation Energy Futures- Combining Strategies for Deep Reductions in Energy Consumption and GHG Emissions

    Energy.gov [DOE]

    Transportation currently accounts for 71% of total U.S. petroleum use and 33% of the nation's total carbon emissions. The TEF project explores how combining multiple strategies could reduce GHG emissions and petroleum use by 80%. Researchers examined four key areas – lightduty vehicles, non-light-duty vehicles, fuels, and transportation demand – in the context of the marketplace, consumer behavior, industry capabilities, technology and the energy and transportation infrastructure. The TEF reports support DOE long-term planning. The reports provide analysis to inform decisions about transportation energy research investments, as well as the role of advanced transportation energy technologies and systems in the development of new physical, strategic, and policy alternatives.

  17. Buildings Energy Data Book: 4.1 Federal Buildings Energy Consumption

    Buildings Energy Data Book

    4 Federal Agency Progress Toward the Renewable Energy Goal (Trillion Btu) (1) Total Renewable Energy Usage DOD EPA (2) DOE GSA NASA DOI Others All Agencies Note(s): Source(s): Total Facility RE as % of Electricity Use Electricity Use 5.6 101.2 6% 0.7 0.4 154% 0.7 16.7 4% 0.8 10.0 8% 0.2 5.5 4% 0.4 2.1 18% 1.1 56.5 2% 9.5 192.8 5% 1) In July 2000, in accordance with Section 503 of Executive Order 13123, the Secretary of Energy approved a goal that the equivalent of 2.5 percent of electricity

  18. "Table 17. Total Delivered Residential Energy Consumption, Projected vs. Actual"

    Energy Information Administration (EIA) (indexed site)

    Total Delivered Residential Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",10.31,10.36,10.36,10.37,10.38,10.4,10.4,10.41,10.43,10.43,10.44,10.45,10.46,10.49,10.51,10.53,10.56,10.6 "AEO 1995",,10.96,10.8,10.81,10.81,10.79,10.77,10.75,10.73,10.72,10.7,10.7,10.69,10.7,10.72,10.75,10.8,10.85 "AEO

  19. "Table 18. Total Delivered Commercial Energy Consumption, Projected vs. Actual"

    Energy Information Administration (EIA) (indexed site)

    Total Delivered Commercial Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",6.82,6.87,6.94,7,7.06,7.13,7.16,7.22,7.27,7.32,7.36,7.38,7.41,7.45,7.47,7.5,7.51,7.55 "AEO 1995",,6.94,6.9,6.95,6.99,7.02,7.05,7.08,7.09,7.11,7.13,7.15,7.17,7.19,7.22,7.26,7.3,7.34 "AEO

  20. "Table 20. Total Delivered Transportation Energy Consumption, Projected vs. Actual"

    Energy Information Administration (EIA) (indexed site)

    Total Delivered Transportation Energy Consumption, Projected vs. Actual" "Projected" " (quadrillion Btu)" ,1993,1994,1995,1996,1997,1998,1999,2000,2001,2002,2003,2004,2005,2006,2007,2008,2009,2010,2011,2012,2013 "AEO 1994",23.62,24.08,24.45,24.72,25.06,25.38,25.74,26.16,26.49,26.85,27.23,27.55,27.91,28.26,28.61,28.92,29.18,29.5 "AEO 1995",,23.26,24.01,24.18,24.69,25.11,25.5,25.86,26.15,26.5,26.88,27.28,27.66,27.99,28.25,28.51,28.72,28.94 "AEO