National Library of Energy BETA

Sample records for baseline household consumption

  1. Household Vehicles Energy Consumption 1991

    U.S. 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...

  2. Household Vehicles Energy Consumption 1991

    U.S. 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...

  3. Household Vehicles Energy Consumption 1991

    U.S. 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) . . . . . . . . ....

  4. Household vehicles energy consumption 1994

    SciTech Connect (OSTI)

    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.

  5. Household energy consumption and expenditures 1987

    SciTech Connect (OSTI)

    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.

  6. Household energy consumption and expenditures, 1990

    SciTech Connect (OSTI)

    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.

  7. Household energy consumption and expenditures 1993

    SciTech Connect (OSTI)

    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.

  8. Household Vehicles Energy Consumption 1991

    U.S. 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...

  9. Household energy consumption and expenditures, 1987

    SciTech Connect (OSTI)

    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. Household Vehicles Energy Consumption 1991

    U.S. 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...

  11. Household Energy Consumption Segmentation Using Hourly Data

    SciTech Connect (OSTI)

    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.

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

    SciTech Connect (OSTI)

    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.

  13. Projecting household energy consumption within a conditional demand framework

    SciTech Connect (OSTI)

    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).

  14. Projecting household energy consumption within a conditional demand framework

    SciTech Connect (OSTI)

    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).

  15. A Glance at China’s Household Consumption

    SciTech Connect (OSTI)

    Shui, Bin

    2009-10-01

    Known for its scale, China is the most populous country with the world’s third largest economy. In the context of rising living standards, a relatively lower share of household consumption in its GDP, a strong domestic market and globalization, China is witnessing an unavoidable increase in household consumption, related energy consumption and carbon emissions. Chinese policy decision makers and researchers are well aware of these challenges and keen to promote green lifestyles. China has developed a series of energy policies and programs, and launched a wide-range social marketing activities to promote energy conservation.

  16. Household Vehicles Energy Consumption 1994 - Appendix C

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

    SciTech Connect (OSTI)

    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. Table 2.5 Household Energy Consumption and Expenditures by End...

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

    5 Household 1 Energy Consumption and Expenditures by End Use, Selected Years, 1978-2005 Year Space ... 3 Fuel Oil 4 LPG 5 Total Electricity 3 Natural Gas Elec- tricity 3 ...

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

    U.S. 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 Information Administration | Drivers of U.S. Household Energy Consumption, 1980-2009 i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any

  20. A Method for Modeling Household Occupant Behavior to Simulate Residential Energy Consumption

    SciTech Connect (OSTI)

    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.

  1. Residential energy consumption across different population groups: Comparative analysis for Latino and non-Latino households in U.S.A.

    SciTech Connect (OSTI)

    Poyer, D.A.; Teotia, A.P.S.; Henderson, L.

    1998-05-01

    Residential energy cost, an important part of the household budget, varies significantly across different population groups. In the United States, researchers have conducted many studies of household fuel consumption by fuel type -- electricity, natural gas, fuel oil, and liquefied petroleum gas (LPG) -- and by geographic areas. The results of past research have also demonstrated significant variation in residential energy use across various population groups, including white, black, and Latino. However, research shows that residential energy demand by fuel type for Latinos, the fastest-growing population group in the United States, has not been explained by economic and noneconomic factors in any available statistical model. This paper presents a discussion of energy demand and expenditure patterns for Latino and non-Latino households in the United States. The statistical model developed to explain fuel consumption and expenditures for Latino households is based on Stone and Geary`s linear expenditure system model. For comparison, the authors also developed models for energy consumption in non-Latino, black, and nonblack households. These models estimate consumption of and expenditures for electricity, natural gas, fuel oil, and LPG by various households at the national level. The study revealed significant variations in the patterns of fuel consumption for Latinos and non-Latinos. The model methodology and results of this research should be useful to energy policymakers in government and industry, researchers, and academicians who are concerned with economic and energy issues related to various population groups.

  2. Survey Consumption

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

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

  3. EIA - Household Transportation report: Household Vehicles Energy...

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

    logo printer-friendly version logo for Portable Document Format file Household Vehicles Energy Consumption 1994 August 1997 Release Next Update: EIA has discontinued this series....

  4. Table 2.4 Household Energy Consumption by Census Region, Selected Years, 1978-2009 (Quadrillion Btu, Except as Noted)

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

    Household 1 Energy Consumption by Census Region, Selected Years, 1978-2009 (Quadrillion Btu, Except as Noted) Census Region 2 1978 1979 1980 1981 1982 1984 1987 1990 1993 1997 2001 2005 2009 United States Total (does not include wood) 10.56 9.74 9.32 9.29 8.58 9.04 9.13 9.22 10.01 10.25 9.86 10.55 10.18 Natural Gas 5.58 5.31 4.97 5.27 4.74 4.98 4.83 4.86 5.27 5.28 4.84 4.79 4.69 Electricity 3 2.47 2.42 2.48 2.42 2.35 2.48 2.76 3.03 3.28 3.54 3.89 4.35 4.39 Distillate Fuel Oil and Kerosene 2.19

  5. Consumption

    U.S. 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...

  6. Consumption

    U.S. 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...

  7. Consumption

    U.S. 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...

  8. Consumption

    U.S. 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...

  9. Consumption

    U.S. 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...

  10. Consumption

    U.S. 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...

  11. Consumption

    U.S. 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...

  12. Consumption

    U.S. 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...

  13. Consumption

    U.S. 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...

  14. Consumption

    U.S. 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...

  15. Consumption

    U.S. 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...

  16. Consumption

    U.S. 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...

  17. Consumption

    U.S. 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...

  18. Consumption

    U.S. 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...

  19. Consumption

    U.S. 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...

  20. Consumption

    U.S. 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...

  1. Consumption

    U.S. 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...

  2. Consumption

    U.S. 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...

  3. Consumption

    U.S. 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...

  4. Consumption

    U.S. 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...

  5. Energy Information Administration/Household Vehicles Energy Consumptio...

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

    , Energy Information AdministrationHousehold Vehicles Energy Consumption 1994 ix Household Vehicles Energy Consumption 1994 presents statistics about energy-related...

  6. Consumption

    U.S. 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...

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

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

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

  8. US ESC TN Site Consumption

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

    than the U.S. average. * Average electricity consumption for Tennessee households is 33% ... CONSUMPTION BY END USE Compared to other areas of the United States, the warmer ...

  9. Housing characteristics, 1987: Residential Energy Consumption Survey

    SciTech Connect (OSTI)

    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. Household Vehicles Energy Consumption 1991

    U.S. 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...

  11. Household Vehicles Energy Consumption 1991

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

    Matching: A model-based procedure used to impute for item nonresponse. This method uses logistic models to compute predicted means that are used to statistically match each...

  12. Household Vehicles Energy Consumption 1991

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

    were imputed as disposed vehicles. To impute vehicle stock changes in the 1991 RTECS, logistic regression equations were used to compute a predicted probability (or propensity)...

  13. Household Vehicles Energy Consumption 1991

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

    production vehicles in order to assess compliance with Corporate Average Fuel Economy (CAFE) standards. The EPA Composite MPG is based on the assumption of a "typical" vehicle-use...

  14. Household Vehicles Energy Consumption 1991

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

    more fuel-efficient vehicles, and the implementation of Corporate Average Fuel Economy (CAFE) 6 standards. Figure 13. Average Fuel Efficiency of All Vehicles, by Model Year 6...

  15. Household Vehicles Energy Consumption 1991

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

    a comparison between the 1991 and previous years RTECS designs; (2) the sample design; (3) the data-collection procedures; (4) the Vehicle Identification Number (VIN); (5)...

  16. Household Vehicles Energy Consumption 1994

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

    DC, October 1995), Table DL-1B. 5. "Chained dollars" is a measure used to express real prices. Real prices are those that have been adjusted to remove the effect of changes...

  17. US SoAtl GA Site Consumption

    Gasoline and Diesel Fuel Update (EIA)

    household averages. * Per household electricity consumption in Georgia is among the highest in ... CONSUMPTION BY END USE Georgia is one of the few states where at least 30% of ...

  18. The impact of rising energy prices on household energy consumption and expenditure patterns: The Persian Gulf crisis as a case example

    SciTech Connect (OSTI)

    Henderson, L.J. ); Poyer, D.A.; Teotia, A.P.S. . Energy Systems Div.)

    1992-09-01

    The Iraqi invasion of Kuwait and the subsequent war between Iraq and an international alliance led by the United States triggered immediate increases in world oil prices. Increases in world petroleum prices and in US petroleum imports resulted in higher petroleum prices for US customers. In this report, the effects of the Persian Gulf War and its aftermath are used to demonstrate the potential impacts of petroleum price changes on majority, black, and Hispanic households, as well as on poor and nonpoor households. The analysis is done by using the Minority Energy Assessment Model developed by Argonne National Laboratory for the US Department of Energy (DOE). The differential impacts of these price increases and fluctuations on poor and minority households raise significant issues for a variety of government agencies, including DOE. Although the Persian Gulf crisis is now over and world oil prices have returned to their prewar levels, the differential impacts of rising energy prices on poor and minority households as a result of any future crisis in the world oil market remains a significant long-term issue.

  19. Determinants of Household Use of Selected Energy Star Appliances - Energy

    Gasoline and Diesel Fuel Update (EIA)

    Information Administration Determinants of Household Use of Selected Energy Star Appliances Release date: May 25, 2016 Introduction According to the 2009 Residential Energy Consumption Survey (RECS), household appliances1accounted for 35% of U.S. household energy consumption, up from 24% in 1993. Thus, improvements in the energy performance of residential appliances as well as increases in the use of more efficient appliances can be effective in reducing household energy consumption and

  20. DOETEIAO32l/2 Residential Energy Consumption Survey; Consumption

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

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

  1. US ENC IL Site Consumption

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

    electricity consumption in the state low relative to other parts of the U.S. * Over 80% of Illinois households use natural gas as their main space heating fuel. CONSUMPTION BY END ...

  2. US ESC TN Site Consumption

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

    ESC TN Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US ESC TN Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US ESC TN Site Consumption kilowatthours $0 $400 $800 $1,200 $1,600 US ESC TN Expenditures dollars ELECTRICITY ONLY average per household * Tennessee households consume an average of 79 million Btu per year, about 12% less than the U.S. average. * Average electricity consumption for Tennessee households is 33%

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

    Open Energy Info (EERE)

    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...

  4. Microsoft Word - Household Energy Use CA

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

    0 20 40 60 80 100 US PAC CA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US PAC CA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US PAC CA Expenditures dollars ELECTRICITY ONLY average per household  California households use 62 million Btu of energy per home, 31% less than the U.S. average. The lower than average site

  5. Microsoft Word - Household Energy Use CA

    Gasoline and Diesel Fuel Update (EIA)

    0 20 40 60 80 100 US PAC CA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US PAC CA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US PAC CA Expenditures dollars ELECTRICITY ONLY average per household  California households use 62 million Btu of energy per home, 31% less than the U.S. average. The lower than average site

  6. Household magnets

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

    Household magnets Chances are very good that you have experimented with magnets. People have been fascinated with magnetism for thousands of years. As familiar to us as they may be, magnets still have some surprises for us. Here is a small collection of some of our favorite magnet experiments. What happens when we break a magnet in half? Radio Shack sells cheap ceramic magnets in several shapes. Get a ring shaped magnet and break it with pliers or a tap with a hammer. Try to put it back

  7. US Mnt(N) CO Site Consumption

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

    gas prices in the state. * Average electricity consumption per household is lower than most ... CONSUMPTION BY END USE Since the weather in Colorado is cooler than other areas of ...

  8. NREL: Climate Neutral Research Campuses - Determine Baseline Energy

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

    Consumption Determine Baseline Energy Consumption To create a climate action plan for your research campus, begin by determining current energy consumption and the resulting greenhouse gas emissions. You can then break down emissions by sector. It important to understand the following at the beginning: The Importance of a Baseline "The baseline inventory also provides a common data set for establishing benchmarks and priorities during the strategic planning stage and a means for

  9. Energy Intensity Baselining and Tracking Guidance | Department of Energy

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

    Technical Assistance » Better Plants » Energy Intensity Baselining and Tracking Guidance Energy Intensity Baselining and Tracking Guidance The Energy Intensity Baselining and Tracking Guidance for the Better Buildings, Better Plants Program helps companies meet the program's reporting requirements by describing the steps necessary to develop an energy consumption and energy intensity baseline and calculating consumption and intensity changes over time. Most of the calculation steps described

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

    Buildings Energy Data Book [EERE]

    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 ...

  11. ASSESSMENT OF HOUSEHOLD CARBON FOOTPRINT REDUCTION POTENTIALS

    SciTech Connect (OSTI)

    Kramer, Klaas Jan; Homan, Greg; Brown, Rich; Worrell, Ernst; Masanet, Eric

    2009-04-15

    The term ?household carbon footprint? refers to the total annual carbon emissions associated with household consumption of energy, goods, and services. In this project, Lawrence Berkeley National Laboratory developed a carbon footprint modeling framework that characterizes the key underlying technologies and processes that contribute to household carbon footprints in California and the United States. The approach breaks down the carbon footprint by 35 different household fuel end uses and 32 different supply chain fuel end uses. This level of end use detail allows energy and policy analysts to better understand the underlying technologies and processes contributing to the carbon footprint of California households. The modeling framework was applied to estimate the annual home energy and supply chain carbon footprints of a prototypical California household. A preliminary assessment of parameter uncertainty associated with key model input data was also conducted. To illustrate the policy-relevance of this modeling framework, a case study was conducted that analyzed the achievable carbon footprint reductions associated with the adoption of energy efficient household and supply chain technologies.

  12. US Mnt(N) CO Site Consumption

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

    Mnt(N) CO Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US Mnt(N) CO Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US Mnt(N) CO Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US Mnt(N) CO Expenditures dollars ELECTRICITY ONLY average per household * Colorado households consume an average of 103 million Btu per year, 15% more than the U.S. average. * Average household energy costs in

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

    Gasoline and Diesel Fuel Update (EIA)

    Energy Usage The 1997 Residential Energy Consumption Survey (RECS) collected household energy data for the four most populated States: California, Florida, New York, and Texas. ...

  14. NASA technical baseline

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

    ... Twitter Google + Vimeo GovDelivery SlideShare SunShot Grand Challenge: Regional Test Centers NASA technical baseline HomeTag:NASA technical baseline Curiosity's multi-mission ...

  15. US SoAtl VA Site Consumption

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

    SoAtl VA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 US SoAtl VA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 4,000 8,000 12,000 16,000 US SoAtl VA Site Consumption kilowatthours $0 $300 $600 $900 $1,200 $1,500 $1,800 US SoAtl VA Expenditures dollars ELECTRICITY ONLY average per household * Virginia households consume an average of 86 million Btu per year, about 4% less than the U.S. average. * Average electricity consumption and costs are

  16. US MidAtl NJ Site Consumption

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

    pay more for electricity than the average U.S. household. * New Jersey homes are 20% larger than the average U.S. home. CONSUMPTION BY END USE Nearly half the energy consumed in ...

  17. US MidAtl NY Site Consumption

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

    U.S. average. * Electricity consumption in New York homes is much lower than the U.S. average, because many households use other fuels for major energy end uses like space ...

  18. Energy Intensity Indicators: Residential Source Energy Consumption

    Broader source: 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...

  19. Baseline data for the residential sector and development of a residential forecasting database

    SciTech Connect (OSTI)

    Hanford, J.W.; Koomey, J.G.; Stewart, L.E.; Lecar, M.E.; Brown, R.E.; Johnson, F.X.; Hwang, R.J.; Price, L.K.

    1994-05-01

    This report describes the Lawrence Berkeley Laboratory (LBL) residential forecasting database. It provides a description of the methodology used to develop the database and describes the data used for heating and cooling end-uses as well as for typical household appliances. This report provides information on end-use unit energy consumption (UEC) values of appliances and equipment historical and current appliance and equipment market shares, appliance and equipment efficiency and sales trends, cost vs efficiency data for appliances and equipment, product lifetime estimates, thermal shell characteristics of buildings, heating and cooling loads, shell measure cost data for new and retrofit buildings, baseline housing stocks, forecasts of housing starts, and forecasts of energy prices and other economic drivers. Model inputs and outputs, as well as all other information in the database, are fully documented with the source and an explanation of how they were derived.

  20. Hazard Baseline Documentation

    Broader source: Directives, Delegations, and Requirements [Office of Management (MA)]

    1995-12-04

    This standard establishes uniform Office of Environmental Management (EM) guidance on hazard baseline documents that identify and control radiological and non-radiological hazards for all EM facilities.

  1. US MidAtl PA Site Consumption

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

    MidAtl PA Site Consumption million Btu $0 $500 $1,000 $1,500 $2,000 $2,500 $3,000 US MidAtl PA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 2,000 4,000 6,000 8,000 10,000 12,000 US MidAtl PA Site Consumption kilowatthours $0 $250 $500 $750 $1,000 $1,250 $1,500 US MidAtl PA Expenditures dollars ELECTRICITY ONLY average per household * Pennsylvania households consume an average of 96 million Btu per year, 8% more than the U.S. average. Pennsylvania residents also

  2. appl_household2001.pdf

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

    Appliances Tables (Million U.S. Households; 60 pages, 240 kb) Contents Pages HC5-1a. Appliances by Climate Zone, Million U.S. Households, 2001 5 HC5-2a. Appliances by Year of Construction, Million U.S. Households, 2001 5 HC5-3a. Appliances by Household Income, Million U.S. Households, 2001 5 HC5-4a. Appliances by Type of Housing Unit, Million U.S. Households, 2001 5 HC5-5a. Appliances by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 5 HC5-6a. Appliances by Type of Rented

  3. Residential Energy Consumption Survey: Quality Profile

    SciTech Connect (OSTI)

    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.

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

    SciTech Connect (OSTI)

    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.

  5. housingunit_household2001.pdf

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

    ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ...

  6. appl_household2001.pdf

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

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ...

  7. ac_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ...

  8. spaceheat_household2001.pdf

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

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ...

  9. Transportation Baseline Report

    SciTech Connect (OSTI)

    Fawcett, Ricky Lee; Kramer, George Leroy Jr.

    1999-12-01

    The National Transportation Program 1999 Transportation Baseline Report presents data that form a baseline to enable analysis and planning for future Department of Energy (DOE) Environmental Management (EM) waste and materials transportation. In addition, this Report provides a summary overview of DOEs projected quantities of waste and materials for transportation. Data presented in this report were gathered as a part of the IPABS Spring 1999 update of the EM Corporate Database and are current as of July 30, 1999. These data were input and compiled using the Analysis and Visualization System (AVS) which is used to update all stream-level components of the EM Corporate Database, as well as TSD System and programmatic risk (disposition barrier) information. Project (PBS) and site-level IPABS data are being collected through the Interim Data Management System (IDMS). The data are presented in appendices to this report.

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

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

    Information Administration (EIA) 3 RECS Survey Data 2009 | 2005 | 2001 | 1997 | 1993 | Previous Housing characteristics Consumption & expenditures Microdata Methodology Housing Characteristics Tables Topical Sections Entire Section All Detailed Tables PDF Tables: HC1 Household Characteristics, Million U.S. Households Presents data relating to location, type, ownership, age, size, construction, and householder demographic and income characteristics. PDF Tables: HC2 Space Heating, Million

  11. Annual Technology Baseline

    Broader source: Energy.gov [DOE]

    The National Renewable Energy Laboratory is conducting a study sponsored by the U.S. Department of Energy DOE, Office of Energy Efficiency and Renewable Energy (EERE), that aims to document and implement an annual process designed to identify a realistic and timely set of input assumptions (e.g., technology cost and performance, fuel costs), and a diverse set of potential futures (standard scenarios), initially for electric sector analysis. This primary product of the Annual Technology Baseline (ATB) project component includes detailed cost and performance data (both current and projected) for both renewable and conventional technologies. This data is presented in MS Excel.

  12. TWRS baseline system description

    SciTech Connect (OSTI)

    Lee, A.K.

    1995-03-28

    This document provides a description of the baseline system conceptualized for remediating the tank waste stored within the Hanford Site. Remediation of the tank waste will be performed by the Tank Waste Remediation System (TWRS). This baseline system description (BSD) document has been prepared to describe the current planning basis for the TWRS for accomplishing the tank waste remediation functions. The BSD document is not intended to prescribe firm program management strategies for implementing the TWRS. The scope of the TWRS Program includes managing existing facilities, developing technology for new systems; building, testing and operating new facilities; and maintaining the system. The TWRS Program will manage the system used for receiving, safely storing, maintaining, treating, and disposing onsite, or packaging for offsite disposal, all tank waste. The scope of the TWRS Program encompasses existing facilities such as waste storage tanks, evaporators, pipelines, and low-level radioactive waste treatment and disposal facilities. It includes support facilities that comprise the total TWRS infrastructure, including upgrades to existing facilities or equipment and the addition of new facilities.

  13. Hazard baseline documentation

    SciTech Connect (OSTI)

    Not Available

    1994-08-01

    This DOE limited technical standard establishes uniform Office of Environmental Management (EM) guidance on hazards baseline documents that identify and control radiological and nonradiological hazards for all EM facilities. It provides a road map to the safety and health hazard identification and control requirements contained in the Department`s orders and provides EM guidance on the applicability and integration of these requirements. This includes a definition of four classes of facilities (nuclear, non-nuclear, radiological, and other industrial); the thresholds for facility hazard classification; and applicable safety and health hazard identification, controls, and documentation. The standard applies to the classification, development, review, and approval of hazard identification and control documentation for EM facilities.

  14. Appliance Commitment for Household Load Scheduling

    SciTech Connect (OSTI)

    Du, Pengwei; Lu, Ning

    2011-06-30

    This paper presents a novel appliance commitment algorithm that schedules thermostatically-controlled household loads based on price and consumption forecasts considering users comfort settings to meet an optimization objective such as minimum payment or maximum comfort. The formulation of an appliance commitment problem was described in the paper using an electrical water heater load as an example. The thermal dynamics of heating and coasting of the water heater load was modeled by physical models; random hot water consumption was modeled with statistical methods. The models were used to predict the appliance operation over the scheduling time horizon. User comfort was transformed to a set of linear constraints. Then, a novel linear, sequential, optimization process was used to solve the appliance commitment problem. The simulation results demonstrate that the algorithm is fast, robust, and flexible. The algorithm can be used in home/building energy-management systems to help household owners or building managers to automatically create optimal load operation schedules based on different cost and comfort settings and compare cost/benefits among schedules.

  15. 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)

  16. Baseline Control Measures.pdf

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

    Individual Permit Baseline Control Measures at Los Alamos National Laboratory, Poster, Individual Permit for Storm Water, NPDES Permit No. NM0030759 Author(s): Veenis, Steven J....

  17. Next Generation Household Refrigerator | Department of Energy

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

    Next Generation Household Refrigerator Next Generation Household Refrigerator Embraco's high efficiency, oil-free linear compressor.
    Credit: Whirlpool Embraco's high ...

  18. Household Vehicles Energy Use Cover Page

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

    Energy Use Cover Page Glossary Home > Households, Buildings & Industry >Transportation Surveys > Household Vehicles Energy Use Cover Page Contact Us * Feedback * PrivacySecurity *...

  19. Strategies for Collecting Household Energy Data | Department...

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

    Collecting Household Energy Data Strategies for Collecting Household Energy Data Better Buildings Neighborhood Program Data and Evaluation Peer Exchange Call: Strategies for ...

  20. ac_household2001.pdf

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

    0a. Air Conditioning by Midwest Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 20.5 13.6 6.8 2.2 Air Conditioners Not Used ........................... 2.1 0.3 Q Q 27.5 Households Using Electric Air-Conditioning 1

  1. ac_household2001.pdf

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

    1a. Air Conditioning by South Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.2 1.3 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 37.2 19.3 6.4 11.5 1.5 Air Conditioners Not Used ........................... 2.1 0.4 Q Q Q 28.2 Households Using Electric Air-Conditioning 1

  2. ac_household2001.pdf

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

    2a. Air Conditioning by West Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.4 1.2 1.7 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 10.7 3.4 7.2 7.1 Air Conditioners Not Used ........................... 2.1 1.1 0.2 0.9 15.5 Households Using Electric Air-Conditioning 1 ........................................ 80.8 9.6 3.2

  3. ac_household2001.pdf

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

    4a. Air Conditioning by Type of Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.6 1.5 1.4 1.8 Households With Electric Air-Conditioning Equipment ........ 82.9 58.7 6.5 12.4 5.3 4.9 Air Conditioners Not Used ............ 2.1 1.1 Q 0.6 Q 21.8 Households Using Electric Air-Conditioning 1

  4. ac_household2001.pdf

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

    8a. Air Conditioning by Urban/Rural Location, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.8 1.4 1.3 1.4 Households With Electric Air-Conditioning Equipment ...................... 82.9 36.8 13.6 18.9 13.6 4.3 Air Conditioners Not Used ........................... 2.1 1.2 0.2 0.4 0.3 21.4 Households Using Electric Air-Conditioning 2 ........................................ 80.8 35.6 13.4

  5. ac_household2001.pdf

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

    9a. Air Conditioning by Northeast Census Region, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.8 Households With Electric Air-Conditioning Equipment ...................... 82.9 14.5 11.3 3.2 3.3 Air Conditioners Not Used ........................... 2.1 0.3 0.3 Q 28.3 Households Using Electric Air-Conditioning 1

  6. HEV America Baseline Test Sequence

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

    BASELINE TEST SEQUENCE Revision 1 September 1, 2006 Prepared by Electric Transportation Applications Prepared by: _______________________________ Date: __________ Roberta Brayer Approved by: _________ _________________________________ Date: _______________ _____ Donald B. Karner ©2005 Electric Transportation Applications All Rights Reserved HEV America Baseline Test Sequence Page 1 HEV PERFORMANCE TEST PROCEDURE SEQUENCE The following test sequence shall be used for conduct of HEV America

  7. Hanford Site technical baseline database

    SciTech Connect (OSTI)

    Porter, P.E., Westinghouse Hanford

    1996-05-10

    This document includes a cassette tape that contains the Hanford specific files that make up the Hanford Site Technical Baseline Database as of May 10, 1996. The cassette tape also includes the delta files that delineate the differences between this revision and revision 3 (April 10, 1996) of the Hanford Site Technical Baseline Database.

  8. homeoffice_household2001.pdf

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

    ... RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... 29.1 5.3 22.7 3.8 1 Below 150 percent of poverty line or 60 percent of median State ...

  9. char_household2001.pdf

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

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... Income Relative to Poverty Line Below 100 Percent ...... 15.0 13.2 1.8 Q ...

  10. char_household2001.pdf

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

    Contact: Stephanie J. Battles, Survey Manager (stephanie.battles@eia.doe.gov) World Wide Web: http:www.eia.doe.govemeuconsumption Table HC2-1a. Household Characteristics by ...

  11. Cover Page of Household Vehicles Energy Use: Latest Data & Trends

    Gasoline and Diesel Fuel Update (EIA)

    Household Vehicles Energy Use Cover Page Cover Page of Household Vehicles Energy Use: Latest Data & Trends...

  12. 324 Building Baseline Radiological Characterization

    SciTech Connect (OSTI)

    R.J. Reeder, J.C. Cooper

    2010-06-24

    This report documents the analysis of radiological data collected as part of the characterization study performed in 1998. The study was performed to create a baseline of the radiological conditions in the 324 Building.

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

    SciTech Connect (OSTI)

    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.

  14. Household energy use in urban Venezuela: Implications from surveys in Maracaibo, Valencia, Merida, and Barcelona-Puerto La Cruz

    SciTech Connect (OSTI)

    Figueroa, M.J.; Sathaye, J.

    1993-08-01

    This report identifies the most important results of a comparative analysis of household commercial energy use in Venezuelan urban cities. The use of modern fuels is widespread among all cities. Cooking consumes the largest share of urban household energy use. The survey documents no use of biomass and a negligible use of kerosene for cooking. LPG, natural gas, and kerosene are the main fuels available. LPG is the fuel choice of low-income households in all cities except Maracaibo, where 40% of all households use natural gas. Electricity consumption in Venezuela`s urban households is remarkably high compared with the levels used in households in comparable Latin American countries and in households of industrialized nations which confront harsher climatic conditions and, therefore, use electricity for water and space heating. The penetration of appliances in Venezuela`s urban households is very high. The appliances available on the market are inefficient, and there are inefficient patterns of energy use among the population. Climate conditions and the urban built form all play important roles in determining the high level of energy consumption in Venezuelan urban households. It is important to acknowledge the opportunities for introducing energy efficiency and conservation in Venezuela`s residential sector, particularly given current economic and financial constraints, which may hamper the future provision of energy services.

  15. ac_household2001.pdf

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

    2a. Air Conditioning by Year of Construction, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.6 1.2 1.1 1.2 1.1 0.9 Households With Electric Air-Conditioning Equipment ........ 82.9 13.6 16.0 14.7 10.4 10.5 17.6 4.7 Air Conditioners Not Used ............ 2.1 Q 0.3 0.5 0.3 0.4 0.5 27.2 Households Using Electric Air-Conditioning 2

  16. ac_household2001.pdf

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

    5a. Air Conditioning by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.5 1.5 1.4 1.8 Households With Electric Air-Conditioning Equipment ........ 59.5 58.7 6.5 12.4 5.3 5.2 Air Conditioners Not Used ............ 1.2 1.1 Q 0.6 Q 23.3 Households Using

  17. ac_household2001.pdf

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

    6a. Air Conditioning by Type of Rented Housing Unit, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.8 0.5 1.4 1.2 1.6 Households With Electric Air-Conditioning Equipment ........ 23.4 58.7 6.5 12.4 5.3 6.1 Air Conditioners Not Used ............ 0.9 1.1 Q 0.6 Q 23.0 Households Using Electric Air-Conditioning

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

    Gasoline and Diesel Fuel Update (EIA)

    U.S. Energy Information Administration (EIA) What's new in our home energy use? RECS 2009 - Release date: March 28, 2011 First results from EIA's 2009 Residential Energy Consumption Survey (RECS) The 2009 RECS collected home energy characteristics data from over 12,000 U.S. households. This report highlights findings from the survey, with details presented in the Household Energy Characteristics tables. How we use energy in our homes has changed substantially over the past three decades.

  19. homeoffice_household2001.pdf

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

    0a. Home Office Equipment by Midwest Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 24.5 17.1 7.4 NE Households Using Office Equipment ......................................... 96.2 22.4 15.7 6.7 1.3 Personal Computers 1 ................................. 60.0

  20. homeoffice_household2001.pdf

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

    1a. Home Office Equipment by South Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.2 1.3 1.6 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Households Using Office Equipment ......................................... 96.2 34.6 18.4 6.0 10.1 1.2 Personal Computers 1

  1. homeoffice_household2001.pdf

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

    2a. Home Office Equipment by West Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.6 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Households Using Office Equipment ......................................... 96.2 21.4 6.2 15.2 1.0 Personal Computers 1 ................................. 60.0 14.3 4.0 10.4 3.7 Number of

  2. homeoffice_household2001.pdf

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

    9a. Home Office Equipment by Northeast Census Region, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.1 1.4 1.2 Total .............................................................. 107.0 20.3 14.8 5.4 NE Households Using Office Equipment ......................................... 96.2 17.9 12.8 5.0 1.3 Personal Computers 1 ................................. 60.0 10.9

  3. homeoffice_household2001.pdf

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

    RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral ... 29.1 5.3 22.7 3.8 1 Below 150 percent of poverty line or 60 percent of median State income

  4. Fact #748: October 8, 2012 Components of Household Expenditures...

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

    Household Expenditures on Transportation, 1984-2010 Fact 748: October 8, 2012 Components of Household Expenditures on Transportation, 1984-2010 The overall share of annual household ...

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

    U.S. 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...

  6. Baseline Wind Energy Facility | Open Energy Information

    Open Energy Info (EERE)

    Wind Energy Facility Jump to: navigation, search Name Baseline Wind Energy Facility Facility Baseline Wind Energy Facility Sector Wind energy Facility Type Commercial Scale Wind...

  7. Baseline Control Measures.pdf

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

    Individual Permit Baseline Control Measures at Los Alamos National Laboratory, Poster, Individual Permit for Storm Water, NPDES Permit No. NM0030759 Author(s): Veenis, Steven J. Intended for: Public Purpose: This poster was prepared for the June 2013 Individual Permit for Storm Water (IP) public meeting. The purpose of the meeting was to update the public on implementation of the permit as required under Part 1.I (7) of the IP (National Pollutant Discharge Elimination System Permit No.

  8. ac_household2001.pdf

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

    2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.7 1.2 1.2 Households With Electric Air-Conditioning Equipment ...................... 82.9 4.9 6.0 7.4 6.2 2.4 Air Conditioners Not Used ........................... 2.1 0.1 0.8 Q 0.1 23.2 Households Using Electric Air-Conditioning 1 ........................................ 80.8 4.7 5.2 7.4 6.1 2.6 Type of Electric Air-Conditioning Used Central

  9. homeoffice_household2001.pdf

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

    2a. Home Office Equipment by Year of Construction, Million U.S. Households, 2001 Home Office Equipment RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.4 1.1 1.1 1.2 1.2 1.0 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Households Using Office Equipment .......................... 96.2 14.9 16.7 17.0 12.2 13.0 22.4 4.4 Personal Computers 2

  10. appl_household2001.pdf

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

    2a. Appliances by West Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.5 1.0 1.7 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 22.1 6.6 15.5 1.1 1

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

    Reports and Publications (EIA)

    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.

  12. Baseline LAW Glass Formulation Testing

    SciTech Connect (OSTI)

    Kruger, Albert A.; Mooers, Cavin; Bazemore, Gina; Pegg, Ian L.; Hight, Kenneth; Lai, Shan Tao; Buechele, Andrew; Rielley, Elizabeth; Gan, Hao; Muller, Isabelle S.; Cecil, Richard

    2013-06-13

    The major objective of the baseline glass formulation work was to develop and select glass formulations that are compliant with contractual and processing requirements for each of the LAW waste streams. Other objectives of the work included preparation and characterization of glasses with respect to the properties of interest, optimization of sulfate loading in the glasses, evaluation of ability to achieve waste loading limits, testing to demonstrate compatibility of glass melts with melter materials of construction, development of glass formulations to support ILAW qualification activities, and identification of glass formulation issues with respect to contract specifications and processing requirements.

  13. FED baseline engineering studies report

    SciTech Connect (OSTI)

    Sager, P.H.

    1983-04-01

    Studies were carried out on the FED Baseline to improve design definition, establish feasibility, and reduce cost. Emphasis was placed on cost reduction, but significant feasibility concerns existed in several areas, and better design definition was required to establish feasibility and provide a better basis for cost estimates. Design definition and feasibility studies included the development of a labyrinth shield ring concept to prevent radiation streaming between the torus spool and the TF coil cryostat. The labyrinth shield concept which was developed reduced radiation streaming sufficiently to permit contact maintenance of the inboard EF coils. Various concepts of preventing arcing between adjacent shield sectors were also explored. It was concluded that installation of copper straps with molybdenum thermal radiation shields would provide the most reliable means of preventing arcing. Other design studies included torus spool electrical/structural concepts, test module shielding, torus seismic response, poloidal conditions in the magnets, disruption characteristics, and eddy current effects. These additional studies had no significant impact on cost but did confirm the feasibility of the basic FED Baseline concept.

  14. Development of the household sample for furnace and boilerlife-cycle cost analysis

    SciTech Connect (OSTI)

    Whitehead, Camilla Dunham; Franco, Victor; Lekov, Alex; Lutz, Jim

    2005-05-31

    Residential household space heating energy use comprises close to half of all residential energy consumption. Currently, average space heating use by household is 43.9 Mbtu for a year. An average, however, does not reflect regional variation in heating practices, energy costs, or fuel type. Indeed, a national average does not capture regional or consumer group cost impacts from changing efficiency levels of heating equipment. The US Department of Energy sets energy standards for residential appliances in, what is called, a rulemaking process. The residential furnace and boiler efficiency rulemaking process investigates the costs and benefits of possible updates to the current minimum efficiency regulations. Lawrence Berkeley National Laboratory (LBNL) selected the sample used in the residential furnace and boiler efficiency rulemaking from publically available data representing United States residences. The sample represents 107 million households in the country. The data sample provides the household energy consumption and energy price inputs to the life-cycle cost analysis segment of the furnace and boiler rulemaking. This paper describes the choice of criteria to select the sample of houses used in the rulemaking process. The process of data extraction is detailed in the appendices and is easily duplicated. The life-cycle cost is calculated in two ways with a household marginal energy price and a national average energy price. The LCC results show that using an national average energy price produces higher LCC savings but does not reflect regional differences in energy price.

  15. appl_household2001.pdf

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

    0a. Appliances by Midwest Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.5 Total .............................................................. 107.0 24.5 17.1 7.4 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 23.8 16.6 7.2 NE 1

  16. appl_household2001.pdf

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

    1a. Appliances by South Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.8 1.1 1.4 1.5 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 36.2 19.4 6.4 10.3 1.5 1

  17. appl_household2001.pdf

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

    4a. Appliances by Type of Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.5 1.7 1.6 1.9 Total ............................................... 107.0 73.7 9.5 17.0 6.8 4.2 Kitchen Appliances Cooking Appliances Oven ........................................... 101.7 69.1 9.4 16.7 6.6 4.3 1

  18. appl_household2001.pdf

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

    5a. Appliances by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.3 0.4 2.1 3.1 1.3 Total ............................................... 72.7 63.2 2.1 1.8 5.7 6.7 Kitchen Appliances Cooking Appliances Oven ...........................................

  19. appl_household2001.pdf

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

    6a. Appliances by Type of Rented Housing Unit, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.8 1.1 0.9 2.5 Total ............................................... 34.3 10.5 7.4 15.2 1.1 6.9 Kitchen Appliances Cooking Appliances Oven ........................................... 33.4 10.1 7.3 14.9 1.1

  20. appl_household2001.pdf

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

    8a. Appliances by Urban/Rural Location, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.5 0.9 1.4 1.2 1.3 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.1 Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 47.5 17.5 19.9 16.8 4.2 1

  1. appl_household2001.pdf

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

    9a. Appliances by Northeast Census Region, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.3 1.6 Total .............................................................. 107.0 20.3 14.8 5.4 NE Kitchen Appliances Cooking Appliances Oven ......................................................... 101.7 19.6 14.5 5.2 1.1 1

  2. homeoffice_household2001.pdf

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

    2001 Home Office Equipment RSE Column Factor: Total U.S. Four Most Populated States RSE Row Factors New York California Texas Florida 0.4 1.1 1.0 1.5 1.5 Total .............................................................. 107.0 7.1 12.3 7.7 6.3 NE Households Using Office Equipment ......................................... 96.2 6.2 11.4 6.7 5.9 1.7 Personal Computers 1 ................................. 60.0 3.4 7.9 4.1 3.8 4.4 Number of Desktop PCs 1

  3. spaceheat_household2001.pdf

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

    0a. Space Heating by Midwest Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. Midwest Census Region RSE Row Factors Total Census Division East North Central West North Central 0.5 1.0 1.2 1.6 Total .............................................................. 107.0 24.5 17.1 7.4 NE Heat Home .................................................... 106.0 24.5 17.1 7.4 NE Do Not Heat Home ....................................... 1.0 Q Q Q 19.8 No

  4. spaceheat_household2001.pdf

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

    1a. Space Heating by South Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. South Census Region RSE Row Factors Total Census Division South Atlantic East South Central West South Central 0.5 0.9 1.2 1.4 1.3 Total .............................................................. 107.0 38.9 20.3 6.8 11.8 NE Heat Home .................................................... 106.0 38.8 20.2 6.8 11.8 NE Do Not Heat Home

  5. spaceheat_household2001.pdf

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

    2a. Space Heating by West Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. West Census Region RSE Row Factors Total Census Division Mountain Pacific 0.6 1.0 1.6 1.2 Total .............................................................. 107.0 23.3 6.7 16.6 NE Heat Home .................................................... 106.0 22.6 6.7 15.9 NE Do Not Heat Home ....................................... 1.0 0.7 Q 0.7 10.6 No Heating Equipment

  6. spaceheat_household2001.pdf

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

    5a. Space Heating by Type of Owner-Occupied Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Owner- Occupied Units Type of Owner-Occupied Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.4 0.4 1.9 3.0 1.3 Total ............................................... 72.7 63.2 2.1 1.8 5.7 6.7 Heat Home ..................................... 72.4 63.0 2.0 1.7 5.7 6.7 Do Not Heat Home

  7. spaceheat_household2001.pdf

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

    6a. Space Heating by Type of Rented Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Rented Units Type of Rented Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.8 1.1 0.9 2.5 Total ............................................... 34.3 10.5 7.4 15.2 1.1 6.9 Heat Home ..................................... 33.7 10.4 7.4 14.8 1.1 6.9 Do Not Heat Home

  8. spaceheat_household2001.pdf

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

    8a. Space Heating by Urban/Rural Location, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Urban/Rural Location 1 RSE Row Factors City Town Suburbs Rural 0.6 0.9 1.3 1.3 1.2 Total .............................................................. 107.0 49.9 18.0 21.2 17.9 4.3 Heat Home .................................................... 106.0 49.1 18.0 21.2 17.8 4.3 Do Not Heat Home ....................................... 1.0 0.7 0.1 0.1 0.1 25.8 No Heating

  9. spaceheat_household2001.pdf

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

    9a. Space Heating by Northeast Census Region, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total U.S. Northeast Census Region RSE Row Factors Total Census Division Middle Atlantic New England 0.5 1.0 1.2 1.7 Total .............................................................. 107.0 20.3 14.8 5.4 NE Heat Home .................................................... 106.0 20.1 14.7 5.4 NE Do Not Heat Home ....................................... 1.0 Q Q Q 19.9 No

  10. Baseline Test Specimen Machining Report

    SciTech Connect (OSTI)

    mark Carroll

    2009-08-01

    The Next Generation Nuclear Plant (NGNP) Project is tasked with selecting a high temperature gas reactor technology that will be capable of generating electricity and supplying large amounts of process heat. The NGNP is presently being designed as a helium-cooled high temperature gas reactor (HTGR) with a large graphite core. The graphite baseline characterization project is conducting the research and development (R&D) activities deemed necessary to fully qualify nuclear-grade graphite for use in the NGNP reactor. Establishing nonirradiated thermomechanical and thermophysical properties by characterizing lot-to-lot and billet-to-billet variations (for probabilistic baseline data needs) through extensive data collection and statistical analysis is one of the major fundamental objectives of the project. The reactor core will be made up of stacks of graphite moderator blocks. In order to gain a more comprehensive understanding of the varying characteristics in a wide range of suitable graphites, any of which can be classified as nuclear grade, an experimental program has been initiated to develop an extensive database of the baseline characteristics of numerous candidate graphites. Various factors known to affect the properties of graphite will be investigated, including specimen size, spatial location within a graphite billet, specimen orientation within a billet (either parallel to [P] or transverse to [T] the long axis of the as-produced billet), and billet-to-billet variations within a lot or across different production lots. Because each data point is based on a certain position within a given billet of graphite, particular attention must be paid to the traceability of each specimen and its spatial location and orientation within each billet. The evaluation of these properties is discussed in the Graphite Technology Development Plan (Windes et. al, 2007). One of the key components in the evaluation of these graphite types will be mechanical testing on

  11. TWRS privatization process technical baseline

    SciTech Connect (OSTI)

    Orme, R.M.

    1996-09-13

    The U.S. Department of Energy (DOE) is planning a two-phased program for the remediation of Hanford tank waste. Phase 1 is a pilot program to demonstrate the procurement of treatment services. The volume of waste treated during the Phase 1 is a small percentage of the tank waste. During Phase 2, DOE intends to procure treatment services for the balance of the waste. The TWRS Privatization Process Technical Baseline (PPTB) provides a summary level flowsheet/mass balance of tank waste treatment operations which is consistent with the tank inventory information, waste feed staging studies, and privatization guidelines currently available. The PPTB will be revised periodically as privatized processing concepts are crystallized.

  12. Pinellas Plant Environmental Baseline Report

    SciTech Connect (OSTI)

    Not Available

    1997-06-01

    The Pinellas Plant has been part of the Department of Energy`s (DOE) nuclear weapons complex since the plant opened in 1957. In March 1995, the DOE sold the Pinellas Plant to the Pinellas County Industry Council (PCIC). DOE has leased back a large portion of the plant site to facilitate transition to alternate use and safe shutdown. The current mission is to achieve a safe transition of the facility from defense production and prepare the site for alternative uses as a community resource for economic development. Toward that effort, the Pinellas Plant Environmental Baseline Report (EBR) discusses the current and past environmental conditions of the plant site. Information for the EBR is obtained from plant records. Historical process and chemical usage information for each area is reviewed during area characterizations.

  13. ,"Total Fuel Oil Consumption

    U.S. 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...

  14. ,"Total Fuel Oil Consumption

    U.S. 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...

  15. Manufacturing Consumption of Energy 1994

    U.S. 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...

  16. Baseline Graphite Characterization: First Billet

    SciTech Connect (OSTI)

    Mark C. Carroll; Joe Lords; David Rohrbaugh

    2010-09-01

    The Next Generation Nuclear Plant Project Graphite Research and Development program is currently establishing the safe operating envelope of graphite core components for a very high temperature reactor design. To meet this goal, the program is generating the extensive amount of quantitative data necessary for predicting the behavior and operating performance of the available nuclear graphite grades. In order determine the in-service behavior of the graphite for the latest proposed designs, two main programs are underway. The first, the Advanced Graphite Creep (AGC) program, is a set of experiments that are designed to evaluate the irradiated properties and behavior of nuclear grade graphite over a large spectrum of temperatures, neutron fluences, and compressive loads. Despite the aggressive experimental matrix that comprises the set of AGC test runs, a limited amount of data can be generated based upon the availability of space within the Advanced Test Reactor and the geometric constraints placed on the AGC specimens that will be inserted. In order to supplement the AGC data set, the Baseline Graphite Characterization program will endeavor to provide supplemental data that will characterize the inherent property variability in nuclear-grade graphite without the testing constraints of the AGC program. This variability in properties is a natural artifact of graphite due to the geologic raw materials that are utilized in its production. This variability will be quantified not only within a single billet of as-produced graphite, but also from billets within a single lot, billets from different lots of the same grade, and across different billets of the numerous grades of nuclear graphite that are presently available. The thorough understanding of this variability will provide added detail to the irradiated property data, and provide a more thorough understanding of the behavior of graphite that will be used in reactor design and licensing. This report covers the

  17. appl_household2001.pdf

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

    a. Appliances by Climate Zone, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Climate Zone 1 RSE Row Factors Fewer than 2,000 CDD and -- 2,000 CDD or More and Fewer than 4,000 HDD More than 7,000 HDD 5,500 to 7,000 HDD 4,000 to 5,499 HDD Fewer than 4,000 HDD 0.4 1.9 1.1 1.1 1.2 1.1 Total .................................................. 107.0 9.2 28.6 24.0 21.0 24.1 7.8 Kitchen Appliances Cooking Appliances Oven

  18. appl_household2001.pdf

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

    2a. Appliances by Year of Construction, Million U.S. Households, 2001 Appliance Types and Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.4 1.5 1.2 1.1 1.2 1.1 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.2 Kitchen Appliances Cooking Appliances Oven ........................................... 101.7 14.3 17.2 17.8 12.9 13.7 25.9 4.2 1

  19. spaceheat_household2001.pdf

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

    2a. Space Heating by Year of Construction, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Year of Construction RSE Row Factors 1990 to 2001 1 1980 to 1989 1970 to 1979 1960 to 1969 1950 to 1959 1949 or Before 0.5 1.5 1.1 1.1 1.1 1.1 0.9 Total ............................................... 107.0 15.5 18.2 18.8 13.8 14.2 26.6 4.3 Heat Home ..................................... 106.0 15.4 18.2 18.6 13.6 13.9 26.4 4.3 Do Not Heat Home ........................

  20. spaceheat_household2001.pdf

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

    4a. Space Heating by Type of Housing Unit, Million U.S. Households, 2001 Space Heating Characteristics RSE Column Factor: Total Type of Housing Unit RSE Row Factors Single-Family Apartments in Buildings With Mobile Home Two to Four Units Five or More Units 0.5 0.5 1.5 1.4 1.7 Total ............................................... 107.0 73.7 9.5 17.0 6.8 4.4 Heat Home ..................................... 106.0 73.4 9.4 16.4 6.8 4.5 Do Not Heat Home ........................ 1.0 0.3 Q 0.6 Q 19.0 No

  1. Revised SRC-I project baseline. Volume 1

    SciTech Connect (OSTI)

    Not Available

    1984-01-01

    International Coal Refining Company (ICRC), in cooperation with the Commonwealth of Kentucky has contracted with the United States Department of Energy (DOE) to design, build and operate a first-of-its-kind plant demonstrating the economic, environmental, socioeconomic and technical feasibility of the direct coal liquefaction process known as SRC-I. ICRC has made a massive commitment of time and expertise to design processes, plan and formulate policy, schedules, costs and technical drawings for all plant systems. These fully integrated plans comprise the Project Baseline and are the basis for all future detailed engineering, plant construction, operation, and other work set forth in the contract between ICRC and the DOE. Volumes I and II of the accompanying documents constitute the updated Project Baseline for the SRC-I two-stage liquefaction plant. International Coal Refining Company believes this versatile plant design incorporates the most advanced coal liquefaction system available in the synthetic fuels field. SRC-I two-stage liquefaction, as developed by ICRC, is the way of the future in coal liquefaction because of its product slate flexibility, high process thermal efficiency, and low consumption of hydrogen. The SRC-I Project Baseline design also has made important state-of-the-art advances in areas such as environmental control systems. Because of a lack of funding, the DOE has curtailed the total project effort without specifying a definite renewal date. This precludes the development of revised accurate and meaningful schedules and, hence, escalated project costs. ICRC has revised and updated the original Design Baseline to include in the technical documentation all of the approved but previously non-incorporated Category B and C and new Post-Baseline Engineering Change Proposals.

  2. Fact #565: April 6, 2009 Household Gasoline Expenditures by Income |

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

    Department of Energy 5: April 6, 2009 Household Gasoline Expenditures by Income Fact #565: April 6, 2009 Household Gasoline Expenditures by Income In the annual Consumer Expenditure Survey, household incomes are grouped into five equal parts called quintiles (each quintile is 20%). Households in the second and third quintiles consistently have a higher share of spending on gasoline each year than households in the other quintiles. Household Gasoline Expenditures by Income Quintile Bar graph

  3. Mitigating Carbon Emissions: the Potential of Improving Efficiencyof Household Appliances in China

    SciTech Connect (OSTI)

    Lin, Jiang

    2006-07-10

    China is already the second's largest energy consumer in the world after the United States, and its demand for energy is expected to continue to grow rapidly in the foreseeable future, due to its fast economic growth and its low level of energy use per capita. From 2001 to 2005, the growth rate of energy consumption in China has exceeded the growth rate of its economy (NBS, 2006), raising serious concerns about the consequences of such energy use on local environment and global climate. It is widely expected that China is likely to overtake the US in energy consumption and greenhouse gas (GHG) emissions during the first half of the 21st century. Therefore, there is considerable interest in the international community in searching for options that may help China slow down its growth in energy consumption and GHG emissions through improving energy efficiency and adopting more environmentally friendly fuel supplies such as renewable energy. This study examines the energy saving potential of three major residential energy end uses: household refrigeration, air-conditioning, and water heating. China is already the largest consumer market in the world for household appliances, and increasingly the global production base for consumer appliances. Sales of household refrigerators, room air-conditioners, and water heaters are growing rapidly due to rising incomes and booming housing market. At the same time, the energy use of Chinese appliances is relatively inefficient compared to similar products in the developed economies. Therefore, the potential for energy savings through improving appliance efficiency is substantial. This study focuses particularly on the impact of more stringent energy efficiency standards for household appliances, given that such policies are found to be very effective in improving the efficiency of household appliances, and are well established both in China and around world (CLASP, 2006).

  4. Kingston Creek Hydro Project Powers 100 Households | Department...

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

    Kingston Creek Hydro Project Powers 100 Households Kingston Creek Hydro Project Powers 100 Households August 21, 2013 - 12:00am Addthis Nevada-based contracting firm Nevada ...

  5. Loan Programs for Low- and Moderate-Income Households | Department...

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

    Programs for Low- and Moderate-Income Households Loan Programs for Low- and Moderate-Income Households Better Buildings Residential Network Multifamily and Low-Income Housing Peer ...

  6. Household Response To Dynamic Pricing Of Electricity: A Survey...

    Open Energy Info (EERE)

    Household Response To Dynamic Pricing Of Electricity: A Survey Of The Experimental Evidence Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Household Response To Dynamic...

  7. Tank waste remediation systems technical baseline database

    SciTech Connect (OSTI)

    Porter, P.E.

    1996-10-16

    This document includes a cassette tape that contains Hanford generated data for the Tank Waste Remediation Systems Technical Baseline Database as of October 09, 1996.

  8. Baselines for Greenhouse Gas Reductions: Problems, Precedents...

    Open Energy Info (EERE)

    Baseline projection, GHG inventory, Pathways analysis Resource Type: Publications, Lessons learnedbest practices Website: www.p2pays.orgref2221739.pdf References:...

  9. ARM: Baseline Solar Radiation Network (BSRN): solar irradiances...

    Office of Scientific and Technical Information (OSTI)

    Baseline Solar Radiation Network (BSRN): solar irradiances Title: ARM: Baseline Solar Radiation Network (BSRN): solar irradiances Baseline Solar Radiation Network (BSRN): solar ...

  10. Long-Baseline Neutrino Facility / Deep Underground Neutrino Project...

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

    Long-Baseline Neutrino Facility Deep Underground Neutrino Project (LBNF-DUNE) Long-Baseline Neutrino Facility Deep Underground Neutrino Project (LBNF-DUNE) Long-Baseline ...

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

    U.S. 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...

  12. 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

  13. Residential Energy Consumption Survey:

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

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

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

    Buildings Energy Data Book [EERE]

    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

  15. Energy Intensity Baselining and Tracking Guidance

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

    ... total energy required to generate, transmit, and distribute electricity from the power generation source to the end user is factored into a company's energy consumption metrics. ...

  16. All Consumption Tables.vp

    U.S. 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...

  17. TWRS technical baseline database manager definition document

    SciTech Connect (OSTI)

    Acree, C.D.

    1997-08-13

    This document serves as a guide for using the TWRS Technical Baseline Database Management Systems Engineering (SE) support tool in performing SE activities for the Tank Waste Remediation System (TWRS). This document will provide a consistent interpretation of the relationships between the TWRS Technical Baseline Database Management software and the present TWRS SE practices. The Database Manager currently utilized is the RDD-1000 System manufactured by the Ascent Logic Corporation. In other documents, the term RDD-1000 may be used interchangeably with TWRS Technical Baseline Database Manager.

  18. Complex System Method to Assess Commercial Vehicle Fuel Consumption |

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

    Department of Energy Complex System Method to Assess Commercial Vehicle Fuel Consumption Complex System Method to Assess Commercial Vehicle Fuel Consumption Two case studies for commercial vehicle applications compare a baseline, contemporary vehicle with advanced, future options. p-08_kasab.pdf (273.12 KB) More Documents & Publications Particle Number & Particulate Mass Emissions Measurements on a 'Euro VI' Heavy-duty Engine using the PMP Methodologies A High Temperature Direct

  19. Hanford Site technical baseline database. Revision 1

    SciTech Connect (OSTI)

    Porter, P.E.

    1995-01-27

    This report lists the Hanford specific files (Table 1) that make up the Hanford Site Technical Baseline Database. Table 2 includes the delta files that delineate the differences between this revision and revision 0 of the Hanford Site Technical Baseline Database. This information is being managed and maintained on the Hanford RDD-100 System, which uses the capabilities of RDD-100, a systems engineering software system of Ascent Logic Corporation (ALC). This revision of the Hanford Site Technical Baseline Database uses RDD-100 version 3.0.2.2 (see Table 3). Directories reflect those controlled by the Hanford RDD-100 System Administrator. Table 4 provides information regarding the platform. A cassette tape containing the Hanford Site Technical Baseline Database is available.

  20. Office Buildings - Energy Consumption

    U.S. 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,...

  1. ,"Total Natural Gas Consumption

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

    Gas Consumption (billion cubic feet)",,,,,"Natural Gas Energy Intensity (cubic feetsquare foot)" ,"Total ","Space Heating","Water Heating","Cook- ing","Other","Total ","Space...

  2. Direct and indirect effect of changes in family structure and lifestyle upon energy consumption, 1950-1080

    SciTech Connect (OSTI)

    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.

  3. Addressing Water Consumption of Evaporative Coolers with Greywater

    SciTech Connect (OSTI)

    Sahai, Rashmi; Shah, Nihar; Phadke, Amol

    2012-07-01

    Evaporative coolers (ECs) provide significant gains in energy efficiency compared to vapor compression air conditioners, but simultaneously have significant onsite water demand. This can be a major barrier to deployment in areas of the world with hot and arid climates. To address this concern, this study determined where in the world evaporative cooling is suitable, the water consumption of ECs in these cities, and the potential that greywater can be used reduce the consumption of potable water in ECs. ECs covered 69percent of the cities where room air conditioners are may be deployed, based on comfort conditions alone. The average water consumption due to ECs was found to be 400 L/household/day in the United States and Australia, with the potential for greywater to provide 50percent this amount. In the rest of the world, the average water consumption was 250 L/household/day, with the potential for greywater to supply 80percent of this amount. Home size was the main factor that contributed to this difference. In the Mediterranean, the Middle East, Northern India, and the Midwestern and Southwestern United States alkalinity levels are high and water used for bleeding will likely contribute significantly to EC water consumption. Although technically feasible, upfront costs for household GW systems are currently high. In both developed and developing parts of the world, however, a direct EC and GW system is cost competitive with conventional vapor compression air conditioners. Moreover, in regions of the world that face problems of water scarcity the benefits can substantially outweigh the costs.

  4. Fort Irwin Integrated Resource Assessment. Volume 2, Baseline detail

    SciTech Connect (OSTI)

    Richman, E.E.; Keller, J.M.; Dittmer, A.L.; Hadley, D.L.

    1994-01-01

    This report documents the assessment of baseline energy use at Fort Irwin, a US Army Forces Command facility near Barstow, California. It is a companion report to Volume 1, Executive Summary, and Volume 3, Integrated Resource Assessment. The US Army Forces Command (FORSCOM) has tasked the US Department of Energy (DOE) Federal Energy Management Program (FEMP), supported by the Pacific Northwest Laboratory (PNL), to identify, evaluate, and assist in acquiring all cost-effective energy projects at Fort Irwin. This is part of a model program that PNL has designed to support energy-use decisions in the federal sector. This program (1) identifies and evaluates all cost-effective energy projects; (2) develops a schedule at each installation for project acquisition considering project type, size, timing, and capital requirements, as well as energy and dollar savings; and (3) targets 100% of the financing required to implement energy efficiency projects. PNL applied this model program to Fort Irwin. This analysis examines the characteristics of electric, propane gas, and vehicle fuel use for a typical operating year. It records energy-use intensities for the facilities at Fort Irwin by building type and energy end use. It also breaks down building energy consumption by fuel type, energy end use, and building type. A complete energy consumption reconciliation is presented that accounts for all energy use among buildings, utilities, and applicable losses.

  5. Fuel Consumption per Vehicle.xls

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

    Selected Survey Years (Gallons) Survey Years Household Composition Households With Children... NA NA 609 597 625 665 Age of Oldest Child Under...

  6. Solid Waste Program technical baseline description

    SciTech Connect (OSTI)

    Carlson, A.B.

    1994-07-01

    The system engineering approach has been taken to describe the technical baseline under which the Solid Waste Program is currently operating. The document contains a mission analysis, function analysis, system definition, documentation requirements, facility and project bases, and uncertainties facing the program.

  7. Waste management project technical baseline description

    SciTech Connect (OSTI)

    Sederburg, J.P.

    1997-08-13

    A systems engineering approach has been taken to describe the technical baseline under which the Waste Management Project is currently operating. The document contains a mission analysis, function analysis, requirement analysis, interface definitions, alternative analysis, system definition, documentation requirements, implementation definitions, and discussion of uncertainties facing the Project.

  8. Indonesia-Danish Government Baseline Workstream | Open Energy...

    Open Energy Info (EERE)

    Indonesia-Danish Government Baseline Workstream Jump to: navigation, search Name Indonesia-Danish Government Baseline Workstream AgencyCompany Organization Danish Government...

  9. China-Danish Government Baseline Workstream | Open Energy Information

    Open Energy Info (EERE)

    Danish Government Baseline Workstream Jump to: navigation, search Name China-Danish Government Baseline Workstream AgencyCompany Organization Danish Government Partner Danish...

  10. UNFCCC-Consolidated baseline and monitoring methodology for landfill...

    Open Energy Info (EERE)

    Consolidated baseline and monitoring methodology for landfill gas project activities Jump to: navigation, search Tool Summary LAUNCH TOOL Name: UNFCCC-Consolidated baseline and...

  11. India-Danish Government Baseline Workstream | Open Energy Information

    Open Energy Info (EERE)

    Danish Government Baseline Workstream Jump to: navigation, search Name India-Danish Government Baseline Workstream AgencyCompany Organization Danish Government Partner Danish...

  12. Baseline and Target Values for PV Forecasts: Toward Improved...

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

    Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting ... Baseline and Target Values for PV Forecasts: Toward Improved Solar Power Forecasting Jie ...

  13. EA-1943: Construction and Operation of the Long Baseline Neutrino...

    Energy Savers [EERE]

    43: Construction and Operation of the Long Baseline Neutrino Facility and Deep Underground ... EA-1943: Construction and Operation of the Long Baseline Neutrino Facility and Deep ...

  14. South Africa-Danish Government Baseline Workstream | Open Energy...

    Open Energy Info (EERE)

    Baseline Workstream Jump to: navigation, search Name South Africa-Danish Government Baseline Workstream AgencyCompany Organization Danish Government Partner Danish Ministry for...

  15. NREL: Energy Analysis - Annual Technology Baseline and Standard...

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

    Annual Technology Baseline and Standard Scenarios - Legacy Versions This section contains earlier versions of NREL's Annual Technology Baseline and Standard Scenarios products. ...

  16. Brazil-Danish Government Baseline Workstream | Open Energy Information

    Open Energy Info (EERE)

    Danish Government Baseline Workstream Jump to: navigation, search Name Brazil-Danish Government Baseline Workstream AgencyCompany Organization Danish Government Partner Danish...

  17. Mexico-Danish Government Baseline Workstream | Open Energy Information

    Open Energy Info (EERE)

    Danish Government Baseline Workstream Jump to: navigation, search Name Mexico-Danish Government Baseline Workstream AgencyCompany Organization Danish Government Partner Danish...

  18. US WNC MO Site Consumption

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

    to historically lower residential electricity prices in the state. * Missouri ... CONSUMPTION BY END USE Consumption of energy for the four major end uses in Missouri homes is ...

  19. Smart Meter Driven Segmentation: What Your Consumption Says About You

    SciTech Connect (OSTI)

    Albert, A; Rajagopal, R

    2013-11-01

    With the rollout of smart metering infrastructure at scale, demand-response (DR) programs may now be tailored based on users' consumption patterns as mined from sensed data. For issuing DR events it is key to understand the inter-temporal consumption dynamics as to appropriately segment the user population. We propose to infer occupancy states from consumption time series data using a hidden Markov model framework. Occupancy is characterized in this model by 1) magnitude, 2) duration, and 3) variability. We show that users may be grouped according to their consumption patterns into groups that exhibit qualitatively different dynamics that may be exploited for program enrollment purposes. We investigate empirically the information that residential energy consumers' temporal energy demand patterns characterized by these three dimensions may convey about their demographic, household, and appliance stock characteristics. Our analysis shows that temporal patterns in the user's consumption data can predict with good accuracy certain user characteristics. We use this framework to argue that there is a large degree of individual predictability in user consumption at a population level.

  20. Baseline Microstructural Characterization of Outer 3013 Containers

    SciTech Connect (OSTI)

    Zapp, Phillip E.; Dunn, Kerry A

    2005-07-31

    Three DOE Standard 3013 outer storage containers were examined to characterize the microstructure of the type 316L stainless steel material of construction. Two of the containers were closure-welded yielding production-quality outer 3013 containers; the third examined container was not closed. Optical metallography and Knoop microhardness measurements were performed to establish a baseline characterization that will support future destructive examinations of 3013 outer containers in the storage inventory. Metallography revealed the microstructural features typical of this austenitic stainless steel as it is formed and welded. The grains were equiaxed with evident annealing twins. Flow lines were prominent in the forming directions of the cylindrical body and flat lids and bottom caps. No adverse indications were seen. Microhardness values, although widely varying, were consistent with annealed austenitic stainless steel. The data gathered as part of this characterization will be used as a baseline for the destructive examination of 3013 containers removed from the storage inventory.

  1. Engineering task plan TWRS technical baseline completion

    SciTech Connect (OSTI)

    Moore, T.L

    1996-03-08

    The Tank Waste Remediation System (TWRS) includes many activities required to remediate the radioactive waste stored in underground waste storage tanks. These activities include routine monitoring of the waste, facilities maintenance, upgrades to existing equipment, and installation of new equipment necessary to manage, retrieve, process, and dispose of the waste. In order to ensure that these multiple activities are integrated, cost effective, and necessary, a sound technical baseline is required from which all activities can be traced and measured. The process by which this technical baseline is developed will consist of the identification of functions, requirements, architecture, and test (FRAT) methodology. This process must be completed for TWRS to a level that provides the technical basis for all facility/system/component maintenance, upgrades, or new equipment installation.

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

    Gasoline and Diesel Fuel Update (EIA)

    Because of the impacts of residential sector energy use on the environment and the economy, this study was undertaken to help provide a better understanding of the factors ...

  3. The Fermilab long-baseline neutrino program

    SciTech Connect (OSTI)

    Goodman, M.; MINOS Collaboration

    1997-10-01

    Fermilab is embarking upon a neutrino oscillation program which includes a long-baseline neutrino experiment MINOS. MINOS will be a 10 kiloton detector located 730 km Northwest of Fermilab in the Soudan underground laboratory. It will be sensitive to neutrino oscillations with parameters above {Delta}m{sup 2} {approximately} 3 {times} 10{sup {minus}3} eV{sup 2} and sin{sup 2}(2{theta}) {approximately} 0.02.

  4. Systematic errors in long baseline oscillation experiments

    SciTech Connect (OSTI)

    Harris, Deborah A.; /Fermilab

    2006-02-01

    This article gives a brief overview of long baseline neutrino experiments and their goals, and then describes the different kinds of systematic errors that are encountered in these experiments. Particular attention is paid to the uncertainties that come about because of imperfect knowledge of neutrino cross sections and more generally how neutrinos interact in nuclei. Near detectors are planned for most of these experiments, and the extent to which certain uncertainties can be reduced by the presence of near detectors is also discussed.

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

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    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

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

    SciTech Connect (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.; 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.

  7. Module 7 - Integrated Baseline Review and Change Control | Department of

    Office of Environmental Management (EM)

    Energy 7 - Integrated Baseline Review and Change Control Module 7 - Integrated Baseline Review and Change Control This module focuses on integrated baseline reviews (IBR) and change control. This module outlines the objective and responsibility of an integrated baseline review. Additionally, this module will discuss the change control process required for implementing earned value. Begin Module >> (418.59

  8. Examining Uncertainty in Demand Response Baseline Models and Variability in Automated Response to Dynamic Pricing

    SciTech Connect (OSTI)

    Mathieu, Johanna L.; Callaway, Duncan S.; Kiliccote, Sila

    2011-08-15

    Controlling electric loads to deliver power system services presents a number of interesting challenges. For example, changes in electricity consumption of Commercial and Industrial (C&I) facilities are usually estimated using counterfactual baseline models, and model uncertainty makes it difficult to precisely quantify control responsiveness. Moreover, C&I facilities exhibit variability in their response. This paper seeks to understand baseline model error and demand-side variability in responses to open-loop control signals (i.e. dynamic prices). Using a regression-based baseline model, we define several Demand Response (DR) parameters, which characterize changes in electricity use on DR days, and then present a method for computing the error associated with DR parameter estimates. In addition to analyzing the magnitude of DR parameter error, we develop a metric to determine how much observed DR parameter variability is attributable to real event-to-event variability versus simply baseline model error. Using data from 38 C&I facilities that participated in an automated DR program in California, we find that DR parameter errors are large. For most facilities, observed DR parameter variability is likely explained by baseline model error, not real DR parameter variability; however, a number of facilities exhibit real DR parameter variability. In some cases, the aggregate population of C&I facilities exhibits real DR parameter variability, resulting in implications for the system operator with respect to both resource planning and system stability.

  9. Fort Drum integrated resource assessment. Volume 2, Baseline detail

    SciTech Connect (OSTI)

    Dixon, D.R.; Armstrong, P.R.; Brodrick, J.R.; Daellenbach, K.K.; Di Massa, F.V.; Keller, J.M.; Richman, E.E.; Sullivan, G.P.; Wahlstrom, R.R.

    1992-12-01

    The US Army Forces Command (FORSCOM) has tasked the Pacific Northwest Laboratory (PNL) as the lead laboratory supporting the US Department of Energy (DOE) Federal Energy Management Program`s mission to identify, evaluate, and assist in acquiring all cost-effective energy projects at Fort Drum. This is a model program PNL is designing for federal customers served by the Niagara Mohawk Power Company. It will identify and evaluate all electric and fossil fuel cost-effective energy projects; develop a schedule at each installation for project acquisition considering project type, size, timing, and capital requirements, as well as energy and dollar savings; and secure 100% of the financing required to implement electric energy efficiency projects from Niagara Mohawk and have Niagara Mohawk procure the necessary contractors to perform detailed audits and install the technologies. This report documents the assessment of baseline energy use at one of Niagara Mohawk`s primary federal facilities, the FORSCOM Fort Drum facility located near Watertown, New York. It is a companion report to Volume 1, the Executive Summary, and Volume 3, the Resource Assessment. This analysis examines the characteristics of electric, gas, oil, propane, coal, and purchased thermal capacity use for fiscal year (FY) 1990. It records energy-use intensities for the facilities at Fort Drum by building type and energy end use. It also breaks down building energy consumption by fuel type, energy end use, and building type. A complete energy consumption reconciliation is presented that includes the accounting of all energy use among buildings, utilities, central systems, and applicable losses.

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

    SciTech Connect (OSTI)

    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)

  11. Determinants of residential electricity consumption: Using smart meter data to examine the effect of climate, building characteristics, appliance stock, and occupants' behavior

    SciTech Connect (OSTI)

    Kavousian, A; Rajagopal, R; Fischer, M

    2013-06-15

    We propose a method to examine structural and behavioral determinants of residential electricity consumption, by developing separate models for daily maximum (peak) and minimum (idle) consumption. We apply our method on a data set of 1628 households' electricity consumption. The results show that weather, location and floor area are among the most important determinants of residential electricity consumption. In addition to these variables, number of refrigerators and entertainment devices (e.g., VCRs) are among the most important determinants of daily minimum consumption, while number of occupants and high-consumption appliances such as electric water heaters are the most significant determinants of daily maximum consumption. Installing double-pane windows and energy-efficient lights helped to reduce consumption, as did the energy-conscious use of electric heater. Acknowledging climate change as a motivation to save energy showed correlation with lower electricity consumption. Households with individuals over 55 or between 19 and 35 years old recorded lower electricity consumption, while pet owners showed higher consumption. Contrary to some previous studies, we observed no significant correlation between electricity consumption and income level, home ownership, or building age. Some otherwise energy-efficient features such as energy-efficient appliances, programmable thermostats, and insulation were correlated with slight increase in electricity consumption. (C) 2013 Elsevier Ltd. All rights reserved.

  12. Lifestyle Factors in U.S. Residential Electricity Consumption

    SciTech Connect (OSTI)

    Sanquist, Thomas F.; Orr, Heather M.; Shui, Bin; Bittner, Alvah C.

    2012-03-30

    A multivariate statistical approach to lifestyle analysis of residential electricity consumption is described and illustrated. Factor analysis of selected variables from the 2005 U.S. Residential Energy Consumption Survey (RECS) identified five lifestyle factors reflecting social and behavioral choices associated with air conditioning, laundry usage, personal computer usage, climate zone of residence, and TV use. These factors were also estimated for 2001 RECS data. Multiple regression analysis using the lifestyle factors yields solutions accounting for approximately 40% of the variance in electricity consumption for both years. By adding the associated household and market characteristics of income, local electricity price and access to natural gas, variance accounted for is increased to approximately 54%. Income contributed only {approx}1% unique variance to the 2005 and 2001 models, indicating that lifestyle factors reflecting social and behavioral choices better account for consumption differences than income. This was not surprising given the 4-fold range of energy use at differing income levels. Geographic segmentation of factor scores is illustrated, and shows distinct clusters of consumption and lifestyle factors, particularly in suburban locations. The implications for tailored policy and planning interventions are discussed in relation to lifestyle issues.

  13. Strategies for Collecting Household Energy Data | Department of Energy

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

    Collecting Household Energy Data Strategies for Collecting Household Energy Data Better Buildings Neighborhood Program Data and Evaluation Peer Exchange Call: Strategies for Collecting Household Energy Data, Call Slides and Discussion Summary, July 19, 2012. Call Slides and Discussion Summary (700.06 KB) More Documents & Publications Homeowner and Contractor Surveys Mastermind: Jim Mikel, Spirit Foundation Generating Energy Efficiency Project Leads and Allocating Leads to Contractors

  14. Delivering Energy Efficiency to Middle Income Single Family Households

    SciTech Connect (OSTI)

    none,

    2011-12-01

    Provides state and local policymakers with information on successful approaches to the design and implementation of residential efficiency programs for households ineligible for low-income programs.

  15. Barriers to household investment in residential energy conservation: preliminary assessment

    SciTech Connect (OSTI)

    Hoffman, W.L.

    1982-12-01

    A general assessment of the range of barriers which impede household investments in weatherization and other energy efficiency improvements for their homes is provided. The relationship of similar factors to households' interest in receiving a free energy audits examined. Rates of return that underly household investments in major conservation improvements are assessed. A special analysis of household knowledge of economically attractive investments is provided that compares high payback improvements specified by the energy audit with the list of needed or desirable conservation improvements identified by respondents. (LEW)

  16. " Million U.S. Housing Units" ,,"2005 Household...

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

    8 Water Heating Characteristics by Household Income, 2005" " Million U.S. Housing Units" ... to 79,999","80,000 or More" "Water Heating Characteristics" ...

  17. Global Nuclear Energy Partnership Waste Treatment Baseline

    SciTech Connect (OSTI)

    Dirk Gombert; William Ebert; James Marra; Robert Jubin; John Vienna

    2008-05-01

    The Global Nuclear Energy Partnership program (GNEP) is designed to demonstrate a proliferation-resistant and sustainable integrated nuclear fuel cycle that can be commercialized and used internationally. Alternative stabilization concepts for byproducts and waste streams generated by fuel recycling processes were evaluated and a baseline of waste forms was recommended for the safe disposition of waste streams. Waste forms are recommended based on the demonstrated or expected commercial practicability and technical maturity of the processes needed to make the waste forms, and performance of the waste form materials when disposed. Significant issues remain in developing technologies to process some of the wastes into the recommended waste forms, and a detailed analysis of technology readiness and availability may lead to the choice of a different waste form than what is recommended herein. Evolving regulations could also affect the selection of waste forms.

  18. Grocery 2009 TSD Miami Baseline | Open Energy Information

    Open Energy Info (EERE)

    Jump to: navigation, search Model Name Grocery 2009 TSD Miami Baseline Building Type Food Sales Model Type Baseline Model Target Type ASHRAE 90.1 2004 Model Year 2009 IDF file...

  19. Grocery 2009 TSD Chicago Baseline | Open Energy Information

    Open Energy Info (EERE)

    Jump to: navigation, search Model Name Grocery 2009 TSD Chicago Baseline Building Type Food Sales Model Type Baseline Model Target Type ASHRAE 90.1 2004 Model Year 2009 IDF file...

  20. Proposed Methodology for LEED Baseline Refrigeration Modeling (Presentation)

    SciTech Connect (OSTI)

    Deru, M.

    2011-02-01

    This PowerPoint presentation summarizes a proposed methodology for LEED baseline refrigeration modeling. The presentation discusses why refrigeration modeling is important, the inputs of energy models, resources, reference building model cases, baseline model highlights, example savings calculations and results.

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

    Gasoline and Diesel Fuel Update (EIA)

    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...

  2. Health Care Buildings: Consumption Tables

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

    Consumption Tables Sum of Major Fuel Consumption by Size and Type of Health Care Building Total (trillion Btu) per Building (million Btu) per Square Foot (thousand Btu) Dollars per...

  3. US ENC WI Site Consumption

    Gasoline and Diesel Fuel Update (EIA)

    electricity consumption in the state low relative to other parts of the U.S. * Wisconsin homes are typically larger and older than homes in other states. CONSUMPTION BY END USE ...

  4. US WSC TX Site Consumption

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

    than the U.S. average. * Average electricity consumption per Texas home is 26% higher than ... CONSUMPTION BY END USE Compared to other areas of the United States, the warmer ...

  5. US ENC MI Site Consumption

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

    site electricity consumption in the state low relative to other parts of the U.S. * Michigan homes are typically older than homes in other states. CONSUMPTION BY END USE Since ...

  6. Energy baseline and energy efficiency resource opportunities for the Forest Products Laboratory, Madison, Wisconsin

    SciTech Connect (OSTI)

    Mazzucchi, R.P.; Richman, E.E.; Parker, G.B.

    1993-08-01

    This report provides recommendations to improve the energy use efficiency at the Forest Products Laboratory in Madison, Wisconsin. The assessment focuses upon the four largest buildings and central heating plant at the facility comprising a total of approximately 287,000 square feet. The analysis is comprehensive in nature, intended primarily to determine what if any energy efficiency improvements are warranted based upon the potential for cost-effective energy savings. Because of this breadth, not all opportunities are developed in detail; however, baseline energy consumption data and energy savings concepts are described to provide a foundation for detailed investigation and project design where warranted.

  7. Griffiss AFB integrated resource assessment. Volume 2, Electric baseline detail

    SciTech Connect (OSTI)

    Dixon, D.R.; Armstrong, P.R.; Keller, J.M.

    1993-02-01

    The US Air Force Air Combat Command has tasked the Pacific Northwest Laboratory (PNL) as the lead laboratory supporting the US Department of Energy (DOE) Federal Energy Management Program`s (FEMP) mission to identify, evaluate, and assist in acquiring all cost-effective energy projects at Griffiss Air Force Base (AFB). This is a model program PNL is designing for federal customers served by the Niagara Mohawk Power Company (Niagara Mohawk). It will (1) identify and evaluate all electric cost-effective energy projects; (2) develop a schedule at each installation for project acquisition considering project type, size, timing, and capital requirements, as well as energy and dollar savings; and (3) secure 100% of the financing required to implement electric energy efficiency projects from Niagara Mohawk and have Niagara Mohawk procure the necessary contractors to perform detailed audits and install the technologies. This report documents the assessment of baseline energy use at one of Niagara Mohawk`s primary federal facilities, Griffiss AFB, an Air Combat Command facility located near Rome, New York. It is a companion report to Volume 1, the Executive Summary, and Volume 3, the Electric Resource Assessment. The analysis examines the characteristics of electric, gas, oil, propane, coal, and purchased thermal capacity use for fiscal year (FY) 1990. The results include energy-use intensities for the facilities at Griffiss AFB by building type and electric energy end use. A complete electric energy consumption reconciliation is presented that accounts for the distribution of all major electric energy uses and losses among buildings, utilities, and central systems.

  8. Gated integrator with signal baseline subtraction

    DOE Patents [OSTI]

    Wang, X.

    1996-12-17

    An ultrafast, high precision gated integrator includes an opamp having differential inputs. A signal to be integrated is applied to one of the differential inputs through a first input network, and a signal indicative of the DC offset component of the signal to be integrated is applied to the other of the differential inputs through a second input network. A pair of electronic switches in the first and second input networks define an integrating period when they are closed. The first and second input networks are substantially symmetrically constructed of matched components so that error components introduced by the electronic switches appear symmetrically in both input circuits and, hence, are nullified by the common mode rejection of the integrating opamp. The signal indicative of the DC offset component is provided by a sample and hold circuit actuated as the integrating period begins. The symmetrical configuration of the integrating circuit improves accuracy and speed by balancing out common mode errors, by permitting the use of high speed switching elements and high speed opamps and by permitting the use of a small integrating time constant. The sample and hold circuit substantially eliminates the error caused by the input signal baseline offset during a single integrating window. 5 figs.

  9. Gated integrator with signal baseline subtraction

    DOE Patents [OSTI]

    Wang, Xucheng

    1996-01-01

    An ultrafast, high precision gated integrator includes an opamp having differential inputs. A signal to be integrated is applied to one of the differential inputs through a first input network, and a signal indicative of the DC offset component of the signal to be integrated is applied to the other of the differential inputs through a second input network. A pair of electronic switches in the first and second input networks define an integrating period when they are closed. The first and second input networks are substantially symmetrically constructed of matched components so that error components introduced by the electronic switches appear symmetrically in both input circuits and, hence, are nullified by the common mode rejection of the integrating opamp. The signal indicative of the DC offset component is provided by a sample and hold circuit actuated as the integrating period begins. The symmetrical configuration of the integrating circuit improves accuracy and speed by balancing out common mode errors, by permitting the use of high speed switching elements and high speed opamps and by permitting the use of a small integrating time constant. The sample and hold circuit substantially eliminates the error caused by the input signal baseline offset during a single integrating window.

  10. Arc melter demonstration baseline test results

    SciTech Connect (OSTI)

    Soelberg, N.R.; Chambers, A.G.; Anderson, G.L.; Oden, L.L.; O`Connor, W.K.; Turner, P.C.

    1994-07-01

    This report describes the test results and evaluation for the Phase 1 (baseline) arc melter vitrification test series conducted for the Buried Waste Integrated Demonstration program (BWID). Phase 1 tests were conducted on surrogate mixtures of as-incinerated wastes and soil. Some buried wastes, soils, and stored wastes at the INEL and other DOE sites, are contaminated with transuranic (TRU) radionuclides and hazardous organics and metals. The high temperature environment in an electric arc furnace may be used to process these wastes to produce materials suitable for final disposal. An electric arc furnace system can treat heterogeneous wastes and contaminated soils by (a) dissolving and retaining TRU elements and selected toxic metals as oxides in the slag phase, (b) destroying organic materials by dissociation, pyrolyzation, and combustion, and (c) capturing separated volatilized metals in the offgas system for further treatment. Structural metals in the waste may be melted and tapped separately for recycle or disposal, or these metals may be oxidized and dissolved into the slag. The molten slag, after cooling, will provide a glass/ceramic final waste form that is homogeneous, highly nonleachable, and extremely durable. These features make this waste form suitable for immobilization of TRU radionuclides and toxic metals for geologic timeframes. Further, the volume of contaminated wastes and soils will be substantially reduced in the process.

  11. LTC vacuum blasting machine (concrete): Baseline report

    SciTech Connect (OSTI)

    1997-07-31

    The LTC shot blast technology was tested and is being evaluated at Florida International University (FIU) as a baseline technology. In conjunction with FIU`s evaluation of efficiency and cost, this report covers the evaluation conducted for safety and health issues. It is a commercially available technology and has been used for various projects at locations throughout the country. The LTC 1073 Vacuum Blasting Machine uses a high-capacity, direct-pressure blasting system which incorporates a continuous feed for the blast media. The blast media cleans the surface within the contained brush area of the blast. It incorporates a vacuum system which removes dust and debris from the surface as it is blasted. The safety and health evaluation during the testing demonstration focused on two main areas of exposure: dust and noise. Dust exposure during maintenance activities was minimal, but due to mechanical difficulties dust monitoring could not be conducted during operation. Noise exposure was significant. Further testing for each of these exposures is recommended because of the outdoor environment where the testing demonstration took place. This may cause the results to be inaccurate. It is feasible that the dust and noise levels will be higher in an enclosed environment. In addition, other safety and health issues found were ergonomics, heat stress, tripping hazards, electrical hazards, lockout/tagout, and arm-hand vibration.

  12. LTC vacuum blasting machine (metal): Baseline report

    SciTech Connect (OSTI)

    1997-07-31

    The LTC coating removal technology was tested and is being evaluated at Florida International University (FIU) as a baseline technology. In conjunction with evaluation of efficiency and cost, this report covers the evaluation conducted for safety and health issues. It is a commercially available technology and has been used for various projects at locations throughout the country. The LTC coating removal system consisted of several hand tools, a Roto Peen scaler, and a needlegun. They are designed to remove coatings from steel, concrete, brick, and wood. These hand tools are used with the LTC PTC-6 vacuum system to capture dust and debris as removal of the coating takes place. The safety and health evaluation during the testing demonstration focused on two main areas of exposure: dust and noise. The dust exposure was minimal but noise exposure was significant. Further testing for each exposure is recommended because of the environment where the testing demonstration took place. It is feasible that the dust and noise levels will be higher in an enclosed operating environment of different construction. In addition, other areas of concern found were arm-hand vibration, whole-body vibration, ergonomics, heat stress, tripping hazards, electrical hazards, machine guarding, and lockout/tagout.

  13. Pentek metal coating removal system: Baseline report

    SciTech Connect (OSTI)

    1997-07-31

    The Pentek coating removal technology was tested and is being evaluated at Florida International University (FIU) as a baseline technology. In conjunction with FIU`s evaluation of efficiency and cost, this report covers evaluation conducted for safety and health issues. It is a commercially available technology and has been used for various projects at locations throughout the country. The Pentek coating removal system consisted of the ROTO-PEEN Scaler, CORNER-CUTTER{reg_sign}, and VAC-PAC{reg_sign}. They are designed to remove coatings from steel, concrete, brick, and wood. The Scaler uses 3M Roto Peen tungsten carbide cutters while the CORNER-CUTTER{reg_sign} uses solid needles for descaling activities. These hand tools are used with the VAC-PAC{reg_sign} vacuum system to capture dust and debris as removal of the coating takes place. The safety and health evaluation during the testing demonstration focused on two main areas of exposure: dust and noise. Dust exposure minimal, but noise exposure was significant. Further testing for each exposure is recommended because of the environment where the testing demonstration took place. It is feasible that the dust and noise levels will be higher in an enclosed operating environment of different construction. In addition, other areas of concern found were arm-hand vibration, whole-body, ergonomics, heat stress, tripping hazards, electrical hazards, machine guarding, and lockout/tagout.

  14. Baseline air quality study at Fermilab

    SciTech Connect (OSTI)

    Dave, M.J.; Charboneau, R.

    1980-10-01

    Air quality and meteorological data collected at Fermi National Accelerator Laboratory are presented. The data represent baseline values for the pre-construction phase of a proposed coal-gasification test facility. Air quality data were characterized through continuous monitoring of gaseous pollutants, collection of meteorological data, data acquisition and reduction, and collection and analysis of discrete atmospheric samples. Seven air quality parameters were monitored and recorded on a continuous real-time basis: sulfur dioxide, ozone, total hydrocarbons, nonreactive hydrocarbons, nitric oxide, nitrogen oxides, and carbon monoxide. A 20.9-m tower was erected near Argonne's mobile air monitoring laboratory, which was located immediately downwind of the proposed facility. The tower was instrumented at three levels to collect continuous meteorological data. Wind speed was monitored at three levels; wind direction, horizontal and vertical, at the top level; ambient temperature at the top level; and differential temperature between all three levels. All continuously-monitored parameters were digitized and recorded on magnetic tape. Appropriate software was prepared to reduce the data. Statistical summaries, grphical displays, and correlation studies also are presented.

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

    Buildings Energy Data Book [EERE]

    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

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

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

    loads account for an increasingly large portion of commercial electricity consumption. ... This includes analysis of their unit energy consumption and annual electricity consumption ...

  17. Perceptions of risk among households in two Australian coastal communities

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Elrick-Barr, Carmen E.; Smith, Timothy F.; Thomsen, Dana C.; Preston, Benjamin L.

    2015-04-20

    There is limited knowledge of risk perceptions in coastal communities despite their vulnerability to a range of risks including the impacts of climate change. A survey of 400 households in two Australian coastal communities, combined with semi-structured interviews, provides insight into household perceptions of the relative importance of climatic and non-climatic risks and the subsequent risk priorities that may inform household adaptive action. In contrast to previous research, the results demonstrated that geographic location and household characteristics might not affect perceptions of vulnerability to environmental hazards. However, past experience was a significant influence, raising the priority of environmental concerns. Overall,more » the results highlight the priority concerns of coastal households (from finance, to health and environment) and suggest to increase the profile of climate issues in coastal communities climate change strategies need to better demonstrate links between climate vulnerability and other household concerns. Moreover, promoting generic capacities in isolation from understanding the context in which households construe climate risks is unlikely to yield the changes required to decrease the vulnerability of coastal communities.« less

  18. Perceptions of risk among households in two Australian coastal communities

    SciTech Connect (OSTI)

    Elrick-Barr, Carmen E.; Smith, Timothy F.; Thomsen, Dana C.; Preston, Benjamin L.

    2015-04-20

    There is limited knowledge of risk perceptions in coastal communities despite their vulnerability to a range of risks including the impacts of climate change. A survey of 400 households in two Australian coastal communities, combined with semi-structured interviews, provides insight into household perceptions of the relative importance of climatic and non-climatic risks and the subsequent risk priorities that may inform household adaptive action. In contrast to previous research, the results demonstrated that geographic location and household characteristics might not affect perceptions of vulnerability to environmental hazards. However, past experience was a significant influence, raising the priority of environmental concerns. Overall, the results highlight the priority concerns of coastal households (from finance, to health and environment) and suggest to increase the profile of climate issues in coastal communities climate change strategies need to better demonstrate links between climate vulnerability and other household concerns. Moreover, promoting generic capacities in isolation from understanding the context in which households construe climate risks is unlikely to yield the changes required to decrease the vulnerability of coastal communities.

  19. Reconstructing householder vectors from Tall-Skinny QR

    DOE Public Access Gateway for Energy & Science Beta (PAGES Beta)

    Ballard, Grey Malone; Demmel, James; Grigori, Laura; Jacquelin, Mathias; Knight, Nicholas; Nguyen, Hong Diep

    2015-08-05

    The Tall-Skinny QR (TSQR) algorithm is more communication efficient than the standard Householder algorithm for QR decomposition of matrices with many more rows than columns. However, TSQR produces a different representation of the orthogonal factor and therefore requires more software development to support the new representation. Further, implicitly applying the orthogonal factor to the trailing matrix in the context of factoring a square matrix is more complicated and costly than with the Householder representation. We show how to perform TSQR and then reconstruct the Householder vector representation with the same asymptotic communication efficiency and little extra computational cost. We demonstratemore » the high performance and numerical stability of this algorithm both theoretically and empirically. The new Householder reconstruction algorithm allows us to design more efficient parallel QR algorithms, with significantly lower latency cost compared to Householder QR and lower bandwidth and latency costs compared with Communication-Avoiding QR (CAQR) algorithm. Experiments on supercomputers demonstrate the benefits of the communication cost improvements: in particular, our experiments show substantial improvements over tuned library implementations for tall-and-skinny matrices. Furthermore, we also provide algorithmic improvements to the Householder QR and CAQR algorithms, and we investigate several alternatives to the Householder reconstruction algorithm that sacrifice guarantees on numerical stability in some cases in order to obtain higher performance.« less

  20. Reconstructing householder vectors from Tall-Skinny QR

    SciTech Connect (OSTI)

    Ballard, Grey Malone; Demmel, James; Grigori, Laura; Jacquelin, Mathias; Knight, Nicholas; Nguyen, Hong Diep

    2015-08-05

    The Tall-Skinny QR (TSQR) algorithm is more communication efficient than the standard Householder algorithm for QR decomposition of matrices with many more rows than columns. However, TSQR produces a different representation of the orthogonal factor and therefore requires more software development to support the new representation. Further, implicitly applying the orthogonal factor to the trailing matrix in the context of factoring a square matrix is more complicated and costly than with the Householder representation. We show how to perform TSQR and then reconstruct the Householder vector representation with the same asymptotic communication efficiency and little extra computational cost. We demonstrate the high performance and numerical stability of this algorithm both theoretically and empirically. The new Householder reconstruction algorithm allows us to design more efficient parallel QR algorithms, with significantly lower latency cost compared to Householder QR and lower bandwidth and latency costs compared with Communication-Avoiding QR (CAQR) algorithm. Experiments on supercomputers demonstrate the benefits of the communication cost improvements: in particular, our experiments show substantial improvements over tuned library implementations for tall-and-skinny matrices. Furthermore, we also provide algorithmic improvements to the Householder QR and CAQR algorithms, and we investigate several alternatives to the Householder reconstruction algorithm that sacrifice guarantees on numerical stability in some cases in order to obtain higher performance.

  1. Fact #618: April 12, 2010 Vehicles per Household and Other Demographic...

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

    per Household and Other Demographic Statistics Fact 618: April 12, 2010 Vehicles per Household and Other Demographic Statistics Since 1969, the number of vehicles per ...

  2. "Table HC7.5 Space Heating Usage Indicators by Household Income...

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

    ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ... for 2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ...

  3. "Table HC7.12 Home Electronics Usage Indicators by Household...

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

    ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ... for 2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ...

  4. "Table HC7.10 Home Appliances Usage Indicators by Household...

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

    ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ... for 2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ...

  5. Fact #748: October 8, 2012 Components of Household Expenditures on

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

    Transportation, 1984-2010 | Department of Energy 8: October 8, 2012 Components of Household Expenditures on Transportation, 1984-2010 Fact #748: October 8, 2012 Components of Household Expenditures on Transportation, 1984-2010 The overall share of annual household expenditures for transportation was lower in 2010 than it was in 1984, reaching its lowest point in 2009 at 15.5%. In the early to mid-1980s when oil prices were high, gasoline and motor oil made up a larger share of transportation

  6. Using Electricity",,,"Electricity Consumption",,,"Electricity...

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

    . Total Electricity Consumption and Expenditures, 2003" ,"All Buildings* Using Electricity",,,"Electricity Consumption",,,"Electricity Expenditures" ,"Number of Buildings...

  7. The Impact of Carbon Control on Low-Income Household Electricity and Gasoline Expenditures

    SciTech Connect (OSTI)

    Eisenberg, Joel Fred

    2008-06-01

    In July of 2007 The Department of Energy's (DOE's) Energy Information Administration (EIA) released its impact analysis of 'The Climate Stewardship And Innovation Act of 2007,' known as S.280. This legislation, cosponsored by Senators Joseph Lieberman and John McCain, was designed to significantly cut U.S. greenhouse gas emissions over time through a 'cap-and-trade' system, briefly described below, that would gradually but extensively reduce such emissions over many decades. S.280 is one of several proposals that have emerged in recent years to come to grips with the nation's role in causing human-induced global climate change. EIA produced an analysis of this proposal using the National Energy Modeling System (NEMS) to generate price projections for electricity and gasoline under the proposed cap-and-trade system. Oak Ridge National Laboratory integrated those price projections into a data base derived from the EIA Residential Energy Consumption Survey (RECS) for 2001 and the EIA public use files from the National Household Transportation Survey (NHTS) for 2001 to develop a preliminary assessment of impact of these types of policies on low-income consumers. ORNL will analyze the impacts of other specific proposals as EIA makes its projections for them available. The EIA price projections for electricity and gasoline under the S.280 climate change proposal, integrated with RECS and NHTS for 2001, help identify the potential effects on household electric bills and gasoline expenditures, which represent S.280's two largest direct impacts on low-income household budgets in the proposed legislation. The analysis may prove useful in understanding the needs and remedies for the distributive impacts of such policies and how these may vary based on patterns of location, housing and vehicle stock, and energy usage.

  8. Mid-Atlantic Baseline Studies Project | Department of Energy

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

    Mid-Atlantic Baseline Studies Project Mid-Atlantic Baseline Studies Project Funded by the Department of Energy, along with a number of partners, the collaborative Mid-Atlantic Baseline Studies Project, led by the Biodiversity Research Institute (BRI), helps improve understanding of species composition and use of the Mid-Atlantic marine environment in order to promote more sustainable offshore wind development. This first-of-its-kind study along the Eastern Seaboard of the United States delivers

  9. Long-Baseline Neutrino Facility / Deep Underground Neutrino Project

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

    (LBNF-DUNE) | Department of Energy Long-Baseline Neutrino Facility / Deep Underground Neutrino Project (LBNF-DUNE) Long-Baseline Neutrino Facility / Deep Underground Neutrino Project (LBNF-DUNE) Long-Baseline Neutrino Facility / Deep Underground Neutrino Project (LBNF-DUNE) Chris Mossey, Deputy Lab Director (Fermi) and Project Director for LBNF-DUNE March 23, 2016 Presentation (5.94 MB) Key Resources PMCDP EVMS PARS IIe FPD Resource Center PM Newsletter Forms and Templates More Documents

  10. 2016 Annual Technology Baseline (ATB) (Conference) | SciTech Connect

    Office of Scientific and Technical Information (OSTI)

    Conference: 2016 Annual Technology Baseline (ATB) Citation Details In-Document Search Title: 2016 Annual Technology Baseline (ATB) Consistent cost and performance data for various electricity generation technologies can be difficult to find and may change frequently for certain technologies. With the Annual Technology Baseline (ATB), National Renewable Energy Laboratory provides an organized and centralized dataset that was reviewed by internal and external experts. It uses the best information