National Library of Energy BETA

Sample records for household consumption profiles

  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, 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.

  6. 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.

  7. 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...

  8. 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.

  9. 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...

  10. 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.

  11. 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.

  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. 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.

  19. 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.

  20. 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 ...

  1. 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

  2. Profiling an application for power consumption during execution on a plurality of compute nodes

    DOE Patents [OSTI]

    Archer, Charles J.; Blocksome, Michael A.; Peters, Amanda E.; Ratterman, Joseph D.; Smith, Brian E.

    2012-08-21

    Methods, apparatus, and products are disclosed for profiling an application for power consumption during execution on a compute node that include: receiving an application for execution on a compute node; identifying a hardware power consumption profile for the compute node, the hardware power consumption profile specifying power consumption for compute node hardware during performance of various processing operations; determining a power consumption profile for the application in dependence upon the application and the hardware power consumption profile for the compute node; and reporting the power consumption profile for the application.

  3. Profiling an application for power consumption during execution on a compute node

    DOE Patents [OSTI]

    Archer, Charles J; Blocksome, Michael A; Peters, Amanda E; Ratterman, Joseph D; Smith, Brian E

    2013-09-17

    Methods, apparatus, and products are disclosed for profiling an application for power consumption during execution on a compute node that include: receiving an application for execution on a compute node; identifying a hardware power consumption profile for the compute node, the hardware power consumption profile specifying power consumption for compute node hardware during performance of various processing operations; determining a power consumption profile for the application in dependence upon the application and the hardware power consumption profile for the compute node; and reporting the power consumption profile for the application.

  4. 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.

  5. 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...

  6. 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....

  7. 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

  8. 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...

  9. 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...

  10. 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...

  11. 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...

  12. 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...

  13. 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...

  14. 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...

  15. 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...

  16. 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...

  17. 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...

  18. 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...

  19. 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...

  20. 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...

  1. 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...

  2. 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...

  3. 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...

  4. 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...

  5. 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...

  6. 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...

  7. 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...

  8. 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...

  9. 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...

  10. 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...

  11. 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 ...

  12. 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...

  13. 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...

  14. 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)...

  15. 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...

  16. 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...

  17. 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)...

  18. 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...

  19. Profiling Real-Time Electricity Consumption Data for Process Monitoring and Control

    SciTech Connect (OSTI)

    Omitaomu, Olufemi A

    2013-01-01

    Today, smart meters serve as key assets to utilities and their customers because they are capable of recording and communicating real-time energy usage data; thus, enabling better understanding of energy usage patterns. Other potential benefits of smart meters data include the ability to improve customer experience, grid reliability, outage management, and operational efficiency. Despite these tangible benefits, many utilities are inundated by data and remain uncertain about how to extract additional value from these deployed assets outside of billing operations. One way to overcome this challenge is the development of new metrics for classifying utility customers. Traditionally, utilities classified their customers based on their business nature (residential, commercial, and industrial) and/or their total annual consumption. While this classification is useful for some operational functions, it is too limited for designing effective monitoring and control strategies. In this paper, a data mining methodology is proposed for clustering and profiling smart meters data in order to form unique classes of customers exhibiting similar usage patterns. The developed clusters could help utilities in identifying opportunities for achieving some of the benefits of smart meters data.

  20. 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 ...

  1. 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.

  2. 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

  3. 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...

  4. 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 ...

  5. 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%

  6. 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...

  7. 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

  8. 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

  9. 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

  10. 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 ...

  11. 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 ...

  12. 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.

  13. 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

  14. 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. ...

  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. Profiling

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

    Profiling your application with Intel VTune at NERSC --- 1 --- VTune background and availability * Focus: O n---node p erformance a nalysis - Sampling a nd t race---based p rofiling - Performance c ounter i ntegra8on - Memory b andwidth a nalysis - On---node p arallelism: vectoriza8on a nd t hreading * Pre---defined a nalysis e xperiments * GUI a nd c ommand---line i nterface ( good f or h eadless collec?on a nd l ater a nalysis) * NERSC a vailability ( as t he vtune m odule) - Edison ( Dual 1

  20. 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

  1. 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

  2. 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.

  3. 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 ...

  4. 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 ...

  5. 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 ...

  6. 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 ...

  7. The scope of the Weatherization Assistance Program: Profile of the population in need

    SciTech Connect (OSTI)

    Eisenberg, J.F.; Michels, E.; Carroll, D.; Berdux, N.

    1994-03-01

    The U.S. Department of Energy (DOE) is conducting a national evaluation of its Weatherization Assistance Program, an energy efficiency program that provides financial assistance to qualifying low-income households for the {open_quotes}weatherization{close_quotes} of their housing units. The evaluation, being conducted for the Department by Oak Ridge National Laboratory (ORNL), is comprised of five studies. One of the five is a two-part analysis of the scope of the Weatherization Assistance Program and other resources devoted to low-income energy efficiency, including the number of dwellings weatherized to date and the population remaining to be served. This study is referred to here as the {open_quotes}Scope{close_quotes} study. This report presents the results of the second part of the {open_quotes}Scope{close_quotes} study, which investigates the characteristics of the population eligible for and in need of the DOE Weatherization Assistance Program - The Profile of the Population in Need. The {open_quotes}Profile{close_quotes} study is an attempt to use the Energy Information Administration`s Residential Energy Consumption Survey (RECS) for 1990 to define the weatherization-related characteristics of the low-income population. The RECS, a national survey with a sample size of 5,095 households, is the most reliable source for information regarding residential energy-use and housing characteristics because data is collected from fuel vendors on actual household energy bills and consumption for a large and representative sample of households.

  8. The Scope of the Weatherization Assistance Program: Profile of the Population in Need

    SciTech Connect (OSTI)

    Eisenberg, J.F.

    1994-01-01

    The U.S. Department of Energy (DOE) is conducting a national evaluation of its Weatherization Assistance Program, an energy efficiency program that provides financial assistance to qualifying low-income households for the ''weatherization'' of their housing units. The evaluation, being conducted for the Department by Oak Ridge National Laboratory (ORNL), is comprised of five studies. One of the five is a two-part analysis of the scope of the Weatherization Assistance Program and other resources devoted to low-income energy efficiency, including the number of dwellings weatherized to date and the population remaining to be served. This study is referred to here as the ''Scope'' study. This report presents the results of the second part of the ''Scope'' study, which investigates the characteristics of the population eligible for and in need of the DOE Weatherization Assistance Program--The Profile of the Population in Need. The ''Profile'' study is an attempt to use the Energy Information Administration's Residential Energy Consumption Survey (RECS) for 1990 to define the weatherization-related characteristics of the low-income population. The RECS, a national survey with a sample size of 5,095 households, is the most reliable source for information regarding residential energy-use and housing characteristics because data is collected from fuel vendors on actual household energy bills and consumption for a large and representative sample of households.

  9. 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

  10. 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

  11. 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.

  12. 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.

  13. 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)

  14. 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 ...

  15. 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 *...

  16. 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 ...

  17. 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

  18. 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

  19. 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

  20. 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

  1. 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

  2. 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

  3. 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 ...

  4. 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 ...

  5. 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 ...

  6. 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...

  7. 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.

  8. 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.

  9. 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

  10. 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

  11. 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

  12. 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.

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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 ...

  19. 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...

  20. 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

  1. 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

  2. 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

  3. 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.

  4. Building America Top Innovations Hall of Fame Profile … High...

    Energy Savers [EERE]

    ... Each home's 2.2-kW photovoltaic system produced about 3,330 kWh during the 12 months studied, about half the average consumption of each household (7,007 kWh). Premier Homes chose ...

  5. 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.

  6. 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

  7. 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

  8. 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

  9. 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 ...........................................

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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

  20. 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

  1. ,"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...

  2. ,"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...

  3. 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...

  4. 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

  5. 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

  6. 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 ........................

  7. 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

  8. 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

  9. 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).

  10. 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 ...

  11. 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 ...

  12. 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...

  13. 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...

  14. Manufacturing consumption of energy 1994

    SciTech Connect (OSTI)

    1997-12-01

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

  15. 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

  16. 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...

  17. 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...

  18. 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,...

  19. ,"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...

  20. 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.

  1. 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.

  2. 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...

  3. Building America Top Innovations 2014 Profile: ASHRAE Standard...

    Energy Savers [EERE]

    consumption. BUILDING AMERICA TOP INNOVATIONS 2014 PROFILE Building America research and support were instrumental in developing and gaining adoption of ASHRAE 62.2, a residential ...

  4. 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 ...

  5. 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.

  6. 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 ...

  7. 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

  8. 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.

  9. 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)

  10. 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.

  11. 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.

  12. 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

  13. 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.

  14. 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)

  15. " 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" ...

  16. 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...

  17. Energy consumption series: Lighting in commercial buildings

    SciTech Connect (OSTI)

    Not Available

    1992-03-11

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

  18. 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...

  19. 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 ...

  20. 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 ...

  1. 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 ...

  2. U.S. Energy Information Administration (EIA) - Ap

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

    Consumption & Efficiency view all Residential Energy Consumption Survey Household end ... U. S. States & Countries State Energy Profiles State level data, analysis, and maps ...

  3. 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

  4. 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 ...

  5. 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

  6. 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.

  7. 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 ...

  8. "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" ...

  9. "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" ...

  10. "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" ...

  11. People Profiles

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

    people profiles People Profiles Featured Profile Hye-Sook Park Pursuing a challenging-and rewarding-career Read More » Henry Hui Henry Hui Tanza Lewis Tanza Lewis Jamie King Jamie King Lisa Burrows Lisa Burrows Jeremy Huckins Jeremy Huckins Ibo Matthews Ibo Matthews Peter Thelin Peter Thelin Susanna Reyes Susana Reyes Jerry Britten Jerry Britten Reggie Drachenberg Reggie Drachenberg Beth Dzenitis Beth Dzenitis Rebecca Dylla-Spears Rebecca Dylla-Spears John Heebner John Heebner Terry Land Terry

  12. 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

  13. 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...

  14. 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.

  15. Manufacturing Consumption of Energy 1994

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

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

  16. Manufacturing Consumption of Energy 1994

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

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

  17. US ENC MI Site Consumption

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

    Illinois, Indiana, Michigan, Ohio, Wisconsin All data from EIA's 2009 Residential Energy Consumption Survey www.eia.govconsumptionresidential Space heating Water ...

  18. US ENC WI Site Consumption

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

    Illinois, Indiana, Michigan, Ohio, Wisconsin All data from EIA's 2009 Residential Energy Consumption Survey www.eia.govconsumptionresidential Space heating Water ...

  19. US ENC IL Site Consumption

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

    Illinois, Indiana, Michigan, Ohio, Wisconsin All data from EIA's 2009 Residential Energy Consumption Survey www.eia.govconsumptionresidential Space heating Water ...

  20. Table 2. Percent of Households with Vehicles, Selected Survey...

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

    Percent of Households with Vehicles, Selected Survey Years " ,"Survey Years" ,1983,1985,1988,1991,1994,2001 "Total",85.5450237,89.00343643,88.75545852,89.42917548,87.25590956,92.08...

  1. Transferring 2001 National Household Travel Survey

    SciTech Connect (OSTI)

    Hu, Patricia S; Reuscher, Tim; Schmoyer, Richard L; Chin, Shih-Miao

    2007-05-01

    Policy makers rely on transportation statistics, including data on personal travel behavior, to formulate strategic transportation policies, and to improve the safety and efficiency of the U.S. transportation system. Data on personal travel trends are needed to examine the reliability, efficiency, capacity, and flexibility of the Nation's transportation system to meet current demands and to accommodate future demand. These data are also needed to assess the feasibility and efficiency of alternative congestion-mitigating technologies (e.g., high-speed rail, magnetically levitated trains, and intelligent vehicle and highway systems); to evaluate the merits of alternative transportation investment programs; and to assess the energy-use and air-quality impacts of various policies. To address these data needs, the U.S. Department of Transportation (USDOT) initiated an effort in 1969 to collect detailed data on personal travel. The 1969 survey was the first Nationwide Personal Transportation Survey (NPTS). The survey was conducted again in 1977, 1983, 1990, 1995, and 2001. Data on daily travel were collected in 1969, 1977, 1983, 1990 and 1995. In 2001, the survey was renamed the National Household Travel Survey (NHTS) and it collected both daily and long-distance trips. The 2001 survey was sponsored by three USDOT agencies: Federal Highway Administration (FHWA), Bureau of Transportation Statistics (BTS), and National Highway Traffic Safety Administration (NHTSA). The primary objective of the survey was to collect trip-based data on the nature and characteristics of personal travel so that the relationships between the characteristics of personal travel and the demographics of the traveler can be established. Commercial and institutional travel were not part of the survey. Due to the survey's design, data in the NHTS survey series were not recommended for estimating travel statistics for categories smaller than the combination of Census division (e.g., New England, Middle

  2. Ventilation Behavior and Household Characteristics in NewCalifornia Houses

    SciTech Connect (OSTI)

    Price, Phillip N.; Sherman, Max H.

    2006-02-01

    A survey was conducted to determine occupant use of windows and mechanical ventilation devices; barriers that inhibit their use; satisfaction with indoor air quality (IAQ); and the relationship between these factors. A questionnaire was mailed to a stratified random sample of 4,972 single-family detached homes built in 2003, and 1,448 responses were received. A convenience sample of 230 houses known to have mechanical ventilation systems resulted in another 67 completed interviews. Some results are: (1) Many houses are under-ventilated: depending on season, only 10-50% of houses meet the standard recommendation of 0.35 air changes per hour. (2) Local exhaust fans are under-utilized. For instance, about 30% of households rarely or never use their bathroom fan. (3) More than 95% of households report that indoor air quality is ''very'' or ''somewhat'' acceptable, although about 1/3 of households also report dustiness, dry air, or stagnant or humid air. (4) Except households where people cook several hours per week, there is no evidence that households with significant indoor pollutant sources get more ventilation. (5) Except households containing asthmatics, there is no evidence that health issues motivate ventilation behavior. (6) Security and energy saving are the two main reasons people close windows or keep them closed.

  3. US WNC MO Site Consumption

    Gasoline and Diesel Fuel Update (EIA)

    WNC MO Site Consumption million Btu 0 500 1,000 1,500 2,000 2,500 US WNC MO ... 9,000 12,000 15,000 US WNC MO Site Consumption kilowatthours 0 300 600 900 1,200 ...

  4. US WSC TX Site Consumption

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

    WSC TX Site Consumption million Btu 0 500 1,000 1,500 2,000 2,500 US WSC TX ... 8,000 12,000 16,000 US WSC TX Site Consumption kilowatthours 0 500 1,000 1,500 ...

  5. US NE MA Site Consumption

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

    NE MA Site Consumption million Btu 0 500 1,000 1,500 2,000 2,500 3,000 US NE MA ... 8,000 10,000 12,000 US NE MA Site Consumption kilowatthours 0 250 500 750 1,000 ...

  6. State coal profiles, January 1994

    SciTech Connect (OSTI)

    Not Available

    1994-02-02

    The purpose of State Coal Profiles is to provide basic information about the deposits, production, and use of coal in each of the 27 States with coal production in 1992. Although considerable information on coal has been published on a national level, there is a lack of a uniform overview for the individual States. This report is intended to help fill that gap and also to serve as a framework for more detailed studies. While focusing on coal output, State Coal Profiles shows that the coal-producing States are major users of coal, together accounting for about three-fourths of total US coal consumption in 1992. Each coal-producing State is profiled with a description of its coal deposits and a discussion of the development of its coal industry. Estimates of coal reserves in 1992 are categorized by mining method and sulfur content. Trends, patterns, and other information concerning production, number of mines, miners, productivity, mine price of coal, disposition, and consumption of coal are detailed in statistical tables for selected years from 1980 through 1992. In addition, coal`s contribution to the State`s estimated total energy consumption is given for 1991, the latest year for which data are available. A US summary of all data is provided for comparing individual States with the Nation as a whole. Sources of information are given at the end of the tables.

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

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

    Statistics | Department of Energy 8: April 12, 2010 Vehicles 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 household has increased by 66% and the number of vehicles per licensed driver has increased by 47%. The number of workers per household has changed the least of the statistics shown here. There has been a decline in the number of persons per household from 1969 to

  8. Advances in Household Appliances- A Review

    SciTech Connect (OSTI)

    Bansal, Pradeep; Vineyard, Edward Allan; Abdelaziz, Omar

    2011-01-01

    An overview of options and potential barriers and risks for reducing the energy consumption, peak demand, and emissions for seven key energy consuming residential products (refrigerator-freezers, dishwashers, clothes washers, clothes dryers, electric ovens, gas ovens and microwave ovens) is presented. The paper primarily concentrates on the potential energy savings from the use of advanced technologies in appliances for the U.S. market. The significance and usefulness of each technology was evaluated in order to prioritize the R&D needs to improve energy efficiency of appliances in view of energy savings, cost, and complexity. The paper provides a snapshot of the future R&D needs for each of the technologies along with the associated barriers. Although significant energy savings may be achieved, one of the major barriers in most cases is high first cost. One way of addressing this issue and promoting the introduction of new technologies is to level the playing field for all manufacturers by establishing Minimum Energy Performance Standards (MEPS) which are not cost prohibitive and promoting energy efficient products through incentives to both manufacturers and consumers.

  9. US NE MA Site Consumption

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

    the U.S. However, spending on electricity is closer to the national average due to higher prices in New England. CONSUMPTION BY END USE Since the weather in Massachusetts and New ...

  10. 2014 Manufacturing Energy Consumption Survey

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

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

  11. Manufacturing Consumption of Energy 1994

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

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

  12. Manufacturing consumption of energy 1991

    SciTech Connect (OSTI)

    Not Available

    1994-12-01

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

  13. Modeling patterns of hot water use in households

    SciTech Connect (OSTI)

    Lutz, J.D.; Liu, Xiaomin; McMahon, J.E.

    1996-11-01

    This report presents a detailed model of hot water use patterns in individual household. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies. 21 refs., 3 figs., 10 tabs.

  14. Modeling patterns of hot water use in households

    SciTech Connect (OSTI)

    Lutz, James D.; Liu, Xiaomin; McMahon, James E.; Dunham, Camilla; Shown, Leslie J.; McCure, Quandra T.

    1996-01-01

    This report presents a detailed model of hot water use patterns in individual households. The model improves upon an existing model by including the effects of four conditions that were previously unaccounted for: the absence of a clothes washer; the absence of a dishwasher; a household consisting of seniors only; and a household that does not pay for its own hot water use. Although these four conditions can significantly affect residential hot water use, and have been noted in other studies, this is the first time that they have been incorporated into a detailed model. This model allows detailed evaluation of the impact of potential efficiency standards for water heaters and other market transformation policies.

  15. Household energy conservation attitudes and behaviors in the Northwest: Tracking changes between 1983 and 1985

    SciTech Connect (OSTI)

    Fang, J.M.; Hattrup, M.P.; Nordi, R.T.; Shankle, S.A.; Ivey, D.L.

    1987-05-01

    Pacific Northwest Laboratory (PNL) has analyzed the changes in consumer energy conservation attitudes and behaviors in the Pacific Northwest between 1983 and 1985. The information was collected through stratified random telephone surveys on 2000 and 1058 households, respectively, for 1983 and 1985 in the Bonneville Power Administration (BPA) service area in Idaho, Oregon, Washington and Western Montana. This report covers four topic areas and tests two hypotheses. The topics are as follows: consumer perceptions and attitudes of energy use and conservation in the home; consumer perceptions of energy institutions and other entities; past and intended conservation actions and investments; and segmentation of homeowners into market prospect groups. The hypotheses tested are as follows: (1) There has been no change in the size and psychographic make-up of the original three market segments found in the 1983 survey analysis; and (2) image profiles of institutions with respect to familiarity, overall impression, and believability as sources of energy conservation information remain unchanged since 1983.

  16. ,"Oklahoma Natural Gas Consumption by End Use"

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

    Data for" ,"Data 1","Oklahoma Natural Gas Consumption by End ... 11:05:14 AM" "Back to Contents","Data 1: Oklahoma Natural Gas Consumption by End Use" ...

  17. ,"Oklahoma Natural Gas Vehicle Fuel Consumption (MMcf)"

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

    Data for" ,"Data 1","Oklahoma Natural Gas Vehicle Fuel Consumption ... 12:00:19 PM" "Back to Contents","Data 1: Oklahoma Natural Gas Vehicle Fuel Consumption ...

  18. ,"Kansas Natural Gas Vehicle Fuel Consumption (MMcf)"

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

    Data for" ,"Data 1","Kansas Natural Gas Vehicle Fuel Consumption ... 7:09:38 AM" "Back to Contents","Data 1: Kansas Natural Gas Vehicle Fuel Consumption ...

  19. ,"Nevada Natural Gas Vehicle Fuel Consumption (MMcf)"

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

    Data for" ,"Data 1","Nevada Natural Gas Vehicle Fuel Consumption ... 1:24:58 AM" "Back to Contents","Data 1: Nevada Natural Gas Vehicle Fuel Consumption ...

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

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

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

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

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

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

  2. Energy Information Administration - Transportation Energy Consumption...

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

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

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

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

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

  4. Using Electricity",,,"Electricity Consumption",,,"Electricity...

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

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

  5. Electricity",,,"Electricity Consumption",,,"Electricity Expenditures...

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

    C9. Total Electricity Consumption and Expenditures, 1999" ,"All Buildings Using Electricity",,,"Electricity Consumption",,,"Electricity Expenditures" ,"Number of Buildings...

  6. Electricity",,,"Electricity Consumption",,,"Electricity Expenditures...

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

    DIV. Total Electricity Consumption and Expenditures by Census Division, 1999" ,"All Buildings Using Electricity",,,"Electricity Consumption",,,"Electricity Expenditures" ,"Number...

  7. US SoAtl VA Site Consumption

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

    than the U.S. average. * Average electricity consumption and costs are higher for Virginia ... CONSUMPTION BY END USE While Virginia's weather is similar to the national average, ...

  8. ,"Fuel Oil Consumption",,,"Fuel Oil Expenditures"

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

    4. Fuel Oil Consumption and Expenditure Intensities for Non-Mall Buildings, 2003" ,"Fuel Oil Consumption",,,"Fuel Oil Expenditures" ,"per Building (gallons)","per Square Foot...

  9. ,"Fuel Oil Consumption",,,"Fuel Oil Expenditures"

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

    2. Fuel Oil Consumption and Expenditure Intensities, 1999" ,"Fuel Oil Consumption",,,"Fuel Oil Expenditures" ,"per Building (gallons)","per Square Foot (gallons)","per Worker...

  10. ,"California Natural Gas Consumption by End Use"

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

    Data for" ,"Data 1","California Natural Gas Consumption by End ... AM" "Back to Contents","Data 1: California Natural Gas Consumption by End Use" ...

  11. ,"Texas Natural Gas Consumption by End Use"

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

    Data for" ,"Data 1","Texas Natural Gas Consumption by End ... 6:36:11 AM" "Back to Contents","Data 1: Texas Natural Gas Consumption by End Use" ...

  12. ,"Texas Natural Gas Vehicle Fuel Consumption (MMcf)"

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

    Data for" ,"Data 1","Texas Natural Gas Vehicle Fuel Consumption ... 7:09:53 AM" "Back to Contents","Data 1: Texas Natural Gas Vehicle Fuel Consumption ...

  13. Energy Information Administration - Commercial Energy Consumption...

    Gasoline and Diesel Fuel Update (EIA)

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

  14. Energy Information Administration - Commercial Energy Consumption...

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

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

  15. Energy Information Administration - Commercial Energy Consumption...

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

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

  16. Displacing Natural Gas Consumption and Lowering Emissions

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

    ADVANCED MANUFACTURING OFFICE Displacing Natural Gas Consumption and Lowering Emissions By ... full advantage of op- portunity fuels and thereby reduce their natural gas consumption. ...

  17. Commercial Buildings Energy Consumption Survey (CBECS) - Analysis...

    Gasoline and Diesel Fuel Update (EIA)

    The Commercial Buildings Energy Consumption Survey (CBECS) project cycle spans at least ... Data collection for the 2012 Commercial Buildings Energy Consumption Survey (CBECS) took ...

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

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

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

  19. ,"Virginia Natural Gas Vehicle Fuel Consumption (MMcf)"

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

    Data for" ,"Data 1","Virginia Natural Gas Vehicle Fuel Consumption ... 12:00:27 PM" "Back to Contents","Data 1: Virginia Natural Gas Vehicle Fuel Consumption ...

  20. ,"West Virginia Natural Gas Residential Consumption (MMcf)"

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

    AM" "Back to Contents","Data 1: West Virginia Natural Gas Residential Consumption (MMcf)" "Sourcekey","N3010WV2" "Date","West Virginia Natural Gas Residential Consumption ...

  1. ,"Virginia Natural Gas Consumption by End Use"

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

    Data for" ,"Data 1","Virginia Natural Gas Consumption by End ... 11:05:20 AM" "Back to Contents","Data 1: Virginia Natural Gas Consumption by End Use" ...

  2. ,"West Virginia Natural Gas Industrial Consumption (MMcf)"

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

    AM" "Back to Contents","Data 1: West Virginia Natural Gas Industrial Consumption (MMcf)" "Sourcekey","N3035WV2" "Date","West Virginia Natural Gas Industrial Consumption ...

  3. ,"West Virginia Natural Gas Total Consumption (MMcf)"

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

    Data for" ,"Data 1","West Virginia Natural Gas Total Consumption ... AM" "Back to Contents","Data 1: West Virginia Natural Gas Total Consumption (MMcf)" ...

  4. ,"New Mexico Natural Gas Total Consumption (MMcf)"

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

    Data for" ,"Data 1","New Mexico Natural Gas Total Consumption ... AM" "Back to Contents","Data 1: New Mexico Natural Gas Total Consumption (MMcf)" ...

  5. ,"North Dakota Natural Gas Total Consumption (MMcf)"

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

    Data for" ,"Data 1","North Dakota Natural Gas Total Consumption ... 9:10:34 AM" "Back to Contents","Data 1: North Dakota Natural Gas Total Consumption ...

  6. ,"North Carolina Natural Gas Total Consumption (MMcf)"

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

    Data for" ,"Data 1","North Carolina Natural Gas Total Consumption ... 9:10:33 AM" "Back to Contents","Data 1: North Carolina Natural Gas Total Consumption ...

  7. ,"Minnesota Natural Gas Vehicle Fuel Consumption (MMcf)"

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

    Data for" ,"Data 1","Minnesota Natural Gas Vehicle Fuel Consumption ... 7:09:42 AM" "Back to Contents","Data 1: Minnesota Natural Gas Vehicle Fuel Consumption ...

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

    Gasoline and Diesel Fuel Update (EIA)

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

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

    Gasoline and Diesel Fuel Update (EIA)

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

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

    Gasoline and Diesel Fuel Update (EIA)

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