National Library of Energy BETA

Sample records for household electricity usage

  1. usage_household2001.pdf

    Gasoline and Diesel Fuel Update (EIA)

    Contact: Stephanie J. Battles, Survey Manager (stephanie.battles@eia.doe.gov) World Wide Web: http:www.eia.doe.govemeuconsumption Table HC6-1a. Usage Indicators by Climate ...

  2. 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...

  3. RECS Electricity Usage Form_v2 (25418 - Activated, Traditional...

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

    electricity usage for this service address between September 2008 and April 2010. Billing ... Electricity was: BBoth Sold and Delivered SSold Only DDelivered Only (select one) B S D ...

  4. Table HC6.10 Home Appliances Usage Indicators by Number of Household Members, 2005

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

    0 Home Appliances Usage Indicators by Number of Household Members, 2005 Total.............................................................................. 111.1 30.0 34.8 18.4 15.9 12.0 Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day........................................... 8.2 1.4 1.9 1.4 1.0 2.4 2 Times A Day........................................................ 24.6 4.3 7.6 4.3 4.8 3.7 Once a Day............................................................ 42.3 9.9

  5. Table HC6.12 Home Electronics Usage Indicators by Number of Household Members, 2005

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

    2 Home Electronics Usage Indicators by Number of Household Members, 2005 Total................................................................................ 111.1 30.0 34.8 18.4 15.9 12.0 Personal Computers Do Not Use a Personal Computer............................. 35.5 16.3 9.4 4.0 2.7 3.2 Use a Personal Computer.......................................... 75.6 13.8 25.4 14.4 13.2 8.8 Most-Used Personal Computer Type of PC Desk-top Model.....................................................

  6. Table HC6.7 Air-Conditioning Usage Indicators by Number of Household Members, 2005

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

    7 Air-Conditioning Usage Indicators by Number of Household Members, 2005 Total........................................................................ 111.1 30.0 34.8 18.4 15.9 12.0 Do Not Have Cooling Equipment.......................... 17.8 5.4 5.3 2.7 2.5 2.0 Have Cooling Equipment...................................... 93.3 24.6 29.6 15.7 13.4 10.0 Use Cooling Equipment....................................... 91.4 24.0 29.1 15.5 13.2 9.7 Have Equipment But Do Not Use it......................

  7. Table HC6.5 Space Heating Usage Indicators by Number of Household Members, 2005

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

    5 Space Heating Usage Indicators by Number of Household Members, 2005 Total U.S. Housing Units.................................. 111.1 30.0 34.8 18.4 15.9 12.0 Do Not Have Heating Equipment..................... 1.2 0.3 0.3 Q 0.2 0.2 Have Space Heating Equipment....................... 109.8 29.7 34.5 18.2 15.6 11.8 Use Space Heating Equipment........................ 109.1 29.5 34.4 18.1 15.5 11.6 Have But Do Not Use Equipment.................... 0.8 Q Q Q Q Q Space Heating Usage During 2005

  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. Issues in International Energy Consumption Analysis: Electricity Usage in

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

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

  12. 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.

  13. Issues in International Energy Consumption Analysis: Electricity Usage in Indias Housing Sector

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

    Issues in International Energy Consumption Analysis: Electricity Usage in India's Housing Sector November 2014 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | Issues in International Energy Consumption Analysis: Electricity Usage in India's Housing Sector i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of

  14. A Mixed Nordic Experience: Implementing Competitive Retail Electricity Markets for Household Customers

    SciTech Connect (OSTI)

    Olsen, Ole Jess; Johnsen, Tor Arnt; Lewis, Philip

    2006-11-15

    Although the Nordic countries were among the first to develop competition in the electricity industry, it took a long time to make retail competition work. In Norway and Sweden a considerable number of households are actively using the market but very few households are active in Finland and Denmark. One problem has been institutional barriers involving metering, limited unbundling of distribution and supply, and limited access to reliable information on contracts and prices. (author)

  15. A material flow analysis on current electrical and electronic waste disposal from Hong Kong households

    SciTech Connect (OSTI)

    Lau, Winifred Ka-Yan; Chung, Shan-Shan; Zhang, Chan

    2013-03-15

    Highlights: ► Most household TWARC waste is sold directly to private e-waste collectors in HK. ► The current e-waste recycling network is popular with HK households. ► About 80% of household generated TWARC is exported overseas each year. ► Over 7000 tonnes/yr of household generated TWARC reach landfills. ► It is necessary to upgrade safety and awareness in HK’s e-waste recycling industry. - Abstract: A material flow study on five types of household electrical and electronic equipment, namely television, washing machine, air conditioner, refrigerator and personal computer (TWARC) was conducted to assist the Government of Hong Kong to establish an e-waste take-back system. This study is the first systematic attempt on identifying key TWARC waste disposal outlets and trade practices of key parties involved in Hong Kong. Results from two questionnaire surveys, on local households and private e-waste traders, were used to establish the material flow of household TWARC waste. The study revealed that the majority of obsolete TWARC were sold by households to private e-waste collectors and that the current e-waste collection network is efficient and popular with local households. However, about 65,000 tonnes/yr or 80% of household generated TWARC waste are being exported overseas by private e-waste traders, with some believed to be imported into developing countries where crude recycling methods are practiced. Should Hong Kong establish a formal recycling network with tight regulatory control on imports and exports, the potential risks of current e-waste recycling practices on e-waste recycling workers, local residents and the environment can be greatly reduced.

  16. A Multi Agent-Based Framework for Simulating Household PHEV Distribution and Electric Distribution Network Impact

    SciTech Connect (OSTI)

    Cui, Xiaohui; Liu, Cheng; Kim, Hoe Kyoung; Kao, Shih-Chieh; Tuttle, Mark A; Bhaduri, Budhendra L

    2011-01-01

    The variation of household attributes such as income, travel distance, age, household member, and education for different residential areas may generate different market penetration rates for plug-in hybrid electric vehicle (PHEV). Residential areas with higher PHEV ownership could increase peak electric demand locally and require utilities to upgrade the electric distribution infrastructure even though the capacity of the regional power grid is under-utilized. Estimating the future PHEV ownership distribution at the residential household level can help us understand the impact of PHEV fleet on power line congestion, transformer overload and other unforeseen problems at the local residential distribution network level. It can also help utilities manage the timing of recharging demand to maximize load factors and utilization of existing distribution resources. This paper presents a multi agent-based simulation framework for 1) modeling spatial distribution of PHEV ownership at local residential household level, 2) discovering PHEV hot zones where PHEV ownership may quickly increase in the near future, and 3) estimating the impacts of the increasing PHEV ownership on the local electric distribution network with different charging strategies. In this paper, we use Knox County, TN as a case study to show the simulation results of the agent-based model (ABM) framework. However, the framework can be easily applied to other local areas in the US.

  17. Usage of Electric Vehicle Supply Equipment Along the Corridors between the EV Project Major Cities

    SciTech Connect (OSTI)

    Mindy Kirkpatrick

    2012-05-01

    The report explains how the EVSE are being used along the corridors between the EV Project cities. The EV Project consists of a nationwide collaboration between Idaho National Laboratory (INL), ECOtality North America, Nissan, General Motors, and more than 40 other city, regional and state governments, and electric utilities. The purpose of the EV Project is to demonstrate the deployment and use of approximately 14,000 Level II (208-240V) electric vehicle supply equipment (EVSE) and 300 fast chargers in 16 major cities. This research investigates the usage of all currently installed EV Project commercial EVSE along major interstate corridors. ESRI ArcMap software products are utilized to create geographic EVSE data layers for analysis and visualization of commercial EVSE usage. This research locates the crucial interstate corridors lacking sufficient commercial EVSE and targets locations for future commercial EVSE placement. The results and methods introduced in this research will be used by INL for the duration of the EV Project.

  18. Usage possibilities of diesel aggregate for room heating and electric energy production

    SciTech Connect (OSTI)

    Kegl, K.; Vor Ic, J.

    1998-07-01

    Article shows reasons for introduction of cogeneration generally. The present manner of heating and electricity connection at the Faculty of electrical engineering and computer science in Maribor is described. The idea is to build in the cogeneration complex in heating room next to the existent boilers. Gathered data of electricity and heat demand are presented. Paper deals with question of electrical, heat and fuel connections. Comparison between two types of cogeneration (motor and turbine) helps to make a decision: cogeneration with motor. Depending to the daily electricity demands diagram and arranged heating diagram the authors focused to the small cogeneration (around 200 kWe). Availability of natural gas at the placement of the cogeneration leads us to the gas motor but leaves the diesel engine possibility opened. A brief economical estimation includes common investment costs regarding to the savings of energy and fuel expenses. Payback time calculation gives precedence to the gas motor if diesel is used with motor instead of fuel oil. Except the energy savings there are greater benefits of the cogeneration: it can be good study case for students of electrotechnics as well as future mechanical engineers.

  19. Biocide usage in cooling towers in the electric power and petroleum refining industries

    SciTech Connect (OSTI)

    Veil, J.; Rice, J.K.; Raivel, M.E.S.

    1997-11-01

    Cooling towers users frequently apply biocides to the circulating cooling water to control growth of microorganisms, algae, and macroorganisms. Because of the toxic properties of biocides, there is a potential for the regulatory controls on their use and discharge to become increasingly more stringent. This report examines the types of biocides used in cooling towers by companies in the electric power and petroleum refining industries, and the experiences those companies have had in dealing with agencies that regulate cooling tower blowdown discharges. Results from a sample of 67 electric power plants indicate that the use of oxidizing biocides (particularly chlorine) is favored. Quaternary ammonia salts (quats), a type of nonoxidizing biocide, are also used in many power plant cooling towers. The experience of dealing with regulators to obtain approval to discharge biocides differs significantly between the two industries. In the electric power industry, discharges of any new biocide typically must be approved in writing by the regulatory agency. The approval process for refineries is less formal. In most cases, the refinery must notify the regulatory agency that it is planning to use a new biocide, but the refinery does not need to get written approval before using it. The conclusion of the report is that few of the surveyed facilities are having any difficulty in using and discharging the biocides they want to use.

  20. Usage Demographics

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

    Demographics Usage Demographics NERSC Usage Demographics 2014 In 2014, NERSC supported about 6,000 users from universities, national laboratories and industry, working on 849...

  1. Electricity storage for grid-connected household dwellings with PV panels

    SciTech Connect (OSTI)

    Mulder, Grietus; Six, Daan; Ridder, Fjo De

    2010-07-15

    Classically electricity storage for PV panels is mostly designed for stand-alone applications. In contrast, we focus in this article on houses connected to the grid with a small-scale storage to store a part of the solar power for postponed consumption within the day or the next days. In this way the house owner becomes less dependent on the grid and does only pay for the net shortage of his energy production. Local storage solutions pave the way for many new applications like omitting over-voltage of the line and bridging periods of power-line black-out. Since 2009 using self-consumption of PV energy is publicly encouraged in Germany, which can be realised by electric storage. This paper develops methods to determine the optimal storage size for grid-connected dwellings with PV panels. From measurements in houses we were able to establish calculation rules for sizing the storage. Two situations for electricity storage are covered: - the storage system is an optimum to cover most of the electricity needs; - it is an optimum for covering the peak power need of a dwelling. After these calculation rules a second step is needed to determine the size of the real battery. The article treats the aspects that should be taken into consideration before buying a specific battery like lead-acid and lithium-ion batteries. (author)

  2. Usage Statistics

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

    Usage Statistics Usage Statistics Genepool Cluster Statistics Period: daily weekly monthly quarter yearly 2year Utilization By Group Jobs Pending Last edited: 2013-09-26 18:21:13...

  3. NERSC Usage Demographics 2010

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

    0 NERSC Usage Demographics 2010 Academic Usage Usage by Discipline DOE & Other Lab Usage Usage by Institution Type Last edited: 2015-03-02 16:21:16...

  4. 1997 RECS data on consumer usage of appliances

    SciTech Connect (OSTI)

    Latta, R.B.

    1998-07-01

    The 1997 Residential Energy Consumption Survey (RECS) conducted by the Energy Information Administration contained questions on how households use various appliances. This includes the following appliance usage (1) personnel computers, (2) cooking appliances, (3) conventional ovens, (4) microwave ovens, (5) clothes washers, and (6) clothes dryer. Many of these items were first collected in the 1997 RECS. In this paper, appliance usage by household demographic characteristics (household income, age of householder, and number of household members) are examined with an emphasis on results for data items that were first collected in the 1997 RECS.

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

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

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

    2014-10-23

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

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

    SciTech Connect (OSTI)

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

    2014-10-23

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

  7. HSI Usage

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

    Usage HSI Usage HSI is a flexible and powerful command-line utility to access the NERSC HPSS storage systems. Like FTP, you can use it to store and retrieve files but it has a much larger set of commands for listing your files and directories, creating directories, changing file permissions, etc. The command set has a UNIX look and feel (e.g. mv, mkdir, rm, cp, cd, etc.) so that moving through your HPSS directory tree is almost identical to what you would find on a UNIX file system. HSI can be

  8. HTAR Usage

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

    Usage HTAR Usage HTAR is a command line utility that creates and manipulates HPSS-resident tar-format archive files. It is ideal for storing groups of files in HPSS. Since the tar file is created directly in HPSS, it is generally faster and uses less local space than creating a local tar file then storing that into HPSS. Furthermore, HTAR creates an index file that (by default) is stored along with the archive in HPSS. This allows you to list the contents of an archive without retrieving it to

  9. Variability of Battery Wear in Light Duty Plug-In Electric Vehicles Subject to Ambient Temperature, Battery Size, and Consumer Usage: Preprint

    SciTech Connect (OSTI)

    Wood, E.; Neubauer, J.; Brooker, A. D.; Gonder, J.; Smith, K. A.

    2012-08-01

    Battery wear in plug-in electric vehicles (PEVs) is a complex function of ambient temperature, battery size, and disparate usage. Simulations capturing varying ambient temperature profiles, battery sizes, and driving patterns are of great value to battery and vehicle manufacturers. A predictive battery wear model developed by the National Renewable Energy Laboratory captures the effects of multiple cycling and storage conditions in a representative lithium chemistry. The sensitivity of battery wear rates to ambient conditions, maximum allowable depth-of-discharge, and vehicle miles travelled is explored for two midsize vehicles: a battery electric vehicle (BEV) with a nominal range of 75 mi (121 km) and a plug-in hybrid electric vehicle (PHEV) with a nominal charge-depleting range of 40 mi (64 km). Driving distance distributions represent the variability of vehicle use, both vehicle-to-vehicle and day-to-day. Battery wear over an 8-year period was dominated by ambient conditions for the BEV with capacity fade ranging from 19% to 32% while the PHEV was most sensitive to maximum allowable depth-of-discharge with capacity fade ranging from 16% to 24%. The BEV and PHEV were comparable in terms of petroleum displacement potential after 8 years of service, due to the BEV?s limited utility for accomplishing long trips.

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

  16. Usage Summaries

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

    Usage Summaries PDSF Group Batch Summary Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 2016 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 Partial SGE62 2015 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 2014 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 2013 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 2012 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62 SGE62

  17. Electricity Demand of PHEVs Operated by Private Households and Commercial Fleets: Effects of Driving and Charging Behavior

    SciTech Connect (OSTI)

    John Smart; Matthew Shirk; Ken Kurani; Casey Quinn; Jamie Davies

    2010-11-01

    Automotive and energy researchers have made considerable efforts to predict the impact of plug-in hybrid vehicle (PHEV) charging on the electrical grid. This work has been done primarily through computer modeling and simulation. The US Department of Energy’s (DOE) Advanced Vehicle Testing Activity (AVTA), in partnership with the University of California at Davis’s Institute for Transportation Stuides, have been collecting data from a diverse fleet of PHEVs. The AVTA is conducted by the Idaho National Laboratory for DOE’s Vehicle Technologies Program. This work provides the opportunity to quantify the petroleum displacement potential of early PHEV models, and also observe, rather than simulate, the charging behavior of vehicle users. This paper presents actual charging behavior and the resulting electricity demand from these PHEVs operating in undirected, real-world conditions. Charging patterns are examined for both commercial-use and personal-use vehicles. Underlying reasons for charging behavior in both groups are also presented.

  18. 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

  19. 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

  20. 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

  1. NERSC Usage Demographics 2011

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

    1 NERSC Usage Demographics 2011 Last edited: 2016-08-18 15:54:34

  2. NERSC Usage Demographics 2012

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

    2 NERSC Usage Demographics 2012 Last edited: 2016-06-29 14:26:22

  3. NERSC Usage Demographics 2013

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

    3 NERSC Usage Demographics 2013 Last edited: 2016-06-29 14:27:1

  4. 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

  5. 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

  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. Form EIA-457E (2001) -- Household Bottled Gas Usage

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

    RoperASW is a well respected survey research firm. You will return your completed forms to ... The government may bring a civil action to prohibit reporting violations which may result ...

  8. Form EIA-457E (2001) -- Household Bottled Gas Usage

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

    ... in a civil penalty of not more than 2,750 per day for each violation, or a fine of not more than 5,000 per day for each willful violation. The government may bring a civil ...

  9. Form EIA-457E (2001) -- Household Bottled Gas Usage

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

    You are not required to respond to this form unless it displays a currently valid OMB control number. You will find the OMB approval number and expiration date at the top left-hand ...

  10. 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.

  11. Advanced Usage Examples

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

    Examples Advanced Usage Examples Transferring Data from Batch Jobs Once you have set up your automatic HPSS authentication you can access HPSS within batch scripts. Read More ...

  12. NERSC Usage Demographics 2014

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

    4 NERSC Usage Demographics 2014 In 2014, NERSC supported about 6,000 users from universities, national laboratories and industry, working on 849 projects with allocations of NERSC...

  13. 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

  14. 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

  15. Updated Miscellaneous Electricity Loads and Appliance Energy Usage Profiles for Use in Home Energy Ratings, the Building America Benchmark Procedures and Related Calculations. Revised

    SciTech Connect (OSTI)

    Parker, Danny; Fairey, Philip; Hendron, Robert

    2011-06-10

    This report discusses how TIAX data, supplemented by the 2005 Residential Energy Consumption Survey (RECS)public use data set was used to make significant improvements in the prediction metods for estimating energy use of miscellaneous electric loads.

  16. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

    Sparn, B.; Jin, X.; Earle, L.

    2013-10-01

    With the advent of the Advanced Metering Infrastructure (AMI) systems capable of two-way communications between the utility's grid and the building, there has been significant effort in the Automated Home Energy Management (AHEM) industry to develop capabilities that allow residential building systems to respond to utility demand events by temporarily reducing their electricity usage. Major appliance manufacturers are following suit by developing Home Area Network (HAN)-tied appliance suites that can take signals from the home's 'smart meter,' a.k.a. AMI meter, and adjust their run cycles accordingly. There are numerous strategies that can be employed by household appliances to respond to demand-side management opportunities, and they could result in substantial reductions in electricity bills for the residents depending on the pricing structures used by the utilities to incent these types of responses. The first step to quantifying these end effects is to test these systems and their responses in simulated demand-response (DR) conditions while monitoring energy use and overall system performance.

  17. Laboratory Testing of Demand-Response Enabled Household Appliances

    SciTech Connect (OSTI)

    Sparn, B.; Jin, X.; Earle, L.

    2013-10-01

    With the advent of the Advanced Metering Infrastructure (AMI) systems capable of two-way communications between the utility's grid and the building, there has been significant effort in the Automated Home Energy Management (AHEM) industry to develop capabilities that allow residential building systems to respond to utility demand events by temporarily reducing their electricity usage. Major appliance manufacturers are following suit by developing Home Area Network (HAN)-tied appliance suites that can take signals from the home's 'smart meter,' a.k.a. AMI meter, and adjust their run cycles accordingly. There are numerous strategies that can be employed by household appliances to respond to demand-side management opportunities, and they could result in substantial reductions in electricity bills for the residents depending on the pricing structures used by the utilities to incent these types of responses.The first step to quantifying these end effects is to test these systems and their responses in simulated demand-response (DR) conditions while monitoring energy use and overall system performance.

  18. NERSC Usage and User Demographics

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

    Usage Demographics Users and Projects Through the Years Careers Visitor Info Web Policies Home » About » Usage and User Demographics NERSC Usage and User Demographics Usage Demographics Number of NERSC Users and Projects Through the Years Number of NERSC Users and Projects Through the Years Read More » Last edited: 2015-03-02 16:21:25

  19. How usage is charged

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

    usage is charged How usage is charged MPP Charging (Computational Systems) When a job runs on a NERSC MPP system, such as Hopper, charges accrue against one of the user's repository allocations. The unit of accounting for these charges is the "MPP Hour". A parallel job is charged for exclusive use of each multi-core node allocated to the job. The MPP charge for such a job is calculated as the product of: the job's elapsed wall-clock time in hours the number of nodes allocated to the

  20. NERSC Usage Demographics 2014

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

    4 NERSC Usage Demographics 2014 In 2014, NERSC supported about 6,000 users from universities, national laboratories and industry, working on 849 projects with allocations of NERSC resources. Our users come from across the U.S. and around the globe, with 48 states and 46 countries represented. Last edited: 2016-06-29 14:26:5

  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. 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 ...

  3. 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 ...

  4. 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 ...

  5. 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 ...

  6. 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.

  7. Lincoln Electric System (Residential)- 2015 Sustainable Energy Program

    Broader source: Energy.gov [DOE]

    Lincoln Electric System (LES) offers several rebates to residential customers who are interested in upgrading to energy efficient household equipment.

  8. 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...

  9. 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...

  10. ELECTRIC

    Office of Legacy Management (LM)

    ELECTRIC cdrtrokArJclaeT 3 I+ &i, y$ \I &OF I*- j< t j,fci..- ir )(yiT !E-li, ( \-,v? Cl -p/4.4 RESEARCH LABORATORIES EAST PITTSBURGH, PA. 8ay 22, 1947 Mr. J. Carrel Vrilson General ?!!mager Atomic Qxzgy Commission 1901 Constitution Avenue Kashington, D. C. Dear Sir: In the course of OUT nuclenr research we are planning to study the enc:ri;y threshold anti cross section for fission. For thib program we require a s<>piAroted sample of metallic Uranium 258 of high purity. A

  11. Electricity 101 | Department of Energy

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

    Resources » Electricity 101 Electricity 101 FREQUENTLY ASKED QUESTIONS Why do other countries use different shaped plugs? Why do outlets have three holes? Why do we have AC electricity? Can we harness lightning as an energy source? Can we have wireless transmission of electricity? SYSTEM What is electricity? Where does electricity come from? What is the "grid"? How much electricity does a typical household use? How did the electric system evolve? What does the future look like? Who

  12. 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.

  13. 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 ...

  14. 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 *...

  15. 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 ...

  16. Lincoln Electric System (Residential)- Sustainable Energy Program

    Broader source: Energy.gov [DOE]

    Lincoln Electric System (LES) offers several rebates to their residential customers who are interested in upgrading to energy efficient household equipment. 

  17. 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 ...

  18. 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) . . . . . . . . ....

  19. 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 ...

  20. 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 ...

  1. 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 ...

  2. 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...

  3. TEP Power Partners Project [Tucson Electric Power

    SciTech Connect (OSTI)

    None, None

    2014-02-06

    The Arizona Governor’s Office of Energy Policy, in partnership with Tucson Electric Power (TEP), Tendril, and Next Phase Energy (NPE), formed the TEP Power Partners pilot project to demonstrate how residential customers could access their energy usage data and third party applications using data obtained from an Automatic Meter Reading (AMR) network. The project applied for and was awarded a Smart Grid Data Access grant through the U.S. Department of Energy. The project participants’ goal for Phase I is to actively engage 1,700 residential customers to demonstrate sustained participation, reduction in energy usage (kWh) and cost ($), and measure related aspects of customer satisfaction. This Demonstration report presents a summary of the findings, effectiveness, and customer satisfaction with the 15-month TEP Power Partners pilot project. The objective of the program is to provide residential customers with energy consumption data from AMR metering and empower these participants to better manage their electricity use. The pilot recruitment goals included migrating 700 existing customers from the completed Power Partners Demand Response Load Control Project (DRLC), and enrolling 1,000 new participants. Upon conclusion of the project on November 19, 2013; 1,390 Home Area Networks (HANs) were registered; 797 new participants installed a HAN; Survey respondents’ are satisfied with the program and found value with a variety of specific program components; Survey respondents report feeling greater control over their energy usage and report taking energy savings actions in their homes after participating in the program; On average, 43 % of the participants returned to the web portal monthly and 15% returned weekly; and An impact evaluation was completed by Opinion Dynamics and found average participant savings for the treatment period1 to be 2.3% of their household use during this period.2 In total, the program saved 163 MWh in the treatment period of 2013.

  4. 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.

  5. Computer usage and national energy consumption: Results from a field-metering study

    SciTech Connect (OSTI)

    Desroches, Louis-Benoit; Fuchs, Heidi; Greenblatt, Jeffery; Pratt, Stacy; Willem, Henry; Claybaugh, Erin; Beraki, Bereket; Nagaraju, Mythri; Price, Sarah; Young, Scott

    2014-12-01

    The electricity consumption of miscellaneous electronic loads (MELs) in the home has grown in recent years, and is expected to continue rising. Consumer electronics, in particular, are characterized by swift technological innovation, with varying impacts on energy use. Desktop and laptop computers make up a significant share of MELs electricity consumption, but their national energy use is difficult to estimate, given uncertainties around shifting user behavior. This report analyzes usage data from 64 computers (45 desktop, 11 laptop, and 8 unknown) collected in 2012 as part of a larger field monitoring effort of 880 households in the San Francisco Bay Area, and compares our results to recent values from the literature. We find that desktop computers are used for an average of 7.3 hours per day (median = 4.2 h/d), while laptops are used for a mean 4.8 hours per day (median = 2.1 h/d). The results for laptops are likely underestimated since they can be charged in other, unmetered outlets. Average unit annual energy consumption (AEC) for desktops is estimated to be 194 kWh/yr (median = 125 kWh/yr), and for laptops 75 kWh/yr (median = 31 kWh/yr). We estimate national annual energy consumption for desktop computers to be 20 TWh. National annual energy use for laptops is estimated to be 11 TWh, markedly higher than previous estimates, likely reflective of laptops drawing more power in On mode in addition to greater market penetration. This result for laptops, however, carries relatively higher uncertainty compared to desktops. Different study methodologies and definitions, changing usage patterns, and uncertainty about how consumers use computers must be considered when interpreting our results with respect to existing analyses. Finally, as energy consumption in On mode is predominant, we outline several energy savings opportunities: improved power management (defaulting to low-power modes after periods of inactivity as well as power scaling), matching the rated power

  6. 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.

  7. 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.

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

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

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

  9. CBECS 2012: Energy Usage Summary

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

    2012 Commercial Buildings Energy Consumption Survey: Energy Usage Summary CBECS 2012 - Release date: March 18, 2016 Despite a 14% increase in total buildings and a 22% increase in total floorspace since 2003, energy use in the estimated 5.6 million U.S. commercial buildings was up just 7% during the same period, according to new analysis from the 2012 Commercial Buildings Energy Consumption Survey (CBECS). Slower growth in commercial building energy demand since 2003 is explained in part by

  10. Opportunistic Resource Usage in CMS

    SciTech Connect (OSTI)

    Kreuzer, Peter; Hufnagel, Dirk; Dykstra, D.; Gutsche, O.; Tadel, M.; Sfiligoi, I.; Letts, J.; Wuerthwein, F.; McCrea, A.; Bockelman, B.; Fajardo, E.; Linares, L.; Wagner, R.; Konstantinov, P.; Blumenfeld, B.; Bradley, D.

    2014-01-01

    CMS is using a tiered setup of dedicated computing resources provided by sites distributed over the world and organized in WLCG. These sites pledge resources to CMS and are preparing them especially for CMS to run the experiment's applications. But there are more resources available opportunistically both on the GRID and in local university and research clusters which can be used for CMS applications. We will present CMS' strategy to use opportunistic resources and prepare them dynamically to run CMS applications. CMS is able to run its applications on resources that can be reached through the GRID, through EC2 compliant cloud interfaces. Even resources that can be used through ssh login nodes can be harnessed. All of these usage modes are integrated transparently into the GlideIn WMS submission infrastructure, which is the basis of CMS' opportunistic resource usage strategy. Technologies like Parrot to mount the software distribution via CVMFS and xrootd for access to data and simulation samples via the WAN are used and will be described. We will summarize the experience with opportunistic resource usage and give an outlook for the restart of LHC data taking in 2015.

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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 ...

  17. Electric Water Heater Modeling and Control Strategies for Demand Response

    SciTech Connect (OSTI)

    Diao, Ruisheng; Lu, Shuai; Elizondo, Marcelo A.; Mayhorn, Ebony T.; Zhang, Yu; Samaan, Nader A.

    2012-07-22

    Abstract Demand response (DR) has a great potential to provide balancing services at normal operating conditions and emergency support when a power system is subject to disturbances. Effective control strategies can significantly relieve the balancing burden of conventional generators and reduce investment on generation and transmission expansion. This paper is aimed at modeling electric water heaters (EWH) in households and tests their response to control strategies to implement DR. The open-loop response of EWH to a centralized signal is studied by adjusting temperature settings to provide regulation services; and two types of decentralized controllers are tested to provide frequency support following generator trips. EWH models are included in a simulation platform in DIgSILENT to perform electromechanical simulation, which contains 147 households in a distribution feeder. Simulation results show the dependence of EWH response on water heater usage . These results provide insight suggestions on the need of control strategies to achieve better performance for demand response implementation. Index Terms Centralized control, decentralized control, demand response, electrical water heater, smart grid

  18. DC Fast Charger Usage in the Pacific Northwest

    SciTech Connect (OSTI)

    Salisbury, Shawn; Smart, John

    2015-02-01

    This document will describe the use of a number of Direct Current Fast Charging Stations throughout Washington and Oregon as a part of of the West Coast Electric Highway. It will detail the usage frequency and location of the charging stations INL has data from. It will also include aggregated data from hundreds of privately owned vehicles that were enrolled in the EV Project regarding driving distance when using one of the West Coast Electric Highway fast chargers. This document is a white paper that will be published on the INL AVTA website.

  19. Miscellaneous electricity use in U.S. homes

    SciTech Connect (OSTI)

    Sanchez, Marla C.; Koomey, Jonathan G.; Moezzi, Mithra M.; Meier, Alan; Huber, Wolfgang

    1999-09-30

    Historically, residential energy and carbon saving efforts have targeted conventional end uses such as water heating, lighting and refrigeration. The emergence of new household appliances has transformed energy use from a few large and easily identifiable end uses into a broad array of ''miscellaneous'' energy services. This group of so called miscellaneous appliances has been a major contributor to growth in electricity demand in the past two decades. We use industry shipment data, lifetimes, and wattage and usage estimates of over 90 individual products to construct a bottom-up end use model (1976-2010). The model is then used to analyze historical and forecasted growth trends, and to identify the largest individual products within the miscellaneous end use. We also use the end use model to identify and analyze policy priorities. Our forecast projects that over the period 1996 to 2010, miscellaneous consumption will increase 115 TWh, accounting for over 90 percent of future residential electricity growth. A large portion of this growth will be due to halogen torchiere lamps and consumer electronics, making these two components of miscellaneous electricity a particularly fertile area for efficiency programs. Approximately 20 percent (40 TWh) of residential miscellaneous electricity is ''leaking electricity'' or energy consumed by appliances when they are not performing their principal function. If the standby power of all appliances with a standby mode is reduced to one watt, the potential energy savings equal 21 TWh/yr, saving roughly $1-2 billion annually.

  20. " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1"

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

    3 Lighting Usage Indicators by Household Income, 2005" " Million U.S. Housing Units" ,,"2005 Household Income",,,,,"Below Poverty Line","Eligible for Federal Assistance1" ,"Housing Units (millions)" ,,"Less than $20,000","$20,000 to $39,999","$40,000 to $59,999","$60,000 to $79,999","$80,000 or More" "Lighting Usage Indicators" "Total U.S. Housing

  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. 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.

  4. 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

  5. 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

  6. 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

  7. 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 ...........................................

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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

  13. 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

  14. 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

  15. 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

  16. 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

  17. 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

  18. 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

  19. 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.

  20. Hawaii Electric Co. Inc. Smart Grid Project | Open Energy Information

    Open Energy Info (EERE)

    Reliability and Power Quality Reduced Operating and Maintenance Costs Reduced Electricity Costs for Customers Reduced Truck Fleet Fuel Usage Reduced Greenhouse Gas and...

  1. Black Hills/Colorado Electric Utility Co. Smart Grid Project...

    Open Energy Info (EERE)

    Thermostats Targeted Benefits Reduced Meter Reading Costs Improved Electric Service Reliability Reduced Ancillary Service Cost Reduced Truck Fleet Fuel Usage Reduced Greenhouse...

  2. Lakeland Electric Smart Grid Project | Open Energy Information

    Open Energy Info (EERE)

    for Customers Reduced Operating and Maintenance Costs Improved Electric Service Reliability Reduced Costs from Distribution Line Losses Reduced Truck Fleet Fuel Usage Reduced...

  3. 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

  4. 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

  5. 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 ........................

  6. 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

  7. Recent Trends in Car Usage in Advanced Economies - Slower Growth...

    Open Energy Info (EERE)

    Trends in Car Usage in Advanced Economies - Slower Growth Ahead? Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Recent Trends in Car Usage in Advanced Economies -...

  8. Level: National Data; Row: NAICS Codes; Column: Usage within...

    Gasoline and Diesel Fuel Update (EIA)

    Technologies, 2010; Level: National Data; Row: NAICS Codes; Column: Usage within ... Technologies, 2010; Level: National Data; Row: NAICS Codes; Column: Usage within ...

  9. Documentation of INL's In Situ Oil Shale Retorting Water Usage...

    Office of Scientific and Technical Information (OSTI)

    Oil Shale Retorting Water Usage System Dynamics Model Citation Details In-Document Search Title: Documentation of INL's In Situ Oil Shale Retorting Water Usage System Dynamics ...

  10. 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

  11. Illinois: High-Energy, Concentration-Gradient Cathode Material for Plug-in Hybrids and All-Electric Vehicles Could Reduce Batteries' Cost and Size

    Broader source: Energy.gov [DOE]

    Batteries for electric drive vehicles and renewable energy storage will reduce petroleum usage, improving energy security and reducing harmful emissions.

  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. 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 ...

  14. 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...

  15. 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 ...

  16. Table 2.6 Household End Uses: Fuel Types, Appliances, and Electronics, Selected Years, 1978-2009

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

    6 Household End Uses: Fuel Types, Appliances, and Electronics, Selected Years, 1978-2009 Appliance Year Change 1978 1979 1980 1981 1982 1984 1987 1990 1993 1997 2001 2005 2009 1980 to 2009 Total Households (millions) 77 78 82 83 84 86 91 94 97 101 107 111 114 32 Percent of Households<//td> Space Heating - Main Fuel 1 Natural Gas 55 55 55 56 57 55 55 55 53 52 55 52 50 -5 Electricity 2 16 17 18 17 16 17 20 23 26 29 29 30 35 17 Liquefied Petroleum Gases 4 5 5 4 5 5 5 5 5 5 5 5 5 0 Distillate

  17. Burlington Electric Department- Multi-Family Rental Energy Efficiency Rebate Program

    Broader source: Energy.gov [DOE]

    Burlington Electric Department offers an innovative rebate program geared towards rental apartment owners. The program is designed to offer rebates on some of the most energy intensive household...

  18. Maximizing the Benefits of Plug-in Electric Vehicles - Continuum...

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

    In fact, most usage scenarios show that PEVs may actually benefit the utility grid." A photo of two electric vehicles in a research facility. Electric vehicle charging stations in ...

  19. Households to pay more than expected to stay warm this winter

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

    Households to pay more than expected to stay warm this winter Following a colder-than-expected November, U.S. households are forecast to consume more heating fuels than previously expected....resulting in higher heating bills. Homeowners that rely on natural gas will see their total winter expenses rise nearly 13 percent from last winter....while users of electric heat will see a 2.6 percent increase in costs. That's the latest forecast from the U.S. Energy Information Administration. Propane

  20. 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...

  1. EERE Success Story—Illinois: High-Energy, Concentration-Gradient Cathode Material for Plug-in Hybrids and All-Electric Vehicles Could Reduce Batteries' Cost and Size

    Broader source: Energy.gov [DOE]

    Batteries for electric drive vehicles and renewable energy storage will reduce petroleum usage, improving energy security and reducing harmful emissions.

  2. NREL Transportation Project to Reduce Fuel Usage

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

    Transportation Project to Reduce Fuel Usage For more information contact: Sarah Holmes Barba, 303-275-3023 email: Sarah Barba Golden, Colo., Mar. 23, 2001 - The Jefferson County Seniors Resource Center (SRC) Paratransit Service has become an important part of Eulalia Gaillard's life since her stroke in 1996. She calls on SRC to drive her to cardiologist, neurologist and chiropractor appointments each week. "It's wonderful," Gaillard says. "I'd give this program 150 plus in regards

  3. Data Center Metering and Power Usage Effectiveness | Department...

    Office of Environmental Management (EM)

    Data Center Metering and Power Usage Effectiveness Data Center Metering and Power Usage Effectiveness July 28, 2016 2:00PM to 3:00PM EDT Webinar will cover material from the Data ...

  4. Search results | Department of Energy

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

    Students learn how electrical usage is counted and priced. They measure and evaluate energy use and cost of representative household and school electrical items. http:...

  5. Watt Does It Cost To Use It?

    K-12 Energy Lesson Plans and Activities Web site (EERE)

    Students learn how electrical usage is counted and priced. They measure and evaluate energy use and cost of representative household and school electrical items.

  6. Guideline For Retrieving Customer Usage Data From Utilities

    Broader source: Energy.gov [DOE]

    This webinar, held on Dec. 16, 2010, provides information for utilities interested in retrieving data on customer usage.

  7. 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

  8. An assessment of worldwide supercomputer usage

    SciTech Connect (OSTI)

    Wasserman, H.J.; Simmons, M.L.; Hayes, A.H.

    1995-01-01

    This report provides a comparative study of advanced supercomputing usage in Japan and the United States as of Spring 1994. It is based on the findings of a group of US scientists whose careers have centered on programming, evaluating, and designing high-performance supercomputers for over ten years. The report is a follow-on to an assessment of supercomputing technology in Europe and Japan that was published in 1993. Whereas the previous study focused on supercomputer manufacturing capabilities, the primary focus of the current work was to compare where and how supercomputers are used. Research for this report was conducted through both literature studies and field research in Japan.

  9. 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...

  10. 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...

  11. 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...

  12. 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.

  13. Comparison of energy expenditures by elderly and non-elderly households: 1975 and 1985

    SciTech Connect (OSTI)

    Siler, A.

    1980-05-01

    The relative position of the elderly in the population is examined and their characteristic use of energy in relation to the total population and their non-elderly counterparts is observed. The 1985 projections are based on demographic, economic, and socio-economic, and energy data assumptions contained in the 1978 Annual Report to Congress. The model used for estimating household energy expenditure is MATH/CHRDS - Micro-Analysis of Transfers to Households/Comprehensive Human Resources Data System. Characteristics used include households disposable income, poverty status, location by DOE region and Standard Metropolitan Statistical Area (SMSA), and race and sex of the household head as well as age. Energy use by fuel type will be identified for total home fuels, including electricity, natural gas, bottled gas and fuel oil, and for all fuels, where gasoline use is also included. Throughout the analysis, both income and expenditure-dollar amounts for 1975 and 1985 are expressed in constant 1978 dollars. Two appendices contain statistical information.

  14. 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.

  15. Parallel File Systems at HPC Centers: Usage,

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

    File Systems at HPC Centers: Usage, Experiences, and Recommendations William ( Bill) E . A llcock ALCF D irector o f O pera:ons Production Systems: ALCF-2 2 Mira - B G/Q s ystem - 49,152 nodes / 786,432 cores - 786 TB of memory - Peak fl op r ate: 1 0 P F - Linpack fl op r ate: 8 .1 P F Vesta --- B G/Q s ystem - 2,048 nodes / 3 2,768 c ores - 32 TB of memory - Peak fl op r ate: 4 19 T F Cetus --- B G/Q s ystem - 1,024 n odes / 1 6,384 c ores - 16 TB of memory - Peak fl op r ate: 2 09 T F Tukey -

  16. Using Wireless Technology to Reduce Facility Energy Usage | Department of

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

    Energy Using Wireless Technology to Reduce Facility Energy Usage Using Wireless Technology to Reduce Facility Energy Usage This presentation details the U.S. Department of Energy's TEAM initiative's wireless technologies and their applications. Using Wireless Technology to Reduce Facility Energy Usage (December 4, 2009) (2.57 MB) More Documents & Publications New and Emerging Technologies Figure 1: Chamber experiment to study impact of air movement on thermal comfort using personally

  17. Documentation of INL's In Situ Oil Shale Retorting Water Usage...

    Office of Scientific and Technical Information (OSTI)

    Documentation of INL's In Situ Oil Shale Retorting Water Usage System Dynamics Model Citation Details In-Document Search Title: Documentation of INL's In Situ Oil Shale Retorting ...

  18. Ethanol Usage in Urban Public Transportation - Presentation of...

    Open Energy Info (EERE)

    - Presentation of Results Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Ethanol Usage in Urban Public Transportation - Presentation of Results AgencyCompany...

  19. Level: National Data; Row: NAICS Codes; Column: Usage within...

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

    Technologies, 2010; Level: National Data; Row: NAICS Codes; Column: Usage within ... Estimate less than 0.5. WWithheld to avoid disclosing data for individual establishments. ...

  20. Evaluation of evolving residential electricity tariffs

    SciTech Connect (OSTI)

    Lai, Judy; DeForest, Nicholas; Kiliccote, Sila; Stadler, Michael; Marnay, Chris; Donadee, Jon

    2011-05-15

    Residential customers in California's Pacific Gas and Electric (PG&E) territory have seen several electricity rate structure changes in the past decade. This poster: examines the history of the residential pricing structure and key milestones; summarizes and analyzes the usage between 2006 and 2009 for different baseline/climate areas; discusses the residential electricity Smart Meter roll out; and compares sample bills for customers in two climates under the current pricing structure and also the future time of use (TOU) structure.

  1. 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

  2. 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.

  3. 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.

  4. 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.

  5. 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)

  6. " 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" ...

  7. Household Vehicles Energy Use: Latest Data & Trends

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

    fuel, diesel motor fuel, electric, and natural gas, excluding propane because NHTSA's CAFE program does not track these vehicles. See Gasoline, Gasohol, Unleaded Gasoline, Leaded...

  8. Jefferson Lab's Education Web Site Hits New High-Usage Record...

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

    Web Site Hits New High-Usage Record Jefferson Lab's Education Web Site Hits New High-Usage Record April 22, 2002 Jefferson Lab's Science Education web site hit a new high in usage ...

  9. Documentation of INL's In Situ Oil Shale Retorting Water Usage...

    Office of Scientific and Technical Information (OSTI)

    Documentation of INL's In Situ Oil Shale Retorting Water Usage System Dynamics Model Earl D Mattson; Larry Hull 02 PETROLEUM water water A system dynamic model was construction to...

  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. 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

  13. 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.

  14. 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).

  15. 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).

  16. 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 ...

  17. Electric Vehicles

    Broader source: Energy.gov [DOE]

    This album contains a variety of all-electric, plug-in hybrid electric and fuel cell electric vehicles. For a full list of all electric vehicles visit the EV Everywhere website.

  18. Electric sales and revenue: 1993

    SciTech Connect (OSTI)

    Not Available

    1995-01-01

    The Electric Sales and Revenue is prepared by the Survey Management Division, Office of Coal, Nuclear, Electric and Alternate Fuels; Energy Information Administration (EIA); US Department of Energy. This publication provides information about sales of electricity, its associated revenue, and the average revenue per kilowatthour sold to residential, commercial, industrial, and other consumers throughout the United States. The sales, revenue, and average revenue per kilowatthour data provided in the Electric Sales and Revenue are based on annual data reported by electric utilities for the calendar year ending December 31, 1993. Operating revenue includes energy charges, demand charges, consumer service charges, environmental surcharges, fuel adjustments, and other miscellaneous charges. The revenue does not include taxes, such as sales and excise taxes, that are assessed on the consumer and collected through the utility. Average revenue per kilowatthour is defined as the cost per unit of electricity sold and is calculated by dividing retail sales into the associated electric revenue. Because electric rates vary based on energy usage, average revenue per kilowatthour are affected by changes in the volume of sales. The sales of electricity, associated revenue, and average revenue per kilowatthour data provided in this report are presented at the national, Census division, State, and electric utility levels.

  19. 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

  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. 2011 Radioactive Materials Usage Survey for Unmonitored Point Sources

    SciTech Connect (OSTI)

    Sturgeon, Richard W.

    2012-06-27

    This report provides the results of the 2011 Radioactive Materials Usage Survey for Unmonitored Point Sources (RMUS), which was updated by the Environmental Protection (ENV) Division's Environmental Stewardship (ES) at Los Alamos National Laboratory (LANL). ES classifies LANL emission sources into one of four Tiers, based on the potential effective dose equivalent (PEDE) calculated for each point source. Detailed descriptions of these tiers are provided in Section 3. The usage survey is conducted annually; in odd-numbered years the survey addresses all monitored and unmonitored point sources and in even-numbered years it addresses all Tier III and various selected other sources. This graded approach was designed to ensure that the appropriate emphasis is placed on point sources that have higher potential emissions to the environment. For calendar year (CY) 2011, ES has divided the usage survey into two distinct reports, one covering the monitored point sources (to be completed later this year) and this report covering all unmonitored point sources. This usage survey includes the following release points: (1) all unmonitored sources identified in the 2010 usage survey, (2) any new release points identified through the new project review (NPR) process, and (3) other release points as designated by the Rad-NESHAP Team Leader. Data for all unmonitored point sources at LANL is stored in the survey files at ES. LANL uses this survey data to help demonstrate compliance with Clean Air Act radioactive air emissions regulations (40 CFR 61, Subpart H). The remainder of this introduction provides a brief description of the information contained in each section. Section 2 of this report describes the methods that were employed for gathering usage survey data and for calculating usage, emissions, and dose for these point sources. It also references the appropriate ES procedures for further information. Section 3 describes the RMUS and explains how the survey results are

  3. 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.

  4. Commercial Building Tenant Energy Usage Aggregation and Privacy

    SciTech Connect (OSTI)

    Livingston, Olga V.; Pulsipher, Trenton C.; Anderson, David M.; Wang, Na

    2014-10-31

    A growing number of building owners are benchmarking their building energy use. This requires the building owner to acquire monthly whole-building energy usage information, which can be challenging for buildings in which individual tenants have their own utility meters and accounts with the utility. Some utilities and utility regulators have turned to aggregation of customer energy use data (CEUD) as a way to give building owners whole-building energy usage data while protecting customer privacy. Meter profile aggregation adds a layer of protection that decreases the risk of revealing CEUD as the number of meters aggregated increases. The report statistically characterizes the similarity between individual energy usage patterns and whole-building totals at various levels of meter aggregation.

  5. Mining Software Usage with the Automatic Library Tracking Database (ALTD)

    SciTech Connect (OSTI)

    Hadri, Bilel; Fahey, Mark R

    2013-01-01

    Tracking software usage is important for HPC centers, computer vendors, code developers and funding agencies to provide more efficient and targeted software support, and to forecast needs and guide HPC software effort towards the Exascale era. However, accurately tracking software usage on HPC systems has been a challenging task. In this paper, we present a tool called Automatic Library Tracking Database (ALTD) that has been developed and put in production on several Cray systems. The ALTD infrastructure prototype automatically and transparently stores information about libraries linked into an application at compilation time and also the executables launched in a batch job. We will illustrate the usage of libraries, compilers and third party software applications on a system managed by the National Institute for Computational Sciences.

  6. WEEE and portable batteries in residual household waste: Quantification and characterisation of misplaced waste

    SciTech Connect (OSTI)

    Bigum, Marianne; Petersen, Claus; Scheutz, Charlotte

    2013-11-15

    Highlights: • We analyse 26.1 Mg of residual waste from 3129 Danish households. • We quantify and characterise misplaced WEEE and portable batteries. • We compare misplaced WEEE and batteries to collection through dedicated schemes. • Characterisation showed that primarily small WEEE and light sources are misplaced. • Significant amounts of misplaced batteries were discarded as built-in WEEE. - Abstract: A total of 26.1 Mg of residual waste from 3129 households in 12 Danish municipalities was analysed and revealed that 89.6 kg of Waste Electrical and Electronic Equipment (WEEE), 11 kg of batteries, 2.2 kg of toners and 16 kg of cables had been wrongfully discarded. This corresponds to a Danish household discarding 29 g of WEEE (7 items per year), 4 g of batteries (9 batteries per year), 1 g of toners and 7 g of unidentifiable cables on average per week, constituting 0.34% (w/w), 0.04% (w/w), 0.01% (w/w) and 0.09% (w/w), respectively, of residual waste. The study also found that misplaced WEEE and batteries in the residual waste constituted 16% and 39%, respectively, of what is being collected properly through the dedicated special waste collection schemes. This shows that a large amount of batteries are being discarded with the residual waste, whereas WEEE seems to be collected relatively successfully through the dedicated special waste collection schemes. Characterisation of the misplaced batteries showed that 20% (w/w) of the discarded batteries were discarded as part of WEEE (built-in). Primarily alkaline batteries, carbon zinc batteries and alkaline button cell batteries were found to be discarded with the residual household waste. Characterisation of WEEE showed that primarily small WEEE (WEEE directive categories 2, 5a, 6, 7 and 9) and light sources (WEEE directive category 5b) were misplaced. Electric tooth brushes, watches, clocks, headphones, flashlights, bicycle lights, and cables were items most frequently found. It is recommended that these

  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. A Look at Health Care Buildings - How do they use electricity

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

    Electricity Usage Return to: A Look at Health Care Buildings How large are they? How many employees are there? Where are they located? How old are they? Who owns and occupies them?...

  9. Fuel bundle design for enhanced usage of plutonium fuel

    DOE Patents [OSTI]

    Reese, Anthony P.; Stachowski, Russell E.

    1995-01-01

    A nuclear fuel bundle includes a square array of fuel rods each having a concentration of enriched uranium and plutonium. Each rod of an interior array of the rods also has a concentration of gadolinium. The interior array of rods is surrounded by an exterior array of rods void of gadolinium. By this design, usage of plutonium in the nuclear reactor is enhanced.

  10. 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.

  11. 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.

  12. 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.

  13. Shared Solar Projects Powering Households Throughout America | Department

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

    of Energy Shared Solar Projects Powering Households Throughout America Shared Solar Projects Powering Households Throughout America January 31, 2014 - 2:30pm Addthis Shared solar projects allow consumers to take advantage of solar energy’s myriad benefits, even though the system is not located on the consumer’s own rooftop. | Photo courtesy of the Vote Solar Initiative Shared solar projects allow consumers to take advantage of solar energy's myriad benefits, even though the system

  14. New York Household Travel Patterns: A Comparison Analysis

    SciTech Connect (OSTI)

    Hu, Patricia S; Reuscher, Tim

    2007-05-01

    In 1969, the U. S. Department of Transportation began collecting detailed data on personal travel to address various transportation planning issues. These issues range from assessing transportation investment programs to developing new technologies to alleviate congestion. This 1969 survey was the birth of the Nationwide Personal Transportation Survey (NPTS). The survey was conducted again in 1977, 1983, 1990 and 1995. Longer-distance travel was collected in 1977 and 1995. In 2001, the survey was renamed to the National Household Travel Survey (NHTS) and collected both daily and longer-distance trips in one survey. In addition to the number of sample households that the national NPTS/NHTS survey allotted to New York State (NYS), the state procured an additional sample of households in both the 1995 and 2001 surveys. In the 1995 survey, NYS procured an addition sample of more than 9,000 households, increasing the final NY NPTS sample size to a total of 11,004 households. Again in 2001, NYS procured 12,000 additional sample households, increasing the final New York NHTS sample size to a total of 13,423 households with usable data. These additional sample households allowed NYS to address transportation planning issues pertinent to geographic areas significantly smaller than for what the national NPTS and NHTS data are intended. Specifically, these larger sample sizes enable detailed analysis of twelve individual Metropolitan Planning Organizations (MPOs). Furthermore, they allowed NYS to address trends in travel behavior over time. In this report, travel data for the entire NYS were compared to those of the rest of the country with respect to personal travel behavior and key travel determinants. The influence of New York City (NYC) data on the comparisons of the state of New York to the rest of the country was also examined. Moreover, the analysis examined the relationship between population density and travel patterns, and the similarities and differences among New

  15. Household heating bills expected to be lower this winter

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

    Household heating bills expected to be lower this winter U.S. consumers are expected to pay less this winter on their home heating bills because of lower oil and natural gas prices and projected milder temperatures than last winter. In its new forecast, the U.S. Energy Information Administration said households that rely on heating oil which are mainly located in the Northeast will pay the lowest heating expenditures in 9 years down 25% from last winter as consumers are expected to save about

  16. 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.

  17. Heat wave contributes to higher summer electricity demand in the Northeast

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

    Drop in residential electricity use to continue through 2015 Improvements in energy efficiency in lighting and home appliances are expected to continue to push residential electricity use lower over the next two years. Electricity use by the average residential customer has been trending downward since 2006 and is expected to fall to the lowest level in more than a decade, according to the U.S. Energy Information Administration EIA's new forecast shows household electricity use is expected to

  18. Residential energy use and conservation in Venezuela: Results and implications of a household survey in Caracas

    SciTech Connect (OSTI)

    Figueroa, M.J.; Ketoff, A.; Masera, O.

    1992-10-01

    This document presents the final report of a study of residential energy use in Caracas, the capital of Venezuela. It contains the findings of a household energy-use survey held in Caracas in 1988 and examines options for introducing energy conservation measures in the Venezuelan residential sector. Oil exports form the backbone of the Venezuelan economy. Improving energy efficiency in Venezuela will help free domestic oil resources that can be sold to the rest of the world. Energy conservation will also contribute to a faster recovery of the economy by reducing the need for major investments in new energy facilities, allowing the Venezuelan government to direct its financial investments towards other areas of development. Local environmental benefits will constitute an important additional by-product of implementing energy-efficiency policies in Venezuela. Caracas`s residential sector shows great potential for energy conservation. The sector is characterized by high saturation levels of major appliances, inefficiency of appliances available in the market, and by careless patterns of energy use. Household energy use per capita average 6.5 GJ/per year which is higher than most cities in developing countries; most of this energy is used for cooking. Electricity accounts for 41% of all energy use, while LPG and natural gas constitute the remainder. Specific options for inducing energy conservation and energy efficiency in Caracas`s residential sector include energy-pricing policies, fuel switching, particularly from electricity to gas, improving the energy performance of new appliances and customer information. To ensure the accomplishment of an energy-efficiency strategy, a concerted effort by energy users, manufacturers, utility companies, government agencies, and research institutions will be needed.

  19. Residential Lighting Usage Estimate Tool, v1.0

    Broader source: Energy.gov [DOE]

    By improving our understanding of residential lighting-energy usage and quantifying it across many different parameters, the new study will be of use to anyone doing energy estimates – such as utilities, market and investment analysts, and government agencies. It will also help manufacturers design products that not only better serve consumers' needs, but that maximize the energy savings that technologies like SSL make possible.

  20. Fuel bundle design for enhanced usage of plutonium fuel

    DOE Patents [OSTI]

    Reese, A.P.; Stachowski, R.E.

    1995-08-08

    A nuclear fuel bundle includes a square array of fuel rods each having a concentration of enriched uranium and plutonium. Each rod of an interior array of the rods also has a concentration of gadolinium. The interior array of rods is surrounded by an exterior array of rods void of gadolinium. By this design, usage of plutonium in the nuclear reactor is enhanced. 10 figs.

  1. Water Usage for In-Situ Oil Shale Retorting - A Systems Dynamics...

    Office of Scientific and Technical Information (OSTI)

    Water Usage for In-Situ Oil Shale Retorting - A Systems Dynamics Model Citation Details In-Document Search Title: Water Usage for In-Situ Oil Shale Retorting - A Systems Dynamics Model ...

  2. Residential Lighting Usage Estimate Tool, v1.0, Windows version...

    Energy Savers [EERE]

    Windows version Residential Lighting Usage Estimate Tool, v1.0, Windows version Windows version of the Residential Lighting Usage Estimate Tool, v1.0. Spreadsheet More Documents &...

  3. Residential Lighting Usage Estimate Tool, v1.0, MacOS version...

    Energy Savers [EERE]

    MacOS version Residential Lighting Usage Estimate Tool, v1.0, MacOS version MacOS version of the Residential Lighting Usage Estimate Tool, v1.0. Spreadsheet More Documents &...

  4. RECS Fuel Oil Usage Form_v1 (Draft).xps

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

    fuel oil usage for this delivery address between September 2008 and April 2010. Delivery ... Form EIA 457G OMB No. 1905-0092 Expires 13113 2009 RECS Fuel Oil and Kerosene Usage Form ...

  5. Water Usage for In-Situ Oil Shale Retorting - A Systems Dynamics...

    Office of Scientific and Technical Information (OSTI)

    Water Usage for In-Situ Oil Shale Retorting - A Systems Dynamics Model Citation Details In-Document Search Title: Water Usage for In-Situ Oil Shale Retorting - A Systems Dynamics ...

  6. Jefferson Lab's Education web site hits new high-usage record...

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

    web site hits new high-usage record during 2003 SOL season Jefferson Lab's Education web site hits new high-usage record during 2003 SOL season April 2, 2003 Jefferson Lab's ...

  7. Red Storm usage model :Version 1.12.

    SciTech Connect (OSTI)

    Jefferson, Karen L.; Sturtevant, Judith E.

    2005-12-01

    Red Storm is an Advanced Simulation and Computing (ASC) funded massively parallel supercomputer located at Sandia National Laboratories (SNL). The Red Storm Usage Model (RSUM) documents the capabilities and the environment provided for the FY05 Tri-Lab Level II Limited Availability Red Storm User Environment Milestone and the FY05 SNL Level II Limited Availability Red Storm Platform Milestone. This document describes specific capabilities, tools, and procedures to support both local and remote users. The model is focused on the needs of the ASC user working in the secure computing environments at Los Alamos National Laboratory (LANL), Lawrence Livermore National Laboratory (LLNL), and SNL. Additionally, the Red Storm Usage Model maps the provided capabilities to the Tri-Lab ASC Computing Environment (ACE) requirements. The ACE requirements reflect the high performance computing requirements for the ASC community and have been updated in FY05 to reflect the community's needs. For each section of the RSUM, Appendix I maps the ACE requirements to the Limited Availability User Environment capabilities and includes a description of ACE requirements met and those requirements that are not met in that particular section. The Red Storm Usage Model, along with the ACE mappings, has been issued and vetted throughout the Tri-Lab community.

  8. A life cycle approach to the management of household food waste - A Swedish full-scale case study

    SciTech Connect (OSTI)

    Bernstad, A.; Cour Jansen, J. la

    2011-08-15

    Research Highlights: > The comparison of three different methods for management of household food waste show that anaerobic digestion provides greater environmental benefits in relation to global warming potential, acidification and ozone depilation compared to incineration and composting of food waste. Use of produced biogas as car fuel provides larger environmental benefits compared to a use of biogas for heat and power production. > The use of produced digestate from the anaerobic digestion as substitution for chemical fertilizer on farmland provides avoidance of environmental burdens in the same ratio as the substitution of fossil fuels with produced biogas. > Sensitivity analyses show that results are highly sensitive to assumptions regarding the environmental burdens connected to heat and energy supposedly substituted by the waste treatment. - Abstract: Environmental impacts from incineration, decentralised composting and centralised anaerobic digestion of solid organic household waste are compared using the EASEWASTE LCA-tool. The comparison is based on a full scale case study in southern Sweden and used input-data related to aspects such as source-separation behaviour, transport distances, etc. are site-specific. Results show that biological treatment methods - both anaerobic and aerobic, result in net avoidance of GHG-emissions, but give a larger contribution both to nutrient enrichment and acidification when compared to incineration. Results are to a high degree dependent on energy substitution and emissions during biological processes. It was seen that if it is assumed that produced biogas substitute electricity based on Danish coal power, this is preferable before use of biogas as car fuel. Use of biogas for Danish electricity substitution was also determined to be more beneficial compared to incineration of organic household waste. This is a result mainly of the use of plastic bags in the incineration alternative (compared to paper bags in the

  9. Heating oil and propane households bills to be lower this winter...

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

    Heating oil and propane households bills to be lower this winter despite recent cold spell Despite the recent cold weather, households that use heating oil or propane as their main ...

  10. Table HC1-3a. Housing Unit Characteristics by Household Income...

    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 ...

  11. Electric vehicles

    SciTech Connect (OSTI)

    Not Available

    1990-03-01

    Quiet, clean, and efficient, electric vehicles (EVs) may someday become a practical mode of transportation for the general public. Electric vehicles can provide many advantages for the nation's environment and energy supply because they run on electricity, which can be produced from many sources of energy such as coal, natural gas, uranium, and hydropower. These vehicles offer fuel versatility to the transportation sector, which depends almost solely on oil for its energy needs. Electric vehicles are any mode of transportation operated by a motor that receives electricity from a battery or fuel cell. EVs come in all shapes and sizes and may be used for different tasks. Some EVs are small and simple, such as golf carts and electric wheel chairs. Others are larger and more complex, such as automobile and vans. Some EVs, such as fork lifts, are used in industries. In this fact sheet, we will discuss mostly automobiles and vans. There are also variations on electric vehicles, such as hybrid vehicles and solar-powered vehicles. Hybrid vehicles use electricity as their primary source of energy, however, they also use a backup source of energy, such as gasoline, methanol or ethanol. Solar-powered vehicles are electric vehicles that use photovoltaic cells (cells that convert solar energy to electricity) rather than utility-supplied electricity to recharge the batteries. This paper discusses these concepts.

  12. A PRACTICAL ONTOLOGY FOR THE LARGE-SCALE MODELING OF SCHOLARLY ARTIFACTS AND THEIR USAGE

    SciTech Connect (OSTI)

    RODRIGUEZ, MARKO A.; BOLLEN, JOHAN; VAN DE SOMPEL, HERBERT

    2007-01-30

    The large-scale analysis of scholarly artifact usage is constrained primarily by current practices in usage data archiving, privacy issues concerned with the dissemination of usage data, and the lack of a practical ontology for modeling the usage domain. As a remedy to the third constraint, this article presents a scholarly ontology that was engineered to represent those classes for which large-scale bibliographic and usage data exists, supports usage research, and whose instantiation is scalable to the order of 50 million articles along with their associated artifacts (e.g. authors and journals) and an accompanying 1 billion usage events. The real world instantiation of the presented abstract ontology is a semantic network model of the scholarly community which lends the scholarly process to statistical analysis and computational support. They present the ontology, discuss its instantiation, and provide some example inference rules for calculating various scholarly artifact metrics.

  13. Department of Energy Federal Acquisition Regulation Clause Usage Guide

    Office of Energy Efficiency and Renewable Energy (EERE)

    Attached for your information is a corrected Department of Energy Federal Acquisition Regulation Clause Usage Guide. This corrected clause matrix is also being posted to the Stripes library. The earlier edition incorrectly designated 52.223-4 Recovered Material Certification and 52.223-9 Estimate of Percentage of Recovered Material Content for EPA-Designated Items, as Not Applicable under management and operating contracts and other facility management contracts. They are actually required clauses as 52.223-17 requires the use of such products in service and construction contracts. They are also being designated as required under the service and construction contract columns.

  14. Use of nanofiltration to reduce cooling tower water usage.

    SciTech Connect (OSTI)

    Sanchez, Andres L.; Everett, Randy L.; Jensen, Richard Pearson; Cappelle, Malynda A.; Altman, Susan Jeanne

    2010-09-01

    Nanofiltration (NF) can effectively treat cooling-tower water to reduce water consumption and maximize water usage efficiency of thermoelectric power plants. A pilot is being run to verify theoretical calculations. A side stream of water from a 900 gpm cooling tower is being treated by NF with the permeate returning to the cooling tower and the concentrate being discharged. The membrane efficiency is as high as over 50%. Salt rejection ranges from 77-97% with higher rejection for divalent ions. The pilot has demonstrated a reduction of makeup water of almost 20% and a reduction of discharge of over 50%.

  15. Green Button Helps More Consumers Click with Their Energy Usage...

    Energy Savers [EERE]

    ... completed their implementations of Green Button: Connecticut Light & Power, Western Massachusetts Electric, Public Service Company of New Hampshire and Yankee Gas in Connecticut. ...

  16. Fact #727: May 14, 2012 Nearly Twenty Percent of Households Own Three or

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

    More Vehicles | Department of Energy 7: May 14, 2012 Nearly Twenty Percent of Households Own Three or More Vehicles Fact #727: May 14, 2012 Nearly Twenty Percent of Households Own Three or More Vehicles Household vehicle ownership has changed over the last six decades. In 1960, over twenty percent of households did not own a vehicle, but by 2010, that number fell to less than 10%. The number of households with three or more vehicles grew from 2% in 1960 to nearly 20% in 2010. Before 1990,

  17. Fact #729: May 28, 2012 Secondary Household Vehicles Travel Fewer Miles |

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

    Department of Energy 9: May 28, 2012 Secondary Household Vehicles Travel Fewer Miles Fact #729: May 28, 2012 Secondary Household Vehicles Travel Fewer Miles When a household has more than one vehicle, the secondary vehicles travel fewer miles than the primary vehicle. In a two-vehicle household, the second vehicle travels less than half of the miles that the primary vehicle travels in a day. In a six-vehicle household, the sixth vehicle travels fewer than five miles a day. Daily Vehicle

  18. Commercial and Multifamily Building Tenant Energy Usage Aggregation and Privacy

    SciTech Connect (OSTI)

    Livingston, Olga V.; Pulsipher, Trenton C.; Wang, Na

    2014-11-17

    In a number of cities and states, building owners are required to disclose and/or benchmark their building energy use. This requires the building owner to possess monthly whole-building energy usage information, which can be challenging for buildings in which individual tenants have their own utility meters and accounts with the utility. Some utilities and utility regulators have turned to aggregation of customer data as a way to give building owners the whole-building energy usage data while protecting customer privacy. However, no utilities or regulators appear to have conducted a concerted statistical, cybersecurity, and privacy analysis to justify the level of aggregation selected. Therefore, the Tennant Data Aggregation Task was established to help utilities address these issues and provide recommendations as well as a theoretical justification of the aggregation threshold. This study is focused on the use case of submitting data for ENERGY STAR Portfolio Manager (ESPM), but it also looks at other potential use cases for monthly energy consumption data.

  19. Government works with technology to boost gas output/usage

    SciTech Connect (OSTI)

    Nicoll, H.

    1996-10-01

    Specially treated ethane gas from fields of the Moomba area in the Cooper basin of South Australia now flows freely through 870 mi of interstate gas pipeline to an end-user in Sydney, New South Wales. This unprecedented usage of ethane is the result of a long-term cooperative agreement. The producer sought to provide the end-user with ethane gas for usage as a petrochemical feedstock to manufacture ethylene and plastic goods. The end-user had strict specifications for a low-CO{sub 2}, very dry ethane product with a small percentage of methane. In order to meet these, the producer committed millions of dollars to construct a high-technology, state-of-the-art ethane treatment facility in the Moomba area, and lay an extensive pipeline. Santos also contracted with the amines supplier to provide a high-performance, deep CO{sub 2} removal solvent with good corrosion prevention characteristics. The paper discusses the Moomba field overflow, gas treatment, government cooperation, and project completion.

  20. Electric Vehicles

    ScienceCinema (OSTI)

    Ozpineci, Burak

    2014-07-23

    Burak Ozpineci sees a future where electric vehicles charge while we drive them down the road, thanks in part to research under way at ORNL.

  1. Electrical Engineer

    Broader source: Energy.gov [DOE]

    Transmission Field Services is responsible for field switching operation and maintenance of Bonneville Power Administration's high-voltage electrical transmission system to provide safe, reliable,...

  2. Electrical Safety

    Office of Environmental Management (EM)

    Handbook that was originally issued in 1998, and revised in 2004. DOE handbooks are ... the National Fire Protection Association (NFPA) 70, the National Electrical Code (NEC), ...

  3. Electric Vehicles

    SciTech Connect (OSTI)

    Ozpineci, Burak

    2014-05-02

    Burak Ozpineci sees a future where electric vehicles charge while we drive them down the road, thanks in part to research under way at ORNL.

  4. Roles of electricity: Electric steelmaking

    SciTech Connect (OSTI)

    Burwell, C.C.

    1986-07-01

    Electric steel production from scrap metal continues to grow both in total quantity and in market share. The economics of electric-steel production in general, and of electric minimills in particular, seem clearly established. The trend towards electric steelmaking provides significant economic and competitive advantages for producers and important overall economic, environmental, and energy advantages for the United States at large. Conversion to electric steelmaking offers up to a 4-to-1 advantage in terms of the overall energy used to produce a ton of steel, and s similar savings in energy cost for the producer. The amount of old scrap used to produce a ton of steel has doubled since 1967 because of the use of electric furnaces.

  5. Infrastructure, Components and System Level Testing and Analysis of Electric Vehicles: Cooperative Research and Development Final Report, CRADA Number CRD-09-353

    SciTech Connect (OSTI)

    Neubauer, J.

    2013-05-01

    Battery technology is critical for the development of innovative electric vehicle networks, which can enhance transportation sustainability and reduce dependence on petroleum. This cooperative research proposed by Better Place and NREL will focus on predicting the life-cycle economics of batteries, characterizing battery technologies under various operating and usage conditions, and designing optimal usage profiles for battery recharging and use.

  6. Electric avenues

    SciTech Connect (OSTI)

    Stone, P.; Chang, A.

    1994-12-31

    Highly efficient electric drive technology developed originally for defense applications is being applied to the development of all electric shuttle buses for the San Jose International Airport. An innovative opportunity charging system using induction chargers will be incorporated to extend operation hours. The project, if successful, is expected to reduce pollution at the airport and generate jobs for displaced defense workers.

  7. Electric machine

    DOE Patents [OSTI]

    El-Refaie, Ayman Mohamed Fawzi; Reddy, Patel Bhageerath

    2012-07-17

    An interior permanent magnet electric machine is disclosed. The interior permanent magnet electric machine comprises a rotor comprising a plurality of radially placed magnets each having a proximal end and a distal end, wherein each magnet comprises a plurality of magnetic segments and at least one magnetic segment towards the distal end comprises a high resistivity magnetic material.

  8. Loss Aversion and Time-Differentiated Electricity Pricing

    SciTech Connect (OSTI)

    Spurlock, C. Anna

    2015-06-01

    I develop a model of loss aversion over electricity expenditure, from which I derive testable predictions for household electricity consumption while on combination time-of-use (TOU) and critical peak pricing (CPP) plans. Testing these predictions results in evidence consistent with loss aversion: (1) spillover effects - positive expenditure shocks resulted in significantly more peak consumption reduction for several weeks thereafter; and (2) clustering - disproportionate probability of consuming such that expenditure would be equal between the TOUCPP or standard flat-rate pricing structures. This behavior is inconsistent with a purely neoclassical utility model, and has important implications for application of time-differentiated electricity pricing.

  9. Usage based indicators to assess the impact of scholarly works: architecture and method

    DOE Patents [OSTI]

    Bollen, Johan; Van De Sompel, Herbert

    2012-03-13

    Although recording of usage data is common in scholarly information services, its exploitation for the creation of value-added services remains limited due to concerns regarding, among others, user privacy, data validity, and the lack of accepted standards for the representation, sharing and aggregation of usage data. A technical, standards-based architecture for sharing usage information is presented. In this architecture, OpenURL-compliant linking servers aggregate usage information of a specific user community as it navigates the distributed information environment that it has access to. This usage information is made OAI-PMH harvestable so that usage information exposed by many linking servers can be aggregated to facilitate the creation of value-added services with a reach beyond that of a single community or a single information service.

  10. Security Implications of Typical Grid Computing Usage Scenarios

    SciTech Connect (OSTI)

    Humphrey, Marty; Thompson, Mary R.

    2001-06-05

    A Computational Grid is a collection of heterogeneous computers and resources spread across multiple administrative domains with the intent of providing users uniform access to these resources. There are many ways to access the resources of a Computational Grid, each with unique security requirements and implications for both the resource user and the resource provider. A comprehensive set of Grid usage scenarios are presented and analyzed with regard to security requirements such as authentication, authorization, integrity, and confidentiality. The main value of these scenarios and the associated security discussions are to provide a library of situations against which an application designer can match, thereby facilitating security-aware application use and development from the initial stages of the application design and invocation. A broader goal of these scenarios are to increase the awareness of security issues in Grid Computing.

  11. Los Alamos National Laboratory Steam Plant Project Usage Data | National

    National Nuclear Security Administration (NNSA)

    Nuclear Security Administration | (NNSA) Usage Data 2 10_SMSI_SteamPlant_ThermalBasis of Analysis-Q1(011514) 2.10_SMSI_ApproxEst$Reconcile-Bechtel2009-SMSI-2013 2.10_SMSI_PipingAnnualR&R-Est_Rev122313 2.10_SMSI_Steam_CombinedEcon_011714_100%(Rev1) 2.10_SMSI_Steam_DistSystemOnlyEcon_011714_100% 2.10_SMSI_Steam_Option1-SteamCapitalEst(No-LANL$'s)_011714_100% 2.10_SMSI-Steam_Option2-HW-CapitalEst(No-LANL$'s)_011714_100% 131209XU50_XURP-LANL-Data_w-CostAlloc_CHP_121213 DOE Complex Experience

  12. Electrical connector

    DOE Patents [OSTI]

    Dilliner, Jennifer L.; Baker, Thomas M.; Akasam, Sivaprasad; Hoff, Brian D.

    2006-11-21

    An electrical connector includes a female component having one or more receptacles, a first test receptacle, and a second test receptacle. The electrical connector also includes a male component having one or more terminals configured to engage the one or more receptacles, a first test pin configured to engage the first test receptacle, and a second test pin configured to engage the second test receptacle. The first test receptacle is electrically connected to the second test receptacle, and at least one of the first test pin and the second test pin is shorter in length than the one or more terminals.

  13. Analysis of data from electric and hybrid electric vehicle student competitions

    SciTech Connect (OSTI)

    Wipke, K.B.; Hill, N.; Larsen, R.P.

    1994-01-01

    The US Department of Energy sponsored several student engineering competitions in 1993 that provided useful information on electric and hybrid electric vehicles. The electrical energy usage from these competitions has been recorded with a custom-built digital meter installed in every vehicle and used under controlled conditions. When combined with other factors, such as vehicle mass, speed, distance traveled, battery type, and type of components, this information provides useful insight into the performance characteristics of electrics and hybrids. All the vehicles tested were either electric vehicles or hybrid vehicles in electric-only mode, and had an average energy economy of 7.0 km/kwh. Based on the performance of the ``ground-up`` hybrid electric vehicles in the 1993 Hybrid Electric Vehicle Challenge, data revealed a I km/kwh energy economy benefit for every 133 kg decrease in vehicle mass. By running all the electric vehicles at a competition in Atlanta at several different constant speeds, the effects of rolling resistance and aerodynamic drag were evaluated. On average, these vehicles were 32% more energy efficient at 40 km/h than at 72 km/h. The results of the competition data analysis confirm that these engineering competitions not only provide an educational experience for the students, but also show technology performance and improvements in electric and hybrid vehicles by setting benchmarks and revealing trends.

  14. Electrical Safety

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

    ... Fig. 1-1. Flow down of Electrical AHJ and worker responsibility. 3 DOE-HDBK-1092-2013 2.0 ... When equipment contains storage batteries, workers should be protected from the various ...

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

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

    Energy 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 Exchange Call Series: Loan Programs for Low- and Moderate-Income Households, March 13, 2014. Call Slides and Discussion Summary (919.64 KB) More Documents & Publications EcoHouse Program Overview Strengthening Relationships Between Energy Programs and Housing Programs Targeted Marketing and Program

  16. Electric generator

    DOE Patents [OSTI]

    Foster, Jr., John S.; Wilson, James R.; McDonald, Jr., Charles A.

    1983-01-01

    1. In an electrical energy generator, the combination comprising a first elongated annular electrical current conductor having at least one bare surface extending longitudinally and facing radially inwards therein, a second elongated annular electrical current conductor disposed coaxially within said first conductor and having an outer bare surface area extending longitudinally and facing said bare surface of said first conductor, the contiguous coaxial areas of said first and second conductors defining an inductive element, means for applying an electrical current to at least one of said conductors for generating a magnetic field encompassing said inductive element, and explosive charge means disposed concentrically with respect to said conductors including at least the area of said inductive element, said explosive charge means including means disposed to initiate an explosive wave front in said explosive advancing longitudinally along said inductive element, said wave front being effective to progressively deform at least one of said conductors to bring said bare surfaces thereof into electrically conductive contact to progressively reduce the inductance of the inductive element defined by said conductors and transferring explosive energy to said magnetic field effective to generate an electrical potential between undeformed portions of said conductors ahead of said explosive wave front.

  17. Effect of Income on Appliances in U.S. Households, The

    Reports and Publications (EIA)

    2004-01-01

    Entails how people live, the factors that cause the most differences in home lifestyle, including energy use in geographic location, socioeconomics and household income.

  18. Fact #614: March 15, 2010 Average Age of Household Vehicles | Department of

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

    Energy 4: March 15, 2010 Average Age of Household Vehicles Fact #614: March 15, 2010 Average Age of Household Vehicles The average age of household vehicles has increased from 6.6 years in 1977 to 9.2 years in 2009. Pickup trucks have the oldest average age in every year listed. Sport utility vehicles (SUVs), first reported in the 1995 survey, have the youngest average age. Average Vehicle Age by Vehicle Type Graph showing the average vehicle age by type (car, van, pickup, SUV, all household

  19. Forum on Enhancing the Delivery of Energy Efficiency to Middle Income Households: Discussion Summary

    SciTech Connect (OSTI)

    none,

    2012-09-20

    Summarizes discussions and recommendations from a forum for practitioners and policymakers aiming to strengthen residential energy efficiency program design and delivery for middle income households.

  20. Electrically powered hand tool

    DOE Patents [OSTI]

    Myers, Kurt S.; Reed, Teddy R.

    2007-01-16

    An electrically powered hand tool is described and which includes a three phase electrical motor having a plurality of poles; an electrical motor drive electrically coupled with the three phase electrical motor; and a source of electrical power which is converted to greater than about 208 volts three-phase and which is electrically coupled with the electrical motor drive.

  1. Jefferson Lab's Education web site hits new high-usage record during 2003

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

    SOL season | Jefferson Lab web site hits new high-usage record during 2003 SOL season Jefferson Lab's Education web site hits new high-usage record during 2003 SOL season April 2, 2003 Jefferson Lab's Science Education web site is hitting new highs in usage - on a daily basis. Just yesterday - in a 24-hour-period - nearly 212,000 pages were viewed, according to Steve Gagnon, JLab Science Education technician. "It has been exciting to see the level of use our web site has gotten

  2. Energy-efficient housing alternatives: a predictive model of factors affecting household perceptions

    SciTech Connect (OSTI)

    Schreckengost, R.L.

    1985-01-01

    The major purpose of this investigation was to assess the impact of household socio-economic factors, dwelling characteristics, energy conservation behavior, and energy attitudes on the perceptions of energy-efficient housing alternatives. Perceptions of passive solar, active solar, earth sheltered, and retrofitted housing were examined. Data used were from the Southern Regional Research Project, S-141, Housing for Low and Moderate Income Families. Responses from 1804 households living in seven southern states were analyzed. A conceptual model was proposed to test the hypothesized relationships which were examined by path analysis. Perceptions of energy efficient housing alternatives were found to be a function of selected household and dwelling characteristics, energy attitude, household economic factors, and household conservation behavior. Age and education of the respondent, family size, housing-income ratio, utility income ratio, energy attitude, and size of the dwelling unit were found to have direct and indirect effects on perceptions of energy-efficient housing alternatives. Energy conservation behavior made a significant direct impact with behavioral energy conservation changes having the most profound influence. Conservation behavior was influenced by selected household and dwelling characteristics, energy attitude, and household economic factors.

  3. Electricity Monthly Update

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

    Methodology and Documentation General The Electricity Monthly Update is prepared by the Electric Power Operations Team, Office of Electricity, Renewables and Uranium Statistics,...

  4. Electricity Monthly Update

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

    Contact Information and Staff The Electricity Monthly Update is prepared by the Electric Power Operations Team, Office of Electricity, Renewables and Uranium Statistics, U.S....

  5. ,"NYSERDA Electric Vehicle Charging Infrastructure Report"

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

    January 2014 through March 2014 " ,"New York State" ,"EVSE Usage - By Access Type",,,,,,,,,,,"Public",,,,,"Limitedі",,,,,,"Private",,,,,,,,,,,"Total" ,"Number of charging ports№",,,,,,,,,,,163,,,,,16,,,,,,28,,,,,,,,,,,207 ,"Number of charging eventsІ",,,,,,,,,,,2343,,,,,113,,,,,,1244,,,,,,,,,,,3700 ,"Electricity consumed (AC MWh)",,,,,,,,,,,19.64,,,,,0.73,,,,,,33.4,,,,,,,,,,,53.76 ,"Percent of

  6. ,"NYSERDA Electric Vehicle Charging Infrastructure Report"

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

    April 2014 through June 2014 " ,"New York State" ,"EVSE Usage - By Access Type",,,,,,,,,,,"Public",,,,,"Limitedі",,,,,,"Private",,,,,,,,,,,"Total" ,"Number of charging ports№",,,,,,,,,,,207,,,,,37,,,,,,30,,,,,,,,,,,274 ,"Number of charging eventsІ",,,,,,,,,,,3931,,,,,392,,,,,,2681,,,,,,,,,,,7004 ,"Electricity consumed (AC MWh)",,,,,,,,,,,26.33,,,,,3.19,,,,,,64.83,,,,,,,,,,,94.36 ,"Percent of

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

    July 2014 through September 2014 " ,"New York State" ,"EVSE Usage - By Access Type",,,,,,,,,,,"Public",,,,,"Limitedі",,,,,,"Private",,,,,,,,,,,"Total" ,"Number of charging ports№",,,,,,,,,,,262,,,,,86,,,,,,29,,,,,,,,,,,377 ,"Number of charging eventsІ",,,,,,,,,,,5900,,,,,985,,,,,,2131,,,,,,,,,,,9016 ,"Electricity consumed (AC MWh)",,,,,,,,,,,36.96,,,,,7.05,,,,,,51.76,,,,,,,,,,,95.78 ,"Percent

  8. ,"NYSERDA Electric Vehicle Charging Infrastructure Report"

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

    4 through December 2014 " ,"New York State" ,"EVSE Usage - By Access Type",,,,,,,,,,,"Public",,,,,"Limitedі",,,,,,"Private",,,,,,,,,,,"Total" ,"Number of charging ports№",,,,,,,,,,,237,,,,,89,,,,,,27,,,,,,,,,,,353 ,"Number of charging eventsІ",,,,,,,,,,,6143,,,,,1366,,,,,,2305,,,,,,,,,,,9814 ,"Electricity consumed (AC MWh)",,,,,,,,,,,40.06,,,,,9.36,,,,,,63.28,,,,,,,,,,,112.7 ,"Percent of time

  9. Water Usage for In-Situ Oil Shale Retorting - A Systems Dynamics...

    Office of Scientific and Technical Information (OSTI)

    Water Usage for In-Situ Oil Shale Retorting - A Systems Dynamics Model Earl D. Mattson; Larry Hull; Kara Cafferty 02 PETROLEUM Water Water A system dynamic model was construction...

  10. API for current energy usage data per consumer | OpenEI Community

    Open Energy Info (EERE)

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