National Library of Energy BETA

Sample records for household electricity usage

  1. usage_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 ...

  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. "Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005"

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

    0 Home Appliances 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" "Home Appliances Usage Indicators"

  4. "Table HC7.12 Home Electronics Usage Indicators by Household Income, 2005"

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

    2 Home Electronics 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" "Home Electronics Usage Indicators"

  5. "Table HC7.5 Space Heating Usage Indicators by Household Income, 2005"

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

    5 Space Heating 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" "Space Heating Usage Indicators" "Total U.S. Housing

  6. 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 ...

  7. 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

  8. 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.....................................................

  9. 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

  10. 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.

  11. 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

  12. 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.

  13. 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.

  14. 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.

  15. 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 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. ... Read More » NERSC Usage Demographics 2013 ... Read More » NERSC Usage Demographics 2012 NERSC Usage Demographics 2011 ... Read More » NERSC Usage Demographics 2010 NERSC

  16. 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)

  17. 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...

  18. 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.

  19. 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

  20. 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.

  1. 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

  2. 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

  3. ac_household2001.pdf

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

    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 ...

  4. ac_household2001.pdf

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

    2001 Air Conditioning Characteristics RSE Column Factor: Total U.S. Four Most Populated ... New York California Texas Florida 0.4 1.1 1.7 1.2 1.2 Households With Electric Air-Conditi...

  5. 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: 2016-04-29 11:35:15

  6. 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

  7. 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

  8. 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.

  9. Usage Reports

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

    Reports Usage Reports Batch Job Statistics See queue wait times, hours used, top users and other summary statistics for jobs run at NERSC (login required). Read More » Parallel Job Statistics (Cray aprun) [rest... Read More » Historical Data Edison Job Size Charts Fraction of Hours Used per Job Size Note: Interactive charts with current and past Cori and Edison data are now available on MyNERSC This chart shows the fraction of hours used on Edison in each of 5 job-core-size bins. 2015 2014

  10. 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 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 2011 SGE62 SGE62 SGE62

  11. 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 Energys (DOE) Advanced Vehicle Testing Activity (AVTA), in partnership with the University of California at Daviss Institute for Transportation Stuides, have been collecting data from a diverse fleet of PHEVs. The AVTA is conducted by the Idaho National Laboratory for DOEs 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.

  12. 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

  13. 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...

  14. NERSC Usage Demographics 2011

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

    1 NERSC Usage Demographics 2011 Last edited: 2016-04-29 11:35:06

  15. NERSC Usage Demographics 2012

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

    2 NERSC Usage Demographics 2012 Last edited: 2016-04-29 11:34:50

  16. NERSC Usage Demographics 2013

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

    3 NERSC Usage Demographics 2013 Last edited: 2016-04-29 11:34:48

  17. 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....

  18. 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 ...

  19. 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 ...

  20. 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 ...

  1. 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.

  2. 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...

  3. 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 ...

  4. 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.

  5. 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.

  6. 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.

  7. Usage by Job Size Table

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

    Usage by Job Size Table Usage by Job Size Table page loading animation Usage Query Interface System All Hopper Edison Cori Carver Planck Matgen Franklin Hopper 1 Magellan Dirac...

  8. 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

  9. 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: 2016-04-29 11:34:32

  10. Try This: Household Magnets

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

    Household Magnets 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

  11. housingunit_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 ...

  12. 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 ...

  13. ac_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 ...

  14. 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.

  15. Electric Transportation Applications All Rights Reserved ETA...

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

    Date: ... Donald B. Karner ETA-TP001 Revision 2 1997 Electric ... 15 Appendix B - Metrology Usage Sheet 21 ETA-TP001 Revision 2 1997 Electric ...

  16. 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.

  17. 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...

  18. 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...

  19. ELECTRIC

    Office of Legacy Management (LM)

    you nay give us will be greatly uppreckted. VPry truly your23, 9. IX. Sin0j3, Mtinager lclectronics and Nuclear Physics Dept. omh , WESTINGHOUSE-THE NAT KING IN ELECTRICITY

  20. 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 ...

  1. 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 ...

  2. 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 *...

  3. 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

  4. 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?

  5. char_household2001.pdf

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

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

  6. 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 ...

  7. 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 ...

  8. homeoffice_household2001.pdf

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

    107.0 7.1 12.3 7.7 6.3 NE Households Using Office Equipment ... NE RSE row factor not estimated because RSE's for all statistics in this row are between ...

  9. homeoffice_household2001.pdf

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

    ......... 107.0 24.5 17.1 7.4 NE Households Using Office Equipment ... NE RSE row factor not estimated because RSE's for all statistics in this row are between ...

  10. homeoffice_household2001.pdf

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

    107.0 38.9 20.3 6.8 11.8 NE Households Using Office Equipment ... NE RSE row factor not estimated because RSE's for all statistics in this row are between ...

  11. homeoffice_household2001.pdf

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

    ......... 107.0 23.3 6.7 16.6 NE Households Using Office Equipment ... NE RSE row factor not estimated because RSE's for all statistics in this row are between ...

  12. spaceheat_household2001.pdf

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

    ... location is over a period of one year, relative to a base temperature of 65 degrees Fahrenheit. A household is assigned to a climate zone according to the 30-year average annual ...

  13. 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) . . . . . . . . ....

  14. 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 ...

  15. ac_household2001.pdf

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

    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 ...

  16. ac_household2001.pdf

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

    8a. Air Conditioning by UrbanRural Location, Million U.S. Households, 2001 Air Conditioning Characteristics RSE Column Factor: Total UrbanRural Location 1 RSE Row Factors City ...

  17. 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...

  18. 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. 

  19. 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.

  20. 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.

  1. 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.

  2. 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 of power supplies to computing needs, and improving the efficiency of individual components.

  3. 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

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

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

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

  5. 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

  6. Microsoft Word - Household Energy Use CA

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

    US PAC CA Expenditures dollars ALL ENERGY average per household (excl. transportation) 0 ... households use 62 million Btu of energy per home, 31% less than the U.S. average. ...

  7. Table HC6.7 Air-Conditioning Usage Indicators by Number of Household...

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

    ... Type of Glass in Windows Single-pane Glass...... Q N Q Q Q Q Proportion of Windows Replaced All......

  8. 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

  9. 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.

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

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

    7 Air-Conditioning 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" "Air-Conditioning Usage Indicators"

  11. " 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

  12. 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.

  13. 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.

  14. Electric Transportation Applications All Rights Reserved ETA...

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

    ... Donald B. Karner Procedure ETA-TP008 Revision 2 2 1997 Electric ... Appendix C - Metrology Usage Sheet 13 Procedure ETA-TP008 Revision 2 3 1997 Electric ...

  15. 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

  16. 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

  17. Evaluating Electric Vehicle Charging Impacts and Customer Charging...

    Energy Savers [EERE]

    the U.S. Department of Energy and the electricity ... in annual sales of plug-in electric vehicles by 2023, 1 which may substantially increase electricity usage and peak ...

  18. Now Available: Evaluating Electric Vehicle Charging Impacts and...

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

    The electric power industry expects a 400% growth in annual sales of plug-in electric vehicles by 2023, which may substantially increase electricity usage and peak demand in high ...

  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. 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...

  1. 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...

  2. 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...

  3. Electricity Transmission System Workshop: EERE Issues and Opportunitie...

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

    ... transmission congestion, line usage, and transmission & distribution losses 80% RE-ITI scenario ... Energy Service Interface (ESI) Electric Vehicle Supply Equipment ...

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

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

    Household Gasoline Expenditures by Income Quintile Bar graph showing the household gasoline expenditures by income quintile in the years 1989, 1997, and 2007. For more detailed ...

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

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

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

  6. 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 ...

  7. 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...

  8. 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.

  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. Cielo Computational Environment Usage Model With Mappings to...

    Office of Scientific and Technical Information (OSTI)

    Technical Report: Cielo Computational Environment Usage Model With Mappings to ACE ... Citation Details In-Document Search Title: Cielo Computational Environment Usage Model ...

  11. 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 -...

  12. 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

  13. 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.

  14. 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...

  15. 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...

  16. 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

  17. 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.

  18. 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:...

  19. 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.

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

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

    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

  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. PDF icon Call Slides and Discussion Summary More Documents & Publications Homeowner and Contractor Surveys Mastermind: Jim Mikel, Spirit Foundation Generating Energy Efficiency Project Leads and Allocating Leads to Contractors

  2. Mihai Anitescu on Electric Grids | Argonne National Laboratory

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

    Mihai Anitescu on Electric Grids Share Description Senior Computational Mathematician Mihai Anitescu (MCS) discusses Electric Grids. Speakers Mihai Anitescu, Senior Computational Mathematician at Argonne National Laboratory Duration 2:08 Topic Energy Energy usage Smart Grid Credit Argonne National Laboratory Browse By - Any - Energy -Energy efficiency --Vehicles ---Alternative fuels ---Automotive engineering ---Diesel ---Electric drive technology ---Hybrid & electric vehicles ---Hydrogen

  3. Average summer electric power bills expected to be lowest in...

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

    years The average U.S. household is expected to pay 395 for electricity this summer. That's down 2.5% from last year and the lowest residential summer power bill in four years, ...

  4. 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.

  5. 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.

  6. 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.

  7. 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...

  8. 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...

  9. 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...

  10. 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 -

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

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

    Energy 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. PDF icon Using Wireless Technology to Reduce Facility Energy Usage (December 4, 2009) More Documents & Publications New and Emerging Technologies Figure 1: Chamber experiment to study impact of air movement on thermal comfort using personally controlled

  12. 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...

  13. Delivering Energy Efficiency to Middle Income Single Family Households

    SciTech Connect (OSTI)

    none,

    2011-12-01

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

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

    SciTech Connect (OSTI)

    Hoffman, W.L.

    1982-12-01

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

  15. 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.

  16. Loan Programs for Low- and Moderate-Income Households

    Broader source: Energy.gov [DOE]

    Better Buildings Residential Network Multifamily and Low-Income Housing Peer Exchange Call Series: Loan Programs for Low- and Moderate-Income Households, March 13, 2014.

  17. 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.

  18. Planning a Home Solar Electric System | Department of Energy

    Office of Environmental Management (EM)

    ... whole-house system design -- an approach for building an energy-efficient home. ... number to your annual electricity usage (called demand) to get an idea of how much you will save. ...

  19. 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...

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

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

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

  2. 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

  3. 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).

  4. 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).

  5. 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.

  6. 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...

  7. Cielo Computational Environment Usage Model With Mappings to ACE

    Office of Scientific and Technical Information (OSTI)

    Requirements for the General Availability User Environment Capabilities Release Version 1.1 (Technical Report) | SciTech Connect Technical Report: Cielo Computational Environment Usage Model With Mappings to ACE Requirements for the General Availability User Environment Capabilities Release Version 1.1 Citation Details In-Document Search Title: Cielo Computational Environment Usage Model With Mappings to ACE Requirements for the General Availability User Environment Capabilities Release

  8. 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...

  9. Fact #614: March 15, 2010 Average Age of Household Vehicles

    Broader source: Energy.gov [DOE]

    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...

  10. Household heating bills expected to be lower this winter

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

    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 ...

  11. 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 Atlantic, and Pacific), MSA size, and the availability of rail. Extrapolating NHTS data within small geographic areas could risk developing and subsequently using unreliable estimates. For example, if a planning agency in City X of State Y estimates travel rates and other travel characteristics based on survey data collected from NHTS sample households that were located in City X of State Y, then the agency could risk developing and using unreliable estimates for their planning process. Typically, this limitation significantly increases as the size of an area decreases. That said, the NHTS contains a wealth of information that could allow statistical inferences about small geographic areas, with a pre-determined level of statistical certainty. The question then becomes whether a method can be developed that integrates the NHTS data and other data to estimate key travel characteristics for small geographic areas such as Census tract and transportation analysis zone, and whether this method can outperform other, competing methods.

  12. Determinants of Household Use of Selected Energy Star Appliances

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

    Determinants of Household Use of Selected Energy Star Appliances May 2016 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | Determinants of Household Use of Selected Energy Star Appliances i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of

  13. 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.

  14. 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 organized. The RMUS Interview Form with the attached RMUS Process Form(s) provides the radioactive materials survey data by technical area (TA) and building number. The survey data for each release point includes information such as: exhaust stack identification number, room number, radioactive material source type (i.e., potential source or future potential source of air emissions), radionuclide, usage (in curies) and usage basis, physical state (gas, liquid, particulate, solid, or custom), release fraction (from Appendix D to 40 CFR 61, Subpart H), and process descriptions. In addition, the interview form also calculates emissions (in curies), lists mrem/Ci factors, calculates PEDEs, and states the location of the critical receptor for that release point. [The critical receptor is the maximum exposed off-site member of the public, specific to each individual facility.] Each of these data fields is described in this section. The Tier classification of release points, which was first introduced with the 1999 usage survey, is also described in detail in this section. Section 4 includes a brief discussion of the dose estimate methodology, and includes a discussion of several release points of particular interest in the CY 2011 usage survey report. It also includes a table of the calculated PEDEs for each release point at its critical receptor. Section 5 describes ES's approach to Quality Assurance (QA) for the usage survey. Satisfactory completion of the survey requires that team members responsible for Rad-NESHAP (National Emissions Standard for Hazardous Air Pollutants) compliance accurately collect and process several types of information, including radioactive materials usage data, process information, and supporting information. They must also perform and document the QA reviews outlined in Section 5.2.6 (Process Verification and Peer Review) of ES-RN, 'Quality Assurance Project Plan for the Rad-NESHAP Compliance Project' to verify that all information is complete and correct.

  15. 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 findings are taken into account when designing new or improving existing special waste collection schemes. Improving the collection of WEEE is also recommended as one way to also improve the collection of batteries due to the large fraction of batteries found as built-in. The findings in this study were comparable to other western European studies, suggesting that the recommendations made in this study could apply to other western European countries as well.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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?...

  1. 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.

  2. A Glance at China’s Household Consumption

    SciTech Connect (OSTI)

    Shui, Bin

    2009-10-22

    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.

  3. 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 York MPOs. The 1995 and 2001 survey data make it possible to examine and identify travel trends over time. This report does not address, however, the causes of the differences and/or trends.

  4. 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.

  5. NREL: Transportation Research - Electric Vehicle Grid Integration

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

    Electric Vehicle Grid Integration Illustration of a house with a roof-top photovoltaic system. A wind turbine and utility towers appear in the background. A car, parked in the garage, is connected via a power cord to a household outlet. A sustainable transportation future will rely on multiple solutions, including innovative systems connecting vehicles, utilities, renewable energy sources, and buildings. Illustration by Josh Bauer, NREL Photo of two cars parked under a solar array. NREL uses

  6. EERE Success Story-Kingston Creek Hydro Project Powers 100 Households...

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

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

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

    Broader source: Energy.gov [DOE]

    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...

  8. Fact #747: October 1, 2012 Behind Housing, Transportation is the Top Household Expenditure

    Broader source: Energy.gov [DOE]

    Except for housing, transportation was the largest single expenditure for the average American household in 2010. The average household spends more on transportation in a year than on food. Vehicle...

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

    Broader source: Energy.gov [DOE]

    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...

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

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

    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 ...

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

    Broader source: Energy.gov [DOE]

    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...

  12. 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 anaerobic) and the use of biofertiliser (digestate) from anaerobic treatment as substitution of chemical fertilisers used in an incineration alternative. Net impact related to GWP from the management chain varies from a contribution of 2.6 kg CO{sub 2}-eq/household and year if incineration is utilised, to an avoidance of 5.6 kg CO{sub 2}-eq/household and year if choosing anaerobic digestion and using produced biogas as car fuel. Impacts are often dependent on processes allocated far from the control of local decision-makers, indicating the importance of a holistic approach and extended collaboration between agents in the waste management chain.

  13. 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.

  14. 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.

  15. 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 ...

  16. 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 &...

  17. 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 &...

  18. 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 ...

  19. 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 ...

  20. 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.

  1. 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.

  2. Department of Energy Federal Acquisition Regulation Clause Usage Guide

    Broader source: Energy.gov [DOE]

    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.

  3. 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%.

  4. 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.

  5. 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.

  6. 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.

  7. Using EMI for Electrical Energy Disaggregation in the Home

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

    ElectriSense Using EMI for Electrical Energy Disaggregation in the Home Sidhant Gupta UbiComp Lab EIA Energy Conference 2014 Saturday, July 12, 14 Saturday, July 12, 14 Electrical energy disaggregation in the home using a single sensor Saturday, July 12, 14 Saturday, July 12, 14 Saturday, July 12, 14 Saturday, July 12, 14 Saturday, July 12, 14 Saturday, July 12, 14 Energy usage is vastly misunderstood Saturday, July 12, 14 Overestimate 'visible' energy Saturday, July 12, 14 Consumers incorrectly

  8. Electrical Safety

    Energy Savers [EERE]

    ... Electrical Design Criteria ... of High-Voltage and Low-Current ... as a higher level of authority. Per the Integrated Safety Management model, ...

  9. 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.

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

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

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

    November, U.S. households are forecast to consume more heating fuels than ... That's the latest forecast from the U.S. Energy Information Administration. Propane users ...

  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. 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.

  19. 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.

  20. 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.

  1. 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 ...

  2. 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.

  3. Table 2.5 Household Energy Consumption and Expenditures by End Use, Selected Years, 1978-2005

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

    5 Household 1 Energy Consumption and Expenditures by End Use, Selected Years, 1978-2005 Year Space Heating Air Conditioning Water Heating Appliances, 2 Electronics, and Lighting Natural Gas Elec- tricity 3 Fuel Oil 4 LPG 5 Total Electricity 3 Natural Gas Elec- tricity 3 Fuel Oil 4 LPG 5 Total Natural Gas Elec- tricity 3 LPG 5 Total Consumption (quadrillion Btu)<//td> 1978 4.26 0.40 2.05 0.23 6.94 0.31 1.04 0.29 0.14 0.06 1.53 0.28 1.46 0.03 1.77 1980 3.41 .27 1.30 .23 5.21 .36 1.15 .30 .22

  4. Residential Network Members Impact More Than 42,000 Households...

    Energy Savers [EERE]

    annual electricity savings of more than 5 million kilowatt-hours; estimated natural gas savings of 71,580 British therms; and 653,245 estimated annual cost savings. In New...

  5. 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.

  6. Energy Cost Calculator for Electric and Gas Water Heaters | Department of

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

    Energy Electric and Gas Water Heaters Energy Cost Calculator for Electric and Gas Water Heaters Vary equipment size, energy cost, hours of operation, and /or efficiency level. INPUT SECTION Input the following data (if any parameter is missing, calculator will set to default value). Defaults Type of Water Heater Electric Gas Electric Average Daily Usage (gallons per day)* gallons 64* Energy Factor† 0.92 (electric) 0.61 (gas) Energy Cost $ / kWh $0.06 per kWh $.60 per therm Quantity of

  7. 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.

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

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

    Lab 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 yesterday. In a 24-hour-period nearly 125,000 pages were viewed, according to Steve Gagnon, JLab Education technician. "Our previous record was 114,094 pages viewed in a single day," Gagnon explained. "On April 18 a total of 124,900 pages were viewed. Our previous record was set last week. Before

  9. 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

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

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

    3a. Housing Unit Characteristics by Household Income, Million U.S. Households, 2001 Housing Unit Characteristics RSE Column Factor: Total 2001 Household Income Below Poverty Line Eli- gible for Fed- eral Assist- ance 1 RSE Row Factors Less than $14,999 $15,000 to $29,999 $30,000 to $49,999 $50,000 or More 0.6 1.3 1.1 1.0 0.9 1.4 1.0 Total ............................................... 107.0 18.7 22.9 27.1 38.3 15.0 33.8 3.3 Census Region and Division Northeast

  11. 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...

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

    Open Energy Info (EERE)

    API for current energy usage data per consumer Home > Groups > Developer Hello, I'm a web application developer working on an app to determine an individuals environmental impact,...

  13. Commercial Building Tenant Energy Usage Data Aggregation and Privacy: Technical Appendix

    SciTech Connect (OSTI)

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

    2014-11-12

    This technical appendix accompanies report PNNL–23786 “Commercial Building Tenant Energy Usage Data Aggregation and Privacy”. The objective is to provide background information on the methods utilized in the statistical analysis of the aggregation thresholds.

  14. Green Button Helps More Consumers Click with Their Energy Usage Data |

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

    Department of Energy Helps More Consumers Click with Their Energy Usage Data Green Button Helps More Consumers Click with Their Energy Usage Data September 12, 2013 - 2:41pm Addthis At the White House Energy Datapalooza in October 2012, developers showcased new apps that help consumers harness and interpret their energy use data. The expanding Green Button movement will make apps like these more ubiquitous. | Photo by Sarah Gerrity, Energy Department. At the White House Energy Datapalooza in

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

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

    This is equivalent to an average annual growth of 1.1% and 1.8%, respectively. As a result, the aggregate energy intensity per household and per square foot declined by 24.2% and ...

  16. EPA Webinar: Bringing Energy Efficiency and Renewable Housing to Low-Income Households

    Broader source: Energy.gov [DOE]

    Hosted by the U.S. Environmental Protection Agency, this webinar will explore the topic of linking and leveraging energy efficiency and renewable energy programs for limited-income households, including the need to coordinate with other energy assistance programs.

  17. Fact #748: October 8, 2012 Components of Household Expenditures on Transportation, 1984-2010

    Broader source: Energy.gov [DOE]

    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...

  18. How Do You Encourage Everyone in Your Household to Save Energy?

    Broader source: Energy.gov [DOE]

    Anyone who has decided to save energy at home knows that the entire household needs to be involved if you really want to see savings. Some people—be they roommates, spouses, children, or maybe even...

  19. 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,...

  20. Electricity Monthly Update

    Gasoline and Diesel Fuel Update (EIA)

    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. ...

  1. 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....

  2. Competition Helps Kids Learn About Energy and Save Their Households Some

    Energy Savers [EERE]

    Money | Department of Energy Competition Helps Kids Learn About Energy and Save Their Households Some Money Competition Helps Kids Learn About Energy and Save Their Households Some Money May 21, 2013 - 2:40pm Addthis Students can register now to save energy and win prizes with the Home Energy Challenge. Students can register now to save energy and win prizes with the Home Energy Challenge. Eric Barendsen Energy Technology Program Specialist, Office of Energy Efficiency and Renewable Energy

  3. Federal options for low-income electricity policy

    SciTech Connect (OSTI)

    Baxter, L.W.

    1998-06-01

    Protection of low-income consumers remains an important public policy concern in a restructuring electricity industry. Policies are needed to ensure that low-income households have enough affordable electricity to protect their health and safety, and that they are not victimized by unscrupulous suppliers. In this paper, the author presents three broad federal roles in setting low-income electricity policy, and discuss three more specific policy areas: universal service, electricity assistance, and health and safety. He discusses the key policy issues that arise when considering these potential federal initiatives and draw upon reviews of proposed low-income policies from restructuring proposals in eight states--California, Massachusetts, New Hampshire, New York, Pennsylvania, Rhode Island, Vermont, and Wisconsin.

  4. Electrical receptacle

    DOE Patents [OSTI]

    Leong, Robert

    1993-01-01

    The invention is a receptacle for a three prong electrical plug which has either a tubular or U-shaped grounding prong. The inventive receptacle has a grounding prong socket which is sufficiently spacious to prevent the socket from significantly stretching when a larger, U-shaped grounding prong is inserted into the socket, and having two ridges to allow a snug fit when a smaller tubular shape grounding prong is inserted into the socket. The two ridges are made to prevent the socket from expanding when either the U-shaped grounding prong or the tubular grounding prong is inserted.

  5. Electrical receptacle

    DOE Patents [OSTI]

    Leong, R.

    1993-06-22

    The invention is a receptacle for a three prong electrical plug which has either a tubular or U-shaped grounding prong. The inventive receptacle has a grounding prong socket which is sufficiently spacious to prevent the socket from significantly stretching when a larger, U-shaped grounding prong is inserted into the socket, and having two ridges to allow a snug fit when a smaller tubular shape grounding prong is inserted into the socket. The two ridges are made to prevent the socket from expanding when either the U-shaped grounding prong or the tubular grounding prong is inserted.

  6. Energy-efficient electric motors study

    SciTech Connect (OSTI)

    Not Available

    1981-03-23

    The study identifies the industrial decision makers, investigated the information they needed to know, how they can best be reached, and the motivating factors for purchasing energy-efficient electric motors. A survey was conducted of purchasers of integral horsepower polyphase motors. The survey measured current knowledge of and awareness of energy-efficient motors, decision-making criteria, information sources, purchase and usage patterns, and related factors. The survey data were used for the electric motor market penetration analysis. Additionally, a telephone survey was made. The study also provides analyses of distribution channels, commercialization constraints, and the impacts of government programs and rising energy prices. A description of study findings, conclusions, and recommendations is presented. Sample questionnaires and copies of letters to respondents are presented in 3 appendices. Appendices D and E contain descriptions of the methods used. (MCW)

  7. Evaluation of evolving residential electricity tariffs

    SciTech Connect (OSTI)

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

    2011-03-22

    Residential customers in California's Pacific Gas and Electric (PG&E) territory have seen several electricity rate structure changes in the past decade. A relatively simple two-tiered pricing system (charges by usage under/over baseline for the home's climate zone) was replaced in the summer of 2001 by a more complicated five-tiered system (usage below baseline and up to 30percent, 100percent, 200percent, and 300percent+ over baseline). In 2009, PG&E began the process of upgrading its residential customers to Smart Meters and laying the groundwork for time of use pricing, due to start in 2011. This paper examines the history of the tiered pricing system, discusses the problems the utility encountered with its Smart Meter roll out, and evaluates the proposed dynamic pricing incentive structures. Scenario analyses of example PG&E customer bills will also be presented. What would these residential customers pay if they were still operating under a tiered structure, and/or if they participated in peak hour reductions?

  8. Low-sulfur coal usage alters transportation strategies

    SciTech Connect (OSTI)

    Stein, H.

    1995-07-01

    As electricity production has grown, so has the amount of coal burned by US utilities. In order to comply with the 1990 Clean Air Act Amendments (CAAA), many utilities have changed from high-sulfur coal to lower-sulfur coal to reduce sulfur dioxide emissions. The primary mode of transporting coal to utilities remains the railroad, and coal represents the largest freight tonnage shipped - two out of every five tons. Since coal is so important to the railroads, it is logical that as utilities have changed their coal-buying strategies, the railroads` strategies have also changed. The increased demand for Western coal has caused rail lines some capacity problems which they are attempting to meet head-on by buying new railcars and locomotives and expanding track capacities. The new railcars typically have aluminum bodies to reduce empty weight, enabling them to carry larger loads of coal. Train locomotives are also undergoing upgrade changes. Most new locomotives have as motors to drive the wheels which deliver more motive power (traction) to the wheel trucks. In fact the motors are up to 30% more efficient at getting the traction to the trucks. Trackage is also being expanded to alleviate serious congestion on the tracks when moving Western coal.

  9. We got a new digital electric meter. Our usage went up 123%. Our Bill went up 65%

    SciTech Connect (OSTI)

    Honebein, Peter C.

    2010-03-15

    There is no question that smart meters are a benefit to utilities, in terms of operational efficiency. But headlines like this one are frightening. They suggest a significant misunderstanding of the technology, marketing, and customer experience surrounding this worthwhile innovation. (author)

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

    SciTech Connect (OSTI)

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

    2005-05-31

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

  11. Level: National Data; Row: NAICS Codes; Column: Usage within Cogeneration Technologies;

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

    3 Number of Establishments by Usage of Cogeneration Technologies, 2006; Level: National Data; Row: NAICS Codes; Column: Usage within Cogeneration Technologies; Unit: Establishment Counts. Establishments with Any Cogeneration NAICS Technology Code(a) Subsector and Industry Establishments(b) in Use(c) In Use(d) Not in Use Don't Know In Use(d) Not in Use Don't Know In Use(d) Not in Use Don't Know In Use(d) Not in Use Don't Know In Use(d) Not in Use Don't Know Total United States 311 Food 14,128 297

  12. Level: National Data; Row: NAICS Codes; Column: Usage within Cogeneration Technologies;

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

    3 Number of Establishments by Usage of Cogeneration Technologies, 2010; Level: National Data; Row: NAICS Codes; Column: Usage within Cogeneration Technologies; Unit: Establishment Counts. Establishments with Any Cogeneration NAICS Technology Code(a) Selected Subsectors and Industry Establishments(b) in Use(c) In Use(d) Not in Use(e) Don't Know In Use(d) Not in Use(e) Don't Know In Use(d) Not in Use(e) Don't Know In Use(d) Not in Use(e) Don't Know In Use(d) Not in Use(e) Don't Know Total United

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

    Office of Scientific and Technical Information (OSTI)

    Dynamics Model (Technical Report) | SciTech Connect 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 Water Usage System Dynamics Model A system dynamic model was construction to evaluate the water balance for in-situ oil shale conversion. The model is based on a systems dynamics approach and uses the Powersim Studio 9(tm) software package. Three phases of an in

  14. "Table HC11.13 Lighting Usage Indicators by Northeast Census Region, 2005"

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

    3 Lighting Usage Indicators by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Lighting Usage Indicators",,,"Middle Atlantic","New England" "Total U.S. Housing Units",111.1,20.6,15.1,5.5 "Indoor Lights Turned On During Summer" "Number of Lights Turned On" "Between

  15. "Table HC12.13 Lighting Usage Indicators by Midwest Census Region, 2005"

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

    3 Lighting Usage Indicators by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Lighting Usage Indicators",,,"East North Central","West North Central" "Total U.S. Housing Units",111.1,25.6,17.7,7.9 "Indoor Lights Turned On During Summer" "Number of Lights Turned On"

  16. "Table HC13.13 Lighting Usage Indicators by South Census Region, 2005"

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

    3 Lighting Usage Indicators by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Lighting Usage Indicators",,,"South Atlantic","East South Central","West South Central" "Total U.S. Housing Units",111.1,40.7,21.7,6.9,12.1 "Indoor Lights Turned On During Summer" "Number of Lights

  17. "Table HC14.13 Lighting Usage Indicators by West Census Region, 2005"

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

    3 Lighting Usage Indicators by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Lighting Usage Indicators",,,"Mountain","Pacific" "Total U.S. Housing Units",111.1,24.2,7.6,16.6 "Indoor Lights Turned On During Summer" "Number of Lights Turned On" "Between 1 and 4 Hours per

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

    Office of Scientific and Technical Information (OSTI)

    (Technical Report) | SciTech Connect 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 A system dynamic model was construction to evaluate the water balance for in-situ oil shale conversion. The model is based on a systems dynamics approach and uses the Powersim Studio 9(tm) software package. Three phases of an insitu retort were consider; a construction

  19. NYSERDA's Green Jobs-Green New York Program: Extending Energy Efficiency Financing To Underserved Households

    SciTech Connect (OSTI)

    Zimring, Mark; Fuller, Merrian

    2011-01-24

    The New York legislature passed the Green Jobs-Green New York (GJGNY) Act in 2009. Administered by the New York State Energy Research and Development Authority (NYSERDA), GJGNY programs provide New Yorkers with access to free or low-cost energy assessments,1 energy upgrade services,2 low-cost financing, and training for various 'green-collar' careers. Launched in November 2010, GJGNY's residential initiative is notable for its use of novel underwriting criteria to expand access to energy efficiency financing for households seeking to participate in New York's Home Performance with Energy Star (HPwES) program.3 The GJGNY financing program is a valuable test of whether alternatives to credit scores can be used to responsibly expand credit opportunities for households that do not qualify for traditional lending products and, in doing so, enable more households to make energy efficiency upgrades.

  20. "Table HC15.3 Household Characteristics by Four Most Populated States, 2005"

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

    3 Household Characteristics by Four Most Populated States, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","Four Most Populated States" "Household Characteristics",,"New York","Florida","Texas","California" "Total",111.1,7.1,7,8,12.1 "Household Size" "1 Person",30,1.8,1.9,2,3.2 "2 Persons",34.8,2.2,2.3,2.4,3.2 "3 Persons",18.4,1.1,1.3,1.2,1.8

  1. VOLTTRON: An Agent Platform for Integrating Electric Vehicles and Smart Grid

    SciTech Connect (OSTI)

    Haack, Jereme N.; Akyol, Bora A.; Tenney, Nathan D.; Carpenter, Brandon J.; Pratt, Richard M.; Carroll, Thomas E.

    2013-12-06

    The VOLTTRON platform provides a secure environment for the deployment of intelligent applications in the smart grid. VOLTTRON design is based on the needs of control applications running on small form factor devices, namely security and resource guarantees. Services such as resource discovery, secure agent mobility, and interacting with smart and legacy devices are provided by the platform to ease the development of control applications and accelerate their deployment. VOLTTRON platform has been demonstrated in several different domains that influenced and enhanced its capabilities. This paper will discuss the features of VOLTTRON and highlight its usage to coordinate electric vehicle charging with home energy usage

  2. Average U.S. household to spend $710 less on gasoline during 2015

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

    Average U.S. household to spend $710 less on gasoline during 2015 Even with the recent increases in gasoline prices, the average U.S. household is still expected save $710 in gasoline costs this year compared with what was paid at the pump in 2014. In its new monthly forecast, the U.S. Energy Information Administration said the national average price for regular gasoline is expected to be $2.39 per gallon this year. That's almost $1 less than the $3.36 average in 2014. Lower crude oil prices

  3. Average household expected to save $675 at the pump in 2015

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

    Average household expected to save $675 at the pump in 2015 Although retail gasoline prices have risen in recent weeks U.S. consumers are still expected to save about $675 per household in motor fuel costs this year. In its new monthly forecast, the U.S. Energy Information Administration says the average pump price for regular grade gasoline in 2015 will be $2.43 per gallon. That's about 93 cents lower than last year's average. The savings for consumers will be even bigger during the

  4. EERE Success Story-Kingston Creek Hydro Project Powers 100 Households |

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

    Department of Energy Kingston Creek Hydro Project Powers 100 Households EERE Success Story-Kingston Creek Hydro Project Powers 100 Households August 21, 2013 - 12:00am Addthis Nevada-based contracting firm Nevada Controls, LLC used a low-interest loan from the Nevada State Office of Energy's Revolving Loan Fund to help construct a hydropower project in the small Nevada town of Kingston. The Kingston Creek Project-benefitting the Young Brothers Ranch-is a 175-kilowatt hydro generation plant

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

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

    Drivers of U.S. Household Energy Consumption, 1980-2009 February 2015 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | Drivers of U.S. Household Energy Consumption, 1980-2009 i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data, analyses, and forecasts are independent of approval by any

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

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

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

  7. An International Survey of Electric Storage Tank Water Heater Efficiency and Standards

    SciTech Connect (OSTI)

    Johnson, Alissa; Lutz, James; McNeil, Michael A.; Covary, Theo

    2013-11-13

    Water heating is a main consumer of energy in households, especially in temperate and cold climates. In South Africa, where hot water is typically provided by electric resistance storage tank water heaters (geysers), water heating energy consumption exceeds cooking, refrigeration, and lighting to be the most consumptive single electric appliance in the home. A recent analysis for the Department of Trade and Industry (DTI) performed by the authors estimated that standing losses from electric geysers contributed over 1,000 kWh to the annual electricity bill for South African households that used them. In order to reduce this burden, the South African government is currently pursuing a programme of Energy Efficiency Standards and Labelling (EES&L) for electric appliances, including geysers. In addition, Eskom has a history of promoting heat pump water heaters (HPWH) through incentive programs, which can further reduce energy consumption. This paper provides a survey of international electric storage water heater test procedures and efficiency metrics which can serve as a reference for comparison with proposed geyser standards and ratings in South Africa. Additionally it provides a sample of efficiency technologies employed to improve the efficiency of electric storage water heaters, and outlines programs to promote adoption of improved efficiency. Finally, it surveys current programs used to promote HPWH and considers the potential for this technology to address peak demand more effectively than reduction of standby losses alone

  8. Electric and Hybrid Electric Vehicle Sales: December 2010 - June...

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

    Electric and Hybrid Electric Vehicle Sales: December 2010 - June 2013 Electric and Hybrid Electric Vehicle Sales: December 2010 - June 2013 Sales data for various models of ...

  9. Estimating the Value of Electricity Storage Resources in Electricity...

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

    Value of Electricity Storage Resources in Electricity Markets - EAC 2011 Estimating the Value of Electricity Storage Resources in Electricity Markets - EAC 2011 The purpose of this ...

  10. Technology Roadmap - Electric and Plug-in Hybrid Electric Vehicles...

    Open Energy Info (EERE)

    Roadmap - Electric and Plug-in Hybrid Electric Vehicles Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Technology Roadmap - Electric and Plug-in Hybrid Electric...

  11. Electrical safety guidelines

    SciTech Connect (OSTI)

    Not Available

    1993-09-01

    The Electrical Safety Guidelines prescribes the DOE safety standards for DOE field offices or facilities involved in the use of electrical energy. It has been prepared to provide a uniform set of electrical safety standards and guidance for DOE installations in order to affect a reduction or elimination of risks associated with the use of electrical energy. The objectives of these guidelines are to enhance electrical safety awareness and mitigate electrical hazards to employees, the public, and the environment.

  12. DOE handbook electrical safety

    SciTech Connect (OSTI)

    1998-01-01

    Electrical Safety Handbook presents the Department of Energy (DOE) safety standards for DOE field offices or facilities involved in the use of electrical energy. It has been prepared to provide a uniform set of electrical safety guidance and information for DOE installations to effect a reduction or elimination of risks associated with the use of electrical energy. The objectives of this handbook are to enhance electrical safety awareness and mitigate electrical hazards to employees, the public, and the environment.

  13. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Oregon Electricity Profile 2013 Table 1. 2013 Summary statistics (Oregon) Item Value Rank Primary energy source Hydroelectric Net summer capacity (megawatts) 15,662 27 Electric ...

  14. Electricity Advisory Committee

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

    Coe Millennium Energy Phyllis Currie Pasadena Water and Power Clark Gellings Electric Power Research Institute Mark Lauby North American Electric Reliability Corporation Janice ...

  15. Electricity Advisory Committee

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

    Carlos Coe Millennium Energy Robert Curry Jr. CurryEnergy Clark Gellings Electric Power Research Institute Michael Heyeck American Electric Power (Ret.) Paul Hudson Stratus ...

  16. Electricity Advisory Committee

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

    Carlos Coe Millennium Energy Robert Curry Jr. CurryEnergy Clark Gellings Electric Power Research Institute Paul Hudson Stratus Energy Group Mark Lauby North American Electric ...

  17. Edison Electric Institute Update

    Broader source: Energy.gov [DOE]

    Presentation—given at the Fall 2011 Federal Utility Partnership Working Group (FUPWG) meeting—discusses the Edison Electric Institute (EEI) and the current electricity landscape.

  18. EIA - State Electricity Profiles

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

    Virginia Electricity Profile 2014 Table 1. 2014 Summary statistics (Virginia) Item Value Rank Primary energy source Nuclear Net summer capacity (megawatts) 26,292 16 Electric ...

  19. EIA - State Electricity Profiles

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

    United States Electricity Profile 2014 Table 1. 2014 Summary statistics (United States) Item Value Primary energy source Coal Net summer capacity (megawatts) 1,068,422 Electric ...

  20. Electricity Monthly Update

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

    Update November 28, 2012 Map of Electric System Selected for Daily Peak Demand was replaced with the correct map showing Selected Wholesale Electricity and Natural Gas Locations....

  1. Electricity Monthly Update

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

    of electricity. End-use data is the first "data page" based on the assumption that information about retail electricity service is of greatest interest to a general...

  2. Electricity Monthly Update

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

    The Electric Power Sector comprises electricity-only and combined heat and power (CHP) plants within the North American Industrial Classification System 22 category whose...

  3. Electricity Monthly Update

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

    See all Electricity Reports Electricity Monthly Update With Data for November 2014 | Release Date: Jan. 26, 2015 | Next Release Date: Feb. 24, 2015 Previous Issues Issue:...

  4. Electricity Monthly Update

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

    Electricity Monthly Update Explained Highlights The Highlights page features in the center ... presents statistics on end-use: retail ratesprices and consumption of electricity. ...

  5. Electricity Monthly Update

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

    Retail ratesprices and consumption In this section, we look at what electricity costs and ... and these competitive retail suppliers offer electricity at a market-based price. ...

  6. Integrated electrical connector (Patent) | DOEPatents

    Office of Scientific and Technical Information (OSTI)

    Integrated electrical connector Title: Integrated electrical connector An electrical ... The opening is also smaller than the diameter of an electrically conductive contact pin. ...

  7. A First Look at the Impact of Electric Vehicle Charging on the Electric Grid in the EV Project

    SciTech Connect (OSTI)

    Stephen L. Schey; John G. Smart; Don R. Scoffield

    2012-05-01

    ECOtality was awarded a grant from the U.S. Department of Energy to lead a large-scale electric vehicle charging infrastructure demonstration, called The EV Project. ECOtality has partnered with Nissan North America, General Motors, the Idaho National Laboratory, and others to deploy and collect data from over 5,000 Nissan LEAFsTM and Chevrolet Volts and over 10,000 charging systems in 18 regions across the United States. This paper summarizes usage of residential charging units in The EV Project, based on data collected through the end of 2011. This information is provided to help analysts assess the impact on the electric grid of early adopter charging of grid-connected electric drive vehicles. A method of data aggregation was developed to summarize charging unit usage by the means of two metrics: charging availability and charging demand. Charging availability is plotted to show the percentage of charging units connected to a vehicle over time. Charging demand is plotted to show charging demand on the electric gird over time. Charging availability for residential charging units is similar in each EV Project region. It is low during the day, steadily increases in evening, and remains high at night. Charging demand, however, varies by region. Two EV Project regions were examined to identify regional differences. In Nashville, where EV Project participants do not have time-of-use electricity rates, demand increases each evening as charging availability increases, starting at about 16:00. Demand peaks in the 20:00 hour on weekdays. In San Francisco, where the majority of EV Project participants have the option of choosing a time-of-use rate plan from their electric utility, demand spikes at 00:00. This coincides with the beginning of the off-peak electricity rate period. Demand peaks at 01:00.

  8. Material World: Forecasting Household Appliance Ownership in a Growing Global Economy

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.

    2009-03-23

    Over the past years the Lawrence Berkeley National Laboratory (LBNL) has developed an econometric model that predicts appliance ownership at the household level based on macroeconomic variables such as household income (corrected for purchase power parity), electrification, urbanization and climate variables. Hundreds of data points from around the world were collected in order to understand trends in acquisition of new appliances by households, especially in developing countries. The appliances covered by this model are refrigerators, lighting fixtures, air conditioners, washing machines and televisions. The approach followed allows the modeler to construct a bottom-up analysis based at the end use and the household level. It captures the appliance uptake and the saturation effect which will affect the energy demand growth in the residential sector. With this approach, the modeler can also account for stock changes in technology and efficiency as a function of time. This serves two important functions with regard to evaluation of the impact of energy efficiency policies. First, it provides insight into which end uses will be responsible for the largest share of demand growth, and therefore should be policy priorities. Second, it provides a characterization of the rate at which policies affecting new equipment penetrate the appliance stock. Over the past 3 years, this method has been used to support the development of energy demand forecasts at the country, region or global level.

  9. Fact #616: March 29, 2010 Household Vehicle-Miles of Travel by Trip Purpose

    Broader source: Energy.gov [DOE]

    In 2009, getting to and from work accounted for about 27% of household vehicle-miles of travel (VMT). Work-related business was 8.4% of VMT in 2001, but declined to 6.7% in 2009, possibly due to...

  10. Electric Energy Management in the Smart Home: Perspectives on Enabling Technologies and Consumer Behavior: Preprint

    SciTech Connect (OSTI)

    Zipperer, A.; Aloise-Young, P. A.; Suryanarayanan, S.; Roche, R.; Earle, L.; Christensen, D.; Bauleo, P.; Zimmerle. D.

    2013-08-01

    Smart homes hold the potential for increasing energy efficiency, decreasing costs of energy use, decreasing the carbon footprint by including renewable resources, and transforming the role of the occupant. At the crux of the smart home is an efficient electric energy management system that is enabled by emerging technologies in the electric grid and consumer electronics. This article presents a discussion of the state-of-the-art in electricity management in smart homes, the various enabling technologies that will accelerate this concept, and topics around consumer behavior with respect to energy usage.

  11. Electric Energy Management in the Smart Home: Perspectives on Enabling Technologies and Consumer Behavior

    SciTech Connect (OSTI)

    Zipperer, A.; Aloise-Young, P. A.; Suryanarayanan, S.; Zimmerle, D.; Roche, R.; Earle, L.; Christensen, D.; Bauleo, P.

    2013-08-01

    Smart homes hold the potential for increasing energy efficiency, decreasing costs of energy use, decreasing the carbon footprint by including renewable resources, and trans-forming the role of the occupant. At the crux of the smart home is an efficient electric energy management system that is enabled by emerging technologies in the electricity grid and consumer electronics. This article presents a discussion of the state-of-the-art in electricity management in smart homes, the various enabling technologies that will accelerate this concept, and topics around consumer behavior with respect to energy usage.

  12. Career Map: Electrical Engineer

    Broader source: Energy.gov [DOE]

    The Wind Program's Career Map provides job description information for Electrical Engineer positions.

  13. HSI Usage

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

    rmdir Delete an HPSS directory Local File and Directory Commands Command Function lcd Change local directory lls List local directory lmkdir Make a local directory lpwd...

  14. HTAR Usage

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

    to Create an HTAR Archive Rather than specifying the list of files and directories on the command line when creating an HTAR archive, you can place the list of file and directory...

  15. Baltimore Gas & Electric Company (Electric) - Residential Energy...

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

    AC: 30 Recycling RefrigeratorFreezer: 50 ACDehumidifier: 25 Summary The Baltimore Gas & Electric Company (BGE) offers rebates for residential customers to improve the...

  16. Model-Based Analysis of Electric Drive Options for Medium-Duty Parcel Delivery Vehicles: Preprint

    SciTech Connect (OSTI)

    Barnitt, R. A.; Brooker, A. D.; Ramroth, L.

    2010-12-01

    Medium-duty vehicles are used in a broad array of fleet applications, including parcel delivery. These vehicles are excellent candidates for electric drive applications due to their transient-intensive duty cycles, operation in densely populated areas, and relatively high fuel consumption and emissions. The National Renewable Energy Laboratory (NREL) conducted a robust assessment of parcel delivery routes and completed a model-based techno-economic analysis of hybrid electric vehicle (HEV) and plug-in hybrid electric vehicle configurations. First, NREL characterized parcel delivery vehicle usage patterns, most notably daily distance driven and drive cycle intensity. Second, drive-cycle analysis results framed the selection of drive cycles used to test a parcel delivery HEV on a chassis dynamometer. Next, measured fuel consumption results were used to validate simulated fuel consumption values derived from a dynamic model of the parcel delivery vehicle. Finally, NREL swept a matrix of 120 component size, usage, and cost combinations to assess impacts on fuel consumption and vehicle cost. The results illustrated the dependency of component sizing on drive-cycle intensity and daily distance driven and may allow parcel delivery fleets to match the most appropriate electric drive vehicle to their fleet usage profile.

  17. Level: National Data; Row: NAICS Codes; Column: Usage within General Energy-Saving Technologies;

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

    2 Number of Establishments by Usage of General Energy-Saving Technologies, 2006; Level: National Data; Row: NAICS Codes; Column: Usage within General Energy-Saving Technologies; Unit: Establishment Counts. NAICS Code(a) Subsector and Industry Establishments(b) In Use(e) Not in Use Don't Know In Use(e) Not in Use Don't Know In Use(e) Not in Use Don't Know In Use(e) Not in Use Don't Know In Use(e) Not in Use Don't Know Total United States 311 Food 14,128 1,632 9,940 2,556 3,509 8,048 2,571 1,590

  18. Relative concordance of human immunodeficiency virus oligomeric and monomeric envelope in CCR5 coreceptor usage

    SciTech Connect (OSTI)

    Teeravechyan, Samaporn; Suphaphiphat, Pirada; Essex, Max; Lee, Tun-Hou

    2008-01-20

    A major difference between binding and fusion assays commonly used to study the human immunodeficiency virus (HIV) envelope is the use of monomeric envelope for the former assay and oligomeric envelope for the latter. Due to discrepancies in their readouts for some mutants, envelope regions involved in CCR5 coreceptor usage were systematically studied to determine whether the discordance is due to inherent differences between the two assays or whether it genuinely reflects functional differences at each entry step. By adding the binding inhibitor TAK-779 to delay coreceptor binding kinetics in the fusion assay, the readouts were found comparable between the assays for the mutants analysed in this study. Our finding indicates that monomeric binding reflects oligomeric envelope-CCR5 interaction, thus discordant results between binding and fusion assays do not necessarily indicate differences in coreceptor usage by oligomeric envelope and monomeric gp120.

  19. "Table HC9.12 Home Electronics Usage Indicators by Climate Zone, 2005"

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

    2 Home Electronics Usage Indicators by Climate Zone, 2005" " Million U.S. Housing Units" ,,"Climate Zone1" ,,"Less than 2,000 CDD and --",,,,"2,000 CDD or More and Less than 4,000 HDD" ,"Housing Units (millions)" ,,"Greater than 7,000 HDD","5,500 to 7,000 HDD","4,000 to 5,499 HDD","Less than 4,000 HDD" "Home Electronics Usage Indicators" "Total",111.1,10.9,26.1,27.3,24,22.8

  20. "Table HC9.5 Space Heating Usage Indicators by Climate Zone, 2005"

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

    5 Space Heating Usage Indicators by Climate Zone, 2005" " Million U.S. Housing Units" ,,"Climate Zone1" ,,"Less than 2,000 CDD and --",,,,"2,000 CDD or More and Less than 4,000 HDD" ,"Housing Units (millions)" ,,"Greater than 7,000 HDD","5,500 to 7,000 HDD","4,000 to 5,499 HDD","Less than 4,000 HDD" "Space Heating Usage Indicators" "Total U.S. Housing

  1. Table HC15.10 Home Appliances Usage Indicators by Four Most Populated States, 2005

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

    0 Home Appliances Usage Indicators by Four Most Populated States, 2005 Total.................................................................................... 111.1 7.1 7.0 8.0 12.1 Cooking Appliances Frequency of Hot Meals Cooked 3 or More Times A Day................................................. 8.2 0.6 0.5 0.8 1.4 2 Times A Day.............................................................. 24.6 1.4 1.5 2.0 3.1 Once a Day...................................................................

  2. Determination of usage patterns and emissions for propane/LPG in California. Final report

    SciTech Connect (OSTI)

    Sullivan, M.

    1992-05-01

    The purpose of the study was to determine California usage patterns of Liquified Petroleum Gas (LPG), and to estimate propane emissions resulting from LPG transfer operations statewide, and by county and air basin. The study is the first attempt to quantify LPG transfer emissions for California. This was accomplished by analyzing data from a telephone survey of California businesses that use LPG, by extracting information from existing databases.

  3. Y-12 reduces water usage and wins award | National Nuclear Security

    National Nuclear Security Administration (NNSA)

    Administration Home / Blog Y-12 reduces water usage and wins award Tuesday, January 5, 2016 - 12:00am NNSA Blog From left: Brad Mattie, Bill Collins, Chris Byrd, Gary Guge and Jake Thompson were instrumental in protecting Y-12 water quality. Y-12 recently received two awards at the 33rd Annual Tennessee Chamber of Commerce and Industry Environment and Energy Conference. Representatives from Y-12's Infrastructure and Environmental Compliance groups accepted the awards at the ceremony held at

  4. Electric arc saw apparatus

    DOE Patents [OSTI]

    Deichelbohrer, Paul R [Richland, WA

    1986-01-01

    A portable, hand held electric arc saw has a small frame for supporting an electrically conducting rotary blade which serves as an electrode for generating an electric arc to erode a workpiece. Electric current is supplied to the blade by biased brushes and a slip ring which are mounted in the frame. A pair of freely movable endless belts in the form of crawler treads stretched between two pulleys are used to facilitate movement of the electric arc saw. The pulleys are formed of dielectric material to electrically insulate the crawler treads from the frame.

  5. Characterization of household hazardous waste from Marin County, California, and New Orleans, Louisiana

    SciTech Connect (OSTI)

    Rathje, W.L.; Wilson, D.C.; Lambou, V.W.; Herndon, R.C.

    1987-09-01

    There is a growing concern that certain constituents of common household products, that are discarded in residential garbage, may be potentially harmful to human health and the environment by adversely affecting the quality of ground and surface water. A survey of hazardous wastes in residential garbage from Marin County, California, and New Orleans, Louisiana, was conducted in order to determine the amount and characteristics of such wastes that are entering municipal landfills. The results of the survey indicate that approximately 642 metric tons of hazardous waste are discarded per year for the New Orleans study area and approximately 259 metric tons are discarded per year for the Marin County study area. Even though the percent of hazardous household waste in the garbage discarded in both study areas was less than 1%, it represents a significant quantity of hazardous waste because of the large volume of garbage involved.

  6. The importance of China's household sector for black carbon emissions - article no. L12708

    SciTech Connect (OSTI)

    Streets, D.G.; Aunan, K.

    2005-06-30

    The combustion of coal and biofuels in Chinese households is a large source of black carbon (BC), representing about 10-15% of total global emissions during the past two decades, depending on the year. How the Chinese household sector develops during the next 50 years will have an important bearing on future aerosol concentrations, because the range of possible outcomes (about 550 Gg yr{sup -1}) is greater than total BC emissions in either the United States or Europe (each about 400-500 Gg yr{sup -1}). In some Intergovernmental Panel on Climate Change scenarios biofuels persist in rural China for at least the next 50 years, whereas in other scenarios a transition to cleaner fuels and technologies effectively mitigates BC emissions. This paper discusses measures and policies that would help this transition and also raises the possibility of including BC emission reductions as a post-Kyoto option for China and other developing countries.

  7. Evaluation of bulk paint worker exposure to solvents at household hazardous waste collection events

    SciTech Connect (OSTI)

    Cameron, M.

    1995-09-01

    In fiscal year 93/94, over 250 governmental agencies were involved in the collection of household hazardous wastes in the State of California. During that time, over 3,237,000 lbs. of oil based paint were collected in 9,640 drums. Most of this was in lab pack drums, which can only hold up to 20 one gallon cans. Cost for disposal of such drums is approximately $1000. In contrast, during the same year, 1,228,000 lbs. of flammable liquid were collected in 2,098 drums in bulk form. Incineration of bulked flammable liquids is approximately $135 per drum. Clearly, it is most cost effective to bulk flammable liquids at household hazardous waste events. Currently, this is the procedure used at most Temporary Household Hazardous Waste Collection Facilities (THHWCFs). THHWCFs are regulated by the Department of Toxic Substances Control (DTSC) under the new Permit-by Rule Regulations. These regulations specify certain requirements regarding traffic flow, emergency response notifications and prevention of exposure to the public. The regulations require that THHWCF operators bulk wastes only when the public is not present. [22 CCR, section 67450.4 (e) (2) (A)].Santa Clara County Environmental Health Department sponsors local THHWCF`s and does it`s own bulking. In order to save time and money, a variance from the regulation was requested and an employee monitoring program was initiated to determine actual exposure to workers. Results are presented.

  8. Electric Efficiency Standard

    Broader source: Energy.gov [DOE]

    In December 2009, the Indiana Utility Regulatory Commission's (IURC) ordered utilities to establish demand-side management (DSM) electric savings goals leading to 2.0% reduction of electricity sa...

  9. Electricity Monthly Update

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

    End Use: August 2015 Retail ratesprices and consumption In this section, we look at what electricity costs and how much is purchased. Charges for retail electric service are based...

  10. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Mai, T.

    2012-10-01

    This presentation library summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050.

  11. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Mai, T.

    2012-11-01

    This presentation summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050.

  12. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Mai, T.

    2013-04-01

    This presentation summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050.

  13. Electric Power Monthly

    Gasoline and Diesel Fuel Update (EIA)

    Electric Power Monthly Data for January 2016 | Release Date: March 25, 2016 | Next ... Revisions made to the March 2016 Electric Power Monthly: March 30, 2016 Tables 2.8.A-B ...

  14. Electricity Monthly Update

    Gasoline and Diesel Fuel Update (EIA)

    cheap price of natural gas reduced coals share of electricity production. Days of Burn Days of burn Coal capacity The average number of days of burn held at electric power...

  15. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Hand, M. M.

    2012-09-01

    This presentation summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050.

  16. Electricity Monthly Update

    Gasoline and Diesel Fuel Update (EIA)

    sales volumes are presented as a proxy for end-use electricity consumption. Average Revenue per kWh by state Percent Change Per KWh map showing U.S. electric industry percent...

  17. Table 2a. Electricity Consumption and Electricity Intensities...

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

    Administration Home Page Home > Commercial Buildings Home > Sq Ft Tables > Table 2a. Electricity Consumption per Sq Ft Table 2a. Electricity Consumption and Electricity...

  18. Panasonic Electric Works Ltd formerly Matsushita Electric Works...

    Open Energy Info (EERE)

    Electric Works Ltd (formerly Matsushita Electric Works) Place: Kadoma-shi, Osaka, Japan Zip: 571-8686 Product: Japanese manufacturer of mainly electric appliances including...

  19. EIA - Electricity Generating Capacity

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

    Electricity Generating Capacity Release Date: January 3, 2013 | Next Release: August 2013 Year Existing Units by Energy Source Unit Additions Unit Retirements 2011 XLS XLS XLS 2010 XLS XLS XLS 2009 XLS XLS XLS 2008 XLS XLS XLS 2007 XLS XLS XLS 2006 XLS XLS XLS 2005 XLS XLS XLS 2004 XLS XLS XLS 2003 XLS XLS XLS Source: Form EIA-860, "Annual Electric Generator Report." Related links Electric Power Monthly Electric Power Annual Form EIA-860 Source Data

  20. Ohio Electricity Restructuring Active

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

    Restructuring Ohio Restructuring Active Other Links Ohio Electricity Profile Ohio Energy Profile Ohio Web Sites Acronyms for the State of Ohio AEP-American Electric Power CG&E-Cincinnati Gas and Electric Company CRES-Certified Retail Electric Supplier DP&L-Dayton Power and Light Company FERC-Federal Energy Regulatory Commission ISO-Independent System Operator OCC-Ohio Consumers' Counsel PUCO-Public Utilities Commission of Ohio Last Updated: September 2010 08/09: Dominion Energy offered

  1. Electric arc saw apparatus

    DOE Patents [OSTI]

    Deichelbohrer, P.R.

    1983-08-08

    A portable, hand-held electric arc saw apparatus comprising a small frame for supporting an electrically conducting rotary blade which serves as an electrode for generating an electric arc between the blade and a workpiece of opposite polarity. Electrically conducting means are provided on said frame for transmitting current to said blade. A pair of freely movable endless belts in the form of crawler treads are employed to facilitate movement of the apparatus relative to the workpiece.

  2. Annual Power Electric

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

    Electric Power Annual Update / Revision Data for 2014 updated: February 16, 2016 February 16, 2016 Table update: The following tables are being withheld pending the availability of additional data: Table 8.5. Revenue and Expense Statistics for U.S. Cooperative Borrower-Owned Electric Utilities Table 8.6.A. Noncoincident Peak Load by North American Electric Reliability Corporation Assessment Area, Actual Table 8.6.B. Noncoincident Peak Load by North American Electric Reliability Corporation

  3. Electrical utilities relay settings

    SciTech Connect (OSTI)

    HACHE, J.M.

    1999-02-24

    This document contains the Hanford transmission and distribution system relay settings that are under the control of Electrical Utilities.

  4. Florida's electric industry and solar electric technologies

    SciTech Connect (OSTI)

    Camejo, N.

    1983-12-01

    The Florida Electric Industry is in a process of diversifying its generation technology and its fuel mix. This is being done in an effort to reduce oil consumption, which in 1981 accounted for 46.5% of the electric generation by fuel type. This does not compare well with the rest of the nation where oil use is lower. New coal and nuclear units are coming on line, and probably more will be built in the near future. However, eventhough conservation efforts may delay their construction, new power plants will have to be built to accomodate the growing demand for electricity. Other alternatives being considered are renewable energy resources. The purpose of this paper is to present the results of a research project in which 10 electric utilities in Florida and the Florida Electric Power Coordinating Group rated six Solar Electric options. The Solar Electric options considered are: 1) Wind, 2) P.V., 3) Solar thermal-electric, 4) OTEC, 5) Ocean current, and 6) Biomass. The questionaire involved rating the economic and technical feasibility, as well as, the potential environmental impact of these options in Florida. It also involved rating the difficulty in overcoming institutional barriers and assessing the status of each option. A copy of the questionaire is included after the references. The combined capacity of the participating utilities represent over 90% of the total generating capacity in Florida. A list of the participating utilities is also included. This research was done in partial fulfillment for the Mater's of Science Degree in Coastal Zone Management. This paper is complementary to another paper (in these condensed conference proceedings) titled COASTAL ZONE ENERGY MANAGEMENT: A multidisciplinary approach for the integration of Solar Electric Systems with Florida's power generation system, which present a summary of the Master's thesis.

  5. Impact of residential PV adoption on Retail Electricity Rates

    SciTech Connect (OSTI)

    Cai, DWH; Adlakha, S; Low, SH; De Martini, P; Chandy, KM

    2013-11-01

    The price of electricity supplied from home rooftop photo voltaic (PV) solar cells has fallen below the retail price of grid electricity in some areas. A number of residential households have an economic incentive to install rooftop PV systems and reduce their purchases of electricity from the grid. A significant portion of the costs incurred by utility companies are fixed costs which must be recovered even as consumption falls. Electricity rates must increase in order for utility companies to recover fixed costs from shrinking sales bases. Increasing rates will, in turn, result in even more economic incentives for customers to adopt rooftop PV. In this paper, we model this feedback between PV adoption and electricity rates and study its impact on future PV penetration and net-metering costs. We find that the most important parameter that determines whether this feedback has an effect is the fraction of customers who adopt PV in any year based solely on the money saved by doing so in that year, independent of the uncertainties of future years. These uncertainties include possible changes in rate structures such as the introduction of connection charges, the possibility of PV prices dropping significantly in the future, possible changes in tax incentives, and confidence in the reliability and maintainability of PV. (C) 2013 Elsevier Ltd. All rights reserved.

  6. User's guide to SERICPAC: A computer program for calculating electric-utility avoided costs rates

    SciTech Connect (OSTI)

    Wirtshafter, R.; Abrash, M.; Koved, M.; Feldman, S.

    1982-05-01

    SERICPAC is a computer program developed to calculate average avoided cost rates for decentralized power producers and cogenerators that sell electricity to electric utilities. SERICPAC works in tandem with SERICOST, a program to calculate avoided costs, and determines the appropriate rates for buying and selling of electricity from electric utilities to qualifying facilities (QF) as stipulated under Section 210 of PURA. SERICPAC contains simulation models for eight technologies including wind, hydro, biogas, and cogeneration. The simulations are converted in a diversified utility production which can be either gross production or net production, which accounts for an internal electricity usage by the QF. The program allows for adjustments to the production to be made for scheduled and forced outages. The final output of the model is a technology-specific average annual rate. The report contains a description of the technologies and the simulations as well as complete user's guide to SERICPAC.

  7. Integrating Electricity Subsector

    Energy Savers [EERE]

    Integrating Electricity Subsector Failure Scenarios into a Risk Assessment Methodology 3002001181 | DEC 2013 Program Leads Jason D. Christopher Technical Lead, Cyber Security Capabilities & Risk Management Department of Energy (DOE), Office of Electricity Delivery and Energy Reliability (OE) Annabelle Lee Senior Technical Executive, Cyber Security Electric Power Research Institute (EPRI) For more information on the DOE's cyber security risk management programs, please contact

  8. DOE Electricity Advisory Committee

    Energy Savers [EERE]

    Electricity Advisory Committee March 2015 1 MEMORANDUM TO: Honorable Patricia Hoffman, Assistant Secretary for Electricity Delivery and Energy Reliability, U.S. Department of Energy FROM: Electricity Advisory Committee (EAC) Richard Cowart, Chair DATE: March 27, 2015 RE: Recommendations on Smart Grid Research and Development Needs _________________________________________________________________________ Overview The Smart Grid is envisioned to provide the enhancements to ensure higher levels of

  9. Epcot Electric | Open Energy Information

    Open Energy Info (EERE)

    Epcot Electric Jump to: navigation, search Name: Epcot Electric Place: Texas Facebook: https:www.facebook.compagesEpcot-Electric108882552477023 References: EIA Form EIA-861...

  10. EWEB- Solar Electric Program (Rebate)

    Broader source: Energy.gov [DOE]

    The Eugene Water & Electric Board's (EWEB) Solar Electric Program offers financial incentives for residential, nonprofit, and government customers that generate electricity solar photovoltaic...

  11. Lincoln Electric | Open Energy Information

    Open Energy Info (EERE)

    Electric Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner Lincoln Electric Developer Lincoln Electric Energy Purchaser Lincoln...

  12. Household`s choices of efficiency levels for appliances: Using stated- and revealed-preference data to identify the importance of rebates and financing arrangements

    SciTech Connect (OSTI)

    Train, K.; Atherton, T.

    1994-11-01

    We examine customers` choice between standard and high-efficiency equipment, and the impact of utility incentives such as rebates and loans on this decision. Using data from interviews with 400 households, we identify the factors that customers consider in their choice of efficiency level for appliances and the relative importance of these factors. We build a model that describes customers` choices and can be used to predict choices in future situations under changes in the attributes of appliances and in the utility`s DSM and as part of the appliance-choice component of utilities` end-use forecasting systems. As examples, the model is used to predict the impacts of: doubling the size of rebates, replacing rebates with financing programs, and offering loans and rebates as alternative options for customers.

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

    SciTech Connect (OSTI)

    Kavousian, A; Rajagopal, R; Fischer, M

    2013-06-15

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

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

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

    HC7 Home Office Equipment, Million U.S. Households PDF PDF Household Energy Usage The 1997 Residential Energy Consumption Survey (RECS) collected household energy data for the ...

  15. Lessons Learned from Dependency Usage in HERA: Implications for THERP-Related HRA Methods

    SciTech Connect (OSTI)

    April M. Whaley; Ronald L. Boring; Harold S. Blackman; Patrick H. McCabe; Bruce P. Hallbert

    2007-08-01

    Dependency occurs when the probability of success or failure on one action changes the probability of success or failure on a subsequent action. Dependency may serve as a modifier on the human error probabilities (HEPs) for successive actions in human reliability analysis (HRA) models. Discretion should be employed when determining whether or not a dependency calculation is warranted: dependency should not be assigned without strongly grounded reasons. Human reliability analysts may sometimes assign dependency in cases where it is unwarranted. This inappropriate assignment is attributed to a lack of clear guidance to encompass the range of scenarios human reliability analysts are addressing. Inappropriate assignment of dependency produces inappropriately elevated HEP values. Lessons learned about dependency usage in the Human Event Repository and Analysis (HERA) system may provide clarification and guidance for analysts using first-generation HRA methods. This paper presents the HERA approach to dependency assessment and discusses considerations for dependency usage in HRA, including the cognitive basis for dependency, direction for determining when dependency should be assessed, considerations for determining the dependency level, temporal issues to consider when assessing dependency, (e.g., considering task sequence versus overall event sequence, and dependency over long periods of time), and diagnosis and action influences on dependency.

  16. A Practical and Cost Effective Demonstration of Efficient Energy Usage and Quality Management Using the NII

    SciTech Connect (OSTI)

    1999-05-01

    In order to be competitive in the changing electric power industry, and to promote energy efficiency and conservation, electric power providers need to have access to information on the power system to a level of detail that has not been available in the past. This level of detail extends beyond the usual voltage, current, power, and energy quantities obtained from traditional utility SCADA systems.

  17. Integrated electrical connector

    DOE Patents [OSTI]

    Benett, William J.; Ackler, Harold D.

    2005-05-24

    An electrical connector is formed from a sheet of electrically conductive material that lies in between the two layers of nonconducting material that comprise the casing of an electrical chip. The connector is electrically connected to an electrical element embedded within the chip. An opening in the sheet is concentrically aligned with a pair of larger holes respectively bored through the nonconducting layers. The opening is also smaller than the diameter of an electrically conductive contact pin. However, the sheet is composed flexible material so that the opening adapts to the diameter of the pin when the pin is inserted therethrough. The periphery of the opening applies force to the sides of the pin when the pin is inserted, and thus holds the pin within the opening and in contact with the sheet, by friction. The pin can be withdrawn from the connector by applying sufficient axial force.

  18. Electric power monthly

    SciTech Connect (OSTI)

    1995-08-01

    The Energy Information Administration (EIA) prepares the Electric Power Monthly (EPM) for a wide audience including Congress, Federal and State agencies, the electric utility industry, and the general public. This publication provides monthly statistics for net generation, fossil fuel consumption and stocks, quantity and quality of fossil fuels, cost of fossil fuels, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fossil fuels are also displayed for the North American Electric Reliability Council (NERC) regions. The EIA publishes statistics in the EPM on net generation by energy source, consumption, stocks, quantity, quality, and cost of fossil fuels; and capability of new generating units by company and plant. The purpose of this publication is to provide energy decisionmakers with accurate and timely information that may be used in forming various perspectives on electric issues that lie ahead.

  19. Electrical system architecture

    DOE Patents [OSTI]

    Algrain, Marcelo C.; Johnson, Kris W.; Akasam, Sivaprasad; Hoff, Brian D.

    2008-07-15

    An electrical system for a vehicle includes a first power source generating a first voltage level, the first power source being in electrical communication with a first bus. A second power source generates a second voltage level greater than the first voltage level, the second power source being in electrical communication with a second bus. A starter generator may be configured to provide power to at least one of the first bus and the second bus, and at least one additional power source may be configured to provide power to at least one of the first bus and the second bus. The electrical system also includes at least one power consumer in electrical communication with the first bus and at least one power consumer in electrical communication with the second bus.

  20. Thermoacoustic magnetohydrodynamic electrical generator

    DOE Patents [OSTI]

    Wheatley, J.C.; Swift, G.W.; Migliori, A.

    1984-11-16

    A thermoacoustic magnetohydrodynamic electrical generator includes an intrinsically irreversible thermoacoustic heat engine coupled to a magnetohydrodynamic electrical generator. The heat engine includes an electrically conductive liquid metal as the working fluid and includes two heat exchange and thermoacoustic structure assemblies which drive the liquid in a push-pull arrangement to cause the liquid metal to oscillate at a resonant acoustic frequency on the order of 1000 Hz. The engine is positioned in the field of a magnet and is oriented such that the liquid metal oscillates in a direction orthogonal to the field of the magnet, whereby an alternating electrical potential is generated in the liquid metal. Low-loss, low-inductance electrical conductors electrically connected to opposite sides of the liquid metal conduct an output signal to a transformer adapted to convert the low-voltage, high-current output signal to a more usable higher voltage, lower current signal.

  1. Thermoacoustic magnetohydrodynamic electrical generator

    DOE Patents [OSTI]

    Wheatley, John C.; Swift, Gregory W.; Migliori, Albert

    1986-01-01

    A thermoacoustic magnetohydrodynamic electrical generator includes an intrinsically irreversible thermoacoustic heat engine coupled to a magnetohydrodynamic electrical generator. The heat engine includes an electrically conductive liquid metal as the working fluid and includes two heat exchange and thermoacoustic structure assemblies which drive the liquid in a push-pull arrangement to cause the liquid metal to oscillate at a resonant acoustic frequency on the order of 1,000 Hz. The engine is positioned in the field of a magnet and is oriented such that the liquid metal oscillates in a direction orthogonal to the field of the magnet, whereby an alternating electrical potential is generated in the liquid metal. Low-loss, low-inductance electrical conductors electrically connected to opposite sides of the liquid metal conduct an output signal to a transformer adapted to convert the low-voltage, high-current output signal to a more usable higher voltage, lower current signal.

  2. Electric Power Research Institute

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

    2015 U.S. Energy Information Administration | Electric Power Monthly Appendix C Technical notes This appendix describes how the U. S. Energy Information Administration (EIA) collects, estimates, and reports electric power data in the EPM. Data quality The EPM is prepared by the Office of Electricity, Renewables & Uranium Statistics (ERUS), Energy Information Administration (EIA), U. S. Department of Energy. Quality statistics begin with the collection of the correct data. To assure this,

  3. Electric Power Monthly

    Gasoline and Diesel Fuel Update (EIA)

    Electric Power Monthly > Electric Power Monthly Back Issues Electric Power Monthly Back Issues Monthly Excel files zipped 2010 January February March April May June July August September October November December 2009 January February March April May June July August September October November December 2008 January February March March Supplement April May June July August September October November December 2007 January February March April May June July August September October November

  4. Office of Electricity Delivery

    Energy Savers [EERE]

    4 DOE Resilient Electric Distribution Grid R&D Workshop June 11, 2014 Upton, New York 2014 DOE Resilient Electric Distribution Grid R&D Workshop Report Page i June 24, 2014 Acknowledgment The U.S. Department of Energy (DOE) acknowledges the support provided by the organizations represented at the Resilient Electric Distribution Grid R&D Workshop. The report content is based on the workshop session discussions, with session summary descriptions taken from the report-out presentations

  5. Table HC6.11 Home Electronics Characteristics by Number of Household Members, 2005

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

    1 Home Electronics Characteristics 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 Number of Desktop PCs 1.................................................................. 50.3 11.9 17.4 8.5 7.3 5.2

  6. Table HC6.2 Living Space Characteristics by Number of Household Members, 2005

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

    2 Living Space Characteristics by Number of Household Members, 2005 Total...................................................................... 111.1 30.0 34.8 18.4 15.9 12.0 Floorspace (Square Feet) Total Floorspace 1 Fewer than 500............................................... 3.2 1.7 0.8 0.4 0.3 Q 500 to 999....................................................... 23.8 10.2 6.4 3.4 2.3 1.5 1,000 to 1,499................................................. 20.8 5.5 6.3 3.0 3.3 2.6 1,500 to

  7. Table HC6.9 Home Appliances Characteristics by Number of Household Members, 2005

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

    HC6.9 Home Appliances Characteristics by Number of Household Members, 2005 Total U.S.............................................................. 111.1 30.0 34.8 18.4 15.9 12.0 Cooking Appliances Conventional Ovens Use an Oven.................................................. 109.6 29.5 34.4 18.2 15.7 11.8 1................................................................. 103.3 28.4 32.0 17.3 14.7 11.0 2 or More.................................................... 6.2 1.1 2.5 1.0 0.9 0.8 Do Not

  8. Assessment of lead contamination in Bahrain environment. I. Analysis of household paint

    SciTech Connect (OSTI)

    Madany, I.M.; Ali, S.M.; Akhter, M.S.

    1987-01-01

    The analysis of lead in household paint collected from various old buildings in Bahrain is reported. The atomic absorption spectrophotometric method, both flame and flameless (graphite furnace) techniques, were used for the analysis. The concentrations of lead in paint were found in the range 200 to 5700 mg/kg, which are low compared to the limit of 0.5% in UK and 0.06% in USA. Nevertheless, these are hazardous. Recommendations are reported in order to avoid paint containing lead. 17 references, 1 table.

  9. The changing character of household waste in the Czech Republic between 1999 and 2009 as a function of home heating methods

    SciTech Connect (OSTI)

    Dolealov, Markta; Beneov, Libue; Zvodsk, Anita

    2013-09-15

    Highlights: The character of household waste in the three different types of households were assesed. The quantity, density and composition of household waste were determined. The physicochemical characteristics were determined. The changing character of household waste during past 10 years was described. The potential of energy recovery of household waste in Czech republic was assesed. - Abstract: The authors of this paper report on the changing character of household waste, in the Czech Republic between 1999 and 2009 in households differentiated by their heating methods. The data presented are the result of two projects, financed by the Czech Ministry of Environment, which were undertaken during this time period with the aim of focusing on the waste characterisation and complete analysis of the physicochemical properties of the household waste. In the Czech Republic, the composition of household waste varies significantly between different types of households based on the methods of home heating employed. For the purposes of these studies, the types of homes were divided into three categories urban, mixed and rural. Some of the biggest differences were found in the quantities of certain subsample categories, especially fine residue (matter smaller than 20 mm), between urban households with central heating and rural households that primarily employ solid fuel such coal or wood. The use of these solid fuels increases the fraction of the finer categories because of the higher presence of ash. Heating values of the residual household waste from the three categories varied very significantly, ranging from 6.8 MJ/kg to 14.2 MJ/kg in 1999 and from 6.8 MJ/kg to 10.5 MJ/kg in 2009 depending on the type of household and season. The same factors affect moisture of residual household waste which varied from 23.2% to 33.3%. The chemical parameters also varied significantly, especially in the quantities of Tl, As, Cr, Zn, Fe and Mn, which were higher in rural households. Because knowledge about the properties of household waste, as well as its physicochemical characteristics, is very important not only for future waste management, but also for the prediction of the behaviour and influence of the waste on the environment as the country continues to streamline its legislation to the European Unions solid waste mandates, the results of these studies were employed by the Czech Ministry of Environment to optimise the national waste management strategy.

  10. 2012 National Electricity Forum

    Energy Savers [EERE]

    and Planning, Arizona Public Service * Jan Strack, Grid Planning, Regulatory & Economics Manager, San Diego Gas & Electric * Mario Villar, Vice President, Transmission, NV ...

  11. Renewable Electricity Generation

    SciTech Connect (OSTI)

    2012-09-01

    This document highlights DOE's Office of Energy Efficiency and Renewable Energy's advancements in renewable electricity generation technologies including solar, water, wind, and geothermal.

  12. Electricity Advisory Committee

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

    Carlos Coe Millennium Energy Robert Curry Jr. CurryEnergy Clark Gellings Electric Power Research Institute Paul Hudson Stratus Energy Group Susan Kelly American Public Power ...

  13. Electricity Advisory Committee

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

    Carlos Coe Millennium Energy Robert Curry Jr. CurryEnergy Clark Gellings Electric Power Research Institute Michael Heyeck The Grid Group Paul Hudson Stratus Energy Group Susan ...

  14. Electricity Advisory Committee

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

    Robert Curry New York State Public Service Commission Clark Gellings Electric Power Research Institute Dian Grueneich Dian Grueneich Consulting, LLC. Michael Heyeck ...

  15. Electricity Monthly Update

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

    Electric Reliability Council of Texas (ERCOT), and two locations in the California ISO (CAISO). Also shown are wholesale prices at trading hubs in Louisiana (into Entergy),...

  16. 2015 Electricity Form Proposals

    Gasoline and Diesel Fuel Update (EIA)

    Quarterly Electricity Imports and Exports Report (EIA-111) OMB Clearance Renewal in 2015 ... Report (EIA-111) survey on August 26, 2015. The initial proposals were announced to ...

  17. Electricity Monthly Update

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

    Wholesale Markets: February 2014 The United States has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale...

  18. Electrical Circuit Tester

    DOE Patents [OSTI]

    Love, Frank

    2006-04-18

    An electrical circuit testing device is provided, comprising a case, a digital voltage level testing circuit with a display means, a switch to initiate measurement using the device, a non-shorting switching means for selecting pre-determined electrical wiring configurations to be tested in an outlet, a terminal block, a five-pole electrical plug mounted on the case surface and a set of adapters that can be used for various multiple-pronged electrical outlet configurations for voltages from 100 600 VAC from 50 100 Hz.

  19. Electricity Monthly Update

    Gasoline and Diesel Fuel Update (EIA)

    Electricity Monthly Update With Data for February 2016 | Release Date: April ... to the gains of other renewable energy sources (such as solar and wind), these recent NPD ...

  20. Energy 101: Electric Vehicles

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

    This edition of Energy 101 highlights the benefits of electric vehicles, including improved fuel efficiency, reduced emissions, and lower maintenance costs.

  1. Electricity Monthly Update

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

    costs, of which fuel costs account for the lion's share. Therefore, we present below, electricity generation output by fuel type and generator type. Since the generatorfuel...

  2. Electricity Monthly Update

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

    (ISO-NE), New York ISO (NYISO), PJM Interconnection (PJM), Midwest ISO (MISO), Electric Reliability Council of Texas (ERCOT), and two locations in the California ISO (CAISO). ...

  3. Electricity Transmission, A Primer

    Energy Savers [EERE]

    ... Biomass plants are best built near their source of fuel for ... the transmission grid by an authorized scheduling utility. ... Power Pool: Two or more inter- connected electric systems ...

  4. Electricity Monthly Update

    Gasoline and Diesel Fuel Update (EIA)

    Electric Power Sector Coal Stocks: February 2016 Stocks In February, U.S. coal stockpiles remained relatively flat compared to the previous month, deviating from the normal ...

  5. Electric Utility Industry Update

    Broader source: Energy.gov [DOE]

    Presentation—given at the April 2012 Federal Utility Partnership Working Group (FUPWG) meeting—covers significant electric industry trends and industry priorities with federal customers.

  6. Perforation patterned electrical interconnects

    DOE Patents [OSTI]

    Frey, Jonathan

    2014-01-28

    This disclosure describes systems and methods for increasing the usable surface area of electrical contacts within a device, such as a thin film solid state device, through the implementation of electrically conductive interconnects. Embodiments described herein include the use of a plurality of electrically conductive interconnects that penetrate through a top contact layer, through one or more multiple layers, and into a bottom contact layer. The plurality of conductive interconnects may form horizontal and vertical cross-sectional patterns. The use of lasers to form the plurality of electrically conductive interconnects from reflowed layer material further aids in the manufacturing process of a device.

  7. Electrical Utility Materials Handler

    Broader source: Energy.gov [DOE]

    Join the Bonneville Power Administration (BPA) for a challenging and rewarding career, while working, living, and playing in the Pacific Northwest. The Electrical Utility Material Handler (EUMH)...

  8. Electrically conductive cellulose composite

    DOE Patents [OSTI]

    Evans, Barbara R.; O'Neill, Hugh M.; Woodward, Jonathan

    2010-05-04

    An electrically conductive cellulose composite includes a cellulose matrix and an electrically conductive carbonaceous material incorporated into the cellulose matrix. The electrical conductivity of the cellulose composite is at least 10 .mu.S/cm at 25.degree. C. The composite can be made by incorporating the electrically conductive carbonaceous material into a culture medium with a cellulose-producing organism, such as Gluconoacetobacter hansenii. The composites can be used to form electrodes, such as for use in membrane electrode assemblies for fuel cells.

  9. Electric Storage Water Heaters

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

    & Events Expand News & Events Skip navigation links Residential Residential Lighting Energy Star Appliances Consumer Electronics Heat Pump Water Heaters Electric Storage Water...

  10. Electricity Monthly Update

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

    Electricity Monthly Update Explained Highlights The Highlights page features in the center a short article about a major event or an informative topic. The left column contains...

  11. CASL - Westinghouse Electric Company

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

    nuclear technology is helping to provide future generations with safe, clean and reliable electricity. Key Contributions Definition of CASL challenge problems Existing codes and...

  12. Electricity Monthly Update

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

    New York ISO (NYISO), PJM Interconnection (PJM), Midwest ISO (MISO), Electric Reliability Council of Texas (ERCOT), and two locations in the California ISO (CAISO). Also...

  13. DOE Electricity Advisory Committee

    Energy Savers [EERE]

    ... In larger buildings they can be Energy Management Systems operating end- uses, electrical and thermal storage and guiding participation in Demand Response programs. 2 Distributed ...

  14. Department of Energy - Electricity

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

    opportunities and challenges that lie ahead. Secretary Moniz headed down to Florida to talk about Grid Modernization. Learn more about our nation's electric grid in this fact...

  15. Electricity Monthly Update

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

    Regional Wholesale Markets: May 2015 The United States has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale...

  16. Electricity Monthly Update

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

    Wholesale Markets: August 2015 The United States has many regional wholesale electricity markets. Below we look at monthly and annual ranges of on-peak, daily wholesale...

  17. Electricity Monthly Update

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

    and fuel consumption In this section, we look at the resources used to produce electricity. Generating units are chosen to run primarily on their operating costs, of which...

  18. Electric power annual 1992

    SciTech Connect (OSTI)

    Not Available

    1994-01-06

    The Electric Power Annual presents a summary of electric utility statistics at national, regional and State levels. The objective of the publication is to provide industry decisionmakers, government policymakers, analysts and the general public with historical data that may be used in understanding US electricity markets. The Electric Power Annual is prepared by the Survey Management Division; Office of Coal, Nuclear, Electric and Alternate Fuels; Energy Information Administration (EIA); US Department of Energy. ``The US Electric Power Industry at a Glance`` section presents a profile of the electric power industry ownership and performance, and a review of key statistics for the year. Subsequent sections present data on generating capability, including proposed capability additions; net generation; fossil-fuel statistics; retail sales; revenue; financial statistics; environmental statistics; electric power transactions; demand-side management; and nonutility power producers. In addition, the appendices provide supplemental data on major disturbances and unusual occurrences in US electricity power systems. Each section contains related text and tables and refers the reader to the appropriate publication that contains more detailed data on the subject matter. Monetary values in this publication are expressed in nominal terms.

  19. Integrating Electricity Subsector

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

    ... The electric sector cyber security domain threat model incorporates the following elements: * Adversaries with intent, driven by money, politics, religion, activist causes, ...

  20. 2013 Electricity Form Proposals

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

    Form EIA-861, "Annual Electric Power Industry Report" The EIA-861 survey has historically collected retail sales, revenue, and a variety of information related to demand response ...

  1. Miniaturized Analytical Platforms From Nanoparticle Components: Studies in the Construction, Characterization, and High-Throughput Usage of These Novel Architectures

    SciTech Connect (OSTI)

    Andrew David Pris

    2003-08-05

    The scientific community has recently experienced an overall effort to reduce the physical size of many experimental components to the nanometer size range. This size is unique as the characteristics of this regime involve aspects of pure physics, biology, and chemistry. One extensively studied example of a nanometer sized experimental component, which acts as a junction between these three principle scientific theologies, is deoxyribonucleic acid (DNA) or ribonucleic acid (RNA). These biopolymers not only contain the biological genetic guide to code for the production of life-sustaining materials, but are also being probed by physicists as a means to create electrical circuits and furthermore as controllable architectural and sensor motifs in the chemical disciplines. Possibly the most common nano-sized component between these sciences are nanoparticles composed of a variety of materials. The cross discipline employment of nanoparticles is evident from the vast amount of literature that has been produced from each of the individual communities within the last decade. Along these cross-discipline lines, this dissertation examines the use of several different types of nanoparticles with a wide array of surface chemistries to understand their adsorption properties and to construct unique miniaturized analytical and immunoassay platforms. This introduction will act as a literature review to provide key information regarding the synthesis and surface chemistries of several types of nanoparticles. This material will set the stage for a discussion of assembling ordered arrays of nanoparticles into functional platforms, architectures, and sensors. The introduction will also include a short explanation of the atomic force microscope that is used throughout the thesis to characterize the nanoparticle-based structures. Following the Introduction, four research chapters are presented as separate manuscripts. Chapter 1 examines the self-assembly of polymeric nanoparticles exhibiting a variety of surface chemistries and attempts to deconvolute general adsorption rules for their assembly on various substrates. Chapter 2 extends the usage of self-assembly of polymeric nanoparticles through a layer-by-layer deposition concept and photolithography methodologies to create analytical platforms with a vertical height controlled within the nanometer regime. This platform is then furthered in Chapter 3 by employing this integrated concept as a bio-recognition platform, with the extension of the method to a high-throughput screening system explored. Chapter 4 exploits two different types of nanoparticles, silica and gold, as multiplexed, self-assembled immunoassay sensors. This final research chapter is followed by a general summation and future prospectus section that concludes the dissertation.

  2. Recovery and separation of high-value plastics from discarded household appliances

    SciTech Connect (OSTI)

    Karvelas, D.E.; Jody, B.J.; Poykala, J.A. Jr.; Daniels, E.J.; Arman, B. |

    1996-03-01

    Argonne National Laboratory is conducting research to develop a cost- effective and environmentally acceptable process for the separation of high-value plastics from discarded household appliances. The process under development has separated individual high purity (greater than 99.5%) acrylonitrile-butadiene-styrene (ABS) and high- impact polystyrene (HIPS) from commingled plastics generated by appliance-shredding and metal-recovery operations. The process consists of size-reduction steps for the commingled plastics, followed by a series of gravity-separation techniques to separate plastic materials of different densities. Individual plastics of similar densities, such as ABS and HIPS, are further separated by using a chemical solution. By controlling the surface tension, the density, and the temperature of the chemical solution we are able to selectively float/separate plastics that have different surface energies. This separation technique has proven to be highly effective in recovering high-purity plastics materials from discarded household appliances. A conceptual design of a continuous process to recover high-value plastics from discarded appliances is also discussed. In addition to plastics separation research, Argonne National Laboratory is conducting research to develop cost-effective techniques for improving the mechanical properties of plastics recovered from appliances.

  3. Electrically conductive diamond electrodes

    DOE Patents [OSTI]

    Swain, Greg; Fischer, Anne ,; Bennett, Jason; Lowe, Michael

    2009-05-19

    An electrically conductive diamond electrode and process for preparation thereof is described. The electrode comprises diamond particles coated with electrically conductive doped diamond preferably by chemical vapor deposition which are held together with a binder. The electrodes are useful for oxidation reduction in gas, such as hydrogen generation by electrolysis.

  4. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Hand, M.

    2012-10-01

    This presentation library summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. It is being presented at the Utility Variable-Generation Integration Group Fall Technical Workshop on October 24, 2012.

  5. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Hand, M.; Mai, T.

    2012-08-01

    This presentation library summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. It was presented in an Union of Concerned Scientists webinar on June 12, 2012.

  6. Electrical Circuit Simulation Code

    Energy Science and Technology Software Center (OSTI)

    2001-08-09

    Massively-Parallel Electrical Circuit Simulation Code. CHILESPICE is a massively-arallel distributed-memory electrical circuit simulation tool that contains many enhanced radiation, time-based, and thermal features and models. Large scale electronic circuit simulation. Shared memory, parallel processing, enhance convergence. Sandia specific device models.

  7. Hawaii electric system reliability.

    SciTech Connect (OSTI)

    Silva Monroy, Cesar Augusto; Loose, Verne William

    2012-09-01

    This report addresses Hawaii electric system reliability issues; greater emphasis is placed on short-term reliability but resource adequacy is reviewed in reference to electric consumers' views of reliability %E2%80%9Cworth%E2%80%9D and the reserve capacity required to deliver that value. The report begins with a description of the Hawaii electric system to the extent permitted by publicly available data. Electrical engineering literature in the area of electric reliability is researched and briefly reviewed. North American Electric Reliability Corporation standards and measures for generation and transmission are reviewed and identified as to their appropriateness for various portions of the electric grid and for application in Hawaii. Analysis of frequency data supplied by the State of Hawaii Public Utilities Commission is presented together with comparison and contrast of performance of each of the systems for two years, 2010 and 2011. Literature tracing the development of reliability economics is reviewed and referenced. A method is explained for integrating system cost with outage cost to determine the optimal resource adequacy given customers' views of the value contributed by reliable electric supply. The report concludes with findings and recommendations for reliability in the State of Hawaii.

  8. Energy 101: Electric Vehicles

    ScienceCinema (OSTI)

    None

    2013-05-29

    This edition of Energy 101 highlights the benefits of electric vehicles, including improved fuel efficiency, reduced emissions, and lower maintenance costs. For more information on electric vehicles from the Office of Energy Efficiency and Renewable Energy, visit the Vehicle Technologies Program website: http://www1.eere.energy.gov/vehiclesandfuels/

  9. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Mai, T.

    2012-08-01

    This presentation summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. This presentation was presented in a Wind Powering America webinar on August 15, 2012 and is now available through the Wind Powering America website.

  10. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Mai, T.

    2012-08-01

    This presentation summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. It was presented in a Power Systems Engineering Research Center webinar on September 4, 2012.

  11. Renewable Electricity Futures (Presentation)

    SciTech Connect (OSTI)

    Hand, M. M.

    2012-08-01

    This presentation library summarizes findings of NREL's Renewable Electricity Futures study, published in June 2012. RE Futures investigated the challenges and impacts of achieving very high renewable electricity generation levels in the contiguous United States by 2050. It was presented in a webinar given by the California Energy Commission.

  12. Alternative Fuels Data Center: Electricity

    Alternative Fuels and Advanced Vehicles Data Center [Office of Energy Efficiency and Renewable Energy (EERE)]

    Electricity Printable Version Share this resource Send a link to Alternative Fuels Data Center: Electricity to someone by E-mail Share Alternative Fuels Data Center: Electricity on Facebook Tweet about Alternative Fuels Data Center: Electricity on Twitter Bookmark Alternative Fuels Data Center: Electricity on Google Bookmark Alternative Fuels Data Center: Electricity on Delicious Rank Alternative Fuels Data Center: Electricity on Digg Find More places to share Alternative Fuels Data Center:

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

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

    3 Household Characteristics 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" "Household Characteristics"

  14. Electric power monthly

    SciTech Connect (OSTI)

    Smith, Sandra R.; Johnson, Melvin; McClevey, Kenneth; Calopedis, Stephen; Bolden, Deborah

    1992-05-01

    The Electric Power Monthly is prepared by the Survey Management Division; Office of Coal, Nuclear, Electric and Alternate Fuels, Energy Information Administration (EIA), Department of Energy. This publication provides monthly statistics at the national, Census division, and State levels for net generation, fuel consumption, fuel stocks, quantity and quality of fuel, cost of fuel, electricity sales, revenue, and average revenue per kilowatthour of electricity sold. Data on net generation, fuel consumption, fuel stocks, quantity and cost of fuel are also displayed for the North American Electric Reliability Council (NERC) regions. Additionally, statistics by company and plant are published in the EPM on capability of new plants, new generation, fuel consumption, fuel stocks, quantity and quality of fuel, and cost of fuel.

  15. Electric turbocompound control system

    DOE Patents [OSTI]

    Algrain, Marcelo C.

    2007-02-13

    Turbocompound systems can be used to affect engine operation using the energy in exhaust gas that is driving the available turbocharger. A first electrical device acts as a generator in response to turbocharger rotation. A second electrical device acts as a motor to put mechanical power into the engine, typically at the crankshaft. Apparatus, systems, steps, and methods are described to control the generator and motor operations to control the amount of power being recovered. This can control engine operation closer to desirable parameters for given engine-related operating conditions compared to actual. The electrical devices can also operate in "reverse," going between motor and generator functions. This permits the electrical device associated with the crankshaft to drive the electrical device associated with the turbocharger as a motor, overcoming deficient engine operating conditions such as associated with turbocharger lag.

  16. Buildings Energy Data Book: 8.5 Federal Government Water Usage

    Buildings Energy Data Book [EERE]

    5 Federal Government Water Usage March 2012 8.5.1 Federal Water Consumption Intensity and Costs (Millions of Gallons) Agency Total Source(s): 164,382.9 536,301.9 3,129,134.9 52.5 FEMP, Annual Report to Congress on Federal Government Energy Management and Conservation Programs FY 2007, Table 9, p. 26, Jan. 2010. HUD 21.8 139.1 1,432.0 15.2 RRB 5.5 19.5 346.9 15.9 SSA 125.0 617.1 9,262.0 13.5 Archives 107.9 552.9 4,062.0 26.6 State 169.0 762.2 4,476.7 37.8 EPA 168.1 1,196.0 3,723.3 45.2 Treasury

  17. Prolonged cold storage of red blood cells by oxygen removal and additive usage

    DOE Patents [OSTI]

    Bitensky, M.W.; Yoshida, Tatsuro

    1998-08-04

    Prolonged cold storage of red blood cells by oxygen removal and additive usage. A cost-effective, 4 C storage procedure that preserves red cell quality and prolongs post-transfusion in vivo survival is described. The improved in vivo survival and the preservation of adenosine triphosphate levels, along with reduction in hemolysis and membrane vesicle production of red blood cells stored at 4 C for prolonged periods of time, is achieved by reducing the oxygen level therein at the time of storage; in particular, by flushing the cells with an inert gas, and storing them in an aqueous solution which includes adenine, dextrose, mannitol, citrate ion, and dihydrogen phosphate ion, but no sodium chloride, in an oxygen-permeable container which is located in an oxygen-free environment containing oxygen-scavenging materials. 8 figs.

  18. Prolonged cold storage of red blood cells by oxygen removal and additive usage

    DOE Patents [OSTI]

    Bitensky, Mark W.; Yoshida, Tatsuro

    1998-01-01

    Prolonged cold storage of red blood cells by oxygen removal and additive usage. A cost-effective, 4.degree. C. storage procedure that preserves red cell quality and prolongs post-transfusion in vivo survival is described. The improved in vivo survival and the preservation of adenosine triphosphate levels, along with reduction in hemolysis and membrane vesicle production of red blood cells stored at 4.degree. C. for prolonged periods of time, is achieved by reducing the oxygen level therein at the time of storage; in particular, by flushing the cells with an inert gas, and storing them in an aqueous solution which includes adenine, dextrose, mannitol, citrate ion, and dihydrogen phosphate ion, but no sodium chloride, in an oxygen-permeable container which is located in an oxygen-free environment containing oxygen-scavenging materials.

  19. "Table HC9.10 Home Appliances Usage Indicators by Climate Zone, 2005"

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

    0 Home Appliances Usage Indicators by Climate Zone, 2005" " Million U.S. Housing Units" ,,"Climate Zone1" ,,"Less than 2,000 CDD and --",,,,"2,000 CDD or More and Less than 4,000 HDD" ,"Housing Units (millions)" ,,"Greater than 7,000 HDD","5,500 to 7,000 HDD","4,000 to 5,499 HDD","Less than 4,000 HDD" "Home Appliances Characteristics" "Total",111.1,10.9,26.1,27.3,24,22.8

  20. "Table HC10.10 Home Appliances Usage Indicators by U.S. Census Regions, 2005"

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

    0 Home Appliances Usage Indicators by U.S. Census Regions, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Home Appliances Usage Indicators",,"Northeast","Midwest","South","West" "Total",111.1,20.6,25.6,40.7,24.2 "Cooking Appliances" "Frequency of Hot Meals Cooked" "3 or More Times A Day",8.2,1.2,1.4,3,2.6 "2 Times A

  1. "Table HC10.12 Home Electronics Usage Indicators by U.S. Census Region, 2005"

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

    2 Home Electronics Usage Indicators by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Home Electronics Usage Indicators",,"Northeast","Midwest","South","West" "Total",111.1,20.6,25.6,40.7,24.2 "Personal Computers" "Do Not Use a Personal Computer",35.5,6.9,8.1,14.2,6.4 "Use a Personal

  2. "Table HC10.13 Lighting Usage Indicators by U.S. Census Region, 2005"

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

    3 Lighting Usage Indicators by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Lighting Usage Indicators",,"Northeast","Midwest","South","West" "Total U.S. Housing Units",111.1,20.6,25.6,40.7,24.2 "Indoor Lights Turned On During Summer" "Number of Lights Turned On" "Between 1 and 4 Hours per

  3. "Table HC10.5 Space Heating Usage Indicators by U.S. Census Region, 2005"

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

    5 Space Heating Usage Indicators by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Space Heating Usage Indicators",,"Northeast","Midwest","South","West" "Total U.S. Housing Units",111.1,20.6,25.6,40.7,24.2 "Do Not Have Heating Equipment",1.2,"Q","Q","Q",0.7 "Have Space Heating

  4. "Table HC10.7 Air-Conditioning Usage Indicators by U.S. Census Region, 2005"

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

    7 Air-Conditioning Usage Indicators by U.S. Census Region, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","U.S. Census Region" "Air Conditioning Usage Indicators",,"Northeast","Midwest","South","West" "Total",111.1,20.6,25.6,40.7,24.2 "Do Not Have Cooling Equipment",17.8,4,2.1,1.4,10.3 "Have Cooling Equipment",93.3,16.5,23.5,39.3,13.9 "Use Cooling

  5. "Table HC11.10 Home Appliances Usage Indicators by Northeast Census Region, 2005"

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

    0 Home Appliances Usage Indicators by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ," U.S. Housing Units (millions) " ,,,"Census Division" ,,"Total Northeast" "Home Appliances Usage Indicators",,,"Middle Atlantic","New England" "Total",111.1,20.6,15.1,5.5 "Cooking Appliances" "Frequency of Hot Meals Cooked" "3 or More Times A

  6. "Table HC11.12 Home Electronics Usage Indicators by Northeast Census Region, 2005"

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

    2 Home Electronics Usage Indicators by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Home Electronics Usage Indicators",,,"Middle Atlantic","New England" "Total",111.1,20.6,15.1,5.5 "Personal Computers" "Do Not Use a Personal Computer",35.5,6.9,5.3,1.6 "Use a

  7. "Table HC11.5 Space Heating Usage Indicators by Northeast Census Region, 2005"

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

    5 Space Heating Usage Indicators by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Space Heating Usage Indicators",,,"Middle Atlantic","New England" "Total U.S. Housing Units",111.1,20.6,15.1,5.5 "Do Not Have Heating Equipment",1.2,"Q","Q","Q"

  8. "Table HC11.7 Air-Conditioning Usage Indicators by Northeast Census Region, 2005"

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

    7 Air-Conditioning Usage Indicators by Northeast Census Region, 2005" " Million U.S. Housing Units" ,,"Northeast Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Northeast" "Air Conditioning Usage Indicators",,,"Middle Atlantic","New England" "Total",111.1,20.6,15.1,5.5 "Do Not Have Cooling Equipment",17.8,4,2.4,1.7 "Have Cooling

  9. "Table HC12.10 Home Appliances Usage Indicators by Midwest Census Region, 2005"

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

    0 Home Appliances Usage Indicators by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Home Appliances Usage Indicators",,,"East North Central","West North Central" "Total",111.1,25.6,17.7,7.9 "Cooking Appliances" "Frequency of Hot Meals Cooked" "3 or More Times A

  10. "Table HC12.12 Home Electronics Usage Indicators by Midwest Census Region, 2005"

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

    2 Home Electronics Usage Indicators by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Home Electronics Usage Indicators",,,"East North Central","West North Central" "Total",111.1,25.6,17.7,7.9 "Personal Computers" "Do Not Use a Personal Computer",35.5,8.1,5.6,2.5 "Use

  11. "Table HC12.5 Space Heating Usage Indicators by Midwest Census Region, 2005"

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

    5 Space Heating Usage Indicators by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Space Heating Usage Indicators",,,"East North Central","West North Central" "Total U.S. Housing Units",111.1,25.6,17.7,7.9 "Do Not Have Heating Equipment",1.2,"Q","Q","N"

  12. "Table HC12.7 Air-Conditioning Usage Indicators by Midwest Census Region, 2005"

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

    7 Air-Conditioning Usage Indicators by Midwest Census Region, 2005" " Million U.S. Housing Units" ,,"Midwest Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total Midwest" "Air Conditioning Usage Indicators",,,"East North Central","West North Central" "Total",111.1,25.6,17.7,7.9 "Do Not Have Cooling Equipment",17.8,2.1,1.8,0.3 "Have Cooling

  13. "Table HC13.10 Home Appliances Usage Indicators by South Census Region, 2005"

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

    0 Home Appliances Usage Indicators by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Home Appliances Usage Indicators",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Cooking Appliances" "Frequency of Hot Meals Cooked"

  14. "Table HC13.12 Home Electronics Usage Indicators by South Census Region, 2005"

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

    2 Home Electronics Usage Indicators by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Home Electronics Usage Indicators",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Personal Computers" "Do Not Use a Personal

  15. "Table HC13.5 Space Heating Usage Indicators by South Census Region, 2005"

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

    5 Space Heating Usage Indicators by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Space Heating Usage Indicators",,,"South Atlantic","East South Central","West South Central" "Total U.S. Housing Units",111.1,40.7,21.7,6.9,12.1 "Do Not Have Heating

  16. "Table HC13.7 Air-Conditioning Usage Indicators by South Census Region, 2005"

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

    7 Air-Conditioning Usage Indicators by South Census Region, 2005" " Million U.S. Housing Units" ,,"South Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total South" "Air Conditioning Usage Indicators",,,"South Atlantic","East South Central","West South Central" "Total",111.1,40.7,21.7,6.9,12.1 "Do Not Have Cooling Equipment",17.8,1.4,0.8,0.2,0.3 "Have

  17. "Table HC14.10 Home Appliances Usage Indicators by West Census Region, 2005"

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

    0 Home Appliances Usage Indicators by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Home Appliances Usage Indicators",,,"Mountain","Pacific" "Total",111.1,24.2,7.6,16.6 "Cooking Appliances" "Frequency of Hot Meals Cooked" "3 or More Times A Day",8.2,2.6,0.7,1.9 "2

  18. "Table HC14.12 Home Electronics Usage Indicators by West Census Region, 2005"

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

    2 Home Electronics Usage Indicators by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Home Electronics Usage Indicators",,,"Mountain","Pacific" "Total",111.1,24.2,7.6,16.6 "Personal Computers" "Do Not Use a Personal Computer",35.5,6.4,2.2,4.2 "Use a Personal

  19. "Table HC14.5 Space Heating Usage Indicators by West Census Region, 2005"

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

    5 Space Heating Usage Indicators by West Census Region, 2005" " Million U.S. Housing Units" ,,"West Census Region" ,"U.S. Housing Units (millions)" ,,,"Census Division" ,,"Total West" "Space Heating Usage Indicators",,,"Mountain","Pacific" "Total U.S. Housing Units",111.1,24.2,7.6,16.6 "Do Not Have Heating Equipment",1.2,0.7,"Q",0.7 "Have Space Heating

  20. "Table HC15.10 Home Appliances Usage Indicators by Four Most Populated States, 2005"

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

    0 Home Appliances Usage Indicators by Four Most Populated States, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","Four Most Populated States" "Home Appliances Usage Indicators",,"New York","Florida","Texas","California" "Total",111.1,7.1,7,8,12.1 "Cooking Appliances" "Frequency of Hot Meals Cooked" "3 or More Times A Day",8.2,0.6,0.5,0.8,1.4 "2 Times

  1. "Table HC15.12 Home Electronics Usage Indicators by Four Most Populated States, 2005"

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

    2 Home Electronics Usage Indicators by Four Most Populated States, 2005" " Million U.S. Housing Units" ,"U.S. Housing Units (millions)","Four Most Populated States" "Home Electronics Usage Indicators",,"New York","Florida","Texas","California" "Total",111.1,7.1,7,8,12.1 "Personal Computers" "Do Not Use a Personal Computer",35.5,3,2,2.7,3.1 "Use a Personal

  2. "Table HC15.13 Lighting Usage Indicators by Four Most Populated States, 2005"

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

    3 Lighting Usage Indicators by Four Most Populated States, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","Four Most Populated States" "Lighting Usage Indicators",,"New York","Florida","Texas","California" "Total U.S. Housing Units",111.1,7.1,7,8,12.1 "Indoor Lights Turned On During Summer" "Number of Lights Turned On" "Between 1 and 4 Hours per

  3. "Table HC15.5 Space Heating Usage Indicators by Four Most Populated States, 2005"

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

    5 Space Heating Usage Indicators by Four Most Populated States, 2005" " Million U.S. Housing Units" ,"U.S. Housing Units (millions)","Four Most Populated States" "Space Heating Usage Indicators",,"New York","Florida","Texas","California" "Total U.S. Housing Units",111.1,7.1,7,8,12.1 "Do Not Have Heating Equipment",1.2,"Q","Q","Q",0.2 "Have Space Heating

  4. "Table HC15.7 Air-Conditioning Usage Indicators by Four Most Populated States, 2005"

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

    7 Air-Conditioning Usage Indicators by Four Most Populated States, 2005" " Million U.S. Housing Units" ,"Housing Units (millions)","Four Most Populated States" "Air Conditioning Usage Indicators",,"New York","Florida","Texas","California" "Total",111.1,7.1,7,8,12.1 "Do Not Have Cooling Equipment",17.8,1.8,"Q","Q",4.9 "Have Cooling Equipment",93.3,5.3,7,7.8,7.2

  5. "Table HC3.10 Home Appliances Usage Indicators by Owner-Occupied Housing Unit, 2005"

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

    0 Home Appliances Usage Indicators by Owner-Occupied Housing Unit, 2005" " Million U.S. Housing Units" ,," Owner-Occupied Housing Units (millions)","Type of Owner-Occupied Housing Unit" ,"U.S. Housing Units (millions)" ,,,"Single-Family Units",,"Apartments in Buildings With--" "Home Appliances Usage Indicators",,,"Detached","Attached","2 to 4 Units","5 or More Units","Mobile

  6. "Table HC3.12 Home Electronics Usage Indicators by Owner-Occupied Housing Unit, 2005"

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

    2 Home Electronics Usage Indicators by Owner-Occupied Housing Unit, 2005" " Million U.S. Housing Units" ,," Owner-Occupied Housing Units (millions)","Type of Owner-Occupied Housing Unit" ,"U.S. Housing Units (millions)" ,,,"Single-Family Units",,"Apartments in Buildings With--" "Home Electronics Usage Indicators",,,"Detached","Attached","2 to 4 Units","5 or More Units","Mobile

  7. "Table HC3.13 Lighting Usage Indicators by Owner-Occupied Housing Unit Zone, 2005"

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

    3 Lighting Usage Indicators by Owner-Occupied Housing Unit Zone, 2005" " Million U.S. Housing Units" ,," Owner-Occupied Housing Units (millions)","Type of Owner-Occupied Housing Unit" ,"U.S. Housing Units (millions" ,,,"Single-Family Units",,"Apartments in Buildings With--" "Lighting Usage Indicators",,,"Detached","Attached","2 to 4 Units","5 or More Units","Mobile Homes"

  8. "Table HC3.5 Space Heating Usage Indicators by Owner-Occupied Housing Unit, 2005"

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

    5 Space Heating Usage Indicators by Owner-Occupied Housing Unit, 2005" " Million U.S. Housing Units" ,," Owner-Occupied Housing Units (millions)","Type of Owner-Occupied Housing Unit" ," Housing Units (millions)" ,,,"Single-Family Units",,"Apartments in Buildings With--" "Space Heating Usage Indicators",,,"Detached","Attached","2 to 4 Units","5 or More Units","Mobile

  9. "Table HC4.10 Home Appliances Usage Indicators by Renter-Occupied Housing Unit, 2005"

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

    0 Home Appliances Usage Indicators by Renter-Occupied Housing Unit, 2005" " Million U.S. Housing Units" ,," Renter-Occupied Housing Units (millions)","Type of Renter-Occupied Housing Unit" ," Housing Units (millions)" ,,,"Single-Family Units",,"Apartments in Buildings With--" "Home Appliances Usage Indicators",,,"Detached","Attached","2 to 4 Units","5 or More Units","Mobile

  10. "Table HC4.12 Home Electronics Usage Indicators by Renter-Occupied Housing Unit, 2005"

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

    2 Home Electronics Usage Indicators by Renter-Occupied Housing Unit, 2005" " Million U.S. Housing Units" ,," Renter-Occupied Housing Units (millions)","Type of Renter-Occupied Housing Unit" ,"U.S. Housing Units (millions)" ,,,"Single-Family Units",,"Apartments in Buildings With--" "Home Electronics Usage Indicators",,,"Detached","Attached","2 to 4 Units","5 or More

  11. "Table HC4.13 Lighting Usage Indicators by Renter-Occupied Housing Unit Zone, 2005"

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

    3 Lighting Usage Indicators by Renter-Occupied Housing Unit Zone, 2005" " Million U.S. Housing Units" ,," Renter-Occupied Housing Units (millions)","Type of Renter-Occupied Housing Unit" ,"U.S. Housing Units (millions" ,,,"Single-Family Units",,"Apartments in Buildings With--" "Lighting Usage Indicators",,,"Detached","Attached","2 to 4 Units","5 or More Units","Mobile

  12. "Table HC4.5 Space Heating Usage Indicators by Renter-Occupied Housing Unit, 2005"

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

    5 Space Heating Usage Indicators by Renter-Occupied Housing Unit, 2005" " Million U.S. Housing Units" ,," Renter-Occupied Housing Units (millions)","Type of Renter-Occupied Housing Unit" ," Housing Units (millions)" ,,,"Single-Family Units",,"Apartments in Buildings With--" "Space Heating Usage Indicators",,,"Detached","Attached","2 to 4 Units","5 or More Units","Mobile

  13. "Table HC4.7 Air-Conditioning Usage Indicators by Renter-Occupied Housing Unit, 2005"

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

    7 Air-Conditioning Usage Indicators by Renter-Occupied Housing Unit, 2005" " Million U.S. Housing Units" ,," Renter-Occupied Housing Units (millions)","Type of Renter-Occupied Housing Unit" ," Housing Units (millions)" ,,,"Single-Family Units",,"Apartments in Buildings With--" "Air Conditioning Usage Indicators",,,"Detached","Attached","2 to 4 Units","5 or More Units","Mobile

  14. "Table HC8.10 Home Appliances Usage Indicators by Urban/Rural Location, 2005"

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

    0 Home Appliances Usage Indicators by Urban/Rural Location, 2005" " Million U.S. Housing Units" ,,"Urban/Rural Location (as Self-Reported)" ,"Housing Units (millions)" "Home Appliances Usage Indicators",,"City","Town","Suburbs","Rural" "Total",111.1,47.1,19,22.7,22.3 "Cooking Appliances" "Frequency of Hot Meals Cooked" "3 or More Times A Day",8.2,3.7,1.6,1.4,1.5 "2

  15. "Table HC8.12 Home Electronics Usage Indicators by Urban/Rural Location, 2005"

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

    2 Home Electronics Usage Indicators by Urban/Rural Location, 2005" " Million U.S. Housing Units" ,,"Urban/Rural Location (as Self-Reported)" ,"Housing Units (millions)" "Home Electronics Usage Indicators",,"City","Town","Suburbs","Rural" "Total",111.1,47.1,19,22.7,22.3 "Personal Computers" "Do Not Use a Personal Computer",35.5,16.9,6.5,4.6,7.6 "Use a Personal

  16. "Table HC8.5 Space Heating Usage Indicators by Urban/Rural Location, 2005"

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

    5 Space Heating Usage Indicators by Urban/Rural Location, 2005" " Million U.S. Housing Units" ,,"Urban/Rural Location (as Self-Reported)" ,"Housing Units (millions)" "Space Heating Usage Indicators",,"City","Town","Suburbs","Rural" "Total U.S. Housing Units",111.1,47.1,19,22.7,22.3 "Do Not Have Heating Equipment",1.2,0.7,"Q",0.2,"Q" "Have Space Heating

  17. Electric Resistance Heating Basics | Department of Energy

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

    Electric Resistance Heating Basics Electric Resistance Heating Basics August 16, 2013 - 3:10pm Addthis Electric resistance heat can be supplied by centralized forced-air electric furnaces or by heaters in each room. Electric resistance heating converts nearly all of the energy in the electricity to heat. Types of Electric Resistance Heaters Electric resistance heat can be provided by electric baseboard heaters, electric wall heaters, electric radiant heat, electric space heaters, electric

  18. Average U.S. household to spend $710 less on gasoline during 2015

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

    power producers using more natural gas in 2015 U.S. electric power producers are increasing their use of natural gas and burning less coal for generating electricity. In its new forecast, the U.S. Energy Information Administration said natural gas-fired generation is expected to produce 30% of U.S. electricity this year. That's up from 27% during 2014. More competitively-priced natural gas is expected to cut coal's share of electricity generation from about 39% last year to just under 36% this

  19. Survey of Recipients of WAP Services Assessment of Household Budget and Energy Behaviors Pre to Post Weatherization DOE

    SciTech Connect (OSTI)

    Tonn, Bruce Edward; Rose, Erin M.; Hawkins, Beth A.

    2015-10-01

    This report presents results from the national survey of weatherization recipients. This research was one component of the retrospective and Recovery Act evaluations of the U.S. Department of Energy s Weatherization Assistance Program. Survey respondents were randomly selected from a nationally representative sample of weatherization recipients. The respondents and a comparison group were surveyed just prior to receiving their energy audits and then again approximately 18 months post-weatherization. This report focuses on budget issues faced by WAP households pre- and post-weatherization, whether household energy behaviors changed from pre- to post, the effectiveness of approaches to client energy education, and use and knowledge about thermostats.

  20. EIA - State Electricity Profiles

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

    Arkansas Electricity Profile 2014 Table 1. 2014 Summary statistics (Arkansas) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 14,754 30 Electric utilities 11,526 23 IPP & CHP 3,227 29 Net generation (megawatthours) 61,592,137 24 Electric utilities 48,752,895 18 IPP & CHP 12,839,241 28 Emissions Sulfur dioxide (short tons) 89,528 15 Nitrogen oxide (short tons) 47,048 20 Carbon dioxide (thousand metric tons) 37,289 23 Sulfur dioxide (lbs/MWh) 2.9 9 Nitrogen oxide

  1. EIA - State Electricity Profiles

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

    Washington Electricity Profile 2014 Table 1. 2014 Summary statistics (Washington) Item Value Rank Primary energy source Hydroelectric Net summer capacity (megawatts) 30,949 10 Electric utilities 27,376 5 IPP & CHP 3,573 26 Net generation (megawatthours) 116,334,363 11 Electric utilities 102,294,256 5 IPP & CHP 14,040,107 24 Emissions Sulfur Dioxide (short tons) 13,716 36 Nitrogen Oxide (short tons) 18,316 40 Carbon Dioxide (thousand metric tons) 12,427 398 Sulfur Dioxide (lbs/MWh) 0.2 44

  2. EIA - State Electricity Profiles

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

    West Virginia Electricity Profile 2014 Table 1. 2014 Summary statistics (West Virginia) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 16,276 25 Electric utilities 11,981 21 IPP & CHP 4,295 21 Net generation (megawatthours) 81,059,577 19 Electric utilities 63,331,833 15 IPP & CHP 17,727,743 17 Emissions Sulfur Dioxide (short tons) 102,406 12 Nitrogen Oxide (short tons) 72,995 11 Carbon Dioxide (thousand metric tons) 73,606 9 Sulfur Dioxide (lbs/MWh) 2.5 14

  3. EIA - State Electricity Profiles

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

    Wisconsin Electricity Profile 2014 Table 1. 2014 Summary statistics (Wisconsin) Item Value Rank Primary Energy Source Coal Net summer capacity (megawatts) 17,166 23 Electric utilities 14,377 18 IPP & CHP 2,788 32 Net generation (megawatthours) 61,064,796 25 Electric utilities 47,301,782 20 IPP & CHP 13,763,014 26 Emissions Sulfur Dioxide (short tons) 81,239 17 Nitrogen Oxide (short tons) 39,597 27 Carbon Dioxide (thousand metric tons) 43,750 19 Sulfur Dioxide (lbs/MWh) 2.7 12 Nitrogen

  4. EIA - State Electricity Profiles

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

    Wyoming Electricity Profile 2014 Table 1. 2014 Summary statistics (Wyoming) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 8,458 37 Electric utilities 7,233 32 IPP & CHP 1,225 43 Net generation (megawatthours) 49,696,183 32 Electric utilities 45,068,982 23 IPP & CHP 4,627,201 41 Emissions Sulfur Dioxide (short tons) 45,704 24 Nitrogen Oxide (short tons) 49,638 18 Carbon Dioxide (thousand metric tons) 47,337 17 Sulfur Dioxide (lbs/MWh) 1.8 22 Nitrogen Oxide

  5. BEEST: Electric Vehicle Batteries

    SciTech Connect (OSTI)

    2010-07-01

    BEEST Project: The U.S. spends nearly a $1 billion per day to import petroleum, but we need dramatically better batteries for electric and plug-in hybrid vehicles (EV/PHEV) to truly compete with gasoline-powered cars. The 10 projects in ARPA-E’s BEEST Project, short for “Batteries for Electrical Energy Storage in Transportation,” could make that happen by developing a variety of rechargeable battery technologies that would enable EV/PHEVs to meet or beat the price and performance of gasoline-powered cars, and enable mass production of electric vehicles that people will be excited to drive.

  6. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Arizona Electricity Profile 2014 Table 1. 2014 Summary statistics (Arizona) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 28,249 13 Electric utilities 21,311 11 IPP & CHP 6,938 17 Net generation (megawatthours) 112,257,187 13 Electric utilities 94,847,135 8 IPP & CHP 17,410,053 19 Emissions Sulfur dioxide (short tons) 22,597 32 Nitrogen oxide (short tons) 56,726 17 Carbon dioxide (thousand metric tons) 53,684 16 Sulfur dioxide (lbs/MWh) 0.4 41 Nitrogen oxide

  7. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    California Electricity Profile 2014 Table 1. 2014 Summary statistics (California) Item Value Rank Primary energy source Natural gas Net summer capacity (megawatts) 74,646 2 Electric utilities 28,201 4 IPP & CHP 46,446 2 Net generation (megawatthours) 198,807,622 5 Electric utilities 71,037,135 14 IPP & CHP 127,770,487 4 Emissions Sulfur dioxide (short tons) 3,102 46 Nitrogen oxide (short tons) 98,348 5 Carbon dioxide (thousand metric tons) 57,223 14 Sulfur dioxide (lbs/MWh) 0.0 49

  8. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Colorado Electricity Profile 2014 Table 1. 2014 Summary statistics (Colorado) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 14,933 29 Electric utilities 10,204 28 IPP & CHP 4,729 18 Net generation (megawatthours) 53,847,386 30 Electric utilities 43,239,615 26 IPP & CHP 10,607,771 30 Emissions Sulfur dioxide (short tons) 28,453 30 Nitrogen oxide (short tons) 44,349 24 Carbon dioxide (thousand metric tons) 38,474 22 Sulfur dioxide (lbs/MWh) 1.1 32 Nitrogen

  9. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Connecticut Electricity Profile 2014 Table 1. 2014 Summary statistics (Connecticut) Item Value Rank Primary energy source Nuclear Net summer capacity (megawatts) 8,832 35 Electric utilities 161 45 IPP & CHP 8,671 12 Net generation (megawatthours) 33,676,980 38 Electric utilities 54,693 45 IPP & CHP 33,622,288 11 Emissions Sulfur dioxide (short tons) 1,897 47 Nitrogen oxide (short tons) 8,910 45 Carbon dioxide (thousand metric tons) 7,959 41 Sulfur dioxide (lbs/MWh) 0.1 46 Nitrogen oxide

  10. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Delaware Electricity Profile 2014 Table 1. 2014 Summary statistics (Delaware) Item Value U.S. rank Primary energy source Natural gas Net summer capacity (megawatts) 3,086 46 Electric utilities 102 46 IPP & CHP 2,984 31 Net generation (megawatthours) 7,703,584 47 Electric utilities 49,050 46 IPP & CHP 7,654,534 35 Emissions Sulfur dioxide (short tons) 824 48 Nitrogen oxide (short tons) 2,836 48 Carbon dioxide (thousand metric tons) 4,276 43 Sulfur dioxide (lbs/MWh) 0.2 45 Nitrogen oxide

  11. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    District of Columbia Electricity Profile 2014 Table 1. 2014 Summary statistics (District of Columbia) Item Value Rank Primary energy source Natural gas Net summer capacity (megawatts) 9 51 Electric utilities IPP & CHP 9 51 Net generation (megawatthours) 67,612 51 Electric utilities IPP & CHP 67,612 51 Emissions Sulfur dioxide (short tons) 0 51 Nitrogen oxide (short tons) 147 51 Carbon dioxide (thousand metric tons) 48 50 Sulfur dioxide (lbs/MWh) 0.0 51 Nitrogen oxide (lbs/MWh) 4.3 3

  12. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Florida Electricity Profile 2014 Table 1. 2014 Summary statistics (Florida) Item Value Rank Primary energy source Natural gas Net summer capacity (megawatts) 59,440 3 Electric utilities 51,775 1 IPP & CHP 7,665 15 Net generation (megawatthours) 230,015,937 2 Electric utilities 211,970,587 1 IPP & CHP 18,045,350 15 Emissions Sulfur dioxide (short tons) 126,600 10 Nitrogen oxide (short tons) 91,356 6 Carbon dioxide (thousand metric tons) 111,549 2 Sulfur dioxide (lbs/MWh) 1.1 30 Nitrogen

  13. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Georgia Electricity Profile 2014 Table 1. 2014 Summary statistics (Georgia) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 38,250 7 Electric utilities 28,873 3 IPP & CHP 9,377 10 Net generation (megawatthours) 125,837,224 10 Electric utilities 109,523,336 4 IPP & CHP 16,313,888 20 Emissions Sulfur dioxide (short tons) 105,998 11 Nitrogen oxide (short tons) 58,144 14 Carbon dioxide (thousand metric tons) 62,516 12 Sulfur dioxide (lbs/MWh) 1.7 24 Nitrogen oxide

  14. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Hawaii Electricity Profile 2014 Table 1. 2014 Summary statistics (Hawaii) Item Value Rank Primary energy source Petroleum Net summer capacity (megawatts) 2,672 47 Electric utilities 1,732 40 IPP & CHP 939 45 Net generation (megawatthours) 10,204,158 46 Electric utilities 5,517,389 39 IPP & CHP 4,686,769 40 Emissions Sulfur dioxide (short tons) 21,670 33 Nitrogen oxide (short tons) 26,928 31 Carbon dioxide (thousand metric tons) 7,313 42 Sulfur dioxide (lbs/MWh) 4.2 4 Nitrogen oxide

  15. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Illinois Electricity Profile 2014 Table 1. 2014 Summary statistics (Illinois) Item Value Rank Primary energy source Nuclear Net summer capacity (megawatts) 44,727 4 Electric utilities 5,263 35 IPP & CHP 39,464 4 Net generation (megawatthours) 202,143,878 4 Electric utilities 10,457,398 36 IPP & CHP 191,686,480 3 Emissions Sulfur dioxide (short tons) 187,536 6 Nitrogen oxide (short tons) 58,076 15 Carbon dioxide (thousand metric tons) 96,624 6 Sulfur dioxide (lbs/MWh) 1.9 20 Nitrogen

  16. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Indiana Electricity Profile 2014 Table 1. 2014 Summary statistics (Indiana) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 27,499 14 Electric utilities 23,319 7 IPP & CHP 4,180 23 Net generation (megawatthours) 115,395,392 12 Electric utilities 100,983,285 6 IPP & CHP 14,412,107 22 Emissions Sulfur dioxide (short tons) 332,396 3 Nitrogen oxide (short tons) 133,412 3 Carbon dioxide (thousand metric tons) 103,391 3 Sulfur dioxide (lbs/MWh) 5.8 1 Nitrogen oxide

  17. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Iowa Electricity Profile 2014 Table 1. 2014 Summary statistics (Iowa) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 16,507 24 Electric utilities 12,655 20 IPP & CHP 3,852 25 Net generation (megawatthours) 56,853,282 28 Electric utilities 43,021,954 27 IPP & CHP 13,831,328 25 Emissions Sulfur dioxide (short tons) 74,422 19 Nitrogen oxide (short tons) 41,793 25 Carbon dioxide (thousand metric tons) 39,312 21 Sulfur dioxide (lbs/MWh) 2.6 13 Nitrogen oxide

  18. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Kansas Electricity Profile 2014 Table 1. 2014 Summary statistics (Kansas) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 14,227 31 Electric utilities 11,468 24 IPP & CHP 2,759 33 Net generation (megawatthours) 49,728,363 31 Electric utilities 39,669,629 29 IPP & CHP 10,058,734 31 Emissions Sulfur dioxide (short tons) 31,550 29 Nitrogen oxide (short tons) 29,014 29 Carbon dioxide (thousand metric tons) 31,794 29 Sulfur dioxide (lbs/MWh) 1.3 29 Nitrogen oxide

  19. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Kentucky Electricity Profile 2014 Table 1. 2014 Summary statistics (Kentucky) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 20,878 21 Electric utilities 19,473 15 IPP & CHP 1,405 40 Net generation (megawatthours) 90,896,435 17 Electric utilities 90,133,403 10 IPP & CHP 763,032 49 Emissions Sulfur dioxide (short tons) 204,873 5 Nitrogen oxide (short tons) 89,253 7 Carbon dioxide (thousand metric tons) 85,795 7 Sulfur dioxide (lbs/MWh) 4.5 3 Nitrogen oxide

  20. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Louisiana Electricity Profile 2014 Table 1. 2014 Summary statistics (Louisiana) Item Value Rank Primary energy source Natural gas Net summer capacity (megawatts) 26,657 15 Electric utilities 18,120 16 IPP & CHP 8,537 13 Net generation (megawatthours) 104,229,402 15 Electric utilities 58,518,271 17 IPP & CHP 45,711,131 8 Emissions Sulfur dioxide (short tons) 96,240 14 Nitrogen oxide (short tons) 83,112 8 Carbon dioxide (thousand metric tons) 57,137 15 Sulfur dioxide (lbs/MWh) 1.8 21

  1. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Maine Electricity Profile 2014 Table 1. 2014 Summary statistics (Maine) Item Value Rank Primary energy source Natural gas Net summer capacity (megawatts) 4,470 43 Electric utilities 10 49 IPP & CHP 4,460 20 Net generation (megawatthours) 13,248,710 44 Electric utilities 523 49 IPP & CHP 13,248,187 27 Emissions Sulfur dioxide (short tons) 10,990 38 Nitrogen oxide (short tons) 8,622 46 Carbon dioxide (thousand metric tons) 3,298 46 Sulfur dioxide (lbs/MWh) 1.7 25 Nitrogen oxide (lbs/MWh)

  2. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Maryland Electricity Profile 2014 Table 1. 2014 Summary statistics (Maryland) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 12,264 33 Electric utilities 85 47 IPP & CHP 12,179 8 Net generation (megawatthours) 37,833,652 35 Electric utilities 20,260 47 IPP & CHP 37,813,392 9 Emissions Sulfur dioxide (short tons) 41,370 26 Nitrogen oxide (short tons) 20,626 35 Carbon dioxide (thousand metric tons) 20,414 34 Sulfur dioxide (lbs/MWh) 2.2 18 Nitrogen oxide

  3. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Massachusetts Electricity Profile 2014 Table 1. 2014 Summary statistics (Massachusetts) Item Value Rank Primary energy source Natural gas Net summer capacity (megawatts) 13,128 32 Electric utilities 971 42 IPP & CHP 12,157 9 Net generation (megawatthours) 31,118,591 40 Electric utilities 679,986 43 IPP & CHP 30,438,606 12 Emissions Sulfur dioxide (short tons) 6,748 41 Nitrogen oxide (short tons) 13,831 43 Carbon dioxide (thousand metric tons) 12,231 39 Sulfur dioxide (lbs/MWh) 0.4 40

  4. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Michigan Electricity Profile 2014 Table 1. 2014 Summary statistics (Michigan) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 30,435 12 Electric utilities 22,260 9 IPP & CHP 8,175 14 Net generation (megawatthours) 106,816,991 14 Electric utilities 84,075,322 12 IPP & CHP 22,741,669 13 Emissions Sulfur dioxide (short tons) 173,521 7 Nitrogen oxide (short tons) 77,950 9 Carbon dioxide (thousand metric tons) 64,062 11 Sulfur dioxide (lbs/MWh) 3.2 7 Nitrogen oxide

  5. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Minnesota Electricity Profile 2014 Table 1. 2014 Summary statistics (Minnesota) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 15,621 28 Electric utilities 11,557 22 IPP & CHP 4,064 24 Net generation (megawatthours) 56,998,330 27 Electric utilities 45,963,271 22 IPP & CHP 11,035,059 29 Emissions Sulfur dioxide (short tons) 39,272 27 Nitrogen oxide (short tons) 38,373 28 Carbon dioxide (thousand metric tons) 32,399 28 Sulfur dioxide (lbs/MWh) 1.4 27 Nitrogen

  6. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Mississippi Electricity Profile 2014 Table 1. 2014 Summary statistics (Mississippi) Item Value Rank Primary energy source Natural gas Net summer capacity (megawatts) 16,090 26 Electric utilities 13,494 19 IPP & CHP 2,597 34 Net generation (megawatthours) 55,127,092 29 Electric utilities 47,084,382 21 IPP & CHP 8,042,710 34 Emissions Sulfur dioxide (short tons) 101,093 13 Nitrogen oxide (short tons) 23,993 32 Carbon dioxide (thousand metric tons) 24,037 33 Sulfur dioxide (lbs/MWh) 3.7 5

  7. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Missouri Electricity Profile 2014 Table 1. 2014 Summary statistics (Missouri) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 21,790 19 Electric utilities 20,538 13 IPP & CHP 1,252 42 Net generation (megawatthours) 87,834,468 18 Electric utilities 85,271,253 11 IPP & CHP 2,563,215 46 Emissions Sulfur dioxide (short tons) 149,842 9 Nitrogen oxide (short tons) 77,749 10 Carbon dioxide (thousand metric tons) 75,735 8 Sulfur dioxide (lbs/MWh) 3.4 6 Nitrogen oxide

  8. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Montana Electricity Profile 2014 Table 1. 2014 Summary statistics (Montana) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 6,330 41 Electric utilities 3,209 38 IPP & CHP 3,121 30 Net generation (megawatthours) 30,257,616 41 Electric utilities 12,329,411 35 IPP & CHP 17,928,205 16 Emissions Sulfur dioxide (short tons) 14,426 34 Nitrogen oxide (short tons) 20,538 36 Carbon dioxide (thousand metric tons) 17,678 36 Sulfur dioxide (lbs/MWh) 1.0 34 Nitrogen oxide

  9. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Nebraska Electricity Profile 2014 Table 1. 2014 Summary statistics (Nebraska) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 8,732 36 Electric utilities 7,913 30 IPP & CHP 819 46 Net generation (megawatthours) 39,431,291 34 Electric utilities 36,560,960 30 IPP & CHP 2,870,331 45 Emissions Sulfur dioxide (short tons) 63,994 22 Nitrogen oxide (short tons) 27,045 30 Carbon dioxide (thousand metric tons) 26,348 31 Sulfur dioxide (lbs/MWh) 3.2 8 Nitrogen oxide

  10. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Nevada Electricity Profile 2014 Table 1. 2014 Summary statistics (Nevada) Item Value Rank Primary energy source Natural gas Net summer capacity (megawatts) 10,485 34 Electric utilities 8,480 29 IPP & CHP 2,006 35 Net generation (megawatthours) 36,000,537 37 Electric utilities 27,758,728 33 IPP & CHP 8,241,809 33 Emissions Sulfur dioxide (short tons) 10,229 40 Nitrogen oxide (short tons) 18,606 39 Carbon dioxide (thousand metric tons) 16,222 37 Sulfur dioxide (lbs/MWh) 0.4 38 Nitrogen

  11. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Hampshire Electricity Profile 2013 Table 1. 2013 Summary statistics (New Hampshire) Item Value Rank Primary energy source Nuclear Net summer capacity (megawatts) 4,413 44 Electric utilities 1,121 41 IPP & CHP 3,292 30 Net generation (megawatthours) 19,778,520 42 Electric utilities 2,266,903 41 IPP & CHP 17,511,617 20 Emissions Sulfur dioxide (short tons) 3,733 44 Nitrogen oxide (short tons) 5,057 47 Carbon dioxide (thousand metric tons) 3,447 46 Sulfur dioxide (lbs/MWh) 0.4 45 Nitrogen

  12. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Jersey Electricity Profile 2014 Table 1. 2014 Summary statistics (New Jersey) Item Value Rank Primary energy source Nuclear Net summer capacity (megawatts) 19,399 22 Electric utilities 544 43 IPP & CHP 18,852 7 Net generation (megawatthours) 68,051,086 23 Electric utilities -117,003 50 IPP & CHP 68,168,089 7 Emissions Sulfur dioxide (short tons) 3,369 44 Nitrogen oxide (short tons) 15,615 41 Carbon dioxide (thousand metric tons) 17,905 35 Sulfur dioxide (lbs/MWh) 0.1 47 Nitrogen oxide

  13. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Mexico Electricity Profile 2014 Table 1. 2014 Summary statistics (New Mexico) Item Value U.S. Rank Primary energy source Coal Net summer capacity (megawatts) 8,072 39 Electric utilities 6,094 33 IPP & CHP 1,978 37 Net generation (megawatthours) 32,306,210 39 Electric utilities 26,422,867 34 IPP & CHP 5,883,343 38 Emissions Sulfur dioxide (short tons) 12,064 37 Nitrogen oxide (short tons) 46,192 22 Carbon dioxide (thousand metric tons) 24,712 32 Sulfur dioxide (lbs/MWh) 0.7 37 Nitrogen

  14. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    York Electricity Profile 2014 Table 1. 2014 Summary statistics (New York) Item Value Rank Primary energy source Natural Gas Net summer capacity (megawatts) 40,404 6 Electric utilities 10,989 27 IPP & CHP 29,416 5 Net generation (megawatthours) 137,122,202 7 Electric utilities 34,082 31 IPP & CHP 103,039,347 5 Emissions Sulfur dioxide (short tons) 31,878 28 Nitrogen oxide (short tons) 46,971 21 Carbon dioxide (thousand metric tons) 33,240 26 Sulfur dioxide (lbs/MWh) 0.5 39 Nitrogen oxide

  15. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Carolina Electricity Profile 2013 Table 1. 2013 Summary statistics (North Carolina) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 30,048 12 Electric utilities 26,706 6 IPP & CHP 3,342 29 Net generation (megawatthours) 125,936,293 9 Electric utilities 116,317,050 2 IPP & CHP 9,619,243 31 Emissions Sulfur dioxide (short tons) 71,293 20 Nitrogen oxide (short tons) 62,397 12 Carbon dioxide (thousand metric tons) 56,940 14 Sulfur dioxide (lbs/MWh) 1.1 32 Nitrogen

  16. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Dakota Electricity Profile 2013 Table 1. 2013 Summary statistics (North Dakota) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 6,566 40 Electric utilities 5,292 34 IPP & CHP 1,274 41 Net generation (megawatthours) 35,021,673 39 Electric utilities 31,044,374 32 IPP & CHP 3,977,299 42 Emissions Sulfur dioxide (short tons) 56,854 23 Nitrogen oxide (short tons) 48,454 22 Carbon dioxide (thousand metric tons) 30,274 28 Sulfur dioxide (lbs/MWh) 3.2 11 Nitrogen oxide

  17. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Ohio Electricity Profile 2014 Table 1. 2014 Summary statistics (Ohio) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 31,507 9 Electric utilities 11,134 26 IPP & CHP 20,372 6 Net generation (megawatthours) 134,476,405 8 Electric utilities 43,290,512 25 IPP & CHP 91,185,893 7 Emissions Sulfur dioxide (short tons) 355,108 1 Nitrogen oxide (short tons) 105,688 4 Carbon dioxide (thousand metrictons) 98,650 5 Sulfur dioxide (lbs/MWh) 5.3 2 Nitrogen oxide (lbs/MWh)

  18. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Oklahoma Electricity Profile 2014 Table 1. 2014 Summary statistics (Oklahoma) Item Value Rank Primary energy source Natural gas Net summer capacity (megawatts) 24,048 17 Electric utilities 17,045 17 IPP & CHP 7,003 16 Net generation (megawatthours) 70,155,504 22 Electric utilities 48,096,026 19 IPP & CHP 22,059,478 14 Emissions Sulfur dioxide 78,556 18 Nitrogen oxide 44,874 23 Carbon dioxide (thousand metric tons) 43,994 18 Sulfur dioxide (lbs/MWh) 2.2 17 Nitrogen oxide (lbs/MWh) 1.3 26

  19. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Pennsylvania Electricity Profile 2014 Table 1. 2014 Summary statistics (Pennsylvania) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 42,723 5 Electric utilities 39 48 IPP & CHP 42,685 3 Net generation (megawatthours) 221,058,365 3 Electric utilities 90,994 44 IPP & CHP 220,967,371 2 Emissions Sulfur dioxide (short tons) 297,598 4 Nitrogen oxide (short tons) 141,486 2 Carbon dioxide (thousand metric tons) 101,361 4 Sulfur dioxide (lbs/MWh) 2.7 11 Nitrogen oxide

  20. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Rhode Island Electricity Profile 2014 Table 1. 2014 Summary statistics (Rhode Island) Item Value Rank Primary energy source Natural gas Net summer capacity (megawatts) 1,810 49 Electric utilities 8 50 IPP & CHP 1,803 38 Net generation (megawatthours) 6,281,748 49 Electric utilities 10,670 48 IPP & CHP 6,271,078 36 Emissions Sulfur dioxide (short tons) 100 49 Nitrogen oxide (short tons) 1,224 49 Carbon dioxide (thousand metric tons) 2,566 48 Sulfur dioxide (lbs/MWh) 0.0 48 Nitrogen oxide

  1. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Carolina Electricity Profile 2014 Table 1. 2014 Summary statistics (South Carolina) Item Value Rank Primary energy source Nuclear Net summer capacity (megawatts) 22,824 18 Electric utilities 20,836 12 IPP & CHP 1,988 36 Net generation (megawatthours) 97,158,465 16 Electric utilities 93,547,004 9 IPP & CHP 3,611,461 43 Emissions Sulfur dioxide (short tons) 43,659 25 Nitrogen oxide (short tons) 21,592 34 Carbon dioxide (thousand metric tons) 33,083 27 Sulfur dioxide (lbs/MWh) 0.9 35

  2. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Tennessee Electricity Profile 2014 Table 1. 2014 Summary statistics (Tennessee) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 20,998 20 Electric utilities 20,490 14 IPP & CHP 508 47 Net generation (megawatthours) 79,506,886 20 Electric utilities 76,986,629 13 IPP & CHP 2,520,257 47 Emissions Sulfur dioxide (short tons) 89,357 16 Nitrogen oxide (short tons) 23,913 33 Carbon dioxide (thousand metric tons) 41,405 20 Sulfur dioxide (lbs/MWh) 2.2 16 Nitrogen oxide

  3. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Texas Electricity Profile 2014 Table 1. 2014 Summary statistics (Texas) Item Value Rank Primary energy source Natural gas Net summer capacity (megawatts) 112,914 1 Electric utilities 29,113 2 IPP & CHP 83,800 1 Net generation (megawatthours) 437,629,668 1 Electric utilities 94,974,953 7 IPP & CHP 342,654,715 1 Emissions Sulfur Dioxide (short tons) 349,245 2 Nitrogen Oxide short tons) 229,580 1 Carbon Dioxide (thousand metric tons) 254,488 1 Sulfur Dioxide (lbs/MWh) 1.6 26 Nitrogen Oxide

  4. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    United States Electricity Profile 2014 Table 1. 2014 Summary statistics (United States) Item Value Primary energy source Coal Net summer capacity (megawatts) 1,068,422 Electric utilities 616,632 IPP & CHP 451,791 Net generation (megawatthours) 4,093,606,005 Electric utilities 2,382,473,495 IPP & CHP 1,711,132,510 Emissions Sulfur Dioxide (short tons) 3,842,005 Nitrogen Oxide (short tons) 2,400,375 Carbon Dioxide (thousand metric tons) 2,160,342 Sulfur Dioxide (lbs/MWh) 1.9 Nitrogen Oxide

  5. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Vermont Electricity Profile 2014 Table 1. 2014 Summary statistics (Vermont) Item Value Rank Primary energy source Nuclear Net summer capacity (megawatts) 650 50 Electric utilities 337 44 IPP & CHP 313 49 Net generation (megawatthours) 7,031,394 48 Electric utilities 868,079 42 IPP & CHP 6,163,315 37 Emissions Sulfur Dioxide (short tons) 71 50 Nitrogen Oxide (short tons) 737 50 Carbon Dioxide (thousand metric tons) 14 51 Sulfur Dioxide (lbs/MWh) 0.0 50 Nitrogen Oxide (lbs/MWh) 0.2 51

  6. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Virginia Electricity Profile 2014 Table 1. 2014 Summary statistics (Virginia) Item Value Rank Primary energy source Nuclear Net summer capacity (megawatts) 26,292 16 Electric utilities 22,062 10 IPP & CHP 4,231 22 Net generation (megawatthours) 77,137,438 21 Electric utilities 62,966,914 16 IPP & CHP 14,170,524 23 Emissions Sulfur Dioxide (short tons) 68,550 20 Nitrogen Oxide (short tons) 40,656 26 Carbon Dioxide (thousand metric tons) 33,295 25 Sulfur Dioxide (lbs/MWh) 1.8 23 Nitrogen

  7. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    West Virginia Electricity Profile 2014 Table 1. 2014 Summary statistics (West Virginia) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 16,276 25 Electric utilities 11,981 21 IPP & CHP 4,295 21 Net generation (megawatthours) 81,059,577 19 Electric utilities 63,331,833 15 IPP & CHP 17,727,743 17 Emissions Sulfur Dioxide (short tons) 102,406 12 Nitrogen Oxide (short tons) 72,995 11 Carbon Dioxide (thousand metric tons) 73,606 9 Sulfur Dioxide (lbs/MWh) 2.5 14

  8. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Wisconsin Electricity Profile 2014 Table 1. 2014 Summary statistics (Wisconsin) Item Value Rank Primary Energy Source Coal Net summer capacity (megawatts) 17,166 23 Electric utilities 14,377 18 IPP & CHP 2,788 32 Net generation (megawatthours) 61,064,796 25 Electric utilities 47,301,782 20 IPP & CHP 13,763,014 26 Emissions Sulfur Dioxide (short tons) 81,239 17 Nitrogen Oxide (short tons) 39,597 27 Carbon Dioxide (thousand metric tons) 43,750 19 Sulfur Dioxide (lbs/MWh) 2.7 12 Nitrogen

  9. EIA - State Electricity Profiles

    Gasoline and Diesel Fuel Update (EIA)

    Wyoming Electricity Profile 2014 Table 1. 2014 Summary statistics (Wyoming) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 8,458 37 Electric utilities 7,233 32 IPP & CHP 1,225 43 Net generation (megawatthours) 49,696,183 32 Electric utilities 45,068,982 23 IPP & CHP 4,627,201 41 Emissions Sulfur Dioxide (short tons) 45,704 24 Nitrogen Oxide (short tons) 49,638 18 Carbon Dioxide (thousand metric tons) 47,337 17 Sulfur Dioxide (lbs/MWh) 1.8 22 Nitrogen Oxide

  10. EIA - State Electricity Profiles

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

    Alaska Electricity Profile 2014 Table 1. 2014 Summary statistics (Alaska) Item Value Rank Primary energy source Natural gas Net summer capacity (megawatts) 2,464 48 Electric utilities 2,313 39 IPP & CHP 151 50 Net generation (megawatthours) 6,042,830 50 Electric utilities 5,509,991 40 IPP & CHP 532,839 50 Emissions Sulfur dioxide (short tons) 4,129 43 Nitrogen oxide (short tons) 19,281 38 Carbon dioxide (thousand metric tons) 3,558 44 Sulfur dioxide (lbs/MWh) 1.4 28 Nitrogen oxide

  11. EIA - State Electricity Profiles

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

    Arizona Electricity Profile 2014 Table 1. 2014 Summary statistics (Arizona) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 28,249 13 Electric utilities 21,311 11 IPP & CHP 6,938 17 Net generation (megawatthours) 112,257,187 13 Electric utilities 94,847,135 8 IPP & CHP 17,410,053 19 Emissions Sulfur dioxide (short tons) 22,597 32 Nitrogen oxide (short tons) 56,726 17 Carbon dioxide (thousand metric tons) 53,684 16 Sulfur dioxide (lbs/MWh) 0.4 41 Nitrogen oxide

  12. EIA - State Electricity Profiles

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

    California Electricity Profile 2014 Table 1. 2014 Summary statistics (California) Item Value Rank Primary energy source Natural gas Net summer capacity (megawatts) 74,646 2 Electric utilities 28,201 4 IPP & CHP 46,446 2 Net generation (megawatthours) 198,807,622 5 Electric utilities 71,037,135 14 IPP & CHP 127,770,487 4 Emissions Sulfur dioxide (short tons) 3,102 46 Nitrogen oxide (short tons) 98,348 5 Carbon dioxide (thousand metric tons) 57,223 14 Sulfur dioxide (lbs/MWh) 0.0 49

  13. EIA - State Electricity Profiles

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

    Colorado Electricity Profile 2014 Table 1. 2014 Summary statistics (Colorado) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 14,933 29 Electric utilities 10,204 28 IPP & CHP 4,729 18 Net generation (megawatthours) 53,847,386 30 Electric utilities 43,239,615 26 IPP & CHP 10,607,771 30 Emissions Sulfur dioxide (short tons) 28,453 30 Nitrogen oxide (short tons) 44,349 24 Carbon dioxide (thousand metric tons) 38,474 22 Sulfur dioxide (lbs/MWh) 1.1 32 Nitrogen

  14. EIA - State Electricity Profiles

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

    Connecticut Electricity Profile 2014 Table 1. 2014 Summary statistics (Connecticut) Item Value Rank Primary energy source Nuclear Net summer capacity (megawatts) 8,832 35 Electric utilities 161 45 IPP & CHP 8,671 12 Net generation (megawatthours) 33,676,980 38 Electric utilities 54,693 45 IPP & CHP 33,622,288 11 Emissions Sulfur dioxide (short tons) 1,897 47 Nitrogen oxide (short tons) 8,910 45 Carbon dioxide (thousand metric tons) 7,959 41 Sulfur dioxide (lbs/MWh) 0.1 46 Nitrogen oxide

  15. EIA - State Electricity Profiles

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

    Delaware Electricity Profile 2014 Table 1. 2014 Summary statistics (Delaware) Item Value U.S. rank Primary energy source Natural gas Net summer capacity (megawatts) 3,086 46 Electric utilities 102 46 IPP & CHP 2,984 31 Net generation (megawatthours) 7,703,584 47 Electric utilities 49,050 46 IPP & CHP 7,654,534 35 Emissions Sulfur dioxide (short tons) 824 48 Nitrogen oxide (short tons) 2,836 48 Carbon dioxide (thousand metric tons) 4,276 43 Sulfur dioxide (lbs/MWh) 0.2 45 Nitrogen oxide

  16. EIA - State Electricity Profiles

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

    District of Columbia Electricity Profile 2014 Table 1. 2014 Summary statistics (District of Columbia) Item Value Rank Primary energy source Natural gas Net summer capacity (megawatts) 9 51 Electric utilities IPP & CHP 9 51 Net generation (megawatthours) 67,612 51 Electric utilities IPP & CHP 67,612 51 Emissions Sulfur dioxide (short tons) 0 51 Nitrogen oxide (short tons) 147 51 Carbon dioxide (thousand metric tons) 48 50 Sulfur dioxide (lbs/MWh) 0.0 51 Nitrogen oxide (lbs/MWh) 4.3 3

  17. EIA - State Electricity Profiles

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

    Florida Electricity Profile 2014 Table 1. 2014 Summary statistics (Florida) Item Value Rank Primary energy source Natural gas Net summer capacity (megawatts) 59,440 3 Electric utilities 51,775 1 IPP & CHP 7,665 15 Net generation (megawatthours) 230,015,937 2 Electric utilities 211,970,587 1 IPP & CHP 18,045,350 15 Emissions Sulfur dioxide (short tons) 126,600 10 Nitrogen oxide (short tons) 91,356 6 Carbon dioxide (thousand metric tons) 111,549 2 Sulfur dioxide (lbs/MWh) 1.1 30 Nitrogen

  18. EIA - State Electricity Profiles

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

    Georgia Electricity Profile 2014 Table 1. 2014 Summary statistics (Georgia) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 38,250 7 Electric utilities 28,873 3 IPP & CHP 9,377 10 Net generation (megawatthours) 125,837,224 10 Electric utilities 109,523,336 4 IPP & CHP 16,313,888 20 Emissions Sulfur dioxide (short tons) 105,998 11 Nitrogen oxide (short tons) 58,144 14 Carbon dioxide (thousand metric tons) 62,516 12 Sulfur dioxide (lbs/MWh) 1.7 24 Nitrogen oxide

  19. EIA - State Electricity Profiles

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

    Hawaii Electricity Profile 2014 Table 1. 2014 Summary statistics (Hawaii) Item Value Rank Primary energy source Petroleum Net summer capacity (megawatts) 2,672 47 Electric utilities 1,732 40 IPP & CHP 939 45 Net generation (megawatthours) 10,204,158 46 Electric utilities 5,517,389 39 IPP & CHP 4,686,769 40 Emissions Sulfur dioxide (short tons) 21,670 33 Nitrogen oxide (short tons) 26,928 31 Carbon dioxide (thousand metric tons) 7,313 42 Sulfur dioxide (lbs/MWh) 4.2 4 Nitrogen oxide

  20. EIA - State Electricity Profiles

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

    Idaho Electricity Profile 2014 Table 1. 2014 Summary statistics (Idaho) Item Value Rank Primary energy source Hydroelectric Net summer capacity (megawatts) 4,944 42 Electric utilities 3,413 37 IPP & CHP 1,531 39 Net generation (megawatthours) 15,184,417 43 Electric utilities 9,628,016 37 IPP & CHP 5,556,400 39 Emissions Sulfur dioxide (short tons) 5,777 42 Nitrogen oxide (short tons) 20,301 37 Carbon dioxide (thousand metric tons) 1,492 49 Sulfur dioxide (lbs/MWh) 0.8 36 Nitrogen oxide

  1. EIA - State Electricity Profiles

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

    Illinois Electricity Profile 2014 Table 1. 2014 Summary statistics (Illinois) Item Value Rank Primary energy source Nuclear Net summer capacity (megawatts) 44,727 4 Electric utilities 5,263 35 IPP & CHP 39,464 4 Net generation (megawatthours) 202,143,878 4 Electric utilities 10,457,398 36 IPP & CHP 191,686,480 3 Emissions Sulfur dioxide (short tons) 187,536 6 Nitrogen oxide (short tons) 58,076 15 Carbon dioxide (thousand metric tons) 96,624 6 Sulfur dioxide (lbs/MWh) 1.9 20 Nitrogen

  2. EIA - State Electricity Profiles

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

    Indiana Electricity Profile 2014 Table 1. 2014 Summary statistics (Indiana) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 27,499 14 Electric utilities 23,319 7 IPP & CHP 4,180 23 Net generation (megawatthours) 115,395,392 12 Electric utilities 100,983,285 6 IPP & CHP 14,412,107 22 Emissions Sulfur dioxide (short tons) 332,396 3 Nitrogen oxide (short tons) 133,412 3 Carbon dioxide (thousand metric tons) 103,391 3 Sulfur dioxide (lbs/MWh) 5.8 1 Nitrogen oxide

  3. EIA - State Electricity Profiles

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

    Iowa Electricity Profile 2014 Table 1. 2014 Summary statistics (Iowa) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 16,507 24 Electric utilities 12,655 20 IPP & CHP 3,852 25 Net generation (megawatthours) 56,853,282 28 Electric utilities 43,021,954 27 IPP & CHP 13,831,328 25 Emissions Sulfur dioxide (short tons) 74,422 19 Nitrogen oxide (short tons) 41,793 25 Carbon dioxide (thousand metric tons) 39,312 21 Sulfur dioxide (lbs/MWh) 2.6 13 Nitrogen oxide

  4. EIA - State Electricity Profiles

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

    Kansas Electricity Profile 2014 Table 1. 2014 Summary statistics (Kansas) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 14,227 31 Electric utilities 11,468 24 IPP & CHP 2,759 33 Net generation (megawatthours) 49,728,363 31 Electric utilities 39,669,629 29 IPP & CHP 10,058,734 31 Emissions Sulfur dioxide (short tons) 31,550 29 Nitrogen oxide (short tons) 29,014 29 Carbon dioxide (thousand metric tons) 31,794 29 Sulfur dioxide (lbs/MWh) 1.3 29 Nitrogen oxide

  5. EIA - State Electricity Profiles

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

    Kentucky Electricity Profile 2014 Table 1. 2014 Summary statistics (Kentucky) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 20,878 21 Electric utilities 19,473 15 IPP & CHP 1,405 40 Net generation (megawatthours) 90,896,435 17 Electric utilities 90,133,403 10 IPP & CHP 763,032 49 Emissions Sulfur dioxide (short tons) 204,873 5 Nitrogen oxide (short tons) 89,253 7 Carbon dioxide (thousand metric tons) 85,795 7 Sulfur dioxide (lbs/MWh) 4.5 3 Nitrogen oxide

  6. EIA - State Electricity Profiles

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

    Louisiana Electricity Profile 2014 Table 1. 2014 Summary statistics (Louisiana) Item Value Rank Primary energy source Natural gas Net summer capacity (megawatts) 26,657 15 Electric utilities 18,120 16 IPP & CHP 8,537 13 Net generation (megawatthours) 104,229,402 15 Electric utilities 58,518,271 17 IPP & CHP 45,711,131 8 Emissions Sulfur dioxide (short tons) 96,240 14 Nitrogen oxide (short tons) 83,112 8 Carbon dioxide (thousand metric tons) 57,137 15 Sulfur dioxide (lbs/MWh) 1.8 21

  7. EIA - State Electricity Profiles

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

    Maine Electricity Profile 2014 Table 1. 2014 Summary statistics (Maine) Item Value Rank Primary energy source Natural gas Net summer capacity (megawatts) 4,470 43 Electric utilities 10 49 IPP & CHP 4,460 20 Net generation (megawatthours) 13,248,710 44 Electric utilities 523 49 IPP & CHP 13,248,187 27 Emissions Sulfur dioxide (short tons) 10,990 38 Nitrogen oxide (short tons) 8,622 46 Carbon dioxide (thousand metric tons) 3,298 46 Sulfur dioxide (lbs/MWh) 1.7 25 Nitrogen oxide (lbs/MWh)

  8. EIA - State Electricity Profiles

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

    Maryland Electricity Profile 2014 Table 1. 2014 Summary statistics (Maryland) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 12,264 33 Electric utilities 85 47 IPP & CHP 12,179 8 Net generation (megawatthours) 37,833,652 35 Electric utilities 20,260 47 IPP & CHP 37,813,392 9 Emissions Sulfur dioxide (short tons) 41,370 26 Nitrogen oxide (short tons) 20,626 35 Carbon dioxide (thousand metric tons) 20,414 34 Sulfur dioxide (lbs/MWh) 2.2 18 Nitrogen oxide

  9. EIA - State Electricity Profiles

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

    Massachusetts Electricity Profile 2014 Table 1. 2014 Summary statistics (Massachusetts) Item Value Rank Primary energy source Natural gas Net summer capacity (megawatts) 13,128 32 Electric utilities 971 42 IPP & CHP 12,157 9 Net generation (megawatthours) 31,118,591 40 Electric utilities 679,986 43 IPP & CHP 30,438,606 12 Emissions Sulfur dioxide (short tons) 6,748 41 Nitrogen oxide (short tons) 13,831 43 Carbon dioxide (thousand metric tons) 12,231 39 Sulfur dioxide (lbs/MWh) 0.4 40

  10. EIA - State Electricity Profiles

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

    Michigan Electricity Profile 2014 Table 1. 2014 Summary statistics (Michigan) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 30,435 12 Electric utilities 22,260 9 IPP & CHP 8,175 14 Net generation (megawatthours) 106,816,991 14 Electric utilities 84,075,322 12 IPP & CHP 22,741,669 13 Emissions Sulfur dioxide (short tons) 173,521 7 Nitrogen oxide (short tons) 77,950 9 Carbon dioxide (thousand metric tons) 64,062 11 Sulfur dioxide (lbs/MWh) 3.2 7 Nitrogen oxide

  11. EIA - State Electricity Profiles

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

    Minnesota Electricity Profile 2014 Table 1. 2014 Summary statistics (Minnesota) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 15,621 28 Electric utilities 11,557 22 IPP & CHP 4,064 24 Net generation (megawatthours) 56,998,330 27 Electric utilities 45,963,271 22 IPP & CHP 11,035,059 29 Emissions Sulfur dioxide (short tons) 39,272 27 Nitrogen oxide (short tons) 38,373 28 Carbon dioxide (thousand metric tons) 32,399 28 Sulfur dioxide (lbs/MWh) 1.4 27 Nitrogen

  12. EIA - State Electricity Profiles

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

    Mississippi Electricity Profile 2014 Table 1. 2014 Summary statistics (Mississippi) Item Value Rank Primary energy source Natural gas Net summer capacity (megawatts) 16,090 26 Electric utilities 13,494 19 IPP & CHP 2,597 34 Net generation (megawatthours) 55,127,092 29 Electric utilities 47,084,382 21 IPP & CHP 8,042,710 34 Emissions Sulfur dioxide (short tons) 101,093 13 Nitrogen oxide (short tons) 23,993 32 Carbon dioxide (thousand metric tons) 24,037 33 Sulfur dioxide (lbs/MWh) 3.7 5

  13. EIA - State Electricity Profiles

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

    Missouri Electricity Profile 2014 Table 1. 2014 Summary statistics (Missouri) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 21,790 19 Electric utilities 20,538 13 IPP & CHP 1,252 42 Net generation (megawatthours) 87,834,468 18 Electric utilities 85,271,253 11 IPP & CHP 2,563,215 46 Emissions Sulfur dioxide (short tons) 149,842 9 Nitrogen oxide (short tons) 77,749 10 Carbon dioxide (thousand metric tons) 75,735 8 Sulfur dioxide (lbs/MWh) 3.4 6 Nitrogen oxide

  14. EIA - State Electricity Profiles

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

    Montana Electricity Profile 2014 Table 1. 2014 Summary statistics (Montana) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 6,330 41 Electric utilities 3,209 38 IPP & CHP 3,121 30 Net generation (megawatthours) 30,257,616 41 Electric utilities 12,329,411 35 IPP & CHP 17,928,205 16 Emissions Sulfur dioxide (short tons) 14,426 34 Nitrogen oxide (short tons) 20,538 36 Carbon dioxide (thousand metric tons) 17,678 36 Sulfur dioxide (lbs/MWh) 1.0 34 Nitrogen oxide

  15. EIA - State Electricity Profiles

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

    Nebraska Electricity Profile 2014 Table 1. 2014 Summary statistics (Nebraska) Item Value Rank Primary energy source Coal Net summer capacity (megawatts) 8,732 36 Electric utilities 7,913 30 IPP & CHP 819 46 Net generation (megawatthours) 39,431,291 34 Electric utilities 36,560,960 30 IPP & CHP 2,870,331 45 Emissions Sulfur dioxide (short tons) 63,994 22 Nitrogen oxide (short tons) 27,045 30 Carbon dioxide (thousand metric tons) 26,348 31 Sulfur dioxide (lbs/MWh) 3.2 8 Nitrogen oxide

  16. EIA - State Electricity Profiles

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

    Nevada Electricity Profile 2014 Table 1. 2014 Summary statistics (Nevada) Item Value Rank Primary energy source Natural gas Net summer capacity (megawatts) 10,485 34 Electric utilities 8,480 29 IPP & CHP 2,006 35 Net generation (megawatthours) 36,000,537 37 Electric utilities 27,758,728 33 IPP & CHP 8,241,809 33 Emissions Sulfur dioxide (short tons) 10,229 40 Nitrogen oxide (short tons) 18,606 39 Carbon dioxide (thousand metric tons) 16,222 37 Sulfur dioxide (lbs/MWh) 0.4 38 Nitrogen

  17. EIA - State Electricity Profiles

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

    Hampshire Electricity Profile 2013 Table 1. 2013 Summary statistics (New Hampshire) Item Value Rank Primary energy source Nuclear Net summer capacity (megawatts) 4,413 44 Electric utilities 1,121 41 IPP & CHP 3,292 30 Net generation (megawatthours) 19,778,520 42 Electric utilities 2,266,903 41 IPP & CHP 17,511,617 20 Emissions Sulfur dioxide (short tons) 3,733 44 Nitrogen oxide (short tons) 5,057 47 Carbon dioxide (thousand metric tons) 3,447 46 Sulfur dioxide (lbs/MWh) 0.4 45 Nitrogen

  18. EIA - State Electricity Profiles

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

    Jersey Electricity Profile 2014 Table 1. 2014 Summary statistics (New Jersey) Item Value Rank Primary energy source Nuclear Net summer capacity (megawatts) 19,399 22 Electric utilities 544 43 IPP & CHP 18,852 7 Net generation (megawatthours) 68,051,086 23 Electric utilities -117,003 50 IPP & CHP 68,168,089 7 Emissions Sulfur dioxide (short tons) 3,369 44 Nitrogen oxide (short tons) 15,615 41 Carbon dioxide (thousand metric tons) 17,905 35 Sulfur dioxide (lbs/MWh) 0.1 47 Nitrogen oxide

  19. EIA - State Electricity Profiles

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

    Mexico Electricity Profile 2014 Table 1. 2014 Summary statistics (New Mexico) Item Value U.S. Rank Primary energy source Coal Net summer capacity (megawatts) 8,072 39 Electric utilities 6,094 33 IPP & CHP 1,978 37 Net generation (megawatthours) 32,306,210 39 Electric utilities 26,422,867 34 IPP & CHP 5,883,343 38 Emissions Sulfur dioxide (short tons) 12,064 37 Nitrogen oxide (short tons) 46,192 22 Carbon dioxide (thousand metric tons) 24,712 32 Sulfur dioxide (lbs/MWh) 0.7 37 Nitrogen

  20. EIA - State Electricity Profiles

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

    York Electricity Profile 2014 Table 1. 2014 Summary statistics (New York) Item Value Rank Primary energy source Natural Gas Net summer capacity (megawatts) 40,404 6 Electric utilities 10,989 27 IPP & CHP 29,416 5 Net generation (megawatthours) 137,122,202 7 Electric utilities 34,082 31 IPP & CHP 103,039,347 5 Emissions Sulfur dioxide (short tons) 31,878 28 Nitrogen oxide (short tons) 46,971 21 Carbon dioxide (thousand metric tons) 33,240 26 Sulfur dioxide (lbs/MWh) 0.5 39 Nitrogen oxide