National Library of Energy BETA

Sample records for operating hours number

  1. Electric System Intra-hour Operation Simulator

    Energy Science and Technology Software Center (OSTI)

    2014-03-07

    ESIOS is a software program developed at Pacific Northwest National Laboratory (PNNL) that performs intra-hour dispatch and automatic generation control (AGC) simulations for electric power system frequency regulation and load/variable generation following. The program dispatches generation resources at minute interval to meet control performance requirements, while incorporating stochastic models of forecast errors and variability with generation, load, interchange and market behaviors. The simulator also contains an operator model that mimics manual actions to adjust resourcemore » dispatch and maintain system reserves. Besides simulating generation fleet intra-hour dispatch, ESIOS can also be used as a test platform for the design and verification of energy storage, demand response, and other technologies helping to accommodate variable generation.« less

  2. Total Number of Operable Refineries

    U.S. Energy Information Administration (EIA) (indexed site)

    Data Series: Total Number of Operable Refineries Number of Operating Refineries Number of Idle Refineries Atmospheric Crude Oil Distillation Operable Capacity (B/CD) Atmospheric Crude Oil Distillation Operating Capacity (B/CD) Atmospheric Crude Oil Distillation Idle Capacity (B/CD) Atmospheric Crude Oil Distillation Operable Capacity (B/SD) Atmospheric Crude Oil Distillation Operating Capacity (B/SD) Atmospheric Crude Oil Distillation Idle Capacity (B/SD) Vacuum Distillation Downstream Charge

  3. Wind Power Plants and System Operation in the Hourly Time Domain...

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

    * NRELCP-500-33955 Wind Power Plants and System Operation in the Hourly Time Domain Preprint M. Milligan To be presented at WINDPOWER 2003 Austin, Texas May 18-21, 2003 National ...

  4. Optimizing hourly hydro operations at the Salt Lake City Area Integrated Projects

    SciTech Connect (OSTI)

    Veselka, T.D.; Hamilton, S.; McCoy, J.

    1995-10-01

    The Salt Lake City Area (SLCA) office of the Western Area Power Administration (Western) is responsible for marketing the capacity and energy generated by the Colorado River Storage, Collbran, and Rio Grande hydropower projects. These federal resources are collectively called the Salt Lake City Area Integrated Projects (SLCA/IP). In recent years, stringent operational limitations have been placed on several of these hydropower plants including the Glen Canyon Dam, which accounts for approximately 80% of the SLCA/IP resources. Operational limitations on SLCA/IP hydropower plants continue to evolve as a result of decisions currently being made in the Glen Canyon Dam Environmental Impact Statement (EIS) and the Power Marketing EIS. The Hydro LP (Linear Program) model, which was developed by Argonne National Laboratory (ANL), was used to analyze a broad range of issues associated with many possible future operational restrictions at SLCA/IP power plants. With technical assistance from Western, the Hydro LP model was configured to simulate hourly power plant operations for weekly periods with the objective of maximizing Western`s net revenues. The model considers hydropower operations for the purpose of serving SLCA firm loads, loads for special projects, Inland Power Pool (IPP) operating reserve requirements, and Western`s purchasing programs. The model estimates hourly SLCA/IP generation and spot market activities. For this paper, hourly SLCA/IP hydropower plant generation was simulated under three operational scenarios and three hydropower conditions. For each scenario an estimate of Western`s net revenue was computed.

  5. Optimizing hourly hydro operations at the Salt Lake City Area integrated projects

    SciTech Connect (OSTI)

    Veselka, T.D.; Hamilton, S.; McCoy, J.

    1995-06-01

    The Salt Lake City Area (SLCA) office of the Western Area Power Administration (Western) is responsible for marketing the capacity and energy generated by the Colorado Storage, Collbran, and Rio Grande hydropower projects. These federal resources are collectively called the Salt Lake City Area Integrated Projects (SLCA/IP). In recent years, stringent operational limitations have been placed on several of these hydropower plants including the Glen Canyon Dam, which accounts for approximately 80% of the SLCA/IP resources. Operational limitations on SLCA/IP hydropower plants continue to evolve as a result of decisions currently being made in the Glen Canyon Dam Environmental Impact Statement (EIS) and the Power Marketing EIS. To analyze a broad range of issues associated with many possible future operational restrictions, Argonne National Laboratory (ANL), with technical assistance from Western has developed the Hydro LP (Linear Program) Model. This model simulates hourly operations at SLCA/IP hydropower plants for weekly periods with the objective of maximizing Western`s net revenues. The model considers hydropower operations for the purpose of serving SLCA firm loads, loads for special projects, Inland Power Pool (IPP) spinning reserve requirements, and Western`s purchasing programs. The model estimates hourly SLCA/IP generation and spot market activities. For this paper, hourly SLCA/IP hydropower plant generation is simulated under three operational scenarios and three hydropower conditions. For each scenario an estimate of Western`s net revenue is computed.

  6. Daily/Hourly Hydrosystem Operation : How the Columbia River System Responds to Short-Term Needs.

    SciTech Connect (OSTI)

    Columbia River System Operation Review

    1994-02-01

    The System Operation Review, being conducted by the Bonneville Power Administration, the US Army Corps of Engineers, and the US Bureau of Reclamation, is analyzing current and potential future operations of the Columbia River System. One goal of the System Operations Review is to develop a new System Operation Strategy. The strategy will be designed to balance the many regionally and nationally important uses of the Columbia River system. Short-term operations address the dynamics that affect the Northwest hydro system and its multiple uses. Demands for electrical power and natural streamflows change constantly and thus are not precisely predictable. Other uses of the hydro system have constantly changing needs, too, many of which can interfere with other uses. Project operators must address various river needs, physical limitations, weather, and streamflow conditions while maintaining the stability of the electric system and keeping your lights on. It takes staffing around the clock to manage the hour-to-hour changes that occur and the challenges that face project operators all the time.

  7. Identifying Challenging Operating Hours for Solar Intergration in the NV Energy System

    SciTech Connect (OSTI)

    Etingov, Pavel V.; Lu, Shuai; Guo, Xinxin; Ma, Jian; Makarov, Yuri V.; Chadliev, Vladimir; Salgo, Richard

    2012-05-09

    Abstract-- In this paper, the ability of the Nevada (NV) Energy generation fleet to meet its system balancing requirements under different solar energy penetration scenarios is studied. System balancing requirements include capacity, ramp rate, and ramp duration requirements for load following and regulation. If, during some operating hours, system capability is insufficient to meet these requirements, there is certain probability that the balancing authoritys control and reliability performance can be compromised. These operating hours are considered as challenging hours. Five different solar energy integration scenarios have been studied. Simulations have shown that the NV Energy system will be potentially able to accommodate up to 942 MW of solar photovoltaic (PV) generation. However, the existing generation scheduling procedure should be adjusted to make it happen. Fast-responsive peaker units need to be used more frequently to meet the increasing ramping requirements. Thus, the NV Energy system operational cost can increase. Index TermsSolar Generation, Renewables Integration, Balancing Process, Load Following, Regulation.

  8. Supplement Number 1 to Operating Plan of Mirnat Potomac River...

    Energy Savers

    1 to Operating Plan of Mirnat Potomac River, LLC in Compliance with Order No. 202-05-03 Supplement Number 1 to Operating Plan of Mirnat Potomac River, LLC in Compliance with Order ...

  9. Mailing Addresses and Information Numbers for Operations, Field, and Site

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

    Offices | Department of Energy About Energy.gov » Mailing Addresses and Information Numbers for Operations, Field, and Site Offices Mailing Addresses and Information Numbers for Operations, Field, and Site Offices Name Telephone Number U.S. Department of Energy Ames Site Office 111 TASF, Iowa State University Ames, Iowa 50011 515-294-9557 U.S. Department of Energy Argonne Site Office 9800 S. Cass Avenue Argonne, IL 60439 630-252-2000 U.S. Department of Energy Berkeley Site Office Berkeley

  10. Survey of lepton number violation via effective operators

    SciTech Connect (OSTI)

    Gouvea, Andre de; Jenkins, James [Northwestern University, Department of Physics and Astronomy, 2145 Sheridan Road, Evanston, Illinois 60208 (United States)

    2008-01-01

    We survey 129 lepton number violating effective operators, consistent with the minimal standard model gauge group and particle content, of mass dimension up to and including 11. Upon requiring that each one radiatively generates the observed neutrino masses, we extract an associated characteristic cutoff energy scale which we use to calculate other observable manifestations of these operators for a number of current and future experimental probes, concentrating on lepton number violating phenomena. These include searches for neutrinoless double-beta decay and rare meson, lepton, and gauge boson decays. We also consider searches at hadron/lepton collider facilities in anticipation of the CERN LHC and the future ILC. We find that some operators are already disfavored by current data, while more are ripe to be probed by next-generation experiments. We also find that our current understanding of lepton mixing disfavors a subset of higher dimensional operators. While neutrinoless double-beta decay is the most promising signature of lepton number violation for the majority of operators, a handful is best probed by other means. We argue that a combination of constraints from various independent experimental sources will help to pinpoint the ''correct'' model of neutrino mass, or at least aid in narrowing down the set of possibilities.

  11. Alertness, performance and off-duty sleep on 8-hour and 12-hour night shifts in a simulated continuous operations control room setting

    SciTech Connect (OSTI)

    Baker, T.L.

    1995-04-01

    A growing number of nuclear power plants in the United States have adopted routine 12-hr shift schedules. Because of the potential impact that extended work shifts could have on safe and efficient power plant operation, the U.S. Nuclear Regulatory Commission funded research on 8-hr and 12-hr shifts at the Human Alertness Research Center (HARC) in Boston, Massachusetts. This report describes the research undertaken: a study of simulated 8-hr and 12-hr work shifts that compares alertness, speed, and accuracy at responding to simulator alarms, and relative cognitive performance, self-rated mood and vigor, and sleep-wake patterns of 8-hr versus 12-hr shift workers.

  12. Supplement Number 5 to the Operating Plan of Mirant Potomac River...

    Energy Savers

    5 to the Operating Plan of Mirant Potomac River, LLC in Compliance with Order No. 202-05-03 Supplement Number 5 to the Operating Plan of Mirant Potomac River, LLC in Compliance ...

  13. Number

    Office of Legacy Management (LM)

    It is seen that all operations are performed vet, thus eliminating almost entirely a dust exposure hazard. A* Monazite sand is at present derived from India which supplies an ore ...

  14. Operability test report for rotary mode core sampling system number 3

    SciTech Connect (OSTI)

    Corbett, J.E.

    1996-03-01

    This report documents the successful completion of operability testing for the Rotary Mode Core Sampling (RMCS) system {number_sign}3. The Report includes the test procedure (WHC-SD-WM-OTP-174), exception resolutions, data sheets, and a test report summary.

  15. Supplement Number 1 to Operating Plan of Mirnat Potomac River, LLC in

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

    Compliance with Order No. 202-05-03 | Department of Energy 1 to Operating Plan of Mirnat Potomac River, LLC in Compliance with Order No. 202-05-03 Supplement Number 1 to Operating Plan of Mirnat Potomac River, LLC in Compliance with Order No. 202-05-03 Docket No. EO-05-01: Pursuant to Section 202(c) of the Federal Power Act, 16 USC §824a(c), Section 301 (b) of the Department of Energy Organization Act, 42 USC §7151 (b), and Order No. 202-05-3, issued by the Department of Energy

  16. Supplement Number 2 to the Operating Plan of Mirant Potomac River, LLC |

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

    Department of Energy 2 to the Operating Plan of Mirant Potomac River, LLC Supplement Number 2 to the Operating Plan of Mirant Potomac River, LLC Docket No. EO-05-01. Order No. 202-05-03: Pursuant to Section 202(c) of the Federal Power Act, 16 USC §824a(c), Section 301(b) of the Department of Energy Organization Act, 42 USC §7151(b), and Order No. 202-05-3, issued by the Department of Energy ("DOE" or the "Department") on December 20,2005 ("Order"), Mirant

  17. Supplement Number 3 to the Operating Plan of Mirant Potomac River, LLC |

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

    Department of Energy 3 to the Operating Plan of Mirant Potomac River, LLC Supplement Number 3 to the Operating Plan of Mirant Potomac River, LLC Docket No. EO-05-01:Pursuant to Section 202(c) of the Federal Power Act, 16 USC §824a(c), Section 301 (b) of the Department of Energy Organization Act, 42 USC §7151 (b), and Order No. 202-05-3, issued by the Department of Energy ("DOE" or the "Department") on December 20, 2005 ("Order"), Mirant Potomac River, LLC

  18. Supplement Number 4 to the Operating Plan of Mirant Potomac River, LLC |

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

    Department of Energy 4 to the Operating Plan of Mirant Potomac River, LLC Supplement Number 4 to the Operating Plan of Mirant Potomac River, LLC Docket No. EO-05-01: Pursuant to Section 202(c) of the Federal Power Act, 16 USC § 824a(c), Section 301(b) of the Department of Energy Organization Act, 42 USC §7151 (b), and Order No, 202-05-3, isslled by the Department of Energy ("DOE" or the "Department") on December 20, 2005 ("Order"), Mirant Potomac River, LLC

  19. Supplement Number 5 to the Operating Plan of Mirant Potomac River, LLC in

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

    Compliance with Order No. 202-05-03 | Department of Energy 5 to the Operating Plan of Mirant Potomac River, LLC in Compliance with Order No. 202-05-03 Supplement Number 5 to the Operating Plan of Mirant Potomac River, LLC in Compliance with Order No. 202-05-03 Docket No. EO-05-01: Pursuant to Section 202(c) of the Federal Power Act, 16 USC §824a(c), Section 301(b) of the Department of Energy Organization Act, 42 USC §7151(b), and Order No. 202-05-3, issued by the Department of Energy

  20. Hopper Hours Used

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

    Hours Used Hopper Hours Used 2015 Hopper Usage Chart Hopper Usage Chart 2014 Hopper Usage ... Hopper Usage Chart 2011 Hopper Usage Chart Hopper Usage Chart 2015 Date Hours Used (in ...

  1. Ombuds Office Location & Hours

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

    Ombuds Office Location & Hours Ombuds Office Location & Hours Committed to the fair and equitable treatment of all employees, contractors, and persons doing business with the...

  2. Effects of Gasoline Direct Injection Engine Operating Parameters on Particle Number Emissions

    SciTech Connect (OSTI)

    He, X.; Ratcliff, M. A.; Zigler, B. T.

    2012-04-19

    A single-cylinder, wall-guided, spark ignition direct injection engine was used to study the impact of engine operating parameters on engine-out particle number (PN) emissions. Experiments were conducted with certification gasoline and a splash blend of 20% fuel grade ethanol in gasoline (E20), at four steady-state engine operating conditions. Independent engine control parameter sweeps were conducted including start of injection, injection pressure, spark timing, exhaust cam phasing, intake cam phasing, and air-fuel ratio. The results show that fuel injection timing is the dominant factor impacting PN emissions from this wall-guided gasoline direct injection engine. The major factor causing high PN emissions is fuel liquid impingement on the piston bowl. By avoiding fuel impingement, more than an order of magnitude reduction in PN emission was observed. Increasing fuel injection pressure reduces PN emissions because of smaller fuel droplet size and faster fuel-air mixing. PN emissions are insensitive to cam phasing and spark timing, especially at high engine load. Cold engine conditions produce higher PN emissions than hot engine conditions due to slower fuel vaporization and thus less fuel-air homogeneity during the combustion process. E20 produces lower PN emissions at low and medium loads if fuel liquid impingement on piston bowl is avoided. At high load or if there is fuel liquid impingement on piston bowl and/or cylinder wall, E20 tends to produce higher PN emissions. This is probably a function of the higher heat of vaporization of ethanol, which slows the vaporization of other fuel components from surfaces and may create local fuel-rich combustion or even pool-fires.

  3. Franklin Hours Used

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

    Franklin Hours Used Franklin Hours Used 2011 Franklin Usage in Hours 2011 Franklin Usage in Hours 2010 2010 Franklin Usage in Hours 2009 2009 Franklin Usage in Hours 2007-2008 2008 Franklin Usage in Hours 2008 Franklin Usage in Hours Date Hours Used (in thousands) Percentage of Maximum Possible (24 hours/day) 04/28/2012 0.00 0.00 04/27/2012 272.62 29.40 04/26/2012 692.81 74.71 04/25/2012 841.60 90.75 04/24/2012 53.86 5.81 04/23/2012 432.01 46.59 04/22/2012 823.23 88.77 04/21/2012 473.95 51.11

  4. Edison Hours Used

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

    Edison Hours Used 2015 Edison Usage Chart Edison Usage Chart 2014 Edison Usage Chart Edison Usage Chart 2013 Edison Usage Chart Edison Usage Chart 2015 Date Hours Used (in ...

  5. Contacts / Hours - Hanford Site

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

    Contacts / Hours Hanford Meteorological Station Real Time Met Data from Around the Site Current and Past 48 Hours HMS Observations Daily HMS Extremes in Met Data Met and Climate Data Summary Products Contacts / Hours Current NWS Forecast for the Tri-Cities NWS Windchill Chart Contacts / Hours Email Email Page | Print Print Page | Text Increase Font Size Decrease Font Size Note: Using the telephone is the ONLY way to get up to the minute information. On duty Forecaster (509) 373-2716 Current

  6. Operability test procedure for rotary mode core sampling system {number_sign}4

    SciTech Connect (OSTI)

    Farris, T.R.; Jarecki, T.D.

    1995-04-26

    This document gives instructions for the Operability Testing of the Rotary Mode Core Sampling (RMCS) System No. 4. This document is based on the Operability Test Procedure for RMCS system No. 2 because the basic design is the same for all three systems. Modifications have been made from the original design only when exact duplication was not feasible or design improvements could be incorporated without affecting the operation of the system. Operability testing of the Rotary Mode Core Sampling System No. 4 will verify that functional and operational requirements have been met. Testing will be completed in two phases. The first phase of testing (section 7) will involve operating the truck equipment to demonstrate its capabilities. The second phase of testing (section 8) will take repeated samples in a simulated operation environment. These tests will be conducted at the ``Rock Slinger`` test site located just south of U-Plant in the 200 West Area. Tests will be done in a simulated tank farm environment. All testing will be non-radioactive and stand-in materials shall be used to simulate waste tank conditions. Systems will be assembled and arranged in a manner similar to that expected in the field.

  7. Operability test procedure for rotary mode core sampling system {number_sign}3

    SciTech Connect (OSTI)

    Farris, T.R.; Jarecki, T.D.

    1995-04-26

    This document gives instructions for the Operability Testing of the Rotary Mode Core Sampling (RMCS) System No. 3. This document is based on the Operability Test Procedure for RMCS system No. 2 because the basic design is the same for all three systems. Modifications have been made from the original design only when exact duplication was not feasible or design improvements could be incorporated without affecting the operation of the system. Operability testing of the Rotary Mode Core Sampling System No. 3, will verify that functional and operational requirements have been met. Testing will be completed in two phases. The first phase of testing (section 7) will involve operating the truck equipment to demonstrate its capabilities. The second phase of testing (section 8) will take repeated samples in a simulated operation environment. These tests will be conducted at the ``Rock Slinger`` test site located just south of U-Plant in the 200 West Area. Tests will be done in a simulated tank farm environment. All testing will be non-radioactive and stand-in materials shall be used to simulate waste tank conditions. Systems will be assembled and arranged in a manner similar to that expected in the field.

  8. More Than 410,000 Hours of Real-World Fuel Cell System Operation Have Been Analyzed by NREL's Technology Validation Team (Fact Sheet)

    SciTech Connect (OSTI)

    Kurtz, J.; Wipke, K.; Sprik, S.; Ramsden, T.

    2011-02-01

    This fact sheet discusses how researchers at the National Renewable Energy Laboratory (NREL) are working to validate hydrogen and fuel cell systems in real-world settings. NREL strives to provide an independent third-party technology assessment that focuses on fuel cell system and hydrogen infrastructure performance, operation, maintenance, and safety.

  9. Office for Analysis and Evaluation of Operational Data 1996 annual report. Volume 10, Number 1: Reactors

    SciTech Connect (OSTI)

    1997-12-01

    This annual report of the US Nuclear Regulatory Commission`s Office for Analysis and Evaluation of Operational Data (AEOD) describes activities conducted during 1996. The report is published in three parts. NUREG-1272, Vol. 10, No. 1, covers power reactors and presents an overview of the operating experience of the nuclear power industry from the NRC perspective, including comments about trends of some key performance measures. The report also includes the principal findings and issues identified in AEOD studies over the past year and summarizes information from such sources as licensee event reports and reports to the NRC`s Operations Center. NUREG-1272, Vol. 10, No. 2, covers nuclear materials and presents a review of the events and concerns during 1996 associated with the use of licensed material in nonreactor applications, such as personnel overexposures and medical misadministrations. Both reports also contain a discussion of the Incident Investigation Team program and summarize both the Incident Investigation Team and Augmented Inspection Team reports. Each volume contains a list of the AEOD reports issued from CY 1980 through 1996. NUREG-1272, Vol. 10, No. 3, covers technical training and presents the activities of the Technical Training Center in support of the NRC`s mission in 1996.

  10. Hopper Hours Used

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

    Hours Used Hopper Hours Used 2015 Hopper Usage Chart Hopper Usage Chart 2014 Hopper Usage Chart Hopper Usage Chart 2013 Hopper Usage Chart Hopper Usage Chart 2012 Hopper Usage Chart Hopper Usage Chart 2011 Hopper Usage Chart Hopper Usage Chart 2015 Date Hours Used (in millions) Percent of Maximum Possible (24 hours/day) 09/20/2015 3.247 88.2 09/19/2015 3.401 92.4 09/18/2015 3.425 93.0 09/17/2015 3.450 93.7 09/16/2015 3.413 92.7 09/15/2015 3.466 94.1 09/14/2015 3.299 89.6 09/13/2015 3.436 93.3

  11. Property:OperatingHours | Open Energy Information

    Open Energy Information (Open El) [EERE & EIA]

    B Blundell 1 Geothermal Facility + 8,587 + Blundell 2 Geothermal Facility + 7,883 + R Raft River Geothermal Facility + 8,338 + Retrieved from "http:en.openei.orgw...

  12. Carver Hours Used

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

    Carver Hours Used Carver Hours Used Hopper Usage Chart Hopper Usage Chart Date Hours Used (in millions) Percent of Maximum Possible (24 hours/day) 12/15/2014 161.25 84.75 12/14/2014 162.32 85.31 12/13/2014 165.95 87.22 12/12/2014 172.69 90.76 12/11/2014 174.45 91.69 12/10/2014 170.09 89.39 12/09/2014 166.50 87.50 12/08/2014 169.20 88.92 12/07/2014 167.44 88.00 12/06/2014 172.83 90.83 12/05/2014 176.73 92.89 12/04/2014 174.69 91.81 12/03/2014 178.77 93.96 12/02/2014 172.30 90.55 12/01/2014 176.12

  13. INTERNATIONAL UNION OF OPERATING ENGINEERS NATIONAL HAZMAT PROGRAM - DEWALT RECIPROCATING SAW OENHP{number_sign}: 2001-01, VERSION A

    SciTech Connect (OSTI)

    Unknown

    2002-01-31

    Florida International University's (FIU) Hemispheric Center for Environmental Technology (HCET) evaluated five saws for their effectiveness in cutting specially prepared fiberglass-reinforced plywood crates. These crates were built as surrogates for crates that presently hold radioactively contaminated glove boxes at the Department of Energy's (DOE) Los Alamos facility. The DeWalt reciprocating saw was assessed on August 13, 2001. During the FIU test of efficacy, a team from the Operating Engineers National Hazmat Program (OENHP) evaluated the occupational safety and health issues associated with this technology. The DeWalt reciprocating saw is a hand-held industrial tool used for cutting numerous materials, including wood and various types of metals depending upon the chosen blade. Its design allows for cutting close to floors, corners, and other difficult areas. An adjustable shoe sets the cut at three separate depths. During the demonstration for the dismantling of the fiberglass-reinforced plywood crate, the saw was used for extended continuous cutting, over a period of approximately two hours. The dismantling operation involved vertical and horizontal cuts, saw blade changes, and material handling. During this process, operators experienced vibration to the hand and arm in addition to a temperature rise on the handgrip. The blade of the saw is partially exposed during handling and fully exposed during blade changes. Administrative controls, such as duty time of the operators and the machine, operator training, and personal protective equipment (PPE), such as gloves, should be considered when using the saw in this application. Personal noise sampling indicated that both workers were exposed to noise levels exceeding the Occupational Safety and Health Administration's (OSHA) Action Level of 85 decibels (dBA) with time-weighted averages (TWA's) of 88.3 and 90.6 dBA. Normally, a worker would be placed in a hearing conservation program if his TWA was greater than

  14. PV Hourly Simulation Tool

    Energy Science and Technology Software Center (OSTI)

    2010-12-31

    This software requires inputs of simple general building characteristics and usage information to calculate the energy and cost benefits of solar PV. This tool conducts and complex hourly simulation of solar PV based primarily on the area available on the rooftop. It uses a simplified efficiency calculation method and real panel characteristics. It includes a detailed rate structure to account for time-of-use rates, on-peak and off-peak pricing, and multiple rate seasons. This tool includes themore » option for advanced system design inputs if they are known. This tool calculates energy savings, demand reduction, cost savings, incentives and building life cycle costs including: simple payback, discounted payback, net-present value, and savings to investment ratio. In addition this tool also displays the environmental benefits of a project.« less

  15. Office for Analysis and Evaluation of Operational Data 1994-FY 95 annual report. Volume 9, Number 2

    SciTech Connect (OSTI)

    1996-09-01

    This annual report of the US Nuclear Regulatory Commission`s Office for Analysis and Evaluation of Operational Data (AEOD) describes activities conducted during CY 1994 and FY 1995. The report is published in three parts. NUREG-1272, Vol. 9, No. 1, covers power reactors and presents an overview of the operating experience of the nuclear power industry from the NRC perspective, including comments about the trends of some key performance measures. The report also includes the principal findings and issues identified in AEOD studies over the past year and summarizes information from such sources as licensee event reports, diagnostic evaluations, and reports to the NRC`s Operations Center. NUREG-1272, Vol. 9, No. 2, covers nuclear materials and presents a review of the events and concerns associated with the use of licensed material in nonreactor applications, such as personnel overexposures and medical misadministrations. Both reports also contain a discussion of the Incident Investigation Team program and summarize both the Incident Investigation Team and Augmented Inspection Team reports. Each volume contains a list of the AEOD reports issued from 1980 through FY 1995. NUREG-1272, Vol. 9, No. 3, covers technical training and presents the activities of the Technical Training Center in support of the NRC`s mission.

  16. INTERNATIONAL UNION OF OPERATING ENGINEERS NATIONAL HAZMAT PROGRAM - ADAMANT CIRCULAR SAW OENHP{number_sign}: 2001-05, VERSION A

    SciTech Connect (OSTI)

    Unknown

    2002-01-01

    Florida International University's (FIU) Hemispheric Center for Environmental Technology (HCET) evaluated five saws for their effectiveness in cutting up specially prepared fiberglass-reinforced plywood crates. These crates were built as surrogates for crates that presently hold radioactive contaminated glove boxes at the Department of Energy's (DOE) Los Alamos facility. The Adamant circular saw was assessed on August 14, 2001. During the FIU test of efficacy, a team from the Operating Engineers National Hazmat Program (OENHP) evaluated the occupational safety and health issues associated with this technology. The Adamant was only used during a limited ''test'' on a regular plywood crate due to safety considerations of the tool for this application. The Adamant circular saw, a counter-rotating twin-cutter, constructed with blades that work differently than conventional cutting wheels with twin blades, each rotating in opposite directions. It is used to cut wood and metals. Each blade is approximately 8 3/4 inches in diameter with a maximum cutting depth of 2 1/2 inches. The machine has two rotation speeds: 1,900 and 2,900 rotations per minute (rpm). The saw is operated with an interlocked, guarded trigger switch located at the end of the saw opposite the cutting blades. To operate the saw, the safety interlock must be depressed prior to powering the saw with the trigger control. The saw is supported by a handle at the front of the saw near the cutting blades. The top part of the blades is guarded near the handle, with approximately three-fourths of the face of the blades exposed. The Adamant circular saw is an innovative technology used to cut metals and wood. Its safety features include: interlocking switch for powering the saw, overload indicator and shutoff, and an electronic brake that stops the engine immediately when the start button is released. The top part of the blades is guarded near the motor. With approximately three-fourths of the face of the blades

  17. Multi-cluster processor operating only select number of clusters during each phase based on program statistic monitored at predetermined intervals

    DOE Patents [OSTI]

    Balasubramonian, Rajeev; Dwarkadas, Sandhya; Albonesi, David

    2009-02-10

    In a processor having multiple clusters which operate in parallel, the number of clusters in use can be varied dynamically. At the start of each program phase, the configuration option for an interval is run to determine the optimal configuration, which is used until the next phase change is detected. The optimum instruction interval is determined by starting with a minimum interval and doubling it until a low stability factor is reached.

  18. Solar Hot Water Hourly Simulation

    Energy Science and Technology Software Center (OSTI)

    2009-12-31

    The Software consists of a spreadsheet written in Microsoft Excel which provides an hourly simulation of a solar hot water heating system (including solar geometry, solar collector efficiency as a function of temperature, energy balance on storage tank and lifecycle cost analysis).

  19. Edison Phase I Hours Used

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

    Edison Phase I Hours Used Edison Phase I Hours Used Edison Usage Chart Edison Usage Chart Date Hours Used (in millions) Percent of Maximum Possible (24 hours/day) 06/23/2013 0.226 88.6 06/22/2013 0.239 93.9 06/21/2013 0.248 97.1 06/20/2013 0.240 94.0 06/19/2013 0.233 91.3 06/18/2013 0.245 96.0 06/17/2013 0.251 98.4 06/16/2013 0.243 95.3 06/15/2013 0.245 95.9 06/14/2013 0.246 96.5 06/13/2013 0.240 94.1 06/12/2013 0.128 50.4 06/11/2013 0.215 84.5 06/10/2013 0.225 88.4 06/09/2013 0.228 89.6

  20. EM River Corridor Cleanup Contractor Surpasses 7 Million Safe Hours

    Energy.gov [DOE]

    RICHLAND, Wash. – EM’s Richland Operations Office contractor Washington Closure Hanford (WCH) and its subcontractor employees achieved a significant safety milestone by working 7 million hours without a lost workday injury.

  1. 20140430_Green Machine Florida Canyon Hourly Data

    SciTech Connect (OSTI)

    Thibedeau, Joe

    2014-05-05

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 April to 30 April 2014.

  2. Green Machine Florida Canyon Hourly Data 20130731

    SciTech Connect (OSTI)

    Vanderhoff, Alex

    2013-08-30

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 7/1/13 to 7/31/13.

  3. Green Machine Florida Canyon Hourly Data

    SciTech Connect (OSTI)

    Vanderhoff, Alex

    2013-07-15

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 6/1/13 to 6/30/13

  4. 20130416_Green Machine Florida Canyon Hourly Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Vanderhoff, Alex

    2013-04-24

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 4/16/13.

  5. Green Machine Florida Canyon Hourly Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Vanderhoff, Alex

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 6/1/13 to 6/30/13

  6. Green Machine Florida Canyon Hourly Data 20130731

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Vanderhoff, Alex

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 7/1/13 to 7/31/13.

  7. 20130416_Green Machine Florida Canyon Hourly Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Vanderhoff, Alex

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 4/16/13.

  8. 20140430_Green Machine Florida Canyon Hourly Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Thibedeau, Joe

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 April to 30 April 2014.

  9. Hour-by-Hour Cost Modeling of Optimized Central Wind-Based Water...

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

    Hour-by-Hour Cost Modeling of Optimized Central Wind-Based Water Electrolysis Production Hour-by-Hour Cost Modeling of Optimized Central Wind-Based Water Electrolysis Production ...

  10. Intra-Hour Dispatch and Automatic Generator Control Demonstration with

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

    Solar Forecasting | Department of Energy Intra-Hour Dispatch and Automatic Generator Control Demonstration with Solar Forecasting Intra-Hour Dispatch and Automatic Generator Control Demonstration with Solar Forecasting UCSD logo2.png The University of California at San Diego (UCSD) is leading a project that will reduce power system operation cost by providing a prediction of the generation fleet's behavior in real time for realistic photovoltaic penetration scenarios. APPROACH The primary

  11. Is the hourly data I get from NREL's PV Watts program adjusted...

    Open Energy Information (Open El) [EERE & EIA]

    Is the hourly data I get from NREL's PV Watts program adjusted for daylight savings time. Home I take the hourly AC output numbers and apply them to a program I built that assigns...

  12. Gate Hours & Services | Stanford Synchrotron Radiation Lightsource

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

    Gate Hours & Services Sand Hill Road Main Gate Open 24 hours a day, 7 days a week ... SLAC has proximity card readers at the entrances from Sand Hill Road and Alpine Road as ...

  13. Labor Standards/Wage and Hour Laws

    Office of Energy Efficiency and Renewable Energy (EERE)

    Labor Standards and Wage/Hour laws establish minimum wage, overtime pay, recordkeeping, and minimum leave requirements:

  14. 100,000 hour design life of turbo compressor packages

    SciTech Connect (OSTI)

    1998-05-20

    Many turbomachinery manufacturers and operators typically quote 100,000 hours as a design limit for service life of turbo compressor components. The Pipeline Research Committee initiated this study to review the life limiting criteria for certain critical components and determine if the design target of 100,000 hours can be safely and reliably met or extended with special component management practices. The first phase of the project was to select the turbomachinery components that would be included in the review. Committee members were surveyed with a detailed questionnaire designed to identify critical components based on: high hours (e.g. at or approaching 100,000 hours) the most common engine types operated by the member organizations, and the components of greatest concern from a risk and expense point of view. The selection made covers a wide range of engine types that are of interest to most of the committee companies. This selection represents some 78% of the high hour units operated by the committee and includes components from GE Frame 3 and Frame 5, Solar Saturn, Rolls Royce Avon, and Cooper RT56 engines. The report goes into detail regarding the various damage mechanism which can be the main life limiting factor of the component; creep, fatigue, environmental attack, wear and microstructure instability. For each of the component types selected, the study identifies the life limiting criteria and outlines how the components may be managed for extended life. Many of the selected components can be reliably operated beyond 100,000 hours by following the management practices set out in the report.

  15. Hour of Code | Argonne National Laboratory

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

    Home Learning Center Undergraduates Graduates Faculty Partners News & Events Learning Center Community Outreach Hour of Code Introduce a Girl to Engineering Science Careers in ...

  16. EIA-930 Hourly and Daily Balancing ...

    U.S. Energy Information Administration (EIA) (indexed site)

    ... file retrieval using business-to-business data transfer or web services technology. ... but are to be included in the posted hourly value for balancing authority net generation. ...

  17. Happy Birthday Unmet Hours! | Department of Energy

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

    Happy Birthday Unmet Hours! Happy Birthday Unmet Hours! September 3, 2015 - 1:43pm Addthis Unmet Hours is a question-and-answer resource for the building energy modeling community. Unmet Hours is a question-and-answer resource for the building energy modeling community. Amir Roth, Ph.D. Amir Roth, Ph.D. Building Energy Modeling Technology Manager A year ago this week, a star was born. Working with IBPSA-USA, the US chapter of the International Building Performance Simulation Association, and Big

  18. Hour of Code | Argonne National Laboratory

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

    1 in 3 students in US schools have tried an Hour of Code activity Over 100M students have participated at 77,000 Hour of Code events worldwide More girls have tried computer science than in the last 70 years Featured Videos Hour of Code Video Argonne's Super Computer Mira Contact education@anl.gov Explore Computer Science! Let your creativity guide your imagination with the tools of computer science, the tools of the future! Argonne National Laboratory researchers will open students' minds and

  19. Bradbury Science Museum announces winter opening hours

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

    Bradbury Science Museum winter hours Bradbury Science Museum announces winter opening hours Museum will be closed on Christmas Day (December 25) and New Year's Day (January 1, 2011). December 21, 2010 Bradbury Science Museum Bradbury Science Museum Contact Communications Office (505) 667-7000 Often called "a window to the Laboratory," the museum annually attracts thousands of visitors from all over the world. LOS ALAMOS, New Mexico, December 21, 2010-Los Alamos National Laboratory's

  20. Fermilab | Visit Fermilab | Hours, Maps and Directions

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

    Hours and site access Check the Fermilab home page for our latest news and a calendar of events, which also includes days that our main building and exhibits are closed. Hours Fermilab's site is open to the public every day of the week from 8 a.m. to 6 p.m. from November to March and from 8 a.m. to 8 p.m. the rest of the year. A map of Fermilab's public areas is available online. Fermilab visitors are allowed to visit two buildings on their own: Wilson Hall and the Leon Lederman Science

  1. INTERNATIONAL UNION OF OPERATING ENGINEERS NATIONAL HAZMAT PROGRAM - MILWAUKEE WORM DRIVE CIRCULAR SAW OENHP{number_sign}: 2001-02, VERSION A

    SciTech Connect (OSTI)

    Unknown

    2002-01-05

    Florida International University's (FIU) Hemispheric Center for Environmental Technology (HCET) evaluated five saws for their effectiveness in cutting specially prepared fiberglass-reinforced plywood crates. These crates were built as surrogates for crates that presently hold radioactively contaminated glove boxes at the Department of Energy's (DOE) Los Alamos facility. The Milwaukee worm drive circular saw was assessed on August 14, 2001. During the FIU test of efficacy, a team from the Operating Engineers National Hazmat Program (OENHP) evaluated the occupational safety and health issues associated with this technology. The Milwaukee worm drive circular saw is a hand-held tool with a 7 1/4-inch diameter circular blade for cutting wood. The saw contains a fixed upper and a retractable lower blade guard to prevent access to the blade during use. The unit is operated with an on/off guarded trigger switch; and is supported with a handgrip mounted on top of the saw. An adjustable lever sets the depth of cut. The retractable blade guard permits blind or plunge cuts and protects from blade access during shutdown and blade coast. Kickback, the sudden reaction to a pinched blade, is possible when using this saw and could cause the saw to lift up and out of the work piece toward the operator. Proper work position and firm control of the saw minimizes the potential for a sprain or strain. Care needs to be exercised to support the work piece properly and to not force the tool. Personal noise sampling indicated that one worker was near the Occupational Safety and Health Administration's (OSHA) Action Level of 85 decibels (dBA) while the other was at the Action Level with time-weighted averages (TWA's) of 82.7 and 84.6 dBA, respectively. These data are not entirely representative as they were gathered during a simulation and not at the actual worksite. Additional sampling should be conducted on-site, but the workers should wear hearing protection until it is determined that it

  2. Shell Canada Limited application to construct and operate an oil sands mine in the Fort McMurray area, decision 99-2, application number 970588

    SciTech Connect (OSTI)

    1999-11-01

    Shell Canada has applied before the Alberta Energy and Utilities Board for approval to construct, operate, and reclaim an oil sands mine and associated bitumen extraction facilities (the Muskeg River Mine) in the Fort McMurray area. This report reviews the views of the applicant, the Board, and various intervenors at the hearing held to consider issues related to the application. Issues discussed include the need for the proposed project, its socio-economic effects, Shell`s public consultation process, mine planning and resource conservation, the extraction process to be used, tailings management, environmental effects, land reclamation, and cumulative effects of oil sands developments. The Board`s conclusion and decision regarding the application are also presented.

  3. Shell Canada Limited application to construct and operate an oil sands mine in the Fort McMurray area, decision 99-2, application number 970588

    SciTech Connect (OSTI)

    Not Available

    1999-01-01

    Shell Canada has applied before the Alberta Energy and Utilities Board for approval to construct, operate, and reclaim an oil sands mine and associated bitumen extraction facilities (the Muskeg River Mine) in the Fort McMurray area. This report reviews the views of the applicant, the Board, and various intervenors at the hearing held to consider issues related to the application. Issues discussed include the need for the proposed project, its socio-economic effects, Shell's public consultation process, mine planning and resource conservation, the extraction process to be used, tailings management, environmental effects, land reclamation, and cumulative effects of oil sands developments. The Board's conclusion and decision regarding the application are also presented.

  4. Hour-by-Hour Cost Modeling of Optimized Central Wind-Based Water

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

    Electrolysis Production | Department of Energy Hour-by-Hour Cost Modeling of Optimized Central Wind-Based Water Electrolysis Production Hour-by-Hour Cost Modeling of Optimized Central Wind-Based Water Electrolysis Production Download the presentation slides from the U.S. Department of Energy Fuel Cell Technologies Office webinar, "Wind-to-Hydrogen Cost Modeling and Project Findings," held on January 17, 2013. Wind-to-Hydrogen Cost Modeling and Project Findings Webinar Slides (2.09

  5. Team Surpasses 1 Million Hours Safety Milestone

    Energy.gov [DOE]

    NISKAYUNA, N.Y. – Vigilance and dedication to safety led the EM program’s disposition project team at the Separations Process Research Unit (SPRU) to achieve a milestone of one million hours — over two-and-a-half-years — without injury or illness resulting in time away from work.

  6. Request Number:

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

    1074438 Name: Gayle Cooper Organization: nla Address: _ Country: United States Phone Number: Fax Number: nla E-mail: . ~===--------- Reasonably Describe Records Description: Information pertaining to the Department of Energy's cost estimate for reinstating pension benefit service years to the Enterprise Company (ENCO) employees who are active plan participants in the Hanford Site Pension Plan. This cost estimate was an outcome of the DOE's Worker Town Hall Meetings held on September 17-18, 2009.

  7. 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.

  8. 20131201-1231_Green Machine Florida Canyon Hourly Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Thibedeau, Joe

    2014-01-08

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Dec to 31 Dec 2013.

  9. 20140701-0731_Green Machine Florida Canyon Hourly Data

    SciTech Connect (OSTI)

    Thibedeau, Joe

    2014-07-31

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 July to 31 July 2014.

  10. 20140101-0131_Green Machine Florida Canyon Hourly Data

    SciTech Connect (OSTI)

    Thibedeau, Joe

    2014-02-03

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Jan to 31 Jan 2014.

  11. 20130501-20130531_Green Machine Florida Canyon Hourly Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Vanderhoff, Alex

    2013-06-18

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from May 2013

  12. 20140201-0228_Green Machine Florida Canyon Hourly Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Thibedeau, Joe

    2014-03-03

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Feb to 28 Feb 2014.

  13. 20140601-0630_Green Machine Florida Canyon Hourly Data

    SciTech Connect (OSTI)

    Thibedeau, Joe

    2014-06-30

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 June to 30 June 2014.

  14. 20140501-0531_Green Machine Florida Canyon Hourly Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Thibedeau, Joe

    2014-06-02

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 May to 31 May 2014.

  15. 20131101-1130_Green Machine Florida Canyon Hourly Data

    SciTech Connect (OSTI)

    Thibedeau, Joe

    2013-12-02

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Nov to 30 Nov 2013.

  16. 20140301-0331_Green Machine Florida Canyon Hourly Data

    SciTech Connect (OSTI)

    Thibedeau, Joe

    2014-04-07

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Mar to 31 Mar 2014.

  17. 20131001-1031_Green Machine Florida Canyon Hourly Data

    SciTech Connect (OSTI)

    Thibedeau, Joe

    2013-11-05

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 1 Oct 2013 to 31 Oct 2013.

  18. 20130901-0930_Green Machine Florida Canyon Hourly Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Thibedeau, Joe

    2013-10-25

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 1 September 2013 to 30 September 2013.

  19. 20130801-0831_Green Machine Florida Canyon Hourly Data

    SciTech Connect (OSTI)

    Vanderhoff, Alex

    2013-09-10

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 8/1/13 to 8/31/13.

  20. 20140501-0531_Green Machine Florida Canyon Hourly Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Thibedeau, Joe

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 May to 31 May 2014.

  1. 20140101-0131_Green Machine Florida Canyon Hourly Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Thibedeau, Joe

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Jan to 31 Jan 2014.

  2. 20130501-20130531_Green Machine Florida Canyon Hourly Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Vanderhoff, Alex

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from May 2013

  3. 20130901-0930_Green Machine Florida Canyon Hourly Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Thibedeau, Joe

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 1 September 2013 to 30 September 2013.

  4. 20131001-1031_Green Machine Florida Canyon Hourly Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Thibedeau, Joe

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 1 Oct 2013 to 31 Oct 2013.

  5. 20140301-0331_Green Machine Florida Canyon Hourly Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Thibedeau, Joe

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Mar to 31 Mar 2014.

  6. 20131201-1231_Green Machine Florida Canyon Hourly Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Thibedeau, Joe

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Dec to 31 Dec 2013.

  7. 20140701-0731_Green Machine Florida Canyon Hourly Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Thibedeau, Joe

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 July to 31 July 2014.

  8. 20130801-0831_Green Machine Florida Canyon Hourly Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Vanderhoff, Alex

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 8/1/13 to 8/31/13.

  9. 20140201-0228_Green Machine Florida Canyon Hourly Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Thibedeau, Joe

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Feb to 28 Feb 2014.

  10. 20140601-0630_Green Machine Florida Canyon Hourly Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Thibedeau, Joe

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 June to 30 June 2014.

  11. 20131101-1130_Green Machine Florida Canyon Hourly Data

    DOE Data Explorer [Office of Scientific and Technical Information (OSTI)]

    Thibedeau, Joe

    Employing innovative product developments to demonstrate financial and technical viability of producing electricity from low temperature geothermal fluids, coproduced in a mining operation, by employing ElectraTherm's modular and mobile heat-to-power "micro geothermal" power plant with output capacity expected in the 30-70kWe range. The Green Machine is an Organic Rankine Cycle power plant. The Florida Canyon machine is powered by geothermal brine with air cooled condensing. The data provided is an hourly summary from 01 Nov to 30 Nov 2013.

  12. (Document Number)

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

    A TA-53 TOUR FORM/RADIOLOGICAL LOG (Send completed form to MS H831) _____________ _____________________________ _________________________________ Tour Date Purpose of Tour or Tour Title Start Time and Approximate Duration ___________________________ ______________ _______________________ _________________ Tour Point of Contact/Requestor Z# (if applicable) Organization/Phone Number Signature Locations Visited: (Check all that apply, and list any others not shown. Prior approval must be obtained

  13. Hour-by-Hour Cost Modeling of Optimized Central Wind-Based Water Electrolysis Production

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

    Hour-by-Hour Cost Modeling of Optimized Central Wind-Based Water Electrolysis Production Genevieve Saur (PI), Chris Ainscough (Presenter), Kevin Harrison, Todd Ramsden National Renewable Energy Laboratory January 17 th , 2013 This presentation does not contain any proprietary, confidential, or otherwise restricted information 2 Acknowledgements * This work was made possible by support from the U.S. Department of Energy's Fuel Cell Technologies Office within the Office of Energy Efficiency and

  14. Making Wind Energy Predictable: New Profilers Provide Hourly...

    Energy Savers

    Making Wind Energy Predictable: New Profilers Provide Hourly Forecasts Making Wind Energy Predictable: New Profilers Provide Hourly Forecasts May 11, 2016 - 6:48pm Addthis ...

  15. Webinar: BioenergizeME Office Hours Webinar: Biomass Basics ...

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

    Biomass Basics Webinar: BioenergizeME Office Hours Webinar: Biomass Basics Webinar: BioenergizeME Office Hours Webinar: Biomass Basics biomasbasicswebinar20150827.pdf (3.05 MB) ...

  16. NREL: Education Center - Hours, Directions, and Contact Information

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

    Hours, Directions, and Contact Information An aerial photo of a tan Education Center. NREL's Education Center Credit: NREL 18591 Hours The Education Center is open Monday through...

  17. Energy Savings Performance Contracting 14-hour Agency Onsite...

    Energy Savers

    Energy Savings Performance Contracting 14-hour Agency Onsite Workshop Energy Savings Performance Contracting 14-hour Agency Onsite Workshop January 20, 2016 8:30AM PST to January...

  18. Quantum random number generator

    DOE Patents [OSTI]

    Pooser, Raphael C.

    2016-05-10

    A quantum random number generator (QRNG) and a photon generator for a QRNG are provided. The photon generator may be operated in a spontaneous mode below a lasing threshold to emit photons. Photons emitted from the photon generator may have at least one random characteristic, which may be monitored by the QRNG to generate a random number. In one embodiment, the photon generator may include a photon emitter and an amplifier coupled to the photon emitter. The amplifier may enable the photon generator to be used in the QRNG without introducing significant bias in the random number and may enable multiplexing of multiple random numbers. The amplifier may also desensitize the photon generator to fluctuations in power supplied thereto while operating in the spontaneous mode. In one embodiment, the photon emitter and amplifier may be a tapered diode amplifier.

  19. LED Solutions for the Dark Hours

    Energy Savers

    technologies 5 LEDs for Street and Roadway Lighting Portland, OR Philadelphia, PA New York, NY Kansas City, MO 6 Boston Las Vegas Seattle Number of LED Replacements to Date (4...

  20. ARM - Historical Operational Statistics

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

    Operational Statistics 2016 Quarterly Reports First Quarter (PDF) Second Quarter (PDF) Third Quarter (PDF) Fourth Quarter (PDF) Past Quarterly Reports Historical Statistics Field Campaigns Operational Visitors and Accounts Data Archive and Usage (October 1995 - Present) Historical Operational Statistics The reporting requirements for DOE national user facilities are based on time. These requirements concern the actual hours of operation (ACTUAL) and the established maximum operation or uptime

  1. Property:OutagePhoneNumber | Open Energy Information

    Open Energy Information (Open El) [EERE & EIA]

    OutagePhoneNumber Jump to: navigation, search Property Name OutagePhoneNumber Property Type String Description An outage hotline or 24-hour customer service number Note: uses...

  2. Exhibit Hall Floor Plan & Hours | Department of Energy

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

    Exhibit Hall Floor Plan & Hours Exhibit Hall Floor Plan & Hours Exhibit Hall Floor Plan & Hours Exhibitor Move-in Hours Tuesday, May 16 9:00 am - 5:00 pm Wednesday, May 17 7:00 am - Noon Exhibit Hall Hours Wednesday, May 17 Opens: Noon - 3:45 pm (Lunch will be served) Closes: 3:45 pm - 5:00 pm) Reopens: 5:00 pm - 7:00 pm (Welcome Reception) Thursday, May 18 Opens: 7:00 am - Noon (Breakfast will be served) Closes: Noon (Lunch will be served) Exhibitor Move-out Hours Thursday, May 18

  3. Fermilab | Visit Fermilab | Hours, Maps and Directions

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

    Map and directions Check the Fermilab home page for our latest news and a calendar of events, which also includes days that our main building and exhibits are closed. Map of Fermilab Fermilab site map (pdf) Directions to Fermilab Fermilab's main entrance is located at the intersection of Kirk Road and Pine Street in Batavia, Illinois, about 45 miles west of Chicago. Delivery trucks need to use the entrance at Kirk Road and Wilson Street. There is no street number assigned to this entrance

  4. DOE's Office of Science Awards 18 Million Hours of Supercomputing...

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

    DOE's Office of Science Awards 18 Million Hours of Supercomputing Time to 15 Teams for Large-Scale Scientific Computing DOE's Office of Science Awards 18 Million Hours of...

  5. After-hours, weekend changes through East Jemez road vehicle...

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

    After-hours, weekend changes through East Jemez Road Vehicle Access Portal After-hours, weekend changes through East Jemez road vehicle access portal begin June 18 All vehicles ...

  6. Oak Ridge: Approaching 4 Million Safe Work Hours | Department...

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

    Oak Ridge: Approaching 4 Million Safe Work Hours Oak Ridge: Approaching 4 Million Safe Work Hours February 27, 2013 - 12:00pm Addthis Mike Tidwell performs a leak check and ...

  7. DOE's Office of Science Awards 18 Million Hours of Supercomputing...

    Energy Savers

    DOE's Office of Science Awards 18 Million Hours of Supercomputing Time to 15 Teams for ... announced today that DOE's Office of Science has awarded a total of 18.2 million hours ...

  8. 1999 Commercial Buildings Characteristics--Off-Hour Equipment...

    U.S. Energy Information Administration (EIA) (indexed site)

    such programs (Figure 1). About the same amount of floorspace had either heating system or cooling system off-hour reduction. Off-hour reduction was least for office...

  9. BioenergizeME Office Hours Webinar: Integrating Bioenergy into...

    Energy Savers

    Office Hours Webinar: Integrating Bioenergy into the 9th-12th Grade Classroom BioenergizeME Office Hours Webinar: Integrating Bioenergy into the 9th-12th Grade Classroom ...

  10. ARM - NSA Operations

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

    AlaskaNSA Operations NSA Related Links Virtual Tour Facilities and Instruments Barrow Atqasuk Oliktok Point (AMF3) ES&H Guidance Statement Operations Science Field Campaigns Visiting the Site NSA Fact Sheet Images Information for Guest Scientists Contacts NSA Operations Barrow Facility Instrumentation at the Barrow facility operates 7 days a week, 24 hours a day, year around. The instrumentation is routinely maintained using an extensive "daily rounds" checklist 5 days a week,

  11. DOE Awards Over a Billion Supercomputing Hours to Address Scientific

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

    Challenges | Department of Energy Over a Billion Supercomputing Hours to Address Scientific Challenges DOE Awards Over a Billion Supercomputing Hours to Address Scientific Challenges January 26, 2010 - 12:00am Addthis Washington, DC. - The U.S. Department of Energy announced today that approximately 1.6 billion supercomputing processor hours have been awarded to 69 cutting-edge research projects through the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program.

  12. Hour of Code sparks interest in computer science

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

    STEM skills Community Connections: Your link to news and opportunities from Los Alamos National Laboratory Latest Issue:November 2, 2016 all issues All Issues » submit Hour of Code sparks interest in computer science Taking the mystery out of programming February 1, 2016 Hour of Code participants work their way through fun computer programming tutorials. Hour of Code participants work their way through fun computer programming tutorials. Contacts Community Programs Director Kathy Keith Email

  13. BioenergizeME Office Hours Webinar: Integrating Bioenergy into the

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

    9th-12th Grade Classroom | Department of Energy BioenergizeME Office Hours Webinar: Integrating Bioenergy into the 9th-12th Grade Classroom BioenergizeME Office Hours Webinar: Integrating Bioenergy into the 9th-12th Grade Classroom bioenergize_me_ngss_20151210.pdf (5.35 MB) More Documents & Publications Webinar: BioenergizeME Office Hours Webinar: Biomass Basics Webinar: BioenergizeME Office Hours Webinar: Guide to the 2016 BioenergizeME Infographic Challenge BioenergizeME Infographic

  14. Pay and Leave Administration and Hours of Duty

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

    1996-09-30

    The order establishes policy, requirements and responsibilities for the management of pay, including overtime and compensatory time, leave administration, and hours of duty.

  15. Department of Energy's Paducah Site Reaches Million-Hour Safety...

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

    environmental risk. The LATA Environmental Services of Kentucky Team, the Department's prime cleanup contractor, in October reached a milestone of 1 million hours without a lost...

  16. Hospital Triage in First Hours After Nuclear or Radiological...

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

    Hospital Triage in the First 24 Hours after a Nuclear or Radiological Disaster Medical professionals with the Radiation Emergency Assistance CenterTraining Site (REACTS) at the...

  17. Reformulated Gasoline Use Under the 8-Hour Ozone Rule

    Reports and Publications

    2002-01-01

    This paper focuses on the impact on gasoline price and supply when additional ozone non-attainment areas come under the new 8-hour ozone standard.

  18. DOE Publishes 20K Hour Testing Results for 2008 GATEWAY Bridge Installation

    Energy Savers

    | Department of Energy K Hour Testing Results for 2008 GATEWAY Bridge Installation DOE Publishes 20K Hour Testing Results for 2008 GATEWAY Bridge Installation October 9, 2014 - 12:00pm Addthis The U.S. Department of Energy has released a report on the longer-term performance of an LED lighting system that was installed on the I-35W Bridge in Minneapolis in September 2008 and represents one of the country's oldest continuously operated exterior LED lighting installations. The report is a

  19. Webinar: 20K Hour GATEWAY Testing Results for I-35W Bridge | Department of

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

    Energy 20K Hour GATEWAY Testing Results for I-35W Bridge Webinar: 20K Hour GATEWAY Testing Results for I-35W Bridge The U.S. Department of Energy has released a GATEWAY Demonstration report on the longer-term performance of an LED lighting system that was installed on the I-35W Bridge in Minneapolis in September 2008 and represents one of the country's oldest continuously operated exterior LED lighting installations. Prior to installation, two of the LED luminaires were tested, along with a

  20. Three-Stage Production Cost Modeling Approach for Evaluating the Benefits of Intra-Hour Scheduling between Balancing Authorities

    SciTech Connect (OSTI)

    Samaan, Nader A.; Milligan, Michael; Hunsaker, Matthew; Guo, Tao

    2015-07-30

    This paper introduces a Production Cost Modeling (PCM) approach to evaluate the benefits of intra-hour scheduling between Balancing Authorities (BAs). The system operation is modeled in a three-stage sequential manner: day ahead (DA)-hour ahead (HA)-real time (RT). In addition to contingency reserve, each BA will need to carry out “up” and “down” load following and regulation reserve capacity requirements in the DA and HA time frames. In the real-time simulation, only contingency and regulation reserves are carried out as load following is deployed. To model current real-time operation with hourly schedules, a new constraint was introduced to force each BA net exchange schedule deviation from HA schedules to be within NERC ACE limits. Case studies that investigate the benefits of moving from hourly exchange schedules between WECC BAs into 10-min exchange schedules under two different levels of wind and solar penetration (11% and 33%) are presented.

  1. Oak Ridge: Approaching 4 Million Safe Work Hours

    Energy.gov [DOE]

    Workers at URS | CH2M Oak Ridge (UCOR), the prime contractor for EM’s Oak Ridge cleanup, are approaching a milestone of 4 million safe work hours without a lost time away incident.

  2. Delayed Start or Cancellation of Business Hours | Argonne National...

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

    the hours of 6:30 a.m. to 6:30 p.m. should report to work as usual. Depending on their job duties and directives from their line management, some employees may be required to...

  3. Pay and Leave Administration and Hours of Duty

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

    2011-01-19

    The order establishes requirements and responsibilities for the management of pay, including overtime pay and compensatory time, leave administration, time and attendance reporting, and hours of duty. Cancels DOE O 322.1B and DOE O 535.1

  4. Pay and Leave Administration and Hours of Duty

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

    2005-01-14

    This Order establishes requirements and responsibilities for the management of pay, including overtime and compensatory time, leave administration, and hours of duty. Cancels DOE O 322.1A. Canceled by DOE O 322.1C.

  5. Balancing Authority Cooperation Concepts - Intra-Hour Scheduling

    SciTech Connect (OSTI)

    Hunsaker, Matthew; Samaan, Nader; Milligan, Michael; Guo, Tao; Liu, Guangjuan; Toolson, Jacob

    2013-03-29

    The overall objective of this study was to understand, on an Interconnection-wide basis, the effects intra-hour scheduling compared to hourly scheduling. Moreover, the study sought to understand how the benefits of intra-hour scheduling would change by altering the input assumptions in different scenarios. This report describes results of three separate scenarios with differing key assumptions and comparing the production costs between hourly scheduling and 10-minute scheduling performance. The different scenarios were chosen to provide insight into how the estimated benefits might change by altering input assumptions. Several key assumptions were different in the three scenarios, however most assumptions were similar and/or unchanged among the scenarios.

  6. Commercial and Residential Hourly Load Data Question | OpenEI...

    Open Energy Information (Open El) [EERE & EIA]

    Commercial and Residential Hourly Load Data Question Home Hi, I saw that you were actively replying to the questions on that page, so thought I'd contact you to ask about the data...

  7. DOE ZERH Virtual Office Hours (4 of 4)

    Energy.gov [DOE]

    TitleZERH Virtual Office Hours: Get the Answers You Need Quickly & EfficientlyDescriptionWhether you’re new to DOE Zero Energy Ready Home or have been involved for a few years, our partners...

  8. DOE ZERH Virtual Office Hours (2 of 4)

    Energy.gov [DOE]

    TitleZERH Virtual Office Hours: Get the Answers You Need Quickly & EfficientlyDescriptionWhether you’re new to DOE Zero Energy Ready Home or have been involved for a few years, our partners...

  9. DOE ZERH Virtual Office Hours (3 of 4)

    Energy.gov [DOE]

    TitleZERH Virtual Office Hours: Get the Answers You Need Quickly & EfficientlyDescriptionWhether you’re new to DOE Zero Energy Ready Home or have been involved for a few years, our partners...

  10. DOE ZERH Virtual Office Hours (1 of 4)

    Energy.gov [DOE]

    TitleZERH Virtual Office Hours: Get the Answers You Need Quickly & EfficientlyDescriptionWhether you’re new to DOE Zero Energy Ready Home or have been involved for a few years, our partners...

  11. Jefferson Lab Groups Encourage Digital Literacy Through Worldwide 'Hour

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

    of Code' Campaign | Jefferson Lab Groups Encourage Digital Literacy Through Worldwide 'Hour of Code' Campaign Dana Cochran, Jefferson Lab staff member, helps students as they participate in a coding activity. Dana Cochran, Jefferson Lab staff member, helps students as they participate in a coding activity. Jefferson Lab Groups Encourage Digital Literacy Through Worldwide 'Hour of Code' Campaign To raise awareness of the need for digital literacy and a basic understanding of computer science,

  12. Ames Laboratory Scientists Receive Hours through DOE's INCITE Program | The

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

    Ames Laboratory Ames Laboratory Scientists Receive Hours through DOE's INCITE Program Scientist Mark Gordon was awarded 200 million processor hours through the INCITE program to work on a research project utilizing Argonne National Laboratory's supercomputer. Gordon and his co-investigators will study the behaviors of liquids and their solutes specifically water and ionic liquids. For more information about the team's work with INCITE visit Argonne Leadership Computing Facility. January 12,

  13. Atmospheric Radiation Measurement program climate research facility operations quarterly report.

    SciTech Connect (OSTI)

    Sisterson, D. L.; Decision and Information Sciences

    2006-09-06

    Individual raw data streams from instrumentation at the Atmospheric Radiation Measurement (ARM) Program Climate Research Facility (ACRF) fixed and mobile sites are collected and sent to the Data Management Facility (DMF) at Pacific Northwest National Laboratory (PNNL) for processing in near real time. Raw and processed data are then sent daily to the ACRF Archive, where they are made available to users. For each instrument, we calculate the ratio of the actual number of data records received daily at the Archive to the expected number of data records. The results are tabulated by (1) individual data stream, site, and month for the current year and (2) site and fiscal year dating back to 1998. The U.S. Department of Energy requires national user facilities to report time-based operating data. The requirements concern the actual hours of operation (ACTUAL); the estimated maximum operation or uptime goal (OPSMAX), which accounts for planned downtime; and the VARIANCE [1-(ACTUAL/OPSMAX)], which accounts for unplanned downtime. The OPSMAX time for the third quarter for the Southern Great Plains (SGP) site is 2,074.80 hours (0.95 x 2,184 hours this quarter). The OPSMAX for the North Slope Alaska (NSA) locale is 1,965.60 hours (0.90 x 2,184), and that for the Tropical Western Pacific (TWP) locale is 1,856.40 hours (0.85 x 2,184). The OPSMAX time for the ARM Mobile Facility (AMF) is 2,074.80 hours (0.95 x 2,184). The differences in OPSMAX performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure OPSMAX for each instrument or data stream. Data availability reported here refers to the average of the individual, continuous data streams that have been received by the Archive. Data not at the Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Therefore, data availability is directly related to individual instrument uptime. Thus, the average percent of data in the Archive

  14. Operating Experience Review of Tritium-in-Water Monitors

    SciTech Connect (OSTI)

    S. A. Bruyere; L. C. Cadwallader

    2011-09-01

    Monitoring tritium facility and fusion experiment effluent streams is an environmental safety requirement. This paper presents data on the operating experience of a solid scintillant monitor for tritium in effluent water. Operating experiences were used to calculate an average monitor failure rate of 4E-05/hour for failure to function. Maintenance experiences were examined to find the active repair time for this type of monitor, which varied from 22 minutes for filter replacement to 11 days of downtime while waiting for spare parts to arrive on site. These data support planning for monitor use; the number of monitors needed, allocating technician time for maintenance, inventories of spare parts, and other issues.

  15. Final environmental impact statement for the construction and operation of an independent spent fuel storage installation to store the Three Mile Island Unit 2 spent fuel at the Idaho National Engineering and Environmental Laboratory. Docket Number 72-20

    SciTech Connect (OSTI)

    1998-03-01

    This Final Environmental Impact Statement (FEIS) contains an assessment of the potential environmental impacts of the construction and operation of an Independent Spent Fuel Storage Installation (ISFSI) for the Three Mile Island Unit 2 (TMI-2) fuel debris at the Idaho National Engineering and Environmental laboratory (INEEL). US Department of Energy-Idaho Operations Office (DOE-ID) is proposing to design, construct, and operate at the Idaho Chemical Processing Plant (ICPP). The TMI-2 fuel debris would be removed from wet storage, transported to the ISFSI, and placed in storage modules on a concrete basemat. As part of its overall spent nuclear fuel (SNF) management program, the US DOE has prepared a final programmatic environmental impact statement (EIS) that provides an overview of the spent fuel management proposed for INEEL, including the construction and operation of the TMI-2 ISFSI. In addition, DOE-ID has prepared an environmental assessment (EA) to describe the environmental impacts associated with the stabilization of the storage pool and the construction/operation of the ISFSI at the ICPP. As provided in NRC`s NEPA procedures, a FEIS of another Federal agency may be adopted in whole or in part in accordance with the procedures outlined in 40 CFR 1506.3 of the regulations of the Council on Environmental Quality (CEQ). Under 40 CFR 1506.3(b), if the actions covered by the original EIS and the proposed action are substantially the same, the agency adopting another agency`s statement is not required to recirculate it except as a final statement. The NRC has determined that its proposed action is substantially the same as actions considered in DOE`s environmental documents referenced above and, therefore, has elected to adopt the DOE documents as the NRC FEIS.

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

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

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

  17. NV Energy Large-Scale Photovoltaic Integration Study: Intra-Hour Dispatch and AGC Simulation

    SciTech Connect (OSTI)

    Lu, Shuai; Etingov, Pavel V.; Meng, Da; Guo, Xinxin; Jin, Chunlian; Samaan, Nader A.

    2013-01-02

    The uncertainty and variability with photovoltaic (PV) generation make it very challenging to balance power system generation and load, especially under high penetration cases. Higher reserve requirements and more cycling of conventional generators are generally anticipated for large-scale PV integration. However, whether the existing generation fleet is flexible enough to handle the variations and how well the system can maintain its control performance are difficult to predict. The goal of this project is to develop a software program that can perform intra-hour dispatch and automatic generation control (AGC) simulation, by which the balancing operations of a system can be simulated to answer the questions posed above. The simulator, named Electric System Intra-Hour Operation Simulator (ESIOS), uses the NV Energy southern system as a study case, and models the system’s generator configurations, AGC functions, and operator actions to balance system generation and load. Actual dispatch of AGC generators and control performance under various PV penetration levels can be predicted by running ESIOS. With data about the load, generation, and generator characteristics, ESIOS can perform similar simulations and assess variable generation integration impacts for other systems as well. This report describes the design of the simulator and presents the study results showing the PV impacts on NV Energy real-time operations.

  18. Differential Angstrom model for predicting insolation from hours of sunshine

    SciTech Connect (OSTI)

    Yeboah-Amankwah, D.; Agyeman, K.

    1990-01-01

    The Angstrom model for predicting insolation is limited in scope because it gives equal weighting to sunshine hours recorded at any time of the day. The differential Angstrom model presented in this paper removes this limitation and relates insolation, q{sub j}, in the j{sup th} hour to the sunshine duration, n{sub j}, of the same period by the equation: q{sub j} = a{sub j} + b{sub j}. By regression analysis of monthly data, the set of constants a{sub j} and b{sub j} for each hour of each month of the year can be determined. Thus, using the appropriate set of a and b regression coefficients, any sunshine data can be transformed to insolation. The sum of the equation over a day gives the daily insolation from which monthly means can be calculated. The method has been applied to the 1986 and 1988 sunshine data recorded at the University of Papua New Guinea to predict the observed insolation to within 3.5%. The differential Angstrom method has applications in places which have much recorded data on hours of sunshine but have limited observed insolation data.

  19. Pay and Leave Administration and Hours of Duty

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

    2011-01-19

    The order establishes requirements and responsibilities for the management of pay, including overtime pay and compensatory time, leave administration, time and attendance reporting, and hours of duty. Admin Chg 1, dated 5-10-12, supersedes DOE O 322.1C.

  20. Number | Open Energy Information

    Open Energy Information (Open El) [EERE & EIA]

    Property:NumOfPlants Property:NumProdWells Property:NumRepWells Property:Number of Color Cameras Property:Number of Devices Deployed Property:Number of Plants included in...

  1. Free-Piston Stirling Engine/linear alternator 1000-hour endurance test

    SciTech Connect (OSTI)

    Rauch, J.; Dochat, G.

    1985-03-01

    The Free-Piston Stirling Engine (FPSE) has the potential to be a long-lived, highly reliable, power conversion device attractive for many product applications such as space, residential or remote-site power. The purpose of endurance testing the FPSE was to demonstrate its potential for long life. The endurance program was directed at obtaining 1000 operational hours under various test conditions: low power, full stroke, duty cycle and stop/start. Critical performance parameters were measured to note any change and/or trend. Inspections were conducted to measure and compare critical seal/bearing clearances. The engine performed well throughout the program, completing more than 1100 hours. Hardware inspection, including the critical clearances, showed no significant change in hardware or clearance dimensions. The performance parameters did not exhibit any increasing or decreasing trends. The test program confirms the potential for long-life FPSE applications.

  2. NSR Key Number Retrieval

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

    NSR Key Number Retrieval Pease enter key in the box Submit

  3. Atmospheric Radiation Measurement program climate research facility operations quarterly report October 1 - December 31, 2008.

    SciTech Connect (OSTI)

    Sisterson, D. L.

    2009-01-15

    Individual raw data streams from instrumentation at the Atmospheric Radiation Measurement (ARM) Program Climate Research Facility (ACRF) fixed and mobile sites are collected and sent to the Data Management Facility (DMF) at Pacific Northwest National Laboratory (PNNL) for processing in near real-time. Raw and processed data are then sent daily to the ACRF Archive, where they are made available to users. For each instrument, they calculate the ratio of the actual number of data records received daily at the Archive to the expected number of data records. The results are tabulated by (1) individual data stream, site, and month for the current year and (2) site and fiscal year (FY) dating back to 1998. The US Department of Energy (DOE) requires national user facilities to report time-based operating data. The requirements concern the actual hours of operation (ACTUAL); the estimated maximum operation or uptime goal (OPSMAX), which accounts for planned downtime; and the VARIANCE [1-(ACTUAL/OPSMAX)], which accounts for unplanned downtime. The OPSMAX time for the first quarter of FY 2009 for the Southern Great Plains (SGP) site is 2,097.60 hours (0.95 x 2,208 hours this quarter). The OPSMAX for the North Slope Alaska (NSA) locale is 1,987.20 hours (0.90 x 2,208), and for the Tropical Western Pacific (TWP) locale is 1,876.80 hours (0.85 x 2,208). The OPSMAX time for the ARM Mobile Facility (AMF) is not reported this quarter because the data have not yet been released from China to the DMF for processing. The differences in OPSMAX performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure OPSMAX for each instrument or data stream. Data availability reported here refers to the average of the individual, continuous data streams that have been received by the Archive. Data not at the Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Therefore, data availability is

  4. 20K Hour GATEWAY Testing Results for I-35W Bridge Webinar

    Energy.gov [DOE]

    The U.S. Department of Energy released a GATEWAY Demonstration report on the longer-term performance of an LED lighting system that was installed on the I-35W Bridge in Minneapolis in September 2008 and represents one of the country’s oldest continuously operated exterior LED lighting installations. Prior to installation, two of the LED luminaires were tested, along with a third luminaire that was not installed on the bridge but was tested for 6,000 hours in a laboratory for comparison purposes.

  5. Analysis of Sub-Hourly Ramping Impacts of Wind Energy and Balancing Area Size: Preprint

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

    Sub-Hourly Ramping Impacts of Wind Energy and Balancing Area Size Preprint M. Milligan National Renewable Energy Laboratory B. Kirby Oak Ridge National Laboratory To be presented at WindPower 2008 Houston, Texas June 1-4, 2008 Conference Paper NREL/CP-500-43434 June 2008 NREL is operated by Midwest Research Institute ● Battelle Contract No. DE-AC36-99-GO10337 NOTICE The submitted manuscript has been offered by an employee of the Midwest Research Institute (MRI), a contractor of the US

  6. Notices Total Estimated Number of Annual

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

    372 Federal Register / Vol. 78, No. 181 / Wednesday, September 18, 2013 / Notices Total Estimated Number of Annual Burden Hours: 10,128. Abstract: Enrollment in the Federal Student Aid (FSA) Student Aid Internet Gateway (SAIG) allows eligible entities to securely exchange Title IV, Higher Education Act (HEA) assistance programs data electronically with the Department of Education processors. Organizations establish Destination Point Administrators (DPAs) to transmit, receive, view and update

  7. Big Numbers | Jefferson Lab

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

    Big Numbers Big Numbers May 16, 2011 This article has some numbers in it. In principle, numbers are just language, like English or Japanese. Nevertheless, it is true that not everyone is comfortable or facile with numbers and may be turned off by too many of them. To those people, I apologize that this article pays less attention to maximizing the readership than some I do. But sometimes it's just appropriate to indulge one's self, so here goes. When we discuss the performance of some piece of

  8. Atmospheric Radiation Measurement Program Climate Research Facility Operations Quarterly Report. October 1 - December 31, 2010.

    SciTech Connect (OSTI)

    Sisterson, D. L.

    2011-02-01

    Individual raw datastreams from instrumentation at the Atmospheric Radiation Measurement (ARM) Climate Research Facility fixed and mobile sites are collected and sent to the Data Management Facility (DMF) at Pacific Northwest National Laboratory (PNNL) for processing in near-real time. Raw and processed data are then sent approximately daily to the ARM Archive, where they are made available to users. For each instrument, we calculate the ratio of the actual number of processed data records received daily at the Archive to the expected number of data records. The results are tabulated by (1) individual datastream, site, and month for the current year and (2) site and fiscal year (FY) dating back to 1998. The U.S. Department of Energy (DOE) requires national user facilities to report time-based operating data. The requirements concern the actual hours of operation (ACTUAL); the estimated maximum operation or uptime goal (OPSMAX), which accounts for planned downtime; and the VARIANCE [1 - (ACTUAL/OPSMAX)], which accounts for unplanned downtime. The OPSMAX time for the first quarter of FY2010 for the Southern Great Plains (SGP) site is 2097.60 hours (0.95 x 2208 hours this quarter). The OPSMAX for the North Slope Alaska (NSA) locale is 1987.20 hours (0.90 x 2208) and for the Tropical Western Pacific (TWP) locale is 1876.80 hours (0.85 x 2208). The first ARM Mobile Facility (AMF1) deployment in Graciosa Island, the Azores, Portugal, continued through this quarter, so the OPSMAX time this quarter is 2097.60 hours (0.95 x 2208). The second ARM Mobile Facility (AMF2) began deployment this quarter to Steamboat Springs, Colorado. The experiment officially began November 15, but most of the instruments were up and running by November 1. Therefore, the OPSMAX time for the AMF2 was 1390.80 hours (.95 x 1464 hours) for November and December (61 days). The differences in OPSMAX performance reflect the complexity of local logistics and the frequency of extreme weather events. It

  9. Mirant: Ambient 24 Hour SO2 Values: Model vs Monitor | Department...

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

    Ambient 24 Hour SO2 Values: Model vs Monitor Mirant: Ambient 24 Hour SO2 Values: Model vs Monitor Docket No. EO-05-01: Mirant: Ambient 24 Hour SO2 Values: Model vs Monitor, March ...

  10. Florida Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Florida Natural Gas Number of Oil Wells (Number of ... Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Florida ...

  11. Analysis of clear hour solar irradiation for seven Canadian stations

    SciTech Connect (OSTI)

    Garrison, J.; Sahami, K.

    1995-12-31

    Hourly global and diffuse irradiation and corresponding surface meteorological data have been analyzed for the seven Canadian stations at Edmonton, Goose Bay, Montreal, Port Hardy, Resolute, Toronto, and Winnipeg. The variation of the most probable clear hour values of clearness index k{sub t}, diffuse index k{sub d}, direct beam index k{sub b}, and Angstrom turbidity coefficient {beta} with solar elevation, atmospheric precipitable water, and snow depth are obtained. Values of these quantities are presented which are consistent with the attenuation and scattering of solar radiation by the atmosphere which is expected. The most probable values of {beta} tend to be lower than the average values of {beta} recently reported by Gueymard. The data indicate a drift in the calibration of the instruments used for measurements of the irradiation data for the stations at Goose Bay and Resolute. The data for the other five stations indicate that the instrument calibration is maintained over the years of the data. 4 refs., 8 figs., 5 tabs.

  12. BioenergizeME Office Hours Webinar: Biomass Basics

    Energy.gov [DOE]

    Many students haven’t thought much about biomass as an option for generating electricity, transportation fuels, and other products. The Biomass Basics Webinar provides general information about bioenergy, its creation, and its potential uses, and is designed to assist teams competing in the 2016 BioenergizeME Infographic Challenge. This challenge, hosted by the U.S. Department of Energy’s Bioenergy Technologies Office (BETO), is a competition for high school students to learn about bioenergy, create infographics to present what they have learned, and share their infographics on social media. This webinar is part of the BioenergizeME Office Hours webinar series developed by BETO in conjunction with the 2016 BioenergizeME Infographic Challenge.

  13. Moab Project Safely Logs 2 Million Work Hours | Department of...

    Energy Savers

    Donald Metzler, Moab Federal Project Director, (970) 257-2115 Wendee Ryan, S&K Aerospace Public Affairs Manager, (970) 257-2145 (Grand Junction, CO) - The number 1,584 may not mean ...

  14. Mailing Addresses and Information Numbers for Operations, Field...

    Energy Savers

    Berkeley National Laboratory 1 Cyclotron Road Berkeley, CA 94720 510-486-5784 U.S. ... Los Alamos Site Office 3747 West Jemez Road Los Alamos, NM 87544 505-667-5491 U.S. ...

  15. Mirant: Case 67a: Units 3 & 4 & 5 at Max Load for 12 hours and...

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

    Case 67a: Units 3 & 4 & 5 at Max Load for 12 hours and at Min Load for 12 hours Mirant: Case 67a: Units 3 & 4 & 5 at Max Load for 12 hours and at Min Load for 12 hours Docket No. ...

  16. Florida Natural Gas Number of Commercial Consumers (Number of...

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Florida Natural Gas Number of Commercial ... Referring Pages: Number of Natural Gas Commercial Consumers Florida Number of Natural Gas ...

  17. Florida Natural Gas Number of Industrial Consumers (Number of...

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Florida Natural Gas Number of Industrial ... Referring Pages: Number of Natural Gas Industrial Consumers Florida Number of Natural Gas ...

  18. Florida Natural Gas Number of Residential Consumers (Number of...

    Gasoline and Diesel Fuel Update

    Residential Consumers (Number of Elements) Florida Natural Gas Number of Residential ... Referring Pages: Number of Natural Gas Residential Consumers Florida Number of Natural Gas ...

  19. New York Natural Gas Number of Commercial Consumers (Number of...

    Annual Energy Outlook

    Commercial Consumers (Number of Elements) New York Natural Gas Number of Commercial ... Referring Pages: Number of Natural Gas Commercial Consumers New York Number of Natural Gas ...

  20. New Mexico Natural Gas Number of Commercial Consumers (Number...

    Gasoline and Diesel Fuel Update

    Commercial Consumers (Number of Elements) New Mexico Natural Gas Number of Commercial ... Referring Pages: Number of Natural Gas Commercial Consumers New Mexico Number of Natural ...

  1. North Dakota Natural Gas Number of Commercial Consumers (Number...

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) North Dakota Natural Gas Number of Commercial ... Referring Pages: Number of Natural Gas Commercial Consumers North Dakota Number of Natural ...

  2. Scalable tuning of building models to hourly data

    SciTech Connect (OSTI)

    Garrett, Aaron; New, Joshua Ryan

    2015-03-31

    Energy models of existing buildings are unreliable unless calibrated so they correlate well with actual energy usage. Manual tuning requires a skilled professional, is prohibitively expensive for small projects, imperfect, non-repeatable, non-transferable, and not scalable to the dozens of sensor channels that smart meters, smart appliances, and cheap/ubiquitous sensors are beginning to make available today. A scalable, automated methodology is needed to quickly and intelligently calibrate building energy models to all available data, increase the usefulness of those models, and facilitate speed-and-scale penetration of simulation-based capabilities into the marketplace for actualized energy savings. The "Autotune'' project is a novel, model-agnostic methodology which leverages supercomputing, large simulation ensembles, and big data mining with multiple machine learning algorithms to allow automatic calibration of simulations that match measured experimental data in a way that is deployable on commodity hardware. This paper shares several methodologies employed to reduce the combinatorial complexity to a computationally tractable search problem for hundreds of input parameters. Furthermore, accuracy metrics are provided which quantify model error to measured data for either monthly or hourly electrical usage from a highly-instrumented, emulated-occupancy research home.

  3. Scalable tuning of building models to hourly data

    DOE PAGES-Beta [OSTI]

    Garrett, Aaron; New, Joshua Ryan

    2015-03-31

    Energy models of existing buildings are unreliable unless calibrated so they correlate well with actual energy usage. Manual tuning requires a skilled professional, is prohibitively expensive for small projects, imperfect, non-repeatable, non-transferable, and not scalable to the dozens of sensor channels that smart meters, smart appliances, and cheap/ubiquitous sensors are beginning to make available today. A scalable, automated methodology is needed to quickly and intelligently calibrate building energy models to all available data, increase the usefulness of those models, and facilitate speed-and-scale penetration of simulation-based capabilities into the marketplace for actualized energy savings. The "Autotune'' project is a novel, model-agnosticmore » methodology which leverages supercomputing, large simulation ensembles, and big data mining with multiple machine learning algorithms to allow automatic calibration of simulations that match measured experimental data in a way that is deployable on commodity hardware. This paper shares several methodologies employed to reduce the combinatorial complexity to a computationally tractable search problem for hundreds of input parameters. Furthermore, accuracy metrics are provided which quantify model error to measured data for either monthly or hourly electrical usage from a highly-instrumented, emulated-occupancy research home.« less

  4. Scalable Tuning of Building Models to Hourly Data

    SciTech Connect (OSTI)

    Garrett, Aaron; New, Joshua Ryan

    2015-01-01

    Energy models of existing buildings are unreliable unless calibrated so they correlate well with actual energy usage. Manual tuning requires a skilled professional, is prohibitively expensive for small projects, imperfect, non-repeatable, non-transferable, and not scalable to the dozens of sensor channels that smart meters, smart appliances, and cheap/ubiquitous sensors are beginning to make available today. A scalable, automated methodology is needed to quickly and intelligently calibrate building energy models to all available data, increase the usefulness of those models, and facilitate speed-and-scale penetration of simulation-based capabilities into the marketplace for actualized energy savings. The ``Autotune'' project is a novel, model-agnostic methodology which leverages supercomputing, large simulation ensembles, and big data mining with multiple machine learning algorithms to allow automatic calibration of simulations that match measured experimental data in a way that is deployable on commodity hardware. This paper shares several methodologies employed to reduce the combinatorial complexity to a computationally tractable search problem for hundreds of input parameters. Accuracy metrics are provided which quantify model error to measured data for either monthly or hourly electrical usage from a highly-instrumented, emulated-occupancy research home.

  5. Report number codes

    SciTech Connect (OSTI)

    Nelson, R.N.

    1985-05-01

    This publication lists all report number codes processed by the Office of Scientific and Technical Information. The report codes are substantially based on the American National Standards Institute, Standard Technical Report Number (STRN)-Format and Creation Z39.23-1983. The Standard Technical Report Number (STRN) provides one of the primary methods of identifying a specific technical report. The STRN consists of two parts: The report code and the sequential number. The report code identifies the issuing organization, a specific program, or a type of document. The sequential number, which is assigned in sequence by each report issuing entity, is not included in this publication. Part I of this compilation is alphabetized by report codes followed by issuing installations. Part II lists the issuing organization followed by the assigned report code(s). In both Parts I and II, the names of issuing organizations appear for the most part in the form used at the time the reports were issued. However, for some of the more prolific installations which have had name changes, all entries have been merged under the current name.

  6. Quantum random number generation

    DOE PAGES-Beta [OSTI]

    Ma, Xiongfeng; Yuan, Xiao; Cao, Zhu; Zhang, Zhen; Qi, Bing

    2016-06-28

    Here, quantum physics can be exploited to generate true random numbers, which play important roles in many applications, especially in cryptography. Genuine randomness from the measurement of a quantum system reveals the inherent nature of quantumness -- coherence, an important feature that differentiates quantum mechanics from classical physics. The generation of genuine randomness is generally considered impossible with only classical means. Based on the degree of trustworthiness on devices, quantum random number generators (QRNGs) can be grouped into three categories. The first category, practical QRNG, is built on fully trusted and calibrated devices and typically can generate randomness at amore » high speed by properly modeling the devices. The second category is self-testing QRNG, where verifiable randomness can be generated without trusting the actual implementation. The third category, semi-self-testing QRNG, is an intermediate category which provides a tradeoff between the trustworthiness on the device and the random number generation speed.« less

  7. DOE/ID-Number

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

    76 Idaho National Laboratory Radiological Response Training Range Environmental Assessment Final October 2010 DOE/EA-1776 Idaho National Laboratory Radiological Response Training Range Environmental Assessment Final October 2010 Prepared for the U.S. Department of Energy Idaho Operations Office i CONTENTS GLOSSARY ................................................................................................................................................ iii EXECUTIVE SUMMARY

  8. DOE/ID-Number

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

    822 Idaho National Laboratory Stand-Off Experiment (SOX) Range Environmental Assessment Final March 2011 DOE/EA-1822 Idaho National Laboratory Stand-Off Experiment (SOX) Range Environmental Assessment Final March 2011 Prepared for the U.S. Department of Energy Idaho Operations Office i CONTENTS ACRONYMS ............................................................................................................................................... iii GLOSSARY

  9. Customer Strategies for Responding to Day-Ahead Market HourlyElectricity Pricing

    SciTech Connect (OSTI)

    Goldman, Chuck; Hopper, Nicole; Bharvirkar, Ranjit; Neenan,Bernie; Boisvert, Dick; Cappers, Peter; Pratt, Donna; Butkins, Kim

    2005-08-25

    Real-time pricing (RTP) has been advocated as an economically efficient means to send price signals to customers to promote demand response (DR) (Borenstein 2002, Borenstein 2005, Ruff 2002). However, limited information exists that can be used to judge how effectively RTP actually induces DR, particularly in the context of restructured electricity markets. This report describes the second phase of a study of how large, non-residential customers' adapted to default-service day-ahead hourly pricing. The customers are located in upstate New York and served under Niagara Mohawk, A National Grid Company (NMPC)'s SC-3A rate class. The SC-3A tariff is a type of RTP that provides firm, day-ahead notice of hourly varying prices indexed to New York Independent System Operator (NYISO) day-ahead market prices. The study was funded by the California Energy Commission (CEC)'s PIER program through the Demand Response Research Center (DRRC). NMPC's is the first and longest-running default-service RTP tariff implemented in the context of retail competition. The mix of NMPC's large customers exposed to day-ahead hourly prices is roughly 30% industrial, 25% commercial and 45% institutional. They have faced periods of high prices during the study period (2000-2004), thereby providing an opportunity to assess their response to volatile hourly prices. The nature of the SC-3A default service attracted competitive retailers offering a wide array of pricing and hedging options, and customers could also participate in demand response programs implemented by NYISO. The first phase of this study examined SC-3A customers' satisfaction, hedging choices and price response through in-depth customer market research and a Constant Elasticity of Substitution (CES) demand model (Goldman et al. 2004). This second phase was undertaken to answer questions that remained unresolved and to quantify price response to a higher level of granularity. We accomplished these objectives with a second customer

  10. Facilities Operations Specialist | Department of Energy

    Office of Environmental Management (EM)

    Announcement Number DOE-BPA-16-11659-DE Job Summary Ross Facilities Operations and Maintenance operates and maintains the office and light industrial facilities, buildings and...

  11. ALARA notes, Number 8

    SciTech Connect (OSTI)

    Khan, T.A.; Baum, J.W.; Beckman, M.C.

    1993-10-01

    This document contains information dealing with the lessons learned from the experience of nuclear plants. In this issue the authors tried to avoid the `tyranny` of numbers and concentrated on the main lessons learned. Topics include: filtration devices for air pollution abatement, crack repair and inspection, and remote handling equipment.

  12. Atmospheric Radiation Measurement Program Climate Research Facility Operations Quarterly Report October 1 - December 31, 2005

    SciTech Connect (OSTI)

    Sisterson, DL

    2005-12-31

    Description. Individual raw data streams from instrumentation at the Atmospheric Radiation Measurement (ARM) Program Climate Research Facility (ACRF) fixed and mobile sites are collected and sent to the Data Management Facility (DMF) at Pacific Northwest National Laboratory (PNNL) for processing in near real time. Raw and processed data are then sent daily to the ACRF Archive, where they are made available to users. For each instrument, we calculate the ratio of the actual number of data records received daily at the Archive to the expected number of data records. The results are tabulated by (1) individual data stream, site, and month for the current year and (2) site and fiscal year dating back to 1998. The U.S. Department of Energy requires national user facilities to report time-based operating data. The requirements concern the actual hours of operation (ACTUAL); the estimated maximum operation or uptime goal (OPSMAX), which accounts for planned downtime; and the VARIANCE [1 – (ACTUAL/OPSMAX)], which accounts for unplanned downtime. The OPSMAX time for the third quarter for the Southern Great Plains (SGP) site is 2,097.6 hours (0.95 × 2,208 hours this quarter). The OPSMAX for the North Slope of Alaska (NSA) locale is 1,987.2 hours (0.90 × 2,208), and that for the Tropical Western Pacific (TWP) locale is 1,876.8 hours (0.85 × 2,208). The OPSMAX time for the ARM Mobile Facility (AMF) is 2,097.6 hours (0.95 × 2,208). The differences in OPSMAX performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure OPSMAX for each instrument or data stream. Data availability reported here refers to the average of the individual, continuous data streams that have been received by the ACRF Archive. Data not at the Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Therefore, data availability is directly related to individual instrument uptime. Thus, the average percent

  13. Atmospheric Radiation Measurement Program Climate Research Facility Operations Quarterly Report January-March 2006

    SciTech Connect (OSTI)

    Sisterson, DL

    2006-03-31

    Description. Individual raw data streams from instrumentation at the Atmospheric Radiation Measurement (ARM) Program Climate Research Facility (ACRF) fixed and mobile sites are collected and sent to the Data Management Facility (DMF) at Pacific Northwest National Laboratory (PNNL) for processing in near real time. Raw and processed data are then sent daily to the ACRF Archive, where they are made available to users. For each instrument, we calculate the ratio of the actual number of data records received daily at the Archive to the expected number of data records. The results are tabulated by (1) individual data stream, site, and month for the current year; and (2) site and fiscal year dating back to 1998. The U.S. Department of Energy requires national user facilities to report time-based operating data. The requirements concern the actual hours of operation (ACTUAL); the estimated maximum operation or uptime goal (OPSMAX), which accounts for planned downtime; and the VARIANCE [1 – (ACTUAL/OPSMAX)], which accounts for unplanned downtime. The OPSMAX time for the second quarter for the Southern Great Plains (SGP) site is 2,052 hours (0.95 × 2,160 hours this quarter). The OPSMAX for the North Slope Alaska (NSA) locale is 1,944 hours (0.90 × 2,160), and that for the Tropical Western Pacific (TWP) locale is 1,836 hours (0.85 × 2,160). The OPSMAX time for the ARM Mobile Facility (AMF) is 2,052 hours (0.95 × 2,160). The differences in OPSMAX performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure OPSMAX for each instrument or data stream. Data availability reported here refers to the average of the individual, continuous data streams that have been received by the Archive. Data not at the Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Therefore, data availability is directly related to individual instrument uptime. Thus, the average percent of data in the

  14. Atmospheric Radiation Measurement Program Climate Research Facility Operations Quarterly Report July 1 - September 30, 2005

    SciTech Connect (OSTI)

    DL Sisterson

    2005-09-30

    Description. Individual raw data streams from instrumentation at the ACRF fixed and mobile sites are collected and sent to the Data Management Facility (DMF) at PNNL for processing in near real time. Raw and processed data are then sent daily to the ACRF Archive, where they are made available to users. For each instrument, we calculate the ratio of the actual number of data records received daily at the Archive to the expected number of data records. The results are tabulated by (1) individual data stream, site, and month for the current year and (2) site and fiscal year dating back to 1998. The DOE requires national user facilities to report time-based operating data. The requirements concern the actual hours of operation (ACTUAL); the estimated maximum operation or uptime goal (OPSMAX), which accounts for planned downtime; and the VARIANCE [1 (ACTUAL/OPSMAX)], which accounts for unplanned downtime. The OPSMAX time for the third quarter for the Southern Great Plains (SGP) site is 2,097.6 hours (0.95 2,208 hours this quarter). The OPSMAX for the North Slope Alaska (NSA) site is 1,987.2 hours (0.90 2,208), and that for the Tropical Western Pacific (TWP) site is 1,876.8 hours (0.85 2,208). The OPSMAX time for the ARM Mobile Facility (AMF) is 2,097.6 hours (0.95 2,208). The differences in OPSMAX performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure OPSMAX for each instrument or data stream. Data availability reported here refers to the average of the individual, continuous data streams that have been received by the ACRF Archive. Data not at the Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Therefore, data availability is directly related to individual instrument uptime. Thus, the average percent of data in the Archive represents the average percent of the time (24 hours per day, 92 days for this quarter) the instruments were operating this

  15. Study of Engine Operating Parameter Effects on GDI Engine Particle...

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

    Study of Engine Operating Parameter Effects on GDI Engine Particle-Number Emissions Study of Engine Operating Parameter Effects on GDI Engine Particle-Number Emissions Results show ...

  16. Atmospheric Radiation Measurement program climate research facility operations quarterly report April 1 - June 30, 2007.

    SciTech Connect (OSTI)

    Sisterson, D. L.

    2007-07-26

    Individual raw data streams from instrumentation at the Atmospheric Radiation Measurement (ARM) Program Climate Research Facility (ACRF) fixed and mobile sites are collected and sent to the Data Management Facility (DMF) at Pacific Northwest National Laboratory (PNNL) for processing in near real time. Raw and processed data are then sent daily to the ACRF Archive, where they are made available to users. For each instrument, we calculate the ratio of the actual number of data records received daily at the Archive to the expected number of data records. The results are tabulated by (1) individual data stream, site, and month for the current year and (2) site and fiscal year (FY) dating back to 1998. The U.S. Department of Energy requires national user facilities to report time-based operating data. The requirements concern the actual hours of operation (ACTUAL); the estimated maximum operation or uptime goal (OPSMAX), which accounts for planned downtime; and the VARIANCE [1 - (ACTUAL/OPSMAX)], which accounts for unplanned downtime. The OPSMAX time for the third quarter of FY 2007 for the Southern Great Plains (SGP) site is 2,074.8 hours (0.95 x 2,184 hours this quarter). The OPSMAX for the North Slope Alaska (NSA) locale is 1,965.6 hours (0.90 x 2,184), and that for the Tropical Western Pacific (TWP) locale is 1,856.4 hours (0.85 x 2,184). The OPSMAX time for the ARM Mobile Facility (AMF) is 2,074.8 hours (0.95 x 2,184). The differences in OPSMAX performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure OPSMAX for each instrument or data stream. Data availability reported here refers to the average of the individual, continuous data streams that have been received by the Archive. Data not at the Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Therefore, data availability is directly related to individual instrument uptime. Thus, the average percent of data in

  17. SPEAR Operations

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

    Operations SPEAR Status SPEAR Status SPEAR Status Web Message Management (authorized access only) ED's stuff Run statistic (preliminary and unofficial) Training Sessions 10/20/03 rev-3 The schedule of talks listed below have a machine operations focus and are intended for operators, physicists and support personnel who will participate in SPEAR3 commissioning and operation. The talks are video taped and stored in the control room along with any pertinent hardcopies for future reference. Date

  18. Atmospheric Radiation Measurement Program Climate Research Facility Operations Quarterly Report October 1 - December 31, 2004

    SciTech Connect (OSTI)

    Sisterson, DL

    2004-12-31

    Description. Individual raw data streams from instrumentation at the Atmospheric Radiation Measurement (ARM) Program Climate Research Facility (ACRF) fixed and mobile sites are collected and sent to the Data Management Facility (DMF) at Pacific Northwest National Laboratory for processing in near real time. Raw and processed data are then sent daily to the ACRF Archive, where they are made available to users. For each instrument, we calculate the ratio of the actual number of data records received daily at the Archive to the expected number of data records. The results are tabulated by (1) individual data stream, site, and month for the current year and (2) site and fiscal year dating back to 1998. The United States Department of Energy requires national user facilities to report time-based operating data. The requirements concern the actual hours of operation (ACTUAL); the estimated maximum operation or uptime goal (OPSMAX), which accounts for planned downtime; and the VARIANCE [1 – (ACTUAL/OPSMAX)], which accounts for unplanned downtime. The annual OPSMAX time for the Southern Great Plains (SGP) site is 8,322 hours per year (0.95 × 8,760, the number hours in a year, not including leap year). The annual OPSMAX for the North Slope Alaska (NSA) site is 7,884 hours per year (0.90 × 8,760), and that for the Tropical Western Pacific (TWP) site is 7,446 hours per year (0.85 × 8,760). The differences in OPSMAX performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure OPSMAX for each instrument or data stream. Data availability reported here refers to the average of the individual, continuous data streams that have been received by the ACRF Archive. Data not at the Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Therefore, data availability is directly related to individual instrument uptime. Thus, the average percent of data in the Archive represents the

  19. WIPP Workers Reach Two Million Man-Hours Without a Lost-Time...

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

    Workers Reach Two Million Man-Hours Without a Lost-Time Accident CARLSBAD, N.M., February ... a safety milestone Feb. 19 by working two million man-hours without a lost-time accident. ...

  20. Pilot Plant Completes Two 1,000-Hour Ethanol Performance Runs...

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

    Pilot Plant Completes Two 1,000-Hour Ethanol Performance Runs Pilot Plant Completes Two 1,000-Hour Ethanol Performance Runs October 19, 2015 - 12:38pm Addthis ICM Inc. announced ...

  1. BioenergizeME Office Hours Webinar: Must-Know Tips for the 2016...

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

    BioenergizeME Office Hours Webinar: Must-Know Tips for the 2016 BioenergizeME Infographic Challenge BioenergizeME Office Hours Webinar: Must-Know Tips for the 2016 BioenergizeME ...

  2. EPA ENERGY STAR Webcast: Portfolio Manager Office Hours, Focus Topic: Sharing Forward and Transfer Ownership

    Energy.gov [DOE]

    Portfolio Manager "Office Hours" is a live webinar that gives all users an opportunity to ask their questions directly to EPA in an open forum. In 2014, Office Hours will be held once a month. We...

  3. Hacking Away at Soft Costs: 24-Hour Coding Event Focuses on Expanding...

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

    Hacking Away at Soft Costs: 24-Hour Coding Event Focuses on Expanding Solar Market Hacking Away at Soft Costs: 24-Hour Coding Event Focuses on Expanding Solar Market May 7, 2014 - ...

  4. Kenya Hourly DNI, GHI and Diffuse Solar Data - Datasets - OpenEI...

    Open Energy Information (Open El) [EERE & EIA]

    Kenya Hourly DNI, GHI and Diffuse Solar Data Abstract Each data file is a set of hourly values of solar radiation (DNI, GHI and diffuse) and meteorological elements for a 1-year...

  5. EPA ENERGY STAR Webcast- Portfolio Manager Office Hours, Focus Topic: Weather Data and Metrics

    Energy.gov [DOE]

    Portfolio Manager "Office Hours" is a live webinar that gives all users an opportunity to ask their questions directly to EPA in an open forum. In 2014, Office Hours will be held once a month. We...

  6. Atmospheric Radiation Measurement program climate research facility operations quarterly report July 1 - Sep. 30, 2009.

    SciTech Connect (OSTI)

    Sisterson, D. L.

    2009-10-15

    Individual raw data streams from instrumentation at the Atmospheric Radiation Measurement (ARM) Program Climate Research Facility (ACRF) fixed and mobile sites are collected and sent to the Data Management Facility (DMF) at Pacific Northwest National Laboratory (PNNL) for processing in near-real time. Raw and processed data are then sent approximately daily to the ACRF Archive, where they are made available to users. For each instrument, we calculate the ratio of the actual number of data records received daily at the Archive to the expected number of data records. The results are tabulated by (1) individual data stream, site, and month for the current year and (2) site and fiscal year (FY) dating back to 1998. The U.S. Department of Energy (DOE) requires national user facilities to report time-based operating data. The requirements concern the actual hours of operation (ACTUAL); the estimated maximum operation or uptime goal (OPSMAX), which accounts for planned downtime; and the VARIANCE [1 - (ACTUAL/OPSMAX)], which accounts for unplanned downtime. The OPSMAX time for the fourth quarter of FY 2009 for the Southern Great Plains (SGP) site is 2,097.60 hours (0.95 ? 2,208 hours this quarter). The OPSMAX for the North Slope Alaska (NSA) locale is 1,987.20 hours (0.90 ? 2,208) and for the Tropical Western Pacific (TWP) locale is 1,876.8 hours (0.85 ? 2,208). The ARM Mobile Facility (AMF) was officially operational May 1 in Graciosa Island, the Azores, Portugal, so the OPSMAX time this quarter is 2,097.60 hours (0.95 x 2,208). The differences in OPSMAX performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure OPSMAX for each instrument or data stream. Data availability reported here refers to the average of the individual, continuous data streams that have been received by the Archive. Data not at the Archive result from downtime (scheduled or unplanned) of the individual instruments. Therefore, data

  7. Self-correcting random number generator

    DOE Patents [OSTI]

    Humble, Travis S.; Pooser, Raphael C.

    2016-09-06

    A system and method for generating random numbers. The system may include a random number generator (RNG), such as a quantum random number generator (QRNG) configured to self-correct or adapt in order to substantially achieve randomness from the output of the RNG. By adapting, the RNG may generate a random number that may be considered random regardless of whether the random number itself is tested as such. As an example, the RNG may include components to monitor one or more characteristics of the RNG during operation, and may use the monitored characteristics as a basis for adapting, or self-correcting, to provide a random number according to one or more performance criteria.

  8. Request for Proposals Number RHB-5-52483

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

    9 National Renewable Energy Laboratory Managed and Operated by the Alliance for Sustainable Energy, LLC Request for Proposals Number RHB-5-52483 "Subsurface Utility Engineering...

  9. Modular redundant number systems

    SciTech Connect (OSTI)

    1998-05-31

    With the increased use of public key cryptography, faster modular multiplication has become an important cryptographic issue. Almost all public key cryptography, including most elliptic curve systems, use modular multiplication. Modular multiplication, particularly for the large public key modulii, is very slow. Increasing the speed of modular multiplication is almost synonymous with increasing the speed of public key cryptography. There are two parts to modular multiplication: multiplication and modular reduction. Though there are fast methods for multiplying and fast methods for doing modular reduction, they do not mix well. Most fast techniques require integers to be in a special form. These special forms are not related and converting from one form to another is more costly than using the standard techniques. To this date it has been better to use the fast modular reduction technique coupled with standard multiplication. Standard modular reduction is much more costly than standard multiplication. Fast modular reduction (Montgomery`s method) reduces the reduction cost to approximately that of a standard multiply. Of the fast multiplication techniques, the redundant number system technique (RNS) is one of the most popular. It is simple, converting a large convolution (multiply) into many smaller independent ones. Not only do redundant number systems increase speed, but the independent parts allow for parallelization. RNS form implies working modulo another constant. Depending on the relationship between these two constants; reduction OR division may be possible, but not both. This paper describes a new technique using ideas from both Montgomery`s method and RNS. It avoids the formula problem and allows fast reduction and multiplication. Since RNS form is used throughout, it also allows the entire process to be parallelized.

  10. Operations Videos

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

    Operations Research Analysts The U.S. Energy Information Administration (EIA) within the Department of Energy has forged a world-class information program that stresses quality, teamwork, and employee growth. In support of our program, we offer a variety of profes- sional positions, including the Operations Research Analyst, whose work is associated with the development and main- tenance of energy modeling systems. Responsibilities: Operations Research Analysts perform or participate in one or

  11. operations center

    National Nuclear Security Administration (NNSA)

    servers and other critical Operations Center equipment

  12. Independent air supply system filtered to protect against biological and radiological agents (99.7%).
  13. <...

  14. Laboratory Operations

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

    ... Hockaday is the associate director of the Experimental Physical Sciences Directorate and Cabbil is associate director for Nuclear and High Hazard Operations. - 12513 Norris ...

  15. Making the Traffic Operations Case for Congestion Pricing: Operational Impacts of Congestion Pricing

    SciTech Connect (OSTI)

    Chin, Shih-Miao; Hu, Patricia S; Davidson, Diane

    2011-02-01

    Congestion begins when an excess of vehicles on a segment of roadway at a given time, resulting in speeds that are significantly slower than normal or 'free flow' speeds. Congestion often means stop-and-go traffic. The transition occurs when vehicle density (the number of vehicles per mile in a lane) exceeds a critical level. Once traffic enters a state of congestion, recovery or time to return to a free-flow state is lengthy; and during the recovery process, delay continues to accumulate. The breakdown in speed and flow greatly impedes the efficient operation of the freeway system, resulting in economic, mobility, environmental and safety problems. Freeways are designed to function as access-controlled highways characterized by uninterrupted traffic flow so references to freeway performance relate primarily to the quality of traffic flow or traffic conditions as experienced by users of the freeway. The maximum flow or capacity of a freeway segment is reached while traffic is moving freely. As a result, freeways are most productive when they carry capacity flows at 60 mph, whereas lower speeds impose freeway delay, resulting in bottlenecks. Bottlenecks may be caused by physical disruptions, such as a reduced number of lanes, a change in grade, or an on-ramp with a short merge lane. This type of bottleneck occurs on a predictable or 'recurrent' basis at the same time of day and same day of week. Recurrent congestion totals 45% of congestion and is primarily from bottlenecks (40%) as well as inadequate signal timing (5%). Nonrecurring bottlenecks result from crashes, work zone disruptions, adverse weather conditions, and special events that create surges in demand and that account for over 55% of experienced congestion. Figure 1.1 shows that nonrecurring congestion is composed of traffic incidents (25%), severe weather (15%), work zones, (10%), and special events (5%). Between 1995 and 2005, the average percentage change in increased peak traveler delay, based on

  16. Atmospheric Radiation Measurement Program Climate Research Facility Operations Quarterly Report January 1 - March 31, 2005

    SciTech Connect (OSTI)

    Sisterson, DL

    2005-03-31

    Description. Individual raw data streams from instrumentation at the Atmospheric Radiation Measurement (ARM) Program Climate Research Facility (ACRF) fixed and mobile sites are collected and sent to the Data Management Facility (DMF) at Pacific Northwest National Laboratory for processing in near real time. Raw and processed data are then sent daily to the ACRF Archive, where they are made available to users. For each instrument, we calculate the ratio of the actual number of data records received daily at the Archive to the expected number of data records. The results are tabulated by (1) individual data stream, site, and month for the current year and (2) site and fiscal year dating back to 1998. The United States Department of Energy requires national user facilities to report time-based operating data. The requirements concern the actual hours of operation (ACTUAL); the estimated maximum operation or uptime goal (OPSMAX), which accounts for planned downtime; and the VARIANCE [1 – (ACTUAL/OPSMAX)], which accounts for unplanned downtime. The OPSMAX time for this second quarter for the Southern Great Plains (SGP) site is 2052 hours (0.95 × 2,160 hours this quarter). The annual OPSMAX for the North Slope Alaska (NSA) site is 1944 hours (0.90 × 2,160), and that for the Tropical Western Pacific (TWP) site is 1836 hours (0.85 × 2,160). The differences in OPSMAX performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure OPSMAX for each instrument or data stream. Data availability reported here refers to the average of the individual, continuous data streams that have been received by the ACRF Archive. Data not at the Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Therefore, data availability is directly related to individual instrument uptime. Thus, the average percent of data in the Archive represents the average percent of the time (24 hours per day, 90

  17. Atmospheric Radiation Measurement Program Climate Research Facility Operations Quarterly Report July 1 – September 30, 2008

    SciTech Connect (OSTI)

    Sisterson, DL

    2008-09-30

    Individual raw data streams from instrumentation at the Atmospheric Radiation Measurement (ARM) Program Climate Research Facility (ACRF) fixed and mobile sites are collected and sent to the Data Management Facility (DMF) at Pacific Northwest National Laboratory (PNNL) for processing in near real-time. Raw and processed data are then sent daily to the ACRF Archive, where they are made available to users. For each instrument, we calculate the ratio of the actual number of data records received daily at the Archive to the expected number of data records. The results are tabulated by (1) individual data stream, site, and month for the current year and (2) site and fiscal year (FY) dating back to 1998. The U.S. Department of Energy (DOE) requires national user facilities to report time-based operating data. The requirements concern the actual hours of operation (ACTUAL); the estimated maximum operation or uptime goal (OPSMAX), which accounts for planned downtime; and the VARIANCE [1 – (ACTUAL/OPSMAX)], which accounts for unplanned downtime. The OPSMAX time for the fourth quarter of FY 2008 for the Southern Great Plains (SGP) site is 2,097.60 hours (0.95 x 2,208 hours this quarter). The OPSMAX for the North Slope Alaska (NSA) locale is 1,987.20 hours (0.90 x 2,208), and for the Tropical Western Pacific (TWP) locale is 1,876.80 hours (0.85 x 2,208). The OPSMAX time for the ARM Mobile Facility (AMF) is not reported this quarter because the data have not yet been released from China to the DMF for processing. The differences in OPSMAX performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure OPSMAX for each instrument or data stream. Data availability reported here refers to the average of the individual, continuous data streams that have been received by the Archive. Data not at the Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Therefore, data availability is

  18. Atmospheric Radiation Measurement Program Climate Research Facility Operations Quarterly Report April 1 - June 30, 2005

    SciTech Connect (OSTI)

    DL Sisterson

    2005-06-30

    Description. Individual raw data streams from instrumentation at the Atmospheric Radiation Measurement (ARM) Program Climate Research Facility (ACRF) fixed and mobile sites are collected and sent to the Data Management Facility (DMF) at Pacific Northwest National Laboratory for processing in near real time. Raw and processed data are then sent daily to the ACRF Archive, where they are made available to users. For each instrument, we calculate the ratio of the actual number of data records received daily at the Archive to the expected number of data records. The results are tabulated by (1) individual data stream, site, and month for the current year and (2) site and fiscal year dating back to 1998. The United States Department of Energy requires national user facilities to report time-based operating data. The requirements concern the actual hours of operation (ACTUAL); the estimated maximum operation or uptime goal (OPSMAX), which accounts for planned downtime; and the VARIANCE [1 (ACTUAL/OPSMAX)], which accounts for unplanned downtime. The OPSMAX time for the third quarter for the Southern Great Plains (SGP) site is 2,074.8 hours (0.95 2,184 hours this quarter). The annual OPSMAX for the North Slope Alaska (NSA) site is 1,965.6 hours (0.90 2,184), and that for the Tropical Western Pacific (TWP) site is 1,856.4 hours (0.85 2,184). The OPSMAX time for the ARM Mobile Facility (AMF) is 2,074.8 (0.95 2,184). The differences in OPSMAX performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure OPSMAX for each instrument or data stream. Data availability reported here refers to the average of the individual, continuous data streams that have been received by the ACRF Archive. Data not at the Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Therefore, data availability is directly related to individual instrument uptime. Thus, the average percent of data in

  19. Wyoming Natural Gas Number of Residential Consumers (Number of...

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Wyoming Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  20. Virginia Natural Gas Number of Residential Consumers (Number...

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Virginia Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  21. Utah Natural Gas Number of Industrial Consumers (Number of Elements...

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Utah Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 ...

  22. Wisconsin Natural Gas Number of Industrial Consumers (Number...

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Wisconsin Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  1. Virginia Natural Gas Number of Commercial Consumers (Number of...

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Virginia Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  2. Wyoming Natural Gas Number of Industrial Consumers (Number of...

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Wyoming Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  3. Utah Natural Gas Number of Residential Consumers (Number of Elements...

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Utah Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  4. Vermont Natural Gas Number of Residential Consumers (Number of...

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Vermont Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  5. Utah Natural Gas Number of Commercial Consumers (Number of Elements...

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Utah Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 ...

  6. Virginia Natural Gas Number of Industrial Consumers (Number of...

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Virginia Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  7. West Virginia Natural Gas Number of Industrial Consumers (Number...

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) West Virginia Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  8. Wisconsin Natural Gas Number of Residential Consumers (Number...

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Wisconsin Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  9. Vermont Natural Gas Number of Commercial Consumers (Number of...

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Vermont Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  10. Wyoming Natural Gas Number of Commercial Consumers (Number of...

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Wyoming Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  11. West Virginia Natural Gas Number of Commercial Consumers (Number...

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) West Virginia Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  12. Washington Natural Gas Number of Commercial Consumers (Number...

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Washington Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  13. Washington Natural Gas Number of Residential Consumers (Number...

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Washington Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  14. Washington Natural Gas Number of Industrial Consumers (Number...

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Washington Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  15. Wisconsin Natural Gas Number of Commercial Consumers (Number...

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Wisconsin Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  16. Vermont Natural Gas Number of Industrial Consumers (Number of...

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Vermont Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  17. West Virginia Natural Gas Number of Residential Consumers (Number...

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) West Virginia Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  18. New York Natural Gas Number of Residential Consumers (Number...

    Annual Energy Outlook

    Residential Consumers (Number of Elements) New York Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  19. New Mexico Natural Gas Number of Residential Consumers (Number...

    Gasoline and Diesel Fuel Update

    Residential Consumers (Number of Elements) New Mexico Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  20. New Jersey Natural Gas Number of Residential Consumers (Number...

    Gasoline and Diesel Fuel Update

    Residential Consumers (Number of Elements) New Jersey Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  1. North Carolina Natural Gas Number of Residential Consumers (Number...

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) North Carolina Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  2. North Carolina Natural Gas Number of Industrial Consumers (Number...

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) North Carolina Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  3. North Dakota Natural Gas Number of Industrial Consumers (Number...

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) North Dakota Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  4. North Dakota Natural Gas Number of Residential Consumers (Number...

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) North Dakota Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  5. North Carolina Natural Gas Number of Commercial Consumers (Number...

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) North Carolina Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  6. New Hampshire Natural Gas Number of Commercial Consumers (Number...

    Gasoline and Diesel Fuel Update

    Commercial Consumers (Number of Elements) New Hampshire Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  7. New Hampshire Natural Gas Number of Industrial Consumers (Number...

    Gasoline and Diesel Fuel Update

    Industrial Consumers (Number of Elements) New Hampshire Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  8. New Hampshire Natural Gas Number of Residential Consumers (Number...

    Annual Energy Outlook

    Residential Consumers (Number of Elements) New Hampshire Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 ...

  9. New Mexico Natural Gas Number of Industrial Consumers (Number...

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) New Mexico Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 ...

  10. MENTOR QUESTIONNAIRE Name: Title: Email: Office Phone Number:

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

    MENTOR QUESTIONNAIRE Name: Title: Email: Office Phone Number: Office Address: is interested in this program because: Are you willing to act as a mentor for ? Yes No Expectations of the Mentoring Program How long? 6-months minimum commitment. Are you willing to commit to the 6-months minimum timeframe? Yes No How much time? You decide with your mentee; 1-4 hours/month is recommended. Please return completed form to Ames Lab Human Resources, 105 TASF. Are you willing to commit 1-4 hours per month

  11. NEUTRONIC REACTOR CONSTRUCTION AND OPERATION

    DOE Patents [OSTI]

    West, J.M.; Weills, J.T.

    1960-03-15

    A method is given for operating a nuclear reactor having a negative coefficient of reactivity to compensate for the change in reactor reactivity due to the burn-up of the xenon peak following start-up of the reactor. When it is desired to start up the reactor within less than 72 hours after shutdown, the temperature of the reactor is lowered prior to start-up, and then gradually raised after start-up.

  12. Operating Costs

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

    1997-03-28

    This chapter is focused on capital costs for conventional construction and environmental restoration and waste management projects and examines operating cost estimates to verify that all elements of the project have been considered and properly estimated.

  13. Nonprofit Organizations: Have Your Los Alamos Employees/Retirees Log Hours

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

    in VolunteerMatch Nonprofit Organizations: Have Your Los Alamos Employees/Retirees Log Hours in VolunteerMatch Community Connections: Your link to news and opportunities from Los Alamos National Laboratory Latest Issue:November 2, 2016 all issues All Issues » submit Nonprofit Organizations: Have Your Los Alamos Employees/Retirees Log Hours in VolunteerMatch Lab employees and retirees should log their VolunteerMatch hours to benefit local nonprofits. March 1, 2013 Volunteers help fill

  14. DOE Awards 265 Million Hours of Supercomputing Time to Advance Leading

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

    Scientific Research Projects | Department of Energy 265 Million Hours of Supercomputing Time to Advance Leading Scientific Research Projects DOE Awards 265 Million Hours of Supercomputing Time to Advance Leading Scientific Research Projects January 17, 2008 - 10:38am Addthis WASHINGTON, DC -The U.S. Department of Energy's (DOE) Office of Science today announced that 265 million processor-hours were awarded to 55 scientific projects, the largest amount of supercomputing resource awards

  15. BioenergizeME Office Hours Webinar: Guide to the 2016 BioenergizeME...

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

    researching their selected topics, developing their infographics, and designing effective social media campaigns. This webinar is part of the BioenergizeME Office Hours webinar...

  16. Reduction/Transformation Operators

    Energy Science and Technology Software Center (OSTI)

    2006-09-01

    RTOp (reduction/transformation operators) is a collection of C++ software that provides the basic mechanism for implementinig vector operations in a flexible and efficient manner. This is the main interface utilized by Thyra to allow for the specification of specific vector reduction and/or transformation operations. The RTOp package contains three different types of software. (a) a small number of interoperability interfaces. (b) support software including code for the parallel SPMD mode based on only Teuchos::Comm(and notmore » MPl directly(, and (c) a library of pre-implemented RTOp subclasses for everything from simple AXPYs and norms, to more specialized vector operations. RTOp allows an algorithm developer to implement their own RTOp subclasses in a way that is independent from any specific serial, parallel, out-of-core or other type of vector implementation. RTOp is a required package by Thyra and MOOCHO. (c)« less

  17. Atmospheric Radiation Measurement Program Climate Research Facility Operations Cumulative Quarterly Report October 1, 2003 - September 30, 2004

    SciTech Connect (OSTI)

    Sisterson, DL

    2004-09-30

    Description. Individual raw data streams from instrumentation at the Atmospheric Radiation Measurement (ARM) Program Climate Research Facility (ACRF) fixed and mobile sites are collected and sent to the Data Management Facility (DMF) at Pacific Northwest National Laboratory for processing in near real time. Raw and processed data are then sent daily to the ACRF Archive, where they are made available to users. For each instrument, we calculate the ratio of the actual number of data records received daily at the Archive to the expected number of data records. The results are tabulated by (1) individual data stream, site, and month for the current year and (2) site and fiscal year (FY) dating back to 1998. The United States Department of Energy requires national user facilities to report time-based operating data. The requirements concern the actual hours of operation (ACTUAL); the estimated maximum operation or uptime goal (OPSMAX), which accounts for planned downtime; and the VARIANCE [1 – (ACTUAL/OPSMAX)], which accounts for unplanned downtime. The annual OPSMAX time for the Southern Great Plains (SGP) site is 8,322 hours per year (0.95 × 8,760, the number hours in a year, not including leap year). The annual OPSMAX for the North Slope Alaska (NSA) site is 7,884 hours per year (0.90 × 8,760), and that for the Tropical Western Pacific (TWP) site is 7,446 hours per year (0.85 × 8,760). The differences in OPSMAX performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure OPSMAX for each instrument or data stream. Data availability reported here refers to the average of the individual, continuous data streams that have been received by the ACRF Archive. Data not at the Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Therefore, data availability is directly related to individual instrument uptime. Thus, the average percent of data in the Archive represents the

  18. Museum Hours

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

    provide a listening-assistance system and translations of the script in French and Spanish. Sorry, a local shop has closed The Otowi Bookstore and Museum Shop, which had been...

  19. Saran-Chloropel plastic suit worker dose rates from airborne tritium exposure - first exposure hour

    SciTech Connect (OSTI)

    Edwards, T.

    1993-04-20

    Radiological Engineering was requested to develop Tritium Stay Time Chart dose rates for the 9 mil Saran-Chloropel (CPE) plastic suit for a period of one hour or less. Assumptions utilized in previous calculations were revised to better address the first hour of exposure in the suit for emergency situations.

  20. Atmospheric Radiation Measurement program climate research facility operations quarterly report January 1 - March 31, 2009.

    SciTech Connect (OSTI)

    Sisterson, D. L.

    2009-04-23

    Individual raw data streams from instrumentation at the Atmospheric Radiation Measurement (ARM) Program Climate Research Facility (ACRF) fixed and mobile sites are collected and sent to the Data Management Facility (DMF) at Pacific Northwest National Laboratory (PNNL) for processing in near real-time. Raw and processed data are then sent daily to the ACRF Archive, where they are made available to users. For each instrument, we calculate the ratio of the actual number of data records received daily at the Archive to the expected number of data records. The results are tabulated by (1) individual data stream, site, and month for the current year and (2) site and fiscal year (FY) dating back to 1998. The U.S. Department of Energy (DOE) requires national user facilities to report time-based operating data. The requirements concern the actual hours of operation (ACTUAL); the estimated maximum operation or uptime goal (OPSMAX), which accounts for planned downtime; and the VARIANCE [1 - (ACTUAL/OPSMAX)], which accounts for unplanned downtime. The OPSMAX time for the second quarter of FY 2009 for the Southern Great Plains (SGP) site is 2,052.00 hours (0.95 x 2,160 hours this quarter). The OPSMAX for the North Slope Alaska (NSA) locale is 1,944.00 hours (0.90 x 2,160), and for the Tropical Western Pacific (TWP) locale is 1,836.00 hours (0.85 x 2,160). The OPSMAX time for the ARM Mobile Facility (AMF) is not reported this quarter because not all of the metadata have been acquired that are used to generate this metric. The differences in OPSMAX performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure OPSMAX for each instrument or data stream. Data availability reported here refers to the average of the individual, continuous data streams that have been received by the Archive. Data not at the Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Therefore, data availability

  1. OMB Control Number: 1910-5165

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

    ... Contract Work Hours and Safety Standards Act (Overtime Violations): o 8. Amount of back wages in paid: Davis-Bacon and Related Acts: oi Contract Work Hours and Safety Standards ...

  2. Tennessee Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Tennessee Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 52 75 NA NA NA - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Tennessee Natural Gas Summ

  3. Texas Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Texas Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 85,030 94,203 96,949 104,205 105,159 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Texas Natural

  4. Pennsylvania Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Pennsylvania Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 7,046 7,627 7,164 8,481 7,557 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Pennsylvania

  5. Louisiana Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Louisiana Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 5,201 5,057 5,078 5,285 4,968 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Louisiana Natural

  6. Michigan Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Michigan Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 510 514 537 584 532 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Michigan Natural Gas Summary

  7. Mississippi Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Mississippi Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 561 618 581 540 501 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Mississippi Natural Gas

  8. Missouri Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Missouri Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 1 1 1 1 NA - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Missouri Natural Gas Summary

  9. Montana Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Montana Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 1,956 2,147 2,268 2,377 2,277 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Montana Natural Gas

  10. Nebraska Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Nebraska Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 84 73 54 51 51 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Nebraska Natural Gas Summar

  11. Nevada Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Nevada Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 4 4 4 4 4 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Nevada Natural Gas Summary

  12. Ohio Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Ohio Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 6,775 6,745 7,038 7,257 5,941 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Ohio Natural Gas

  13. Oklahoma Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Oklahoma Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 6,723 7,360 8,744 7,105 8,368 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Oklahoma Natural

  14. Alabama Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Alabama Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 346 367 402 436 414 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Alabama Natural Gas Sum

  15. Alaska Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Alaska Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 2,040 1,981 2,006 2,042 2,096 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Alaska Natural Gas

  16. Arizona Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Arizona Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 1 1 1 0 1 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Arizona Natural Gas Summary

  17. Arkansas Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Arkansas Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 165 174 218 233 240 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Arkansas Natural Gas

  18. California Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) California Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 25,958 26,061 26,542 26,835 27,075 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) California

  19. Colorado Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Colorado Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 5,963 6,456 6,799 7,771 7,733 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Colorado Natural

  20. Utah Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Utah Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 3,119 3,520 3,946 4,249 3,966 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Utah Natural Gas

  1. Virginia Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Virginia Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 2 1 1 2 2 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Virginia Natural Gas Summary

  2. Wyoming Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Wyoming Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 4,430 4,563 4,391 4,538 4,603 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Wyoming Natural Gas

  3. Kentucky Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oil Wells (Number of Elements) Kentucky Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 317 358 340 NA NA - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Kentucky Natural Gas Su

  4. WIPP Site By The Numbers August 2015

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

    0 ft. By the Numbers The Waste Isolation Pilot Plant (WIPP) is a Department of Energy facility designed to safely isolate defense- related transuranic (TRU) waste from people and the environment. WIPP, which began waste disposal operations in 1999, is located 26 miles outside of Carlsbad, New Mexico. Waste temporarily stored at sites around the country is shipped to WIPP and permanently disposed in rooms mined out of an ancient salt formation below the surface. TRU waste destined for WIPP

  5. Control algorithms for effective operation of variable-speed wind turbines

    SciTech Connect (OSTI)

    Not Available

    1993-10-01

    This report describes a computer code, called ASYM and provides results from its application in simulating the control of the 34-m Test Bed vertical-axis wind turbine (VAWT) in Bushland, Texas. The code synthesizes dynamic wind speeds on a second-by-second basis in the time domain. The wind speeds conform to a predetermined spectral content governed by the hourly average wind speed that prevails at each hour of the simulation. The hourly average values are selected in a probabilistic sense through the application of Markov chains, but their cumulative frequency of occurrence conforms to a Rayleigh distribution that is governed by the mean annual wind speed of the site selected. The simulated wind speeds then drive a series of control algorithms that enable the code to predict key operational parameters such as number of annual starts and stops, annual energy production, and annual fatigue damage at a critically stressed joint on the wind turbine. This report also presents results from the application of ASYM that pertain to low wind speed cut-in and cut-out conditions and controlled operation near critical speed ranges that excite structural vibrations that can lead to accelerated fatigue damage.

  6. DOE's Office of Science Awards 95 Million Hours of Supercomputing Time to

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

    Advance Research in Science, Academia and Industry | Department of Energy 95 Million Hours of Supercomputing Time to Advance Research in Science, Academia and Industry DOE's Office of Science Awards 95 Million Hours of Supercomputing Time to Advance Research in Science, Academia and Industry January 8, 2007 - 9:59am Addthis WASHINGTON, D.C. - The U.S. Department of Energy's (DOE) Office of Science announced today that 45 projects were awarded a total of 95 million hours of computing time on

  7. EERE Success Story-Pilot Plant Completes Two 1,000-Hour Ethanol

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

    Performance Runs | Department of Energy Pilot Plant Completes Two 1,000-Hour Ethanol Performance Runs EERE Success Story-Pilot Plant Completes Two 1,000-Hour Ethanol Performance Runs January 22, 2016 - 11:01am Addthis ICM Inc. announced successful completion of two 1,000-hour performance runs of its patent-pending Generation 2.0 Co-Located Cellulosic Ethanol process at its cellulosic ethanol pilot plant in St. Joseph, Missouri. This is an important step toward the commercialization of

  8. SunShot Announces 24-Hour Solar Data Hackathon | Department of Energy

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

    Announces 24-Hour Solar Data Hackathon SunShot Announces 24-Hour Solar Data Hackathon May 8, 2014 - 11:45am Addthis SunShot will host a 24-hour solar data hackathon at the 2014 SunShot Grand Challenge Summit. Learn more over at the EERE blog and register here. Addthis Related Articles Douglas Hitching (left), CEO of Silicon Solar Solutions and Henry Chung, LG, talk during a one-on-one networking session at the National Renewable Energy Laboratory's Industry Growth Forum in 2012. The SunShot

  9. Jefferson Lab Group Gets 10 Million Hours of Supercomputer Time | Jefferson

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

    Lab Group Gets 10 Million Hours of Supercomputer Time Jefferson Lab Group Gets 10 Million Hours of Supercomputer Time January 25, 2007 XT3 The Cray XT3 at DOE's Oak Ridge National Laboratory. Newport News, Va. - A project led by the U.S. Department of Energy's Thomas Jefferson National Accelerator Facility's Theory Center has been allotted 10 million hours of processing time by DOE's 2007 INCITE program on the Cray XT3 located at Oak Ridge National Laboratory. According to Jefferson Lab

  10. Hourly Wage and Fringe Benefit Rates FY16 WAGE SUPPLEMENT Issued 10-01-15

    National Nuclear Security Administration (NNSA)

    Supplement to PLAs Hourly Wage and Fringe Benefit Rates FY16 WAGE SUPPLEMENT Issued 10-01-15 Craft Agmt. Type Classification (Alphabetical) BN Job Code Current Hourly Wage Rates (Use most recent 04/01/15 Re- Allocation (increase HW emploee portion) (letter dated 5/1/15 states for April hours) 10/01/15 (Allocation $1.00 wages) $0.00 $1.00 MEE Maintenance Engineer I (ME-I) 037502 28.26 29.26 MEE Maintenance Engineer II (ME-II) 037503 32.40 33.40 MEE Lead Maintenance Engineer (LME) $1.50 over ME-II

  11. After-hours Power Status of Office Equipment and Inventory of Miscellaneous Plug-load Equipment

    SciTech Connect (OSTI)

    Roberson, Judy A.; Webber, Carrie A.; McWhinney, Marla C.; Brown, Richard E.; Pinckard, Margaret J.; Busch, John F.

    2004-01-22

    This research was conducted in support of two branches of the EPA ENERGY STAR program, whose overall goal is to reduce, through voluntary market-based means, the amount of carbon dioxide emitted in the U.S. The primary objective was to collect data for the ENERGY STAR Office Equipment program on the after-hours power state of computers, monitors, printers, copiers, scanners, fax machines, and multi-function devices. We also collected data for the ENERGY STAR Commercial Buildings branch on the types and amounts of ''miscellaneous'' plug-load equipment, a significant and growing end use that is not usually accounted for by building energy managers. This data set is the first of its kind that we know of, and is an important first step in characterizing miscellaneous plug loads in commercial buildings. The main purpose of this study is to supplement and update previous data we collected on the extent to which electronic office equipment is turned off or automatically enters a low power state when not in active use. In addition, it provides data on numbers and types of office equipment, and helps identify trends in office equipment usage patterns. These data improve our estimates of typical unit energy consumption and savings for each equipment type, and enables the ENERGY STAR Office Equipment program to focus future effort on products with the highest energy savings potential. This study expands our previous sample of office buildings in California and Washington DC to include education and health care facilities, and buildings in other states. We report data from twelve commercial buildings in California, Georgia, and Pennsylvania: two health care buildings, two large offices (> 500 employees each), three medium offices (50-500 employees), four education buildings, and one ''small office'' that is actually an aggregate of five small businesses. Two buildings are in the San Francisco Bay area of California, five are in Pittsburgh, Pennsylvania, and five are in Atlanta

  12. Maryland Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Maryland Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Maryland Natural Gas Summary

  13. Oregon Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Oregon Natural Gas Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Oregon Natural Gas Summary

  14. Alaska Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Alaska Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 10 11 8 1990's 8 8 10 11 11 9 202 7 7 9 2000's 9 8 9 9 10 12 11 11 6 3 2010's 3 5 3 3 1 4 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Natural

  15. Hawaii Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Hawaii Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 27 26 29 2000's 28 28 29 29 29 28 26 27 27 25 2010's 24 24 22 22 23 25 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Natural Gas Indu

  16. Indiana Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's NA NA NA NA NA - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Indiana Natural Gas Summary

  17. Kansas Natural Gas Number of Oil Wells (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Number of Oil Wells (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2010's 0 0 0 0 0 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016 Referring Pages: Number of Gas Producing Oil Wells Number of Gas Producing Oil Wells (Summary) Kansas Natural Gas Summary

  18. Operations Office

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

    (~ii~,Richland Operations Office ~Z4TESO~Richland, Washington 99352 SEP 2 2009 CERTIFIED MAIL Ms. Sarah Washburn Heart of America Northwest 1314 N.E. 5 6 th Street Suite 100 Seattle, Washington 98105 Dear Ms. Washburn: FREEDOM OF INFORMATION ACT REQUEST (FOI 2009-0067) You requested, pursuant to the Freedom of Information Act (FOJA), the following documents relating to: 1 . "The authorization, decision to use, and actual use of any and all pesticides and herbicides anywhere within the

  19. EPA ENERGY STAR Webinar: Portfolio Manager Office Hours, Focus Topic: Understanding Energy Metrics

    Office of Energy Efficiency and Renewable Energy (EERE)

    Portfolio Manager "Office Hours" is a live webinar that gives all users an opportunity to ask their questions directly to EPA in an open forum. We will plan to spend the first 20-30 minutes of each...

  20. EPA ENERGY STAR Webcast: Portfolio Manager Office Hours, Focus Topic: Responding to a Data Request

    Office of Energy Efficiency and Renewable Energy (EERE)

    Portfolio Manager "Office Hours" is a live webinar that gives all users an opportunity to ask their questions directly to EPA in an open forum. We will plan to spend the first 20-30 minutes of each...

  1. Building Technologies Program: Tax Deduction Qualified Software- Hourly Analysis Program (HAP) version 4.34

    Energy.gov [DOE]

    Provides required documentation that Hourly Analysis Program (HAP) version 4.34 meets Internal Revenue Code §179D, Notice 2006-52, dated June 2, 2006, for calculating commercial building energy and power cost savings.

  2. Building Technologies Program: Tax Deduction Qualified Software- Hourly Analysis Program (HAP) version 4.31

    Energy.gov [DOE]

    Provides required documentation that Hourly Analysis Program (HAP) version 4.31 meets Internal Revenue Code §179D, Notice 2006-52, dated June 2, 2006, for calculating commercial building energy and power cost savings.

  3. Building Technologies Program: Tax Deduction Qualified Software- Hourly Analysis Program (HAP) version 4.41

    Office of Energy Efficiency and Renewable Energy (EERE)

    Provides required documentation that Hourly Analysis Program (HAP) version 4.41 meets Internal Revenue Code §179D, Notice 2006-52, dated April 10, 2009, for calculating commercial building energy and power cost savings.

  4. Building Technologies Program: Tax Deduction Qualified Software- Hourly Analysis Program (HAP) version 4.40

    Office of Energy Efficiency and Renewable Energy (EERE)

    Provides required documentation that Hourly Analysis Program (HAP) version 4.40 meets Internal Revenue Code §179D, Notice 2006-52, dated April 10, 2009, for calculating commercial building energy and power cost savings.

  5. Building Technologies Program: Tax Deduction Qualified Software- Hourly Analysis Program (HAP) version 4.50

    Office of Energy Efficiency and Renewable Energy (EERE)

    Provides required documentation that Hourly Analysis Program (HAP) version 4.50 meets Internal Revenue Code §179D, Notice 2006-52, dated June 2, 2006, for calculating commercial building energy and power cost savings.

  6. Department of Energy’s Paducah Site Reaches Million-Hour Safety Milestone

    Energy.gov [DOE]

    PADUCAH, KY – The U.S. Department of Energy’s Paducah Site has reached a million hours of safe work toward completing cleanup objectives to reduce environmental risk.

  7. Webinar: BioenergizeME Office Hours Webinar: Guide to the 2016...

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

    Guide to the 2016 BioenergizeME Infographic Challenge Webinar: BioenergizeME Office Hours Webinar: Guide to the 2016 BioenergizeME Infographic Challenge Webinar: BioenergizeME ...

  8. Y-12 Construction hits one million-hour mark without a lost-time...

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

    Construction hits one ... Y-12 Construction hits one million-hour mark without a lost-time accident Posted: August 30, 2012 - 5:30pm The B&W Y-12 Direct-Hire Construction team has ...

  9. Paducah Site Exceeds 2.5 Million Hours Without Lost Workdays

    Energy.gov [DOE]

    This month, EM’s cleanup contractor at the Paducah site celebrated surpassing 2.5 million work hours without lost workdays resulting from job-related injury or illness.

  10. Earth Hour 2009: March 28, 8:30-9:30 PM Local Time | Department...

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

    This global event asks everyone to "go dark" for an hour to make a powerful statement of ... Residents are requested to turn off their lights (and other energy-consuming appliances). ...

  11. Pilot Plant Completes Two 1,000-Hour Ethanol Performance Runs

    Energy.gov [DOE]

    ICM Inc. announced successful completion of two 1,000-hour performance runs of its patent-pending Generation 2.0 Co-Located Cellulosic Ethanol process at its cellulosic ethanol pilot plant in St....

  12. Workers at Paducah Site Exceed 1.5 Million Hours Without Lost-Time Injury, Illness

    Energy.gov [DOE]

    PADUCAH, Ky. – Workers with Paducah site infrastructure contractor Swift & Staley, Inc. recently exceeded 1.5 million hours without lost time away from work due to injury or illness, representing nine years of safe performance.

  13. EPA ENERGY STAR Webcast- Portfolio Manager® Office Hours, Focus Topic: Portfolio Manager 2015 Priorities

    Energy.gov [DOE]

    Portfolio Manager "Office Hours" is a live webinar that gives all users an opportunity to ask their questions directly to EPA in an open forum. We will plan to spend the first 20-30 minutes of each...

  14. Operating internationally

    SciTech Connect (OSTI)

    Seeley, R.S.

    1994-02-01

    When Enron Power Corp. took over a 28 MW power facility at the former US Naval base in Subic Bay, the Philippines, the company was required to employ 139 people to run the plant. This large labor force was necessary not because of the plant's operational needs, but because of local labor practices and unemployment pressures. Independent power companies have become all too familiar with the high cost and complexity of developing projects in emerging international markets. Some of the most significant issues involve taxation, unfamiliar legal systems, changing regulations, and foreign investment restrictions. In addition, questions about currency exchange, national credit worthiness, and political stability add to the difficulty of international development. However, one of the most daunting challenges centers not on development, but on long-term operations and maintenance (O M). A key concern is finding qualified labor. Most developers and O M companies agree that local people should run the plant, with the top person, or persons, thoroughly trained in the developer's company philosophy.

  15. Insights from Smart Meters: The Potential for Peak Hour Savings from Behavior-Based Programs

    Energy.gov [DOE]

    This report focuses on one example of the value that analysis of this data can provide: insights into whether BB efficiency programs have the potential to provide peak-hour energy savings. This is important because there is increasing interest in using BB programs as a stand-alone peak reduction program, as well as integrating behavior-based strategies into residential incentive-based DR programs and time-based retail rates as a way to augment peak-hour energy savings.

  16. Computer Code Gives Astrophysicists First Full Simulation of Star's Final Hours

    ScienceCinema (OSTI)

    Andy Nonaka

    2010-01-08

    The precise conditions inside a white dwarf star in the hours leading up to its explosive end as a Type Ia supernova are one of the mysteries confronting astrophysicists studying these massive stellar explosions. But now, a team of researchers, composed of three applied mathematicians at the U.S. Department of Energy's (DOE) Lawrence Berkeley National Laboratory and two astrophysicists, has created the first full-star simulation of the hours preceding the largest thermonuclear explosions in the universe.

  17. California Independent System Operator | Open Energy Information

    Open Energy Information (Open El) [EERE & EIA]

    search 200px Name: California Independent System Operator Address: California ISO P.O. Box 639014 Place: Folsom, California Zip: 95763-9014 Sector: Services Phone Number:...

  18. ARM - Measurement - Particle number concentration

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

    number concentration ARM Data Discovery Browse Data Comments? We would love to hear from you! Send us a note below or call us at 1-888-ARM-DATA. Send Measurement : Particle number concentration The number of particles present in any given volume of air. Categories Aerosols Instruments The above measurement is considered scientifically relevant for the following instruments. Refer to the datastream (netcdf) file headers of each instrument for a list of all available measurements, including those

  19. Compendium of Experimental Cetane Numbers

    SciTech Connect (OSTI)

    Yanowitz, J.; Ratcliff, M. A.; McCormick, R. L.; Taylor, J. D.; Murphy, M. J.

    2014-08-01

    This report is an updated version of the 2004 Compendium of Experimental Cetane Number Data and presents a compilation of measured cetane numbers for pure chemical compounds. It includes all available single compound cetane number data found in the scientific literature up until March 2014 as well as a number of unpublished values, most measured over the past decade at the National Renewable Energy Laboratory. This Compendium contains cetane values for 389 pure compounds, including 189 hydrocarbons and 201 oxygenates. More than 250 individual measurements are new to this version of the Compendium. For many compounds, numerous measurements are included, often collected by different researchers using different methods. Cetane number is a relative ranking of a fuel's autoignition characteristics for use in compression ignition engines; it is based on the amount of time between fuel injection and ignition, also known as ignition delay. The cetane number is typically measured either in a single-cylinder engine or a constant volume combustion chamber. Values in the previous Compendium derived from octane numbers have been removed, and replaced with a brief analysis of the correlation between cetane numbers and octane numbers. The discussion on the accuracy and precision of the most commonly used methods for measuring cetane has been expanded and the data has been annotated extensively to provide additional information that will help the reader judge the relative reliability of individual results.

  20. Advanced Materials for RSOFC Dual Operation with Low Degradation

    SciTech Connect (OSTI)

    Eric, Tang; Tony, Wood; Sofiane, Benhaddad; Casey, Brown; Hongpeng, He; Jeff, Nelson; Oliver, Grande; Ben, Nuttall; Mark, Richards; Randy, Petri

    2012-12-27

    Reversible solid oxide fuel cells (RSOFCs) are energy conversion devices. They are capable of operating in both power generation mode (SOFC) and electrolysis modes (SOEC). RSOFC can integrate renewable production of electricity and hydrogen when power generation and steam electrolysis are coupled in a system, which can turn intermittent solar and wind energy into "firm power." In this DOE EERE project, VPS continuously advanced RSOFC cell stack technology in the areas of endurance and performance. Over 20 types of RSOFC cells were developed in the project. Many of those exceeded performance (area specific resistance less than 300 mohmcm2) and endurance (degradation rate less than 4% per 1000 hours) targets in both fuel cell and electrolysis modes at 750C. One of those cells, RSOFC-7, further demonstrated the following: Steady-state electrolysis with a degradation rate of 1.5% per 1000 hours. Ultra high current electrolysis over 3 A/cm2 at 75% water electrolysis efficiency voltage of 1.67 V. Daily SOFC/SOEC cyclic test of over 600 days with a degradation rate of 1.5% per 1000 hours. Over 6000 SOFC/SOEC cycles in an accelerated 20-minute cycling with degradation less than 3% per 1000 cycles. In RSOFC stack development, a number of kW-class RSOFC stacks were developed and demonstrated the following: Steady-state electrolysis operation of over 5000 hours. Daily SOFC/SOEC cyclic test of 100 cycles. Scale up capability of using large area cells with 550 cm2 active area showing the potential for large-scale RSOFC stack development in the future. Although this project is an open-ended development project, this effort, leveraging Versa Power Systems' years of development experience, has the potential to bring renewable energy RSOFC storage systems significantly closer to commercial viability through improvements in RSOFC durability, performance, and cost. When unitized and deployed in renewable solar and wind installations, an RSOFC system can enable higher availability for

  1. Analysis of Actual Operating Conditions of an Off-grid Solid Oxide Fuel Cell

    SciTech Connect (OSTI)

    Dennis Witmer; Thomas Johnson; Jack Schmid

    2008-12-31

    Fuel cells have been proposed as ideal replacements for other technologies in remote locations such as Rural Alaska. A number of suppliers have developed systems that might be applicable in these locations, but there are several requirements that must be met before they can be deployed: they must be able to operate on portable fuels, and be able to operate with little operator assistance for long periods of time. This project was intended to demonstrate the operation of a 5 kW fuel cell on propane at a remote site (defined as one without access to grid power, internet, or cell phone, but on the road system). A fuel cell was purchased by the National Park Service for installation in their newly constructed visitor center at Exit Glacier in the Kenai Fjords National Park. The DOE participation in this project as initially scoped was for independent verification of the operation of this demonstration. This project met with mixed success. The fuel cell has operated over 6 seasons at the facility with varying degrees of success, with one very good run of about 1049 hours late in the summer of 2006, but in general the operation has been below expectations. There have been numerous stack failures, the efficiency of electrical generation has been lower than expected, and the field support effort required has been far higher than expected. Based on the results to date, it appears that this technology has not developed to the point where demonstrations in off road sites are justified.

  2. Rhode Island Natural Gas Number of Industrial Consumers (Number of

    U.S. Energy Information Administration (EIA) (indexed site)

    Elements) Industrial Consumers (Number of Elements) Rhode Island Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,158 1,152 1,122 1990's 1,135 1,107 1,096 1,066 1,064 359 363 336 325 302 2000's 317 283 54 236 223 223 245 256 243 260 2010's 249 245 248 271 266 260 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release

  3. South Dakota Natural Gas Number of Industrial Consumers (Number of

    U.S. Energy Information Administration (EIA) (indexed site)

    Elements) Industrial Consumers (Number of Elements) South Dakota Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 261 267 270 1990's 275 283 319 355 381 396 444 481 464 445 2000's 416 402 533 526 475 542 528 548 598 598 2010's 580 556 574 566 575 578 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date:

  4. Maine Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Maine Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 73 73 74 1990's 80 81 80 66 89 74 87 81 110 108 2000's 178 233 66 65 69 69 73 76 82 85 2010's 94 102 108 120 126 136 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  5. Montana Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Montana Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 435 435 428 1990's 457 452 459 462 453 463 466 462 454 397 2000's 71 73 439 412 593 716 711 693 693 396 2010's 384 381 372 372 369 366 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date:

  6. Nevada Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Nevada Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 93 98 100 1990's 100 113 114 117 119 120 121 93 93 109 2000's 90 90 96 97 179 192 207 220 189 192 2010's 184 177 177 195 219 215 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date:

  7. Arizona Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Arizona Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 358 344 354 1990's 526 532 532 526 519 530 534 480 514 555 2000's 526 504 488 450 414 425 439 395 383 390 2010's 368 371 379 383 386 400 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release

  8. Delaware Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Delaware Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 241 233 235 1990's 240 243 248 249 252 253 250 265 257 264 2000's 297 316 182 184 186 179 170 185 165 112 2010's 114 129 134 138 141 144 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release

  9. Idaho Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Idaho Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 219 132 64 1990's 62 65 66 75 144 167 183 189 203 200 2000's 217 198 194 191 196 195 192 188 199 187 2010's 184 178 179 183 189 187 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date:

  10. Calutron Operations | Y-12 National Security Complex

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

    Operations Calutron Operations

  11. BioenergizeME Office Hours Webinar: Must-Know Tips for the 2016 BioenergizeME Infographic Challenge

    Energy.gov [DOE]

    Infographics are a useful visual tool for explaining complex information, numbers, or data quickly and effectively. However, you do not need to be an experienced graphic designer to make an eye-catching infographic. To assist student teams with the 2016 BioenergizeME Infographic Challenge, this webinar will highlight strategies for designing engaging infographics and will provide creative approaches that can bring attention to your infographic and motivate others to share it across their social media networks. The webinar will also include lessons learned from previous challenges and tips from last year’s winning team. The U.S. Department of Energy (DOE) BioenergizeME Infographic Challenge engages 9th–12th-grade high school teams to research one of four cross-curricular bioenergy topics and design an infographic to share what they have learned. This webinar is part of the BioenergizeME Office Hours webinar series developed by the DOE Bioenergy Technologies Office.

  12. Use of annual profiles of hourly data for analyzing DOE-2 building simulation program results

    SciTech Connect (OSTI)

    Haberl, J.; MacDonald, M.; Eden, A.

    1987-06-01

    This paper presents an approach for improving potential building energy analyses using the DOE-2 computer program. The approach makes use of the ability to generate hour-by-hour data results from DOE-2 simulations, and uses a plotting package to generate 3-dimensional annual profiles of the hour-by-hour data for specific quantities of interest. The annual profiles of hourly data provide a graphical check of voluminous data in a condensed form allowing several different types of data to be plotted over a year. These profiles provide the user the opportunity to: check simulation results, check potential problems with simulations, provide graphs to customers who may want a simpler presentation, visualize interactions in simulations, and understand where weak areas may exist in simulations. Future analysis, using such profiles, may allow methods to be developed to check consistency between simulations, check for potential errors in modeling buildings, and better understand how simulations compared with data from real buildings. 14 refs., 24 figs.

  13. Departmental Business Instrument Numbering System

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

    2005-01-27

    The Order prescribes the procedures for assigning identifying numbers to all Department of Energy (DOE) and National Nuclear Security Administration (NNSA) business instruments. Cancels DOE O 540.1. Canceled by DOE O 540.1B.

  14. Departmental Business Instrument Numbering System

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

    2000-12-05

    To prescribe procedures for assigning identifying numbers to all Department of Energy (DOE), including the National Nuclear Security Administration, business instruments. Cancels DOE 1331.2B. Canceled by DOE O 540.1A.

  15. Sub-Hour Solar Data for Power System Modeling From Static Spatial Variability Analysis: Preprint

    SciTech Connect (OSTI)

    Hummon, M.; Ibanez, E.; Brinkman, G.; Lew, D.

    2012-12-01

    High penetration renewable integration studies need high quality solar power data with spatial-temporal correlations that are representative of a real system. This paper will summarize the research relating sequential point-source sub-hour global horizontal irradiance (GHI) values to static, spatially distributed GHI values. This research led to the development of an algorithm for generating coherent sub-hour datasets that span distances ranging from 10 km to 4,000 km. The algorithm, in brief, generates synthetic GHI values at an interval of one-minute, for a specific location, using SUNY/Clean Power Research, satellite-derived, hourly irradiance values for the nearest grid cell to that location and grid cells within 40 km.

  16. Tennessee Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Tennessee Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 77,104 81,159 84,040 1990's 88,753 89,863 91,999 94,860 97,943 101,561 103,867 105,925 109,772 112,978 2000's 115,691 118,561 120,130 131,916 125,042 124,755 126,970 126,324 128,007 127,704 2010's 127,914 128,969 130,139 131,091 131,027 132,392 - = No Data Reported; -- = Not Applicable; NA = Not

  17. Tennessee Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Tennessee Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,206 2,151 2,555 1990's 2,361 2,369 2,425 2,512 2,440 2,393 2,306 2,382 5,149 2,159 2000's 2,386 2,704 2,657 2,755 2,738 2,498 2,545 2,656 2,650 2,717 2010's 2,702 2,729 2,679 2,581 2,595 2,651 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  18. Tennessee Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Tennessee Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 534,882 565,856 599,042 1990's 627,031 661,105 696,140 733,363 768,421 804,724 841,232 867,793 905,757 937,896 2000's 969,537 993,363 1,009,225 1,022,628 1,037,429 1,049,307 1,063,328 1,071,756 1,084,102 1,083,573 2010's 1,085,387 1,089,009 1,084,726 1,094,122 1,106,917 1,124,572 - = No Data

  19. Texas Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Texas Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 294,879 284,013 270,227 1990's 268,181 269,411 292,990 297,516 306,376 325,785 329,287 332,077 320,922 314,598 2000's 315,906 314,858 317,446 320,786 322,242 322,999 329,918 326,812 324,671 313,384 2010's 312,277 314,041 314,811 314,036 316,756 319,512 - = No Data Reported; -- = Not Applicable; NA = Not

  20. Texas Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Texas Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 4,852 4,427 13,383 1990's 13,659 13,770 5,481 5,823 5,222 9,043 8,796 5,339 5,318 5,655 2000's 11,613 10,047 9,143 9,015 9,359 9,136 8,664 11,063 5,568 8,581 2010's 8,779 8,713 8,953 8,525 8,398 6,655 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  1. Texas Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Texas Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 3,155,948 3,166,168 3,201,316 1990's 3,232,849 3,274,482 3,285,025 3,346,809 3,350,314 3,446,120 3,501,853 3,543,027 3,600,505 3,613,864 2000's 3,704,501 3,738,260 3,809,370 3,859,647 3,939,101 3,984,481 4,067,508 4,156,991 4,205,412 4,248,613 2010's 4,288,495 4,326,156 4,370,057 4,424,103 4,469,282

  2. Pennsylvania Natural Gas Number of Commercial Consumers (Number of

    U.S. Energy Information Administration (EIA) (indexed site)

    Elements) Commercial Consumers (Number of Elements) Pennsylvania Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 166,901 172,615 178,545 1990's 186,772 191,103 193,863 198,299 206,812 209,245 214,340 215,057 216,519 223,732 2000's 228,037 225,911 226,957 227,708 231,051 233,132 231,540 234,597 233,462 233,334 2010's 233,751 233,588 235,049 237,922 239,681 241,682 - = No Data Reported; -- = Not

  3. Pennsylvania Natural Gas Number of Industrial Consumers (Number of

    U.S. Energy Information Administration (EIA) (indexed site)

    Elements) Industrial Consumers (Number of Elements) Pennsylvania Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 6,089 6,070 6,023 1990's 6,238 6,344 6,496 6,407 6,388 6,328 6,441 6,492 6,736 7,080 2000's 6,330 6,159 5,880 5,577 5,726 5,577 5,241 4,868 4,772 4,745 2010's 4,624 5,007 5,066 5,024 5,084 4,932 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  4. Pennsylvania Natural Gas Number of Residential Consumers (Number of

    U.S. Energy Information Administration (EIA) (indexed site)

    Elements) Residential Consumers (Number of Elements) Pennsylvania Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,237,877 2,271,801 2,291,242 1990's 2,311,795 2,333,377 2,363,575 2,386,249 2,393,053 2,413,715 2,431,909 2,452,524 2,493,639 2,486,704 2000's 2,519,794 2,542,724 2,559,024 2,572,584 2,591,458 2,600,574 2,605,782 2,620,755 2,631,340 2,635,886 2010's 2,646,211 2,667,392 2,678,547

  5. Rhode Island Natural Gas Number of Commercial Consumers (Number of

    U.S. Energy Information Administration (EIA) (indexed site)

    Elements) Commercial Consumers (Number of Elements) Rhode Island Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 15,128 16,096 16,924 1990's 17,765 18,430 18,607 21,178 21,208 21,472 21,664 21,862 22,136 22,254 2000's 22,592 22,815 23,364 23,270 22,994 23,082 23,150 23,007 23,010 22,988 2010's 23,049 23,177 23,359 23,742 23,934 24,088 - = No Data Reported; -- = Not Applicable; NA = Not

  6. Rhode Island Natural Gas Number of Residential Consumers (Number of

    U.S. Energy Information Administration (EIA) (indexed site)

    Elements) Residential Consumers (Number of Elements) Rhode Island Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 180,656 185,861 190,796 1990's 195,100 196,438 197,926 198,563 200,959 202,947 204,259 212,777 208,208 211,097 2000's 214,474 216,781 219,769 221,141 223,669 224,320 225,027 223,589 224,103 224,846 2010's 225,204 225,828 228,487 231,763 233,786 236,323 - = No Data Reported; -- =

  7. South Carolina Natural Gas Number of Commercial Consumers (Number of

    U.S. Energy Information Administration (EIA) (indexed site)

    Elements) Commercial Consumers (Number of Elements) South Carolina Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 35,414 37,075 38,856 1990's 39,904 39,999 40,968 42,191 45,487 47,293 48,650 50,817 52,237 53,436 2000's 54,794 55,257 55,608 55,909 56,049 56,974 57,452 57,544 56,317 55,850 2010's 55,853 55,846 55,908 55,997 56,323 56,871 - = No Data Reported; -- = Not Applicable; NA = Not

  8. South Carolina Natural Gas Number of Industrial Consumers (Number of

    U.S. Energy Information Administration (EIA) (indexed site)

    Elements) Industrial Consumers (Number of Elements) South Carolina Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,256 1,273 1,307 1990's 1,384 1,400 1,568 1,625 1,928 1,802 1,759 1,764 1,728 1,768 2000's 1,715 1,702 1,563 1,574 1,528 1,535 1,528 1,472 1,426 1,358 2010's 1,325 1,329 1,435 1,452 1,442 1,438 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  9. South Carolina Natural Gas Number of Residential Consumers (Number of

    U.S. Energy Information Administration (EIA) (indexed site)

    Elements) Residential Consumers (Number of Elements) South Carolina Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 302,321 313,831 327,527 1990's 339,486 344,763 357,818 370,411 416,773 412,259 426,088 443,093 460,141 473,799 2000's 489,340 501,161 508,686 516,362 527,008 541,523 554,953 570,213 561,196 565,774 2010's 570,797 576,594 583,633 593,286 605,644 620,555 - = No Data Reported; -- =

  10. South Dakota Natural Gas Number of Commercial Consumers (Number of

    U.S. Energy Information Administration (EIA) (indexed site)

    Elements) Commercial Consumers (Number of Elements) South Dakota Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 12,480 12,438 12,771 1990's 13,443 13,692 14,133 16,523 15,539 16,285 16,880 17,432 17,972 18,453 2000's 19,100 19,378 19,794 20,070 20,457 20,771 21,149 21,502 21,819 22,071 2010's 22,267 22,570 22,955 23,214 23,591 24,040 - = No Data Reported; -- = Not Applicable; NA = Not

  11. South Dakota Natural Gas Number of Residential Consumers (Number of

    U.S. Energy Information Administration (EIA) (indexed site)

    Elements) Residential Consumers (Number of Elements) South Dakota Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 101,468 102,084 103,538 1990's 105,436 107,846 110,291 128,029 119,544 124,152 127,269 130,307 133,095 136,789 2000's 142,075 144,310 147,356 150,725 148,105 157,457 160,481 163,458 165,694 168,096 2010's 169,838 170,877 173,856 176,204 179,042 182,568 - = No Data Reported; -- =

  12. Louisiana Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Louisiana Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 67,382 66,472 64,114 1990's 62,770 61,574 61,030 62,055 62,184 62,930 62,101 62,270 63,029 62,911 2000's 62,710 62,241 62,247 63,512 60,580 58,409 57,097 57,127 57,066 58,396 2010's 58,562 58,749 63,381 59,147 58,996 57,873 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld

  13. Louisiana Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Louisiana Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,617 1,503 1,531 1990's 1,504 1,469 1,452 1,592 1,737 1,383 1,444 1,406 1,380 1,397 2000's 1,318 1,440 1,357 1,291 1,460 1,086 962 945 988 954 2010's 942 920 963 916 883 845 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  14. Louisiana Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Louisiana Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 952,079 946,970 934,472 1990's 934,007 936,423 940,403 941,294 945,387 957,558 945,967 962,786 962,436 961,925 2000's 964,133 952,753 957,048 958,795 940,400 905,857 868,353 879,612 886,084 889,570 2010's 893,400 897,513 963,688 901,635 903,686 888,023 - = No Data Reported; -- = Not Applicable; NA

  15. Maine Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Maine Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 3,435 3,731 3,986 1990's 4,250 4,455 4,838 4,979 5,297 5,819 6,414 6,606 6,662 6,582 2000's 6,954 6,936 7,375 7,517 7,687 8,178 8,168 8,334 8,491 8,815 2010's 9,084 9,681 10,179 11,415 11,810 11,888 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  16. Maine Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Maine Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 12,134 11,933 11,902 1990's 12,000 12,424 13,766 13,880 14,104 14,917 14,982 15,221 15,646 15,247 2000's 17,111 17,302 17,921 18,385 18,707 18,633 18,824 18,921 19,571 20,806 2010's 21,142 22,461 23,555 24,765 27,047 31,011 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  17. Maryland Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Maryland Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 51,252 53,045 54,740 1990's 55,576 61,878 62,858 63,767 64,698 66,094 69,991 69,056 67,850 69,301 2000's 70,671 70,691 71,824 72,076 72,809 73,780 74,584 74,856 75,053 75,771 2010's 75,192 75,788 75,799 77,117 77,846 78,138 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld

  18. Maryland Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Maryland Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 5,222 5,397 5,570 1990's 5,646 520 514 496 516 481 430 479 1,472 536 2000's 329 795 1,434 1,361 1,354 1,325 1,340 1,333 1,225 1,234 2010's 1,255 1,226 1,163 1,173 1,179 1,169 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data.

  19. Maryland Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Maryland Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 755,294 760,754 767,219 1990's 774,707 782,373 894,677 807,204 824,137 841,772 871,012 890,195 901,455 939,029 2000's 941,384 959,772 978,319 987,863 1,009,455 1,024,955 1,040,941 1,053,948 1,057,521 1,067,807 2010's 1,071,566 1,077,168 1,078,978 1,099,272 1,101,292 1,113,342 - = No Data Reported;

  20. Massachusetts Natural Gas Number of Commercial Consumers (Number of

    U.S. Energy Information Administration (EIA) (indexed site)

    Elements) Commercial Consumers (Number of Elements) Massachusetts Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 84,636 93,005 92,252 1990's 85,775 88,746 85,873 102,187 92,744 104,453 105,889 107,926 108,832 113,177 2000's 117,993 120,984 122,447 123,006 125,107 120,167 126,713 128,965 242,693 153,826 2010's 144,487 138,225 142,825 144,246 139,556 140,533 - = No Data Reported; -- = Not

  1. Massachusetts Natural Gas Number of Industrial Consumers (Number of

    U.S. Energy Information Administration (EIA) (indexed site)

    Elements) Industrial Consumers (Number of Elements) Massachusetts Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 5,626 7,199 13,057 1990's 6,539 5,006 8,723 7,283 8,019 10,447 10,952 11,058 11,245 8,027 2000's 8,794 9,750 9,090 11,272 10,949 12,019 12,456 12,678 36,928 19,208 2010's 12,751 10,721 10,840 11,063 10,946 11,266 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  2. Massachusetts Natural Gas Number of Residential Consumers (Number of

    U.S. Energy Information Administration (EIA) (indexed site)

    Elements) Residential Consumers (Number of Elements) Massachusetts Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,082,777 1,100,635 1,114,920 1990's 1,118,429 1,127,536 1,137,911 1,155,443 1,179,869 1,180,860 1,188,317 1,204,494 1,212,486 1,232,887 2000's 1,278,781 1,283,008 1,295,952 1,324,715 1,306,142 1,297,508 1,348,848 1,361,470 1,236,480 1,370,353 2010's 1,389,592 1,408,314 1,447,947

  3. Michigan Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Michigan Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 178,469 185,961 191,474 1990's 195,766 198,890 201,561 204,453 207,629 211,817 214,843 222,726 224,506 227,159 2000's 230,558 225,109 247,818 246,123 246,991 253,415 254,923 253,139 252,382 252,017 2010's 249,309 249,456 249,994 250,994 253,127 254,484 - = No Data Reported; -- = Not Applicable; NA =

  4. Michigan Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Michigan Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 10,885 11,117 11,452 1990's 11,500 11,446 11,460 11,425 11,308 11,454 11,848 12,233 11,888 14,527 2000's 11,384 11,210 10,468 10,378 10,088 10,049 9,885 9,728 10,563 18,186 2010's 9,332 9,088 8,833 8,497 8,156 7,931 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  5. Michigan Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Michigan Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,452,554 2,491,149 2,531,304 1990's 2,573,570 2,609,561 2,640,579 2,677,085 2,717,683 2,767,190 2,812,876 2,859,483 2,903,698 2,949,628 2000's 2,999,737 3,011,205 3,110,743 3,140,021 3,161,370 3,187,583 3,193,920 3,188,152 3,172,623 3,169,026 2010's 3,152,468 3,153,895 3,161,033 3,180,349

  6. Minnesota Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Minnesota Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 88,789 90,256 92,916 1990's 95,474 97,388 99,707 93,062 102,857 103,874 105,531 108,686 110,986 114,127 2000's 116,529 119,007 121,751 123,123 125,133 126,310 129,149 128,367 130,847 131,801 2010's 132,163 132,938 134,394 135,557 136,380 138,871 - = No Data Reported; -- = Not Applicable; NA = Not

  7. Minnesota Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Minnesota Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,585 2,670 2,638 1990's 2,574 2,486 2,515 2,477 2,592 2,531 2,564 2,233 2,188 2,267 2000's 2,025 1,996 2,029 2,074 2,040 1,432 1,257 1,146 1,131 2,039 2010's 2,106 1,770 1,793 1,870 1,880 1,868 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  8. Minnesota Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Minnesota Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 872,148 894,380 911,001 1990's 946,107 970,941 998,201 1,074,631 1,049,263 1,080,009 1,103,709 1,134,019 1,161,423 1,190,190 2000's 1,222,397 1,249,748 1,282,751 1,308,143 1,338,061 1,364,237 1,401,362 1,401,623 1,413,162 1,423,703 2010's 1,429,681 1,436,063 1,445,824 1,459,134 1,472,663 1,496,790

  9. Mississippi Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Mississippi Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 43,362 44,170 44,253 1990's 43,184 43,693 44,313 45,310 43,803 45,444 46,029 47,311 45,345 47,620 2000's 50,913 51,109 50,468 50,928 54,027 54,936 55,741 56,155 55,291 50,713 2010's 50,537 50,636 50,689 50,153 49,911 49,821 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  10. Mississippi Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Mississippi Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,312 1,263 1,282 1990's 1,317 1,314 1,327 1,324 1,313 1,298 1,241 1,199 1,165 1,246 2000's 1,199 1,214 1,083 1,161 996 1,205 1,181 1,346 1,132 1,141 2010's 980 982 936 933 943 930 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company

  11. Mississippi Natural Gas Number of Residential Consumers (Number of

    U.S. Energy Information Administration (EIA) (indexed site)

    Elements) Residential Consumers (Number of Elements) Mississippi Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 370,094 372,238 376,353 1990's 382,251 386,264 392,155 398,472 405,312 415,123 418,442 423,397 415,673 426,352 2000's 434,501 438,069 435,146 438,861 445,212 445,856 437,669 445,043 443,025 437,715 2010's 436,840 442,479 442,840 445,589 440,252 439,359 - = No Data Reported; -- =

  12. Missouri Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Missouri Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 96,711 97,939 99,721 1990's 105,164 117,675 125,174 125,571 132,378 130,318 133,445 135,553 135,417 133,464 2000's 133,969 135,968 137,924 140,057 141,258 142,148 143,632 142,965 141,529 140,633 2010's 138,670 138,214 144,906 142,495 143,134 141,216 - = No Data Reported; -- = Not Applicable; NA = Not

  13. Missouri Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Missouri Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,832 2,880 3,063 1990's 3,140 3,096 2,989 3,040 3,115 3,033 3,408 3,097 3,151 3,152 2000's 3,094 3,085 2,935 3,115 3,600 3,545 3,548 3,511 3,514 3,573 2010's 3,541 3,307 3,692 3,538 3,497 3,232 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  14. Missouri Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Missouri Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,180,546 1,194,985 1,208,523 1990's 1,213,305 1,211,342 1,220,203 1,225,921 1,281,007 1,259,102 1,275,465 1,293,032 1,307,563 1,311,865 2000's 1,324,282 1,326,160 1,340,726 1,343,614 1,346,773 1,348,743 1,353,892 1,354,173 1,352,015 1,348,781 2010's 1,348,549 1,342,920 1,389,910 1,357,740

  15. Montana Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Montana Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 21,382 22,246 22,219 1990's 23,331 23,185 23,610 24,373 25,349 26,329 26,374 27,457 28,065 28,424 2000's 29,215 29,429 30,250 30,814 31,357 31,304 31,817 32,472 33,008 33,731 2010's 34,002 34,305 34,504 34,909 35,205 35,777 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  16. Montana Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Montana Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 167,883 171,785 171,156 1990's 174,384 177,726 182,641 188,879 194,357 203,435 205,199 209,806 218,851 222,114 2000's 224,784 226,171 229,015 232,839 236,511 240,554 245,883 247,035 253,122 255,472 2010's 257,322 259,046 259,957 262,122 265,849 269,766 - = No Data Reported; -- = Not Applicable; NA =

  17. Nebraska Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Nebraska Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 60,707 61,365 60,377 1990's 60,405 60,947 61,319 60,599 62,045 61,275 61,117 51,661 63,819 53,943 2000's 55,194 55,692 56,560 55,999 57,087 57,389 56,548 55,761 58,160 56,454 2010's 56,246 56,553 56,608 58,005 57,191 57,521 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld

  18. Nebraska Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Nebraska Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 675 684 702 1990's 712 718 696 718 766 2,432 2,234 11,553 10,673 10,342 2000's 10,161 10,504 9,156 9,022 8,463 7,973 7,697 7,668 11,627 7,863 2010's 7,912 7,955 8,160 8,495 8,791 8,868 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  19. Nebraska Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Nebraska Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 400,218 403,657 406,723 1990's 407,094 413,354 418,611 413,358 428,201 427,720 439,931 444,970 523,790 460,173 2000's 475,673 476,275 487,332 492,451 497,391 501,279 499,504 494,005 512,013 512,551 2010's 510,776 514,481 515,338 527,397 522,408 525,165 - = No Data Reported; -- = Not Applicable; NA

  20. Nevada Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Nevada Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 18,294 18,921 19,924 1990's 20,694 22,124 22,799 23,207 24,521 25,593 26,613 27,629 29,030 30,521 2000's 31,789 32,782 33,877 34,590 35,792 37,093 38,546 40,128 41,098 41,303 2010's 40,801 40,944 41,192 41,710 42,338 42,860 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  1. Nevada Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Nevada Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 213,422 219,981 236,237 1990's 256,119 283,307 295,714 305,099 336,353 364,112 393,783 426,221 458,737 490,029 2000's 520,233 550,850 580,319 610,756 648,551 688,058 726,772 750,570 758,315 760,391 2010's 764,435 772,880 782,759 794,150 808,970 824,039 - = No Data Reported; -- = Not Applicable; NA =

  2. Ohio Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Ohio Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 213,601 219,257 225,347 1990's 233,075 236,519 237,861 240,684 245,190 250,223 259,663 254,991 258,076 266,102 2000's 269,561 269,327 271,160 271,203 272,445 277,767 270,552 272,555 272,899 270,596 2010's 268,346 268,647 267,793 269,081 269,758 269,981 - = No Data Reported; -- = Not Applicable; NA = Not

  3. Ohio Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Ohio Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 7,929 8,163 8,356 1990's 8,301 8,479 8,573 8,678 8,655 8,650 8,672 7,779 8,112 8,136 2000's 8,267 8,515 8,111 8,098 7,899 8,328 6,929 6,858 6,806 6,712 2010's 6,571 6,482 6,381 6,554 6,526 6,502 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  4. Ohio Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Ohio Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,648,972 2,678,838 2,714,839 1990's 2,766,912 2,801,716 2,826,713 2,867,959 2,921,536 2,967,375 2,994,891 3,041,948 3,050,960 3,111,108 2000's 3,178,840 3,195,584 3,208,466 3,225,908 3,250,068 3,272,307 3,263,062 3,273,791 3,262,716 3,253,184 2010's 3,240,619 3,236,160 3,244,274 3,271,074 3,283,968

  5. Oklahoma Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Oklahoma Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 87,824 86,666 86,172 1990's 85,790 86,744 87,120 88,181 87,494 88,358 89,852 90,284 89,711 80,986 2000's 80,558 79,045 80,029 79,733 79,512 78,726 78,745 93,991 94,247 94,314 2010's 92,430 93,903 94,537 95,385 96,005 96,471 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld

  6. Oklahoma Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Oklahoma Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,772 2,689 2,877 1990's 2,889 2,840 2,859 2,912 2,853 2,845 2,843 2,531 3,295 3,040 2000's 2,821 3,403 3,438 3,367 3,283 2,855 2,811 2,822 2,920 2,618 2010's 2,731 2,733 2,872 2,958 3,062 3,059 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  7. Oklahoma Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Oklahoma Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 809,171 805,107 806,875 1990's 814,296 824,172 832,677 842,130 845,448 856,604 866,531 872,454 877,236 867,922 2000's 859,951 868,314 875,338 876,420 875,271 880,403 879,589 920,616 923,650 924,745 2010's 914,869 922,240 927,346 931,981 937,237 941,137 - = No Data Reported; -- = Not Applicable; NA

  8. Oregon Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Oregon Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 40,967 41,998 43,997 1990's 47,175 55,374 50,251 51,910 53,700 55,409 57,613 60,419 63,085 65,034 2000's 66,893 68,098 69,150 74,515 71,762 73,520 74,683 80,998 76,868 76,893 2010's 77,370 77,822 78,237 79,276 80,480 80,877 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  9. Oregon Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Oregon Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 676 1,034 738 1990's 699 787 740 696 765 791 799 704 695 718 2000's 717 821 842 926 907 1,118 1,060 1,136 1,075 1,051 2010's 1,053 1,066 1,076 1,085 1,099 1,117 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date:

  10. Oregon Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Oregon Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 280,670 288,066 302,156 1990's 326,177 376,166 354,256 371,151 391,845 411,465 433,638 456,960 477,796 502,000 2000's 523,952 542,799 563,744 625,398 595,495 626,685 647,635 664,455 674,421 675,582 2010's 682,737 688,681 693,507 700,211 707,010 717,999 - = No Data Reported; -- = Not Applicable; NA =

  11. Alabama Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Alabama Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 53 54,306 55,400 56,822 1990's 56,903 57,265 58,068 57,827 60,320 60,902 62,064 65,919 76,467 64,185 2000's 66,193 65,794 65,788 65,297 65,223 65,294 66,337 65,879 65,313 67,674 2010's 68,163 67,696 67,252 67,136 67,847 67,746 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld

  12. Alabama Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Alabama Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2 2,313 2,293 2,380 1990's 2,431 2,523 2,509 2,458 2,477 2,491 2,512 2,496 2,464 2,620 2000's 2,792 2,781 2,730 2,743 2,799 2,787 2,735 2,704 2,757 3,057 2010's 3,039 2,988 3,045 3,143 3,244 3,300 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  13. Alabama Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Alabama Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 656 662,217 668,432 683,528 1990's 686,149 700,195 711,043 730,114 744,394 751,890 766,322 781,711 788,464 775,311 2000's 805,689 807,770 806,389 809,754 806,660 809,454 808,801 796,476 792,236 785,005 2010's 778,985 772,892 767,396 765,957 769,900 768,568 - = No Data Reported; -- = Not Applicable;

  14. Alaska Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Alaska Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 11 11,484 11,649 11,806 1990's 11,921 12,071 12,204 12,359 12,475 12,584 12,732 12,945 13,176 13,409 2000's 13,711 14,002 14,342 14,502 13,999 14,120 14,384 13,408 12,764 13,215 2010's 12,998 13,027 13,133 13,246 13,399 13,549 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld

  15. Alaska Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Alaska Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 66 67,648 68,612 69,540 1990's 70,808 72,565 74,268 75,842 77,670 79,474 81,348 83,596 86,243 88,924 2000's 91,297 93,896 97,077 100,404 104,360 108,401 112,269 115,500 119,039 120,124 2010's 121,166 121,736 122,983 124,411 126,416 128,605 - = No Data Reported; -- = Not Applicable; NA = Not

  16. Arizona Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Arizona Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 46 46,702 46,636 46,776 1990's 47,292 53,982 47,781 47,678 48,568 49,145 49,693 50,115 51,712 53,022 2000's 54,056 54,724 56,260 56,082 56,186 56,572 57,091 57,169 57,586 57,191 2010's 56,676 56,547 56,532 56,585 56,649 56,793 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld

  17. Arizona Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Arizona Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 545 567,962 564,195 572,461 1990's 586,866 642,659 604,899 610,337 635,335 661,192 689,597 724,911 764,167 802,469 2000's 846,016 884,789 925,927 957,442 993,885 1,042,662 1,088,574 1,119,266 1,128,264 1,130,047 2010's 1,138,448 1,146,286 1,157,688 1,172,003 1,186,794 1,200,783 - = No Data Reported;

  18. Arkansas Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Arkansas Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 60 60,355 61,630 61,848 1990's 61,530 61,731 62,221 62,952 63,821 65,490 67,293 68,413 69,974 71,389 2000's 72,933 71,875 71,530 71,016 70,655 69,990 69,475 69,495 69,144 69,043 2010's 67,987 67,815 68,765 68,791 69,011 69,265 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  19. Arkansas Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Arkansas Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1 1,410 1,151 1,412 1990's 1,396 1,367 1,319 1,364 1,417 1,366 1,488 1,336 1,300 1,393 2000's 1,414 1,122 1,407 1,269 1,223 1,120 1,120 1,055 1,104 1,025 2010's 1,079 1,133 990 1,020 1,009 1,023 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  20. Arkansas Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Arkansas Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 475 480,839 485,112 491,110 1990's 488,850 495,148 504,722 513,466 521,176 531,182 539,952 544,460 550,017 554,121 2000's 560,055 552,716 553,192 553,211 554,844 555,861 555,905 557,966 556,746 557,355 2010's 549,970 551,795 549,959 549,764 549,034 550,108 - = No Data Reported; -- = Not Applicable;

  1. California Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) California Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 413 404,507 407,435 410,231 1990's 415,073 421,278 412,467 411,648 411,140 411,535 408,294 406,803 588,224 416,791 2000's 413,003 416,036 420,690 431,795 432,367 434,899 442,052 446,267 447,160 441,806 2010's 439,572 440,990 442,708 444,342 443,115 446,510 - = No Data Reported; -- = Not Applicable;

  2. California Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) California Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 31 44,764 44,680 46,243 1990's 46,048 44,865 40,528 42,748 38,750 38,457 36,613 35,830 36,235 36,435 2000's 35,391 34,893 33,725 34,617 41,487 40,226 38,637 39,134 39,591 38,746 2010's 38,006 37,575 37,686 37,996 37,548 36,854 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  3. California Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) California Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 7,626 7,904,858 8,113,034 8,313,776 1990's 8,497,848 8,634,774 8,680,613 8,726,187 8,790,733 8,865,541 8,969,308 9,060,473 9,181,928 9,331,206 2000's 9,370,797 9,603,122 9,726,642 9,803,311 9,957,412 10,124,433 10,329,224 10,439,220 10,515,162 10,510,950 2010's 10,542,584 10,625,190 10,681,916

  4. Colorado Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Colorado Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 108 109,770 110,769 112,004 1990's 112,661 113,945 114,898 115,924 115,994 118,502 121,221 123,580 125,178 129,041 2000's 131,613 134,393 136,489 138,621 138,543 137,513 139,746 141,420 144,719 145,624 2010's 145,460 145,837 145,960 150,145 150,235 150,545 - = No Data Reported; -- = Not Applicable;

  5. Colorado Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Colorado Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1 896 923 976 1990's 1,018 1,074 1,108 1,032 1,176 1,528 2,099 2,923 3,349 4,727 2000's 4,994 4,729 4,337 4,054 4,175 4,318 4,472 4,592 4,816 5,084 2010's 6,232 6,529 6,906 7,293 7,823 8,098 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  6. Colorado Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Colorado Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 925 942,571 955,810 970,512 1990's 983,592 1,002,154 1,022,542 1,044,699 1,073,308 1,108,899 1,147,743 1,183,978 1,223,433 1,265,032 2000's 1,315,619 1,365,413 1,412,923 1,453,974 1,496,876 1,524,813 1,558,911 1,583,945 1,606,602 1,622,434 2010's 1,634,587 1,645,716 1,659,808 1,672,312 1,690,581

  7. Connecticut Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Connecticut Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 38 40,886 41,594 43,703 1990's 45,364 45,925 46,859 45,529 45,042 45,935 47,055 48,195 47,110 49,930 2000's 52,384 49,815 49,383 50,691 50,839 52,572 52,982 52,389 53,903 54,510 2010's 54,842 55,028 55,407 55,500 56,591 57,403 - = No Data Reported; -- = Not Applicable; NA = Not Available; W =

  8. Connecticut Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Connecticut Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2 2,709 2,818 2,908 1990's 3,061 2,921 2,923 2,952 3,754 3,705 3,435 3,459 3,441 3,465 2000's 3,683 3,881 3,716 3,625 3,470 3,437 3,393 3,317 3,196 3,138 2010's 3,063 3,062 3,148 4,454 4,217 3,945 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  9. Connecticut Natural Gas Number of Residential Consumers (Number of

    U.S. Energy Information Administration (EIA) (indexed site)

    Elements) Residential Consumers (Number of Elements) Connecticut Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 400 411,349 417,831 424,036 1990's 428,912 430,078 432,244 427,761 428,157 431,909 433,778 436,119 438,716 442,457 2000's 458,388 458,404 462,574 466,913 469,332 475,221 478,849 482,902 487,320 489,349 2010's 490,185 494,970 504,138 513,492 522,658 531,380 - = No Data Reported; --

  10. Delaware Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Delaware Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 6 6,180 6,566 7,074 1990's 7,485 7,895 8,173 8,409 8,721 9,133 9,518 9,807 10,081 10,441 2000's 9,639 11,075 11,463 11,682 11,921 12,070 12,345 12,576 12,703 12,839 2010's 12,861 12,931 12,997 13,163 13,352 13,430 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid

  11. Delaware Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Delaware Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 81 82,829 84,328 86,428 1990's 88,894 91,467 94,027 96,914 100,431 103,531 106,548 109,400 112,507 115,961 2000's 117,845 122,829 126,418 129,870 133,197 137,115 141,276 145,010 147,541 149,006 2010's 150,458 152,005 153,307 155,627 158,502 161,607 - = No Data Reported; -- = Not Applicable; NA =

  12. Georgia Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Georgia Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 94 98,809 102,277 106,690 1990's 108,295 109,659 111,423 114,889 117,980 120,122 123,200 123,367 126,050 225,020 2000's 128,275 130,373 128,233 129,867 128,923 128,389 127,843 127,832 126,804 127,347 2010's 124,759 123,454 121,243 126,060 122,578 123,307 - = No Data Reported; -- = Not Applicable; NA =

  13. Georgia Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Georgia Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 3 3,034 3,144 3,079 1990's 3,153 3,124 3,186 3,302 3,277 3,261 3,310 3,310 3,262 5,580 2000's 3,294 3,330 3,219 3,326 3,161 3,543 3,053 2,913 2,890 2,254 2010's 2,174 2,184 2,112 2,242 2,481 2,548 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  14. Georgia Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Georgia Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,190 1,237,201 1,275,128 1,308,972 1990's 1,334,935 1,363,723 1,396,860 1,430,626 1,460,141 1,495,992 1,538,458 1,553,948 1,659,730 1,732,865 2000's 1,680,749 1,737,850 1,735,063 1,747,017 1,752,346 1,773,121 1,726,239 1,793,650 1,791,256 1,744,934 2010's 1,740,587 1,740,006 1,739,543 1,805,425

  15. Hawaii Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Hawaii Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,896 2,852 2,842 1990's 2,837 2,786 2,793 3,222 2,805 2,825 2,823 2,783 2,761 2,763 2000's 2,768 2,777 2,781 2,804 2,578 2,572 2,548 2,547 2,540 2,535 2010's 2,551 2,560 2,545 2,627 2,789 2,815 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  16. Hawaii Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Hawaii Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 28,502 28,761 28,970 1990's 29,137 29,701 29,805 29,984 30,614 30,492 31,017 30,990 30,918 30,708 2000's 30,751 30,794 30,731 30,473 26,255 26,219 25,982 25,899 25,632 25,466 2010's 25,389 25,305 25,184 26,374 28,919 28,952 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld

  17. Idaho Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Idaho Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 17,482 18,454 18,813 1990's 19,452 20,328 21,145 21,989 22,999 24,150 25,271 26,436 27,697 28,923 2000's 30,018 30,789 31,547 32,274 33,104 33,362 33,625 33,767 37,320 38,245 2010's 38,506 38,912 39,202 39,722 40,229 40,744 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  18. Idaho Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Idaho Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 104,824 111,532 113,898 1990's 113,954 126,282 136,121 148,582 162,971 175,320 187,756 200,165 213,786 227,807 2000's 240,399 251,004 261,219 274,481 288,380 301,357 316,915 323,114 336,191 342,277 2010's 346,602 350,871 353,963 359,889 367,394 374,557 - = No Data Reported; -- = Not Applicable; NA =

  19. Illinois Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Illinois Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 241,367 278,473 252,791 1990's 257,851 261,107 263,988 268,104 262,308 264,756 265,007 268,841 271,585 274,919 2000's 279,179 278,506 279,838 281,877 273,967 276,763 300,606 296,465 298,418 294,226 2010's 291,395 293,213 297,523 282,743 294,391 295,869 - = No Data Reported; -- = Not Applicable; NA =

  20. Illinois Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Illinois Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 19,460 20,015 25,161 1990's 25,991 26,489 27,178 27,807 25,788 25,929 29,493 28,472 28,063 27,605 2000's 27,348 27,421 27,477 26,698 29,187 29,887 26,109 24,000 23,737 23,857 2010's 25,043 23,722 23,390 23,804 23,829 23,049 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld

  1. Illinois Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Illinois Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 3,170,364 3,180,199 3,248,117 1990's 3,287,091 3,320,285 3,354,679 3,388,983 3,418,052 3,452,975 3,494,545 3,521,707 3,556,736 3,594,071 2000's 3,631,762 3,670,693 3,688,281 3,702,308 3,754,132 3,975,961 3,812,121 3,845,441 3,869,308 3,839,438 2010's 3,842,206 3,855,942 3,878,806 3,838,120

  2. Indiana Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Indiana Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 116,571 119,458 122,803 1990's 124,919 128,223 129,973 131,925 134,336 137,162 139,097 140,515 141,307 145,631 2000's 148,411 148,830 150,092 151,586 151,943 159,649 154,322 155,885 157,223 155,615 2010's 156,557 161,293 158,213 158,965 159,596 160,051 - = No Data Reported; -- = Not Applicable; NA =

  3. Indiana Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Indiana Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 5,497 5,696 6,196 1990's 6,439 6,393 6,358 6,508 6,314 6,250 6,586 6,920 6,635 19,069 2000's 10,866 9,778 10,139 8,913 5,368 5,823 5,350 5,427 5,294 5,190 2010's 5,145 5,338 5,204 5,178 5,098 5,095 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  4. Indiana Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Indiana Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,250,476 1,275,401 1,306,747 1990's 1,327,772 1,358,640 1,377,023 1,402,770 1,438,483 1,463,640 1,489,647 1,509,142 1,531,914 1,570,253 2000's 1,604,456 1,613,373 1,657,640 1,644,715 1,588,738 1,707,195 1,661,186 1,677,857 1,678,158 1,662,663 2010's 1,669,026 1,707,148 1,673,132 1,681,841 1,693,267

  5. Iowa Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Iowa Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 80,797 81,294 82,549 1990's 83,047 84,387 85,325 86,452 86,918 88,585 89,663 90,643 91,300 92,306 2000's 93,836 95,485 96,496 96,712 97,274 97,767 97,823 97,979 98,144 98,416 2010's 98,396 98,541 99,113 99,017 99,186 99,662 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  6. Iowa Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Iowa Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 2,033 1,937 1,895 1990's 1,883 1,866 1,835 1,903 1,957 1,957 2,066 1,839 1,862 1,797 2000's 1,831 1,830 1,855 1,791 1,746 1,744 1,670 1,651 1,652 1,626 2010's 1,528 1,465 1,469 1,491 1,572 1,572 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual

  7. Iowa Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Iowa Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 690,532 689,655 701,687 1990's 706,842 716,088 729,081 740,722 750,678 760,848 771,109 780,746 790,162 799,015 2000's 812,323 818,313 824,218 832,230 839,415 850,095 858,915 865,553 872,980 875,781 2010's 879,713 883,733 892,123 895,414 900,420 908,058 - = No Data Reported; -- = Not Applicable; NA =

  8. Kansas Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Kansas Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 82,934 83,810 85,143 1990's 85,539 86,874 86,840 87,735 86,457 88,163 89,168 85,018 89,654 86,003 2000's 87,007 86,592 87,397 88,030 86,640 85,634 85,686 85,376 84,703 84,715 2010's 84,446 84,874 84,673 84,969 85,654 86,034 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to

  9. Kansas Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Kansas Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 4,440 4,314 4,366 1990's 4,357 3,445 3,296 4,369 3,560 3,079 2,988 7,014 10,706 5,861 2000's 8,833 9,341 9,891 9,295 8,955 8,300 8,152 8,327 8,098 7,793 2010's 7,664 7,954 7,970 7,877 7,328 7,218 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  10. Kansas Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Kansas Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 725,676 733,101 731,792 1990's 747,081 753,839 762,545 777,658 773,357 797,524 804,213 811,975 841,843 824,803 2000's 833,662 836,486 843,353 850,464 855,272 856,761 862,203 858,304 853,125 855,454 2010's 853,842 854,730 854,800 858,572 860,441 861,419 - = No Data Reported; -- = Not Applicable; NA =

  11. Kentucky Natural Gas Number of Commercial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Commercial Consumers (Number of Elements) Kentucky Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 63,024 63,971 65,041 1990's 67,086 68,461 69,466 71,998 73,562 74,521 76,079 77,693 80,147 80,283 2000's 81,588 81,795 82,757 84,110 84,493 85,243 85,236 85,210 84,985 83,862 2010's 84,707 84,977 85,129 85,999 85,630 85,961 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld

  12. Kentucky Natural Gas Number of Industrial Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Industrial Consumers (Number of Elements) Kentucky Natural Gas Number of Industrial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 1,391 1,436 1,443 1990's 1,544 1,587 1,608 1,585 1,621 1,630 1,633 1,698 1,864 1,813 2000's 1,801 1,701 1,785 1,695 1,672 1,698 1,658 1,599 1,585 1,715 2010's 1,742 1,705 1,720 1,767 2,008 2,041 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of

  13. Kentucky Natural Gas Number of Residential Consumers (Number of Elements)

    U.S. Energy Information Administration (EIA) (indexed site)

    Residential Consumers (Number of Elements) Kentucky Natural Gas Number of Residential Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 596,320 606,106 614,058 1990's 624,477 633,942 644,281 654,664 668,774 685,481 696,989 713,509 726,960 735,371 2000's 744,816 749,106 756,234 763,290 767,022 770,080 770,171 771,047 753,531 754,761 2010's 758,129 759,584 757,790 761,575 761,935 764,946 - = No Data Reported; -- = Not Applicable; NA

  14. Illinois Natural Gas Number of Oil Wells (Number of Elements)

    Gasoline and Diesel Fuel Update

    Commercial Consumers (Number of Elements) Illinois Natural Gas Number of Commercial Consumers (Number of Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1980's 241,367 278,473 252,791 1990's 257,851 261,107 263,988 268,104 262,308 264,756 265,007 268,841 271,585 274,919 2000's 279,179 278,506 279,838 281,877 273,967 276,763 300,606 296,465 298,418 294,226 2010's 291,395 293,213 297,523 282,743 294,391 295,869 - = No Data Reported; -- = Not Applicable; NA =

  15. Hacking Away at Soft Costs: 24-Hour Coding Event Focuses on Expanding Solar

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

    Market | Department of Energy Hacking Away at Soft Costs: 24-Hour Coding Event Focuses on Expanding Solar Market Hacking Away at Soft Costs: 24-Hour Coding Event Focuses on Expanding Solar Market May 7, 2014 - 2:45pm Addthis Douglas Hitching (left), CEO of Silicon Solar Solutions and Henry Chung, LG, talk during a one-on-one networking session at the National Renewable Energy Laboratory's Industry Growth Forum in 2012. The SunShot Initiative and the National Renewable Energy Laboratory are

  16. Computer Code Gives Astrophysicists First Full Simulation of Star's Final Hours

    ScienceCinema (OSTI)

    Applin, Bradford

    2013-05-29

    The precise conditions inside a white dwarf star in the hours leading up to its explosive end as a Type Ia supernova are one of the mysteries confronting astrophysicists studying these massive stellar explosions. But now, a team of researchers, composed of three applied mathematicians at the U.S. Department of Energy's (DOE) Lawrence Berkeley National Laboratory and two astrophysicists, has created the first full-star simulation of the hours preceding the largest thermonuclear explosions in the universe. http://www.lbl.gov/cs/Archive/news091509.html

  17. Y-12 Construction hits one million-hour mark without a lost-time accident |

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

    Y-12 National Security Complex Construction hits one ... Y-12 Construction hits one million-hour mark without a lost-time accident Posted: August 30, 2012 - 5:30pm The B&W Y-12 Direct-Hire Construction team has worked one million hours, covering a 633-day period, without a lost-time injury. Some 285 people including building trade crafts, non-manual staff and escorts worked without a lost-time accident during this period. The Construction team's last lost workday was in September 2010. A

  18. SHINES - the Answer to 24-Hour Solar Energy | Department of Energy

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

    SHINES - the Answer to 24-Hour Solar Energy SHINES - the Answer to 24-Hour Solar Energy May 6, 2016 - 4:27pm Addthis Austin Energy – Mueller development<br /> SHINES is a funding program from the Department of Energy’s SunShot Initiative Austin Energy - Mueller development SHINES is a funding program from the Department of Energy's SunShot Initiative As part of the Grid Modernization Initiative, EERE recently announced $18 million in funding for six new projects that could make

  19. BioenergizeME Office Hours Webinar: An Overview of Bioenergy and the 2017

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

    BioenergizeME Infographic Challenge | Department of Energy BioenergizeME Office Hours Webinar: An Overview of Bioenergy and the 2017 BioenergizeME Infographic Challenge BioenergizeME Office Hours Webinar: An Overview of Bioenergy and the 2017 BioenergizeME Infographic Challenge November 17, 2016 4:00PM to 5:00PM EST Bring renewable energy science into the classroom and ENERGIZE your curriculum with the U.S. Department of Energy Bioenergy Technologies Office's (BETO's) 2017 BioenergizeME

  20. Stack Monitor Operating Experience Review

    SciTech Connect (OSTI)

    L. C. Cadwallader; S. A. Bruyere

    2009-05-01

    Stack monitors are used to sense radioactive particulates and gases in effluent air being vented from rooms of nuclear facilities. These monitors record the levels and types of effluents to the environment. This paper presents the results of a stack monitor operating experience review of the U.S. Department of Energy (DOE) Occurrence Reporting and Processing System (ORPS) database records from the past 18 years. Regulations regarding these monitors are briefly described. Operating experiences reported by the U.S. DOE and in engineering literature sources were reviewed to determine the strengths and weaknesses of these monitors. Electrical faults, radiation instrumentation faults, and human errors are the three leading causes of failures. A representative “all modes” failure rate is 1E-04/hr. Repair time estimates vary from an average repair time of 17.5 hours (with spare parts on hand) to 160 hours (without spare parts on hand). These data should support the use of stack monitors in any nuclear facility, including the National Ignition Facility and the international ITER project.

  1. Tax Deduction Qualified Software: Hourly Analysis Program Version 4.91

    Office of Energy Efficiency and Renewable Energy (EERE)

    Provides required documentation that the Hourly Analysis Program (HAP) version 4.91 meets Internal Revenue Code §179D (c)(1) and (d) Regulations Notice 2006-52, Section 6 requirements as amplified by Notice 2008-40, Section 4 requirements.

  2. Tax Deduction Qualified Software: Hourly Analysis Program Version 4.90

    Office of Energy Efficiency and Renewable Energy (EERE)

    Provides required documentation that the Hourly Analysis Program (HAP) version 4.90 meets Internal Revenue Code §179D (c)(1) and (d) Regulations Notice 2006-52, Section 6 requirements as amplified by Notice 2008-40, Section 4 requirements.

  3. Six- and three-hourly meteorological observations from 223 USSR stations

    SciTech Connect (OSTI)

    Razuvaev, V.N.; Apasova, E.B.; Martuganov, R.A.; Kaiser, D.P.

    1995-04-01

    This document describes a database containing 6- and 3-hourly meteorological observations from a 223-station network of the former Soviet Union. These data have been made available through cooperation between the two principal climate data centers of the United States and Russia: the National Climatic Data Center (NCDC), in Asheville, North Carolina, and the All-Russian Research Institute of Hydrometeorological Information -- World Data Centre (RIHMI-WDC) in Obninsk. Station records consist of 6- and 3-hourly observations of some 24 meteorological variables including temperature, weather type, precipitation amount, cloud amount and type, sea level pressure, relative humidity, and wind direction and speed. The 6-hourly observations extend from 1936 to 1965; the 3-hourly observations extend from 1966 through the mid-1980s (1983, 1984, 1985, or 1986; depending on the station). These data have undergone extensive quality assurance checks by RIHMI-WDC, NCDC, and the Carbon Dioxide Information Analysis Center (CDIAC). The database represents a wealth of meteorological information for a large and climatologically important portion of the earth`s land area, and should prove extremely useful for a wide variety of regional climate change studies. These data are available free of charge as a numeric data package (NDP) from CDIAC. The NDP consists of this document and 40 data files that are available via the Internet or on 8mm tape. The total size of the database is {approximately}2.6 gigabytes.

  4. Pilot Plant Completes Two 1,000-Hour Ethanol Performance Runs

    Energy.gov [DOE]

    ICM Inc. announced successful completion of two 1,000-hour performance runs of its patent-pending Generation 2.0 Co-Located Cellulosic Ethanol process at its cellulosic ethanol pilot plant in St. Joseph, Missouri. This is an important step toward the commercialization of cellulosic ethanol from switchgrass and energy sorghum.

  5. West Valley Demonstration Project Contractor Reaches 2 Million Safe Work Hours

    Office of Energy Efficiency and Renewable Energy (EERE)

    WEST VALLEY, N.Y. – EM’s West Valley Demonstration Project (WVDP) contractor CH2M HILL BWXT West Valley (CHBWV) and its subcontractors achieved this month 2 million safe work hours without a lost-time accident over the past 30 months

  6. Coiled tubing; Operations and services

    SciTech Connect (OSTI)

    Sas-Jaworsky, A. II )

    1991-12-01

    This article outlines the minimum safety requirements that should be considered for onshore and offshore oil well service operations with coiled tubing equipment. These guidelines comply with Minerals Management Service (MMS) regulations issued on May 31, 1988, for offshore work. Where specific MMS regulations are sited, the regulation reference, Incident of Non-Compliance (INC), number is provided. These guidelines can be used by operators and contractors, and although U.S. offshore operations are emphasized, they are applicable wherever coiled tubing services are used.

  7. LLWnotes - Volume 11, Number 4

    SciTech Connect (OSTI)

    1996-05-01

    This document is the May 1996 issue of LLWnotes. It contains articles and news items on the following topics: news items related to states and compacts; Low-Level Radioactive Waste (LLW) Forum activities; court rulings and calendars; US DOE testing at Ward Valley; US BLM contract with Lawrence Livermore National Laboratory; Mixed Waste Pilot Project Schedule; extension of US EPA`s mixed waste enforcement moratorium; EPA Advisory Committee on research program operation; and decommissioning.

  8. Unmanned boiler operation a reality in Europe

    SciTech Connect (OSTI)

    Ilg, E.

    1996-08-01

    With the rise in liquid level technology in Europe comes new standards for boiler operation. SMART technology for level probes and auxiliary equipment, means many European countries allow a boiler to operate completely unmanned (without operators) for up to 72 hours at a time. It is not just a level control system, but a total boiler control scheme. This incorporates level control, continuous TDS monitoring with blowdown, automatic timed bottom blowdown, feed water control, contamination detection systems for monitoring of incoming feed water, monitoring of exhaust stack temperatures, over pressure alarms and timed automatic blowdown of level pots. One of the main reasons for the development of the SMART equipment and the new boiler codes was to increase reliability of boiler operation. Surveys in Germany and England showed that almost 90 percent of boiler failures was due to operator error, this has almost been eliminated through the use of new equipment based on the new codes.

  9. Line Equipment Operator

    Energy.gov [DOE]

    There are several Line Equipment Operator positions located in Washington and Oregon. A successful candidate in this position will perform Line Equipment Operator work operating trucks and all...

  10. Electric rate that shifts hourly may foretell spot-market kWh

    SciTech Connect (OSTI)

    Springer, N.

    1985-11-25

    Four California industrial plants have cut their electricity bills up to 16% by shifting from the traditional time-of-use rates to an experimental real-time program (RTP) that varies prices hourly. The users receive a price schedule reflecting changing generating costs one day in advance to encourage them to increase power consumption during the cheapest time periods. Savings during the pilot program range between $11,000 and $32,000 per customer. The hourly cost breakdown encourages consumption during the night and early morning. The signalling system could be expanded to cogenerators and independent small power producers. If an electricity spot market develops, forecasters think a place on the stock exchanges for future-delivery contracts could develop in the future.

  11. Job Code Description Hourly Wage TR-I Job Code TR I Wage TR-II

    National Nuclear Security Administration (NNSA)

    17 031007 Firefighter/CIC/EMT $33.13 Engineer/CIC/EMT $19.76 Engineer/CIC/EMT $35.99 Chiefs Aide/CIC/EMT $19.76 Chiefs Aide/CIC/EMT $35.99 Lieutenant/CIC/EMT $20.99 Lieutenant/CIC/EMT $38.21 Captain/CIC/EMT $22.23 Captain/CIC/EMT $40.44 Assistant Chief/CIC/EMT $25.42 Assistant Chief/CIC/EMT $46.18 FP Tech/CIC/EMT $21.13 031019 FP Tech/CIC/EMT $38.47 031049 FP Captain/CIC/EMT $23.60 FP Captain/CIC/EMT $42.91 56-HOUR EMT & HAZ $1.11 10-HOUR EMT & HAZ $2.00 031047 Firefighter/CIC/EMT/HAZ

  12. Job Code Description Hourly Wage TR-I Job Code TR I Wage TR-II

    National Nuclear Security Administration (NNSA)

    71 031007 Firefighter/CIC/EMT $33.67 Engineer/CIC/EMT $20.30 Engineer/CIC/EMT $36.53 Chiefs Aide/CIC/EMT $20.30 Chiefs Aide/CIC/EMT $36.53 Lieutenant/CIC/EMT $21.53 Lieutenant/CIC/EMT $38.75 Captain/CIC/EMT $22.77 Captain/CIC/EMT $40.98 Assistant Chief/CIC/EMT $25.96 Assistant Chief/CIC/EMT $46.72 FP Tech/CIC/EMT $21.67 031019 FP Tech/CIC/EMT $39.01 031049 FP Captain/CIC/EMT $24.14 FP Captain/CIC/EMT $43.45 56-HOUR EMT & HAZ $1.11 10-HOUR EMT & HAZ $2.00 031047 Firefighter/CIC/EMT/HAZ

  13. SolOPT: PV and Solar Hot Water Hourly Simulation Software Tool - Energy

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

    Innovation Portal Solar Photovoltaic Solar Photovoltaic Building Energy Efficiency Building Energy Efficiency Find More Like This Return to Search SolOPT: PV and Solar Hot Water Hourly Simulation Software Tool National Renewable Energy Laboratory Contact NREL About This Technology Publications: PDF Document Publication Using SolOPT (835 KB) Technology Marketing Summary In order to increase the speed and scale of Renewable Energy (RE) solar project deployment on buildings, energy savings

  14. Solar Reserve Methodology for Renewable Energy Integration Studies Based on Sub-Hourly Variability Analysis: Preprint

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

    Solar Reserve Methodology for Renewable Energy Integration Studies Based on Sub-Hourly Variability Analysis Preprint E. Ibanez, G. Brinkman, M. Hummon, and D. Lew To be presented at the 2nd Annual International Workshop on Integration of Solar Power into Power Systems Conference Lisbon, Portugal November 12-13, 2012 Conference Paper NREL/CP-5500-56169 August 2012 NOTICE The submitted manuscript has been offered by an employee of the Alliance for Sustainable Energy, LLC (Alliance), a contractor

  15. BioenergizeME Office Hours Webinar: Integrating Bioenergy into the 9th-12th Grade Classroom

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

    December 10, 2015 BioenergizeME Office Hours Integrating Bioenergy into the 9 th__ 12 th Grade Classroom Alexis Martin Knauss Fellow Bioenergy Technologies Office U.S. Department of Energy Shannon Zaret Contractor, The Hannon Group Bioenergy Technologies Office U.S. Department of Energy 2 | Bioenergy Technologies Office Agenda 1. Overview Of Energy Literacy 2. Overview of Next Generation Science Standards 3. Bioenergy Basics 5. Incorporation of Bioenergy into the Classroom 4. 2016 BioenergizeME

  16. BioenergizeME Office Hours: Guide to the 2016 BioenergizeME Infographic Challenge

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

    October 15, 2015 BioenergizeME Office Hours Guide to the 2016 BioenergizeME Infographic Challenge Shannon Zaret Communications Specialist, The Hannon Group Contractor to the U.S. Department of Energy's Bioenergy Technologies Office 2 | Bioenergy Technologies Office | Bioenergy Technologies Office Agenda * Overview * Research Topic Areas And Prompts * Research Resources * Infographic Resources * Rubric * Social Media Campaign * Awards * Registration * Resources for Educators * Questions 3 |

  17. Supercomputing Award of 5.78 Billion Hours to 55 Computational Research

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

    Projects | Argonne Leadership Computing Facility Supercomputing Award of 5.78 Billion Hours to 55 Computational Research Projects Author: ALCF Staff November 14, 2016 Facebook Twitter LinkedIn Google E-mail Printer-friendly version LEMONT, Ill., Nov. 14, 2016-The U.S. Department of Energy's Office of Science announced 55 projects with high potential for accelerating discovery through its Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program. These awards

  18. Question/comment: An estimate of the direct productive labor hours (DPLH) per l

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

    Question/comment: An estimate of the direct productive labor hours (DPLH) per labor category is not provided in the Request for Proposal for DE-SOL-0005388. Will the Government provide such information so that Offerors may develop a responsive proposal? Response: Historical data reflecting full time equivalent (FTE) support personnel by labor category is provided in Section J.9, Attachment D of the RFP in the table titled Position Qualifications. Each Offeror is expected to propose the labor

  19. PPPL team wins 80 million processor hours on nation's fastest supercomputer

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

    | Princeton Plasma Physics Lab team wins 80 million processor hours on nation's fastest supercomputer By John Greenwald January 26, 2016 Tweet Widget Google Plus One Share on Facebook Model of colliding magnetic fields before magnetic reconnection. (Model by Will Fox courtesy of Physical Review Letters 113, 105003 2014) Model of colliding magnetic fields before magnetic reconnection. (Model by Will Fox courtesy of Physical Review Letters 113, 105003 2014) The U.S Department of Energy (DOE)

  20. PPPL team wins 80 million processor hours on nation's fastest supercomputer

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

    | Princeton Plasma Physics Lab team wins 80 million processor hours on nation's fastest supercomputer By John Greenwald January 26, 2016 Tweet Widget Google Plus One Share on Facebook Model of colliding magnetic fields before magnetic reconnection. (Model by Will Fox courtesy of Physical Review Letters 113, 105003 2014) Model of colliding magnetic fields before magnetic reconnection. (Model by Will Fox courtesy of Physical Review Letters 113, 105003 2014) The U.S Department of Energy (DOE)

  1. Performing a local barrier operation

    DOE Patents [OSTI]

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

    2014-03-04

    Performing a local barrier operation with parallel tasks executing on a compute node including, for each task: retrieving a present value of a counter; calculating, in dependence upon the present value of the counter and a total number of tasks performing the local barrier operation, a base value, the base value representing the counter's value prior to any task joining the local barrier; calculating, in dependence upon the base value and the total number of tasks performing the local barrier operation, a target value of the counter, the target value representing the counter's value when all tasks have joined the local barrier; joining the local barrier, including atomically incrementing the value of the counter; and repetitively, until the present value of the counter is no less than the target value of the counter: retrieving the present value of the counter and determining whether the present value equals the target value.

  2. Performing a local barrier operation

    DOE Patents [OSTI]

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

    2014-03-04

    Performing a local barrier operation with parallel tasks executing on a compute node including, for each task: retrieving a present value of a counter; calculating, in dependence upon the present value of the counter and a total number of tasks performing the local barrier operation, a base value of the counter, the base value representing the counter's value prior to any task joining the local barrier; calculating, in dependence upon the base value and the total number of tasks performing the local barrier operation, a target value, the target value representing the counter's value when all tasks have joined the local barrier; joining the local barrier, including atomically incrementing the value of the counter; and repetitively, until the present value of the counter is no less than the target value of the counter: retrieving the present value of the counter and determining whether the present value equals the target value.

  3. Operating Experience Committee Charter

    Energy.gov [DOE]

    The Operating Experience Committee (OEC) charter provides a description of the OEC's purpose, background, membership, functions, and operations.

  4. Atmospheric Radiation Measurement Program Climate Research Facility Operation quarterly report July 1 - September 30, 2010.

    SciTech Connect (OSTI)

    Sisterson, D. L.

    2010-10-26

    Individual raw datastreams from instrumentation at the Atmospheric Radiation Measurement (ARM) Climate Research Facility fixed and mobile sites are collected and sent to the Data Management Facility (DMF) at Pacific Northwest National Laboratory (PNNL) for processing in near real-time. Raw and processed data are then sent approximately daily to the ARM Archive, where they are made available to users. For each instrument, we calculate the ratio of the actual number of data records received daily at the Archive to the expected number of data records. The results are tabulated by (1) individual datastream, site, and month for the current year and (2) site and fiscal year (FY) dating back to 1998. The U.S. Department of Energy (DOE) requires national user facilities to report time-based operating data. The requirements concern the actual hours of operation (ACTUAL); the estimated maximum operation or uptime goal (OPSMAX), which accounts for planned downtime; and the VARIANCE [1-(ACTUAL/OPSMAX)], which accounts for unplanned downtime. The OPSMAX time for the fourth quarter of FY2010 for the Southern Great Plains (SGP) site is 2097.60 hours (0.95 2208 hours this quarter). The OPSMAX for the North Slope of Alaska (NSA) locale is 1987.20 hours (0.90 2208) and for the Tropical Western Pacific (TWP) locale is 1876.80 hours (0.85 2208). The first ARM Mobile Facility (AMF1) deployment in Graciosa Island, the Azores, Portugal, continues, so the OPSMAX time this quarter is 2097.60 hours (0.95 x 2208). The differences in OPSMAX performance reflect the complexity of local logistics and the frequency of extreme weather events. It is impractical to measure OPSMAX for each instrument or datastream. Data availability reported here refers to the average of the individual, continuous datastreams that have been received by the Archive. Data not at the Archive are caused by downtime (scheduled or unplanned) of the individual instruments. Therefore, data availability is directly related to

  5. and Operations | National Nuclear Security Administration

    National Nuclear Security Administration (NNSA)

    and Operations

  6. Lessons learned bulletin. Number 2

    SciTech Connect (OSTI)

    Not Available

    1994-05-01

    During the past four years, the Department of Energy -- Savannah River Operations Office and the Westinghouse Savannah River Company (WSRC) Environmental Restoration (ER) Program completed various activities ranging from waste site investigations to closure and post closure projects. Critiques for lessons learned regarding project activities are performed at the completion of each project milestone, and this critique interval allows for frequent recognition of lessons learned. In addition to project related lessons learned, ER also performs lessons learned critiques. T`he Savannah River Site (SRS) also obtains lessons learned information from general industry, commercial nuclear industry, naval nuclear programs, and other DOE sites within the complex. Procedures are approved to administer the lessons learned program, and a database is available to catalog applicable lessons learned regarding environmental remediation, restoration, and administrative activities. ER will continue to use this database as a source of information available to SRS personnel.

  7. Technology applications bulletins: Number one

    SciTech Connect (OSTI)

    Koncinski, W. Jr.

    1989-02-01

    Martin Marietta Energy Systems, Inc. (Energy Systems), operates five facilities for the US Department of Energy (DOE): the Oak Ridge National Laboratory (ORNL), which is a large, multidisciplinary research and development (R and D) center whose primary mission is energy research; the Oak Ridge Y-12 Plant, which engages in defense research, development, and production; and the uranium-enrichment plants at Oak Ridge; Paducah, Kentucky; and Portsmouth, Ohio. Much of the research carried out at these facilities is of interest to industry and to state or local governments. To make information about this research available, the Energy Systems Office of Technology Applications publishes brief descriptions of selected technologies and reports. These technology applications bulletins describe the new technology and inform the reader about how to obtain further information, gain access to technical resources, and initiate direct contact with Energy Systems researchers.

  8. Sub-Hourly Impacts of High Solar Penetrations in the Western United States: Preprint

    SciTech Connect (OSTI)

    Lew, D.; Brinkman, G.; Ibanez, E.; Hummon, M.; Hodge, B. M.; Heaney, M.; King, J.

    2012-09-01

    This paper presents results of analysis on the sub-hourly impacts of high solar penetrations from the Western Wind and Solar Integration Study Phase 2. Extreme event analysis showed that most large ramps were due to sunrise and sunset events, which have a significant predictability component. Variability in general was much higher in the high-solar versus high-wind scenario. Reserve methodologies that had already been developed for wind were therefore modified to take into account the predictability component of solar variability.

  9. SeizAlert could give patients 4.5 hour warning of seizure

    ScienceCinema (OSTI)

    Dr. Lee Hively and Kara Kruse

    2010-01-08

    One percent of Americans, 3 million people, suffer from epilepsy. And their lives are about to be dramatically changed by scientists at Oak Ridge National Laboratory. For 15 years, Dr. Lee Hively has been working on "SeizAlert", a seizure-detecting device that resembles a common PDA. "It allows us to analyze scalp brain waves and give us up to 4.5 hours' forewarning of that event," he said. With the help of partner Kara Kruse, he's now able to help patients predict the previously unpredictable.

  10. Verification Challenges at Low Numbers

    SciTech Connect (OSTI)

    Benz, Jacob M.; Booker, Paul M.; McDonald, Benjamin S.

    2013-06-01

    Many papers have dealt with the political difficulties and ramifications of deep nuclear arms reductions, and the issues of “Going to Zero”. Political issues include extended deterrence, conventional weapons, ballistic missile defense, and regional and geo-political security issues. At each step on the road to low numbers, the verification required to ensure compliance of all parties will increase significantly. Looking post New START, the next step will likely include warhead limits in the neighborhood of 1000 . Further reductions will include stepping stones at1000 warheads, 100’s of warheads, and then 10’s of warheads before final elimination could be considered of the last few remaining warheads and weapons. This paper will focus on these three threshold reduction levels, 1000, 100’s, 10’s. For each, the issues and challenges will be discussed, potential solutions will be identified, and the verification technologies and chain of custody measures that address these solutions will be surveyed. It is important to note that many of the issues that need to be addressed have no current solution. In these cases, the paper will explore new or novel technologies that could be applied. These technologies will draw from the research and development that is ongoing throughout the national laboratory complex, and will look at technologies utilized in other areas of industry for their application to arms control verification.

  11. Richland Operations Office - Hanford Site

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

    Richland Operations Office Richland Operations Office Richland Operations Office River Corridor Central Plateau Groundwater Mission Support Newsroom Richland Operations Office...

  12. An overview of 3-D graphical analysis using DOE-2 hourly simulation data

    SciTech Connect (OSTI)

    Haberl, J.S.; MacDonald, M.; Eden, A.

    1988-01-01

    This paper presents an overview of a 3-D graphical approach for improving the potential of building energy analyses using the DOE-2 computer program. The approach produces 3-D annual profiles from hourly data generated by DOE-2 simulations using a statistical plotting package for specific quantities of interest. The annual profiles of hourly data provide a useful graphical check of voluminous data in a condensed form, allowing several different types of data to be plotted over a year. These profiles provide the user with the opportunity to check simulation results, check for potential problems with user input, provide graphs to customers who may want a simpler presentation, visualize interactions in simulations, and understand where inappropriate modeling conditions may exist in simulations. Future analysis, using such profiles, may allow methods to be developed to check consistency between simulations, check for potential hidden errors in modeling buildings, and better understand how simulations compare with data from real buildings. 22 refs., 23 figs., 1 tab.

  13. Continuity of Operations Plan (COOP)

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

    You are here: DOE-ID Home > COOP Continuity of Operations Plan (COOP) Call-In Number: 1-208-526-COOP (2667) or 1-877-DOE-DOE1 (1-877-363-3631) Wait for recording to start then Dial 382: If you are directed or forced to evacuate your current location to an alternate site, please contact us as soon as possible to advise us that you are safe and with a means of contacting you. This toll free or local number can be used by employees or their families to report their whereabouts or the

  14. ARM - AMF2 Operations

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

    AMF2 Organization and Contacts Management and Operations Operations Overview ARM Links BCR | ECR ECO, EWO Extraview PIF, CAR, DQR & DQPR Operations Status System i.arm.gov AMF2 ...

  15. Moab Project Logs 2 Million Work Hours Without Lost-Time Injury or Illness

    Energy.gov [DOE]

    GRAND JUNCTION, Colo. – The number 1,584 may not mean much to most people, but for the workers on EM’s Moab Uranium Mill Tailings Remedial Action Project, it represents the number of days without a work-related, lost-time injury or illness, as defined by the Occupational Safety and Health Administration.

  16. Developing and Enhancing Workforce Training Programs: Number...

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

    Developing and Enhancing Workforce Training Programs: Number of Projects by State Developing and Enhancing Workforce Training Programs: Number of Projects by State Map of the ...

  17. BioenergizeME Office Hours Webinar: Guide to the 2016 BioenergizeME Infographic Challenge

    Energy.gov [DOE]

    The U.S. Department of Energy (DOE) BioenergizeME Infographic Challenge is an engaging way for students to explore topics in bioenergy and share what they have learned with others across the nation. In this challenge, high school-aged teams (grades 9–12) will use technology to research, interpret, apply, and then design an infographic that responds to one of four cross-curricular bioenergy topics. To make the challenge easier and more effective, this webinar is designed to guide interested students, teachers, and other educators through the submission process and highlight the resources that are available on the BioenergizeME Infographic Challenge website. These resources will assist students with researching their selected topics, developing their infographics, and designing effective social media campaigns. This webinar is part of the BioenergizeME Office Hours webinar series developed by the DOE Bioenergy Technologies Office.

  18. Performance of Blackglas{trademark} composites in 4000-hour oxidation study

    SciTech Connect (OSTI)

    Campbell, S.; Gonczy, S.; McNallan, M.; Cox, A.

    1996-12-31

    The effect of long term (4000 hour) oxidation on the mechanical properties of Blackglas{trademark}-Nitrided Nextel{trademark}312 Ceramic Matrix Composites in the temperature range of 500{degrees} - 700{degrees}C was investigated. Flexure specimens of the title composites prepared using three different pyrolysis processes were subjected to oxidation in flowing dry air at 500{degrees}, 600{degrees}C, and 700{degrees}C. Samples were removed at several different time intervals for 3-point flexure analysis. Results indicate that processing conditions had very little effect on the oxidation resistance of this system. At 600{degrees} and 700{degrees}C the mechanical properties degrade continuously to a steady value about half the original flexure strength. At 500{degrees}C, material properties initially improve then begin to slowly degrade. Optical microscopy indicates that oxidation of the matrix begins at the matrix/fiber interface and microcracks and proceeds into the bulk of the matrix.

  19. Table 7.7 Coal Mining Productivity, 1949-2011 (Short Tons per Employee Hour )

    U.S. Energy Information Administration (EIA) (indexed site)

    Coal Mining Productivity, 1949-2011 (Short Tons per Employee Hour 1) Year Mining Method Location Total 2 Underground Surface 2 East of the Mississippi West of the Mississippi Underground Surface 2 Total 2 Underground Surface 2 Total 2 1949 0.68 [3] 1.92 [3] NA NA NA NA NA NA 0.72 1950 .72 [3] 1.96 [3] NA NA NA NA NA NA .76 1951 .76 [3] 2.00 [3] NA NA NA NA NA NA .80 1952 .80 [3] 2.10 [3] NA NA NA NA NA NA .84 1953 .88 [3] 2.22 [3] NA NA NA NA NA NA .93 1954 1.00 [3] 2.48 [3] NA NA NA NA NA NA

  20. BioenergizeME Office Hours Webinar: Integrating Bioenergy into the 9th–12th Grade Classroom

    Energy.gov [DOE]

    Biofuel is the only viable substitute for petroleum-based liquid transportation fuel in the near term. It is, therefore, increasingly relevant to enhance conceptual knowledge of biofuels and other types of bioenergy in today’s classroom environment. Bioenergy has applications across multiple science and engineering disciplines and also provides opportunities for real-world learning. This webinar is designed to support high school educators in planning activities for their classrooms that integrate bioenergy topics with the life sciences, physical sciences, earth and space sciences, and engineering and technology. This information can also help support advisors who are interested in participating in the 2016 BioenergizeME Infographic Challenge. This webinar is part of the BioenergizeME Office Hours webinar series developed by the U.S. Department of Energy’s Bioenergy Technologies Office.

  1. Webinar: BioenergizeME Office Hours Webinar: Guide to the 2016 BioenergizeME Infographic Challenge

    Energy.gov [DOE]

    The U.S. Department of Energy (DOE) BioenergizeME Infographic Challenge is an engaging way for students to explore topics in bioenergy and share what they have learned with others across the nation. In this challenge, high school-aged teams (grades 9–12) will use technology to research, interpret, apply, and then design an infographic that responds to one of four cross-curricular bioenergy topics. To make the challenge easier and more effective, this webinar is designed to guide interested students, teachers, and other educators through the submission process and highlight the resources that are available on the BioenergizeME Infographic Challenge website. These resources will assist students with researching their selected topics, developing their infographics, and designing effective social media campaigns. This webinar is part of the BioenergizeME Office Hours webinar series developed by the DOE Bioenergy Technologies Office.

  2. L & O Power Co-operative | Open Energy Information

    Open Energy Information (Open El) [EERE & EIA]

    O Power Co-operative Jump to: navigation, search Name: L & O Power Co-operative Place: Iowa Phone Number: 712-472-2556 Website: www.landopowercoop.com Outage Hotline:...

  3. KCP&L Greater Missouri Operations | Open Energy Information

    Open Energy Information (Open El) [EERE & EIA]

    KCP&L Greater Missouri Operations Jump to: navigation, search Name: KCP&L Greater Missouri Operations Place: Missouri Phone Number: (660) 359-2208 Outage Hotline: (660) 359-2208...

  4. Moab Project Logs 2 Million Work Hours Without Lost-Time Injury...

    Office of Environmental Management (EM)

    Empty containers on haul trucks are loaded with mill tailings. GRAND JUNCTION, Colo. - The number 1,584 may not mean much to most people, but for the workers on EM's Moab Uranium ...

  5. Proposed Rule To Implement the 1997 8-Hour Ozone National Ambient...

    National Nuclear Security Administration (NNSA)

    ... The http:www.regulations.gov Web Site is an ''anonymous access'' system, which means EPA ... The telephone number for the Public Reading Room is (202) 566-1744. The EPA Web site for ...

  6. Operating Experience Committee Charter

    Energy.gov [DOE]

    The Operating Experience Committe Charter explains the purpose of the Department of Energy (DOE) Operating Experience Committee (OEC), which is to support line management within DOE and the DOE community in developing and sustaining effective oeprating experience programs so that lessons from inernal and external operating experience lead to improvement in future operational and safety performance.

  7. Operation Warfighter Internship Fair

    Energy.gov [DOE]

    Attendees: Participants of Operation Warfighter Program Cost: Free Supports: Veteran and Disability Employment Programs

  8. Pilot Integrated Cellulosic Biorefinery Operations to Fuel Ethanol

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

    Biorefinery Operations to Fuel Ethanol Award Number: DE-EE0002875 March 23, 2015 ... to refine cellulosic biomass into fuel ethanol and co-products Create an ...

  9. Continuous Air Monitor Operating Experience Review

    SciTech Connect (OSTI)

    L. C. Cadwallader; S. A. Bruyere

    2008-09-01

    Continuous air monitors (CAMs) are used to sense radioactive particulates in room air of nuclear facilities. CAMs alert personnel of potential inhalation exposures to radionuclides and can also actuate room ventilation isolation for public and environmental protection. This paper presents the results of a CAM operating experience review of the DOE Occurrence Reporting and Processing System (ORPS) database from the past 18 years. Regulations regarding these monitors are briefly reviewed. CAM location selection and operation are briefly discussed. Operating experiences reported by the U.S. Department of Energy and in other literature sources were reviewed to determine the strengths and weaknesses of these monitors. Power losses, human errors, and mechanical issues cause the majority of failures. The average “all modes” failure rate is 2.65E-05/hr. Repair time estimates vary from an average repair time of 9 hours (with spare parts on hand) to 252 hours (without spare parts on hand). These data should support the use of CAMs in any nuclear facility, including the National Ignition Facility and the international ITER experiment.

  10. Florida Natural Gas Number of Gas and Gas Condensate Wells (Number...

    Gasoline and Diesel Fuel Update

    Gas and Gas Condensate Wells (Number of Elements) Florida Natural Gas Number of Gas and ...2016 Referring Pages: Number of Producing Gas Wells (Summary) Florida Natural Gas Summary

  11. DOE's Office of Science Awards 18 Million Hours of Supercomputing Time to 15 Teams for Large-Scale Scientific Computing

    Office of Energy Efficiency and Renewable Energy (EERE)

    WASHINGTON, D.C. - Secretary of Energy Samuel W. Bodman announced today that DOE's Office of Science has awarded a total of 18.2 million hours of computing time on some of the world's most powerful...

  12. Insights from Smart Meters: The Potential for Peak-Hour Savings from Behavior-Based Programs

    SciTech Connect (OSTI)

    Todd, Annika; Perry, Michael; Smith, Brian; Sullivan, Michael; Cappers, Peter; Goldman, Charles

    2014-03-25

    The rollout of smart meters in the last several years has opened up new forms of previously unavailable energy data. Many utilities are now able in real-time to capture granular, household level interval usage data at very high-frequency levels for a large proportion of their residential and small commercial customer population. This can be linked to other time and locationspecific information, providing vast, constantly growing streams of rich data (sometimes referred to by the recently popular buzz word, “big data”). Within the energy industry there is increasing interest in tapping into the opportunities that these data can provide. What can we do with all of these data? The richness and granularity of these data enable many types of creative and cutting-edge analytics. Technically sophisticated and rigorous statistical techniques can be used to pull interesting insights out of this highfrequency, human-focused data. We at LBNL are calling this “behavior analytics”. This kind of analytics has the potential to provide tremendous value to a wide range of energy programs. For example, highly disaggregated and heterogeneous information about actual energy use would allow energy efficiency (EE) and/or demand response (DR) program implementers to target specific programs to specific households; would enable evaluation, measurement and verification (EM&V) of energy efficiency programs to be performed on a much shorter time horizon than was previously possible; and would provide better insights in to the energy and peak hour savings associated with specifics types of EE and DR programs (e.g., behavior-based (BB) programs). In this series, “Insights from Smart Meters”, we will present concrete, illustrative examples of the type of value that insights from behavior analytics of these data can provide (as well as pointing out its limitations). We will supply several types of key findings, including: • Novel results, which answer questions the industry

  13. Atmospheric Radiation Measurement program climate research facility operations quarterly report October 1 - December 31, 2006.

    SciTech Connect (OSTI)

    Sisterson, D. L.

    2007-03-14

    Individual raw data streams from instrumentation at the Atmospheric Radiation Measurement (ARM) Program Climate Research Facility (ACRF) fixed and mobile sites are collected and sent to the Data Management Facility (DMF) at Pacific Northwest National Laboratory (PNNL) for processing in near real time. Raw and processed data are then sent daily to the ACRF Archive, where they are made available to users. For each instrument, we calculate the ratio of the actual number of data records received daily at the Archive to the expected number of data records. The results are tabulated by (1) individual data stream, site, and month for the current year and (2) site and fiscal year dating back to 1998. Table 1 shows the accumulated maximum operation time (planned uptime), the actual hours of operation, and the variance (unplanned downtime) for the period October 1 through December 31, 2006, for the fixed and mobile sites. Although the AMF is currently up and running in Niamey, Niger, Africa, the AMF statistics are reported separately and not included in the aggregate average with the fixed sites. The first quarter comprises a total of 2,208 hours. For all fixed sites, the actual data availability (and therefore actual hours of operation) exceeded the individual (and well as aggregate average of the fixed sites) operational goal for the first quarter of fiscal year (FY) 2007. The Site Access Request System is a web-based database used to track visitors to the fixed sites, all of which have facilities that can be visited. The NSA locale has the Barrow and Atqasuk sites. The SGP site has a Central Facility, 23 extended facilities, 4 boundary facilities, and 3 intermediate facilities. The TWP locale has the Manus, Nauru, and Darwin sites. NIM represents the AMF statistics for the current deployment in Niamey, Niger, Africa. PYE represents the AMF statistics for the Point Reyes, California, past deployment in 2005. In addition, users who do not want to wait for data to be

  14. ISDAC - NRC Convair-580 Flight Hours Date Flight From To Start

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

    - NRC Convair-580 Flight Hours Date Flight From To Start End hrs 03/21/08 F01-Test-01 Ottawa Ottawa 16:15Z 18:15Z 2.2 03/22/08 F02-Test-02 Ottawa Ottawa 12:45Z 15:50Z 3.3 03/28/08 F03-Transit-01 Ottawa, ON Kenora, ON 12:23Z 15:44Z 3.6 03/28/08 F04-Transit-02 Kenora, ON Calgary, AB 16:30Z 19:36Z 3.3 03/28/08 F05-Transit-03 Calgary, AB Comox, BC 20:24Z 22:17Z 2.1 03/29/08 F06-Transit-04 Comox, BC Whitehorse, YK 17:43Z 20:50Z 3.3 03/29/08 F07-Transit-05 Whitehorse, YK Fairbanks 21:51Z 23:42Z 2.1

  15. Total number of longwall faces drops below 50

    SciTech Connect (OSTI)

    Fiscor, S.

    2009-02-15

    For the first time since Coal Age began its annual Longwall Census the number of faces has dropped below 50. A total of five mines operate two longwall faces. CONSOL Energy remains the leader with 12 faces. Arch Coal operates five longwall mines; Robert E. Murray owns five longwall mines. West Virginia has 13 longwalls, followed by Pennsylvania (8), Utah (6) and Alabama (6). A detailed table gives for each longwall installation, the ownership, seam height, cutting height, panel width and length, overburden, number of gate entries, depth of cut, model of equipment used (shearer, haulage system, roof support, face conveyor, stage loader, crusher, electrical controls and voltage to face). 2 tabs., 1 photo.

  16. Climate Data Operators (CDO)

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

    Climate Data Operators (CDO) Climate Data Operators (CDO) Description and Overview CDO is a large tool set for working on climate data. NetCDF 34, GRIB including SZIP compression, ...

  17. Paducah Operations Timeline | Department of Energy

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

    Operations Timeline Paducah Operations Timeline Paducah Operations Timeline

  18. Calutron Operators | Y-12 National Security Complex

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

    Operators Calutron Operators Young women recruited to operate the calutrons

  19. Study of Engine Operating Parameter Effects on GDI Engine Particle-Number Emissions

    Energy.gov [DOE]

    Results show that fuel-injection timing is the dominant factor contributing to PN emissions from this wall-guided GDI engine.

  20. U.S. Crude Oil Rotary Rigs in Operation (Number of Elements)

    Gasoline and Diesel Fuel Update

    Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's NA NA NA NA NA NA NA 1980's NA NA NA NA NA NA NA NA 554 453 1990's 532 482 373 373 335 323 306 376 264 128 2000's 197 217 137 157 165 194 274 297 379 278 2010's 591 984 1,357

  1. U.S. Crude Oil and Natural Gas Rotary Rigs in Operation (Number of

    Gasoline and Diesel Fuel Update

    Elements) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1940's 2,017 1950's 2,154 2,543 2,641 2,613 2,508 2,686 2,620 2,426 1,922 2,071 1960's 1,748 1,761 1,641 1,499 1,501 1,388 1,272 1,135 1,169 1,194 1970's 1,028 976 1,107 1,194 1,472 1,660 1,658 2,001 2,259 2,177 1980's 2,909 3,970 3,105 2,232 2,428 1,980 964 936 936 869 1990's 1,010 860 721 754 775 723 779 943 827 625 2000's 918 1,156 830 1,032 1,192 1,381 1,649 1,768 1,879 1,089 2010's 1,546 1,879 1,

  2. U.S. Natural Gas Rotary Rigs in Operation (Number of Elements)

    Gasoline and Diesel Fuel Update

    (Million Barrels) Acquisitions (Million Barrels) U.S. Natural Gas Liquids Lease Condensate, Proved Reserves Acquisitions (Million Barrels) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 2000's 37 2010's 140 273 84 138 408 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 11/19/2015 Next Release Date: 12/31/2016 Referring Pages: Lease Condensate Reserves Acquisitions (Million

  3. U.S. Offshore Crude Oil and Natural Gas Rotary Rigs in Operation (Number of

    Gasoline and Diesel Fuel Update

    Biomass Gas (Million Cubic Feet) U.S. Natural Gas Supplemental Gas - Biomass Gas (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1990's 4,484 4,155 3,133 2,964 2,705 2,731 3,104 2000's 3,571 2,097 0 253 358 406 457 375 382 508 2010's 1,294 1,405 1,573 1,585 1,503 1,425 - = No Data Reported; -- = Not Applicable; NA = Not Available; W = Withheld to avoid disclosure of individual company data. Release Date: 10/31/2016 Next Release Date: 11/30/2016

  4. U.S. Onshore Crude Oil and Natural Gas Rotary Rigs in Operation (Number of

    Gasoline and Diesel Fuel Update

    875,945 2,416,644 2,044,643 1,859,469 1,804,544 1,820,202 Elements)

    Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1940's NA 1950's NA NA NA NA NA NA NA NA NA NA 1960's NA NA NA NA NA NA NA NA NA NA 1970's NA NA NA 1,110 1,378 1,554 1,529 1,834 2,074 1,970 1980's 2,678 3,714 2,862 2,033 2,215 1,774 865 841 813 764 1990's 902 779 669 672 673 622 671 821 703 519 2000's 778 1,003 717 924 1,095 1,287 1,559 1,695 1,814 1,046 2010's 1,514 1,846 1,871

  5. U.S. Crude Oil Rotary Rigs in Operation (Number of Elements)

    Gasoline and Diesel Fuel Update

    Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1973 NA NA NA NA NA NA NA NA NA NA NA NA 1974 NA NA NA NA NA NA NA NA NA NA NA NA 1975 NA NA NA NA NA NA NA NA NA NA NA NA 1976 NA NA NA NA NA NA NA NA NA NA NA NA 1977 NA NA NA NA NA NA NA NA NA NA NA NA 1978 NA NA NA NA NA NA NA NA NA NA NA NA 1979 NA NA NA NA NA NA NA NA NA NA NA NA 1980 NA NA NA NA NA NA NA NA NA NA NA NA 1981 NA NA NA NA NA NA NA NA NA NA NA NA 1982 NA NA NA NA NA NA NA NA NA NA NA NA 1983 NA NA NA NA NA NA NA NA NA NA NA

  6. U.S. Crude Oil and Natural Gas Rotary Rigs in Operation (Number of

    Gasoline and Diesel Fuel Update

    Elements) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1973 1,219 1,126 1,049 993 1,046 1,118 1,156 1,222 1,266 1,334 1,390 1,405 1974 1,372 1,355 1,367 1,381 1,413 1,432 1,480 1,518 1,527 1,584 1,596 1,643 1975 1,615 1,611 1,651 1,605 1,592 1,613 1,617 1,645 1,699 1,716 1,757 1,793 1976 1,711 1,594 1,540 1,480 1,496 1,546 1,597 1,691 1,744 1,794 1,840 1,861 1977 1,850 1,856 1,887 1,907 1,982 2,008 2,023 2,066 2,084 2,101 2,113 2,141 1978 2,128 2,135 2,159 2,198 2,249 2,287 2,307

  7. U.S. Natural Gas Rotary Rigs in Operation (Number of Elements)

    Gasoline and Diesel Fuel Update

    Processed (Million Cubic Feet) U.S. Natural Gas Processed (Million Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1960's 15,641,633 16,316,674 17,655,108 1970's 18,509,309 19,252,807 19,947,740 19,679,291 18,684,480 17,748,426 17,717,951 17,569,835 17,012,234 1980's 14,816,393 14,163,667 13,173,129 13,946,385 13,434,644 12,949,592 12,874,263 12,794,932 12,810,246 1990's 14,610,303 16,229,684 16,045,855 16,396,894 16,459,516 16,930,662 17,470,017

  8. U.S. Offshore Crude Oil and Natural Gas Rotary Rigs in Operation (Number of

    Gasoline and Diesel Fuel Update

    Production from Reserves (Billion Cubic Feet) Estimated Production from Reserves (Billion Cubic Feet) U.S. Nonassociated Natural Gas, Wet After Lease Separation, Estimated Production from Reserves (Billion Cubic Feet) Decade Year-0 Year-1 Year-2 Year-3 Year-4 Year-5 Year-6 Year-7 Year-8 Year-9 1970's 16,674 1980's 16,095 16,238 15,044 13,235 14,514 13,344 12,958 13,553 14,274 14,653 1990's 15,067 15,044 15,238 15,773 16,303 15,988 16,845 17,112 16,486 16,543 2000's 16,863 17,451 17,260

  9. U.S. Onshore Crude Oil and Natural Gas Rotary Rigs in Operation (Number of

    Gasoline and Diesel Fuel Update

    Elements) Year Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 1973 1,120 1,037 959 914 974 1,042 1,075 1,140 1,183 1,250 1,304 1,318 1974 1,283 1,264 1,272 1,280 1,319 1,342 1,387 1,426 1,437 1,493 1,497 1,540 1975 1,521 1,518 1,549 1,503 1,490 1,507 1,508 1,533 1,586 1,604 1,644 1,677 1976 1,588 1,468 1,408 1,356 1,375 1,426 1,465 1,563 1,618 1,666 1,703 1,716 1977 1,704 1,690 1,724 1,745 1,813 1,839 1,851 1,888 1,906 1,932 1,945 1,973 1978 1,956 1,954 1,979 2,016 2,066 2,103 2,122 2,127

  10. SWPF Crane Lift Operation

    SciTech Connect (OSTI)

    2010-01-01

    A multiple vview shot of the SWPF crane lift operation at the Savannah River Site. Funded by the Recovery Act.

  11. Low Mach Number Models in Computational Astrophysics

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

    Ann Almgren Low Mach Number Models in Computational Astrophysics February 4, 2014 Ann Almgren. Berkeley Lab Downloads Almgren-nug2014.pdf | Adobe Acrobat PDF file Low Mach Number...

  12. Climate Zone Number 5 | Open Energy Information

    Open Energy Information (Open El) [EERE & EIA]

    Climate Zone Number 5 Jump to: navigation, search A type of climate defined in the ASHRAE 169-2006 standard. Climate Zone Number 5 is defined as Cool- Humid(5A) with IP Units 5400...

  13. Renewable Electricity Futures. Operational Analysis of the Western Interconnection at Very High Renewable Penetrations

    SciTech Connect (OSTI)

    Brinkman, Gregory

    2015-09-01

    The Renewable Electricity Futures Study (RE Futures)--an analysis of the costs and grid impacts of integrating large amounts of renewable electricity generation into the U.S. power system--examined renewable energy resources, technical issues regarding the integration of these resources into the grid, and the costs associated with high renewable penetration scenarios. These scenarios included up to 90% of annual generation from renewable sources, although most of the analysis was focused on 80% penetration scenarios. Hourly production cost modeling was performed to understand the operational impacts of high penetrations. One of the conclusions of RE Futures was that further work was necessary to understand whether the operation of the system was possible at sub-hourly time scales and during transient events. This study aimed to address part of this by modeling the operation of the power system at sub-hourly time scales using newer methodologies and updated data sets for transmission and generation infrastructure. The goal of this work was to perform a detailed, sub-hourly analysis of very high penetration scenarios for a single interconnection (the Western Interconnection). It focused on operational impacts, and it helps verify that the operational results from the capacity expansion models are useful. The primary conclusion of this study is that sub-hourly operation of the grid is possible with renewable generation levels between 80% and 90%.

  14. Webinar: 20K Hour GATEWAY Testing Results for I-35W Bridge Presentation |

    Energy Savers

    SITING energy.gov/consentbasedsiting Over the coming months there will be a number of ways for the public to provide input on important elements in designing a consent- based process. These include: OPPORTUNITIES TO PARTICIPATE How can the Department ensure that the process for selecting a site is fair? What models and experience should the Department use in designing the process? Who should be involved in the process for selecting a site, and what is their role? What information and resources

  15. Risk assessment in international operations

    SciTech Connect (OSTI)

    Stricklin, Daniela L.

    2008-11-15

    During international peace-keeping missions, a diverse number of non-battle hazards may be encountered, which range from heavily polluted areas, endemic disease, toxic industrial materials, local violence, traffic, and even psychological factors. Hence, elevated risk levels from a variety of sources are encountered during deployments. With the emphasis within the Swedish military moving from national defense towards prioritization of international missions in atypical environments, the risk of health consequences, including long term health effects, has received greater consideration. The Swedish military is interested in designing an optimal approach for assessment of health threats during deployments. The Medical Intelligence group at FOI CBRN Security and Defence in Umea has, on request from and in collaboration with the Swedish Armed Forces, reviewed a variety of international health threat and risk assessment models for military operations. Application of risk assessment methods used in different phases of military operations will be reviewed. An overview of different international approaches used in operational risk management (ORM) will be presented as well as a discussion of the specific needs and constraints for health risk assessment in military operations. This work highlights the specific challenges of risk assessment that are unique to the deployment setting such as the assessment of exposures to a variety of diverse hazards concurrently.

  16. Supervisory Physical Scientist (Power Operations)

    Energy.gov [DOE]

    This position is located in Duty Scheduling (PGSD), Generation Scheduling (PGS), Power Services (P), Bonneville Power Administration. Duty Scheduling provides 24-hour coverage of the real-time...

  17. General displaced SU(1, 1) number states: Revisited

    SciTech Connect (OSTI)

    Dehghani, A. E-mail: a-dehghani@tabrizu.ac.ir

    2014-04-15

    The most general displaced number states, based on the bosonic and an irreducible representation of the Lie algebra symmetry of su(1, 1) and associated with the Calogero-Sutherland model are introduced. Here, we utilize the Barut-Girardello displacement operator instead of the Klauder-Perelomov counterpart, to construct new kind of the displaced number states which can be classified in nonlinear coherent states regime, too, with special nonlinearity functions. They depend on two parameters, and can be converted into the well-known Barut-Girardello coherent and number states, respectively, depending on which of the parameters equal to zero. A discussion of the statistical properties of these states is included. Significant are their squeezing properties and anti-bunching effects which can be raised by increasing the energy quantum number. Depending on the particular choice of the parameters of the above scenario, we are able to determine the status of compliance with flexible statistics. Major parts of the issue is spent on something that these states, in fact, should be considered as new kind of photon-added coherent states, too. Which can be reproduced through an iterated action of a creation operator on new nonlinear Barut-Girardello coherent states. Where the latter carry, also, outstanding statistical features.

  18. Job Code Description Hourly Wage TR-I Job Code TR I Wage TR-II Job

    National Nuclear Security Administration (NNSA)

    Wage TR-I Job Code TR I Wage TR-II Job Code TR II Wage TR-III Job Code TR III Wage Job Code Description Hourly Wage TR-I Job Code TR I Wage TR-II Job Code TR II Wage TR-III Job Code TR III Wage 56-HOUR TOUR Hourly Premiums TR-I 0.25 TR-II $0.50 TR-III $0.75 10-HOUR SHIFT Hourly Premiums TR-I $0.45 TR-II $0.90 TR-III $1.35 CIC $0.60 CIC $1.08 HAZ $0.81 HAZ $1.46 UD/BA $0.25 UD/BA $0.45 ELF $0.30 ELF $0.54 TR-I $0.25 TR-I $0.45 TR-II $0.50 TR-II $0.90 TR-III $0.75 TR-III $1.35 021450 Entry-Level

  19. Safety aspects of cryochamber operation

    SciTech Connect (OSTI)

    Chorowski, M.; Piotrowska, A.; Sieron, A.; Stanek, A.

    2014-01-29

    Local and whole body cryotherapy is well recognized, developed and appreciated both from medical and technical point of view. Poland is a country with a highest number of medical cryochambers in operation (above 200) and more than 3 millions of whole body cryotherapeutic sessions have been performed since 1989. Cryogenic temperatures applied for whole-body apart from medical effects have also significant influence on patient's psyche. A number of cryochambers is constantly increasing in hospitals, sport centers and spas. A temperature inside a cryochamber should be below 150 K. To achieve and stabilize such low temperature, either cascade compressor unit or liquid cryogens evaporation (N{sub 2} or synthetic air) are used. This paper presents safety oriented review of cryochamber design and constructions.

  20. METHOD OF OPERATING NUCLEAR REACTORS

    DOE Patents [OSTI]

    Untermyer, S.

    1958-10-14

    A method is presented for obtaining enhanced utilization of natural uranium in heavy water moderated nuclear reactors by charging the reactor with an equal number of fuel elements formed of natural uranium and of fuel elements formed of uranium depleted in U/sup 235/ to the extent that the combination will just support a chain reaction. The reactor is operated until the rate of burnup of plutonium equals its rate of production, the fuel elements are processed to recover plutonium, the depleted uranium is discarded, and the remaining uranium is formed into fuel elements. These fuel elements are charged into a reactor along with an equal number of fuel elements formed of uranium depleted in U/sup 235/ to the extent that the combination will just support a chain reaction, and reuse of the uranium is continued as aforesaid until it wlll no longer support a chain reaction when combined with an equal quantity of natural uranium.