National Library of Energy BETA

Sample records for forecast evaluation table

  1. Metrics for Evaluating the Accuracy of Solar Power Forecasting (Presentation)

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B.; Florita, A.; Lu, S.; Hamann, H.; Banunarayanan, V.

    2013-10-01

    This presentation proposes a suite of metrics for evaluating the performance of solar power forecasting.

  2. Metrics for Evaluating the Accuracy of Solar Power Forecasting: Preprint

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.; Florita, A.; Lu, S.; Hamann, H. F.; Banunarayanan, V.

    2013-10-01

    Forecasting solar energy generation is a challenging task due to the variety of solar power systems and weather regimes encountered. Forecast inaccuracies can result in substantial economic losses and power system reliability issues. This paper presents a suite of generally applicable and value-based metrics for solar forecasting for a comprehensive set of scenarios (i.e., different time horizons, geographic locations, applications, etc.). In addition, a comprehensive framework is developed to analyze the sensitivity of the proposed metrics to three types of solar forecasting improvements using a design of experiments methodology, in conjunction with response surface and sensitivity analysis methods. The results show that the developed metrics can efficiently evaluate the quality of solar forecasts, and assess the economic and reliability impact of improved solar forecasting.

  3. SECTION M EVALUATION FACTORS FOR AWARD TABLE OF CONTENTS M-1 EVALUATION OF PROPOSALS .....................................................................................2

    National Nuclear Security Administration (NNSA)

    TABLE OF CONTENTS M-1 EVALUATION OF PROPOSALS .....................................................................................2 M-2 BASIS FOR CONTRACT AWARD ...................................................................................3 M-3 TECHNICAL AND MANAGEMENT CRITERIA ..........................................................3 M-4 COST EVALUATION CRITERION .................................................................................5 Section M, Evaluation Factors Request for

  4. SECTION M EVALUATION FACTORS FOR AWARD TABLE OF CONTENTS M-1 EVALUATION OF PROPOSALS .....................................................................................2

    National Nuclear Security Administration (NNSA)

    M EVALUATION FACTORS FOR AWARD TABLE OF CONTENTS M-1 EVALUATION OF PROPOSALS .....................................................................................2 M-2 BASIS FOR CONTRACT AWARD ...................................................................................3 M-3 TECHNICAL AND MANAGEMENT CRITERIA ..........................................................3 M-4 COST CRITERION

  5. Economic Evaluation of Short-Term Wind Power Forecasts in ERCOT: Preliminary Results; Preprint

    SciTech Connect (OSTI)

    Orwig, K.; Hodge, B. M.; Brinkman, G.; Ela, E.; Milligan, M.; Banunarayanan, V.; Nasir, S.; Freedman, J.

    2012-09-01

    Historically, a number of wind energy integration studies have investigated the value of using day-ahead wind power forecasts for grid operational decisions. These studies have shown that there could be large cost savings gained by grid operators implementing the forecasts in their system operations. To date, none of these studies have investigated the value of shorter-term (0 to 6-hour-ahead) wind power forecasts. In 2010, the Department of Energy and National Oceanic and Atmospheric Administration partnered to fund improvements in short-term wind forecasts and to determine the economic value of these improvements to grid operators, hereafter referred to as the Wind Forecasting Improvement Project (WFIP). In this work, we discuss the preliminary results of the economic benefit analysis portion of the WFIP for the Electric Reliability Council of Texas. The improvements seen in the wind forecasts are examined, then the economic results of a production cost model simulation are analyzed.

  6. FY 2005 Laboratory Table

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

    Congressional Budget Request Laboratory Tables Preliminary Department of Energy FY 2005 Congressional Budget Request Office of Management, Budget and Evaluation/CFO February 2004 Laboratory Tables Preliminary Department of Energy Department of Energy FY 2005 Congressional Budget FY 2005 Congressional Budget Request Request Office of Management, Budget and Evaluation/CFO February 2004 Laboratory Tables Laboratory Tables Printed with soy ink on recycled paper Preliminary Preliminary The numbers

  7. FY 2005 State Table

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

    Office of Management, Budget and Evaluation/CFO February 2004 State Tables State Tables Preliminary Preliminary Department of Energy Department of Energy FY 2005 Congressional Budget FY 2005 Congressional Budget Request Request Office of Management, Budget and Evaluation/CFO February 2004 State Tables State Tables Printed with soy ink on recycled paper Preliminary Preliminary The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The

  8. Evaluation of Forecasted Southeast Pacific Stratocumulus in the NCAR, GFDL and ECMWF Models

    SciTech Connect (OSTI)

    Hannay, C; Williamson, D L; Hack, J J; Kiehl, J T; Olson, J G; Klein, S A; Bretherton, C S; K?hler, M

    2008-01-24

    We examine forecasts of Southeast Pacific stratocumulus at 20S and 85W during the East Pacific Investigation of Climate (EPIC) cruise of October 2001 with the ECMWF model, the Atmospheric Model (AM) from GFDL, the Community Atmosphere Model (CAM) from NCAR, and the CAM with a revised atmospheric boundary layer formulation from the University of Washington (CAM-UW). The forecasts are initialized from ECMWF analyses and each model is run for 3 days to determine the differences with the EPIC field data. Observations during the EPIC cruise show a stable and well-mixed boundary layer under a sharp inversion. The inversion height and the cloud layer have a strong and regular diurnal cycle. A key problem common to the four models is that the forecasted planetary boundary layer (PBL) height is too low when compared to EPIC observations. All the models produce a strong diurnal cycle in the Liquid Water Path (LWP) but there are large differences in the amplitude and the phase compared to the EPIC observations. This, in turn, affects the radiative fluxes at the surface. There is a large spread in the surface energy budget terms amongst the models and large discrepancies with observational estimates. Single Column Model (SCM) experiments with the CAM show that the vertical pressure velocity has a large impact on the PBL height and LWP. Both the amplitude of the vertical pressure velocity field and its vertical structure play a significant role in the collapse or the maintenance of the PBL.

  9. Use of Data Denial Experiments to Evaluate ESA Forecast Sensitivity Patterns

    SciTech Connect (OSTI)

    Zack, J; Natenberg, E J; Knowe, G V; Manobianco, J; Waight, K; Hanley, D; Kamath, C

    2011-09-13

    The overall goal of this multi-phased research project known as WindSENSE is to develop an observation system deployment strategy that would improve wind power generation forecasts. The objective of the deployment strategy is to produce the maximum benefit for 1- to 6-hour ahead forecasts of wind speed at hub-height ({approx}80 m). In this phase of the project the focus is on the Mid-Columbia Basin region which encompasses the Bonneville Power Administration (BPA) wind generation area shown in Figure 1 that includes Klondike, Stateline, and Hopkins Ridge wind plants. The Ensemble Sensitivity Analysis (ESA) approach uses data generated by a set (ensemble) of perturbed numerical weather prediction (NWP) simulations for a sample time period to statistically diagnose the sensitivity of a specified forecast variable (metric) for a target location to parameters at other locations and prior times referred to as the initial condition (IC) or state variables. The ESA approach was tested on the large-scale atmospheric prediction problem by Ancell and Hakim 2007 and Torn and Hakim 2008. ESA was adapted and applied at the mesoscale by Zack et al. (2010a, b, and c) to the Tehachapi Pass, CA (warm and cools seasons) and Mid-Colombia Basin (warm season only) wind generation regions. In order to apply the ESA approach at the resolution needed at the mesoscale, Zack et al. (2010a, b, and c) developed the Multiple Observation Optimization Algorithm (MOOA). MOOA uses a multivariate regression on a few select IC parameters at one location to determine the incremental improvement of measuring multiple variables (representative of the IC parameters) at various locations. MOOA also determines how much information from each IC parameter contributes to the change in the metric variable at the target location. The Zack et al. studies (2010a, b, and c), demonstrated that forecast sensitivity can be characterized by well-defined, localized patterns for a number of IC variables such as 80-m

  10. Seismic fragility evaluation of a piping system in a nuclear power plant by shaking table test and numerical analysis

    SciTech Connect (OSTI)

    Kim, M. K.; Kim, J. H.; Choi, I. K.

    2012-07-01

    In this study, a seismic fragility evaluation of the piping system in a nuclear power plant was performed. For the evaluation of seismic fragility of the piping system, this research was progressed as three steps. At first, several piping element capacity tests were performed. The monotonic and cyclic loading tests were conducted under the same internal pressure level of actual nuclear power plants to evaluate the performance. The cracks and wall thinning were considered as degradation factors of the piping system. Second, a shaking tale test was performed for an evaluation of seismic capacity of a selected piping system. The multi-support seismic excitation was performed for the considering a difference of an elevation of support. Finally, a numerical analysis was performed for the assessment of seismic fragility of piping system. As a result, a seismic fragility for piping system of NPP in Korea by using a shaking table test and numerical analysis. (authors)

  11. 10Li General Tables

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

    Li General Table The General Table for 10Li is subdivided into the following categories: Reviews Theoretical Ground State Properties Shell Model Cluster Model Other Models Special States Astrophysical Electromagnetic Transitions Hypernuclei Photodisintegration Light-Ion and Neutron Induced Reactions These General Tables correspond to the 2003 preliminary evaluation of ``Energy Levels of Light Nuclei, A = 10''. The prepublication version of A = 10 is available on this website in PDF format: A =

  12. Solar Forecasting

    Broader source: Energy.gov [DOE]

    On December 7, 2012, DOE announced $8 million to fund two solar projects that are helping utilities and grid operators better forecast when, where, and how much solar power will be produced at U.S....

  13. Value of Wind Power Forecasting

    SciTech Connect (OSTI)

    Lew, D.; Milligan, M.; Jordan, G.; Piwko, R.

    2011-04-01

    This study, building on the extensive models developed for the Western Wind and Solar Integration Study (WWSIS), uses these WECC models to evaluate the operating cost impacts of improved day-ahead wind forecasts.

  14. FY 2006 Laboratory Table

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

    Laboratory Tables Preliminary Department of Energy FY 2006 Congressional Budget Request Office of Management, Budget and Evaluation/CFO February 2005 Laboratory Tables Preliminary Printed with soy ink on recycled paper The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, uses of prior year balances, deferrals,

  15. FY 2006 State Table

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

    State Tables Preliminary Department of Energy FY 2006 Congressional Budget Request Office of Management, Budget and Evaluation/CFO February 2005 State Tables Preliminary Printed with soy ink on recycled paper The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, uses of prior year balances, deferrals, rescissions, or

  16. Central Wind Forecasting Programs in North America by Regional Transmission Organizations and Electric Utilities: Revised Edition

    SciTech Connect (OSTI)

    Rogers, J.; Porter, K.

    2011-03-01

    The report and accompanying table addresses the implementation of central wind power forecasting by electric utilities and regional transmission organizations in North America. The first part of the table focuses on electric utilities and regional transmission organizations that have central wind power forecasting in place; the second part focuses on electric utilities and regional transmission organizations that plan to adopt central wind power forecasting in 2010. This is an update of the December 2009 report, NREL/SR-550-46763.

  17. Table 4

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

    112 70 83 98 99 117 150 5.89 Notes: -- To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. -- Because of rounding, data may...

  18. Table 4

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

    125 43 101 95 99 130 149 8.25 Notes: -- To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. -- Because of rounding, data may...

  19. Table 4

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

    125 69 112 131 137 158 7.36 Notes: -- To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. -- Because of rounding, data may...

  20. EERE Guide for Managing General Program Evaluation Studies

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

    ... 34 Table 6. Selection of Evaluation Research Design for Impact Evaluations... 35 Table 7. Example:...

  1. Forecast Change

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

    Forecast Change 2011 2012 2013 2014 2015 2016 from 2015 United States Usage (kWh) 3,444 3,354 3,129 3,037 3,151 3,302 4.8% Price (cents/kWh) 12.06 12.09 12.58 13.04 12.95 12.84 -0.9% Expenditures $415 $405 $393 $396 $408 $424 3.9% New England Usage (kWh) 2,122 2,188 2,173 1,930 1,992 2,082 4.5% Price (cents/kWh) 15.85 15.50 16.04 17.63 18.64 18.37 -1.5% Expenditures $336 $339 $348 $340 $371 $382 3.0% Mid-Atlantic Usage (kWh) 2,531 2,548 2,447 2,234 2,371 2,497 5.3% Price (cents/kWh) 16.39 15.63

  2. Table 4

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

    10.8 0.3 0.8 1.6 2.0 2.2 4.0 11.94 Notes: -- To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. -- Because of rounding, data may...

  3. Table 4

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

    10.8 0.9 2.9 1.9 2.8 2.3 9.84 Notes: -- To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. -- Because of rounding, data may...

  4. Table 4

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

    0.6 0.8 0.6 1.4 2.3 1.9 2.5 12.69 Notes: -- To obtain the RSE percentage for any table cell, multiply the corresponding column and row factors. -- Because of rounding, data may...

  5. A = 5 General Tables

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

    5 General Tables The General Table for 5H is subdivided into the following categories: Cluster Model Hypernuclei Model Calculations Photodisintegration Pions The General Table for...

  6. Table 7

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

    1 Table 7 Created on: 8/29/2016 8:24:42 AM Table 7. Marketed production of natural gas in selected states and the Federal Gulf of Mexico, 2011-2016 (million cubic feet) Year and Month Alaska Arkansas California Colorado Kansas Louisiana Montana New Mexico North Dakota Ohio 2011 Total 356,225 1,072,212 250,177 1,637,576 309,124 3,029,206 74,624 1,237,303 97,102 78,858 2012 Total 351,259 1,146,168 246,822 1,709,376 296,299 2,955,437 66,954 1,215,773 172,242 84,482 2013 Total 338,182 1,139,654

  7. A=19 Tables

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

    Tables for A = 19 Available in the following years: (1995), (1987), (1983), (1978), (1972), (1959) Adobe Reader Download Tables from (1995TI07): Introductory Table 3 in PS or PDF. Table 19.1 in PS or PDF. Table 19.2 in PS or PDF. Table 19.3 in PS or PDF. Table 19.4 in PS or PDF. Table 19.5 in PS or PDF. Table 19.6 in PS or PDF. Table 19.7 in PS or PDF. Table 19.8 in PS or PDF. Table 19.9 in PS or PDF. Table 19.10 in PS or PDF. Table 19.11 in PS or PDF. Table 19.12 in PS or PDF. Table 19.13 in PS

  8. A=20 Tables

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

    Tables for A = 20 Available in the following years: (1998), (1987), (1983), (1978), (1972), (1959) Adobe Reader Download Tables from (1998TI06): Introductory Table 3 in PS or PDF. Table 20.1 in PS or PDF. Table 20.2 in PS or PDF. Table 20.3 in PS or PDF. Table 20.4 in PS or PDF. Table 20.5 in PS or PDF. Table 20.6 in PS or PDF. Table 20.7 in PS or PDF. Table 20.8 in PS or PDF. Table 20.9 in PS or PDF. Table 20.10 in PS or PDF. Table 20.11 in PS or PDF. Table 20.12 in PS or PDF. Table 20.13 in PS

  9. 1999 CBECS Detailed Tables

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

    Commercial Buildings Energy Consumption Survey (CBECS) > Detailed Tables 1999 CBECS Detailed Tables Building Characteristics | Consumption & Expenditures Data from the 1999...

  10. 8C General Tables

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

    C General Tables The General Table for 8C is subdivided into the following categories: Reviews Other Theoretical Work...

  11. 6Be General Tables

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

    6Be General Table The General Table for 6Be is subdivided into the following categories: Cluster Model Model Calculations...

  12. A=18 Tables

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

    (1959) Adobe Reader Download Tables from (1995TI07): Introductory Table 3 in PS or PDF. Table 18.1 in PS or PDF. Table 18.2 in PS or PDF. Table 18.3 in PS or PDF. Table 18.4...

  13. Flood Forecasting in River System Using ANFIS

    SciTech Connect (OSTI)

    Ullah, Nazrin; Choudhury, P.

    2010-10-26

    The aim of the present study is to investigate applicability of artificial intelligence techniques such as ANFIS (Adaptive Neuro-Fuzzy Inference System) in forecasting flood flow in a river system. The proposed technique combines the learning ability of neural network with the transparent linguistic representation of fuzzy system. The technique is applied to forecast discharge at a downstream station using flow information at various upstream stations. A total of three years data has been selected for the implementation of this model. ANFIS models with various input structures and membership functions are constructed, trained and tested to evaluate efficiency of the models. Statistical indices such as Root Mean Square Error (RMSE), Correlation Coefficient (CORR) and Coefficient of Efficiency (CE) are used to evaluate performance of the ANFIS models in forecasting river flood. The values of the indices show that ANFIS model can accurately and reliably be used to forecast flood in a river system.

  14. Wind Power Forecasting Data

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

    Operations Call 2012 Retrospective Reports 2012 Retrospective Reports 2011 Smart Grid Wind Integration Wind Integration Initiatives Wind Power Forecasting Wind Projects Email...

  15. probabilistic energy production forecasts

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

    energy production forecasts - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary ...

  16. Wind Power Forecasting

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

    data Presentations BPA Super Forecast Methodology Related Links Near Real-time Wind Animation Meteorological Data Customer Supplied Generation Imbalance Dynamic Transfer Limits...

  17. Forecasting Water Quality & Biodiversity

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

    Forecasting Water Quality & Biodiversity March 25, 2015 Cross-cutting Sustainability ... that measure feedstock production, water quality, water quantity, and biodiversity. ...

  18. A critical evaluation of the upper ocean heat budget in the Climate Forecast System Reanalysis data for the south central equatorial Pacific

    SciTech Connect (OSTI)

    Liu H.; Lin W.; Liu, X.; Zhang, M.

    2011-08-26

    Coupled ocean-atmospheric models suffer from the common bias of a spurious rain belt south of the central equatorial Pacific throughout the year. Observational constraints on key processes responsible for this bias are scarce. The recently available reanalysis from a coupled model system for the National Centers for Environmental Prediction (NCEP) Climate Forecast System Reanalysis (CFSR) data is a potential benchmark for climate models in this region. Its suitability for model evaluation and validation, however, needs to be established. This paper examines the mixed layer heat budget and the ocean surface currents - key factors for the sea surface temperature control in the double Inter-Tropical Convergence Zone in the central Pacific - from 5{sup o}S to 10{sup o}S and 170{sup o}E to 150{sup o}W. Two independent approaches are used. The first approach is through comparison of CFSR data with collocated station observations from field experiments; the second is through the residual analysis of the heat budget of the mixed layer. We show that the CFSR overestimates the net surface flux in this region by 23 W m{sup -2}. The overestimated net surface flux is mainly due to an even larger overestimation of shortwave radiation by 44 W m{sup -2}, which is compensated by a surface latent heat flux overestimated by 14 W m{sup -2}. However, the quality of surface currents and the associated oceanic heat transport in CFSR are not compromised by the surface flux biases, and they agree with the best available estimates. The uncertainties of the observational data from field experiments are also briefly discussed in the present study.

  19. 1995 Detailed Tables

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

    Households, Buildings & Industry > Commercial Buildings Energy Consumption Survey > Detailed Tables 1995 Detailed Tables Data from the 1995 Commercial Buildings Energy Consumption...

  20. 7He General Tables

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

    He General Table The General Table for 7He is subdivided into the following categories: Experimental Theoretical Model Calculations Hypernuclei and Mesons Pions

  1. 9He General Tables

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

    He General Table The General Table for 9He is subdivided into the following categories: Shell Model Other Model Calculations Theoretical

  2. 5He General Tables

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

    He General Table The General Table for 5He is subdivided into the following categories: Ground State Properties Theoretical Special States Model Discussions Shell Model Cluster...

  3. 6He General Tables

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

    He General Table The General Table for 6He is subdivided into the following categories: Ground State Properties Theoretical Special States Shell Model Cluster and alpha-particle...

  4. 7Be General Tables

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

    Be General Table The General Table for 7Be is subdivided into the following categories: Reviews Experimental Work Shell Model Cluster Model Other Theoretical Work Model...

  5. A = 10 General Tables

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

    Table for 10He is subdivided into the following categories: Theoretical Shell Model Cluster Model Other Models Special States Electromagnetic Transitions The General Table for...

  6. 5H General Tables

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

    H General Table The General Table for 5H is subdivided into the following categories: Cluster Model Hypernuclei Model Calculations Photodisintegration Pions...

  7. 10He General Tables

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

    General Table The General Table for 10He is subdivided into the following categories: Theoretical Shell Model Cluster Model Other Models Special States Electromagnetic Transitions...

  8. FY 2005 Statistical Table

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

    Statistical Table by Appropriation (dollars in thousands - OMB Scoring) Table of Contents Summary...................................................................................................... 1 Mandatory Funding....................................................................................... 3 Energy Supply.............................................................................................. 4 Non-Defense site acceleration

  9. NREL: Transmission Grid Integration - Forecasting

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

    Forecasting NREL researchers use solar and wind resource assessment and forecasting techniques to develop models that better characterize the potential benefits and impacts of ...

  10. Ramp Forecasting Performance from Improved Short-Term Wind Power Forecasting: Preprint

    SciTech Connect (OSTI)

    Zhang, J.; Florita, A.; Hodge, B. M.; Freedman, J.

    2014-05-01

    The variable and uncertain nature of wind generation presents a new concern to power system operators. One of the biggest concerns associated with integrating a large amount of wind power into the grid is the ability to handle large ramps in wind power output. Large ramps can significantly influence system economics and reliability, on which power system operators place primary emphasis. The Wind Forecasting Improvement Project (WFIP) was performed to improve wind power forecasts and determine the value of these improvements to grid operators. This paper evaluates the performance of improved short-term wind power ramp forecasting. The study is performed for the Electric Reliability Council of Texas (ERCOT) by comparing the experimental WFIP forecast to the current short-term wind power forecast (STWPF). Four types of significant wind power ramps are employed in the study; these are based on the power change magnitude, direction, and duration. The swinging door algorithm is adopted to extract ramp events from actual and forecasted wind power time series. The results show that the experimental short-term wind power forecasts improve the accuracy of the wind power ramp forecasting, especially during the summer.

  11. 2016 Solar Forecasting Workshop

    Office of Energy Efficiency and Renewable Energy (EERE)

    On August 3, 2016, the SunShot Initiative's systems integration subprogram hosted the Solar Forecasting Workshop to convene experts in the areas of bulk power system operations, distribution system operations, weather and solar irradiance forecasting, and photovoltaic system operation and modeling. The goal was to identify the technical challenges and opportunities in solar forecasting as a capability that can significantly reduce the integration cost of high levels of solar energy into the electricity grid. This will help SunShot to assess current technology and practices in this field and identify the gaps and needs for further research.

  12. Today's Forecast: Improved Wind Predictions

    Broader source: Energy.gov [DOE]

    Accurate weather forecasts are critical for making energy sources -- including wind and solar -- dependable and predictable.

  13. Solar Forecast Improvement Project

    Office of Energy Efficiency and Renewable Energy (EERE)

    For the Solar Forecast Improvement Project (SFIP), the Earth System Research Laboratory (ESRL) is partnering with the National Center for Atmospheric Research (NCAR) and IBM to develop more...

  14. CBECS Buildings Characteristics --Revised Tables

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

    Energy Sources and End Use Tables (27 pages, 152 kb) CONTENTS PAGES Table 18. Energy Sources, Number of Buildings, 1995 Table 19. Energy Sources, Floorspace, 1995 Table 20. Energy End Uses, Number of Buildings and Floorspace, 1995 Table 21. Space-Heating Energy Sources, Number of Buildings, 1995 Table 22. Space-Heating Energy Sources, Floorspace, 1995 Table 23. Primary Space-Heating Energy Sources, Number of Buildings, 1995 Table 24. Primary Space-Heating Energy Sources, Floorspace, 1995 Table

  15. CBECS Buildings Characteristics --Revised Tables

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

    End-Use Equipment Tables (27 pages, 151 kb) CONTENTS PAGES Table 33. Heating Equipment, Number of Buildings, 1995 Table 34. Heating Equipment, Floorspace, 1995 Table 35. Cooling Equipment,Number of Buildings, 1995 Table 36. Cooling Equipment, Floorspace, 1995 Table 37. Refrigeration Equipment, Number of Buildings and Floorspace, 1995 Table 38. Water-Heating Equipment, Number of Buildings and Floorspace, 1995 Table 39. Lighting Equipment, Number of Buildings, 1995 Table 40. Lighting Equipment,

  16. Acquisition Forecast | Department of Energy

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

    Acquisition Forecast Acquisition Forecast Acquisition Forecast It is the policy of the U.S. Department of Energy (DOE) to provide timely information to the public regarding DOE's forecast of future prime contracting opportunities and subcontracting opportunities which are available via the Department's major site and facilities management contractors. This forecast has been expanded to also provide timely status information for ongoing prime contracting actions that are valued in excess of the

  17. 8Be General Tables

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

    Be General Tables The General Table for 8Be is subdivided into the following categories: Reviews Ground State Properties Shell Model Cluster Model Other Models Photodisintegration Fission and Fusion Astrophysical b-decay Hypernuclei

  18. 8He General Tables

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

    He General Tables The General Table for 8He is subdivided into the following categories: Reviews Ground-state Properties Shell Model Cluster Model Other Theoretical Work Elastic and Inelastic Scattering b-decay

  19. 9B General Tables

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

    B General Table The General Table for 9B is subdivided into the following categories: Shell Model Cluster Model Theoretical Other Model Calculations Complex Reactions Beta-Decay Pions Light-ion and Neutron Induced Reactions Hypernuclei

  20. 9C General Tables

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

    C General Table The General Table for 9C is subdivided into the following categories: Shell Model Cluster Model Other Models Theoretical Beta-Decay Light-ion and Neutron Induced Reactions Astrophysical

  1. Tabled Execution in Scheme

    SciTech Connect (OSTI)

    Willcock, J J; Lumsdaine, A; Quinlan, D J

    2008-08-19

    Tabled execution is a generalization of memorization developed by the logic programming community. It not only saves results from tabled predicates, but also stores the set of currently active calls to them; tabled execution can thus provide meaningful semantics for programs that seemingly contain infinite recursions with the same arguments. In logic programming, tabled execution is used for many purposes, both for improving the efficiency of programs, and making tasks simpler and more direct to express than with normal logic programs. However, tabled execution is only infrequently applied in mainstream functional languages such as Scheme. We demonstrate an elegant implementation of tabled execution in Scheme, using a mix of continuation-passing style and mutable data. We also show the use of tabled execution in Scheme for a problem in formal language and automata theory, demonstrating that tabled execution can be a valuable tool for Scheme users.

  2. 6Li General Tables

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

    Li General Table The General Table for 6Li is subdivided into the following categories: Ground State Properties of 6Li Special States Theoretical Shell Model Cluster Models Complex...

  3. Hot cell examination table

    DOE Patents [OSTI]

    Gaal, Peter S.; Ebejer, Lino P.; Kareis, James H.; Schlegel, Gary L.

    1991-01-01

    A table for use in a hot cell or similar controlled environment for use in examining specimens. The table has a movable table top that can be moved relative to a table frame. A shaft is fixedly mounted to the frame for axial rotation. A shaft traveler having a plurality of tilted rollers biased against the shaft is connected to the table top such that rotation of the shaft causes the shaft traveler to roll along the shaft. An electromagnetic drive is connected to the shaft and the frame for controllably rotating the shaft.

  4. Issues in midterm analysis and forecasting, 1996

    SciTech Connect (OSTI)

    1996-08-01

    This document consists of papers which cover topics in analysis and modeling that underlie the Annual Energy Outlook 1996. Topics include: The Potential Impact of Technological Progress on U.S. Energy Markets; The Outlook for U.S. Import Dependence; Fuel Economy, Vehicle Choice, and Changing Demographics, and Annual Energy Outlook Forecast Evaluation.

  5. 1997 Housing Characteristics Tables Housing Unit Tables

    Gasoline and Diesel Fuel Update (EIA)

    Contact: Robert Latta, Survey Manager (rlatta@eia.doe.gov) World Wide Web: http:www.eia.doe.govemeuconsumption Table HC1-1a. Housing Unit Characteristics by Climate Zone, ...

  6. Final Report- Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations

    Office of Energy Efficiency and Renewable Energy (EERE)

    Four major research objectives were completed over the course of this study. Three of the objectives were to evaluate three, new, state-of-the-art solar irradiance forecasting models. The fourth objective was to improve the California independent system operator’s load forecasts by integrating behind-the-meter photovoltaic forecasts.

  7. SECTION J - TABLE OF CONTENTS

    National Nuclear Security Administration (NNSA)

    Conformed to Mod 0108 DE-NA0000622 Section J Page i PART III - LIST OF DOCUMENTS, EXHIBITS, AND OTHER ATTACHMENTS SECTION J LIST OF APPENDICES TABLE OF CONTENTS Appendix A Statement of Work (Replaced by Mod 002; Modified Mod 016; Replaced Mod 029) Appendix B Performance Evaluation Plan (Replaced by Mods 002, 016, 020, 029, 0084) Appendix C Contractor's Transition Plan Appendix D Sensitive Foreign Nations Control Appendix E Performance Guarantee Agreement(s) Appendix F National Work Breakdown

  8. 1997 MWD comparison tables

    SciTech Connect (OSTI)

    Wiseman, K.

    1997-05-01

    This year`s MWD Comparison Tables include a Quick Reference Guide listing MWD sensors by collar size for each manufacturer. Following the Quick Reference Guide are the comparison tables, which list general, directional, gamma ray, resistivity, density and neutron data for each tool. The MWD Tables should only be used as a reference source. System specifications frequently change as tools are refined and developed. Consult MWD marketing representatives prior to making final tool selections. A contact key for all the companies listed in the tables appears on the last page.

  9. Table of Contents

    Energy Savers [EERE]

    Table 10 Costs of Foreign Travel, IG-0397 Table 10 Costs of Foreign Travel, IG-0397 Table 10 Costs of Foreign Travel, IG-0397 Table 10 Costs of Foreign Travel, IG-0397 (242.36 KB) More Documents & Publications Inspection Report: IG-0397 Audit of Department of Energy International Charter Flights, IG-0397 John C. Layton: Before The Subcommittee on Oversight and Investigations Committee on Commerce

    U U . . S S . . D D E E P P A A R R T T M M E E N N T T O O F F E E N N E E R R G G Y Y O O F

  10. Description of Detailed Tables

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

    for the 1999 Commercial Buildings Energy Consumption Survey (CBECS) consists of building characteristics tables B1 through B39, which contain the number of buildings and...

  11. A = 9 General Tables

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

    The General Table for 9Li is subdivided into the following categories: Shell Model Cluster Model Theoretical Ground State Properties Special States Other Model Calculations...

  12. 5Li General Tables

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

    Table for 5Li is subdivided into the folowing categories: Ground State Properties Cluster Model Shell Model Special States Model Calculations Model Discussions Complex...

  13. 10N General Tables

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

    subdivided into the following categories: Reviews Ground-State Properties Shell Model Cluster Model Other Theoretical Work These General Tables correspond to "Energy Levels of...

  14. 7Li General Tables

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

    Li General Table The General Table for 7Li is subdivided into the following categories: Reviews Ground State Properties Shell Model Cluster Model Other Theoretical Work Model Calculations Photodisintegration Polarization Fission and Fusion Elastic and Inelastic Scattering Projectile Fragmentation and Multifragmentation Astrophysical Hyperfine Structure b-decay Muons Hypernuclei and Mesons Hypernuclei and Baryons Pion, Kaon and Eta-Mesons Other Work Applications

  15. 8B General Tables

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

    B General Tables The General Table for 8B is subdivided into the following categories: Reviews Ground State Properties Shell Model Cluster Model Other Models Photodisintegration and Coulomb Dissociation Elastic and Inelastic Scattering Fragmentation Reactions Astrophysical b Decay Nucleon Spatial Distribution

  16. 8Li General Tables

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

    Li General Tables The General Table for 8Li is subdivided into the following categories: Reviews Ground State Properties Shell Model Cluster Model Other Models Photodissociation Fusion and Fission Elastic and Inelastic Scattering Fragmentation Reactions Astrophysical b Decay Hypernuclei Pions, Kaons and h-mesons

  17. 9Li General Tables

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

    Li General Table The General Table for 9Li is subdivided into the following categories: Shell Model Cluster Model Theoretical Ground State Properties Special States Other Model Calculations Complex Reactions Beta-Decay Pions Muons Photodisintegration Elastic and Inelastic Scattering Electromagnetic Transitions Astrophysical

  18. 1996 MWD comparison tables

    SciTech Connect (OSTI)

    Gastineau, J.

    1996-05-01

    Petroleum Engineer International`s ninth annual Measurement While Drilling Tables compare the different operating capabilities of survey and logging tools from 13 MWD vendors. This year`s MWD Comparison Tables include a Quick Reference Guide listing MWD sensors by collar size for each manufacturer. Following the Quick Reference Guide are the comparison tables, listing general, directional, gamma ray, resistivity, density and neutron data for each tool. The MWD Tables should serve only as a reference source. System specifications can change rapidly as tools are refined and developed. Consultation with MWD marketing representatives before making a final tool selection is recommended. A contact key for all of the companies listed in the tables is provided.

  19. 1995 CECS C&E Tables

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

    Fuel Oil Tables (10 pages, 58 kb) CONTENTS PAGES Table 26. Total Fuel Oil Consumption and Expenditures, 1995 Table 27. Fuel Oil Consumption and Expenditure Intensities, 1995 Table...

  20. Microsoft Word - 2012 RCRA CRP comment table.docx

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

    Notice - June 2011 Independent Statistics & Analysis U.S. Energy Information Administration June 2011 Short-Term Energy Outlook Notice: Suspension of Regional Residential Heating Oil and Propane Price Forecasts Because of fiscal year 2011 budget reductions, the U.S. Energy Information Administration (EIA) has suspended surveys that were the source of historical price data published in Tables 12-15 and 34-38 of the Petroleum Marketing Monthly (PMM) that supported the residential retail

  1. All Consumption Tables.vp

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

    4) June 2007 State Energy Consumption Estimates 1960 Through 2004 2004 Consumption Summary Tables Table S1. Energy Consumption Estimates by Source and End-Use Sector, 2004...

  2. Using Wikipedia to forecast diseases

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

    Using Wikipedia to forecast diseases Using Wikipedia to forecast diseases Scientists can now monitor and forecast diseases around the globe more effectively by analyzing views of Wikipedia articles. November 13, 2014 Del Valle and her team observe findings from their research on disease patterns from analyzing Wikipedia articles. Del Valle and her team observe findings from their research on disease patterns from analyzing Wikipedia articles. Contact Nancy Ambrosiano Communications Office (505)

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

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

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

  4. UWIG Forecasting Workshop -- Albany (Presentation)

    SciTech Connect (OSTI)

    Lew, D.

    2011-04-01

    This presentation describes the importance of good forecasting for variable generation, the different approaches used by industry, and the importance of validated high-quality data.

  5. The forecast calls for flu

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

    Science on the Hill: The forecast calls for flu Using mathematics, computer programs, ... We're getting close. Using mathematics, computer programs, statistics and information ...

  6. Forecast Energy | Open Energy Information

    Open Energy Info (EERE)

    Zip: 94965 Region: Bay Area Sector: Services Product: Intelligent Monitoring and Forecasting Services Year Founded: 2010 Website: www.forecastenergy.net Coordinates:...

  7. TABLE OF CONTENTS

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

    3, Revision 0 i TABLE OF CONTENTS 1.0 Summary .............................................................................................................................. 1 2.0 Introduction .......................................................................................................................... 1 3.0 Discussion ............................................................................................................................ 4 3.1 Selection of Tanks for Level Decrease

  8. TABLE OF CONTENTS

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

    4, Revision 0 i TABLE OF CONTENTS 1.0 Summary .............................................................................................................................. 1 2.0 Introduction .......................................................................................................................... 1 3.0 Discussion ............................................................................................................................ 4 3.1 Selection of Tanks for Level Decrease

  9. TABLE OF CONTENTS

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

    5, Revision 0 i TABLE OF CONTENTS 1.0 Summary .............................................................................................................................. 1 2.0 Introduction .......................................................................................................................... 1 3.0 Discussion ............................................................................................................................ 4 3.1 Selection of Tanks for Level Decrease

  10. Tables of Energy Levels

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

    of Energy Levels The Image Map below will direct you to the table of energy levels PDF format only for that particular nuclide from the most recent publication found within...

  11. table11.xls

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

    ... 14.1 NA 17.9 18.3 19.6 20.1 Table 11. Fuel Economy, Selected Survey Years (Miles Per Gallon) Survey Years Page A-1 of A-5 1983 1985 1988...

  12. table3.2

    Gasoline and Diesel Fuel Update (EIA)

    ... NAICS Code(a) Subsector and Industry Total Net Electricity(b... RSE Row Factors Table 3.2 Fuel Consumption, 2002; Level: ... of Energy Markets and End Use, Energy Consumption ...

  13. Building Materials Property Table

    SciTech Connect (OSTI)

    2010-04-16

    This information sheet describes a table of some of the key technical properties of many of the most common building materials taken from ASHRAE Fundamentals - 2001, Moisture Control in Buildings, CMHC, NRC/IRC, IEA Annex 24, and manufacturer data.

  14. A = 7 General Tables

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

    Hyperfine Structure b-decay Muons Hypernuclei and Baryons Pion, Kaon and Eta-Mesons Other Work Applications The General Table for 7Be is subdivided into the following categories:...

  15. TABLE OF CONTENTS

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

    008 High Temperature Superconductivity for Electric Systems Peer Review Final Report i TABLE OF CONTENTS High Temperature Superconductivity for Electric Systems Program Overview ...... 1 The Peer Review................................................................................................................ 3 Review Criteria ................................................................................................................. 5 Guidelines

  16. Table_of_Contents

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

    Table of Contents 1. Physical Security .............................................................................................................................. 1-1 101. Headquarters Security Badges ........................................................................................ 101-1 102. HSPD-12 Badges and the PIV Process ........................................................................... 102-1 103. Prohibited Articles

  17. Table G3

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

    May 28, 2010 Voluntary Reporting of Greenhouse Gases 14 Table G3. Decision Chart for a ... Form EIA-1605 Voluntary Reporting of Greenhouse Gases Form Approved OMB No. 1905-0194 ...

  18. Fy 2009 Laboratory Table

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

    Laboratory Tables Preliminary February 2008 Office of Chief Financial Officer Department of Energy FY 2009 Congressional Budget Request Laboratory Tables Preliminary The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, use of prior year balances, deferrals, rescissions, or other adjustments appropriated as offsets to

  19. FY 2007 Laboratory Table

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

    Laboratory tables preliminary Department of Energy FY 2007 Congressional Budget Request February 2006 Printed with soy ink on recycled paper Office of Chief Financial Officer Laboratory tables preliminary The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, uses of prior year balances, deferrals, rescissions, or other

  20. FY 2007 State Table

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

    state tables preliminary Department of Energy FY 2007 Congressional Budget Request February 2006 Printed with soy ink on recycled paper Office of Chief Financial Officer state tables preliminary The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, uses of prior year balances, deferrals, rescissions, or other

  1. FY 2008 Laboratory Table

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

    Laboratory Table Preliminary Department of Energy FY 2008 Congressional Budget Request February 2007 Office of Chief Financial Officer Laboratory Table Preliminary Printed with soy ink on recycled paper The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, uses of prior year balances, deferrals, rescissions, or other

  2. FY 2008 State Table

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

    State Table Preliminary Department of Energy FY 2008 Congressional Budget Request February 2007 Office of Chief Financial Officer State Table Preliminary Printed with soy ink on recycled paper The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, uses of prior year balances, deferrals, rescissions, or other adjustments

  3. FY 2010 Laboratory Table

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

    Laboratory Tables Preliminary May 2009 Office of Chief Financial Officer FY 2010 Congressional Budget Request Laboratory Tables Preliminary The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, use of prior year balances, deferrals, rescissions, or other adjustments appropriated as offsets to the DOE appropriations by

  4. FY 2011 Laboratory Table

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

    Laboratory Tables Department of Energy FY 2011 Congressional Budget Request DOE/CF-0055 March 2010 Office of Chief Financial Officer Laboratory Tables Printed with soy ink on recycled paper The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, use of prior year balances, deferrals, rescissions, or other adjustments

  5. FY 2011 State Table

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

    State Tables Department of Energy FY 2011 Congressional Budget Request DOE/CF-0054 March 2010 Office of Chief Financial Officer State Tables Printed with soy ink on recycled paper The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider revenues/receipts, use of prior year balances, deferrals, rescissions, or other adjustments appropriated

  6. FY 2012 State Table

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

    6 Department of Energy FY 2012 Congressional Budget Request State Tables P li i Preliminary February 2012 Office of Chief Financial Officer DOE/CF-0066 Department of Energy FY 2012 Congressional Budget Request State Tables P li i Preliminary The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They displayed. The figures include both the discretionary and

  7. FY 2013 State Table

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

    9 Department of Energy FY 2013 Congressional Budget Request State Tables P li i Preliminary February 2012 Office of Chief Financial Officer DOE/CF-0079 Department of Energy FY 2013 Congressional Budget Request State Tables P li i Preliminary The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They displayed. The figures include both the discretionary and

  8. CPMS Tables | Department of Energy

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

    Program Management » Quality Assurance » CPMS Tables CPMS Tables EM Quality Assurance Corporate Performance Metrics table. CPMS Tables (233.47 KB) More Documents & Publications EM Corporate QA Performance Metrics QA Corporate Board Meeting - July 2008 QA Corporate Board Meeting - November 2008

  9. CBECS Buildings Characteristics --Revised Tables

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

    Structure Tables (16 pages, 93 kb) CONTENTS PAGES Table 8. Building Size, Number of Buildings, 1995 Table 9. Building Size, Floorspace, 1995 Table 10. Year Constructed, Number of Buildings, 1995 Table 11. Year Constructed, Floorspace, 1995 These data are from the 1995 Commercial Buildings Energy Consumption Survey (CBECS), a national probability sample survey of commercial buildings sponsored by the Energy Information Administration, that provides information on the use of energy in commercial

  10. Upcoming Funding Opportunity for Wind Forecasting Improvement...

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

    Wind Forecasting Improvement Project in Complex Terrain Upcoming Funding Opportunity for Wind Forecasting Improvement Project in Complex Terrain February 12, 2014 - 10:47am ...

  11. Solar Energy Market Forecast | Open Energy Information

    Open Energy Info (EERE)

    Market Forecast Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Solar Energy Market Forecast AgencyCompany Organization: United States Department of Energy Sector:...

  12. Project Profile: Forecasting and Influencing Technological Progress...

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

    Soft Costs Project Profile: Forecasting and Influencing Technological Progress in Solar Energy Project Profile: Forecasting and Influencing Technological Progress in Solar ...

  13. National Oceanic and Atmospheric Administration Provides Forecasting...

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

    ... will share their expertise with CLASIC and CHAPS forecasters and project leaders as they consult on the forecast that will determine the day's operations plan. -- Storm Prediction ...

  14. Intermediate future forecasting system

    SciTech Connect (OSTI)

    Gass, S.I.; Murphy, F.H.; Shaw, S.H.

    1983-12-01

    The purposes of the Symposium on the Department of Energy's Intermediate Future Forecasting System (IFFS) were: (1) to present to the energy community details of DOE's new energy market model IFFS; and (2) to have an open forum in which IFFS and its major elements could be reviewed and critiqued by external experts. DOE speakers discussed the total system, its software design, and the modeling aspects of oil and gas supply, refineries, electric utilities, coal, and the energy economy. Invited experts critiqued each of these topics and offered suggestions for modifications and improvement. This volume documents the proceedings (papers and discussion) of the Symposium. Separate abstracts have been prepared for each presentation for inclusion in the Energy Data Base.

  15. T-583: Linux Kernel OSF Partition Table Buffer Overflow Lets Local Users Obtain Information

    Broader source: Energy.gov [DOE]

    A local user can create a storage device with specially crafted OSF partition tables. When the kernel automatically evaluates the partition tables, a buffer overflow may occur and data from kernel heap space may leak to user-space.

  16. FY 2012 Laboratory Table

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

    5 Department of Energy FY 2012 Congressional Budget Request Laboratory Tables y Preliminary February 2012 Office of Chief Financial Officer DOE/CF-0065 Department of Energy FY 2012 Congressional Budget Request Laboratory Tables P li i Preliminary h b d i d i hi d h l l f b d h i f h The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider

  17. Microsoft Word - table_01

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

    U.S. Energy Information Administration | Natural Gas Monthly 3 Table 1 Table 1. Summary of natural gas supply and disposition in the United States, 2011-2016 (billion cubic feet) Year and Month Gross Withdrawals Marketed Production NGPL Production a Dry Gas Production b Supplemental Gaseous Fuels c Net Imports Net Storage Withdrawals d Balancing Item e Consumption f 2011 Total 28,479 24,036 1,134 22,902 60 1,963 -354 -94 24,477 2012 Total 29,542 25,283 1,250 24,033 61 1,519 -9 -66 25,538 2013

  18. Microsoft Word - table_08

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

    3 Table 8 Created on: 8/26/2016 3:14:08 PM Table 8. Underground natural gas storage - all operators, 2011-2016 (volumes in billion cubic feet) Year and Month Natural Gas in Underground Storage at End of Period Change in Working Gas from Same Period Previous Year Storage Activity Base Gas Working Gas Total a Volume Percent Injections Withdrawals Net Withdrawals b 2011 Total c -- -- -- -- -- 3,422 3,074 -348 2012 Total c -- -- -- -- -- 2,825 2,818 -7 2013 Total c -- -- -- -- -- 3,156 3,702 546

  19. Microsoft Word - table_09

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

    5 Table 9 Created on: 8/26/2016 3:14:26 PM Table 9. Underground natural gas storage - by season, 2014-2016 (volumes in billion cubic feet) Year, Season, and Month Natural Gas in Underground Storage at End of Period Change in Working Gas from Same Period Previous Year Storage Activity Base Gas Working Gas Total Volume Percent Injections Withdrawals Net Withdrawals a 2014 Refill Season April 4,357 1,066 5,423 -789 -42.5 323 105 -217 May 4,353 1,548 5,901 -722 -31.8 529 51 -478 June 4,358 2,005

  20. Microsoft Word - table_11

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

    7 Table 11 Created on: 8/26/2016 3:15:09 PM Table 11. Underground natural gas storage - storage fields other than salt caverns, 2011-2016 (volumes in billion cubic feet) Year and Month Natural Gas in Underground Storage at End of Period Change in Working Gas from Same Period Previous Year Storage Activity Base Gas Working Gas Total Volume Percent Injections Withdrawals Net Withdrawals a 2011 Total b -- -- -- -- -- 2,889 2,634 -255 2012 Total b -- -- -- -- -- 2,360 2,373 12 2013 Total b -- -- --

  1. Microsoft Word - table_13

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

    U.S. Energy Information Administration | Natural Gas Monthly 33 Table 13 Table 13. Activities of underground natural gas storage operators, by state, June 2016 (volumes in million cubic feet) State Field Count Total Storage Capacity Working Gas Storage Capacity Natural Gas in Underground Storage at End of Period Change in Working Gas from Same Period Previous Year Storage Activity Base Gas Working Gas Total Volume Percent Injections Withdrawals Alabama 2 43,600 33,150 10,450 23,615 34,065 3,085

  2. FY 2013 Laboratory Table

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

    8 Department of Energy FY 2013 Congressional Budget Request Laboratory Tables y Preliminary February 2012 Office of Chief Financial Officer DOE/CF-0078 Department of Energy FY 2013 Congressional Budget Request Laboratory Tables P li i Preliminary h b d i d i hi d h l l f b d h i f h The numbers depicted in this document represent the gross level of DOE budget authority for the years displayed. The figures include both the discretionary and mandatory funding in the budget. They do not consider

  3. Appendix B: Summary Tables

    Gasoline and Diesel Fuel Update (EIA)

    U.S. Energy Information Administration | Analysis of Impacts of a Clean Energy Standard as requested by Chairman Bingaman Appendix B: Summary Tables Table B1. The BCES and alternative cases compared to the Reference case, 2025 2009 2025 Ref Ref BCES All Clean Partial Credit Revised Baseline Small Utilities Credit Cap 2.1 Credit Cap 3.0 Stnds + Cds Generation (billion kilowatthours) Coal 1,772 2,049 1,431 1,305 1,387 1,180 1,767 1,714 1,571 1,358 Petroleum 41 45 43 44 44 44 45 45 45 43 Natural

  4. Science on Tap - Forecasting illness

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

    Science on Tap - Forecasting illness Science on Tap - Forecasting illness WHEN: Mar 17, 2016 5:30 PM - 7:00 PM WHERE: UnQuarked Wine Room 145 Central Park Square, Los Alamos, New Mexico 87544 USA CONTACT: Linda Anderman (505) 665-9196 CATEGORY: Bradbury INTERNAL: Calendar Login Event Description Mark your calendars for this event held every third Thursday from 5:30 to 7 p.m. A short presentation is followed by a lively discussion on a different subject each month. Forecasting the flu (and other

  5. TABLE OF CONTENTS

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

    DE-EM0001840 Page 2 of 108 WIPP Transportation Services Table of Contents SECTION B - SUPPLIES OR SERVICES AND PRICES/COSTS ................................................................ 3 SECTION C - DESCRIPTION/SPECIFICTIONS ....................................................................................... 10 SECTION D -PACKAGING AND MARKING .............................................................................................. 34 SECTION E - INSPECTION AND ACCEPTANCE

  6. FY 2006 Statistical Table

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

    Statistical Table by Appropriation (dollars in thousands - OMB Scoring) FY 2004 FY 2005 FY 2006 Comparable Comparable Request to FY 2006 vs. FY 2005 Approp Approp Congress Discretionary Summary By Appropriation Energy And Water Development Appropriation Summary: Energy Programs Energy supply Operation and maintenance................................................. 787,941 909,903 862,499 -47,404 -5.2% Construction......................................................................... 6,956

  7. TABLE OF CONTENTS

    National Nuclear Security Administration (NNSA)

    AC05-00OR22800 TABLE OF CONTENTS Contents Page # TOC - i SECTION A - SOLICITATION/OFFER AND AWARD ......................................................................... A-i SECTION B - SUPPLIES OR SERVICES AND PRICES/COSTS ........................................................ B-i B.1 SERVICES BEING ACQUIRED ....................................................................................B-2 B.2 TRANSITION COST, ESTIMATED COST, MAXIMUM AVAILABLE FEE, AND AVAILABLE FEE (Modification 295,

  8. Table of Contents

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

    COMMUNICATIONS REQUIREMENTS OF SMART GRID TECHNOLOGIES October 5, 2010 i Table of Contents I. Introduction and Executive Summary.......................................................... 1 a. Overview of Smart Grid Benefits and Communications Needs................. 2 b. Summary of Recommendations .................................................................... 5 II. Federal Government Smart Grid Initiatives ................................................ 7 a. DOE Request for Information

  9. FY 2013 Statistical Table

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

    Statistical Table by Appropriation (dollars in thousands - OMB Scoring) FY 2011 FY 2012 FY 2013 Current Enacted Congressional Approp. Approp. * Request $ % Discretionary Summary By Appropriation Energy And Water Development, And Related Agencies Appropriation Summary: Energy Programs Energy efficiency and renewable energy........................................ 1,771,721 1,809,638 2,337,000 +527,362 +29.1% Electricity delivery and energy reliability.........................................

  10. Acquisition Forecast Download | Department of Energy

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

    Acquisition Forecast Download Acquisition Forecast Download Click on the link to download a copy of the DOE HQ Acquisition Forecast. Acquisition-Forecast-2016-07-20.xlsx (72.85 KB) More Documents & Publications Small Business Program Manager Directory EA-1900: Notice of Availability of a Draft Environmental Assessment Assessment Report: OAS-V-15-01

  11. 1995 CECS C&E Tables

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

    Electricity Tables (35 pages, 218 kb) CONTENTS PAGES Table 9. Total Electricity Consumption and Expenditures, 1995 Table 10. Electricity Consumption and Expenditure Intensities,...

  12. 1995 CECS C&E Tables

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

    kb) CONTENTS PAGES Table 1. Total Energy Consumption by Major Fuel, 1995 Table 9. Total Electricity Consumption and Expenditures, 1995 Table 20. Total Natural Gas Consumption and...

  13. 1995 CECS C&E Tables

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

    pages, 95 kb) CONTENTS PAGES Table 3. Consumption for Sum of Major Fuels, 1995 Table 10. Electricity Consumption and Expenditure Intensities, 1995 Table 21. Natural Gas...

  14. 1995 CECS C&E Tables

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

    kb) CONTENTS PAGES Table 2. Total Energy Expenditures by Major Fuel, 1995 Table 9. Total Electricity Consumption and Expenditures, 1995 Table 20. Total Natural Gas Consumption and...

  15. 1995 CECS C&E Tables

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

    pages, 95 kb) CONTENTS PAGES Table 4. Expenditures for Sum of Major Fuels, 1995 Table10. Electricity Consumption and Expenditure Intensities, 1995 Table 21. Natural Gas...

  16. table3.5_02

    Gasoline and Diesel Fuel Update (EIA)

    ... Wood Chips, Bark Table 3.5 Selected Byproducts in Fuel Consumption, 2002; Level: National ... Notes: To obtain the RSE percentage for any table cell, multiply the cell's corresponding ...

  17. Advanced Vehicle Technologies Awards Table

    Broader source: Energy.gov [DOE]

    The table contains a listing of the applicants, their locations, the amounts of the awards, and description of each project.

  18. Energy.gov Data Tables

    Broader source: Energy.gov [DOE]

    Follow these guidelines for creating Section 508-compliant data tables in the Energy.gov Drupal environment.

  19. 2003 CBECS Detailed Tables: Summary

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

    c32.pdf c32.xls c32.html Fuel Oil (Tables C33-C36) set12-pdf Table C33. Total Fuel Oil Consumption and Expenditures c33-pdf c33.xls c33.html Table C34. Fuel Oil Consumption...

  20. Selected papers on fuel forecasting and analysis

    SciTech Connect (OSTI)

    Gordon, R.L.; Prast, W.G.

    1983-05-01

    Of the 19 presentations at this seminar, covering coal, uranium, oil, and gas issues as well as related EPRI research projects, eleven papers are published in this volume. Nine of the papers primarily address coal-market analysis, coal transportation, and uranium supply. Two additional papers provide an evaluation and perspective on the art and use of coal-supply forecasting models and on the relationship between coal and oil prices. The authors are energy analysts and EPRI research contractors from academia, the consulting profession, and the coal industry. A separate abstract was prepared for each of the 11 papers.

  1. TABLE OF CONTENTS

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

    irecusa.org | LMI Guidelines | 0 www.irecusa.org | LMI Guidelines | i TABLE OF CONTENTS Executive Summary iv Content Overview vii Introduction 1 I. Identifying LMI Customers and Designing Facilities to Serve LMI Customers 5 A. LMI Customers 5 B. Designing Facilities to Serve LMI Customers 6 II. Barriers to Adoption and Opportunities for Engagement 11 A. Financial Barriers 11 B. Ownership Barriers and Split Incentives 14 C. Marketing, Education, and Outreach Barriers 15 D. Opportunities for

  2. Description of Energy Intensity Tables (12)

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

    3. Description of Energy Intensity Data Tables There are 12 data tables used as references for this report. Specifically, these tables are categorized as tables 1 and 2 present...

  3. The Wind Forecast Improvement Project (WFIP). A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations -- the Northern Study Area

    SciTech Connect (OSTI)

    Finley, Cathy

    2014-04-30

    This report contains the results from research aimed at improving short-range (0-6 hour) hub-height wind forecasts in the NOAA weather forecast models through additional data assimilation and model physics improvements for use in wind energy forecasting. Additional meteorological observing platforms including wind profilers, sodars, and surface stations were deployed for this study by NOAA and DOE, and additional meteorological data at or near wind turbine hub height were provided by South Dakota State University and WindLogics/NextEra Energy Resources over a large geographical area in the U.S. Northern Plains for assimilation into NOAA research weather forecast models. The resulting improvements in wind energy forecasts based on the research weather forecast models (with the additional data assimilation and model physics improvements) were examined in many different ways and compared with wind energy forecasts based on the current operational weather forecast models to quantify the forecast improvements important to power grid system operators and wind plant owners/operators participating in energy markets. Two operational weather forecast models (OP_RUC, OP_RAP) and two research weather forecast models (ESRL_RAP, HRRR) were used as the base wind forecasts for generating several different wind power forecasts for the NextEra Energy wind plants in the study area. Power forecasts were generated from the wind forecasts in a variety of ways, from very simple to quite sophisticated, as they might be used by a wide range of both general users and commercial wind energy forecast vendors. The error characteristics of each of these types of forecasts were examined and quantified using bulk error statistics for both the local wind plant and the system aggregate forecasts. The wind power forecast accuracy was also evaluated separately for high-impact wind energy ramp events. The overall bulk error statistics calculated over the first six hours of the forecasts at both the

  4. International Program Action Table - October 2012 | Department...

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

    Communication & Engagement International Programs International Program Action Table - October 2012 International Program Action Table - October 2012 International Program ...

  5. Wind Forecast Improvement Project Southern Study Area Final Report...

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

    Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern ...

  6. Picture of the Week: Forecasting Flu

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

    3 Forecasting Flu What if we could forecast infectious diseases the same way we forecast the weather, and predict how diseases like Dengue, Typhus or Zika were going to spread? March 6, 2016 flu epidemics modellled using social media Watch the video on YouTube. Forecasting Flu What if we could forecast infectious diseases the same way we forecast the weather, and predict how diseases like Dengue, Typhus or Zika were going to spread? Using real-time data from Wikipedia and social media, Sara del

  7. Forecasting the 2013–2014 influenza season using Wikipedia

    SciTech Connect (OSTI)

    Hickmann, Kyle S.; Fairchild, Geoffrey; Priedhorsky, Reid; Generous, Nicholas; Hyman, James M.; Deshpande, Alina; Del Valle, Sara Y.; Salathé, Marcel

    2015-05-14

    Infectious diseases are one of the leading causes of morbidity and mortality around the world; thus, forecasting their impact is crucial for planning an effective response strategy. According to the Centers for Disease Control and Prevention (CDC), seasonal influenza affects 5% to 20% of the U.S. population and causes major economic impacts resulting from hospitalization and absenteeism. Understanding influenza dynamics and forecasting its impact is fundamental for developing prevention and mitigation strategies. We combine modern data assimilation methods with Wikipedia access logs and CDC influenza-like illness (ILI) reports to create a weekly forecast for seasonal influenza. The methods are applied to the 2013-2014 influenza season but are sufficiently general to forecast any disease outbreak, given incidence or case count data. We adjust the initialization and parametrization of a disease model and show that this allows us to determine systematic model bias. In addition, we provide a way to determine where the model diverges from observation and evaluate forecast accuracy. Wikipedia article access logs are shown to be highly correlated with historical ILI records and allow for accurate prediction of ILI data several weeks before it becomes available. The results show that prior to the peak of the flu season, our forecasting method produced 50% and 95% credible intervals for the 2013-2014 ILI observations that contained the actual observations for most weeks in the forecast. However, since our model does not account for re-infection or multiple strains of influenza, the tail of the epidemic is not predicted well after the peak of flu season has passed.

  8. Forecasting the 2013–2014 influenza season using Wikipedia

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

    Hickmann, Kyle S.; Fairchild, Geoffrey; Priedhorsky, Reid; Generous, Nicholas; Hyman, James M.; Deshpande, Alina; Del Valle, Sara Y.; Salathé, Marcel

    2015-05-14

    Infectious diseases are one of the leading causes of morbidity and mortality around the world; thus, forecasting their impact is crucial for planning an effective response strategy. According to the Centers for Disease Control and Prevention (CDC), seasonal influenza affects 5% to 20% of the U.S. population and causes major economic impacts resulting from hospitalization and absenteeism. Understanding influenza dynamics and forecasting its impact is fundamental for developing prevention and mitigation strategies. We combine modern data assimilation methods with Wikipedia access logs and CDC influenza-like illness (ILI) reports to create a weekly forecast for seasonal influenza. The methods are appliedmore » to the 2013-2014 influenza season but are sufficiently general to forecast any disease outbreak, given incidence or case count data. We adjust the initialization and parametrization of a disease model and show that this allows us to determine systematic model bias. In addition, we provide a way to determine where the model diverges from observation and evaluate forecast accuracy. Wikipedia article access logs are shown to be highly correlated with historical ILI records and allow for accurate prediction of ILI data several weeks before it becomes available. The results show that prior to the peak of the flu season, our forecasting method produced 50% and 95% credible intervals for the 2013-2014 ILI observations that contained the actual observations for most weeks in the forecast. However, since our model does not account for re-infection or multiple strains of influenza, the tail of the epidemic is not predicted well after the peak of flu season has passed.« less

  9. National Targets Table

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

    Nov 2011 For instructions on how to use the table and footnotes, see page 2 Education 144 63% 58 K-12 School College/University (campus level) 244 63% 104 Food Sales 570 86% 193 Grocery Store/Food Market Convenience store (with or without gas station) 657 90% 228 Food Service 575 59% 267 Restaurant/Cafeteria 434 53% 207 Fast Food 1170 64% 418 Inpatient Health Care (Hospital) Lodging 163 61% 72 Dormitory/Fraternity/Sorority Hotel/Motel/Inn Mall (Strip and Enclosed) 247 71% 94 Nursing/Assisted

  10. Microsoft Word - table_10

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

    6 Created on: 8/26/2016 3:14:45 PM Table 10. Underground natural gas storage - salt cavern storage fields, 2011-2016 (volumes in billion cubic feet) Year and Month Natural Gas in Underground Storage at End of Period Change in Working Gas from Same Period Previous Year Storage Activity Base Gas Working Gas Total Volume Percent Injections Withdrawals Net Withdrawals a 2011 Total b -- -- -- -- -- 533 440 -92 2012 Total b -- -- -- -- -- 465 445 -20 2013 Total b -- -- -- -- -- 492 521 29 2014 January

  11. The Value of Wind Power Forecasting

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

    ... day-ahead wind generation forecasts yields an average of 195M savings in annual operating costs. Figure 6 shows how operating cost savings vary with improvements in forecasting. ...

  12. EIA lowers forecast for summer gasoline prices

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

    EIA lowers forecast for summer gasoline prices U.S. gasoline prices are expected to be ... according to the new monthly forecast from the U.S. Energy Information Administration. ...

  13. UPF Forecast | Y-12 National Security Complex

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

    Subcontracting / Subcontracting Forecasts / UPF Forecast UPF Forecast UPF Procurement provides the following forecast of subcontracting opportunities. Keep in mind that these requirements may be revised or cancelled, depending on program budget funding or departmental needs. If you have questions or would like to express an interest in any of the opportunities listed below, contact UPF Procurement. Descriptiona Methodb NAICS Est. Dollar Range RFP release/ Award datec Buyer/ Phone Commodities

  14. Wind Forecasting Improvement Project | Department of Energy

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

    Forecasting Improvement Project Wind Forecasting Improvement Project October 3, 2011 - 12:12pm Addthis This is an excerpt from the Third Quarter 2011 edition of the Wind Program R&D Newsletter. In July, the Department of Energy launched a $6 million project with the National Oceanic and Atmospheric Administration (NOAA) and private partners to improve wind forecasting. Wind power forecasting allows system operators to anticipate the electrical output of wind plants and adjust the electrical

  15. Sandia Unstructured Triangle Table Generator

    Energy Science and Technology Software Center (OSTI)

    2013-09-16

    The software generates data tables for thermodynamic and transport properties of materials as described by a set of input models. For each input model parameterization, an associated table is created on an unstructured triangular grid. These grids all conform to the same topology. A statistical accuracy guarantee is provided for the tabular representation of the model. Details of the model and table specification are given in a XML input deck.

  16. Health Care Buildings: Subcategories Table

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

    Subcategories Table Selected Data by Type of Health Care Building Number of Buildings (thousand) Percent of Buildings Floorspace (million square feet) Percent of Floorspace Square...

  17. Health Care Buildings: Equipment Table

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

    Equipment Table Buildings, Size and Age Data by Equipment Types for Health Care Buildings Number of Buildings (thousand) Percent of Buildings Floorspace (million square feet)...

  18. table3.6_02

    Gasoline and Diesel Fuel Update (EIA)

    ... Selected Wood and Wood-Related Products in Fuel Consumption, 2002; Level: National and ... Notes: To obtain the RSE percentage for any table cell, multiply the cell's corresponding ...

  19. MECS 1991 Publications and Tables

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

    Capability To Switch Fuels Appendices Appendix A. Detailed Tables Appendix B. Survey Design, Implementation, and Estimates (file size 141,211 bytes) pages: 22. Appendix C....

  20. Table 1. Crude Oil Prices

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

    from Table 24. Refiner acquisition costs -- Energy Information Administration, Form FEA-P110-M-1, "Refiners' Monthly Cost Allocation Report," January 1978 through June 1978;...

  1. Thirty-Year Solid Waste Generation Maximum and Minimum Forecast for SRS

    SciTech Connect (OSTI)

    Thomas, L.C.

    1994-10-01

    This report is the third phase (Phase III) of the Thirty-Year Solid Waste Generation Forecast for Facilities at the Savannah River Site (SRS). Phase I of the forecast, Thirty-Year Solid Waste Generation Forecast for Facilities at SRS, forecasts the yearly quantities of low-level waste (LLW), hazardous waste, mixed waste, and transuranic (TRU) wastes generated over the next 30 years by operations, decontamination and decommissioning and environmental restoration (ER) activities at the Savannah River Site. The Phase II report, Thirty-Year Solid Waste Generation Forecast by Treatability Group (U), provides a 30-year forecast by waste treatability group for operations, decontamination and decommissioning, and ER activities. In addition, a 30-year forecast by waste stream has been provided for operations in Appendix A of the Phase II report. The solid wastes stored or generated at SRS must be treated and disposed of in accordance with federal, state, and local laws and regulations. To evaluate, select, and justify the use of promising treatment technologies and to evaluate the potential impact to the environment, the generic waste categories described in the Phase I report were divided into smaller classifications with similar physical, chemical, and radiological characteristics. These smaller classifications, defined within the Phase II report as treatability groups, can then be used in the Waste Management Environmental Impact Statement process to evaluate treatment options. The waste generation forecasts in the Phase II report includes existing waste inventories. Existing waste inventories, which include waste streams from continuing operations and stored wastes from discontinued operations, were not included in the Phase I report. Maximum and minimum forecasts serve as upper and lower boundaries for waste generation. This report provides the maximum and minimum forecast by waste treatability group for operation, decontamination and decommissioning, and ER activities.

  2. Microsoft Word - table_03

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

    7 Created on: 8/26/2016 3:17:42 PM Table 3. Selected national average natural gas prices, 2011-2016 (dollars per thousand cubic feet, except where noted) Year and Month NGPL Composite Spot Price a Natural Gas Spot Price b Citygate Price Delivered to Consumers Electric Power Price d Residential Commercial Industrial Price % of Total c Price % of Total c Price % of Total c 2011 Annual Average 15.12 4.00 5.63 11.03 96.2 8.91 67.3 5.13 16.3 4.89 2012 Annual Average 10.98 2.75 4.73 10.65 95.8 8.10

  3. QTR table of respondents | Department of Energy

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

    table of respondents QTR table of respondents (108.44 KB) More Documents & Publications Table of QTR comments in response to Federal Register RFI Table of QTR comments in response to Federal Register RFI Table of QTR comments in response to Federal Register RFI

  4. EM International Program Action Table - June 2014 | Department...

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

    Action Table - June 2014 EM International Program Action Table - June 2014 EM International Program Action Table - June 2014 PDF icon EM International Program Action Table - June ...

  5. 1999 Commercial Building Characteristics--Detailed Tables--Principal...

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

    Principal Building Activities > Detailed Tables-Principal Building Activities Complete Set of 1999 CBECS Detailed Tables Detailed Tables-Principal Building Activities Table B1....

  6. 1999 Commercial Building Characteristics--Detailed Tables--Year...

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

    Year Constructed > Detailed Tables-Year Constructed Complete Set of 1999 CBECS Detailed Tables Detailed Tables-Year Constructed Table B8. Year Constructed, Number of Buildings...

  7. Supply Forecast and Analysis (SFA)

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

    Matthew Langholtz Science Team Leader Oak Ridge National Laboratory DOE Bioenergy Technologies Office (BETO) 2015 Project Peer Review Supply Forecast and Analysis (SFA) 2 | Bioenergy Technologies Office Goal Statement * Provide timely and credible estimates of feedstock supplies and prices to support - the development of a bioeconomy; feedstock demand analysis of EISA, RFS2, and RPS mandates - the data and analysis of other projects in Analysis and Sustainability, Feedstock Supply and Logistics,

  8. Precision Flow Table | Open Energy Information

    Open Energy Info (EERE)

    Table Jump to: navigation, search Basic Specifications Facility Name Flow Table Overseeing Organization United States Army Corp of Engineers (ERDC) Hydrodynamic Testing Facility...

  9. 1995 CECS C&E Tables

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

    Building Level Intensities (percentile) (6 pages, 39 kb) CONTENTS PAGES Table 10. Electricity Consumption and Expenditure Intensities, 1995 Table 21. Natural Gas Consumption and...

  10. 1995 CECS C&E Tables

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

    and Gross Energy Intensity by Census Region for Sum of Major Fuels, 1995 Table 11. Electricity Consumption and Conditional Energy Intensity by Census Region, 1995 Table 22....

  11. 1995 CECS C&E Tables

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

    and Gross Energy Intensity by Year Constructed for Sum of Major Fuels, 1995 Table 14. Electricity Consumption and Conditional Energy Intensity by Year Constructed, 1995 Table...

  12. 1995 CECS C&E Tables

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

    and Gross Energy Intensity by Building Size for Sum of Major Fuels, 1995 Table13. Electricity Consumption and Conditional Energy Intensity by Building Size, 1995 Table 24....

  13. Commerial Buildings Characteristics, 1995 (Table of Contents...

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

    Number of Buildings and Relative Standard Errors, 1995 Table I.2. Participation in Energy Conservation Programs, Floorspace and Relative Standard Errors, 1995 Table J.1....

  14. Trends in Commercial Buildings--Table

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

    Home > Trends in Commercial Buildings > Energy Consumption - Part 1> Site Energy Consumption Tables Table 1. Total site energy consumption, relative standard errors, and 95%...

  15. 1995 CECS C&E Tables

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

    Category (6 pages, 36 kb) CONTENTS PAGES Table 17. Peak Electricity Demand Category, Number of Buildings, 1995 Table 18. Peak Electricity Demand Category, Floorspace, 1995 These...

  16. Appendix B: Technical Projection Tables, Bioenergy Technologies...

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

    Tables B-2 Last updated: November 2014 Table B-2: Terrestrial Feedstock Supply and Logistics Costs to Supply Feedstock to a Pyrolysis Conversion Process Processing Area Cost...

  17. Annual Energy Outlook (AEO) 2006 - Supplemental Tables - All Tables

    SciTech Connect (OSTI)

    2009-01-18

    Tables describing regional energy consumption and prices by sector; residential, commercial, and industrial demand sector data; transportation demand sector; electricity and renewable fuel; and petroleum, natural gas, and coal data.

  18. Table of tables: A database design tool for SYBASE

    SciTech Connect (OSTI)

    Brown, B.C.; Coulter, K.; Glass, H.D.; Glosson, R.; Hanft, R.W.; Harding, D.J.; Trombly-Freytag, K.; Walbridge, D.G.C.; Wallis, D.B. ); Allen, M.E. )

    1991-01-04

    The Table of Tables' application system captures in a set of SYBASE tables the basic design specification for a database schema. Specification of tables, columns (including the related defaults and rules for the stored values) and keys is provided. The feature which makes this application specifically useful for SYBASE is the ability to automatically generate SYBASE triggers. A description field is provided for each database object. Based on the data stored, SQL scripts for creating complete schema including the tables, their defaults and rules, their indexes, and their SYBASE triggers, are written by TOT. Insert, update and delete triggers are generated from TOT to guarantee integrity of data relations when tables are connected by single column foreign keys. The application is written in SYBASE's APT-SQL and includes a forms based data entry system. Using the features of TOT we can create a complete database schema for which the data integrity specified by our design is guaranteed by the SYBASE triggers generated by TOT. 3 refs.

  19. Review of Wind Energy Forecasting Methods for Modeling Ramping Events

    SciTech Connect (OSTI)

    Wharton, S; Lundquist, J K; Marjanovic, N; Williams, J L; Rhodes, M; Chow, T K; Maxwell, R

    2011-03-28

    Tall onshore wind turbines, with hub heights between 80 m and 100 m, can extract large amounts of energy from the atmosphere since they generally encounter higher wind speeds, but they face challenges given the complexity of boundary layer flows. This complexity of the lowest layers of the atmosphere, where wind turbines reside, has made conventional modeling efforts less than ideal. To meet the nation's goal of increasing wind power into the U.S. electrical grid, the accuracy of wind power forecasts must be improved. In this report, the Lawrence Livermore National Laboratory, in collaboration with the University of Colorado at Boulder, University of California at Berkeley, and Colorado School of Mines, evaluates innovative approaches to forecasting sudden changes in wind speed or 'ramping events' at an onshore, multimegawatt wind farm. The forecast simulations are compared to observations of wind speed and direction from tall meteorological towers and a remote-sensing Sound Detection and Ranging (SODAR) instrument. Ramping events, i.e., sudden increases or decreases in wind speed and hence, power generated by a turbine, are especially problematic for wind farm operators. Sudden changes in wind speed or direction can lead to large power generation differences across a wind farm and are very difficult to predict with current forecasting tools. Here, we quantify the ability of three models, mesoscale WRF, WRF-LES, and PF.WRF, which vary in sophistication and required user expertise, to predict three ramping events at a North American wind farm.

  20. Natural Gas Prices Forecast Comparison--AEO vs. Natural Gas Markets

    SciTech Connect (OSTI)

    Wong-Parodi, Gabrielle; Lekov, Alex; Dale, Larry

    2005-02-09

    This paper evaluates the accuracy of two methods to forecast natural gas prices: using the Energy Information Administration's ''Annual Energy Outlook'' forecasted price (AEO) and the ''Henry Hub'' compared to U.S. Wellhead futures price. A statistical analysis is performed to determine the relative accuracy of the two measures in the recent past. A statistical analysis suggests that the Henry Hub futures price provides a more accurate average forecast of natural gas prices than the AEO. For example, the Henry Hub futures price underestimated the natural gas price by 35 cents per thousand cubic feet (11.5 percent) between 1996 and 2003 and the AEO underestimated by 71 cents per thousand cubic feet (23.4 percent). Upon closer inspection, a liner regression analysis reveals that two distinct time periods exist, the period between 1996 to 1999 and the period between 2000 to 2003. For the time period between 1996 to 1999, AEO showed a weak negative correlation (R-square = 0.19) between forecast price by actual U.S. Wellhead natural gas price versus the Henry Hub with a weak positive correlation (R-square = 0.20) between forecasted price and U.S. Wellhead natural gas price. During the time period between 2000 to 2003, AEO shows a moderate positive correlation (R-square = 0.37) between forecasted natural gas price and U.S. Wellhead natural gas price versus the Henry Hub that show a moderate positive correlation (R-square = 0.36) between forecast price and U.S. Wellhead natural gas price. These results suggest that agencies forecasting natural gas prices should consider incorporating the Henry Hub natural gas futures price into their forecasting models along with the AEO forecast. Our analysis is very preliminary and is based on a very small data set. Naturally the results of the analysis may change, as more data is made available.

  1. Health Care Buildings: Consumption Tables

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

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

  2. table1.4_02

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

    ... products (e.g., crude oil converted to residual and distillate fuel oils) are excluded. ... Notes: To obtain the RSE percentage for any table cell, multiply the cell's corresponding ...

  3. Microsoft Word - table_19.doc

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

    7 Table 19. Natural gas delivered to industrial consumers for the account of others by state, 2010-2014 (volumes in million cubic feet) Alabama 109,031 75.2 117,277 76.5 133,765 ...

  4. Microsoft Word - table_17.doc

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

    4 Table 17. Natural gas delivered to residential consumers for the account of others by state, 2010-2014 (volumes in million cubic feet) Alabama 0 -- 0 -- 0 -- 0 -- 0 -- Alaska 0 ...

  5. ARM - CARES - Tracer Forecast for CARES

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

    CampaignsCarbonaceous Aerosols and Radiative Effects Study (CARES)Tracer Forecast for CARES Related Links CARES Home AAF Home ARM Data Discovery Browse Data Post-Campaign Data Sets Field Updates CARES Wiki Campaign Images Experiment Planning Proposal Abstract and Related Campaigns Science Plan Operations Plan Measurements Forecasts News News & Press Backgrounder (PDF, 1.45MB) G-1 Aircraft Fact Sheet (PDF, 1.3MB) Contacts Rahul Zaveri, Lead Scientist Tracer Forecasts for CARES This webpage

  6. LED Lighting Forecast | Department of Energy

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

    Publications » Market Studies » LED Lighting Forecast LED Lighting Forecast The DOE report Energy Savings Forecast of Solid-State Lighting in General Illumination Applications estimates the energy savings of LED white-light sources over the analysis period of 2013 to 2030. With declining costs and improving performance, LED products have been seeing increased adoption for general illumination applications. This is a positive development in terms of energy consumption, as LEDs use significantly

  7. ARM - Instrument - s-table

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

    govInstrumentss-table Documentation 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 Instrument : Stabilized Platform (S-TABLE) Instrument Categories Ocean Observations For ship-based deployments, some instruments require actively stabilized platforms to compensate for the ship's motion, especially rotations around the long axis of the ship (roll), short axis (pitch), and, for some instruments, vertical axis (yaw).

  8. 2012 NISE Awards Summary Table

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

    Awards » 2012 NISE Summary Table 2012 NISE Awards Summary Table Investigator NERSC repo Hours awarded DOE Office Project Title Gilbert Compo, University of Colorado at Boulder m958 10,000,000 BER Climate Research Ocean-Atmosphere Reanalysis for Climate Applications (OARCA) 1850-2013 Silvia Crivelli, Lawrence Berkeley National Laboratory m1532 1,550,000 BER Biological Systems Science WeFold: A collaborative effort for protein structure prediction Thomas Hamill, National Oceanic & Atmospheric

  9. 2013 NISE Awards Summary Table

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

    Awards » 2013 NISE Summary Table 2013 NISE Awards Summary Table Investigator NERSC repo Hours awarded DOE Office Project Title Katie Antypas, Lawrence Berkeley National Laboratory m1759 250,000 ASCR Applied Mathematical Sciences NERSC Application Readiness for Future Architectures Inez Fung, University of California Berkeley m189 750,000 BER Climate and Environmental Sciences Carbon Data Assimilation with a Coupled Ensemble Kalman Filter Thomas Hamill, National Oceanic & Atmospheric

  10. NREL: Resource Assessment and Forecasting Home Page

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

    are used to plan and develop renewable energy technologies and support climate change research. Learn more about NREL's resource assessment and forecasting research:...

  11. Funding Opportunity Announcement for Wind Forecasting Improvement...

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

    There is no cost to participate and all applicants are encouraged to attend. To join the ... Related Articles Upcoming Funding Opportunity for Wind Forecasting Improvement Project in ...

  12. Module 6 - Metrics, Performance Measurements and Forecasting...

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

    This module reviews metrics such as cost and schedule variance along with cost and schedule performance indices. In addition, this module will outline forecasting tools such as ...

  13. Forecast and Funding Arrangements - Hanford Site

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

    Annual Waste Forecast and Funding Arrangements About Us Hanford Site Solid Waste Acceptance Program What's New Acceptance Criteria Acceptance Process Becoming a new Hanford...

  14. NREL: Resource Assessment and Forecasting - Webmaster

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

    email address: Your message: Send Message Printable Version Resource Assessment & Forecasting Home Capabilities Facilities Working with Us Research Staff Data & Resources Did...

  15. Development and Demonstration of Advanced Forecasting, Power...

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

    and Demonstration of Advanced Forecasting, Power and Environmental Planning and Management Tools and Best Practices 63wateruseoptimizationprojectanlgasper.ppt (7.72 MB) More ...

  16. Sandia National Labs: PCNSC: IBA Table

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

    Departments Radiation, Nano Materials, & Interface Sciences > Radiation & Solid Interactions > Nanomaterials Sciences > Surface & Interface Sciences Semiconductor & Optical Sciences Energy Sciences Small Science Cluster Business Office News Partnering Research Ion Beam Analysis (IBA) Periodic Table (HTML) IBA Table (HTML) | IBA Table (135KB GIF) | IBA Table (1.2MB PDF) | IBA Table (33MB TIF) | Heavy Ion Backscattering Spectrometry (HIBS) | Virtual Lab Tour (6MB) The

  17. Sensing, Measurement, and Forecasting | Grid Modernization | NREL

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

    Sensing, Measurement, and Forecasting NREL measures weather resources and power systems, forecasts renewable resources and grid conditions, and converts measurements into operational intelligence to support a modern grid. Photo of solar resource monitoring equipment Modernizing the grid involves assessing its health in real time, predicting its behavior and potential disruptions, and quickly responding to events-which requires understanding vital parameters throughout the electric

  18. Study forecasts disappearance of conifers due to climate change

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

    Study forecasts disappearance of conifers due to climate change Study forecasts disappearance of conifers due to climate change New results, reported in a paper released today in ...

  19. 915 MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

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

    Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory M Jensen MJ ... Wind Profiler for Cloud Forecasting at Brookhaven National Laboratory M Jensen, ...

  20. Data Collection and Comparison with Forecasted Unit Sales of...

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

    Data Collection and Comparison with Forecasted Unit Sales of Five Lamp Types Data Collection and Comparison with Forecasted Unit Sales of Five Lamp Types PDF icon Data Collection ...

  1. 2011 NISE Awards Summary Table

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

    Awards » 2011 NISE Summary Table 2011 NISE Awards Summary Table Investigator NERSC Repo Hours Awarded DOE Office Project Title Dmitri Babikov, Marquette University m409 1,450,000 BES Chemistry New potential energy surface for ozone molecule Connor Balance, Auburn University m41 600,000 Fusion Energy Hybrid OpenMP/MPI approach to R-matrix scattering Amitava Bhattacharjee, University of New Hampshire m148 1,000,000 Fusion Energy Global Effects on the Dynamics of Plasmoids and Flux Ropes during

  2. Radioactive decay data tables

    SciTech Connect (OSTI)

    Kocher, D.C.

    1981-01-01

    The estimation of radiation dose to man from either external or internal exposure to radionuclides requires a knowledge of the energies and intensities of the atomic and nuclear radiations emitted during the radioactive decay process. The availability of evaluated decay data for the large number of radionuclides of interest is thus of fundamental importance for radiation dosimetry. This handbook contains a compilation of decay data for approximately 500 radionuclides. These data constitute an evaluated data file constructed for use in the radiological assessment activities of the Technology Assessments Section of the Health and Safety Research Division at Oak Ridge National Laboratory. The radionuclides selected for this handbook include those occurring naturally in the environment, those of potential importance in routine or accidental releases from the nuclear fuel cycle, those of current interest in nuclear medicine and fusion reactor technology, and some of those of interest to Committee 2 of the International Commission on Radiological Protection for the estimation of annual limits on intake via inhalation and ingestion for occupationally exposed individuals.

  3. EA-1909: South Table Wind Farm Project, Kimball County, Nebraska

    Broader source: Energy.gov [DOE]

    DOE’s Western Area Power Administration is preparing this EA to evaluate the environmental impacts of interconnecting the proposed South Table Wind Project, which would generate approximately 60 megawatts from about 40 turbines, to Western’s existing Archer-Sidney 115-kV Transmission Line in Kimball County, Nebraska.

  4. Microsoft Word - table_27.doc

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

    8 Table 28. Percent distribution of natural gas delivered to consumers by state, 2014 Alabama 0.8 0.8 2.5 0.6 4.2 Alaska 0.3 0.5 0.1 < 0.4 Arizona 0.6 0.9 0.3 5.8 2.5 Arkansas 0.7 ...

  5. Microsoft Word - table_07.doc

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

    8 Table 7. Supplemental gas supplies by state, 2014 (million cubic feet) Colorado 0 10 0 4,110 4,120 Delaware 0 6 0 0 6 Georgia 0 0 608 26 635 Hawaii 2,733 10 0 0 2,743 Illinois 0 ...

  6. Microsoft Word - table_18.doc

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

    5 Table 18. Natural gas delivered to commercial consumers for the account of others by state, 2010-2014 (volumes in million cubic feet) Alabama 5,494 20.3 5,313 21.1 5,126 23.8 ...

  7. Microsoft Word - table_04.doc

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

    2 Table 4. Offshore gross withdrawals of natural gas by state and the Gulf of Mexico, 2010-2014 (million cubic feet) 2010 Total 234,236 341,365 575,601 1,701,665 598,679 2,300,344 ...

  8. Microsoft Word - table_23.doc

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

    6 Table 23. Average citygate price of natural gas in the United States, 2010- 2014 (dollars per thousand cubic feet) Alabama 6.46 5.80 5.18 4.65 4.93 Alaska 6.67 6.53 6.14 6.02 ...

  9. Microsoft Word - table_13.doc

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

    3 Table 13. Additions to and withdrawals from gas storage by state, 2014 (million cubic feet) Alabama 34,286 28,683 5,603 1,664 1,869 -206 5,397 Alaska 11,675 6,523 5,152 0 0 0 ...

  10. Microsoft Word - table_14.doc

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

    44 Table 14. Underground natural gas storage capacity by state, December 31, 2014 (million cubic feet) Alabama 1 21,950 30,100 0 0 0 1 11,200 13,500 2 33,150 43,600 Alaska 0 0 0 0 ...

  11. 1993 Pacific Northwest Loads and Resources Study, Pacific Northwest Economic and Electricity Use Forecast, Technical Appendix: Volume 1.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    1994-02-01

    This publication documents the load forecast scenarios and assumptions used to prepare BPA`s Whitebook. It is divided into: intoduction, summary of 1993 Whitebook electricity demand forecast, conservation in the load forecast, projection of medium case electricity sales and underlying drivers, residential sector forecast, commercial sector forecast, industrial sector forecast, non-DSI industrial forecast, direct service industry forecast, and irrigation forecast. Four appendices are included: long-term forecasts, LTOUT forecast, rates and fuel price forecasts, and forecast ranges-calculations.

  12. NREL: Resource Assessment and Forecasting - Facilities

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

    The Solar Radiation Research Laboratory gathers solar radiation and meteorological data on South Table Mountain. NREL's Solar Radiation Research Laboratory (SRRL) has been ...

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

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

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

  14. FY 2014 Budget Request Statistical Table | Department of Energy

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

    Statistical Table FY 2014 Budget Request Statistical Table PDF icon Stats Table FY2014.pdf More Documents & Publications FY 2009 Environmental Management Budget Request to Congress ...

  15. FY 2014 Budget Request Summary Table | Department of Energy

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

    PDF icon Summary Table by Appropriations PDF icon Summary Table by Organization More Documents & Publications FY 2014 Budget Request Statistical Table FY 2014 Budget Justification ...

  16. Toward a science of tumor forecasting for clinical oncology

    SciTech Connect (OSTI)

    Yankeelov, Thomas E.; Quaranta, Vito; Evans, Katherine J.; Rericha, Erin C.

    2015-03-15

    We propose that the quantitative cancer biology community makes a concerted effort to apply lessons from weather forecasting to develop an analogous methodology for predicting and evaluating tumor growth and treatment response. Currently, the time course of tumor response is not predicted; instead, response is only assessed post hoc by physical examination or imaging methods. This fundamental practice within clinical oncology limits optimization of a treatment regimen for an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoply of molecularly targeted therapies is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. Furthermore, with a successful methodology toward tumor forecasting, it should be possible to integrate large tumor-specific datasets of varied types and effectively defeat one cancer patient at a time.

  17. Toward a science of tumor forecasting for clinical oncology

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

    Yankeelov, Thomas E.; Quaranta, Vito; Evans, Katherine J.; Rericha, Erin C.

    2015-03-15

    We propose that the quantitative cancer biology community makes a concerted effort to apply lessons from weather forecasting to develop an analogous methodology for predicting and evaluating tumor growth and treatment response. Currently, the time course of tumor response is not predicted; instead, response is only assessed post hoc by physical examination or imaging methods. This fundamental practice within clinical oncology limits optimization of a treatment regimen for an individual patient, as well as to determine in real time whether the choice was in fact appropriate. This is especially frustrating at a time when a panoply of molecularly targeted therapiesmore » is available, and precision genetic or proteomic analyses of tumors are an established reality. By learning from the methods of weather and climate modeling, we submit that the forecasting power of biophysical and biomathematical modeling can be harnessed to hasten the arrival of a field of predictive oncology. Furthermore, with a successful methodology toward tumor forecasting, it should be possible to integrate large tumor-specific datasets of varied types and effectively defeat one cancer patient at a time.« less

  18. CBECS 1992 - Building Characteristics, Detailed Tables

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

    major topics of each table. Directions for calculating an approximate relative standard error (RSE) for each estimate in the tables are presented in Figure A1, "Use of RSE Row...

  19. table3.4_02.xls

    Gasoline and Diesel Fuel Update (EIA)

    ... Notes: To obtain the RSE percentage for any table cell, multiply the cell's corresponding ... were Table 3.4 Number of Establishments by Fuel Consumption, 2002; Level: National Data; ...

  20. TableHC2.7.xls

    Gasoline and Diesel Fuel Update (EIA)

    ... Table HC7.7 Air-Conditioning Usage Indicators by Household Income, 2005 Below Poverty Line ... Table HC7.7 Air-Conditioning Usage Indicators by Household Income, 2005 Below Poverty Line ...

  1. TableHC2.10.xls

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

    ... Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005 Below Poverty Line ... Table HC7.10 Home Appliances Usage Indicators by Household Income, 2005 Below Poverty Line ...

  2. Coal Fired Power Generation Market Forecast | OpenEI Community

    Open Energy Info (EERE)

    Coal Fired Power Generation Market Forecast Home There are currently no posts in this category. Syndicate...

  3. Offshore Lubricants Market Forecast | OpenEI Community

    Open Energy Info (EERE)

    Offshore Lubricants Market Forecast Home There are currently no posts in this category. Syndicate...

  4. Distribution of Wind Power Forecasting Errors from Operational Systems (Presentation)

    SciTech Connect (OSTI)

    Hodge, B. M.; Ela, E.; Milligan, M.

    2011-10-01

    This presentation offers new data and statistical analysis of wind power forecasting errors in operational systems.

  5. Forecast of transportation energy demand through the year 2010

    SciTech Connect (OSTI)

    Mintz, M.M.; Vyas, A.D.

    1991-04-01

    Since 1979, the Center for Transportation Research (CTR) at Argonne National Laboratory (ANL) has produced baseline projections of US transportation activity and energy demand. These projections and the methodologies used to compute them are documented in a series of reports and research papers. As the lastest in this series of projections, this report documents the assumptions, methodologies, and results of the most recent projection -- termed ANL-90N -- and compares those results with other forecasts from the current literature, as well as with the selection of earlier Argonne forecasts. This current forecast may be used as a baseline against which to analyze trends and evaluate existing and proposed energy conservation programs and as an illustration of how the Transportation Energy and Emission Modeling System (TEEMS) works. (TEEMS links disaggregate models to produce an aggregate forecast of transportation activity, energy use, and emissions). This report and the projections it contains were developed for the US Department of Energy's Office of Transportation Technologies (OTT). The projections are not completely comprehensive. Time and modeling effort have been focused on the major energy consumers -- automobiles, trucks, commercial aircraft, rail and waterborne freight carriers, and pipelines. Because buses, rail passengers services, and general aviation consume relatively little energy, they are projected in the aggregate, as other'' modes, and used primarily as scaling factors. These projections are also limited to direct energy consumption. Projections of indirect energy consumption, such as energy consumed in vehicle and equipment manufacturing, infrastructure, fuel refining, etc., were judged outside the scope of this effort. The document is organized into two complementary sections -- one discussing passenger transportation modes, and the other discussing freight transportation modes. 99 refs., 10 figs., 43 tabs.

  6. Text-Alternative Version LED Lighting Forecast

    Office of Energy Efficiency and Renewable Energy (EERE)

    The DOE report Energy Savings Forecast of Solid-State Lighting in General Illumination Applications estimates the energy savings of LED white-light sources over the analysis period of 2013 to 2030....

  7. energy data + forecasting | OpenEI Community

    Open Energy Info (EERE)

    energy data + forecasting Home FRED Description: Free Energy Database Tool on OpenEI This is an open source platform for assisting energy decision makers and policy makers in...

  8. Code Tables | National Nuclear Security Administration | (NNSA)

    National Nuclear Security Administration (NNSA)

    Code Tables U.S. Department of Energy / U.S. Nuclear Regulatory Commission Nuclear Materials Management & Safeguards System Code Tables Action Code The action code identifies the type of activity being reported in a transaction. The Action Code table shows the valid action codes. Nature of Transaction (TI) Code The financial code signifies the nature of the financial or contractual activity that is involved in the transaction. The Nature of Transaction (TI) Code table shows the valid action

  9. SEP Program Transition Tables | Department of Energy

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

    Transition Tables SEP Program Transition Tables The Program Transition Tables provide information concerning the level of effort required to move from a traditional, industrial incentive program to Strategic Energy Management, ISO 50001, or SEP. Both the customers' and utility program administrators' perspectives are considered. Utilities and PAs can use these detailed tables to understand and develop estimates of scope, resources, and realistic implementation timelines. View Program Transition

  10. Nambe Pueblo Water Budget and Forecasting model.

    SciTech Connect (OSTI)

    Brainard, James Robert

    2009-10-01

    This report documents The Nambe Pueblo Water Budget and Water Forecasting model. The model has been constructed using Powersim Studio (PS), a software package designed to investigate complex systems where flows and accumulations are central to the system. Here PS has been used as a platform for modeling various aspects of Nambe Pueblo's current and future water use. The model contains three major components, the Water Forecast Component, Irrigation Scheduling Component, and the Reservoir Model Component. In each of the components, the user can change variables to investigate the impacts of water management scenarios on future water use. The Water Forecast Component includes forecasting for industrial, commercial, and livestock use. Domestic demand is also forecasted based on user specified current population, population growth rates, and per capita water consumption. Irrigation efficiencies are quantified in the Irrigated Agriculture component using critical information concerning diversion rates, acreages, ditch dimensions and seepage rates. Results from this section are used in the Water Demand Forecast, Irrigation Scheduling, and the Reservoir Model components. The Reservoir Component contains two sections, (1) Storage and Inflow Accumulations by Categories and (2) Release, Diversion and Shortages. Results from both sections are derived from the calibrated Nambe Reservoir model where historic, pre-dam or above dam USGS stream flow data is fed into the model and releases are calculated.

  11. Science on the Hill: The forecast calls for flu

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

    The forecast calls for flu The forecast calls for flu Using mathematics, computer programs, statistics and information about how disease develops and spreads, a research team at Los Alamos National Laboratory found a way to forecast the flu season and even next week's sickness trends. January 15, 2016 Forecasting flu A team from Los Alamos has developed a method to predict flu outbreaks based in part on influenza-related searches of Wikipedia. The forecast calls for flu Beyond the familiar flu,

  12. RADIOACTIVE ELEMENTS IN THE STANDARD ATOMIC WEIGHTS TABLE

    SciTech Connect (OSTI)

    Holden, N.E.; Holden, N.; Holden,N.E.

    2011-07-27

    , from which an atomic weight value could be calculated to five or more figure accuracy, without prior knowledge of the sample involved. These elements were again listed in the Atomic Weights Table with no further information, i.e., with no mass number or atomic weight value. For the elements, which have no stable characteristic terrestrial isotopic composition, the data on the half-lives and the relative atomic masses for the nuclides of interest for those elements have been evaluated. The values of the half-lives with their uncertainties are listed in the table. The uncertainties are given for the last digit quoted of the half-life and are given in parentheses. A half-life entry for the Table having a value and an uncertainty of 7 {+-} 3 is listed in the half-life column as 7 (3). The criteria to include data in this Table, is to be the same as it has been for over sixty years. It is the same criteria, which are used for all data that are evaluated for inclusion in the Standard Table of Atomic Weights. If a report of data is published in a peer-reviewed journal, that data is evaluated and considered for inclusion in the appropriate table of the biennial report of the Atomic Weights Commission. As better data becomes available in the future, the information that is contained in either of the Tables of Standard Atomic Weights or in the Table of Radioactive Elements may be modified. It should be noted that the appearance of any datum in the Table of the Radioactive Elements is merely for the purposes of calculating an atomic mass value for any sample of a radioactive material, which might have a variety of isotopic compositions and it has no implication as to the priority for claiming discovery of a given element and is not intended to. The atomic mass values have been taken primarily from the 2003 Atomic Mass Table. Mass values for those radioisotopes that do not appear in the 2003 Atomic mass Table have been taken from preliminary data of the Atomic Mass Data Center

  13. FY 2014 Budget Request Laboratory Table | Department of Energy

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

    Laboratory Table FY 2014 Budget Request Laboratory Table Lab Table FY2014.pdf (235.54 KB) More Documents & Publications FY 2014 Budget Request State Table Fiscal Year 2013 President's Budget Request Fiscal Year 2013 President's

  14. FY 2014 Budget Request State Table | Department of Energy

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

    State Table FY 2014 Budget Request State Table State Table FY2014.pdf (279.32 KB) More Documents & Publications FY 2014 Budget Request Laboratory Table FY 2007 Congressional Budget Request FY 2007 Congressional

  15. 1999 Commercial Building Characteristics--Detailed Tables--Census...

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

    Census Region > Detailed Tables-Census Region Complete Set of 1999 CBECS Detailed Tables Detailed Tables-Census Region Table B3. Census Region, Number of Buildings and Floorspace...

  16. TableBuster V1.0

    Energy Science and Technology Software Center (OSTI)

    2003-06-06

    Brief Description:TableBuster enables Telelogic DOORS users to export tables with split merged cells from Microsoft Word into DOORS. Practical Application: Users of Telelogic DOORS will be more easily able to track and manage requirements that are initally defined in Microsoft Word tables containing split or merged cells. Method of Solution: TableSplitter contains two procedures. The Setup subroutine unlinks all Word fields in the active Word document. It next counts all the tables in the documentmore » and then calls the SplitCells subroutine. SplitCells splits the appropriate cells for each table, so a n row by m column table actually has n by m cells that DOORS can import.« less

  17. 1994 Solid waste forecast container volume summary

    SciTech Connect (OSTI)

    Templeton, K.J.; Clary, J.L.

    1994-09-01

    This report describes a 30-year forecast of the solid waste volumes by container type. The volumes described are low-level mixed waste (LLMW) and transuranic/transuranic mixed (TRU/TRUM) waste. These volumes and their associated container types will be generated or received at the US Department of Energy Hanford Site for storage, treatment, and disposal at Westinghouse Hanford Company`s Solid Waste Operations Complex (SWOC) during a 30-year period from FY 1994 through FY 2023. The forecast data for the 30-year period indicates that approximately 307,150 m{sup 3} of LLMW and TRU/TRUM waste will be managed by the SWOC. The main container type for this waste is 55-gallon drums, which will be used to ship 36% of the LLMW and TRU/TRUM waste. The main waste generator forecasting the use of 55-gallon drums is Past Practice Remediation. This waste will be generated by the Environmental Restoration Program during remediation of Hanford`s past practice sites. Although Past Practice Remediation is the primary generator of 55-gallon drums, most waste generators are planning to ship some percentage of their waste in 55-gallon drums. Long-length equipment containers (LECs) are forecasted to contain 32% of the LLMW and TRU/TRUM waste. The main waste generator forecasting the use of LECs is the Long-Length Equipment waste generator, which is responsible for retrieving contaminated long-length equipment from the tank farms. Boxes are forecasted to contain 21% of the waste. These containers are primarily forecasted for use by the Environmental Restoration Operations--D&D of Surplus Facilities waste generator. This waste generator is responsible for the solid waste generated during decontamination and decommissioning (D&D) of the facilities currently on the Surplus Facilities Program Plan. The remaining LLMW and TRU/TRUM waste volume is planned to be shipped in casks and other miscellaneous containers.

  18. 1999 Commercial Buildings Energy Consumption Survey Detailed Tables

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

    Consumption and Expenditures Tables Table C1. Total Energy Consumption by Major Fuel ............................................... 124 Table C2. Total Energy Expenditures by Major Fuel................................................ 130 Table C3. Consumption for Sum of Major Fuels ...................................................... 135 Table C4. Expenditures for Sum of Major Fuels....................................................... 140 Table C5. Consumption and Gross Energy Intensity by

  19. Table

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

    5.4 from (1991AJ01): Energy levels of 15 N a E x J ; T m or Decay Reactions (MeV keV) c.m. (keV) 0 1 2 - ; 1 2 - stable 3, 4, 5, 6, 13, 14, 16, 17, 18, 19, 20, 24, 25,...

  20. Table

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

    from (2012KE01): Energy Levels of 11 Li E x (MeV ± keV) J π ; T T 1 2 or Γ Decay Reactions g.s. 3 2 - ; 5 2 T 1 2 = 8.75 ± 0.14 ms β - 1, 2, 4, 5, 6, 8, 9 1.220 ± 40 Γ = 0.53 ± 0.15 MeV n 2, 6, 7, 9, 10 2.420 ± 50 Γ = 1.26 ± 0.30 MeV n 2, 4, 6, 7, 9, 10 3.700 ± 130 Γ < 200 keV n 7 4.860 ± 60 Γ < 100 keV n 2, 4, 9 6.230 ± 60 Γ < 100 keV n 2, 4, 9 11.300 n 2 1

  1. Table

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

    4 from (2012KE01): Energy levels of 11 Be E x (MeV ± keV) J π ; T T 1 2 or Γ c.m. (keV) Decay Reactions 0 1 2 + ; 3 2 T 1 2 = 13.76 ± 0.07 s β - 1, 3, 4, 5, 6, 8, 9, 10, 12, 14, 16, 17, 19, 23, 24, 25, 26, 27, 28, 30, 31, 32 0.32004 ± 0.1 1 2 - T 1 2 = 115 ± 10 fs γ 4, 5, 6, 8, 9, 10, 14, 15, 16, 17, 19, 21, 22, 23, 26, 28, 29, 30, 33 1.783 ± 4 5 2 + Γ = 100 ± 10 n 4, 5, 6, 9, 10, 14, 23, 26, 28 2.654 ± 10 3 2 - a 206 ± 8 n 5, 6, 9, 10, 15, 16, 21, 22, 23, 28, 29 3.40 ± 6 ( 3 2 - ,

  2. Table

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

    8 from (2012KE01): Energy levels of 11 B E x J π ; T Γ cm (keV) Decay Reactions (MeV ± keV) 0 3 2 - ; 1 2 stable 2, 3, 7, 8, 11, 15, 16, 17, 18, 19, 22, 26, 27, 28, 29, 30, 32, 33, 34, 35, 36, 37, 39, 40, 42, 44, 45, 46, 47, 48, 49, 50, 51, 53, 54, 55, 56, 57, 58, 59, 60, 61, 63, 67, 68, 69, 70, 71, 72, 73, 74 2.124693 ± 0.027 1 2 - 0.117 ± 0.004 eV γ 2, 7, 8, 11, 15, 16, 17, 18, 19, 26, 27, 28, 30, 32, 33, 35, 36, 37, 39, 40, 42, 44, 51, 53, 54, 55, 56, 57, 58, 59, 60, 61, 63, 67, 68, 69,

  3. Table

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

    38 from (2012KE01): Energy levels of 11 C a E x in 11 C J π ; T T 1 2 or Γ cm Decay Reactions (MeV ± keV) 0 3 2 - ; 1 2 T 1 2 = 20.364 ± 0.014 min β + 1, 2, 6, 7, 10, 16, 17, 18, 19, 21, 22, 23, 24, 25, 26, 27, 28, 30, 31, 32, 33, 34, 35, 37, 38, 39, 40, 41, 43, 44 2.0000 ± 0.4 1 2 - T 1 2 = 7.1 ± 0.5 fs γ 2, 3, 6, 7, 10, 16, 17, 18, 19, 21, 22, 26, 28, 30, 31, 32, 33, 38, 39, 44 4.3188 ± 1.2 5 2 - < 8.3 fs γ 2, 3, 6, 7, 10, 16, 17, 19, 21, 22, 26, 28, 30, 31, 34, 38, 39, 44 4.8042

  4. Table

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

    5 from (2012KE01): Energy levels of 11 N E res (MeV ± keV) E x (MeV ± keV) J π ; T Γ (keV) Decay Reactions 1.49 ± 60 0 1 2 + ; 3 2 830 ± 30 p 1, 2, 3, 6 2.22 ± 30 0.73 ± 70 1 2 - 600 ± 100 p 1, 2, 3, 5, 6 3.06 ± 80 (1.57 ± 80) < 100 p 3 3.69 ± 30 2.20 ± 70 5 2 + 540 ± 40 p 1, 3, 5, 6 4.35 ± 30 2.86 ± 70 3 2 - 340 ± 40 p 1, 3, 5, 6 5.12 ± 80 (3.63 ± 100) ( 5 2 - ) < 220 p 5 5.91 ± 30 4.42 ± 70 ( 5 2 - ) p 3, 5, 6 6.57 ± 100 5.08 ± 120 ( 3 2 - ) 100 ± 60 p 3, 6 1

  5. Table

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

    6.13 from (1993TI07): Energy Levels of 16 O a E x (MeV ± keV) J π ; T K π Γ c.m. or τ m (keV) Decay Reactions 0 0 + ; 0 stable 5, 7, 11, 12, 13, 14, 15, 16, 17, 18, 19, 22, 23, 24, 30, 32, 33, 34, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82 6.0494 ± 1.0 0 + ; 0 0 + τ m = 96 ± 7 psec π 5, 7, 11, 12, 13, 15, 17, 19, 21, 23, 30, 32, 33, 34, 38, 39, 43, 44,

  6. Table

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

    transitions in A 18-19 nuclei a Nucleus E xi E xf J i J f b Mult. S (MeV) (eV) (W.u.) 18 O c 1.98 0 2 + 0 + (2.35 0.06) 10 -4 E2 3.32 ...

  7. Table

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

    - 17 a Nucleus E xi E xf J i (T i ) J f (T f ) (eV) Branching ratio Mult. S (W.u.) (MeV) (%) 16 N b 0.12 0 0 - (1) 2 - (1) (8.7 0.1) 10 -11 100 E2...

  8. Table

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

    transitions in A 5 - 10 a Nucleus E xi E xf (MeV) J i J f b (eV) Mult. S (W.u.) 5 He 16.75 0 3 2 + 3 2 - 2.1 0.4 E1 (2.3 0.4) 10 -3 5 Li...

  9. Table

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

    transitions in A 11 - 12 a Nucleus E xi E xf J i J f b Mult. S (MeV) (eV) (W.u.) 11 Be 0.32 0 1 2 - 1 2 + (3.97 0.36) 10 -3 E1 0.360...

  10. Table

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

    transitions in A 20 nuclei a Nucleus E xi E xf J i J f b Mult. S (MeV) (eV) (W.u.) 20 O c 1.67 0 2 + 0 + (6.28 0.24) 10 -5 E2 1.80 ...