National Library of Energy BETA

Sample records for interindustry forecasting project

  1. Solar Forecast Improvement Project | Department of Energy

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

    Solar Forecast Improvement Project Solar Forecast Improvement Project NOAA.png 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 accurate methods for solar forecasts using their state-of-the-art weather models. APPROACH NOAA solar.png SFIP has three main goals: 1) to develop solar forecasting metrics tailored to the utility sector; 2) to improve solar

  2. 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

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

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

    Influencing Technological Progress in Solar Energy Project Profile: Forecasting and ... energy technologies based on estimates of future rates of progress and adoption. ...

  4. Upcoming Funding Opportunity for Wind Forecasting Improvement Project in

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

    Complex Terrain | Department of Energy Wind Forecasting Improvement Project in Complex Terrain Upcoming Funding Opportunity for Wind Forecasting Improvement Project in Complex Terrain February 12, 2014 - 10:47am Addthis On February 11, 2014 the Wind Program announced a Notice of Intent to issue a funding opportunity entitled "Wind Forecasting Improvement Project in Complex Terrain." By researching the physical processes that take place in complex terrain, this funding would improve

  5. Funding Opportunity Announcement for Wind Forecasting Improvement Project

    Office of Environmental Management (EM)

    in Complex Terrain | Department of Energy Funding Opportunity Announcement for Wind Forecasting Improvement Project in Complex Terrain Funding Opportunity Announcement for Wind Forecasting Improvement Project in Complex Terrain April 4, 2014 - 9:47am Addthis On April 4, 2014 the U.S. Department of Energy announced a $2.5 million funding opportunity entitled "Wind Forecasting Improvement Project in Complex Terrain." By researching the physical processes that take place in complex

  6. The Wind Forecast Improvement Project (WFIP): A Public/Private...

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

    research project whose overarching goals are to improve the accuracy of short-term wind energy forecasts, and to demonstrate the economic value of these improvements. WFIP Round...

  7. The Wind Forecast Improvement Project (WFIP): A Public-Private Partnership Addressing Wind Energy Forecast Needs

    SciTech Connect (OSTI)

    Wilczak, J. M.; Finley, Cathy; Freedman, Jeff; Cline, Joel; Bianco, L.; Olson, J.; Djalaova, I.; Sheridan, L.; Ahlstrom, M.; Manobianco, J.; Zack, J.; Carley, J.; Benjamin, S.; Coulter, R. L.; Berg, Larry K.; Mirocha, Jeff D.; Clawson, K.; Natenberg, E.; Marquis, M.

    2015-10-11

    The Wind Forecast Improvement Project (WFIP) is a public-private research program, the goals of which are to improve the accuracy of short-term (0-6 hr) wind power forecasts for the wind energy industry and then to quantify the economic savings that accrue from more efficient integration of wind energy into the electrical grid. WFIP was sponsored by the U.S. Department of Energy (DOE), with partners that include the National Oceanic and Atmospheric Administration (NOAA), private forecasting companies (WindLogics and AWS Truepower), DOE national laboratories, grid operators, and universities. WFIP employed two avenues for improving wind power forecasts: first, through the collection of special observations to be assimilated into forecast models to improve model initial conditions; and second, by upgrading NWP forecast models and ensembles. The new observations were collected during concurrent year-long field campaigns in two high wind energy resource areas of the U.S. (the upper Great Plains, and Texas), and included 12 wind profiling radars, 12 sodars, 184 instrumented tall towers and over 400 nacelle anemometers (provided by private industry), lidar, and several surface flux stations. Results demonstrate that a substantial improvement of up to 14% relative reduction in power root mean square error (RMSE) was achieved from the combination of improved NOAA numerical weather prediction (NWP) models and assimilation of the new observations. Data denial experiments run over select periods of time demonstrate that up to a 6% relative improvement came from the new observations. The use of ensemble forecasts produced even larger forecast improvements. Based on the success of WFIP, DOE is planning follow-on field programs.

  8. The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership

    Energy Savers [EERE]

    for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations | Department of Energy 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 Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations The Wind Forecast Improvement

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

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

    Department of Energy PDF icon Wind Forecast Improvement Project Southern Study Area Final Report.pdf More Documents & Publications QER - Comment of Edison Electric Institute (EEI) 1 QER - Comment of Canadian Hydropower Association QER - Comment of Edison Electric Institute (EEI) 2

  10. 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 Southern Study Area, Final Report

    SciTech Connect (OSTI)

    Freedman, Jeffrey M.; Manobianco, John; Schroeder, John; Ancell, Brian; Brewster, Keith; Basu, Sukanta; Banunarayanan, Venkat; Hodge, Bri-Mathias; Flores, Isabel

    2014-04-30

    This Final Report presents a comprehensive description, findings, and conclusions for the Wind Forecast Improvement Project (WFIP) -- Southern Study Area (SSA) work led by AWS Truepower (AWST). This multi-year effort, sponsored by the Department of Energy (DOE) and National Oceanographic and Atmospheric Administration (NOAA), focused on improving short-term (15-minute - 6 hour) wind power production forecasts through the deployment of an enhanced observation network of surface and remote sensing instrumentation and the use of a state-of-the-art forecast modeling system. Key findings from the SSA modeling and forecast effort include: 1. The AWST WFIP modeling system produced an overall 10 - 20% improvement in wind power production forecasts over the existing Baseline system, especially during the first three forecast hours; 2. Improvements in ramp forecast skill, particularly for larger up and down ramps; 3. The AWST WFIP data denial experiments showed mixed results in the forecasts incorporating the experimental network instrumentation; however, ramp forecasts showed significant benefit from the additional observations, indicating that the enhanced observations were key to the model systems’ ability to capture phenomena responsible for producing large short-term excursions in power production; 4. The OU CAPS ARPS simulations showed that the additional WFIP instrument data had a small impact on their 3-km forecasts that lasted for the first 5-6 hours, and increasing the vertical model resolution in the boundary layer had a greater impact, also in the first 5 hours; and 5. The TTU simulations were inconclusive as to which assimilation scheme (3DVAR versus EnKF) provided better forecasts, and the additional observations resulted in some improvement to the forecasts in the first 1 - 3 hours.

  11. Waste generation forecast for DOE-ORO`s Environmental Restoration OR-1 Project: FY 1995-FY 2002, September 1994 revision

    SciTech Connect (OSTI)

    Not Available

    1994-12-01

    A comprehensive waste-forecasting task was initiated in FY 1991 to provide a consistent, documented estimate of the volumes of waste expected to be generated as a result of U.S. Department of Energy-Oak Ridge Operations (DOE-ORO) Environmental Restoration (ER) OR-1 Project activities. Continual changes in the scope and schedules for remedial action (RA) and decontamination and decommissioning (D&D) activities have required that an integrated data base system be developed that can be easily revised to keep pace with changes and provide appropriate tabular and graphical output. The output can then be analyzed and used to drive planning assumptions for treatment, storage, and disposal (TSD) facilities. The results of this forecasting effort and a description of the data base developed to support it are provided herein. The initial waste-generation forecast results were compiled in November 1991. Since the initial forecast report, the forecast data have been revised annually. This report reflects revisions as of September 1994.

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

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

    Funding Opportunity Announcement for Wind Forecasting Improvement Project in Complex Terrain Funding Opportunity Announcement for Wind Forecasting Improvement Project in Complex...

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

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

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

  14. Energy consumption and expenditure projections by population group on the basis of the annual energy outlook 1999 forecast

    SciTech Connect (OSTI)

    Poyer, D.A.; Balsley, J.H.

    2000-01-07

    This report presents an analysis of the relative impact of the base-case scenario used in Annual Energy Outlook 1999 on different population groups. Projections of energy consumption and expenditures, as well as energy expenditure as a share of income, from 1996 to 2020 are given. The projected consumption of electricty, natural gas, distillate fuel, and liquefied petroleum gas during this period is also reported for each population group. In addition, this report compares the findings of the Annual Energy Outlook 1999 report with the 1998 report. Changes in certain indicators and information affect energy use forecasts, and these effects are analyzed and discussed.

  15. 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...

  16. Wind Energy Management System EMS Integration Project: Incorporating Wind Generation and Load Forecast Uncertainties into Power Grid Operations

    SciTech Connect (OSTI)

    Makarov, Yuri V.; Huang, Zhenyu; Etingov, Pavel V.; Ma, Jian; Guttromson, Ross T.; Subbarao, Krishnappa; Chakrabarti, Bhujanga B.

    2010-01-01

    The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind and solar power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation), and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind/solar forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. To improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter unique features make this work a significant step forward toward the objective of incorporating of wind, solar, load, and other uncertainties into power system operations. Currently, uncertainties associated with wind and load forecasts, as well as uncertainties associated with random generator outages and unexpected disconnection of supply lines, are not taken into account in power grid operation. Thus, operators have little means to weigh the likelihood and magnitude of upcoming events of power imbalance. In this project, funded by the U.S. Department of Energy (DOE), a framework has been developed for incorporating uncertainties associated with wind and load forecast errors, unpredicted ramps, and forced generation disconnections into the energy management system (EMS) as well as generation dispatch and commitment applications. A new approach to evaluate the uncertainty ranges for the required generation performance envelope including balancing capacity, ramping capability, and ramp duration has been proposed. The approach includes three stages: forecast and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence levels. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis, incorporating all sources of uncertainties of both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures) nature. A new method called the “flying brick” technique has been developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation algorithm has been developed to validate the accuracy of the confidence intervals.

  17. Solar Forecasting | Department of Energy

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

    Systems Integration » Solar Forecasting Solar Forecasting 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. solar energy plants. Part of the SunShot Systems Integration efforts, the Solar Forecasting projects will allow power system operators to integrate more solar energy into the electricity grid, and ensure the economic and reliable delivery of

  18. Forecasting Flu

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

    Forecasting Flu March 6, 2016 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 Valle and her team from Los Alamos National Laboratory have developed a global disease-forecasting system that will improve the way we respond to epidemics. Using this model, individuals and public health officials can monitor

  19. RACORO Forecasting

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

    Hartsock CIMMS, University of Oklahoma  ARM AAF Wiki page  Weather Briefings  Observed Weather  Cloud forecasting models  BUFKIT forecast soundings + guidance from Norman NWS enhanced pages and discussions NAM-WRF updated twice/day (12Z and 00Z) Forecast out to 84-hours RUC (updated every 3 hours) Operational RUC forecast only goes out 12 hours (developmental out 24 hours)

  20. Waste Generation Forecast for DOE-ORO`s Environmental Restoration OR-1 Project: FY 1994--FY 2001. Environmental Restoration Program, September 1993 Revision

    SciTech Connect (OSTI)

    Not Available

    1993-12-01

    This Waste Generation Forecast for DOE-ORO`s Environmental Restoration OR-1 Project. FY 1994--FY 2001 is the third in a series of documents that report current estimates of the waste volumes expected to be generated as a result of Environmental Restoration activities at Department of Energy, Oak Ridge Operations Office (DOE-ORO), sites. Considered in the scope of this document are volumes of waste expected to be generated as a result of remedial action and decontamination and decommissioning activities taking place at these sites. Sites contributing to the total estimates make up the DOE-ORO Environmental Restoration OR-1 Project: the Oak Ridge K-25 Site, the Oak Ridge National Laboratory, the Y-12 Plant, the Paducah Gaseous Diffusion Plant, the Portsmouth Gaseous Diffusion Plant, and the off-site contaminated areas adjacent to the Oak Ridge facilities (collectively referred to as the Oak Ridge Reservation Off-Site area). Estimates are available for the entire fife of all waste generating activities. This document summarizes waste estimates forecasted for the 8-year period of FY 1994-FY 2001. Updates with varying degrees of change are expected throughout the refinement of restoration strategies currently in progress at each of the sites. Waste forecast data are relatively fluid, and this document represents remediation plans only as reported through September 1993.

  1. 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 individual wind plant and at the system-wide aggregate level over the one year study period showed that the research weather model-based power forecasts (all types) had lower overall error rates than the current operational weather model-based power forecasts, both at the individual wind plant level and at the system aggregate level. The bulk error statistics of the various model-based power forecasts were also calculated by season and model runtime/forecast hour as power system operations are more sensitive to wind energy forecast errors during certain times of year and certain times of day. The results showed that there were significant differences in seasonal forecast errors between the various model-based power forecasts. The results from the analysis of the various wind power forecast errors by model runtime and forecast hour showed that the forecast errors were largest during the times of day that have increased significance to power system operators (the overnight hours and the morning/evening boundary layer transition periods), but the research weather model-based power forecasts showed improvement over the operational weather model-based power forecasts at these times.

  2. Acquisition Forecast

    Broader source: Energy.gov [DOE]

    It is the policy of the Department of Energy (DOE) and the National Nuclear Security Administration (NNSA) to provide timely information to the public regarding DOE/NNSA’s forecast of future prime contracting opportunities and subcontracting opportunities which are available via the Department’s major site and facilities management contractors.

  3. ANL Software Improves Wind Power Forecasting | Department of Energy

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

    ANL Software Improves Wind Power Forecasting ANL Software Improves Wind Power Forecasting May 1, 2012 - 3:19pm Addthis This is an excerpt from the Second Quarter 2012 edition of the Wind Program R&D Newsletter. Since 2008, Argonne National Laboratory and INESC TEC (formerly INESC Porto) have conducted a research project to improve wind power forecasting and better use of forecasting in electricity markets. One of the main results from the project is ARGUS PRIMA (PRediction Intelligent

  4. Forecasting Water Quality & Biodiversity

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

    Forecasting Water Quality & Biodiversity March 25, 2015 Cross-cutting Sustainability Platform Review Principle Investigator: Dr. Henriette I. Jager Organization: Oak Ridge National Laboratory This presentation does not contain any proprietary, confidential, or otherwise restricted information 2015 DOE Bioenergy Technologies Office (BETO) Project Peer Review Goal Statement Addresses the following MYPP BETO goals:  Advance scientific methods and models for measuring and understanding

  5. 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,

  6. Today's Forecast: Improved Wind Predictions | Department of Energy

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

    Today's Forecast: Improved Wind Predictions Today's Forecast: Improved Wind Predictions July 20, 2011 - 6:30pm Addthis Stan Calvert Wind Systems Integration Team Lead, Wind & Water Power Program What does this project do? It will increase the accuracy of weather forecast models for predicting substantial changes in winds at heights important for wind energy up to six hours in advance, allowing grid operators to predict expected wind power production. Accurate weather forecasts are critical

  7. Improving the Accuracy of Solar Forecasting Funding Opportunity...

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

    Opportunity, DOE is funding solar projects that are helping utilities, grid operators, solar power plant owners, and other stakeholders better forecast when, where, and how much...

  8. Contract/Project Management

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

    1 ContractProject Management Primary Performance Metrics FY 2011 Target FY 2011 Forecast FY 2011 Pre- & Post-CAP Forecast Comment 1a. Capital Asset Line Item Projects: ...

  9. EIA projections of coal supply and demand

    SciTech Connect (OSTI)

    Klein, D.E.

    1989-10-23

    Contents of this report include: EIA projections of coal supply and demand which covers forecasted coal supply and transportation, forecasted coal demand by consuming sector, and forecasted coal demand by the electric utility sector; and policy discussion.

  10. 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...

  11. 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.

  12. NREL: Transmission Grid Integration - Forecasting

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

    generation output by using forecasts that incorporate meteorological data to predict production. Such systems typically provide forecasts at a number of timescales, ranging from...

  13. Improving the Accuracy of Solar Forecasting Funding Opportunity

    Broader source: Energy.gov [DOE]

    Through the Improving the Accuracy of Solar Forecasting Funding Opportunity, DOE is funding solar projects that are helping utilities, grid operators, solar power plant owners, and other...

  14. 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 ...

  15. Issues in midterm analysis and forecasting 1998

    SciTech Connect (OSTI)

    1998-07-01

    Issues in Midterm Analysis and Forecasting 1998 (Issues) presents a series of nine papers covering topics in analysis and modeling that underlie the Annual Energy Outlook 1998 (AEO98), as well as other significant issues in midterm energy markets. AEO98, DOE/EIA-0383(98), published in December 1997, presents national forecasts of energy production, demand, imports, and prices through the year 2020 for five cases -- a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. The forecasts were prepared by the Energy Information Administration (EIA), using EIA`s National Energy Modeling System (NEMS). The papers included in Issues describe underlying analyses for the projections in AEO98 and the forthcoming Annual Energy Outlook 1999 and for other products of EIA`s Office of Integrated Analysis and Forecasting. Their purpose is to provide public access to analytical work done in preparation for the midterm projections and other unpublished analyses. Specific topics were chosen for their relevance to current energy issues or to highlight modeling activities in NEMS. 59 figs., 44 tabs.

  16. The forecast calls for flu

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

    Laboratory found a way to forecast the flu season and even next week's sickness trends. ... Laboratory found a way to forecast the flu season and even next week's sickness trends. ...

  17. Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System

    Office of Environmental Management (EM)

    Operations | Department of Energy Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations Clean Power Research logo.jpg This project will address the need for a more accurate approach to forecasting net utility load by taking into consideration the contribution of customer-sited PV energy generation. Tasks within the project are designed to integrate novel PV power

  18. probabilistic energy production forecasts

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

    probabilistic energy production forecasts - Sandia Energy Energy Search Icon Sandia Home Locations Contact Us Employee Locator Energy & Climate Secure & Sustainable Energy Future Stationary Power Energy Conversion Efficiency Solar Energy Wind Energy Water Power Supercritical CO2 Geothermal Natural Gas Safety, Security & Resilience of the Energy Infrastructure Energy Storage Nuclear Power & Engineering Grid Modernization Battery Testing Nuclear Fuel Cycle Defense Waste Management

  19. Contract/Project Management

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

    1 ContractProject Management Primary Performance Metrics FY 2011 Target FY 2011 Actual & Forecast FY 2011 Pre- & Post-CAP Comment 1a. Capital Asset Line Item Projects: ...

  20. 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)

  1. 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:...

  2. 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.

  3. Using Wikipedia to forecast diseases

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

    based on today's forecast." Del Valle and her team were able to successfully monitor influenza in the United States, Poland, Japan and Thailand, dengue fever in Brazil and...

  4. Watt-Sun: A Multi-Scale, Multi-Model, Machine-Learning Solar Forecasting

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

    Technology | Department of Energy Watt-Sun: A Multi-Scale, Multi-Model, Machine-Learning Solar Forecasting Technology Watt-Sun: A Multi-Scale, Multi-Model, Machine-Learning Solar Forecasting Technology IBM logo.png As part of this project, new solar forecasting technology will be developed that leverages big data processing, deep machine learning, and cloud modeling integrated in a universal platform with an open architecture. Similar to the Watson computer system, this proposed technology

  5. 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.

  6. 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:...

  7. 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

  8. 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.

  9. 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.

  10. 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.

  11. Integration of Behind-the-Meter PV Fleet Forecasts into Utility...

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

    Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations Clean Power Research logo.jpg This project will address the need for a more accurate approach ...

  12. CCPP-ARM Parameterization Testbed Model Forecast Data

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

    Klein, Stephen

    2008-01-15

    Dataset contains the NCAR CAM3 (Collins et al., 2004) and GFDL AM2 (GFDL GAMDT, 2004) forecast data at locations close to the ARM research sites. These data are generated from a series of multi-day forecasts in which both CAM3 and AM2 are initialized at 00Z every day with the ECMWF reanalysis data (ERA-40), for the year 1997 and 2000 and initialized with both the NASA DAO Reanalyses and the NCEP GDAS data for the year 2004. The DOE CCPP-ARM Parameterization Testbed (CAPT) project assesses climate models using numerical weather prediction techniques in conjunction with high quality field measurements (e.g. ARM data).

  13. CCPP-ARM Parameterization Testbed Model Forecast Data

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

    Klein, Stephen

    Dataset contains the NCAR CAM3 (Collins et al., 2004) and GFDL AM2 (GFDL GAMDT, 2004) forecast data at locations close to the ARM research sites. These data are generated from a series of multi-day forecasts in which both CAM3 and AM2 are initialized at 00Z every day with the ECMWF reanalysis data (ERA-40), for the year 1997 and 2000 and initialized with both the NASA DAO Reanalyses and the NCEP GDAS data for the year 2004. The DOE CCPP-ARM Parameterization Testbed (CAPT) project assesses climate models using numerical weather prediction techniques in conjunction with high quality field measurements (e.g. ARM data).

  14. Projecting

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

    Projecting the scale of the pipeline network for CO2-EOR and its implications for CCS ... for CO 2 -EOR and CO 2 transportation for CCS assuming a carbon price are discussed. ...

  15. Contract/Project Management

    Office of Environmental Management (EM)

    Second Quarter Overall Contract and Project Management Improvement Performance Metrics and Targets 1 Contract/Project Management Primary Performance Metrics FY 2011 Target FY 2011 Forecast FY 2011 Pre- & Post-CAP Forecast Comment 1a. Capital Asset Line Item Projects: (Pre-RCA/CAP) Projects completed within 110% of CD-2 TPC. 1b. Capital Asset Line Item Projects: (Post-RCA/CAP) 90% Line Item 84% Line Item 78% Pre-CAP 100% Post-CAP This is based on a 3-year rolling average (FY09 to FY11). TPC

  16. Contract/Project Management

    Office of Environmental Management (EM)

    Third Quarter Overall Contract and Project Management Improvement Performance Metrics and Targets 1 Contract/Project Management Primary Performance Metrics FY 2011 Target FY 2011 Forecast FY 2011 Pre- & Post-CAP Forecast Comment 1a. Capital Asset Line Item Projects: (Pre-RCA/CAP) Projects completed within 110% of CD-2 TPC. 1b. Capital Asset Line Item Projects: (Post-RCA/CAP) 90% Line Item 84% Line Item 78% Pre-CAP 100% Post-CAP This is based on a 3-year rolling average (FY09 to FY11). TPC is

  17. Contract/Project Management

    Office of Environmental Management (EM)

    First Quarter Overall Contract and Project Management Improvement Performance Metrics and Targets 1 Contract/Project Management Performance Metric FY 2012 Target FY 2012 Forecast FY 2012 Pre- & Post-CAP Forecast Comment Capital Asset Project Success: Complete 90% of capital asset projects at original scope and within 110% of CD-2 TPC. 90%* 84% Construction 83% Cleanup 85% 77% Pre-CAP 86% Post- CAP This is based on a 3- year rolling average (FY10 to FY12). TPC is Total Project Cost.

  18. Contract/Project Management

    Office of Environmental Management (EM)

    Second Quarter Overall Contract and Project Management Improvement Performance Metrics and Targets 1 Contract/Project Management Performance Metric FY 2012 Target FY 2012 Forecast FY 2012 Pre- & Post-CAP Forecast Comment Capital Asset Project Success: Complete 90% of capital asset projects at original scope and within 110% of CD-2 TPC. 90%* 88% Construction 87% Cleanup 89% 77% Pre-CAP 92% Post- CAP This is based on a 3- year rolling average (FY10 to FY12). TPC is Total Project Cost.

  19. Contract/Project Management

    Office of Environmental Management (EM)

    Third Quarter Overall Contract and Project Management Improvement Performance Metrics and Targets 1 Contract/Project Management Performance Metric FY 2012 Target FY 2012 Forecast FY 2012 Pre- & Post-CAP Forecast Comment Capital Asset Project Success: Complete 90% of capital asset projects at original scope and within 110% of CD-2 TPC. 90%* 87% Construction 87% Cleanup 87% 77% Pre-CAP 90% Post- CAP This is based on a 3- year rolling average (FY10 to FY12). TPC is Total Project Cost.

  20. Perspectives on Project Finance

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

    Project Finance July 29 2014 Project Company (Borrower) Off-take Agreements Feedstock Agreements O&M Agreement EPC Contract (construct) Technology License Agreements Sponsor's Equity Project Level Equity Investors Senior Project Debt Providers Equity Investors Typical Project Finance Structure 2 SOUND PROJECT ECONOMICS Leads to Adequate Debt Service Coverage And Acceptable Equity Returns Market Risk Assessment Competitive positioning. Supply / demand forecasts. Competing suppliers.

  1. 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

  2. Voluntary Green Power Market Forecast through 2015

    SciTech Connect (OSTI)

    Bird, L.; Holt, E.; Sumner, J.; Kreycik, C.

    2010-05-01

    Various factors influence the development of the voluntary 'green' power market--the market in which consumers purchase or produce power from non-polluting, renewable energy sources. These factors include climate policies, renewable portfolio standards (RPS), renewable energy prices, consumers' interest in purchasing green power, and utilities' interest in promoting existing programs and in offering new green options. This report presents estimates of voluntary market demand for green power through 2015 that were made using historical data and three scenarios: low-growth, high-growth, and negative-policy impacts. The resulting forecast projects the total voluntary demand for renewable energy in 2015 to range from 63 million MWh annually in the low case scenario to 157 million MWh annually in the high case scenario, representing an approximately 2.5-fold difference. The negative-policy impacts scenario reflects a market size of 24 million MWh. Several key uncertainties affect the results of this forecast, including uncertainties related to growth assumptions, the impacts that policy may have on the market, the price and competitiveness of renewable generation, and the level of interest that utilities have in offering and promoting green power products.

  3. Assessment of the possibility of forecasting future natural gas curtailments

    SciTech Connect (OSTI)

    Lemont, S.

    1980-01-01

    This study provides a preliminary assessment of the potential for determining probabilities of future natural-gas-supply interruptions by combining long-range weather forecasts and natural-gas supply/demand projections. An illustrative example which measures the probability of occurrence of heating-season natural-gas curtailments for industrial users in the southeastern US is analyzed. Based on the information on existing long-range weather forecasting techniques and natural gas supply/demand projections enumerated above, especially the high uncertainties involved in weather forecasting and the unavailability of adequate, reliable natural-gas projections that take account of seasonal weather variations and uncertainties in the nation's energy-economic system, it must be concluded that there is little possibility, at the present time, of combining the two to yield useful, believable probabilities of heating-season gas curtailments in a form useful for corporate and government decision makers and planners. Possible remedial actions are suggested that might render such data more useful for the desired purpose in the future. The task may simply require the adequate incorporation of uncertainty and seasonal weather trends into modeling systems and the courage to report projected data, so that realistic natural gas supply/demand scenarios and the probabilities of their occurrence will be available to decision makers during a time when such information is greatly needed.

  4. Contract/Project Management

    Office of Environmental Management (EM)

    Second Quarter Overall Root Cause Analysis (RCA)/Corrective Action Plan (CAP) Performance Metrics 1 Contract/Project Management Performance Metric FY 2013 Target FY 2013 Forecast FY 2013 Pre- & Post-CAP* Forecast Comment Capital Asset Project Success: Complete 90% of capital asset projects at original scope and within 110% of CD-2 TPC. 90%* 83% Construction 85% Cleanup 80% 70% Pre-CAP 84% Post-CAP This is based on a 3- year rolling average (FY11 to FY13). TPC is Total Project Cost.

  5. Contract/Project Management

    Office of Environmental Management (EM)

    3 Third Quarter Overall Root Cause Analysis (RCA)/Corrective Action Plan (CAP) Performance Metrics 1 Contract/Project Management Performance Metric FY 2013 Target FY 2013 Forecast FY 2013 Pre- & Post-CAP* Forecast Comment Capital Asset Project Success: Complete 90% of capital asset projects at original scope and within 110% of CD-2 TPC. 90%* 83% Construction 85% Cleanup 80% 70% Pre-CAP 84% Post-CAP This is based on a 3- year rolling average (FY11 to FY13). TPC is Total Project Cost.

  6. Energy Department Announces $2.5 Million to Improve Wind Forecasting |

    Office of Environmental Management (EM)

    Department of Energy .5 Million to Improve Wind Forecasting Energy Department Announces $2.5 Million to Improve Wind Forecasting January 8, 2015 - 12:00pm Addthis The Energy Department today announced $2.5 million for a new project to research the atmospheric processes that generate wind in mountain-valley regions. This in-depth research, conducted by Vaisala of Louisville, Colorado, will be used to improve the wind industry's weather models for short-term wind forecasts, especially for

  7. Cloudnet Project

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

    Hogan, Robin

    2008-01-15

    Cloudnet is a research project supported by the European Commission. This project aims to use data obtained quasi-continuously for the development and implementation of cloud remote sensing synergy algorithms. The use of active instruments (lidar and radar) results in detailed vertical profiles of important cloud parameters which cannot be derived from current satellite sensing techniques. A network of three already existing cloud remote sensing stations (CRS-stations) will be operated for a two year period, activities will be co-ordinated, data formats harmonised and analysis of the data performed to evaluate the representation of clouds in four major european weather forecast models.

  8. Cloudnet Project

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

    Hogan, Robin

    Cloudnet is a research project supported by the European Commission. This project aims to use data obtained quasi-continuously for the development and implementation of cloud remote sensing synergy algorithms. The use of active instruments (lidar and radar) results in detailed vertical profiles of important cloud parameters which cannot be derived from current satellite sensing techniques. A network of three already existing cloud remote sensing stations (CRS-stations) will be operated for a two year period, activities will be co-ordinated, data formats harmonised and analysis of the data performed to evaluate the representation of clouds in four major european weather forecast models.

  9. 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

  10. UPF Forecast | Y-12 National Security Complex

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

    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 Equipment Rental FOC 238910 TBD 3Q FY15/ 3Q

  11. 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:...

  12. 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...

  13. Contract/Project Management

    Office of Environmental Management (EM)

    Third Quarter Overall Contract and Project Management Performance Metrics and Targets 1 Contract/Project Management Primary Performance Metrics FY 2010 Target FY 2010 Forecast FY 2010 Pre- & Post-CAP Comment 1a. Capital Asset Line Item Projects: (Pre-RCA/CAP) 90% of projects completed within 110% of CD-2 TPC by FY11. 1b. Capital Asset Line Item Projects: (Post-RCA/CAP) 85% Line Item 71% Line Item 70% Pre-CAP 100% Post-CAP This is a projection based on a 3-year rolling average (FY08 to FY10).

  14. EIA lowers forecast for summer gasoline prices

    Gasoline and Diesel Fuel Update (EIA)

    EIA lowers forecast for summer gasoline prices U.S. gasoline prices are expected to be lower this summer than previously thought. The price for regular gasoline this summer is now expected to average $3.53 a gallon, according to the new monthly forecast from the U.S. Energy Information Administration. That's down 10 cents from last month's forecast and 16 cents cheaper than last summer. After reaching a weekly peak of $3.78 a gallon in late February, pump prices fell nine weeks in a row to $3.52

  15. EIA revises up forecast for U.S. 2013 crude oil production by 70,000 barrels per day

    Gasoline and Diesel Fuel Update (EIA)

    EIA revises up forecast for U.S. 2013 crude oil production by 70,000 barrels per day The forecast for U.S. crude oil production keeps going higher. The U.S. Energy Information Administration revised upward its projection for crude oil output in 2013 by 70,000 barrels per day and for next year by 190,000 barrels per day. U.S. oil production is now on track to average 7.5 million barrels per day this year and rise to 8.4 million barrels per day in 2014, according to EIA's latest monthly forecast.

  16. Contract/Project Management

    Office of Environmental Management (EM)

    First Quarter Overall Contract and Project Management Performance Metrics and Targets 1 Contract/Project Management Primary Performance Metrics FY 2011 Target FY 2011 Actual & Forecast FY 2011 Pre- & Post-CAP Comment 1a. Capital Asset Line Item Projects: (Pre-RCA/CAP) Projects completed within 110% of CD-2 TPC. 1b. Capital Asset Line Item Projects: (Post-RCA/CAP) 90% Line Item 79% Line Item 71% Pre-CAP 100% Post-CAP This is based on a 3-year rolling average (FY09 to FY11). TPC is Total

  17. Text-Alternative Version LED Lighting Forecast

    Broader source: Energy.gov [DOE]

    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....

  18. 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...

  19. Offshore Lubricants Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

  20. 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...

  1. 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.

  2. 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.

  3. 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.

  4. Comparison of AEO 2010 Natural Gas Price Forecast to NYMEX Futures Prices

    SciTech Connect (OSTI)

    Bolinger, Mark A.; Wiser, Ryan H.

    2010-01-04

    On December 14, 2009, the reference-case projections from Annual Energy Outlook 2010 were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables can play in itigating such risk. As such, we were curious to see how the latest AEO reference-case gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings.

  5. ARM - Science Project Ideas

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

    TeachersScience Project Ideas Outreach Home Room News Publications Traditional Knowledge Kiosks Barrow, Alaska Tropical Western Pacific Site Tours Contacts Students Study Hall About ARM Global Warming FAQ Just for Fun Meet our Friends Cool Sites Teachers Teachers' Toolbox Lesson Plans Science Project Ideas Do changes in air pressure affect the weather? What is the relationship between air pressure and temperature? Monitor the weather forecast data from the web to find the answer. How does the

  6. Projects | Department of Energy

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

    Projects Projects

  7. 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.

  8. Short Mountain Landfill gas recovery project

    SciTech Connect (OSTI)

    Not Available

    1992-05-01

    The Bonneville Power Administration (BPA), a Federal power marketing agency, has statutory responsibilities to supply electrical power to its utility, industrial, and other customers in the Pacific Northwest. BPA's latest load/resource balance forecast, projects the capability of existing resources to satisfy projected Federal system loads. The forecast indicates a potential resource deficit. The underlying need for action is to satisfy BPA customers' demand for electrical power.

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

    Office of Environmental Management (EM)

    Southern Study Area Final Report.pdf More Documents & Publications QER - Comment of Edison Electric Institute (EEI) 1 QER - Comment of Canadian Hydropower Association QER -...

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

    Broader source: Energy.gov [DOE]

    The University of North Carolina at Charlotte, along with their partners at Arizona State University and the University of Oxford, under the Solar Energy Evolution and Diffusion Studies (SEEDS)...

  11. Solar Forecasting Gets a Boost from Watson, Accuracy Improved...

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

    Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% October 27, 2015 - 11:48am Addthis IBM ...

  12. A Review of Variable Generation Forecasting in the West: July...

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

    rely on an array of VG forecasts suited to different purposes. Some of the most common types of VG forecasts are defined below: 2 This report is available at no cost from the...

  13. PBL FY 2003 Second Quarter Review Forecast of Generation Accumulated...

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

    the rate period (i.e., FY 2002-2006), a forecast of that end-of-year Accumulated Net Revenue (ANR) will be completed. If the ANR at the end of the forecast year falls below the...

  14. 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.

  15. NREL: Resource Assessment and Forecasting - Capabilities

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

    Capabilities Best Practices Handbook Helps Industry Collect and Interpret Solar Resource Data Read about this new comprehensive resource for the solar industry. NREL's resource assessment and forecasting research staff provides expertise in renewable energy measurement and instrumentation. Major capabilities include solar resource measurement, instrument calibration, instrument characterization, solar monitoring training, and standards development and information dissemination. Solar Resource

  16. Wind Power Forecasting Error Distributions over Multiple Timescales (Presentation)

    SciTech Connect (OSTI)

    Hodge, B. M.; Milligan, M.

    2011-07-01

    This presentation presents some statistical analysis of wind power forecast errors and error distributions, with examples using ERCOT data.

  17. Wind power forecasting in U.S. electricity markets.

    SciTech Connect (OSTI)

    Botterud, A.; Wang, J.; Miranda, V.; Bessa, R. J.; Decision and Information Sciences; INESC Porto

    2010-04-01

    Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts.

  18. Wind power forecasting in U.S. Electricity markets

    SciTech Connect (OSTI)

    Botterud, Audun; Wang, Jianhui; Miranda, Vladimiro; Bessa, Ricardo J.

    2010-04-15

    Wind power forecasting is becoming an important tool in electricity markets, but the use of these forecasts in market operations and among market participants is still at an early stage. The authors discuss the current use of wind power forecasting in U.S. ISO/RTO markets, and offer recommendations for how to make efficient use of the information in state-of-the-art forecasts. (author)

  19. Combined Heat And Power Installation Market Forecast | OpenEI...

    Open Energy Info (EERE)

    Combined Heat And Power Installation Market Forecast Home There are currently no posts in this category. Syndicate...

  20. DOE Taking Wind Forecasting to New Heights | Department of Energy

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

    Taking Wind Forecasting to New Heights DOE Taking Wind Forecasting to New Heights May 18, 2015 - 3:24pm Addthis A 2013 study conducted for the U.S. Department of Energy (DOE) by the National Oceanic and Atmospheric Administration (NOAA), AWS Truepower, and WindLogics in the Great Plains and Western Texas, demonstrated that wind power forecasts can be improved substantially using data collected from tall towers, remote sensors, and other devices, and incorporated into improved forecasting models

  1. Uncertainty Reduction in Power Generation Forecast Using Coupled

    Office of Scientific and Technical Information (OSTI)

    Wavelet-ARIMA (Conference) | SciTech Connect Conference: Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA Citation Details In-Document Search Title: Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA In this paper, we introduce a new approach without implying normal distributions and stationarity of power generation forecast errors. In addition, it is desired to more accurately quantify the forecast uncertainty by reducing prediction

  2. Operational forecasting based on a modified Weather Research and Forecasting model

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18

    Accurate short-term forecasts of wind resources are required for efficient wind farm operation and ultimately for the integration of large amounts of wind-generated power into electrical grids. Siemens Energy Inc. and Lawrence Livermore National Laboratory, with the University of Colorado at Boulder, are collaborating on the design of an operational forecasting system for large wind farms. The basis of the system is the numerical weather prediction tool, the Weather Research and Forecasting (WRF) model; large-eddy simulations and data assimilation approaches are used to refine and tailor the forecasting system. Representation of the atmospheric boundary layer is modified, based on high-resolution large-eddy simulations of the atmospheric boundary. These large-eddy simulations incorporate wake effects from upwind turbines on downwind turbines as well as represent complex atmospheric variability due to complex terrain and surface features as well as atmospheric stability. Real-time hub-height wind speed and other meteorological data streams from existing wind farms are incorporated into the modeling system to enable uncertainty quantification through probabilistic forecasts. A companion investigation has identified optimal boundary-layer physics options for low-level forecasts in complex terrain, toward employing decadal WRF simulations to anticipate large-scale changes in wind resource availability due to global climate change.

  3. The impact of forecasted energy price increases on low-income consumers

    SciTech Connect (OSTI)

    Eisenberg, Joel F.

    2005-10-31

    The Department of Energy’s Energy Information Administration (EIA) recently released its short term forecast for residential energy prices for the winter of 2005-2006. The forecast indicates significant increases in fuel costs, particularly for natural gas, propane, and home heating oil, for the year ahead. In the following analysis, the Oak Ridge National Laboratory has integrated the EIA price projections with the Residential Energy Consumption Survey (RECS) for 2001 in order to project the impact of these price increases on the nation’s low-income households by primary heating fuel type, nationally and by Census Region. The statistics are intended for the use of policymakers in the Department of Energy’s Weatherization Assistance Program and elsewhere who are trying to gauge the nature and severity of the problems that will be faced by eligible low-income households during the 2006 fiscal year.

  4. Forecastability as a Design Criterion in Wind Resource Assessment: Preprint

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.

    2014-04-01

    This paper proposes a methodology to include the wind power forecasting ability, or 'forecastability,' of a site as a design criterion in wind resource assessment and wind power plant design stages. The Unrestricted Wind Farm Layout Optimization (UWFLO) methodology is adopted to maximize the capacity factor of a wind power plant. The 1-hour-ahead persistence wind power forecasting method is used to characterize the forecastability of a potential wind power plant, thereby partially quantifying the integration cost. A trade-off between the maximum capacity factor and the forecastability is investigated.

  5. New Forecasting Tools Enhance Wind Energy Integration In Idaho and Oregon

    Office of Environmental Management (EM)

    New Forecasting Tools Enhance Wind Energy Integration in Idaho and Oregon Page 1 Under the American Recovery and Reinvestment Act of 2009, the U.S. Department of Energy and the electricity industry have jointly invested over $7.9 billion in 99 cost-shared Smart Grid Investment Grant projects to modernize the electric grid, strengthen cybersecurity, improve interoperability, and collect an unprecedented level of data on smart grid and customer operations. 1. Summary Idaho Power Company (IPC)

  6. Forecasting hotspots using predictive visual analytics approach

    DOE Patents [OSTI]

    Maciejewski, Ross; Hafen, Ryan; Rudolph, Stephen; Cleveland, William; Ebert, David

    2014-12-30

    A method for forecasting hotspots is provided. The method may include the steps of receiving input data at an input of the computational device, generating a temporal prediction based on the input data, generating a geospatial prediction based on the input data, and generating output data based on the time series and geospatial predictions. The output data may be configured to display at least one user interface at an output of the computational device.

  7. Global disease monitoring and forecasting with Wikipedia

    SciTech Connect (OSTI)

    Generous, Nicholas; Fairchild, Geoffrey; Deshpande, Alina; Del Valle, Sara Y.; Priedhorsky, Reid; Salathé, Marcel

    2014-11-13

    Infectious disease is a leading threat to public health, economic stability, and other key social structures. Efforts to mitigate these impacts depend on accurate and timely monitoring to measure the risk and progress of disease. Traditional, biologically-focused monitoring techniques are accurate but costly and slow; in response, new techniques based on social internet data, such as social media and search queries, are emerging. These efforts are promising, but important challenges in the areas of scientific peer review, breadth of diseases and countries, and forecasting hamper their operational usefulness. We examine a freely available, open data source for this use: access logs from the online encyclopedia Wikipedia. Using linear models, language as a proxy for location, and a systematic yet simple article selection procedure, we tested 14 location-disease combinations and demonstrate that these data feasibly support an approach that overcomes these challenges. Specifically, our proof-of-concept yields models with up to 0.92, forecasting value up to the 28 days tested, and several pairs of models similar enough to suggest that transferring models from one location to another without re-training is feasible. Based on these preliminary results, we close with a research agenda designed to overcome these challenges and produce a disease monitoring and forecasting system that is significantly more effective, robust, and globally comprehensive than the current state of the art.

  8. A survey on wind power ramp forecasting.

    SciTech Connect (OSTI)

    Ferreira, C.; Gama, J.; Matias, L.; Botterud, A.; Wang, J.

    2011-02-23

    The increasing use of wind power as a source of electricity poses new challenges with regard to both power production and load balance in the electricity grid. This new source of energy is volatile and highly variable. The only way to integrate such power into the grid is to develop reliable and accurate wind power forecasting systems. Electricity generated from wind power can be highly variable at several different timescales: sub-hourly, hourly, daily, and seasonally. Wind energy, like other electricity sources, must be scheduled. Although wind power forecasting methods are used, the ability to predict wind plant output remains relatively low for short-term operation. Because instantaneous electrical generation and consumption must remain in balance to maintain grid stability, wind power's variability can present substantial challenges when large amounts of wind power are incorporated into a grid system. A critical issue is ramp events, which are sudden and large changes (increases or decreases) in wind power. This report presents an overview of current ramp definitions and state-of-the-art approaches in ramp event forecasting.

  9. Global disease monitoring and forecasting with Wikipedia

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

    Generous, Nicholas; Fairchild, Geoffrey; Deshpande, Alina; Del Valle, Sara Y.; Priedhorsky, Reid; Salathé, Marcel

    2014-11-13

    Infectious disease is a leading threat to public health, economic stability, and other key social structures. Efforts to mitigate these impacts depend on accurate and timely monitoring to measure the risk and progress of disease. Traditional, biologically-focused monitoring techniques are accurate but costly and slow; in response, new techniques based on social internet data, such as social media and search queries, are emerging. These efforts are promising, but important challenges in the areas of scientific peer review, breadth of diseases and countries, and forecasting hamper their operational usefulness. We examine a freely available, open data source for this use: accessmore » logs from the online encyclopedia Wikipedia. Using linear models, language as a proxy for location, and a systematic yet simple article selection procedure, we tested 14 location-disease combinations and demonstrate that these data feasibly support an approach that overcomes these challenges. Specifically, our proof-of-concept yields models with up to 0.92, forecasting value up to the 28 days tested, and several pairs of models similar enough to suggest that transferring models from one location to another without re-training is feasible. Based on these preliminary results, we close with a research agenda designed to overcome these challenges and produce a disease monitoring and forecasting system that is significantly more effective, robust, and globally comprehensive than the current state of the art.« less

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

    SciTech Connect (OSTI)

    Zhang, Jie; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Lehman, Brad; Simmons, Joseph; Campos, Edwin; Banunarayanan, Venkat

    2015-08-05

    Accurate solar power forecasting allows utilities to get the most out of the solar resources on their systems. To truly measure the improvements that any new solar forecasting methods can provide, it is important to first develop (or determine) baseline and target solar forecasting at different spatial and temporal scales. This paper aims to develop baseline and target values for solar forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output. forecasting metrics. These were informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of solar power output.

  11. 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.

  12. Short Mountain Landfill Gas Recovery Project : Stage 1 Environmental Assessment.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    1992-05-01

    The Bonneville Power Administration (BPA), a Federal power marketing agency, has statutory responsibilities to supply electrical power to its utility, industrial, and other customers in the Pacific Northwest. BPA`s latest load/resource balance forecast, projects the capability of existing resources to satisfy projected Federal system loads. The forecast indicates a potential resource deficit. The underlying need for action is to satisfy BPA customers` demand for electrical power.

  13. Module 6 - Metrics, Performance Measurements and Forecasting | Department

    Energy Savers [EERE]

    of Energy 6 - Metrics, Performance Measurements and Forecasting Module 6 - Metrics, Performance Measurements and Forecasting This module focuses on the metrics and performance measurement tools used in Earned Value. 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 estimate to complete (ETC) and estimate at completion (EAC)

  14. DOE Benefits Forecasts: Report of the External Peer Review Panel |

    Office of Environmental Management (EM)

    Department of Energy Benefits Forecasts: Report of the External Peer Review Panel DOE Benefits Forecasts: Report of the External Peer Review Panel A report for the FY 2007 GPRA methodology review, highlighting the views of an external expert peer review panel on DOE benefits forecasts. PDF icon Report of the External Peer Review Panel More Documents & Publications Industrial Technologies Funding Profile by Subprogram Survey of Emissions Models for Distributed Combined Heat and Power

  15. NREL: Resource Assessment and Forecasting - Webmaster

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

    Webmaster Use this form to send us your comments and questions, report problems with the site, or ask for help finding information on the site. Please enter your name and email address in the boxes provided, then type your message below. When you are finished, click "Send Message." NOTE: If you enter your e-mail address incorrectly, we will be unable to reply. Your name: Your email address: Your message: Send Message Printable Version Resource Assessment & Forecasting Home

  16. Ensemble Solar Forecasting Statistical Quantification and Sensitivity Analysis: Preprint

    SciTech Connect (OSTI)

    Cheung, WanYin; Zhang, Jie; Florita, Anthony; Hodge, Bri-Mathias; Lu, Siyuan; Hamann, Hendrik F.; Sun, Qian; Lehman, Brad

    2015-12-08

    Uncertainties associated with solar forecasts present challenges to maintain grid reliability, especially at high solar penetrations. This study aims to quantify the errors associated with the day-ahead solar forecast parameters and the theoretical solar power output for a 51-kW solar power plant in a utility area in the state of Vermont, U.S. Forecasts were generated by three numerical weather prediction (NWP) models, including the Rapid Refresh, the High Resolution Rapid Refresh, and the North American Model, and a machine-learning ensemble model. A photovoltaic (PV) performance model was adopted to calculate theoretical solar power generation using the forecast parameters (e.g., irradiance, cell temperature, and wind speed). Errors of the power outputs were quantified using statistical moments and a suite of metrics, such as the normalized root mean squared error (NRMSE). In addition, the PV model's sensitivity to different forecast parameters was quantified and analyzed. Results showed that the ensemble model yielded forecasts in all parameters with the smallest NRMSE. The NRMSE of solar irradiance forecasts of the ensemble NWP model was reduced by 28.10% compared to the best of the three NWP models. Further, the sensitivity analysis indicated that the errors of the forecasted cell temperature attributed only approximately 0.12% to the NRMSE of the power output as opposed to 7.44% from the forecasted solar irradiance.

  17. Wind Power Forecasting Error Distributions: An International Comparison; Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Lew, D.; Milligan, M.; Holttinen, H.; Sillanpaa, S.; Gomez-Lazaro, E.; Scharff, R.; Soder, L.; Larsen, X. G.; Giebel, G.; Flynn, D.; Dobschinski, J.

    2012-09-01

    Wind power forecasting is expected to be an important enabler for greater penetration of wind power into electricity systems. Because no wind forecasting system is perfect, a thorough understanding of the errors that do occur can be critical to system operation functions, such as the setting of operating reserve levels. This paper provides an international comparison of the distribution of wind power forecasting errors from operational systems, based on real forecast data. The paper concludes with an assessment of similarities and differences between the errors observed in different locations.

  18. FY 2004 Second Quarter Review Forecast of Generation Accumulated...

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

    Bonneville Power Administration Power Business Line Generation (PBL) Accumulated Net Revenue Forecast for Financial-Based Cost Recovery Adjustment Clause (FB CRAC) and Safety-Net...

  19. PBL FY 2003 Third Quarter Review Forecast of Generation Accumulated...

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

    2003 Bonneville Power Administration Power Business Line Generation Accumulated Net Revenue Forecast for Financial-Based Cost Recovery Adjustment Clause (FB CRAC) and Safety-Net...

  20. Roel Neggers European Centre for Medium-range Weather Forecasts

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

    transition from shallow to deep convection using a dual mass flux boundary layer scheme Roel Neggers European Centre for Medium-range Weather Forecasts Introduction " " % % &...

  1. Comparison of Wind Power and Load Forecasting Error Distributions: Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Florita, A.; Orwig, K.; Lew, D.; Milligan, M.

    2012-07-01

    The introduction of large amounts of variable and uncertain power sources, such as wind power, into the electricity grid presents a number of challenges for system operations. One issue involves the uncertainty associated with scheduling power that wind will supply in future timeframes. However, this is not an entirely new challenge; load is also variable and uncertain, and is strongly influenced by weather patterns. In this work we make a comparison between the day-ahead forecasting errors encountered in wind power forecasting and load forecasting. The study examines the distribution of errors from operational forecasting systems in two different Independent System Operator (ISO) regions for both wind power and load forecasts at the day-ahead timeframe. The day-ahead timescale is critical in power system operations because it serves the unit commitment function for slow-starting conventional generators.

  2. Short-Term Energy Outlook Model Documentation: Macro Bridge Procedure to Update Regional Macroeconomic Forecasts with National Macroeconomic Forecasts

    Reports and Publications (EIA)

    2010-01-01

    The Regional Short-Term Energy Model (RSTEM) uses macroeconomic variables such as income, employment, industrial production and consumer prices at both the national and regional1 levels as explanatory variables in the generation of the Short-Term Energy Outlook (STEO). This documentation explains how national macroeconomic forecasts are used to update regional macroeconomic forecasts through the RSTEM Macro Bridge procedure.

  3. 3TIER Environmental Forecast Group Inc 3TIER | Open Energy Information

    Open Energy Info (EERE)

    TIER Environmental Forecast Group Inc 3TIER Jump to: navigation, search Name: 3TIER Environmental Forecast Group Inc (3TIER) Place: Seattle, Washington Zip: 98121 Sector: Renewable...

  4. Energy Savings Forecast of Solid-State Lighting in General Illuminatio...

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

    Forecast of Solid-State Lighting in General Illumination Applications Energy Savings Forecast of Solid-State Lighting in General Illumination Applications PDF icon...

  5. Wind Energy Forecasting: A Collaboration of the National Center for Atmospheric Research (NCAR) and Xcel Energy

    SciTech Connect (OSTI)

    Parks, K.; Wan, Y. H.; Wiener, G.; Liu, Y.

    2011-10-01

    The focus of this report is the wind forecasting system developed during this contract period with results of performance through the end of 2010. The report is intentionally high-level, with technical details disseminated at various conferences and academic papers. At the end of 2010, Xcel Energy managed the output of 3372 megawatts of installed wind energy. The wind plants span three operating companies1, serving customers in eight states2, and three market structures3. The great majority of the wind energy is contracted through power purchase agreements (PPAs). The remainder is utility owned, Qualifying Facilities (QF), distributed resources (i.e., 'behind the meter'), or merchant entities within Xcel Energy's Balancing Authority footprints. Regardless of the contractual or ownership arrangements, the output of the wind energy is balanced by Xcel Energy's generation resources that include fossil, nuclear, and hydro based facilities that are owned or contracted via PPAs. These facilities are committed and dispatched or bid into day-ahead and real-time markets by Xcel Energy's Commercial Operations department. Wind energy complicates the short and long-term planning goals of least-cost, reliable operations. Due to the uncertainty of wind energy production, inherent suboptimal commitment and dispatch associated with imperfect wind forecasts drives up costs. For example, a gas combined cycle unit may be turned on, or committed, in anticipation of low winds. The reality is winds stayed high, forcing this unit and others to run, or be dispatched, to sub-optimal loading positions. In addition, commitment decisions are frequently irreversible due to minimum up and down time constraints. That is, a dispatcher lives with inefficient decisions made in prior periods. In general, uncertainty contributes to conservative operations - committing more units and keeping them on longer than may have been necessary for purposes of maintaining reliability. The downside is costs are higher. In organized electricity markets, units that are committed for reliability reasons are paid their offer price even when prevailing market prices are lower. Often, these uplift charges are allocated to market participants that caused the inefficient dispatch in the first place. Thus, wind energy facilities are burdened with their share of costs proportional to their forecast errors. For Xcel Energy, wind energy uncertainty costs manifest depending on specific market structures. In the Public Service of Colorado (PSCo), inefficient commitment and dispatch caused by wind uncertainty increases fuel costs. Wind resources participating in the Midwest Independent System Operator (MISO) footprint make substantial payments in the real-time markets to true-up their day-ahead positions and are additionally burdened with deviation charges called a Revenue Sufficiency Guarantee (RSG) to cover out of market costs associated with operations. Southwest Public Service (SPS) wind plants cause both commitment inefficiencies and are charged Southwest Power Pool (SPP) imbalance payments due to wind uncertainty and variability. Wind energy forecasting helps mitigate these costs. Wind integration studies for the PSCo and Northern States Power (NSP) operating companies have projected increasing costs as more wind is installed on the system due to forecast error. It follows that reducing forecast error would reduce these costs. This is echoed by large scale studies in neighboring regions and states that have recommended adoption of state-of-the-art wind forecasting tools in day-ahead and real-time planning and operations. Further, Xcel Energy concluded reduction of the normalized mean absolute error by one percent would have reduced costs in 2008 by over $1 million annually in PSCo alone. The value of reducing forecast error prompted Xcel Energy to make substantial investments in wind energy forecasting research and development.

  6. Project Assessment and Reporting System (PARS II) Data Quality Memo

    Broader source: Energy.gov [DOE]

    While PARS II is but one of many tools used to monitor project performance, when information and earned value data in the system are deficient and do not accurately reflect current project status or provide acceptable forecasts, effective project management is impaired. If we are to demonstrate long-term improvement in contract and project management, we must insist on project information that facilitates management, not impedes it.

  7. Analysis & Projections - U.S. Energy Information Administration (EIA) -

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

    U.S. Energy Information Administration (EIA) Analysis & Projections Glossary › FAQS › Overview Projection Data Monthly Short-Term Forecasts to 2012 Annual Projections to 2035 International Projections Analysis & Projections Most Requested All Reports Models & Documentation Technical Workshop on Behavior Economics Presentations November 15, 2013 About the workshop The U.S. Department of Energy's Energy Information Administration (EIA) conducted a technical workshop on July 17,

  8. Development and testing of improved statistical wind power forecasting methods.

    SciTech Connect (OSTI)

    Mendes, J.; Bessa, R.J.; Keko, H.; Sumaili, J.; Miranda, V.; Ferreira, C.; Gama, J.; Botterud, A.; Zhou, Z.; Wang, J.

    2011-12-06

    Wind power forecasting (WPF) provides important inputs to power system operators and electricity market participants. It is therefore not surprising that WPF has attracted increasing interest within the electric power industry. In this report, we document our research on improving statistical WPF algorithms for point, uncertainty, and ramp forecasting. Below, we provide a brief introduction to the research presented in the following chapters. For a detailed overview of the state-of-the-art in wind power forecasting, we refer to [1]. Our related work on the application of WPF in operational decisions is documented in [2]. Point forecasts of wind power are highly dependent on the training criteria used in the statistical algorithms that are used to convert weather forecasts and observational data to a power forecast. In Chapter 2, we explore the application of information theoretic learning (ITL) as opposed to the classical minimum square error (MSE) criterion for point forecasting. In contrast to the MSE criterion, ITL criteria do not assume a Gaussian distribution of the forecasting errors. We investigate to what extent ITL criteria yield better results. In addition, we analyze time-adaptive training algorithms and how they enable WPF algorithms to cope with non-stationary data and, thus, to adapt to new situations without requiring additional offline training of the model. We test the new point forecasting algorithms on two wind farms located in the U.S. Midwest. Although there have been advancements in deterministic WPF, a single-valued forecast cannot provide information on the dispersion of observations around the predicted value. We argue that it is essential to generate, together with (or as an alternative to) point forecasts, a representation of the wind power uncertainty. Wind power uncertainty representation can take the form of probabilistic forecasts (e.g., probability density function, quantiles), risk indices (e.g., prediction risk index) or scenarios (with spatial and/or temporal dependence). Statistical approaches to uncertainty forecasting basically consist of estimating the uncertainty based on observed forecasting errors. Quantile regression (QR) is currently a commonly used approach in uncertainty forecasting. In Chapter 3, we propose new statistical approaches to the uncertainty estimation problem by employing kernel density forecast (KDF) methods. We use two estimators in both offline and time-adaptive modes, namely, the Nadaraya-Watson (NW) and Quantilecopula (QC) estimators. We conduct detailed tests of the new approaches using QR as a benchmark. One of the major issues in wind power generation are sudden and large changes of wind power output over a short period of time, namely ramping events. In Chapter 4, we perform a comparative study of existing definitions and methodologies for ramp forecasting. We also introduce a new probabilistic method for ramp event detection. The method starts with a stochastic algorithm that generates wind power scenarios, which are passed through a high-pass filter for ramp detection and estimation of the likelihood of ramp events to happen. The report is organized as follows: Chapter 2 presents the results of the application of ITL training criteria to deterministic WPF; Chapter 3 reports the study on probabilistic WPF, including new contributions to wind power uncertainty forecasting; Chapter 4 presents a new method to predict and visualize ramp events, comparing it with state-of-the-art methodologies; Chapter 5 briefly summarizes the main findings and contributions of this report.

  9. Solid Waste Integrated Forecast Technical (SWIFT) Report FY2001 to FY2046 Volume 1

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2000-08-31

    This report provides up-to-date life cycle information about the radioactive solid waste expected to be managed by Hanford's Waste Management (WM) Project from onsite and offsite generators. It includes: an overview of Hanford-wide solid waste to be managed by the WM Project; program-level and waste class-specific estimates; background information on waste sources; and comparisons to previous forecasts and other national data sources. This report does not include: waste to be managed by the Environmental Restoration (EM-40) contractor (i.e., waste that will be disposed of at the Environmental Restoration Disposal Facility (ERDF)); waste that has been received by the WM Project to date (i.e., inventory waste); mixed low-level waste that will be processed and disposed by the River Protection Program; and liquid waste (current or future generation). Although this report currently does not include liquid wastes, they may be added as information becomes available.

  10. Solid waste integrated forecast technical (SWIFT) report: FY1997 to FY 2070, Revision 1

    SciTech Connect (OSTI)

    Valero, O.J.; Templeton, K.J.; Morgan, J.

    1997-01-07

    This web site provides an up-to-date report on the radioactive solid waste expected to be managed by Hanford's Waste Management (WM) Project from onsite and offsite generators. It includes: an overview of Hanford-wide solid waste to be managed by the WM Project; program-level and waste class-specific estimates; background information on waste sources; and comparisons with previous forecasts and with other national data sources. This web site does not include: liquid waste (current or future generation); waste to be managed by the Environmental Restoration (EM-40) contractor (i.e., waste that will be disposed of at the Environmental Restoration Disposal Facility (ERDF)); or waste that has been received by the WM Project to date (i.e., inventory waste). The focus of this web site is on low-level mixed waste (LLMW), and transuranic waste (both non-mixed and mixed) (TRU(M)). Some details on low-level waste and hazardous waste are also provided. Currently, this web site is reporting data th at was requested on 10/14/96 and submitted on 10/25/96. The data represent a life cycle forecast covering all reported activities from FY97 through the end of each program's life cycle. Therefore, these data represent revisions from the previous FY97.0 Data Version, due primarily to revised estimates from PNNL. There is some useful information about the structure of this report in the SWIFT Report Web Site Overview.

  11. U.S. Regional Demand Forecasts Using NEMS and GIS

    SciTech Connect (OSTI)

    Cohen, Jesse A.; Edwards, Jennifer L.; Marnay, Chris

    2005-07-01

    The National Energy Modeling System (NEMS) is a multi-sector, integrated model of the U.S. energy system put out by the Department of Energy's Energy Information Administration. NEMS is used to produce the annual 20-year forecast of U.S. energy use aggregated to the nine-region census division level. The research objective was to disaggregate this regional energy forecast to the county level for select forecast years, for use in a more detailed and accurate regional analysis of energy usage across the U.S. The process of disaggregation using a geographic information system (GIS) was researched and a model was created utilizing available population forecasts and climate zone data. The model's primary purpose was to generate an energy demand forecast with greater spatial resolution than what is currently produced by NEMS, and to produce a flexible model that can be used repeatedly as an add-on to NEMS in which detailed analysis can be executed exogenously with results fed back into the NEMS data flow. The methods developed were then applied to the study data to obtain residential and commercial electricity demand forecasts. The model was subjected to comparative and statistical testing to assess predictive accuracy. Forecasts using this model were robust and accurate in slow-growing, temperate regions such as the Midwest and Mountain regions. Interestingly, however, the model performed with less accuracy in the Pacific and Northwest regions of the country where population growth was more active. In the future more refined methods will be necessary to improve the accuracy of these forecasts. The disaggregation method was written into a flexible tool within the ArcGIS environment which enables the user to output the results in five year intervals over the period 2000-2025. In addition, the outputs of this tool were used to develop a time-series simulation showing the temporal changes in electricity forecasts in terms of absolute, per capita, and density of demand.

  12. Science and Engineering of an Operational Tsunami Forecasting System

    ScienceCinema (OSTI)

    Gonzalez, Frank

    2010-01-08

    After a review of tsunami statistics and the destruction caused by tsunamis, a means of forecasting tsunamis is discussed as part of an overall program of reducing fatalities through hazard assessment, education, training, mitigation, and a tsunami warning system. The forecast is accomplished via a concept called Deep Ocean Assessment and Reporting of Tsunamis (DART). Small changes of pressure at the sea floor are measured and relayed to warning centers. Under development is an international modeling network to transfer, maintain, and improve tsunami forecast models.

  13. Comparison of AEO 2006 Natural Gas Price Forecast to NYMEX FuturesPrices

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2005-12-19

    On December 12, 2005, the reference case projections from ''Annual Energy Outlook 2006'' (AEO 2006) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have in the past compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk (see, for example, http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf). As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past five years, forward natural gas contracts (with prices that can be locked in--e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past five years at least, levelized cost comparisons of fixed-price renewable generation with variable price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are ''biased'' in favor of gas-fired generation, presuming that long-term price stability is valued. In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2006. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past five AEO releases (AEO 2001-AEO 2005), we once again find that the AEO 2006 reference case gas price forecast falls well below where NYMEX natural gas futures contracts were trading at the time the EIA finalized its gas price forecast. In fact, the NYMEX-AEO 2006 reference case comparison yields by far the largest premium--$2.3/MMBtu levelized over five years--that we have seen over the last six years. In other words, on average, one would have had to pay $2.3/MMBtu more than the AEO 2006 reference case natural gas price forecast in order to lock in natural gas prices over the coming five years and thereby replicate the price stability provided intrinsically by fixed-price renewable generation (or other forms of generation whose costs are not tied to the price of natural gas). Fixed-price generation (like certain forms of renewable generation) obviously need not bear this added cost, and moreover can provide price stability for terms well in excess of five years.

  14. Comparison of AEO 2007 Natural Gas Price Forecast to NYMEX FuturesPrices

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2006-12-06

    On December 5, 2006, the reference case projections from 'Annual Energy Outlook 2007' (AEO 2007) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk (see, for example, http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf). As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past six years, forward natural gas contracts (with prices that can be locked in--e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past six years at least, levelized cost comparisons of fixed-price renewable generation with variable-price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are 'biased' in favor of gas-fired generation, presuming that long-term price stability is valued. In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2007. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past six AEO releases (AEO 2001-AEO 2006), we once again find that the AEO 2007 reference case gas price forecast falls well below where NYMEX natural gas futures contracts were trading at the time the EIA finalized its gas price forecast. Specifically, the NYMEX-AEO 2007 premium is $0.73/MMBtu levelized over five years. In other words, on average, one would have had to pay $0.73/MMBtu more than the AEO 2007 reference case natural gas price forecast in order to lock in natural gas prices over the coming five years and thereby replicate the price stability provided intrinsically by fixed-price renewable generation (or other forms of generation whose costs are not tied to the price of natural gas). Fixed-price generation (like certain forms of renewable generation) obviously need not bear this added cost, and moreover can provide price stability for terms well in excess of five years.

  15. Comparison of AEO 2005 natural gas price forecast to NYMEX futures prices

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2004-12-13

    On December 9, the reference case projections from ''Annual Energy Outlook 2005 (AEO 2005)'' were posted on the Energy Information Administration's (EIA) web site. As some of you may be aware, we at LBNL have in the past compared the EIA's reference case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables play in mitigating such risk. As such, we were curious to see how the latest AEO gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. As a refresher, our past work in this area has found that over the past four years, forward natural gas contracts (e.g., gas futures, swaps, and physical supply) have traded at a premium relative to contemporaneous long-term reference case gas price forecasts from the EIA. As such, we have concluded that, over the past four years at least, levelized cost comparisons of fixed-price renewable generation with variable price gas-fired generation that have been based on AEO natural gas price forecasts (rather than forward prices) have yielded results that are ''biased'' in favor of gas-fired generation (presuming that long-term price stability is valued). In this memo we simply update our past analysis to include the latest long-term gas price forecast from the EIA, as contained in AEO 2005. For the sake of brevity, we do not rehash information (on methodology, potential explanations for the premiums, etc.) contained in our earlier reports on this topic; readers interested in such information are encouraged to download that work from http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or, more recently (and briefly), http://eetd.lbl.gov/ea/ems/reports/54751.pdf. As was the case in the past four AEO releases (AEO 2001-AE0 2004), we once again find that the AEO 2005 reference case gas price forecast falls well below where NYMEX natural gas futures contracts were trading at the time the EIA finalized its gas price forecast. In fact, the NYMEXAEO 2005 reference case comparison yields by far the largest premium--$1.11/MMBtu levelized over six years--that we have seen over the last five years. In other words, on average, one would have to pay $1.11/MMBtu more than the AEO 2005 reference case natural gas price forecast in order to lock in natural gas prices over the coming six years and thereby replicate the price stability provided intrinsically by fixed-price renewable generation. Fixed-price renewables obviously need not bear this added cost, and moreover can provide price stability for terms well in excess of six years.

  16. Energy Forecasting Framework and Emissions Consensus Tool (EFFECT...

    Open Energy Info (EERE)

    Tool (EFFECT) EFFECT is an open, Excel-based modeling tool used to forecast greenhouse gas emissions from a range of development scenarios at the regional and national levels....

  17. Network Bandwidth Utilization Forecast Model on High Bandwidth Network

    SciTech Connect (OSTI)

    Yoo, Wucherl; Sim, Alex

    2014-07-07

    With the increasing number of geographically distributed scientific collaborations and the scale of the data size growth, it has become more challenging for users to achieve the best possible network performance on a shared network. We have developed a forecast model to predict expected bandwidth utilization for high-bandwidth wide area network. The forecast model can improve the efficiency of resource utilization and scheduling data movements on high-bandwidth network to accommodate ever increasing data volume for large-scale scientific data applications. Univariate model is developed with STL and ARIMA on SNMP path utilization data. Compared with traditional approach such as Box-Jenkins methodology, our forecast model reduces computation time by 83.2percent. It also shows resilience against abrupt network usage change. The accuracy of the forecast model is within the standard deviation of the monitored measurements.

  18. Solar Trackers Market Forecast | OpenEI Community

    Open Energy Info (EERE)

    Solar Trackers Market Forecast Home John55364's picture Submitted by John55364(100) Contributor 12 May, 2015 - 03:54 Solar Trackers Market - Global Industry Analysis, Size, Share,...

  19. Forecasting Crude Oil Spot Price Using OECD Petroleum Inventory Levels

    Reports and Publications (EIA)

    2003-01-01

    This paper presents a short-term monthly forecasting model of West Texas Intermediate crude oil spot price using Organization for Economic Cooperation and Development (OECD) petroleum inventory levels.

  20. Value of Improved Short-Term Wind Power Forecasting

    SciTech Connect (OSTI)

    Hodge, B. M.; Florita, A.; Sharp, J.; Margulis, M.; Mcreavy, D.

    2015-02-01

    This report summarizes an assessment of improved short-term wind power forecasting in the California Independent System Operator (CAISO) market and provides a quantification of its potential value.

  1. DOE Announces Webinars on Solar Forecasting Metrics, the DOE...

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

    The Energy Department will present a live webinar titled "Solar Forecasting Metrics" on Thursday, February 13, from 3:00 p.m. to 5:00 p.m. Eastern Standard Time. During this ...

  2. PBL FY 2002 Second Quarter Review Forecast of Generation Accumulated...

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

    Slice true-ups, and actual expense levels. Any variation of these can change the net revenue situation. FY 2002 Forecasted Second Quarter Results 170 (418) FY 2002 Unaudited...

  3. World oil inventories forecast to grow significantly in 2016...

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

    World oil inventories forecast to grow significantly in 2016 and 2017 Global oil inventories are expected to continue strong growth over the next two years which should keep oil ...

  4. Development and Demonstration of Advanced Forecasting, Power and Environmental Planning and Management Tools and Best Practices

    Broader source: Energy.gov [DOE]

    Development and Demonstration of Advanced Forecasting, Power and Environmental Planning and Management Tools and Best Practices

  5. 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 the journal Nature Climate Change, suggest that global models may underestimate predictions of forest death. December 21, 2015 Los Alamos scientist Nate McDowell discusses how climate change is killing trees with PBS NewsHour reporter Miles O'Brien. Los Alamos scientist Nate McDowell discusses how climate change is

  6. Forecasting neutrino masses from combining KATRIN and the CMB observations:

    Office of Scientific and Technical Information (OSTI)

    Frequentist and Bayesian analyses (Journal Article) | SciTech Connect SciTech Connect Search Results Journal Article: Forecasting neutrino masses from combining KATRIN and the CMB observations: Frequentist and Bayesian analyses Citation Details In-Document Search Title: Forecasting neutrino masses from combining KATRIN and the CMB observations: Frequentist and Bayesian analyses We present a showcase for deriving bounds on the neutrino masses from laboratory experiments and cosmological

  7. Energy Department Forecasts Geothermal Achievements in 2015 | Department of

    Office of Environmental Management (EM)

    Energy Forecasts Geothermal Achievements in 2015 Energy Department Forecasts Geothermal Achievements in 2015 The 40th annual Stanford Geothermal Workshop in January featured speakers in the geothermal sector, including Jay Nathwani, Acting Director of the Energy Department's Geothermal Technologies Office. Nathwani shared achievements and challenges in the program's technical portfolio. The 40th annual Stanford Geothermal Workshop in January featured speakers in the geothermal sector,

  8. Expert Panel: Forecast Future Demand for Medical Isotopes | Department of

    Office of Environmental Management (EM)

    Energy Expert Panel: Forecast Future Demand for Medical Isotopes Expert Panel: Forecast Future Demand for Medical Isotopes The Expert Panel has concluded that the Department of Energy and National Institutes of Health must develop the capability to produce a diverse supply of radioisotopes for medical use in quantities sufficient to support research and clinical activities. Such a capability would prevent shortages of isotopes, reduce American dependence on foreign radionuclide sources and

  9. National Oceanic and Atmospheric Administration Provides Forecasting Support for CLASIC and CHAPS 2007

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

    NOAA Provides Forecasting Support for CLASIC and CHAPS 2007 Forecasting Challenge While weather experiments in the heart of Tornado Alley typically focus on severe weather, the CLASIC and CHAPS programs will have different emphases. Forecasters from the National Oceanic and Atmospheric Administration in Norman, Okla. will provide weather forecasting support to these two Department of Energy experiments based in the state. Forecasting support for meteorological research field programs usually

  10. 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 wind speed and vertical temperature difference. Ideally, the data assimilation scheme used in the experiments would have been based upon an ensemble Kalman filter (EnKF) that was similar to the ESA method used to diagnose the Mid-Colombia Basin sensitivity patterns in the previous studies. However, the use of an EnKF system at high resolution is impractical because of the very high computational cost. Thus, it was decided to use the three-dimensional variational analysis data assimilation that is less computationally intensive and more economically practical for generating operational forecasts. There are two tasks in the current project effort designed to validate the ESA observational system deployment approach in order to move closer to the overall goal: (1) Perform an Observing System Experiment (OSE) using a data denial approach which is the focus of this task and report; and (2) Conduct a set of Observing System Simulation Experiments (OSSE) for the Mid-Colombia basin region. The results of this task are presented in a separate report. The objective of the OSE task involves validating the ESA-MOOA results from the previous sensitivity studies for the Mid-Columbia Basin by testing the impact of existing meteorological tower measurements on the 0- to 6-hour ahead 80-m wind forecasts at the target locations. The testing of the ESA-MOOA method used a combination of data assimilation techniques and data denial experiments to accomplish the task objective.

  11. AVLIS: a technical and economic forecast

    SciTech Connect (OSTI)

    Davis, J.I.; Spaeth, M.L.

    1986-01-01

    The AVLIS process has intrinsically large isotopic selectivity and hence high separative capacity per module. The critical components essential to achieving the high production rates represent a small fraction (approx.10%) of the total capital cost of a production facility, and the reference production designs are based on frequent replacement of these components. The specifications for replacement frequencies in a plant are conservative with respect to our expectations; it is reasonable to expect that, as the plant is operated, the specifications will be exceeded and production costs will continue to fall. Major improvements in separator production rates and laser system efficiencies (approx.power) are expected to occur as a natural evolution in component improvements. With respect to the reference design, such improvements have only marginal economic value, but given the exigencies of moving from engineering demonstration to production operations, we continue to pursue these improvements in order to offset any unforeseen cost increases. Thus, our technical and economic forecasts for the AVLIS process remain very positive. The near-term challenge is to obtain stable funding and a commitment to bring the process to full production conditions within the next five years. If the funding and commitment are not maintained, the team will disperse and the know-how will be lost before it can be translated into production operations. The motivation to preserve the option for low-cost AVLIS SWU production is integrally tied to the motivation to maintain a competitive nuclear option. The US industry can certainly survive without AVLIS, but our tradition as technology leader in the industry will certainly be lost.

  12. 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.

  13. 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

  14. Residential sector end-use forecasting with EPRI-Reeps 2.1: Summary input assumptions and results

    SciTech Connect (OSTI)

    Koomey, J.G.; Brown, R.E.; Richey, R.

    1995-12-01

    This paper describes current and projected future energy use by end-use and fuel for the U.S. residential sector, and assesses which end-uses are growing most rapidly over time. The inputs to this forecast are based on a multi-year data compilation effort funded by the U.S. Department of Energy. We use the Electric Power Research Institute`s (EPRI`s) REEPS model, as reconfigured to reflect the latest end-use technology data. Residential primary energy use is expected to grow 0.3% per year between 1995 and 2010, while electricity demand is projected to grow at about 0.7% per year over this period. The number of households is expected to grow at about 0.8% per year, which implies that the overall primary energy intensity per household of the residential sector is declining, and the electricity intensity per household is remaining roughly constant over the forecast period. These relatively low growth rates are dependent on the assumed growth rate for miscellaneous electricity, which is the single largest contributor to demand growth in many recent forecasts.

  15. Annual energy outlook 1995, with projections to 2010

    SciTech Connect (OSTI)

    1995-01-01

    The Annual Energy Outlook 1995 (AEO95) presents the midterm energy forecasts of the Energy Information Administration (EIA). This year`s report presents projections and analyses of energy supply, demand, and prices through 2010, based on results from the National Energy Modeling System (NEMS). Quarterly forecasts of energy supply and demand for 1995 and 1996 are published in the Short-Term Energy Outlook (February 1995). Forecast tables for the five cases examined in the AEO95 are provided in Appendixes A through C. Appendix A gives historical data and forecasts for selected years from 1992 through 2010 for the reference case. Appendix B presents two additional cases, which assume higher and lower economic growth than the reference case. Appendix C presents two cases that assume higher and lower world oil prices. Appendix D presents a summary of the forecasts in units of oil equivalence. Appendix E presents a summary of household energy expenditures. Appendix F provides detailed comparisons of the AEO95 forecasts with those of other organizations. Appendix G briefly describes NEMS and the major AEO95 forecast assumptions. Appendix H presents a stand-alone high electricity demand case. Appendix 1 provides a table of energy conversion factors and a table of metric conversion factors. 89 figs., 23 tabs.

  16. Survey of Variable Generation Forecasting in the West: August 2011 - June 2012

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2012-04-01

    This report surveyed Western Interconnection Balancing Authorities regarding their implementation of variable generation forecasting, the lessons learned to date, and recommendations they would offer to other Balancing Authorities who are considering variable generation forecasting. Our survey found that variable generation forecasting is at an early implementation stage in the West. Eight of the eleven Balancing Authorities interviewed began forecasting in 2008 or later. It also appears that less than one-half of the Balancing Authorities in the West are currently utilizing variable generation forecasting, suggesting that more Balancing Authorities in the West will engage in variable generation forecasting should more variable generation capacity be added.

  17. About Projects

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

    DOE Projects MicroBooNE Project Web Pages The Project Pages hold information and links for the collaboration and its Project Managers, and also hold links to project Director's and...

  18. Impacts of Improved Day-Ahead Wind Forecasts on Power Grid Operations: September 2011

    SciTech Connect (OSTI)

    Piwko, R.; Jordan, G.

    2011-11-01

    This study analyzed the potential benefits of improving the accuracy (reducing the error) of day-ahead wind forecasts on power system operations, assuming that wind forecasts were used for day ahead security constrained unit commitment.

  19. DOE Releases Latest Report on Energy Savings Forecast of Solid-State Lighting

    Broader source: Energy.gov [DOE]

    DOE has published a new report forecasting the energy savings of LED white-light sources compared with conventional white-light sources. The sixth iteration of the Energy Savings Forecast of Solid...

  20. Status of Centralized Wind Power Forecasting in North America: May 2009-May 2010

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2010-04-01

    Report surveys grid wind power forecasts for all wind generators, which are administered by utilities or regional transmission organizations (RTOs), typically with the assistance of one or more wind power forecasting companies.

  1. EERE Success Story-Solar Forecasting Gets a Boost from Watson...

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

    Forecasting Gets a Boost from Watson, Accuracy Improved by 30% EERE Success Story-Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% October 27, 2015 - 11:48am ...

  2. PROJECT PROFILE: EdgePower (Incubator 10) | Department of Energy

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

    EdgePower (Incubator 10) PROJECT PROFILE: EdgePower (Incubator 10) Project Title: Predictive Solar-Integrated Commercial Building Load Control Funding Opportunity: SunShot Technology to Market (Incubator 10) SunShot Subprogram: Technology to Market Location: Aspen, CO Amount Awarded: $495,248 Awardee Cost Share: $143,000 Project Investigator: Nathan Glasgow EdgePower is creating hardware and software solutions that will integrate the HVAC and lighting loads of a building with forecast data and

  3. 2011 DOE Project Management Workshop | Department of Energy

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

    DOE Project Management Workshop 2011 DOE Project Management Workshop Workshop Speakers and Presentations Paul Bosco, The New DOE O 413.3B Jeff Baker, EERE's Research Support Facility Patrick Ferraro, Contract Management/ Project Management Summit Outbrief Anirban Basu, Construction Economic Forecast John Curran, LED Lighting Michael Deane, Construction and Demolition Debris Recycle Mark Fallon, Leadership & Safety Cost Estimating Panel, The Science and Art of Cost Estimating Tom Fox, Leading

  4. Weather forecast-based optimization of integrated energy systems.

    SciTech Connect (OSTI)

    Zavala, V. M.; Constantinescu, E. M.; Krause, T.; Anitescu, M.

    2009-03-01

    In this work, we establish an on-line optimization framework to exploit detailed weather forecast information in the operation of integrated energy systems, such as buildings and photovoltaic/wind hybrid systems. We first discuss how the use of traditional reactive operation strategies that neglect the future evolution of the ambient conditions can translate in high operating costs. To overcome this problem, we propose the use of a supervisory dynamic optimization strategy that can lead to more proactive and cost-effective operations. The strategy is based on the solution of a receding-horizon stochastic dynamic optimization problem. This permits the direct incorporation of economic objectives, statistical forecast information, and operational constraints. To obtain the weather forecast information, we employ a state-of-the-art forecasting model initialized with real meteorological data. The statistical ambient information is obtained from a set of realizations generated by the weather model executed in an operational setting. We present proof-of-concept simulation studies to demonstrate that the proposed framework can lead to significant savings (more than 18% reduction) in operating costs.

  5. Weather Research and Forecasting Model with the Immersed Boundary Method

    Energy Science and Technology Software Center (OSTI)

    2012-05-01

    The Weather Research and Forecasting (WRF) Model with the immersed boundary method is an extension of the open-source WRF Model available for wwww.wrf-model.org. The new code modifies the gridding procedure and boundary conditions in the WRF model to improve WRF's ability to simutate the atmosphere in environments with steep terrain and additionally at high-resolutions.

  6. 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.

  7. Central Wind Power Forecasting Programs in North America by Regional Transmission Organizations and Electric Utilities

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2009-12-01

    The report addresses the implementation of central wind power forecasting by electric utilities and regional transmission organizations in North America.

  8. A Public-Private-Academic Partnership to Advance Solar Power Forecasting |

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

    Department of Energy A Public-Private-Academic Partnership to Advance Solar Power Forecasting A Public-Private-Academic Partnership to Advance Solar Power Forecasting UCAR logo2.jpg The University Corporation for Atmospheric Research (UCAR) will develop a solar power forecasting system that advances the state of the science through cutting-edge research. APPROACH UCAR value chain.png The team will develop a solar power forecasting system that advances the state of the science through

  9. Use of wind power forecasting in operational decisions.

    SciTech Connect (OSTI)

    Botterud, A.; Zhi, Z.; Wang, J.; Bessa, R.J.; Keko, H.; Mendes, J.; Sumaili, J.; Miranda, V.

    2011-11-29

    The rapid expansion of wind power gives rise to a number of challenges for power system operators and electricity market participants. The key operational challenge is to efficiently handle the uncertainty and variability of wind power when balancing supply and demand in ths system. In this report, we analyze how wind power forecasting can serve as an efficient tool toward this end. We discuss the current status of wind power forecasting in U.S. electricity markets and develop several methodologies and modeling tools for the use of wind power forecasting in operational decisions, from the perspectives of the system operator as well as the wind power producer. In particular, we focus on the use of probabilistic forecasts in operational decisions. Driven by increasing prices for fossil fuels and concerns about greenhouse gas (GHG) emissions, wind power, as a renewable and clean source of energy, is rapidly being introduced into the existing electricity supply portfolio in many parts of the world. The U.S. Department of Energy (DOE) has analyzed a scenario in which wind power meets 20% of the U.S. electricity demand by 2030, which means that the U.S. wind power capacity would have to reach more than 300 gigawatts (GW). The European Union is pursuing a target of 20/20/20, which aims to reduce greenhouse gas (GHG) emissions by 20%, increase the amount of renewable energy to 20% of the energy supply, and improve energy efficiency by 20% by 2020 as compared to 1990. Meanwhile, China is the leading country in terms of installed wind capacity, and had 45 GW of installed wind power capacity out of about 200 GW on a global level at the end of 2010. The rapid increase in the penetration of wind power into power systems introduces more variability and uncertainty in the electricity generation portfolio, and these factors are the key challenges when it comes to integrating wind power into the electric power grid. Wind power forecasting (WPF) is an important tool to help efficiently address this challenge, and significant efforts have been invested in developing more accurate wind power forecasts. In this report, we document our work on the use of wind power forecasting in operational decisions.

  10. Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison: Preprint

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.; Gomez-Lazaro, E.; Lovholm, A. L.; Berge, E.; Miettinen, J.; Holttinen, H.; Cutululis, N.; Litong-Palima, M.; Sorensen, P.; Dobschinski, J.

    2013-10-01

    One of the critical challenges of wind power integration is the variable and uncertain nature of the resource. This paper investigates the variability and uncertainty in wind forecasting for multiple power systems in six countries. An extensive comparison of wind forecasting is performed among the six power systems by analyzing the following scenarios: (i) wind forecast errors throughout a year; (ii) forecast errors at a specific time of day throughout a year; (iii) forecast errors at peak and off-peak hours of a day; (iv) forecast errors in different seasons; (v) extreme forecasts with large overforecast or underforecast errors; and (vi) forecast errors when wind power generation is at different percentages of the total wind capacity. The kernel density estimation method is adopted to characterize the distribution of forecast errors. The results show that the level of uncertainty and the forecast error distribution vary among different power systems and scenarios. In addition, for most power systems, (i) there is a tendency to underforecast in winter; and (ii) the forecasts in winter generally have more uncertainty than the forecasts in summer.

  11. HONEYWELL - KANSAS CITY PLANT FISCAL YEARS 2009 THRU 2015 SMALL BUSINESS PROGRAM RESULTS & FORECAST

    National Nuclear Security Administration (NNSA)

    HONEYWELL - KANSAS CITY PLANT FISCAL YEARS 2009 THRU 2015 SMALL BUSINESS PROGRAM RESULTS & FORECAST CATEGORY Total Procurement Total SB Small Disad. Bus Woman-Owned SB Hub-Zone SB Veteran-Owned SB Service Disabled Vet. SB FY 2009 Dollars Goal (projected) $183,949,920 $82,690,000 $4,550,000 $8,829,596 $3,370,000 $5,025,000 $460,000 FY 2009 Dollars Accomplished $143,846,731 $68,174,398 $9,247,214 $11,333,905 $4,979,858 $6,713,791 $1,612,136 FY 2009 % Goal 45.0% 2.5% 4.8% 1.8% 2.7% 0.25% FY

  12. Annual energy outlook 1994: With projections to 2010

    SciTech Connect (OSTI)

    Not Available

    1994-01-01

    The Annual Energy Outlook 1994 (AEO94) presents the midterm energy forecasts of the Energy Information Administration (EIA). This year`s report presents projects and analyses of energy supply, demand, and prices through 2010, based for the first time on results from the National Energy Modeling System (NEMS). NEMS is the latest in a series of computer-based energy modeling systems used over the past 2 decades by EIA and its predecessor organization, the Federal Energy Administration, to analyze and forecast energy consumption and supply in the midterm period (about 20 years). Quarterly forecasts of energy supply and demand for 1994 and 1995 are published in the Short-Term Energy Outlook (February 1994). Forecast tables for 2000, 2005, and 2010 for each of the five scenarios examined in the AEO94 are provided in Appendices A through E. The five scenarios include a reference case and four additional cases that assume higher and lower economic growth and higher and lower world oil prices. Appendix F provides detailed comparisons of the AEO94 forecasts with those of other organizations. Appendix G briefly described the NEMS and the major AEO94 forecast assumptions. Appendix H summarizes the key results for the five scenarios.

  13. NREL: Energy Analysis - Energy Forecasting and Modeling Staff

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

    Energy Forecasting and Modeling The following includes summary bios of staff expertise and interests in analysis relating to energy economics, energy system planning, risk and uncertainty modeling, and energy infrastructure planning. Team Lead: Nate Blair Administrative Support: Elizabeth Torres Clayton Barrows Dave Bielen Aaron Bloom Greg Brinkman Brian W Bush Stuart Cohen Wesley Cole Paul Denholm Victor Diakov Nicholas DiOrio Aron Dobos Kelly Eurek Janine Freeman Bethany Frew Pieter Gagnon

  14. NREL: Resource Assessment and Forecasting - Data and Resources

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

    Data and Resources National Solar Radiation Database NREL resource assessment and forecasting research information is available from the following sources. Renewable Resource Data Center (RReDC) Provides information about biomass, geothermal, solar, and wind energy resources. Measurement and Instrumentation Data Center Provides irradiance and meteorological data from stations throughout the United States. Baseline Measurement System (BMS) Provides live solar radiation data from approximately 70

  15. Towards a Science of Tumor Forecast for Clinical Oncology

    SciTech Connect (OSTI)

    Yankeelov, Tom; Quaranta, Vito; Evans, Katherine J; Rericha, Erin

    2015-01-01

    We propose that the quantitative cancer biology community make a concerted effort to apply the methods of weather forecasting to develop an analogous theory for predicting tumor growth and treatment response. Currently, the time course of response is not predicted, but rather assessed post hoc by physical exam or imaging methods. This fundamental limitation of clinical oncology makes it extraordinarily difficult to select an optimal treatment regimen for a particular tumor of 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. With a successful theory of tumor forecasting, it should be possible to integrate large tumor specific datasets of varied types, and effectively defeat cancer one patient at a time.

  16. SOLID WASTE INTEGRATED FORECAST TECHNICAL (SWIFT) REPORT FY2005 THRU FY2035 2005.0 VOLUME 2

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2005-08-17

    This report provides up-to-date life cycle information about the radioactive solid waste expected to be managed by Hanford's Waste Management (WM) Project from onsite and offsite generators. It includes: (1) an overview of Hanford-wide solid waste to be managed by the WM Project; (2) multi-level and waste class-specific estimates; (3) background information on waste sources; and (4) comparisons to previous forecasts and other national data sources. The focus of this report is low-level waste (LLW), mixed low-level waste (MLLW), and transuranic waste, both non-mixed and mixed (TRU(M)). Some details on hazardous waste are also provided, however, this information is not considered comprehensive. This report includes data requested in December, 2004 with updates through March 31,2005. The data represent a life cycle forecast covering all reported activities from FY2005 through the end of each program's life cycle and are an update of the previous FY2004.1 data version.

  17. Short and Long-Term Perspectives: The Impact on Low-Income Consumers of Forecasted Energy Price Increases in 2008 and A Cap & Trade Carbon Policy in 2030

    SciTech Connect (OSTI)

    Eisenberg, Joel Fred

    2008-01-01

    The Department of Energy's Energy Information Administration (EIA) recently released its short-term forecast for residential energy prices for the winter of 2007-2008. The forecast indicates increases in costs for low-income consumers in the year ahead, particularly for those using fuel oil to heat their homes. In the following analysis, the Oak Ridge National Laboratory has integrated the EIA price projections with the Residential Energy Consumption Survey (RECS) for 2001 in order to project the impact of these price increases on the nation's low-income households by primary heating fuel type, nationally and by Census Region. The report provides an update of bill estimates provided in a previous study, "The Impact Of Forecasted Energy Price Increases On Low-Income Consumers" (Eisenberg, 2005). The statistics are intended for use by policymakers in the Department of Energy's Weatherization Assistance Program and elsewhere who are trying to gauge the nature and severity of the problems that will be faced by eligible low-income households during the 2008 fiscal year. In addition to providing expenditure forecasts for the year immediately ahead, this analysis uses a similar methodology to give policy makers some insight into one of the major policy debates that will impact low-income energy expenditures well into the middle decades of this century and beyond. There is now considerable discussion of employing a cap-and-trade mechanism to first limit and then reduce U.S. emissions of carbon into the atmosphere in order to combat the long-range threat of human-induced climate change. The Energy Information Administration has provided an analysis of projected energy prices in the years 2020 and 2030 for one such cap-and-trade carbon reduction proposal that, when integrated with the RECS 2001 database, provides estimates of how low-income households will be impacted over the long term by such a carbon reduction policy.

  18. Accounting for fuel price risk: Using forward natural gas prices instead of gas price forecasts to compare renewable to natural gas-fired generation

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan; Golove, William

    2003-08-13

    Against the backdrop of increasingly volatile natural gas prices, renewable energy resources, which by their nature are immune to natural gas fuel price risk, provide a real economic benefit. Unlike many contracts for natural gas-fired generation, renewable generation is typically sold under fixed-price contracts. Assuming that electricity consumers value long-term price stability, a utility or other retail electricity supplier that is looking to expand its resource portfolio (or a policymaker interested in evaluating different resource options) should therefore compare the cost of fixed-price renewable generation to the hedged or guaranteed cost of new natural gas-fired generation, rather than to projected costs based on uncertain gas price forecasts. To do otherwise would be to compare apples to oranges: by their nature, renewable resources carry no natural gas fuel price risk, and if the market values that attribute, then the most appropriate comparison is to the hedged cost of natural gas-fired generation. Nonetheless, utilities and others often compare the costs of renewable to gas-fired generation using as their fuel price input long-term gas price forecasts that are inherently uncertain, rather than long-term natural gas forward prices that can actually be locked in. This practice raises the critical question of how these two price streams compare. If they are similar, then one might conclude that forecast-based modeling and planning exercises are in fact approximating an apples-to-apples comparison, and no further consideration is necessary. If, however, natural gas forward prices systematically differ from price forecasts, then the use of such forecasts in planning and modeling exercises will yield results that are biased in favor of either renewable (if forwards < forecasts) or natural gas-fired generation (if forwards > forecasts). In this report we compare the cost of hedging natural gas price risk through traditional gas-based hedging instruments (e.g., futures, swaps, and fixed-price physical supply contracts) to contemporaneous forecasts of spot natural gas prices, with the purpose of identifying any systematic differences between the two. Although our data set is quite limited, we find that over the past three years, forward gas prices for durations of 2-10 years have been considerably higher than most natural gas spot price forecasts, including the reference case forecasts developed by the Energy Information Administration (EIA). This difference is striking, and implies that resource planning and modeling exercises based on these forecasts over the past three years have yielded results that are biased in favor of gas-fired generation (again, presuming that long-term stability is desirable). As discussed later, these findings have important ramifications for resource planners, energy modelers, and policy-makers.

  19. Short-term energy outlook. Quarterly projections, Third quarter 1994

    SciTech Connect (OSTI)

    Not Available

    1994-08-02

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets. (See Short-Term Energy Outlook Annual Supplement, DOE/EIA-0202). The feature article for this issue is Demand, Supply and Price Outlook for Reformulated Gasoline, 1995.

  20. PROJECT PROFILE: Improving PV performance Estimates in the System Advisor

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

    Model with Component and System Reliability Metrics | Department of Energy Improving PV performance Estimates in the System Advisor Model with Component and System Reliability Metrics PROJECT PROFILE: Improving PV performance Estimates in the System Advisor Model with Component and System Reliability Metrics Funding Opportunity: SuNLaMP SunShot Subprogram: Photovoltaics Location: Sandia National Laboratories, Albuquerque, NM Amount Awarded: $600,000 This project will improve the forecasting

  1. Research Projects

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

    LaboratoryNational Security Education Center Menu NSEC Educational Programs Los Alamos Dynamics Summer School Science of Signatures Advanced Studies Institute Judicial Science School SHM Data Sets and Software Research Projects Current Projects Past Projects Publications NSEC » Engineering Institute » Research Projects » Joint Los Alamos National Laboratory/UCSD research projects Past Research Projects Previous collaborations between Los Alamos National Laboratory and the University of

  2. Research Projects

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

    Current Research Projects Joint Los Alamos National LaboratoryUCSD Research Projects Collaborations between Los Alamos National Laboratory and the University of California at San...

  3. Project Management

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

    Project Management Project Management MaRIE is the experimental facility needed to control the time-dependent properties of materials for national security science missions. It...

  4. Project Accounts

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

    Project Accounts Project Accounts A redirector page has been set up without anywhere to redirect to. Last edited: 2016-02-01 08:06:53

  5. Annual energy outlook 1999, with projections to 2020

    SciTech Connect (OSTI)

    1998-12-01

    The Annual Energy Outlook 1999 (AEO99) presents midterm forecasts of energy supply, demand, and prices through 2020 prepared by the Energy Information Administration (EIA). The projections are based on results from EIA`s National Energy Modeling System (NEMS). The report begins with an Overview summarizing the AEO99 reference case. The next section, Legislation and Regulations, describes the assumptions made with regard to laws that affect energy markets and discusses evolving legislative and regulatory issues. Issues in Focus discusses current energy issues--the economic decline in East Asia, growth in demand for natural gas, vehicle emissions standards, competitive electricity pricing, renewable portfolio standards, and carbon emissions. It is followed by the analysis of energy market trends. The analysis in AEO99 focuses primarily on a reference case and four other cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. Forecast tables for these cases are provided in Appendixes A through C. Appendixes D and E present a summary of the reference case forecasts in units of oil equivalence and household energy expenditures. The AEO99 projections are based on Federal, State, and local laws and regulations in effect on July 1, 1998. Pending legislation and sections of existing legislation for which funds have not been appropriated are not reflected in the forecasts. Historical data used for the AEOI99 projections were the most current available as of July 31, 1998, when most 1997 data but only partial 1998 data were available.

  6. 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.

  7. The Value of Improved Short-Term Wind Power Forecasting

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

    The Value of Improved Short- Term Wind Power Forecasting B.-M. Hodge and A. Florita National Renewable Energy Laboratory J. Sharp Sharply Focused, LLC M. Margulis and D. Mcreavy Lockheed Martin Technical Report NREL/TP-5D00-63175 February 2015 NREL is a national laboratory of the U.S. Department of Energy Office of Energy Efficiency & Renewable Energy Operated by the Alliance for Sustainable Energy, LLC This report is available at no cost from the National Renewable Energy Laboratory (NREL)

  8. Value of Improved Wind Power Forecasting in the Western Interconnection (Poster)

    SciTech Connect (OSTI)

    Hodge, B.

    2013-12-01

    Wind power forecasting is a necessary and important technology for incorporating wind power into the unit commitment and dispatch process. It is expected to become increasingly important with higher renewable energy penetration rates and progress toward the smart grid. There is consensus that wind power forecasting can help utility operations with increasing wind power penetration; however, there is far from a consensus about the economic value of improved forecasts. This work explores the value of improved wind power forecasting in the Western Interconnection of the United States.

  9. ARM - PI Product - CCPP-ARM Parameterization Testbed Model Forecast Data

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

    ProductsCCPP-ARM Parameterization Testbed Model Forecast Data 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 PI Product : CCPP-ARM Parameterization Testbed Model Forecast Data Dataset contains the NCAR CAM3 (Collins et al., 2004) and GFDL AM2 (GFDL GAMDT, 2004) forecast data at locations close to the ARM research sites. These data are generated from a series of multi-day forecasts in which both CAM3 and AM2 are

  10. Report of the external expert peer review panel: DOE benefits forecasts

    SciTech Connect (OSTI)

    None, None

    2006-12-20

    A report for the FY 2007 GPRA methodology review, highlighting the views of an external expert peer review panel on DOE benefits forecasts.

  11. Energy Forecast, ForskEL (Smart Grid Project) | Open Energy Informatio...

    Open Energy Info (EERE)

    meeting both the clients' demand for cost stability and at the same time encourages a demand response. 2. Lack of information and awareness about the possibilities and...

  12. Live Webinar on the Funding Opportunity for Wind Forecasting Improvement Project in Complex Terrain

    Broader source: Energy.gov [DOE]

    On April 21, 2014 from 3:00 to 5:00 PM EST the Wind Program will hold a live webinar to provide information to potential applicants for this Funding Opportunity Announcement. There is no cost to...

  13. Project Controls

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

    1997-03-28

    Project controls are systems used to plan, schedule, budget, and measure the performance of a project/program. The cost estimation package is one of the documents that is used to establish the baseline for project controls. This chapter gives a brief description of project controls and the role the cost estimation package plays.

  14. Project Information

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

    Project Information Slider award map The REE Program funds projects focused on developing economically feasible and environmentally benign technologies for recovering REEs from coal and/or coal by-products. Project Information The listed projects represent the current REE program portfolio. Agreement Number Project Title Performer Name FWP-ORD REE FY2016-2020 Rare Earth Elements (REE) from Coal and Coal By-Products National Energy Technology Laboratory

  15. Hawaii Energy Strategy: Program guide. [Contains special sections on analytical energy forecasting, renewable energy resource assessment, demand-side energy management, energy vulnerability assessment, and energy strategy integration

    SciTech Connect (OSTI)

    Not Available

    1992-09-01

    The Hawaii Energy Strategy program, or HES, is a set of seven projects which will produce an integrated energy strategy for the State of Hawaii. It will include a comprehensive energy vulnerability assessment with recommended courses of action to decrease Hawaii's energy vulnerability and to better prepare for an effective response to any energy emergency or supply disruption. The seven projects are designed to increase understanding of Hawaii's energy situation and to produce recommendations to achieve the State energy objectives of: Dependable, efficient, and economical state-wide energy systems capable of supporting the needs of the people, and increased energy self-sufficiency. The seven projects under the Hawaii Energy Strategy program include: Project 1: Develop Analytical Energy Forecasting Model for the State of Hawaii. Project 2: Fossil Energy Review and Analysis. Project 3: Renewable Energy Resource Assessment and Development Program. Project 4: Demand-Side Management Program. Project 5: Transportation Energy Strategy. Project 6: Energy Vulnerability Assessment Report and Contingency Planning. Project 7: Energy Strategy Integration and Evaluation System.

  16. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

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

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together intomore » larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.« less

  17. Analysis of Variability and Uncertainty in Wind Power Forecasting: An International Comparison (Presentation)

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B.; Miettinen, J.; Holttinen, H.; Gomez-Lozaro, E.; Cutululis, N.; Litong-Palima, M.; Sorensen, P.; Lovholm, A.; Berge, E.; Dobschinski, J.

    2013-10-01

    This presentation summarizes the work to investigate the uncertainty in wind forecasting at different times of year and compare wind forecast errors in different power systems using large-scale wind power prediction data from six countries: the United States, Finland, Spain, Denmark, Norway, and Germany.

  18. Energy Savings Forecast of Solid-State Lighting in General Illumination

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

    Applications | Department of Energy Forecast of Solid-State Lighting in General Illumination Applications Energy Savings Forecast of Solid-State Lighting in General Illumination Applications PDF icon energysavingsforecast14.pdf More Documents & Publications Energy Savings Potential of Solid-State Lighting in General Illumination Applications - Report LED ADOPTION REPORT Solid-State Lighting R&D

  19. 3D cloud detection and tracking system for solar forecast using multiple sky imagers

    SciTech Connect (OSTI)

    Peng, Zhenzhou; Yu, Dantong; Huang, Dong; Heiser, John; Yoo, Shinjae; Kalb, Paul

    2015-06-23

    We propose a system for forecasting short-term solar irradiance based on multiple total sky imagers (TSIs). The system utilizes a novel method of identifying and tracking clouds in three-dimensional space and an innovative pipeline for forecasting surface solar irradiance based on the image features of clouds. First, we develop a supervised classifier to detect clouds at the pixel level and output cloud mask. In the next step, we design intelligent algorithms to estimate the block-wise base height and motion of each cloud layer based on images from multiple TSIs. Thus, this information is then applied to stitch images together into larger views, which are then used for solar forecasting. We examine the system’s ability to track clouds under various cloud conditions and investigate different irradiance forecast models at various sites. We confirm that this system can 1) robustly detect clouds and track layers, and 2) extract the significant global and local features for obtaining stable irradiance forecasts with short forecast horizons from the obtained images. Finally, we vet our forecasting system at the 32-megawatt Long Island Solar Farm (LISF). Compared with the persistent model, our system achieves at least a 26% improvement for all irradiance forecasts between one and fifteen minutes.

  20. Line Projects

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

    Grand Coulee Transmission Line Replacement Project Hooper Springs McNary-John Day Montana-to-Washington Transmission System Upgrade Project - M2W Olympia-Grand Coulee No. 1...

  1. Short-term energy outlook: Quarterly projections. Second quarter 1995

    SciTech Connect (OSTI)

    1995-05-02

    The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent projections with those of other forecasting services, and discusses current topics related to the short-term energy markets. (See Short-Term Energy Outlook Annual Supplement, DOE/EIA-0202.) The forecast period for this issue of the Outlook extends from the second quarter of 1995 through the fourth quarter of 1996. Values for the first quarter of 1995, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data, compiled into the second quarter 1995 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS database is archived quarterly and is available from the National Technical Information Service.

  2. Project Gnome

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

    Project Gnome Double Beta Decay Dark Matter Biology Repository Science Renewable Energy The first underground physics experiment near Carlsbad was Project Gnome, December 10, 1961 Totally unrelated (and many years prior) to WIPP, the Project Gnome detonation was the first U.S. underground nuclear test with the objective of using nuclear explosives for peaceful applications. Project Gnome was intended to provide a detailed understanding of the underground environment created when a nuclear

  3. 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.

  4. 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.

  5. Weather Research and Forecasting Model with Vertical Nesting Capability

    Energy Science and Technology Software Center (OSTI)

    2014-08-01

    The Weather Research and Forecasting (WRF) model with vertical nesting capability is an extension of the WRF model, which is available in the public domain, from www.wrf-model.org. The new code modifies the nesting procedure, which passes lateral boundary conditions between computational domains in the WRF model. Previously, the same vertical grid was required on all domains, while the new code allows different vertical grids to be used on concurrently run domains. This new functionality improvesmore » WRF's ability to produce high-resolution simulations of the atmosphere by allowing a wider range of scales to be efficiently resolved and more accurate lateral boundary conditions to be provided through the nesting procedure.« less

  6. Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types, Notice of Data Availability

    Broader source: Energy.gov [DOE]

    Energy Conservation Program: Data Collection and Comparison with Forecasted Unit Sales for Five Lamp Types, Notice of Data Availability

  7. Final Report, 2011-2014. Forecasting Carbon Storage as Eastern Forests Age. Joining Experimental and Modeling Approaches at the UMBS AmeriFlux Site

    SciTech Connect (OSTI)

    Curtis, Peter; Bohrer, Gil; Gough, Christopher; Nadelhoffer, Knute

    2015-03-12

    At the University of Michigan Biological Station (UMBS) AmeriFlux sites (US-UMB and US-UMd), long-term C cycling measurements and a novel ecosystem-scale experiment are revealing physical, biological, and ecological mechanisms driving long-term trajectories of C cycling, providing new data for improving modeling forecasts of C storage in eastern forests. Our findings provide support for previously untested hypotheses that stand-level structural and biological properties constrain long-term trajectories of C storage, and that remotely sensed canopy structural parameters can substantially improve model forecasts of forest C storage. Through the Forest Accelerated Succession ExperimenT (FASET), we are directly testing the hypothesis that forest C storage will increase due to increasing structural and biological complexity of the emerging tree communities. Support from this project, 2011-2014, enabled us to incorporate novel physical and ecological mechanisms into ecological, meteorological, and hydrological models to improve forecasts of future forest C storage in response to disturbance, succession, and current and long-term climate variation

  8. Effects of the Financial Crisis on Photovoltaics: An Analysis of Changes in Market Forecasts from 2008 to 2009

    SciTech Connect (OSTI)

    Bartlett, J. E.; Margolis, R. M.; Jennings, C. E.

    2009-09-01

    To examine how the financial crisis has impacted expectations of photovoltaic production, demand and pricing over the next several years, we surveyed the market forecasts of industry analysts that had issued projections in 2008 and 2009. We find that the financial crisis has had a significant impact on the PV industry, primarily through increasing the cost and reducing the availability of investment into the sector. These effects have been more immediately experienced by PV installations than by production facilities, due to the different types and duration of investments, and thus PV demand has been reduced by a greater proportion than PV production. By reducing demand more than production, the financial crisis has accelerated previously expected PV overcapacity and resulting price declines.

  9. Comparison of AEO 2009 Natural Gas Price Forecast to NYMEX Futures Prices

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2009-01-28

    On December 17, 2008, the reference-case projections from Annual Energy Outlook 2009 (AEO 2009) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables can play in mitigating such risk. As such, we were curious to see how the latest AEO reference-case gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. Note that this memo pertains only to natural gas fuel price risk (i.e., the risk that natural gas prices might differ over the life of a gas-fired generation asset from what was expected when the decision to build the gas-fired unit was made). We do not take into consideration any of the other distinct attributes of gas-fired and renewable generation, such as dispatchability (or lack thereof), differences in capital costs and O&M expenses, or environmental externalities. A comprehensive comparison of different resource types--which is well beyond the scope of this memo--would need to account for differences in all such attributes, including fuel price risk. Furthermore, our analysis focuses solely on natural-gas-fired generation (as opposed to coal-fired or nuclear generation, for example), for several reasons: (1) price volatility has been more of a concern for natural gas than for other fuels used to generate power; (2) for environmental and other reasons, natural gas has, in recent years, been the fuel of choice among power plant developers; and (3) natural gas-fired generators often set the market clearing price in competitive wholesale power markets throughout the United States. That said, a more-complete analysis of how renewables mitigate fuel price risk would also need to consider coal, uranium, and other fuel prices. Finally, we caution readers about drawing inferences or conclusions based solely on this memo in isolation: to place the information contained herein within its proper context, we strongly encourage readers interested in this issue to read through our previous, more-detailed studies, available at http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf.

  10. Comparison of AEO 2008 Natural Gas Price Forecast to NYMEX Futures Prices

    SciTech Connect (OSTI)

    Bolinger, Mark A; Bolinger, Mark; Wiser, Ryan

    2008-01-07

    On December 12, 2007, the reference-case projections from Annual Energy Outlook 2008 (AEO 2008) were posted on the Energy Information Administration's (EIA) web site. We at LBNL have, in the past, compared the EIA's reference-case long-term natural gas price forecasts from the AEO series to contemporaneous natural gas prices that can be locked in through the forward market, with the goal of better understanding fuel price risk and the role that renewables can play in mitigating such risk. As such, we were curious to see how the latest AEO reference-case gas price forecast compares to the NYMEX natural gas futures strip. This brief memo presents our findings. Note that this memo pertains only to natural gas fuel price risk (i.e., the risk that natural gas prices might differ over the life of a gas-fired generation asset from what was expected when the decision to build the gas-fired unit was made). We do not take into consideration any of the other distinct attributes of gas-fired and renewable generation, such as dispatchability (or lack thereof) or environmental externalities. A comprehensive comparison of different resource types--which is well beyond the scope of this memo--would need to account for differences in all such attributes, including fuel price risk. Furthermore, our analysis focuses solely on natural-gas-fired generation (as opposed to coal-fired generation, for example), for several reasons: (1) price volatility has been more of a concern for natural gas than for other fuels used to generate power; (2) for environmental and other reasons, natural gas has, in recent years, been the fuel of choice among power plant developers (though its appeal has diminished somewhat as prices have increased); and (3) natural gas-fired generators often set the market clearing price in competitive wholesale power markets throughout the United States. That said, a more-complete analysis of how renewables mitigate fuel price risk would also need to consider coal and other fuel prices. Finally, we caution readers about drawing inferences or conclusions based solely on this memo in isolation: to place the information contained herein within its proper context, we strongly encourage readers interested in this issue to read through our previous, more-detailed studies, available at http://eetd.lbl.gov/ea/EMS/reports/53587.pdf or http://eetd.lbl.gov/ea/ems/reports/54751.pdf.

  11. An Optimized Autoregressive Forecast Error Generator for Wind and Load Uncertainty Study

    SciTech Connect (OSTI)

    De Mello, Phillip; Lu, Ning; Makarov, Yuri V.

    2011-01-17

    This paper presents a first-order autoregressive algorithm to generate real-time (RT), hour-ahead (HA), and day-ahead (DA) wind and load forecast errors. The methodology aims at producing random wind and load forecast time series reflecting the autocorrelation and cross-correlation of historical forecast data sets. Five statistical characteristics are considered: the means, standard deviations, autocorrelations, and cross-correlations. A stochastic optimization routine is developed to minimize the differences between the statistical characteristics of the generated time series and the targeted ones. An optimal set of parameters are obtained and used to produce the RT, HA, and DA forecasts in due order of succession. This method, although implemented as the first-order regressive random forecast error generator, can be extended to higher-order. Results show that the methodology produces random series with desired statistics derived from real data sets provided by the California Independent System Operator (CAISO). The wind and load forecast error generator is currently used in wind integration studies to generate wind and load inputs for stochastic planning processes. Our future studies will focus on reflecting the diurnal and seasonal differences of the wind and load statistics and implementing them in the random forecast generator.

  12. Review of Variable Generation Forecasting in the West: July 2013 - March 2014

    SciTech Connect (OSTI)

    Widiss, R.; Porter, K.

    2014-03-01

    This report interviews 13 operating entities (OEs) in the Western Interconnection about their implementation of wind and solar forecasting. The report updates and expands upon one issued by NREL in 2012. As in the 2012 report, the OEs interviewed vary in size and character; the group includes independent system operators, balancing authorities, utilities, and other entities. Respondents' advice for other utilities includes starting sooner rather than later as it can take time to plan, prepare, and train a forecast; setting realistic expectations; using multiple forecasts; and incorporating several performance metrics.

  13. Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% |

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

    Department of Energy Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% October 27, 2015 - 11:48am Addthis IBM Youtube Video | Courtesy of IBM Remember when IBM's super computer Watson defeated Jeopardy! champions Ken Jennings and Brad Rutter? With funding from the U.S. Department of Energy SunShot Initiative, IBM researchers are using Watson-like technology to improve solar forecasting accuracy by as much

  14. Research Projects

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

    structure whose behavior is fundamentally nonlinear. Thus, the students assigned to this project will develop control techniques that will allow an electrodynamic shake table to...

  15. Project Construction

    Office of Energy Efficiency and Renewable Energy (EERE)

    Integrating renewable energy into Federal new construction or major renovations requires effective structuring of the construction team and project schedule. This overview discusses key construction team considerations for renewable energy as well as timing and expectations for the construction phase. The project construction phase begins after a project is completely designed and the construction documents (100%) have been issued. Construction team skills and experience with renewable energy technologies are crucial during construction, as is how the integration of renewable energy affects the project construction schedule.

  16. project management

    National Nuclear Security Administration (NNSA)

    3%2A en Project Management and Systems Support http:www.nnsa.energy.govaboutusouroperationsapmprojectmanagementandsystemssupport

  17. Custom Projects

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

    Energy Management Small Industrial Lighting Compressed Air ESUE Motors Federal Agriculture Custom Projects No two industrial customers are alike; each has its own unique...

  18. project management

    National Nuclear Security Administration (NNSA)

    %2A en Project Management and Systems Support http:nnsa.energy.govaboutusouroperationsapmprojectmanagementandsystemssupport

  19. Project Tour

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

    Project Tour Transportation Transportation to the tour will be provided from Hilton Santa Fe Buffalo Thunder to Los Alamos National Laboratory, Technical Area 55. After the...

  20. Project Complete

    Broader source: Energy.gov [DOE]

    DOE has published its Record of Decision announcing and explaining DOE’s chosen project alternative and describing any commitments for mitigating potential environmental impacts. The NEPA process...

  1. Awarded projects

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

    projects Awarded projects 2016 Allocation Awards This page lists the allocation awards for NERSC for the 2016 allocation year (Jan 12, 2016 through Jan 09, 2017). Read More » Previous Year Awards Last edited: 2016-02-01 08:07:34

  2. Resource Information and Forecasting Group; Electricity, Resources, & Building Systems Integration (ERBSI) (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2009-11-01

    Researchers in the Resource Information and Forecasting group at NREL provide scientific, engineering, and analytical expertise to help characterize renewable energy resources and facilitate the integration of these clean energy sources into the electricity grid.

  3. Examining Information Entropy Approaches as Wind Power Forecasting Performance Metrics: Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Orwig, K.; Milligan, M.

    2012-06-01

    In this paper, we examine the parameters associated with the calculation of the Renyi entropy in order to further the understanding of its application to assessing wind power forecasting errors.

  4. Analysis and Synthesis of Load Forecasting Data for Renewable Integration Studies: Preprint

    SciTech Connect (OSTI)

    Steckler, N.; Florita, A.; Zhang, J.; Hodge, B. M.

    2013-11-01

    As renewable energy constitutes greater portions of the generation fleet, the importance of modeling uncertainty as part of integration studies also increases. In pursuit of optimal system operations, it is important to capture not only the definitive behavior of power plants, but also the risks associated with systemwide interactions. This research examines the dependence of load forecast errors on external predictor variables such as temperature, day type, and time of day. The analysis was utilized to create statistically relevant instances of sequential load forecasts with only a time series of historic, measured load available. The creation of such load forecasts relies on Bayesian techniques for informing and updating the model, thus providing a basis for networked and adaptive load forecast models in future operational applications.

  5. Short-Term Load Forecasting Error Distributions and Implications for Renewable Integration Studies: Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Lew, D.; Milligan, M.

    2013-01-01

    Load forecasting in the day-ahead timescale is a critical aspect of power system operations that is used in the unit commitment process. It is also an important factor in renewable energy integration studies, where the combination of load and wind or solar forecasting techniques create the net load uncertainty that must be managed by the economic dispatch process or with suitable reserves. An understanding of that load forecasting errors that may be expected in this process can lead to better decisions about the amount of reserves necessary to compensate errors. In this work, we performed a statistical analysis of the day-ahead (and two-day-ahead) load forecasting errors observed in two independent system operators for a one-year period. Comparisons were made with the normal distribution commonly assumed in power system operation simulations used for renewable power integration studies. Further analysis identified time periods when the load is more likely to be under- or overforecast.

  6. Ramping Effect on Forecast Use: Integrated Ramping as a Mitigation Strategy; NREL (National Renewable Energy Laboratory)

    SciTech Connect (OSTI)

    Diakov, Victor; Barrows, Clayton; Brinkman, Gregory; Bloom, Aaron; Denholm, Paul

    2015-06-23

    Power generation ramping between forecasted (net) load set-points shift the generation (MWh) from its scheduled values. The Integrated Ramping is described as a method that mitigates this problem.

  7. U.S. Crude Oil Production Forecast-Analysis of Crude Types

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

    of Energy Washington, DC 20585 U.S. Energy Information Administration | U.S. Crude Oil Production Forecast-Analysis of Crude Types i This report was prepared by the U.S....

  8. U.S. diesel fuel price forecast to be 1 penny lower this summer...

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

    That's down 12 percent from last summer's record exports. Biodiesel production, which averaged 68,000 barrels a day last summer, is forecast to jump to 82,000 barrels a day this ...

  9. NOAA Teams Up with Department of Energy & Industry to Improve Wind Forecasts

    Broader source: Energy.gov [DOE]

    The growth of wind-generated power in the United States  is creating greater demand for improved wind forecasts. To address this need, the Department of Energy is working with NOAA and industry on...

  10. Impact of Improved Solar Forecasts on Bulk Power System Operations in ISO-NE: Preprint

    SciTech Connect (OSTI)

    Brancucci Martinez-Anido, C.; Florita, A.; Hodge, B. M.

    2014-09-01

    The diurnal nature of solar power is made uncertain by variable cloud cover and the influence of atmospheric conditions on irradiance scattering processes. Its forecasting has become increasingly important to the unit commitment and dispatch process for efficient scheduling of generators in power system operations. This study examines the value of improved solar power forecasting for the Independent System Operator-New England system. The results show how 25% solar power penetration reduces net electricity generation costs by 22.9%.

  11. Forecasting Wind and Solar Generation: Improving System Operations, Greening the Grid

    SciTech Connect (OSTI)

    2016-01-01

    This document discusses improving system operations with forecasting and solar generation. By integrating variable renewable energy (VRE) forecasts into system operations, power system operators can anticipate up- and down-ramps in VRE generation in order to cost-effectively balance load and generation in intra-day and day-ahead scheduling. This leads to reduced fuel costs, improved system reliability, and maximum use of renewable resources.

  12. Investigating the Correlation Between Wind and Solar Power Forecast Errors in the Western Interconnection: Preprint

    SciTech Connect (OSTI)

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

    2013-05-01

    Wind and solar power generations differ from conventional energy generation because of the variable and uncertain nature of their power output. This variability and uncertainty can have significant impacts on grid operations. Thus, short-term forecasting of wind and solar generation is uniquely helpful for power system operations to balance supply and demand in an electricity system. This paper investigates the correlation between wind and solar power forecasting errors.

  13. Nuclear Theory Helps Forecast Neutron Star Temperatures | U.S. DOE Office

    Office of Science (SC) Website

    of Science (SC) Nuclear Theory Helps Forecast Neutron Star Temperatures Nuclear Physics (NP) NP Home About Research Facilities Science Highlights Benefits of NP Funding Opportunities Nuclear Science Advisory Committee (NSAC) Community Resources Contact Information Nuclear Physics U.S. Department of Energy SC-26/Germantown Building 1000 Independence Ave., SW Washington, DC 20585 P: (301) 903-3613 F: (301) 903-3833 E: Email Us More Information » 05.01.14 Nuclear Theory Helps Forecast Neutron

  14. U.S. Department of Energy Workshop Report: Solar Resources and Forecasting

    SciTech Connect (OSTI)

    Stoffel, T.

    2012-06-01

    This report summarizes the technical presentations, outlines the core research recommendations, and augments the information of the Solar Resources and Forecasting Workshop held June 20-22, 2011, in Golden, Colorado. The workshop brought together notable specialists in atmospheric science, solar resource assessment, solar energy conversion, and various stakeholders from industry and academia to review recent developments and provide input for planning future research in solar resource characterization, including measurement, modeling, and forecasting.

  15. Solar energy conversion: Technological forecasting. (Latest citations from the Aerospace database). Published Search

    SciTech Connect (OSTI)

    Not Available

    1993-12-01

    The bibliography contains citations concerning current forecasting of Earth surface-bound solar energy conversion technology. Topics consider research, development and utilization of this technology in relation to electric power generation, heat pumps, bioconversion, process heat and the production of renewable gaseous, liquid, and solid fuels for industrial, commercial, and domestic applications. Some citations concern forecasts which compare solar technology with other energy technologies. (Contains 250 citations and includes a subject term index and title list.)

  16. Solar energy conversion: Technological forecasting. (Latest citations from the Aerospace database). Published Search

    SciTech Connect (OSTI)

    1995-01-01

    The bibliography contains citations concerning current forecasting of Earth surface-bound solar energy conversion technology. Topics consider research, development and utilization of this technology in relation to electric power generation, heat pumps, bioconversion, process heat and the production of renewable gaseous, liquid, and solid fuels for industrial, commercial, and domestic applications. Some citations concern forecasts which compare solar technology with other energy technologies. (Contains 250 citations and includes a subject term index and title list.)

  17. Impact of Improved Solar Forecasts on Bulk Power System Operations in ISO-NE (Presentation)

    SciTech Connect (OSTI)

    Brancucci Martinez-Anido, C.; Florita, A.; Hodge, B.M.

    2014-11-01

    The diurnal nature of solar power is made uncertain by variable cloud cover and the influence of atmospheric conditions on irradiance scattering processes. Its forecasting has become increasingly important to the unit commitment and dispatch process for efficient scheduling of generators in power system operations. This presentation is an overview of a study that examines the value of improved solar forecasts on Bulk Power System Operations.

  18. DOE Announces Webinars on Solar Forecasting Metrics, the DOE Wind Vision,

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

    and More | Department of Energy Solar Forecasting Metrics, the DOE Wind Vision, and More DOE Announces Webinars on Solar Forecasting Metrics, the DOE Wind Vision, and More February 12, 2014 - 7:38pm Addthis EERE offers webinars to the public on a range of subjects, from adopting the latest energy efficiency and renewable energy technologies to training for the clean energy workforce. Webinars are free; however, advanced registration is typically required. You can also watch archived webinars

  19. Short-Term Energy Carbon Dioxide Emissions Forecasts August 2009

    Reports and Publications (EIA)

    2009-01-01

    Supplement to the Short-Term Energy Outlook. Short-term projections for U.S. carbon dioxide emissions of the three fossil fuels: coal, natural gas, and petroleum.

  20. Wind Power Forecasting Error Frequency Analyses for Operational Power System Studies: Preprint

    SciTech Connect (OSTI)

    Florita, A.; Hodge, B. M.; Milligan, M.

    2012-08-01

    The examination of wind power forecasting errors is crucial for optimal unit commitment and economic dispatch of power systems with significant wind power penetrations. This scheduling process includes both renewable and nonrenewable generators, and the incorporation of wind power forecasts will become increasingly important as wind fleets constitute a larger portion of generation portfolios. This research considers the Western Wind and Solar Integration Study database of wind power forecasts and numerical actualizations. This database comprises more than 30,000 locations spread over the western United States, with a total wind power capacity of 960 GW. Error analyses for individual sites and for specific balancing areas are performed using the database, quantifying the fit to theoretical distributions through goodness-of-fit metrics. Insights into wind-power forecasting error distributions are established for various levels of temporal and spatial resolution, contrasts made among the frequency distribution alternatives, and recommendations put forth for harnessing the results. Empirical data are used to produce more realistic site-level forecasts than previously employed, such that higher resolution operational studies are possible. This research feeds into a larger work of renewable integration through the links wind power forecasting has with various operational issues, such as stochastic unit commitment and flexible reserve level determination.

  1. RENOTER Project

    Broader source: Energy.gov [DOE]

    Overview of French project on thermoelectric waste heat recovery for cars and trucks with focus on cheap, available, efficient, and sustainable TE materials, as well as efficient material integration and production process.

  2. Research Projects

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

    Research Projects Joint Los Alamos National Laboratory/UCSD Research Projects Collaborations between Los Alamos National Laboratory and the University of California at San Diego (UCSD) Jacobs School of Engineering Contact Institute Director Charles Farrar (505) 663-5330 Email UCSD EI Director Michael Todd (858) 534-5951 Professional Staff Assistant Jutta Kayser (505) 663-5649 Email Administrative Assistant Stacy Baker (505) 663-5233 Email "Since 2003, LANL has funded numerous collaborative

  3. Enhancing Cloud Radiative Processes and Radiation Efficiency in the Advanced Research Weather Research and Forecasting (WRF) Model

    SciTech Connect (OSTI)

    Iacono, Michael J.

    2015-03-09

    The objective of this research has been to evaluate and implement enhancements to the computational performance of the RRTMG radiative transfer option in the Advanced Research version of the Weather Research and Forecasting (WRF) model. Efficiency is as essential as accuracy for effective numerical weather prediction, and radiative transfer is a relatively time-consuming component of dynamical models, taking up to 30-50 percent of the total model simulation time. To address this concern, this research has implemented and tested a version of RRTMG that utilizes graphics processing unit (GPU) technology (hereinafter RRTMGPU) to greatly improve its computational performance; thereby permitting either more frequent simulation of radiative effects or other model enhancements. During the early stages of this project the development of RRTMGPU was completed at AER under separate NASA funding to accelerate the code for use in the Goddard Space Flight Center (GSFC) Goddard Earth Observing System GEOS-5 global model. It should be noted that this final report describes results related to the funded portion of the originally proposed work concerning the acceleration of RRTMG with GPUs in WRF. As a k-distribution model, RRTMG is especially well suited to this modification due to its relatively large internal pseudo-spectral (g-point) dimension that, when combined with the horizontal grid vector in the dynamical model, can take great advantage of the GPU capability. Thorough testing under several model configurations has been performed to ensure that RRTMGPU improves WRF model run time while having no significant impact on calculated radiative fluxes and heating rates or on dynamical model fields relative to the RRTMG radiation. The RRTMGPU codes have been provided to NCAR for possible application to the next public release of the WRF forecast model.

  4. Wind power forecasting : state-of-the-art 2009.

    SciTech Connect (OSTI)

    Monteiro, C.; Bessa, R.; Miranda, V.; Botterud, A.; Wang, J.; Conzelmann, G.; Decision and Information Sciences; INESC Porto

    2009-11-20

    Many countries and regions are introducing policies aimed at reducing the environmental footprint from the energy sector and increasing the use of renewable energy. In the United States, a number of initiatives have been taken at the state level, from renewable portfolio standards (RPSs) and renewable energy certificates (RECs), to regional greenhouse gas emission control schemes. Within the U.S. Federal government, new energy and environmental policies and goals are also being crafted, and these are likely to increase the use of renewable energy substantially. The European Union is pursuing implementation of its ambitious 20/20/20 targets, which aim (by 2020) to reduce greenhouse gas emissions by 20% (as compared to 1990), increase the amount of renewable energy to 20% of the energy supply, and reduce the overall energy consumption by 20% through energy efficiency. With the current focus on energy and the environment, efficient integration of renewable energy into the electric power system is becoming increasingly important. In a recent report, the U.S. Department of Energy (DOE) describes a model-based scenario, in which wind energy provides 20% of the U.S. electricity demand in 2030. The report discusses a set of technical and economic challenges that have to be overcome for this scenario to unfold. In Europe, several countries already have a high penetration of wind power (i.e., in the range of 7 to 20% of electricity consumption in countries such as Germany, Spain, Portugal, and Denmark). The rapid growth in installed wind power capacity is expected to continue in the United States as well as in Europe. A large-scale introduction of wind power causes a number of challenges for electricity market and power system operators who will have to deal with the variability and uncertainty in wind power generation when making their scheduling and dispatch decisions. Wind power forecasting (WPF) is frequently identified as an important tool to address the variability and uncertainty in wind power and to more efficiently operate power systems with large wind power penetrations. Moreover, in a market environment, the wind power contribution to the generation portofolio becomes important in determining the daily and hourly prices, as variations in the estimated wind power will influence the clearing prices for both energy and operating reserves. With the increasing penetration of wind power, WPF is quickly becoming an important topic for the electric power industry. System operators (SOs), generating companies (GENCOs), and regulators all support efforts to develop better, more reliable and accurate forecasting models. Wind farm owners and operators also benefit from better wind power prediction to support competitive participation in electricity markets against more stable and dispatchable energy sources. In general, WPF can be used for a number of purposes, such as: generation and transmission maintenance planning, determination of operating reserve requirements, unit commitment, economic dispatch, energy storage optimization (e.g., pumped hydro storage), and energy trading. The objective of this report is to review and analyze state-of-the-art WPF models and their application to power systems operations. We first give a detailed description of the methodologies underlying state-of-the-art WPF models. We then look at how WPF can be integrated into power system operations, with specific focus on the unit commitment problem.

  5. DOE Project Scorecards

    Broader source: Energy.gov [DOE]

    DOE Project Scorecards DOE project scorecards summarize capital asset project performance compared to the current approved baseline. 

  6. WindSENSE Project Summary: FY2009-2011

    SciTech Connect (OSTI)

    Kamath, C

    2011-09-25

    Renewable resources, such as wind and solar, are providing an increasingly larger percentage of our energy needs. To successfully integrate these intermittent resources into the power grid while maintaining its reliability, we need to better understand the characteristics and predictability of the variability associated with these power generation resources. WindSENSE, a three year project at Lawrence Livermore National Laboratory, considered the problem of scheduling wind energy on the grid from the viewpoint of the control room operator. Our interviews with operators at Bonneville Power Administration (BPA), Southern California Edison (SCE), and California Independent System Operator (CaISO), indicated several challenges to integrating wind power generation into the grid. As the percentage of installed wind power has increased, the variable nature of the generation has become a problem. For example, in the Bonneville Power Administration (BPA) balancing area, the installed wind capacity has increased from 700 MW in 2006-2007 to over 1300 MW in 2008 and more than 2600 MW in 2009. To determine the amount of energy to schedule for the hours ahead, operators typically use 0-6 hour ahead forecasts, along with the actual generation in the previous hours and days. These forecasts are obtained from numerical weather prediction (NWP) simulations or based on recent trends in wind speed in the vicinity of the wind farms. However, as the wind speed can be difficult to predict, especially in a region with complex terrain, the forecasts can be inaccurate. Complicating matters are ramp events, where the generation suddenly increases or decreases by a large amount in a short time (Figure 1, right panel). These events are challenging to predict, and given their short duration, make it difficult to keep the load and the generation balanced. Our conversations with BPA, SCE, and CaISO indicated that control room operators would like (1) more accurate wind power generation forecasts for use in scheduling and (2) additional information that can be exploited when the forecasts do not match the actual generation. To achieve this, WindSENSE had two areas of focus: (1) analysis of historical data for better insights, and (2) observation targeting for improved forecasts. The goal was to provide control room operators with an awareness of wind conditions and energy forecasts so they can make well-informed scheduling decisions, especially in the case of extreme events such as ramps.

  7. The PROJECT

    Office of Scientific and Technical Information (OSTI)

    PROJECT Copies of this publication are available while supply lasts from the Office of Scientific and Technical Information P.O. Box 62 Oak Ridge, TN 37831 Attention: Information Services Telephone: (423) 576-8401 Also Available: The United States Department of Energy: A Summary History, 1977-1994 @ Printed with soy ink on recycled paper The PROJECT U N I T E D S T A T E S D E P A R T M E N T O F E N E R G Y F.G. Gosling History Division Executive Secretariat Management and Administration

  8. (SSS)GAO Metrics - Project Success 2015-04-29 1100.xls

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

    Second Quarter Overall Root Cause Analysis (RCA)/Corrective Action Plan (CAP) Performance Metrics No. Contract/Project Management Performance Metrics FY 2015 Target FY 2015 Pre- & Post- CAP* Forecast Comment 1 Capital Asset Project Success: Complete 90% of capital asset projects at original scope and within 110% of CD-2 TPC. 90% 100% Pre-CAP 77% Post-CAP Based on 3-year rolling period (FY13 to FY15). TPC is Total Project Cost. No. FY 2015 Target FY 2015 2nd Qtr Actual 2 95% 85% 3 95% 98% 4

  9. Optimization Based Data Mining Approah for Forecasting Real-Time Energy Demand

    SciTech Connect (OSTI)

    Omitaomu, Olufemi A; Li, Xueping; Zhou, Shengchao

    2015-01-01

    The worldwide concern over environmental degradation, increasing pressure on electric utility companies to meet peak energy demand, and the requirement to avoid purchasing power from the real-time energy market are motivating the utility companies to explore new approaches for forecasting energy demand. Until now, most approaches for forecasting energy demand rely on monthly electrical consumption data. The emergence of smart meters data is changing the data space for electric utility companies, and creating opportunities for utility companies to collect and analyze energy consumption data at a much finer temporal resolution of at least 15-minutes interval. While the data granularity provided by smart meters is important, there are still other challenges in forecasting energy demand; these challenges include lack of information about appliances usage and occupants behavior. Consequently, in this paper, we develop an optimization based data mining approach for forecasting real-time energy demand using smart meters data. The objective of our approach is to develop a robust estimation of energy demand without access to these other building and behavior data. Specifically, the forecasting problem is formulated as a quadratic programming problem and solved using the so-called support vector machine (SVM) technique in an online setting. The parameters of the SVM technique are optimized using simulated annealing approach. The proposed approach is applied to hourly smart meters data for several residential customers over several days.

  10. PROJECT MANAGEMENT PLANS Project Management Plans

    Office of Environmental Management (EM)

    MANAGEMENT PLANS Project Management Plans  Overview  Project Management Plan Suggested Outline Subjects  Crosswalk between the Suggested PMP Outline Subjects and a Listing of Project Planning Elements  Elements of Deactivation Project Planning  Examples From Project Management Plans Overview The purpose here is to assist project managers and project planners in creating a project plan by providing examples and pointing to information that have been successfully used by others in

  11. World Energy Projection System model documentation

    SciTech Connect (OSTI)

    Hutzler, M.J.; Anderson, A.T.

    1997-09-01

    The World Energy Projection System (WEPS) was developed by the Office of Integrated Analysis and Forecasting within the Energy Information Administration (EIA), the independent statistical and analytical agency of the US Department of Energy. WEPS is an integrated set of personal computer based spreadsheets containing data compilations, assumption specifications, descriptive analysis procedures, and projection models. The WEPS accounting framework incorporates projections from independently documented models and assumptions about the future energy intensity of economic activity (ratios of total energy consumption divided by gross domestic product GDP), and about the rate of incremental energy requirements met by natural gas, coal, and renewable energy sources (hydroelectricity, geothermal, solar, wind, biomass, and other renewable resources). Projections produced by WEPS are published in the annual report, International Energy Outlook. This report documents the structure and procedures incorporated in the 1998 version of the WEPS model. It has been written to provide an overview of the structure of the system and technical details about the operation of each component of the model for persons who wish to know how WEPS projections are produced by EIA.

  12. Hydropower Projects

    SciTech Connect (OSTI)

    2015-04-02

    The Water Power Program helps industry harness this renewable, emissions-free resource to generate environmentally sustainable and cost-effective electricity. Through support for public, private, and nonprofit efforts, the Water Power Program promotes the development, demonstration, and deployment of advanced hydropower devices and pumped storage hydropower applications. These technologies help capture energy stored by diversionary structures, increase the efficiency of hydroelectric generation, and use excess grid energy to replenish storage reserves for use during periods of peak electricity demand. In addition, the Water Power Program works to assess the potential extractable energy from domestic water resources to assist industry and government in planning for our nation’s energy future. From FY 2008 to FY 2014, DOE’s Water Power Program announced awards totaling approximately $62.5 million to 33 projects focused on hydropower. Table 1 provides a brief description of these projects.

  13. Gasoline price forecast to stay below 3 dollar a gallon in 2015

    Gasoline and Diesel Fuel Update (EIA)

    Gasoline price forecast to stay below $3 a gallon in 2015 The national average pump price of gasoline is expected to stay below $3 per gallon during 2015. In its new monthly forecast, the U.S. Energy Information Administration said the retail price for regular gasoline should average $2.33 per gallon this year. The price of gasoline increased in early February after falling for 17 weeks in a row. But gasoline prices will continue to remain low in 2015 when compared with pump prices in recent

  14. EERE Success Story-Solar Forecasting Gets a Boost from Watson, Accuracy

    Office of Environmental Management (EM)

    Improved by 30% | Department of Energy Forecasting Gets a Boost from Watson, Accuracy Improved by 30% EERE Success Story-Solar Forecasting Gets a Boost from Watson, Accuracy Improved by 30% October 27, 2015 - 11:48am Addthis IBM Youtube Video | Courtesy of IBM Remember when IBM's super computer Watson defeated Jeopardy! champions Ken Jennings and Brad Rutter? With funding from the U.S. Department of Energy SunShot Initiative, IBM researchers are using Watson-like technology to improve solar

  15. Research Projects

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

    Past Research Projects Composite-to-Steel Joint Integrity Monitoring and Assessment Collaboration between Los Alamos National Laboratory and the University of California at San Diego (UCSD) Jacobs School of Engineering Contact Institute Director Charles Farrar (505) 663-5330 Email UCSD EI Director Michael Todd (858) 534-5951 Professional Staff Assistant Ellie Vigil (505) 667-2818 Email Administrative Assistant Rebecca Duran (505) 665-8899 Email UCSD Faculty and Graduate Students Professor

  16. MONTICELLO PROJECTS

    Office of Legacy Management (LM)

    09 January 2010 Doc. No. S06172 Page 1 1.3 Peripheral Properties (Private and City-Owned) * No land use or supplemental standards compliance issues were observed or reported by LTSM on-site staff. Monticello National Priorities List Sites Federal Facilities Agreement (FFA) Quarterly Report: October 1-December 31, 2009 This report summarizes project status and activities implemented October through December 2009, and provides a schedule of near-term activities for the Monticello Mill Tailings

  17. MONTICELLO PROJECTS

    Office of Legacy Management (LM)

    1 July 2011 Doc. No. S07978 Page 1 Monticello, Utah, National Priorities List Sites Federal Facility Agreement (FFA) Quarterly Report: April 1-June 30, 2011 This report summarizes project status and activities implemented April through June 2011 and provides a schedule for near-term activities at the Monticello Vicinity Properties (MVP) site and the Monticello Mill Tailings Site (MMTS) located in and near Monticello, Utah. The MMTS and MVP were placed on the U.S. Environmental Protection Agency

  18. MONTICELLO PROJECTS

    Office of Legacy Management (LM)

    31, 2011 April 2011 Doc. No. S07666 Page 1 Monticello, Utah, National Priorities List Sites Federal Facility Agreement (FFA) Quarterly Report: January 1-March 31, 2011 This report summarizes project status and activities implemented January through March 2011 and provides a schedule for near-term activities at the Monticello Vicinity Properties (MVP) site and the Monticello Mill Tailings Site (MMTS) located in and near Monticello, Utah. The MMTS and MVP were placed on the U.S. Environmental

  19. Hallmark Project

    Office of Environmental Management (EM)

    Project Commercialization of the Secure SCADA Communications Protocol, a cryptographic security solution for device-to-device communication Increased connectivity and automation in the control systems that manage the nation's energy infrastructure have improved system functionality, but left systems more vulnerable to cyber attack. Intruders could severely disrupt control system operation by sending fabricated information or commands to control system devices. To ensure message integrity,

  20. PROJECT MANGEMENT PLAN EXAMPLES Project Organization Examples

    Office of Environmental Management (EM)

    Organization Examples Example 8 4.0 PROJECT ORGANIZATION Chapter 4.0 describes the principle project organizations, including their responsibilities and relationships. Other organizations, that have an interest in the project, also are described. 4.1 Principal Project Organizations and Responsibilities The management organization for the 324/327 Buildings Stabilization/Deactivation Project represents a partnership between four principal project organizations responsible for the project. The four

  1. MHK Projects/Manchac Point Project | Open Energy Information

    Open Energy Info (EERE)

    el":"","visitedicon":"" Project Profile Project Start Date 112008 Project City St Gabriel, LA Project StateProvince Louisiana Project Country United States Project Resource...

  2. MHK Projects/Claiborne Island Project | Open Energy Information

    Open Energy Info (EERE)

    el":"","visitedicon":"" Project Profile Project Start Date 112008 Project City St Gabriel, LA Project StateProvince Louisiana Project Country United States Project Resource...

  3. MHK Projects/Point Pleasant Project | Open Energy Information

    Open Energy Info (EERE)

    el":"","visitedicon":"" Project Profile Project Start Date 112008 Project City St Gabriel, LA Project StateProvince Louisiana Project Country United States Project Resource...

  4. MHK Projects/College Point Project | Open Energy Information

    Open Energy Info (EERE)

    bel":"","visitedicon":"" Project Profile Project Start Date 112008 Project City St James, LA Project StateProvince Louisiana Project Country United States Project Resource...

  5. SOLID WASTE INTEGRATED FORECAST TECHNICAL (SWIFT) REPORT FY2003 THRU FY2046 VERSION 2003.1 VOLUME 2 [SEC 1 & 2

    SciTech Connect (OSTI)

    BARCOT, R.A.

    2003-12-01

    This report includes data requested on September 10, 2002 and includes radioactive solid waste forecasting updates through December 31, 2002. The FY2003.0 request is the primary forecast for fiscal year FY 2003.

  6. FUSRAP Project

    Office of Legacy Management (LM)

    Project 23b 14501 FUSRAP TECHNICAL BULLETIN N O . - R 3 v . L DATE: 1.2 9-99 SUBJECT : Pr.pec.d BY T r m L u d Approval Summary of the results for the Springdale characterization activities performed per WI-94-015, Rev. 0. TUO separate radiological characterization surveys and a limited cherical characterization survey were performed on the Springdale Site in Octcjer and December, 1993. The design of the radiological surveys were to supplement and define existing ORNL surveys. The limited

  7. Enhanced Short-Term Wind Power Forecasting and Value to Grid Operations: Preprint

    SciTech Connect (OSTI)

    Orwig, K.; Clark, C.; Cline, J.; Benjamin, S.; Wilczak, J.; Marquis, M.; Finley, C.; Stern, A.; Freedman, J.

    2012-09-01

    The current state of the art of wind power forecasting in the 0- to 6-hour time frame has levels of uncertainty that are adding increased costs and risk on the U.S. electrical grid. It is widely recognized within the electrical grid community that improvements to these forecasts could greatly reduce the costs and risks associated with integrating higher penetrations of wind energy. The U.S. Department of Energy has sponsored a research campaign in partnership with the National Oceanic and Atmospheric Administration (NOAA) and private industry to foster improvements in wind power forecasting. The research campaign involves a three-pronged approach: 1) a 1-year field measurement campaign within two regions; 2) enhancement of NOAA's experimental 3-km High-Resolution Rapid Refresh (HRRR) model by assimilating the data from the field campaign; and 3) evaluation of the economic and reliability benefits of improved forecasts to grid operators. This paper and presentation provides an overview of the regions selected, instrumentation deployed, data quality and control, assimilation of data into HRRR, and preliminary results of HRRR performance analysis.

  8. Ecological Forecasting in Chesapeake Bay: Using a Mechanistic-Empirical Modelling Approach

    SciTech Connect (OSTI)

    Brown, C. W.; Hood, Raleigh R.; Long, Wen; Jacobs, John M.; Ramers, D. L.; Wazniak, C.; Wiggert, J. D.; Wood, R.; Xu, J.

    2013-09-01

    The Chesapeake Bay Ecological Prediction System (CBEPS) automatically generates daily nowcasts and three-day forecasts of several environmental variables, such as sea-surface temperature and salinity, the concentrations of chlorophyll, nitrate, and dissolved oxygen, and the likelihood of encountering several noxious species, including harmful algal blooms and water-borne pathogens, for the purpose of monitoring the Bay's ecosystem. While the physical and biogeochemical variables are forecast mechanistically using the Regional Ocean Modeling System configured for the Chesapeake Bay, the species predictions are generated using a novel mechanistic empirical approach, whereby real-time output from the coupled physical biogeochemical model drives multivariate empirical habitat models of the target species. The predictions, in the form of digital images, are available via the World Wide Web to interested groups to guide recreational, management, and research activities. Though full validation of the integrated forecasts for all species is still a work in progress, we argue that the mechanistic–empirical approach can be used to generate a wide variety of short-term ecological forecasts, and that it can be applied in any marine system where sufficient data exist to develop empirical habitat models. This paper provides an overview of this system, its predictions, and the approach taken.

  9. Annual energy outlook 1997 with projections to 2015

    SciTech Connect (OSTI)

    1996-12-01

    The Annual Energy Outlook 1997 (AEO97) presents midterm forecasts of energy supply, demand, and prices through 2015 prepared by the Energy Information Administration (EIA). These projections are based on results of EIA`s National Energy Modeling System (NEMS). This report begins with a summary of the reference case, followed by a discussion of the legislative assumptions and evolving legislative and regulatory issues. ``Issues in Focus`` discusses emerging energy issues and other topics of particular interest. It is followed by the analysis of energy market trends. The analysis in AEO97 focuses primarily on a reference case and four other cases that assume higher and lower economic growth and higher and lower world oil prices than in the reference case. Forecast tables for these cases are provided in Appendixes A through C. Appendixes D and E present summaries of the reference case forecasts in units of oil equivalence and household energy expenditures. Twenty-three other cases explore the impacts of varying key assumptions in NEMS--generally, technology penetration, with the major results shown in Appendix F. Appendix G briefly describes NEMS and the major AEO97 assumptions, with a summary table. 114 figs., 22 tabs.

  10. Capital Project Prioritization

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

    Capital-Project-Prioritization Sign In About | Careers | Contact | Investors | bpa.gov Search News & Us Expand News & Us Projects & Initiatives Expand Projects &...

  11. Project Grandmaster

    Energy Science and Technology Software Center (OSTI)

    2013-09-16

    The purpose of the Project Grandmaster Application is to allow individuals to opt-in and give the application access to data sources about their activities on social media sites. The application will cross-reference these data sources to build up a picture of each individual activities they discuss, either at present or in the past, and place this picture in reference to groups of all participants. The goal is to allow an individual to place themselves inmore » the collective and to understand how their behavior patterns fit with the group and potentially find changes to make, such as activities they weren’t already aware of or different groups of interest they might want to follow.« less

  12. Project Grandmaster

    SciTech Connect (OSTI)

    2013-09-16

    The purpose of the Project Grandmaster Application is to allow individuals to opt-in and give the application access to data sources about their activities on social media sites. The application will cross-reference these data sources to build up a picture of each individual activities they discuss, either at present or in the past, and place this picture in reference to groups of all participants. The goal is to allow an individual to place themselves in the collective and to understand how their behavior patterns fit with the group and potentially find changes to make, such as activities they weren?t already aware of or different groups of interest they might want to follow.

  13. A Distributed Modeling System for Short-Term to Seasonal Ensemble Streamflow Forecasting in Snowmelt Dominated Basins

    SciTech Connect (OSTI)

    Wigmosta, Mark S.; Gill, Muhammad K.; Coleman, Andre M.; Prasad, Rajiv; Vail, Lance W.

    2007-12-01

    This paper describes a distributed modeling system for short-term to seasonal water supply forecasts with the ability to utilize remotely-sensed snow cover products and real-time streamflow measurements. Spatial variability in basin characteristics and meteorology is represented using a raster-based computational grid. Canopy interception, snow accumulation and melt, and simplified soil water movement are simulated in each computational unit. The model is run at a daily time step with surface runoff and subsurface flow aggregated at the basin scale. This approach allows the model to be updated with spatial snow cover and measured streamflow using an Ensemble Kalman-based data assimilation strategy that accounts for uncertainty in weather forecasts, model parameters, and observations used for updating. Model inflow forecasts for the Dworshak Reservoir in northern Idaho are compared to observations and to April-July volumetric forecasts issued by the Natural Resource Conservation Service (NRCS) for Water Years 2000 – 2006. October 1 volumetric forecasts are superior to those issued by the NRCS, while March 1 forecasts are comparable. The ensemble spread brackets the observed April-July volumetric inflows in all years. Short-term (one and three day) forecasts also show excellent agreement with observations.

  14. Project Management Lessons Learned

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

    2008-08-05

    The guide supports DOE O 413.3A, Program and Project Management for the Acquisition of Capital Assets, and aids the federal project directors and integrated project teams in the execution of projects.

  15. Contract/Project Management

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

    Capital Asset Line Item Projects: (Pre-RCACAP) Projects completed within 110% of CD-2 ... Projects: (Pre- RACCAP) 90% of Projects completed within 110% of CD-2 TPC by FY12. 2b. ...

  16. Contract/Project Management

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

    90% of projects completed within 110% of CD-2 TPC by FY11. 80% - Two projects completed ... projects. 3. Certified EVM Systems: Post CD-3, 95% of line item projects and EM cleanup ...

  17. Contract/Project Management

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

    Projects: (Pre-RCACAP) 90% of projects completed within 110% of CD-2 TPC by FY11. 1b. ... Projects: (Pre- RACCAP) 90% of projects completed within 110% of CD-2 TPC by FY11. 2b. ...

  18. A Processor to get UV-A and UV-B Radiation Products from the ECMWF Forecast

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

    System A Processor to get UV-A and UV-B Radiation Products from the ECMWF Forecast System Morcrette, Jean-Jacques European Centre for Medium-Range Weather Forecasts Category: Radiation A new processor for evaluating the UV-B and UV-A radiation at the surface, based on modifications to the current shortwave radiation scheme of the ECMWF forecast system is described. Sensitivity studies of the UV surface irradiance and Erythemal Dose Rate to spectral resolution, representation and atmospheric

  19. Oxygenate Supply/Demand Balances in the Short-Term Integrated Forecasting Model (Released in the STEO March 1998)

    Reports and Publications (EIA)

    1998-01-01

    The blending of oxygenates, such as fuel ethanol and methyl tertiary butyl ether (MTBE), into motor gasoline has increased dramatically in the last few years because of the oxygenated and reformulated gasoline programs. Because of the significant role oxygenates now have in petroleum product markets, the Short-Term Integrated Forecasting System (STIFS) was revised to include supply and demand balances for fuel ethanol and MTBE. The STIFS model is used for producing forecasts in the Short-Term Energy Outlook. A review of the historical data sources and forecasting methodology for oxygenate production, imports, inventories, and demand is presented in this report.

  20. Western Interconnection Synchrophasor Project

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

    Demonstration Project Western Interconnection Synchrophasor Project Resources & Links Demand Response Energy Efficiency Emerging Technologies Synchrophasor measurements are a...

  1. Project File System

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

    Project File System Project File System Overview The project file system is a global file system available on all NERSC computational systems. It allows sharing of data between users, systems, and/or (via science gateways) the "outside world". Default project directories are provided to every MPP project. Additional project directories can be provided upon request. Purging No, files in project directories are not subject to purging. Backup Daily backups are performed for project

  2. Community Renewables Projects

    Broader source: Energy.gov [DOE]

    This webinar covered introduction and barriers to individual renewable projects, resources for community and group buy projects, and permitting guidelines.

  3. MHK Projects/Admirality Inlet Tidal Energy Project | Open Energy...

    Open Energy Info (EERE)

    eLabel":"","visitedicon":"" Project Profile Project Start Date 112006 Project City Port Townsend, WA Project StateProvince Washington Project Country United States...

  4. Demonstration project Smart Charging (Smart Grid Project) | Open...

    Open Energy Info (EERE)

    Smart Grid Projects Smart Grid Projects in Europe Smart Grid Projects - Grid Automation Distribution Smart Grid Projects - Integrated System Smart Grid Projects - Home...

  5. Implementation and assessment of turbine wake models in the Weather Research and Forecasting model for both mesoscale and large-eddy simulation

    SciTech Connect (OSTI)

    Singer, M; Mirocha, J; Lundquist, J; Cleve, J

    2010-03-03

    Flow dynamics in large wind projects are influenced by the turbines located within. The turbine wakes, regions characterized by lower wind speeds and higher levels of turbulence than the surrounding free stream flow, can extend several rotor diameters downstream, and may meander and widen with increasing distance from the turbine. Turbine wakes can also reduce the power generated by downstream turbines and accelerate fatigue and damage to turbine components. An improved understanding of wake formation and transport within wind parks is essential for maximizing power output and increasing turbine lifespan. Moreover, the influence of wakes from large wind projects on neighboring wind farms, agricultural activities, and local climate are all areas of concern that can likewise be addressed by wake modeling. This work describes the formulation and application of an actuator disk model for studying flow dynamics of both individual turbines and arrays of turbines within wind projects. The actuator disk model is implemented in the Weather Research and Forecasting (WRF) model, which is an open-source atmospheric simulation code applicable to a wide range of scales, from mesoscale to large-eddy simulation. Preliminary results demonstrate the applicability of the actuator disk model within WRF to a moderately high-resolution large-eddy simulation study of a small array of turbines.

  6. Preparing for Project Implementation Financing Project Implementation

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

    August 11, 2010 9 - Preparing for Project Implementation Financing Project Implementation Save Energy Now LEADER Web Conference Project Implementation Seminar Series Save Energy Now LEADER Web Conference Agenda  Seminar Series Overview  Recap Seminar # 8 - "Announcing the PRIZE"  Financing Project Implementation Fred Schoeneborn - ORNL team Robert Varcoe - UAW & General Motors  Questions/Future Seminars Save Energy Now LEADER Web Conference Project Implementation Series

  7. Seneca Compressed Air Energy Storage (CAES) Project

    SciTech Connect (OSTI)

    2012-11-30

    Compressed Air Energy Storage (CAES) is a hybrid energy storage and generation concept that has many potential benefits especially in a location with increasing percentages of intermittent wind energy generation. The objectives of the NYSEG Seneca CAES Project included: for Phase 1, development of a Front End Engineering Design for a 130MW to 210 MW utility-owned facility including capital costs; project financials based on the engineering design and forecasts of energy market revenues; design of the salt cavern to be used for air storage; draft environmental permit filings; and draft NYISO interconnection filing; for Phase 2, objectives included plant construction with a target in-service date of mid-2016; and for Phase 3, objectives included commercial demonstration, testing, and two-years of performance reporting. This Final Report is presented now at the end of Phase 1 because NYSEG has concluded that the economics of the project are not favorable for development in the current economic environment in New York State. The proposed site is located in NYSEG’s service territory in the Town of Reading, New York, at the southern end of Seneca Lake, in New York State’s Finger Lakes region. The landowner of the proposed site is Inergy, a company that owns the salt solution mining facility at this property. Inergy would have developed a new air storage cavern facility to be designed for NYSEG specifically for the Seneca CAES project. A large volume, natural gas storage facility owned and operated by Inergy is also located near this site and would have provided a source of high pressure pipeline quality natural gas for use in the CAES plant. The site has an electrical take-away capability of 210 MW via two NYSEG 115 kV circuits located approximately one half mile from the plant site. Cooling tower make-up water would have been supplied from Seneca Lake. NYSEG’s engineering consultant WorleyParsons Group thoroughly evaluated three CAES designs and concluded that any of the designs would perform acceptably. Their general scope of work included development of detailed project construction schedules, capital cost and cash flow estimates for both CAES cycles, and development of detailed operational data, including fuel and compression energy requirements, to support dispatch modeling for the CAES cycles. The Dispatch Modeling Consultant selected for this project was Customized Energy Solutions (CES). Their general scope of work included development of wholesale electric and gas market price forecasts and development of a dispatch model specific to CAES technologies. Parsons Brinkerhoff Energy Storage Services (PBESS) was retained to develop an air storage cavern and well system design for the CAES project. Their general scope of work included development of a cavern design, solution mining plan, and air production well design, cost, and schedule estimates for the project. Detailed Front End Engineering Design (FEED) during Phase 1 of the project determined that CAES plant capital equipment costs were much greater than the $125.6- million originally estimated by EPRI for the project. The initial air storage cavern Design Basis was increased from a single five million cubic foot capacity cavern to three, five million cubic foot caverns with associated air production wells and piping. The result of this change in storage cavern Design Basis increased project capital costs significantly. In addition, the development time required to complete the three cavern system was estimated at approximately six years. This meant that the CAES plant would initially go into service with only one third of the required storage capacity and would not achieve full capability until after approximately five years of commercial operation. The market price forecasting and dispatch modeling completed by CES indicated that the CAES technologies would operate at only 10 to 20% capacity factors and the resulting overall project economics were not favorable for further development. As a result of all of these factors, the Phase 1 FEED developed an installed CAES plant cost estimate of approximately $2,300/KW for the 210MW CAES 1A and 2 cycles. The capital cost for the 136 MW CAES 1 cycle was even higher due to the lower generating capacity of the cycle. Notably, the large equipment could have generated additional capacity (up to 270MW) which would have improved the cost per KW; however, the output was limited by the night time transmission system capability. The research herein, therefore, is particular to the site-specific factors that influenced the design and the current and forecasted generation mix and energy prices in Upstate New York and may not necessarily indicate that CAES plants cannot be economically constructed in other places in New York State or the world.

  8. Integration of Wind Generation and Load Forecast Uncertainties into Power Grid Operations

    SciTech Connect (OSTI)

    Makarov, Yuri V.; Etingov, Pavel V.; Huang, Zhenyu; Ma, Jian; Chakrabarti, Bhujanga B.; Subbarao, Krishnappa; Loutan, Clyde; Guttromson, Ross T.

    2010-04-20

    In this paper, a new approach to evaluate the uncertainty ranges for the required generation performance envelope, including the balancing capacity, ramping capability and ramp duration is presented. The approach includes three stages: statistical and actual data acquisition, statistical analysis of retrospective information, and prediction of future grid balancing requirements for specified time horizons and confidence intervals. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on a histogram analysis incorporating all sources of uncertainty and parameters of a continuous (wind forecast and load forecast errors) and discrete (forced generator outages and failures to start up) nature. Preliminary simulations using California Independent System Operator (CAISO) real life data have shown the effectiveness and efficiency of the proposed approach.

  9. 2007 Wholesale Power Rate Case Final Proposal : Market Price Forecast Study.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    2006-07-01

    This study presents BPA's market price forecasts for the Final Proposal, which are based on AURORA modeling. AURORA calculates the variable cost of the marginal resource in a competitively priced energy market. In competitive market pricing, the marginal cost of production is equivalent to the market-clearing price. Market-clearing prices are important factors for informing BPA's power rates. AURORA was used as the primary tool for (a) estimating the forward price for the IOU REP Settlement benefits calculation for fiscal years (FY) 2008 and 2009, (b) estimating the uncertainty surrounding DSI payments and IOU REP Settlements benefits, (c) informing the secondary revenue forecast and (d) providing a price input used for the risk analysis. For information about the calculation of the secondary revenues, uncertainty regarding the IOU REP Settlement benefits and DSI payment uncertainty, and the risk run, see Risk Analysis Study WP-07-FS-BPA-04.

  10. Unit commitment with wind power generation: integrating wind forecast uncertainty and stochastic programming.

    SciTech Connect (OSTI)

    Constantinescu, E. M.; Zavala, V. M.; Rocklin, M.; Lee, S.; Anitescu, M.

    2009-10-09

    We present a computational framework for integrating the state-of-the-art Weather Research and Forecasting (WRF) model in stochastic unit commitment/energy dispatch formulations that account for wind power uncertainty. We first enhance the WRF model with adjoint sensitivity analysis capabilities and a sampling technique implemented in a distributed-memory parallel computing architecture. We use these capabilities through an ensemble approach to model the uncertainty of the forecast errors. The wind power realizations are exploited through a closed-loop stochastic unit commitment/energy dispatch formulation. We discuss computational issues arising in the implementation of the framework. In addition, we validate the framework using real wind speed data obtained from a set of meteorological stations. We also build a simulated power system to demonstrate the developments.

  11. Are there Gains from Pooling Real-Time Oil Price Forecasts?

    Gasoline and Diesel Fuel Update (EIA)

    Are there Gains from Pooling Real- Time Oil Price Forecasts? Christiane Baumeister, Bank of Canada Lutz Kilian, University of Michigan Thomas K. Lee, U.S. Energy Information Administration February 12, 2014 Independent Statistics & Analysis www.eia.gov U.S. Energy Information Administration Washington, DC 20585 This paper is released to encourage discussion and critical comment. The analysis and conclusions expressed here are those of the authors and not necessarily those of the U.S. Energy

  12. Validation of Global Weather Forecast and Climate Models Over the North

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

    Slope of Alaska Validation of Global Weather Forecast and Climate Models Over the North Slope of Alaska Xie, Shaocheng Lawrence Livermore National Laboratory Klein, Stephen Lawrence Livermore National Laboratory Boyle, Jim Lawrence Livermore National Laboratory Fiorino, Michael DOE/Lawrence Livermore National Laboratory Hnilo, Justin DOE/Lawrence Livermore National Laboratory Phillips, Thomas PCMDI/LLNL Potter, Gerald Lawrence Livermore National Laboratory Beljaars, Anton ECMWF Category:

  13. Executive Summary: Assessment of Parabolic Trough and Power Tower Solar Technology Cost and Performance Forecasts

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

    5060 Sargent & Lundy LLC Consulting Group Chicago, Illinois Executive Summary: Assessment of Parabolic Trough and Power Tower Solar Technology Cost and Performance Forecasts National Renewable Energy Laboratory 1617 Cole Boulevard Golden, Colorado 80401-3393 NREL is a U.S. Department of Energy Laboratory Operated by Midwest Research Institute * Battelle * Bechtel Contract No. DE-AC36-99-GO10337 October 2003 * NREL/SR-550-35060 Executive Summary: Assessment of Parabolic Trough and Power Tower

  14. Forecasting the Magnitude of Sustainable Biofeedstock Supplies: the Challenges and the Rewards

    SciTech Connect (OSTI)

    Graham, Robin Lambert

    2007-01-01

    Forecasting the magnitude of sustainable biofeedstock supplies is challenging because of 1) the myriad of potential feedstock types and their management 2) the need to account for the spatial variation of both the supplies and their environmental and economic consequences, and 3) the inherent challenges of optimizing across economic and environmental considerations. Over the last two decades U.S. biomass forecasts have become increasingly complex and sensitive to environmental and economic considerations. More model development and research is needed however, to capture the landscape and regional tradeoffs of differing biofeedstock supplies especially with regards water quality concerns and wildlife/biodiversity. Forecasts need to be done in the context of the direction of change and what the probable land use and attendant environmental and economic outcomes would be if biofeedstocks were not being produced. To evaluate sustainability, process-oriented models need to be coupled or used to inform sector models and more work needs to be done on developing environmental metrics that are useful for evaluating economic and environmental tradeoffs. These challenges are exciting and worthwhile as they will enable the bioenergy industry to capture environmental and social benefits of biofeedstock production and reduce risks.

  15. Why Models Don%3CU%2B2019%3Et Forecast.

    SciTech Connect (OSTI)

    McNamara, Laura A.

    2010-08-01

    The title of this paper, Why Models Don't Forecast, has a deceptively simple answer: models don't forecast because people forecast. Yet this statement has significant implications for computational social modeling and simulation in national security decision making. Specifically, it points to the need for robust approaches to the problem of how people and organizations develop, deploy, and use computational modeling and simulation technologies. In the next twenty or so pages, I argue that the challenge of evaluating computational social modeling and simulation technologies extends far beyond verification and validation, and should include the relationship between a simulation technology and the people and organizations using it. This challenge of evaluation is not just one of usability and usefulness for technologies, but extends to the assessment of how new modeling and simulation technologies shape human and organizational judgment. The robust and systematic evaluation of organizational decision making processes, and the role of computational modeling and simulation technologies therein, is a critical problem for the organizations who promote, fund, develop, and seek to use computational social science tools, methods, and techniques in high-consequence decision making.

  16. Decreasing the temporal complexity for nonlinear, implicit reduced-order models by forecasting

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

    Carlberg, Kevin; Ray, Jaideep; van Bloemen Waanders, Bart

    2015-02-14

    Implicit numerical integration of nonlinear ODEs requires solving a system of nonlinear algebraic equations at each time step. Each of these systems is often solved by a Newton-like method, which incurs a sequence of linear-system solves. Most model-reduction techniques for nonlinear ODEs exploit knowledge of system's spatial behavior to reduce the computational complexity of each linear-system solve. However, the number of linear-system solves for the reduced-order simulation often remains roughly the same as that for the full-order simulation. We propose exploiting knowledge of the model's temporal behavior to (1) forecast the unknown variable of the reduced-order system of nonlinear equationsmore » at future time steps, and (2) use this forecast as an initial guess for the Newton-like solver during the reduced-order-model simulation. To compute the forecast, we propose using the Gappy POD technique. As a result, the goal is to generate an accurate initial guess so that the Newton solver requires many fewer iterations to converge, thereby decreasing the number of linear-system solves in the reduced-order-model simulation.« less

  17. 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.

  18. Turbulence-driven coronal heating and improvements to empirical forecasting of the solar wind

    SciTech Connect (OSTI)

    Woolsey, Lauren N.; Cranmer, Steven R.

    2014-06-01

    Forecasting models of the solar wind often rely on simple parameterizations of the magnetic field that ignore the effects of the full magnetic field geometry. In this paper, we present the results of two solar wind prediction models that consider the full magnetic field profile and include the effects of Alfvén waves on coronal heating and wind acceleration. The one-dimensional magnetohydrodynamic code ZEPHYR self-consistently finds solar wind solutions without the need for empirical heating functions. Another one-dimensional code, introduced in this paper (The Efficient Modified-Parker-Equation-Solving Tool, TEMPEST), can act as a smaller, stand-alone code for use in forecasting pipelines. TEMPEST is written in Python and will become a publicly available library of functions that is easy to adapt and expand. We discuss important relations between the magnetic field profile and properties of the solar wind that can be used to independently validate prediction models. ZEPHYR provides the foundation and calibration for TEMPEST, and ultimately we will use these models to predict observations and explain space weather created by the bulk solar wind. We are able to reproduce with both models the general anticorrelation seen in comparisons of observed wind speed at 1 AU and the flux tube expansion factor. There is significantly less spread than comparing the results of the two models than between ZEPHYR and a traditional flux tube expansion relation. We suggest that the new code, TEMPEST, will become a valuable tool in the forecasting of space weather.

  19. Decreasing the temporal complexity for nonlinear, implicit reduced-order models by forecasting

    SciTech Connect (OSTI)

    Carlberg, Kevin; Ray, Jaideep; van Bloemen Waanders, Bart

    2015-02-14

    Implicit numerical integration of nonlinear ODEs requires solving a system of nonlinear algebraic equations at each time step. Each of these systems is often solved by a Newton-like method, which incurs a sequence of linear-system solves. Most model-reduction techniques for nonlinear ODEs exploit knowledge of system's spatial behavior to reduce the computational complexity of each linear-system solve. However, the number of linear-system solves for the reduced-order simulation often remains roughly the same as that for the full-order simulation. We propose exploiting knowledge of the model's temporal behavior to (1) forecast the unknown variable of the reduced-order system of nonlinear equations at future time steps, and (2) use this forecast as an initial guess for the Newton-like solver during the reduced-order-model simulation. To compute the forecast, we propose using the Gappy POD technique. As a result, the goal is to generate an accurate initial guess so that the Newton solver requires many fewer iterations to converge, thereby decreasing the number of linear-system solves in the reduced-order-model simulation.

  20. National forecast for geothermal resource exploration and development with techniques for policy analysis and resource assessment

    SciTech Connect (OSTI)

    Cassel, T.A.V.; Shimamoto, G.T.; Amundsen, C.B.; Blair, P.D.; Finan, W.F.; Smith, M.R.; Edeistein, R.H.

    1982-03-31

    The backgrund, structure and use of modern forecasting methods for estimating the future development of geothermal energy in the United States are documented. The forecasting instrument may be divided into two sequential submodels. The first predicts the timing and quality of future geothermal resource discoveries from an underlying resource base. This resource base represents an expansion of the widely-publicized USGS Circular 790. The second submodel forecasts the rate and extent of utilization of geothermal resource discoveries. It is based on the joint investment behavior of resource developers and potential users as statistically determined from extensive industry interviews. It is concluded that geothermal resource development, especially for electric power development, will play an increasingly significant role in meeting US energy demands over the next 2 decades. Depending on the extent of R and D achievements in related areas of geosciences and technology, expected geothermal power development will reach between 7700 and 17300 Mwe by the year 2000. This represents between 8 and 18% of the expected electric energy demand (GWh) in western and northwestern states.

  1. Modeling and forecasting the distribution of Vibrio vulnificus in Chesapeake Bay

    SciTech Connect (OSTI)

    Jacobs, John M.; Rhodes, M.; Brown, C. W.; Hood, Raleigh R.; Leight, A.; Long, Wen; Wood, R.

    2014-11-01

    The aim is to construct statistical models to predict the presence, abundance and potential virulence of Vibrio vulnificus in surface waters. A variety of statistical techniques were used in concert to identify water quality parameters associated with V. vulnificus presence, abundance and virulence markers in the interest of developing strong predictive models for use in regional oceanographic modeling systems. A suite of models are provided to represent the best model fit and alternatives using environmental variables that allow them to be put to immediate use in current ecological forecasting efforts. Conclusions: Environmental parameters such as temperature, salinity and turbidity are capable of accurately predicting abundance and distribution of V. vulnificus in Chesapeake Bay. Forcing these empirical models with output from ocean modeling systems allows for spatially explicit forecasts for up to 48 h in the future. This study uses one of the largest data sets compiled to model Vibrio in an estuary, enhances our understanding of environmental correlates with abundance, distribution and presence of potentially virulent strains and offers a method to forecast these pathogens that may be replicated in other regions.

  2. Short-Term Energy Outlook Supplement: Uncertainties in the Short-Term Global Petroleum and Other Liquids Supply Forecast

    Gasoline and Diesel Fuel Update (EIA)

    Uncertainties in the Short-Term Global Petroleum and Other Liquids Supply Forecast February 2014 Independent Statistics & Analysis www.eia.gov U.S. Department of Energy Washington, DC 20585 U.S. Energy Information Administration | STEO Supplement: Uncertainties in the Global Petroleum and Other Liquids Supply Forecast i This report was prepared by the U.S. Energy Information Administration (EIA), the statistical and analytical agency within the U.S. Department of Energy. By law, EIA's data,

  3. Step 3: Project Refinement

    Energy Savers [EERE]

    3: Project Refinement 2 1 Potential 3 Refinement 4 Implementation 5 Operations & Maintenance 2 Options 3 Refinement 1/28/2016 2 3 FUNDING AND FINANCING OPTIONS Project Ownership Financing structure is highly dependent on size of the project and the capital available for a given project: * Tribe owns the project (cash purchase or debt) * Tribe hosts the project and buys the electricity (power purchase agreement) * Tribe partners with private sector and co-owns the project (uncertainties about

  4. FY 1996 solid waste integrated life-cycle forecast characteristics summary. Volumes 1 and 2

    SciTech Connect (OSTI)

    Templeton, K.J.

    1996-05-23

    For the past six years, a waste volume forecast has been collected annually from onsite and offsite generators that currently ship or are planning to ship solid waste to the Westinghouse Hanford Company`s Central Waste Complex (CWC). This document provides a description of the physical waste forms, hazardous waste constituents, and radionuclides of the waste expected to be shipped to the CWC from 1996 through the remaining life cycle of the Hanford Site (assumed to extend to 2070). In previous years, forecast data has been reported for a 30-year time period; however, the life-cycle approach was adopted this year to maintain consistency with FY 1996 Multi-Year Program Plans. This document is a companion report to two previous reports: the more detailed report on waste volumes, WHC-EP-0900, FY1996 Solid Waste Integrated Life-Cycle Forecast Volume Summary and the report on expected containers, WHC-EP-0903, FY1996 Solid Waste Integrated Life-Cycle Forecast Container Summary. All three documents are based on data gathered during the FY 1995 data call and verified as of January, 1996. These documents are intended to be used in conjunction with other solid waste planning documents as references for short and long-term planning of the WHC Solid Waste Disposal Division`s treatment, storage, and disposal activities over the next several decades. This document focuses on two main characteristics: the physical waste forms and hazardous waste constituents of low-level mixed waste (LLMW) and transuranic waste (both non-mixed and mixed) (TRU(M)). The major generators for each waste category and waste characteristic are also discussed. The characteristics of low-level waste (LLW) are described in Appendix A. In addition, information on radionuclides present in the waste is provided in Appendix B. The FY 1996 forecast data indicate that about 100,900 cubic meters of LLMW and TRU(M) waste is expected to be received at the CWC over the remaining life cycle of the site. Based on ranges provided by the waste generators, this baseline volume could fluctuate between a minimum of about 59,720 cubic meters and a maximum of about 152,170 cubic meters. The range is primarily due to uncertainties associated with the Tank Waste Remediation System (TWRS) program, including uncertainties regarding retrieval of long-length equipment, scheduling, and tank retrieval technologies.

  5. Project Reports for Haida Corporation- 2010 Project

    Broader source: Energy.gov [DOE]

    The Reynolds Creek Hydroelectric Project ("Reynolds Creek" or the "Project") is a 5 MW hydroelectric resource to be constructed on Prince of Wales Island, Alaska, approximately 10 miles east of Hydaburg.

  6. Project Information Form for Usability Projects

    Broader source: Energy.gov [DOE]

    For user-centered design projects such as a survey or card sort, complete the user-centered design project information form and send it to the Web Governance Team facilitator.

  7. Project Reports for Chickasaw Nation- 2010 Project

    Broader source: Energy.gov [DOE]

    Under this project, the Chickasaw Nation, Division of Commerce (CNDC) will upgrade old, inefficient lighting systems throughout CNDC to new, energy saving systems. Learn more about this project or...

  8. Step 4: Project Implementation

    Energy Savers [EERE]

    Process Step 4: Project Implementation Presentation Agenda * Step 4: Project Implementation - Pre-construction - Contract execution - Interconnection - Project construction - Commissioning * Project Example 2 1/28/2016 2 1 Potential 3 Refinement 5 Operations & Maintenance 2 Options 4 Implementation 4 Implementation 3 Potential Options Refinement Implementation Operations & Maintenance Step 4: Implementation 4 Purpose: Contract and begin physical construction of project Tasks: * Finalize

  9. Annual energy outlook 1998 with projections to 2020

    SciTech Connect (OSTI)

    1997-12-01

    The Annual Energy Outlook 1998 (AEO98) is the first AEO with projections to 2020. Key issues for the forecast extension are trends in energy efficiency improvements, the effects of increasing production and productivity improvements on energy prices, and the reduction in nuclear generating capacity. Projections in AEO98 also reflect a greater shift to electricity market restructuring. Restructuring is addressed through several changes that are assumed to occur in the industry, including a shorter capital recovery period for capacity expansion decisions and a revised financial structure that features a higher cost of capital as the result of higher competitive risk. Both assumptions tend to favor less capital-intensive generation technologies, such as natural gas, over coal or baseload renewable technologies. The forecasts include specific restructuring plans in those regions that have announced plans. California, New York, and New England are assumed to begin competitive pricing in 1998. The provisions of the California legislation for stranded cost recovery and price caps are incorporated. In New York and New England, stranded cost recovery is assumed to be phased out by 2008.

  10. Short-term energy outlook: Quarterly projections, fourth quarter 1997

    SciTech Connect (OSTI)

    1997-10-14

    The Energy Information Administration (EIA) prepares quarterly short-term energy supply, demand, and price projections for printed publication in January, April, July, and October in the Short-Term Energy Outlook. The details of these projections, as well as monthly updates on or about the 6th of each interim month, are available on the internet at: www.eia.doe.gov/emeu/steo/pub/contents.html. The forecast period for this issue of the Outlook extends from the fourth quarter of 1997 through the fourth quarter of 1998. Values for the fourth quarter of 1997, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in EIA`s Weekly Petroleum Status Report) or are calculated from model simulations that use the latest exogenous information available (for example, electricity sales and generation are simulated by using actual weather data). The historical energy data, compiled in the fourth quarter 1997 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS model is driven principally by three sets of assumptions or inputs: estimates of key macroeconomic variables, world oil price assumptions, and assumptions about the severity of weather. 19 tabs.

  11. Contract/Project Management

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

    of projects completed within 110% of CD-2 TPC by FY11. 80% - No 1 st Qtr FY09 completions. ... projects. 3. Certified EVM Systems: Post CD-3, 95% of line item projects and EM cleanup ...

  12. Contract/Project Management

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

    90% of projects completed within 110% of CD-2 TPC by FY11. 75% 76% This is a 3-year ... projects. 3. Certified EVM Systems: Post CD-3, 95% of line item projects and EM cleanup ...

  13. Contract/Project Management

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

    Pre- & Post-CAP Comment 1a. Capital Asset Line Item Projects: (Pre-RCACAP) 90% of projects completed within 110% of CD-2 TPC by FY11. 1b. Capital Asset Line Item Projects: ...

  14. Buckman Direct Diversion Project

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

    Buckman Direct Diversion Project Buckman Direct Diversion Project This project takes surface water from the Rio Grande, and then treats and distributes these waters to the city and county of Santa Fe through their drinking water distribution systems. August 1, 2013 Water flumes at Buckman Direct Diversion Project Water flumes at Buckman Direct Diversion Project The City of Santa Fe and Santa Fe County completed the construction of the Buckman Direct Diversion (BDD) Project in December 2010. The

  15. PROJECT MANGEMENT PLAN EXAMPLES

    Office of Environmental Management (EM)

    Baselines - Performance Baseline Examples Example 34 6.0 PROJECT BASELINE This section presents a summary of the PFP Stabilization and Deactivation Project baseline, which was prepared by an inter- contractor team to support an accelerated planning case for the project. The project schedules and associated cost profiles presented in this section are compared to the currently approved project baseline, as contained in the Facility Stabilization Project Fiscal Year 1999 Multi-Year Work Plan (MYWP)

  16. Bradys EGS Project

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

    Bradys EGS Project DOE: DE-FG36-08GO18200 Kyle Snyder Ezra Zemach Ormat Nevada Inc. Project Officer: Bill Vandermeer Total Project Funding: $6.6M April 22nd, 2013 This presentation does not contain any proprietary confidential, or otherwise restricted information. Insert photo of your choice 2 | US DOE Geothermal Program eere.energy.gov - Timeline * Project start date: September 2008, contract singed on June 2009 * Project end date: December 2013 * percent complete: ~50% - Budget * Total project

  17. Projects | Department of Energy

    Energy Savers [EERE]

    Projects Projects The U.S. Department of Energy supports a variety of energy-related projects on tribal lands. Through these projects, tribes have built the institutional capacity to manage their energy needs, assessed the feasibility of energy efficiency and renewable energy installation, and demonstrated the viability of installing renewable energy systems on tribal lands. View a map of projects, get information on project funding history, learn about Tribal Energy Deployment Program staff,

  18. Transmission Commercial Project Integration

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

    Projects Expand Projects Skip navigation links Ancillary and Control Area Services (ACS) Practices Forum Attachment K Commercial Business Process Improvement (CBPI) Customer...

  19. Projects & Facilities - Hanford Site

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

    Facilities About Us Projects & Facilities Email Email Page | Print Print Page |Text Increase Font Size Decrease Font Size Projects & Facilities 100 Area 118-K-1 Burial Ground 200...

  20. 2016 Technology Innovation Projects

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

    Projects FY 2016 Technology Innovation Project Briefs Demand Response TIP 292: Advanced Heat Pump Water Heater Research TIP 336: Scaled Deployment and Demonstration of Demand...

  1. Falls Creek Hydroelectric Project

    SciTech Connect (OSTI)

    Gustavus Electric Company; Richard Levitt; DOE Project Officer - Keith Bennett

    2007-06-12

    This project was for planning and construction of a 700kW hydropower project on the Fall River near Gustavus, Alaska.

  2. Sandia National Laboratories: Projects

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

    Projects Threat and Intelligence Insight Game-changing projects with a high degree of technical risk realized and produced in support of the warfighter Threat and Intelligence...

  3. GTO Project Portfolio

    Office of Energy Efficiency and Renewable Energy (EERE)

    The Office funds 154 research and development projects leveraging nearly $500 million in total combined investment. Each project represents a growing technology sector in conventional hydrothermal,...

  4. Evaluation Project 4492

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

    Organization area to allow the movement and radio-graphing of component for evaluation to determine the proper Project Execution Plan for dismantlement. Evaluation Project...

  5. All Selected Projects

    Energy Savers [EERE]

    Selected Projects Oct 23, 2009 (rev. Dec. 14, 2010) 99 Projects SMART GRID INVESTMENT GRANTS Type Advanced Metering Infrastructure Customer Systems Electric Systems Distribution...

  6. Campo Net Meter Project

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

    Campo Net Meter Project Michael Connolly Miskwish, MA EconomistEngineer Campo Kumeyaay Nation Location map Tribal Energy Planning Current 50 MW project Proposed 160 MW ...

  7. MHK Projects/Clarence Strait Tidal Energy Project | Open Energy...

    Open Energy Info (EERE)

    Project Country Australia Project Resource Click here Current Tidal Project Nearest Body of Water Clarence Strait Coordinates -12.083533792616, 131.04972839355 Project...

  8. MHK Projects/Twelve Mile Point Project | Open Energy Information

    Open Energy Info (EERE)

    Province Louisiana Project Country United States Project Resource Click here Current Tidal Coordinates 29.9177, -89.9307 Project Phase Phase 1 Project Installed Capacity...

  9. NNSA project receives DOE Secretary's Award for Project Management...

    National Nuclear Security Administration (NNSA)

    project receives DOE Secretary's Award for Project Management Improvement | National ... Blog Home NNSA Blog NNSA project receives DOE Secretary's Award for ... NNSA project ...

  10. Validation of a 20-year forecast of US childhood lead poisoning: Updated prospects for 2010

    SciTech Connect (OSTI)

    Jacobs, David E. . E-mail: dejacobs@starpower.net; Nevin, Rick

    2006-11-15

    We forecast childhood lead poisoning and residential lead paint hazard prevalence for 1990-2010, based on a previously unvalidated model that combines national blood lead data with three different housing data sets. The housing data sets, which describe trends in housing demolition, rehabilitation, window replacement, and lead paint, are the American Housing Survey, the Residential Energy Consumption Survey, and the National Lead Paint Survey. Blood lead data are principally from the National Health and Nutrition Examination Survey. New data now make it possible to validate the midpoint of the forecast time period. For the year 2000, the model predicted 23.3 million pre-1960 housing units with lead paint hazards, compared to an empirical HUD estimate of 20.6 million units. Further, the model predicted 498,000 children with elevated blood lead levels (EBL) in 2000, compared to a CDC empirical estimate of 434,000. The model predictions were well within 95% confidence intervals of empirical estimates for both residential lead paint hazard and blood lead outcome measures. The model shows that window replacement explains a large part of the dramatic reduction in lead poisoning that occurred from 1990 to 2000. Here, the construction of the model is described and updated through 2010 using new data. Further declines in childhood lead poisoning are achievable, but the goal of eliminating children's blood lead levels {>=}10 {mu}g/dL by 2010 is unlikely to be achieved without additional action. A window replacement policy will yield multiple benefits of lead poisoning prevention, increased home energy efficiency, decreased power plant emissions, improved housing affordability, and other previously unrecognized benefits. Finally, combining housing and health data could be applied to forecasting other housing-related diseases and injuries.

  11. Climatic Forecasting of Net Infiltration at Yucca Montain Using Analogue Meteororological Data

    SciTech Connect (OSTI)

    B. Faybishenko

    2006-09-11

    At Yucca Mountain, Nevada, future changes in climatic conditions will most likely alter net infiltration, or the drainage below the bottom of the evapotranspiration zone within the soil profile or flow across the interface between soil and the densely welded part of the Tiva Canyon Tuff. The objectives of this paper are to: (a) develop a semi-empirical model and forecast average net infiltration rates, using the limited meteorological data from analogue meteorological stations, for interglacial (present day), and future monsoon, glacial transition, and glacial climates over the Yucca Mountain region, and (b) corroborate the computed net-infiltration rates by comparing them with the empirically and numerically determined groundwater recharge and percolation rates through the unsaturated zone from published data. In this paper, the author presents an approach for calculations of net infiltration, aridity, and precipitation-effectiveness indices, using a modified Budyko's water-balance model, with reference-surface potential evapotranspiration determined from the radiation-based Penman (1948) formula. Results of calculations show that net infiltration rates are expected to generally increase from the present-day climate to monsoon climate, to glacial transition climate, and then to the glacial climate. The forecasting results indicate the overlap between the ranges of net infiltration for different climates. For example, the mean glacial net-infiltration rate corresponds to the upper-bound glacial transition net infiltration, and the lower-bound glacial net infiltration corresponds to the glacial transition mean net infiltration. Forecasting of net infiltration for different climate states is subject to numerous uncertainties-associated with selecting climate analogue sites, using relatively short analogue meteorological records, neglecting the effects of vegetation and surface runoff and runon on a local scale, as well as possible anthropogenic climate changes.

  12. Projects - Summer 2016 Cyclotron Institute REU Program

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

    2016 Student Projects

  13. FY 1996 solid waste integrated life-cycle forecast container summary volume 1 and 2

    SciTech Connect (OSTI)

    Valero, O.J.

    1996-04-23

    For the past six years, a waste volume forecast has been collected annually from onsite and offsite generators that currently ship or are planning to ship solid waste to the Westinghouse Hanford Company`s Central Waste Complex (CWC). This document provides a description of the containers expected to be used for these waste shipments from 1996 through the remaining life cycle of the Hanford Site. In previous years, forecast data have been reported for a 30-year time period; however, the life-cycle approach was adopted this year to maintain consistency with FY 1996 Multi-Year Program Plans. This document is a companion report to the more detailed report on waste volumes: WHC-EP0900, FY 1996 Solid Waste Integrated Life-Cycle Forecast Volume Summary. Both of these documents are based on data gathered during the FY 1995 data call and verified as of January, 1996. These documents are intended to be used in conjunction with other solid waste planning documents as references for short and long-term planning of the WHC Solid Waste Disposal Division`s treatment, storage, and disposal activities over the next several decades. This document focuses on the types of containers that will be used for packaging low-level mixed waste (LLMW) and transuranic waste (both non-mixed and mixed) (TRU(M)). The major waste generators for each waste category and container type are also discussed. Containers used for low-level waste (LLW) are described in Appendix A, since LLW requires minimal treatment and storage prior to onsite disposal in the LLW burial grounds. The FY 1996 forecast data indicate that about 100,900 cubic meters of LLMW and TRU(M) waste are expected to be received at the CWC over the remaining life cycle of the site. Based on ranges provided by the waste generators, this baseline volume could fluctuate between a minimum of about 59,720 cubic meters and a maximum of about 152,170 cubic meters.

  14. Energy Savings Forecast of Solid-State Lighting in General Illumination Applications

    SciTech Connect (OSTI)

    none,

    2014-08-29

    With declining production costs and increasing technical capabilities, LED adoption has recently gained momentum in general illumination applications. This is a positive development for our energy infrastructure, as LEDs use significantly less electricity per lumen produced than many traditional lighting technologies. The U.S. Department of Energy’s Energy Savings Forecast of Solid-State Lighting in General Illumination Applications examines the expected market penetration and resulting energy savings of light-emitting diode, or LED, lamps and luminaires from today through 2030.

  15. U.S. oil production forecast update reflects lower rig count

    Gasoline and Diesel Fuel Update (EIA)

    U.S. oil production forecast update reflects lower rig count Lower oil prices and fewer rigs drilling for crude oil are expected to slow U.S. oil production growth this year and in 2016. U.S. crude oil production is still expected to average 9.2 million barrels per day this year. That's up half a million barrels per day from last year and the highest output level in more than four decades. A substantial part of the year-over-year increase reflects rapid production growth throughout 2014.

  16. A hybrid procedure for MSW generation forecasting at multiple time scales in Xiamen City, China

    SciTech Connect (OSTI)

    Xu, Lilai; Gao, Peiqing; Cui, Shenghui; Liu, Chun

    2013-06-15

    Highlights: ? We propose a hybrid model that combines seasonal SARIMA model and grey system theory. ? The model is robust at multiple time scales with the anticipated accuracy. ? At month-scale, the SARIMA model shows good representation for monthly MSW generation. ? At medium-term time scale, grey relational analysis could yield the MSW generation. ? At long-term time scale, GM (1, 1) provides a basic scenario of MSW generation. - Abstract: Accurate forecasting of municipal solid waste (MSW) generation is crucial and fundamental for the planning, operation and optimization of any MSW management system. Comprehensive information on waste generation for month-scale, medium-term and long-term time scales is especially needed, considering the necessity of MSW management upgrade facing many developing countries. Several existing models are available but of little use in forecasting MSW generation at multiple time scales. The goal of this study is to propose a hybrid model that combines the seasonal autoregressive integrated moving average (SARIMA) model and grey system theory to forecast MSW generation at multiple time scales without needing to consider other variables such as demographics and socioeconomic factors. To demonstrate its applicability, a case study of Xiamen City, China was performed. Results show that the model is robust enough to fit and forecast seasonal and annual dynamics of MSW generation at month-scale, medium- and long-term time scales with the desired accuracy. In the month-scale, MSW generation in Xiamen City will peak at 132.2 thousand tonnes in July 2015 – 1.5 times the volume in July 2010. In the medium term, annual MSW generation will increase to 1518.1 thousand tonnes by 2015 at an average growth rate of 10%. In the long term, a large volume of MSW will be output annually and will increase to 2486.3 thousand tonnes by 2020 – 2.5 times the value for 2010. The hybrid model proposed in this paper can enable decision makers to develop integrated policies and measures for waste management over the long term.

  17. Solar Energy Science Projects

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

    Science Projects Curriculum: Solar Power -(thermodynamics, lightelectromagnetic, radiation, energy transformation, conductionconvection, seasons, trigonometry) Grade Level: ...

  18. Fairbanks Geothermal Energy Project

    Broader source: Energy.gov [DOE]

    Fairbanks Geothermal Energy Project presentation at the April 2013 peer review meeting held in Denver, Colorado.

  19. PROJECT MANGEMENT PLAN EXAMPLES Project Execution Example

    Office of Environmental Management (EM)

    Project Execution Example Example 73 6.3 Project Approach The overall schedule strategy for the PFP project includes ongoing minimum safe activities, combined with stabilization of materials followed by materials disposition, and subsequent transition of the PFP complex to a decommissioned state. The PFP material stabilization baseline was developed using a functionally-based work WBS. The WBS defines all activities required to take each material stream from their current location/conditions

  20. Reynolds Creek Hydroelectric Project, Project Status

    Energy Savers [EERE]

    Hydroelectric Project Project Status November 17, 2009 By : Alvin Edenshaw, President Haida Corporation and Haida Energy, Inc. Mike Stimac, P.E. Vice President, HDR Engineering, Inc. Project Manager November 17, 2009 2 Haida Corporation  Located in Hydaburg on Prince of Wales Island in SE Alaska  Hydaburg population = 350 people (called Kaigani Haida)  Hydaburg is largest Haida Village in Alaska  Subsistence and Commercial Fishing Lifestyle  Substantial Timber Holdings 

  1. January 2016 Project Dashboard

    Broader source: Energy.gov [DOE]

    The Office of Project Management Oversight and Assessments (PM) provides a monthly assessment of DOE’s portfolio of capital assets projects, which is summarized in the monthly Project Dashboard report. The current portfolio consists of 32 active projects with established scope, schedule, and cost performance baselines. Based on current performance, projects that are expected to meet their performance baseline are assessed as GREEN, projects that are at-risk of breaching their performance baselines are assessed as YELLOW, and projects that are expected to breach their performance baselines are assessed as RED.

  2. March 2016 Project Dashboard

    Broader source: Energy.gov [DOE]

    The Office of Project Management Oversight and Assessments (PM) provides a monthly assessment of DOE’s portfolio of capital assets projects, which is summarized in the monthly Project Dashboard report. The current portfolio consists of 33 active projects with established scope, schedule, and cost performance baselines. Based on current performance, projects that are expected to meet their performance baseline are assessed as GREEN, projects that are at-risk of breaching their performance baselines are assessed as YELLOW, and projects that are expected to breach their performance baselines are assessed as RED.

  3. December 2015 Project Dashboard

    Broader source: Energy.gov [DOE]

    The Office of Project Management Oversight and Assessments (PM) provides a monthly assessment of DOE’s portfolio of capital assets projects, which is summarized in the monthly Project Dashboard report. The current portfolio consists of 32 active projects with established scope, schedule, and cost performance baselines. Based on current performance, projects that are expected to meet their performance baseline are assessed as GREEN, projects that are at-risk of breaching their performance baselines are assessed as YELLOW, and projects that are expected to breach their performance baselines are assessed as RED.

  4. Contract/Project Management

    Office of Environmental Management (EM)

    2 nd Quarter Overall Contract and Project Management Performance Metrics and Targets Contract/Project Management Performance Metrics FY 2009 Target FY 2009 Actual Comment 1. Capital Asset Line Item Projects: 90% of projects completed within 110% of CD-2 TPC by FY11. 80% - Two projects completed in the 2 nd Qtr FY09. This is a 3-year rolling average (FY07 to FY09). 2. EM Cleanup (Soil and Groundwater Remediation, D&D, and Waste Treatment and Disposal) Projects: 90% of EM cleanup projects

  5. Project Reports for Winnebago Tribe- 2014 Project

    Broader source: Energy.gov [DOE]

    Following through with the Winnebago Tribe's commitment to reduce energy usage and consumption, the Winnebago Tribe Solar Project will focus on renewable energy production and energy cost savings...

  6. ARRA Electrification Projects

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

    U.S. Department of Energy funded multiple electrification projects through the American Recovery and Reinvestment Act to accelerate the deployment of electric drive vehicles and charging equipment. These included Clean Cities electric drive projects and transportation electrification projects. Use the interactive map above to learn more about the plan and status of the various projects. The U.S. Department of Energy funded multiple electrification projects through the American Recovery and

  7. Short-term energy outlook: Quarterly projections, second quarter 1997

    SciTech Connect (OSTI)

    1997-04-01

    The Energy Information Administration (EIA) prepares quarterly short-term energy supply, demand, and price projections for publication in January, April, July, and October in the Outlook. The forecast period for this issue of the Outlook extends from the second quarter of 1997 through the fourth quarter of 1998. Values for the first quarter of 1997, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in EIA`s Weekly Petroleum Status Report) or are calculated from model simulations that use the latest exogenous information available (for example, electricity sales and generation are simulated by using actual weather data). The historical energy data, compiled in the second quarter 1997 version of the Short-Term Integrated Forecasting System (STIFS) database, are mostly EIA data regularly published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding. The STIFS database is archived quarterly and is available from the National Technical Information Service. The STIFS model is driven principally by three sets of assumptions or inputs: estimates of key macroeconomic variables, world oil price assumptions, and assumptions about the severity of weather. Macroeconomic estimates are produced by DRI/McGraw-Hill but are adjusted by EIA to reflect EIA assumptions about the world price of crude oil, energy product prices, and other assumptions which may affect the macroeconomic outlook. By varying the assumptions, alternative cases are produced by using the Short-Term Integrated Forecasting System (STIFS). 34 figs., 19 tabs.

  8. Crude oil and alternate energy production forecasts for the twenty-first century: The end of the hydrocarbon era

    SciTech Connect (OSTI)

    Edwards, J.D.

    1997-08-01

    Predictions of production rates and ultimate recovery of crude oil are needed for intelligent planning and timely action to ensure the continuous flow of energy required by the world`s increasing population and expanding economies. Crude oil will be able to supply increasing demand until peak world production is reached. The energy gap caused by declining conventional oil production must then be filled by expanding production of coal, heavy oil and oil shales, nuclear and hydroelectric power, and renewable energy sources (solar, wind, and geothermal). Declining oil production forecasts are based on current estimated ultimate recoverable conventional crude oil resources of 329 billion barrels for the United States and close to 3 trillion barrels for the world. Peak world crude oil production is forecast to occur in 2020 at 90 million barrels per day. Conventional crude oil production in the United States is forecast to terminate by about 2090, and world production will be close to exhaustion by 2100.

  9. Great Plains Wind Energy Transmission Development Project

    SciTech Connect (OSTI)

    Brad G. Stevens, P.E.; Troy K. Simonsen; Kerryanne M. Leroux

    2012-06-09

    In fiscal year 2005, the Energy & Environmental Research Center (EERC) received funding from the U.S. Department of Energy (DOE) to undertake a broad array of tasks to either directly or indirectly address the barriers that faced much of the Great Plains states and their efforts to produce and transmit wind energy at the time. This program, entitled Great Plains Wind Energy Transmission Development Project, was focused on the central goal of stimulating wind energy development through expansion of new transmission capacity or development of new wind energy capacity through alternative market development. The original task structure was as follows: Task 1 - Regional Renewable Credit Tracking System (later rescoped to Small Wind Turbine Training Center); Task 2 - Multistate Transmission Collaborative; Task 3 - Wind Energy Forecasting System; and Task 4 - Analysis of the Long-Term Role of Hydrogen in the Region. As carried out, Task 1 involved the creation of the Small Wind Turbine Training Center (SWTTC). The SWTTC, located Grand Forks, North Dakota, consists of a single wind turbine, the Endurance S-250, on a 105-foot tilt-up guyed tower. The S-250 is connected to the electrical grid on the 'load side' of the electric meter, and the power produced by the wind turbine is consumed locally on the property. Establishment of the SWTTC will allow EERC personnel to provide educational opportunities to a wide range of participants, including grade school through college-level students and the general public. In addition, the facility will allow the EERC to provide technical training workshops related to the installation, operation, and maintenance of small wind turbines. In addition, under Task 1, the EERC hosted two small wind turbine workshops on May 18, 2010, and March 8, 2011, at the EERC in Grand Forks, North Dakota. Task 2 involved the EERC cosponsoring and aiding in the planning of three transmission workshops in the midwest and western regions. Under Task 3, the EERC, in collaboration with Meridian Environmental Services, developed and demonstrated the efficacy of a wind energy forecasting system for use in scheduling energy output from wind farms for a regional electrical generation and transmission utility. With the increased interest at the time of project award in the production of hydrogen as a critical future energy source, many viewed hydrogen produced from wind-generated electricity as an attractive option. In addition, many of the hydrogen production-related concepts involve utilization of energy resources without the need for additional electrical transmission. For this reason, under Task 4, the EERC provided a summary of end uses for hydrogen in the region and focused on one end product in particular (fertilizer), including several process options and related economic analyses.

  10. Contract/Project Management

    Office of Environmental Management (EM)

    8 4 th Quarter Metrics Final Overall Contract and Project Management Performance Metrics and Targets Contract/Project Management Performance Metrics FY 2008 Target FY 2008 Actual Comment 1. Capital Asset Line Item Projects: 90% of projects completed within 110% of CD-2 TPC by FY11. 75% 76% This is a 3-year rolling average Data includes FY06 to FY08. (37/48) 2. EM Cleanup (Soil and Groundwater Remediation, D&D, and Waste Treatment and Disposal) Projects: 90% of EM cleanup projects complete

  11. Contract/Project Management

    Office of Environmental Management (EM)

    1 st Quarter Overall Contract and Project Management Performance Metrics and Targets Contract/Project Management Performance Metrics FY 2009 Target FY 2009 Actual Comment 1. Capital Asset Line Item Projects: 90% of projects completed within 110% of CD-2 TPC by FY11. 80% - No 1 st Qtr FY09 completions. This is a 3-year rolling average (FY07 to FY09). 2. EM Cleanup (Soil and Groundwater Remediation, D&D, and Waste Treatment and Disposal) Projects: 90% of EM cleanup projects complete 80% of

  12. Contract/Project Management

    Office of Environmental Management (EM)

    3 rd Quarter Overall Contract and Project Management Performance Metrics and Targets Contract/Project Management Performance Metrics FY 2009 Target FY 2009 Actual Comment 1. Capital Asset Line Item Projects: 90% of projects completed within 110% of CD-2 TPC by FY11. 80% 72% This is a 3-year rolling average (FY07 to FY09). No 3 rd qtr FY09 completions. 2. EM Cleanup (Soil and Groundwater Remediation, D&D, and Waste Treatment and Disposal) Projects: 90% of EM cleanup projects complete 80% of

  13. Contract/Project Management

    Office of Environmental Management (EM)

    4 th Quarter Metrics Final Overall Contract and Project Management Performance Metrics and Targets Contract/Project Management Performance Metrics FY 2009 Target FY 2009 Actual Comment 1. Capital Asset Line Item Projects: 90% of projects completed within 110% of CD-2 TPC by FY11. 80% 73% This is a 3-year rolling average (FY07 to FY09). 2. EM Cleanup (Soil and Groundwater Remediation, D&D, and Waste Treatment and Disposal) Projects: 90% of EM cleanup projects complete 80% of scope within 125%

  14. Contract/Project Management

    Office of Environmental Management (EM)

    1 st Quarter Overall Contract and Project Management Performance Metrics and Targets 1 Contract/Project Management Primary Performance Metrics FY 2010 Target 1st Qtr FY 2010 Actual FY 2010 Pre- & Post-CAP Comment 1a. Capital Asset Line Item Projects: (Pre-RCA/CAP) 90% of projects completed within 110% of CD-2 TPC by FY11. 1b. Capital Asset Line Item Projects: (Post-RCA/CAP) 85% Line Item 73% Line Item 70% Pre-CAP 100% Post-CAP This is a projection based on a 3-year rolling average (FY08 to

  15. Contract/Project Management

    Office of Environmental Management (EM)

    Second Quarter Overall Contract and Project Management Performance Metrics and Targets 1 Contract/Project Management Primary Performance Metrics FY 2010 Target FY 2010 Actual FY 2010 Pre- & Post-CAP Comment 1a. Capital Asset Line Item Projects: (Pre-RCA/CAP) 90% of projects completed within 110% of CD-2 TPC by FY11. 1b. Capital Asset Line Item Projects: (Post-RCA/CAP) 85% Line Item 73% Line Item 70% Pre-CAP 100% Post-CAP This is a projection based on a 3-year rolling average (FY08 to FY10).

  16. Sample Project Execution Plan

    Broader source: Energy.gov [DOE]

    The project execution plan (PEP) is the governing document that establishes the means to execute, monitor, and control projects.  The plan serves as the main communication vehicle to ensure that...

  17. Haida Corporation- 2010 Project

    Broader source: Energy.gov [DOE]

    The Reynolds Creek Hydroelectric Project ("Reynolds Creek" or the "Project") is a 5 MW hydroelectric resource to be constructed on Prince of Wales Island, Alaska, approximately 10 miles east of Hydaburg.

  18. Contract/Project Management

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

    within 110% of CD-2 TPC by FY11. 80% 72% This is a 3-year rolling average (FY07 to FY09). ... projects. 3. Certified EVM Systems: Post CD-3, 95% of line item projects and EM cleanup ...

  19. Information Technology Project Management

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

    2012-12-03

    The Order provides program and project management direction for the acquisition and management of IT projects, investments, and initiatives. Cancels DOE G 200.1-1. Admin Chg 1 approved 1-16-2013.

  20. Contract/Project Management

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

    1 ContractProject Management Primary Performance Metrics FY 2011 Target FY 2011 Actual FY 2011 Pre- & Post-CAP Actual Comment 1a. Capital Asset Line Item Projects: ...

  1. Contract/Project Management

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

    Targets 1 ContractProject Management Primary Performance Metrics FY 2010 Target FY 2010 Actual FY 2010 Pre- & Post-CAP Comment 1a. Capital Asset Line Item Projects: (Pre-RCA...

  2. Improving Project Management

    Office of Environmental Management (EM)

    Improving Project Management Report of the Contract and Project Management Working Group November 2014 1 TABLE OF CONTENTS 1. Foreword ........................................................................................................................................................................... 2 2. Executive Summary ...................................................................................................................................................... 3 2.1 Summary of

  3. Acquisition and Project Management

    National Nuclear Security Administration (NNSA)

    4%2A en Acquisition and Project Management Office volunteers get up-close look at Office of Secure Transportation exercise http:nnsa.energy.govblogacquisition-and-project-mana...

  4. GHPsRUS Project

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

    Battocletti, Liz

    The GHPsRUS Project's full name is "Measuring the Costs and Benefits of Nationwide Geothermal Heat Pump Deployment." The dataset contains employment and installation price data collected by four economic surveys: (1)GHPsRUS Project Manufacturer & OEM Survey, (2) GHPsRUS Project Geothermal Loop Survey, (3) GHPsRUS Project Mechanical Equipment Installation Survey, and (4) GHPsRUS Geothermal Heat Pump Industry Survey

  5. GHPsRUS Project

    SciTech Connect (OSTI)

    Battocletti, Liz

    2013-07-09

    The GHPsRUS Project's full name is "Measuring the Costs and Benefits of Nationwide Geothermal Heat Pump Deployment." The dataset contains employment and installation price data collected by four economic surveys: (1)GHPsRUS Project Manufacturer & OEM Survey, (2) GHPsRUS Project Geothermal Loop Survey, (3) GHPsRUS Project Mechanical Equipment Installation Survey, and (4) GHPsRUS Geothermal Heat Pump Industry Survey

  6. WIPP Projects Interative Map

    Broader source: Energy.gov [DOE]

    View WIPP Projects in a larger map. To report corrections, please email WeatherizationInnovation@ee.doe.gov.

  7. Mentors and Projects

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

    Mentors, Projects Mentors and Projects Bringing together top space science students with internationally recognized researchers at Los Alamos in an educational, collaborative atmosphere Contacts Director Misa Cowee Email Administrative Assistant Mary Wubbena Email Request more information Email Students work closely with their mentors, who are Laboratory scientists, on challenging research projects in the Space Weather Summer School. Projects are related to current research topics in space

  8. Step 2: Project Options

    Energy Savers [EERE]

    2: Project Options 2 2 Design 1 Potential 3 Refinement 4 Implementation 2 Options 5 Operations & Maintenance 1/28/2016 2 Presentation Agenda * Step 2: Project Options * Project members and roles * Activity * Project ownership options - Interconnection, net metering, permitting, and considerations * Tools * Case in Point 3 Potential Options Refinement Implementation Operations & Maintenance 4 Step 2: Roles, Business Structures, & Regulatory Considerations Purpose: Determine ownership

  9. Red Lake Weatherization Project

    Energy Savers [EERE]

    REVIEW RED LAKE WEATHERIZATION PROJECT BERT VAN WERT ENERGY ACTIVITIES COORDINATOR Project Overview To develop the capacity to conduct energy audits Implement energy efficiency measures into Tribal homes Develop a Tribally administered Energy Efficiency Program and business PROJECT LOCATION Our project is located at Red Lake Housing Authority Red Lake Band of Chippewa Indians Red Lake , MN Red Lake Band of Chippewas Area overview Reservation (Diminished Lands) and Surroundings Red Lake Band of

  10. Step 4: Project Implementation

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

    4: Project Implementation Project Implementation 2 1 Potential 3 Refinement 5 Operations & Maintenance 2 Options 4 Implementation Step 4: Implementation 3 1 Potential 3 Refinement 5 Operations & Maintenance 2 Options 4 Implementation Step 4: Implementation 1. Pre-construction - Project kickoff - Design and construction documents, plans/schedules, submittals 2. Construction of project - Contract oversight/quality control - Change control 3. Commissioning - Testing and verification -

  11. Project Reports for Pawnee Nation- 2006 Project

    Broader source: Energy.gov [DOE]

    The primary goal of this project is to move the energy vision of the Pawnee Nation forward by conducting specific data collection and analysis tasks to assess the viable options available to Pawnee to meet future energy needs sustainable.

  12. Project Reports for Hualapai Tribe- 2010 Project

    Broader source: Energy.gov [DOE]

    The project will build on the potential for renewable energy development on the Hualapai Reservation that was identified during the Phase l renewable energy resource assessment conducted by the Hualapai Tribe since 2005.

  13. MHK Projects/Tensas | Open Energy Information

    Open Energy Info (EERE)

    ","visitedicon":"" Project Profile Project Start Date 112009 Project City Butte la Rose, LA Project StateProvince Louisiana Project Country United States Project Resource...

  14. Department of Energy award DE-SC0004164 Climate and National Security: Securing Better Forecasts

    SciTech Connect (OSTI)

    Reno Harnish

    2011-08-16

    The Climate and National Security: Securing Better Forecasts symposium was attended by senior policy makers and distinguished scientists. The juxtaposition of these communities was creative and fruitful. They acknowledged they were speaking past each other. Scientists were urged to tell policy makers about even improbable outcomes while articulating clearly the uncertainties around the outcomes. As one policy maker put it, we are accustomed to making these types of decisions. These points were captured clearly in an article that appeared on the New York Times website and can be found with other conference materials most easily on our website, www.scripps.ucsd.edu/cens/. The symposium, generously supported by the NOAA/JIMO, benefitted the public by promoting scientifically informed decision making and by the transmission of objective information regarding climate change and national security.

  15. Updated Eastern Interconnect Wind Power Output and Forecasts for ERGIS: July 2012

    SciTech Connect (OSTI)

    Pennock, K.

    2012-10-01

    AWS Truepower, LLC (AWST) was retained by the National Renewable Energy Laboratory (NREL) to update wind resource, plant output, and wind power forecasts originally produced by the Eastern Wind Integration and Transmission Study (EWITS). The new data set was to incorporate AWST's updated 200-m wind speed map, additional tall towers that were not included in the original study, and new turbine power curves. Additionally, a primary objective of this new study was to employ new data synthesis techniques developed for the PJM Renewable Integration Study (PRIS) to eliminate diurnal discontinuities resulting from the assimilation of observations into mesoscale model runs. The updated data set covers the same geographic area, 10-minute time resolution, and 2004?2006 study period for the same onshore and offshore (Great Lakes and Atlantic coast) sites as the original EWITS data set.

  16. A comparison of water vapor quantities from model short-range forecasts and ARM observations

    SciTech Connect (OSTI)

    Hnilo, J J

    2006-03-17

    Model evolution and improvement is complicated by the lack of high quality observational data. To address a major limitation of these measurements the Atmospheric Radiation Measurement (ARM) program was formed. For the second quarter ARM metric we will make use of new water vapor data that has become available, and called the 'Merged-sounding' value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Darwin Australia (DAR) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both DAR and NSA. The merged-sounding data have been interpolated to 37 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3 hourly data for direct comparison to our model output.

  17. A comparison of model short-range forecasts and the ARM Microbase data

    SciTech Connect (OSTI)

    Hnilo, J J

    2006-09-22

    For the fourth quarter ARM metric we will make use of new liquid water data that has become available, and called the 'Microbase' value added product (referred to as OBS, within the text) at three sites: the North Slope of Alaska (NSA), Tropical West Pacific (TWP) and the Southern Great Plains (SGP) and compare these observations to model forecast data. Two time periods will be analyzed March 2000 for the SGP and October 2004 for both TWP and NSA. The Microbase data have been averaged to 35 pressure levels (e.g., from 1000hPa to 100hPa at 25hPa increments) and time averaged to 3hourly data for direct comparison to our model output.

  18. Desert Peak EGS Project

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

    Desert Peak EGS Project DOE Award: DE-FC6-02ID14406 Ethan Chabora GeothermEx, a Schlumberger Company Ezra Zemach Ormat Nevada Inc. Project Officer: Bill Vandermeer Total Project Funding: $7.6M April 22nd, 2013 This presentation does not contain any proprietary confidential, or otherwise restricted information. Insert photo of your choice 2 | US DOE Geothermal Program eere.energy.gov - Timeline * Project start date: September 2002 * Project end date: Q3 2013 * Percentage complete: 90% - Budget *

  19. Contract/Project Management

    Office of Environmental Management (EM)

    3 First Quarter Overall Contract and Project Management Improvement Performance Metrics and Targets 1 Contract/Project Management Performance Metric FY 2013 Target FY 2013 Final FY 2013 Pre- & Post-CAP Final Comment Capital Asset Project Success: Complete 90% of capital asset projects at original scope and within 110% of CD-2 TPC. 90%* 83% Construction 86% Cleanup 80% 70% Pre-CAP 84% Post-CAP This is based on a 3- year rolling average (FY11 to FY13). TPC is Total Project Cost.

  20. Contract/Project Management

    Office of Environmental Management (EM)

    Fourth Quarter Overall Root Cause Analysis (RCA)/Corrective Action Plan (CAP) Performance Metrics 1 Contract/Project Management Performance Metric FY 2013 Target FY 2013 Actual FY 2013 Pre- & Post-CAP* Actual Comment Capital Asset Project Success: Complete 90% of capital asset projects at original scope and within 110% of CD-2 TPC. 90% 83% Construction 84% Cleanup 82% 70% Pre-CAP 84% Post-CAP Based on 3-year rolling period (FY11 to FY13) of 93 projects. TPC is Total Project Cost.

  1. Contract/Project Management

    Office of Environmental Management (EM)

    Fourth Quarter Overall Contract and Project Management Performance Metrics and Targets 1 Contract/Project Management Primary Performance Metrics FY 2010 Target FY 2010 Actual FY 2010 Pre- & Post-CAP Comment 1a. Capital Asset Line Item Projects: (Pre-RCA/CAP) 90% of projects completed within 110% of CD-2 TPC by FY11. 1b. Capital Asset Line Item Projects: (Post-RCA/CAP) 85% Line Item 69% Line Item 67% Pre-CAP 100% Post-CAP This is based on a 3-year rolling average (FY08 to FY10). TPC is Total

  2. Contract/Project Management

    Office of Environmental Management (EM)

    Fourth Quarter Overall Contract and Project Management Improvement Performance Metrics and Targets 1 Contract/Project Management Primary Performance Metrics FY 2011 Target FY 2011 Actual FY 2011 Pre- & Post-CAP Actual Comment 1a. Capital Asset Line Item Projects: (Pre-RCA/CAP) Projects completed within 110% of CD-2 TPC. 1b. Capital Asset Line Item Projects: (Post-RCA/CAP) 90% Line Item 84% Line Item 77% Pre-CAP 100% Post-CAP This is based on a 3-year rolling average (FY09 to FY11). TPC is

  3. Contract/Project Management

    Office of Environmental Management (EM)

    Fourth Quarter Overall Contract and Project Management Improvement Performance Metrics and Targets 1 Contract/Project Management Performance Metric FY 2012 Target FY 2012 Final FY 2012 Pre- & Post-CAP Final Comment Capital Asset Project Success: Complete 90% of capital asset projects at original scope and within 110% of CD-2 TPC. 90%* 86% Construction 87% Cleanup 84% 77% Pre-CAP 89% Post-CAP This is based on a 3- year rolling average (FY10 to FY12). TPC is Total Project Cost.

  4. Fast Physics Testbed for the FASTER Project

    SciTech Connect (OSTI)

    Lin, W.; Liu, Y.; Hogan, R.; Neggers, R.; Jensen, M.; Fridlind, A.; Lin, Y.; Wolf, A.

    2010-03-15

    This poster describes the Fast Physics Testbed for the new FAst-physics System Testbed and Research (FASTER) project. The overall objective is to provide a convenient and comprehensive platform for fast turn-around model evaluation against ARM observations and to facilitate development of parameterizations for cloud-related fast processes represented in global climate models. The testbed features three major components: a single column model (SCM) testbed, an NWP-Testbed, and high-resolution modeling (HRM). The web-based SCM-Testbed features multiple SCMs from major climate modeling centers and aims to maximize the potential of SCM approach to enhance and accelerate the evaluation and improvement of fast physics parameterizations through continuous evaluation of existing and evolving models against historical as well as new/improved ARM and other complementary measurements. The NWP-Testbed aims to capitalize on the large pool of operational numerical weather prediction products. Continuous evaluations of NWP forecasts against observations at ARM sites are carried out to systematically identify the biases and skills of physical parameterizations under all weather conditions. The highresolution modeling (HRM) activities aim to simulate the fast processes at high resolution to aid in the understanding of the fast processes and their parameterizations. A four-tier HRM framework is established to augment the SCM- and NWP-Testbeds towards eventual improvement of the parameterizations.

  5. Forecasting the response of Earth's surface to future climatic and land use changes: A review of methods and research needs

    SciTech Connect (OSTI)

    Pelletier, Jon D.; Murray, A. Brad; Pierce, Jennifer L.; Bierman, Paul R.; Breshears, David D.; Crosby, Benjamin T.; Ellis, Michael; Foufoula-Georgiou, Efi; Heimsath, Arjun M.; Houser, Chris; Lancaster, Nick; Marani, Marco; Merritts, Dorothy J.; Moore, Laura J.; Pederson, Joel L.; Poulos, Michael J.; Rittenour, Tammy M.; Rowland, Joel C.; Ruggiero, Peter; Ward, Dylan J.; Wickert, Andrew D.; Yager, Elowyn M.

    2015-07-14

    In the future, Earth will be warmer, precipitation events will be more extreme, global mean sea level will rise, and many arid and semiarid regions will be drier. Human modifications of landscapes will also occur at an accelerated rate as developed areas increase in size and population density. We now have gridded global forecasts, being continually improved, of the climatic and land use changes (C&LUC) that are likely to occur in the coming decades. However, besides a few exceptions, consensus forecasts do not exist for how these C&LUC will likely impact Earth-surface processes and hazards. In some cases, we have the tools to forecast the geomorphic responses to likely future C&LUC. Fully exploiting these models and utilizing these tools will require close collaboration among Earth-surface scientists and Earth-system modelers. This paper assesses the state-of-the-art tools and data that are being used or could be used to forecast changes in the state of Earth's surface as a result of likely future C&LUC. We also propose strategies for filling key knowledge gaps, emphasizing where additional basic research and/or collaboration across disciplines are necessary. The main body of the paper addresses cross-cutting issues, including the importance of nonlinear/threshold-dominated interactions among topography, vegetation, and sediment transport, as well as the importance of alternate stable states and extreme, rare events for understanding and forecasting Earth-surface response to C&LUC. Five supplements delve into different scales or process zones (global-scale assessments and fluvial, aeolian, glacial/periglacial, and coastal process zones) in detail.

  6. Forecasting the response of Earth's surface to future climatic and land use changes: A review of methods and research needs

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

    Pelletier, Jon D.; Murray, A. Brad; Pierce, Jennifer L.; Bierman, Paul R.; Breshears, David D.; Crosby, Benjamin T.; Ellis, Michael; Foufoula-Georgiou, Efi; Heimsath, Arjun M.; Houser, Chris; et al

    2015-07-14

    In the future, Earth will be warmer, precipitation events will be more extreme, global mean sea level will rise, and many arid and semiarid regions will be drier. Human modifications of landscapes will also occur at an accelerated rate as developed areas increase in size and population density. We now have gridded global forecasts, being continually improved, of the climatic and land use changes (C&LUC) that are likely to occur in the coming decades. However, besides a few exceptions, consensus forecasts do not exist for how these C&LUC will likely impact Earth-surface processes and hazards. In some cases, we havemore » the tools to forecast the geomorphic responses to likely future C&LUC. Fully exploiting these models and utilizing these tools will require close collaboration among Earth-surface scientists and Earth-system modelers. This paper assesses the state-of-the-art tools and data that are being used or could be used to forecast changes in the state of Earth's surface as a result of likely future C&LUC. We also propose strategies for filling key knowledge gaps, emphasizing where additional basic research and/or collaboration across disciplines are necessary. The main body of the paper addresses cross-cutting issues, including the importance of nonlinear/threshold-dominated interactions among topography, vegetation, and sediment transport, as well as the importance of alternate stable states and extreme, rare events for understanding and forecasting Earth-surface response to C&LUC. Five supplements delve into different scales or process zones (global-scale assessments and fluvial, aeolian, glacial/periglacial, and coastal process zones) in detail.« less

  7. EM Capital Asset Project List

    Broader source: Energy.gov [DOE]

    Read the EM Capital Asset Project List, which includes the project's name, site, current critical decision and current total project cost.

  8. Principal Associate Director - Capital Projects

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

    Principal Associate Director - Capital Projects As Principal Associate Director for Capital Projects (interim), Larry Simmons is responsible for institutional large-project...

  9. Framework for Probabilistic Projections of Energy-Relevant Streamflow Indicators under Climate Change Scenarios for the U.S.

    SciTech Connect (OSTI)

    Wagener, Thorsten; Mann, Michael; Crane, Robert

    2014-04-29

    This project focuses on uncertainty in streamflow forecasting under climate change conditions. The objective is to develop easy to use methodologies that can be applied across a range of river basins to estimate changes in water availability for realistic projections of climate change. There are three major components to the project: Empirical downscaling of regional climate change projections from a range of Global Climate Models; Developing a methodology to use present day information on the climate controls on the parameterizations in streamflow models to adjust the parameterizations under future climate conditions (a trading-space-for-time approach); and Demonstrating a bottom-up approach to establishing streamflow vulnerabilities to climate change. The results reinforce the need for downscaling of climate data for regional applications, and further demonstrates the challenges of using raw GCM data to make local projections. In addition, it reinforces the need to make projections across a range of global climate models. The project demonstrates the potential for improving streamflow forecasts by using model parameters that are adjusted for future climate conditions, but suggests that even with improved streamflow models and reduced climate uncertainty through the use of downscaled data, there is still large uncertainty is the streamflow projections. The most useful output from the project is the bottom-up vulnerability driven approach to examining possible climate and land use change impacts on streamflow. Here, we demonstrate an inexpensive and easy to apply methodology that uses Classification and Regression Trees (CART) to define the climate and environmental parameters space that can produce vulnerabilities in the system, and then feeds in the downscaled projections to determine the probability top transitioning to a vulnerable sate. Vulnerabilities, in this case, are defined by the end user.

  10. MHK Projects/UEK Yukon River Project | Open Energy Information

    Open Energy Info (EERE)

    StateProvince Alaska Project Country United States Project Resource Click here Current Tidal Coordinates 64.7881, -141.2 Project Phase Phase 1 Project Details UEK is has...

  11. River Protection Project (RPP) Project Management Plan

    SciTech Connect (OSTI)

    SEEMAN, S.E.

    2000-04-01

    The U.S. Department of Energy (DOE), in accordance with the Strom Thurmond National Defense Authorization Act for Fiscal Year 1999, established the Office of River Protection (ORP) to successfully execute and manage the River Protection Project (RPP), formerly known as the Tank Waste Remediation System (TWRS). The mission of the RPP is to store, retrieve, treat, and dispose of the highly radioactive Hanford tank waste in an environmentally sound, safe, and cost-effective manner. The team shown in Figure 1-1 is accomplishing the project. The ORP is providing the management and integration of the project; the Tank Farm Contractor (TFC) is responsible for providing tank waste storage, retrieval, and disposal; and the Privatization Contractor (PC) is responsible for providing tank waste treatment.

  12. Silver State Geothermal Project | Open Energy Information

    Open Energy Info (EERE)

    State Geothermal Project Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Development Project: Silver State Geothermal Project Project Location Information Coordinates...

  13. Orita 3 Geothermal Project | Open Energy Information

    Open Energy Info (EERE)

    3 Geothermal Project Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Development Project: Orita 3 Geothermal Project Project Location Information Coordinates...

  14. Panther Canyon Geothermal Project | Open Energy Information

    Open Energy Info (EERE)

    Canyon Geothermal Project Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Development Project: Panther Canyon Geothermal Project Project Location Information...

  15. Kelsey North Geothermal Project | Open Energy Information

    Open Energy Info (EERE)

    North Geothermal Project Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Development Project: Kelsey North Geothermal Project Project Location Information...

  16. Devil's Canyon Geothermal Project | Open Energy Information

    Open Energy Info (EERE)

    Canyon Geothermal Project Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Development Project: Devil's Canyon Geothermal Project Project Location Information...

  17. Dead Horse Geothermal Project | Open Energy Information

    Open Energy Info (EERE)

    Horse Geothermal Project Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Development Project: Dead Horse Geothermal Project Project Location Information...

  18. Delcer Butte Geothermal Project | Open Energy Information

    Open Energy Info (EERE)

    Butte Geothermal Project Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Development Project: Delcer Butte Geothermal Project Project Location Information...

  19. Drum Mountain Geothermal Project | Open Energy Information

    Open Energy Info (EERE)

    Mountain Geothermal Project Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Development Project: Drum Mountain Geothermal Project Project Location Information...

  20. Puna Geothermal Project | Open Energy Information

    Open Energy Info (EERE)

    Puna Geothermal Project Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Development Project: Puna Geothermal Project Project Location Information Coordinates...

  1. Reese River Geothermal Project | Open Energy Information

    Open Energy Info (EERE)

    River Geothermal Project Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Development Project: Reese River Geothermal Project Project Location Information...

  2. Baltazor Springs Geothermal Project | Open Energy Information

    Open Energy Info (EERE)

    Baltazor Springs Geothermal Project Jump to: navigation, search GEOTHERMAL ENERGYGeothermal Home Development Project: Baltazor Springs Geothermal Project Project Location...

  3. Project Reports for Hualapai Tribe- 2005 Project

    Broader source: Energy.gov [DOE]

    The Hualapai Tribe is located on the end of their existing utility grid which has subjected them to high costs and poor reliability of electric service. The first phase of the project will establish a tribally operated utility to provide service to tribal customers at Grand Canyon West, which has been operating without grid power for the past seven years. The second phase of the project will examine the feasibility and strategy for establishing a tribal utility to serve the remainder of the Hualapai Reservation.

  4. Estimating the greenhouse gas benefits of forestry projects: A Costa Rican Case Study

    SciTech Connect (OSTI)

    Busch, Christopher; Sathaye, Jayant; Sanchez Azofeifa, G. Arturo

    2000-09-01

    If the Clean Development Mechanism proposed under the Kyoto Protocol is to serve as an effective means for combating global climate change, it will depend upon reliable estimates of greenhouse gas benefits. This paper sketches the theoretical basis for estimating the greenhouse gas benefits of forestry projects and suggests lessons learned based on a case study of Costa Rica's Protected Areas Project, which is a 500,000 hectare effort to reduce deforestation and enhance reforestation. The Protected Areas Project in many senses advances the state of the art for Clean Development Mechanism-type forestry projects, as does the third-party verification work of SGS International Certification Services on the project. Nonetheless, sensitivity analysis shows that carbon benefit estimates for the project vary widely based on the imputed deforestation rate in the baseline scenario, e.g. the deforestation rate expected if the project were not implemented. This, along with a newly available national dataset that confirms other research showing a slower rate of deforestation in Costa Rica, suggests that the use of the 1979--1992 forest cover data originally as the basis for estimating carbon savings should be reconsidered. When the newly available data is substituted, carbon savings amount to 8.9 Mt (million tones) of carbon, down from the original estimate of 15.7 Mt. The primary general conclusion is that project developers should give more attention to the forecasting land use and land cover change scenarios underlying estimates of greenhouse gas benefits.

  5. Battleground Energy Recovery Project

    SciTech Connect (OSTI)

    Daniel Bullock

    2011-12-31

    In October 2009, the project partners began a 36-month effort to develop an innovative, commercial-scale demonstration project incorporating state-of-the-art waste heat recovery technology at Clean Harbors, Inc., a large hazardous waste incinerator site located in Deer Park, Texas. With financial support provided by the U.S. Department of Energy, the Battleground Energy Recovery Project was launched to advance waste heat recovery solutions into the hazardous waste incineration market, an area that has seen little adoption of heat recovery in the United States. The goal of the project was to accelerate the use of energy-efficient, waste heat recovery technology as an alternative means to produce steam for industrial processes. The project had three main engineering and business objectives: Prove Feasibility of Waste Heat Recovery Technology at a Hazardous Waste Incinerator Complex; Provide Low-cost Steam to a Major Polypropylene Plant Using Waste Heat; and ï?· Create a Showcase Waste Heat Recovery Demonstration Project.

  6. Structuring small projects

    SciTech Connect (OSTI)

    Pistole, C.O.

    1995-11-01

    One of the most difficult hurdles facing small project developers is obtaining financing. Many major banks and institutional investors are unwilling to become involved in projects valued at less than $25 million. To gain the interest of small project investors, developers will want to present a well-considered plan and an attractive rate of return. Waste-to-energy projects are one type that can offer diversified revenue sources that assure maximum profitability. The Ripe Touch Greenhouse project, a $14.5 million waste tire-to-energy facility in Colorado, provides a case study of how combining the strengths of the project partners can help gain community and regulatory acceptance and maximize profit opportunities.

  7. Gasification Systems Project Information

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

    Project Information Gasifier Optimization Archived Projects Agreement Number Project Title Performer Name Technology Area FE0023497 Alstom's Limestone Chemical Looping Gasification Process for High Hydrogen Syngas Generation Alstom Power, Inc Gasification Systems FE0023577 Advanced Gasifier and Water Gas Shift Technologies for Low Cost Coal Conversion to High Hydrogen Syngas Gas Technology Institute Coal & Coal-Biomass to Liquids, Gasification Systems FE0023915 Pilot Scale Operation and

  8. Funding for CSES Projects

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

    Funding for CSES Projects Funding for CSES Projects High quality, cutting-edge science in the areas of astrophysics, space physics, solid planetary geoscience, and climate science. Contact Director Reiner Friedel (505) 665-1936 Email Professional Staff Assistant Georgia D. Sanchez (505) 665-0855 Email CSES Student and Postdoctoral Fellow Program Funding intervals are based on the federal fiscal year spanning the year from October 1 through September 30 of the following year. For all projects

  9. Infrastructure Projects | Jefferson Lab

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

    Infrastructure Projects June 3, 2010 What do you think of the TEDF? How about the UIM project? What would have happened if we had not got the ARRA funding for the NP GPP projects last year? Gobbledegook!? Acronymia? Certainly different from the usual PREx, or QWeak, or DVCS that we hear from the physics side of the house! TEDF, UIM and the others are acronyms used by the facilities people, those trying to build, modernize and maintain our infrastructure. TEDF (Technology and Engineering

  10. Microwave solidification project overview

    SciTech Connect (OSTI)

    Sprenger, G.

    1993-01-01

    The Rocky Flats Plant Microwave Solidification Project has application potential to the Mixed Waste Treatment Project and the The Mixed Waste Integrated Program. The technical areas being addressed include (1) waste destruction and stabilization; (2) final waste form; and (3) front-end waste handling and feed preparation. This document covers need for such a program; technology description; significance; regulatory requirements; and accomplishments to date. A list of significant reports published under this project is included.

  11. Tribal Energy Projects

    Energy Savers [EERE]

    PROJECTS U.S. DEPARTMENT OF ENERGY U.S. DEPARTMENT OF ENERGY OFFICE OF ENERGY EFFICIENCY AND RENEWABLE ENERGY OFFICE OF ENERGY EFFICIENCY AND RENEWABLE ENERGY TRIBAL ENERGY PROGRAM TRIBAL ENERGY PROGRAM DOE's Tribal Energy Program DOE's Tribal Energy Program Tribal Energy Projects Tribal Energy Projects First Steps Toward Developing Renewable Energy and Energy Efficiency * Strategic planning * Energy options analysis * Capacity building * Organizational development Renewable Energy Development

  12. Project Submission Template

    Energy Savers [EERE]

    Cooperation Project Title: Country/Organizations: Foreign: Foreign POC: U.S: U.S. POC: Technology Area: Scope of Collaborative Research and Development: Justification of Approach: Work Completed to Date: Overview of Proposed Scope for FY12: Summary Brief Description of Specific Project(s): Timeline: Estimated Cost: Status: CONTINUATION or NEW? Type of Contracting Instrument: (Int'l agreements, lab-lab agreement, etc) Participant Organizations General Scope Budget Foreign (Technical Scope) US

  13. Evaluation Project 4492

    National Nuclear Security Administration (NNSA)

    12-2010 NNSA-B-10-0412 Sandia National Laboratories/New Mexico (SNL/NM) proposes to support the Bio-Response Operational Testing and Evaluation (BOTE) project. The BOTE project would involve multiple releases of a biological simulant, characterization sampling, decontamination, and clearance sampling, at the Idaho National Laboratory (INL) Test Site. Sandia Site Office Bio-Response Operational Testing and Evaluation (BOTE) Project (TA-I, TA-III, & Offsite at INL) INL LACY,SUSAN DOYLENE

  14. The CHPRC Columbia River Protection Project Quality Assurance Project Plan

    SciTech Connect (OSTI)

    Fix, N. J.

    2008-11-30

    Pacific Northwest National Laboratory researchers are working on the CHPRC Columbia River Protection Project (hereafter referred to as the Columbia River Project). This is a follow-on project, funded by CH2M Hill Plateau Remediation Company, LLC (CHPRC), to the Fluor Hanford, Inc. Columbia River Protection Project. The work scope consists of a number of CHPRC funded, related projects that are managed under a master project (project number 55109). All contract releases associated with the Fluor Hanford Columbia River Project (Fluor Hanford, Inc. Contract 27647) and the CHPRC Columbia River Project (Contract 36402) will be collected under this master project. Each project within the master project is authorized by a CHPRC contract release that contains the project-specific statement of work. This Quality Assurance Project Plan provides the quality assurance requirements and processes that will be followed by the Columbia River Project staff.

  15. Penobscot Tribe- 2012 Project

    Broader source: Energy.gov [DOE]

    With this award, the Penobscot Indian Nation will advance the preconstruction activities required to secure funding for the proposed 227-megawatt (MW) Alder Stream wind project.

  16. NREL: Biomass Research - Projects

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

    Spectrometer analyzes vapors during the gasification and pyrolysis processes. NREL's biomass projects are designed to advance the production of liquid transportation fuels from...

  17. Pit 9 Project

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

    July 11, 2007 Pit 9 Project Structures Removed For many years, the Pit 9 project at the Department of Energy's Idaho Site was the symbol of frustration for its cleanup program. All of that is coming to a close now, however, as North Wind, Inc. and its subcontractors are successfully tearing down and removing the structures and equipment left over by the original subcontractor for the Pit 9 project. The goal of this dismantlement and disposal project is to remove buildings and equipment to allow

  18. Production Project Accounts

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

    accounting logs. PIs and PI Proxies can request a Project Account by logging into nim and selecting "Request a Collaboration Account" under the blue "Actions" tab. Accessing...

  19. The MAJORANA project

    SciTech Connect (OSTI)

    Elliott, Steven R [Los Alamos National Laboratory

    2009-01-01

    The Majorana Project, a neutrinoless double-beta decay experiment is described with an emphasis on the choice of Ge-detector configuration.

  20. Mascoma: Frontier Biorefinery Project

    Broader source: Energy.gov [DOE]

    This project involves the construction and operation of a biorefinery that produces ethanol and other co-products from cellulosic materials through advanced consolidated bioprocessing.

  1. Fit for Purpose Projects

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

    that needs to be addressed by current and future Fit-for-Purpose projects includes: Reservoir pressure management - In deep saline formations, pressure increases due to...

  2. Funding for IGPPS Projects

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

    which may, in certain circumstances, require several months to implement after the start of the fiscal year. For all projects supported with Los Alamos National Laboratory...

  3. Classroom Projects - Hanford Site

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

    Hanford For Students and Kids Classroom Projects Hanford For Students and Kids Hanford Fun Facts Classroom Projects Famous People of Hanford Classroom Projects Email Email Page | Print Print Page |Text Increase Font Size Decrease Font Size If you've been assigned to write a report or complete a classroom assignment that involves Hanford, we've got some tools that might help you with your project! Photographs The first is an online photo gallery of pictures. We've got thousands of photographs

  4. Custom Renewable Energy Projects

    Broader source: Energy.gov [DOE]

    Project development assistance funding is available for a variety of purposes, including grant writing, feasibility studies, or technical assistance with design, permitting, or utility interconne...

  5. NREL: Transportation Research - Projects

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

    Projects 3-D illustration of tractor trailor cab, garbage truck, and car. NREL research helps optimize the energy efficiency of a wide range of vehicle technologies and...

  6. Major Capital Projects

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

    BPA on 242015 and does not contain Agency-approved Financial Information. 1 Includes capital projects authorized at the agency level since August 2007 2 Direct capital costs...

  7. Major Capital Projects

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

    BPA on 622014 and does not contain Agency-approved Financial Information. 1 Includes capital projects authorized at the agency level since August 2007 2 Direct capital costs...

  8. Major Capital Projects

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

    on 1142014 and does not contain Agency-approved Financial Information. 1 Includes capital projects authorized at the agency level since August 2007 2 Direct capital costs...

  9. Major Capital Projects

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

    on 2112014 and does not contain Agency-approved Financial Information. 1 Includes capital projects authorized at the agency level since August 2007 2 Direct capital costs...

  10. Final Project Report

    SciTech Connect (OSTI)

    Wang, Qiang; Dandy, David S.

    2015-05-15

    This is the final technical report of the DOE project DE-FG02-07ER46448 awarded to Colorado State University.

  11. Portable Power Projects

    Broader source: Energy.gov [DOE]

    DOE's Portable Power, Auxiliary Power Units, and R&D for Off-Road Fuel Cell Applications Research Projects Awarded April 2004

  12. Project Reports | Department of Energy

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

    Project Reports Project Reports This page contains links to project reports summarizing the solid-state lighting projects funded by DOE, providing project descriptions and information on project partners, funding, and research period. The following documents are available as Adobe Acrobat PDFs. Download Adobe Reader. 2015 Project Portfolio Overviews of all current DOE-funded R&D projects related to solid-state lighting, including brief description, partners, funding level, and proposed time

  13. Project Management | Department of Energy

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

    Project Management Project Management Some of the Project Management Division’s many functions involve developing risk management plans, managing project risks, and providing input on prime contractor performance. Some of the Project Management Division's many functions involve developing risk management plans, managing project risks, and providing input on prime contractor performance. Employees in our Project Management Division address projects' planning and execution, as specified in

  14. Project Reports for Kootznoowoo Incorporated- 2010 Project

    Broader source: Energy.gov [DOE]

    Thayer Lake Hydropower Development (TLHD) consists of a 1 MW+ run of the river hydropower project located in the Tongass Forest in the Admiralty Island National Monument Park that will provide the energy to the City of Angoon and Angoon Community Association (traditional tribe as recognized by Indian Reorganization Act).

  15. River Protection Project (RPP) Project Management Plan

    SciTech Connect (OSTI)

    NAVARRO, J.E.

    2001-03-07

    The Office of River Protection (ORP) Project Management Plan (PMP) for the River Protection Project (RPP) describes the process for developing and operating a Waste Treatment Complex (WTC) to clean up Hanford Site tank waste. The Plan describes the scope of the project, the institutional setting within which the project must be completed, and the management processes and structure planned for implementation. The Plan is written from the perspective of the ORP as the taxpayers' representative. The Hanford Site, in southeastern Washington State, has one of the largest concentrations of radioactive waste in the world, as a result of producing plutonium for national defense for more than 40 years. Approximately 53 million gallons of waste stored in 177 aging underground tanks represent major environmental, social, and political challenges for the U.S. Department of Energy (DOE). These challenges require numerous interfaces with state and federal environmental officials, Tribal Nations, stakeholders, Congress, and the US Department of Energy-Headquarters (DOE-HQ). The cleanup of the Site's tank waste is a national issue with the potential for environmental and economic impacts to the region and the nation.

  16. Hydropower Projects | Department of Energy

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

    Projects Hydropower Projects This report covers the Wind and Water Power Technologies Office's hydropower projects from fiscal years 2008 to 2014. PDF icon Hydropower Projects 2008-2014 More Documents & Publications Marine and Hydrokinetic Energy Projects Offshore Wind Projects Real World Demonstration of a New American Low-Head Hydropower Unit

  17. DE-SC0004670 Final Technical Report Project Title: Two-Way Integration of WRF and CCSM for Regional Climate Simulations

    Office of Scientific and Technical Information (OSTI)

    SC0004670 Final Technical Report Project Title: Two-Way Integration of WRF and CCSM for Regional Climate Simulations Investigators: Wuyin Lin, Minghua Zhang, Xiangmin Jiao, Brian Colle, Andrew M. Vogelmann, Marat Khairoutdinov, and L. Ruby Leung Under the support of the DOE award DE-SC0004670, we have successfully developed an integrated climate modeling system by nesting Weather Research and Forecasting (WRF) model within the Community Climate System Model (CCSM) and the ensuing new generation

  18. Wind Energy Projects | Department of Energy

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

    Wind Energy Projects Wind Energy Projects Wind Energy Projects Wind Energy Projects Wind Energy Projects Wind Energy Projects Wind Energy Projects Wind Energy Projects Wind Energy Projects Wind Energy Projects Wind Energy Projects Wind Energy Projects WIND ENERGY 4 PROJECTS in 5 LOCATIONS 1,025 MW GENERATION CAPACITY 2,190,000 MWh PROJECTED ANNUAL GENERATION * 1,225,000 METRIC TONS OF CO2 EMISSIONS PREVENTED ANNUALLY ALL FIGURES AS OF MARCH 2015 * Calculated using the project's and NREL

  19. Project organizations and schedules

    SciTech Connect (OSTI)

    Briggs, R.J.

    1990-07-01

    The Superconducting Super Collider Laboratory (SSCL) faces the challenge of simultaneously carrying out a large-scale construction project with demanding cost, schedule, and performance goals; and creating a scientific laboratory capable of exploiting this unique scientific instrument. This paper describes the status of the laboratory organization developed to achieve these goals, and the major near-term schedule objectives of the project.

  20. The human genome project

    SciTech Connect (OSTI)

    Yager, T.D.; Zewert, T.E.; Hood, L.E. )

    1994-04-01

    The Human Genome Project (HGP) is a coordinated worldwide effort to precisely map the human genome and the genomes of selected model organisms. The first explicit proposal for this project dates from 1985 although its foundations (both conceptual and technological) can be traced back many years in genetics, molecular biology, and biotechnology. The HGP has matured rapidly and is producing results of great significance.

  1. The Home Microbiome Project

    SciTech Connect (OSTI)

    Gilbert, Jack

    2014-08-25

    The Home Microbiome Project is an initiative aimed at uncovering the dynamic co-associations between people's bacteria and the bacteria found in their homes.The hope is that the data and project will show that routine monitoring of the microbial diversity of your body and of the environment in which you live is possible.

  2. Coal. [Great Plains Project

    SciTech Connect (OSTI)

    Not Available

    1981-03-01

    The status of various research projects related to coal is considered: gasification (approximately 30 processes) and in-situ gasification. Methanol production, retrofitting internal combustion engines to stratified charge engines, methanation (Conoco), direct reduction of iron ores, water resources, etc. Approximately 200 specific projects related to coal are considered with respect to present status. (LTN)

  3. The Home Microbiome Project

    ScienceCinema (OSTI)

    Gilbert, Jack

    2014-09-15

    The Home Microbiome Project is an initiative aimed at uncovering the dynamic co-associations between people's bacteria and the bacteria found in their homes.The hope is that the data and project will show that routine monitoring of the microbial diversity of your body and of the environment in which you live is possible.

  4. PROJECT MANGEMENT PLAN EXAMPLES Prepare Project Support Plans and

    Office of Environmental Management (EM)

    Risk Assessment Examples Example 54 10.0 PROJECT RISK This section outlines a methodology which will be used to qualitatively/subjectively assess the project risk. The approach is modeled after project risk assessment processes outlined in standard project management texts and training courses but tailored to the unique risks encountered in the DOE projects. In the context of this section, project risk means risk to one of the project baselines (technical, cost, or schedule) and should not be

  5. Project Reports for Seneca Nation - 2007 Project | Department of Energy

    Energy Savers [EERE]

    Seneca Nation - 2007 Project Project Reports for Seneca Nation - 2007 Project On the three territories of the Seneca Nation, there exist opportunities for energy development from both renewable and nonrenewable resources. Learn more about this project or find details in the below status reports. PDF icon November 2007 status report PDF icon November 2008 status report PDF icon Final report More Documents & Publications Project Reports for Seneca Nation - 2003 Project Project Reports for

  6. GAD (Smart Grid Project) | Open Energy Information

    Open Energy Info (EERE)

    Projects in Europe Smart Grid Projects - Smart Meter and AMI Smart Grid Projects - Integrated System Smart Grid Projects - Home application Smart Grid Projects - Customer Behavior...

  7. Address (Smart Grid Project) | Open Energy Information

    Open Energy Info (EERE)

    Categories: Smart Grid Projects Smart Grid Projects in Europe Smart Grid Projects - Integrated System Smart Grid Projects - Home application Smart Grid Projects - Customer Behavior...

  8. 2016 Project Portfolio | Department of Energy

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

    6 Project Portfolio 2016 Project Portfolio PDF icon 2016ssl-project-portfolio.pdf More Documents & Publications 2015 Project Portfolio 2014 Solid-State Lighting Project Portfolio ...

  9. Comparing Price Forecast Accuracy of Natural Gas Models andFutures Markets

    SciTech Connect (OSTI)

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

    2005-06-30

    The purpose of this article is to compare the accuracy of forecasts for natural gas prices as reported by the Energy Information Administration's Short-Term Energy Outlook (STEO) and the futures market for the period from 1998 to 2003. The analysis tabulates the existing data and develops a statistical comparison of the error between STEO and U.S. wellhead natural gas prices and between Henry Hub and U.S. wellhead spot prices. The results indicate that, on average, Henry Hub is a better predictor of natural gas prices with an average error of 0.23 and a standard deviation of 1.22 than STEO with an average error of -0.52 and a standard deviation of 1.36. This analysis suggests that as the futures market continues to report longer forward prices (currently out to five years), it may be of interest to economic modelers to compare the accuracy of their models to the futures market. The authors would especially like to thank Doug Hale of the Energy Information Administration for supporting and reviewing this work.

  10. Demand forecasting and revenue requirements, with implications for consideration in British Columbia

    SciTech Connect (OSTI)

    Acton, J.P.

    1983-05-01

    This paper was filed as an exhibit on behalf of The Consumers' Association of Canada (B.C. Branch), The Federated Anti-Poverty Groups of B.C., The Sierra Club of Western Canada, and the B.C. Old Age Pensioners' Organization. It was subjected to cross-examination on October 29, 1982, during Phase I of the hearings. The Utilities Commission had designated Phase I for consideration of (1) demand, (2) assets in service, (3) revenue requirements excluding return, and (4) financing and capital requirements. This paper presents a general discussion of the elements of a rate structure and their relationship to the demand for electricity, a systematic review of some 50 empirical studies of the demand for electricity as a function of price and other factors by the three principal classes of customers, and a discussion of the notion of revenue requirements. The paper should be of interest to utility regulators, rate specialists, and forecasters for its review of demand models and to academics concerned with the study of energy demand.

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

    SciTech Connect (OSTI)

    Letschert, Virginie; McNeil, Michael A.

    2009-03-23

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

  12. Project Reports for Yurok Tribe- 2005 Project

    Broader source: Energy.gov [DOE]

    The Yurok Tribe has a great need for improved energy services on the reservation. The members pay $328 per month per household on average for energy, with just a $9,000 median household income. The project will assess the need for energy efficiency services on the reservation, identify available resources, and develop an implementation plan for meeting these needs. With an unemployment rate of 42%, the job training component of this program will benefit the tribe. Past attempts have been made to provide energy efficiency and renewable energy maintenance services on the reservation, but many of these services have not endured because they were not tribe-driven. This project will build tribal expertise, increase awareness, and form collaborative relationships with local energy services.

  13. Combining multi-objective optimization and bayesian model averaging to calibrate forecast ensembles of soil hydraulic models

    SciTech Connect (OSTI)

    Vrugt, Jasper A; Wohling, Thomas

    2008-01-01

    Most studies in vadose zone hydrology use a single conceptual model for predictive inference and analysis. Focusing on the outcome of a single model is prone to statistical bias and underestimation of uncertainty. In this study, we combine multi-objective optimization and Bayesian Model Averaging (BMA) to generate forecast ensembles of soil hydraulic models. To illustrate our method, we use observed tensiometric pressure head data at three different depths in a layered vadose zone of volcanic origin in New Zealand. A set of seven different soil hydraulic models is calibrated using a multi-objective formulation with three different objective functions that each measure the mismatch between observed and predicted soil water pressure head at one specific depth. The Pareto solution space corresponding to these three objectives is estimated with AMALGAM, and used to generate four different model ensembles. These ensembles are post-processed with BMA and used for predictive analysis and uncertainty estimation. Our most important conclusions for the vadose zone under consideration are: (1) the mean BMA forecast exhibits similar predictive capabilities as the best individual performing soil hydraulic model, (2) the size of the BMA uncertainty ranges increase with increasing depth and dryness in the soil profile, (3) the best performing ensemble corresponds to the compromise (or balanced) solution of the three-objective Pareto surface, and (4) the combined multi-objective optimization and BMA framework proposed in this paper is very useful to generate forecast ensembles of soil hydraulic models.

  14. North American LNG Project Sourcebook

    SciTech Connect (OSTI)

    2007-06-15

    The report provides a status of the development of LNG Import Terminal projects in North America, and includes 1-2 page profiles of 63 LNG projects in North America which are either in operation, under construction, or under development. For each project, the sourcebook provides information on the following elements: project description, project ownership, project status, projected operation date, storage capacity, sendout capacity, and pipeline interconnection.

  15. WINDExchange: Wind for Schools Project

    Wind Powering America (EERE)

    Participant Roles & Responsibilities Affiliate Projects Pilot Project Results Project Funding School Project Locations Education & Training Programs Curricula & Teaching Materials Resources Wind for Schools Project The U.S. Department of Energy funds the Wind for Schools project, which helps develop a future wind energy workforce by engaging students at higher education institutions to join Wind Application Centers and serve as project consultants for small wind turbine

  16. Development of an Immersed Boundary Method to Resolve Complex Terrain in the Weather Research and Forecasting Model

    SciTech Connect (OSTI)

    Lunquist, K A; Chow, F K; Lundquist, J K; Mirocha, J D

    2007-09-04

    Flow and dispersion processes in urban areas are profoundly influenced by the presence of buildings which divert mean flow, affect surface heating and cooling, and alter the structure of turbulence in the lower atmosphere. Accurate prediction of velocity, temperature, and turbulent kinetic energy fields are necessary for determining the transport and dispersion of scalars. Correct predictions of scalar concentrations are vital in densely populated urban areas where they are used to aid in emergency response planning for accidental or intentional releases of hazardous substances. Traditionally, urban flow simulations have been performed by computational fluid dynamics (CFD) codes which can accommodate the geometric complexity inherent to urban landscapes. In these types of models the grid is aligned with the solid boundaries, and the boundary conditions are applied to the computational nodes coincident with the surface. If the CFD code uses a structured curvilinear mesh, then time-consuming manual manipulation is needed to ensure that the mesh conforms to the solid boundaries while minimizing skewness. If the CFD code uses an unstructured grid, then the solver cannot be optimized for the underlying data structure which takes an irregular form. Unstructured solvers are therefore often slower and more memory intensive than their structured counterparts. Additionally, urban-scale CFD models are often forced at lateral boundaries with idealized flow, neglecting dynamic forcing due to synoptic scale weather patterns. These CFD codes solve the incompressible Navier-Stokes equations and include limited options for representing atmospheric processes such as surface fluxes and moisture. Traditional CFD codes therefore posses several drawbacks, due to the expense of either creating the grid or solving the resulting algebraic system of equations, and due to the idealized boundary conditions and the lack of full atmospheric physics. Meso-scale atmospheric boundary layer simulations, on the other hand, are performed by numerical weather prediction (NWP) codes, which cannot handle the geometry of the urban landscape, but do provide a more complete representation of atmospheric physics. NWP codes typically use structured grids with terrain-following vertical coordinates, include a full suite of atmospheric physics parameterizations, and allow for dynamic synoptic scale lateral forcing through grid nesting. Terrain following grids are unsuitable for urban terrain, as steep terrain gradients cause extreme distortion of the computational cells. In this work, we introduce and develop an immersed boundary method (IBM) to allow the favorable properties of a numerical weather prediction code to be combined with the ability to handle complex terrain. IBM uses a non-conforming structured grid, and allows solid boundaries to pass through the computational cells. As the terrain passes through the mesh in an arbitrary manner, the main goal of the IBM is to apply the boundary condition on the interior of the domain as accurately as possible. With the implementation of the IBM, numerical weather prediction codes can be used to explicitly resolve urban terrain. Heterogeneous urban domains using the IBM can be nested into larger mesoscale domains using a terrain-following coordinate. The larger mesoscale domain provides lateral boundary conditions to the urban domain with the correct forcing, allowing seamless integration between mesoscale and urban scale models. Further discussion of the scope of this project is given by Lundquist et al. [2007]. The current paper describes the implementation of an IBM into the Weather Research and Forecasting (WRF) model, which is an open source numerical weather prediction code. The WRF model solves the non-hydrostatic compressible Navier-Stokes equations, and employs an isobaric terrain-following vertical coordinate. Many types of IB methods have been developed by researchers; a comprehensive review can be found in Mittal and Iaccarino [2005]. To the authors knowledge, this is the first IBM approach that is able to

  17. Energy Efficiency Project Development

    SciTech Connect (OSTI)

    IUEP

    2004-03-01

    The International Utility Efficiency Partnerships, Inc. (IUEP) has been a leader among the industry groups that have supported voluntary initiatives to promote international energy efficiency projects and address global climate change. The IUEP maintains its leadership by both supporting international greenhouse gas (GHG) reduction projects under the auspices of the U.S. Department of Energy (DOE) and by partnering with U.S. and international organizations to develop and implement strategies and specific energy efficiency projects. The goals of the IUEP program are to (1) provide a way for U.S. industry to maintain a leadership role in international energy efficiency infrastructure projects; (2) identify international energy project development opportunities to continue its leadership in supporting voluntary market-based mechanisms to reduce GHG emissions; and (3) demonstrate private sector commitment to voluntary approaches to global climate issues. The IUEP is dedicated to identifying, promoting, managing, and assisting in the registration of international energy efficiency projects that result in demonstrated voluntary reductions of GHG emissions. This Final Technical Report summarizes the IUEP's work in identifying, promoting, managing, and assisting in development of these projects and IUEP's effort in creating international cooperative partnerships to support project development activities that develop and deploy technologies that (1) increase efficiency in the production, delivery and use of energy; (2) increase the use of cleaner, low-carbon fuels in processing products; and (3) capture/sequester carbon gases from energy systems. Through international cooperative efforts, the IUEP intends to strengthen partnerships for energy technology innovation and demonstration projects capable of providing cleaner energy in a cost-effective manner. As detailed in this report, the IUEP met program objectives and goals during the reporting period January 1, 2001 through December 31, 2002. At the request of the DOE, we have also included in this report additional activities during the reporting period January, 1999 through January, 2001. This additional information had been reported earlier in the Final Technical Reports that summarized activities undertaken in those earlier periods.

  18. Intra-Hour Dispatch and Automatic Generator Control Demonstration with Solar Forecasting

    Broader source: Energy.gov [DOE]

    The University of California at San Diego (UCSD) is leading a project that will reduce power system operation cost by providing a prediction of the generation fleet's behavior in real time for...

  19. Integrated Project Team RM

    Office of Environmental Management (EM)

    Integrated Project Team (IPT) Review Module March 2010 CD-0 This R O 0 Review Modul OFFICE OF Inte C CD-1 le was piloted F ENVIRO Standard R grated P Rev Critical Decis CD-2 M at the OR U 23 incorporated ONMENTAL Review Plan Project Te view Module sion (CD) Ap CD March 2010 33 Disposition in the Review L MANAGE n (SRP) eam (IPT e pplicability D-3 Project in 200 Module. EMENT T) CD-4 09. Lessons lea Post Ope arned have been eration n Standard Review Plan, 2 nd Edition, March 2010 i FOREWORD The

  20. NAVAJO ELECTRIFICATION DEMONSTRATION PROJECT

    SciTech Connect (OSTI)

    Terry W. Battiest

    2008-06-11

    The Navajo Electrification Demonstration Project (NEDP) is a multi-year project which addresses the electricity needs of the unserved and underserved Navajo Nation, the largest American Indian tribe in the United States. The program serves to cumulatively provide off-grid electricty for families living away from the electricty infrastructure, line extensions for unserved families living nearby (less than 1/2 mile away from) the electricity, and, under the current project called NEDP-4, the construction of a substation to increase the capacity and improve the quality of service into the central core region of the Navajo Nation.

  1. Tulalip Tribe - Biogas Project

    Energy Savers [EERE]

    Bio-Gas Project Daryl Williams November 18, 2008 Introduction Background Description of Project Partnership Feasibility Study/Business Plan Creation of Quil Ceda Power Funding Creation of Qualco Energy Closing Background Land-Use Changes from Agriculture to Other Types of Development Skykomish River WQ Problems Bacteria Nutrient Loading Relationship Between Tribes and Dairies Poor Economy for Dairy Operations Project Description Sewage Treatment for

  2. Breckinridge Project, initial effort. Report X. Economic analysis and financial plan

    SciTech Connect (OSTI)

    1982-01-01

    The economic evaluation presented in this volume is based upon the cost estimates developed in the Phase Zero effort and an evaluation of product market values developed by the PACE Company Engineers and Consultants, Inc. All costs and revenues have been adjusted to reflect the impact of inflation, consistent with the forecast shown in Table 2.1, Page 2-19. Tax treatment reflects expert interpretation of the tax law in effect January 1981. The Marketing Analysis section is an abstract of a detailed report prepared by the PACE Company for the Breckinridge Project. It provides the reader with an understanding of the methodology used to establish product values, and identifies and interprets the effects of key variables that impact market prices. The base case economic scenario, considered the most likely to occur, anticipates that the world economic growth, as well as that of the United States, will be substantially less than that experienced during the previous twenty years. Under the scenario, major disruptions in crude oil supply will not occur. Therefore, prices in real terms at the end of this century are projected to be slightly higher than the peak price of 1981. Domestic natural gas supplies are expected to expand as a result of deregulation and increased importation of LNG. Two alternate economic scenarios are also considered. Sensitivity analysis of both alternate economic scenarios and key project variables clearly point to the market price of crude oil as the dominant economic factor determining this project's soundness. The base case forecast is considered to be not only the most likely case but one not likely to be proven optimistic. The Financial Plan section outlines provisions and presents a plan for financial management of the project.

  3. Hydrothermal Projects | Department of Energy

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

    Hydrothermal Projects Hydrothermal Projects Hydrothermal Projects Geothermal electricity production has grown steadily, tapping a reliable, nearly inexhaustible reserve of hydrothermal systems where fluid, heat, and permeability intersect naturally in the subsurface. The United States Geological Survey estimates that 30 GW of hydrothermal resources lie beneath the surface--ten times the current installed capacity. Hydrothermal Projects Projects Database Program Links What is Play Fairway

  4. Winnebago Tribe- 2014 Project

    Broader source: Energy.gov [DOE]

    Following through with the Winnebago Tribe's commitment to reduce energy usage and consumption, the Winnebago Tribe Solar Project will focus on renewable energy production and energy cost savings consistent with protecting our natural environment.

  5. Renewable energy projects approved

    Broader source: Energy.gov [DOE]

    Two renewable energy projects representing a $100 million-plus investment by Las Vegas-based Nevada Power Co.—a cost likely to be covered over time by the utility's customers—were approved Wednesday by state regulators.

  6. Power Project Loan Fund

    Office of Energy Efficiency and Renewable Energy (EERE)

    The loan term is related to the life of the project, but may not exceed 50 years. Interest rates are the lesser of the average weekly yield of municipal bonds for the 12 months preceding the date...

  7. Hualapai Tribe- 2010 Project

    Broader source: Energy.gov [DOE]

    The project will build on the potential for renewable energy development on the Hualapai Reservation that was identified during the Phase l renewable energy resource assessment conducted by the Hualapai Tribe since 2005.

  8. START Program Project Sites

    Broader source: Energy.gov [DOE]

    The Strategic Technical Assistance Response Team (START) Program is part of the DOE Office of Indian Energy effort to assist in the development of tribal renewable energy projects. Through START,...

  9. NATURALHY Project Overview

    Broader source: Energy.gov [DOE]

    Presentation by 05-Florisson to DOE Hydrogen Pipeline R&D Project Review Meeting held January 5-6, 2005 at Oak Ridge National Laboratory in Oak Ridge, Tennessee.

  10. Lake Charles CCS Project

    SciTech Connect (OSTI)

    Leib, Thomas; Cole, Dan

    2015-06-30

    In late September 2014 development of the Lake Charles Clean Energy (LCCE) Plant was abandoned resulting in termination of Lake Charles Carbon Capture and Sequestration (CCS) Project which was a subset the LCCE Plant. As a result, the project was only funded through Phase 2A (Design) and did not enter Phase 2B (Construction) or Phase 2C (Operations). This report was prepared relying on information prepared and provided by engineering companies which were engaged by Leucadia Energy, LLC to prepare or review Front End Engineering and Design (FEED) for the Lake Charles Clean Energy Project, which includes the Carbon Capture and Sequestration (CCS) Project in Lake Charles, Louisiana. The Lake Charles Carbon Capture and Sequestration (CCS) Project was to be a large-scale industrial CCS project intended to demonstrate advanced technologies that capture and sequester carbon dioxide (CO2) emissions from industrial sources into underground formations. The Scope of work was divided into two discrete sections; 1) Capture and Compression prepared by the Recipient Leucadia Energy, LLC, and 2) Transport and Sequestration prepared by sub-Recipient Denbury Onshore, LLC. Capture and Compression-The Lake Charles CCS Project Final Technical Report describes the systems and equipment that would be necessary to capture CO2 generated in a large industrial gasification process and sequester the CO2 into underground formations. The purpose of each system is defined along with a description of its equipment and operation. Criteria for selection of major equipment are provided and ancillary utilities necessary for safe and reliable operation in compliance with environmental regulations are described. Construction considerations are described including a general arrangement of the CCS process units within the overall gasification project. A cost estimate is provided, delineated by system area with cost breakdown showing equipment, piping and materials, construction labor, engineering, and other costs. The CCS Project Final Technical Report is based on a Front End Engineering and Design (FEED) study prepared by SK E&C, completed in [June] 2014. Subsequently, Fluor Enterprises completed a FEED validation study in mid-September 2014. The design analyses indicated that the FEED package was sufficient and as expected. However, Fluor considered the construction risk based on a stick-build approach to be unacceptable, but construction risk would be substantially mitigated through utilization of modular construction where site labor and schedule uncertainty is minimized. Fluor’s estimate of the overall EPC project cost utilizing the revised construction plan was comparable to SKE&C’s value after reflecting Fluor’s assessment of project scope and risk characteristic. Development was halted upon conclusion of Phase 2A FEED and the project was not constructed.Transport and Sequestration – The overall objective of the pipeline project was to construct a pipeline to transport captured CO2 from the Lake Charles Clean Energy project to the existing Denbury Green Line and then to the Hastings Field in Southeast Texas to demonstrate effective geologic sequestration of captured CO2 through commercial EOR operations. The overall objective of the MVA portion of the project was to demonstrate effective geologic sequestration of captured CO2 through commercial Enhanced Oil Recovery (EOR) operations in order to evaluate costs, operational processes and technical performance. The DOE target for the project was to capture and implement a research MVA program to demonstrate the sequestration through EOR of approximately one million tons of CO2 per year as an integral component of commercial operations.

  11. Project Management Plan Examples

    Broader source: Energy.gov [DOE]

    The following material has been extracted from several project management plans. The order in which it is presented is arbitrary. The elements table below should be used to navigate to the subject...

  12. Capital Project Authorization

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

    This policy applies to capital projects in these asset categories: 1. Transmission investment in assets owned or leased by BPA, whether funded by bonds issued to the U.S....

  13. Pawnee Nation- 2006 Project

    Broader source: Energy.gov [DOE]

    The primary goal of this project is to move the energy vision of the Pawnee Nation forward by conducting specific data collection and analysis tasks to assess the viable options available to Pawnee to meet future energy needs sustainable.

  14. CNEEC - Research Projects

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

    of developing systems that can lead to break-out high-efficiency, cost-effective solar energy-to-fuel technologies. The projects are closely tied together through two mechanisms:...

  15. Navajo Electrification Demonstraiton Project

    SciTech Connect (OSTI)

    Larry Ahasteen, Project Manager

    2006-07-17

    This is a final technical report required by DOE for the Navajo Electrification Demonstration Program, This report covers the electric line extension project for Navajo families that currently without electric power.

  16. Offshore Wind Project Map

    Broader source: Energy.gov [DOE]

    Image that shows the demonstration project site and developer headquarters for two funding opportunity announcements: the 2011 Grants for Technology Development and the 2011 Grants for Removing Market Barriers.

  17. Portsmouth Paducah Project Office

    Broader source: Energy.gov [DOE]

    The U.S. Department of Energy (DOE) established the Portsmouth/Paducah Project Office (PPPO) on October 1, 2003, to provide focused leadership to the Environmental Management missions at the...

  18. St. Bernard Project Update

    Broader source: Energy.gov [DOE]

    The folks at St. Bernard Project are helping survivors of Hurricane Katrina get back into their homes -- and are using new technologies to reduce energy and save money for the returning residents.

  19. Major Capital Projects

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

    93016 500 kV Spare Transformer Project Acquire 5 spares and relocate 2 existing transformers to be used as spares. The spares will be placed strategically across the system....

  20. Major Capital Projects

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

    thru FY14 500 kV Spare Transformer Project Acquire 5 spares and relocate 2 existing transformers to be used as spares. The spares will be placed strategically across the system....

  1. Major Capital Projects

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

    122818 500 kV Spare Transformer Project Acquire 5 spares and relocate 2 existing transformers to be used as spares. The spares will be placed strategically across the system....

  2. Major Capital Projects

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

    121917 500 kV Spare Transformer Project Acquire 5 spares and relocate 2 existing transformers to be used as spares. The spares will be placed strategically across the system....

  3. Manhattan Project: People

    Office of Scientific and Technical Information (OSTI)

    groups of people contributing to the success of the Manhattan Project can be obtained by reading the summary pages for each of the categories, located in the left navigation bar. ...

  4. Chickasaw Nation- 2010 Project

    Broader source: Energy.gov [DOE]

    Under this project, the Chickasaw Nation, Division of Commerce (CNDC) will upgrade old, inefficient lighting systems throughout CNDC to new, energy saving systems. This will be the first step in a...

  5. Project financial evaluation

    SciTech Connect (OSTI)

    None, None

    2009-01-18

    The project financial section of the Renewable Energy Technology Characterizations describes structures and models to support the technical and economic status of emerging renewable energy options for electricity supply.

  6. Black Pine Circle Project

    ScienceCinema (OSTI)

    Mytko, Christine

    2014-09-15

    A group of seventh graders from Black Pine Circle school in Berkeley had the opportunity to experience the Advanced Light Source (ALS) as "users" via a collaborative field trip and proposal project. The project culminated with a field trip to the ALS for all seventh graders, which included a visit to the ALS data visualization room, a diffraction demonstration, a beamline tour, and informative sessions about x-rays and tomography presented by ALS scientists.

  7. PROJECT TASK STATEMENT

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

    PROJECT TASK STATEMENT BETWEEN Sandia Corporation AND British East India Company a corporation of the United Kingdom having a principal office in London, United Kingdom (hereinafter "Participant") Geothermal Dynamics This Project Task Statement (PTS) is under the authority and subject to all terms and conditions of Cooperative Research and Development Agreement (CRADA) No. SC##/####.##.##. A. PURPOSE Sandia National Laboratories (Sandia) and the British East India Company (BEIC) are

  8. Black Pine Circle Project

    SciTech Connect (OSTI)

    Mytko, Christine

    2014-03-31

    A group of seventh graders from Black Pine Circle school in Berkeley had the opportunity to experience the Advanced Light Source (ALS) as "users" via a collaborative field trip and proposal project. The project culminated with a field trip to the ALS for all seventh graders, which included a visit to the ALS data visualization room, a diffraction demonstration, a beamline tour, and informative sessions about x-rays and tomography presented by ALS scientists.

  9. PROJECT MANGEMENT PLAN EXAMPLES

    Office of Environmental Management (EM)

    Integrated Safety Management Examples Example 10 8.2 PFP INTEGRATED SAFETY STRATEGY The following discussion identifies the process that will be used by the PFP Stabilization and Deactivation Project to ensure that the safety of the worker, public, and the environment are adequately addressed during the project. The primary activities involved in the process include the following:  Implementation of the Integrated Safety Management System (ISMS),  Identification, control, or mitigation of

  10. PROJECT MANGEMENT PLAN EXAMPLES

    Office of Environmental Management (EM)

    Development of Detailed End Points - End Point Document Examples Example 28 7.0 ENDPOINTS Chapter 7.0 describes the endpoint development principles and methodology, administration, closure, and turnover package for the 324 and 327 Buildings Stabilization/Deactivation Project. 7.1 Background The endpoint method for the 324 and 327 Buildings Stabilization/Deactivation Project will follow the EM-60 guidance, published in DOE/EM-0318, Rev. 0, U.S. Department of Energy, Office of Environmental

  11. Manhattan Project: Places

    Office of Scientific and Technical Information (OSTI)

    Places "Met Lab" (Metallurgical Laboratory) Oak Ridge: Clinton Engineer Works Hanford Engineer Works Los Alamos Other Places Places of the Manhattan Project Places PLEASE NOTE: The Places pages are not yet available. Links to the pages listed below and to the left will be activated as content is developed. Select topics relating to the places where the Manhattan Project occurred have been grouped into the categories listed to the left. A quick overview of places involved in the

  12. Manhattan Project: Science

    Office of Scientific and Technical Information (OSTI)

    Science In the Laboratory Particle Accelerators and Other Technologies The Atom and Atomic Structure Nuclear Physics Bomb Design and Components Radioactivity Science and technology of the Manhattan Project Science PLEASE NOTE: The Science pages are not yet available. Links to the pages listed below and to the left will be activated as content is developed. Select topics relating to the science and technology of the Manhattan Project have been grouped into the categories listed to the left. A

  13. Hopi Tribe- 2005 Project

    Broader source: Energy.gov [DOE]

    The Hopi Tribe will conduct a feasibility study to determine if development of a utility-scale wind power project with a capacity of approximately 100 MW located on Hopi lands held in fee simple in northern Arizona is feasible. If the feasibility study determines there is no impact or minimal impact to the environment, the tribe may develop the wind power project on two large mesas called East and West Sunset Mountains approximately 16 miles southwest of the city of Winslow.

  14. The Manhattan Project

    Office of Scientific and Technical Information (OSTI)

    The Manhattan Project Sites and Their Contributions * Key Events * Scientists * Its Story * Additional Information * Related Information President Roosevelt Establishes the Manhattan Project President Roosevelt instructs the Army to take responsibility for construction of atomic weapons complex. The Army delegates the task to the Corps of Engineers, which establishes the Manhattan Engineer District. Courtesy of National Nuclear Security Administration August 13, 2012 was the 70th anniversary of

  15. BETO Active Project Management

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

    BETO Active Project Management Bioenergy Technologies Office - Program Management Review 6/25/15 Liz Moore Technology Manager eere.energy.gov Program Managers * Manages portfolio within their technology area * Establishes technical and cost goals * Strategic planning for technology area * Budget preparation/justification for technology portfolio * Identifies needs for workshops and FOAs * Oversees portfolio reviews including high-level project status Technology Managers * Plans/conducts

  16. Reynolds Ceek Hydro Project

    Energy Savers [EERE]

    Reynolds Creek Hydroelectric Project Project Status October 28, 2010 By : Alvin Edenshaw, President Haida Corporation and Haida Energy, Inc. Haida Corporation  Located in Hydaburg on Prince of Wales Island in SE Alaska  Hydaburg population = 350 people (called Kaigani Haida)  Hydaburg is largest Haida Village in Alaska  Subsistence and Commercial Fishing Lifestyle  Substantial Timber Holdings  Hydaburg has Excellent School System October 28, 2009 2 Haida Energy, Inc.  Joint

  17. Reynolds Ceek Hydroelelctric Project

    Energy Savers [EERE]

    Hydroelectric Project Project Status November, 2011 By : Alvin Edenshaw, President Haida Corporation and Haida Energy, Inc. June 9, 2010 2 Haida Corporation b Located in Hydaburg on Prince of Wales Island in SE Alaska b Hydaburg population = 350 people (called Kaigani Haida) b Hydaburg is largest Haida Village in Alaska b Subsistence and Commercial Fishing Lifestyle b Substantial Timber Holdings b Hydaburg has Excellent School System June 9, 2010 3 Haida Energy, Inc. b Joint Venture b

  18. The Mississippi CCS Project

    SciTech Connect (OSTI)

    Doug Cathro

    2010-09-30

    The Mississippi CCS Project is a proposed large-scale industrial carbon capture and sequestration (CCS) project which would have demonstrated advanced technologies to capture and sequester carbon dioxide (CO{sub 2}) emissions from industrial sources into underground formations. Specifically, the Mississippi CCS Project was to accelerate commercialization of large-scale CO{sub 2} storage from industrial sources by leveraging synergy between a proposed petcoke to Substitute Natural Gas (SNG) plant that is selected for a Federal Loan Guarantee and would be the largest integrated anthropogenic CO{sub 2} capture, transport, and monitored sequestration program in the U.S. Gulf Coast Region. The Mississippi CCS Project was to promote the expansion of enhanced oil recovery (EOR) in the Mississippi, Alabama and Louisiana region which would supply greater energy security through increased domestic energy production. The capture, compression, pipeline, injection, and monitoring infrastructure would have continued to sequester CO{sub 2} for many years after the completion of the term of the DOE agreement. The objectives of this project were expected to be fulfilled through two distinct phases. The overall objective of Phase 1 was to develop a fully definitive project basis for a competitive Renewal Application process to proceed into Phase 2 - Design, Construction and Operations. Phase 1 included the studies that establish the engineering design basis for the capture, compression and transportation of CO{sub 2} from the MG SNG Project, and the criteria and specifications for a monitoring, verification and accounting (MVA) plan at the Soso oil field in Mississippi. The overall objective of Phase 2, was to execute design, construction and operations of three capital projects: the CO{sub 2} capture and compression equipment, the Mississippi CO{sub 2} Pipeline to Denbury's Free State Pipeline, and an MVA system at the Soso oil field.

  19. Hualapai Tribal Utility Project

    Office of Environmental Management (EM)

    Hualapai Tribal Utility Project Tribal Utility Project DOE First Steps Program DOE First Steps Program Jack Ehrhardt Jack Ehrhardt - - Hualapai Planning Director Hualapai Planning Director WHO WE ARE WHO WE ARE ~1 MILLION ACRES IN ~1 MILLION ACRES IN NW ARIZONA NW ARIZONA 108 MILES OF THE 108 MILES OF THE GRAND CANYON GRAND CANYON 2500 Members 2500 Members Peach Springs Peach Springs Community Community ~240 electric customers ~240 electric customers ECONOMIC SITUATION ECONOMIC SITUATION Very

  20. Integrated Projects - Non-DOE Projects | Department of Energy

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

    Technology Validation » Integrated Projects » Integrated Projects - Non-DOE Projects Integrated Projects - Non-DOE Projects In addition to the integrated technology validation projects sponsored by DOE, universities, along with state and local government entities throughout the world are partnering with industry to demonstrate integrated hydrogen and fuel cell technologies in real-world applications. GM/DOW Chemical Partnership The first General Motors fuel cell trailer is in place at the Dow