Sample records for wind energy forecasts

  1. Modeling of Uncertainty in Wind Energy Forecast

    E-Print Network [OSTI]

    regression and splines are combined to model the prediction error from Tunø Knob wind power plant. This data of the thesis is quantile regression and splines in the context of wind power modeling. Lyngby, February 2006Modeling of Uncertainty in Wind Energy Forecast Jan Kloppenborg Møller Kongens Lyngby 2006 IMM-2006

  2. Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center

    E-Print Network [OSTI]

    Washington at Seattle, University of

    Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime meteorological data from sites upwind of wind farms can be efficiently used to improve short-term forecasts acknowledges the support of PPM Energy, Inc. The data used in this work were obtained from Oregon State

  3. Probabilistic wind power forecasting -European Wind Energy Conference -Milan, Italy, 7-10 May 2007 Probabilistic short-term wind power forecasting

    E-Print Network [OSTI]

    Paris-Sud XI, Universit de

    Probabilistic wind power forecasting - European Wind Energy Conference - Milan, Italy, 7-10 May 2007 Probabilistic short-term wind power forecasting based on kernel density estimators Jeremie Juban jeremie.juban@ensmp.fr; georges.kariniotakis@ensmp.fr Abstract Short-term wind power forecasting tools

  4. Wind Energy Technology Trends: Comparing and Contrasting Recent Cost and Performance Forecasts (Poster)

    SciTech Connect (OSTI)

    Lantz, E.; Hand, M.

    2010-05-01T23:59:59.000Z

    Poster depicts wind energy technology trends, comparing and contrasting recent cost and performance forecasts.

  5. 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

    2011-03-28T23:59:59.000Z

    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.

  6. European Wind Energy Conference -Brussels, Belgium, April 2008 Data mining for wind power forecasting

    E-Print Network [OSTI]

    Paris-Sud XI, Universit de

    European Wind Energy Conference - Brussels, Belgium, April 2008 Data mining for wind power-term forecasting of wind energy produc- tion up to 2-3 days ahead is recognized as a major contribution the improvement of predic- tion systems performance is recognised as one of the priorities in wind energy research

  7. Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime-Switching

    E-Print Network [OSTI]

    Genton, Marc G.

    Calibrated Probabilistic Forecasting at the Stateline Wind Energy Center: The Regime at a wind energy site and fits a conditional predictive model for each regime. Geographically dispersed was applied to 2-hour-ahead forecasts of hourly average wind speed near the Stateline wind energy center

  8. Test application of a semi-objective approach to wind forecasting for wind energy applications

    SciTech Connect (OSTI)

    Wegley, H.L.; Formica, W.J.

    1983-07-01T23:59:59.000Z

    The test application of the semi-objective (S-O) wind forecasting technique at three locations is described. The forecasting sites are described as well as site-specific forecasting procedures. Verification of the S-O wind forecasts is presented, and the observed verification results are interpreted. Comparisons are made between S-O wind forecasting accuracy and that of two previous forecasting efforts that used subjective wind forecasts and model output statistics. (LEW)

  9. NCAR WRF-based data assimilation and forecasting systems for wind energy applications power

    E-Print Network [OSTI]

    Kim, Guebuem

    NCAR WRF-based data assimilation and forecasting systems for wind energy applications power Yuewei of these modeling technologies w.r.t. wind energy applications. Then I'll discuss wind farm

  10. European Wind Energy Conference & Exhibition EWEC 2003, Madrid, Spain. Forecasting of Regional Wind Generation by a Dynamic

    E-Print Network [OSTI]

    Paris-Sud XI, Universit de

    European Wind Energy Conference & Exhibition EWEC 2003, Madrid, Spain. Forecasting of Regional Wind. Abstract-Short-term wind power forecasting is recognized nowadays as a major requirement for a secure and economic integration of wind power in a power system. In the case of large-scale integration, end users

  11. Wind Forecasting Improvement Project | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilA group currentBradley NickellApril 16, 2008 TBD-0075 -In theWide

  12. 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.

    2011-10-01T23:59:59.000Z

    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.

  13. MPC for Wind Power Gradients --Utilizing Forecasts, Rotor Inertia, and Central Energy Storage

    E-Print Network [OSTI]

    MPC for Wind Power Gradients -- Utilizing Forecasts, Rotor Inertia, and Central Energy Storage define an extremely low power output gradient and demonstrate how decentralized energy storage conservative bids on the power market. Energy storage strikes the major problems of wind power and joining

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

    Office of Environmental Management (EM)

    The Wind Forecast Improvement Project (WFIP): A PublicPrivate Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations The...

  15. The Value of Wind Power Forecasting

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

    Wind Power Forecasting Preprint Debra Lew and Michael Milligan National Renewable Energy Laboratory Gary Jordan and Richard Piwko GE Energy Presented at the 91 st American...

  16. Wind Speed Forecasting for Power System Operation

    E-Print Network [OSTI]

    Zhu, Xinxin

    2013-07-22T23:59:59.000Z

    In order to support large-scale integration of wind power into current electric energy system, accurate wind speed forecasting is essential, because the high variation and limited predictability of wind pose profound challenges to the power system...

  17. Wind Speed Forecasting for Power System Operation

    E-Print Network [OSTI]

    Zhu, Xinxin

    2013-07-22T23:59:59.000Z

    In order to support large-scale integration of wind power into current electric energy system, accurate wind speed forecasting is essential, because the high variation and limited predictability of wind pose profound challenges to the power system...

  18. 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 [WindLogics

    2014-04-30T23:59:59.000Z

    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. A comprehensive analysis of wind energy forecast errors for the various model-based power forecasts was presented for a suite of wind energy ramp definitions. The results compiled over the year-long study period showed that the power forecasts based on the research models (ESRL_RAP, HRRR) more accurately predict wind energy ramp events than the current operational forecast models, both at the system aggregate level and at the local wind plant level. At the system level, the ESRL_RAP-based forecasts most accurately predict both the total number of ramp events and the occurrence of the events themselves, but the HRRR-based forecasts more accurately predict the ramp rate. At the individual site level, the HRRR-based forecasts most accurately predicted the actual ramp occurrence, the total number of ramps and the ramp rates (40-60% improvement in ramp rates over the coarser resolution forecast

  19. 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.

    2010-01-01T23:59:59.000Z

    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.

  20. Wind Energy Management System 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.

    2010-09-01T23:59:59.000Z

    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 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 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. In order 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. In this report, a new methodology to predict the uncertainty ranges for the required balancing capacity, ramping capability and ramp duration is presented. Uncertainties created by system load forecast errors, wind and solar forecast errors, generation forced outages are taken into account. The uncertainty ranges are evaluated for different confidence levels of having the actual generation requirements within the corresponding limits. The methodology helps to identify system balancing reserve requirement based on a desired system performance levels, identify system breaking points, where the generation system becomes unable to follow the generation requirement curve with the user-specified probability level, and determine the time remaining to these potential events. 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 (California ISO) real life data have shown the effectiveness of the proposed approach. A tool developed based on the new methodology described in this report will be integrated with the California ISO systems. Contractual work is currently in place to integrate the tool with the AREVA EMS system.

  1. ANL Wind Power Forecasting and Electricity Markets | Open Energy

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2,AUDITCaliforniaWeifangwiki Home Jweers'sAIRMaster+

  2. Value of Wind Power Forecasting

    SciTech Connect (OSTI)

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

    2011-04-01T23:59:59.000Z

    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.

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742Energy China 2015ofDepartmentDepartment of2 of 5) ALARA TrainingANDREW W. TUNNELL t: (205)This is

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del SolStrengthening a solidSynthesisAppliances Tips: ShoppingAdministrationToday's

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn't Your Destiny: The Future of1 A Strategic Framework for8.pdfAL2008-07.pdf2ProgramAMWTPANDREW

  6. 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

    SciTech Connect (OSTI)

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

    2014-04-30T23:59:59.000Z

    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.

  7. Wind Power Forecasting Data

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron SpinPrincetonUsingWhat is abig world of tinyWind Industry

  8. A survey on wind power ramp forecasting.

    SciTech Connect (OSTI)

    Ferreira, C.; Gama, J.; Matias, L.; Botterud, A.; Wang, J. (Decision and Information Sciences); (INESC Porto)

    2011-02-23T23:59:59.000Z

    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. Wind Power Forecasting andWind Power Forecasting and Electricity Market Operations

    E-Print Network [OSTI]

    Kemner, Ken

    forecasting methods and better integration of advanced wind power forecasts into system and plant operations and wind power plants) ­ Review and assess current practices Propose and test new and improved approachesWind Power Forecasting andWind Power Forecasting and Electricity Market Operations Audun Botterud

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

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

    collects data on a variety of physical processes that impact the wind forecasts used by wind farms, system operators and other industry professionals. By having access to...

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

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

    collects data on a variety of physical processes that impact the wind forecasts used by wind farms, system operators and other industry professionals. By having access to...

  12. EWEC 2006, Athens, The Anemos Wind Power Forecasting Platform Technology The Anemos Wind Power Forecasting Platform Technology -

    E-Print Network [OSTI]

    Boyer, Edmond

    the fluctuating output from wind farms into power plant dispatching and energy trading, wind power predictionsEWEC 2006, Athens, The Anemos Wind Power Forecasting Platform Technology 1 The Anemos Wind Power a professional, flexible platform for operating wind power prediction models, laying the main focus on state

  13. Optimal combined wind power forecasts using exogeneous variables

    E-Print Network [OSTI]

    Optimal combined wind power forecasts using exogeneous variables Fannar Orn Thordarson Kongens of the thesis is combined wind power forecasts using informations from meteorological forecasts. Lyngby, January

  14. Optimal Bidding Strategies for Wind Power Producers with Meteorological Forecasts

    E-Print Network [OSTI]

    Giannitrapani, Antonello

    bid is computed by exploiting the forecast energy price for the day ahead market, the historical wind renewable energy resources, such as wind and photovoltaic, has grown rapidly. It is well known the problem of optimizing energy bids for an independent Wind Power Producer (WPP) taking part

  15. Wind Power Forecasting

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del SolStrengtheningWildfires may contribute more to global

  16. Development and Deployment of an Advanced Wind Forecasting Technique

    E-Print Network [OSTI]

    Kemner, Ken

    findings. Part 2 addresses how operators of wind power plants and power systems can incorporate advanced the output of advanced wind energy forecasts into decision support models for wind power plant and power and applications of power market simulation models around the world. Argonne's software tools are used extensively

  17. New Concepts in Wind Power Forecasting Models

    E-Print Network [OSTI]

    Kemner, Ken

    New Concepts in Wind Power Forecasting Models Vladimiro Miranda, Ricardo Bessa, Joo Gama, Guenter to the training of mappers such as neural networks to perform wind power prediction as a function of wind characteristics (mainly speed and direction) in wind parks connected to a power grid. Renyi's Entropy is combined

  18. PSO (FU 2101) Ensemble-forecasts for wind power

    E-Print Network [OSTI]

    PSO (FU 2101) Ensemble-forecasts for wind power Analysis of the Results of an On-line Wind Power Ensemble- forecasts for wind power (FU2101) a demo-application producing quantile forecasts of wind power correct) quantile forecasts of the wind power production are generated by the application. However

  19. The effects of energy storage properties and forecast accuracy on mitigating variability in wind power generation

    E-Print Network [OSTI]

    Jaworsky, Christina A

    2013-01-01T23:59:59.000Z

    Electricity generation from wind power is increasing worldwide. Wind power can offset traditional fossil fuel generators which is beneficial to the environment. However, wind generation is unpredictable. Wind speeds have ...

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

    SciTech Connect (OSTI)

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

    2011-10-01T23:59:59.000Z

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

  1. 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. (Decision and Information Sciences); (INESC Porto)

    2011-11-29T23:59:59.000Z

    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.

  2. PSO (FU 2101) Ensemble-forecasts for wind power

    E-Print Network [OSTI]

    PSO (FU 2101) Ensemble-forecasts for wind power Wind Power Ensemble Forecasting Using Wind Speed the problems of (i) transforming the meteorological ensembles to wind power ensembles and, (ii) correcting) data. However, quite often the actual wind power production is outside the range of ensemble forecast

  3. Subhourly wind forecasting techniques for wind turbine operations

    SciTech Connect (OSTI)

    Wegley, H.L.; Kosorok, M.R.; Formica, W.J.

    1984-08-01T23:59:59.000Z

    Three models for making automated forecasts of subhourly wind and wind power fluctuations were examined to determine the models' appropriateness, accuracy, and reliability in wind forecasting for wind turbine operation. Such automated forecasts appear to have value not only in wind turbine control and operating strategies, but also in improving individual wind turbine control and operating strategies, but also in improving individual wind turbine operating strategies (such as determining when to attempt startup). A simple persistence model, an autoregressive model, and a generalized equivalent Markhov (GEM) model were developed and tested using spring season data from the WKY television tower located near Oklahoma City, Oklahoma. The three models represent a pure measurement approach, a pure statistical method and a statistical-dynamical model, respectively. Forecasting models of wind speed means and measures of deviations about the mean were developed and tested for all three forecasting techniques for the 45-meter level and for the 10-, 30- and 60-minute time intervals. The results of this exploratory study indicate that a persistence-based approach, using onsite measurements, will probably be superior in the 10-minute time frame. The GEM model appears to have the most potential in 30-minute and longer time frames, particularly when forecasting wind speed fluctuations. However, several improvements to the GEM model are suggested. In comparison to the other models, the autoregressive model performed poorly at all time frames; but, it is recommended that this model be upgraded to an autoregressive moving average (ARMA or ARIMA) model. The primary constraint in adapting the forecasting models to the production of wind turbine cluster power output forecasts is the lack of either actual data, or suitable models, for simulating wind turbine cluster performance.

  4. Verification of hourly forecasts of wind turbine power output

    SciTech Connect (OSTI)

    Wegley, H.L.

    1984-08-01T23:59:59.000Z

    A verification of hourly average wind speed forecasts in terms of hourly average power output of a MOD-2 was performed for four sites. Site-specific probabilistic transformation models were developed to transform the forecast and observed hourly average speeds to the percent probability of exceedance of an hourly average power output. (This transformation model also appears to have value in predicting annual energy production for use in wind energy feasibility studies.) The transformed forecasts were verified in a deterministic sense (i.e., as continuous values) and in a probabilistic sense (based upon the probability of power output falling in a specified category). Since the smoothing effects of time averaging are very pronounced, the 90% probability of exceedance was built into the transformation models. Semiobjective and objective (model output statistics) forecasts were made compared for the four sites. The verification results indicate that the correct category can be forecast an average of 75% of the time over a 24-hour period. Accuracy generally decreases with projection time out to approx. 18 hours and then may increase due to the fairly regular diurnal wind patterns that occur at many sites. The ability to forecast the correct power output category increases with increasing power output because occurrences of high hourly average power output (near rated) are relatively rare and are generally not forecast. The semiobjective forecasts proved superior to model output statistics in forecasting high values of power output and in the shorter time frames (1 to 6 hours). However, model output statistics were slightly more accurate at other power output levels and times. Noticeable differences were observed between deterministic and probabilistic (categorical) forecast verification results.

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

    SciTech Connect (OSTI)

    Hodge, B.

    2013-12-01T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.

    2014-04-01T23:59:59.000Z

    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.

  7. 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.

    2012-09-01T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

    Hodge, B. M.; Milligan, M.

    2011-07-01T23:59:59.000Z

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

  9. Skill forecasting from different wind power ensemble prediction methods This article has been downloaded from IOPscience. Please scroll down to see the full text article.

    E-Print Network [OSTI]

    Paris-Sud XI, Universit de

    Skill forecasting from different wind power ensemble prediction methods This article has been Contact us My IOPscience #12;Skill forecasting from different wind power ensemble prediction methods uncertainty (and energy imbalances). Wind power ensemble predictions are derived from the transformation

  10. Wind Energy

    Broader source: Energy.gov [DOE]

    Presentation covers wind energy at the Federal Utility Partnership Working Group (FUPWG) meeting, held on November 18-19, 2009.

  11. Optimal Storage Policies with Wind Forecast Uncertainties [Extended Abstract

    E-Print Network [OSTI]

    Dalang, Robert C.

    Optimal Storage Policies with Wind Forecast Uncertainties [Extended Abstract] Nicolas Gast EPFL, IC generation. The use of energy storage compensates to some extent these negative effects; it plays a buffer role between demand and production. We revisit a model of real storage proposed by Bejan et al.[1]. We

  12. Gaussian Processes for Short-Horizon Wind Power Forecasting Joseph Bockhorst, Chris Barber

    E-Print Network [OSTI]

    Bockhorst, Joseph

    on this task, and attention has shifted to statistical and machine learning approaches. Among the challenges of wind energy into electrical trans- mission systems. The importance of wind forecasts for wind energy throughout a power system must be nearly in balance at all times, 2) because it depends strongly on wind

  13. WP2 IEA Wind Task 26:The Past and Future Cost of Wind Energy

    E-Print Network [OSTI]

    Lantz, Eric

    2014-01-01T23:59:59.000Z

    Chinas activities alone could nearly double global capacity by 2020. The Global Wind Energy Council deployment forecast

  14. Forecasting Uncertainty Related to Ramps of Wind Power Production

    E-Print Network [OSTI]

    Boyer, Edmond

    - namic reserve quantification [8], for the optimal oper- ation of combined wind-hydro power plants [5, 1Forecasting Uncertainty Related to Ramps of Wind Power Production Arthur Bossavy, Robin Girard - The continuous improvement of the accuracy of wind power forecasts is motivated by the increasing wind power

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

    Office of Environmental Management (EM)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742 33Frequently Asked QuestionsDepartment ofDepartment of Energy NewPollution,Prudent

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative FuelsNovember 13,Statement | DepartmentBlog Energy BlogDeployment |Geothermal

  17. Wind-Wave Probabilistic Forecasting based on Ensemble

    E-Print Network [OSTI]

    have to be jointly taken into account in some decision-making problems, e.g. offshore wind farmWind-Wave Probabilistic Forecasting based on Ensemble Predictions Maxime FORTIN Kongens Lyngby 2012.imm.dtu.dk IMM-PhD-2012-86 #12;Summary Wind and wave forecasts are of a crucial importance for a number

  18. Wind Power Forecasting: State-of-the-Art 2009

    E-Print Network [OSTI]

    Kemner, Ken

    Wind Power Forecasting: State-of-the-Art 2009 ANL/DIS-10-1 Decision and Information Sciences about Argonne and its pioneering science and technology programs, see www.anl.gov. #12;Wind Power................................................ 14 2.2.3 Critical Processes for Wind Forecast

  19. Managing Wind Power Forecast Uncertainty in Electric Brandon Keith Mauch

    E-Print Network [OSTI]

    i Managing Wind Power Forecast Uncertainty in Electric Grids Brandon Keith Mauch Co for the modeled wind- CAES system would not cover annualized capital costs. We also estimate market prices-ahead market is roughly $100, with large variability due to electric power prices. Wind power forecast errors

  20. 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.

    2013-05-01T23:59:59.000Z

    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.

  1. 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.

    2012-09-01T23:59:59.000Z

    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.

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

    Office of Environmental Management (EM)

    Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report.pdf More Documents & Publications Computational Advances in Applied...

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

    SciTech Connect (OSTI)

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

    2014-05-01T23:59:59.000Z

    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.

  4. WIND ENERGY Wind Energ. (2014)

    E-Print Network [OSTI]

    Peinke, Joachim

    2014-01-01T23:59:59.000Z

    loads from the wind inflow through rotor aerodynamics, drive train and power electronics is stillWIND ENERGY Wind Energ. (2014) Published online in Wiley Online Library (wileyonlinelibrary wind inflow conditions M. R. Luhur, J. Peinke, J. Schneemann and M. Wchter ForWind-Center for Wind

  5. ENERGY DEMAND FORECAST METHODS REPORT

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION ENERGY DEMAND FORECAST METHODS REPORT Companion Report to the California Energy Demand 2006-2016 Staff Energy Demand Forecast Report STAFFREPORT June 2005 CEC-400. Hall Deputy Director Energy Efficiency and Demand Analysis Division Scott W. Matthews Acting Executive

  6. Skill forecasting from ensemble predictions of wind power P. Pinson,a

    E-Print Network [OSTI]

    Paris-Sud XI, Universit de

    Skill forecasting from ensemble predictions of wind power P. Pinson,a , H.Aa. Nielsena , H. Madsena with the commonly provided short-term wind power point predictions. Alternative approaches for the use uncertainty (and potential energy imbalances). Wind power ensemble predictions are derived from the conversion

  7. Powering Up With Space-Time Wind Forecasting Amanda S. HERING and Marc G. GENTON

    E-Print Network [OSTI]

    Genton, Marc G.

    Powering Up With Space-Time Wind Forecasting Amanda S. HERING and Marc G. GENTON The technology to harvest electricity from wind energy is now advanced enough to make entire cities powered by it a reality be more realistically assessed with a loss measure that depends upon the power curve relating wind speed

  8. Wind Energy Leasing Handbook

    E-Print Network [OSTI]

    Balasundaram, Balabhaskar "Baski"

    Wind Energy Leasing Handbook Wind Energy Leasing Handbook E-1033 Oklahoma Cooperative Extension?..................................................................................................................... 31 What do wind developers consider in locating wind energy projects?............................................................................................ 37 How do companies and individuals invest in wind energy projects?....................................................................

  9. 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

    2009-11-20T23:59:59.000Z

    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.

  10. 20% Wind Energy 20% Wind Energy

    E-Print Network [OSTI]

    Powell, Warren B.

    (government, industry, utilities, NGOs) Analyzes wind's potential contributions to energy security, economic · Transmission a challenge #12;Wind Power Class Resource Potential Wind Power Density at 50 m W/m 2 Wind Speed20% Wind Energy by 2030 20% Wind Energy by 2030 #12;Presentation and Objectives Overview Background

  11. Forecast Energy | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual SiteofEvaluating A PotentialJumpGermanFife Energy Park atFisiaFlorida:Forecast Energy Jump to:

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

    SciTech Connect (OSTI)

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

    2012-07-01T23:59:59.000Z

    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.

  13. WIND POWER ENSEMBLE FORECASTING Henrik Aalborg Nielsen1

    E-Print Network [OSTI]

    WIND POWER ENSEMBLE FORECASTING Henrik Aalborg Nielsen1 , Henrik Madsen1 , Torben Skov Nielsen1. In this paper we address the problems of (i) transforming the mete- orological ensembles to wind power ensembles the uncertainty which follow from historical (climatological) data. However, quite often the actual wind power

  14. Probabilistic Wind Speed Forecasting Using Ensembles and Bayesian Model Averaging

    E-Print Network [OSTI]

    Raftery, Adrian

    the chance of winds high enough to pose dangers for boats or aircraft. In situations calling for a cost/loss analysis, the probabilities of different outcomes need to be known. For wind speed, this issue often arisesProbabilistic Wind Speed Forecasting Using Ensembles and Bayesian Model Averaging J. Mc

  15. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    Energy Commission's final forecasts for 2012­2022 electricity consumption, peak, and natural gas demand Electricity, demand, consumption, forecast, weather normalization, peak, natural gas, self generation CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST Volume 2: Electricity Demand

  16. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    the California Energy Commission staff's revised forecasts for 2012­2022 electricity consumption, peak Electricity, demand, consumption, forecast, weather normalization, peak, natural gas, self generation REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 1: Statewide Electricity Demand

  17. REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022

    E-Print Network [OSTI]

    Energy Commission staff's revised forecasts for 2012­2022 electricity consumption, peak, and natural Electricity, demand, consumption, forecast, weather normalization, peak, natural gas, self generation REVISED CALIFORNIA ENERGY DEMAND FORECAST 20122022 Volume 2: Electricity Demand by Utility

  18. Large-scale Probabilistic Forecasting in Energy Systems using Sparse Gaussian Conditional Random Fields

    E-Print Network [OSTI]

    Kolter, J. Zico

    -Gaussian case using the copula transform. On a wind power forecasting task, we show that this probabilisticLarge-scale Probabilistic Forecasting in Energy Systems using Sparse Gaussian Conditional Random high-dimensional conditional Gaussian distributions to forecasting wind power and extend it to the non

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2010-04-01T23:59:59.000Z

    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.

  20. Improvements in wind speed forecasts for wind power prediction purposes using Kalman filtering

    E-Print Network [OSTI]

    Paris-Sud XI, Universit de

    1 Improvements in wind speed forecasts for wind power prediction purposes using Kalman filtering P : 10.1016/j.jweia.2008.03.013 #12;2 Abstract This paper studies the application of Kalman filtering forecasts. The application of Kalman filter to these data leads to the elimination of any possible

  1. 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. (Decision and Information Sciences); (INESC Porto)

    2011-12-06T23:59:59.000Z

    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.

  2. Sandia National Laboratories: wind energy

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

    Wind Energy Manufacturing Lab Helps Engineers Improve Wind Power On November 15, 2011, in Energy, News, Partnership, Renewable Energy, Wind Energy Researchers at the Wind Energy...

  3. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

    has developed longterm forecasts of transportation energy demand as well as projected ranges of transportation fuel and crude oil import requirements. The transportation energy demand forecasts makeCALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY POLICY

  4. American Wind Energy Association Wind Energy Finance and Investment...

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

    American Wind Energy Association Wind Energy Finance and Investment Seminar American Wind Energy Association Wind Energy Finance and Investment Seminar October 20, 2014 8:00AM EDT...

  5. Space-time forecasting and evaluation of wind speed with statistical tests for comparing accuracy of spatial predictions

    E-Print Network [OSTI]

    Hering, Amanda S.

    2010-10-12T23:59:59.000Z

    High-quality short-term forecasts of wind speed are vital to making wind power a more reliable energy source. Gneiting et al. (2006) have introduced a model for the average wind speed two hours ahead based on both spatial and temporal information...

  6. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST Volume 2: Electricity Demand The California Energy Demand 2014 ­ 2024 Revised Forecast, Volume 2: Electricity Demand by Utility Planning Area Energy Policy Report. The forecast includes three full scenarios: a high energy demand case, a low

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

    SciTech Connect (OSTI)

    Piwko, R.; Jordan, G.

    2011-11-01T23:59:59.000Z

    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.

  8. Wind energy systems: program summary

    SciTech Connect (OSTI)

    None

    1980-05-01T23:59:59.000Z

    The Federal Wind Energy Program (FWEP) was initiated to provide focus, direction and funds for the development of wind power. Each year a summary is prepared to provide the American public with an overview of government sponsored activities in the FWEP. This program summary describes each of the Department of Energy's (DOE) current wind energy projects initiated or renewed during FY 1979 (October 1, 1978 through September 30, 1979) and reflects their status as of April 30, 1980. The summary highlights on-going research, development and demonstration efforts and serves as a record of progress towards the program objectives. It also provides: the program's general management structure; review of last year's achievements; forecast of expected future trends; documentation of the projects conducted during FY 1979; and list of key wind energy publications.

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2009-12-01T23:59:59.000Z

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

  10. Wind energy bibliography

    SciTech Connect (OSTI)

    None

    1995-05-01T23:59:59.000Z

    This bibliography is designed to help the reader search for information on wind energy. The bibliography is intended to help several audiences, including engineers and scientists who may be unfamiliar with a particular aspect of wind energy, university researchers who are interested in this field, manufacturers who want to learn more about specific wind topics, and librarians who provide information to their clients. Topics covered range from the history of wind energy use to advanced wind turbine design. References for wind energy economics, the wind energy resource, and environmental and institutional issues related to wind energy are also included.

  11. Probabilistic Wind Vector Forecasting Using Ensembles and Bayesian Model Averaging

    E-Print Network [OSTI]

    Raftery, Adrian

    : J. McLean Sloughter, Department of Mathematics, Seattle University, 901 12th Ave., P.O. Box 222000Probabilistic Wind Vector Forecasting Using Ensembles and Bayesian Model Averaging J. MCLEAN SLOUGHTER Seattle University, Seattle, Washington TILMANN GNEITING Heidelberg University, Heidelberg

  12. Grid-scale Fluctuations and Forecast Error in Wind Power

    E-Print Network [OSTI]

    G. Bel; C. P. Connaughton; M. Toots; M. M. Bandi

    2015-03-29T23:59:59.000Z

    The fluctuations in wind power entering an electrical grid (Irish grid) were analyzed and found to exhibit correlated fluctuations with a self-similar structure, a signature of large-scale correlations in atmospheric turbulence. The statistical structure of temporal correlations for fluctuations in generated and forecast time series was used to quantify two types of forecast error: a timescale error ($e_{\\tau}$) that quantifies the deviations between the high frequency components of the forecast and the generated time series, and a scaling error ($e_{\\zeta}$) that quantifies the degree to which the models fail to predict temporal correlations in the fluctuations of the generated power. With no $a$ $priori$ knowledge of the forecast models, we suggest a simple memory kernel that reduces both the timescale error ($e_{\\tau}$) and the scaling error ($e_{\\zeta}$).

  13. Grid-scale Fluctuations and Forecast Error in Wind Power

    E-Print Network [OSTI]

    Bel, G; Toots, M; Bandi, M M

    2015-01-01T23:59:59.000Z

    The fluctuations in wind power entering an electrical grid (Irish grid) were analyzed and found to exhibit correlated fluctuations with a self-similar structure, a signature of large-scale correlations in atmospheric turbulence. The statistical structure of temporal correlations for fluctuations in generated and forecast time series was used to quantify two types of forecast error: a timescale error ($e_{\\tau}$) that quantifies the deviations between the high frequency components of the forecast and the generated time series, and a scaling error ($e_{\\zeta}$) that quantifies the degree to which the models fail to predict temporal correlations in the fluctuations of the generated power. With no $a$ $priori$ knowledge of the forecast models, we suggest a simple memory kernel that reduces both the timescale error ($e_{\\tau}$) and the scaling error ($e_{\\zeta}$).

  14. Module Handbook Specialisation Wind Energy

    E-Print Network [OSTI]

    Habel, Annegret

    ;Specialisation Wind Energy, NTU Athens, 2nd Semester Module 1/Wind Energy: Wind potential, Aerodynamics & Loading of Wind Turbines Module name: Wind potential, Aerodynamics & Loading of Wind Turbines Section Classes Evaluation of Wind Energy Potential Wind turbine Aerodynamics Static and dynamic Loading of Wind turbines

  15. 20% Wind Energy by 2030: Increasing Wind Energy's Contribution...

    Energy Savers [EERE]

    : Increasing Wind Energy's Contribution to U.S. Electricity Supply (Executive Summary) 20% Wind Energy by 2030: Increasing Wind Energy's Contribution to U.S. Electricity Supply...

  16. Next Generation Short-Term Forecasting of Wind Power Overview of the ANEMOS Project.

    E-Print Network [OSTI]

    Boyer, Edmond

    of difficulties to the power system operation. This is due to the fluctuating nature of wind generation to the management of wind generation. Accurate and reliable forecasting systems of the wind production are widely

  17. Wind Energy Benefits, Wind Powering America (WPA) (Fact Sheet...

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

    Energy Benefits, Wind Powering America (WPA) (Fact Sheet), Wind And Water Power Program (WWPP) Wind Energy Benefits, Wind Powering America (WPA) (Fact Sheet), Wind And Water Power...

  18. Wind Energy Act (Maine)

    Broader source: Energy.gov [DOE]

    The Maine Wind Energy Act is a summary of legislative findings that indicate the state's strong interest in promoting the development of wind energy and establish the state's desire to ease the...

  19. 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.

    2012-09-01T23:59:59.000Z

    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.

  20. Wind energy information guide

    SciTech Connect (OSTI)

    NONE

    1996-04-01T23:59:59.000Z

    This book is divided into nine chapters. Chapters 1--8 provide background and annotated references on wind energy research, development, and commercialization. Chapter 9 lists additional sources of printed information and relevant organizations. Four indices provide alphabetical access to authors, organizations, computer models and design tools, and subjects. A list of abbreviations and acronyms is also included. Chapter topics include: introduction; economics of using wind energy; wind energy resources; wind turbine design, development, and testing; applications; environmental issues of wind power; institutional issues; and wind energy systems development.

  1. 20% Wind Energy by 2030: Increasing Wind Energy's Contribution...

    Office of Environmental Management (EM)

    a new vision for wind energy through 2050. Taking into account all facets of wind energy (land-based, offshore, distributed), the new Wind Vision Report defines the...

  2. CALIFORNIA ENERGY DEMAND 20142024 REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 2014­2024 REVISED FORECAST Volume 1: Statewide Electricity Demand, EndUser Natural Gas Demand, and Energy Efficiency SEPTEMBER 2013 CEC2002013004SDV1REV CALIFORNIA The California Energy Demand 2014 ­ 2024 Revised Forecast, Volume 1: Statewide Electricity Demand and Methods

  3. wind energy

    National Nuclear Security Administration (NNSA)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOn AprilAElectronic Input Options Gary L. HirschOccurrencei-rapter | ¡MA-0518 Origins

  4. Advanced statistical methods for shortterm wind power forecasting Research proposal draft

    E-Print Network [OSTI]

    Barnett, Alex

    Barnett July 2001 1 Background Over the last decade wind power has become a costeffective alternative at a turbine) using linear or nonlinear timeseries analysis (Alex iadis 1999), or 2) forecasting windAdvanced statistical methods for shortterm wind power forecasting Research proposal draft Alex

  5. 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.

    2013-10-01T23:59:59.000Z

    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.

  6. TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY

    E-Print Network [OSTI]

    requirements. The transportation energy demand forecasts make assumptions about fuel price forecastsCALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS FOR THE 2007 INTEGRATED ENERGY POLICY ENERGY COMMISSION Gordon Schremp, Jim Page, and Malachi Weng-Gutierrez Principal Authors Jim Page Project

  7. 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.

    2013-10-01T23:59:59.000Z

    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.

  8. 2015 Iowa Wind Power Conference and Iowa Wind Energy Association...

    Energy Savers [EERE]

    2015 Iowa Wind Power Conference and Iowa Wind Energy Association Midwest Regional Energy Job Fair 2015 Iowa Wind Power Conference and Iowa Wind Energy Association Midwest Regional...

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

    SciTech Connect (OSTI)

    Rogers, J.; Porter, K.

    2011-03-01T23:59:59.000Z

    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.

  10. Upstream Measurements of Wind Profiles with Doppler Lidar for Improved Wind Energy Integration

    SciTech Connect (OSTI)

    Rodney Frehlich

    2012-10-30T23:59:59.000Z

    New upstream measurements of wind profiles over the altitude range of wind turbines will be produced using a scanning Doppler lidar. These long range high quality measurements will provide improved wind power forecasts for wind energy integration into the power grid. The main goal of the project is to develop the optimal Doppler lidar operating parameters and data processing algorithms for improved wind energy integration by enhancing the wind power forecasts in the 30 to 60 minute time frame, especially for the large wind power ramps. Currently, there is very little upstream data at large wind farms, especially accurate wind profiles over the full height of the turbine blades. The potential of scanning Doppler lidar will be determined by rigorous computer modeling and evaluation of actual Doppler lidar data from the WindTracer system produced by Lockheed Martin Coherent Technologies, Inc. of Louisville, Colorado. Various data products will be investigated for input into numerical weather prediction models and statistically based nowcasting algorithms. Successful implementation of the proposed research will provide the required information for a full cost benefit analysis of the improved forecasts of wind power for energy integration as well as the added benefit of high quality wind and turbulence information for optimal control of the wind turbines at large wind farms.

  11. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    supervised data preparation. Steven Mac and Keith O'Brien prepared the historical energy consumption data. Nahid Movassagh forecasted consumption for the agriculture and water pumping sectors. Cynthia Rogers generation, conservation, energy efficiency, climate zone, investorowned, public, utilities, additional

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

    SciTech Connect (OSTI)

    Pennock, K.

    2012-10-01T23:59:59.000Z

    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.

  13. Sandia Energy - Wind Plant Optimization

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

    Wind Plant Optimization Home Stationary Power Energy Conversion Efficiency Wind Energy Wind Plant Optimization Wind Plant OptimizationTara Camacho-Lopez2015-05-29T21:33:21+00:00...

  14. WIND ENERGY Wind Energ. (2014)

    E-Print Network [OSTI]

    2014-01-01T23:59:59.000Z

    in the near wake. In conclusion, WiTTS performs satisfactorily in the rotor region of wind turbine wakes under neutral stability. Copyright 2014 John Wiley & Sons, Ltd. KEYWORDS wind turbine wake; wake model; self in wind farms along several rows and columns. Because wind turbines generate wakes that propagate downwind

  15. Wind | Department of Energy

    Office of Environmental Management (EM)

    in the world. To stay competitive in this sector, the Energy Department invests in wind projects, both on land and offshore, to advance technology innovations, create job...

  16. Sandia Energy - Sandia Wind Turbine Loads Database

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

    Sandia Wind Turbine Loads Database Home Stationary Power Energy Conversion Efficiency Wind Energy Resources Wind Software Downloads Sandia Wind Turbine Loads Database Sandia Wind...

  17. Wind energy conversion system

    DOE Patents [OSTI]

    Longrigg, Paul (Golden, CO)

    1987-01-01T23:59:59.000Z

    The wind energy conversion system includes a wind machine having a propeller connected to a generator of electric power, the propeller rotating the generator in response to force of an incident wind. The generator converts the power of the wind to electric power for use by an electric load. Circuitry for varying the duty factor of the generator output power is connected between the generator and the load to thereby alter a loading of the generator and the propeller by the electric load. Wind speed is sensed electro-optically to provide data of wind speed upwind of the propeller, to thereby permit tip speed ratio circuitry to operate the power control circuitry and thereby optimize the tip speed ratio by varying the loading of the propeller. Accordingly, the efficiency of the wind energy conversion system is maximized.

  18. Short-term Wind Power Forecasting Using Advanced Statistical T.S. Nielsen1

    E-Print Network [OSTI]

    Paris-Sud XI, Universit de

    , in order to be able to absorb a large fraction of wind power in the electrical systems reliable short from refer- ence MET forecasts to the actual wind farm, wind farm power curve models, dynamical models of art wind power prediction system is outlined in Section 2. Numerical Weather Prediction (NWP

  19. Wind energy applications guide

    SciTech Connect (OSTI)

    anon.

    2001-01-01T23:59:59.000Z

    The brochure is an introduction to various wind power applications for locations with underdeveloped transmission systems, from remote water pumping to village electrification. It includes an introductory section on wind energy, including wind power basics and system components and then provides examples of applications, including water pumping, stand-alone systems for home and business, systems for community centers, schools, and health clinics, and examples in the industrial area. There is also a page of contacts, plus two specific example applications for a wind-diesel system for a remote station in Antarctica and one on wind-diesel village electrification in Russia.

  20. American Wind Energy Association Wind Energy Finance and Investment Seminar

    Broader source: Energy.gov [DOE]

    The American Wind Energy Association Wind Energy Finance and Investment Seminar will be attended by representatives in the financial sector, businesses, bankers, government and other nonprofit...

  1. Wind | Department of Energy

    Energy Savers [EERE]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directed off Energy.gov. Are you sureReportsofDepartmentSeries |Attacksof EnergyWhenWindWind ResearchWind

  2. CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2006-2016 STAFF ENERGY DEMAND FORECAST Manager Kae Lewis Acting Manager Demand Analysis Office Valerie T. Hall Deputy Director Energy Efficiency Demand Forecast report is the product of the efforts of many current and former California Energy

  3. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST

    E-Print Network [OSTI]

    and water pumping sectors. Mark Ciminelli forecasted energy for transportation, communication and utilities. Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption data at the California Public Utilities Commission. This forecast was produced with the Energy Commission demand forecast

  4. Wind Energy Resources and Technologies

    Broader source: Energy.gov [DOE]

    This page provides a brief overview of wind energy resources and technologies supplemented by specific information to apply wind energy within the Federal sector.

  5. Great Plains Wind Energy Transmission Development Project

    SciTech Connect (OSTI)

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

    2012-06-09T23:59:59.000Z

    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.

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

    SciTech Connect (OSTI)

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

    2012-08-01T23:59:59.000Z

    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.

  7. Wind Energy and Spatial Technology

    E-Print Network [OSTI]

    Schweik, Charles M.

    2/3/2011 1 Wind Energy and Spatial Technology Lori Pelech Why Wind Energy? A clean, renewable 2,600 tons of carbon emissions annually The economy Approximately 85,000 wind energy workers to Construct a Wind Farm... Geo-Spatial Components of Wind Farm Development Process Selecting a Project Site

  8. The wind power probability density forecast problem can be formulated as: forecast the wind power pdf at time step t for each look-ahead time step t+k of a given time-horizon

    E-Print Network [OSTI]

    Kemner, Ken

    The wind power probability density forecast problem can be formulated as: forecast the wind power ahead) knowing a set of explanatory variables (e.g. numerical weather predictions (NWPs), wind power measured values). Translating this sentence to an equation, we have: where pt+k is the wind power

  9. CALIFORNIA ENERGY DEMAND 20142024 FINAL FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY DEMAND 2014­2024 FINAL FORECAST Volume 1: Statewide Electricity Demand, EndUser Natural Gas Demand, and Energy Efficiency DECEMBER 2013 CEC2002013004SFV1 CALIFORNIA and expertise of numerous California Energy Commission staff members in the Demand Analysis Office. In addition

  10. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF DRAFT FORECAST

    E-Print Network [OSTI]

    procurement process at the California Public Utilities Commission. This forecast was produced with the Energy Commission demand forecast models. Both the staff draft energy consumption and peak forecasts are slightly and commercial sectors. Keywords Electricity demand, electricity consumption, demand forecast, weather

  11. Evaluation of Advanced Wind Power Forecasting Models Results of the Anemos Project

    E-Print Network [OSTI]

    Paris-Sud XI, Universit de

    1 Evaluation of Advanced Wind Power Forecasting Models Results of the Anemos Project I. Mart1.kariniotakis@ensmp.fr Abstract An outstanding question posed today by end-users like power system operators, wind power producers or traders is what performance can be expected by state-of-the-art wind power prediction models. This paper

  12. Short-term Forecasting of Offshore Wind Farm Production Developments of the Anemos Project

    E-Print Network [OSTI]

    Paris-Sud XI, Universit de

    Short-term Forecasting of Offshore Wind Farm Production Developments of the Anemos Project J to the large dimensions of offshore wind farms, their electricity production must be known well in advance networks) models were calibrated on power data from two offshore wind farms: Tunoe and Middelgrunden

  13. Wind Energy Systems Exemption

    Broader source: Energy.gov [DOE]

    Tennessee House Bill 809, enacted into law in Public Chapter 377, Acts of 2003 and codified under Title 67, Chapter 5, states that wind energy systems operated by public utilities, businesses or...

  14. Collegiate Wind Competition Engages Tomorrow's Wind Energy Innovators...

    Office of Environmental Management (EM)

    Engages Tomorrow's Wind Energy Innovators Collegiate Wind Competition Engages Tomorrow's Wind Energy Innovators January 6, 2014 - 10:00am Addthis 2014 Collegiate Teams Boise State...

  15. Sandia Energy - Wind & Water Power Newsletter

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

    Wind & Water Power Newsletter Home Stationary Power Energy Conversion Efficiency Wind Energy Resources Wind & Water Power Newsletter Wind & Water Power NewsletterTara...

  16. Performance Indicators of Wind Energy Production

    E-Print Network [OSTI]

    D'Amico, G; Prattico, F

    2015-01-01T23:59:59.000Z

    Modeling wind speed is one of the key element when dealing with the production of energy through wind turbines. A good model can be used for forecasting, site evaluation, turbines design and many other purposes. In this work we are interested in the analysis of the future financial cash flows generated by selling the electrical energy produced. We apply an indexed semi-Markov model of wind speed that has been shown, in previous investigation, to reproduce accurately the statistical behavior of wind speed. The model is applied to the evaluation of financial indicators like the Internal Rate of Return, semi-Elasticity and relative Convexity that are widely used for the assessment of the profitability of an investment and for the measurement and analysis of interest rate risk. We compare the computation of these indicators for real and synthetic data. Moreover, we propose a new indicator that can be used to compare the degree of utilization of different power plants.

  17. Wind Events | Department of Energy

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

    Below is an industry calendar with meetings, conferences, and webinars of interest to the wind energy technology communities. IEA Wind Task 34 (WREN) Quarterly Webinar 3:...

  18. Sandia National Laboratories: wind energy

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

    More Energy with Less Weight On May 18, 2011, in Energy, News, Renewable Energy, Wind Energy The following is from an article published in WindStats Newsletter Vol. 19, No. 4. The...

  19. CALIFORNIA ENERGY DEMAND 20122022 FINAL FORECAST

    E-Print Network [OSTI]

    , Gary Occhiuzzo, and Keith O'Brien prepared the historical energy consumption data. Nahid Movassagh forecasted consumption for the agriculture and water pumping sectors. Don Schultz and Doug Kemmer developed. California Energy Commission, Electricity Supply Analysis Division. Publication Number: CEC2002012001CMFVI

  20. Wind energy offers considerable promise; the wind itself is free,

    E-Print Network [OSTI]

    Langendoen, Koen

    Wind energy offers considerable promise; the wind itself is free, wind power is clean. One of these sources, wind energy, offers considerable promise; the wind itself is free, wind power is clean, and it is virtually inexhaustible. In recent years, research on wind energy has accelerated

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

    SciTech Connect (OSTI)

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

    2012-06-01T23:59:59.000Z

    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.

  2. AUTOMATION OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S.

    E-Print Network [OSTI]

    Povinelli, Richard J.

    AUTOMATION OF ENERGY DEMAND FORECASTING by Sanzad Siddique, B.S. A Thesis submitted to the Faculty OF ENERGY DEMAND FORECASTING Sanzad Siddique, B.S. Marquette University, 2013 Automation of energy demand of the energy demand forecasting are achieved by integrating nonlinear transformations within the models

  3. Sandia National Laboratories: wind energy

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

    iNEMI Renewable Energy Workshop On May 18, 2011, in Energy, News, Renewable Energy, Wind Energy, Workshops The International Electronics Manufacturing Initiative (iNEMI) held a...

  4. Probabilistic Wind Resource Assessment and Power Predictions

    E-Print Network [OSTI]

    Firestone, Jeremy

    Probabilistic Wind Resource Assessment and Power Predictions Luca Delle Monache (lucadm Accurate wind resource assessment and power forecasts and reliable quanXficaXon of their uncertainty Mo5va5on Power forecast: o Increase wind energy penetra

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

    SciTech Connect (OSTI)

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

    2009-03-01T23:59:59.000Z

    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.

  6. The use of real-time off-site observations as a methodology for increasing forecast skill in prediction of large wind power ramps one or more hours ahead of their impact on a wind plant.

    SciTech Connect (OSTI)

    Martin Wilde, Principal Investigator

    2012-12-31T23:59:59.000Z

    ABSTRACT Application of Real-Time Offsite Measurements in Improved Short-Term Wind Ramp Prediction Skill Improved forecasting performance immediately preceding wind ramp events is of preeminent concern to most wind energy companies, system operators, and balancing authorities. The value of near real-time hub height-level wind data and more general meteorological measurements to short-term wind power forecasting is well understood. For some sites, access to onsite measured wind data - even historical - can reduce forecast error in the short-range to medium-range horizons by as much as 50%. Unfortunately, valuable free-stream wind measurements at tall tower are not typically available at most wind plants, thereby forcing wind forecasters to rely upon wind measurements below hub height and/or turbine nacelle anemometry. Free-stream measurements can be appropriately scaled to hub-height levels, using existing empirically-derived relationships that account for surface roughness and turbulence. But there is large uncertainty in these relationships for a given time of day and state of the boundary layer. Alternatively, forecasts can rely entirely on turbine anemometry measurements, though such measurements are themselves subject to wake effects that are not stationary. The void in free-stream hub-height level measurements of wind can be filled by remote sensing (e.g., sodar, lidar, and radar). However, the expense of such equipment may not be sustainable. There is a growing market for traditional anemometry on tall tower networks, maintained by third parties to the forecasting process (i.e., independent of forecasters and the forecast users). This study examines the value of offsite tall-tower data from the WINDataNOW Technology network for short-horizon wind power predictions at a wind farm in northern Montana. The presentation shall describe successful physical and statistical techniques for its application and the practicality of its application in an operational setting. It shall be demonstrated that when used properly, the real-time offsite measurements materially improve wind ramp capture and prediction statistics, when compared to traditional wind forecasting techniques and to a simple persistence model.

  7. OWEMES -Offshore Wind And Other Marine Renewable Energies In Mediterranean And European Seas Civitavecchia (Italy), 20th

    E-Print Network [OSTI]

    Heinemann, Detlev

    OWEMES - Offshore Wind And Other Marine Renewable Energies In Mediterranean And European Seas Civitavecchia (Italy), 20th -22th April 2006 How to avoid Biases in Offshore Wind Power Forecasting Lueder von, adaptive system, Neural Network, single site forecast, systematic error Abstract Large-scale offshore wind

  8. Paper presented at EWEC 2008, Brussels, Belgium (31 March-03 April) Uncertainty Estimation of Wind Power Forecasts

    E-Print Network [OSTI]

    Paris-Sud XI, Universit de

    -Antipolis, France Abstract--Short-term wind power forecasting tools providing "single-valued" (spot) predictions associated to the future wind power produc- tion for performing more efficiently functions such as reserves and modelling architec- tures for probabilistic wind power forecasting. Then, a comparison is carried out

  9. Wind energy | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown ofNationwideWTEDBird,Wilsonville, Oregon: EnergyWindCooperativesWind Works

  10. Shaping Tomorrow's Wind Energy Leaders | Department of Energy

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

    Shaping Tomorrow's Wind Energy Leaders Shaping Tomorrow's Wind Energy Leaders Addthis Duration 2:22 Topic Wind Science Education...

  11. 20% Wind Energy by 2030: Increasing Wind Energy's Contribution...

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

    0% Wind Energy by 2030 Increasing Wind Energy's Contribution to U.S. Electricity Supply DOEGO-102008-2578 * December 2008 More information is available on the web at:...

  12. Sandia Energy - Continuous Reliability Enhancement for Wind ...

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

    Enhancement for Wind (CREW): Project Update Home Renewable Energy Energy News Wind Energy News & Events Systems Analysis Continuous Reliability Enhancement for Wind (CREW):...

  13. SPRING 2014 wind energy's impact

    E-Print Network [OSTI]

    Tullos, Desiree

    SPRING 2014 wind energy's impact on birds, bats......... 2-3 school news........... 4-5 alumni news measurable benefits reaped by the use of wind energy. But, it is a fact: all energy sources, alternative Interactions with Offshore Wind Energy Facilities," involves the design, deployment and testing

  14. West Winds Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTri GlobalJump to: navigation,Goff,Holt WindInformationWestWinds Wind

  15. Sandia National Laboratories: wind energy

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

    Dutch University MOU Signing On May 18, 2011, in Energy, News, Renewable Energy, Wind Energy singlepic id632 w320 h240 floatrightINTERNATIONAL COLLABORATIONS - Sid Gutierrez,...

  16. Wind energy | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit withTianlinPapers Home Kyoung's pictureWind Power Energia JumpMaps.jpgWind

  17. Wind energy | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit withTianlinPapers Home Kyoung's pictureWind Power Energia JumpMaps.jpgWind

  18. Sandia Energy - Wind Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742EnergyOnItemResearch > TheNuclear PressLaboratorySoftware HometdheinrWater/Energy

  19. Sandia Energy - Wind Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's PossibleRadiationImplementing Nonlinear757KelleyEffectsonSandia'sEventNotECWillie LukEnergy

  20. Wind | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative JC3 RSS SeptemberRenewableAbout Key ActivitiesWhy EnergyWindPeer06 WindScience &

  1. Energy 101: Wind Turbines

    ScienceCinema (OSTI)

    None

    2013-05-29T23:59:59.000Z

    See how wind turbines generate clean electricity from the power of the wind. Highlighted are the various parts and mechanisms of a modern wind turbine.

  2. Energy 101: Wind Turbines

    SciTech Connect (OSTI)

    None

    2011-01-01T23:59:59.000Z

    See how wind turbines generate clean electricity from the power of the wind. Highlighted are the various parts and mechanisms of a modern wind turbine.

  3. Sandia Energy - Wind Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's PossibleRadiationImplementing Nonlinear757KelleyEffectsonSandia'sEventNotECWillie Luk

  4. 2008 Wind Energy Projects, Wind Powering America (Poster)

    SciTech Connect (OSTI)

    Not Available

    2009-01-01T23:59:59.000Z

    The Wind Powering America program produces a poster at the end of every calendar year that depicts new U.S. wind energy projects. The 2008 poster includes the following projects: Stetson Wind Farm in Maine; Dutch Hill Wind Farm in New York; Grand Ridge Wind Energy Center in Illinois; Hooper Bay, Alaska; Forestburg, South Dakota; Elbow Creek Wind Project in Texas; Glacier Wind Farm in Montana; Wray, Colorado; Smoky Hills Wind Farm in Kansas; Forbes Park Wind Project in Massachusetts; Spanish Fork, Utah; Goodland Wind Farm in Indiana; and the Tatanka Wind Energy Project on the border of North Dakota and South Dakota.

  5. Sandia Energy - Wind Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del Sol Home DistributionTransportation Safety HomeWater Power PersonnelH2FIRSTWind

  6. Wind Webinar Presentation Slides | Department of Energy

    Office of Environmental Management (EM)

    Wind Webinar Presentation Slides Wind Webinar Presentation Slides Download presentation slides from the DOE Office of Indian Energy webinar on wind renewable energy. DOE Office of...

  7. Sandia National Laboratories: Solar Energy Forecasting and Resource...

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

    & Events, Partnership, Photovoltaic, Renewable Energy, Solar, Systems Analysis The book, Solar Energy Forecasting and Resource Assessment, provides an authoritative voice on the...

  8. Wind | Department of Energy

    Energy Savers [EERE]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directed off Energy.gov. Are you sure you want toworldPower 2010 1 TNews &AppliancesYourAboutPoliciesWind

  9. Version:April 2014 Wind Energy EFA

    E-Print Network [OSTI]

    Kusiak, Andrew

    Version:April 2014 Wind Energy EFA Wind energy has become a major source of clean energy. Wind backgrounds and knowledge of wind energy fundamentals are needed to fill these jobs. The Wind Energy EFA prepares students for a career in wind energy, and allows for completing all requirements

  10. Sandia National Laboratories: Wind Energy

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

    Wind Energy National Rotor Testbed Rotor Design Integrated Airfoil Performance Results On February 24, 2015, in Computational Modeling & Simulation, Energy, Facilities, News, News...

  11. Univariate Modeling and Forecasting of Monthly Energy Demand Time Series

    E-Print Network [OSTI]

    Abdel-Aal, Radwan E.

    Univariate Modeling and Forecasting of Monthly Energy Demand Time Series Using Abductive and Neural dedicated models to forecast the 12 individual months directly. Results indicate better performance is superior to naïve forecasts based on persistence and seasonality, and is better than results quoted

  12. 20% Wind Energy by 2030

    SciTech Connect (OSTI)

    Not Available

    2008-07-01T23:59:59.000Z

    This analysis explores one clearly defined scenario for providing 20% of our nations electricity demand with wind energy by 2030 and contrasts it to a scenario of no new wind power capacity.

  13. The Solar Wind Energy Flux

    E-Print Network [OSTI]

    Chat, G Le; Meyer-Vernet, N

    2012-01-01T23:59:59.000Z

    The solar-wind energy flux measured near the ecliptic is known to be independent of the solar-wind speed. Using plasma data from Helios, Ulysses, and Wind covering a large range of latitudes and time, we show that the solar-wind energy flux is independent of the solar-wind speed and latitude within 10%, and that this quantity varies weakly over the solar cycle. In other words the energy flux appears as a global solar constant. We also show that the very high speed solar-wind (VSW > 700 km/s) has the same mean energy flux as the slower wind (VSW < 700 km/s), but with a different histogram. We use this result to deduce a relation between the solar-wind speed and density, which formalizes the anti-correlation between these quantities.

  14. Wind energy: Program overview, FY 1992

    SciTech Connect (OSTI)

    Not Available

    1993-06-01T23:59:59.000Z

    The DOE Wind Energy Program assists utilities and industry in developing advanced wind turbine technology to be economically competitive as an energy source in the marketplace and in developing new markets and applications for wind systems. This program overview describes the commercial development of wind power, wind turbine development, utility programs, industry programs, wind resources, applied research in wind energy, and the program structure.

  15. PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022

    E-Print Network [OSTI]

    PRELIMINARY CALIFORNIA ENERGY DEMAND FORECAST 2012-2022 AUGUST 2011 CEC-200-2011-011-SD CALIFORNIA for electric vehicles. #12;ii #12;iii ABSTRACT The Preliminary California Energy Demand Forecast 2012 includes three full scenarios: a high energy demand case, a low energy demand case, and a mid energy demand

  16. Diablo Winds Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489 No revision hasda62829c05bGabbs TypeWinds Wind Farm Jump to:

  17. Wind Energy Program: Top 10 Program Accomplishments

    Broader source: Energy.gov [DOE]

    Brochure on the top accomplishments of the Wind Energy Program, including the development of large wind machines, small machines for the residential market, wind tunnel testing, computer codes for modeling wind systems, high definition wind maps, and successful collaborations.

  18. Solar Forecasting | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn'tOriginEducationVideo »UsageSecretary ofSmallConfidential,2 Solar BackgroundWakePowersSystems

  19. Wind turbulence characterization for wind energy development

    SciTech Connect (OSTI)

    Wendell, L.L.; Gower, G.L.; Morris, V.R.; Tomich, S.D.

    1991-09-01T23:59:59.000Z

    As part of its support of the US Department of Energy's (DOE's) Federal Wind Energy Program, the Pacific Northwest Laboratory (PNL) has initiated an effort to work jointly with the wind energy community to characterize wind turbulence in a variety of complex terrains at existing or potential sites of wind turbine installation. Five turbulence characterization systems were assembled and installed at four sites in the Tehachapi Pass in California, and one in the Green Mountains near Manchester, Vermont. Data processing and analyses techniques were developed to allow observational analyses of the turbulent structure; this analysis complements the more traditional statistical and spectral analyses. Preliminary results of the observational analyses, in the rotating framework or a wind turbine blade, show that the turbulence at a site can have two major components: (1) engulfing eddies larger than the rotor, and (2) fluctuating shear due to eddies smaller than the rotor disk. Comparison of the time series depicting these quantities at two sites showed that the turbulence intensity (the commonly used descriptor of turbulence) did not adequately characterize the turbulence at these sites. 9 refs., 10 figs.,

  20. CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST

    E-Print Network [OSTI]

    CALIFORNIA ENERGY COMMISSION CALIFORNIA ENERGY DEMAND 2008-2018 STAFF REVISED FORECAST, and utilities. Mitch Tian prepared the peak demand forecast. Ted Dang prepared the historic energy consumption STAFFFINALREPORT NOVEMBER 2007 CEC-200-2007-015-SF2 Arnold Schwarzenegger, Governor #12;CALIFORNIA ENERGY

  1. WIND ENERGY Wind Energ. 2013; 16:7790

    E-Print Network [OSTI]

    Papalambros, Panos

    energy industry lags far behind the wind energy industry, it has the potential to become a role player is equal to the long-term potential of onshore wind energy.1,2 Therefore, the utilisation of marineWIND ENERGY Wind Energ. 2013; 16:77­90 Published online 19 March 2012 in Wiley Online Library

  2. Sandia National Laboratories: Offshore Wind Energy Simulation...

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

    Offshore Wind Energy Simulation Toolkit Sandia Vertical-Axis Wind-Turbine Research Presented at Science of Making Torque from Wind Conference On July 8, 2014, in Computational...

  3. Cost of Offshore Wind Energy Charlene Nalubega

    E-Print Network [OSTI]

    Mountziaris, T. J.

    water as well as on land based wind farms. The specific offshore wind energy case under consideration, most of the offshore wind farms are in Europe, which started being developed in the early 1990's Cost of Offshore Wind Energy

  4. Forecasting of wind speed using wavelets analysis and cascade-correlation neural networks

    E-Print Network [OSTI]

    Paris-Sud XI, Universit de

    such as sunlight, wind, rain or geothermal heat. Wind energy is actually one of the fastest-growing forms, that is why its wind energy market has been progressing steadily in recent years. While in 2000, there were only 30 MW of wind generating capacity in France, the total installed capacity at the end of 2007

  5. analytical energy forecasting: Topics by E-print Network

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

    COMMISSION Tom Gorin Lynn Marshall Principal Author Tom Gorin Project 11 Short-Term Solar Energy Forecasting Using Wireless Sensor Networks Computer Technologies and...

  6. Sandia Energy - Sandia Wind Energy in the News

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

    Sandia Wind Energy in the News Home Stationary Power Energy Conversion Efficiency Wind Energy Resources Sandia Wind Energy in the News Sandia Wind Energy in the NewsTara...

  7. 20% Wind Energy by 2030 - Chapter 2: Wind Turbine Technology...

    Energy Savers [EERE]

    Wind Energy's Contribution to U.S. Electricity Supply Testing, Manufacturing, and Component Development Projects U.S. Offshore Wind Manufacturing and Supply Chain Development...

  8. Commercial Wind Energy Property Valuation

    Broader source: Energy.gov [DOE]

    Prior to 2007, wind energy devices generating electricity for commercial sale were assessed differently depending on where they were located. Some counties valued the entire turbine structure ...

  9. Wind Energy Benefits (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2015-01-01T23:59:59.000Z

    This fact sheet outlines the top 10 benefits of wind energy, including cost, water savings, job creation, indigenous resource, and low operating costs.

  10. High Winds Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, search OpenEIHesperia, California: Energy Resources JumpSheldon Energy Wind

  11. Energy 101: Wind Turbines - 2014 Update

    SciTech Connect (OSTI)

    None

    2014-05-06T23:59:59.000Z

    See how wind turbines generate clean electricity from the power of wind. The video highlights the basic principles at work in wind turbines, and illustrates how the various components work to capture and convert wind energy to electricity. This updated version also includes information on the Energy Department's efforts to advance offshore wind power. Offshore wind energy footage courtesy of Vestas.

  12. Energy 101: Wind Turbines - 2014 Update

    ScienceCinema (OSTI)

    None

    2014-06-05T23:59:59.000Z

    See how wind turbines generate clean electricity from the power of wind. The video highlights the basic principles at work in wind turbines, and illustrates how the various components work to capture and convert wind energy to electricity. This updated version also includes information on the Energy Department's efforts to advance offshore wind power. Offshore wind energy footage courtesy of Vestas.

  13. Wind Energy EFA Wind energy has become a major source of clean energy. Wind energy is expected to grow over the next

    E-Print Network [OSTI]

    Kusiak, Andrew

    Wind Energy EFA Wind energy has become a major source of clean energy. Wind energy is expected of wind energy fundamentals are needed to fill these jobs. The Wind Energy EFA prepares students for a career in wind energy, and allows for completing all requirements for the Certificate in Wind Energy

  14. Saturation wind power potential and its implications for wind energy

    E-Print Network [OSTI]

    Saturation wind power potential and its implications for wind energy Mark Z. Jacobsona,1 at 10 km above ground in the jet streams assuming airborne wind energy devices ("jet stream the theoretical limit of wind energy available at these altitudes, particularly because some recent studies

  15. Wind Energy Ordinances (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2010-08-01T23:59:59.000Z

    Due to increasing energy demands in the United States and more installed wind projects, rural communities and local governments with limited or no experience with wind energy now have the opportunity to become involved in this industry. Communities with good wind resources may be approached by entities with plans to develop the resource. Although these opportunities can create new revenue in the form of construction jobs and land lease payments, they also create a new responsibility on the part of local governments to create ordinances to regulate wind turbine installations. Ordinances are laws, often found within municipal codes that provide various degrees of control to local governments. These laws cover issues such as zoning, traffic, consumer protection, and building codes. Wind energy ordinances reflect local needs and wants regarding wind turbines within county or city lines and aid the development of safe facilities that will be embraced by the community. Since 2008 when the National Renewable Energy Laboratory released a report on existing wind energy ordinances, many more ordinances have been established throughout the United States, and this trend is likely to continue in the near future as the wind energy industry grows. This fact sheet provides an overview of elements found in typical wind energy ordinances to educate state and local government officials, as well as policy makers.

  16. Distributed Wind Energy in Idaho

    SciTech Connect (OSTI)

    Gardner, John; Ferguson, James; Ahmed-Zaid, Said; Johnson, Kathryn; Haynes, Todd; Bennett, Keith

    2009-01-31T23:59:59.000Z

    Project Objective: This project is a research and development program aimed at furthering distributed wind technology. In particular, this project addresses some of the barriers to distributed wind energy utilization in Idaho. Background: At its core, the technological challenge inherent in Wind Energy is the transformation of a highly variable form of energy to one which is compatible with the commercial power grid or another useful application. A major economic barrier to the success of distributed wind technology is the relatively high capital investment (and related long payback periods) associated with wind turbines. This project will carry out fundamental research and technology development to address both the technological and economic barriers. â?¢ Active drive train control holds the potential to improve the overall efficiency of a turbine system by allowing variable speed turbine operation while ensuring a tight control of generator shaft speed, thus greatly simplifying power conditioning. â?¢ Recent blade aerodynamic advancements have been focused on large, utility-scale wind turbine generators (WTGs) as opposed to smaller WTGs designed for distributed generation. Because of Reynolds Number considerations, blade designs do not scale well. Blades which are aerodynamically optimized for distributed-scale WTGs can potentially reduce the cost of electricity by increasing shaft-torque in a given wind speed. â?¢ Grid-connected electric generators typically operate at a fixed speed. If a generator were able to economically operate at multiple speeds, it could potentially convert more of the windâ??s energy to electricity, thus reducing the cost of electricity. This research directly supports the stated goal of the Wind and Hydropower Technologies Program for Distributed Wind Energy Technology: By 2007, reduce the cost of electricity from distributed wind systems to 10 to 15 cents/kWh in Class 3 wind resources, the same level that is currently achievable in Class 5 winds.

  17. Wind Energy R&D Opportunity: Energy Department Announces $125...

    Energy Savers [EERE]

    Wind Energy R&D Opportunity: Energy Department Announces 125 Million for Transformational Energy Projects Wind Energy R&D Opportunity: Energy Department Announces 125 Million for...

  18. Wind Vision Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTriWildcat 1 Wind Project Jump to:Wilson Hot

  19. Prairie Winds Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation,Pillar Group BV Jump to: navigation,Power Rental MarketEthanol LLC JumpWinds ND

  20. energy data + forecasting | OpenEI Community

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit withTianlinPapersWindey Wind Home Rmckeel's Home Kyoung's picture Submitted

  1. Searchlight Wind Energy Project DEIS Appendix A

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

    Searchlight Wind Energy Project DEIS Appendix A Page | A Appendix A: Public Scoping Report SCOPING SUMMARY REPORT SEARCHLIGHT WIND ENERGY PROJECT ENVIRONMENTAL IMPACT STATEMENT...

  2. Energy Department Announces 2016 Collegiate Wind Competition...

    Office of Environmental Management (EM)

    Energy Department Announces 2016 Collegiate Wind Competition Participants Energy Department Announces 2016 Collegiate Wind Competition Participants February 18, 2015 - 1:30pm...

  3. American Wind Energy Association Offshore WINDPOWER Conference...

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

    American Wind Energy Association Offshore WINDPOWER Conference & Exhibition American Wind Energy Association Offshore WINDPOWER Conference & Exhibition October 7, 2014 9:00AM EDT...

  4. WP2 IEA Wind Task 26:The Past and Future Cost of Wind Energy

    E-Print Network [OSTI]

    Lantz, Eric

    2014-01-01T23:59:59.000Z

    Energy Efficiency and Renewable Energy, Wind and HydropowerSpeed Sites. European Wind Energy Association. Marseille,Innovation and the price of wind energy in the US. Energy

  5. Solar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting Questionnaire As someone who is familiar with solar energy issues, we hope that you will tak

    E-Print Network [OSTI]

    Islam, M. Saif

    Page 1 Solar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting QuestionnaireSolar Resource and Forecasting Questionnaire As someone who is familiar with solar energy issues, we hope that you will take a few moments to answer this short survey

  6. Wind Energy Status and Future Wind Engineering Challenges: Preprint

    SciTech Connect (OSTI)

    Thresher, R.; Schreck, S.; Robinson, M.; Veers, P.

    2008-08-01T23:59:59.000Z

    This paper describes the current status of wind energy technology, the potential for future wind energy development and the science and engineering challenges that must be overcome for the technology to meet its potential.

  7. FEBRUARY 1999 119O ' C O N N O R E T A L . Forecast Verification for Eta Model Winds Using Lake Erie

    E-Print Network [OSTI]

    FEBRUARY 1999 119O ' C O N N O R E T A L . Forecast Verification for Eta Model Winds Using Lake. The in- crease in computer power in recent years and advances in numerical mesoscale models of both ocean Forecasting System (GLCFS) can be used to validate wind forecasts for the Great Lakes using observed

  8. Wind Gallery | Department of Energy

    Energy Savers [EERE]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2, 2015Visiting Strong, Smart,Department EFFICIENCY MEASURES *WindWindWind

  9. International Energy Agency 2011 Wind Energy Annual Report Available...

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

    International Energy Agency 2011 Wind Energy Annual Report Available for Download International Energy Agency 2011 Wind Energy Annual Report Available for Download October 1, 2012...

  10. Community Renewable Energy Success Stories: Wind Energy in Urban...

    Office of Environmental Management (EM)

    Community Renewable Energy Success Stories: Wind Energy in Urban Environments Webinar (text version) Community Renewable Energy Success Stories: Wind Energy in Urban Environments...

  11. Solar Energy Market Forecast | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-f < RAPID‎ |RippeyInformationSodaAtlas (PACA RegionEnergyMarket

  12. The Future of Offshore Wind Energy

    E-Print Network [OSTI]

    Firestone, Jeremy

    1 The Future of Offshore Wind Energy #12;2 #12;3 Offshore Wind Works Offshore wind parks: 28 in 10 countries Operational since 1991 Current installed capacity: 1,250 MW Offshore wind parks in the waters around Europe #12;4 US Offshore Wind Projects Proposed Atlantic Ocean Gulf of Mexico Cape Wind

  13. Wind Energy at NREL's National Wind Technology Center

    SciTech Connect (OSTI)

    None

    2010-01-01T23:59:59.000Z

    It is a pure, plentiful natural resource. Right now wind is in high demand and it holds the potential to transform the way we power our homes and businesses. NREL is at the forefront of wind energy research and development. NREL's National Wind Technology Center (NWTC) is a world-class facility dedicated to accelerating and deploying wind technology.

  14. Wind Energy at NREL's National Wind Technology Center

    ScienceCinema (OSTI)

    None

    2013-05-29T23:59:59.000Z

    It is a pure, plentiful natural resource. Right now wind is in high demand and it holds the potential to transform the way we power our homes and businesses. NREL is at the forefront of wind energy research and development. NREL's National Wind Technology Center (NWTC) is a world-class facility dedicated to accelerating and deploying wind technology.

  15. Arnold Schwarzenegger California Wind Energy

    E-Print Network [OSTI]

    Albany, New York Contract No. 500-03-006 Prepared For: Public Interest Energy Research (PIER) ProgramArnold Schwarzenegger Governor California Wind Energy Resource Modeling and Measurement Prepared For: California Energy Commission Public Interest Energy Research Program Prepared By: AWS Truewind

  16. Wind Energy Conversion Systems (Minnesota)

    Broader source: Energy.gov [DOE]

    This section distinguishes between large (capacity 5,000 kW or more) and small (capacity of less than 5,000 kW) wind energy conversion systems (WECS), and regulates the siting of large conversion...

  17. Energy from Offshore Wind: Preprint

    SciTech Connect (OSTI)

    Musial, W.; Butterfield, S.; Ram, B.

    2006-02-01T23:59:59.000Z

    This paper provides an overview of the nascent offshore wind energy industry including a status of the commercial offshore industry and the technologies that will be needed for full market development.

  18. Wind Energy Permitting Standards

    Broader source: Energy.gov [DOE]

    All wind facilities larger than 0.5 megawatts (MW) that begin construction after July 1, 2010, must obtain a permit from any county in which the facility is located. Facilities must also obtain...

  19. WP2 IEA Wind Task 26:The Past and Future Cost of Wind Energy

    E-Print Network [OSTI]

    Lantz, Eric

    2014-01-01T23:59:59.000Z

    Speed Sites. European Wind Energy Association. Marseille,Innovation and the price of wind energy in the US. EnergyThe Economics of Wind Energy. Renewable and Sustainable

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

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page onYouTube YouTube Note: SinceDevelopment | Department ofPartnerships ToolkitWasteWho Will BeWhy SOFCWilliamWindDepartment

  1. QER- Comment of Governors' Wind Energy Coalition

    Broader source: Energy.gov [DOE]

    Attached please find the Governors' Wind Energy Coalition's comments on the QER. Thank you. Larry Pearce

  2. Sandia Energy - Innovative Offshore Vertical-Axis Wind Turbine...

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

    Vertical-Axis Wind Turbine Rotors Home Stationary Power Energy Conversion Efficiency Wind Energy Offshore Wind Innovative Offshore Vertical-Axis Wind Turbine Rotors Innovative...

  3. Sandia Energy - Offshore Wind RD&D: Sediment Transport

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

    Transport Home Stationary Power Energy Conversion Efficiency Wind Energy Offshore Wind Offshore Wind RD&D: Sediment Transport Offshore Wind RD&D: Sediment TransportTara...

  4. Sandia Energy - Innovative Offshore Vertical-Axis Wind Turbine...

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

    Innovative Offshore Vertical-Axis Wind Turbine Rotors Home Stationary Power Energy Conversion Efficiency Wind Energy Offshore Wind Innovative Offshore Vertical-Axis Wind Turbine...

  5. Paper accepted for presentation at 2003 IEEE Bologna PowerTech Conference, June 23-26, Bologna, Italy Wind Power Forecasting using Fuzzy Neural Networks

    E-Print Network [OSTI]

    Paris-Sud XI, Universit de

    , Italy Wind Power Forecasting using Fuzzy Neural Networks Enhanced with On-line Prediction Risk) as input, to predict the power production of wind park8 48 hours ahead. The prediction system integrates of the numerical weather predictions. Index Term-Wind power, short-term forecasting, numerical weather predictions

  6. Wind Testing and Certification | Department of Energy

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

    wind plant levels. These testing facilities are geographically diverse, located in key wind energy regions, and possess unique testing capabilities that allow the Department of...

  7. Wind Success Stories | Department of Energy

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

    clean, affordable, and reliable domestic wind power tap into enormous energy-saving potential across the United States. Explore EERE's wind power success stories below. February...

  8. RSE Wind | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2,AUDITCalifornia Sector: Wind energy Product:Anatolia JumpRSE Wind Jump to:

  9. Wind Events | Department of Energy

    Energy Savers [EERE]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directed off Energy.gov. Are you sureReportsofDepartmentSeries |Attacksof EnergyWhenWind Events Wind

  10. Wind Program | Department of Energy

    Energy Savers [EERE]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directed off Energy.gov. Are you sureReportsofDepartmentSeries |Attacksof EnergyWhenWind EventsWind

  11. 20% Wind Energy by 2030 - Chapter 6: Wind Power Markets Summary...

    Energy Savers [EERE]

    6: Wind Power Markets Summary Slides 20% Wind Energy by 2030 - Chapter 6: Wind Power Markets Summary Slides Summary slides overviewing wind power markets, growth, applications, and...

  12. Wind Energy Permitting Standards (North Carolina)

    Broader source: Energy.gov [DOE]

    North Carolina has statewide permitting requirements for wind energy facilities. Any wind turbine or collection of wind turbines located within a half mile of each other with a collective rated...

  13. Fact Sheet: Tehachapi Wind Energy Storage Project (October 2012...

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

    Tehachapi Wind Energy Storage Project (October 2012) Fact Sheet: Tehachapi Wind Energy Storage Project (October 2012) The Tehachapi Wind Energy Storage Project (TSP) Battery Energy...

  14. Wind Energy Career Development Program

    SciTech Connect (OSTI)

    Gwen Andersen

    2012-03-29T23:59:59.000Z

    Saint Francis University has developed curriculum in engineering and in business that is meeting the needs of students and employers (Task 1) as well as integrating wind energy throughout the curriculum. Through a variety of approaches, the University engaged in public outreach and education that reached over 2,000 people annually (Task 2). We have demonstrated, through the success of these programs, that students are eager to prepare for emerging jobs in alternative energy, that employers are willing to assist in developing employees who understand the broader business and policy context of the industry, and that people want to learn about wind energy.

  15. SOLAR IRRADIANCE FORECASTING FOR THE MANAGEMENT OF SOLAR ENERGY SYSTEMS

    E-Print Network [OSTI]

    Heinemann, Detlev

    SOLAR IRRADIANCE FORECASTING FOR THE MANAGEMENT OF SOLAR ENERGY SYSTEMS Detlev Heinemann Oldenburg.girodo@uni-oldenburg.de ABSTRACT Solar energy is expected to contribute major shares of the future global energy supply. Due to its and solar energy conversion processes has to account for this behaviour in respective operating strategies

  16. Funding Opportunity Announcement for Wind Forecasting Improvement Project

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page onYouTube YouTube Note: Since the.pdf Flash2006-52.pdf0.pdfDepartment ofEnergy 3 FuelModelOpportunitiesof Energyin

  17. Energy Department Announces Distributed Wind Competitiveness...

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

    for projects led by Pika Energy, Northern Power Systems, Endurance Wind Power, and Urban Green Energy that will help drive down the cost of small and medium-sized wind energy...

  18. WIND ENERGY Wind Energ. 2013; 00:112

    E-Print Network [OSTI]

    that by a novel change of variables, which focuses on power flows, we can transform the problem to one with linear rejection, model predictive control, convex optimization, wind power control, energy storage, power output to reliable operation of power systems due to the fluctuating nature of wind power. Thus, modern wind power

  19. Mesoscale Simulations of a Wind Ramping Event for Wind Energy Prediction

    SciTech Connect (OSTI)

    Rhodes, M; Lundquist, J K

    2011-09-21T23:59:59.000Z

    Ramping events, or rapid changes of wind speed and wind direction over a short period of time, present challenges to power grid operators in regions with significant penetrations of wind energy in the power grid portfolio. Improved predictions of wind power availability require adequate predictions of the timing of ramping events. For the ramping event investigated here, the Weather Research and Forecasting (WRF) model was run at three horizontal resolutions in 'mesoscale' mode: 8100m, 2700m, and 900m. Two Planetary Boundary Layer (PBL) schemes, the Yonsei University (YSU) and Mellor-Yamada-Janjic (MYJ) schemes, were run at each resolution as well. Simulations were not 'tuned' with nuanced choices of vertical resolution or tuning parameters so that these simulations may be considered 'out-of-the-box' tests of a numerical weather prediction code. Simulations are compared with sodar observations during a wind ramping event at a 'West Coast North America' wind farm. Despite differences in the boundary-layer schemes, no significant differences were observed in the abilities of the schemes to capture the timing of the ramping event. As collaborators have identified, the boundary conditions of these simulations probably dominate the physics of the simulations. They suggest that future investigations into characterization of ramping events employ ensembles of simulations, and that the ensembles include variations of boundary conditions. Furthermore, the failure of these simulations to capture not only the timing of the ramping event but the shape of the wind profile during the ramping event (regardless of its timing) indicates that the set-up and execution of such simulations for wind power forecasting requires skill and tuning of the simulations for a specific site.

  20. Ris National Laboratory Wind Energy Department

    E-Print Network [OSTI]

    Ris National Laboratory Postprint Wind Energy Department Year 2007 Paper: www at the National Test Site for wind turbines at Hvsre (Denmark) and at a 250 m high TV tower at Hamburg (Germany in predictions of the wind profile in the lowest few hundred metres of the atmosphere for use in wind energy

  1. Upcoming Funding Opportunity for Wind Forecasting Improvement Project in

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page onYouTube YouTube Note: SinceDevelopment | Department of Energy $18Unrevised SFO ParagraphsDepartment of

  2. National Wind | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOfRose BendMiasoleTremor(Question)8/14/2007NCPVEnergyOpenlaboratoryWindWind

  3. Wind World | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit withTianlinPapers Home Kyoung's pictureWind Power Energia JumpMaps.jpgWind World

  4. Wind Energy Benefits, Wind Powering America (WPA) (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2011-04-01T23:59:59.000Z

    This fact sheet outlines the top 10 benefits of wind energy, including cost, water savings, job creation, indigenous resource, and low operating costs.

  5. Energy Department Offers Conditional Commitment to Cape Wind...

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

    Cape Wind Offshore Wind Generation Project Energy Department Offers Conditional Commitment to Cape Wind Offshore Wind Generation Project July 1, 2014 - 9:23am Addthis News Media...

  6. Cloudy Computing: Leveraging Weather Forecasts in Energy Harvesting Sensor Systems

    E-Print Network [OSTI]

    Shenoy, Prashant

    Cloudy Computing: Leveraging Weather Forecasts in Energy Harvesting Sensor Systems Navin Sharma,gummeson,irwin,shenoy}@cs.umass.edu Abstract--To sustain perpetual operation, systems that harvest environmental energy must carefully regulate their usage to satisfy their demand. Regulating energy usage is challenging if a system's demands

  7. Leveraging Weather Forecasts in Renewable Energy Navin Sharmaa,

    E-Print Network [OSTI]

    Shenoy, Prashant

    Leveraging Weather Forecasts in Renewable Energy Systems Navin Sharmaa, , Jeremy Gummesonb , David, Binghamton, NY 13902 Abstract Systems that harvest environmental energy must carefully regulate their us- age to satisfy their demand. Regulating energy usage is challenging if a system's demands are not elastic, since

  8. Short-Term Solar Energy Forecasting Using Wireless Sensor Networks

    E-Print Network [OSTI]

    Cerpa, Alberto E.

    Short-Term Solar Energy Forecasting Using Wireless Sensor Networks Stefan Achleitner, Tao Liu an advantage for output power prediction. Solar Energy Prediction System Our prediction model is based variability of more then 100 kW per minute. For practical usage of solar energy, predicting times of high

  9. TRANSPORTATION ENERGY FORECASTS AND ANALYSES FOR THE 2009

    E-Print Network [OSTI]

    Page Manager FOSSIL FUELS OFFICE Mike Smith Deputy Director FUELS AND TRANSPORTATION DIVISION Melissa, Weights and Measurements/Gary Castro, Allan Morrison, John Mough, Ed Williams Clean Energy FuelsCALIFORNIA ENERGY COMMISSION TRANSPORTATION ENERGY FORECASTS AND ANALYSES FOR THE 2009 INTEGRATED

  10. Manzanita Wind Energy Feasibility Study

    SciTech Connect (OSTI)

    Trisha Frank

    2004-09-30T23:59:59.000Z

    The Manzanita Indian Reservation is located in southeastern San Diego County, California. The Tribe has long recognized that the Reservation has an abundant wind resource that could be commercially utilized to its benefit. Manzanita has explored the wind resource potential on tribal land and developed a business plan by means of this wind energy feasibility project, which enables Manzanita to make informed decisions when considering the benefits and risks of encouraging large-scale wind power development on their lands. Technical consultant to the project has been SeaWest Consulting, LLC, an established wind power consulting company. The technical scope of the project covered the full range of feasibility assessment activities from site selection through completion of a business plan for implementation. The primary objectives of this feasibility study were to: (1) document the quality and suitability of the Manzanita Reservation as a site for installation and long-term operation of a commercially viable utility-scale wind power project; and, (2) develop a comprehensive and financeable business plan.

  11. WREF 2012: THE PAST AND FUTURE COST OF WIND ENERGY

    E-Print Network [OSTI]

    Wiser, Ryan

    2013-01-01T23:59:59.000Z

    2009). Technology Roadmap Wind Energy. Paris, France:5) Cea, A; Simonot, E. (2011). The Cost of Wind Energy.Spanish Wind Energy Association (AEE) contribution to IEA

  12. Value Capture in the Global Wind Energy Industry

    E-Print Network [OSTI]

    Dedrick, Jason; Kraemer, Kenneth L.

    2011-01-01T23:59:59.000Z

    investigations/wind-energy-funds-going-overseas/ Dedrick,America. GWEC (Global Wind Energy Council) (2010). Globaland investment flows in the wind energy industry. Peterson

  13. EIS-0470: Cape Wind Energy Project, Final General Conformity...

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

    70: Cape Wind Energy Project, Final General Conformity Determination EIS-0470: Cape Wind Energy Project, Final General Conformity Determination Cape Wind Energy Project, Final...

  14. Shenyang Huachuang Wind Energy Corporation HCWE aka China Creative...

    Open Energy Info (EERE)

    Shenyang Huachuang Wind Energy Corporation HCWE aka China Creative Wind Energy Co Ltd Jump to: navigation, search Name: Shenyang Huachuang Wind Energy Corporation (HCWE) (aka China...

  15. Department of Energy Wind Vision: An Industry Preview | Department...

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

    Department of Energy Wind Vision: An Industry Preview Department of Energy Wind Vision: An Industry Preview The "Department of Energy Wind Vision: An Industry Preview,"...

  16. Standardized Software for Wind Load Forecast Error Analyses and Predictions Based on Wavelet-ARIMA Models - Applications at Multiple Geographically Distributed Wind Farms

    SciTech Connect (OSTI)

    Hou, Zhangshuan; Makarov, Yuri V.; Samaan, Nader A.; Etingov, Pavel V.

    2013-03-19T23:59:59.000Z

    Given the multi-scale variability and uncertainty of wind generation and forecast errors, it is a natural choice to use time-frequency representation (TFR) as a view of the corresponding time series represented over both time and frequency. Here we use wavelet transform (WT) to expand the signal in terms of wavelet functions which are localized in both time and frequency. Each WT component is more stationary and has consistent auto-correlation pattern. We combined wavelet analyses with time series forecast approaches such as ARIMA, and tested the approach at three different wind farms located far away from each other. The prediction capability is satisfactory -- the day-ahead prediction of errors match the original error values very well, including the patterns. The observations are well located within the predictive intervals. Integrating our wavelet-ARIMA (stochastic) model with the weather forecast model (deterministic) will improve our ability significantly to predict wind power generation and reduce predictive uncertainty.

  17. Comparison of Bottom-Up and Top-Down Forecasts: Vision Industry Energy Forecasts with ITEMS and NEMS

    E-Print Network [OSTI]

    Roop, J. M.; Dahowski, R. T

    Comparisons are made of energy forecasts using results from the Industrial module of the National Energy Modeling System (NEMS) and an industrial economic-engineering model called the Industrial Technology and Energy Modeling System (ITEMS), a model...

  18. Mesoscale and Large-Eddy Simulations for Wind Energy

    SciTech Connect (OSTI)

    Marjanovic, N

    2011-02-22T23:59:59.000Z

    Operational wind power forecasting, turbine micrositing, and turbine design require high-resolution simulations of atmospheric flow over complex terrain. The use of both Reynolds-Averaged Navier Stokes (RANS) and large-eddy (LES) simulations is explored for wind energy applications using the Weather Research and Forecasting (WRF) model. To adequately resolve terrain and turbulence in the atmospheric boundary layer, grid nesting is used to refine the grid from mesoscale to finer scales. This paper examines the performance of the grid nesting configuration, turbulence closures, and resolution (up to as fine as 100 m horizontal spacing) for simulations of synoptically and locally driven wind ramping events at a West Coast North American wind farm. Interestingly, little improvement is found when using higher resolution simulations or better resolved turbulence closures in comparison to observation data available for this particular site. This is true for week-long simulations as well, where finer resolution runs show only small changes in the distribution of wind speeds or turbulence intensities. It appears that the relatively simple topography of this site is adequately resolved by all model grids (even as coarse as 2.7 km) so that all resolutions are able to model the physics at similar accuracy. The accuracy of the results is shown in this paper to be more dependent on the parameterization of the land-surface characteristics such as soil moisture rather than on grid resolution.

  19. AWEA State Wind Energy Forum - Michigan | Department of Energy

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

    State Wind Energy Forum - Michigan AWEA State Wind Energy Forum - Michigan January 20, 2015 8:00AM to 5:00PM EST Lansing, MI Michigan has 988 MW of installed wind capacity,...

  20. Wind Energy Resources and Technologies | Department of Energy

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

    Wind Energy Resources and Technologies Wind Energy Resources and Technologies Photo of two wind turbines standing on a mountain in front of a cloudy blue sky. The Department of...

  1. Vantage Wind Energy Center | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTri Global EnergyUtility Rate Home >VairexAlstyne,Wind FarmWind Energy

  2. Cowal Wind Energy Ltd | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2,AUDIT REPORTEnergy Offshore Place:WindOilCowal Wind Energy Ltd Jump to:

  3. Energy in the Wind

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOEThe Bonneville Power AdministrationField8, 2000Consumption SurveyEnergy Storage EnergyD Energy and(DailyEnergy

  4. Comments of the American Wind Energy...

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

    and wind power development. Assuming a conservative 35MWh value for curtailed wholesale energy would put a value of over 100 million on the wind energy that was curtailed...

  5. Currituck County- Wind Energy Systems Ordinance

    Broader source: Energy.gov [DOE]

    In January 2008, Currituck County adopted an ordinance to regulate the use of wind-energy systems. The ordinance directs any individual or organization wishing to install a wind-energy system to...

  6. AWEA Wind Energy Regional Summit: Northeast

    Office of Energy Efficiency and Renewable Energy (EERE)

    The AWEA Wind Energy Northeast Regional Summit will connect you with New England-area wind energy professionals and offers the opportunity to discuss significant issues related to land-based and...

  7. Examples of Wind Energy Curtailment Practices

    SciTech Connect (OSTI)

    Rogers, J.; Fink, S.; Porter, K.

    2010-07-01T23:59:59.000Z

    This report addresses examples of wind energy curtailment practices internationally and in regions across the United States.

  8. Wind energy systems information user study

    SciTech Connect (OSTI)

    Belew, W.W.; Wood, B.L.; Marle, T.L.; Reinhardt, C.L.

    1981-01-01T23:59:59.000Z

    This report describes the results of a series of telephone interviews with potential users of information on wind energy conversion. These interviews, part of a larger study covering nine different solar technologies, attempted to identify: the type of information each distinctive group of information users needed, and the best way of getting information to that group. Groups studied include: wind energy conversion system researchers; wind energy conversion system manufacturer representatives; wind energy conversion system distributors; wind turbine engineers; utility representatives; educators; county agents and extension service agents; and wind turbine owners.

  9. Integrating agricultural pest biocontrol into forecasts of energy biomass production

    E-Print Network [OSTI]

    Gratton, Claudio

    Analysis Integrating agricultural pest biocontrol into forecasts of energy biomass production T), University of Lome, 114 Rue Agbalepedogan, BP: 20679, Lome, Togo e Center for Agricultural & Energy Policy model of potential biomass supply that incorporates the effect of biological control on crop choice

  10. Exploiting weather forecasts for sizing photovoltaic energy bids

    E-Print Network [OSTI]

    Giannitrapani, Antonello

    1 Exploiting weather forecasts for sizing photovoltaic energy bids Antonio Giannitrapani, Simone for a photovoltaic (PV) power producer taking part into a competitive electricity market characterized by financial set from an Italian PV plant. Index Terms--Energy market, bidding strategy, photovoltaic power

  11. Ris National Laboratory Wind Energy Department

    E-Print Network [OSTI]

    and the wind power density 36 (Troen & Petersen, 1989). In screening for potential offshore wind 37farm sitesRisø National Laboratory Postprint Wind Energy Department Year 2006 Paper: www.risoe.dk/rispubl/art/2006_96.pdf Wind resource assessment from C-band SAR Merete Bruun Christiansen a, Wolfgang Koch b

  12. Minco Wind Energy Center | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOfRose BendMiasole Inc JumpMicroPlanet Name:I & II Wind FarmWind Energy

  13. Stateline Wind Energy Project | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-f < RAPID‎SolarCity CorpSpringfield,WindForeignForestWind Energy

  14. The communication dimension of wind energy

    E-Print Network [OSTI]

    McCalley, James D.

    The communication dimension of wind energy: Challenges and opportunities #12;OPPORTUNITIES #12;Pew;1. Emergent anti-wind energy advocacy groups #12;2. A multi-faceted technical issue that is difficult to explain Wind energy Policy Science Engineering Ethics Public relations Others #12;3. Different audience

  15. Wind Energy Facility Reliability and Maintenance

    E-Print Network [OSTI]

    Ding, Yu

    Wind Energy Facility Reliability and Maintenance Eunshin Byon, Lewis Ntaimo, Chanan Singh and Yu related to wind energy facility reliability and mainte- nance focused more on qualitative aspects. In this chapter, we provide a comprehensive account of the existing research regarding wind energy facility

  16. CREST Wind | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof EnergyInnovation inOpen Energy InformationSeries JumpCREST Geothermal JumpWind

  17. Prediction of wind speed profiles for short-term forecasting in the offshore environment R.J. Barthelmie and G. Giebel

    E-Print Network [OSTI]

    in planning of maintenance visits to offshore wind farms. In most cases the basis for the predictionPrediction of wind speed profiles for short-term forecasting in the offshore environment R wind farms. The main effects considered here are: wind speed gradients in the coastal zone, vertical

  18. WINDExchange: Wind Energy Ordinances

    Wind Powering America (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTownDells, Wisconsin:Deployment Activities Printable Version

  19. WREF 2012: THE PAST AND FUTURE COST OF WIND ENERGY

    E-Print Network [OSTI]

    Wiser, Ryan

    2013-01-01T23:59:59.000Z

    5. DRIVERS OF FUTURE WIND ENERGY COST REDUCTIONS A largeput upward pressure on wind energy costs, such as continuedE. (2011). The Cost of Wind Energy. Spanish Wind Energy

  20. Offshore Wind Power USA

    Broader source: Energy.gov [DOE]

    The Offshore Wind Power USA conference provides the latest offshore wind market updates and forecasts.

  1. Wind Energy Development & Wildlife Striving for Co-existence

    E-Print Network [OSTI]

    McCalley, James D.

    Wind Energy Development & Wildlife Striving for Co-existence Caroline Jezierski Nebraska Wind #12;Wind Energy Potential @ 30m http://www.nrel.gov/gis/images/30m_US_Wind.jpg #12;Wind Energy Potential @ 50m http://www.nrel.gov/gis/images/US-50m-wind-power-map.jpg #12;Wind Energy Potential @ 80m

  2. Wind Energy | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645 3,625 1,006 492 742Energy China 2015ofDepartment of EnergyThe U.S. DepartmentEnergyWilliam E.Much asPhoto

  3. WREF 2012: THE PAST AND FUTURE COST OF WIND ENERGY

    E-Print Network [OSTI]

    Wiser, Ryan

    2013-01-01T23:59:59.000Z

    WIND ENERGY by as much as 270% when comparing todays turbinesTurbines in Denmark. Presentation to IEA Wind Task 26 (12) European Wind Energy

  4. Wind Energy Education and Outreach Project

    SciTech Connect (OSTI)

    David G. Loomis

    2011-04-15T23:59:59.000Z

    The purpose of Illinois State University??s wind project was to further the education and outreach of the university concerning wind energy. This project had three major components: to initiate and coordinate a Wind Working Group for the State of Illinois, to launch a Renewable Energy undergraduate program, and to develop the Center for Renewable Energy that will sustain the Illinois Wind Working Group and the undergraduate program.

  5. Energy Report: U.S. Wind Energy Production and Manufacturing...

    Energy Savers [EERE]

    Report: U.S. Wind Energy Production and Manufacturing Surges, Supporting Jobs and Diversifying U.S. Energy Economy Energy Report: U.S. Wind Energy Production and Manufacturing...

  6. Harbor Wind | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, search OpenEI ReferenceJumpEnergyStrategy | OpenHalfWind Jump to: navigation,

  7. Horn Wind | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are8COaBulkTransmissionSitingProcess.pdfGetecGtel Jump to:Pennsylvania: EnergyHopkinsville,Wind Jump to: navigation,

  8. Auwahi Wind | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia: Energy ResourcesInformationGuideInformationAuwahi Wind Jump

  9. Modular Wind | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal Pwer Plant JumpMarysville,Missoula, Montana: EnergyAnalysis ofDecker,ModernizingModular Wind

  10. Wyoming Wind Energy Center | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTriWildcat 1 Wind Project JumpWisconsin:WorldWorldIowa:Wuxi,WyomingWind

  11. Oliver Wind Energy Center | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOfRoseConcernsCompany Oil and Gas CompanyOklahoma/WindOkpilakII Wind

  12. Mogul Energy Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOfRose BendMiasole IncMinuteman WindMoana(Tempel,Moe Wind Farm Jump

  13. Sandia Energy - Offshore Wind

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del Sol Home Distribution Grid Integration PermalinkClimateNumericalPublications

  14. Women of Wind Energy Leadership Forum

    Broader source: Energy.gov [DOE]

    The 2014 Women of Wind Energy Leadership Forum combines professional development with tools to advance renewable energy. Join professionals from across the country to discuss current renewable...

  15. Searchlight Wind Energy Project FEIS Appendix B

    Office of Environmental Management (EM)

    Bird and Bat Conservation Strategy Searchlight BBCS i October 2012 Searchlight Wind Energy Project Bird and Bat Conservation Strategy Prepared for: Duke Energy Renewables 550...

  16. Oregon Department of Energy Webinar: Offshore Wind

    Broader source: Energy.gov [DOE]

    The intended audience for this webinar on offshore wind basics is decision-makers, energy industry practitioners, utilities, and those knowledgeable about renewable energy. The webinar will feature...

  17. Wind Energy Workforce Development: A Roadmap to a Wind Energy Educational Infrastructure (Presentation)

    SciTech Connect (OSTI)

    Baring-Gould, I.

    2011-05-01T23:59:59.000Z

    Wind Powering America national technical director Ian Baring-Gould made this presentation about workforce development in the wind energy industry to an audience at the American Wind Energy Association's annual WINDPOWER conference in Anaheim. The presentation outlines job projections from the 20% Wind Energy by 2030 report and steps to take at all levels of educational institutions to meet those projections.

  18. Sandia Energy » Wind Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What's PossibleRadiationImplementingnpitche Home About npitcheSandian Wins Award in 2015 OMAEAustralian

  19. Copyright notice: this is the self-archived version of an article accepted for publication in Wind Energy, September 2013. The copyright now belongs to John Wiley & Sons, Ltd. DOI: 10.1002/we.1680

    E-Print Network [OSTI]

    Boyer, Edmond

    . The stochastic nature of wind power production is a source of uncertainty in the grid energy balance which has: http://onlinelibrary.wiley.com/doi/1 .1 2/we.168 /abstract Energy storage sizing for wind power: impact dispatchability of wind power production. However, the stochastic nature of forecast errors prevents a wind farm

  20. Wind Energy Department Annual Progress Report 2002

    E-Print Network [OSTI]

    Wind Energy Department Annual Progress Report 2002 Edited by Birgitte D. Johansen and Ulla Riis The new Test Station at Hvsre Ris National Laboratory December 2003 Ris-R-1419(EN) #12;Wind Energy Aeroelastic Design (AED) p. 10 Atmospheric Physics (ATM) p. 15 Electrical Design and Control (EDS) p. 24 Wind

  1. Wind Energy Department Annual Progress Report 2003

    E-Print Network [OSTI]

    Wind Energy Department Annual Progress Report 2003 Edited by Birgitte D. Johansen and Ulla Riis 2003 p. 6 Projects of the Department Meteorology (MET) p. 11 Aeroelastic Design (AED) p. 30 Wind Turbines (VIM) p. 36 Wind Energy Systems (VES) p. 41 Test and Measurements (TEM) p. 53 Sparkr Blade Test

  2. Capacity Building in Wind Energy for PICs

    E-Print Network [OSTI]

    indicates that significant wind energy potential exists. · A monitoring project showed that in Rarotonga system. · About 30 other islands could have potential for grid connected wind turbines in the 100-1000 k1 Capacity Building in Wind Energy for PICs Presentation of the project Regional Workshop Suva

  3. 20% Wind Energy by 2030 - Chapter 5: Wind Power Siting and Environment...

    Energy Savers [EERE]

    5: Wind Power Siting and Environmental Effects Summary Slides 20% Wind Energy by 2030 - Chapter 5: Wind Power Siting and Environmental Effects Summary Slides Environment and siting...

  4. Sandia Energy - Wind Energy Staff

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del Sol Home DistributionTransportation Safety HomeWater PowerEnergy Staff Home

  5. Adaptive Energy Forecasting and Information Diffusion for Smart Power Grids

    E-Print Network [OSTI]

    Prasanna, Viktor K.

    1 Adaptive Energy Forecasting and Information Diffusion for Smart Power Grids Yogesh Simmhan, prasanna}@usc.edu I. INTRODUCTION Smart Power Grids exemplify an emerging class of Cyber Physical-on paradigm to support operational needs. Smart Grids are an outcome of instrumentation, such as Phasor

  6. Sandia Energy - Wind Vision 2015: A New Era for Wind Power in...

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

    Wind Power in the United States Home Stationary Power Energy Conversion Efficiency Wind Energy Special Programs Wind Vision 2015: A New Era for Wind Power in the United States...

  7. WP2 IEA Wind Task 26:The Past and Future Cost of Wind Energy

    E-Print Network [OSTI]

    Lantz, Eric

    2014-01-01T23:59:59.000Z

    Bolinger, M. ( 2011). 2010 Wind Technologies Market Report.Cost of Energy From U.S. Wind Power Projects. Presentationand Energy Capture at Low Wind Speed Sites. European Wind

  8. Camden County- Wind Energy Systems Ordinance

    Broader source: Energy.gov [DOE]

    In September 2007, Camden County adopted a wind ordinance to regulate the use of wind-energy systems in the county and to describe the conditions by which a permit for installing such a system may...

  9. Watauga County- Wind Energy System Ordinance

    Broader source: Energy.gov [DOE]

    In 2006, Watauga County adopted a wind ordinance to regulate the use of wind-energy systems in the county and to describe the conditions by which a permit for installing such a system may be...

  10. Hyde County- Wind Energy Facility Ordinance

    Broader source: Energy.gov [DOE]

    Hyde County, located in eastern North Carolina, adopted a wind ordinance in 2008 to regulate the use of wind energy facilities throughout the county, including waters within the boundaries of Hyde...

  11. Tyrrell County- Wind Energy Facility Ordinance

    Broader source: Energy.gov [DOE]

    Tyrrell County, located in northeastern North Carolina, adopted a wind ordinance in 2009 to regulate the use of wind energy facilities in the unincorporated areas of the county. The ordinance is...

  12. 2010 Cost of Wind Energy Review

    SciTech Connect (OSTI)

    Tegen, S.; Hand, M.; Maples, B.; Lantz, E.; Schwabe, P.; Smith, A.

    2012-04-01T23:59:59.000Z

    This document provides a detailed description of NREL's levelized cost of wind energy equation, assumptions and results in 2010, including historical cost trends and future projections for land-based and offshore utility-scale wind.

  13. WREF 2012: THE PAST AND FUTURE COST OF WIND ENERGY

    E-Print Network [OSTI]

    Wiser, Ryan

    2013-01-01T23:59:59.000Z

    A; Simonot, E. (2011). The Cost of Wind Energy. Spanish Wind5. DRIVERS OF FUTURE WIND ENERGY COST REDUCTIONS A largeput upward pressure on wind energy costs, such as continued

  14. Perceived Socioeconomic Impacts of Wind Energy in West Texas

    E-Print Network [OSTI]

    Persons, Nicole D.

    2010-07-14T23:59:59.000Z

    Wind power is a fast growing alternative energy source. Since 2000, wind energy capacity has increased 24 percent per year with Texas leading the U.S. in installed wind turbine capacity. Most socioeconomic research in wind energy has focused...

  15. Perceived Socioeconomic Impacts of Wind Energy in West Texas

    E-Print Network [OSTI]

    Persons, Nicole D.

    2010-07-14T23:59:59.000Z

    Wind power is a fast growing alternative energy source. Since 2000, wind energy capacity has increased 24 percent per year with Texas leading the U.S. in installed wind turbine capacity. Most socioeconomic research in wind energy has focused...

  16. A WRF Ensemble for Improved Wind Speed Forecasts at Turbine Height ADAM J. DEPPE AND WILLIAM A. GALLUS JR.

    E-Print Network [OSTI]

    McCalley, James D.

    . 1. Introduction In recent years, wind energy production has under- gone rapid growth, and the U over both space and time. Therefore, the production rates of wind energy fluctuate more strongly than percentage of total power per capita coming from wind energy in 2010 (Department of Energy 2010). Even fewer

  17. Garnet Wind | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489InformationFrenchtown, NewG22 Jump to:Garnet Wind Jump to:

  18. Evance Wind | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual SiteofEvaluating A PotentialJumpGerman Aerospace Center (DLR)European FuelEvaderEvance Wind

  19. Sandia Energy - Wind Plant Optimization

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del Sol Home DistributionTransportation Safety HomeWater PowerEnergy Staff HomeWind

  20. Willmar Wind | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTriWildcat 1 Wind Project Jump to: navigation,Williamsport, Indiana:

  1. Wind Walkers | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTriWildcat 1 Wind Project Jump to:Wilson HotWalkers Jump to: navigation,

  2. Wind turbine | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTriWildcat 1 Wind Project Jump to:Wilson HotWalkers Jump to:group has

  3. Wiota Wind | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTriWildcat 1 Wind Project Jump to:WilsonIIa

  4. Kawailoa Wind | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOf Kilauea Volcano, Hawaii |Island,Kas Farms Wind Farm Jump to:Kawailoa

  5. Rockland Wind | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-f < RAPID‎ |Rippey Jump to: navigation,RockPortRockland County, NewWind

  6. Sheffield Wind | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-f < RAPID‎ |Rippey JumpAirPower Partners Wind FarmSheep Valley

  7. Wind 7 | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit withTianlinPapers Home Kyoung's picture SubmittedWielandJumpWimberley,Wind 7 Jump

  8. Royal Wind | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro Industries Pvt Ltd Jump to:Roscommon County, Michigan:RotokawaRoxboroughEstates, Florida:Wind

  9. Impact of Energy Imbalance Tariff on Wind Energy

    SciTech Connect (OSTI)

    Wan, Y.; Milligan, M.; Kirby, B.

    2007-07-01T23:59:59.000Z

    This paper summarizes the results of a study that uses actual wind power data and actual energy prices to analyze the impact of an energy imbalance tariff imposed by the Federal Energy Regulatory Commission on wind power.

  10. A sensitivity analysis of the treatment of wind energy in the AEO99 version of NEMS

    SciTech Connect (OSTI)

    Osborn, Julie G; Wood, Frances; Richey, Cooper; Sanders, Sandy; Short, Walter; Koomey, Jonathan

    2001-01-01T23:59:59.000Z

    Each year, the U.S. Department of Energy's Energy Information Administration (EIA) publishes a forecast of the domestic energy economy in the Annual Energy Outlook (AEO). During the forecast period of the AEO (currently through 2020), renewable energy technologies have typically not achieved significant growth. The contribution of renewable technologies as electric generators becomes more important, however, in scenarios analyzing greenhouse gas emissions reductions or significant technological advancements. We examined the economic assumptions about wind power used for producing forecasts with the National Energy Modeling System (NEMS) to determine their influence on the projected capacity expansion of this technology. This analysis should help illustrate to policymakers what types of issues may affect wind development, and improve the general understanding of the NEMS model itself. Figure 1 illustrates the model structure and factors relevant to wind deployment. We found that NEMS uses various cost multipliers and constraints to represent potential physical and economic limitations to growth in wind capacity, such as resource depletion, costs associated with rapid manufacturing expansion, and grid stability with high levels of capacity from intermittent resources. The model's flexibility allows the user to make alternative assumptions about the magnitude of these factors. While these assumptions have little effect on the Reference Case forecast for the 1999 edition of the AEO, they can make a dramatic difference when wind is more attractive, such as under a carbon permit trading system. With $100/ton carbon permits, the wind capacity projection for 2020 ranges from 15 GW in the unaltered model (AEO99 Reference Case) to 168 GW in the extreme case when all the multipliers and constraints examined in this study are removed. Furthermore, if modifications are made to the model allowing inter-regional transmission of electricity, wind capacity is forecast to reach 214 GW when all limitations are removed. The figures in the upper end of these ranges are not intended to be viewed as reasonable projections, but their magnitude illustrates the importance of the parameters governing the growth of wind capacity and resource availability in forecasts using NEMS. In addition, many uncertainties exist regarding these assumptions that potentially affect the growth of wind power. We suggest several areas in which to focus future research in order to better model the potential development of this resource. Because many of the assumptions related to wind in the model are also used for other renewable technologies, these suggestions could be applied to other renewable resources as well.

  11. Sandia Energy - Wind Energy Publications

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del Sol Home DistributionTransportation Safety HomeWater Power

  12. Wind Powering America Fact Sheet Series 1 Wind energy is more expensive than conventional energy.

    E-Print Network [OSTI]

    Massachusetts at Amherst, University of

    Wind Powering America Fact Sheet Series 1 Wind energy is more expensive than conventional energy. Wind's variability does increase the day-to-day and minute-to- minute operating costs of a utility system because the wind variations do affect the operation of other plants. But investigations by utility

  13. WP2 IEA Wind Task 26:The Past and Future Cost of Wind Energy

    E-Print Network [OSTI]

    Lantz, Eric

    2014-01-01T23:59:59.000Z

    G. ; Zervos, A. (2011). Wind Energy. In IPCC Special ReportSpeed Sites. European Wind Energy Association. Marseille,Innovation and the price of wind energy in the US. Energy

  14. Diamond Willow Wind (08) Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489 No revision hasda62829c05bGabbs TypeWinds Wind Farm8) Wind Farm

  15. Mid-Atlantic Regional Wind Energy Institute

    SciTech Connect (OSTI)

    Courtney Lane

    2011-12-20T23:59:59.000Z

    As the Department of Energy stated in its 20% Wind Energy by 2030 report, there will need to be enhanced outreach efforts on a national, state, regional, and local level to communicate wind development opportunities, benefits and challenges to a diverse set of stakeholders. To help address this need, PennFuture was awarded funding to create the Mid-Atlantic Regional Wind Energy Institute to provide general education and outreach on wind energy development across Maryland, Virginia, Delaware, Pennsylvania and West Virginia. Over the course of the two-year grant period, PennFuture used its expertise on wind energy policy and development in Pennsylvania and expanded it to other states in the Mid-Atlantic region. PennFuture accomplished this through reaching out and establishing connections with policy makers, local environmental groups, health and economic development organizations, and educational institutions and wind energy developers throughout the Mid-Atlantic region. PennFuture conducted two regional wind educational forums that brought together wind industry representatives and public interest organizations from across the region to discuss and address wind development in the Mid-Atlantic region. PennFuture developed the agenda and speakers in collaboration with experts on the ground in each state to help determine the critical issue to wind energy in each location. The sessions focused on topics ranging from the basics of wind development; model ordinance and tax issues; anti-wind arguments and counter points; wildlife issues and coalition building. In addition to in-person events, PennFuture held three webinars on (1) Generating Jobs with Wind Energy; (2) Reviving American Manufacturing with Wind Power; and (3) Wind and Transmission. PennFuture also created a web page for the institute (http://www.midatlanticwind.org) that contains an online database of fact sheets, research reports, sample advocacy letters, top anti-wind claims and information on how to address them, wind and wildlife materials and sample model ordinances. Video and presentations from each in-person meeting and webinar recordings are also available on the site. At the end of the two-year period, PennFuture has accomplished its goal of giving a unified voice and presence to wind energy advocates in the Mid-Atlantic region. We educated a broad range of stakeholders on the benefits of wind energy and gave them the tools to help make a difference in their states. We grew a database of over 500 contacts and hope to continue the discussion and work around the importance of wind energy in the region.

  16. Wind Energy Alaska | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown ofNationwideWTEDBird,Wilsonville, Oregon: EnergyWind Energy Alaska Place:

  17. Wind Energy Benefits | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown ofNationwideWTEDBird,Wilsonville, Oregon: EnergyWind Energy Alaska

  18. Wind Energy Community Acceptance | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown ofNationwideWTEDBird,Wilsonville, Oregon: EnergyWind Energy AlaskaAcceptance

  19. Wind Energy Group WEG | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown ofNationwideWTEDBird,Wilsonville, Oregon: EnergyWind Energy AlaskaAcceptanceWEG

  20. Wind Energy Technology Module | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown ofNationwideWTEDBird,Wilsonville, Oregon: EnergyWind EnergyTechnology Module

  1. Wind Energy Transmission | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown ofNationwideWTEDBird,Wilsonville, Oregon: EnergyWind EnergyTechnologyPhotoshop

  2. Prairie Wind Energy LLC | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere I Geothermal PwerPerkins County, Nebraska: EnergyPiratiniEdwards,PoseyPoudrePowersPrairie Wind Energy LLC

  3. China Wind Energy Association | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2,AUDIT REPORTEnergy Offshore Place:Wind Energy Association Place: Beijing,

  4. Geronimo Wind Energy | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2,AUDIT REPORTEnergyFarms A SUK Place:Georgia DepartmentGeronimo Wind Energy

  5. Baseline Wind Energy Facility | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia: EnergyAvignon, France:Barstow, California:Baseline Wind Energy

  6. Establishing a Comprehensive Wind Energy Program

    SciTech Connect (OSTI)

    Fleeter, Sanford [Purdue University

    2012-09-30T23:59:59.000Z

    This project was directed at establishing a comprehensive wind energy program in Indiana, including both educational and research components. A graduate/undergraduate course ME-514 - Fundamentals of Wind Energy has been established and offered and an interactive prediction of VAWT performance developed. Vertical axis wind turbines for education and research have been acquired, instrumented and installed on the roof top of a building on the Calumet campus and at West Lafayette (Kepner Lab). Computational Fluid Dynamics (CFD) calculations have been performed to simulate these urban wind environments. Also, modal dynamic testing of the West Lafayette VAWT has been performed and a novel horizontal axis design initiated. The 50-meter meteorological tower data obtained at the Purdue Beck Agricultural Research Center have been analyzed and the Purdue Reconfigurable Micro Wind Farm established and simulations directed at the investigation of wind farm configurations initiated. The virtual wind turbine and wind turbine farm simulation in the Visualization Lab has been initiated.

  7. Wind Vision | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del SolStrengtheningWildfires may contribute more to globalWind Power

  8. Wind Program | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuels DataEnergy TechConnect WorldVeteran Programs VeteranYou|RenewableWindNews

  9. Forecast of Regional Power Output of Wind Turbines Hans Georg Beyer, Detlev Heinemann, Harald Mellinghoff, Kai Monnich, Hans-Peter Waldl

    E-Print Network [OSTI]

    Heinemann, Detlev

    Forecast of Regional Power Output of Wind Turbines Hans Georg Beyer, Detlev Heinemann, Harald of wind turbines connected to the public electricity grid will be intro- duced. Using this procedure and Northern Germany. At the moment, the installed capacity of wind turbines is in the order of magnitude

  10. Strengthening America's Energy Security with Offshore Wind (Fact Sheet) (Revised)

    SciTech Connect (OSTI)

    Not Available

    2012-04-01T23:59:59.000Z

    This fact sheet provides a brief description of offshore wind energy development in the U.S. and DOE's Wind Program offshore wind R&D activities.

  11. WREF 2012: THE PAST AND FUTURE COST OF WIND ENERGY

    E-Print Network [OSTI]

    Wiser, Ryan

    2013-01-01T23:59:59.000Z

    2009). Technology Roadmap Wind Energy. Paris, France:Bolinger, M. (2011). 2010 Wind Technologies Market Report.konomi (The Economy of Wind Power). EUDP 33033-0196.

  12. australia wind energy: Topics by E-print Network

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

    energy the siting of a wind farm is dependent upon reliable information about the wind climate within the area 40 WIND ENERGY Wind Energ. 2013; 16:7790 Engineering Websites...

  13. american wind energy: Topics by E-print Network

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

    energy the siting of a wind farm is dependent upon reliable information about the wind climate within the area 34 WIND ENERGY Wind Energ. 2013; 16:7790 Engineering Websites...

  14. arctic wind energy: Topics by E-print Network

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

    energy the siting of a wind farm is dependent upon reliable information about the wind climate within the area 38 WIND ENERGY Wind Energ. 2013; 16:7790 Engineering Websites...

  15. Value Capture in the Global Wind Energy Industry

    E-Print Network [OSTI]

    Dedrick, Jason; Kraemer, Kenneth L.

    2011-01-01T23:59:59.000Z

    Wind Energy Council, 2011 New installation in 2010 The wind industry value chain Wind turbineWind Energy Council (GWEC, 2011) domestic content in U.S. -deployed turbines

  16. Improved diagnostic model for estimating wind energy

    SciTech Connect (OSTI)

    Endlich, R.M.; Lee, J.D.

    1983-03-01T23:59:59.000Z

    Because wind data are available only at scattered locations, a quantitative method is needed to estimate the wind resource at specific sites where wind energy generation may be economically feasible. This report describes a computer model that makes such estimates. The model uses standard weather reports and terrain heights in deriving wind estimates; the method of computation has been changed from what has been used previously. The performance of the current model is compared with that of the earlier version at three sites; estimates of wind energy at four new sites are also presented.

  17. Wind Energy Benefits, Wind Powering America (WPA) (Fact Sheet), Wind And Water Power Program (WWPP)

    Broader source: Energy.gov [DOE]

    This fact sheet outlines the top 10 benefits of wind energy, including cost, water savings, job creation, indigenous resource, and low operating costs.

  18. HTH Wind Energy Inc | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2,AUDIT REPORTEnergyFarms A SUKHydrogenGuascor GeratecGyeongnamHMHHTH Wind

  19. Innovative Wind Energy, Inc | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2,AUDIT REPORTEnergyFarmsPower Co Ltd Jump to:Innovative Wind Concepts

  20. Navajo Wind Energy | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2,AUDIT REPORTEnergyFarmsPower CoLongxingPartnersNRELAct YearNTPCNauticaWind

  1. Wales Wind Energy Project | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTri Global EnergyUtilityInformation Waiver of Preferential RightWind

  2. Havoco Wind Energy LLC | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, search OpenEI ReferenceJumpEnergyStrategy |Hatchet Ridge Wind Farm JumpHavoco

  3. Illinois Wind Energy | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are8COaBulkTransmissionSitingProcess.pdfGetecGtel JumpCounty, Texas:ITCSolidIdaho‎ |Idylwood,Ike SkeltonIncEnergyWind

  4. Cambrian Wind Energy | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2,AUDIT REPORT Americium/CuriumAguaBBBWind-BrizaHKC WindCTCalRENEW-1Greater

  5. World Wind Energy Association | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit withTianlinPapers Home Kyoung'sWoongjin Polysilicon Co LtdWorldWind Energy

  6. Freedom Wind Energy LLC | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are8COaBulkTransmissionSitingProcess.pdf Jump1946865°, -86.0529604° Show MapFredericksburg Place:Freedom Wind Energy

  7. Wind Program: Wind Vision | Department of Energy

    Energy Savers [EERE]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2, 2015Visiting Strong, Smart,Department

  8. Renewable Energy RFPs: Solicitation Response and Wind Contract Prices

    E-Print Network [OSTI]

    Wiser, Ryan; Bolinger, Mark

    2005-01-01T23:59:59.000Z

    Energy RFPs: Solicitation Response and Wind Contract Pricesenergy capacity (especially wind). Though detailed information on bid prices

  9. Final Environmental Assessment, Burleigh County Wind Energy Center

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

    Assessment Environmental Assessment Environmental Assessment Burleigh County Wind Energy Center Burleigh County, North Dakota Final Burleigh County Wind, LLC BASIN...

  10. Carteret County- Wind Energy System Ordinance

    Broader source: Energy.gov [DOE]

    Carteret County passed an ordinance to specify the permitting process and establish siting requirements for wind energy systems. There are different rules and a different permitting process...

  11. Overview of Existing Wind Energy Ordinances

    Broader source: Energy.gov [DOE]

    The purpose of this report is to educate and engage state and local governments, as well as policymakers, about existing large wind energy ordinances.

  12. Energy Department Announces Offshore Wind Demonstration Awardees...

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

    demonstration partnerships with broad consortia that are developing breakthrough offshore wind energy generation projects. The primary goals of these projects are to...

  13. WP2 IEA Wind Task 26:The Past and Future Cost of Wind Energy

    E-Print Network [OSTI]

    Lantz, Eric

    2014-01-01T23:59:59.000Z

    that have influenced wind energy costs in the past and areSources of Future Wind Energy Cost Reductions R&D/Learninghistorical declines, wind energy costs were increasing for

  14. Solar and Wind Energy Equipment Exemption

    Broader source: Energy.gov [DOE]

    In Wisconsin, any value added by a solar-energy system or a wind-energy system is exempt from general property taxes. A solar-energy system is defined as "equipment which directly converts and then...

  15. National Offshore Wind Energy Grid Interconnection Study

    SciTech Connect (OSTI)

    Daniel, John P. [ABB Inc; Liu, Shu [ABB Inc; Ibanez, Eduardo [National Renewable Energy Laboratory; Pennock, Ken [AWS Truepower; Reed, Greg [University of Pittsburgh; Hanes, Spencer [Duke Energy

    2014-07-30T23:59:59.000Z

    The National Offshore Wind Energy Grid Interconnection Study (NOWEGIS) considers the availability and potential impacts of interconnecting large amounts of offshore wind energy into the transmission system of the lower 48 contiguous United States. A total of 54GW of offshore wind was assumed to be the target for the analyses conducted. A variety of issues are considered including: the anticipated staging of offshore wind; the offshore wind resource availability; offshore wind energy power production profiles; offshore wind variability; present and potential technologies for collection and delivery of offshore wind energy to the onshore grid; potential impacts to existing utility systems most likely to receive large amounts of offshore wind; and regulatory influences on offshore wind development. The technologies considered the reliability of various high-voltage ac (HVAC) and high-voltage dc (HVDC) technology options and configurations. The utility system impacts of GW-scale integration of offshore wind are considered from an operational steady-state perspective and from a regional and national production cost perspective.

  16. The Cost of Transmission for Wind Energy: A Review of Transmission Planning Studies

    E-Print Network [OSTI]

    Mills, Andrew D.

    2009-01-01T23:59:59.000Z

    2006. Transmission and Wind Energy: Capturing the Prevailingand Renewable Energy (Wind & Hydropower Technologiesand Renewable Energy Wind & Hydropower Technologies Program

  17. Fostering a Renewable Energy Technology Industry: An International Comparison of Wind Industry Policy Support Mechanisms

    E-Print Network [OSTI]

    Lewis, Joanna; Wiser, Ryan

    2005-01-01T23:59:59.000Z

    and Renewable Energy, Wind & Hydropower Technologiesand Renewable Energy, Wind & Hydropower Technologies2004. International Wind Energy Development, World Market

  18. Solar and Wind Energy Resource Assessment Programme's Renewable...

    Open Energy Info (EERE)

    Solar and Wind Energy Resource Assessment Programme's Renewable Energy Resource Explorer Jump to: navigation, search Tool Summary LAUNCH TOOL Name: Solar and Wind Energy Resource...

  19. Sandia Energy - Quantifying Offshore Wind Scour with Sandia's...

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

    Sandia's Environmental Fluid Dynamics Code (SNL---EFDC) Home Renewable Energy Energy News Wind Energy News & Events Computational Modeling & Simulation Quantifying Offshore Wind...

  20. Upcoming Funding Opportunity to Develop and Field Test Wind Energy...

    Energy Savers [EERE]

    and operating wind energy facilities in locations with sensitive bat species. As wind energy continues to grow as a renewable source of energy for communities throughout...

  1. Solar Forecast Improvement Project | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page onYouTube YouTube Note: Since the.pdfBreakingMayDepartment of Energy Ready,SmartEnergyEnergy Resource LibrarySolar

  2. Venture Wind II Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTri Global EnergyUtility Rate HomeVela Jump to:I Wind Farm Jump to:II Wind

  3. Wind Energy Education and Training Programs (Postcard)

    SciTech Connect (OSTI)

    Not Available

    2012-07-01T23:59:59.000Z

    As the United States dramatically expands wind energy deployment, the industry is challenged with developing a skilled workforce to support it. The Wind Powering America website features a map of wind energy education and training program locations at community colleges, universities, and other institutions in the United States. The map includes links to contacts and program details. This postcard is a marketing piece that stakeholders can provide to interested parties; it will guide them to this online resource for wind energy education and training programs episodes.

  4. IEA Wind Energy Annual Report 2000

    SciTech Connect (OSTI)

    Not Available

    2001-05-01T23:59:59.000Z

    The twenty-third IEA Wind Energy Annual Report reviews the progress during 2000 of the activities in the Implementing Agreement for Co-operation in the Research and Development on Wind Turbine Systems under the auspices of the International Energy Agency (IEA). The agreement and its program, which is known as IEA R&D Wind, is a collaborative venture among 19 contracting parties from 17 IEA member countries and the European Commission.

  5. Energy 101: Wind Turbines | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page onYouTube YouTube Note: Since the YouTube|6721 Federal Register /of Energy 3 BTOWebinar Energy 101 Webinar101: Wind

  6. Gary Wind Energy Project | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489InformationFrenchtown, NewG22 Jump to:Garnet Wind Jump to:Gary

  7. Wind Energy Corporation | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTriWildcat 1 Wind Project Jump to:Wilson Hot SpringNevada:

  8. Howard Wind Energy Project | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, search OpenEIHesperia, California:Project Jump to:Would You RebuildlocationsWind

  9. Idaho Wind Energy | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are8COaBulkTransmissionSitingProcess.pdfGetecGtel JumpCounty, Texas:ITCSolid Waste WebpageInformationGroupsWind

  10. Global Wind Energy Council | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are8COaBulkTransmissionSitingProcess.pdfGetec AG Contracting Jump to:Echo,GEF Jump to: navigation,GWTradeGlobalWind

  11. Astraeus Wind Energy Inc | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTriWildcatAntrimArkansasAshford,AsotinAston Solar LLC Jump to:Astraeus Wind

  12. Wind Energy & Manufacturing | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit withTianlinPapers Home Kyoung's picture SubmittedWielandJumpWimberley,Wind 7

  13. Wind Energy Myths | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit withTianlinPapers Home Kyoung's picture SubmittedWielandJumpWimberley,WindMyths

  14. Wind Energy Facilities and Residential Properties: The Effect of Proximity and View on Sales Prices

    E-Print Network [OSTI]

    Hoen, Ben

    2012-01-01T23:59:59.000Z

    and Renewable Energy (Wind & Hydropower TechnologiesU.S. Department of Energy (Wind and Hydropower TechnologiesPublic Perceptions of Wind Energy. Wind Energy, 2004, 8:2,

  15. Wind Energy Facilities and Residential Properties: The Effect of Proximity and View on Sales Prices

    E-Print Network [OSTI]

    Hoen, Ben

    2012-01-01T23:59:59.000Z

    U.S. Department of Energy (Wind and Hydropower Technologiesand Renewable Energy (Wind & Hydropower TechnologiesPublic Perceptions of Wind Energy. Wind Energy, 2004, 8:2,

  16. NREL: Wind Research - Wind Energy Videos

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of Science (SC)Integrated CodesTransparency VisitSilver Toyota Prius being drivenandWebmaster

  17. OpenEI Community - energy data + forecasting

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOfRoseConcernsCompany Oil and GasOff<div class="form-item">

  18. Wind energy global trends: Opportunities and challenges

    SciTech Connect (OSTI)

    Ancona, D.F. [Dept. of Energy, Washington, DC (United States). Wind/Hydro/Ocean Division; Koontz, R.P. [Princeton Economic Research, Inc., Rockville, MD (United States)

    1995-12-31T23:59:59.000Z

    Wind energy is one of the least cost and environmentally attractive new electricity source options for many parts of the world. Because of new wind turbine technology, reduced costs, short installation time, and environmental benefits, countries all over the world are beginning to once again develop one of the world`s oldest energy technologies. A unique set of opportunities and challenges now faces the wind industry and its proponents. This paper discusses the potential and challenges of wind power. The US Department of Energy (DOE) is working closely with industry to develop new, improved wind turbine technology and to support both domestic and international deployment. The US DOE Wind Program is discussed within this context.

  19. Wind energy and SAR wind mapping Charlotte Hasager(2) and merete christiansen(1)

    E-Print Network [OSTI]

    offshore wind farms are operating and more are in construction. Thus the study is focussed on an area is ongoing, and the series of wind maps are used for investigation of offshore wind resources. In wind energy the siting of a wind farm is dependent upon reliable information about the wind climate within the area

  20. 20% Wind Energy By 2030 Meeting The Challenges Proceedings of...

    Energy Savers [EERE]

    from the Wind Manufacturing Workshop: Achieving 20% Wind Energy in the U.S. by 2030, May 2009 U.S. Offshore Wind Manufacturing and Supply Chain Development Offshore Wind Projects...

  1. LED Lighting Forecast | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels DataDepartment of Energy Your Density Isn't YourTransport(FactDepartment ofLetter Report:40PM toLED Lighting Facts LED Lighting Facts

  2. First Wind (Formerly UPC Wind) (Massachusetts) | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489 NoEuropeStrat.pdfInactive JumpFirst Wind (Formerly UPC Wind)

  3. First Wind (Formerly UPC Wind) (Oregon) | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489 NoEuropeStrat.pdfInactive JumpFirst Wind (Formerly UPC Wind)First

  4. Wind Power Partners '94 Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTriWildcat 1 Wind Project Jump to:Wilson Hot SpringNevada:Data0-'92 Wind4

  5. JD Wind 7 Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOf Kilauea Volcano, Hawaii | Wind Farm Jump to: navigation, search7 Wind

  6. JD Wind 8 Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOf Kilauea Volcano, Hawaii | Wind Farm Jump to: navigation, search7 Wind8

  7. JD Wind 9 Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOf Kilauea Volcano, Hawaii | Wind Farm Jump to: navigation, search7 Wind89

  8. Diamond Willow Wind (07) Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489 No revision hasda62829c05bGabbs TypeWinds Wind Farm

  9. Wind Turbine Basics | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level:Energy: Grid Integration Redefining What'sis Taking Over OurThe Iron SpinPrincetonUsingWhat is abig world of tinyWind IndustryWindWindWind»

  10. Wind Power Today: Building a New Energy Future, Wind and Hydropower Technologies Program 2009 (Brochure)

    SciTech Connect (OSTI)

    Not Available

    2009-04-01T23:59:59.000Z

    Wind Power Today is an annual publication that provides an overview of the wind energy research conducted by the U.S. Department of Energy Wind and Hydropower Technologies Program.

  11. Xcel Energy Wind and Biomass Generation Mandate

    Broader source: Energy.gov [DOE]

    Minnesota law (Minn. Stat. 216B.2423) requires Xcel Energy to build or contract for 225 megawatts (MW) of installed wind-energy capacity in the state by December 31, 1998, and to build or...

  12. Wind Energy Technologies - Energy Innovation Portal

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative1 First Use of Energy for All Purposes (Fuel and Nonfuel), 2002; Level: National5Sales for4,645U.S. DOE Office of ScienceandMesa del SolStrengtheningWildfires may contribute more to global warmingGlobal » MayWind

  13. Energy Department Announces New Regional Approach to Wind Energy...

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

    Energy Initiates New Outreach Efforts to Address a Changing Wind Industry This map shows wind potential capacity for turbine hub heights at 140 meters. Mapping the Frontier of New...

  14. Monitoring bat and bird fatalities at the Casselman Wind Energy...

    Energy Savers [EERE]

    Monitoring bat and bird fatalities at the Casselman Wind Energy Center in Pennsylvania Monitoring bat and bird fatalities at the Casselman Wind Energy Center in Pennsylvania...

  15. Deployment Barriers to Distributed Wind Energy: Workshop Report...

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

    Deployment Barriers to Distributed Wind Energy: Workshop Report, October 28, 2010 Deployment Barriers to Distributed Wind Energy: Workshop Report, October 28, 2010 This report...

  16. EA-1852: Cloud County Community College Wind Energy Project,...

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

    2: Cloud County Community College Wind Energy Project, Cloud County, Kansas EA-1852: Cloud County Community College Wind Energy Project, Cloud County, Kansas Summary This EA...

  17. Wind Energy Status and R&D Challenges

    SciTech Connect (OSTI)

    Parsons, B.

    2006-03-01T23:59:59.000Z

    A presentation made to the European Wind Energy Conference in Athens, Greece, February 27--March 2, 2006, on wind energy technology.

  18. Securing Clean, Domestic, Affordable Energy with Wind (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2012-10-01T23:59:59.000Z

    This fact sheet provides a brief description of the Wind Energy Market and describes the U.S. Department of Energy's Wind Program research and development efforts.

  19. Energy Department Releases Report, Evaluates Potential for Wind...

    Energy Savers [EERE]

    Energy Department Releases Report, Evaluates Potential for Wind Power in All 50 States Energy Department Releases Report, Evaluates Potential for Wind Power in All 50 States May...

  20. Fact Sheet: Tehachapi Wind Energy Storage Project (October 2012...

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

    Wind Resource Area because it is one of the largest wind resource areas in the world. Electricity Delivery & Energy Reliability Energy Storage Program Southern California...

  1. Sandia National Laboratories: support wind-energy development

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

    support wind-energy development Sandia Develops Tool to Evaluate Wind-TurbineRadar Impacts On December 3, 2014, in Computational Modeling & Simulation, Energy, News, News &...

  2. Student Competition Prepares the Next Generation of Wind Energy...

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

    Competition Prepares the Next Generation of Wind Energy Entrepreneurs Student Competition Prepares the Next Generation of Wind Energy Entrepreneurs April 11, 2013 - 11:32am Addthis...

  3. Expanding Educational Opportunities for the Wind Energy Workforce...

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

    Expanding Educational Opportunities for the Wind Energy Workforce Expanding Educational Opportunities for the Wind Energy Workforce April 11, 2013 - 12:00am Addthis The University...

  4. WINDExchange Webinar: Wind Energy and Eagles: The Problem, the...

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

    WINDExchange Webinar: Wind Energy and Eagles: The Problem, the Permit, and the Path Forward WINDExchange Webinar: Wind Energy and Eagles: The Problem, the Permit, and the Path...

  5. NREL: Systems Engineering - 2015 Wind Energy Systems Engineering...

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

    Research Systems Engineering Printable Version 2015 Wind Energy Systems Engineering Workshop The third NREL Wind Energy Systems Engineering Workshop took place on the 14th and 15th...

  6. Recovery Act: Wind Energy Consortia between Institutions of Higher...

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

    Recovery Act: Wind Energy Consortia between Institutions of Higher Learning and Industry Recovery Act: Wind Energy Consortia between Institutions of Higher Learning and Industry A...

  7. EIS-0470: Cape Wind Energy Project, Nantucket Sound, Offshore...

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

    June 25, 2014 EIS-0470: Cape Wind Energy Project, Final General Conformity Determination Cape Wind Energy Project, Final General Conformity Determination, June 23, 2014 December...

  8. MESOSCALE MODELLING OF WIND ENERGY OVER NON-HOMOGENEOUS TERRAIN

    E-Print Network [OSTI]

    Pielke, Roger A.

    MESOSCALE MODELLING OF WIND ENERGY OVER NON-HOMOGENEOUS TERRAIN (ReviewArticle) Y. MAHRER.1. OBSERVATIONALAPPROACHES Evaluations of wind energy based on wind observations (usually surface winds) at well, the resolution of the wind energy pattern throughout an extended area by this methodology requires a large number

  9. Ris-R-1479(EN) Satellite information for wind energy

    E-Print Network [OSTI]

    wind power potential. Scatterometer wind data are observed ~ twice per day, whereas SAR onlyRisø-R-1479(EN) Satellite information for wind energy applications Morten Nielsen, Poul Astrup Title: Satellite information for wind energy applications Department: Wind Energy Department Risø-R-1479

  10. Brazos Wind Ranch Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia: EnergyAvignon,BelcherBlundellBowles,EnergyBrazil: EnergyWind Ranch

  11. WP2 IEA Wind Task 26:The Past and Future Cost of Wind Energy

    E-Print Network [OSTI]

    Lantz, Eric

    2014-01-01T23:59:59.000Z

    Energy Efficiency and Renewable Energy. Wiser, R. ; Lantz,Economics of Wind Energy. Renewable and Sustainable EnergyGolden, CO: National Renewable Energy Laboratory. Carbon

  12. Paul S. Veers Wind Energy Technology Department

    E-Print Network [OSTI]

    Ginzel, Matthew

    turbulence simulation, fatigue analysis, reliability, structural dynamics, aeroelastic tailoring of blades journal for progress and applications in wind power. He has a MS in Engineering Mechanics fromPaul S. Veers Wind Energy Technology Department Sandia National Laboratories Thursday, April 8th 3

  13. Wind energy curriculum development at GWU

    SciTech Connect (OSTI)

    Hsu, Stephen M [GWU

    2013-06-08T23:59:59.000Z

    A wind energy curriculum has been developed at the George Washington University, School of Engineering and Applied Science. Surveys of student interest and potential employers expectations were conducted. Wind industry desires a combination of mechanical engineering training with electrical engineering training. The curriculum topics and syllabus were tested in several graduate/undergraduate elective courses. The developed curriculum was then submitted for consideration.

  14. 2011 Cost of Wind Energy Review

    SciTech Connect (OSTI)

    Tegen, S.; Lantz, E.; Hand, M.; Maples, B.; Smith, A.; Schwabe, P.

    2013-03-01T23:59:59.000Z

    This report describes the levelized cost of energy (LCOE) for a typical land-based wind turbine installed in the United States in 2011, as well as the modeled LCOE for a fixed-bottom offshore wind turbine installed in the United States in 2011. Each of the four major components of the LCOE equation are explained in detail, such as installed capital cost, annual energy production, annual operating expenses, and financing, and including sensitivity ranges that show how each component can affect LCOE. These LCOE calculations are used for planning and other purposes by the U.S. Department of Energy's Wind Program.

  15. WindConnect | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown ofNationwideWTEDBird,Wilsonville, Oregon: EnergyWindCooperativesWindWindConnect

  16. Wind Energy Guide for County Commissioners

    SciTech Connect (OSTI)

    Costanti, M.

    2006-10-01T23:59:59.000Z

    One of the key stakeholders associated with economic development are local government officials, who are often required to evaluate and vote on commercial wind energy project permits, as well as to determine and articulate what wind energy benefits accrue to their counties. Often these local officials lack experience with large-scale wind energy and need to make important decisions concerning what may be a complicated and controversial issue. These decisions can be confounded with diverse perspectives from various stakeholders. This project is designed to provide county commissioners, planners, and other local county government officials with a practical overview of information required to successfully implement commercial wind energy projects in their county. The guidebook provides readers with information on the following 13 topics: Brief Wind Energy Overview; Environmental Benefits; Wind Energy Myths and Facts; Economic Development Benefits; Wind Economics; The Development Process; Public Outreach; Siting Issues; Property Tax Incentives; Power System Impacts; Permitting, Zoning, and Siting Processes; Case Studies; and Further Information. For each of the above topics, the guidebook provides an introduction that identifies the topic, why local government should care, a topic snapshot, how the topic will arise, and a list of resources that define and assess the topic.

  17. 2013DvorakandSailor'sEnergy Model Forecasting Accuracy Along

    E-Print Network [OSTI]

    Firestone, Jeremy

    available buoy and tower data hourly from 2006-2010 NOAA National Data Buoy Center buoys (23) and tall. #12;2013DvorakandSailor'sEnergy What Time is Offshore Wind Power Most Useful? Analyzed hourly a REpower 5M, 5 MW power curve, determined capacity factor out to 200-m depth Incredibly strong resource

  18. Wind for Schools: Fostering the Human Talent Supply Chain for a 20% Wind Energy Future (Poster)

    SciTech Connect (OSTI)

    Baring-Gould, I.

    2011-03-01T23:59:59.000Z

    As the United States dramatically expands wind energy deployment, the industry is challenged with developing a skilled workforce and addressing public resistance. Wind Powering America's Wind for Schools project addresses these issues by: 1) Developing Wind Application Centers (WACs) at universities; WAC students assist in implementing school wind turbines and participate in wind courses. 2) Installing small wind turbines at community "host" schools. 3) Implementing teacher training with interactive curricula at each host school.

  19. Aleutian Pribilof Islands Wind Energy Feasibility Study

    SciTech Connect (OSTI)

    Bruce A. Wright

    2012-03-27T23:59:59.000Z

    Under this project, the Aleutian Pribilof Islands Association (APIA) conducted wind feasibility studies for Adak, False Pass, Nikolski, Sand Point and St. George. The DOE funds were also be used to continue APIA's role as project coordinator, to expand the communication network quality between all participants and with other wind interest groups in the state and to provide continued education and training opportunities for regional participants. This DOE project began 09/01/2005. We completed the economic and technical feasibility studies for Adak. These were funded by the Alaska Energy Authority. Both wind and hydro appear to be viable renewable energy options for Adak. In False Pass the wind resource is generally good but the site has high turbulence. This would require special care with turbine selection and operations. False Pass may be more suitable for a tidal project. APIA is funded to complete a False Pass tidal feasibility study in 2012. Nikolski has superb potential for wind power development with Class 7 wind power density, moderate wind shear, bi-directional winds and low turbulence. APIA secured nearly $1M from the United States Department of Agriculture Rural Utilities Service Assistance to Rural Communities with Extremely High Energy Costs to install a 65kW wind turbine. The measured average power density and wind speed at Sand Point measured at 20m (66ft), are 424 W/m2 and 6.7 m/s (14.9 mph) respectively. Two 500kW Vestas turbines were installed and when fully integrated in 2012 are expected to provide a cost effective and clean source of electricity, reduce overall diesel fuel consumption estimated at 130,000 gallons/year and decrease air emissions associated with the consumption of diesel fuel. St. George Island has a Class 7 wind resource, which is superior for wind power development. The current strategy, led by Alaska Energy Authority, is to upgrade the St. George electrical distribution system and power plant. Avian studies in Nikolski and Sand Point have allowed for proper wind turbine siting without killing birds, especially endangered species and bald eagles. APIA continues coordinating and looking for funding opportunities for regional renewable energy projects. An important goal for APIA has been, and will continue to be, to involve community members with renewable energy projects and energy conservation efforts.

  20. WIND ENERGY Wind Energ. 2001; 4:173181 (DOI: 10.1002/we.54)

    E-Print Network [OSTI]

    Pryor, Sara C.

    WIND ENERGY Wind Energ. 2001; 4:173181 (DOI: 10.1002/we.54) Research Article Comparison of Geography, Indiana University, Bloomington, IN 47405, USA R. J. Barthelmie, Department of Wind Energy Wiley & Sons, Ltd. Introduction With the announcement of plans to develop offshore wind energy in many

  1. Pitt County- Wind Energy Systems Ordinance

    Broader source: Energy.gov [DOE]

    The Pitt County Board of Commissioners adopted amendments to the county zoning ordinance in March 2010 which classify wind energy systems as an accessory use and establish siting and permitting...

  2. 2013 Cost of Wind Energy Review

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

    on the Furthering of Competition in Relation to the Establishment of Large Offshore Wind Farms in Denmark. The Danish Ministry of Climate and Energy (ENS). http:www.ens.dk...

  3. Overview of Existing Wind Energy Ordinances

    SciTech Connect (OSTI)

    Oteri, F.

    2008-12-01T23:59:59.000Z

    Due to increased energy demand in the United States, rural communities with limited or no experience with wind energy now have the opportunity to become involved in this industry. Communities with good wind resources may be approached by entities with plans to develop the resource. Although these opportunities can create new revenue in the form of construction jobs and land lease payments, they also create a new responsibility on the part of local governments to ensure that ordinances will be established to aid the development of safe facilities that will be embraced by the community. The purpose of this report is to educate and engage state and local governments, as well as policymakers, about existing large wind energy ordinances. These groups will have a collection of examples to utilize when they attempt to draft a new large wind energy ordinance in a town or county without existing ordinances.

  4. Coastal zone wind energy. Part I. Synoptic and mesoscale controls and distributions of coastal wind energy

    SciTech Connect (OSTI)

    Garstang, M.; Nnaji, S.; Pielke, R.A.; Gusdorf, J.; Lindsey, C.; Snow, J.W.

    1980-03-01T23:59:59.000Z

    This report describes a method of determining coastal wind energy resources. Climatological data and a mesoscale numerical model are used to delineate the available wind energy along the Atlantic and Gulf coasts of the United States. It is found that the spatial distribution of this energy is dependent on the locations of the observing sites in relation to the major synoptic weather features as well as the particular orientation of the coastline with respect to the large-scale wind.

  5. Sandia National Laboratories: wind energy

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

    in Matlab which simplifies the process of creating a three-dimensional model of a wind turbine blade. The graphical, user-friendly tool manages all blade information including...

  6. Model Wind Energy Facility Ordinance

    Broader source: Energy.gov [DOE]

    Note: This model ordinance was designed to provide guidance to local governments that wish to develop their own siting rules for wind turbines. While it was developed as part of a cooperative...

  7. Design of wind farm layout for maximum wind energy capture Andrew Kusiak*, Zhe Song

    E-Print Network [OSTI]

    Kusiak, Andrew

    Design of wind farm layout for maximum wind energy capture Andrew Kusiak*, Zhe Song Intelligent Accepted 24 August 2009 Available online 22 September 2009 Keywords: Wind farm Wind turbine Layout design Optimization Evolutionary algorithms Operations research a b s t r a c t Wind is one of the most promising

  8. Camp Springs Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty EditCalifornia:Power LPInformation 8thCalwind II CEC WindCamelot1Q08) WindWind

  9. Wind Power in China | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualProperty Edit withTianlinPapers Home Kyoung's pictureWind Power Energia Jump to:Wind PowerWind

  10. Dillon Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489 No revision hasda62829c05bGabbs TypeWinds WindDilconWind Farm

  11. Shenyang Huachuang Wind Energy Corporation HCWE aka China Creative Wind

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2,AUDITCalifornia Sector: WindRiegotecSeaScape

  12. Venture Wind I Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTri Global EnergyUtility Rate HomeVela Jump to:I Wind Farm Jump to:

  13. Walnut Wind Project Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-fTri Global EnergyUtilityInformation Waiver ofAcquisitions JumpWind

  14. Stetson Wind Expansion Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-f < RAPID‎SolarCityInformation GlassOpen EnergyStetson Wind

  15. Wind Energy Workforce Development: Engineering, Science, & Technology

    SciTech Connect (OSTI)

    Lesieutre, George A.; Stewart, Susan W.; Bridgen, Marc

    2013-03-29T23:59:59.000Z

    Broadly, this project involved the development and delivery of a new curriculum in wind energy engineering at the Pennsylvania State University; this includes enhancement of the Renewable Energy program at the Pennsylvania College of Technology. The new curricula at Penn State includes addition of wind energy-focused material in more than five existing courses in aerospace engineering, mechanical engineering, engineering science and mechanics and energy engineering, as well as three new online graduate courses. The online graduate courses represent a stand-alone Graduate Certificate in Wind Energy, and provide the core of a Wind Energy Option in an online intercollege professional Masters degree in Renewable Energy and Sustainability Systems. The Pennsylvania College of Technology erected a 10 kilowatt Xzeres wind turbine that is dedicated to educating the renewable energy workforce. The entire construction process was incorporated into the Renewable Energy A.A.S. degree program, the Building Science and Sustainable Design B.S. program, and other construction-related coursework throughout the School of Construction and Design Technologies. Follow-on outcomes include additional non-credit opportunities as well as secondary school career readiness events, community outreach activities, and public awareness postings.

  16. Tools supporting wind energy trade in deregulated markets

    E-Print Network [OSTI]

    Tools supporting wind energy trade in deregulated markets ?? Ulfar Linnet Kongens Lyngby 2005 IMM.imm.dtu.dk IMM­THESIS: ISSN 0909­3192 #12; Abstract A large share of the wind energy produced in Scandinavia in a fine, called regulation cost. As wind energy comes from an uncontrollable energy source ­ the wind

  17. Nancy Rader, Executive Director California Wind Energy Association

    E-Print Network [OSTI]

    Nancy Rader, Executive Director California Wind Energy Association Improving Methods for Estimating Fatality of Birds and Bats at Wind Energy Facilities California Wind Energy Association Public Webinar Wind Energy Development 2008 CEC Research "Roadmap" on Impact Assessment Methods 2008 CEC PIER RFP 2009

  18. Tools supporting wind energy trade in deregulated markets

    E-Print Network [OSTI]

    Tools supporting wind energy trade in deregulated markets ´Ulfar Linnet Kongens Lyngby 2005 IMM.imm.dtu.dk IMM-THESIS: ISSN 0909-3192 #12;Abstract A large share of the wind energy produced in Scandinavia in a fine, called regulation cost. As wind energy comes from an uncontrollable energy source - the wind

  19. Forecasting the Market Penetration of Energy Conservation Technologies: The Decision Criteria for Choosing a Forecasting Model

    E-Print Network [OSTI]

    Lang, K.

    1982-01-01T23:59:59.000Z

    capital requirements and research and development programs in the alum inum industry. : CONCLUSIONS Forecasting the use of conservation techndlo gies with a market penetration model provides la more accountable method of projecting aggrega...

  20. High Energy Studies of Pulsar Wind Nebulae

    E-Print Network [OSTI]

    Patrick Slane

    2008-11-12T23:59:59.000Z

    The extended nebulae formed as pulsar winds expand into their surroundings provide information about the composition of the winds, the injection history from the host pulsar, and the material into which the nebulae are expanding. Observations from across the electromagnetic spectrum provide constraints on the evolution of the nebulae, the density and composition of the surrounding ejecta, the geometry of the systems, the formation of jets, and the maximum energy of the particles in the nebulae. Here I provide a broad overview of the structure of pulsar wind nebulae, with specific examples that demonstrate our ability to constrain the above parameters. The association of pulsar wind nebulae with extended sources of very high energy gamma-ray emission are investigated, along with constraints on the nature of such high energy emission.

  1. Sandia Energy - Offshore Wind RD&D: Large Offshore Rotor Development

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

    Offshore Rotor Development Home Stationary Power Energy Conversion Efficiency Wind Energy Offshore Wind Offshore Wind RD&D: Large Offshore Rotor Development Offshore Wind RD&D:...

  2. Sandia Energy - Offshore Wind RD&D: Large Offshore Rotor Development

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

    Offshore Wind RD&D: Large Offshore Rotor Development Home Stationary Power Energy Conversion Efficiency Wind Energy Offshore Wind Offshore Wind RD&D: Large Offshore Rotor...

  3. Utilization of Wind Energy at High Altitude

    E-Print Network [OSTI]

    Alexander Bolonkin

    2007-01-10T23:59:59.000Z

    Ground based, wind energy extraction systems have reached their maximum capability. The limitations of current designs are: wind instability, high cost of installations, and small power output of a single unit. The wind energy industry needs of revolutionary ideas to increase the capabilities of wind installations. This article suggests a revolutionary innovation which produces a dramatic increase in power per unit and is independent of prevailing weather and at a lower cost per unit of energy extracted. The main innovation consists of large free-flying air rotors positioned at high altitude for power and air stream stability, and an energy cable transmission system between the air rotor and a ground based electric generator. The air rotor system flies at high altitude up to 14 km. A stability and control is provided and systems enable the changing of altitude. This article includes six examples having a high unit power output (up to 100 MW). The proposed examples provide the following main advantages: 1. Large power production capacity per unit - up to 5,000-10,000 times more than conventional ground-based rotor designs; 2. The rotor operates at high altitude of 1-14 km, where the wind flow is strong and steady; 3. Installation cost per unit energy is low. 4. The installation is environmentally friendly (no propeller noise). -- * Presented in International Energy Conversion Engineering Conference at Providence., RI, Aug. 16-19. 2004. AIAA-2004-5705. USA. Keyword: wind energy, cable energy transmission, utilization of wind energy at high altitude, air rotor, windmills, Bolonkin.

  4. WP2 IEA Wind Task 26:The Past and Future Cost of Wind Energy

    E-Print Network [OSTI]

    Lantz, Eric

    2014-01-01T23:59:59.000Z

    2011b). Development in LCOE for Wind Turbines in Denmark.levelized cost of energy (LCOE) analyses are shown in Tablethe levelized cost of energy (LCOE) for onshore wind energy.

  5. Forecasting the Hourly Ontario Energy Price by Multivariate Adaptive Regression Splines

    E-Print Network [OSTI]

    Cañizares, Claudio A.

    1 Forecasting the Hourly Ontario Energy Price by Multivariate Adaptive Regression Splines H. In this paper, the MARS technique is applied to forecast the hourly Ontario energy price (HOEP). The MARS models values of the latest pre- dispatch price and demand information, made available by the Ontario

  6. Wind-To-Hydrogen Energy Pilot Project

    SciTech Connect (OSTI)

    Ron Rebenitsch; Randall Bush; Allen Boushee; Brad G. Stevens; Kirk D. Williams; Jeremy Woeste; Ronda Peters; Keith Bennett

    2009-04-24T23:59:59.000Z

    WIND-TO-HYDROGEN ENERGY PILOT PROJECT: BASIN ELECTRIC POWER COOPERATIVE In an effort to address the hurdles of wind-generated electricity (specifically wind's intermittency and transmission capacity limitations) and support development of electrolysis technology, Basin Electric Power Cooperative (BEPC) conducted a research project involving a wind-to-hydrogen system. Through this effort, BEPC, with the support of the Energy & Environmental Research Center at the University of North Dakota, evaluated the feasibility of dynamically scheduling wind energy to power an electrolysis-based hydrogen production system. The goal of this project was to research the application of hydrogen production from wind energy, allowing for continued wind energy development in remote wind-rich areas and mitigating the necessity for electrical transmission expansion. Prior to expending significant funding on equipment and site development, a feasibility study was performed. The primary objective of the feasibility study was to provide BEPC and The U.S. Department of Energy (DOE) with sufficient information to make a determination whether or not to proceed with Phase II of the project, which was equipment procurement, installation, and operation. Four modes of operation were considered in the feasibility report to evaluate technical and economic merits. Mode 1 - scaled wind, Mode 2 - scaled wind with off-peak, Mode 3 - full wind, and Mode 4 - full wind with off-peak In summary, the feasibility report, completed on August 11, 2005, found that the proposed hydrogen production system would produce between 8000 and 20,000 kg of hydrogen annually depending on the mode of operation. This estimate was based on actual wind energy production from one of the North Dakota (ND) wind farms of which BEPC is the electrical off-taker. The cost of the hydrogen produced ranged from $20 to $10 per kg (depending on the mode of operation). The economic sensitivity analysis performed as part of the feasibility study showed that several factors can greatly affect, both positively and negatively, the "per kg" cost of hydrogen. After a September 15, 2005, meeting to evaluate the advisability of funding Phase II of the project DOE concurred with BEPC that Phase I results did warrant a "go" recommendation to proceed with Phase II activities. The hydrogen production system was built by Hydrogenics and consisted of several main components: hydrogen production system, gas control panel, hydrogen storage assembly and hydrogen-fueling dispenser The hydrogen production system utilizes a bipolar alkaline electrolyzer nominally capable of producing 30 Nm3/h (2.7 kg/h). The hydrogen is compressed to 6000 psi and delivered to an on-site three-bank cascading storage assembly with 80 kg of storage capacity. Vehicle fueling is made possible through a Hydrogenics-provided gas control panel and dispenser able to fuel vehicles to 5000 psi. A key component of this project was the development of a dynamic scheduling system to control the wind energy's variable output to the electrolyzer cell stacks. The dynamic scheduling system received an output signal from the wind farm, processed this signal based on the operational mode, and dispatched the appropriate signal to the electrolyzer cell stacks. For the study BEPC chose to utilize output from the Wilton wind farm located in central ND. Site design was performed from May 2006 through August 2006. Site construction activities were from August to November 2006 which involved earthwork, infrastructure installation, and concrete slab construction. From April - October 2007, the system components were installed and connected. Beginning in November 2007, the system was operated in a start-up/shakedown mode. Because of numerous issues, the start-up/shakedown period essentially lasted until the end of January 2008, at which time a site acceptance test was performed. Official system operation began on February 14, 2008, and continued through the end of December 2008. Several issues continued to prevent consistent operation, resulting in operation o

  7. Ris Energy Report 5 Wind 2 In the past 20 years wind energy has proved itself as a

    E-Print Network [OSTI]

    Ris Energy Report 5 Wind 2 6.1 Status In the past 20 years wind energy has proved itself all these achievements, wind energy remains on the fringes of power generation. For people working ignorance and emo- tional opposition. Wind energy is far from having been proved to lay people, large

  8. Expedited Permitting of Grid-Scale Wind Energy Development (Maine)

    Broader source: Energy.gov [DOE]

    Maine's Expedited Permitting of Grid-Scale Wind Energy Development statue provides an expedited permitting pathway for proposed wind developments in certain designated locations, known as expedited...

  9. Timken Producing Parts for Wind Turbines | Department of Energy

    Energy Savers [EERE]

    at businesses around the state. | File photo Concrete Company Aims Higher for More Wind Energy Boston's Wind Technology Testing Center, funded in part with Recovery Act...

  10. Next-Generation Wind Technology | Department of Energy

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

    and reliability of next-generation wind technologies while lowering the cost of wind energy. The program's research efforts have helped to increase the average capacity...

  11. Assessment of Offshore Wind Energy Resources for the United States...

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

    Offshore Wind Energy Resources for the United States This report summarizes the offshore wind resource potential for the contiguous United States and Hawaii as of May 2009. The...

  12. RidgeWind Ltd | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2,AUDITCalifornia Sector: Wind energyInformationRenovaliaRidgeWind Ltd

  13. Wind Research and Development | Department of Energy

    Energy Savers [EERE]

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directed off Energy.gov. Are you sureReportsofDepartmentSeries |Attacksof EnergyWhenWindWind Research and

  14. Cielo Wind Power | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2,AUDIT REPORTEnergy Offshore Place:Wind EnergyCielo Wind Power Jump to:

  15. Clear Wind Renewable Power | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2,AUDIT REPORTEnergy Offshore Place:Wind EnergyCielo Wind PowerWaterPower

  16. Craig Wind Farm Ltd | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2,AUDIT REPORTEnergy Offshore Place:WindOilCowal Wind Energy Ltd Jump

  17. Wind Energy in Indian Country: Turning to Wind for the Seventh Generation

    E-Print Network [OSTI]

    Kammen, Daniel M.

    Wind Energy in Indian Country: Turning to Wind for the Seventh Generation by Andrew D. Mills: ___________________________________________ Jane Stahlhut Date #12;Wind Energy in Indian Country A.D. Mills Abstract - ii - Abstract Utility-scale wind projects are increasingly being developed in rural areas of the United States. In the West

  18. Portsmouth Abbey School Wind Turbine Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation,Pillar Group BV Jump to: navigation, searchPocatelloIII WindPort

  19. JD Wind 1 Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOf Kilauea Volcano, Hawaii | Wind Farm Jump to: navigation, search Name JD

  20. JD Wind 10 Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOf Kilauea Volcano, Hawaii | Wind Farm Jump to: navigation, search Name JD0

  1. JD Wind 11 Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOf Kilauea Volcano, Hawaii | Wind Farm Jump to: navigation, search Name

  2. JD Wind 2 Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOf Kilauea Volcano, Hawaii | Wind Farm Jump to: navigation, search Name2

  3. JD Wind 3 Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOf Kilauea Volcano, Hawaii | Wind Farm Jump to: navigation, search Name23

  4. JD Wind 4 Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOf Kilauea Volcano, Hawaii | Wind Farm Jump to: navigation, search Name234

  5. JD Wind 5 Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOf Kilauea Volcano, Hawaii | Wind Farm Jump to: navigation, search Name2345

  6. JD Wind 6 Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOf Kilauea Volcano, Hawaii | Wind Farm Jump to: navigation, search

  7. North Dakota Wind I Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOfRoseConcerns Jumpsource History View New Pages RecentI Wind Farm Facility

  8. North Dakota Wind II Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOfRoseConcerns Jumpsource History View New Pages RecentI Wind Farm

  9. Solano Wind Project Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to:Ezfeedflag JumpID-f < RAPID‎ |RippeyInformationSoda Springs,SolaicxSolanoWind Farm

  10. Metro Wind LLC Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOfRose Bend <StevensMcClellan,II JumpMepsolarMesilla,MethanetoMetricWind

  11. Mountain Wind I Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOfRose BendMiasole IncMinutemanVistaZephyr)Mountain Air JumpIV JumpI Wind

  12. Mountain Wind II Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, searchOfRose BendMiasole IncMinutemanVistaZephyr)Mountain Air JumpIV JumpI WindII

  13. East Winds (formerly Altech III) Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnualPropertyd8c-a9ae-f8521cbb8489 No revision| Open Jump to:(RES-AEI)CoastSoda Lake GeothermalWinds

  14. Strengthening America's Energy Security with Offshore Wind (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2012-02-01T23:59:59.000Z

    This fact sheet describes the current state of the offshore wind industry in the United States and the offshore wind research and development activities conducted the U.S. Department of Energy Wind and Water Power Program.

  15. Articles about Wind Siting | Department of Energy

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

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page on Google Bookmark EERE: Alternative Fuels Data Center Home Page on Delicious Rank EERE: Alternative Fuels DataEnergyDepartmentWind Siting Articles about Wind Siting RSS Below are

  16. 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

  17. Green Power Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are beingZealand Jump to: navigation, search OpenEI ReferenceJump to: navigation,II WindAirplaneGreenEnergy |Power Wind

  18. Wind Works LLC | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov YouKizildere IRaghuraji Agro IndustriesTown ofNationwideWTEDBird,Wilsonville, Oregon: EnergyWindCooperativesWind Works LLC

  19. Marquiss Wind Power | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2,AUDIT REPORTEnergyFarmsPower CoLongxing WindMaoming Zhong ao Wind

  20. Ohio Green Wind, LLC | Open Energy Information

    Open Energy Info (EERE)

    AFDC Printable Version Share this resource Send a link to EERE: Alternative Fuels Data Center Home Page to someone by E-mail Share EERE: Alternative Fuels Data Center Home Page on Facebook Tweet about EERE: Alternative Fuels Data Center Home Page on Twitter Bookmark EERE: Alternative Fuels Data Center Home Page onYou are now leaving Energy.gov You are now leaving Energy.gov You are being directedAnnual Siteof Energy 2,AUDIT REPORTEnergyFarmsPowerKaitianOstsee Wind AG Jump to:Ohio Green Wind,