Sample records for wind power forecasting

  1. 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

  2. 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...

  3. 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...

  4. 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

  5. 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

  6. 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.

  7. 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...

  8. New Concepts in Wind Power Forecasting Models

    E-Print Network [OSTI]

    Kemner, Ken

    New Concepts in Wind Power Forecasting Models Vladimiro Miranda, Ricardo Bessa, João 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

  9. 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

  10. 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.

  11. 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

  12. 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.

  13. 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.

  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. 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

  16. 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

  17. 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

  18. 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, Université 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 J´er´emie Juban jeremie.juban@ensmp.fr; georges.kariniotakis@ensmp.fr Abstract Short-term wind power forecasting tools

  19. 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.

  20. 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

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

    SciTech Connect (OSTI)

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

    2012-07-01T23:59:59.000Z

    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.

  2. 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.

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. 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.

  8. 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.

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université 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

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université 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

  11. 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 ($e_{\\zeta}$).

  12. 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 ($e_{\\zeta}$).

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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

  19. 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

  20. 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.

  1. 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.

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université 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

  3. Offshore Wind Power USA

    Broader source: Energy.gov [DOE]

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

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 Evaluation of Advanced Wind Power Forecasting Models ­ Results of the Anemos Project I. Martí1.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

  5. 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.

  6. 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.

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université 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

  8. 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

  9. 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

  10. 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

  11. 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

  12. 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.

  13. 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, Université 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

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université 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

  15. 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, Université 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

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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 ...

  1. 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.

  2. 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

  3. 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

  4. PSO2004/FU5766 Improved wind power prediction

    E-Print Network [OSTI]

    PSO2004/FU5766 Improved wind power prediction Optimal combined wind power forecasts using exogenous prediction can be accomplished. The application of combining wind power forecasts for certain wind power

  5. 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

  6. 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.

  7. 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

  8. 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...

  9. 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...

  10. PSO2004/FU5766 Improved wind power prediction

    E-Print Network [OSTI]

    PSO2004/FU5766 Improved wind power prediction Spatio-temporal modelling of short-term wind power of wind power generation in power systems. The quality of the forecast is very important, and a reliable estimate of the uncertainty of the forecast is known to be essential. Today the forecasts of wind power

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université 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

  12. 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.

  13. 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.

  14. Reference wind farm selection for regional wind power prediction models

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    1 Reference wind farm selection for regional wind power prediction models Nils Siebert George.siebert@ensmp.fr, georges.kariniotakis@ensmp.fr Abstract Short-term wind power forecasting is recognized today as a major requirement for a secure and economic integration of wind generation in power systems. This paper deals

  15. 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...

  16. Wind power and Wind power and

    E-Print Network [OSTI]

    Wind power and the CDM #12; Wind power and the CDM Emerging practices in developing wind power 2005 Jyoti P. Painuly, Niels-Erik Clausen, Jørgen Fenhann, Sami Kamel and Romeo Pacudan #12; WIND POWER AND THE CDM Emerging practices in developing wind power projects for the Clean Development Mechanism Energy

  17. 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.

  18. 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

  19. 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)

  20. Automatic selection of tuning parameters in wind power prediction

    E-Print Network [OSTI]

    Automatic selection of tuning parameters in wind power prediction Lasse Engbo Christiansen (lec Report number: IMM-Technical Report-2007-12 Project title: Intelligent wind power prediction systems PSO The wind power forecasting system developed at DTU - the Wind Power Prediction Tool (WPPT) - predicts

  1. Wind Power

    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 SoarsWind

  2. Wind Power

    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 >Internship Program TheSiteEurekaWeekly UserWhat's New Today aboutWind

  3. Wind Power Today

    SciTech Connect (OSTI)

    Not Available

    2006-05-01T23:59:59.000Z

    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.

  4. Wind Power Today

    SciTech Connect (OSTI)

    Not Available

    2007-05-01T23:59:59.000Z

    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.

  5. 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...

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université 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

  7. Residential Wind Power

    E-Print Network [OSTI]

    Willis, Gary

    2011-12-16T23:59:59.000Z

    This research study will explore the use of residential wind power and associated engineering and environmental issues. There is various wind power generating devices available to the consumer. The study will discuss the dependencies of human...

  8. EA-1726: Kahuku Wind Power, LLC Wind Power Generation Facility...

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

    6: Kahuku Wind Power, LLC Wind Power Generation Facility, O'ahu, HI EA-1726: Kahuku Wind Power, LLC Wind Power Generation Facility, O'ahu, HI May 3, 2010 EA-1726: Final...

  9. 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

  10. ANEMOS: Development of a Next Generation Wind Power Forecasting System for the Large-Scale Integration of Onshore &

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    -NTUA, Greece. * georges.kariniotakis@ensmp.fr, tel:+33-493957501, Ecole des Mines de Paris, Centre d'Energetique 6% to 12% by 2010. Under this target, the problem of integration of RES and namely of wind energy

  11. 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...

  12. Benefits of Stochastic Scheduling for Power Systems with Significant Installed Wind Power

    E-Print Network [OSTI]

    Benefits of Stochastic Scheduling for Power Systems with Significant Installed Wind Power Aidan Abstract-- Wind energy on a power system alters the unit commitment and dispatch problem, as it adds generation, Power system eco- nomics, Power generation dispatch, Unit Commitment, Wind Forecasting. I

  13. Wind Power Outlook 2004

    SciTech Connect (OSTI)

    anon.

    2004-01-01T23:59:59.000Z

    The brochure, expected to be updated annually, provides the American Wind Energy Association's (AWAE's) up-to-date assessment of the wind industry. It provides a summary of the state of wind power in the U.S., including the challenges and opportunities facing the industry. It provides summary information on the growth of the industry, policy-related factors such as the federal wind energy production tax credit status, comparisons with natural gas, and public views on wind energy.

  14. Wind power today

    SciTech Connect (OSTI)

    NONE

    1998-04-01T23:59:59.000Z

    This publication highlights initiatives of the US DOE`s Wind Energy Program. 1997 yearly activities are also very briefly summarized. The first article describes a 6-megawatt wind power plant installed in Vermont. Another article summarizes technical advances in wind turbine technology, and describes next-generation utility and small wind turbines in the planning stages. A village power project in Alaska using three 50-kilowatt turbines is described. Very brief summaries of the Federal Wind Energy Program and the National Wind Technology Center are also included in the publication.

  15. 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

  16. 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

  17. Enabling Wind Power Nationwide

    Office of Environmental Management (EM)

    including natural gas, and competing renewable power resources such as solar photovoltaics. Figure 4-3. Wind turbine hub height trends in Germany from 2007 to 2014 Source:...

  18. Wind Power Career Chat

    SciTech Connect (OSTI)

    Not Available

    2011-01-01T23:59:59.000Z

    This document will teach students about careers in the wind energy industry. Wind energy, both land-based and offshore, is expected to provide thousands of new jobs in the next several decades. Wind energy companies are growing rapidly to meet America's demand for clean, renewable, and domestic energy. These companies need skilled professionals. Wind power careers will require educated people from a variety of areas. Trained and qualified workers manufacture, construct, operate, and manage wind energy facilities. The nation will also need skilled researchers, scientists, and engineers to plan and develop the next generation of wind energy technologies.

  19. 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...

  20. A quick guide to wind power forecating : state-of-the-art 2009.

    SciTech Connect (OSTI)

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

    2009-11-20T23:59:59.000Z

    This document contains a summary of the main findings from our full report entitled 'Wind Power Forecasting: State-of-the-Art 2009'. The aims of this document are to provide guidelines and a quick overview of the current state-of-the-art in wind power forecasting (WPF) and to point out lines of research in the future development of forecasting systems.

  1. 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

  2. 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

  3. Validation of Power Output for the WIND Toolkit

    SciTech Connect (OSTI)

    King, J.; Clifton, A.; Hodge, B. M.

    2014-09-01T23:59:59.000Z

    Renewable energy integration studies require wind data sets of high quality with realistic representations of the variability, ramping characteristics, and forecast performance for current wind power plants. The Wind Integration National Data Set (WIND) Toolkit is meant to be an update for and expansion of the original data sets created for the weather years from 2004 through 2006 during the Western Wind and Solar Integration Study and the Eastern Wind Integration Study. The WIND Toolkit expands these data sets to include the entire continental United States, increasing the total number of sites represented, and it includes the weather years from 2007 through 2012. In addition, the WIND Toolkit has a finer resolution for both the temporal and geographic dimensions. Three separate data sets will be created: a meteorological data set, a wind power data set, and a forecast data set. This report describes the validation of the wind power data set.

  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. Wind Power Today, 2010, Wind and Water Power Program (WWPP)

    SciTech Connect (OSTI)

    Not Available

    2010-05-01T23:59:59.000Z

    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 Water Power Program.

  6. 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...

  7. 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...

  8. 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.

  9. Proceedings Nordic Wind Power Conference

    E-Print Network [OSTI]

    Estimation of Possible Power for Wind Plant Control Power Fluctuations from Offshore Wind Farms; Model Validation System grounding of wind farm medium voltage cable grids Faults in the Collection Grid of Offshore systems of wind turbines and wind farms. NWPC presents the newest research results related to technical

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

    SciTech Connect (OSTI)

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

    2013-10-01T23:59:59.000Z

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

  11. Sinomatech Wind Power Blade aka Sinoma Science Technology Wind...

    Open Energy Info (EERE)

    Sinomatech Wind Power Blade aka Sinoma Science Technology Wind Turbine Blade Co Ltd Jump to: navigation, search Name: Sinomatech Wind Power Blade (aka Sinoma Science & Technology...

  12. EWEC'07 Conference, 7-10 May 2007, Milan, Italy. POW'WOW Virtual Laboratory for Wind Power

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    EWEC'07 Conference, 7-10 May 2007, Milan, Italy. 1 POW'WOW Virtual Laboratory for Wind Power for the short-term prediction of wind power production. The relevant and common forecast length of these tools purposes. A state of the art on wind power forecasting has been published by Giebel et al [1]. On the other

  13. A NOVEL METHODOLOGY FOR COMPARISON OF DIFFERENT WIND POWER RAMP CHARACTERIZATION APPROACHES

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    A NOVEL METHODOLOGY FOR COMPARISON OF DIFFERENT WIND POWER RAMP CHARACTERIZATION APPROACHES Arthur.bossavy@mines-paristech.fr Telephone : +33.4.93.95.74.80, Fax : +33.4.93.95.75.35 ABSTRACT Wind power forecasting is recognized as a means to facilitate large scale wind power integration into power systems. Recently, focus has been

  14. SHORT TERM PREDICTIONS FOR THE POWER OUTPUT OF ENSEMBLES OF WIND TURBINES AND PV-GENERATORS

    E-Print Network [OSTI]

    Heinemann, Detlev

    SHORT TERM PREDICTIONS FOR THE POWER OUTPUT OF ENSEMBLES OF WIND TURBINES AND PV-GENERATORS Hans the state of the art of power predictios for wind and solar power plants.with a time horizon of several market there is a need for a forecast of the power production of wind and solar generators with time

  15. Abstract--This paper discusses using the battery energy storage system (BESS) to mitigate wind power intermittency, so

    E-Print Network [OSTI]

    Peng, Huei

    to compensate for wind power forecast errors and minimize operation costs to the wind farm owner. A ramp rate wholesale market and grid operators, in that wind power outputs are intermittent, which may increase demands power intermittency, so that wind power can be dispatchable on an hourly basis like fossil fuel power

  16. 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.

  17. 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

  18. 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

  19. Wind Powering America Webinar Series (Postcard), Wind Powering America (WPA)

    SciTech Connect (OSTI)

    Not Available

    2012-02-01T23:59:59.000Z

    Wind Powering America offers a free monthly webinar series that provides expert information on today?s key wind energy topics. This postcard is an outreach tool that provides a brief description of the webinars as well as the URL.

  20. Wind Powering America Podcasts, Wind Powering America (WPA)

    SciTech Connect (OSTI)

    Not Available

    2012-04-01T23:59:59.000Z

    Wind Powering America and the National Association of Farm Broadcasters produce a series of radio interviews featuring experts discussing wind energy topics. The interviews are aimed at a rural stakeholder audience and are available as podcasts. On the Wind Powering America website, you can access past interviews on topics such as: Keys to Local Wind Energy Development Success, What to Know about Installing a Wind Energy System on Your Farm, and Wind Energy Development Can Revitalize Rural America. This postcard is a marketing piece that stakeholders can provide to interested parties; it will guide them to this online resource for podcast episodes.

  1. 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

  2. Enabling Wind Power Nationwide

    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 BTO PeerDepartment ofWind Power

  3. Wind Power Link

    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 Links These other

  4. Wind Power Outreach Campaign

    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 Links These other

  5. Wind Power Software

    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 Links These

  6. Power-Capacity and Ramp-Capability Reserves for Wind Integration ...

    E-Print Network [OSTI]

    German Morales-España

    2014-07-08T23:59:59.000Z

    Jul 8, 2014 ... These power and ramp requirements can be obtained from wind forecast information. ... power-trajectories instead of the traditional energy-blocks and takes ... The operation cost comparison is made through 5-min economic ...

  7. Kahuku Wind Power (First Wind) | Department of Energy

    Office of Environmental Management (EM)

    The project employs the integration of Clipper LibertyTM wind turbine generators and a control system to more efficiently integrate wind power with the utility's power grid....

  8. Active Power Control from Wind Power (Presentation)

    SciTech Connect (OSTI)

    Ela, E.; Brooks, D.

    2011-04-01T23:59:59.000Z

    In order to keep the electricity grid stable and the lights on, the power system relies on certain responses from its generating fleet. This presentation evaluates the potential for wind turbines and wind power plants to provide these services and assist the grid during critical times.

  9. Voluntary Green Power Market Forecast through 2015

    SciTech Connect (OSTI)

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

    2010-05-01T23:59:59.000Z

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

  10. Wind power outlook 2006

    SciTech Connect (OSTI)

    anon.

    2006-04-15T23:59:59.000Z

    This annual brochure provides the American Wind Energy Association's up-to-date assessment of the wind industry in the United States. This 2006 general assessment shows positive signs of growth, use and acceptance of wind energy as a vital component of the U.S. energy mix.

  11. 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.

  12. Sixth Northwest Conservation and Electric Power Plan Appendix B: Economic Forecast

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Appendix B: Economic Forecast Role of the Economic Forecast..................................................................................................................................... 2 Economic Growth Assumptions

  13. Enabling Wind Power Nationwide

    Office of Environmental Management (EM)

    hub heights of 110 meters (m) (which are already in wide commercial deployment in Germany and other European countries), the technical potential for wind deployment is...

  14. 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.

  15. Wind Power Systems 1.0 Overview

    E-Print Network [OSTI]

    Ding, Yu

    Wind Power Systems 1.0 Overview 2.0 Simulation model for wind farm operation 3.0 Research topics #12;Contents 1. Overview of wind power systems 2. Simulation model of wind farm operations 3. Research area of wind power systems 3.0 Overview 3.1 Economic dispatch 3.2 Correlation analysis 3.3 Energy

  16. System-wide emissions implications of increased wind power penetration.

    SciTech Connect (OSTI)

    Valentino, L.; Valenzuela, V.; Botterud, A.; Zhou, Z.; Conzelmann, G. (Decision and Information Sciences); (Univ. of Illinois, Champaign/Urbana); (Georgia Institute of Technology)

    2012-01-01T23:59:59.000Z

    This paper discusses the environmental effects of incorporating wind energy into the electric power system. We present a detailed emissions analysis based on comprehensive modeling of power system operations with unit commitment and economic dispatch for different wind penetration levels. First, by minimizing cost, the unit commitment model decides which thermal power plants will be utilized based on a wind power forecast, and then, the economic dispatch model dictates the level of production for each unit as a function of the realized wind power generation. Finally, knowing the power production from each power plant, the emissions are calculated. The emissions model incorporates the effects of both cycling and start-ups of thermal power plants in analyzing emissions from an electric power system with increasing levels of wind power. Our results for the power system in the state of Illinois show significant emissions effects from increased cycling and particularly start-ups of thermal power plants. However, we conclude that as the wind power penetration increases, pollutant emissions decrease overall due to the replacement of fossil fuels.

  17. 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...

  18. Wind Power Overview Windpoweristhefastestgrowingformofrenewableenergy,withpoten-

    E-Print Network [OSTI]

    Wind Power Overview · Windpoweristhefastestgrowingformofrenewableenergy Offshore Wind Power for Florida? · AveragehouseholdelectricitycostsforFloridaare expectedtoincreaseby4.7%($7.50/month)each yearoverthenextdecade2 . · Offshore winds are typically stronger and more

  19. Wind Farm Monitoring at Lake Benton II Wind Power Project - Equipment Only: Cooperative Research and Development Final Report, CRADA Number CRD-08-275

    SciTech Connect (OSTI)

    Gevorgian, V.

    2014-06-01T23:59:59.000Z

    Long-term, high-resolution wind turbine and wind power plant output data are important to assess the impact of wind power on grid operations and to derive meaningful statistics for better understanding of the variability nature of wind power. These data are used for many research and analyses activities consistent with the Wind Program mission: Establish a database of long-term wind power similar to other long-term renewable energy resource databases (e.g. solar irradiance and hydrology); produce meaningful statistics about long-term variation of wind power, spatial and temporal diversity of wind power, and the correlation of wind power, other renewable energy resources, and utility load; provide high quality, realistic wind power output data for system operations impact studies and wind plant and forecasting model validation.

  20. Wind Power in Norway -Innovation strategy -

    E-Print Network [OSTI]

    Müller, Ralf R.

    Wind Power in Norway - Innovation strategy - Liana Müller #12;2 Introduction The existing energy and, at the same time, not to irreversibly damage the life on Earth. The use of waterpower, wind power, the growth of the wind power industry in Norway. In the sequel, a brief history of wind power energy

  1. Intelligent wind power prediction systems final report

    E-Print Network [OSTI]

    Intelligent wind power prediction systems ­ final report ­ Henrik Aalborg Nielsen (han (FU 4101) Ens. journal number: 79029-0001 Project title: Intelligent wind power prediction systems #12;#12;Intelligent wind power prediction systems 1/36 Contents 1 Introduction 6 2 The Wind Power Prediction Tool 7 3

  2. Impact of Wind Shear and Tower Shadow Effects on Power System with Large Scale Wind Power

    E-Print Network [OSTI]

    Hu, Weihao

    Impact of Wind Shear and Tower Shadow Effects on Power System with Large Scale Wind Power to wind speed variations, the wind shear and the tower shadow effects. The fluctuating power may be ableSILENT/PowerFactory. In this paper, the impacts of wind shear and tower shadow effects on the small signal stability of power systems

  3. POWER SYSTEMS STABILITY WITH LARGE-SCALE WIND POWER PENETRATION

    E-Print Network [OSTI]

    Bak-Jensen, Birgitte

    of offshore wind farms, wind power fluctuations may introduce several challenges to reliable power system behaviour due to natural wind fluctuations. The rapid power fluctuations from the large scale wind farms Generation Control (AGC) system which includes large- scale wind farms for long-term stability simulation

  4. Long-Term Wind Power Variability

    SciTech Connect (OSTI)

    Wan, Y. H.

    2012-01-01T23:59:59.000Z

    The National Renewable Energy Laboratory started collecting wind power data from large commercial wind power plants (WPPs) in southwest Minnesota with dedicated dataloggers and communication links in the spring of 2000. Over the years, additional WPPs in other areas were added to and removed from the data collection effort. The longest data stream of actual wind plant output is more than 10 years. The resulting data have been used to analyze wind power fluctuations, frequency distribution of changes, the effects of spatial diversity, and wind power ancillary services. This report uses the multi-year wind power data to examine long-term wind power variability.

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

    SciTech Connect (OSTI)

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

    2013-10-01T23:59:59.000Z

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

  6. Computational methods in wind power meteorology

    E-Print Network [OSTI]

    Computational methods in wind power meteorology Bo Hoffmann Jørgensen, Søren Ott, Niels Nørmark, Jakob Mann and Jake Badger Title: Computational methods in wind power meteorology Department: Wind in connection with the project called Computational meth- ods in wind power meteorology which was supported

  7. Power Quality Aspects in a Wind Power Plant: Preprint

    SciTech Connect (OSTI)

    Muljadi, E.; Butterfield, C. P.; Chacon, J.; Romanowitz, H.

    2006-01-01T23:59:59.000Z

    Although many operational aspects affect wind power plant operation, this paper focuses on power quality. Because a wind power plant is connected to the grid, it is very important to understand the sources of disturbances that affect the power quality.

  8. This project is funded by an MIT Martin Family Fellowship and a MITEI Seed Fund Grant Leveraging High Performance Computation for Statistical Wind Power Prediction

    E-Print Network [OSTI]

    High Performance Computation for Statistical Wind Power Prediction Cy Chan*, James Stalker**, Alan for wind power forecasting is becoming imperative as wind energy becomes a larger contributor to the energy learning techniques for improving wind power prediction, with the goal of finding better ways to deliver

  9. Wind Fins: Novel Lower-Cost Wind Power System

    SciTech Connect (OSTI)

    David C. Morris; Dr. Will D. Swearingen

    2007-10-08T23:59:59.000Z

    This project evaluated the technical feasibility of converting energy from the wind with a novel “wind fin” approach. This patent-pending technology has three major components: (1) a mast, (2) a vertical, hinged wind structure or fin, and (3) a power takeoff system. The wing structure responds to the wind with an oscillating motion, generating power. The overall project goal was to determine the basic technical feasibility of the wind fin technology. Specific objectives were the following: (1) to determine the wind energy-conversion performance of the wind fin and the degree to which its performance could be enhanced through basic design improvements; (2) to determine how best to design the wind fin system to survive extreme winds; (3) to determine the cost-effectiveness of the best wind fin designs compared to state-of-the-art wind turbines; and (4) to develop conclusions about the overall technical feasibility of the wind fin system. Project work involved extensive computer modeling, wind-tunnel testing with small models, and testing of bench-scale models in a wind tunnel and outdoors in the wind. This project determined that the wind fin approach is technically feasible and likely to be commercially viable. Project results suggest that this new technology has the potential to harvest wind energy at approximately half the system cost of wind turbines in the 10kW range. Overall, the project demonstrated that the wind fin technology has the potential to increase the economic viability of small wind-power generation. In addition, it has the potential to eliminate lethality to birds and bats, overcome public objections to the aesthetics of wind-power machines, and significantly expand wind-power’s contribution to the national energy supply.

  10. Wind Power Integration: Exploring Impacts and Alternatives

    E-Print Network [OSTI]

    Walter, M.Todd

    Wind Power Integration: Exploring Impacts and Alternatives Assist. Prof. C sustainable sources of energy. The idea of harnessing wind energy has been there have been no less than fifteen in-depth wind integration studies

  11. Low-Maintenance Wind Power System

    E-Print Network [OSTI]

    Rasson, Joseph E

    2010-01-01T23:59:59.000Z

    with widespread adoption of wind energy. The project hasProject: Low-Maintenance Wind Power System Summary of theImproved Vertical Axis Wind Turbine and Aerodynamic Control

  12. 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

  13. Wind Powering America Initiative (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2011-01-01T23:59:59.000Z

    The U.S. Department of Energy's Wind Powering America initiative engages in technology market acceptance, barrier reduction, and technology deployment support activities. This fact sheet outlines ways in which the Wind Powering America team works to reduce barriers to appropriate wind energy deployment, primarily by focusing on six program areas: workforce development, communications and outreach, stakeholder analysis and resource assessment, wind technology technical support, wind power for Native Americans, and federal sector support and collaboration.

  14. Primer on Wind Power for Utility Applications

    SciTech Connect (OSTI)

    Wan, Y.

    2005-12-01T23:59:59.000Z

    The wind industry still faces many market barriers, some of which stem from utilities' lack of experience with the technology. Utility system operators and planners need to understand the effects of fluctuating wind power on system regulation and stability. Without high-frequency wind power data and realistic wind power plant models to analyze the problem, utilities often rely on conservative assumptions and worst-case scenarios to make engineering decisions. To remedy the situation, the National Renewable Energy Laboratory (NREL) has undertaken a project to record long-term, high-resolution (1-hertz [Hz]) wind power output data from large wind power plants in various regions. The objective is to systematically collect actual wind power data from large commercial wind power plants so that wind power fluctuations, their frequency distribution, the effects of spatial diversity, and the ancillary services of large commercial wind power plants can be analyzed. It also aims to provide the industry with nonproprietary wind power data in different wind regimes for system planning and operating impact studies. This report will summarize the results of data analysis performed at NREL and discuss the wind power characteristics related to power system operation and planning.

  15. Wind for Schools: A Wind Powering America Project (Brochure)

    SciTech Connect (OSTI)

    Baring-Gould, I.

    2009-08-01T23:59:59.000Z

    This brochure provides an overview of Wind Powering America's Wind for Schools Project, including a description of the project, the participants, funding sources, the basic configurations, and how interested parties can become involved.

  16. Wind for Schools: A Wind Powering America Project (Alaska) (Brochure)

    SciTech Connect (OSTI)

    Not Available

    2010-02-01T23:59:59.000Z

    This brochure provides an overview of Wind Powering America's Wind for Schools Project, including a description of the project, the participants, funding sources, the basic configurations, and how interested parties can become involved.

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

    Broader source: Energy.gov [DOE]

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

  18. Wind Powering America Program Overview (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2008-04-01T23:59:59.000Z

    This fact sheet provides an overview of the U.S. Department of Energy's Wind Powering America Program.

  19. Wind Power FAQ

    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 warmingGlobalPower

  20. Wind power communication Design and implementation

    E-Print Network [OSTI]

    Wind power communication ­ Design and implementation of test environment for IEC61850/UCA2 Elforsk rapport 02:16 Anders Johnsson, Jörgen Svensson April 2002 #12;#12;Wind power communication ­ Design 2002 #12;#12;Wind power communication ­ Design and implementation of test environment for IEC61850/UCA2

  1. Scenario Generation for Price Forecasting in Restructured Wholesale Power Markets

    E-Print Network [OSTI]

    Tesfatsion, Leigh

    1 Scenario Generation for Price Forecasting in Restructured Wholesale Power Markets Qun Zhou--In current restructured wholesale power markets, the short length of time series for prices makes are fitted between D&O and wholesale power prices in order to obtain price scenarios for a specified time

  2. Wind Vision Chapter 2: Wind Power in the United States

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

    M; Holtinnen, H.; Sder, L.; Clark, C.; Pineda, I. "Markets to Facilitate Wind and Solar Energy Integration in the Bulk Power Supply: An IEA Task 25 Collaboration."...

  3. The Political Economy of Wind Power in China

    E-Print Network [OSTI]

    Swanson, Ryan Landon

    2011-01-01T23:59:59.000Z

    some or all of the wind generation. ? 118 Because Chinahas grown faster than wind generation, wind-generatedhtm. ?Analysis of UK Wind Power Generation: November 2008 to

  4. The Political Economy of Wind Power in China

    E-Print Network [OSTI]

    Swanson, Ryan Landon

    2011-01-01T23:59:59.000Z

    by which wind turbine technology converts wind energy intoWind energy developers – usually power companies combined with a wind turbine

  5. Sandia National Laboratories: Wind Power

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

    Wind Energy Staff On March 24, 2011, in Wind Energy On November 10, 2010, in Wind Plant Opt. Rotor Innovation Materials, Reliability & Standards Siting & Barrier Mitigation...

  6. Offshore Wind Power Farm Environmental Impact Assessment

    E-Print Network [OSTI]

    Horns Rev Offshore Wind Power Farm Environmental Impact Assessment on Water Quality #12;Prepared with a planned 150 MW offshore wind farm at Horns Rev, an assessment was made of the effects the wind farm would for the preparation of EIA studies for offshore wind farms." Horns Rev is situated off Blåvands Huk, which is Denmark

  7. Engineering innovation to reduce wind power COE

    SciTech Connect (OSTI)

    Ammerman, Curtt Nelson [Los Alamos National Laboratory

    2011-01-10T23:59:59.000Z

    There are enough wind resources in the US to provide 10 times the electric power we currently use, however wind power only accounts for 2% of our total electricity production. One of the main limitations to wind use is cost. Wind power currently costs 5-to-8 cents per kilowatt-hour, which is more than twice the cost of electricity generated by burning coal. Our Intelligent Wind Turbine LDRD Project is applying LANL's leading-edge engineering expertise in modeling and simulation, experimental validation, and advanced sensing technologies to challenges faced in the design and operation of modern wind turbines.

  8. Datang Jilin Wind Power Stockholding Co Ltd Formerly Jilin Noble...

    Open Energy Info (EERE)

    Stockholding Co Ltd Formerly Jilin Noble Wind Power Stockholding Co Ltd Jump to: navigation, search Name: Datang Jilin Wind Power Stockholding Co Ltd(Formerly Jilin Noble Wind...

  9. Wind Power Today, 2010, Wind and Water Power Program (WWPP)

    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 DensityEnergy U.S.-China Electric VehicleCenters | Department ofofto PurchaseAprilWind Power

  10. 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...

  11. 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

  12. 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...

  13. Power and Frequency Control as it Relates to Wind-Powered Generation

    E-Print Network [OSTI]

    Lacommare, Kristina S H

    2011-01-01T23:59:59.000Z

    of large amounts of wind power production might requirewill be satisfactory as wind power provides an increasing64   7.2   Wind Power in Relation to System

  14. Hydraulic Wind Power Transfer Technology Afshin Izadian

    E-Print Network [OSTI]

    Zhou, Yaoqi

    Hydraulic Wind Power Transfer Technology Afshin Izadian Purdue School of Engineering and Technology of renewable energy tax credits in general and a gap in wind energy breakthroughs in particular have caused high cost of wind energy and technological dependency on countries such as China and Germany. Reducing

  15. Wind Farm Power System Model Development: Preprint

    SciTech Connect (OSTI)

    Muljadi, E.; Butterfield, C. P.

    2004-07-01T23:59:59.000Z

    In some areas, wind power has reached a level where it begins to impact grid operation and the stability of local utilities. In this paper, the model development for a large wind farm will be presented. Wind farm dynamic behavior and contribution to stability during transmission system faults will be examined.

  16. Wind Powering America's Wind for Schools Project: Summary Report

    SciTech Connect (OSTI)

    Baring-Gould, I.; Newcomb, C.

    2012-06-01T23:59:59.000Z

    This report provides an overview of the U.S. Department of Energy, Wind Powering America, Wind for Schools project. It outlines teacher-training activities and curriculum development; discusses the affiliate program that allows school districts and states to replicate the program; and contains reports that provide an update on activities and progress in the 11 states in which the Wind for Schools project operates.

  17. Previous Wind Power Announcements (generation/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:Energy: Grid Integration Redefining What's Possible forPortsmouth/Paducah ProjectPRE-AWARDenergyEnergytransmission-rates Sign In About |Wind

  18. Sixth Northwest Conservation and Electric Power Plan Appendix D: Wholesale Electricity Price Forecast

    E-Print Network [OSTI]

    Sixth Northwest Conservation and Electric Power Plan Appendix D: Wholesale Electricity Price.................................................................................................................................. 27 INTRODUCTION The Council prepares and periodically updates a 20-year forecast of wholesale to forecast wholesale power prices. AURORAxmp® provides the ability to inco

  19. Uncertainty Reduction in Power Generation Forecast Using Coupled Wavelet-ARIMA

    SciTech Connect (OSTI)

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

    2014-10-27T23:59:59.000Z

    In this paper, we introduce a new approach without implying normal distributions and stationarity of power generation forecast errors. In addition, it is desired to more accurately quantify the forecast uncertainty by reducing prediction intervals of forecasts. We use automatically coupled wavelet transform and autoregressive integrated moving-average (ARIMA) forecasting to reflect multi-scale variability of forecast errors. The proposed analysis reveals slow-changing “quasi-deterministic” components of forecast errors. This helps improve forecasts produced by other means, e.g., using weather-based models, and reduce forecast errors prediction intervals.

  20. Xi an Nordex Wind Turbine Co Ltd aka Xi an Weide Wind Power Equipment...

    Open Energy Info (EERE)

    Wind Turbine Co Ltd aka Xi an Weide Wind Power Equipment Co Ltd Jump to: navigation, search Name: Xi'an Nordex Wind Turbine Co Ltd (aka Xi'an Weide Wind Power Equipment Co Ltd)...

  1. Power Transformer Application for Wind Plant Substations

    SciTech Connect (OSTI)

    Behnke, M. R. [IEEE PES Wind Plant Collector System Design Working Group; Bloethe, W.G. [IEEE PES Wind Plant Collector System Design Working Group; Bradt, M. [IEEE PES Wind Plant Collector System Design Working Group; Brooks, C. [IEEE PES Wind Plant Collector System Design Working Group; Camm, E H [IEEE PES Wind Plant Collector System Design Working Group; Dilling, W. [IEEE PES Wind Plant Collector System Design Working Group; Goltz, B. [IEEE PES Wind Plant Collector System Design Working Group; Li, J. [IEEE PES Wind Plant Collector System Design Working Group; Niemira, J. [IEEE PES Wind Plant Collector System Design Working Group; Nuckles, K. [IEEE PES Wind Plant Collector System Design Working Group; Patino, J. [IEEE PES Wind Plant Collector System Design Working Group; Reza, M [IEEE PES Wind Plant Collector System Design Working Group; Richardson, B. [IEEE PES Wind Plant Collector System Design Working Group; Samaan, N. [IEEE PES Wind Plant Collector System Design Working Group; Schoene, Jens [IEEE PES Wind Plant Collector System Design Working Group; Smith, Travis M [ORNL; Snyder, Isabelle B [ORNL; Starke, Michael R [ORNL; Walling, R. [IEEE PES Wind Plant Collector System Design Working Group; Zahalka, G. [IEEE PES Wind Plant Collector System Design Working Group

    2010-01-01T23:59:59.000Z

    Wind power plants use power transformers to step plant output from the medium voltage of the collector system to the HV or EHV transmission system voltage. This paper discusses the application of these transformers with regard to the selection of winding configuration, MVA rating, impedance, loss evaluation, on-load tapchanger requirements, and redundancy.

  2. Wind Power Price Trends in the United States

    E-Print Network [OSTI]

    Bolinger, Mark

    2010-01-01T23:59:59.000Z

    49 Figure 5. Installed Wind Project Costs Over Time Capacitynot represent the true cost of wind generation (which wouldinstalled project costs on wind power prices. Specifically,

  3. Wind Power: How Much, How Soon, and At What Cost?

    E-Print Network [OSTI]

    Wiser, Ryan H

    2010-01-01T23:59:59.000Z

    on U.S. Wind Power Installation, Cost, and Performanceaccess the nation's lowest-cost wind resources can be builtpressure on installed wind project costs while the industry

  4. Global ocean wind power sensitivity to surface layer stability

    E-Print Network [OSTI]

    Capps, Scott B; Zender, Charles S

    2009-01-01T23:59:59.000Z

    2005), Evaluation of global wind power, J. Geophys. Res. ,Pryor (2003), Can satellite sampling of offshore wind speedsrealistically represent wind speed distributions? , J. Appl.

  5. RELIABILITY OF WIND POWER FROM DISPERSED SITES: A PRELIMINARY ASSESSMENT

    E-Print Network [OSTI]

    Kahn, E.

    2011-01-01T23:59:59.000Z

    Coincidence of Demand and Wind Resource Diurnal PowerOutput Variations for Three Wind Regimes List of TablesCAPACITY CREDIT FOR WIND ARRAYS: THE PROBLEM . . . . . . .

  6. Sandia National Laboratories: Wind Power

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

    known that large amounts of wind energy are not effectively harvested in large wind farms because the turbines "shadow" each other and reduce the output of the turbines located...

  7. Impact of Wind Power Plants on Voltage and Transient Stability of Power Systems

    SciTech Connect (OSTI)

    Muljadi, E.; Nguyen, Tony B.; Pai, M. A.

    2008-09-30T23:59:59.000Z

    A standard three-machine, nine-bus wind power system is studied and augmented by a radially connected wind power plant that contains 22 wind turbine generators.

  8. Active Power Controls from Wind Power: Bridging the Gaps

    SciTech Connect (OSTI)

    Ela, E.; Gevorgian, V.; Fleming, P.; Zhang, Y. C.; Singh, M.; Muljadi, E.; Scholbrook, A.; Aho, J.; Buckspan, A.; Pao, L.; Singhvi, V.; Tuohy, A.; Pourbeik, P.; Brooks, D.; Bhatt, N.

    2014-01-01T23:59:59.000Z

    This paper details a comprehensive study undertaken by the National Renewable Energy Laboratory, Electric Power Research Institute, and the University of Colorado to understand how the contribution of wind power providing active power control (APC) can benefit the total power system economics, increase revenue streams, improve the reliability and security of the power system, and provide superior and efficient response while reducing any structural and loading impacts that may reduce the life of the wind turbine or its components. The study includes power system simulations, control simulations, and actual field tests using turbines at NREL's National Wind Technology Center (NWTC). The study focuses on synthetic inertial control, primary frequency control, and automatic generation control, and analyzes timeframes ranging from milliseconds to minutes to the lifetime of wind turbines, locational scope ranging from components of turbines to large wind plants to entire synchronous interconnections, and additional topics ranging from economics to power system engineering to control design.

  9. Wind Power Price Trends in the United States

    E-Print Network [OSTI]

    Bolinger, Mark

    2010-01-01T23:59:59.000Z

    price of power from new U.S. wind projects higher in 2009.should eventually help wind power regain the downward pricein Modern Energy Review] Wind Power Price Trends in the

  10. RELIABILITY OF WIND POWER FROM DISPERSED SITES: A PRELIMINARY ASSESSMENT

    E-Print Network [OSTI]

    Kahn, E.

    2011-01-01T23:59:59.000Z

    ON METHODOLOGY: FROM WIND POWER FREQUENCY TO LOSS-OF-LOADJ.P. , "Some Aspects of Wind Power Statistics, " J. of Appl.J • J METHODOLOGY: FROM WIND POWER FREQUENCY TO LOSS-OF-LOAD

  11. Global ocean wind power sensitivity to surface layer stability

    E-Print Network [OSTI]

    Capps, Scott B; Zender, Charles S

    2009-01-01T23:59:59.000Z

    Evaluation of global wind power, J. Geophys. Res. , 110,W. Tang, and X. Xie (2008), Wind power distribution over theApproach to Short-Term Wind Power Prediction, 1st ed. ,

  12. Wind Power Price Trends in the United States

    E-Print Network [OSTI]

    Bolinger, Mark

    2010-01-01T23:59:59.000Z

    should eventually help wind power regain the downward priceModern Energy Review] Wind Power Price Trends in the Unitedled the world in adding new wind power capacity in 2008, and

  13. The Political Economy of Wind Power in China

    E-Print Network [OSTI]

    Swanson, Ryan Landon

    2011-01-01T23:59:59.000Z

    adds 18.9 GW of new wind power capacity in 2010. ? GlobalEnd Challenged Subsidies in Wind Power Case. ? Internationalemergence in the global wind power industry. ? Ph. D.

  14. Wind Power: How Much, How Soon, and At What Cost?

    E-Print Network [OSTI]

    Wiser, Ryan H

    2010-01-01T23:59:59.000Z

    Evaluation of Global Wind Power." Journal of Geophysical2008. "The Economics of Wind Power with Energy Storage."Economics of Large-Scale Wind Power in a Carbon Constrained

  15. Wind Power: How Much, How Soon, and At What Cost?

    E-Print Network [OSTI]

    Wiser, Ryan H

    2010-01-01T23:59:59.000Z

    World's Electricity from Wind Power by 2020." Prepared forof the 2004 Global Wind Power Conference. 29-31 March.of Storage Technologies to Wind Power." NREL/CP-670-43510.

  16. RELIABILITY OF WIND POWER FROM DISPERSED SITES: A PRELIMINARY ASSESSMENT

    E-Print Network [OSTI]

    Kahn, E.

    2011-01-01T23:59:59.000Z

    ON METHODOLOGY: FROM WIND POWER FREQUENCY TO LOSS-OF-LOADJ.P. , "Some Aspects of Wind Power Statistics, " J. of Appl.S£CTION Reliability of Wind Power From Dispersed Sites: A Pr

  17. The amount of power in the wind is very dependent on the speed of the wind. Because the power in the wind

    E-Print Network [OSTI]

    Massachusetts at Amherst, University of

    the potential benefits of a wind power installation, wind speeds and other characteristics of a site's wind for potential wind power sites. However, these maps do not elimi- nate the need for more precise and thoroughThe amount of power in the wind is very dependent on the speed of the wind. Because the power

  18. Dynamic Models for Wind Turbines and Wind Power Plants

    SciTech Connect (OSTI)

    Singh, M.; Santoso, S.

    2011-10-01T23:59:59.000Z

    The primary objective of this report was to develop universal manufacturer-independent wind turbine and wind power plant models that can be shared, used, and improved without any restrictions by project developers, manufacturers, and engineers. Manufacturer-specific models of wind turbines are favored for use in wind power interconnection studies. While they are detailed and accurate, their usages are limited to the terms of the non-disclosure agreement, thus stifling model sharing. The primary objective of the work proposed is to develop universal manufacturer-independent wind power plant models that can be shared, used, and improved without any restrictions by project developers, manufacturers, and engineers. Each of these models includes representations of general turbine aerodynamics, the mechanical drive-train, and the electrical characteristics of the generator and converter, as well as the control systems typically used. To determine how realistic model performance is, the performance of one of the models (doubly-fed induction generator model) has been validated using real-world wind power plant data. This work also documents selected applications of these models.

  19. Sandia National Laboratories: wind turbines produce rated power

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

    wind turbines produce rated power Increasing the Scaled Wind Farm Technology Facility's Power Production On April 7, 2014, in Energy, Facilities, News, News & Events, Partnership,...

  20. Conventional Hydropower Technologies, Wind And Water Power Program...

    Office of Environmental Management (EM)

    Conventional Hydropower Technologies, Wind And Water Power Program (WWPP) (Fact Sheet) Conventional Hydropower Technologies, Wind And Water Power Program (WWPP) (Fact Sheet) The US...

  1. Local Content Requirements in British Columbia's Wind Power Industry

    E-Print Network [OSTI]

    Pedersen, Tom

    Local Content Requirements in British Columbia's Wind Power Industry May Hao, Matt Mackenzie, Alex..................................................................................8 4.1 Current Wind Power Projects

  2. Analysis of Wind Power Ramping Behavior in ERCOT

    SciTech Connect (OSTI)

    Wan, Y. H.

    2011-03-01T23:59:59.000Z

    This report analyzes the wind power ramping behavior using 10-minute and hourly average wind power data from ERCOT and presents statistical properties of the large ramp events.

  3. POWER PURCHASE AGREEMENT DELMARVA POWER & LIGHT COMPANY

    E-Print Network [OSTI]

    Firestone, Jeremy

    POWER PURCHASE AGREEMENT between DELMARVA POWER & LIGHT COMPANY ("Buyer") and BLUEWATER WIND 3.5 Energy Forecasts, Scheduling and Balancing.......................................... 39 3

  4. Wind Power Reliability: Breaking Down a Barrier

    Broader source: Energy.gov [DOE]

    The steady increase of wind power on the grid presents new challenges for power system operators charged with making sure the grid stays up and running. "We need to ensure that we are going down a path that will lead to better reliability [with wind power]," said Bob Zavadil, an executive vice president at EnerNex Corporation in Knoxville, Tenn., a firm specializing in renewable energy grid interconnection and integration. "If this piece isn't done, there will be problems." EnerNex has spent the last decade perfecting wind turbine and plant models that test a wind plant's influence on the grid and its ability to provide grid support. In its latest effort, the company is using American Recovery and Reinvestment Act funds worth $750,000 to develop documentation and validations of computer wind turbine models.

  5. Challenges in Predicting Power Output from Offshore Wind Farms

    E-Print Network [OSTI]

    Pryor, Sara C.

    Challenges in Predicting Power Output from Offshore Wind Farms R. J. Barthelmie1 and S. C. Pryor2 Abstract: Offshore wind energy is developing rapidly in Europe and the trend is towards large wind farms an offshore wind farm, accurate assessment of the wind resource/power output from the wind farm is a necessity

  6. Sixth Northwest Conservation and Electric Power Plan Appendix A: Fuel Price Forecast

    E-Print Network [OSTI]

    ............................................................................................................................... 12 Oil Price Forecast Range. The price of crude oil was $25 a barrel in January of 2000. In July 2008 it averaged $127, even approachingSixth Northwest Conservation and Electric Power Plan Appendix A: Fuel Price Forecast Introduction

  7. Wind Powering America Webinar: Wind Power Economics: Past, Present...

    Energy Savers [EERE]

    Economics: Past, Present, and Future Trends November 23, 2011 - 1:43pm Addthis Wind turbine prices in the United States have declined, on average, by nearly one-third since...

  8. UNIVERSITY OF CALIFORNIA, Surface Wind Speed Distributions: Implications for Climate and Wind Power

    E-Print Network [OSTI]

    Zender, Charles

    and Wind Power DISSERTATION submitted in partial satisfaction of the requirements for the degree of DOCTOR . . . . . . . . . . . . . . . . . 19 1.3 Global Ocean Wind Power and Surface Layer Stability . . . . . . . . 23 1.3.1 Global Winds . . . . . . 27 1.4 Usable Offshore Wind Power . . . . . . . . . . . . . . . . . . . . . . . 31 1.4.1 Wind Turbine

  9. Wind Power Amercia Final Report

    SciTech Connect (OSTI)

    Brian Spangler, Kathi Montgomery and Paul Cartwright

    2012-01-30T23:59:59.000Z

    The objective of this grant was to further the development of Montana�¢����s vast wind resources for small, medium and large scale benefits to Montana and the nation. This was accomplished through collaborative work with wind industry representatives, state and local governments, the agricultural community and interested citizens. Through these efforts DEQ was able to identify development barriers, educate and inform citizens as well as participate in regional and national dialogue that will spur the development of wind resources.

  10. On the Wind Power Input to the Ocean General Circulation

    E-Print Network [OSTI]

    Zhai, Xiaoming

    The wind power input to the ocean general circulation is usually calculated from the time-averaged wind products. Here, this wind power input is reexamined using available observations, focusing on the role of the synoptically ...

  11. Wind Farm Aggregation Impact on Power Quality: Preprint

    SciTech Connect (OSTI)

    Bialasiewicz, J. T.; Muljadi, E.

    2006-11-01T23:59:59.000Z

    This paper explores the effects of wind farm power fluctuations on the power network. A dynamic simulation of a wind farm is performed and the spatial distribution of the wind turbines is considered.

  12. Wind Powering America FY06 Activities Summary

    SciTech Connect (OSTI)

    Not Available

    2007-02-01T23:59:59.000Z

    The Wind Powering America FY06 Activities Summary reflects the accomplishments of our state wind working groups, our programs at the National Renewable Energy Laboratory, and our partner organizations. The national WPA team remains a leading force for moving wind energy forward in the United States. WPA continues to work with its national, regional, and state partners to communicate the opportunities and benefits of wind energy to a diverse set of stakeholders. WPA now has 29 state wind working groups (welcoming New Jersey, Indiana, Illinois, and Missouri in 2006) that form strategic alliances to communicate wind's benefits to the state stakeholders. More than 120 members of national and state public and private sector organizations from 34 states attended the 5th Annual WPA All-States Summit in Pittsburgh in June.

  13. 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

  14. Power and Frequency Control as it Relates to Wind-Powered Generation

    SciTech Connect (OSTI)

    Lacommare, Kristina S H

    2010-12-20T23:59:59.000Z

    This report is a part of an investigation of the ability of the U.S. power system to accommodate large scale additions of wind generation. The objectives of this report are to describe principles by which large multi-area power systems are controlled and to anticipate how the introduction of large amounts of wind power production might require control protocols to be changed. The operation of a power system is described in terms of primary and secondary control actions. Primary control is fast, autonomous, and provides the first-line corrective action in disturbances; secondary control takes place on a follow-up time scale and manages the deployment of resources to ensure reliable and economic operation. This report anticipates that the present fundamental primary and secondary control protocols will be satisfactory as wind power provides an increasing fraction of the total production, provided that appropriate attention is paid to the timing of primary control response, to short term wind forecasting, and to management of reserves for control action.

  15. Sandia National Laboratories: Wind Power

    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...

  16. Title: Ontario Wind Power Allocation Ontario Ministry of Natural Resources

    E-Print Network [OSTI]

    Title: Ontario Wind Power Allocation Data Creator / Copyright Owner: Ontario Ministry of Natural/A Updates: N/A Abstract: This data consists of a polygon shapefile, Wind Power Allocation Block. A Wind Power Allocation Block is an area that could be allocated for the exploration of wind power generation

  17. Environmentally Sound Design and Recycling of Future Wind Power Systems

    E-Print Network [OSTI]

    Environmentally Sound Design and Recycling of Future Wind Power Systems Presentation at the IEA R state-of-the-art wind power system Mapping current trends of wind power technologies and concepts Expert wind power systems Expert panel brainstorm on environmental aspects of decommissioning current

  18. MSU-Wind Applications Center: Wind Resource Worksheet Theoretical Power Calculation

    E-Print Network [OSTI]

    Dyer, Bill

    MSU-Wind Applications Center: Wind Resource Worksheet Theoretical Power Calculation Equations: A= swept area = air density v= velocity R= universal gas constant Steps: 1. Measure wind speed from fan. = ___________/(________*________)= _________kg/m3 5. Theoretical Power a. Low Setting Theoretical Wind Power i. Power= ½*______*______*______*.59

  19. Wind Power (pbl/generation)

    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 SoarsWind

  20. Testing Active Power Control from Wind Power at the National Wind Technology Center (NWTC) (Presentation)

    SciTech Connect (OSTI)

    Ela, E.

    2011-05-01T23:59:59.000Z

    In order to keep the electricity grid stable and the lights on, the power system relies on certain responses from its generating fleet. This presentation evaluates the potential for wind turbines and wind power plants to provide these services and assist the grid during critical times.

  1. Analysis of wind power for battery charging

    SciTech Connect (OSTI)

    Muljadi, E.; Drouilhet, S.; Holz, R. [National Renewable Energy Lab., Golden, CO (United States); Gevorgian, V. [University of Armenia, Yerevan (Armenia). State Engineering

    1995-11-01T23:59:59.000Z

    One type of wind-powered battery charging will be explored in this paper. It consists of a wind turbine driving a permanent magnet alternator and operates at variable speed. The alternator is connected to a battery bank via a rectifier. The characteristic of the system depends on the wind turbine, the alternator, and the system configuration. If the electrical load does not match the wind turbine, the performance of the system will be degraded. By matching the electrical load to the wind turbine, the system can be improved significantly. This paper analyzes the properties of the system components. The effects of parameter variation and the system configuration on the system performance are investigated. Two basic methods of shaping the torque-speed characteristic of the generator are presented. The uncompensated as well as the compensated systems will be discussed. Control strategies to improve the system performance will be explored. Finally, a summary of the paper will be presented in the last section.

  2. 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

  3. Wind Farm Diversification and Its Impact on Power System Reliability

    E-Print Network [OSTI]

    Degeilh, Yannick

    2010-10-12T23:59:59.000Z

    of potential wind farming sites for which the wind patterns are statistically known. The objective is to demonstrate the benefits of diversification for the reliability of wind-sustained systems through the search for steadier overall power outputs. Three... power output. Reported studies are generally concerned about the selection of a given potential wind farming site based on its wind patterns [1], but not about the beneficial interactions that various power outputs from various wind parks may yield...

  4. Wind Powering America FY07 Activities Summary

    SciTech Connect (OSTI)

    Not Available

    2008-02-01T23:59:59.000Z

    The Wind Powering America FY07 Activities Summary reflects the accomplishments of our state wind working groups, our programs at the National Renewable Energy Laboratory, and our partner organizations. The national WPA team remains a leading force for moving wind energy forward in the United States. WPA continues to work with its national, regional, and state partners to communicate the opportunities and benefits of wind energy to a diverse set of stakeholders. WPA now has 30 state wind working groups (welcoming Georgia and Wisconsin in 2007) that form strategic alliances to communicate wind's benefits to the state stakeholders. More than 140 members of national and state public and private sector organizations from 39 U.S. states and Canada attended the 6th Annual WPA All-States Summit in Los Angeles in June. WPA's emphasis remains on the rural agricultural sector, which stands to reap the significant economic development benefits of wind energy development. Additionally, WPA continues its program of outreach, education, and technical assistance to Native American communities, public power entities, and regulatory and legislative bodies.

  5. Analysis of Wind Power Generation of Texas 

    E-Print Network [OSTI]

    Liu, Z.; Haberl, J.; Subbarao, K.; Baltazar, J. C.

    2007-01-01T23:59:59.000Z

    1 ? Energy Systems Laboratory, Texas A&M University Page 1 ANALYSIS OF WIND POWER GENERATION OF TEXAS April 2007 Zi ?Betty? Liu, Ph.D., Jeff Haberl, Ph.D., P.E., Kris Subbarao, Ph.D., P.E., Juan-Carlos Baltazar, Ph.D. Energy Systems Laboratory... from Jul 2002 to Jan 2003 Degradation Analysis - On average, no degradation observed for nine wind farms analyzed over 4-year period. Application of Method 1 to New Site- Sweetwater I Wind Farm ? Energy Systems Laboratory, Texas A&M University Page 3...

  6. Wind Powering America Webinar: Wind Power Economics: Past, Present, and

    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 DensityEnergy U.S.-China Electric VehicleCenters | Department ofofto PurchaseAprilWindFuture Trends |

  7. 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

  8. PowerJet Wind Turbine Project

    SciTech Connect (OSTI)

    Bartlett, Raymond J

    2008-11-30T23:59:59.000Z

    PROJECT OBJECTIVE The PowerJet wind turbine overcomes problems characteristic of the small wind turbines that are on the market today by providing reliable output at a wide range of wind speeds, durability, silent operation at all wind speeds, and bird-safe operation. Prime Energy�s objective for this project was to design and integrate a generator with an electrical controller and mechanical controls to maximize the generation of electricity by its wind turbine. The scope of this project was to design, construct and test a mechanical back plate to control rotational speed in high winds, and an electronic controller to maximize power output and to assist the base plate in controlling rotational speed in high winds. The test model will continue to operate beyond the time frame of the project, with the ultimate goal of manufacturing and marketing the PowerJet worldwide. Increased Understanding of Electronic & Mechanical Controls Integrated With Electricity Generator The PowerJet back plate begins to open as wind speed exceeds 13.5 mps. The pressure inside the turbine and the turbine rotational speed are held constant. Once the back plate has fully opened at approximately 29 mps, the controller begins pulsing back to the generator to limit the rotational speed of the turbine. At a wind speed in excess of 29 mps, the controller shorts the generator and brings the turbine to a complete stop. As the wind speed subsides, the controller releases the turbine and it resumes producing electricity. Data collection and instrumentation problems prevented identification of the exact speeds at which these events occur. However, the turbine, controller and generator survived winds in excess of 36 mps, confirming that the two over-speed controls accomplished their purpose. Technical Effectiveness & Economic Feasibility Maximum Electrical Output The output of electricity is maximized by the integration of an electronic controller and mechanical over-speed controls designed and tested during the course of this project. The output exceeds that of the PowerJet�s 3-bladed counterparts (see Appendix). Durability All components of the PowerJet turbine assembly�including the electronic and mechanical controls designed, manufactured and field tested during the course of this project�proved to be durable through severe weather conditions, with constant operation and no interruption in energy production. Low Cost Materials for the turbine, generator, tower, charge controllers and ancillary parts are available at reasonable prices. Fabrication of these parts is also readily available worldwide. The cost of assembling and installing the turbine is reduced because it has fewer parts and requires less labor to manufacture and assemble, making it competitively priced compared with turbines of similar output manufactured in the U.S. and Europe. The electronic controller is the unique part to be included in the turbine package. The controllers can be manufactured in reasonably-sized production runs to keep the cost below $250 each. The data logger and 24 sensors are for research only and will be unnecessary for the commercial product. Benefit To Public The PowerJet wind-electric system is designed for distributed wind generation in 3 and 4 class winds. This wind turbine meets DOE�s requirements for a quiet, durable, bird-safe turbine that eventually can be deployed as a grid-connected generator in urban and suburban settings. Results As described more fully below and illustrated in the Appendices, the goals and objectives outlined in 2060 SOPO were fully met. Electronic and mechanical controls were successfully designed, manufactured and integrated with the generator. The turbine, tower, controllers and generators operated without incident throughout the test period, surviving severe winter and summer weather conditions such as extreme temperatures, ice and sustained high winds. The electronic controls were contained in weather-proof electrical boxes and the elec

  9. ForPeerReview PUBLIC ACCEPTANCE OF OFFSHORE WIND POWER

    E-Print Network [OSTI]

    Firestone, Jeremy

    ForPeerReview PUBLIC ACCEPTANCE OF OFFSHORE WIND POWER PROJECTS IN THE UNITED STATES Journal: Wind, Andrew; Minerals Management Service Keywords: offshore wind power, public opinion, social acceptancePeerReview 1 PUBLIC ACCEPTANCE OF OFFSHORE WIND POWER PROJECTS IN THE UNITED STATES Jeremy Firestone*, Willett

  10. Power and Frequency Control as it Relates to Wind-Powered Generation

    E-Print Network [OSTI]

    Lacommare, Kristina S H

    2011-01-01T23:59:59.000Z

    per hour in both balancing areas Wind power ramps down atper hour in both balancing areas Wind power ramps down atbalancing area 2 Power and Frequency Control as it Relates to Wind-

  11. Power and Frequency Control as it Relates to Wind-Powered Generation

    E-Print Network [OSTI]

    Lacommare, Kristina S H

    2011-01-01T23:59:59.000Z

    Control as it Relates to Wind- Powered Generation AppendixControl as it Relates to Wind-Powered Generation JohnControl as it Relates to Wind-Powered Generation LBNL-XXXXX

  12. The Political Economy of Wind Power in China

    E-Print Network [OSTI]

    Swanson, Ryan Landon

    2011-01-01T23:59:59.000Z

    solar panels are too expensive to install domestically, China‘China,? as Chinese wind resources are abundant and wind power is cheaper than solar

  13. Wind Powering America: FY09 Activities Summary (Book)

    SciTech Connect (OSTI)

    Not Available

    2010-03-01T23:59:59.000Z

    The Wind Powering America FY09 Activities Summary reflects the accomplishments of state Wind Working Groups, WPA programs at the National Renewable Energy Laboratory, and partner organizations.

  14. Wind Powering America FY08 Activities Summary (Book)

    SciTech Connect (OSTI)

    Not Available

    2009-02-01T23:59:59.000Z

    The Wind Powering America FY08 Activities Summary reflects the accomplishments of state Wind Working Groups, WPA programs at the National Renewable Energy Laboratory, and partner organizations.

  15. Wind Power Project Repowering: History, Economics, and Demand...

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

    Wind Power Project Repowering: History, Economics, and Demand Wind Exchange Webinar Eric Lantz January 21, 2015 NRELPR-6A20-63591 2 Presentation Overview 1. Background - Concepts...

  16. Wind Farm Diversification and Its Impact on Power System Reliability 

    E-Print Network [OSTI]

    Degeilh, Yannick

    2010-10-12T23:59:59.000Z

    As wind exploitation gains prominence in the power industry, the extensive use of this intermittent source of power may heavily rely on our ability to select the best combination of wind farming sites that yields maximal reliability of power systems...

  17. Wind Power Price Trends in the United States: Struggling to Remain Competitive in the Face of Strong Growth

    E-Print Network [OSTI]

    Bolinger, Mark A

    2009-01-01T23:59:59.000Z

    and forecast future wind cost and pricing trends (see,long-term forecast of future wind costs or competitiveness,To put the material on wind cost and pricing trends in

  18. This introduction to wind power technology is meant to help communities in considering or planning wind

    E-Print Network [OSTI]

    Massachusetts at Amherst, University of

    This introduction to wind power technology is meant to help communities in considering or planning wind power. It focuses on commercial and medium-scale wind turbine technology that is available in the United States. This fact sheet also discusses the integration of wind power into the electrical grid

  19. The Political Economy of Wind Power in China

    E-Print Network [OSTI]

    Swanson, Ryan Landon

    2011-01-01T23:59:59.000Z

    on the expansion of nuclear power to decouple China‘s energyoffshore wind power to be cheaper than nuclear power. 21 In

  20. Electricity for road transport, flexible power systems and wind...

    Open Energy Info (EERE)

    for road transport, flexible power systems and wind power (Smart Grid Project) Jump to: navigation, search Project Name Electricity for road transport, flexible power systems and...

  1. Wind Power Plant Voltage Stability Evaluation: Preprint

    SciTech Connect (OSTI)

    Muljadi, E.; Zhang, Y. C.

    2014-09-01T23:59:59.000Z

    Voltage stability refers to the ability of a power system to maintain steady voltages at all buses in the system after being subjected to a disturbance from a given initial operating condition. Voltage stability depends on a power system's ability to maintain and/or restore equilibrium between load demand and supply. Instability that may result occurs in the form of a progressive fall or rise of voltages of some buses. Possible outcomes of voltage instability are the loss of load in an area or tripped transmission lines and other elements by their protective systems, which may lead to cascading outages. The loss of synchronism of some generators may result from these outages or from operating conditions that violate a synchronous generator's field current limit, or in the case of variable speed wind turbine generator, the current limits of power switches. This paper investigates the impact of wind power plants on power system voltage stability by using synchrophasor measurements.

  2. 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

  3. Wind Power Renewables | 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 Power

  4. PBS: Wind Power for Educators

    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'tOrigin of Contamination in ManyDepartmentOutreachDepartment ofProgram49, thePAGEPART I -PBS: Wind

  5. The Political Economy of Wind Power in China

    E-Print Network [OSTI]

    Swanson, Ryan Landon

    2011-01-01T23:59:59.000Z

    woes hamper China wind farms‘ push for profitability. ?China adds 18.9 GW of new wind power capacity in 2010. ?Global Wind Energy Council. 6 April 2011. http://

  6. 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.

  7. Proceedings of national avian-wind power planning meeting 2

    SciTech Connect (OSTI)

    NONE

    1998-02-01T23:59:59.000Z

    This meeting was the second in a series. The purposes of this meeting were to: (1) provide information on avian/wind power interactions that will help meet the needs of regulators, researchers, and other stakeholders concerned with responsible development and permitting of wind plants; (2) create dialogue among regulators, researchers and other stakeholders to help all parties understand the role that research can play in responsible development and permitting of wind plants, and allow researchers to understand the relevance of their research to the process; and (3) propose research projects and the appropriate sponsorship. The meeting began with oral presentations and discussions of nine White Papers on the theory and methods for studying and understanding impacts. The Proceedings include the written version of each of the nine White Papers, plus a summary of the oral discussion associated with each paper. The second part of the meeting consisted of four working group sessions: (1) site evaluation and pre-permit research and planning; (2) operational monitoring; (3) modeling and forecasting, including population dynamics models; and (4) avian behavior and mortality reduction. The Proceedings includes a summary of the discussions on these topics, including each working group`s recommendations for future research or associated activities. A final plenary session drew together the main recommendations.

  8. Considering Air Density in Wind Power Production

    E-Print Network [OSTI]

    Zénó Farkas

    2011-03-11T23:59:59.000Z

    In the wind power production calculations the air density is usually considered as constant in time. Using the CIPM-2007 equation for the density of moist air as a function of air temperature, air pressure and relative humidity, we show that it is worth taking the variation of the air density into account, because higher accuracy can be obtained in the calculation of the power production for little effort.

  9. Considering Air Density in Wind Power Production

    E-Print Network [OSTI]

    Farkas, Zénó

    2011-01-01T23:59:59.000Z

    In the wind power production calculations the air density is usually considered as constant in time. Using the CIPM-2007 equation for the density of moist air as a function of air temperature, air pressure and relative humidity, we show that it is worth taking the variation of the air density into account, because higher accuracy can be obtained in the calculation of the power production for little effort.

  10. Biennial Assessment of the Fifth Power Plan Interim Report on Electric Price Forecasts

    E-Print Network [OSTI]

    because natural gas fired electric generating plants are on the margin much of the time in Western marketsBiennial Assessment of the Fifth Power Plan Interim Report on Electric Price Forecasts Electricity prices in the Council's Power Plan are forecast using the AURORATM Electricity Market Model of the entire

  11. Wind Power Plant Prediction by Using Neural Networks: Preprint

    SciTech Connect (OSTI)

    Liu, Z.; Gao, W.; Wan, Y. H.; Muljadi, E.

    2012-08-01T23:59:59.000Z

    This paper introduces a method of short-term wind power prediction for a wind power plant by training neural networks based on historical data of wind speed and wind direction. The model proposed is shown to achieve a high accuracy with respect to the measured data.

  12. Mark Your Calendar! Indiana's only statewide wind power

    E-Print Network [OSTI]

    Ginzel, Matthew

    Mark Your Calendar! Indiana's only statewide wind power conference is July 21-22, 2010. WIndiana in Track 1. Wind power supply chain information will be in Track 2. Track 3 is an expanded Community Wind 2010. First, there will be three separate session tracks to choose from. Big Wind will be represented

  13. Judi Danielson Wind Power: From Niche to Mainstream

    E-Print Network [OSTI]

    , was the federal production tax incentive, which lowers the cost of wind power for potential investorsJudi Danielson Wind Power: From Niche to Mainstream What's Inside (continued on page 11) Winter sailboats to sail-type windmills. Today, the wind is converted into electricity through wind turbine

  14. Analysis of Wind Power and Load Data at Multiple Time Scales

    E-Print Network [OSTI]

    Coughlin, Katie

    2011-01-01T23:59:59.000Z

    Wan, Yih-Huei. 2004. Wind Power Plant Behaviors: Analyses ofthe output of wind power plants. In a typical studyfluctuations across wind power plants located in the same

  15. Assessment of wind power predictability as a decision factor in the investment phase of wind farms

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Assessment of wind power predictability as a decision factor in the investment phase of wind farms on market revenue of, respectively, the predictability and the capacity factor of a wind farm or a cluster of wind farms. This is done through a real-life case study in West Denmark, including wind farm production

  16. The Answer Is Blowing in the Wind: Analysis of Powering Internet Data Centers with Wind Energy

    E-Print Network [OSTI]

    of real-world wind power traces from 69 wind farms. The idea is to leverage the front-end load dispatching generally lie in a range from 44% to 96%, depending on how the locations of wind farms are selected. We" IDCs through a wind- aware load balancing design? and 2) How to select data center or wind farm

  17. Wind power: executive summary on research on network wind power over the Pacific Northwest. Progress report, October 1979-September 1980

    SciTech Connect (OSTI)

    Baker, R.W.; Hewson, E.W.

    1980-10-01T23:59:59.000Z

    This research in FY80 is composed of six primary tasks. These tasks include data collection and analysis, wind flow studies around an operational wind turbine generator (WTG), kite anemometer calibration, wind flow analysis and prediction, the Klickitat County small wind energy conversion system (SWECS) program, and network wind power analysis. The data collection and analysis task consists of four sections, three of which deal with wind flow site surveys and the fourth with collecting and analyzing wind data from existing data stations.

  18. Arkansas Preparing for Wind Power | Department of Energy

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

    Arkansas Preparing for Wind Power Arkansas Preparing for Wind Power April 15, 2010 - 5:25pm Addthis Joshua DeLung Renowned science fiction author Isaac Asimov once said, "No...

  19. Structural responses and power output of a wind turbine are strongly affected by the wind field acting on the wind turbine. Knowledge about the wind field and its

    E-Print Network [OSTI]

    Stanford University

    ABSTRACT Structural responses and power output of a wind turbine are strongly affected by the wind field acting on the wind turbine. Knowledge about the wind field and its variations is essential not only for designing, but also for cost-efficiently managing wind turbines. Wind field monitoring

  20. 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

  1. 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

  2. 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:

  3. NREL Small Wind Turbine Test Project: Mariah Power's Windspire Wind Turbine Test Chronology

    SciTech Connect (OSTI)

    Huskey, A.; Forsyth, T.

    2009-06-01T23:59:59.000Z

    This report presents a chronology of tests conducted at NREL's National Wind Technology Center on Mariah Power's Windspire 1.2-kW wind turbine and a letter of response from Mariah Power.

  4. The Political Economy of Wind Power in China

    E-Print Network [OSTI]

    Swanson, Ryan Landon

    2011-01-01T23:59:59.000Z

    wind power, while others may mandate daily operating limits or are based upon thresholds for the percentage of balancing

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

    SciTech Connect (OSTI)

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

    2014-09-01T23:59:59.000Z

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

  6. Synchrophasor Applications for Wind Power Generation

    SciTech Connect (OSTI)

    Muljadi, E.; Zhang, Y. C.; Allen, A.; Singh, M.; Gevorgian, V.; Wan, Y. H.

    2014-02-01T23:59:59.000Z

    The U.S. power industry is undertaking several initiatives that will improve the operations of the electric power grid. One of those is the implementation of wide-area measurements using phasor measurement units to dynamically monitor the operations and status of the network and provide advanced situational awareness and stability assessment. The overviews of synchrophasors and stability analyses in this report are intended to present the potential future applications of synchrophasors for power system operations under high penetrations of wind and other renewable energy sources.

  7. Wind Farm Power Prediction: A Data-Mining Approach

    E-Print Network [OSTI]

    Kusiak, Andrew

    Wind Farm Power Prediction: A Data-Mining Approach Andrew Kusiak*, Haiyang Zheng and Zhe Song, IA 52242­1527, USA In this paper, models for short- and long-term prediction of wind farm power length of the long-term prediction model is 84 h. The wind farm power prediction models are built

  8. Characterization of the Wind Power Resource in Europe and its

    E-Print Network [OSTI]

    Characterization of the Wind Power Resource in Europe and its Intermittency Alexandra Cosseron, C;1 Characterization of the Wind Power Resource in Europe and its Intermittency Alexandra Cosseron* , C. Adam Schlosser , and Udaya Bhaskar Gunturu Abstract Wind power is assessed over Europe, with special attention given

  9. Characterization of wind power resource in the United States*

    E-Print Network [OSTI]

    Characterization of wind power resource in the United States* U. Bhaskar Gunturu and C. Adam Chemistry and Physics Characterization of wind power resource in the United States U. B. Gunturu and C. A, 120 m turbine hub heights. The wind power density (WPD) estimates at 50 m are qualitatively similar

  10. Ris-R-1527(EN) Wind Power Prediction using Ensembles

    E-Print Network [OSTI]

    Risø-R-1527(EN) Wind Power Prediction using Ensembles Gregor Giebel (ed.), Jake Badger, Lars, Lars Voulund Title: Wind Power Prediction using Ensembles Risø-R-1527(EN) September 2005 ISSN 0106 from the operational use - Elsam 35 5.2.1 Control room functions 35 5.2.2 Use of wind power predictions

  11. Stochastic Analysis of Wind Turbine Power Curves Edgar Anahua

    E-Print Network [OSTI]

    Peinke, Joachim

    Stochastic Analysis of Wind Turbine Power Curves Edgar Anahua Oldenburg 2007 Zur Homepage der Dissertation #12;#12;Stochastic Analysis of Wind Turbine Power Curves Edgar Anahua Von der Fakult¨at f the wind turbine's power per- formance directly from high frequency fluctuating measurements. In particular

  12. Control of Wind Turbines for Power Regulation and

    E-Print Network [OSTI]

    Control of Wind Turbines for Power Regulation and Load Reduction Juan Jose Garcia Quirante Kongens regulation and load reduction and their ensemble in a variable-speed wind turbine. The power regulation aspects of mathematical modelling of wind turbines, and especially the control methods suited for power

  13. FORECAST OF ENSEMBLE POWER PRODUCTION BY GRID-CONNECTED PV SYSTEMS Elke Lorenz*, Detlev Heinemann*, Hashini Wickramarathne*, Hans Georg Beyer +

    E-Print Network [OSTI]

    Heinemann, Detlev

    FORECAST OF ENSEMBLE POWER PRODUCTION BY GRID-CONNECTED PV SYSTEMS Elke Lorenz*, Detlev HeinemannH, Spicherer Straße 48, D-86157 Augsburg, Germany ABSTRACT: The contribution of power production by PV systems and evaluate an approach to forecast regional PV power production. The forecast quality was investigated

  14. Wind Power on Native American Lands: Process and Progress (Poster)

    SciTech Connect (OSTI)

    Jimenez, A.; Flowers, L.; Gough, R.; Taylor, R.

    2005-05-01T23:59:59.000Z

    The United States is home to more than 700 American Indian tribes and Native Alaska villages and corporations located on 96 million acres. Many of these tribes and villages have excellent wind resources that could be commercially developed to meet their electricity needs or for electricity export. The Wind Powering America program engages Native Americans in wind energy development. This poster describes the process and progress of Wind Powering America's involvement with Native American wind energy projects.

  15. Global Wind Power Conference September 18-21, 2006, Adelaide, Australia Design and Operation of Power Systems with Large Amounts of Wind Power, first

    E-Print Network [OSTI]

    of Power Systems with Large Amounts of Wind Power, first results of IEA collaboration Hannele Holttinen1.holttinen@vtt.fi Abstract: An international forum for exchange of knowledge of power system impacts of wind power has been Systems with Large Amounts of Wind Power"will analyse existing case studies from different power systems

  16. WIND POWER PROGRAM WIND PROGRAM ACCOMPLISHMENTS U.S. Department...

    Office of Environmental Management (EM)

    capturing more wind than ever before through the installation of innovative offshore wind turbines and systems in U.S. waters, the Atmosphere to Electrons initiative which...

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

    SciTech Connect (OSTI)

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

    2014-11-01T23:59:59.000Z

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

  18. 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

  19. Concurrent Wind Cooling in Power Transmission Lines

    SciTech Connect (OSTI)

    Jake P Gentle

    2012-08-01T23:59:59.000Z

    Idaho National Laboratory and the Idaho Power Company, with collaboration from Idaho State University, have been working on a project to monitor wind and other environmental data parameters along certain electrical transmission corridors. The combination of both real-time historical weather and environmental data is being used to model, validate, and recommend possibilities for dynamic operations of the transmission lines for power and energy carrying capacity. The planned results can also be used to influence decisions about proposed design criteria for or upgrades to certain sections of the transmission lines.

  20. India Wind Power 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 SiteofEvaluatingGroup | OpenHunan Runhua New EnergyIT PowerImagineWind Power Ltd Jump to:

  1. Contribution to the Chapter on Wind Power Energy Technology

    E-Print Network [OSTI]

    turbines, are being implemented across all wind energy countries. The cost of wind-generated electricityContribution to the Chapter on Wind Power Energy Technology Perspectives 2008 Jørgen Lemming; Poul; Poul Erik Morthorst; Niels-Erik Clausen; Peter Hjuler Jensen Title: Contribution to the Chapter on Wind

  2. Operating the Irish Power System with Increased Levels of Wind Power

    E-Print Network [OSTI]

    Operating the Irish Power System with Increased Levels of Wind Power Aidan Tuohy, Student Member of Ireland. Using results from various studies performed on this system, it is shown that wind power of installed wind power will have implications for the operation of power systems. These will be seen

  3. 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

  4. New England Wind Forum: A Wind Powering America Project - Newsletter #6 - September 2010, (NEWF)

    SciTech Connect (OSTI)

    Grace, R.; Gifford, J.; Leeds, T.; Bauer, S.

    2010-09-01T23:59:59.000Z

    Wind Powering America program launched the New England Wind Forum (NEWF) in 2005 to provide a single comprehensive source of up-to-date, Web-based information on a broad array of wind energy issues pertaining to New England. The NEWF newsletter provides New England stakeholders with updates on wind energy development in the region.

  5. Scotrenewables Wind Power and Marine Power 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: WindRiegotec InternacionalhasASSciraWind Power and

  6. Comment on "Air Emissions Due to Wind and Solar Power" and Supporting Information

    E-Print Network [OSTI]

    Mills, Andrew D.

    2011-01-01T23:59:59.000Z

    Consulting, Analysis of Wind Generation Impact on ERCOTE. ; O’Malley, M. Wind generation, power system operation,E. ; O’Malley, M. Wind generation, power system operation,

  7. Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends: 2006

    E-Print Network [OSTI]

    2008-01-01T23:59:59.000Z

    on U.S. Wind Power Installation, Cost, and Performanceand Capital Costs Drive Wind Power Prices. . . . . 14Figure 18. Installed Wind Project Costs over Time Installed

  8. Analysis of Wind Power and Load Data at Multiple Time Scales

    E-Print Network [OSTI]

    Coughlin, Katie

    2011-01-01T23:59:59.000Z

    The spectrum of power from wind turbines. Journal of PowerAWEA 2010. American Wind Energy Association ProjectsErik and Jason Kemper. 2009. Wind Plant Ramping Behavior.

  9. 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.

  10. Stochastic Modeling of Multi-Area Wind Power Production

    E-Print Network [OSTI]

    Oren, Shmuel S.

    Stochastic Modeling of Multi-Area Wind Power Production Anthony Papavasiliou Department we present a stochastic model for multi-area wind production that is used for planning reserves model accounts for the inter-temporal and spatial dependencies of multi-area wind power production

  11. Ris-R-Report Power fluctuations from large wind farms -

    E-Print Network [OSTI]

    Abstract (max. 2000 char.): Experience from power system operation with the first large offshore wind farm acquired at the two large offshore wind farms in Denmark are applied to validate the models. FinallyRisø-R-Report Power fluctuations from large wind farms - Final report Poul Sørensen, Pierre Pinson

  12. Dynamic wind turbine models in power system simulation tool

    E-Print Network [OSTI]

    Dynamic wind turbine models in power system simulation tool DIgSILENT Anca D. Hansen, Florin Iov Iov, Poul Sørensen, Nicolaos Cutululis, Clemens Jauch, Frede Blaabjerg Title: Dynamic wind turbine system simulation tool PowerFactory DIgSILENT for different wind turbine concepts. It is the second

  13. FEED-IN TARIFFS AND OFFSHORE WIND POWER DEVELOPMENT

    E-Print Network [OSTI]

    Firestone, Jeremy

    FEED-IN TARIFFS AND OFFSHORE WIND POWER DEVELOPMENT Prepared by Jon Lilley, Blaise Sheridan, Dawn.......................................................................................................................... 25 FERC Clarification as Applied to Offshore Wind........................................................................................................................ 28 #12; 3 Feed-in Tariffs and Offshore Wind Power Development Prepared Pursuant to DOE Grant Em

  14. Electric power from offshore wind via synoptic-scale interconnection

    E-Print Network [OSTI]

    Firestone, Jeremy

    Electric power from offshore wind via synoptic-scale interconnection Willett Kemptona,1 , Felipe M regional estimate, Kempton et al. (2) calculated that two-thirds of the offshore wind power off the U in the U.S. Atlantic region is already underway. Fig. 1 shows as black squares offshore wind developments

  15. The Potential Wind Power Resource in Australia: A New Perspective*

    E-Print Network [OSTI]

    The Potential Wind Power Resource in Australia: A New Perspective* Willow Hallgren, Udaya Bhaskar: globalchange@mit.edu Website: http://globalchange.mit.edu/ #12;The Potential Wind Power Resource in Australia density, and analyzes the variation of these characteristics with current and potential wind turbine hub

  16. The Potential Wind Power Resource in Australia: A New Perspective

    E-Print Network [OSTI]

    The Potential Wind Power Resource in Australia: A New Perspective Willow Hallgren, Udaya Bhaskar;1 The Potential Wind Power Resource in Australia: A New Perspective Willow Hallgren* , Udaya Bhaskar Gunturu intermittency can potentially be mitigated by the aggregation of geographically dispersed wind farms. Our

  17. System-Wide Emissions Implications of Increased Wind Power Penetration

    E-Print Network [OSTI]

    Kemner, Ken

    of incorporating wind energy into the electric power system. We present a detailed emissions analysis based on comprehensive modeling of power system operations with unit commitment and economic dispatch for different wind of both cycling and start-ups of thermal power plants in analyzing emissions from an electric power system

  18. The Political Economy of Wind Power in China

    E-Print Network [OSTI]

    Swanson, Ryan Landon

    2011-01-01T23:59:59.000Z

    plants each week,? and wind power‘s current share of total electricity generationplants, an examination of China‘s efforts to integrate wind power into its electricity generationelectricity generation mix. It is important to note that in 2009, coal-fired power plants

  19. Low-Maintenance Wind Power System

    E-Print Network [OSTI]

    Rasson, Joseph E

    2010-01-01T23:59:59.000Z

    Improved Vertical Axis Wind Turbine and Aerodynamic ControlDarrieus Vertical Axis Wind Turbines and Aerodynamic Control

  20. New England Wind Forum: A Wind Powering America Project, Newsletter #5 -- January 2010, Wind and Hydropower Technologies Program (WHTP)

    SciTech Connect (OSTI)

    Grace, R. C.; Gifford, J.

    2010-01-01T23:59:59.000Z

    Wind Powering America program launched the New England Wind Forum (NEWF) in 2005 to provide a single comprehensive source of up-to-date, Web-based information on a broad array of wind energy issues pertaining to New England. The NEWF newsletter provides New England stakeholders with updates on wind energy development in the region. In addition to regional updates, Issue #5 offers an interview with Angus King, former governor of Maine and co-founder of Independence Wind.

  1. Pitfalls of modeling wind power using Markov chains

    E-Print Network [OSTI]

    Kirtley, James L., Jr.

    An increased penetration of wind turbines have given rise to a need for wind speed/power models that generate realistic synthetic data. Such data, for example, might be used in simulations to size energy storage or spinning ...

  2. The Political Economy of Wind Power in China

    E-Print Network [OSTI]

    Swanson, Ryan Landon

    2011-01-01T23:59:59.000Z

    Policies for Renewable Energy-the example of China‘s windframework,? Energy Policy 32 (2004): ?PR China,? Global WindWind Power in China: Policy and development challenges,? Energy Policy

  3. The Potential Wind Power Resource in Australia: A New Perspective

    E-Print Network [OSTI]

    Hallgren, Willow

    Australia is considered to have very good wind resources, and the utilization of this renewable energy resource is increasing. Wind power installed capacity increased by 35% from 2006 to 2011 and is predicted to account ...

  4. The Potential Wind Power Resource in Australia: A New Perspective

    E-Print Network [OSTI]

    Hallgren, Willow

    Australia’s wind resource is considered to be very good, and the utilization of this renewable energy resource is increasing rapidly: wind power installed capacity increased by 35% from 2006 to 2011 and is predicted to ...

  5. Synoptic and local influences on boundary layer processes, with an application to California wind power

    E-Print Network [OSTI]

    Mansbach, David K.

    2010-01-01T23:59:59.000Z

    maps showing locations of wind power conversion facilities,of US winds and wind power at 80 m derived fromEvaluation of global wind power. Journal of Geo- physical

  6. Wind: wind power density GIS data at 50m above ground and 1km...

    Open Energy Info (EERE)

    GIS ... Dataset Activity Stream Wind: wind power density GIS data at 50m above ground and 1km resolution for Ghana from NREL (Abstract):  Raster GIS data, exported as BIL...

  7. Wind: wind power density GIS data at 50m above ground and 1km...

    Open Energy Info (EERE)

    file, 50 m wind power density for eastern China. (Purpose): To provide information on the wind resource potential in eastern China. Values range from 0 to 3079 Wm2. (Supplemental...

  8. The Political Economy of Wind Power in China

    E-Print Network [OSTI]

    Swanson, Ryan Landon

    2011-01-01T23:59:59.000Z

    the risk of default on power purchase contracts [being] oneon Supervision of Power-Grid Enterprise Purchases of Fullgrid companies purchase wind power at the price fixed by the

  9. Wind Power Variability, Its Cost, and Effect on Power Plant Emissions

    E-Print Network [OSTI]

    Wind Power Variability, Its Cost, and Effect on Power Plant Emissions A Dissertation Submitted The recent growth in wind power is transforming the operation of electricity systems by introducing. As a result, system operators are learning in real-time how to incorporate wind power and its variability

  10. Heilongjiang Lishu 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 REPORTEnergyFarms AHefei Sungrow Power Supply Co Ltd SPSLishu Wind

  11. Padoma Wind Power 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 WindEnergy InformationPadoma

  12. Northwestern 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 beingZealand Jump to: navigation, searchOfRoseConcerns Jumpsource History ViewTexas: EnergyWind Power Jump to:

  13. Shiloh Wind Power 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 < RAPID‎ |Rippey JumpAirPower Partners WindSherbino 2ShikunIII

  14. CECIC Wind Power Zhangbei | 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 Wind Power Company

  15. Moraine Wind Power 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, searchOfRose BendMiasole IncMinutemanVistaZephyr) Jump to: navigation,Wind Power

  16. Neppel Wind Power 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, searchOfRoseConcerns Jump to:Neppel Wind Power Project Jump to: navigation,

  17. Laizhou Luneng 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 SiteofEvaluatingGroup |Jilin Zhongdiantou NewKorea PartsLLNLLaizhou Luneng Wind Power Jump to:

  18. Wind Power Energia | 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: navigation,

  19. Wind Power 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 directedAnnualProperty Edit withTianlinPapers Home Kyoung's pictureWind Power Energia Jump to:

  20. Desert 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 directedAnnualPropertyd8c-a9ae-f8521cbb8489 No revision hasda62829c05bGabbs ValleyWind Power Jump to:

  1. Fenner Wind Power 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-f8521cbb8489 NoEurope BV JumpFederal Highway AdministrationFellowsWind Power

  2. Wind Power: How Much, How Soon, and At What Cost?

    SciTech Connect (OSTI)

    Wiser, Ryan H; Hand, Maureen

    2010-01-01T23:59:59.000Z

    The global wind power market has been growing at a phenomenal pace, driven by favorable policies towards renewable energy and the improving economics of wind projects. On a going forward basis, utility-scale wind power offers the potential for significant reductions in the carbon footprint of the electricity sector. Specifically, the global wind resource is vast and, though accessing this potential is not costless or lacking in barriers, wind power can be developed at scale in the near to medium term at what promises to be an acceptable cost.

  3. Sizing Storage and Wind Generation Capacities in Remote Power Systems

    E-Print Network [OSTI]

    Victoria, University of

    Sizing Storage and Wind Generation Capacities in Remote Power Systems by Andy Gassner B Capacities in Remote Power Systems by Andy Gassner B.Sc., University of Wisconsin ­ Madison, 2003 Supervisory and small power systems. However, the variability due to the stochastic nature of the wind resource

  4. Ris-R-1257(EN) Isolated Systems with Wind Power

    E-Print Network [OSTI]

    energy in isolated communities. So far most studies of isolated systems with wind power have been case and economical feasibility of isolated power supply systems with wind energy. General guidelines and checklists project costs 24 5.5.2 Cost of Energy, COE 25 5.5.3 Value of Energy, VOE 25 Primary power supply 25

  5. QUALIFIED FORECAST OF ENSEMBLE POWER PRODUCTION BY SPATIALLY DISPERSED GRID-CONNECTED PV SYSTEMS

    E-Print Network [OSTI]

    Heinemann, Detlev

    QUALIFIED FORECAST OF ENSEMBLE POWER PRODUCTION BY SPATIALLY DISPERSED GRID- CONNECTED PV SYSTEMS: The contribution of power production by Photovoltaic (PV) systems to the electricity supply is constantly of the electricity grids and for energy trading. This paper presents an approach to predict regional PV power output

  6. Solar Power Forecasting at UC San Diego Jan Kleissl, Dept of Mechanical & Aerospace Engineering, UCSD

    E-Print Network [OSTI]

    Fainman, Yeshaiahu

    show 2 cloud layers. Vaisala Fig. 4: Observed solar power output (black line) and simulation (Fig. 4). Tier 3: Power output forecast As cloud related solar radiation reductions are observed algorithm to determine actual expected solar power output at each PV array over the hour ahead. #12;

  7. Optimization Online - The Worst-case Wind Power Scenario for ...

    E-Print Network [OSTI]

    German Morales-España

    2014-09-16T23:59:59.000Z

    Sep 16, 2014 ... The Worst-case Wind Power Scenario for Adaptive Robust Unit Commitment Problems. German Morales-España(gmorales ***at*** kth.se).

  8. Wind Power Siting: Public Acceptance and Land Use

    Wind Powering America (EERE)

    by the Alliance for Sustainable Energy, LLC. Wind Power Siting: Public Acceptance and Land Use Suzanne Tegen WINDExchange Webinar June 17, 2015 2 Overview * Current NREL Research *...

  9. Microsoft Word - Argonne_WindPowerForecasting_Report_Final_Nov...

    Office of Scientific and Technical Information (OSTI)

    1 , A. Botterud 2 , J. Wang 2 , and G. Conzelmann 2 1 Institute for Systems and Computer Engineering of Porto (INESC Porto) 2 Decision and Information Sciences Division, Argonne...

  10. 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

  11. 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

  12. 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+

  13. 20% Wind Energy by 2030 - Chapter 6: Wind Power Markets Summary...

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

    6: Wind Power Markets Summary Slides California: 20% by 2017 State renewable energy incentives Illinois: 15% by 2012 New York: 25% by 2013 Renewable portfolio standards (RPS) * 25...

  14. Maximum power tracking control scheme for wind generator systems

    E-Print Network [OSTI]

    Mena Lopez, Hugo Eduardo

    2008-10-10T23:59:59.000Z

    The purpose of this work is to develop a maximum power tracking control strategy for variable speed wind turbine systems. Modern wind turbine control systems are slow, and they depend on the design parameters of the turbine and use wind and/or rotor...

  15. Maximum power tracking control scheme for wind generator systems

    E-Print Network [OSTI]

    Mena, Hugo Eduardo

    2009-05-15T23:59:59.000Z

    The purpose of this work is to develop a maximum power tracking control strategy for variable speed wind turbine systems. Modern wind turbine control systems are slow, and they depend on the design parameters of the turbine and use wind and/or rotor...

  16. Wind Power Resource Assessment in Ohio and Puerto Rico

    E-Print Network [OSTI]

    Womeldorf, Carole

    Wind Power Resource Assessment in Ohio and Puerto Rico: A Motivational and Educational Tool Juan University, Athens, Ohio Abstract This paper presents an educational guide and example of a wind resource calculations. New data representing wind speed and direction for locations in Ohio and Puerto Rico

  17. Offshore Wind Power Experiences, Potential and Key Issues for

    E-Print Network [OSTI]

    offshore wind farms are installed in British, Swedish and Danish waters, and present-day costs in 2015, 2030 and 2050 14 3.1 Offshore wind farms under construction and in planning stage 14 3Offshore Wind Power Experiences, Potential and Key Issues for Deployment Jørgen Lemming, Poul Erik

  18. Maximum power tracking control scheme for wind generator systems 

    E-Print Network [OSTI]

    Mena, Hugo Eduardo

    2009-05-15T23:59:59.000Z

    The purpose of this work is to develop a maximum power tracking control strategy for variable speed wind turbine systems. Modern wind turbine control systems are slow, and they depend on the design parameters of the turbine and use wind and/or rotor...

  19. Maximum power tracking control scheme for wind generator systems 

    E-Print Network [OSTI]

    Mena Lopez, Hugo Eduardo

    2008-10-10T23:59:59.000Z

    The purpose of this work is to develop a maximum power tracking control strategy for variable speed wind turbine systems. Modern wind turbine control systems are slow, and they depend on the design parameters of the turbine and use wind and/or rotor...

  20. Fast Verification of Wind Turbine Power Summary of Project Results

    E-Print Network [OSTI]

    Fast Verification of Wind Turbine Power Curves: Summary of Project Results by: Cameron Brown ­ s equation on high frequency wind turbine measurement data sampled at one sample per second or more. The aim's Nordtank wind turbine at the Risø site, the practical application of this new method was tested

  1. Ex Post Analysis of Economic Impacts from Wind Power Development in U.S. Counties

    E-Print Network [OSTI]

    Brown, Jason P.

    2014-01-01T23:59:59.000Z

    use requirements of modern wind power plants in the United2002. Economic impacts of wind power in Kittitas County:Office, 2004. Renewable energy: Wind power’s contribution to

  2. 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.

  3. Use of Slip Ring Induction Generator for Wind Power Generation

    E-Print Network [OSTI]

    K Y Patil; D S Chavan

    Wind energy is now firmly established as a mature technology for electricity generation. There are different types of generators that can be used for wind energy generation, among which Slip ring Induction generator proves to be more advantageous. To analyse application of Slip ring Induction generator for wind power generation, an experimental model is developed and results are studied. As power generation from natural sources is the need today and variable speed wind energy is ample in amount in India, it is necessary to study more beneficial options for wind energy generating techniques. From this need a model is developed by using Slip ring Induction generator which is a type of Asynchronous generator.

  4. Power Performance Test Report for the SWIFT Wind Turbine

    SciTech Connect (OSTI)

    Mendoza, I.; Hur, J.

    2012-12-01T23:59:59.000Z

    This report summarizes the results of a power performance test that NREL conducted on the SWIFT wind turbine. This test was conducted in accordance with the International Electrotechnical Commission's (IEC) standard, Wind Turbine Generator Systems Part 12: Power Performance Measurements of Electricity Producing Wind Turbines, IEC 61400-12-1 Ed.1.0, 2005-12. However, because the SWIFT is a small turbine as defined by IEC, NREL also followed Annex H that applies to small wind turbines. In these summary results, wind speed is normalized to sea-level air density.

  5. Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends: 2006

    E-Print Network [OSTI]

    2008-01-01T23:59:59.000Z

    Western Wind, and Midwest Wind Energy. Table 4. Merger andHorizon) Noble Power CPV Wind Catamount Western Wind EnergyCoastal Wind Energy LLC Tierra Energy, LLC Renewable

  6. 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

  7. National-Scale Wind Resource Assessment for Power Generation (Presentation)

    SciTech Connect (OSTI)

    Baring-Gould, E. I.

    2013-08-01T23:59:59.000Z

    This presentation describes the current standards for conducting a national-scale wind resource assessment for power generation, along with the risk/benefit considerations to be considered when beginning a wind resource assessment. The presentation describes changes in turbine technology and viable wind deployment due to more modern turbine technology and taller towers and shows how the Philippines national wind resource assessment evolved over time to reflect changes that arise from updated technologies and taller towers.

  8. Surpassing Expectations: State of the U.S. Wind Power Market

    E-Print Network [OSTI]

    Bolinger, Mark A

    2009-01-01T23:59:59.000Z

    on U.S. Wind Power Installation, Cost, and Performancecontinued to put upward pressure on wind turbine costs,wind project costs, and wind power prices in 2007. Since

  9. How Do Wind and Solar Power Affect Grid Operations: The Western Wind and Solar Integration Study

    SciTech Connect (OSTI)

    Lew, D.; Milligan, M.; Jordan, G.; Freeman, L.; Miller, N.; Clark, K.; Piwko, R.

    2009-01-01T23:59:59.000Z

    The Western Wind and Solar Integration Study is one of the largest regional wind and solar integration studies to date, examining the operational impact of up to 35% wind, photovoltaics, and concentrating solar power on the WestConnect grid in Arizona, Colorado, Nevada, New Mexico, and Wyoming. This paper reviews the scope of the study, the development of wind and solar datasets, and the results to date on three scenarios.

  10. BPA supports wind power for the Pacific Northwest - Mar 2009...

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

    Northwest wind power boom is continuing, and much of this growth is occurring in the heart of the Bonneville Power Administration system. The agency now has more than 2,000...

  11. Modeling the Benefits of Storage Technologies to Wind Power

    SciTech Connect (OSTI)

    Sullivan, P.; Short, W.; Blair, N.

    2008-06-01T23:59:59.000Z

    Rapid expansion of wind power in the electricity sector is raising questions about how wind resource variability might affect the capacity value of wind farms at high levels of penetration. Electricity storage, with the capability to shift wind energy from periods of low demand to peak times and to smooth fluctuations in output, may have a role in bolstering the value of wind power at levels of penetration envisioned by a new Department of Energy report ('20% Wind by 2030, Increasing Wind Energy's Contribution to U.S. Electricity Supply'). This paper quantifies the value storage can add to wind. The analysis was done employing the Regional Energy Deployment System (ReEDS) model, formerly known as the Wind Deployment System (WinDS) model. ReEDS was used to estimate the cost and development path associated with 20% penetration of wind in the report. ReEDS differs from the WinDS model primarily in that the model has been modified to include the capability to build and use three storage technologies: pumped-hydroelectric storage (PHS), compressed-air energy storage (CAES), and batteries. To assess the value of these storage technologies, two pairs of scenarios were run: business-as-usual, with and without storage; 20% wind energy by 2030, with and without storage. This paper presents the results from those model runs.

  12. A Letter from Patrick Gilman: Wind Powering America Is Now Stakeholder Engagement and Outreach

    Broader source: Energy.gov [DOE]

    Patrick Gilman, Wind Energy Deployment manager, explains why Wind Powering America's name is in the process of being changed.

  13. Wind Power Development in the United States: Current Progress, Future Trends

    E-Print Network [OSTI]

    Wiser, Ryan H

    2009-01-01T23:59:59.000Z

    high levels of wind generation. Figure 5. Installed Windis that the increased wind generation offsets both coal andmuch higher levels of wind power generation than currently

  14. Wind Power Development in the United States: Current Progress, Future Trends

    E-Print Network [OSTI]

    Wiser, Ryan H

    2009-01-01T23:59:59.000Z

    supply curve for wind using cost and performance assumptionspressure on installed wind project costs while the industryon U.S. Wind Power Installation, Cost, and Performance

  15. Henan Mingdu Wind Power Co Ltd aka He Nan Ming Du Feng Dian Limited...

    Open Energy Info (EERE)

    Company) Place: Jiaozuo, Henan Province, China Sector: Wind energy Product: Wind turbine blades provider. References: Henan Mingdu Wind Power Co Ltd (aka He Nan Ming Du Feng...

  16. Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends: 2006

    E-Print Network [OSTI]

    2008-01-01T23:59:59.000Z

    Power, Exergy, U.S. Wind Force, Wind Capital Group,Developer enXco Navitas US Wind Force Atlantic Renewable

  17. Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends: 2006

    E-Print Network [OSTI]

    2008-01-01T23:59:59.000Z

    to Drive Wind Development. . . . . . . . . . . . . . .5 GE Wind Is the Dominant Turbine Manufacturer, with SiemensAnnual Report on U.S. Wind Power Installation, Cost, and

  18. Synoptic and local influences on boundary layer processes, with an application to California wind power

    E-Print Network [OSTI]

    Mansbach, David K.

    2010-01-01T23:59:59.000Z

    California o?shore wind energy potential. Renewable Energy,2008: Ex- ploring wind energy potential o? the Californiafor estimates of wind power potential. Journal of Applied

  19. Abstract--Forecasting of future electricity demand is very important for decision making in power system operation and

    E-Print Network [OSTI]

    Ducatelle, Frederick

    Abstract--Forecasting of future electricity demand is very important for decision making in power industry, accurate forecasting of future electricity demand has become an important research area for secure operation, management of modern power systems and electricity production in the power generation

  20. Wind Powering America's Wind for Schools Team Honored with Wirth...

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

    Second Quarter 2012 edition of the Wind Program R&D Newsletter. The University of Colorado at Denver and the Wirth Chair awarded the Energy Department's National Renewable Energy...

  1. The Impact of Wind Power Projects on Residential Property Values in the United States: A Multi-Site Hedonic Analysis

    E-Print Network [OSTI]

    Hoen, Ben

    2010-01-01T23:59:59.000Z

    2002) Economic Impacts of Wind Power in Kittitas County, WA.about Large Offshore Wind Power: Underlying Factors. EnergyOpinion on Offshore Wind Power - Interim Report. University

  2. Estimated global ocean wind power potential from QuikSCAT observations, accounting for turbine characteristics and siting

    E-Print Network [OSTI]

    Capps, Scott B; Zender, Charles S

    2010-01-01T23:59:59.000Z

    ZENDER: GLOBAL OCEAN WIND POWER POTENTIAL Serpetzoglou, E. ,Estimated global ocean wind power potential from QuikSCATEstimated global ocean wind power potential from QuikSCAT

  3. Power Forecasting for Plug-in Electric Vehicles

    E-Print Network [OSTI]

    Lavaei, Javad

    .........................................................................................................4 2.1 Power battery of EVs

  4. COE projection for the modular WARP{trademark} wind power system for wind farms and electric utility power transmission

    SciTech Connect (OSTI)

    Weisbrich, A.L. [ENECO, West Simsbury, CT (United States); Ostrow, S.L.; Padalino, J. [Raytheon Engineers and Constructors, New York, NY (United States)

    1995-09-01T23:59:59.000Z

    Wind power has emerged as an attractive alternative source of electricity for utilities. Turbine operating experience from wind farms has provided corroborating data of wind power potential for electric utility application. Now, a patented modular wind power technology, the Toroidal Accelerator Rotor Platform (TARP{trademark}) Windframe{trademark}, forms the basis for next generation megawatt scale wind farm and/or distributed wind power plants. When arranged in tall vertically clustered TARP{trademark} module stacks, such power plant units are designated Wind Amplified Rotor Platform (WARP{trademark}) Systems. While heavily building on proven technology, these systems are projected to surpass current technology windmills in terms of performance, user-friendly operation and ease of maintenance. In its unique generation and transmission configuration, the WARP{trademark}-GT System combines both electricity generation through wind energy conversion and electric power transmission. Furthermore, environmental benefits include dramatically less land requirement, architectural appearance, lower noise and EMI/TV interference, and virtual elimination of bird mortality potential. Cost-of-energy (COE) is projected to be from under $0.02/kWh to less than $0.05/kWh in good to moderate wind resource sites.

  5. Comment on "Air Emissions Due to Wind and Solar Power" and Supporting Information

    E-Print Network [OSTI]

    Mills, Andrew D.

    2011-01-01T23:59:59.000Z

    due to wind and solar power. Environ. Sci. Technol. (2)Emissions Due to Wind and Solar Power” Andrew Mills, ? , †due to wind and solar power. Environ. Sci. Technol. (2)

  6. Analysis of Wind Power and Load Data at Multiple Time Scales

    E-Print Network [OSTI]

    Coughlin, Katie

    2011-01-01T23:59:59.000Z

    Huei. 2005. Primer on Wind Power for Utility Applications.Wan, Yih-Huei. 2004. Wind Power Plant Behaviors: Analysesof Long-Term Wind Power Data. National Renewable Energy Lab

  7. Surpassing Expectations: State of the U.S. Wind Power Market

    E-Print Network [OSTI]

    Bolinger, Mark A

    2009-01-01T23:59:59.000Z

    The Annual Report on U.S. Wind Power Installation, Cost, andState of the U.S. Wind Power Market Intro Sidebar: The U.S.Annual Report on U.S. Wind Power Installation, Cost, and

  8. Yinhe Avantis Wind Power Co Ltd formerly known as Avantis Yinhe...

    Open Energy Info (EERE)

    Yinhe Avantis Wind Power Co Ltd formerly known as Avantis Yinhe Wind Power Co Ltd Jump to: navigation, search Name: Yinhe Avantis Wind Power Co Ltd (formerly known as Avantis Yinhe...

  9. Power Control and Optimization of Photovoltaic and Wind Energy Conversion Systems /

    E-Print Network [OSTI]

    Ghaffari, Azad

    2013-01-01T23:59:59.000Z

    be realized by capturing wind power at altitudes over the2011. [2] ——, “High altitude wind power systems: A survey onOckels, “Optimal cross-wind towing and power generation with

  10. Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends: 2006

    E-Print Network [OSTI]

    2008-01-01T23:59:59.000Z

    Annual Report on U.S. Wind Power Installation, Cost, and3 U.S. Wind Power Capacity Increased by 27% inAre Significant. . . . . . . 9 Wind Power Prices Are Up in

  11. Wind Power Development in the United States: Current Progress, Future Trends

    E-Print Network [OSTI]

    Wiser, Ryan H

    2009-01-01T23:59:59.000Z

    Annual Report on U.S. Wind Power Installation, Cost, andWind Power Development in the United States: Current94720 Abstract: The U.S. wind power industry is in an era of

  12. Analysis of Wind Power Generation of Texas

    E-Print Network [OSTI]

    Liu, Z.; Haberl, J.; Subbarao, K.; Baltazar, J. C.

    from Jul 2002 to Jan 2003 Degradation Analysis - On average, no degradation observed for nine wind farms analyzed over 4-year period. Application of Method 1 to New Site- Sweetwater I Wind Farm ? Energy Systems Laboratory, Texas A&M University Page 3...&M University Page 10 Weather Data: NOAA- ABI 1999 and 2005 Hourly Wind Speed NOAA -ABI Hourly Wind Speed -1999 0 10 20 30 40 Jan-99 Feb-99 M ar-99 Apr-99 M ay-99 Jun-99 Jul-99 Aug-99 Sep-99 Oct-99 Nov-99 Dec-99 W in d Spe ed [m ph ] NOAA -ABI Hourly Wind...

  13. Limits to the power density of very large wind farms

    E-Print Network [OSTI]

    Nishino, Takafumi

    2013-01-01T23:59:59.000Z

    A simple analysis is presented concerning an upper limit of the power density (power per unit land area) of a very large wind farm located at the bottom of a fully developed boundary layer. The analysis suggests that the limit of the power density is about 0.38 times $\\tau_{w0}U_{F0}$, where $\\tau_{w0}$ is the natural shear stress on the ground (that is observed before constructing the wind farm) and $U_{F0}$ is the natural or undisturbed wind speed averaged across the height of the farm to be constructed. Importantly, this implies that the maximum extractable power from such a very large wind farm will not be proportional to the cubic of the wind speed at the farm height, or even the farm height itself, but be proportional to $U_{F0}$.

  14. Wind Power Price Trends in the United States

    SciTech Connect (OSTI)

    Bolinger, Mark; Wiser, Ryan

    2009-07-15T23:59:59.000Z

    For the fourth year in a row, the United States led the world in adding new wind power capacity in 2008, and also surpassed Germany to take the lead in terms of cumulative installed wind capacity. The rapid growth of wind power in the U.S. over the past decade (Figure 1) has been driven by a combination of increasingly supportive policies (including the Federal production tax credit (PTC) and a growing number of state renewables portfolio standards), uncertainty over the future fuel costs and environmental liabilities of natural gas and coal-fired power plants, and wind's competitive position among generation resources. This article focuses on just the last of these drivers - i.e., trends in U.S. wind power prices - over the period of strong capacity growth since 1998.

  15. The Great Plains Wind Power Test Facility

    SciTech Connect (OSTI)

    Schroeder, John

    2014-01-31T23:59:59.000Z

    This multi-year, multi-faceted project was focused on the continued development of a nationally-recognized facility for the testing, characterization, and improvement of grid-connected wind turbines, integrated wind-water desalination systems, and related educational and outreach topics. The project involved numerous faculty and graduate students from various engineering departments, as well as others from the departments of Geosciences (in particular the Atmospheric Science Group) and Economics. It was organized through the National Wind Institute (NWI), which serves as an intellectual hub for interdisciplinary and transdisciplinary research, commercialization and education related to wind science, wind energy, wind engineering and wind hazard mitigation at Texas Tech University (TTU). Largely executed by an academic based team, the project resulted in approximately 38 peer-reviewed publications, 99 conference presentations, the development/expansion of several experimental facilities, and two provisional patents.

  16. Systems and methods for an integrated electrical sub-system powered by wind energy

    DOE Patents [OSTI]

    Liu, Yan (Ballston Lake, NY); Garces, Luis Jose (Niskayuna, NY)

    2008-06-24T23:59:59.000Z

    Various embodiments relate to systems and methods related to an integrated electrically-powered sub-system and wind power system including a wind power source, an electrically-powered sub-system coupled to and at least partially powered by the wind power source, the electrically-powered sub-system being coupled to the wind power source through power converters, and a supervisory controller coupled to the wind power source and the electrically-powered sub-system to monitor and manage the integrated electrically-powered sub-system and wind power system.

  17. 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

  18. Remote sensing for wind power potential: a prospector's handbook

    SciTech Connect (OSTI)

    Wade, J.E.; Maule, P.A.; Bodvarsson, G.; Rosenfeld, C.L.; Woolley, S.G.; McClenahan, M.R.

    1983-02-01T23:59:59.000Z

    Remote sensing can aid in identifying and locating indicators of wind power potential from the terrestrial, marine, and atmospheric environments (i.e.: wind-deformed trees, white caps, and areas of thermal flux). It is not considered as a tool for determining wind power potential. A wide variety of remotely sensed evidence is described in terms of the scale at which evidence of wind power can be identified, and the appropriate remote sensors for finding such evidence. Remote sensing can be used for regional area prospecting using small-scale imagery. The information from such small-scale imagery is most often qualitative, and if it is transitory, examination of a number of images to verify presistence of the feature may be required. However, this evidence will allow rapid screening of a large area. Medium-scale imagery provides a better picture of the evidence obtained from small-scale imagery. At this level it is best to use existing imagery. Criteria relating to land use, accessibility, and proximity of candidate sites to nearby transmission lines can also be effectively evaluated from medium-scale imagery. Large-scale imagery provides the most quantitative evidence of the strength of wind. Wind-deformed trees can be identified at a large number of sites using only a few hours in locally chartered aircraft. A handheld 35mm camera can adequately document any evidence of wind. Three case studies that employ remote sensing prospecting techniques are described. Based on remotely sensed evidence, the wind power potential in three geographically and climatically diverse areas of the United States is estimated, and the estimates are compared to actual wind data in those regions. In addition, the cost of each survey is discussed. The results indicate that remote sensing for wind power potential is a quick, cost effective, and fairly reliable method for screening large areas for wind power potential.

  19. Fault Analysis at a Wind Power Plant for One Year of Observation: Preprint

    SciTech Connect (OSTI)

    Muljadi, E.; Mills, Z.; Foster, R.; Conto, J.; Ellis, A.

    2008-07-01T23:59:59.000Z

    This paper analyzes the fault characteristics observed at a wind power plant, and the behavior of the wind power plant under fault events.

  20. Building a New Energy Future with Wind Power (Revised) (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2013-01-01T23:59:59.000Z

    This fact sheet provides an overview of the U.S. Department of Energy's Wind and Water Power Program's wind power research activities.

  1. FOUR ESSAYS ON OFFSHORE WIND POWER POTENTIAL, DEVELOPMENT, REGULATORY FRAMEWORK, AND INTEGRATION

    E-Print Network [OSTI]

    Firestone, Jeremy

    FOUR ESSAYS ON OFFSHORE WIND POWER POTENTIAL, DEVELOPMENT, REGULATORY FRAMEWORK, AND INTEGRATION 2010 Amardeep Dhanju All Rights Reserved #12;FOUR ESSAYS ON OFFSHORE WIND POWER POTENTIAL, DEVELOPMENT

  2. Wind power manufacturing and supply chain summit USA.

    SciTech Connect (OSTI)

    Hill, Roger Ray

    2010-12-01T23:59:59.000Z

    The area of wind turbine component manufacturing represents a business opportunity in the wind energy industry. Modern wind turbines can provide large amounts of electricity, cleanly and reliably, at prices competitive with any other new electricity source. Over the next twenty years, the US market for wind power is expected to continue to grow, as is the domestic content of installed turbines, driving demand for American-made components. Between 2005 and 2009, components manufactured domestically grew eight-fold to reach 50 percent of the value of new wind turbines installed in the U.S. in 2009. While that growth is impressive, the industry expects domestic content to continue to grow, creating new opportunities for suppliers. In addition, ever-growing wind power markets around the world provide opportunities for new export markets.

  3. Final Scientific Report - Wind Powering America State Outreach Project

    SciTech Connect (OSTI)

    Sinclair, Mark; Margolis, Anne

    2012-02-01T23:59:59.000Z

    The goal of the Wind Powering America State Outreach Project was to facilitate the adoption of effective state legislation, policy, finance programs, and siting best practices to accelerate public acceptance and development of wind energy. This was accomplished by Clean Energy States Alliance (CESA) through provision of informational tools including reports and webinars as well as the provision of technical assistance to state leaders on wind siting, policy, and finance best practices, identification of strategic federal-state partnership activities for both onshore and offshore wind, and participation in regional wind development collaboratives. The Final Scientific Report - Wind Powering America State Outreach Project provides a summary of the objectives, activities, and outcomes of this project as accomplished by CESA over the period 12/1/2009 - 11/30/2011.

  4. WPA Omnibus Award MT Wind Power Outreach

    SciTech Connect (OSTI)

    Brian Spangler, Manager Energy Planning and Renewables

    2012-01-30T23:59:59.000Z

    The objective of this grant was to further the development of Montanaâ??s vast wind resources for small, medium, and large scale benefits to Montana and the nation. This was accomplished through collaborative work with wind industry representatives, state and local governments, the agricultural community, and interested citizens. Through these efforts MT Dept Environmental Quality (DEQ) was able to identify development barriers, educate and inform citizens, as well as to participate in regional and national dialogue that will spur the development of wind resources. The scope of DEQâ??s wind outreach effort evolved over the course of this agreement from the development of the Montana Wind Working Group and traditional outreach efforts, to the current focus on working with the stateâ??s university system to deliver a workforce trained to enter the wind industry.

  5. Sandia National Laboratories: Wind & Water Power Newsletter

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

    reports, papers, and events published by Sandia. This monthly newsletter is intended for wind industry partners, stakeholders, universities and potential partners. This issue...

  6. World-Unique Wind Facilities Designed to protect us from storms, harness the power of wind and

    E-Print Network [OSTI]

    Denham, Graham

    World-Unique Wind Facilities Designed to protect us from storms, harness the power of wind and develop sustainable cities, the Wind Engineering, Energy and the Environment (WindEEE) Institute at Western University is home to the world's first three-dimensional wind-testing chamber. Its facilities

  7. Effect of ocean surface currents on wind stress, heat flux, and wind power input to the ocean

    E-Print Network [OSTI]

    Thompson, LuAnne

    Effect of ocean surface currents on wind stress, heat flux, and wind power input to the ocean, J. T., and L. Thompson (2006), Effect of ocean surface currents on wind stress, heat flux, and wind power input to the ocean, Geophys. Res. Lett., 33, L09604, doi:10.1029/2006GL025784. 1. Introduction [2

  8. EA-1726: Kahuku Wind Power, LLC Wind Power Generation Facility, O'ahu, HI

    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 U.S.ContaminationJuly 2011D APPENDIXKahuku Wind Power, LLC, Construction of the|

  9. Wind for Schools Project Power System Brief, Wind Powering America Fact Sheet Series

    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 Printable80 mPilot ProjectWind Powering

  10. Datang Jilin Wind Power Stockholding Co Ltd Formerly Jilin Noble Wind Power

    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:WindOilCowalJilin Power Generation

  11. Wind Power Today, 2010, Wind and Water Power Program (WWPP) | Department of

    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 DensityEnergy U.S.-China Electric VehicleCenters | Department ofofto PurchaseAprilWind PowerEnergy

  12. Wind Power Price Trends in the United States: Struggling to Remain Competitive in the Face of Strong Growth

    E-Print Network [OSTI]

    Bolinger, Mark A

    2009-01-01T23:59:59.000Z

    timeframe. Projected Wind Generation as % of Electricityrepresent the cost of wind generation. Wind Power Price (time-variability of wind generation is often such that its

  13. Estimated global ocean wind power potential from QuikSCAT observations, accounting for turbine characteristics and siting

    E-Print Network [OSTI]

    Capps, Scott B; Zender, Charles S

    2010-01-01T23:59:59.000Z

    Wind Energy Association (2009), American Wind Energy Asso-ciation annual wind industry report: Year ending 2008,2005), Evaluation of global wind power, J. Geophys. Res. ,

  14. Review of Historical and Modern Utilization of Wind Power Publications Department

    E-Print Network [OSTI]

    UTILIZATION TODAY WIND POWER TECHNOLOGY q Modern wind turbine technology q Concepts COST OF WIND ENERGY TYPES costs BEGINNERS GUIDE TO WIND ENERGY STUDIES q Selected text books on wind energy and wind turbines WECS - Wind Energy Conversion Systems. To co-ordinate the many terms derived from ancient Teutonic

  15. Final Technical Report - Kotzebue Wind Power Project - Volume II

    SciTech Connect (OSTI)

    Rana Zucchi, Global Energy Concepts, LLC; Brad Reeve, Kotzebue Electric Association; DOE Project Officer - Doug Hooker

    2007-10-31T23:59:59.000Z

    The Kotzebue Wind Power Project is a joint undertaking of the U.S. Department of Energy (DOE); Kotzebue Electric Association (KEA); and the Alaska Energy Authority (AEA). The goal of the project is to develop, construct, and operate a wind power plant interconnected to a small isolated utility grid in an arctic climate in Northwest Alaska. The primary objective of KEA’s wind energy program is to bring more affordable electricity and jobs to remote Alaskan communities. DOE funding has allowed KEA to develop a multi-faceted approach to meet these objectives that includes wind project planning and development, technology transfer, and community outreach. The first wind turbines were installed in the summer of 1997 and the newest turbines were installed in the spring of 2007. The total installed capacity of the KEA wind power project is 1.16 MW with a total of 17 turbines rated between 65 kW and 100 kW. The operation of the wind power plant has resulted in a wind penetration on the utility system in excess of 35% during periods of low loads. This document and referenced attachments are presented as the final technical report for the U.S. Department of Energy (DOE) grant agreement DE-FG36-97GO10199. Interim deliverables previously submitted are also referenced within this document and where reasonable to do so, specific sections are incorporated in the report or attached as appendices.

  16. Proceedings of National Avian-Wind Power Planning Meeting IV

    SciTech Connect (OSTI)

    NWCC Avian Subcommittee

    2001-05-01T23:59:59.000Z

    OAK-B135 The purpose of the fourth meeting was to (1) share research and update research conducted on avian wind interactions (2) identify questions and issues related to the research results, (3) develop conclusions about some avian/wind power issues, and (4) identify questions and issues for future avian research.

  17. Ris-R-1256(EN) Isolated Systems with Wind Power

    E-Print Network [OSTI]

    of methods and guidelines rather than "universal solutions" for the use of wind energy in isolated the technical and economical feasibility of isolated power supply systems with wind energy. As a part of the project the following tasks were carried out: Review of literature, field measurements in Egypt

  18. Understanding Inertial and Frequency Response of Wind Power Plants: Preprint

    SciTech Connect (OSTI)

    Muljadi, E.; Gevorgian, V.; Singh, M.; Santoso, S.

    2012-07-01T23:59:59.000Z

    The objective of this paper is to analyze and quantify the inertia and frequency responses of wind power plants with different wind turbine technologies (particularly those of fixed speed, variable slip with rotor-resistance controls, and variable speed with vector controls).

  19. Electrical Collection and Transmission Systems for Offshore Wind Power: Preprint

    SciTech Connect (OSTI)

    Green, J.; Bowen, A.; Fingersh, L.J.; Wan, Y.

    2007-03-01T23:59:59.000Z

    The electrical systems needed for offshore wind farms to collect power from wind turbines--and transmit it to shore--will be a significant cost element of these systems. This paper describes the development of a simplified model of the cost and performance of such systems.

  20. Execution Version POWER PURCHASE AGREEMENT

    E-Print Network [OSTI]

    Firestone, Jeremy

    ") and BLUEWATER WIND DELAWARE LLC ("Seller") June 23, 2008 #12;Execution Version POWER PURCHASE AGREEMENT TableExecution Version POWER PURCHASE AGREEMENT between DELMARVA POWER & LIGHT COMPANY ("Buyer 3.5 Energy Forecasts, Scheduling and Balancing.......................................... 40 3

  1. EFFECT OF PITCH CONTROL AND POWER CONDITIONING ON POWER QUALITY OF VARIABLE SPEED WIND TURBINE GENERATORS

    E-Print Network [OSTI]

    EFFECT OF PITCH CONTROL AND POWER CONDITIONING ON POWER QUALITY OF VARIABLE SPEED WIND TURBINE), Curtin University of Technology, WA Abstract: Variable speed wind turbine generators provide the opportunity to capture more power than fixed speed turbines. However the variable speed machine output can

  2. Variability of wind power near Oklahoma City and implications for siting of wind turbines

    SciTech Connect (OSTI)

    Kessler, E.; Eyster, R.

    1987-09-01T23:59:59.000Z

    Data from five sites near Oklahoma City were examined to assess wind power availability. Wind turbines of identical manufacture were operated at three of the sites, one of which was also equipped with anemometers on a 100-ft tower. Comprehensive anemometric data were available from the other two sites. The study indicates that the average wind speed varies substantially over Oklahoma's rolling plains, which have often been nominally regarded as flat for purposes of wind power generation. Average wind differences may be as much as 5 mph at 20 ft above ground level, and 7 mph at 100 ft above ground level for elevation differences of about 200 ft above mean sea level, even in the absence of substantial features of local terrain. Local altitude above mean sea level seems to be as influential as the shape of local terrain in determining the average wind speed. The wind turbine used at a meteorologically instrumented site in the study produced the power expected from it for the wind regime in which it was situated. The observed variations of local wind imply variations in annual kWh of as much as a factor of four between identical turbines located at similar heights above ground level in shallow valleys and on hilltops or elevated extended flat areas. 17 refs., 39 figs., 11 tabs.

  3. A Framework to Determine the Probability Density Function for the Output Power of Wind Farms

    E-Print Network [OSTI]

    Liberzon, Daniel

    A Framework to Determine the Probability Density Function for the Output Power of Wind Farms Sairaj to the power output of a wind farm while factoring in the availability of the wind turbines in the farm availability model for the wind turbines, we propose a method to determine the wind-farm power output pdf

  4. Wholesale Electricity Price Forecast This appendix describes the wholesale electricity price forecast of the Fifth Northwest Power

    E-Print Network [OSTI]

    Wholesale Electricity Price Forecast This appendix describes the wholesale electricity price as traded on the wholesale, short-term (spot) market at the Mid-Columbia trading hub. This price represents noted. BASE CASE FORECAST The base case wholesale electricity price forecast uses the Council's medium

  5. Wind power on BPA system sets another new record

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

    RELEASE Tuesday, March 20, 2012 CONTACT: Mike Hansen, BPA 503-230-4328 or 503-230-5131 Wind power on BPA system sets another new record The renewable resource passes 4,000...

  6. Sandia National Laboratories: grid-tied wind-power inverters

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

    wind-power inverters Sandia, DOE Energy Storage Program, GeneSiC Semiconductor, U.S. Army ARDEC: Ultra-High-Voltage Silicon Carbide Thyristors On March 29, 2013, in Capabilities,...

  7. New Report Evaluates Impacts of DOE's Wind Powering America Initiative...

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

    Department of Energy (DOE) in 1999, was to facilitate a rapid increase in U.S. wind power capacity by engaging in activities that address barriers to deployment on national,...

  8. accurate wind power: Topics by E-print Network

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

    Plant in Iran will be studied, in this article, focus is made mostly on computerized simulation of power plant sites for optimized configuration of wind farm turbines by using...

  9. aggregated wind power: Topics by E-print Network

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

    Plant in Iran will be studied, in this article, focus is made mostly on computerized simulation of power plant sites for optimized configuration of wind farm turbines by using...

  10. QER- Comment of Oceti Sakowin Sioux Wind Power Project

    Broader source: Energy.gov [DOE]

    Dear Secretariat: Attached please find the Comments of the Oceti Sakowin Sioux Wind Power Project, for inclusion in the record of the QER. If any questions, please direct to the undersigned.

  11. The Political Economy of Wind Power in China

    E-Print Network [OSTI]

    Swanson, Ryan Landon

    2011-01-01T23:59:59.000Z

    farms. For example, the Inner Mongolia Power Company, whichoperates in western Inner Mongolia and has access to some ofstrong winds in Inner Mongolia, China‘s FIT may provide high

  12. Impact of Increasing Distributed Wind Power and Wind Turbine Siting on Rural Distribution Feeder Voltage Profiles: Preprint

    SciTech Connect (OSTI)

    Allen, A.; Zhang, Y. C.; Hodge, B. M.

    2013-09-01T23:59:59.000Z

    Many favorable wind energy resources in North America are located in remote locations without direct access to the transmission grid. Building transmission lines to connect remotely-located wind power plants to large load centers has become a barrier to increasing wind power penetration in North America. By connecting utility-sized megawatt-scale wind turbines to the distribution system, wind power supplied to consumers could be increased greatly. However, the impact of including megawatt-scale wind turbines on distribution feeders needs to be studied. The work presented here examined the impact that siting and power output of megawatt-scale wind turbines have on distribution feeder voltage. This is the start of work to present a general guide to megawatt-scale wind turbine impact on the distribution feeder and finding the amount of wind power that can be added without adversely impacting the distribution feeder operation, reliability, and power quality.

  13. Wind Powering America: A Key Influence on U.S. Wind Market (Fact Sheet)

    SciTech Connect (OSTI)

    O'Dell, K.

    2013-09-01T23:59:59.000Z

    This fact sheet summarizes an evaluation of the effectiveness of the Wind Powering America initiative conducted by an independent consultant funded by the U.S. Department of Energy.

  14. Sinomatech Wind Power Blade aka Sinoma Science Technology Wind Turbine

    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:Shrenik Industries Jump to:Simran Wind Project

  15. NREL: Wind Research - Wind and Water Power Fact Sheets

    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 Possible for Renewable Energy: GridTruck Platooning Testing Photofrom U.S.6SiteUtility-ScaleWind

  16. Wind Powering America Hosts Fifth Annual Wind for Schools Summit |

    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 DensityEnergy U.S.-China Electric VehicleCenters | Department ofofto PurchaseAprilWind

  17. Wind Powering America Webinar: Wind and Wildlife Interactions | Department

    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 DensityEnergy U.S.-China Electric VehicleCenters | Department ofofto PurchaseAprilWindFuture Trends |of

  18. MAST/GEOG 667: Wind Power Meteorology Fall 2013, 3 credit hours

    E-Print Network [OSTI]

    Delaware, University of

    to understand onshore, offshore, and airborne wind power. Topics include: forces affecting-level winds: Pressure Gradient Force and Coriolis (pressure surfaces, geostrophic flowMAST/GEOG 667: Wind Power Meteorology Fall 2013, 3 credit hours 1

  19. Ex post analysis of economic impacts from wind power development in U.S. counties

    E-Print Network [OSTI]

    Brown, Jason P

    2014-01-01T23:59:59.000Z

    2011) Figure 1. Location of Wind Power Development in theUnited States Figure 2: U.S. Wind Resource Map (Source:Resource Potential for Wind Capacity (Power Class 3-7, MW)

  20. Surpassing Expectations: State of the U.S. Wind Power Market

    E-Print Network [OSTI]

    Bolinger, Mark A

    2009-01-01T23:59:59.000Z

    The Annual Report on U.S. Wind Power Installation, Cost, andExpectations: State of the U.S. Wind Power Market IntroSidebar: The U.S. wind industry experienced unprecedented

  1. Examining the Variability of Wind Power Output in the Regulation Time Frame: Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Shedd, S.; Florita, A.

    2012-08-01T23:59:59.000Z

    This work examines the distribution of changes in wind power for different time scales in the regulation time frame as well as the correlation of changes in power output for individual wind turbines in a wind plant.

  2. Transient Stability Assessment of Power System with Large Amount of Wind Power Penetration: the

    E-Print Network [OSTI]

    Bak, Claus Leth

    the transient stability. In Denmark, the onshore and offshore wind farms are connected to distribution system and transmission system respectively. The control and protection methodologies of onshore and offshore wind farms definitely affect the transient stability of power system. In this paper, the onshore and offshore wind farms

  3. Water Power for a Clean Energy Future (Fact Sheet), Wind and...

    Energy Savers [EERE]

    Water Power for a Clean Energy Future (Fact Sheet), Wind and Water Power Program (WWPP) Water Power for a Clean Energy Future (Fact Sheet), Wind and Water Power Program (WWPP) This...

  4. Federal Incentives for Wind Power (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2013-05-01T23:59:59.000Z

    This fact sheet describes the federal incentives available as of April 2013 that encourage increased development and deployment of wind energy technologies, including research grants, tax incentives, and loan programs.

  5. REAP Islanded Grid Wind Power Conference

    Broader source: Energy.gov [DOE]

    Hosted by Renewable Energy Alaska Project, this three-day conference will show attendees how to learn, network, and share information on wind systems in island and islanded grid environments through expert panel discussions, stakeholder dialogue, and training.

  6. The Wind Integration National Dataset (WIND) toolkit (Presentation)

    SciTech Connect (OSTI)

    Caroline Draxl: NREL

    2014-01-01T23:59:59.000Z

    Regional wind integration studies require detailed wind power output data at many locations to perform simulations of how the power system will operate under high penetration scenarios. The wind datasets that serve as inputs into the study must realistically reflect the ramping characteristics, spatial and temporal correlations, and capacity factors of the simulated wind plants, as well as being time synchronized with available load profiles.As described in this presentation, the WIND Toolkit fulfills these requirements by providing a state-of-the-art national (US) wind resource, power production and forecast dataset.

  7. EA-1992: Funding for Principle Power, Inc., for the WindFloat Pacific Offshore Wind Demonstration Project, offshore of Coos Bay, Oregon

    Broader source: Energy.gov [DOE]

    Funding for Principle Power, Inc., for the WindFloat Pacific Offshore Wind Demonstration Project, offshore of Coos Bay, Oregon

  8. July 29th -30th 2010 1Integration of Wind Power in the Danish Energy System Integration of Wind Power in the Danish Energy System

    E-Print Network [OSTI]

    1984 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 MW Offshore Onshore Wind · Wind farms: · Grid codes ensure capability to regulate #12;July 29th - 30th 2010 9Integration of WindJuly 29th - 30th 2010 1Integration of Wind Power in the Danish Energy System Integration of Wind

  9. Oscillation Damping: A Comparison of Wind and Photovoltaic Power Plant Capabilities: Preprint

    SciTech Connect (OSTI)

    Singh, M.; Allen, A.; Muljadi, E.; Gevorgian, V.

    2014-07-01T23:59:59.000Z

    This work compares and contrasts strategies for providing oscillation damping services from wind power plants and photovoltaic power plants.

  10. Web-based Tool for Preliminary Assessment of Wind Power Plant Design

    E-Print Network [OSTI]

    Mustakerov, Ivan

    Web-based Tool for Preliminary Assessment of Wind Power Plant Design Daniela Borissova1 and Ivan. Designing of reliable and cost-effective industrial wind power plant is a prerequisite for the effective use of wind power as an alternative resource. The design of a wind power plant includes the determination

  11. Wind power bidding in a soft penalty market Antonio Giannitrapani, Simone Paoletti, Antonio Vicino, Donato Zarrilli

    E-Print Network [OSTI]

    Giannitrapani, Antonello

    Wind power bidding in a soft penalty market Antonio Giannitrapani, Simone Paoletti, Antonio Vicino, Donato Zarrilli Abstract-- In this paper we consider the problem of offering wind power in a market of the prior wind power statistics, is derived analytically by maximizing the expected profit of the wind power

  12. Opportunities For Wind In The APX Green Power MarketTM

    E-Print Network [OSTI]

    Green Power Market. These include wind, solar, geothermal, biomass, landfill gas, and small hydro (less

  13. Towns across Massachusetts are considering wind power, not only because it is one of the cleanest,

    E-Print Network [OSTI]

    Massachusetts at Amherst, University of

    Towns across Massachusetts are considering wind power, not only because it is one of the cleanest managed wind power project can be a net source of income. This fact sheet introduces the major factors to consider in determining whether your town can benefit from wind power. Can my community use wind power

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

    E-Print Network [OSTI]

    Paris-Sud XI, Université 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

  15. 7th International Workshop on Large-Scale Integration of Wind Power and on Transmission Networks for Offshore Wind Farms Models for HLI analysis of power systems with

    E-Print Network [OSTI]

    Bak-Jensen, Birgitte

    for Offshore Wind Farms 1 Models for HLI analysis of power systems with offshore wind farms and distributed power plants, distributed generation and offshore wind farms. Particular attention is paid to the latter]-[4], but there is a lack of models of offshore wind farms, which introduce new issues for their representation, due to some

  16. Abstract--The offshore wind farm with installed back-to-back power converter in wind turbines is studied. As an

    E-Print Network [OSTI]

    Bak, Claus Leth

    Abstract--The offshore wind farm with installed back-to- back power converter in wind turbines is studied. As an example the Burbo Bank offshore wind farm with Siemens Wind Power wind turbines is taken are compared with measurement data from the Burbo Bank offshore wind farm. The delimitations of both power

  17. Abstract--This paper introduces the power quality issues of wind power installations in a historic perspective, as the

    E-Print Network [OSTI]

    1 Abstract--This paper introduces the power quality issues of wind power installations large offshore wind farms connected at transmission level. In this perspective, the power quality issues and global issues related to the power system control and stability. Power quality characteristics of wind

  18. Wind Turbine Generator System Duration Test Report for the Mariah Power Windspire Wind Turbine

    SciTech Connect (OSTI)

    Huskey, A.; Bowen, A.; Jager, D.

    2010-05-01T23:59:59.000Z

    This test was conducted as part of the U.S. Department of Energy's (DOE) Independent Testing project to help reduce the barriers of wind energy expansion by providing independent testing results for small turbines. In total, five turbines are being tested at the National Wind Technology Center (NWTC) as a part of the first round of this project. Duration testing is one of up to five tests that may be performed on the turbines. Other tests include power performance, safety and function, noise, and power quality tests. NWTC testing results provide manufacturers with reports that may be used to meet part of small wind turbine certification requirements. This duration test report focuses on the Mariah Power Windspire wind turbine.

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

    SciTech Connect (OSTI)

    Lundquist, J; Glascoe, L; Obrecht, J

    2010-03-18T23:59:59.000Z

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

  20. Economic Benefits, Carbon Dioxide (CO2) Emissions Reductions, and Water Conservation Benefits from 1,000 Megawatts (MW) of New Wind Power in West Virginia (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2008-10-01T23:59:59.000Z

    The U.S. Department of Energy?s Wind Powering America Program is committed to educating state-level policymakers and other stakeholders about the economic, CO2 emissions, and water conservation impacts of wind power. This analysis highlights the expected impacts of 1000 MW of wind power in West Virginia. Although construction and operation of 1000 MW of wind power is a significant effort, six states have already reached the 1000-MW mark. We forecast the cumulative economic benefits from 1000 MW of development in West Virginia to be $1.0 billion, annual CO2 reductions are estimated at 3.3 million tons, and annual water savings are 1,763 million gallons.

  1. Economic Benefits, Carbon Dioxide (CO2) Emissions Reductions, and Water Conservation Benefits from 1,000 Megawatts (MW) of New Wind Power in Pennsylvania (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2008-10-01T23:59:59.000Z

    The U.S. Department of Energy?s Wind Powering America Program is committed to educating state-level policymakers and other stakeholders about the economic, CO2 emissions, and water conservation impacts of wind power. This analysis highlights the expected impacts of 1000 MW of wind power in Pennsylvania. Although construction and operation of 1000 MW of wind power is a significant effort, six states have already reached the 1000-MW mark. We forecast the cumulative economic benefits from 1000 MW of development in Pennsylvania to be $1.2 billion, annual CO2 reductions are estimated at 3.4 million tons, and annual water savings are 1,837 million gallons.

  2. Analysis of the effects of integrating wind turbines into a conventional utility: a case study. Final report

    SciTech Connect (OSTI)

    Goldenblatt, M.K.; Wegley, H.L.; Miller, A.H.

    1982-08-01T23:59:59.000Z

    The impact on a utility incorporating wind turbine generation due to wind speed sampling frequency, wind turbine performance model, and wind speed forecasting accuracy is examined. The utility analyzed in the study was the Los Angeles Department of Water and Power and the wind turbine assumed was the MOD-2. The sensitivity of the economic value of wind turbine generation to wind speed sampling frequency and wind turbine modeling technique is examined as well as the impact of wind forecasting accuracy on utility operation and production costs. Wind speed data from San Gorgonio Pass, California during 1979 are used to estimate wind turbine performance using four different simulation methods. (LEW)

  3. Analysis of the effects of integrating wind turbines into a conventional utility: a case study. Revised final report

    SciTech Connect (OSTI)

    Goldenblatt, M.K.; Wegley, H.L.; Miller, A.H.

    1983-03-01T23:59:59.000Z

    The impact on a utility incorporating wind turbine generation due to wind speed sampling frequency, wind turbine performance model, and wind speed forecasting accuracy is examined. The utility analyzed in this study was the Los Angeles Department of Water and Power, and the wind turbine assumed was the MOD-2. The sensitivity of the economic value of wind turbine generation to wind speed sampling frequency and wind turbine modeling technique is examined as well as the impact of wind forecasting accuracy on utility operation and production costs. Wind speed data from San Gorgonio Pass, California during 1979 are used to estimate wind turbine performance using four different simulation methods. (LEW)

  4. Wind Generation in the Future Competitive California Power Market

    SciTech Connect (OSTI)

    Sezgen, O.; Marnay, C.; Bretz, S.

    1998-03-01T23:59:59.000Z

    The goal of this work is to develop improved methods for assessing the viability of wind generation in competitive electricity markets. The viability of a limited number of possible wind sites is assessed using a geographic information system (GIS) to determine the cost of development, and Elfin, an electric utility production costing and capacity expansion model, to estimate the possible revenues and profits of wind farms at the sites. This approach improves on a simple profitability calculation by using a site-specific development cost calculation and by taking the effect of time varying market prices on revenues into account. The first component of the work is to develop data characterizing wind resources suitable for use in production costing and capacity expansion models, such as Elfin, that are capable of simulating competitive electricity markets. An improved representation of California wind resources is built, using information collected by the California Energy Commission (CE C) in previous site evaluations, and by using a GIS approach to estimating development costs at 36 specific sites. These sites, which have been identified as favorable for wind development, are placed on Digital Elevation Maps (DEMs) and development costs are calculated based on distances to roads and transmission lines. GIS is also used to develop the potential capacity at each site by making use of the physical characteristics of the terrain, such as ridge lengths. In the second part of the effort, using a previously developed algorithm for simulating competitive entry to the California electricity market, the Elfin model is used to gauge the viability of wind farms at the 36 sites. The results of this exercise are forecasts of profitable development levels at each site and the effects of these developments on the electricity system as a whole. Under best guess assumptions, including prohibition of new nuclear and coal capacity, moderate increase in gas prices and some decline in renewable capital costs, about 7.35 GW of the 10 GW potential capacity at the 36 specific sites is profitably developed and 62 TWh of electricity produced per annum by the year 2030. Most of the development happens during the earlier years of the forecast. Sensitivity of these results to future gas price scenarios is also presented. This study also demonstrates that an analysis based on a simple levelized profitability calculation approach does not sufficiently capture the implications of time varying prices in a competitive market.

  5. Daqing Longjiang 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:WindOilCowal WindDakshidinDeta

  6. Fenton Wind Power 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-f8521cbb8489 NoEurope BV JumpFederal Highway AdministrationFellowsWindWind

  7. Impact of DFIG wind turbines on transient stability of power systems a review

    E-Print Network [OSTI]

    Pota, Himanshu Roy

    Impact of DFIG wind turbines on transient stability of power systems ­ a review Authors Na Abstract of wind farms are using variable speed wind turbines equipped with doubly-fed induction generators (DFIG) due to their advantages over other wind turbine generators. Therefore, the analysis of wind power

  8. Power Control and Optimization of Photovoltaic and Wind Energy Conversion Systems /

    E-Print Network [OSTI]

    Ghaffari, Azad

    2013-01-01T23:59:59.000Z

    both AC drives and wind energy Turbine, shaft, and Gear BoxWind Energy Conversion Systems using Extremum Seeking Wind turbines (wind energy generation can be realized by capturing wind power at altitudes over the ground that cannot be reached by wind turbines.

  9. Short-term Wind Power Prediction for Offshore Wind Farms -Evaluation of Fuzzy-Neural Network Based Models

    E-Print Network [OSTI]

    Paris-Sud XI, Université de

    Short-term Wind Power Prediction for Offshore Wind Farms - Evaluation of Fuzzy-Neural Network Based of offshore farms and their secure integration to the grid. Modeling the behavior of large wind farms presents the new considerations that have to be made when dealing with large offshore wind farms

  10. Wind power development -Status and perspectives

    E-Print Network [OSTI]

    countries together covering ap- prox. 80% of the growth in installed wind turbine capacity world wide years the global in- stalled capacity has increased almost threefold, from approx. 2.3 GW in 1991 has increased - in 1995 and 1996 global capacity has increased by approx. 1.3 GW annually or more than

  11. Factors driving wind power development in the United States

    SciTech Connect (OSTI)

    Bird, Lori A.; Parsons, Brian; Gagliano, Troy; Brown, Matthew H.; Wiser, Ryan H.; Bolinger, Mark

    2003-05-15T23:59:59.000Z

    In the United States, there has been substantial recent growth in wind energy generating capacity, with growth averaging 24 percent annually during the past five years. About 1,700 MW of wind energy capacity was installed in 2001, while another 410 MW became operational in 2002. This year (2003) shows promise of significant growth with more than 1,500 MW planned. With this growth, an increasing number of states are experiencing investment in wind energy projects. Wind installations currently exist in about half of all U.S. states. This paper explores the key factors at play in the states that have achieved a substantial amount of wind energy investment. Some of the factors that are examined include policy drivers, such as renewable portfolio standards (RPS), federal and state financial incentives, and integrated resource planning; as well as market drivers, such as consumer demand for green power, natural gas price volatility, and wholesale market rules.

  12. Fourth International Workshop on Large-Scale Integration of Wind Power and Transmission Networks for Offshore Wind Farms,

    E-Print Network [OSTI]

    for Offshore Wind Farms, 20-21 October 2003, Billund, Denmark C. S. Nielsen, Hans F. Ravn, Camilla Schaumburg1 Fourth International Workshop on Large-Scale Integration of Wind Power and Transmission Networks of Denmark, B. 321, DK-2800 Lyngby, Denmark, csm@imm.dtu.dk Two wind power prognosis criteria and regulating

  13. On the Wind Power Input to the Ocean General Circulation XIAOMING ZHAI

    E-Print Network [OSTI]

    Johnson, Helen

    On the Wind Power Input to the Ocean General Circulation XIAOMING ZHAI Atmospheric, Oceanic January 2012, in final form 3 May 2012) ABSTRACT The wind power input to the ocean general circulation is usually calculated from the time-averaged wind products. Here, this wind power input is reexamined using

  14. PERFORMANCE ENHANCEMENT OF WIND TURBINE POWER REGULATION BY SWITCHED LINEAR CONTROL

    E-Print Network [OSTI]

    Duffy, Ken

    PERFORMANCE ENHANCEMENT OF WIND TURBINE POWER REGULATION BY SWITCHED LINEAR CONTROL D.J.Leith W Power regulation of horizontal-axis grid-connected up-wind constant-speed pitch-regulated wind turbines ENHANCEMENT OF WIND TURBINE POWER REGULATION BY SWITCHED LINEAR CONTROL D.J.Leith W.E.Leithead Department

  15. Demand Side Management for Wind Power Integration in Microgrid Using Dynamic Potential Game Theory

    E-Print Network [OSTI]

    Huang, Jianwei

    Demand Side Management for Wind Power Integration in Microgrid Using Dynamic Potential Game Theory, Wind Power Integration, Markov Chain, Dynamic Potential Game Theory, Nash Equilibrium. I. INTRODUCTION the intermittency in wind power generation. Our focus is on an isolated microgrid with one wind turbine, one fast

  16. Coal Fired Power Generation Market Forecast | 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 EditCalifornia:PowerCER.png El CER esDatasetCityFundCo-benefits EvaluationCoal Fired

  17. Session: Poster Session + Poster Award + Scientific Award + Excellent young wind doctor award (PO.72) Track: Technical

    E-Print Network [OSTI]

    -term forecasting of wind power and wind resource assessment including offshore wakes in large wind farms. In both offshore wakes in large wind farms. For this, it is necessary to be able to evaluate state benchmarking exercises. The POWWOW project (Prediction of Waves, Wakes and Offshore Wind, a EU Coordination

  18. Wind Resource Assessment of Gujarat (India)

    SciTech Connect (OSTI)

    Draxl, C.; Purkayastha, A.; Parker, Z.

    2014-07-01T23:59:59.000Z

    India is one of the largest wind energy markets in the world. In 1986 Gujarat was the first Indian state to install a wind power project. In February 2013, the installed wind capacity in Gujarat was 3,093 MW. Due to the uncertainty around existing wind energy assessments in India, this analysis uses the Weather Research and Forecasting (WRF) model to simulate the wind at current hub heights for one year to provide more precise estimates of wind resources in Gujarat. The WRF model allows for accurate simulations of winds near the surface and at heights important for wind energy purposes. While previous resource assessments published wind power density, we focus on average wind speeds, which can be converted to wind power densities by the user with methods of their choice. The wind resource estimates in this study show regions with average annual wind speeds of more than 8 m/s.

  19. Maoming Zhong ao Wind Power Co 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 REPORTEnergyFarmsPower CoLongxing WindMaoming Zhong ao Wind Power Co

  20. 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

  1. wind powering america | 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 Hometcdb Home Graham7781'sHome

  2. TS Wind Power Developers | 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:Shrenik IndustriesState ofSwitchpowerTCITMETS Wind

  3. Hardscrabble Wind Power 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 OpenEI ReferenceJumpEnergyStrategy | OpenHalfWind Jump

  4. 2014 Year-End Wind Power Capacity

    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: EnergyWyandanch,EagaAbout PrintableEducation PrintableWind2 0

  5. Madison Wind Power 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, searchOfRose Bend < MHKconverter <WAGMadison Gas & Electric CoWind

  6. Infinity Wind Power 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 are8COaBulkTransmissionSitingProcess.pdfGetecGtel JumpCounty,Jump7Open EnergyHydrogen Jump to: navigation, searchWind

  7. Examination of Capacity and Ramping Impacts of Wind Energy on Power Systems

    SciTech Connect (OSTI)

    Kirby, B.; Milligan, M.

    2008-07-01T23:59:59.000Z

    When wind plants serve load within the balancing area, no additional capacity required to integrate wind power into the system. We present some thought experiments to illustrate some implications for wind integration studies.

  8. Community wind power ownership schemes in Europe and their relevance to the United States

    E-Print Network [OSTI]

    Bolinger, Mark

    2001-01-01T23:59:59.000Z

    Wizelius, T. 1999c. “Wind bank opens to Swedish co-ops. ”Andersen, P.D. 1998. Wind Power in Denmark: Technology,of Community Ownership in a Wind Energy Project at Harlock

  9. On the Patterns of Wind-Power Input to the Ocean Circulation

    E-Print Network [OSTI]

    Roquet, Fabien

    Pathways of wind-power input into the ocean general circulation are analyzed using Ekman theory. Direct rates of wind work can be calculated through the wind stress acting on the surface geostrophic flow. However, because ...

  10. Stochastic Modeling of Multi-Area Wind Power Production Anthony Papavasiliou

    E-Print Network [OSTI]

    Oren, Shmuel S.

    Stochastic Modeling of Multi-Area Wind Power Production Anthony Papavasiliou CORE, UCL anthony of wind power production on power system operations over an entire year, it is necessary to account for the non-stationary (seasonal and diurnal) patterns of wind power production. This paper presents a multi

  11. PEV-based Reactive Power Compensation for Wind DG Units: A Stackelberg Game Approach

    E-Print Network [OSTI]

    Mohsenian-Rad, Hamed

    balancing supply and demand for active power, we also need to compensate reactive power for each wind DGPEV-based Reactive Power Compensation for Wind DG Units: A Stackelberg Game Approach Chenye Wu, in particular wind power, in form of distributed generation (DG) units. However, one important challenge

  12. Wind Power Integration via Aggregator-Consumer Coordination: A Game Theoretic Approach

    E-Print Network [OSTI]

    Mohsenian-Rad, Hamed

    the balance between load and generation in the power grid at all times [2]. Moreover, wind generation is nonWind Power Integration via Aggregator-Consumer Coordination: A Game Theoretic Approach Chenye Wu@ie.cuhk.edu.hk Abstract--Due to the stochastic nature of wind power, its large-scale integration into the power grid

  13. PEV-based Reactive Power Compensation for Wind DG Units: A Stackelberg Game Approach

    E-Print Network [OSTI]

    Huang, Jianwei

    balancing supply and demand for active power, we also need to compensate reactive power for each wind DG1 PEV-based Reactive Power Compensation for Wind DG Units: A Stackelberg Game Approach Chenye Wu, in particular wind power, in form of distributed generation (DG) units. However, one important challenge

  14. Importance of the Equlibrium Node in Preventing the Voltage Collapse Occurs in the Wind Power System

    E-Print Network [OSTI]

    Lavaei, Javad

    Importance of the Equlibrium Node in Preventing the Voltage Collapse Occurs in the Wind Power collapse will occurs in a wind power system is discussed next. The method of power flow calculation is the specific analysis of a given simplified wind power system. Keywords--voltage collapse; Newton

  15. LQ Optimal Control of Wind Turbines in Hybrid Power Systems N.A. Cutululis1

    E-Print Network [OSTI]

    LQ Optimal Control of Wind Turbines in Hybrid Power Systems N.A. Cutululis1 , H. Bindner1 , I power systems represent a viable solution for rural electrification. One of the most important aspects taken into account for the design of a wind ­ diesel power system is the wind power penetration, which

  16. innovati nNREL Confirms Large Potential for Grid Integration of Wind, Solar Power

    E-Print Network [OSTI]

    innovati nNREL Confirms Large Potential for Grid Integration of Wind, Solar Power To fully harvest a database of potential wind power sites and detailed, time-dependent estimates of the power that would the nation's bountiful wind and solar resources, it is critical to know how much electrical power from

  17. 2007 Wholesale Power Rate Case Final Proposal : Market Price Forecast Study.

    SciTech Connect (OSTI)

    United States. Bonneville Power Administration.

    2006-07-01T23:59:59.000Z

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

  18. The Impact of Wind Power Projects on Residential Property Values in the United States: A Multi-Site Hedonic Analysis

    E-Print Network [OSTI]

    Hoen, Ben

    2010-01-01T23:59:59.000Z

    Offshore Wind Power: Underlying Factors. Energy Policy. 35(Wind Development on Local Property Values. Renewable Energy Policy

  19. Wind Power Price Trends in the United States: Struggling to Remain Competitive in the Face of Strong Growth

    E-Print Network [OSTI]

    Bolinger, Mark A

    2009-01-01T23:59:59.000Z

    Build a Durable Market for Wind Power in the United States”Consult. 2008. “International Wind Energy Development: WorldGlobal Experience Curves for Wind Farms. ” Energy Policy,

  20. Advancements in Wind Integration Study Data Modeling: The Wind Integration National Dataset (WIND) Toolkit; Preprint

    SciTech Connect (OSTI)

    Draxl, C.; Hodge, B. M.; Orwig, K.; Jones, W.; Searight, K.; Getman, D.; Harrold, S.; McCaa, J.; Cline, J.; Clark, C.

    2013-10-01T23:59:59.000Z

    Regional wind integration studies in the United States require detailed wind power output data at many locations to perform simulations of how the power system will operate under high-penetration scenarios. The wind data sets that serve as inputs into the study must realistically reflect the ramping characteristics, spatial and temporal correlations, and capacity factors of the simulated wind plants, as well as be time synchronized with available load profiles. The Wind Integration National Dataset (WIND) Toolkit described in this paper fulfills these requirements. A wind resource dataset, wind power production time series, and simulated forecasts from a numerical weather prediction model run on a nationwide 2-km grid at 5-min resolution will be made publicly available for more than 110,000 onshore and offshore wind power production sites.

  1. Network Wind Power Over the Pacific Northwest. Progress Report, October 1979-September 1980.

    SciTech Connect (OSTI)

    Baker, Robert W.; Hewson, E. Wendell

    1980-10-01T23:59:59.000Z

    The research in FY80 is composed of six primary tasks. These tasks include data collection and analysis, wind flow studies around an operational wind turbine generator (WTG), kite anemometer calibration, wind flow analysis and prediction, the Klickitat County small wind energy conversion system (SWECS) program, and network wind power analysis. The data collection and analysis task consists of four sections, three of which deal with wind flow site surveys and the fourth with collecting and analyzing wind data from existing data stations. This report also includes an appendix which contains mean monthly wind speed data summaries, wind spectrum summaries, time series analysis plots, and high wind summaries.

  2. This introduction to wind power technology is meant to help communities begin considering or

    E-Print Network [OSTI]

    Massachusetts at Amherst, University of

    call both liquids and gases "fluids" ­ i.e. things that flow). A wind turbine's blades use aerodynamic of a typical wind turbine are: - Rotor: a wind turbine's blades and the hub to which they attach form the rotor or planning wind power. It focuses on commercial and medium-scale wind turbine technology available

  3. IEEE TRANSACTIONS ON POWER SYSTEMS, VOL. 26, NO. 4, NOVEMBER 2011 2197 Reserve Requirements for Wind Power Integration: A

    E-Print Network [OSTI]

    Oren, Shmuel S.

    for Wind Power Integration: A Scenario-Based Stochastic Programming Framework Anthony Papavasiliou, Student-stage stochastic programming model for committing reserves in systems with large amounts of wind power. We describe wind power generation in terms of a representative set of appropriately weighted scenarios, and we

  4. Wind Power Project Repowering: History, Economics, and Demand (Presentation)

    SciTech Connect (OSTI)

    Lantz, E.

    2015-01-01T23:59:59.000Z

    This presentation summarizes a related NREL technical report and seeks to capture the current status of wind power project repowering in the U.S. and globally, analyze the economic and financial decision drivers that surround repowering, and to quantify the level and timing of demand for new turbine equipment to supply the repowering market.

  5. Bottom Drag, eddy diffusivity, wind work and the power integrals

    E-Print Network [OSTI]

    Young, William R.

    Bottom Drag, eddy diffusivity, wind work and the power integrals Bill Young, Andrew Thompson field i.e., the meridional heat flux is pro Moreover, the mechanical energy balance in a statistical Moreover, the mechanical energy balance in a statistically st Appendix A) is U-2 x = | - 2 |2 + hyp

  6. Temporal structure of aggregate power fluctuations in large-eddy simulations of extended wind-farms

    E-Print Network [OSTI]

    Stevens, Richard J A M

    2014-01-01T23:59:59.000Z

    Fluctuations represent a major challenge for the incorporation of electric power from large wind-farms into power grids. Wind farm power output fluctuates strongly in time, over various time scales. Understanding these fluctuations, especially their spatio-temporal characteristics, is particularly important for the design of backup power systems that must be readily available in conjunction with wind-farms. In this work we analyze the power fluctuations associated with the wind-input variability at scales between minutes to several hours, using large eddy simulations (LES) of extended wind-parks, interacting with the atmospheric boundary layer. LES studies enable careful control of parameters and availability of wind-velocities simultaneously across the entire wind-farm. The present study focuses on neutral atmospheric conditions and flat terrain, using actuator-disk representations of the individual wind-turbines. We consider power from various aggregates of wind-turbines such as the total average power sign...

  7. Reactive power control of grid-connected wind farm based on adaptive dynamic programming

    E-Print Network [OSTI]

    He, Haibo

    Reactive power control of grid-connected wind farm based on adaptive dynamic programming Yufei Tang Wind farm Power system Adaptive control a b s t r a c t Optimal control of large-scale wind farm has of wind farm with doubly fed induction generators (DFIG). Specifically, we investigate the on

  8. Nonlinear State Space Model of a Hydraulic Wind Power Transfer Masoud Vaezi1

    E-Print Network [OSTI]

    Zhou, Yaoqi

    state space representation of a hydraulic wind energy transfer for a single wind turbine systemNonlinear State Space Model of a Hydraulic Wind Power Transfer Masoud Vaezi1 , Majid Deldar1 1, IUPUI. Gearless hydraulic wind power systems are considered as nonlinear models because of some discrete

  9. Offshore Wind Power: Science, engineering, and policy MAST 628-010, Fall 2008

    E-Print Network [OSTI]

    Firestone, Jeremy

    Offshore Wind Power: Science, engineering, and policy MAST 628-010, Fall 2008 Revised 10 October@udel.edu Class web site with lecture notes: www.udel.edu/sakai UD offshore wind research: http, plan, regulate, and develop offshore wind resources for large-scale power production. Offshore wind

  10. Wind Power Price Trends in the United States

    E-Print Network [OSTI]

    Bolinger, Mark

    2010-01-01T23:59:59.000Z

    the true cost of wind generation (which would be at least $and wind’s competitive position among generation resources.

  11. Sixth Northwest Conservation & Electric Power Plan Draft Wholesale Power Price Forecasts

    E-Print Network [OSTI]

    Higher Coal Prices Medium Long-term Trend Forecasts for PNW Zones 0.00 0.20 0.40 0.60 0.80 1.00 1.20 1 Mexico Arizona Utah Nevada North Alberta Baja California North Nevada South PNW Westside 10 Northwest

  12. 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.

  13. General Comparison of Power Loss in Single-Layer and Multi-Layer Windings

    E-Print Network [OSTI]

    General Comparison of Power Loss in Single-Layer and Multi-Layer Windings M. E. Dale C. R. Sullivan the IEEE. #12;General Comparison of Power Loss in Single-Layer and Multi-Layer Windings Magdalena E. Dale

  14. Balancing act - BPA grid responds to huge influx of wind power...

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

    territory A large fraction of the wind power in the Northwest is locating in the heart of BPA's transmission grid. Wind power in BPA's balancing area has grown from 25 MW 10...

  15. Energy Department Awards $4.5 Million for Innovative Wind Power...

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

    Energy Department Awards 4.5 Million for Innovative Wind Power R&D Projects Energy Department Awards 4.5 Million for Innovative Wind Power R&D Projects September 5, 2014 -...

  16. Annual Report on U.S. Wind Power Installation, Cost, and Performance Trends: 2007 (Revised)

    SciTech Connect (OSTI)

    Wiser, R.; Bolinger, M.

    2008-05-01T23:59:59.000Z

    This report focuses on key trends in the U.S. wind power market, with an emphasis on the latest year, and presents a wealth of data, some of which has not historically been mined by wind power analysts.

  17. The effect of wind speed fluctuations on the performance of a wind-powered membrane system for brackish water desalination 

    E-Print Network [OSTI]

    Park, Gavin L.; Schäfer, Andrea; Richards, Bryce S.

    2011-01-01T23:59:59.000Z

    A wind-powered reverse osmosis membrane (wind-membrane) system without energy storage was tested using synthetic brackish water (2750 and 5500 mg/L NaCl) over a range of simulated wind speeds under both steady-state and ...

  18. Potential order-of-magnitude enhancement of wind farm power density via counter-rotating vertical-axis wind

    E-Print Network [OSTI]

    Dabiri, John O.

    Potential order-of-magnitude enhancement of wind farm power density via counter-rotating vertical an alternative approach to wind farming that has the potential to concurrently reduce the cost, size-axis wind turbine arrays John O. Dabiria) Graduate Aeronautical Laboratories and Bioengineering, California

  19. EWEC 2006 Scientific Track Advanced Forecast Systems for the Grid Integration of 25 GW

    E-Print Network [OSTI]

    Heinemann, Detlev

    forecasts, smoothing effects Abstract The economic success of offshore wind farms in liberalised electricity of offshore wind farms, their electricity production must be known well in advance to allow an efficient Oldenburg, Germany Key words: Offshore wind power, grid integration, short-term prediction, regional

  20. Estimated global ocean wind power potential from QuikSCAT observations, accounting for turbine characteristics and siting

    E-Print Network [OSTI]

    Capps, Scott B; Zender, Charles S

    2010-01-01T23:59:59.000Z

    Evaluation of global wind power, J. Geophys. Res. , 110,2009), Global ocean wind power sensitivity to surface layerCO 2 reductions via offshore wind power matched to inherent