National Library of Energy BETA

Sample records for wind power forecasting

  1. Wind Power Forecasting Data

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

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

  2. Wind Power Forecasting

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

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

  3. Value of Wind Power Forecasting

    SciTech Connect (OSTI)

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

    2011-04-01

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

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

    SciTech Connect (OSTI)

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

    2011-10-01

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

  5. A survey on wind power ramp forecasting.

    SciTech Connect (OSTI)

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

    2011-02-23

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

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

    SciTech Connect (OSTI)

    Hodge, B. M.; Milligan, M.

    2011-07-01

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

  7. The Value of Wind Power Forecasting

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

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

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

    SciTech Connect (OSTI)

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

    2010-04-01

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

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

    SciTech Connect (OSTI)

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

    2010-04-15

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

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

    SciTech Connect (OSTI)

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

    2012-09-01

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

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

    SciTech Connect (OSTI)

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

    2012-07-01

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

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

    SciTech Connect (OSTI)

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

    2014-05-01

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

  13. Use of wind power forecasting in operational decisions.

    SciTech Connect (OSTI)

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

    2011-11-29

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

  14. Value of Improved Short-Term Wind Power Forecasting

    SciTech Connect (OSTI)

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

    2015-02-01

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

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

    SciTech Connect (OSTI)

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

    2011-12-06

    Wind power forecasting (WPF) provides important inputs to power system operators and electricity market participants. It is therefore not surprising that WPF has attracted increasing interest within the electric power industry. In this report, we document our research on improving statistical WPF algorithms for point, uncertainty, and ramp forecasting. Below, we provide a brief introduction to the research presented in the following chapters. For a detailed overview of the state-of-the-art in wind power forecasting, we refer to [1]. Our related work on the application of WPF in operational decisions is documented in [2]. Point forecasts of wind power are highly dependent on the training criteria used in the statistical algorithms that are used to convert weather forecasts and observational data to a power forecast. In Chapter 2, we explore the application of information theoretic learning (ITL) as opposed to the classical minimum square error (MSE) criterion for point forecasting. In contrast to the MSE criterion, ITL criteria do not assume a Gaussian distribution of the forecasting errors. We investigate to what extent ITL criteria yield better results. In addition, we analyze time-adaptive training algorithms and how they enable WPF algorithms to cope with non-stationary data and, thus, to adapt to new situations without requiring additional offline training of the model. We test the new point forecasting algorithms on two wind farms located in the U.S. Midwest. Although there have been advancements in deterministic WPF, a single-valued forecast cannot provide information on the dispersion of observations around the predicted value. We argue that it is essential to generate, together with (or as an alternative to) point forecasts, a representation of the wind power uncertainty. Wind power uncertainty representation can take the form of probabilistic forecasts (e.g., probability density function, quantiles), risk indices (e.g., prediction risk index) or scenarios

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2010-04-01

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

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

    SciTech Connect (OSTI)

    Porter, K.; Rogers, J.

    2009-12-01

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

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

    SciTech Connect (OSTI)

    Piwko, R.; Jordan, G.

    2011-11-01

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

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

    SciTech Connect (OSTI)

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

    2012-08-01

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

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

    SciTech Connect (OSTI)

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

    2009-11-20

    Many countries and regions are introducing policies aimed at reducing the environmental footprint from the energy sector and increasing the use of renewable energy. In the United States, a number of initiatives have been taken at the state level, from renewable portfolio standards (RPSs) and renewable energy certificates (RECs), to regional greenhouse gas emission control schemes. Within the U.S. Federal government, new energy and environmental policies and goals are also being crafted, and these are likely to increase the use of renewable energy substantially. The European Union is pursuing implementation of its ambitious 20/20/20 targets, which aim (by 2020) to reduce greenhouse gas emissions by 20% (as compared to 1990), increase the amount of renewable energy to 20% of the energy supply, and reduce the overall energy consumption by 20% through energy efficiency. With the current focus on energy and the environment, efficient integration of renewable energy into the electric power system is becoming increasingly important. In a recent report, the U.S. Department of Energy (DOE) describes a model-based scenario, in which wind energy provides 20% of the U.S. electricity demand in 2030. The report discusses a set of technical and economic challenges that have to be overcome for this scenario to unfold. In Europe, several countries already have a high penetration of wind power (i.e., in the range of 7 to 20% of electricity consumption in countries such as Germany, Spain, Portugal, and Denmark). The rapid growth in installed wind power capacity is expected to continue in the United States as well as in Europe. A large-scale introduction of wind power causes a number of challenges for electricity market and power system operators who will have to deal with the variability and uncertainty in wind power generation when making their scheduling and dispatch decisions. Wind power forecasting (WPF) is frequently identified as an important tool to address the variability and

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

    SciTech Connect (OSTI)

    Hodge, B.

    2013-12-01

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

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

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

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

    ... up-ramp reserves c down cost in MWh of down-ramp reserves R down MW range for ... power forecasting and the increased gas usage that comes with less-accurate forecasting. ...

  4. The Value of Improved Wind Power Forecasting in the Western Interconne...

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

    of this research will facilitate a better functional understanding of wind forecasting accuracy and power system operations at various spatial and temporal scales.* Of particular ...

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  6. Offshore Wind Power USA

    Broader source: Energy.gov [DOE]

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

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

    SciTech Connect (OSTI)

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

    2013-05-01

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

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

    SciTech Connect (OSTI)

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

    2009-10-09

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

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

    SciTech Connect (OSTI)

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

    2012-09-01

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

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

    SciTech Connect (OSTI)

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

    2012-06-01

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

  11. ANL Software Improves Wind Power Forecasting | Department of...

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

    ... The licensing arrangement helps to facilitate transfer of the statistical learning algorithms developed in the project to industry use. A leading forecast provider in the United ...

  12. Wind Forecasting Improvement Project | Department of Energy

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

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

  13. Wind Power Forecasting Error Distributions over Multiple Timescales: Preprint

    SciTech Connect (OSTI)

    Hodge, B. M.; Milligan, M.

    2011-03-01

    In this paper, we examine the shape of the persistence model error distribution for ten different wind plants in the ERCOT system over multiple timescales. Comparisons are made between the experimental distribution shape and that of the normal distribution.

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

    SciTech Connect (OSTI)

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

    2012-09-01

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

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

    SciTech Connect (OSTI)

    Pennock, K.

    2012-10-01

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

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

    SciTech Connect (OSTI)

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

    2010-01-01

    The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind and solar power production forecasts to achieve future balance between the conventional generation and energy storage on the one side, and system load, intermittent resources (such as wind and solar generation), and scheduled interchange on the other side. Although in real life the forecasting procedures imply some uncertainty around the load and wind/solar forecasts (caused by forecast errors), only their mean values are actually used in the generation dispatch and commitment procedures. Since the actual load and intermittent generation can deviate from their forecasts, it becomes increasingly unclear (especially, with the increasing penetration of renewable resources) whether the system would be actually able to meet the conventional generation requirements within the look-ahead horizon, what the additional balancing efforts would be needed as we get closer to the real time, and what additional costs would be incurred by those needs. To improve the system control performance characteristics, maintain system reliability, and minimize expenses related to the system balancing functions, it becomes necessary to incorporate the predicted uncertainty ranges into the scheduling, load following, and, in some extent, into the regulation processes. It is also important to address the uncertainty problem comprehensively by including all sources of uncertainty (load, intermittent generation, generators’ forced outages, etc.) into consideration. All aspects of uncertainty such as the imbalance size (which is the same as capacity needed to mitigate the imbalance) and generation ramping requirement must be taken into account. The latter

  17. 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.

    2010-09-01

    The power system balancing process, which includes the scheduling, real time dispatch (load following) and regulation processes, is traditionally based on deterministic models. Since the conventional generation needs time to be committed and dispatched to a desired megawatt level, the scheduling and load following processes use load and wind 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

  18. Today's Forecast: Improved Wind Predictions

    Broader source: Energy.gov [DOE]

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

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

    SciTech Connect (OSTI)

    Zhang, J.; Hodge, B. M.

    2014-04-01

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

  20. Incorporating Uncertainty of Wind Power Generation Forecast into Power System Operation, Dispatch, and Unit Commitment Procedures

    SciTech Connect (OSTI)

    Makarov, Yuri V.; Etingov, Pavel V.; Ma, Jian; Huang, Zhenyu; Subbarao, Krishnappa

    2011-06-23

    An approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed. The approach includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for a specified time horizon and a given confidence level. An assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on histogram analysis, incorporating sources of uncertainty - both continuous (wind and load forecast errors) and discrete (forced generator outages and start-up failures). A new method called the 'flying-brick' technique is developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation process is used to validate the accuracy of the confidence intervals. To demonstrate the validity of the developed uncertainty assessment methods and its impact on grid operation, a framework for integrating the proposed methods with an EMS system is developed. Demonstration through EMS integration illustrates the applicability of the proposed methodology and the developed tool for actual grid operation and paves the road for integration with EMS systems in control rooms.

  1. Wind power forecasting : state-of-the-art 2009. (Technical Report...

    Office of Scientific and Technical Information (OSTI)

    ... 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. ...

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

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

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

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

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

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

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

    SciTech Connect (OSTI)

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

    2010-04-20

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

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

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

    ... RIT forecasting is saving costs and improving operational practices for IPC and helping integrate wind power more efficiently and cost effectively. Figure 3 shows how the ...

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

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

    ... Demand response, energy storage, and improved wind power forecasting techniques have often ... parties by reducing total production costs, increasing wind power revenue streams, ...

  7. Incorporating Wind Generation Forecast Uncertainty into Power System Operation, Dispatch, and Unit Commitment Procedures

    SciTech Connect (OSTI)

    Makarov, Yuri V.; Etingov, Pavel V.; Huang, Zhenyu; Ma, Jian; Subbarao, Krishnappa

    2010-10-19

    In this paper, an approach to evaluate the uncertainties of the balancing capacity, ramping capability, and ramp duration requirements is proposed. The approach includes three steps: forecast data acquisition, statistical analysis of retrospective information, and prediction of grid balancing requirements for a specified time horizon and a given confidence level. Assessment of the capacity and ramping requirements is performed using a specially developed probabilistic algorithm based on histogram analysis, incorporating sources of uncertainty 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 is developed to evaluate the look-ahead required generation performance envelope for the worst case scenario within a user-specified confidence level. A self-validation process is used to validate the accuracy of the confidence intervals. To demonstrate the validity of the developed uncertainty assessment methods and its impact on grid operation, a framework for integrating the proposed methods with an EMS system is developed. Demonstration through integration with an EMS system illustrates the applicability of the proposed methodology and the developed tool for actual grid operation and paves the road for integration with EMS systems from other vendors.

  8. Wind Power

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

    Wind Power As the accompanying map of New Mexico shows, the best wind power generation potential near WIPP is along the Delaware Mountain ridge line of the southern Guadalupe Mountains, about 50-60 miles southwest. The numeric grid values indicate wind potential, with a range from 1 (poor) to 7 (superb). Just inside Texas in the southern Guadalupe Mountains, the Delaware Mountain Wind Power Facility in Culbertson County, Texas currently generates over 30 MW, and could be expanded to a 250 MW

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

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

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

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

    SciTech Connect (OSTI)

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

    2015-10-30

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

  11. 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

    2012-12-31

    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

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

    SciTech Connect (OSTI)

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

    2011-03-28

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

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

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

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

  14. WINDExchange: Selling Wind Power

    Wind Powering America (EERE)

    Market Sectors Printable Version Bookmark and Share Utility-Scale Wind Distributed Wind Motivations for Buying Wind Power Buying Wind Power Selling Wind Power Selling Wind Power Owners of wind turbines interconnected directly to the transmission or distribution grid, or that produce more power than the host consumes, can sell wind power as well as other generation attributes. Wind-Generated Electricity Electricity generated by wind turbines can be used to cover on-site energy needs

  15. 915 MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

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

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

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

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

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

  17. ARGUS-PRIMA: Wind Power Prediction | Argonne National Laboratory

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

    ARGUS-PRIMA: Wind Power Prediction ARGUS-PRIMA: Wind Power Prediction ARGUS-PRIMA is a software platform for testing statistical algorithms for short-term wind power forecasting. ...

  18. Solar and wind power advancing

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

    Solar and wind power advancing U.S. electricity generation from wind and solar energy show no signs of slowing down. In its new monthly forecast, the U.S. Energy Information Administration expects wind-powered generation to grow by 19 percent this year and rise another 8 percent in 2014. Congress's extension in January of a tax credit for electricity producers that use renewables is behind the wind power boost. Solar generation in the electric power sector is expected to grow even more, rising

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

    SciTech Connect (OSTI)

    Rogers, J.; Porter, K.

    2011-03-01

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

  20. Final Report on California Regional Wind Energy Forecasting Project:Application of NARAC Wind Prediction System

    SciTech Connect (OSTI)

    Chin, H S

    2005-07-26

    Wind power is the fastest growing renewable energy technology and electric power source (AWEA, 2004a). This renewable energy has demonstrated its readiness to become a more significant contributor to the electricity supply in the western U.S. and help ease the power shortage (AWEA, 2000). The practical exercise of this alternative energy supply also showed its function in stabilizing electricity prices and reducing the emissions of pollution and greenhouse gases from other natural gas-fired power plants. According to the U.S. Department of Energy (DOE), the world's winds could theoretically supply the equivalent of 5800 quadrillion BTUs of energy each year, which is 15 times current world energy demand (AWEA, 2004b). Archer and Jacobson (2005) also reported an estimation of the global wind energy potential with the magnitude near half of DOE's quote. Wind energy has been widely used in Europe; it currently supplies 20% and 6% of Denmark's and Germany's electric power, respectively, while less than 1% of U.S. electricity is generated from wind (AWEA, 2004a). The production of wind energy in California ({approx}1.2% of total power) is slightly higher than the national average (CEC & EPRI, 2003). With the recently enacted Renewable Portfolio Standards calling for 20% of renewables in California's power generation mix by 2010, the growth of wind energy would become an important resource on the electricity network. Based on recent wind energy research (Roulston et al., 2003), accurate weather forecasting has been recognized as an important factor to further improve the wind energy forecast for effective power management. To this end, UC-Davis (UCD) and LLNL proposed a joint effort through the use of UCD's wind tunnel facility and LLNL's real-time weather forecasting capability to develop an improved regional wind energy forecasting system. The current effort of UC-Davis is aimed at developing a database of wind turbine power curves as a function of wind speed and

  1. Wyoming Wind Power Project (generation/wind)

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

    Wind Power > Generation Hydro Power Wind Power Monthly GSP BPA White Book Dry Year Tools Firstgov Wyoming Wind Power Project (Foote Creek Rim I and II) Thumbnail image of wind...

  2. Wind Power Today

    SciTech Connect (OSTI)

    Not Available

    2006-05-01

    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.

  3. Wind Power Today

    SciTech Connect (OSTI)

    Not Available

    2007-05-01

    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 Forecast Improvement Project Southern Study Area Final Report |

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

    Department of Energy Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report Wind Forecast Improvement Project Southern Study Area Final Report.pdf (15.76 MB) More Documents & Publications QER - Comment of Edison Electric Institute (EEI) 1 QER - Comment of Canadian Hydropower Association QER - Comment of Edison Electric Institute (EEI) 2

  5. WINDExchange: Buying Wind Power

    Wind Powering America (EERE)

    Buying Wind Power Individuals, communities, businesses, and government entities may decide that buying wind power to supply their energy needs is the right fit. There are several ways to purchase wind power. Green Power Marketing Green power marketing refers to green power being offered by multiple suppliers in a competitive marketplace. In states that have established retail competition, customers may be able to purchase green power from a competitive supplier. Learn more about green power

  6. Wethersfield Wind Power Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    Wethersfield Wind Power Wind Farm Jump to: navigation, search Name Wethersfield Wind Power Wind Farm Facility Wethersfield Wind Power Sector Wind energy Facility Type Commercial...

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

    SciTech Connect (OSTI)

    Finley, Cathy

    2014-04-30

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

  8. Operating Reserves and Wind Power Integration; An International...

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

    ... As shown in Fig. 5 wind power forecasting errors can increase the cost associated to the operation of deviation management and the tertiary reserve. D. The Netherlands The ...

  9. Wind Power (pbl/generation)

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

    Generation Hydro Power Wind Power Monthly GSP BPA White Book Dry Year Tools Firstgov Wind Power (Updated June 16, 2014) Project Descriptions Foote Creek I Wind Project (Carbon...

  10. Wind power soars

    SciTech Connect (OSTI)

    Flavin, C.

    1996-12-31

    Opinions on the world market for wind power are presented in this paper. Some data for global wind power generating capacity are provided. European and other markets are discussed individually. Estimated potential for wind power is given for a number of countries. 3 figs.

  11. 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 EA-1726: Final Environmental ...

  12. Wind & Water Power Newsletter

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

    & Water Power Newsletter - Sandia Energy Energy Search Icon Sandia Home Locations Contact ... Energy Conversion Efficiency Solar Energy Wind Energy Water Power Supercritical CO2 ...

  13. Upcoming Funding Opportunity for Wind Forecasting Improvement Project in

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

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

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

    Open Energy Info (EERE)

    4 Wind Farm Jump to: navigation, search Name Wind Power Partners '94 Wind Farm Facility Wind Power Partners '94 Sector Wind energy Facility Type Commercial Scale Wind Facility...

  15. Wind Power Outlook 2004

    SciTech Connect (OSTI)

    anon.

    2004-01-01

    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.

  16. Development of an Equivalent Wind Plant Power-Curve: Preprint

    SciTech Connect (OSTI)

    Wan, Y. H.; Ela, E.; Orwig, K.

    2010-06-01

    Development of an equivalent wind plant power-curve becomes highly desirable and useful in predicting plant output for a given wind forecast. Such a development is described and summarized in this paper.

  17. Wind Power Career Chat

    SciTech Connect (OSTI)

    L. Flowers

    2011-01-01

    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.

  18. 915 MHz Wind Profiler for Cloud Forecasting at Brookhaven National...

    Office of Scientific and Technical Information (OSTI)

    U.S. DEPARTMENT OF HP IENERGY Office of Science DOESC-ARM-15-024 915-MHz Wind Profiler ... M Jensen et al., March 2016, DOESC-ARM-15-024 915-MHz Wind Profiler for Cloud Forecasting ...

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

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

    The Wind Forecast Improvement Project (WFIP) is a U. S. Department of Energy (DOE) sponsored research project whose overarching goals are to improve the accuracy of short-term wind ...

  20. Shiloh Wind Power Project | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Project Jump to: navigation, search Name Shiloh Wind Power Project Facility Shiloh Wind Power Project Sector Wind energy Facility Type Commercial Scale Wind Facility...

  1. Fenton Wind Power Project | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Project Jump to: navigation, search Name Fenton Wind Power Project Facility Fenton Wind Power Project Sector Wind energy Facility Type Commercial Scale Wind Facility...

  2. Madison Wind Power Project | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Project Jump to: navigation, search Name Madison Wind Power Project Facility Madison Wind Power Project Sector Wind energy Facility Type Commercial Scale Wind Facility...

  3. Somerset Wind Power Project | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Project Jump to: navigation, search Name Somerset Wind Power Project Facility Somerset Wind Power Project Sector Wind energy Facility Type Commercial Scale Wind Facility...

  4. Desert Wind Power | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Jump to: navigation, search Name Desert Wind Power Facility Desert Wind Power Sector Wind energy Facility Type Commercial Scale Wind Facility Status Proposed Developer...

  5. Moraine Wind Power Project | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Project Jump to: navigation, search Name Moraine Wind Power Project Facility Moraine Wind Power Project Sector Wind energy Facility Type Commercial Scale Wind Facility...

  6. Fenner Wind Power Project | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Project Jump to: navigation, search Name Fenner Wind Power Project Facility Fenner Wind Power Project Sector Wind energy Facility Type Commercial Scale Wind Facility...

  7. Enabling Wind Power Nationwide

    SciTech Connect (OSTI)

    Jose, Zayas; Michael, Derby; Patrick, Gilman; Ananthan, Shreyas; Lantz, Eric; Cotrell, Jason; Beck, Fredic; Tusing, Richard

    2015-05-01

    Leveraging this experience, the U.S. Department of Energy’s (DOE’s) Wind and Water Power Technologies Office has evaluated the potential for wind power to generate electricity in all 50 states. This report analyzes and quantifies the geographic expansion that could be enabled by accessing higher above ground heights for wind turbines and considers the means by which this new potential could be responsibly developed.

  8. Renaissance for wind power

    SciTech Connect (OSTI)

    Flavin, C.

    1981-10-01

    Wind research and development during the 1970s and recent studies showing wind to be a feasible source of both electrical and mechanical power are behind the rapid expansion of wind energy. Improved technology should make wind energy economical in most countries having sufficient wind and appropriate needs. A form of solar energy, winds form a large pattern of global air circulation because the earth's rotation causes differences in pressure and oceans cause differences in temperature. New development in the ancient art of windmill making date to the 1973 oil embargo, but wind availability must be determined at local sites to determine feasibility. Whether design features of the new technology and the concept of large wind farms will be incorporated in national energy policies will depend on changing attitudes, acceptance by utilities, and the speed with which new information is developed and disseminated. 44 references, 6 figures. (DCK)

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

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

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

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

    SciTech Connect (OSTI)

    Not Available

    2010-05-01

    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.

  11. WINDExchange: Where Is Wind Power?

    Wind Powering America (EERE)

    Where Is Wind Power? WINDExchange offers maps to help you visualize the wind resource at a local level and to show how much wind power has been installed in the United States. How much wind power is on my land? Go to the wind resource maps. Go to the wind resource maps. Go to the wind resource maps. If you want to know how much wind power is in a particular area, these wind resource maps can give you a visual indication of the average wind speeds to a local level such as a neighborhood. These

  12. 2015 Iowa Wind Power Conference and Iowa Wind Energy Association...

    Office of Environmental Management (EM)

    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...

  13. Validation of Power Output for the WIND Toolkit

    SciTech Connect (OSTI)

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

    2014-09-01

    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.

  14. Crownbutte Wind Power LLC | Open Energy Information

    Open Energy Info (EERE)

    Crownbutte Wind Power LLC Jump to: navigation, search Name: Crownbutte Wind Power LLC Place: Mandan, North Dakota Zip: 58554 Sector: Wind energy Product: North Dakota wind power...

  15. Hardscrabble Wind Power Project | Open Energy Information

    Open Energy Info (EERE)

    Hardscrabble Wind Power Project Jump to: navigation, search Name Hardscrabble Wind Power Project Facility Hardscrabble Wind Power Project Sector Wind energy Facility Type...

  16. 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

    2009-11-20

    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.

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

    SciTech Connect (OSTI)

    Lantz, E.; Hand, M.

    2010-05-01

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

  18. Wind Power Career Chat, Wind And Water Power Program (WWPP)

    Wind Powering America (EERE)

    WIND AND WATER POWER PROGRAM Wind Power Career Chat Overview Students will learn 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. Trained and qualified workers manufacture, construct, operate, and manage wind energy facilities. In

  19. Green Power Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    Wind Farm Jump to: navigation, search Name Green Power Wind Farm Facility Green Power Sector Wind energy Facility Type Commercial Scale Wind Facility Status In Service Owner...

  20. Gansu Xinhui Wind Power | Open Energy Information

    Open Energy Info (EERE)

    Xinhui Wind Power Jump to: navigation, search Name: Gansu Xinhui Wind Power Place: China Sector: Wind energy Product: China-based joint venture engaged in developing wind projects....

  1. Northwestern Wind Power | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Jump to: navigation, search Name: Northwestern Wind Power Place: Wasco, Oregon Zip: OR 97065 Sector: Wind energy Product: US-based wind project developer. Coordinates:...

  2. Daqing Longjiang Wind Power | Open Energy Information

    Open Energy Info (EERE)

    Longjiang Wind Power Jump to: navigation, search Name: Daqing Longjiang Wind Power Place: Daqing, Heilongjiang Province, China Zip: 163316 Sector: Wind energy Product: Local wind...

  3. Laizhou Luneng Wind Power | Open Energy Information

    Open Energy Info (EERE)

    Laizhou Luneng Wind Power Jump to: navigation, search Name: Laizhou Luneng Wind Power Place: Laizhou, Shandong Province, China Sector: Wind energy Product: A wind project...

  4. Clear Wind Renewable Power | Open Energy Information

    Open Energy Info (EERE)

    Wind Renewable Power Jump to: navigation, search Name: Clear Wind Renewable Power Place: Minneapolis, Minnesota Zip: 55416 Sector: Wind energy Product: Clear Wind focuses its...

  5. Padoma Wind Power LLC | Open Energy Information

    Open Energy Info (EERE)

    Padoma Wind Power LLC Jump to: navigation, search Name: Padoma Wind Power LLC Place: La Jolla, California Zip: 92037 Sector: Wind energy Product: A wind energy consulting and...

  6. Evergreen Wind Power LLC | Open Energy Information

    Open Energy Info (EERE)

    Wind Power LLC Jump to: navigation, search Name: Evergreen Wind Power LLC Place: Bangor, Maine Zip: 4401 Sector: Wind energy Product: Formed to develop wind projects in Maine....

  7. Heilongjiang Lishu Wind Power | Open Energy Information

    Open Energy Info (EERE)

    Lishu Wind Power Jump to: navigation, search Name: Heilongjiang Lishu Wind Power Place: Heilongjiang Province, China Sector: Wind energy Product: China-based wind project developer...

  8. TS Wind Power Developers | Open Energy Information

    Open Energy Info (EERE)

    TS Wind Power Developers Jump to: navigation, search Name: TS Wind Power Developers Place: Satara, Maharashtra, India Sector: Wind energy Product: Setting up 30MW wind farm in...

  9. WINDExchange: What Is Wind Power?

    Wind Powering America (EERE)

    What Is Wind Power? A three-bladed wind turbine with the internal components visible. Six turbines in a row are electrically connected to the power grid. Wind Power Animation This aerial view of a wind turbine plant shows how a group of wind turbines can make electricity for the utility grid. The electricity is sent through transmission and distribution lines to homes, businesses, schools, and so on. View the wind turbine animation to see how a wind turbine works or take a look inside. Wind

  10. WATER POWER SOLAR POWER WIND POWER

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

    get curren WATER POWER SOLAR POWER WIND POWER Be part of the Clean Energy Generation! YOUR HOUSE BIOMASS ENERGY GEOTHERMAL ENERGY Clean energy can come from the sun. 2 The energy in wind can make electricity. We can make energy with moving water. Bioenergy comes from plants we can turn into fuel. Logs Wood Chips Straw Corn Switchgrass We can use energy from the earth to heat and cool our homes. Check out these cool websites to learn more about clean energy! Energy Information Administration

  11. Recent Trends in Variable Generation Forecasting and Its Value to the Power System

    SciTech Connect (OSTI)

    Orwig, Kirsten D.; Ahlstrom, Mark L.; Banunarayanan, Venkat; Sharp, Justin; Wilczak, James M.; Freedman, Jeffrey; Haupt, Sue Ellen; Cline, Joel; Bartholomy, Obadiah; Hamann, Hendrik F.; Hodge, Bri-Mathias; Finley, Catherine; Nakafuji, Dora; Peterson, Jack L.; Maggio, David; Marquis, Melinda

    2014-12-23

    We report that the rapid deployment of wind and solar energy generation systems has resulted in a need to better understand, predict, and manage variable generation. The uncertainty around wind and solar power forecasts is still viewed by the power industry as being quite high, and many barriers to forecast adoption by power system operators still remain. In response, the U.S. Department of Energy has sponsored, in partnership with the National Oceanic and Atmospheric Administration, public, private, and academic organizations, two projects to advance wind and solar power forecasts. Additionally, several utilities and grid operators have recognized the value of adopting variable generation forecasting and have taken great strides to enhance their usage of forecasting. In parallel, power system markets and operations are evolving to integrate greater amounts of variable generation. This paper will discuss the recent trends in wind and solar power forecasting technologies in the U.S., the role of forecasting in an evolving power system framework, and the benefits to intended forecast users.

  12. Recent Trends in Variable Generation Forecasting and Its Value to the Power System

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

    Orwig, Kirsten D.; Ahlstrom, Mark L.; Banunarayanan, Venkat; Sharp, Justin; Wilczak, James M.; Freedman, Jeffrey; Haupt, Sue Ellen; Cline, Joel; Bartholomy, Obadiah; Hamann, Hendrik F.; et al

    2014-12-23

    We report that the rapid deployment of wind and solar energy generation systems has resulted in a need to better understand, predict, and manage variable generation. The uncertainty around wind and solar power forecasts is still viewed by the power industry as being quite high, and many barriers to forecast adoption by power system operators still remain. In response, the U.S. Department of Energy has sponsored, in partnership with the National Oceanic and Atmospheric Administration, public, private, and academic organizations, two projects to advance wind and solar power forecasts. Additionally, several utilities and grid operators have recognized the value ofmore » adopting variable generation forecasting and have taken great strides to enhance their usage of forecasting. In parallel, power system markets and operations are evolving to integrate greater amounts of variable generation. This paper will discuss the recent trends in wind and solar power forecasting technologies in the U.S., the role of forecasting in an evolving power system framework, and the benefits to intended forecast users.« less

  13. 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...

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

    SciTech Connect (OSTI)

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

    2011-10-01

    The focus of this report is the wind forecasting system developed during this contract period with results of performance through the end of 2010. The report is intentionally high-level, with technical details disseminated at various conferences and academic papers. At the end of 2010, Xcel Energy managed the output of 3372 megawatts of installed wind energy. The wind plants span three operating companies1, serving customers in eight states2, and three market structures3. The great majority of the wind energy is contracted through power purchase agreements (PPAs). The remainder is utility owned, Qualifying Facilities (QF), distributed resources (i.e., 'behind the meter'), or merchant entities within Xcel Energy's Balancing Authority footprints. Regardless of the contractual or ownership arrangements, the output of the wind energy is balanced by Xcel Energy's generation resources that include fossil, nuclear, and hydro based facilities that are owned or contracted via PPAs. These facilities are committed and dispatched or bid into day-ahead and real-time markets by Xcel Energy's Commercial Operations department. Wind energy complicates the short and long-term planning goals of least-cost, reliable operations. Due to the uncertainty of wind energy production, inherent suboptimal commitment and dispatch associated with imperfect wind forecasts drives up costs. For example, a gas combined cycle unit may be turned on, or committed, in anticipation of low winds. The reality is winds stayed high, forcing this unit and others to run, or be dispatched, to sub-optimal loading positions. In addition, commitment decisions are frequently irreversible due to minimum up and down time constraints. That is, a dispatcher lives with inefficient decisions made in prior periods. In general, uncertainty contributes to conservative operations - committing more units and keeping them on longer than may have been necessary for purposes of maintaining reliability. The downside is costs are

  15. Wind to Power Systems | Open Energy Information

    Open Energy Info (EERE)

    Power Systems Jump to: navigation, search Name: Wind to Power Systems Place: Madrid, Spain Zip: 28108 Sector: Wind energy Product: Wind to Power Systems designs, supplies and...

  16. Berkshire Wind Power Cooperative | Open Energy Information

    Open Energy Info (EERE)

    Power Cooperative Jump to: navigation, search Name: Berkshire Wind Power Cooperative Place: Holyoke, Massachusetts Sector: Wind energy Product: The Berkshire Wind Power Cooperative...

  17. Coal Fired Power Generation Market Forecast | OpenEI Community

    Open Energy Info (EERE)

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

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

  19. Enabling Wind Power Nationwide

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

    Wind Power Nationwide May 2015 This report is being disseminated by the U.S. Department of Energy (DOE). As such, this document was prepared in compliance with Section 515 of the Treasury and General Government Appropriations Act for fiscal year 2001 (Public Law 106-554) and information quality guidelines issued by DOE. Though this report does not constitute "influential" information, as that term is defined in DOE's information quality guidelines or the Office of Management and

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

    SciTech Connect (OSTI)

    Not Available

    2012-02-01

    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.

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

    SciTech Connect (OSTI)

    Not Available

    2012-04-01

    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.

  2. Wind Power: Options for Industry

    SciTech Connect (OSTI)

    Not Available

    2003-03-01

    This six-page brochure outlines ways for industry to integrate wind power, including assessing wind power, building wind farms, using a developer, capitalizing on technology, enhancing the corporate image, and preparing RFPs. Company examples and information resources are also provided.

  3. Marquiss Wind Power | Open Energy Information

    Open Energy Info (EERE)

    Marquiss Wind Power Jump to: navigation, search Name: Marquiss Wind Power Place: Folsom, California Zip: 95630 Sector: Wind energy Product: US-based manufacturer of patented ducted...

  4. CECIC Wind Power Zhangbei | Open Energy Information

    Open Energy Info (EERE)

    CECIC Wind Power Zhangbei Jump to: navigation, search Name: CECIC Wind Power (Zhangbei) Place: Zhangbei, Hebei Province, China Sector: Wind energy Product: A joint venture of CECIC...

  5. Guohua Hulunbeier Wind Power | Open Energy Information

    Open Energy Info (EERE)

    Hulunbeier Wind Power Jump to: navigation, search Name: Guohua (Hulunbeier) Wind Power Place: Hulunbeier, Inner Mongolia Autonomous Region, China Zip: 21300 Sector: Wind energy...

  6. Guohua Qiqihaer Wind Power | Open Energy Information

    Open Energy Info (EERE)

    Qiqihaer Wind Power Jump to: navigation, search Name: Guohua (Qiqihaer) Wind Power Place: Qiqihaer, Heilongjiang Province, China Zip: 161005 Sector: Wind energy Product: Guohua...

  7. Wind Power Associates LLC | Open Energy Information

    Open Energy Info (EERE)

    Power Associates LLC Jump to: navigation, search Name: Wind Power Associates LLC Place: Goldendale, Washington State Sector: Wind energy Product: Wind farm developer and operater....

  8. Infinity Wind Power Inc | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Inc Jump to: navigation, search Name: Infinity Wind Power, Inc. Place: Santa Barbara, California Zip: 93105 Sector: Renewable Energy, Wind energy Product:...

  9. Peel Wind Power | Open Energy Information

    Open Energy Info (EERE)

    Peel Wind Power Jump to: navigation, search Name: Peel Wind Power Place: United Kingdom Product: Clean energy subsidiary of property company Peel Holdings. References: Peel Wind...

  10. Cielo Wind Power | Open Energy Information

    Open Energy Info (EERE)

    Cielo Wind Power Jump to: navigation, search Name: Cielo Wind Power Address: 823 Congress Avenue Place: Austin, Texas Zip: 78701 Region: Texas Area Sector: Wind energy Product:...

  11. EERE 2014 Wind Technologies Market Report Finds Wind Power at...

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

    2014 Wind Technologies Market Report Finds Wind Power at Record Low Prices EERE 2014 Wind Technologies Market Report Finds Wind Power at Record Low Prices August 10, 2015 - 11:00am ...

  12. The Wind Forecast Improvement Project (WFIP): A Public/Private Partnership for Improving Short Term Wind Energy Forecasts and Quantifying the Benefits of Utility Operations. The Southern Study Area, Final Report

    SciTech Connect (OSTI)

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

    2014-04-30

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

  13. DOE Wind and Water Power Technologies Office

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

    Wind and Water Power Technologies Office - Sandia Energy Energy Search Icon Sandia Home ... Stationary Power Energy Conversion Efficiency Solar Energy Wind Energy Water Power ...

  14. Southwest Wind Power | Open Energy Information

    Open Energy Info (EERE)

    Power Jump to: navigation, search Name: Southwest Wind Power Place: Flagstaff, AZ Website: www.windenergy.com References: Southwest Wind Power1 Information About Partnership...

  15. Active Power Control from Wind Power (Presentation)

    SciTech Connect (OSTI)

    Ela, E.; Brooks, D.

    2011-04-01

    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.

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

    Open Energy Info (EERE)

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

  17. PBS: Wind Power for Educators

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

    PBS: Wind Power for Educators Grades: 5-8, 9-12 Topic: Wind Energy Owner: PBS This educational material is brought to you by the U.S. Department of Energy's Office of Energy Efficiency and Renewable Energy. Click here to find out more! NOW with Bill Moyers. For Educators. Wind Power | PBS Page 1 of 5 Support for PBS.org provided by: What's this? Wind Power More on This Lesson: Select One Lesson Plan This lesson is designed for physical science, earth science, or environmental science classrooms,

  18. Wild Horse Wind Power Project | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Project Jump to: navigation, search Name Wild Horse Wind Power Project Facility Wild Horse Wind Power Project Sector Wind energy Facility Type Commercial Scale Wind...

  19. Mill Run Wind Power Project | Open Energy Information

    Open Energy Info (EERE)

    Run Wind Power Project Jump to: navigation, search Name Mill Run Wind Power Project Facility Mill Run Wind Power Project Sector Wind energy Facility Type Commercial Scale Wind...

  20. Devon Wind Power Ltd | Open Energy Information

    Open Energy Info (EERE)

    Devon Wind Power Ltd Jump to: navigation, search Name: Devon Wind Power Ltd Place: Exeter, United Kingdom Zip: EX1 1TL Sector: Wind energy Product: Wind project developer - has...

  1. Wind power outlook 2006

    SciTech Connect (OSTI)

    anon.

    2006-04-15

    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.

  2. Wind Vision: A New Era for Wind Power

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

    Highlights Wind Vision: A New Era for Wind Power in the United States Wind Vision Objectives The U.S. Department of Energy's (DOE's) Wind and Water Power Technologies Office has conducted a comprehensive analysis to evaluate future pathways for the wind industry. Through a broad-based collaborative effort, the Wind Vision analysis includes four principal objectives: 1. Documentation of the current state of wind power in the United States and identification of key technological and societal

  3. Wind Power Energia | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Energia Place: Fortaleza, Ceara, Brazil Zip: 60160-230 Sector: Wind energy Product: Brazil-based small scale wind turbine manufacturer. Coordinates: -3.718404,...

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

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

    Powering America's Wind for Schools Team Honored with Wirth Chair Award Wind Powering America's Wind for Schools Team Honored with Wirth Chair Award May 1, 2012 - 2:46pm Addthis ...

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

    Wind Powering America (EERE)

    Wind Powering America Fact Sheet Series Energy Efficiency & Renewable Energy Wind for Schools Project Power System Brief Wind for Schools Project Power System Brief Wind for Schools Project Power System Brief This fact sheet provides an overview of the system components of a Wind Powering America Wind for Schools project. Wind Powering America's (WPA's) Wind for Schools project uses a basic system configuration for each school project. The system incorporates a single SkyStream(tm) wind

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

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

    Energy Wind Power Today, 2010, Wind and Water Power Program (WWPP) Wind Power Today, 2010, Wind and Water Power Program (WWPP) 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. 47531.pdf (6.07 MB) More Documents & Publications Federal Interagency Wind Turbine Radar Interference Mitigation Strategy Wind Program Accomplishments Final Report DE-EE0005380 - Assessment of

  7. Cielo Wind Power LLC | Open Energy Information

    Open Energy Info (EERE)

    Power LLC Jump to: navigation, search Name: Cielo Wind Power LLC Place: Austin, Texas Zip: 78701 2459 Sector: Wind energy Product: Currently the largest wind power developer in the...

  8. US DOE Wind Powering America | Open Energy Information

    Open Energy Info (EERE)

    US DOE Wind Powering America (Redirected from Wind Powering America) Jump to: navigation, search Logo: Wind Powering America Name Wind Powering America AgencyCompany Organization...

  9. Enabling Wind Power Nationwide | Department of Energy

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

    Enabling Wind Power Nationwide Enabling Wind Power Nationwide The cover of the 2015 report Enabling Wind Power Nationwide with a wind turbine on the right side, surrounded by trees. This report shows how the United States can unlock the vast potential for wind energy deployment in all 50 states-made possible through the next-generation of larger wind turbines. It highlights wind energy's potential to generate electricity even in states with no utility-scale wind energy development today. Through

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

    Broader source: Energy.gov [DOE]

    The Wind Forecast Improvement Project (WFIP) is a U. S. Department of Energy (DOE) sponsored research project whose overarching goals are to improve the accuracy of short-term wind energy forecasts, and to demonstrate the economic value of these improvements.

  11. Application of Ensemble Sensitivity Analysis to Observation Targeting for Short-term Wind Speed Forecasting

    SciTech Connect (OSTI)

    Zack, J; Natenberg, E; Young, S; Manobianco, J; Kamath, C

    2010-02-21

    The operators of electrical grids, sometimes referred to as Balancing Authorities (BA), typically make critical decisions on how to most reliably and economically balance electrical load and generation in time frames ranging from a few minutes to six hours ahead. At higher levels of wind power generation, there is an increasing need to improve the accuracy of 0- to 6-hour ahead wind power forecasts. Forecasts on this time scale have typically been strongly dependent on short-term trends indicated by the time series of power production and meteorological data from a wind farm. Additional input information is often available from the output of Numerical Weather Prediction (NWP) models and occasionally from off-site meteorological towers in the region surrounding the wind generation facility. A widely proposed approach to improve short-term forecasts is the deployment of off-site meteorological towers at locations upstream from the wind generation facility in order to sense approaching wind perturbations. While conceptually appealing, it turns out that, in practice, it is often very difficult to derive significant benefit in forecast performance from this approach. The difficulty is rooted in the fact that the type, scale, and amplitude of the processes controlling wind variability at a site change from day to day if not from hour to hour. Thus, a location that provides some useful forecast information for one time may not be a useful predictor a few hours later. Indeed, some processes that cause significant changes in wind power production operate predominantly in the vertical direction and thus cannot be monitored by employing a network of sensors at off-site locations. Hence, it is very challenging to determine the type of sensors and deployment locations to get the most benefit for a specific short-term forecast application. Two tools recently developed in the meteorological research community have the potential to help determine the locations and parameters to

  12. Voluntary Green Power Market Forecast through 2015

    SciTech Connect (OSTI)

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

    2010-05-01

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

  13. Boulder Wind Power | Open Energy Information

    Open Energy Info (EERE)

    Power Jump to: navigation, search Name: Boulder Wind Power Address: 2845 Wilderness Place Suite 201 Place: Boulder, CO Zip: 80301 Sector: Wind energy Website: www.boulderwindpower....

  14. India Wind Power Ltd | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Ltd Place: Ahmedabad, Gujarat, India Zip: 380054 Product: Ahmedabad-based turbine manufacturer and project developer. References: India Wind Power Ltd1 This article is...

  15. Dynamic Models for Wind Turbines and Wind Power Plants

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

    ... Each of these models includes representations of general turbine aerodynamics, the ... 9 1.1.2 Wind power integration and wind turbine modeling ......

  16. 1,"Kingdom Community Wind","Wind","Green Mountain Power Corp...

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

    Vermont" ,"Plant","Primary energy source","Operating company","Net summer capacity (MW)" 1,"Kingdom Community Wind","Wind","Green Mountain Power Corp",65 2,"J C ...

  17. 2008 Wind Energy Projects, Wind Powering America (Poster)

    SciTech Connect (OSTI)

    Not Available

    2009-01-01

    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.

  18. Wind Powering America Hosts Fifth Annual Wind for Schools Summit...

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

    Fifth Annual Wind for Schools Summit Wind Powering America Hosts Fifth Annual Wind for Schools Summit February 24, 2012 - 10:46am Addthis This is an excerpt from the First Quarter ...

  19. Wind Power Ltd | Open Energy Information

    Open Energy Info (EERE)

    Conducting research into alternative, large scale wind turbine design. References: Wind Power Ltd1 This article is a stub. You can help OpenEI by expanding it. Wind Power...

  20. Tianjin Jinneng Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Co Ltd Jump to: navigation, search Name: Tianjin Jinneng Wind Power Co Ltd Place: Tianjin Municipality, China Sector: Wind energy Product: Tianjin-based wind power...

  1. White Creek Wind Power Project | Open Energy Information

    Open Energy Info (EERE)

    Creek Wind Power Project Jump to: navigation, search Name White Creek Wind Power Project Facility White Creek Wind Power Project Sector Wind energy Facility Type Commercial Scale...

  2. Kittitas Valley Wind Power Project | Open Energy Information

    Open Energy Info (EERE)

    Valley Wind Power Project Jump to: navigation, search Name Kittitas Valley Wind Power Project Facility Kittitas Valley Wind Power Project Sector Wind energy Facility Type...

  3. Guodian Linghai Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Linghai Wind Power Co Ltd Jump to: navigation, search Name: Guodian Linghai Wind Power Co Ltd Place: China Sector: Wind energy Product: Wind power project developer. References:...

  4. Oasis Power Partners Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    Oasis Power Partners Wind Farm Jump to: navigation, search Name Oasis Power Partners Wind Farm Facility Oasis Power Partners Sector Wind energy Facility Type Commercial Scale Wind...

  5. Buffalo Ridge II Wind Power Project | Open Energy Information

    Open Energy Info (EERE)

    II Wind Power Project Jump to: navigation, search Name Buffalo Ridge II Wind Power Project Facility Buffalo Ridge II Wind Power Project Sector Wind energy Facility Type Commercial...

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

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

    SciTech Connect (OSTI)

    Valentino, L.; Valenzuela, V.; Botterud, A.; Zhou, Z.; Conzelmann, G.

    2012-01-01

    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.

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

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

    | Department of Energy 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 Environmental Assessment Loan Guarantee to Kahuku Wind Power, LLC for Construction of the Kahuku Wind Power Facility in Kahuku, O'ahu, Hawai'i May 13, 2010 Kahuku Wind Power Biological Opinion Kahuku Wind Power, LLC, Construction of the Kahuku Wind Power Facility in Kahuku, O'ahu, Hawaii May 27, 2010

  9. 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.

    2013-03-19

    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.

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

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

    December 2013, the U.S. wind industry totaled more than 60,000 MW of installed power capacity, over 20% of the 300,000 MW needed to achieve 20% by 2030. Wind power is expanding ...

  11. Long-Term Wind Power Variability

    SciTech Connect (OSTI)

    Wan, Y. H.

    2012-01-01

    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.

  12. Wind and Power | Open Energy Information

    Open Energy Info (EERE)

    search Name: Wind and Power Place: Warszawa, Poland Zip: 04-320 Sector: Solar, Wind energy Product: The firm offers small-scale PV panels, inverters, accumulators, solar...

  13. Wind Powering America FY09 Activities Summary

    SciTech Connect (OSTI)

    none,

    2010-03-22

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

  14. Scotrenewables Wind Power and Marine Power Ltd | Open Energy...

    Open Energy Info (EERE)

    Wind Power and Marine Power Ltd Jump to: navigation, search Name: Scotrenewables Wind Power and Marine Power Ltd Place: Orkey, Scotland, United Kingdom Zip: KW16 3AW Sector:...

  15. Oak Creek Wind Power Phase 2 Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Phase 2 Wind Farm Jump to: navigation, search Name Oak Creek Wind Power Phase 2 Wind Farm Facility Oak Creek Wind Power Phase 2 Sector Wind energy Facility Type...

  16. China Longyuan Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Co Ltd Jump to: navigation, search Name: China Longyuan Wind Power Co Ltd Place: China Sector: Wind energy Product: Wind farm development subsidiary of Longyuan...

  17. Tianyuan Juneng Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Tianyuan Juneng Wind Power Co Ltd Jump to: navigation, search Name: Tianyuan Juneng Wind Power Co Ltd Place: Shuangliao, Jilin Province, China Sector: Wind energy Product: Wind...

  18. Lanco Wind Power Pvt Ltd | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Pvt Ltd Jump to: navigation, search Name: Lanco Wind Power Pvt. Ltd. Place: Hyderabad, Andhra Pradesh, India Sector: Wind energy Product: Hyderabad-based wind division...

  19. Nordex Baoding Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Baoding Wind Power Co Ltd Jump to: navigation, search Name: Nordex (Baoding) Wind Power Co. Ltd. Place: Baoding, Hebei Province, China Sector: Wind energy Product: Chinese wind...

  20. Harbin Wind Power Equipment Company | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Equipment Company Jump to: navigation, search Name: Harbin Wind Power Equipment Company Place: Harbin, Heilongjiang Province, China Sector: Wind energy Product: A wind...

  1. Liaoning Kangping Jinshan Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Kangping Jinshan Wind Power Co Ltd Jump to: navigation, search Name: Liaoning Kangping Jinshan Wind Power Co Ltd Place: Liaoning Province, China Sector: Wind energy Product: Wind...

  2. Liaoning Zhangwu Jinshan Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Zhangwu Jinshan Wind Power Co Ltd Jump to: navigation, search Name: Liaoning Zhangwu Jinshan Wind Power Co Ltd Place: Liaoning Province, China Sector: Wind energy Product: Wind...

  3. Wind Power Renewables | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Renewables Place: Norfolk, United Kingdom Zip: NR29 5BG Sector: Wind energy Product: Wind project developer Coordinates: 36.846825, -76.285069 Show Map Loading...

  4. Offshore Wind Power | Open Energy Information

    Open Energy Info (EERE)

    Offshore Wind Power Place: St Albans, United Kingdom Zip: AL1 3AW Sector: Wind energy Product: Formed to develop offshore wind farms around the coast of Great Britain. References:...

  5. Wind Powering America Initiative (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2011-01-01

    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.

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

    SciTech Connect (OSTI)

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

    2013-10-01

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

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

    SciTech Connect (OSTI)

    Not Available

    2010-02-01

    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.

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

    SciTech Connect (OSTI)

    Baring-Gould, I.

    2009-08-01

    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.

  9. Success Stories (Postcard), Wind Powering America (WPA)

    SciTech Connect (OSTI)

    Not Available

    2012-02-01

    Wind Powering America shares best practices and lessons learned on the Wind Powering America website. This postcard is an outreach tool that provides a brief description of the success stories as well as the URL.

  10. wind powering america | OpenEI Community

    Open Energy Info (EERE)

    wind powering america Home Graham7781's picture Submitted by Graham7781(2017) Super contributor 30 January, 2013 - 10:55 Wind Powering America Guidebook officially launched on...

  11. Loranger Power Generation Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    Loranger Power Generation Wind Farm Jump to: navigation, search Name Loranger Power Generation Wind Farm Facility Loranger Power Generation Sector Wind energy Facility Type...

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

    Open Energy Info (EERE)

    Wind Power 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...

  13. Shaokatan Power Partners Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    Power Partners Wind Farm Jump to: navigation, search Name Shaokatan Power Partners Wind Farm Facility Shaokatan Power Partners Sector Wind energy Facility Type Commercial Scale...

  14. Federal Incentives for Wind Power Deployment | Department of...

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

    Incentives for Wind Power Deployment Federal Incentives for Wind Power Deployment Document that lists some of the major federal incentives for wind power deployment. ...

  15. Traverse City Light & Power Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    City Light & Power Wind Farm Jump to: navigation, search Name Traverse City Light & Power Wind Farm Facility Traverse City Light & Power Sector Wind energy Facility Type Community...

  16. Minnkota Power Cooperative Wind Turbine (Petersburg) | Open Energy...

    Open Energy Info (EERE)

    Minnkota Power Cooperative Wind Turbine (Petersburg) Jump to: navigation, search Name Minnkota Power Cooperative Wind Turbine (Petersburg) Facility Minnkota Power Cooperative Wind...

  17. Wind Power Partners '90-'92 Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    0-'92 Wind Farm Jump to: navigation, search Name Wind Power Partners '90-'92 Wind Farm Facility Wind Power Partners '90-'92 Sector Wind energy Facility Type Commercial Scale Wind...

  18. Wind Powering America Program Overview (Fact Sheet)

    SciTech Connect (OSTI)

    Not Available

    2008-04-01

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

  19. Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting

    SciTech Connect (OSTI)

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

    2015-11-10

    Accurate solar photovoltaic (PV) power forecasting allows utilities to reliably utilize solar resources on their systems. However, to truly measure the improvements that any new solar forecasting methods provide, it is important to develop a methodology for determining baseline and target values for the accuracy of solar forecasting at different spatial and temporal scales. This paper aims at developing a framework to derive baseline and target values for a suite of generally applicable, value-based, and custom-designed solar forecasting metrics. The work was informed by close collaboration with utility and independent system operator partners. The baseline values are established based on state-of-the-art numerical weather prediction models and persistence models in combination with a radiative transfer model. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of PV power output. The proposed reserve-based methodology is a reasonable and practical approach that can be used to assess the economic benefits gained from improvements in accuracy of solar forecasting. Lastly, the financial baseline and targets can be translated back to forecasting accuracy metrics and requirements, which will guide research on solar forecasting improvements toward the areas that are most beneficial to power systems operations.

  20. Baseline and target values for regional and point PV power forecasts: Toward improved solar forecasting

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

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

    2015-11-10

    Accurate solar photovoltaic (PV) power forecasting allows utilities to reliably utilize solar resources on their systems. However, to truly measure the improvements that any new solar forecasting methods provide, it is important to develop a methodology for determining baseline and target values for the accuracy of solar forecasting at different spatial and temporal scales. This paper aims at developing a framework to derive baseline and target values for a suite of generally applicable, value-based, and custom-designed solar forecasting metrics. The work was informed by close collaboration with utility and independent system operator partners. The baseline values are established based onmore » state-of-the-art numerical weather prediction models and persistence models in combination with a radiative transfer model. The target values are determined based on the reduction in the amount of reserves that must be held to accommodate the uncertainty of PV power output. The proposed reserve-based methodology is a reasonable and practical approach that can be used to assess the economic benefits gained from improvements in accuracy of solar forecasting. Lastly, the financial baseline and targets can be translated back to forecasting accuracy metrics and requirements, which will guide research on solar forecasting improvements toward the areas that are most beneficial to power systems operations.« less

  1. WIND POWER PROGRAM WIND PROGRAM ACCOMPLISHMENTS U.S. Department of Energy's Wind

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

    PROGRAM WIND PROGRAM ACCOMPLISHMENTS U.S. Department of Energy's Wind Program-Lasting Impressions State of the Industry Wind power has the potential to provide vast amounts electricity for the nation with more than 66,000 MW of installed power capacity delivering clean energy to homes and businesses. Wind power is expanding across the United States with utility-scale turbines deployed in 39 states and territories. Texas alone has more installed wind power than all but five countries around the

  2. Engineering innovation to reduce wind power COE

    SciTech Connect (OSTI)

    Ammerman, Curtt Nelson

    2011-01-10

    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.

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

    SciTech Connect (OSTI)

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

    2011-01-17

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

  4. Gansu China Power Jiuquan Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    China Power Jiuquan Wind Power Co Ltd Jump to: navigation, search Name: Gansu China Power Jiuquan Wind Power Co Ltd Place: Gansu Province, China Sector: Wind energy Product:...

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

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

    Wind and Water Power Fact Sheets The capabilities for research at the National Wind Technology Center (NWTC) are numerous. Below you will find fact sheets about the many facilities and capabilities at the NWTC, including field testing research, modeling and simulation, and the Wind-Wildlife Impacts Literature Database. Fact Sheet Cover 35 Years of Innovation: Leading the Way to a Clean Energy Future Fact Sheet Cover Wind-Wildlife Impacts Literature Database (WILD) Fact Sheet Cover NREL Software

  6. Wind and Water Power Program - Wind Power Opens Door To Diverse Opportunities (Green Jobs)

    SciTech Connect (OSTI)

    2010-04-01

    The strong projected growth of wind power will require a stream of trained and qualified workers to manufacture, construct, operate, and maintain the wind energy facilities.

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

    Office of Energy Efficiency and Renewable Energy (EERE)

    On April 4, 2014 the U.S. Department of Energy announced a $2.5 million funding opportunity entitled “Wind Forecasting Improvement Project in Complex Terrain.” By researching the physical processes...

  8. Mountain View Power Partners II Wind Farm | Open Energy Information

    Open Energy Info (EERE)

    II Wind Farm Jump to: navigation, search Name Mountain View Power Partners II Wind Farm Facility Mountain View Power Partners II Sector Wind energy Facility Type Commercial Scale...

  9. Heilongjiang Fulong Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Fulong Wind Power Co Ltd Jump to: navigation, search Name: Heilongjiang Fulong Wind Power Co., Ltd. Place: Fujin, Heilongjiang Province, China Zip: 156100 Sector: Wind energy...

  10. Ningxia Tianjing Shenzhou Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Tianjing Shenzhou Wind Power Co Ltd Jump to: navigation, search Name: Ningxia Tianjing Shenzhou Wind Power Co Ltd Place: Ningxia Autonomous Region, China Zip: 750002 Sector: Wind...

  11. Zhangjiakou Kunyuan Wind Power Equipment Co | Open Energy Information

    Open Energy Info (EERE)

    Kunyuan Wind Power Equipment Co Jump to: navigation, search Name: Zhangjiakou Kunyuan Wind Power Equipment Co Place: Zhangjiakou, Hebei Province, China Sector: Wind energy Product:...

  12. Miracle Wind Power Components Manufacture Co Ltd | Open Energy...

    Open Energy Info (EERE)

    Wind Power Components Manufacture Co Ltd Jump to: navigation, search Name: Miracle Wind Power Components Manufacture Co Ltd Place: Wuxi, Jiangsu Province, China Sector: Wind energy...

  13. Guohua Dongtai Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Dongtai Wind Power Co Ltd Jump to: navigation, search Name: Guohua (Dongtai) Wind Power Co Ltd Place: Dongtai, Jiangsu Province, China Zip: 224200 Sector: Wind energy Product:...

  14. Jiangsu Longyuan Wind Power Co | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Co Jump to: navigation, search Name: Jiangsu Longyuan Wind Power Co. Place: Jiangsu Province, China Sector: Wind energy Product: A joint-venture established for the...

  15. Zhongshan Yixiong Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Yixiong Wind Power Co Ltd Jump to: navigation, search Name: Zhongshan Yixiong Wind Power Co Ltd Place: Zhongshan, Guangdong Province, China Sector: Wind energy Product: A producer...

  16. Baicheng Fuyu Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Baicheng Fuyu Wind Power Co Ltd Jump to: navigation, search Name: Baicheng Fuyu Wind Power Co. Ltd. Place: Baicheng City, Jiangsu Province, China Zip: 137000 Sector: Wind energy...

  17. Qingdao Hengfeng Wind Power Generator Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Hengfeng Wind Power Generator Co Ltd Jump to: navigation, search Name: Qingdao Hengfeng Wind Power Generator Co Ltd Place: Jiaonan, Shandong Province, China Sector: Wind energy...

  18. Inner Mongolia Damo Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Damo Wind Power Co Ltd Jump to: navigation, search Name: Inner Mongolia Damo Wind Power Co Ltd Place: Inner Mongolia Autonomous Region, China Sector: Wind energy Product:...

  19. Baoding Huide Wind Power Engineering Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Huide Wind Power Engineering Co Ltd Jump to: navigation, search Name: Baoding Huide Wind Power Engineering Co Ltd Place: Baoding, Hebei Province, China Sector: Wind energy Product:...

  20. Jilin Tianhe Wind Power Equipment Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Equipment Co Ltd Jump to: navigation, search Name: Jilin Tianhe Wind Power Equipment Co Ltd Place: Baicheng, Jilin Province, China Sector: Wind energy Product:...

  1. Zhejiang Wind Power Development Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Development Co Ltd Jump to: navigation, search Name: Zhejiang Wind Power Development Co Ltd Place: Hangzhou, Zhejiang Province, China Zip: 31005 Sector: Wind energy...

  2. Huaneng Shantou Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Shantou Wind Power Co Ltd Jump to: navigation, search Name: Huaneng Shantou Wind Power Co Ltd Place: Guangzhou, Guangdong Province, China Zip: 510630 Sector: Wind energy Product:...

  3. Zhejiang Xingxing Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Xingxing Wind Power Co Ltd Jump to: navigation, search Name: Zhejiang Xingxing Wind Power Co Ltd Place: Taizhou, Zhejiang Province, China Sector: Wind energy Product: Taizhou-based...

  4. Foshan Dongxing Fengying Wind Power Equipment Co Ltd | Open Energy...

    Open Energy Info (EERE)

    Dongxing Fengying Wind Power Equipment Co Ltd Jump to: navigation, search Name: Foshan Dongxing Fengying Wind Power Equipment Co Ltd Place: Foshan, China Zip: 528000 Sector: Wind...

  5. Jilin Longyuan Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Longyuan Wind Power Co Ltd Jump to: navigation, search Name: Jilin Longyuan Wind Power Co Ltd Place: Changchun, Jilin Province, China Zip: 130061 Sector: Wind energy Product: Joint...

  6. Ningxia Yinyi Wind Power Generation Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Yinyi Wind Power Generation Co Ltd Jump to: navigation, search Name: Ningxia Yinyi Wind Power Generation Co Ltd Place: Ningxia Autonomous Region, China Sector: Wind energy Product:...

  7. Xinjiang Tianfeng Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Tianfeng Wind Power Co Ltd Jump to: navigation, search Name: Xinjiang Tianfeng Wind Power Co Ltd Place: Urumuqi, Xinjiang Autonomous Region, China Zip: 830002 Sector: Wind energy...

  8. Inner Mongolia Wind Power Corporation | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Corporation Jump to: navigation, search Name: Inner Mongolia Wind Power Corporation Place: Inner Mongolia Autonomous Region, China Sector: Wind energy Product: A company...

  9. Jiangsu Guoshen Wind Power Equipment Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Guoshen Wind Power Equipment Co Ltd Jump to: navigation, search Name: Jiangsu Guoshen Wind Power Equipment Co Ltd Place: Yancheng, Jiangsu Province, China Sector: Wind energy...

  10. Yongsheng National Energy Wind Power Co | Open Energy Information

    Open Energy Info (EERE)

    Yongsheng National Energy Wind Power Co Jump to: navigation, search Name: Yongsheng National Energy Wind Power Co Place: Inner Mongolia Autonomous Region, China Sector: Wind energy...

  11. Dongbai Mountain Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Dongbai Mountain Wind Power Co Ltd Jump to: navigation, search Name: Dongbai Mountain Wind Power Co Ltd Place: Zhejiang Province, China Sector: Wind energy Product: Dongyang-based...

  12. Changdao Liankai Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Changdao Liankai Wind Power Co Ltd Jump to: navigation, search Name: Changdao Liankai Wind Power Co Ltd Place: Yantai City, Shandong Province, China Zip: 265800 Sector: Wind energy...

  13. Yantai Tianfeng Wind Power Development Co Ltd | Open Energy Informatio...

    Open Energy Info (EERE)

    Tianfeng Wind Power Development Co Ltd Jump to: navigation, search Name: Yantai Tianfeng Wind Power Development Co Ltd Place: Shandong Province, China Sector: Wind energy Product:...

  14. Nantong Kailian Wind Power Company | Open Energy Information

    Open Energy Info (EERE)

    Kailian Wind Power Company Jump to: navigation, search Name: Nantong Kailian Wind Power Company Place: Nantong, Jiangsu Province, China Zip: 226009 Sector: Wind energy Product:...

  15. Jilin Wind Power Stockholding Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Wind Power Stockholding Co Ltd Jump to: navigation, search Name: Jilin Wind Power Stockholding Co Ltd Place: Changchun, Jilin Province, China Zip: 130021 Sector: Hydro, Wind energy...

  16. Lianyungang Zhongneng United Wind Power Co Ltd | Open Energy...

    Open Energy Info (EERE)

    Zhongneng United Wind Power Co Ltd Jump to: navigation, search Name: Lianyungang Zhongneng United Wind Power Co Ltd Place: Lianyungang, Jiangsu Province, China Sector: Wind energy...

  17. Hangtian Longyuan Benxi Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Hangtian Longyuan Benxi Wind Power Co Ltd Jump to: navigation, search Name: Hangtian Longyuan (Benxi) Wind Power Co Ltd Place: Liaoning Province, China Sector: Wind energy Product:...

  18. Jilin Taihe Wind Power Limited | Open Energy Information

    Open Energy Info (EERE)

    Taihe Wind Power Limited Jump to: navigation, search Name: Jilin Taihe Wind Power Limited Place: Zhenlai, Jilin Province, China Sector: Wind energy Product: Top Well and Tianjin DH...

  19. Xilinguole Guotai Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Xilinguole Guotai Wind Power Co Ltd Jump to: navigation, search Name: Xilinguole Guotai Wind Power Co Ltd Place: China Sector: Wind energy Product: Hong Kong-based project...

  20. GWPS Global Wind Power Systems | Open Energy Information

    Open Energy Info (EERE)

    GWPS Global Wind Power Systems Jump to: navigation, search Name: GWPS (Global Wind Power Systems) Place: Hamburg, Germany Zip: 20095 Sector: Wind energy Product: Company...

  1. Zhangbei Guotou Wind Power Plant | Open Energy Information

    Open Energy Info (EERE)

    Zhangbei Guotou Wind Power Plant Jump to: navigation, search Name: Zhangbei Guotou Wind Power Plant Place: Beijing Municipality, China Zip: 100037 Sector: Wind energy Product: A...

  2. Datang Zhangzhou Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Datang Zhangzhou Wind Power Co Ltd Jump to: navigation, search Name: Datang Zhangzhou Wind Power Co Ltd Place: Zhangzhou, Fujian Province, China Sector: Wind energy Product:...

  3. Inner Mongolia Sansheng Wind Power | Open Energy Information

    Open Energy Info (EERE)

    Sansheng Wind Power Jump to: navigation, search Name: Inner Mongolia Sansheng Wind Power Place: Inner Mongolia Autonomous Region, China Sector: Wind energy Product: China-based...

  4. Tongliao Taihe Wind Power Limited | Open Energy Information

    Open Energy Info (EERE)

    Taihe Wind Power Limited Jump to: navigation, search Name: Tongliao Taihe Wind Power Limited Place: Tongliao City, Inner Mongolia Autonomous Region, China Sector: Wind energy...

  5. Guodian Hefeng Wind Power Development Company | Open Energy Informatio...

    Open Energy Info (EERE)

    Hefeng Wind Power Development Company Jump to: navigation, search Name: Guodian Hefeng Wind Power Development Company Place: Huludao, Liaoning Province, China Sector: Wind energy...

  6. The CECIC Wind Power Xinjiang Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    CECIC Wind Power Xinjiang Co Ltd Jump to: navigation, search Name: The CECIC Wind Power (Xinjiang) Co Ltd Place: Beijing, Beijing Municipality, China Zip: 100037 Sector: Wind...

  7. Beijing Wende Xingye Wind Power Technology Co Ltd | Open Energy...

    Open Energy Info (EERE)

    Wende Xingye Wind Power Technology Co Ltd Jump to: navigation, search Name: Beijing Wende Xingye Wind Power Technology Co Ltd Place: Beijing, China Sector: Wind energy Product:...

  8. Huaneng Shouguang Wind Power Company Limited | Open Energy Information

    Open Energy Info (EERE)

    Huaneng Shouguang Wind Power Company Limited Jump to: navigation, search Name: Huaneng Shouguang Wind Power Company Limited Place: Shouguang, Shandong Province, China Sector: Wind...

  9. Yichun Xinganling Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Yichun Xinganling Wind Power Co Ltd Jump to: navigation, search Name: Yichun Xinganling Wind Power Co Ltd Place: Suihua, Heilongjiang Province, China Zip: 152061 Sector: Wind...

  10. Changtu Liaoneng Xiexin Wind Power Co Ltd | Open Energy Information

    Open Energy Info (EERE)

    Changtu Liaoneng Xiexin Wind Power Co Ltd Jump to: navigation, search Name: Changtu Liaoneng Xiexin Wind Power Co Ltd Place: Liaoning Province, China Sector: Wind energy Product:...