WorldWideScience

Sample records for wind resource predictions

  1. Prediction of Wind Energy Resources (PoWER) Users Guide

    Science.gov (United States)

    2016-01-01

    ARL-TR-7573● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources ( PoWER ) User’s Guide by David P Sauter...not return it to the originator. ARL-TR-7573 ● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources ( PoWER ...2016 2. REPORT TYPE Final 3. DATES COVERED (From - To) 09/2015–11/2015 4. TITLE AND SUBTITLE Prediction of Wind Energy Resources ( PoWER ) User’s

  2. A methodology for the prediction of offshore wind energy resources

    Energy Technology Data Exchange (ETDEWEB)

    Watson, S.J.; Watson, G.M. [Rutherford Appleton Lab., Oxfordshire (United Kingdom); Holt, R.J. [Univ. of East Anglia, Climatic Research Unit, Norwich (United Kingdom)] Barthelmie, R.J. [Risoe National Lab., Dept. of Wind Energy and Atmospheric Physics, Roskilde (Denmark); Zuylen, E.J. van [Ecofys Energy and Environment, Utrecht (Netherlands)] Cleijne, J.W. [Kema Sustainable, Arnhem (Netherlands)

    1999-03-01

    There are increasing constraints on the development of wind power on land. Recently, there has been a move to develop wind power offshore, though the amount of measured wind speed data at potential offshore wind farm sites is sparse. We present a novel methodology for the prediction of offshore wind power resources which is being applied to European Union waters. The first stage is to calculate the geostrophic wind from long-term pressure fields over the sea area of interest. Secondly, the geostrophic wind is transformed to the sea level using WA{sup s}P, taking account of near shore topography. Finally, these values are corrected for land/sea climatology (stability) effects using an analytical Coastal discontinuity Model (CDM). These values are further refined using high resolution offshore data at selected sites. The final values are validated against existing offshore datasets. Preliminary results are presented of the geostrophic wind speed validation in European Union waters. (au)

  3. Stochastic Prediction of Wind Generating Resources Using the Enhanced Ensemble Model for Jeju Island’s Wind Farms in South Korea

    OpenAIRE

    Deockho Kim; Jin Hur

    2017-01-01

    Due to the intermittency of wind power generation, it is very hard to manage its system operation and planning. In order to incorporate higher wind power penetrations into power systems that maintain secure and economic power system operation, an accurate and efficient estimation of wind power outputs is needed. In this paper, we propose the stochastic prediction of wind generating resources using an enhanced ensemble model for Jeju Island’s wind farms in South Korea. When selecting the poten...

  4. Climate Wind Power Resources

    Directory of Open Access Journals (Sweden)

    Nana M. Berdzenishvili

    2013-01-01

    Full Text Available Georgia as a whole is characterized by rather rich solar energy resources, which allows to construct alternative power stations in the close proximity to traditional power plants. In this case the use of solar energy is meant. Georgia is divided into 5 zones based on the assessment of wind power resources. The selection of these zones is based on the index of average annual wind speed in the examined area, V> 3 m / s and V> 5 m / s wind speed by the summing duration in the course of the year and V = 0. . . 2 m / s of passive wind by total and continuous duration of these indices per hour.

  5. Wind resource estimation and siting of wind turbines

    DEFF Research Database (Denmark)

    Lundtang Petersen, Erik; Mortensen, N.G.; Landberg, L.

    1994-01-01

    Detailed knowledge of the characteristics of the natural wind is necessary for the design, planning and operational aspect of wind energy systems. Here, we shall only be concerned with those meteorological aspects of wind energy planning that are termed wind resource estimation. The estimation...... of the wind resource ranges from the overall estimation of the mean energy content of the wind over a large area - called regional assessment - to the prediction of the average yearly energy production of a specific wind turbine at a specific location - called siting. A regional assessment will most often...

  6. Mongolia wind resource assessment project

    International Nuclear Information System (INIS)

    Elliott, D.; Chadraa, B.; Natsagdorj, L.

    1998-01-01

    The development of detailed, regional wind-resource distributions and other pertinent wind resource characteristics (e.g., assessment maps and reliable estimates of seasonal, diurnal, and directional) is an important step in planning and accelerating the deployment of wind energy systems. This paper summarizes the approach and methods being used to conduct a wind energy resource assessment of Mongolia. The primary goals of this project are to develop a comprehensive wind energy resource atlas of Mongolia and to establish a wind measurement program in specific regions of Mongolia to identify prospective sites for wind energy projects and to help validate some of the wind resource estimates. The Mongolian wind resource atlas will include detailed, computerized wind power maps and other valuable wind resource characteristic information for the different regions of Mongolia

  7. Fort Carson Wind Resource Assessment

    Energy Technology Data Exchange (ETDEWEB)

    Robichaud, R.

    2012-10-01

    This report focuses on the wind resource assessment, the estimated energy production of wind turbines, and economic potential of a wind turbine project on a ridge in the southeastern portion of the Fort Carson Army base.

  8. Wind power prediction models

    Science.gov (United States)

    Levy, R.; Mcginness, H.

    1976-01-01

    Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.

  9. Offshore wind resource estimation for wind energy

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Badger, Merete; Mouche, A.

    2010-01-01

    Satellite remote sensing from active and passive microwave instruments is used to estimate the offshore wind resource in the Northern European Seas in the EU-Norsewind project. The satellite data include 8 years of Envisat ASAR, 10 years of QuikSCAT, and 23 years of SSM/I. The satellite observati......Satellite remote sensing from active and passive microwave instruments is used to estimate the offshore wind resource in the Northern European Seas in the EU-Norsewind project. The satellite data include 8 years of Envisat ASAR, 10 years of QuikSCAT, and 23 years of SSM/I. The satellite...... observations are compared to selected offshore meteorological masts in the Baltic Sea and North Sea. The overall aim of the Norsewind project is a state-of-the-art wind atlas at 100 m height. The satellite winds are all valid at 10 m above sea level. Extrapolation to higher heights is a challenge. Mesoscale...... modeling of the winds at hub height will be compared to data from wind lidars observing at 100 m above sea level. Plans are also to compare mesoscale model results and satellite-based estimates of the offshore wind resource....

  10. Wind conditions and resource assessment

    DEFF Research Database (Denmark)

    Lundtang Petersen, Erik; Troen, Ib

    2012-01-01

    The development of wind power as a competitive energy source requires resource assessment of increasing accuracy and detail (including not only the long-term ‘raw’ wind resource, but also turbulence, shear, and extremes), and in areas of increasing complexity. This in turn requires the use...

  11. Wind Energy Resource Atlas of the Philippines

    Energy Technology Data Exchange (ETDEWEB)

    Elliott, D.; Schwartz, M.; George, R.; Haymes, S.; Heimiller, D.; Scott, G.; McCarthy, E.

    2001-03-06

    This report contains the results of a wind resource analysis and mapping study for the Philippine archipelago. The study's objective was to identify potential wind resource areas and quantify the value of those resources within those areas. The wind resource maps and other wind resource characteristic information will be used to identify prospective areas for wind-energy applications.

  12. Wind resource analysis. Annual report

    Energy Technology Data Exchange (ETDEWEB)

    Hardy, D. M.

    1978-12-01

    FY78 results of the Wind Resource Analyses task of the ERAB are described. Initial steps were taken to acquire modern atmosphere models of near-surface wind flow and primary data sets used in previous studies of national and regional wind resources. Because numerous assumptions are necessary to interpret available data in terms of wind energy potential, conclusions of previous studies differ considerably. These data analyses may be improved by future SERI research. State-of-the-art atmosphere models are a necessary component of the SERI wind resource analyses capacity. However, these methods also need to be tested and verified in diverse applications. The primary data sets and principal features of the models are discussed.

  13. Are local wind power resources well estimated?

    Science.gov (United States)

    Lundtang Petersen, Erik; Troen, Ib; Jørgensen, Hans E.; Mann, Jakob

    2013-03-01

    project is structured around three areas of work, to be implemented in parallel. Creation and publication of a European wind atlas in electronic form [2], which will include the underlying data and a new EU wind climate database which will as a minimum include: wind resources and their associated uncertainty; extreme wind and uncertainty; turbulence characteristics; adverse weather conditions such as heavy icing, electrical storms and so on together with the probability of occurrence; the level of predictability for short-term forecasting and assessment of uncertainties; guidelines and best practices for the use of data especially for micro-siting. Development of dynamical downscaling methodologies and open-source models validated through measurement campaigns, to enable the provision of accurate wind resource and external wind load climatology and short-term prediction at high spatial resolution and covering Europe. The developed downscaling methodologies and models will be fully documented and made publicly available and will be used to produce overview maps of wind resources and other relevant data at several heights and at high horizontal resolution. Measurement campaigns to validate the model chain used in the wind atlas. At least five coordinated measurement campaigns will be undertaken and will cover complex terrains (mountains and forests), offshore, large changes in surface characteristics (roughness change) and cold climates. One of the great challenges to the project is the application of mesoscale models for wind resource calculation, which is by no means a simple matter [3]. The project will use global reanalysis data as boundary conditions. These datasets, which are time series of the large-scale meteorological situation covering decades, have been created by assimilation of measurement data from around the globe in a dynamical consistent fashion using large-scale numerical models. For wind energy, the application of the reanalysis datasets is as a long

  14. Connecting Communities to Wind Resources

    Energy Technology Data Exchange (ETDEWEB)

    Baring-Gould, Edward I [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2017-08-18

    WINDExchange is the platform for the U.S. Department of Energy's (DOE's) Wind Energy Technologies Office to disseminate credible wind energy information on a national level. Stakeholder engagement and outreach activities are designed to enable well-informed decisions about appropriate wind energy deployment. WINDExchange focuses on wind energy outreach at the national level while managing and supporting similar regional efforts through the implementation of DOE Regional Resource Centers (RRCs). This fact sheet provides an overview of DOE's WINDExchange initiative and the RRCs. Examples of RRC activities are provided.

  15. Wind Energy Resource Atlas of Armenia

    Energy Technology Data Exchange (ETDEWEB)

    Elliott, D.; Schwartz, M.; Scott, G.; Haymes, S.; Heimiller, D.; George, R.

    2003-07-01

    This wind energy resource atlas identifies the wind characteristics and distribution of the wind resource in the country of Armenia. The detailed wind resource maps and other information contained in the atlas facilitate the identification of prospective areas for use of wind energy technologies for utility-scale power generation and off-grid wind energy applications. The maps portray the wind resource with high-resolution (1-km2) grids of wind power density at 50-m above ground. The wind maps were created at the National Renewable Energy Laboratory (NREL) using a computerized wind mapping system that uses Geographic Information System (GIS) software.

  16. Research Needs for Wind Resource Characterization

    Science.gov (United States)

    Schreck, S. J.; Lundquist, J. K.; Shaw, W. J.

    2008-12-01

    Currently, wind energy provides about 1 percent of U.S. electricity generation. A recent analysis by DOE, NREL, and AWEA showed the feasibility of expanding U.S. wind energy capacity to 20 percent, comprising approximately 300 gigawatts. Though not a prediction of the future, this represents a plausible scenario for U.S. wind energy. To exploit these opportunities, a workshop on Research Needs for Wind Resource Characterization was held during January 2008. This event was organized on behalf of two DOE organizations; the Office of Biological and Environmental Research and the Office of Energy Efficiency and Renewable Energy. Over 120 atmospheric science and wind energy researchers attended the workshop from industry, academia, and federal laboratories in North America and Europe. Attendees identified problems that could impede achieving the 20 percent wind scenario and formulated research recommendations to attack these problems. Findings were structured into four focus areas: 1) Turbine Dynamics, 2) Micrositing and Array Effects, 3) Mesoscale Processes, and 4) Climate Effects. In the Turbine Dynamics area, detailed characterizations of inflows and turbine flow fields were deemed crucial to attaining accuracy levels in aerodynamics loads required for future designs. To address the complexities inherent in this area, an incremental approach involving hierarchical computational modeling and detailed measurements was recommended. Also recommended was work to model extreme and anomalous atmospheric inflow events and aerostructural responses of turbines to these events. The Micrositing and Array Effects area considered improved wake models important for large, multiple row wind plants. Planetary boundary layer research was deemed necessary to accurately determine inflow characteristics in the presence of atmospheric stability effects and complex surface characteristics. Finally, a need was identified to acquire and exploit large wind inflow data sets, covering heights

  17. Wind Resource Assessment of Gujarat (India)

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-07-01

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

  18. Wind Energy Resource Atlas of Oaxaca

    Energy Technology Data Exchange (ETDEWEB)

    Elliott, D.; Schwartz, M.; Scott, G.; Haymes, S.; Heimiller, D.; George, R.

    2003-08-01

    The Oaxaca Wind Resource Atlas, produced by the National Renewable Energy Laboratory's (NREL's) wind resource group, is the result of an extensive mapping study for the Mexican State of Oaxaca. This atlas identifies the wind characteristics and distribution of the wind resource in Oaxaca. The detailed wind resource maps and other information contained in the atlas facilitate the identification of prospective areas for use of wind energy technologies, both for utility-scale power generation and off-grid wind energy applications.

  19. European Wind Atlas and Wind Resource Research in Denmark

    DEFF Research Database (Denmark)

    Mortensen, Niels Gylling

    to estimate the actual wind climate at any specific site and height within this region. The Danish and European Wind Atlases are examples of how the wind atlas methodology can be employed to estimate the wind resource potential for a country or a sub-continent. Recently, the methodology has also been used...... - from wind measurements at prospective sites to wind tunnel simulations and advanced flow modelling. Among these approaches, the wind atlas methodology - developed at Ris0 National Laboratory over the last 25 years - has gained widespread recognition and is presently considered by many as the industry......-standard tool for wind resource assessment and siting of wind turbines. The PC-implementation of the methodology, the Wind Atlas Analysis and Application Program (WAsP), has been applied in more than 70 countries and territories world-wide. The wind atlas methodology is based on physical descriptions and models...

  20. Wind energy prediction; Prediccion eolica

    Energy Technology Data Exchange (ETDEWEB)

    Xiberta, B. J.; Florez, M. V. E.

    2004-07-01

    On March 12th, 2004 the Spanish Government modified the legal situation of the renewable energies following the approval of RD 436/2004. This makes necessary the development of wind energy prediction models for its entrance to the daily electricity market like the conventional energies. The improvement of physical models, meteorological models, or a combination of both, is necessary for the prediction of the wind generation. This will guarantee the wind energy full utilization and the participation in the electrical market, as well as the remuneration of the complementary services and the regulation of reactive electricity. In this way wind energy turns into a perfectly manageable one. (Author)

  1. The potential wind power resource in Australia: a new perspective.

    Science.gov (United States)

    Hallgren, Willow; Gunturu, Udaya Bhaskar; Schlosser, Adam

    2014-01-01

    Australia's wind resource is considered to be very good, and the utilization of this renewable energy resource is increasing rapidly: wind power installed capacity increased by 35% from 2006 to 2011 and is predicted to account for over 12% of Australia's electricity generation in 2030. Due to this growth in the utilization of the wind resource and the increasing importance of wind power in Australia's energy mix, this study sets out to analyze and interpret the nature of Australia's wind resources using robust metrics of the abundance, variability and intermittency of wind power density, and analyzes the variation of these characteristics with current and potential wind turbine hub heights. We also assess the extent to which wind intermittency, on hourly or greater timescales, can potentially be mitigated by the aggregation of geographically dispersed wind farms, and in so doing, lessen the severe impact on wind power economic viability of long lulls in wind and power generated. Our results suggest that over much of Australia, areas that have high wind intermittency coincide with large expanses in which the aggregation of turbine output does not mitigate variability. These areas are also geographically remote, some are disconnected from the east coast's electricity grid and large population centers, which are factors that could decrease the potential economic viability of wind farms in these locations. However, on the eastern seaboard, even though the wind resource is weaker, it is less variable, much closer to large population centers, and there exists more potential to mitigate it's intermittency through aggregation. This study forms a necessary precursor to the analysis of the impact of large-scale circulations and oscillations on the wind resource at the mesoscale.

  2. The potential wind power resource in Australia: a new perspective.

    Directory of Open Access Journals (Sweden)

    Willow Hallgren

    Full Text Available Australia's wind resource is considered to be very good, and the utilization of this renewable energy resource is increasing rapidly: wind power installed capacity increased by 35% from 2006 to 2011 and is predicted to account for over 12% of Australia's electricity generation in 2030. Due to this growth in the utilization of the wind resource and the increasing importance of wind power in Australia's energy mix, this study sets out to analyze and interpret the nature of Australia's wind resources using robust metrics of the abundance, variability and intermittency of wind power density, and analyzes the variation of these characteristics with current and potential wind turbine hub heights. We also assess the extent to which wind intermittency, on hourly or greater timescales, can potentially be mitigated by the aggregation of geographically dispersed wind farms, and in so doing, lessen the severe impact on wind power economic viability of long lulls in wind and power generated. Our results suggest that over much of Australia, areas that have high wind intermittency coincide with large expanses in which the aggregation of turbine output does not mitigate variability. These areas are also geographically remote, some are disconnected from the east coast's electricity grid and large population centers, which are factors that could decrease the potential economic viability of wind farms in these locations. However, on the eastern seaboard, even though the wind resource is weaker, it is less variable, much closer to large population centers, and there exists more potential to mitigate it's intermittency through aggregation. This study forms a necessary precursor to the analysis of the impact of large-scale circulations and oscillations on the wind resource at the mesoscale.

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

    Science.gov (United States)

    Hallgren, Willow; Gunturu, Udaya Bhaskar; Schlosser, Adam

    2014-01-01

    Australia’s wind resource is considered to be very good, and the utilization of this renewable energy resource is increasing rapidly: wind power installed capacity increased by 35% from 2006 to 2011 and is predicted to account for over 12% of Australia’s electricity generation in 2030. Due to this growth in the utilization of the wind resource and the increasing importance of wind power in Australia’s energy mix, this study sets out to analyze and interpret the nature of Australia’s wind resources using robust metrics of the abundance, variability and intermittency of wind power density, and analyzes the variation of these characteristics with current and potential wind turbine hub heights. We also assess the extent to which wind intermittency, on hourly or greater timescales, can potentially be mitigated by the aggregation of geographically dispersed wind farms, and in so doing, lessen the severe impact on wind power economic viability of long lulls in wind and power generated. Our results suggest that over much of Australia, areas that have high wind intermittency coincide with large expanses in which the aggregation of turbine output does not mitigate variability. These areas are also geographically remote, some are disconnected from the east coast’s electricity grid and large population centers, which are factors that could decrease the potential economic viability of wind farms in these locations. However, on the eastern seaboard, even though the wind resource is weaker, it is less variable, much closer to large population centers, and there exists more potential to mitigate it’s intermittency through aggregation. This study forms a necessary precursor to the analysis of the impact of large-scale circulations and oscillations on the wind resource at the mesoscale. PMID:24988222

  4. Wind Energy Resource Atlas of Southeast China

    Energy Technology Data Exchange (ETDEWEB)

    Elliott, D.; Schwartz, M.; Scott, G.; Haymes, S.; Heimiller, D.; George, R.

    2002-11-01

    This wind energy resource atlas identifies the wind characteristics and distribution of the wind resource in two regions of southeast China. The first region is the coastal area stretching from northern Fujian south to eastern Guangdong and extending approximately 100 km inland. The second region is centered on the Poyang Lake area in northern Jiangxi. This region also includes parts of two other provinces-Anhui and Hubei-and extends from near Anqing in Anhui south to near Nanchang in Jiangxi. The detailed wind resource maps and other information contained in the atlas facilitate the identification of prospective areas for use of wind energy technologies, both for utility-scale power generation and off-grid wind energy applications. We created the high-resolution (1-km2) maps in 1998 using a computerized wind resource mapping system developed at the National Renewable Energy Laboratory (NREL). The mapping system uses software known as a Geographical Information System (GIS).

  5. Offshore Wind Energy Resource Assessment for Alaska

    Energy Technology Data Exchange (ETDEWEB)

    Doubrawa Moreira, Paula [National Renewable Energy Lab. (NREL), Golden, CO (United States); Scott, George N. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Musial, Walter D. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Kilcher, Levi F. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Draxl, Caroline [National Renewable Energy Lab. (NREL), Golden, CO (United States); Lantz, Eric J. [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2018-01-02

    This report quantifies Alaska's offshore wind resource capacity while focusing on its unique nature. It is a supplement to the existing U.S. Offshore Wind Resource Assessment, which evaluated the offshore wind resource for all other U.S. states. Together, these reports provide the foundation for the nation's offshore wind value proposition. Both studies were developed by the National Renewable Energy Laboratory. The analysis presented herein represents the first quantitative evidence of the offshore wind energy potential of Alaska. The technical offshore wind resource area in Alaska is larger than the technical offshore resource area of all other coastal U.S. states combined. Despite the abundant wind resource available, significant challenges inhibit large-scale offshore wind deployment in Alaska, such as the remoteness of the resource, its distance from load centers, and the wealth of land available for onshore wind development. Throughout this report, the energy landscape of Alaska is reviewed and a resource assessment analysis is performed in terms of gross and technical offshore capacity and energy potential.

  6. Wind resource characterization in the Arabian Peninsula

    KAUST Repository

    Yip, Chak Man Andrew

    2015-12-28

    Wind energy is expected to contribute to alleviating the rise in energy demand in the Middle East that is driven by population growth and industrial development. However, variability and intermittency in the wind resource present significant challenges to grid integration of wind energy systems. These issues are rarely addressed in the literature of wind resource assessment in the Middle East due to sparse meteorological observations with varying record lengths. In this study, the wind field with consistent space–time resolution for over three decades at three hub heights (50m, 80m, 140m) over the whole Arabian Peninsula is constructed using the Modern Era Retrospective-Analysis for Research and Applications (MERRA) dataset. The wind resource is assessed at a higher spatial resolution with metrics of temporal variations in the wind than in prior studies. Previously unrecognized locations of interest with high wind abundance and low variability and intermittency have been identified in this study and confirmed by recent on-site observations. In particular, the western mountains of Saudi Arabia experience more abundant wind resource than most Red Sea coastal areas. The wind resource is more variable in coastal areas along the Arabian Gulf than their Red Sea counterparts at a similar latitude. Persistent wind is found along the coast of the Arabian Gulf.

  7. Wind resource in the urban environment

    Directory of Open Access Journals (Sweden)

    Derek Joseph Kearney

    2013-10-01

    Full Text Available Renewable energy technologies, such as wind turbines, have to be considered for new building over 1000m2 under the Energy Performance of Buildings Directive (2002. Accurate assessment of the wind resource is a key component in the success of a wind installation. Designers, planners and architects also need wind data from urban areas to support low-energy building design, natural ventilation, air quality, pollution control, insurance and wind engineering. Over the last six years instrumentation has been installed at the Dublin Institute of Technology (DIT in two separate locations to monitor the wind. The data has shown that the wind resource will vary quite considerably on a given site and this is due to local variations in topography, and other factors associated with wind and turbulence in the built environment. Difficulties were encountered in measuring the wind and turbulence on site. IEC 61400-12-1: 2005 states that “... analytical tools (anemometers presently available offer little help in identifying the impact of these variables, and experimental methods encounter equally-serious difficulties.” The practical experience of measuring wind in the urban environment informed the development of a prototype anemometer that may be capable of digitally mapping accurate real-time three-dimensional data on wind speed, wind direction and, uniquely in the field of wind instrumentation, wind turbulence.

  8. Satellite winds as a tool for offshore wind resource assessment: The Great Lakes Wind Atlas

    DEFF Research Database (Denmark)

    Doubrawa, Paula; Barthelmie, Rebecca Jane; Pryor, Sara C.

    2015-01-01

    This work presents a new observational wind atlas for the Great Lakes, and proposes a methodology to combine in situ and satellite wind observations for offshore wind resource assessment. Efficient wind energy projects rely on accurate wind resource estimates, which are complex to obtain offshore...... the North American Regional Reanalysis. Generalized wind climates are obtained for each buoy and coastal site with the wind model WAsP, and combined into a single wind speed estimate for the Great Lakes region. The method of classes is used to account for the temporal sparseness in the SAR data set...

  9. Wind Resource Estimation using QuikSCAT Ocean Surface Winds

    DEFF Research Database (Denmark)

    Xu, Qing; Zhang, Guosheng; Cheng, Yongcun

    2011-01-01

    In this study, the offshore wind resources in the East China Sea and South China Sea were estimated from over ten years of QuikSCAT scatterometer wind products. Since the errors of these products are larger close to the coast due to the land contamination of radar backscatter signal and the compl...

  10. Wind Resource Estimation using QuikSCAT Ocean Surface Winds

    DEFF Research Database (Denmark)

    Xu, Qing; Zhang, Guosheng; Cheng, Yongcun

    2011-01-01

    In this study, the offshore wind resources in the East China Sea and South China Sea were estimated from over ten years of QuikSCAT scatterometer wind products. Since the errors of these products are larger close to the coast due to the land contamination of radar backscatter signal...

  11. Cultural Resource Predictive Modeling

    Science.gov (United States)

    2017-10-01

    refining formal, inductive predictive models is the quality of the archaeological and environmental data. To build models efficiently, relevant...geomorphology, and historic information . Lessons Learned: The original model was focused on the identification of prehistoric resources. This...system but uses predictive modeling informally . For example, there is no probability for buried archaeological deposits on the Burton Mesa, but there is

  12. A detailed and verified wind resource atlas for Denmark

    Energy Technology Data Exchange (ETDEWEB)

    Mortensen, N.G.; Landberg, L.; Rathmann, O.; Nielsen, M.N. [Risoe National Lab., Roskilde (Denmark); Nielsen, P. [Energy and Environmental Data, Aalberg (Denmark)

    1999-03-01

    A detailed and reliable wind resource atlas covering the entire land area of Denmark has been established. Key words of the methodology are wind atlas analysis, interpolation of wind atlas data sets, automated generation of digital terrain descriptions and modelling of local wind climates. The atlas contains wind speed and direction distributions, as well as mean energy densities of the wind, for 12 sectors and four heights above ground level: 25, 45, 70 and 100 m. The spatial resolution is 200 meters in the horizontal. The atlas has been verified by comparison with actual wind turbine power productions from over 1200 turbines. More than 80% of these turbines were predicted to within 10%. The atlas will become available on CD-ROM and on the Internet. (au)

  13. Calculation of depleted wind resources near wind farms

    DEFF Research Database (Denmark)

    Nielsen, Morten

    2015-01-01

    Traditional wind resource maps include wind distribution, energy density and potential power production without wake effects. Adding wake effect to such maps is feasible by means of a new method based on Fourier transformation,and the extra computational work is comparable to that of the basic wind...... resource map. The method is mainly intended for mapping inter-farm wake effects. It will work for all linear wake models and may even be extended to complex terrain by certain simplifying assumptions. The method is implemented for the Park model and Fuga models. A test example shows that these models...

  14. Wind resource modelling for micro-siting - Validation at a 60-MW wind farm site

    Energy Technology Data Exchange (ETDEWEB)

    Hansen, J.C.; Gylling Mortensen, N. [Risoe National Lab., Wind Energy and Atmospheric Physics Dept., Roskilde (Denmark); Said, U.S. [New and Renewable Energy Authority, Cairo (Egypt)

    1999-03-01

    This paper investigates and validates the applicability of the WAsP-model for layout optimization and micro-siting of wind turbines at a given site for a 60-MW wind farm at Zafarana at the Gulf of Suez in Egypt. Previous investigations show large gradients in the wind climate within the area. For the design and optimization of the wind farm it was found necessary to verify the WAsP extrapolation of wind atlas results from 2 existing meteorological masts located 5 and 10 km, respectively, from the wind farm site. On-site measurements at the 3.5 x 3.5 km{sup 2} wind farm site in combination with 7 years of near-site wind atlas measurements offer significant amounts of data for verification of wind conditions for micro-siting. Wind speeds, wind directions, turbulence intensities and guests in 47.5 m a.g.l. have been measured at 9 locations across the site. Additionally, one of the site masts is equipped as a reference mast, measuring both vertical profiles of wind speed and temperature as well as air pressure and temperature. The exercise is further facilitated by the fact that winds are highly uni-directional; the north direction accounting for 80-90% of the wind resource. The paper presents comparisons of 5 months of on-site measurements and modeled predictions from 2 existing meteorological masts located at distances of 5 and 10 km, respectively, from the wind farm site. Predictions based on terrain descriptions of the Wind Atlas for the Gulf of Suez 1991-95 showed over-predictions of wind speeds of 4-10%. With calibrated terrain descriptions, made based on measured data and a re-visit to critical parts of the terrain, the average prediction error of wind speeds was reduced to about 1%. These deviations are smaller than generally expected for such wind resource modeling, clearly documenting the validity of using WAsP modeling for micro-siting and layout optimization of the wind farm. (au)

  15. Wind and solar resource data sets

    DEFF Research Database (Denmark)

    Clifton, Andrew; Hodge, Bri-Mathias; Draxl, Caroline

    2017-01-01

    The range of resource data sets spans from static cartography showing the mean annual wind speed or solar irradiance across a region to high temporal and high spatial resolution products that provide detailed information at a potential wind or solar energy facility. These data sets are used...... to support continental-scale, national, or regional renewable energy development; facilitate prospecting by developers; and enable grid integration studies. This review first provides an introduction to the wind and solar resource data sets, then provides an overview of the common methods used...... for their creation and validation. A brief history of wind and solar resource data sets is then presented, followed by areas for future research. For further resources related to this article, please visit the WIREs website....

  16. Wind Energy Resource Atlas of Sri Lanka and the Maldives

    Energy Technology Data Exchange (ETDEWEB)

    Elliott, D.; Schwartz, M.; Scott, G.; Haymes, S.; Heimiller, D.; George, R.

    2003-08-01

    The Wind Energy Resource Atlas of Sri Lanka and the Maldives, produced by the National Renewable Energy Laboratory's (NREL's) wind resource group identifies the wind characteristics and distribution of the wind resource in Sri Lanka and the Maldives. The detailed wind resource maps and other information contained in the atlas facilitate the identification of prospective areas for use of wind energy technologies, both for utility-scale power generation and off-grid wind energy applications.

  17. Cost of wind energy: comparing distant wind resources to local resources in the midwestern United States.

    Science.gov (United States)

    Hoppock, David C; Patiño-Echeverri, Dalia

    2010-11-15

    The best wind sites in the United States are often located far from electricity demand centers and lack transmission access. Local sites that have lower quality wind resources but do not require as much power transmission capacity are an alternative to distant wind resources. In this paper, we explore the trade-offs between developing new wind generation at local sites and installing wind farms at remote sites. We first examine the general relationship between the high capital costs required for local wind development and the relatively lower capital costs required to install a wind farm capable of generating the same electrical output at a remote site,with the results representing the maximum amount an investor should be willing to pay for transmission access. We suggest that this analysis can be used as a first step in comparing potential wind resources to meet a state renewable portfolio standard (RPS). To illustrate, we compare the cost of local wind (∼50 km from the load) to the cost of distant wind requiring new transmission (∼550-750 km from the load) to meet the Illinois RPS. We find that local, lower capacity factor wind sites are the lowest cost option for meeting the Illinois RPS if new long distance transmission is required to access distant, higher capacity factor wind resources. If higher capacity wind sites can be connected to the existing grid at minimal cost, in many cases they will have lower costs.

  18. Wind Power Prediction Considering Nonlinear Atmospheric Disturbances

    Directory of Open Access Journals (Sweden)

    Yagang Zhang

    2015-01-01

    Full Text Available This paper considers the effect of nonlinear atmospheric disturbances on wind power prediction. A Lorenz system is introduced as an atmospheric disturbance model. Three new improved wind forecasting models combined with a Lorenz comprehensive disturbance are put forward in this study. Firstly, we define the form of the Lorenz disturbance variable and the wind speed perturbation formula. Then, different artificial neural network models are used to verify the new idea and obtain better wind speed predictions. Finally we separately use the original and improved wind speed series to predict the related wind power. This proves that the corrected wind speed provides higher precision wind power predictions. This research presents a totally new direction in the wind prediction field and has profound theoretical research value and practical guiding significance.

  19. Wind power error estimation in resource assessments.

    Science.gov (United States)

    Rodríguez, Osvaldo; Del Río, Jesús A; Jaramillo, Oscar A; Martínez, Manuel

    2015-01-01

    Estimating the power output is one of the elements that determine the techno-economic feasibility of a renewable project. At present, there is a need to develop reliable methods that achieve this goal, thereby contributing to wind power penetration. In this study, we propose a method for wind power error estimation based on the wind speed measurement error, probability density function, and wind turbine power curves. This method uses the actual wind speed data without prior statistical treatment based on 28 wind turbine power curves, which were fitted by Lagrange's method, to calculate the estimate wind power output and the corresponding error propagation. We found that wind speed percentage errors of 10% were propagated into the power output estimates, thereby yielding an error of 5%. The proposed error propagation complements the traditional power resource assessments. The wind power estimation error also allows us to estimate intervals for the power production leveled cost or the investment time return. The implementation of this method increases the reliability of techno-economic resource assessment studies.

  20. Wind power production: from the characterisation of the wind resource to wind turbine technologies

    International Nuclear Information System (INIS)

    Beslin, Guy; Multon, Bernard

    2016-01-01

    Illustrated by graphs and tables, this article first describes the various factors and means related to the assessment of wind resource in the World, in Europe, and the factors which characterize a local wind resource. In this last respect, the authors indicate how local topography is taken into account to calculate wind speed, how time variations are taken into account (at the yearly, seasonal or daily level), the different methods used to model a local wind resource, how to assess the power recoverable by a wind turbine with horizontal axis (notion of Betz limit). In the second part, the authors present the different wind turbines, their benefits and drawbacks: vertical axis, horizontal axis (examples of a Danish-type wind turbine, of wind turbines designed for extreme conditions). Then, they address the technology of big wind turbines: evolution of technology and of commercial offer, aerodynamic characteristics of wind turbine and benefit of a varying speed (technological solutions, importance of the electric generator). They describe how to choose a wind turbine, how product lines are organised, how the power curve and energy capacity are determined. The issue of integration of wind energy into the power system is then addressed. The next part addressed the economy of wind energy production (annualized production cost, order of magnitude of wind electric power production cost). Future trends are discussed and offshore wind energy production is briefly addressed

  1. NANA Wind Resource Assessment Program Final Report

    Energy Technology Data Exchange (ETDEWEB)

    Jay Hermanson

    2010-09-23

    NANA Regional Corporation (NRC) of northwest Alaska is located in an area with abundant wind energy resources. In 2007, NRC was awarded grant DE-FG36-07GO17076 by the US Department of Energy's Tribal Energy Program for funding a Wind Resource Assessment Project (WRAP) for the NANA region. The NANA region, including Kotzebue Electric Association (KEA) and Alaska Village Electric Cooperative (AVEC) have been national leaders at developing, designing, building, and operating wind-diesel hybrid systems in Kotzebue (starting in 1996) and Selawik (2002). Promising sites for the development of new wind energy projects in the region have been identified by the WRAP, including Buckland, Deering, and the Kivalina/Red Dog Mine Port Area. Ambler, Shungnak, Kobuk, Kiana, Noorvik & Noatak were determined to have poor wind resources at sites in or very near each community. However, all five of these communities may have better wind resources atop hills or at sites with slightly higher elevations several miles away.

  2. On the Predictability of Hub Height Winds

    DEFF Research Database (Denmark)

    Draxl, Caroline

    of power output at wind farms. Since the power available in the wind is proportional to the wind speed cubed, even small wind forecast errors result in large power prediction errors. Accurate wind forecasts are worth billions of dollars annually; forecast improvements will result in reduced costs....... This is particularly relevant with offshore facilities, which represent a significant portion of new wind farms being constructed. Furthermore, a novel aspect to this study is the presentation of a verification methodology that takes into account wind at different heights where turbines operate. The increasing number...... grids. These systems require forecasts with temporal scales of tens of minutes to a few days in advance at wind farm locations. Traditionally these forecasts predict the wind at turbine hub heights; this information is then converted by transmission system operators and energy companies into predictions...

  3. Deterministic prediction of surface wind speed variations

    Directory of Open Access Journals (Sweden)

    G. V. Drisya

    2014-11-01

    Full Text Available Accurate prediction of wind speed is an important aspect of various tasks related to wind energy management such as wind turbine predictive control and wind power scheduling. The most typical characteristic of wind speed data is its persistent temporal variations. Most of the techniques reported in the literature for prediction of wind speed and power are based on statistical methods or probabilistic distribution of wind speed data. In this paper we demonstrate that deterministic forecasting methods can make accurate short-term predictions of wind speed using past data, at locations where the wind dynamics exhibit chaotic behaviour. The predictions are remarkably accurate up to 1 h with a normalised RMSE (root mean square error of less than 0.02 and reasonably accurate up to 3 h with an error of less than 0.06. Repeated application of these methods at 234 different geographical locations for predicting wind speeds at 30-day intervals for 3 years reveals that the accuracy of prediction is more or less the same across all locations and time periods. Comparison of the results with f-ARIMA model predictions shows that the deterministic models with suitable parameters are capable of returning improved prediction accuracy and capturing the dynamical variations of the actual time series more faithfully. These methods are simple and computationally efficient and require only records of past data for making short-term wind speed forecasts within practically tolerable margin of errors.

  4. Wind energy resource atlas. Volume 4. The Northeast region

    Energy Technology Data Exchange (ETDEWEB)

    Pickering, K.E.; Vilardo, J.M.; Schakenbach, J.T.; Elliott, D.L.; Barchet, W.R.; George, R.L.

    1980-09-01

    This atlas of the wind energy resource is composed of introductory and background information, a regional summary of the wind resource, and assessments of the wind resource in each state of the region. Background is presented on how the wind resource is assessed and on how the results of the assessment should be interpreted. A description of the wind resource on a regional scale is then given. The results of the wind energy assessments for each state are assembled in this chapter into an overview and summary of the various features of the regional wind energy resource. An introduction and outline are provided for in the descriptions of the wind resource given for each state. Assessments for individual states are presented. The state wind energy resources are described in greater detail than is the regional wind energy resource, and features of selected stations are discussed. This preface outlines the use and interpretation of the information found in the state chapters.

  5. Wind energy resource atlas. Volume 9. The Southwest Region

    Energy Technology Data Exchange (ETDEWEB)

    Simon, R.L.; Norman, G.T.; Elliott, D.L.; Barchet, W.R.; George, R.L.

    1980-11-01

    This atlas of the wind energy resource is composed of introductory and background information, a regional summary of the wind resource, and assessments of the wind resource in Nevada and California. Background on how the wind resource is assessed and on how the results of the assessment should be interpreted is presented. A description of the wind resource on a regional scale is then given. The results of the wind energy assessments for each state are assembled into an overview and summary of the various features of the regional wind energy resource. An introduction and outline to the descriptions of the wind resource given for each state are given. Assessments for individual states are presented as separate chapters. The state wind energy resources are described in greater detail than is the regional wind energy resource, and features of selected stations are discussed.

  6. State of the Art and Trends in Wind Resource Assessment

    Directory of Open Access Journals (Sweden)

    Oliver Probst

    2010-06-01

    Full Text Available Given the significant rise of the utilization of wind energy the accurate assessment of the wind potential is becoming increasingly important. Direct applications of wind assessment techniques include the creation of wind maps on a local scale (typically 5 20 km and the micrositing of wind turbines, the estimation of vertical wind speed variations, prospecting on a regional scale (>100 km, estimation of the long-term wind resource at a given site, and forecasting. The measurement of wind speed and direction still widely relies on cup anemometers, though sonic anemometers are becoming increasingly popular. Moreover, remote sensing by Doppler techniques using the backscattering of either sonic beams (SODAR or light (LIDAR allowing for vertical profiling well beyond hub height are quickly moving into the mainstream. Local wind maps are based on the predicted modification of the regional wind flow pattern by the local atmospheric boundary layer which in turn depends on both topographic and roughness features and the measured wind rose obtained from one or several measurement towers within the boundaries of the planned development site. Initial models were based on linearized versions of the Navier-Stokes equations, whereas more recently full CFD models have been applied to wind farm micrositing. Linear models tend to perform well for terrain slopes lower than about 25% and have the advantage of short execution times. Long-term performance is frequently estimated from correlations with nearby reference stations with concurrent information and continuous time series over a period of at least 10 years. Simple methods consider only point-to-point linear correlations; more advanced methods like multiple regression techniques and methods based on the theory of distributions will be discussed. Both for early prospecting in regions where only scarce or unreliable reference information is available, wind flow modeling on a larger scale (mesoscale is becoming

  7. Wind energy resource assessment in Madrid region

    Energy Technology Data Exchange (ETDEWEB)

    Migoya, Emilio; Crespo, Antonio; Jimenez, Angel; Garcia, Javier; Manuel, Fernando [Laboratorio de Mecanica de Fluidos, Departamento de Ingenieria Energetica y Fluidomecanica, Escuela Tecnica Superior Ingenieros Industriales (ETSII), Universidad Politecnica de Madrid (UPM), C/Jose Gutierrez Abascal, 2-28006, Madrid (Spain)

    2007-07-15

    The Comunidad Autonoma de Madrid (Autonomous Community of Madrid, in the following Madrid Region), is a region located at the geographical centre of the Iberian Peninsula. Its area is 8.028 km{sup 2}, and its population about five million people. The Department of Economy and Technological Innovation of the Madrid Region, together with some organizations dealing on energy saving and other research institutions have elaborated an Energy Plan for the 2004-12 period. As a part of this work, the Fluid Mechanics Laboratory of the Superior Technical School of Industrial Engineers of the Polytechnic University of Madrid has carried out the assessment of the wind energy resources [Crespo A, Migoya E, Gomez Elvira R. La energia eolica en Madrid. Potencialidad y prospectiva. Plan energetico de la Comunidad de Madrid, 2004-2012. Madrid: Comunidad Autonoma de Madrid; 2004]; using for this task the WAsP program (Wind Atlas Analysis and Application Program), and the own codes, UPMORO (code to study orography effects) and UPMPARK (code to study wake effects in wind parks). Different kinds of data have been collected about climate, topography, roughness of the land, environmentally protected areas, town and village distribution, population density, main facilities and electric power supply. The Spanish National Meteorological Institute has nine wind measurement stations in the region, but only four of them have good and reliable temporary wind data, with time measurement periods that are long enough to provide representative correlations among stations. The Observed Wind Climates of the valid meteorological stations have been made. The Wind Atlas and the resource grid have been calculated, especially in the high wind resource areas, selecting appropriate measurements stations and using criteria based on proximity, similarity and ruggedness index. Some areas cannot be used as a wind energy resource mainly because they have environmental regulation or, in some cases, are very close

  8. Wind Resource Assessment – Østerild National Test Centre for Large Wind Turbines

    DEFF Research Database (Denmark)

    Hansen, Brian Ohrbeck; Courtney, Michael; Mortensen, Niels Gylling

    This report presents a wind resource assessment for the seven test stands at the Østerild National Test Centre for Large Wind Turbines in Denmark. Calculations have been carried out mainly using wind data from three on-site wind lidars. The generalized wind climates applied in the wind resource...... calculations for the seven test stands are based on correlations between a short period of on-site wind data from the wind lidars with a long-term reference. The wind resource assessment for the seven test stands has been made applying the WAsP 11.1 and WindPRO 2.9 software packages....

  9. Wind Energy Resource Atlas of the Dominican Republic

    Energy Technology Data Exchange (ETDEWEB)

    Elliott, D.; Schwartz, M.; George, R.; Haymes, S.; Heimiller, D.; Scott, G.; Kline, J.

    2001-10-01

    The Wind Energy Resource Atlas of the Dominican Republic identifies the wind characteristics and the distribution of the wind resource in this country. This major project is the first of its kind undertaken for the Dominican Republic. The information contained in the atlas is necessary to facilitate the use of wind energy technologies, both for utility-scale power generation and off-grid wind energy applications. A computerized wind mapping system developed by NREL generated detailed wind resource maps for the entire country. This technique uses Geographic Information Systems (GIS) to produce high-resolution (1-square kilometer) annual average wind resource maps.

  10. Nebraska wind resource assessment first year results

    Energy Technology Data Exchange (ETDEWEB)

    Hurley, P.J.F.; Vilhauer, R. [RLA Consulting, Inc., Bothell, WA (United States); Stooksbury, D. [Univ. of Nebraska, Lincoln, NE (United States)

    1996-12-31

    This paper presents the preliminary results from a wind resource assessment program in Nebraska sponsored by the Nebraska Power Association. During the first year the measured annual wind speed at 40 meters ranged from 6.5 - 7.5 m/s (14.6 - 16.8 mph) at eight stations across the state. The site selection process is discussed as well as an overview of the site characteristics at the monitoring locations. Results from the first year monitoring period including data recovery rate, directionality, average wind speeds, wind shear, and turbulence intensity are presented. Results from the eight sites are qualitatively compared with other midwest and west coast locations. 5 figs., 2 tabs.

  11. Distributed Wind Resource Assessment: State of the Industry

    Energy Technology Data Exchange (ETDEWEB)

    Fields, Jason [National Renewable Energy Lab. (NREL), Golden, CO (United States); Tinnesand, Heidi [National Renewable Energy Lab. (NREL), Golden, CO (United States); Baring-Gould, Ian [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2016-06-01

    In support of the U.S. Department of Energy (DOE) Wind and Water Power Technologies Office (WWPTO) goals, researchers from DOE's National Renewable Energy Laboratory (NREL), National Wind Technology Center (NWTC) are investigating the Distributed Wind Resource Assessment (DWRA) process, which includes pre-construction energy estimation as well as turbine site suitability assessment. DWRA can have a direct impact on the Wind Program goals of maximizing stakeholder confidence in turbine performance and safety as well as reducing the levelized cost of energy (LCOE). One of the major components of the LCOE equation is annual energy production. DWRA improvements can maximize the annual energy production, thereby lowering the overall LCOE and improving stakeholder confidence in the distributed wind technology sector by providing more accurate predictions of power production. Over the long term, one of the most significant benefits of a more defined DWRA process could be new turbine designs, tuned to site-specific characteristics that will help the distributed wind industry follow a similar trajectory to the low-wind-speed designs in the utility-scale industry sector. By understanding the wind resource better, the industry could install larger rotors, capture more energy, and as a result, increase deployment while lowering the LCOE. a direct impact on the Wind Program goals of maximizing stakeholder confidence in turbine performance and safety as well as reducing the levelized cost of energy (LCOE). One of the major components of the LCOE equation is annual energy production. DWRA improvements can maximize the annual energy production, thereby lowering the overall LCOE and improving stakeholder confidence in the distributed wind technology sector by providing more accurate predictions of power production. Over the long term, one of the most significant benefits of a more defined DWRA process could be new turbine designs, tuned to site-specific characteristics that

  12. Bayesian Predictive Models for Rayleigh Wind Speed

    DEFF Research Database (Denmark)

    Shahirinia, Amir; Hajizadeh, Amin; Yu, David C

    2017-01-01

    predictive model of the wind speed aggregates the non-homogeneous distributions into a single continuous distribution. Therefore, the result is able to capture the variation among the probability distributions of the wind speeds at the turbines’ locations in a wind farm. More specifically, instead of using...... a wind speed distribution whose parameters are known or estimated, the parameters are considered as random whose variations are according to probability distributions. The Bayesian predictive model for a Rayleigh which only has a single model scale parameter has been proposed. Also closed-form posterior......One of the major challenges with the increase in wind power generation is the uncertain nature of wind speed. So far the uncertainty about wind speed has been presented through probability distributions. Also the existing models that consider the uncertainty of the wind speed primarily view...

  13. Wind resource in metropolitan France: assessment methods, variability and trends

    International Nuclear Information System (INIS)

    Jourdier, Benedicte

    2015-01-01

    France has one of the largest wind potentials in Europe, yet far from being fully exploited. The wind resource and energy yield assessment is a key step before building a wind farm, aiming at predicting the future electricity production. Any over-estimation in the assessment process puts in jeopardy the project's profitability. This has been the case in the recent years, when wind farm managers have noticed that they produced less than expected. The under-production problem leads to questioning both the validity of the assessment methods and the inter-annual wind variability. This thesis tackles these two issues. In a first part are investigated the errors linked to the assessment methods, especially in two steps: the vertical extrapolation of wind measurements and the statistical modelling of wind-speed data by a Weibull distribution. The second part investigates the inter-annual to decadal variability of wind speeds, in order to understand how this variability may have contributed to the under-production and so that it is better taken into account in the future. (author) [fr

  14. Wind Power Prediction Considering Nonlinear Atmospheric Disturbances

    OpenAIRE

    Yagang Zhang; Jingyun Yang; Kangcheng Wang; Zengping Wang

    2015-01-01

    This paper considers the effect of nonlinear atmospheric disturbances on wind power prediction. A Lorenz system is introduced as an atmospheric disturbance model. Three new improved wind forecasting models combined with a Lorenz comprehensive disturbance are put forward in this study. Firstly, we define the form of the Lorenz disturbance variable and the wind speed perturbation formula. Then, different artificial neural network models are used to verify the new idea and obtain better wind spe...

  15. Wind Resource Assessment – Østerild National Test Centre for Large Wind Turbines

    OpenAIRE

    Hansen, Brian Ohrbeck; Courtney, Michael; Mortensen, Niels Gylling

    2014-01-01

    This report presents a wind resource assessment for the seven test stands at the Østerild National Test Centre for Large Wind Turbines in Denmark. Calculations have been carried out mainly using wind data from three on-site wind lidars. The generalized wind climates applied in the wind resource calculations for the seven test stands are based on correlations between a short period of on-site wind data from the wind lidars with a long-term reference. The wind resource assessment for the seven ...

  16. Offshore Wind Resources Assessment from Multiple Satellite Data and WRF Modeling over South China Sea

    Directory of Open Access Journals (Sweden)

    Rui Chang

    2015-01-01

    Full Text Available Using accurate inputs of wind speed is crucial in wind resource assessment, as predicted power is proportional to the wind speed cubed. This study outlines a methodology for combining multiple ocean satellite winds and winds from WRF simulations in order to acquire the accurate reconstructed offshore winds which can be used for offshore wind resource assessment. First, wind speeds retrieved from Synthetic Aperture Radar (SAR and Scatterometer ASCAT images were validated against in situ measurements from seven coastal meteorological stations in South China Sea (SCS. The wind roses from the Navy Operational Global Atmospheric Prediction System (NOGAPS and ASCAT agree well with these observations from the corresponding in situ measurements. The statistical results comparing in situ wind speed and SAR-based (ASCAT-based wind speed for the whole co-located samples show a standard deviation (SD of 2.09 m/s (1.83 m/s and correlation coefficient of R 0.75 (0.80. When the offshore winds (i.e., winds directed from land to sea are excluded, the comparison results for wind speeds show an improvement of SD and R, indicating that the satellite data are more credible over the open ocean. Meanwhile, the validation of satellite winds against the same co-located mast observations shows a satisfactory level of accuracy which was similar for SAR and ASCAT winds. These satellite winds are then assimilated into the Weather Research and Forecasting (WRF Model by WRF Data Assimilation (WRFDA system. Finally, the wind resource statistics at 100 m height based on the reconstructed winds have been achieved over the study area, which fully combines the offshore wind information from multiple satellite data and numerical model. The findings presented here may be useful in future wind resource assessment based on satellite data.

  17. Review of Methodologies for Offshore Wind Resource Assessment in European Seas

    DEFF Research Database (Denmark)

    Sempreviva, Anna Maria; Barthelmie, Rebecca Jane; Pryor, Sara

    2008-01-01

    The wind resource offshore is generally larger than at geographically nearby onshore sites, which can offset the higher installation, operation and maintenance costs associated with offshore wind parks. Successful offshore wind energy development relies to some extent on accurate prediction of wind...... promising wind farm sites and (ii) a site specific evaluation of wind climatology and vertical profiles of wind and atmospheric turbulence, in addition to an assessment of historical and possibly future changes due to climate non-stationarity. Phase (i) of the process can involve use of in situ observations...

  18. Wind and solar resource data sets: Wind and solar resource data sets

    Energy Technology Data Exchange (ETDEWEB)

    Clifton, Andrew [National Renewable Energy Laboratory, Golden CO USA; Hodge, Bri-Mathias [National Renewable Energy Laboratory, Golden CO USA; Power Systems Engineering Center, National Renewable Energy Laboratory, Golden CO USA; Draxl, Caroline [National Renewable Energy Laboratory, Golden CO USA; National Wind Technology Center, National Renewable Energy Laboratory, Golden CO USA; Badger, Jake [Department of Wind Energy, Danish Technical University, Copenhagen Denmark; Habte, Aron [National Renewable Energy Laboratory, Golden CO USA; Power Systems Engineering Center, National Renewable Energy Laboratory, Golden CO USA

    2017-12-05

    The range of resource data sets spans from static cartography showing the mean annual wind speed or solar irradiance across a region to high temporal and high spatial resolution products that provide detailed information at a potential wind or solar energy facility. These data sets are used to support continental-scale, national, or regional renewable energy development; facilitate prospecting by developers; and enable grid integration studies. This review first provides an introduction to the wind and solar resource data sets, then provides an overview of the common methods used for their creation and validation. A brief history of wind and solar resource data sets is then presented, followed by areas for future research.

  19. Wind Power predictability a risk factor in the design, construction and operation of Wind Generation Turbines

    Science.gov (United States)

    Thiesen, J.; Gulstad, L.; Ristic, I.; Maric, T.

    2010-09-01

    Summit: The wind power predictability is often a forgotten decision and planning factor for most major wind parks, both onshore and offshore. The results of the predictability are presented after having examined a number of European offshore and offshore parks power predictability by using three(3) mesoscale model IRIE_GFS and IRIE_EC and WRF. Full description: It is well known that the potential wind production is changing with latitude and complexity in terrain, but how big are the changes in the predictability and the economic impacts on a project? The concept of meteorological predictability has hitherto to some degree been neglected as a risk factor in the design, construction and operation of wind power plants. Wind power plants are generally built in places where the wind resources are high, but these are often also sites where the predictability of the wind and other weather parameters is comparatively low. This presentation addresses the question of whether higher predictability can outweigh lower average wind speeds with regard to the overall economy of a wind power project. Low predictability also tends to reduce the value of the energy produced. If it is difficult to forecast the wind on a site, it will also be difficult to predict the power production. This, in turn, leads to increased balance costs and a less reduced carbon emission from the renewable source. By investigating the output from three(3) mesoscale models IRIE and WRF, using ECMWF and GFS as boundary data over a forecasting period of 3 months for 25 offshore and onshore wind parks in Europe, the predictability are mapped. Three operational mesoscale models with two different boundary data have been chosen in order to eliminate the uncertainty with one mesoscale model. All mesoscale models are running in a 10 km horizontal resolution. The model output are converted into "day a head" wind turbine generation forecasts by using a well proven advanced physical wind power model. The power models

  20. 2016 Offshore Wind Energy Resource Assessment for the United States

    Energy Technology Data Exchange (ETDEWEB)

    Musial, Walt [National Renewable Energy Lab. (NREL), Golden, CO (United States); Heimiller, Donna [National Renewable Energy Lab. (NREL), Golden, CO (United States); Beiter, Philipp [National Renewable Energy Lab. (NREL), Golden, CO (United States); Scott, George [National Renewable Energy Lab. (NREL), Golden, CO (United States); Draxl, Caroline [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2016-09-01

    This report, the 2016 Offshore Wind Energy Resource Assessment for the United States, was developed by the National Renewable Energy Laboratory, and updates a previous national resource assessment study, and refines and reaffirms that the available wind resource is sufficient for offshore wind to be a large-scale contributor to the nation's electric energy supply.

  1. A high resolution global wind atlas - improving estimation of world wind resources

    DEFF Research Database (Denmark)

    Badger, Jake; Ejsing Jørgensen, Hans

    2011-01-01

    data and the tools necessary are present, so the time is right to link the parts together to create a much needed dataset. Geospatial information systems (GIS) will be one of the significant applications of the Global Wind Atlas datasets. As location of wind resource, and its relationships...... resources. These aspects will also be addressed by the Global Wind Atlas. The Global Wind Atlas, through a transparent methodology, will provide a unified, high resolution, and public domain dataset of wind energy resources for the whole world. The wind atlas data will be the most appropriate wind resource...

  2. Using machine learning to predict wind turbine power output

    International Nuclear Information System (INIS)

    Clifton, A; Kilcher, L; Lundquist, J K; Fleming, P

    2013-01-01

    Wind turbine power output is known to be a strong function of wind speed, but is also affected by turbulence and shear. In this work, new aerostructural simulations of a generic 1.5 MW turbine are used to rank atmospheric influences on power output. Most significant is the hub height wind speed, followed by hub height turbulence intensity and then wind speed shear across the rotor disk. These simulation data are used to train regression trees that predict the turbine response for any combination of wind speed, turbulence intensity, and wind shear that might be expected at a turbine site. For a randomly selected atmospheric condition, the accuracy of the regression tree power predictions is three times higher than that from the traditional power curve methodology. The regression tree method can also be applied to turbine test data and used to predict turbine performance at a new site. No new data are required in comparison to the data that are usually collected for a wind resource assessment. Implementing the method requires turbine manufacturers to create a turbine regression tree model from test site data. Such an approach could significantly reduce bias in power predictions that arise because of the different turbulence and shear at the new site, compared to the test site. (letter)

  3. Optimal prediction intervals of wind power generation

    DEFF Research Database (Denmark)

    Wan, Can; Wu, Zhao; Pinson, Pierre

    2014-01-01

    direct optimization of both the coverage probability and sharpness to ensure the quality. The proposed method does not involve the statistical inference or distribution assumption of forecasting errors needed in most existing methods. Case studies using real wind farm data from Australia have been...... penetration beforehand. This paper proposes a novel hybrid intelligent algorithm approach to directly formulate optimal prediction intervals of wind power generation based on extreme learning machine and particle swarm optimization. Prediction intervals with Associated confidence levels are generated through...

  4. Wind Power Prediction using Ensembles

    DEFF Research Database (Denmark)

    Giebel, Gregor; Badger, Jake; Landberg, Lars

    2005-01-01

    offshore wind farm and the whole Jutland/Funen area. The utilities used these forecasts for maintenance planning, fuel consumption estimates and over-the-weekend trading on the Leipzig power exchange. Othernotable scientific results include the better accuracy of forecasts made up from a simple...... superposition of two NWP provider (in our case, DMI and DWD), an investigation of the merits of a parameterisation of the turbulent kinetic energy within thedelivered wind speed forecasts, and the finding that a “naïve” downscaling of each of the coarse ECMWF ensemble members with higher resolution HIRLAM did...

  5. Estimating the Wind Resource in Uttarakhand: Comparison of Dynamic Downscaling with Doppler Lidar Wind Measurements

    Energy Technology Data Exchange (ETDEWEB)

    Lundquist, J. K. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Pukayastha, A. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Martin, C. [Univ. of Colorado, Boulder, CO (United States); Newsom, R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

    2014-03-01

    Previous estimates of the wind resources in Uttarakhand, India, suggest minimal wind resources in this region. To explore whether or not the complex terrain in fact provides localized regions of wind resource, the authors of this study employed a dynamic down scaling method with the Weather Research and Forecasting model, providing detailed estimates of winds at approximately 1 km resolution in the finest nested simulation.

  6. Wind Resource and Feasibility Assessment Report for the Lummi Reservation

    Energy Technology Data Exchange (ETDEWEB)

    DNV Renewables (USA) Inc.; J.C. Brennan & Associates, Inc.; Hamer Environmental L.P.

    2012-08-31

    This report summarizes the wind resource on the Lummi Indian Reservation (Washington State) and presents the methodology, assumptions, and final results of the wind energy development feasibility assessment, which included an assessment of biological impacts and noise impacts.

  7. 75 FR 75961 - Notice of Implementation of the Wind Erosion Prediction System for Soil Erodibility System...

    Science.gov (United States)

    2010-12-07

    ... Wind Erosion Prediction System for Soil Erodibility System Calculations for the Natural Resources... Erosion Prediction System (WEPS) for soil erodibility system calculations scheduled for implementation for... Erosion Equation (WEQ) where applicable. DATES: Effective Date: This is effective December 7, 2010...

  8. Comparison of SAR Wind Speed Retrieval Algorithms for Evaluating Offshore Wind Energy Resources

    DEFF Research Database (Denmark)

    Kozai, K.; Ohsawa, T.; Takeyama, Y.

    2010-01-01

    Envisat/ASAR-derived offshore wind speeds and energy densities based on 4 different SAR wind speed retrieval algorithms (CMOD4, CMOD-IFR2, CMOD5, CMOD5.N) are compared with observed wind speeds and energy densities for evaluating offshore wind energy resources. CMOD4 ignores effects of atmospheric...

  9. Short-term wind power prediction

    DEFF Research Database (Denmark)

    Joensen, Alfred K.

    2003-01-01

    The present thesis consists of 10 research papers published during the period 1997-2002 together with a summary report. The objective of the work described in the thesis is to develop models and methods for calculation of high accuracy predictions of wind power generated electricity, and to imple......The present thesis consists of 10 research papers published during the period 1997-2002 together with a summary report. The objective of the work described in the thesis is to develop models and methods for calculation of high accuracy predictions of wind power generated electricity......, and to implement these models and methods in an on-line software application. The economical value of having predictions available is also briefly considered. The summary report outlines the background and motivation for developing wind power prediction models. The meteorological theory which is relevant...

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

    Energy Technology Data Exchange (ETDEWEB)

    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.

  11. Wind Technology Advancements and Impacts on Western Wind Resources (Presentation)

    Energy Technology Data Exchange (ETDEWEB)

    Robichaud, R.

    2014-09-01

    Robi Robichaud made this presentation at the Bureau of Land Management West-wide Wind Opportunities and Constraints Mapping (WWOCM) Project public meeting in Denver, Colorado in September 2014. This presentation outlines recent wind technology advancements, evolving turbine technologies, and industry challenges. The presentation includes maps of mean wind speeds at 50-m, 80-m, and 100-m hub heights on BLM lands. Robichaud also presented on the difference in mean wind speeds from 80m to 100m in Wyoming.

  12. Assessment of regional wind energy resources over the Ukraine

    Science.gov (United States)

    Sobchenko, Anastasiia; Khomenko, Inna

    2015-04-01

    The purpose of the study has been to provide a preliminary assessment of different regions of the Ukraine. Investigation is based on thirty-minute wind observations collected through an 8-year period (January 1, 2002 to December 31, 2008) for seven airports of the Ukraine. For renewal of vertical profile of the wind direction and speed radiosounding data were used. By applying of the probabilistic analysis techniques to series of wind data and the wind extreme values, yearly, monthly and diurnal variation of wind speed and direction are derived. Based on these results theoretical distribution functions and exceeding probability are found for each airport. The statistic characteristics obtained were compared with the correspondent values provided for 1936-1960 and 1961-1990 periods and site-related temporal changeability is determined. For each period considered assessment of wind resources at 10 meters height is carried out. Since the geostrophic wind are frequently used to calculate the surface wind at heights between 10 and 200 m, in the research the distribution of the geostrophic wind for each airport were determined. Comparative analysis of distribution and statistic characteristics of geostrophic and surface winds are made. The relation between a set of values of the geostrophic wind and a set of values of the surface wind speed was provided for each airport. Using different relationship for variation of wind speed with height wind resources at heights between 10 and 200 were assessed. The results obtained show that with the lapse of the time wind speed and wind resources is decreased half the size. It is reflected general tendencies in the wind speed changeability over the European territory. Places which are most perspective for wind turbine installation are off-shore sites such as Odessa, and sites situated in the Crimea mountain (Simferopol) and the Donetsk ridge (Donetsk). The results derived in the contribution may be used for modeling and mapping wind

  13. Offshore wind resources at Danish measurement sites

    Energy Technology Data Exchange (ETDEWEB)

    Barthelmie, R.J.; Courtney, M.S.; Lange, B.; Nielsen, M.; Sempreviva, A.M. [Risoe National Lab., Dept. of Wind Energy and Atmospheric Physics, Roskilde (Denmark); Svenson, J.; Olsen, F. [SEAS, Haslev (Denmark); Christensen, T. [Elsamprojekt, Fredericia (Denmark)

    1999-03-01

    In order to characterise wind and turbulence characteristics at prospective offshore wind energy sites, meteorological observations from a number of purpose-built offshore monitoring sites have been analyzed and compared with long wind speed time series. New analyses have been conducted on the data sets focussing on meteorology, turbulence, extreme winds and wind and wave interactions. Relationships between wind speed, turbulence and fetch are highly complex. Minimum turbulence intensity offshore is associated with wind speeds of about 12 m/s. At lower wind speeds, stability effects are important while at higher winds speeds wind and wave interactions appear to dominate. On average, turbulence intensity offshore at 48 m height is approximately 0.08 if no coastal effects are present. However, the effect of the coastal discontinuity persists in wind speed and turbulence characteristics for considerable distances offshore. The majority of the adjustment of appears to occur within 20 km of the coast. (au)

  14. Neural Network Classifiers for Local Wind Prediction.

    Science.gov (United States)

    Kretzschmar, Ralf; Eckert, Pierre; Cattani, Daniel; Eggimann, Fritz

    2004-05-01

    This paper evaluates the quality of neural network classifiers for wind speed and wind gust prediction with prediction lead times between +1 and +24 h. The predictions were realized based on local time series and model data. The selection of appropriate input features was initiated by time series analysis and completed by empirical comparison of neural network classifiers trained on several choices of input features. The selected input features involved day time, yearday, features from a single wind observation device at the site of interest, and features derived from model data. The quality of the resulting classifiers was benchmarked against persistence for two different sites in Switzerland. The neural network classifiers exhibited superior quality when compared with persistence judged on a specific performance measure, hit and false-alarm rates.

  15. Assessment and prediction of wind turbine noise

    International Nuclear Information System (INIS)

    Lowson, M.V.

    1993-01-01

    The significance of basic aerodynamic noise sources for wind turbine noise are assessed, using information on the aero-acoustic mechanisms of other rotors, which have been studied in depth for many years. From the analysis, areas of potential improvement in wind turbine noise prediction are defined. Suggestions are made for approaches to wind turbine noise control which separate the noise problems at cut-in from those at rated power. Some of these offer the possibility of noise reduction without unfavourable effects on performance. Based on this analysis, a new model for prediction of wind turbine noise is presented and comparisons made between prediction and experiment. The model is based on well established aeroacoustic theory and published laboratory data for the two principal sources, inflow turbulence and boundary layer trailing edge interaction. The new method gives good agreement with experiment with the case studied so far. Parametric trends and sensitivities for the model are presented. Comparisons with previous prediction methods are also given. A consequence of the new model is to put more emphasis on boundary layer trailing edge interaction as a noise source. There are prospects for reducing noise from this source detail changes to the wind turbine design. (author)

  16. Load prediction of stall regulated wind turbines

    Energy Technology Data Exchange (ETDEWEB)

    Bjoerck, A.; Dahlberg, J.Aa. [Aeronautical Research Inst. of Sweden, Bromma (Sweden); Carlen, I. [Chalmers Univ. of Technology, Goeteborg (Sweden). Div. of Marine Structural Engineering; Ganander, H. [Teknikgruppen AB, Sollentua (Sweden)

    1996-12-01

    Measurements of blade loads on a turbine situated in a small wind farm shows that the highest blade loads occur during operation close to the peak power i.e. when the turbine operates in the stall region. In this study the extensive experimental data base has been utilised to compare loads in selected campaigns with corresponding load predictions. The predictions are based on time domain simulations of the wind turbine structure, performed by the aeroelastic code VIDYN. In the calculations a model were adopted in order to include the effects of dynamic stall. This paper describes the work carried out so far within the project and key results. 5 refs, 10 figs

  17. Predictability and Variability of Wave and Wind

    DEFF Research Database (Denmark)

    Chozas, Julia Fernandez; Kofoed, Jens Peter; Sørensen, Hans Christian

    This project covers two fields of study: a) Wave energy predictability and electricity markets. b) Variability of the power output of WECs in diversified systems : diversified renewable systems with wave and offshore wind production. See page 2-4 in the report for a executive summery.......This project covers two fields of study: a) Wave energy predictability and electricity markets. b) Variability of the power output of WECs in diversified systems : diversified renewable systems with wave and offshore wind production. See page 2-4 in the report for a executive summery....

  18. Conditional prediction intervals of wind power generation

    DEFF Research Database (Denmark)

    Pinson, Pierre; Kariniotakis, Georges

    2010-01-01

    A generic method for the providing of prediction intervals of wind power generation is described. Prediction intervals complement the more common wind power point forecasts, by giving a range of potential outcomes for a given probability, their so-called nominal coverage rate. Ideally they inform...... of the situation-specific uncertainty of point forecasts. In order to avoid a restrictive assumption on the shape of forecast error distributions, focus is given to an empirical and nonparametric approach named adapted resampling. This approach employs a fuzzy inference model that permits to integrate expertise...

  19. Applicability of Synthetic Aperture Radar Wind Retrievals on Offshore Wind Resources Assessment in Hangzhou Bay, China

    DEFF Research Database (Denmark)

    Chang, Rui; Zhu, Rong; Badger, Merete

    2014-01-01

    ENVISAT advanced SAR (ASAR) for mapping wind resources with high spatial resolution. Around 181 collected pairs of wind data from SAR wind maps and from 13 meteorological stations in Hangzhou Bay are compared. The statistical results comparing in situ wind speed and SAR-based wind speed show a standard...... deviation (SD) of 1.99 m/s and correlation coefficient of R = 0.67. The model wind directions, which are used as input for the SAR wind speed retrieval, show a high correlation coefficient (R = 0.89) but a large standard deviation (SD = 42.3°) compared to in situ observations. The Weibull probability...

  20. Wind power in Scotland - a critique of recent resource assessments

    International Nuclear Information System (INIS)

    Twidell, J.W.

    1995-01-01

    A critical analysis of 4 recent UK official reports relating to the renewable energy resources of Scotland, particularly the large wind resource, and including institutional and economic factors. Key points are listed with comments for use in supporting wind power developments. (Author)

  1. Remotely sensed data fusion for offshore wind energy resource mapping

    International Nuclear Information System (INIS)

    Ben Ticha, M.B.

    2007-11-01

    Wind energy is a component of an energy policy contributing to a sustainable development. Last years, offshore wind parks have been installed offshore. These parks benefit from higher wind speeds and lower turbulence than onshore. To sit a wind park, it is necessary to have a mapping of wind resource. These maps are needed at high spatial resolution to show wind energy resource variations at the scale of a wind park. Wind resource mapping is achieved through the description of the spatial variations of statistical parameters characterizing wind climatology. For a precise estimation of these statistical parameters, high temporal resolution wind speed and direction measurements are needed. However, presently, there is no data source allying high spatial resolution and high temporal resolution. We propose a data fusion method taking advantage of the high spatial resolution of some remote sensing instruments (synthetic aperture radars) and the high temporal resolution of other remote sensing instruments (scatterometers). The data fusion method is applied to a case study and the results quality is assessed. The results show the pertinence of data fusion for the mapping of wind energy resource offshore. (author)

  2. Management of moderate wind energy coastal resources

    International Nuclear Information System (INIS)

    Karamanis, D.

    2011-01-01

    Research highlights: → Life cycle analysis reveals the viability of moderate wind fields utilization. → Wind turbine is the greenest electricity generator at a touristic site. → Wind parks should be collective applications of small hotel-apartments owners. -- Abstract: The feasibility of wind energy utilization at moderate wind fields was investigated for a typical touristic coastal site in Western Greece. Initially, the wind speed and direction as well as its availability, duration and diurnal variation were assessed. For an analysis period of eight years, the mean wind speed at ten meters was determined as 3.8 m s -1 with a small variation in monthly average wind speeds between 3.0 (January) and 4.4 m s -1 (October). The mean wind power density was less than 200 W m -2 at 10 m indicating the limiting suitability of the site for the usual renewable energy applications. However, life cycle analysis for wind turbine generators with lower cut-in, cut-out, and rated speeds revealed that the energy yield ratio can reach a value of six for a service life of 20 years while the energy pay-back period can be 3 years with 33 kt CO 2 -e of avoided greenhouse emissions. Therefore, the recent technological turbine improvements make wind power viable even at moderate wind fields. Moreover, the study of electricity supply of typical small hotel-apartments in the region of Western Greece indicated that the installation of 300 wind turbine generators in these moderate wind fields would cover the total consumption during the open touristic period with profits during the rest of the year. According to these results, wind turbine generators are the 'greenest' way of generating electricity in touristic coastal sites, even of moderate wind speeds.

  3. Predicting annoyance by wind turbine noise

    NARCIS (Netherlands)

    Janssen, S.A.; Vos, H.; Eisses, A.R.; Pedersen, E.

    2010-01-01

    While wind turbines have beneficial effects for the environment, they inevitably generate environmental noise. In order to protect residents against unacceptable levels of noise, exposure-response relationships are needed to predict the expected percentage of people annoyed or highly annoyed at a

  4. Wind Resource Assessment Report: Mille Lacs Indian Reservation, Minnesota

    Energy Technology Data Exchange (ETDEWEB)

    Jimenez, Antonio C. [National Renewable Energy Lab. (NREL), Golden, CO (United States); Robichaud, Robi [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2013-12-01

    The U.S. Environmental Protection Agency (EPA) launched the RE-Powering America's Land initiative to encourage development of renewable energy on potentially contaminated land and mine sites. EPA collaborated with the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL) and the Mille Lacs Band of Chippewa Indians to evaluate the wind resource and examine the feasibility of a wind project at a contaminated site located on the Mille Lacs Indian Reservation in Minnesota. The wind monitoring effort involved the installation of a 60-m met tower and the collection of 18 months of wind data at multiple heights above the ground. This report focuses on the wind resource assessment, the estimated energy production of wind turbines, and an assessment of the economic feasibility of a potential wind project sited this site.

  5. Asynchrony of wind and hydropower resources in Australia

    KAUST Repository

    Gunturu, Udaya

    2017-08-14

    Wind and hydropower together constitute nearly 80% of the renewable capacity in Australia and their resources are collocated. We show that wind and hydro generation capacity factors covary negatively at the interannual time scales. Thus, the technology diversity mitigates the variability of renewable power generation at the interannual scales. The asynchrony of wind and hydropower resources is explained by the differential impact of the two modes of the El Ni˜no Southern Oscillation – canonical and Modoki – on the wind and hydro resources. Also, the Modoki El Ni˜no and the Modoki La Ni˜na phases have greater impact. The seasonal impact patterns corroborate these results. As the proportion of wind power increases in Australia’s energy mix, this negative covariation has implications for storage capacity of excess wind generation at short time scales and for generation system adequacy at the longer time scales.

  6. Asynchrony of wind and hydropower resources in Australia.

    Science.gov (United States)

    Gunturu, Udaya Bhaskar; Hallgren, Willow

    2017-08-18

    Wind and hydropower together constitute nearly 80% of the renewable capacity in Australia and their resources are collocated. We show that wind and hydro generation capacity factors covary negatively at the interannual time scales. Thus, the technology diversity mitigates the variability of renewable power generation at the interannual scales. The asynchrony of wind and hydropower resources is explained by the differential impact of the two modes of the El Ni˜no Southern Oscillation - canonical and Modoki - on the wind and hydro resources. Also, the Modoki El Ni˜no and the Modoki La Ni˜na phases have greater impact. The seasonal impact patterns corroborate these results. As the proportion of wind power increases in Australia's energy mix, this negative covariation has implications for storage capacity of excess wind generation at short time scales and for generation system adequacy at the longer time scales.

  7. Wind energy resource atlas. Volume 7. The south central region

    Energy Technology Data Exchange (ETDEWEB)

    Edwards, R.L.; Graves, L.F.; Sprankle, A.C.; Elliott, D.L.; Barchet, W.R.; George, R.L.

    1981-03-01

    This atlas of the south central region combines seven collections of wind resource data: one for the region, and one for each of the six states (Arkansas, Kansas, Louisiana, Missouri, Oklahoma, and Texas). At the state level, features of the climate, topography, and wind resource are discussed in greater detail than that provided in the regional discussion, and the data locations on which the assessment is based are mapped. Variations, over several time scales, in the wind resource at selected stations in each state are shown on graphs of monthly average and interannual wind speed and power, and hourly average wind speed for each season. Other graphs present speed, direction, and duration frequencies of the wind at these locations.

  8. Wind energy resource atlas. Volume 3. Great Lakes Region

    Energy Technology Data Exchange (ETDEWEB)

    Paton, D.L.; Bass, A.; Smith, D.G.; Elliott, D.L.; Barchet, W.R.; George, R.L.

    1981-02-01

    The Great Lakes Region atlas assimilates six collections of wind resource data, one for the region and one for each of the five states that compose the Great Lakes region: Illinois, Indiana, Michigan, Ohio, Wisconsin. At the state level, features of the climate, topography, and wind resource are discussed in greater detail than in the regional discussion and the data locations on which the assessment is based are mapped. Variations over several time scales in the wind resource at selected stations in each state are shown on graphs of monthly average and interannual wind speed and power, and of hourly average wind speed for each season. Other graphs present speed, direction, and duration frequencies of the wind at these locations.

  9. Quantifying offshore wind resources from satellite wind maps: Study area the North Sea

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Barthelmie, Rebecca Jane; Christiansen, Merete B.

    2006-01-01

    Offshore wind resources are quantified from satellite synthetic aperture radar (SAR) and satellite scatterometer observations at local and regional scale respectively at the Horns Rev site in Denmark. The method for wind resource estimation from satellite observations interfaces with the wind atlas...... of the Horns Rev wind farm is quantified from satellite SAR images and compared with state-of-the-art wake model results with good agreement. It is a unique method using satellite observations to quantify the spatial extent of the wake behind large offshore wind farms. Copyright © 2006 John Wiley & Sons, Ltd....... analysis and application program (WAsP). An estimate of the wind resource at the new project site at Horns Rev is given based on satellite SAR observations. The comparison of offshore satellite scatterometer winds, global model data and in situ data shows good agreement. Furthermore, the wake effect...

  10. Wind Resource Assessment in Abadan Airport in Iran

    Directory of Open Access Journals (Sweden)

    Mojtaba Nedaei

    2012-11-01

    Full Text Available Renewable energies have potential for supplying of relatively clean and mostly local energy. Wind energy generation is expected to increase in the near future and has experienced dramatic growth over the past decade in many countries. Wind speed is the most important parameter in the design and study of wind energy conversion systems. Probability density functions such as Weibull and Rayleigh are often used in wind speed and wind energy analyses. This paper presents an assessment of wind energy at three heights during near two years based on Weibull distribution function in Abadan Airport. Extrapolation of the 10 m and 40 m data, using the power law, has been used to determine the wind speed at height of 80 m. According to the results wind speed at 80 m height in Abadan is ranged from 5.8 m/s in Nov to 8.5 m/s in Jun with average value of 7.15 m/s. In this study, different parameters such as Weibull parameters, diurnal and monthly wind speeds, cumulative distribution and turbulence intensity have been estimated and analyzed. In addition Energy production of different wind turbines at different heights was estimated. The results show that the studied site has good potential for Installation of large and commercial wind turbines at height of 80 m or higher. Keywords: Abadan, Iran, wind energy, wind resource, wind turbine, Weibull

  11. Wind resource assessment and siting analysis in Italy

    International Nuclear Information System (INIS)

    Ricci, A.; Mizzoni, G.; Rossi, E.

    1992-01-01

    Recently, the wind power industry has matured; consequently, in many countries a lot of wind energy applications have been programmed. Many of them are already realized and running. As such, there is a direct necessity to identify a sizeable number of wind power plant sites. Choosing the right sites to match specific Wind Energy Conversion Systems (WECS) is also needed to harness this clean energy from the points of view of industrial viability and project financing. As a pre-requisite to install a wind turbine at a particular site, it is necessary to have knowledge of the theoretical available wind energy at the site, as well as, of the practicability of the design in matching the characteristics of the WECS. In this paper, ENEA (Italian National Agency for New Technology, Energy and Environment) wind siting and resource assessment activities, currently on-going in different regions in Italy, along with the present status and future prospects of the wind power industry

  12. Wind as a renewable energy resource

    Science.gov (United States)

    Hawsey, R. A.; Ferraro, R. J.

    1988-12-01

    A description of the United States wind energy technology status, a discussion of recent milestones achieved in wind power, and a call for action in order for competitive wind systems to become practical in an international marketplace is presented in this report. An immediate opportunity to initiate a joint venture project with the government, equipment developers, equipment manufacturers, utilities, and the Electric Power Research Institute is described. The key technical areas of materials technology for reduced airfoil fatigue, airfoil design for optimum new-site performance, and power electronics for variable-speed wind turbines are highlighted.

  13. Wind energy resource assessment using wind atlas and meteorological data for the City of Guelph, Canada

    Energy Technology Data Exchange (ETDEWEB)

    McIntyre, J.H.; Lubitz, W.D.; Stiver, W.H. [Guelph Univ., ON (Canada). School of Engineering

    2008-07-01

    Community awareness of energy in the City of Guelph has led to the development of an energy plan that involves the use of energy supplied from renewable sources, including wind resources which are particularly difficult to evaluate at the community level. This paper reported on a study that estimated the total wind energy resource that could potentially be harnessed within the boundaries of the City of Guelph. The study also compared the power production potential forecast by various models. The goal relied on several objectives such as obtaining wind speed data from local meteorological stations and using that data to obtain wind speed distribution parameters at several heights. Available wind atlases were used to obtain wind speed distribution parameters from these resource and to estimate the potential power output of two wind turbines. The potential power output of an array of these wind turbines was determined based on the footprint necessary to minimize interference between turbines. The wind turbine arrays were ranked based on total power output. The different data sources produced wind energy estimates all within 44 per cent of each other for a small wind turbine of 10 kW. Community scale generation was estimated through a uniform grid of turbines across the city. Nearly 18,000 small wind turbines generate 139 GWh while 128 utility-scale turbines generate 424 GWh. These utility-scale turbines could potentially deliver 24 per cent of Guelph's 2005 electrical demand. 12 refs., 2 tabs., 5 figs.

  14. Assessment of Global Wind Energy Resource Utilization Potential

    Science.gov (United States)

    Ma, M.; He, B.; Guan, Y.; Zhang, H.; Song, S.

    2017-09-01

    Development of wind energy resource (WER) is a key to deal with climate change and energy structure adjustment. A crucial issue is to obtain the distribution and variability of WER, and mine the suitable location to exploit it. In this paper, a multicriteria evaluation (MCE) model is constructed by integrating resource richness and stability, utilization value and trend of resource, natural environment with weights. The global resource richness is assessed through wind power density (WPD) and multi-level wind speed. The utilizable value of resource is assessed by the frequency of effective wind. The resource stability is assessed by the coefficient of variation of WPD and the frequency of prevailing wind direction. Regression slope of long time series WPD is used to assess the trend of WER. All of the resource evaluation indicators are derived from the atmospheric reanalysis data ERA-Interim with spatial resolution 0.125°. The natural environment factors mainly refer to slope and land-use suitability, which are derived from multi-resolution terrain elevation data 2010 (GMTED 2010) and GlobalCover2009. Besides, the global WER utilization potential map is produced, which shows most high potential regions are located in north of Africa. Additionally, by verifying that 22.22 % and 48.8 9% operational wind farms fall on medium-high and high potential regions respectively, the result can provide a basis for the macroscopic siting of wind farm.

  15. Assessing Global Ocean Wind Energy Resources Using Multiple Satellite Data

    Directory of Open Access Journals (Sweden)

    Qiaoying Guo

    2018-01-01

    Full Text Available Wind energy, as a vital renewable energy source, also plays a significant role in reducing carbon emissions and mitigating climate change. It is therefore of utmost necessity to evaluate ocean wind energy resources for electricity generation and environmental management. Ocean wind distribution around the globe can be obtained from satellite observations to compensate for limited in situ measurements. However, previous studies have largely ignored uncertainties in ocean wind energy resources assessment with multiple satellite data. It is against this background that the current study compares mean wind speeds (MWS and wind power densities (WPD retrieved from scatterometers (QuikSCAT, ASCAT and radiometers (WindSAT and their different combinations with National Data Buoy Center (NDBC buoy measurements at heights of 10 m and 100 m (wind turbine hub height above sea level. Our results show an improvement in the accuracy of wind resources estimation with the use of multiple satellite observations. This has implications for the acquisition of reliable data on ocean wind energy in support of management policies.

  16. Wind Resource Assessment and Requested Wind Turbine Recommendations

    Energy Technology Data Exchange (ETDEWEB)

    Smith, Ken [Municipal Civil Corporation, Gas City, IN (United States); Wolar, John [Municipal Civil Corporation, Gas City, IN (United States)

    2012-10-22

    Alternate Energy Solutions, Inc. (“AESWR”) was engaged by the Town of Brookston (“Brookston”) to assemble, erect and maintain one 60 m XHD meteorological tower manufactured by NRG Systems, Inc.; for monitoring, recording and evaluating collected wind data. It is the opinion of AESWR staff that study results support the development of a wind turbine project at the Bol Family Farm provided: a) additional land is leased for the project; b) project construction costs are controlled; and c) a prudent power purchase agreement is negotiated with a power take-off entity. We believe that a project having an aggregate nameplate rating sized from 6.0 MW to 20 MW would be appropriate for this location. We recommend 100-125 acres of land per installed MW be used as a general rule for acquiring wind energy land lease agreements, total land lease holdings to be acquired would then approach 750 acres to 2,500 acres.

  17. Session: What can we learn from developed wind resource areas

    Energy Technology Data Exchange (ETDEWEB)

    Thelander, Carl; Erickson, Wally

    2004-09-01

    This session at the Wind Energy and Birds/Bats workshop was composed of two parts intended to examine what existing science tells us about wind turbine impacts at existing wind project sites. Part one dealt with the Altamont Wind Resource area, one of the older wind projects in the US, with a paper presented by Carl Thelander titled ''Bird Fatalities in the Altamont Pass Wind Resource Area: A Case Study, Part 1''. Questions addressed by the presenter included: how is avian habitat affected at Altamont and do birds avoid turbine sites; are birds being attracted to turbine strings; what factors contribute to direct impacts on birds by wind turbines at Altamont; how do use, behavior, avoidance and other factors affect risk to avian species, and particularly impacts those species listed as threatened, endangered, or of conservation concern, and other state listed species. The second part dealt with direct impacts to birds at new generation wind plants outside of California, examining such is sues as mortality, avoidance, direct habitat impacts from terrestrial wind projects, species and numbers killed per turbine rates/MW generated, impacts to listed threatened and endangered species, to USFWS Birds of Conservation Concern, and to state listed species. This session focused on newer wind project sites with a paper titled ''Bird Fatality and Risk at New Generation Wind Projects'' by Wally Erickson. Each paper was followed by a discussion/question and answer period.

  18. Terminology Guideline for Classifying Offshore Wind Energy Resources

    Energy Technology Data Exchange (ETDEWEB)

    Beiter, Philipp [National Renewable Energy Lab. (NREL), Golden, CO (United States); Musial, Walt [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2016-09-01

    The purpose of this guideline is to establish a clear and consistent vocabulary for conveying offshore wind resource potential and to interpret this vocabulary in terms that are familiar to the oil and gas (O&G) industry. This involves clarifying and refining existing definitions of offshore wind energy resource classes. The terminology developed in this guideline represents one of several possible sets of vocabulary that may differ with respect to their purpose, data availability, and comprehensiveness. It was customized to correspond with established offshore wind practices and existing renewable energy industry terminology (e.g. DOE 2013, Brown et al. 2015) while conforming to established fossil resource classification as best as possible. The developers of the guideline recognize the fundamental differences that exist between fossil and renewable energy resources with respect to availability, accessibility, lifetime, and quality. Any quantitative comparison between fossil and renewable energy resources, including offshore wind, is therefore limited. For instance, O&G resources are finite and there may be significant uncertainty associated with the amount of the resource. In contrast, aboveground renewable resources, such as offshore wind, do not generally deplete over time but can vary significantly subhourly, daily, seasonally, and annually. The intent of this guideline is to make these differences transparent and develop an offshore wind resource classification that conforms to established fossil resource classifications where possible. This guideline also provides methods to quantitatively compare certain offshore wind energy resources to O&G resource classes for specific applications. Finally, this guideline identifies areas where analogies to established O&G terminology may be inappropriate or subject to misinterpretation.

  19. Satellite based wind resource assessment over the South China Sea

    DEFF Research Database (Denmark)

    Badger, Merete; Astrup, Poul; Hasager, Charlotte Bay

    2014-01-01

    years of WRF data – specifically the parameters heat flux, air temperature, and friction velocity – are used to calculate a long-term correction for atmospheric stability effects. The stability correction is applied to the satellite based wind resource maps together with a vertical wind profile...... from satellite synthetic aperture radar (SAR) data are particularly suitable for offshore wind energy applications because they offer a spatial resolution up to 500 m and include coastal seas. In this presentation, satellite wind maps are used in combination with mast observations and numerical...... modeling to develop procedures and best practices for satellite based wind resource assessment offshore. All existing satellite images from the Envisat Advanced SAR sensor by the European Space Agency (2002-12) have been collected over a domain in the South China Sea. Wind speed is first retrieved from...

  20. A comprehensive measure of the energy resource: Wind power potential (WPP)

    International Nuclear Information System (INIS)

    Zhang, Jie; Chowdhury, Souma; Messac, Achille

    2014-01-01

    Highlights: • A more comprehensive metric is developed to accurately assess the quality of wind resources at a site. • WPP exploits the joint distribution of wind speed and direction, and yields more credible estimates. • WPP investigates the effect of wind distribution on the optimal net power generation of a farm. • The results show that WPD and WPP follow different trends. - Abstract: Currently, the quality of available wind energy at a site is assessed using wind power density (WPD). This paper proposes to use a more comprehensive metric: the wind power potential (WPP). While the former accounts for only wind speed information, the latter exploits the joint distribution of wind speed and wind direction and yields more credible estimates. The WPP investigates the effect of wind velocity distribution on the optimal net power generation of a farm. A joint distribution of wind speed and direction is used to characterize the stochastic variation of wind conditions. Two joint distribution methods are adopted in this paper: bivariate normal distribution and anisotropic lognormal method. The net power generation for a particular farmland size and installed capacity is maximized for different distributions of wind speed and wind direction, using the Unrestricted Wind Farm Layout Optimization (UWFLO) framework. A response surface is constructed to represent the computed maximum wind farm capacity factor as a function of the parameters of the wind distribution. Two different response surface methods are adopted in this paper: (i) the adaptive hybrid functions (AHF), and (ii) the quadratic response surface method (QRSM). Toward this end, for any farm site, we can (i) estimate the parameters of the joint distribution using recorded wind data (for bivariate normal or anisotropic lognormal distributions) and (ii) predict the maximum capacity factor for a specified farm size and capacity using this response surface. The WPP metric is illustrated using recorded wind

  1. High-altitude wind resources in the Middle East

    KAUST Repository

    Yip, Chak Man Andrew

    2017-08-23

    In the Middle East, near-surface wind resources are intermittent. However, high-altitude wind resources are abundant, persistent, and readily available and may provide alternative energy resources in this fossil-fuel-dependent region. Using wind field data from the Modern-Era Retrospective Analysis for Research and Applications Version 2 (MERRA-2), this study identifies areas favorable to the deployment of airborne wind energy (AWE) systems in the Middle East and computes the optimal heights at which such systems would best operate. AWE potential is estimated using realistic AWE system specifications and assumptions about deployment scenarios and is compared with the near-surface wind generation potential with respect to diurnal and seasonal variability. The results show the potential utility of AWE in areas in the Middle East where the energy demand is high. In particular, Oman and Saudi Arabia have a high level of the potential power generation with low annual variability.

  2. Reliability benefits of dispersed wind resource development

    International Nuclear Information System (INIS)

    Milligan, M.; Artig, R.

    1998-05-01

    Generating capacity that is available during the utility peak period is worth more than off-peak capacity. Wind power from a single location might not be available during enough of the peak period to provide sufficient value. However, if the wind power plant is developed over geographically disperse locations, the timing and availability of wind power from these multiple sources could provide a better match with the utility's peak load than a single site. There are other issues that arise when considering disperse wind plant development. Singular development can result in economies of scale and might reduce the costs of obtaining multiple permits and multiple interconnections. However, disperse development can result in cost efficiencies if interconnection can be accomplished at lower voltages or at locations closer to load centers. Several wind plants are in various stages of planning or development in the US. Although some of these are small-scale demonstration projects, significant wind capacity has been developed in Minnesota, with additional developments planned in Wyoming, Iowa and Texas. As these and other projects are planned and developed, there is a need to perform analysis of the value of geographically disperse sites on the reliability of the overall wind plant.This paper uses a production-cost/reliability model to analyze the reliability of several wind sites in the state of Minnesota. The analysis finds that the use of a model with traditional reliability measures does not produce consistent, robust results. An approach based on fuzzy set theory is applied in this paper, with improved results. Using such a model, the authors find that system reliability can be optimized with a mix of disperse wind sites

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2012-08-01

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

  4. Applicability of Synthetic Aperture Radar Wind Retrievals on Offshore Wind Resources Assessment in Hangzhou Bay, China

    Directory of Open Access Journals (Sweden)

    Rui Chang

    2014-05-01

    Full Text Available In view of the high cost and sparse spatial resolution of offshore meteorological observations, ocean winds retrieved from satellites are valuable in offshore wind resource assessment as a supplement to in situ measurements. This study examines satellite synthetic aperture radar (SAR images from ENVISAT advanced SAR (ASAR for mapping wind resources with high spatial resolution. Around 181 collected pairs of wind data from SAR wind maps and from 13 meteorological stations in Hangzhou Bay are compared. The statistical results comparing in situ wind speed and SAR-based wind speed show a standard deviation (SD of 1.99 m/s and correlation coefficient of R = 0.67. The model wind directions, which are used as input for the SAR wind speed retrieval, show a high correlation coefficient (R = 0.89 but a large standard deviation (SD = 42.3° compared to in situ observations. The Weibull probability density functions are compared at one meteorological station. The SAR-based results appear not to estimate the mean wind speed, Weibull scale and shape parameters and wind power density from the full in situ data set so well due to the lower number of satellite samples. Distributions calculated from the concurrent 81 SAR and in situ samples agree well.

  5. Preliminary results of Aruba wind resource assessment

    Energy Technology Data Exchange (ETDEWEB)

    Guda, M.H. [Fundashon Antiyano Pa Energia, Curacao (Netherlands Antilles)

    1996-12-31

    As part of a project to assess the possibilities for wind energy utilitization in the Dutch Antilles islands, windspeed and -direction data were collected in Aruba for two years, from March 1992 to February 1994. Five sites that were estimated to be representative for the islands` wind regimes, were monitored during this period: two sites on the windward coast, one east and one west; two inland sites, again one east and one west, and one site topping the cliffs overlooking the eastern windward coast. Additionally, twenty years worth of data were analyzed for the reference site at the airport, which is in the middle part of the island, on the leeward coast. Correlation calculations between these data and the data for the project sites were performed, in order to establish a methodology for estimating the long-term behavior of the wind regimes at these sites. 8 figs., 3 tabs.

  6. Estimating near-shore wind resources

    DEFF Research Database (Denmark)

    Floors, Rogier Ralph; Hahmann, Andrea N.; Peña, Alfredo

    An evaluation and sensitivity study using the WRF mesoscale model to estimate the wind in a coastal area is performed using a unique data set consisting of scanning, profiling and floating lidars. The ability of the WRF model to represent the wind speed was evaluated by running the model for a four...... RMSE and correlation coefficient. Using a finer grid spacing of 1 and 0.5 km did not give better results and sensitivity to the input of different SST and land cover data in the RUNE area was small. The difference in mean wind speed between all simulations over a region 80 km around the RUNE area were...... month period in twelve different set-ups. The atmospheric boundary layer was parametrized using the first-order YSU scheme and the 1.5-order MYJ scheme. Simulations with two sources of land use data, two sources of reanalysis data, two sources of sea-surface temperatures and three different horizontal...

  7. NWTC Helps Chart the World's Wind Resource Potential

    Energy Technology Data Exchange (ETDEWEB)

    2015-09-01

    Researchers at the National Renewable Energy Laboratory's (NREL's) National Wind Technology Center (NWTC) provide the wind industry, policymakers, and other stakeholders with applied wind resource data, information, maps, and technical assistance. These tools, which emphasize wind resources at ever-increasing heights, help stakeholders evaluate the wind resource and development potential for a specific area.

  8. Wind speed prediction using statistical regression and neural network

    Indian Academy of Sciences (India)

    Prediction of wind speed in the atmospheric boundary layer is important for wind energy assess- ment,satellite launching and aviation,etc.There are a few techniques available for wind speed prediction,which require a minimum number of input parameters.Four different statistical techniques,viz.,curve fitting,Auto Regressive ...

  9. Improved Offshore Wind Resource Assessment in Global Climate Stabilization Scenarios

    Energy Technology Data Exchange (ETDEWEB)

    Arent, D.; Sullivan, P.; Heimiller, D.; Lopez, A.; Eurek, K.; Badger, J.; Jorgensen, H. E.; Kelly, M.; Clarke, L.; Luckow, P.

    2012-10-01

    This paper introduces a technique for digesting geospatial wind-speed data into areally defined -- country-level, in this case -- wind resource supply curves. We combined gridded wind-vector data for ocean areas with bathymetry maps, country exclusive economic zones, wind turbine power curves, and other datasets and relevant parameters to build supply curves that estimate a country's offshore wind resource defined by resource quality, depth, and distance-from-shore. We include a single set of supply curves -- for a particular assumption set -- and study some implications of including it in a global energy model. We also discuss the importance of downscaling gridded wind vector data to capturing the full resource potential, especially over land areas with complex terrain. This paper includes motivation and background for a statistical downscaling methodology to account for terrain effects with a low computational burden. Finally, we use this forum to sketch a framework for building synthetic electric networks to estimate transmission accessibility of renewable resource sites in remote areas.

  10. Dst Prediction Based on Solar Wind Parameters

    Directory of Open Access Journals (Sweden)

    Yoon-Kyung Park

    2009-12-01

    Full Text Available We reevaluate the Burton equation (Burton et al. 1975 of predicting Dst index using high quality hourly solar wind data supplied by the ACE satellite for the period from 1998 to 2006. Sixty magnetic storms with monotonously decreasing main phase are selected. In order to determine the injection term (Q and the decay time (tau of the equation, we examine the relationships between Dst* and VB_s, Delta Dst* and VB_s, and Delta Dst* and Dst* during the magnetic storms. For this analysis, we take into account one hour of the propagation time from the ACE satellite to the magnetopause, and a half hour of the response time of the magnetosphere/ring current to the solar wind forcing. The injection term is found to be Q({nT}/h=-3.56VB_s for VB_s>0.5mV/m and Q({nT}/h=0 for VB_s leq0.5mV/m. The tau (hour is estimated as 0.060 Dst* + 16.65 for Dst*>-175nT and 6.15 hours for Dst* leq -175nT. Based on these empirical relationships, we predict the 60 magnetic storms and find that the correlation coefficient between the observed and predicted Dst* is 0.88. To evaluate the performance of our prediction scheme, the 60 magnetic storms are predicted again using the models by Burton et al. (1975 and O'Brien & McPherron (2000a. The correlation coefficients thus obtained are 0.85, the same value for both of the two models. In this respect, our model is slightly improved over the other two models as far as the correlation coefficients is concerned. Particularly our model does a better job than the other two models in predicting intense magnetic storms (Dst* lesssim -200nT.

  11. Enhanced wind turbine noise prediction tool SILANT

    International Nuclear Information System (INIS)

    Boorsma, K.; Schepers, J.G.

    2012-02-01

    Wind turbine noise often is quantified in terms of time averaged overall sound power levels, whilst annoyance due to noise level fluctuations in mid- to high-range frequencies ('swish') are not taken into account. Recent experimental research on wind turbine noise has revealed the major causes of the swishing noise to be due to the directivity of the noise sources and convective amplification effects of the moving turbine blades. The findings have been incorporated in the noise prediction tool SILANT which in addition to sound power levels gives sound pressure level predictions for specified observer positions. The noise sources that are taken into account are trailing edge, inflow and tip noise, using the models of Brooks, Pope and Marcolini (BPM) and Amiet and Lowson. The blade is divided into a number of independent elements for which effective inflow velocity and angle of attack information is a necessary input. A distinction is made between the various profiles along the blade span by including their boundary layer displacement thicknesses at the trailing edge in a profile database. The propagation model includes directivity, convective amplification, Doppler shift and atmospheric absorption. The effect of the retarded time is taken into account individually for the separate elements along the blade span using the time dependent rotor azimuth position. A simple empirical model is applied to quantify meteorological effects influencing refraction and ground effects. Prediction results are compared to SIROCCO project measurements from microphones positioned in a circle around a turbine. The high spatial and temporal resolution of the SILANT simulations gives new insights in the variation of wind turbine inflow and trailing edge noise as a function of observer position, rotor azimuth angle and frequency band. The influence of directivity is illustrated for the dominant noise sources.

  12. Wind resource assessment: San Nicolas Island, California

    Energy Technology Data Exchange (ETDEWEB)

    McKenna, E. [National Renewable Energy Lab., Golden, CO (United States); Olsen, T.L. [Timothy L. Olsen Consulting, (United States)

    1996-01-01

    San Nicolas Island (SNI) is the site of the Navy Range Instrumentation Test Site which relies on an isolated diesel-powered grid for its energy needs. The island is located in the Pacific Ocean 85 miles southwest of Los Angeles, California and 65 miles south of the Naval Air Weapons Station (NAWS), Point Mugu, California. SNI is situated on the continental shelf at latitude N33{degree}14` and longitude W119{degree}27`. It is approximately 9 miles long and 3.6 miles wide and encompasses an area of 13,370 acres of land owned by the Navy in fee title. Winds on San Nicolas are prevailingly northwest and are strong most of the year. The average wind speed is 7.2 m/s (14 knots) and seasonal variation is small. The windiest months, March through July, have wind speeds averaging 8.2 m/s (16 knots). The least windy months, August through February, have wind speeds averaging 6.2 m/s (12 knots).

  13. Using wind tunnels to predict bird mortality in wind farms: the case of griffon vultures.

    Science.gov (United States)

    de Lucas, Manuela; Ferrer, Miguel; Janss, Guyonne F E

    2012-01-01

    Wind farms have shown a spectacular growth during the last 15 years. Avian mortality through collision with moving rotor blades is well-known as one of the main adverse impacts of wind farms. In Spain, the griffon vulture incurs the highest mortality rates in wind farms. As far as we know, this study is the first attempt to predict flight trajectories of birds in order to foresee potentially dangerous areas for wind farm development. We analyse topography and wind flows in relation to flight paths of griffon vultures, using a scaled model of the wind farm area in an aerodynamic wind tunnel, and test the difference between the observed flight paths of griffon vultures and the predominant wind flows. Different wind currents for each wind direction in the aerodynamic model were observed. Simulations of wind flows in a wind tunnel were compared with observed flight paths of griffon vultures. No statistical differences were detected between the observed flight trajectories of griffon vultures and the wind passages observed in our wind tunnel model. A significant correlation was found between dead vultures predicted proportion of vultures crossing those cells according to the aerodynamic model. Griffon vulture flight routes matched the predominant wind flows in the area (i.e. they followed the routes where less flight effort was needed). We suggest using these kinds of simulations to predict flight paths over complex terrains can inform the location of wind turbines and thereby reduce soaring bird mortality.

  14. Using wind tunnels to predict bird mortality in wind farms: the case of griffon vultures.

    Directory of Open Access Journals (Sweden)

    Manuela de Lucas

    Full Text Available BACKGROUND: Wind farms have shown a spectacular growth during the last 15 years. Avian mortality through collision with moving rotor blades is well-known as one of the main adverse impacts of wind farms. In Spain, the griffon vulture incurs the highest mortality rates in wind farms. METHODOLOGY/PRINCIPAL FINDINGS: As far as we know, this study is the first attempt to predict flight trajectories of birds in order to foresee potentially dangerous areas for wind farm development. We analyse topography and wind flows in relation to flight paths of griffon vultures, using a scaled model of the wind farm area in an aerodynamic wind tunnel, and test the difference between the observed flight paths of griffon vultures and the predominant wind flows. Different wind currents for each wind direction in the aerodynamic model were observed. Simulations of wind flows in a wind tunnel were compared with observed flight paths of griffon vultures. No statistical differences were detected between the observed flight trajectories of griffon vultures and the wind passages observed in our wind tunnel model. A significant correlation was found between dead vultures predicted proportion of vultures crossing those cells according to the aerodynamic model. CONCLUSIONS: Griffon vulture flight routes matched the predominant wind flows in the area (i.e. they followed the routes where less flight effort was needed. We suggest using these kinds of simulations to predict flight paths over complex terrains can inform the location of wind turbines and thereby reduce soaring bird mortality.

  15. Extreme wave and wind response predictions

    DEFF Research Database (Denmark)

    Jensen, Jørgen Juncher; Olsen, Anders S.; Mansour, Alaa E.

    2011-01-01

    The aim of the paper is to advocate effective stochastic procedures, based on the First Order Reliability Method (FORM) and Monte Carlo simulations (MCS), for extreme value predictions related to wave and wind-induced loads.Due to the efficient optimization procedures implemented in standard FORM...... codes and the short duration of the time domain simulations needed (typically 60–300s to cover the hydro- and aerodynamic memory effects in the response) the calculation of the mean out-crossing rates of a given response is fast. Thus non-linear effects can be included. Furthermore, the FORM analysis...

  16. Model Predictive Control with Constraints of a Wind Turbine

    DEFF Research Database (Denmark)

    Henriksen, Lars Christian; Poulsen, Niels Kjølstad

    2007-01-01

    Model predictive control of wind turbines offer a more systematic approach of constructing controllers that handle constraints while focusing on the main control objective. In this article several controllers are designed for different wind conditions and appropriate switching conditions ensure...... an efficient control of the wind turbine over the entire range of wind speeds. Both onshore and floating offshore wind turbines are tested with the controllers....

  17. Prediction models for wind speed at turbine locations in a wind farm

    DEFF Research Database (Denmark)

    Knudsen, Torben; Bak, Thomas; Soltani, Mohsen

    2011-01-01

    turbulence models. The esti- mator includes a nonlinear time varying wind speed model, which compared with literature results in an adaptive filter. Given the estimated effective wind speed, it is possible to establish wind speed prediction models by system identification. As the prediction models are based...... manifested through the wind field is hence required. This paper develops models for this relationship. The result is based on two new contributions: the first is related to the estimation of effective wind speeds, which serves as a basis for the second contribution to wind speed prediction models. Based...... on standard turbine measurements such as rotor speed and power produced, an effective wind speed, which represents the wind field averaged over the rotor disc, is derived. The effective wind speed estimator is based on a continuous–discrete extended Kalman filter that takes advantage of nonlinear time varying...

  18. Wind Tunnel Management and Resource Optimization: A Systems Modeling Approach

    Science.gov (United States)

    Jacobs, Derya, A.; Aasen, Curtis A.

    2000-01-01

    Time, money, and, personnel are becoming increasingly scarce resources within government agencies due to a reduction in funding and the desire to demonstrate responsible economic efficiency. The ability of an organization to plan and schedule resources effectively can provide the necessary leverage to improve productivity, provide continuous support to all projects, and insure flexibility in a rapidly changing environment. Without adequate internal controls the organization is forced to rely on external support, waste precious resources, and risk an inefficient response to change. Management systems must be developed and applied that strive to maximize the utility of existing resources in order to achieve the goal of "faster, cheaper, better". An area of concern within NASA Langley Research Center was the scheduling, planning, and resource management of the Wind Tunnel Enterprise operations. Nine wind tunnels make up the Enterprise. Prior to this research, these wind tunnel groups did not employ a rigorous or standardized management planning system. In addition, each wind tunnel unit operated from a position of autonomy, with little coordination of clients, resources, or project control. For operating and planning purposes, each wind tunnel operating unit must balance inputs from a variety of sources. Although each unit is managed by individual Facility Operations groups, other stakeholders influence wind tunnel operations. These groups include, for example, the various researchers and clients who use the facility, the Facility System Engineering Division (FSED) tasked with wind tunnel repair and upgrade, the Langley Research Center (LaRC) Fabrication (FAB) group which fabricates repair parts and provides test model upkeep, the NASA and LARC Strategic Plans, and unscheduled use of the facilities by important clients. Expanding these influences horizontally through nine wind tunnel operations and vertically along the NASA management structure greatly increases the

  19. Kaneohe, Hawaii Wind Resource Assessment Report

    Energy Technology Data Exchange (ETDEWEB)

    Robichaud, R.; Green, J.; Meadows, B.

    2011-11-01

    The Department of Energy (DOE) has an interagency agreement to assist the Department of Defense (DOD) in evaluating the potential to use wind energy for power at residential properties at DOD bases in Hawaii. DOE assigned the National Renewable Energy Laboratory (NREL) to facilitate this process by installing a 50-meter (m) meteorological (Met) tower on residential property associated with the Marine Corps Base Housing (MCBH) Kaneohe Bay in Hawaii.

  20. Wind Resource Mapping Using Landscape Roughness and Spatial Interpolation Methods

    Directory of Open Access Journals (Sweden)

    Samuel Van Ackere

    2015-08-01

    Full Text Available Energy saving, reduction of greenhouse gasses and increased use of renewables are key policies to achieve the European 2020 targets. In particular, distributed renewable energy sources, integrated with spatial planning, require novel methods to optimise supply and demand. In contrast with large scale wind turbines, small and medium wind turbines (SMWTs have a less extensive impact on the use of space and the power system, nevertheless, a significant spatial footprint is still present and the need for good spatial planning is a necessity. To optimise the location of SMWTs, detailed knowledge of the spatial distribution of the average wind speed is essential, hence, in this article, wind measurements and roughness maps were used to create a reliable annual mean wind speed map of Flanders at 10 m above the Earth’s surface. Via roughness transformation, the surface wind speed measurements were converted into meso- and macroscale wind data. The data were further processed by using seven different spatial interpolation methods in order to develop regional wind resource maps. Based on statistical analysis, it was found that the transformation into mesoscale wind, in combination with Simple Kriging, was the most adequate method to create reliable maps for decision-making on optimal production sites for SMWTs in Flanders (Belgium.

  1. Development and Validation of High-Resolution State Wind Resource Maps for the United States

    Energy Technology Data Exchange (ETDEWEB)

    Elliott, D.; Schwartz, M.

    2005-07-01

    The National Renewable Energy Laboratory (NREL) has coordinated the development and validation of high-resolution state wind resource maps for much of the United States. The majority of these maps were produced for NREL by TrueWind Solutions (now AWS Truewind [AWST]) based in Albany, New York, using its proprietary MesoMap system. AWST's system uses a version of a numerical mesoscale weather prediction model as the basis for calculating the wind resource and important wind flow characteristics. The independent validation project was a cooperative activity among NREL, AWST, and private meteorological consultants. This paper describes the mapping and validation approach and results and discusses the technical modeling issues encountered during the project.

  2. Potential for Development of Solar and Wind Resource in Bhutan

    Energy Technology Data Exchange (ETDEWEB)

    Gilman, P.; Cowlin, S.; Heimiller, D.

    2009-09-01

    With support from the U.S. Agency for International Development (USAID), the U.S. Department of Energy's National Renewable Energy Laboratory (NREL) produced maps and data of the wind and solar resources in Bhutan. The solar resource data show that Bhutan has an adequate resource for flat-plate collectors, with annual average values of global horizontal solar radiation ranging from 4.0 to 5.5 kWh/m2-day (4.0 to 5.5 peak sun hours per day). The information provided in this report may be of use to energy planners in Bhutan involved in developing energy policy or planning wind and solar projects, and to energy analysts around the world interested in gaining an understanding of Bhutan's wind and solar energy potential.

  3. Modelling of a CFD Microscale Model and Its Application in Wind Energy Resource Assessment

    Directory of Open Access Journals (Sweden)

    Yue Jie-shun

    2016-01-01

    Full Text Available The prediction of a wind farm near the wind turbines has a significant effect on the safety as well as economy of wind power generation. To assess the wind resource distribution within a complex terrain, a computational fluid dynamics (CFD based wind farm forecast microscale model is developed. The model uses the Reynolds Averaged Navier-Stokes (RANS model to characterize the turbulence. By using the results of Weather Research and Forecasting (WRF mesoscale weather forecast model as the input of the CFD model, a coupled model of CFD-WRF is established. A special method is used for the treatment of the information interchange on the lateral boundary between two models. This established coupled model is applied in predicting the wind farm near a wind turbine in Hong Gang-zi, Jilin, China. The results from this simulation are compared to real measured data. On this basis, the accuracy and efficiency of turbulence characterization schemes are discussed. It indicates that this coupling system is easy to implement and can make these two separate models work in parallel. The CFD model coupled with WRF has the advantage of high accuracy and fast speed, which makes it valid for the wind power generation.

  4. Vulnerability of wind power resources to climate change in the continental United States

    International Nuclear Information System (INIS)

    Breslow, Paul B.; Sailor, David J.

    2002-01-01

    Renewable energy resources will play a key role in meeting the world's energy demand over the coming decades. Unfortunately, these resources are all susceptible to variations in climate, and hence vulnerable to climate change. Recent findings in the atmospheric science literature suggest that the impacts of greenhouse gas induced warming are likely to significantly alter climate patterns in the future. In this paper we investigate the potential impacts of climate change on wind speeds and hence on wind power, across the continental US. General Circulation Model output from the Canadian Climate Center and the Hadley Center were used to provide a range of possible variations in seasonal mean wind magnitude. These projections were used to investigate the vulnerability of current and potential wind power generation regions. The models were generally consistent in predicting that the US will see reduced wind speeds of 1.0 to 3.2% in the next 50 years, and 1.4 to 4.5% over the next 100 years. In both cases the Canadian model predicted larger decreases in wind speeds. At regional scales the two models showed some similarities in early years of simulations (e.g. 2050), but diverged significantly in their predictions for 2100. Hence, there is still a great deal of uncertainty regarding how wind fields will change in the future. Nevertheless, the two models investigated here are used as possible scenarios for use in investigating regional wind power vulnerabilities, and point to the need to consider climate variability and long term climate change in citing wind power facilities. (Author)

  5. Avian use of Norris Hill Wind Resource Area, Montana

    Energy Technology Data Exchange (ETDEWEB)

    Harmata, A.; Podruzny, K.; Zelenak, J. [Montana State Univ., Bozeman, MT (United States). Biology Dept.

    1998-07-01

    This document presents results of a study of avian use and mortality in and near a proposed wind resource area in southwestern Montana. Data collected in autumn 1995 through summer 1996 represented preconstruction condition; it was compiled, analyzed, and presented in a format such that comparison with post-construction data would be possible. The primary emphasis of the study was recording avian migration in and near the wind resource area using state-of-the-art marine surveillance radar. Avian use and mortality were investigated during the breeding season by employing traditional avian sampling methods, radiotelemetry, radar, and direct visual observation. 61 figs., 34 tabs.

  6. Wind speed prediction using statistical regression and neural network

    Indian Academy of Sciences (India)

    Four different statistical techniques,viz.,curve fitting,Auto Regressive Integrated Moving Average Model (ARIMA),extrapolation with periodic function and Artificial Neural Networks (ANN)are employed to predict wind speed.These methods require wind speeds of previous hours as input.It has been found that wind speed can ...

  7. Estimation of wind and solar resources in Mali

    Energy Technology Data Exchange (ETDEWEB)

    Badger, J.; Kamissoko, F.; Olander Rasmussen, M.; Larsen, Soeren; Guidon, N.; Boye Hansen, L.; Dewilde, L.; Alhousseini, M.; Noergaard, P.; Nygaard, I.

    2012-11-15

    The wind resource has been estimated for all of Mali at 7.5 km resolution using the KAMM/WAsP numerical wind atlas methodology. Three domains were used to cover entire country and three sets of wind classes used to capture change in large scale forcing over country. The final output includes generalized climate statistics for any location in Mali, giving wind direction and wind speed distribution. The modelled generalized climate statistics can be used directly in the WAsP software. The preliminary results show a wind resource, which is relatively low, but which under certain conditions may be economically feasible, i.e. at favourably exposed sites, giving enhanced winds, and where practical utilization is possible, given consideration to grid connection or replacement or augmentation of diesel-based electricity systems. The solar energy resource for Mali was assessed for the period between July 2008 and June 2011 using a remote sensing based estimate of the down-welling surface shortwave flux. The remote sensing estimates were adjusted on a month-by-month basis to account for seasonal differences between the remote sensing estimates and in situ data. Calibration was found to improve the coefficient of determination as well as decreasing the mean error both for the calibration and validation data. Compared to the results presented in the ''Renewable energy resources in Mali - preliminary mapping''-report that showed a tendency for underestimation compared to data from the NASA PPOWER/SSE database, the presented results show a very good agreement with the in situ data (after calibration) with no significant bias. Unfortunately, the NASA-database only contains data up until 2005, so a similar comparison could not be done for the time period analyzed in this study, although the agreement with the historic NASA data is still useful as reference. (LN)

  8. Wind assessment and power prediction from a wind farm in southern Saskatchewan

    Science.gov (United States)

    Chakravarthy, Mukundhan

    Mesoscale and Microscale Modeling are two methods used to estimate wind energy resources. The main parameters of wind resource estimation are the mean wind speed and the mean wind power density. Mesoscale Modeling was applied to three different regions, Regina, Saskatoon, and Gull Lake, located in southern Saskatchewan, Canada. The areas were selected as centers of a domain for a grid with a horizontal resolution of 3 kilometers. Mesoscale Modeling was performed using the software tool, Anemoscope. Wind resources for the regions and the areas surrounding them have been generated for three elevations (30, 50, and 80 meters). As it is a site for a large wind turbine farm, the region in and around Swift Current in southern Saskatchewan (approximately 36 km x 36 km in area) was the site of choice for this study in Microscale Modeling. A widely popular software, WAsP, was chosen to perform the study. Statistical wind data was obtained from a Swift Current meteorological station over a period of ten years (2000-2009). A wind resource grid has been set up for the area at a horizontal resolution of 200 meters, and wind resource maps have been generated for heights of 50, 65, and 80 meters above ground level as the heights are the potential wind turbine hub heights. In order to simulate the SaskPower Centennial Wind Power Station, a wind farm was set up with 83 wind turbines in the Coulee Municipality region near Swift Current. The annual energy production for the entire farm, along with those of the individual turbines, has been calculated. Both total and individual wind turbine productions were accurately modeled.

  9. Model Predictive Control of Wind Turbines using Uncertain LIDAR Measurements

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood; Soltani, Mohsen; Poulsen, Niels Kjølstad

    2013-01-01

    The problem of Model predictive control (MPC) of wind turbines using uncertain LIDAR (LIght Detection And Ranging) measurements is considered. A nonlinear dynamical model of the wind turbine is obtained. We linearize the obtained nonlinear model for different operating points, which are determined......, we simplify state prediction for the MPC. Consequently, the control problem of the nonlinear system is simplified into a quadratic programming. We consider uncertainty in the wind propagation time, which is the traveling time of wind from the LIDAR measurement point to the rotor. An algorithm based...... by the effective wind speed on the rotor disc. We take the wind speed as a scheduling variable. The wind speed is measurable ahead of the turbine using LIDARs, therefore, the scheduling variable is known for the entire prediction horizon. By taking the advantage of having future values of the scheduling variable...

  10. Robust Kalman filter design for predictive wind shear detection

    Science.gov (United States)

    Stratton, Alexander D.; Stengel, Robert F.

    1991-01-01

    Severe, low-altitude wind shear is a threat to aviation safety. Airborne sensors under development measure the radial component of wind along a line directly in front of an aircraft. In this paper, optimal estimation theory is used to define a detection algorithm to warn of hazardous wind shear from these sensors. To achieve robustness, a wind shear detection algorithm must distinguish threatening wind shear from less hazardous gustiness, despite variations in wind shear structure. This paper presents statistical analysis methods to refine wind shear detection algorithm robustness. Computational methods predict the ability to warn of severe wind shear and avoid false warning. Comparative capability of the detection algorithm as a function of its design parameters is determined, identifying designs that provide robust detection of severe wind shear.

  11. A new measure-correlate-predict approach for resource assessment

    Energy Technology Data Exchange (ETDEWEB)

    Joensen, A.; Landberg, L. [Risoe National Lab., Dept. of Wind Energy and Atmospheric Physics, Roskilde (Denmark); Madsen, H. [The Technical Univ. of Denmark, Dept. of Mathematical Modelling, Lyngby (Denmark)

    1999-03-01

    In order to find reasonable candidate site for wind farms, it is of great importance to be able to calculate the wind resource at potential sites. One way to solve this problem is to measure wind speed and direction at the site, and use these measurements to predict the resource. If the measurements at the potential site cover less than e.g. one year, which most likely will be the case, it is not possible to get a reliable estimate of the long-term resource, using this approach. If long-term measurements from e.g. some nearby meteorological station are available, however, then statistical methods can be used to find a relation between the measurements at the site and at the meteorological station. This relation can then be used to transform the long-term measurements to the potential site, and the resource can be calculated using the transformed measurements. Here, a varying-coefficient model, estimated using local regression, is applied in order to establish a relation between the measurements. The approach is evaluated using measurements from two sites, located approximately two kilometres apart, and the results show that the resource in this case can be predicted accurately, although this approach has serious shortcomings. (au)

  12. Model Predictive Control of Wind Turbines

    DEFF Research Database (Denmark)

    Henriksen, Lars Christian

    Wind turbines play a major role in the transformation from a fossil fuel based energy production to a more sustainable production of energy. Total-cost-of-ownership is an important parameter when investors decide in which energy technology they should place their capital. Modern wind turbines...... are controlled by pitching the blades and by controlling the electro-magnetic torque of the generator, thus slowing the rotation of the blades. Improved control of wind turbines, leading to reduced fatigue loads, can be exploited by using less materials in the construction of the wind turbine or by reducing...... the need for maintenance of the wind turbine. Either way, better total-cost-of-ownership for wind turbine operators can be achieved by improved control of the wind turbines. Wind turbine control can be improved in two ways, by improving the model on which the controller bases its design or by improving...

  13. Skill forecasting from ensemble predictions of wind power

    DEFF Research Database (Denmark)

    Pinson, Pierre; Nielsen, Henrik Aalborg; Madsen, Henrik

    2009-01-01

    Optimal management and trading of wind generation calls for the providing of uncertainty estimates along with the commonly provided short-term wind power point predictions. Alternative approaches for the use of probabilistic forecasting are introduced. More precisely, focus is given to prediction...... risk indices aiming to give a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the spread of ensemble forecasts (i.e. a set...... of alternative scenarios for the coming period) for a single prediction horizon or over a took-ahead period. It is shown on the test case of a Danish offshore wind farm how these prediction risk indices may be related to several levels of forecast uncertainty (and potential energy imbalances). Wind power...

  14. Water resources assessment and prediction in China

    Directory of Open Access Journals (Sweden)

    W. Guangsheng

    2016-10-01

    Full Text Available Water resources assessment in China, can be classified into three groups: (i comprehensive water resources assessment, (ii annual water resources assessment, and (iii industrial project water resources assessment. Comprehensive water resources assessment is the conventional assessment where the frequency distribution of water resources in basins or provincial regions are analyzed. For the annual water resources assessment, water resources of the last year in basins or provincial regions are usually assessed. For the industrial project water resources assessment, the water resources situation before the construction of industrial project has to be assessed. To address the climate and environmental changes, hydrological and statistical models are widely applied for studies on assessing water resources changes. For the water resources prediction in China usually the monthly runoff prediction is used. In most low flow seasons, the flow recession curve is commonly used as prediction method. In the humid regions, the rainfall-runoff ensemble prediction (ESP has been widely applied for the monthly runoff prediction. The conditional probability method for the monthly runoff prediction was also applied to assess next month runoff probability under a fixed initial condition.

  15. Multidimensional optimal droop control for wind resources in DC microgrids

    Science.gov (United States)

    Bunker, Kaitlyn J.

    Two important and upcoming technologies, microgrids and electricity generation from wind resources, are increasingly being combined. Various control strategies can be implemented, and droop control provides a simple option without requiring communication between microgrid components. Eliminating the single source of potential failure around the communication system is especially important in remote, islanded microgrids, which are considered in this work. However, traditional droop control does not allow the microgrid to utilize much of the power available from the wind. This dissertation presents a novel droop control strategy, which implements a droop surface in higher dimension than the traditional strategy. The droop control relationship then depends on two variables: the dc microgrid bus voltage, and the wind speed at the current time. An approach for optimizing this droop control surface in order to meet a given objective, for example utilizing all of the power available from a wind resource, is proposed and demonstrated. Various cases are used to test the proposed optimal high dimension droop control method, and demonstrate its function. First, the use of linear multidimensional droop control without optimization is demonstrated through simulation. Next, an optimal high dimension droop control surface is implemented with a simple dc microgrid containing two sources and one load. Various cases for changing load and wind speed are investigated using simulation and hardware-in-the-loop techniques. Optimal multidimensional droop control is demonstrated with a wind resource in a full dc microgrid example, containing an energy storage device as well as multiple sources and loads. Finally, the optimal high dimension droop control method is applied with a solar resource, and using a load model developed for a military patrol base application. The operation of the proposed control is again investigated using simulation and hardware-in-the-loop techniques.

  16. Wind Power Prediction Based on LS-SVM Model with Error Correction

    Directory of Open Access Journals (Sweden)

    ZHANG, Y.

    2017-02-01

    Full Text Available As conventional energy sources are non-renewable, the world's major countries are investing heavily in renewable energy research. Wind power represents the development trend of future energy, but the intermittent and volatility of wind energy are the main reasons that leads to the poor accuracy of wind power prediction. However, by analyzing the error level at different time points, it can be found that the errors of adjacent time are often approximately the same, the least square support vector machine (LS-SVM model with error correction is used to predict the wind power in this paper. According to the simulation of wind power data of two wind farms, the proposed method can effectively improve the prediction accuracy of wind power, and the error distribution is concentrated almost without deviation. The improved method proposed in this paper takes into account the error correction process of the model, which improved the prediction accuracy of the traditional model (RBF, Elman, LS-SVM. Compared with the single LS-SVM prediction model in this paper, the mean absolute error of the proposed method had decreased by 52 percent. The research work in this paper will be helpful to the reasonable arrangement of dispatching operation plan, the normal operation of the wind farm and the large-scale development as well as fully utilization of renewable energy resources.

  17. Frequency weighted model predictive control of wind turbine

    DEFF Research Database (Denmark)

    Klauco, Martin; Poulsen, Niels Kjølstad; Mirzaei, Mahmood

    2013-01-01

    This work is focused on applying frequency weighted model predictive control (FMPC) on three blade horizontal axis wind turbine (HAWT). A wind turbine is a very complex, non-linear system influenced by a stochastic wind speed variation. The reduced dynamics considered in this work...... are the rotational degree of freedom of the rotor and the tower for-aft movement. The MPC design is based on a receding horizon policy and a linearised model of the wind turbine. Due to the change of dynamics according to wind speed, several linearisation points must be considered and the control design adjusted...... accordingly. In practice is very hard to measure the effective wind speed, this quantity will be estimated using measurements from the turbine itself. For this purpose stationary predictive Kalman filter has been used. Stochastic simulations of the wind turbine behaviour with applied frequency weighted model...

  18. Errors in wind resource and energy yield assessments based on the Weibull distribution

    Science.gov (United States)

    Jourdier, Bénédicte; Drobinski, Philippe

    2017-05-01

    The methodology used in wind resource assessments often relies on modeling the wind-speed statistics using a Weibull distribution. In spite of its common use, this distribution has been shown to not always accurately model real wind-speed distributions. Very few studies have examined the arising errors in power outputs, using either observed power productions or theoretical power curves. This article focuses on France, using surface wind measurements at 89 locations covering all regions of the country. It investigates how statistical modeling using a Weibull distribution impacts the prediction of the wind energy content and of the power output in the context of an annual energy production assessment. For this purpose it uses a plausible power curve adapted to each location. Three common methods for fitting the Weibull distribution are tested (maximum likelihood, first and third moments, and the Wind Atlas Analysis and Application Program (WAsP) method). The first two methods generate large errors in the production (mean absolute error around 5 %), especially in the southern areas where the goodness of fit of the Weibull distribution is poorer. The production is mainly overestimated except at some locations with bimodal wind distributions. With the third method, the errors are much lower at most locations (mean absolute error around 2 %). Another distribution, a mixed Rayleigh-Rice distribution, is also tested and shows better skill at assessing the wind energy yield.

  19. Enhanced method for multiscale wind simulations over complex terrain for wind resource assessment

    Science.gov (United States)

    Flores-Maradiaga, A.; Benoit, R.; Masson, C.

    2016-09-01

    Due to the natural variability of the wind, it is necessary to conduct thorough wind resource assessments to determine how much energy can be extracted at a given site. Lately, important advancements have been achieved in numerical methods of multiscale models used for high resolution wind simulations over steep topography. As a contribution to this effort, an enhanced numerical method was devised in the mesoscale compressible community (MC2) model of the Meteorological Service of Canada, adapting a new semi-implicit scheme with its imbedded large-eddy simulation (LES) capability for mountainous terrain. This implementation has been verified by simulating the neutrally stratified atmospheric boundary layer (ABL) over flat terrain and a Gaussian ridge. These preliminary results indicate that the enhanced MC2-LES model reproduces efficiently the results reported by other researchers who use similar models with more sophisticated sub-grid scale turbulence schemes. The proposed multiscale method also provides a new wind initialization scheme and additional utilities to improve numerical accuracy and stability. The resulting model can be used to assess the wind resource at meso- and micro-scales, reducing significantly the wind speed overestimation in mountainous areas.

  20. Model predictive control for wind power gradients

    DEFF Research Database (Denmark)

    Hovgaard, Tobias Gybel; Boyd, Stephen; Jørgensen, John Bagterp

    2015-01-01

    We consider the operation of a wind turbine and a connected local battery or other electrical storage device, taking into account varying wind speed, with the goal of maximizing the total energy generated while respecting limits on the time derivative (gradient) of power delivered to the grid. We...... wind data and modern wind forecasting methods. The simulation results using real wind data demonstrate the ability to reject the disturbances from fast changes in wind speed, ensuring certain power gradients, with an insignificant loss in energy production....... ranges. The system dynamics are quite non-linear, and the constraints and objectives are not convex functions of the control inputs, so the resulting optimal control problem is difficult to solve globally. In this paper, we show that by a novel change of variables, which focuses on power flows, we can...

  1. A Novel Sampling Method for Satellite-Based Offshore Wind Resource Estimation

    DEFF Research Database (Denmark)

    Badger, Merete; Badger, Jake; Hasager, Charlotte Bay

    of wind resources. The method is applied within a wind and solar resource assessment study for the United Arab Emirates funded by MASDAR and coordinated by UNEP. Thirty years of NCEP/NCAR reanalysis data are used to define approximately 100 geostrophic wind classes. These wind classes show...

  2. Wind prediction in Malaysia using Mycielski-1 approach

    Science.gov (United States)

    Lee, S. W.; Kok, B. C.; Goh, K. C.; Goh, H. H.

    2012-11-01

    In this paper, the wind speed prediction in Kudat, Malaysia had been done by using Mycielski-1 approach. There is some improvement in obtaining the random number of Mycielski-1. The wind prediction is important to study a favorable site's wind potential. The prediction is based on 3 years history data provided by Meteorology Department of Malaysia and 1 year data as the reference to check the accuracy of this algorithm. The basic concept of this algorithm is to predict the next value by looking to history data. The result shows the prediction of Mycielski-1 algorithm is promising. The wind speed is predicted in order to obtain the mean power for energy planning.

  3. Small scale wind power harnessing in Colombian oil industry facilities: Wind resource and technology issues

    Energy Technology Data Exchange (ETDEWEB)

    Giraldo, Mauricio; Nieto, Cesar; Escudero, Ana C.; Cobos, Juan C.; Delgado, Fernando

    2010-07-01

    Full text: Looking to improve its national and international standing, Colombia's national oil company, Ecopetrol, has set its goal on becoming involved on the production of energy from multiple sources, most importantly, on having an important percentage of its installed capacity from renewable sources. Part of this effort entices the evaluation of wind power potential on its facilities, including production, transportation and administrative, as well as identifying those technologies most suitable for the specific conditions of an equatorial country such as Colombia. Due to the lack of adequate site information, the first step consisted in superimposing national data to the facilities map of the company; this allowed for the selection of the first set of potential sites. From this set, the terminal at Covenas-Sucre was selected taking into account not only wind resource, but ease of access and power needs, as well as having a more or less representative wind potential in comparison to the rest of the country. A weather station was then installed to monitor wind variables. Measurements taken showed high variations in wind direction, and relatively low velocity profiles, making most commercially available wind turbines difficult to implement. In light of the above, a series of iterative steps were taken, first considering a range of individual Vertical Axis Wind Turbines (VAWT), given their capacity to adapt to changing wind directions. However, wind speed variations proved to be a challenge for individual VAWT's, i.e. Darriues turbines do not work well with low wind speeds, and Savonius turbines are not efficient of high wind speeds. As a result, a combined Darrieus- Savonius VAWT was selected given the capacity to adapt to both wind regimes, while at the same time modifying the size and shape of the blades in order to adapt to the lower average wind speeds present at the site. The resulting prototype is currently under construction and is scheduled to

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

    Energy Technology Data Exchange (ETDEWEB)

    Schwartz, M.; Heimiller, D.; Haymes, S.; Musial, W.

    2010-06-01

    This report summarizes the offshore wind resource potential for the contiguous United States and Hawaii as of May 2009. The development of this assessment has evolved over multiple stages as new regional meso-scale assessments became available, new validation data was obtained, and better modeling capabilities were implemented. It is expected that further updates to the current assessment will be made in future reports.

  5. State of the art on wind resource estimation

    Energy Technology Data Exchange (ETDEWEB)

    Maribo Pedersen, B.

    1998-12-31

    With the increasing number of wind resource estimation studies carried out for regions, countries and even larger areas all over the world, the IEA finds that the time has come to stop and take stock of the various methods used in these studies. The IEA would therefore like to propose an Experts Meeting on wind resource estimation. The Experts Meeting should describe the models and databases used in the various studies. It should shed light on the strengths and shortcomings of the models and answer questions like: where and under what circumstances should a specific model be used? what is the expected accuracy of the estimate of the model? and what is the applicability? When addressing databases the main goal will be to identify the content and scope of these. Further, the quality, availability and reliability of the databases must also be recognised. In the various studies of wind resources the models and databases have been combined in different ways. A final goal of the Experts Meeting is to see whether it is possible to develop systems of methods which would depend on the available input. These systems of methods should be able to address the simple case (level 0) of a region with barely no data, to the complex case of a region with all available measurements: surface observations, radio soundings, satellite observations and so on. The outcome of the meeting should be an inventory of available models as well as databases and a map of already studied regions. (au)

  6. Development and Application of Advanced Weather Prediction Technologies for the Wind Energy Industry (Invited)

    Science.gov (United States)

    Mahoney, W. P.; Wiener, G.; Liu, Y.; Myers, W.; Johnson, D.

    2010-12-01

    Wind energy decision makers are required to make critical judgments on a daily basis with regard to energy generation, distribution, demand, storage, and integration. Accurate knowledge of the present and future state of the atmosphere is vital in making these decisions. As wind energy portfolios expand, this forecast problem is taking on new urgency because wind forecast inaccuracies frequently lead to substantial economic losses and constrain the national expansion of renewable energy. Improved weather prediction and precise spatial analysis of small-scale weather events are crucial for renewable energy management. In early 2009, the National Center for Atmospheric Research (NCAR) began a collaborative project with Xcel Energy Services, Inc. to perform research and develop technologies to improve Xcel Energy's ability to increase the amount of wind energy in their generation portfolio. The agreement and scope of work was designed to provide highly detailed, localized wind energy forecasts to enable Xcel Energy to more efficiently integrate electricity generated from wind into the power grid. The wind prediction technologies are designed to help Xcel Energy operators make critical decisions about powering down traditional coal and natural gas-powered plants when sufficient wind energy is predicted. The wind prediction technologies have been designed to cover Xcel Energy wind resources spanning a region from Wisconsin to New Mexico. The goal of the project is not only to improve Xcel Energy’s wind energy prediction capabilities, but also to make technological advancements in wind and wind energy prediction, expand our knowledge of boundary layer meteorology, and share the results across the renewable energy industry. To generate wind energy forecasts, NCAR is incorporating observations of current atmospheric conditions from a variety of sources including satellites, aircraft, weather radars, ground-based weather stations, wind profilers, and even wind sensors on

  7. Model Predictive Control of Wind Turbines using Uncertain LIDAR Measurements

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood; Soltani, Mohsen; Poulsen, Niels Kjølstad

    2013-01-01

    The problem of Model predictive control (MPC) of wind turbines using uncertain LIDAR (LIght Detection And Ranging) measurements is considered. A nonlinear dynamical model of the wind turbine is obtained. We linearize the obtained nonlinear model for different operating points, which are determined...

  8. Building Chinese wind data for Wind Erosion Prediction System using surrogate US data

    Science.gov (United States)

    Wind erosion is a global problem, especially in arid and semiarid regions of the world, which leads to land degradation and atmosphere pollution. The process-based Wind Erosion Prediction System (WEPS), developed by the USDA, is capable of simulating the windblown soil loss with changing weather and...

  9. A hybrid measure-correlate-predict method for long-term wind condition assessment

    International Nuclear Information System (INIS)

    Zhang, Jie; Chowdhury, Souma; Messac, Achille; Hodge, Bri-Mathias

    2014-01-01

    Highlights: • A hybrid measure-correlate-predict (MCP) methodology with greater accuracy is developed. • Three sets of performance metrics are proposed to evaluate the hybrid MCP method. • Both wind speed and direction are considered in the hybrid MCP method. • The best combination of MCP algorithms is determined. • The developed hybrid MCP method is uniquely helpful for long-term wind resource assessment. - Abstract: This paper develops a hybrid measure-correlate-predict (MCP) strategy to assess long-term wind resource variations at a farm site. The hybrid MCP method uses recorded data from multiple reference stations to estimate long-term wind conditions at a target wind plant site with greater accuracy than is possible with data from a single reference station. The weight of each reference station in the hybrid strategy is determined by the (i) distance and (ii) elevation differences between the target farm site and each reference station. In this case, the wind data is divided into sectors according to the wind direction, and the MCP strategy is implemented for each wind direction sector separately. The applicability of the proposed hybrid strategy is investigated using five MCP methods: (i) the linear regression; (ii) the variance ratio; (iii) the Weibull scale; (iv) the artificial neural networks; and (v) the support vector regression. To implement the hybrid MCP methodology, we use hourly averaged wind data recorded at five stations in the state of Minnesota between 07-01-1996 and 06-30-2004. Three sets of performance metrics are used to evaluate the hybrid MCP method. The first set of metrics analyze the statistical performance, including the mean wind speed, wind speed variance, root mean square error, and mean absolute error. The second set of metrics evaluate the distribution of long-term wind speed; to this end, the Weibull distribution and the Multivariate and Multimodal Wind Distribution models are adopted. The third set of metrics analyze

  10. VT Predicted Mean Wind Speed - 30 meter height

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) Wind speed predictions at 30m are generated by a numerical model that simulates weather conditions over a 15-year period, taking into account...

  11. VT Predicted Mean Wind Power - 50 meter height

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) Wind power predictions at 50m are generated by a numerical model that simulates weather conditions over a 15-year period, taking into account...

  12. VT Predicted Mean Wind Speed - 70 meter height

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) Wind speed predictions at 70m are generated by a numerical model that simulates weather conditions over a 15-year period, taking into account...

  13. Wind Plant Performance Prediction (WP3) Project

    Energy Technology Data Exchange (ETDEWEB)

    Craig, Anna [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

    2018-01-26

    The methods for analysis of operational wind plant data are highly variable across the wind industry, leading to high uncertainties in the validation and bias-correction of preconstruction energy estimation methods. Lack of credibility in the preconstruction energy estimates leads to significant impacts on project financing and therefore the final levelized cost of energy for the plant. In this work, the variation in the evaluation of a wind plant's operational energy production as a result of variations in the processing methods applied to the operational data is examined. Preliminary results indicate that selection of the filters applied to the data and the filter parameters can have significant impacts in the final computed assessment metrics.

  14. Empirical models for predicting wind potential for wind energy applications in rural locations of Nigeria

    Energy Technology Data Exchange (ETDEWEB)

    Odo, F.C. [National Centre for Energy Research and Development, University of Nigeria, Nsukka (Nigeria); Department of Physics and Astronomy, University of Nigeria, Nsukka (Nigeria); Akubue, G.U.; Offiah, S.U.; Ugwuoke, P.E. [National Centre for Energy Research and Development, University of Nigeria, Nsukka (Nigeria)

    2013-07-01

    In this paper, we use the correlation between the average wind speed and ambient temperature to develop models for predicting wind potentials for two Nigerian locations. Assuming that the troposphere is a typical heterogeneous mixture of ideal gases, we find that for the studied locations, wind speed clearly correlates with ambient temperature in a simple polynomial of 3rd degree. The coefficient of determination and root-mean-square error of the models are 0.81; 0.0024 and 0.56; 0.0041, respectively, for Enugu (6.40N; 7.50E) and Owerri (5.50N; 7.00E). These results suggest that the temperature-based model can be used, with acceptable accuracy, in predicting wind potentials needed for preliminary design assessment of wind energy conversion devices for the locations and others with similar meteorological conditions.

  15. Short-term prediction of local wind conditions

    DEFF Research Database (Denmark)

    Landberg, L.

    2001-01-01

    This paper will describe a system which predicts the expected power output of a number of wind farms. The system is automatic and operates on-line. The paper will quantify the accuracy of the predictions and will also give examples of the performance for specific storm events. An actual implement......This paper will describe a system which predicts the expected power output of a number of wind farms. The system is automatic and operates on-line. The paper will quantify the accuracy of the predictions and will also give examples of the performance for specific storm events. An actual...

  16. Validation of wind speed prediction methods at offshore sites

    Science.gov (United States)

    McQueen, Dougal; Watson, Simon

    2006-01-01

    As ever more offshore sites are being investigated for the installation of wind farms, there is a need for accurate estimates of the long-term mean wind speeds at these sites. The cost of installing masts at offshore sites is high compared with onshore sites. In the short term this cost may be difficult to avoid. However, if a developer could get an estimate of the expected long-term mean wind speed at a potential offshore site using available onshore data sets, this could at least inform the choice of site for more advanced monitoring. With this in mind we present the results of using a number of simple standard analyses to infer the wind speed at three UK offshore masts and a mast and lighthouse off the coast of Ireland. Onshore surface wind measurements, upper air measurements, numerical weather prediction model output pressure data on a regular grid, wind speed output from two numerical weather prediction models and reanalysis data are transformed to the sites of interest using relatively simple methods neglecting the effect of topography or a roughness change-induced internal boundary layer and assuming neutral atmospheric stability. The predicted wind speeds are compared with actual measurements at the offshore masts and any discrepancies are assessed and discussed. Copyright

  17. Error analysis of short term wind power prediction models

    International Nuclear Information System (INIS)

    De Giorgi, Maria Grazia; Ficarella, Antonio; Tarantino, Marco

    2011-01-01

    The integration of wind farms in power networks has become an important problem. This is because the electricity produced cannot be preserved because of the high cost of storage and electricity production must follow market demand. Short-long-range wind forecasting over different lengths/periods of time is becoming an important process for the management of wind farms. Time series modelling of wind speeds is based upon the valid assumption that all the causative factors are implicitly accounted for in the sequence of occurrence of the process itself. Hence time series modelling is equivalent to physical modelling. Auto Regressive Moving Average (ARMA) models, which perform a linear mapping between inputs and outputs, and Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS), which perform a non-linear mapping, provide a robust approach to wind power prediction. In this work, these models are developed in order to forecast power production of a wind farm with three wind turbines, using real load data and comparing different time prediction periods. This comparative analysis takes in the first time, various forecasting methods, time horizons and a deep performance analysis focused upon the normalised mean error and the statistical distribution hereof in order to evaluate error distribution within a narrower curve and therefore forecasting methods whereby it is more improbable to make errors in prediction. (author)

  18. Danish-Czech wind resource know-how transfer project. Interim report 2002

    DEFF Research Database (Denmark)

    Rathmann, O.; Nørgård, Per Bromand; Frandsen, Sten Tronæs

    2003-01-01

    The progress of the Danish-Czech Wind Resource Know-how Transfer Project is reported. The know-how transfer component of the project has consisted in performing a wind resource training workshop for about 13 individuals from the Czech Republic, rangingfrom scientists to wind farm project developers...

  19. Wind Energy Resource Assessment on Alaska Native Lands in Cordova Region of Prince William Sound

    Energy Technology Data Exchange (ETDEWEB)

    Whissel, John C. [Native Village of Eyak, Cordova, AK (United States); Piche, Matthew [Native Village of Eyak, Cordova, AK (United States)

    2015-06-29

    The Native Village of Eyak (NVE) has been monitoring wind resources around Cordova, Alaska in order to determine whether there is a role for wind energy to play in the city’s energy scheme, which is now supplies entirely by two run-of-the-river hydro plants and diesel generators. These data are reported in Appendices A and B. Because the hydro resources decline during winter months, and wind resources increase, wind is perhaps an ideal counterpart to round out Cordova’s renewable energy supply. The results of this effort suggests that this is the case, and that developing wind resources makes sense for our small, isolated community.

  20. Decadal predictability of regional scale wind speed and wind energy potentials over Central Europe

    Directory of Open Access Journals (Sweden)

    Julia Moemken

    2016-03-01

    Full Text Available Decadal predictions on timescales from one year to one decade are gaining importance since this time frame falls within the planning horizon of politics, economy and society. The present study examines the decadal predictability of regional wind speed and wind energy potentials in three generations of the MiKlip (‘Mittelfristige Klimaprognosen’ decadal prediction system. The system is based on the global Max-Planck-Institute Earth System Model (MPI-ESM, and the three generations differ primarily in the ocean initialisation. Ensembles of uninitialised historical and yearly initialised hindcast experiments are used to assess the forecast skill for 10 m wind speeds and wind energy output (Eout over Central Europe with lead times from one year to one decade. With this aim, a statistical-dynamical downscaling (SDD approach is used for the regionalisation. Its added value is evaluated by comparison of skill scores for MPI-ESM large-scale wind speeds and SDD-simulated regional wind speeds. All three MPI-ESM ensemble generations show some forecast skill for annual mean wind speed and Eout over Central Europe on yearly and multi-yearly time scales. This forecast skill is mostly limited to the first years after initialisation. Differences between the three ensemble generations are generally small. The regionalisation preserves and sometimes increases the forecast skills of the global runs but results depend on lead time and ensemble generation. Moreover, regionalisation often improves the ensemble spread. Seasonal Eout skills are generally lower than for annual means. Skill scores are lowest during summer and persist longest in autumn. A large-scale westerly weather type with strong pressure gradients over Central Europe is identified as potential source of the skill for wind energy potentials, showing a similar forecast skill and a high correlation with Eout anomalies. These results are promising towards the establishment of a decadal prediction

  1. 76 FR 36532 - Iberdrola Renewables, Inc., PacifiCorp, NextEra Energy Resources, LLC, Invenergy Wind North...

    Science.gov (United States)

    2011-06-22

    ..., Invenergy Wind North America LLC, Horizon Wind Energy LLC v. Bonneville Power Administration; Notice of... Resources, LLC, Invenergy Wind North America LLC, and Horizon Wind Energy LLC (Complainants) filed a formal...

  2. 7 CFR 610.13 - Equations for predicting soil loss due to wind erosion.

    Science.gov (United States)

    2010-01-01

    ... 7 Agriculture 6 2010-01-01 2010-01-01 false Equations for predicting soil loss due to wind erosion... Erosion Prediction Equations § 610.13 Equations for predicting soil loss due to wind erosion. (a) The equation for predicting soil loss due to wind in the Wind Erosion Equation (WEQ) is E = f(IKCLV). (For...

  3. Probabilistic maximum-value wind prediction for offshore environments

    DEFF Research Database (Denmark)

    Staid, Andrea; Pinson, Pierre; Guikema, Seth D.

    2015-01-01

    statistical models to predict the full distribution of the maximum-value wind speeds in a 3 h interval. We take a detailed look at the performance of linear models, generalized additive models and multivariate adaptive regression splines models using meteorological covariates such as gust speed, wind speed......, convective available potential energy, Charnock, mean sea-level pressure and temperature, as given by the European Center for Medium-Range Weather Forecasts forecasts. The models are trained to predict the mean value of maximum wind speed, and the residuals from training the models are used to develop......, and probabilistic forecasts result in greater value to the end-user. The models outperform traditional baseline forecast methods and achieve low predictive errors on the order of 1–2 m s−1. We show the results of their predictive accuracy for different lead times and different training methodologies....

  4. The influence of waves on the offshore wind resource

    Energy Technology Data Exchange (ETDEWEB)

    Lange, B. [Risoe National Lab., Roskilde (Denmark); Hoejstrup, J. [NEG Micon, Randers (Denmark)

    1999-03-01

    With the growing interest in offshore wind resources, it has become increasingly important to establish and refine models for the interaction between wind and waves in order to obtain accurate models for the sea surface roughness. The simple Charnock relation that has been applied for open sea conditions does not work well in the shallow water near-coastal areas that are important for offshore wind energy. A model for the surface roughness of the sea has been developed based on this concept, using an expression for the Charnock constant as a function of wave age, and then relating the wave `age` to the distance to the nearest upwind coastline. The data used in developing these models originated partly from analysis of data from the Vindeby site, partly from previously published results. The scatter in the data material was considerable and consequently there is a need to test these models further by analysing data from sites exhibiting varying distances to the coast. Results from such analysis of recent data are presented for sites with distances to the coast varying from 10 km to several hundreds of km. The model shows a good agreement also with this data. (au)

  5. Wind/hydrogen hybrid systems: opportunity for Ireland’s wind resource to provide consistent sustainable energy supply

    OpenAIRE

    Carton, James; Olabi, Abdul-Ghani

    2010-01-01

    Ireland with its resource of wind has the potential to use this natural resource and sustain the country’s power needs for the future. However, one of the biggest drawbacks to renewable energy generation, particularly wind generated electricity is that it is an intermittent and a variable source of power. Even at the "best" sites wind varies dramatically from hour to hour and minute to minute. This leads to two main problems: 1) When the wind drops below a lower limit or goes above a highe...

  6. Improving Maryland’s Offshore Wind Energy Resource Estimate Using Doppler Wind Lidar Technology to Assess Microtmeteorology Controls

    Directory of Open Access Journals (Sweden)

    Pé Alexandra St.

    2016-01-01

    Compared to lidar measurements, power law extrapolation estimates and operational National Weather Service models underestimated hub-height wind speeds in the WEA. In addition, lidar observations suggest the frequent development of a low-level wind maximum (LLWM, with high turbinelayer wind shear and low turbulence intensity within a turbine’s rotor layer (40m-160m. Results elucidate the advantages of using Doppler wind lidar technology to improve offshore wind resource estimates and its ability to monitor under-sampled offshore meteorological controls impact on a potential turbine’s ability to produce power.

  7. Research on wind field algorithm of wind lidar based on BP neural network and grey prediction

    Science.gov (United States)

    Chen, Yong; Chen, Chun-Li; Luo, Xiong; Zhang, Yan; Yang, Ze-hou; Zhou, Jie; Shi, Xiao-ding; Wang, Lei

    2018-01-01

    This paper uses the BP neural network and grey algorithm to forecast and study radar wind field. In order to reduce the residual error in the wind field prediction which uses BP neural network and grey algorithm, calculating the minimum value of residual error function, adopting the residuals of the gray algorithm trained by BP neural network, using the trained network model to forecast the residual sequence, using the predicted residual error sequence to modify the forecast sequence of the grey algorithm. The test data show that using the grey algorithm modified by BP neural network can effectively reduce the residual value and improve the prediction precision.

  8. Extreme load predictions for floating offshore wind turbines

    DEFF Research Database (Denmark)

    Jensen, Jørgen Juncher

    2009-01-01

    An effective stochastic procedure for extreme value predictions related to wave and wind induced stochastic loads is applied to a tension-leg concept for floating offshore wind turbines. The method is based on the First Order Reliability Method (FORM) and as the procedure makes use of only short...... time-domain simulations all kinds of non-linearities can be included. The procedure has been used previously for wave induced loads and is in this note extended to combined wave and wind loads....

  9. Danish-Czech wind resource know-how transfer project. Interim report 2002

    Energy Technology Data Exchange (ETDEWEB)

    Rathmann, O.; Noergaerd, P.; Frandsen, S.

    2003-12-01

    The progress of the Danish-Czech Wind Resource Know-how Transfer Project is reported. The know-how transfer component of the project has consisted in performing a wind resource training workshop for about 13 individuals from the Czech Republic, ranging from scientists to wind farm project developers, and in donating modern software for evaluating wind resources. The project has also included a review of a Czech overview-study of wind speeds inside the country as well as a study of the electricity tariffs and their impact on wind energy utilization in the Czech Republic. A problematic existing Czech wind farm project, locked up in a no-production situation, was also addressed. However, this situation turned out to be related to problems with economy and owner-ship to a higher degree than to low wind resources and technical problems, and it was not possible for the project to point out a way out of this situation. (au)

  10. Improving urban wind flow predictions through data assimilation

    Science.gov (United States)

    Sousa, Jorge; Gorle, Catherine

    2017-11-01

    Computational fluid dynamic is fundamentally important to several aspects in the design of sustainable and resilient urban environments. The prediction of the flow pattern for example can help to determine pedestrian wind comfort, air quality, optimal building ventilation strategies, and wind loading on buildings. However, the significant variability and uncertainty in the boundary conditions poses a challenge when interpreting results as a basis for design decisions. To improve our understanding of the uncertainties in the models and develop better predictive tools, we started a pilot field measurement campaign on Stanford University's campus combined with a detailed numerical prediction of the wind flow. The experimental data is being used to investigate the potential use of data assimilation and inverse techniques to better characterize the uncertainty in the results and improve the confidence in current wind flow predictions. We consider the incoming wind direction and magnitude as unknown parameters and perform a set of Reynolds-averaged Navier-Stokes simulations to build a polynomial chaos expansion response surface at each sensor location. We subsequently use an inverse ensemble Kalman filter to retrieve an estimate for the probabilistic density function of the inflow parameters. Once these distributions are obtained, the forward analysis is repeated to obtain predictions for the flow field in the entire urban canopy and the results are compared with the experimental data. We would like to acknowledge high-performance computing support from Yellowstone (ark:/85065/d7wd3xhc) provided by NCAR.

  11. Artificial intelligence to predict short-term wind speed

    Energy Technology Data Exchange (ETDEWEB)

    Pinto, Tiago; Soares, Joao; Ramos, Sergio; Vale, Zita [Polytechnic of Porto (Portugal). GECAD - ISEP

    2012-07-01

    The use of renewable energy is increasing exponentially in many countries due to the introduction of new energy and environmental policies. Thus, the focus on energy and on the environment makes the efficient integration of renewable energy into the electric power system extremely important. Several European countries have been seeing a high penetration of wind power, representing, gradually, a significant penetration on electricity generation. The introduction of wind power in the network power system causes new challenges for the power system operator due to the variability and uncertainty in weather conditions and, consequently, in the wind power generation. As result, the scheduling dispatch has a significantly portion of uncertainty. In order to deal with the uncertainty in wind power and, with that, introduce improvements in the power system operator efficiency, the wind power forecasting may reveal as a useful tool. This paper proposes a data-mining-based methodology to forecast wind speed. This method is based on the use of data mining techniques applied to a real database of historical wind data. The paper includes a case study based on a real database regarding the last three years to predict wind speed at 5 minute intervals. (orig.)

  12. A model of rotationally-sampled wind turbulence for predicting fatigue loads in wind turbines

    Science.gov (United States)

    Spera, David A.

    1995-01-01

    Empirical equations are presented with which to model rotationally-sampled (R-S) turbulence for input to structural-dynamic computer codes and the calculation of wind turbine fatigue loads. These equations are derived from R-S turbulence data which were measured at the vertical-plane array in Clayton, New Mexico. For validation, the equations are applied to the calculation of cyclic flapwise blade loads for the NASA/DOE Mod-2 2.5-MW experimental HAWT's (horizontal-axis wind turbines), and the results compared to measured cyclic loads. Good correlation is achieved, indicating that the R-S turbulence model developed in this study contains the characteristics of the wind which produce many of the fatigue loads sustained by wind turbines. Empirical factors are included which permit the prediction of load levels at specified percentiles of occurrence, which is required for the generation of fatigue load spectra and the prediction of the fatigue lifetime of structures.

  13. Skill forecasting from different wind power ensemble prediction methods

    International Nuclear Information System (INIS)

    Pinson, Pierre; Nielsen, Henrik A; Madsen, Henrik; Kariniotakis, George

    2007-01-01

    This paper presents an investigation on alternative approaches to the providing of uncertainty estimates associated to point predictions of wind generation. Focus is given to skill forecasts in the form of prediction risk indices, aiming at giving a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the dispersion of ensemble members for a single prediction horizon, or over a set of successive look-ahead times. It is shown on the test case of a Danish offshore wind farm how prediction risk indices may be related to several levels of forecast uncertainty (and energy imbalances). Wind power ensemble predictions are derived from the transformation of ECMWF and NCEP ensembles of meteorological variables to power, as well as by a lagged average approach alternative. The ability of risk indices calculated from the various types of ensembles forecasts to resolve among situations with different levels of uncertainty is discussed

  14. Model output statistics applied to wind power prediction

    Energy Technology Data Exchange (ETDEWEB)

    Joensen, A.; Giebel, G.; Landberg, L. [Risoe National Lab., Roskilde (Denmark); Madsen, H.; Nielsen, H.A. [The Technical Univ. of Denmark, Dept. of Mathematical Modelling, Lyngby (Denmark)

    1999-03-01

    Being able to predict the output of a wind farm online for a day or two in advance has significant advantages for utilities, such as better possibility to schedule fossil fuelled power plants and a better position on electricity spot markets. In this paper prediction methods based on Numerical Weather Prediction (NWP) models are considered. The spatial resolution used in NWP models implies that these predictions are not valid locally at a specific wind farm. Furthermore, due to the non-stationary nature and complexity of the processes in the atmosphere, and occasional changes of NWP models, the deviation between the predicted and the measured wind will be time dependent. If observational data is available, and if the deviation between the predictions and the observations exhibits systematic behavior, this should be corrected for; if statistical methods are used, this approaches is usually referred to as MOS (Model Output Statistics). The influence of atmospheric turbulence intensity, topography, prediction horizon length and auto-correlation of wind speed and power is considered, and to take the time-variations into account, adaptive estimation methods are applied. Three estimation techniques are considered and compared, Extended Kalman Filtering, recursive least squares and a new modified recursive least squares algorithm. (au) EU-JOULE-3. 11 refs.

  15. Danish-Czech wind resource know-how transfer project. Final report

    DEFF Research Database (Denmark)

    Rathmann, O.; Nørgård, Per Bromand; Frandsen, S.

    2004-01-01

    The course of the Danish-Czech Wind Resource Know-how Transfer Project is reported. The know-how transfer component of the project has consisted in performing a wind resource training workshop for about 13 individuals from the Czech Republic, ranging fromscientists to wind farm project developers...... through a helping package consisting of a training course for the wind farm technicians and in apackage of relevant spare parts....

  16. Wind Power Meteorology

    DEFF Research Database (Denmark)

    Lundtang Petersen, Erik; Mortensen, Niels Gylling; Landberg, Lars

    Wind power meteorology has evolved as an applied science, firmly founded on boundary-layer meteorology, but with strong links to climatology and geography. It concerns itself with three main areas: siting of wind turbines, regional wind resource assessment, and short-term prediction of the wind...... resource. The history, status and perspectives of wind power meteorology are presented, with emphasis on physical considerations and on its practical application. Following a global view of the wind resource, the elements of boundary layer meteorology which are most important for wind energy are reviewed......: wind profiles and shear, turbulence and gust, and extreme winds. The data used in wind power meteorology stem mainly from three sources: onsite wind measurements, the synoptic networks, and the re-analysis projects. Wind climate analysis, wind resource estimation and siting further require a detailed...

  17. Decadal predictability of regional scale wind speed and wind energy potentials over Central Europe

    Science.gov (United States)

    Moemken, Julia; Reyers, Mark; Buldmann, Benjamin; Pinto, Joaquim G.

    2016-04-01

    Regional climate predictions on timescales from one year to one decade are gaining importance since this time frame falls within the planning horizon of politics, economy, and society. In this context, decadal predictions are of particular interest for the development of renewable energies such as wind energy. The present study examines the decadal predictability of regional scale wind speed and wind energy potentials in the framework of the MiKlip consortium ("Mittelfristige Klimaprognosen"; www.fona-miklip.de). This consortium aims to develop a model system based on the Max-Planck-Institute Earth System Model (MPI-ESM) that can provide skilful decadal predictions on regional and global scales. Three generations of the decadal prediction system, which differ primarily in their ocean initialisation, are analysed here. Ensembles of uninitialised historical and yearly initialised hindcast experiments are used to assess different skill scores for 10m wind speeds and wind energy output (Eout) over Central Europe, with special focus given to Germany. With this aim, a statistical-dynamical downscaling (SDD) approach is used for the regionalisation of the global datasets. Its added value is evaluated by comparison of skill scores for MPI-ESM large-scale wind speeds and SDD simulated regional wind speeds. All three MPI-ESM ensemble generations show some forecast skill for annual mean wind speed and Eout over Central Europe on yearly and multi-yearly time scales. The forecast skill is mostly limited to the first years after initialisation. Differences between the three ensemble generations are generally small. The regionalisation preserves and sometimes increases the forecast skill of the global runs but results depend on lead time and ensemble generation. Moreover, regionalisation often improves the ensemble spread. Seasonal Eout skills are generally lower than for annual means. Skill scores are lowest during summer, and persist longest in autumn. A large-scale westerly

  18. Modeling Feasibility of a Proposed Renewable Energy System with Wind and Solar Resources and Hydro Storage in Complex Terrain

    Science.gov (United States)

    Jiang, J.; Koracin, D.; Hamilton, R.; Hagen, D.; King, K. C.

    2012-04-01

    High temporal and spatial variability in wind and solar power brings difficulties in integrating these resources into an electricity grid. These difficulties are even more emphasized in areas with complex topography due to complicated flow patterns and cloudiness evolution. This study investigates the feasibility and efficiency of a proposed renewable energy system with wind and solar resources and hydro storages in western Nevada, U.S.A. The state-of-the-art Weather Research and Forecasting (WRF) model was used for the prediction of wind fields and incoming solar radiation at the ground surface. Forecast winds and solar radiation were evaluated with observational data from four wind masts and four meteorological towers in two months, July 2007 and January 2010. Based on a hypothetical wind farm and an assumed neighboring solar power plant both located near the hydro storage facility, as well as considering local power demand, the efficiency of the renewable energy system is projected. One of the main questions was how to optimize a schedule of activating pump storages according to the characteristics of several available hydro pumps, and wind and/or solar power predictions. The results show that segmentation of the pump-storage channel provides improved efficiency of the entire system. This modeled renewable energy system shows promise for possible applications and grid integration.

  19. Probabilistic stability and "tall" wind profiles: theory and method for use in wind resource assessment

    DEFF Research Database (Denmark)

    Kelly, Mark C.; Troen, Ib

    2016-01-01

    to the methodology. Results of the modeling are shown for a number of sites, with discussion of the models’ efficacy and the relative improvement shown by the new model, for situations where a user lacks local heat flux information, as well as performance of the new model using measured flux statistics. Further......, the uncertainty in vertical extrapolation is characterized for the EWA model contained in standard (i.e., WAsP) wind resource assessment, as well as for the new model. Copyright © 2015 John Wiley & Sons, Ltd....

  20. Selection of References in Wind Turbine Model Predictive Control Design

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Hovgaard, Tobias

    2015-01-01

    a model predictive controller for a wind turbine. One of the important aspects for a tracking control problem is how to setup the optimal reference tracking problem, as it might be relevant to track, e.g., the three concurrent references: optimal pitch angle, optimal rotational speed, and optimal power....... The importance if the individual references differ depending in particular on the wind speed. In this paper we investigate the performance of a reference tracking model predictive controller with two different setups of the used optimal reference signals. The controllers are evaluated using an industrial high...

  1. Wind as a utility-grade supply resource: A planning framework for the Pacific Northwest

    International Nuclear Information System (INIS)

    Johnson, M.S.; Litchfield, J.

    1993-12-01

    Many areas throughout the United States possess favorable wind resources that, as yet, remain undeveloped. This paper provides valuable information on the type of information developers can provide, utility interpretation of the information in regard to electric energy and capacity attributes, and wind resource characteristics of interest to utilities. The paper also reviews key utility planning contexts within which prospective wind resources may be evaluated

  2. Model predictive control of wind energy conversion systems

    CERN Document Server

    Yaramasu, Venkata Narasimha R

    2017-01-01

    The authors provide a comprehensive analysis on the model predictive control of power converters employed in a wide variety of variable-speed wind energy conversion systems (WECS). The contents of this book includes an overview of wind energy system configurations, power converters for variable-speed WECS, digital control techniques, MPC, modeling of power converters and wind generators for MPC design. Other topics include the mapping of continuous-time models to discrete-time models by various exact, approximate, and quasi-exact discretization methods, modeling and control of wind turbine grid-side two-level and multilevel voltage source converters. The authors also focus on the MPC of several power converter configurations for full variable-speed permanent magnet synchronous generator based WECS, squirrel-cage induction generator based WECS, and semi-variable-speed doubly fed induction generator based WECS.

  3. Robust Model Predictive Control of a Wind Turbine

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood; Poulsen, Niels Kjølstad; Niemann, Hans Henrik

    2012-01-01

    , a new sensor is introduced in the EKF to give faster estimations. Wind speed estimation error is used to assess uncertainties in the linearized model. Significant uncertainties are considered to be in the gain of the system (B matrix of the state space model). Therefore this special structure......In this work the problem of robust model predictive control (robust MPC) of a wind turbine in the full load region is considered. A minimax robust MPC approach is used to tackle the problem. Nonlinear dynamics of the wind turbine are derived by combining blade element momentum (BEM) theory...... and first principle modeling of the turbine flexible structure. Thereafter the nonlinear model is linearized using Taylor series expansion around system operating points. Operating points are determined by effective wind speed and an extended Kalman filter (EKF) is employed to estimate this. In addition...

  4. Analysis of the potential for hydrogen production in the province of Cordoba, Argentina, from wind resources

    Energy Technology Data Exchange (ETDEWEB)

    Rodriguez, C.R.; Santa Cruz, R.; Aisa, S. [Universidad Empresarial Siglo 21, Monsenor Pablo Cabrera s/n calle, 5000 Cordoba (Argentina); Riso, M.; Jimenez Yob, G.; Ottogalli, R. [Subsecretaria de Infraestructuras y Programas, Ministerio de Obras y Servicios Publicos del Gobierno de la Provincia de Cordoba, Av. Poeta Lugones 12, 2do. Piso, 5000 Cordoba (Argentina); Jeandrevin, G. [Instituto Universitario Aeronautico, Avenida Fuerza Aerea km 6 1/2, 5022 Cordoba (Argentina); Leiva, E.P.M. [INFIQC, Unidad de Matematica y Fisica, Facultad de Ciencias Quimicas, Universidad Nacional de Cordoba, Haya de la Torre s/n, 5010 Cordoba (Argentina)

    2010-06-15

    The potential for hydrogen production from wind resources in the province of Cordoba, second consumer of fossil fuels for transportation in Argentina, is analyzed. Three aspects of the problem are considered: the evaluation of the hydrogen resource from wind power, the analysis of the production costs via electrolysis and the annual requirements of wind energy to generate hydrogen to fuel the vehicular transport of the province. Different scenarios were considered, including pure hydrogen as well as the so-called CNG plus, where hydrogen is mixed with compressed natural gas in a 20% V/V dilution of the former. The potential for hydrogen production from wind resources is analyzed for each department of the province, excluding those regions not suited for wind farms. The analysis takes into account the efficiency of the electrolyzer and the capacity factor of the wind power system. It is concluded that the automotive transportation could be supplied by hydrogen stemming from wind resources via electrolysis. (author)

  5. Model predictive control for power fluctuation supression in hybrid wind/PV/battery systems

    DEFF Research Database (Denmark)

    You, Shi; Liu, Zongyu; Zong, Yi

    2015-01-01

    A hybrid energy system, the combination of wind turbines, PV panels and battery storage with effective control mechanism, represents a promising solution to the power fluctuation problem when integrating renewable energy resources (RES) into conventional power systems. This paper proposes a model...... predictive control (MPC)-based algorithm for battery management in a hybrid wind/PV/battery system to suppress the short-term power fluctuation on the ‘minute’ scale. A case study with data collected from a practical hybrid system setup is used to demonstrate the effectiveness of the proposed algorithm...

  6. Three-model ensemble wind prediction in southern Italy

    Directory of Open Access Journals (Sweden)

    R. C. Torcasio

    2016-03-01

    Full Text Available Quality of wind prediction is of great importance since a good wind forecast allows the prediction of available wind power, improving the penetration of renewable energies into the energy market. Here, a 1-year (1 December 2012 to 30 November 2013 three-model ensemble (TME experiment for wind prediction is considered. The models employed, run operationally at National Research Council – Institute of Atmospheric Sciences and Climate (CNR-ISAC, are RAMS (Regional Atmospheric Modelling System, BOLAM (BOlogna Limited Area Model, and MOLOCH (MOdello LOCale in H coordinates. The area considered for the study is southern Italy and the measurements used for the forecast verification are those of the GTS (Global Telecommunication System. Comparison with observations is made every 3 h up to 48 h of forecast lead time. Results show that the three-model ensemble outperforms the forecast of each individual model. The RMSE improvement compared to the best model is between 22 and 30 %, depending on the season. It is also shown that the three-model ensemble outperforms the IFS (Integrated Forecasting System of the ECMWF (European Centre for Medium-Range Weather Forecast for the surface wind forecasts. Notably, the three-model ensemble forecast performs better than each unbiased model, showing the added value of the ensemble technique. Finally, the sensitivity of the three-model ensemble RMSE to the length of the training period is analysed.

  7. Three-model ensemble wind prediction in southern Italy

    Science.gov (United States)

    Torcasio, Rosa Claudia; Federico, Stefano; Calidonna, Claudia Roberta; Avolio, Elenio; Drofa, Oxana; Landi, Tony Christian; Malguzzi, Piero; Buzzi, Andrea; Bonasoni, Paolo

    2016-03-01

    Quality of wind prediction is of great importance since a good wind forecast allows the prediction of available wind power, improving the penetration of renewable energies into the energy market. Here, a 1-year (1 December 2012 to 30 November 2013) three-model ensemble (TME) experiment for wind prediction is considered. The models employed, run operationally at National Research Council - Institute of Atmospheric Sciences and Climate (CNR-ISAC), are RAMS (Regional Atmospheric Modelling System), BOLAM (BOlogna Limited Area Model), and MOLOCH (MOdello LOCale in H coordinates). The area considered for the study is southern Italy and the measurements used for the forecast verification are those of the GTS (Global Telecommunication System). Comparison with observations is made every 3 h up to 48 h of forecast lead time. Results show that the three-model ensemble outperforms the forecast of each individual model. The RMSE improvement compared to the best model is between 22 and 30 %, depending on the season. It is also shown that the three-model ensemble outperforms the IFS (Integrated Forecasting System) of the ECMWF (European Centre for Medium-Range Weather Forecast) for the surface wind forecasts. Notably, the three-model ensemble forecast performs better than each unbiased model, showing the added value of the ensemble technique. Finally, the sensitivity of the three-model ensemble RMSE to the length of the training period is analysed.

  8. Evaluation of offshore wind resources by scale of development

    DEFF Research Database (Denmark)

    Möller, Bernd; Hong, Lixuan; Lonsing, Reinhard

    Offshore wind energy has developed rapidly in terms of turbine and project size, and currently undergoes a significant up-scaling to turbines and parks at greater distance to shore and deeper waters. Expectations to the positive effect of economies of scale on power production costs, however, hav......-of-the-art development as well as a sketch of smaller, locally owned parks that may have several economic advantages but require a greater planning and acceptance because of higher visual impact and area competition....... not materialized as yet. On the contrary, anticipated electricity generation costs have been on the increase for each increment of technology scale. Moreover, the cost reductions anticipated for progressing along a technological learning curve have are not apparent, and it seems that not all the additional costs...... can be explained by deeper water, higher distance to shore, bottlenecks in supply or higher raw material costs. The present paper addresses the scale of offshore wind parks for Denmark and invites to reconsider the technological and institutional choices made. Based on a continuous resource...

  9. Evaluation of offshore wind resources by scale of development

    DEFF Research Database (Denmark)

    Möller, Bernd; Hong, Lixuan; Lonsing, Reinhard

    2012-01-01

    Offshore wind energy has developed rapidly in terms of turbine and project size, and currently undergoes a significant up-scaling to turbines and parks at greater distance to shore and deeper waters. Expectations to the positive effect of economies of scale on power production costs, however, hav......-of-the-art development as well as a sketch of smaller, locally owned parks that may have several economic advantages but require a greater planning and acceptance because of higher visual impact and area competition....... not materialized as yet. On the contrary, anticipated electricity generation costs have been on the increase for each increment of technology scale. Moreover, the cost reductions anticipated for progressing along a technological learning curve have are not apparent, and it seems that not all the additional costs...... can be explained by deeper water, higher distance to shore, bottlenecks in supply or higher raw material costs. The present paper addresses the scale of offshore wind parks for Denmark and invites to reconsider the technological and institutional choices made. Based on a continuous resource...

  10. WSA-Enlil Solar Wind Prediction

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSA-Enlil is a large-scale, physics-based prediction model of the heliosphere, used by the Space Weather Forecast Office to provide 1-4 day advance warning of solar...

  11. Prediction of wind energy distribution in complex terrain using CFD

    DEFF Research Database (Denmark)

    Xu, Chang; Li, Chenqi; Yang, Jianchuan

    2013-01-01

    Based on linear models, WAsP software predicts wind energy distribution, with a good accuracy for flat terrain, but with a large error under complicated topography. In this paper, numerical simulations are carried out using the FLUENT software on a mesh generated by the GAMBIT and ARGIS software...

  12. Doppler weather radar with predictive wind shear detection capabilities

    Science.gov (United States)

    Kuntman, Daryal

    1991-01-01

    The status of Bendix research on Doppler weather radar with predictive wind shear detection capability is given in viewgraph form. Information is given on the RDR-4A, a fully coherent, solid state transmitter having Doppler turbulence capability. Frequency generation data, plans, modifications, system characteristics and certification requirements are covered.

  13. Avian risk behavior and fatalities at the Altamont Wind Resource Area: March 1998 - February 1999

    Energy Technology Data Exchange (ETDEWEB)

    Thelander, C.; Rugge, L.

    2000-05-08

    Since 1981, more than 7,000 wind turbines have been installed in the Altamont Wind Resource Area in north-central California. Currently, about 5,000 turbines are operating. Past research efforts demonstrated that wind turbines frequently kill birds, especially raptors. Little is known about the specific flight and perching behaviors by birds near wind turbines. A better understanding of these interactions may one day yield insights on how to minimize bird fatalities. This Phase 1 progress report summarizes research findings obtained at 20 study plots totaling 785 turbines of various configurations and conducted between March 1998 and February 1999. The authors examined bird use and behaviors and collected data on fatalities at the same turbines throughout the course of the surveys. They completed 745 30-minute point counts (1,702 bird observations) that quantified bird risk behaviors and bird use of the study plots. The four most frequently observed bird species were red-tailed hawks, common ravens, turkey vultures, and golden eagles. During the same period, the authors recorded 95 bird fatalities. Raptors represent 51% (n=49) of the kills found. The data indicate that the relative abundance of species observed does not predict the relative frequency of fatalities per species. Phase II of the research is underway.

  14. Wind energy resources assessment for Yanbo, Saudi Arabia

    International Nuclear Information System (INIS)

    Rehman, Shafiqur

    2004-01-01

    The paper presents long term wind data analysis in terms of annual, seasonal and diurnal variations at Yanbo, which is located on the west coast of Saudi Arabia. The wind speed and wind direction hourly data for a period of 14 years between 1970 and 1983 is used in the analysis. The analysis showed that the seasonal and diurnal pattern of wind speed matches the electricity load pattern of the location. Higher winds of the order of 5.0 m/s and more were observed during the summer months of the year and noon hours (09:00 to 16:00 h) of the day. The wind duration availability is discussed as the percent of hours during which the wind remained in certain wind speed intervals or bins. Wind energy calculations were performed using wind machines of sizes 150, 250, 600, 800, 1000, 1300, 1500, 2300 and 2500 kW rated power. Wind speed is found to remain above 3.5 m/s for 69% of the time during the year at 40, 50, 60, and 80 m above ground level. The energy production analysis showed higher production from wind machines of smaller sizes than the bigger ones for a wind farm of 30 MW installed capacity. Similarly, higher capacity factors were obtained for smaller wind machines compared to larger ones

  15. Smoothing out the volatility of South Africa’s wind and solar energy resources

    CSIR Research Space (South Africa)

    Mushwana, Crescent

    2015-10-01

    Full Text Available In the past, renewables were mainly driven by the US, Europe and China, but South Africa is slowly picking up. This presentation discusses South Africa's wind and solar resources as alternative energy resources....

  16. The Use of Reanalysis Data for Wind Resource Assessment at the National Renewable Energy Laboratory

    International Nuclear Information System (INIS)

    Elliott, D.; Schwartz, M.; George, R.

    1999-01-01

    An important component of the National Renewable Energy Laboratory wind resource assessment methodology is the use of available upper-air data to construct detailed vertical profiles for a study region. Currently, the most useful upper-air data for this type of analysis are archived observations from approximately 1800 rawinsonde and pilot balloon stations worldwide. However, significant uncertainty exists in the accuracy of the constructed profiles for many regions. The United States Reanalysis Data Set, recently created by the National Center for Atmospheric Research and the National Centers for Environmental Prediction, has the potential to improve the quality of the vertical profiles. The initial evaluation of the usefulness of the Reanalysis data for wind resource assessment consisted of contrasting reanalysis-derived vertical profiles of the wind characteristics to those generated from upper-air observations for comparable locations. The results indicate that, while reanalysis data can be substituted for upper-air observation data in the assessment methodology for areas of the world where observation data are limited, enough discrepancies with observation data have been noticed to warrant further studies

  17. Down-scaling wind energy resource from mesoscale to local scale by nesting and data assimilation with a CFD model

    International Nuclear Information System (INIS)

    Duraisamy Jothiprakasam, Venkatesh

    2014-01-01

    The development of wind energy generation requires precise and well-established methods for wind resource assessment, which is the initial step in every wind farm project. During the last two decades linear flow models were widely used in the wind industry for wind resource assessment and micro-siting. But the linear models inaccuracies in predicting the wind speeds in very complex terrain are well known and led to use of CFD, capable of modeling the complex flow in details around specific geographic features. Mesoscale models (NWP) are able to predict the wind regime at resolutions of several kilometers, but are not well suited to resolve the wind speed and turbulence induced by the topography features on the scale of a few hundred meters. CFD has proven successful in capturing flow details at smaller scales, but needs an accurate specification of the inlet conditions. Thus coupling NWP and CFD models is a better modeling approach for wind energy applications. A one-year field measurement campaign carried out in a complex terrain in southern France during 2007-2008 provides a well-documented data set both for input and validation data. The proposed new methodology aims to address two problems: the high spatial variation of the topography on the domain lateral boundaries, and the prediction errors of the mesoscale model. It is applied in this work using the open source CFD code Code-Saturne, coupled with the mesoscale forecast model of Meteo-France (ALADIN). The improvement is obtained by combining the mesoscale data as inlet condition and field measurement data assimilation into the CFD model. Newtonian relaxation (nudging) data assimilation technique is used to incorporate the measurement data into the CFD simulations. The methodology to reconstruct long term averages uses a clustering process to group the similar meteorological conditions and to reduce the number of CFD simulations needed to reproduce 1 year of atmospheric flow over the site. The assimilation

  18. Wind resources at turbine height from Envisat and Sentinel-1 SAR

    DEFF Research Database (Denmark)

    Badger, Merete; Hasager, Charlotte Bay; Pena Diaz, Alfredo

    is used to obtain the equivalent neutral wind speed. A correction is applied to compensate for lower radar backscatter at HH polarization compared to VV polarization. Ancillary data used for the SAR-wind processing include wind directions from the Global Forecast System (GFS) and ice mask data from the US...... of 0.5m/s. The SAR-based wind resource maps are used in the New European Wind Atlas – an EU-funded project where European nations work together to produce an updated and validated wind atlas for Europe...

  19. Using meteorological forecasts in on-line predictions of wind power

    DEFF Research Database (Denmark)

    Nielsen, Torben Skov; Nielsen, Henrik Aalborg; Madsen, Henrik

    1999-01-01

    This report describes a model investigation into wind power prediction model as well as a tool for predicting the power production from wind turbines in an area - the Wind Power Prediction Tool (WPPT). The predictions are based on on-line measurements of power production for a selected set...

  20. Performance Prediction of Wind Power Turbine by CAD Analysis

    International Nuclear Information System (INIS)

    Kim, Jongho; Kim, Jongbong; Oh, Younglok

    2013-01-01

    The performance of a vertical-type wind power generator system was predicted by CAD analysis. In the analysis, the reaction torque was calculated for a given rotational speed of the blades. The blade torque of a wind power system was obtained for various rotational speeds, and the generation power was calculated using the obtained torque and the rotational speed. The optimum generator specification, therefore, could be decided using the relationship between the generated power and the rotational speeds. The effects of the number of blades and blade shapes on the generation power were also investigated. Finally, the analysis results were compared with the experimental results

  1. A history of wind erosion prediction models in the United States Department of Agriculture: The Wind Erosion Prediction System (WEPS)

    Science.gov (United States)

    Development of the Wind Erosion Prediction System (WEPS) was officially inaugurated in 1985 by United States Department of Agriculture-Agricultural Research Service (USDA-ARS) scientists in response to customer requests, particularly those coming from the USDA Soil Conservation Service (SCS), for im...

  2. Quantifying wind resource assessment and grid integration challenges for Delaware offshore wind power utilizing mesoscale modeling techniques

    Science.gov (United States)

    Brodie, Joseph F.

    Offshore wind in the United States continues to be a focused area of research as our society grapples with the Earth's changing climate and our ongoing and increasing demand for electricity. While the first offshore wind project in the U.S. is expected to be operational soon, much still remains to be done to help improve viability of offshore wind in additional locations. This dissertation discusses three studies conducted to improve the understanding of and expectations from developing wind energy in the Delaware Wind Energy Area off the Delaware coast. The first study examines the capabilities of the Weather Research and Forecasting (WRF) model to account for variations in wind farm array geometries in an idealized set-up of the model, and determines features of those array geometries that can positively influence the energy production of an offshore farm. The second study investigates the impacts that the misprediction of wind ramp events would have on the interaction of an offshore wind farm with the electricity grid, quantifying some of these impacts and discussing factors which contribute to grid instability. The third study combines the knowledge gained in the first two studies to evaluate potential wind farm array geometries in a regional study of the Delaware Wind Energy Area using WRF along with a selection of case study dates selected to examine the impacts of the synoptic variability of the region throughout the year. These studies demonstrate that careful consideration of the meteorology and climatology of a region when determining the layout of an offshore wind array can improve the power production of the farm, thereby improving wind farm viability. It is shown that using a mesoscale model that incorporates a wind farm parameterization can improve resource assessment by allowing the assessment to evaluate the wind farm's interactions with the weather and climate in the Delaware Wind Energy Area. Furthermore, it is shown that while certain synoptic

  3. Wind Energy Based Electric Vehicle Charging Stations Sitting. A GIS/Wind Resource Assessment Approach

    Directory of Open Access Journals (Sweden)

    George Xydis

    2015-11-01

    Full Text Available The transportation sector is severely correlated with major problems in environment, citizens’ health, climate and economy. Issues such as traffic, fuel cost and parking space have make life more difficult, especially in the dense urban environment. Thus, there is a great need for the development of the electric vehicle (EV sector. The number of cars in cities has increased so much that the current transportation system (roads, parking places, traffic lights, etc. cannot accommodate them properly. The increasing number of vehicles does not affect only humans but also the environment, through air and noise pollution. According to EPA, the 39.2% of total gas emissions in 2007 was caused by transportation activities. Studies have shown that the pollutants are not only gathered in the major roads and/or highways but can travel depending on the meteorological conditions leading to generic pollution. The promotion of EVs and the charging stations are both equally required to be further developed in order EVs to move out of the cities and finally confront the range problem. In this work, a wind resource and a GIS analysis optimizes in a wider area the sitting of wind based charging stations and proposes an optimizing methodology.

  4. Prediction of the far field noise from wind energy farms

    Science.gov (United States)

    Shepherd, K. P.; Hubbard, H. H.

    1986-01-01

    The basic physical factors involved in making predictions of wind turbine noise and an approach which allows for differences in the machines, the wind energy farm configurations and propagation conditions are reviewed. Example calculations to illustrate the sensitivity of the radiated noise to such variables as machine size, spacing and numbers, and such atmosphere variables as absorption and wind direction are presented. It is found that calculated far field distances to particular sound level contours are greater for lower values of atmospheric absorption, for a larger total number of machines, for additional rows of machines and for more powerful machines. At short and intermediate distances, higher sound pressure levels are calculated for closer machine spacings, for more powerful machines, for longer row lengths and for closer row spacings.

  5. The statistical prediction of offshore winds from land-based data for wind-energy applications

    DEFF Research Database (Denmark)

    Walmsley, J.L.; Barthelmie, R.J.; Burrows, W.R.

    2001-01-01

    Land-based meteorological measurements at two locations on the Danish coast are used to predict offshore wind speeds. Offshore wind-speed data are used only for developing the statistical prediction algorithms and for verification. As a first step, the two datasets were separated into nine...... percentile-based bins, with a minimum of 30 data records in each bin. Next, the records were randomly selected with approximately 70% of the data in each bin being used as a training set for development of the prediction algorithms, and the remaining 30% being reserved as a test set for evaluation purposes....... The binning procedure ensured that both training and test sets fairly represented the overall data distribution. To base the conclusions on firmer ground, five permutations of these training and test sets were created. Thus, all calculations were based on five cases, each one representing a different random...

  6. Incorporating Wind Power Forecast Uncertainties Into Stochastic Unit Commitment Using Neural Network-Based Prediction Intervals.

    Science.gov (United States)

    Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

    2015-09-01

    Penetration of renewable energy resources, such as wind and solar power, into power systems significantly increases the uncertainties on system operation, stability, and reliability in smart grids. In this paper, the nonparametric neural network-based prediction intervals (PIs) are implemented for forecast uncertainty quantification. Instead of a single level PI, wind power forecast uncertainties are represented in a list of PIs. These PIs are then decomposed into quantiles of wind power. A new scenario generation method is proposed to handle wind power forecast uncertainties. For each hour, an empirical cumulative distribution function (ECDF) is fitted to these quantile points. The Monte Carlo simulation method is used to generate scenarios from the ECDF. Then the wind power scenarios are incorporated into a stochastic security-constrained unit commitment (SCUC) model. The heuristic genetic algorithm is utilized to solve the stochastic SCUC problem. Five deterministic and four stochastic case studies incorporated with interval forecasts of wind power are implemented. The results of these cases are presented and discussed together. Generation costs, and the scheduled and real-time economic dispatch reserves of different unit commitment strategies are compared. The experimental results show that the stochastic model is more robust than deterministic ones and, thus, decreases the risk in system operations of smart grids.

  7. Atlas de Recursos Eólicos del Estado de Oaxaca (The Spanish version of Wind Energy Resource Atlas of Oaxaca)

    Energy Technology Data Exchange (ETDEWEB)

    Elliott, D.; Schwartz, M.; Scott, G.; Haymes, S.; Heimiller, D.; George, R.

    2004-04-01

    The Oaxaca Wind Resource Atlas, produced by the National Renewable Energy Laboratory's (NREL's) wind resource group, is the result of an extensive mapping study for the Mexican State of Oaxaca. This atlas identifies the wind characteristics and distribution of the wind resource in Oaxaca. The detailed wind resource maps and other information contained in the atlas facilitate the identification of prospective areas for use of wind energy technologies, both for utility-scale power generation and off-grid wind energy applications.

  8. Statistical characterization of roughness uncertainty and impact on wind resource estimation

    DEFF Research Database (Denmark)

    Kelly, Mark C.; Ejsing Jørgensen, Hans

    2017-01-01

    In this work we relate uncertainty in background roughness length (z0) to uncertainty in wind speeds, where the latter are predicted at a wind farm location based on wind statistics observed at a different site. Sensitivity of predicted winds to roughness is derived analytically for the industry-...... between mean wind speed and AEP. Following our developments, we provide guidance on approximate roughness uncertainty magnitudes to be expected in industry practice, and we also find that sites with larger background roughness incur relatively larger uncertainties....

  9. Wind energy resource atlas. Volume 8. The southern Rocky Mountain region

    Energy Technology Data Exchange (ETDEWEB)

    Andersen, S.R.; Freeman, D.L.; Hadley, D.L.; Elliott, D.L.; Barchet, W.R.; George, R.L.

    1981-03-01

    The Southern Rocky Mountain atlas assimilates five collections of wind resource data: one for the region and one for each of the four states that compose the Southern Rocky Mountain region (Arizona, Colorado, New Mexico, and Utah). At the state level, features of the climate, topography and wind resource are discussed in greater detail than is provided in the regional discussion, and the data locations on which the assessment is based are mapped. Variations, over several time scales, in the wind resource at selected stations in each state are shown on graphs of monthly average and interannual wind speed and power, and hourly average wind speed for each season. Other graphs present speed, direction, and duration frequencies of the wind at these locations.

  10. Combining the VAS 3D interpolation method and Wind Atlas methodology to produce a high-resolution wind resource map for the Czech Republic

    Czech Academy of Sciences Publication Activity Database

    Hanslian, David; Hošek, Jiří

    2015-01-01

    Roč. 77, May (2015), s. 291-299 ISSN 0960-1481 Institutional support: RVO:68378289 Keywords : wind resource map * wind field modelling * wind measurements * wind climatology * Czech Republic * WAsP Subject RIV: DG - Athmosphere Sciences, Meteorology Impact factor: 3.404, year: 2015 http://www.sciencedirect.com/science/article/pii/S0960148114008398#

  11. Large-scale, high-resolution wind resource mapping for wind farm planning and development in South Africa

    DEFF Research Database (Denmark)

    Mortensen, Niels Gylling; Badger, Jake; Hansen, Jens Carsten

    2014-01-01

    -climatological inputs to the wind resource mapping are wind atlas data sets derived from mesoscale modelling using the Karlsruhe Atmospheric Mesoscale Model (KAMM). The topographical inputs to the microscale modelling are 20-m digital height contours from 1:50,000 South African topographical maps and vector-format land...... estimates are designed for national and provincial planning and strategic environmental impact assessment for wind power in South Africa and the results have therefore been made available in common GIS formats. The database of results is in the public domain and can be downloaded from the WASA web site...

  12. Wind turbine power curve prediction with consideration of rotational augmentation effects

    Science.gov (United States)

    Tang, X.; Huang, X.; Sun, S.; Peng, R.

    2016-11-01

    Wind turbine power curve expresses the relationship between the rotor power and the hub wind speed. Wind turbine power curve prediction is of vital importance for power control and wind energy management. To predict power curve, the Blade Element Moment (BEM) method is used in both academic and industrial communities. Due to the limited range of angles of attack measured in wind tunnel testing and the three-dimensional (3D) rotational augmentation effects in rotating turbines, wind turbine power curve prediction remains a challenge especially at high wind speeds. This paper presents an investigation of considering the rotational augmentation effects using characterized lift and drag coefficients from 3D computational fluid dynamics (CFD) simulations coupled in the BEM method. A Matlab code was developed to implement the numerical calculation. The predicted power outputs were compared with the NREL Phase VI wind turbine measurements. The results demonstrate that the coupled method improves the wind turbine power curve prediction.

  13. Smoothing of wind farm output power using prediction based flywheel energy storage system

    Science.gov (United States)

    Islam, Farzana

    Being socially beneficial, economically competitive and environment friendly, wind energy is now considered to be the world's fastest growing renewable energy source. However, the stochastic nature of wind imposes a considerable challenge in the optimal management and operation of wind power system. Wind speed prediction is critical for wind energy conversion system since it greatly influences the issues related to effective energy management, dynamic control of wind turbine, and improvement of the overall efficiency of the power generation system. This thesis focuses on integration of energy storage system with wind farm, considering wind speed prediction in the control scheme to overcome the problems associated with wind power fluctuations. In this thesis, flywheel energy storage system (FESS) with adjustable speed rotary machine has been considered for smoothing of output power in a wind farm composed of a fixed speed wind turbine generator (FSWTG). Since FESS has both active and reactive power compensation ability, it enhances the stability of the system effectively. An efficient energy management system combined with supervisory control unit (SCU) for FESS and wind speed prediction has been developed to improve the smoothing of the wind farm output effectively. Wind speed prediction model is developed by artificial neural network (ANN) which has advantages over the conventional prediction scheme including data error tolerance and ease in adaptability. The model for prediction with ANN is developed in MATLAB/Simulink and interfaced with PSCAD/EMTDC. Effectiveness of the proposed control system is illustrated using real wind speed data in various operating conditions.

  14. Offshore Wind Resource Estimation in Mediterranean Area Using SAR Images

    DEFF Research Database (Denmark)

    Calaudi, Rosamaria; Arena, Felice; Badger, Merete

    Satellite observations of the ocean surface from Synthetic Aperture Radars (SAR) provide information about the spatial wind variability over large areas. This is of special interest in the Mediterranean, where spatial wind information is only provided by sparse buoys, often with long periods...

  15. Climate Change Impacts on South African Wind Energy Resources ...

    African Journals Online (AJOL)

    Consideration of the potential risks posed by climate change to the wind energy sector is critical for its development in South Africa. This study determines if future wind speeds might change under two climate change projections by employing climate model data at 0.44°latitude (~45km)×0.44ºlongitude (~50km) resolution.

  16. Wind and Solar Resource Assessment of Sri Lanka and the Maldives (CD-ROM)

    Energy Technology Data Exchange (ETDEWEB)

    Elliott, D.; Schwartz, M.; Scott, G.; Haymes, S.; Heimiller, D.; George, R.

    2003-08-01

    The Wind and Solar Resource Assessment of Sri Lanka and the Maldives CD contains an electronic version of Wind Energy Resource Atlas of Sri Lanka and the Maldives (NREL/TP-500-34518), Solar Resource Assessment for Sri Lanka and the Maldives (NREL/TO-710-34645), Sri Lanka Wind Farm Analysis and Site Selection Assistance (NREL/SR-500-34646), GIS Data Viewer (software and data files with a readme file), and Hourly Solar and Typical Meteorological Year Data with a readme file.

  17. Distributed Model Predictive Control for Active Power Control of Wind Farm

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Rasmussen, Claus Nygaard

    2014-01-01

    This paper presents the active power control of a wind farm using the Distributed Model Predictive Controller (D- MPC) via dual decomposition. Different from the conventional centralized wind farm control, multiple objectives such as power reference tracking performance and wind turbine load can......-scale wind farm control....

  18. Application of an atmospheric CFD code to wind resource assessment in complex terrain

    International Nuclear Information System (INIS)

    Laporte, Laurent

    2008-01-01

    This thesis is organized in two parts. The first part presents the use of the atmospheric CFD code Mercure Saturne to estimate the wind resource in complex terrain. A measurement campaign was led by EDF to obtain data for validation. A methodology was developed using meso-scale profiles as boundary conditions. Clustering of meteorological situations was used to reduce the number of simulations needed to calculate the wind resource. The validation of the code on the Askervein hill, the methodology and comparisons with measurements from the complex site are presented. The second part presents the modeling of wakes with the Mercure Saturne code. Forces, generated by the blades on the wind, are modeled by source terms, calculated by the BEM method. Two comparisons are proposed to validate the method: the first compares the numerical model with wind tunnel measurements from a small wind turbine, the second with measurements made on porous disks in an atmospheric boundary layer wind tunnel (author) [fr

  19. SAR-based Wind Resource Statistics in the Baltic Sea

    DEFF Research Database (Denmark)

    Hasager, Charlotte Bay; Badger, Merete; Pena Diaz, Alfredo

    2011-01-01

    and from 10 meteorological masts, established specifically for wind energy in the study area, are compared. The statistical results comparing in situ wind speed and SAR-based wind speed show a root mean square error of 1.17 m s−1, bias of −0.25 m s−1, standard deviation of 1.88 m s−1 and correlation...... coefficient of R2 0.783. Wind directions from a global atmospheric model, interpolated in time and space, are used as input to the geophysical model function CMOD-5 for SAR wind retrieval. Wind directions compared to mast observations show a root mean square error of 6.29° with a bias of 7.75°, standard...... deviation of 20.11° and R2 of 0.950. The scale and shape parameters, A and k, respectively, from the Weibull probability density function are compared at only one available mast and the results deviate ~2% for A but ~16% for k. Maps of A and k, and wind power density based on more than 1000 satellite images...

  20. Danish-Czech wind resource know-how transfer project. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Rathmann, O.; Noergaerd, P.; Frandsen, S.

    2004-06-01

    The course of the Danish-Czech Wind Resource Know-how Transfer Project is reported. The know-how transfer component of the project has consisted in performing a wind resource training work-shop for about 13 individuals from the Czech Republic, ranging from scientists to wind farm project developers, and in donating modern software for evaluating wind resources. The project has also included a review of a Czech overview-study of wind speeds inside the country as well as an investigation of the electricity tariffs and their impact on wind energy utilization in the Czech Republic. A problematic existing Czech wind farm project, locked up in a no-production situation, was also addressed. Not until the purchase by a new owner-company, which initiated the necessary repair and maintenance, the wind farm resumed normal operation. As its last task, the present project assisted in consolidating future operation through a helping package consisting of a training course for the wind farm technicians and in a package of relevant spare parts. (au)

  1. COMPLEX MAPPING OF ENERGY RESOURCES FOR ALLOCATION OF SOLAR AND WIND ENERGY OBJECTS

    Directory of Open Access Journals (Sweden)

    B. A. Novakovskiy

    2016-01-01

    Full Text Available The paper presents developed methodology of solar and wind energy resources complex mapping at the regional level, taking into account the environmental and socio-economic factors affecting the placement of renewable energy facilities. Methodology provides a reasonable search and allocation of areas, the most promising for the placement of wind and solar power plants.

  2. Very short-term spatio-temporal wind power prediction using a censored Gaussian field

    DEFF Research Database (Denmark)

    Baxevani, Anastassia; Lenzi, Amanda

    2018-01-01

    to predict the level of wind power and the associated variability are critical. Ideally, one would like to obtain reliable probability density forecasts for the wind power distributions. We aim at contributing to the literature of wind power prediction by developing and analysing a spatio...

  3. Wind Resource Assessment and Forecast Planning with Neural Networks

    Directory of Open Access Journals (Sweden)

    Nicolus K. Rotich

    2014-06-01

    Full Text Available In this paper we built three types of artificial neural networks, namely: Feed forward networks, Elman networks and Cascade forward networks, for forecasting wind speeds and directions. A similar network topology was used for all the forecast horizons, regardless of the model type. All the models were then trained with real data of collected wind speeds and directions over a period of two years in the municipal of Puumala, Finland. Up to 70th percentile of the data was used for training, validation and testing, while 71–85th percentile was presented to the trained models for validation. The model outputs were then compared to the last 15% of the original data, by measuring the statistical errors between them. The feed forward networks returned the lowest errors for wind speeds. Cascade forward networks gave the lowest errors for wind directions; Elman networks returned the lowest errors when used for short term forecasting.

  4. High altitude wind resource in the Middle East

    Science.gov (United States)

    Yip, Chak Man Andrew; Gunturu, Udaya B.; Stenchikov, Georgiy L.

    2016-04-01

    This study presents a first identification of areas favorable to Airborne Wind Energy (AWE) Systems deployment in the Middle East and illustrates their diurnal and seasonal characteristics. Optimal heights of AWE system deployment are computed. The AWE literature has conventionally used a top-down approach where AWE potentials are estimated as a fraction of wind power density. This study takes the bottom-up approach where the regional AWE potentials are estimated using realistic machine specification with assumptions upon deployment conditions. The annual energy production per capita illustrates the potential of AWE systems in fulfilling electricity needs at the current level for several countries in the region. Our estimate also compares favorably to the near-surface wind power potential using identical data source from a previous study. In addition, the non-monotonicity in the vertical profile is examined for areas with potential LLJ influences, where behaviors in wind speed and direction similar to that of inertial oscillations are identified.

  5. Wind Resource Estimation and Mapping at the National Renewable Energy Laboratory

    Energy Technology Data Exchange (ETDEWEB)

    Schwartz, M.

    1999-04-07

    The National Renewable Energy Laboratory (NREL) has developed an automated technique for wind resource mapping to aid in the acceleration of wind energy deployment. The new automated mapping system was developed with the following two primary goals: (1) to produce a more consistent and detailed analysis of the wind resource for a variety of physiographic settings, particularly in areas of complex terrain; and (2) to generate high quality map products on a timely basis. Using computer mapping techniques reduces the time it takes to produce a wind map that reflects a consistent analysis of the distribution of the wind resource throughout the region of interest. NREL's mapping system uses commercially available geographic information system software packages. Regional wind resource maps using this new system have been produced for areas of the United States, Mexico, Chile, Indonesia (1), and China. Countrywide wind resource assessments are under way for the Philippines, the Dominican Re public, and Mongolia. Regional assessments in Argentina and Russia are scheduled to begin soon.

  6. Modelling the Spatial Distribution of Wind Energy Resources in Latvia

    Science.gov (United States)

    Aniskevich, S.; Bezrukovs, V.; Zandovskis, U.; Bezrukovs, D.

    2017-12-01

    The paper studies spatial wind energy flow distribution in Latvia based on wind speed measurements carried out at an altitude of 10 m over a period of two years, from 2015 to 2016. The measurements, with 1 min increments, were carried out using certified measuring instruments installed at 22 observation stations of the Latvian National Hydrometeorological and Climatological Service of the Latvian Environment, Geology and Meteorology Centre (LEGMC). The models of the spatial distribution of averaged wind speed and wind energy density were developed using the method of spatial interpolation based on the historical measurement results and presented in the form of colour contour maps with a 1×1 km resolution. The paper also provides the results of wind speed spatial distribution modelling using a climatological reanalysis ERA5 at the altitudes of 10, 54, 100 and 136 m with a 31×31 km resolution. The analysis includes the comparison of actual wind speed measurement results with the outcomes of ERA5 modelling for meteorological observation stations in Ainazi, Daugavpils, Priekuli, Saldus and Ventspils.

  7. A CASE STUDY OF CHINA ́S WIND POWER RESOURCES

    OpenAIRE

    Xue Yanping

    2013-01-01

    At present, China is the largest energy producer and the second largest energy consumer in the world. With the increasing pressure to cut GHS emissions and to improve energy efficiency, China is now changing its traditional energy mix, mainly through consuming more renewable energy instead of fossil energy. This change has resulted in a policy adjustment which in turn boosts the utilization of the wind power resources. However, the development of the wind power resources in China is confronte...

  8. Forecasting Electricity Spot Prices Accounting for Wind Power Predictions

    DEFF Research Database (Denmark)

    Jónsson, Tryggvi; Pinson, Pierre; Nielsen, Henrik Aalborg

    2013-01-01

    A two-step methodology for forecasting of electricity spot prices is introduced, with focus on the impact of predicted system load and wind power generation. The nonlinear and nonstationary influence of these explanatory variables is accommodated in a first step based on a nonparametric and time......-varying regression model. In a second step, time-series models, i.e., ARMA and Holt–Winters, are applied to account for residual autocorrelation and seasonal dynamics. Empirical results are presented for out-of-sample forecasts of day-ahead prices in the Western Danish price area of Nord Pool's Elspot, during a two...

  9. Map-Based Repowering and Reorganization of a Wind Resource Area to Minimize Burrowing Owl and Other Bird Fatalities

    Directory of Open Access Journals (Sweden)

    Lee Neher

    2009-10-01

    Full Text Available Wind turbines in the Altamont Pass Wind Resource Area (Alameda/Contra Costa Counties, California, USA generate about 730 GWh of electricity annually, but have been killing thousands of birds each year, including >2,000 raptors and hundreds of burrowing owls. We have developed collision hazard maps and hazard ratings of wind turbines to guide relocation of existing wind turbines and careful repowering to modern turbines to reduce burrowing owl fatalities principally, and other birds secondarily. Burrowing owls selected burrow sites lower on slopes and on smaller, shallower slopes than represented by the average 10 × 10 m2 grid cell among 187,908 grid cells sampled from 2,281,169 grid cells comprising a digital elevation model (DEM of the study area. Fuzzy logic and discriminant function analysis produced likelihood surfaces encompassing most burrowing owl burrows within a fraction of the study area, and the former corresponded with burrowing owl fatalities and the latter with other raptor fatalities. Our ratings of wind turbine hazard were more predictive of burrowing owl fatalities, but would be more difficult to implement. Careful repowering to modern wind turbines would most reduce fatalities of burrowing owls and other birds while adding about 1,000 GWh annually toward California’s 33% Renewable Portfolio Standard.

  10. PREDICTION OF POWER GENERATION OF SMALL SCALE VERTICAL AXIS WIND TURBINE USING FUZZY LOGIC

    Directory of Open Access Journals (Sweden)

    Altab Hossain

    2009-01-01

    Full Text Available Renewable energy from the wind turbine has been focused for the alternative source of power generation due to the following advances of the of the wind turbine. Firstly, the wind turbine is highly efficient and eco-friendly. Secondly, the turbine has the ability to response for the changeable power generation based on the wind velocity and structural framework. However, the competitive efficiency of the wind turbine is necessary to successfully alternate the conventional power sources. The most relevant factor which affects the overall efficiency of the wind turbine is the wind velocity and the relative turbine dimensions. Artificial intelligence systems are widely used technology that can learn from examples and are able to deal with non-linear problems. Compared with traditional approach, fuzzy logic approach is more efficient for the representation, manipulation and utilization. Therefore, the primary purpose of this work was to investigate the relationship between wind turbine power generation and wind velocity, and to illustrate how fuzzy expert system might play an important role in prediction of wind turbine power generation. The main purpose of the measurement over the small scaled prototype vertical axis wind turbine for the wind velocity is to predict the performance of full scaled H-type vertical axis wind turbine. Prediction of power generation at the different wind velocities has been tested at the Thermal Laboratory of Faculty of Engineering, Universiti Industri Selangor (UNISEL and results concerning the daily prediction have been obtained.

  11. An Improved Global Wind Resource Estimate for Integrated Assessment Models: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Eurek, Kelly [National Renewable Energy Lab. (NREL), Golden, CO (United States); Sullivan, Patrick [National Renewable Energy Lab. (NREL), Golden, CO (United States); Gleason, Michael [National Renewable Energy Lab. (NREL), Golden, CO (United States); Hettinger, Dylan [National Renewable Energy Lab. (NREL), Golden, CO (United States); Heimiller, Donna [National Renewable Energy Lab. (NREL), Golden, CO (United States); Lopez, Anthony [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2017-02-01

    This paper summarizes initial steps to improving the robustness and accuracy of global renewable resource and techno-economic assessments for use in integrated assessment models. We outline a method to construct country-level wind resource supply curves, delineated by resource quality and other parameters. Using mesoscale reanalysis data, we generate estimates for wind quality, both terrestrial and offshore, across the globe. Because not all land or water area is suitable for development, appropriate database layers provide exclusions to reduce the total resource to its technical potential. We expand upon estimates from related studies by: using a globally consistent data source of uniquely detailed wind speed characterizations; assuming a non-constant coefficient of performance for adjusting power curves for altitude; categorizing the distance from resource sites to the electric power grid; and characterizing offshore exclusions on the basis of sea ice concentrations. The product, then, is technical potential by country, classified by resource quality as determined by net capacity factor. Additional classifications dimensions are available, including distance to transmission networks for terrestrial wind and distance to shore and water depth for offshore. We estimate the total global wind generation potential of 560 PWh for terrestrial wind with 90% of resource classified as low-to-mid quality, and 315 PWh for offshore wind with 67% classified as mid-to-high quality. These estimates are based on 3.5 MW composite wind turbines with 90 m hub heights, 0.95 availability, 90% array efficiency, and 5 MW/km2 deployment density in non-excluded areas. We compare the underlying technical assumption and results with other global assessments.

  12. Analysis the Transient Process of Wind Power Resources when there are Voltage Sags in Distribution Grid

    Science.gov (United States)

    Nhu Y, Do

    2018-03-01

    Vietnam has many advantages of wind power resources. Time by time there are more and more capacity as well as number of wind power project in Vietnam. Corresponding to the increase of wind power emitted into national grid, It is necessary to research and analyze in order to ensure the safety and reliability of win power connection. In national distribution grid, voltage sag occurs regularly, it can strongly influence on the operation of wind power. The most serious consequence is the disconnection. The paper presents the analysis of distribution grid's transient process when voltage is sagged. Base on the analysis, the solutions will be recommended to improve the reliability and effective operation of wind power resources.

  13. A CASE STUDY OF CHINA ́S WIND POWER RESOURCES

    Directory of Open Access Journals (Sweden)

    Xue Yanping

    2013-11-01

    Full Text Available At present, China is the largest energy producer and the second largest energy consumer in the world. With the increasing pressure to cut GHS emissions and to improve energy efficiency, China is now changing its traditional energy mix, mainly through consuming more renewable energy instead of fossil energy. This change has resulted in a policy adjustment which in turn boosts the utilization of the wind power resources. However, the development of the wind power resources in China is confronted with some significant challenges, such as greater installed electricity capacity than the electricity generation, greater electricity generation than the electricity transmission capacity and greater inland wind power generation than the offshore wind power generation. Therefore, the further development of China’s wind power electricity in the coming years depends largely on the ways these challenges will be addressed.

  14. Statistical characterization of roughness uncertainty and impact on wind resource estimation

    Directory of Open Access Journals (Sweden)

    M. Kelly

    2017-04-01

    Full Text Available In this work we relate uncertainty in background roughness length (z0 to uncertainty in wind speeds, where the latter are predicted at a wind farm location based on wind statistics observed at a different site. Sensitivity of predicted winds to roughness is derived analytically for the industry-standard European Wind Atlas method, which is based on the geostrophic drag law. We statistically consider roughness and its corresponding uncertainty, in terms of both z0 derived from measured wind speeds as well as that chosen in practice by wind engineers. We show the combined effect of roughness uncertainty arising from differing wind-observation and turbine-prediction sites; this is done for the case of roughness bias as well as for the general case. For estimation of uncertainty in annual energy production (AEP, we also develop a generalized analytical turbine power curve, from which we derive a relation between mean wind speed and AEP. Following our developments, we provide guidance on approximate roughness uncertainty magnitudes to be expected in industry practice, and we also find that sites with larger background roughness incur relatively larger uncertainties.

  15. Large-scale, high-resolution wind resource mapping for wind farm planning and development in South Africa

    DEFF Research Database (Denmark)

    Mortensen, Niels Gylling; Badger, Jake; Hansen, Jens Carsten

    sur-face roughness maps based on the USGS Global Land Cover Characteristics database (GLCC). A transformation table was used to relate land cover to roughness length. The detailed resource map has been verified at ten mast locations where high-quality wind measurements are available. Overall...... estimates are designed for national and provincial planning and strategic environmental impact assessment for wind power in South Africa and the results have therefore been made available in common GIS formats. The database of results is in the public domain and can be downloaded from the WASA web site...

  16. The predictability of large-scale wind-driven flows

    Directory of Open Access Journals (Sweden)

    A. Mahadevan

    2001-01-01

    Full Text Available The singular values associated with optimally growing perturbations to stationary and time-dependent solutions for the general circulation in an ocean basin provide a measure of the rate at which solutions with nearby initial conditions begin to diverge, and hence, a measure of the predictability of the flow. In this paper, the singular vectors and singular values of stationary and evolving examples of wind-driven, double-gyre circulations in different flow regimes are explored. By changing the Reynolds number in simple quasi-geostrophic models of the wind-driven circulation, steady, weakly aperiodic and chaotic states may be examined. The singular vectors of the steady state reveal some of the physical mechanisms responsible for optimally growing perturbations. In time-dependent cases, the dominant singular values show significant variability in time, indicating strong variations in the predictability of the flow. When the underlying flow is weakly aperiodic, the dominant singular values co-vary with integral measures of the large-scale flow, such as the basin-integrated upper ocean kinetic energy and the transport in the western boundary current extension. Furthermore, in a reduced gravity quasi-geostrophic model of a weakly aperiodic, double-gyre flow, the behaviour of the dominant singular values may be used to predict a change in the large-scale flow, a feature not shared by an analogous two-layer model. When the circulation is in a strongly aperiodic state, the dominant singular values no longer vary coherently with integral measures of the flow. Instead, they fluctuate in a very aperiodic fashion on mesoscale time scales. The dominant singular vectors then depend strongly on the arrangement of mesoscale features in the flow and the evolved forms of the associated singular vectors have relatively short spatial scales. These results have several implications. In weakly aperiodic, periodic, and stationary regimes, the mesoscale energy

  17. A new approach to very short term wind speed prediction using k-nearest neighbor classification

    International Nuclear Information System (INIS)

    Yesilbudak, Mehmet; Sagiroglu, Seref; Colak, Ilhami

    2013-01-01

    Highlights: ► Wind speed parameter was predicted in an n-tupled inputs using k-NN classification. ► The effects of input parameters, nearest neighbors and distance metrics were analyzed. ► Many useful and reasonable inferences were uncovered using the developed model. - Abstract: Wind energy is an inexhaustible energy source and wind power production has been growing rapidly in recent years. However, wind power has a non-schedulable nature due to wind speed variations. Hence, wind speed prediction is an indispensable requirement for power system operators. This paper predicts wind speed parameter in an n-tupled inputs using k-nearest neighbor (k-NN) classification and analyzes the effects of input parameters, nearest neighbors and distance metrics on wind speed prediction. The k-NN classification model was developed using the object oriented programming techniques and includes Manhattan and Minkowski distance metrics except from Euclidean distance metric on the contrary of literature. The k-NN classification model which uses wind direction, air temperature, atmospheric pressure and relative humidity parameters in a 4-tupled space achieved the best wind speed prediction for k = 5 in the Manhattan distance metric. Differently, the k-NN classification model which uses wind direction, air temperature and atmospheric pressure parameters in a 3-tupled inputs gave the worst wind speed prediction for k = 1 in the Minkowski distance metric

  18. Benefits for wind energy in electricity markets from using short term wind power prediction tools: a simulation study

    International Nuclear Information System (INIS)

    Usaola, J.; Ravelo, O.; Gonzalez, G.; Soto, F.; Davila, M.C.; Diaz-Guerra, B.

    2004-01-01

    One of the characteristics of wind energy, from the grid point of view, is its non-dispatchability, i.e. generation cannot be ordered, hence integration in electrical networks may be difficult. Short-term wind power prediction-tools could make this integration easier, either by their use by the grid System Operator, or by promoting the participation of wind farms in the electricity markets and using prediction tools to make their bids in the market. In this paper, the importance of a short-term wind power-prediction tool for the participation of wind energy systems in electricity markets is studied. Simulations, according to the current Spanish market rules, have been performed to the production of different wind farms, with different degrees of accuracy in the prediction tool. It may be concluded that income from participation in electricity markets is increased using a short-term wind power prediction-tool of average accuracy. This both marginally increases income and also reduces the impact on system operation with the improved forecasts. (author)

  19. Multi-step-ahead Method for Wind Speed Prediction Correction Based on Numerical Weather Prediction and Historical Measurement Data

    Science.gov (United States)

    Wang, Han; Yan, Jie; Liu, Yongqian; Han, Shuang; Li, Li; Zhao, Jing

    2017-11-01

    Increasing the accuracy of wind speed prediction lays solid foundation to the reliability of wind power forecasting. Most traditional correction methods for wind speed prediction establish the mapping relationship between wind speed of the numerical weather prediction (NWP) and the historical measurement data (HMD) at the corresponding time slot, which is free of time-dependent impacts of wind speed time series. In this paper, a multi-step-ahead wind speed prediction correction method is proposed with consideration of the passing effects from wind speed at the previous time slot. To this end, the proposed method employs both NWP and HMD as model inputs and the training labels. First, the probabilistic analysis of the NWP deviation for different wind speed bins is calculated to illustrate the inadequacy of the traditional time-independent mapping strategy. Then, support vector machine (SVM) is utilized as example to implement the proposed mapping strategy and to establish the correction model for all the wind speed bins. One Chinese wind farm in northern part of China is taken as example to validate the proposed method. Three benchmark methods of wind speed prediction are used to compare the performance. The results show that the proposed model has the best performance under different time horizons.

  20. Offshore Wind Resources Assessment from Multiple Satellite Data and WRF Modeling over South China Sea

    DEFF Research Database (Denmark)

    Chang, Rui; Rong, Zhu; Badger, Merete

    2015-01-01

    the Navy Operational Global Atmospheric Prediction System (NOGAPS) and ASCAT agree well with these observations from the corresponding in situ measurements. The statistical results comparing in situ wind speed and SAR-based (ASCAT-based) wind speed for the whole co-located samples show a standard deviation...

  1. On the Wind Energy Resource and Its Trend in the East China Sea

    Directory of Open Access Journals (Sweden)

    Adekunle Ayodotun Osinowo

    2017-01-01

    Full Text Available This study utilizes a 30-year (1980–2009 10 m wind field dataset obtained from the European Center for Medium Range Weather Forecast to investigate the wind energy potential in the East China Sea (ECS by using Weibull shape and scale parameters. The region generally showed good wind characteristics. The calculated annual mean of the wind power resource revealed the potential of the region for large-scale grid-connected wind turbine applications. Furthermore, the spatiotemporal variations showed strong trends in wind power in regions surrounding Taiwan Island. These regions were evaluated with high wind potential and were rated as excellent locations for installation of large wind turbines for electrical energy generation. Nonsignificant and negative trends dominated the ECS and the rest of the regions; therefore, these locations were found to be suitable for small wind applications. The wind power density exhibited an insignificant trend in the ECS throughout the study period. The trend was strongest during spring and weakest during autumn.

  2. U.S. Virgin Islands Wind Resources Update 2014

    Energy Technology Data Exchange (ETDEWEB)

    Roberts, J. O.; Warren, A.

    2014-12-01

    This report summarizes the data collected from two 60-meter meteorological towers and three sonic detection and ranging units on St. Thomas and St. Croix in 2012 and 2013. These results are an update to the previous feasibility study; the collected data are critical to the successful development of a wind project at either site.

  3. A Wind Power and Load Prediction Based Frequency Control Approach for Wind-Diesel-Battery Hybrid Power System

    Directory of Open Access Journals (Sweden)

    Chao Peng

    2015-01-01

    Full Text Available A frequency control approach based on wind power and load power prediction information is proposed for wind-diesel-battery hybrid power system (WDBHPS. To maintain the frequency stability by wind power and diesel generation as much as possible, a fuzzy control theory based wind and diesel power control module is designed according to wind power and load prediction information. To compensate frequency fluctuation in real time and enhance system disturbance rejection ability, a battery energy storage system real-time control module is designed based on ADRC (active disturbance rejection control. The simulation experiment results demonstrate that the proposed approach has a better disturbance rejection ability and frequency control performance compared with the traditional droop control approach.

  4. How Many Model Evaluations Are Required To Predict The AEP Of A Wind Power Plant?

    DEFF Research Database (Denmark)

    Murcia Leon, Juan Pablo; Réthoré, Pierre-Elouan; Natarajan, Anand

    2015-01-01

    (AEP) predictions expensive. The objective of the present paper is to minimize the number of model evaluations required to capture the wind power plant's AEP using stationary wind farm flow models. Polynomial chaos techniques are proposed based on arbitrary Weibull distributed wind speed and Von Misses......Wind farm flow models have advanced considerably with the use of large eddy simulations (LES) and Reynolds averaged Navier-Stokes (RANS) computations. The main limitation of these techniques is their high computational time requirements; which makes their use for wind farm annual energy production...... distributed wind direction. The correlation between wind direction and wind speed are captured by defining Weibull-parameters as functions of wind direction. In order to evaluate the accuracy of these methods the expectation and variance of the wind farm power distributions are compared against...

  5. Repetitive model predictive approach to individual pitch control of wind turbines

    DEFF Research Database (Denmark)

    Adegas, Fabiano Daher; Stoustrup, Jakob; Odgaard, Peter Fogh

    2011-01-01

    Wind turbines are inherently exposed to nonuniform wind fields with of wind shear, tower shadow, and possible wake contributions. Asymmetrical aerodynamic rotor loads are a consequence of such periodic, repetitive wind disturbances experienced by the blades. A controller may estimate and use this....... A simulation comparison betweeen the proposed controller and an industry-standard PID controller shows better mitigation of drive-train, blade and tower loads.......Wind turbines are inherently exposed to nonuniform wind fields with of wind shear, tower shadow, and possible wake contributions. Asymmetrical aerodynamic rotor loads are a consequence of such periodic, repetitive wind disturbances experienced by the blades. A controller may estimate and use...... this peculiar disturbance pattern to better attenuate loads and regulate power by controlling the blade pitch angles individually. A novel model predictive (MPC) approach for individual pitch control of wind turbines is proposed in this paper. A repetitive wind disturbance model is incorporated into the MPC...

  6. Predicting Faults in Wind Turbines Using SCADA Data

    DEFF Research Database (Denmark)

    Borchersen, Anders Bech; Larsen, Jesper Abildgaard; Stoustrup, Jakob

    2013-01-01

    The cost of operation and maintenance of wind turbines is a significant part of the overall cost of wind turbines. To reduce this cost a method for enabling early fault detection is proposed and tested in this paper. The method is taking advantage of the fact that wind turbines in wind farms are ...

  7. U.S. Department of Energy Regional Resource Centers Report: State of the Wind Industry in the Regions

    Energy Technology Data Exchange (ETDEWEB)

    Baranowski, Ruth [National Renewable Energy Lab. (NREL), Golden, CO (United St; Oteri, Frank [National Renewable Energy Lab. (NREL), Golden, CO (United St; Baring-Gould, Ian [National Renewable Energy Lab. (NREL), Golden, CO (United St; Tegen, Suzanne [National Renewable Energy Lab. (NREL), Golden, CO (United St

    2016-03-01

    The wind industry and the U.S. Department of Energy (DOE) are addressing technical challenges to increasing wind energy's contribution to the national grid (such as reducing turbine costs and increasing energy production and reliability), and they recognize that public acceptance issues can be challenges for wind energy deployment. Wind project development decisions are best made using unbiased information about the benefits and impacts of wind energy. In 2014, DOE established six wind Regional Resource Centers (RRCs) to provide information about wind energy, focusing on regional qualities. This document summarizes the status and drivers for U.S. wind energy development on regional and state levels. It is intended to be a companion to DOE's 2014 Distributed Wind Market Report, 2014 Wind Technologies Market Report, and 2014 Offshore Wind Market and Economic Analysis that provide assessments of the national wind markets for each of these technologies.

  8. Wind deployment in the United States: states, resources, policy, and discourse.

    Science.gov (United States)

    Wilson, Elizabeth J; Stephens, Jennie C

    2009-12-15

    A transformation in the way the United States produces and uses energy is needed to achieve greenhouse gas reduction targets for climate change mitigation. Wind power is an important low-carbon technology and the most rapidly growing renewable energy technology in the U.S. Despite recent advances in wind deployment, significant state-by-state variation in wind power distribution cannot be explained solely by wind resource patterns nor by state policy. Other factors embedded within the state-level socio-political context also contribute to wind deployment patterns. We explore this socio-political context in four U.S. states by integrating multiple research methods. Through comparative state-level analysis of the energy system, energy policy, and public discourse as represented in the media, we examine variation in the context for wind deployment in Massachusetts, Minnesota, Montana, and Texas. Our results demonstrate that these states have different patterns of wind deployment, are engaged in different debates about wind power, and appear to frame the risks and benefits of wind power in different ways. This comparative assessment highlights the complex variation of the state-level socio-political context and contributes depth to our understanding of energy technology deployment processes, decision-making, and outcomes.

  9. Optimal day-ahead wind-thermal unit commitment considering statistical and predicted features of wind speeds

    International Nuclear Information System (INIS)

    Sun, Yanan; Dong, Jizhe; Ding, Lijuan

    2017-01-01

    Highlights: • A day–ahead wind–thermal unit commitment model is presented. • Wind speed transfer matrix is formed to depict the sequential wind features. • Spinning reserve setting considering wind power accuracy and variation is proposed. • Verified study is performed to check the correctness of the program. - Abstract: The increasing penetration of intermittent wind power affects the secure operation of power systems and leads to a requirement of robust and economic generation scheduling. This paper presents an optimal day–ahead wind–thermal generation scheduling method that considers the statistical and predicted features of wind speeds. In this method, the statistical analysis of historical wind data, which represents the local wind regime, is first implemented. Then, according to the statistical results and the predicted wind power, the spinning reserve requirements for the scheduling period are calculated. Based on the calculated spinning reserve requirements, the wind–thermal generation scheduling is finally conducted. To validate the program, a verified study is performed on a test system. Then, numerical studies to demonstrate the effectiveness of the proposed method are conducted.

  10. Integrated resource planning - a long and winding road

    International Nuclear Information System (INIS)

    Reuter, A.L.

    1995-01-01

    The separation of Croatia from former Yugoslavia and the military turbulence at its borders during the last years caused a number of problems in the Croatian energy system. Resources for improving the situation are scarce. So it is necessary to plan the rehabilitation and modernization of the Croatian energy system in a way which includes all national resources and allocates these resources where they lead to the highest benefits to the national economy. In this paper it is shown that Integrated Resource Planning (IRP) is such a method which enables the rational use of national resources. Also presented in this paper is a transparent and rational procedure which allows the energy planner to support the decision maker in developing an energy policy under consideration of interests of affected groups. This procedure is called Structured Analysis Procedure and step by step leads from the problem formulation to the decision on which action is to be applied to solve the problem. (author)

  11. Generation of a wind and stability atlas for the optimized utilization of offshore wind resources in the North Sea Region

    Science.gov (United States)

    Drüke, Sonja; Steinfeld, Gerald; Heinemann, Detlev; Günther, Robert

    2014-05-01

    The European Wind Energy Association expects 150 GW of installed wind capacity offshore in Europe by the year 2030. However, detailed knowledge on the atmospheric conditions offshore is still lacking. Satellite-based instruments can provide at spatial information on sea surface temperature and near-surface winds only at a low temporal resolution. Continuous in-situ observations providing vertical information on the marine boundary-layer have only been available from a handful of offshore met masts since roughly ten years, a time period too short to determine the long-term (climatological) wind resource. The lack of spatially distributed, long-term measurements in offshore regions has led to the application of mesoscale models for the derivation of information on atmospheric conditions offshore. The technique of dynamical downscaling is used in order to derive information on the meso-gamma scale from reanalysis data on the meso-beta scale. The downscaled atmospheric data gives hints which sites might be especially interesting for wind energy. The attractiveness of a site cannot be determined from the mean wind speed alone. Other criteria such as the distribution of the wind speed or the atmospheric stability should be taken into account as well. Recent analysis of data from several offshore wind farms has shown the dependency of wind farm power outputs from atmospheric stability. In the framework of the EU-funded research project ClusterDesign (www.cluster-design.eu) a wind and stability atlas (WASA) for the North Sea region based on dynamical downscaling of 21 years (1992-2012) of CFSR data with the mesoscale model WRF has been derived. Surface boundary conditions for offshore sites have been derived from the OSTIA SST data set. The WASA presented here has a spatial resolution of 2 km and is based on 10 minutes data. The WASA is a NetCDF-file that provides information on how often a combination of a certain wind speed, wind direction, air density, stability

  12. Bird Mortaility at the Altamont Pass Wind Resource Area: March 1998--September 2001

    Energy Technology Data Exchange (ETDEWEB)

    Smallwood, K. S.; Thelander, C. G.

    2005-09-01

    Over the past 15 years, research has shown that wind turbines in the Altamont Pass Wind Resource Area (APWRA) kill many birds, including raptors, which are protected by the Migratory Bird Treaty Act (MBTA), the Bald and Golden Eagle Protection Act, and/or state and federal Endangered Species Acts. Early research in the APWRA on avian mortality mainly attempted to identify the extent of the problem. In 1998, however, the National Renewable Energy Laboratory (NREL) initiated research to address the causal relationships between wind turbines and bird mortality. NREL funded a project by BioResource Consultants to perform this research directed at identifying and addressing the causes of mortality of various bird species from wind turbines in the APWRA.With 580 megawatts (MW) of installed wind turbine generating capacity in the APWRA, wind turbines there provide up to 1 billion kilowatt-hours (kWh) of emissions-free electricity annually. By identifying and implementing new methods and technologies to reduce or resolve bird mortality in the APWRA, power producers may be able to increase wind turbine electricity production at the site and apply similar mortality-reduction methods at other sites around the state and country.

  13. Eight years of wind measurements from scatterometer for wind resource mapping in the Mediterranean Sea

    DEFF Research Database (Denmark)

    Furevik, Birgitte R.; Sempreviva, Anna Maria; Cavaleri, Luigi

    2011-01-01

    that the scatterometer is able to provide similar long-term statistics as available from buoy data, such as annual and monthly wind indexes. Such statistics is useful to give an overview of the climatology in the different areas. The correlation between QuikScat and in situ observations is degraded towards the coast...

  14. US East Coast offshore wind energy resources and their relationship to time-varying electricity demand

    Science.gov (United States)

    Dvorak, M. J.; Corcoran, B. A.; Ten Hoeve, J. E.; Jacobson, M. Z.; McIntyre, N.

    2011-12-01

    This study characterizes the annual-mean US East Coast (USEC) offshore wind energy (OWE) resource based on 5 years of skillful, high resolution mesoscale model (WRF-ARW) results at the turbine hub height of 90 m. Model output was validated buoys and offshore towers, which provides insight into the relative errors of forecasting winds in the region. The most suitable locations for OWE are prescribed, based on their wind resource, shallow bathymetry, low hurricane risk, and peak-power generation potential. The offshore region from Maine to Virginia was found to have exceptional overall resource the best wind resource, shallow water, and low hurricane risk. The region east of Long Island, NY to Cape Cod, MA has the best summertime peak resource, due to regional upwelling that often strengthens the sea breeze. Overall, the resource from Maine to Florida out to 200-m depth, using turbine capacity factor cutoffs of 45% and 40% is between 1175-1672 TWh (134-191 GW avg.). Between 30-42% of the electricity demand for the entire US (2009) could be provided using USEC OWE alone and 93-133% of Maine to Florida (2008) demand.

  15. Demand side resource operation on the Irish power system with high wind power penetration

    DEFF Research Database (Denmark)

    Keane, A.; Tuohy, A.; Meibom, Peter

    2011-01-01

    part of the power system plant mix and contribute to the flexible operation of a power system. A model for demand side resources is proposed here that captures its key characteristics for commitment and dispatch calculations. The model is tested on the all island Irish power system, and the operation...... of the model is simulated over one year in both a stochastic and deterministic mode, to illustrate the impact of wind and load uncertainty. The results illustrate that demand side resources can contribute to the efficient, flexible operation of systems with high penetrations of wind by replacing some......The utilisation of demand side resources is set to increase over the coming years with the advent of advanced metering infrastructure, home area networks and the promotion of increased energy efficiency. Demand side resources are proposed as an energy resource that, through aggregation, can form...

  16. The role of energy storage in accessing remote wind resources in the Midwest

    International Nuclear Information System (INIS)

    Lamy, Julian; Azevedo, Inês L.; Jaramillo, Paulina

    2014-01-01

    Replacing current generation with wind energy would help reduce the emissions associated with fossil fuel electricity generation. However, integrating wind into the electricity grid is not without cost. Wind power output is highly variable and average capacity factors from wind farms are often much lower than conventional generators. Further, the best wind resources with highest capacity factors are often located far away from load centers and accessing them therefore requires transmission investments. Energy storage capacity could be an alternative to some of the required transmission investment, thereby reducing capital costs for accessing remote wind farms. This work focuses on the trade-offs between energy storage and transmission. In a case study of a 200 MW wind farm in North Dakota to deliver power to Illinois, we estimate the size of transmission and energy storage capacity that yields the lowest average cost of generating and delivering electricity ($/MW h) from this farm. We find that transmission costs must be at least $600/MW-km and energy storage must cost at most $100/kW h in order for this application of energy storage to be economical. - Highlights: • We evaluate the break-even cost of energy storage to replace transmission. • We focus on a wind farm in North Dakota that must deliver power to Illinois. • Energy storage capital costs must be less than $100/kW h. • Transmission capital costs must be greater than $600/MW-km

  17. Avian Monitoring and Risk Assessment at the San Gorgonio Wind Resource Area

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, R.; Tom, J.; Neumann, N.; Erickson, W. P.; Strickland, M. D.; Bourassa, M.; Bay, K. J.; Sernka, K. J.

    2005-08-01

    The primary objective of this study at the San Gorgonio Wind Resource Area was to estimate and compare bird utilization, fatality rates, and the risk index among factors including bird taxonomic groups, wind turbine and reference areas, wind turbine sizes and types, and geographic locations. The key questions addressed to meet this objective include: (1) Are there any differences in the level of bird activity, called ''utilization rate'' or ''use'', with the operating wind plant and within the surrounding undeveloped areas (reference area)?; (2) Are there any differences in the rate of bird fatalities (or avian fatality) within the operating wind plant or the surrounding undeveloped areas (reference area)?; (3) Does bird use, fatality rates, or bird risk index vary according to the geographic location, type and size of wind turbine, and/or type of bird within the operating wind plant and surrounding undeveloped areas (reference area)?; and (4) How do raptor fatality rates at San Gorgonio compare to other wind projects with comparable data?

  18. Wind energy in Vietnam: Resource assessment, development status and future implications

    International Nuclear Information System (INIS)

    Nguyen, Khanh Q.

    2007-01-01

    The aim of this study is to estimate the technical potential of wind energy in Vietnam and discuss strategies for promoting the market penetration of wind energy in the country. For the wind resource assessment, a geographical information system (GIS)- assisted approach has been developed. It is found that Vietnam has a good potential for wind energy. About 31,000 km 2 of land area can be available for wind development in which 865 km 2 equivalents to a wind power of 3572 MW has a generation cost less than 6 US cents/kWh. The study also proves that wind energy could be a good solution for about 300,000 rural non-electrified households. While wind energy brings about ecological, economic and social benefits, it is only modestly exploited in Vietnam, where the main barrier is the lack of political impetus and a proper framework for promoting renewable energy. The priority task therefore is to set a target for renewable energy development and to find instruments to achieve such a target. The main instruments proposed here are setting feed-in tariff and providing investment incentives

  19. Short-term wind power prediction based on LSSVM–GSA model

    International Nuclear Information System (INIS)

    Yuan, Xiaohui; Chen, Chen; Yuan, Yanbin; Huang, Yuehua; Tan, Qingxiong

    2015-01-01

    Highlights: • A hybrid model is developed for short-term wind power prediction. • The model is based on LSSVM and gravitational search algorithm. • Gravitational search algorithm is used to optimize parameters of LSSVM. • Effect of different kernel function of LSSVM on wind power prediction is discussed. • Comparative studies show that prediction accuracy of wind power is improved. - Abstract: Wind power forecasting can improve the economical and technical integration of wind energy into the existing electricity grid. Due to its intermittency and randomness, it is hard to forecast wind power accurately. For the purpose of utilizing wind power to the utmost extent, it is very important to make an accurate prediction of the output power of a wind farm under the premise of guaranteeing the security and the stability of the operation of the power system. In this paper, a hybrid model (LSSVM–GSA) based on the least squares support vector machine (LSSVM) and gravitational search algorithm (GSA) is proposed to forecast the short-term wind power. As the kernel function and the related parameters of the LSSVM have a great influence on the performance of the prediction model, the paper establishes LSSVM model based on different kernel functions for short-term wind power prediction. And then an optimal kernel function is determined and the parameters of the LSSVM model are optimized by using GSA. Compared with the Back Propagation (BP) neural network and support vector machine (SVM) model, the simulation results show that the hybrid LSSVM–GSA model based on exponential radial basis kernel function and GSA has higher accuracy for short-term wind power prediction. Therefore, the proposed LSSVM–GSA is a better model for short-term wind power prediction

  20. An improved canopy wind model for predicting wind adjustment factors and wildland fire behavior

    Science.gov (United States)

    W. J. Massman; J. M. Forthofer; M. A. Finney

    2017-01-01

    The ability to rapidly estimate wind speed beneath a forest canopy or near the ground surface in any vegetation is critical to practical wildland fire behavior models. The common metric of this wind speed is the "mid-flame" wind speed, UMF. However, the existing approach for estimating UMF has some significant shortcomings. These include the assumptions that...

  1. Temporal and spatial complementarity of the wind and the solar resources in the Iberian Peninsula

    Science.gov (United States)

    Jerez, Sonia; Trigo, Ricardo M.; Sarsa, Antonio; Lorente-PLazas, Raquel; Pozo-Vázquez, David; Montávez, Juan Pedro

    2013-04-01

    Both Iberian countries (Portugal and Spain) are investing considerably in new wind and solar power plants to achieve a sustainable future, both in environmental and economic terms. Resource evaluation, aimed at optimizing the power generation according to the energy demand, is a mandatory requisite for the success of such a large amount of investments. However, this aim is difficult to attain due to the lack of lengthy and reliable observational datasets, implying poor spatial coverage. Hence, here we rely on a hindcast simulation spanning the period 1959-2007 and covering the whole Iberian Peninsula with resolution of 10 km, to retrieve the primary meteorological variables from which estimations of wind and solar power are done. Based on that, we have investigated the temporal (at the monthly timescale) and spatial complementarity of the wind and the solar resources in the Iberian Peninsula. The annual cycle of energy demand in Iberia shows two maxima centered in winter and summer and relatively smaller loads during the transitional seasons, with both the shape and the monthly values of this cycle having experienced small changes in the recent years. Since the annual cycle of wind (solar) power presents a clear maximum in winter (summer), it is immediate to infer that both cycles could be combined in order to achieve the shape required by the annual cycle of energy demand. Interannually, both resources show large variability in the winter months. Nevertheless, our results indicate that the monthly series of wind and solar power are strongly anticorrelated during winter and thus, both series could be also combined in order to achieve minimum interannual variability in the resulting wind-plus-solar production output. Moreover we found that this interannual complementarity is related, at least partially, to the multiple influence of the three main large-scale modes of climatic variability affecting Europe (NAO, EA and SCAND) since while their positive phases enhance

  2. Distributed Model Predictive Control of A Wind Farm for Optimal Active Power Control

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Guo, Qinglai

    2015-01-01

    , which combines the clustering, linear identification and pattern recognition techniques. The developed model, consisting of 47 affine dynamics, is verified by the comparison with a widely-used nonlinear wind turbine model. It can be used as a predictive model for the Model Predictive Control (MPC......This paper presents a dynamic discrete-time Piece- Wise Affine (PWA) model of a wind turbine for the optimal active power control of a wind farm. The control objectives include both the power reference tracking from the system operator and the wind turbine mechanical load minimization. Instead...... of partial linearization of the wind turbine model at selected operating points, the nonlinearities of the wind turbine model are represented by a piece-wise static function based on the wind turbine system inputs and state variables. The nonlinearity identification is based on the clustering-based algorithm...

  3. Wind and Solar Energy Resource Assessment for Navy Installations in the Midwestern US

    Science.gov (United States)

    Darmenova, K.; Apling, D.; Higgins, G. J.; Carnes, J.; Smith, C.

    2012-12-01

    A stable supply of energy is critical for sustainable economic development and the ever-increasing demand for energy resources drives the need for alternative weather-driven renewable energy solutions such as solar and wind-generated power. Recognizing the importance of energy as a strategic resource, the Department of the Navy has focused on energy efficient solutions aiming to increase tactical and shore energy security and reduce greenhouse gas emissions. Implementing alternative energy solutions will alleviate the Navy installations demands on the National power grid, however transitioning to renewable energy sources is a complex multi-stage process that involves initial investment in resource assessment and feasibility of building solar and wind power systems in Navy's facilities. This study focuses on the wind and solar energy resource assessment for Navy installations in the Midwestern US. We use the dynamically downscaled datasets at 12 km resolution over the Continental US generated with the Weather Research and Forecasting (WRF) model to derive the wind climatology in terms of wind speed, direction, and wind power at 20 m above the surface for 65 Navy facilities. In addition, we derived the transmissivity of the atmosphere, diffuse radiation fraction, cloud cover and seasonal energy potential for a zenith facing surface with unobstructed horizon for each installation location based on the results of a broadband radiative transfer model and our cloud database based on 17-years of GOES data. Our analysis was incorporated in a GIS framework in combination with additional infrastructure data that enabled a synergistic resource assessment based on the combination of climatological and engineering factors.

  4. Offshore Wind Resource, Cost, and Economic Potential in the State of Maine

    Energy Technology Data Exchange (ETDEWEB)

    Musial, Walter D. [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2018-02-12

    This report provides information for decision-makers about floating offshore wind technologies in the state of Maine. It summarizes research efforts performed at the National Renewable Energy Laboratory between 2015 and 2017 to analyze the resource potential, cost of offshore wind, and economic potential of offshore wind from four primary reports: Musial et al. (2016); Beiter et al. (2016, 2017); and Mone et al. (unpublished). From Musial et al. (2016), Maine's technical offshore wind resource potential ranked seventh in the nation overall with more than 411 terawatt-hours/year of offshore resource generating potential. Although 90% of this wind resource is greater than 9.0-meters-per-second average velocity, most of the resource is over deep water, where floating wind technology is needed. Levelized cost of energy and levelized avoided cost of energy were computed to estimate the unsubsidized 'economic potential' for Maine in the year 2027 (Beiter et al. 2016, 2017). The studies found that Maine may have 65 gigawatts of economic potential by 2027, the highest of any U.S. state. Bottom-line costs for the Aqua Ventus project, which is part of the U.S. Department of Energy's Advanced Technology Demonstration project, were released from a proprietary report written by NREL in 2016 for the University of Maine (Mone et al. unpublished). The report findings were that economies of scale and new technology advancements lowered the cost from $300/megawatt-hour (MWh) for the two-turbine 12-megawatt (MW) Aqua Ventus 1 project, to $126/MWh for the commercial-scale, 498-MW Aqua Ventus-2 project. Further cost reductions to $77/MWh were found when new technology advancements were applied for the 1,000-MW Aqua Ventus-3 project in 2030. No new analysis was conducted for this report.

  5. On Practical tuning of Model Uncertainty in Wind Turbine Model Predictive Control

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Hovgaard, Tobias

    2015-01-01

    model of a wind turbine. In this paper, we investigate the impact of this approach on the performance of a wind turbine. In particular, we focus on the most non-linear operational ranges of a wind turbine. The MPC controller is designed for, tested, and evaluated at an industrial high fidelity wind......Model predictive control (MPC) has in previous works been applied on wind turbines with promising results. These results apply linear MPC, i.e., linear models linearized at different operational points depending on the wind speed. The linearized models are derived from a nonlinear first principles...... parameters in the linearized model to fit the actual physical wind turbine behavior. We evaluate the MPC with the different model parameters, and show that, e.g., over-speed events are avoided, and a good performance of the wind turbine control is obtained....

  6. Effect of accuracy of wind power prediction on power system operator

    Science.gov (United States)

    Schlueter, R. A.; Sigari, G.; Costi, T.

    1985-01-01

    This research project proposed a modified unit commitment that schedules connection and disconnection of generating units in response to load. A modified generation control is also proposed that controls steam units under automatic generation control, fast responding diesels, gas turbines and hydro units under a feedforward control, and wind turbine array output under a closed loop array control. This modified generation control and unit commitment require prediction of trend wind power variation one hour ahead and the prediction of error in this trend wind power prediction one half hour ahead. An improved meter for predicting trend wind speed variation is developed. Methods for accurately simulating the wind array power from a limited number of wind speed prediction records was developed. Finally, two methods for predicting the error in the trend wind power prediction were developed. This research provides a foundation for testing and evaluating the modified unit commitment and generation control that was developed to maintain operating reliability at a greatly reduced overall production cost for utilities with wind generation capacity.

  7. Effect of accuracy of wind power prediction on power system operator

    Science.gov (United States)

    Schlueter, R. A.; Sigari, G.; Costi, T.

    1985-06-01

    This research project proposed a modified unit commitment that schedules connection and disconnection of generating units in response to load. A modified generation control is also proposed that controls steam units under automatic generation control, fast responding diesels, gas turbines and hydro units under a feedforward control, and wind turbine array output under a closed loop array control. This modified generation control and unit commitment require prediction of trend wind power variation one hour ahead and the prediction of error in this trend wind power prediction one half hour ahead. An improved meter for predicting trend wind speed variation is developed. Methods for accurately simulating the wind array power from a limited number of wind speed prediction records was developed. Finally, two methods for predicting the error in the trend wind power prediction were developed. This research provides a foundation for testing and evaluating the modified unit commitment and generation control that was developed to maintain operating reliability at a greatly reduced overall production cost for utilities with wind generation capacity.

  8. Probabilistic modelling for forecasting the wind energy resource at the seasonal horizon

    Science.gov (United States)

    Alonzo, Bastien; Drobinski, Philippe; Plougonven, Riwal; Tankov, Peter

    2017-04-01

    We build and evaluate a probabilistic model designed for forecasting the distribution of the daily mean wind speed at the seasonal timescale. On such long-term timescales, numerical weather prediction models can bring valuable information on the large-scale circulation of the atmosphere which strongly influences surface wind speed. As an example, variations in the position of the storm track over the Atlantic directly impact surface winds in the North of France in autumn and winter. The model aims at predicting the daily mean wind speed distribution knowing the large scale situation of the atmosphere which is summarized by an index derived from the multi-polynomial regression between the 10 first Principal Components of the 500hPa geopotential height and the daily mean wind speed. The conditionnal probability density function of the wind speed knowing the index is estimated by a gaussian kernel density estimation over 20 years of daily reanalysis data. Evaluating the probabilistic model on a validation period of 15 years, we show that it is at least as well calibrated as the seasonal climatology which can be taken as a first guess prediction at such long-term horizon. We also show that the model is 20% sharper than the climatology in average, due to a less pronounced seasonal variability of the confidence interval width. We use the ECMWF seasonal forecast ensemble in order to predict the daily mean wind speed distribution at the seasonal timescale. The ensemble forecast, from which the index is derived, displays a growing uncertainty with time leading to an increase of the confidence interval width predicted by the probabilistic model. We show that the model remains sharper than the climatology at the monthly horizon, but tends to the climatological interval width after 30 days.

  9. How Many Model Evaluations Are Required To Predict The AEP Of A Wind Power Plant?

    International Nuclear Information System (INIS)

    Murcia, J P; Réthoré, P E; Natarajan, A; Sørensen, J D

    2015-01-01

    Wind farm flow models have advanced considerably with the use of large eddy simulations (LES) and Reynolds averaged Navier-Stokes (RANS) computations. The main limitation of these techniques is their high computational time requirements; which makes their use for wind farm annual energy production (AEP) predictions expensive. The objective of the present paper is to minimize the number of model evaluations required to capture the wind power plant's AEP using stationary wind farm flow models. Polynomial chaos techniques are proposed based on arbitrary Weibull distributed wind speed and Von Misses distributed wind direction. The correlation between wind direction and wind speed are captured by defining Weibull-parameters as functions of wind direction. In order to evaluate the accuracy of these methods the expectation and variance of the wind farm power distributions are compared against the traditional binning method with trapezoidal and Simpson's integration rules.The wind farm flow model used in this study is the semi-empirical wake model developed by Larsen [1]. Three test cases are studied: a single turbine, a simple and a real offshore wind power plant. A reduced number of model evaluations for a general wind power plant is proposed based on the convergence of the present method for each case. (paper)

  10. Impacts of climate change on wind energy resources in France: a regionalization study

    International Nuclear Information System (INIS)

    Najac, J.

    2008-11-01

    In this work, we study the impact of climate change on surface winds in France and draw conclusions concerning wind energy resources. Because of their coarse spatial resolution, climate models cannot properly reproduce the spatial variability of surface winds. Thus, 2 down-scaling methods are developed in order to regionalize an ensemble of climate scenarios: a statistical method based on weather typing and a statistic-dynamical method that resorts to high resolution mesoscale modelling. By 2050, significant but relatively small changes are depicted with, in particular, a decrease of the wind speed in the southern and an increase in the northern regions of France. The use of other down-scaling methods enables us to study several uncertainty sources: it appears that most of the uncertainty is due to the climate models. (author)

  11. Coordinated Voltage Control of a Wind Farm based on Model Predictive Control

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Guo, Qinglai

    2016-01-01

    This paper presents an autonomous wind farm voltage controller based on Model Predictive Control (MPC). The reactive power compensation and voltage regulation devices of the wind farm include Static Var Compensators (SVCs), Static Var Generators (SVGs), Wind Turbine Generators (WTGs) and On...... are calculated based on an analytical method to improve the computation efficiency and overcome the convergence problem. Two control modes are designed for both voltage violated and normal operation conditions. A wind farm with 20 wind turbines was used to conduct case studies to verify the proposed coordinated...

  12. Opportunities for wind resources in the future competitive California power market

    International Nuclear Information System (INIS)

    Sezgen, O.; Marnay, C.; Bretz, S.; Markel, R.; Wiser, R.

    1998-01-01

    The goal of this work is to evaluate the profitability of wind development in the future competitive California power market. The viability of possible wind sites is assessed using a geographic information system (GIS) to determine the cost of development and Elfin, an electric utility production costing and capacity expansion model, to estimate the possible revenues and profits of wind farms at the sites. This approach improves on a simple profitability calculation by using site specific development cost calculations and by taking the effect of time varying market prices on revenues into account. The first component of the work is the characterization of wind resources suitable for use in production costing and capacity expansion models such as Elfin that are capable of simulating competitive electricity markets. An improved representation of California wind resources is built, using information collected by the California Energy Commission in previous site evaluations, and by using a GIS approach to estimating development costs at 36 specific sites. These sites, which have been identified as favorable for wind development, are placed on Digital Elevation Models and development costs are calculated based on distances to roads and transmission lines. GIS is also used to develop the potential capacity at each site by making use of the physical characteristics of the terrain, such as ridge lengths. In the second part of the effort, using a previously developed algorithm for simulating competitive entry to the California electricity market, Elfin is used to gauge the viability of wind farms at the 36 sites. The results of this exercise are forecasts of profitable development levels at each site and the effects of these developments on the electricity system as a whole. Results suggest that by the year 2030, about 7.5 GW of potential wind capacity can be profitably developed assuming rising natural gas prices. This example demonstrates that an analysis based on a

  13. Validation of Updated State Wind Resource Maps for the United States: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Schwartz, M.; Elliott, D.

    2004-07-01

    The National Renewable Energy Laboratory (NREL) has coordinated the validation of updated state wind resource maps for multiple regions of the United States. The purpose of the validation effort is to produce the best map possible within fairly stringent time constraints.

  14. Importance of thermal effects and sea surface roughness for offshore wind resource assessment

    DEFF Research Database (Denmark)

    Lange, B.; Larsen, Søren Ejling; Højstrup, Jørgen

    2004-01-01

    -Obukhov theory, a simple correction method to account for this effect has been developed and is tested in the same way. The models for the estimation of the sea surface roughness were found to lead only to small differences. For the purpose of wind resource assessment, even the assumption of a constant roughness...

  15. Predicting stillbirth in a low resource setting

    NARCIS (Netherlands)

    Kayode, Gbenga A; Grobbee, Diederick E; Amoakoh-Coleman, Mary; Adeleke, Ibrahim Taiwo; Ansah, Evelyn; de Groot, Joris A H; Klipstein-Grobusch, Kerstin

    2016-01-01

    BACKGROUND: Stillbirth is a major contributor to perinatal mortality and it is particularly common in low- and middle-income countries, where annually about three million stillbirths occur in the third trimester. This study aims to develop a prediction model for early detection of pregnancies at

  16. Hierarchical Model Predictive Control for Resource Distribution

    DEFF Research Database (Denmark)

    Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob

    2010-01-01

    This paper deals with hierarchichal model predictive control (MPC) of distributed systems. A three level hierachical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level of autonomous...

  17. Use of the WEST-1 wind turbine simulator to predict blade fatigue load distribution

    Science.gov (United States)

    Janetzke, D. C.

    1983-01-01

    To test the ability of WEST-1 to predict blade fatigue load distribution, actual wind signals were fed into the simulator and the response data were recorded and processed in the same manner as actual wind turbine data. The WEST-1 simulator was operated in a stable, unattended mode for six hours. The probability distribution of the cyclic flatwise bending moment for the blade was comparable to that for an actual wind turbine in winds with low turbulence. The input from a stationary anemometer was found to be inadequate for use in the prediction of fatigue load distribution for blade design purposes and modifications are necessary.

  18. The Small Wind Energy Estimation Tool (SWEET –a practical application for a complicated resource

    Directory of Open Access Journals (Sweden)

    Keith Sunderland

    2013-10-01

    Full Text Available Of the forms of renewable energy available, wind energy is at the forefront of the European (and Irish green initiative with wind farms supplying a significant proportion of electrical energy demand. Increasingly, this type of distributed generation (DG represents a “paradigm shift” towards increased decentralisation of energy supply. However, because of the distances of most DG from urban areas where demand is greatest, there is a loss of efficiency. One possible solution, placing smaller wind energy systems in urban areas, faces significant challenges. However, if a renewable solution to increasing energy demand is to be achieved, energy conversion systems in cities, where populations are concentrated, must be considered. That said, assessing the feasibility of small/micro wind energy systems within the built environment is still a major challenge. These systems are aerodynamically rough and heterogeneous surfaces create complex flows that disrupt the steady-state conditions ideal for the operation of small wind turbines. In particular, a considerable amount of uncertainty is attributable to the lack of understanding concerning how turbulence within urban environments affects turbine productivity. This paper addresses some of these issues by providing an improved understanding of the complexities associated with wind energy prediction. This research used detailed wind observations to model its turbulence characteristics. The data was obtained using a sonic anemometer that measures wind speed along three orthogonal axes to resolve the wind vector at a temporal resolution of 10Hz. That modelling emphasises the need for practical solutions by optimising standard meteorological observations of mean speeds, and associated standard deviations, to facilitate an improved appreciation of turbulence. The results of the modelling research are incorporated into a practical tool developed in EXCEL, namely the Small Wind Energy Estimation Tool (SWEET

  19. Development of Wind Farm AEP Prediction Program Considering Directional Wake Effect

    Energy Technology Data Exchange (ETDEWEB)

    Yang, Kyoungboo; Cho, Kyungho; Huh, Jongchul [Jeju Nat’l Univ., Jeju (Korea, Republic of)

    2017-07-15

    For accurate AEP prediction in a wind farm, it is necessary to effectively calculate the wind speed reduction and the power loss due to the wake effect in each wind direction. In this study, a computer program for AEP prediction considering directional wake effect was developed. The results of the developed program were compared with the actual AEP of the wind farm and the calculation result of existing commercial software to confirm the accuracy of prediction. The applied equations are identical with those of commercial software based on existing theories, but there is a difference in the calculation process of the detection of the wake effect area in each wind direction. As a result, the developed program predicted to be less than 1% of difference to the actual capacity factor and showed more than 2% of better results compared with the existing commercial software.

  20. Increasing the competitiveness of wind energy. New technologies for advanced wind predictability

    International Nuclear Information System (INIS)

    Bertolotti, Fabio

    2013-01-01

    The performance of thermal and nuclear power plants is assessed routinely and precisely, whereas the performance assessment of wind turbines is lagging far behind. This increases operational costs, reduces energy capture, and makes wind energy less competitive. The paper presents a technology and system with improved 24-h power forecasting, as well as condition monitoring of the rotor blades. The system can be employed by any wind power plant and offers potentials to increase the competitiveness of the power industry. (orig.)

  1. Increasing the competitiveness of wind energy. New technologies for advanced wind predictability

    Energy Technology Data Exchange (ETDEWEB)

    Bertolotti, Fabio [SSB Wind Systems GmbH und Co. KG, Salzbergen (Germany). Research and Technology

    2013-10-01

    The performance of thermal and nuclear power plants is assessed routinely and precisely, whereas the performance assessment of wind turbines is lagging far behind. This increases operational costs, reduces energy capture, and makes wind energy less competitive. The paper presents a technology and system with improved 24-h power forecasting, as well as condition monitoring of the rotor blades. The system can be employed by any wind power plant and offers potentials to increase the competitiveness of the power industry. (orig.)

  2. Prediction of wind power potential by wind speed probability distribution in a hilly terrain near Bh

    Energy Technology Data Exchange (ETDEWEB)

    Ahmed, Siraj; Diwakar, Nilesh

    2010-09-15

    Daily wind speed data in metre per second and its direction of flow in degree were recorded from of the India Meteorological Department for a site near the Bhopal Airport for the period of eleven years. The influence of roughness of the terrain, obstacles and topography in terms of contour for the area were also taken into consideration. These data were analysed using WAsP programme and regional wind climate of the area was determined. It is seen from the analysis of the wind speed data and keeping the topographical variation of terrain, exploitable wind speed is experienced at 50 m.

  3. Offshore wind power resource assessment using Oceansat-2 scatterometer data at a regional scale

    International Nuclear Information System (INIS)

    Gadad, Sanjeev; Deka, Paresh Chandra

    2016-01-01

    Highlights: • Accuracy assessment of Oceansat-2 scatterometer (OSCAT) winds by the in situ real-time ship observations for study area. • OSCAT data for two years (2011 and 2012) were used to evaluate the offshore wind power potential for the Karnataka state. • Wind speed and power atlases are developed to study the spatial distribution over study area. • 9,091 MW potential was estimated using 5 MW wind turbine in the Monopile region. • Recommend development of 10% of the estimated potential, 116% of energy deficit for 2012–13 can be met. - Abstract: In the offshore region the scarcity of in situ wind data in space proves to be a major setback for wind power potential assessments. Satellite data effectively overcomes this setback by providing continuous and total spatial coverage. The study intends to assess the offshore wind power resource of the Karnataka state, which is located on the west coast of India. Oceansat-2 scatterometer (OSCAT) wind data and GIS based methodology were adopted in the study. The OSCAT data accuracy was assessed using INCOIS Realtime All Weather Station (IRAWS) data. Wind speed maps at 10 m, 90 m and wind power density maps using OSCAT data were developed to understand the spatial distribution of winds over the study area. Bathymetric map was developed based on the available foundation types and demarking various exclusion zones to help in minimizing conflicts. The wind power generation capacity estimation performed using REpower 5 MW turbine, based on the water depth classes was found to be 9,091 MW in Monopile (0–35 m), 11,709 MW in Jacket (35–50 m), 23,689 MW in Advanced Jacket (50–100 m) and 117,681 MW in Floating (100–1000 m) foundation technology. In Indian scenario major thrust for wind farm development in Monopile region is required. Therefore as first phase of development, if 10% of the estimated potential in the region can be developed then, 116% of energy deficit for FY 2011–12 could be met. Also, up to 79

  4. Application of a ray theory model to the prediction of noise emissions from isolated wind turbines and wind parks

    International Nuclear Information System (INIS)

    Prospathopoulos, John M.; Voutsinas, Spyros G.

    2006-01-01

    Various propagation models have been developed to estimate the level of noise near residential areas. Predictions and measurements have proven that proper modelling of the propagation medium is of particular importance. In the present work, calculations are performed using a ray theory methodology. The ray trajectory and transport equations are derived from the linear acoustics equations for a moving medium in three dimensions. Ground and atmospheric absorption, wave refraction and diffraction and atmospheric turbulence are taken into account by introducing appropriate coefficients in the equations. In the case of a wind turbine (W/T) it is assumed that noise is produced by a point source located at the rotor centre. Given the sound power spectrum, the noise spectrum at the receiver is obtained by solving the axisymmetric propagation problem. The procedure consists of (a) finding the eigenrays, (b) calculating the energy losses along the eigenrays and (c) synthesizing the sound pressure level (SPL) by superposing the contributions of the eigenrays. In the case of a wind park the total SPL is calculated by superposing the contributions of all W/Ts. Application is made to five cases of isolated W/Ts in terrains of varying complexity. In flat or even smooth terrain the predictions agree well with the measurements. In complex terrain the predictions can be considered satisfactory, taking into account the assumption of constant wind velocity profile. Application to a wind park shows clearly the influence of the terrain on the wind velocity and consequently on the SPL. (Author)

  5. Numerical prediction of wind loads on low buildings | Ahmad ...

    African Journals Online (AJOL)

    In the present study, 2-D numerical simulation of wind loads on low-rise buildings has been carried out. The simulation was carried out under FLUENT package environment in which full-scale Reynolds number, boundary layer and turbulence properties have been simulated. Wind loading effect numerically obtained on flat ...

  6. LONG TERM WIND SPEED PREDICTION USING WAVELET COEFFICIENTS AND SOFT COMPUTING

    Directory of Open Access Journals (Sweden)

    Manju Khanna

    2016-10-01

    Full Text Available In the past researches, scholars have carried out short-term prediction for wind speed. The present work deals with long-term wind speed prediction, required for hybrid power generation design and contract planning. As the total database is quite large for long-term prediction, feature extraction of data by application of Lifting wavelet coefficients is exploited, along with soft computing techniques for time series data, which is scholastic in nature.

  7. On wake modeling, wind-farm gradients, and AEP predictions at the Anholt wind farm

    Directory of Open Access Journals (Sweden)

    A. Peña

    2018-04-01

    Full Text Available We investigate wake effects at the Anholt offshore wind farm in Denmark, which is a farm experiencing strong horizontal wind-speed gradients because of its size and proximity to land. Mesoscale model simulations are used to study the horizontal wind-speed gradients over the wind farm. From analysis of the mesoscale simulations and supervisory control and data acquisition (SCADA, we show that for westerly flow in particular, there is a clear horizontal wind-speed gradient over the wind farm. We also use the mesoscale simulations to derive the undisturbed inflow conditions that are coupled with three commonly used wake models: two engineering approaches (the Park and G. C. Larsen models and a linearized Reynolds-averaged Navier–Stokes approach (Fuga. The effect of the horizontal wind-speed gradient on annual energy production estimates is not found to be critical compared to estimates from both the average undisturbed wind climate of all turbines' positions and the undisturbed wind climate of a position in the middle of the wind farm. However, annual energy production estimates can largely differ when using wind climates at positions that are strongly influenced by the horizontal wind-speed gradient. When looking at westerly flow wake cases, where the impact of the horizontal wind-speed gradient on the power of the undisturbed turbines is largest, the wake models agree with the SCADA fairly well; when looking at a southerly flow case, where the wake losses are highest, the wake models tend to underestimate the wake loss. With the mesoscale-wake model setup, we are also able to estimate the capacity factor of the wind farm rather well when compared to that derived from the SCADA. Finally, we estimate the uncertainty of the wake models by bootstrapping the SCADA. The models tend to underestimate the wake losses (the median relative model error is 8.75 % and the engineering wake models are as uncertain as Fuga. These results are specific for

  8. Data estimation and prediction for natural resources public data

    Science.gov (United States)

    Hans T. Schreuder; Robin M. Reich

    1998-01-01

    A key product of both Forest Inventory and Analysis (FIA) of the USDA Forest Service and the Natural Resources Inventory (NRI) of the Natural Resources Conservation Service is a scientific data base that should be defensible in court. Multiple imputation procedures (MIPs) have been proposed both for missing value estimation and prediction of non-remeasured cells in...

  9. Combined wind, hydropower and photovoltaic systems for generation of electric power and control of water resources

    International Nuclear Information System (INIS)

    Abid, M.; Karimov, K.S.; Akhmedov, K.M.

    2011-01-01

    In this paper the present day energy consumption and potentialities of utilization of wind- and hydropower resources in some Central and Southern Asian Republics, in particular, in the Republic of Tajikistan, Kyrgyzstan and Pakistan are presented. The maximum consumption of electric power is observed in winter time when hydropower is the minimum, but wind power is the maximum. At the same time water is needed mostly in summer time for irrigation and in winter time for generation of electric power. This results in conflicts between countries that utilize water mostly for irrigation and those which use water for generation of electric power. It is proposed that the utilization of water with the supplement of wind and solar energy will facilitate the proper and efficient management of water resources in Central Asia. In the future in Tajikistan, wind power systems with a capacity of 30-100 MW and more will be installed, providing power balance of the country in winter; hence saving water in reservoirs, especially in drought years. This will provide the integration of electricity generated by wind, hydroelectric power and photovoltaic system in the unified energy system of the country. (author)

  10. Wind erosion in semiarid landscapes: Predictive models and remote sensing methods for the influence of vegetation

    Science.gov (United States)

    Musick, H. Brad

    1993-01-01

    The objectives of this research are: to develop and test predictive relations for the quantitative influence of vegetation canopy structure on wind erosion of semiarid rangeland soils, and to develop remote sensing methods for measuring the canopy structural parameters that determine sheltering against wind erosion. The influence of canopy structure on wind erosion will be investigated by means of wind-tunnel and field experiments using structural variables identified by the wind-tunnel and field experiments using model roughness elements to simulate plant canopies. The canopy structural variables identified by the wind-tunnel and field experiments as important in determining vegetative sheltering against wind erosion will then be measured at a number of naturally vegetated field sites and compared with estimates of these variables derived from analysis of remotely sensed data.

  11. Growth curves and sustained commissioning modelling of renewable energy: Investigating resource constraints for wind energy

    International Nuclear Information System (INIS)

    Davidsson, Simon; Grandell, Leena; Wachtmeister, Henrik; Höök, Mikael

    2014-01-01

    Several recent studies have proposed fast transitions to energy systems based on renewable energy technology. Many of them dismiss potential physical constraints and issues with natural resource supply, and do not consider the growth rates of the individual technologies needed or how the energy systems are to be sustained over longer time frames. A case study is presented modelling potential growth rates of the wind energy required to reach installed capacities proposed in other studies, taking into account the expected service life of wind turbines. A sustained commissioning model is proposed as a theoretical foundation for analysing reasonable growth patterns for technologies that can be sustained in the future. The annual installation and related resource requirements to reach proposed wind capacity are quantified and it is concluded that these factors should be considered when assessing the feasibility, and even the sustainability, of fast energy transitions. Even a sustained commissioning scenario would require significant resource flows, for the transition as well as for sustaining the system, indefinitely. Recent studies that claim there are no potential natural resource barriers or other physical constraints to fast transitions to renewable energy appear inadequate in ruling out these concerns. - Highlights: • Growth rates and service life is important when evaluating energy transitions. • A sustained commissioning model is suggested for analysing renewable energy. • Natural resource requirements for renewable energy are connected to growth rates. • Arguments by recent studies ruling out physical constraints appear inadequate

  12. Estimation of uncertainty of wind energy predictions with application to weather routing and wind power generation

    CERN Document Server

    Zastrau, David

    2017-01-01

    Wind drives in combination with weather routing can lower the fuel consumption of cargo ships significantly. For this reason, the author describes a mathematical method based on quantile regression for a probabilistic estimate of the wind propulsion force on a ship route.

  13. Enhanced Voltage Control of VSC-HVDC Connected Offshore Wind Farms Based on Model Predictive Control

    OpenAIRE

    Guo, Yifei; Gao, Houlei; Wu, Qiuwei; Zhao, Haoran; Østergaard, Jacob; Shahidehpour, Mohammad

    2018-01-01

    This paper proposes an enhanced voltage control strategy (EVCS) based on model predictive control (MPC) for voltage source converter based high voltage direct current (VSCHVDC) connected offshore wind farms (OWFs). In the proposed MPC based EVCS, all wind turbine generators (WTGs) as well as the wind farm side VSC are optimally coordinated to keep voltages within the feasible range and reduce system power losses. Considering the high ratio of the OWF collector system, the effects of active po...

  14. An adaptive short-term prediction scheme for wind energy storage management

    International Nuclear Information System (INIS)

    Blonbou, Ruddy; Monjoly, Stephanie; Dorville, Jean-Francois

    2011-01-01

    Research highlights: → We develop a real time algorithm for grid-connected wind energy storage management. → The method aims to guarantee, with ±5% error margin, the power sent to the grid. → Dynamic scheduling of energy storage is based on short-term energy prediction. → Accurate predictions reduce the need in storage capacity. -- Abstract: Efficient forecasting scheme that includes some information on the likelihood of the forecast and based on a better knowledge of the wind variations characteristics along with their influence on power output variation is of key importance for the optimal integration of wind energy in island's power system. In the Guadeloupean archipelago (French West-Indies), with a total wind power capacity of 25 MW; wind energy can represent up to 5% of the instantaneous electricity production. At this level, wind energy contribution can be equivalent to the current network primary control reserve, which causes balancing difficult. The share of wind energy is due to grow even further since the objective is set to reach 118 MW by 2020. It is an absolute evidence for the network operator that due to security concerns of the electrical grid, the share of wind generation should not increase unless solutions are found to solve the prediction problem. The University of French West-Indies and Guyana has developed a short-term wind energy prediction scheme that uses artificial neural networks and adaptive learning procedures based on Bayesian approach and Gaussian approximation. This paper reports the results of the evaluation of the proposed approach; the improvement with respect to the simple persistent prediction model was globally good. A discussion on how such a tool combined with energy storage capacity could help to smooth the wind power variation and improve the wind energy penetration rate into island utility network is also proposed.

  15. Wind energy

    International Nuclear Information System (INIS)

    Anon.

    1992-01-01

    This chapter discusses the role wind energy may have in the energy future of the US. The topics discussed in the chapter include historical aspects of wind energy use, the wind energy resource, wind energy technology including intermediate-size and small wind turbines and intermittency of wind power, public attitudes toward wind power, and environmental, siting and land use issues

  16. Short-Term Wind Speed Prediction Using EEMD-LSSVM Model

    Directory of Open Access Journals (Sweden)

    Aiqing Kang

    2017-01-01

    Full Text Available Hybrid Ensemble Empirical Mode Decomposition (EEMD and Least Square Support Vector Machine (LSSVM is proposed to improve short-term wind speed forecasting precision. The EEMD is firstly utilized to decompose the original wind speed time series into a set of subseries. Then the LSSVM models are established to forecast these subseries. Partial autocorrelation function is adopted to analyze the inner relationships between the historical wind speed series in order to determine input variables of LSSVM models for prediction of every subseries. Finally, the superposition principle is employed to sum the predicted values of every subseries as the final wind speed prediction. The performance of hybrid model is evaluated based on six metrics. Compared with LSSVM, Back Propagation Neural Networks (BP, Auto-Regressive Integrated Moving Average (ARIMA, combination of Empirical Mode Decomposition (EMD with LSSVM, and hybrid EEMD with ARIMA models, the wind speed forecasting results show that the proposed hybrid model outperforms these models in terms of six metrics. Furthermore, the scatter diagrams of predicted versus actual wind speed and histograms of prediction errors are presented to verify the superiority of the hybrid model in short-term wind speed prediction.

  17. The effects of tropical wind data on the prediction of ultralong waves

    Science.gov (United States)

    Baker, W. E.

    1981-01-01

    The influence of tropical wind data on the prediction of planetary waves were studied. Two assimilation experiments were performed, one with and one without FGGE tropical winds. The planetary wave error was then analyzed in 72 h forecasts from the initial conditions provided by the two assimilations.

  18. High-altitude wind prediction and measurement technology assessment

    Science.gov (United States)

    2009-06-30

    The principles and operational characteristics of balloon and radar-based techniques for measuring upper air winds in support of launches and recoveries are presented. Though either a balloon or radar system could serve as a standalone system, the sa...

  19. A GLOBAL ASSESSMENT OF SOLAR ENERGY RESOURCES: NASA's Prediction of Worldwide Energy Resources (POWER) Project

    Science.gov (United States)

    Zhang, T.; Stackhouse, P. W., Jr.; Chandler, W.; Hoell, J. M.; Westberg, D.; Whitlock, C. H.

    2010-12-01

    NASA's POWER project, or the Prediction of the Worldwide Energy Resources project, synthesizes and analyzes data on a global scale. The products of the project find valuable applications in the solar and wind energy sectors of the renewable energy industries. The primary source data for the POWER project are NASA's World Climate Research Project (WCRP)/Global Energy and Water cycle Experiment (GEWEX) Surface Radiation Budget (SRB) project (Release 3.0) and the Global Modeling and Assimilation Office (GMAO) Goddard Earth Observing System (GEOS) assimilation model (V 4.0.3). Users of the POWER products access the data through NASA's Surface meteorology and Solar Energy (SSE, Version 6.0) website (http://power.larc.nasa.gov). Over 200 parameters are available to the users. The spatial resolution is 1 degree by 1 degree now and will be finer later. The data covers from July 1983 to December 2007, a time-span of 24.5 years, and are provided as 3-hourly, daily and monthly means. As of now, there have been over 18 million web hits and over 4 million data file downloads. The POWER products have been systematically validated against ground-based measurements, and in particular, data from the Baseline Surface Radiation Network (BSRN) archive, and also against the National Solar Radiation Data Base (NSRDB). Parameters such as minimum, maximum, daily mean temperature and dew points, relative humidity and surface pressure are validated against the National Climate Data Center (NCDC) data. SSE feeds data directly into Decision Support Systems including RETScreen International clean energy project analysis software that is written in 36 languages and has greater than 260,000 users worldwide.

  20. Wind energy prospecting: socio-economic value of a new wind resource assessment technique based on a NASA Earth science dataset

    Science.gov (United States)

    Vanvyve, E.; Magontier, P.; Vandenberghe, F. C.; Delle Monache, L.; Dickinson, K.

    2012-12-01

    Wind energy is amongst the fastest growing sources of renewable energy in the U.S. and could supply up to 20 % of the U.S power production by 2030. An accurate and reliable wind resource assessment for prospective wind farm sites is a challenging task, yet is crucial for evaluating the long-term profitability and feasibility of a potential development. We have developed an accurate and computationally efficient wind resource assessment technique for prospective wind farm sites, which incorporates innovative statistical techniques and the new NASA Earth science dataset MERRA. This technique produces a wind resource estimate that is more accurate than that obtained by the wind energy industry's standard technique, while providing a reliable quantification of its uncertainty. The focus now is on evaluating the socio-economic value of this new technique upon using the industry's standard technique. Would it yield lower financing costs? Could it result in lower electricity prices? Are there further down-the-line positive consequences, e.g. job creation, time saved, greenhouse gas decrease? Ultimately, we expect our results will inform efforts to refine and disseminate the new technique to support the development of the U.S. renewable energy infrastructure. In order to address the above questions, we are carrying out a cost-benefit analysis based on the net present worth of the technique. We will describe this approach, including the cash-flow process of wind farm financing, how the wind resource assessment factors in, and will present current results for various hypothetical candidate wind farm sites.

  1. A new wind power prediction method based on chaotic theory and Bernstein Neural Network

    International Nuclear Information System (INIS)

    Wang, Cong; Zhang, Hongli; Fan, Wenhui; Fan, Xiaochao

    2016-01-01

    The accuracy of wind power prediction is important for assessing the security and economy of the system operation when wind power connects to the grids. However, multiple factors cause a long delay and large errors in wind power prediction. Hence, efficient wind power forecasting approaches are still required for practical applications. In this paper, a new wind power forecasting method based on Chaos Theory and Bernstein Neural Network (BNN) is proposed. Firstly, the largest Lyapunov exponent as a judgment for wind power system's chaotic behavior is made. Secondly, Phase Space Reconstruction (PSR) is used to reconstruct the wind power series' phase space. Thirdly, the prediction model is constructed using the Bernstein polynomial and neural network. Finally, the weights and thresholds of the model are optimized by Primal Dual State Transition Algorithm (PDSTA). The practical hourly data of wind power generation in Xinjiang is used to test this forecaster. The proposed forecaster is compared with several current prominent research findings. Analytical results indicate that the forecasting error of PDSTA + BNN is 3.893% for 24 look-ahead hours, and has lower errors obtained compared with the other forecast methods discussed in this paper. The results of all cases studying confirm the validity of the new forecast method. - Highlights: • Lyapunov exponent is used to verify chaotic behavior of wind power series. • Phase Space Reconstruction is used to reconstruct chaotic wind power series. • A new Bernstein Neural Network to predict wind power series is proposed. • Primal dual state transition algorithm is chosen as the training strategy of BNN.

  2. Should we build wind farms close to load or invest in transmission to access better wind resources in remote areas? A case study in the MISO region

    International Nuclear Information System (INIS)

    Lamy, Julian V.; Jaramillo, Paulina; Azevedo, Inês L.; Wiser, Ryan

    2016-01-01

    Wind speeds in remote areas are sometimes very high, but transmission costs to access these locations can be prohibitive. We present a conceptual model to estimate the economics of accessing high quality wind resources in remote areas to comply with renewable energy policy targets, and apply the model to the Midwestern grid (MISO) as a case study. We assess the goal of providing 40 TWh of new wind generation while minimizing costs, and include temporal aspects of wind power (variability costs and correlation to market prices) as well as total wind power produced from different farms. We find that building wind farms in North/South Dakota (windiest states) compared to Illinois (less windy, but close to load) would only be economical if the incremental transmission costs to access them were below $360/kW of wind capacity (break-even value). Historically, the incremental transmission costs for wind development in North/South Dakota compared to in Illinois are about twice this value. However, the break-even incremental transmission cost for wind farms in Minnesota/Iowa (also windy states) is $250/kW, which is consistent with historical costs. We conclude that wind development in Minnesota/Iowa is likely more economical to meet MISO renewable targets compared to North/South Dakota or Illinois. - Highlights: •We evaluate the economics of building wind farms in remote areas in MISO. •We present a conceptual wind site selection model to meet 40 TWh of new wind. •We use the model to compare remote windy sites to less windy ones closer to load. •We show break-even transmission costs that would justify remote wind development. •Comparing break-even values to historical costs, MN/IA sites are most economical.

  3. Using data-driven approach for wind power prediction: A comparative study

    International Nuclear Information System (INIS)

    Taslimi Renani, Ehsan; Elias, Mohamad Fathi Mohamad; Rahim, Nasrudin Abd.

    2016-01-01

    Highlights: • Double exponential smoothing is the most accurate model in wind speed prediction. • A two-stage feature selection method is proposed to select most important inputs. • Direct prediction illustrates better accuracy than indirect prediction. • Adaptive neuro fuzzy inference system outperforms data mining algorithms. • Random forest performs the worst compared to other data mining algorithm. - Abstract: Although wind energy is intermittent and stochastic in nature, it is increasingly important in the power generation due to its sustainability and pollution-free. Increased utilization of wind energy sources calls for more robust and efficient prediction models to mitigate uncertainties associated with wind power. This research compares two different approaches in wind power forecasting which are indirect and direct prediction methods. In indirect method, several times series are applied to forecast the wind speed, whereas the logistic function with five parameters is then used to forecast the wind power. In this study, backtracking search algorithm with novel crossover and mutation operators is employed to find the best parameters of five-parameter logistic function. A new feature selection technique, combining the mutual information and neural network is proposed in this paper to extract the most informative features with a maximum relevancy and minimum redundancy. From the comparative study, the results demonstrate that, in the direct prediction approach where the historical weather data are used to predict the wind power generation directly, adaptive neuro fuzzy inference system outperforms five data mining algorithms namely, random forest, M5Rules, k-nearest neighbor, support vector machine and multilayer perceptron. Moreover, it is also found that the mean absolute percentage error of the direct prediction method using adaptive neuro fuzzy inference system is 1.47% which is approximately less than half of the error obtained with the

  4. Temporal and spatial complementarity of wind and solar resources in Lower Silesia (Poland)

    Science.gov (United States)

    Jurasz, Jakub; Wdowikowski, Marcin; Kaźmierczak, Bartosz; Dąbek, Paweł

    2017-11-01

    This paper investigates the concept of temporal and spatial complementarity of wind and solar resources in Lower Silesia (south-wester Poland). For the purpose of our research we have used hourly load and energy yield from photovoltaics and wind turbines covering period 2010-2014. In order to assess the spatial complementarity we have divided the considered voivodeship into 74 squared regions with maximal area of 400 km2. The obtained results indicate an existence of temporal complementarity on a monthly time scale and a positive correlation between load and wind generation patterns (also on a monthly time scale). The temporal complementarity for hourly time series in relatively low but has potential to smooth the energy generation curves.

  5. Measured and predicted rotor performance for the SERI advanced wind turbine blades

    Energy Technology Data Exchange (ETDEWEB)

    Tangler, J.; Smith, B.; Kelley, N.; Jager, D.

    1992-02-01

    Measured and predicted rotor performance for the SERI advanced wind turbine blades were compared to assess the accuracy of predictions and to identify the sources of error affecting both predictions and measurements. An awareness of these sources of error contributes to improved prediction and measurement methods that will ultimately benefit future rotor design efforts. Propeller/vane anemometers were found to underestimate the wind speed in turbulent environments such as the San Gorgonio Pass wind farm area. Using sonic or cup anemometers, good agreement was achieved between predicted and measured power output for wind speeds up to 8 m/sec. At higher wind speeds an optimistic predicted power output and the occurrence of peak power at wind speeds lower than measurements resulted from the omission of turbulence and yaw error. In addition, accurate two-dimensional (2-D) airfoil data prior to stall and a post stall airfoil data synthesization method that reflects three-dimensional (3-D) effects were found to be essential for accurate performance prediction. 11 refs.

  6. Standardizing the performance evaluation of short-term wind prediction models

    DEFF Research Database (Denmark)

    Madsen, Henrik; Pinson, Pierre; Kariniotakis, G.

    2005-01-01

    Short-term wind power prediction is a primary requirement for efficient large-scale integration of wind generation in power systems and electricity markets. The choice of an appropriate prediction model among the numerous available models is not trivial, and has to be based on an objective...... evaluation of model performance. This paper proposes a standardized protocol for the evaluation of short-term wind-poser preciction systems. A number of reference prediction models are also described, and their use for performance comparison is analysed. The use of the protocol is demonstrated using results...... from both on-shore and off-shore wind forms. The work was developed in the frame of the Anemos project (EU R&D project) where the protocol has been used to evaluate more than 10 prediction systems....

  7. Development of a wind farm noise propagation prediction model - project progress to date

    International Nuclear Information System (INIS)

    Robinson, P.; Bullmore, A.; Bass, J.; Sloth, E.

    1998-01-01

    This paper describes a twelve month measurement campaign which is part of a European project (CEC Project JOR3-CT95-0051) with the aim to substantially reduce the uncertainties involved in predicting environmentally radiated noise levels from wind farms (1). This will be achieved by comparing noise levels measure at varying distances from single and multiple sources over differing complexities of terrain with those predicted using a number of currently adopted sound propagation models. Specific objectives within the project are to: establish the important parameters controlling the propagation of wind farm noise to the far field; develop a planning tool for predicting wind farm noise emission levels under practically encountered conditions; place confidence limits on the upper and lower bounds of the noise levels predicted, thus enabling developers to quantify the risk whether noise emission from wind farms will cause nuisance to nearby residents. (Author)

  8. Externalities in utility resource selection: A means to formally recognize the envionmental benefits of wind farms

    International Nuclear Information System (INIS)

    Birner, S.

    1992-01-01

    Wind can only make its full contribution to the minimization of the total cost of energy services if it is valued for all the costs that it avoids, including avoided environmental costs. Means of incorporating environmental costs, or externalities, into utility planning decisions are described. Externalities are defined as uncompensated costs or benefits of an action borne by a party other than the one causing the costs. A simple example of the use of externalities in utility resource selection is presented, comparing costs of a coal-fired power plant and a wind farm. Externalities of wind farms are analyzed and found to be very low. An examination of some aspects of legislation in the USA and Canada shows a trend for utility commissions and other regulatory bodies to determine that including externalitites lies within their mandate. By formally recognizing and accounting for the environmental benefits of wind farms, it is seen that externalities can have a significant effect on utility demand for wind energy. A review of USA state actions regarding externalities is appended. 10 refs

  9. Assessing climate change impacts on the near-term stability of the wind energy resource over the United States.

    Science.gov (United States)

    Pryor, S C; Barthelmie, R J

    2011-05-17

    The energy sector comprises approximately two-thirds of global total greenhouse gas emissions. For this and other reasons, renewable energy resources including wind power are being increasingly harnessed to provide electricity generation potential with negligible emissions of carbon dioxide. The wind energy resource is naturally a function of the climate system because the "fuel" is the incident wind speed and thus is determined by the atmospheric circulation. Some recent articles have reported historical declines in measured near-surface wind speeds, leading some to question the continued viability of the wind energy industry. Here we briefly articulate the challenges inherent in accurately quantifying and attributing historical tendencies and making robust projections of likely future wind resources. We then analyze simulations from the current generation of regional climate models and show, at least for the next 50 years, the wind resource in the regions of greatest wind energy penetration will not move beyond the historical envelope of variability. Thus this work suggests that the wind energy industry can, and will, continue to make a contribution to electricity provision in these regions for at least the next several decades.

  10. Wind and solar energy resources on the 'Roof of the World'

    Science.gov (United States)

    Zandler, Harald; Morche, Thomas; Samimi, Cyrus

    2015-04-01

    The Eastern Pamirs of Tajikistan, often referred to as 'Roof of the World', are an arid high mountain plateau characterized by severe energy poverty that may have great potential for renewable energy resources due to the prevailing natural conditions. The lack of energetic infrastructure makes the region a prime target for decentralized integration of wind and solar power. However, up to date no scientific attempt to assess the regional potential of these resources has been carried out. In this context, it is particularly important to evaluate if wind and solar energy are able to provide enough power to generate thermal energy, as other thermal energy carriers are scarce or unavailable and the existing alternative, local harvest of dwarf shrubs, is unsustainable due to the slow regeneration in this environment. Therefore, this study examines the feasibility of using wind and solar energy as thermal energy sources. Financial frame conditions were set on a maximum amount of five million Euros. This sum provides a realistic scenario as it is based on the current budget of the KfW development bank to finance the modernization of the local hydropower plant in the regions only city, Murghab, with about 1500 households. The basis for resource assessment is data of four climate stations, erected for this purpose in 2012, where wind speed, wind direction, global radiation and temperature are measured at a half hourly interval. These measurements confirm the expectation of a large photovoltaic potential and high panel efficiency with up to 84 percent of extraterrestrial radiation reaching the surface and only 16 hours of temperatures above 25°C were measured in two years at the village stations on average. As these observations are only point measurements, radiation data and the ASTER GDEM was used to train a GIS based solar radiation model to spatially extrapolate incoming radiation. With mean validation errors ranging from 5% in July (minimum) to 15% in December (maximum

  11. Wind Power Ramp Events Prediction with Hybrid Machine Learning Regression Techniques and Reanalysis Data

    Directory of Open Access Journals (Sweden)

    Laura Cornejo-Bueno

    2017-11-01

    Full Text Available Wind Power Ramp Events (WPREs are large fluctuations of wind power in a short time interval, which lead to strong, undesirable variations in the electric power produced by a wind farm. Its accurate prediction is important in the effort of efficiently integrating wind energy in the electric system, without affecting considerably its stability, robustness and resilience. In this paper, we tackle the problem of predicting WPREs by applying Machine Learning (ML regression techniques. Our approach consists of using variables from atmospheric reanalysis data as predictive inputs for the learning machine, which opens the possibility of hybridizing numerical-physical weather models with ML techniques for WPREs prediction in real systems. Specifically, we have explored the feasibility of a number of state-of-the-art ML regression techniques, such as support vector regression, artificial neural networks (multi-layer perceptrons and extreme learning machines and Gaussian processes to solve the problem. Furthermore, the ERA-Interim reanalysis from the European Center for Medium-Range Weather Forecasts is the one used in this paper because of its accuracy and high resolution (in both spatial and temporal domains. Aiming at validating the feasibility of our predicting approach, we have carried out an extensive experimental work using real data from three wind farms in Spain, discussing the performance of the different ML regression tested in this wind power ramp event prediction problem.

  12. Uncertainty quantification and predictability of wind speed over the Iberian Peninsula

    Science.gov (United States)

    Fernández-González, S.; Martín, M. L.; Merino, A.; Sánchez, J. L.; Valero, F.

    2017-04-01

    During recent decades, the use of probabilistic forecasting methods has increased markedly. However, these predictions still need improvement in uncertainty quantification and predictability analysis. For this reason, the main aim of this paper is to develop tools for quantifying uncertainty and predictability of wind speed over the Iberian Peninsula. To achieve this goal, several spread indexes extracted from an ensemble prediction system are defined in this paper. Subsequently, these indexes were evaluated with the aim of selecting the most appropriate for the characterization of uncertainty associated to the forecasting. Selection is based on comparison of the average magnitude of ensemble spread (ES) and mean absolute percentage error (MAPE). MAPE is estimated by comparing the ensemble mean with wind speed values from different databases. Later, correlation between MAPE and ES was evaluated. Furthermore, probability distribution functions (PDFs) of spread indexes are analyzed to select the index with greater similarity to MAPE PDFs. Then, the spread index selected as optimal is used to carry out a spatiotemporal analysis of model uncertainty in wind forecasting. The results indicate that mountainous regions and the Mediterranean coast are characterized by strong uncertainty, and the spread increases more rapidly in areas affected by strong winds. Finally, a predictability index is proposed for obtaining a tool capable of providing information on whether the predictability is higher or lower than average. The applications developed may be useful in the forecasting of wind potential several days in advance, with substantial importance for estimating wind energy production.

  13. Prediction of the wind turbine performance by using BEM with airfoil data extracted from CFD

    DEFF Research Database (Denmark)

    Yang, Hua; Shen, Wen Zhong; Xu, Haoran

    2014-01-01

    Blade element momentum (BEM) theory with airfoil data is a widely used technique for prediction of wind turbine aerodynamic performance, but the reliability of the airfoil data is an important factor for the prediction accuracy of aerodynamic loads and power. The airfoil characteristics used in BEM...... codes are mostly based on 2D wind tunnel measurements of airfoils with constant span. Due to 3D effects, a BEM code using airfoil data obtained directly from 2D wind tunnel measurements will not yield the correct loading and power. As a consequence, 2D airfoil characteristics have to be corrected before...

  14. Wind speed and wind power short and medium range predictions for complex terrain using artificial neural networks and ensemble calibration

    Science.gov (United States)

    Schicker, Irene; Papazek, Petrina; Kann, Alexander; Wang, Yong

    2017-04-01

    Reliable predictions of wind speed and wind power are vital for balancing the electricity network. Within the last two decades the amount of energy stemming from renewable sources increased substantially relying heavily on the prevailing synoptic conditions. Especially for regions with complex terrain and forested surfaces providing reliable predictions is a challenging task. Forecasts in the nowcasting as well as in the (two) day-ahead range are thus essential for the network balancing. Predictions of wind speed and wind power from the nowcasting to the +72-hour forecast range using NWP models in regions with complex terrain need a suitable horizontal, vertical and temporal resolution (e.g. 10 - 15 minute forecasts for the Nowcasting range) requiring high performance computing. To be able to provide sub-hourly to hourly forecasts different approaches such as model output statistics (MOS) or artificial neural networks (ANN) - including feed forward recurrent neural networks, fuzzy logic, particle swarm optimizations - are needed as computational costs are too high. To represent the forecast uncertainties additional probabilistic ensemble predictions are required increasing the computational needs. Ensemble prediction systems account for errors and uncertainties in the initial and boundary conditions, parameterizations, numeric, etc. Due to the underestimation of model and sampling errors ensemble predictions tend to be underdispersive and biased. They lack, too, sharpness and reliability. These shortcomings can be accounted for using statistical post-processing methods such as the non-homogeneous Gaussian regression (NGR) to calibrate an ensemble. These calibrated ensembles provide forecasts in the medium range for any arbitrary location where observations are available. In this study an ANN is used to provide forecasts for the nowcasting and medium-range with sub-hourly to hourly predictions for different Austrian sites, including high alpine sites as well as low

  15. Resource Use of Wind Farms in the German North Sea—The Example of Alpha Ventus and Bard Offshore I

    Directory of Open Access Journals (Sweden)

    Holger Rohn

    2013-10-01

    Full Text Available The German government aims to obtain at least 40 percent of its electricity from renewable sources by 2030. One of the central steps to reach this target is the construction of deep sea offshore wind farms. The paper presents a material intensity analysis of the offshore wind farms “Alpha Ventus” and “Bard Offshore I” under consideration of the grid connection. An additional onshore scenario is considered for comparison. The results show that offshore wind farms have higher resource consumption than onshore farms. In general, and in respect to the resource use of other energy systems, both can be tagged as resource efficient.

  16. Importance of Dynamic Inflow Model Predictive Control of Wind Turbines

    DEFF Research Database (Denmark)

    Odgaard, Peter Fogh; Knudsen, Torben; Overgaard, Anders

    2015-01-01

    The efficiency of including dynamic inflow in the model based design of wind turbine controller has been discussed for many years in the wind energy community with out getting to a safe conclusion. This paper delivers a good argument in favor of including dynamic inflow. The main contributions...... pronounces. For this the well accepted NREL 5MW reference turbine simulated with FAST is used. The main result is a reduction in tower fatigue load at 22% while power error, rotor speed error, generator torque and pitch rate is improved from 2 to 33%....

  17. Estimation of Separation Buffers for Wind-Prediction Error in an Airborne Separation Assistance System

    Science.gov (United States)

    Consiglio, Maria C.; Hoadley, Sherwood T.; Allen, B. Danette

    2009-01-01

    Wind prediction errors are known to affect the performance of automated air traffic management tools that rely on aircraft trajectory predictions. In particular, automated separation assurance tools, planned as part of the NextGen concept of operations, must be designed to account and compensate for the impact of wind prediction errors and other system uncertainties. In this paper we describe a high fidelity batch simulation study designed to estimate the separation distance required to compensate for the effects of wind-prediction errors throughout increasing traffic density on an airborne separation assistance system. These experimental runs are part of the Safety Performance of Airborne Separation experiment suite that examines the safety implications of prediction errors and system uncertainties on airborne separation assurance systems. In this experiment, wind-prediction errors were varied between zero and forty knots while traffic density was increased several times current traffic levels. In order to accurately measure the full unmitigated impact of wind-prediction errors, no uncertainty buffers were added to the separation minima. The goal of the study was to measure the impact of wind-prediction errors in order to estimate the additional separation buffers necessary to preserve separation and to provide a baseline for future analyses. Buffer estimations from this study will be used and verified in upcoming safety evaluation experiments under similar simulation conditions. Results suggest that the strategic airborne separation functions exercised in this experiment can sustain wind prediction errors up to 40kts at current day air traffic density with no additional separation distance buffer and at eight times the current day with no more than a 60% increase in separation distance buffer.

  18. Assessment of Off-shore Wind Energy Resource in China using QuikSCAT Satellite data and SAR Satellite Images

    DEFF Research Database (Denmark)

    Xiuzhi, Zhang; Yanbo, Shen; Jingwei, Xu

    2010-01-01

    From August 2008 to August 2009, the project ‘Off-Shore Wind Energy Resource Assessment and Feasibility Study of Off-Shore Wind Farm Development in China’ was carried out by China Meteorological Administration (CMA), which was funded by the EU-China Energy and Environment Programme (EEP). As one ...... part of the project, off-shore wind energy resource in China was assessed with QuikSCAT Satellite data and SAR Satellite Images. In this paper, the results from these two ways were introduced.......From August 2008 to August 2009, the project ‘Off-Shore Wind Energy Resource Assessment and Feasibility Study of Off-Shore Wind Farm Development in China’ was carried out by China Meteorological Administration (CMA), which was funded by the EU-China Energy and Environment Programme (EEP). As one...

  19. Greater Sage-Grouse Habitat Use and Population Demographics at the Simpson Ridge Wind Resource Area, Carbon County, Wyoming

    Energy Technology Data Exchange (ETDEWEB)

    Gregory D. Johnson; Chad W. LeBeau; Ryan Nielsen; Troy Rintz; Jamey Eddy; Matt Holloran

    2012-03-27

    This study was conducted to obtain baseline data on use of the proposed Simpson Ridge Wind Resource Area (SRWRA) in Carbon County, Wyoming by greater sage-grouse. The first two study years were designed to determine pre-construction seasonally selected habitats and population-level vital rates (productivity and survival). The presence of an existing wind energy facility in the project area, the PacifiCorp Seven Mile Hill (SMH) project, allowed us to obtain some information on initial sage-grouse response to wind turbines the first two years following construction. To our knowledge these are the first quantitative data on sage-grouse response to an existing wind energy development. This report presents results of the first two study years (April 1, 2009 through March 30, 2011). This study was selected for continued funding by the National Wind Coordinating Collaborative Sage-Grouse Collaborative (NWCC-SGC) and has been ongoing since March 30, 2011. Future reports summarizing results of this research will be distributed through the NWCC-SGC. To investigate population trends through time, we determined the distribution and numbers of males using leks throughout the study area, which included a 4-mile radius buffer around the SRWRA. Over the 2-year study, 116 female greater sage-grouse were captured by spotlighting and use of hoop nets on roosts surrounding leks during the breeding period. Radio marked birds were located anywhere from twice a week to once a month, depending on season. All radio-locations were classified to season. We developed predictor variables used to predict success of fitness parameters and relative probability of habitat selection within the SRWRA and SMH study areas. Anthropogenic features included paved highways, overhead transmission lines, wind turbines and turbine access roads. Environmental variables included vegetation and topography features. Home ranges were estimated using a kernel density estimator. We developed resource selection

  20. Resource Use of Wind Farms in the German North Sea—The Example of Alpha Ventus and Bard Offshore I

    OpenAIRE

    Holger Rohn; Klaus Wiesen; Jens Teubler

    2013-01-01

    The German government aims to obtain at least 40 percent of its electricity from renewable sources by 2030. One of the central steps to reach this target is the construction of deep sea offshore wind farms. The paper presents a material intensity analysis of the offshore wind farms “Alpha Ventus” and “Bard Offshore I” under consideration of the grid connection. An additional onshore scenario is considered for comparison. The results show that offshore wind farms have higher resource consumpti...

  1. Study on new energy development planning and absorptive capability of Xinjiang in China considering resource characteristics and demand prediction

    Science.gov (United States)

    Shao, Hai; Miao, Xujuan; Liu, Jinpeng; Wu, Meng; Zhao, Xuehua

    2018-02-01

    Xinjiang, as the area where wind energy and solar energy resources are extremely rich, with good resource development characteristics, can provide a support for regional power development and supply protection. This paper systematically analyzes the new energy resource and development characteristics of Xinjiang and carries out the demand prediction and excavation of load characteristics of Xinjiang power market. Combing the development plan of new energy of Xinjiang and considering the construction of transmission channel, it analyzes the absorptive capability of new energy. It provides certain reference for the comprehensive planning of new energy development in Xinjiang and the improvement of absorptive capacity of new energy.

  2. Assessing risk to birds from industrial wind energy development via paired resource selection models.

    Science.gov (United States)

    Miller, Tricia A; Brooks, Robert P; Lanzone, Michael; Brandes, David; Cooper, Jeff; O'Malley, Kieran; Maisonneuve, Charles; Tremblay, Junior; Duerr, Adam; Katzner, Todd

    2014-06-01

    When wildlife habitat overlaps with industrial development animals may be harmed. Because wildlife and people select resources to maximize biological fitness and economic return, respectively, we estimated risk, the probability of eagles encountering and being affected by turbines, by overlaying models of resource selection for each entity. This conceptual framework can be applied across multiple spatial scales to understand and mitigate impacts of industry on wildlife. We estimated risk to Golden Eagles (Aquila chrysaetos) from wind energy development in 3 topographically distinct regions of the central Appalachian Mountains of Pennsylvania (United States) based on models of resource selection of wind facilities (n = 43) and of northbound migrating eagles (n = 30). Risk to eagles from wind energy was greatest in the Ridge and Valley region; all 24 eagles that passed through that region used the highest risk landscapes at least once during low altitude flight. In contrast, only half of the birds that entered the Allegheny Plateau region used highest risk landscapes and none did in the Allegheny Mountains. Likewise, in the Allegheny Mountains, the majority of wind turbines (56%) were situated in poor eagle habitat; thus, risk to eagles is lower there than in the Ridge and Valley, where only 1% of turbines are in poor eagle habitat. Risk within individual facilities was extremely variable; on average, facilities had 11% (SD 23; range = 0-100%) of turbines in highest risk landscapes and 26% (SD 30; range = 0-85%) of turbines in the lowest risk landscapes. Our results provide a mechanism for relocating high-risk turbines, and they show the feasibility of this novel and highly adaptable framework for managing risk of harm to wildlife from industrial development. © 2014 Society for Conservation Biology.

  3. Seal carrion is a predictable resource for coastal ecosystems

    Science.gov (United States)

    Quaggiotto, Maria-Martina; Barton, Philip S.; Morris, Christopher D.; Moss, Simon E. W.; Pomeroy, Patrick P.; McCafferty, Dominic J.; Bailey, David M.

    2018-04-01

    The timing, magnitude, and spatial distribution of resource inputs can have large effects on dependent organisms. Few studies have examined the predictability of such resources and no standard ecological measure of predictability exists. We examined the potential predictability of carrion resources provided by one of the UK's largest grey seal (Halichoerus grypus) colonies, on the Isle of May, Scotland. We used aerial (11 years) and ground surveys (3 years) to quantify the variability in time, space, quantity (kg), and quality (MJ) of seal carrion during the seal pupping season. We then compared the potential predictability of seal carrion to other periodic changes in food availability in nature. An average of 6893 kg of carrion •yr-1 corresponding to 110.5 × 103 MJ yr-1 was released for potential scavengers as placentae and dead animals. A fifth of the total biomass from dead seals was consumed by the end of the pupping season, mostly by avian scavengers. The spatial distribution of carcasses was similar across years, and 28% of the area containing >10 carcasses ha-1 was shared among all years. Relative standard errors (RSE) in space, time, quantity, and quality of carrion were all below 34%. This is similar to other allochthonous-dependent ecosystems, such as those affected by migratory salmon, and indicates high predictability of seal carrion as a resource. Our study illustrates how to quantify predictability in carrion, which is of general relevance to ecosystems that are dependent on this resource. We also highlight the importance of carrion to marine coastal ecosystems, where it sustains avian scavengers thus affecting ecosystem structure and function.

  4. EnviroAtlas - Annual average potential wind energy resource by 12-digit HUC for the Conterminous United States

    Data.gov (United States)

    U.S. Environmental Protection Agency — This EnviroAtlas dataset shows the annual average potential wind energy resource in kilowatt hours per square kilometer per day for each 12-digit Hydrologic Unit...

  5. Jet stream wind power as a renewable energy resource: little power, big impacts

    Directory of Open Access Journals (Sweden)

    L. M. Miller

    2011-11-01

    Full Text Available Jet streams are regions of sustained high wind speeds in the upper atmosphere and are seen by some as a substantial renewable energy resource. However, jet streams are nearly geostrophic flow, that is, they result from the balance between the pressure gradient and Coriolis force in the near absence of friction. Therefore, jet stream motion is associated with very small generation rates of kinetic energy to maintain the high wind velocities, and it is this generation rate that will ultimately limit the potential use of jet streams as a renewable energy resource. Here we estimate the maximum limit of jet stream wind power by considering extraction of kinetic energy as a term in the free energy balance of kinetic energy that describes the generation, depletion, and extraction of kinetic energy. We use this balance as the basis to quantify the maximum limit of how much kinetic energy can be extracted sustainably from the jet streams of the global atmosphere as well as the potential climatic impacts of its use. We first use a simple thought experiment of geostrophic flow to demonstrate why the high wind velocities of the jet streams are not associated with a high potential for renewable energy generation. We then use an atmospheric general circulation model to estimate that the maximum sustainable extraction from jet streams of the global atmosphere is about 7.5 TW. This estimate is about 200-times less than previous estimates and is due to the fact that the common expression for instantaneous wind power 12 ρv3 merely characterizes the transport of kinetic energy by the flow, but not the generation rate of kinetic energy. We also find that when maximum wind power is extracted from the jet streams, it results in significant

  6. Model Predictive Control for Dynamic Unreliable Resource Allocation

    National Research Council Canada - National Science Library

    Castanon, David

    2002-01-01

    .... The approximation is used in a model predictive control (MPC) algorithm. For single resource problems, the MPC algorithm completes over 98 percent of the task value completed by an optimal dynamic programming algorithm in over 1,000 randomly generated problems. On average, it achieves 99.5 percent of the optimal performance while requiring over 6 orders of magnitude less comnutation.

  7. Evaluation and Prediction of Water Resources Based on AHP

    Science.gov (United States)

    Li, Shuai; Sun, Anqi

    2017-01-01

    Nowadays, the shortage of water resources is a threat to us. In order to solve the problem of water resources restricted by varieties of factors, this paper establishes a water resources evaluation index model (WREI), which adopts the fuzzy comprehensive evaluation (FCE) based on analytic hierarchy process (AHP) algorithm. After considering influencing factors of water resources, we ignore secondary factors and then hierarchical approach the main factors according to the class, set up a three-layer structure. The top floor is for WREI. Using analytic hierarchy process (AHP) to determine weight first, and then use fuzzy judgment to judge target, so the comprehensive use of the two algorithms reduce the subjective influence of AHP and overcome the disadvantages of multi-level evaluation. To prove the model, we choose India as a target region. On the basis of water resources evaluation index model, we use Matlab and combine grey prediction with linear prediction to discuss the ability to provide clean water in India and the trend of India’s water resources changing in the next 15 years. The model with theoretical support and practical significance will be of great help to provide reliable data support and reference for us to get plans to improve water quality.

  8. A prediction model for wind speed ratios at pedestrian level with simplified urban canopies

    Science.gov (United States)

    Ikegaya, N.; Ikeda, Y.; Hagishima, A.; Razak, A. A.; Tanimoto, J.

    2017-02-01

    The purpose of this study is to review and improve prediction models for wind speed ratios at pedestrian level with simplified urban canopies. We adopted an extensive database of velocity fields under various conditions for arrays consisting of cubes, slender or flattened rectangles, and rectangles with varying roughness heights. Conclusions are summarized as follows: first, a new geometric parameter is introduced as a function of the plan area index and the aspect ratio so as to express the increase in virtual density that causes wind speed reduction. Second, the estimated wind speed ratios in the range 0.05 coefficients between the wind speeds averaged over the entire region, and the front or side region values are larger than 0.8. In contrast, in areas where the influence of roughness elements is significant, such as behind a building, the wind speeds are weakly correlated.

  9. AN EFFICIENT PATIENT INFLOW PREDICTION MODEL FOR HOSPITAL RESOURCE MANAGEMENT

    Directory of Open Access Journals (Sweden)

    Kottalanka Srikanth

    2017-07-01

    Full Text Available There has been increasing demand in improving service provisioning in hospital resources management. Hospital industries work with strict budget constraint at the same time assures quality care. To achieve quality care with budget constraint an efficient prediction model is required. Recently there has been various time series based prediction model has been proposed to manage hospital resources such ambulance monitoring, emergency care and so on. These models are not efficient as they do not consider the nature of scenario such climate condition etc. To address this artificial intelligence is adopted. The issues with existing prediction are that the training suffers from local optima error. This induces overhead and affects the accuracy in prediction. To overcome the local minima error, this work presents a patient inflow prediction model by adopting resilient backpropagation neural network. Experiment are conducted to evaluate the performance of proposed model inter of RMSE and MAPE. The outcome shows the proposed model reduces RMSE and MAPE over existing back propagation based artificial neural network. The overall outcomes show the proposed prediction model improves the accuracy of prediction which aid in improving the quality of health care management.

  10. Wind power, network congestion and hydro resource utilisation in the Norwegian power market

    International Nuclear Information System (INIS)

    Foersund, Finn; Singh, Balbir; Jensen, Trond; Larsen, Cato

    2005-01-01

    Capacity constraints in electricity networks can have important impacts on utilization of new renewable energy (RE) capacity and incumbent generation resources. Neglect of such impacts in development of RE resources can result in crowding-out of incumbent generation. This trade-off is particularly problematic if the incumbent generation also consists of renewable sources, such as hydropower in the Norwegian electricity system. This paper presents a numerical analysis of the current wind-power development plans in North Norway and their impacts on utilization of hydropower. Policy simulations in paper are conducted using a dynamic partial equilibrium model that is calibrated to reflect the structure of the Nordic power market. The paper draws conclusion and policy implications for integration of RE resources in the Norwegian power market. (Author)

  11. Dynamic computing resource allocation in online flood monitoring and prediction

    Science.gov (United States)

    Kuchar, S.; Podhoranyi, M.; Vavrik, R.; Portero, A.

    2016-08-01

    This paper presents tools and methodologies for dynamic allocation of high performance computing resources during operation of the Floreon+ online flood monitoring and prediction system. The resource allocation is done throughout the execution of supported simulations to meet the required service quality levels for system operation. It also ensures flexible reactions to changing weather and flood situations, as it is not economically feasible to operate online flood monitoring systems in the full performance mode during non-flood seasons. Different service quality levels are therefore described for different flooding scenarios, and the runtime manager controls them by allocating only minimal resources currently expected to meet the deadlines. Finally, an experiment covering all presented aspects of computing resource allocation in rainfall-runoff and Monte Carlo uncertainty simulation is performed for the area of the Moravian-Silesian region in the Czech Republic.

  12. Wind Power Grid Connected Capacity Prediction Using LSSVM Optimized by the Bat Algorithm

    Directory of Open Access Journals (Sweden)

    Qunli Wu

    2015-12-01

    Full Text Available Given the stochastic nature of wind, wind power grid-connected capacity prediction plays an essential role in coping with the challenge of balancing supply and demand. Accurate forecasting methods make enormous contribution to mapping wind power strategy, power dispatching and sustainable development of wind power industry. This study proposes a bat algorithm (BA–least squares support vector machine (LSSVM hybrid model to improve prediction performance. In order to select input of LSSVM effectively, Stationarity, Cointegration and Granger causality tests are conducted to examine the influence of installed capacity with different lags, and partial autocorrelation analysis is employed to investigate the inner relationship of grid-connected capacity. The parameters in LSSVM are optimized by BA to validate the learning ability and generalization of LSSVM. Multiple model sufficiency evaluation methods are utilized. The research results reveal that the accuracy improvement of the present approach can reach about 20% compared to other single or hybrid models.

  13. Nonlinear Predictive Control of Wind Energy Conversion System Using Dfig with Aerodynamic Torque Observer

    Science.gov (United States)

    Kamel, Ouari; Mohand, Ouhrouche; Toufik, Rekioua; Taib, Nabil

    2015-01-01

    In order to improvement of the performances for wind energy conversions systems (WECS), an advanced control techniques must be used. In this paper, as an alternative to conventional PI-type control methods, a nonlinear predictive control (NPC) approach is developed for DFIG-based wind turbine. To enhance the robustness of the controller, a disturbance observer is designed to estimate the aerodynamic torque which is considered as an unknown perturbation. An explicitly analytical form of the optimal predictive controller is given consequently on-line optimization is not necessary The DFIG is fed through the rotor windings by a back-to-back converter controlled by Pulse Width Modulation (PWM), where the stator winding is directly connected to the grid. The presented simulation results show a good performance in trajectory tracking of the proposed strategy and rejection of disturbances is successfully achieved.

  14. A novel implementation of kNN classifier based on multi-tupled meteorological input data for wind power prediction

    International Nuclear Information System (INIS)

    Yesilbudak, Mehmet; Sagiroglu, Seref; Colak, Ilhami

    2017-01-01

    Highlights: • An accurate wind power prediction model is proposed for very short-term horizon. • The k-nearest neighbor classifier is implemented based on the multi-tupled inputs. • The variation of wind power prediction errors is evaluated in various aspects. • Our approach shows the superior prediction performance over the persistence method. - Abstract: With the growing share of wind power production in the electric power grids, many critical challenges to the grid operators have been emerged in terms of the power balance, power quality, voltage support, frequency stability, load scheduling, unit commitment and spinning reserve calculations. To overcome such problems, numerous studies have been conducted to predict the wind power production, but a small number of them have attempted to improve the prediction accuracy by employing the multidimensional meteorological input data. The novelties of this study lie in the proposal of an efficient and easy to implement very short-term wind power prediction model based on the k-nearest neighbor classifier (kNN), in the usage of wind speed, wind direction, barometric pressure and air temperature parameters as the multi-tupled meteorological inputs and in the comparison of wind power prediction results with respect to the persistence reference model. As a result of the achieved patterns, we characterize the variation of wind power prediction errors according to the input tuples, distance measures and neighbor numbers, and uncover the most influential and the most ineffective meteorological parameters on the optimization of wind power prediction results.

  15. A New Global Regression Analysis Method for the Prediction of Wind Tunnel Model Weight Corrections

    Science.gov (United States)

    Ulbrich, Norbert Manfred; Bridge, Thomas M.; Amaya, Max A.

    2014-01-01

    A new global regression analysis method is discussed that predicts wind tunnel model weight corrections for strain-gage balance loads during a wind tunnel test. The method determines corrections by combining "wind-on" model attitude measurements with least squares estimates of the model weight and center of gravity coordinates that are obtained from "wind-off" data points. The method treats the least squares fit of the model weight separate from the fit of the center of gravity coordinates. Therefore, it performs two fits of "wind- off" data points and uses the least squares estimator of the model weight as an input for the fit of the center of gravity coordinates. Explicit equations for the least squares estimators of the weight and center of gravity coordinates are derived that simplify the implementation of the method in the data system software of a wind tunnel. In addition, recommendations for sets of "wind-off" data points are made that take typical model support system constraints into account. Explicit equations of the confidence intervals on the model weight and center of gravity coordinates and two different error analyses of the model weight prediction are also discussed in the appendices of the paper.

  16. Assessing Long-Term Wind Conditions by Combining Different Measure-Correlate-Predict Algorithms: Preprint

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, J.; Chowdhury, S.; Messac, A.; Hodge, B. M.

    2013-08-01

    This paper significantly advances the hybrid measure-correlate-predict (MCP) methodology, enabling it to account for variations of both wind speed and direction. The advanced hybrid MCP method uses the recorded data of multiple reference stations to estimate the long-term wind condition at a target wind plant site. The results show that the accuracy of the hybrid MCP method is highly sensitive to the combination of the individual MCP algorithms and reference stations. It was also found that the best combination of MCP algorithms varies based on the length of the correlation period.

  17. Combined Active and Reactive Power Control of Wind Farms based on Model Predictive Control

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Wang, Jianhui

    2017-01-01

    This paper proposes a combined wind farm controller based on Model Predictive Control (MPC). Compared with the conventional decoupled active and reactive power control, the proposed control scheme considers the significant impact of active power on voltage variations due to the low X=R ratio...... of wind farm collector systems. The voltage control is improved. Besides, by coordination of active and reactive power, the Var capacity is optimized to prevent potential failures due to Var shortage, especially when the wind farm operates close to its full load. An analytical method is used to calculate...

  18. Informativeness of Wind Data in Linear Madden-Julian Oscillation Prediction

    Science.gov (United States)

    2016-08-15

    equatorial cloud patterns that are not actu- ally part of a predictable wave in the real physical mem- ory variables (inertia or water vapor or perhaps...outgoing longwave radiation (OLR) related to the MJO on intraseasonal timescales in the tropics has been examined for a variety of LIMs using OLR and...encompassing Outgoing Longwave Radiation (OLR) and zonal wind at 850 and 200 hPa (u850 and u200). The relevance of including wind field information in

  19. Causes of bat fatalities at wind turbines: Hypotheses and predictions

    Science.gov (United States)

    Cryan, P.M.; Barclay, R.M.R.

    2009-01-01

    Thousands of industrial-scale wind turbines are being built across the world each year to meet the growing demand for sustainable energy. Bats of certain species are dying at wind turbines in unprecedented numbers. Species of bats consistently affected by turbines tend to be those that rely on trees as roosts and most migrate long distances. Although considerable progress has been made in recent years toward better understanding the problem, the causes of bat fatalities at turbines remain unclear. In this synthesis, we review hypothesized causes of bat fatalities at turbines. Hypotheses of cause fall into 2 general categoriesproximate and ultimate. Proximate causes explain the direct means by which bats die at turbines and include collision with towers and rotating blades, and barotrauma. Ultimate causes explain why bats come close to turbines and include 3 general types: random collisions, coincidental collisions, and collisions that result from attraction of bats to turbines. The random collision hypothesis posits that interactions between bats and turbines are random events and that fatalities are representative of the bats present at a site. Coincidental hypotheses posit that certain aspects of bat distribution or behavior put them at risk of collision and include aggregation during migration and seasonal increases in flight activity associated with feeding or mating. A surprising number of attraction hypotheses suggest that bats might be attracted to turbines out of curiosity, misperception, or as potential feeding, roosting, flocking, and mating opportunities. Identifying, prioritizing, and testing hypothesized causes of bat collisions with wind turbines are vital steps toward developing practical solutions to the problem. ?? 2009 American Society of Mammalogists.

  20. Bayesian state prediction of wind turbine bearing failure

    DEFF Research Database (Denmark)

    Herp, Jürgen; Ramezani, Mohammad H.; Bach-Andersen, Martin

    2017-01-01

    A statistical approach to abstract and predict turbine states in an online manner has been developed. Online inference is performed on temperature measurement residuals to predict the failure state δn steps ahead of time. In this framework a case study is performed showing the ability to predict...... bearing failure 33 days, on average, ahead of time. The approach is based on the separability of the sufficient statistics and a hidden variable, namely the state length. The predictive probability is conditioned on the data available, as well as the state variables. It is shown that the predictive...... probability can be calculated by a model for the samples and a hazard function describing the probability for undergoing a state transition. This study is concerned with the prior training of the model, for which run-to-failure time series of bearing measurements are used. For the sample model prediction...

  1. Resource Sharing in the Logistics of the Offshore Wind Farm Installation Process based on a Simulation Study

    Directory of Open Access Journals (Sweden)

    Thies Beinke

    2017-06-01

    Full Text Available This present contribution examines by means of a discrete event and agent-based simulation the potential of a joint use of resources in the installation phase of offshore wind energy. To this end, wind farm projects to be installed simultaneously are being examined, the impact of weather restrictions on the processes of loading, transport and installation are also taken into consideration, and both the wind farm specific resource allocation and the approach of a resource pool or resource sharing, respectively, are being implemented. This study is motivated by the large number of wind farms that will be installed in the future and by the potential savings that might be realized through resource sharing. While, so far, the main driver of the resource sharing approach has been the end consumer market, it has been applied in more and more areas, even in relatively conservative industries such as logistics. After the presentation of the backgrounds and of the underlying methodology, and the description of the prior art in this context, the network of the offshore wind energy installation phase will be described. This is the basis for the subsequent determination of the savings potential of a shared resource utilization, which is determined by the performance indicators such as the total installation time and degree of utilization of the resources. The results of the simulation show that weather restrictions have a significant effect on the installation times and the usage times of the resources as well as on their degree of utilization. In addition, the resource sharing approach, has been identified to have significant savings potential for the offshore wind energy installation.

  2. Wind turbine control and model predictive control for uncertain systems

    DEFF Research Database (Denmark)

    Thomsen, Sven Creutz

    as disturbance models for controller design. The theoretical study deals with Model Predictive Control (MPC). MPC is an optimal control method which is characterized by the use of a receding prediction horizon. MPC has risen in popularity due to its inherent ability to systematically account for time...

  3. The new generation of tools for prediction of wind power potential and site selection

    DEFF Research Database (Denmark)

    Lundtang Petersen, Erik

    2012-01-01

    Today a number of well established models and methodologies exist for estimating resources and design parameters and in many cases they work well. This is true if good local data are available for calibrating the models or for verification. But the wind energy community is still hampered by many...

  4. Verification of some numerical models for operationally predicting mesoscale winds aloft

    International Nuclear Information System (INIS)

    Cornett, J.S.; Randerson, D.

    1977-01-01

    Four numerical models are described for predicting mesoscale winds aloft for a 6 h period. These models are all tested statistically against persistence as the control forecast and against predictions made by operational forecasters. Mesoscale winds aloft data were used to initialize the models and to verify the predictions on an hourly basis. The model yielding the smallest root-mean-square vector errors (RMSVE's) was the one based on the most physics which included advection, ageostrophic acceleration, vertical mixing and friction. Horizontal advection was found to be the most important term in reducing the RMSVE's followed by ageostrophic acceleration, vertical advection, surface friction and vertical mixing. From a comparison of the mean absolute errors based on up to 72 independent wind-profile predictions made by operational forecasters, by the most complete model, and by persistence, we conclude that the model is the best wind predictor in the free air. In the boundary layer, the results tend to favor the forecaster for direction predictions. The speed predictions showed no overall superiority in any of these three models

  5. Aero-acoustic noise of wind turbines. Noise prediction models

    Energy Technology Data Exchange (ETDEWEB)

    Maribo Pedersen, B. [ed.

    1997-12-31

    Semi-empirical and CAA (Computational AeroAcoustics) noise prediction techniques are the subject of this expert meeting. The meeting presents and discusses models and methods. The meeting may provide answers to the following questions: What Noise sources are the most important? How are the sources best modeled? What needs to be done to do better predictions? Does it boil down to correct prediction of the unsteady aerodynamics around the rotor? Or is the difficult part to convert the aerodynamics into acoustics? (LN)

  6. Prediction of Typhoon Wind Speeds under Global Warming Conditions

    Energy Technology Data Exchange (ETDEWEB)

    Choun, Young Sun; Kim, Min Kyu [KAERI, Daejeon (Korea, Republic of); Kang, Ju Whan; Kim, Yang Seon [Mokpo National University, Muan (Korea, Republic of)

    2016-05-15

    The continuous increase of SST by global warming conditions in the western North Pacific Ocean results in an increased occurrence of supertyphoons in East Asia and the Korean Peninsula. Recent numerical experiments have found that the central pressures of two historical typhoons, Maemi (2003) and Rusa (2002), which recorded the highest storm surges along the coasts of the Korean Peninsula, dropped about 19 and 17 hPa, respectively, when considering the future SST (a warming of 3.9 .deg. C for 100 years) over the East China Sea. The maximum wind speeds increase under global warming conditions. The probability of occurrence of super-typhoons increases in the future. The estimated return period for supertyphoons affecting the Younggwang site is about 1,000,000 years.

  7. Prediction of Typhoon Wind Speeds under Global Warming Conditions

    International Nuclear Information System (INIS)

    Choun, Young Sun; Kim, Min Kyu; Kang, Ju Whan; Kim, Yang Seon

    2016-01-01

    The continuous increase of SST by global warming conditions in the western North Pacific Ocean results in an increased occurrence of supertyphoons in East Asia and the Korean Peninsula. Recent numerical experiments have found that the central pressures of two historical typhoons, Maemi (2003) and Rusa (2002), which recorded the highest storm surges along the coasts of the Korean Peninsula, dropped about 19 and 17 hPa, respectively, when considering the future SST (a warming of 3.9 .deg. C for 100 years) over the East China Sea. The maximum wind speeds increase under global warming conditions. The probability of occurrence of super-typhoons increases in the future. The estimated return period for supertyphoons affecting the Younggwang site is about 1,000,000 years.

  8. Two-Stage Coordinated Operational Strategy for Distributed Energy Resources Considering Wind Power Curtailment Penalty Cost

    Directory of Open Access Journals (Sweden)

    Jing Qiu

    2017-07-01

    Full Text Available The concept of virtual power plant (VPP has been proposed to facilitate the integration of distributed renewable energy. VPP behaves similar to a single entity that aggregates a collection of distributed energy resources (DERs such as distributed generators, storage devices, flexible loads, etc., so that the aggregated power outputs can be flexibly dispatched and traded in electricity markets. This paper presents an optimal scheduling model for VPP participating in day-ahead (DA and real-time (RT markets. In the DA market, VPP aims to maximize the expected profit and reduce the risk in relation to uncertainties. The risk is measured by a risk factor based on the mean-variance Markowitz theory. In the RT market, VPP aims to minimize the imbalance cost and wind power curtailment by adjusting the scheduling of DERs in its portfolio. In case studies, the benefits (e.g., surplus profit and reduced wind power curtailment of aggregated VPP operation are assessed. Moreover, we have investigated how these benefits are affected by different risk-aversion levels and uncertainty levels. According to the simulation results, the aggregated VPP scheduling approach can effectively help the integration of wind power, mitigate the impact of uncertainties, and reduce the cost of risk-aversion.

  9. Wind gust estimation by combining numerical weather prediction model and statistical post-processing

    Science.gov (United States)

    Patlakas, Platon; Drakaki, Eleni; Galanis, George; Spyrou, Christos; Kallos, George

    2017-04-01

    The continuous rise of off-shore and near-shore activities as well as the development of structures, such as wind farms and various offshore platforms, requires the employment of state-of-the-art risk assessment techniques. Such analysis is used to set the safety standards and can be characterized as a climatologically oriented approach. Nevertheless, a reliable operational support is also needed in order to minimize cost drawbacks and human danger during the construction and the functioning stage as well as during maintenance activities. One of the most important parameters for this kind of analysis is the wind speed intensity and variability. A critical measure associated with this variability is the presence and magnitude of wind gusts as estimated in the reference level of 10m. The latter can be attributed to different processes that vary among boundary-layer turbulence, convection activities, mountain waves and wake phenomena. The purpose of this work is the development of a wind gust forecasting methodology combining a Numerical Weather Prediction model and a dynamical statistical tool based on Kalman filtering. To this end, the parameterization of Wind Gust Estimate method was implemented to function within the framework of the atmospheric model SKIRON/Dust. The new modeling tool combines the atmospheric model with a statistical local adaptation methodology based on Kalman filters. This has been tested over the offshore west coastline of the United States. The main purpose is to provide a useful tool for wind analysis and prediction and applications related to offshore wind energy (power prediction, operation and maintenance). The results have been evaluated by using observational data from the NOAA's buoy network. As it was found, the predicted output shows a good behavior that is further improved after the local adjustment post-process.

  10. Report on the use of stability parameters and mesoscale modelling in short-term prediction[Wind speed at wind farm sites

    Energy Technology Data Exchange (ETDEWEB)

    Badger, J.; Giebel, G.; Guo Larsen, X.; Skov Nielsen, T.; Aalborg Nielsen, H.; Madsen, Henrik; Toefting, J.

    2007-06-15

    In this report investigations using atmospheric stability measures to improve wind speed predictions at wind farm sites are described. Various stability measures have been calculated based on numerical weather prediction model output. Their ability to improve the wind speed predictions is assessed at three locations. One of the locations is in complex terrain. Mesoscale modelling has been carried out using KAMM at this location. The characteristics of the measured winds are captured well by the mesoscale modelling. It can be seen that the atmospheric stability plays an important role in determining how the flow is influence by the terrain. A prediction system employing a look-up table approach based on wind class simulations is presented. The mesoscale modelling results produced by KAMM were validated using an alternative mesoscale model called WRF. A good agreement in the results of KAMM and WRF was found. It is shown that including a stability parameter in physical and/or statistical modelling can improve the wind speed predictions at a wind farm site. A concept for the inclusion of a stability measure in the WPPT prediction system is presented, and the testing of the concept is outlined. (au)

  11. Bayesian based Prognostic Model for Predictive Maintenance of Offshore Wind Farms

    DEFF Research Database (Denmark)

    Asgarpour, Masoud; Sørensen, John Dalsgaard

    2018-01-01

    monitoring, fault prediction and predictive maintenance of offshore wind components is defined. The diagnostic model defined in this paper is based on degradation, remaining useful lifetime and hybrid inspection threshold models. The defined degradation model is based on an exponential distribution......The operation and maintenance costs of offshore wind farms can be significantly reduced if existing corrective actions are performed as efficient as possible and if future corrective actions are avoided by performing sufficient preventive actions. In this paper a prognostic model for degradation...

  12. Discussion of “Prediction intervals for short-term wind farm generation forecasts” and “Combined nonparametric prediction intervals for wind power generation”

    DEFF Research Database (Denmark)

    Pinson, Pierre; Tastu, Julija

    2014-01-01

    A new score for the evaluation of interval forecasts, the so-called coverage width-based criterion (CWC), was proposed and utilized.. This score has been used for the tuning (in-sample) and genuine evaluation (out-ofsample) of prediction intervals for various applications, e.g., electric load [1......], electricity prices [2], general purpose prediction [3], and wind power generation [4], [5]. Indeed, two papers by the same authors appearing in the IEEE Transactions On Sustainable Energy employ that score and use it to conclude on the comparative quality of alternative approaches to interval forecasting...

  13. Wind versus coal: Comparing the local economic impacts of energy resource development in Appalachia

    International Nuclear Information System (INIS)

    Collins, Alan R.; Hansen, Evan; Hendryx, Michael

    2012-01-01

    Two energy development scenarios were compared for the Coal River Mountain in Raleigh County, West Virginia: (1) mountaintop mining (MTM) of coal, and (2) wind energy plus underground mining of coal. Economic impact computations over the life of each energy development scenario were made on a county basis for output of goods and services, the number of jobs created, and local earnings. Externality costs were assigned monetary values for coal mining and subtracted from earnings. Premature mortality within the general population due to additional coal mining accounted for 96% of these external cost computations. The results showed that economic output over the life of each scenario was twice as high for MTM mining as wind energy plus underground coal mining. Over the short term, employment and earnings were higher for MTM mining, but towards the end of the scenario, cumulative employment and earnings became higher under scenario (2). When local externality costs were subtracted from local earnings, MTM coal production had an overall negative net social impact on the citizens of Raleigh County. The external costs of MTM coal production provide an explanation of the existence of a “resource curse” and the conflicting results of output versus income provide insights into why coal-producing counties are underdeveloped. - Highlights: ► Mountaintop mining (MTM) was compared to wind plus underground mining. ► Economic output was twice as high for MTM. ► Employment and earnings were cumulatively higher for wind energy. ► Including local externality costs, MTM had an overall negative net social impact. ► Results provide insights into why coal-producing counties are underdeveloped.

  14. Health-aware Model Predictive Control of Wind Turbines using Fatigue Prognosis

    DEFF Research Database (Denmark)

    Sardi, Hector Eloy Sanchez; Escobet, Teressa; Puig, Vicenc

    2015-01-01

    Wind turbines components are subject to considerable fatigue due to extreme environmental conditions to which are exposed, especially those located offshore. Interest in the integration of control with fatigue load minimization has increased in recent years. The integration of a system health...... management module with the control provides a mechanism for the wind turbine to operate safely and optimize the trade-off between components life and energy production. The research presented in this paper explores the integration of model predictive control (MPC) with fatigue-based prognosis approach...... to minimize the damage of wind turbine components (the blades). The controller objective is modified by adding an extra criterion that takes into account the accumulated damage. The scheme is implemented and tested using a high fidelity simulator of a utility scale wind turbine....

  15. Joint Evaluation of the Wave and Offshore Wind Energy Resources in the Developing Countries

    Directory of Open Access Journals (Sweden)

    Eugen Rusu

    2017-11-01

    Full Text Available The objective of the present work is to assess the global wind and wave resources in the vicinity of some developing countries by evaluating 16-year of data (2001–2016, coming from the European Centre for Medium range Weather Forecast (ECMWF. Until now, not much work has been done to evaluate and use the renewable energy sources from these marine environments. This is because most of the attention was focused on more promising areas, such as the European coasts, which are more advanced in terms of technical and economical aspects. A general perspective of the current energy market from the selected target areas is first presented, indicating at the same time the progresses that have been reported in the field of the renewable energy. Besides the spatial and seasonal variations of the marine resources considered, the results also indicate the energy potential of these coastal environments as well as the performances of some offshore wind turbines, which may operate in these regions.

  16. A Gaussian process regression based hybrid approach for short-term wind speed prediction

    International Nuclear Information System (INIS)

    Zhang, Chi; Wei, Haikun; Zhao, Xin; Liu, Tianhong; Zhang, Kanjian

    2016-01-01

    Highlights: • A novel hybrid approach is proposed for short-term wind speed prediction. • This method combines the parametric AR model with the non-parametric GPR model. • The relative importance of different inputs is considered. • Different types of covariance functions are considered and combined. • It can provide both accurate point forecasts and satisfactory prediction intervals. - Abstract: This paper proposes a hybrid model based on autoregressive (AR) model and Gaussian process regression (GPR) for probabilistic wind speed forecasting. In the proposed approach, the AR model is employed to capture the overall structure from wind speed series, and the GPR is adopted to extract the local structure. Additionally, automatic relevance determination (ARD) is used to take into account the relative importance of different inputs, and different types of covariance functions are combined to capture the characteristics of the data. The proposed hybrid model is compared with the persistence model, artificial neural network (ANN), and support vector machine (SVM) for one-step ahead forecasting, using wind speed data collected from three wind farms in China. The forecasting results indicate that the proposed method can not only improve point forecasts compared with other methods, but also generate satisfactory prediction intervals.

  17. An Intelligent Ensemble Neural Network Model for Wind Speed Prediction in Renewable Energy Systems.

    Science.gov (United States)

    Ranganayaki, V; Deepa, S N

    2016-01-01

    Various criteria are proposed to select the number of hidden neurons in artificial neural network (ANN) models and based on the criterion evolved an intelligent ensemble neural network model is proposed to predict wind speed in renewable energy applications. The intelligent ensemble neural model based wind speed forecasting is designed by averaging the forecasted values from multiple neural network models which includes multilayer perceptron (MLP), multilayer adaptive linear neuron (Madaline), back propagation neural network (BPN), and probabilistic neural network (PNN) so as to obtain better accuracy in wind speed prediction with minimum error. The random selection of hidden neurons numbers in artificial neural network results in overfitting or underfitting problem. This paper aims to avoid the occurrence of overfitting and underfitting problems. The selection of number of hidden neurons is done in this paper employing 102 criteria; these evolved criteria are verified by the computed various error values. The proposed criteria for fixing hidden neurons are validated employing the convergence theorem. The proposed intelligent ensemble neural model is applied for wind speed prediction application considering the real time wind data collected from the nearby locations. The obtained simulation results substantiate that the proposed ensemble model reduces the error value to minimum and enhances the accuracy. The computed results prove the effectiveness of the proposed ensemble neural network (ENN) model with respect to the considered error factors in comparison with that of the earlier models available in the literature.

  18. Human Resource Predictive Analytics HRPA For HR Management In Organizations

    Directory of Open Access Journals (Sweden)

    Sujeet N. Mishra

    2015-08-01

    Full Text Available Human resource predictive analytics is an evolving application field of analytics for HRM purposes. The purpose of HRM is measuring employee performance and engagement studying workforce collaboration patterns analyzing employee churn and turnover and modelling employee lifetime value. The motive of applying HRPA is to optimize performances and produce better return on investment for organizations through decision making based on data collection HR metrics and predictive models. The paper is divided into three sections to understand the emergence of HR predictive analytics for HRM. Firstly the paper introduces the concept of HRPA. Secondly the paper discusses three aspects of HRPA a Need b Approach amp Application c Impact. Lastly the paper leads to the conclusion on HRPA.

  19. The National Wind Erosion Research Network: Building a standardized long-term data resource for aeolian research, modeling and land management

    Science.gov (United States)

    Webb, Nicholas P.; Herrick, Jeffrey E.; Van Zee, Justin W; Courtright, Ericha M; Hugenholtz, Ted M; Zobeck, Ted M; Okin, Gregory S.; Barchyn, Thomas E; Billings, Benjamin J; Boyd, Robert A.; Clingan, Scott D; Cooper, Brad F; Duniway, Michael C.; Derner, Justin D.; Fox, Fred A; Havstad, Kris M.; Heilman, Philip; LaPlante, Valerie; Ludwig, Noel A; Metz, Loretta J; Nearing, Mark A; Norfleet, M Lee; Pierson, Frederick B; Sanderson, Matt A; Sharrat, Brenton S; Steiner, Jean L; Tatarko, John; Tedela, Negussie H; Todelo, David; Unnasch, Robert S; Van Pelt, R Scott; Wagner, Larry

    2016-01-01

    The National Wind Erosion Research Network was established in 2014 as a collaborative effort led by the United States Department of Agriculture’s Agricultural Research Service and Natural Resources Conservation Service, and the United States Department of the Interior’s Bureau of Land Management, to address the need for a long-term research program to meet critical challenges in wind erosion research and management in the United States. The Network has three aims: (1) provide data to support understanding of basic aeolian processes across land use types, land cover types, and management practices, (2) support development and application of models to assess wind erosion and dust emission and their impacts on human and environmental systems, and (3) encourage collaboration among the aeolian research community and resource managers for the transfer of wind erosion technologies. The Network currently consists of thirteen intensively instrumented sites providing measurements of aeolian sediment transport rates, meteorological conditions, and soil and vegetation properties that influence wind erosion. Network sites are located across rangelands, croplands, and deserts of the western US. In support of Network activities, http://winderosionnetwork.org was developed as a portal for information about the Network, providing site descriptions, measurement protocols, and data visualization tools to facilitate collaboration with scientists and managers interested in the Network and accessing Network products. The Network provides a mechanism for engaging national and international partners in a wind erosion research program that addresses the need for improved understanding and prediction of aeolian processes across complex and diverse land use types and management practices.

  20. Predicting the Extreme Loads on a Wind Turbine Considering Uncertainty in Airfoil Data

    DEFF Research Database (Denmark)

    Abdallah, Imad; Natarajan, Anand; Sørensen, John Dalsgaard

    2014-01-01

    The sources contributing to uncertainty in a wind turbine blade static airfoil data include wind tunnel testing, CFD calculations, 3D rotational corrections based on CFD or emprircal models, surface roughness corrections, Reynolds number corrections, expansion to the full 360-degree angle of attack...... range, validation by full scale measurements, and geometric distortions of the blade during manufacturing and under loading. In this paper a stochastic model of the static airfoil data is proposed to supplement the prediction of extreme loads effects for large wind turbines. It is shown...... that the uncertainty in airfoil data can have e significant impact on the prediction of extreme loads effects depending on the component, and the correlation along the span of the blade....

  1. Enhanced Voltage Control of VSC-HVDC Connected Offshore Wind Farms Based on Model Predictive Control

    DEFF Research Database (Denmark)

    Guo, Yifei; Gao, Houlei; Wu, Qiuwei

    2018-01-01

    This paper proposes an enhanced voltage control strategy (EVCS) based on model predictive control (MPC) for voltage source converter based high voltage direct current (VSCHVDC) connected offshore wind farms (OWFs). In the proposed MPC based EVCS, all wind turbine generators (WTGs) as well...... as the wind farm side VSC are optimally coordinated to keep voltages within the feasible range and reduce system power losses. Considering the high ratio of the OWF collector system, the effects of active power outputs of WTGs on voltage control are also taken into consideration. The predictive model of VSC...... with a typical cascaded control structure is derived in details. The sensitivity coefficients are calculated by an analytical method to improve the computational efficiency. A VSC-HVDC connected OWF with 64 WTGs was used to validate the proposed voltage control strategy....

  2. An overview of the reliability prediction related aspects of high power IGBTs in wind power applications

    DEFF Research Database (Denmark)

    Busca, Christian; Teodorescu, Remus; Blaabjerg, Frede

    2011-01-01

    Reliability is becoming more and more important as the size and number of installed Wind Turbines (WTs) increases. Very high reliability is especially important for offshore WTs because the maintenance and repair of such WTs in case of failures can be very expensive. WT manufacturers need...... to consider the reliability aspect when they design new power converters. By designing the power converter considering the reliability aspect the manufacturer can guarantee that the end product will ensure high availability. This paper represents an overview of the various aspects of reliability prediction...... of high power Insulated Gate Bipolar Transistors (IGBTs) in the context of wind power applications. At first the latest developments and future predictions about wind energy are briefly discussed. Next the dominant failure mechanisms of high power IGBTs are described and the most commonly used lifetime...

  3. Energy Yield prediction of offshore wind farm clusters at the EERA–DTOC European project

    DEFF Research Database (Denmark)

    Cantero, E.; Sanz, J.; Lozano, S.

    power plant interconnection and energy yield models all interrelated with a simplified cost model for the evaluation of layout scenarios. The overall aim is to produce an efficient, easy to use and flexible tool - to facilitate the optimized design of individual and clusters of offshore wind farms....... A demonstration phase at the end of the project will assess the value of the integrated design tool with the help of potential end-users from industry. In order to provide an accurate value of the expected net energy yield, the offshore wind resource assessment process has been reviewed as well as the sources...... and gross energy yield....

  4. Comparison of four Adaboost algorithm based artificial neural networks in wind speed predictions

    International Nuclear Information System (INIS)

    Liu, Hui; Tian, Hong-qi; Li, Yan-fei; Zhang, Lei

    2015-01-01

    Highlights: • Four hybrid algorithms are proposed for the wind speed decomposition. • Adaboost algorithm is adopted to provide a hybrid training framework. • MLP neural networks are built to do the forecasting computation. • Four important network training algorithms are included in the MLP networks. • All the proposed hybrid algorithms are suitable for the wind speed predictions. - Abstract: The technology of wind speed prediction is important to guarantee the safety of wind power utilization. In this paper, four different hybrid methods are proposed for the high-precision multi-step wind speed predictions based on the Adaboost (Adaptive Boosting) algorithm and the MLP (Multilayer Perceptron) neural networks. In the hybrid Adaboost–MLP forecasting architecture, four important algorithms are adopted for the training and modeling of the MLP neural networks, including GD-ALR-BP algorithm, GDM-ALR-BP algorithm, CG-BP-FR algorithm and BFGS algorithm. The aim of the study is to investigate the promoted forecasting percentages of the MLP neural networks by the Adaboost algorithm’ optimization under various training algorithms. The hybrid models in the performance comparison include Adaboost–GD-ALR-BP–MLP, Adaboost–GDM-ALR-BP–MLP, Adaboost–CG-BP-FR–MLP, Adaboost–BFGS–MLP, GD-ALR-BP–MLP, GDM-ALR-BP–MLP, CG-BP-FR–MLP and BFGS–MLP. Two experimental results show that: (1) the proposed hybrid Adaboost–MLP forecasting architecture is effective for the wind speed predictions; (2) the Adaboost algorithm has promoted the forecasting performance of the MLP neural networks considerably; (3) among the proposed Adaboost–MLP forecasting models, the Adaboost–CG-BP-FR–MLP model has the best performance; and (4) the improved percentages of the MLP neural networks by the Adaboost algorithm decrease step by step with the following sequence of training algorithms as: GD-ALR-BP, GDM-ALR-BP, CG-BP-FR and BFGS

  5. Model Predictive Control of Trailing Edge Flaps on a wind turbine blade

    DEFF Research Database (Denmark)

    Castaignet, Damien; Poulsen, Niels Kjølstad; Buhl, Thomas

    2011-01-01

    Trailing Edge Flaps on wind turbine blades have been studied in order to achieve fatigue load reduction on the turbine components. We show in this paper how Model Predictive Control can be used to do frequency weighted control of the trailing edge flaps in order to reduce fatigue damage on the bl...

  6. Improved prediction of aerodynamic noise from wind turbines

    Energy Technology Data Exchange (ETDEWEB)

    Guidati, G.; Bareiss, R.; Wagner, S. [Univ. of Stuttgart, Inst. of Aerodynamics and Gasdynamics, Stuttgart (Germany)

    1997-12-31

    This paper focuses on an improved prediction model for inflow-turbulence noise which takes the true airfoil shape into account. Predictions are compared to the results of acoustic measurements on three 2D-models of 0.25 m chord. Two of the models have NACA-636xx airfoils of 12% and 18% relative thickness. The third airfoil was acoustically optimized by using the new prediction model. In the experiments the turbulence intensity of the flow was strongly increased by mounting a grid with 60 mm wide meshes and 12 mm thick rods onto the tunnel exhaust nozzle. The sound radiated from the airfoil was distinguished by the tunnel background noise by using an acoustic antenna consisting of a cross array of 36 microphones in total. An application of a standard beam-forming algorithm allows to determine how much noise is radiated from different parts of the models. This procedure normally results in a peak at the leading and trailing edge of the airfoil. The strength of the leading-edge peak is taken as the source strength for inflow-turbulence noise. (LN) 14 refs.

  7. Evaporation suppression from reservoirs using floating covers: Lab scale wind-tunnel observations and mechanistic model predictions

    Science.gov (United States)

    Or, Dani; Lehmann, Peter; Aminzadeh, Milad; Sommer, Martina; Wey, Hannah; Krentscher, Christiane; Wunderli, Hans; Breitenstein, Daniel

    2017-04-01

    The competition over dwindling fresh water resources is expected to intensify with projected increase in human population in arid regions, expansion of irrigated land and changes in climate and drought patterns. The volume of water stored in reservoirs would also increase to mitigate seasonal shortages due to rainfall variability and to meet irrigation water needs. By some estimates up to half of the stored water is lost to evaporation, thereby exacerbating the water scarcity problem. Recently, there is an upsurge in the use of self-assembling floating covers to suppress evaporation, yet the design and implementation remain largely empirical. We report a systematic experimental evaluation of different cover types and external drivers (radiation, wind, wind plus radiation) on evaporation suppression and energy balance of a 1.4 m2 basin placed in a wind-tunnel. Surprisingly, evaporation suppression by black and white floating covers (balls and plates) were similar despite significantly different energy balance regimes over the cover surfaces. Moreover, the evaporation suppression efficiency was a simple function of the uncovered area (square root of the uncovered fraction) with linear relations with the covered area in some cases. The thermally decoupled floating covers offer an efficient solution to the evaporation suppression with limited influence of the surface energy balance (water temperature for black and white covers was similar and remained nearly constant). The results will be linked with a predictive evaporation-energy balance model and issues of spatial scales and long exposure times will be studied.

  8. Overview and Meteorological Validation of the Wind Integration National Dataset toolkit

    Energy Technology Data Exchange (ETDEWEB)

    Draxl, C. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Hodge, B. M. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Clifton, A. [National Renewable Energy Laboratory (NREL), Golden, CO (United States); McCaa, J. [3TIER by VAisala, Seattle, WA (United States)

    2015-04-13

    The Wind Integration National Dataset (WIND) Toolkit described in this report fulfills these requirements, and constitutes a state-of-the-art national wind resource data set covering the contiguous United States from 2007 to 2013 for use in a variety of next-generation wind integration analyses and wind power planning. The toolkit is a wind resource data set, wind forecast data set, and wind power production and forecast data set derived from the Weather Research and Forecasting (WRF) numerical weather prediction model. WIND Toolkit data are available online for over 116,000 land-based and 10,000 offshore sites representing existing and potential wind facilities.

  9. Predicting extreme loads effects on wind turbines considering uncertainty in airfoil data

    DEFF Research Database (Denmark)

    Abdallah, Imad; Natarajan, Anand; Sørensen, John Dalsgaard

    2013-01-01

    The sources contributing to uncertainty in a wind turbine blade static airfoil data include wind tunnel testing, CFD calculations, 3D rotational corrections based on CFD or empirical models, surface roughness corrections, Reynolds number corrections, expansion to the full 360-degree angle of atta...... that the uncertainty in airfoil data can have a significant impact on the prediction of extreme loads effects depending on the component, and the correlation along the span of the blade.......The sources contributing to uncertainty in a wind turbine blade static airfoil data include wind tunnel testing, CFD calculations, 3D rotational corrections based on CFD or empirical models, surface roughness corrections, Reynolds number corrections, expansion to the full 360-degree angle of attack...... range, validation by full scale measurements, and geometric distortions of the blade during manufacturing and under loading. In this paper a stochastic model of the static airfoil data is proposed to supplement the prediction of extreme loads effects for large wind turbines. It is shown...

  10. Observations and Predictability of Gap Winds in the Salmon River Canyon of Central Idaho, USA

    Directory of Open Access Journals (Sweden)

    Natalie S. Wagenbrenner

    2018-01-01

    Full Text Available This work investigates gap winds in a steep, deep river canyon prone to wildland fire. The driving mechanisms and the potential for forecasting the gap winds are investigated. The onset and strength of the gap winds are found to be correlated to the formation of an along-gap pressure gradient linked to periodic development of a thermal trough in the Pacific Northwest, USA. Numerical simulations are performed using a reanalysis dataset to investigate the ability of numerical weather prediction (NWP to simulate the observed gap wind events, including the timing and flow characteristics within the canyon. The effects of model horizontal grid spacing and terrain representation are considered. The reanalysis simulations suggest that horizontal grid spacings used in operational NWP could be sufficient for simulating the gap flow events given the regional-scale depression in which the Salmon River Canyon is situated. The strength of the events, however, is under-predicted due, at least in part, to terrain smoothing in the model. Routine NWP, however, is found to have mixed results in terms of forecasting the gap wind events, primarily due to problems in simulating the regional sea level pressure system correctly.

  11. Assessment of Predictive Capabilities of L1 Orbiters using Realtime Solar Wind Data

    Science.gov (United States)

    Holmes, J.; Kasper, J. C.; Welling, D. T.

    2017-12-01

    Realtime measurements of solar wind conditions at L1 point allow us to predict geomagnetic activity at Earth up to an hour in advance. These predictions are quantified in the form of geomagnetic indices such as Kp and Ap, allowing for a concise, standardized prediction and measurement system. For years, the Space Weather Prediction Center used ACE realtime solar wind data to develop its one and four-hour Kp forecasts, but has in the past year switched to using DSCOVR data as its source. In this study, the performance of both orbiters in predicting Kp over the course of one month was assessed in an attempt to determine whether or not switching to DSCOVR data has resulted in improved forecasts. The period of study was chosen to encompass a time when the satellites were close to each other, and when moderate to high activity was observed. Kp predictions were made using the Geospace Model, part of the Space Weather Modeling Framework, to simulate conditions based on observed solar wind parameters. The performance of each satellite was assessed by comparing the model output to observed data.

  12. A comparison of predicted and observed turbulent wind fields present in natural and internal wind park environments

    Energy Technology Data Exchange (ETDEWEB)

    Kelly, N D; Wright, A D

    1991-10-01

    This paper assesses the accuracy of simulated wind fields for both the natural flow and that within a wind park environment. The simulated fields are compared with the observed ones in both the time and frequency domains. Actual measurements of the wind fields and the derived kinematic scaling parameters upwind and downwind of a large San Gorgonio Pass wind park are used. The deviations in the modeled wind field from the observed are discussed. 10 refs., 6 figs., 2 tabs.

  13. Correaltion of full-scale drag predictions with flight measurements on the C-141A aircraft. Phase 2: Wind tunnel test, analysis, and prediction techniques. Volume 1: Drag predictions, wind tunnel data analysis and correlation

    Science.gov (United States)

    Macwilkinson, D. G.; Blackerby, W. T.; Paterson, J. H.

    1974-01-01

    The degree of cruise drag correlation on the C-141A aircraft is determined between predictions based on wind tunnel test data, and flight test results. An analysis of wind tunnel tests on a 0.0275 scale model at Reynolds number up to 3.05 x 1 million/MAC is reported. Model support interference corrections are evaluated through a series of tests, and fully corrected model data are analyzed to provide details on model component interference factors. It is shown that predicted minimum profile drag for the complete configuration agrees within 0.75% of flight test data, using a wind tunnel extrapolation method based on flat plate skin friction and component shape factors. An alternative method of extrapolation, based on computed profile drag from a subsonic viscous theory, results in a prediction four percent lower than flight test data.

  14. Model predictive control of PMSG-based wind turbines for frequency regulation in an isolated grid

    DEFF Research Database (Denmark)

    Wang, Haixin; Yang, Junyou; Ma, Yiming

    2017-01-01

    on system parameters, a model predictive controller (MPC) of wind farm is designed to generate torque compensation for each deloaded WTG. The key feature of this strategy is that each WTG reacts to grid disturbances in different ways, which depends on generator speeds. Hardware-in-the-loop simulation...... in different speed regions and provide WTGs a certain capacity of power reserves. Considering the torque compensation may bring about power oscillation, speed reference of conventional pitch control system should be reset. Moreover, to suppress disturbances of load and wind speed as well as overcome dependence...

  15. Bayesian based Prognostic Model for Predictive Maintenance of Offshore Wind Farms

    DEFF Research Database (Denmark)

    Asgarpour, Masoud

    2017-01-01

    monitoring, fault detection and predictive maintenance of offshore wind components is defined. The diagnostic model defined in this paper is based on degradation, remaining useful lifetime and hybrid inspection threshold models. The defined degradation model is based on an exponential distribution......The operation and maintenance costs of offshore wind farms can be significantly reduced if existing corrective actions are performed as efficient as possible and if future corrective actions are avoided by performing sufficient preventive actions. In this paper a prognostic model for degradation...

  16. Online Bayesian Learning with Natural Sequential Prior Distribution Used for Wind Speed Prediction

    Science.gov (United States)

    Cheggaga, Nawal

    2017-11-01

    Predicting wind speed is one of the most important and critic tasks in a wind farm. All approaches, which directly describe the stochastic dynamics of the meteorological data are facing problems related to the nature of its non-Gaussian statistics and the presence of seasonal effects .In this paper, Online Bayesian learning has been successfully applied to online learning for three-layer perceptron's used for wind speed prediction. First a conventional transition model based on the squared norm of the difference between the current parameter vector and the previous parameter vector has been used. We noticed that the transition model does not adequately consider the difference between the current and the previous wind speed measurement. To adequately consider this difference, we use a natural sequential prior. The proposed transition model uses a Fisher information matrix to consider the difference between the observation models more naturally. The obtained results showed a good agreement between both series, measured and predicted. The mean relative error over the whole data set is not exceeding 5 %.

  17. A Gaussian mixture copula model based localized Gaussian process regression approach for long-term wind speed prediction

    International Nuclear Information System (INIS)

    Yu, Jie; Chen, Kuilin; Mori, Junichi; Rashid, Mudassir M.

    2013-01-01

    Optimizing wind power generation and controlling the operation of wind turbines to efficiently harness the renewable wind energy is a challenging task due to the intermittency and unpredictable nature of wind speed, which has significant influence on wind power production. A new approach for long-term wind speed forecasting is developed in this study by integrating GMCM (Gaussian mixture copula model) and localized GPR (Gaussian process regression). The time series of wind speed is first classified into multiple non-Gaussian components through the Gaussian mixture copula model and then Bayesian inference strategy is employed to incorporate the various non-Gaussian components using the posterior probabilities. Further, the localized Gaussian process regression models corresponding to different non-Gaussian components are built to characterize the stochastic uncertainty and non-stationary seasonality of the wind speed data. The various localized GPR models are integrated through the posterior probabilities as the weightings so that a global predictive model is developed for the prediction of wind speed. The proposed GMCM–GPR approach is demonstrated using wind speed data from various wind farm locations and compared against the GMCM-based ARIMA (auto-regressive integrated moving average) and SVR (support vector regression) methods. In contrast to GMCM–ARIMA and GMCM–SVR methods, the proposed GMCM–GPR model is able to well characterize the multi-seasonality and uncertainty of wind speed series for accurate long-term prediction. - Highlights: • A novel predictive modeling method is proposed for long-term wind speed forecasting. • Gaussian mixture copula model is estimated to characterize the multi-seasonality. • Localized Gaussian process regression models can deal with the random uncertainty. • Multiple GPR models are integrated through Bayesian inference strategy. • The proposed approach shows higher prediction accuracy and reliability

  18. Bat mortality and activity at a Northern Iowa wind resource area

    Science.gov (United States)

    Jain, A.A.; Koford, Rolf R.; Hancock, A.W.; Zenner, G.G.

    2011-01-01

    We examined bat collision mortality, activity and species composition at an 89-turbine wind resource area in farmland of north-central Iowa from mid-Apr. to mid-Dec., 2003 and mid-Mar. to mid-Dec., 2004. We found 30 bats beneath turbines on cleared ground and gravel access areas in 2003 and 45 bats in 2004. After adjusting for search probability, search efficiency and scavenging rate, we estimated total bat mortality at 396 ?? 72 (95 ci) in 2003 and 636 ?? 112 (95 ci) in 2004. Although carcasses were mostly migratory tree bats, we found a considerable proportion of little brown bats (Myotis lucifugus). We recorded 1465 bat echolocation call files at turbine sites ( 34.88 call files/detector-night) and 1536 bat call files at adjacent non-turbine sites ( 36.57 call files/detector-night). Bat activity did not differ significantly between turbine and non-turbine sites. A large proportion of recorded call files were made by Myotis sp. but this may be because we detected activity at ground level only. There was no relationship between types of turbine lights and either collision mortality or echolocation activity. The highest levels of bat echolocation activity and collision mortality were recorded during Jul. and Aug. during the autumn dispersal and migration period. The fatality rates for bats in general and little brown bats in particular were higher at the Top of Iowa Wind Resource Area than at other, comparable studies in the region. Future efforts to study behavior of bats in flight around turbines as well as cumulative impact studies should not ignore non-tree dwelling bats, generally regarded as minimally affected. ?? 2011, American Midland Naturalist.

  19. Two approaches for incorporating climate change into natural resource management planning at Wind Cave National Park

    Science.gov (United States)

    Symstad, Amy J.; Long, Andrew J.; Stamm, John; King, David A.; Bachelet, Dominque M.; Norton, Parker A.

    2014-01-01

    Wind Cave National Park (WICA) protects one of the world’s longest caves, has large amounts of high quality, native vegetation, and hosts a genetically important bison herd. The park’s relatively small size and unique purpose within its landscape requires hands-on management of these and other natural resources, all of which are interconnected. Anthropogenic climate change presents an added challenge to WICA natural resource management because it is characterized by large uncertainties, many of which are beyond the control of park and National Park Service (NPS) staff. When uncertainty is high and control of this uncertainty low, scenario planning is an appropriate tool for determining future actions. In 2009, members of the NPS obtained formal training in the use of scenario planning in order to evaluate it as a tool for incorporating climate change into NPS natural resource management planning. WICA served as one of two case studies used in this training exercise. Although participants in the training exercise agreed that the scenario planning process showed promise for its intended purpose, they were concerned that the process lacked the scientific rigor necessary to defend the management implications derived from it in the face of public scrutiny. This report addresses this concern and others by (1) providing a thorough description of the process of the 2009 scenario planning exercise, as well as its results and management implications for WICA; (2) presenting the results of a follow-up, scientific study that quantitatively simulated responses of WICA’s hydrological and ecological systems to specific climate projections; (3) placing these climate projections and the general climate scenarios used in the scenario planning exercise in the broader context of available climate projections; and (4) comparing the natural resource management implications derived from the two approaches. Wind Cave National Park (WICA) protects one of the world’s longest caves

  20. A Diagnostic and Predictive Framework for Wind Turbine Drive Train Monitoring

    DEFF Research Database (Denmark)

    Bach-Andersen, Martin

    Vast amount of data are collected minute by minute from wind turbines around the world. This thesis represents a focused research effort into discovering new ways of processing these data streams in order to gain insights which can be used to lower the maintenance costs of wind turbines and increase...... the turbine availability. First, it is demonstrated how simple sensor data streams can be leveraged based on a combination of non-linear predictive models and unsupervised fault detection to provide warnings of a critical bearing failure more than a month earlier compared to existing alarm systems. Second......, early fault identification based on analysis of complex vibration patterns which is a domain previously reserved for human experts, is shown to be solved with high accuracy using deep learning architecture strained in a fully supervised sense from the data collected in a large scale wind turbine...

  1. Prediction and Reduction of Noise from a 2.3 MW Wind Turbine

    International Nuclear Information System (INIS)

    Leloudas, G; Zhu, W J; Soerensen, J N; Shen, W Z; Hjort, S

    2007-01-01

    We address the issue of noise emission from a 2.3 MW SWT-2.3-93 wind turbine and compare simulations from a semi-empirical acoustic model with measurements. The noise measurements were taken at the Hoevsoere test site for large wind turbines. The acoustic model is based on the Blade-Element Momentum (BEM) technique and various semi-empirical acoustic relations. The comparison demonstrates a generally good agreement between predicted and measured noise levels. The acoustic model is further employed to carry out a parametrical study to optimize the performance/noise of the wind turbine by changing tip speed and pitch setting. We show that it is possible to reduce the noise level up to 2 dB(A) without sacrificing too much the power yield

  2. A LIDAR-assisted model predictive controller added on a traditional wind turbine controller

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood; Hansen, Morten Hartvig

    2016-01-01

    LIDAR-assisted collective pitch control shows promising results for load reduction in the full load operating region of horizontal axis wind turbines (WT). Utilizing LIDARs in WT control can be approached in different ways; One method is to design the WT controller from ground up based on the LIDAR...... measurements. Nevertheless, to make the LIDAR-assisted controller easily implementable on existing wind turbines, one can design a controller that is added to the original and existing WT controller. This add-on solution makes it easier to prove the applicability and performance of the LIDAR-assisted WT...... control and opens the market of retrofitting existing wind turbines with the new technology. In this paper, we suggest a model predictive controller (MPC) that is added to the basic gain scheduled PI controller of a WT to enhance the performance of the closed loop system using LIDAR measurements...

  3. Research on Short-Term Wind Power Prediction Based on Combined Forecasting Models

    Directory of Open Access Journals (Sweden)

    Zhang Chi

    2016-01-01

    Full Text Available Short-Term wind power forecasting is crucial for power grid since the generated energy of wind farm fluctuates frequently. In this paper, a physical forecasting model based on NWP and a statistical forecasting model with optimized initial value in the method of BP neural network are presented. In order to make full use of the advantages of the models presented and overcome the limitation of the disadvantage, the equal weight model and the minimum variance model are established for wind power prediction. Simulation results show that the combination forecasting model is more precise than single forecasting model and the minimum variance combination model can dynamically adjust weight of each single method, restraining the forecasting error further.

  4. Gain-Scheduled Model Predictive Control of Wind Turbines using Laguerre Functions

    DEFF Research Database (Denmark)

    Adegas, Fabiano Daher; Wisniewski, Rafal; Larsen, Lars Finn Sloth

    2014-01-01

    This paper presents a systematic approach to design gain-scheduled predictive controllers for wind turbines. The predictive control law is based on Laguerre functions to parameterize control signals and a parameter-dependent cost function that is analytically determined from turbine data....... The approach can be utilized to the design of new controllers and to represent existing gain-scheduled controllers as predictive controllers. The numerical example and simulations illustrate the design of a speed controller augmented with active damping of the tower fore-aft displacement....

  5. Application of numerical weather prediction in wind power forecasting: Assessment of the diurnal cycle

    Directory of Open Access Journals (Sweden)

    Tobias Heppelmann

    2017-06-01

    Full Text Available For a secure integration of weather dependent renewable energies in Germany's mixed power supply, precise forecasts of expected wind power are indispensable. These in turn are heavily dependent on numerical weather prediction (NWP. With this relevant area of application, NWP models need to be evaluated concerning new variables such as wind speed at hub heights of wind power plants. This article presents verification results of the deterministic NWP forecasts of the global ICON model, its ICON-EU nest, the COSMO-EU, and the COSMO-DE as well as of the ensemble prediction system COSMO-DE-EPS of the German National Weather Service (DWD, against wind mast observations. The focus is on the diurnal cycle in the Planetary Boundary Layer as wind power forecasts for Germany exhibit pronounced systematic amplitude and phase errors in the morning and evening hours. NWP forecasts with lead times up to 48 hours are examined. All considered NWP models reveal shortcomings concerning the representation of the diurnal cycle. Especially in summertime at onshore locations, when Low-Level Jets form, nocturnal wind speeds at hub height are underestimated. In the COSMO model, stable conditions are not sufficiently reflected in the first part of the night and the vertical mixing after sunrise establishes too late. The verification results of the COSMO-DE-EPS confirm the deficiencies of the deterministic forecasts. The deficiencies are present in all ensemble members and thus indicate potential for improvement not only in the model physics parameterization but also concerning the physical ensemble perturbations.

  6. Vibration Analysis and Time Series Prediction for Wind Turbine Gearbox Prognostics

    Directory of Open Access Journals (Sweden)

    Hossam A. Gabbar

    2013-01-01

    Full Text Available Premature failure of a gearbox in a wind turbine poses a high risk of increasing the operational and maintenance costs and decreasing the profit margins. Prognostics and health management (PHM techniques are widely used to access the current health condition of the gearbox and project it in future to predict premature failures. This paper proposes such techniques for predicting gearbox health condition index extracted from the vibration signals emanating from the gearbox. The progression of the monitoring index is predicted using two different prediction techniques, adaptive neuro-fuzzy inference system (ANFIS and nonlinear autoregressive model with exogenous inputs (NARX. The proposed prediction techniques are evaluated through sun-spot data-set and applied on vibration based health related monitoring index calculated through psychoacoustic phenomenon. A comparison is given for their prediction accuracy. The results are helpful in understanding the relationship of machine conditions, the corresponding indicating features, the level of damage/degradation, and their progression.

  7. Wind Technologies & Evolving Opportunities (Presentation)

    Energy Technology Data Exchange (ETDEWEB)

    Robichaud, R.

    2014-07-01

    This presentation covers opportunities for wind technology; wind energy market trends; an overview of the National Wind Technology Center near Boulder, Colorado; wind energy price and cost trends; wind turbine technology improvements; and wind resource characterization improvements.

  8. Energy Coordinative Optimization of Wind-Storage-Load Microgrids Based on Short-Term Prediction

    Directory of Open Access Journals (Sweden)

    Changbin Hu

    2015-02-01

    Full Text Available According to the topological structure of wind-storage-load complementation microgrids, this paper proposes a method for energy coordinative optimization which focuses on improvement of the economic benefits of microgrids in the prediction framework. First of all, the external characteristic mathematical model of distributed generation (DG units including wind turbines and storage batteries are established according to the requirements of the actual constraints. Meanwhile, using the minimum consumption costs from the external grid as the objective function, a grey prediction model with residual modification is introduced to output the predictive wind turbine power and load at specific periods. Second, based on the basic framework of receding horizon optimization, an intelligent genetic algorithm (GA is applied to figure out the optimum solution in the predictive horizon for the complex non-linear coordination control model of microgrids. The optimum results of the GA are compared with the receding solution of mixed integer linear programming (MILP. The obtained results show that the method is a viable approach for energy coordinative optimization of microgrid systems for energy flow and reasonable schedule. The effectiveness and feasibility of the proposed method is verified by examples.

  9. Critical Resources for Emerging Clean Technologies: Case study of Wind Turbines. World Resource Forum 2012; 21-23 October, 2012; Beijing, China

    DEFF Research Database (Denmark)

    Habib, Komal; Wenzel, Henrik

    2012-01-01

    approach to resource criticality assessment on the technology level and it compares alternative wind turbine technologies. It involves the trade-off between higher Dysprosium and Neodymium consumption in the direct drive turbine and higher Copper consumption of the gearbox turbine and it strives......The dilemma of resource scarcity is not new but its focus has changed from fossil fuels depletion to the mineral resource constraints of clean energy technologies. In order to be independent of fossil fuels we need broad implementation of clean technologies such as wind turbines, photovoltaic...... to quantify and assess this trade-off. [1] Graedel, T.E., Barr, R., Chandler, C., Chase, T., Choi, J., Christoffersen, L., Friedlander, E., Henly, C., Jun,C., Nassar, N.T., Schechner, D., Warren, S., Yang, M and Zhu, C. 2012. Methodology of Metal Criticality Determination. Environ. Sci. Technol: 46 (2). pp...

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2013-10-01

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

  11. Wind Speed Prediction Using a Univariate ARIMA Model and a Multivariate NARX Model

    Directory of Open Access Journals (Sweden)

    Erasmo Cadenas

    2016-02-01

    Full Text Available Two on step ahead wind speed forecasting models were compared. A univariate model was developed using a linear autoregressive integrated moving average (ARIMA. This method’s performance is well studied for a large number of prediction problems. The other is a multivariate model developed using a nonlinear autoregressive exogenous artificial neural network (NARX. This uses the variables: barometric pressure, air temperature, wind direction and solar radiation or relative humidity, as well as delayed wind speed. Both models were developed from two databases from two sites: an hourly average measurements database from La Mata, Oaxaca, Mexico, and a ten minute average measurements database from Metepec, Hidalgo, Mexico. The main objective was to compare the impact of the various meteorological variables on the performance of the multivariate model of wind speed prediction with respect to the high performance univariate linear model. The NARX model gave better results with improvements on the ARIMA model of between 5.5% and 10. 6% for the hourly database and of between 2.3% and 12.8% for the ten minute database for mean absolute error and mean squared error, respectively.

  12. A GIS-assisted approach to wide-area wind resource assessment and site selection for the state of Colorado

    Energy Technology Data Exchange (ETDEWEB)

    Brower, M.C. [Brower & Company, Andover, MA (United States); Hurley, P. [RLA Consulting, Bothell, WA (United States); Simon, R. [Consulting Meteorologist, Mill Valley, CA (United States)

    1996-12-31

    This paper describes the methodology and results of a wide-area wind resource assessment and site selection in Colorado. This was the first phase in a three-part assessment and monitoring program conducted for the State of Colorado Office of Energy Conservation and several collaborating utilities. The objective of this phase was to identify up to 20 candidate sites for evaluation and possible long-term monitoring. This was accomplished using a geographic information system (GIS), which takes into account such factors as topography, existing wind resource data, locations of transmission lines, land cover, and land use. The resulting list of sites recommended for evaluation in Phase 2 of the study includes locations throughout Colorado, but most are in the eastern plains. The GIS wind siting model may be modified and updated in the future as additional information becomes available. 3 figs., 1 tab.

  13. Feature selection in wind speed prediction systems based on a hybrid coral reefs optimization – Extreme learning machine approach

    International Nuclear Information System (INIS)

    Salcedo-Sanz, S.; Pastor-Sánchez, A.; Prieto, L.; Blanco-Aguilera, A.; García-Herrera, R.

    2014-01-01

    Highlights: • A novel approach for short-term wind speed prediction is presented. • The system is formed by a coral reefs optimization algorithm and an extreme learning machine. • Feature selection is carried out with the CRO to improve the ELM performance. • The method is tested in real wind farm data in USA, for the period 2007–2008. - Abstract: This paper presents a novel approach for short-term wind speed prediction based on a Coral Reefs Optimization algorithm (CRO) and an Extreme Learning Machine (ELM), using meteorological predictive variables from a physical model (the Weather Research and Forecast model, WRF). The approach is based on a Feature Selection Problem (FSP) carried out with the CRO, that must obtain a reduced number of predictive variables out of the total available from the WRF. This set of features will be the input of an ELM, that finally provides the wind speed prediction. The CRO is a novel bio-inspired approach, based on the simulation of reef formation and coral reproduction, able to obtain excellent results in optimization problems. On the other hand, the ELM is a new paradigm in neural networks’ training, that provides a robust and extremely fast training of the network. Together, these algorithms are able to successfully solve this problem of feature selection in short-term wind speed prediction. Experiments in a real wind farm in the USA show the excellent performance of the CRO–ELM approach in this FSP wind speed prediction problem

  14. The predictability of wind gusts associated with winter storms over central Europe

    Science.gov (United States)

    Pantillon, Florian; Knippertz, Peter; Corsmeier, Ulrich

    2017-04-01

    Wind storms associated with low-pressure systems from the North Atlantic are the most important natural hazard for central Europe. Although the forecast of winter storms has generally improved over the last decades, a detailed prediction of the associated wind gusts is still challenging due to the multiple scales involved. Here we report about new insights into the synoptic-scale predictability of 25 severe storms of the 1995-2015 period using data from the recently available homogeneous re-forecast dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF) evaluated against ERA-Interim reanalysis. In contrast to operational predictions, the re-forecast dataset is generated with an identical data assimilation and forecasting system over a time period long enough to allow a statistical analysis of historical events. The predictability of the storms is assessed with two sets of metrics: (a) the position and intensity to investigate the storms' propagation and dynamics and (b) the Storm Severity Index (SSI) to estimate the impact of wind gusts associated with the storms. This analysis shows that the storms are captured by the ensemble re-forecasts up to 2-4 days ahead only, which restricts the use of ensemble mean and spread to relatively short lead times. However, the metrics also show that the storms are correctly predicted at least by some ensemble members up to one week ahead. Following this result, the Extreme Forecast Index (EFI) and Shift of Tails (SOT) are computed from the individual re-forecasts and the model climate. Using these indices, we show that the model has some skill in forecasting the area covered by extreme wind gusts up to 10 days, which indicates clear potential for the early warning of storms. However, a large variability is found between the predictability of individual storms, which does not appear to be related to the storms' characteristics. This may be due to the limited sample of 25 cases, but also suggests that each

  15. Using innovative technologies to ease wind resource penetration into power grid

    Energy Technology Data Exchange (ETDEWEB)

    Tholomier, D.; Rola, J.; Willemse, C. [Areva T and D Automation Canada Inc., Monteal, PQ (Canada)

    2008-07-01

    This paper summarized several innovative concepts brought through Substation Automation and Energy management software that help to improve the integration of wind generation to power grid systems. It addressed the need for coordinated control between wind generator excitation systems and static or dynamic VAR compensation equipment. The latest developments in the area of wind forecasting applications were also presented. In addition, the main features of the new International Electrotechnical Commission (IEC) 61400-25 standard were explained in terms of its benefits for the integration of wind farms into the electric system. This standard allows vendor-independent data access to, and command of, the wind farm via remote links. It was derived from IEC61850, and has been developed to modularize object models, to model information exchanges and map communication profiles related to wind turbines. The focus of IEC61400-25 is on the communications between wind power plant components such as wind turbines as well as SCADA and Substation Automation Systems. Energy management and trading and risk management were presented as other alternative soft methods for improving large wind farm dispatchability. It was concluded that regulators will need to establish suitable market frameworks for wind operators to receive financial incentives to invest, which would result in a better wind generation integration. This would also require a closer co-operation between real-time automation experts and wind turbine suppliers to progress into the development of innovative wind farm control strategies. 12 figs.

  16. Prediction of windings temperature rise in induction motors supplied with distorted voltage

    International Nuclear Information System (INIS)

    Gnacinski, P.

    2008-01-01

    One of the features of ship power systems is a different level and intensity of disturbances appearing during routine operation - the rms voltage value and frequency deviation, voltage unbalance and waveform voltage distortion. As a result, marine induction machines are exposed to overheating due to the lowered voltage quality. This paper is devoted to windings temperature rise prediction in marine induction cage machines supplied with distorted voltage, which means real voltage conditions. The proposed method of prediction does not require detailed knowledge of the thermal properties of a machine. Although the method was developed for marine induction motors, it is applicable for industry machines supplied with distorted voltage. It can also be generalized and used for estimation of the steady state windings temperature rise of any electrical machinery in various work conditions

  17. Implementation of wind power in the Norwegian market; the reason why some of the best wind resources in Europe were not utilised by 2010

    International Nuclear Information System (INIS)

    Blindheim, Bernt

    2013-01-01

    Norway has some of the best wind resources in Europe. In 1999, the Norwegian Parliament committed to attain an annual onshore wind power production goal of 3.0 TWh by 2010; however, in 2010, onshore wind power production measured only 1.0 TWh. This article discusses the reasons that this goal was not achieved. The analysis addresses the key figures on the strategic, tactical and operational levels. This model is combined with a time line that seeks to define when different actors should have secured concessions and funding to achieve the goal. After introducing the time line, a list of questions is introduced for these key actors. The three-level model, the time line and the questions constitute the analytical framework. Explanations for the failure to achieve the goal may be identified on all three levels. However, the primary explanatory factors were political uncertainty in the support scheme and wind power's role in the energy market in general; both of these factors are identified on the strategic level. Uncertainty on the strategic level influenced the lower levels, which led to bottlenecks in the concession process and jittery investors who thought that the risk of investment in wind power was too high. - Highlights: • Implementation of wind power in the Norwegian energy system up to 2010. • The concession process, the support scheme and the marked players are considered. • Uncertainty about the support scheme slowed down the implementation process. • The concession process has been a bottleneck. • The support scheme has only to a certain degree trigged investments

  18. Predicting Automotive Interior Noise Including Wind Noise by Statistical Energy Analysis

    OpenAIRE

    Yoshio Kurosawa

    2017-01-01

    The applications of soundproof materials for reduction of high frequency automobile interior noise have been researched. This paper presents a sound pressure prediction technique including wind noise by Hybrid Statistical Energy Analysis (HSEA) in order to reduce weight of acoustic insulations. HSEA uses both analytical SEA and experimental SEA. As a result of chassis dynamo test and road test, the validity of SEA modeling was shown, and utility of the method was confirmed.

  19. Lifetime prediction of towers with respect to lateral and longitudinal wind load

    Czech Academy of Sciences Publication Activity Database

    Pospíšil, Stanislav; Hračov, Stanislav; Lahodný, J.; Janata, V.; Urushadze, Shota

    2014-01-01

    Roč. 55, č. 2 (2014), s. 117-126 ISSN 1028-365X R&D Projects: GA MPO(CZ) FR-TI3/654; GA ČR(CZ) GA103/09/0094; GA ČR(CZ) GP13-41574P Institutional support: RVO:68378297 Keywords : lifetime prediction * spectrum * towers * wind load * fatigue Subject RIV: JM - Building Engineering http://www.iass-structures.org/index.cfm/journal.article?aID=702

  20. Remotely sensed data fusion for offshore wind energy resource mapping; Fusion de donnees satellitaires pour la cartographie du potentiel eolien offshore

    Energy Technology Data Exchange (ETDEWEB)

    Ben Ticha, M.B

    2007-11-15

    Wind energy is a component of an energy policy contributing to a sustainable development. Last years, offshore wind parks have been installed offshore. These parks benefit from higher wind speeds and lower turbulence than onshore. To sit a wind park, it is necessary to have a mapping of wind resource. These maps are needed at high spatial resolution to show wind energy resource variations at the scale of a wind park. Wind resource mapping is achieved through the description of the spatial variations of statistical parameters characterizing wind climatology. For a precise estimation of these statistical parameters, high temporal resolution wind speed and direction measurements are needed. However, presently, there is no data source allying high spatial resolution and high temporal resolution. We propose a data fusion method taking advantage of the high spatial resolution of some remote sensing instruments (synthetic aperture radars) and the high temporal resolution of other remote sensing instruments (scatterometers). The data fusion method is applied to a case study and the results quality is assessed. The results show the pertinence of data fusion for the mapping of wind energy resource offshore. (author)

  1. A pilot golden eagle population study in the Altamont Pass Wind Resource Area, California

    Energy Technology Data Exchange (ETDEWEB)

    Hunt, G. [California Univ., Santa Cruz, CA (United States). Predatory Bird Research Group

    1995-05-01

    Orloff and Flannery (1992) estimated that several hundred reports are annually killed by turbine collisions, wire strikes, and electrocutions at the Altamont Pass Wind Resource Area (WRA). The most common fatalities were those of red-tailed hawks (Buteo jamaicensis), American kestrels (Falco sparvatius), and golden eagles (Aquila chrysaetos), with lesser numbers of turkey vultures (Cathartes aura), common ravens (Corvus corax), bam owls (Tyto alba), and others. Among the species of raptors killed at Altamont Pass, the one whose local population is most likely to be impacted is the golden eagle. Besides its being less abundant than the others, the breeding and recruitment rates of golden eagles are naturally slow, increasing their susceptibility to decline as a result of mortality influences. The golden eagle is a species afforded special federal protection because of its inclusion within the Bald Eagle Protection Act as amended in 1963. There are no provisions within the Act which would allow the killing ``taking`` of golden eagles by WRA structures. This report details the results of field studies conducted during 19941. The primary purpose of the investigation is to lay the groundwork for determining whether or not turbine strikes and other hazards related to energy at Altamont Pass may be expected to affect golden eagles on a population basis. We also seek an understanding of the physical and biotic circumstances which attract golden eagles to the WRA within the context of the surrounding landscape and the conditions under which they are killed by wind turbines. Such knowledge may suggest turbine-related or habitat modifications that would result in a lower incidence of eagle mortality.

  2. Active Power Optimal Control of Wind Turbines with Doubly Fed Inductive Generators Based on Model Predictive Control

    Directory of Open Access Journals (Sweden)

    Guo Jiuwang

    2015-01-01

    Full Text Available Because of the randomness and fluctuation of wind energy, as well as the impact of strongly nonlinear characteristic of variable speed constant frequency (VSCF wind power generation system with doubly fed induction generators (DFIG, traditional active power control strategies are difficult to achieve high precision control and the output power of wind turbines is more fluctuated. In order to improve the quality of output electric energy of doubly fed wind turbines, on the basis of analyzing the operating principles and dynamic characteristics of doubly fed wind turbines, this paper proposes a new active power optimal control method of doubly fed wind turbines based on predictive control theory. This method uses state space model of wind turbines, based on the prediction of the future state of wind turbines, moves horizon optimization, and meanwhile, gets the control signals of pitch angle and generator torque. Simulation results show that the proposed control strategies can guarantee the utilization efficiency for wind energy. Simultaneously, they can improve operation stability of wind turbines and the quality of electric energy.

  3. Predicting and mapping potential Whooping Crane stopover habitat to guide site selection for wind energy projects.

    Science.gov (United States)

    Belaire, J Amy; Kreakie, Betty J; Keitt, Timothy; Minor, Emily

    2014-04-01

    Migratory stopover habitats are often not part of planning for conservation or new development projects. We identified potential stopover habitats within an avian migratory flyway and demonstrated how this information can guide the site-selection process for new development. We used the random forests modeling approach to map the distribution of predicted stopover habitat for the Whooping Crane (Grus americana), an endangered species whose migratory flyway overlaps with an area where wind energy development is expected to become increasingly important. We then used this information to identify areas for potential wind power development in a U.S. state within the flyway (Nebraska) that minimize conflicts between Whooping Crane stopover habitat and the development of clean, renewable energy sources. Up to 54% of our study area was predicted to be unsuitable as Whooping Crane stopover habitat and could be considered relatively low risk for conflicts between Whooping Cranes and wind energy development. We suggest that this type of analysis be incorporated into the habitat conservation planning process in areas where incidental take permits are being considered for Whooping Cranes or other species of concern. Field surveys should always be conducted prior to construction to verify model predictions and understand baseline conditions. © 2013 Society for Conservation Biology.

  4. Smoothing out the volatility of South Africa's wind and PV energy resources

    CSIR Research Space (South Africa)

    Bofinger, S

    2015-10-01

    Full Text Available Solar PV & wind are the cheapest new-build options per kWh in South Africa. By 2020, a mix of PV, wind and flexible gas (LNG-based) costs the same as new coal, even without any value given to excess wind/PV energy. South Africa has abundant solar...

  5. The Structure of Vertical Wind Shear in Tropical Cyclone Environments: Implications for Forecasting and Predictability

    Science.gov (United States)

    Finocchio, Peter M.

    The vertical wind shear measured between 200 and 850 hPa is commonly used to diagnose environmental interactions with a tropical cyclone (TC) and to forecast the storm's intensity and structural evolution. More often than not, stronger vertical shear within this deep layer prohibits the intensification of TCs and leads to predictable asymmetries in precipitation. But such bulk measures of vertical wind shear can occasionally mislead the forecaster. In the first part of this dissertation, we use a series of idealized numerical simulations to examine how a TC responds to changing the structure of unidirectional vertical wind shear while fixing the 200-850-hPa shear magnitude. These simulations demonstrate a significant intensity response, in which shear concentrated in shallow layers of the lower troposphere prevents vortex intensification. We attribute the arrested development of TCs in lower-level shear to the intrusion of mid-level environmental air over the surface vortex early in the simulations. Convection developing on the downshear side of the storm interacts with the intruding air so as to enhance the downward flux of low-entropy air into the boundary layer. We also construct a two-dimensional intensity response surface from a set of simulations that sparsely sample the joint shear height-depth parameter space. This surface reveals regions of the two-parameter space for which TC intensity is particularly sensitive. We interpret these parameter ranges as those which lead to reduced intensity predictability. Despite the robust response to changing the shape of a sheared wind profile in idealized simulations, we do not encounter such sensitivity within a large set of reanalyzed TCs in the Northern Hemisphere. Instead, there is remarkable consistency in the structure of reanalyzed wind profiles around TCs. This is evident in the distributions of two new parameters describing the height and depth of vertical wind shear, which highlight a clear preference for

  6. Comparative Evaluation of the Third-Generation Reanalysis Data for Wind Resource Assessment of the Southwestern Offshore in South Korea

    Directory of Open Access Journals (Sweden)

    Hyun-Goo Kim

    2018-02-01

    Full Text Available This study evaluated the applicability of long-term datasets among third-generation reanalysis data CFSR, ERA-Interim, MERRA, and MERRA-2 to determine which dataset is more suitable when performing wind resource assessment for the ‘Southwest 2.5 GW Offshore Wind Power Project’, which is currently underway strategically in South Korea. The evaluation was performed by comparing the reanalyses with offshore, onshore, and island meteorological tower measurements obtained in and around the southwest offshore. In the pre-processing of the measurement data, the shading sectors due to a meteorological tower were excluded from all observation data, and the measurement heights at the offshore meteorological towers were corrected considering the sea level change caused by tidal difference. To reflect the orographic forcing by terrain features, the reanalysis data were transformed by using WindSim, a flow model based on computational fluid dynamics and statistical-dynamic downscaling. The comparison of the reanalyses with the measurement data showed the fitness in the following order in terms of coefficient of determination: MERRA-2 > CFSR = MERRA > ERA-Interim. Since the measurement data at the onshore meteorological towers strongly revealed a local wind system such as sea-land breeze, it is judged to be inappropriate for use as supplementary data for offshore wind resource assessment.

  7. Resources

    Science.gov (United States)

    ... Colon cancer - resources Cystic fibrosis - resources Depression - resources Diabetes - resources Digestive disease - resources Drug abuse - resources Eating disorders - resources Elder care - resources Epilepsy - resources Family ...

  8. Predicting hurricane wind damage by claim payout based on Hurricane Ike in Texas

    Directory of Open Access Journals (Sweden)

    Ji-Myong Kim

    2016-09-01

    Full Text Available The increasing occurrence of natural disasters and their related damage have led to a growing demand for models that predict financial loss. Although considerable research on the financial losses related to natural disasters has found significant predictors, there has been a lack of comprehensive study that addresses the relationship among vulnerabilities, natural disasters, and the economic losses of individual buildings. This study identifies the vulnerability indicators for hurricanes to establish a metric to predict the related financial loss. We classify hurricane-prone areas by highlighting the spatial distribution of losses and vulnerabilities. This study used a Geographical Information System (GIS to combine and produce spatial data and a multiple regression method to establish a wind damage prediction model. As the dependent variable, we used the value of the Texas Windstorm Insurance Association (TWIA claim payout divided by the appraised values of the buildings to predict real economic loss. As independent variables, we selected a hurricane indicator and built environment vulnerability indicators. The model we developed can be used by government agencies and insurance companies to predict hurricane wind damage.

  9. Linear prediction studies for the solar wind and Saturn kilometric radiation

    Directory of Open Access Journals (Sweden)

    U. Taubenschuss

    2006-11-01

    Full Text Available The external control of Saturn kilometric radiation (SKR by the solar wind has been investigated in the frame of the Linear Prediction Theory (LPT. The LPT establishes a linear filter function on the basis of correlations between input signals, i.e. time profiles for solar wind parameters, and output signals, i.e. time profiles for SKR intensity. Three different experiments onboard the Cassini spacecraft (RPWS, MAG and CAPS yield appropriate data sets for compiling the various input and output signals. The time period investigated ranges from DOY 202 to 326, 2004 and is only limited due to limited availability of CAPS plasma data for the solar wind. During this time Cassini was positioned mainly on the morning side on its orbit around Saturn at low southern latitudes. Four basic solar wind quantities have been found to exert a clear influence on the SKR intensity profile. These quantities are: the solar wind bulk velocity, the solar wind ram pressure, the magnetic field strength of the interplanetary magnetic field (IMF and the y-component of the IMF. All four inputs exhibit nearly the same level of efficiency for the linear prediction indicating that all four inputs are possible drivers for triggering SKR. Furthermore, they act at completely different lag times ranging from ~13 h for the ram pressure to ~52 h for the bulk velocity. The lag time for the magnetic field strength is usually beyond ~40 h and the lag time for the y-component of the magnetic field is located around 30 h. Considering that all four solar wind quantities are interrelated in a corotating interaction region, only the influence of the ram pressure seems to be of reasonable relevance. An increase in ram pressure causes a substantial compression of Saturn's magnetosphere leading to tail collapse, injection of hot plasma from the tail into the outer magnetosphere and finally to an intensification of auroral dynamics and SKR emission. So, after the onset of magnetospheric

  10. Intelligent and robust prediction of short term wind power using genetic programming based ensemble of neural networks

    International Nuclear Information System (INIS)

    Zameer, Aneela; Arshad, Junaid; Khan, Asifullah; Raja, Muhammad Asif Zahoor

    2017-01-01

    Highlights: • Genetic programming based ensemble of neural networks is employed for short term wind power prediction. • Proposed predictor shows resilience against abrupt changes in weather. • Genetic programming evolves nonlinear mapping between meteorological measures and wind-power. • Proposed approach gives mathematical expressions of wind power to its independent variables. • Proposed model shows relatively accurate and steady wind-power prediction performance. - Abstract: The inherent instability of wind power production leads to critical problems for smooth power generation from wind turbines, which then requires an accurate forecast of wind power. In this study, an effective short term wind power prediction methodology is presented, which uses an intelligent ensemble regressor that comprises Artificial Neural Networks and Genetic Programming. In contrast to existing series based combination of wind power predictors, whereby the error or variation in the leading predictor is propagated down the stream to the next predictors, the proposed intelligent ensemble predictor avoids this shortcoming by introducing Genetical Programming based semi-stochastic combination of neural networks. It is observed that the decision of the individual base regressors may vary due to the frequent and inherent fluctuations in the atmospheric conditions and thus meteorological properties. The novelty of the reported work lies in creating ensemble to generate an intelligent, collective and robust decision space and thereby avoiding large errors due to the sensitivity of the individual wind predictors. The proposed ensemble based regressor, Genetic Programming based ensemble of Artificial Neural Networks, has been implemented and tested on data taken from five different wind farms located in Europe. Obtained numerical results of the proposed model in terms of various error measures are compared with the recent artificial intelligence based strategies to demonstrate the

  11. Wind Energy

    International Nuclear Information System (INIS)

    Rodriguez D, J.M.

    1998-01-01

    The general theory of the wind energy conversion systems is presented. The availability of the wind resource in Colombia and the ranges of the speed of the wind in those which is possible economically to use the wind turbines are described. It is continued with a description of the principal technological characteristics of the wind turbines and are split into wind power and wind-powered pumps; and its use in large quantities grouped in wind farms or in autonomous systems. Finally, its costs and its environmental impact are presented

  12. Short-term load and wind power forecasting using neural network-based prediction intervals.

    Science.gov (United States)

    Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

    2014-02-01

    Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time.

  13. Pressure integration technique for predicting wind-induced response in high-rise buildings

    Directory of Open Access Journals (Sweden)

    Aly Mousaad Aly

    2013-12-01

    Full Text Available This paper presents a procedure for response prediction in high-rise buildings under wind loads. The procedure is illustrated in an application example of a tall building exposed to both cross-wind and along-wind loads. The responses of the building in the lateral directions combined with torsion are estimated simultaneously. Results show good agreement with recent design standards; however, the proposed procedure has the advantages of accounting for complex mode shapes, non-uniform mass distribution, and interference effects from the surrounding. In addition, the technique allows for the contribution of higher modes. For accurate estimation of the acceleration response, it is important to consider not only the first two lateral vibrational modes, but also higher modes. Ignoring the contribution of higher modes may lead to underestimation of the acceleration response; on the other hand, it could result in overestimation of the displacement response. Furthermore, the procedure presented in this study can help decision makers, involved in a tall building design/retrofit to choose among innovative solutions like aerodynamic mitigation, structural member size adjustment, damping enhancement, and/or materials change, with an objective to improve the resiliency and the serviceability under extreme wind actions.

  14. Predicting wind-induced vibrations of high-rise buildings using unsteady CFD and modal analysis

    KAUST Repository

    Zhang, Yue

    2015-01-01

    This paper investigates the wind-induced vibration of the CAARC standard tall building model, via unsteady Computational Fluid Dynamics (CFD) and a structural modal analysis. In this numerical procedure, the natural unsteady wind in the atmospheric boundary layer is modeled with an artificial inflow turbulence generation method. Then, the turbulent flow is simulated by the second mode of a Zonal Detached-Eddy Simulation, and a conservative quadrature-projection scheme is adopted to transfer unsteady loads from fluid to structural nodes. The aerodynamic damping that represents the fluid-structure interaction mechanism is determined by empirical functions extracted from wind tunnel experiments. Eventually, the flow solutions and the structural responses in terms of mean and root mean square quantities are compared with experimental measurements, over a wide range of reduced velocities. The significance of turbulent inflow conditions and aeroelastic effects is highlighted. The current methodology provides predictions of good accuracy and can be considered as a preliminary design tool to evaluate the unsteady wind effects on tall buildings.

  15. Smoothing out the volatility of South Africa’s wind and PV energy resources for an increased share of renewables

    CSIR Research Space (South Africa)

    Mushwana, C

    2015-11-01

    Full Text Available : cmushwana@csir.co.za 2 Agenda Background Objectives of the wind and PV resource aggregation study Study progress to-date and Port Elizabeth case study Animated/interactive GUI (wind/PV/Residual load) in the proposed REDZ... O&M costs per MWh); Assumptions: average efficiency for CCGT = 50%, OCGT = 35%; coal = 37%; nuclear = 33%; IRP cost from Jan 2012 escalated with CPI to May 2015; assumed EPC CAPEX inflated by 10% to convert EPC/LCOE into tariff; CSP: 50% annual...

  16. Improving Wind Farm Dispatchability Using Model Predictive Control for Optimal Operation of Grid-Scale Energy Storage

    Directory of Open Access Journals (Sweden)

    Douglas Halamay

    2014-09-01

    Full Text Available This paper demonstrates the use of model-based predictive control for energy storage systems to improve the dispatchability of wind power plants. Large-scale wind penetration increases the variability of power flow on the grid, thus increasing reserve requirements. Large energy storage systems collocated with wind farms can improve dispatchability of the wind plant by storing energy during generation over-the-schedule and sourcing energy during generation under-the-schedule, essentially providing on-site reserves. Model predictive control (MPC provides a natural framework for this application. By utilizing an accurate energy storage system model, control actions can be planned in the context of system power and state-of-charge limitations. MPC also enables the inclusion of predicted wind farm performance over a near-term horizon that allows control actions to be planned in anticipation of fast changes, such as wind ramps. This paper demonstrates that model-based predictive control can improve system performance compared with a standard non-predictive, non-model-based control approach. It is also demonstrated that secondary objectives, such as reducing the rate of change of the wind plant output (i.e., ramps, can be considered and successfully implemented within the MPC framework. Specifically, it is shown that scheduling error can be reduced by 81%, reserve requirements can be improved by up to 37%, and the number of ramp events can be reduced by 74%.

  17. High resolution topography and land cover databases for wind resource assessment using mesoscale models

    Science.gov (United States)

    Barranger, Nicolas; Stathopoulos, Christos; Kallos, Georges

    2013-04-01

    In wind resource assessment, mesoscale models can provide wind flow characteristics without the use of mast measurements. In complex terrain, local orography and land cover data assimilation are essential parameters to accurately simulate the wind flow pattern within the atmospheric boundary layer. State-of-the-art Mesoscale Models such as RAMS usually provides orography and landuse data with of resolution of 30s (about 1km). This resolution is necessary for solving mesocale phenomena accurately but not sufficient when the aim is to quantitatively estimate the wind flow characteristics passing over sharp hills or ridges. Furthermore, the abrupt change in land cover characterization is nor always taken into account in the model with a low resolution land use database. When land cover characteristics changes dramatically, parameters such as roughness, albedo or soil moisture that can highly influence the Atmospheric Boundary Layer meteorological characteristics. Therefore they require to be accurately assimilated into the model. Since few years, high resolution databases derived from satellite imagery (Modis, SRTM, LandSat, SPOT ) are available online. Being converted to RAMS requirements inputs, an evaluation of the model requires to be achieved. For this purpose, three new high resolution land cover and two topographical databases are implemented and tested in RAMS. The analysis of terrain variability is performed using basis functions of space frequency and amplitude. Practically, one and two dimension Fast Fourier Transform is applied to terrain height to reveal the main characteristics of local orography according to the obtained wave spectrum. By this way, a comparison between different topographic data sets is performed, based on the terrain power spectrum entailed in the terrain height input. Furthermore, this analysis is a powerful tool in the determination of the proper horizontal grid resolution required to resolve most of the energy containing spectrum

  18. On-Line Flutter Prediction Tool for Wind Tunnel Flutter Testing using Parameter Varying Estimation Methodology Project

    Data.gov (United States)

    National Aeronautics and Space Administration — ZONA Technology, Inc. (ZONA) proposes to develop an on-line flutter prediction tool for wind tunnel model using the parameter varying estimation (PVE) technique to...

  19. On-Line Flutter Prediction Tool for Wind Tunnel Flutter Testing using Parameter Varying Estimation Methodology, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — ZONA Technology, Inc. (ZONA) proposes to develop an on-line flutter prediction tool for wind tunnel model using the parameter varying estimation (PVE) technique to...

  20. Predictive Understanding of the Oceans' Wind-Driven Circulation on Interdecadal Time Scales

    Energy Technology Data Exchange (ETDEWEB)

    Ghil, Michael [Univ. of California, Los Angeles, CA (United States). Dept. of Atmospheric and Oceanic Sciences and IGPP; Temam, Roger [Indiana Univ., Bloomington, IN (United States). Dept. of Mathematics; Feliks, Y. [IIBR (France); Simonnet, E. [INLN (France); Tachim-Medjo, T. [Florida International Univ. (FIU), Miami, FL (United States)

    2008-09-30

    The goal of this project was to obtain a predictive understanding of a major component of the climate system's interdecadal variability: the oceans' wind-driven circulation. To do so, we developed and applied advanced computational and statistical methods to the problem of climate variability and climate change. The methodology was developed first for models of intermediate complexity, such as the quasi-geostrophic and the primitive equations, which describe the wind-driven, near-surface flow in mid-latitude ocean basins. Our computational work consisted in developing efficient multi-level methods to simulate this flow and study its dependence on physically relevant parameters. Our oceanographic and climate work consisted in applying these methods to study the bifurcations in the wind-driven circulation and their relevance to the flows observed at present and those that might occur in a warmer climate. Both aspects of the work are crucial for the efficient treatment of large-scale, eddy-resolving numerical simulations of the oceans and an increased understanding and better prediction of climate change. Considerable progress has been achieved in understanding ocean-atmosphere interaction in the mid-latitudes. An important by-product of this research is a novel approach to explaining the North Atlantic Oscillation.

  1. Prediction of the Dst index from solar wind parameters by a neural network method

    Science.gov (United States)

    Watanabe, S.; Sagawa, E.; Ohtaka, K.; Shimazu, H.

    2002-12-01

    Using the Elman-type neural network technique, operational models are constructed that predict the Dst index two hours in advance. The input data consist of real-time solar wind velocity, density, and magnetic field data obtained by the Advanced Composition Explorer (ACE) spacecraft since May 1998 (http://www2.crl.go.jp/uk/uk223/service/nnw/index.html). During the period from February to October 1998, eleven storms occurred with minimum Dst values below -80 nT. For ten of these storms the differences between the predicted minimum Dst and the minimum Dst calculated from ground-based magnetometer data were less than 23%. For the remaining one storm (beginning on 19 October 1998) the difference was 48%. The discrepancy is likely to stem from a imperfect correlation between the solar wind parameters near ACE and those near the earth. While the IMF Bz remains to be the most important parameter, other parameters do have their effects. For instance, Dst appears to be enhanced when the azimuthal direction of IMF is toward the sun. A trapezoid-shaped increase in the solar wind density enhances the main phase Dst by almost 10% compared with the case of no density increase. Velocity effects appear to be stronger than the density effects. Our operational models have, in principle, no limitations in applicability with respect to storm intensity.

  2. AE Geomagnetic Index Predictability for High Speed Solar Wind Streams: A Wavelet Decomposition Technique

    Science.gov (United States)

    Guarnieri, Fernando L.; Tsurutani, Bruce T.; Hajra, Rajkumar; Echer, Ezequiel; Gonzalez, Walter D.; Mannucci, Anthony J.

    2014-01-01

    High speed solar wind streams cause geomagnetic activity at Earth. In this study we have applied a wavelet interactive filtering and reconstruction technique on the solar wind magnetic field components and AE index series to allowed us to investigate the relationship between the two. The IMF Bz component was found as the most significant solar wind parameter responsible by the control of the AE activity. Assuming magnetic reconnection associated to southward directed Bz is the main mechanism transferring energy into the magnetosphere, we adjust parameters to forecast the AE index. The adjusted routine is able to forecast AE, based only on the Bz measured at the L1 Lagrangian point. This gives a prediction approximately 30-70 minutes in advance of the actual geomagnetic activity. The correlation coefficient between the observed AE data and the forecasted series reached values higher than 0.90. In some cases the forecast reproduced particularities observed in the signal very well.The high correlation values observed and the high efficacy of the forecasting can be taken as a confirmation that reconnection is the main physical mechanism responsible for the energy transfer during HILDCAAs. The study also shows that the IMF Bz component low frequencies are most important for AE prediction.

  3. Optimal Active Power Control of A Wind Farm Equipped with Energy Storage System based on Distributed Model Predictive Control

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei; Guo, Qinglai

    2016-01-01

    This paper presents the Distributed Model Predictive Control (D-MPC) of a wind farm equipped with fast and short-term Energy Storage System (ESS) for optimal active power control using the fast gradient method via dual decomposition. The primary objective of the D-MPC control of the wind farm...... is power reference tracking from system operators. Besides, by optimal distribution of the power references to individual wind turbines and the ESS unit, the wind turbine mechanical loads are alleviated. With the fast gradient method, the convergence rate of the DMPC is significantly improved which leads...... to a reduction of the iteration number. Accordingly, the communication burden is reduced. Case studies demonstrate that the additional ESS unit can lead to a larger wind turbine load reduction, compared to the conventional wind farm control without ESS. Moreover, the efficiency of the developed D-MPC algorithm...

  4. Predictive control strategies for wind turbine system based on permanent magnet synchronous generator.

    Science.gov (United States)

    Maaoui-Ben Hassine, Ikram; Naouar, Mohamed Wissem; Mrabet-Bellaaj, Najiba

    2016-05-01

    In this paper, Model Predictive Control and Dead-beat predictive control strategies are proposed for the control of a PMSG based wind energy system. The proposed MPC considers the model of the converter-based system to forecast the possible future behavior of the controlled variables. It allows selecting the voltage vector to be applied that leads to a minimum error by minimizing a predefined cost function. The main features of the MPC are low current THD and robustness against parameters variations. The Dead-beat predictive control is based on the system model to compute the optimum voltage vector that ensures zero-steady state error. The optimum voltage vector is then applied through Space Vector Modulation (SVM) technique. The main advantages of the Dead-beat predictive control are low current THD and constant switching frequency. The proposed control techniques are presented and detailed for the control of back-to-back converter in a wind turbine system based on PMSG. Simulation results (under Matlab-Simulink software environment tool) and experimental results (under developed prototyping platform) are presented in order to show the performances of the considered control strategies. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

  5. Predicting the aeroelastic behavior of a wind-tunnel model using transonic small disturbance theory

    Science.gov (United States)

    Silva, Walter A.; Bennett, Robert M.

    1990-01-01

    The CAP-TSD (Computational Aeroelasticity Program - Transonic Small Disturbance) code, developed at the NASA-Langley Research Center, is applied to the Active Flexible Wing (AFW) wind-tunnel model for prediction of the model's transonic aeroelastic behavior. Static aeroelastic solutions using CAP-TSD are computed. Dynamic (flutter) analyses are then performed as perturbations about the static aeroelastic deformations of the AFW. The accuracy of the static aeroelastic procedure is investigated by comparing analytical results to those from AFW wind-tunnel experiments. Dynamic results are presented in the form of root loci at different Mach numbers for a heavy gas and for air test mediums. The resultant flutter boundaries for both gases, and the effects of viscous damping and angle of attack on the flutter boundary in air, are also presented.

  6. Numerical Prediction for the Size and Shape of a Flare in a Cross–Wind

    Directory of Open Access Journals (Sweden)

    W. Vicente y Rodríguez

    2009-10-01

    Full Text Available A computational fluid–dynamics model is used to simulate the turbulent combustion in a flare exposed to a cross–wind. Our research is mostly focused on the cross flow velocity influence to flame aerodynamics. The flow simulation is performed as three dimensional along a Cartesian coordinates system. In order to simulate the combustion process, a fast–chemistry model with a 1–step global irreversible reaction to form CO2 and H2O is used. A radiation model is used to identify the mean flame trajectory. The simulated configuration consists in a propane discharge into an air stream, get ting oxygen supply from the cross–wind. The velocity of this cross–flow is increased from 0.8 m/s to 12 m/s. Comparative analysis of our predicted values with respect to available experimental results shows good agreement in terms of flame length as well as inclination angles.

  7. Wave Disturbance Reduction of a Floating Wind Turbine Using a Reference Model-based Predictive Control

    DEFF Research Database (Denmark)

    Christiansen, Søren; Tabatabaeipour, Seyed Mojtaba; Bak, Thomas

    2013-01-01

    a controller designed for an onshore wind turbine yields instability in the fore-aft rotation. In this paper, we propose a general framework, where a reference model models the desired closed-loop behavior of the system. Model predictive control combined with a state estimator finds the optimal rotor blade...... pitch such that the state trajectories of the controlled system tracks the reference trajectories. The framework is demonstrated with a reference model of the desired closed-loop system undisturbed by the incident waves. This allows the wave-induced motion of the platform to be damped significantly...... compared to a baseline floating wind turbine controller at the cost of more pitch action....

  8. Real time simulation of nonlinear generalized predictive control for wind energy conversion system with nonlinear observer.

    Science.gov (United States)

    Ouari, Kamel; Rekioua, Toufik; Ouhrouche, Mohand

    2014-01-01

    In order to make a wind power generation truly cost-effective and reliable, an advanced control techniques must be used. In this paper, we develop a new control strategy, using nonlinear generalized predictive control (NGPC) approach, for DFIG-based wind turbine. The proposed control law is based on two points: NGPC-based torque-current control loop generating the rotor reference voltage and NGPC-based speed control loop that provides the torque reference. In order to enhance the robustness of the controller, a disturbance observer is designed to estimate the aerodynamic torque which is considered as an unknown perturbation. Finally, a real-time simulation is carried out to illustrate the performance of the proposed controller. Copyright © 2013 ISA. Published by Elsevier Ltd. All rights reserved.

  9. Numerical Predictions of Wind Turbine Power and Aerodynamic Loads for the NREL Phase II and IV Combined Experiment Rotor

    Science.gov (United States)

    Duque, Earl P. N.; Johnson, Wayne; vanDam, C. P.; Chao, David D.; Cortes, Regina; Yee, Karen

    1999-01-01

    Accurate, reliable and robust numerical predictions of wind turbine rotor power remain a challenge to the wind energy industry. The literature reports various methods that compare predictions to experiments. The methods vary from Blade Element Momentum Theory (BEM), Vortex Lattice (VL), to variants of Reynolds-averaged Navier-Stokes (RaNS). The BEM and VL methods consistently show discrepancies in predicting rotor power at higher wind speeds mainly due to inadequacies with inboard stall and stall delay models. The RaNS methodologies show promise in predicting blade stall. However, inaccurate rotor vortex wake convection, boundary layer turbulence modeling and grid resolution has limited their accuracy. In addition, the inherently unsteady stalled flow conditions become computationally expensive for even the best endowed research labs. Although numerical power predictions have been compared to experiment. The availability of good wind turbine data sufficient for code validation experimental data that has been extracted from the IEA Annex XIV download site for the NREL Combined Experiment phase II and phase IV rotor. In addition, the comparisons will show data that has been further reduced into steady wind and zero yaw conditions suitable for comparisons to "steady wind" rotor power predictions. In summary, the paper will present and discuss the capabilities and limitations of the three numerical methods and make available a database of experimental data suitable to help other numerical methods practitioners validate their own work.

  10. Behavior of the aggregate wind resource in the ISO regions in the United States

    KAUST Repository

    Gunturu, Udaya

    2015-04-01

    The collective behavior of wind farms in seven Independent System Operator (ISO) areas has been studied. The generation duration curves for each ISO show that there is no aggregated power for some fraction of time. Aggregation of wind turbines mitigates intermittency to some extent, but in each ISO there is considerable fraction of time when there is less than 5% capacity. The hourly wind power time series show benefit of aggregation but the high and low wind events are lumped in time, thus indicating that intermittency is synchronized in each region. The timeseries show that there are instances when there is no wind power in most ISOs because of large-scale high pressure systems. An analytical consideration of the collective behavior of aggregated wind turbines shows that the benefit of aggregation saturates beyond a certain number of generating units asymptotically. Also, the benefit of aggregation falls rapidly with temporal correlation between the generating units.

  11. Coupling a Mesoscale Numerical Weather Prediction Model with Large-Eddy Simulation for Realistic Wind Plant Aerodynamics Simulations (Poster)

    Energy Technology Data Exchange (ETDEWEB)

    Draxl, C.; Churchfield, M.; Mirocha, J.; Lee, S.; Lundquist, J.; Michalakes, J.; Moriarty, P.; Purkayastha, A.; Sprague, M.; Vanderwende, B.

    2014-06-01

    Wind plant aerodynamics are influenced by a combination of microscale and mesoscale phenomena. Incorporating mesoscale atmospheric forcing (e.g., diurnal cycles and frontal passages) into wind plant simulations can lead to a more accurate representation of microscale flows, aerodynamics, and wind turbine/plant performance. Our goal is to couple a numerical weather prediction model that can represent mesoscale flow [specifically the Weather Research and Forecasting model] with a microscale LES model (OpenFOAM) that can predict microscale turbulence and wake losses.

  12. Variant Effect Prediction Analysis Using Resources Available at Gramene Database.

    Science.gov (United States)

    Naithani, Sushma; Geniza, Matthew; Jaiswal, Pankaj

    2017-01-01

    The goal of Gramene database ( www.gramene.org ) is to empower the plant research community in conducting comparative genomics studies across model plants and crops by employing a phylogenetic framework and orthology-based projections. Gramene database (release #49) provides resources for comparative plant genomics including well-annotated plant genomes (39 complete reference genomes and six partial genomes), genetic or structural variation data for 14 plant species, pathways for 58 plant species, and gene expression data for 14 species including Arabidopsis, rice, maize, soybean, wheat, etc. (fetched from EBI-EMBL Gene Expression Atlas database). Gramene also facilitates visualization and analysis of user-defined data in the context of species-specific Genome Browsers or pathways. This chapter describes basic navigation for Gramene users and illustrates how they can use the genome section to analyze the gene expression and nucleotide variation data generated in their labs. This includes (1) upload and display of genomic data onto a Genome Browser track, (2) analysis of variation data using online Variant Effect Predictor (VEP) tool for smaller data sets, and (3) the use of the stand-alone Perl scripts and command line protocols for variant effect prediction on larger data sets.

  13. Understanding predicted shifts in diazotroph biogeography using resource competition theory

    Directory of Open Access Journals (Sweden)

    S. Dutkiewicz

    2014-10-01

    Full Text Available We examine the sensitivity of the biogeography of nitrogen fixers to a warming climate and increased aeolian iron deposition in the context of a global earth system model. We employ concepts from the resource-ratio theory to provide a simplifying and transparent interpretation of the results. First we demonstrate that a set of clearly defined, easily diagnosed provinces are consistent with the theory. Using this framework we show that the regions most vulnerable to province shifts and changes in diazotroph biogeography are the equatorial and South Pacific, and central Atlantic. Warmer and dustier climates favor diazotrophs due to an increase in the ratio of supply rate of iron to fixed nitrogen. We suggest that the emergent provinces could be a standard diagnostic for global change models, allowing for rapid and transparent interpretation and comparison of model predictions and the underlying mechanisms. The analysis suggests that monitoring of real world province boundaries, indicated by transitions in surface nutrient concentrations, would provide a clear and easily interpreted indicator of ongoing global change.

  14. Short term prediction of the horizontal wind vector within a wake vortex warning system

    Energy Technology Data Exchange (ETDEWEB)

    Frech, M.; Holzaepfel, F.; Gerz, T. [DLR Deutsches Zentrum fuer Luft- und Raumfahrt e.V., Wessling (Germany). Inst. fuer Physik der Atmosphaere; Konopka, J. [Deutsche Flugsicherung (DFS) GmbH, Langen (Germany)

    2000-07-14

    A wake vortex warning system (WVWS) has been developed for Frankfurt airport. This airport has two parallel runways which are separated by 518 m, a distance too short to operate them independently because wake vortices may be advected to the adjacent runway. The objective of the WVWS is to enable operation with reduced separation between two aircraft approaching the parallel runways at appropriate wind conditions. The WVWS applies a statistical persistence model to predict the crosswind within a 20 minute period. One of the main problems identified in the old WVWS are discontinuities between successive forecasts. These forecast breakdowns were not acceptable to airtraffic controllers. At least part of the problem was related to the fact that the forecast was solely based on the prediction of crosswind. A new method is developed on the basis of 523 days of sonic anemometer measurements at Frankfurt airport. It is demonstrated that the prediction of the horizontal wind vector avoids these difficulties and significantly improves the system's performance. (orig.)

  15. Solar PV resource for higher penetration through a combined spatial aggregation with wind

    CSIR Research Space (South Africa)

    Bischof-Niemz, ST

    2016-06-01

    Full Text Available between wind and solar PV and how these would be reflected in the power system. The benefits of spatial distribution of renewables are well understood, but the impact of the combined spatial aggregation of wind and solar PV is central to the design...

  16. A probabilistic assessment of large scale wind power development for long-term energy resource planning

    Science.gov (United States)

    Kennedy, Scott Warren

    A steady decline in the cost of wind turbines and increased experience in their successful operation have brought this technology to the forefront of viable alternatives for large-scale power generation. Methodologies for understanding the costs and benefits of large-scale wind power development, however, are currently limited. In this thesis, a new and widely applicable technique for estimating the social benefit of large-scale wind power production is presented. The social benefit is based upon wind power's energy and capacity services and the avoidance of environmental damages. The approach uses probabilistic modeling techniques to account for the stochastic interaction between wind power availability, electricity demand, and conventional generator dispatch. A method for including the spatial smoothing effect of geographically dispersed wind farms is also introduced. The model has been used to analyze potential offshore wind power development to the south of Long Island, NY. If natural gas combined cycle (NGCC) and integrated gasifier combined cycle (IGCC) are the alternative generation sources, wind power exhibits a negative social benefit due to its high capacity cost and the relatively low emissions of these advanced fossil-fuel technologies. Environmental benefits increase significantly if charges for CO2 emissions are included. Results also reveal a diminishing social benefit as wind power penetration increases. The dependence of wind power benefits on natural gas and coal prices is also discussed. In power systems with a high penetration of wind generated electricity, the intermittent availability of wind power may influence hourly spot prices. A price responsive electricity demand model is introduced that shows a small increase in wind power value when consumers react to hourly spot prices. The effectiveness of this mechanism depends heavily on estimates of the own- and cross-price elasticities of aggregate electricity demand. This work makes a valuable

  17. Assessing Potential Wind Energy Resources in Saudi Arabia with a Skew-t Distribution

    KAUST Repository

    Tagle, Felipe

    2017-03-13

    Facing increasing domestic energy consumption from population growth and industrialization, Saudi Arabia is aiming to reduce its reliance on fossil fuels and to broaden its energy mix by expanding investment in renewable energy sources, including wind energy. A preliminary task in the development of wind energy infrastructure is the assessment of wind energy potential, a key aspect of which is the characterization of its spatio-temporal behavior. In this study we examine the impact of internal climate variability on seasonal wind power density fluctuations using 30 simulations from the Large Ensemble Project (LENS) developed at the National Center for Atmospheric Research. Furthermore, a spatio-temporal model for daily wind speed is proposed with neighbor-based cross-temporal dependence, and a multivariate skew-t distribution to capture the spatial patterns of higher order moments. The model can be used to generate synthetic time series over the entire spatial domain that adequately reproduces the internal variability of the LENS dataset.

  18. Frequency-Weighted Model Predictive Control of Trailing Edge Flaps on a Wind Turbine Blade

    DEFF Research Database (Denmark)

    Castaignet, Damien; Couchman, Ian; Poulsen, Niels Kjølstad

    2013-01-01

    This paper presents the load reduction achieved with trailing edge flaps during a full-scale test on a Vestas V27 wind turbine. The trailing edge flap controller is a frequency-weighted linear model predictive control (MPC) where the quadratic cost consists of costs on the zero-phase filtered...... flapwise blade root moment and trailing edge flap deflection. Frequency-weighted MPC is chosen for its ability to handle constraints on the trailing edge flaps deflection, and to target at loads with given frequencies only. The controller is first tested in servo-aeroelastic simulations, before being...

  19. Scaling up from field to region for wind erosion prediction using a field-scale wind erosion model and GIS

    Science.gov (United States)

    Zobeck, T.M.; Parker, N.C.; Haskell, S.; Guoding, K.

    2000-01-01

    Factors that affect wind erosion such as surface vegetative and other cover, soil properties and surface roughness usually change spatially and temporally at the field-scale to produce important field-scale variations in wind erosion. Accurate estimation of wind erosion when scaling up from fields to regions, while maintaining meaningful field-scale process details, remains a challenge. The objectives of this study were to evaluate the feasibility of using a field-scale wind erosion model with a geographic information system (GIS) to scale up to regional levels and to quantify the differences in wind erosion estimates produced by different scales of soil mapping used as a data layer in the model. A GIS was used in combination with the revised wind erosion equation (RWEQ), a field-scale wind erosion model, to estimate wind erosion for two 50 km2 areas. Landsat Thematic Mapper satellite imagery from 1993 with 30 m resolution was used as a base map. The GIS database layers included land use, soils, and other features such as roads. The major land use was agricultural fields. Data on 1993 crop management for selected fields of each crop type were collected from local government agency offices and used to 'train' the computer to classify land areas by crop and type of irrigation (agroecosystem) using commercially available software. The land area of the agricultural land uses was overestimated by 6.5% in one region (Lubbock County, TX, USA) and underestimated by about 21% in an adjacent region (Terry County, TX, USA). The total estimated wind erosion potential for Terry County was about four times that estimated for adjacent Lubbock County. The difference in potential erosion among the counties was attributed to regional differences in surface soil texture. In a comparison of different soil map scales in Terry County, the generalised soil map had over 20% more of the land area and over 15% greater erosion potential in loamy sand soils than did the detailed soil map. As

  20. Wind energy applications of synthetic aperture radar

    Energy Technology Data Exchange (ETDEWEB)

    Bruun Christiansen, M.

    2006-11-15

    Synthetic aperture radars (SAR), mounted on satellites or aircraft, have proven useful for ocean wind mapping. Wind speeds at the height 10 m may be retrieved from measurements of radar backscatter using empirical model functions. The resulting wind fields are valuable in offshore wind energy planning as a supplement to on site measurements, which are costly and sparse, and model wind fields, which are not fully validated. Two applications of SAR measurements in offshore wind energy planning are addressed here: the study of wind farm wake effects and the potential of using SAR winds in offshore wind resource assessment. Firstly, wind wakes behind two large offshore wind farms in Denmark Horns Rev and Nysted are identified. A region of reduced wind speed is found downstream of both wind farms from the SAR wind fields. The wake extent and magnitude depends on the wind speed, the atmospheric stability, and the fraction of turbines operating. Wind farm wake effects are detected up to 20 km downwind of the last turbine. This distance is longer than predicted by state-of-the art wake models. Wake losses are typically 10-20% near the wind farms. Secondly, the potential of using SAR wind maps in offshore wind resource assessment is investigated. The resource assessment is made through Weibull fitting to frequency observations of wind speed and requires at least 100 satellite observations per year for a given site of interest. Predictions of the energy density are very sensitive to the wind speed and the highest possible accuracy on SAR wind retrievals is therefore sought. A 1.1 m s{sup -1} deviation on the mean wind speed is found through comparison with mast measurements at Horns Rev. The accuracy on mean wind speeds and energy densities found from satellite measurements varies with different empirical model functions. Additional uncertainties are introduced by the infrequent satellite sampling at fixed times of the day. The accuracy on satellite based wind resource

  1. Three dimensional numerical prediction of icing related power and energy losses on a wind turbine

    Science.gov (United States)

    Sagol, Ece

    Regions of Canada experience harsh winter conditions that may persist for several months. Consequently, wind turbines located in these regions are exposed to ice accretion and its adverse effects, from loss of power to ceasing to function altogether. Since the weather-related annual energy production loss of a turbine may be as high as 16% of the nominal production for Canada, estimating these losses before the construction of a wind farm is essential for investors. A literature survey shows that most icing prediction methods and codes are developed for aircraft, and, as this information is mostly considered corporate intellectual property, it is not accessible to researchers in other domains. Moreover, aircraft icing is quite different from wind turbine icing. Wind turbines are exposed to icing conditions for much longer periods than aircraft, perhaps for several days in a harsh climate, whereas the maximum length of exposure of an aircraft is about 3-4 hours. In addition, wind turbine blades operate at subsonic speeds, at lower Reynolds numbers than aircraft, and their physical characteristics are different. A few icing codes have been developed for wind turbine icing nevertheless. However, they are either in 2D, which does not consider the 3D characteristics of the flow field, or they focus on simulating each rotation in a time-dependent manner, which is not practical for computing long hours of ice accretion. Our objective in this thesis is to develop a 3D numerical methodology to predict rime ice shape and the power loss of a wind turbine as a function of wind farm icing conditions. In addition, we compute the Annual Energy Production of a sample turbine under both clean and icing conditions. The sample turbine we have selected is the NREL Phase VI experimental wind turbine installed on a wind farm in Sweden, the icing events at which have been recorded and published. The proposed method is based on computing and validating the clean performance of the turbine

  2. Drivers and seasonal predictability of extreme wind speeds in the ECMWF System 4 and a statistical model

    Science.gov (United States)

    Walz, M. A.; Donat, M.; Leckebusch, G. C.

    2017-12-01

    As extreme wind speeds are responsible for large socio-economic losses in Europe, a skillful prediction would be of great benefit for disaster prevention as well as for the actuarial community. Here we evaluate patterns of large-scale atmospheric variability and the seasonal predictability of extreme wind speeds (e.g. >95th percentile) in the European domain in the dynamical seasonal forecast system ECMWF System 4, and compare to the predictability based on a statistical prediction model. The dominant patterns of atmospheric variability show distinct differences between reanalysis and ECMWF System 4, with most patterns in System 4 extended downstream in comparison to ERA-Interim. The dissimilar manifestations of the patterns within the two models lead to substantially different drivers associated with the occurrence of extreme winds in the respective model. While the ECMWF System 4 is shown to provide some predictive power over Scandinavia and the eastern Atlantic, only very few grid cells in the European domain have significant correlations for extreme wind speeds in System 4 compared to ERA-Interim. In contrast, a statistical model predicts extreme wind speeds during boreal winter in better agreement with the observations. Our results suggest that System 4 does not seem to capture the potential predictability of extreme winds that exists in the real world, and therefore fails to provide reliable seasonal predictions for lead months 2-4. This is likely related to the unrealistic representation of large-scale patterns of atmospheric variability. Hence our study points to potential improvements of dynamical prediction skill by improving the simulation of large-scale atmospheric dynamics.

  3. Renewable Energy Potential of Greenland with emphasis on wind resource assessment

    DEFF Research Database (Denmark)

    Jakobsen, Kasper Rønnow

    of Profitable (required returns of investment), more can economically be saved by replacing outdated equipment. The renewable energy potential for both solar and wind was relatively high, with solar radiation above 1000 kWh=m2=year and mean wind speeds of 6.1 m/s at 10 MAG. For a 50 kWp PV installation the 25...... a dedicated wind monitoring system usable in the Arctic environment and to test it at different types of sites. The instrument test showed that even the highest quality of equipment failed in harsh climate. An extended test was planned, but due to delays, the test result is not ready yet. Based...

  4. Beyond Host Language Proficiency: Coping Resources Predicting International Students' Satisfaction

    Science.gov (United States)

    Mak, Anita S.; Bodycott, Peter; Ramburuth, Prem

    2015-01-01

    As international students navigate in a foreign educational environment, having higher levels of coping or stress-resistance resources--both internal and external--could be related to increased satisfaction with personal and university life. The internal coping resources examined in this study were host language proficiency, self-esteem,…

  5. A Predictive Power Control Strategy for DFIGs Based on a Wind Energy Converter System

    Directory of Open Access Journals (Sweden)

    Xiaoliang Yang

    2017-07-01

    Full Text Available A feasible control strategy is proposed to control a doubly fed induction generator based on the wind energy converter system (DFIG-WECS. The main aim is to enhance the steady state and dynamic performance under the condition of the parameter perturbations and external disturbances and to satisfy the stator power response of the system. Within the proposed control method, the control scheme for the rotor side converter (RSC is developed on the model predictive control. Firstly, the self-adaptive reference trajectory is established from the deduced discrete state-space equation of the generator. Then, the rotor voltage is calculated by minimizing the global performance index under the current prediction steps at the sampling instant. Through the control scheme for the grid side converter (GSC and wind turbine, we have re-applied the conventional control. The effectiveness of the proposed control strategy is verified via time domain simulation of a 150 kW-575 V DFIG-WECS using Matlab/Simulink. The simulation result shows that the control of the DFIG with the proposed control method can enhance the steady and dynamic response capability better than the conventional ones when the system faces errors due to the parameter perturbations, external disturbances and the rotor speed.

  6. NASA Prediction of Worldwide Energy Resource High Resolution Meteorology Data For Sustainable Building Design

    Science.gov (United States)

    Chandler, William S.; Hoell, James M.; Westberg, David; Zhang, Taiping; Stackhouse, Paul W., Jr.

    2013-01-01

    A primary objective of NASA's Prediction of Worldwide Energy Resource (POWER) project is to adapt and infuse NASA's solar and meteorological data into the energy, agricultural, and architectural industries. Improvements are continuously incorporated when higher resolution and longer-term data inputs become available. Climatological data previously provided via POWER web applications were three-hourly and 1x1 degree latitude/longitude. The NASA Modern Era Retrospective-analysis for Research and Applications (MERRA) data set provides higher resolution data products (hourly and 1/2x1/2 degree) covering the entire globe. Currently POWER solar and meteorological data are available for more than 30 years on hourly (meteorological only), daily, monthly and annual time scales. These data may be useful to several renewable energy sectors: solar and wind power generation, agricultural crop modeling, and sustainable buildings. A recent focus has been working with ASHRAE to assess complementing weather station data with MERRA data. ASHRAE building design parameters being investigated include heating/cooling degree days and climate zones.

  7. Exercise and sleep predict personal resources in employees' daily lives.

    Science.gov (United States)

    Nägel, Inga J; Sonnentag, Sabine

    2013-11-01

    The present study investigates the interaction of exercise and sleep on state-like personal resources in employees' daily lives. Further, the study examines the association between state-like personal resources and emotional exhaustion. We conducted a diary study over five consecutive working days (total of 443 days) with 144 employees who answered daily online surveys after work and before bedtime. Multilevel modeling showed that exercise after work was positively related to the next day's personal resources when sleep duration during the night time was longer compared to other nights. Furthermore, personal resources positively related to lower emotional exhaustion after work on the next day. This study demonstrates that exercise and sleep may help to renew personal resources. Results stress the importance of balancing exercise and sleep in daily life. © 2013 The International Association of Applied Psychology.

  8. Intercomparison of state-of-the-art models for wind energy resources with mesoscale models:

    Science.gov (United States)

    Olsen, Bjarke Tobias; Hahmann, Andrea N.; Sempreviva, Anna Maria; Badger, Jake; Joergensen, Hans E.

    2016-04-01

    1. Introduction Mesoscale models are increasingly being used to estimate wind conditions to identify perspective areas and sites where to develop wind farm projects. Mesoscale models are functional for giving information over extensive areas with various terrain complexities where measurements are scarce and measurement campaigns costly. Several mesoscale models and families of models are being used, and each often contains thousands of setup options. Since long-term integrations are expensive and tedious to carry out, only limited comparisons exist. To remedy this problem and for evaluating the capabilities of mesoscale models to estimate site wind conditions, a tailored benchmarking study has been co-organized by the European Wind Energy Association (EWEA) and the European Energy Research Alliance Joint Programme Wind Energy (EERA JP WIND). EWEA hosted results and ensured that participants were anonymous. The blind evaluation was performed at the Wind Energy Department of the Technical University of Denmark (DTU) with the following objectives: (1) To highlight common issues on mesoscale modelling of wind conditions on sites with different characteristics, and (2) To identify gaps and strengths of models and understand the root conditions for further evaluating uncertainties. 2. Approach Three experimental sites were selected: FINO 3 (offshore, GE), Høvsore (coastal, DK), and Cabauw (land-based, NL), and three other sites without observations based on . The three mast sites were chosen because the availability of concurrent suitable time series of vertical profiles of winds speed and other surface parameters. The participants were asked to provide hourly time series of wind speed, wind direction, temperature, etc., at various vertical heights for a complete year. The methodology used to derive the time series was left to the choice of the participants, but they were asked for a brief description of their model and many other parameters (e.g., horizontal and

  9. Wind as a resource for summer nautical recreation. Guincho beach study case

    Directory of Open Access Journals (Sweden)

    Wenzel Vermeersch

    2013-06-01

    Full Text Available Guincho is known as the windiest beach of Portugal, ideal for nautical activities, such as windsurfing and kitesurfing. the main goals of this study are to explore the wind characteristics in Guincho and to compare the synoptic forecasts accessible to the public with actually occurring weather conditions. We used meteorological data, synoptical information, forecasts and field observations during the summers of 2009 and 2010. a sample of 124 days with good conditions for windsurfing were selected and classified into different groups. Within each group, the wind measured (and indirectly observed in Guincho was compared to the results of the Global Forecast System (Gfs. this analysis led to a useful classification allowing interpretation of Gfs surface wind forecasts available to surfers at Guincho. We conclude that global weather models do not accurately forecast the wind, particularly due to model resolution and parameterisations, which do not detail local phenomena

  10. Towards more accurate wind and solar power prediction by improving NWP model physics

    Science.gov (United States)

    Steiner, Andrea; Köhler, Carmen; von Schumann, Jonas; Ritter, Bodo

    2014-05-01

    The growing importance and successive expansion of renewable energies raise new challenges for decision makers, economists, transmission system operators, scientists and many more. In this interdisciplinary field, the role of Numerical Weather Prediction (NWP) is to reduce the errors and provide an a priori estimate of remaining uncertainties associated with the large share of weather-dependent power sources. For this purpose it is essential to optimize NWP model forecasts with respect to those prognostic variables which are relevant for wind and solar power plants. An improved weather forecast serves as the basis for a sophisticated power forecasts. Consequently, a well-timed energy trading on the stock market, and electrical grid stability can be maintained. The German Weather Service (DWD) currently is involved with two projects concerning research in the field of renewable energy, namely ORKA*) and EWeLiNE**). Whereas the latter is in collaboration with the Fraunhofer Institute (IWES), the project ORKA is led by energy & meteo systems (emsys). Both cooperate with German transmission system operators. The goal of the projects is to improve wind and photovoltaic (PV) power forecasts by combining optimized NWP and enhanced power forecast models. In this context, the German Weather Service aims to improve its model system, including the ensemble forecasting system, by working on data assimilation, model physics and statistical post processing. This presentation is focused on the identification of critical weather situations and the associated errors in the German regional NWP model COSMO-DE. First steps leading to improved physical parameterization schemes within the NWP-model are presented. Wind mast measurements reaching up to 200 m height above ground are used for the estimation of the (NWP) wind forecast error at heights relevant for wind energy plants. One particular problem is the daily cycle in wind speed. The transition from stable stratification during

  11. Wind power forecasting for a real onshore wind farm on complex terrain using WRF high resolution simulations.

    Science.gov (United States)

    Ángel Prósper Fernández, Miguel; Casal, Carlos Otero; Canoura Fernández, Felipe; Miguez-Macho, Gonzalo

    2017-04-01

    Regional meteorological models are becoming a generalized tool for forecasting wind resource, due to their capacity to simulate local flow dynamics impacting wind farm production. This study focuses on the production forecast and validation of a real onshore wind farm using high horizontal and vertical resolution WRF (Weather Research and Forecasting) model simulations. The wind farm is located in Galicia, in the northwest of Spain, in a complex terrain region with high wind resource. Utilizing the Fitch scheme, specific for wind farms, a period of one year is simulated with a daily operational forecasting set-up. Power and wind predictions are obtained and compared with real data provided by the management company. Results show that WRF is able to yield good wind power operational predictions for this kind of wind farms, due to a good representation of the planetary boundary layer behaviour of the region and the good performance of the Fitch scheme under these conditions.

  12. Final Report for ALCC Allocation: Predictive Simulation of Complex Flow in Wind Farms

    Energy Technology Data Exchange (ETDEWEB)

    Barone, Matthew F. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Ananthan, Shreyas [National Renewable Energy Lab. (NREL), Golden, CO (United States); Churchfield, Matt [National Renewable Energy Lab. (NREL), Golden, CO (United States); Domino, Stefan P. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Henry de Frahan, Marc [National Renewable Energy Lab. (NREL), Golden, CO (United States); Knaus, Robert C. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Melvin, Jeremy [Univ. of Texas, Austin, TX (United States); Moser, Robert [Univ. of Texas, Austin, TX (United States); Sprague, Michael [National Renewable Energy Lab. (NREL), Golden, CO (United States); Thomas, Stephen [National Renewable Energy Lab. (NREL), Golden, CO (United States)

    2017-08-01

    This report documents work performed using ALCC computing resources granted under a proposal submitted in February 2016, with the resource allocation period spanning the period July 2016 through June 2017. The award allocation was 10.7 million processor-hours at the National Energy Research Scientific Computing Center. The simulations performed were in support of two projects: the Atmosphere to Electrons (A2e) project, supported by the DOE EERE office; and the Exascale Computing Project (ECP), supported by the DOE Office of Science. The project team for both efforts consists of staff scientists and postdocs from Sandia National Laboratories and the National Renewable Energy Laboratory. At the heart of these projects is the open-source computational-fluid-dynamics (CFD) code, Nalu. Nalu solves the low-Mach-number Navier-Stokes equations using an unstructured- grid discretization. Nalu leverages the open-source Trilinos solver library and the Sierra Toolkit (STK) for parallelization and I/O. This report documents baseline computational performance of the Nalu code on problems of direct relevance to the wind plant physics application - namely, Large Eddy Simulation (LES) of an atmospheric boundary layer (ABL) flow and wall-modeled LES of a flow past a static wind turbine rotor blade. Parallel performance of Nalu and its constituent solver routines residing in the Trilinos library has been assessed previously under various campaigns. However, both Nalu and Trilinos have been, and remain, in active development and resources have not been available previously to rigorously track code performance over time. With the initiation of the ECP, it is important to establish and document baseline code performance on the problems of interest. This will allow the project team to identify and target any deficiencies in performance, as well as highlight any performance bottlenecks as we exercise the code on a greater variety of platforms and at larger scales. The current study is

  13. The influence of the new ECMWF Ensemble Prediction System resolution on wind power forecast accuracy and uncertainty estimation

    DEFF Research Database (Denmark)

    Alessandrini, S.; Pinson, Pierre; Sperati, S.

    2011-01-01

    The importance of wind power forecasting (WPF) is nowadays commonly recognized because it represents a useful tool to reduce problems of grid integration and to facilitate energy trading. If on one side the prediction accuracy is fundamental to these scopes, on the other it has become also clear...... Prediction System (EPS) can be used as indicator of a three-hourly, three days ahead, wind power forecast’s accuracy. In particular it has been noticed that to extract usable information from data the Ensemble members needed to be statistically calibrated, since the rank histograms for the three-day period...... that a reliable estimation of their uncertainty could be a useful information too. In fact the prediction accuracy is unfortunately not constant and can depend on the location of a particular wind farm, on the forecast time and on the atmospheric situation. Previous studies indicated that the ECMWF Ensemble...

  14. DEWEPS - Development and Evaluation of new Wind forecasting tools with an Ensemble Prediction System

    Energy Technology Data Exchange (ETDEWEB)

    Moehrlen, C.; Joergensen, Jess

    2012-02-15

    There is an ongoing trend of increased privatization in the handling of renewable energy. This trend is required to ensure an efficient energy system, where improvements that make economic sense are prioritised. The reason why centralized forecasting can be a challenge in that matter is that the TSOs tend to optimize on physical error rather than cost. Consequently, the market is likely to speculate against the TSO, which in turn increases the cost of balancing. A privatized pool of wind and/or solar power is more difficult to speculate against, because the optimization criteria is unpredictable due to subjective risk considerations that may be taken into account at any time. Although there is and additional level of costs for the trading of the private volume, it can be argued that competition will accelerate efficiency from an economic perspective. The amount of power put into the market will become less predictable, when the wind power spot market bid takes place on the basis of a risk consideration in addition to the forecast information itself. The scope of this project is to contribute to more efficient wind power integration targeted both to centralised and decentralised cost efficient IT solutions, which will complement each other in market based energy systems. The DEWEPS project resulted in an extension of the number of Ensemble forecasts, an incremental trade strategy for balancing unpredictable power production, and an IT platform for efficient handling of power generation units. Together, these three elements contribute to less need for reserves, more capacity in the market, and thus more competition. (LN)

  15. Avian Monitoring and Risk Assessment at the Tehachapi Pass Wind Resource Area; Period of Performance: October 2, 1996--May 27, 1998

    Energy Technology Data Exchange (ETDEWEB)

    Anderson, R.; Neumann, N.; Tom, J.; Erickson, W. P.; Strickland, M. D.; Bourassa, M.; Bay, K. J.; Sernka, K. J.

    2004-09-01

    Observations of dead raptors at the Altamont Pass Wind Resource Area triggered concerns on the parts of regulatory agencies, environmental/conservation groups, wildlife resource agencies, and wind and electric utility industries about possible impacts to birds from wind energy development. Bird fatality rates observed at most wind projects are not currently considered significant to individual bird species populations. Although many bird species have observed fatalities, raptors have received the most attention. The primary objective of this study was to estimate and compare bird utilization, fatality rates, and collision risk indices among factors such as bird taxonomic groups, turbine types, and turbine locations within the operating wind plant in the Tehachapi Pass WRA, in south-central California between October 1996 and May 1998.

  16. Solar-wind predictions for the Parker Solar Probe orbit. Near-Sun extrapolations derived from an empirical solar-wind model based on Helios and OMNI observations

    Science.gov (United States)

    Venzmer, M. S.; Bothmer, V.

    2018-03-01

    Context. The Parker Solar Probe (PSP; formerly Solar Probe Plus) mission will be humanitys first in situ exploration of the solar corona with closest perihelia at 9.86 solar radii (R⊙) distance to the Sun. It will help answer hitherto unresolved questions on the heating of the solar corona and the source and acceleration of the solar wind and solar energetic particles. The scope of this study is to model the solar-wind environment for PSPs unprecedented distances in its prime mission phase during the years 2018 to 2025. The study is performed within the Coronagraphic German And US SolarProbePlus Survey (CGAUSS) which is the German contribution to the PSP mission as part of the Wide-field Imager for Solar PRobe. Aim. We present an empirical solar-wind model for the inner heliosphere which is derived from OMNI and Helios data. The German-US space probes Helios 1 and Helios 2 flew in the 1970s and observed solar wind in the ecliptic within heliocentric distances of 0.29 au to 0.98 au. The OMNI database consists of multi-spacecraft intercalibrated in situ data obtained near 1 au over more than five solar cycles. The international sunspot number (SSN) and its predictions are used to derive dependencies of the major solar-wind parameters on solar activity and to forecast their properties for the PSP mission. Methods: The frequency distributions for the solar-wind key parameters, magnetic field strength, proton velocity, density, and temperature, are represented by lognormal functions. In addition, we consider the velocity distributions bi-componental shape, consisting of a slower and a faster part. Functional relations to solar activity are compiled with use of the OMNI data by correlating and fitting the frequency distributions with the SSN. Further, based on the combined data set from both Helios probes, the parameters frequency distributions are fitted with respect to solar distance to obtain power law dependencies. Thus an empirical solar-wind model for the inner

  17. Using Multiple Seasonal Holt-Winters Exponential Smoothing to Predict Cloud Resource Provisioning

    OpenAIRE

    Ashraf A. Shahin

    2016-01-01

    Elasticity is one of the key features of cloud computing that attracts many SaaS providers to minimize their services' cost. Cost is minimized by automatically provision and release computational resources depend on actual computational needs. However, delay of starting up new virtual resources can cause Service Level Agreement violation. Consequently, predicting cloud resources provisioning gains a lot of attention to scale computational resources in advance. However, most of current approac...

  18. Renewable Generation (Wind/Solar and Load Modeling through Modified Fuzzy Prediction Interval

    Directory of Open Access Journals (Sweden)

    Syed Furqan Rafique

    2018-01-01

    Full Text Available The accuracy of energy management system for renewable microgrid, either grid-connected or isolated, is heavily dependent on the forecasting precision such as wind, solar, and load. In this paper, an improved fuzzy prediction horizon forecasting method is developed to address the issue of intermittence and uncertainty problem related to renewable generation and load forecast. In the first phase, a Takagi-Sugeno type fuzzy system is trained with many evolutionary optimization algorithms and established coverage grade indicator to check the accuracy of interval forecast. Secondly, a wind, solar, and load forecaster is developed for renewable microgrid test bed which is located in Beijing, China. One day and one step ahead results for the proposed forecaster are expressed with lowest RMSE and training time. In order to check the efficiency of the proposed method, a comparison is carried out with the existing models. The fuzzy interval-based model for the microgrid test bed will help to formulate the energy management problem with more accuracy and robustness.

  19. Sustainable use of marine resources through offshore wind and mussel farm co-location

    DEFF Research Database (Denmark)

    Di Tullio, Giacomo R.; Mariani, Patrizio; Benassai, Guido

    2018-01-01

    wind farms and open-water mussel cultivation. An index of co-location sustainability (SI) was developed based on the application of MCE technique constructed with physical and biological parameters on the basis of remote-sensing data. The relevant physical factors considered were wind velocity, depth...... range, concerning the site location for energy production, and sea surface temperature anomaly. The biological variables used were Chlorofill-a (as a measurement of the productivity) and Particle Organic Carbon(POC) concentration, in order to assess their influence on the probable benefits and complete...

  20. State-Space Modeling and Performance Analysis of Variable-Speed Wind Turbine Based on a Model Predictive Control Approach

    Directory of Open Access Journals (Sweden)

    H. Bassi

    2017-04-01

    Full Text Available Advancements in wind energy technologies have led wind turbines from fixed speed to variable speed operation. This paper introduces an innovative version of a variable-speed wind turbine based on a model predictive control (MPC approach. The proposed approach provides maximum power point tracking (MPPT, whose main objective is to capture the maximum wind energy in spite of the variable nature of the wind’s speed. The proposed MPC approach also reduces the constraints of the two main functional parts of the wind turbine: the full load and partial load segments. The pitch angle for full load and the rotating force for the partial load have been fixed concurrently in order to balance power generation as well as to reduce the operations of the pitch angle. A mathematical analysis of the proposed system using state-space approach is introduced. The simulation results using MATLAB/SIMULINK show that the performance of the wind turbine with the MPC approach is improved compared to the traditional PID controller in both low and high wind speeds.

  1. Model predictive control of trailing edge flaps on a wind turbine blade

    DEFF Research Database (Denmark)

    Castaignet, Damien Bruno

    -weighted model predictive control, tuned in order to target only the flapwise blade root loads at the frequencies contributing the most to blade root fatigue damage (the 1P, 2P and 3P frequencies), and to avoid unnecessary wear and tear of the actuators at high frequencies. A disturbance model consisting...... in periodic disturbances at the rotor speed harmonic frequencies and a quasi-steady input disturbance is aggregated to an analytical model of a spinning blade with trailing edge flaps. Simulations on a multi-megawatt wind turbine show the potential of the trailing edge flaps to reduce the flapwise blade root......, in Roskilde, Denmark. One blade of the turbine was equipped with three independent trailing edge flaps. In spite of the failure of several sensors and actuators, the test of the trailing edge flaps controller described in this thesis showed a consistent flapwise blade root fatigue load reduction. An average...

  2. Method to predict fatigue lifetimes of GRP wind turbine blades and comparison with experiments

    Energy Technology Data Exchange (ETDEWEB)

    Echtermeyer, A.T. [Det Norske Veritas Research AS, Hoevik (Norway); Kensche, C. [Deutsche Forschungsanstalt fuer Luft- und Raumfahrt e.V. (DLR), Stuttgart (Germany, F.R); Bach, P. [Netherlands Energy Research Foundation (ECN), Petten (Netherlands); Poppen, M. [Aeronautical Research Inst. of Sweden, Bromma (Sweden); Lilholt, H.; Andersen, S.I.; Broendsted, P. [Risoe National Lab., Roskilde (Denmark)

    1996-12-01

    This paper describes a method to predict fatigue lifetimes of fiber reinforced plastics in wind turbine blades. It is based on extensive testing within the EU-Joule program. The method takes the measured fatigue properties of a material into account so that credit can be given to materials with improved fatigue properties. The large number of test results should also give confidence in the fatigue calculation method for fiber reinforced plastics. The method uses the Palmgren-Miner sum to predict lifetimes and is verified by tests using well defined load sequences. Even though this approach is generally well known in fatigue analysis, many details in the interpretation and extrapolation of the measurements need to be clearly defined, since they can influence the results considerably. The following subjects will be described: Method to measure SN curves and to obtain tolerance bounds, development of a constant lifetime diagram, evaluation of the load sequence, use of Palmgren-Miner sum, requirements for load sequence testing. The fatigue lifetime calculation method has been compared against measured data for simple loading sequences and the more complex WISPERX loading sequence for blade roots. The comparison is based on predicted mean lifetimes, using the same materials to obtain the basic SN curves and to measure laminates under complicated loading sequences. 24 refs, 7 figs, 5 tabs

  3. The use of different ensemble forecasting systems for wind power prediction on a real case in the South of Italy

    DEFF Research Database (Denmark)

    Alessandrini, Stefano; Sperati, Simone; Pinson, Pierre

    2012-01-01

    Short-term forecasting applied to wind energy is becoming increasingly important due to the constant growth of this renewable source, whose uncertainty requires a constant effort to meet the needs of the national electrical systems and their operators. Regarding to this, the probabilistic approach...... the data to wind energy: the spread calculated on wind power can then be used as an accuracy predictor due to its level of correlation with the deterministic WPF error. In this presentation we investigate the performances for both wind power and accuracy prediction of the new EPS used at the ECMWF, whose...... horizontal resolution was increased on January 2010 from 60 km to 32 km, on a complex terrain area already used in previous studies and located in Southern Italy. The work consists in the use of the ECMWF deterministic model in a WPF approach followed by a recursive feed-forward Neural Networks (NN...

  4. A Transmission-Cost-Based Model to Estimate the Amount of Market-Integrable Wind Resources

    DEFF Research Database (Denmark)

    Morales González, Juan Miguel; Pinson, Pierre; Madsen, Henrik

    2012-01-01

    -cost perspective. This model accounts for the uncertain character of wind by using a modeling framework based on stochastic optimization, simulates market barriers by means of a bi-level structure, and considers the financial risk of investments in transmission through the conditional value-at-risk. The major...

  5. Experimental Validation of Energy Resources Integration in Microgrids via Distributed Predictive Control

    DEFF Research Database (Denmark)

    Mantovani, Giancarlo; Costanzo, Giuseppe Tommaso; Marinelli, Mattia

    2014-01-01

    This paper presents an innovative control scheme for the management of energy consumption in commercial build- ings with local energy production, such as photovoltaic panels or wind turbine and an energy storage unit. The presented scheme is based on distributed model predictive controllers, which...... manage the storage system and the building space heating and cooling. The proposed approach is implemented and tested in SYSLAB, the experimental facility for distributed energy systems at the Techni- cal University of Denmark, Risø Campus. The experimental setup consists of wind and solar renewable...

  6. A Population Study of Golden Eagles in the Altamont Pass Wind Resource Area: Population Trend Analysis, 1994-1997

    Energy Technology Data Exchange (ETDEWEB)

    Hunt, W. G.; Jackman, R. E.; Hunt, T. L.; Driscoll, D. E.; Culp, L.

    1999-07-20

    The wind industry has annually reported 28-43 turbine blade strike casualties of golden eagles in the Altamont Pass Wind Resource Area, and many more carcasses have doubtless gone unnoticed. Because this species is especially sensitive to adult survival rate changes, we focused upon estimating the demographic trend of the population. In aerial surveys, we monitored survival within a sample of 179 radio-tagged eagles over a four-year period. We also obtained data on territory occupancy and reproduction of about 65 eagle pairs residing in the area. Of 61 recorded deaths of radio-tagged eagles during the four-year investigation, 23 (38%) were caused by wind turbine blade strikes. Additional fatalities were unrecorded because blade strikes sometimes destroy radio transmitters. Annual survival was estimated at 0.7867 (SE=0.0263) for non-territorial eagles and 0.8964 (SE=0.0371) for territorial ones. Annual reproduction was 0.64 (SE=0.08) young per territorial pair (0.25 per female). These parameters were used to estimate population growth rates under different modeling frameworks. At present, there are indications that a reserve of non-breeding adults still exists, i.e., there is an annual territorial reoccupancy rate of 100% and a low incidence (3%) of subadults as members of breeding pairs.

  7. Bird Risk Behaviors and Fatalities at the Altamont Pass Wind Resource Area: Period of Performance, March 1998--December 2000

    Energy Technology Data Exchange (ETDEWEB)

    Thelander, C. G.; Smallwood, K. S.; Rugge, L.

    2003-12-01

    It has been documented that wind turbine operations at the Altamont Pass Wind Resource Area kill large numbers of birds of multiple species, including raptors. We initiated a study that integrates research on bird behaviors, raptor prey availability, turbine design, inter-turbine distribution, landscape attributes, and range management practices to explain the variation in avian mortality at two levels of analysis: the turbine and the string of turbines. We found that inter-specific differences in intensities of use of airspace within close proximity did not explain the variation in mortality among species. Unique suites of attributes relate to mortality of each species, so species-specific analyses are required to understand the factors that underlie turbine-caused fatalities. We found that golden eagles are killed by turbines located in the canyons and that rock piles produced during preparation of the wind tower laydown areas related positively to eagle mortality, perhaps due to the use of these rock piles as cover by desert cottontails. Other similar relationships between fatalities and environmental factors are identified and discussed. The tasks remaining to complete the project are summarized.

  8. Electric car with solar and wind energy may change the environment and economy: A tool for utilizing the renewable energy resource

    Science.gov (United States)

    Liu, Quanhua

    2014-01-01

    Energy and environmental issues are among the most important problems of public concern. Wind and solar energy may be one of the alternative solutions to overcome energy shortage and to reduce greenhouse gaseous emission. Using electric cars in cities can significantly improve the air quality there. Through our analyses and modeling on the basis of the National Centers for Environment Prediction data we confirm that the amount of usable solar and wind energy far exceeds the world's total energy demand, considering the feasibility of the technology being used. Storing the surplus solar and wind energy and then releasing this surplus on demand is an important approach to maintaining uninterrupted solar- and wind-generated electricity. This approach requires us to be aware of the available solar and wind energy in advance in order to manage their storage. Solar and wind energy depends on weather conditions and we know weather forecasting. This implies that solar and wind energy is predictable. In this article, we demonstrate how solar and wind energy can be forecasted. We provide a web tool that can be used by all to arrive at solar and wind energy amount at any location in the world. The tool is available at http://www.renewableenergyst.org. The website also provides additional information on renewable energy, which is useful to a wide range of audiences, including students, educators, and the general public.

  9. Decadal predictability of wind energy potentials over Germany in the Earth System Model of the Max-Planck-Institute

    Science.gov (United States)

    Moemken, Julia; Reyers, Mark; Pinto, Joaquim G.

    2015-04-01

    Regional climate predictions on timescales from one year to one decade are gaining importance since this time frame falls within the planning horizon of politics, economy, and society. In this context, decadal predictions are of particular interest for the development of renewable energies such as wind energy. The present study examines the decadal predictability of wind energy potentials in the framework of the ongoing MiKlip consortium (www.fona-miklip.de). This consortium aims to develop a model system based on the Max-Planck-Institute Earth System Model (MPI-ESM), that can provide skillful decadal predictions on regional and global scales. Three generations of the decadal prediction system of the MPI-ESM are analysed here with respect to wind energy potentials on the regional and local scale. Ensembles of uninitialized historical and yearly initialized hindcast experiments are used to assess the forecast skill for wind energy output (Eout) over Central Europe, with special focus given to Germany. With this aim, a statistical-dynamical downscaling (SDD) approach is used for the regionalisation of the global datasets. All three MPI-ESM ensemble generations, which are based on different hindcast initialisations, show some forecast skill for wind energy potentials on yearly and multi-yearly time scales over Germany, Poland, Czech Republic and Benelux. In general, the predictive skill for the two latest MPI-ESM generations (baseline1 and prototype) is higher than for the first generation (baseline0). The predictability varies with different leading-time periods and declines with increasing time since initialisation. Regarding seasonal means, skill scores are lowest during winter, and persist longest for autumn in all three generations. In the summer months, differences between the three generations are more pronounced than for the other seasons. In general, forecast skill for wind energy potential is found for all three MPI-ESM ensemble generations. This skill is

  10. A Collision Risk Model to Predict Avian Fatalities at Wind Facilities: An Example Using Golden Eagles, Aquila chrysaetos.

    Directory of Open Access Journals (Sweden)

    Leslie New

    Full Text Available Wind power is a major candidate in the search for clean, renewable energy. Beyond the technical and economic challenges of wind energy development are environmental issues that may restrict its growth. Avian fatalities due to collisions with rotating turbine blades are a leading concern and there is considerable uncertainty surrounding avian collision risk at wind facilities. This uncertainty is not reflected in many models currently used to predict the avian fatalities that would result from proposed wind developments. We introduce a method to predict fatalities at wind facilities, based on pre-construction monitoring. Our method can directly incorporate uncertainty into the estimates of avian fatalities and can be updated if information on the true number of fatalities becomes available from post-construction carcass monitoring. Our model considers only three parameters: hazardous footprint, bird exposure to turbines and collision probability. By using a Bayesian analytical framework we account for uncertainties in these values, which are then reflected in our predictions and can be reduced through subsequent data collection. The simplicity of our approach makes it accessible to ecologists concerned with the impact of wind development, as well as to managers, policy makers and industry interested in its implementation in real-world decision contexts. We demonstrate the utility of our method by predicting golden eagle (Aquila chrysaetos fatalities at a wind installation in the United States. Using pre-construction data, we predicted 7.48 eagle fatalities year-1 (95% CI: (1.1, 19.81. The U.S. Fish and Wildlife Service uses the 80th quantile (11.0 eagle fatalities year-1 in their permitting process to ensure there is only a 20% chance a wind facility exceeds the authorized fatalities. Once data were available from two-years of post-construction monitoring, we updated the fatality estimate to 4.8 eagle fatalities year-1 (95% CI: (1.76, 9.4; 80th

  11. A Collision Risk Model to Predict Avian Fatalities at Wind Facilities: An Example Using Golden Eagles, Aquila chrysaetos.

    Science.gov (United States)

    New, Leslie; Bjerre, Emily; Millsap, Brian; Otto, Mark C; Runge, Michael C

    2015-01-01

    Wind power is a major candidate in the search for clean, renewable energy. Beyond the technical and economic challenges of wind energy development are environmental issues that may restrict its growth. Avian fatalities due to collisions with rotating turbine blades are a leading concern and there is considerable uncertainty surrounding avian collision risk at wind facilities. This uncertainty is not reflected in many models currently used to predict the avian fatalities that would result from proposed wind developments. We introduce a method to predict fatalities at wind facilities, based on pre-construction monitoring. Our method can directly incorporate uncertainty into the estimates of avian fatalities and can be updated if information on the true number of fatalities becomes available from post-construction carcass monitoring. Our model considers only three parameters: hazardous footprint, bird exposure to turbines and collision probability. By using a Bayesian analytical framework we account for uncertainties in these values, which are then reflected in our predictions and can be reduced through subsequent data collection. The simplicity of our approach makes it accessible to ecologists concerned with the impact of wind development, as well as to managers, policy makers and industry interested in its implementation in real-world decision contexts. We demonstrate the utility of our method by predicting golden eagle (Aquila chrysaetos) fatalities at a wind installation in the United States. Using pre-construction data, we predicted 7.48 eagle fatalities year-1 (95% CI: (1.1, 19.81)). The U.S. Fish and Wildlife Service uses the 80th quantile (11.0 eagle fatalities year-1) in their permitting process to ensure there is only a 20% chance a wind facility exceeds the authorized fatalities. Once data were available from two-years of post-construction monitoring, we updated the fatality estimate to 4.8 eagle fatalities year-1 (95% CI: (1.76, 9.4); 80th quantile, 6

  12. A population study of golden eagles in the Altamont Pass Wind Resource area. Second-year progress report

    Energy Technology Data Exchange (ETDEWEB)

    NONE

    1997-07-01

    Since January 1994, the Predatory Bird Research Group, University of California, Santa Cruz, has been conducting a field investigation of the ecology of golden eagles (Aquila chrysaetos) in the vicinity of the Altamont Pass Wind Resource Area (WRA). The 190 km{sup 2} facility lies just east of San Francisco Bay in California and contains about 6,500 wind turbines. Grassland and oak savanna habitats surrounding the WRA support a substantial resident population of golden eagles. Each year, the U.S. Fish and Wildlife Service receivers reports from the wind industry of about 30 golden eagle casualties occurring at the WRA, and it is probable that many more carcasses go unnoticed. Over 90 percent of the casualties are attributed to collisions with wind turbines. The main purpose of this study is to estimate the effect of turbine-related mortality on the golden eagle population of the area. Assessing the impact of the WRA kills on the population requires quantification of both survival and reproduction. To estimate survival rates of both territorial and non-territorial golden eagles, we tagged 179 individuals with radio-telemetry transmitters expected to function for about four years and equipped with mortality sensors. Population segments represented in the tagged sample include 79 juveniles, 45 subadults, 17n floaters (non-territorial adults), and 38 breeders. Effective sample sizes in the older segments increase as younger eagles mature or become territorial. Since the beginning of the study, we have conducted weekly roll-call surveys by airplane to locate the tagged eagles in relation to the WRA and to monitor their survival. The surveyed area extends from the Oakland Hills southeast through the Diablo Mountain Range to San Luis Reservoir about 75 km southeast of the WRA. The surveys show that breeding eagles rarely enter the WRA while the non-territorial eagles tend to move about freely throughout the study area and often visit the WRA.

  13. Application of the nonlinear time series prediction method of genetic algorithm for forecasting surface wind of point station in the South China Sea with scatterometer observations

    International Nuclear Information System (INIS)

    Zhong Jian; Dong Gang; Sun Yimei; Zhang Zhaoyang; Wu Yuqin

    2016-01-01

    The present work reports the development of nonlinear time series prediction method of genetic algorithm (GA) with singular spectrum analysis (SSA) for forecasting the surface wind of a point station in the South China Sea (SCS) with scatterometer observations. Before the nonlinear technique GA is used for forecasting the time series of surface wind, the SSA is applied to reduce the noise. The surface wind speed and surface wind components from scatterometer observations at three locations in the SCS have been used to develop and test the technique. The predictions have been compared with persistence forecasts in terms of root mean square error. The predicted surface wind with GA and SSA made up to four days (longer for some point station) in advance have been found to be significantly superior to those made by persistence model. This method can serve as a cost-effective alternate prediction technique for forecasting surface wind of a point station in the SCS basin. (paper)

  14. Extreme Motion Predictions for Deepwater TLP Floaters for Offshore Wind Turbines

    DEFF Research Database (Denmark)

    Jensen, Jørgen Juncher; Mansour, A. E.

    2006-01-01

    The paper addresses the calculation of extreme motion of a TLP type of floater for an offshore wind turbine. Motions are of significant importance for the operation of the wind turbine as they influence the blade loadings and hence the downtime of the wind turbine energy production. The paper ill...

  15. Assessment of the Uniqueness of Wind Tunnel Strain-Gage Balance Load Predictions

    Science.gov (United States)

    Ulbrich, N.

    2016-01-01

    A new test was developed to assess the uniqueness of wind tunnel strain-gage balance load predictions that are obtained from regression models of calibration data. The test helps balance users to gain confidence in load predictions of non-traditional balance designs. It also makes it possible to better evaluate load predictions of traditional balances that are not used as originally intended. The test works for both the Iterative and Non-Iterative Methods that are used in the aerospace testing community for the prediction of balance loads. It is based on the hypothesis that the total number of independently applied balance load components must always match the total number of independently measured bridge outputs or bridge output combinations. This hypothesis is supported by a control volume analysis of the inputs and outputs of a strain-gage balance. It is concluded from the control volume analysis that the loads and bridge outputs of a balance calibration data set must separately be tested for linear independence because it cannot always be guaranteed that a linearly independent load component set will result in linearly independent bridge output measurements. Simple linear math models for the loads and bridge outputs in combination with the variance inflation factor are used to test for linear independence. A highly unique and reversible mapping between the applied load component set and the measured bridge output set is guaranteed to exist if the maximum variance inflation factor of both sets is less than the literature recommended threshold of five. Data from the calibration of a six{component force balance is used to illustrate the application of the new test to real-world data.

  16. Space-time extreme wind waves: Analysis and prediction of shape and height

    Science.gov (United States)

    Alvise, Benetazzo; Francesco, Barbariol; Filippo, Bergamasco; Sandro, Carniel; Mauro, Sclavo

    2017-05-01

    In this study, we present the analysis of the temporal profile and height of space-time (ST) extreme wind waves. Wave data were gathered from an observational ST sample of sea surface elevations collected during an active sea state, and they were examined to detect the highest waves (exceeding the rogue wave threshold) of specific 3D wave groups close to the apex of their development. Two different investigations are conducted. Firstly, local maximum elevations of the groups are examined within the framework of statistical models for ST extreme waves, and compared with observations and predictions of maxima derived by one-point time series of sea surface elevations. Secondly, the temporal profile near the maximum wave crests is analyzed and compared with the expectations of the linear and second-order nonlinear extension of the Quasi-Determinism (QD) theory. Our goal is to verify, with real sea data, to what extent, one can estimate the shape and the crest-to-trough height of near-focusing large 3D wave groups using the QD and ST extreme model results. From this study, it emerges that the elevations close to the crest apex are narrowly distributed around a mean profile, whilst a larger dispersion is observed away from the maximum elevation. Yet the QD model furnishes, on average, a fair prediction of the maximum wave heights, especially when nonlinearities are taken into account. Moreover, we discuss how the combination of ST extreme and QD model predictions allows establishing, for a given sea condition, the portrait of waves with very large crest height. Our results show that these theories have the potential to be implemented in a numerical spectral model for wave extreme prediction.

  17. Wind pollination and propagule formation in Rhizophora mangle L. (Rhizophoraceae: resource or pollination limitation?

    Directory of Open Access Journals (Sweden)

    TARCILA L. NADIA

    2014-03-01

    Full Text Available Rhizophora mangle is considered as a self-compatible mangrove, and is pollinated by wind and insects. However, there is no information about fruit production by autogamy and agamospermy and on the foraging behavior of its flower visitors. Hence, the present study analyzed the pollination and reproductive systems of R. mangle in a mangrove community in northern Pernambuco, Brazil. Floral morphology, sequence of anthesis, and behavior of flower visitors were described; the proportion of flowers that resulted in mature propagules was also recorded. Autogamy, agamospermy, and wind pollination tests were performed, and a new anemophily index is proposed. The flowers of R. mangle are hermaphrodite, protandric, and have high P/O rate. Flies were observed on flowers only during the male phase, probably feeding on mites that consume pollen. Rhizophora mangle is not agamospermic and its fruit production rate by spontaneous self-pollination is low (2.56% compared to wind pollination (19.44%. The anemophily index was high 0.98, and thus it was considered as a good indicator. Only 13.79% of the flowers formed mature propagules. The early stages of fruit development are the most critical and susceptible to predation. Rhizophora mangle is, therefore, exclusively anemophilous in the study area and the propagule dispersal seems to be limited by herbivory.

  18. The state-of-the-art in short-term prediction of wind power. A literature overview

    Energy Technology Data Exchange (ETDEWEB)

    Giebel, G.; Brownsword, R.; Kariniotakis, G.

    2003-08-01

    Based on an appropriate questionnaire (WP1.1) and some other works already in progress, this report details the state-of-the-art in short term prediction of wind power, mostly summarising nearly all existing literature on the topic. (au)

  19. Directed flight and optimal airspeeds: homeward-bound gulls react flexibly to wind yet fly slower than predicted

    NARCIS (Netherlands)

    McLaren, J.D.; Shamoun, J.; Camphuysen, C.J.; Bouten, W.

    2016-01-01

    Birds in flight are proposed to adjust their body orientation (heading) and airspeed to wind conditions adaptively according to time and energy constraints. Airspeeds in goal-directed flight are predicted to approach or exceed maximum-range airspeeds, which minimize transport costs (energy

  20. Prediction of geomagnetic storms from solar wind data with the use of a neural network

    Directory of Open Access Journals (Sweden)

    H. Lundstedt

    Full Text Available An artificial feed-forward neural network with one hidden layer and error back-propagation learning is used to predict the geomagnetic activity index (Dst one hour in advance. The Bz-component and ΣBz, the density, and the velocity of the solar wind are used as input to the network. The network is trained on data covering a total of 8700 h, extracted from the 25-year period from 1963 to 1987, taken from the NSSDC data base. The performance of the network is examined with test data, not included in the training set, which covers 386 h and includes four different storms. Whilst the network predicts the initial and main phase well, the recovery phase is not modelled correctly, implying that a single hidden layer error back-propagation network is not enough, if the measured Dst is not available instantaneously. The performance of the network is independent of whether the raw parameters are used, or the electric field and square root of the dynamical pressure.

  1. A review on the young history of the wind power short-term prediction

    Energy Technology Data Exchange (ETDEWEB)

    Costa, Alexandre; Navarro, Jorge [Wind Energy, Division of Renewable Energies, Department of Energy, CIEMAT, Av. Complutense, 22, Ed. 42, 28044 Madrid (Spain); Crespo, Antonio [Laboratorio de Mecanica de Fluidos, Departmento de Ingenieria Energetica y Fluidomecanica, ETSII, Universidad Politecnica de Madrid, C/Jose Gutierrez Abascal, 2-28006 Madrid (Spain); Lizcano, Gil [Oxford University Centre for the Environment, University of Oxford, South Parks Road, Oxford OX1 3QY (United Kingdom); Madsen, Henrik [Informatics and Mathematical Modelling - IMM, Technical University of Denmark, Richard Petersens Plads, Building 321, Office 019, 2800 Kgs. Lyngby (Denmark); Feitosa, Everaldo [Brazilian Wind Energy Centre - CBEE, Centro de Tecnologia e Geociencias, UFPE-50.740-530 Recife, PE (Brazil)

    2008-08-15

    This paper makes a brief review on 30 years of history of the wind power short-term prediction, since the first ideas and sketches on the theme to the actual state of the art on models and tools, giving emphasis to the most significant proposals and developments. The two principal lines of thought on short-term prediction (mathematical and physical) are indistinctly treated here and comparisons between models and tools are avoided, mainly because, on the one hand, a standard for a measure of performance is still not adopted and, on the other hand, it is very important that the data are exactly the same in order to compare two models (this fact makes it almost impossible to carry out a quantitative comparison between a huge number of models and methods). In place of a quantitative description, a qualitative approach is preferred for this review, remarking the contribution (and innovative aspect) of each model. On the basis of the review, some topics for future research are pointed out. (author)

  2. Modular Resource Centric Learning for Workflow Performance Prediction

    OpenAIRE

    Singh, Alok; Nguyen, Mai; Purawat, Shweta; Crawl, Daniel; Altintas, Ilkay

    2017-01-01

    Workflows provide an expressive programming model for fine-grained control of large-scale applications in distributed computing environments. Accurate estimates of complex workflow execution metrics on large-scale machines have several key advantages. The performance of scheduling algorithms that rely on estimates of execution metrics degrades when the accuracy of predicted execution metrics decreases. This in-progress paper presents a technique being developed to improve the accuracy of pred...

  3. Assessing risk to birds from industrial wind energy development via paired resource selection nodels

    Science.gov (United States)

    Tricia A. Miller; Robert P. Brooks; Michael Lanzone; David Brandes; Jeff Cooper; Kieran O' malley; Charles Maisonneuve; Junior Tremblay; Adam Duerr; Todd. Katzner

    2014-01-01

    When wildlife habitat overlaps with industrial development animals may be harmed. Because wildlife and people select resources to maximize biological fitness and economic return, respectively, we estimated risk, the probability of eagles encountering and being affected by turbines, by overlaying models of resource selection for each entity. This conceptual framework...

  4. Wind energy program overview

    International Nuclear Information System (INIS)

    1992-02-01

    This overview emphasizes the amount of electric power that could be provided by wind power rather than traditional fossil fuels. New wind power markets, advances in technology, technology transfer, and wind resources are some topics covered in this publication

  5. Hybrid PV/Wind Power Systems Incorporating Battery Storage and Considering the Stochastic Nature of Renewable Resources

    Science.gov (United States)

    Barnawi, Abdulwasa Bakr

    Hybrid power generation system and distributed generation technology are attracting more investments due to the growing demand for energy nowadays and the increasing awareness regarding emissions and their environmental impacts such as global warming and pollution. The price fluctuation of crude oil is an additional reason for the leading oil producing countries to consider renewable resources as an alternative. Saudi Arabia as the top oil exporter country in the word announced the "Saudi Arabia Vision 2030" which is targeting to generate 9.5 GW of electricity from renewable resources. Two of the most promising renewable technologies are wind turbines (WT) and photovoltaic cells (PV). The integration or hybridization of photovoltaics and wind turbines with battery storage leads to higher adequacy and redundancy for both autonomous and grid connected systems. This study presents a method for optimal generation unit planning by installing a proper number of solar cells, wind turbines, and batteries in such a way that the net present value (NPV) is minimized while the overall system redundancy and adequacy is maximized. A new renewable fraction technique (RFT) is used to perform the generation unit planning. RFT was tested and validated with particle swarm optimization and HOMER Pro under the same conditions and environment. Renewable resources and load randomness and uncertainties are considered. Both autonomous and grid-connected system designs were adopted in the optimal generation units planning process. An uncertainty factor was designed and incorporated in both autonomous and grid connected system designs. In the autonomous hybrid system design model, the strategy including an additional amount of operation reserve as a percent of the hourly load was considered to deal with resource uncertainty since the battery storage system is the only backup. While in the grid-connected hybrid system design model, demand response was incorporated to overcome the impact of

  6. Using Forecasting to Predict Long-Term Resource Utilization for Web Services

    Science.gov (United States)

    Yoas, Daniel W.

    2013-01-01

    Researchers have spent years understanding resource utilization to improve scheduling, load balancing, and system management through short-term prediction of resource utilization. Early research focused primarily on single operating systems; later, interest shifted to distributed systems and, finally, into web services. In each case researchers…

  7. Rate Predictions and Trigger/DAQ Resource Monitoring in ATLAS

    CERN Document Server

    Schaefer, D M; The ATLAS collaboration

    2012-01-01

    Since starting in 2010, the Large Hadron Collider (LHC) has pro- duced collisions at an ever increasing rate. The ATLAS experiment successfully records the collision data with high eciency and excel- lent data quality. Events are selected using a three-level trigger system, where each level makes a more re ned selection. The level-1 trigger (L1) consists of a custom-designed hardware trigger which seeds two higher software based trigger levels. Over 300 triggers compose a trig- ger menu which selects physics signatures such as electrons, muons, particle jets, etc. Each trigger consumes computing resources of the ATLAS trigger system and oine storage. The LHC instantaneous luminosity conditions, desired physics goals of the collaboration, and the limits of the trigger infrastructure determine the composition of the ATLAS trigger menu. We describe a trigger monitoring frame- work for computing the costs of individual trigger algorithms such as data request rates and CPU consumption. This framework has been used...

  8. A history of wind erosion prediction models in the United States Department of Agriculture Prior to the Wind Erosion Prediction System

    Science.gov (United States)

    The Great Plains experienced an influx of settlers in the late 1850s to 1900. Periodic drought was hard on both settlers and the soil and caused severe wind erosion. The period known as the Dirty Thirties, 1931 to 1939, produced many severe windstorms, and the resulting dusty sky over Washington, D....

  9. Stochastic Model Predictive Fault Tolerant Control Based on Conditional Value at Risk for Wind Energy Conversion System

    Directory of Open Access Journals (Sweden)

    Yun-Tao Shi

    2018-01-01

    Full Text Available Wind energy has been drawing considerable attention in recent years. However, due to the random nature of wind and high failure rate of wind energy conversion systems (WECSs, how to implement fault-tolerant WECS control is becoming a significant issue. This paper addresses the fault-tolerant control problem of a WECS with a probable actuator fault. A new stochastic model predictive control (SMPC fault-tolerant controller with the Conditional Value at Risk (CVaR objective function is proposed in this paper. First, the Markov jump linear model is used to describe the WECS dynamics, which are affected by many stochastic factors, like the wind. The Markov jump linear model can precisely model the random WECS properties. Second, the scenario-based SMPC is used as the controller to address the control problem of the WECS. With this controller, all the possible realizations of the disturbance in prediction horizon are enumerated by scenario trees so that an uncertain SMPC problem can be transformed into a deterministic model predictive control (MPC problem. Finally, the CVaR object function is adopted to improve the fault-tolerant control performance of the SMPC controller. CVaR can provide a balance between the performance and random failure risks of the system. The Min-Max performance index is introduced to compare the fault-tolerant control performance with the proposed controller. The comparison results show that the proposed method has better fault-tolerant control performance.

  10. Wind Power Forecasting Using Multi-Objective Evolutionary Algorithms for Wavelet Neural Network-Optimized Prediction Intervals

    Directory of Open Access Journals (Sweden)

    Yanxia Shen

    2018-01-01

    Full Text Available The intermittency of renewable energy will increase the uncertainty of the power system, so it is necessary to predict the short-term wind power, after which the electrical power system can operate reliably and safely. Unlike the traditional point forecasting, the purpose of this study is to quantify the potential uncertainties of wind power and to construct prediction intervals (PIs and prediction models using wavelet neural network (WNN. Lower upper bound estimation (LUBE of the PIs is achieved by minimizing a multi-objective function covering both interval width and coverage probabilities. Considering the influence of the points out of the PIs to shorten the width of PIs without compromising coverage probability, a new, improved, multi-objective artificial bee colony (MOABC algorithm combining multi-objective evolutionary knowledge, called EKMOABC, is proposed for the optimization of the forecasting model. In this paper, some comparative simulations are carried out and the results show that the proposed model and algorithm can achieve higher quality PIs for wind power forecasting. Taking into account the intermittency of renewable energy, such a type of wind power forecast can actually provide a more reliable reference for dispatching of the power system.

  11. Short-term wind speed prediction based on the wavelet transformation and Adaboost neural network

    Science.gov (United States)

    Hai, Zhou; Xiang, Zhu; Haijian, Shao; Ji, Wu

    2018-03-01

    The operation of the power grid will be affected inevitably with the increasing scale of wind farm due to the inherent randomness and uncertainty, so the accurate wind speed forecasting is critical for the stability of the grid operation. Typically, the traditional forecasting method does not take into account the frequency characteristics of wind speed, which cannot reflect the nature of the wind speed signal changes result from the low generality ability of the model structure. AdaBoost neural network in combination with the multi-resolution and multi-scale decomposition of wind speed is proposed to design the model structure in order to improve the forecasting accuracy and generality ability. The experimental evaluation using the data from a real wind farm in Jiangsu province is given to demonstrate the proposed strategy can improve the robust and accuracy of the forecasted variable.

  12. Predicting Atmospheric Ionization and Excitation by Precipitating SEP and Solar Wind Protons Measured By MAVEN

    Science.gov (United States)

    Jolitz, Rebecca; Dong, Chuanfei; Lee, Christina; Lillis, Rob; Brain, David; Curry, Shannon; Halekas, Jasper; Bougher, Stephen W.; Jakosky, Bruce

    2017-10-01

    Precipitating energetic particles ionize and excite planetary atmospheres, increasing electron content and producing aurora. At Mars, the solar wind and solar energetic particles (SEPs) can precipitate directly into the atmosphere because solar wind protons can charge exchange to become neutral and pass the magnetosheath, and SEPs are sufficiently energetic to cross the magnetosheath unchanged. We will compare ionization and Lyman alpha emission rates for solar wind and SEP protons during nominal solar activity and a CME shock front impact event on May 16 2016. We will use the Atmospheric Scattering of Protons and Energetic Neutrals (ASPEN) model to compare excitation and ionization rates by SEPs and solar wind protons currently measured by the SWIA (Solar Wind Ion Analyzer) and SEP instruments aboard the MAVEN spacecraft. Results will help quantify how SEP and solar wind protons influence atmospheric energy deposition during solar minimum.

  13. Power and loads for wind turbines in yawed conditions. Analysis of field measurements and aerodynamic predictions

    Energy Technology Data Exchange (ETDEWEB)

    Boorsma, K. [ECN Wind Energy, Petten (Netherlands)

    2012-11-15

    A description is given of the work carried out within the framework of the FLOW (Far and Large Offshore Wind) project on single turbine performance in yawed flow conditions. Hereto both field measurements as well as calculations with an aerodynamic code are analyzed. The rotors of horizontal axis wind turbines follow the changes in the wind direction for optimal performance. The reason is that the power is expected to decrease for badly oriented rotors. So, insight in the effects of the yaw angle on performance is important for optimization of the yaw control of each individual turbine. The effect of misalignment on performance and loads of a single 2.5 MW wind turbine during normal operation is investigated. Hereto measurements at the ECN Wind Turbine Test Site Wieringermeer (EWTW) are analyzed from December 2004 until April 2009. Also, the influence of yaw is studied using a design code and results from this design code are compared with wind tunnel measurements.

  14. A genome-wide gene function prediction resource for Drosophila melanogaster.

    Directory of Open Access Journals (Sweden)

    Han Yan

    2010-08-01

    Full Text Available Predicting gene functions by integrating large-scale biological data remains a challenge for systems biology. Here we present a resource for Drosophila melanogaster gene function predictions. We trained function-specific classifiers to optimize the influence of different biological datasets for each functional category. Our model predicted GO terms and KEGG pathway memberships for Drosophila melanogaster genes with high accuracy, as affirmed by cross-validation, supporting literature evidence, and large-scale RNAi screens. The resulting resource of prioritized associations between Drosophila genes and their potential functions offers a guide for experimental investigations.

  15. Improving Wind Predictions in the Marine Atmospheric Boundary Layer through Parameter Estimation in a Single-Column Model

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Jared A.; Hacker, Joshua P.; Delle Monache, Luca; Kosović, Branko; Clifton, Andrew; Vandenberghe, Francois; Rodrigo, Javier Sanz

    2016-12-14

    A current barrier to greater deployment of offshore wind turbines is the poor quality of numerical weather prediction model wind and turbulence forecasts over open ocean. The bulk of development for atmospheric boundary layer (ABL) parameterization schemes has focused on land, partly due to a scarcity of observations over ocean. The 100-m FINO1 tower in the North Sea is one of the few sources worldwide of atmospheric profile observations from the sea surface to turbine hub height. These observations are crucial to developing a better understanding and modeling of physical processes in the marine ABL. In this study, we use the WRF single column model (SCM), coupled with an ensemble Kalman filter from the Data Assimilation Research Testbed (DART), to create 100-member ensembles at the FINO1 location. The goal of this study is to determine the extent to which model parameter estimation can improve offshore wind forecasts.

  16. Air-Loads Prediction of a UH-60A Rotor inside the 40- by 80-Foot Wind Tunnel

    Science.gov (United States)

    Chang, I-Chung; Romander, Ethan A.; Potsdam, Mark; Yeo, Hyeonsoo

    2010-01-01

    The presented research extends the capability of a loose coupling computational fluid dynamics (CFD) and computational structure dynamics (CSD) code to calculate the flow-field around a rotor and test stand mounted inside a wind tunnel. Comparison of predicted air-load results for a full-scale UH-60A rotor recently tested inside the National Full-Scale Aerodynamics Complex (NFAC) 40- by 80-Foot Wind Tunnel at Ames Research Center and in free-air flight are made for three challenging flight data points from the earlier conducted UH-60A Air-loads Program. Overall results show that the extension of the coupled CFD/CSD code to the wind-tunnel environment is generally successful.

  17. Sexual-size dimorphism modulates the trade-off between exploiting food and wind resources in a large avian scavenger.

    Science.gov (United States)

    Alarcón, Pablo A E; Morales, Juan M; Donázar, José A; Sánchez-Zapata, José A; Hiraldo, Fernando; Lambertucci, Sergio A

    2017-09-13

    Animals are expected to synchronize activity routines with the temporal patterns at which resources appear in nature. Accordingly, species that depend on resources showing temporally mismatched patterns should be expected to schedule routines that balance the chances of exploiting each of them. Large avian scavengers depend on carcasses which are more likely available early in the morning, but they also depend on wind resources (i.e. uplifts) to subside flight which are stronger in afternoon hours. To understand how these birds deal with this potential trade-off, we studied the daily routines of GPS-tagged individuals of the world's largest terrestrial soaring scavenger, the Andean condor (Vultur gryphus). Andean condors vary largely in weight and show a huge sexual dimorphism that allowed us to evaluate the effect of sex and body size on their daily routines. We found that condors use an intermediate solution strategy between the best times to exploit carcasses and uplifts, with this strategy changing over the year. Bigger males scheduled earlier routines that aligned more closely with uplift availability compared to smaller females, resulting in a partial temporal segregation between sexes. Condors' routines reflect a sexual-size dependent trade-off that may underpin ecological and sociobiological traits of the studied population.

  18. Relative performance of different numerical weather prediction models for short term predition of wind wnergy

    Energy Technology Data Exchange (ETDEWEB)

    Giebel, G.; Landberg, L. [Risoe National Lab., Wind Energy and Atmospheric Physics Dept., Roskilde (Denmark); Moennich, K.; Waldl, H.P. [Carl con Ossietzky Univ., Faculty of Physics, Dept. of Energy and Semiconductor, Oldenburg (Germany)

    1999-03-01

    In several approaches presented in other papers in this conference, short term forecasting of wind power for a time horizon covering the next two days is done on the basis of Numerical Weather Prediction (NWP) models. This paper explores the relative merits of HIRLAM, which is the model used by the Danish Meteorological Institute, the Deutschlandmodell from the German Weather Service and the Nested Grid Model used in the US. The performance comparison will be mainly done for a site in Germany which is in the forecasting area of both the Deutschlandmodell and HIRLAM. In addition, a comparison of measured data with the forecasts made for one site in Iowa will be included, which allows conclusions on the merits of all three models. Differences in the relative performances could be due to a better tailoring of one model to its country, or to a tighter grid, or could be a function of the distance between the grid points and the measuring site. Also the amount, in which the performance can be enhanced by the use of model output statistics (topic of other papers in this conference) could give insights into the performance of the models. (au)

  19. Prediction and control of coupled-mode flutter in future wind turbine blades

    Science.gov (United States)

    Modarres-Sadeghi, Yahya; Currier, Todd; Caracoglia, Luca; Lackner, Matthew; Hollot, Christopher

    2017-11-01

    Coupled-mode flutter can be observed in future offshore wind turbine blades. We have shown this fact by considering various candidate blade designs, in all of which the blade's first torsional mode couples with one of its flapwise modes, resulting in coupled-mode flutter. We have shown how the ratio of these two natural frequencies can result in blades with a critical flutter speed even lower than their rated speed, especially for blades with low torsional natural frequencies. We have also shown how the stochastic nature of the system parameters (as an example, due to uncertainties in the manufacturing process) can significantly influence the onset of instability. We have proposed techniques to predict the onset of these instabilities and the resulting limit-cycle response, and strategies to control them, by either postponing the onset of instability, or lowering the magnitude of the limit-cycle response. The work is supported by the National Science Foundation, Award CBET-1437988 and Collaborative Awards CMMI-1462646 and CMMI-1462774.

  20. Value of Flexible Resources, Virtual Bidding, and Self-Scheduling in Two-Settlement Electricity Markets With Wind Generation – Part I: Principles and Competitive Model

    DEFF Research Database (Denmark)

    Kazempour, Jalal; Hobbs, Benjamin F.

    2017-01-01

    Part one of this two-part paper presents new models for evaluating flexible resources in two-settlement electricity markets (day-ahead and real-time) with uncertain net loads (demand minus wind). Physical resources include wind together with fast- and slow-start demand response and thermal genera...... of certain equivalencies of the four models. We show how virtual bidding enhances market performance, since, together with self-scheduling by slow-start generators, it can help deterministic day-ahead market to choose the most efficient unit commitment....