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

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

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.

Philippines Wind Energy Resource Atlas Development

Energy Technology Data Exchange (ETDEWEB)

Elliott, D.

2000-11-29

This paper describes the creation of a comprehensive wind energy resource atlas for the Philippines. The atlas was created to facilitate the rapid identification of good wind resource areas and understanding of the salient wind characteristics. Detailed wind resource maps were generated for the entire country using an advanced wind mapping technique and innovative assessment methods recently developed at the National Renewable Energy Laboratory.

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.

A GIS wind resource map with tabular printout of monthly and annual wind speeds for 2,000 towns in Iowa

Energy Technology Data Exchange (ETDEWEB)

Brower, M.C. [Brower & Company, Andover, MA (United States); Factor, T. [Iowa Wind Energy Institute, Fairfield, IA (United States)

1997-12-31

The Iowa Wind Energy Institute, under a grant from the Iowa Energy Center, undertook in 1994 to map wind resources in Iowa. Fifty-meter met towers were erected at 13 locations across the state deemed promising for utility-scale wind farm development. Two years of summarized wind speed, direction, and temperature data were used to create wind resource maps incorporating effects of elevation, relative exposure, terrain roughness, and ground cover. Maps were produced predicting long-term mean monthly and annual wind speeds on a one-kilometer grid. The estimated absolute standard error in the predicted annual average wind speeds at unobstructed locations is 9 percent. The relative standard error between points on the annual map is estimated to be 3 percent. These maps and tabular data for 2,000 cities and towns in Iowa are now available on the Iowa Energy Center`s web site (http.//www.energy.iastate.edu).

Wind Speed Prediction with Wavelet Time Series Based on Lorenz Disturbance

Directory of Open Access Journals (Sweden)

ZHANG, Y.

2017-08-01

Full Text Available Due to the sustainable and pollution-free characteristics, wind energy has been one of the fastest growing renewable energy sources. However, the intermittent and random fluctuation of wind speed presents many challenges for reliable wind power integration and normal operation of wind farm. Accurate wind speed prediction is the key to ensure the safe operation of power system and to develop wind energy resources. Therefore, this paper has presented a wavelet time series wind speed prediction model based on Lorenz disturbance. Therefore, in this paper, combined with the atmospheric dynamical system, a wavelet-time series improved wind speed prediction model based on Lorenz disturbance is proposed and the wind turbines of different climate types in Spain and China are used to simulate the disturbances of Lorenz equations with different initial values. The prediction results show that the improved model can effectively correct the preliminary prediction of wind speed, improving the prediction. In a word, the research work in this paper will be helpful to arrange the electric power dispatching plan and ensure the normal operation of the wind farm.

Development of distributed topographical forecasting model for wind resource assessment using artificial neural networks

Energy Technology Data Exchange (ETDEWEB)

Narayana, P.B. [Green Life Energy Solutions LLP, Secunderabad (India); Rao, S.S. [National Institute of Technology. Dept. of Mechanical Engineering, Warangal (India); Reddy, K.H. [JNT Univ.. Dept. of Mechanical Engineering, Anantapur (India)

2012-07-01

Economics of wind power projects largely depend on the availability of wind power density. Wind resource assessment is a study estimating wind speeds and wind power densities in the region under consideration. The accuracy and reliability of data sets comprising of wind speeds and wind power densities at different heights per topographic region characterized by elevation or mean sea level, is important for wind power projects. Indian Wind Resource Assessment program conducted in 80's consisted of wind data measured by monitoring stations at different topographies in order to measure wind power density values at 25 and 50 meters above the ground level. In this paper, an attempt has been made to assess wind resource at a given location using artificial neural networks. Existing wind resource data has been used to train the neural networks. Location topography (characterized by longitude, latitude and mean sea level), air density, mean annual wind speed (MAWS) are used as inputs to the neural network. Mean annual wind power density (MAWPD) in watt/m{sup 2} is predicted for a new topographic location. Simple back propagation based neural network has been found to be sufficient for predicting these values with suitable accuracy. This model is closely linked to the problem of wind energy forecasting considering the variations of specific atmospheric variables with time horizons. This model will help the wind farm developers to have an initial estimation of the wind energy potential at a particular topography. (Author)

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.

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.

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.

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

DEFF Research Database (Denmark)

Badger, Jake; Ejsing Jørgensen, Hans

2011-01-01

to population centres, electrical transmission grids, terrain types, and protected land areas are important parts of the resource assessment downstream of the generation of wind climate statistics. Related to these issues of integration are the temporal characteristics and spatial correlation of the wind...... 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...

Wind Resource Atlas of Oaxaca (CD-ROM)

Energy Technology Data Exchange (ETDEWEB)

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

2003-08-01

The CD version of 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.

Wind Energy Resource Atlas of Mongolia

Energy Technology Data Exchange (ETDEWEB)

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

2001-08-27

The United States Department of Energy (DOE) and the United States Agency for International Development (USAID) sponsored a project to help accelerate the large-scale use of wind energy technologies in Mongolia through the development of a wind energy resource atlas of Mongolia. DOE's National Renewable Energy Laboratory (NREL) administered and conducted this project in collaboration with USAID and Mongolia. The Mongolian organizations participating in this project were the Scientific, Production, and Trade Corporation for Renewable Energy (REC) and the Institute of Meteorology and Hydrology (IMH). The primary goals of the project were to develop detailed wind resource maps for all regions of Mongolia for a comprehensive wind resource atlas, and to establish a wind-monitoring program to identify prospective sites for wind energy projects and help validate some of the wind resource estimates.

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...

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

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......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......) of the project often still requires in situ observations (which may or may not be supplemented with ground-based remote sensing technologies) and application of tools to provide a climatological context for the resulting measurements. Current methodologies for undertaking these aspects of the resource assessment...

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)

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.

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.

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 complexity of air-sea interaction processes, an empirical relationship that adjusts QuikSCAT winds in coastal waters was first proposed based on vessel measurements. Then the shape and scale parameters of Weibull function are determined for wind resource estimation. The wind roses are also plotted. Results...

Evaluation model of wind energy resources and utilization efficiency of wind farm

Science.gov (United States)

Ma, Jie

2018-04-01

Due to the large amount of abandoned winds in wind farms, the establishment of a wind farm evaluation model is particularly important for the future development of wind farms In this essay, consider the wind farm's wind energy situation, Wind Energy Resource Model (WERM) and Wind Energy Utilization Efficiency Model(WEUEM) are established to conduct a comprehensive assessment of the wind farm. Wind Energy Resource Model (WERM) contains average wind speed, average wind power density and turbulence intensity, which assessed wind energy resources together. Based on our model, combined with the actual measurement data of a wind farm, calculate the indicators using the model, and the results are in line with the actual situation. We can plan the future development of the wind farm based on this result. Thus, the proposed establishment approach of wind farm assessment model has application value.

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 ...

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...

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)

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.

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.

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 of the...

Complex terrain wind resource estimation with the wind-atlas method: Prediction errors using linearized and nonlinear CFD micro-scale models

DEFF Research Database (Denmark)

Troen, Ib; Bechmann, Andreas; Kelly, Mark C.

2014-01-01

Using the Wind Atlas methodology to predict the average wind speed at one location from measured climatological wind frequency distributions at another nearby location we analyse the relative prediction errors using a linearized flow model (IBZ) and a more physically correct fully non-linear 3D...... flow model (CFD) for a number of sites in very complex terrain (large terrain slopes). We first briefly describe the Wind Atlas methodology as implemented in WAsP and the specifics of the “classical” model setup and the new setup allowing the use of the CFD computation engine. We discuss some known...

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.

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....

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

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.

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)

Computer modelling of the UK wind energy resource: UK wind speed data package and user manual

Energy Technology Data Exchange (ETDEWEB)

Burch, S F; Ravenscroft, F

1993-12-31

A software package has been developed for IBM-PC or true compatibles. It is designed to provide easy access to the results of a programme of work to estimate the UK wind energy resource. Mean wind speed maps and quantitative resource estimates were obtained using the NOABL mesoscale (1 km resolution) numerical model for the prediction of wind flow over complex terrain. NOABL was used in conjunction with digitised terrain data and wind data from surface meteorological stations for a ten year period (1975-1984) to provide digital UK maps of mean wind speed at 10m, 25m and 45m above ground level. Also included in the derivation of these maps was the use of the Engineering Science Data Unit (ESDU) method to model the effect on wind speed of the abrupt change in surface roughness that occurs at the coast. With the wind speed software package, the user is able to obtain a display of the modelled wind speed at 10m, 25m and 45m above ground level for any location in the UK. The required co-ordinates are simply supplied by the user, and the package displays the selected wind speed. This user manual summarises the methodology used in the generation of these UK maps and shows computer generated plots of the 25m wind speeds in 200 x 200 km regions covering the whole UK. The uncertainties inherent in the derivation of these maps are also described, and notes given on their practical usage. The present study indicated that 23% of the UK land area had speeds over 6 m/s, with many hill sites having 10m speeds over 10 m/s. It is concluded that these `first order` resource estimates represent a substantial improvement over the presently available `zero order` estimates. (18 figures, 3 tables, 6 references). (author)

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.

Wind resource assessment and wind energy system cost analysis: Fort Huachuca, Arizona

Energy Technology Data Exchange (ETDEWEB)

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

1997-12-01

The objective of this joint DOE and National Renewable Energy Laboratory (NREL) Strategic Environmental Research and Development Program (SERDP) project is to determine whether wind turbines can reduce costs by providing power to US military facilities in high wind areas. In support of this objective, one year of data on the wind resources at several Fort Huachuca sites was collected. The wind resource data were analyzed and used as input to an economic study for a wind energy installation at Fort Huachuca. The results of this wind energy feasibility study are presented in the report.

Computer modelling of the UK wind energy resource: final overview report

Energy Technology Data Exchange (ETDEWEB)

Burch, S F; Ravenscroft, F

1993-12-31

This report describes the results of a programme of work to estimate the UK wind energy resource. Mean wind speed maps and quantitative resource estimates were obtained using the NOABL mesoscale (1 km resolution) numerical model for the prediction of wind flow over complex terrain. NOABL was used in conjunction with digitised terrain data and wind data from surface meteorological stations for a ten year period (1975-1984) to provide digital UK maps of mean wind speed at 10m, 25m and 45m above ground level. Also included in the derivation of these maps was the use of the Engineering Science Data Unit (ESDU) method to model the effect on wind speed of the abrupt change in surface roughness that occurs at the coast. Existing isovent maps, based on standard meteorological data which take no account of terrain effects, indicate that 10m annual mean wind speeds vary between about 4.5 and 7 m/s over the UK with only a few coastal areas over 6 m/s. The present study indicated that 23% of the UK land area had speeds over 6 m/s, with many hill sites having 10m speeds over 10 m/s. It is concluded that these `first order` resource estimates represent a substantial improvement over the presently available `zero order` estimates. (20 figures, 7 tables, 10 references). (author)

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.

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.

Characterization of wind power resource and its intermittency

Science.gov (United States)

Gunturu, U. B.; Schlosser, C. A.

2011-12-01

Wind resource in the continental and offshore United States has been calculated and characterized using metrics that describe - apart from abundance - its availability, persistence and intermittency. The Modern Era Retrospective-Analysis for Research and Applications (MERRA) boundary layer flux data has been used to construct wind power density profiles at 50, 80, 100 and 120 m turbine hub heights. The wind power density estimates at 50 m are qualitatively similar to those in the US wind atlas developed by the National Renewable Energy Laboratory (NREL), but quantitatively a class less in some regions, but are within the limits of uncertainty. We also show that for long tailed distributions like those of the wind power density, the mean is an overestimation and median is a more robust metric for summary representation of wind power resource.Generally speaking, the largest and most available wind power density resources are found in off-shore regions of the Atlantic and Pacific coastline, and the largest on-shore resource potential lies in the central United States. However, the intermittency and widespread synchronicity of on-shore wind power density are substantial, and highlights areas where considerable back-up generation technologies will be required. Generation-duration curves are also presented for the independent systems operator (ISO) zones of the U.S. to highlight the regions with the largest capacity factor (MISO, ERCOT, and SWPP) as well as the periods and extent to which all ISOs contain no wind power and the potential benefits of aggregation on wind power intermittency in each region. The impact of raising the wind turbine hub height on metrics of abundance, persistence, variability and intermittency is analyzed. There is a general increase in availability and abundance of wind resource but there is also an increase in intermittency with respect to a 'usable wind power' crossing level in low resource regions. A similar perspective of wind resource for

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.

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...

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.

Total, accessible and reserve wind energy resources in Bulgaria

International Nuclear Information System (INIS)

Ivanov, P.; Trifonova, L.

1996-01-01

The article is a part of the international project 'Bulgaria Country Study to Address Climate Change Inventory of the Greenhouse Gases Emission and Sinks Alternative Energy Balance and Technology Programs' sponsored by the Department of Energy, US. The 'total' average annual wind resources in Bulgaria determined on the basis wind velocity density for more than 100 meteorological stations are estimated on 125 000 TWh. For the whole territory the theoretical wind power potential is about 14200 GW. The 'accessible' wind resources are estimated on about 62000 TWh. The 'reserve' (or usable) wind resources are determined using 8 velocity intervals for WECS (Wind Energy Conversion Systems) operation, number and disposition of turbines, and the usable (3%) part of the territory. The annual reserve resources are estimated at about 21 - 33 TWh. The 'economically beneficial' wind resources (EBWR) are those part of the reserve resources which could be included in the country energy balance using specific technologies in specific time period. It is foreseen that at year 2010 the EBWR could reach 0.028 TWh. 7 refs., 2 tabs., 1 fig

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

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)

Tatarko, John; Sporcic, Michael A.; Skidmore, Edward L.

2013-09-01

The Great Plains experienced an influx of settlers in the late 1850s-1900. Periodic drought was hard on both settlers and the soil and caused severe wind erosion. The period known as the Dirty Thirties, 1931-1939, produced many severe windstorms, and the resulting dusty sky over Washington, DC helped Hugh Hammond Bennett gain political support for the Soil Conservation Act of 1937 that started the USDA Soil Conservation Service (SCS). Austin W. Zingg and William S. Chepil began wind erosion studies at a USDA laboratory at Kansas State University in 1947. Neil P. Woodruff and Francis H. Siddoway published the first widely used model for wind erosion in 1965, called the Wind Erosion Equation (WEQ). The WEQ was solved using a series of charts and lookup tables. Subsequent improvements to WEQ included monthly magnitudes of the total wind, a computer version of WEQ programmed in FORTRAN, small-grain equivalents for range grasses, tillage systems, effects of residue management, crop row direction, cloddiness, monthly climate factors, and the weather. The SCS and the Natural Resources Conservation Service (NRCS) produced several computer versions of WEQ with the goal of standardizing and simplifying it for field personnel including a standalone version of WEQ was developed in the late 1990s using Microsoft Excel. Although WEQ was a great advancement to the science of prediction and control of wind erosion on cropland, it had many limitations that prevented its use on many lands throughout the United States and the world. In response to these limitations, the USDA developed a process-based model know as the Wind Erosion Prediction System (WEPS). The USDA Agricultural Research Service has taken the lead in developing science and technology for wind erosion prediction.

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.

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

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.

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.

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.

Wind power error estimation in resource assessments.

Directory of Open Access Journals (Sweden)

Osvaldo Rodríguez

Full Text Available 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.

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.

Satellite SAR wind resource mapping in China (SAR-China)

Energy Technology Data Exchange (ETDEWEB)

Badger, M.

2009-07-15

The project 'Off-Shore Wind Energy Resource Assessment and Feasibility Study of Off-Shore Wind Farm Development in China' is funded by the EU-China Energy and Environment Programme (EEP) and runs for one year (August 2008 - August 2009). The project is lead by the China Meteorological Administration (CMA) and supported by SgurrEnergy Ltd. Risoe National Laboratory for Sustainable Energy at the Technical University of Denmark (Risoe DTU) has been commissioned to perform a satellite based wind resource analysis as part of the project. The objective of this analysis is to map the wind resource offshore at a high spatial resolution (1 km). The detailed wind resource maps will be used, in combination with other data sets, for an assessment of potential sites for offshore wind farm development along the coastline from Fujian to Shandong in China. (au)

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.

Asynchrony of wind and hydropower resources in Australia

KAUST Repository

Gunturu, Udaya; Hallgren, Willow

2017-01-01

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.

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.

Computer modelling of the UK wind energy resource. Phase 2. Application of the methodology

Energy Technology Data Exchange (ETDEWEB)

Burch, S F; Makari, M; Newton, K; Ravenscroft, F; Whittaker, J

1993-12-31

This report presents the results of the second phase of a programme to estimate the UK wind energy resource. The overall objective of the programme is to provide quantitative resource estimates using a mesoscale (resolution about 1km) numerical model for the prediction of wind flow over complex terrain, in conjunction with digitised terrain data and wind data from surface meteorological stations. A network of suitable meteorological stations has been established and long term wind data obtained. Digitised terrain data for the whole UK were obtained, and wind flow modelling using the NOABL computer program has been performed. Maps of extractable wind power have been derived for various assumptions about wind turbine characteristics. Validation of the methodology indicates that the results are internally consistent, and in good agreement with available comparison data. Existing isovent maps, based on standard meteorological data which take no account of terrain effects, indicate that 10m annual mean wind speeds vary between about 4.5 and 7 m/s over the UK with only a few coastal areas over 6 m/s. The present study indicates that 28% of the UK land area had speeds over 6 m/s, with many hill sites having 10m speeds over 10 m/s. It is concluded that these `first order` resource estimates represent a substantial improvement over the presently available `zero order` estimates. The results will be useful for broad resource studies and initial site screening. Detailed resource evaluation for local sites will require more detailed local modelling or ideally long term field measurements. (12 figures, 14 tables, 21 references). (Author)

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...... on the characteristics of prediction errors for providing conditional interval forecasts. By simultaneously generating prediction intervals with various nominal coverage rates, one obtains full predictive distributions of wind generation. Adapted resampling is applied here to the case of an onshore Danish wind farm...... to the case of a large number of wind farms in Europe and Australia among others is finally discussed....

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

On the Predictability of Hub Height Winds

DEFF Research Database (Denmark)

Draxl, Caroline

Wind energy is a major source of power in over 70 countries across the world, and the worldwide share of wind energy in electricity consumption is growing. The introduction of signicant amounts of wind energy into power systems makes accurate wind forecasting a crucial element of modern electrical...... 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...... 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...

High-altitude wind resources in the Middle East

KAUST Repository

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

2017-01-01

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.

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.

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 atmospheri...

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.

Rooftop wind resource assessment using a three-dimensional ultrasonic anemometer

Energy Technology Data Exchange (ETDEWEB)

Anderson, D.C.; Whale, J.; Livingston, P.O.; Chan, D. [Murdoch Univ., Murdoch, WA (Australia)

2008-07-01

Building integrated wind turbines (BUWTs) are designed for the built environment and can be located on or next to buildings. In general, these types of urban wind turbines are less than 20 kW in rated capacity, and have the potential to contribute to the energy needs of the building and reduce overall emissions. There are currently over 32 manufacturers and 57 different urban wind turbine products available in Europe alone. The first rooftop wind system in Australia was installed in 2006. To data, 5 systems have been installed and there are plans for up to 20 more. The main problems associated with these types of systems are due to poor wind resources at the location or improper site selection for the turbine. This paper reported on a research study into initiating best practice guidelines for rooftop wind systems. There is a concern that environmentally conscious homeowners or businesses will install rooftop wind systems in support of sustainability, but without adequate consideration of safety, structural building integrity or turbine performance. The potential consequence of such projects could be the failure of the project due to underperforming turbines, noise, and vibration; or the development of a negative reputation for wind energy and the renewable energy industry. This study included 2 primary initiatives, notably a computer simulated modeling exercise and an onsite rooftop wind monitoring station. This paper focused on the methodology and justification for developing the monitoring station. An ultrasonic 3D anemometer was used to collect data and to develop a 3D wind profile. The wind regime on the rooftop in the complex terrain of the built environment was highly dynamic, turbulent, and included a strong vertical component. It was concluded that site selection for turbines must be determined by a proper feasibility study involving accurate data. Although the initial phase of the project to predict the resource and deploy the monitoring station has been

Wind Predictions Upstream Wind Turbines from a LiDAR Database

Directory of Open Access Journals (Sweden)

Soledad Le Clainche

2018-03-01

Full Text Available This article presents a new method to predict the wind velocity upstream a horizontal axis wind turbine from a set of light detection and ranging (LiDAR measurements. The method uses higher order dynamic mode decomposition (HODMD to construct a reduced order model (ROM that can be extrapolated in space. LiDAR measurements have been carried out upstream a wind turbine at six different planes perpendicular to the wind turbine axis. This new HODMD-based ROM predicts with high accuracy the wind velocity during a timespan of 24 h in a plane of measurements that is more than 225 m far away from the wind turbine. Moreover, the technique introduced is general and obtained with an almost negligible computational cost. This fact makes it possible to extend its application to both vertical axis wind turbines and real-time operation.

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.

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...

Where, when and how much wind is available? A provincial-scale wind resource assessment for China

International Nuclear Information System (INIS)

He, Gang; Kammen, Daniel M.

2014-01-01

China's wind installed capacity has grown at a remarkable rate, over 80% annually average growth since 2005, reaching 91.5 GW of capacity by end of 2013, accounting for over 27% of global capacity. This rapid growth has been the result of a domestic manufacturing base and favorable national policies. Further evolution will be greatly aided with a detailed wind resource assessment that incorporates spatial and temporal variability across China. We utilized 200 representative locations for which 10 years of hourly wind speed data exist to develop provincial capacity factors from 2001 to 2010, and to build analytic wind speed profiles. From these data and analysis we find that China's annual wind generation could reach 2000 TWh to 3500 TWh. Nationally this would correspond to an average capacity factor of 0.18. The diurnal and seasonal variation shows spring and winter has better wind resources than in the summer and fall. A highly interconnected and coordinated power system is needed to effectively exploit this large but variable resource. A full economic assessment of exploitable wind resources demands a larger, systems-level analysis of China's energy options, for which this work is a core requirement. - Highlights: • We assessed China's wind resources by utilizing 10 years of hourly wind speed data of 200 sites. • We built provincial scale wind speed profiles and develop provincial capacity factors for China. • We found that China's wind generation could reach 2000 TWh to 3500 TWh annually. • We observed similar temporal variation pattern of wind availability across China

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.

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...... grid spacings were performed for each of the two schemes. An evaluation of the wind profile using vertical profilers revealed small differences in modelled mean wind speed between the different set-ups, with the YSU scheme predicting slightly higher mean wind speeds. Larger differences between...... the different simulations were observed when comparing the root-mean-square error (RMSE) between modelled and measured wind, with the ERA interim-based simulations having the lowest errors. The simulations with finer horizontal grid spacing had a larger MSE. Horizontal transects of mean wind speed across...

Wind resource characterization in the Arabian Peninsula

KAUST Repository

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

2015-01-01

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

Planning and Development of Wind Farms: Wind Resource Assessment and Siting

DEFF Research Database (Denmark)

Mortensen, Niels Gylling

These course notes are intended for the three-week course 45700 Planning and Development of Wind Farms given at the Technical University of Denmark. The purpose of the course notes is to give an introduction to wind resource assessment and siting issues using the WAsP suite of programs....

Planning and Development of Wind Farms: Wind Resource Assessment and Siting

DEFF Research Database (Denmark)

Mortensen, Niels Gylling

These course notes are intended for the three-week course 46200 Planning and Development of Wind Farms given at the Technical University of Denmark. The purpose of the course notes is to give an introduction to wind resource assessment and siting issues using the WAsP suite of programs....

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)

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

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)

Improved Wind Speed Prediction Using Empirical Mode Decomposition

Directory of Open Access Journals (Sweden)

ZHANG, Y.

2018-05-01

Full Text Available Wind power industry plays an important role in promoting the development of low-carbon economic and energy transformation in the world. However, the randomness and volatility of wind speed series restrict the healthy development of the wind power industry. Accurate wind speed prediction is the key to realize the stability of wind power integration and to guarantee the safe operation of the power system. In this paper, combined with the Empirical Mode Decomposition (EMD, the Radial Basis Function Neural Network (RBF and the Least Square Support Vector Machine (SVM, an improved wind speed prediction model based on Empirical Mode Decomposition (EMD-RBF-LS-SVM is proposed. The prediction result indicates that compared with the traditional prediction model (RBF, LS-SVM, the EMD-RBF-LS-SVM model can weaken the random fluctuation to a certain extent and improve the short-term accuracy of wind speed prediction significantly. In a word, this research will significantly reduce the impact of wind power instability on the power grid, ensure the power grid supply and demand balance, reduce the operating costs in the grid-connected systems, and enhance the market competitiveness of the wind power.

Short-term wind power prediction

DEFF Research Database (Denmark)

Joensen, Alfred K.

2003-01-01

, 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......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...

The wind resource assessment program in Quebec Canada

Energy Technology Data Exchange (ETDEWEB)

Kahawita, R.; Bilodeau, L.; Gaudette, M.; Gratton, Y.; Noel, R.; Quach, T.T.

1982-09-01

This paper provides an overview of the wind resource assessment programme undertaken by the provincial power utility Hydro-Quebec, in Quebec, Canada. The methodology used in different phases of the project is enunciated and explained and the results discussed. Supplementary studies of airflow over complex terrain using numerical modelling are described and the results evaluated. Since the program is still far from completion, conclusive statements cannot, at this time, be made about the viability of the wind energy resource. However, tentative conclusions are that wind energy as an alternate source of energy for the province is likely to be commerciaally viable since two of the most important requirements viz, the presence of a good wind regime and the availability of suitable land are satisfied in many regions.

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

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...... 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...

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)

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...

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.

Wind resource assessment in heterogeneous terrain

Science.gov (United States)

Vanderwel, C.; Placidi, M.; Ganapathisubramani, B.

2017-03-01

High-resolution particle image velocimetry data obtained in rough-wall boundary layer experiments are re-analysed to examine the influence of surface roughness heterogeneities on wind resource. Two different types of heterogeneities are examined: (i) surfaces with repeating roughness units of the order of the boundary layer thickness (Placidi & Ganapathisubramani. 2015 J. Fluid Mech. 782, 541-566. (doi:10.1017/jfm.2015.552)) and (ii) surfaces with streamwise-aligned elevated strips that mimic adjacent hills and valleys (Vanderwel & Ganapathisubramani. 2015 J. Fluid Mech. 774, 1-12. (doi:10.1017/jfm.2015.228)). For the first case, the data show that the power extraction potential is highly dependent on the surface morphology with a variation of up to 20% in the available wind resource across the different surfaces examined. A strong correlation is shown to exist between the frontal and plan solidities of the rough surfaces and the equivalent wind speed, and hence the wind resource potential. These differences are also found in profiles of graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="RSTA20160109IM1"/> and graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="RSTA20160109IM2"/> (where U is the streamwise velocity), which act as proxies for thrust and power output. For the second case, the secondary flows that cause low- and high-momentum pathways when the spacing between adjacent hills is beyond a critical value result in significant variations in wind resource availability. Contour maps of graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="RSTA20160109IM3"/> and graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="RSTA20160109IM4"/> show a large difference in thrust and power potential (over 50%) between hills and valleys (at a fixed vertical height). These variations do not seem to be present when adjacent hills are close to each other (i.e. when the spacing is much less than the boundary layer thickness). The

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...... and predictive inferences under different reasonable choices of prior distribution in sensitivity analysis have been presented....

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.

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

Could Crop Height Affect the Wind Resource at Agriculturally Productive Wind Farm Sites?

Science.gov (United States)

Vanderwende, Brian; Lundquist, Julie K.

2016-03-01

The collocation of cropland and wind turbines in the US Midwest region introduces complex meteorological interactions that could influence both agriculture and wind-power production. Crop management practices may affect the wind resource through alterations of land-surface properties. We use the weather research and forecasting (WRF) model to estimate the impact of crop height variations on the wind resource in the presence of a large turbine array. A hypothetical wind farm consisting of 121 1.8-MW turbines is represented using the WRF model wind-farm parametrization. We represent the impact of selecting soybeans rather than maize by altering the aerodynamic roughness length in a region approximately 65 times larger than that occupied by the turbine array. Roughness lengths of 0.1 and 0.25 m represent the mature soy crop and a mature maize crop, respectively. In all but the most stable atmospheric conditions, statistically significant hub-height wind-speed increases and rotor-layer wind-shear reductions result from switching from maize to soybeans. Based on simulations for the entire month of August 2013, wind-farm energy output increases by 14 %, which would yield a significant monetary gain. Further investigation is required to determine the optimal size, shape, and crop height of the roughness modification to maximize the economic benefit and minimize the cost of such crop-management practices. These considerations must be balanced by other influences on crop choice such as soil requirements and commodity prices.

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.

Hourly Wind Speed Interval Prediction in Arid Regions

Science.gov (United States)

Chaouch, M.; Ouarda, T.

2013-12-01

The long and extended warm and dry summers, the low rate of rain and humidity are the main factors that explain the increase of electricity consumption in hot arid regions. In such regions, the ventilating and air-conditioning installations, that are typically the most energy-intensive among energy consumption activities, are essential for securing healthy, safe and suitable indoor thermal conditions for building occupants and stored materials. The use of renewable energy resources such as solar and wind represents one of the most relevant solutions to overcome the increase of the electricity demand challenge. In the recent years, wind energy is gaining more importance among the researchers worldwide. Wind energy is intermittent in nature and hence the power system scheduling and dynamic control of wind turbine requires an estimate of wind energy. Accurate forecast of wind speed is a challenging task for the wind energy research field. In fact, due to the large variability of wind speed caused by the unpredictable and dynamic nature of the earth's atmosphere, there are many fluctuations in wind power production. This inherent variability of wind speed is the main cause of the uncertainty observed in wind power generation. Furthermore, producing wind power forecasts might be obtained indirectly by modeling the wind speed series and then transforming the forecasts through a power curve. Wind speed forecasting techniques have received substantial attention recently and several models have been developed. Basically two main approaches have been proposed in the literature: (1) physical models such as Numerical Weather Forecast and (2) statistical models such as Autoregressive integrated moving average (ARIMA) models, Neural Networks. While the initial focus in the literature has been on point forecasts, the need to quantify forecast uncertainty and communicate the risk of extreme ramp events has led to an interest in producing probabilistic forecasts. In short term

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)

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 rotatio...... predictive controller are presented. Statistical comparison between frequency weighted MPC, standard MPC and baseline PI controller is shown as well.......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...

Remapping of the Wind Energy Resource in the Midwestern United States: Preprint

International Nuclear Information System (INIS)

Schwartz, M.; Elliot, D.

2001-01-01

A recent increase in interest and development of wind energy in the Midwestern United States has focused the need for updating wind resource maps of this area. The wind resource assessment group at the National Renewable Energy Lab., a U.S. Department of Energy (DOE) laboratory, has produced updated high-resolution (1-km) wind resource maps for several states in this region. This abstract describes the computerized tools and methodology used by NREL to create the higher resolution maps

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

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.

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

Wind Energy Resource Atlas. Volume 11. Hawaii and Pacific Islands Region

Energy Technology Data Exchange (ETDEWEB)

Schroeder, T.A.; Hori, A.M.; Elliott, D.L.; Barchet, W.R.; George, R.L.

1981-02-01

This atlas of the wind energy resource is composed of introductory and background information, and assessments of the wind resource in each division of the region. Background on how the wind resource is assessed and on how the results of the assessment should be inerpreted is presented. An introduction and outline to the descriptions of the wind resource for each division are provided. Assessments for individual divisions are presented as separate chapters. Much of the information in the division chapters is given in graphic or tabular form. The sequences for each chapter are similar, but some presentations used for Hawaii are inappropriate or impractical for presentation with the Pacific Islands. Hawaii chapter figure and tables are cited below and appropriate Pacific Islands figure and table numbers are included in brackets ().

Wind resource assessment using the WAsP software (DTU Wind Energy E-0135)

DEFF Research Database (Denmark)

Mortensen, Niels Gylling

These course notes are intended for the three-week course 46200 Planning and Development of Wind Farms given each year at the Technical University of Denmark. The purpose of the course notes is to give an introduction to wind resource assessment and siting issues using the WAsP suite of programs....

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.

The wind power prediction research based on mind evolutionary algorithm

Science.gov (United States)

Zhuang, Ling; Zhao, Xinjian; Ji, Tianming; Miao, Jingwen; Cui, Haina

2018-04-01

When the wind power is connected to the power grid, its characteristics of fluctuation, intermittent and randomness will affect the stability of the power system. The wind power prediction can guarantee the power quality and reduce the operating cost of power system. There were some limitations in several traditional wind power prediction methods. On the basis, the wind power prediction method based on Mind Evolutionary Algorithm (MEA) is put forward and a prediction model is provided. The experimental results demonstrate that MEA performs efficiently in term of the wind power prediction. The MEA method has broad prospect of engineering application.

Satellite based wind resource assessment over the South China Sea

DEFF Research Database (Denmark)

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

2014-01-01

variations are clearly visible across the domain; for instance sheltering effects caused by the land masses. The satellite based wind resource maps have two shortcomings. One is the lack of information at the higher vertical levels where wind turbines operate. The other is the limited number of overlapping...... 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...

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.

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...

Analysis of the solar/wind resources in Southern Spain for optimal sizing of hybrid solar-wind power generation systems

Science.gov (United States)

Quesada-Ruiz, S.; Pozo-Vazquez, D.; Santos-Alamillos, F. J.; Lara-Fanego, V.; Ruiz-Arias, J. A.; Tovar-Pescador, J.

2010-09-01

A drawback common to the solar and wind energy systems is their unpredictable nature and dependence on weather and climate on a wide range of time scales. In addition, the variation of the energy output may not match with the time distribution of the load demand. This can partially be solved by the use of batteries for energy storage in stand-alone systems. The problem caused by the variable nature of the solar and wind resources can be partially overcome by the use of energy systems that uses both renewable resources in a combined manner, that is, hybrid wind-solar systems. Since both resources can show complementary characteristics in certain location, the independent use of solar or wind systems results in considerable over sizing of the batteries system compared to the use of hybrid solar-wind systems. Nevertheless, to the day, there is no single recognized method for properly sizing these hybrid wind-solar systems. In this work, we present a method for sizing wind-solar hybrid systems in southern Spain. The method is based on the analysis of the wind and solar resources on daily scale, particularly, its temporal complementary characteristics. The method aims to minimize the size of the energy storage systems, trying to provide the most reliable supply.

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)

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

The value of co-locating energy storage with wind resources

Energy Technology Data Exchange (ETDEWEB)

Fox, C. [Victoria Univ., BC (Canada). Inst. for Integrated Energy Systems

2010-07-01

This PowerPoint presentation discussed the value of wind energy storage systems. The systems can be used to downsize transmission requirements and to minimize reliability and forecast uncertainty. Revenue factors in relation to wind power energy storage are determined by the amount of wind power produced each hour with the wind farm capacity and hourly electricity price. Case studies of a wind farm in Ontario over a period of 20 years were used to determine capacity and revenue factors as well as gross revenues. The maximum revenue factor was determined by multiplying the greatest wind energy output by the highest electricity prices. A hybrid wind farm energy storage system was designed to determine energy storage discharges and charges to and from the grid at pool prices. The method allowed for time-shifts in wind generation resources and downsized transmission requirements for remote resources. The mixed integer linear program model co-optimized revenues from the wind farm and the energy storage facility. Combined output was constrained to the transmission capacity. Transmission losses were neglected, and capital costs were considered. Future studies are needed to determine levelized electricity costs under different load growth scenarios. tabs., figs.

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.

Analysis of the balancing of the wind and solar energy resources in Andalusia (Southern Spain)

Science.gov (United States)

Santos-Alamillos, F. J.; Pozo-Vazquez, D.; Lara-Fanego, V.; Ruiz-Arias, J. A.; Hernandez-Alvaro, J.; Tova-Pescador, J.

2010-09-01

A higher penetration of the renewable energy in the electric system in the future will be conditioned to a reduction of the uncertainty of the yield. A way to obtain this goal is to analyze the balancing between the productions of different sources of renewable energy, trying to combine these productions. In this work we analyze, from a meteorological point of view, the balancing between wind and solar energy resources in Andalusia (southern Iberian Peninsula). To this end, wind speed and global radiation data corresponding to an one year integration of the Weather Research and Forecasting (WRF) Numerical Weather Prediction (NWP) model were analyzed. Two method of analysis were used: a point correlation analysis and a Canonical Correlation Analysis (CCA). Results from these analyses allow obtaining, eventually, areas of local and distributed balancing between the wind and solar energy resources. The analysis was carried out separately for the different seasons of the year. Results showed, overall, a considerable balancing effect between the wind and solar resources in the mountain areas of the interior of the region, along the coast of the central part of the region and, specially, in the coastal area near the Gibraltar strait. Nevertheless, considerable differences were found between the seasons of the year, which may lead to compensating effects. Autumn proved to be the season with the most significant results.

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.

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

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

DEFF Research Database (Denmark)

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

for the standard output level of 10 m above the sea surface. This presentation demonstrates the effects of two recent improvements related to satellite-based wind resource mapping: 1) The number of satellite samples has increased dramatically since the launch of Sentinel-1A/B 2) A new method looks promising...... National Ice Center. Once the instantaneous wind maps are stored in our database, they can be organized as time series in order to calculate wind resources for any point location or area. Since the time series comprises data from both Envisat and Sentinel-1, a check of the data calibration against one....... To extrapolate the 10-m wind resource maps from SAR to higher levels within the atmospheric boundary layer, we estimate a wind profile for each grid cell in the maps. Simulations from the Weather Research and Forecasting (WRF) model are used to correct this profile for long-term atmospheric stability effects...

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.

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 a...... 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.......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...

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 ...

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.

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.

Statistical downscaling of historical monthly mean winds over a coastal region of complex terrain. II. Predicting wind components

Energy Technology Data Exchange (ETDEWEB)

Kamp, Derek van der [University of Victoria, Pacific Climate Impacts Consortium, Victoria, BC (Canada); University of Victoria, School of Earth and Ocean Sciences, Victoria, BC (Canada); Curry, Charles L. [Environment Canada University of Victoria, Canadian Centre for Climate Modelling and Analysis, Victoria, BC (Canada); University of Victoria, School of Earth and Ocean Sciences, Victoria, BC (Canada); Monahan, Adam H. [University of Victoria, School of Earth and Ocean Sciences, Victoria, BC (Canada)

2012-04-15

A regression-based downscaling technique was applied to monthly mean surface wind observations from stations throughout western Canada as well as from buoys in the Northeast Pacific Ocean over the period 1979-2006. A predictor set was developed from principal component analysis of the three wind components at 500 hPa and mean sea-level pressure taken from the NCEP Reanalysis II. Building on the results of a companion paper, Curry et al. (Clim Dyn 2011), the downscaling was applied to both wind speed and wind components, in an effort to evaluate the utility of each type of predictand. Cross-validated prediction skill varied strongly with season, with autumn and summer displaying the highest and lowest skill, respectively. In most cases wind components were predicted with better skill than wind speeds. The predictive ability of wind components was found to be strongly related to their orientation. Wind components with the best predictions were often oriented along topographically significant features such as constricted valleys, mountain ranges or ocean channels. This influence of directionality on predictive ability is most prominent during autumn and winter at inland sites with complex topography. Stations in regions with relatively flat terrain (where topographic steering is minimal) exhibit inter-station consistencies including region-wide seasonal shifts in the direction of the best predicted wind component. The conclusion that wind components can be skillfully predicted only over a limited range of directions at most stations limits the scope of statistically downscaled wind speed predictions. It seems likely that such limitations apply to other regions of complex terrain as well. (orig.)

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.

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.

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.

Wind power in Eritrea, Africa: A preliminary resource assessment

Energy Technology Data Exchange (ETDEWEB)

Garbesi, K.; Rosen, K. [San Jose State Univ., CA (United States); Van Buskirk, R. [Dept. of Energy, Eritrea (Ethiopia)

1997-12-31

The authors preliminary assessment of Eritrean wind energy potential identified two promising regions: (1) the southeastern Red Sea coast and (2) the mountain passes that channel winds between the coastal lowlands and the interior highlands. The coastal site, near the port city of Aseb, has an exceptionally good resource, with estimated average annual wind speeds at 10-m height above 9 m/s at the airport and 7 m/s in the port. Furthermore, the southern 200 km of coastline has offshore WS{sub aa} > 6 m/s. This area has strong potential for development, having a local 20 MW grid and unmet demand for the fishing industry and development. Although the highland sites contain only marginal wind resources ({approximately} 5 m/s), they warrant further investigation because of their proximity to the capital city, Asmera, which has the largest unmet demand and a larger power grid (40 MW with an additional 80 MW planned) to absorb an intermittent source without storage.

Development of Regional Wind Resource and Wind Plant Output Datasets for the Hawaiian Islands

Energy Technology Data Exchange (ETDEWEB)

Manobianco, J.; Alonge, C.; Frank, J.; Brower, M.

2010-07-01

In March 2009, AWS Truepower was engaged by the National Renewable Energy Laboratory (NREL) to develop a set of wind resource and plant output data for the Hawaiian Islands. The objective of this project was to expand the methods and techniques employed in the Eastern Wind Integration and Transmission Study (EWITS) to include the state of Hawaii.

A model to predict the power output from wind farms

Energy Technology Data Exchange (ETDEWEB)

Landberg, L. [Riso National Lab., Roskilde (Denmark)

1997-12-31

This paper will describe a model that can predict the power output from wind farms. To give examples of input the model is applied to a wind farm in Texas. The predictions are generated from forecasts from the NGM model of NCEP. These predictions are made valid at individual sites (wind farms) by applying a matrix calculated by the sub-models of WASP (Wind Atlas Application and Analysis Program). The actual wind farm production is calculated using the Riso PARK model. Because of the preliminary nature of the results, they will not be given. However, similar results from Europe will be given.

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

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

Satellite SAR wind resource mapping in China (SAR-China)

DEFF Research Database (Denmark)

Badger, Merete

The project ‘Off-Shore Wind Energy Resource Assessment and Feasibility Study of Off-Shore Wind Farm Development in China’ is funded by the EU-China Energy and Environment Programme (EEP) and runs for one year (August 2008 - August 2009). The project is lead by the China Meteorological Administrat...

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.

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

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.

46200 Planning and Development of Wind Farms: Wind resource assessment using the WAsP software

DEFF Research Database (Denmark)

Mortensen, Niels Gylling

These course notes are intended for the three-week course 46200 Planning and Development of Wind Farms given each year at the Technical University of Denmark. The purpose of the course notes is to give an introduction to wind resource assessment and siting issues using the WAsP suite of programs....

Wind power prediction based on genetic neural network

Science.gov (United States)

Zhang, Suhan

2017-04-01

The scale of grid connected wind farms keeps increasing. To ensure the stability of power system operation, make a reasonable scheduling scheme and improve the competitiveness of wind farm in the electricity generation market, it's important to accurately forecast the short-term wind power. To reduce the influence of the nonlinear relationship between the disturbance factor and the wind power, the improved prediction model based on genetic algorithm and neural network method is established. To overcome the shortcomings of long training time of BP neural network and easy to fall into local minimum and improve the accuracy of the neural network, genetic algorithm is adopted to optimize the parameters and topology of neural network. The historical data is used as input to predict short-term wind power. The effectiveness and feasibility of the method is verified by the actual data of a certain wind farm as an example.

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.

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.

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.

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

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.

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.

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)

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.......-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...

Ultra-Short-Term Wind Power Prediction Using a Hybrid Model

Science.gov (United States)

Mohammed, E.; Wang, S.; Yu, J.

2017-05-01

This paper aims to develop and apply a hybrid model of two data analytical methods, multiple linear regressions and least square (MLR&LS), for ultra-short-term wind power prediction (WPP), for example taking, Northeast China electricity demand. The data was obtained from the historical records of wind power from an offshore region, and from a wind farm of the wind power plant in the areas. The WPP achieved in two stages: first, the ratios of wind power were forecasted using the proposed hybrid method, and then the transformation of these ratios of wind power to obtain forecasted values. The hybrid model combines the persistence methods, MLR and LS. The proposed method included two prediction types, multi-point prediction and single-point prediction. WPP is tested by applying different models such as autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN). By comparing results of the above models, the validity of the proposed hybrid model is confirmed in terms of error and correlation coefficient. Comparison of results confirmed that the proposed method works effectively. Additional, forecasting errors were also computed and compared, to improve understanding of how to depict highly variable WPP and the correlations between actual and predicted wind power.

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...... the full probabilistic distribution of maximum wind speed. Knowledge of the maximum wind speed for an offshore location within a given period can inform decision-making regarding turbine operations, planned maintenance operations and power grid scheduling in order to improve safety and reliability...

Wind Resource Variations Over Selected Sites in the West African Sub-Region

International Nuclear Information System (INIS)

Iheonu, E. E.; Akingbade, F.O A.; Ocholi, M.

2002-01-01

The analysis of wind characteristics and wind resource potentials at 4 locations in the West African sub-region is presented, applying data obtained at the Ibadan central station of the International Institute of Tropical Agriculture (IITA-Ibadan, Nigeria). The study has shown that the annual variations of wind speed have coefficient of variability between 10 and 15% but the available wind power at the studied locations is generally poor with values ranging between 2 and 10 Wm2 at the standard meteorological height of 10 m. Cotonou (Lat. 6.4 0 N, Long. 2.3 0 E) Benin Republic has however been distinguished from the other three locations in Nigeria, as the most promising site for wind resource development and utilization in the sub-region. With appropriate choice of wind turbine characteristics and design efficiency, establishing wind farms at the Cotonou location for electrical energy production could be feasible

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

prediction. As a consequence, individual pitch feed-forward control action is generated by the controller, taking ”future” wind disturbance into account. Information about the estimated wind spatial distribution one blade experience can be used in the prediction model to better control the next passing blade......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...

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.

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

In wind farms, individual turbines disturb the wind field by generating wakes that influence other turbines in the farm. From a control point of view, there is an interest in dynamic optimization of the balance between fatigue and production, and an understanding of the relationship between turbines...... 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...... on the result related to effective wind speed, it is possible to predict wind speeds at neighboring turbines, with a separation of over 700 m, up to 1 min ahead reducing the error by 30% compared with a persistence method. The methodological results are demonstrated on data from an off-shore wind farm...

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.

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.

Global assessment of onshore wind power resources considering the distance to urban areas

International Nuclear Information System (INIS)

Silva Herran, Diego; Dai, Hancheng; Fujimori, Shinichiro; Masui, Toshihiko

2016-01-01

This study assessed global onshore wind power resources considering the distance to urban areas in terms of transmission losses and costs, and visibility (landscape impact) restrictions. Including this factor decreased the economic potential considerably depending on the level of supply cost considered (at least 37% and 16% for an economic potential below 10 and 14 US cents/kWh, respectively). Its importance compared to other factors was secondary below 15 US cents/kWh. At higher costs it was secondary only to land use, and was more important than economic and technical factors. The impact of this factor was mixed across all regions of the world, given the heterogeneity of wind resources in remote and proximal areas. Regions where available resources decreased the most included the European Union, Japan, Southeast Asia, the Middle East, and Africa. The supply cost chosen to evaluate the economic potential and uncertainties influencing the estimation of distance to the closest urban area are critical for the assessment. Neglecting the restrictions associated with integration into energy systems and social acceptability resulted in an overestimation of global onshore wind resources. These outcomes are fundamental for global climate policies because they help to clarify the limits of wind energy resource availability. - Highlights: • Global onshore wind resources were assessed including the distance to urban areas. • We evaluate the impact of transmission losses and cost, and visibility restrictions. • The distance to urban areas' impact was considerable, depending on the supply cost. • This factor's importance was secondary to economic, land use, and technical factors. • Neglecting this factor resulted in an overestimation of global wind resources.

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....

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

Science.gov (United States)

2011-06-22

... Renewables, Inc., PacifiCorp, NextEra Energy Resources, LLC, Invenergy Wind North America LLC, Horizon Wind...), Iberdrola Renewables, Inc., PacifiCorp, NextEra Energy Resources, LLC, Invenergy Wind North America LLC, and Horizon Wind Energy LLC (Complainants) filed a formal complaint against Bonneville Power Administration...

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

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...

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.

Robust Model Predictive Control of a Wind Turbine

DEFF Research Database (Denmark)

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

2012-01-01

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...... of the uncertain system is employed and a norm-bounded uncertainty model is used to formulate a minimax model predictive control. The resulting optimization problem is simplified by semidefinite relaxation and the controller obtained is applied on a full complexity, high fidelity wind turbine model. Finally...... 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...

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

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.

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)

Error analysis of short term wind power prediction models

Energy Technology Data Exchange (ETDEWEB)

De Giorgi, Maria Grazia; Ficarella, Antonio; Tarantino, Marco [Dipartimento di Ingegneria dell' Innovazione, Universita del Salento, Via per Monteroni, 73100 Lecce (Italy)

2011-04-15

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)

Short-term prediction method of wind speed series based on fractal interpolation

International Nuclear Information System (INIS)

Xiu, Chunbo; Wang, Tiantian; Tian, Meng; Li, Yanqing; Cheng, Yi

2014-01-01

Highlights: • An improved fractal interpolation prediction method is proposed. • The chaos optimization algorithm is used to obtain the iterated function system. • The fractal extrapolate interpolation prediction of wind speed series is performed. - Abstract: In order to improve the prediction performance of the wind speed series, the rescaled range analysis is used to analyze the fractal characteristics of the wind speed series. An improved fractal interpolation prediction method is proposed to predict the wind speed series whose Hurst exponents are close to 1. An optimization function which is composed of the interpolation error and the constraint items of the vertical scaling factors in the fractal interpolation iterated function system is designed. The chaos optimization algorithm is used to optimize the function to resolve the optimal vertical scaling factors. According to the self-similarity characteristic and the scale invariance, the fractal extrapolate interpolation prediction can be performed by extending the fractal characteristic from internal interval to external interval. Simulation results show that the fractal interpolation prediction method can get better prediction result than others for the wind speed series with the fractal characteristic, and the prediction performance of the proposed method can be improved further because the fractal characteristic of its iterated function system is similar to that of the predicted wind speed series

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.

A study on the survey of wind energy resources for potential areas

Energy Technology Data Exchange (ETDEWEB)

Park, Kyung Ho; Kim, Keon Hoon; Yoo, Seung Won; Choi, Chang Joon; Ahn, Jung Jong [Korea Inst. of Energy Research, Taejon (Korea, Republic of)

1995-12-01

Among the wind energy utilization projects, the siting work for wind turbine installation is one of the most important procedure because the wind energy distribution is very different regionally and wind energy density influences greatly to the feasibility of wind energy utilization. So, the potential sites of wind generating in our country must be surveyed and analyzed the feasibility of wind energy utilization. In addition to this, the technique of wind energy prediction considered of the topography, surface roughness and obstacle condition must be established for the reliable analysis of wind energy utilization. The contents carried out in this project are shown below, 1. Determining of the measuring sites of wind data - Wyoulryung-ri, Youngrag-ri, Gapa-ri in Cheju Province - Heul-ri, Gangwon Province. 2. Analysis of wind energy at measuring sites The characteristics of wind energy at the measured sites were analysed. It will be continued to measure the wind data by wind data logger. 3. A study on wind energy prediction technique It was studied how to obtain the topographic map data for using WAsP(WIndAtlas Analysis and Application Program). (author). 21 refs., 59 figs., 19 tabs.

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.

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.

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)

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.

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.

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.

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

SAR-Based Wind Resource Statistics in the Baltic Sea

Directory of Open Access Journals (Sweden)

Alfredo Peña

2011-01-01

Full Text Available Ocean winds in the Baltic Sea are expected to power many wind farms in the coming years. This study examines satellite Synthetic Aperture Radar (SAR images from Envisat ASAR for mapping wind resources with high spatial resolution. Around 900 collocated pairs of wind speed from SAR wind maps 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 show wind power density values to range from 300 to 800 W m−2 for the 14 existing and 42 planned wind farms.

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)

Evaluation of the climate change impact on wind resources in Taiwan Strait

International Nuclear Information System (INIS)

Chang, Tsang-Jung; Chen, Chun-Lung; Tu, Yi-Long; Yeh, Hung-Te; Wu, Yu-Ting

2015-01-01

Highlights: • We propose a new statistical downscaling framework to evaluate the climate change impact on wind resources in Taiwan Strait. • The statistical model relates Weibull distribution parameters to output of a GCM model and regression coefficients. • Validation of the simulated wind speed distribution presents an acceptable agreement with meteorological data. • Three chosen GCMs show the same tendency that the eastern half of Taiwan Strait stores higher wind resources. - Abstract: A new statistical downscaling framework is proposed to evaluate the climate change impact on wind resources in Taiwan Strait. In this framework, a two-parameter Weibull distribution function is used to estimate the wind energy density distribution in the strait. An empirically statistical downscaling model that relates the Weibull parameters to output of a General Circulation Model (GCM) and regression coefficients is adopted. The regression coefficients are calculated using wind speed results obtained from a past climate (1981–2000) simulation reconstructed by a Weather Research and Forecasting (WRF) model. These WRF-reconstructed wind speed results are validated with data collected at a weather station on an islet inside the strait. The comparison shows that the probability distributions of the monthly wind speeds obtained from WRF-reconstructed and measured wind speed data are in acceptable agreement, with small discrepancies of 10.3% and 7.9% for the shape and scale parameters of the Weibull distribution, respectively. The statistical downscaling framework with output from three chosen GCMs (i.e., ECHAM5, CM2.1 and CGCM2.3.2) is applied to evaluate the wind energy density distribution in Taiwan Strait for three future climate periods of 2011–2040, 2041–2070, and 2071–2100. The results show that the wind energy density distributions in the future climate periods are higher in the eastern half of Taiwan Strait, but reduce slightly by 3% compared with that in the

WPPT, a tool for on-line wind power prediction

Energy Technology Data Exchange (ETDEWEB)

Skov Nielsen, T. [Dept. of Mathematical Modelling (IMM-DTU), Kgs. Lyngby (Denmark); Madsen, H. [Dept. of Mathematical Modelling (IMM-DTU) Kgs. Lyngby (Denmark); Toefting, J. [Elsam, Fredericia (Denmark)

2004-07-01

This paper dsecribes VPPT (Wind Power Prediction Tool), an application for assessing the future available wind power up to 36 hours ahead in time. WPPT has been installed in the Eltra/Elsam central dispatch center since October 1997. The paper describes the prediction model used, the actual implementation of WPPT as well as the experience gained by the operators in the dispatch center (au)

Evaluation of offshore wind resources by scale of development

DEFF Research Database (Denmark)

Möller, Bernd; Hong, Lixuan; Lonsing, Reinhard

-economic model operating in a geographical information systems (GIS) environment, which describes resources, costs and area constraints in a spatially explicit way, the relation between project size, location, costs and ownership is analysed. Two scenarios are presented, which describe a state......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, have...... 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...

Evaluation of offshore wind resources by scale of development

DEFF Research Database (Denmark)

Möller, Bernd; Hong, Lixuan; Lonsing, Reinhard

2012-01-01

-economic model operating in a geographical information systems (GIS) environment, which describes resources, costs and area constraints in a spatially explicit way, the relation between project size, location, costs and ownership is analysed. Two scenarios are presented, which describe a state......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, have...... 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...

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...

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

Development of a methodology to assess the climate evolution and its impacts on wind energy

Energy Technology Data Exchange (ETDEWEB)

Simard, I. [Moncton Univ., NB (Canada); Yu, W. [Moncton Univ., NB (Canada). Meteorological Research Div.; Gagnon, Y. [Moncton Univ., NB (Canada). K.C. Irving Chair in Sustainable Development

2010-07-01

Maps of wind resources were used to develop a method of evaluating climatic changes and their potential impacts on wind energy resources. Global IPCC climate change scenarios were used to predict climatic conditions for the future, while past wind resource availability was simulated and validated using NCEP and NCAR reanalysis data as well as observed meteorological data from Environment Canada. The simulations were used to compare each 5-year period with a 50-year reference period. Regional scale climate change impacts were evaluated using a statistical dynamic down-scaling method. Advanced meteorological models were used to predict wind flow patterns across specific landscapes. The evolution of past wind resource availability was then simulated. Five-year wind resource simulations for a 50-year period were simulated at 25 km{sup 2} wind speeds at 80 m above the ground. Average wind speed variations were then evaluated. The method has been used to simulate 5-year periods within a 50-year reference period in New Brunswick. Further studies will be conducted to simulate future wind resources availability. tabs., figs.

Using Wind Tunnels to Predict Bird Mortality in Wind Farms: The Case of Griffon Vultures

OpenAIRE

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

2012-01-01

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 topo...

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

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

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......Lowering the cost of energy is one of the major focus areas in the wind turbine industry. Recent research has indicated that wind turbine controllers based on model predictive control methods can be useful in obtaining this objective. A number of design considerations have to be made when designing....... 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...

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

DEFF Research Database (Denmark)

Baxevani, Anastassia; Lenzi, Amanda

2018-01-01

Wind power is a renewable energy resource, that has relatively cheap installation costs and it is highly possible that will become the main energy resource in the near future. Wind power needs to be integrated efficiently into electricity grids, and to optimize the power dispatch, techniques...

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

Model Predictive Control of Wind Turbines using Uncertain LIDAR Measurements

DEFF Research Database (Denmark)

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

2013-01-01

, 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......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...... on wind speed estimation and measurements from the LIDAR is devised to find an estimate of the delay and compensate for it before it is used in the controller. Comparisons between the MPC with error compensation, the MPC without error compensation and an MPC with re-linearization at each sample point...

Prediction and analysis of infra and low-frequency noise of upwind horizontal axis wind turbine using statistical wind speed model

Energy Technology Data Exchange (ETDEWEB)

Lee, Gwang-Se; Cheong, Cheolung, E-mail: ccheong@pusan.ac.kr [School of Mechanical Engineering, Pusan National University, Busan, 609-745, Rep. of Korea (Korea, Republic of)

2014-12-15

Despite increasing concern about low-frequency noise of modern large horizontal-axis wind turbines (HAWTs), few studies have focused on its origin or its prediction methods. In this paper, infra- and low-frequency (the ILF) wind turbine noise are closely examined and an efficient method is developed for its prediction. Although most previous studies have assumed that the ILF noise consists primarily of blade passing frequency (BPF) noise components, these tonal noise components are seldom identified in the measured noise spectrum, except for the case of downwind wind turbines. In reality, since modern HAWTs are very large, during rotation, a single blade of the turbine experiences inflow with variation in wind speed in time as well as in space, breaking periodic perturbations of the BPF. Consequently, this transforms acoustic contributions at the BPF harmonics into broadband noise components. In this study, the ILF noise of wind turbines is predicted by combining Lowson’s acoustic analogy with the stochastic wind model, which is employed to reproduce realistic wind speed conditions. In order to predict the effects of these wind conditions on pressure variation on the blade surface, unsteadiness in the incident wind speed is incorporated into the XFOIL code by varying incident flow velocities on each blade section, which depend on the azimuthal locations of the rotating blade. The calculated surface pressure distribution is subsequently used to predict acoustic pressure at an observing location by using Lowson’s analogy. These predictions are compared with measured data, which ensures that the present method can reproduce the broadband characteristics of the measured low-frequency noise spectrum. Further investigations are carried out to characterize the IFL noise in terms of pressure loading on blade surface, narrow-band noise spectrum and noise maps around the turbine.

Prediction and analysis of infra and low-frequency noise of upwind horizontal axis wind turbine using statistical wind speed model

Directory of Open Access Journals (Sweden)

Gwang-Se Lee

2014-12-01

Full Text Available Despite increasing concern about low-frequency noise of modern large horizontal-axis wind turbines (HAWTs, few studies have focused on its origin or its prediction methods. In this paper, infra- and low-frequency (the ILF wind turbine noise are closely examined and an efficient method is developed for its prediction. Although most previous studies have assumed that the ILF noise consists primarily of blade passing frequency (BPF noise components, these tonal noise components are seldom identified in the measured noise spectrum, except for the case of downwind wind turbines. In reality, since modern HAWTs are very large, during rotation, a single blade of the turbine experiences inflow with variation in wind speed in time as well as in space, breaking periodic perturbations of the BPF. Consequently, this transforms acoustic contributions at the BPF harmonics into broadband noise components. In this study, the ILF noise of wind turbines is predicted by combining Lowson’s acoustic analogy with the stochastic wind model, which is employed to reproduce realistic wind speed conditions. In order to predict the effects of these wind conditions on pressure variation on the blade surface, unsteadiness in the incident wind speed is incorporated into the XFOIL code by varying incident flow velocities on each blade section, which depend on the azimuthal locations of the rotating blade. The calculated surface pressure distribution is subsequently used to predict acoustic pressure at an observing location by using Lowson’s analogy. These predictions are compared with measured data, which ensures that the present method can reproduce the broadband characteristics of the measured low-frequency noise spectrum. Further investigations are carried out to characterize the IFL noise in terms of pressure loading on blade surface, narrow-band noise spectrum and noise maps around the turbine.

Analysis of available wind resources and their suitability for hydrogen production in the Sacramento area

International Nuclear Information System (INIS)

Bartholomy, O.J.

2004-01-01

This paper looks at the technical, economic, environmental and regulatory barriers to the production of hydrogen from local wind resources in Sacramento, CA. Both central and distributed hydrogen generation are compared. The technical analysis uses 6 years of hourly wind data from Solano County to define the diurnal and seasonal wind resource. The impacts of a fluctuating power source on the electrolyzer are examined as well as the grid or hydrogen distribution and storage infrastructure constraints for implementation. An economic analysis comparing the price of hydrogen produced from the local wind resource is done with sensitivity analyses for capital and operating costs of both wind turbines and electrolyzers. In addition, the economic analysis includes considerations of increased demand for wind electricity by California utilities attempting to meet their Renewable Portfolio Standards. The environmental analysis compares the emissions reductions of CO 2 and criteria pollutants for different energy usage scenarios. These include comparing electricity and transportation emissions rates to optimize the use of wind energy and natural gas, as well as comparison of SULEV hybrid vehicles with FCV's and H 2 ICE's. Finally, an examination of the existing regulatory structure and policies that could prevent or encourage the use of wind to produce hydrogen in Sacramento is also included. (author)

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#

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.

Results from utility wind resource assessment programs in Nebraska, Colorado, and Arizona

Energy Technology Data Exchange (ETDEWEB)

Drapeau, C.L. [Global Energy Concepts, Inc., Bothell, WA (United States)

1997-12-31

Global Energy Concepts (GEC) has been retained by utilities in Colorado, Nebraska, and Arizona to site, install, and operate 21 wind monitoring stations as part of the Utility Wind Resource Assessment Program (U*WRAP). Preliminary results indicate wind speed averages at 40 meters (132 ft) of 6.5 - 7.4 m/s (14.5-16.5 mph) in Nebraska and 7.6 - 8.9 m/s (17.0-19.9 mph) in Colorado. The Arizona stations are not yet operational. This paper presents the history and current status of the 21 monitoring stations as well as preliminary data results. Information on wind speeds, wind direction, turbulence intensity, wind shear, frequency distribution, and data recovery rates are provided.

A new ensemble model for short term wind power prediction

DEFF Research Database (Denmark)

Madsen, Henrik; Albu, Razvan-Daniel; Felea, Ioan

2012-01-01

As the objective of this study, a non-linear ensemble system is used to develop a new model for predicting wind speed in short-term time scale. Short-term wind power prediction becomes an extremely important field of research for the energy sector. Regardless of the recent advancements in the re-search...... of prediction models, it was observed that different models have different capabilities and also no single model is suitable under all situations. The idea behind EPS (ensemble prediction systems) is to take advantage of the unique features of each subsystem to detain diverse patterns that exist in the dataset...

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.

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

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.

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

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.

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.

Model Predictive Voltage Control of Wind Power Plants

DEFF Research Database (Denmark)

Zhao, Haoran; Wu, Qiuwei

2018-01-01

the efficacy of the proposed WFVC, two case scenarios were designed: the wind farm is under normal operating conditions and the internal wind power fluctuation is considered; and besides internal power fluctuation, the impact of the external grid on the wind farm is considered.......This chapter proposes an autonomous wind farm voltage controller (WFVC) based on model predictive control (MPC). It also introduces the analytical expressions for the voltage sensitivity to tap positions of a transformer. The chapter then describes the discrete models for the wind turbine...... generators (WTGs) and static var compensators (SVCs)/static var generators (SVGs). Next, it describes the implementation of the on‐load tap changing (OLTC) in the MPC. Furthermore, the chapter examines the cost function as well as the constraints of the MPC‐based WFVC for both control modes. In order to test...

Two Machine Learning Approaches for Short-Term Wind Speed Time-Series Prediction.

Science.gov (United States)

Ak, Ronay; Fink, Olga; Zio, Enrico

2016-08-01

The increasing liberalization of European electricity markets, the growing proportion of intermittent renewable energy being fed into the energy grids, and also new challenges in the patterns of energy consumption (such as electric mobility) require flexible and intelligent power grids capable of providing efficient, reliable, economical, and sustainable energy production and distribution. From the supplier side, particularly, the integration of renewable energy sources (e.g., wind and solar) into the grid imposes an engineering and economic challenge because of the limited ability to control and dispatch these energy sources due to their intermittent characteristics. Time-series prediction of wind speed for wind power production is a particularly important and challenging task, wherein prediction intervals (PIs) are preferable results of the prediction, rather than point estimates, because they provide information on the confidence in the prediction. In this paper, two different machine learning approaches to assess PIs of time-series predictions are considered and compared: 1) multilayer perceptron neural networks trained with a multiobjective genetic algorithm and 2) extreme learning machines combined with the nearest neighbors approach. The proposed approaches are applied for short-term wind speed prediction from a real data set of hourly wind speed measurements for the region of Regina in Saskatchewan, Canada. Both approaches demonstrate good prediction precision and provide complementary advantages with respect to different evaluation criteria.

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.)

Southward shift of the global wind energy resource under high carbon dioxide emissions

Science.gov (United States)

Karnauskas, Kristopher B.; Lundquist, Julie K.; Zhang, Lei

2018-01-01

The use of wind energy resource is an integral part of many nations' strategies towards realizing the carbon emissions reduction targets set forth in the Paris Agreement, and global installed wind power cumulative capacity has grown on average by 22% per year since 2006. However, assessments of wind energy resource are usually based on today's climate, rather than taking into account that anthropogenic greenhouse gas emissions continue to modify the global atmospheric circulation. Here, we apply an industry wind turbine power curve to simulations of high and low future emissions scenarios in an ensemble of ten fully coupled global climate models to investigate large-scale changes in wind power across the globe. Our calculations reveal decreases in wind power across the Northern Hemisphere mid-latitudes and increases across the tropics and Southern Hemisphere, with substantial regional variations. The changes across the northern mid-latitudes are robust responses over time in both emissions scenarios, whereas the Southern Hemisphere changes appear critically sensitive to each individual emissions scenario. In addition, we find that established features of climate change can explain these patterns: polar amplification is implicated in the northern mid-latitude decrease in wind power, and enhanced land-sea thermal gradients account for the tropical and southern subtropical increases.

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.

Human resources challenges for wind energy

Energy Technology Data Exchange (ETDEWEB)

Cottingham, C. [Electricity Sector Council, Ottawa, ON (Canada)

2006-07-01

The potential role of the Electricity Sector Council in wind power workforce development was reviewed. Canada is a major exporter of electricity, and production of electricity in the country has grown by 10 per cent in the last 10 years. The electric industry has become increasingly interested in the development of renewable and sustainable energy sources in order to reduce the environmental impacts of electricity production and use, as well to address potential supply shortages. However, total labour force growth in Canada is expected to drop to 0.5 per cent by 2010, and is expected to keep falling. Engineering and science enrolments in post-secondary institutions are declining. Many immigrants to Canada choose to settle in metropolitan areas, and only 4 in 10 immigrants are able to achieve validation of their credentials in the Canadian education system. One-third of Canadian employees are expected to retire in the next 8 years. The wind energy sector is the fastest growing energy source sector in Canada, and there are limited training facilities available. Competency profiles for roles in the industry are not clearly defined. Many provinces have very little development to support or sustain educational services for wind power training. This presentation suggested that the wind energy sector should prepare for the anticipated workforce shortage by planning training programs and building partnerships in workforce development. Investments in wind power research and development should have contract provisions regarding labour and skills development. Retiring electricity workers may provide a source of labour support. Sector councils provide a neutral forum for employers, educators, and employees, with a focus on human resource development for specific industry sectors. The councils represent an estimated 45 to 50 per cent of the labour market, and have significant federal funding. The Electricity Sector Council offers advanced career and workforce training; youth

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.

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

Directory of Open Access Journals (Sweden)

Altab Md. Hossain

2009-12-01

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.

Wind Turbine Generator Efficiency Based on Powertrain Combination and Annual Power Generation Prediction

Directory of Open Access Journals (Sweden)

Dongmyung Kim

2018-05-01

Full Text Available Wind turbine generators are eco-friendly generators that produce electric energy using wind energy. In this study, wind turbine generator efficiency is examined using a powertrain combination and annual power generation prediction, by employing an analysis model. Performance testing was conducted in order to analyze the efficiency of a hydraulic pump and a motor, which are key components, and so as to verify the analysis model. The annual wind speed occurrence frequency for the expected installation areas was used to predict the annual power generation of the wind turbine generators. It was found that the parallel combination of the induction motors exhibited a higher efficiency when the wind speed was low and the serial combination showed higher efficiency when wind speed was high. The results of predicting the annual power generation considering the regional characteristics showed that the power generation was the highest when the hydraulic motors were designed in parallel and the induction motors were designed in series.

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.

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.

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

International Nuclear Information System (INIS)

Thelander, C.; Rugge, L.

2000-01-01

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

Characterization of the Wind Power Resource in Europe and its Intermittency

Science.gov (United States)

Cosseron, Alexandra; Gunturu, Bhaskar; Schlosser, Adam

2013-04-01

Thanks to incentives from the European Union and recent events, the political situation in Europe has never been so favorable towards renewables. As one of the most mature technologies among them, wind power has been chosen to be assessed over Europe, with a special care given to intermittency and variability quantifications. The goal of this study is to construct and analyze the availability and variability of the wind potential across Europe using the methodology developed in Gunturu and Schlosser (2011). The Modern Era Retrospective-Analysis for Research and Applications (MERRA) boundary flux data was used to construct wind profiles at 50, 80, 100 and 120 meters height over a domain spreading from Iceland to the western end of Ukraine. Comparisons and contrasts with previous works have asserted the reliability of the data and computations used in the analysis. It must be emphasized though that the data set used in this study has a thirty-year length, a time resolution of an hour and is a reconstruction of the atmospheric state by assimilating observational data from different platforms into a global model. Various metrics, such as coefficients of variation, inter-quartile ranges, capacity factors and wind episode lengths, have been introduced to assess magnitude and variability of wind power. Then, unconventional variables have been designed to further study the availability and reliability of this resource. Thus, to study the correlation between wind episodes across Europe, parameters called antiCoincidence and antiNullCoincidence have been built. Pragmatically, the seven closest grid points in each direction at every grid point have been studied to assess whether they had wind when the considered point had or had not. The analysis of these variables leads to the conclusion that wind-proponents' favorite statement, "wind always blows somewhere", may not be so true. All of these metrics have finally allowed a better understanding of wind power features over

Cultural Resource Predictive Modeling

Science.gov (United States)

2017-10-01

CR cultural resource CRM cultural resource management CRPM Cultural Resource Predictive Modeling DoD Department of Defense ESTCP Environmental...resource management ( CRM ) legal obligations under NEPA and the NHPA, military installations need to demonstrate that CRM decisions are based on objective...maxim “one size does not fit all,” and demonstrate that DoD installations have many different CRM needs that can and should be met through a variety

A study of single multiplicative neuron model with nonlinear filters for hourly wind speed prediction

International Nuclear Information System (INIS)

Wu, Xuedong; Zhu, Zhiyu; Su, Xunliang; Fan, Shaosheng; Du, Zhaoping; Chang, Yanchao; Zeng, Qingjun

2015-01-01

Wind speed prediction is one important methods to guarantee the wind energy integrated into the whole power system smoothly. However, wind power has a non–schedulable nature due to the strong stochastic nature and dynamic uncertainty nature of wind speed. Therefore, wind speed prediction is an indispensable requirement for power system operators. Two new approaches for hourly wind speed prediction are developed in this study by integrating the single multiplicative neuron model and the iterated nonlinear filters for updating the wind speed sequence accurately. In the presented methods, a nonlinear state–space model is first formed based on the single multiplicative neuron model and then the iterated nonlinear filters are employed to perform dynamic state estimation on wind speed sequence with stochastic uncertainty. The suggested approaches are demonstrated using three cases wind speed data and are compared with autoregressive moving average, artificial neural network, kernel ridge regression based residual active learning and single multiplicative neuron model methods. Three types of prediction errors, mean absolute error improvement ratio and running time are employed for different models’ performance comparison. Comparison results from Tables 1–3 indicate that the presented strategies have much better performance for hourly wind speed prediction than other technologies. - Highlights: • Developed two novel hybrid modeling methods for hourly wind speed prediction. • Uncertainty and fluctuations of wind speed can be better explained by novel methods. • Proposed strategies have online adaptive learning ability. • Proposed approaches have shown better performance compared with existed approaches. • Comparison and analysis of two proposed novel models for three cases are provided

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.

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.

Practical Robust Optimization Method for Unit Commitment of a System with Integrated Wind Resource

Directory of Open Access Journals (Sweden)

Yuanchao Yang

2017-01-01

Full Text Available Unit commitment, one of the significant tasks in power system operations, faces new challenges as the system uncertainty increases dramatically due to the integration of time-varying resources, such as wind. To address these challenges, we propose the formulation and solution of a generalized unit commitment problem for a system with integrated wind resources. Given the prespecified interval information acquired from real central wind forecasting system for uncertainty representation of nodal wind injections with their correlation information, the proposed unit commitment problem solution is computationally tractable and robust against all uncertain wind power injection realizations. We provide a solution approach to tackle this problem with complex mathematical basics and illustrate the capabilities of the proposed mixed integer solution approach on the large-scale power system of the Northwest China Grid. The numerical results demonstrate that the approach is realistic and not overly conservative in terms of the resulting dispatch cost outcomes.

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

Vertical Wind Tunnel for Prediction of Rocket Flight Dynamics

Directory of Open Access Journals (Sweden)

Hoani Bryson

2016-03-01

Full Text Available A customized vertical wind tunnel has been built by the University of Canterbury Rocketry group (UC Rocketry. This wind tunnel has been critical for the success of UC Rocketry as it allows the optimization of avionics and control systems before flight. This paper outlines the construction of the wind tunnel and includes an analysis of flow quality including swirl. A minimal modelling methodology for roll dynamics is developed that can extrapolate wind tunnel behavior at low wind speeds to much higher velocities encountered during flight. The models were shown to capture the roll flight dynamics in two rocket launches with mean roll angle errors varying from 0.26° to 1.5° across the flight data. The identified model parameters showed consistent and predictable variations over both wind tunnel tests and flight, including canard–fin interaction behavior. These results demonstrate that the vertical wind tunnel is an important tool for the modelling and control of sounding rockets.

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....

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...

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.

Map-based repowering and reorganization of a wind resource area to minimize burrowing owl and other bird fatalities

Energy Technology Data Exchange (ETDEWEB)

Smallwood, K. S. [Research Ecologist, 3108 Finch Street, Davis, CA 95616 (United States); Neher, L. [Gis Specialist, Neher Consulting, 7241 34th Street, North Highlands, CA 95660 (United States); Bell, D. A. [East Bay Regional Park District, 2950 Peralta Oaks Court, Oakland, CA 94605-0381 (United States)

2009-07-01

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 x 10 m{sup 2} 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. (author)

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.

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.

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

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

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.

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.

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....

Comparison of several measure-correlate-predict models using support vector regression techniques to estimate wind power densities. A case study

International Nuclear Information System (INIS)

Díaz, Santiago; Carta, José A.; Matías, José M.

2017-01-01

Highlights: • Eight measure-correlate-predict (MCP) models used to estimate the wind power densities (WPDs) at a target site are compared. • Support vector regressions are used as the main prediction techniques in the proposed MCPs. • The most precise MCP uses two sub-models which predict wind speed and air density in an unlinked manner. • The most precise model allows to construct a bivariable (wind speed and air density) WPD probability density function. • MCP models trained to minimise wind speed prediction error do not minimise WPD prediction error. - Abstract: The long-term annual mean wind power density (WPD) is an important indicator of wind as a power source which is usually included in regional wind resource maps as useful prior information to identify potentially attractive sites for the installation of wind projects. In this paper, a comparison is made of eight proposed Measure-Correlate-Predict (MCP) models to estimate the WPDs at a target site. Seven of these models use the Support Vector Regression (SVR) and the eighth the Multiple Linear Regression (MLR) technique, which serves as a basis to compare the performance of the other models. In addition, a wrapper technique with 10-fold cross-validation has been used to select the optimal set of input features for the SVR and MLR models. Some of the eight models were trained to directly estimate the mean hourly WPDs at a target site. Others, however, were firstly trained to estimate the parameters on which the WPD depends (i.e. wind speed and air density) and then, using these parameters, the target site mean hourly WPDs. The explanatory features considered are different combinations of the mean hourly wind speeds, wind directions and air densities recorded in 2014 at ten weather stations in the Canary Archipelago (Spain). The conclusions that can be drawn from the study undertaken include the argument that the most accurate method for the long-term estimation of WPDs requires the execution of a

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?

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...

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...

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...

Siting guidelines for utility application of wind turbines. Final report

Energy Technology Data Exchange (ETDEWEB)

Pennell, W.T.

1983-01-01

Utility-oriented guidelines are described for identifying viable sites for wind turbines. Topics and procedures are also discussed that are important in carrying out a wind turbine siting program. These topics include: a description of the Department of Energy wind resource atlases; procedures for predicting wind turbine performance at potential sites; methods for analyzing wind turbine economics; procedures for estimating installation and maintenance costs; methods for anlayzing the distribution of wind resources over an area; and instrumentation for documenting wind behavior at potential sites. The procedure described is applicable to small and large utilities. Although the procedure was developed as a site-selection tool, it can also be used by a utility who wishes to estimate the potential for wind turbine penetration into its future generation mix.

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.

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

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...... (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...

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)

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.

A Free Wake Numerical Simulation for Darrieus Vertical Axis Wind Turbine Performance Prediction

Science.gov (United States)

Belu, Radian

2010-11-01

In the last four decades, several aerodynamic prediction models have been formulated for the Darrieus wind turbine performances and characteristics. We can identified two families: stream-tube and vortex. The paper presents a simplified numerical techniques for simulating vertical axis wind turbine flow, based on the lifting line theory and a free vortex wake model, including dynamic stall effects for predicting the performances of a 3-D vertical axis wind turbine. A vortex model is used in which the wake is composed of trailing stream-wise and shedding span-wise vortices, whose strengths are equal to the change in the bound vortex strength as required by the Helmholz and Kelvin theorems. Performance parameters are computed by application of the Biot-Savart law along with the Kutta-Jukowski theorem and a semi-empirical stall model. We tested the developed model with an adaptation of the earlier multiple stream-tube performance prediction model for the Darrieus turbines. Predictions by using our method are shown to compare favorably with existing experimental data and the outputs of other numerical models. The method can predict accurately the local and global performances of a vertical axis wind turbine, and can be used in the design and optimization of wind turbines for built environment applications.

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)

A tall tower study of Missouri winds

Energy Technology Data Exchange (ETDEWEB)

Fox, Neil I. [Department of Soil, Environmental and Atmospheric Sciences, 332 ABNR Building, University of Missouri, Columbia, MO 65211 (United States)

2011-01-15

This paper summarizes the results of a study of wind speeds observed at heights up to 150 m above ground level around Missouri. This is an amalgamation of four projects that allowed a total of eleven tall communication towers to be instrumented with wind observation equipment across the State of Missouri. This provided an assessment of the wind resource and the characteristics of the seasonal and diurnal cycles of wind in different areas of Missouri at the heights of utility scale wind turbines. Comparisons were also made to wind speeds predicted at these levels from a previously published wind map. The main finding was that the observed winds at each tower were smaller than those presented in the wind map. The discrepancy is most likely to be due to underestimation of the surface roughness and turbulence leading to an overestimation of near-surface wind shear. However, the wind shear, as expressed by the shear parameter was consistently greater than the 'standard' value of 1.4. The reconciliation of these two apparently contradictory findings is that the shear varies with the height at which it is measured. In wind resource assessment, wind shear is usually observed below 50 m and is tacitly assumed to be constant with height when used to extrapolate winds to higher levels. The author advocates the use of the friction velocity as a measure of shear in wind power applications in preference to the shear parameter that is usually used. This is because the shear parameter has a velocity bias that can also manifest as a bias with height or season. As wind power resource assessment is starting to use taller towers than the standard 50 m, intercomparison of site resources and extrapolation to turbine heights can be compromised if the shear parameter is used. (author)

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...

Aerodynamic performance prediction of Darrieus-type wind turbines

Directory of Open Access Journals (Sweden)

Ion NILĂ

2010-06-01

Full Text Available The prediction of Darrieus wind turbine aerodynamic performances provides the necessarydesign and operational data base related to the wind potential. In this sense it provides the type ofturbine suitable to the area where it is to be installed. Two calculation methods are analyzed for arotor with straight blades. The first one is a global method that allows an assessment of the turbinenominal power by a brief calculation. This method leads to an overestimation of performances. Thesecond is the calculation method of the gust factor and momentum which deals with the pale as beingcomposed of different elements that don’t influence each other. This method, developed based on thetheory of the turbine blades, leads to values close to the statistical data obtained experimentally. Thevalues obtained by the calculation method of gust factor - momentum led to the concept of a Darrieusturbine, which will be tested for different wind values in the INCAS subsonic wind tunnel.

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.

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.

Climate change impacts on wind energy resources in northern Europe

International Nuclear Information System (INIS)

Pryor, S.C.; Barthelmie, R.J.; Kjellstroem, E.

2005-01-01

Energy is a fundamental human need. Heat, light and transport for individuals combined with the needs of industry have created a demand for energy which for the last 100-200 years has been met largely through consumption of fossil fuels leading to altered atmospheric composition and modification of the global climate. These effects will be realised on local scales affecting not just temperature and precipitation but also wind, radiation and other parameters. Annual mean wind speeds and wind energy density over northern Europe were significantly higher at the end of twentieth century than during the middle portion of that century, with the majority of the change being focused on the winter season. To address questions regarding possible future wind climates we employ dynamical and empirical downscaling techniques that seek to take coarse resolution output from General Circulation Models (GCM), run to provide scenarios of future climate, and develop higher resolution regional wind climates. Analyses of the wind climate during the historical record indicate that both the dynamical approach and the empirical approach are capable of generating accurate, robust and quantitative assessments of the wind climate and energy density in northern Europe, and hence that they may be of great utility to those seeking financing for, or risk management of, wind farms in the face of climate uncertainty. The synthesis of application of these downscaling tools to climate projections for northern Europe is that there is no evidence of major changes in the wind energy resource. However, more research is required to quantify the uncertainties in developing these projections and to reduce those uncertainties. Further work should also be conducted to assess the validity of these downscaling approaches in other geographical locations. (BA)

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...... be considered to achieve a trade-off between them. Additionally, D- MPC is based on communication among the subsystems. Through the interaction among the neighboring subsystems, the global optimization could be achieved, which significantly reduces the computation burden. It is suitable for the modern large......-scale wind farm control....

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.

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 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...... 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...

Reduction of wind power induced reserve requirements by advanced shortest-term forecasts and prediction intervals

Energy Technology Data Exchange (ETDEWEB)

Dobschinski, Jan; Wessel, Arne; Lange, Bernhard; Bremen, Lueder von [Fraunhofer Institut fuer Windenergie und Energiesystemtechnik (IWES), Kassel (Germany)

2009-07-01

In electricity systems with large penetration of wind power, the limited predictability of the wind power generation leads to an increase in reserve and balancing requirements. At first the present study concentrates on the capability of dynamic day-ahead prediction intervals to reduce the wind power induced reserve and balancing requirements. Alternatively the reduction of large forecast errors of the German wind power generation by using advanced shortest-term predictions has been evaluated in a second approach. With focus on the allocation of minute reserve power the aim is to estimate the maximal remaining uncertainty after trading activities on the intraday market. Finally both approaches were used in a case study concerning the reserve requirements induced by the total German wind power expansion in 2007. (orig.)

Predicting wind shear effects: A study of Minnesota wind data collected at heights up to 70 meters

Energy Technology Data Exchange (ETDEWEB)

Artig, R. [Minnesota Dept. of Public Service, St. Paul, MN (United States)

1997-12-31

The Minnesota Department of Public Service (DPS) collects wind data at carefully selected sites around the state and analyzes the data to determine Minnesota`s wind power potential. DPS recently installed advanced new monitoring equipment at these sites and began to collect wind data at 30, 50, and 70 meters above ground level, with two anemometers at each level. Previously, the Department had not collected data at heights above ground level higher than 30 meters. DPS also, with the U.S. Department of Energy (DOE), installed four sophisticated monitoring sites as part of a Tall Tower Wind Shear Study that is assessing the effects of wind shear on wind power potential. At these sites, wind data are being collected at the 10, 30, 40, 50, 60, and 70 meter heights. This paper presents the preliminary results of the analysis of wind data from all sites. These preliminary results indicate that the traditional 1/7 power law does not effectively predict wind shear in Minnesota, and the result is an underestimation of Minnesota`s wind power potential at higher heights. Using a power factor of 1/5 or 1/4 may be more accurate and provide sound justification for installing wind turbines on taller towers in Minnesota.

A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

International Nuclear Information System (INIS)

Pousinho, H.M.I.; Mendes, V.M.F.; Catalao, J.P.S.

2011-01-01

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.

Atmospheric air density analysis with Meteo-40S wind monitoring system

Directory of Open Access Journals (Sweden)

Zahariea Dănuţ

2017-01-01

Full Text Available In order to estimate the wind potential of wind turbine sites, the wind resource maps can be used for mean annual wind speed, wind speed frequency distribution and mean annual wind power density determination. The general evaluation of the wind resource and the wind turbine ratings are based on the standard air density measured at sea level and at 15°C, ρs=1.225 kg/m3. Based on the experimental data obtained for a continental climate specific location, this study will present the relative error between the standard air density and the density of the dry and the moist air. Considering a cold day, for example on Friday 10th February 2017, on 1-second measurement rate and 10-minute measuring interval starting at 16:20, the mean relative errors obtained are 10.4145% for dry air, and 10.3634% for moist air. Based on these results, a correction for temperature, atmospheric air pressure and relative humidity should be always considered for wind resource assessment, as well as for the predicting the wind turbines performance.

Bayesian based Prognostic Model for Predictive Maintenance of Offshore Wind Farms

DEFF Research Database (Denmark)

Asgarpour, Masoud; Sørensen, John Dalsgaard

2018-01-01

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...... 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...

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...

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.

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...

Validated Loads Prediction Models for Offshore Wind Turbines for Enhanced Component Reliability

DEFF Research Database (Denmark)

Koukoura, Christina

To improve the reliability of offshore wind turbines, accurate prediction of their response is required. Therefore, validation of models with site measurements is imperative. In the present thesis a 3.6MW pitch regulated-variable speed offshore wind turbine on a monopole foundation is built...... are used for the modification of the sub-structure/foundation design for possible material savings. First, the background of offshore wind engineering, including wind-wave conditions, support structure, blade loading and wind turbine dynamics are presented. Second, a detailed description of the site...

Controllable and affordable utility-scale electricity from intermittent wind resources and compressed air energy storage (CAES)

International Nuclear Information System (INIS)

Cavallo, Alfred

2007-01-01

World wind energy resources are substantial, and in many areas, such as the US and northern Europe, could in theory supply all of the electricity demand. However, the remote or challenging location (i.e. offshore) and especially the intermittent character of the wind resources present formidable barriers to utilization on the scale required by a modern industrial economy. All of these technical challenges can be overcome. Long distance transmission is well understood, while offshore wind technology is being developed rapidly. Intermittent wind power can be transformed to a controllable power source with hybrid wind/compressed air energy storage (CAES) systems. The cost of electricity from such hybrid systems (including transmission) is affordable, and comparable to what users in some modern industrial economies already pay for electricity. This approach to intermittent energy integration has many advantages compared to the current strategy of forcing utilities to cope with supply uncertainty and transmission costs. Above all, it places intermittent wind on an equal technical footing with every other generation technology, including nuclear power, its most important long-term competitor

Hybrid biomass-wind power plant for reliable energy generation

International Nuclear Information System (INIS)

Perez-Navarro, A.; Alfonso, D.; Alvarez, C.; Ibanez, F.; Sanchez, C.; Segura, I.

2010-01-01

Massive implementation of renewable energy resources is a key element to reduce CO 2 emissions associated to electricity generation. Wind resources can provide an important alternative to conventional electricity generation mainly based on fossil fuels. However, wind generators are greatly affected by the restrictive operating rules of electricity markets because, as wind is naturally variable, wind generators may have serious difficulties on submitting accurate generation schedules on a day ahead basis, and on complying with scheduled obligations in real-time operation. In this paper, an innovative system combining a biomass gasification power plant, a gas storage system and stand-by generators to stabilize a generic 40 MW wind park is proposed and evaluated with real data. The wind park power production model is based on real data about power production of a Spanish wind park and a probabilistic approach to quantify fluctuations and so, power compensation needs. The hybrid wind-biomass system is analysed to obtain main hybrid system design parameters. This hybrid system can mitigate wind prediction errors and so provide a predictable source of electricity. An entire year cycle of hourly power compensations needs has been simulated deducing storage capacity, extra power needs of the biomass power plant and stand-by generation capacity to assure power compensation during critical peak hours with acceptable reliability. (author)

A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

Energy Technology Data Exchange (ETDEWEB)

Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal); Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal)

2011-01-15

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches. (author)

Short-term wind speed prediction using an unscented Kalman filter based state-space support vector regression approach

International Nuclear Information System (INIS)

Chen, Kuilin; Yu, Jie

2014-01-01

Highlights: • A novel hybrid modeling method is proposed for short-term wind speed forecasting. • Support vector regression model is constructed to formulate nonlinear state-space framework. • Unscented Kalman filter is adopted to recursively update states under random uncertainty. • The new SVR–UKF approach is compared to several conventional methods for short-term wind speed prediction. • The proposed method demonstrates higher prediction accuracy and reliability. - Abstract: Accurate wind speed forecasting is becoming increasingly important to improve and optimize renewable wind power generation. Particularly, reliable short-term wind speed prediction can enable model predictive control of wind turbines and real-time optimization of wind farm operation. However, this task remains challenging due to the strong stochastic nature and dynamic uncertainty of wind speed. In this study, unscented Kalman filter (UKF) is integrated with support vector regression (SVR) based state-space model in order to precisely update the short-term estimation of wind speed sequence. In the proposed SVR–UKF approach, support vector regression is first employed to formulate a nonlinear state-space model and then unscented Kalman filter is adopted to perform dynamic state estimation recursively on wind sequence with stochastic uncertainty. The novel SVR–UKF method is compared with artificial neural networks (ANNs), SVR, autoregressive (AR) and autoregressive integrated with Kalman filter (AR-Kalman) approaches for predicting short-term wind speed sequences collected from three sites in Massachusetts, USA. The forecasting results indicate that the proposed method has much better performance in both one-step-ahead and multi-step-ahead wind speed predictions than the other approaches across all the locations

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 functions of conventional peaking plant. Demand side resources are also shown to be capable of improving the reliability of the system, with reserve capability identified as a key requirement in this respect....... 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...

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.

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

are made to share the expenses in transmission derived from their integration, they may see the doors of electricity markets closed for not being competitive enough. This paper presents a model to decide the amount of wind resources that are economically exploitable at a given location from a transmission......In the pursuit of the large-scale integration of wind power production, it is imperative to evaluate plausible frictions among the stochastic nature of wind generation, electricity markets, and the investments in transmission required to accommodate larger amounts of wind. If wind producers......-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...

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)

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.

Wind power application research on the fusion of the determination and ensemble prediction

Science.gov (United States)

Lan, Shi; Lina, Xu; Yuzhu, Hao

2017-07-01

The fused product of wind speed for the wind farm is designed through the use of wind speed products of ensemble prediction from the European Centre for Medium-Range Weather Forecasts (ECMWF) and professional numerical model products on wind power based on Mesoscale Model5 (MM5) and Beijing Rapid Update Cycle (BJ-RUC), which are suitable for short-term wind power forecasting and electric dispatch. The single-valued forecast is formed by calculating the different ensemble statistics of the Bayesian probabilistic forecasting representing the uncertainty of ECMWF ensemble prediction. Using autoregressive integrated moving average (ARIMA) model to improve the time resolution of the single-valued forecast, and based on the Bayesian model averaging (BMA) and the deterministic numerical model prediction, the optimal wind speed forecasting curve and the confidence interval are provided. The result shows that the fusion forecast has made obvious improvement to the accuracy relative to the existing numerical forecasting products. Compared with the 0-24 h existing deterministic forecast in the validation period, the mean absolute error (MAE) is decreased by 24.3 % and the correlation coefficient (R) is increased by 12.5 %. In comparison with the ECMWF ensemble forecast, the MAE is reduced by 11.7 %, and R is increased 14.5 %. Additionally, MAE did not increase with the prolongation of the forecast ahead.

Siting wind farms in and around forests

Energy Technology Data Exchange (ETDEWEB)

Douglas, N. [Natural Power Consultants, Vancouver, BC (Canada)

2010-07-01

This PowerPoint presentation discussed methods of assessing the impact of trees on wind resources. Turbulence is generated and also absorbed by trees. Disturbances generated at tree level are then transported upwards and down-wind by the wind. The turbulence induced by trees can be felt kilometers downwind of forests at wind turbine hub heights. Wind speeds can be less than predicted, and significant over-estimations can occur with modelled results. The effects of high shear and high turbulence can also have an impact on power curve performance and lead to higher levels of mechanical stress. A SCADA analysis was used to demonstrate the impact of forests on power curves. Wind power predictions near forests can be optimized by using a full year of data capture at hub height, full rotor measurements, and a consideration of seasonal variations. Accurate tree maps are needed to determine the effects of trees on wind shear. Various forestry scenarios were modelled to demonstrate the effects of forestry management over time. tabs., figs.

Climate change implications for wind power resources in the Northwest United States

International Nuclear Information System (INIS)

Sailor, David J.; Smith, Michael; Hart, Melissa

2008-01-01

Using statistically downscaled output from four general circulation models (GCMs), we have investigated scenarios of climate change impacts on wind power generation potential in a five-state region within the Northwest United States (Idaho, Montana, Oregon, Washington, and Wyoming). All GCM simulations were extracted from the standardized set of runs created for the Intergovernmental Panel on Climate Change (IPCC). Analysis of model runs for the 20th century (20c3m) simulations revealed that the direct output of wind statistics from these models is of relatively poor quality compared with observations at airport weather stations within each state. When the GCM output was statistically downscaled, the resulting estimates of current climate wind statistics are substantially better. Furthermore, in looking at the GCM wind statistics for two IPCC future climate scenarios from the Special Report on Emissions Scenarios (SRES A1B and A2), there was significant disagreement in the direct model output from the four GCMs. When statistical downscaling was applied to the future climate simulations, a more coherent story unfolded related to the likely impact of climate change on the region's wind power resource. Specifically, the results suggest that summertime wind speeds in the Northwest may decrease by 5-10%, while wintertime wind speeds may decrease by relatively little, or possibly increase slightly. When these wind statistics are projected to typical turbine hub heights and nominal wind turbine power curves are applied, the impact of the climate change scenarios on wind power may be as high as a 40% reduction in summertime generation potential. (author)

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%.

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)

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

Moroccan wind farm potential feasibility. Case study

International Nuclear Information System (INIS)

Nouri, Abdellatif; Ait Babram, Mohamed; Elwarraki, Elmostafa; Enzili, Mustapha

2016-01-01

Highlights: • A new methodology for the technical feasibility of wind farm potentials is proposed. • The wind resources of two different sites in Morocco are compared. • Comparison between short and long term data using multivariate analysis is made. • Geographic information system implementation. • A 10 MW wind farm is designed and optimized. - Abstract: The subject of this paper is the elaboration of a methodology to study the technical feasibility of a wind farm potential. The implementation of this methodology allows a comparison between the wind resources of two different sites in Morocco. One site is located in the region of Essaouira, whereas the other one is located in the region of Safi. The comparison is based on real wind data collected from two masts at the heights of 30, 50, and 60 m. Each of the masts is installed at one of the mentioned potential sites over a fixed time period, lasting fifteen months for the first site, and eight months for the second one. The aim is the determination of the most applicable site presenting a good potential for a statistical study in order to predict long-term wind behaviors. Thus, the geographical situation study of the chosen site including topography, roughness and obstacles, is carried out. Furthermore, the wind resource using data, generated by the measuring masts, is evaluated. Finally, the areas which present great wind potential are located and the wind farm turbine locations are optimized by using the WAsP software.

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.

The Numerical Wind Atlas - the KAMM/WAsP Method

Energy Technology Data Exchange (ETDEWEB)

Frank, H P; Rathmann, O; Mortensen, N G; Landberg, L

2001-06-01

The method of combining the Karlsruhe Atmospheric Mesoscale Model, KAMM, with the Wind Atlas Analysis and Application Program, WAsP, to make local predictions of the wind resource is presented. It combines the advantages of meso-scale modeling - overview over a big region and use of global data bases - with the local prediction capacity of the small-scale model WAsP. Results are presented for Denmark, Ireland, Northern Portugal and Galicia, and the Faroe Islands. Wind atlas files were calculated from wind data simulated with the meso-scale model using model grids with a resolution of 2.5, 5, and 10 km. Using these wind atlas files in WAsP the local prediction of the mean wind does not depend on the grid resolution of the meso-scale model. The local predictions combining KAMM and WAsP are much better than simple interpolation of the wind simulated by KAMM. In addition an investigation was made on the dependence of wind atlas data on the size of WAsP-maps. It is recommended that a topographic map around a site should extend 10 km out from it. If there is a major roughness change like a coast line further away in a frequent wind direction this should be included at even greater distances, perhaps up to 20 km away.

77 FR 2286 - Iberdrola Renewables, Inc., PacifiCorp, NextEra Energy Resources, LLC, Invenergy Wind North...

Science.gov (United States)

2012-01-17

... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Docket No. EL11-44-000] Iberdrola Renewables, Inc., PacifiCorp, NextEra Energy Resources, LLC, Invenergy Wind North America LLC, Horizon Wind Energy LLC v. Bonneville Power Administration; Notice of Designation of Certain Commission Personnel as...

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)

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.

Grid Integration of Offshore Wind | Wind | NREL

Science.gov (United States)

Grid Integration of Offshore Wind Grid Integration of Offshore Wind Much can be learned from the existing land-based integration research for handling the variability and uncertainty of the wind resource Arklow Bank offshore wind park consists of seven GE Wind 3.6-MW wind turbines. Integration and

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.

Wind Energy Department: Scientific and technical progress 1999-2000

DEFF Research Database (Denmark)

2001-01-01

The activities of the Wind Energy Department fall within boundary layer meteorology, atmospheric turbulence, aerodynamics, aero-acoustics, structural dynamics, machine and construction technology and design of power systems and power system controls. Theobjective is to develop methods for design......; test and siting of wind turbines; prediction of wind loads and wind resources as well as methods to determine the dispersion, transformation and effect of air pollution. The present report describes theorganisation of the department and presents selected scientific highlights and results from the two...

Wind energy: Overcoming inadequate wind and modeling uncertainties

Energy Technology Data Exchange (ETDEWEB)

Kane, Vivek

2010-09-15

'Green Energy' is the call of the day, and significance of Wind Energy can never be overemphasized. But the key question here is - What if the wind resources are inadequate? Studies reveal that the probability of finding favorable wind at a given place on land is only 15%. Moreover, there are inherent uncertainties associated with wind business. Can we overcome inadequate wind resources? Can we scientifically quantify uncertainty and model it to make business sense? This paper proposes a solution, by way of break-through Wind Technologies, combined with advanced tools for Financial Modeling, enabling vital business decisions.

ANEMOS: Development of a next generation wind power forecasting system for the large-scale integration of onshore and offshore wind farms.

Science.gov (United States)

Kariniotakis, G.; Anemos Team

2003-04-01

offshore wind farms taking into account advances in marine meteorology (interaction between wind and waves, coastal effects). The benefits from the use of satellite radar images for modeling local weather patterns are investigated. A next generation forecasting software, ANEMOS, will be developed to integrate the various models. The tool is enhanced by advanced Information Communication Technology (ICT) functionality and can operate both in stand alone, or remote mode, or be interfaced with standard Energy or Distribution Management Systems (EMS/DMS) systems. Contribution: The project provides an advanced technology for wind resource forecasting applicable in a large scale: at a single wind farm, regional or national level and for both interconnected and island systems. A major milestone is the on-line operation of the developed software by the participating utilities for onshore and offshore wind farms and the demonstration of the economic benefits. The outcome of the ANEMOS project will help consistently the increase of wind integration in two levels; in an operational level due to better management of wind farms, but also, it will contribute to increasing the installed capacity of wind farms. This is because accurate prediction of the resource reduces the risk of wind farm developers, who are then more willing to undertake new wind farm installations especially in a liberalized electricity market environment.

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

An appraisal of wind speed distribution prediction by soft computing methodologies: A comparative study

International Nuclear Information System (INIS)

Petković, Dalibor; Shamshirband, Shahaboddin; Anuar, Nor Badrul; Saboohi, Hadi; Abdul Wahab, Ainuddin Wahid; Protić, Milan; Zalnezhad, Erfan; Mirhashemi, Seyed Mohammad Amin

2014-01-01

Highlights: • Probabilistic distribution functions of wind speed. • Two parameter Weibull probability distribution. • To build an effective prediction model of distribution of wind speed. • Support vector regression application as probability function for wind speed. - Abstract: The probabilistic distribution of wind speed is among the more significant wind characteristics in examining wind energy potential and the performance of wind energy conversion systems. When the wind speed probability distribution is known, the wind energy distribution can be easily obtained. Therefore, the probability distribution of wind speed is a very important piece of information required in assessing wind energy potential. For this reason, a large number of studies have been established concerning the use of a variety of probability density functions to describe wind speed frequency distributions. Although the two-parameter Weibull distribution comprises a widely used and accepted method, solving the function is very challenging. In this study, the polynomial and radial basis functions (RBF) are applied as the kernel function of support vector regression (SVR) to estimate two parameters of the Weibull distribution function according to previously established analytical methods. Rather than minimizing the observed training error, SVR p oly and SVR r bf attempt to minimize the generalization error bound, so as to achieve generalized performance. According to the experimental results, enhanced predictive accuracy and capability of generalization can be achieved using the SVR approach compared to other soft computing methodologies

A 100% renewable electricity generation system for New Zealand utilising hydro, wind, geothermal and biomass resources

International Nuclear Information System (INIS)

Mason, I.G.; Page, S.C.; Williamson, A.G.

2010-01-01

The New Zealand electricity generation system is dominated by hydro generation at approximately 60% of installed capacity between 2005 and 2007, augmented with approximately 32% fossil-fuelled generation, plus minor contributions from geothermal, wind and biomass resources. In order to explore the potential for a 100% renewable electricity generation system with substantially increased levels of wind penetration, fossil-fuelled electricity production was removed from an historic 3-year data set, and replaced by modelled electricity production from wind, geothermal and additional peaking options. Generation mixes comprising 53-60% hydro, 22-25% wind, 12-14% geothermal, 1% biomass and 0-12% additional peaking generation were found to be feasible on an energy and power basis, whilst maintaining net hydro storage. Wind capacity credits ranged from 47% to 105% depending upon the incorporation of demand management, and the manner of operation of the hydro system. Wind spillage was minimised, however, a degree of residual spillage was considered to be an inevitable part of incorporating non-dispatchable generation into a stand-alone grid system. Load shifting was shown to have considerable advantages over installation of new peaking plant. Application of the approach applied in this research to countries with different energy resource mixes is discussed, and options for further research are outlined.

Dynamic Modeling and Very Short-term Prediction of Wind Power Output Using Box-Cox Transformation

Science.gov (United States)

Urata, Kengo; Inoue, Masaki; Murayama, Dai; Adachi, Shuichi

2016-09-01

We propose a statistical modeling method of wind power output for very short-term prediction. The modeling method with a nonlinear model has cascade structure composed of two parts. One is a linear dynamic part that is driven by a Gaussian white noise and described by an autoregressive model. The other is a nonlinear static part that is driven by the output of the linear part. This nonlinear part is designed for output distribution matching: we shape the distribution of the model output to match with that of the wind power output. The constructed model is utilized for one-step ahead prediction of the wind power output. Furthermore, we study the relation between the prediction accuracy and the prediction horizon.

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.

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

International Nuclear Information System (INIS)

Keane, A.; Tuohy, A.; Meibom, P.; Denny, E.; Flynn, D.; Mullane, A.; O'Malley, M.

2011-01-01

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 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 of the functions of conventional peaking plant. Demand side resources are also shown to be capable of improving the reliability of the system, with reserve capability identified as a key requirement in this respect. - Highlights: → Demand side resource model presented for use in unit commitment and dispatch calculations. → Benefits of demand side aggregation demonstrated specifically as a peaking unit and provider of reserve. → Potential to displace or defer construction of conventional peaking units.

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

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.

Wind energy department: Scientific and technical progress 1999 - 2000

International Nuclear Information System (INIS)

Skrumsager, B.; Larsen, G.

2001-01-01

The activities of the Wind Energy Department fall within boundary layer meteorology, atmospheric turbulence, aerodynamics, aero-acoustics, structural dynamics, machine and construction technology and design of power systems and power system controls. The objective is to develop methods for design; test and siting of wind turbines; prediction of wind loads and wind resources as well as methods to determine the dispersion, transformation and effect of air pollution. The present report describes the organisation of the department and presents selected scientific highlights and results from the two-year period 1999-2000. (au)

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)

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)

SAT-WIND project. Final report[Winds from satellites for offshore and coastal wind energy mapping and wind-indexing

Energy Technology Data Exchange (ETDEWEB)

Hasager, C.B.; Astrup, P.; Nielsen, M. (and others)

2007-04-15

The SAT-WIND project 'Winds from satellites for offshore and coastal wind energy mapping and wind-indexing' was a research project funded by STVF/DSF in the years 2003 to 2006 (Sagsnr. 2058-03-0006). The goal of the project was to verify the applicability of satellite wind maps derived from passive microwave, altimeter, scatterometer and imaging Synthetic Aperture Radar (SAR) technologies for wind energy tools for wind resources and wind-indexing. The study area was the Danish Seas including the North Sea, interior seas and the Baltic Sea. The report describes technical details on the satellite data sources including: 1) passive microwave (SSM/I, AMSR-E), 2) passive microwave polarimetric (WindSat), 3) scatterometer (ERS, QuikSCAT, Midori-2 and NSCAT), 4) altimeter (ERS, Topex, Poseidon, GFO-1, Jason-1), 5) SAR (ERS, Envisat). The SAR wind maps were treated in S-WAsP developed by Risoe National Laboratory in cooperation with GRAS A/S in the innovative project SAT-WIND-SMV (Sagsnr. 2104-05-0084) in the years 2005 and 2006 in parallel with SAT-WIND. The results from the SAT-WIND project are presented. These include ocean wind statistics, offshore wind resource estimates and comparison results for wind-indexing. (au)

SAT-WIND project. Final report[Winds from satellites for offshore and coastal wind energy mapping and wind-indexing

Energy Technology Data Exchange (ETDEWEB)

Hasager, C B; Astrup, P; Nielsen, M [and others

2007-04-15

The SAT-WIND project 'Winds from satellites for offshore and coastal wind energy mapping and wind-indexing' was a research project funded by STVF/DSF in the years 2003 to 2006 (Sagsnr. 2058-03-0006). The goal of the project was to verify the applicability of satellite wind maps derived from passive microwave, altimeter, scatterometer and imaging Synthetic Aperture Radar (SAR) technologies for wind energy tools for wind resources and wind-indexing. The study area was the Danish Seas including the North Sea, interior seas and the Baltic Sea. The report describes technical details on the satellite data sources including: 1) passive microwave (SSM/I, AMSR-E), 2) passive microwave polarimetric (WindSat), 3) scatterometer (ERS, QuikSCAT, Midori-2 and NSCAT), 4) altimeter (ERS, Topex, Poseidon, GFO-1, Jason-1), 5) SAR (ERS, Envisat). The SAR wind maps were treated in S-WAsP developed by Risoe National Laboratory in cooperation with GRAS A/S in the innovative project SAT-WIND-SMV (Sagsnr. 2104-05-0084) in the years 2005 and 2006 in parallel with SAT-WIND. The results from the SAT-WIND project are presented. These include ocean wind statistics, offshore wind resource estimates and comparison results for wind-indexing. (au)

Wind resource assessment handbook: Fundamentals for conducting a successful monitoring program

International Nuclear Information System (INIS)

Bailey, B.H.; McDonald, S.L.; Bernadett, D.W.; Markus, M.J.; Elsholz, K.V.

1997-01-01

This handbook presents industry-accepted guidelines for planning and conducting a wind resource measurement program to support a wind energy feasibility initiative. These guidelines, which are detailed and highly technical, emphasize the tasks of selecting, installing, and operating wind measurement equipment, as well as collecting and analyzing the associated data, once one or more measurement sites are located. The handbook's scope encompasses state-of-the-art measurement and analysis techniques at multiple heights on tall towers (e.g., 40 m) for a measurement duration of at least one year. These guidelines do not represent every possible method of conducting a quality wind measurement program, but they address the most important elements based on field-proven experience. The intended audience for this handbook is any organization or individual who desires the planning framework and detailed procedures for conducting a formally structured wind measurement program. Personnel from the management level to field technicians will find this material applicable. The organizational aspects of a measurement program, including the setting of clear program objectives and designing commensurate measurement and quality assurance plans, all of which are essential to ensuring the program's successful outcome, are emphasized. Considerable attention is also given to the details of actually conducting the measurement program in its many aspects, from selecting instrumentation that meets minimum performance standards to analyzing and reporting on the collected data. 5 figs., 15 tabs

Performance and wake predictions of HAWTs in wind farms

Energy Technology Data Exchange (ETDEWEB)

Leclerc, C.; Masson, C.; Paraschivoiu, I. [Ecole Polytechnique, Montreal (Canada)

1997-12-31

The present contribution proposes and describes a promising way towards performance prediction of an arbitrary array of turbines. It is based on the solution of the time-averaged, steady-state, incompressible Navier-Stokes equations with an appropriate turbulence closure model. The turbines are represented by distributions of momentum sources in the Navier-Stokes equations. In this paper, the applicability and viability of the proposed methodology is demonstrated using an axisymmetric implementation. The k-{epsilon} model has been chosen for the closure of the time-averaged, turbulent flow equations and the properties of the incident flow correspond to those of a neutral atmospheric boundary layer. The proposed mathematical model is solved using a Control-Volume Finite Element Method (CVFEM). Detailed results have been obtained using the proposed method for an isolated wind turbine and for two turbines one behind another. In the case of an isolated turbine, accurate wake velocity deficit predictions are obtained and an increase in power due to atmospheric turbulence is found in agreement with measurements. In the case of two turbines, the proposed methodology provides an appropriate modelling of the wind-turbine wake and a realistic prediction of the performance degradation of the downstream turbine.

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.

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...

Technology Roadmap: Wind Energy. 2013 edition

Energy Technology Data Exchange (ETDEWEB)

NONE

2013-07-01

The IEA Wind Power Technology Roadmap 2013 Edition recognises the very significant progress made since the first edition was published in 2009. The technology continues to improve rapidly, and costs of generation from land-based wind installations continue to fall. Wind power is now being deployed in countries with good resources without any dedicated financial incentives. The 2013 Edition targets an increased share (15% to 18%) of global electricity to be provided by wind power in 2050, compared to 12% in the original roadmap of 2009. However, increasing levels of low-cost wind still require predictable, supportive regulatory environments and appropriate market designs. The challenges of integrating higher levels of variable wind power into the grid need to be addressed. For offshore wind, much remains to be done to develop appropriate large-scale systems and to reduce costs. The 2013 Wind Power Roadmap also provides updated analysis on the barriers that exist for the technology and suggests ways to address them, including legal and regulatory recommendations.

Wind climate from the regional climate model REMO

DEFF Research Database (Denmark)

Larsén, Xiaoli Guo; Mann, Jakob; Berg, Jacob

2010-01-01

Selected outputs from simulations with the regional climate model REMO from the Max Planck Institute, Hamburg, Germany were studied in connection with wind energy resource assessment. It was found that the mean wind characteristics based on observations from six mid-latitude stations are well...... described by the standard winds derived from the REMO pressure data. The mean wind parameters include the directional wind distribution, directional and omni-directional mean values and Weibull fitting parameters, spectral analysis and interannual variability of the standard winds. It was also found that......, on average, the wind characteristics from REMO are in better agreement with observations than those derived from the National Centers for Environmental Prediction/National Center for Atmospheric Research (NCEP/NCAR) re-analysis pressure data. The spatial correlation of REMO surface winds in Europe...

The Impact of Variable Wind Shear Coefficients on Risk Reduction of Wind Energy Projects.

Science.gov (United States)

Corscadden, Kenneth W; Thomson, Allan; Yoonesi, Behrang; McNutt, Josiah

2016-01-01

Estimation of wind speed at proposed hub heights is typically achieved using a wind shear exponent or wind shear coefficient (WSC), variation in wind speed as a function of height. The WSC is subject to temporal variation at low and high frequencies, ranging from diurnal and seasonal variations to disturbance caused by weather patterns; however, in many cases, it is assumed that the WSC remains constant. This assumption creates significant error in resource assessment, increasing uncertainty in projects and potentially significantly impacting the ability to control gird connected wind generators. This paper contributes to the body of knowledge relating to the evaluation and assessment of wind speed, with particular emphasis on the development of techniques to improve the accuracy of estimated wind speed above measurement height. It presents an evaluation of the use of a variable wind shear coefficient methodology based on a distribution of wind shear coefficients which have been implemented in real time. The results indicate that a VWSC provides a more accurate estimate of wind at hub height, ranging from 41% to 4% reduction in root mean squared error (RMSE) between predicted and actual wind speeds when using a variable wind shear coefficient at heights ranging from 33% to 100% above the highest actual wind measurement.

Beyond Classical Upscaling : Integrated Aeroservoelastic Design and Optimization of Large Offshore Wind Turbines

NARCIS (Netherlands)

Ashuri, T.

2012-01-01

Issues related to environmental concern and fossil fuel exhaustion has made wind energy the most widely accepted renewable energy resource. However, there are still several challenges to be solved such as the integrated design of wind turbines, aeroelastic response and stability prediction, grid

Model predictive control of a wind turbine modelled in Simpack

International Nuclear Information System (INIS)

Jassmann, U; Matzke, D; Reiter, M; Abel, D; Berroth, J; Schelenz, R; Jacobs, G

2014-01-01

Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine

Model predictive control of a wind turbine modelled in Simpack

Science.gov (United States)

Jassmann, U.; Berroth, J.; Matzke, D.; Schelenz, R.; Reiter, M.; Jacobs, G.; Abel, D.

2014-06-01

Wind turbines (WT) are steadily growing in size to increase their power production, which also causes increasing loads acting on the turbine's components. At the same time large structures, such as the blades and the tower get more flexible. To minimize this impact, the classical control loops for keeping the power production in an optimum state are more and more extended by load alleviation strategies. These additional control loops can be unified by a multiple-input multiple-output (MIMO) controller to achieve better balancing of tuning parameters. An example for MIMO control, which has been paid more attention to recently by wind industry, is Model Predictive Control (MPC). In a MPC framework a simplified model of the WT is used to predict its controlled outputs. Based on a user-defined cost function an online optimization calculates the optimal control sequence. Thereby MPC can intrinsically incorporate constraints e.g. of actuators. Turbine models used for calculation within the MPC are typically simplified. For testing and verification usually multi body simulations, such as FAST, BLADED or FLEX5 are used to model system dynamics, but they are still limited in the number of degrees of freedom (DOF). Detailed information about load distribution (e.g. inside the gearbox) cannot be provided by such models. In this paper a Model Predictive Controller is presented and tested in a co-simulation with SlMPACK, a multi body system (MBS) simulation framework used for detailed load analysis. The analysis are performed on the basis of the IME6.0 MBS WT model, described in this paper. It is based on the rotor of the NREL 5MW WT and consists of a detailed representation of the drive train. This takes into account a flexible main shaft and its main bearings with a planetary gearbox, where all components are modelled flexible, as well as a supporting flexible main frame. The wind loads are simulated using the NREL AERODYN v13 code which has been implemented as a routine to

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.

Predicting geomagnetic storms from solar-wind data using time-delay neural networks

Directory of Open Access Journals (Sweden)

H. Gleisner

1996-07-01

Full Text Available We have used time-delay feed-forward neural networks to compute the geomagnetic-activity index Dst one hour ahead from a temporal sequence of solar-wind data. The input data include solar-wind density n, velocity V and the southward component Bz of the interplanetary magnetic field. Dst is not included in the input data. The networks implement an explicit functional relationship between the solar wind and the geomagnetic disturbance, including both direct and time-delayed non-linear relations. In this study we especially consider the influence of varying the temporal size of the input-data sequence. The networks are trained on data covering 6600 h, and tested on data covering 2100 h. It is found that the initial and main phases of geomagnetic storms are well predicted, almost independent of the length of the input-data sequence. However, to predict the recovery phase, we have to use up to 20 h of solar-wind input data. The recovery phase is mainly governed by the ring-current loss processes, and is very much dependent on the ring-current history, and thus also the solar-wind history. With due consideration of the time history when optimizing the networks, we can reproduce 84% of the Dst variance.

Statistical downscaling of IPCC sea surface wind and wind energy predictions for U.S. east coastal ocean, Gulf of Mexico and Caribbean Sea

Science.gov (United States)

Yao, Zhigang; Xue, Zuo; He, Ruoying; Bao, Xianwen; Song, Jun

2016-08-01

A multivariate statistical downscaling method is developed to produce regional, high-resolution, coastal surface wind fields based on the IPCC global model predictions for the U.S. east coastal ocean, the Gulf of Mexico (GOM), and the Caribbean Sea. The statistical relationship is built upon linear regressions between the empirical orthogonal function (EOF) spaces of a cross- calibrated, multi-platform, multi-instrument ocean surface wind velocity dataset (predictand) and the global NCEP wind reanalysis (predictor) over a 10 year period from 2000 to 2009. The statistical relationship is validated before applications and its effectiveness is confirmed by the good agreement between downscaled wind fields based on the NCEP reanalysis and in-situ surface wind measured at 16 National Data Buoy Center (NDBC) buoys in the U.S. east coastal ocean and the GOM during 1992-1999. The predictand-predictor relationship is applied to IPCC GFDL model output (2.0°×2.5°) of downscaled coastal wind at 0.25°×0.25° resolution. The temporal and spatial variability of future predicted wind speeds and wind energy potential over the study region are further quantified. It is shown that wind speed and power would significantly be reduced in the high CO2 climate scenario offshore of the mid-Atlantic and northeast U.S., with the speed falling to one quarter of its original value.

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....

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.

A Joint Evaluation of the Wind and Wave Energy Resources Close to the Greek Islands

Directory of Open Access Journals (Sweden)

Daniel Ganea

2017-06-01

Full Text Available The objective of this work is to analyze the wind and wave energy potential in the proximity of the Greek islands. Thus, by evaluating the synergy between wind and waves, a more comprehensive picture of the renewable energy resources in the target area is provided. In this study, two different data sources are considered. The first data set is provided by the European Centre for Medium-Range Weather Forecasts (ECMWF through the ERA-Interim project and covers an 11-year period, while the second data set is Archiving, Validation and Interpretation of Satellite Oceanographic data (AVISO and covers six years of information. Using these data, parameters such as wind speed, significant wave height (SWH and mean wave period (MWP are analyzed. The following marine areas are targeted: Ionian Sea, Aegean Sea, Sea of Crete, Libyan Sea and Levantine Sea, near the coastal environment of the Greek islands. Initially, 26 reference points were considered. For a more detailed analysis, the number of reference points was narrowed down to 10 that were considered more relevant. Since in the island environments the resources are in general rather limited, the proposed work provides some outcomes concerning the wind and wave energy potential and the synergy between these two natural resources in the vicinity of the Greek islands. From the analysis performed, it can be noticed that the most energetic wind conditions are encountered west of Cios Island, followed by the regions east of Tinos and northeast of Crete. In these locations, the annual average values of the wind power density (Pwind are in the range of 286–298.6 W/m2. Regarding the wave power density (Pwave, the most energetic locations can be found in the vicinity of Crete, north, south and southeast of the island. There, the wave energy potential is in the range of 2.88–2.99 kW/m.

Profiles of Wind and Turbulence in the Coastal Atmospheric Boundary Layer of Lake Erie

KAUST Repository

Wang, H; Barthelmie, R J; Crippa, P; Doubrawa, P; Pryor, S C

2014-01-01

Prediction of wind resource in coastal zones is difficult due to the complexity of flow in the coastal atmospheric boundary layer (CABL). A three week campaign was conducted over Lake Erie in May 2013 to investigate wind characteristics and improve

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...

78 FR 15718 - Iberdrola Renewables, Inc. PacifiCorp NextEra Energy Resources, LLC Invenergy Wind North America...

Science.gov (United States)

2013-03-12

... DEPARTMENT OF ENERGY Federal Energy Regulatory Commission [Docket No. EL11-44-006] Iberdrola Renewables, Inc. PacifiCorp NextEra Energy Resources, LLC Invenergy Wind North America LLC Horizon Wind Energy LLC v. Bonneville Power Administration; Notice of Filing Take notice that on March 1, 2013...

Assessment of wind resources and annual energy production of wind farms

DEFF Research Database (Denmark)

the last 17 years. In Denmark the plan is to increase to 50% share of total electricity consumption in 2020 compared to 26% in 2011. In EU this was 6.3% in 2011. In EU new installed wind power was 9 GW and 0.8 GW, onshore and offshore, respectively, in 2011. The total capacity in Europe is 96 GW......Wind energy provides a significant share of EU’s renewable energy source. It is anticipated in the European Commission (EC), the International Energy Agency (IEA), and the European Wind Energy Association (EWEA) that wind energy expands further. Wind energy has had an annual growth of 15.6% during...

An analysis of wind and solar energy resources for the State of Kuwait

Science.gov (United States)

Alhusainan, Haya Nasser

Kuwait is an important producer of oil and gas. Its rapid socio-economic growth has been characterized by increasing population, high rates of urbanization, and substantial industrialization, which is transforming it into a large big energy consumer as well. In addition to urbanization, climatic conditions have played an important function in increasing demand for electricity in Kuwait. Electricity for thermal cooling has become essential in the hot desert climate, and its use has developed rapidly along with the economic development, urbanization, and population growth. This study examines the long-term wind and solar resources over the Kuwait to determine the feasibility of these resources as potential sustainable and renewable energy sources. The ultimate goal of this research is to help identify the potential role of renewable energy in Kuwait. This study will examine the drivers and requirements for the deployment of these energy sources and their possible integration into the electricity generation sector to illustrate how renewable energy can be a suitable resource for power production in Kuwait and to illustrate how they can also be used to provide electricity for the country. For this study, data from sixteen established stations monitored by the meteorological department were analyzed. A solar resource map was developed that identifies the most suitable locations for solar farm development. A range of different relevant variables, including, for example, electric networks, population zones, fuel networks, elevation, water wells, streets, and weather stations, were combined in a geospatial analysis to predict suitable locations for solar farm development and placement. An analysis of recommendations, future energy targets and strategies for renewable energy policy in Kuwait are then conducted. This study was put together to identify issues and opportunities related to renewable energy in the region, since renewable energy technologies are still limited in

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...

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.

Adjoint-based model predictive control of wind farms : Beyond the quasi steady-state power maximization

NARCIS (Netherlands)

Vali, M.; Petrović, Vlaho; Boersma, S.; van Wingerden, J.W.; Kuhn, Martin; Dochain, Denis; Henrion, Didier; Peaucelle, Dimitri

2017-01-01

In this paper, we extend our closed-loop optimal control framework for wind farms to minimize wake-induced power losses. We develop an adjoint-based model predictive controller which employs a medium-fidelity 2D dynamic wind farm model. The wind turbine axial induction factors are considered here

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

International Nuclear Information System (INIS)