A new method for improved hub height mean wind speed estimates using short-term hub height data

The estimation of the wind resource at the hub height of a wind turbine is one of the primary goals of site assessment. Because the measurement heights of meteorological towers (met towers) are typically significantly lower than turbine hub heights, a shear model is generally needed to extrapolate the measured wind resource at the lower measurement height to the hub height of the turbine. This paper presents methods for improving the estimate of the hub height wind resource from met tower data through the use of ground-based remote sensing devices. The methods leverage the two major advantages of these devices: their portability and their ability to measure at the wind turbine hub height. Specifically, the methods rely on augmenting the one year of met tower measurements with short-term measurements from a ground-based remote sensing device. The results indicate that the methods presented are capable of producing substantial improvements in the accuracy and uncertainty of shear extrapolation predictions. The results suggest that the typical site assessment process can be reevaluated, and alternative strategies that utilize ground-based remote sensing devices can be incorporated to significantly improve the process.     

Wind energy resource assessment for the Fiji Islands: Kadavu Island and Suva Peninsula

Wind energy assessment of two sites in the Fiji Islands is presented. The wind resource of the remote island of Kadavu is analysed along with the urban Suva Peninsula. The former has average (mean) wind speeds of 3.59 ms⁻¹and 3.88 ms^-1 at 20 m and 34 m above ground level (AGL). The latter has average wind speeds of 5.65 ms^-1 and 6.38 ms^-1, respectively. The prevailing wind direction for both the sites corresponds to the South-East winds. A wind shear analysis shows the variations in wind speeds during different periods of the day for the Suva site. A high resolution wind resource map of both the sites is simulated using the WAsP software for a radius of 5 km. The WasP analysis indicates good wind power development potential for Kadavu is for the windward side of the Kadavu ridge in the eastern region. The Suva Peninsula site showed good wind power development potential for the Laucala Bay area. A power analysis using the Vestas V27 225 kW turbine is carried out for the specific sites.     

Properties of the offshore low level jet and rotor layer wind shear as measured by scanning Doppler Lidar

The atmospheric flow phenomenon known as the Low Level Jet (LLJ) is an important source of wind power production in the Great Plains. However, due to the lack of measurements with the precision and vertical resolution needed, particularly at rotor heights, it is not well‐characterized or understood in offshore regions being considered for wind‐farm development. The present paper describes the properties of LLJs and wind shear through the rotor layer of a hypothetical wind turbine, as measured from a ship‐borne Doppler lidar in the Gulf of Maine in July–August 2004. LLJs, frequently observed below 600 m, were mostly during nighttime and transitional periods, but they were also were seen during some daytime hours. The presence of a LLJ significantly modified wind profiles producing vertical wind speed shear. When the wind shear was strong, the estimates of wind power based upon wind speeds measured at hub‐height could have significant errors. Additionally, the inference of hub‐height winds from near‐surface measurements may introduce further error in the wind power estimate. The lidar dataset was used to investigate the uncertainty of the simplified power‐law relation that is often employed in engineering approaches for the extrapolation of surface winds to higher elevations. The results show diurnal and spatial variations of the shear exponent empirically found from surface and hub‐height measurements. Finally, the discrepancies between wind power estimates using lidar‐measured hub‐height winds and rotor equivalent winds are discussed. Copyright © 2016 John Wiley & Sons, Ltd.     

Evaluating winds and vertical wind shear from Weather Research and Forecasting model forecasts using seven planetary boundary layer schemes

The existence of vertical wind shear in the atmosphere close to the ground requires that wind resource assessment and prediction with numerical weather prediction (NWP) models use wind forecasts at levels within the full rotor span of modern large wind turbines. The performance of NWP models regarding wind energy at these levels partly depends on the formulation and implementation of planetary boundary layer (PBL) parameterizations in these models. This study evaluates wind speeds and vertical wind shears simulated by the Weather Research and Forecasting model using seven sets of simulations with different PBL parameterizations at one coastal site over western Denmark. The evaluation focuses on determining which PBL parameterization performs best for wind energy forecasting, and presenting a validation methodology that takes into account wind speed at different heights. Winds speeds at heights ranging from 10 to 160 m, wind shears, temperatures and surface turbulent fluxes from seven sets of hindcasts are evaluated against observations at Høvsøre, Denmark. The ability of these hindcast sets to simulate mean wind speeds, wind shear, and their time variability strongly depends on atmospheric static stability. Wind speed hindcasts using the Yonsei University PBL scheme compared best with observations during unstable atmospheric conditions, whereas the Asymmetric Convective Model version 2 PBL scheme did so during near‐stable and neutral conditions, and the Mellor–Yamada–Janjic PBL scheme prevailed during stable and very stable conditions. The evaluation of the simulated wind speed errors and how these vary with height clearly indicates that for wind power forecasting and wind resource assessment, validation against 10 m wind speeds alone is not sufficient. Copyright © 2012 John Wiley & Sons, Ltd.     

风切变指数在风电场风资源评估中的应用

以内蒙古地区3座70m高测风塔连续2年的实测数据来分析风切变指数的变化,结果表明:1)不同高度梯度的风切变指数受地面粗糙度及周围地形地貌的影响较大。2)计算相邻高度的风速时,采用相邻高度间的风切变指数计算得到的结果较好;计算相差较大的高度间风速时,采用拟合曲线得到的风切变指数计算得到的结果较好。3)利用3～25m/s的风切变指数计算各月风速及年均风速结果都与实测值最接近;而利用全部风速数据的风切变指数计算统计各月风速往往比实测值偏大;利用3～25m/s拟合曲线得到的风切变指数统计各月风速比实测值偏小。     

平坦地形风剪切特性的研究

研究了山东、江苏、河南等区域平坦地形风剪切的特性,包括风切变指数随高度的变化、日内变化以及月变化特性。通过分析150 m高度测风塔完整年的数据,发现不同区域风切变指数随高度呈现不同的变化特性,即：最高层风切变指数最小,100～150 m高度风切变指数变化平缓,次高层约130 m风切变指数减小、风切变指数随高度呈现波动的特性。风切变指数的日内变化呈中午前后较小、夜间及凌晨较大的特点,且该规律在100 m高度以下尤其显著。风切变指数的月变化在100 m高度以上无规律性,在100 m高度以下呈平缓增加和波动的特性。     

Quantifying sources of uncertainty in reanalysis derived wind speed

Reanalysis data are attractive for wind-power studies because they can offer wind speed data for large areas and long time periods and in locations where historical data are not available. However, reanalysis-predicted wind speeds can have significant uncertainties and biases relative to measured wind speeds. In this work we develop a model of the bias and uncertainty of CFS reanalysis wind speed than can be used to correct the data and identify sources of error. We find the CFS reanalysis data underestimate wind speeds at high elevations, at high measurement heights, and in unstable atmospheric conditions. For example, at a site with an elevation of 500 m and hub height of 80 m, a CFS reanalysis wind speed of 8 m/s is 0.2 m/s higher to 1.3 m/s lower than the measured wind speed. We also find a seasonal bias that correlates with surface roughness length used by the reanalysis model during the spring season. The corrections we propose reduce the average bias of reanalysis wind speed extrapolated to hub height to nearly zero, an improvement of 0.3–0.9 m/s. These corrections also reduce the RMS error by 0.1–0.4 m/s, a small improvement compared to the uncorrected RMS errors of 1.5–2.4 m/s.     

The influence of the wind speed profile on wind turbine performance measurements

To identify the influence of wind shear and turbulence on wind turbine performance, flat terrain wind profiles are analysed up to a height of 160 m. The profiles' shapes are found to extend from no shear to high wind shear, and on many occasions, local maxima within the profiles are also observed. Assuming a certain turbine hub height, the profiles with hub‐height wind speeds between 6 m s^?1 and 8 m s^?1 are normalized at 7 m s^?1 and grouped to a number of mean shear profiles. The energy in the profiles varies considerably for the same hub‐height wind speed. These profiles are then used as input to a Blade Element Momentum model that simulates the Siemens 3.6 MW wind turbine. The analysis is carried out as time series simulations where the electrical power is the primary characterization parameter. The results of the simulations indicate that wind speed measurements at different heights over the swept rotor area would allow the determination of the electrical power as a function of an ‘equivalent wind speed’ where wind shear and turbulence intensity are taken into account. Electrical power is found to correlate significantly better to the equivalent wind speed than to the single point hub‐height wind speed. Copyright © 2008 John Wiley & Sons, Ltd.     

Wind energy analysis based on turbine and developed site power curves: A case-study of Darling City

The observed wind at a given site varies continuously as a function of time and season, increasing hub heights, topography of the terrain, prevailing weather condition etc. The quality of wind resource is one of the important site factors to be considered when assessing the wind potential of any location for any energy project. In this study, two wind energy analysis techniques are presented: the use of direct technique where the electrical power outputs of the wind turbines at a time t are estimated using the turbine power curve(s) and the use of statistical-based technique where the power outputs are estimated based on the developed site power curve(s). The wind resource assessment at Darling site is conducted using a 5-min time series weather data collected on a 10 m height over a period of 24 months. Because of the non-linearity of the site's wind speed and its corresponding power output, the wind resources are modeled and the developed site power curve(s) are used to estimate the long term energy outputs of the wind turbines for changing weather conditions. Three wind turbines rating of 1.3 MW, 1.3 MW and 1.0 MW were selected for the energy generation based on the gauged wind resource(s) at 50, 60 and 70 m heights, respectively. The energy outputs at 50 m height using the 1.3 MW WT were compared to the energy outputs at 60 m to determine the standard height for utility scale energy generation at this site. An additional energy generation of 190.71 MWh was available by deploying the same rated turbine at a 60 m height. Furthermore, comparisons were made between the use of turbine and site power curve for wind energy analysis at the considered heights. The results show that the analysis of the energy outputs of the WTs based on the site power curve is an accurate technique for wind energy analysis as compared to the turbine power curve. Conclusions are drawn on the suitability of this site for utility scale generation based on the wind resources evaluation at different heights.     

Optimization of turbine design in wind farms with multiple hub heights,using exact analytic gradients and structural constraints

Wind farms are generally designed with turbines of all the same hub height. If wind farms were designed with turbines of different hub heights, wake interference between turbines could be reduced, lowering the cost of energy (COE). This paper demonstrates a method to optimize onshore wind farms with two different hub heights using exact, analytic gradients. Gradient‐based optimization with exact gradients scales well with large problems and is preferable in this application over gradient‐free methods. Our model consisted of the following: a version of the FLOw Redirection and Induction in Steady‐State wake model that accommodated three‐dimensional wakes and calculated annual energy production, a wind farm cost model, and a tower structural model, which provided constraints during optimization. Structural constraints were important to keep tower heights realistic and account for additional mass required from taller towers and higher wind speeds. We optimized several wind farms with tower height, diameter, and shell thickness as coupled design variables. Our results indicate that wind farms with small rotors, low wind shear, and closely spaced turbines can benefit from having two different hub heights. A nine‐by‐nine grid wind farm with 70‐meter rotor diameters and a wind shear exponent of 0.08 realized a 4.9% reduction in COE by using two different tower sizes. If the turbine spacing was reduced to 3 diameters, the reduction in COE decreased further to 11.2%. Allowing for more than two different turbine heights is only slightly more beneficial than two heights and is likely not worth the added complexity.     

Evaluation of three mainstream numerical weather prediction models with observations from meteorological mast IJmuiden at the North Sea

Numerical weather prediction models play an important role in the field of wind energy, for example, in power forecasting, resource assessment, wind farm (wake) simulations, and load assessment. Continuous evaluation of their performance is crucial for successful operations and further understanding of meteorology for wind energy purposes. However, extensive offshore observations are rarely available. In this paper, we use unique met mast and Lidar observations up to 315 m from met mast “IJmuiden,” located in the North Sea 85 km off the Dutch coast, to evaluate the representation of wind and other relevant variables in three mainstream meteorological models: ECMWF‐IFS, HARMONIE‐AROME, and WRF‐ARW, for a wide range of weather conditions. Overall performance for hub‐height wind speed is found to be comparable between the models, with a systematic wind speed bias <0.5 m/s and random wind speed errors (centered RMSE) <2 m/s. However, the model performance differs considerably between cases, with better performance for strong wind regimes and well‐mixed wind and potential temperature profiles. Conditions characterized by moderate wind speeds combined with stable stratification, which typically produce substantial wind shear and power fluctuations, lead to the largest misrepresentations in all models.     

Evaluating the impact of wind induced roughness change and tidal range on extrapolation of offshore vertical wind speed profiles

Wind energy resource estimation frequently requires extrapolation of wind speeds from typical measurement heights to turbine hub‐heights. However, this extrapolation is uncertain, and this uncertainty is exacerbated in the offshore environment by the effect of the dynamic surface (i.e. surface roughness and height respond to wind speed or vary over time). This paper examines the impact of roughness variations and small tidal ranges on mean predicted wind speeds in near‐neutral conditions. Roughness variations offshore are in the range 0.002 and 0.00002 m. This range of roughnesses gives a difference in predicted wind speed extrapolated from 10 to 50 m of less than 8%. For a more typical range of 0.0005 tp 0.00005 m, the difference will be smaller (～3%). With a tidal range of 4 m the difference in mean wind speed extrapolated from 10 to 50 m height is about 1%. Copyright © 2001 John Wiley & Sons, Ltd.     

Assessment of wind energy potentiality at Kudat and Labuan, Malaysia using Weibull distribution function

The wind resource is a crucial step in planning a wind energy project and detailed knowledge of the wind characteristic at a site is needed to estimate the performance of a wind energy project. In this paper, with the help of 2-parameter Weibull distribution, the assessment of wind energy potentiality at Kudat and Labuan in 2006-2008 was carried out. “WRPLOT” software has been used to show the wind direction and resultant of the wind speed direction. The monthly and yearly highest mean wind speeds were 4.76 m/s at Kudat and 3.39 m/s at Labuan respectively. The annual highest values of the Weibull shape parameter (k) and scale parameter (c) were 1.86 and 3.81 m/s respectively. The maximum wind power density was found to be 67.40 W/m² at Kudat for the year 2008. The maximum wind energy density was found to be 590.40 kWh/m²/year at Kudat in 2008. The highest most probable wind speed and wind speed carrying maximum energy were estimated 2.44 m/s at Labuan in 2007 and 6.02 m/s at Kudat in 2007. The maximum deviation, at wind speed more than 2 m/s, between observed and Weibull frequency distribution was about 5%. The most probable wind directions (blowing from) were 190° and 269° at Kudat and Labuan through the study years. From this study, it is concluded that these sites are unsuitable for the large-scale wind energy generation. However, small-scale wind energy can be generated at the turbine height of 100 m.     

Feasibility study of harnessing wind energy for turbine installation in province of Yazd in Iran

This paper analyses the wind speed of some major cities in province of Yazd which is located in central part of Iran. Also, the feasibility study of implementing wind turbines to take advantage of wind power is reviewed and then the subject of wind speed and wind potential at different stations is considered. This paper utilized wind speed data over a period of almost 13 years between 1992 and 2005 from 11 stations, to assess the wind power potential at these sites. In this paper, the hourly measured wind speed data at 10 m, 20 m and 40 m height for Yazd province have been statically analyzed to determine the potential of wind power generation. Extrapolation of the 10 m data, using the Power Law, has been used to determine the wind data at heights of 20 m and 40 m. The results showed that most of the stations have annual average wind speed of less than 4.5 m/s which is considered as unacceptable for installation of the wind turbines. City of Herat has higher wind energy potential with annual wind speed average of 5.05 m/s and 6.86 m/s, respectively, at height of 10 m and 40 m above ground level (AGL). This site is a good candidate for remote area wind energy applications. But some more information is required, because the collected data for Herat is only for 2004. Cities of Aghda with 3.96 m/s, Gariz with 3.95 m/s, and Maybod with 3.83 m/s annual wind speed average at height of 10 m above ground level are also able to harness wind by installing small wind turbines. The Tabas and Bafgh sites wind speed data indicated that the two sites have lower annual wind speed averages between 1.56 m/s and 2.22 m/s at 10 m height. The monthly and annual wind speeds at different heights have been studied to ensure optimum selection of wind turbine installation for different stations in Yazd.     

Wind characteristics and wind energy potential in western Nevada

The wind potential in western Nevada was assessed by using wind, temperature, and pressure data over a period of four and half years from four 50 m tall towers. The seasonal wind patterns for all towers show a maximum during the spring season. Diurnal wind speed patterns for all seasons and months showed a minimum during the late morning and a maximum during the late afternoon. The highest values are during the spring season with multi-annual hourly wind speeds at or above 8 m/s and relative frequency of the wind speed in the optimum turbine range (5–25 m/s) of 70% or higher for the Tonopah tower, with lower values for the other three towers. The monthly power law index values are lower than the standard value 0.147 (in general 0.13 or lower). The hourly turbulence intensities were higher at lower elevations, with values of about 0.35 or higher at the 10 m level and at lower wind speed range (5.0 m/s or less). Higher turbulence intensities were found for all towers and heights during the spring and summer seasons and lower values during the rest of the year. The daily gust factor for the 2003–2007 composite data sets shows low probabilities (2% or less) of the wind gusts exceeding 25 m/s.     

Airborne wind energy: Optimal locations and variability

This paper explores the global wind power potential of Airborne Wind Energy (AWE), a relatively new branch of renewable energy that utilizes airborne tethered devices to generate electricity from the wind. Unlike wind turbines mounted on towers, AWE systems can be automatically raised and lowered to the height of maximum wind speeds, thereby providing a more temporally consistent power production. Most locations on Earth have significant power production potential above the height of conventional turbines. The ideal candidates for AWE farms, however, are where temporally consistent and high wind speeds are found at the lowest possible altitudes, to minimize the drag induced by the tether. A criterion is introduced to identify and characterize regions with wind speeds in excess of 10 m s⁻¹ occurring at least 15% of the time in each month for heights below 3000 m AGL. These features exhibit a jet-like profile with remarkable temporal constancy in many locations and are termed here “wind speed maxima” to distinguish them from diurnally varying low-level jets. Their properties are investigated using global, 40 km-resolution, hourly reanalyses from the National Center for Atmospheric Research's Climate Four Dimensional Data Assimilation, performed over the 1985–2005 period. These wind speed maxima are more ubiquitous than previously thought and can have extraordinarily high wind power densities (up to 15,000 W m⁻²). Three notable examples are the U.S. Great Plains, the oceanic regions near the descending branches of the Hadley cells, and the Somali jet offshore of the horn of Africa. If an intermediate number of AWE systems per unit of land area could be deployed at all locations exhibiting wind speed maxima, without accounting for possible climatic feedbacks or landuse conflicts, then several terawatts of electric power (1 TW = 10¹² W) could be generated, more than enough to provide electricity to all of humanity.     

Extrapolating wind speed time series vs. Weibull distribution to assess wind resource to the turbine hub height: A case study on coastal location in Southern Italy

Increasing knowledge on wind shear models to strengthen their reliability appears as a crucial issue, markedly for energy investors to accurately predict the average wind speed at different turbine hub heights, and thus the expected wind energy output. This is particularly helpful during the feasibility study to abate the costs of a wind power project, thus avoiding installation of tall towers, or even more expensive devices such as LIDAR or SODAR.The power law (PL) was found to provide the finest representation of wind speed profiles and is hence the focus of the present study. Besides commonly used for vertical extrapolation of wind speed time series, the PL relationship between “instantaneous” wind profiles was demonstrated by Justus and Mikhail to be consistent with the height variation of Weibull distribution. Therefore, in this work a comparison is performed between these two different PL–based extrapolation approaches to assess wind resource to the turbine hub height: (i) extrapolation of wind speed time series, and (ii) extrapolation of Weibull wind speed distribution. The models developed by Smedman–Högström and Högström (SH), and Panofsky and Dutton (PD) were used to approach (i), while those from Justus and Mikhail (JM) and Spera and Richards (SR) to approach (ii). Models skill in estimating wind shear coefficient was also assessed and compared.PL extrapolation models have been tested over a flat and rough location in Apulia region (Southern Italy), where the role played by atmospheric stability and surface roughness, along with their variability with time and wind characteristics, has been also investigated. A 3-year (1998–2000) 1–h dataset, including wind measurements at 10 and 50 m, has been used. Based on 10–m wind speed observations, the computation of 50–m extrapolated wind resource, Weibull distribution and energy yield has been made. This work is aimed at proceeding the research issue addressed within a previous study, where PL extrapolation models were tested and compared in extrapolating wind resource and energy yield from 10 to 100 m over a complex–topography and smooth coastal site in Tuscany region (Central Italy). As a result, wind speed time series extrapolating models proved to be the most skilful, particularly PD, based on the similarity theory and thus addressing all stability conditions. However, comparable results are returned by the empirical JM Weibull distribution extrapolating model, which indeed proved to be preferable as being: (i) far easier to be used, as z₀–, stability–, and wind speed time series independent; (ii) more conservative, as wind energy is underpredicted rather than overpredicted.     

Preliminary results from a network of stations for wind resource assessment at North of Yucatan Peninsula

In order to increase the use of the wind as energy source is essential to study the periodical patterns of the wind resources by means of high quality data obtained from measurement stations, specially configured to evaluate the energy available in the wind. The work presented in this paper shows the preliminary results of a network of ultrasonic wind sensors which were installed and operated by the Autonomous University of Yucatan. Located in the tropical region at Eastern of Mexico, the research zone have been studied previously just by means of wind data measured at local meteorological stations and observatories. The developed measurement network includes six stations with towers between 40 m and 50 m height located around an important region of the North side of the Yucatan Peninsula. The preliminary results have shown a highly directional behaviour of the winds with better wind resources in the sites located on the coastline.     

A surface-layer wind speed correction: A case-study of Darling station

In previous study, the vertical wind speed extrapolation from measurement station to modern turbine hubs over an open homogenous terrain was considered. It was presented that an assumption of wind shear exponent under different stability conditions was an inaccurate representation of the actual wind climates as the precise knowledge of the site's wind characteristics at different levels and seasons are essential for planning and implementation of a proposed energy project. In this study, the surface-layer wind speed correction at Darling using the WRF modeling with mesoscale terrain corrections is presented. An hourly mesoscale modeled winds at 3 km grid spacing obtained for one month are postprocessed for estimation of local wind speed profiles at 10 and 50 m height AGL. The sensitivity of the modeled winds to surface terrain corrections is investigated using mesoscale topography parameterizations. Furthermore, 6-hourly mesoscale modeled and satellite observed winds as well as measurements from Darling station are utilized for validation of the statistical downscaling method utilized for the postprocessing of the boundary layer winds over land. It is presented that the precision of the mesoscale modeled winds for local wind speed estimates at potential site without historical measurements can be significantly improved. The confidence in the validity of this methodology for local wind speed correction is estimated at 96–98%.     

Climatic conditions for operation of wind turbines in Hungary

According to wind-climatic requirement of wind farms wind speed should exceed the so called cut-in speed. If this inequality is realized then regarding the wind-climatic features of Hungary the following conditions may occur: the wind turbine is operating with high probability, energy is generated; it is working in a regulated mode with low probability; it is not working with very low probability. Therefore in terms of continuous energy production by wind one question arises: are there any temporal and/or orographic shifts in different heights compared to the wind-climatic condition mentioned above. In this paper this question is analyzed on the basis of seven Hungarian meteorological stations that have hourly measured wind speed data considering the period between 1991 and 2000. The probability of wind speeds exceeding 3 m/s, statistics of wind speed intervals higher and lower than 3 m/s and statistics of average hourly wind speed intervals higher than 3 m/s were analyzed at the heights of 10, 30 and 60 m. A statistical parameter that is proportional to the average specific wind power of a day in a time period was defined and, its connection to the average length of those intervals that have higher or equal hourly average wind speeds more than 3 m/s in a given month was investigated. With the help of such parameters the value of monthly average specific wind power can be estimated.