One‐year observations of the wind distribution and low‐level jet occurrence at Braunschweig,North German Plain

A data set consisting of one‐year vertical profiles of horizontal wind speed obtained with lidar at Braunschweig Airport, North German Plain, is analyzed with respect to the low‐level jet (LLJ). The observations reveal a typical LLJ altitude between 80 and 360 m, a frequency of occurrence up to almost 9% for some altitudes, and a typical wind speed between 4 and 9 m s^?1. LLJ events occurred most frequently in summer during the night. In the winter, LLJs were observed both during day and night. The Weibull distribution for wind speed is presented for different heights. The most probable wind speed of the Weibull distribution increases from 4 m s^?1 at 40 m altitude to values exceeding 7 m s^?1 for altitudes above 240 m. There is a significant difference for the Weibull parameters determined with a monthly, seasonal and annual data set. The contribution of the LLJ to the overall wind speed distribution is analyzed. An LLJ event occurred on 52% of the days over the year, with a total measurement time of 739 h. As the typical rated speed for onshore wind turbines is in the range from 11.5 to 14.5 m s^?1 and the typical hub height is in the range of 100 to 150 m, it can be expected that wind turbines are affected by the LLJ. Copyright © 2015 John Wiley & Sons, Ltd.     

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.     

Wind shear coefficients and their effect on energy production

This paper provides realistic values of wind shear coefficients calculated using measured values of wind speed at 20, 30 and 40 m above the ground for the first time in Saudi Arabia in particular and, to the best of the authors’ knowledge, in the Gulf region in general. The paper also presents air density values calculated using the measured air temperature and surface pressure and the effects of wind shear factor on energy production from wind machines of different sizes. The measured data used in the study covered a period of almost three years between June 17, 1995 and December 1998. An overall mean value of wind shear coefficient of 0.194 can be used with confidence to calculate the wind speed at different heights if measured values are known at one height. The study showed that the wind shear coefficient is significantly influenced by seasonal and diurnal changes. Hence, for precise estimations of wind speed at a height, both monthly or seasonal and hourly or night time and day time average values of wind shear coefficient must be used. It is suggested that the wind shear coefficients must be calculated either (i) using long term average values of wind speed at different heights or (ii) using those half hourly mean values of wind speed for which the wind shear coefficient lies in the range ⩾0 and ⩽0.51. The air density, calculated using measured temperature and pressure was found to be 1.18 kg/m³. The air density values were also found to vary with the season of the year and hour of the day, and hence, care must be taken when precise calculations are to be made. The air density values, as shown in this paper, have no significant variation with height. The energy production analysis showed that the actual wind shear coefficient presented in this paper produced 6% more energy compared to that obtained using the 1/7 power law. Similarly, higher plant capacity factors were obtained with the wind shear factor of 0.194 compared to that with 0.143.     

Difficulties in using power laws for wind energy assessment

A 1/7 power law is often used to estimate atmospheric wind profiles. The use of this relationship, while perhaps appropriate in a climatological sense for daytime wind profiles in the lower atmosphere, frequently results in serious underestimates of wind speeds aloft at night. Several years of wind speed data from a 45 m tower and from use of a Doppler acoustic sounder (sodar) indicate that low-level wind speed maxima seem to form on 50 per cent of summer nights and 15 per cent of winter nights in northeastern Illinois. Even with 24 hr averages, the extrapolation of 6 m wind speeds to those at 45 m calculated with the 1/7 power law expression are found to be approximately 15 per cent too small, corresponding to a 40 per cent underestimate of wind power potential.     

Investigation of wind power density at different heights in the Gelibolu peninsula of Turkey

This study aims to determine the wind characteristics and wind power potential of the Gelibolu peninsula in the Çanakkale region of Turkey. For this purpose, hourly average wind data observed at the Gelibolu meteorological station were used. The Weibull probability density functions and Weibull parameters of time-series of wind speed, mean wind speed, and mean wind power potential were determined for different heights as 10, 20, 30, 40, and 50 m. According to the results obtained at 10- and 50-m heights above the ground level, the annual wind speed varied from 6.85 to 8.58 m/s in this region, respectively. The annual wind power potential of the site was determined as 407 and 800 W/m² for 10- and 50-m heights, respectively. These results indicate that the investigated site has a reasonable wind power potential for generating electricity.     

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.     

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.     

Estimation of wind speed profile using adaptive neuro-fuzzy inference system (ANFIS)

Wind energy has become a major competitor of traditional fossil fuel energy, particularly with the successful operation of multi-megawatt sized wind turbines. However, wind with reasonable speed is not adequately sustainable everywhere to build an economical wind farm. The potential site has to be thoroughly investigated at least with respect to wind speed profile and air density. Wind speed increases with height, thus an increase of the height of turbine rotor leads to more generated power. Therefore, it is imperative to have a precise knowledge of wind speed profiles in order to assess the potential for a wind farm site. This paper proposes a clustering algorithm based neuro-fuzzy method to find wind speed profile up to height of 100 m based on knowledge of wind speed at heights 10, 20, 30, 40 m. The model estimated wind speed at 40 m based on measured data at 10, 20, and 30 m has 3% mean absolute percent error when compared with measured wind speed at height 40 m. This close agreement between estimated and measured wind speed at 40 m indicates the viability of the proposed method. The comparison with the 1/7th law and experimental wind shear method further proofs the suitability of the proposed method for generating wind speed profile based on knowledge of wind speed at lower heights.     

Demonstrating the effect of vertical and directional shear for resource mapping of wind power

The use of wind energy is growing around the world, and its growth is set to continue into the foreseeable future. Estimates of the wind speed and power are helpful to assess the potential of new sites for development and to facilitate electric grid integration studies. In the present paper, wind speed and power resource mapping analyses are performed. These resource mappings are produced on a 13 km, hourly model grid over the entire continental USA for the years of 2006–2014. The effects of the rotor equivalent wind speed (REWS) along with directional shear are investigated. The total dataset (wind speed and power) contains ≈152,000 model grid points, with each location containing ≈78,000 hourly time steps. The resource mapping and dataset are created from analysis fields, which are output from an advanced weather assimilation model. Two different methods were used to estimate the wind speed over the rotor swept area (with rotor diameter of 100 m). First, using a single wind speed at hub height (80 m) and, second, the REWS with directional shear. The demonstration study shows that in most locations the incorporation of the REWS reduces the average available wind power. In addition, the REWS technique estimates more wind power production at night and less production in the day compared with the hub height technique; potentially critical for siting new wind turbines and plants. However, the wind power estimate differences are dependent on seasonality, diurnal cycle and geographic location. More research is warranted into these effects to determine the level at which these features are observed at actual wind plants.© 2015 The Authors. Wind Energy published by John Wiley & Sons, Ltd.     

MM5模式在大连近海风资源评估中的应用

利用中尺度MM5气象模式系统,对大连及其近海地区风场进行了较为系统的高分辨率数值模拟,定性及定量地得到了该地区10 m高度处的年平均风速等直线图、年有效风能小时数等值线图、年有效风能功率等值线图及长海地区的年风玫瑰图,进一步研究了该地区年有效风能功率密度沿垂直高度的变化。综合考虑该地区沿海水深、港口运输及水产养殖等因素的影响,建设性地提出了3个近海风能重点开发区域,并给出了这3个地区的年风速分布概率情况。基于MM5模式的数值评估结果,为该地区近海风资源的开发利用提供了重要的参考依据。     

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.     

A wind energy analysis of Grenada: an estimation using the ‘Weibull’ density function

The Weibull density function has been used to estimate the wind energy potential in Grenada, West Indies. Based on historic recordings of mean hourly wind velocity this analysis shows the importance to incorporate the variation in wind energy potential during diurnal cycles. Wind energy assessments that are based on Weibull distribution using average daily/seasonal wind speeds fail to acknowledge that wind speed probabilities can vary significantly during day and night. In particular where wind energy estimation is linked to electricity loads neglecting diurnal wind patterns can result in significant under/overestimation of wind power potential.     

Accounting for the speed shear in wind turbine power performance measurement

The current IEC standard for wind turbine power performance measurement only requires measurement of the wind speed at hub height assuming this wind speed to be representative for the whole rotor swept area. However, the power output of a wind turbine depends on the kinetic energy flux, which itself depends on the wind speed profile, especially for large turbines. Therefore, it is important to characterize the wind profile in front of the turbine, and this should be preferably achieved by measuring the wind speed over the vertical range between lower and higher rotor tips. In this paper, we describe an experiment in which wind speed profiles were measured in front of a multimegawatt turbine using a ground–based pulsed lidar. Ignoring the vertical shear was shown to overestimate the kinetic energy flux of these profiles, in particular for those deviating significantly from a power law profile. As a consequence, the power curve obtained for these deviant profiles was different from that obtained for the ‘near power law’ profiles. An equivalent wind speed based on the kinetic energy derived from the measured wind speed profile was then used to plot the performance curves. The curves obtained for the two kinds of profiles were very similar, corresponding to a significant reduction of the scatter for an undivided data set. This new method for power curve measurement results in a power curve less sensitive to shear. It is therefore expected to eventually reduce the power curve measurement uncertainty and improve the annual energy production estimation. Copyright © 2011 John Wiley & Sons, Ltd.     

Wind shear coefficients and energy yield for Dhahran, Saudi Arabia

This study presents calculated values of wind shear coefficients (WSE) using measured values of wind speed at 20, 30, and 40 m above ground level (AGL), for Dhahran, Saudi Arabia. The study also includes the air density estimated using measured air temperature and surface pressure and effect of wind shear coefficient on energy yield from a wind farm of 60 MW installed capacity developed using 40 wind turbines of 1500 kW size. The data used in the determination of wind shear coefficient covered a period of almost 5 years between 4 October 1995 and 30 November 2000.The study suggests a value of 0.189 of wind shear coefficient for the calculation of wind speed at different heights if measured values are known at one height. No regular seasonal trend was observed in the values of wind shear coefficients. In case of diurnal variation, higher values were observed during nighttime and early hours of the day and comparatively smaller values during day light hours. The air density, calculated using measured temperature and pressure was found to be 1.18 kg/m³. The energy yield obtained using RetScreen software, showed that the actual wind shear coefficient presented in this paper produced around 11–12% more energy compared to that obtained using 1/7 power law. Accordingly, 2–3% higher plant capacity factors were achieved using actual site-dependent wind shear coefficient instead of 1/7th wind power law exponent for the calculation of wind speed at hub-height.     

Classifying rotor‐layer wind to reduce offshore available power uncertainty

Rotor‐layer wind resource and turbine available power uncertainties prior to wind farm construction may contribute to significant increases in project risk and costs. Such uncertainties exist in part due to limited offshore wind measurements between 40 and 250 m and the lack of empirical methods to describe wind profiles that deviate from a priori, expected power law conditions. In this article, we introduce a novel wind profile classification algorithm that accounts for nonstandard, unexpected profiles that deviate from near power law conditions. Using this algorithm, offshore Doppler wind lidar measurements in the Mid‐Atlantic Bight are classified based on goodness‐of‐fit to several mathematical expressions and relative speed criteria. Results elucidate the limitations of using power law extrapolation methods to approximate average wind profile shape/shear conditions, as only approximately 18% of profiles fit well with this expression, while most consist of unexpected wind shear. Further, results demonstrate a relationship between classified profile variability and coastal meteorological features, including stability and offshore fetch. Power law profiles persist during unstable conditions and relatively weaker northeasterly flow from water (large fetch), whereas unexpected classified profiles are prevalent during stable conditions and stronger southwesterly flow from land (small fetch). Finally, the magnitude of the discrepancy between hub‐height wind speed and rotor equivalent wind speed available power estimates varies by classified wind‐profile type. During unexpected classified profiles, both a significant overprediction and underprediction of hub‐height wind available power is possible, illustrating the importance of accounting for site‐specific rotor‐layer wind shear when predicting available power.     

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.     

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 Morocco

The wind characteristics of 11 sites in the windy regions in Morocco have been analysed. The annual average wind speed for the considered sites ranged from 5 m/s to 10 m/s and the average power density from 100 W/m² to 1000 W/m², which might be suitable for electrical power production by installing wind farms. On an annual scale the observations of the distribution of hourly wind speed are better fitted by the Weibull hybrid distribution in contrast to the Weibull distribution.The wind power is estimated to be 1817 MW, that is to say, the exploitable wind energy is 15198 GWh, which represents theoretically 11% of the total consumed energy in Morocco in 1994.     

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.     

Market behaviour with large amounts of intermittent generation

This paper evaluates the impact of intermittent wind generation on hourly equilibrium prices and output, using data on expected wind generation capacity and demand for 2020. Hourly wind data for the period 1993–2005 are used to obtain wind output generation profiles for thirty regions (onshore and offshore) across Great Britain. Matching the wind profiles for each month to the actual hourly demand (scaled to possible 2020 values), we find that the volatility of prices will increase, and that there is significant year-to-year variation in generators’ profits. Above-average wind speeds lead to below-average prices, but annual revenues for British wind generators (producing more in the winter) are almost as great as for base-load generators. In the presence of significant market power (the equivalent of two symmetric firms owning fossil-fuelled capacity, rather than six), the level of prices more than doubled, and their volatility increased. However, wind generators’ average revenues rose by 20% less than those of base-load plant.