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.     

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.     

2. Outline of the Commission's Wind Energy R&D Programme

Wind speed data (in metres per second) and direction (in degrees) were recorded at hourly intervals for a period of 1 year from September 2004 to August 2005 at two mast heights of 10 and 25 m. The data recorded were analysed and the regional wind climate determined using the WAsP 8.2 program and a vector map of the region covering 12×12 km. The orography of the area was characterised by elevation contours at 5 m intervals. On the basis of details obtained from the aerial photographic images, the roughness classes were also assigned. The time series wind data were analysed and the Weibull distribution for the two projected heights of 50 and 70 m as per the requirement of the proposed wind turbine generator (WTG) was evaluated. It is seen that the annual energy production in the area from 1 MW WTG is 3.712 GWh at 50 m hub height and 4.431 GWh at 70 m hub height, indicating a satisfactory wind energy generation potential. This paper describes the methodology adopted for the evaluation of wind energy potential for the site.     

Designing an index for assessing wind energy potential

To meet the increasing global demand for renewable energy, such as wind energy, an increasing number of wind parks are being constructed worldwide. Finding a suitable location requires a detailed and often costly analysis of local wind conditions. Plain average wind speed maps cannot provide a precise forecast of wind power because of the non-linear relationship between wind speed and production. We suggest a new approach to assess the local wind energy potential. First, meteorological reanalysis data are applied to obtain long-term low-scale wind speed data at specific turbine locations and hub heights. Second, the relation between wind data and energy production is determined via a five parameter logistic function using actual high-frequency energy production data. The resulting wind energy index allows for a turbine-specific estimation of the expected wind power at an unobserved location. A map of the wind power potential for Germany exemplifies our approach.     

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.     

Impact of low‐level wind maxima below hub height on wind turbine sound propagation

An analysis of the effect of low‐level wind maxima (LLWM) below hub height on sound propagating from wind turbines has been performed at a site in northern Sweden. The stably stratified boundary layer, which is typical for cold climates, commonly features LLWM. The simplified concept for the effects of refraction, based on the logarithmic wind profile or other approaches where the wind speed is continuously increasing with height, is often not applicable there. Long‐term meteorological measurements in the vicinity of a wind farm were therefore used to identify LLWM. Sound measurements were conducted simultaneously to the meteorological measurements. LLWM below hub height decrease the sound level close to the surface downwind of the wind farm. This effect increases with increasing strength of the LLWM. The occurrence of LLWM as well as strength and height of the LLWM are dependent on the wind direction.     

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.     

Investigation of wind shear coefficients and their effect on electrical energy generation

Wind measurements are generally performed below wind turbine hub heights due to higher measurement and tower costs. In order to obtain the wind speed at the hub height of the turbine, the measurements are extrapolated, assuming that the wind shear is constant. This assumption may result in some critical errors between the estimated and actual energy outputs. In this paper wind data collected in Bal?kesir from October 2008 to September 2009, has been used to show the effects of wind shear coefficient on energy production. Results of the study showed that, the difference between wind energy production using extrapolated wind data and energy production using measured wind data at hub height may be up to 49.6%.     

Worldwide wind energy status and the characteristics of wind energy in Iran,case study: the province of Sistan and Baluchestan

In this paper, the recent trend of the worldwide wind energy utilisation is reviewed and the recent activities in using renewable energy sources in Iran are explained. As a case study, the wind characteristics of the province of Sistan and Baluchestan are statistically analysed. The wind characteristics such as the monthly mean wind speed and the wind power density of each station are presented. The monthly variation of the wind direction is presented and also the dominant wind direction is shown in a wind rose diagram. The values of turbulence intensity at different heights are calculated. The results show that the stations of Khash and Nosratabad are more suitable for limited off-grid utility applications. Lootak with the average annual wind power density of 388?W?m^?2 at the height of 40?m and constant wind direction is recommended for large-scale grid-connected wind turbines.     

Investigation of wind energy potentials in Brunei Darussalam

Conventional power generation mainly depends on natural gas and diesel oil in Brunei Darussalam. The power utility company is now thinking of power generation using natural wind. In this paper, wind energy, being one of the most readily available renewable energy sources, was studied. The wind characteristic, velocity and directions were studied using Weibull distribution based on the measurement of wind speed at two different locations in Brunei Darussalam. These wind speed distributions were modeled using the Wind Power program. The wind rose graph was obtained for the wind direction to analyze the wind power density onshore and offshore. Based on this analysis, it has been found that the wind speed of 3 to 5 m/s has a probability of occurrence of 40%. Besides, the annual energy production at a wind speed of 5 m/s has been found to be in the range between 1000 and 1500 kWh for both the locations in Brunei Darussalam.     

Sensitivity of southern California wind energy to turbine characteristics

Using output from a high‐resolution meteorological simulation, we evaluate the sensitivity of southern California wind energy generation to variations in key characteristics of current wind turbines. These characteristics include hub height, rotor diameter and rated power, and depend on turbine make and model. They shape the turbine's power curve and thus have large implications for the energy generation capacity of wind farms. For each characteristic, we find complex and substantial geographical variations in the sensitivity of energy generation. However, the sensitivity associated with each characteristic can be predicted by a single corresponding climate statistic, greatly simplifying understanding of the relationship between climate and turbine optimization for energy production. In the case of the sensitivity to rotor diameter, the change in energy output per unit change in rotor diameter at any location is directly proportional to the weighted average wind speed between the cut‐in speed and the rated speed. The sensitivity to rated power variations is likewise captured by the percent of the wind speed distribution between the turbines rated and cut‐out speeds. Finally, the sensitivity to hub height is proportional to lower atmospheric wind shear. Using a wind turbine component cost model, we also evaluate energy output increase per dollar investment in each turbine characteristic. We find that rotor diameter increases typically provide a much larger wind energy boost per dollar invested, although there are some zones where investment in the other two characteristics is competitive. Our study underscores the need for joint analysis of regional climate, turbine engineering and economic modeling to optimize wind energy production. Copyright © 2012 John Wiley & Sons, Ltd.     

Potential wind power generation in the State of Kuwait

The wind characteristics of six locations in the State of Kuwait have been assessed. The annual average wind speed for the considered sites ranged from 3.7 to 5.5 m/s and a mean wind power density from 80 to 167 W/m² at standard height of 10 m. The Weibull parameters and power density of each station have been determined using Weibull distribution. The wind data at heights 15, 20, 25 and 30 m were obtained by extrapolation of the 10 m data using the Power-Law. The potential wind energy at different heights was estimated using Weibull parameters. Maximum power density is found at 30 m height which varies between 130 and 275 W/m² with 70% increase from the standard height indicating fairly potential wind energy especially in the northern part of the country. The highest potential wind power was found during the summer season which is the peak demand season of electricity in Kuwait.     

Coherent Doppler lidar for wind farm characterization

Coherent Doppler lidar measurements are of increasing interest for the wind energy industry. Wind measurements are fundamental inputs for the evaluation of potential energy yield and performance of wind farms. Three‐dimensional scanning Doppler lidar may provide a new basis for wind farm site selection, design and optimization. In this paper, the authors discuss Doppler lidar measurements obtained for a wind energy development. The possibility of using lidar measurements to more fully characterize the wind field is discussed, specifically terrain effects, spatial variation of winds, power density and the effect of shear at different layers within the rotor swept area. Vector retrieval methods have been applied to the lidar data, and results are presented on an elevated terrain‐following surface at hub height. The vector retrieval estimates are compared with tower measurements, after interpolation to the appropriate level. Doppler lidar data are used to estimate the spatial power density at hub height (for the period of the deployment). An example wind farm layout is presented for demonstration purposes based purely on lidar measurement, even though the lidar data acquisition period cannot be considered climatological. The strength of this approach is the ability to directly measure spatial variations of the wind field over the wind farm. Also, because Doppler lidar can measure winds at different vertical levels, an approach for estimating wind power density over the rotor swept area (rather than only the hub height) is explored. Finally, advanced vector retrieval algorithms have been applied to better characterize local wind variations and shear. Copyright © 2012 John Wiley & Sons, Ltd.     

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.     

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.     

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.     

Do we really need rotor equivalent wind speed?

The use of the rotor equivalent wind speed for determination of power curves and annual energy production for wind turbines is advocated in the second edition of the IEC 61400‐12‐1 standard. This requires the measurements of wind speeds at different heights, for which remote sensing equipment is recommended in addition to meteorological masts. In this paper, we present a theoretical analysis that shows that the relevance of the rotor equivalent wind speed method depends on turbine dimensions and wind shear regime. For situations where the ratio of rotor diameter and hub height is smaller than 1.8, the rotor equivalent wind speed method is not needed if the wind shear coefficient at the location of the wind turbine has a constant value between ?0.05 and 0.4: in these cases, the rotor equivalent wind speed and the wind speed at hub height are within 1%. For complex terrains with high wind shear deviations are larger. The effect of non‐constant wind shear exponent, ie, different wind shear coefficients for lower and upper half of the rotor swept area especially at offshore conditions is limited to also about 1%.     

Feasibility study of wind energy potential in two provinces of Iran: North and South Khorasan

In this study, the measured wind speed data for year 2007 at 10 m, 30 m and 40 m heights for two provinces of Iran, North and South Khorasan, have been statistically analyzed to determine the potential of wind power generation. This paper presents the wind energy potential at four zones in these provinces, Bojnourd, Esfarayen of North Khorasan province and Nehbandan, and Fadashk of South Khorasan province. The objective is to evaluate the most important characteristic of wind energy in the studied sites. The statistical attitudes permit us to estimate the mean wind speed, the wind speed distribution function, the mean wind power density in the sites at the height of 10 m, 30 m and 40 m. Also, three new types of wind rose diagrams were shown.