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.     

Copula-based joint distribution analysis of wind speed and wind direction: Wind energy development for Hong Kong

Accurate and reliable assessment of wind energy potential has important implication to the wind energy industry. Most previous studies on wind energy assessment focused solely on wind speed, whereas the dependence of wind energy on wind direction was much less considered and documented. In this paper, a copula-based method is proposed to better characterize the direction-related wind energy potential at six typical sites in Hong Kong. The joint probability density function (JPDF) of wind speed and wind direction is constructed by a series of copula models. It shows that Frank copula has the best performance to fit the JPDF at hilltop and offshore sites while Gumbel copula outperforms other models at urban sites. The derived JPDFs are applied to estimate the direction-related wind power density at the considered sites. The obtained maximum direction-related wind energy density varies from 41.3 W/m² at an urban site to 507.9 W/m² at a hilltop site. These outcomes are expected to facilitate accurate micro-site selection of wind turbines, thereby improving the economic benefits of wind farms in Hong Kong. Meanwhile, the developed copula-based method provides useful references for further investigations regarding direction-related wind energy assessments at various terrain regions. Notably, the proposed copula-based method can also be applied to characterize the direction-related wind energy potential somewhere other than Hong Kong.     

Data efficient measure-correlate-predict approaches to wind resource assessment for small-scale wind energy

The feasibility of predicting the long-term wind resource at 22 UK sites using a measure-correlate-predict (MCP) approach based on just three months onsite wind speed measurements has been investigated. Three regression based techniques were compared in terms of their ability to predict the wind resource at a target site based on measurements at a nearby reference site. The accuracy of the predicted parameters of mean wind speed, mean wind power density, standard deviation of wind speeds and the Weibull shape factor was assessed, and their associated error distributions were investigated, using long-term measurements recorded over a period of 10 years. For each site, 120 wind resource predictions covering the entire data period were obtained using a sliding window approach to account for inter-annual and seasonal variations. Both the magnitude and sign of the prediction errors were found to be strongly dependent on the season used for onsite measurements. Averaged across 22 sites and all seasons, the best performing MCP approach resulted in mean absolute and percentage errors in the mean wind speed of 0.21 ms⁻¹ and 4.8% respectively, and in the mean wind power density of 11 Wm⁻² and 14%. The average errors were reduced to 3.6% in the mean wind speed and 10% in the mean wind power density when using the optimum season for onsite wind measurements. These values were shown to be a large improvement on the predictions obtained using an established semi-empirical model based on boundary layer scaling. The results indicate that the MCP approaches applied to very short onsite measurement periods have the potential to be a valuable addition to the wind resource assessment toolkit for small-scale wind developers.     

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.     

Convertible wind energy based on predicted wind speed at hub-height

Support vector machine is proposed to find wind speed at higher heights using measurements at lower heights. The mean absolute percentage error between measured and the estimated wind speed at height 40 m is found to be satisfactory. After validation at 40 m, the model was used to calculate the wind speed at hub heights up to 100 m. Annual energy yield was found to be increasing with hub height and, hence, accurate estimation of wind speed at heights becomes essential for realistic wind energy assessment. Furthermore, the plant capacity factor was found to be increasing approximately 1% for each 10-m increase in hub height.     

Evaluating the performance of wind turbines in selected locations in Oyo state,Nigeria

The wind speed distribution and wind energy potential are investigated in three selected locations in Oyo state using wind speed data that span between 12 and 20 years measured at 10 m height. In addition, the performance of selected small to medium size wind turbines in these sites were examined. The annual energy output and capacity factor for these turbines were determined. It was found that the monthly mean wind speeds in Oyo state ranges from 2.85 m/s to 5.20 m/s. While the monthly mean power density varies between 27.08 W/m² and 164.48 W/m², while the annual mean power density is in the range of 67.28 W/m² and 106.60 W/m². Based on annual energy output, wind turbines with cut-in wind speed of about 2.5 m/s and moderate rated wind speeds will be best suited for all the sites.     

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 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 speed variability across the UK between 1957 and 2011

By using surface data from 57 UK meteorological stations, a national [British Atmospheric Data Centre (BADC)‐57] and regional wind index for the UK has been calculated for the period 1983–2011. For a subset of seven stations, an additional national index (BADC‐7) has been calculated for the period 1957–2011. The indices show an annual variability of 4% over their respective periods, corresponding to a variation in typical wind turbine capacity factor of 7%. These indices are compared with indices calculated from other sources, namely an index generated using a gridded dataset of observed values interpolated across the UK, an index calculated from an area bounding the UK using the ERA‐40 re‐analysis dataset, indices calculated from bilinear interpolation of the ERA‐40 re‐analysis dataset to the 57 and 7 stations and another independent UK wind index. The indices show variation in trends, with all showing some level of decline with the exception of that generated using the ERA‐40 re‐analysis dataset averaged over the UK, which shows a significant increase. The various indices show varying degrees of agreement with correlation coefficients, after trends are removed, ranging between 0.611 and 0.979. The effect of changes in site exposure, instrument bias and measuring height was considered for the BADC‐7 and BADC‐57 indices. The change in instrument measurement height appears to have a significant biasing effect, and it is likely that this along with changes in exposure at urban sites has caused the decline in annual wind speeds observed for some of the indices. There does not appear to be evidence for significant changes in large‐area (mesoscale) surface roughness. The correlation between annual mean wind speeds at the seven surface station sites used to calculate the BADC‐7 index is seen to be quite weak, indicating very localized variations in inter‐annual variability. When regional differences in the index are investigated, it is seen that wind speeds show a very slight decline across the UK in all regions except the south‐east, which shows a slight increase. The greatest decrease is seen in the north‐west. These changes are in the same direction as the tentative predictions given by climate models for future changes in wind speed across the UK, although the uncertainty is large given the large degree of inter‐annual variation. Copyright © 2013 John Wiley & Sons, Ltd.     

Viability and economic analysis of wind energy resource for power generation in Johannesburg,South Africa

In this study, wind characteristics and wind power potential of Johannesburg are investigated using 5-min average time series wind speed collected between 2005 and 2009 at anemometer height of 10 m. The statistical distribution that best fits the empirical wind speed data at the site of study is first determined based on the coefficient of determination and root mean square error criteria. The statistical parameters and wind power density based on this model are estimated for different months of the year using standard deviation method. Economic analyses of some wind turbines are also carried out. Some of the key results show that the site is only suitable for small wind turbines in a standalone application. A 10 kW wind turbine with cut-in wind speed of 3.5 m/s, rated wind speed of 9 m/s, and cut-out wind speed of 25 m/s seems most appropriate in Johannesburg with the lowest cost that varies from 0.25 to 0.33 $/kWh.     

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.     

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.     

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.     

An analysis of wind power potential in Port Said,Egypt

Measurement station with mast of 19 m has been established in a built-up area, near the seashore to study the structure of a coastal location “Port Said” on Suez Canal–Mediterranean Sea intercept in Egypt. From our analysis of the wind data, an important characteristic is revealed in that the wind speed Spring months are more than that in Winter period. This characteristic is opposite to the prevailing wind speed parameters in most European countries. This paper also gives a detailed analysis of measured frequency distributions and monthly wind speed variation with air temperature that can exploited in the best way for fast wind machines.A numerical model was introduced to calculate the monthly and annual average wind energy flux and found to be quite moderate (in excess of 92 kW/m² per year at 50 m hub height) for this area.It appears from our research that the expected energy from the wind in Port Said region – which is nearly like an island – lies in the medium range. This potential can be converted to electrical energy specially in the Spring months. However, an immediate application seems to be limited to electricity generation using medium size wind farms and water pumping.     

A dynamical downscaling of ERA‐Interim in the North Sea using WRF with a 3 km grid—for wind resource applications

Large offshore wind energy projects are being planned and installed in the North Sea, and there is an urgent demand for high‐resolution atmospheric statistics to assess potential power production and revenue. Meteorological observations are too sparse to obtain those statistics, and global reanalyses like ERA‐Interim have a resolution too coarse in space and time to capture important small‐scale and terrain‐driven features of the atmospheric flow. We therefore dynamically downscale ERA‐Interim with the mesoscale model Weather Research and Forecasting to a 3 km grid to capture those unresolved features, for the period 1999–2008. The large‐scale flow is conditioned by spectral nudging, and we make use of observation nudging towards QuikSCAT near‐surface winds. The downscaling results in 100 m wind‐speed distributions and mean wind speeds, which are closer to the observations than ERA‐Interim, while the accuracy in terms of root‐mean‐square error decreases. The observation nudging partially counteracts this latter effect, improving the root‐mean‐square error of wind speed and direction by 0.5 m s^?1 and ~10°, respectively. We also introduce the power skill score, specifically designed to evaluate model performance within wind resource mapping. The power skill score confirms that the dynamical downscaling improves the distribution of wind speed in ranges where high accuracy is important for wind resource assessment. Copyright © 2016 John Wiley & Sons, Ltd.     

Investigating the possibility of using different hub height wind turbines in a wind farm

Many researchers have focused on the layout design of a wind farm using the computational methods. Most of previous researches focused on relevant large cell size and using same hub height wind turbines. In this paper, the authors investigate the possibility of using different hub height wind turbines in a wind farm. A limited area (2?km?×?2?km) with constant wind speed and direction is considered as the potential wind farm area, and a nested genetic algorithm is used as optimisation algorithm. Two different hub height wind turbines are introduced with two different cell sizes. Power output, cost, payback period, and total profit are selected as evaluation criteria when comparing the layouts with same hub height wind turbines with the layouts with different hub height wind turbines. The results demonstrate that it is feasible and possible to use different hub height wind turbines in a wind farm.     

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.     

Low wind speed turbines and wind power potential in Minnesota, USA

Wind power development in Minnesota largely has been focused in the “windy” southwestern part of the state. This research evaluates the additional power that potentially could be generated via low wind speed turbines, particularly for areas of the state where there has been comparatively little wind energy investment. Data consist of 3 years (2002–2004) of wind speed measurements at 70–75 m above ground level, at four sites representing the range of wind speed regimes (Classes 2–5) found in Minnesota. Power estimates use three configurations of the General Electric 1.5-MW series turbine that vary in rotor diameter and in cut-in, cut-out, and rated speeds. Results show that lower cut-in, cut-out, and rated speeds, and especially the larger rotor diameters, yield increases of 15–30% in wind power potential at these sites. Gains are largest at low wind speed (Class 2) sites and during the summer months at all four sites. Total annual wind power at each site shows some year-to-year variability, with peaks at some sites partially compensating for lulls at others. Such compensation does not occur equally in all years: when large-scale atmospheric circulation patterns are strong (e.g., 2002), the four sites show similar patterns of above- and below-average wind power, somewhat reducing the ability of geographic dispersion to mitigate the effects of wind speed variability.     

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.     

Influence of atmospheric stability on wind turbine loads

Simulations of wind turbine loads for the NREL 5 MW reference wind turbine under diabatic conditions are performed. The diabatic conditions are incorporated in the input wind field in the form of wind profile and turbulence. The simulations are carried out for mean wind speeds between 3 and 16 m s ^{? 1} at the turbine hub height. The loads are quantified as the cumulative sum of the damage equivalent load for different wind speeds that are weighted according to the wind speed and stability distribution. Four sites with a different wind speed and stability distribution are used for comparison. The turbulence and wind profile from only one site is used in the load calculations, which are then weighted according to wind speed and stability distributions at different sites. It is observed that atmospheric stability influences the tower and rotor loads. The difference in the calculated tower loads using diabatic wind conditions and those obtained assuming neutral conditions only is up to 17%, whereas the difference for the rotor loads is up to 13%. The blade loads are hardly influenced by atmospheric stability, where the difference between the calculated loads using diabatic and neutral input wind conditions is up to 3% only. The wind profiles and turbulence under diabatic conditions have contrasting influences on the loads; for example, under stable conditions, loads induced by the wind profile are larger because of increased wind shear, whereas those induced by turbulence are lower because of less turbulent energy. The tower base loads are mainly influenced by diabatic turbulence, whereas the rotor loads are influenced by diabatic wind profiles. The blade loads are influenced by both, diabatic wind profile and turbulence, that leads to nullifying the contrasting influences on the loads. The importance of using a detailed boundary‐layer wind profile model is also demonstrated. The difference in the calculated blade and rotor loads is up to 6% and 8%, respectively, when only the surface‐layer wind profile model is used in comparison with those obtained using a boundary‐layer wind profile model. Finally, a comparison of the calculated loads obtained using site‐specific and International Electrotechnical Commission (IEC) wind conditions is carried out. It is observed that the IEC loads are up to 96% larger than those obtained using site‐specific wind conditions.Copyright © 2012 John Wiley & Sons, Ltd.