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.     

The wind shear exponent in a Mediterranean island climate

The difficulties in estimating the long term mean wind speed and subsequently wind turbine energy output derive from the fact that more often than not, available data is taken at a level other than machine hub height. The 1/7th power law has been recognised as a handy tool to carry out vertical wind speed extrapolation to the desired hub height. It is also understood that using an exponent of 1/7th could lead to underestimation of the actual long-term mean wind speed aloft. This paper strives to evaluate the power law with respect to wind data taken on a 25 m mast on the central Mediterranean island of Malta. Whilst deriving a site-specific factor affiliated to a typical terrain type, it also strives to determine characteristic variations of the power law exponent over appropriate sampling intervals.     

Analysis and parameterisation of wind profiles in the low atmosphere

Knowledge of temporal and spatial variation of the wind is important to obtain accurate calculations of wind power potential. The best estimation method involves direct measurement of wind speed which, however, is not always possible. In such cases, a good parameterisation of wind profile is necessary. A RASS sodar located in Northern Spain has been used in this paper. This device provided a broad database of 10-min averages from August 2002 to January 2004. The vertical range extended from 40 to 500 m in 20 m levels, although the 220 m level was selected as the upper boundary by analysis of wind speed and temperature vertical profiles. Hourly medians were calculated each month in the 10 lower levels, yielding a sharp contrast between day and night. Flat wind speed profiles were clear during day, mainly in summer, due to convection produced by surface heating. However, stable stratification favoured horizontal movement and wind speed values increasing with height were observed during the night. Power and logarithmic laws have been fitted from vertical profiles of hourly wind speed medians. The exponent of the power law showed hourly medians greater than 0.5 during the night and lower than 0.2 during the day. A simple model has been proposed for the parameters of both expressions, consisting of an addition of three harmonic functions with periods of 1 year, 1 day and half a day. Hourly wind speed medians were successfully fitted at the heights of interest, although the fit proved better for the power law. Finally, a slight decrease in fitting at increasing heights was also observed.     

Evaluation of log‐of‐power extremum seeking control for wind turbines using large eddy simulations

The extremum seeking control (ESC) algorithm has been proposed to determine operating parameters that maximize power production below rated wind speeds (region II). This is usually done by measuring the turbine's power signal to determine optimal values for parameters of the control law or actuator settings. This paper shows that the standard ESC with power feedback is quite sensitive to variations in mean wind speed, with long convergence time at low wind speeds and aggressive transient response, possibly unstable, at high wind speeds. The paper also evaluates the performance, as measured by the dynamic and steady state response, of the ESC with feedback of the logarithm of the power signal (LP‐ESC). Large eddy simulations (LES) demonstrate that the LP‐ESC, calibrated at a given wind speed, exhibits consistent robust performance at all wind speeds in a typical region II. The LP‐ESC is able to achieve the optimal set‐point within a prescribed settling time, despite variations in the mean wind speed, turbulence, and shear. The LES have been conducted using realistic wind input profiles with shear and turbulence. The ESC and LP‐ESC are implemented in the LES without assuming the availability of analytical gradients.     

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.     

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.     

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.     

The effect of a leading edge erosion shield on the aerodynamic performance of a wind turbine blade

Armour EDGE is a novel shield developed to protect the leading edge of wind turbine blades from erosion. The aerodynamic impact on aerofoils of National Renewable Energy Laboratory (NREL) 5MW wind turbine has been investigated using 2D fully turbulent computational fluid dynamics (CFD), with three profiles at critical locations along the blade simulated both with and without the shield to compare aerodynamic performance. Two wind speeds were investigated that reflect regular operating conditions: at rated speed of 11.4 m/s and a below rated speed of 7 m/s. The results showed that the presence of the shield during rated wind speed reduced the drag by as much as 4.5%, where the lift‐to‐drag ratio increased by a maximum of 4%. At the below rated wind speeds, the shield had negligible impact on the performance of all but one National Advisory Committee for Aeronautics (NACA) 64‐618 profile, which resulted in an increase in the drag coefficient of 7%. It was also found that the suction side of the aerofoil is much more sensitive to leading edge protection placement than the pressure side. It was concluded that the erosion shield as a method of leading edge protection, with a gradual transition from shield to blade, will not have a major impact on the aerodynamic performance of a multi‐megawatt wind turbine blade and could slightly increase aerofoil efficiency at high wind speeds.     

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.     

Meteorological wind energy potential in the Alps using ERA40 and wind measurement sites in the Tyrolean Alps

The peculiarities of meteorological wind potential in alpine settings compared to flatland and offshore sites are studied. Four data sources are used: Global reanalysis ERA40 from ECMWF, long‐term stations in the Tyrolean Alps, spatially dense measurements near the best site and Doppler sodar wind profiles. Due to the decrease of density with height, alpine sites suffer from a nearly linear decrease of harvestable power with altitude, which is more than offset by the increase of wind speed at altitudes above 1.5 km MSL. ERA40 data show higher potential on the northern than on the southern side of the Alps. The best locations are not isolated peaks but ridges within wide orographic channels. The best potential sites in the Tyrolean part of the Alps have median wind speeds of up to 7.1 m s^?1 and extractable potentials between 2900 and 1600 kWh per year and per square meter of rotor area. The profile of horizontal wind speed at ridge sites is often not logarithmic but approximately constant within the height of a wind turbine due to a (nearly) complete absence of upwind fetch. Also, the turbulence intensity is independent of height. Icing can cause considerable downtimes. Copyright © 2010 John Wiley & Sons, Ltd.     

Modified wind power formulation and its comparison with Betz limits

Among the renewable energy types, wind provides intermittent but environmentally friendly energy source that does not pollute atmosphere. Wind power calculations are initiated from the kinetic energy definition, and finally, the power is found as proportional to the half (1/2) of air density multiplied by the wind velocity cube. In this paper, wind power formulation is derived first by use of kinetic energy definition and then the basic physical definitions of power as the ratio of work per time, the work as the force multiplied by the distance and the force as the change of momentum. These considerations lead to wind power formulation with 1/3 factor instead of 1/2. Furthermore, formulation with factor of 1/3 gives results close to Betz limit within 10% difference at very high wind speeds (> 12 m/s), which remains within practically acceptable limits. 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.     

Wind energy statistics for large arrays of wind turbines (New England and Central U.S. Regions)

The performance characteristics have been simulated for large dispersed arrays of 500–1500 kW wind turbines producing power and feeding it directly into the New England or Central U.S. utility distribution grids. These studies, based on design power performance curves, indicate that in good wind environments the 500 kW generators can average (on an annual basis) up to 240 kW mean power output, and the 1500 kW generators can average up to 350 kW mean power output. Higher mean power output (averaging up to 470 kW) is indicated, however from a hypothetical 1125 kW rated power unit designed to operate at wind speeds near those observed throughout the study area, rather than the higher design operating wind speed of the 1500 kW unit. The beneficial effect of operating large disperse arrays of wind turbines is that available power output can be increased—if winds are not blowing over one part of the array, chances are they will over some other part of the array. These studies indicate that wind power availability levels of 200 kW per 1125 kW generator were 77–93 per cent, depending on season. Reasonably steady high wind power in winter and high afternoon peak wind power in summer (corresponding to peak air conditioning load) means that significant peak load displacement can be achieved without the use of storage.     

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.     

On wind speed pattern and energy potential in Nigeria

The aim of this paper is to review wind speed distribution and wind energy availability in Nigeria and discuss the potential of using this resource for generation of wind power in the country. The power output from a wind turbine is strongly dependent on the wind speed and accurate information about the wind data in a targeted location is essential. The annual mean wind speeds in Nigeria range from about 2 to 9.5 m/s and the annual power density range between 3.40 and 520 kW/m² based on recent reported data. The trend shows that wind speeds are low in the south and gradually increases to relatively high speeds in the north. The areas that are suitable for exploitation of wind energy for electricity generation as well as for water pumping were identified. Also some of the challenges facing the development of wind energy and suggested solutions were presented.     

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.     

Wind to power a new city in Oman

This paper proposes the use of wind power as a source of electricity in a new city being developed in the Duqm area of Oman. Recent wind speed measurements taken at the Duqm metrological station are analyzed to obtain the annual and monthly wind probability distribution profiles represented by Weibull parameters. The monthly average mean wind speed ranges between 2.93 m/s in February and 9.76 m/s in July, with an annual average of 5.33 m/s.A techno-economic evaluation of a wind power project is presented to illustrate the project's viability. Given Duqm's wind profile and the power curve characteristics of a V90-1.8 turbine, an annual capacity factor of 0.36 is expected. For the base-case assumptions, the cost of electricity is about $0.05 and $0.08 per kWh for discount rates of 5% and 10%, respectively. These values are higher than that of the existing generation system, due to the subsidized prices of domestically available natural gas. However, given high international natural gas prices, the country's long-term LNG export obligations, and the expansion of natural gas-based industries, investments in wind power in Duqm can be justified. A feed-in tariff and capital cost allowance policies are recommended to facilitate investments in this sector.     

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.     

Wind energy evaluation for electricity generation using WECS in seven selected locations in Nigeria

This paper statistically examine wind characteristics from seven meteorological stations within the North-West (NW) geo-political region of Nigeria using 36-year (1971–2007) wind speed data measured at 10 m height subjected to 2-parameter Weibull analysis. It is observed that the monthly mean wind speed in this region ranges from 2.64 m/s to 9.83 m/s. The minimum monthly mean wind speed was recorded in Yelwa in the month of November while the maximum value is observed in Katsina in the month of June. The annual wind speeds range from 3.61 m/s in Yelwa to 7.77 m/s in Kano. It is further shown that Sokoto, Katsina and Kano are suitable locations for wind turbine installations with annual mean wind speeds of 7.61, 7.45 and 7.77 m/s, respectively. The results also suggest that Gusau and Zaria should be applicable for wind energy development using taller wind turbine towers due to their respective annual mean speeds and mean power density while Kaduna is considered as marginal. In addition, higher wind speeds were recorded in the morning hours than afternoon periods for this region. A technical electricity generation assessment using four commercial wind turbines were carried out. The results indicate that, while the highest annual power is obtained with Nordex N80–2.5 MW as 14233.53 kW/year in Kano, the lowest is in Yelwa having 618.06 kW/year for Suzlon S52. It is further shown that the highest capacity factor is 64.95% for Suzlon S52–600 kW in Kano while the lowest is 3.82% for Vestas V80–2 MW in Yelwa.     

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.