Production of a Numerical Icing Atlas for Finland

Ice on wind turbine blades reduces efficiency and causes financial loss to energy companies. Thus, it is important to know the possible risk of icing already in the planning phase of a wind park. This paper presents a new Finnish Icing Atlas and the methodology behind it and is prepared by applying the mesoscale numerical weather prediction model AROME with 2.5km horizontal resolution and an ice growth model based on ISO 12494. The same meteorological dataset is used as was used in the Finnish Wind Atlas (published in 2009), and thus is fully compatible with and comparable with existing climatological wind resource estimations. Representation of the selected time period is evaluated from an icing point of view. Comparing reanalysed temperature and humidity datasets for both the past 20 years and the wind atlas period, we conclude that the used time period represents large‐scale atmospheric conditions favourable for icing. We perform a series of sensitivity tests to evaluate how sensitive this ice model is to input from the weather model. The new atlas presents climatological distributions of active and passive icing periods and wind power production loss in map form for three different heights (50, 100 and 200m) over all of Finland. The results show that the risk for active icing is much greater in coastal areas, while the risk of passive icing is larger inland. © 2016 The Authors. Wind Energy Published by John Wiley & Sons Ltd.     

Offshore wind resource assessment with WAsP and MM5: comparative study for the German Bight

In this study, two different approaches to estimate the wind resource over the German Bight in the North Sea are compared: the mesoscale meteorological model MM5 and the wind resource assessment program WAsP. The dynamics of the atmosphere of the year 2004 was simulated with the MM5 model, with input from the NCEP global model, without directly utilizing measurement data. WAsP estimations were calculated on the basis of six measurement stations: three on islands, two offshore and one onshore. The annual mean wind speed at onshore, offshore and island sites is estimated by both models. The predictions are compared both with each other and with measured data. A spatial comparison of the wind resource calculated by the two models is made by means of a geographical information system. The results show that the accuracy of the WAsP predictions depends mainly on the measurement station used as input. Small differences are shown in the estimations performed by the three island stations, despite the large geographical distance between them. Compared with the measurements of the offshore sites, they seem to be suitable for estimating the offshore wind resource from measurements on land. The two offshore stations show differences when predicting each other's mean wind speed with the WAsP method, while the MM5 calculations show a similar deviation for both sites. The largest differences between the two models are found at distances of 5–50km from the coast. While in WAsP the increase occurs in the first 10km from the coast, MM5 models an increase due to coastal effects for at least 50km. Copyright © 2006 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.     

Hindcasting hourly wind power across Scotland based on met station data

This paper presents methods and results from a study where long‐term wind measurements at 10 m above ground level from meteorological stations across Scotland were used to hindcast both average and hour‐by‐hour local wind speeds. For this, Scotland was divided into 21 simulation areas each containing a meteorological station. The Wind Atlas Analysis and Application Program (WAsP) was then used—well outside its specified range for both distance and area slope—to predict the wind climate at 80 m above ground level on a square kilometre basis. With further processing, time series of wind speed were derived for selected locations. Based on wind turbine power curves it was then possible to derive time series of power which were applied in power system analysis and used to study the degree of matching between renewable generation and electricity demand. This paper focuses on the creation of the onshore wind speed and power time series for areas of interest in Scotland. Copyright © 2007 John Wiley & Sons, Ltd.     

两种数值模式用于风场模拟的对比研究

以珠海横琴风电场为实例,分别使用线性模型WAsP及基于Fluent的计算流体力学(CFD)模型进行风场模拟及发电量计算,得出两种模型下的计算结果;分别对两者的模拟风速、计算发电量与实际发电量进行比较,并分析误差原因.试验结果表明:对于地形复杂的横琴风电场,WAsP模拟的风速值普遍高于Fluent模拟的风速值;WAsP计算年发电量的误差为21.6％,Fluent的误差为10.4％;基于Fluent的CFD模型在风场模拟中比线性模型WAsP具有更高的准确性.     

Statistical analysis of wind speed and direction in Cyprus

The aim of this study is to establish the meteorological basis for the assessment of wind energy resources in Cyprus and to provide suitable data for evaluating the potential wind power. For this purpose the mean values, the systematic daily and annual variations, the frequency distributions and the estimation of the extreme values are determined. Predictions were also obtained from the WAsP model and, finally, the Wind Atlas of the island, in the form of contours of constant wind speed, was produced.     

WEPAS和WAsP在复杂地形条件下的适应性

利用WEPAS和WAsP软件分别计算了南澳风电场的发电量,在充分考虑岛屿型复杂地形地貌条件下对2个软件的计算结果进行对比分析,研究表明,对于地形复杂的南澳风电场,WEPAS和WAsP软件发电量计算结果与实际发电量差值分别为-15.18%和28.02%。其中,WEPAS软件计算的风电场风速和风功率密度上下限偏差较小,结果比较平滑;WAsP软件计算结果比实际值偏高,但是单台风机平均风速和发电量计算结果与实际风况变化趋势比较一致。对上述结论的可能原因进行分析,初步显示2种软件的风场风况计算模式在复杂地形条件下存在较大的不足,风场诊断模式不能较好地模拟复杂地形条件下大气边界层风廓线的实际流动状况。因此,需要改进模式,研发出适用于大气边界层流动计算的风廓线模型、湍流模型和地表函数模型。     

Atmospheric stability‐dependent infinite wind‐farm models and the wake‐decay coefficient

We extend the infinite wind‐farm boundary‐layer (IWFBL) model of Frandsen to take into account atmospheric static stability effects. This extended model is compared with the IWFBL model of Emeis and to the Park wake model used in Wind Atlas Analysis and Application Program (WAsP), which is computed for an infinite wind farm. The models show similar behavior for the wind‐speed reduction when accounting for a number of surface roughness lengths, turbine to turbine separations and wind speeds under neutral conditions. For a wide range of atmospheric stability and surface roughness length values, the extended IWFBL model of Frandsen shows a much higher wind‐speed reduction dependency on atmospheric stability than on roughness length (roughness has been generally thought to have a major effect on the wind‐speed reduction). We further adjust the wake‐decay coefficient of the Park wake model for an infinite wind farm to match the wind‐speed reduction estimated by the extended IWFBL model of Frandsen for different roughness lengths, turbine to turbine separations and atmospheric stability conditions. It is found that the WAsP‐recommended values for the wake‐decay coefficient of the Park wake model are (i) larger than the adjusted values for a wide range of neutral to stable atmospheric stability conditions, a number of roughness lengths and turbine separations lower than ～ 10 rotor diameters and (ii) too large compared with those obtained by a semiempirical formulation (relating the ratio of the friction to the hub‐height free velocity) for all types of roughness and atmospheric stability conditions. © 2013 The Authors. Wind Energy published by John Wiley & Sons, Ltd.     

Wind power resource in the south-western region of Algeria

In this study, we present a statistical analysis of wind speeds at Tindouf in Algeria using Risoe National Laboratory's Wind Atlas Analysis and Application Program (WAsP). It requires information related to the sheltering obstacles, surface roughness changes and terrain height variations in order to calculate their effects on the wind. Wind data, consisting of hourly wind speed records over a 5-year period, 2002–2006, were obtained from SONELGAZ R&D Office; the average wind speed at a height of 17 m above ground level was found to range from 7.19 to 7.95 m/s. The Weibull distributions parameters (c and k) were found to vary between 8.0 and 8.9 m/s and 2.54–3.23, respectively, with average power density ranging from 318 to 458 W/m². The dominant wind directions and the frequency distributions were also determined.     

Investigation of wind energy application possibilities for a specific island (Bozcaada) in Turkey

1975–1984 wind data and other parameters such as obstacle information were taken for a specific inhabited island (Bozacaada) on the west coast of Turkey and used for calculation of wind energy usage possibilities on this island. Calculations were made by using appropriate computer programs which were prepared by the authors and also a computer program WAsP (Wind Atlas Analysis and Application Program, Mortensen, 1993) was used. Conclusions were classified according to the height above ground level and were discussed with the performances of some available commercial wind turbine systems in these conditions.     

Prediction of local wind climatology from Met Office models: Virtual Met Mast techniques

The Met Office has developed the Virtual Met Mast? (VMM) tool for assessing the feasibility of potential wind farm sites. It provides site‐specific climatological wind information for both onshore and offshore locations. The VMM relies on existing data from past forecasts from regional‐scale numerical weather prediction (NWP) models, to which corrections are applied to account for local site complexity. The techniques include corrections to account for the enhanced roughness lengths used in NWP models to represent drag due to sub‐grid orography and downscaling methods that predict local wind acceleration over small‐scale terrain. The corrected NWP data are extended to cover long periods (decades) using a technique in which the data are related to alternative long‐term datasets. For locations in the UK, the VMM currently relies on operational mesoscale model forecast data at 4 km horizontal resolution. Predictions have been verified against observations made at typical wind turbine hub heights at over 80 sites across the UK. In general, the predictions compare well with the observations. The techniques provide an efficient method for screening potential wind resource sites. Examples of how the VMM techniques can be used to produce local wind maps are also presented. © 2016 Crown copyright. Wind Energy © 2016 John Wiley & Sons, Ltd     

Application of mesoscale ensemble forecast method for prediction of wind speed ramps

Sudden changes in wind speed, so‐called wind speed ramps, are a major concern for wind power system operators. The present study applies the mesoscale ensemble forecast method for the prediction of wind speed ramps at wind farms in Japan and evaluates the ability and utility of this method. The mesoscale ensemble forecast in this study (ENS21) consists of 21 members with a horizontal resolution of 10 km for a 5‐year period. The simulated results show that ENS21 produces better accuracy than the deterministic forecast with a horizontal resolution of 10 km (DET_L). On the other hand, the deterministic forecast with a horizontal resolution of 5 km (DET_H) also produces better accuracy than DET_L. From a practical perspective, however, the ENS21 is computationally expensive. Thus, the eight‐member mesoscale ensemble forecast (ENS8) with as same computational cost as a deterministic forecast with a horizontal resolution of 5 km (DET_H) is also evaluated. The simulated results show that ENS8 has almost same accuracy as ENS21 and DET_H in wind speed ramp forecasts. ENS8 has advantages over ENS21 and DET_H because ENS8 is computationally efficient and is able to benefit wind power operators with flexibility in the selection of probability thresholds for decision processes compared with a single. It can be concluded that the mesoscale ensemble forecast method is more useful for prediction of the wind speed ramp than the single deterministic forecast method with the same computational cost if the ensemble members are successfully selected.     

Simulation of a wind farm in swift current region in Southern Saskatchewan (Canada)

An attempt is made to simulate the Centennial wind farm consisting of 83 wind turbines. The farm is located in the Coulee municipality region near Swift Current, Southern Saskatchewan (Canada). The Wind Atlas Analysis and Application Program and other mapping programs were used for generating the annual energy production (AEP). Based on the generated wind atlas and using both the meteorological data for a period of 10 years (2000–2009), and a vector map with height contour and surface roughness lines, the total AEP for the wind farm was calculated. In addition, AEPs of the wind farm were individually calculated for 2007, 2008 and 2009. The results of the simulated model were compared to the actual values for 3 years. The average absolute deviation between the predicted and actual mean AEP values was found to be less than 7%.     

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.     

A pre-feasibility study of wind resources in Kutubdia Island, Bangladesh

Kutubdia is one of the coastal islands in Bangladesh. The wind speed data at the wind monitoring station of Bangladesh Meteorological Department (BMD), Kutubdia, located in a built-up area, appears to be low, but at another location, near the seashore, Bangladesh Centre for Advanced Studies (BCAS) finds that the wind energy availability should be reasonably high. Considering the surface roughness, obstacle condition and terrain information of the island, a micro-scale prediction has been done using (100×100 m²) grid cells in the Wind Atlas Analysis and Application Program (WAsP) to develop monthly and annual wind atlas and also a wind resource map which shows that at 50 m height, the annual wind speed over Kutubdia coast varies from 5.1 to 5.8 m/s. Southern and Eastern sides of Kutubdia appear to be promising for wind electricity generation using large turbines where wind power density at a height of 50 m or higher is found to be above 200 W/m² annually over the year September 1996 to August 1997. It is found that at 30 m height, the coast side of Kutubdia should be sustainable for small turbines.     

Technoeconomic study for the optimization of turbine size and wind farm layouts

A technoeconomic analysis and optimization of wind turbine size and layout are performed using WAsP software. A case study of a 100‐MW wind farm located in Egypt is considered. Wind atlas for Egypt was used as the input data of the WAsP software. Two turbine models of powers 52 and 80 MW are considered for this project. The wind turbine size and distributions are selected based on the technoeconomic optimization, namely minimum wake effect, maximum annual energy production (AEP) rate, optimum cash flow, and payback period. The future worth method is adopted in economic comparison between the two alternatives, and the cash flow diagram provided the payback period and future worth after the lifetime of the plant. The results showed that (1) the AEP dramatically decreases for a wind farm area less than 15 km²; (2) the turbine spacing, spacing‐to‐diameter ratio, and the setback distances decrease and the wind turbine density and wake losses increase with decreasing the wind turbines size; (3) the total net AEP using G52 is lower than that of using G80 by about 16%; (4) the technoeconomic analysis recommended using G80 as it has higher profit than those of G52 by about $20 million.     

WAsP in the Forest

This article compares mean wind estimates from a WAsP analysis for three forest sites and one site near a forest with measurements taken at the sites. By standard WAsP settings for forest, the mean wind speed at the sites was overestimated. Agreement between the estimates and the measurements improved significantly if displacement height and roughness length as calculated from the forest mast data were used or if a simple model estimate of roughness length and displacement height based on stand density (frontal area index) was used. The two estimates of displacement height and roughness length (mast data and simple model) did not agree well with each other. One reason for this may be that all evaluated sites are windy and that both d and z₀ depend on the wind speed. All analysed forest sites are dense, in which case the influence from the roughness sublayer is limited and the effect on mean wind speeds from this layer could not be evaluated. Copyright © 2005 John Wiley & Sons, Ltd.     

Wind energy resources on Phuquoc Island,Vietnam

This study analyzes the wind energy resources on Phuquoc Island, Vietnam. Daily wind data are collected from 2005 to 2011 in this study. The annual mean speed and power density are 6 m/s and 355 W/m², respectively. Results show that more than 35% of the wind energy comes from the northwest. In this study, a 75 MW wind farm with 25 wind turbines is simulated by using the WAsP 10 program. The wind farm can produce over 189.636 GWh annually. In addition, the effects of wind disturbance and three-phase short circuit of the grid are analyzed using the ETAP 7.0 program.     

Assessment of offshore wind farm characteristics with the cloud resolving storm simulator: A case study in Japan

Wind conditions and output power characteristics of a wind farm in Japan are evaluated with highly resolved weather predictions from the so‐called cloud resolving storm simulator. One year of 30‐hour‐ahead predictions with 2‐km spatial resolution and 1‐hour time resolution are evaluated against 10‐minute averaged measurements (averaged to hourly data) from the wind farm. Also, extremely detailed shorter‐term predictions with 200‐m spatial resolution and 1‐second time resolution are evaluated against 1‐Hz measurements. For the hourly data, wind speeds are predicted with an RMSE of 3.0 to 3.5 m/s, and wind power with about 0.3 per unit. Wind direction is predicted with a standard deviation of errors of 16° to 28° for hourly data, and generally below 10° for the 1‐Hz data. We show that wind power variability—here in terms of increments—can be assessed on the timescale of several hours. The measured and predicted wind spectra are found similar on both short and long timescales.     

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

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