Wind over complex terrain – Microscale modelling with two types of mesoscale winds at Nygårdsfjell

Nygårdsfjell, a complex terrain near Norwegian-Swedish border, is characterized by its significant wind resources. The feasibility of using mesoscale winds as input to microscale model is studied in this work. The main objective is to take into account the actual terrain effects on wind flow over complex terrain. First set of mesoscale winds are modelled with Weather Research and Forecasting (WRF) numerical tool whereas second set of mesoscale winds are taken from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) data system. WindSim, a computational fluid dynamics based numerical solver is used as microscale modelling tool. The results suggest that the performance of microscale model is largely dependent upon the quality of mesoscale winds as input. The proposed coupled models achieve improvements in wind speed modelling, especially during cold weather. WRF-WindSim coupling showed better results than MERRA-WindSim coupling in all three test cases, as root mean square error (RMSE) decreased by 70.9% for the February case, 61.5% for October and 14.4% for June case respectively. Raw mesoscale winds from the WRF model were also more correct than the mesoscale winds from MERRA data set when extracted directly at the wind turbine by decreasing the RMSE by 62.6% for the February case, 62.7% for October and 23.7% for June case respectively. The difference of RMSE values between the mesoscale winds directly at wind turbine versus the coupled meso-microscale model outputs are not conclusive enough to indicate any specific trend.     

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.     

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     

Wind energy analysis based on turbine and developed site power curves: A case-study of Darling City

The observed wind at a given site varies continuously as a function of time and season, increasing hub heights, topography of the terrain, prevailing weather condition etc. The quality of wind resource is one of the important site factors to be considered when assessing the wind potential of any location for any energy project. In this study, two wind energy analysis techniques are presented: the use of direct technique where the electrical power outputs of the wind turbines at a time t are estimated using the turbine power curve(s) and the use of statistical-based technique where the power outputs are estimated based on the developed site power curve(s). The wind resource assessment at Darling site is conducted using a 5-min time series weather data collected on a 10 m height over a period of 24 months. Because of the non-linearity of the site's wind speed and its corresponding power output, the wind resources are modeled and the developed site power curve(s) are used to estimate the long term energy outputs of the wind turbines for changing weather conditions. Three wind turbines rating of 1.3 MW, 1.3 MW and 1.0 MW were selected for the energy generation based on the gauged wind resource(s) at 50, 60 and 70 m heights, respectively. The energy outputs at 50 m height using the 1.3 MW WT were compared to the energy outputs at 60 m to determine the standard height for utility scale energy generation at this site. An additional energy generation of 190.71 MWh was available by deploying the same rated turbine at a 60 m height. Furthermore, comparisons were made between the use of turbine and site power curve for wind energy analysis at the considered heights. The results show that the analysis of the energy outputs of the WTs based on the site power curve is an accurate technique for wind energy analysis as compared to the turbine power curve. Conclusions are drawn on the suitability of this site for utility scale generation based on the wind resources evaluation at different heights.     

A wind map of Bangladesh

Utilization of wind energy in Bangladesh has been slow mainly due to lack of quality wind data. Recent measurements in some places have shown significant wind energy potentials in Bangladesh. In this paper, a wind map is presented which incorporates several microscale features, such as terrain roughness, elevation etc. with a mesoscale model. Several meso-maps were obtained from global databases and a suitable model was chosen and modified for a 30-m elevation. Ground data from various sources were collected and modified for height and land condition adjustments based on local knowledge and GIS information. It was found that, the generated wind map and the modified ground data resemble. Annual average wind speed at 30 m height along the coastal belt is above 5 m/s. Wind speed in northeastern parts is above 4.5 m/s while inland wind speed is around 3.5 m/s for most part of Bangladesh. Small-scale wind turbines could be installed and tested in locations such as St. Martins Island, Cox’s Bazar, Patenga, Bhola, Barguna, Dinajpur, Thakurgaon and Panchagar.     

The selective dynamical downscaling method for extreme‐wind atlases

A selective dynamical downscaling method is developed to obtain extreme‐wind atlases for large areas. The method is general, efficient and flexible. The method consists of three steps: (i) identifying storm episodes for a particular area, (ii) downscaling of the storms using mesoscale modelling and (iii) post‐processing. The post‐processing generalizes the winds from the mesoscale modelling to standard conditions, i.e. 10‐m height over a homogeneous surface with roughness length of 5 cm. The generalized winds are then used to calculate the 50‐year wind using the annual maximum method for each mesoscale grid point. The generalization of the mesoscale winds through the post‐processing provides a framework for data validation and for applying further the mesoscale extreme winds at specific places using microscale modelling. The results are compared with measurements from two areas with different types of extreme‐wind climates, and the results are promising. Copyright © 2012 John Wiley & Sons, Ltd.     

A wind field downscaling strategy based on domain segmentation and transfer functions

This paper presents a novel methodology for mesoscale‐to‐microscale downscaling of near‐surface wind fields. The model chain consists on the Weather Research and Forecast mesoscale model and the Alya‐CFDWind microscale model (assuming neutral stability). The downscaling methodology combines precomputed microscale simulations with a mesoscale forecast using a domain segmentation technique and transfer functions. As a result, the downscaled wind field preserves the mesoscale pattern but, at the same time, incorporates local mesoscale subgrid terrain effects, particularly at valleys and channelling zones. The methodology has been validated over a 9‐month period on a very complex terrain site instrumented with a dense observational network of meteorological masts. With respect to mesoscale results, the global skills of the downscaled wind at masts improve for wind direction and remain similar for wind velocity. However, a substantial improvement occurs under stable and neutral conditions and for high wind velocity regimes.     

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.     

Large‐eddy simulation of turbulent flow past wind turbines/farms: the Virtual Wind Simulator (VWiS)

A large‐eddy simulation framework, dubbed as the Virtual Wind Simulator (VWiS), for simulating turbulent flow over wind turbines and wind farms in complex terrain is developed and validated. The wind turbines are parameterized using the actuator line model. The complex terrain is represented by the curvilinear immersed boundary method. The predictive capability of the present method is evaluated by simulating two available wind tunnel experimental cases: the flow over a stand‐alone turbine and an aligned wind turbine array. Systematic grid refinement studies are carried out, for both single turbine and multi‐turbine array cases, and the accuracy of the computed results is assessed through detailed comparisons with wind tunnel experiments. The model is further applied to simulate the flow over an operational utility‐scale wind farm. The inflow velocities for this case are interpolated from a mesoscale simulation using a Weather Research and Forecasting (WRF) model with and without adding synthetic turbulence to the WRF‐computed velocity fields. Improvements on power predictions are obtained when synthetic turbulence is added at the inlet. Finally the VWiS is applied to simulate a yet undeveloped wind farm at a complex terrain site where wind resource measurements have already been obtained. Good agreement with field measurements is obtained in terms of the time‐averaged streamwise velocity profiles. To demonstrate the ability of the model to simulate the interactions of terrain‐induced turbulence with wind turbines, eight hypothetical turbines are placed in this area. The computed extracted power underscores the significant effect of site‐specific topography on turbine performance. Copyright © 2014 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.     

Wind energy potential assessment for the offshore areas of Taiwan west coast and Penghu Archipelago

The average wind speed and wind power density of Taiwan had been evaluated at 10 m, 30 m and 50 m by simulation of mesoscale numerical weather prediction model (MM5). The results showed that wind energy potential of this area is excellent. Taiwan has offered funds to encourage the founding of offshore wind farms in this area. The purpose of this study is to make a high resolution wind energy assessment for the offshore area of Taiwan west coast and Penghu archipelago by using WAsP. The result of this study has been used to the relative financial planning of offshore wind farm projects in Taiwan. The basic inputs of WAsP include wind weather data and terrain data. The wind weather data was from a monitoring station located on a remote island, Tongi, because that all of weather stations in the area of Taiwan west coast are affected by urbanization. SRTM was selected to be used as terrain data and downloaded from CGIAR-CSI for voids problem. The coverage of considered terrain area in this assessment work is about 300 km × 400 km that made some difficulties to run wind energy assessment of the whole area with a high resolution of 100 m. So the interested area of this study is divided into 19 areas for the wind energy assessment and mapping. The assessment results show the Changhua area has best wind energy potential in the area of Taiwan west coast which power density is above 1000 W/m² height and the areas of Penghu archipelago are above 1300 W. These results are higher than the expected from NWP. 180 of 3 MW wind turbines were used in the study of micro sitting in the Changhua area.The type and number of the wind turbines and the layout of the wind farm is similar to the prior study of Taipower Company for demonstrating the reliability of this study. The assessment result of average net annual energy production (AEP) of the wind farm is about 11.3 GWh that is very close to the prior study. The terrain effect is also studied. The average net annual energy production will decrease about 0.7 GWh if the wind turbines were moved eastward 3600 m closer to the coast because of terrain effect. As the same reason, the average net annual energy production would be increased to 11.392 GWh if the wind farm is moved westward 3600 m away from the coast.     

Assessment of wave energy resources in Hawaii

Hawaii is subject to direct approach of swells from distant storms as well as seas generated by trade winds passing through the islands. The archipelago creates a localized weather system that modifies the wave energy resources from the far field. We implement a nested computational grid along the major Hawaiian Islands in the global WaveWatch3 (WW3) model and utilize the Weather Research and Forecast (WRF) model to provide high-resolution mesoscale wind forcing over the Hawaii region. Two hindcast case studies representative of the year-round conditions provide a quantitative assessment of the regional wind and wave patterns as well as the wave energy resources along the Hawaiian Island chain. These events of approximately two weeks each have a range of wind speeds, ground swells, and wind waves for validation of the model system with satellite and buoy measurements. The results demonstrate the wave energy potential in Hawaii waters. While the episodic swell events have enormous power reaching 60 kW/m, the wind waves, augmented by the local weather, provide a consistent energy resource of 15–25 kW/m throughout the year.     

A wind‐tunnel study of the wake development behind wind turbines over sinusoidal hills

In the present work, the wake development behind small‐scale wind turbines is studied when introducing local topography variations consisting of a series of sinusoidal hills. Additionally, wind‐tunnel tests with homogeneous and sheared turbulent inflows were performed to understand how shear and ambient turbulence influence the results. The scale of the wind‐turbine models was about 1000 times smaller than full‐size turbines, suggesting that the present results should only be qualitatively extrapolated to real‐field scenarios. Wind‐tunnel measurements were made by means of stereoscopic particle image velocimetry to characterize the flow velocity in planes perpendicular to the flow direction. Over flat terrain, the wind‐turbine wake was seen to slowly approach the ground while it propagated downstream. When introducing hilly terrain, the downward wake deflection was enhanced in response to flow variations induced by the hills, and the turbulent kinetic energy content in the wake increased because of the speed‐up seen over the hills. The combined wake observed behind 2 streamwise aligned turbines was more diffused and when introducing hills, it was more prone to deflect towards the ground compared to the wake behind an isolated turbine. Since wake interactions are common at sites with multiple turbines, this suggested that it is important to consider the local hill‐induced velocity variations when onshore wind farms are analysed. Differences in the flow fields were seen when introducing either homogeneous or sheared turbulent inflow conditions, emphasizing the importance of accounting for the prevailing turbulence conditions at a given wind‐farm site to accurately capture the downstream wake development.     

Extreme winds from the NCEP/NCAR reanalysis data

In this study, we test a method to estimate the extreme winds by using the NCEP/NCAR reanalysis data. From the reanalysis pressure or geopotential height records, the geostrophic wind is first calculated, and then extrapolated to 10 m height over a homogeneous surface with roughness length of 0.05 m, i.e. the so‐called standard wind. The software Wind Analysis and Application Program will then use this standard wind in a flow model, with the roughness, orography and obstacles around the turbine site to obtain the site‐specific wind. The ‘annual maximum method’ is used to calculate the 50 year wind. We examined extreme winds in different places where the strongest wind events are weather phenomena of different scales, including the mid‐latitude lows in Denmark, channelling winds in the Gulf of Suez, typhoons in the western North Pacific, cyclones in the Caribbean Sea, local strong winds: the Mistral in the Gulf of Lions and the Bora in the north Adriatic Sea. It was found that the method introduced here can be applied to places where the extreme wind events are synoptic weather phenomena like in north‐western Europe, but a more complicated downscaling, e.g. based on a mesoscale model, is needed for places where the extreme wind events are of mesoscale origin. Copyright © 2009 John Wiley & Sons, Ltd.     

Effect of direction on wind speed estimation in complex terrain using neural networks

A method of estimating the annual average wind speed at a selected site using neural networks is presented. The method proposed uses only a few measurements taken at the selected site in a short time period and data collected at nearby fixed stations.The neural network used in this study is a multilayer perceptron with one hidden layer of 15 neurons, trained by the Bayesian regularization algorithm. The number of inputs that must be used in the neural network was analyzed in detail, and results suggest that only wind speed and direction data for a single station are required. In sites of complex terrain, direction is a very important input that can cause a decrease of 23% in root mean square (RMS).The results obtained by simulating the annual average wind speed at the selected site based on data from nearby stations are satisfactory, with errors below 2%.     

Feasibility study of offshore wind turbine installation in Iran compared with the world

Renewable energies have potential for supplying of relatively clean and mostly local energy. Wind energy generation is expected to increase in the near future and has experienced dramatic growth over the past decade in many countries. Offshore winds are generally stronger and more constant than onshore winds in many areas. The economic feasibility for utilization of offshore wind energy depends on the favorable wind conditions in the area. The present paper analyses offshore wind speed in global scale and also studies feasibility of introducing this technology for harnessing wind in Persian Gulf, Caspian Sea, Urmia Lake and Gulf of Oman. Wind speed data were collected from different sources. The ocean surface winds at a 10 m height from satellite passes as processed by NOAA/NESDIS, from near real-time data collected by NASA/JPL's Sea Winds Scatterometer aboard the QuikSCAT. Development of renewable energy is one of priority research goals in Iran. There are many installed wind turbines in suitable regions like Manjil and Binalood, but there has not been any offshore wind installation yet in Iran. It is suggested that policy makers to invest and pay more attentions toward harnessing renewable energy sources like offshore wind in Persian Gulf and Gulf of Oman in southern parts of Iran.     

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.     

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.     

Feasibility assessment of wind energy resources in Malaysia based on NWP models

There is a common belief that countries located in the doldrums with prevailing monotonous weather, characterized by light winds, cannot harness the wind for feasible energy production. This paper reexamines such a belief and presents a novel approach to assess the techno-economic potential of wind turbine generator sites in Malaysia, which lies in the equatorial, low wind speed doldrums. Dissimilar to other techniques that account for planetary-scale winds only, a numerical weather prediction (NWP) prospecting tool for mesoscale winds is used to forecast the wind characteristics. Potential sites from the forecasting studies are further investigated for economic feasibility by using a commercial wind turbine generator and a financial analysis method. From the economic analysis, it is found that unlike what is widely touted, there is an actual potential of wind energy in Malaysia, manifested through the several economically viable wind turbine generating sites.