Evaluation of the Weather Research and Forecasting model on forecasting low‐level jets: implications for wind energy

Nocturnal low‐level jet (LLJ) events are commonly observed over the Great Plains region of the USA, thus making this region more favorable for wind energy production. At the same time, the presence of LLJs can significantly modify vertical shear and nocturnal turbulence in the vicinities of wind turbine hub height, and therefore has detrimental effects on turbine rotors. Accurate numerical modeling and forecasting of LLJs are thus needed for precise assessment of wind resources, reliable prediction of power generation and robust design of wind turbines. However, mesoscale numerical weather prediction models face a challenge in precisely forecasting the development, magnitude and location of LLJs. This is due to the fact that LLJs are common in nocturnal stable boundary layers, and there is a general consensus in the literature that our contemporary understanding and modeling capability of this boundary‐layer regime is quite poor. In this paper, we investigate the potential of the Weather Research and Forecasting (WRF) model in forecasting LLJ events over West Texas and southern Kansas. Detailed observational data from both cases were used to assess the performance of the WRF model with different model configurations. Our results indicate that the WRF model can capture some of the essential characteristics of observed LLJs, and thus offers the prospect of improving the accuracy of wind resource estimates and short‐term wind energy forecasts. However, the core of the LLJ tended to be higher as well as slower than what was observed, leaving room for improvement in model performance. Copyright © 2008 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.     

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.     

基于中微尺度耦合模式的风电场风资源评估方法研究

针对传统风资源评估方法采用假设的入流风廓线模型而无法考虑宏观大气环流对风电场内风流动影响的问题,文章基于中尺度WRF模式和微尺度CFD模型,研究了基于中微尺度耦合模式的风资源评估方法。首先,建立基于WRF模式的中尺度数值模拟方法和基于CFD方法的微尺度风资源评估方法;其次,研究了中微尺度数值模拟方法的耦合原理,构建了从中尺度模拟结果中提取微尺度建模计算边界附近风速廓线的方法,建立了中微尺度耦合风资源评估流程;最后,通过某复杂山地风电场进行验证。验证结果表明,中尺度模拟结果可以改善微尺度CFD模型的入流边界条件,并有效降低风资源评估的误差。     

基于MM5的沿海风资源数值模拟方法研究

提出通过历史观测资料和中尺度大气模式相融合的方法为沿海区域风能资源的分析评估提供一定时空分辨率的风场数值分析产品。主要探讨了将海洋站逐时测风资料、卫星微波遥感散射计风场反演资料计人中尺度大气模式MM5的同化方法，并对广东沿海区域天气个例进行了模拟试验，将不同模拟试验结果与实测值进行了统计对比分析。分析结果表明，时空分辨率较高的经过质量控制的观测资料的同化对风场模拟结果具有一定的改善作用。     

A comparison between Advanced Scatterometer and Weather Research and Forecasting wind speeds for the Japanese offshore wind resource map

This paper investigates the validity of the method used in the Japanese offshore wind map (NeoWins) to seamlessly connecting satellite‐derived wind speed for open oceans to mesoscale model‐simulated wind speed for coastal waters. In the NeoWins, the former was obtained from the satellite‐borne Advanced Scatterometer (ASCAT), and the latter was obtained from numerical simulations using the Weather Research and Forecasting (WRF) model. In this study, the consistency of the ASCAT and WRF 10‐m height wind speeds is examined in their overwrapping areas. The comparison between ASCAT and WRF model reveals that their differences in annual mean wind speed are mostly within ±5% and that the ASCAT annual mean wind speed is, as a whole, slightly higher than the WRF annual mean wind speed. The results indicate that there are no large wind speed gaps between WRF and ASCAT in most parts of the Japanese offshore areas. It is moreover found that the discrepancies between the two wind speeds are due to two factors: one is the existence of winter sea ice in the ASCAT observation in the Sea of Okhotsk in ASCAT observation and the other is that the accuracy of the WRF wind speed depends on atmospheric stability.     

Evaluation of four numerical wind flow models for wind resource mapping

A wide range of numerical wind flow models are available to simulate atmospheric flows. For wind resource mapping, the traditional approach has been to rely on linear Jackson–Hunt type wind flow models. Mesoscale numerical weather prediction (NWP) models coupled to linear wind flow models have been in use since the end of the 1990s. In the last few years, computational fluid dynamics (CFD) methods, in particular Reynolds‐averaged Navier–Stokes (RANS) models, have entered the mainstream, whereas more advanced CFD models such as large‐eddy simulations (LES) have been explored in research but remain computationally intensive. The present study aims to evaluate the ability of four numerical models to predict the variation in mean wind speed across sites with a wide range of terrain complexities, surface characteristics and wind climates. The four are (1) Jackson–Hunt type model, (2) CFD/RANS model, (3) coupled NWP and mass‐consistent model and (4) coupled NWP and LES model. The wind flow model predictions are compared against high‐quality observations from a total of 26 meteorological masts in four project areas. The coupled NWP model and NWP‐LES model produced the lowest root mean square error (RMSE) as measured between the predicted and observed mean wind speeds. The RMSE for the linear Jackson‐Hunt type model was 29% greater than the coupled NWP models and for the RANS model 58% greater than the coupled NWP models. The key advantage of the coupled NWP models appears to be their ability to simulate the unsteadiness of the flow as well as phenomena due to atmospheric stability and other thermal effects. Copyright © 2012 John Wiley & Sons, Ltd.     

Mesoscale modeling of offshore wind turbine wakes at the wind farm resolving scale: a composite‐based analysis with the Weather Research and Forecasting model over Horns Rev

The use of mesoscale modeling to reproduce the power deficits associated with wind turbine wakes in an offshore environment is analyzed. The study is based on multiyear (3 years) observational and modeling results at the Horns Rev wind farm. The simulations are performed with the Weather Research and Forecasting mesoscale model configured at a high horizontal resolution of 333 m over Horns Rev. The wind turbines are represented as an elevated momentum sink and a source of turbulent kinetic energy. Composites with different atmospheric conditions are extracted from both the observed and simulated datasets in order to inspect the ability of the model to reproduce the power deficit in a wide range of atmospheric conditions. Results indicate that mesoscale models such as Weather Research and Forecasting are able to qualitatively reproduce the power deficit at the wind farm scale. Some specific differences are identified. Mesoscale modeling is therefore a suitable framework to analyze potential downstream effects associated with offshore wind farms. Copyright © 2014 John Wiley & Sons, Ltd.     

Investigation of boundary‐layer wind predictions during nocturnal low‐level jet events using the Weather Research and Forecasting model

The accuracy of boundary‐layer wind profiles occurring during nocturnal low‐level jet (LLJ) events, and their sensitivities to variations of user‐specifiable model configuration parameters within the Weather Research and Forecasting model, was investigated. Simulations were compared against data from a wind‐profiling lidar, deployed to the Northern Great Plains during the U.S. Department of Energy‐supported Weather Forecast Improvement Project. Two periods during the autumn of 2011 featuring LLJs of similar magnitudes and durations occurring during several consecutive nights were selected for analysis. Simulated wind speed and direction at 80 and 180 m above the surface, the former a typical wind turbine hub height, bulk vertical gradients between 40 and 120 m, a typical rotor span, and the maximum wind speeds occurring at 80 and 180 m, and their times of occurrence, were compared with the observations. Sensitivities of these parameters to the horizontal and vertical grid spacing, planetary boundary layer and land surface model physics options, and atmospheric forcing dataset, were assessed using ensembles encompassing changes of each of these configuration parameters. Each simulation captured the diurnal cycle of wind speed and stratification, producing LLJs during each overnight period; however, large discrepancies in relation to the observations were frequently observed, with each ensemble producing a wide range of distributions, reflecting highly variable representations of stratification during the weakly stable overnight conditions. Root mean square error and bias values computed over the LLJ cycle (late evening through the following morning) revealed that, while some configurations performed better or worse in different aspects and at different times, none exhibited definitively superior performance. The considerable root mean square error and bias values, even among the ‘best’ performing simulations, underscore the need for improved simulation capabilities for the prediction of near‐surface winds during LLJ conditions. Copyright © 2015 John Wiley & Sons, Ltd.     

US East Coast offshore wind energy resources and their relationship to peak‐time electricity demand

This study characterized the annual mean US East Coast (USEC) offshore wind energy (OWE) resource on the basis of 5 years of high‐resolution mesoscale model (Weather Research and Forecasting–Advanced Research Weather Research and Forecasting) results at 90 m height. Model output was evaluated against 23 buoys and nine offshore towers. Peak‐time electrical demand was analyzed to determine if OWE resources were coincident with the increased grid load. The most suitable locations for large‐scale development of OWE were prescribed, on the basis of the wind resource, bathymetry, hurricane risk and peak‐time generation potential. The offshore region from Virginia to Maine was found to have the most exceptional overall resource with annual turbine capacity factors (CF) between 40% and 50%, shallow water and low hurricane risk. The best summer resource during peak time, in water of ≤ 50 m depth, is found between Long Island, New York and Cape Cod, Massachusetts, due in part to regional upwelling, which often strengthens the sea breeze. In the South US region, the waters off North Carolina have adequate wind resource and shallow bathymetry but high hurricane risk. Overall, the resource from Florida to Maine out to 200 m depth, with the use of turbine CF cutoffs of 45% and 40%, is 965–1372 TWh (110–157 GW average). About one‐third of US or all of Florida to Maine electric demand can technically be provided with the use of USEC OWE. With the exception of summer, all peak‐time demand for Virginia to Maine can be satisfied with OWE in the waters off those states. Copyright © 2012 John Wiley & Sons, Ltd.     

Large‐eddy simulation of stable boundary layer turbulence and estimation of associated wind turbine loads

Stochastic simulation of turbulent inflow fields commonly used in wind turbine load computations is unable to account for contrasting states of atmospheric stability. Flow fields in the stable boundary layer, for instance, have characteristics such as enhanced wind speed and directional shear; these effects can influence loads on utility‐scale wind turbines. To investigate these influences, we use large‐eddy simulation (LES) to generate an extensive database of high‐resolution ( ～ 10 m), four‐dimensional turbulent flow fields. Key atmospheric conditions (e.g., geostrophic wind) and surface conditions (e.g., aerodynamic roughness length) are systematically varied to generate a diverse range of physically realizable atmospheric stabilities. We show that turbine‐scale variables (e.g., hub height wind speed, standard deviation of the longitudinal wind speed, wind speed shear, wind directional shear and Richardson number) are strongly interrelated. Thus, we strongly advocate that these variables should not be prescribed as independent degrees of freedom in any synthetic turbulent inflow generator but rather that any turbulence generation procedure should be able to bring about realistic sets of such physically realizable sets of turbine‐scale flow variables. We demonstrate the utility of our LES‐generated database in estimation of loads on a 5‐MW wind turbine model. More importantly, we identify specific turbine‐scale flow variables that are responsible for large turbine loads—e.g., wind speed shear is found to have a greater influence on out‐of‐plane blade bending moments for the turbine studied compared with its influence on other loads such as the tower‐top yaw moment and the fore‐aft tower base moment. Overall, our study suggests that LES may be effectively used to model inflow fields, to study characteristics of flow fields under various atmospheric stability conditions and to assess turbine loads for conditions that are not typically examined in design standards. Copyright © 2013 John Wiley & Sons, Ltd.     

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.     

中尺度风资源数值模拟试验分析

应用中尺度数值模式模拟地区的风资源状况是一种比较先进的方法。该模拟成果对大范围区域风能资源的宏观评估和风电场宏观选址具有很好的参考价值。着重介绍了WRF(Weather Research and Forecast)数值模式模拟方法,并采用该模拟方法对近海风电场的风资源进行了模拟。     

Diurnal and semidiurnal variability of coastal wind over Taiwanese waters

The Taiwan Strait is rich in offshore wind energy. Developing offshore wind farms is vital for renewable energy development. Rapid variations in the speed of offshore wind affect the capacity and operations of wind farms. On the basis of the demand for developing offshore wind farms in Taiwanese waters, this study examined in situ coastal wind data and documented the characteristics of the diurnal and semidiurnal oscillations in surface wind as well as the seasonal and spatial characteristics of these oscillations. Wavelet‐based rotary spectral analysis and significance level theory were adopted to quantify the occurrence probability and intensity of diurnal and semidiurnal wind fields. The occurrence probability of semidiurnal variations was approximately 50% greater than that of diurnal variations across Taiwan, with persistent occurrence of such variations near the southwest coast. The intensity of the diurnal phenomena was twice that of the semidiurnal phenomena, reaching an average of 27% of the wind energy variation at the potential sites located in Western Taiwan. Diurnal wind velocity oscillations were most intense during the fall but declined as the latitude moved from north to south. The instantaneous rotary spectrum was used to estimate the ellipticity of the wind vector. The analysis indicated that diurnal wind was dominated by land‐sea breezes. Moreover, the semidiurnal wind was less influenced by surface thermal effects than by diurnal phenomena. The effects of these phenomena on offshore wind energy conversion are considerable and should not be ignored. Copyright © 2014 John Wiley & Sons, Ltd.     

Automated classification of simulated wind field patterns from multiphysics ensemble forecasts

In this study, we have proposed an automated classification approach to identify meaningful patterns in wind field data. Utilizing an extensive simulated wind database, we have demonstrated that the proposed approach can identify low‐level jets, near‐uniform profiles, and other patterns in a reliable manner. We have studied the dependence of these wind profile patterns on locations (eg, offshore vs onshore), seasons, and diurnal cycles. Furthermore, we have found that the probability distributions of some of the patterns depend on the underlying planetary boundary layer schemes in a significant way. The future potential of the proposed approach in wind resource assessment and, more generally, in mesoscale model parameterization improvement is touched upon in this paper.     

A new turbulence model for offshore wind turbine standards

Correct turbulence intensity modeling is crucial for fatigue load estimation for wind turbine structural design. It is well known that the International Electrotechnical Commission 61400‐3 Normal Turbulence Model recommended for offshore wind turbine design is not representative of offshore wind conditions. A new model is urgently needed as offshore wind energy is rapidly developing worldwide. After evaluating the suitability of the Normal Turbulence Model at three sites in Asia, Europe and the USA, it is found that wind–wave interaction and stability correction should be taken into account in modeling the offshore turbulence intensity and wind speed relationship. Therefore, a new turbulence intensity model, which models wind–wave interaction with the Charnock equation and adjusts for the influence of atmospheric stability through empirical turbulence scaling functions for the unstable atmospheric boundary layer, was developed. The new model is physically based and is tested against observations from the three sites. It shows better performance than the Normal Turbulence Model and hence is recommended to replace the Normal Turbulence Model. For model application, only two parameters are required, which are defined herein to represent offshore sites with high, medium and low turbulence intensities. Copyright © 2013 John Wiley & Sons, Ltd.     

Estimation of offshore extreme wind from wind‐wave coupled modeling

A coupledwind‐wave modeling system is used to simulate 23 years of storms and estimate offshore extreme wind statistics. In this system, the atmospheric Weather Research and Forecasting (WRF) model and Spectral Wave model for Near shore (SWAN) are coupled, through a wave boundary layer model (WBLM) that is implemented in SWAN. The WBLM calculates momentum and turbulence kinetic energy budgets, using them to transfer wave‐induced stress to the atmospheric modeling. While such coupling has a trivial impact on the wind modeling for 10‐m wind speeds less than 20 ms^?1, the effect becomes appreciable for stronger winds—both compared with uncoupled WRF modeling and with standard parameterization schemes for roughness length. The coupled modeling output is shown to be satisfactory compared with measurements, in terms of the distribution of surface‐drag coefficient with wind speed. The coupling is also shown to be important for estimation of extreme winds offshore, where the WBLM‐coupled results match observations better than results from noncoupled modeling, as supported by measurements from a number of stations.     

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     

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.     

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.