Validation of boundary layer parameterization schemes in the weather research and forecasting model under the aspect of offshore wind energy applications— Part I: Average wind speed and wind shear

Five different planetary boundary layer (PBL) schemes in the weather research and forecasting model have been tested with respect to their capability to model boundary layer parameters relevant for offshore wind deployments. For the year 2005 model simulations based on the Yonsei University, asymmetric convection model version 2, quasi‐normal scale elimination, Mellor–Yamada–Janjic and Mellor–Yamada–Nakanishi–Niino PBL schemes with weather research and forecasting have been performed for the North Sea and validated against measurements of the Forschungsplattformen in Nord‐ und Ostsee Nr.1 platform. The investigations have been focused on the key parameters 100 m mean wind speed and wind shear expressed by the power law exponent α. All PBL‐schemes are doing well in reproducing averages and average annual statistics of the 100 m wind speed. However, two of the schemes (Yonsei University and Mellor–Yamada–Nakanishi–Niino) overestimate the wind speed above 15 m s^?1 systematically. The results for the power law wind profile show a large variability between the models and the observations for different atmospheric stability conditions and also differ a lot from the industry standards. Overall, the Mellor–Yamada–Janjic scheme performs slightly better than the others and is suggested as first choice for marine atmospheric boundary layer simulations without apriori information of atmospheric stability in the region of interest. Copyright © 2014 John Wiley & Sons, Ltd.     

Comparison of the atmospheric stability and wind profiles at two wind farm sites over a long marine fetch in the North Sea

A comparison of the atmospheric stability and wind profiles using data from meteorological masts located near two wind farm sites in the North Sea, Egmond aan Zee (up to 116 m) in the Dutch North Sea and Horns Rev (HR; up to 45 m) in the Danish North Sea, is presented. Only the measurements that represent long marine fetch are considered. It was observed that within a long marine fetch, the conditions in the North Sea are dominated by unstable [41% at Egmond aan Zee Offshore Wind Farm (OWEZ) and 33% at HR] and near‐neutral conditions (49% at OWEZ and 47% at HR), and stable conditions (10% at OWEZ and 20% at HR) occur for a limited period. The logarithmic wind profiles with the surface‐layer stability correction terms and Charnock's roughness model agree with the measurements at both sites in all unstable and near‐neutral conditions. An extended wind profile valid for the entire boundary layer is compared with the measurements. For the tall mast at Egmond aan Zee, it was found that for stable conditions, the scaling of the wind profiles with respect to boundary‐layer height is necessary, and the addition of another length scale parameter is preferred. At the lower mast at HR, the effect was not noticeable. Copyright © 2011 John Wiley & Sons, Ltd.     

Atmospheric stability and turbulence fluxes at Horns Rev—an intercomparison of sonic,bulk and WRF model data

Direct estimations of turbulent fluxes and atmospheric stability were performed from a sonic anemometer at 50 m height on a meteorological mast at the Horns Rev wind farm in the North Sea. The stability and flux estimations from the sonic measurements are compared with bulk results from a cup anemometer at 15 m height and potential temperature differences between the water and the air above. Surface flux estimations from the advanced weather research and forecast (WRF) model are also validated against the sonic and bulk data. The correlation between the sonic and bulk estimates of friction velocity is high and the highest among all velocity comparisons. From the sonic–bulk–WRF inter‐comparison, it is found that the atmospheric stability measures at the sonic height tend to be closer to the neutral value than the WRF and bulk estimates, which are performed within an air layer closer to the surface, not only from a systematic bulk and WRF under‐prediction of the friction velocity when compared with the sonic value but also because of the lower magnitude of the sonic heat flux compared with that from the WRF simulations. Although they are not measured but parameterized or estimated, the bulk–WRF comparisons of friction velocity and 10 m wind speed show good agreement. It is also shown that on a long‐term basis, the WRF and bulk estimates of stability are nearly equal and that a correction towards a slightly stable atmospheric condition has to be applied to the long‐term wind profile at Horns Rev and at other locations over the North Sea, the correction being larger for points close to the coast. Copyright © 2011 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.     

Offshore validation of a 3 km ERA‐Interim downscaling—WRF model's performance on static stability

In the evaluation of performance of numerical models, static stability has gained less interest and attention than many other atmospheric parameters. Nevertheless, this parameter may in fact have rather large implications as it controls such features as gravity waves and turbulence. In this paper, a closer look has been taken at the behavior of static stability in a 3 km gridded numerical downscaling of the ERA‐Interim reanalysis. The simulation performed with the Weather Research and Forecasting model has been nudged towards large scale analysis (spectral nudging) and satellite‐derived ocean surface winds (Quick Scatterometer). The validation of low‐level static stability was conducted in the North Sea using data from the FINO1 mast for year 2008, and a deeper part of the atmosphere was validated using the Ekofisk oil platform radiosonde data for years 2007–2010. The offshore mast comparison shows that the model over‐predicts the number of unstable cases and that the unstable cases are not unstable enough. The model simulated a clear dependency between vertical wind shear and static stability; however, this was not the case in the observations. The model produced too few events with weak turbulence, but rather put the emphasis on intermediate turbulent intensities. With the radiosonde data measuring the static stability over a deeper part of the atmosphere, similar results as for lower levels showed. In addition, the temperature gradient across the inversion at the boundary layer top was too shallow in the model, potentially letting too much wave energy escape the boundary layer. © 2015 The Authors Wind Energy Published by John Wiley & Sons Ltd.     

WRF模式在江苏省沿海风能预报系统中的应用

为研究WRF模式在沿海风能预报系统中的应用能力,以江苏省大丰市某70m高测风塔的2006年观测记录为例,基于4种不同近地面层-边界层参数化方案的组合,运用WRF模式分别模拟了该塔1、4、7、10月的逐小时风速,评估了不同近地面层-边界层参数化方案组合对沿海风电场轮毂高度风速的模拟效果,分析了WRF模式模拟沿海风电场风速的误差特征。结果表明,不同近地面-边界层参数化方案组合的总体模拟效果不同,MM5similarity近地面层和YSU边界层参数化方案组合的方案A效果稍好;4种参数化方案组合对秋、冬季节的风电场风速模拟精度都要明显好于春、夏季节,存在明显的季节性;WRF模式对海向风的模拟好于陆向风,且其模拟误差存在明显的方向性,沿海地区特殊的地形分布对其有显著的影响。     

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.     

Improving wind speed forecasts from the Weather Research and Forecasting model at a wind farm in the semiarid Coquimbo region in central Chile

Accurate predictions of the wind field are key for better wind power forecasts. Wind speed forecasts from numerical weather models present differences with observations, especially in places with complex topography, such as the north of Chile. The present study has two goals: (a) to find the WRF model boundary layer (PBL) scheme that best reproduces the observations at the Totoral Wind Farm, located in the semiarid Coquimbo region in north‐central Chile, and (b) to use an artificial neural network (ANN) to postprocess wind speed forecasts from different model domains to analyze the sensitivity to horizontal resolution. The WRF model was run with three different PBL schemes (MYNN, MYNN3, and QNSE) for 2013. The WRF simulation with the QNSE scheme showed the best agreement with observations at the wind farm, and its outputs were postprocessed using two ANNs with two algorithms: backpropagation (BP) and particle swarm optimization (PSO). These two ANNs were applied to the innermost WRF domains with 3‐km (d03) and 1‐km (d04) horizontal resolutions. The root‐mean‐square errors (RMSEs) between raw WRF forecasts and observations for d03 and d04 were 2.7 and 2.4 ms^?1 , respectively. When both ANN models (BP and PSO) were applied to Domains d03 and d04, the RMSE decreased to values lower than 1.7 ms^?1 , and they showed similar performances, supporting the use of an ANN to postprocess a three‐nested WRF domain configuration to provide more accurate forecasts in advance for the region.     

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.     

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.     

A simple atmospheric boundary layer model applied to large eddy simulations of wind turbine wakes

A simple model for including the influence of the atmospheric boundary layer in connection with large eddy simulations of wind turbine wakes is presented and validated by comparing computed results with measurements as well as with direct numerical simulations. The model is based on an immersed boundary type technique where volume forces are used to introduce wind shear and atmospheric turbulence. The application of the model for wake studies is demonstrated by combining it with the actuator line method, and predictions are compared with field measurements. Copyright © 2013 John Wiley & Sons, Ltd.     

ENDOW (efficient development of offshore wind farms): modelling wake and boundary layer interactions

While experience gained through the offshore wind energy projects currently operating is valuable, a major uncertainty in estimating power production lies in the prediction of the dynamic links between the atmosphere and wind turbines in offshore regimes. The objective of the ENDOW project was to evaluate, enhance and interface wake and boundary layer models for utilization offshore. The project resulted in a significant advance in the state of the art in both wake and marine boundary layer models, leading to improved prediction of wind speed and turbulence profiles within large offshore wind farms. Use of new databases from existing offshore wind farms and detailed wake profiles collected using sodar provided a unique opportunity to undertake the first comprehensive evaluation of wake models in the offshore environment. The results of wake model performance in different wind speed, stability and roughness conditions relative to observations provided criteria for their improvement. Mesoscale model simulations were used to evaluate the impact of thermal flows, roughness and topography on offshore wind speeds. The model hierarchy developed under ENDOW forms the basis of design tools for use by wind energy developers and turbine manufacturers to optimize power output from offshore wind farms through minimized wake effects and optimal grid connections. The design tools are being built onto existing regional‐scale models and wind farm design software which was developed with EU funding and is in use currently by wind energy developers. Copyright © 2004 John Wiley & Sons, Ltd.     

Computational Fluid Dynamics model of stratified atmospheric boundary‐layer flow

For wind resource assessment, the wind industry is increasingly relying on computational fluid dynamics models of the neutrally stratified surface‐layer. So far, physical processes that are important to the whole atmospheric boundary‐layer, such as the Coriolis effect, buoyancy forces and heat transport, are mostly ignored. In order to decrease the uncertainty of wind resource assessment, the present work focuses on atmospheric flows that include stability and Coriolis effects. The influence of these effects on the whole atmospheric boundary‐layer are examined using a Reynolds‐averaged Navier–Stokes k‐ ε model. To validate the model implementations, results are compared against measurements from several large‐scale field campaigns, wind tunnel experiments, and previous simulations and are shown to significantly improve the predictions. Copyright © 2013 John Wiley & Sons, Ltd.     

Exploring the gap between ‘best knowledge’ and ‘best practice’ in boundary layer meteorology for offshore wind energy

Onshore wind turbine technology is moving offshore, and the offshore wind industry tends to use larger turbines than those used over land. This calls for an improved understanding of the marine boundary layer. The standards used in the design of offshore wind turbines, particularly the rotor–nacelle assembly, are similar to those used for onshore wind turbines. As a result, simplifications regarding the marine boundary layer are made. Atmospheric stability considerations and wave effects, including the dynamic sea surface roughness, are two major factors affecting flow over sea versus land. Neutral stratification and a flat, smooth sea surface are routinely used as assumptions in wind energy calculations. Newly published literature in the field reveals that the assumption of a neutral stratification is not necessarily a conservative approach. Design tests based on neutral stratification give the lowest fatigue damage on the rotors. Turbulence, heat exchange and momentum transfer depend on the sea state, but this is usually ignored, and the sea surface is thought of as level and smooth. Field experiments and numerical simulations show that during swell conditions, the wind profile will no longer exhibit a logarithmic shape, and the surface drag relies on the sea state. Stratification and sea state are parameters that can be accounted for, and they should therefore be considered in design calculations, energy assessments and power output predictions. Copyright © 2012 John Wiley & Sons, Ltd.     

Optimal turbine spacing in fully developed wind farm boundary layers

As wind farms become larger, the asymptotic limit of the ‘fully developed’, or ‘infinite’, wind farm has been receiving an increased interest. This limit is relevant for wind farms on flat terrain whose length exceeds the height of the atmospheric boundary layer by over an order of magnitude. Recent computational studies based on large eddy simulation have identified various mean velocity equilibrium layers and have led to parameterizations of the effective roughness height that allow the prediction of the wind velocity at hub height as a function of parameters such as wind turbine spacing and loading factors. In the current paper, we employ this as a tool in making predictions of optimal wind turbine spacing as a function of these parameters, as well as in terms of the ratio of turbine costs to land surface costs. For realistic cost ratios, we find that the optimal average turbine spacing may be considerably higher than that conventionally used in current wind farm implementations. Copyright © 2011 John Wiley & Sons, Ltd.     

A statistical methodology for the estimation of extreme wave conditions for offshore renewable applications

Accurate estimation of extreme wave conditions is critical for offshore renewable energy activities and applications. The use of numerical wind and wave models gives a credible and convenient way of monitoring the general atmospheric and sea state conditions, especially in the absence of sufficient observational networks. However, when focusing on the study of non-frequent cases, in particular over coastal areas, increased uncertainty in the model outputs and accordingly in the reliability of the estimation of extreme waves becomes an important issue. The current study introduces a methodology to validate and post-process outputs from a high resolution numerical wave modeling system for extreme wave estimation based on the significant wave height. This approach is demonstrated through the data analysis at a relatively deep water site, FINO 1, as well as a relatively shallow water area, coastal site Horns Rev, which is located in the North Sea, west of Denmark. The post-processing targets at correcting the modeled time series of the significant wave height, in order to match the statistics of the corresponding measurements, including not only the conventional parameters such as the mean and standard deviation, but also a new parameter, the second-order spectral moment. This second-order spectral moment is essential for extreme value estimation but has so far been neglected in relevant studies. The improved model results are utilized for the estimation of the 50-year values of significant wave height as a characteristic index of extreme wave conditions. The results from the proposed methodology seem to be in a good agreement with the measurements at both the relatively deep, open water and the shallow, coastal water sites, providing a potentially useful tool for offshore renewable energy applications.     

LiDAR measurements for an onshore wind farm: Wake variability for different incoming wind speeds and atmospheric stability regimes

Wind measurements were performed with the UTD mobile LiDAR station for an onshore wind farm located in Texas with the aim of characterizing evolution of wind‐turbine wakes for different hub‐height wind speeds and regimes of the static atmospheric stability. The wind velocity field was measured by means of a scanning Doppler wind LiDAR, while atmospheric boundary layer and turbine parameters were monitored through a met‐tower and SCADA, respectively. The wake measurements are clustered and their ensemble statistics retrieved as functions of the hub‐height wind speed and the atmospheric stability regime, which is characterized either with the Bulk Richardson number or wind turbulence intensity at hub height. The cluster analysis of the LiDAR measurements has singled out that the turbine thrust coefficient is the main parameter driving the variability of the velocity deficit in the near wake. In contrast, atmospheric stability has negligible influence on the near‐wake velocity field, while it affects noticeably the far‐wake evolution and recovery. A secondary effect on wake‐recovery rate is observed as a function of the rotor thrust coefficient. For higher thrust coefficients, the enhanced wake‐generated turbulence fosters wake recovery. A semi‐empirical model is formulated to predict the maximum wake velocity deficit as a function of the downstream distance using the rotor thrust coefficient and the incoming turbulence intensity at hub height as input. The cluster analysis of the LiDAR measurements and the ensemble statistics calculated through the Barnes scheme have enabled to generate a valuable dataset for development and assessment of wind farm models.     

The effect of rotation on the boundary layer of a wind turbine blade

Design and analysis methods for wind turbines are presently based on relatively simple models of rotor blade aerodynamics, such as 2-D blade element/momentum theory (BEMT). Field investigations over the past few years have shown discrepancies between predicted and measured performance, owing to the effect of rotation on the wind turbine blade boundary layer distribution. The present paper is aimed at describing a fundamental phenomenon: the effect of rotation on the blade boundary layer of a wind turbine. In this paper, 3-D incompressible steady momentum integral boundary layer equations are employed to study this complex problem. By solving the 3-D integral boundary layer equations with the assumed velocity profiles and a closure model (including both laminar and turbulent boundary layer models), the effects of rotation on blade boundary layers are investigated. Several key parameters, such as separation position and momentum thickness, are calculated and compared for the rotation and non-rotation cases. It is concluded that the stall is postponed due to rotation and the separation point is delayed as a result of increasing rotation speed or decreasing blade spanwise position. Possible modifications that should be considered to the existing 2-D BEMT method are suggested.     

Enhanced estimation of boundary layer advective properties to improve space‐to‐time conversion processes for wind energy applications

Remote sensing instruments that scan have the ability to provide high‐resolution spatial measurements of atmospheric boundary layer winds across a region. However, the ability to use these spatially distributed measurements to extract temporal variations in the flow at time scales less than the measurement revisit period is historically limited. As part of this work, the framework for an enhanced space‐to‐time conversion technique is established, allowing for time histories of atmospheric boundary layer wind characteristics to be reliably extracted for locations within the measurement domain. This space‐to‐time conversion technique is made possible by quantifying momentum advection within the measurement domain, rather than simply assuming a uniform advection based on a singular mean wind speed and direction. The use of this technique enables the extraction of long lead‐time (ie, upwards of 60 seconds) forecasts of wind speed and direction at individual locations within the measurement domain, thereby expanding the application and potential benefits of scanning instruments. For example, these long lead‐time forecasts can be used to enhance proactive wind turbine control and more accurately define wind turbine wake statistics.     

Generalized coupled wake boundary layer model: applications and comparisons with field and LES data for two wind farms

We describe a generalization of the coupled wake boundary layer (CWBL) model for wind farms that can be used to evaluate the performance of wind farms under arbitrary wind inflow directions, whereas the original CWBL model (Stevens et al., J. Renewable and Sustainable Energy 7 , 023115 (2015)) focused on aligned or staggered wind farms. The generalized CWBL approach combines an analytical Jensen wake model with a ‘top‐down’ boundary layer model coupled through an iterative determination of the wake expansion coefficient and an effective wake coverage area for which the velocity at hub‐height obtained using both models converges in the ‘deep‐array’ portion (fully developed region) of the wind farm. The approach accounts for the effect of the wind direction by enforcing the coupling for each wind direction. Here, we present detailed comparisons of model predictions with large eddy simulation results and field measurements for the Horns Rev and Nysted wind farms operating over a wide range of wind inflow directions. Our results demonstrate that two‐way coupling between the Jensen wake model, and a ‘top‐down’ model enables the generalized CWBL model to predict the ‘deep‐array’ performance of a wind farm better than the Jensen wake model alone. The results also show that the new generalization allows us to study a much larger class of wind farms than the original CWBL model, which increases the utility of the approach for wind farm designers. Copyright © 2016 John Wiley & Sons, Ltd.