Modeling stable thermal stratification and its impact on wind flow over topography

Microscale flow models used in the wind energy industry commonly assume statically neutral conditions. These models can provide reasonable wind speed predictions for statically unstable and neutral flows; however, they do not provide reliable predictions for stably stratified flows, which can represent a substantial fraction of the available energy at a given site. With the objective of improving wind speed predictions and in turn reducing uncertainty in energy production estimates, we developed a Reynolds‐Averaged Navier–Stokes (RANS)‐based model of the stable boundary layer. We then applied this model to eight prospective wind farms and compared the results with on‐site wind speed measurements classified using proxies for stability; the comparison also included results from linear and RANS wind flow models that assume neutral stratification. This validation demonstrates that a RANS‐based model of the stable boundary layer can significantly and consistently improve wind speed predictions. Copyright © 2014 John Wiley & Sons, Ltd.     

基于分离涡方法的定日镜风效应研究

选用RANS湍流模型、大涡模拟与分离涡模型等计算流体动力学(CFD)方法,应用由新的湍流脉动流场产生方法DSRFG(discretizing and synthesizing random flow generation)模拟风场实际的湍流边界条件,对定日镜结构的风压分布及流场进行分析。将数值模拟结果与风洞试验数据进行对比,给出风向角为0°工况下定日镜结构的风压系数分布规律及特点,分析5种模型下定日镜周围的流场分布和涡量分布。结果表明,RANS模型虽然能够模拟出结构周围流场的基本规律,但却无法模拟出风场中的紊流和涡旋的分离扩散情况。大涡模拟及分离涡模型对风场中的紊流和涡旋的分离扩散有较好的模拟效果,在风压系数的分布上也与风洞试验数据拟合较好。在定日镜周围流场中脉动风压系数的分布上,分离涡模型的模拟结果较大涡模拟更为接近风洞试验值,且耗时更少。     

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.     

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     

Implementation of a Model Output Statistics based on meteorological variable screening for short‐term wind power forecast

A combination of physical and statistical treatments to post‐process numerical weather predictions (NWP) outputs is needed for successful short‐term wind power forecasts. One of the most promising and effective approaches for statistical treatment is the Model Output Statistics (MOS) technique. In this study, a MOS based on multiple linear regression is proposed: the model screens the most relevant NWP forecast variables and selects the best predictors to fit a regression equation that minimizes the forecast errors, utilizing wind farm power output measurements as input. The performance of the method is evaluated in two wind farms, located in different topographical areas and with different NWP grid spacing. Because of the high seasonal variability of NWP forecasts, it was considered appropriate to implement monthly stratified MOS. In both wind farms, the first predictors were always wind speeds (at different heights) or friction velocity. When friction velocity is the first predictor, the proposed MOS forecasts resulted to be highly dependent on the friction velocity–wind speed correlation. Negligible improvements were encountered when including more than two predictors in the regression equation. The proposed MOS performed well in both wind farms, and its forecasts compare positively with an actual operative model in use at Risø DTU and other MOS types, showing minimum BIAS and improving NWP power forecast of around 15% in terms of root mean square error. Further improvements could be obtained by the implementation of a more refined MOS stratification, e.g. fitting specific equations in different synoptic situations. Copyright © 2012 John Wiley & Sons, Ltd.     

A stochastic wind turbine wake model based on new metrics for wake characterization

Understanding the detailed dynamics of wind turbine wakes is critical to predicting the performance and maximizing the efficiency of wind farms. This knowledge requires atmospheric data at a high spatial and temporal resolution, which are not easily obtained from direct measurements. Therefore, research is often based on numerical models, which vary in fidelity and computational cost. The simplest models produce axisymmetric wakes and are only valid beyond the near wake. Higher‐fidelity results can be obtained by solving the filtered Navier–Stokes equations at a resolution that is sufficient to resolve the relevant turbulence scales. This work addresses the gap between these two extremes by proposing a stochastic model that produces an unsteady asymmetric wake. The model is developed based on a large‐eddy simulation (LES) of an offshore wind farm. Because there are several ways of characterizing wakes, the first part of this work explores different approaches to defining global wake characteristics. From these, a model is developed that captures essential features of a LES‐generated wake at a small fraction of the cost. The synthetic wake successfully reproduces the mean characteristics of the original LES wake, including its area and stretching patterns, and statistics of the mean azimuthal radius. The mean and standard deviation of the wake width and height are also reproduced. This preliminary study focuses on reproducing the wake shape, while future work will incorporate velocity deficit and meandering, as well as different stability scenarios. Copyright © 2016 John Wiley & Sons, Ltd.     

Application of the actuator surface concept to wind turbine rotor aerodynamics

The structure of blade tip vortices is recognized as a key issue in wind turbine aerodynamic modelling by many researchers in the field. In the search for an intermediate model between full Navier–Stokes and blade‐element momentum simulations, this article presents a method using rotating actuator surfaces to model wind turbine aerodynamics. An actuator surface is a simple planar surface, porous to the flow, which is characterized by velocity and pressure discontinuities, whose action on the flow is achieved through an attached system of forces. These discontinuities and forces are determined from blade‐element analysis and the Kutta–Joukowski relation. After implementing this concept in a three‐dimensional CFD (Computational Fluid Dynamics) method, results are produced for the experimental rotors of NREL and TUDelft. The method is validated against both experimental measurements and the predictions of three other numerical models for wind turbine aerodynamic analysis. Qualitative and quantitative comparisons show that the actuator surface concept agrees well with the other numerical models. In addition to rotor aerodynamic analysis, the actuator surface concept can be used in the study of wake aerodynamics, or as the Eulerian flow solver in hybrid methods. Copyright © 2009 John Wiley & Sons, Ltd.     

基于NWP/CFD嵌套的复杂地形风场模拟研究

为解决复杂地形边界层风场模拟的边界条件问题,结合中尺度数值天气预报(NWP)和小尺度计算流体动力学(CFD)技术,提出一种基于NWP/CFD嵌套的降尺度风场模拟方法。该方法依据NWP低分辨率输出结果,建立目标区域来流边界数据库,并结合反距加权插值获得CFD边界精细格点信息。以沿海地区2处复杂地形为对象,重现目标区域内的风场日变化。参考经验风剖面分布形式,验证插值算法在中小尺度耦合界面数据传递的适用性。然后基于模拟域内实测点数据及误差统计指标,评估风场模拟效果。结果表明,所提降尺度风场模拟方法能有效反映微地形、微气象对风力机尺度大气运动影响。     

基于奇异值分解与卡尔曼滤波修正多位置NWP的短期风电功率预测

考虑到数值天气预报网格点位置和系统误差对短期风电功率预测精度的影响,提出一种基于奇异值分解与卡尔曼滤波修正多位置数值天气预报的短期风电功率预测模型。首先通过奇异值分解对多位置数值天气预报数据进行特征提取与降维处理;然后使用卡尔曼滤波方法修正数值天气预报风速数据,降低数值天气预报的系统误差;最后基于极端随机森林算法,利用修正的数值天气预报数据搭建短期风电功率预测模型。通过对某风电场进行仿真,并与单位置、未降维、未修正模型比较,结果表明降维修正模型的预测效果最好,平均误差和均方根误差分别为7.94%和9.96%。     

Buoyancy-driven single-sided natural ventilation in buildings with large openings

Full-scale experimental and computational fluid dynamics (CFD) methods were used to investigate buoyancy-driven single-sided natural ventilation with large openings. Detailed airflow characteristics inside and outside of the room and the ventilation rate were measured. The experimental data were used to validate two CFD models: Reynolds averaged Navier-Stokes equation (RANS) modeling and large eddy simulation (LES). LES provides better results than the RANS modeling. With LES, the mechanism of single-sided ventilation was examined by turbulence statistical analysis. It is found that most energy is contained in low-frequency regions, and mean flow fields play an important role.     

Using nacelle‐based wind speed observations to improve power curve modeling for wind power forecasting

Wind power forecasting for projection times of 0–48 h can have a particular value in facilitating the integration of wind power into power systems. Accurate observations of the wind speed received by wind turbines are important inputs for some of the most useful methods for making such forecasts. In particular, they are used to derive power curves relating wind speeds to wind power production. By using power curve modeling, this paper compares two types of wind speed observations typically available at wind farms: the wind speed and wind direction measurements at the nacelles of the wind turbines and those at one or more on‐site meteorological masts (met masts). For the three Australian wind farms studied in this project, the results favor the nacelle‐based observations despite the inherent interference from the nacelle and the blades and despite calibration corrections to the met mast observations. This trend was found to be stronger for wind farm sites with more complex terrain. In addition, a numerical weather prediction (NWP) system was used to show that, for the wind farms studied, smaller single time‐series forecast errors can be achieved with the average wind speed from the nacelle‐based observations. This suggests that the nacelle‐average observations are more representative of the wind behavior predicted by an NWP system than the met mast observations. Also, when using an NWP system to predict wind farm power production, it suggests the use of a wind farm power curve based on nacelle‐average observations instead of met mast observations. Further, it suggests that historical and real‐time nacelle‐average observations should be calculated for large wind farms and used in wind power forecasting. Copyright © 2011 John Wiley & Sons, Ltd.     

On wind turbine loads during the evening transition period

The late afternoon hours in the diurnal cycle precede the development of the nocturnal stable boundary layer. This “evening transition” (ET) period is often when energy demand peaks. This period also corresponds to the time of day that is a precursor to late‐afternoon downbursts, a subject of separate interest. To capture physical characteristics of wind fields in the atmospheric boundary layer (ABL) during this ET period, particularly the interplay of shear and turbulence, stochastic simulation approaches, although more tractable, are not suitable. Large‐eddy simulation (LES), on the other hand, may be used to generate high‐resolution ABL turbulent flow fields. We present a suite of idealized LES four‐dimensional flow fields that define a database representing different combinations of large‐scale atmospheric conditions (characterized by associated geostrophic winds) and surface boundary conditions (characterized by surface heat fluxes). Our objective is to evaluate the performance of wind turbines during the ET period. Accordingly, we conduct a statistical analysis of turbine‐scale wind field variables. We then employ the database of these LES‐based inflow wind fields in aeroelastic simulations of a 5‐MW wind turbine. We discuss how turbine loads change as the ET period evolves. We also discuss maximum and fatigue loads on the rotor and tower resulting from different ABL conditions. Results of this study suggest that, during the ET period, the prevailing geostrophic wind speed affects the mean and variance of longitudinal winds greatly and thus has significant influence on all loads except the yaw moment which is less sensitive to uniform and symmetric incoming flow. On the other hand, surface heat flux levels affect vertical turbulence and wind shear more and, as a result, only affect maximum blade flapwise bending and tower fore‐aft bending loads.     

Estimating the potential yield of small building‐mounted wind turbines

The wind profile in the urban boundary layer is described as following a logarithmic curve above the mean building height and an exponential curve below it. By considering the urban landscape to be an array of cubes, a method is described for calculating the surface roughness length and displacement height of this profile. Firstly, a computational fluid dynamics (CFD) model employing a k‐? turbulence model is used to simulate the flow around a cube. The results of this simulation are compared with wind tunnel measurements in order to validate the code. Then, the CFD model is used to simulate the wind flow around a simple pitched‐roof building, using a semi‐logarithmic inflow profile. An array of similar pitched‐roof houses is modelled using CFD to determine the flow characteristics within an urban area. Mean wind speeds at potential turbine mounting points are studied, and optimum mounting points are identified for different prevailing wind directions. A methodology is proposed for estimating the energy yield of a building‐mounted turbine from simple information such as wind atlas wind speed and building density. The energy yield of a small turbine on a hypothetical house in west London is estimated. The energy yield is shown to be very low, particularly if the turbine is mounted below rooftop height. It should be stressed that the complexity of modelling such urban environments using such a computational model has limitations and results can only be considered approximate, but nonetheless, gives an indication of expected yields within the built environment. Copyright © 2007 John Wiley & Sons, Ltd.     

Unstructured overset incompressible computational fluid dynamics for unsteady wind turbine simulations

Overset computational fluid dynamics (CFD) methods are the most sophisticated methods currently available to predict the unsteady motion of wind turbine blades without the need for additional simplifications or restrictions on the turbine operational conditions. An unstructured implementation of the governing equations of motion permits rapid modeling of the salient components, such as nacelles, towers and other localized obstructions of interest. A time‐accurate incompressible formulation accelerates the convergence of the solution, in addition to eliminating the need for low‐Mach number preconditioning, which can be problematic and computationally expensive for time‐accurate simulations. The use of a hybrid Reynolds‐averaged Navier–Stokes/large eddy simulation (RANS/LES) turbulence method is observed to improve the prediction and extent of separation, as well as integrated performance variables for stalled rotors under fully turbulent conditions. Copyright © 2012 John Wiley & Sons, Ltd.     

Evaluation of layout and atmospheric stability effects in wind farms using large‐eddy simulation

Large‐eddy simulation (LES) has been used previously to study the effect of either configuration or atmospheric stability on the power generated by large wind farms. This is the first study to consider both stability and wind farm configuration simultaneously and methodically with LES. Two prevailing wind directions, two layouts (turbines aligned versus staggered with respect to the wind) and three stabilities (neutral and moderately unstable and stable) were evaluated. Compared with neutral conditions, unstable conditions led to reduced wake losses in one configuration, to enhanced wake losses in two and to unchanged wake losses in one configuration. Conversely, stable conditions led to increased wake losses in one, decreased wake losses in two and unchanged wake losses in one configuration. Three competing effects, namely, rates of wake recovery due to vertical mixing, horizontal spread of wakes and localized regions of acceleration caused by multiple upstream wakes, were identified as being responsible for the observed trends in wake losses. The detailed flow features responsible for these non‐linear interactions could only be resolved by the LES. Existing analytical models ignore stability and non‐linear configuration effects, which therefore need to be incorporated. Copyright © 2017 John Wiley & Sons, Ltd.     

Diurnal cycle RANS simulations applied to wind resource assessment

Microscale computational fluid dynamics (CFD) models can be used for wind resource assessment on complex terrains. These models generally assume neutral atmospheric stratification, an assumption that can lead to inaccurate modeling results and to large uncertainties at certain sites. We propose a methodology for wind resource evaluation based on unsteady Reynolds averaged Navier‐Stokes (URANS) simulations of diurnal cycles including the effect of thermal stratification. Time‐dependent boundary conditions are generated by a 1D precursor to drive 3D diurnal cycle simulations for a given geostrophic wind direction sector. Time instants of the cycle representative of four thermal stability regimes are sampled within diurnal cycle simulations and combined with masts time series to obtain the wind power density (WPD). The methodology has been validated on a complex site instrumented with seven met masts. The WPD spatial distribution is in good agreement with observations with the mean absolute error improving 17.1% with respect to the neutral stratification assumption.     

Physical modelling and advanced simulations of gas–liquid two-phase jet flows in atomization and sprays

This review attempts to summarize the physical models and advanced methods used in computational studies of gas–liquid two-phase jet flows encountered in atomization and spray processes. In traditional computational fluid dynamics (CFD) based on Reynolds-averaged Navier–Stokes (RANS) approach, physical modelling of atomization and sprays is an essential part of the two-phase flow computation. In more advanced CFD such as direct numerical simulation (DNS) and large-eddy simulation (LES), physical modelling of atomization and sprays is still inevitable. For multiphase flows, there is no model-free DNS since the interactions between different phases need to be modelled. DNS of multiphase flows based on the one-fluid formalism coupled with interface tracking algorithms seems to be a promising way forward, due to the advantageous lower costs compared with a multi-fluid approach. In LES of gas–liquid two-phase jet flows, subgrid-scale (SGS) models for complex multiphase flows are very immature. There is a lack of well-established SGS models to account for the interactions between the different phases. In this paper, physical modelling of atomization and sprays in the context of CFD is reviewed with modelling assumptions and limitations discussed. In addition, numerical methods used in advanced CFD of atomization and sprays are discussed, including high-order numerical schemes. Other relevant issues of modelling and simulation of atomization and sprays such as nozzle internal flow, dense spray, and multiscale modelling are also briefly reviewed.     

Analysing wind power ramp events and improving very short-term wind power predictions by including wind speed observations

Though wind power predictions have been consistently improved in the last decade, persistent reasons for remaining uncertainties are sudden large changes in wind speed, so-called ramps. Here, we analyse the occurrence of ramp events in a wind farm in Eastern Germany and the performance of a wind power prediction tool in forecasting these events for forecasting horizons of 15 and 30 min. Results on the seasonality of ramp events and their diurnal cycle are presented for multiple ramp definition thresholds. Ramps were found to be most frequent in March and April and least frequent in November and December. For the analysis, the wind power prediction tool is fed by different wind velocity forecast products, for example, numerical weather prediction (NWP) model and measurement data. It is shown that including observational wind speed data for very short-term wind power forecasts improves the performance of the power prediction tool compared to the NWP reference, both in terms of ramp detection and in decreasing the mean absolute error between predicted and generated wind power. This improvement is enhanced during ramp events, highlighting the importance of wind observations for very short-term wind power prediction.     

风力机翼型大攻角分离流的数值模拟

为了准确预测风力机翼型在大攻角下分离流动的气动性能,并且为风力机的设计与安全运行提供一种可靠的数值模拟手段,针对某风力机专用翼型,分别采用基于非定常不可压缩Navier-Stokes方程的大涡模拟(LES)模型、RNG k-ε模型和Standard k-ε模型对其气动性能进行数值模拟,并计算出翼型攻角为35～90°,雷诺数为2×106时的气动力参数。将不同湍流模型的计算结果与风洞试验数据进行比较,并分析流场结构。分析结果表明,LES模型能够准确地模拟出翼型表面的分离流动,计算结果与试验数据取得了很好的一致性,并且优于RNG k-ε模型和Standard k-ε模型的模拟结果。     

Development of a geophysic model output statistics module for improving short‐term numerical wind predictions over complex sites

Developed for short‐term (0–48 h) wind power forecasting purposes, high‐resolution meteorological forecasts for Eastern Canada are available from Environment Canada's Numerical Weather Prediction (NWP) model configured on a limited area (GEM‐LAM). This paper uses 3 years of forecast data from this model for the region of North Cape (Prince Edward Island, Canada). Although the model resolution is relatively high (2.5 km), statistical analysis and site inspection reveal that the model does not have a sufficiently refined grid to properly represent the meteorological phenomena over this complex coastal site. To cope with such representation error, a generalized Geophysic Model Output Statistics (GMOS) module is developed and applied to reduce the forecast error of the NWP forecasts. GMOS differs from other Model Output Statistics (MOS) that are widely used by meteorological centres in the following aspects: (i) GMOS takes into account the surrounding geophysical parameters such as surface roughness, terrain height, etc., along with wind direction; (ii) GMOS can be directly applied for model output correction without any training. Compared with other methods, GMOS using a multiple grid point approach improves the GEM‐LAM predictions root mean squared error by 1–5% for all time horizons and most meteorological conditions. Also, the topographic signature of the forecast error (uneven directional distribution of the forecast error related to the surface characteristics) due to misrepresentation issues is significantly reduced. The NWP forecasts combined with GMOS outperform the persistence model from a 2 h horizon, instead of 3 h using MOS. Finally, GMOS is applied and validated at two other sites located in New Brunswick, Canada. Similar improvements on the forecasts were observed, thus showing the general applicability of GMOS. Copyright © 2012 John Wiley & Sons, Ltd.