实际地形风场CFD模拟中粗糙度的影响分析

以苏格兰Askervein小山为例,基于Fluent流体计算平台,结合NURBS地形建模方法,模拟了实际地形下的风场分布.分别在粗糙度长度为0～0.05m的情况下进行CFD风场模拟试验.与实测的风速加速比进行比较,发现模拟所得的风速加速比均方根误差在迎风面保持在6%以内,而背风面最大为26.56%,表明粗糙度条件对CFD风场模拟结果有较大影响.实现了用于CFD风场模拟的下垫面粗糙度精细化方法.在迎风坡和背风坡设置不同粗糙度长度的情况下,风速加速比均方根误差减小为7.42%,模拟结果在背风坡区域有明显改善.最后指出,在进行复杂地形风场CFD数值模拟时,有必要进行粗糙度条件的精细化设置.     

一种中微尺度耦合方法在风资源评估中的应用

风资源评估过程中,在缺少实际测风数据的情况下完成风场的精细化模拟具有重要的工程意义。在微尺度风场模拟过程中,引入中尺度数据为风场提供真实的边界条件,实现了降尺度精细化风场模拟。结合测风塔推算发现：相较于传统的统一边界条件的设置,利用中尺度数据分扇区生成边界条件进行降尺度的平均风速的精度有较明显提升。此外,还利用中尺度数据作为虚拟测风数据,对风资源评估中的定向计算结果进行校正,完成对机位点风机发电量等计算,解决无测风数据时风资源评估困难的难题。案例分析结果证实了该方法的先进性与工程应用价值。     

从天气尺度到风力机尺度大气运动的动力模拟

建立起中尺度天气模式WRF(weather research and forecasting)和计算流体力学模式Fluent的耦合系统,将WRF输出当做边界条件驱动Fluent,用于风场信息的精确模拟。利用该系统对下垫面条件复杂的鄱阳湖区域风场进行模拟分析,并将模拟数据与两个测风数据集进行定量比较,结果表明WRF耦合Fluent系统模拟的近地风场信息比WRF直接模拟结果有明显改善,证实中尺度天气模式耦合计算流体力学模式的技术思路有很好的可行性。这个耦合系统实现了从天气尺度到风力机尺度大气运动的模拟,能相对准确地给出风电场区域小尺度地形变化引起的风场细节。     

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。     

中国典型复杂地形风能资源特性及其形成机制

为提高对复杂地形风资源特性及其形成机制的认识,改进复杂地形风场数值模拟方法,分别选取代表极大起伏山地与宽谷地形的藏南谷地、代表极大起伏山地与深谷地形的横断山区以及代表中、小起伏丘陵山地的山西高原开展风资源特性观测实验,分析不同典型复杂地形条件下天气背景风场、局地大气环流、地形动力强迫、地表摩擦与热力作用对风资源特性形成的贡献,结果表明：山西高原局地大气环流的作用较小;藏南谷地和横断山区的山谷风环流对其风能资源特性的形成起主要作用,尤其是横断山区还存在多尺度的局地大气环流,传统的风电场风资源CFD数值模拟不足以描述如此复杂的风场。因此,在局地大气环流作用明显的复杂地形地区,需要采用中尺度与CFD结合的风电场选址风资源数值模拟方法。     

MICRO-SITING TECHNIQUE FOR WIND TURBINES UNDER COMPLEX TERRAIN

结合某油田井组周围实际复杂地形状况,在充分考虑周围地形的影响后建立简化三维分析模型.采用基于计算流体力学(CFD)的数值模拟方法,实现过山气流在低空复杂地形中的三维湍流模拟.在分别研究所建模型在不同来流风向时的风场分布及山丘表面的风速分布图后,最终确定了该井组内安装风力机的最佳位置及风力机塔架的高度.     

基于GWR模型的海河流域地下水储量降尺度研究

利用GRACE重力卫星数据联合GLDAS数据反演可得到地下水储量变化,能够在大尺度范围监测研究区域内的地下水储量变化,但得到的数据空间分辨率仅有0.25°,在小尺度范围内难以应用。基于GRACE陆地水储量及GLDAS浅层地表水储量与降水、NDVI之间的空间关系,提出一种基于地理加权回归模型(GWR模型)的地下水储量变化的降尺度方法,将地下水储量空间分辨率降尺度到1 km。结果表明,GWR模型降尺度方法成功应用于海河流域地区,降尺度后的地下水储量数据变化与46个验证点实测地下水位数据的相关系数均大于0.6,模拟结果合理可靠。进而利用降尺度结果分析了海河流域与北京平原的地下水储量的时空变化特征,结果与现有数据高度吻合,表明基于GWR模型的降尺度方法能有效提高地下水储量变化数据的空间分辨率。     

两种数值模式用于风场模拟的对比研究

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

动态风工况下复杂地形风电场流场多尺度仿真

首先在秒级风速数据的基础上构建动态风速函数模拟真实风速工况,同时基于高程数据构建某真实复杂地形的三维结构图。基于格子玻尔兹曼方法并结合自适应格子排布,对复杂地形风电场非定常流场进行数值计算,得到该风电场的风资源分布。之后在典型位置布置2台2 MW风力发电机,考虑真实风力机叶片的动态旋转计算风力机及真实复杂地形在动态风工况下的流场。研究实际复杂地形和动态风速下风电场的风速分布及尾流结构演变规律。结果表明：该方法可实现对复杂地形在动态来流风速作用下的风资源分布预测,并考虑风力机小尺度尾流结构实现对真实风电场流场的多尺度仿真。     

一种基于邻域保持的数值天气预报数据降维可信度评估准则

针对以风电、光伏发电为代表的新能源发电功率预测中数值天气预报（NWP）数据降维问题,应用不同特征选择和特征转换算法进行降维后,提出一种基于邻域保持的NWP降维可信度评估准则。该评估准则基于数据降维投影过程中样本点邻域变化,不考虑降维算法本身的降维原理及目标函数,可对不同降维算法在NWP数据降维中的可信度进行有效评估。研究结果可为其他研究提供选取NWP降维算法提供参考。     

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.     

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.     

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.     

Characterizing future large,rapid changes in aggregated wind power using Numerical Weather Prediction spatial fields

A critical limiting factor to the successful deployment of a large proportion of wind power in power systems is its predictability. Power system operators play a vital role in maintaining system security, and this task is greatly aided by useful characterizations of future system operations. A wind farm power forecast generally relies on the forecast output from a Numerical Weather Prediction (NWP) model, typically at a single grid point in the model to represent the wind farm's physical location. A key limitation of this approach is the spatial misplacement of weather features often found in NWP forecasts. This paper presents a methodology to display wind forecast information from multiple grid points at hub height around the wind farm location. If the raw forecast wind speeds at hub height at multiple grid points were to be displayed directly, they would be misleading as the NWP outputs take account of the estimated local surface roughness and terrain at each grid point. Hence, the methodology includes a transformation of the wind speed at each grid point to an equivalent value that represents the surface roughness and terrain at the chosen single grid point for the wind farm site. The chosen‐grid‐point‐equivalent wind speeds for the wind farm can then be transformed to available wind farm power. The result is a visually‐based decision support tool which can help the forecast user to assess the possibilities of large, rapid changes in available wind power from wind farms. A number of methods for displaying the field for multiple wind farms are discussed. The chosen‐grid‐point‐equivalent transformation also has other potential applications in wind power forecasting such as assessing deterministic forecast uncertainty and improving downscaling results. Copyright © 2008 John Wiley & Sons, Ltd.     

水平轴风力机静态失速特性

采用叶片表面边界层理论分析,三维旋转流场的数值模拟以及实验风力机模型的流动测量方法对水平轴风力机的静态失速特性进行了较为系统的研究。研究表明,旋转速度使得实际三维旋转风轮翼型表面的静压分布与二维非旋转条件下翼型表面静压分布产生较大差别,这是造成静态失速的原因之一。     

Performance and wake comparison of horizontal and vertical axis wind turbines under varying surface roughness conditions

A numerical study of both a horizontal axis wind turbine (HAWT) and a vertical axis wind turbine (VAWT) with similar size and power rating is presented. These large scale turbines have been tested when operating stand‐alone at their optimal tip speed ratio (TSR) within a neutrally stratified atmospheric boundary layer (ABL). The impact of three different surface roughness lengths on the turbine performance is studied for the both turbines. The turbines performance, the response to the variation in the surface roughness of terrain, and the most relevant phenomena involved on the resulting wake were investigated. The main goal was to evaluate the differences and similarities of these two different types of turbine when they operate under the same atmospheric flow conditions. An actuator line model (ALM) was used together with the large eddy simulation (LES) approach for predicting wake effects, and it was implemented using the open‐source computational fluid dynamics (CFD) library OpenFOAM to solve the governing equations and to compute the resulting flow fields. This model was first validated using wind tunnel measurements of power coefficients and wake of interacting HAWTs, and then employed to study the wake structure of both full scale turbines. A preliminary study test comparing the forces on a VAWT blades against measurements was also investigated. These obtained results showed a better performance and shorter wake (faster recovery) for an HAWT compared with a VAWT for the same atmospheric conditions.     

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.     

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.