水平轴风力机尾迹流场试验

在水平轴风力机模型不同尖速比条件下,利用旋转单斜丝热线在风轮下游进行尾迹流场速度测量。采用周期性采样和锁相平均技术热线测量技术,获得了风轮下游尾迹三维流场的定量信息,为准确计算风力机的流场、载荷和气动特性等提供了依据。试验结果表明:风轮下游尾迹区内气流存在明显的三维性。尾迹在向风轮下游的发展传播过程中,尾迹中心形成的运动轨迹是与风轮叶片旋转方向相反的螺旋线。尾迹区内的速度亏损随风轮下游轴向位置的增加而减弱,在气流向下游流动的过程中尾迹速度亏损值逐渐衰减,尾迹区的宽度不断扩大,并逐渐与主流掺混融合。尾迹区内相同轴向位置上不同叶高处的速度型相似。在叶片的尾迹区内,流动的紊流强度大大高于周围的非尾迹区,其中紊流强度径向、切向分量较大,轴向分量最小,尾迹区内的紊流具有高度不均匀性。     

水平轴风力机尾迹三维流场的热线测量

利用单斜丝热线旋转进行水平轴风力机模型的尾迹流场测量。热线测量过程中采用了周期性采样和锁相平均技术,获得了风轮下游尾迹三维流场的定量信息,并利用自行编制的MATLAB程序求出尾迹流场的三维平均速度。试验结果表明：采用旋转单斜丝热线结合周期性多点采样技术构成的热线测量系统,能够获得风轮流场速度分布等准确的定量信息,是一种比较有效的风力机三维流场动态测试方法。风轮下游的尾迹区内存在速度亏损,速度亏损随着风轮下游轴向位置的增加而减弱。风轮下游4倍弦长外,尾迹区的速度就已经基本恢复到主流速度。在气流向下游流动的过程中尾迹的轴向速度亏损形成的波谷曲线渐趋平缓,尾迹区的宽度不断扩大,2倍弦长以后尾迹宽度基本不再扩大,并逐渐与主流掺混融合。     

水平轴风力机尾迹流场PIV实验研究

在水平轴风力机模型不同尖速比条件下,利用PIV粒子图像测速技术对风轮尾迹流场进行了测量。采用锁相平均测量技术,获得了风轮尾迹流场的瞬时速度场、时均速度场、涡量场等有关定量信息,为准确计算风力机的流场、载荷和气动特性等提供了依据。实验结果表明:风轮叶片尾缘后侧的尾迹中存在轴向速度亏损区。尾迹在叶片尾缘生成后,随即发生膨胀。直到风轮下游2倍弦长以后,尾迹低速区逐渐衰减,轴向速度不断增加,尾迹区同时发生收缩现象。风轮尾迹涡从叶片尾缘脱落后,在向下游发展传播过程中,尾迹涡的涡心所形成的运动轨迹是与风轮叶片旋转方向相反的螺旋线,涡量数值随着螺旋线向风轮下游的延伸而减小。由于风力机叶片数少,相邻叶片之间的尾迹基本上不存在互相干扰的现象。     

水平轴风力机风轮子午面流场结构的实验研究

利用线式互相关PIV系统,采用轴编码器定位周期采样技术,在不同尖速比下对旋转水平轴风力机风轮不同子午面下游流场结构进行测量.分析得到不同条件下的瞬时图、时均图,重点对叶尖涡诱导效应区进行研究.实验结果表明:在风轮下游尾迹中可清晰看到叶轮近尾迹流场中的外部主流区、叶尖涡诱导效应区和中心尾迹区.其中风轮下游尾迹流管廓线是锥形螺旋体;叶尖涡核直径随轴向距离的增加而增大,随着测试方位角的增加,尾迹中各叶片产生的叶尖涡沿螺旋锥形廓线有序地向下游扩散流动;随着尖速比的增加,内部中心尾迹区轴向速度亏损值逐渐增加,并且中心尾迹区的范围逐渐扩大.     

水平轴风力机尾流特性的数值研究

对600kW单风轮和7倍风轮直径(7D)间距的两风轮水平轴风力机在不同来流风速条件进行三维流场数值模拟.结果显示:风力机下游流场存在三维速度流动,轴向速度在尾迹区存在明显亏损,且随尾迹向下游的发展,轴向速度亏损逐渐减少.不同来流风速条件下风轮尾迹流的发展有一定区别,在来流风速较低的条件下尾流风速恢复较快.风场在布置风力机时应考虑当地的风速条件,若多数情况在额定风速或超过额定风速工况下运行,则前后风轮间距应大于7倍风轮直径;否则可考虑缩短前后风轮间距.     

水平轴风力机塔筒近尾迹流场PIV实验研究

应用PIV粒子图像测速技术,在风洞中测量水平轴风力机模型塔筒的近尾迹流场。通过对模型风力机在不同运行尖速比下、不同叶高平面内的塔筒近尾迹速度场和涡量场的分析,得到了塔筒近尾迹流场的结构特征,为水平轴风力机气动设计、性能预测及CFD数值模拟提供了依据。实验结果表明,受到风轮旋转效应的影响,在水平轴风力机塔筒下游轴向距离6倍当地弦长范围内,近尾迹在水平面内向一侧明显偏转,近尾迹流场相对塔筒中心轴面呈非对称分布。随着尖速比的减小,塔筒下游轴向距离6倍当地弦长范围内,近尾迹涡流宽度逐渐增大,且尾迹向一侧偏转的程度也越大。风力机叶片对塔筒近尾迹涡流的影响,在叶根部位高度平面内尤为显著,随着叶片高度的增加,叶片对塔筒近尾迹涡流的影响逐渐减弱。     

风剪切来流对风力机近尾迹流动特性影响

在风剪切来流风况下,对WindPACT 1.5MW风力机近尾迹流动特性进行了数值计算,同时研究了三种风剪切系数(0.1、0.2和0.3)对风力机近尾迹流动特性的影响。基于雷诺平均不可压N-S方程的计算流体力学方法数值模拟三维非定常的风力机流场,其中,湍流模型选取Shear Stress Transport k-ω湍流模型。研究结果表明:在近尾迹区域,来流空气的轴向诱导因子和切向诱导因子受到旋转叶片的强烈影响,并在风力机下游形成明显的轴向速度亏损。这种轴向速度亏损随空气向下游流动过程中,逐渐减弱。轴向诱导因子和切向诱导因子受风剪切影响,呈非周期性分布,并且风剪切系数增加,这种影响随之增强。     

叶片旋向对风力机尾流特性影响的试验研究

采用一种简单、有效的方法来改善风力机尾流效应,提升下游风力机功率。进行叶片旋向对风力机尾流特性的试验研究,利用低频粒子图像测速（PIV）系统对NACA4415翼型的叶片进行扰流流场测试并采集风力机的尾流数据。当2台串列排布的风力机旋向不同时,首先在下游风力机前1D(D为风轮直径)处,叶尖涡涡核位置向中央尾迹区偏移,而外部主流区的流体在叶尖涡诱导区的输运和卷吸作用下持续进入中央尾迹区并与之掺混使得轴向速度恢复得更佳;进而分析下游风力机后1D的流场数据,结果显示：虽然下游风力机叶尖涡几何结构被“打碎”,但涡核能量却未降低;最后探讨影响风力机功率特性的因素,下游风力机入流角的增大促使下游风力机捕获更多风能,在风轮间距为2D时,逆向旋转的功率比比同向旋转时高4.70%,且功率比随间距增加其增幅逐渐减小。     

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。     

水平轴风力机近尾迹流场数值模拟

在水平轴风力机模型不同尖速比条件下,对风轮的近尾迹流场进行了数值模拟,获得了风轮近尾迹流场的速度分布特点、尾迹的流动发展规律等有关定量信息,为准确计算风力机的流场、载荷和气动特性等提供了参考依据。     

On atmospheric stability in the dynamic wake meandering model

The present study investigates a new approach for capturing the effects of atmospheric stability on wind turbine wake evolution and wake meandering by using the dynamic wake meandering model. The most notable impact of atmospheric stability on the wind is the changes in length and velocity scales of the atmospheric turbulence. The length and velocity scales in the turbulence are largely responsible for the way in which wind turbine wakes meander as they convect downstream. The hypothesis of the present work is that appropriate turbulence scales can be extracted from the oncoming atmospheric turbulence spectra and applied to the dynamic wake meandering model to capture the correct wake meandering behaviour. The ambient turbulence in all stability classes is generated using the Mann turbulence model, where the effects of non‐neutral atmospheric stability are approximated by the selection of input parameters. In order to isolate the effect of atmospheric stability, simulations of neutral and unstable atmospheric boundary layers using large‐eddy simulation are performed at the same streamwise turbulence intensity level. The turbulence intensity is kept constant by calibrating the surface roughness in the computational domain. The changes in the turbulent length scales due to the various atmospheric stability states impact the wake meandering characteristics and thus the power generation by the individual turbines. The proposed method is compared with results from both large‐eddy simulation coupled with an actuator line model and field measurements, where generally good agreement is found with respect to the velocity, turbulence intensity and power predictions. Copyright © 2013 John Wiley & Sons, Ltd.     

安装高程对潮流能水轮机尾迹特性影响试验研究

为探究安装高程对潮流能水轮机尾迹特性的影响,以模型潮流能水轮机为研究对象,采用ADV采集尾流场速度数据,对比分析不同高程下的尾流场特性,揭示安装高程对潮流能水轮机尾迹特性的影响规律.结果表明:随着安装高程的增加,转轮后方尾流速恢复速度逐渐加快,而湍流强度和雷诺切应力恢复速度有逐渐减小的趋势;横向尾流场水动力特性沿转轮中...     

Flow characterization in the near‐wake region of a horizontal axis wind turbine

An experimental study is conducted to investigate the flow dynamics within the near‐wake region of a horizontal axis wind turbine using particle image velocimetry (PIV). Measurements were performed in the horizontal plane in a row of four radially distributed measurement windows (tiles), which are then patched together to obtain larger measurement field. The mean and turbulent components of the flow field were measured at various blade phase angles. The mean velocity and turbulence characteristics show high dependency on the blade phase angle in the near‐wake region closer to the blade tip and become phase independent further downstream at a distance of about one rotor diameter. In the near‐wake region, both the mean and turbulent characteristics show a systemic variation with the phase angle in the blade tip region, where the highest levels of turbulence are observed. The streamlines of the instantaneous velocity field at a given phase allowed to track a tip vortex which showed wandering trend. The tip vortices are mostly formed at r/R > 1, which indicates the wake expansion. Results also show the gradual movement of the vortex region in the axial direction, which can be attributed to the dynamics of the helical tip vortices which after being generated from the tip, rotate with respect to the blade and move in the axial direction because of the axial momentum of the flow. The axial velocity deficit was compared with other laboratory and field measurements. The comparison shows qualitative similarity. Copyright © 2015 John Wiley & Sons, Ltd.     

Near and far field flow disturbances induced by model hydrokinetic turbine: ADV and ADP comparison

Wake flows downstream of hydrokinetic turbines are characterized by hub and tip vortices, a velocity deficit and an increase in turbulence intensity. Velocity and turbulence recovery in the wakes of individual turbines constrains the density of turbines in an array and limits the amount of energy that can be produced by a turbine farm. However, few hydrokinetic turbine flow recovery studies have been conducted, especially on the far-field flow characteristics. Nor have studies evaluated the accuracy of acoustic Doppler profiler measurements in the wakes of turbines. The present study examines vertical profiles of mean velocity and turbulence, as well as longitudinal profiles of velocity deficit and turbulence levels measured at the symmetry plane of a model three-blade axial flow turbine in a large open channel flow. Mean velocity and turbulence statistics are measured using an acoustic Doppler velocimeter (ADV) and a pulse coherent acoustic Doppler profiler (ADP). ADV and corrected-ADP derived values of mean velocity, turbulence intensity and root-mean-square velocity constitute a well-documented data set that can be used to validate numerical models simulating the effects of hydrokinetic turbine arrays. We found that 80% of the flow recovery occurred about ten diameters downstream from the rotor plane, which suggests that practical values for longitudinal spacing of turbines should be between ten and fifteen diameters. Significant errors observed in mean velocity and turbulence statistics derived from ADP measurements in the near wake region raise concerns on the use of these instruments for such measurements in lab and field studies. Although the cause of some of the errors requires further investigation, we show that errors in turbulence intensity can be successfully corrected with supplemental ADV measurements.     

Investigation of the influence of various numbers of impeller blades on internal flow field analysis and the pressure pulsation of an axial pump based on transient flow behavior

In the current study, the flow behavior in an axial pump through changing the number of impeller blades is analyzed. Due to the number of blades being very important geometrical parameters in the pump, the study of the influence of various numbers of blades on flow and pressure pulsation in the pump is carried out using the computational fluid dynamics technique. The sliding mesh with the standard turbulence k‐ε model is used to investigate the unsteady flow with several flows and impeller blades. Pump performance prediction results with available experimental data indicate reasonable and good agreement with each other. Static pressure, shear stress, and different velocity compounds are qualitatively analyzed. Moreover, the fluctuation pressure and average pressure under different operating conditions and impeller blades are quantitatively investigated. The numerical results show that the impeller blade has a high impact on pressure, shear stress, magnitude velocity, axial velocity, radial velocity, tangential velocity, and average pressure. Furthermore, this numerical study provides good and useful information for the hydraulic design of axial pumps.     

An Experimental Study on 3—D Flow in an Annular Cascade of High Turning Angle Turbine Blades

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Parabolic RANS solver for low‐computational‐cost simulations of wind turbine wakes

A numerical framework for simulations of wake interactions associated with a wind turbine column is presented. A Reynolds‐averaged Navier‐Stokes (RANS) solver is developed for axisymmetric wake flows using parabolic and boundary‐layer approximations to reduce computational cost while capturing the essential wake physics. Turbulence effects on downstream evolution of the time‐averaged wake velocity field are taken into account through Boussinesq hypothesis and a mixing length model, which is only a function of the streamwise location. The calibration of the turbulence closure model is performed through wake turbulence statistics obtained from large‐eddy simulations of wind turbine wakes. This strategy ensures capturing the proper wake mixing level for a given incoming turbulence and turbine operating condition and, thus, accurately estimating the wake velocity field. The power capture from turbines is mimicked as a forcing in the RANS equations through the actuator disk model with rotation. The RANS simulations of the wake velocity field associated with an isolated 5‐MW NREL wind turbine operating with different tip speed ratios and turbulence intensity of the incoming wind agree well with the analogous velocity data obtained through high‐fidelity large‐eddy simulations. Furthermore, different cases of columns of wind turbines operating with different tip speed ratios and downstream spacing are also simulated with great accuracy. Therefore, the proposed RANS solver is a powerful tool for simulations of wind turbine wakes tailored for optimization problems, where a good trade‐off between accuracy and low‐computational cost is desirable.     

Application of a LES technique to characterize the wake deflection of a wind turbine in yaw

When a wind turbine works in yaw, the wake intensity and the power production of the turbine become slightly smaller and a deflection of the wake is induced. Therefore, a good understanding of this effect would allow an active control of the yaw angle of upstream turbines to steer the wake away from downstream machines, reducing its effect on them. In wind farms where interaction between turbines is significant, it is of interest to maximize the power output from the wind farm as a whole and to reduce fatigue loads on downstream turbines due to the increase of turbulence intensity in wakes. A large eddy simulation model with particular wind boundary conditions has been used recently to simulate and characterize the turbulence generated by the presence of a wind turbine and its evolution downstream the machine. The simplified turbine is placed within an environment in which relevant flow properties like wind speed profile, turbulence intensity and the anisotropy of turbulence are found to be similar to the ones of the neutral atmosphere. In this work, the model is used to characterize the wake deflection for a range of yaw angles and thrust coefficients of the turbine. The results are compared with experimental data obtained by other authors with a particle image velocimetry technique from wind tunnel experiments. Also, a comparison with simple analytical correlations is carried out. Copyright © 2009 John Wiley & Sons, Ltd.     

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.