Turbulence characterization from a forward-looking nacelle lidar
Turbulence characterization from a forward-looking nacelle lidar
复制标题
前视机舱激光雷达的湍流表征
DOI：
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发表时间：
2016
期刊：
影响因子：
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通讯作者：
N. Dimitrov
中科院分区：
文献类型：
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作者：
A. Peña;J. Mann;N. Dimitrov
抽象的。我们提出了两种方法来表征湍流的涡轮机流入使用径向速度测量从机舱安装激光雷达。第一个使用的三维谱速度张量的模型结合激光雷达的空间径向速度平均的模型，和第二个使用的合奏平均多普勒径向速度谱。使用前者，过滤湍流估计可以预测，而后者无模型方法允许我们估计未经过滤的湍流措施。两种类型的前视机舱激光雷达进行了研究：脉冲系统，使用五束配置和连续波系统，扫描圆锥。对于这两种类型的激光雷达，我们展示了激光雷达光束的径向速度谱是如何受到湍流特性的影响，以及如何提取速度张量参数，这些参数对预测涡轮机上的负载是有用的。我们还展示了如何从激光雷达光束的径向速度未滤波方差估计速度分量方差和协方差。我们演示的方法使用的测量在北方丹麦，其中两种类型的激光雷达安装在风涡轮机的机舱进行的实验。将基于激光雷达的顺风未滤波方差与安装在靠近涡轮机的气象桅杆上的杯式风速计的方差进行比较，显示偏差仅为2%。激光雷达光束的未经过滤和过滤的径向速度方差的比杯风速计的方差很好地预测的光谱模型。然而，其他激光雷达得出的速度分量方差和协方差的估计不同意从桅杆上的声波风速计，我们主要归因于激光雷达的小锥角。在近中性大气稳定度和高风速条件下，来自声速风速计速度谱和来自激光雷达径向速度谱的速度张量参数吻合良好，差异随着风速的减小和稳定度的增加而增大。我们也将这些差异部分归因于激光雷达光束配置。
Abstract. We present two methods to characterize turbulence in the turbine inflow using radial velocity measurements from nacelle-mounted lidars. The first uses a model of the three-dimensional spectral velocity tensor combined with a model of the spatial radial velocity averaging of the lidars, and the second uses the ensemble-averaged Doppler radial velocity spectrum. With the former, filtered turbulence estimates can be predicted, whereas the latter model-free method allows us to estimate unfiltered turbulence measures. Two types of forward-looking nacelle lidars are investigated: a pulsed system that uses a five-beam configuration and a continuous-wave system that scans conically. For both types of lidars, we show how the radial velocity spectra of the lidar beams are influenced by turbulence characteristics, and how to extract the velocity-tensor parameters that are useful to predict the loads on a turbine. We also show how the velocity-component variances and co-variances can be estimated from the radial-velocity unfiltered variances of the lidar beams. We demonstrate the methods using measurements from an experiment conducted at the Norrekaer Enge wind farm in northern Denmark, where both types of lidars were installed on the nacelle of a wind turbine. Comparison of the lidar-based along-wind unfiltered variances with those from a cup anemometer installed on a meteorological mast close to the turbine shows a bias of just 2 %. The ratios of the unfiltered and filtered radial velocity variances of the lidar beams to the cup-anemometer variances are well predicted by the spectral model. However, other lidar-derived estimates of velocity-component variances and co-variances do not agree with those from a sonic anemometer on the mast, which we mostly attribute to the small cone angle of the lidar. The velocity-tensor parameters derived from sonic-anemometer velocity spectra and those derived from lidar radial velocity spectra agree well under both near-neutral atmospheric stability and high wind-speed conditions, with differences increasing with decreasing wind speed and increasing stability. We also partly attribute these differences to the lidar beam configuration.