LiSBOA：LiDAR统计Barnes客观分析，用于LiDAR扫描的最佳设计和风统计数据的检索。II部分：应用于风力机尾流的合成和真实LiDAR数据
LiSBOA: LiDAR Statistical Barnes Objective Analysis for optimal design of LiDAR scans and retrieval of wind statistics. Part II: Applications to synthetic and real LiDAR data of wind turbine wakes
摘要：
LiDAR统计巴恩斯客观分析（LiSBOA），在Letizia等人，是激光雷达扫描的优化设计和计算的速度场的统计矩的笛卡尔网格的程序。将LiSBOA应用于风力机尾流的LiDAR数据，重建风速场的平均值和湍流强度。所提出的程序首先测试的数值数据集通过虚拟激光雷达技术应用到从大涡模拟（LES）获得的数据。从LiSBOA中检索出扫描多普勒脉冲测风激光雷达的最佳采样参数，然后计算出归一化平均速度和湍流强度的最大误差约为4%的统计量。随后，在复杂地形的风电场进行的实地活动期间收集的激光雷达数据进行了分析，通过LiSBOA两种不同的配置。在第一种情况下，四个公用事业规模的涡轮机的尾流速度场重建的三维网格，显示的能力的LiSBOA捕捉复杂的流动特征，如高速射流周围的机舱和尾流湍流剪切层。对于第二种情况，由四个相互作用的涡轮机产生的尾流的统计数据计算在一个二维笛卡尔网格，并比较由机舱安装的风速计提供的测量。归一化平均速度和湍流强度的最大差异低至3%，支持LiSBOA应用于基于LiDAR的风力资源评估和风电场诊断调查。
英文摘要：
The LiDAR Statistical Barnes Objective Analysis (LiSBOA), presented in Letizia et al., is a procedure for the optimal design of LiDAR scans and calculation over a Cartesian grid of the statistical moments of the velocity field. The LiSBOA is applied to LiDAR data collected in the wake of wind turbines to reconstruct mean and turbulence intensity of the wind velocity field. The proposed procedure is firstly tested for a numerical dataset obtained by means of the virtual LiDAR technique applied to the data obtained from a large eddy simulation (LES). The optimal sampling parameters for a scanning Doppler pulsed wind LiDAR are retrieved from the LiSBOA, then the estimated statistics are calculated showing a maximum error of about 4% for both the normalized mean velocity and the turbulence intensity. Subsequently, LiDAR data collected during a field campaign conducted at a wind farm in complex terrain are analyzed through the LiSBOA for two different configurations. In the first case, the wake velocity fields of four utility-scale turbines are reconstructed on a 3D grid, showing the capability of the LiSBOA to capture complex flow features, such as high-speed jet around the nacelle and the wake turbulent shear layers. For the second case, the statistics of the wakes generated by four interacting turbines are calculated over a 2D Cartesian grid and compared to the measurements provided by the nacelle-mounted anemometers. Maximum discrepancies as low as 3% for the normalized mean velocity and turbulence intensity endorse the application of the LiSBOA for LiDAR-based wind resource assessment and diagnostic surveys for wind farms.
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