统计分析风电机组间的风速相关性对风电场的等值建模、风速/风功率预测及机组集群控制优化均具有指导意义.鉴于风电机组间的风速相关性研究工作开展较少,首先构建基于风电机组输出功率为索引的风电机组实际运行数据清洗方法与流程,然后基于Copula函数理论建立风电机组间风速相关性计算方法,最后基于张北地区某风电场风电机组运行数据进行案例应用分析.案例分析结果表明,提出的数据清洗整定方法可有效消除异常数据,提高风速相关性分析基础数据的质量;不同的时间尺度、风速、风向下的相同风电机组间的风速相关系数差异较大,案例中相同两台风电机组不同条件下风速运行数据相关性最大可达0.96,最小则降为0.55,风电机组间的风速相关系数表现出的时变性和差异性对基于风速相关性的风电场等值建模、风速/风功率预测精度影响较大.%Statistical analysis for wind speed correlation (WSC) between wind turbines has guiding significance to wind farm equivalence modeling, wind velocity/power prediction and wind farm cluster control optimization. In view of the situation that the research for WSC analysis is rarely carried out, a method that sets power output for tuning index is proposed for wind turbines data cleaning and tuning in this paper. Then based on the theory of Copula function, the calculation method for WSC coefficient between wind turbines has been established. Finally, the case study is carried out based on the operation data of a wind farm in Zhangbei area. The statistical analysis results show that the data cleaning and turning method presented in the paper, which can effectively eliminate the influence of abnormal data and significantly improve the quality of the basic data for WSC analysis;and the WSC coefficient between the same wind turbine have major variability under different time scale, wind velocity and wind direction, the correlation of this case can up to 0.96 and the minimum is reduced to 0.55 in the studied case. The time variation and difference of WSC coefficient between wind turbines have a great influence on the accuracy of equivalent modeling of wind farm and wind velocity/power based on WSC coefficient.
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