基于运行数据的风电机组间风速相关性统计分析

发布时间：2019-03-27 10:07

【摘要】：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。
[Abstract]:Statistical analysis of wind speed correlation among wind turbines is of guiding significance to wind farm equivalent modeling, wind speed / wind power prediction and cluster control optimization. In view of the less research on wind speed correlation among wind turbines, firstly, the data cleaning method and process of wind turbine actual operation based on wind turbine output power index are constructed. Then the calculation method of wind speed correlation among wind turbines is established based on the theory of Copula function. Finally, a case study is carried out based on the wind turbine operation data of a wind farm in Zhangbei area. The result of case analysis shows that the proposed data cleaning setting method can effectively eliminate abnormal data and improve the quality of the basic data of wind speed correlation analysis. Different time scales, wind speed, wind direction of the same wind turbine wind speed correlation coefficient is different, in the case of the same two wind turbines under different conditions, the maximum wind speed data correlation can reach 0.96, the smallest is 0.55, The time variability and difference of wind speed correlation coefficient among wind turbines have great influence on wind farm equivalent modeling based on wind speed correlation, and the accuracy of wind speed / wind power prediction is greatly affected.
【作者单位】：同济大学电子与信息工程学院;同济大学汽车学院;
【基金】：中央高校基本业务经费资助项目(0800219312)
【分类号】：TM614

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