摘要
波动性是风资源的固有特性。定量分析风向波动性对优化风电机组偏航系统控制参数有重要意义。文章采用风电机组自身测量的风资源数据,提出了基于波动幅值A和波动持续时间T的风向波动量描述方法。采用Weibull分布对风向波动量的边缘分布概率密度进行函数拟合,使用Frank-Copula函数对边缘分布进行连接,构建了二维风向波动量的联合概率密度函数。与实际运行数据比对分析,验证了该风向联合概率分布的正确性。文章提取了一组能够精确量化风电机组本地风向波动特性的概率指标集,为风电机组偏航系统的参数优化设置及提升机组发电效率提供了支持。
Based on the wind-resource data measured by the wind turbine itself,a method was proposed to describe the volatility by means offluctuation amplitude A and fluctuation duration T.The Weibull distribution was employed to fit the edge distribution probability density of the volatility,and the Frank-Copula function was used to connect the edge distributions,establishing the joint probability density function of two-dimensional volatility of wind direction,which was verified in comparison with the real operating data.A group of indicators were extracted for probability distribution,which can accuratelyquantify the local wind direction fluctuation behavior of wind turbine.It plays a significant role in the individual optimal settings for the parameters of yaw controlling system,and can be helpful in increasing the generating efficiency of wind turbine.
作者
宋鹏
柳玉
郭鹏
徐金晖
Song Peng;Liu Yu;Guo Peng;Xu Jinhui(North China Electric Power Research Institute Co.,Ltd.,Beijing 100045,China;School of Control and Computer Engineering,North China Electric Power University,Beijing 102206,China)
出处
《可再生能源》
CAS
北大核心
2020年第4期491-496,共6页
Renewable Energy Resources
基金
国家自然科学基金面上项目(51677067)。
