中国电机工程学报2017，Vol.37Issue(z1)：144-151,8.DOI:10.13334/j.0258-8013.pcsee.170759
基于风特征分析的风电机组异常数据识别算法
An Algorithm for Abnormal Data Identification of Wind Turbine Based on Wind Characteristic Analysis
摘要
Abstract
The study of wind power often depends on historical power data, and the historical data collected by wind turbine often contains a lot of abnormal data, which seriously affects the analysis of wind power characteristics. According to the measured power data of wind turbines, the influence of RISE-FALL-Feature of wind speed and wind direction characteristics on the output power of wind turbine was analyzed, and the data of different wind characteristics were discussed separately. Using Copula function to get the probability power curve, three types of anomaly data were summed up according to the timing characteristics of anomaly data and the exception data recognition model was established. The actual data and artificial date of wind turbine were used for simulation analysis. The results show that the proposed method can identify all kinds of anomaly data efficiently, which is of great significance to wind power research.关键词
风电功率/异常数据/风速升降特征/风向特征/时序特征Key words
wind power/abnormal date/rise-fall feature of wind speed/wind direction characteristics/timing characteristics分类
信息技术与安全科学引用本文复制引用
杨茂,翟冠强,苏欣..基于风特征分析的风电机组异常数据识别算法[J].中国电机工程学报,2017,37(z1):144-151,8.基金项目
国家重点研发计划项目课题(2016YFB0900101) National Key Research and Development Program of China (2016YFB0900101). （2016YFB0900101）
