电测与仪表2025，Vol.62Issue(2)：76-82,7.DOI:10.19753/j.issn1001-1390.2025.02.010
风电机组功率异常数据剔除方法研究
Research on elimination method of abnormal power data of wind turbine
摘要
Abstract
Wind speed-power curve is widely used in power prediction,condition monitoring and fault diagnosis of wind turbine.Its main construction method is to fit the supervisory control and data acquisition(SCADA)data.However,due to wind abandonment,power limitation,instrument failure and other factors,some abnormal power data exist in SCADA data.In order to ensure the accuracy and reliability of fitting results,these abnormal data should be eliminated first.In this paper,a method for eliminating abnormal data of wind turbine is proposed.First-ly,the quantile method is used to eliminate the discrete points far from the normal data.Then,K-means clustering method and improved time series method are combined to eliminate the central accumulation points.Finally,the combination method of quantile method and density-based spatial clustering of applications with noise(DBSCAN)clustering method is used to eliminate the discrete points close to the normal data.In this paper,the quantile meth-od,the basic time series method and the method in this paper are compared and tested by using the simulation data set and the measured data set respectively.The results show that the proposed method is optimal and has a good effect on eliminating both the middle accumulation points and discrete points.关键词
风力发电/异常数据剔除/聚类方法/分位数Key words
wind power generation/abnormal data elimination/clustering method/quantile分类
信息技术与安全科学引用本文复制引用
杨心月,荆博,梅志刚,钱政..风电机组功率异常数据剔除方法研究[J].电测与仪表,2025,62(2):76-82,7.基金项目
国家自然科学基金资助项目(61573046) （61573046）
