In view of the characteristics of high proportion of abnormal data and poor overall quality of data in the original opera-tion data of photovoltaic power station,the identification and cleaning of abnormal data is the premise of data analysis and pre-diction.Therefore,this paper analyzes the characteristics and sources of photovoltaic power station radiation intensity-power a-nomaly data,and proposes a change point detection method based on linear fitting of sliding standard deviation curve and a change point quartile joint photovoltaic power anomaly data recognition algorithm.The effectiveness and universality of the pro-posed algorithm are verified by the data of several photovoltaic power stations,and the good detection of scattered,stacked and other abnormal data is realized.
关键词
光伏电站/异常检测/光伏功率/变点检测/四分位
Key words
photovoltaic power station/anomaly detection/photovoltaic power/change point detection/quartile
维普
万方数据