Photovoltaic Anomaly Data Detection Based on Optimized Change Point and Quartile
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.
photovoltaic power stationanomaly detectionphotovoltaic powerchange point detectionquartile
万方数据
维普
