Research on Abnormal Signal Identification Algorithm of Distribution Network Operation Based on Big Data Mining

Conventional algorithm for identifying abnormal signals of distribution network mainly uses ESD (extreme studied deviate test) to obtain signal time series, which is easily influenced by proximity clustering relationship, resulting in poor identification performance. Therefore, it is necessary to design a new algorithm for identifying abnormal signals of distribution network based on big data mining. That is, the abnormal signal of distribution network operation is collected, and the characteristics of abnormal signal of distribution network operation are extracted by big data mining, and the optimization algorithm of abnormal signal identification of distribution network operation is generated, thus realizing the identification of abnormal signal of distribution network operation. The experimental results show that the designed algorithm for identifying abnormal signals of distribution network operation has good recognition performance, high accuracy, recall and F1 score, and it is reliable and has certain application value, which has made certain contributions to reducing the operation risk of distribution network.