Recognition Method of Abnormal Power Consumption State of Power Users Based on Strategy Gradient Algorithm

Abstract

Because the traditional method ignores the problem of power load data preprocessing, the accuracy of the recognition result of the power consumption status is not high, the recognition efficiency is not high, and the recognition effect is not good. For this reason, a method for identifying the abnormal power consumption status of power users based on the strategy gradient algorithm is proposed. The preprocessing of power load data mainly includes the completion of missing data and the feature extraction of power load data. Based on the results of the preprocessing, the abnormal increase in user power consumption is detected. Finally, the strategy gradient algorithm is used for initial training and training process testing to complete the identification of the abnormal state of power users. The experimental results show that the accuracy of the power status recognition result of the proposed method is higher, and the recognition time is always less than 2.0 s, indicating that the recognition effect of the method is better.