Research on Abnormal Detection of User Power Metering Based on Carrier Technology

In order to improve the accuracy of anomaly detection in user electricity metering, a method based on carrier technology for anomaly detection in user electricity metering is proposed. Firstly, carrier technology is used to collect user electricity metering data, and missing items in the metering data are filled in to obtain optimized data with stronger power consumption behavior characterization ability. Then analyze the working principle of the user′s electrical energy metering device, and obtain the commonly used electrical characteristics under seven fault states, including shunt, phase shift, and phase sequence disorder. Finally, the collected user energy measurement data is input into the deep recurrent neural network, and the user energy measurement anomaly detection is realized based on the abnormal characteristics of power consumption. The experimental results show that the proposed method has high detection accuracy and the detected anomalies are consistent with the real situation.