Research on Line Loss Abnormal Diagnosis System Based on Deep Learning

In order to cope with the possible problem of line loss, this paper studies the diagnosis system of line loss abnormality based on deep learning and applies it to line loss management. Obtain massive line loss-related power consumption data from the power consumption collection system of the State Grid Power Supply Company. Conduct in-depth mining of the data through deep learning methods, and build a reliable power theft detection model. Based on the model, Diagnose the main transformer failure in the station area, suspected meter, suspected household transformer problem, etc. This system can reduce the time cost of line loss abnormal situation analysis, improve the efficiency of power management and management. It is an important measure to realize the intelligent management of power grid enterprises.