Electricity Stealing Behavior Detection Method based on BP Neural Network

In view of the outstanding problems of current equipment stealing, device specialization, concealed behavior, and large-scale implementation, this paper proposes a detection model of electricity stealing users to realize the screening of electricity stealing users. The model first preprocesses the user's electricity data to determine the evaluation indicators of electricity theft; then uses the PCA method to achieve the feature extraction, thereby improving the efficiency and reducing the load on the detection system; then using BP neural network, the network completes the diagnosis of the user's electricity stealing behavior, and realizes the judgment of normal users and electricity stealing users. Finally, the power consumption data of enterprise large users provided by a power grid company is used for experimental analysis to verify the validity and applicability of the model.