Abstract

In order to effectively combat electricity theft and improve the ability to recognize electricity theft, this paper proposes an anti-electricity theft method based on the analysis of users’ electricity consumption behavior. First, determine the appropriate outlier detection electrical parameters through reasonable research on users. , Using the outlier detection algorithm to filter the user’s electrical data, preprocessing the original data, performing multi-feature fusion analysis on the user’s electrical parameters, using the discriminant rule to filter out the outliers, and then using the electricity based on the clustering algorithm Pattern analysis for detection, to achieve active identification of low-voltage power theft. In this paper, combined with the user profile data of the electricity consumption information collection system, it conducts in-depth analysis of the user’s electricity consumption data. Through the discovery of abnormal electricity consumption data users, the analysis finds out the electricity theft users and improves the quality and efficiency of the anti-stealing work.

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