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Line loss can be divided into statistical line loss, technical line loss and management line loss according to structure. It not only refers to the energy loss in the form of heat energy, but also the management line loss caused by the electricity stealing behavior [1]. The calculation of power system line loss and the realization of system lean management are of great significance in guiding the reduction of energy conservation and the promotion of line loss management. To this end, in-depth analysis of the massive user data accumulated in the marketing automation process of the electricity information system in recent years, so as to establish a reasonable and efficient mathematical model of line loss analysis. By mining the useful information behind these data in smart electric meter, the abnormal power usage behavior detection of the user is realized, so as to achieve the purpose of preventing electric larceny and leakage and thereby reducing the line loss. This paper proposes a layer-based power line electric larceny detection method based on data mining technology .This method optimizes the traditional LOF algorithm and is a weighted LOF algorithm. By performing weighted outlier analysis on massive user data, the location of abnormal power users can be more efficiently completed. Keywords-Component Management Line Loss, Data Mining; Layer-Based Analysis; Weighted LOF Algorithm; Outlier Analysis; Abnormal User Location

Research on Smart Electric Meter Data Mining Technology Method for Line Loss Diagnosis of Low Voltage Station Area