This work is supported by National Natural Science Foundation of China (No. 51777015), State Grid Corporation of China and Hunan Provincial Natural Science Foundation of China (No. 2020JJ4611).
Data-driven power theft detection methods mainly identify low power abnormalies according to power and derived indicators, which could result in high false positive due to interference. Taking the advantage of the characteristic that the indicies of production and operation status of industrial and commercial users are generally constant, a second inspection method for electricity theft based on identification of production and operation status is proposed. First, the daily three-phase power of the detected abnormal low-power users is used as t...
