The Research on User Short-Term Electricity Load Forecasting for Judging Electric Theft

作者：Xianguang Dong, Songhui Zhang, Yanjie Dai, Zhi Zhang, Pingxin Wang, Zhiru Chen, Yu Xing, Yanxi Liu, Chao Yu · 年份：2019 · DOI：10.1109/cisce.2019.00050 · 被引用次数：4 · 研究领域：Energy Load and Power Forecasting、Electricity Theft Detection Techniques、Smart Grid Energy Management

With the continuous development of society and the increasing demand for electricity, the importance of anti-electric theft has become increasingly prominent. At present, the power grid is developing rapidly, the phenomenon of electric theft is frequent, but the quality of relevant inspectors and related technologies are inadequate in identifying electricity stealing. In view of the above problems, this paper proposes a new method for judging electric theft, which can predict the short-term electricity load forecasting of users. A short-term load curve prediction method based on multi-granularity information optimization template matching is proposed. The experimental results on the relevant data sets show that the proposed method has a good effect.