Technical Analysis of Probability Early Warning of User Stealing Electricity Based on Big Data

With the continuous development of smart grids, the large amount of data accumulated by power companies provides a data basis for enterprises to analyze electricity theft, which is of great significance for promoting the development of the power industry and improving the utilization rate of electrical energy. The outstanding problems in the management of electricity theft are solved by the big data mining technology in this paper. With the help of the data association of the “perception layer” of the smart grid and the big data analysis of the “application layer”, the probability early warning analysis model of electricity theft is built based on the logistic regression algorithm to identify the suspected users who steal electricity. At the same time, by continuous learning and training, optimization and reconstruction, the experimental analysis based on the fitting data of a certain place have verified the feasibility of the model method proposed in this paper.