Open AccessA Method for Anti-electric Theft Based on User Electricity Load Forecasting and Historical Load Data
Author(s) -
Zhang Zhi,
Xianguang Dong,
Liang Bo,
Yanjie Dai,
Zhiru Chen,
Pingxin Wang
Publication year - 2019
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/631/4/042050
Subject(s) - electricity , computer science , electrical load , computer security , operations research , engineering , electrical engineering , voltage
With the development of socioeconomic and the increasing demand for electricity, the electricity safety requirements are getting higher and higher and the importance of anti-electric theft has become increasingly prominent. At present, 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 anti-electric theft, which can predict the load of users. User load forecasting curve is formed [1] , and combined with user history data, user forecasting load curve and industry load characteristic data, logistic regression algorithm is used to establish user electric theft judgment model and judge the possibility of user electric theft . The experimental results on the relevant datasets show that the proposed algorithm has a good effect.