Research on tariff recovery risks assessment method based on electrical user portrait technology

Abstract

Tariff recovery risks of electrical users are always big problems for electric power company, and the user portrait technology can realize tariff recovery risks assessment and defense by analyzing user power consumption, payment and arrears data from electricity information acquisition system and marketing system. This paper studies the multi-source data fusion and clean technology to handle power consumption, payment and arrears data. On this basis, the electrical user label system is established, the scene design of tariff recovery risks assessment is realized, and the C4.5 algorithm is used to evaluate the risks of tariff recovery. The analysis results of test case show that the model and algorithm proposed in this paper have high availability and accuracy, and can provide the references for electric power company to reduce the risk of tariff recovery.