Research on fault prediction and self-healing strategy of power distribution system based on big data analysis

In modern society, the power system, as one of the infrastructure, plays a vital role in human life and production. However, as an important part of the power system, the distribution system often faces a variety of faults and problems, which will not only lead to power supply interruption, but also may cause safety accidents and economic losses. Therefore, it is urgent to timely and accurately predict the failure of the distribution system and adopt effective self-healing strategies. This paper studies the fault prediction and self-healing strategy based on big data. First, using the RS-IA model, a new method can precisely locate the fault points of the distribution network. Secondly, the fault diagnosis and prediction model of the distribution network based on fuzzy integration is established. By mathematical description of fuzzy integration, the preliminary diagnosis results are pretreatment, the fuzzy metric is determined, and the high-precision fault prediction of the distribution network is realized. The experimental results show that the algorithm presented in is effective.