Min Xu, Jian Yang, Jian Yang, Lin Peng, Shiyang Tang, Ning Li, Zhansheng Hou, Zhimin He, Gang Wang, He Wang, Xingchuan Bao, Hai Yu, Liang Zhu, Zehao Zhang, Jing Li, Tianxiong Gu, Yang Yang, Dai Ye
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Power Grid Disaster Loss Information Fusion Analysis and Prediction Technology
After the natural disaster attacks the power grid, a large number of alarm information will flow into the control center, especially when the power grid has complex faults or the automatic device acts abnormally. Because there are some uncertain factors in protection, circuit breaker misoperation, rejection and channel reasons, a kind of disaster assessment method that can realize uncertain information is of great significance. Although the traditional evaluation algorithm based on rough set can deal with uncertain information, it can only deal with discrete data effectively. In practice, there are continuous data and most of them are fuzzy, and the boundary between concepts is not very clear. Fuzzy set can overcome this disadvantage. This paper creatively proposes a method based on intuitionistic fuzzy rough set to evaluate power grid disasters timely and accurately. In the evaluation, attribute filtering and data cleaning are used to reduce the redundancy of disaster attributes; Through value filtering, the evaluation rules are extracted, the disaster level is determined through matching, and adjusted and updated with the development of the situation, so as to provide a scientific basis for emergency decision-making.