Research on Intelligent Early Warning Algorithm for Distribution Network Considering Extreme Climate Conditions

Autor: Ji Guang Zhao, Zheng Rong Wu, Li Qun Han, Yan Zhang Gu, Lu Lu Yuan, Wen Tao Huang
Rok vydání: 2020
Předmět:
Zdroj: 2020 15th IEEE Conference on Industrial Electronics and Applications (ICIEA).
Popis: The distribution network is an important part of the power supply of the power grid, which is related to the safety and reliability of the power supply of the power grid. Under extreme climate conditions, the probability of failure of the power distribution network will greatly increase, and the occurrence of such failures is often difficult to prevent effectively. The reason why it is difficult to prevent is that extreme climate data belongs to non-electrical variables, while actual data of distribution network operation belongs to electrical variables. In this context, this paper proposes an intelligent mining algorithm for early warning of distribution network operation faults in an intelligent gateway. Data mining, and correlation analysis and causality analysis of data, so as to achieve a full range of early warning of distribution network operation failures. The intelligent early warning algorithm proposed in this paper can effectively mine and analyze climate data such as typhoons, ice disasters, thunderstorms, and extreme high temperatures, and obtain risk prediction results. Early warning and preventive control of the safe operation of the distribution network can be effectively improved The ability of the distribution network to cope with extreme weather conditions.
Databáze: OpenAIRE