Digital intelligent distribution network fault risk early warning system based on data mining

Yong Wang; Yi Wang; Lei Zhang; Siyuan Liu; Quan Li

doi:10.1117/12.2673156

25 April 2023 Digital intelligent distribution network fault risk early warning system based on data mining

Yong Wang, Yi Wang, Lei Zhang, Siyuan Liu, Quan Li

Proceedings Volume 12598, Eighth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2022); 1259831 (2023) https://doi.org/10.1117/12.2673156
Event: Eighth International Conference on Energy Materials and Electrical Engineering (ICMEE 2022), 2022, Guangzhou, China

Abstract

Aiming at the problems of low fault warning efficiency and failure to transmit warning information in time in China's distribution network, a digital smart distribution network fault risk warning system based on data mining is proposed. The Oracle database is used to call and manage the data of the distribution network as a whole, and then the data mining method is used to collect and process the fault data. On this basis, the fault early warning model is established to realize the timely early warning of distribution network fault risk. Finally, the conventional fault risk early warning system is selected as the comparison system for the comparison test. The test results show that the fault risk early warning system of the distribution network based on data mining is superior to the conventional system in data transmission delay, which is conducive to improving the early warning efficiency and providing a guarantee for the safe and stable operation of distribution network.

Citation Download Citation

Yong Wang, Yi Wang, Lei Zhang, Siyuan Liu, and Quan Li "Digital intelligent distribution network fault risk early warning system based on data mining", Proc. SPIE 12598, Eighth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2022), 1259831 (25 April 2023); https://doi.org/10.1117/12.2673156

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