Design and verification of enhancement algorithm for small sample data of power grid meteorology based on neural network

Xiangzhou Chen; Lingchao Gao

doi:10.1117/12.2685698

15 August 2023 Design and verification of enhancement algorithm for small sample data of power grid meteorology based on neural network

Xiangzhou Chen, Lingchao Gao

Author Affiliations +

Proceedings Volume 12719, Second International Conference on Electronic Information Technology (EIT 2023); 127190H (2023) https://doi.org/10.1117/12.2685698
Event: Second International Conference on Electronic Information Technology (EIT 2023), 2023, Wuhan, China

Abstract

The purpose of this paper is to extract the effective information of power grid operation by using various meteorological monitoring and forecasting information. In all meteorological disasters, considering that the damage to power facilities caused by strong wind accounts for 68% of the total disasters, and considering that the snow and ice disasters in 2008 caused serious losses in large areas, this paper makes prediction for meteorological disasters and derivative disasters such as strong wind, ice, snow in a certain area, studies the probability of grid failure caused by ice and estimates the severity of snow to estimate the probability of grid failure caused by ice. Finally, a decision support system for comprehensive prevention of power grid faults is established. The research and application of this system can scientifically arrange the planning and operation of power grid dispatching, and effectively realize the disaster prevention and reduction of power grid facilities and the refined management of power grid safe operation.

Citation Download Citation

Xiangzhou Chen and Lingchao Gao "Design and verification of enhancement algorithm for small sample data of power grid meteorology based on neural network", Proc. SPIE 12719, Second International Conference on Electronic Information Technology (EIT 2023), 127190H (15 August 2023); https://doi.org/10.1117/12.2685698

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