Research on artificial intelligence-aided decision-making system for power grid operation mode

Qiuquan Deng; Dong Mo; Yin Wu; Cuiyun Luo; Yan Sun; Fengjiao Xu

doi:10.1117/12.2672995

25 April 2023 Research on artificial intelligence-aided decision-making system for power grid operation mode

Qiuquan Deng, Dong Mo, Yin Wu, Cuiyun Luo, Yan Sun, Fengjiao Xu

Proceedings Volume 12598, Eighth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2022); 1259839 (2023) https://doi.org/10.1117/12.2672995
Event: Eighth International Conference on Energy Materials and Electrical Engineering (ICMEE 2022), 2022, Guangzhou, China

Abstract

The dynamic stability analysis of Nanning power grid operation mode and optimal arrangement of power outage plan are studied. Firstly, the expert empirical rule base of scheduling plan considering security constraints is established to ensure that the boundary conditions of optimization model meet the outage requirements. Considering the complexity of non-closed-loop state analysis of ground modulated power grid topology, the power grid knowledge graph is established to accurately analyze the graph data relationship. In order to meet the principle of safe and stable operation of the power grid and to achieve the principle of "transfer without stopping", bus load forecasts are made for the main network of Nanning power grid. Combined with the grid knowledge graph, the load to power supply scheme is given, and the overload warning is given. The outage windows for outage plans are recommended based on the transfer schemes to achieve reasonable outage arrangements. Finally, the outage window period and outage rule base combined with the mixed integer algorithm model are considered to give the optimal scheduling plan for the outage plan.

Citation Download Citation

Qiuquan Deng, Dong Mo, Yin Wu, Cuiyun Luo, Yan Sun, and Fengjiao Xu "Research on artificial intelligence-aided decision-making system for power grid operation mode", Proc. SPIE 12598, Eighth International Conference on Energy Materials and Electrical Engineering (ICEMEE 2022), 1259839 (25 April 2023); https://doi.org/10.1117/12.2672995

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