Power grid reactive power and voltage partition method based on fuzzy clustering

Chuanwei Zhou; Lanjiang Wu; Liyuan He

doi:10.1117/12.2656051

12 January 2023 Power grid reactive power and voltage partition method based on fuzzy clustering

Chuanwei Zhou, Lanjiang Wu, Liyuan He

Proceedings Volume 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022); 125090Y (2023) https://doi.org/10.1117/12.2656051
Event: Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 2022, Guangzhou, China

Abstract

In the case of the existing power grid partition, the actual transmission between each node has fluctuations, which will lead to low electrical modularity of each partition. To solve this problem, this paper proposes a method of reactive power and voltage partitioning based on fuzzy clustering. The transmission state between any two nodes of the power grid is analyzed in detail by using the index parameter electric coupling strength which directly reflects the electric characteristics of the power grid, and then the fuzzy clustering method is used to realize the partition processing of the reactive power and voltage of the power network according to the analysis results. According to the relationship between the power flow coefficient and the node electric coupling strength coefficient obtained by the Newton-Raphson iteration method, the buses corresponding to the coupling strength coefficient are clustered based on the integrated grid load. Finally, the reactive voltage partition is realized according to the scale standard of 0. 2. The test results show that the electrical modularity of the partition results of the design method is always stable above 0. 60, which is better than the comparison method and has high feasibility.

Citation Download Citation

Chuanwei Zhou, Lanjiang Wu, and Liyuan He "Power grid reactive power and voltage partition method based on fuzzy clustering", Proc. SPIE 12509, Third International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI 2022), 125090Y (12 January 2023); https://doi.org/10.1117/12.2656051

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