Functional Community Detection in Power Grids

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Abstract

Community detection algorithm is broadly applied in amount of studies to partition networks. But not all available methods are equally suitable for power grids. This paper proposes the concept of functional community structure based on functionality of the network. And a novel partitioning algorithm is presented by upgrading the Newman fast algorithm of community detection. The coupling strength is therefore proposed to replace conventional adjacency matrix to represent the relationship between nodes in networks. The electrical coupling strength (ECS) is defined to better reflect electrical characteristics between any two nodes in power grids. Furthermore, to consider the functionality of node type distribution, power supply strength (PSS) is proposed based on ECS only from generation nodes to load nodes to evaluate the impact of different node type distribution in the power supply. Moreover, modularity is redefined as power supply modularity based on PSS to evaluate the partitioning performance of power grids. Finally, considering the functionality of power grids. The Newman fast algorithm is upgraded based on power supply modularity.

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Wang, X., Xue, F., Lu, S., Jiang, L., & Wu, Q. (2020). Functional Community Detection in Power Grids. In Studies in Computational Intelligence (Vol. 882 SCI, pp. 883–894). Springer. https://doi.org/10.1007/978-3-030-36683-4_70

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