Identification of Key Nodes in a Power Grid Based on Modified PageRank Algorithm

Darui Zhu, Haifeng Wang, Rui Wang, Jiandong Duan and Jing Bai
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Darui Zhu: School of Electrical Engineering, Xi’an University of Technology, Xi’an 710048, China
Haifeng Wang: School of Electrical Engineering, Xi’an University of Technology, Xi’an 710048, China
Rui Wang: School of Electrical Engineering, Xi’an University of Technology, Xi’an 710048, China
Jiandong Duan: School of Electrical Engineering, Xi’an University of Technology, Xi’an 710048, China
Jing Bai: School of Electrical Engineering, Xi’an University of Technology, Xi’an 710048, China

Energies, 2022, vol. 15, issue 3, 1-15

Abstract: For avoiding the occurrence of large-scale blackouts due to disconnected nodes in the power grid, a modified PageRank algorithm is proposed to identify key nodes by integrating the topological information and node type. The node betweenness index is first introduced based on complex network theory, which is modified to reflect the node topological information in the power grid. Then, according to the characteristics of different node types in the power grid, a modified PageRank algorithm is proposed to rapidly identify key nodes, which takes the generator nodes, load nodes, and contact nodes into account. IEEE 39-Bus system and IEEE 118-Bus system are used for the simulations. Simulation results showed that the network transmission efficiencies of the power grid are reduced from 64.23% to 5.62% and from 45.4% to 5.12% in the two simulation systems compared with other methods. The proposed identification algorithm improved the accuracy, and a provincial power grid simulation system in China is used to verify the feasibility and validity. The identified nodes are removed, which split the power grid according to importance index values. The proposed method in this paper is helpful to prevent the occurrence of cascading failure in the power system, and it can also be used to power systems with renewable energy sources and an AC/DC hybrid power grid.

Keywords: complex network; node betweenness; modified PageRank algorithm; transmission efficiency; empirical verification (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
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