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ORIGINAL RESEARCH article

Front. Energy Res.
Sec. Smart Grids
Volume 12 - 2024 | doi: 10.3389/fenrg.2024.1498678
This article is part of the Research Topic Advancements in Power System Condition Monitoring, Fault Diagnosis and Environmental Compatibility View all 13 articles

Vulnerability analysis of power grid structure based on complex network theory

Provisionally accepted
Zhichun Yang Zhichun Yang 1Huaidong Min Huaidong Min 1Jie Zhao Jie Zhao 2*Xuzhu Dong Xuzhu Dong 2Fan Yang Fan Yang 1Chenhao Wang Chenhao Wang 2Nan Zhang Nan Zhang 1
  • 1 Electric Power Research Institute, State Grid Hubei Electric Power Co., Ltd., Wuhan, Hubei Province, China
  • 2 Wuhan University, Wuhan, Hubei Province, China

The final, formatted version of the article will be published soon.

    The key nodes of an intelligent distribution network significantly impact the reliability and stability of the distribution network's operation. The failure of these key nodes can severely affect the safe operation of the distribution network. Therefore, vulnerability analysis of key nodes is particularly important. This paper proposes a comprehensive weighting method for evaluating indicators, combining the Analytic Hierarchy Process (AHP) and entropy weighting method, while considering the structure and operational status of the power system grid. Key node structural evaluation indicators such as node degree, node shrinkage centrality, and electric mediator are established considering "significance" and "destructiveness". State indicators are established based on the degree of impact of current, voltage, and load changes on the grid, as well as the uniformity of their distribution, including the improved current distribution entropy, voltage Terre entropy, and three-phase state indicators of lost load. Subsequently, based on the AHP and entropy weighting method, a comprehensive weighting method is proposed to assign subjective and objective weights to the comprehensive evaluation indicators, obtaining the comprehensive weights of the indicators. Finally, the grey correlation degree is introduced to improve the ideal solution of the multi-objective decision-making method, obtaining the criticality of the grid nodes, and then identifying the critical nodes. The example analysis presented in this paper shows that the identified critical nodes of the power grid have a high degree of overlap with the identification results of different methods, can better identify edge nodes, and validates the effectiveness of the proposed evaluation indicators and key node identification methods.

    Keywords: Comprehensive weights, key nodes, Improved TOPSIS method, AHP, Comprehensive evaluation indexes

    Received: 19 Sep 2024; Accepted: 26 Nov 2024.

    Copyright: © 2024 Yang, Min, Zhao, Dong, Yang, Wang and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Jie Zhao, Wuhan University, Wuhan, 430072, Hubei Province, China

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.