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Vulnerable Node Identification Method for Distribution Networks Based on Complex Networks and Improved TOPSIS Theory
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  • Enyu Jiang,
  • Wentao Zhang,
  • Ang Xue,
  • Shunfu Lin,
  • Yang Mi,
  • Dongdong Li
Enyu Jiang
Shanghai University of Electric Power

Corresponding Author:enyu_1981@163.com

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Wentao Zhang
Shanghai University of Electric Power
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Ang Xue
Shanghai University of Electric Power
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Shunfu Lin
Shanghai University of Electric Power
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Yang Mi
Shanghai University of Electric Power
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Dongdong Li
Shanghai University of Electric Power
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Abstract

A method for identifying vulnerable nodes in distribution networks is proposed, which is based on complex networks and optimized TOPSIS. This method aims to address the issues of one-sided evaluation indicators and inaccurate indicator weights that are present in existing methods for identifying vulnerable nodes in distribution networks. Based on the theory of complex networks, a comprehensive set of vulnerability indicators for distribution network nodes is constructed by considering both the topology structure and system operation status of the distribution network. The TOPSIS comprehensive evaluation model for optimization is proposed to enhance the selection process of optimal and worst indicator values. The advantages and disadvantages of each indicator are characterized using Mahalanobis distance. The calculation of proximity is optimized by establishing a virtual negative ideal solution, which makes the identification of vulnerable nodes more reasonable. The simulation results demonstrate that this method is more effective in identifying vulnerable nodes in the power grid compared to traditional methods, and has significant practical applications.
08 Jun 2023Submitted to IET Generation, Transmission & Distribution
10 Jun 2023Submission Checks Completed
10 Jun 2023Assigned to Editor
26 Jun 2023Reviewer(s) Assigned
06 Aug 2023Review(s) Completed, Editorial Evaluation Pending
07 Aug 2023Editorial Decision: Revise Major
18 Aug 20231st Revision Received
21 Aug 2023Submission Checks Completed
21 Aug 2023Assigned to Editor
21 Aug 2023Review(s) Completed, Editorial Evaluation Pending
22 Aug 2023Reviewer(s) Assigned
18 Sep 2023Editorial Decision: Accept