• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
  • Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
Volume 56 Issue 4
Jul.  2021
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Article Contents
LIU Zhigang, ZHANG Qiao, HE Xiaofeng, FAN Wenli. A Review of Vulnerable Line Identification in Power Systems[J]. Journal of Southwest Jiaotong University, 2021, 56(4): 673-688. doi: 10.3969/j.issn.0258-2724.20200717
Citation: LIU Zhigang, ZHANG Qiao, HE Xiaofeng, FAN Wenli. A Review of Vulnerable Line Identification in Power Systems[J]. Journal of Southwest Jiaotong University, 2021, 56(4): 673-688. doi: 10.3969/j.issn.0258-2724.20200717

A Review of Vulnerable Line Identification in Power Systems

doi: 10.3969/j.issn.0258-2724.20200717
  • Received Date: 22 Oct 2020
  • Rev Recd Date: 28 Dec 2020
  • Available Online: 03 Mar 2021
  • Publish Date: 15 Aug 2021
  • With the further interconnection of the power grid, the scope of blackouts have become more extensive. Identification of vulnerable lines has important theoretical and practical significance for preventing cascading failures and ensuring the safety and stable operation of the system. The current research methods of vulnerable lines identification are summarized. The related research results in recent years are divided into two categories. The first category is based on power system status analysis, concentrating on power flow calculation and power grid dynamic characteristics. The application of entropy theory, cascading fault simulation method, risk assessment theory, energy function theory and reinforcement learning theory in the identification of vulnerable lines is introduced. The second category takes the complex network theory as the background. The application of the improved betweenness method, maximum flow theory method and dual graph method in the identification of vulnerable lines is summarized. According to the analysis, the existing methods favorably take into account the system structure and status, and the static and dynamic characteristics of the system, but exclude the uncertainty of the source and load; i.e., they only consider the vulnerability of a single line. Finally, given the development and demands of power systems, the main research interests in the future are illustrated as new energy grid integration, mobile shock load access, data-driven based and composite vulnerable lines identification.

     

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