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Identification of Two Vulnerability Features: A New Framework for Electrical Networks Based on the Load Redistribution Mechanism of Complex Networks

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  • Xiaoguang Wei
  • Shibin Gao
  • Tao Huang
  • Tao Wang
  • Wenli Fan

Abstract

This paper proposes a new framework to analyze two vulnerability features, impactability and susceptibility, in electrical networks under deliberate attacks based on complex network theory: these two features are overlooked but vital in vulnerability analyses. To analyze these features, metrics are proposed based on correlation graphs constructed via critical paths, which replace the original physical network. Moreover, we analyze the relationship between the proposed metrics according to degree from the perspective of load redistribution mechanisms by adjusting parameters associated with the metrics, which can change the load redistribution rules. Finally, IEEE 118- and 300-bus systems and a realistic large-scale French grid are used to validate the effectiveness of the proposed metrics.

Suggested Citation

  • Xiaoguang Wei & Shibin Gao & Tao Huang & Tao Wang & Wenli Fan, 2019. "Identification of Two Vulnerability Features: A New Framework for Electrical Networks Based on the Load Redistribution Mechanism of Complex Networks," Complexity, Hindawi, vol. 2019, pages 1-14, January.
  • Handle: RePEc:hin:complx:3531209
    DOI: 10.1155/2019/3531209
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    References listed on IDEAS

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    1. Crucitti, Paolo & Latora, Vito & Marchiori, Massimo, 2004. "A topological analysis of the Italian electric power grid," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 338(1), pages 92-97.
    2. Ying Wang & Xiangmei Li & Jiangfeng Li & Zhengdong Huang & Renbin Xiao, 2018. "Impact of Rapid Urbanization on Vulnerability of Land System from Complex Networks View: A Methodological Approach," Complexity, Hindawi, vol. 2018, pages 1-18, May.
    3. Long Guo & Xu Cai, 2008. "Degree And Weighted Properties Of The Directed China Railway Network," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 19(12), pages 1909-1918.
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    Cited by:

    1. Upama Nakarmi & Mahshid Rahnamay Naeini & Md Jakir Hossain & Md Abul Hasnat, 2020. "Interaction Graphs for Cascading Failure Analysis in Power Grids: A Survey," Energies, MDPI, vol. 13(9), pages 1-25, May.
    2. Tao Wang & Xiaoguang Wei & Tao Huang & Jun Wang & Luis Valencia-Cabrera & Zhennan Fan & Mario J. Pérez-Jiménez, 2019. "Cascading Failures Analysis Considering Extreme Virus Propagation of Cyber-Physical Systems in Smart Grids," Complexity, Hindawi, vol. 2019, pages 1-15, March.
    3. Tianlei Zang & Zian Wang & Xiaoguang Wei & Yi Zhou & Jiale Wu & Buxiang Zhou, 2023. "Current Status and Perspective of Vulnerability Assessment of Cyber-Physical Power Systems Based on Complex Network Theory," Energies, MDPI, vol. 16(18), pages 1-38, September.

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