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Multiple robustness assessment method for understanding structural and functional characteristics of the power network

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  • Wang, Shuliang
  • Zhang, Jianhua
  • Yue, Xin

Abstract

This paper develops a methodological framework to study robustness of the power network from both structural and functional perspective, and uses the central China power grid as an example to illustrate the usage and effectiveness of the proposed framework. Specifically, we use percolation to determine the phase transition process, and use controllability theory to calculate the number of minimum driver nodes in structural robustness analysis. We obtain the vulnerability curves and identify the critical dense areas that are most likely to be targets of attack in functional robustness analysis. Results show that the power network here exhibits similar characteristics as scale free network and is relatively vulnerable to deliberate attacks. Some of the dense areas in the power network are highly sensitive to terrorist attacks. The proposed framework can be applied to other infrastructure networks to give a deep understanding of the system robustness.

Suggested Citation

  • Wang, Shuliang & Zhang, Jianhua & Yue, Xin, 2018. "Multiple robustness assessment method for understanding structural and functional characteristics of the power network," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 261-270.
    • Handle: RePEc:eee:phsmap:v:510:y:2018:i:c:p:261-270
    DOI: 10.1016/j.physa.2018.06.117
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    Cited by:

    1. Nie, Yan & Zhang, Guoxing & Duan, Hongbo, 2020. "An interconnected panorama of future cross-regional power grid: A complex network approach," Resources Policy, Elsevier, vol. 67(C).
    2. Guo, Jingni & Xu, Junxiang & He, Zhenggang & Liao, Wei, 2021. "Research on risk propagation method of multimodal transport network under uncertainty," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 563(C).
    3. Wang, Shuliang & Lv, Wenzhuo & Zhang, Jianhua & Luan, Shengyang & Chen, Chen & Gu, Xifeng, 2021. "Method of power network critical nodes identification and robustness enhancement based on a cooperative framework," Reliability Engineering and System Safety, Elsevier, vol. 207(C).

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