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Robustness of the Chinese power grid to cascading failures under attack and defense strategies

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  • Li, Kaiwen
  • Liu, Kai
  • Wang, Ming

Abstract

The power grid system is one of the most important and complex infrastructure systems in our society. Catastrophic blackouts caused by cascading failures, however, still occur and lead to devastating effects. Here, for the first time, we investigate the robustness of the Chinese power grid (CPG) system under various attack and defense scenarios by considering cascading failures. The simulation results illustrate that the effect of the loading level of the power grid network has a large influence on the cascading process. When the initial load of the edge is smaller (α ≤ 1.6), the ascending order strategy of the edge collective influence is the most effective attack strategy for triggering cascading failures over the CPG network. While when the initial load of the edge is larger (α≥1.6), the high load strategy appears to outperform the other strategies. To protect the national power grid from cascading failure, two approaches can be adopted: one approach is to improve the network load capacity, and the other approach is to protect the critical edges. The efforts needed to improve the cascading robustness of the CPG network within these two approaches are quantified. Our results can guide protective measures to avoid large cascading failures and are useful for the design of a robust national power grid network.

Suggested Citation

  • Li, Kaiwen & Liu, Kai & Wang, Ming, 2021. "Robustness of the Chinese power grid to cascading failures under attack and defense strategies," International Journal of Critical Infrastructure Protection, Elsevier, vol. 33(C).
  • Handle: RePEc:eee:ijocip:v:33:y:2021:i:c:s187454822100024x
    DOI: 10.1016/j.ijcip.2021.100432
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    References listed on IDEAS

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    Cited by:

    1. Di Zhang & Limin Jia & Jin Ning & Yujiang Ye & Hao Sun & Ruifeng Shi, 2023. "Power Grid Structure Performance Evaluation Based on Complex Network Cascade Failure Analysis," Energies, MDPI, vol. 16(2), pages 1-15, January.
    2. Wang, Shuliang & Dong, Qiqi, 2023. "A multi-source power grid's resilience enhancement strategy based on subnet division and power dispatch," International Journal of Critical Infrastructure Protection, Elsevier, vol. 41(C).
    3. Chen, Jiarui & Lu, Yiqin & Zhang, Yang & Huang, Fang & Qin, Jiancheng, 2023. "A management knowledge graph approach for critical infrastructure protection: Ontology design, information extraction and relation prediction," International Journal of Critical Infrastructure Protection, Elsevier, vol. 43(C).
    4. Ma, Shan & Shen, Binda & Ma, Junfeng & Hu, Wenfeng & Peng, Tao, 2023. "Improvement of network robustness against cascading failures based on the min–max edge-adding strategy," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 611(C).
    5. Beyza, Jesus & Yusta, Jose M., 2021. "The effects of the high penetration of renewable energies on the reliability and vulnerability of interconnected electric power systems," Reliability Engineering and System Safety, Elsevier, vol. 215(C).

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