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Dynamic risk analysis of accidents chain and system protection strategy based on complex network and node structure importance

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  • Feng, Jian Rui
  • Zhao, Mengke
  • Yu, Guanghui
  • Zhang, Jiaqing
  • Lu, Shouxiang

Abstract

Due to the increasing complexity and nonlinearity of complex industrial systems, traditional risk analysis methods have become inapplicable. A method of dynamic risk analysis and system protection based on complex networks and node structure importance was established. The effectiveness of this method is demonstrated through case studies, where we compare and analyze six protection strategies. In light of the topology and directivity of the accidents chain network (ACN) in the complex industrial system, a node structure importance evaluation method and an ACN evaluation method were established to measure the protection cost. An optimal protection strategy model with the protection cost constraint was proposed, and a study was carried out on the ACN of UHV converter transformer. The results show that ACN in UHV converter transformer belongs to a scale-free network. The structural importance evaluation method can identify the critical nodes in ACN, and better reflect the structural importance of nodes than the traditional degree indicator. Considering the dual objectives of the complex system, the optimal protection strategy proposed by the optimal protection model achieves better effect than other strategies, no matter how the protection cost factor and the protection cost budget coefficient change.

Suggested Citation

  • Feng, Jian Rui & Zhao, Mengke & Yu, Guanghui & Zhang, Jiaqing & Lu, Shouxiang, 2023. "Dynamic risk analysis of accidents chain and system protection strategy based on complex network and node structure importance," Reliability Engineering and System Safety, Elsevier, vol. 238(C).
    • Handle: RePEc:eee:reensy:v:238:y:2023:i:c:s0951832023003277
    DOI: 10.1016/j.ress.2023.109413
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    Citations

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    Cited by:

    1. Liu, Jintao & Chen, Keyi & Duan, Huayu & Li, Chenling, 2024. "A knowledge graph-based hazard prediction approach for preventing railway operational accidents," Reliability Engineering and System Safety, Elsevier, vol. 247(C).
    2. Feng, Jian Rui & Zhao, Meng-ke & Lu, Shou-xiang, 2024. "Accident spread and risk propagation mechanism in complex industrial system network," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    3. Li, Haibao & Cai, Zhiqiang & Zhang, Shuai & Zhao, Jiangbin & Si, Shubin, 2024. "Time series importance measure-based reliability optimization for cellular manufacturing systems," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    4. Sun, Qin & Li, Hongxu & Zhong, Yuanfu & Ren, Kezhou & Zhang, Yingchao, 2024. "Deep reinforcement learning-based resilience enhancement strategy of unmanned weapon system-of-systems under inevitable interferences," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    5. Zhang, Chenwei & Wang, Ying & Zheng, Tao & Wang, Chen & Zhang, Kaifeng, 2024. "Identifying critical weak points of power-gas integrated energy system based on complex network theory," Reliability Engineering and System Safety, Elsevier, vol. 246(C).

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