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Vulnerability analysis and critical areas identification of the power systems under terrorist attacks

Author

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  • Wang, Shuliang
  • Zhang, Jianhua
  • Zhao, Mingwei
  • Min, Xu

Abstract

This paper takes central China power grid (CCPG) as an example, and analyzes the vulnerability of the power systems under terrorist attacks. To simulate the intelligence of terrorist attacks, a method of critical attack area identification according to community structures is introduced. Meanwhile, three types of vulnerability models and the corresponding vulnerability metrics are given for comparative analysis. On this basis, influence of terrorist attacks on different critical areas is studied. Identifying the vulnerability of different critical areas will be conducted. At the same time, vulnerabilities of critical areas under different tolerance parameters and different vulnerability models are acquired and compared. Results show that only a few number of vertex disruptions may cause some critical areas collapse completely, they can generate great performance losses the whole systems. Further more, the variation of vulnerability values under different scenarios is very large. Critical areas which can cause greater damage under terrorist attacks should be given priority of protection to reduce vulnerability. The proposed method can be applied to analyze the vulnerability of other infrastructure systems, they can help decision makers search mitigation action and optimum protection strategy.

Suggested Citation

  • Wang, Shuliang & Zhang, Jianhua & Zhao, Mingwei & Min, Xu, 2017. "Vulnerability analysis and critical areas identification of the power systems under terrorist attacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 473(C), pages 156-165.
    • Handle: RePEc:eee:phsmap:v:473:y:2017:i:c:p:156-165
    DOI: 10.1016/j.physa.2017.01.003
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    References listed on IDEAS

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    1. Ouyang, Min & Zhao, Lijing & Hong, Liu & Pan, Zhezhe, 2014. "Comparisons of complex network based models and real train flow model to analyze Chinese railway vulnerability," Reliability Engineering and System Safety, Elsevier, vol. 123(C), pages 38-46.
    2. Ouyang, Min, 2014. "Review on modeling and simulation of interdependent critical infrastructure systems," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 43-60.
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    4. Hong, Liu & Ouyang, Min & Peeta, Srinivas & He, Xiaozheng & Yan, Yongze, 2015. "Vulnerability assessment and mitigation for the Chinese railway system under floods," Reliability Engineering and System Safety, Elsevier, vol. 137(C), pages 58-68.
    5. Hong, Liu & Yan, Yongze & Ouyang, Min & Tian, Hui & He, Xiaozheng, 2017. "Vulnerability effects of passengers' intermodal transfer distance preference and subway expansion on complementary urban public transportation systems," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 58-72.
    6. Nan, Cen & Eusgeld, Irene, 2011. "Adopting HLA standard for interdependency study," Reliability Engineering and System Safety, Elsevier, vol. 96(1), pages 149-159.
    7. Ouyang, Min, 2016. "Critical location identification and vulnerability analysis of interdependent infrastructure systems under spatially localized attacks," Reliability Engineering and System Safety, Elsevier, vol. 154(C), pages 106-116.
    8. Ouyang, Min & Zhao, Lijing & Pan, Zhezhe & Hong, Liu, 2014. "Comparisons of complex network based models and direct current power flow model to analyze power grid vulnerability under intentional attacks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 403(C), pages 45-53.
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    Citations

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    Cited by:

    1. Jing Liu & Huapu Lu & He Ma & Wenzhi Liu, 2017. "Network Vulnerability Analysis of Rail Transit Plans in Beijng-Tianjin-Hebei Region Considering Connectivity Reliability," Sustainability, MDPI, vol. 9(8), pages 1-17, August.
    2. Abedi, Amin & Gaudard, Ludovic & Romerio, Franco, 2019. "Review of major approaches to analyze vulnerability in power system," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 153-172.
    3. 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.
    4. 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).
    5. Mingyu Chen & Huapu Lu, 2020. "Analysis of Transportation Network Vulnerability and Resilience within an Urban Agglomeration: Case Study of the Greater Bay Area, China," Sustainability, MDPI, vol. 12(18), pages 1-14, September.

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