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Determination of the Most Interconnected Sections of Main Gas Pipelines Using the Maximum Clique Method

Author

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  • Sergey Vorobev

    (Melentiev Energy Systems Institute SB RAS, 664033 Irkutsk, Russia)

  • Anton Kolosnitsyn

    (Melentiev Energy Systems Institute SB RAS, 664033 Irkutsk, Russia)

  • Ilya Minarchenko

    (Melentiev Energy Systems Institute SB RAS, 664033 Irkutsk, Russia)

Abstract

This article is devoted to the definition of the most important combinations of objects in critical network infrastructures. This study was carried out using the example of the Russian gas transmission network. Since natural gas is widely used in the energy sector, the gas transmission network can be exposed to terrorist threats, and the actions of intruders can be directed at both gas fields and gas pipelines. A defender–attacker model was proposed to simulate attacks. In this model, the defender solves the maximum flow problem to satisfy the needs of gas consumers. By excluding gas pipelines, the attacker tries to minimize the maximum flow in the gas transmission network. Russian and European gas transmission networks are territorially very extensive and have a significant number of mutual intersections and redundant pipelines. Therefore, one of the approaches to inflicting maximum damage on the system is modeled as an attack on a clique. A clique in this study is several interconnected objects. The article presents the list of the most interconnected sections of main gas pipelines, the failure of which can cause the greatest damage to the system in the form of a gas shortage among consumers. Conclusions were drawn about the applicability of the maximum clique method for identifying the most important objects in network critical infrastructures.

Suggested Citation

  • Sergey Vorobev & Anton Kolosnitsyn & Ilya Minarchenko, 2022. "Determination of the Most Interconnected Sections of Main Gas Pipelines Using the Maximum Clique Method," Energies, MDPI, vol. 15(2), pages 1-14, January.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:2:p:501-:d:722230
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    References listed on IDEAS

    as
    1. Tichý, Lukáš, 2019. "Energy infrastructure as a target of terrorist attacks from the Islamic state in Iraq and Syria," International Journal of Critical Infrastructure Protection, Elsevier, vol. 25(C), pages 1-13.
    2. Han, Fangyuan & Zio, Enrico, 2019. "A multi-perspective framework of analysis of critical infrastructures with respect to supply service, controllability and topology," International Journal of Critical Infrastructure Protection, Elsevier, vol. 24(C), pages 1-13.
    3. Wang, WuChang & Zhang, Yi & Li, YuXing & Hu, Qihui & Liu, Chengsong & Liu, Cuiwei, 2022. "Vulnerability analysis method based on risk assessment for gas transmission capabilities of natural gas pipeline networks," Reliability Engineering and System Safety, Elsevier, vol. 218(PB).
    4. Yu, Weichao & Huang, Weihe & Wen, Yunhao & Li, Yichen & Liu, Hongfei & Wen, Kai & Gong, Jing & Lu, Yanan, 2021. "An integrated gas supply reliability evaluation method of the large-scale and complex natural gas pipeline network based on demand-side analysis," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    5. Emenike, Scholastica N. & Falcone, Gioia, 2020. "A review on energy supply chain resilience through optimization," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    6. Ouyang, Min, 2017. "A mathematical framework to optimize resilience of interdependent critical infrastructure systems under spatially localized attacks," European Journal of Operational Research, Elsevier, vol. 262(3), pages 1072-1084.
    7. Tsavdaroglou, Margarita & Al-Jibouri, Saad H.S. & Bles, Thomas & Halman, Johannes I.M., 2018. "Proposed methodology for risk analysis of interdependent critical infrastructures to extreme weather events," International Journal of Critical Infrastructure Protection, Elsevier, vol. 21(C), pages 57-71.
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    Cited by:

    1. Artur Kierzkowski & Agnieszka A. Tubis, 2023. "Transportation Systems Modeling, Simulation and Analysis with Reference to Energy Supplying," Energies, MDPI, vol. 16(8), pages 1-6, April.
    2. Zhou, Jun & Zhu, Jiaxing & Liang, Guangchuan & Ma, Junjie & He, Jiayi & Du, Penghua & Ye, Zhanpeng, 2024. "Three-layer and robust planning models to evaluate the strategies of defense layer, attack layer, and operation layer for optimal protection in natural gas pipeline network," Reliability Engineering and System Safety, Elsevier, vol. 249(C).

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