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Quantitative Resilience Assessment under a Tri-Stage Framework for Power Systems

Author

Listed:
  • Han Zhang

    (The State Key Laboratory of Electrical Insulation and Power Equipment, the Shaanxi Key Laboratory of Smart Grid, Xi’an Jiaotong University, Xi’an 710049, China)

  • Hanjie Yuan

    (The State Key Laboratory of Electrical Insulation and Power Equipment, the Shaanxi Key Laboratory of Smart Grid, Xi’an Jiaotong University, Xi’an 710049, China)

  • Gengfeng Li

    (The State Key Laboratory of Electrical Insulation and Power Equipment, the Shaanxi Key Laboratory of Smart Grid, Xi’an Jiaotong University, Xi’an 710049, China)

  • Yanling Lin

    (The State Key Laboratory of Electrical Insulation and Power Equipment, the Shaanxi Key Laboratory of Smart Grid, Xi’an Jiaotong University, Xi’an 710049, China)

Abstract

The frequent occurrence of natural disasters and malicious attacks has exerted unprecedented disturbances on power systems, accounting for the extensive attention paid to power system resilience. Combined with the evolving nature of general disasters, this paper proposes resilience assessment approaches for power systems under a tri-stage framework. The pre-disaster toughness is proposed to quantify the robustness of power systems against potential disasters, where the thinking of area division and partitioned multi-objective risk method (PMRM) is introduced. In the case of information deficiency caused by disasters, the during-disaster resistance to disturbance is calculated to reflect the real-time system running state by state estimation (SE). The post-disaster restoration ability consists of response ability, restoration efficiency and restoration economy, which is evaluated by Sequential Monte-Carlo Simulation to simulate the system restoration process. Further, a synthetic metric system is presented to quantify the resilience performance of power systems from the above three aspects. The proposed approaches and framework are validated on the IEEE RTS 79 system, and helpful conclusions are drawn from extensive case studies.

Suggested Citation

  • Han Zhang & Hanjie Yuan & Gengfeng Li & Yanling Lin, 2018. "Quantitative Resilience Assessment under a Tri-Stage Framework for Power Systems," Energies, MDPI, vol. 11(6), pages 1-23, June.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:6:p:1427-:d:150361
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    References listed on IDEAS

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    4. Whitson, John C. & Ramirez-Marquez, Jose Emmanuel, 2009. "Resiliency as a component importance measure in network reliability," Reliability Engineering and System Safety, Elsevier, vol. 94(10), pages 1685-1693.
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    Cited by:

    1. Plotnek, Jordan J. & Slay, Jill, 2021. "Power systems resilience: Definition and taxonomy with a view towards metrics," International Journal of Critical Infrastructure Protection, Elsevier, vol. 33(C).
    2. Xue, Jiayue & Mohammadi, Farshad & Li, Xin & Sahraei-Ardakani, Mostafa & Ou, Ge & Pu, Zhaoxia, 2020. "Impact of transmission tower-line interaction to the bulk power system during hurricane," Reliability Engineering and System Safety, Elsevier, vol. 203(C).
    3. Zou, Qiling & Chen, Suren, 2019. "Enhancing resilience of interdependent traffic-electric power system," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    4. Adel Mottahedi & Farhang Sereshki & Mohammad Ataei & Ali Nouri Qarahasanlou & Abbas Barabadi, 2021. "The Resilience of Critical Infrastructure Systems: A Systematic Literature Review," Energies, MDPI, vol. 14(6), pages 1-32, March.
    5. Han Zhang & Gengfeng Li & Hanjie Yuan, 2018. "Collaborative Optimization of Post-Disaster Damage Repair and Power System Operation," Energies, MDPI, vol. 11(10), pages 1-21, September.

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