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Topological Modeling Research on the Functional Vulnerability of Power Grid under Extreme Weather

Author

Listed:
  • Banghua Xie

    (Faculty of Engineering, China University of Geosciences, Wuhan 430074, China)

  • Changfan Li

    (Faculty of Engineering, China University of Geosciences, Wuhan 430074, China)

  • Zili Wu

    (Faculty of Engineering, China University of Geosciences, Wuhan 430074, China)

  • Weiming Chen

    (Faculty of Engineering, China University of Geosciences, Wuhan 430074, China)

Abstract

The large-scale interconnection of the power grid has brought great benefits to social development, but simultaneously, the frequency of large-scale fault accidents caused by extreme weather is also rocketing. The power grid is regarded as a representative complex network in this paper to analyze its functional vulnerability. First, the actual power grid topology is modeled on the basis of the complex network theory, which is transformed into a directed-weighted topology model after introducing the node voltage together with line reactance. Then, the algorithm of weighted reactance betweenness is proposed by analyzing the characteristic parameters of the power grid topology model. The product of unit reliability and topology model’s characteristic parameters under extreme weather is used as the index to measure the functional vulnerability of the power grid, which considers the extreme weather of freezing and gale and quantifies the functional vulnerability of lines under wind load, ice load, and their synergistic effects. Finally, a simulation using the IEEE-30 node system is implemented. The result shows that the proposed method can effectively measure the short-term vulnerability of power grid units under extreme weather. Meanwhile, the example analysis verifies the different effects of normal and extreme weather on the power grid and identifies the nodes and lines with high vulnerability under extreme weather, which provides theoretical support for preventing and reducing the impact of extreme weather on the power grid.

Suggested Citation

  • Banghua Xie & Changfan Li & Zili Wu & Weiming Chen, 2021. "Topological Modeling Research on the Functional Vulnerability of Power Grid under Extreme Weather," Energies, MDPI, vol. 14(16), pages 1-27, August.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:16:p:5183-:d:619292
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    References listed on IDEAS

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    1. Bo, Zeng & Shaojie, Ouyang & Jianhua, Zhang & Hui, Shi & Geng, Wu & Ming, Zeng, 2015. "An analysis of previous blackouts in the world: Lessons for China׳s power industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 1151-1163.
    2. Cadini, Francesco & Agliardi, Gian Luca & Zio, Enrico, 2017. "A modeling and simulation framework for the reliability/availability assessment of a power transmission grid subject to cascading failures under extreme weather conditions," Applied Energy, Elsevier, vol. 185(P1), pages 267-279.
    3. Duncan J. Watts & Steven H. Strogatz, 1998. "Collective dynamics of ‘small-world’ networks," Nature, Nature, vol. 393(6684), pages 440-442, June.
    4. Sperstad, Iver Bakken & Kjølle, Gerd H. & Gjerde, Oddbjørn, 2020. "A comprehensive framework for vulnerability analysis of extraordinary events in power systems," Reliability Engineering and System Safety, Elsevier, vol. 196(C).
    5. Abedi, Amin & Gaudard, Ludovic & Romerio, Franco, 2020. "Power flow-based approaches to assess vulnerability, reliability, and contingency of the power systems: The benefits and limitations," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    6. Wang, Yi & Rousis, Anastasios Oulis & Strbac, Goran, 2020. "On microgrids and resilience: A comprehensive review on modeling and operational strategies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    7. Jufri, Fauzan Hanif & Widiputra, Victor & Jung, Jaesung, 2019. "State-of-the-art review on power grid resilience to extreme weather events: Definitions, frameworks, quantitative assessment methodologies, and enhancement strategies," Applied Energy, Elsevier, vol. 239(C), pages 1049-1065.
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