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Resilient distribution network planning under the severe windstorms using a risk-based approach

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  • Popović, Željko N.
  • KovaÄ ki, Neven V.
  • Popović, Dragan S.

Abstract

This paper proposes a risk-based approach for planning resilient radial distribution networks to severe windstorms. The proposed approach is based on the concept of interval analysis, Relative Distance Measure (RDM) interval arithmetic, mixed integer linear programming, and risk analysis. It enables obtaining a number of different resilient network plans taking into account dependence among the following uncertain inputs: maximum wind speed, storm duration and its annual frequency of occurrence, fragility of network components, repair duration, forecasted load and generation from renewable generators. In order to improve the computational efficiency of the proposed approach a hybrid simulated annealing and mixed integer linear programming algorithm is introduced. The best resilient plan is selected by employing the Minimal risk (Minimax) criterion for measuring and managing risk. In this way, the proposed approach provides a decision-maker with a means of determining the resilient network plan that minimizes the risk of significant costs due to severe windstorms.

Suggested Citation

  • Popović, Željko N. & KovaÄ ki, Neven V. & Popović, Dragan S., 2020. "Resilient distribution network planning under the severe windstorms using a risk-based approach," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    • Handle: RePEc:eee:reensy:v:204:y:2020:i:c:s0951832020306153
    DOI: 10.1016/j.ress.2020.107114
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    References listed on IDEAS

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    1. Li, Yanfu & Zio, Enrico, 2012. "Uncertainty analysis of the adequacy assessment model of a distributed generation system," Renewable Energy, Elsevier, vol. 41(C), pages 235-244.
    2. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    3. Salman, Abdullahi M. & Li, Yue & Stewart, Mark G., 2015. "Evaluating system reliability and targeted hardening strategies of power distribution systems subjected to hurricanes," Reliability Engineering and System Safety, Elsevier, vol. 144(C), pages 319-333.
    4. 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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