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Resiliency-Oriented operation of distribution networks under unexpected wildfires using Multi-Horizon Information-Gap decision theory

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  • Izadi, Mehdi
  • Hossein Hosseinian, Seyed
  • Dehghan, Shahab
  • Fakharian, Ahmad
  • Amjady, Nima

Abstract

Extreme events may trigger cascading outages of different components in power systems and cause a substantial loss of load. Forest wildfires, as a common type of extreme events, may damage transmission/distribution lines across the forest and disconnect a large number of consumers from the electric network. Hence, this paper presents a robust scheduling model based on the notion of information-gap decision theory (IGDT) to enhance the resilience of a distribution network exposed to wildfires. Since the thermal rating of a transmission/distribution line is a function of its temperature and current, it is assumed that the tie-line connecting the distribution network to the main grid is equipped with a dynamic thermal rating (DTR) system aiming at accurately evaluating the impact of a wildfire on the ampacity of the tie-line. The proposed approach as a multi-horizon IGDT-based optimization problem finds a robust operation plan protected against the uncertainty of wind power, solar power, load, and ampacity of tie-lines under a specific uncertainty budget (UB). Since all uncertain parameters compete to maximize their robust regions under a specific uncertainty budget, the proposed multi-horizon IGDT-based model is solved by the augmented normalized normal constraint (ANNC) method as an effective multi-objective optimization approach. Moreover, a posteriori out-of-sample analysis is used to find (i) the best solution among the set of Pareto optimal solutions obtained from the ANNC method given a specific uncertainty budget, and (ii) the best resiliency level by varying the uncertainty budget and finding the optimal uncertainty budget. The proposed approach is tested on a 33-bus distribution network under different circumstances. The case study under different conditions verifies the effectiveness of the proposed operation planning model to enhance the resilience of a distribution network under a close wildfire.

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  • Izadi, Mehdi & Hossein Hosseinian, Seyed & Dehghan, Shahab & Fakharian, Ahmad & Amjady, Nima, 2023. "Resiliency-Oriented operation of distribution networks under unexpected wildfires using Multi-Horizon Information-Gap decision theory," Applied Energy, Elsevier, vol. 334(C).
    • Handle: RePEc:eee:appene:v:334:y:2023:i:c:s0306261922017937
    DOI: 10.1016/j.apenergy.2022.120536
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    References listed on IDEAS

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    1. Tan, Hong & Wang, Yuwei & Wang, Qiujie & Lin, Zhenjia & Mohamed, Mohamed A., 2024. "Day-ahead dispatch of electricity-hydrogen systems under solid-state transportation mode of hydrogen energy via FV-IGDT approach," Energy, Elsevier, vol. 300(C).
    2. Chen, Lei & Jiang, Yuqi & Zheng, Shencong & Deng, Xinyi & Chen, Hongkun & Islam, Md. Rabiul, 2023. "A two-layer optimal configuration approach of energy storage systems for resilience enhancement of active distribution networks," Applied Energy, Elsevier, vol. 350(C).
    3. Wang, Zhaoqi & Zhang, Lu & Tang, Wei & Ma, Ziyao & Huang, Jiajin, 2024. "Equilibrium configuration strategy of vehicle-to-grid-based electric vehicle charging stations in low-carbon resilient distribution networks," Applied Energy, Elsevier, vol. 361(C).
    4. Yin, Linfei & Cai, Zhenjian, 2024. "Multimodal multi-objective hierarchical distributed consensus method for multimodal multi-objective economic dispatch of hierarchical distributed power systems," Energy, Elsevier, vol. 295(C).

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