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A secure tri-level planner-disaster-risk-averse replanner model for enhancing the resilience of energy systems

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  • Aldarajee, Ammar H.M.
  • Hosseinian, Seyed H.
  • Vahidi, Behrooz

Abstract

This paper presents a secure tri-level planner-disaster-risk-averse-replanner model for resilience-oriented investment planning in integrated electric power and natural gas networks, where generation units, static VAr compensators, wind farms, transmission lines, and gas pipelines are considered as investment candidates. Additionally, emergency demand response is utilized to enhance the resilience of the integrated energy system. The proposed model is capable of controlling the resilience of the integrated energy system through a specific parameter designated as the resilience indicator and solved by a sequential three-level algorithm. The first-level problem finds the optimal investment plan before any disruptive event. Given the optimal investment plan obtained by solving the first-level problem, the second-level problem finds worst-case disruptive events affecting different components in the integrated energy system, where the vulnerability of these components is evaluated, aiming at considering a multi-disaster and multi-zone resilience model. Given a specific resilience budget, which limits replanning costs, the third-level problem maximizes the resilience of the integrated network by replanning investment decisions of the first-level problem, aiming at compensating for the unserved demand caused by the second-level problem. Case studies justify the suitability of the proposed model to enhance the resilience of the integrated system under different disastrous events.

Suggested Citation

  • Aldarajee, Ammar H.M. & Hosseinian, Seyed H. & Vahidi, Behrooz, 2020. "A secure tri-level planner-disaster-risk-averse replanner model for enhancing the resilience of energy systems," Energy, Elsevier, vol. 204(C).
    • Handle: RePEc:eee:energy:v:204:y:2020:i:c:s0360544220310239
    DOI: 10.1016/j.energy.2020.117916
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    5. Jalilpoor, Kamran & Oshnoei, Arman & Mohammadi-Ivatloo, Behnam & Anvari-Moghaddam, Amjad, 2022. "Network hardening and optimal placement of microgrids to improve transmission system resilience: A two-stage linear program," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    6. Fu, Wei & Xie, Haipeng & Zhu, Hao & Wang, Hefeng & Jiang, Lizhou & Chen, Chen & Bie, Zhaohong, 2023. "Coordinated post-disaster restoration for resilient urban distribution systems: A hybrid quantum-classical approach," Energy, Elsevier, vol. 284(C).
    7. Ambrosius, Mirjam & Egerer, Jonas & Grimm, Veronika & van der Weijde, Adriaan H., 2022. "Risk aversion in multilevel electricity market models with different congestion pricing regimes," Energy Economics, Elsevier, vol. 105(C).
    8. Wang, Chong & Ju, Ping & Wu, Feng & Pan, Xueping & Wang, Zhaoyu, 2022. "A systematic review on power system resilience from the perspective of generation, network, and load," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    9. Sun, Qirun & Wu, Zhi & Ma, Zhoujun & Gu, Wei & Zhang, Xiao-Ping & Lu, Yuping & Liu, Pengxiang, 2022. "Resilience enhancement strategy for multi-energy systems considering multi-stage recovery process and multi-energy coordination," Energy, Elsevier, vol. 241(C).
    10. 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).

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