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Collaborative Optimization of Post-Disaster Damage Repair and Power System Operation

Author

Listed:
  • Han Zhang

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

  • Gengfeng Li

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

  • Hanjie Yuan

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

Abstract

After disasters, enhancing the resilience of power systems and restoring power systems rapidly can effectively reduce the economy damage and bad social impacts. Reasonable post-disaster restoration strategies are the most critical part of power system restoration work. This paper co-optimizes post-disaster damage repair and power system operation together to formulate the optimal repair route, the unit output and transmission switching plan. The power outage loss will be minimized, with possible small expense of damage repair and power system operation cost. The co-optimization model is formulated as a mixed integer second order cone program (MISOCP), while the AC-power-flow model, the complex power system restoration constraints and the changing processes of component available states are synthetically considered to make the model more realistic. Lagrange relaxation (LR) decomposes the model into the damage repair routing sub problem and the power system operation sub problem, which can be solved iteratively. An acceleration strategy is used to improve the solving efficiency. The proposed model and algorithm are validated by the IEEE 57-bus test system and the results indicate that the proposed model can realize the enhancement of resilience and the economic restoration of post-disaster power systems.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:10:p:2611-:d:173069
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    References listed on IDEAS

    as
    1. 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.
    2. Lin, Yanling & Bie, Zhaohong, 2018. "Tri-level optimal hardening plan for a resilient distribution system considering reconfiguration and DG islanding," Applied Energy, Elsevier, vol. 210(C), pages 1266-1279.
    3. X. Zhao & P. B. Luh & J. Wang, 1999. "Surrogate Gradient Algorithm for Lagrangian Relaxation," Journal of Optimization Theory and Applications, Springer, vol. 100(3), pages 699-712, March.
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    Cited by:

    1. Juan Toctaquiza & Diego Carrión & Manuel Jaramillo, 2023. "An Electrical Power System Reconfiguration Model Based on Optimal Transmission Switching under Scenarios of Intentional Attacks," Energies, MDPI, vol. 16(6), pages 1-17, March.
    2. 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.
    3. Francisco Quinteros & Diego Carrión & Manuel Jaramillo, 2022. "Optimal Power Systems Restoration Based on Energy Quality and Stability Criteria," Energies, MDPI, vol. 15(6), pages 1-23, March.

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