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An Integrated Planning Strategy for a Power Network and the Charging Infrastructure of Electric Vehicles for Power System Resilience Enhancement

Author

Listed:
  • Fang Yao

    (School of Electric Power Engineering, Shanxi University, Taiyuan 030013, China)

  • Jiawei Wang

    (Economic Research Institute of State Grid Shanxi Electric Power Company, Taiyuan 030001, China)

  • Fushuan Wen

    (Department for Management of Science and Technology Development, Ton Duc Thang University, Ho Chi Minh City, Vietnam
    Faculty of Electrical and Electronics Engineering, Ton Duc Thang University, Ho Chi Minh City, Vietnam)

  • Chung-Li Tseng

    (UNSW School of Business, University of New South Wales, Sydney, NSW 2052, Australia)

  • Xingyong Zhao

    (School of Electric Power Engineering, Shanxi University, Taiyuan 030013, China)

  • Qiang Wang

    (State Grid Shanxi Electric Power Company, Taiyuan 030001, China)

Abstract

This paper addresses the integrated planning problem of a power network and the charging infrastructure of electric vehicles (EVs) for enhancing power system resilience under various extreme weather scenarios. The planning methodology determines the optimal joint expansion decisions while modeling the benchmark system operation under the n − k resilience criterion. The proposed coordinated planning framework is a robust two-stage/tri-level mixed-integer optimization model. The proposed robust joint planning model includes the construction plan in the first level, identifying the worst-case scenario in the second level, and optimizing the operation cost and load shedding in the final level. To solve this model, a duality-based column and constraint generation (D-CCG) algorithm is developed. Using case studies, both the robust sole transmission planning and joint planning models are demonstrated on the IEEE 30-bus and IEEE 118-bus power systems. Numerical simulations of the benchmark systems validate the effectiveness of the developed framework and the efficiency of the proposed solution approach. Simulation results show the superiority of the proposed robust integrated planning over the sole transmission planning model.

Suggested Citation

  • Fang Yao & Jiawei Wang & Fushuan Wen & Chung-Li Tseng & Xingyong Zhao & Qiang Wang, 2019. "An Integrated Planning Strategy for a Power Network and the Charging Infrastructure of Electric Vehicles for Power System Resilience Enhancement," Energies, MDPI, vol. 12(20), pages 1-20, October.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:20:p:3918-:d:277041
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    References listed on IDEAS

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    1. 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.
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    Cited by:

    1. Zhang, Dongdong & Li, Chunjiao & Goh, Hui Hwang & Ahmad, Tanveer & Zhu, Hongyu & Liu, Hui & Wu, Thomas, 2022. "A comprehensive overview of modeling approaches and optimal control strategies for cyber-physical resilience in power systems," Renewable Energy, Elsevier, vol. 189(C), pages 1383-1406.
    2. 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).
    3. Hassan Yousif Ahmed & Ziad M. Ali & Mohamed M. Refaat & Shady H. E. Abdel Aleem, 2023. "A Multi-Objective Planning Strategy for Electric Vehicle Charging Stations towards Low Carbon-Oriented Modern Power Systems," Sustainability, MDPI, vol. 15(3), pages 1-23, February.
    4. Antonio T. Alexandridis, 2020. "Modern Power System Dynamics, Stability and Control," Energies, MDPI, vol. 13(15), pages 1-8, July.

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