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Evaluation of Accommodation Capability for Electric Vehicles of a Distribution System Considering Coordinated Charging Strategies

Author

Listed:
  • Qing Deng

    (School of Electrical Engineering, Zhejiang University, Hangzhou 310027, China)

  • Changsen Feng

    (School of Electrical Engineering, Zhejiang University, Hangzhou 310027, 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 Business School, The University of New South Wales, Sydney, NSW 2052, Australia)

  • Lei Wang

    (State Grid Zhejiang Economic Research Institute, Hangzhou 310008, China)

  • Bo Zou

    (State Grid Zhejiang Economic Research Institute, Hangzhou 310008, China)

  • Xizhu Zhang

    (State Grid Zhejiang Economic Research Institute, Hangzhou 310008, China)

Abstract

In recent years, the ever-increasing charging demand of electric vehicles (EVs) imposes challenges on both power supply security and reliability in the distribution system. In this paper, an EV accommodation capability evaluation model of a distribution system, with high penetrations of flexible resources, is established. Firstly, according to the actual classifications of EVs and transportation rules, a Monte Carlo simulation is used to simulate the charging behaviors of EVs so as to obtain the relevant parameters of EV charging. Then, a coordinated charging optimization model for various types of EVs is proposed based on the charging characteristics of EVs. The presented model comprises a mixed-integer linear programming problem and a constrained optimization problem which are respectively solved by CPLEX (the Simplex method implemented in the °C programming language) and the particle swarm optimization (PSO) algorithm. Last of all, a real-life distribution system in the coastal areas of China is served for demonstrating the feasibility and efficiency of the proposed approach. Moreover, the impacts of flexible resources, distribution network zoning rules, and EV growth on the EV accommodation capability of a distribution system are also discussed.

Suggested Citation

  • Qing Deng & Changsen Feng & Fushuan Wen & Chung-Li Tseng & Lei Wang & Bo Zou & Xizhu Zhang, 2019. "Evaluation of Accommodation Capability for Electric Vehicles of a Distribution System Considering Coordinated Charging Strategies," Energies, MDPI, vol. 12(16), pages 1-20, August.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:16:p:3056-:d:255913
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    References listed on IDEAS

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    Cited by:

    1. Munseok Chang & Sungwoo Bae & Gilhwan Cha & Jaehyun Yoo, 2021. "Aggregated Electric Vehicle Fast-Charging Power Demand Analysis and Forecast Based on LSTM Neural Network," Sustainability, MDPI, vol. 13(24), pages 1-17, December.
    2. Bahman Ahmadi & Elham Shirazi, 2023. "A Heuristic-Driven Charging Strategy of Electric Vehicle for Grids with High EV Penetration," Energies, MDPI, vol. 16(19), pages 1-26, October.
    3. Zeeshan Anjum Memon & Dalila Mat Said & Mohammad Yusri Hassan & Hafiz Mudassir Munir & Faisal Alsaif & Sager Alsulamy, 2023. "Effective Deterministic Methodology for Enhanced Distribution Network Performance and Plug-in Electric Vehicles," Sustainability, MDPI, vol. 15(9), pages 1-37, April.

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