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Combined Optimal Planning and Operation of a Fast EV-Charging Station Integrated with Solar PV and ESS

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  • Leon Fidele Nishimwe H.

    (Department of Electrical Engineering, Soongsil University, Seoul 06978, Korea)

  • Sung-Guk Yoon

    (Department of Electrical Engineering, Soongsil University, Seoul 06978, Korea)

Abstract

Sufficient and convenient fast-charging facilities are crucial for the effective integration of electric vehicles. To construct enough fast electric vehicle-charging stations, station owners need to earn a reasonable profit. This paper proposed an optimization framework for profit maximization, which determined the combined planning and operation of the charging station considering the vehicle arrival pattern, intermittent solar photovoltaic generation, and energy storage system management. In a planning horizon, the proposed optimization framework finds an optimal configuration of a grid-connected charging station. Besides, during the operation horizon, it determines an optimal power scheduling in the charging station. We formulated an optimization framework to maximize the expected profit of the station. Four types of costs were considered during the planning period: the investment cost, operational cost, maintenance cost, and penalties. The penalties arose from vehicle customers’ dissatisfaction associated with waiting time in queues and rejection by the station. The simulation results showed the optimal investment configuration and daily power scheduling in the charging station in various environments such as the downtown, highway, and public stations. Furthermore, it was shown that the optimal configuration was different according to the environments. In addition, the effectiveness of solar photovoltaic, energy storage system, and queue management was demonstrated in terms of the optimal solution through a sensitivity analysis.

Suggested Citation

  • Leon Fidele Nishimwe H. & Sung-Guk Yoon, 2021. "Combined Optimal Planning and Operation of a Fast EV-Charging Station Integrated with Solar PV and ESS," Energies, MDPI, vol. 14(11), pages 1-18, May.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:11:p:3152-:d:564084
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    References listed on IDEAS

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    Cited by:

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    2. Kenji Araki & Yasuyuki Ota & Anju Maeda & Minoru Kumano & Kensuke Nishioka, 2023. "Solar Electric Vehicles as Energy Sources in Disaster Zones: Physical and Social Factors," Energies, MDPI, vol. 16(8), pages 1-25, April.
    3. Tsiropoulos, Ioannis & Siskos, Pelopidas & Capros, Pantelis, 2022. "The cost of recharging infrastructure for electric vehicles in the EU in a climate neutrality context: Factors influencing investments in 2030 and 2050," Applied Energy, Elsevier, vol. 322(C).
    4. Tostado-Véliz, Marcos & Kamel, Salah & Hasanien, Hany M. & Arévalo, Paul & Turky, Rania A. & Jurado, Francisco, 2022. "A stochastic-interval model for optimal scheduling of PV-assisted multi-mode charging stations," Energy, Elsevier, vol. 253(C).
    5. Qiwei Yang & Yantai Huang & Qiangqiang Zhang & Jinjiang Zhang, 2023. "A Bi-Level Optimization and Scheduling Strategy for Charging Stations Considering Battery Degradation," Energies, MDPI, vol. 16(13), pages 1-15, June.
    6. Ruisheng Wang & Zhong Chen & Qiang Xing & Ziqi Zhang & Tian Zhang, 2022. "A Modified Rainbow-Based Deep Reinforcement Learning Method for Optimal Scheduling of Charging Station," Sustainability, MDPI, vol. 14(3), pages 1-14, February.
    7. Jun-Mo Kim & Jeong Lee & Jin-Wook Kim & Junsin Yi & Chung-Yuen Won, 2021. "Power Conversion System Operation to Reduce the Electricity Purchasing Cost of Energy Storage Systems," Energies, MDPI, vol. 14(16), pages 1-20, August.
    8. Natascia Andrenacci & Mauro Di Monaco & Giuseppe Tomasso, 2022. "Influence of Battery Aging on the Operation of a Charging Infrastructure," Energies, MDPI, vol. 15(24), pages 1-18, December.
    9. Raymond Kene & Thomas Olwal & Barend J. van Wyk, 2021. "Sustainable Electric Vehicle Transportation," Sustainability, MDPI, vol. 13(22), pages 1-16, November.

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