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Determining Equipment Capacity of Electric Vehicle Charging Station Operator for Profit Maximization

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  • Se Hoon Baik

    (Department of Electrical and Computer Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea)

  • Young Gyu Jin

    (Department of Electrical Engineering, Jeju National University, 102 Jejudaehak-ro, Jeju-si 63243, Korea)

  • Yong Tae Yoon

    (Department of Electrical and Computer Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea)

Abstract

Related to global efforts to reduce greenhouse gases, numerous electric vehicles (EVs) are expected to be integrated to the power grid. However, the introduction of EVs, particularly in Korea, is still marginal due to the lack of EV charging infrastructure, even though various supportive policies exist. To address this shortage of EV charging stations, the EV charging business needs to be profitable. As with any business, the profitability of the EV charging business is significantly affected by the initial capital investment related to EV chargers and auxiliary equipment such as power conditioning system (PCS), battery energy storage system (BESS), and on-site photovoltaic (PV) generation system. Thus, we propose a formulation to determine the number of EV chargers and the capacity of auxiliary equipment with the objective of a charging station operator (CSO) maximizing profit under regulatory, economic, and physical constraints. The effectiveness of the proposed method is verified with simulations considering various EV charging patterns. The study results will help improve the EV charging infrastructure by encouraging individuals and companies to participate in EV charging business.

Suggested Citation

  • Se Hoon Baik & Young Gyu Jin & Yong Tae Yoon, 2018. "Determining Equipment Capacity of Electric Vehicle Charging Station Operator for Profit Maximization," Energies, MDPI, vol. 11(9), pages 1-15, September.
    • Handle: RePEc:gam:jeners:v:11:y:2018:i:9:p:2301-:d:167064
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Chao-Tsung Ma, 2019. "System Planning of Grid-Connected Electric Vehicle Charging Stations and Key Technologies: A Review," Energies, MDPI, vol. 12(21), pages 1-22, November.
    2. Qiongjie Dai & Jicheng Liu & Qiushuang Wei, 2019. "Optimal Photovoltaic/Battery Energy Storage/Electric Vehicle Charging Station Design Based on Multi-Agent Particle Swarm Optimization Algorithm," Sustainability, MDPI, vol. 11(7), pages 1-21, April.
    3. LaMonaca, Sarah & Ryan, Lisa, 2022. "The state of play in electric vehicle charging services – A review of infrastructure provision, players, and policies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    4. Ana Pavlićević & Saša Mujović, 2022. "Impact of Reactive Power from Public Electric Vehicle Stations on Transformer Aging and Active Energy Losses," Energies, MDPI, vol. 15(19), pages 1-24, September.
    5. Andu Dukpa & Boguslaw Butrylo, 2022. "MILP-Based Profit Maximization of Electric Vehicle Charging Station Based on Solar and EV Arrival Forecasts," Energies, MDPI, vol. 15(15), pages 1-14, August.
    6. Hyung Tae Kim & Young Gyu Jin & Yong Tae Yoon, 2019. "An Economic Analysis of Load Leveling with Battery Energy Storage Systems (BESS) in an Electricity Market Environment: The Korean Case," Energies, MDPI, vol. 12(9), pages 1-16, April.
    7. Dong, Xiao-Jian & Shen, Jia-Ni & Liu, Cheng-Wu & Ma, Zi-Feng & He, Yi-Jun, 2024. "Simultaneous capacity configuration and scheduling optimization of an integrated electrical vehicle charging station with photovoltaic and battery energy storage system," Energy, Elsevier, vol. 289(C).
    8. Rabl, Regina & Reuter-Oppermann, Melanie & Jochem, Patrick E.P., 2024. "Charging infrastructure for electric vehicles in New Zealand," Transport Policy, Elsevier, vol. 148(C), pages 124-144.

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