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Optimal Design of Electric Vehicle Fast-Charging Station’s Structure Using Metaheuristic Algorithms

Author

Listed:
  • Phiraphat Antarasee

    (Department of Electrical Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand)

  • Suttichai Premrudeepreechacharn

    (Department of Electrical Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand)

  • Apirat Siritaratiwat

    (Department of Electrical Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002, Thailand)

  • Sirote Khunkitti

    (Department of Electrical Engineering, Faculty of Engineering, Chiang Mai University, Chiang Mai 50200, Thailand)

Abstract

The fast development of electric vehicles (EVs) has resulted in several topics of research in this area, such as the development of a charging pricing strategy, charging control, location of the charging station, and the structure within the charging station. This paper proposes the optimal design of the structure of an EV fast-charging station (EVFCS) connected with a renewable energy source and battery energy storage systems (BESS) by using metaheuristic algorithms. The optimal design of this structure aims to find the number and power of chargers. Moreover, the renewable energy source and BESS can reduce the impact on the grid, so these energy sources are considered as ones of the optimally-designed structure of EVFCS in this work. Thus, it is necessary to determine the optimal sizing of the renewable energy source, BESS, and the grid power connected to EVFCS. This optimal structure can improve the profitability of the station. To solve the optimization problem, three metaheuristic algorithms, including particle swarm optimization (PSO), Salp swarm algorithm (SSA), and arithmetic optimization algorithm (AOA), are adopted. These algorithms aim to find the optimal structure which maximizes the profit of the EVFCS determined by its net present value (NPV), and the results obtained from these algorithms were compared. The results demonstrate that all considered algorithms could find the feasible solutions of the optimal design of the EVFCS structure where PSO provided the best NPV, followed by AOA and SSA.

Suggested Citation

  • Phiraphat Antarasee & Suttichai Premrudeepreechacharn & Apirat Siritaratiwat & Sirote Khunkitti, 2022. "Optimal Design of Electric Vehicle Fast-Charging Station’s Structure Using Metaheuristic Algorithms," Sustainability, MDPI, vol. 15(1), pages 1-22, December.
    • Handle: RePEc:gam:jsusta:v:15:y:2022:i:1:p:771-:d:1021854
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    References listed on IDEAS

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    1. Supanat Chamchuen & Apirat Siritaratiwat & Pradit Fuangfoo & Puripong Suthisopapan & Pirat Khunkitti, 2021. "High-Accuracy Power Quality Disturbance Classification Using the Adaptive ABC-PSO as Optimal Feature Selection Algorithm," Energies, MDPI, vol. 14(5), pages 1-18, February.
    2. Ali M. Eltamaly & M. S. Al-Saud & A. G. Abo-Khalil, 2020. "Performance Improvement of PV Systems’ Maximum Power Point Tracker Based on a Scanning PSO Particle Strategy," Sustainability, MDPI, vol. 12(3), pages 1-20, February.
    3. 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.
    4. Sadeghi-Barzani, Payam & Rajabi-Ghahnavieh, Abbas & Kazemi-Karegar, Hosein, 2014. "Optimal fast charging station placing and sizing," Applied Energy, Elsevier, vol. 125(C), pages 289-299.
    5. Nathphol Khaboot & Chitchai Srithapon & Apirat Siritaratiwat & Pirat Khunkitti, 2019. "Increasing Benefits in High PV Penetration Distribution System by Using Battery Enegy Storage and Capacitor Placement Based on Salp Swarm Algorithm," Energies, MDPI, vol. 12(24), pages 1-20, December.
    6. Ali M. Eltamaly, 2021. "A Novel Strategy for Optimal PSO Control Parameters Determination for PV Energy Systems," Sustainability, MDPI, vol. 13(2), pages 1-28, January.
    7. Sirote Khunkitti & Apirat Siritaratiwat & Suttichai Premrudeepreechacharn & Rongrit Chatthaworn & Neville R. Watson, 2018. "A Hybrid DA-PSO Optimization Algorithm for Multiobjective Optimal Power Flow Problems," Energies, MDPI, vol. 11(9), pages 1-21, August.
    8. Dominic A. Savio & Vimala A. Juliet & Bharatiraja Chokkalingam & Sanjeevikumar Padmanaban & Jens Bo Holm-Nielsen & Frede Blaabjerg, 2019. "Photovoltaic Integrated Hybrid Microgrid Structured Electric Vehicle Charging Station and Its Energy Management Approach," Energies, MDPI, vol. 12(1), pages 1-28, January.
    9. Happy Aprillia & Hong-Tzer Yang & Chao-Ming Huang, 2020. "Short-Term Photovoltaic Power Forecasting Using a Convolutional Neural Network–Salp Swarm Algorithm," Energies, MDPI, vol. 13(8), pages 1-20, April.
    10. Hafez, Omar & Bhattacharya, Kankar, 2017. "Optimal design of electric vehicle charging stations considering various energy resources," Renewable Energy, Elsevier, vol. 107(C), pages 576-589.
    11. Rong-Ceng Leou & Jeng-Jiun Hung, 2017. "Optimal Charging Schedule Planning and Economic Analysis for Electric Bus Charging Stations," Energies, MDPI, vol. 10(4), pages 1-17, April.
    12. Fathabadi, Hassan, 2020. "Novel stand-alone, completely autonomous and renewable energy based charging station for charging plug-in hybrid electric vehicles (PHEVs)," Applied Energy, Elsevier, vol. 260(C).
    13. Vermaak, Herman Jacobus & Kusakana, Kanzumba, 2014. "Design of a photovoltaic–wind charging station for small electric Tuk–tuk in D.R.Congo," Renewable Energy, Elsevier, vol. 67(C), pages 40-45.
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