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A Case Study in Qatar for Optimal Energy Management of an Autonomous Electric Vehicle Fast Charging Station with Multiple Renewable Energy and Storage Systems

Author

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  • Abdulla Al Wahedi

    (Division of Sustainable Development (DSD), College of Science and Engineering (CSE), Hamad Bin Khalifa University (HBKU), Education City 5825, Doha, Qatar)

  • Yusuf Bicer

    (Division of Sustainable Development (DSD), College of Science and Engineering (CSE), Hamad Bin Khalifa University (HBKU), Education City 5825, Doha, Qatar)

Abstract

E-Mobility deployment has attained increased interest during recent years in various countries all over the world. This interest has focused mainly on reducing the reliance on fossil fuel-based means of transportation and decreasing the harmful emissions produced from this sector. To secure the electricity required to satisfy Electric Vehicles’ (EVs’) charging needs without expanding or overloading the existing electricity infrastructure, stand-alone charging stations powered by renewable sources are considered as a reasonable solution. This paper investigates the simulation of the optimal energy management of a proposed grid-independent, multi-generation, fast-charging station in the State of Qatar, which comprises hybrid wind, solar and biofuel systems along with ammonia, hydrogen and battery storage units. The study aims to assess the optimal sizing of the solar, wind and biofuel units to be incorporated in the design along with the optimal ammonia, hydrogen and battery storage capacities to fulfill the daily EV demand in an uninterruptable manner. The main objective is to fast-charge a minimum of 50 EVs daily, while the constraints are the intermittent and volatile nature of renewable energy sources, the stochastic nature of EV demand, local meteorological conditions and land space limitations. The results show that the selection of a 468 kWp concentrated photovoltaic thermal plant, 250 kW-rated wind turbine, 10 kW biodiesel power generator unit and 595 kWh battery storage system, along with the on-site production of hydrogen and ammonia, to generate 200 kW power via fuel cells can achieve the desired target, with a total halt of on-site hydrogen and ammonia production during October and November and 50% reduction during December.

Suggested Citation

  • Abdulla Al Wahedi & Yusuf Bicer, 2020. "A Case Study in Qatar for Optimal Energy Management of an Autonomous Electric Vehicle Fast Charging Station with Multiple Renewable Energy and Storage Systems," Energies, MDPI, vol. 13(19), pages 1-26, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:19:p:5095-:d:421845
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    References listed on IDEAS

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    1. Gong, Lili & Cao, Wu & Liu, Kangli & Yu, Yue & Zhao, Jianfeng, 2020. "Demand responsive charging strategy of electric vehicles to mitigate the volatility of renewable energy sources," Renewable Energy, Elsevier, vol. 156(C), pages 665-676.
    2. Gouveia, João Pedro & Dias, Luís & Martins, Inês & Seixas, Júlia, 2014. "Effects of renewables penetration on the security of Portuguese electricity supply," Applied Energy, Elsevier, vol. 123(C), pages 438-447.
    3. 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.
    4. Wu, Di & Radhakrishnan, Nikitha & Huang, Sen, 2019. "A hierarchical charging control of plug-in electric vehicles with simple flexibility model," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    5. Carlos Méndez & Yusuf Bicer, 2019. "Qatar’s Wind Energy Potential with Associated Financial and Environmental Benefits for the Natural Gas Industry," Energies, MDPI, vol. 12(17), pages 1-19, August.
    6. Hung, Duong Quoc & Mithulananthan, N. & Bansal, R.C., 2014. "An optimal investment planning framework for multiple distributed generation units in industrial distribution systems," Applied Energy, Elsevier, vol. 124(C), pages 62-72.
    7. Goli, P. & Shireen, W., 2014. "PV powered smart charging station for PHEVs," Renewable Energy, Elsevier, vol. 66(C), pages 280-287.
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    Cited by:

    1. Hidab Hamwi & Rajeev Alasseri & Sara Aldei & Mariam Al-Kandari, 2022. "A Pilot Study of Electrical Vehicle Performance, Efficiency, and Limitation in Kuwait’s Harsh Weather and Environment," Energies, MDPI, vol. 15(20), pages 1-14, October.
    2. Evgeny Solomin & Shanmuga Priya Selvanathan & Sudhakar Kumarasamy & Anton Kovalyov & Ramyashree Maddappa Srinivasa, 2021. "The Comparison of Solar-Powered Hydrogen Closed-Cycle System Capacities for Selected Locations," Energies, MDPI, vol. 14(9), pages 1-18, May.
    3. Al Wahedi, Abdulla & Bicer, Yusuf, 2022. "Techno-economic optimization of novel stand-alone renewables-based electric vehicle charging stations in Qatar," Energy, Elsevier, vol. 243(C).
    4. Roberto Ruggieri & Marco Ruggeri & Giuliana Vinci & Stefano Poponi, 2021. "Electric Mobility in a Smart City: European Overview," Energies, MDPI, vol. 14(2), pages 1-29, January.

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