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Optimization of an Energy Storage System for Electric Bus Fast-Charging Station

Author

Listed:
  • Xiaowei Ding

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China
    Beijing Huashang Sanyou New Energy Technology Co., Ltd., Beijing 271000, China)

  • Weige Zhang

    (School of Electrical Engineering, Beijing Jiaotong University, Beijing 100044, China)

  • Shaoyuan Wei

    (Sunwoda Electronic Co., Ltd., Shenzhen 518108, China
    School of Electric Power, South China University of Technology, Tianhe District, Guangzhou 510641, China)

  • Zhenpo Wang

    (National Engineering Laboratory for Electric Vehicles, Beijing Institute of Technology, Beijing 100081, China)

Abstract

To relieve the peak operating power of the electric grid for an electric bus fast-charging station, this paper proposes to install a stationary energy storage system and introduces an optimization problem for obtaining the optimal sizes of an energy buffer. The charging power demands of the fast-charging station are uncertain due to arrival time of the electric bus and returned state of charge of the onboard energy storage system can be affected by actual traffic conditions, ambient temperature and other factors. The introduced optimization is formulated as a stochastic program, where the power matching equality of the total charging demands of connected electric buses is described as a chance constraint by denoting a satisfaction probability, then a stochastic supremum for the operating power of the electric grid is defined by actual data and the problem finally can be solved by convex programming. A case study for an existing electric bus fast-charging station in Beijing, China was utilized to verify the optimization method. The result shows that the operation capacity cost and electricity cost of the electric grid can be decreased significantly by installing a 325 kWh energy storage system in the case of a 99% satisfaction probability.

Suggested Citation

  • Xiaowei Ding & Weige Zhang & Shaoyuan Wei & Zhenpo Wang, 2021. "Optimization of an Energy Storage System for Electric Bus Fast-Charging Station," Energies, MDPI, vol. 14(14), pages 1-17, July.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:14:p:4143-:d:591354
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    References listed on IDEAS

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    Cited by:

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    2. Alessandro Di Giorgio & Emanuele De Santis & Lucia Frettoni & Stefano Felli & Francesco Liberati, 2023. "Electric Vehicle Fast Charging: A Congestion-Dependent Stochastic Model Predictive Control under Uncertain Reference," Energies, MDPI, vol. 16(3), pages 1-16, January.
    3. Edgar Sokolovskij & Arkadiusz Małek & Jacek Caban & Agnieszka Dudziak & Jonas Matijošius & Andrzej Marciniak, 2023. "Selection of a Photovoltaic Carport Power for an Electric Vehicle," Energies, MDPI, vol. 16(7), pages 1-16, March.
    4. Sami M. Alshareef, 2022. "A Novel Fairness-Based Cost Model for Adopting Smart Charging at Fast Charging Stations," Sustainability, MDPI, vol. 14(11), pages 1-28, May.
    5. Shariatio, O. & Coker, P.J. & Smith, S.T. & Potter, B. & Holderbaum, W., 2024. "An integrated techno-economic approach for design and energy management of heavy goods electric vehicle charging station with energy storage systems," Applied Energy, Elsevier, vol. 369(C).
    6. Lorenzo Ricciardi Celsi & Anna Valli, 2023. "Applied Control and Artificial Intelligence for Energy Management: An Overview of Trends in EV Charging, Cyber-Physical Security and Predictive Maintenance," Energies, MDPI, vol. 16(12), pages 1-23, June.
    7. Seyedamin Valedsaravi & Abdelali El Aroudi & Luis Martínez-Salamero, 2022. "Review of Solid-State Transformer Applications on Electric Vehicle DC Ultra-Fast Charging Station," Energies, MDPI, vol. 15(15), pages 1-35, August.
    8. Matteo Ravasio & Gian Paolo Incremona & Patrizio Colaneri & Andrea Dolcini & Piero Moia, 2021. "Distributed Nonlinear AIMD Algorithms for Electric Bus Charging Plants," Energies, MDPI, vol. 14(15), pages 1-17, July.
    9. Graham Town & Seyedfoad Taghizadeh & Sara Deilami, 2022. "Review of Fast Charging for Electrified Transport: Demand, Technology, Systems, and Planning," Energies, MDPI, vol. 15(4), pages 1-30, February.
    10. Ali Saadon Al-Ogaili & Ali Q. Al-Shetwi & Thanikanti Sudhakar Babu & Yap Hoon & Majid A. Abdullah & Ameer Alhasan & Ammar Al-Sharaa, 2021. "Electric Buses in Malaysia: Policies, Innovations, Technologies and Life Cycle Evaluations," Sustainability, MDPI, vol. 13(21), pages 1-22, October.

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