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Spatial arbitrage through bidirectional electric vehicle charging with delivery fleets

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  • Mohammadian, Mostafa
  • Baker, Kyri
  • Crozier, Constance

Abstract

The adoption of electric vehicles (EVs), including electric taxis and buses, as a mode of transportation, is rapidly increasing in cities. In addition to providing economic and environmental benefits, these fleets can potentially participate in the energy arbitrage market by leveraging their mobile energy storage capabilities. This presents an opportunity for EV owners to contribute to a more sustainable and efficient energy system while also reducing their operational costs. The present study introduces deterministic and single-stage stochastic optimization frameworks that aim to maximize revenue by optimizing the charging, discharging, and travel of a fleet of electric vehicles in the context of both spatial and temporal energy prices. The simulations are performed on a fleet of electric delivery trucks, which have to make deliveries to certain locations on specific dates. The findings indicate the promising potential of bidirectional electric vehicle charging as a mobile grid asset. However, it is important to note that significant revenue is only realized in scenarios where there is substantial variation in prices between different areas, and when these price variations can be accurately forecasted with a high level of confidence.

Suggested Citation

  • Mohammadian, Mostafa & Baker, Kyri & Crozier, Constance, 2025. "Spatial arbitrage through bidirectional electric vehicle charging with delivery fleets," Applied Energy, Elsevier, vol. 381(C).
    • Handle: RePEc:eee:appene:v:381:y:2025:i:c:s0306261924024206
    DOI: 10.1016/j.apenergy.2024.125036
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    References listed on IDEAS

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    1. Pegah Alaee & Julius Bems & Amjad Anvari-Moghaddam, 2023. "A Review of the Latest Trends in Technical and Economic Aspects of EV Charging Management," Energies, MDPI, vol. 16(9), pages 1-28, April.
    2. Zhang, Qian & Wu, Xiaohan & Deng, Xiaosong & Huang, Yaoyu & Li, Chunyan & Wu, Jiaqi, 2023. "Bidding strategy for wind power and Large-scale electric vehicles participating in Day-ahead energy and frequency regulation market," Applied Energy, Elsevier, vol. 341(C).
    3. Nizami, M.S.H. & Hossain, M.J. & Amin, B.M. Ruhul & Fernandez, Edstan, 2020. "A residential energy management system with bi-level optimization-based bidding strategy for day-ahead bi-directional electricity trading," Applied Energy, Elsevier, vol. 261(C).
    4. Thomas Steffen & Ashley Fly & William Mitchell, 2020. "Optimal Electric Vehicle Charging Considering the Effects of a Financial Incentive on Battery Ageing," Energies, MDPI, vol. 13(18), pages 1-15, September.
    5. Crozier, Constance & Morstyn, Thomas & Deakin, Matthew & McCulloch, Malcolm, 2020. "The case for Bi-directional charging of electric vehicles in low voltage distribution networks," Applied Energy, Elsevier, vol. 259(C).
    6. Zhang, Hao & Lei, Nuo & Wang, Zhi, 2024. "Ammonia-hydrogen propulsion system for carbon-free heavy-duty vehicles," Applied Energy, Elsevier, vol. 369(C).
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    Cited by:

    1. Safari, Ashkan & Rahimi, Afshin, 2025. "Vehicle-to-everything mode of operation technologies: A state-of-art systematic review," Applied Energy, Elsevier, vol. 398(C).

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