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Potential and flexibility analysis of electric taxi fleets V2G system based on trajectory data and agent-based modeling

Author

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  • Yu, Qing
  • Wang, Zhen
  • Song, Yancun
  • Shen, Xinwei
  • Zhang, Haoran

Abstract

The utilization of Vehicle-to-Grid (V2G) technology, which facilitates the integration of electric vehicles (EVs) into the power grid, is promising for energy management systems. Among them, electric taxi (ET) is an important part of EVs. The relatively stable and predictable operating patterns of the ET fleets could have a scale effect, effectively managing load demand and supply with V2G technology. This paper investigates the potential and flexibility of V2G technology for urban power system based on real-world ET trajectory data. To evaluate the flexibility of V2G more precisely, a general framework is proposed to infer vehicle charging, energy consumption, and reconstruction of the State of Charge (SoC) for ETs. The V2G potential estimation model is established for each ET, followed by a bottom-up agent-based model to simulate flexibility changes in the system during various V2G events. The proposed methodology is tested on 19,900 ETs in Shenzhen over a month to explore the potential and flexibility of V2G technology. The results show that the V2G system could supply at least 50 MW for 1 h, 30 MW for 2 h, and 20 MW for 3 h during peak periods, while simultaneously recovering within 2–3 h, without disrupting the regular operations of ETs. The great potential of ETs to supply additional energy during peak periods and recover energy during valley periods is highlighted, which could lead to a more efficient and sustainable management of energy resources.

Suggested Citation

  • Yu, Qing & Wang, Zhen & Song, Yancun & Shen, Xinwei & Zhang, Haoran, 2024. "Potential and flexibility analysis of electric taxi fleets V2G system based on trajectory data and agent-based modeling," Applied Energy, Elsevier, vol. 355(C).
    • Handle: RePEc:eee:appene:v:355:y:2024:i:c:s0306261923016872
    DOI: 10.1016/j.apenergy.2023.122323
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    14. Rehman, Anis Ur & Lu, Junwei & Du, Bo & Bai, Feifei & Sanjari, Mohammad J. & Hossain, Md Alamgir, 2026. "Vehicle-to-grid technology for load balancing and energy management: A comprehensive review of technical, economic and environmental perspectives," Applied Energy, Elsevier, vol. 402(PB).
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    18. Chen, Jiawen & Zou, Yuan & Zhang, Jun & Zhang, Xudong & Du, Guodong & Meng, Yihao, 2026. "Optimal energy management at solar-integrated hubs for e-taxis with battery swapping and fast charging under power network constraints," Applied Energy, Elsevier, vol. 402(PB).
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    20. Gharibvand, Hossein & Gharehpetian, G.B. & Anvari-Moghaddam, A., 2024. "A survey on microgrid flexibility resources, evaluation metrics and energy storage effects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 201(C).
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