IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v324y2025ics0360544225016391.html
   My bibliography  Save this article

Harnessing the power of electric taxis: A data-driven exploration of V2G potential in taxi service areas

Author

Listed:
  • Ma, Chuanqi
  • Pei, Mingyang
  • Cai, Ming
  • Zhong, Lingshu
  • Fu, Xiao

Abstract

Electric taxis (ETs) operating daily in urban areas can bring huge vehicle-to-grid (V2G) potential. However, previous studies often ignore the needs of electric taxi owners when assessing this potential. This work focuses on ETs, a high-usage group with significant implications for urban energy management, to assess their V2G potential. We construct an ET driving behavior model and a taxi service area probability assessment model, comprehensively considering the influence of service area location, capacity, and accessibility on V2G potential. An improved Monte Carlo algorithm, combining actual operational data with random variables, is employed to evaluate V2G potential. Using operational data from Guangzhou, China, our findings indicate that the maximum peak V2G potential can reach approximately 6500 kW. These insights provide practical recommendations for enhancing V2G implementation with electric taxis, offering a novel and comprehensive approach that integrates service area dynamics and real-world operational data.

Suggested Citation

  • Ma, Chuanqi & Pei, Mingyang & Cai, Ming & Zhong, Lingshu & Fu, Xiao, 2025. "Harnessing the power of electric taxis: A data-driven exploration of V2G potential in taxi service areas," Energy, Elsevier, vol. 324(C).
    • Handle: RePEc:eee:energy:v:324:y:2025:i:c:s0360544225016391
    DOI: 10.1016/j.energy.2025.135997
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544225016391
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2025.135997?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:324:y:2025:i:c:s0360544225016391. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.