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ORIGINAL RESEARCH article

Front. Future Transp.
Sec. Transportation Systems Modeling
Volume 5 - 2024 | doi: 10.3389/ffutr.2024.1500224

Forecasting the vehicle energy potential to support the needs of electricity grid: a floating car data-based methodology

Provisionally accepted
Antonio Comi Antonio Comi 1,2*Umberto Crisalli Umberto Crisalli 1Simone Sportiello Simone Sportiello 1
  • 1 Department of Enterprise Engineering, University of Rome Tor Vergata, Rome, Italy
  • 2 University of Rome Tor Vergata, Roma, Italy

The final, formatted version of the article will be published soon.

    In a global context characterized by climate warming, the transport sector has found the use of electric vehicles to be one of the possible measures of decarbonization. Although the purchase rate of this type of vehicle is still low, there are many research fields related to both the development of the electric charging network and the improvement of batteries to ensure features that meet the expectations of users. Moreover, the increase of the use of electricity can cause issues in electrical network stability, especially during the peak hours. Therefore, this sector is facing new challenges, including the case of vehicle-to-grid (V2G), which is a solution that allows the use of vehicle batteries, not only as a source of energy for the vehicles, but also as stabilizers of the supply network when the vehicles are parked (i.e., no energy is needed for their activity). In the recent years, the researchers mainly focused on the energy infrastructure and technologies, neglecting problems related to the identification of the best locations for V2G services and the potential acceptance of the electric vehicles' owners, as well as on the potential energy that can be transferred to the grid according to the users' needs (e.g., to continue to use their vehicle for completing the daily activities). This paper proposes a methodology aimed at identifying potential areas for deploying V2G services by using floating car data (FCD) and at estimating the potential energy to be transferred to the grid without interfering with the daily activities. This methodology is finally applied to a case study of five provinces of the Veneto region, showing the significant results obtained.

    Keywords: V2G, Vehicle-to-grid, Charging location, FCD, Floating car data, Parking areas, Trip detection, electric vehicle

    Received: 22 Sep 2024; Accepted: 15 Oct 2024.

    Copyright: © 2024 Comi, Crisalli and Sportiello. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Antonio Comi, Department of Enterprise Engineering, University of Rome Tor Vergata, Rome, Italy

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.