IDEAS home Printed from https://ideas.repec.org/a/pkp/ijseer/v11y2022i2p67-85id3081.html
   My bibliography  Save this article

Smart Charging for Electric Ride-Hailing Vehicles using Renewables: A San Francisco Case Study

Author

Listed:
  • Stefania Mitova
  • Alejandro Henao
  • Rudy Kahsar
  • Carson JQ Farmer

Abstract

Charging large fleets of electric ride-hailing vehicles (ERVs) is a complex matter that could serve different objectives: lower carbon dioxide emissions, lower monetary expenditures, or maximize solar photovoltaics (PV) energy consumption. Currently, it is unclear how each of those objectives could impact the business and performance of a ride-hailing fleet. In order to fill this gap, this article employs a dynamic transportation model: a smart charging simulation that combines agent-based, discrete-event, and system dynamic modelling by comparing the above-mentioned objectives in separate scenarios. The results show that each scenario successfully manages to shift between 34% and 87% of all load to hours of the day when the objectives of those scenarios are met. Therefore, in comparison to the baseline, smart charging can save between 5% and 26% of monthly emissions and between 4% and 57% of monthly expenditures. The solar PV scenario, however, results in the highest savings, while ensuring profitable economics via net metering in the short- as well as long term. Finally, the sensitivity analysis points to important trade-offs between several fleet performance metrics. The article concludes by giving business and policy recommendations for maximising the economic, energy and environmental efficiency of large ERV fleets.

Suggested Citation

  • Stefania Mitova & Alejandro Henao & Rudy Kahsar & Carson JQ Farmer, 2022. "Smart Charging for Electric Ride-Hailing Vehicles using Renewables: A San Francisco Case Study," International Journal of Sustainable Energy and Environmental Research, Conscientia Beam, vol. 11(2), pages 67-85.
    • Handle: RePEc:pkp:ijseer:v:11:y:2022:i:2:p:67-85:id:3081
    as

    Download full text from publisher

    File URL: https://archive.conscientiabeam.com/index.php/13/article/view/3081/6839
    Download Restriction: no
    ---><---

    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:pkp:ijseer:v:11:y:2022:i:2:p:67-85:id:3081. 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: Dim Michael (email available below). General contact details of provider: https://archive.conscientiabeam.com/index.php/13/ .

    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.