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Electric Vehicle User Behavior: An Analysis of Charging Station Utilization in Canada

Author

Listed:
  • Tim Jonas

    (Department of Mechanical, Industrial and Systems Engineering, University of Rhode Island, Kingston, RI 02881, USA)

  • Noah Daniels

    (Department of Computer Science and Statistics, University of Rhode Island, Kingston, RI 02881, USA)

  • Gretchen Macht

    (Department of Mechanical, Industrial and Systems Engineering, University of Rhode Island, Kingston, RI 02881, USA)

Abstract

For a user-centered deployment of electric vehicle supply equipment (EVSE) infrastructure, it is vital to understand electric vehicle user charging behavior. This study identifies user behavioral patterns by analyzing data from more than 7000 charging stations in Canada, comparing residential vs. public Level 2, and public direct current fast (DCFC) vs. public Level 2 charging. A novel algorithm, CHAODA, was applied to identify differences between DCFC and other Level 2 charging options. Through a multivariate and holistic methodology, various patterns emerge, identifying differences in the utilization and seasonality of different EVSE types. The study provides evidence of an “EV Duck Curve” that amplifies the baseline of the power production “Duck Curve,” confirming future challenges for grid stability. Implementations of this study can support future EVSE infrastructure planning efforts and help improve the overall service of electric vehicle supply equipment and grid stability.

Suggested Citation

  • Tim Jonas & Noah Daniels & Gretchen Macht, 2023. "Electric Vehicle User Behavior: An Analysis of Charging Station Utilization in Canada," Energies, MDPI, vol. 16(4), pages 1-19, February.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:4:p:1592-:d:1058381
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    References listed on IDEAS

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    Cited by:

    1. Bingkun Song & Udaya K. Madawala & Craig A. Baguley, 2023. "Optimal Planning Strategy for Reconfigurable Electric Vehicle Chargers in Car Parks," Energies, MDPI, vol. 16(20), pages 1-21, October.
    2. Xiuli Wang & Junkai Wei & Fushuan Wen & Kai Wang, 2023. "A Trading Mode Based on the Management of Residual Electric Energy in Electric Vehicles," Energies, MDPI, vol. 16(17), pages 1-23, August.
    3. Marcelo Bruno Capeletti & Bruno Knevitz Hammerschmitt & Leonardo Nogueira Fontoura da Silva & Nelson Knak Neto & Jordan Passinato Sausen & Carlos Henrique Barriquello & Alzenira da Rosa Abaide, 2024. "User Behavior in Fast Charging of Electric Vehicles: An Analysis of Parameters and Clustering," Energies, MDPI, vol. 17(19), pages 1-20, September.
    4. Ahmad Almaghrebi & Kevin James & Fares Al Juheshi & Mahmoud Alahmad, 2024. "Insights into Household Electric Vehicle Charging Behavior: Analysis and Predictive Modeling," Energies, MDPI, vol. 17(4), pages 1-20, February.

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