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Impact of Electric Vehicles Charging on Urban Residential Power Distribution Networks

Author

Listed:
  • Mohamed El-Hendawi

    (Faculty of Engineering and Applied Science, University of Regina, Regina, SK S4S 0A2, Canada)

  • Zhanle Wang

    (Faculty of Engineering and Applied Science, University of Regina, Regina, SK S4S 0A2, Canada)

  • Raman Paranjape

    (Faculty of Engineering and Applied Science, University of Regina, Regina, SK S4S 0A2, Canada)

  • James Fick

    (Saskatchewan Power Corporation, Regina, SK S4P 0S1, Canada)

  • Shea Pederson

    (Saskatchewan Power Corporation, Regina, SK S4P 0S1, Canada)

  • Darcy Kozoriz

    (Saskatchewan Power Corporation, Regina, SK S4P 0S1, Canada)

Abstract

Achieving transportation decarbonization and reducing carbon emissions are global initiatives that have attracted a lot of effort. The use of electric vehicles (EVs) has experienced a significant increase lately, which will have a considerable impact on current power systems. This study develops a framework to evaluate/mitigate the negative impact of increasing EV charging on urban power distribution systems. This framework includes data analytics of actual residential electrical load and EV charging profiles, and the development of optimal EV charging management and AC load flow models using an actual residential power distribution system in Saskatchewan, Canada. We use statistical methods to identify a statistically-extreme situation for a power system, which a power utility needs to prepare for. The philosophy is that if the power system can accommodate this situation, the power system will be stable 97.7% of the time. Simulation results show the house voltage and transformer loading at various EV penetration levels under this statistically-extreme situation. We also identify that the particular 22-house power distribution system can accommodate a maximum number of 11 EVs (representing 50% EV penetration) under this statistically-extreme situation. The results also show that the proposed optimal EV charging management model can reduce the peak demand by 43%. Since we use actual data for this study, it reflects the current real-world situation, which presents a useful reference for power utilities. The framework can also be used to evaluate/mitigate the impact of EV charging on power systems and optimize EV infrastructure development.

Suggested Citation

  • Mohamed El-Hendawi & Zhanle Wang & Raman Paranjape & James Fick & Shea Pederson & Darcy Kozoriz, 2024. "Impact of Electric Vehicles Charging on Urban Residential Power Distribution Networks," Energies, MDPI, vol. 17(23), pages 1-22, November.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:23:p:5905-:d:1528585
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    References listed on IDEAS

    as
    1. Yin, Wanjun & Ji, Jianbo & Wen, Tao & Zhang, Chao, 2023. "Study on orderly charging strategy of EV with load forecasting," Energy, Elsevier, vol. 278(C).
    2. LaMonaca, Sarah & Ryan, Lisa, 2022. "The state of play in electric vehicle charging services – A review of infrastructure provision, players, and policies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    3. Crozier, Constance & Morstyn, Thomas & McCulloch, Malcolm, 2020. "The opportunity for smart charging to mitigate the impact of electric vehicles on transmission and distribution systems," Applied Energy, Elsevier, vol. 268(C).
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