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Power Demand Patterns of Public Electric Vehicle Charging: A 2030 Forecast Based on Real-Life Data

Author

Listed:
  • Marco Baronchelli

    (Department of Energy, Politecnico di Milano, 20156 Milano, Italy)

  • Davide Falabretti

    (Department of Energy, Politecnico di Milano, 20156 Milano, Italy)

  • Francesco Gulotta

    (Department of Energy System Development, Ricerca sul Sistema Energetico, 20134 Milano, Italy)

Abstract

As the adoption of electric vehicles accelerates, understanding the impact of public charging on the power grid is crucial. However, today, a notable gap exists in the literature regarding approaches capable of accurately estimating the expected influence of e-mobility power demand on electrical grids, especially at medium and low voltage levels. To fill this gap, in this study, a procedure is proposed to estimate the power demand patterns of public car parks in a 2030 scenario. To this end, data collected from real-life car parks in Italy are used in Monte Carlo simulations, where probabilistic daily power demand curves are created with different maximum charging powers (from 7.4 kW to ultra-fast charging). The results highlight high variability in the power demand depending on the location and type of car park. City center car parks exhibit peak demand during morning hours, linked to commercial activities, while car parks near railway stations and hospitals show demand patterns aligned with transportation and healthcare needs. Business area car parks, in contrast, have a more pronounced demand during work hours on weekdays, with much lower activity during weekends. This study also demonstrates that, in some situations, ultra-fast charging can increase peak power demand from the grid by up to 210%. Given their contribution to the existing literature, the power demand patterns from this research constitute a valuable starting point for future studies aimed at quantitatively assessing the impact of e-mobility on the power system. In addition, they can effectively support decision-makers in optimally designing the e-mobility recharge infrastructure.

Suggested Citation

  • Marco Baronchelli & Davide Falabretti & Francesco Gulotta, 2025. "Power Demand Patterns of Public Electric Vehicle Charging: A 2030 Forecast Based on Real-Life Data," Sustainability, MDPI, vol. 17(3), pages 1-41, January.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:3:p:1028-:d:1578314
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    References listed on IDEAS

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