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Electric Vehicle Charger Static and Dynamic Modelling for Power System Studies

Author

Listed:
  • Hengqing Tian

    (Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow G1 1XW, UK)

  • Dimitrios Tzelepis

    (Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow G1 1XW, UK)

  • Panagiotis N. Papadopoulos

    (Department of Electronic and Electrical Engineering, University of Strathclyde, Glasgow G1 1XW, UK)

Abstract

Electric Vehicles (EVs) are becoming increasingly available and are expected to be a large part of the load in future power systems. EV chargers are a relatively new type of load and are mainly interfaced with the grid through power electronics. It is therefore important to investigate the impact they have on power system dynamic behaviour. In this paper, two detailed EV charger models (representing a typical slow and fast charger) were investigated. The aim was to test the capability of standard static—and more importantly, dynamic—load models, commonly used in power system studies, to represent the static and dynamic behaviour of EV chargers. Different control parameter settings for two types of EV chargers were investigated, as were the limits of standard power system dynamic load model structures’ accurate representation. Typical parameter sets have also been provided for cases where proper representation was possible.

Suggested Citation

  • Hengqing Tian & Dimitrios Tzelepis & Panagiotis N. Papadopoulos, 2021. "Electric Vehicle Charger Static and Dynamic Modelling for Power System Studies," Energies, MDPI, vol. 14(7), pages 1-16, March.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:7:p:1801-:d:523149
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    References listed on IDEAS

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    1. Andrés Arias-Londoño & Oscar Danilo Montoya & Luis Fernando Grisales-Noreña, 2020. "A Chronological Literature Review of Electric Vehicle Interactions with Power Distribution Systems," Energies, MDPI, vol. 13(11), pages 1-23, June.
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    Cited by:

    1. Andu Dukpa & Boguslaw Butrylo, 2022. "MILP-Based Profit Maximization of Electric Vehicle Charging Station Based on Solar and EV Arrival Forecasts," Energies, MDPI, vol. 15(15), pages 1-14, August.

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