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Modeling the Impact of Electric Vehicle Charging Infrastructure on Regional Energy Systems: Fields of Action for an Improved e-Mobility Integration

Author

Listed:
  • Dominik Husarek

    (Technology, Research in Energy and Electronics, Siemens AG, 81739 Munich, Germany
    Technology and Economics of Multimodal Energy Systems, Technical University of Darmstadt, 64289 Darmstadt, Germany)

  • Vjekoslav Salapic

    (Technology, Research in Energy and Electronics, Siemens AG, 81739 Munich, Germany)

  • Simon Paulus

    (Technology, Research in Energy and Electronics, Siemens AG, 81739 Munich, Germany)

  • Michael Metzger

    (Technology, Research in Energy and Electronics, Siemens AG, 81739 Munich, Germany)

  • Stefan Niessen

    (Technology, Research in Energy and Electronics, Siemens AG, 81739 Munich, Germany
    Technology and Economics of Multimodal Energy Systems, Technical University of Darmstadt, 64289 Darmstadt, Germany)

Abstract

Since e-Mobility is on the rise worldwide, large charging infrastructure networks are required to satisfy the upcoming charging demand. Planning these networks not only involves different objectives from grid operators, drivers and Charging Station (CS) operators alike but it also underlies spatial and temporal uncertainties of the upcoming charging demand. Here, we aim at showing these uncertainties and assess different levers to enable the integration of e-Mobility. Therefore, we introduce an Agent-based model assessing regional charging demand and infrastructure networks with the interactions between charging infrastructure and electric vehicles. A global sensitivity analysis is applied to derive general guidelines for integrating e-Mobility effectively within a region by considering the grid impact, the economic viability and the Service Quality of the deployed Charging Infrastructure (SQCI). We show that an improved macro-economic framework should enable infrastructure investments across different types of locations such as public, highway and work to utilize cross-locational charging peak reduction effects. Since the height of the residential charging peak depends up to 18% on public charger availability, supporting public charging infrastructure investments especially in highly utilized power grid regions is recommended.

Suggested Citation

  • Dominik Husarek & Vjekoslav Salapic & Simon Paulus & Michael Metzger & Stefan Niessen, 2021. "Modeling the Impact of Electric Vehicle Charging Infrastructure on Regional Energy Systems: Fields of Action for an Improved e-Mobility Integration," Energies, MDPI, vol. 14(23), pages 1-27, November.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:23:p:7992-:d:691617
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    References listed on IDEAS

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    1. Yuchao Cai & Jie Zhang & Quan Gu & Chenlu Wang, 2024. "An Analytical Framework for Assessing Equity of Access to Public Electric Vehicle Charging Stations: The Case of Shanghai," Sustainability, MDPI, vol. 16(14), pages 1-38, July.
    2. Domenico Tomaselli & Dieter Most & Enkel Sinani & Paul Stursberg & Hans Joerg Heger & Stefan Niessen, 2024. "Leveraging Prosumer Flexibility to Mitigate Grid Congestion in Future Power Distribution Grids," Energies, MDPI, vol. 17(17), pages 1-17, August.

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