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

Dominik Husarek, Vjekoslav Salapic, Simon Paulus, Michael Metzger and Stefan Niessen
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Dominik Husarek: Technology, Research in Energy and Electronics, Siemens AG, 81739 Munich, 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

Energies, 2021, vol. 14, issue 23, 1-27

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.

Keywords: charging infrastructure assessment; e-Mobility integration; Agent-based modeling; levers; global sensitivity analysis; service quality (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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