The increasing integration of renewable energy sources and electric vehicles is reshaping distribution networks, calling for advanced control strategies to maintain power system quality, stability and resilience, intended to capacity to maintain stability after severe perturbations. This paper investigates the application of grid-forming (GFM) controls, of two types: droop and virtual synchronous machine, within high-power EV charging stations (HPCS) connected to medium voltage distribution grids. Through detailed simulation of five representative case studies, our results show that GFM converters can sustain isolated grids, support black-start procedures, and provide voltage/frequency regulation. Notably, compared to traditional grid-following inverters, GFM strategies enable HPCS to enhance grid resilience to faults (short circuits considered) and also recovery after blackouts. All models are released as open-source Modelica code, enabling reproducibility and further research. These findings highlight the potential of leveraging charging infrastructure as a flexible, grid-supportive resource in future energy systems. The considered control actions may require bi-directional exchange of power between vehicles and the grid, usually called V2G (vehicle-to-grid) control. However, interesting opportunities also exist in the context of V1G (Smart Charging), where power flow is unidirectional but still controllable. They can in principle used also to interface grid-connected independent battery energy storage systems, but using charging battery-electric vehicles for this purpose has the advantage of exploiting infrastructure already in place (the charging station), adding grid services to it, to enhance its economic competitiveness. The importance of using future charging battery electric vehicles to support grid services is confirmed by the fact that this study has been funded by a research project devoted to this.

Grid Forming Inverters for Electric Vehicle Charging Stations to Enhance Distribution Grid Resilience

Stefano Barsali;Massimo Ceraolo;Gianluca Pasini
2025-01-01

Abstract

The increasing integration of renewable energy sources and electric vehicles is reshaping distribution networks, calling for advanced control strategies to maintain power system quality, stability and resilience, intended to capacity to maintain stability after severe perturbations. This paper investigates the application of grid-forming (GFM) controls, of two types: droop and virtual synchronous machine, within high-power EV charging stations (HPCS) connected to medium voltage distribution grids. Through detailed simulation of five representative case studies, our results show that GFM converters can sustain isolated grids, support black-start procedures, and provide voltage/frequency regulation. Notably, compared to traditional grid-following inverters, GFM strategies enable HPCS to enhance grid resilience to faults (short circuits considered) and also recovery after blackouts. All models are released as open-source Modelica code, enabling reproducibility and further research. These findings highlight the potential of leveraging charging infrastructure as a flexible, grid-supportive resource in future energy systems. The considered control actions may require bi-directional exchange of power between vehicles and the grid, usually called V2G (vehicle-to-grid) control. However, interesting opportunities also exist in the context of V1G (Smart Charging), where power flow is unidirectional but still controllable. They can in principle used also to interface grid-connected independent battery energy storage systems, but using charging battery-electric vehicles for this purpose has the advantage of exploiting infrastructure already in place (the charging station), adding grid services to it, to enhance its economic competitiveness. The importance of using future charging battery electric vehicles to support grid services is confirmed by the fact that this study has been funded by a research project devoted to this.
2025
Barsali, Stefano; Bojoi, Radu; Ceraolo, Massimo; Mallemaci, Vincenzo; Mandrile, Fabio; Mocci, Susanna; Pasini, Gianluca
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1363447
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