MV and LV Residential Grid Impact of Combined Slow and Fast Charging of Electric Vehicles
Niels Leemput,
Frederik Geth,
Juan Van Roy,
Pol Olivella-Rosell,
Johan Driesen,
Andreas Sumper
Affiliations
Niels Leemput
Faculty of Engineering, Department of Electrical Engineering, Division Electrical Energy & Computer Architectures, KU Leuven, Kasteelpark Arenberg 10, Box 2445, 3001 Leuven, Belgium
Frederik Geth
Faculty of Engineering, Department of Electrical Engineering, Division Electrical Energy & Computer Architectures, KU Leuven, Kasteelpark Arenberg 10, Box 2445, 3001 Leuven, Belgium
Juan Van Roy
Faculty of Engineering, Department of Electrical Engineering, Division Electrical Energy & Computer Architectures, KU Leuven, Kasteelpark Arenberg 10, Box 2445, 3001 Leuven, Belgium
Pol Olivella-Rosell
Centre of Technological Innovation in Static Converters and Drives, Department of Electrical Engineering, College of Industrial Engineering of Barcelona, Universitat Politècnica de Catalunya-BarcelonaTech, Carrer Comte d'Urgell, 187-08036 Barcelona, Spain
Johan Driesen
Faculty of Engineering, Department of Electrical Engineering, Division Electrical Energy & Computer Architectures, KU Leuven, Kasteelpark Arenberg 10, Box 2445, 3001 Leuven, Belgium
Andreas Sumper
Centre of Technological Innovation in Static Converters and Drives, Department of Electrical Engineering, College of Industrial Engineering of Barcelona, Universitat Politècnica de Catalunya-BarcelonaTech, Carrer Comte d'Urgell, 187-08036 Barcelona, Spain
This article investigates the combined low voltage (LV) and medium voltage (MV) residential grid impact for slow and fast electric vehicle (EV) charging, for an increasing local penetration rate and for different residential slow charging strategies. A realistic case study for a Flemish urban distribution grid is used, for which three residential slow charging strategies are modeled: uncoordinated charging, residential off-peak charging, and EV-based peak shaving. For each slow charging strategy, the EV hosting capacity is determined, with and without the possibility of fast charging, while keeping the grid within its operating limits. The results show that the distribution grid impact is much less sensitive to the presence of fast charging compared to the slow charging strategy. EV-based peak shaving results in the lowest grid impact, allowing for the highest EV hosting capacity. Residential off-peak charging has the highest grid impact, due the load synchronization effect that occurs, resulting in the lowest EV hosting capacity. Therefore, the EV users should be incentivized to charge their EVs in a more grid-friendly manner when the local EV penetration rate becomes significant, as this increases the EV hosting capacity much more than the presence of fast charging decreases it.