The rapid integration of Distributed Renewable Energy Sources and Electric Vehicles (EVs) is transforming modern Distribution Networks (DNs), introducing technical challenges such as voltage deviation, reverse power flows, and line congestion. However, Electric Vehicle Charging Stations (EVCSs) also present an opportunity to absorb local renewable generation and support voltage regulation. This paper proposes an iterative optimisation algorithm based on a full non-linear AC power flow model to determine the optimal EVCS placement within a real low-voltage DN in the UK. Simulations were conducted under various load and generation profiles using real charging data for 22 kW public EVCSs. Results show that with optimal placement, up to 15 EVCSs can be integrated without violating grid constraints. The best placement strategy, which minimises energy absorbed from the MV/LV transformer, reduced voltage standard deviation by over 54% and eliminated reverse power flows. Additionally, the presence of EVCSs enabled a 193.88% increase in Photovoltaic (PV) generation compared to the reference scenario, while maintaining voltage within operational limits. In scenarios with high load and limited generation, EVCS integration was constrained due to line loading limits. Conversely, in high-generation scenarios, EVCSs successfully reduced RPFs by over 90% and allowed more local energy consumption. Further simulations demonstrated that even with energy absorption constraints, strategic placement of just 5 EVCSs was sufficient to eliminate RPFs. The study confirms that properly located EVCSs are essential for enhancing grid flexibility and PV self-consumption, enabling higher DRES penetration, and improving overall DN performance. To the best of our knowledge, this is the first demonstration of EVCS siting that simultaneously eliminates reverse power flows and enhances PV integration in a real DN case study.
Simulation and performance evaluation of optimal electric vehicle charging stations placement under diverse electrical load demand and renewable energy sources generation scenarios in a low-voltage distribution network
Anna Pinnarelli;Fabio Gallo;Pasquale Vizza;Alireza Soleimani
2025-01-01
Abstract
The rapid integration of Distributed Renewable Energy Sources and Electric Vehicles (EVs) is transforming modern Distribution Networks (DNs), introducing technical challenges such as voltage deviation, reverse power flows, and line congestion. However, Electric Vehicle Charging Stations (EVCSs) also present an opportunity to absorb local renewable generation and support voltage regulation. This paper proposes an iterative optimisation algorithm based on a full non-linear AC power flow model to determine the optimal EVCS placement within a real low-voltage DN in the UK. Simulations were conducted under various load and generation profiles using real charging data for 22 kW public EVCSs. Results show that with optimal placement, up to 15 EVCSs can be integrated without violating grid constraints. The best placement strategy, which minimises energy absorbed from the MV/LV transformer, reduced voltage standard deviation by over 54% and eliminated reverse power flows. Additionally, the presence of EVCSs enabled a 193.88% increase in Photovoltaic (PV) generation compared to the reference scenario, while maintaining voltage within operational limits. In scenarios with high load and limited generation, EVCS integration was constrained due to line loading limits. Conversely, in high-generation scenarios, EVCSs successfully reduced RPFs by over 90% and allowed more local energy consumption. Further simulations demonstrated that even with energy absorption constraints, strategic placement of just 5 EVCSs was sufficient to eliminate RPFs. The study confirms that properly located EVCSs are essential for enhancing grid flexibility and PV self-consumption, enabling higher DRES penetration, and improving overall DN performance. To the best of our knowledge, this is the first demonstration of EVCS siting that simultaneously eliminates reverse power flows and enhances PV integration in a real DN case study.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.


