Assessment and enhancement of low voltage distribution network EV hosting capacity

To electrify transportation and minimize carbon emissions, the adoption of electric vehicles (EVs) continues to rise. This growth has driven an expansion of the charging infrastructure supplied directly from the distribution network. However, EV charging leads to significant challenges in the network, such as voltage variations, thermal limits violations, transformer overload, harmonics, high losses, and others. Recent research is focused on improving the capacity of the distribution network to host the high EV charging load. This study investigates the impact of EV penetration on a low-voltage distribution network (DN). It also investigates the enhancement of its EVs' hosting capacity using distributed generation (DG). The DG is optimally sized and located using a Multi-Objective Genetic Algorithm (MOGA). To utilize available renewable energy resources, a combined PV and energy storage system (ESS) is considered. Deep Q-network (DQN) is employed to optimally control the ESS in the presence of PV generations and EV loads. The result shows that EV penetration is highly constrained by grid parameters. The low-voltage DN lines' thermal limits are the first to be violated at 30 % penetration. With the addition of optimally located PV with optimally controlled ESS, the network's capacity is enhanced to support 60 % penetration.