Multi-Objective Approach for Optimal Sizing and Placement of EVCS in Distribution Networks With Distributed Rooftop PV in Metropolitan City

The optimal sizing and location of electric vehicle charging station (EVCS) integrated with distributed generation (DG) in the distribution network are the subject of this study. In modern electric power systems, the integration of EVCS and DG must be carefully planned. Inappropriate sizing and location of EVCS can cause network overload, increase power losses, and allow for voltage variations outside the standard. This study adopts a reference distribution network that is representative of a typical business distribution network in a metropolitan city in Indonesia. To resolve the issue of determining the size and location of EVCS, the hybrid genetic algorithm-modified salp swarm algorithm (HGAMSSA) optimization method with multi-objective function is implemented. There are three scenarios used when determining the size and placement of EVCS. In the first scenario, the EVCS comprises chargers at levels 1, 2, and 3, with DG integration. In the second scenario, EVCS is comprised of level 2 and level 3, with DG integration. While in the third scenario, EVCS only consists of level 3 chargers with DG integration. The simulation results indicate that network utilization can be optimized at 79.00%, 75.53%, and 76.37% when electric cars (EV) operate in grid to vehicle (G2V) mode, compared to a base load of 29.46%. In vehicle to grid (V2G) mode, the energy supplied by the electric vehicle (EV) via the EVCS is 0.91 MWh. Additionally, the distribution network receives 10.036 MWh of electricity from rooftop photovoltaic (PV).