With the rise in the quantity of electric vehicles, the characteristics of electric vehicle charging patterns can significantly influence distribution systems, particularly depending on the location of the electric vehicle charging. So, it requires effective charging infrastructure deployment to provide stable and sustainable power delivery. This study discusses how to locate (optimal placement) EV charging stations in a distribution system to reduce power losses, voltage instability and operational expenses. Particle Swarm Optimization (PSO) and Genetic Algorithm (GA), two prominent metaheuristics for complex, nonlinear optimization, tackle the optimization problem. These algorithms are compared to determine their usefulness in improving power quality and system stability as EV penetration rises. The IEEE 33-bus radial distribution network is employed as the test system to minimize power losses and voltage variations. Simulation results show that both algorithms can find optimal solutions, but PSO converges faster while GA explores the solution space more broadly. The main goal is to locate the EVCS as optimally as possible inside the current radial distribution network, taking into account both the voltage at the system’s buses and real (active) power losses.