Optimizing Distribution Generation and EV Charging Station Placement with Particle Swarm Optimization under Variable Load Condition

Effectively managing a distribution system entails a crucial undertaking to minimize power losses and conserve energy. The utilization of Distributed Generation (DG) emerges as a highly efficient strategy for achieving this goal. However, the widespread implementation of Electric Vehicle Charging Stations (EVCSs) on a larger scale presents a notable challenge for distribution system operators in terms of optimal planning. The increasing integration of Electric Vehicles (EVs) into the distribution network exacerbates the mismatch between power generation and demand, leading to escalated power losses and compromised voltage levels. Addressing the adverse effects of the expanding EV load on distribution systems requires strategically integrating EVCS at suitable locations. This work delves into an optimization approach that concurrently determines the sizing and placement of both EVCS and DG, considering diverse load models. The primary objective is to minimize active power loss in the electrical distribution system. The proposed method is tested on a 33-bus system, employing the Particle Swarm Optimization (PSO) algorithm for system objective optimization. The results illustrate that this optimization technique significantly improves system performance and efficiency by optimizing the planning and operation of DG and Electric Vehicles while considering various load models.