A Hybrid Pso–Emsocp Approach for Optimal Ev Charging Station Placement and Distributed Generation Planning in Radial Distribution Networks

The growing adoption of electric vehicles (EVs) has led to a significant rise in electricity demand, creating challenges for the reliability of distribution networks. Strategic placement of EV charging stations (EVCSs) is crucial for ensuring grid stability and minimizing disruptions. To mitigate the impact of EVCSs on radial distribution networks (RDNs), this study explores the integration of distributed generators (DGs) within a reconfigured network, where optimal switch positions and power flow adjustments enhance overall system efficiency. However, poor placement and sizing of DGs and EVCSs can significantly affect system performance. This study analyses the impact of EVCSs on RDNs using Particle Swarm Optimization (PSO). The planning process consists of two stages: first, using PSO to determine the best location for EVCSs, and second, reconfiguring the network while simultaneously determining the optimal locations and sizes of DGs using Second-Order Cone Programming (SOCP) to ensure greater system stability. The methodology, validated on the IEEE 33-bus network, aims to reduce power losses and enhance voltage stability. The outcomes demonstrate how well the suggested strategy works to maximize DG and EVCS installation without sacrificing grid stability. This planning strategy not only optimizes network configuration by reducing power losses and voltage deviations but also contributes to a more resilient and efficient power distribution system in the era of widespread EV adoption.