Multi-Objective Optimization of EVCS and DGs Placement under Varying Load Scenarios in Radial Distribution System

The integration of electric vehicles (EVs) and distributed generation (DG) into modern distribution networks necessitates optimized planning to maintain efficiency and stability. This paper proposes a multi-objective framework for optimal placement of Electric Vehicle Charging Stations (EVCS) and DGs using the Flower Pollination Algorithm (FPA). The algorithm combines biotic and abiotic pollination mechanisms to balance exploration and exploitation, minimizing active and reactive power losses while ensuring voltage limits under load variations of 100%, 125%, and 150%. Simulation results demonstrate that the combined EVCS-DG configuration achieves significant improvements, reducing active power losses by 58.59%, 71.05%, and 79.80% and reactive power losses by 46.38%, 61.40%, and 71.92% across respective load levels. Minimum bus voltages improved to 0.9661 p.u., 0.9616 p.u., and 0.9646 p.u., with convergence times ranging from 102.64 to 123.75 seconds. Comparative analysis confirms superior performance of the proposed method over existing approaches, ensuring enhanced efficiency and network reliability.