Optimized sizing and placement of electric vehicle charging stations for maximum efficiency in radial distribution systems

Abstract

The increasing integration of electric vehicles (EVs) into the transportation sector is shifting energy demands and reducing voltage stability margins within the grid. To mitigate these challenges, it is crucial to coordinate the placement and sizing of Electric Vehicle Charging Stations (EVCS) to minimize the impact of EV load penetration in radial distribution systems. The proposed approach is the Lotus Effect Optimization Algorithm (LEOA). The major aim of the proposed method is to enhance voltage stability and system efficiency through the optimal placement and sizing of EVCS integrated with radial distribution networks. The LEOA is used to optimize the sizing of the EVCS. The method is implemented on the MATLAB platform, utilizing the IEEE 33-bus system, and compared with existing techniques, such as the Arithmetic Optimization Algorithm (AOA), Particle Swarm Optimization (PSO), and Many-objective Stochastic Competition Optimization (MOSCO). The comparison demonstrates that the proposed LEOA method outperforms the existing methods, achieving an efficiency of approximately 98%. In contrast, the AOA method reaches 85%, PSO achieves 78%, and MOSCO attains 65%. This comparison demonstrates its ability to optimize the placement and sizing of EVCS utilizing the proposed advanced method, as well as its superior performance in minimizing power losses and enhancing the efficiency of power distribution networks