OPTIMAL ALLOCATION OF CHARGING STATIONSFOR ELECTRICVEHICLE INDISTRIBUTIONSYSTEM USING ARTIFICIAL INTELLIGENCE TECHNIQUES

In this paper, two optimal sizing and sitting techniques are proposed for an Electric Vehicle Charging Station (EVCS) on a Distribution System in Elshorouk City, Cairo, Egypt. An improved metaheuristic, named Archimedes Optimization Algorithm (AOA) and Particle Swarm Optimization (PSO) are proposed; to determine the optimal alocations for EVCS considering the objectives of minimizing real power loss, minimizing cost, and maintaning the required voltage profile. In this work, the photovoltaic (PV) is used as a renewable source as a main feeder for the charge stations (CSs). The 46-bus distribution system in Elshorouk City, Cairo, Egypt is testing network as a conducts simulation tests. The results highlight the need of the EVCS sizing and sitting to improve the performance. The optimization technique (AOA) results is compared to the results of the other optimization technique algorithm (PSO). It shows its effectiveness (fast speed, short time and accuracy) and above all gave better power losses and costs as required.