Optimal sizing and sitting of electric vehicle charging station by using archimedes optimization algorithm technique

Abstract

Increasing penetration of electric vehicle (EV) load into the electricity sector will result in generation imbalance, an increase in real power loss, a low voltage profile and consequently a decrease in the margin of stability of voltage. It is necessary for the coordination of charging stations (CSs) for EV at the relevant locations to minimize the effect of increased EV load penetration in radial systems. In this paper, a new optimization method named Archimedes optimization algorithm (AOA) is proposed; it determined the optimal location and size for EV-CS for reducing power losses and improved voltage profile. In this work we used the photovoltaic (PV) renewable source as a main feeder for the CSs. Many of Artificial Intelligence technique are applied to determine the optimal sizing and sitting of EV-CSs considering the objective of minimization of real power loss. IEEE 33-bus testing network conducts simulation tests. The results highlighted the need to refine the EV-CS allocation to improve the performance. The ability to solve complex, non-linear objective optimization issues using AOA and to compare the results with other algorithms, namely particle swarm optimization (PSO), cuckoo search algorithm (CSA), shows its effectiveness in minimizing the power loss as required.