Deploying Multiple EV Fast Charging Stations in IEEE 33-Bus System Using Evolutionary Computation Technique

The transportation sector is currently going through a period of upheaval, with low carbon as well as green environment serving as its primary goals. The transportation industry is going electric. There is no denying that the installation of charging stations has been heavily influenced by the promotion of EVs (Electric vehicles). To meet the demand for quick energy replenishment while driving, it is crucial to establish rapid charging stations in accessible public spaces. Nevertheless, the sporadic arrival of electric vehicles (EVs) at charging stations and their connection to the grid network for rapid charging result in fluctuation of power as well as peak-valley loads intermittently, so disrupting the power system. The primary goals of this work are the establishment of rapid charging stations in the power grid and a contextual analysis of the IEEE 33-bus system. This article presents a case study of the IEEE.33-bus system, demonstrating how to properly place many fast-charging stations for electric vehicles inside the system without exceeding the voltage magnitude limit and line ratings in four different test scenarios. Using PSO (particle swarm optimization), this study demonstrates how to optimally distribute rapid charging stations for electric vehicles.