Optimal Location Placement of EVFCS in Distribution Network Using Genetic Algorithm

In recent times, as the number of electrical vehicle (EV) became increased, many researches has been done on finding the optimal placement of Electrical Vehicle Charging Stations (EVCS). EV research has become one of the most fascinating, interesting, intriguing and exciting field areas in transportation system due to its low CO2 emission, lower energy consumption and high efficiency. It also has lower maintenance costs compared to normal internal combustion engine vehicles. Inappropriate placement of EVCS lead to under-utilization, grid strain, traffic and safety concerns, limited accessibility, environmental and zoning issues. In this study, Genetic Algorithm (GA) based approach model for electrical distribution network are developed to find best placement of Electrical Vehicle Fast Charging Station (EVFCS). Model has been developed to optimize the location of EVFCS in the power distribution network. The distance from each proximity area to EVFCS is considered as objective function of problem formulation and constructed for the acquired model. In this research, the power loss cost of distribution network, fixed installation cost and the line cost of EVFCS are analyzed. The duration time for EVCS is determined and the optimal time is identified. The GA use crossover, mutation, and selection to distribute EVFCS in a way that would best place them in various proximity areas. According to the results the proposed optimal controller outperforms best performance and efficient energy used.