A Genetic Algorithm based Network Friendly Charging Scheme for Electric Vehicles

The massive electrification of the transportation sector worldwide faces significant challenges in terms of appropriate charging facilities from the complex power grid infrastructure. The uncontrolled charging of large-scale electric vehicles (EVs) creates a high level of difficulties in the smooth operation of the power grid. Therefore, in the domestic network, some levels of coordinated EV charging schemes are required to maintain the ease of operation of the power system. In this paper, a Genetic Algorithm (GA)-based optimization technique has been incorporated with the valley-filling technique to control the charging patterns of the EVs considering residential distribution feeder capacity. Both the users' convenience and network stress are addressed in the proposed charging scheme. The proposed scheme maximizes the number of vehicles that can be integrated under a feeder transformer without exceeding its capacity. Results indicate that the proposed charging scheme for electric vehicles flattens the load profile with the utilization of maximum supply energy from the system. Several case studies prove the robustness of the proposed method.