Multi-objective siting and sizing of E charging stations in the distribution system

This paper addresses the siting and sizing of electric vehicle (EV) charging stations in the distribution system as a multi-objective optimization problem. The minimization of total real power loss and total voltage deviation are considered as the objective functions of the problem. An algorithm based on integration of Non-dominated Sorting Genetic Algorithm II (NSGA-II) with Gauss-Seidel load flow algorithm is proposed to solve the aforementioned problem. The proposed algorithm is implemented on a 14 bus network which is a segment of the distribution network of Jurong Lake District, Singapore. To investigate the performance of the algorithm, the siting and sizing problem is solved as a single-objective optimization problem as well. The simulation results indicate that the total real power loss and total voltage deviation objectives worsen as EV penetration level increases. Further, the simulation results demonstrate that the proposed algorithm can efficiently obtain the trade-off optimal solutions for the multi-objective EV charging stations allocation problem.