Optimal Charging Coordination of Electric Vehicles Considering Users Charging Behavior Using Particle Swarm Optimization (PSO)

In recent years, electric vehicles (EVs) have become more popular as technology has improved and support for clean transportation has grown. As the number of EVs continues to rise, more and more charging stations are being installed to the grid. Grid with high penetration of EVs causes a problem to the stability of the distribution system. Therefore, optimal charging coordination is needed to reduce the impact of charging. This study presents optimal charging coordination of EVs in a residential distribution network considering EV users charging behavior and daily residential load demand profile in Malaysia using particle swarm optimization (PSO) algorithm. The proposed optimization is operated within operating constraints such as power demand and bus voltage constraints while achieving the objective function of minimizing power losses. The optimization also considers EV users charging behavior i.e., urgent charging and nonurgent charging. EV users can choose their preferable charging mode based on the charging urgency, ensuring their preferences and satisfaction. The performance of the proposed method is evaluated using IEEE 33-bus radial distribution network with the assumption that each bus connected to a residential feeder populated with EVs. Comparison analysis between uncoordinated and coordinated charging considering four different EV penetration levels is conducted. Results show that the proposed coordinated charging manages to optimize the load with EV and produces a promising reduction in the network’s power losses compared to uncoordinated charging.