Optimal Sequential Distribution Planning for Low Voltage Network with Electric Vehicle Loads

This paper develops a particle swarm optimization-based methodology for low voltage distribution system planning to support the extensive use of electric vehicles. The entry of electric vehicles unavoidably alters load profile, therefore affecting the voltage of customer load points and capacity loading of the distribution feeders and distribution transformers. The system reinforcement to accommodate the increased EV loads can be achieved by yearly sequential decision making, given updated information of the locations and amount of EV loads. The individual load profile can be simulated by a Monte Carlo Simulation. The objective function is to minimize the total cost associated with installing and dismantling control devices and energy loss over a planning period. The proposed methodology was tested with a 30-bus system. The results show that the optimal yearly schedule can keep the voltage profile and feeder and transformer loading within acceptable operating limits while minimizing the system total cost.