Electric vehicle charging station planning with dynamic prediction of elastic charging demand: a hybrid particle swarm optimization algorithm

Abstract This paper is concerned with the electric vehicle (EV) charging station planning problem based on dynamic demand. Considering behavior of EV users, a prediction method demand proposed by analyzing users’ travel law via trip chain approach. In addition, multi-objective planing formulated to achieve three objectives: (1) maximize captured demands; (2) minimize total cost electricity and time consumed for charging; (3) load variance power grid. To solve such problem, novel combining hybrid particle swarm optimization (HPSO) algorithm entropy-based technique order preference similarity ideal solution (ETOPSIS) method. Specifically, HPSO used obtain Pareto solutions, ETOPSIS employed determine optimal scheme. Based method, siting sizing can be planned in an way. Finally, effectiveness verified case study test system composed IEEE 33-node distribution traffic network system.