Optimization of Large-Scale Commercial Electric Vehicles Fleet Charging Location Schedule Under the Distributed wind Power Supply

The electrification of commercial vehicles is underway which brings practical interest for transportation companies to optimize the charging scheduling of electric vehicles (EVs) to reduce the operating cost. This paper considers the joint optimization problem for the charging location schedule of a commercial EV fleet considering the distributed wind power supply and makes three main contributions. First, a bi-level bipartite graph (BBG) model is first proposed for this problem where the upper level tries to coordinate the wind power among the local wind power generators, and the lower level tries to find out the optimal charging location schedule for all EVs. Second, a bi-level iteration optimization method combining linear programming and Kuhn-Munkres (KM) algorithm is developed for the real-time market operation, and its optimality is proved mathematically. Third, the effectiveness of our method on reducing the operating cost and maintaining a high service rate is demonstrated by a case study compared with other policies.