集中型充电站高维多目标优化调度模型研究

Research on High-dimensional Multi-objective Optimization Scheduling Model of Centralized Charging Station

为了增强电动汽车电池调度的合理性,在集中型充电站换电模式下,结合集中型充电站、配送站和换电站,分析电池的联合调度问题。首先,考虑充电成本、充电负荷、运输成本和时间成本,提出了一种集中型充电站换电模式高维多目标优化调度模型。然后,采用非支配排序遗传算法-Ⅲ(non-dominated sorting genetic algorithm-Ⅲ,NSGA-Ⅲ)对该调度模型进行优化。同时,根据实际调度问题,对NSGA-Ⅲ的交叉和变异方式进行改进。最后,通过仿真实验测试算法的性能。实验结果表明,与其他高维多目标优化算法相比,该算法在换电模式下的优化性能具有明显的优势。

In order to enhance the rationality of battery scheduling for electric vehicles,the joint scheduling problem of batteries is analyzed by combining centralized charging stations,distribution stations and battery swapping stations under the battery swapping mode.Firstly,considering charging cost,charging load,transportation cost and time cost,a high-dimensional multi-objective optimization scheduling model of centralized charging stations is proposed.Then,non-dominated sorting genetic algorithm-III(NSGA-III)is used to optimize the scheduling model.At the same time,according to the actual scheduling problem,the cross and mutation modes of NSGA-III is improved.Finally,the performance of the algorithm is tested by simulation experiments.The experimental results show that compared with other multi-objective optimization algorithms,the proposed algorithm has obvious advantages in the optimization performance under the battery swapping mode.