基于改进多目标遗传算法的电动汽车换电站选址研究

Research on the Location Planning of Electric Vehicle Battery Swap Stations Based on Improved Multi-Objective Genetic Algorithm

换电模式高效、便捷的补能形式预计成为未来电动汽车充能的主流方式。换电站选址是否合理影响重大,本文以换电站建设成本及用户出行成本最小化、用户覆盖率最大化为目标函数,建立双目标混合整数规划模型,设计改进带精英策略的非支配排序遗传算法,获得帕累托最优解集。通过数值模拟,验证了模型可行性,为电动汽车换电站网络规划提供了依据。

The swap mode,with its efficient and convenient form battery exchange,will become the mainstream way of supplement energy for the future,and whether the site selection of the battery swap station is reasonable has a significant impact on investment decisions and transportation travel.This paper based on minimizing construction cost of battery swap stations and the cost of user travel,as well as maximizing user coverage as the objective function,designs an improved non-dominated sorting genetic algorithm(NSGA-II)with elite strategy to solve the dual objective mixed integer programming model and obtain the pareto optimal solution set.Taking numerical simulation as an example,verifies the feasibility of model construction,providing a methodological basis for the planning of the electric vehicle battery swap station network.