需求不确定的电动汽车换电站选址鲁棒模型

Research on robust battery swap stations location model of electric vehicles

在电动汽车换电站选址问题中,用户充电需求是重要的输入参数,而需求受到技术发展、电动汽车保有量、国家相关政策等因素的影响,通常较难准确预测。假设交通网络上用户需求是不确定的,利用基约束鲁棒优化方法提出基于用户路径流量不确定的换电站选址鲁棒模型,并将鲁棒模型转换为等价的线性规划。最后应用Nguyen-Dupius网络作为数值算例进行分析,结果表明当解的鲁棒水平较低时,通过适当增加选址成本,可以较大程度地提高解的鲁棒性。同时对模型的重要参数作灵敏性分析,随着鲁棒水平的提高,换电站选址成本对路径流量的波动越来越敏感,续航里程的改变对换电站选址策略影响较大。

The users’charging demand is important input parameters in the battery swap stations location problem of electric vehicles.The demand is influenced by technological development,the number of electric vehicles and the relevant policies,and it is often difficult to predict accurately.This paper examined the robust battery swap stations location problem with flow uncertainty.Supposing the users’demand on the traffic network path was uncertain,it employed the cardinality constrained robust approach to formulate the robust battery swap stations location model and transformed model to a linear optimization problem.It used the Nguyen-Dupius network as a numerical example.The results show that when the robust level of the solution is low,the robust level can be improved greatly by appropriately increasing the location cost.In addition,the sensitivity analysis is conducted for important parameters of the model.The results show that,the location cost is increasingly sensitive to the fluctuation of path flow with the improvement of robust level.The change of driving range has a great impact on the location strategy.