基于排队论及遗传模拟退火算法的充电站站址优化

Site optimization of charging stations based on queuing theory and genetic-simulated annealing algorithm

针对多目标、非线性的电动汽车充电站站址规划问题,提出考虑满意度和网损影响的选址方法。在研究充电站排队系统的特点的基础上,根据排队论构建了充电站排队模型。考虑电动汽车用户和充电站双方的利益,提出满意度函数的概念,并以此确定充电站数量。以接入电动汽车后系统网损最小为目标函数,构建充电站选址优化模型,采用遗传模拟退火算法求解模型。算例仿真结果表明,通过合理规划充电站,可以提高充电站利用率,减少顾客逗留时间并且使充电负荷对系统网损的影响最小,验证了模型的实用性和合理性,为充电站选址提供参考。

In allusion to the multi-target and non-linear problem of selecting location of electric vehicle charging station,a location-select method considering the satisfaction and network loss was proposed.On the basis of analyzing the characteristics of charging station queuing system,a charging station queuing model which was based on queuing theory was built.Considering the interests of both electric vehicle users and charging stations,put forward the concept of satisfaction function,and according to the satisfaction function,the number of charging stations was determined.Taking the minimal network loss with electric vehicles accessing to power network as objective function,then the optimization model of selecting the location of charging station was established.The genetic-simulated annealing algorithm was used to solve the model.Case study results show that,rational planning of charging stations can improve the utilization of the charging station and reduce customer’s stay time,what’s more,the network loss is minimal,so the practicality and rationality of the model are verified,and it can provide a reference for selecting location of electric vehicle charging station.