具有随机充电需求的混合动态网络平衡模型  

Mixed network equilibrium model with stochastic charging demand

作　　者：闫云娟 查伟雄 石俊刚 李剑 YAN Yun-juan;ZHA Wei-xiong;SHI Jun-gang;LI Jian(College of Mechatronics&Vehicle Engineering,East China Jiaotong University,Nanchang 330013,China;Institute of Transportation and Economics,East China Jiaotong University,Nanchang 330013,China)

机构地区：[1]华东交通大学机电与车辆工程学院,南昌330013 [2]华东交通大学交通运输与物流学院,南昌330013

出　　处：《吉林大学学报（工学版）》2022年第1期136-143,共8页Journal of Jilin University:Engineering and Technology Edition

基　　金：国家自然科学基金项目(52065021);国家自然科学青年科学基金项目(71801093,62002117);江西省教育厅科学技术项目(190306).

摘　　要：考虑电动汽车用户在途随机充电需求,基于随机充电行为及充电排队仿真构建了混合用户平衡模型。在电动汽车不同初始电量状态及市场占有率下,预测了网络平衡交通流和可能充电需求流的变化趋势。利用Frank-Wolfe算法和多标号算法,以Nguyen-Dupius网络为例,设计了电动汽车充电排队仿真的平衡交通流预测模型,本文研究结果可为交通管理者提供科学参考。With the increase of electric vehicle mileage and the increase of public charging facilities,it is inevitable that electric vehicles choose to charge in their commute more and more widely.Considering the stochastic charging demand of electric vehicle users,a mixed user equilibrium model is constructed based on the stochastic charging behavior and charging queuing simulation.Under different initial state of charge and market share of electric vehicles,the trend of equilibrium traffic flow and potential charging demand flow is predicted.Based on stochastic charging behavior and charging queuing simulation,a mixed user equilibrium model is constructed.The model is based on Frank⁃Wolfe algorithm and multi-label algorithm.Taking Nguyen-Dupius network as an example,this paper designs an equilibrium traffic flow prediction model integrating electric vehicle charging queuing simulation,which provides a scientific management scheme for traffic managers.

关 键 词：交通运输规划与管理 混合用户平衡模型 Frank⁃wolfe算法 排队逗留时间 随机充电概率 

分 类 号：U491[交通运输工程—交通运输规划与管理]