控制理论与应用2024，Vol.41Issue(8)：1438-1450,13.DOI:10.7641/CTA.2023.20280
车联网中多主体参与的电动汽车预充电路径规划
Electric vehicle pre-charging path planning with multi-agent participation in the internet of vehicles
摘要
Abstract
With the development and popularization of electric vehicles,the coupling between energy network,traffic network and information network have been deepened,and the traditional path planning model based on a single traffic system on the road side can no longer adapt to the demand of electric vehicle charging navigation decision in the road-electric coupling scenario.In this paper,a multi-participant EV pre-charging path planning model based on the interaction of vehicle-road-station-grid system information is established to address this problem,taking into account the energy-side load demand response and traffic-side traffic distribution constraints.Then,based on the comprehensive evaluation of user-side travel cost,distribution network load fluctuation and aggregator's operation benefit,the optimal charging pile and its reservation time in the planning area are solved by using the heuristic A*algorithm.Finally,the effectiveness of the model in short time scale scheduling is verified by combining the road network in a certain area of Changsha city with a random and flexible electric private car as the modeling object.The results show that the proposed model can effectively reduce the user-side costs,promote the safe and stable operation of the grid.Meanwhile,it also can balance the regional differences in the use of charging piles to a certain extent.In a word,this model can realize the comprehensive optimal path planning that integrates the objectives of multiple subjects.关键词
电动汽车/车网互动/路电耦合/路径规划/多主体决策Key words
electric vehicles/vehicle to grid/transportation-energy coupling/path planning/multi-subject decision making引用本文复制引用
刘东奇,谢金焕,王耀南..车联网中多主体参与的电动汽车预充电路径规划[J].控制理论与应用,2024,41(8):1438-1450,13.基金项目
国家自然科学基金项目(51807013,52177068)资助.Supported by the National Natural Science Foundation of China(51807013,52177068). （51807013,52177068）
