摘要
5G技术发展使用户能够通过车联网和V2X(vehicle to everything)技术快速获取周围物理环境的信息。车辆、电网运营商等也能根据路网信息进行更好的资源分配与调度,从而促进现代化智慧交通、智慧城市等发展战略的实现。考虑到现代化城市不同区域承担着不同功能,在车辆停靠、电网容量、土地约束、成本价格等方面具有不同特征,为优化充电站部署,建立了V2X辅助下城市区域特征差异充电站模型。考虑实际情况,引入M/M/S/K排队模型和用户充电决策模型对用户行为进行刻画。进一步建立优化模型,在用地面积、电网容量以及服务需求的约束下,通过充电站点选择和充电桩部署,最大化运营商收益。为求解该问题,设计了一种基于站点容量和用户充电行为的充电站网络规划方法,首先求解给定站点的最优充电桩部署数目,然后对候选站点进行筛选聚合实现充电站网络优化。仿真验证了所提优化方法的有效性,所提充电站网络优化方法能够有效提高站点内充电桩利用率,减少运营商建设成本,提升运营商整体盈利。
With the development of the 5G technology,much progress has been made in vehicle to everything(V2X)and the Internet of Vehicle.Mobile users could quickly obtain relevant physical facility information,and facility operators could better allocate scheduling resources based on the road network information.In the city planning,different area has different functions.From the view of electrical vehicle,two area will own the same characteristic in the arriving distribution if they belong to the same function.In addition,the grid capacity,land restriction,cost and price will have similar patterns.Based on the area characteristics and the V2X assistance,the station network model was proposed in this paper.Concerning about the aim of commercial charging network,we optimize the charging station network within a giving area with the objective of retained profits and the constraints of grid capacity and land.A charging network strategy which is on the basis of station parameter and parking distribution is devised.The strategy includes two parts,the first part calculates the optimal charger number in the given station;the second part removes and aggregates some candidate station to optimal the charging network station.The M/M/S/K queue model and user charging intention curve are introduced to picture the user behavior in charging station.The impacts of critical parameters of charging network on the system performance is provided.
作者
熊轲
吴思宇
郑海娜
王蕊
张煜
XIONG Ke;WU Siyu;ZHENG Haina;WANG Rui;ZHANG Yu(School of Computer and Information Technology,Beijing Jiaotong University,Beijing 100044,China;School of Vehicle and Mobility,Tsinghua University,Beijing 100084,China;Liaoning Radio and Television University,Shenyang 110034,China;State Grid Energy Research Institute Co.,Ltd.,Beijing 102209,China)
出处
《中国电力》
CSCD
北大核心
2021年第3期89-98,共10页
Electric Power
基金
国家自然科学基金资助项目(基于信息年龄的射频能量采集无线网络设计理论与方法,62071033)
中央高校基本科研业务专项资金资助项目(高速列车服役性能保持和提升关键技术研究,2020JBZD010)
国网能源研究院有限公司科技项目(SGNY202009014)。