摘要
电动汽车因排放的温室气体极少,在力图实现绿色交通的今天具有巨大应用潜力。然而,其充电时间长及充电拥挤等问题,极大地影响了电动汽车用户的出行体验。为优化电动汽车充电服务,充电站选择方案(于何处充电)及充电调度策略(于何时充电)成为了解决城市电动汽车充电问题的关键。面向以未来6G为承载的交通物联网应用,提出了一项考虑充电优先级(Charging Priority,CP)的抢占式充电调度策略。该策略以经典排队论为基础,允许充电优先级(由充电需求和剩余停车时长计算)较高的电动汽车以抢占的方式充电,最大限度优化充电时序。在CP充电调度策略的基础上,该方案进一步结合预约信息对充电站选择方案进行优化,为电动汽车选择充电行程时长(含一次充电行为)最短的充电站。其中,该方案要求电动汽车上传其充电预约信息以准确预测充电站的服务拥塞状态,从而高效地调配充电资源。方案的结果验证基于赫尔辛基城市交通场景,对充电网络进行了仿真模拟。结果表明,所提优化充电管理方案(CP充电调度策略及基于预约的充电站选择方案)能有效缩短电动汽车的平均充电行程时长,并在有限停车时长内为更多电动汽车提供完整的充电服务。
The introduction of electric vehicles(EVs)alleviates greenhouse gases emission.Its application has huge potential in the attempt to achieve green transportation today.However,the long charging time and charging congestion greatly affect the travel experience of EVs.To optimize EV charging,the charging station(CS)selection scheme(where to charge)and the charging scheduling strategy(when to charge)become the core of solving the problem of urban EV charging.In this paper,the preemptive charging scheduling strategy considering the charging priority(CP)is proposed.This strategy allows the preemptive charging of EVs with high urgency of charging(calculated from the charging demand and the remaining parking duration).Based on the CP charging scheduling strategy,a CS selection scheme that further combines reservation information is optimized.This scheme selects the CS with the shortest charging travel time(including one-time charging process)for EVs.Meanwhile,EVs are required to report their charging reservation information to accurately predict the congestion status of CSs,so as to efficiently allocate charging resources.The charging network is simulated through the urban traffic scene of Helsinki.The results show that the charging management scheme,CP scheduling strategy and reservation-based CS selection scheme proposed in this paper,can effectively shorten the average charging travel time of EVs and provide fully charging service for more EVs within a limited parking duration.
作者
张捷
唐强
刘朔晗
曹越
赵维
刘韬
谢士明
ZHANG Jie;TANG Qiang;LIU Shuo-han;CAO Yue;ZHAO Wei;LIU Tao;XIE Shi-ming(School of Cyber Science and Engineering,Wuhan University,Wuhan 430072,China;SG Star Energy(Sichuan)Technology Co.Ltd,Chengdu 610000,China)
出处
《计算机科学》
CSCD
北大核心
2022年第6期55-65,共11页
Computer Science
基金
湖北省国际科技合作计划项目(2021EHB012)。
关键词
电动汽车
电动汽车充电
充电调度
充电站选择
充电优化
Electric vehicle
Electric vehicle charging
Charging scheduling
Charging station selection
Charging optimization