南方电网技术2025，Vol.19Issue(2)：57-67,11.DOI:10.13648/j.cnki.issn1674-0629.2025.02.007
考虑调度可行性的电动出租车时空双层充电优化
Spatiotemporal Bi-Level Charging Optimization of Electric Taxi Considering Scheduling Feasibility
摘要
Abstract
With the continuous expansion of electric taxi fleets in various cities,their large-scale and unregulated charging behaviors will not only aggravate the fluctuation of the power grid load curve,threaten the stability and security of the power grid,but also reduce the equipment utilization rates of remote charging stations.Therefore,an electric taxi orderly charging guidance system is established based on the information cooperation of"vehicle-station-network",which proposes a spatiotemporal bi-level charging optimization of electric taxi considering the feasibility of user participation in scheduling.In the temporal level model,a multi-objective optimization model is established based on minimizing the peak-valley difference,standard deviation and the charging cost of users.This model optimizes the charging time load of electric taxis in advance and reserves charging time windows for each user.In the spatial level model,real-time scheduling of the spatial load of electric taxi charging is carried out with the objectives of balanc-ing the average utilization rate of each charging station and minimizing users' charging time cost,in order to allocate the optimal charging station for each user.Finally,the effectiveness of the proposed optimization strategy is verified through a case simulation,demonstrating its ability to balance the interests of power distribution network,charging station operators and electric taxi users.关键词
电动出租车/充电引导/调度可行性/时空负荷调度/多目标优化Key words
electric taxi/charging guidance/scheduling feasibility/spatiotemporal load scheduling/multi-objective optimization分类
交通运输引用本文复制引用
田晟,李乐洋..考虑调度可行性的电动出租车时空双层充电优化[J].南方电网技术,2025,19(2):57-67,11.基金项目
国家重点研发计划资助项目(2021年国家科技部"新能源汽车"重点专项"(2021YFB2501104)) （2021年国家科技部"新能源汽车"重点专项"(2021YFB2501104）
广东省自然科学基金资助项目(2021A1515011587,2020A1515010382). Supported by the National Key Research and Development Program(2021YFB2501104) （2021A1515011587,2020A1515010382）
the Natural Science Foundation of Guangdong Province(2021A1515011587,2020A15150 10382). （2021A1515011587,2020A15150 10382）
