摘要
基于ETC门架数据,提出了一种充电站选址与容量规划的两阶段优化模型,服务于区域交通走廊的高速公路。模型综合考虑现有服务区利用、充电需求的时空变化及排队时间,以提供高效的电动汽车充电服务并优化布局和容量配置。第一阶段采用K-means聚类算法构建选址优化模型,实现现有服务区的最大化利用。第二阶段引入排队论,通过贪心算法优化容量配置,同时设置排队时间约束以提升服务效率。以济青走廊高速公路网为案例验证,结果表明该方法能够有效满足充电需求,降低建设成本和用户等待时间。方案一(全新选址)在充电站和充电桩数量最少的情况下,建设成本较方案二(现有站点优先)减少15.70%;方案二在减少排队时间方面表现最佳,排队时间比方案一减少17.65%。方案三(现有站点最大化利用)虽成本较低,但用户排队时间相对最长。
Based on ETC gantry data,a two-stage optimization model for charging station siting and capacity planning is proposed,serving the expressways along the regional transportation corridors.The model comprehensively considers the utilization of existing service areas,the spatiotemporal variation of charging demand,and the impact of queuing time factors,so as to provide efficient charging services for long-distance electric vehicle travel while optimizing the layout and capacity of charging stations to achieve cost savings.In the first stage,K-means clustering algorithm is used to build a location optimization model to maximize the utilization of the existing service area.In the second stage,queuing theory is introduced,capacity allocation is optimized by greedy algorithm,and queuing time constraints are set to improve service efficiency.The Jinan-Qingdao Corridor expressway network is taken as verification background,and the results indicate that this method not only meets the charging demands of long-distance electric vehicles but also effectively reduces construction costs and user waiting times.Scheme One(new siting)minimizes both the number of charging stations and charging piles,leading to a construction cost reduction of 15.70%compared to Scheme Two(prioritizing existing sites).Scheme Two demonstrates the best performance in reducing queuing times,with a 17.65%decrease in user waiting times compared to Scheme One.Although Scheme Three(maximizing the utilization of existing sites)incurs lower costs,it results in the longest queuing times for users.
作者
何世玉
郭甲
王达
李婷
贾健民
HE Shi-yu;GUO Jia;WANG Da;LI Ting;JIA Jian-min(School of Traffic Engineering,Shandong Jianzhu University,Jinan 25010l,China)
出处
《公路》
北大核心
2025年第8期218-228,共11页
Highway
基金
国家自然科学基金项目,项目编号41901396
山东省高等学校青创科技支持计划项目资助,项目编号2022KJ203。
关键词
交通规划
充电站选址
高速公路网络
K-MEANS聚类
排队论
容量规划
数据驱动
transportation planning
charging station siting
expressway network
K-means clustering
queuing theory
capacity planning
data-driven
