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作 者:胡晓伟[1,2] 宋帅 邱振洋 王健[1,2] HU Xiaowei;SONG Shuai;QIU Zhenyang;WANG Jian(School of Transportation Science and Engineering,Harbin Institute of Technology,Harbin 150090,China;Heilongjiang Key Laboratory of Intelligent Transportation Management and Technology,Harbin Institute of Technology,Harbin 150090,China)
机构地区:[1]哈尔滨工业大学交通科学与工程学院,哈尔滨150090 [2]哈尔滨工业大学黑龙江省智能交通管理与技术重点实验室,哈尔滨150090
出 处:《交通运输系统工程与信息》2024年第2期281-292,共12页Journal of Transportation Systems Engineering and Information Technology
基 金:国家自然科学基金(52272332);黑龙江省自然科学基金(YQ2021E031);中央高校基本科研业务费专项资金(HIT.OCEF.2022026)。
摘 要:寒区低温环境导致电动公交动力电池容量衰减,充电设施服务范围及规划数量受到影响,给电动公交充电站选址及定容规划带来挑战。为提高电动公交充电站的低温适应性,提出针对寒区电动公交充电站的选址算法及定容模型。首先,在选址规划中,构建充电站渐进覆盖服务半径,利用改进近邻传播聚类算法确定充电站选址点,基于算法聚类中心构建充电站Voronoi图划分充电集群。其次,在定容规划中,构建动力电池低温容量衰减模型,确定寒区电动公交的充电需求;基于容量有限的截尾排队论模型建立充电站有效服务强度、拒绝服务率及充电满意度等约束;引入成本权衡系数,以规划年限内全社会成本最小为优化目标,建立寒区充电站定容规划模型,并设计遗传算法进行求解。最后,以哈尔滨市市区电动公交充电站选址定容规划为例进行分析,算例结果得到9个充电站选址点及其充电集群,以及各充电站的充电机配置数量和各项成本。针对环境温度和成本权衡系数进行灵敏度分析,结果表明:寒区低温环境对充电站的充电机配置数量和各项成本有显著影响,合理权衡充电站和电动公交两者利益有助于提高充电服务满意度,降低全社会成本。Low-temperature environments in cold regions can lead to a decrease in the travel ranges of electric buses(EB),which affects the service area and planning of charging facilities.In order to improve the low-temperature adaptability of EB charging stations in cold regions,a location algorithm and capacity planning model for EB charging stations are proposed.Firstly,in the charging station location problem,the gradual coverage service radius of the charging station was constructed and an improved affinity propagation(AP)clustering algorithm was used to determine the charging station location.Based on the algorithm clustering centers,a Voronoi diagram of the charging stations was constructed to divide the charging clusters.In the capacity planning problem,a low-temperature capacity attenuation model for power batteries was constructed to determine the charging demand for EBs in cold regions.Based on the truncated queue theory model with limited capacity,the constraints associated with effective service intensity,denial of service rate,and charging satisfaction of charging stations were formulated.By introducing cost balancing coefficients,a charging station capacity planning model in cold regions was established to minimize the whole social cost within the planning period.A genetic algorithm(GA)was designed for the solution.Finally,the Harbin urban area is taken as an example to conduct the numerical study.The results obtain nine locations with charging clusters for charging stations as well as the number of charging facilities and the costs for each charging station.Based on the sensitivity analysis of environmental temperature and the cost balancing coefficients,the results show that the low-temperature environment in cold regions has a significant impact on the number of chargers and various costs of charging stations.Reasonably balancing the interests of charging stations and EBs can improve the satisfaction of charging service and reduce overall social costs.
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