摘要
城轨运营能耗是城轨列车运营主要成本之一,随着能源价格的日益增长、城轨开行密度和运营里程的持续增大,能耗成本在城轨列车运营成本中的份额越来越高。优化列车时刻表、实现列车节能运行对于降低整个城市轨道交通运营成本具有重要的现实意义。为了避免因过度追求时刻表的节能效果,而导致满足时刻表车底接续方案的车底使用成本以及列车总运行成本增加,基于给定的初始列车时刻表与各区间候选列车牵引策略集,研究考虑列车运行能耗和车底运用的城轨时刻表优化问题。首先,以列车运行节能与车底运用时间总成本最小化为优化目标,考虑列车车站到发时刻调整量、列车旅行总时长、车底衔接时长以及安全时间间隔等约束,构建考虑列车运行节能和车底运用的城轨时刻表优化模型,实现列车区间节能运行策略、车站到发时刻、车底衔接方案的协同优化。其次,在构造车底衔接计划生成策略、不可行解修复策略的基础上,设计一种高效粒子群算法对模型进行求解。最后,以广州地铁9号线为例的算例分析表明,通过所建协同优化方法获得的节能时刻表和车底衔接方案能使列车能耗成本与车底成本之和降低3.81%。
Energy consumption is one of the main costs of urban rail operation. With the increase in energy price,urban rail operation density, and mileage, the energy consumption cost accounts for an increasing share of urban rail operation costs. Optimizing train schedules and realizing energy saving is of great practical significance to reduce the operation cost of urban rail transit. The order to avoid blindly pursuing the energy-saving effect of the schedule leads to the increase in the cost of the use of the rolling stock meeting the train circulation plan, which leads to the increase in the total running cost of the train. This paper proposed an urban rail schedule optimization model considering energy saving and a train circulation plan based on the initial train schedule and candidate traction strategies. First, the optimization objective was set to minimize the total cost of train traction energy consumption and rolling stock operation time, and constraints such as the adjustment of trains’ arrival and departure times, all trains’ travel times, the rolling stock connection time, and the safety headway were considered. An urban rail schedule optimization model considering energy saving and a train circulation plan was constructed to realize the coordinated optimization of the trains’ traction strategies in each rail section, the trains’ arrival and departure times at each station, and the connection plan of the rolling stocks. Second, an efficient particle swarm optimization(PSO) algorithm was designed to solve the model based on constructing the generation strategy of the train circulation plan and the repair strategy of an unfeasible solution. Finally, several numerical experiments based on Guangzhou Metro Line 9 of China illustrate that the collaborative optimization method can reduce the total operation cost of trains by 3.81% as compared to the initial train schedule.
作者
周文梁
黄裕
邓连波
ZHOU Wenliang;HUANG Yu;DENG Lianbo(School of Traffic and Transportation Engineering,Central South University,Changsha 410075,China)
出处
《铁道科学与工程学报》
EI
CAS
CSCD
北大核心
2023年第2期473-482,共10页
Journal of Railway Science and Engineering
基金
国家自然科学基金资助项目(71871226,U1934216)
中国国家铁路集团有限公司系统性重大课题(P2021X008)。
关键词
城市轨道交通
节能时刻表优化
车底衔接计划
列车运行策略
粒子群算法
urban rail transit
energy-efficient train scheduling
train circulation planning
train tracking strategy
particle swarm algorithm
