考虑储能装置的普速铁路列车节能运行图优化OA
Energy-efficient train timetable optimization for conventional railways considering energy storage systems
针对普速铁路系统再生制动能量利用率低和能源浪费严重等问题,以提升能源利用效率为核心目标,建立安装储能装置的节能运行图优化系统理论,探索再生制动能即时利用与延时利用的协同优化路径.基于普速铁路列车运行特性,以列车首站发车间隔和停站时间为决策变量,同时考虑列车追踪间隔安全阈值、越行情况动态调整规则及储能装置容量限制等多维度约束条件,建立以再生制动能总利用量最大化为目标函数的优化模型.设计基于模拟退火的求解算法并以兰新线兰州至武威段为案例进行验证,构建包含15个车站、白天某时段共43列客货列车的场景测试.结果表明,系统总再生制动能利用量达到4 134.38 kW∙h,再生制动能利用率达到56.28%.探讨发车间隔、停站时间、储能装置容量、列车开行对数及可以产生再生制动能的机车比例变化对节能率的影响,结果显示,在高密度行车与高再生能机车比例(约58%)条件下,协同优化运行图参数与储能装置容量,节能率最高可达86.33%.通过净现值方法进行经济效益分析,在10 a评估期内,储能装置投资的净现值始终保持正值,充分证明了储能装置的安装不仅能够有效提高能源利用效率,同时也能带来可观的经济效益.
To address the low utilization of regenerative braking energy and significant energy waste in conventional railway systems,this study aims to improve energy utilization efficiency by developing an energy-efficient timetable optimization framework incorporating energy storage systems.The proposed approach enables coordinated utilization of regenerative braking energy through both immediate and delayed mechanisms.Based on operational characteristics of conventional railways,an optimization model is formulated with the objective of maximizing total regenerative braking energy utilization.The decision variables include train departure intervals at the origin station and dwell times,subject to multiple constraints such as safety headway requirements,dynamic overtaking rules,and energy storage capacity limits.A simulated annealing-based solution algorithm is developed and validated through a case study of the Lanzhou-Wuwei section of the Lanxin railway.A test scenario involving 15 stations and 43 passenger and freight trains during a certain daytime period shows that the total regenerative energy utilization reaches 4 134.38 kWh,corresponding to a utilization rate of 56.28%.Sensitivity analysis is conducted to examine the effects of departure intervals,dwell times,storage capacity,train frequency,and the proportion of regenerative braking-capable locomotives on energy-saving performance.Results indicate that under high-density operation of regenerative braking-capable locomotives(approximately 58%),coordinated optimization of timetable parameters and storage capacity can achieve a maximum energy-saving rate of 86.33%.An economic evaluation based on net present value(NPV)method shows consistently positive returns on energy storage investment over a 10-year horizon.These findings demonstrate that integrating energy storage systems into timetable optimization not only enhances energy utilization efficiency but also yields significant economic benefits.
冀璇;张玉召;高珅盈泽;崔朝晖
兰州交通大学交通运输学院,甘肃 兰州 730070兰州交通大学交通运输学院,甘肃 兰州 730070||高原铁路运输智慧管控铁路行业重点实验室,甘肃 兰州 730070兰州交通大学交通运输学院,甘肃 兰州 730070中国国家铁路集团有限公司运输调度指挥中心,北京 100844
交通工程
铁路运输节能运行图储能装置普速铁路再生制动能交通规划模拟退火算法
railway transportationenergy-efficient train timetableenergy storage systemsconventional railwayregenerative braking energytraffic schedulingsimulated annealing algorithm
《深圳大学学报(理工版)》 2026 (3)
316-326,11
National Natural Science Foundation of China(71761025)Science and Technology Research and Development Program of China State Railway Group Co.Ltd.(P2024X003) 国家自然科学基金资助项目(71761025)国家铁路集团有限公司科技研究开发计划资助项目(P2024X003)
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