基于遗传优化算法的城市轨道交通多列车运行节能计算方法
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摘要
针对地铁列车多列车节能问题,提出一种基于遗传优化算法的多列车运行节能计算方法。分析多列车运行过程中制动能量传递使用过程;建立以能耗最少、旅行时间准点为目标,以全天列车运行对数、高/低峰行车对数为约束的多列车运行节能模型;采用遗传算法获得各站最优的停站时间和发车间隔序列,并计算出全线能耗、列车能耗和线路损耗。同时,以我国某地铁线路4个区间组成的短线进行多列车节能仿真,优化得到各站的停站时间和发车间隔时间。
Aiming at the energy saving problems of multi-vehicle metro train,a calculation method of multi-vehicle operation energy saving is presented based on genetic algorithm.Firstly,the process of braking energy transfer in multi-train operation is analyzed; secondly,the least energy consumption and travel time are taken as the target,with numbers of the allday train and the high/low peak traffic as the constraint,a multi-vehicle energy saving model is established; thirdly,the genetic algorithm is used to obtain the optimal stopping time and starting interval,the total energy consumption,train energy consumption and line loss are calculated. Finally,the multivehicle energy saving is simulated by using the short line consisting of four sections on a Line in Beijing,the stopping time and the starting interval at each station are optimized.
Aiming at the energy saving problems of multi-vehicle metro train,a calculation method of multi-vehicle operation energy saving is presented based on genetic algorithm.Firstly,the process of braking energy transfer in multi-train operation is analyzed; secondly,the least energy consumption and travel time are taken as the target,with numbers of the allday train and the high/low peak traffic as the constraint,a multi-vehicle energy saving model is established; thirdly,the genetic algorithm is used to obtain the optimal stopping time and starting interval,the total energy consumption,train energy consumption and line loss are calculated. Finally,the multivehicle energy saving is simulated by using the short line consisting of four sections on a Line in Beijing,the stopping time and the starting interval at each station are optimized.
引文
[1]王勇博.采用遗传算法优化地铁多区间速度曲线和停站时间实现牵引节能的仿真研究[D].南京:南京理工大学,2013.
[2]李坤妃.多列车协同控制节能优化方法的研究[D].北京:北京交通大学,2014.
[3]刘宝林.地铁列车能耗分析[J].电力机车与城轨车辆,2007(4):65.
[4]赵乐.基于再生制动的地铁列车时刻表优化模型与算法研究[D].北京:北京交通大学,2014.
[5]王德春,李克平,李想.多目标列车节能调度模型及模糊优化算法[J].科学技术与工程,2012,12:2869.
[6]赵莹莹.考虑再生制动能量利用的城轨交通多列车节能运行研究[D].北京:北京交通大学,2015.
[7]伍勇,刘思宁.基于节能和面向旅客服务的列车编组方案研究[J].城市轨道交通研究,2004(6):27.
[8]薛艳冰,马大炜,王烈.列车牵引能耗计算方法[J].中国铁道科学,2007(3):84.
[9] SIDELNIKOV V. Computation of optimal controls of a railroad locomotive[J]. Proceedings of State Railw ay Research Institute,1965(2):52.
[10] MILROY I P. Aspects of automatic train control[D]. Leicestershire:Loughborough University,1980.
[11]冯佳.考虑节能目标的城市轨道交通列车运行行为优化研究[D].北京:北京交通大学,2014.
[2]李坤妃.多列车协同控制节能优化方法的研究[D].北京:北京交通大学,2014.
[3]刘宝林.地铁列车能耗分析[J].电力机车与城轨车辆,2007(4):65.
[4]赵乐.基于再生制动的地铁列车时刻表优化模型与算法研究[D].北京:北京交通大学,2014.
[5]王德春,李克平,李想.多目标列车节能调度模型及模糊优化算法[J].科学技术与工程,2012,12:2869.
[6]赵莹莹.考虑再生制动能量利用的城轨交通多列车节能运行研究[D].北京:北京交通大学,2015.
[7]伍勇,刘思宁.基于节能和面向旅客服务的列车编组方案研究[J].城市轨道交通研究,2004(6):27.
[8]薛艳冰,马大炜,王烈.列车牵引能耗计算方法[J].中国铁道科学,2007(3):84.
[9] SIDELNIKOV V. Computation of optimal controls of a railroad locomotive[J]. Proceedings of State Railw ay Research Institute,1965(2):52.
[10] MILROY I P. Aspects of automatic train control[D]. Leicestershire:Loughborough University,1980.
[11]冯佳.考虑节能目标的城市轨道交通列车运行行为优化研究[D].北京:北京交通大学,2014.