Research On The Energy-efficient Train Operation In Multi-interval For Urban Rail Transit

With the rapid development of the economy in China,more and more attention is being paid on energy reduction as well as the resulting serious environmental problems.In the 13th Five Year Plan of China,energy conservation and emissions reduction have become an important concept for a better development.At the same time,the urban rail transit in China consumes a large amount of energy with its fast development.The train traction energy consumption accounts for more than 40%of the daily energy consumption in urban rail transit.As a result,cutting down the traction energy through various efficient methods can make a great difference to energy reduction.Considering the train operations in multi-intervals,the total energy consumption is related to the traction energy consumption and the utilization of regenerative braking energy among trains,which depends on the train driving strategies and timetable.This paper aims to minimize the total energy consumption of multi-trains by optimizing the driving strategy and timetable.Research on the single train operation is the basis of multi-train operation and research on the driving strategy for a single interval is the basis of multi-interval operation.Based on the driving strategy optimization model,the single train energy-efficient driving strategy optimization method based on Genetic Algorithm(GA)is proposed.And the Particle Swarm Optimization(PSO)is designed to optimize the timetable of multi-trains in this paper:(1)Firstly,with the trip time constraint for a single train,different driving strategy with different trip time and the corresponding energy consumption are obtained by a circularly GA optimization algorithm,from which the fitting relationship between the trip time and energy consumption is found;(2)Then,the timetable which contains operation time,dwell time and headway time of multi-trains is optimized by the PSO algorithm with considering the utilization of regenerative braking energy.In the PSO algorithm,the train driving strategy is obtained with the proposed GA algorithm.The approach in this is illustrated by conducting two case studies from two specific scenarios,i.e.,two train's operation in a single interval but different direction,and two train's operation in multi-interval and the same direction.The simulation verification in this paper is conducted based on the real line data of Beijing Subway Line 7.The results show that the energy reduction of the up train and down train in Dajiaoting is 14.46%by applying the proposed method;And in the second case,the energy of the two trains running from Huagong to Jiulongshan is reduced by 16.24%.The simulation shows that the proposed method has a good energy-efficient performance,which also shows the feasibility and the effectiveness of the proposed method.