Research On Train Timetable Optimization For Energy-Saving Operations In Urban Rail Transit

Due to its high capacity,safety,efficiency,punctuality and other advantages,the urban rail transit system has received rapid development around the world.With the same passenger capacity,energy consumption of the urban rail transit is equivalent to about one third of the bus or one ninth of the car.Therefore,the urban rail transit is considered as the most energy-efficient transportation mode.Despite all this,the total energy consumption of the urban rail transit is huge and sharply increased along with its rapid development.The large energy consumption gives rise to high costs and emissions,which brings pressure to both urban rail operation companies and energy supply departments.Therefore,reducing the energy consumption of the urban rail transit is an urgent problem to be solved and highly contributes to the energy conservation and emission reduction of the whole country.The main purpose of this paper is to optimize the timetable for reducing the energy consumption of urban rail trains,such that the energy consumption of the urban rail transit systems can also be reduced.From two perspectives of improving the utilization of regenerative energy and directly reducing the tractive energy consumption,this paper studies the model formulation and solution algorithm of timetable optimization.In detail,this paper does the following research works:1.The paper firstly introduces the distribution of energy consumption in urban rail transit systems.Then the tractive energy consumption and regenerative braking energy which are closely relative to train operations are analyzed.In details,we introduce the constitution of power supply system for the urban rail transit,describe the tractive energy consumption process during train operations,provide the principle of regenerative braking technique,and summarize the handling methods of regenerative braking energy.Finally,it is concluded that timetable optimization is an efficient way to directly reduce the tractive energy consumption and improve the utilization of regenerative energy.2.The paper proposes a timetable optimization method to improve the overlapping time between accelerating and braking processes of adjacent trains within the same electrical section,such that the regenerative energy from braking trains can be immediately utilized by accelerating trains to reduce their tractive energy consumption.We formulate an integer programming model and design a genetic algorithm to find the optimal solution.According to the operation data from the Beijing Metro Yizhuang Line,the results of numerical examples illustrate that the proposed method can significantly improve the overlapping time at both peak hours and off-peak hours.3.Based on the above optimization method,we developed an energy-efficient timetable optimization method using the mechanical energy consumption as the objective function instead of the overlapping time.The main contributions are considering the utilization of regenerative energy among all trains within the same electrical section instead of adjacent trains and keeping the cycle time and the number of trains unchanged in the metro operations.The results of numerical examples illustrate that this developed optimization method can improve the utilization of regenerative energy and reduce the total energy consumption in comparison with the optimization method proposed in point 2.4.Other than studying the utilization of regenerative energy in points 2 and 3,this point studies how to reduce trains' tractive energy consumption directly.According to the uncertainty of train mass at different inter-stations and at different operation periods,we develop an integrated timetable and speed profile optimization method to minimize the total tractive energy consumption.We firstly formulate a two-stage stochastic programming model to determine the timetable and speed profile.Then we design a simulation-based genetic algorithm incorporated with the optimal train control algorithm to obtain the optimal solution.Finally,two numerical examples based on the operation data from the Beijing Metro Yizhuang Line are presented.The results show that the optimal timetable and speed profile can achieve a good energy performance in comparison with the current timetable and speed profile during peak hours,off-peak hours and night hours.