Optimization Of Metro Train Timetable For Energy Saving

The subway system has the advantages of large capacity and low energy intensity under unit transportation workload.With the increase of running mileage in major cities in recent years,the total energy consumption in subway system is also growing rapidly.The main form of subway system energy consumption is electricity.For example,annual operating power consumption of subway system has been more than 1 billion kWh in the metropolis like Beijing,Shanghai,of which the energy consumption of train operation accounted for more than 50%in general.Statistics indicate that the energy consumption of train operation with the same track profiles varies with different timetables.Optimizing train timetable is of great importance for energy saving of the subway system without deteriorating the safety and punctuality of train operations.This study first develops an initial train timetabling aiming at reduce daily train travel mileage,by matching the service provision to demand.Then,a scheduling model on train timetable is proposed to find the optimal inter-station run-time,train headway and utilization rates of tractive and braking force for energy saving,taking into account energy-efficient train control,the constraints such as train speed limit,the limit capacity of the power supply system and service level.Genetic algorithm is applied to attain solutions of the proposed model.The main contents of this study include the following aspects:1.Train travel mileage has a great influence on the operation energy consumption.To this end,this thesis puts forward a method of timetable scheduling considering the matching of the capacity of transport supply and passenger demand.Train timetable is compiled by dividing the operating time into a series of periods and then calculating train headways within each period as well as the transition periods.Comparing with the timetable adopted in practice,the scheduled timetable reduced the total traveling mileage by 9%while the service provision satisfies the passenger demand,which contributes to reduce the train operation energy consumption of the subway system.2.The train control strategy also has a great influence on the train operation energy consumption.The existing studies suggest that train energy-saving operation consists of four phases:traction,cruising,coasting and braking.However,during the section with long steep downgrade,braking control may be applied in the cruising phase.However,braking will lead to energy loss,which is unfavorable for energy saving.To this end,this thesis proposes an energy-efficient train control model which can avoid braking as far as possible when in cruising phase,and genetic algorithm is adopted to solve the proposed model.In comparison with the traditional method,the proposed approach is able to save 11%and 7.9%of energy consumption with constant speed limit and variable speed limits,respectively.3.Based on the given number of train service in each period,this thesis developed an energy-saving timetable optimization model with consideration of energy-efficient train control.By optimizing the headway,inter-station run-time and maximum allowable utilization coefficient of traction and braking force,the model aims to reduce the energy consumption of train traction and makes better utilization of regenerative energy.As a result,the energy consumption of train movement is minimized and the instantaneous peak power of electrical supply system is reduced.Genetic algorithm is adopted to solve the proposed model.Numerical test reveals that,optimizing the maximum allowed coefficient of the traction and braking force is able to extend the overlapping time of motoring and braking trains within the same power supply interval.As a result,the energy consumption of train operation is reduced by 3.81%.Case studies indicate that the proposed approach facilitate to save more than 7%of the energy consumption of train movement as well as ensure the limitation of the instantaneous peak power of electrical supply system.