Study On The Timetable Synchronization And Energy Saving Optimization Of First And Last Trains For Urban Rail Transits

With the advantage of green environment protection,convenient and comfortable,large passenger capacity and low energy consumption per capita,rail transit is an important carrier for urban residents to commute.At present,the rail transit systems of many cities are gradually shifting from independent operation of a single line to networked operation of multiple lines,which puts forward higher requirements for the operation coordination and organization between lines.Improving the service level of rail transit can increase the proportion of residents using rail transit to travel,thereby indirectly achieving energy conservation and emission reduction in the urban comprehensive transportation system.In addition,the total electricity consumption of rail transit has been increasing year by year,and it is necessary to optimize the energy consumption of rail transit systems to relieve the pressure of electricity consumption in cities.This dissertation takes the urban rail transit train timetable as the research object,considers the travel time cost of passengers and the energy consumption cost of the rail transit companies.By analyzing the deficiencies of the first and last train timetables,the focus is on the timetable synchronization optimization and the train traction energy consumption optimization of the first and last trains.The first and last train timetable optimization models under different operation scenarios are established,the solution algorithms are designed,and the effectiveness of the models and algorithms are verified by taking the rail transit network of Beijing,Nanjing and Hefei as examples,respectively.The main research contents and conclusions are as follows:1.For a rail transit network with interval train depot,the effect of operating interval trains originating from intermediate stations on the first train transfer is studied.An optimization model of the first train timetable synchronization considering interval trains is constructed,and a genetic simulated annealing algorithm is designed to solve the model.A case study of Beijing rail transit network is conducted,and analyzed the energy-saving effect of operating interval trains.After optimization,for the optimization model without considering interval trains,the total transfer waiting time and the number of directions with long transfer waiting time decreased by 29.5%and 20.6%,respectively;for the optimization model with considering interval trains,the total transfer waiting time and the number of directions with long transfer waiting time decreased by 32.9%and 29.5%,respectively.The results indicate that operating interval trains can effectively alleviate the problem of long transfer waiting time for the first train.2.For a rail transit network without interval train depot,the effect of operating the first deadheading train on passenger travel and rail transit company operation is studied.An energy-efficient optimization model of the first train timetable considering deadheading is constructed,and a variable neighborhood simulated annealing algorithm is designed to solve the model.A case study of Nanjing rail transit network is conducted.After optimization,the waiting time at skipped stations increased by 178 minutes,the waiting time at transfer stations decreased by 262.24 minutes,the total waiting time decreased by 84.24 minutes,and the total energy consumption of the first trains decreased from 5806.28 kWh to 4390.92 kWh.These results show that operating the first deadheading train can simultaneously reduce the time cost of the first train passengers and the energy consumption cost of the rail transit company.3.For a rail transit network without interval train depot,the effect of deadheading train multi-point departure on the first train transfer is studied.A mixed integer nonlinear programming model is constructed,by linearizing the model,the optimization software COPT is applied to solve the model.A case study of Hefei rail transit network is conducted,and analyzed the energy-saving effect of operating multipoint departure interval trains.After optimization,with the increase of interval train operation frequency,the total transfer waiting time gradually decreases.When two bidirectional lines operate 12 interval trains,the total transfer waiting time and the number of directions with long transfer waiting time decreased by 39.09%and 56.25%respectively.The results indicate that the multi-point departure scheme can effectively improve the transfer efficiency of the first train passengers.4.To address the problem that the random delay of the last train will affect transfer connection,the last train timetable rescheduling considering random delay is studied.With the optimization objective of maximizing the total transfer connection of the last trains and minimizing the traction energy consumption of the last trains,a last train rescheduling model considering random delay is constructed.A genetic algorithm is developed to solve the model,and a sample network is selected to validate the proposed model.A case study of Beijing rail transit network is conducted.The results show that the model can quickly generate an adjustment scheme for the case of last train delays,the adoption of this adjustment scheme can effectively improve the transfer accessibility between lines,and reduce the energy consumption of trains and the operation cost of the metro companies.This study helps to improve the service level of urban rail transit system,increase the willingness of urban residents to use rail transit to travel,and achieve energy saving and emission reduction of urban integrated transportation systems.