Research On Integrated Decision Model And Algorithm Of Urban Rail Transit Train Timetable And Speed Curve Based On Hierarchical Collaborative Optimization

With the acceleration of China’s urbanization construction,a large number of people are flocking to cities to work and live.The number of permanent urban residents and the number of residents’ private cars are constantly increasing,resulting in increasingly serious traffic congestion and traffic pollution.Urban rail transit has become the preferred mode of public transportation in many cities in recent years because of its fast,punctual,efficient and energy saving characteristics.However,with the rapid development of urban rail transit,the continuous expansion of line network and the continuous increase of operating mileage,it not only provides fast and convenient travel for urban residents,but also brings huge energy consumption costs and challenges to the sustainable and healthy development of subway operating companies.Therefore,on the basis of satisfying passenger travel service,it is of great significance to study how to reduce train running energy consumption for the sustainable development of urban rail transit in China.In this paper,on the basis of related research at home and abroad for reference,considering the regenerative braking and energy storage device can be real-time used delay using two scenarios,respectively established based on hierarchical collaborative optimization of urban rail transit train schedules and speed curve integration optimization model,to minimize passengers’ waiting time and train the net energy consumption as objective function,effectively improve the quality of passenger service and at the same time reduce the energy consumption of rail transit system.The main research contents are as follows:(1)The calculation formulas of passenger waiting time and train net energy consumption are given.First,analyzed the specific process of the station passenger volume changes over time,gives the calculation formula of passenger waiting time,contain the station passenger waiting time,off time on time within the station passenger waiting time,stranded passengers waiting time for the train capacity limits and start new arrived at the station passenger waiting time interval.Furthermore,the effective regenerative braking energy utilized by the front and rear adjacent trains in real time is analyzed,and the influence of passenger mass on train energy consumption is considered.(2)An integrated layered optimization model of urban rail train schedule and speed curve based on regenerative braking energy utilization is established.The upper layer is the schedule optimization model,and the decision variables are the running time,stopping time and departure interval of the train between stations.The lower layer is the optimization model of the train’s net energy consumption and speed curve,and the decision variables are the train’s inter-station traction time,braking time,traction acceleration and braking deceleration.The upper and lower layer optimization models are solved using genetic algorithm respectively,and the layered optimization solving steps based on genetic algorithm are given.By analyzing the example of Beijing Subway Yizhuang Line,the results show that the optimized train schedule can reduce the passenger waiting time by 29.8% and save the train energy consumption by 7.1%,which proves the validity of the model.(3)Based on the above,an integrated layered optimization model of urban rail transit train schedule and speed curve based on the utilization of energy storage device is established.This paper analyzes the calculation idea of the net energy consumption of the lower train by the energy storage device,gives the calculation process of the net energy consumption of the lower train,and then USES genetic algorithm to solve the optimization model of the upper and lower trains.Finally,through the example simulation,the passenger waiting time of the optimized train schedule is reduced by25.8%,and the actual energy consumption of the train is reduced by 24.2%.The validity of the model is proved,which shows that the energy consumption of urban rail transit system can be effectively reduced by installing energy storage device on the premise of satisfying passenger service level.