Energy-Saving And Cooperation Control Strategy Optimization Of Urban Rail Train Group Operation

With advantages of safety,efficiency and convenience,urban rail transit systems have become an important part of urban public transport systems.In order to meet the increasing passenger demand,urban rail transit systems usually adopt high-frequency and high-speed operation modes,which causes two issues: huge energy consumption and poor antiinterference.Energy-saving and efficient operation of urban rail transit systems can be achieved by reasonable timetable scheduling and effective implementation of scheduled timetables.Based on this,this paper has studied the optimization of train speed curves,timetables and regulation strategies The research contents include the following four aspects:1)The optimization method of train speed curves is studied to minimize the train operational traction energy consumption.Firstly,according to the line conditions,the running process between two stations is divided into multiple intervals.Then,according to the "energy-running time" index of each interval,coasting regimes are reasonably inserted to minimize the train operational traction energy consumption under the constraint of scheduled running time.The simulation cases based on the Beijing Batong line show that,in comparison to practical speed curves from automatic train operation systems,the optimized speed curves can reduce the train operational traction energy consumption by around 20% without changing the running time.In addition,the engineering verification results show that,in comparison to the driver driving mode,the driver assistance system based on the coasting control algorithm can reduce the train operational traction energy consumption by around 10%.2)The optimization method of train timetables with the objective of maximizing the utilization rate of regenerative braking energy of train group is studied.Firstly,the overlapping energy and quantity indexes of train accelerating and braking regimes are introduced to indirectly characterize the utilization of regenerative braking energy between trains.In the timetable optimization model,the utilization rate of regenerative braking energy is improved by maximizing the overlapping energy or quantity.In addition,the timetable optimization model is rebuilt into a mixed integer linear programming model,so that it can be solved efficiently.The simulation cases based on the Beijing Batong line show that,in comparison to the original timetables,the optimized timetables can improve the utilization rate of regenerative braking energy by around 5% and reduce the energy consumption of traction substation by around 2%.3)The optimization method of train regulation strategies with the objectives of minimizing the influence of disturbances and peak power of traction substation is studied.Firstly,based on the traditional train regulation optimization model,a multi-objective train regulation optimization model is built considering minimizing the overlapping time or quantity of train accelerating regimes.Then,a model predictive control algorithm is designed to realize the real-time calculation of train regulation strategies.The simulation cases based on the Guangzhou Metro Line 8 show that,by optimizing train regulation strategies,the peak power duration of traction substation can be reduced by around 20%.Meanwhile,the timetable and headway deviations can be reduced to ensure the effective implementation of scheduled timetables.4)The train regulation strategies and speed curves optimization methods considering Train-to-Train communication are studied to minimize the influence of disturbances and the multi-train operational energy consumption.An on-board two-level optimization framework considering the exchanged states through Train-to-Train communication is proposed,which is combined with the train regulation strategies and speed curves optimization.At the train regulation strategies optimization level,a train regulation strategy optimization model with the objectives of minimizing the timetable and headway deviations is built,and a distributed model predictive control algorithm is designed to realize the self-calculation of the train regulation strategies of each train.At the train speed curves optimization level,considering the utilization of regenerative braking energy between trains,a speed curve optimization model with the objective of minimizing the multi-train operational energy consumption is built,and a three-dimensional state space dynamic programming algorithm is designed to calculate the energy-saving speed curves.The simulation cases based on the Guangzhou Metro Line 8show that,by applying the on-board two-level optimization framework,the total timetable deviation can be reduced by about 68%,the total headway deviation can be reduced by about69%,and the energy consumption of traction substation can be reduced by about 3%.