Energy-saving Optimization Method Of Urban Rail Transit Based On Multi-train Cooperation

Large-scale development of urban rail transit can effectively alleviate the increasingly severe traffic congestion,but it also brings the problem of energy consumption which can not be ignored.The increasing energy consumption of urban rail transit networks increases the operating cost and causes a heavy burden on the city’s energy supply.Therefore,the research on energy-saving optimization of urban rail transit is of great significance to realize the sustainable development strategy of low-carbon and environmental protection.Based on the optimization of the energy-saving speed curve of a single train,the multi-train cooperation optimization methods for regenerative braking energy utilization are explored.For this purpose,this thesis focuses on two aspects: the off-line energy-saving optimization of timetable and the real-time optimization of scheduling and control integration.The main research contents of this thesis are as follows:(1)Based on the traditional optimal train control strategy,the energy-saving speed curve of the single urban rail train under complex speed limit scenarios is studied.Considering the characteristics of train traction and braking,speed limit,and slope,a more consummate optimization model of the train speed curve is constructed,then a speed curve optimization algorithm based on a time allocation strategy is proposed.Finally,compared with the genetic algorithm,the effectiveness and efficiency of the proposed algorithm are verified.(2)According to the principle of multi-train cooperation optimization,an offline optimization method of the periodic timetable is proposed.By coordinating the dwell times,the time shift of downbound timetable,and headway,the maximum traction and maximum braking processes of different trains in the same power supply section can be better matched to realize the utilization of regenerative braking energy as much as possible.While guaranteeing the number of running trains unchanged,a two-level algorithm is designed to solve the optimized timetable.In the upper level,the multiresolution-based traversal algorithm is used to search for the better feasible values of the headway and time shift of the downbound timetable.And in the lower level,the decomposition coordination algorithm is designed,in which the dwell times are optimized in an optimization subproblem.The simulation results show that the method can reduce energy consumption by 11.12%,and has high computational efficiency and good robustness.(3)The optimization method of train scheduling and control integration under the condition of random delay is studied.Firstly,a comprehensive optimization model with punctuality and energy saving as optimization objectives is established for the scenario of random delay caused by passenger flow.Then,an optimization algorithm of scheduling and control integration is designed.The scheduling layer of the algorithm adjusts the departure time of the current station and the arrival time of the next station according to the delay state and adjustment space for scheduling policy of the target train.In the control layer,the speed curve optimization and adjustment algorithm based on multi-train cooperation is used to calculate the train speed curve.Numerical examples show that the proposed method has high computational efficiency and strong robustness,can effectively improve the punctuality rate of trains,and significantly reduce traction energy consumption.