Energy Saving Research Of Urban Rail Transit Train Based On Regenerative Braking Energy

Urban rail transit system is a comprehensive system with complex structure,sophisticated technology and huge energy consumption.In order to reduce energy consumption,which contains a lot of potential economic and social value,many technical methods are worthy of being considered.With more widespread energy feedback traction power supply device applied,many researchs focus on regenerative braking energy utilization.The goal of this paper is to save energy of urban rail train by improving utilization rate of regenerative braking energy.The succession time,station dwell time and travle time between staions are optimization variables in this paper.Three potential applications are considered,the main contents and conclusions can be summarized as follows:(1)Static optimization of urban rail train timetable.Based on energy model of train and principle of regenerative braking energy,energy consumption model of urban rail tainsit timetable is established.To minimize this energy consumption,the succession time and station dwell time are selected to be optimization variable.Combining energy consumption model,train operation constraints and mixed logic dynamic model constraints,the optimization problem is transformed into a nolinear mixed integer program problem.Although the optimization problem is large-scale and complex,it can be solved by using simulated annealing algorithm.Based on Chengdu metro line 4,the simulation on the MATLAB platform verifies the effectiveness of the solving algorithm.It shows that the succession time contributes more than 10% energy saving rate while station dwell time contributes less than 3%.(2)Dynamic adjustment in case of urban rail train delay.The problem of train delay often appears because of stochastic disturbance.To reduce the decay and retrieve the established timetable,station dwell time can act as optimization variable.Meanwhile,it allows the delayed train to save energy if regenerative braking energy is used properly.The results of adjustment need to be obtained in real time,so solving algorithm is designed based on greedy algorithm.Cases of different delay situation are simulated on the MATLAB plarform to verify adjusting result.It shows that the strategy proposed by this paper has lower energy consumption that fastest adjustment strategy.Base on adjustable accumulated upper limit,best adjustment strategy can be given according to the practical train delay.(3)Local adjustment of trains in the same power supply area.Travle time between staions is hard to be optimized because it affects both speed curve and power curve of the train.In order to add it as optimization variable,a linearized model is established by calculating overlap time of equivalent power curves.Linearized model is applied to adjust trains in the same power supply area.In this paper,it has been applied to solve dynamic adjustment problem in case of train delay and local adjustment problem at a given succession time.Simulation result shows that the linearized model can give a energy better solution without changing operational requirements.