Integrated Optimization Research Of Metro Energy Conservation Strategy And Passenger Transfer In Rail Transit System

With the rapid development of economy and society,the urbanization process of China is accelerating continuously.And the public transportation system is difficult to meet the increasing demand of passengers.In order to release the pressure of public transportation system,the rail transit system has been put into operation in many cities,and become the preferred transport for passengers.The rail transit system,as a huge underground transportation network,has huge energy consumption and complicated passenger flow.Therefore,the optimization of energy conservation measures of metro trains and passenger transfer strategies has a great practical significance to reduce train operation cost and passenger travel cost.In order to solve the problems of train energy consumption and passenger transfer,this paper established an integrated optimization model to balance metro energy consumption and passenger transfer strategy.First,the train operating conditions and dynamic characteristics of each operating condition were analyzed.Under the consideration of complex operation environment such as curves,ramps and speed limits,a single train energy-saving optimization model was established as bottom sub-model of the integrated optimization model.The genetic algorithm was applied to optimize the train operation curve,which can obtain the optimal energy-saving control strategy of single train.The bottom sub-model can achieve the basic energy conservation of metro trains.Then,based on the operation power data from the bottom sub-model,a tab coding power matrix,combined with the principle of regenerative energy utilization,was established for calculating the regenerative energy efficiently.Afterwards,by analyzing the passenger transfer process,the arrival time matrix was built to calculate the transfer waiting time.Through the analysis and calculation of the regenerative energy recycling and the transfer waiting time sub-model,an upper-layer optimization model based on time scheduling parameters was proposed.And the genetic algorithms was used to optimize the parameters such as departure interval and station dwell time,which can obtain the optimal multiple trains control strategy.The upper-layer optimization model has achieved the purpose of further energy conservation and convenient travel in rail transit system.The simulation results show that it has a fast calculation speed,high resolution and great comprehensive effect.Finally,a simulation system of metro conservation and control optimization was developed based on the proposed theory,which realized the online optimization and adjustment of multiple trains in multiple lines.The simulation system can provide theoretical and technical support for energy conservation of rail transit system.