Research On Method Of Energy-efficient Optimization In Multi-interval For Fully Automatic Operation System

As the direction for the development of future urban rail transit,fully automatic operation system has the advantages of safety,efficiency and comfort.Compared to the traditional urban rail transit system,fully automatic operation system with greatly improved intelligence degree,it can automatically adjust train operation and organization conditions on the basis of transportation demand,in addition,train control system is equipped with higher control precision.However,in the process of train operation,different operation strategy and organization conditions can affect train operation energy consumption.At present,the research for fully automatic operation system focuses on the fields of system function implementation,this paper took the energy-efficient strategy into account for the fully automatic operation system,which further improves the intelligent control level of the fully automatic operation system and promotes the development of green rail transit simultaneously.Hence,it is of vital significance to study the issue of energy conversation for fully automatic operation system.According to the features of fully automatic operation system,this paper focuses on the issue of energy-efficient optimization for single interval and multi-interval train operation,the single interval operation research was the foundation of multi-interval.Firstly,the factors affecting the energy consumption of the train are analyzed from the perspective of infrastructure and operation organization by studying characteristics of train operation.For the research content in this paper,the relationship between operation strategy and travel time were considered comprehensively and the influence for train operation energy consumption were studied,train energy-efficient optimization model was built on the basis of train operation scenario in single interval and multi-interval.Then,the energy-efficient optimization scheme of fully automatic operation system was designed.Combined with realistic lines and train conditions,line discretization model and train energy consumption model were built.Considered train speed restriction?travel time?condition transformation and some other constraint conditions,energy-efficient optimization targets were set.In addition,energy-efficient optimization methods based on Genetic Algorithm(GA)and Particle Swarm Optimization(PSO)were designed respectively.Train operation strategy and travel time were optimized.Finally,train operation was simulated on the basis of optimization results and train operation features,simulation curve?travel time and consumption of train operation was obtained.This paper chose the typical scenarios to simulate after analyzing the realistic line features of two fully automatic operation system lines.The result show that when GA and PSO were used,the optimized energy saving rate in the scenario of multi-interval were 10.53%and 9.80%respectively,both two optimization methods can decrease train operation energy consumption effectively by analyzing optimization results of different scenes.Rationality and feasibility of optimization scheme proposed by this paper were verified.Aimed at different operation scenarios of fully automatic operation system,appropriate optimization method was recommended.On the basis of above,in order to optimize conveniently,energy-efficient optimization simulation platform for fully automatic operation system was set up.