Research On Energy-Saving Operation Control Of Urban Rail Transit Based On Firefly Algorithm

In recent years,with the rapid development of urban rail transit in China,more and more cities have opened urban rail lines,and the number of operation lines and passenger traffic are growing fast.Accordingly,the electricity cost is also increasing rapidly.Among them,the energy consumption of train operation accounts for a large proportion,so reducing the energy consumption of train traction has a great significance.This thesis aims to study the problem of the urban rail train energy-saving optimization from two aspects.One is to reduce the energy consumption of train station operation and the other is to improve the utilization rate of regenerative braking energy.Two optimization models are established respectively and the firefly algorithm is used to solve the problems.In order to improve the quality of the solution,a variable step strategy for population iteration is proposed.Firstly,based on the force analysis of the train movement process,the multi-particle kinematics model of the train is established.According to the traction and braking characteristics of the train and the theory of energy consumption calculation,the optimization model of single train operation is established on the consideration of factors such as ramp condition,speed limit condition,punctuality requirement and parking accuracy requirement etc.In order to reduce the range of feasible solutions,the line between stations is discretized into sub-intervals which as energy calculation units on the principle of ramp and rate-limiting uniqueness.Taking the maximum speed of train subsection as variable and punctuality as constraints,the firefly algorithm is adopted to minimize the traction energy consumption of train operation.Secondly,on the basis of single train operation optimization,according to the beginning and end time of the traction and braking process during the operation of the train between the stations,the trains in traction and braking conditions at the same time are matched.Through the analysis of train diagram,the maximum utilization value of regenerative braking energy in the overlapping period is taken as the optimization objective,and the time between departure is selected as variables to establish a multi-train collaborative optimization model.Finally,the method of generating speed curve designed in this thesis,which conforms to the time constraints,speed limit conditions as well as precise parking requirements,and the firefly algorithm are simulated with the actual track parameters of urban rail transit as scenarios.The validity of the algorithm is verified.On this basis,the maximum regenerative braking energy that can be used by two trains is obtained.The full text contains 47 pictures,8 tables,and 36 references.