| In recent years,urban rail transit(URT)is developing rapidly and plays an increasingly important role in the field of public transportation.On one hand,the development of URT alleviates the pressure of road traffic,and on the other hand,it conforms to the concept of green travelling.However,the rapid development of URT also causes a large number of energy consumption.Therefore,the study of energy-saving optimization in train operation is of great significance to the sustainable development of URT.Aiming at reducing the energy consumption of train traction and improving the utilization rate of regenerative braking energy,this thesis adopts adaptive genetic algorithm to study the cooperative control method of energy-saving operations of multiple trains.The actual operation data of Beijing Metro Yizhuang Line is employed to stimulate and verify the energy-saving effects of the method.The main research work and results are described as follows.(1)The kinematic model of a train is established.The force conditions of a train under different working conditions are analyzed,and the calculation method of train traction energy consumption based on mechanical energy work is given.Then,the energy-saving operation strategy of train combining the three-stage operation strategy of“traction-coasting-breaking” with the coasting operation strategy are determined according to the Pontryagin maximum principle.(2)The adaptive crossover and mutation operators are introduced into the traditional genetic algorithm to improve the convergence ability and effectiveness of the algorithm.Taking the minimum traction energy consumption as the goal and the switching points of train working conditions as decision variables,the improved genetic algorithm is adopted to obtain the optimal operation curve of a single train during the fixed running time.Based on the approximately inverse relationship between traction energy consumption and running time,a running time allocation algorithm of single train within all sections of a rail line is established to minimize the total traction energy consumption.The results indicate that the total traction energy consumption of an up direction train of Yizhuang Line running under the optimized timetable deceases by 39.9k Wh compared with the original timetable during the fixed running time.The reduction rate of the total traction energy consumption is 14.8%.(3)The generation,utilization and calculation methods of regenerative energy are summarized,and the utilization scenarios of regenerative braking energy in rush hour train are analyzed.Considering the switching between regenerative braking and air braking of trains and the transmission loss of regenerative energy,a regenerative energy utilization model is established for cooperative operations of multiple trains with maximum overlap time between traction and braking.Based on the optimal time allocation between stations,the genetic algorithm is adopted to optimize the train departure intervals and dwell time,respectively.The effectiveness of the algorithm is verified by numerical examples,and the results are analyzed.32 Figures,17 Tables,and 48 References. |
