Research On Optimization Method Of Energy Saving Operation Speed Curve Of Energy Storage Metro

With the rapid growth of urban scale,as the most important means of transportation for urban development,the power consumption of subway traffic is increasing day by day.The optimization of train energy-saving speed curve and the utilization of regenerative braking energy are two important energy-saving means in urban subway traffic operation.The optimization of train energy-saving operation speed curve aims to reduce the traction energy consumption in the process of train operation;the utilization of regenerative energy is to effectively utilize the regenerative braking energy generated by train braking through technical means.Based on the energy utilization mode of regenerative braking with energy storage,this paper establishes energy-saving operation models between single station and multi station respectively for on-board and on-site energy storage metro trains,and uses a new adaptive mutation strategy immune genetic algorithm to obtain the optimal energy-saving speed curve.Through the example simulation,the rapidity and convergence of the optimization algorithm,the practicability of the model and the energy saving of the optimal energy saving speed curve are verified.The specific work is as follows:(1)The performance of immune genetic algorithm(IGA)is improved.In this paper,adaptive mutation strategy immune genetic algorithm(AMIGA)is proposed by introducing adaptive strategy into mutation operator.In AMIGA algorithm,the mutation probability is dynamically adjusted between the average fitness and the maximum fitness according to the individual fitness.Four typical test functions with different complexity are optimized and compared with IGA algorithm.The test results show that AMIGA algorithm has faster convergence speed and stronger optimization ability than IGA algorithm.(2)Aiming at the optimization of energy-saving operation speed curve of metro trains between single stations,an energy-saving operation optimization scheme based on energy storage regenerative braking energy utilization mode is designed.For the on-board energy storage metro train,the objective function with minimum net energy consumption as the objective and multiple constraints is established,and the optimal energy-saving operation speed curve is solved by iterative optimization using AMIGA algorithm.Through the example simulation,the energy consumption of train operation is reduced by 10.08% compared with the actual operation energy consumption;for the on-board energy storage metro train,different weight coefficients are set for the optimization objective,and the optimal energy-saving operation speed curve is established.The objective function with the minimum net energy consumption,the minimum time error and the closest installation position as the optimization objectives is established.The AMIGA algorithm is used for iterative optimization to solve the optimal energy-saving operation speed curve.Through the example simulation,when the installation position of the energy storage device is 60 m away from the station position and the time error is 1.52 s,the train operation energy consumption is reduced by12.93% compared with the actual operation energy consumption.(3)Aiming at the optimization of energy-saving operation speed curve of multi station Metro train,an energy-saving optimization scheme of bidirectional closed line operation based on energy storage regenerative braking energy utilization mode is designed.In the actual case,by optimizing the quality and capacity of on-board energy storage equipment,the running energy consumption of the train is reduced by 13.61% compared with that of the train without energy storage equipment;by optimizing the location of the energy storage equipment on the line,the running energy consumption of the train is reduced by 21.53%compared with that of the train without energy storage equipment.