A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Energy Efficient Metro Train Running Time Rescheduling Model for Fully Automatic Operation Lines
Reducing energy consumption without degrading the normal operation of metro trains and service quality has received increasing attention. Besides, fully automatic operation (FAO), for which no drivers and crew attendants are needed and all functions are controlled automatically, has been applied as a new generation train operation integrated control technology to achieve better performance. In this paper, a two-level energy-efficient optimization approach is proposed based on the characteristics of the FAO system. First, we formulate a single train trajectory optimization model and develop a genetic algorithm to calculate the optimal speed curves with variable running time. The Pareto frontier that represents the relationship between energy consumption and running time can be obtained. Second, we propose a sensitivity analysis method to distribute the total running time among different station segments based on the Pareto solutions in Level 1. Furthermore, the global optimal solution can be obtained. Finally, a case study of the Nanning Rail Transit Line 5 demonstrates that an optimal distribution of running time leads to extra energy savings compared to the original timetable.
Energy Efficient Metro Train Running Time Rescheduling Model for Fully Automatic Operation Lines
Reducing energy consumption without degrading the normal operation of metro trains and service quality has received increasing attention. Besides, fully automatic operation (FAO), for which no drivers and crew attendants are needed and all functions are controlled automatically, has been applied as a new generation train operation integrated control technology to achieve better performance. In this paper, a two-level energy-efficient optimization approach is proposed based on the characteristics of the FAO system. First, we formulate a single train trajectory optimization model and develop a genetic algorithm to calculate the optimal speed curves with variable running time. The Pareto frontier that represents the relationship between energy consumption and running time can be obtained. Second, we propose a sensitivity analysis method to distribute the total running time among different station segments based on the Pareto solutions in Level 1. Furthermore, the global optimal solution can be obtained. Finally, a case study of the Nanning Rail Transit Line 5 demonstrates that an optimal distribution of running time leads to extra energy savings compared to the original timetable.
Energy Efficient Metro Train Running Time Rescheduling Model for Fully Automatic Operation Lines
He, Deqiang (author) / Guo, Songlin (author) / Chen, Yanjun (author) / Liu, Bin (author) / Chen, Jiqing (author) / Xiang, Weibin (author)
2021-05-10
Article (Journal)
Electronic Resource
Unknown
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