As the operating mileage increases year by year, the power consumption of metro systems in major cities in China also increases rapidly, with train energy consumption accounting for more than half of the total energy consumption of the system. Through multi-vehicle coordinated control, reasonable optimization of train schedules can increase the use of regenerative braking energy by trains, thereby saving energy consumption in train operation. The multi-train collaborative control energy-saving optimization model with the minimum energy consumption of the train group as the optimization target and the train control scheme as the control variable is established. The improved particle swarm optimization algorithm is used to solve the model. By adjusting the stop time of the adjacent train, the running energy consumption of the train group can be effectively reduced.
Timetable Optimization Model for Metro Trains: Considering Energy Saving
19th COTA International Conference of Transportation Professionals ; 2019 ; Nanjing, China
CICTP 2019 ; 4132-4143
2019-07-02
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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