Abstract
Subway systems consume a large amount of energy each year. How to reduce the energy consumption of subway systems has already become an issue of concern in recent years. This paper proposes an energy-efficient approach to reduce the traction energy by optimizing the train operation for multiple interstations. Both the trip time and driving strategy are considered in the proposed optimization approach. Firstly, a bi-level programming model of multiple interstations is developed for the energy-efficient train operation problem, which is then converted into an integrated model to calculate the driving strategy for multiple interstations. Additionally, the multi-population genetic algorithm (MPGA) is used to solve the problem, followed by calculating the energy-efficient trip times. Finally, the paper presents some examples based on the operation data of the Beijing Changping subway line. The simulation results show that the proposed approach presents a better energy-efficient performance than that with only optimizing the driving strategy for a single interstation.
Highlights
With the rapid development of railway transportation, the energy consumption problem of the railway transportation industry is becoming prominent
Train traction energy consumption accounts for the largest proportion in subway systems, which is closely related to the train operation
This paper proposes an energy-efficient approach to reduce the traction energy by optimizing the train operation for multiple interstations
Summary
With the rapid development of railway transportation, the energy consumption problem of the railway transportation industry is becoming prominent. Train traction energy consumption accounts for the largest proportion in subway systems, which is closely related to the train operation. Reducing the traction energy by optimizing the train operation becomes more important. Many studies have been focusing on the energy-efficient operation of railway trains. Ishikawa [1] studied the optimal control model with constant traction efficiency. For applying the theory into practice, many studies take gradients, speed limit and variable traction efficiency into consideration. Milroy [3] and Asnis et al [4] put forward a model with constant slope in the lines, calculated the optimal control sequence with the minimum energy consumption. Golovitcher [5,6] studied the problem with variable gradients to find the general rules for optimizing the control sequence. Howlett et al [7]
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