Abstract

How to reduce the energy consumption of metro trains by optimizing both the timetable and control strategy is a major focus. Due to the complexity and difficulty of the combinatorial operation problem, the commonly-used method to optimize the train operation problem is based on an unchanged dwelling time for all trains at a specific station. Here, we develop a simulation-based method to design an energy-efficient train control strategy under the optimized timetable constraints, which assign the dwelling time margin to the running time. This time margin is caused by dynamically uncertain passenger demands in off-peak hours. Firstly, we formulate a dwelling time calculation model to minimize the passenger boarding and alighting time. Secondly, we design an optimal train control strategy with fixed time and develop a time-based model to describe mass-belt train movement. Finally, based on this simulation module, we present numerical examples based on the real-world operation data from the Beijing metro Line 2, in which the energy consumption of one train can be reduced by 21.9%. These results support the usefulness of the proposed approach.

Highlights

  • IntroductionA major current focus in metro systems is how to reduce the energy consumption

  • Metro systems play an important role to relieve urban traffic congestion in public transportation.A major current focus in metro systems is how to reduce the energy consumption

  • A recent emerging research interest is in the field of regenerative energy utilization [1,2,3,4,5,6], which focuses on developing a timetable including the dwelling time at stations and running time at sections in order to improve the utilization of regenerative energy by synchronizing the operations of accelerating and braking trains [7]

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Summary

Introduction

A major current focus in metro systems is how to reduce the energy consumption. There are two main levels of train energy-efficient operation approaches. A recent emerging research interest is in the field of regenerative energy utilization [1,2,3,4,5,6], which focuses on developing a timetable including the dwelling time at stations and running time at sections (between two adjacent stations) in order to improve the utilization of regenerative energy by synchronizing the operations of accelerating and braking trains [7]. To calculate the speed profile with minimum tractive energy consumption under the timetable constraints [22]. The simulation-based method is commonly used to calculate the train traction energy consumption under complex track alignments [23,24,25,26,27] by energy-efficient driving [28,29,30,31]

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