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Journal of Advanced Transportation
Volume 2018, Article ID 7905820, 19 pages
https://doi.org/10.1155/2018/7905820
Research Article

Integrated Optimization on Train Control and Timetable to Minimize Net Energy Consumption of Metro Lines

1MOE Key Laboratory for Urban Transportation Complex Systems Theory and Technology, Beijing Jiaotong University, Beijing 100044, China
2Department of Civil and Environmental Engineering, Imperial College London, London SW7 2AZ, UK

Correspondence should be addressed to Yun Bai; nc.ude.utjb@iabnuy

Received 15 December 2017; Revised 21 February 2018; Accepted 19 March 2018; Published 26 April 2018

Academic Editor: Andrea D’Ariano

Copyright © 2018 Yuhe Zhou et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Energy-efficient metro operation has received increasing attention because of the energy cost and environmental concerns. This paper developed an integrated optimization model on train control and timetable to minimize the net energy consumption. The extents of train motoring and braking as well as timetable configurations such as train headway and interstation runtime are optimized to minimize the net energy consumption with consideration of utilizing regenerative energy. An improved model on train control is proposed to reduce traction energy by allowing coasting on downhill slopes as much as possible. Variations of train mass due to the change of onboard passengers are taken into account. The brute force algorithm is applied to attain energy-efficient speed profiles and an NS-GSA algorithm is designed to attain the optimal extents of motoring/braking and timetable configurations. Case studies on Beijing Metro Line 5 illustrate that the improved train control approach can save traction energy consumption by 20% in the sections with steep downhill slopes, in comparison with the commonly adopted train control sequence in timetable optimization. Moreover, the integrated model is able to significantly prolong the overlapping time between motoring and braking trains, and the net energy consumption is accordingly reduced by 4.97%.