Reference
X. Luan, Y. Wang, B. De Schutter, L. Meng, G. Lodewijks, and F. Corman,
"Integration of real-time traffic management and train control for rail
networks - Part 2: Extensions towards energy-efficient train operations,"
Transportation Research Part B, vol. 115, pp. 72-94, Sept.
2018.
Abstract
We study the integration of real-time traffic management and train control by
using mixed-integer nonlinear programming (MINLP) and mixed-integer linear
programming (MILP) approaches. In Part 1 of the paper, three integrated
optimization problems, namely the P
NLP problem (NLP:
nonlinear programming), the P
PWA problem (PWA:
piecewise affine), and the P
TSPO problem (TSPO: train
speed profile option), have been developed for real-time traffic management
that inherently include train control. A two-level approach and a
custom-designed two-step approach have been proposed to solve these
optimization problems. In Part 2 of the paper, aiming at energy-efficient train
operation, we extend the three proposed optimization problems by introducing
energy-related formulations. We first evaluate the energy consumption of a
train motion. A set of nonlinear constraints is first proposed to calculate the
energy consumption, which is further reformulated as a set of linear
constraints for the P
TSPO problem and approximated by
using a piecewise constant function for the P
NLP and
P
PWA problems. Moreover, we consider the option of
regenerative braking and present linear formulations to calculate the
utilization of the regenerative energy obtained through braking trains. We
focus on two objectives, i.e., delay recovery and energy efficiency, through
using a weighted-sum formulation and an ϵ-constraint formulation.
With these energy-related extensions, the nature of the three optimization
problems remains same to Part 1. In numerical experiments conducted based on
the Dutch test case, we consider the P
NLP approach and
the P
TSPO approach only and compare their performance
with the inclusion of the energy-related aspects; the
P
PWA approach is neglected due to its bad performance,
as evaluated in Part 1. According to the experimental results, the
P
TSPO approach still yields a better performance
within the required computation time. The trade-off between train delay and
energy consumption is investigated. The results show the possibility of
reducing train delay and saving energy at the same time through managing train
speed, by up to 4.0% and 5.6% respectively. In our case study, applying
regenerative braking leads to a 22.9% reduction of the total energy
consumption.
Publisher page
Downloads
Companion paper
- X. Luan, Y. Wang, B. De Schutter, L. Meng, G. Lodewijks, and F. Corman, "Integration of real-time traffic management and train control for rail networks - Part 1: Optimization problems and solution approaches," Transportation Research Part B, vol. 115, pp. 41-71, Sept. 2018. (online paper, abstract, bibtex, tech. report (pdf))
BibTeX
@article{LuaWan:18-015,
author = {Luan, Xiaojie and Wang, Yihui and De Schutter, Bart and Meng,
Lingyun and Lodewijks, Gabriel and Corman, Francesco},
title = {Integration of Real-Time Traffic Management and Train Control for
Rail Networks -- {Part 2: Extensions} Towards Energy-Efficient
Train Operations},
journal = {Transportation Research Part B},
volume = {115},
pages = {72--94},
month = sep,
year = {2018}
}