An integrated energy-efficient operation methodology for metro systems based on a real case of Shanghai Metro Line One

Gong, Cheng, Zhang, Shiwen, Zhang, Feng, Jiang, Jianguo and Wang, Xinheng ORCID: https://orcid.org/0000-0001-8771-8901 (2014) An integrated energy-efficient operation methodology for metro systems based on a real case of Shanghai Metro Line One. Energies, 7 (12). pp. 7305-7329. ISSN 1996-1073

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Abstract

Metro systems are one of the most important transportation systems in people's lives. Due to the huge amount of energy it consumes every day, highly-efficient operation of a metro system will lead to significant energy savings. In this paper, a new integrated Energy-efficient Operation Methodology (EOM) for metro systems is proposed and validated. Compared with other energy saving methods, EOM does not incur additional cost. In addition, it provides solutions to the frequent disturbance problems in the metro systems. EOM can be divided into two parts: Timetable Optimization (TO) and Compensational Driving Strategy Algorithm (CDSA). First, to get a basic energy-saving effect, a genetic algorithm is used to modify the dwell time of each stop to obtain the most optimal energy-efficient timetable. Then, in order to save additional energy when disturbances happen, a novel CDSA algorithm is formulated and proposed based on the foregoing method. To validate the correctness and effectiveness of the energy-savings possible with EOM, a real case of Shanghai Metro Line One (SMLO) is studied, where EOM was applied. The result shows that a significant amount of energy can be saved by using EOM.

Item Type: Article
Identifier: 10.3390/en7117305
Additional Information: © 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/)
Keywords: metro system; energy-saving; energy-efficient operation methodology; timetable optimization; compensational driving strategy algorithm
Subjects: Computing > Systems > Computer networking
Depositing User: Henry Wang
Date Deposited: 01 Feb 2018 10:59
Last Modified: 04 Nov 2024 12:03
URI: https://repository.uwl.ac.uk/id/eprint/4357

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