Towards Smart Railways: A Charging Strategy for Railway Energy Storage Systems

Vítor Morais; João Afonso; António Martins

Research Article

Towards Smart Railways: A Charging Strategy for Railway Energy Storage Systems

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@ARTICLE{10.4108/eai.14-1-2021.168136,
    author={V\^{\i}tor A. Morais and Jo\"{a}o L. Afonso and Ant\^{o}nio P. Martins},
    title={Towards Smart Railways: A Charging Strategy for Railway Energy Storage Systems},
    journal={EAI Endorsed Transactions on Energy Web},
    volume={8},
    number={34},
    publisher={EAI},
    journal_a={EW},
    year={2021},
    month={1},
    keywords={Energy Efficiency, Energy Storage Systems, Fuzzy Logic Controllers, Genetic Algorithms, Smart Railways},
    doi={10.4108/eai.14-1-2021.168136}
}

Vítor A. Morais
João L. Afonso
António P. Martins
Year: 2021
Towards Smart Railways: A Charging Strategy for Railway Energy Storage Systems
EW
EAI
DOI: 10.4108/eai.14-1-2021.168136

Vítor A. Morais¹^,*, João L. Afonso², António P. Martins¹

1: Department of Electrical and Computers Engineering, University of Porto, 4200-465 Porto, Portugal
2: Centro ALGORITMI, University of Minho, 4800-058 Guimarães, Portugal

*Contact email: v.morais@fe.up.pt

Abstract

The huge power requirements of future railways require the usage of energy-efficient strategies towards amore intelligent railway system. The usage of on-board energy storage systems enables better usage of the traction energy with a higher degree of freedom. In this article is proposed a top-level charging controller forthe on-board and wayside railway energy storage systems. Its structure comprehends two processing levels: a real-time fuzzy logic controller for each energy storage system, and a genetic algorithm meta-heuristic, that remotely and automatically tune the fuzzy rules weight. As global results, the reduction of regenerated energy is 22.3% with the fuzzy logic controller. With the optimization strategy, this reduction can be further extendedto 28.7%. The need for a smart railway framework is also discussed towards a realistic implementation of such charging strategy. Thus, with a high degree of flexibility, the efficiency of railway energy systems can be increased with the proposed framework.

Keywords: Energy Efficiency, Energy Storage Systems, Fuzzy Logic Controllers, Genetic Algorithms, Smart Railways

Received: 2020-09-07
Accepted: 2021-01-06
Published: 2021-01-14
Publisher: EAI

: http://dx.doi.org/10.4108/eai.14-1-2021.168136

Copyright © 2021 Vítor A. Morais et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution license, which permits unlimited use, distribution and reproduction in any medium solong as the original work is properly cited.