ew 18: e41

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: Online First},
        keywords={Energy Efficiency, Energy Storage Systems, Fuzzy Logic Controllers, Genetic Algorithms, Smart Railways},
  • Vítor A. Morais
    João L. Afonso
    António P. Martins
    Year: 2021
    Towards Smart Railways: A Charging Strategy for Railway Energy Storage Systems
    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


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.