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

被引：0

作者：

Morais V.A. ^{[1
]}

Afonso J.L. ^{[2
]}

Martins A.P. ^{[1
]}

机构：

[1] Department of Electrical and Computers Engineering, University of Porto, Porto

[2] Centro Algoritmi, University Of Minho, Guimarães

来源：

EAI Endorsed Transactions on Energy Web | 2021年 / 8卷 / 34期

基金：

欧盟地平线“2020”;

关键词：

Energy Efficiency; Energy Storage Systems; Fuzzy Logic Controllers; Genetic Algorithms; Smart Railways;

D O I：

10.4108/eai.14-1-2021.168136

中图分类号：

学科分类号：

摘要：

The huge power requirements of future railways require the usage of energy-efficient strategies towards a more 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 for the 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 extended to 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. © 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 so long as the original work is properly cited.

引用

页码：1 / 17

页数：16

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