Charge/Discharge Control of Wayside Batteries via Reinforcement Learning for Energy-Saving in Electrified Railway Systems-Reference-Cited by-同舟云学术

Charge/Discharge Control of Wayside Batteries via Reinforcement Learning for Energy-Saving in Electrified Railway Systems

Published:2020-11-01 Issue:11 Volume:140 Page:807-816
ISSN:0913-6339
Container-title:IEEJ Transactions on Industry Applications
language:en
Short-container-title:IEEJ Trans. IA

Author:

Yoshida Yasuhiro¹,Arai Sachiyo¹,Kobayashi Hiroyasu²,Kondo Keiichiro²

Affiliation:

1. Department of Urban Environment Systems, Division of Earth and Environmental Sciences,Graduate School of Science and Engineering, Chiba University

2. Department of Electrical Engineering and Bioscience, Faculty of Science and Engineering, Waseda University

Publisher

Institute of Electrical Engineers of Japan (IEE Japan)

Subject

Electrical and Electronic Engineering,Industrial and Manufacturing Engineering

Link

https://www.jstage.jst.go.jp/article/ieejias/140/11/140_807/_pdf

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2. (2) A. Fernández-Rodríguez, A. Fernández-Cardador, and A. P. Cucala: “Balancing energy consumption and risk of delay in high speed trains: A three-objective real-time eco-driving algorithm with fuzzy parameters”, Transportation Research Part C: Emerging Technologies, Vol. 95, pp. 652-678 (2018)

3. (3) M. Miyatake and K. Matsuda: “Energy Saving Speed and ChargeDischarge Control of a Railway Vehicle with On-board Energy Storage by Means of an Optimization Model”, IEEJ Transactions on Electrical and Electronic Engineering, Vol. 4, No. 6, pp. 771-778 (2009)

4. (4) P. Arboleya, B. Mohamed, and I. El-Sayed: “DC railway simulation including controllable power electronic and energy storage devices”, IEEE Transactions on Power Systems (2018)

5. (5) D. Cornic: “Efficient recovery of braking energy through a reversible dc substation”, Electrical systems for aircraft, railway and ship propulsion. IEEE (2010)

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