A Real-Time Energy Management Strategy of Flexible Smart Traction Power Supply System Based on Deep Q-Learning-Reference-Cited by-同舟云学术

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A Real-Time Energy Management Strategy of Flexible Smart Traction Power Supply System Based on Deep Q-Learning

Published:2024-08 Issue:8 Volume:25 Page:8938-8948
ISSN:1524-9050
Container-title:IEEE Transactions on Intelligent Transportation Systems
language:
Short-container-title:IEEE Trans. Intell. Transport. Syst.

Author:

Ying Yichen¹^ORCID,Tian Zhongbei²^ORCID,Wu Mingli³^ORCID,Liu Qiujiang³^ORCID,Tricoli Pietro²^ORCID

Affiliation:

1. School of Electrical Engineering, Shanghai University of Electric Power, Shanghai, China

2. Department of Electronic, Electrical and Systems Engineering, University of Birmingham, Birmingham, U.K.

3. School of Electrical Engineering, Beijing Jiaotong University, Beijing, China

Funder

Engineering and Physical Sciences Research Council

China Scholarship Council

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/6979/10621861/10570349.pdf?arnumber=10570349

Reference36 articles.

1. Stochastic Process and Simulation of Traction Load for High Speed Railways

2. A novel modeling approach of negative-sequence current for electrified railway traction substation

3. Voltage Unbalance Probability Pre-Assessment of Electrified Railways With Uncertain Traction Load

4. An Energy Storage System for Recycling Regenerative Braking Energy in High-Speed Railway

5. High-Order Harmonic Resonances in Traction Power Supplies: A Review Based on Railway Operational Data, Measurements, and Experience

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