Thermal Constrained Energy Optimization of Railway Co-phase Systems with ESS Integration - An FRA-pruned DQN Approach

Xing, C, Li, K orcid.org/0000-0001-6657-0522 and Su, J (2023) Thermal Constrained Energy Optimization of Railway Co-phase Systems with ESS Integration - An FRA-pruned DQN Approach. IEEE Transactions on Transportation Electrification, 9 (4). 5122 -5139. ISSN 2332-7782

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Item Type: Article
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Keywords: Co-phase railway traction system; thermal constraint; deep Q-learning network; agent pruning
Dates:
  • Published: December 2023
  • Published (online): 1 November 2022
  • Accepted: 25 October 2022
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Institute of Communication & Power Networks (Leeds)
Funding Information:
Funder
Grant number
Ofgem
Not Known
SP Transmission PLC
Not Known
Depositing User: Symplectic Publications
Date Deposited: 31 Oct 2022 10:59
Last Modified: 22 Aug 2024 13:40
Status: Published
Publisher: Institute of Electrical and Electronics Engineers
Identification Number: 10.1109/TTE.2022.3218762
Open Archives Initiative ID (OAI ID):

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