Scheduling of futuristic railway microgrids—A FRA-pruned twins-actor DDPG approach

Zhao, S. orcid.org/0000-0001-9660-6821, Li, K., Yu, J. et al. (1 more author) (2024) Scheduling of futuristic railway microgrids—A FRA-pruned twins-actor DDPG approach. Energy, 313. 134089. ISSN 0360-5442

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Item Type: Article
Authors/Creators:
Copyright, Publisher and Additional Information:

This is an author produced version of an article published in Energy, made available under the terms of the Creative Commons Attribution License (CC-BY), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited.

Keywords: Railway power supply systems, Microgrid, Machine learning, Renewable generation, Energy storage
Dates:
  • Published: 30 December 2024
  • Published (online): 8 December 2024
  • Accepted: 3 December 2024
Institution: The University of Leeds
Academic Units: The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds)
Depositing User: Symplectic Publications
Date Deposited: 10 Dec 2024 12:27
Last Modified: 20 Feb 2025 11:15
Status: Published
Publisher: Elsevier BV
Identification Number: 10.1016/j.energy.2024.134089
Open Archives Initiative ID (OAI ID):

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