Coordinated control of wind turbine and hybrid energy storage system based on multi-agent deep reinforcement learning for wind power smoothing

Wang, X., Zhou, J., Qin, B. et al. (1 more author) (2023) Coordinated control of wind turbine and hybrid energy storage system based on multi-agent deep reinforcement learning for wind power smoothing. Journal of Energy Storage, 57. 106297. ISSN 2352-152X

Abstract

Metadata

Item Type: Article
Authors/Creators:
  • Wang, X.
  • Zhou, J.
  • Qin, B.
  • Guo, L.
Copyright, Publisher and Additional Information:

© 2022 Elsevier Ltd. This is an author produced version of a paper subsequently published in Journal of Energy Storage. Uploaded in accordance with the publisher's self-archiving policy. Article available under the terms of the CC-BY-NC-ND licence (https://creativecommons.org/licenses/by-nc-nd/4.0/).

Keywords: Wind power smoothing; Hybrid energy storage system (HESS); Pitch control; Rotor kinetic energy control; Coordinated control; Multi-agent deep reinforcement learning TD3
Dates:
  • Published: January 2023
  • Published (online): 9 December 2022
  • Accepted: 28 November 2022
Institution: The University of Sheffield
Academic Units: The University of Sheffield > Faculty of Engineering (Sheffield) > Department of Automatic Control and Systems Engineering (Sheffield)
Depositing User: Symplectic Sheffield
Date Deposited: 09 Dec 2022 17:47
Last Modified: 09 Dec 2023 01:13
Status: Published
Publisher: Elsevier BV
Refereed: Yes
Identification Number: 10.1016/j.est.2022.106297
Open Archives Initiative ID (OAI ID):

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