Omaruddin, A. and Trodden, P. orcid.org/0000-0002-8787-7432 (2023) LMI-based decentralized load frequency control of a hybrid power system with a virtual synchronous generator and battery storage. In: Ishii, H., Ebihara, Y., Imura, J. and Yamakita, M., (eds.) IFAC-PapersOnLine. 22nd World Congress of the International Federation of Automatic Control (IFAC 2023), 09-14 Jul 2023, Yokohama, Japan. Elsevier , pp. 10910-10916.
Abstract
This paper proposes the participation of wind generation in the decentralized control of load frequency of a hybrid power system consisting of, in addition to wind generation, conventional generation and battery storage. The wind generation is modelled as a ‘Virtual Synchronous Generator (VSG)’ in a separate control area with its own virtual frequency. It has also been proposed to operate the wind generation system in a ‘de-loaded’ mode, thereby allowing it to take part in frequency regulation services. For the purposes of a decentralized control design, the overall system model is decomposed into three subsystems. Static state-feedback control gains are computed by posing the decentralized control problem as a set of linear matrix inequalities (LMIs) subject to structural and stabilizing constraints.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Editors: |
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Copyright, Publisher and Additional Information: | © 2023 The Authors. This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/) |
Keywords: | Optimal operation and control of power systems; Control of renewable energy resources; Control system design |
Dates: |
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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: | 16 Jun 2023 12:37 |
Last Modified: | 07 Dec 2023 15:51 |
Status: | Published |
Publisher: | Elsevier |
Refereed: | Yes |
Identification Number: | 10.1016/j.ifacol.2023.10.775 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:200507 |