Jamali, M., Sadabadi, M.S. and Davari, M. (2025) A set-theoretic adaptive current control design for grid-following inverter-based resources to tackle practically non-ideal control inputs. IEEE Transactions on Automation Science and Engineering. ISSN 1545-5955
Abstract
Three-phase grid-following (GFL) inverter-based resources (IBRs) play a vital role as an interface for integrating renewable energy resources and flexible loads, such as electric vehicles, into the power grid. This paper introduces a novel set-theoretic adaptive control scheme for the primary control of three-phase GFL IBRs, designed to mitigate the impacts of uncertainties or non-ideal conditions affecting the control layer. These uncertainties will risk losing the stability and intended operation of three-phase GFL IBRs by potentially influencing the control commands transmitted to pulse width modulators. In order to address this issue, this study proposes an add-on control signal generated through an adaptive architecture to retrofit the existing (pre-designed) state feedback controller of GFL IBRs. As the name implies, this retrofit control strategy entails upgrading or modifying the existing feedback control instead of completely replacing it. The proposed control scheme is based on a set-theoretic adaptive controller design that employs generalized restricted potential functions. A notable aspect of this framework is its ability to ensure that the reference tracking error bound remains below a user-defined threshold, making it “computable” by providing the control design parameters. The stability of the closed-loop system and the approximate reference tracking performance of the proposed control scheme for GFL IBRs are validated through a theoretical analysis employing the Lyapunov theory. Simulation-based and experimental results further confirm the efficacy of the proposed GFL IBR controller. Note to Practitioners—Given the strive to focus on renewables-intensive and modern power grids, inverters must exhibit enhanced intelligence and versatility to accommodate various functionalities. However, uncertainties or non-ideal conditions originating from diverse sources significantly threaten the optimal operation of inverter-based resources. These uncertainties introduce errors into the control loop of grid-following inverter-based resources, potentially compromising their stability and performance. In order to tackle this compelling challenge, this paper proposes a novel set-theoretic adaptive current control scheme for grid-following inverter-based resources using an add-on control signal. The aim is to mitigate the adverse effects of uncertainties affecting the control commands in grid-following inverter-based resources. By incorporating the additional control signals into the feedback controller, reference tracking is assured despite uncertainties. This approach offers a more cost-effective solution by enhancing the existing feedback control instead of entirely replacing it. Lyapunov stability theory provides a theoretical framework for analyzing stability and ensuring the uniform boundedness of output trajectories in grid-following inverter-based resources. Simulation and experimental results confirm the feasibility and effectiveness of the proposed approach in mitigating the uncertainties affecting the control commands.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 The Authors. Except as otherwise noted, this author-accepted version of a journal article published in IEEE Transactions on Automation Science and Engineering is made available via the University of Sheffield Research Publications and Copyright Policy under the terms of the Creative Commons Attribution 4.0 International License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ |
Keywords: | Set-theoretic adaptive control; three-phase grid-following (GFL) inverter-based resources (IBRs); uncertainties; vector current control |
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: | 26 Feb 2025 15:09 |
Last Modified: | 26 Feb 2025 15:09 |
Status: | Published online |
Publisher: | Institute of Electrical and Electronics Engineers (IEEE) |
Refereed: | Yes |
Identification Number: | 10.1109/tase.2024.3507616 |
Related URLs: | |
Sustainable Development Goals: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:223809 |