LAPSE:2023.8626v1
Published Article

LAPSE:2023.8626v1
Adaptive Resilient Control of AC Microgrids under Unbounded Actuator Attacks
February 24, 2023
Abstract
Existing secondary control methods using fault-tolerant and/or H∞ control techniques for multi-inverter microgrids generally assume bounded faults and/or disturbances. Herein, we study unknown unbounded attacks on the input channels of both frequency and voltage control loops of inverters that could deteriorate the cooperative performance and affect the microgrid stability. We propose a fully distributed attack-resilient control framework using adaptive control techniques that, using stability analysis with Lyapunov techniques, are shown to preserve the uniformly ultimately bounded consensus for frequency regulation and voltage containment. Moreover, the ultimate bound can be set by adjusting the tuning parameters. The proposed result is validated for a modified IEEE 34-bus test feeder benchmark system augmented with four inverters.
Existing secondary control methods using fault-tolerant and/or H∞ control techniques for multi-inverter microgrids generally assume bounded faults and/or disturbances. Herein, we study unknown unbounded attacks on the input channels of both frequency and voltage control loops of inverters that could deteriorate the cooperative performance and affect the microgrid stability. We propose a fully distributed attack-resilient control framework using adaptive control techniques that, using stability analysis with Lyapunov techniques, are shown to preserve the uniformly ultimately bounded consensus for frequency regulation and voltage containment. Moreover, the ultimate bound can be set by adjusting the tuning parameters. The proposed result is validated for a modified IEEE 34-bus test feeder benchmark system augmented with four inverters.
Record ID
Keywords
containment, inverters, microgrids, resilience, unbounded attacks
Subject
Suggested Citation
Zuo S, Zhang Y, Wang Y. Adaptive Resilient Control of AC Microgrids under Unbounded Actuator Attacks. (2023). LAPSE:2023.8626v1
Author Affiliations
Zuo S: Department of Electrical and Computer Engineering, University of Connecticut, Storrs, CT 06269, USA
Zhang Y: Department of Electrical and Computer Engineering, University of Connecticut, Storrs, CT 06269, USA [ORCID]
Wang Y: Department of Electrical and Computer Engineering, University of Connecticut, Storrs, CT 06269, USA
Zhang Y: Department of Electrical and Computer Engineering, University of Connecticut, Storrs, CT 06269, USA [ORCID]
Wang Y: Department of Electrical and Computer Engineering, University of Connecticut, Storrs, CT 06269, USA
Journal Name
Energies
Volume
15
Issue
20
First Page
7458
Year
2022
Publication Date
2022-10-11
ISSN
1996-1073
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Original Submission
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PII: en15207458, Publication Type: Journal Article
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LAPSE:2023.8626v1
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https://doi.org/10.3390/en15207458
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Feb 24, 2023
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