Monitoring, estimation, and robust control of microgrids for safe operation

Shafei, Hamidreza

Monitoring, estimation, and robust control of microgrids for safe operation

Shafei, Hamidreza

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Publication Type:: Thesis
Issue Date:: 2025

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Field	Value	Language
dc.contributor.author	Shafei, Hamidreza
dc.date.accessioned	2026-01-15T03:08:44Z
dc.date.available	2026-01-15T03:08:44Z
dc.date.issued	2025
dc.identifier.uri	http://hdl.handle.net/10453/191851
dc.description	University of Technology Sydney. Faculty of Engineering and Information Technology.	en_US.UTF-8
dc.description.abstract	To meet the growing global energy demand, microgrids (MGs) have gained significant attention due to their numerous advantages. However, ensuring safe operation remains the foremost requirement for MGs, even during contingencies. MGs must function safely in both islanded and grid-connected modes, even when exposed to intentional or unintentional disruptive events. These events may stem from factors such as equipment failures, extreme weather conditions, sudden changes in load demand, noise, or cyber-attacks, all of which can negatively impact the safety, resilience, and reliability of MGs. While noise and fault signals are typically bounded, cyber-attacks pose a unique and critical threat as they are deliberately engineered to maximize damage and are not inherently constrained. Thus, ensuring the safe operation of MGs in the face of cyber-attacks has become a rapidly expanding area of research, presenting significant challenges in both detection and control strategies that remain to be addressed. Among all kinds of attacks, false data injection attacks (FDIAs) are deliberately crafted by intelligent adversaries to mimic normal system behaviour, making them difficult to detect using conventional methods. Unlike natural disturbances, which are random and bounded by physical laws, FDI attacks are unconstrained and can be targeted to manipulate system dynamics and cause instability without triggering alarms. This thesis presents novel observer-based cyberattack-resilient control and operation methods for both dc and ac MGs, designed to enhance cybersecurity against FDI attacks. To effectively detect cyber-attacks targeting communication channels, two advanced model-based techniques have been developed: sliding mode and projection operator-based observers, both capable of attack reconstruction under unknown inputs. Since the proposed observers estimate the states of neighboring units without full access to their internal information, unknown input observers (UIOs) are employed to accurately reconstruct attacks under limited system knowledge. In this regard, each DG unit is equipped with a bank of these observers to estimate the dynamic states of all neighboring units. The developed attack reconstruction methods are integrated into a robust control and operation framework, designed to be resilient against cyber-attacks and focused on mitigating the harmful effects of FDIAs. Extensive real-time numerical simulations are conducted to evaluate the practicality and efficiency of the proposed approach under various attack scenarios. The results demonstrate its superiority over existing methods by reducing overshoot by 21.43\%, achieving a slightly faster settling time, and significantly improving the rise time by 83.95\%.	en_US.UTF-8
dc.format	Thesis (PhD)
dc.language.iso	en_US	en_US.UTF-8
dc.relation	https://opus.lib.uts.edu.au/bitstream/10453/191851/1/thesis.pdf
dc.rights	info:eu-repo/semantics/openAccess
dc.rights	The author owns the copyright in this thesis including all reproduction and reuse rights for the work. The work may not be altered without the permission of the copyright owner. Attribution is essential when quoting or paraphrasing from this thesis.
dc.rights	© 2025 Hamidreza Shafei
dc.rights	au.edu.uts.lib/cph
dc.title	Monitoring, estimation, and robust control of microgrids for safe operation	en_US.UTF-8
dc.type	Thesis
utslib.copyright.status	open_access	*

Abstract:

To meet the growing global energy demand, microgrids (MGs) have gained significant attention due to their numerous advantages. However, ensuring safe operation remains the foremost requirement for MGs, even during contingencies. MGs must function safely in both islanded and grid-connected modes, even when exposed to intentional or unintentional disruptive events. These events may stem from factors such as equipment failures, extreme weather conditions, sudden changes in load demand, noise, or cyber-attacks, all of which can negatively impact the safety, resilience, and reliability of MGs. While noise and fault signals are typically bounded, cyber-attacks pose a unique and critical threat as they are deliberately engineered to maximize damage and are not inherently constrained. Thus, ensuring the safe operation of MGs in the face of cyber-attacks has become a rapidly expanding area of research, presenting significant challenges in both detection and control strategies that remain to be addressed. Among all kinds of attacks, false data injection attacks (FDIAs) are deliberately crafted by intelligent adversaries to mimic normal system behaviour, making them difficult to detect using conventional methods. Unlike natural disturbances, which are random and bounded by physical laws, FDI attacks are unconstrained and can be targeted to manipulate system dynamics and cause instability without triggering alarms. This thesis presents novel observer-based cyberattack-resilient control and operation methods for both dc and ac MGs, designed to enhance cybersecurity against FDI attacks. To effectively detect cyber-attacks targeting communication channels, two advanced model-based techniques have been developed: sliding mode and projection operator-based observers, both capable of attack reconstruction under unknown inputs. Since the proposed observers estimate the states of neighboring units without full access to their internal information, unknown input observers (UIOs) are employed to accurately reconstruct attacks under limited system knowledge. In this regard, each DG unit is equipped with a bank of these observers to estimate the dynamic states of all neighboring units. The developed attack reconstruction methods are integrated into a robust control and operation framework, designed to be resilient against cyber-attacks and focused on mitigating the harmful effects of FDIAs. Extensive real-time numerical simulations are conducted to evaluate the practicality and efficiency of the proposed approach under various attack scenarios. The results demonstrate its superiority over existing methods by reducing overshoot by 21.43\%, achieving a slightly faster settling time, and significantly improving the rise time by 83.95\%.

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