The integration of renewable energy resources, energy storage systems, and controllable loads into large-scale power systems has become a cornerstone of modern energy transitions, with microgrids emerging as a practical and scalable solution. A key enabler of this transition is the widespread deployment of inverter-based resources (IBRs), which integrate with the grid via power-electronic converters. However, their lack of inherent inertia, fast response dynamics, and software-defined control introduce distinct operational challenges, necessitating specialised analytical and design approaches to ensure stable operation.
Simultaneously, the growing integration of information and communication technologies with modern power systems has led to cyber-physical microgrids, where physical components---such as smart inverters---are interconnected with computational and communication layers. While this convergence enhances flexibility, it also exposes microgrids to cyber threats, particularly attacks targeting the cyber layer.
This thesis develops cyber-resilient control schemes for microgrids and IBRs within a hierarchical control structure, focusing on primary and secondary control layers. At the primary level, adaptive resilient current control strategies for grid-following IBRs are designed to mitigate the effects of false data injection attacks---ensuring accurate current tracking, despite manipulated measurements and control inputs. At the secondary level, resilient frequency control strategies are introduced to ensure operational stability and compliance with secondary control objectives despite cyberattacks. These schemes effectively constrain frequency deviations within permissible limits while ensuring proportional active power sharing.
Rigorous stability analyses grounded in Lyapunov theory confirm the bounded-input bounded-output stability or uniform boundedness of the closed-loop control system. Additionally, the efficacy of these proposed control schemes is thoroughly evaluated through comprehensive MATLAB simulations and experiments. The results highlight their effectiveness and demonstrate significant performance improvements over conventional---and, in some cases, even other advanced---control strategies under realistic operating conditions and attack scenarios.
