When studying for a doctoral degree (PhD), candidates submit a thesis that provides a critical review of the current state of knowledge of the thesis subject as well as the student’s own contributions to the subject. The distinguishing criterion of doctoral graduate research is a significant and original contribution to knowledge.
Once accepted, the candidate presents the thesis orally. This oral exam is open to the public.
One of the key challenges currently facing by the energy sector is to meet the growing demands for electricity in a safe, secure, and environment-friendly way. Nowadays, governments across the globe are investing in smart grid and renewable energy systems (especially wind turbines and solar photovoltaic systems) to overcome the shortcomings of the conventional power grid and diversify energy resources. To enhance the availability, reliability, and security of renewable energy systems (in smart grid framework) and achieve a more cost-effective operation, innovative approaches for fault detection, diagnosis, and fault-tolerant control along with intrusion detection, diagnosis, and attack-resilient control systems should be taken into consideration. Given that, the research of the thesis has two parts. In the first part, it studies a hybrid renewable microgrid (i.e., microgrids are the fundamental components of smart grid that must act as single controllable entities) made up of a variety of distributed generation systems (solar, wind, and battery). Novel solutions for detection and identification of physical faults and cyber-attacks as well as fault-tolerant and attack-resilient control strategies are proposed for photovoltaic systems at microgrid level. In the second part, it focuses on wind farms. An intrusion detection and fault diagnosis system, and cooperative fault-tolerant and attack-resilient control strategies are proposed to effectively accommodate and mitigate adverse impacts of physical faults and cyber-attacks at wind farm level, respectively. Moreover, a fault-tolerant cooperative control scheme for large-scale wind farms is introduced. In particular, this thesis aims to design novel cyber-physical condition monitoring, diagnosis and fault-tolerant and attack-resilient control strategies with application to renewable energy resources including solar photovoltaic systems (at microgrid level) and wind turbines (at wind farm level) to ensure their efficient and reliable performance under both physical faults and cyber-attacks. The proposed solutions and strategies in this research are verified by a series of simulations on advance microgrid and wind farm benchmark models with their real-life nonlinear nature in the presence of measurement noises, possible disturbances and different realistic faults and attacks scenarios.