Nonlinear Robust Control and Optimisation of Microgrids

This book introduces significant innovations to the field of power systems control. It follows a control-theoretic approach to analyzing networked microgrids, providing a deep understanding of system-dynamical behavior and insights into different system parameters. It promotes rigorous control design methods to achieve stable closed-loop dynamics. The proposed methods offer additional benefits such as robustness to system parameter perturbations and constrained operation.

The book adds successive levels of complexity in the control design process, enhancing system behavior with valuable properties. Starting with the design of a distributed control scheme for meshed microgrids that enforces both coupled and uncoupled constraints, the book moves on to:

• reduce conservatism of the control schemes and increase the closed-loop system’s region of attraction using a geometric approach;
• limit system trajectories within the desired operational range by constructing control barrier functions and positive invariant sets; and
• facilitate the generalization of results to increase relevance beyond their origin in the control of power electronics.

This book begins with an extensive introduction to relevant topics, making it accessible to recent graduates, professional engineers, and academic researchers.

Dr. Grigorios Michos is a postdoctoral researcher in the Department of Electrical and Computer Engineering, University of Patras, Rion, Greece. He received his B.Sc. in automation engineering from the West Attica University, Greece, in 2017 and his M.Sc. and Ph.D. degrees from the University of Sheffield, U.K., in 2019 and 2023, respectively. He has published in high-impact factor journals including IEEE Transactions on Control of Network Systems, IEEE Control Systems Letters and Systems & Control Letters. He has also published his work in conferences of IEEE Control System Society. His research interests include nonlinear system analysis and control, robust control, distributed optimization methods, and smart grid applications.