Model Predictive Control for Renewable Energy in Microgrids explores how advanced control techniques can address the challenges of integrating variable renewable generation into modern microgrids. While renewables such as solar PV and wind are essential for decarbonization, their intermittent and fluctuating nature can lead to voltage and frequency instability, especially in grid-connected operation.
This book provides a focused introduction to model predictive control (MPC) as a tool for stabilizing and optimizing microgrids. Originally developed for industries such as chemical processing and oil refining, MPC has in recent years been applied successfully to power electronics and distributed generation systems.
Key topics include:
-
Fundamentals of power electronic converters and their control
-
Modelling and hierarchical control structures for microgrids
-
MPC applications for photovoltaic and wind power integration
-
Voltage support strategies and stability enhancement
-
Parallel PV–energy storage system (ESS) microgrids
-
Secondary restoration capabilities after disturbances
-
Tertiary-level optimization of power flows
With simulation and experimental case studies, the book demonstrates both the potential and current limitations of MPC for microgrids, offering insights into future research directions.
It is a concise and valuable resource for researchers, practicing engineers, and graduate students working on renewable energy integration, microgrid design, and advanced control systems.
