Modeling and intelligent load frequency control of an islanded microgrid. ( FR : Modélisation et contrôle intelligent de la fréquence de charge d’un microgrid ilôté)

Abstract

This thesis presents a comprehensive study on the modeling, analysis, and control of hybrid microgrid systems with a primary focus on frequency stability. The work begins with a review of microgrid concepts, classifications, and applications, highlighting their role in reducing emissions, improving efficiency, and providing reliable power in isolated regions. Accurate mathematical models of renewable and conventional energy sources, as well as Plug-in Hybrid Electric Vehicles (PHEVs) as flexible storage units, were developed to capture system dynamics and support effective control design. A Multi-Stage PID (MPID) controller was proposed and tuned using both conventional methods (ZN and CDM) and advanced optimization algorithms (CSA and ACO). Results showed significant improvements in frequency regulation compared to classical PID controllers. The study was further extended with Type-1 and Type-2 Fuzzy Logic, which enhanced robustness and adaptability against uncertainties and stochastic variations. The findings confirm that frequency stability is a cornerstone for reliable microgrid operation, especially in islanded mode where renewable energy variability is most pronounced. By integrating advanced control strategies and flexible storage such as PHEVs, hybrid microgrids can achieve higher resilience, flexibility, and sustainability. The proposed framework offers valuable insights for researchers, engineers, and policymakers in developing efficient, clean, and decentralized energy systems that meet growing global electricity demands while supporting long-term energy security and environmental goa