Résumé:
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
