This thesis presents control and optimization techniques for islanded AC and hybrid AC/DC microgrids. It gives formulations and control algorithms for microgrids integrated with different types of distributed generators, power converters, renewable energy sources, and battery systems. The control and optimization approaches presented are classified as secondary-level controllers, addressing some of the common objectives for this level, such as power loss minimization, AC frequency and DC voltage restoration, proportional power dispatch, battery systems coordination, and optimal reconfiguration. Different system architectures were studied, including a fully distributed optimization approach, a consensus-based distributed control system, and a centralized learning classifier system.
|Qualification||Doctor of Philosophy|
|Award date||10 Sep 2021|
|Publication status||Unpublished - 2021|