The study explores heuristic, mathematical, and hybrid methods for microgrid sizing and optimization-based energy management approaches, addressing the need for detailed energy planning and seamless integration between these stages. It also highlights the importance of adaptive learning techniques for controlling autonomous microgrids.
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