This paper aims to provide a comprehensive analysis of recent research on microgrid hierarchical control, specifically focusing on the control schemes and the application of machine learning (ML) techniques. . High penetration of Renewable Energy Resources (RESs) introduces numerous challenges into the Microgrids (MG), such as supply–demand imbalance, non-linear loads, voltage instability, etc. Hence, to address these issues, an effective control system is essential. However, challenges, such as computational intensity, the need for stability analysis, and experimental validation, remain to be addressed. . The Microgrid (MG) concept is an integral part of the DG system and has been proven to possess the promising potential of providing clean, reliable and efficient power by effectively integrating renewable energy sources as well as other distributed energy sources.
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