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[pdf] Therefore, in this research work, a comprehensive review of different control strategies that are applied at different hierarchical levels (primary, secondary, and tertiary control levels) to accomplish different control objectives is presented. A main consideration is not only given to the. . In conclusion, it is highlighted that machine learning in microgrid hierarchical control can enhance control accuracy and address system optimization concerns. However, challenges, such as computational intensity, the need for stability analysis, and experimental validation, remain to be addressed. This paper examines a secondary control. .
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