Hierarchical Control for Microgrids: A Comprehensive Review of Traditional and Machine Learning Approaches

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The article Hierarchical Control for Microgrids: A Survey on Classical and Machine Learning-Based Methods provides insights into how microgrids can be controlled using different methods. This includes classical and machine learning-based techniques that can be implemented in hierarchical control systems for microgrids. The use of these methods is important in enhancing the stability and reliability of microgrids.

This article is published by MDPI, a company that promotes open access to scientific research. The company focuses on creating an environment where researchers can share their work and ideas without any restrictions. This emphasizes the importance of collaboration to advance research.

The person mentioned in this article is someone who has carried out research on microgrid control using different techniques. The article refers to the person’s survey on classical and machine learning-based methods for controlling microgrids. The contribution of this research is significant in improving the understanding of microgrid systems and their control.

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