Enhancing Virtual Inertia Control in Microgrid Clusters: A Novel Frequency Response Model Based on Deep Reinforcement Learning

Traditional control strategies, such as droop-frequency and PI controllers, often show limited adaptability when the system operates under highly variable renewable generation and load conditions. In order to overcome this limitation, this study proposes the design and simulation of a clustered micr...

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Hauptverfasser:	Adrián Criollo, Dario Benavides, Paul Arévalo-Cordero, Danny Ochoa-Correa, Luis I. Minchala-Avila, Marcos Tostado-Véliz
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	MDPI AG 2026-07-01
Schriftenreihe:	Applied Sciences
Schlagworte:	virtual-inertia microgrids-cluster dynamic estimation stability reinforcement learning
Online-Zugang:	https://www.mdpi.com/2076-3417/16/13/6685
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