Multi-Agent Proximal Policy Optimization for Coordinated Adaptive Control of Photovoltaic Inverter Clusters in Active Distribution Networks

High penetration of distributed photovoltaic (PV) generation has transformed active distribution networks into inverter-dominated systems, where maintaining voltage stability, minimizing power losses, and maximizing renewable utilization under uncertainty remain significant challenges. Conventional...

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Detalles Bibliográficos

Principais autores:	Gongrun Wang, Shumin Sun, Yan Cheng, Peng Yu, Shibo Wang, Xueshen Zhao
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2026-02-01
Series:	Energies
Assuntos:	multi-agent reinforcement learning proximal policy optimization photovoltaic inverter clusters active distribution networks stochastic robust optimization voltage stability and loss minimization
Acceso en liña:	https://www.mdpi.com/1996-1073/19/4/978
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