Decentralized Voltage and Var Control of Active Distribution Network Based on Parameter-Sharing Deep Reinforcement Learning

This work introduces a Parameter Sharing - twin-delay deep deterministic policy gradient (PS-TD3) method for carrying out decentralized voltage and var control in active distribution networks. The more renewable energies are integrated, the more Active Distribution Networks (ADNs) are at risk of ins...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE access Jg. 13; S. 115090 - 115101
Hauptverfasser:	Zhang, Binqiao, He, Changlin
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Aerospace electronics Biological system modeling Costs Deep reinforcement learning Distribution networks Energy storage Inverters Machine learning Neural networks Optimization techniques parameter sharing Parameters Photovoltaic cells Reactive power Static VAr compensators twin-delay deep deterministic policy gradient algorithm Voltage and var control (VVC) Voltage control voltage regulation Voltage stability Wind power
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!