Accelerating the learning process of deep reinforcement learning algorithms in distribution network reconfiguration using an innovative replay method

Abstract Distribution network reconfiguration (DNR) is one of the most widely employed methods for minimizing distribution network power losses with minimal investment. Most methods used for DNR are based on an accurate model. However, this study employs deep reinforcement learning (DRL), a model-fr...

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出版年:	Scientific Reports
主要な著者:	Amirhossein Ghaemipour, Habib Rajabi Mashhadi, Seyed Hossein Mostafavi
フォーマット:	論文
言語:	英語
出版事項:	Nature Portfolio 2026-03-01
主題:	Distribution network reconfiguration Deep reinforcement learning Experience replay
オンライン･アクセス:	https://doi.org/10.1038/s41598-026-40508-4