Deep Reinforcement Learning-Based Control Scheme for Performance Enhancement of PMSG Wind Turbine With Vienna Rectifier

A novel control scheme based on deep reinforcement learning (DRL) is presented to improve the operational performance of a permanent magnet synchronous generator (PMSG) with a Vienna rectifier (PGVR) in a wind turbine generator system. This article investigates the harmonics problem of stator curren...

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Vydané v:	IEEE journal of emerging and selected topics in power electronics Ročník 13; číslo 1; s. 432 - 444
Hlavní autori:	Du, Yucheng, Cai, Bin, Yan, Shaomin, Zhang, Weiyu, Xing, Zida, Qiu, Yalan, Chu, Xiaoguang, Song, Xiaoyu
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Piscataway IEEE 01.02.2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:	Algorithms Control systems Deep learning Deep reinforcement learning (DRL) Fluctuations Harmonic analysis Performance enhancement permanent magnet synchronous generator (PMSG) Permanent magnets Rectifiers Stators Synchronous machines Task analysis Turbogenerators twin delay deep deterministic policy gradient (TD3) Vienna rectifier Wind speed Wind turbines
ISSN:	2168-6777, 2168-6785
On-line prístup:	Získať plný text
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