Condition monitoring and performance forecasting of wind turbines based on denoising autoencoder and novel convolutional neural networks

With the proportion of wind power in the grid increasing, the monitoring and maintenance of wind turbines is becoming more and more important for the reliability of the grid. In this study, a data-driven modelling framework based on deep convolutional neural networks is constructed for wind turbines...

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Veröffentlicht in:	Energy reports Jg. 7; S. 6354 - 6365
Hauptverfasser:	Jia, Xiongjie, Han, Yang, Li, Yanjun, Sang, Yichen, Zhang, Guolei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Elsevier Ltd 01.11.2021 Elsevier
Schlagworte:	Condition monitoring Denoising autoencoder Performance forecasting Residual attention module Wind turbine Condition monitoring Performance forecasting Denoising autoencoder Residual attention module Wind turbine
ISSN:	2352-4847, 2352-4847
Online-Zugang:	Volltext
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