GRL-ITransformer: An Intelligent Method for Multi-Wind-Turbine Wake Analysis Based on Graph Representation Learning With Improved Transformer

The importance of examining the wake effect of wind farms for optimizing their layout and augmenting their power generation efficiency is immense. Considering that the establishment of extensive wind farms often leads to a significant number of turbines being positioned downstream of preceding ones,...

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Veröffentlicht in:	IEEE access Jg. 13; S. 43572 - 43592
Hauptverfasser:	Han, Kang, Xu, Li
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Accuracy Algorithms attention mechanism Data models graph representation learning Graph representations Graphical representations improved transformer Learning Model reduction Neural networks Prediction algorithms Predictive models reduced-order model Representation learning series forecasting algorithm Transformers Wakes Wind effects Wind farms Wind power generation Wind speed Wind turbine wakes Wind turbines
ISSN:	2169-3536, 2169-3536
Online-Zugang:	Volltext
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