Machine-learning identification of the variability of mean velocity and turbulence intensity for wakes generated by onshore wind turbines: Cluster analysis of wind LiDAR measurements

Wind turbine wakes are the result of the extraction of kinetic energy from the incoming atmospheric wind exerted from a wind turbine rotor. Therefore, the reduced mean velocity and enhanced turbulence intensity within the wake are affected by the characteristics of the incoming wind, turbine blade a...

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Veröffentlicht in:	arXiv.org 2021-09
Hauptverfasser:	G Valerio Iungo, Maulik, Romit, S Ashwin Renganathan, Letizia, Stefano
Format:	Artikel
Sprache:	eng
Schlagworte:	Aerodynamics Algorithms Cluster analysis Clustering Coefficients Datasets Kinetic energy Lidar Machine learning Meteorological data Physics - Atmospheric and Oceanic Physics Physics - Fluid Dynamics Proper Orthogonal Decomposition Rotors Stability Statistical analysis Statistical methods Supervisory control and data acquisition Thrust Turbine blades Turbines Turbulence intensity Velocity Velocity distribution Wind power Wind turbines
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