Abstract

With the rapid growth of wind turbine installation in recent decades, fundamental physical understanding of the flow around wind turbines and farms is becoming increasingly critical for further efficiency increases. However, the effort to develop this understanding is hindered by the significant challenges involved in modelling such a complex dynamic system with a wide range of relevant scales (blade boundary layer thickness at ∼ 1 mm to atmospheric scales at ∼ 1 km). Additionally, conventional methods used to measure air flow around wind turbines in the field (e.g., lidar) are limited by low spatio-temporal resolutions.

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