In the realm of wind energy, understanding the behavior of wind turbine wakes is crucial for optimizing wind farm performance. A team of researchers from École Normale Supérieure de Lyon, the University of Lyon, and the German Aerospace Center (DLR) has delved into this topic, presenting their findings in a study titled “The spatial organization of wind turbine wakes,” published in the Journal of Renewable and Sustainable Energy.
The researchers, led by Janka Lengyel and Stéphane G. Roux from École Normale Supérieure de Lyon, employed a novel approach to analyze wind turbine wakes using two-dimensional LiDAR scans. Their method, called spatially localized multifractal analysis, quantifies the strength of dependencies and extreme velocity fluctuations in turbine wakes, providing a more nuanced understanding of wake behavior.
The study identified four distinct wake zones, each with unique patterns of roughness and intermittency. These zones were found to emerge 2 to 5 rotor diameters downstream of the turbine. The researchers also observed coherent, strongly correlated patches within the wakes, with intermittency strengthening periodically at multiple positions and along the wake-free-flow interface.
One of the key findings was the redefinition of the classical “intermittency ring” as a set of localized “intermittency bubbles.” These bubbles interact dynamically with the ambient atmosphere through an inverse energy cascade, transferring energy from small to large scales. This finding was supported by concurrent cup anemometer observations under free-inflow conditions.
The practical implications of this research are significant for the wind energy sector. The robust and cost-effective diagnostic framework developed by the researchers can be used for wake characterization and wake-model validation. This, in turn, can directly inform wind-farm design and control, ultimately enhancing the efficiency and output of wind farms.
In summary, this study provides valuable insights into the spatial organization of wind turbine wakes, offering a more detailed understanding of wake behavior and its impact on wind farm performance. The methods and findings presented can be readily applied to improve wind farm design and control strategies, contributing to the advancement of wind energy technology.
This article is based on research available at arXiv.