scholarly journals Parametric dependencies of the yawed wind‐turbine wake development

Wind Energy ◽  
2020 ◽  
Vol 23 (6) ◽  
pp. 1367-1380
Author(s):  
Elektra Kleusberg ◽  
Philipp Schlatter ◽  
Dan S. Henningson
Keyword(s):  
Wind Turbine ◽  
Parametric Dependencies ◽  
Turbine Wake ◽  
Wind Turbine Wake

A REVIEW OF WIND TURBINE WAKE MODELS FOR WIND PARK OPTIMIZATION

2019 ◽  
Author(s):  
Antonio Neiva ◽  
Vanessa Guedes ◽  
Caio Leandro Suzano Massa ◽  
Daniel Davy Bello de Freitas
Keyword(s):  
Wind Turbine ◽  
Wind Park ◽  
Turbine Wake ◽  
Wind Turbine Wake

scholarly journals Advances in large-eddy simulation of a wind turbine wake

2007 ◽  
Vol 75 ◽  
pp. 012041 ◽  
Author(s):  
A Jimenez ◽  
A Crespo ◽  
E Migoya ◽  
J Garcia
Keyword(s):  
Large Eddy Simulation ◽  
Wind Turbine ◽  
Eddy Simulation ◽  
Large Eddy ◽  
Turbine Wake ◽  
Wind Turbine Wake

scholarly journals Utility-Scale Wind Turbine Wake Characterization Using Nacelle-Based Long-Range Scanning Lidar

2014 ◽  
Vol 31 (7) ◽  
pp. 1529-1539 ◽  
Author(s):  
Matthew L. Aitken ◽  
Julie K. Lundquist
Keyword(s):  
Wind Turbine ◽  
Long Range ◽  
Wind Farm ◽  
Thrust Coefficient ◽  
Velocity Deficit ◽  
Scanning Lidar ◽  
Range Scanning ◽  
Utility Scale ◽  
Turbine Wake ◽  
Wind Turbine Wake

Abstract To facilitate the optimization of turbine spacing at modern wind farms, computational simulations of wake effects must be validated through comparison with full-scale field measurements of wakes from utility-scale turbines operating in the real atmosphere. Scanning remote sensors are particularly well suited for this objective, as they can sample wind fields over large areas at high temporal and spatial resolutions. Although ground-based systems are useful, the vantage point from the nacelle is favorable in that scans can more consistently transect the central part of the wake. To the best of the authors’ knowledge, the work described here represents the first analysis in the published literature of a utility-scale wind turbine wake using nacelle-based long-range scanning lidar. The results presented are of a field experiment conducted in the fall of 2011 at a wind farm in the western United States, quantifying wake attributes such as the velocity deficit, centerline location, and wake width. Notable findings include a high average velocity deficit, decreasing from 60% at a downwind distance x of 1.8 rotor diameters (D) to 40% at x = 6D, resulting from a low average wind speed and therefore a high average turbine thrust coefficient. Moreover, the wake width was measured to expand from 1.5D at x = 1.8D to 2.5D at x = 6D. Both the wake growth rate and the amplitude of wake meandering were observed to be greater for high ambient turbulence intensity and daytime conditions as compared to low turbulence and nocturnal conditions.

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