Integrated numerical method for the prediction of wind turbine noise and the long range propagation

2010 ◽  
Vol 10 (2) ◽  
pp. S316-S319 ◽  
Author(s):  
Eunkuk Son ◽  
Hyunjung Kim ◽  
Hogeon Kim ◽  
Wooyoung Choi ◽  
Soogab Lee
Keyword(s):  
Wind Turbine ◽  
Numerical Method ◽  
Long Range ◽  
Wind Turbine Noise

Tonality evaluation of wind turbine noise by filter-segmentation

Measurement ◽  
2012 ◽  
Vol 45 (4) ◽  
pp. 711-718 ◽  
Author(s):  
Xiaofeng Liu ◽  
Lin Bo ◽  
Martin Veidt
Keyword(s):  
Wind Turbine ◽  
Wind Turbine Noise

scholarly journals Simplified theory of wind turbine noise

2007 ◽  
Author(s):  
Allan D. Pierce ◽  
Evangelia Kotsaros
Keyword(s):  
Wind Turbine ◽  
Wind Turbine Noise

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.

Long-term exposure to wind turbine noise at night and risk for diabetes: A nationwide cohort study

2018 ◽  
Vol 165 ◽  
pp. 40-45 ◽  
Author(s):  
Aslak Harbo Poulsen ◽  
Ole Raaschou-Nielsen ◽  
Alfredo Peña ◽  
Andrea N. Hahmann ◽  
Rikke Baastrup Nordsborg ◽  
...  
Keyword(s):  
Cohort Study ◽  
Wind Turbine ◽  
Wind Turbine Noise
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