Experimental investigation on wake characteristics of wind turbine and a new two-dimensional wake model

Xiaoling Liang, Shifeng Fu, Fulin Cai, Xingxing Han, Weijun Zhu, Hua Yang and Wenzhong Shen

Renewable Energy, 2023, vol. 203, issue C, 373-381

Abstract: Wind tunnel experiments are performed to investigate the wake characteristics of a model wind turbine using Particle Image Velocimetry (PIV) and Hot-wire velocimetry. Results show that the velocity deficit at the hub height is the largest, and the stratification of the velocity shear layer at the blade tip is obvious. The instantaneous turbulence kinetic energy (TKE) level is much larger than the mean TKE, especially downstream of the blade tip. In the x/dT=4 position of the wake region, the mean TKE increased by two times due to the blade tip disturbance. The Reynolds stresses also increase and the instantaneous value is the highest along the blade’s tip. A thin vortex band appears at the root and tip of the blade, the vortex core expands and diffuses with the development of the wake along the downstream direction. The two-dimensional distributions of velocity spectra fΦu reveal that the velocity fluctuation at x/dT=2 location is small and that at x/dT=4 position is the largest. Based on Jensen’s wake model, a new theoretical wake model is proposed to predict the velocity distribution in the wind turbine wake. The calculated results of the wake model are in good agreement with the experimental data.

Keywords: Particle Image Velocimetry; Wake characteristics; Turbulence kinetic energy; Vortex; Wake model; Velocity fluctuation (search for similar items in EconPapers)
Date: 2023
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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:203:y:2023:i:c:p:373-381

DOI: 10.1016/j.renene.2022.12.070

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