Investigation and validation of 3D wake model for horizontal-axis wind turbines based on filed measurements

Xiaoxia Gao, Bingbing Li, Tengyuan Wang, Haiying Sun, Hongxing Yang, Yonghua Li, Yu Wang and Fei Zhao

Applied Energy, 2020, vol. 260, issue C, No S0306261919319592

Abstract: To further investigate the three-dimensional wake profiles for horizontal-axis wind turbines, a three-dimensional Jensen-Gaussian (3DJG) wake model is proposed and validated using field measurement data. The proposed 3DJG model takes the wind shear effect into account and considers the wind speed difference between wind shear inflow and uniform inflow. In addition, the influence of turbulence intensity in wake region on anisotropic wake expansion rate k is also modified. Different from previous ones, this model does not need multiple trial calculations to determine some empirical parameters, such as the wake expansion rate k when predicting the wake profile. The value of k is assigned based on the incoming wind conditions firstly and followed by the wake profile predictions. Performance of the newly proposed 3DJG model is compared and validated with previous models as well as the field measurement data. The corresponding experiment using two ground-based scanning LiDARs was conducted to detect the 3D wake characteristics of horizontal-axis wind turbines in a wind farm located in northern Hebei Province, China. Results show that the 3DJG model has higher accuracies in both horizontal plane and vertical height direction in the prediction of wake profiles. Guidelines for the quantification of turbines’ wake characteristics and model modifications can be provided by this study.

Keywords: 3D wake model; Wind shear effect; Field measurements; Wake characteristics (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (43)

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DOI: 10.1016/j.apenergy.2019.114272

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