LAPSE:2023.14001v1
Published Article

LAPSE:2023.14001v1
Large-Eddy Simulation of Wakes of Waked Wind Turbines
March 1, 2023
Abstract
The wake dynamics of a wind turbine are influenced by the atmospheric turbulence and the wake of its upwind turbine. In this work, we investigate the wake characteristics of a waked wind turbine for four different downwind spacings and three different inflows using large-eddy simulation with a turbine parameterized using the actuator surface model. The wake statistics of the waked turbine are compared with those of the stand-alone wind turbine under the same inflow. The results show that the oncoming wake significantly affects the near wake of the waked turbine, where it accelerates the wake recovery by increasing the turbulent convection, and increases the turbulence kinetic energy. The velocity deficit and turbulence kinetic energy in the far wake, on the other hand, are fairly similar with each other for the considered different turbine spacings, and are close to those of the stand-alone wind turbine. As for the wake meandering of the waked wind turbines, it is initiated quickly and enhanced by the oncoming wake turbulence, as shown by the meandering amplitudes and the power spectral density of the instantaneous wake positions. The growth rates of the wake meandering from the waked wind turbines, on the other hand, are close to that of the stand-alone wind turbine, indicating the critical role of the atmospheric turbulence on wake meandering. The present work details how the oncoming wake influences the wake dynamics of the downwind turbine, and provides physical insights on developing engineering models to take into account such effects.
The wake dynamics of a wind turbine are influenced by the atmospheric turbulence and the wake of its upwind turbine. In this work, we investigate the wake characteristics of a waked wind turbine for four different downwind spacings and three different inflows using large-eddy simulation with a turbine parameterized using the actuator surface model. The wake statistics of the waked turbine are compared with those of the stand-alone wind turbine under the same inflow. The results show that the oncoming wake significantly affects the near wake of the waked turbine, where it accelerates the wake recovery by increasing the turbulent convection, and increases the turbulence kinetic energy. The velocity deficit and turbulence kinetic energy in the far wake, on the other hand, are fairly similar with each other for the considered different turbine spacings, and are close to those of the stand-alone wind turbine. As for the wake meandering of the waked wind turbines, it is initiated quickly and enhanced by the oncoming wake turbulence, as shown by the meandering amplitudes and the power spectral density of the instantaneous wake positions. The growth rates of the wake meandering from the waked wind turbines, on the other hand, are close to that of the stand-alone wind turbine, indicating the critical role of the atmospheric turbulence on wake meandering. The present work details how the oncoming wake influences the wake dynamics of the downwind turbine, and provides physical insights on developing engineering models to take into account such effects.
Record ID
Keywords
actuator surface model, large-eddy simulation, waked turbine, wind turbine wakes
Subject
Suggested Citation
Liu X, Li Z, Yang X, Xu D, Kang S, Khosronejad A. Large-Eddy Simulation of Wakes of Waked Wind Turbines. (2023). LAPSE:2023.14001v1
Author Affiliations
Liu X: The State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China; School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
Li Z: The State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China; School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
Yang X: The State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China; School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing 100049, China [ORCID]
Xu D: The State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China; School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
Kang S: Civil and Environmental Engineering Department, Hanyang University, Seoul 133791, Korea
Khosronejad A: Civil Engineering Department, Stony Brook University, Stony Brook, NY 11794, USA [ORCID]
Li Z: The State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China; School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
Yang X: The State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China; School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing 100049, China [ORCID]
Xu D: The State Key Laboratory of Nonlinear Mechanics, Institute of Mechanics, Chinese Academy of Sciences, Beijing 100190, China; School of Engineering Sciences, University of Chinese Academy of Sciences, Beijing 100049, China
Kang S: Civil and Environmental Engineering Department, Hanyang University, Seoul 133791, Korea
Khosronejad A: Civil Engineering Department, Stony Brook University, Stony Brook, NY 11794, USA [ORCID]
Journal Name
Energies
Volume
15
Issue
8
First Page
2899
Year
2022
Publication Date
2022-04-15
ISSN
1996-1073
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PII: en15082899, Publication Type: Journal Article
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LAPSE:2023.14001v1
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https://doi.org/10.3390/en15082899
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