Analysis and Modifications of Turbulence Models for Wind Turbine Wake Simulations in Atmospheric Boundary Layers

Author:

Antonini Enrico G. A.1,Romero David A.1,Amon Cristina H.2

Affiliation:

1. Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON M5S 3G8, Canada e-mail:

2. Professor Department of Mechanical and Industrial Engineering, University of Toronto, Toronto, ON M5S 3G8, Canada e-mail:

Abstract

Computational fluid dynamics (CFD) simulations of wind turbine wakes are strongly influenced by the choice of the turbulence model used to close the Reynolds-averaged Navier-Stokes (RANS) equations. A wrong choice can lead to incorrect predictions of the velocity field characterizing the wind turbine wake and, consequently, to an incorrect power estimation for wind turbines operating downstream. This study aims to investigate the influence of different turbulence models, namely the k–ε, k–ω, SSTk–ω, and Reynolds stress models (RSM), on the results of CFD wind turbine simulations. Their influence was evaluated by comparing the CFD results with the publicly available experimental measurements of the velocity field and turbulence quantities from the Sexbierum and Nibe wind farms. Consistent turbulence model constants were proposed for atmospheric boundary layer (ABL) and wake flows according to previous literature and appropriate experimental observations, and modifications of the derived turbulence model constants were also investigated in order to improve agreement with experimental data. The results showed that the simulations using the k–ε and k–ω turbulence models consistently overestimated the velocity and turbulence quantities in the wind turbine wakes, whereas the simulations using the shear-stress transport (SST) k–ω and RSMs could accurately match the experimental data. Results also showed that the predictions from the k–ε and k–ω turbulence models could be improved by using the modified set of turbulence coefficients.

Publisher

ASME International

Subject

Energy Engineering and Power Technology,Renewable Energy, Sustainability and the Environment

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