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

[+] Author Affiliations
Enrico G. A. Antonini, David A. Romero, Cristina H. Amon

University of Toronto, Toronto, ON, Canada

Paper No. IMECE2016-67353, pp. V06BT08A062; 12 pages
  • ASME 2016 International Mechanical Engineering Congress and Exposition
  • Volume 6B: Energy
  • Phoenix, Arizona, USA, November 11–17, 2016
  • Conference Sponsors: ASME
  • ISBN: 978-0-7918-5059-6
  • Copyright © 2016 by ASME


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 on the results of CFD wind turbine simulations. In particular, the k–ε, k–ω, SSTk–ω, and Reynolds stress models are used to close the RANS equations and their influence on the CFD simulations is evaluated from the flow field generated downstream a stand-alone wind turbine. The assessment of the turbulence models was conducted by comparing the CFD results with publicly available experimental measurements of the flow field from the Sexbierum wind farm. Consistent turbulence model constants were proposed for atmospheric boundary layer and wake flows according to previous literature and appropriate experimental observations. 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 in the wind turbine wakes. On the other hand, the simulations using the SSTk–ω and Reynolds stress models could accurately capture the velocity in the wake of the wind turbine. 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.

Copyright © 2016 by ASME



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