Adaptive neuro-fuzzy generalization of wind turbine wake added turbulence models

2014 ◽  
Vol 36 ◽  
pp. 270-276 ◽  
Author(s):  
Shahaboddin Shamshirband ◽  
Dalibor Petković ◽  
Nor Badrul Anuar ◽  
Abdullah Gani
2008 ◽  
Vol 32 (5) ◽  
pp. 459-475 ◽  
Author(s):  
A. Duckworth ◽  
R.J. Barthelmie

This article discusses the application of widely used, state of the art, wake models, focusing on the Ainslie [1], Katic [2] and Larsen [3] models, breaking these down and explaining the individual, integral components. Models used to predict the turbulence intensity within the wake are also explained. Measured data are subsequently used to validate these wake and turbulence models, showing acceptable results for the prediction of velocity deficit within the wake, wake width and wake shape. Results also highlight the validity of the analysed turbulence models. The paper describes the problems encountered when using measured data to validate wake models and concludes by outlining subsequent work which could be carried out to further validate these models.


Author(s):  
Shahaboddin Shamshirband ◽  
Dalibor Petković ◽  
Roslan Hashim ◽  
Shervin Motamedi ◽  
Nor Badrul Anuar

Author(s):  
Enrico G. A. Antonini ◽  
David A. Romero ◽  
Cristina H. Amon

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.


2018 ◽  
Vol 140 (3) ◽  
Author(s):  
Enrico G. A. Antonini ◽  
David A. Romero ◽  
Cristina H. Amon

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.


2015 ◽  
Vol 45 ◽  
pp. 1-6 ◽  
Author(s):  
Eiman Tamah Al-Shammari ◽  
Mohsen Amirmojahedi ◽  
Shahaboddin Shamshirband ◽  
Dalibor Petković ◽  
Nenad T. Pavlović ◽  
...  

Author(s):  
Peng Zhou ◽  
Xiuling Wang

This research focuses on the computational fluid dynamics simulation of near wind turbine wake. Three dimensional wind turbine model is built based on S809 airfoil data [1]. Three different turbulence models are used and compared. They are Realizable k-ε model, SST k-ω model, and Large Eddy Simulation (LES) model. The simulation results from different turbulence models are compared with the NREL Phase VI experiment data. Different boundary conditions, including neutral and unstable conditions, were adopted in the simulation to analyze their influence on wake flow. Updraft and downdraft are considered in this part. Overall numerical results match well with the experiment data. The discussion also compares wind turbine wake under different atmospheric boundary conditions.


2018 ◽  
Vol 61 ◽  
pp. 95 ◽  
Author(s):  
Eiman Tamah Al-Shammari ◽  
Mohsen Amirmojahedi ◽  
Shahaboddin Shamshirband ◽  
Dalibor Petković ◽  
NenadT. Pavlović ◽  
...  

Author(s):  
Antonio Neiva ◽  
Vanessa Guedes ◽  
Caio Leandro Suzano Massa ◽  
Daniel Davy Bello de Freitas

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