Computational Fluid Dynamics (CFD) Investigation of NREL Phase VI Wind Turbine Performance Using Various Turbulence Models

被引:0
|
作者
Al-Ttowi, Abobakr [1 ]
Mohammed, Akmal Nizam [2 ]
Al-Alimi, Sami [3 ]
Zhou, Wenbin [4 ]
Saif, Yazid [5 ]
Ismail, Iman Fitri [6 ]
机构
[1] Univ Tun Hussein Onn Malaysia UTHM, Fac Mech & Mfg Engn, Parit Raja 86400, Malaysia
[2] Univ Tun Hussein Onn Malaysia UTHM, Ctr Energy & Ind Environm Studies, Parit Raja 86400, Malaysia
[3] Univ Tun Hussein Onn Malaysia UTHM, Adv Mfg & Mat Ctr SMARTAMMC, Sustainable Mfg & Recycling Technol, Parit Raja 86400, Malaysia
[4] Univ Dundee, Sch Sci & Engn, Dundee DD1 4HN, Scotland
[5] Univ Tun Hussein Onn Malaysia UTHM, Inst Integrat Engn, Adv Mat & Mfg Ctr AMMC, Parit Raja 86400, Malaysia
[6] Univ Tun Hussein Onn Malaysia UTHM, Fac Mech & Mfg Engn, Combust Res Grp CRG, Parit Raja 86400, Malaysia
关键词
CFD; wind turbine; wake effect; Gaussian model; turbulence models; PREDICTION; SIMULATION;
D O I
10.3390/pr12091994
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
This study presents a detailed computational fluid dynamics (CFD) investigation into the aerodynamic performance of the NREL Phase VI wind turbine, focusing on torque and power generation under different turbulence models. The primary objective was to analyse the effect of various turbulence models and their responses in wind turbine torque generation. Furthermore, it also investigates the distance effect on wind velocity deficit. The research utilizes 2D and 3D simulations of the S809 airfoil and the full rotor, examining the predictive capabilities of the k-epsilon, k-omega, and k-omega SST turbulence models. The study incorporates both experimental validation and wake analysis using the Gaussian wake model to assess wind velocity deficits. Simulations were conducted for a wind speed range of (6-10 m/s), with results indicating that the k-epsilon model provided the closest match to experimental data, particularly at higher wind speeds within the targeted range. Even though k-epsilon results had better agreement when validated with experimental data, theoretically k-omega (SST) should perform better as it combines k-epsilon and k-omega advantages in predicting the flow regardless of its farness from the wall. However, in simulations using the k-omega (SST), the separation of flow and the shear stress transients were only visible at wind speeds of 10 m/s or higher. Wake effects, on the other hand, were found to cause significant velocity deficits behind the turbine, following an exponential decay pattern. The findings offer valuable insights into improving wind turbine performance through turbulence model selection and wake impact analysis, providing practical guidelines for future wind energy optimizations.
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页数:23
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