DOI: https://doi.org/10.14710/ijred.7.3.213-222

Effects of turbulence models and grid densities on computational accuracy of flows over a vertical axis wind turbine

School of Mechanical Engineering, Suranaree University of Technology. 111 University Avenue, Suranaree Sub-District, Muang Nakhon Ratchasima District, Nakhon Ratchasima 30000, Thailand

Published: 15 Dec 2018.
Editor(s): H Hadiyanto

Citation Format:
Abstract

Flows through a vertical axis wind turbine (VAWT) are very complex due to their inherent unsteadiness caused by large variations of the angle of attacks as the turbine is rotating and changing its azimuth angles simultaneously. In addition, a turbine must go through a wide range of operating conditions especially the change in blade speed ratio (BSR). Accurate prediction of flows over VAWT using Reynolds-Averaged Navier-Stokes (RANS) model needs a well-tested turbulence model as well as a careful grid control around the airfoil. This paper aimed to compare various turbulence models and seek the most accurate one. Furthermore, grid convergence was studied using the Roache method to determine the sufficient number of grid elements around the blade section. The three-dimensional grid was generated by extrution from the two-dimensional grid along with the appropriate y+ controlling. Comparisons were made among the three turbulence models that are widely used namely: the RNG model, the shear stress transport k-ω model (SST) and the Menter’s shear stress transport k-ω model (transition SST). Results obtained clearly showed that turbulence models significantly affected computational accuracy. The SST turbulence model showed best agreement with reported experimental data at BSR lower than 2.35, while the transition SST model showed better results when BSR is higher than 2.35. In addition, grid extruding technique with y+ control could reduce total grid requirement while maintaining acceptable prediction accuracy.

Article History: Received April 15th 2018; Received in revised form June 16th 2018; Accepted September 17th 2018; Available online

How to Cite This Article: Chaiyanupong,J and Chitsomboon, T. (2018) Effects of Turbulence Models and Grid Densities on Computational Accuracy of Flows Over a Vertical Axis Wind Turbine. Int. Journal of Renewable Energy Development, 7(3), 213-222.

http://dx.doi.org/10.14710/ijred.7.3.213-222

 

Fulltext View|Download
Keywords: VAWT; CFD; Aerodynamic; Turbulence model; Wind turbine; Vertical axis
Funding: The Royal Golden Jubilee Ph.D. Programm of The Thailand Research Fund (TRF)

Article Metrics:

Article Info
Section: Original Research Article
Language : EN
Recent articles
Optimal operating scenario for Polerood hydropower station to maximize peak shaving and produced profit Comparison between conventional design and cathode gas recirculation design of a direct-syngas solid oxide fuel cell–gas turbine hybrid systems part II: Effect of temperature difference at the fuel cell stack Aerodynamic analysis of backward swept in HAWT rotor blades using CFD More recent articles
Most cited articles
Electricity from Wind for Off-Grid Applications in Bangladesh: A Techno-Economic Assessment Preliminary Investigation on Generation of Electricity Using Micro Wind Turbines Placed on A Car Generating Organic Liquid Products from Catalytic Cracking of Used Cooking Oil over Mechanically Mixed Catalysts Investigating the effect of DG infeed on the effective cover of distance protection scheme in mixed-MV distribution network Modeling Operation Problem of Micro-grids Considering Economical, Technical and Environmental issues as Mixed-Integer Non-Linear Programming More cited articles
  1. Almohammadi, K. M., Ingham, D. B., Ma, L., & Pourkashanian, M. (2015). Modeling dynamic stall of a straight blade vertical axis wind turbine. Journal of Fluids and Structures, 57, 144-158
  2. Chowdhury, A. M., Akimoto, H., & Hara, Y. (2016). Comparative CFD analysis of vertical axis wind turbine in upright and tilted configuration. Renewable Energy, 85, 327-337
  3. Fujisawa, N., & Shibuya, S. (2001). Observations of dynamic stall on Darrieus wind turbine blades. Journal of Wind Engineering and Industrial Aerodynamics, 89(2), 201-214
  4. Graham, G. M. (1982). Measurement of instantaneous pressure distributions and blade forces on an airfoil undergoing cycloidal motion (Doctoral dissertation, Texas Tech University)
  5. Howell, R., Qin, N., Edwards, J., & Durrani, N. (2010). Wind tunnel and numerical study of a small vertical axis wind turbine. Renewable energy, 35(2), 412-422
  6. Jones, W. P., & Launder, B. (1972). The prediction of laminarization with a two-equation model of turbulence. International journal of heat and mass transfer, 15(2), 301-314
  7. Mccullough, G. B., & Gault, D. E. (1951). Examples of three representative types of airfoil-section stall at low speed
  8. Menter, F. L. O. R. I. A. N. R. (1993, July). Zonal two equation kw turbulence models for aerodynamic flows. In 23rd fluid dynamics, plasmadynamics, and lasers conference (p. 2906)
  9. Menter, F. R. (1994). Two-equation eddy-viscosity turbulence models for engineering applications. AIAA journal, 32(8), 1598-1605
  10. Menter, F. R., Kuntz, M., & Langtry, R. (2003). Ten years of industrial experience with the SST turbulence model. Turbulence, heat and mass transfer, 4(1), 625-632
  11. Menter, F. R., Langtry, R. B., Likki, S. R., Suzen, Y. B., Huang, P. G., & Völker, S. (2006). A correlation-based transition model using local variables—Part I: model formulation. Journal of turbomachinery, 128(3), 413-422
  12. Nobile, R., Vahdati, M., Barlow, J. F., & Mewburn-Crook, A. (2013, July). Unsteady flow simulation of a vertical axis wind turbine: a two-dimensional study. In EngD Conference, 2nd July
  13. Nobile, R., Vahdati, M., Barlow, J. F., & Mewburn-Crook, A. (2014). Unsteady flow simulation of a vertical axis augmented wind turbine: A two-dimensional study. Journal of Wind Engineering and Industrial Aerodynamics, 125, 168-179
  14. Oler, J. W., Strickland, J. H., Im, B. J., & Graham, G. H. (1983). Dynamic-stall regulation of the Darrieus turbine
  15. Graham, Gary M. Measurement of instantaneous pressure distributions and blade forces on an airfoil undergoing cycloidal motion. Diss. Texas Tech University, 1982
  16. Paraschivoiu, I. (2002). Wind turbine design: with emphasis on Darrieus concept
  17. Paraschivoiu, M., Komeili, M., & Zadeh, S. N. (2014). Mesh convergence study for 2-d straight-blade vertical axis wind turbine simulations and estimation for 3-d simulations. Transactions of the Canadian Society for Mechanical Engineering,, 38(4)
  18. Roache, P. J. (1998). Verification and validation in computational science and engineering (Vol. 895). Albuquerque, NM: Hermosa
  19. Spalart, P., & Allmaras, S. (1992, January). A one-equation turbulence model for aerodynamic flows. In 30th aerospace sciences meeting and exhibit (p. 439)
  20. Wilcox, D. C. (1993). Comparison of two-equation turbulence models for boundary layers with pressure gradient. AIAA journal, 31(8), 1414-1421
  21. Orszag, Steven A., et al. "Renormalization group modeling and turbulence simulations." Near-wall turbulent flows (1993): 1031-1046
  22. Wilcox, D. C. (1993). Turbulence modeling for CFD

Last update:

  1. Analytical and Numerical Solution for H-type Darrieus Wind Turbine Performance at the Tip Speed Ratio of Below One

    Pedram Ghiasi, Gholamhassan Najafi, Barat Ghobadian, Ali Jafari. International Journal of Renewable Energy Development, 10 (2), 2021. doi: 10.14710/ijred.2021.33169

  2. CFD-Study of the H-Rotor Darrius wind turbine performance in Drag-Lift and lift Regime: Impact of Type, thickness and chord length of blades

    Pedram Ghiasi, Gholamhassan Najafi, Barat Ghobadian, Ali Jafari, Rizalman Mamat, Mohd Fairusham Ghazali. Alexandria Engineering Journal, 67 , 2023. doi: 10.1016/j.aej.2022.10.013

Last update: 2024-11-21 06:08:06

  1. Analytical and Numerical Solution for H-type Darrieus Wind Turbine Performance at the Tip Speed Ratio of Below One

    Pedram Ghiasi, Gholamhassan Najafi, Barat Ghobadian, Ali Jafari. International Journal of Renewable Energy Development, 10 (2), 2021. doi: 10.14710/ijred.2021.33169