An Engineering Approach to Improve Performance Predictions for Wind Turbine Applications: Comparison with Full Navier-Stokes Model and Experimental Measurements

Document Type : Regular Article

Authors

1 Laboratory of Green and Mechanical Development (LGMD), National Polytechnic School -ENP-, P.B. 182 El-Harrach, Algiers, 16200, Algeria

2 Department of Civil Engineering, University of Ferhat Abbas-Setif 1, Route de Bejaia, Setif, Algeria

3 Department of Mechanical Engineering, University of Sherbrooke, 2500 Boulevard de l’Université, Sherbrooke (QC) J1K2R1, Canada

10.47176/jafm.17.7.2404

Abstract

Accurate predictions of aerodynamic performance and near wake expansion around Horizontal Axis Wind Turbine (HAWT) rotors is pivotal for studying wind turbine wake interactions and optimizing wind farm layouts. This study introduces a novel engineering model centered on stall delay correction to enhance the precision of the Actuator Disk Method (ADM) predictions in both aerodynamic performance and near wake expansion around HAWT rotors. The model is developed based on a comprehensive study of the 3D lift coefficient evolution over the rotor blade, incorporating a shift parameter that considers both stall angle detection and radial decrement. The proposed approach demonstrates remarkable agreements, showcasing discrepancies as low as 7% for both loads and axial wake predictions. These quantifiable results underscore the effectiveness of the model in capturing intricate aerodynamic phenomena. Looking forward, the success of this approach opens avenues for broader applications, guiding future research in wind energy towards improved simulation accuracy and optimized wind farm designs. 

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AbdelSalam, A. M., & Ramalingam, V. (2014). Wake prediction of horizontal-axis wind turbine using full-rotor modeling. Journal of Wind Engineering and Industrial Aerodynamics 124, 7–19. https://doi.org/10.1016/j.jweia.2013.11.005
Amini, S., Golzarian, M. R., Mahmoodi, E., Jeromin, A., & Abbaspour-Fard, M. H. (2021). Numerical simulation of the mexico wind turbine using the actuator disk model along with the 3d correction of aerodynamic coefficients in openfoam. Renewable Energy, 163, 2029–2036. https://doi.org/10.1016/j.renene.2020.10.120
Boorsma, K., & Schepers, J. (2016). Rotor experiments in controlled conditions continued: New mexico. Journal of Physics: Conference Series, 753, 022004. https://doi.org/10.1088/1742-6596/753/2/022004
Bouhelal, A., Ladjal, A., & Smaili, A. (2023a). Blade element momentum theory coupled with machine learning to predict wind turbine aerodynamic performances. AIAA SCITECH 2023 Forum. https://doi.org/10.2514/6.2023-1153
Bouhelal, A., Smaili, A., Masson, C., & Guerri, O. (2017). Comparison of BEM and full Navier-Stokes CFD methods for prediction of aerodynamics performance of HAWT rotors. In 2017 International Renewable and Sustainable Energy Conference (IRSEC) (pp. 1-6). IEEE. https://doi.org/10.1109/icweaa.2018.8605050
Bouhelal, A., Smaili, A., Guerri, O., & Masson, C. (2018a). Numerical investigation of turbulent flow around a recent horizontal axis wind turbine using low and high Reynolds models. Journal of Applied Fluid Mechanics 11(1), 151–164. https://doi.org/10.29252/JAFM.11.01.28074
Bouhelal, A., Smaili, A., Guerri, O., & Masson, C. (2023b). Numerical investigations on the fluid behavior in the near wake of an experimental wind turbine model in the presence of the nacelle. Journal of Applied Fluid Mechanics 16(1), 21–33. https://doi.org/10.47176/jafm.16.01.1382
Bouhelal, A., Guerri, O., Smaili, A., & Masson, C. (2018b). Contribution to the aerodynamic study of the air-sand flow around a wind turbine blade installed in desert environment of algeria. 2018 International Conference on Wind Energy and Applications in Algeria (ICWEAA), IEEE. https://doi.org/10.1109/ICWEAA.2018.8605050
Breton, S. P., Coton, F. N., & Moe, G. (2008). A study on rotational effects and different stall delay models using a prescribed wake vortex scheme and nrel phase vi experiment data. Wind Energy, 11(5), 459–482. https://doi.org/10.1002/we.269
Chaviaropoulos, P. K., & Hansen, M. O. L. (2000). Investigating three-dimensional and rotational effects on wind turbine blades by means of a Quasi-3D navier-stokes solver. Journal of Fluids Engineering, 122(2), 330–336. https://doi.org/10.1115/1.483261
Choi, N. J., Hyun Nam, S., Hyun Jeong, J., & Chun Kim, K. (2013). Numerical study on the horizontal axis turbines arrangement in a wind farm: Effect of separation distance on the turbine aerodynamic power output. Journal of Wind Engineering and Industrial Aerodynamics, 117, 11–17. https://doi.org/10.1016/j.jweia.2013.04.005
Conway, J. T. (1998). Exact actuator disk solutions for non-uniform heavy loading and slipstream contraction. Journal of Fluid Mechanics, 365, 235–267. https://doi.org/10.1017/s0022112098001372
Dobrev, I., Massouh, F., & Rapin, M. (2007). Actuator surface hybrid model. Journal of Physics: Conference Series, IOP Publishing. https://doi.org/10.1088/1742-6596/75/1/012019
Du, Z., & Selig, M. (1998). A 3-d stall-delay model for horizontal axis wind turbine performance prediction. 1998 ASME Wind Energy Symposium. https://doi.org/10.2514/6.1998-21
Dumitrescu, H., & Cardos, V. (2009). Inboard boundary layer state on wind turbine blades. ZAMM-Journal of Applied Mathematics and Mechanics: Applied Mathematics and Mechanics, 89(3), 163–173. https://doi.org/10.1002/zamm.200800105
Greenshields, C. J., et al. (2015). Openfoam user guide. OpenFOAM Foundation Ltd, version, 3(1), 47. https://doi.org/10.51560/ofj.v1.26
Guntur, S., & Sørensen, N. (2013). A detailed study of the rotational augmentation and dynamic stall phenomena for wind turbines [PhD thesis, Technical Univ. of Denmark], Lyngby, Denmark.
Hamlaoui, M. N., Smaili, A., & Fellouah, H. (2018). Improved bem method for hawt performance predictions. 2018 International Conference on Wind Energy and Applications in Algeria (ICWEAA), IEEE. https://doi.org/10.1109/icweaa.2018.8605096
Hamlaoui, M. N., Smaili, A., & Fellouah, H. (2021b). New stall delay approach for hawt performance predictions using a cfd hybrid method. AIAA Scitech Forum. https://doi.org/10.2514/6.2021-0951
Hamlaoui, M., Smaili, A., & Fellouah, H. (2021a). Improved stall delay model for hawt performance predictions using 3d navier-stokes solver and actuator disk method. Journal of Applied Fluid Mechanics 15(1), 37–50. https://doi.org/10.47176/jafm.15.01.32651
Hamlaoui, M., Smaili, A., Dobrev, I., Pereira, M., Fellouah, H., & Khelladi, S. (2022). Numerical and experimental investigations of hawt near wake predictions using particle image velocimetry and actuator disk method. Energy, 238, 121660. https://doi.org/10.1016/j.energy.2021.121660
IRENA. (2019). Future of wind: Deployment, investment, technology, grid integration and socio-economic aspects. International Renewable Energy Agency, Abu Dhabi. https://doi.org/10.20508/ijrer.v9i3.9741.g7722
Lindenburg, C. (2004). Modelling of rotational augmentation based on engineering considerations and measurements. European Wind Energy Conference, London. pp. 22–25.
Masson, C., Smaili, A., & Leclerc, C. (2001). Aerodynamic analysis of hawts operating in unsteady conditions. Wind Energy, 4(1), 1– 22. https://doi.org/10.1002/we.43
Narramore, J., & Vermeland, R. (1992). Navierstokes calculations of inboard stall delay due to rotation. Journal of Aircraft, 29(1), 73–78. https://doi.org/10.2514/3.46127
Patankar, S. (2018). Numerical heat transfer and fluid flow. Taylor & Francis. https://doi.org/10.1201/9781482234213
Ramesh Kumar, K., & Selvaraj, M. (2023). Investigations on integrated funnel, fan and diffuser augmented unique wind turbine to enhance the wind speed. Journal of Applied Fluid Mechanics, 16(3), 575-589. https://doi.org/10.47176/jafm.16.03.1498
Rehman, S., Alam, M., Alhems, L. M., Rafique, M. M., et al. (2018). Horizontal axis wind turbine blade design methodologies for efficiency enhancement—a review. Energies, 11(3), 506. https://doi.org/10.3390/en11030506
Rhodes, C. J. (2016). The 2015 paris climate change conference: Cop21. Science Progress, 99(1), 97–104. https://doi.org/10.3184/003685016x14528569315192
Schepers, J., Boorsma, K., & Munduate, X. (2014). Final results from mexnext-i: Analysis of detailed aerodynamic measurements on a 4.5 m diameter rotor placed in the large german dutch wind tunnel dnw. Journal of Physics: Conference Series. IOP Publishing. https://doi.org/10.1088/1742-6596/555/1/012089
Shen, W. Z., Mikkelsen, R., Sørensen, J. N., & Bak, C. (2005). Tip loss corrections for wind turbine computations. Wind Energy, 8(4), 457–475. https://doi.org/10.1002/we.153
Snel, H. (2003). Review of aerodynamics for wind turbines. Wind Energy: An International Journal for Progress and Applications in Wind Power Conversion Technology, 6(3), 203–211. https://doi.org/10.1002/we.97
Snel, H., Houwink, R., Bosschers, J., et al. (1994). Sectional prediction of lift coefficients on rotating wind turbine blades in stall. Netherlands Energy Research Foundation Petten, Netherlands.
Sørensen, J. N., & Myken, A. (1992). Unsteady actuator disc model for horizontal axis wind turbines. Journal of Wind Engineering and Industrial Aerodynamics, 39(1-3), 139–149. https://doi.org/10.1016/0167-6105(92)90540-Q
Stevens, R. J., Mart´ınez-Tossas, L. A., & Meneveau, C. (2018). Comparison of wind farm large eddy simulations using actuator disk and actuator line models with wind tunnel experiments. Renewable Energy, 116, 470 – 478. https://doi.org/10.1016/j.renene.2017.08.072
Sturge, D., Sobotta, D., Howell, R., While, A., & Lou, J. (2015). A hybrid actuator disc – full rotor cfd methodology for modelling the effects of wind turbine wake interactions on performance. Renewable Energy, 80, 525– 537. https://doi.org/10.1016/j.renene.2015.02.053
Tian, L., Song, Y., Zhao, N., Shen, W., Zhu, C., & Wang, T. (2020). Effects of turbulence modelling in ad/rans simulations of single wind tidal turbine wakes and double wake interactions. Energy, 208, 118440. https://doi.org/10.1016/j.energy.2020.118440
Yakhot, V., & Orszag, S. A. (1986). Renormalization group analysis of turbulence. i. basic theory. Journal of Scientific Computing, 1(1), 3–51. https://doi.org/10.1007/bf01061452