School of Automotive Engineering, Xiangtan Institute of Technology, Xiangtan 410219, China
| Abstract: | The design theory of wind turbine airfoil is the fundamental factor determining the power characteristics of a wind turbine. By altering geometric parameters such as maximum relative thickness, maximum camber, and leading-edge radius of the airfoil, different geometric shapes and aerodynamic performance of the wind turbine airfoil can be achieved. However, the existing airfoil design methods suffer from low computational efficiency and poor sample convergence, which may result in inadequate aerodynamic performance of the wind turbine airfoil. To address the shortcomings mentioned above, an improved optimization algorithm utilizing a weighted Kriging model is proposed based on the parameterized model of the wind turbine airfoil. Firstly, the weighted Kriging model is combined with a Pareto multi-objective optimization method that incorporates a niche genetic algorithm. This approach utilizes the efficient predictive performance of the weighted Kriging model and the nonlinear numerical processing capability of the Pareto multi-objective optimization method to achieve multi-objective aerodynamic optimization design of the wind turbine airfoil. Secondly, aiming to maximize the lift-to-drag ratio and lift coefficient of the wind turbine airfoil, with constraints on the moment coefficient, maximum relative thickness and its position, as well as the location of the upper surface transition point, a multi-objective aerodynamic optimization design model for a specific relative thickness wind turbine airfoil is established based on the weighted Kriging model and the Pareto multi-objective optimization method. The optimized design results include the improvement of lift-to-drag ratio characteristics by a factor of 2 when considering the optimized angle of attack. Finally, while ensuring the rationality of the wind turbine airfoil structure, recommendations are made to improve its aerodynamic performance. These suggestions provide engineering guidance for enhancing the aerodynamic performance of wind turbine airfoils. |
| Keywords: | Kriging Model; Multi-objective Optimization Design; Aerodynamic Characteristics; Wind Turbine Airfoil |
| DOI: | 10.57237/j.mse.2023.03.001 |
| [1] | 陈进, 张石强, EECEN P J, 等. 风力机翼型参数化表达及收敛特性 [J]. 机械工程学报, 2010, 46 (10): 132-138. |
| [2] | LIU D, LITVINENKO A, SCHILLINGS C, et al. Quantification of airfoil geometry-induced aerodynamic uncertainties comparison of approaches [J]. SIAM/ASA Journal on Uncertainty Quantification, 2017, 5 (1): 334-352. |
| [3] | Papadimitriou D. I, Papadimitriou C. Aerodynamic shape optimization for minimum robust drag and lift reliability constraint [J]. Aerospace Science and Technology, 2016, 55: 24-33. |
| [4] | Ram K R, Lal S P, Ahmed M R. Design and optimization of airfoils and a 20kW wind turbine using multi-objective genetic algorithm and HARP_Opt code [J]. Renewable Energy, 2019, 144: 56-67. |
| [5] | 王迅, 蔡晋生, 屈崑. 基于改进 CST 参数化方法和转捩模型的翼型优化设计 [J]. 航空学报, 2015, 36 (2): 449-461. |
| [6] | Mortazavi S. M, Soltani M. R, Motieyan H. A Pareto optimal multi-objective optimization for a horizontal axis wind turbine blade airfoil sections utilizing exergy analysis and neural networks [J]. Journal of Wind Engineering and Industrial Aerodynamics, 2015, 136: 62-72. |
| [7] | Liu P. Y, Yu G. H, Zhu X. C. Unsteady aerodynamic prediction for dynamic stall of wind turbine airfoils with the reduced order modeling [J]. Renewable Energy, 2014, 69-74. |
| [8] | Chaudhuri A, Haftka R. T, Ifju P. Experimental flapping wing optimization and uncertainty quantification using limited samples [J]. Structural and Multidisciplinary Optimization, 2015, 51 (4): 1-14. |
| [9] | Liu J, Song W. P, Han Z. H. Efficient aerodynamic shape optimization of transonic wings using a parallel infilling strategy and surrogate models [J]. Structural and Multidisciplinary Optimization, 2017, 55 (3): 925-943. |
| [10] | 陈学孔. 低雷诺数翼型气动外形优化设计及其应用 [D]. 长沙: 国防科学技术大学, 2011. |
| [11] | 文泽军, 孟祥恒, 肖钊, 等. 基于数论网格法与Morris法的翼型气动特性敏感性分析 [J]. 工程设计学报, 2022, 42 (4): 1-8. |
| [12] | 王龙, 宋文萍, 许建华. 基于Pareto遗传算法的风力机翼型多点优化设计 [J]. 太阳能学报, 2013, 34 (10): 1685-1689. |
| [13] | Kleijn E. J. Regression and Kriging metamodels with their experimental designs in simulation: a review [J]. European Journal of Operational Research, 2017, 256 (1): 1-16. |
| [14] | 洪星. 基于气动性能与截面刚度特性的风力机翼型廓线设计研究 [D]. 武汉: 湖北工业大学, 2019. |
| [15] | L. O M H. Aerodynamics of Wind Turbines [M]. Taylor and Francis: 2015. |
We invite active, qualified and high profile scientists and researchers to join as Editorial Board Members.
Join UsScholars with a strong interest in reviewing are invited to join the reviewer panel to ensure the quality of the research to be published.
Join Us