风力机抗结冰翼型气动外形多步优化设计

邢天宇; 王骥飞; 董芝良; 薛滂

doi:10.19912/j.0254-0096.tynxb.2024-0334

PDF(2313 KB)

太阳能学报 ›› 2025, Vol. 46 ›› Issue (7) : 336-345. DOI: 10.19912/j.0254-0096.tynxb.2024-0334

第二十七届中国科协年会学术论文

风力机抗结冰翼型气动外形多步优化设计

邢天宇^1,2, 王骥飞^1,2, 董芝良^1,2, 薛滂^1,2

作者信息 +

MULTI-STEP OPTIMIZATION DESIGN OF AERODYNAMIC SHAPE FOR ANTI-ICING WIND TURBINE AIRFOILS

Xing Tianyu^1,2, Wang Jifei^1,2, Dong Zhiliang^1,2, Xue Pang^1,2

Author information +

文章历史 +

摘要

风资源丰富地区运行的风力机叶片易结冰,因此需在风力机叶片气动外形设计中着重考虑防冰性能。对风力机S809翼型开展多步抗结冰气动外形优化设计,减少翼型因结冰产生的气动性能损失。首先快速进行全局寻优得到初步优化翼型,再以初步优化翼型为基础进行局部精细优化。因精细优化中结冰模拟所需时间过长,加入代理模型替代数值模拟提高优化效率。优化获得了在结冰前后都具有良好气动性能的翼型,与原准翼型对比,优化后翼型具有较大的前缘半径,且压力面变厚、吸力面变薄。优化翼型结冰后气动性能损失从原始翼型的7.6%降低到1.74%,证明可借助优化设计手段获得抗结冰翼型。

Abstract

The high altitude and low temperature in areas with abundant wind resources can easily cause wind turbine blades to freeze. Therefore, it is necessary to focus on anti icing performance in the aerodynamic design of wind turbine blades. This article presents a multi-step aerodynamic shape optimization design for the S809 wind turbine airfoil to reduce aerodynamic performance losses caused by icing. Firstly, quickly conduct global optimization to obtain a preliminary optimized airfoil, and then conduct local fine optimization based on the preliminary optimized airfoil. Due to the long time required for ice simulation in fine optimization, the addition of surrogate models to replace numerical simulations improves optimization efficiency. The optimized airfoil has achieved good aerodynamic performance both before and after icing. Compared with the baseline quasi airfoil, the optimized airfoil has a larger leading-edge radius, thicker pressure surface, and thinner suction surface. The aerodynamic performance loss of the optimized airfoil after icing has been reduced from 7.6% of the original airfoil to 1.74%, proving that anti icing airfoils can be obtained through optimization design methods, providing ideas for optimizing the anti icing design of wind turbine blade airfoils.

导出引用

邢天宇, 王骥飞, 董芝良, 薛滂. 风力机抗结冰翼型气动外形多步优化设计[J]. 太阳能学报. 2025, 46(7): 336-345 https://doi.org/10.19912/j.0254-0096.tynxb.2024-0334

Xing Tianyu, Wang Jifei, Dong Zhiliang, Xue Pang. MULTI-STEP OPTIMIZATION DESIGN OF AERODYNAMIC SHAPE FOR ANTI-ICING WIND TURBINE AIRFOILS[J]. Acta Energiae Solaris Sinica. 2025, 46(7): 336-345 https://doi.org/10.19912/j.0254-0096.tynxb.2024-0334

中图分类号： TK83

参考文献

[1] 战培国. 国外寒冷地区风力机结冰问题研究[J]. 航空科学技术, 2016, 27(2): 1-6.
ZHAN P G.Review of the wind turbine icing in overseas cold regions[J]. Aeronautical science & technology, 2016, 27(2): 1-6.
[2] 范必双, 蒋李亚, 周强, 等. 风力机叶片气热除冰技术研究现状与展望[J]. 热能动力工程, 2023, 38(2): 1-9.
FAN B S, JIANG L Y, ZHOU Q, et al.Research status and prospect of air-heating deicing technology for wind turbine blades[J]. Journal of engineering for thermal energy and power, 2023, 38(2): 1-9.
[3] LI B W, SUN Q Q, XIAO D D, et al.Numerical investigation of the aerofoil aerodynamics with surface heating for anti-icing[J]. Aerospace, 2022, 9(7): 338.
[4] 郭文峰, 张影微, 董笑宇, 等. 基于超声微振动的风力机叶片除冰研究[J]. 工程热物理学报, 2023, 44(7): 1808-1814.
GUO W F, ZHANG Y W, DONG X Y, et al.Researches on ultrasonic de-icing method of wind turbine blade[J]. Journal of engineering thermophysics, 2023, 44(7): 1808-1814.
[5] 胡琴, 王欢, 舒立春等. 覆冰条件下风力机叶片防/除冰方法综述[J]. 电工技术学报, 2024, 39(17): 5482-5496.
HU Q, WANG H, SHU L C, et al.Review of anti/de-icing methods for wind turbine blades under icing conditions[J]. Transactions of China Electrotechnical Society, 2024, 39(17): 5482-5496.
[6] 潘洋洋, 林瑞霖, 刘伯运. 基于CFD技术的风机翼型多目标优化设计[J]. 机电工程技术, 2018, 47(1): 57-60, 138.
PAN Y Y, LIN R L, LIU B Y.Multi-objective optimization design of airfoil of fan based on CFD[J]. Mechanical & electrical engineering technology, 2018, 47(1): 57-60, 138.
[7] 王清, 张敏, 李德顺, 等. 基于低速预处理的风力机翼型外形优化设计[J]. 太阳能学报, 2022, 43(5): 351-358.
WANG Q, ZHANG M, LI D S, et al.Aerodynamic shape optimization of wind turbine airfoil based on low speed preconditioning[J]. Acta energiae solaris sinica, 2022, 43(5): 351-358.
[8] 黄意坚, 宋文萍, 韩忠华, 等. 平底后缘风力机翼型的优化设计[J]. 太阳能学报, 2015, 36(10): 2442-2447.
HUANG Y J, SONG W P, HAN Z H, et al.Design and numerical optimization of flatback airfoils[J]. Acta energiae solaris sinica, 2015, 36(10): 2442-2447.
[9] 陈海昕, 邓凯文, 李润泽. 机器学习技术在气动优化中的应用[J]. 航空学报, 2019, 40(1): 522480.
CHEN H X, DENG K W, LI R Z.Utilization of machine learning technology in aerodynamic optimization[J]. Acta aeronautica et astronautica sinica, 2019, 40(1): 522480.
[10] LIU J Q, CHEN R Q, LOU J H, et al.Airfoils optimization based on deep reinforcement learning to improve the aerodynamic performance of rotors[J]. Aerospace science and technology, 2023, 143: 108737.
[11] 张强, 缪维跑, 常林森, 等. 基于代理模型的风力机翼型动态失速优化设计[J]. 太阳能学报, 2023, 44(6): 343-350.
ZHANG Q, MIAO W P, CHANG L S, et al.Optimal design of dynamic stall of wind turbine airfoil based on surrogate model[J]. Acta energiae solaris sinica, 2023, 44(6): 343-350.
[12] 王璐瑶, 于佳鑫, 王晓东, 等. 基于代理模型与遗传算法的翼型优化设计方法研究[J]. 风机技术, 2021, 63(6): 69-75.
WANG L Y, YU J X, WANG X D, et al.Investigations on airfoil optimization method based on surrogate model and genetic algorithm[J]. Chinese journal of turbomachinery, 2021, 63(6): 69-75.
[13] 蒋传鸿. 风力机结冰翼型的气动性能分析及优化设计[D]. 重庆: 重庆大学, 2014.
JIANG C H.Aerodynamic performance analysis and optimization design of wind turbine with iced airfoil[D]. Chongqing: Chongqing University, 2014.
[14] SPALART P, ALLMARAS S.A one-equation turbulence model for aerodynamic flows[C]//30th Aerospace Sciences Meeting and Exhibit. Reno, NV, USA, 1992: 439.
[15] SHIN J, CHEN H, CEBECI T.A turbulence model for iced airfoils and its validation[C]//30th Aerospace Sciences Meeting and Exhibit. Reno, NV, USA, 1992: 417.
[16] 关晓辉, 李占科, 宋笔锋. CST气动外形参数化方法研究[J]. 航空学报, 2012, 33(4): 625-633.
GUAN X H, LI Z K, SONG B F.A study on CST aerodynamic shape parameterization method[J]. Acta aeronautica et astronautica sinica, 2012, 33(4): 625-633.
[17] 卜月鹏, 宋文萍, 韩忠华, 等. 基于CST参数化方法的翼型气动优化设计[J]. 西北工业大学学报, 2013, 31(5): 829-836.
BO Y P, SONG W P, HAN Z H, et al.Aerodynamic optimization design of airfoil based on CST parameterization method[J]. Journal of Northwestern Polytechnical University, 2013, 31(5): 829-836.
[18] DRELA M, YOUNGREN H.XFOIL subsonic airfoil development system[R]. Massachusetts Institule of Technology, 2013, 23.
[19] Somers D M.Design and experimental results for the S809 airfoil[R]. National Renewable Energy Lab.(NREL), Golden, CO(United States), 1997.
[20] 张强, 缪维跑, 刘青松, 等. 基于多目标遗传算法的垂直轴风力机专用翼型优化设计[J]. 太阳能学报, 2023, 44(4): 9-16.
ZHANG Q, MIAO W P, LIU Q S, et al.Optimal design of vertical axis wind turbine special airfoil based on multi-objective genetic algorithm[J]. Acta energiae solaris sinica, 2023, 44(4): 9-16.
[21] 余镇, 樊志华, 石宏雨, 等. 基于代理优化算法的水下滑翔机外形优化设计[J]. 机械强度, 2023, 45(4): 879-886.
YU Z, FAN Z H, SHI H Y, et al.Shape optimization design of the underwater glider based on surrogate optimal algorithm[J]. Journal of mechanical strength, 2023, 45(4): 879-886.
[22] 崔宝珍, 孔维娜, 马恺. 多项式响应面代理模型在立柱结构优化中的应用[J]. 机械设计, 2017, 34(4): 44-48.
CUI B Z, KONG W N, MA K.Application of polynomial response surface surrogate model in the large column structure optimization[J]. Journal of machine design, 2017, 34(4): 44-48.
[23] OH S.Comparison of a response surface method and artificial neural network in predicting the aerodynamic performance of a wind turbine airfoil and its optimization[J]. Applied sciences, 2020, 10(18): 6277.
[24] 叶鹏程, 潘光, 高山. 一种快速优化拉丁超立方试验设计方法[J]. 西北工业大学学报, 2019, 37(4): 714-723.
YE P C, PAN G, GAO S.Sampling design method of fast optimal Latin hypercube[J]. Journal of Northwestern Polytechnical University, 2019, 37(4): 714-723.