基于流量守恒,提出一种H型VAWT的三维解析尾流模型,该模型考虑了风切变效应,并采用多元高斯分布。首先,通过风洞试验及大涡模拟数据进行模型验证,结果表明在x/D>3的远尾流区,横向剖面的相对误差小于2%,垂向剖面的相对误差小于3%。然后,从下游4个位置(x/D=3、6、9、12)、3种推力系数(CT=0.6、0.7、0.8)、4种风切变指数(α=0、0.1、0.15、0.2)、两种湍流强度(I0=5%、8.3%)下演示了一系列预测结果,结果显示该文模型能有效地描述尾流风速的空间分布。由于考虑了高度影响,该模型可用于风力机轮毂高度的优化及风电场的布局优化,有利于提高风电场的功率输出。
Abstract
Considering flow conservation, a three-dimensional analytical wake model of H-type VAWT that incorporates wind shear effects and uses a multivariate Gaussian distribution is proposed. Wind tunnel tests and large eddy simulation data are firstly used to validate the model. The results show that the relative errors are less than 2% for the transverse profile and less than 3% for the perpendicular profile in the far wake region with x/D>3. Next, a series of results are demonstrated from four downstream locations (x/D=3,6,9,12), three thrust coefficients (CT=0.6,0.7,0.8), four wind shear indices (α=0,0.1,0.15,0.2), and two turbulence intensities (I0=5%,8.3%), and the results show that the model in this paper can effectively describe the spatial distribution of the wake wind speed. By considering the height effect, the model can be used for the optimization of wind turbine hub heights and the layout optimization of wind farms, which is beneficial to increase wind farms'power output.
关键词
垂直轴风力机 /
解析模型 /
高斯分布 /
三维尾流模型
Key words
vertical axis wind turbines /
analytical models /
Gaussian distribution /
three-dimensional wake model
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参考文献
[1] ZHAO Z Z, WANG D D, WANG T G, et al.A review: approaches for aerodynamic performance improvement of lift-type vertical axis wind turbine[J]. Sustainable energy technologies and assessments, 2022, 49: 101789.
[2] 罗帅, 缪维跑, 李春, 等. 基于定常吸气的垂直轴风力机流动控制研究[J]. 中国电机工程学报, 2020, 40(21): 7078-7087.
LUO S, MIAO W P, LI C, et al.Research on flow control of vertical axis wind turbine based on steady suction[J]. Proceedings of the CSEE, 2020, 40(21): 7078-7087.
[3] BATTISTI L, ZANNE L, DELL'ANNA S, et al. Aerodynamic measurements on a vertical axis wind turbine in a large scale wind tunnel[J]. Journal of energy resources technology, 2011, 133(3): 031201.
[4] LI Q A, MAEDA T, KAMADA Y, et al.Investigation of power performance and wake on a straight-bladed vertical axis wind turbine with field experiments[J]. Energy, 2017, 141: 1113-1123.
[5] SHAMSODDIN S, PORTÉ-AGEL F.Large eddy simulation of vertical axis wind turbine wakes[J]. Energies, 2014, 7(2): 890-912.
[6] ABKAR M, DABIRI J O.Self-similarity and flow characteristics of vertical-axis wind turbine wakes: an LES study[J]. Journal of turbulence, 2017, 18(4): 373-389.
[7] PENG H Y, LAM H F, LEE C F.Investigation into the wake aerodynamics of a five-straight-bladed vertical axis wind turbine by wind tunnel tests[J]. Journal of wind engineering and industrial aerodynamics, 2016, 155: 23-35.
[8] ABKAR M.Theoretical modeling of vertical-axis wind turbine wakes[J]. Energies, 2018, 12(1): 10.
[9] CHEN Y, LI H, JIN K, et al.Wind farm layout optimization using genetic algorithm with different hub height wind turbines[J]. Energy conversion and management, 2013, 70: 56-65.
[10] GE M W, WU Y, LIU Y Q, et al. A two-dimensional model based on the expansion of physical wake boundary for wind-turbine wakes[J]. Applied energy, 2019, 233/234: 975-984.
[11] BARTHELMIE R J, LARSEN G C, FRANDSEN S T, et al.Comparison of wake model simulations with offshore wind turbine wake profiles measured by sodar[J]. Journal of atmospheric and oceanic technology, 2006, 23(7): 888-901.
[12] GAO X X, LI B B, WANG T Y, et al.Investigation and validation of 3D wake model for horizontal-axis wind turbines based on filed measurements[J]. Applied energy, 2020, 260: 114272.
[13] SUN H Y, YANG H X.Study on an innovative three-dimensional wind turbine wake model[J]. Applied energy, 2018, 226: 483-493.
基金
国家自然科学基金(51876054; 52106239; 11502070); 江苏风力发电工程技术中心开放基金(ZK22-03-01)