空气动力学学报2023，Vol.41Issue(11)：71-79,9.DOI:10.7638/kqdlxxb-2022.0134
考虑风切变影响的三维尾流模型风场实验
Experimental study on wind field of three-dimensional wake model considering the influence of wind shear
摘要
Abstract
Aiming at the problem that the current wind turbine wake model can only describe the wake distribution in the far wake region and ignores the wake characteristics in the near wake region,this paper derives a new three-dimensional wake model based on the double-Gaussian function,using the flow conservation theorem and through rotation correction.The wake model considers the influence of wind shear and is able to describe the three-dimensional wake distribution characteristics in the near wake region and the far wake region.Wind field experiments were carried out with two ground-based scanning laser radars.The experimental data shows that the distribution of near wake in the horizontal direction has the symmetrical double-Gaussian shape,and the distribution of far wake area has the symmetrical Gaussian shape,while due to the influence of wind shear in the vertical direction,the distribution of wake in the near wake area has the asymmetrical double-Gaussian shape,and the distribution of far wake area has the asymmetrical Gaussian shape.The horizontal and vertical profiles predicted by the three-dimensional wake model are compared and verified by using the measured data.The validation results show that the prediction curves of the three-dimensional wake model are in good agreement with the experimental data,and the average relative errors are mostly within 5%.The newly proposed three-dimensional wake model can better predict the spatial distribution of the whole wake area downstream of the wind turbine and can provide an optimization scheme for the layout of the wind farm.关键词
三维尾流模型/风切变/风场实验/双高斯函数/激光雷达Key words
three-dimensional wake model/wind shear/wind field experiment/double-Gaussian function/laser radar分类
能源科技引用本文复制引用
张绍海,高晓霞,朱霄珣,王瑜,王喜..考虑风切变影响的三维尾流模型风场实验[J].空气动力学学报,2023,41(11):71-79,9.基金项目
国家自然科学基金(52076081) （52076081）
中央高校基本科研基金资助项目(2020MS107) （2020MS107）
