摘要
针对目前存在的尾流模型对叠加尾流空间分布特征描述不完整的问题,提出了一种基于双高斯函数的三维叠加尾流模型(3DJGF-M模型),以达到对叠加尾流更准确、全面地预测。首先,修正了三维双高斯全尾流模型(3DJGF模型)的尾流膨胀系数,该系数不需要多次试验计算来确定,可减少计算成本;其次,通过引入风切变的影响,修正了速度亏损叠加原理;此外,以3DJGF模型为基础,利用考虑风切变的叠加原理推导了3DJGF-M模型;最后,利用激光雷达进行了风场实验,验证了3DJGF-M模型的准确性。结果表明:3DJGF-M模型在预测整个尾流区水平剖面以及垂直剖面的相对误差基本都在5%以内,预测效果良好,对于风电场布局优化有较大的应用潜力。
Aiming at the problem that the existing wake model can not completely describe the spatial distribution characteristics of superimposed wake,a three-dimensional superimposed wake model based on double-Gaussian function(3DJGF-M model)was proposed to achieve a more accurate and comprehensive prediction of superimposed wake.Firstly,the wake expansion coefficient of the three-dimensional double-Gaussian full wake model(3DJGF model)was corrected.The coefficient does not need to be determined by many tests and calculations,which can reduce computational cost.Secondly,by introducing the influence of wind shear,the superposition principle of velocity loss was modified.In addition,based on the 3DJGF model,the 3DJGF-M model was derived using the superposition principle considering wind shear.Finally,wind field experiments were carried out with lidars to verify the accuracy of 3DJGF-M model.Results show that the relative error of 3DJGF-M model in predicting the horizontal profiles and vertical profiles of the whole wake region is basically within 5%,and the prediction effect is good.It has great application potential for the layout optimization of wind farms.
作者
张绍海
高晓霞
徐施耐
朱霄珣
王瑜
王喜
ZHANG Shaohai;GAO Xiaoxia;XU Shinai;ZHU Xiaoxun;WANG Yu;WANG Xi(School of Energy Power&Mechanical Engineering,North China Electric Power University,Baoding 071003,Hebei Province,China;Hebei Key Laboratory of Low Carbon and High Efficiency Power Generation Technology,North China Electric Power University,Baoding 071003,Hebei Province,China;Baoding Key Laboratory of Low Carbon and High Efficiency Power Generation Technology,Baoding 071003,Hebei Province,China;Department of Electronic&Communication Engineering,North China Electric Power University,Baoding 071000,Hebei Province,China;Hebei Longyuan Wind Power Generation Co.,Ltd.,Zhangjiakou 076450,Hebei Province,China)
出处
《动力工程学报》
CAS
CSCD
北大核心
2023年第9期1223-1229,共7页
Journal of Chinese Society of Power Engineering
基金
国家自然科学基金资助项目(52076081)
中央高校基本科研基金资助项目(2020MS107)。
关键词
风力机
尾流模型
叠加尾流
风场实验
双高斯函数
wind turbine
wake model
superimposed wake
wind field test
double-Gaussian function
