能源工程2025，Vol.45Issue(1)：48-54,7.DOI:10.16189/j.nygc.2025.01.007
耦合垂直风廓线的机器学习风速订正模型
Wind speed correction model based on machine learning coupled with vertical distribution of wind speed
摘要
Abstract
In this study,a method is proposed for training a machine learning model for wind speed correction under the constraint of vertical wind speed distribution patterns(coupled model)to improve model generalization performance.The CNN_LSTM model is adopted in the experiment for the machine learning model.The vertical wind speed distribution pattern refers to the exponential distribution pattern where certain rules are satisfied by average wind speeds at different heights over a period of time.This method combines physics and data to enhance correction effectiveness.It is indicated by the research that,compared to using measured wind data as a baseline,the results from coupled model are closer to the measured data.The root-mean-square error of the coupled model is up to 1.74 m/s lower than that of WRF simulated wind speed and up to 0.46 m/s lower than that of CNN_LSTM.Two different correction methods can increase the correlation coefficient from 0.65 to 0.9,and the correlation coefficient of the coupled model can be increased to about 0.92.The method proposed in this study,where the vertical wind speed distribution pattern is coupled with machine learning model training,effectively improves the generalization capability of the correction model.关键词
风速订正/机器学习/垂直风廓线/耦合模型Key words
wind speed correction/machine learning correction model/vertical distribution of wind speed/coupling model分类
能源科技引用本文复制引用
张流杰,王强,明轩萱,杨树林,叶时彤,王凯,罗坤,樊建人..耦合垂直风廓线的机器学习风速订正模型[J].能源工程,2025,45(1):48-54,7.基金项目
国家自然科学基金项目(52206281) （52206281）
浙江省自然科学基金资助项目(LY24E060002). （LY24E060002）
