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程正兵,冀骁文.基于Copula函数和风速正交分量的风矢量联合概率密度研究[J].计算力学学报,2024,41(5):942~947
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基于Copula函数和风速正交分量的风矢量联合概率密度研究
Research on joint probability density of wind vector based on Copula function and wind speed orthogonal components
投稿时间:2023-04-15  修订日期:2023-05-25
DOI:10.7511/jslx20230415002
中文关键词:  Copula函数  正交分解  风矢量  联合概率密度  混合Normal
英文关键词:copula function  orthogonal decomposition  wind vector  joint probability density  mixed Normal
基金项目:国家自然科学基金(51908014;52278135)资助项目.
作者单位E-mail
程正兵 北京工业大学 城市与工程安全减灾教育部重点实验室, 北京 100124  
冀骁文 北京工业大学 城市与工程安全减灾教育部重点实验室, 北京 100124 jixiaowen900308@gmail.com 
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中文摘要:
      准确地表示风矢量联合概率密度对于风能的评估和风机结构设计具有重要意义,本文将围绕提升风矢量联合概率密度表示结果准确性展开研究。首先,将风矢量表示为风速正交分量,采用混合Normal分布分别对边缘概率密度进行表示,并提出了估计混合Normal分布参数的方法。然后,基于Copula函数考虑风速正交分量间的相关性,从而得到二者的联合概率密度,其中Copula参数通过最小二乘法估计,紧接着通过雅可比变换得到风矢量联合概率密度。最后,采用印度风能研究所的测点S3和S7的每小时平均风速和风向数据,与以往基于Copula函数和风速、风向变量得到的风矢量联合概率密度结果进行对比。结果表明,与以往方法相比,所提方法得到的风矢量联合概率密度结果准确性有很大的提升,本文可为风能的开采和利用提供理论依据。
英文摘要:
      Accurately representing the joint probability density of wind vector is significant for wind energy assessment,as well as structural design of wind turbine.This study will focus on improving the accuracy of describing joint probability density of wind vector.Firstly,the wind vector is represented as orthogonal components,a mixed Normal distribution is used to represent their marginal probability density,and a method for estimating the initial values of parameters is proposed.Then,based on Copula function,the correlation between the orthogonal components of wind speed is considered to obtain their joint probability density,the Copula parameter is estimated by the Least Squares estimation,and then joint probability density of wind vector is obtained through Jacobian transformation.Finally,the hourly average wind speed and direction data in point S3 and S7 from the Indian Wind Energy Research Institute is used to compare with previous joint probability density results of wind vector obtained based on the Copula function and wind speed and direction variables.The results show that the joint probability density of wind vector obtained by proposed method is more accuracy than previous method.This study can provide a theoretical basis for the exploitation and utilization of wind energy.
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