Research on joint probability density of wind vector based on Copula function and wind speed orthogonal components
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.
copula functionorthogonal decompositionwind vectorjoint probability densitymixed Normal
万方数据
维普
