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Modeling Correlated Wind Speeds by Trigonometric Archimedean Copulas

机译：通过三角拱门共速建模相关风速

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摘要

In this paper, the statistical features of correlated wind speeds at multiple sites are characterized by marginal distributions and Archimedean copulas. Firstly, the generalized lambda distribution (GLD), kappa distribution and Weibull distribution are employed to recover the quantile function of wind speed at each site. Then, three new Archimedean copula models are constructed to characterize the dependence structure of historical wind speed data. Based on Rosenblatt transformation, a generic algorithm is presented to produce sample realizations of correlated wind speeds, which would have the same statistical features as historical wind speed data. Finally, numerical examples are given to illustrate the proposed methods.
机译：在本文中，多个站点的相关风速的统计特征是由边缘分布和阿基米德共施加的特征。首先，采用广义的λ分布（GLD），κ分布和威布尔分布来恢复每个站点的风速的量子函数。然后，构造了三种新的Archimedean Copula模型以表征历史风速数据的依赖结构。基于Rosenblatt转换，提出了一种通用算法以产生相关风速的样本实现，其具有与历史风速数据相同的统计特征。最后，给出了数值例子来说明所提出的方法。

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