
A note on the multivariate Archimedean dependence structure in small wind generation sites
Author(s) -
Díaz Guzmán
Publication year - 2014
Publication title -
wind energy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.743
H-Index - 92
eISSN - 1099-1824
pISSN - 1095-4244
DOI - 10.1002/we.1633
Subject(s) - multivariate statistics , mathematics , econometrics , geometry , statistical physics , statistics , physics
This paper discusses the conjecture that Archimedean copulas—mainly Gumbel copulas—provide better stochastic models than Gaussian copulas for multivariate analysis of small wind energy generation clusters (focused on the analysis of microgrid viability). The paper provides guidance on how to model the multivariate Gumbel copula, thus allowing to follow up some recently published results that show that the correlation structure in bivariate models (generator pairing) is best defined by bivariate Gumbel copulas rather than by their Gaussian counterpart. However, it is shown in this paper that the higher the dimension (the larger the number of microgrid generators) the more probably the Gaussian copulas outperform the Gumbel copulas. Copyright © 2013 John Wiley & Sons, Ltd.