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Soukissiana, T.H. and Karathanasia, F.E. (2017) On the Selection of Bivariate Parametric Models for Wind Data. Applied Energy, 188, 229-236.
https://doi.org/10.1016/j.apenergy.2016.11.097

has been cited by the following article:

• TITLE: Modeling Wind Energy Using Copula

  AUTHORS: Zuhair Bahraoui, Fatima Bahraoui, M. Amin Bahraoui

  KEYWORDS: Weibull, Nonparametric Estimation, Copula, Wind Speed

  JOURNAL NAME: Open Access Library Journal, Vol.5 No.11, November 30, 2018

  ABSTRACT: In most studies related to wind energy, the quantity of the air density is considered constant, but actually, we know that it is variable and depending on others natural factors. We present a new procedure to estimate the wind density power energy by simulating the components of the air density. The procedure uses the copula theory and demonstrates that the estimated power energy is higher if the air density is not constant.