This paper analyses importance of correlating wind speed (WS) and wind direction (WD) for a more confident evaluation of uncertainty in wind turbine (WT) power output (Pout). Using the available measurements of actual WTs, the paper first presents a new model for the analysis of the Pout-WS-WD correlations, based on Gaussian mixture Copula model (GMCM) and vine Copula (i.e., vine-GMCM framework). Afterwards, the paper compares results of a two-dimensional Pout-WS-WD model, previously proposed by some of the authors, with the cross-correlated three-dimensional Pout-WS-WD model, demonstrating that the ranges of variations of Pout can be better modelled by considering not only wind speed, but also wind direction.
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