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.

On the Importance of Correlating Wind Speed and Wind Direction for Evaluating Uncertainty in Wind Turbine Power Output

Di Giorgio V.;Langella R.;Testa A.
2019

Abstract

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.
978-1-7281-1356-2
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11591/469972
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