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

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 ($\mathrm {P}_{\mathrm {o}\mathrm {u}\mathrm {t}}$). Using the available measurements of actual WTs, the paper first presents a new model for the analysis of the $\mathrm {P}_{\mathrm {o}\mathrm {u}\mathrm {t}}$-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 $\mathrm {P}_{\mathrm {o}\mathrm {u}\mathrm {t}}$-WS-WD model, previously proposed by some of the authors, with the cross-correlated three-dimensional $\mathrm {P}_{\mathrm {o}\mathrm {u}\mathrm {t}}$-WS-WD model, demonstrating that the ranges of variations of $\mathrm {P}_{\mathrm {o}\mathrm {u}\mathrm {t}}$ can be better modelled by considering not only wind speed, but also wind direction.