Power curve model classification to estimate wind turbine power output. Issue 3 (June 2019)

• Record Type: Journal Article
• Authors: Dongre, Bharti; Pateriya, Rajesh K
• Is Part Of: Wind engineering. Volume 43:Issue 3(2019)
• Page Start: 213
• Page End: 224
• Publication Date: 2019-06
• Subjects: Wind turbine -- power curve -- piecewise polynomial -- cubic spline interpolation -- logistic function -- polynomial regression; Wind-pressure -- Periodicals; Winds -- Periodicals; Wind power -- Periodicals; Engineering meteorology -- Periodicals; Pression du vent; Vents; Énergie éolienne; Météorologie appliquée; Engineering meteorology; Wind power; Wind-pressure; Winds; Periodicals; 621.4505
• DOI: 10.1177/0309524X18780393
• Languages: English
• ISSNs: 0309-524X

Abstract

This article presents a comparative study of empirical power curve models to estimate the output power of the turbine as a function of the wind speed. In these models, modelling strategy relies on the objective of modelling, data being used for the modelling and targeted accuracy. It has been observed that models based on presumed shape of power curve lack desired accuracy since these are developed using the power ratings of wind turbine which are not sufficient to exactly replicate the turbine's actual behaviour. The performance of various models which comes under manufacturer power curve modelling methodology has been compared with reference to commercially available wind turbines. It has been found that power curves obtained through method of least squares and cubic spline interpolation methods exactly match with manufacturer power curve, whereas 5PL method gives sufficiently accurate results. Modelling based on actual data of wind farm has been found to be a powerful technique for developing site-specific power curves.