Advanced power coefficient modeling for stall-regulated wind turbines

Abstract

This paper introduces a novel parametric model for estimating the power coefficient of stall-regulated wind turbines as a function of tip speed ratio and pitch angle. The proposed model improves upon existing polynomial, sinusoidal, and exponential formulations by incorporating the variation in drag-to-lift ratio, which significantly enhances the accuracy of power predictions. Model calibration is performed using a deterministic nonlinear least squares method to ensure robust parameter estimation. The enhanced model achieves a notable increase in predictive accuracy, with the adjusted R 2 improving from 0.93 to 0.96 and the root mean square error decreasing from 0.41 kW to 0.33 kW.