@article{Yang_Hu_Yin_Chen_Liao_2014, title={Clustering-interpolation Method and Its Application to Wind Turbine Generator Curve}, volume={20}, url={https://eejournal.ktu.lt/index.php/elt/article/view/5195}, DOI={10.5755/j01.eee.20.8.5195}, abstractNote={The real-time operating wind turbine power curve (WPC) of a wind turbine generator (WTG) is not completely identical to a WPC provided by the manufacturer because of various factors. In order to obtain an accurate WPC model that can consider various factors, this paper improves a bisecting k-means clustering algorithm. The improved clustering algorithm is used for partitioning the measured data into a certain number of groups, which can be expressed in their centroids. The interpolation method based on the polynomial is carried out for modelling a WPC of WTG. The modelled WPC is applied to the reliability analysis of the generating systems with a wind farm. The results show that the accuracy of the linear interpolation is higher than that of quadratic interpolation and cubic spline interpolation when there are a relatively large number of clusters. <p>DOI: <a href="http://dx.doi.org/10.5755/j01.eee.20.8.5195">http://dx.doi.org/10.5755/j01.eee.20.8.5195</a></p>}, number={8}, journal={Elektronika ir Elektrotechnika}, author={Yang, Hejun and Hu, Bo and Yin, Lei and Chen, Ya and Liao, Qinglong}, year={2014}, month={Oct.}, pages={13-19} }