Modeling of meteorological parameters and improving the classification accuracy for the wind turbines

In this study novel solutions are presented for challenge subjects such as the weighting of wind energy parameters and classifying of meteorological data that should be consider in the installation of wind turbines. For this purpose, the relationships between the meteorological parameters and wind turbines are explored with an intuitive k-Nearest Neighbor algorithm. Thus, the effects of meteorological data on the power of wind turbines are modeled. In the experimental studies the power class of wind turbines is determined depending on the weighted and unweighted parameters and the performances of various classifiers are compared. The results show that the intuitive classification algorithm determines the power class of wind turbines successfully and produce more correct results than classic k-NN approach.