Babysitting hyperparameter optimization and 10-fold-cross-validation to enhance the performance of ML methods in predicting wind speed and energy generation

Abstract

Academics have been interested in renewable energy for a long time, and research has been done on how to use it, collect it, manage it, make it more efficient, and find uses for it. all the different ways to use renewable energy have the potential to replace traditional fossil fuels slowly. in Galicia, Spain (43.354377 N, 7.881213 W), the Sotavento wind farm comprises 24 wind turbines with a total installed capacity of 17.56 MW. The babysitting method was used to optimize the Hyperparameter of the light gradient boosting machine, gradient boosting, random forest, and k-neighbor algorithms. Also, 10-fold cross-validation was used to enhance the performance and reliability of ML methods.