Machine Learning Prediction of Wind Turbine Energy Production

Abstract

This study used statistical data to create predictive models for effective and efficient use of energy generation systems using machine learning algorithms. Four different models predicted wind energy production and compared with actual production data. Model validity and verification were evaluated using mean square error, mean absolute error, and R-squared values. The model constructed with the random forest method is the most successful model. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.