Efficient Wind Speed Prediction Using Machine Learning

As a form of clean energy, wind energy has been used effectively in electrical systems. However, wind speed shows strong nonlinearity and instability due to atmospheric boundary layer effects. Therefore, accurate and stable wind speed forecasts are essential for the safety of the power grid. Industry can also use forecasted wind speed data to calculate the amount of electricity they need to generate or purchase in addition to electricity generated by wind power. A new hybrid prediction system is needed to improve the prediction accuracy. Machine learning models can help predict wind speeds. Competing regressors such as linear regressor, random forest regressor, XGBoost, decision tree regressor, Support Vector and lightweight gradient boosting machine were compared to choose the best machine learning model that provides high accuracy results.