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What is Machine Learning for Renewable Energy Forecasting about?

This study explores the application of machine learning models to predict wind and solar power generation, addressing challenges in grid stability and resource management due to the intermittent nature of renewable energy. Random Forest Regression was found to be the most effective model, providing reliable forecasts through rigorous data preprocessing and feature selection. The findings emphasize the potential of machine learning in enhancing renewable energy integration and suggest future research directi

Author

Tarek

Language

EN