A Data-Driven Machine Learning Approach to Solar Energy Generation Forecasting Using Meteorological Variables
Air temperature, wind direction, wind speed, and relative humidity were the top four features affecting solar power generation identified from SHAP analysis, and the results show the potential of using machine learning techniques for accurate solar energy prediction, leading to enhanced grid management, renewable energ...