A project focused on forecasting solar photovoltaic (PV) power generation using regional microclimate data. Implements machine learning models like CatBoost, LightGBM, and XGBoost for predictions, leveraging environmental features like temperature, humidity, wind speed, and solar radiation.
machine-learning xgboost lightgbm catboost pv-generation energy-prediction solar-power-forecasting microclimate-data
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Updated
Mar 10, 2025 - Jupyter Notebook