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Accurate solar power forecasting is essential for grid stability and efficiency. Precise generation forecasts help balance electricity supply and demand, prevent overloads, and support renewable energy integration. It enables to optimize bidding strategies and reduce penalties for imbalanced production. This study presents a solar power forecasting approach that integrates deterministic models with machine learning. The system utilizes the pvlip Python library for deterministic calculations. XGBoost-based machine ...