Explainable and physics-constrained PV power prediction via a hybrid framework Integrating secondary decomposition and improved Transformer-LSTM

Key Points

• The hybrid framework improves pv power prediction accuracy significantly, enhancing explainability.
• Using transformer-lstm, the method achieves up to 15% higher prediction accuracy compared to previous models.
• Assessment involved integrating secondary decomposition to enrich data processing capabilities, optimizing results.
• This approach highlights the potential for more reliable solar energy forecasting systems, reducing uncertainty.