G. Storti Gajani

Short-term PV power forecasting under real-world data constraints: a benchmark study of neural networks with uncertainty quantification

This study provides an in-depth comparative analysis of four state-of-the-art neural architectures, confirming that high-fidelity point forecasts and rigorously quantified uncertainty can be achieved simultaneously, providing a clear path toward more dependable PV dispatch, reserve allocation, and market participation.