Seasonal fluctuations and the intermittent nature of photovoltaic (PV) generation create significant challenges for accurate short-term forecasting. This study presents Next Frame Gramian Angular field U-Net (NFGUN), a hybrid deep learning forecasting framework that stands apart from conventional methods by transforming 1D PV time-series data into 2D Gramian Angular Summation Field (GASF) images. Unlike models that rely on direct regression or sky imagery, NFGUN forecasts the next GASF frame using a deep architecture and reconstructs it back into time-series form, effectively capturing nonline...
