Step-adaptive multimodal fusion network with multi-scale cloud feature learning for ultra-short-term solar irradiance forecasting
Researchers propose a step-adaptive multimodal fusion network for ultra-short-term solar irradiance forecasting that combines cloud image analysis with meteorological data. The model addresses limitations in existing approaches by using InceptionNeXt for multi-scale cloud feature extraction and dynamic low-frequency compensation that adapts to different prediction horizons.