Speaker
Description
Solar energy forms an important pillar of climate change mitigation. Short-term forecasts of surface solar irradiance (SSI) are gaining more importance for power grid operators seeking to balance supply and demand in a secure and economical way. Regional-scale SSI forecasts are essential since most solar power is provided by decentralized PV plants. Solar nowcast models offer SSI predictions at forecast lead times of minutes to hours. I will provide an introduction to spatiotemporal forecasting of solar energy as applicable across Europe and other global regions and will introduce the first two regional-scale solar nowcast models, SolarSTEPS and SHADECast, which provide probabilistic satellite-based solar forecasts for minutes to hours, enabling uncertainty quantification for regions of dozens to thousands of kilometers in size. I will also present a first intercomparison of probabilistic solar forecast models and how they perform for national-scale PV forecasting.
