SnowFogS
Detection and prediction of fog and snow for PV forecasts
The PV power forecasting system Suncast shows a very high accuracy and reliability for most weather situations. But weather conditions with fog oder snow can lead to uncertainties in the PV power forecast, though models for fog and snow detection are well established within the PV power forecasting system by energy & meteo system. These situations are hard to predict precisely and can have an significant impact on local or regional PV power production. The regionally variable formation and dissipation of fog is insufficiently represented in state-of-the-art numerical weather predictions, addressing the impact of snow requires highly resolved information of snowfall and melting of snow.
The research project SnowFogS addresses new methods for detecting and predicting fog and snow based on satellite information. Focus of this project was laid on the short-term forecast horizon of several hours ahead which is especially relevant for intraday markets and grid control. The satellite data utilized and methods developed are especially suitable for deriving locally highly resolved information on distribution of fog and snow covered ground. In addition to the satellite information ground-based measurements and models for fog dissipation were used. The derived methods and input data were experimentally integrated into the PV power forecasting system Suncast by energy and meteo systems. The use of this newly developed approaches were analysed and evaluated by users within this project.
The SnowFogS research project (January 2021 to March 2024) was funded by the Federal ministry of economic affairs and climate action (BMWK). It was coordinated by the Fraunhofer Institute for Solar Energy Systems (ISE) Freiburg and carried out in cooperation with the Karlsruhe Institute of Technology (KIT), TenneT TSO GmbH and Amprion GmbH.