HAF

Helmholtz Analytic Framework

Cloud and Solar Power Prediction

The proper forecasting of clouds in the use case Cloud and Solar Power Prediction is important for the short-term predictions of photovoltaic power, photo-chemically impaired air quality, and precipitation. Cloud scenarios are best observed by satellites. The transfer of this space-borne information in prognostic models, expected to result in a demonstrated beneficial effect on cloud evolution and prediction capabilities, is an unresolved issue. Major Scientific Big Data Analytics (SBDA) methods to be applied are supervised learning as well as parallel and scalable classification algorithms.