Steadycast Project : Intraday solar forecasting innovation

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Short-term forecasting plays an increasingly important role in integrating solar energy into power systems and electricity markets.

Yet, the capabilities of state-of-the-art operational solutions often struggle to meet customers’ increasingly demanding needs and expectations. Lack of accuracy mainly arises from limitations of Numerical Weather Prediction (NWP) models (resolutions, update frequency, data assimilation gaps) and solar radiation nowcasting systems (simplified modeling of atmospheric physics such as clouds and Radiative Transfer). Dealing with forecasting uncertainties, large amounts of data and decision making in complex weather situations are also huge challenges for end-users.

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Steadycast aims at providing best-in-class short-term solar forecasting services:

- Cloud-based one-stop shop solution available worldwide (SaaS)
- Unprecedented accuracy level (+10-15% improvement at the intraday scale)
- Custom end-user tools and analytics
- 99.9% guaranteed availability

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Steadycast Project : Intraday solar forecasting innovation

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The innovation displays a breakthrough in the data processing and forecasting approach delivering unprecedented level of performance fueled by:

- The fusion of heterogeneous data (satellite imagery, numerical weather predictions, in-situ observations) in a unique modeling chain
- A forecasting approach based on the alliance between AI (e.g. nowcasting of clouds based on Deep Learning) and physical models (e.g. Speed-up Monte-carlo Advanced Radiative Transfer code)
- The advanced use of Big Data & analytics for data storage, access, processing and visualization
- A scalable cloud computing infrastructure

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GIF showing the evolution of cloud cover over the Alps through satellite imagery.

GIF showing the evolution of cloud cover over the Alps through satellite imagery.

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Our partners:
DSE-Data Science Experts, Hygeos et Gisaia.

The project is supported by ESA Space Solutions.

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