DeepHeliosat (ongoing)

Advancing satellite-based solar resource modelling with deep learning techniques.

Vadim BECQUET's work paves the way for next-generation satellite-based SSI retrieval methods, harnessing deep learning and the enhanced resolution of third generation geostationary satellites for greater accuracy in solar resource assessment.

GeoFishEye (ongoing)

Simulated sky camera networks for spatial SSI.

The research work of Max ARAGÓN CERECEDES focuses on producing multi-view synthetic sky imagery for training and evaluating machine learning algorithms, with a special emphasis on sky camera networks for SSI modelling.

This work is of value for PV nowcasting, PV performance monitoring, and in the integration of all-sky irradiances into cloudscale
weather models.

SSI Variability (ongoing)

Modelling, characterization and prediction of SSI variability.

Jose GOMEZ GOMEZ is exploring and developing methodologies for generating SSI data with high spatial and temporal resolutions.

This work enhances energy storage planning, smart grid management and solar power plant optimization. It also provides valuable data for insurance and finance sectors to improve risk assessment and financial modelling in solar projects.

FishSPN1 (upcoming - 03/25)

Data fusion of information from a fish-eye camera and a global/direct/diffuse pyranometric sensor with no moving part.

Low-Cost All-Sky Imaging (completed)

Imaging for solar radiance estimation.

Valentin BAUER developed a low-cost all-sky imager using a Raspberry Pi and a compatible fish-eye camera. His project focused on estimating sky radiance at a specific location on Earth, leveraging affordable hardware and open-source sensor and software.

SSI Variability (completed)

Characterizing SSI data using wavelet transforms.

Pierre CHAPEL focused on the mathematical modelling of SSI variability. He used wavelet transforms to model the statistical nature of the SSI under different atmospheric conditions.

Solar Measurements in Polar Regions (completed)

Characterizing SSI data using wavelet transforms.

Arthur PAOLINI's project focused on developing an innovative method to measure solar irradiance in Arctic regions using a fish-eye camera. This approach was designed to overcome the challenges posed by harsh Arctic conditions. In this work traditional pyranometers were replaced with a versatile, camera-based method for measuring solar irradiance.