[HTML][HTML] Improving cross-site generalisability of vision-based solar forecasting models with physics-informed transfer learning

Q Paletta, Y Nie, YM Saint-Drenan… - Energy Conversion and …, 2024 - Elsevier
Forecasting solar energy from cloud cover observations is crucial to truly anticipate future
changes in power supply. On an intra-hour timescale, ground-level sky cameras located …

Improving cross-site generalisability of vision-based solar forecasting models with physics-informed transfer learning

Q Paletta, Y Nie, YM Saint-Drenan, B Le Saux - 2024 - hal.science
Forecasting solar energy from cloud cover observations is crucial to truly anticipate future
changes in power supply. On an intra-hour timescale, ground-level sky cameras located …

Improving cross-site generalisability of vision-based solar forecasting models with physics-informed transfer learning

Q Paletta, Y Nie, YM Saint-Drenan… - Energy Conversion …, 2024 - ui.adsabs.harvard.edu
Forecasting solar energy from cloud cover observations is crucial to truly anticipate future
changes in power supply. On an intra-hour timescale, ground-level sky cameras located …

Improving cross-site generalisability of vision-based solar forecasting models with physics-informed transfer learning

Q Paletta, Y Nie, YM Saint-Drenan, B Le Saux - 2024 - repository.cam.ac.uk
Forecasting solar energy from cloud cover observations is crucial to truly anticipate future
changes in power supply. On an intra-hour timescale, ground-level sky cameras located …

[PDF][PDF] Improving cross-site generalisability of vision-based solar forecasting models with physics-informed transfer learning

Q Paletta, Y Nie, YM Saint-Drenan, B Le Saux - hal.science
Forecasting solar energy from cloud cover observations is crucial to truly anticipate future
changes in power supply. On an intra-hour timescale, ground-level sky cameras located …