SolarBench

SolarBench aims to reduce barriers for researchers and practitioners to access quality-controlled, standardized environmental data and machine learning tools to advance solar energy nowcasting for large-scale solar integration.

This repo contains multiple data modalities and is structured as follows:

• ground: Ground-based sensor data include sky images, a variety of weather measurements, and labels for solar forecasting tasks, namely different solar irradiance components (i.e., GHI, DHI, and DNI) or power generation from solar panels.
• ground_no_sky_img: A lite version of ground by excluding sky images. Useful for fast analysis and training non-vision models or performing ablation studies.
• satellite: Geostationary satellite imagery including GOES, Himawari, MSG.
• GFS: Numerical weather prediction data from NOAA's Global Forecast System (GFS).
• ERA5: Retrospective climate reanalysis data from the ECMWF Reanalysis version 5 (ERA5) single-level dataset.

Datasets