DTU Risø All-Sky Imager Testbed: One-Week Sky Image and Calibration Dataset

This research focuses on developing and testing a ground-based all-sky imager (ASI) network at the DTU Risø Campus to improve very short-term solar irradiance forecasting. Clouds are the primary source of intra-hour variability in solar power, and their rapid movement across the sky presents challenges for predicting Global Horizontal Irradiance (GHI). Existing methods such as satellite-based forecasts provide regional coverage but lack the temporal and spatial resolution needed for second-to-minute scale predictions at PV plant level.To address this gap, three high-resolution ASIs were installed at different locations on the campus, separated by 400–1200 meters. Each camera was carefully calibrated using a fisheye lens model, producing lookup tables that map every image pixel to its corresponding solar azimuth and zenith angles. These calibrations enable geometric correction of the raw images and equidistant projections of the sky dome.The system has been tested in a spatial casting configuration (no forecasting horizon), where irradiance maps generated by one camera are compared to pyranometer measurements at other locations across the campus, including a solar meteorological station. Results from a full day of 30-second resolution data show that the ASI-based method reproduces the timing and magnitude of irradiance ramps caused by passing clouds, though discrepancies remain in cases of fast cloud movement or complex multi-layer cloud fields.The research provides a testbed for validating ASI-based solar forecasting methods, where controlled experiments can quantify the effect of camera distance to PV plants, cloud fraction, and seasonal variation on forecast accuracy. This contributes to the broader goal of enabling cost-effective, high-frequency solar forecasting solutions that can be scaled for grid integration, PV plant operation, and energy market participation.