The Proa Forecasting System (PFS) uses multiple methods to provide an optimal combined forecast for all time scales. Each component forecasts is calculated independently, using independent input data, which creates redundancy and increases overall reliability.
- Skycam Cloud Motion Vectoring forecasts (CMV): images of the entire sky above a solar farm or PV system are taken by our onsite cameras, and advanced algorithms detect clouds and track their motion.
- Satellite CMV: images of the entire Australian continent are taken by the Himawari-8 meteorological satellite every 10 minutes, and clouds are again detected and tracked. The combination of both skycam and satellite images together provides extraordinarily detailed information on cloud motion.
- Live data forecasts (LDF): real time monitoring of the generation of a single system, or a group of PV systems, is used to estimate the current cloud cover for a location or region.
- Numerical Weather Prediction forecasts (NWP): dynamic equations and physical models of the atmosphere to estimate cloud formation and dissipation, and hence solar irradiance. The PFS uses several global and mesoscale NWP models.
The PFS forecast combines each of these methods, with optimal weights as a function of the forecast horizon, so that the combined forecast has the best performance over all time scales.
Contact us for more information on forecast performance and technical features.
Custom input data
We can also incorporate your custom data feeds to improve the forecast accuracy. For example, if you have sky camera feeds for your site, we can include these to improve the forecasts. Our forecast engine will automatically combine all forecasts with the optimal weighting for each forecast horizon. Contact us to discuss custom input data further.