Solar Energy Forecasting
Solar energy generation can be affected by many different factors, but the most important driver of solar variability is cloud cover.
AI-enhanced, satellite-based forecasting
Fortunately, we now have access to new types of satellite imagery that provide highly detailed information on the locations of clouds. There are also new techniques arising out of the artificial intelligence motion prediction community that are incredibly effective at forecasting movement in imagery.
Our proprietary forecasting solution applies these latest AI techniques to satellite imagery — enabling us to forecast the formation and movement of clouds at a high resolution. Such cloud forecasts can improve the accuracy of solar generation forecasts by 20% over conventional solar forecasting approaches.
Highly localised forecasts
Cloud formation and movement is a highly localised process that can be heavily affected by conditions specific to a given site – for example how close it is to the coast, or to mountains, or to whatever other micro-climatic effects it may be subject to. In other words, cloud motion forecasts become more accurate if they are targeted at and trained on data for a specific site.
We train models specific to your use case, whether it is a solar farm, a region of your network, or a larger market region — taking these local effects into account.
Easily deployable
Since we rely on satellite data, there is no need for any local hardware, which can be costly to install and maintain. Our forecasts are available via API, FTP, or any other common delivery mechanism. We can forecast generation, capacity, or irradiance (GHI, POA, or your preferred quantity). Our forecasts can be made available at 1 minute resolution, with high update frequency, and less than 2 minute latency from availability of the last satellite image. Need a helpful dashboard to inspect performance or see future cloud movement? We can provide that too.
Ready to try our forecasts?
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