Try the Solcast API
Solcast takes on the many challenges of producing live and forecast solar data, so that you don’t have to. That means making the data easy to access, validate and integrate. We provide instant access to live and forecast data products via this web interface, which is free to try. These include direct estimates of global, direct and diffuse solar radiation, as well as PV power output.
Commonly Asked Questions about Rooftop PV Model
The Solcast Rooftop PV model uses key parameters including system azimuth and tilt, module efficiency, shading effects, weather conditions (such as irradiance and temperature), and system losses. These parameters significantly influence the accuracy of the power output estimation.
The ideal tilt angle for rooftop PV panels depends on the geographic location and the latitude of the installation site which you can input when making Solcast API requests. The ideal azimuth angle for rooftop PV panels is typically true south in the Northern Hemisphere and true north in the Southern Hemisphere.
In Solcast rooftop PV systems, DC (Direct Current) refers to the electricity generated by the solar panels, while AC (Alternating Current) is the electricity output after it has been converted by the inverter for use in the grid or home. The Solcast model is calibrated to inverter output (AC) data from many systems.
Common challenges include accurately capturing the variability in solar irradiance due to changing weather conditions and accounting for the specific characteristics of each PV system, such as tilt, azimuth, and shading. Solcast’s high-resolution data, updated every 5 minutes, helps track these factors to deliver accurate, reliable forecasts.
Site measurements, such as historical power production data, can be used to fine-tune a rooftop PV power model. This tuning process helps capture specific factors like shading from trees or buildings, which can vary throughout the year, leading to more accurate power output predictions.
Rather than building a custom PV model from scratch, which can be time-consuming and prone to errors, using and tuning an existing rooftop PV power model can be more efficient. This approach ensures that important factors like shading and snow soiling are accurately accounted for, leading to better forecast performance.