These papers highlight the benefit of combining high-quality solar ground data with satellite derived solar irradiance data to reduce solar project uncertainty.
Although the uncertainty of satellite data such as SolarAnywhere® Data has been shown to be low, it can be challenging...
This paper quantifies the residual errors in plane of array irradiance (POAI) at locations where ground-measured GHI...
In this presentation, you'll learn about which type of solar irradiance data—typical year, ground or satellite—is...
This paper describes procedures suitable for the optimal combination of ground-based and satellite-based irradiance...
Clean Power Research® is thrilled to announce the launch of SolarAnywhere® Sub-Hourly Typical Meteorological Year (TMY) irradiance and weather data! This feature provides SolarAnywhere customers with sub-hourly data, enhancing the precision of solar resource...
Soiling and snow on PV systems can lead to significant annual energy losses, reaching up to 50%1 and 40%2 in certain regions. Our study investigates common models for estimating soiling and snow-related energy impacts. By analyzing these soiling and snow loss models...
Clean Power Research® releases a new SolarAnywhere® data version annually. This year’s update addresses the changing needs of the solar industry as projects expand to more northern, snowy locations with appreciable wind risk by offering new high-latitude irradiance...