Grid-connected PV in the U.S. has grown substantially over the past several years and grid operators are increasingly...
Metrics used in assessing irradiance model accuracy such as Root Mean Square Error (RMSE) and Mean Absolute Error...
This paper presents a study of how PV performance model results are affected when satellite-based weather data is used...
This paper describes how to generate more accurate Weather-Adjusted Performance Guarantees for PV systems using a...
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...