This research provides government researchers, utilities, independent system operators and developers information on PV power output models and methods of calculating and quantifying the accuracy of satellite-derived solar irradiance data for specific applications.
Satellite-derived solar irradiance data are known to underestimate temporal variability compared to point measurements...
The ability to forecast solar irradiance plays an indispensable role in solar power forecasting, which constitutes an...
As interest in bifacial PV modules grows, there is a need to quantify the impact of additional energy generation for...
Solar PV system specifications are critical to accurately modeling PV system production (along with high-quality...
This paper provides the results of using an alternative method to calculate annual insolation probability of...
This article calculates day-head forecast variability as function of historical clearness index based on intraday...
This article evaluates the accuracy of solar forecast models, including SolarAnywhere®, as a function of geographic...
This article presents and validates the latest version of the SUNY model for using satellite imagery to calculate...
The California Energy Commission’s Public Interest Energy Research (CEC PIER) program awarded Clean Power Research a...
This paper summarizes operational improvements to the existing SUNY satellite-to-solar irradiance model used to...
This paper summarizes the deployment of a 71 station solar monitoring network in Sacramento, Calif., and its use in...
This article evaluates the ability of three operational satellite models (SolarAnywhere® Standard, Enhanced, and High...
Metrics used in assessing irradiance model accuracy such as Root Mean Square Error (RMSE) and Mean Absolute Error...
This presentation provides the results of a study evaluating the short, medium and long-term accuracy of irradiance...
This paper presents a validation of the short- and medium-term global irradiance forecasts that are produced as part...
This paper presents a study of how PV performance model results are affected when satellite-based weather data is used...
This paper validates the Clean Power Estimator obstruction analysis algorithm based on results produced by the Solar...
This paper describes and validates a simple PV simulation model capable of predicting average PV output as a function...
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...