Developers, utilities and independent system operators depend on accurate time-series solar irradiance data for project siting, planning and operations. Groundbreaking solar prediction research quantifies the accuracy of PV output modeling, solar irradiance data and irradiance forecasting, as well as describing methods for modeling high-speed PV output variability.
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...
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...
Small-scale variabilities of solar irradiance are important for many applications. Downscaling approaches need to be...
This article evaluates the accuracy of solar forecast models, including SolarAnywhere®, as a function of geographic...
This article presents an experimental evaluation of the combined effective capacity of off-shore wind and...
This presentation describes the importance of PV output variability as a factor in calculating the value of a fleet of...
This paper describes how to generate more accurate Weather-Adjusted Performance Guarantees for PV systems using a...
This presentation describes how measured data was used to evaluate the potential of PV to satisfy the electrical needs...
This presentation demonstrates how a new approach to PV fleet forecasting can address the problem of artificially high...
This report, prepared with an Electric Program Investment Charge (EPIC) fund, describes new methods for improving...
This report, prepared with an Electric Program Investment Charge (EPIC) fund, describes the results of research to...
This presentation discusses how probabilistic forecasting enables electric utilities and grid operators to reduce...
This paper describes a study, funded by the U.S. Department of Energy, to evaluate new, state-of-the-art solar...
Clean Power Research received a California Solar Initiative (CSI) Research, Development, Demonstration and Deployment...
SolarAnywhere® FleetView® is generating behind-the-meter PV forecasts in California, enabling utilities and ISOs to...
Lean how SolarAnywhere® FleetView® is being integrated into CAISO planning and operations tools to provide power...
Clean Power Research received a California Solar Initiative (CSI) Research, Development, Demonstration and Deployment...
Lean how SolarAnywhere® FleetView® is being integrated into CAISO planning and operations tools to provide power...
Learn how SolarAnywhere® FleetView® can be used for behind-the-meter PV fleet forecasting. Presented at the Utility...
This paper summarizes the deployment of a 71 station solar monitoring network in Sacramento, Calif., and its use in...
This paper summarizes and analyzes recent research by the authors and others to understand, characterize, and model...
In April 2010, Clean Power Research received a California Solar Initiative (CSI) Research, Development, Demonstration...
This paper describes the initial validation of a method of quantifying PV variability by using satellite-derived solar...
This paper introduces a novel approach to estimating the maximum short‐term output variability that an arbitrary fleet...
This article focuses on station pairs, and investigates the correlation of their short-term variability as a function...
This paper describes analytical methods and tools to quantify PV fleet output variability that can be used by utility...
This article presents a set of empirical models capable of extracting metrics quantifying the short‐term variability...
This paper introduces a novel approach to estimate the maximum short‐term output variability that a fleet of PV...
This presentation describes methods for evaluating the power output variability of PV fleets, and how that information...
This paper presents a new approach to rigorously quantify power output variability from a fleet of PV systems, ranging...
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...