Research: Solar Prediction

Research: Solar Prediction

Observed Recent Trends in the Solar Resource across North America: Changing Cloud-cover, AOD and the Implications for PV Yield
+  |  September 2020

In years recent to 2020, low solar-resource in the Eastern U.S. was observed in the SolarAnywhere® dataset. This paper...

Improved PV System Modeling with ML-Based Power Model: Case Study of a Commercial Building
+  |  September 2019

Solar PV system specifications are critical to accurately modeling PV system production (along with high-quality...

EPIC Solar Forecasting Task 3 Final Report: Grid-Connected and Embedded PV Fleet Forecasting Accuracy
+  |  July 2019

This report, prepared with an Electric Program Investment Charge (EPIC) fund, describes new methods for improving...

EPIC Solar Forecasting Task 2 Final Report: Data Forecasting Accuracy
+  |  July 2019

This report, prepared with an Electric Program Investment Charge (EPIC) fund, describes the results of research to...

Advancing the Science of Behind-the-Meter PV Forecasting
+  |  July 2019

This presentation discusses how probabilistic forecasting enables electric utilities and grid operators to reduce...

Day-Ahead Irradiance Forecast Variability Characterization Using Satellite Data
+  |  July 2016

This article calculates day-head forecast variability as function of historical clearness index based on intraday...

Importance of Input Data and Uncertainty Associated with Tuning Satellite to Ground Solar Irradiation
+  |  July 2016

Although the uncertainty of satellite data such as SolarAnywhere® Data has been shown to be low, it can be challenging...

Solar Energy Forecast Validation for Extended Areas & Economic Impact of Forecast Accuracy
+  |  July 2016

This article evaluates the accuracy of solar forecast models, including SolarAnywhere®, as a function of geographic...

Integration of Behind-the-Meter PV Fleet Forecasts into Utility Grid System Operations
+  |  May 2016

This paper describes a study, funded by the U.S. Department of Energy, to evaluate new, state-of-the-art solar...

Behind-the-Meter PV Fleet Forecasting
+  |  March 2013

Grid-connected PV in the U.S. has grown substantially over the past several years and grid operators are increasingly...

Forecasting Output for 130,000 PV Systems in California
+  |  February 2013

Lean how SolarAnywhere® FleetView™ is being integrated into CAISO planning and operations tools to provide power...

Reporting of Irradiance Model Relative Errors
+  |  March 2012

Metrics used in assessing irradiance model accuracy such as Root Mean Square Error (RMSE) and Mean Absolute Error...

Off-Shore Wind and Grid-Connected PV: High Penetration Peak Shaving for New York City
+  |  March 2012

This article presents an experimental evaluation of the combined effective capacity of off-shore wind and...

Evaluating Irradiance Accuracy Using California ISO Data: Lessons Learned
+  |  February 2012

This presentation provides the results of a study evaluating the short, medium and long-term accuracy of irradiance...

Blog

Reducing uncertainty with observational MET programs
Jul 8, 2025
Reducing uncertainty with observational MET programs

This week, we’re pleased to present a guest post from GroundWork® Renewables’ Director of Data and Analytics Julie Chard. At GroundWork, we’re committed to delivering high-quality solar-meteorological (MET) data to reduce uncertainty in solar resource assessments. With more than 15 years of experience supporting the solar development community, our observational MET programs combine best-in-class equipment and […]

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The new SolarAnywhere® Probabilistic Forecast enhances risk management
Jun 25, 2025
The new SolarAnywhere® Probabilistic Forecast enhances risk management

PV forecasts are important for energy scheduling and grid stability. Traditional methods for near-term forecasts involve blending an ensemble of Numerical Weather Predictions (NWPs) into a single deterministic output, which is favored because it is simple to implement in operations. However, deterministic forecasts do not convey any information about marginal risks or the propensity for […]

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Streamlining Large Load Request Workflows
Jun 10, 2025
Streamlining Large Load Request Workflows

This year’s DTECH Data Centers and AI conference made it clear that in the era of AI and data centers, large load requests are hitting utilities faster and at greater scale than ever before. Policy, pricing, supply chain, and physical infrastructure are well-known...

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