Contact: Kathy Lantz (Phone: 303.497.7280)
For the Solar Forecast Improvement Project (SFIP), the Earth System Research Laboratory (ESRL) is partnering with the National Center for Atmospheric Research (NCAR) and IBM to develop more accurate methods for solar forecasts using their state-of-the-art weather models. The Department of Energy (DOE) is funding this effort.
SFIP has three main goals: 1) to develop solar forecasting metrics tailored to the utility sector; 2) to improve solar radiation forecasts from minutes to several hours to two days; and 3) to incorporate solar forecasts into utility and Independent System Operator (ISO) system operations and identify economic and reliability benefits.
NOAA is providing numerical weather prediction (NWP) modeling with new information that will help solar forecasts. Specifically, NOAA is modifying forecasts from the 3-km High-Resolution Rapid Refresh (HRRR) model and an advanced version of the 13-km Rapid Refresh (RAP) model to provide information forecasters need to predict power production from photovoltaic (PV) and concentrating solar power (CSP) systems. NOAA is providing these grids to the NCAR and IBM teams.
NOAA is also providing high-quality, ground-based solar measurements from its Integrated Surface Irradiation Study (ISIS) and SURFace RADiation (SURFRAD) networks. The ISIS and SURFRAD instruments at sites across the U.S. measure incoming direct beam, total and diffuse solar radiation with the high accuracy required to calibrate satellites and verify model output. NOAA also will provide advanced satellite products.
NCAR and IBM began work on SFIP in January 2013, and NOAA began work in May 2014. The project will continue through December 2016.
- ESRL Global Monitoring Division Integrated Surface Irradiance Study (ISIS)
- ESRL Global Monitoring Division Surface Radiation (SURFRAD) Network
- Keeping the lights on...ESRL helps improve solar energy forecasts for more efficient power management
- NREL Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications