EPRI wins $1.8 million for solar forecasting technology research

The Electric Power Research Institute won a $1.8 million award from the U.S. Department of Energy Solar Energy Technologies Office to develop and demonstrate new methods to operate power systems with high penetrations of solar power.

The award is part of the Solar Energy Technologies Office’s Solar Forecasting 2 funding program to advance predictive modeling capabilities for solar generation for more accurate forecasts of solar generation levels.

Solar Forecasting 2 projects are designed to enable electric utilities to better manage the variability and uncertainty of solar power and improve grid reliability.

EPRI’s project, “Operational Probabilistic Tools for Solar Uncertainty,” will use solar power forecasts to capture the uncertainty inherent in solar power output. Using actual data from three energy companies, the research will develop a platform that enables new power system operating methods and tools.

The project has three objectives:

·      Develop improved probabilistic solar power forecasts for both utility-scale and distributed solar.

·      Design advanced use cases for probabilistic forecasts through detailed simulation of power system operations for three energy companies.

·      Develop and demonstrate a scheduling management platform that enables the integration of forecasts into operations.

The three energy companies, Hawaiian Electric, Duke Energy, and Southern Co., offer diverse operating practices at various stages of solar installation and integration, including specific system characteristics such as the size of the region; current and expected solar penetration; daily and seasonal load shape; generation mix; and other factors. These diverse experiences with solar may allow for combined results from the project to provide a broad range of lessons for solar integration across the entire power industry, while providing specific results for the three companies.

Hawaiian Electric, Duke Energy, and Southern Co. are providing an additional $760,000 for the project in the form of cost share, bringing total funding for the research up to about $2.6 million.


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