The U.S.
Department of Energy (DOE) has announced $12 million in new funding for eight
projects to advance predictive modeling capabilities for solar generation. The DOE says
these models will lead to more accurate forecasts of solar generation levels, enabling
utilities to better manage the variability and uncertainty of solar power and improve grid
reliability.
“These projects will address a critical gap in our research, which is knowing precisely
how much solar electricity to expect at any given hour on any given day,” states U.S.
Secretary of Energy Rick Perry. “These tools are becoming more important as the solar
industry continues to grow and will work to ensure that solar contributes to the
reliability, affordability, and resilience of our nation’s electric grid.”
According to the DOE, the new funding will advance solar forecasting technologies in a
coordinated way with partnerships between national labs, universities, and industry.
Posted by Joseph Bebon – December 20, 2017
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Four projects are aimed at making significant advances in predicting solar generation.
Another project at the University of Arizona will build a testing framework to allow
industry and academia to evaluate and compare the performance of advanced models
according to a transparent set of rules and metrics.
Finally, three projects will study the integration of advanced forecasting technologies
with grid planning and operations systems in partnership with the California Independent
System Operator, the Midcontinent Independent System Operator, and the Electric
Reliability Council of Texas. The DOE says this research will validate whether these
technologies can be efficiently integrated into energy management systems and
enhance grid operation efficiency, while working to identify any future research needs.
The DOE’s Solar Energy Technologies Office supports early-stage research and
development to improve the reliability and performance of solar technologies. This new
$12 million DOE investment will spur an additional $2.6 million of private-sector funding
through cost share requirements, yielding a total public and