DOE Makes New Solar Energy Grid Investments
As part of its SunShot Initiative, the Department of Energy announced a $29 million investment in four projects that will help advance cost competitive renewable energy for U.S. families and businesses.
These projects are aimed at improving grid connection and reducing installation costs through innovative plug-and-play technologies and reliable solar power forecasts.
“The price of solar panels has fallen dramatically in recent years, but we also need to reduce the cost and time required to actually install them in homes and businesses, and help utility companies better integrate renewable energy into the grid.” said Energy Secretary Steven Chu. “Projects like these can help reduce the cost of solar power and make it easier for American families and businesses to access clean, affordable energy.”
Plug-and-Play Photovoltaic Systems
Plug-and-play PV systems will make the process of buying, installing and connecting solar energy systems faster, easier and less expensive for homeowners. This effort is part of the DOE’s broader initiative to bring down “soft” or non-module hardware costs, which now account for a majority of the total costs of residential systems.
Based in Cambridge, Massachusetts, Fraunhofer USA’s Center for Sustainable Energy Systems will develop PV technologies that allow homeowners to easily select the right solar system for their house and install, wire and connect to the grid.
Additionally, North Carolina State University will lead a project to create standard PV components and system designs that can adapt simply to any residential roof and can be installed and connected to the grid quickly and efficiently.
Reliable Solar Forecasting
The DOE also announced an $8 million investment in two projects to help utilities and grid operators better forecast when, where, and how much solar power will be produced at U.S. solar energy plants. Enhanced solar forecasting technologies will help power system operators to integrate cost-competitive, reliable solar energy into the electricity grid and provide clean, renewable energy to U.S. consumers.
Through this initiative, the University Corporation for Atmospheric Research, based in Boulder, Colorado, will research methods to understand cloud impact and develop short-term prediction techniques based on this work. In Armonk, New York, the IBM Thomas J. Watson Research Center will lead a new project based on the Watson computer system that uses big data processing and self-adjusting algorithms to integrate different prediction models and learning technologies.
These projects are working with the DOE and the National Oceanic and Atmospheric Association to improve the accuracy of solar forecasts and share the results of this work with industry and academia.
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