DOE Announces $29M to Bring Down Costs for Solar Installation

The Department of Energy (DOE) on Friday announced a $29 million investment in four solar projects aimed at improving grid connection and reducing installation costs through plug-and-play technologies and reliable solar power forecasts. The awards are part of the agency’s SunShot Initiative, which is working to make solar energy competitive with other forms of energy without subsidy by the end of the decade.

The agency made a five-year $21 million investment to design plug-and-play photovoltaic (PV) systems that can be purchased, installed, and operational in one day. “Plug-and-play PV systems will make the process of buying, installing and connecting solar energy systems faster, easier and less expensive for homeowners,” the DOE said. This effort is part of the agency’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 it 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 be installed and connected to the grid quickly and efficiently.

The Energy Department 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 Energy Department and the National Oceanic and Atmospheric Administration to improve the accuracy of solar forecasts and share the results of this work with industry and academia.

The price of solar panels has fallen dramatically in recent years, but much work remains to reduce the cost and time required to actually install solar panels at homes and businesses, and for utility companies to better integrate solar power into the grid, noted 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."

Source: DOE

—Edited by Sonal Patel, Senior Writer (@POWERmagazine)

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