DOE Using Data Analytics To Lower Cost Of Solar Energy


As part of its SunShot Initiative, the U.S. Department of Energy (DOE) is investing approximately $9 million in seven data-driven projects designed to unearth new opportunities for reducing costs and accelerating solar energy deployment in the U.S.

The projects – located in California, Colorado, Connecticut, Massachusetts, North Carolina and Texas – will result in viable methods for dramatically transforming the operations of solar researchers, manufacturers, developers, installers and policymakers, and speed the commercialization and deployment of solar energy, the DOE says.

‘Through powerful analytical tools developed by our nation's top universities and national labs, we can gain unparalleled insight into solar deployment that will help lower the cost of solar power and create new businesses and jobs,’ says DOE Secretary Steven Chu. ‘Projects like these will help accelerate technological and financing innovations, making it easier for American families and businesses to access clean, affordable energy.’

The projects will help scientists, project developers, installers and communities work together to discover previously unexplored ways to improve solar cell efficiency, reduce costs and streamline installation processes.

As part of the investment, the DOE will provide $7 million to research teams, led by Sandia National Laboratories, the National Renewable Energy Laboratory (NREL), Yale University and the University of Texas-Austin. These teams will partner with public and private financial institutions, utilities and state agencies to apply statistical and computational tools to industry problem-solving and lead regional pilot projects across the country to test the impact and scalability of their innovations.

For example, Yale University researchers will partner with SmartPower's New England Solar Challenge to design and implement innovative strategies that can increase the effectiveness of community-led bulk solar purchase programs. The team from the University of Texas-Austin will work with complex data sets from six Texas utilities to better understand customer needs and to identify opportunities to streamline installation and interconnection, the DOE explains.

Similarly, NREL will lead another project with Clean Power Finance to develop a computational model that will analyze data from over 1,300 solar installation companies to establish new types of community- and regional-scale financing structures.

Additionally, the DOE is investing $2 million across three projects led by the University of North Carolina-Charlotte (UNC Charlotte), the Massachusetts Institute of Technology (MIT) and SRI International to analyze decades' worth of scientific publications, patents, and cost and production data. Through these projects, researchers will be able to obtain a complete picture of the U.S. solar energy industry, discover methods to accelerate technological breakthroughs, and remove roadblocks to greater cost reduction, the DOE explains.

Menlo Park, Calif.-based SRI International will develop advanced software that reads and analyzes thousands of scientific publications and patents to discover new ways to speed solar energy technology innovation and commercialization. Meanwhile, MIT and UNC Charlotte will apply computational tools to patent, cost and production data in order to speed up solar technology cost reductions and better forecast future cost reductions for new energy technologies.

More information on the projects is available here

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