As part of the Obama Administration’s SunShot Initiative, the US Department of Energy (DOE) today (January 30) announced it will invest around $9 million spread across seven projects in six states that entail making use of new “Big Data” analytical tools to accelerate solar energy deployment and realize further reductions in solar energy costs.
The funding will be for research teams in California, Colorado, Connecticut, Massachusetts, North Carolina, and Texas. The projects “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 affordable, clean solar energy,” the DOE stated in a press release.
Harnessing Computational Power to Drive Ongoing Advances in Solar PV
The underlying goal of the DOE’s new $9 million solar energy R&D investment is to “help scientists, project developers, system installers, and communities to work together to discover previously unexplored ways to improve solar cell efficiency, reduce costs, and streamline installation processes.”
“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,” Energy Secretary Steven Chu said. “Projects like these will help accelerate technological and financing innovations—making it easier for American families and businesses to access clean, affordable energy.”
In Europe, prices for solar PV panels dropped between 30% and 41% between September 2011 and September 2012, and between 51% and 64% for the two years to end September 2012, according to a recently released report from the International Renewable Energy Agency (IRENA), sister site Green Building Elements reported, with further reductions out to 2020 anticipated.
The median installed price of residential and commercial PV systems in California dropped between 3% and 7% during the first six months of 2012, following year-over-year reductions of between 11% and 14% in 2011, according to the most recent Department of Energy Lawrence Berkeley National Laboratory’s “Tracking the Sun” report. Overall, installed costs for home solar PV panels for all of 2012 ranged between $1750 and $2500 per kilowatt (kW), or $1.75–$2.50 per watt, according to Renewable Green Energy Power data.
Meanwhile, the amount of solar PV on the grid in the US nearly doubled in 2011, a record year, and quadrupled between 2008 and 2011, according to the Energy Information Administration (EIA)’s new survey-based estimate of national solar power capacity.
The DOE aims to spur cost reductions and accelerate deployments further with its latest investments in developing powerful new analytic tools. Seven of the $9 million will go to research teams led by researchers at Sandia National Laboratories, the National Renewable Energy Laboratory (NREL), Yale University, and the University of Texas-Austin. These teams, in turn, will partner with private and public financial organizations, 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,” the DOE explains.
Yale University, for instance, will be partnering with SmartPower’s New England Solar Challenge team to design and implement innovative strategies to boost the effectiveness of community bulk solar PV system purchases. Residents of Salt Lake City who signed up to participate in the solar PV system bulk buying program organized as part of the Wasatch Rooftop Solar Challenge have realized savings of 40% on the total installed cost of their rooftop PV systems, according to a recent DOE report.
The University of Texas-Austin research team will work with large, complex sets of data from six Texas utilities to better understand the needs of customers and identify opportunities that streamline PV system installation and interconnection.
In an effort that entails developing a computational model capable of analyzing data across some 1,300 solar installation companies, NREL and Clean Power Finance aim to create new forms of financing vehicles at the community and regional scales.
Examining the vast amount of historical data pertaining to research, development, and deployment of solar energy, the DOE is providing $2 million in funding for three projects led by the University of North Carolina-Charlotte (UNC-Charlotte), the Massachusetts Institute of Technology (MIT), and SRI International. The research teams will “anlayze decades’ of scientific publications, patents, and cost and production data… to obtain a complete picture on the U.S. solar industry, discover methods to accelerate technological breakthroughs, and remove roadblocks to greater cost reduction,” the DOE explains.
Supporting this initiative, SRI International will be developing software capable of reading and analyzing thousands of scientific publications and patents. Teams at MIT and the UNC-Charlotte will apply computational tools to such data sets in order to accelerate further cost reductions and better forecast the path of declining costs for new energy technologies.