AI Program Finds More Solar Installations Than Expected in U.S.

A new machine learning program developed by Stanford University, DeepSolar, offers a quantitative first look at how many solar energy systems have been installed in the U.S.

DeepSolar trawled through more than 1 billion satellite images of the country and found 1.47 million rooftop solar systems or solar plants in 48 states, Fast Company reports, far surpassing previous estimates. With no official central database to report these installations, previous estimates of the number of U.S. installations were lower: 1 million, based on volunteer data in the Open PV database, and 0.67 million counted by Google’s Project Sunroof, a project that also uses AI and satellite data, though methodology for the program isn't published.

Knowing how many solar panels exist–and where they are–can help renewable power run smoothly and grow faster. “Utilities and system operators can figure out where there’s more solar power being produced, in which neighborhoods, and adjust their operations and planning,” says Ram Rajagopal, an associate professor of civil and environmental engineering at Stanford, and one of the authors of a new study about the project. “For example, a utility can decide to invest in storage after looking at this data.”

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