Stanford researchers Jiafan Yu and Zhecheng Wang have used a machine learning algorithm and thousands of satellite images to identify nearly every solar power installation in the contiguous 48 states. This new database has produced an unprecedented array of information about the conditions that encourage installation of solar panels, with the promise of more findings to come. The group’s data could be useful to utilities, regulators, solar panel marketers and others. Yu is supported by a State Grid Fellowship from Stanford Energy’s Bits & Watts initiative.
You can read more about DeepSolar's findings in the December 19, 2018 Stanford Report news story.
To access the interactive database, visit the project website at: http://web.stanford.edu/group/deepsolar/home
The Bits & Watts Community Forum is builds a community of Stanford students, faculty, and researchers doing work on the future electric grid. Engineers, lawyers, policy experts, economists, and psychologists alike are invited to participate. The gathering provides a regular opportunity for the Stanford research and industry communities to network and discuss the latest ideas and news about grid research and innovations. The Community Forum takes place on Thursdays during Stanford term time.
To learn more about the Bits & Watts Initiative, contact firstname.lastname@example.org or visit the initiative’s website at https://bitsandwatts.stanford.edu/ .