The process of testing new solar cell technologies has traditionally been slow and costly, requiring multiple steps. Led by a fifth-year PhD student, a Johns Hopkins team has developed a machine ...

Researchers at Sweden's Uppsala University have applied deep machine learning to automatically identify photovoltaic and solar-thermal systems in aerial imagery and said their work yielded mixed ...

The software tool uses self-supervised learning to detect long-term defects in solar assets weeks or years before ...

Researchers from Stony Brook University, in collaboration with Ecosuite and Ecogy Energy, have developed a self-supervised machine-learning algorithm designed to identify physical anomalies in solar ...

Kicking your utility to the curb sounds like a great deal, but it's more difficult than it sounds. Here's what it takes to go off the grid with solar panels. CNET contributor Eric Mack knows all too ...