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 ...

Electrical power systems engineers need practical methods for predicting solar output power under varying environmental conditions of a single panel. By integrating an Arduino-based real-time data ...

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 ...

An international group of scientists developed a novel dust detection method for PV systems. The new technique is based on deep learning and utilizes an improved version of the adaptive moment ...