Fault Identification for Photovoltaic Systems Using a Multi-Output Deep Learning Approach

•Fault classification and localization are carried out in a photovoltaic system.•A multi-output scalable machine- and deep-learning approach is developed.•A 50% reduction in the number of sensors needed per string is achieved.•Deep Learning models are more resilient to noise and are more accurate.•Accuracy up to 99.98% and cross-entropy loss as low as 0.002 are attained.