Detection, classification, and localization of faults and failures in photovoltaic arrays: a review, comparative analysis, and path forward

Photovoltaic (PV) systems are being increasingly integrated to support a sustainable and resilient power grid. However, as one of the most physically exposed components, they are vulnerable to various faults and failures, which hinder its performance, safety, and reliability. This review article presents a comprehensive analysis of PV faults and performance degradation mechanisms, focusing on detection, classification, and localization techniques. Three major categories of degradation: external, internal, and system level faults are identified and examined. This review consolidates these insights to evaluate the strengths and limitations of state of the art fault detection techniques and highlights gaps in fault localization, and real world robustness. Recent image based diagnostic methods achieve over 90–99% accuracy in detecting panel defects, while arc fault detection methods report detection times as low as 5 microseconds. The key contributions of this study include: (i) a unified categorization of all major PV faults and failures; (ii) a comparative analysis of existing detection, classification, and localization methods; and (iii) a structured path forward emphasizing reliability under real world operating conditions. This work aims to support researchers and industry practitioners in developing more effective and resilient PV fault diagnosis technologies.