Fault diagnosis in a photovoltaic system through I-V characteristics analysis

In the photovoltaic field, regarding the importance of sustainability, monitoring systems are a paramount component for yield assessment. Yet in the industrial production, fault detection remains a manually handled issue. However, faults are responsible for significant power loss and sometimes, even dramatically damages are reported such fire hazard or material deterioration. This paper presents a methodology for fault detection in the photovoltaic system regarding the different impacts of faults on the I-V curve. Indeed, fault classification is a crucial step for the failure diagnosis. The proposed method mainly covers uniform dust faults, partial shading faults, short circuit faults, and aging. The proposed algorithm is assessed through a simulation on Matlab Simulink and finally, it is validated using experimental I-V curves measurements in faulty cases.