Fault diagnosis of photovoltaic modules: A review

Abstract

The fault diagnosis technology of photovoltaic (PV) components is very important to ensure the stable operation of PV power station. The application of intelligent fault detection method can effectively improve the accuracy and efficiency of fault detection. In this paper, the latest progress in the field of PV module fault diagnosis in recent years is reviewed, with emphasis on fault detection methods based on electrical characteristic parameters and image processing technology. Firstly, this paper introduces the types, causes and traditional diagnosis methods of the common faults of PV modules. Then, the fault detection technology based on electrical characteristic parameters was discussed, including the method based on I-V characteristic curve analysis and mathematical model. Then, the paper reviews the fault detection technology based on image processing, especially the application of unmanned aerial vehicle (UAV)-assisted image detection technology in fault location and identification of PV modules, and focuses on the development and challenges of machine vision technology in fault detection. Finally, the existing data sets and performance evaluation indicators are summarized, and the development trend of intelligent fault diagnosis technology for PV modules in the future is prospected. This paper aims to provide reference for researchers in related fields and promote the innovation and development of PV module fault diagnosis technology.