Performance Monitoring Algorithm for Detection of Encapsulation Failures and Cell Corrosion in PV Modules

This research work aims to develop a fault detection and performance monitoring system for a photovoltaic (PV) system that can detect and communicate errors to the user. The proposed system uses real-time data from various sensors to identify performance problems and faults in the PV system, particularly for encapsulation failure and module corrosion. The system incorporates a user interface that operates on a micro-computer utilizing Python software to show the detected errors from the PV miniature scale system. Fault detection is achieved by comparing the One-diode model with a controlled state retrieved through field testing. A database is generated by the system based on acceptable training data and it serves as a reference point for detecting faults. The user is notified of any deviations based on the threshold value from the training data as an indication of an error by the system. The system offers real-time monitoring, easy-to-understand error messages, and remote access capability, making it an efficient and effective tool for both users and maintenance personnel to manage and maintain the PV system.