NOVEL EMBEDDED SYSTEM FOR REAL TIME FAULT DIAGNOSIS OF PHOTOVOLTAIC MODULES

Abstract

The innovative embedded technology described here can improve the efficiency and dependability of solar energy systems by detecting problems with photovoltaic (PV) modules in real time. To detect, categorize, and foresee problems like discoloration, degeneration, and hotspots, the system employs sophisticated machine learning algorithms and data processing techniques. The suggested technique leads to more efficient power generation, fewer power outages, and lower maintenance costs. An important resource for green power administration, the system has been experimentally validated to prove its rightness and efficacy in actual photovoltaic configurations.