Intelligent learning based performance monitoring of PV arrays

Abstract

PV systems use solar energy to generate electricity and have enormous generation newlinepotential as well as widespread implementation around the world. Despite newlineexponential technological advancements in PV technology, systems are still newlineprone to various types of breakdowns that degrade system performance. As a newlineresult, continuous monitoring of PV systems is critical to ensure fault-free newlineoperation and early detection of any potential faults. This thesis investigates newlinevarious intelligent learning technique-based fault diagnosis strategies that can newlineefficiently diagnose faults. The initial focus is on a fault diagnosis strategy based newlineon the RUSBoost algorithm. newline