Study of different diagnosing methods faults in a photovoltaic system

Abstract

This memoir explores the simulation and analysis of photovoltaic (PV) systems, focusing on fault detection and diagnosis (FDD). Chapter 1 provides an overview of PV systems, including their history, types of PV cells, and operational principles. Chapter 2 categorises FDD methods into signal processing, AI techniques, and inference methods, discussing their applications, benefits, and limitations. Chapter 3 details the creation and validation of a custom PV array (60 cells) and the development of a 4x4 PV farm. It includes simulations of three fault scenarios (partial shading, bypass diode failure, and line-to-line faults), each evaluated under two cases. Signal processing methods (I-V and P-V curve analysis) assess performance differences between normal and faulty states. The findings highlight the impact of faults on PV system efficiency and provide recommendations for improved fault detection.