Detection and Classification of Faults in Residential PV Systems with a Synthetic PV Training Database: A Machine Learning-Based Approach Using the PVMD Toolbox to Generate Synthetic PV Yield Data

In this thesis, a new photovoltaic fault detection and classification method is proposed. It combines the generation of a synthetic photovoltaic training database and the use of a machine learning model to detect and classify faults in small-scale residential PV systems. The database was generated in Matlab, and the machine learning modeling was...