Fault detection in photovoltaic power converter

Abstract

Fault detection is a sub-field of control engineering that is concerned with monitoring a system, and identifying expected fault. The main objective of this thesis is to propose a method for detecting the expected errors in the system converter for photovoltaic energy, And this process is controlled by the expected ratio in the same converter system between its normal state and its abnormal state using machine learning algorithms and determining the detection of expected faults with their location. The KNN, NB and SVM algorithms was used to help us in the study.