An Intelligent Faults Diagnosis and Detection Method Based an Artificial Neural Networks for Photovoltaic Array

Abstract

At present, renewable energy has many sources, most important of which are PV systems. It is therefore necessary to contribute to the diagnosis of the state of the photovoltaic system and the detection and diagnosis of malfunction. And identify and resolve failures in photovoltaic systems as quickly as possible, so that the system will operate at the expected levels of performance and reliability, thereby ensuring the expected return on investment. This article proposes modeling, detection and classification of photovoltaic system faults by Artificial neural network: ANN using measured values of the PV system voltage (v) and the current of the PV system (I). The method allows the classification of the PV state into several possible situations: normal operation and some different faults, modeling or simulations of MatLab. This method has proved to be able to detect and identify the faults in the PV array accurately and efficiently.