Conception d’un système de supervision d’une installation photovoltaïque dédié à la détection et à la localisation des défauts à l’aide de techniques intelligentes

Abstract

Solar energy systems are efficient in generating electricity in a clean manner. The use of this system in domestic and industrial systems has led to malfunctions in its installations. These systems break down when operating, necessitating the introduction of a diagnostic system to maintain maximum power by quickly identifying faults and correcting them. Fault detection algorithms in photovoltaic systems based on fuzzy logic, artificial neural networks and fuzzy neural networks are developed in this work. Calculate the voltage and current values produced by each element of the photovoltaic system and process them by the control device, which determines the nature of the fault. The results show that many faults in the photovoltaic field, the DC-DC converter and the battery can be detected using AI smart control by calculating the voltage and current.