Design, contrôle et tests des performances en temps réel d’un convertisseur quasi-Z-source à courant continu pour un système photovoltaïque autonome

Abstract

As renewable energies are increasingly integrated into power grids, studies are being carried out to improve the efficiency of energy conversion systems. Reducing production costs and maximizing consumption of renewable resources are global challenges. In terms of implementation costs, photovoltaic energy is a very promising energy source. In this context and as part of my research project, a DC-DC boost converter named Quasi-Z-Source (QZS) to integrate this stochastic source safely and cost-effectively is suggested. An in-depth study and mathematical model of a QZS converter are presented. The development and testing of a control technique based on artificial intelligence (AI) are exposed to optimize the energy generated by the photovoltaic panels (PV) in presence of different weather conditions. It is shown how the AI-based MPPT technique is selected compares using other technologies like Perturbation and Observation (P&O) based technique. An entire system, including control, is tested in a prototype in a laboratory. According to the results obtained, the proposed elements of the full configuration are properly configured, controlled, and designed.

Date	18 Dec 2023
Original language	French
Awarding Institution	École de technologie supérieure
Supervisor	Ambrish Chandra (Supervisor) & Miloud Rezkallah (Co-supervisor)