This project meets a strong national need for the development of renewable energies and the Smart Grid. It is being set up in collaboration with Tunisian industrial partners. In Tunisia, as elsewhere in the world, photovoltaic (PV) solar energy is playing an increasingly important role in the production of electricity, thanks to its non-polluting nature and sustainability. By way of indication, total worldwide installed capacity in 2019 was estimated at 116.9 GW, with an increase of around 13% on the previous year. Tunisia enjoys a strategic geographical location that is highly favorable to the exploitation of this source, with daily sunshine levels of around 1,800 Wh/m²/day. The State's strategy in this energy field is to achieve a PV inverter installation capacity of around 30% of national electricity production. This increase in renewable resources will support the Tunisian power grid, especially during peak summer periods, when conventional power plants are no longer able to cope with the growing demand for electricity, thereby compromising the stability of the Tunisian power grid.
This research project is divided into several sub-projects:
The aim of this project is to improve the quality of injection of renewable electrical energy into the power grid. We have developed high-efficiency single-phase and three-phase converter structures, while reducing the electromagnetic disturbances generated by the converter, as well as leakage current. We have designed and built a three-phase current inverter that is more reliable than a voltage inverter, and can be connected to the grid at low DC bus voltages. So, in order to improve the efficiency of this PV converter, we studied the impact of using SiC components on converter losses. For this purpose, we adopted the double pulse test technique and PLECS software to evaluate the converter's efficiency.
This work was carried out in collaboration with Professor Kamal Al-Hadda Canada Research Chair in Energy Conversion and Power Electronics, ETS de Montreal, Canada.
Leader: Hamouda Mahmoud
Team: Ben Hadj Slama Jaleleddine, Boudhir Kraiem Sana, K. Ezzeddine
The aim of this project is to guarantee the permanent injection of renewable energy into the electrical grid, even when the latter presents disturbances such as voltage dips, harmonics and frequency variations.
We have developed techniques for fast, accurate extraction of fundamental components, unbalance and offset, even in the event of frequency jumps. This has been tested and validated under highly disturbed network voltage conditions. The results obtained in simulation and real-time emulation demonstrate the effectiveness of this approach in estimating, with high accuracy, the instantaneous parameters of the grid voltage without any steady-state ripple, and without the integration of adaptive filters.
This work is developed in collaboration with Professor Kamal Al-Haddad Canada Research Chair in Energy Conversion and Power Electronics, ETS de Montreal, QC, Canada.
Manager: Ben Hadj Slama Jaleleddine
Team: Hamouda Mahmoud, Mellouli Mohamed
The reliability of photovoltaic inverters is essential to guarantee continuity of service on the electricity grid. In this project, we are developing intelligent fault diagnosis methods for photovoltaic inverters, based on the analysis of the electromagnetic signature of these inverters, using advanced signal processing techniques. These methods will be extended in a second stage to prognosticate component ageing.
The proposed methodology was initially validated on a three-phase NPC inverter. The method was then adapted for application to other advanced structures, using various signal processing analyses. The proposed method is capable of detecting and isolating a single open switch fault in a five-level U-cell single-phase inverter (type PUC5).
Numerical and experimental validations have shown that the proposed method is robust to variations in load current and operating parameters.
With a view to using electromagnetic disturbances as a signature of power component ageing, we are implementing advanced signal processing techniques such as autocorrelation...
This work is developed in collaboration with Professor Kamal Al-Haddad Canada Research Chair in Energy Conversion and Power Electronics, ETS de Montreal, QC, Canada.
Manager: Ben Hadj Slama Jaleleddine