Article Per Year (5 Year)
p-Index From 2021 - 2026
0.444
P-Index
This Author published in this journals
All Journal International Journal of Power Electronics and Drive Systems (IJPEDS)
Toumi, Djaafar
Unknown Affiliation
Control & Systems Engineering Electrical & Electronics Engineering

Published : 2 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 2 Documents
Search

 1 
Shunt active power filter control based on Z-source inverter fed by PV system Abdelkarim, Ahfouda; Youcef, Bekakra; Toumi, Djaafar; Ibrahim, Ahmed; Zellouma, Laid; Messaoud, Hettiri
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 15, No 3: September 2024
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v15.i3.pp1777-1787

Abstract

In this paper, an integration of a Z-source inverter (ZSI)-based shunt active power filter (SAPF) fed by a photovoltaic (PV) system for the enhancement of power quality is proposed. The ZSI provides substantial advantages including improved boost functionality, reduced harmonics, and superior performance compared to traditional inverters. In this paper, the SAPF control is based on instantaneous reactive power theory. A proportional-integral (PI) controller is implemented for DC-link voltage control, with the primary aim of this study being the elimination of total harmonic distortion (THD) in the source current. To demonstrate the effectiveness of the proposed approach, simulations were conducted using MATLAB/Simulink across various operating conditions. The outcomes substantiate and validate the efficacy of the proposed method.
Study of neural controller based MPPT in comparison with P&O for PV systems Toumi, Djaafar; Tiar, Mourad; Boucetta, Abir; Boucetta, Ikram; Ibrahim, Ahmed
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 17, No 1: March 2026
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v17.i1.pp797-808

Abstract

This study investigated the performance of two prominent maximum power point tracking (MPPT) strategies: the established perturb and observe (P&O) technique and an artificial neural network (ANN)-based controller. Through simulations conducted in MATLAB/Simulink, a 50 W photovoltaic (PV) array was evaluated under dynamic irradiance and temperature variations. Notably, data generated by the P&O system served as the training dataset for the ANN model. The simulation results indicate that the ANN controller effectively and accurately identifies the PV system’s optimal operating point even amidst fluctuating environmental conditions. When compared to the conventional P&O method, the ANN approach demonstrated superior characteristics, including a significantly faster response, diminished oscillations around the maximum power point, and enhanced tracking accuracy during rapid environmental shifts. These findings underscore the substantial potential of ANN-based MPPT strategies for improving both the efficiency and operational stability of photovoltaic power systems.
Co-Authors Abdelkarim, Ahfouda Boucetta, Abir Boucetta, Ikram Ibrahim, Ahmed Messaoud, Hettiri Tiar, Mourad Youcef, Bekakra Zellouma, Laid