Publications Scientifiques

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    SVPWM-Based Control of a Three-Phase Five-Level NPC Inverter for Grid-Connected Solar Power System
    (Institute of Electrical and Electronics, 2025) Elamri, Oumaymah; Toubal Maamar, Alla Eddine; Oukassi, Abdellah; El Kharki, Abdellah; Hammoudi, Abderazek; Mekhilef, Saad
    This study focuses on analyzing a photovoltaic system for energy production and its integration into the grid. Take into account the key grid parameters, including frequency, three-phase system symmetry, and voltage waveforms. Non-sinusoidal voltages can cause interference that affects the operation of networked equipment. To address this issue, a three-phase five-level neutral-point-clamped inverter is incorporated into the system, utilizing the space vector pulse width modulation technique for control. The control strategy of the converter is presented in detail. The study was carried out utilizing Matlab/Simulink, and the simulation outcomes demonstrate the efficiency of this control approach for renewable energy applications
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    Performance evaluation of metaheuristic techniques for optimal sizing of a stand-alone hybrid PV/wind/battery system
    (Elsevier, 2021) Fares, Dalila; Fathi, Mohamed; Mekhilef, Saad
    This study presents a performance evaluation of ten metaheuristics optimization techniques that are applied to solve the sizing problem for a stand-alone hybrid renewable energy system including a photovoltaic module, wind turbine, and a battery (PV/WT/Battery). The algorithms include genetic algorithm (GA), cuckoo search (CS), simulated annealing (SA), harmony search (HS), Jaya algorithm, firefly optimization algorithm (FA), flower pollination algorithm (FPA), moth flame optimization (MFO), brainstorm optimization in objective space (BSO-OS), and the simplified squirrel search algorithm (S-SSA). The optimization process aims to minimize the total net present cost (TNPC) of the system while maintaining the acceptable deficiency of power supply probability (DPSP). The levelized energy cost and the relative excess power generated criteria are also considered. The studied algorithms have been simulated for four DPSP values (0%, 0.3%, 1%, and 5%), each for 50 independent runs. Based on the simulation results, FPA and SA demonstrated high robustness and accuracy with zero standard deviation and a 0% increase in the TNPC values compared to the optimal solutions. The FAO showed the best performance in terms of execution time with an average of 6.32 s, followed by BSO-OS (6.36 s) and SA (7.84 s). The SA has the best compromise between robustness, accuracy, and rapidity, and is found to be the best option to solve the sizing problem. The FPA is the most advantageous in case the execution time is not crucial for the optimization. Our findings will be a good reference for researchers to select the best technique for the sizing problem
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    State feedback control for stabilization of PMSM-based servo-drive with parametric uncertainty using interval analysis
    (Wiley, 2021) Khelouat, Lila; Ahriche, Aimad; Mekhilef, Saad
    For a class of multivariable uncertain dynamic systems, the parametric uncertainties are belonging to a closed interval with lower and upper boundaries a priori known. Thereby, these systems can be analyzed based on interval structures and interval matrices. In this article, a fully interval analysis–based method is developed and applied to the state feedback control of permanent magnet synchronous motor (PMSM) in order to design a stabilized servo-drive. Indeed, the parametric uncertainties are investigated in state space representation, which represents a simplified and effective way to analyze the robust stability for the interval system. Firstly, a robust state feedback control technique, dedicated to an uncertain system is introduced. For that, the robust controllability test is performed for the interval system by using the linear independency condition of column interval vectors. It is proven that there is a direct correlation between the controllability test and the existence of a robust modal P-regulator for the correction of the uncertain system. It is also shown that it invariably relies on each input's controllability indices and thus their effect on the uncertain system's state variables. In order to ensure stability in a closed loop, the modal P-regulator is designed with possibility of incorporation of an integral action. The modified modal PI regulator has the ability to reject disturbance and guarantee zero-steady-state error for step inputs. In fact, the stability is achieved by placing all coefficients of the system characteristic polynomial within assigned intervals based on Kharitonov's Theorem. The technique provides a matrix gain with interval coefficients for the stabilizing regulator. Finally, the developed approach is applied to position control of linearized model of the PMSM-based servo-drive, presenting parametrical uncertainties. To demonstrate the efficiency of the proposed method, a numerical and graphical comparison of conventional LQR and pole placement, state feedback controllers for the PMSM servo-drive with the robust interval controller is provided. In order to verify the feasibility of the whole proposed technique, calculations and simulations are performed by using Matlab/Intlab toolbox. Real-time simulation is also investigated using Lab-View Compact-RIO
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    Nonparametric Kullback-divergence-PCA for intelligent mismatch detection and power quality monitoring in grid-connected rooftop PV
    (Elsevier, 2019) Bakdi, Azzeddine; Bounoua, Wahiba; Mekhilef, Saad; Halabi, Laith M.
    In parallel to sustainable growth in solar fraction, continuous reductions in Photovoltaic (PV) module and installation costs fuelled a profound adoption of residential Rooftop Mounted PV (RMPV) installations already reaching grid parity. RMPVs are promoted for economic, social, and environmental factors, energy performance, reduced greenhouse effects and bill savings. RMPV modules and energy conversion units are subject to anomalies which compromise power quality and promote fire risk and safety hazards for which reliable protection is crucial. This article analyses historical data and presents a novel design that easily integrates with data storage units of RMPV systems to automatically process real-time data streams for reliable supervision. Dominant Transformed Components (TCs) are online extracted through multiblock Principal Component Analysis (PCA), most sensitive components are selected and their time-varying characteristics are recursively estimated in a moving window using smooth Kernel Density Estimation (KDE). Novel monitoring indices are developed as preventive alarms using Kullback-Leibler Divergence (KLD). This work exploits data records during 2015–2017 from thin-film, monocrystalline, and polycrystalline RMPV energy conversion systems. Fourteen test scenarios include array faults (line-to-line, line-to-ground, transient arc faults); DC-side mismatches (shadings, open circuits); grid-side anomalies (voltage sags, frequency variations); in addition to inverter anomalies and sensor faults
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    A novel global MPPT technique based on squirrel search algorithm for PV module under partial shading conditions
    (Elsevier, 2021) Fares, Dalila; Fathi, Mohamed; Shams, Immad; Mekhilef, Saad
    The partial shading condition (PSC) makes it challenging for the PV system to harvest maximum power via maximum power point tracking (MPPT). Various MPPT algorithms based on bio-inspired optimization methods were proposed in the literature. The mechanism employed by these algorithms varies from one to another, making them perform differently when tracking the GMPP. This paper introduces a novel MPPT technique based on the improved squirrel search algorithm (ISSA). The performance of the proposed ISSA improved the tracking time by 50% in comparison with the conventional SSA algorithm. Similarly, the proposed method has also been compared with popular Genetic algorithm (GA), and particle swarm optimization (PSO). The results proved the ability of the proposed algorithm in tracking the GMPP with faster convergence and fewer power oscillations in comparison. The feasibility and effectiveness of the proposed ISSA based MPPT have been validated experimentally, and the results clearly demonstrate its capability in tracking the GMPP with an average efficiency of 99.48% and average tracking time of 0.66 s.