Publications Scientifiques

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    Deep learning and wbg devices combining to improve pv system efficiency: anfis-based mppt controller
    (2025) Bouchetob, Elaid; Nadji, Bouchra
    With the escalating demand for renewable energy sources, photovoltaic (PV) systems have emerged as a pivotal solution for sustainable power generation. The efficacy of these systems is paramount for their widespread implementation. This research article delves into the efficiency assessment of silicon carbide (SiC) components within a boost converter integrated into a PV system. Notably, the boost converter switch is under the intelligent control of an adaptive neuro-fuzzy inference system (ANFIS) based maximum power point tracking (MPPT) controller. This innovative approach leverages AI to optimize energy extraction from PV panels, thereby enhancing overall system efficiency. The cooperation of SiC components and AI-driven control presents a novel perspective on robust and efficient PV systems. To substantiate the research, data collected from the Sidi Bel-Abès PV central is utilized to train the ANFIS. The utilization of real-world data enhances the accuracy of the predictive model, thereby increasing its applicability to practical scenarios. Integrating AI technologies with PV systems marks a significant advancement toward intelligent and adaptive energy systems
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    Boosting Reliability: A Comparative Study of Silicon Carbide (Sic) and Silicon (Si) in Boost Converter Design Using MIL-HDBK-217
    (J.J. Strossmayer University of Osijek , Faculty of Electrical Engineering, Computer Science and Information Technology, 2024) Bouchetob, Elaid; Nadji, Bouchra
    Reliability is very important in the world of electronic device design and production, particularly in applications where continuous and flawless performance is a necessity. This directs our attention to the boost converter, which forms the foundation of power electronics, renewable energy systems, and electric vehicles. However, as technology progresses, the choice of materials for these converters is a big challenge. For that, in this paper, the impact of using Silicon Carbide (SiC) devices, with their promising material properties, on the reliability of boost converters is presented. Because the results showed that more than 80% of boost converter failures are caused by semiconductors, the use of SiC materials is assessed by determining its reliability using MIL-HDBK-217 standard. In addition, a comparative study with the use of traditional Silicon (Si) is conducted. The results showed that the failure rate of boost converters based on SiC devices reduced from 8.335 failure/10-6h to 6.243 failure/10-6h. This notable shift in failure rates establishes SiC as a pivotal material in the evolution of boost converter technology, offering a compelling solution to address the persistent challenges associated with semiconductor-related failures.
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    Contribution to The Reliability Study of Photovoltaic Systems Using Static and Dynamic Analysis Methods
    (Inderscience, 2019) Mahdi, Ismahan; Nadji, Bouchra; Simeu-Abazi, Zineb
    The study of reliability has not been received great attention from researchers, an estimation of a lifetime and why not improve enhance is still possible. For that, it is necessary to distinguish the different failure modes, their causes and their effects on solar modules, in our case composed by Silicon, the most spread technology and the most used in the production of electricity. In this article, we will present a contribution to the reliability study of photovoltaic systems. First, the study will be focused on the static analysis of our system by using: structured analysis and design technique and function analysis system technique methods, which make it possible to carry out a functional analysis of our system. Next, our study will be based on the dynamic analysis by using: failure mode, effects, and criticality analysis, fault tree analysis and finally stochastic Petri nets methods. These allow making a dysfunctional analysis of the system by introducing the ‘time’ which is a very important factor in our study
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    Reliability study of a system dedicated to renewable energies by using stochastic petri nets : application to photovoltaic (PV) system
    (Elsevier, 2017) Mahdi, Ismahan; Chalah, Samira; Nadji, Bouchra
    Access to energy is essential to reduce poverty. Globally, around 1.2 billion people, about 16% of the global population, still do not have access to electricity. Knowing that photovoltaic (PV) energy already lengthily showed its evidence in terms of operation and reliability, its development observed an improvement of technologies in terms of solar energy transformation output by the semiconductor, and the research in this field does not cease to progress. However, reliability and availability study of PV systems have not been received great attention from researchers, for that we decided to give it a consideration in our research works. So, we seek to study the reliability of such system by using functional and dysfunctional analysis methods. In this paper, we will be interested in the two parts of PV system: “PV module” composed by Silicon cells, and “the converter” which is the expensive component and the most complex in a PV system