MOURAD Naidji

Ghozlene Guediri

Impact de la pénétration massive de l'éolien sur la stabilité dynamique des réseaux électriques

Habi mohamed amir , Merdjedjou lina, Achari allaeddine

Surveillance intelligente du réseau de distribution en vue d'une maintenance proactive

Loubna Sadiou , Sara Zoghlami

Etude et protection d’une installation électrique contre les surtensions

Chahinaz Boudinar , Sarah Mazouzi

Analyse des réseaux de distribution en présence des sources d'énergie renouvelable

T. Bachene , A. Nasri

Etude et dimensionnement de l'éclairage d'un bâtiment résidentiel

A. Mksser , F. Allaoui

Etude et dimensionnement de l'éclairage d'un local industriel

Emerging as a vital component in the worldwide shift towards environmentally friendly power generation is wind energy. Maximizing energy output and reducing cost depend on well-designed wind farms, particularly considering the growing demand for renewable energy. This work expands on several ideal wind turbine configurations suggested in previous work and chooses them as basis for more thorough investigation and enhancement. While most previous studies have concentrated mostly on lowering the cost per kilowatt of generated power, this work takes a more all-encompassing view aiming to improve general wind farm efficiency through strategic optimization of turbine tower heights and rotor diameters, so simultaneously lowering total costs. This kind of approach might produce more flexible and efficient wind farms. A Particle Swarm Optimization (PSO) method is used to find the best arrangement of rotor diameters and tower heights over the wind farm in order to reach these targets.

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mourad naidji , Mohamed Ilyas Rahal, Alla Eddine Toubal Maamar, Aicha Aissa-Bokhtache, Maamar Latroch, Radu-Florin Porumb, ,(2025-12-15), A Heuristic Optimization Approach for Wind Turbine Dimensions to Enhance Energy Capture and Reduce Costs,IEEE International Conference on Artificial Intelligence, Embedded Systems, and Renewable Energy (AIESRE),Tizi Ouzou, Algeria

Solar energy has seen remarkable technological advancements with photovoltaic (PV) and floating PV (FPV) technologies leading the way in decentralized power solutions. These technologies not only enhance solar efficiency and affordability but also enable intelligent integration into smart grids, hence enhancing the sustainability and scalability of clean power. This essay delves into next-generation technologies driving the revolution of PV and floating PV systems, their economic viability, environmental-friendliness, and capacity to alter the global energy landscape. The theme of policy incentives and education as drivers of deployment will be shown, and their importance in the future of sustainable energy generation will be emphasized.

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mourad naidji , ,(2025-12-15), Advancements in Solar Energy Systems: Innovations in Photovoltaic (PV) and Floating PV Technologies for Decentralized Energy Generation,IEEE International Conference on Artificial Intelligence, Embedded Systems, and Renewable Energy (AIESRE),Tizi Ouzou, Algeria

This study gives an in-depth analysis of the influence of high penetration of wind turbines (WTs) into power electrical grid transmission systems, focusing on dynamic impacts of wind generation during large system disturbances. The main aim is to assess the effects of integration of wind power on the grid response, especially under fault scenarios. The IEEE 9-bus test system was a basis model for stability analysis. The modeling and simulations were done using PSAT (Power System Analysis Toolbox), along with Matlab. The most significant aspect of the study was to explore the impacts of a three-phase short circuit, a severe fault that generates a severe disturbance in the system. The dynamic research was divided into three phases: pre-fault, fault, and post-fault to capture the total impact on system performance. The results showed important data related to primary electrical and electromechanical variables, identifying the contribution of wind farms to grid stability, and specifically the robustness of the transmission network and its ability to respond to disturbances. Finally, the paper deepens the knowledge of how renewable energy sources (RES), in this case wind power, can assist in enhancing power system stability under severe conditions.

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mourad naidji , Alla Eddine Toubal Maamar, Mohamed Ilyas Rahal, Aicha Aissa-Bokhtache, ,(2025-12-13), Impact of Massive Wind Penetration on the Dynamic Stability of Electrical Transmission Grids,The 1st National Conference on Electronics, Electrical Engineering and Telecommunications,El Bayadh, Algeria

In order to guarantee effective Maximum Power Point Tracking (MPPT), this research proposes an integrated control strategy for a Wind Energy Conversion System (WECS). A drive train carries the mechanical energy that the wind turbine has captured to a Doubly-Fed Induction Generator (DFIG), which transforms it into electrical power. Two control systems are used to maximise this conversion: the reliable Sliding Mode Controller (SMC) and the traditional Proportional-Integral (PI) controller. To optimise power extraction, the main goal is to modify the rotor speed in response to changing wind conditions. To depict the DFIG's behaviour under various operating circumstances, a comprehensive dynamic model is created. This model serves as the basis for a power control strategy that aims to independently regulate active and reactive power, which is crucial for grid stability. To assess both controllers' performance in the entire turbine– generator system, MATLAB/Simulink is used for design and testing.

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mourad naidji , Mohamed Ilyas Rahal, Adel Makhbouche, Zine Eddine Meguetta, Gerardo Ayala-Jaimes, ,(2025-12-13), Integrated MPPT and Power Control Strategy for DFIG-Based Wind Energy Systems Using PI and Sliding Mode Controllers,The 1st National Conference on Electronics, Electrical Engineering and Telecommunications, Challenges and Applications (NCEET'25),El Bayadh, Algeria

This paper provides a comprehensive analysis of the impact of wind farm integration on the stability of an electrical power system, with a particular focus on the dynamic effects induced by wind power during severe system disturbances. The primary objective is to evaluate how wind power integration influences system behavior, particularly under fault conditions. The research utilized the IEEE 9-bus test system, which consists of three generators and nine buses, as a reference benchmark for the stability analysis. Simulations and modeling were performed using PSAT (Power System Analysis Toolbox), a robust tool for static, dynamic, and control analysis of power systems, integrated with Matlab. The study specifically investigated the effects of a three-phase short circuit, representing a significant system disturbance. The dynamic analysis was structured into three phases: pre-fault, fault, and post-fault, to capture the complete impact on system behavior. The results provided valuable insights into critical electrical and electromechanical variables, shedding light on the role of wind farms in maintaining the stability of the power grid, with particular emphasis on the transmission network's resilience and response to disturbances. This work offers a deeper understanding of the integration of renewable energy sources in enhancing grid stability during extreme events.

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mourad naidji , Salim Djeriou , Mohamed Ilyas Rahal, Alla Eddine Toubal Maamar, Aicha Aissa-Bokhtache, Mohamed Boudour, ,(2025-12-10), Dynamic Analysis of Transmission Power Systems with High Wind Power Integration under Severe Disturbances,IEEE 2nd International Conference of Advanced Technology in Electronic and Electrical Engineering (ICATEEE),M'Sila, Algeria

Comprehensive Design and Analysis of Overcurrent Relay Protection and Coordination for a 220 MW Grid-Connected Power Plant

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mourad naidji , Salim Djeriou , ABDERRAHIM Zemmit , ISMAIL Ghadbane , RIYADH Rouabhi , assia.bounif@univ-msila.dz, ,(2025-12-10), Comprehensive Design and Analysis of Overcurrent Relay Protection and Coordination for a 220 MW Grid-Connected Power Plant,IEEE 2nd International Conference of Advanced Technology in Electronic and Electrical Engineering (ICATEEE),M'Sila, Algeria

This article proposes an advanced control strategy to improve the performance of ultraviolet-C ( UVC ) water sterilization systems . The main contribution of this study is the application of model predictive control ( MPC ) to the electronic ballast power supply system using a 50 kHz single-phase full-bridge inverter. The objective is to regulate the arc current through the discharge lamp to generate UV-C at 253.7 nm, improving radiation intensity and preserving lamp life, with particular emphasis on achieving high-quality sinusoidal waveforms and minimizing total harmonic distortion ( THD ). This method addresses key challenges such as current variations, which negatively impact lamp longevity, UV radiation consistency, and overall system reliability. By ensuring precise current regulation, the proposed method improves water disinfection efficiency, prevents the survival of harmful microorganisms, and reduces energy losses and overheating. MATLAB tools were used to evaluate the performance of the MPC -based system and compare it with the conventional proportional-integral ( PI ) control method, thus verifying the effectiveness of the proposed control strategy. The results indicate that the predictive control technique maintains the sinusoidal current with a THD of 2.21%, 65% less than conventional PI control (6.00% THD ). Furthermore, MPC rejects load disturbances in 0.001 s, 50% faster than PI control (0.002 s), and tracks the reference signal with a steady-state error of less than 0.5%. These aspects highlight how well model predictive control achieves stable and efficient operation of the discharge lamp.

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mourad naidji , Aicha AISSA-BOKHTACHE, Maamar Latroch, Alla Eddine Toubal Maamar, Amina Merini, Lemya DJAFER, , (2025-11-30), Design of Predictive Controller Applied to a Discharge Lamp-electronic Ballast System, Revista Politécnica, Vol:56, Issue:1, pages:29–36, The Polytechnic Journal of the National Polytechnic School

The electrical subsystem of a wind energy conversion system is the main subject of this research. A thorough mathematical model of the Doubly-Fed Induction Generator (DFIG) is created in the first section, accounting for its dynamic behaviour in different wind situations. In order to achieve independent regulation of active and reactive power—a crucial component of grid stability and effective energy transfer—a control strategy is suggested based on this model. A Sliding Mode Controller (SMC) and a ProportionalIntegral (PI) controller are the two controller kinds that are designed and put into use. The effectiveness of both control schemes is assessed through MATLAB/Simulink simulation. The outcomes show how well each technique works to guarantee dynamic stability and precise power control. Keywords—Control strategy, Proportional-Integral (PI), Sliding Mode Controller (SMC), Doubly-Fed Induction Generator (DFIG), Wind energy conversion.

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mourad naidji , Mohamed Ilyas Rahal, Adel Makhbouche, Zine Eddine Meguetta, Gerardo Ayala-Jaimes, ,(2025-11-25), Comparative Study of Power Control Strategies for DFIG Wind Turbines: PI vs Sliding Mode,IEEE International Conference on Mechanical and Electrical Engineering for Green Energy Technologies – MEEGET25,Algiers, Algeria

This study focuses on the analysis and experimental investigation of Selective Harmonic Elimination (SHE) for emerging single-phase multilevel inverter using Genetic Algorithm (GA), among the best algorithms for optimization. The employed inverter, a widely adopted emerging topology, uses fewer switches than conventional designs while delivering a five-level output voltage. GA solves transcendental nonlinear equations to find SHE’s optimal commutation angles. Simulation outcomes closely align with theoretical predictions, demonstrating the method’s simplicity compared to analytical techniques, suitability for inverter control, and cost-effectiveness for real-time implementation on a low-cost Arduino ATmega2560 Microcontroller. Theoretical analysis is validated through MATLAB/Simulink simulations and a hardware prototype built with efficient electronic components. Both simulation and experimental findings validate the resilience and efficacy of the presented modulation technique for emerging single-phase five-level inverters.

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mourad naidji , Alla Eddine TOUBAL MAAMAR, Touhami ABDELOUAHED, Aimad BOUDOUDA, Radu PORUMB, Saad MEKHILEF, ,(2025-11-18), Optimization of Selective Harmonic Elimination for Emerging Single-Phase Five-Level Inverter Using Genetic Algorithm,IEEE 6th International Conference on Power Electronics and their Applications (ICPEA),Ghardaïa, Algeria

This paper proposes a resilient sliding mode control (SMC) strategy for the stabilization of a cart-pendulum system, tackling significant issues in nonlinear control, including parametric uncertainties and external disturbances. The suggested solution uses a two-step process: first, an open-loop energy-based swing-up to lift the pendulum, and then a closedloop SMC phase to keep it stable. The designed controller uses a saturation function to reduce chattering, which is different from methods that depend on linearized models or complicated gain tuning. The simulation results show that the accuracy is very high, with settling times of about 5 seconds for the pendulum angle and 7 seconds for the cart position. The controller works well even when the system mass and disturbances change by 10%, as long as the cart can only move ±0.5 m and the control forces can only be ±10 N. Stability is reached from the most unfavorable initial condition, the pendulum's downward-hanging position, with a steady-state error of under 1% in essential state variables. This work offers a computationally efficient and adaptive solution, appropriate for real-time applications in robotics and aerospace where resilience to nonlinear dynamics and uncertainty is essential.

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mourad naidji , Lalia Miloudi, Alla Eddine Toubal Maamar, Oumaymah Elamri, Tassadit Benabdallah, Abdelkader Garmat, ,(2025-11-18), Design of Sliding Mode Control Applied to Inverted Cart-Pendulum for Good Stability Performances,IEEE 2025 5th International Conference on Applied Automation and Industrial Diagnostics (ICAAID),Ghardaïa, Algeria

This study suggests an enhancement of the Jiles–Atherton model for simulating magnetic hysteresis in ferromagnetic materials by integrating the frequency effect into the model parameters. Utilizing experimental data from a MnZn ferrite toroidal core exposed to rapid magnetic fields, the model parameters are refined through the Particle Swarm Optimization (PSO) technique and adjusted for frequency dynamics. This method makes it possible to model hysteretic behavior in a realistic way, especially at high frequencies, where phase shift and hysteresis loop broadening effects are most important. The results have been experimentally validated and show a good match with the extended Jiles– Atherton model. This opens up new possibilities for use in high-frequency electrical engineering devices.

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mourad naidji , Mourad Dafri, Abdelaziz Ladjimi, Wafa Tourab, Abdelhamid Ksentini, ,(2025-11-16), Extended Jiles–Atherton Model for Frequency Analysis of Magnetic Hysteresis,The first International Conference on Electrical Engineering and its Applications,Guelma, Algeria

The optimal location of the wind turbines (WTs) is a critical component in the design of the WT, which can guarantee maximum output power. For that, several recent methodologies have been carried out for optimizing wind turbines in a wind farm using different optimization algorithms. This paper proposes a novel approach for the optimization of wind farm layout using Quantumbehaved particle swarm optimization (QPSO) algorithm. Three case studies are considered to express the presence of wake impact. The effectiveness of the proposed approach is validated through simulations conducted in MATLAB. The performance findings are compared against results from previously published works, revealing that the proposed optimization technique consistently achieves higher total power output and improves the total efficiency of the WT.

Citation

mourad naidji , ALLA EDDINE TOUBAL MAAMAR, MOHAMED ILYAS RAHAL, RACHID TALEB, ,(2025-10-28), A Novel Nature-Inspired Approach for Wind Farm Location Optimization Considering Wake Effects,Springer 9th International Conference on Artificial Intelligence in Renewable Energetic Systems,Mostaganem, Algeria

The Internet of Things (IoT) plays a central role in the conversion to Industry 4.0 by enabling intelligent connectivity, real-time remote monitoring, and advanced automation of industrial processes. In this context, the main purpose of automatic bottle filling and cap systems is to improve production efficiency by minimizing or eliminating human intervention. One of the most important performance goals is to reduce filling accuracy, reduce operational errors, increase overall and reduce labor costs. This paper presents a concrete example of IoT integration in industrial automation through the design and implementation of intelligent bottle filling and capping systems based on an Arduino microcontroller. The system enables real-time and remote control monitoring via an IoT platform, and uses components such as infrared sensors, relay modules, DC engines, and specialized mechanical structures to recognize and manage filling and cap processes. By using IoT technology, the system is consistent with Industry 4.0 principles. This improves operational visibility, reduces human dependency, and reduces process optimization. This approach is particularly relevant to sectors such as food, drinks and medicines where accuracy, hygiene and efficiency are of great importance.

Citation

mourad naidji , Mohamed Ilyas Rahal, Adel Makhbouche, Zine Eddine Meguetta, ,(2025-10-28), Towards Smart Automation: An IoT-Integrated Control Strategy for Industry 4.0,Springer 9th International Conference on Artificial Intelligence in Renewable Energetic Systems,Mostaganem, Algeria

The application of renewable energy generated using solar panels has gained a lot of interest because of the growing demand for electricity, global warming, and air pollution. A solar panel is made up of a chain of photovoltaic cells, where a solar cell is used to convert the light into electrical energy due to the photovoltaic effect. The voltage of the solar cell can range from 0.3V to 0.6V based on the semiconductor material used and also its temperature. The voltage, current and therefore the power of a solar cell is not suitable for common uses, thus it is necessary to have the cell connected in sets in order to form a solar panel. The experimental installation of the different algorithms and techniques for power flow control and energy optimization from the solar panel to the load can destroy this equipment's, so mathematical modeling and simulation would be an extremely critical step to examine the algorithms behavior before its installation. The aim of this research study is to offer a tutorial guide on the modeling and simulation of the solar panel using MATLAB/Simscape. In this paper, we have given all the required data to model and simulate a photovoltaic panel step by step with all algorithms and simulation tips shared. The two main contributions of this paper are the model created and MATLAB algorithm developed for simulating the solar panel, which can be easily be changed by any user for any other research purpose.

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mourad naidji , Alla Eddine TOUBAL MAAMAR, Aicha AISSA-BOKHTACHE, Rachid TALEB, ,(2025-10-28), A simple and accurate script to simulate a solar panel models at variable environmental conditions of temperature and irradiation,Springer 9th International Conference on Artificial Intelligence in Renewable Energetic Systems,Mostaganem, Algeria

Solar panel systems play an important role in the supply of energy to the world, yet their reliability and efficiency are often impaired by various faults, including mismatch faults, partial shading, and environmental degradation. Early detection and classification of faults is crucial to prevent performance loss, early system degradation, and fire risk. This paper discusses the use of the artificial neural network (ANN) algorithm for fault detection and classification on solar panel system using a multilayer perceptron (MLP) type. The MLP was chosen because of its high computational power, generalization, and capacity to model complex, non-linear patterns in data. An MLP neural network is built and trained with current-voltage (I-V) and power-voltage (P-V) measurements to precisely detect and distinguish common PV faults. The system under consideration is adequate for classification, and the outcome shows a general fault detection accuracy of 95% at training for more than 30,000 iterations. The research strongly supports the feasibility of diagnosing typical PV faults like series resistance mismatch, cell degradation, shunt faults, and partial shading by applying ANN. The results demonstrate the stability of ANN-based fault diagnosis to enhance the reliability and maintenance of solar PV systems and serve as a solid point of reference for further studies on intelligent PV monitoring and fault detection.

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mourad naidji , Alla Eddine TOUBAL MAAMAR, Aicha Aissa-Bokhtache, Touhami ABDELOUAHED, ,(2025-10-12), An Efficient MLP Neural Network Algorithm for Diagnosis of Solar Panel Faults,The 1st National Conference on Mechatronic Engineering (NCME’2025),Boumerdes

The world has never been more in need of a shift to renewable power. Electricity demand will increase 50% by 2050 (IEA, 2023) and solar power represented more than 60 % of new installations of renewable capacity in 2023 (IRENA), with photovoltaic (PV) technology leading the way in green energy solutions. Solar panel, which are made up of series-connected photovoltaic cells, produce electricity by converting sunlight via the photovoltaic effect with voltages of 0.3V to 0.6V per cell, depending on semiconductor materials and ambient conditions. However, solar energy system is replete with basic challenges. Experimental confirmation of power flow control and energy management methods in practice can risk costly equipment—rendering mathematical modeling and simulation as a pivotal departure point to secure efficiency and reliability. Even with the explosive expansion of solar power, numerous students, and researchers continue to experience difficulty gaining information for precise PV system simulation. The present research paper fills this void by offering a comprehensive tutorial on solar panel experimental test and modeling with MATLAB/Simscape. We explain all the steps from basic principles to complex algorithms and unveil essential simulation methodologies for maximum power extraction. The significant contributions of this work are: A flexible MATLAB-based PV model easily implementable for varied research goals; Implementation and simple modeling of 85W solar panel, which any user can modify for other research purposes, such as optimization and power flow control techniques. Such knowledge can help the world meet its decarbonization goals and build a cleaner, more efficient energy future.

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mourad naidji , Alla Eddine TOUBAL MAAMAR, Aicha AISSA-BOKHTACHE, Maamar LATROCH, Touhami ABDELOUAHED, Aimad BOUDOUDA, ,(2025-06-11), Experimental Evaluation and Modeling of 85 W Solar Panel for Maximum Power Extraction,Materials Sciences And Engineering (MSE’25),Chlef, Algeria

Solving the optimal power flow (OPF) problem is a fundamental yet intricate challenge in power system optimization. From an optimization perspective, OPF aims to minimize specific objective functions while ensuring optimal operational settings for the power network. This involves considering key system parameters, including generator outputs. The power grid may consist of both conventional fossil-fuel-based generators and renewable energy sources (RES) such as wind and solar power. Due to the highly nonlinear nature of OPF, its complexity further escalates with the integration of intermittent RES. In this paper, a Quantum-behaved Particle Swarm Optimization with Differential Mutation (QPSODM) algorithm is introduced to address OPF under uncertainty. This approach incorporates the stochastic nature of wind and solar energy alongside conventional thermal power generation. The primary objective is to minimize total generation costs while accounting for carbon emission tax imposed on fossil fuel-based generators. The proposed method has been tested on a modified IEEE 30-bus system, and simulation results demonstrate its effectiveness in solving the OPF problem while yielding logical and optimal results.

Citation

mourad naidji , Mohamed Ilyas Rahal, Alla Eddine Toubal Maamar, ,(2025-05-06), Optimizing Power Flow with Renewable Energy Sources: A Cost-Effective Approach,The First National Conference on Renewable Energies and Advanced Electrical Engineering (NC REAEE'25),M'Sila, Algeria

The fundamental objective of an automatic bottle filling system is to optimize production by minimizing or eliminating the need for human intervention. The key focus areas include ensuring filling accuracy, reducing errors, increasing productivity, and potentially lowering labor costs. By integrating technologies such as IoT and microcontrollers like Arduino, these systems enable remote monitoring and simplified management, contributing to the overall optimization of the filling process. A concrete example of this approach is illustrated in this paper, which focuses on an IoT- and Arduino-based system dedicated to automatic bottle filling and capping. The aim is to simplify business access to such processes, particularly in the manufacturing of carbonated beverages and pharmaceuticals. This paper implements various components, including the Arduino microcontroller, infrared transmitters and receivers, relay drivers, DC motors, and specialized mechanical devices, utilizing infrared detection to guide the process. Remote monitoring via IoT ensures efficient management, reduces labor dependency, and optimizes the entire process. Keywords—Automatic bottle filling, IoT, Arduino, remote monitoring, industrial automation, infrared detection, relay drivers, DC motors, capping system, manufacturing optimization.

Citation

mourad naidji , Mohamed Ilyas Rahal, Oualid Bendjama, Ahmed Boukhemla, Adel Makhbouche, Zine Eddine Meguetta, ,(2025-05-06), IoT-Driven Automatic Bottle Filling and Capping System Using Arduino,The First National Conference on Renewable Energies and Advanced Electrical Engineering (NC REAEE'25),M'Sila, Algeria

In light of the pressing concerns regarding global warming and the diminishing availability of fossil fuels, there has been a notable surge in the adoption of distributed generation (DG) systems, which harness clean and renewable energy sources. These systems are strategically placed in close proximity to end-users, thereby reducing power losses. However, without effective control mechanisms, issues such as voltage instability and increased power losses can impede the efficient functioning of the power grid. In this paper, an innovative approach termed Optimal Coordinated Voltage Control (OCVC) designed for distribution networks integrating dispersed renewable energy sources. Employing a genetic algorithm (GA) methodology and implementing multi-core simulation using the open-source platform OpenDSS, this method aims to optimize the settings of voltage control devices remotely. Moreover, it accounts for dynamic variations in both load and generation patterns through day-ahead scheduling. To evaluate the efficacy of the proposed technique, simulations are conducted on a test distribution network featuring the integration of DG systems.

Citation

mourad naidji , Mourad Dafri, Abdelbaset Laib, , (2025-02-28), Optimal Coordinated Voltage Control of Distribution Networks Considering Renewable Energy Sources, ECTI Transactions on Electrical Engineering, Electronics, and Communications, Vol:23, Issue:1, pages:1–11, ECTI Association Sirindhon International Institute of Technology

Performing an optimal power flow (OPF) represents an indispensable and complex optimization problem in power systems. From an optimization point of view, the OPF problem implicates the minimization of some objectives. OPF problem is expressed with all pertinent parameters of the power system including generator outputs to get the optimal settings. The power system can include of conventional fossil generators as well as renewable energy sources (RES) such as solar and wind. Classical OPF is considered as a highly non-linear complex problem. The integration of an intermittent source of RES increases the complexity of the problem. In this paper, Quantumbehaved particle swarm optimization differential mutation (QPSODM) algorithm is proposed to solve the OPF problem by combining stochastic wind and solar power with conventional thermal power generators in the system. The objective to be minimized is total generation cost taking into account the tax imposed on the carbon emission by conventional thermal generators. The proposed approach has been examined and confirmed on the modified IEEE 30-bus. Simulation results show that the proposed approach can solve the OPF effectively and can give best and logic results.

Citation

mourad naidji , Mourad Dafri, Abdelbaset Laib, ,(2023-10-25), Optimal Power Flow Solution using QPSODM Algorithm,The first international Conference on Advances in Electronics, Control and Computer Technologies ICAECCT’23,Mascara, Algeria

The optimal layout of the wind turbines is an important factor in the design of the wind farm, which can guarantee maximum output power. For that, several recent methodologies have been carried out for optimizing wind turbines in a wind farm using different optimization algorithms. This paper proposes a novel approach for the optimization of wind farm layout using Quantumbehaved particle swarm optimization differential mutation (QPSODM) algorithm. Three case studies are considered to express the presence/absence of wake impact. The MATLAB simulation results verify the proposed methodology. Moreover, the results are compared with those of existing research works, and it shows that the proposed optimization strategy can give best and logic results in terms of total power output and high efficiency of the wind farm.

Citation

mourad naidji , Mourad Dafri, ,(2023-10-25), A novel approach for wind farm layout optimization using QPSODM algorithm,The first international Conference on Advances in Electronics, Control and Computer Technologies ICAECCT’23,Mascara, Algeria

This work is to model the hysteretic behavior of magnetic materials and to integrate Preisach model associated with the Student distribution function using the finite element method in 2D into the Matlab software. Simulations performed using the computational code allowed us to investigate the effect of the hysteresis phenomenon on the magnetic quantity and the change in losses as a function of temperature.

Citation

mourad naidji , Mourad Dafri, Abdelaziz Ladjimi, ,(2023-10-25), Integration and modeling thermal effect in Preisach model associated with the student distribution function using the finite element method,The first international Conference on Advances in Electronics, Control and Computer Technologies ICAECCT’23,Mascara, Algeria