Browsing by Author "Kheldoun, Aissa (Supervisor)"

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Analysis and design of an analytical MPPT applied for different converter configurations
(2022) Djouider, Abderrazak Ziane; Tahir, Mustapha; Kheldoun, Aissa (Supervisor)
This project is intended to analyze the maximum power point tracking constraint conditions of the 12 PV systems under ideal conditions; The constraint conditions are necessary and sufficient conditions to guarantee the existence of the maximum power points of these PV systems. These constraint conditions are expressed by the modal parameters of the PV, therefore they show the inherent relationship between the load and the cell parameters when the maximum power point of the system always exist. In addition to apply them in practice, the maximum power point tracking constraint condition of the practical application are nvestigated. Furthermore, our work includes the variable weather parameter maximum power point tracking method based on equation solution (ES-VWP method). This equation consists of two analytic equations which represent two different operating points of the PV system. The simulation of this technique has shown a good effectiveness in terms of maximum power point and time response.
Analysis of frequency response of the Algerian power system
(Université M’Hamed BOUGARA de Boumerdes : Institut de génie electrique et electronique (IGEE), 2023) Hamam, Lyes; Ykhlef, Abdessemed Abdelwaheb; Kheldoun, Aissa (Supervisor)
The frequency response of a power system is a key parameter that reflects its stability and ability to maintain a consistent supply of power. This project presents an analysis of the frequency response characteristics of the Algerian power system, with a focus on frequency control techniques, reserve capacity, flywheel battery and battery energy storage system (BESS) integration. Furthermore, this analysis explores the role of reserve capacity in frequency regulation. Reserve capacity is spare generation capacity that stands by to deal with sudden frequency excursions or imbalances between supply and demand. The assessment focuses on the adequacy of reserve capacity in the Algerian grid and its impact on frequency stability. Finally, the project considers the integration of Battery Energy Storage Systems (BESS) and flywheel battery as a potential solution to improve frequency response capability.
Application of golden section search MPPT control to grid-connected wind turbine driven PMSG
(2018) Khelifa, Ayoub; Ben Haoua, Seif Eddine; Kheldoun, Aissa (Supervisor)
This project is intended to design a PMSG based wind energy conversion system. Classical controllers, such as P&O MPPT algorithms are employed to ensure maximum power extraction from wind turbine. Speed of the generator is adjusted to match the wind turbine power- speed characteristics. In this project, a new MPPT algorithm is investigated to maximize the power coefficient Cp. The algorithm is based on Golden Section search principle and expected to be faster than the aforementioned algorithms.
Control of stand-alone PV system with global maximum power point identification
(Université M’Hamed Bougara de Boumerdes : Institut de génie electrique et electronique (IGEE), 2024) Damou, Rezkallah; Saheb, Anis; Kheldoun, Aissa (Supervisor)
As the world faces the depletion of fossil fuels and the adverse environmental impacts of their use, renewable energy sources have become crucial for sustainable development. Solar energy, one of the most abundant renewable resources, is harnessed using photovoltaic (PV) systems that convert sunlight into electrical energy. Despite their potential, PV systems are plagued by low efficiency and dependency on various factors such as solar irradiance, temperature, electrical load, and ambient conditions. One of the major challenges in PV systems is partial shading, which occurs when only a portion of the PV array is obstructed from sunlight. This shading can drastically reduce the overall power output and create multiple local maximum power points (LMPs) on the power curve, complicating the optimization process. In PV systems with partial shading, multiple LMPs and one global maximum power point (GMPP) exist. Hence, the identification of global maximum power point GMPP is needed, which is the main topic of this thesis. The project's method is applied and simulated using MATLAB and Simulink on a stand-alone photovoltaic system powered by an MPPT controller. The suggested method (Enhanced Adaptive P&O) produced outstanding results in differentiating between uniform irradiance and partial shading occurrences under a variety of insolation levels and complex shading scenarios. A comparative study based on convergence time, and efficiency is conducted along with other well-known techniques: Particle Swarm Optimization (PSO) and Grey Wolf Optimization (GWO). The obtained results demonstrated that the EA-P&O is either excellent or competitive with respect to tracking efficiency, convergence speed and eliminate the oscillation problem.
Deep learrning based PV power forecasters in python for different time horizons
(2021) Chakhchoukh, Taha Yassine; Tebbal, Said; Kheldoun, Aissa (Supervisor)
The major points worked on throughout this report are: achieving accurate fore- caster with less complexity and computational cost, using the minimum available data set for training and reaching the farthest possible span in the future. For the aim of developing forecasters in this work, then RNNs and DL were employed with the use of the python programming language for their modelling. A data set of GHI recordings collected during January 21, 2011, through March 4, 2012 and from December 20, 2012, through January 20, 2014 is used to compare the above DNN based models for three different time spans. Moreover, various evaluation metrics such as MAPE, RMSE, r and R2 have been used for the assessment of the models to explore their performance when spanning different time horizons such that each one has a specific training samples. The obtained results have showed that the AE LSTM is the most efficient and less sensitive to the number of training samples.
Design and implementation of T-type three level inverter based grid-connected PV system
(2018) Merazka, Abdeslam; Lazoueche, Yossouf; Kheldoun, Aissa (Supervisor)
Due to its intermittence, strong dependability on the climate conditions, penetration of PV plants to grid utilities is a big challenge for the power system operators. This project is intended to design and implement a three-phase grid-connected PV system. Two controllers will be developed namely the Golden Section Search (GSS) –based MPPT and the SVM for the three level T-type inverter being used as interface with the Gird. The MPPT algorithm ensures maximum power extraction from the PV generator and the SVM ensures the requirements of grid connection standard in terms of power
Design and implementation of two level shunt active power filter
(2019) Dekari, Cherif; Dahmani, Seifeddine; Kheldoun, Aissa (Supervisor)
Power quality has become of utmost importance for the power systems owners, where, the power electronics systems are found nowadays in all systems, such as industrial applications, appliances and telecommunications. These systems, which use power switching devices, are source of harmonics and consequently deteriorate the quality of voltage and current in the grid utilities. For this reason, the passive filters can be used to eliminate some of these harmonics; however, they are not enough to improve the quality being required by standards. Therefore, shunt active power filter is proposed for study in this project. A two-level inverter configuration is proposed and control system will be designed and implemented to satisfy the required quality. MATLAB/Simulink with STM32f4 microcontroller will be employed to carry out the simulation and the experimental implementation of this project. The results will be analyzed and discussed.
Design of hybrid system based on solar and wind energies
(2021) Liamini Zaidi, Takieddine; Bouchedjira, Abderrahim; Kheldoun, Aissa (Supervisor)
Renewable energy is useful energy that is collected from renewable resources, which are naturally replenished on a human timescale, including carbon neutral sources like sunlight, wind, rain, tides, waves, and geothermal heat. This type of energy source stands in contrast to fossil fuels, which are being used far more quickly than they are being replenished. Although most renewable energy is sustainable energy, some is not, for instance biomass energy is unsustainable. Reasons to replace conventional energy with renewable energy are due to the disadvantages of the first one with respect to the seond one. Pollution, cost and sustainability are amongst other advantages which favor the renewable energy source. The presented system includes solar energy source and wind turbine generator being adopted to feed power to the load. As these sources are intermittent, the diesel energy,as a buck-up,is mostly adopted for remote loads such as villages or irrigation system. For better efficiency of the microgrid, a grid connection common coupling point is provided to absorb the excessof energy. Simulation results of the microgrid with energy management system allow continuously satisfying the load and absorbing the available renewable energy effectively.
Design of power management algorithm for hybrid power system
(2019) Kerbouche, Ammar; Chaib, Fakhr El Islam; Kheldoun, Aissa (Supervisor)
Solar and wind energy can be used to deliver electricity for grid utility as well as remote micro-grid. These sources are used more and more to mitigate the consequences of greenhouse gases being produced by convention power plants. However, due to their intermittence, solar as well as wind energy source alone cannot meet the requirement of micro-grids or remote loads in terms power. To this, hybrid system is preferred to ensure supplying the power demand. In general, a diesel and a battery are associated to store and supply power when there is excess and lack of power respectively. For the best operation, an energy management system must be used to connect the appropriate renewable source as the power demand varies. In this project, an energy management is proposed and simulated for a given hybrid system.
Desing and implementation of electric vehicles bidirectional charger
(2023) Ghodbane, Anouar Cherif; Malki, Youcef Islem; Kheldoun, Aissa (Supervisor); Khettab, Soufian
This project aims to enhance the design and implementation of a bidirectional electric vehicle (EV) charger, a vital component in modern energy systems. The bidirectional charger not only facilitates charging and discharging of energy to and from the grid or energy storage systems but also enables efficient energy management and utilization. Additionally, it can serve as a shunt active power filter ,effectively mitigating harmonics generated during power conversion, thereby reducing total harmonic distortion (THD) and ensuring grid reliability. To regulate the operation of this power electronic device, two control techniques were investigated: hysteresis current control (HCC) and model predictive control. Through comprehensive simulation studies, the results obtained from both techniques were presented and compared. Furthermore, real-time evaluations were conducted to validate the efficacy of the employed control techniques. By improving the bidirectional EV charger’s design and employing advanced control strategies, this project contributes to the development of more efficient and reliable energy systems while addressing power quality concerns through harmonic reduction.
Detection and diagnosis of PV system faults
(2018) Boudjadar, Mohamed Mounib; Kheldoun, Aissa (Supervisor)
solar energy is green and renewable. In spite of the instability of electricity generation and the low efficiency, the PV systems have relatively long life span. Similar to any other system, the PVS endure losses and are exposed to failures with different significance. Hence a diagnosis system is required to monitor and detect the faults’ existence. This project concern is developing a fault diagnosis system with the purpose of identifying the occurrence of the most common faults in a PV system based on the current and voltage assessment under different conditions.
Detection and diagnosis of PV system faults
(2018) boudjadar, Mohamed Mounib; Kheldoun, Aissa (Supervisor)
The photovoltaic systems are gaining more importance as reliable energy producing systems, due to the fact of that the solar energy is green and renewable. In spite of the instability of electricity generation and the low efficiency, the PV systems have relatively long life span. Similar to any other system, the PVS endure losses and are exposed to failures with different significance. Hence a diagnosis system is required to monitor and detect the faults’ existence. This project concern is developing a fault diagnosis system with the purpose of identifying the occurrence of the most common faults in a PV system based on the current and voltage assessment under different conditions.
Droop-controlled single phase AC micrigrid using SOGI-PLL
(2022) Diaf, Hadil; Kheldoun, Aissa (Supervisor)
A microgrid (MG) is deﬁned as a low or medium voltage distribution network that is also connected to a number of distributed generation sources, energy storage elements, and con- trollable loads. A MG can operate both in grid-tied mode, when its bus is connected to the main grid, or in islanded more, when it’s disconnected. MG control strategy is considerably diﬀerent than that of the traditional grid. A hierarchi- cal control architecture consisting of primary, secondary, and tertiary control is adopted to regulate voltage and frequency and ensure a stable and reliable network. In order to oﬀer a good power quality for end users in islanded microgrids, the power sharing between distributed generators (DGs) is the ﬁrst challenge that must be dealt with. In this report, a droop control method based primary control for two parallel single-phase VSIs forming an islanded microgrid is presented. The controller aims to ensure optimal power sharing between diﬀerent DGs using mod- iﬁed droop-control technique and introducing SOGI-PLL for parameter estimation and DC- oﬀset rejection, during islanded operation.
Energy management system for hybrid renewable energy system
(2020) Attou, Abd Elhak; Rebhi, Madani; Kheldoun, Aissa (Supervisor)
Conventional power system is mainly based on fossil fuel power plant. The latter is huge source of pollution while its primary energy, fossil fuel, is being rapidly depleted. However, some remote loads and villages cannot benefit from this electric energy for the raison that there is no network. Renewable off-grid electricity supply is one alternative that has gained attention especially for those types of load or villages. The aim of this project is to present an optimal hybrid energy system to meet the electrical demand in a reliable and sustainable manner for an off-grid remote village.The proposed system is composed of Photovoltaic source, diesel generator and battery storage. In fact, solar energy source alone cannot meet the requirement of micro-grids or remote loads in terms energy. Therefore, diesel and a battery are associated to store and supply power when there is excess and lack of power respectively.Anenergy management system to control the hybrid system is proposed. It is built based on three goals which are: (i) energy demand satisfaction; (ii) system cost reduction; and (iii) reduction of gas emission.Obtained results have showed that the proposed energy management system accurately uses solar energy source to minimize operation of Diesel and battery.
Evaluation of global MPPT algorithm for stand-alone PV system
(2018) Maallem, yahia; Ghedjati, Karim Eddine; Kheldoun, Aissa (Supervisor)
Solar energy, at the present time is considered as an important source in electricity generation. Electricity from the solar energy can be generated using solar photovoltaic (PV) modules. The maximization of solar power extracted from a PV module is of special concern as its efficiency is very low. The output power of a PV module is highly dependent on the geographical location and weather conditions such as solar irradiation, shading and temperature. Due to the complexity of the tracker mechanism and non-linear nature of photovoltaic system, to obtain maximum power from PV module, it usually requires maximum power point tracking (MPPT) controller. In this project, exchange market algorithm based
Evaluation of global MPPT for stand-alone PV system
(2018) Soufi, Ali; Mohammadi, Abdelhaq; Kheldoun, Aissa (Supervisor)
Under partial shading conditions (e.g., due to buildings, trees, and clouds), multiple peaks may exist on the power-voltage (P-V) characteristic curve of photovoltaic (PV) array, leading to the conventional maximum power point tracking methods fail to extract the global maximum power point (GMPP). To further complicate matters, most conventional Maximum Power Point Tracking methods develop errors under certain circumstances (for example, they detect the local Maximum Power Point (LMPP) instead of the global MPP) and reduce the efficiency of PV systems even further. Presently, much research has been undertaken to improve upon them. This work describes a new fast and efficient technique based on Particle Swarm Optimization (PSO), compared with the conventional technique Perturb and Observe (P&O) which is inadequate to track the GMPP subject to these conditions resulting in a dramatic reduction in the efficiency of the PV system. Simulations are performed in MATLAB/SIMULINK software. A system includes a DC-DC buck-boost converter to step up or down the voltage to required magnitude. P&O and PSO maximum power point tracking (MPPT) algorithms have been used to extract the possible maximum power point from the PV system. A DSP microcontroller is also used to control the duty cycle of the IGBT accompanied with this system. The results verify the accuracy of the proposed scheme. Also the results show that the proposed method has better characteristic and performance in compare with P&O methods.
Evaluation of global MPPT for stand-alone PV system
(2018) Soufi, Ali; Mohammadi, Abdelhaq; Kheldoun, Aissa (Supervisor)
Under partial shading conditions (e.g., due to buildings, trees, and clouds), multiple peaks may exist on the power-voltage (P-V) characteristic curve of photovoltaic (PV) array, leading to the conventional maximum power point tracking methods fail to extract the global maximum power point (GMPP). To further complicate matters, most conventional Maximum Power Point Tracking methods develop errors under certain circumstances (for example, they detect the local Maximum Power Point (LMPP) instead of the global MPP) and reduce the efficiency of PV systems even further. Presently, much research has been undertaken to improve upon them. This work describes a new fast and efficient
Evolutionary algorithms-based optimal preventive maintenance scheduling of power systems generators
(Université M’Hamed BOUGARA de Boumerdes : Institut de génie electrique et electronique (IGEE), 2023) Elhazati, Bouchra; Kheldoun, Aissa (Supervisor); Belagoune, S.
This thesis addresses the optimal Generators preventive-Maintenance Scheduling (GMS) problem in electric power systems that includes several machines. This problem can be solved using a variety of ways, such as metaheuristic methods and mathematical programming. The problem is formulated as a mathematical optimization model using mathematical programming techniques, and the best solution is then found using algorithms. Simulating the maintenance schedule allows you to assess its effectiveness while modeling the equipment and its failure behavior. Metaheuristic methods entail creating maintenance schedules utilizing generalizations or subject-matter expertise. The primary objective of this thesis is to contribute to the performance improvement of a discrete evolutionary algorithm for a reliable and extremely accurate optimization of the discrete objective functions in order to address the issue of the best preventive maintenance scheduling of power systems generators. For planning the generator preventative maintenance, a modern metaheuristic algorithm named "the Discrete Mayfly Optimization (DMFO)" has been designed. This algorithm was proposed as an innovative swarm intelligence optimization algorithm in 2020, it combines the advantages of several existing optimization algorithms. his algorithm has been used in several applications including industrial optimization, ensemble forecasting system, and photovoltaic systems. A First-Bit Flip and Shift (FBFS) strategy for binary vectors, which is a process of manipulating binary vectors, has been first proposed to improve the performance of evolutionary algorithms. The FBFS strategy is a local search strategy that performs small changes to the obtained solutions to help evolutionary algorithms in local optimization and avoiding them from getting stuck in local optima. The proposed technique has been evaluated on a 21-unit test power system with a peak power load demand of 4739 MW in three cases where the total number of the workers available per week is limited. The improved algorithm showed at the end its effectiveness to find a solution for the GMS problem where the Sum of Squares of the Reserves (SSR) of generation is minimized. The results are compared to previous works that used other metaheuristic techniques in order to evaluate the performance of the proposed FBFS-DMFO algorithm and its search process in solving power system GMS problem.
Fuzzy logic – based hill climbing MPPT for wind driven permanent synchronous generator
(2020) Abdellali, Lotfi; Merabet, Oussama; Kheldoun, Aissa (Supervisor)
Wind power has become a rapidly growing technology as a kind of renewable energy resources. It plays a more and more important role with the increasing demand on energy every day. Unlike fossil fuel power sources, with the fact that it emits no air pollution or greenhouse gas, also its ability to generate high amount of power with no fuel consumption, therefore it is becoming much more reliable and promising to be number one source for clean energy in the very near future. Research of Wind Energy Conversion Systems (WECS) has gained great interest in the recent years to improve its behavior and response. One of the most important aspects is the Maximum Power Point Tracking (MPPT). The latter allows extracting the maximum power at the different wind speeds and therefore increasing the efficiency of the Variable-Speed Wind Turbine system when the wind speed is below the rated speed. Fuzzy sets are proposed in the present work to design the Maximum Power Point Controller. Simulation using Matlab /Simulink have shown that the investigated controller is fast and accurate.
Identification and control of asynchronous motor using meta-heuristic algorithms
(2023) Ghernaout, Rayane; Kheldoun, Aissa (Supervisor); Belmadani, Hamza
The present study is centered on the examination, regulation, and enhancement of induction motors (IMs) through the application of meta-heuristic algorithms. The aim of this study is to optimize the performance and efficiency of induction motors (IMs) in various applications. The study begins with the formulation of a mathe- matical model for induction motors (IMs). Subsequently, meta-heuristic algorithms, namely EO, RSBA, and JAYA, are employed to determine the parameters of the IM.The estimation of parameters is conducted by utilizing the inputs of measured stator voltages, currents, and rotor speed. This study focuses on the modeling of indirect rotor flux-oriented control(IRFOC )and the utilization of the resulting IM param- eters to identify the motor. Control gains are then optimized through the imple- mentation of RSBA and JAYA algorithms. The findings of the simulation indicate that the system’s performance has been enhanced in comparison to conventional manual tuning techniques. The project acknowledges the difficulties involved in the optimization process and emphasizes the significance of meticulous parameterse- lection. In summary, this study serves as a valuable contribution to the progression of IM technology, highlighting its potential to enhance performance and efficiency in industrial settings.