M. BOUDJELLAL Bilal

MCA

Directory of teachers

Department

DEPARTEMENT OF: ELECTRICAL ENGINEERING

Research Interests

Electrical drives control and diagnostic Power electronics Fault tolerant control Hardware implementation Renewable energy systems control Optimization and artificial intelligence

Contact Info

University of M'Sila, Algeria

Email : bilal.boudjellal@univ-msila.dz

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Recent Publications

2023-09-11

Study of an open-switch fault detection algorithm for a three-phase interleaved DC–DC boost converter in a photovoltaic system

This paper presents a novel fault detection algorithm for a three-phase interleaved DC–DC boost converter integrated in a photovoltaic system. Interleaved DC–DC converters have been used widely due to their advantages in terms of efficiency, ripple reductions, modularity and small filter components. The fault detection algorithm depends on the input current waveform as a fault indicator and does not require any additional sensors in the system. To guarantee service continuity, a fault tolerant topology is achieved by connecting a redundant switch to the interleaved converter. The proposed fault detection algorithm is validated under different scenarios by the obtained results.
Citation

M. BOUDJELLAL Bilal, (2023-09-11), "Study of an open-switch fault detection algorithm for a three-phase interleaved DC–DC boost converter in a photovoltaic system", [national] Archives of Electrical Engineering , Polish Academy of Sciences

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2022-11-26

Fault Detection Algorithm for Three-Level DC–DC Converter in a Photovoltaic System

This paper presents an open-switch fault detection algorithm for a three-level DC–DC boost converter in a photovoltaic system. Three-level DC–DC converter and its various derivatives are popular topologies in high-voltage, high-power converter applications. To ensure service continuity, a reliable fault diagnostic algorithm and a fault tolerant strategy are strongly mandatory. The fault diagnostic method does not necessitate any additional sensors and relies on the input current waveform and the necessary control variables for maximum power point tracking. The fault tolerant strategy is realized by including redundant switches to the converter to assurance continuity of service. The proposed fault detection algorithm is validated under different scenarios by the obtained results.
Citation

M. BOUDJELLAL Bilal, (2022-11-26), "Fault Detection Algorithm for Three-Level DC–DC Converter in a Photovoltaic System", [international] 2022 International Conference of Advanced Technology in Electronic and Electrical Engineering (ICATEEE) , M'sila University, Algeria.

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2020-10-10

Active and Reactive Powers Control of DFIG Based WECS Using PI Controller and Artificial Neural Network Based Controller

The purpose of this study is to improve the control performance of a Doubly Fed Induction Generator (DFIG) in a Wind Energy Conversion System (WECS) by using both of the conventional Proportional-Integral (PI) controllers and an Artificial Neural Network (ANN) based controllers. The rotor-side converter (RSC) voltages are controlled using a stator flux oriented control (FOC) to achieve an independent control of the active and reactive powers, exchanged between the stator of the DFIG and the power grid. Afterward, the PI controllers of the FOC are replaced with two ANN based controllers. A Maximum Power Point Tracking (MPPT) control strategy is necessary in order to extract the maximum power from the of wind energy system. A simulation model was carried out in MATLAB environment under different scenarios. The obtained results demonstrate the efficiency of the proposed ANN control strategy.
Citation

M. BOUDJELLAL Bilal, (2020-10-10), "Active and Reactive Powers Control of DFIG Based WECS Using PI Controller and Artificial Neural Network Based Controller", [national] Modelling, Measurement and Control A , IIETA | Advancing the World of Information and Engineering

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2017

Energy Management of a Grid-Connected Hybrid PV System under variable load demands

This paper presents the study of a hybrid PV System connected to the grid under variable load demand and different solar irradiances. The studied system consists of 100 kW photovoltaic (PV) array, battery energy storage system and super-capacitor (SC), in addition to, DC and AC loads. The PV array is controlled to generate the available maximum power using Perturb and Observation (P&O) control method. All these elements are connected to a DC bus. The DC bus is connected to the grid through a bidirectional 6-pulse PWM converter, it controls the active and reactive power transfer to the grid by the indirect field orientation control (FOC). Super-capacitor is used to filter the PV array output and to reduce the small charging and discharging cycle of the battery. An energy management strategy is proposed to extract the maximum power from the PV array, and to ensure voltage stability and smooth power transfer between the system and grid (figure .1). The simulation results of the studied system are presented and discussed to validate the proposed energy management strategy under variable load demands (figure 3).
Citation

M. BOUDJELLAL Bilal, (2017), "Energy Management of a Grid-Connected Hybrid PV System under variable load demands", [international] INTERNATIONAL CONFERENCE ON ELECTRONICS AND NEW TECHNOLOGIES (ICENT-2017) , M’sila, ALGERIA

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2016

Artificial Neural Network-based control of wind energy conversion system based on a doubly fed induction generator

This paper presents the study of a variable speed Wind Energy Conversion System (WECS) based on a fully Artificial Neural Network (ANN)-Controlled Doubly Fed Induction Generator (DFIG). This system is controlled, on one hand, to maximize its conversion efficiency, and on the other hand, to improve its power control performances. For this purpose, three different ANN-based controllers are used. The first ANN-based controller is applied to achieve a better performance control of active and reactive powers exchanged between the stator of the DFIG and the power grid. The second one is applied to ensure the Maximum Power Point Tracking (MPPT) of wind energy conversion system by controlling DFIG's electromagnetic torque. The third one is applied to control the pitch angle to limit the mechanical energy extracted from wind energy below rated power for different wind speeds. The proposed control strategies are carried out in MATLAB/SIMULINK environment using a 3MW DFIG and simulation results are presented and discussed.
Citation

M. BOUDJELLAL Bilal, (2016), "Artificial Neural Network-based control of wind energy conversion system based on a doubly fed induction generator", [international] The Mediterranean Journal of Measurement and Control , The Mediterranean Journal of Measurement and Control

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Open-switch fault-tolerant control of power converters in a grid-connected photovoltaic system

This paper presents the study of an open switch fault tolerant control of a grid-connected photovoltaic system. The studied system is based on the classical DC-DC boost converter and a bidirectional 6-pulse DC-AC converter. The objective is to provide an open-switch fault detection method and fault-tolerant control for both of boost converter and grid-side converter (GSC) in a grid-connected photovoltaic system. A fast fault detection method and a reliable fault-tolerant topology are required to ensure continuity of service, and achieve a faster corrective maintenance. In this work, the mean value of the error voltages is used as fault indicator for the GSC, while, for the boost converter the inductor current form is used as fault indicator. The fault-tolerant topology was achieved by adding one redundant switch to the boost converter, and by adding one redundant leg to the GSC. The results of the fault tolerant control are presented and discussed to validate the proposed approach under different scenarios and different solar irradiances. © 2016 Institute of Advanced Engineering and Science. All rights reserved.
Citation

M. BOUDJELLAL Bilal, (2016), "Open-switch fault-tolerant control of power converters in a grid-connected photovoltaic system", [national] International Journal of Power Electronics and Drive Systems (IJPEDS) , IJPEDS

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2015

Artificial neural networks controller for power system voltage improvement

In this paper, power system voltage improvement using wind turbine is presented. Two controllers are used: a PI controller and Artificial Neural Networks (ANN) controller are investigated. The power flow exchanged between the wind turbine and the power system has been controlled in order to improve the bus voltage based on reactive power injection (or absorption) produced by variable speed wind turbine. The wind turbine is based on a doubly fed induction generator (DFIG) controlled by field-oriented control. Indirect control is used to control of the reactive power flow exchanged between the DFIG and the power system. The proposed controllers are tested on power system for large voltage disturbances.
Citation

M. BOUDJELLAL Bilal, (2015), "Artificial neural networks controller for power system voltage improvement", [national] IREC2015 The Sixth International Renewable Energy Congress , IEEE

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2014

Power System Voltage Control Using Wind Farms Based on a Doubly Fed Induction Generation (DFIG)

This paper shows the modeling and the effectiveness of wind turbine for voltage improvement of power systems. The wind turbine is based on a doubly-fed induction generator (DFIG). A field-oriented control is used to control of the power flow exchanged between the DFIG and the power system. A simplified wind turbine model based on independent control of active and reactive powers is used in this paper. The proposed methodology is tested in the single machine power system connected to a wind farms in the case of sudden voltage variations.
Citation

M. BOUDJELLAL Bilal, (2014), "Power System Voltage Control Using Wind Farms Based on a Doubly Fed Induction Generation (DFIG)", [international] Advanced Materials Research , Advanced Materials Research

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Power system voltage control using wind turbine based on a doubly fed induction generation (DFIG)

Power system voltage control using wind turbine based on a doubly fed induction generation (DFIG)
Citation

M. BOUDJELLAL Bilal, (2014), "Power system voltage control using wind turbine based on a doubly fed induction generation (DFIG)", [international] La 1ere Conférence Nationale sur les Energies Renouvelables et leurs Applications , Adrar, Algérie

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2013

Improvement of Power System Transient Stability Using a Wind Turbine Based on DFIG

Improvement of Power System Transient Stability Using a Wind Turbine Based on DFIG.
Citation

M. BOUDJELLAL Bilal, (2013), "Improvement of Power System Transient Stability Using a Wind Turbine Based on DFIG", [international] The First International Conference on Power Electronics and their Applications , Djelfa, Algeria

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Field oriented control of active and reactive power of a DFIG with MPPT for variable speed wind energy conversion

Field oriented control of active and reactive power of a DFIG with MPPT for variable speed wind energy conversion.
Citation

M. BOUDJELLAL Bilal, (2013), "Field oriented control of active and reactive power of a DFIG with MPPT for variable speed wind energy conversion", [international] The First International Conference on Power Electronics and their Applications , Djelfa, Algeria

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