Periodica Polytechnica Electrical Engineering and Computer Science
In this paper, an experimental study of a Wind Energy Conversion System (WECS) is performed. A te... more In this paper, an experimental study of a Wind Energy Conversion System (WECS) is performed. A test bench with a power of 1.5 kW is setup. The system consists of a Doubly-Fed Induction Generator (DFIG) and a wind emulator based on a DC motor associated with a Maximum Power Point Tracking (MPPT) control. The proposed emulator is driven by a four quadrants DC/DC converter to produce a real wind turbine behavior. The aim of this work is to improve the DIFG performances by using the fuzzy logic-based intelligent controller. This control technic is designed to monitor the stator reactive and active powers. This can be achieved by the DFIG rotor side converter (RSC) using the field-oriented control. The experimental setup uses a dSPACE DS1104 device, MATLAB/Simulink software and a ControlDesk interface. The paper shows that, the desired amount of active and reactive powers has been independently controlled and the implementation is successfully verified the effectiveness of the proposed c...
2019 Progress in Applied Electrical Engineering (PAEE), 2019
The aim of this paper is the improvement of the double fed induction generator (DFIG) torque cont... more The aim of this paper is the improvement of the double fed induction generator (DFIG) torque control by using a Backstepping approach. The used 7.5 KW DFIG is fed by two cascaded two-level inverters where the control pulses are generated from the Backstepping control scheme. The performances of the suggested approach are tested by simulation under different operating conditions and compared to those of the well-known DTC control.
2021 18th International Multi-Conference on Systems, Signals & Devices (SSD), 2021
This article discusses a comparative study between classical PI control and Artificial Neural Net... more This article discusses a comparative study between classical PI control and Artificial Neural Network (ANN) based control of a brushless DC motor. BLDC is recommended for drives that require a large load torque, these types of motors are non-linear systems which require robust control. Due to the saturation characteristic presented by the conventional PI regulator which causes the instability of the system, we have used an artificial neuron-based controller to overcome these aspects and to provide a better dynamic and quick response, in order to control the speed of a BLDC motor as well as the reduction in torque ripples. Simulation results obtained using MATLAB / SIMULINK show that the artificial neuron network controller performance evaluation are better than those obtained by the standard PI controller.
The present research paper deals with a study of a variable speed wind energy conversion system (... more The present research paper deals with a study of a variable speed wind energy conversion system (VSWECS) based on a Doubly Fed Induction Generator (DFIG), the stator is directly connected to the grid and driven by climbed back-to-back converters. Direct control of DFIG with a variable structure based on an artificial neural network is presented. Artificial Neuronal Network ANN is proposed to improve performances and to substitute the classical PI regulators in the direct control of active and reactive powers of the DFIG. The performance of the approach has been tested and validated by simulation for different operating conditions. Simulation results and improvement of the behavior of the DFIG are presented, using Matlab/Simulink software.
Periodica Polytechnica Electrical Engineering and Computer Science
In this paper, an experimental study of a Wind Energy Conversion System (WECS) is performed. A te... more In this paper, an experimental study of a Wind Energy Conversion System (WECS) is performed. A test bench with a power of 1.5 kW is setup. The system consists of a Doubly-Fed Induction Generator (DFIG) and a wind emulator based on a DC motor associated with a Maximum Power Point Tracking (MPPT) control. The proposed emulator is driven by a four quadrants DC/DC converter to produce a real wind turbine behavior. The aim of this work is to improve the DIFG performances by using the fuzzy logic-based intelligent controller. This control technic is designed to monitor the stator reactive and active powers. This can be achieved by the DFIG rotor side converter (RSC) using the field-oriented control. The experimental setup uses a dSPACE DS1104 device, MATLAB/Simulink software and a ControlDesk interface. The paper shows that, the desired amount of active and reactive powers has been independently controlled and the implementation is successfully verified the effectiveness of the proposed c...
2019 Progress in Applied Electrical Engineering (PAEE), 2019
The aim of this paper is the improvement of the double fed induction generator (DFIG) torque cont... more The aim of this paper is the improvement of the double fed induction generator (DFIG) torque control by using a Backstepping approach. The used 7.5 KW DFIG is fed by two cascaded two-level inverters where the control pulses are generated from the Backstepping control scheme. The performances of the suggested approach are tested by simulation under different operating conditions and compared to those of the well-known DTC control.
2021 18th International Multi-Conference on Systems, Signals & Devices (SSD), 2021
This article discusses a comparative study between classical PI control and Artificial Neural Net... more This article discusses a comparative study between classical PI control and Artificial Neural Network (ANN) based control of a brushless DC motor. BLDC is recommended for drives that require a large load torque, these types of motors are non-linear systems which require robust control. Due to the saturation characteristic presented by the conventional PI regulator which causes the instability of the system, we have used an artificial neuron-based controller to overcome these aspects and to provide a better dynamic and quick response, in order to control the speed of a BLDC motor as well as the reduction in torque ripples. Simulation results obtained using MATLAB / SIMULINK show that the artificial neuron network controller performance evaluation are better than those obtained by the standard PI controller.
The present research paper deals with a study of a variable speed wind energy conversion system (... more The present research paper deals with a study of a variable speed wind energy conversion system (VSWECS) based on a Doubly Fed Induction Generator (DFIG), the stator is directly connected to the grid and driven by climbed back-to-back converters. Direct control of DFIG with a variable structure based on an artificial neural network is presented. Artificial Neuronal Network ANN is proposed to improve performances and to substitute the classical PI regulators in the direct control of active and reactive powers of the DFIG. The performance of the approach has been tested and validated by simulation for different operating conditions. Simulation results and improvement of the behavior of the DFIG are presented, using Matlab/Simulink software.
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Papers by mohamed HALLOUZ