Robust Direct Power Control of a DFIG Fed by a Five- Level NPC Inverter Using Neural SVPWM Technique

Benbouhenni, Habib

doi:10.18280/ti-ijes.650118

Cited by 6 publications

(8 citation statements)

References 19 publications

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“…The aerodynamic power P tur captured by the wind turbine is given by [12][13][14][15][16][17][18][19][20][21][22]:…”

Section: Modelling Of the Wind Turbinementioning

confidence: 99%

“…Artificial neural control is very powerful tool capable of achieving very good results in the control of complex systems. It is preferred to use Artificial Neural Networks (ANN) for control when requirements for precision are high and system is not identified precisely, or its parameters are changing [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17].…”

Section: Introductionmentioning

confidence: 99%

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Robust Neural Control of Wind Turbine Based Doubly Fed Induction Generator and NPC Three Level Inverter

Narimene

Kheira

Mohamed

2022

Period. Polytech. Elec. Eng. Comp. Sci.

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This paper presents dynamic modeling and control of Doubly Fed Induction Generator (DFIG) based on wind turbine systems, where the stator of DFIG is directly connected to the grid and the rotor was fed by a three level PWM NPC inverter. The active and reactive power control of the DFIG is based on the feedback technique by vector control method by using a classical regulator of Proportional-Integral (PI) type which allows us, in association with the looping of powers, to obtain an efficient and robust system. This approach is a very attractive solution for devices using DFIG as wind energy conversion systems; because, it is a simple, practical implementation, commonly applied in the wind turbine industry and it presents very acceptable performance, However, this control approach has certain limitations and has several causes, vector command with NPC three-level inverter pulse width modulation (PWM) is used to control the reactive power and active power of the generator. Then, use the neural network design to replace the traditional proportional-integral (PI) controller. Finally, the Matlab/Simulink software is used for simulation to prove the effectiveness of the command strategy.

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“…The aerodynamic power P tur captured by the wind turbine is given by [12][13][14][15][16][17][18][19][20][21][22]:…”

Section: Modelling Of the Wind Turbinementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robust Neural Control of Wind Turbine Based Doubly Fed Induction Generator and NPC Three Level Inverter

Narimene

Kheira

Mohamed

2022

Period. Polytech. Elec. Eng. Comp. Sci.

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“…In this proposed method, the reference tension is not used or calculated as well as the regions where the reference tension is present. This proposed method in [26] is simpler and more intuitive compared to the classical SVM method. In this part, the proposed fuzzy SVM technique is used to control a five-level inverter for an asynchronous generator placed in a multi-turbine wind system.…”

Section: Proposed Five-level Fuzzy Svm Strategymentioning

confidence: 99%

“…In this method, the calculation of reference voltage and zones is relied upon, which makes this method more complicated, especially in the case of a multi-level inverter [25]. To overcome this problem, a new idea for this method was presented in [26], where the calculation of the maximum and minimum values of the three-phase feeding voltages was used in this proposed method. In this proposed method, the reference tension is not used or calculated as well as the regions where the reference tension is present.…”

Section: Proposed Five-level Fuzzy Svm Strategymentioning

confidence: 99%

Simplified Super Twisting Sliding Mode Approaches of the Double-Powered Induction Generator-Based Multi-Rotor Wind Turbine System

et al. 2022

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This work proposes a new indirect filed-oriented control (IFOC) scheme for double-powered induction generators (DPIGs) in multi-rotor wind turbine systems (MRWTS). The IFOC strategy is characterized by its simplicity, ease of use, and fast dynamic speed. However, there are drawbacks to this method. Among its disadvantages is the presence of ripples in the level of torque, active power, and current. In addition, the total harmonic distortion (THD) value of the electric current is higher compared to the direct torque control method. In order to overcome these shortcomings and in terms of improving the effectiveness and performance of this method, a new algorithm is proposed for the super twisting algorithm (STA). In this work, a new STA method called simplified STA (SSTA) algorithm is proposed and applied to the traditional IFOC strategy in order to reduce the ripples of torque, current, and active power. On the other hand, the inverter of the DPIG is controlled by using a five-level fuzzy simplified space vector modulation (FSSVM) technique to obtain a signal at the inverter output of a fixed frequency. The results obtained from this proposed IFOC-SSTA method with FSSVM strategy are compared with the classical IFOC method which uses the classical controller based on a proportional-integral (PI) controller. The proposed method is achieved using the Matlab/Simulink software, where a generator with a large capacity of 1.5 megawatts is used. The generator is placed in a multi-rotor electric power generation system. On the other hand, the two methods are compared in terms of ripple ratio, dynamic response, durability, and total harmonic distortion (THD) value of the electric current. Through the results obtained from this work, the proposed method based on SSTA provided better results in terms of ripple ratio, response dynamic, and even THD value compared to the classical method, and this shows the robustness of the proposed method in improving the performance and efficiency of the generator in the multi-rotor wind system.

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“…The first method has less THD. The work [18] proposed a new DPC strategy based on a second order sliding mode controller of a doubly fed induction generator (DFIG) integrated in a wind energy conversion system. In the first step it proposed to use a five-level inverter based on the neural space vector pulse width modulation to supply the DFIG rotor side.…”

mentioning

confidence: 99%

New application of artificial neural network-based direct power control for permanent magnet synchronous generator

Akkouchi

Rahmani

Lebied³

2021

Electrical Engineering & Electromechanics

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Purpose. This article proposes a new strategy for Direct Power Control (DPC) based on the use of Artificial Neural Networks (ANN-DPC). The proposed ANN-DPC scheme is based on the replacement of PI and hysteresis regulators by neural regulators. Simulation results for a 1 kW system are provided to demonstrate the efficiency and robustness of the proposed control strategy during variations in active and reactive power and in DC bus voltage. Methodology. Our strategy is based on direct control of instant active and reactive powers. The voltage regulator and hysteresis are replaced by more efficient and robust artificial neuron networks. The proposed control technique strategy is validated using MATLAB / Simulink software to analysis the working performances. Results. The results obtained clearly show that neuronal regulators have good dynamic performances compared to conventional regulators (minimum response time, without overshoots). Originality. Regulation of continuous bus voltage and sinusoidal currents on the network side by using artificial neuron networks. Practical value. The work concerns the comparative study and the application of DPC based on ANN techniques to achieve a good performance control system of the permanent magnet synchronous generator. This article presents a comparative study between the conventional DPC control and the ANN-DPC control. The first strategy based on the use of a PI controller for the control of the continuous bus voltage and hysteresis regulators for the instantaneous powers control. In the second technique, the PI and hysteresis regulators are replaced by more efficient neuronal controllers more robust for the system parameters variation. The study is validated by the simulation results based on MATLAB / Simulink software.

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Robust Direct Power Control of a DFIG Fed by a Five- Level NPC Inverter Using Neural SVPWM Technique

Cited by 6 publications

References 19 publications

Robust Neural Control of Wind Turbine Based Doubly Fed Induction Generator and NPC Three Level Inverter

Robust Neural Control of Wind Turbine Based Doubly Fed Induction Generator and NPC Three Level Inverter

Simplified Super Twisting Sliding Mode Approaches of the Double-Powered Induction Generator-Based Multi-Rotor Wind Turbine System

New application of artificial neural network-based direct power control for permanent magnet synchronous generator

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