A vector control of a cascaded doubly fed induction generator for a wind energy conversion system

Boukettaya, Ghada; Naifar, Omar; Ouali, A.

doi:10.1109/ssd.2014.6808821

Cited by 12 publications

(9 citation statements)

References 9 publications

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“…For lossless systems, the maximum C p is equal to 0.59; accordingly it is possible to only extract 59% of the wind energy [30,31]. The value for C p can be computed as [31]:…”

Section: Wind Turbine Modelmentioning

confidence: 99%

“…Equation ( 12) shows how complex the BDFTIG system is, and confirms that there exists an electrical coupling between the control machine stator through the rotor to the power machine stator and shows that the power machine stator current is determined by power machine stator flux, rotor flux and control machine stator current. However, the power machines stator flux ψ sp has almost constant value due to the stiff grid connection assuming small stator winding resistance [30,32].…”

Section: Flux Equationsmentioning

confidence: 99%

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Indirect Vector-Controlled Brushless Doubly-Fed Twin-Stator Induction Generator for Wind Energy Conversion Application

2020

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Wind energy conversion systems (WECSs) seem certain to play a major part in the world’s energy future due to their known high power capacity. The maximum power tracking is unavoidable due to the wind velocity variation and the non-linear relation with the turbine mechanical power. Commercial wind turbines are commonly coupled to either doubly-fed induction generators (DFIGs), wound rotor synchronous generators (WRSG) or permanent magnet synchronous generators (PMSGs). The DFIG-based WECS has several advantages over others. One of which is the power converter in such systems only deals with rotor power, hence the converter rating can run at reduced power rating. However, DFIG has the famous disadvantage of the presence of slip rings which leads to increased maintenance costs and outage times. Hence, brushless doublyfed induction machines (BDFIMs) can be considered as a viable alternative at the penalty of complicated controller requirement and limited decoupling control capability due to the machine’s non-linearity. In this paper, an enhanced performance indirect vector controller is proposed for WECS based on brushless doubly-fed twin-stator induction generator (BDFTSIG). The presented controller offers (i) simplified implementation, (ii) decoupled active-reactive power control, and (iii) a wide range of operation. The proposed controller performance is investigated under various loading conditions showing enhanced transient and minimal steady-state oscillations in addition to complete active/reactive power decoupling. The rigorous simulation and experimental results verify the claimed controller effectiveness under all possible operating conditions for sub- and super-synchronous speed range.

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“…For lossless systems, the maximum C p is equal to 0.59; accordingly it is possible to only extract 59% of the wind energy [30,31]. The value for C p can be computed as [31]:…”

Section: Wind Turbine Modelmentioning

confidence: 99%

Section: Flux Equationsmentioning

confidence: 99%

Indirect Vector-Controlled Brushless Doubly-Fed Twin-Stator Induction Generator for Wind Energy Conversion Application

2020

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“…Fractional-order filters [22,23] have many advantages; they tune the shaper bandwidth and ensure a better selectivity. Moreover, the use of fractional orders in a lot of applications [24,25], where the system is extremely complex, allows solving huge problems such as reducing high control values. In this paper, L 1 fractional adaptive control is implemented, and it has proved a reduction of the error (elimination of the time lag) and reduction of the energy consumption.…”

Section: Introductionmentioning

confidence: 99%

$L_{1}$ Adaptive Fractional Control Optimized by Genetic Algorithms with Application to Polyarticulated Robotic Systems

Maalej

Khlif

Mhiri

et al. 2021

Mathematical Problems in Engineering

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Recently, an adaptive control approach has been proposed. This approach, named L 1 adaptive control, involves the insertion of a low-pass filter at the input of the Model Reference Adaptive Control (MRAC). This controller has been designed to overcome several limitations of classical adaptive controllers such as (i) the initialization of estimated parameters, (ii) the stability problems with high adaptation gains, and (iii) the appropriate parameter excitation. In this paper, a new design of the filter is presented, used for L 1 adaptive control, for which the desired performances are guaranteed (appropriate values of the control during start-up, a high filtering of noises, a reduced time lag, and a reduced energy consumption). Parameters of the new proposed filter have been optimised by genetic algorithms. The proposed L 1 adaptive fractional control is applied to a polyarticulated robotic system. Simulation results show the efficiency of the proposed control approach with respect to the classical L 1 adaptive control in the nominal case and in the presence of a multiplicative noise.

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“…For this reason, there are various speed control techniques available for the induction engine to solve this decoupling issue [3,4]. Among all methods, indirect vector control or IFOC is the most popular for achieving high efficiency [5,6].…”

Section: Introductionmentioning

confidence: 99%

Active Disturbance Rejection Control for a Five-Level Cascaded H-Bridge Inverter Fed Induction Motor Sensorless Field-Oriented

Bourhichi

Oukassi

Bahir

et al. 2021

Mathematical Problems in Engineering

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In this paper, a robust vector control sensorless based on three Active Disturbance Rejection Controllers (ADRC) for an induction motor fed by a five-level cascaded H-bridge was developed. The estimation of rotor position is achieved using a Luenberger estimator. The proposed model considers the disturbances and the inaccuracies of the system and compensates them using the extended state observer of ADRC. Moreover, a five-level cascaded H-bridge inverter is the best topology to minimize the torque ripples and to improve the current output of IMunder control. The suggested control system was simulated under different conditions using MATLAB-Simulink. The results demonstrate the effectiveness and the robustness of the proposed system against disturbances such as variations of parameters and load torque.

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A vector control of a cascaded doubly fed induction generator for a wind energy conversion system

Cited by 12 publications

References 9 publications

Indirect Vector-Controlled Brushless Doubly-Fed Twin-Stator Induction Generator for Wind Energy Conversion Application

Indirect Vector-Controlled Brushless Doubly-Fed Twin-Stator Induction Generator for Wind Energy Conversion Application

$L_{1}$ Adaptive Fractional Control Optimized by Genetic Algorithms with Application to Polyarticulated Robotic Systems

Active Disturbance Rejection Control for a Five-Level Cascaded H-Bridge Inverter Fed Induction Motor Sensorless Field-Oriented

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A vector control of a cascaded doubly fed induction generator for a wind energy conversion system

Cited by 12 publications

References 9 publications

Indirect Vector-Controlled Brushless Doubly-Fed Twin-Stator Induction Generator for Wind Energy Conversion Application

Indirect Vector-Controlled Brushless Doubly-Fed Twin-Stator Induction Generator for Wind Energy Conversion Application

L 1 Adaptive Fractional Control Optimized by Genetic Algorithms with Application to Polyarticulated Robotic Systems

Active Disturbance Rejection Control for a Five-Level Cascaded H-Bridge Inverter Fed Induction Motor Sensorless Field-Oriented

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Product

Resources

About

$L_{1}$ Adaptive Fractional Control Optimized by Genetic Algorithms with Application to Polyarticulated Robotic Systems