Stator side active and reactive power control with improved rotor position and speed estimator of a grid connected DFIG (doubly-fed induction generator)

Gayen, Pritam Kumar; Chatterjee, Dheeman; Goswami, S. K.

doi:10.1016/j.energy.2015.05.111

Cited by 27 publications

(10 citation statements)

References 37 publications

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“…4. In the proposed scheme, the estimation of the rotor position and speed is done by employing the model reference adaptive system (MRAS) control technique [27].…”

Section: Figure 3 Schematic Circuit For Dfig Systemmentioning

confidence: 99%

An SSM-PSO Based MPPT Scheme for Wind Driven DFIG System

et al. 2022

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In this work, a searching space minimization-based particle swarm optimization (SSM-PSO) scheme has been proposed for maximum power point tracking (MPPT) in a doubly fed induction generator (DFIG) based wind energy conversion system (WECS). DFIG displays non-linearity in 𝑃 − 𝜔 characteristics. So different types of conventional and optimization-based schemes are developed for MPPT. The drawbacks in the conventional perturb and observe (P&O) scheme has been successfully abolished by the proposed SSM-PSO method. Because of its weather-insensitive nature, the conventional P&O MPP tracking scheme results in the fluctuation of DFIG output under a sudden change in wind speed. To avoid this problem, maximum and minimum limits for the optimal rotor speed have been determined in the proposed SSM-PSO scheme. Further, the obtained limits for rotor speed are employed to improve the searching space within the non-linear 𝑃 − 𝜔 curve. This initial confinement of particles to a limited searching space in SSM-PSO results in a faster response of the system. Since the proposed SSM-PSO is atmosphere sensitive, it avoids fluctuations under an abrupt variation in wind velocity. The improved initialization part of SSM-PSO leads to better dynamic characteristics compared to existing P&O and optimization-based schemes. The proposed SSM-PSO scheme is implemented for a 2MW DFIG system in MATLAB Simulink atmosphere and showed satisfactory results.

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“…4. In the proposed scheme, the estimation of the rotor position and speed is done by employing the model reference adaptive system (MRAS) control technique [27].…”

Section: Figure 3 Schematic Circuit For Dfig Systemmentioning

confidence: 99%

An SSM-PSO Based MPPT Scheme for Wind Driven DFIG System

et al. 2022

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“…The second one is to orient the q ‐axis along the stator voltage and delay the d ‐axis by 90° because the two vectors are shifted by 90°. The first option is the widely proposed for wind power generation using DFIG and is the classical method used in the literature …”

Section: Control Strategies For the Wecsmentioning

confidence: 99%

“…The first option is the widely proposed for wind power generation using DFIG and is the classical method used in the literature. [36][37][38]…”

Section: Indirect Field-oriented Control Structurementioning

confidence: 99%

Power control of variable speed wind turbine based on doubly fed induction generator using indirect field‐oriented control with fuzzy logic controllers for performance optimization

Zamzoum

Mourabit

Errouha

et al. 2018

Energy Science & Engineering

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The main objective of this study is to improve the energy quality extracted by variable speed wind turbine based on doubly fed induction generator. First, the dynamic modeling of different parts of the system is presented. The electrical machine is modeled in PARK reference frame. Thereafter, the control technique is detailed. Indirect field‐oriented control with fuzzy logic controllers (FLC) is used to control the rotor currents and consequently the real and reactive powers of the stator generator. Then, the design of FLC is detailed by tuning its most significant parameters, which are scaling factor rules base and membership functions. Finally, a simulation using the MATLAB/SIMULINK environment is carried out to prove the validation of the control strategy using a 2 MW wind turbine. The results show a satisfactory performance in terms of rapidity, stability, and precision under variable wind speed conditions.

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“…Many researchers focus their studies based on field oriented control (FOC) using linear regulator proportional integrator (PI) in order to control rotor side converter (RSC) as mention in [16][17][18], by calculationg Kp and Ki.…”

Section: Introductionmentioning

confidence: 99%

Stator Active and Reactive Power Ripples Minimization for DVC Control of Dfig by Using Five-Level Neural Space Vector Modulation

Benbouhenni¹,

Audin²

2019

AEI

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This paper presents a direct vector control (DVC) strategy for the doubly fed induction generator (DFIG)based wind turbine systems. The major disadvantages that are usually associated with DVC control scheme are the electromagnetic torque, reactive power and active power ripples. To overcome these disadvantages an advanced five-level space vector modulation (5L-SVM) strategy based on neural networks (NNs) controller is proposed. The proposed controller is shown to be able to reduce the reactive and active powers ripples and to improve the performances of the DVC control. Simulation results are shown by using Matlab/Simulink.

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Stator side active and reactive power control with improved rotor position and speed estimator of a grid connected DFIG (doubly-fed induction generator)

Cited by 27 publications

References 37 publications

An SSM-PSO Based MPPT Scheme for Wind Driven DFIG System

An SSM-PSO Based MPPT Scheme for Wind Driven DFIG System

Power control of variable speed wind turbine based on doubly fed induction generator using indirect field‐oriented control with fuzzy logic controllers for performance optimization

Stator Active and Reactive Power Ripples Minimization for DVC Control of Dfig by Using Five-Level Neural Space Vector Modulation

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