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A Predictive Repetitive Current Control in Stationary Reference Frame for DFIG Systems Under Distorted Voltage Operation

Eliomar R. Conde D., Angelo Lunardi, Luís F. Normandia Lourenço, Alfeu J. Sguarezi Filho

2022IEEE Journal of Emerging and Selected Topics in Power Electronics14 citationsDOI

Abstract

This article presents a stationary reference frame implementation of the predictive repetitive controller under ideal and nonideal stator voltage conditions. Thanks to the combination of the model predictive control (MPC) and the repetitive control techniques, the predictive repetitive control uses the capabilities of both techniques to achieve the control objectives without the need of using a PLL for the stator flux in ideal conditions as the approach is developed in the stationary reference frame <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\alpha \beta $ </tex-math></inline-formula> . For the operation of the technique, it is also not necessary to know the harmonic content of the nonideal stator voltage beforehand, but, for this case, and given the nature of the distortions, the use of the PLL is necessary to estimate the phase angle and the magnitude of the voltage’s fundamental component. This means a great advantage over previous techniques due to the fact that special considerations are not needed over the mathematical model of the doubly fed induction generator (DFIG). Experimental results of the proposed technique are presented in ideal and nonideal grid conditions, and under variable rotor speed. Moreover, a comparison with the classic MPC technique is presented.

Topics & Concepts

Stationary Reference FrameControl theory (sociology)StatorReference frameModel predictive controlRotor (electric)Frame (networking)VoltageController (irrigation)Generator (circuit theory)HarmonicsHarmonicPhase-locked loopIdeal (ethics)Computer scienceEngineeringElectronic engineeringControl (management)Power (physics)Induction motorPhysicsElectrical engineeringArtificial intelligenceEpistemologyTelecommunicationsBiologyQuantum mechanicsJitterPhilosophyAgronomyMicrogrid Control and OptimizationMultilevel Inverters and ConvertersIterative Learning Control Systems