Intelligence Indirect Vector Control of a DFIG based Wind Turbines

Benbouhenni, Habib

Document Type : Review Article

Author

Habib Benbouhenni

Laboratoire LAAS, Ecole Nationale Polytechnique d’Oran Maurice Audin, Oran, Algérie.

Abstract

An intelligence Indirect Vector Control (IVC) of a Doubly Fed Induction Generator (DFIG) by using a five-level inverter with space vector modulation (5L-SVM) strategy is proposed in this article. The novelty of the proposed intelligence strategy is an Artificial Neural Network (ANN), which is utilised for the IVC command of the DFIG. In this research, ANN has been replaced with the hysteresis comparators of the 5L-SVM technique. The backpropagation process is used for the training process of the ANN. By using the ANN outputs, the SVM-ANN strategy develops command pulses for the five-level inverter. Subsequently, the proposed intelligence strategy is implemented in the MATLAB/Simulink platform and the effectiveness is analysed by comparing different tests. The simulation and comparison results have demonstrated the superiority of the proposed approach and confirmed the potential of the proposed system for solving the problem.

Keywords

References

Reference

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Majlesi Journal of Electrical Engineering

Intelligence Indirect Vector Control of a DFIG based Wind Turbines

References

References

Volume 13, Issue 3 - Serial Number 3
September 2019
Pages 27-35

Intelligence Indirect Vector Control of a DFIG based Wind Turbines

References

References

Volume 13, Issue 3 - Serial Number 3September 2019Pages 27-35

Volume 13, Issue 3 - Serial Number 3
September 2019
Pages 27-35