Using Four-Level NSVM Technique to Improve DVC Control of a DFIG Based Wind Turbine Systems

  • Habib Benbouhenni Electrical Engineering Department, National Polytechnique School of Oran Maurice Audin, LAAS Research Laboratory, BP. 1523 El M’Naouer 31000 Oran, Algeria
  • Zinelaabidine Boudjema Electrical Engineering Department, Hassiba Benbouali University, LGEER Research Laboratory, Salem district 02000 Chlef, Algeria
  • Abdelkader Belaidi Electrical Engineering Department, National Polytechnique School of Oran Maurice Audin, LAAS Research Laboratory, BP. 1523 El M’Naouer 31000 Oran, Algeria

Abstract

Traditional direct vector control (DVC) compositions which consist of proportional-integral (PI) regulators of a doubly fed induction generator (DFIG) driven have several disadvantages such as parameter variation problem, low dynamic performances and poor robustness. Therefore, based on examination of the DFIG model supplied by new modulation method, this work addresses a four-level space vector modulation (SVM) based on neural networks (NSVM). The conventional DVC control with SVM strategy has large ripples on the electromagnetic torque, harmonic distortion of rotor current, stator reactive and active powers developed by the DFIG-based wind turbine systems (WTSs). In order to resolve these problems, the DVC technique with NSVM strategy is proposed. Simulation results show the effectiveness of the proposed control technique especially in electromagnetic torque, power ripples and robustness against parameters variations.

Keywords: direct vector control, doubly fed induction generator, space vector modulation, neural space vector modulation, neural networks
Published online
2019-03-29
How to Cite
Benbouhenni, H., Boudjema, Z. and Belaidi, A. (2019) “Using Four-Level NSVM Technique to Improve DVC Control of a DFIG Based Wind Turbine Systems”, Periodica Polytechnica Electrical Engineering and Computer Science, 63(3), pp. 144-150. doi: https://doi.org/10.3311/PPee.13636.
Section
Articles