Enhanced control technique for a sensor-less wind driven doubly fed induction generator for energy conversion purpose

• Published in: Energy reports Vol. 7; pp. 5815 - 5833
• Main Authors: Mossa, Mahmoud A., Echeikh, Hamdi, Iqbal, Atif
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01-11-2021; Elsevier
• Subjects: DFIG; MPPT; Observer; Power angle; Predictive control; Wind energy; Power angle; Wind energy; MPPT; Observer; Predictive control; DFIG
• ISSN: 2352-4847; 2352-4847
• DOI: 10.1016/j.egyr.2021.08.183

The current paper is concerned with introducing a predictive polar flux control (PPFC) scheme for a variable speed wind driven doubly fed induction generator (DFIG) without speed sensor. The operation of the designed PPFC is based on the power angle regulation. The adaptation process is performed through studying the relation between the generator’s torque and the power angle between the stator and rotor flux vectors. A robust observer is designed based on the back-stepping theory to estimate the rotor speed, stator currents, rotor flux and stator and rotor resistances. Furthermore, an effective maximum power point tracking (MPPT) scheme is designed to achieve the optimal wind power exploitation. To recognize the operation of the schemed PPFC, a discursive performance evaluation is performed for the modeled control scheme and the classic predictive torque control (PTC) scheme. The achieved results report that the DFIG’s performance is effectively enhanced with the proposed PPFC in comparison with the PTC technique. The improved dynamics are observed through the ripples reduction and reduced switching frequency. In addition, the designed observer has successfully managed in estimating the specified variables with high precision.
•A new predictive control is designed and tested with a wind driven DFIG.•A robust variables estimator is designed using the back-stepping theory.•A noticeable dynamic enhancement is achieved with the presented control.•The low ripples and low computation burden are the most significant improvements.