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Intelligent control of a brushless doubly-fed induction generator


Brushless doubly-fed induction generator (BDFIG) has drawn significant attention in recent years in variable speed drive applications due to such features as simple and robust construction, favorable operating characteristics and reduced maintenance. The objective of BDFIG control is to achieve better performance compared to the doubly fed induction generator using the well-established vector control method. Control of a BDFIG with back-to-back PWM converters using an artificial intelligence approach, fuzzy PID controller, is proposed for a BDFIG-based variable speed wind energy conversion system. The proposed controller is adaptive in the manner that the controller parameters are modified online by using the fuzzy control rules. Comparative performance of the BDFIG with the proposed fuzzy PID controller and the conventional fixed-parameters PID controller under various operating speeds, stator reactive power references and a 100% voltage dip is investigated. Results of simulation studies using MATLAB® reported in the paper show that the limitations of the conventional PID controller can have negative effects on both quality and quantity of the generated power. Performance of the system can be improved with the proposed adaptive fuzzy PID controller under dynamic conditions.

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V w :

Wind speed (m/s)

\(\omega_{p} , \omega_{c} , \omega_{r} \;and\;\omega_{n}\) :

Power winding angular frequency, control winding angular frequency, synchronous rotor speed and natural angular frequency

P m :

Mechanical power, Watts

P mec_ opt :

Optimal mechanical power, Watts

P t :

Mechanical power of the turbine, Watts

P w :

Theoretical power available in the wind, Watts

Pp, Pc :

Active power of the power winding and control winding, respectively, Watts

Qp, Qc :

Reactive power of the power winding and control winding, respectively, Var

PT, QT :

Total active and reactive power at the AC-side of the BDFIG


Air density, kg/m3


Surface area swept by the blade, m2

Cp, CPmax :

Power coefficient and maximum power coefficient of the wind turbine


Tip speed ratio of the turbine blade


Radius of the rotor, m

Tt :

Mechanical torque of the turbine, Watts


Gearbox ratio

Tg :

Torque at shaft end, Nm

Tem :

Electromagnetic torque, Nm

Ωt :

Speed at shaft end, rad/s

Ωmec :

Mechanical speed of the rotor, rad/s


Moment of inertia, kg m2


Coefficient of friction

Nr :

Number of rotor loops

pp, pc :

Pole pair number of the power winding and control winding, respectively

\({\text{v}}_{\rm{sp}}^{\rm{dq}} , {\text{i}}_{\rm{sp}}^{\rm{dq}} \;{\text{and }}\;\uppsi_{\rm{sp}}^{\rm{dq}}\) :

d–q components of the power winding voltage, current and flux

\({\text{v}}_{\rm{sc}}^{\rm{dq}} , {\text{i}}_{\rm{sc}}^{\rm{dq}} \;{\text{and}}\;\uppsi_{\rm{sc}}^{\rm{dq}}\) :

d–q components of the control winding voltage, current and flux

\({\text{v}}_{\rm{r}}^{\rm{dq}} , {\text{i}}_{\rm{r}}^{\rm{dq}} \;{\text{and}}\;\uppsi_{\rm{r}}^{\rm{dq}}\) :

d–q components of the rotor winding voltage, current and flux

Vdc :

DC-link voltage

Subscripts ‘p’ and ‘c’:

Stand for the power winding and control winding, respectively


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Correspondence to Zoheir Tir.

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Tir, Z., Malik, O.P. & Hashemnia, M.N. Intelligent control of a brushless doubly-fed induction generator. Int J Syst Assur Eng Manag 10, 326–338 (2019).

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  • Brushless doubly fed induction generator
  • Fuzzy PID controller
  • Power flow
  • Wind energy system