Optimization of the DFIG Wind Turbine Controller Parameters by the Gray Wolf Algorithm

Document Type : Original Research (Full Papers)


Faculty of Electrical, Biomedical and Mechatronics Engineering, Qazvin Branch, Islamic Azad University, Qazvin, Iran


The increase in the power generated by the wind has
had effects on the performance of the power system in
cases such as power quality, safety, stability, and
voltage control. The wind turbines are used to generate
electrical energy from wind. They can work in fixed
or variable speeds. The asynchronous generator is
directly connected to the grid for the fixed-speed wind
turbines. In order to connect the DFIG (Doubly-Fed
Induction Generator) to the grid, this machine must be
able to integrate its generated power into the grid in a
specific voltage (the grid voltage level). The main
DFIG controlling method is the use of field-oriented
vector control for regulating the rotor flux. The DFIG
vector control consists of two main parts as grid side
converter control and rotor side converter control. The
rotor side converter is used to control the grid output
power. This converter regulates the power factors in
the terminals, and actually restores the generated
power deviation from the reference power through the
PID controllers, besides guaranteeing the stability of
the induction generator. In the current study, the power
was controlled through the determination of the PID
optimal coefficient of the rotor and grid sides
controllers and the gray wolf algorithm in the
MATLAB software. In addition, the stability of the
small signal of the grid equipped with the doubly-fed
wind generator in the wind speed turbulence
conditions was optimized to satisfy the required
criteria in output active and reactive power of a DFIG.
From the simulation results it is observed that the
proposed controller yields better results when
compared to other methods in literature in terms of
performance index.


  • Receive Date: 21 November 2021
  • Revise Date: 13 February 2022
  • Accept Date: 14 February 2022
  • First Publish Date: 14 February 2022