Control (management)

Voltage

Engineering

Induction motor

Control system

Control engineering

Linear-quadratic regulator

Vector control

Computer science

Mathematical optimization

Pitch control

AC power

Mathematics

Artificial intelligence

Optimal control

Wind power

Control theory (sociology)

Gain scheduling

Electrical engineering

Journal of Electrical and Computer Engineering

This paper proposes an optimal gain-scheduling for linear quadratic regulator (LQR) control framework to improve the performance of wind turbines based Doubly Fed Induction Generator (DFIG). Active and reactive power decoupling is performed using the field-oriented vector control which is used to simplify DFIG’s nonlinearity and derive a compact linearized state-space model. The performance of the optimal controller represented by a linear quadratic regulator is further enhanced using the whale optimization algorithm in a multiobjective optimization environment. Adaptiveness against wind speed variation is achieved in an offline training process at a discretized wind speed domain. Lookup tables are used to store the optimal controller parameter and called upon during the online implementation. The control framework further integrates the effects of pitch angle control mechanism for active power ancillary services and possible improvements on reactive power support. The results of the proposed control framework improve the overall performance of the system compared to the conventional PI controller. Comparison is performed using the MATLAB Simulink platform.

Active and Reactive Power Control for Wind Turbines Based DFIG Using LQR Controller with Optimal Gain-Scheduling