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Related Experiment Video

Updated: May 8, 2026

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

Real time simulation of nonlinear generalized predictive control for wind energy conversion system with nonlinear

Kamel Ouari¹, Toufik Rekioua¹, Mohand Ouhrouche²

¹Laboratory LTII, University of Bejaia, Algeria.

ISA Transactions

|September 12, 2013

Summary

This study introduces an advanced control strategy for Doubly-Fed Induction Generators (DFIGs) in wind turbines. The nonlinear generalized predictive control (NGPC) approach enhances cost-effectiveness and reliability in wind power generation.

Keywords:

DFIG-based wind turbine Doubly-fed induction generator (DFIG)Nonlinear generalized predictive control (NGPC)Real-time simulation

Related Experiment Videos

Last Updated: May 8, 2026

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Experimental Investigation of the Hierarchical Control in DC Microgrids Using a Real-time Simulator

Published on: February 14, 2025

Area of Science:

Renewable Energy Systems
Control Engineering
Electrical Engineering

Background:

Wind power generation requires advanced control for cost-effectiveness and reliability.
Doubly-Fed Induction Generators (DFIGs) are commonly used in wind turbines.
Existing control methods may not fully address uncertainties and performance demands.

Purpose of the Study:

To develop a novel control strategy for DFIG-based wind turbines.
To improve the robustness and performance of wind turbine controllers.
To enhance the cost-effectiveness and reliability of wind power generation.

Main Methods:

Development of a nonlinear generalized predictive control (NGPC) approach.
Implementation of an NGPC-based torque-current control loop for rotor reference voltage.
Design of an NGPC-based speed control loop for torque reference.
Integration of a disturbance observer to estimate aerodynamic torque as an unknown perturbation.

Main Results:

The proposed NGPC strategy effectively controls the DFIG.
The disturbance observer enhances controller robustness against aerodynamic torque variations.
Real-time simulations demonstrate the successful performance of the developed control system.

Conclusions:

The NGPC-based control strategy offers a promising solution for advanced DFIG wind turbine control.
The integration of a disturbance observer significantly improves system robustness.
This approach contributes to more reliable and cost-effective wind power generation.