Intelligent MPPT and coordinated control for voltage stability in brushless DFIG wind turbines.

Area of Science:

• Electrical Engineering
• Renewable Energy Systems
• Control Systems

Background:

• Brushless Doubly Fed Induction Generators (DFIGs) are crucial for wind energy conversion.
• Ensuring voltage stability and maximizing power extraction in DFIG-based WECS are significant challenges.
• Existing control methods may not adequately address dynamic grid conditions and harmonic distortions.

Purpose of the Study:

• To develop a novel control approach for Brushless Doubly Fed Induction Generator (DFIG) based Wind Energy Conversion Systems (WECS).
• To improve voltage stability and maximize power extraction under dynamic operating conditions.
• To enhance grid support features and reduce harmonic distortion.

Main Methods:

• Utilizing a Chaotic Salp Swarm Optimization (CSSO) tuned Adaptive Neuro Fuzzy Inference System (ANFIS) for Maximum Power Point Tracking (MPPT).
• Implementing coordinated control between the Rotor Side Converter (RSC) and Grid Side Converter (GSC).
• Employing a d-q reference frame based current control strategy for harmonic suppression.

Main Results:

• Achieved high tracking efficiency ([Formula: see text]) with improved tracking speed (0.08s).
• Reduced total harmonic distortion (THD) to below 2.85%.
• Demonstrated significant improvements in voltage stability and wind energy harvesting efficiency.

Conclusions:

• The developed CSSO-ANFIS control approach effectively enhances voltage stability and power extraction in DFIG-WECS.
• The coordinated control strategy improves grid support and reduces harmonic distortion.
• The controller shows robust performance under both steady-state and dynamic conditions, validated in MATLAB/Simulink.