Experimental validation of metaheuristic-optimized control for standalone DFIG dynamic performance enhancement

Area of Science:

• Electrical Engineering
• Renewable Energy Systems
• Control Systems

Background:

• Standalone Doubly Fed Induction Generator (DFIG) systems are crucial for off-grid power generation.
• Unbalanced loads significantly degrade the dynamic performance and power quality of DFIG systems.
• Conventional PI controllers often struggle to maintain optimal performance under dynamic load variations.

Purpose of the Study:

• To develop a robust control strategy for standalone DFIG systems facing unbalanced loads.
• To optimize Proportional-Integral (PI) controllers using metaheuristic algorithms for enhanced dynamic response and power quality.
• To validate the proposed control strategy through simulations and experimental testing.

Main Methods:

• Implementation of a direct-voltage control scheme for the rotor-side converter.
• Application of Cuckoo Search Algorithm (CSA) and Whale Optimization Algorithm (WOA) for PI controller tuning.
• Validation using a dSPACE DS1104 platform for comprehensive simulation and experimental analysis.

Main Results:

• Optimized PI controllers significantly improved transient response, reducing overshoot by up to 88% and rise time by 99%.
• Stator voltage Total Harmonic Distortion (THD) was suppressed by 82% under load and voltage step variations.
• Experimental results confirmed the superiority of CSA and WOA optimized controllers over conventional tuning methods.

Conclusions:

• Metaheuristic optimization using CSA and WOA provides a robust control strategy for standalone DFIG systems.
• The proposed method effectively enhances dynamic performance and power quality, particularly under unbalanced load conditions.
• This approach offers a significant advancement for reliable off-grid DFIG wind energy applications.