Adaptive hybrid virtual inertia controller for PMSG-based wind turbine based on fuzzy logic control.

Area of Science:

• Electrical Engineering
• Control Systems
• Renewable Energy Systems

Background:

• Microgrids with renewable energy sources (RES) face reduced inertia, impacting frequency stability.
• Conventional virtual inertia controllers struggle with varying microgrid conditions and performance requirements like frequency nadir and rate of change of frequency (ROCOF).

Purpose of the Study:

• To propose a hybrid adaptive virtual inertia control strategy to enhance frequency support in low-inertia microgrids.
• To improve microgrid resilience against disturbances from RES and load variations.

Main Methods:

• A hybrid adaptive virtual inertia control strategy is developed, integrating kinetic energy (KE) based virtual inertia control and virtual capacitance control.
• Fuzzy logic is employed to adapt the gains of both control loops simultaneously.
• Simulations are conducted using MATLAB/Simulink to evaluate dynamic performance.

Main Results:

• The proposed strategy effectively enhances system inertia and frequency support.
• Simulations demonstrate improved performance under various RES disturbances and load changes.
• The adaptive nature of the controller ensures robustness across different microgrid operating conditions.

Conclusions:

• The proposed Fuzzy logic-based hybrid adaptive virtual inertia control strategy offers a robust solution for frequency stability in low-inertia microgrids.
• This approach effectively mitigates the challenges associated with integrating a high penetration of converter-based RES.
• The study highlights the potential for enhanced microgrid performance and reliability through advanced control techniques.