Genetic algorithm type 2 fuzzy logic controller of microgrid system with a fractional-order technique.

Area of Science:

• Electrical Engineering
• Control Systems
• Renewable Energy Systems

Background:

• Microgrids face control challenges due to fluctuating renewable energy sources and varying loads.
• Traditional control methods may struggle with inherent system uncertainties and dynamic responses.
• Effective microgrid management is crucial for grid stability and efficient power delivery.

Purpose of the Study:

• To develop and evaluate a hybrid fractional-order type-2 fuzzy logic controller (FO-T2FLC) optimized by a genetic algorithm (GA) for microgrid control.
• To enhance the dynamic response, power quality, and robustness of a microgrid system.
• To reduce total harmonic distortion (THD) and improve voltage regulation in the microgrid.

Main Methods:

• A hybrid control strategy combining a GA-optimized T2FLC with fractional-order calculus was designed.
• The controller was applied to a microgrid system with photovoltaic array, battery storage, and a multi-functional inverter with active power filter.
• Performance was validated using MATLAB simulations, comparing the proposed FO-T2FLC-GA against T2FLC-GA and third-order sliding mode control.

Main Results:

• The FO-T2FLC-GA approach significantly reduced current total harmonic distortion (THD) by up to 80%.
• It improved direct current (DC) link voltage regulation, reducing steady-state error, undershoot, fluctuations, and overshoot by notable percentages compared to T2FLC-GA.
• Compared to third-order sliding mode control, the proposed method showed substantial improvements in response time, overshoot, and ripples.

Conclusions:

• The proposed FO-T2FLC-GA approach offers a robust and efficient solution for microgrid control, outperforming existing methods.
• Its model-independent nature and superior performance in power quality improvement and voltage regulation make it suitable for diverse industrial applications.
• This advanced control strategy holds promise for future microgrid implementations and other complex power systems.