Optimal hybrid resonant current controller for microgrids connected to an unbalanced IEEE test distribution network

Area of Science:

• Electrical Engineering
• Power Systems Engineering
• Control Systems

Background:

• Conventional distribution networks face power quality issues.
• Microgrids (MGs) offer a solution but require optimal control strategies.
• Hybrid controllers can enhance MG performance and grid integration.

Purpose of the Study:

• To develop and validate a novel hybrid Proportional-Resonant (PR) and Linear Quadratic Regulator (LQR) controller for microgrids.
• To optimize the hybrid controller parameters using the Grey Wolf Optimizer (GWO).
• To assess the controller's effectiveness in improving power quality and reducing unbalanced currents in distribution networks.

Main Methods:

• Designed a hybrid PR+LQR controller merging PR and LQR controller properties.
• Utilized the Grey Wolf Optimizer (GWO) for tuning control parameters via a fitness function.
• Validated the approach on the IEEE 13-bus test feeder with two strategically placed MGs.
• Conducted simulations under various renewable energy penetration levels and power factor conditions.

Main Results:

• The hybrid PR+LQR controller, optimized by GWO, demonstrated high performance.
• Simulations showed an average reduction in unbalanced current of 30.03%.
• Robustness and stability were confirmed using disk margin and Nyquist criterion.

Conclusions:

• The proposed hybrid PR+LQR controller driven by GWO is a reliable strategy for enhancing microgrid performance.
• This approach effectively mitigates power quality issues, specifically unbalanced currents, in distribution networks.
• The controller offers a significant improvement over existing methods for microgrid control and grid integration.