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

Abstract

Microgrids (MGs) based on renewable energies have emerged as a proficient strategy for tackling power quality issues in conventional distribution networks. Nonetheless, MG systems require a suitable control scheme to supply energy optimally towards the electrical grid. This paper presents an innovative framework for designing hybrid Proportional-Resonant (PR) controllers with Linear Quadratic Regulators (LQR), PR+LQR, which merge relevant properties of PR and LQR controllers. This method simultaneously determines the MG control parameters and the current unbalanced factor generated at the distribution network. We select the traditional IEEE 13-bus test feeder network and place two MGs at strategic locations to validate our approach. Moreover, we use the Grey Wolf Optimizer (GWO) to find control parameters through a reliable fitness function that leads to high-performance microgrids. Finally, we conceive several tests to assess the efficacy of GWO for tuning the hybrid controller and compare the resulting data across distinct realistic operation conditions representing power quality events. So, we choose four case studies considering different renewable energy penetration indexes and power factors and evaluate the effects of the MGs over the distribution grid. We also compare the proposed hybrid PR+LQR controller against closely-related alternatives from the literature and validate its robustness and stability through the disk margin approach and the Nyquist criterion. Our numerical simulations prove that hybrid controllers driven by GWO are highly reliable strategies, yielding an average unbalanced current reduction of 30.03%.

Keywords

• Grey Wolf Optimizer
• Microgrid
• IEEE test distribution network
• Resonant controller
• Unbalanced loads