Secondary Control Techniques for Frequency Restoration in Microgrids Considering Communication Delays

Microgrids (MGs) offer a sustainable solution for integrating distributed energy resources and allow for independent operation during grid disruptions. Although droop control is widely used for managing power distribution among generation units, it can result in system frequency and voltage deviations. Communication delays within the secondary control system can negatively impact system stability.This study evaluates and compares three secondary control techniques, Proportional-Integral (PI), Fractional-Order Proportional-Integral (FOPI), and Artificial Neural Network (ANN) based controllers, in mitigating frequency deviations in MGs with communication delays. A MATLAB/Simulink-based microgrid model incorporating three voltage source converters (VSCs) is developed to analyze the performance of these controllers under varying conditions. Results demonstrate that ANN-based control significantly outperforms PI and FOPI controllers regarding stability, response time, and robustness to communication delays as ANN controller exhibits lower peak overshoot, faster settling time, and superior adaptability, showing promise for MG secondary control.