Improving frequency and voltage performance in interconnected microgrids using virtual inertial control

Frequency and voltage deviations are the two serious challenges in microgrids (MGs) caused by load changes and the integration of renewable energies. These challenges are significantly more pronounced in MGs compared to traditional power systems, as MGs possess considerably less inertia. Load frequency control (LFC) and automatic voltage regulator (AVR) strategies are tasked with maintaining frequency and voltage within acceptable limits, respectively. A promising solution to the inertia challenge in MGs is the implementation of the virtual inertial control (VIC) technique. This paper aims to explore the impact of VIC on the simultaneously control of frequency and voltage in MGs under various disturbances, including load oscillations. To achieve this, two island MGs connected via a tie-line are utilized as the test system. The PID controller is employed in the LFC, AVR, and VIC loops. To optimize the control parameters of these controllers, the quantum version of teaching–learning based optimization (quantum TLBO) is applied. The outcomes of the proposed method are compared with those of TLBO, whale optimization algorithm (WOA), grey wolf optimization (GWO), differential evolution (DE), and RCGA to assess the effectiveness of the proposed method. To evaluate the performance of the proposed method, a sensitivity analysis is conducted. Additionally, a real-time hardware-in-the-loop (HIL) simulator, known as the OPAL-RT OP4510, is employed to practically verify the simulation results. The simulation results demonstrate the significant influence of VIC on the performance of LFC-AVR in MGs.