The existence of low-frequency oscillations in power systems is the cause of power angle instability, limiting the transmission of maximum tie-line power. One of the effective ways to improve the stability limits is by installing a power system stabilizer and supplementary excitation control to augment with an automatic voltage regulator (AVR) supplemental feedback stabilizing signal. This paper proposes a new strategy for simultaneously tuning the power system stabilizer (PSS) and FACTS controller, considering time delays. The design of the proposed controller is modeled as an optimization problem, and the parameters of the controller are optimized through the grasshopper optimization algorithm (GOA). The suggested controller’s efficacy is evaluated for both single-machine infinite bus systems and multi-machine power systems under various disturbances. It also investigated the performance of the proposed controller with variations in signal transmission delays. The results obtained from GOA optimized proposed controller are compared with those obtained from the differential evolution algorithm, genetic algorithm, and whale optimization algorithm. In this context, the proposed GOA optimized controller reduced the objective function value by 16.32%, 14.56%, and 13.72%, respectively, in the SMIB system and 1.41%, 9.98%, and 13.31%, respectively, for the multi-machine system compared with the recently published WOA, and the well-established GA and DE. Further, the proposed controller is found to be stable and effectively increases stability even under small disturbances.

Frequency stability is one of the major challenges in renewable energy source-based microgrids. This issue can be resolved by employing virtual inertia control that helps in improving damping properties and stability. In applying this control method, a phase-locked loop (PLL) is used to acquire the assessment of the frequency data of the microgrid. Nonetheless, the application of PLL in microgrids produces larger frequency oscillation due to its system dynamics. To solve such issues, we propose a robust Interval Type-2 Fuzzy Logic PID Controller (IT2FPID) for the virtual inertia control to limit the unwanted frequency measurement impacts while simultaneously improving the microgrid system stability. Further, a novel improved parasitism predation algorithm (IPPA) algorithm is proposed to tune the controller parameters. The performance of our proposed solutions is studied by comparing the simulation results with a few standard techniques considering the change in system parameters and different paces of renewable energy source penetration.