An improved parasitism predation algorithm for frequency regulation of a virtual inertia control based AC microgrid

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.