Optimal Control Design for Power System Stabilizers and Virtual Inertia Control using Grey Wolf Optimization

Power system stability is a critical challenge in modern power grids, especially with the increasing penetration of Renewable Energy Sources (RES) and reduced system inertia. To address this problem, effective tuning of Power System Stabilizers (PSS) and Virtual Inertia Control (VIC) is essential for enhancing dynamic stability. This research proposes an optimal control approach for tuning PSS and VIC parameters using Grey Wolf Optimization (GWO) algorithm. The Photovoltaic (PV) generation reduces the inertia in the system and causes challenges in frequency stability. Flywheel Energy Storage (FESS) is employed to emulate the Virtual Inertia. The optimal parameters of PSS and VIC are achieved using GWO by minimizing the Integral Time Absolute Error (ITAE) as an objective function. The results obtained after simulation conclude that PSS and VIC together provide the most effective solution to damp Frequency Oscillation (LFO) compared to using either PSS or VIC alone. Its effectiveness is validated in both low and high inertia conditions. The combination of PSS-VIC in high inertia systems has minimized the maximum deviation by 84.65%, improved the frequency nadir by 62.61%, and reduced the settling time by 0.457 s. Additionally, the rotor angle deviation improved by 99.98%, with a settling time reduction of 0.489 s.