Smart virtual rotor for frequency stability enhancement considering inverter-based renewable energy sources

Abstract

This paper proposes a novel smart virtual rotor controller (VRC) that combines the Bat Algorithm (BA) with extreme learning machine (ELM) to enhance frequency stability in power systems. To reflect the impact of renewable integration, inverter-based power plants are incorporated to simulate high levels of penetration from power-electronics-based generation. The proposed method first tunes the virtual rotor parameters (virtual inertia and damping control) using BA under varying operating conditions. These parameters are then trained with ELM to enable adaptive control across different scenarios. Time-domain simulations demonstrate that the proposed approach outperforms existing methods in terms of frequency nadir and settling time, while also achieving a significant reduction in execution time, requiring only 0.0033 seconds.