Enhanced Frequency Control in Power Systems Using a Novel Meerkat Optimization Algorithm

Abstract

Frequency regulation in power systems remains a significant challenge due to inherent nonlinearities and dynamic load variations. This paper introduces a novel adaptive control strategy that integrates state feedback with the Meerkat Optimization Algorithm (MOA) to enhance frequency stability and minimize power imbalances. The proposed approach explicitly incorporates nonlinear constraints-such as governor saturation and power quality disturbances-within a multi-objective optimization framework to strategically position the closed-loop system poles for improved transient response and robustness. Furthermore, fuzzy logic is integrated into the MOA to dynamically tune control parameters in real time, thereby addressing system parameter variations and operational constraints. Numerical simulations on both a two-area power system with nonlinear governor constraints and the New England 39-bus test system demonstrate that the proposed MOA-based controller significantly outperforms conventional Proportional-Integral (PI) controllers as well as other recent optimization methods. Notable improvements include reductions in settling time and peak overshoot of up to 35% and 20%, respectively, underscoring the efficacy of the proposed approach in achieving superior frequency regulation under realistic operating conditions.