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The rapid integration of wind and solar energy sources into modern power systems has exacerbated frequency regulation challenges due to increased variability, uncertainty, and reduced system inertia. Traditional Proportional-Integral-Derivative controllers often exhibit poor tuning and limited adaptability, resulting in frequency oscillations and potential instability under fluctuating load and generation conditions. To address these limitations, this study proposes a Fractional Order Proportional-Integral-Derivative (FOPID) controller optimised via three metaheuristic algorithms–Particle Swarm Optimization, Genetic Algorithm, and Teaching-Learning-Based Optimization. Simulation results show that FOPID controllers significantly enhance load frequency control compared to their conventional PID counterparts. Among the optimisation methods, the TLBO-optimised FOPID achieved the lowest Integral Time Absolute Error, with an overshoot of 0.7295 Hz and an undershoot of −0.163 Hz. Notably, it attained an ITAE of 0.7497, outperforming the 2.7594 observed in PSO-optimised PID controllers. In addition this paper provides a comprehensive review of robust and metaheuristic-based LFC techniques for RE-integrated power systems. These findings illustrate that metaheuristically tuned FOPID controllers offer superior adaptability, robustness, and efficiency for load frequency control in renewable energy–integrated power systems, thereby highlighting the importance of advanced control strategies in maintaining grid stability amidst escalating renewable penetration.
Pandey et al. (Sun,) studied this question.