OPTIMIZED LOAD FREQUENCY CONTROL OF A SOLAR PV-INTEGRATED TWO-AREA INTERCONNECTED POWER SYSTEM USING A HYBRID BROWN BEAR–GREY WOLF OPTIMIZATION ALGORITHM

Abstract

Higher solar PV penetration poses frequency regulation issues since inverter-interfaced PV generation offers minimal inherent inertia and governor response, while fast variations of PV add another disturbance to the grid. In this study, a two-stage LFC scheme for a two-area power system with PV integration is designed, differentiating optimization issues from controller structure issues. In the first stage, an area control error-based PID controller is designed using Hybrid Brown Bear-Grey Wolf Optimization (BBO-GWO) and is compared against Brown Bear Optimization, Political Optimizer, Grey Wolf Optimization, particle swarm optimization, and genetic algorithm. Thirty independent optimization runs, Wilcoxon test, and parameter variation analysis are carried out to evaluate the consistency and robustness of the optimization. In the second stage, the optimized PID is compared against a two-degree-of-freedom PID (2DOF-PID) and a PV-aware 2DOF-PID controller, which takes the measured PV active power as an additional feedforward signal. Using Hybrid BBO-GWO, Area 1 ITAE is reduced by 95.2%, settling time is reduced from 8.26 to 2.34 s relative to trial-and-error PID, and stability under ±20% parameter variation is achieved. While the optimization performance is statistically equivalent to other algorithms, the controller structure gives a higher gain in terms of frequency regulation under PV fluctuation. The hybridization of BBO-GWO–PV awareness based 2DOF-PID controller shows that effective tuning and the use of measured PV-power feedforward significantly enhance frequency regulation in the presence of load and renewables disturbances; it is advisable for future studies to verify the effectiveness of the developed framework on real power system networks.