Impact of solid oxide FC-RFB and IPFC on a renewable multi-area power system using combined PI and FOPD controllers optimized by the African Vulture algorithm.

The expanding complexity of modern energy systems and the increasing integration of renewable sources make stable load frequency control (LFC) in interconnected power networks a continuing issue. Traditional controllers, such as proportional-integral (PI), proportional-integral-derivative (PID), and other subordinate control methods, frequently fail to control frequency adequately, especially in multi-source generating systems. Furthermore, standard optimization techniques may exhibit sluggish convergence and inefficient tuning, limiting their usefulness in real-time applications. To address these problems, this study suggest an enhanced LFC framework for a three-area power system that includes thermal-biodiesel (Area-1), thermal (Area-2), and hydro-thermal (Area-3) components. The African Vulture Optimization Algorithm (AVOA) is used to improve a novel PI(FOPD) controller that combines integer-order PI with fractional-order Proportional Derivative (FOPD). According to a comparative investigation, the AVOA-augmented PI(FOPD) controller outperforms conventional I, PI, and PID controllers in terms of transient responsiveness, stability, and convergence. Additionally, AVOA outperforms optimization approaches such as Cuckoo Search, Particle Swarm Optimization, and the Firefly Algorithm. The integration of a Dish-Stirling solar thermal system, a Flexible AC Transmission System (FACTS) device, and an energy storage component improves system robustness. The results show that the AVOA-optimized PI(FOPD) controller greatly enhances LFC performance, making it a promising alternative for current power networks.