This research enhances automatic generation control (AGC) within interlinked power systems (IPS), which is critical for ensuring power grid stability and efficiency. However, challenges such as dynamic load variations, system nonlinearities, and diverse power sources can limit its effectiveness. To address these issues, a proportional-derivative–proportional-integral (PD-PI) cascade controller (CC), optimized by the fire Hawk optimizer (FHO), is proposed and tested across three systems to evaluate their efficacy in solving AGC problems. FHO is utilized in AGC investigations as a novel application, revealing further research gaps that require attention. FHO is inspired by the foraging strategies of whistling kites, brown falcons, and black kites, which use fire-starting techniques to capture prey. The proposed FHO: PD-PI CC is evaluated using the integral time multiplied absolute error (ITAE) metric. The robustness of the closed-loop system is assessed through sensitivity analysis in response to various step load changes (SLC) in a two-area non-reheat thermal IPS, both with and without governor dead band nonlinearity. The comprehensive applicability method is demonstrated through an examination of various power plant models, including reheat, hydro, and gas units with distinct SLC under a high-voltage direct current link. The proposed FHO: PD-PI CC scheme's performance surpasses alternative controller schemes, including HHO: PD-PI, HBFO-PSO: PI, TLBO: PID, ISFS: PID, IGWO: PID, DE: PID, and CPSO: PI, in terms of objective values and settling times. In the three systems analyzed, the FHO: PD-PI demonstrates lower ITAE quantities compared to the HHO: PD-PI, with improvements of 74.4%, 4.5%, and 5.7%, respectively. The results highlight the proposed approach’s effectiveness in improving AGC performance and its feasibility for practical application.
