  This work proposes the adoption of Enhanced Gradient-Based Optimizer (EGBO)
as a new approach to the Load Frequency Control (LFC) problem in a two-area
interconnected power system. The importance of determining the optimal
parameters for the controllers for the LFC problem cannot be overstated, and
the fact that estimating these parameters require complex and nonlinear
computations makes the optimization procedure even more unique and challenging.
Consequently, application of an efficient optimization algorithm to
successfully attain optimal controller parameters is critical. To accomplish
this task, the proposed EGBO algorithm is compared to the fundamental
Gradient-Based Optimizer (GBO), Chimp Optimization Algorithm (ChOA), Sine
Cosine Algorithm (SCA), Grey Wolf Optimization (GWO), and Particle Swarm
Optimization (PSO) for optimizing an Integral-Time-multiplied-Absolute-Error
(ITAE) based objective function. The relevant findings show that the EGBO
algorithm is competitively superior in terms of resilience, precision, and
latency when compared to other optimization methods. Lastly, the statistical
comparison further strengthens the outcome of the study.
