Enhanced parameter optimization of PID controller for single area power system using hybrid ALO-GBO algorithm

This paper focuses on applying two evolutionary algorithms, Ant Lion Optimization (ALO) and Gradient-based Optimization (GBO), to enhance load frequency control (LFC) in a power system. LFC is crucial for stable power operation, but traditional methods struggle with system complexity and uncertainties. ALO mimics lion hunting behavior, while GBO uses gradients for optimization. Both are known for tackling complex problems. The study implements these algorithms in a single-area power system model, tuning controller parameters to minimize frequency deviations and improving the performance. This paper includes mathematical modeling, algorithm implementation, and result analysis to show how hybrid of both ALO and GBO algorithm improve stability and performance as compared to traditional methods.