<p>This study explores a decentralized control scheme for load frequency control (LFC) in a three-area interconnected power system, focusing on dynamic performance enhancement through advanced control techniques. The system comprises three diverse power generation units: reheat thermal power plant, nuclear power plant, and wind turbine power plant. The proposed approach leverages a hybrid controller designed using metaheuristic optimization techniques that are Bayesian optimization (BO), ant colony optimization (ACO), and wild horse optimization (WHO). The proposed controller optimizes key parameters of the LFC system, ensuring effective frequency regulation while addressing the unique dynamics of each generation unit. The hybrid controller adapts to system disturbances, load changes, and renewable energy variability ensuring minimal frequency deviations and maintaining inter-area power balance. The study explores various modern control techniques and compares their effectiveness in stabilizing the three-area power system. Metaheuristic algorithms like BO, ACO, and WHO are advantageous due to their ability to navigate complex optimization landscapes and converge on global optima. Simulation results demonstrate superior performance of the hybrid controller in terms of frequency stabilization, reduced settling times, reducing peak time, reduced rise time, and minimal overshoot compared to conventional and standalone metaheuristic controllers. The research highlights the potential of hybrid metaheuristic controllers in advancing LFC for multi-area power systems, ensuring scalability and resilience making it suitable for modern and future energy grids. The findings provide valuable insights into the design of reliable LFC strategies offering a robust framework for addressing frequency control challenges in interconnected systems with diverse power generation sources.</p>