The primary goal of load frequency control is to preserve the target output power while keeping the frequency constant regardless of the load’s change. Due to its widespread availability and widespread use, the integrated controller is the subject of this paper’s description of the ideal load frequency control for a two-area linked power system. In order to get the optimum dynamic performance, the controller’s parameters were designed using three techniques: Particle Swarm Optimization (PSO), Genetic Algorithm (GA), and Adaptive neuro fuzzy inference system (ANFIS). The investigation focuses on how altering the frequency bias impacts the system’s dynamic performance. The PSO algorithm has quickly risen to prominence as a leading swarm intelligence strategy and evolutionary computing technique. While PSO methods have numerous advantages, they also carry the risk of local optimum trapping owing to too early convergence, among other potential drawbacks. PID settings are improved via GA and ANFIS-style approaches. After MATLAB-Simulink examination, ANFIS operates GA and PSO on all key measures and the proposed technique is efficient.