This work uses Particle Swarm Optimization (PSO) search techniques based on proportional integral derivative (PID), proportional integral (PI), and proportional derivative (PD) to determine how to optimize a nonlinear Automatic PI, and PD to determine how to optimize a nonlinear Automatic Generation Control (AGC)’s parameters. Conventional energy sources are used in the multi-area power system model with multiple generation sources in various combinations to balance the system’s load and generation demand. The suggested algorithm is first applied to two areas that have interconnected hydro-thermal and non-reheat thermal power systems with multiple sources. Subsequently, further research was extended to three areas with multi-source power systems as then: (i) area 1 with multi-units non-reheat thermal, (ii) area 2 with multi-sources system having non-reheat, reheat thermal power systems, (iii) area 3 with multi-sources system having reheat thermal, hydropower systems for more thorough verification of the suggested algorithm’s efficacy. Using a fitness function with PID, PI, PD based on integral time multiplied absolute error (ITAE), the PSO algorithm optimizes the gains of the controller. According to simulation results, PSO for multi-areas with multi source power systems that have been trained with the aforementioned algorithms has good adjustment capability and sustainable effectiveness.