Tuning of Optimal Classical and Fractional Order PID Parameters forAutomatic Generation Control Based on the Bacterial Swarm Optimization

Particle Swarm Optimization algorithm converges rapidly during the initial stage of a global search, but around global optimum, the search process slows down. In order to overcome this problem and to further enhance the performance of Particle Swarm Optimization, this paper implements a hybrid algorithm, Bacterial Swarm Optimization, combining the features of Bacterial Foraging Optimization and Particle Swarm Optimization. The PID parameters of classical and fractional-order controllers are optimized with Bacterial Swarm Optimization for load frequency control of a two area power system. Simulation results show fractional-order PID controller has less settling time and less overshoot than the classical PID controller for most of studies.