Performance evaluation of differential evolution algorithm on automatic generation control

In this paper load frequency control of two area interconnected power system with classical controller is considered. The optimum gains of PI controller is optimized using genetic algorithm (GA), bacterial foraging optimization algorithm (BFOA), particle swarm optimization (PSO) and differential evolution (DE) algorithm. The results of all the heuristic optimization algorithms are compared. Investigations are carried out considering step load change in one area and simultaneously both areas. Investigations reveal that proposed DE algorithm performs better compared to other techniques. To show the superiority of proposed controller, size of step load perturbation is varied and dynamic performances are studied.