AGC parameters optimization using real coded genetic algorithm

A real coded genetic algorithm (RCGA) for parameter optimization of multiarea automatic generating control (AGC) has been proposed. Instead of using a traditional analysis algorithm to obtain the controller parameters, GA optimization technology is introduced and the MATLAB Simulink model is designed as an AGC parameter optimization tool to deal with the interconnection of the AGC loops. Utilizing GA´s parallel strings searching in many peaks, the multi variable optimization of multiarea power systems AGC is processed quickly. The nonlinear objects such as generation rate constraint (GRC) and deadband of the turbine governor are treated easily by combination of GA with Simulink. The simulation of a two-area power systems with PID controllers is reported and the results are reasonable.