An optimal artificial neural network controller for load frequency control of a four-area interconnected power system

In this paper, an optimal artificial neural network (ANN) controller for load frequency control (LFC) of a four-area interconnected power system with non-linearity is presented. A feed forward multi-layers and Bayesian regularization backpropagation (BRB) training function used. This designed on the basis theory to overcome problem as changes in system. The comprised transfer models twothermal units, one nuclear unit hydro unit. model developed by considering generation rate constraint (GRC) different units non-linearity. typical parameters obtained from IEEE press engineering series EPRI books. robustness, effectiveness, performance proposed ANN step change random simulated through using MATLAB-Simulink. time response characteristics are compared that proportional, integral derivative (PID) non-linear autoregressive-moving average (NARMA-L2) controller. results show algorithm has superiority accuracy other two controllers.