Design of an Intelligent Controller Based on Wavelet Neural Network to Improve the Stability of Power Systems

Abstract

To damp the oscillations in a power system, a new intelligent controller is proposed. This controller is an online trained wavelet neural network controller (OTWNNC) in which adaptive learning rates derived by the Lyapunov stability are employed to guarantee the convergence of the proposed controller. During the online control process, the identification of system is not necessary, because of learning ability of the proposed controller. One of the proposed controller features is robustness to different operating conditions and disturbances. Moreover, the Prony method is used to obtain the exponential damping of power system oscillations in this paper. The test power system is a two-area four-machine system power. The simulation results show that the oscillations are satisfactorily damped out by the OTWNNC.