Frequency estimation of power system signals with chaotic oscillations using music and esprit algorithms

Chaotic ferroresonance is one of the disturbances of a power system, which may cause chaotic oscillations with over voltages and over currents. In order to protect system and keep it stable the frequency estimation should be fulfilled accurately. In this study first chaotic oscillations of ferroresonance are modeled with forced Duffing oscillator's dynamical equations. MUSIC (Multiple Signal Classification) and ESPRIT (Estimation of Parameters by Rotationally Invariant Technique) methods are proposed for frequency estimation of chaotically distorted power system signals. Frequency is estimated efficiently by using the MUSIC and ESPRIT methods. Finally, computer simulations have been carried out for the performance analysis of the proposed methods and the comparison results of the proposed methods based on the SNR (Signal to noise ratio) values are given.