Kalman filter for identification of power system fuzzy harmonic components

The ability to estimate the harmonic components in a power system is necessary for delivering a high quality power to the end user. This paper proposes a new approach for identifying harmonic components in a power system based on treating the non-fundamental sinusoid voltage or current waveform as a fuzzy noise having a linear model. The parameters of this model are assumed to be fuzzy numbers with a membership function that has central and spread values. Kalman filter is used for identifying the center and spread of each coefficient. It is assumed that the distortion of the sinusoid waveform is due to noise and/or undesired sinusoidal components with different frequencies. Kalman filter filters the noise, the undesired components will be estimated as a spread in the membership functions of the coefficients. Numerical examples are presented to illustrate the effectiveness of this technique.