Harmonic estimation methods in power systems and theirs performance analysis

In modern power systems, power quality problems have occurred with increase of non-linear loads, power electronics components and circuits. Harmonics are the fundamental factors that affect power quality. Therefore, it is significantly important to detect measure, estimate and suppress harmonics. Many different methods have been developed for measurement and estimation of harmonics. In this study, several techniques (Fourier transform, Hilbert-Huang transform, discrete Hartley transform, Chirp z-transform, multiple signal classification method, Prony's method, Kalman filtering, gradient descent-based adaptive filters) were researched comprehensively, their mathematical backgrounds were examined and classified according to its principles. Harmonic estimation application was realized in MATLAB with combining presented methods In addition, the methods examined were tested according to power quality parameters and compared for performance evaluation. It was detected that Hartley Transform, Hilbert-Huang Transform and multiple signal classification methods were affected by changes in input signals. Furthermore, amplitude and frequency estimation were carried out with Hilbert Huang transform Prony and multiple signal classification methods while amplitude and phase estimation were realized with Chirp-z Transform, gradient descent based adaptive filters and Kalman filters. It was observed that error rate was approximately zero in Hilbert-Huang Transform and Prony method. In addition, performance evaluation was made in case of voltage sag, voltage swell, harmonic distortion, voltage interruption, DC offset, addition of noise component.