Power quality evaluation using advanced spectrum estimation methods

The authors show that the use of high-resolution spectrum estimation methods instead of Fourier-based techniques can improve the accuracy of measurement of spectral parameters of distorted waveforms encountered in power systems, in particular the estimation of the power quality indices (such as inter/harmonic groups and subgroups) . The comparison of the frequency and amplitude estimation error, based on numerical simulations is presented. Presentation of selected power quality indices is then followed by comparison of estimation error in the case of application of FFT-based algorithms and parametric methods. Investigated waveforms are typical for dc arc furnace plant. MUSIC and ESPRIT high-resolution methods are used to analyze waveforms in a supply system of a DC arc furnace. Reduction of variance of results is achieved by using robust averaging procedure (winsorized mean)