The paper presents a technique based on the use of single-variable Kalman filters (KFs) to track the frequency variation of signal components in multifrequency phasor analysis. KF-based tracking is employed for accurate frequency estimation of both harmonic and inter-harmonic components in a Compressive Sensing Taylor Fourier Multifrequency (CSTFM) algorithm. This novel approach improves robustness of the CSTFM method to the effects of spectral interference among harmonic and interharmonic components, allowing better estimates of each component and extending the range of application beyond pure phasor measurement unit (PMU) devices. Computational efficiency compared to a plain CSTFM algorithm is also enhanced. Significant case studies, with signals including timevarying harmonic and interharmonic components, are analyzed and discussed with regards, in particular, to frequency estimation. Moreover, it is shown that intermittent components can be handled without loss of accuracy by KF-based tracking features.
Frequency tracking for efficient phasor measurement based on a CSTFM model
BERTOCCO, MATTEO;FRIGO, GUGLIELMO;GIORGI, GIADA;NARDUZZI, CLAUDIO
2015
Abstract
The paper presents a technique based on the use of single-variable Kalman filters (KFs) to track the frequency variation of signal components in multifrequency phasor analysis. KF-based tracking is employed for accurate frequency estimation of both harmonic and inter-harmonic components in a Compressive Sensing Taylor Fourier Multifrequency (CSTFM) algorithm. This novel approach improves robustness of the CSTFM method to the effects of spectral interference among harmonic and interharmonic components, allowing better estimates of each component and extending the range of application beyond pure phasor measurement unit (PMU) devices. Computational efficiency compared to a plain CSTFM algorithm is also enhanced. Significant case studies, with signals including timevarying harmonic and interharmonic components, are analyzed and discussed with regards, in particular, to frequency estimation. Moreover, it is shown that intermittent components can be handled without loss of accuracy by KF-based tracking features.Pubblicazioni consigliate
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