Abstract
Due to the highly increasing integration of renewable energy sources with the power grid and their fluctuations, besides the recent growth of new power electronics equipment, the noise in power systems has become colored. The colored noise affects the methodologies for power quality parameters’ estimation, such as harmonic and interharmonic components. Estimation of signal parameters via rotational invariance techniques (ESPRIT) as a parametric technique with high resolution has proven its efficiency in the estimation of power signal components’ frequencies, amplitudes, and phases for quality analysis, under the assumption of white Gaussian noise. Since ESPRIT suffers from high computational effort, filter bank ESPRIT (FB-ESPRIT) was suggested for mitigation of the complexity. This manuscript suggests FB-ESPRIT as well for accurate and robust estimation of power signal components’ parameters in the presence of the colored noise. Even though the parametric techniques depend on the Gaussianity of contaminating noise to perform properly, FB-ESPRIT performs well in colored noise. The FB-ESPRIT superiority compared with the conventional ESPRIT and MUSIC techniques was demonstrated through many simulations runs on synthetic power signals with multiple harmonics, interharmonics, and subharmonic components in the presence of noises of different colors and different SNR levels. FB-ESPRIT had a significant efficiency superiority in power quality analysis with a wide gap distance from the other estimators, especially under the high level of colored noise.
Highlights
Electrical power quality (EPQ) analysis [1,2] considerably assists power system planners and designers in hybrid energy storage loss mitigation [3], renewable energy monitoring [4,5], observing the disturbances in power quality [6], proper connection of electric vehicles to the grid [7], etc
The estimation of signal parameters via rotational invariance technique (ESPRIT) is a parametric spectrum estimation methodology introduced by Roy et al [17,18,19]
Considering the above-mentioned evaluation for the 60 Hz fundamental component estimation, FB-ESPRIT indicated a superior estimation of frequency, amplitude, and phase parameters for the signal s1 (t) contaminated with colored noise when compared to the technique ESPRIT
Summary
Electrical power quality (EPQ) analysis [1,2] considerably assists power system planners and designers in hybrid energy storage loss mitigation [3], renewable energy monitoring [4,5], observing the disturbances in power quality [6], proper connection of electric vehicles to the grid [7], etc. As a subspace-based parametric method, ESPRIT heavily relies on the assumption of the whiteness of any contaminating noise, and its estimation efficiency is degraded when the signal components are contaminated with colored noise [36]. The work in [37] overcame its complexity by the association of ESPRIT with a filter bank (FB-ESPRIT) This manuscript demonstrates that the association of the filter bank mitigates the complexity of ESPRIT, and results in higher efficiency in the parameters’ estimation of a signal contaminated by different types of colored noise (pink, red, blue, and violet).
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