Power Measurement Using Stockwell Transform

The spread of harmonics in electric power systems causes deviations in voltage and current waveforms from the ideal sinusoidal form and, consequently, the traditional power calculation is unsuitable. One of the power theories defined for non-sinusoidal conditions is the IEEE Standard 1459-2010, base...

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Bibliographic Details
Published in:IEEE transactions on power delivery 2021-10, Vol.36 (5), p.3091-3100
Main Authors: Coelho, Rodrigo de Almeida, Brito, Nubia Silva Dantas
Format: Article
Language:English
Subjects:
Discrete wavelet transforms
Electric power systems
Fourier transforms
Harmonic analysis
harmonic distortion
IEEE Standards
Linear circuits
non-sinusoidal systems
Power measurement
power quality
Power system harmonics
Sine waves
Stockwell transform
Time-frequency analysis
Waveforms
Wavelet transforms
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Summary:The spread of harmonics in electric power systems causes deviations in voltage and current waveforms from the ideal sinusoidal form and, consequently, the traditional power calculation is unsuitable. One of the power theories defined for non-sinusoidal conditions is the IEEE Standard 1459-2010, based on Fourier Transform (FT). However, when applied to non-stationary signals, the FT leads to miscalculation due to spectral leakage, being unsuitable for non-stationary waveforms. In this paper, a new approach for the IEEE Standard 1459-2010 definitions is proposed using Stockwell Transform (ST). The ST provides a time-frequency resolution which retains magnitude and phase information of signals over time. The performance of the proposed method was evaluated in three scenarios including stationary waveforms, a non-linear circuit, and real measured data. The results were compared to the IEEE Standard 1459-2010 using the FT and the Stationary Discrete Wavelet Packet Transform (SDWPT) approaches. In the three scenarios studied, the proposed method presented a good estimation for each quantity defined in IEEE Standard 1459-2010 and provided more accurate results than FT-based and SDWPT-based methods.
ISSN:0885-8977
1937-4208
DOI:10.1109/TPWRD.2020.3033403