Adaptive Fourier Decomposition-Based Unified Phasor and Waveform Measurement Method for Power System Signals

Frequency-domain phasor and time-domain waveform measurements are fundamental techniques in power systems, with the former applied to non-transient conditions and the latter to transient processes where phasor representation becomes inadequate. Synchrophasor measurement relies on Fourier transforms, whereas waveform measurement depends on data compression. The absence of a unified mathematical foundation between these methods hinders seamless technical integration and increases operational costs due to discrete measurement techniques. This study proposes an adaptive Fourier decomposition (AFD) algorithm based on the Takenaka-Malmquist (TM) system for measuring transient and steady-state signals in power systems. A power signal representation model is developed using the TM system, analogous to conventional Fourier-based models, and its mathematical foundation is established. A unified phasor-waveform measurement framework is introduced, leveraging traditional phasors during non-electromagnetic transient periods and TM phasors during electromagnetic transient periods. The characteristics of TM phasors are examined across various scenarios, and the influence of AFD parameters is analyzed, leading to a unified synchrophasor-waveform measurement method that integrates time- and frequency-domain measurement approaches. Extensive testing, encompassing IEC/IEEE 60255-118-1 standard signals and field fault recording signals, validates that the proposed method meets P-class PMU requirements with tenfold accuracy in most cases and yields the lowest waveform reconstruction root mean square error across diverse transient conditions.

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Publication Details

Journal
IEEE Transactions on Instrumentation and Measurement
Published
2025-01-01
DOI
https://doi.org/10.1109/tim.2025.3573002
Primary Topic
Smart Grid and Power Systems
Type
article
Field-Weighted Citation Impact
0.00

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article

Adaptive Fourier Decomposition-Based Unified Phasor and Waveform Measurement Method for Power System Signals

Tianshu Bi, Boyu Zhao, Hao Liu
IEEE Transactions on Instrumentation and Measurement
Smart Grid and Power Systems
article

Adaptive Fourier Decomposition-Based Unified Phasor and Waveform Measurement Method for Power System Signals

Tianshu Bi, Boyu Zhao, Hao Liu
article en

Abstract

Frequency-domain phasor and time-domain waveform measurements are fundamental techniques in power systems, with the former applied to non-transient conditions and the latter to transient processes where phasor representation becomes inadequate. Synchrophasor measurement relies on Fourier transforms, whereas waveform measurement depends on data compression. The absence of a unified mathematical foundation between these methods hinders seamless technical integration and increases operational costs due to discrete measurement techniques. This study proposes an adaptive Fourier decomposition (AFD) algorithm based on the Takenaka-Malmquist (TM) system for measuring transient and steady-state signals in power systems. A power signal representation model is developed using the TM system, analogous to conventional Fourier-based models, and its mathematical foundation is established. A unified phasor-waveform measurement framework is introduced, leveraging traditional phasors during non-electromagnetic transient periods and TM phasors during electromagnetic transient periods. The characteristics of TM phasors are examined across various scenarios, and the influence of AFD parameters is analyzed, leading to a unified synchrophasor-waveform measurement method that integrates time- and frequency-domain measurement approaches. Extensive testing, encompassing IEC/IEEE 60255-118-1 standard signals and field fault recording signals, validates that the proposed method meets P-class PMU requirements with tenfold accuracy in most cases and yields the lowest waveform reconstruction root mean square error across diverse transient conditions.

IEEE Transactions on Instrumentation and MeasurementVol. 74
North China Electric Power University (CN)
National Natural Science Foundation of China
Affordable and clean energy
Openalex Percentile: Top 91%
Smart Grid and Power Systems
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