Application of Synchrosqueezed Wavelet Transforms for Extraction of the Oscillatory Parameters of Subsynchronous Oscillation in Power Systems

The most classical subsynchronous oscillation (SSO) mode extraction methods have some shortcomings, such as lower mode identification and poor anti-noise properties. Thus, this paper proposes a new time-frequency analysis method, namely, synchrosqueezed wavelet transforms (SWT). SWT combines the adv...

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Main Authors: Yan Zhao, Haohan Cui, Hong Huo, Yonghui Nie
Format: Article
Language:English
Published: MDPI AG 2018-06-01
Series:Energies
Subjects:
Online Access:http://www.mdpi.com/1996-1073/11/6/1525
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spelling doaj-d089744540614b939781fbe76ddd74a02020-11-24T21:35:14ZengMDPI AGEnergies1996-10732018-06-01116152510.3390/en11061525en11061525Application of Synchrosqueezed Wavelet Transforms for Extraction of the Oscillatory Parameters of Subsynchronous Oscillation in Power SystemsYan Zhao0Haohan Cui1Hong Huo2Yonghui Nie3School of Power Transmission and Distribution Technology, Northeast Electric Power University, Jilin 132012, ChinaSchool of Electrical Engineering, Northeast Electric Power University, Jilin 132012, ChinaSchool of Electrical Engineering, Northeast Electric Power University, Jilin 132012, ChinaAcademic Administration Office, Northeast Electric Power University, Jilin 132012, ChinaThe most classical subsynchronous oscillation (SSO) mode extraction methods have some shortcomings, such as lower mode identification and poor anti-noise properties. Thus, this paper proposes a new time-frequency analysis method, namely, synchrosqueezed wavelet transforms (SWT). SWT combines the advantages of empirical mode decomposition (EMD) and wavelet, which has the adaptability of EMD, and improve the ability of anti-mode mixing on EMD and wavelet. Thus, better anti-noise property and higher mode identification can be achieved. Firstly, the SSO signal is transformed by SWT and its time-frequency spectrum is obtained. Secondly, the attenuation characteristic of each intrinsic mode type (IMT) component in its time-frequency spectrum is analyzed by an automatic identification algorithm, and determine which IMT component needs reconstruction. After that, the selected IMT components with divergent characteristic are reconstructed. Thirdly, high-accuracy detection for mode parameter identification is achieved by the Hilbert transform (HT). Simulation and application examples prove the effectiveness of the proposed method.http://www.mdpi.com/1996-1073/11/6/1525subsynchronous oscillation (SSO)time-frequency analysissynchrosqueezed wavelet transforms (SWT)Hilbert transform (HT)
collection DOAJ
language English
format Article
sources DOAJ
author Yan Zhao
Haohan Cui
Hong Huo
Yonghui Nie
spellingShingle Yan Zhao
Haohan Cui
Hong Huo
Yonghui Nie
Application of Synchrosqueezed Wavelet Transforms for Extraction of the Oscillatory Parameters of Subsynchronous Oscillation in Power Systems
Energies
subsynchronous oscillation (SSO)
time-frequency analysis
synchrosqueezed wavelet transforms (SWT)
Hilbert transform (HT)
author_facet Yan Zhao
Haohan Cui
Hong Huo
Yonghui Nie
author_sort Yan Zhao
title Application of Synchrosqueezed Wavelet Transforms for Extraction of the Oscillatory Parameters of Subsynchronous Oscillation in Power Systems
title_short Application of Synchrosqueezed Wavelet Transforms for Extraction of the Oscillatory Parameters of Subsynchronous Oscillation in Power Systems
title_full Application of Synchrosqueezed Wavelet Transforms for Extraction of the Oscillatory Parameters of Subsynchronous Oscillation in Power Systems
title_fullStr Application of Synchrosqueezed Wavelet Transforms for Extraction of the Oscillatory Parameters of Subsynchronous Oscillation in Power Systems
title_full_unstemmed Application of Synchrosqueezed Wavelet Transforms for Extraction of the Oscillatory Parameters of Subsynchronous Oscillation in Power Systems
title_sort application of synchrosqueezed wavelet transforms for extraction of the oscillatory parameters of subsynchronous oscillation in power systems
publisher MDPI AG
series Energies
issn 1996-1073
publishDate 2018-06-01
description The most classical subsynchronous oscillation (SSO) mode extraction methods have some shortcomings, such as lower mode identification and poor anti-noise properties. Thus, this paper proposes a new time-frequency analysis method, namely, synchrosqueezed wavelet transforms (SWT). SWT combines the advantages of empirical mode decomposition (EMD) and wavelet, which has the adaptability of EMD, and improve the ability of anti-mode mixing on EMD and wavelet. Thus, better anti-noise property and higher mode identification can be achieved. Firstly, the SSO signal is transformed by SWT and its time-frequency spectrum is obtained. Secondly, the attenuation characteristic of each intrinsic mode type (IMT) component in its time-frequency spectrum is analyzed by an automatic identification algorithm, and determine which IMT component needs reconstruction. After that, the selected IMT components with divergent characteristic are reconstructed. Thirdly, high-accuracy detection for mode parameter identification is achieved by the Hilbert transform (HT). Simulation and application examples prove the effectiveness of the proposed method.
topic subsynchronous oscillation (SSO)
time-frequency analysis
synchrosqueezed wavelet transforms (SWT)
Hilbert transform (HT)
url http://www.mdpi.com/1996-1073/11/6/1525
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AT honghuo applicationofsynchrosqueezedwavelettransformsforextractionoftheoscillatoryparametersofsubsynchronousoscillationinpowersystems
AT yonghuinie applicationofsynchrosqueezedwavelettransformsforextractionoftheoscillatoryparametersofsubsynchronousoscillationinpowersystems
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