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

Yan Zhao, Haohan Cui, Hong Huo and Yonghui Nie
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Yan Zhao: School of Power Transmission and Distribution Technology, Northeast Electric Power University, Jilin 132012, China
Haohan Cui: School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China
Hong Huo: School of Electrical Engineering, Northeast Electric Power University, Jilin 132012, China
Yonghui Nie: Academic Administration Office, Northeast Electric Power University, Jilin 132012, China

Energies, 2018, vol. 11, issue 6, 1-18

Abstract: 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.

Keywords: subsynchronous oscillation (SSO); time-frequency analysis; synchrosqueezed wavelet transforms (SWT); Hilbert transform (HT) (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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