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2020 IEEE Industry Applications Society Annual Meeting by Ma, Yue (author);Huang, Qi (author) is a nonfiction available to read on EtoBox.

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This paper proposes a new method for subsynchronous oscillation (SSO) detection and modal parameter estimation, which utilizes the abundant information contained in signals and the superiority of multisynchrosqueezing transform (MSST) in multi-modal signal time-frequency analysis. Firstly, MSST is used to process the real-time data of the voltage or current collected by the phasor measurement unit (PMU) to obtain the time-frequency spectrum representation of the signal. Non-zero MSST coefficients are used to represent the frequency components of the original signal at each time. Then, for the unknown number of sub-synchronous frequency range components, mean-shift (an unsupervised clustering method) is applied to the non-zero MSST coefficients to determine the number of SSO modes contained in the signal and the mode type to which non-zero MSST coefficients belong. Afterwards, for each detected SSO mode, the corresponding MSST coefficients exceeding the threshold are used to reconstruct the components of the original signal. Finally, the least squares estimation method is used on the reconstructed signal to obtain the parameters of each mode, such as amplitude, phase angle, and damp

Who reads 2020 IEEE Industry Applications Society Annual Meeting?

Author

Ma, Yue (author);Huang, Qi (author)

Publisher

IEEE

Published

2020

Language

EN

Category

nonfiction