Mode Identification of Broad-band Oscillation Signal Based on Improved VMD Method

Lin, Sisi; Liu, Fang; Dreglea, Aliona

doi:10.23919/ccc50068.2020.9188487

Cited by 4 publications

(2 citation statements)

References 14 publications

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“…The analysis of SSOs using time-frequency-domain based methods such as variational mode decomposition (VMD), multi-synchrosqeezing transform, and Taylor Fourier transform is proposed in [8], [16]- [18]. VMD-based methods are proposed in [16], [17]. In [17], a VMD-Hilbert method is used for estimating the parameters of the SSO.…”

Section: Introductionmentioning

confidence: 99%

Empirical Wavelet Transform Based Method for Identification and Analysis of Sub-synchronous Oscillation Modes Using PMU Data

G. Philip,

Jung,

Onen

2024

Journal of Modern Power Systems and Clean Energy

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This paper proposes an empirical wavelet transform (EWT) based method for identification and analysis of sub-synchronous oscillation (SSO) modes in the power system using phasor measurement unit (PMU) data. The phasors from PMUs are preprocessed to check for the presence of oscillations. If the presence is established, the signal is decomposed using EWT and the parameters of the mono-components are estimated through Yoshida algorithm. The superiority of the proposed method is tested using test signals with known parameters and simulated using actual SSO signals from the Hami Power Grid in Northwest China. Results show the effectiveness of the proposed EWT-Yoshida method in detecting the SSO and estimating its parameters.

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Section: Introductionmentioning

confidence: 99%

Empirical Wavelet Transform Based Method for Identification and Analysis of Sub-synchronous Oscillation Modes Using PMU Data

G. Philip,

Jung,

Onen

2024

Journal of Modern Power Systems and Clean Energy

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“…Renewable energy sources are connected to the power grid through power converters, which will make the power system exhibit the characteristics of highly penetrative power electronics. The high penetration of power electronic equipment provides system coupling between the generation side, load side and transmission network in many forms with variable oscillation modes, showing strong time-variability, stochasticity, and strong nonlinearity [1,2]. As a result, the probability of system oscillations caused by power electronic devices will increase significantly.…”

Section: Introductionmentioning

confidence: 99%

An Intelligent Location Method for Power System Oscillation Sources Based on a Digital Twin

Yang,

Wang,

Gao

et al. 2023

Electronics

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Aiming at the difficult problem of broadband oscillation localization in power systems, the intelligent localization method of an oscillation source based on a digital twin is proposed, and the oscillation source localization system is thus constructed. Firstly, a digital twin-based oscillation source localization method and its system architecture are proposed. Furthermore, an intelligent positioning method of the oscillation source, based on data-driven and mechanism fusion, is proposed. It includes three steps: oscillation signal preprocessing, oscillation modal analysis and oscillation source localization. For the oscillation signal preprocessing, the generative adversarial imputation network is used to repair the missing samples, and the super-resolution technique is used to realize the super-resolution measurement of broadband oscillation. In the oscillation modal analysis, the spectrum of the oscillation signal is extracted using the fast Fourier transform. To accurately locate the oscillation source, branch potential energy is used as the input to the data-driven model, such as LSTM and CNN. Finally, an oscillation source localization system is developed based on the digital twin workshop CloudPSS-XStudio, which can locate the oscillation source quickly and accurately.

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Identification of Power System Oscillation Modes Using Empirical Wavelet Transform and Yoshida-Bertecco Algorithm

2022

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Mode Identification of Broad-band Oscillation Signal Based on Improved VMD Method

Cited by 4 publications

References 14 publications

Empirical Wavelet Transform Based Method for Identification and Analysis of Sub-synchronous Oscillation Modes Using PMU Data

Empirical Wavelet Transform Based Method for Identification and Analysis of Sub-synchronous Oscillation Modes Using PMU Data

An Intelligent Location Method for Power System Oscillation Sources Based on a Digital Twin

Identification of Power System Oscillation Modes Using Empirical Wavelet Transform and Yoshida-Bertecco Algorithm

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