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Shetty, D., Prabhu, N.. (1402). Power Spectral Density based Identification of Low frequency ‎Oscillations in Multimachine Power system. سامانه مدیریت نشریات علمی, 11(3), 173-181. doi: 10.22098/joape.2023.10072.1710
D. Shetty; N. Prabhu. "Power Spectral Density based Identification of Low frequency ‎Oscillations in Multimachine Power system". سامانه مدیریت نشریات علمی, 11, 3, 1402, 173-181. doi: 10.22098/joape.2023.10072.1710
Shetty, D., Prabhu, N.. (1402). 'Power Spectral Density based Identification of Low frequency ‎Oscillations in Multimachine Power system', سامانه مدیریت نشریات علمی, 11(3), pp. 173-181. doi: 10.22098/joape.2023.10072.1710
Shetty, D., Prabhu, N.. Power Spectral Density based Identification of Low frequency ‎Oscillations in Multimachine Power system. سامانه مدیریت نشریات علمی, 1402; 11(3): 173-181. doi: 10.22098/joape.2023.10072.1710

Power Spectral Density based Identification of Low frequency ‎Oscillations in Multimachine Power system

Journal of Operation and Automation in Power Engineering
دوره 11، شماره 3، دی 2023، صفحه 173-181    اصل مقاله (1.08 M)
نوع مقاله: Research paper
شناسه دیجیتال (DOI): 10.22098/joape.2023.10072.1710
نویسندگان
D. Shetty؛ N. Prabhu*
Department of Electrical and Electroinics Engineering, NMAM Institute of Technology Nitte, Karkala,India
چکیده
The paper presents a Fast Fourier Transform (FFT) based Power Spectral Density (PSD) filter for denoising the PMU signal received from the smart power system network to identify the low frequency Oscillation modes (LFO). Small disturbances are introduced during normal operation of power system causes low frequency oscillations and may hinder the power system transfer capabilities of a system. The traditional signal processing method cannot extract the information from ambient signals effectively during noisy measurement. In this paper, the performance of the Prony analysis with reduced sampling rate is analysed for the PMU data with noiseless and noise environment. It is observed that, the performance of the Prony approach is not satisfactory under noisy measurement data.  In the present work FFT-PSD is used to denoise the noisy measurement signal and identify the nature of the decrement factor of the low frequency oscillatory modes. The accuracy of the estimated decrement factors of modes are verified with eigenvalues to validate the proposed method. The performance of proposed method is compared with signal processing method for IEEE New England power system and found effective and suitable during noisy PMU measurements.
کلیدواژه‌ها
Fast Fourier Transform؛ Power Spectral Density؛ Wide area Monitoring system.‎
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