University of Mohaghegh Ardabili Journal of Operation and Automation in Power Engineering 2322-4576 11 3 2023 10 01 Power Spectral Density based Identification of Low frequency ‎Oscillations in Multimachine Power system شناسایی نوسانات فرکانس پایین بر اساس چگالی طیفی توان در سیستم قدرت چند ماشینی 173 181 1656 10.22098/joape.2023.10072.1710 EN D. Shetty Department of Electrical and Electroinics Engineering, NMAM Institute of Technology Nitte, Karkala,India N. Prabhu Department of Electrical and Electroinics Engineering, NMAM Institute of Technology Nitte, Karkala,India Journal Article 2022 01 02 <em>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</em>. https://joape.uma.ac.ir/article_1656_88fdab482e83947d238a94a13b60ea4f.pdf