Identification of Low Frequency Oscillation Modal based on Sparse Component Analysis

Low frequency oscillation monitoring and modal parameters identification are crucial for the diagnosis of power system faults. This paper presents a method utilizing sparse component analysis (SCA) to identify low frequency oscillation signals. The main steps include single-channel blind source separation and single-modal signal parameter identification. The proposed method utilizes variational mode decomposition (VMD) to construct virtual channels, employs SCA for source signal separation, and finally uses Hilbert transform (HT) to identify single modal oscillation parameters. The performance of the proposed method is assessed through numerical simulations and PSAT simulations, confirming its effectiveness, accuracy, and robustness.