LAUSR

Real-time monitoring ofoscillation events provides enhanced wide-area situational awareness to the system operator. This article focuses on visualizing low frequency oscillatory modes, their detection, and classification following an event. The significant oscillatory modes present in the signal are extracted through a novel energy preserving, nonredundant “frequency partition based mode extraction (FPBME)” algorithm. These modes are analytically deduced and classified as governor mode, interarea mode, and local mode through a novel “energy based mode detection and classification (EBMDC)” algorithm. This article proposed method introduces the concept of “visualization” that is highly operator-friendly through the time domain plots of extracted modes. Time-domain plots of mode’s instantaneous frequency and instantaneous energy, which are considered fundamental characterization of low-frequency oscillations, are also portrayed through the developed method. The proposed method is validated through various scenarios of Kundur’s two-area system and IEEE-39 bus system. A practical test case on the ISO-NE system is also verified through the suggested scheme. Comparison of the proposed method in the context of visualization with other methods such as the Hilbert–Huang technique and continuous wavelet transform is also discussed in this article. The comparative assessment demonstrates the superior performance of the proposed method.