Forced Oscillation Identification and Filtering From Multi-Channel Time-Frequency Representation

Location of non-stationary forced oscillation (FO) sources can be a challenging task, especially under resonance condition with natural system modes. In this case, the magnitudes of the oscillations could be greater in places distant from the source and the oscillation spreads over a large region of the power system. Detection, frequency identification and filtering of FO oscillatory components constitutes an initial and critical step for the application of oscillation source location (OSL) methods. Specifically, this step has a major impact on the performance of the OSL method, such as the Dissipating Energy Flow (DEF) method. In this paper we develop a systematic methodology for detection, identification and filtering of non-stationary FO based on multi-channel time-frequency (TF) representation (TFR). We compare three TF approaches applied together with the DEF method: short-time Fourier transform (STFT), STFT-based synchrosqueezing transform (FSST) and second order FSST (FSST2). We have used simulated signals and real world PMU data to show that the proposed method provides a systematic framework for the identification and filtering of power systems non-stationary forced oscillations.