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Forced Oscillation Source Location of Bulk Power Systems Using Synchrosqueezing Wavelet Transform

Forced oscillation source location (FOSL) plays a significant role in mitigating forced oscillations (FOs), which threaten the power system stability. Here, this paper proposes a data-driven approach for FOSL in power systems using synchrosqueezing wavelet transform (SWT). The proposed approach conducts SWT on the measured system responses to obtain the SWT matrix. Then, the SWT-based dissipating energy flow (DEF) model in time-frequency domain and dissipating energy spectrum (DES) model in frequency domain are derived from the traditional DEF model. Further, the characteristics of SWT-based DEF and DES are revealed by referring to the traditional DEF, and the FOSL criteria of the SWT-based DEF and DES can be hereby obtained. Using the obtained FOSL criteria, the FO source can be located from the measured responses. The performance of the proposed FOSL method is evaluated by simulation data of the WECC 179-bus test system and field-measurement PMU data of the ISO New England. The results confirm the accuracy and efficiency of the proposed method in the FOSL.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Estimation of Participation Factors Using the Synchrosqueezed Wavelet Transform

This paper proposes a data-driven approach for estimating participation factors for a power system using only simulation results on selected disturbances. The approach is purely response-based and does not need a linearized system model for eigen-analysis, which makes it applicable to systems whose detailed, complete mathematical models are not available. Considering the unavoidable nonlinearity as exhibited in the transient period of a system response, the Synchrosqueezed Wavelet Transform is applied to simulated responses for modal analysis to obtain participation factors. Based on simulations of Kundur's two-area system using both the electromagnetic transient model and phasor model, the participation factors estimated by the proposed approach are compared with two other signal processing tools, the Prony analysis and continuous wavelet transform, and are also benchmarked with conventional model-based participation factors.

participation factor↗