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Summary form only given. Prony analysis has been applied to estimate inter-area oscillation modes using phasor measurement unit (PMU) measurements. To suppress noise and signal offset effects, a high-order Prony model usually is used to over-fit the data. As such, some trivial modes are intentionally added to improve the estimation accuracy of the dominant modes. Therefore, to reduce the rate of false alarms, it is important to distinguish between the dominant modes that reflect the dynamic features of a power system and the trivial modes that are artificially introduced to improve the estimation accuracy. In this paper, a stepwise-regression method is applied to automatically identify the dominant modes from Prony analysis. A Monte-Carlo method is applied to evaluate the performance of the proposed method using data obtained from simulations. Field-measured PMU data are used to verify the applicability of the proposed method. A comparison of results obtained using the proposed approach with results from a traditional energy-sorting method shows the improved performance of the proposed method.
Power and Energy Society General Meeting, 2012 IEEE
Date of Conference: 22-26 July 2012