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An approach to refine linear models used in small signal stability assessment

In this paper, an approach is proposed to improve linear models adopted in small-signal stability studies using information extracted from measured outputs of real system, as small disturbance data recorded by phasor measurement units (PMU). With this aim, a trajectory sensitivity technique is applied on the mismatch between the output of the simulated model and the response of the real system. Using this error signal and the sensitivity curves, this method can refine linear model in order to obtain a good match between the model and the measurements. In addition, this technique allows to identify which coefficients of the linear model can be refined from available data. Results obtained for a test case show that the proposed approach, which uses signals that can be directly measured by PMUs, is effective to calibrate the coefficients of interest in the system linear model.