Data-Driven Identification of Nonlinear Power System Dynamics Using Output-Only Measurements

نویسندگان

چکیده

In this paper, we propose a novel approach for the data-driven characterization of power system dynamics. The developed method Extended Subspace Identification (ESI) is suitable systems with output measurements when all dynamics states are not observable. It particularly applicable dynamic identification using Phasor Measurement Units (PMUs) measurements. As in case systems, it often expensive or impossible to measure internal components such as generators, controllers and loads. PMU capture voltages, currents, injection frequencies, which can be considered outputs ESI identification, capturing nonlinear modes, computing participation factor modes identifying parameters inertia. proposed noise similar realistic addresses some known deficiencies existing methods. validated multiple network models event scenarios synthetic

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ژورنال

عنوان ژورنال: IEEE Transactions on Power Systems

سال: 2022

ISSN: ['0885-8950', '1558-0679']

DOI: https://doi.org/10.1109/tpwrs.2021.3131639