PMU-based reduced-order modeling of power system dynamics via selective modal analysis Conference Paper uri icon

abstract

  • 2016 IEEE. This paper investigates how to perform online system identification employing synchrophasor data. Two approaches to identifying a reduced-order model are presented: a purely data-driven approach, and an approach that integrates online data-driven dynamic system identification with first-principle offline selective modal analysis. With prior knowledge of the frequency range interesting to power system operators, it is shown that the second approach recovers the key modes of the original system and produces a much reduced-order model of grid-level dynamics. Even with the presence of uncertainty about the actual modes of interest, an automatic tuning scheme is devised to adaptively adjust the frequency range to improve system identification. Numerical examples with synthetic synchrophasor data demonstrate the efficacy of the proposed identification approach.

name of conference

  • 2016 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)

published proceedings

  • 2016 IEEE/PES Transmission and Distribution Conference and Exposition (T&D)

author list (cited authors)

  • Wiseman, B. P., Chen, Y., Xie, L. e., & Kumar, P. R.

citation count

  • 4

complete list of authors

  • Wiseman, Benjamin P||Chen, Yang||Xie, Le||Kumar, PR

publication date

  • May 2016

publisher