From Event Data to Wind Power Plant DQ Admittance and Stability Risk Assessment

Zhengyu Wang, Li Bao, Lingling Fan, Zhixin Miao, Shahil Shah

Research output: Contribution to journalArticlepeer-review

5 Scopus Citations

Abstract

This paper presents a dynamic event data-based stability risk assessment method for power grids with high penetrations of inverter-based resources (IBRs). This method relies on obtaining the IBRs' DQ admittance through dynamic event data and computing the system's eigenvalues based on the admittance models. Two critical technologies are employed in this research, including time-domain and frequency-domain data fitting and dq-frame voltage and current signal derivation. The first technology is key to obtaining the s-domain expressions from the transient response data, and the s-domain DQ admittance model from the frequency-domain measurements. The second technology is key to obtaining the dq-frame voltage and current signals from either the three-phase instantaneous measurements or the phasor measurement unit (PMU) data. The method is illustrated using data generated from a Type-4 wind power plant modeled in PSCAD. This paper demonstrates the technical feasibility of the proposed approach.

Original languageAmerican English
Pages (from-to)4400-4408
Number of pages9
JournalIEEE Transactions on Power Systems
Volume37
Issue number6
DOIs
StatePublished - 1 Nov 2022

Bibliographical note

Publisher Copyright:
© 1969-2012 IEEE.

NREL Publication Number

  • NREL/JA-5D00-80004

Keywords

  • Admittance model
  • event data
  • stability analysis
  • wind power plant

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