Mode identification method of low-frequency oscillation for power system based on ambient data

• Hong-Yan Yan ^[1] ; Jin Kwon Hwang ^[2]
  1. [1] Hebei University of Engineering

     Hebei University of Engineering

     China

     
  2. [2] Woosuk University

     Woosuk University

     Corea del Sur

     
• Localización: Compel: International journal for computation and mathematics in electrical and electronic engineering, ISSN 0332-1649, Vol. 40, Nº 3, 2021, págs. 441-455
• Idioma: inglés
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• Resumen

  • Purpose The purpose of this paper is to improve the online monitoring level of low-frequency oscillation in the power system. A modal identification method of discrete Fourier transform (DFT) curve fitting based on ambient data is proposed in this study.

    Design/methodology/approach An autoregressive moving average mathematical model of ambient data was established, parameters of low-frequency oscillation were designed and parameters of low-frequency oscillation were estimated via DFT curve fitting. The variational modal decomposition method is used to filter direct current components in ambient data signals to improve the accuracy of identification. Simulation phasor measurement unit data and measured data of the power grid proved the correctness of this method.

    Findings Compared with the modified extended Yule-Walker method, the proposed approach demonstrates the advantages of fast calculation speed and high accuracy.

    Originality/value Modal identification method of low-frequency oscillation based on ambient data demonstrated high precision and short running time for small interference patterns. This study provides a new research idea for low-frequency oscillation analysis and early warning of power systems.