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Dynamic phasor estimation using adaptive artificial neural network

Author

Listed:
  • A. V. Koteswara Rao

    (Amity University Uttar Pradesh)

  • K. M. Soni

    (Amity University Uttar Pradesh)

  • Sanjay Kumar Sinha

    (Amity University Uttar Pradesh)

  • Ibraheem Nasiruddin

    (Jamia Millia Islamia University)

Abstract

The variation in amplitude and phase of voltage and current signals of a power system under dynamics is often the basis for inaccurate phasor estimation. Further, the frequency estimator derived from estimated phasor is being affected under such dynamic characteristics. This paper presents a method to compute the magnitude and phase angle of the signal during the dynamics using an artificial neural network. First the modeling of signal during dynamics is presented then a multi-layered feed-forward neural network algorithm is developed to estimate the unknown parameters of the model. Subsequently, the magnitude and phase angle and frequency of the signal are calculated using the estimated parameters. The performance of the proposed method is evaluated using standard test signals as per the synchrophasor standard.

Suggested Citation

  • A. V. Koteswara Rao & K. M. Soni & Sanjay Kumar Sinha & Ibraheem Nasiruddin, 2021. "Dynamic phasor estimation using adaptive artificial neural network," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(2), pages 310-317, April.
  • Handle: RePEc:spr:ijsaem:v:12:y:2021:i:2:d:10.1007_s13198-021-01082-2
    DOI: 10.1007/s13198-021-01082-2
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