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A Frequency Estimation Method Based on a Revised 3-Level Discrete Fourier Transform with an Estimation Delay Reduction Technique

Author

Listed:
  • Sang-Hee Kang

    (Department of Electrical Engineering, Myongji University, Yongin 17058, Korea)

  • Woo-Seok Seo

    (Department of Electrical Engineering, Myongji University, Yongin 17058, Korea)

  • Soon-Ryul Nam

    (Department of Electrical Engineering, Myongji University, Yongin 17058, Korea)

Abstract

In this paper, a frequency estimation method based on a revised three-level discrete Fourier transform (DFT) with an estimation delay reduction technique is proposed. First, the input signal passes through a sine filter twice to improve the ability to decrease the level of harmonics and inter-harmonics. Secondly, the second sine-filtered signal is decomposed into two orthogonal components by DFT with a hamming window to enhance the ability to suppress inter-harmonics. The frequency of the signal is derived using orthogonal components without a zero-crossing problem, which can cause numerical estimation error. This process causes the estimation delay of three cycles and three samples in total. Therefore, the estimation delay reduction technique compensating for the phase delay of the phasor is proposed. To evaluate the performance of the proposed method, several frequency changes were considered when the test signals were generated according to the IEEE PMU Standards C37.118.1a-2014. The performance of the proposed method was also evaluated under dynamic and fault conditions in a five-bus transmission system modeled with PSCAD/EMTDC. The simulation results show that the proposed method accurately estimated the frequency of the signal.

Suggested Citation

  • Sang-Hee Kang & Woo-Seok Seo & Soon-Ryul Nam, 2020. "A Frequency Estimation Method Based on a Revised 3-Level Discrete Fourier Transform with an Estimation Delay Reduction Technique," Energies, MDPI, vol. 13(9), pages 1-16, May.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:9:p:2256-:d:353839
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    Citations

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    Cited by:

    1. Babak Jafarpisheh & Anamitra Pal, 2021. "A Robust Algorithm for Real-Time Phasor and Frequency Estimation under Diverse System Conditions," Energies, MDPI, vol. 14(21), pages 1-20, November.
    2. Malgorzata Binek & Andrzej Kanicki & Pawel Rozga, 2021. "Application of an Artificial Neural Network for Measurements of Synchrophasor Indicators in the Power System," Energies, MDPI, vol. 14(9), pages 1-14, April.

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