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The Influence of Power Network Disturbances on Short Delayed Estimation of Fundamental Frequency Based on IpDFT Method with GMSD Windows

Author

Listed:
  • Józef Borkowski

    (Faculty of Electronics, Photonics and Microsystems, Wroclaw University of Science and Technology, 50-372 Wroclaw, Poland)

  • Mirosław Szmajda

    (Faculty of Electrical Engineering, Automatic Control and Informatics, Division of Control Science and Engineering, Opole University of Technology, 45-758 Opole, Poland)

  • Janusz Mroczka

    (Faculty of Electronics, Photonics and Microsystems, Wroclaw University of Science and Technology, 50-372 Wroclaw, Poland)

Abstract

This paper presents an application of the IpDFT spectrum interpolation method to estimate the fundamental frequency of a power waveform. Zero-crossing method (ZC) with signal prefiltering was used as a reference method. Test models of disturbances were applied, based on real disturbances recorded in power networks, including voltage harmonics and interharmonics, transient overvoltages, frequency spikes, dips and noise. It was determined that the IpDFT method is characterized by much better dynamic parameters with better estimation precision. In an example, in the presence of interharmonics, the frequency estimation error was three times larger for the reference method than that for the IpDFT method. Furthermore, during the occurrence of fast transient overvoltages, the IpDFT method reached its original accuracy about three times faster than the ZC method. Finally, using IpDFT, it was possible to identify the type of disturbances: impulsive, step changes of frequency or voltage dips.

Suggested Citation

  • Józef Borkowski & Mirosław Szmajda & Janusz Mroczka, 2021. "The Influence of Power Network Disturbances on Short Delayed Estimation of Fundamental Frequency Based on IpDFT Method with GMSD Windows," Energies, MDPI, vol. 14(20), pages 1-26, October.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:20:p:6465-:d:652660
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    References listed on IDEAS

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    1. Soseul Jeong & Junghun Lee & Minhan Yoon & Gilsoo Jang, 2020. "Energy Storage System Event-Driven Frequency Control Using Neural Networks to Comply with Frequency Grid Code," Energies, MDPI, vol. 13(7), pages 1-17, April.
    2. Rosa Anna Mastromauro, 2020. "Grid Synchronization and Islanding Detection Methods for Single-Stage Photovoltaic Systems," Energies, MDPI, vol. 13(13), pages 1-25, July.
    3. Adam Gozdowiak, 2020. "Faulty Synchronization of Salient Pole Synchronous Hydro Generator," Energies, MDPI, vol. 13(20), pages 1-21, October.
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    Cited by:

    1. Zbigniew Leonowicz & Michal Jasinski, 2022. "Machine Learning and Data Mining Applications in Power Systems," Energies, MDPI, vol. 15(5), pages 1-2, February.

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