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Application of Spectral Kurtosis to Characterize Amplitude Variability in Power Systems’ Harmonics

Author

Listed:
  • Jose-María Sierra-Fernández

    (PAIDI-TIC-168, Computational Instrumentation, University of Cádiz, Av. Ramón Puyol, 11202 Algeciras, Spain)

  • Sarah Rönnberg

    (Electric Power Engineering, Luleå University of Technology, Forskargatan 1, 931 87 Skellefteå, Sweden)

  • Juan-José González de la Rosa

    (PAIDI-TIC-168, Computational Instrumentation, University of Cádiz, Av. Ramón Puyol, 11202 Algeciras, Spain)

  • Math H. J. Bollen

    (Electric Power Engineering, Luleå University of Technology, Forskargatan 1, 931 87 Skellefteå, Sweden)

  • José-Carlos Palomares-Salas

    (PAIDI-TIC-168, Computational Instrumentation, University of Cádiz, Av. Ramón Puyol, 11202 Algeciras, Spain)

Abstract

The highly-changing concept of Power Quality (PQ) needs to be continuously reformulated due to the new schemas of the power grid or Smart Grid (SG). In general, the spectral content is characterized by their averaged or extreme values. However, new PQ events may consist of large variations in amplitude that occur in a short time or small variations in amplitude that take place continuously. Thus, the former second-order techniques are not suitable to monitor the dynamics of the power spectrum. In this work, a strategy based on Spectral Kurtosis (SK) is introduced to detect frequency components with a constant amplitude trend, which accounts for amplitude values’ dispersion related to the mean value of that spectral component. SK has been proven to measure frequency components that follow a constant amplitude trend. Two practical real-life cases have been considered: electric current time-series from an arc furnace and the power grid voltage supply. Both cases confirm that the more concentrated the amplitude values are around the mean value, the lower the SK values are. All this confirms SK as an effective tool for evaluating frequency components with a constant amplitude trend, being able to provide information beyond maximum variation around the mean value and giving a progressive index of value dispersion around the mean amplitude value, for each frequency component.

Suggested Citation

  • Jose-María Sierra-Fernández & Sarah Rönnberg & Juan-José González de la Rosa & Math H. J. Bollen & José-Carlos Palomares-Salas, 2019. "Application of Spectral Kurtosis to Characterize Amplitude Variability in Power Systems’ Harmonics," Energies, MDPI, vol. 12(1), pages 1-15, January.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:1:p:194-:d:195876
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    References listed on IDEAS

    as
    1. Khan, O. & Xiao, W., 2017. "Review and qualitative analysis of submodule-level distributed power electronic solutions in PV power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 516-528.
    2. Juan José González De la Rosa & José María Sierra-Fernández & José Carlos Palomares-Salas & Agustín Agüera-Pérez & Álvaro Jiménez Montero, 2015. "An Application of Spectral Kurtosis to Separate Hybrid Power Quality Events," Energies, MDPI, vol. 8(9), pages 1-17, September.
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    Cited by:

    1. Juan-José González de-la-Rosa & Manuel Pérez-Donsión, 2020. "Special Issue “Analysis for Power Quality Monitoring”," Energies, MDPI, vol. 13(3), pages 1-6, January.
    2. Paula Remigio-Carmona & Juan-José González-de-la-Rosa & Olivia Florencias-Oliveros & José-María Sierra-Fernández & Javier Fernández-Morales & Manuel-Jesús Espinosa-Gavira & Agustín Agüera-Pérez & José, 2022. "Current Status and Future Trends of Power Quality Analysis," Energies, MDPI, vol. 15(7), pages 1-18, March.

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