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Wavelet Packet Decomposition for IEC Compliant Assessment of Harmonics under Stationary and Fluctuating Conditions

Author

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  • Stefano Lodetti

    (Instituto Universitario de Investigación CIRCE (Fundación CIRCE—Universidad de Zaragoza), C/Mariano Esquillor 15, 50018 Zaragoza, Spain)

  • Jorge Bruna

    (Instituto Universitario de Investigación CIRCE (Fundación CIRCE—Universidad de Zaragoza), C/Mariano Esquillor 15, 50018 Zaragoza, Spain)

  • Julio J. Melero

    (Instituto Universitario de Investigación CIRCE (Fundación CIRCE—Universidad de Zaragoza), C/Mariano Esquillor 15, 50018 Zaragoza, Spain)

  • José F. Sanz

    (Instituto Universitario de Investigación CIRCE (Fundación CIRCE—Universidad de Zaragoza), C/Mariano Esquillor 15, 50018 Zaragoza, Spain)

Abstract

This paper presents the validation and characterization of a wavelet based decomposition method for the assessment of harmonic distortion in power systems, under stationary and non-stationary conditions. It uses Wavelet Packet Decomposition with Butterworth Infinite Impulse Response filters and a decomposition structure, which allows the measurement of both odd and even harmonics, up to the 63rd order, fully compliant with the requirements of the IEC 61000-4-7 standard. The method is shown to fulfil the IEC accuracy requirements for stationary harmonics, obtaining the same accuracy even under fluctuating conditions. Then, it is validated using simulated signals with real harmonic content. The proposed method is proven to be fully equivalent to Fourier analysis under stationary conditions, being often more accurate. Under non-stationary conditions, instead, it provides significantly higher accuracy, while the IEC strategy produces large errors. Lastly, the method is tested with real current and voltage signals, measured in conditions of high harmonic distortion. The proposed strategy provides a method with superior performance for fluctuating harmonics, but at the same time IEC compliant under stationary conditions.

Suggested Citation

  • Stefano Lodetti & Jorge Bruna & Julio J. Melero & José F. Sanz, 2019. "Wavelet Packet Decomposition for IEC Compliant Assessment of Harmonics under Stationary and Fluctuating Conditions," Energies, MDPI, vol. 12(22), pages 1-15, November.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:22:p:4389-:d:288416
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    References listed on IDEAS

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    1. Wang, Chun & Yang, Ruixin & Yu, Quanqing, 2019. "Wavelet transform based energy management strategies for plug-in hybrid electric vehicles considering temperature uncertainty," Applied Energy, Elsevier, vol. 256(C).
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    3. Luciano Telesca & Fabian Guignard & Nora Helbig & Mikhail Kanevski, 2019. "Wavelet Scale Variance Analysis of Wind Extremes in Mountainous Terrains," Energies, MDPI, vol. 12(16), pages 1-10, August.
    4. Petar Mostarac & Roman Malarić & Katarina Mostarac & Marko Jurčević, 2019. "Noise Reduction of Power Quality Measurements with Time-Frequency Depth Analysis," Energies, MDPI, vol. 12(6), pages 1-19, March.
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    Cited by:

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    2. Junghwan Kim, 2021. "In-Cylinder Pressure Based Engine Knock Classification Model for High-Compression Ratio, Automotive Spark-Ignition Engines Using Various Signal Decomposition Methods," Energies, MDPI, vol. 14(11), pages 1-18, May.

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