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Voltage Flicker Detection Based on Probability Resampling

Author

Listed:
  • Haitao Gao

    (College of Electrical and Electronic Engineering, Anhui Science and Technology University, Bengbu 233030, China)

  • Peng Xu

    (Marine Engineering College, Dalian Maritime University, Dalian 116026, China)

  • Jin Tao

    (Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland
    College of Engineering, Peking University, Beijing 100871, China)

  • Shihui Huang

    (Shenzhen Pluke Intelligent Test Equipment Co., Ltd., Shenzhen 518068, China)

  • Rugang Wang

    (Shenzhen Pluke Intelligent Test Equipment Co., Ltd., Shenzhen 518068, China)

  • Quan Zhou

    (Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland)

Abstract

Digital flicker detection devices need to store a large amount of evaluation data during measurement process, which leads to high requirements for hardware resources and algorithm execution efficiency. In this paper, a digital flicker detection method based on probability resampling is studied. In particular, before statistical evaluation, probability resampling is applied to screen the instantaneous flicker visual sensitivity data to compress redundant data. Additionally, the effectiveness of the method was numerically simulated and experimentally tested. The results show that the proposed method can accurately measure the voltage flicker value and can effectively compress the redundant evaluation data to be evaluated and has significant advantages in releasing hardware storage space, in improving algorithm execution efficiency and real-time performance, and in reducing processor workload. This method provides an engineering application reference for designing digital flicker detectors, especially for the software upgrade of traditional power quality testing equipment.

Suggested Citation

  • Haitao Gao & Peng Xu & Jin Tao & Shihui Huang & Rugang Wang & Quan Zhou, 2020. "Voltage Flicker Detection Based on Probability Resampling," Energies, MDPI, vol. 13(13), pages 1-12, June.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:13:p:3350-:d:378741
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    References listed on IDEAS

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    1. Koldo Redondo & José Julio Gutiérrez & Izaskun Azcarate & Purificación Saiz & Luis Alberto Leturiondo & Sofía Ruiz de Gauna, 2019. "Experimental Study of the Summation of Flicker Caused by Wind Turbines," Energies, MDPI, vol. 12(12), pages 1-13, June.
    2. Stefano Lodetti & Izaskun Azcarate & José Julio Gutiérrez & Luis Alberto Leturiondo & Koldo Redondo & Purificación Sáiz & Julio J. Melero & Jorge Bruna, 2019. "Flicker of Modern Lighting Technologies Due to Rapid Voltage Changes," Energies, MDPI, vol. 12(5), pages 1-16, March.
    3. Paolo Castello & Carlo Muscas & Paolo Attilio Pegoraro & Sara Sulis, 2019. "PMU’s Behavior with Flicker-Generating Voltage Fluctuations: An Experimental Analysis," Energies, MDPI, vol. 12(17), pages 1-14, August.
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    Cited by:

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    2. Krzysztof Kołek & Andrzej Firlit & Krzysztof Piątek & Krzysztof Chmielowiec, 2021. "Analysis of the Practical Implementation of Flicker Measurement Coprocessor for AMI Meters," Energies, MDPI, vol. 14(6), pages 1-17, March.

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