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Statistical Analysis of Partial Discharges in SF 6 Gas via Optical Detection in Various Spectral Ranges

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  • Ming Ren

    (State Key Laboratory of Electrical Insulation for Power Equipment, Xi’an Jiaotong University, Xi’an 710049, China
    Institute of Materials Science, University of Connecticut, Storrs, CT 06269, USA)

  • Ming Dong

    (State Key Laboratory of Electrical Insulation for Power Equipment, Xi’an Jiaotong University, Xi’an 710049, China)

  • Jialin Liu

    (State Key Laboratory of Electrical Insulation for Power Equipment, Xi’an Jiaotong University, Xi’an 710049, China)

Abstract

Partial discharge (PD) detection is essential to the operation of high-voltage systems. In this context, we investigate the basic characteristics of light emission during PDs in SF 6 gas from the perspective of insulation diagnosis. A synchronous system is constructed using three optical photoelectric instruments with separate wavelength responses in the ultraviolet (UV, 189–352 nm), visible (VIS, 381–675 nm), and near-infrared (NIR, 737–920 nm) spectral ranges and a wide-band PD current pulse detector with a response of 1 pC. The results indicate that light emission depends upon the type of insulation defect and discharge energy. An increase in PD charge gives rise to more components in the spectral range from UV to VIS, and the presence of an insulator surface in discharges yields a more complex VIS-to-NIR spectrum. The phase-resolved partial discharge pattern (PRPD) of UV light pulses can reasonably reflect the electroluminescence process in the presence of the insulator surface and weak corona at negative voltage points. The PRPD of VIS light describes the features of the actual PD pattern in most cases. In comparison with the other two spectral ranges, light intensity in the VIS range is more sensitive to changes in gas-pressure-normalized voltage ( V rms / p ). The linear fitting analysis of the relationships between the light intensity and PD charge shows that UV light detection has a greater sensitivity to the PD charge and that UV detection exhibits a greater degree of linearity. NIR detection is applicable only to severe PDs. We believe that our findings can significantly aid in application of optical PD diagnosis in SF 6 gas insulated systems.

Suggested Citation

  • Ming Ren & Ming Dong & Jialin Liu, 2016. "Statistical Analysis of Partial Discharges in SF 6 Gas via Optical Detection in Various Spectral Ranges," Energies, MDPI, vol. 9(3), pages 1-15, March.
    • Handle: RePEc:gam:jeners:v:9:y:2016:i:3:p:152-:d:64882
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    References listed on IDEAS

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    1. Ju Tang & Jiabin Zhou & Xiaoxing Zhang & Fan Liu, 2012. "A Transformer Partial Discharge Measurement System Based on Fluorescent Fiber," Energies, MDPI, vol. 5(5), pages 1-13, May.
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    Cited by:

    1. Xiaoxin Chen & Chen Li & Liangjin Chen & Hui Wang & Yiming Zang & Weijia Yao, 2020. "Influence of Different Structure and Specification Parameters on the Propagation Characteristics of Optical Signals Generated by GIL Partial Discharge," Energies, MDPI, vol. 13(12), pages 1-18, June.
    2. Emilio Parrado-Hernández & Guillermo Robles & Jorge Alfredo Ardila-Rey & Juan Manuel Martínez-Tarifa, 2018. "Robust Condition Assessment of Electrical Equipment with One Class Support Vector Machines Based on the Measurement of Partial Discharges," Energies, MDPI, vol. 11(3), pages 1-18, February.
    3. Ju Tang & Miao Jin & Fuping Zeng & Siyuan Zhou & Xiaoxing Zhang & Yi Yang & Yan Ma, 2017. "Feature Selection for Partial Discharge Severity Assessment in Gas-Insulated Switchgear Based on Minimum Redundancy and Maximum Relevance," Energies, MDPI, vol. 10(10), pages 1-14, October.
    4. Marek Florkowski & Dariusz Krześniak & Maciej Kuniewski & Paweł Zydroń, 2020. "Partial Discharge Imaging Correlated with Phase-Resolved Patterns in Non-Uniform Electric Fields with Various Dielectric Barrier Materials," Energies, MDPI, vol. 13(11), pages 1-15, May.
    5. Jingxin Zou & Weigen Chen & Fu Wan & Zhou Fan & Lingling Du, 2016. "Raman Spectral Characteristics of Oil-Paper Insulation and Its Application to Ageing Stage Assessment of Oil-Immersed Transformers," Energies, MDPI, vol. 9(11), pages 1-14, November.

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