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Performance Comparison of PD Data Acquisition Techniques for Condition Monitoring of Medium Voltage Cables

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  • Muhammad Shafiq

    (School of Technology and Innovations, Electrical Engineering, University of Vaasa, 65200 Vaasa, Finland)

  • Ivar Kiitam

    (Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia)

  • Kimmo Kauhaniemi

    (School of Technology and Innovations, Electrical Engineering, University of Vaasa, 65200 Vaasa, Finland)

  • Paul Taklaja

    (Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia)

  • Lauri Kütt

    (Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia)

  • Ivo Palu

    (Department of Electrical Power Engineering and Mechatronics, Tallinn University of Technology, 19086 Tallinn, Estonia)

Abstract

Already installed cables are aging and the cable network is growing rapidly. Improved condition monitoring methods are required for greater visibility of insulation defects in the cable networks. One of the critical challenges for continuous monitoring is the large amount of partial discharge (PD) data that poses constraints on the diagnostic capabilities. This paper presents the performance comparison of two data acquisition techniques based on phase resolved partial discharge (PRPD) and pulse acquisition (PA). The major contribution of this work is to provide an in-depth understanding of these techniques considering the perspective of randomness of the PD mechanism and improvements in the reliability of diagnostics. Experimental study is performed on the medium voltage (MV) cables in the laboratory environment. It has been observed that PRPD based acquisition not only requires a significantly larger amount of data but is also susceptible to losing the important information especially when multiple PD sources are being investigated. On the other hand, the PA technique presents improved performance for PD diagnosis. Furthermore, the use of the PA technique enables the efficient practical implementation of the continuous PD monitoring by reducing the amount of data that is acquired by extracting useful signals and discarding the silent data intervals.

Suggested Citation

  • Muhammad Shafiq & Ivar Kiitam & Kimmo Kauhaniemi & Paul Taklaja & Lauri Kütt & Ivo Palu, 2020. "Performance Comparison of PD Data Acquisition Techniques for Condition Monitoring of Medium Voltage Cables," Energies, MDPI, vol. 13(16), pages 1-14, August.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:16:p:4272-:d:400671
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    References listed on IDEAS

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    1. Yuanlin Luo & Zhaohui Li & Hong Wang, 2017. "A Review of Online Partial Discharge Measurement of Large Generators," Energies, MDPI, vol. 10(11), pages 1-32, October.
    2. Wen, Lulu & Zhou, Kaile & Yang, Shanlin & Li, Lanlan, 2018. "Compression of smart meter big data: A survey," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 59-69.
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    Cited by:

    1. Xianjie Rao & Kai Zhou & Yuan Li & Guangya Zhu & Pengfei Meng, 2020. "A New Cross-Correlation Algorithm Based on Distance for Improving Localization Accuracy of Partial Discharge in Cables Lines," Energies, MDPI, vol. 13(17), pages 1-13, September.
    2. Maninder Choudhary & Muhammad Shafiq & Ivar Kiitam & Amjad Hussain & Ivo Palu & Paul Taklaja, 2022. "A Review of Aging Models for Electrical Insulation in Power Cables," Energies, MDPI, vol. 15(9), pages 1-20, May.

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