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On-Line Partial Discharge Monitoring System for Power Transformers Based on the Simultaneous Detection of High Frequency, Ultra-High Frequency, and Acoustic Emission Signals

Author

Listed:
  • Wojciech Sikorski

    (Institute of Electric Power Engineering, Poznan University of Technology, 60-965 Poznan, Poland)

  • Krzysztof Walczak

    (Institute of Electric Power Engineering, Poznan University of Technology, 60-965 Poznan, Poland)

  • Wieslaw Gil

    (Mikronika, 60-001 Poznan, Poland)

  • Cyprian Szymczak

    (Institute of Electric Power Engineering, Poznan University of Technology, 60-965 Poznan, Poland)

Abstract

The article presents a novel on-line partial discharge (PD) monitoring system for power transformers, whose functioning is based on the simultaneous use of three unconventional methods of PD detection: high-frequency (HF), ultra-high frequency (UHF), and acoustic emission (AE). It is the first monitoring system equipped in an active dielectric window (ADW), which is a combined ultrasonic and electromagnetic PD sensor. The article discusses in detail the process of designing and building individual modules of hardware and software layers of the system, wherein the most attention was paid to the PD sensors, i.e., meandered planar inverted-F antenna (MPIFA), high-frequency current transformer (HFCT), and active dielectric window with ultrasonic transducer, which were optimized for detection of PDs occurring in oil-paper insulation. The prototype of the hybrid monitoring system was first checked on a 330 MVA large power transformer during the induced voltage test with partial discharge measurement (IVPD). Next, it was installed on a 31.5 MVA substation power transformer and integrated according to the standard IEC 61850 with SCADA (Supervisory Control and Data Acquisition) system registering voltage, active power, and oil temperature of the monitored unit. The obtained results showed high sensitivity of the manufactured PD sensors as well as the advantages of the simultaneous use of three techniques of PD detection and the possibility of discharge parameter correlation with other power transformer parameters.

Suggested Citation

  • Wojciech Sikorski & Krzysztof Walczak & Wieslaw Gil & Cyprian Szymczak, 2020. "On-Line Partial Discharge Monitoring System for Power Transformers Based on the Simultaneous Detection of High Frequency, Ultra-High Frequency, and Acoustic Emission Signals," Energies, MDPI, vol. 13(12), pages 1-37, June.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:12:p:3271-:d:375981
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    References listed on IDEAS

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    1. Wojciech Sikorski & Krzysztof Walczak & Piotr Przybylek, 2016. "Moisture Migration in an Oil-Paper Insulation System in Relation to Online Partial Discharge Monitoring of Power Transformers," Energies, MDPI, vol. 9(12), pages 1-16, December.
    2. Jian Li & Xudong Li & Lin Du & Min Cao & Guochao Qian, 2016. "An Intelligent Sensor for the Ultra-High-Frequency Partial Discharge Online Monitoring of Power Transformers," Energies, MDPI, vol. 9(5), pages 1-15, May.
    3. Xiaoxing Zhang & Guozhi Zhang & Yalong Li & Jian Zhang & Rui Huang, 2017. "On the Feasibility of Gap Detection of Power Transformer Partial Discharge UHF Signals: Gap Propagation Characteristics of Electromagnetic Waves," Energies, MDPI, vol. 10(10), pages 1-16, October.
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    Citations

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    Cited by:

    1. Krzysztof Walczak & Wojciech Sikorski, 2021. "Non-Contact High Voltage Measurement in the Online Partial Discharge Monitoring System," Energies, MDPI, vol. 14(18), pages 1-20, September.
    2. Shaorui Qin & Siyuan Zhou & Taiyun Zhu & Shenglong Zhu & Jianlin Li & Zheran Zheng & Shuo Qin & Cheng Pan & Ju Tang, 2021. "Sinusoidal Noise Removal in PD Measurement Based on Synchrosqueezing Transform and Singular Spectrum Analysis," Energies, MDPI, vol. 14(23), pages 1-22, November.
    3. Franciszek Witos & Aneta Olszewska & Zbigniew Opilski & Agnieszka Lisowska-Lis & Grzegorz Szerszeń, 2020. "Application of Acoustic Emission and Thermal Imaging to Test Oil Power Transformers," Energies, MDPI, vol. 13(22), pages 1-20, November.
    4. Dmitry A. Ivanov & Marat F. Sadykov & Danil A. Yaroslavsky & Aleksandr V. Golenishchev-Kutuzov & Tatyana G. Galieva, 2021. "Non-Contact Methods for High-Voltage Insulation Equipment Diagnosis during Operation," Energies, MDPI, vol. 14(18), pages 1-16, September.
    5. Zbigniew Nadolny, 2022. "Impact of Changes in Limit Values of Electric and Magnetic Field on Personnel Performing Diagnostics of Transformers," Energies, MDPI, vol. 15(19), pages 1-15, October.
    6. Daria Wotzka & Wojciech Sikorski & Cyprian Szymczak, 2022. "Investigating the Capability of PD-Type Recognition Based on UHF Signals Recorded with Different Antennas Using Supervised Machine Learning," Energies, MDPI, vol. 15(9), pages 1-20, April.
    7. Krzysztof Walczak, 2023. "Localization of HV Insulation Defects Using a System of Associated Capacitive Sensors," Energies, MDPI, vol. 16(5), pages 1-15, February.
    8. Franciszek Witos & Aneta Olszewska, 2023. "Investigation of Partial Discharges within Power Oil Transformers by Acoustic Emission," Energies, MDPI, vol. 16(9), pages 1-20, April.

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