IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v18y2025i10p2583-d1657555.html
   My bibliography  Save this article

A Review of Partial Discharge Electrical Localization Techniques in Power Cables: Practical Approaches and Circuit Models

Author

Listed:
  • Mohammad Alqtish

    (L.E. PR.E. High Voltage Laboratory, Department of Engineering, University of Palermo, 90128 Palermo, Italy)

  • Alessio Di Fatta

    (L.E. PR.E. High Voltage Laboratory, Department of Engineering, University of Palermo, 90128 Palermo, Italy)

  • Giuseppe Rizzo

    (Prysmian, 20126 Milan, Italy)

  • Ghulam Akbar

    (L.E. PR.E. High Voltage Laboratory, Department of Engineering, University of Palermo, 90128 Palermo, Italy
    Department of Electrical Engineering, Sukkur IBA University, Sukkur 65200, Pakistan)

  • Vincenzo Li Vigni

    (Prysmian, 20126 Milan, Italy)

  • Antonino Imburgia

    (L.E. PR.E. High Voltage Laboratory, Department of Engineering, University of Palermo, 90128 Palermo, Italy)

  • Guido Ala

    (L.E. PR.E. High Voltage Laboratory, Department of Engineering, University of Palermo, 90128 Palermo, Italy)

  • Roberto Candela

    (Prysmian, 20126 Milan, Italy)

  • Pietro Romano

    (L.E. PR.E. High Voltage Laboratory, Department of Engineering, University of Palermo, 90128 Palermo, Italy)

Abstract

This paper remedies the lack of comparison between studies specifically addressing partial discharge (PD) localization using electrical techniques. It identifies all the elements in need in each technique as well as the equations leading to a precise determination of the discharge site in a cable with a certain length and documents several circuit models set to simulate various types of PD. From the details in this paper, different detection methods can be combined based on the specific requirements of each method for detecting PD. This work thoroughly evaluates several electrical PD detection approaches, including time-based, frequency band, and electromagnetic time reversal (EMTR). Additionally, it gathers circuit modeling for various types of PD along cables to improve detection accuracy. It is evident that all time-dependent methods, despite their simplicity and requiring only a small number of components, face challenges when applied to long cables. This is primarily due to their reliance on signal propagation time. The authors provide profound insights into suggestions for future study areas. This review will provide essential insights and serve as a foundation for researchers to develop more effective methods for detecting PD in cables.

Suggested Citation

  • Mohammad Alqtish & Alessio Di Fatta & Giuseppe Rizzo & Ghulam Akbar & Vincenzo Li Vigni & Antonino Imburgia & Guido Ala & Roberto Candela & Pietro Romano, 2025. "A Review of Partial Discharge Electrical Localization Techniques in Power Cables: Practical Approaches and Circuit Models," Energies, MDPI, vol. 18(10), pages 1-22, May.
  • Handle: RePEc:gam:jeners:v:18:y:2025:i:10:p:2583-:d:1657555
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/18/10/2583/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/18/10/2583/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Xiaohua Zhang & Bo Pang & Yaxin Liu & Shaoyu Liu & Peng Xu & Yan Li & Yifan Liu & Leijie Qi & Qing Xie, 2021. "Review on Detection and Analysis of Partial Discharge along Power Cables," Energies, MDPI, vol. 14(22), pages 1-21, November.
    3. Sinda Kaziz & Mohamed Hadj Said & Antonino Imburgia & Bilel Maamer & Denis Flandre & Pietro Romano & Fares Tounsi, 2023. "Radiometric Partial Discharge Detection: A Review," Energies, MDPI, vol. 16(4), pages 1-33, February.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. Haresh Kumar & Muhammad Shafiq & Kimmo Kauhaniemi & Mohammed Elmusrati, 2024. "A Review on the Classification of Partial Discharges in Medium-Voltage Cables: Detection, Feature Extraction, Artificial Intelligence-Based Classification, and Optimization Techniques," Energies, MDPI, vol. 17(5), pages 1-31, February.
    3. Tanachai Somsak & Thanapong Suwanasri & Cattareeya Suwanasri, 2021. "Lifetime Estimation Based Health Index and Conditional Factor for Underground Cable System," Energies, MDPI, vol. 14(23), pages 1-15, December.
    4. 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.
    5. 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.
    6. Wojciech Sikorski & Jaroslaw Gielniak, 2025. "Online Monitoring of Partial Discharges in Large Power Transformers Using Ultra-High Frequency and Acoustic Emission Methods: Case Studies," Energies, MDPI, vol. 18(7), pages 1-26, March.
    7. 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.
    8. 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.
    9. 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.
    10. Marek Florkowski, 2024. "Comparison of Effects of Partial Discharge Echo in Various High-Voltage Insulation Systems," Energies, MDPI, vol. 17(20), pages 1-17, October.
    11. Jian-Hsing Lee & Chih-Cherng Liao & Yeh-Jen Huang & Ching-Ho Li & Li-Yang Hong & Yeh-Ning Jou & Ke-Horng Chen, 2022. "Unipolar Arc Ignited Partial Discharge for 650-V AlGaN/GaN HEMTs during the DC Breakdown Voltage Measurement," Energies, MDPI, vol. 15(20), pages 1-12, October.
    12. Krzysztof Walczak & Aleksandra Schött-Szymczak, 2025. "Use of Capacitive Probes to Detect Asymmetry and Earth Fault in a Medium-Voltage Power Network," Energies, MDPI, vol. 18(9), pages 1-16, April.
    13. Michał Kozioł & Łukasz Nagi & Tomasz Boczar & Zbigniew Nadolny, 2023. "Quantitative Analysis of Surface Partial Discharges through Radio Frequency and Ultraviolet Signal Measurements," Energies, MDPI, vol. 16(9), pages 1-15, April.
    14. Marek Florkowski, 2023. "Effect of Interplay between Parallel and Perpendicular Magnetic and Electric Fields on Partial Discharges," Energies, MDPI, vol. 16(13), pages 1-16, June.
    15. Simone A. Rocha & Thiago G. Mattos & Rodrigo T. N. Cardoso & Eduardo G. Silveira, 2022. "Applying Artificial Neural Networks and Nonlinear Optimization Techniques to Fault Location in Transmission Lines—Statistical Analysis," Energies, MDPI, vol. 15(11), pages 1-24, June.
    16. 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.
    17. Krzysztof Walczak, 2023. "Localization of HV Insulation Defects Using a System of Associated Capacitive Sensors," Energies, MDPI, vol. 16(5), pages 1-15, February.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:18:y:2025:i:10:p:2583-:d:1657555. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.