IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i13p4847-d1176138.html
   My bibliography  Save this article

Effect of Interplay between Parallel and Perpendicular Magnetic and Electric Fields on Partial Discharges

Author

Listed:
  • Marek Florkowski

    (Department of Electrical and Power Engineering, AGH University of Science and Technology, Al. Mickiewicza 30, 30-059 Kraków, Poland)

Abstract

This paper reports on the influence of a magnetic field on the dynamics of partial discharges (PDs) in two distinct configurations with respect to the mutual orientation of electric fields. The broad application areas include electrical insulation systems of both high-voltage grids and industrial network devices as well as emerging segments such as electric vehicles or more electric aircraft. Traditionally, PD measurements are only carried out in an electric field. In all current-carrying power equipment, magnetic fields are also superimposed onto electric ones, thus influencing partial discharge behavior. It has been observed that the interplay between electric and magnetic fields influences the dynamics of PDs; parallel and perpendicular mutual orientations were specifically investigated. The measurement technique allowed us to quantitively detect the effect of magnetic fields on PDs in a corona point–plane arrangement. The novel element presented in this article is a detection of PD intensity modulated by a magnetic field, with both perpendicular and parallel orientations with respect to electric one, and a quantitative visualization in the form of the time-sequence diagrams. The simulation of electron trajectories in the presence of electric and magnetic fields revealed the elongation of the pathways and differentiation of the charged particle propagation times. The perpendicularly oriented magnetic field led to a twisting effect, whereas the parallel alignment reflected the propagation along a helical trajectory. A slightly stronger PD intensity amplification effect was observed in the case of a parallel alignment of electric versus magnetic fields as compared with the perpendicular orientation. The presented results may contribute to PD measurement methodology in both electric and magnetic fields as well as a better understanding of the underlying physical mechanisms. The observed effect of the modulation of the magnetically based PD dynamics may be relevant for the insulation systems of power equipment.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:13:p:4847-:d:1176138
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/13/4847/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/13/4847/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. Henryka Danuta Stryczewska & Mariusz Adam Stępień & Oleksandr Boiko, 2022. "Plasma and Superconductivity for the Sustainable Development of Energy and the Environment," Energies, MDPI, vol. 15(11), pages 1-30, June.
    4. Marek Florkowski, 2020. "Classification of Partial Discharge Images Using Deep Convolutional Neural Networks," Energies, MDPI, vol. 13(20), pages 1-17, October.
    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. Marek Florkowski, 2021. "Anomaly Detection, Trend Evolution, and Feature Extraction in Partial Discharge Patterns," Energies, MDPI, vol. 14(13), pages 1-18, June.
    2. Gustavo de Oliveira Machado & Luciano Coutinho Gomes & Augusto Wohlgemuth Fleury Veloso da Silveira & Carlos Eduardo Tavares & Darizon Alves de Andrade, 2022. "Impacts of Harmonic Voltage Distortions on the Dynamic Behavior and the PRPD Patterns of Partial Discharges in an Air Cavity Inside a Solid Dielectric Material," Energies, MDPI, vol. 15(7), pages 1-20, April.
    3. Alper Aydogan & Fatih Atalar & Aysel Ersoy Yilmaz & Pawel Rozga, 2020. "Using the Method of Harmonic Distortion Analysis in Partial Discharge Assessment in Mineral Oil in a Non-Uniform Electric Field," Energies, MDPI, vol. 13(18), pages 1-18, September.
    4. Gulmira Abbas & Alimujiang Kasimu, 2023. "Characteristics of Land-Use Carbon Emissions and Carbon Balance Zoning in the Economic Belt on the Northern Slope of Tianshan," Sustainability, MDPI, vol. 15(15), pages 1-27, July.
    5. 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.
    6. Grzegorz Komarzyniec & Michał Aftyka, 2023. "Cooperation of the Plasma Reactor with a Converter Power Supply Equipped with a Transformer with Special Design," Energies, MDPI, vol. 16(19), pages 1-17, September.
    7. Jinseok Kim & Ki-Il Kim, 2021. "Partial Discharge Online Detection for Long-Term Operational Sustainability of On-Site Low Voltage Distribution Network Using CNN Transfer Learning," Sustainability, MDPI, vol. 13(9), pages 1-20, April.
    8. Sara Mantach & Ahmed Ashraf & Hamed Janani & Behzad Kordi, 2021. "A Convolutional Neural Network-Based Model for Multi-Source and Single-Source Partial Discharge Pattern Classification Using Only Single-Source Training Set," Energies, MDPI, vol. 14(5), pages 1-16, March.
    9. Jianfeng Zheng & Zhichao Chen & Qun Wang & Hao Qiang & Weiyue Xu, 2022. "GIS Partial Discharge Pattern Recognition Based on Time-Frequency Features and Improved Convolutional Neural Network," Energies, MDPI, vol. 15(19), pages 1-14, October.
    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. Sara Mantach & Abdulla Lutfi & Hamed Moradi Tavasani & Ahmed Ashraf & Ayman El-Hag & Behzad Kordi, 2022. "Deep Learning in High Voltage Engineering: A Literature Review," Energies, MDPI, vol. 15(14), pages 1-32, July.
    12. Ramon C. F. Araújo & Rodrigo M. S. de Oliveira & Fabrício J. B. Barros, 2022. "Automatic PRPD Image Recognition of Multiple Simultaneous Partial Discharge Sources in On-Line Hydro-Generator Stator Bars," Energies, MDPI, vol. 15(1), pages 1-26, January.
    13. Marek Florkowski, 2020. "Influence of Insulating Material Properties on Partial Discharges at DC Voltage," Energies, MDPI, vol. 13(17), pages 1-17, August.
    14. Marek Florkowski, 2020. "Classification of Partial Discharge Images Using Deep Convolutional Neural Networks," Energies, MDPI, vol. 13(20), pages 1-17, October.
    15. 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.
    16. Henryka Danuta Stryczewska & Oleksandr Boiko & Mariusz Adam Stępień & Paweł Lasek & Masaaki Yamazato & Akira Higa, 2023. "Selected Materials and Technologies for Electrical Energy Sector," Energies, MDPI, vol. 16(12), pages 1-26, June.
    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:16:y:2023:i:13:p:4847-:d:1176138. 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.