Dielectric Breakdown and Electrical Aging of Insulating Polymer Materials in High Voltage Systems

Notice

This is an unedited manuscript accepted for publication and provided as an Article in Press for early access at the author’s request. The article will undergo copyediting, typesetting, and galley proof review before final publication. Please be aware that errors may be identified during production that could affect the content. All legal disclaimers of the journal apply.

Year : 2025 | Volume : 13 | 06 | Page :
    By

    Digvijay Kanase,

  • Suraj Pawar,

  • Gajkumar Kavathekar,

  • Sachin Jadhav,

  • Shankar Chavan,

  • Swapnil Patil,

  • Abhay Dashrath,

  • Girish Modak,

  • Ganesh Patil,

  • Kamalkishor Maniyar,

  1. , Department of Electrical Engineering, Dr. D. Y. Patil Institute of Technology, Pimpri, Pune, Maharashtra, India
  2. , Department of Electrical Engineering, Annasaheb Dange College of Engineering and Technology Ashta, , India
  3. , Department of Electrical Engineering, Annasaheb Dange College of Engineering and Technology Ashta, , India
  4. , Department of Electrical Engineering, Rajarambapu Institute of Technology Islampur, , India
  5. , Department of Electrical Engineering, Dr. D. Y. Patil Institute of Technology, Pimpri, Pune, Maharashtra, India
  6. , Department of Electrical Engineering, Walchand College of Engineering, Sangli, ,
  7. , Department of Humanities and Engineering Sciences, MIT Academy of Engineering, Alandi Road, Pune, , India
  8. , Department of Mechanical Engineering PES Modern College of Engineering, Pune, Maharashtra, India
  9. , Department of Electrical Engineering, Dr. D. Y. Patil Institute of Technology, Pimpri, Pune, Maharashtra, India
  10. , Department of Mechanical Engineering, Dr. D. Y. Patil Institute of Technology, Pimpri, Pune, Maharashtra, India

Abstract

In this paper, a detailed analysis of dielectric breakdown and electrical aging behaviour of high-voltage insulating polymer material has been proposed through sophisticated MATLAB simulation. The research involves electric field modelling, ageing life prediction, partial discharge (PD) behaviour and uncertainty modelling using Monte Carlo analysis. Electric field hotspots causing critical behavior, sensitivity of the lifespan to electric stress, and the stochastic PD build-up allow predictive diagnostics of the health of insulating polymer materials, simulated results say. This method gives a common simulation platform that can be applicable to researchers and the practitioners in the industry who deal with high voltage systems. A clear lack exists in the form of an integrated, multi-dimensional simulation capability which would enhance deterministic and probabilistic analyses into a coupled and user-friendly framework. In particular, a tool enabling engineers and researchers to see electric field distribution, calculate insulation life at different stress levels, model PD events as random processes, and include statistical deviations in polymer material parameters. This would not only be an academic exploration tool, but it would also enable the industry practitioners to have a predictive diagnostic ability, as well as the ability to do design verification. The gap is closed in this research with the proposed integrated MATLAB based simulation framework, which captures all the key factors of insulation aging. In doing so it addresses a long-standing gap in the capability to diagnose polymer materials at high voltage and establishes the foundation of a new generation of insulation system design and health monitoring

Keywords: Polymer materials, Dielectric breakdown, electrical aging, high voltage insulation, partial discharge, Monte Carlo analysis, electric field distribution, insulation reliability.

How to cite this article:
Digvijay Kanase, Suraj Pawar, Gajkumar Kavathekar, Sachin Jadhav, Shankar Chavan, Swapnil Patil, Abhay Dashrath, Girish Modak, Ganesh Patil, Kamalkishor Maniyar. Dielectric Breakdown and Electrical Aging of Insulating Polymer Materials in High Voltage Systems. Journal of Polymer and Composites. 2025; 13(06):-.
How to cite this URL:
Digvijay Kanase, Suraj Pawar, Gajkumar Kavathekar, Sachin Jadhav, Shankar Chavan, Swapnil Patil, Abhay Dashrath, Girish Modak, Ganesh Patil, Kamalkishor Maniyar. Dielectric Breakdown and Electrical Aging of Insulating Polymer Materials in High Voltage Systems. Journal of Polymer and Composites. 2025; 13(06):-. Available from: https://journals.stmjournals.com/jopc/article=2025/view=231722


References

  1. Albarracín, R., Ardila-Rey, J. A., & Mas’ud, A. A. (2023). Monte Carlo-based uncertainty quantification for electrical aging models in high-voltage insulation. Polymer Degradation and Stability, 208, 110265. https://doi.org/10.1016/j.polymdegradstab.2023.110265
  2. Andritsch, T., Kochetov, R., & Morshuis, P. H. F. (2020). Accelerated aging tests and life modeling of polymeric insulators under DC stress. IEEE Transactions on Dielectrics and Electrical Insulation, 27(3), 872–880. https://doi.org/10.1109/TDEI.2020.008634
  3. Boggs, S. (2021). Partial discharge as a diagnostic tool for insulation systems: Recent advances. IEEE Electrical Insulation Magazine, 37(2), 7–18. https://doi.org/10.1109/MEI.2021.9373820.
  4. Cavallini, A., Montanari, G. C., & Contin, A. (2022). Stochastic partial discharge modeling for insulation reliability prediction. International Journal of Electrical Power & Energy Systems, 142, 108297. https://doi.org/10.1016/j.ijepes.2022.108297
  5. Dissado, L. A., Fothergill, J. C., & See, A. (2019). Molecular modeling of dielectric breakdown in polymers. Journal of Applied Physics, 126(15), 155101. https://doi.org/10.1063/1.5119687
  6. Du, B. X., Li, J., & Du, W. (2023). Thermo-electrical aging of silicone rubber composites for outdoor insulation: Experiment and simulation. Composite Structures, 304, 116455. https://doi.org/10.1016/j.compstruct.2022.116455
  7. Gao, Y., Wang, L., & Li, Z. (2020). Life prediction of XLPE cable insulation under electro-thermal stress using inverse power law model. Polymer Testing, 89, 106601. https://doi.org/10.1016/j.polymertesting.2020.106601
  8. Gulski, E., Cichecki, P., & Smit, J. J. (2021). Advanced PD diagnostics for insulation health assessment in high-voltage equipment. High Voltage, 6(4), 592–605. https://doi.org/10.1049/hve2.12075
  9. Hao, M., Wang, B., & Zhang, C. (2024). Deep learning-assisted Monte Carlo simulation for insulation failure risk assessment. Reliability Engineering & System Safety, 244, 109032. https://doi.org/10.1016/j.ress.2024.109032
  10. Huang, Z., Lau, K. Y., & Lai, L. L. (2023). Multi-stress aging of epoxy resin in power electronics: Experimental and numerical study. Microelectronics Reliability, 150, 115092. https://doi.org/10.1016/j.microrel.2023.115092
  11. Hussain, G. A., Illias, H. A., & Bashir, N. (2023). Multi-physics simulation of electrical treeing in epoxy insulation using COMSOL-MATLAB integration. Polymers, 15(5), 1287. https://doi.org/10.3390/polym15051287
  12. Köhler, W., Frechette, L. E., & Kindersberger, J. (2022). Influence of nanofillers on partial discharge resistance of XLPE for HVDC applications. Journal of Materials Science: Materials in Electronics, 33(20), 16241–16253. https://doi.org/10.1007/s10854-022-08514-0
  13. Kumar, S., Thomas, M. J., & Singh, B. P. (2022). Electric field hotspot detection in GIS spacers using machine learning and FEM. Engineering Failure Analysis, 141, 106678. https://doi.org/10.1016/j.engfailanal.2022.106678
  14. Li, S., Wang, Z., Zhang, Q., & Chen, G. (2024). Machine learning-driven prediction of dielectric breakdown in XLPE cables using partial discharge signatures. Electric Power Systems Research, 226, 109912. https://doi.org/10.1016/j.epsr.2023.109912
  15. Montanari, G. C. (2023). Stochastic life modeling of insulation systems under multi-stress aging. IEEE Transactions on Dielectrics and Electrical Insulation, 30(2), 407–414. https://doi.org/10.1109/TDEI.2023.324567
  16. Morshuis, P. H. F., Bodega, R., & Fabiani, D. (2019). Degradation metrics for solid dielectrics under combined AC-DC stresses. Journal of Physics D: Applied Physics, 52(49), 495501. https://doi.org/10.1088/1361-6463/ab3e9c
  17. Raymond, W. J. K., Illias, H. A., & Bakar, A. H. A. (2022). Uncertainty quantification in insulation lifetime estimation using Bayesian inference. IEEE Transactions on Dielectrics and Electrical Insulation, 29(1), 225–233. https://doi.org/10.1109/TDEI.2022.3145689
  18. Wang, Q., Zhou, X., & He, J. (2023). Probabilistic lifetime assessment of transformer insulation under combined electrical-thermal stresses. IEEE Access, 11, 23456 23467https://doi.org/10.1109/ACCESS.2023.3267890
  19. Zhang, Y., Li, H., & Liu, Y. (2022). Finite element analysis of electric field distribution in defective cable insulation using MATLAB PDE toolbox. Energies, 15(18), 6782. https://doi.org/10.3390/en15186782
  20. Lv, Z., Wang, S., & Li, C. (2021). MATLAB-based electric field optimization in high-voltage bushings using genetic algorithms. IEEE Transactions on Power Delivery, 36(5), 3105–3114. https://doi.org/10.1109/TPWRD.2020.3043278
Ahead of Print Subscription Review Article
Volume 13
06
Received 21/08/2025
Accepted 11/11/2025
Published 13/11/2025
Publication Time 84 Days
282

Login


My IP

PlumX Metrics