From Microscopic Degradation to Grid Resilience: A Comprehensive Analysis of Surface Tracking Mechanisms and Predictive Mitigation in Polymeric Insulators

Abdelati M. Taher Jermi

doi:10.65405/fwhheg45

المؤلفون

Abdelati M. Taher Jermi Department of Renewable Energy, Faculty of Natural Resource Engineering, University of Zawia, Libya Author

DOI:

https://doi.org/10.65405/fwhheg45

الكلمات المفتاحية:

Polymeric insulators, surface tracking, dielectric failure, RBGF, electrical maintenance

الملخص

This study investigates surface tracking phenomena in polymeric insulators, focusing on how material composition, design integrity, and operational conditions influence their performance and reliability in high-voltage applications. Polymeric insulators are increasingly favored in modern power systems due to their lightweight nature, hydrophobic properties, and resistance to vandalism. However, their susceptibility to surface degradation surface tracking poses significant operational challenges. The research emphasizes the critical role of each insulator component, including the weather-resistant polymeric housing, reinforced glass fiber (RBGF) core, metal end fittings, and sealing interfaces. Any deterioration, especially at the junctions between polymeric and metallic parts, can initiate surface tracking, potentially leading to dielectric failure, current leakage, and outages. Through analysis of structural composition and field performance, the study underscores the importance of material selection, proper engineering design, and proactive maintenance strategies. Enhancing understanding of surface tracking mechanisms is vital to mitigating operational risks and ensuring long-term stability and safety in electrical power networks.

التنزيلات

تنزيل البيانات ليس متاحًا بعد.

المراجع

1. Ghosh, D., & Khastgir, D. (2018). Degradation and Stability of Polymeric High-Voltage Insulators and Prediction of Their Service Life through Environmental and Accelerated Aging Processes. ACS Omega, 3(9), 11317–11330.

2. Hackam, R. (1999). Outdoor HV composite polymeric insulators. IEEE Transactions on Dielectrics and Electrical Insulation, 6(5), 557–585.

3. Wang, H., Zhang, Z., & Li, J. (2021). Surface tracking characteristics of polymeric insulators under salt-fog and wet contamination. IEEE Access, 9, 12403–12412.

4. Anghelescu, L., Handra, A. D., & Diaconu, B. M. (2025). Degradation pathways of electrical cable insulation: A review of aging mechanisms and fire hazards. Fire, 8(10), 397.

5. Chrzan, K., & Rosiński, M. (2016). Failure analysis of composite insulators in power networks. Energies, 9(3), 204.

6. Sundararajan, R., Gorur, R. S., & El-Hag, A. H. (2004). Material characterization of polymeric housing materials for outdoor insulators. IEEE Transactions on Dielectrics and Electrical Insulation, 11(2), 348–361.

7. International Electrotechnical Commission (IEC). (2022). IEC 60587:2022: Electrical insulating materials used under severe ambient conditions—Test methods for evaluating resistance to tracking and erosion. Geneva, Switzerland: IEC.

8. Alabi, A. S., Popoola, P. A., Popoola, O. M., Umaru, O. B., & Joshua, G. (2026). Overview on the recent technique on the evaluation of insulation of the polymer micro-and nanocomposite materials. In Polymer Micro and Nanocomposites for High Voltage Insulation (pp. 195-219). Elsevier.

9. Karim, A. M., Karal, Ö., & Çelebi, F. V. (2018, July). A new automatic epilepsy serious detection method by using deep learning based on discrete wavelet transform. In Proceedings of the 3rd International Conference on Engineering Technology and Applied Sciences (ICETAS) (Vol. 4, pp. 15-18).

10. Ramadan, Nizar, and Imad Omara Shebani Etomi. "Impact of Pollution on Leakage Current in Polymeric Insulators: Time and Frequency Domain Analysis." Surman Journal of Science and Technology 6.2 (2024): 093-102.‏

11. Madi, Ali Mustafa, et al. "Biodegradation of Polymeric Insulators Used in Electrical power." Surman Journal of Science and Technology 5.1 (2023): 031-040.‏

12. Madi, Ali Mustafa, et al. "Surface Degradation of Polymer Insulator under Ultraviolet Stress." Int. J. Eng. Res. & Technol 5.2 (2016): 315-319.‏

13. Tavakol, N., Teimoortashloo, M., & Esmaeelzadeh, F. (2025). Modeling and Analysis of Surface Contamination in Ceramic and Polymeric Insulators Using Partial Discharge Signal Characteristics. Journal of Resource Management and Decision Engineering, 4(1), 1-13.

14. Guwaeder, Abdulmunim, et al. "Modeling monthly insolation data." Nonimaging Optics: Efficient Design for Illumination and Solar Concentration XVII. Vol. 11495. SPIE, 2020.‏

15. Madi, Ali, et al. "Surface tracking on polymeric insulators used in electrical transmission lines." Indonesian Journal of Electrical Engineering and Computer Science 3.3 (2016): 639-645.‏

16. Jin, J. (2025, October). Research Progress on Aging of Insulation Materials of Power Equipment under Extreme Temperature Cycles. In Proceedings of the 2025 2nd International Conference on Electrical Engineering and Intelligent Control (EEIC 2025) (p. 183). Springer Nature.

17. Dalla, L. B., Karal, Ö., Mhamed, E. S., & Alsharif, A. (2026). An IoT-Enabled, THD-Based Fault Detection and Predictive Maintenance Framework for Solar PV Systems in Harsh Climates: Integrating DFT and Machine Learning for Enhanced Performance and Resilience. Wadi Alshatti University Journal of Pure and Applied Sciences, 41-55.‏

18. Mavrikakis, N., & Siderakis, K. (2026). Condition Assessment of Field-Aged Composite Insulators Following Incidents of Insulator Flashunder. Energies, 19(10), 2325.

19. EL-sseid M, Abdulgader A, Ben Dalla LOF, Elzer R, Abdussalam A, Ali T,Ali F, Alarafi M, Agaal A, Salih A.(2026). The novelty based on Energy Management Technologies for Integrated Microgrid frameworks. Comprehensive Journal of Science, 11(42), 163-174. https://doi.org/10.65405/f9606j11

20. Ramadhan, H. R. S. R., Osman, M., Ben-Dalla, L., Rashid, T., Albaraesi, M., EL-sseid, M. A. M., & Alnnale, T. (2025). A New Approach of the Machine Learning Framework Integrating Policy Design to Predict Renewable Electricity Penetration in Resource-Constrained Settings. Comprehensive Journal of Science, 10(Supplement 38), 2929-2950.

21. Danisman, K. E. N. A. N., Dalkiran, I., & Celebi, F. V. (2006). Design of a high precision temperature measurement system based on artificial neural network for different thermocouple types. Measurement, 39(8), 695-700.

22. Ghunem, Refat. A Study of the Erosion Mechanisms of Silicone Rubber Housing Composites. Diss. University of Waterloo, 2014.

23. El-Khozondar, Hala J., Yasser F. Nassar, Rifa J. El-Khozondar, Mohamed Elnaggar, Wael A. Salah, Sassi Rekik, Monaem Elmnifi, Mohamed Khaleel, and Llahm Omar Ben Dalla. "Analysis of a grid/wind/hydrogen hybrid energy system for producing electricity, vehicle fuel and freshwater for Gaza Strip-Palestine." Fuel 428 (2027): 140358.

24. Madi, Ali Mustafa, et al. "Degradation of Polymers Insulators used in Electrical Transmission Lines under the Rate of Bond Breaking." Surman Journal of Science and Technology 6.1 (2024): 016-028.‏

25. Syakur A, Hermawan, Sarjiya, Hamzah Berahim. Analyze of Hydrophobic Characteristics of Surface Material Based on The Value of THD Leakage Current. TELKOMNIKA Indonesian Journal of Electrical Engineering. 2009; 7(2):109-118.

26. Madi, Ali Mustafa, et al. "(Design Criteria for Silicone Rubber Insulators (Composite Insulator." Surman Journal of Science and Technology 2.3 (2020): 006-001.‏

27. Alsharif, A., Dalla, L. B., Essgaer, M., Ahmed, A. A., Rashid, T. A., & Alnnale, T. (2026). The Water-Energy-Food-Ecosystems (WEFE) Nexus in Libya: Challenges, Opportunities, and Integrated Governance Mechanisms. Al-Farooq Journal of Sciences, 2(Supplement 3), 1187-1198.

28. Brady J, Thermographer LI. Corona and Tracking Conditions in Metal-clad Switchgear Case Studies. Brady Infrared Inspections. 2006.

29. Begovic MM, editor. Electrical Transmission Systems and Smart Grids: Selected Entries from the Encyclopedia of Sustainability Science and Technology. Springer Science & Business Media; 2012 Dec 12.

30. Arora R, Mosch W. High voltage and electrical insulation engineering. John Wiley & Sons; 2011 Aug 4.

31. Ben Dalla. LOF, Asma Farhat MOHAMMED, ÖMER KARAL , Mansour Essgaer, Hala J. EL-KHOZONDAR, Yasser Fathi Nassar.(2026).Predictive Modeling of Daily Performance Ratio and Fault Classification in Photovoltaic Systems: A Comparative Deep Learning Study Using Real-World IoT Telemetry in a semi-arid desert climate.Trend and Advanced Studies in Engineering.Publisher’s Certification Number: 72273.ISBN: 978-625-8839-39-5. All Sciences Academy,https://www.allsciencesacademy.com/_files/ugd/13252f_9af950f099ca4c9d93d837f5dc82e130.pdf

32. Alsharif, A., Ibrahim, A. A., Waheshi, Y. A. A., Alsharif, M., Alhoudier, T. E., Esmail, E. M. A., & Dalla, L. O. F. B. (2025). An Analysis of Power Sector Investment by Technology in the Middle East and North Africa. African Journal of Academic Publishing in Science and Technology (AJAPST), 1(4), 25-39.

33. Dalla, L. O. B., KARAL, Ö., Degirmenci, A., CANBOLAT, H., ÇELEBI, F. V., & Nassar, Y. F. (2026). A Novel Hybrid Optimization Framework for Renewable Energy Investment in Hot Arid Regions: Integrating Time-Series Forecasting and AI-Driven Algorithms for Algeria’s Grid-Export Strategy. Fezzan University Scientific Journal, 62-76.

34. Madi, Ali Mustafa, Yadong He, and Lilong Jiang. "Design and testing of an improved profile for silicone rubber composite insulators." IEEE Transactions on Dielectrics and Electrical Insulation 24.5 (2017): 2930-2936.