Surface Discharge Analysis of High Voltage Glass Insulators Using Ultraviolet Pulse Voltage

Saiful Mohammad Iezham Suhaimi, Nouruddeen Bashir, Nor Asiah Muhamad, Nurun Najah Abdul Rahim, Noor Azlinda Ahmad and Mohd Nazri Abdul Rahman
Additional contact information
Saiful Mohammad Iezham Suhaimi: Tenaga Nasional Berhad, Tumpat 16250, Kelantan, Malaysia
Nouruddeen Bashir: Power Equipment & Electrical Machinery Development Institute (PEEMADI), National Agency for Science and Engineering Infrastructure (NASENI), P.M.B 1029 Okene, Kogi State, Nigeria
Nor Asiah Muhamad: School of Electrical and Electronic Engineering, Universiti Sains Malaysia (USM), 14300 Nibong Tebal, Malaysia
Nurun Najah Abdul Rahim: School of Electrical and Electronic Engineering, Universiti Sains Malaysia (USM), 14300 Nibong Tebal, Malaysia
Noor Azlinda Ahmad: Institute of High Voltage and High Current (IVAT), Universiti Teknologi Malaysia, 81310 Skudai, Johor, Malaysia
Mohd Nazri Abdul Rahman: Faculty of Education, University of Malaya, 50603 Kuala Lumpur, Malaysia

Energies, 2019, vol. 12, issue 2, 1-26

Abstract: Surface discharges are precursors to flashover. To pre-empt the occurrence of flashover incidents, utility companies need to regularly monitor the condition of line insulators. Recent studies have shown that monitoring of UV signals emitted by surface discharges of insulators is a promising technique. In this work, the UV signals’ time and frequency components of a set of contaminated and field-aged insulator under varying contamination levels and degrees of ageing were studied. Experimental result shows that a strong correlation exists between the discharge intensity levels under varying contamination levels and degree of ageing. As the contamination level increases, the discharge level of the insulator samples also intensifies, resulting in the increase of total harmonic distortion and fundamental frequencies. Total harmonic distortion and fundamental frequencies of the UV signals were employed to develop a technique based on artificial neural networks (ANNs) to classify the flashover prediction based on the discharge intensity levels of the insulator samples. The results of the ANN simulation showed 87% accuracy in the performance index. This study illustrates that the UV pulse detection method is a potential tool to monitor insulator surface conditions during service.

Keywords: contamination flashover; ultraviolet; glass insulator; total harmonic distortion; artificial neutral network; surface discharges (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
https://www.mdpi.com/1996-1073/12/2/204/pdf (application/pdf)
https://www.mdpi.com/1996-1073/12/2/204/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:12:y:2019:i:2:p:204-:d:196273

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().