Correlation of partial discharge occurrence in power transformer by using self organizing map, acoustic partial discharge and DGA

R. Samsudinl, Tiong Sk, Ahmad Qisti Ramli

Research output: Contribution to journalArticle

Abstract

Power transformer consists of components which are under consistent thermal and electrical stresses. The major component which degrades under these stresses is the paper insulation of power transformer. The degradation is accelerated by the existence of partial discharge in the transformer. The partial discharge activity in the transformer will generate gasses such as Hydrogen (H 2) and Methane (CH 4). According to IEC 60599, hydrogen may be produced by other ways than PD itself. The current predictive maintenance methodology practiced by utility that could detect partia discharge in the transformer is the dissolved gas analysis (DGA). Hydrogen is the main gas used for decision making process. In this project, acoustic partial discharge measurement technique was used together with the monthly generation rates of hydrogen and methane in proportion to Total Dissolved Combustible Gas (TDCG) method was used to identify the PD occurrence in power transformer. In this paper, a field testing was done on 120 transformers to verify the proposed method by using classification tool such as Self Organizing Map (SOM). The monthly generation rates of hydrogen and methane in proportion to TDCG method serves as useful information in identifying the partial discharge occurrence in power transformer. The correlation between the monthly generation rates of hydrogen and methane in proportion to TDCG and PD activities has been established by using SOM. As a result, the SOM gave two regions which represents the "with PD" and "no PD" region. This result has been confirmed by doing acoustic PD measurements.

Original languageEnglish
Pages (from-to)1239-1244
Number of pages6
JournalWorld Academy of Science, Engineering and Technology
Volume38
Publication statusPublished - 01 Feb 2009

Fingerprint

Gas fuel analysis
Power transformers
Partial discharges
Self organizing maps
Acoustics
Hydrogen
Methane
Gases
Insulation
Decision making
Degradation
Testing

All Science Journal Classification (ASJC) codes

  • Engineering(all)

Cite this

@article{8f97a80879174a22955f40e68755eeed,
title = "Correlation of partial discharge occurrence in power transformer by using self organizing map, acoustic partial discharge and DGA",
abstract = "Power transformer consists of components which are under consistent thermal and electrical stresses. The major component which degrades under these stresses is the paper insulation of power transformer. The degradation is accelerated by the existence of partial discharge in the transformer. The partial discharge activity in the transformer will generate gasses such as Hydrogen (H 2) and Methane (CH 4). According to IEC 60599, hydrogen may be produced by other ways than PD itself. The current predictive maintenance methodology practiced by utility that could detect partia discharge in the transformer is the dissolved gas analysis (DGA). Hydrogen is the main gas used for decision making process. In this project, acoustic partial discharge measurement technique was used together with the monthly generation rates of hydrogen and methane in proportion to Total Dissolved Combustible Gas (TDCG) method was used to identify the PD occurrence in power transformer. In this paper, a field testing was done on 120 transformers to verify the proposed method by using classification tool such as Self Organizing Map (SOM). The monthly generation rates of hydrogen and methane in proportion to TDCG method serves as useful information in identifying the partial discharge occurrence in power transformer. The correlation between the monthly generation rates of hydrogen and methane in proportion to TDCG and PD activities has been established by using SOM. As a result, the SOM gave two regions which represents the {"}with PD{"} and {"}no PD{"} region. This result has been confirmed by doing acoustic PD measurements.",
author = "R. Samsudinl and Tiong Sk and Ramli, {Ahmad Qisti}",
year = "2009",
month = "2",
day = "1",
language = "English",
volume = "38",
pages = "1239--1244",
journal = "World Academy of Science, Engineering and Technology",
issn = "2010-376X",
publisher = "World Academy of Science Engineering and Technology",

}

TY - JOUR

T1 - Correlation of partial discharge occurrence in power transformer by using self organizing map, acoustic partial discharge and DGA

AU - Samsudinl, R.

AU - Sk, Tiong

AU - Ramli, Ahmad Qisti

PY - 2009/2/1

Y1 - 2009/2/1

N2 - Power transformer consists of components which are under consistent thermal and electrical stresses. The major component which degrades under these stresses is the paper insulation of power transformer. The degradation is accelerated by the existence of partial discharge in the transformer. The partial discharge activity in the transformer will generate gasses such as Hydrogen (H 2) and Methane (CH 4). According to IEC 60599, hydrogen may be produced by other ways than PD itself. The current predictive maintenance methodology practiced by utility that could detect partia discharge in the transformer is the dissolved gas analysis (DGA). Hydrogen is the main gas used for decision making process. In this project, acoustic partial discharge measurement technique was used together with the monthly generation rates of hydrogen and methane in proportion to Total Dissolved Combustible Gas (TDCG) method was used to identify the PD occurrence in power transformer. In this paper, a field testing was done on 120 transformers to verify the proposed method by using classification tool such as Self Organizing Map (SOM). The monthly generation rates of hydrogen and methane in proportion to TDCG method serves as useful information in identifying the partial discharge occurrence in power transformer. The correlation between the monthly generation rates of hydrogen and methane in proportion to TDCG and PD activities has been established by using SOM. As a result, the SOM gave two regions which represents the "with PD" and "no PD" region. This result has been confirmed by doing acoustic PD measurements.

AB - Power transformer consists of components which are under consistent thermal and electrical stresses. The major component which degrades under these stresses is the paper insulation of power transformer. The degradation is accelerated by the existence of partial discharge in the transformer. The partial discharge activity in the transformer will generate gasses such as Hydrogen (H 2) and Methane (CH 4). According to IEC 60599, hydrogen may be produced by other ways than PD itself. The current predictive maintenance methodology practiced by utility that could detect partia discharge in the transformer is the dissolved gas analysis (DGA). Hydrogen is the main gas used for decision making process. In this project, acoustic partial discharge measurement technique was used together with the monthly generation rates of hydrogen and methane in proportion to Total Dissolved Combustible Gas (TDCG) method was used to identify the PD occurrence in power transformer. In this paper, a field testing was done on 120 transformers to verify the proposed method by using classification tool such as Self Organizing Map (SOM). The monthly generation rates of hydrogen and methane in proportion to TDCG method serves as useful information in identifying the partial discharge occurrence in power transformer. The correlation between the monthly generation rates of hydrogen and methane in proportion to TDCG and PD activities has been established by using SOM. As a result, the SOM gave two regions which represents the "with PD" and "no PD" region. This result has been confirmed by doing acoustic PD measurements.

UR - http://www.scopus.com/inward/record.url?scp=78651564811&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78651564811&partnerID=8YFLogxK

M3 - Article

VL - 38

SP - 1239

EP - 1244

JO - World Academy of Science, Engineering and Technology

JF - World Academy of Science, Engineering and Technology

SN - 2010-376X

ER -