Prediction modelling of power transformer health index

Also available in printed version

Bibliographic Details
Main Author: Tajul Ariffin Aman
Other Authors: Saifulnizam Abd. Khalid, supervisor
Format: Master's thesis
Language:English
Published: Universiti Teknologi Malaysia 2025
Subjects:
Online Access:https://utmik.utm.my/handle/123456789/39821
Abstract Abstract here
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author Tajul Ariffin Aman
author2 Saifulnizam Abd. Khalid, supervisor
author_facet Saifulnizam Abd. Khalid, supervisor
Tajul Ariffin Aman
author_sort Tajul Ariffin Aman
description Also available in printed version
format Master's thesis
id utm-123456789-39821
institution Universiti Teknologi Malaysia
language English
publishDate 2025
publisher Universiti Teknologi Malaysia
record_format dspace
record_pdf Abstract
spelling utm-123456789-398212025-08-21T05:45:52Z Prediction modelling of power transformer health index Tajul Ariffin Aman Saifulnizam Abd. Khalid, supervisor Electrical engineering Also available in printed version Power transformer is a critical asset in Grid System and its failure can cause major downtime in the electrical supply with revenue losses to the power utilities. The reliability and availability of electrical network is highly depending on the high performance of the power transformer. The main objective of this thesis is to predict the health index of power transformer based on their individual pattern and characteristic. Each transformer make has different gases produced and detected by performing Dissolved Gas Analysis (DGA) test. Different transformer make will give different conditions of the transformer health index that was investigated in this research. The changes of the insulating oil properties are due to different value of gases produce was found in the transformer make and gas level response. The analysis using Matrix Laboratory (MATLAB) indicates that different combustible gases value gives different modelling pattern to identify the different make of transformer conditions based on their health index. In this research, the unique characteristic pattern of each transformer make was determined by single or double DGA gases above limit. Different make of power transformer usually using different make of transformer oil but with similar standard and quality requested from the utility. The combustible gases such as Methane (CH4), Ethylene (C2H4) and Ethane (C2H6) value may different from one manufacturer with another. Transformer with high Ethylene (C2H4) value but less than 65ppm, 70ppm, 80ppm, 100ppmand 120ppm show Good Condition of Health Index with different graphical pattern by different make of power transformer. Both Ethylene (C2H4) and Ethane (C2H6) gases with high value but less than 150ppm still show Good Condition of Health Index. High Methane (CH4) gas that more than 200ppm and high Ethane (C2H6) gas that more than 500ppm show Moderate Condition of health index. High Methane (CH4) gas but less than 130ppm and high Ethane (C2H6) gas but less than 210ppm also show Moderate Condition of Health Index. This research has demonstrated that different type of transformer will be having different type of gas produced and the pattern characteristic will show different type of health index. fahmimoksen UTM 121 p. Thesis (Sarjana Falsafah (Kejuruteraan Eletrik)) - Universiti Teknologi Malaysia, 2023 2025-03-05T04:54:52Z 2025-03-05T04:54:52Z 2023 Master's thesis https://utmik.utm.my/handle/123456789/39821 vital:156320 valet-20240313-143457 ENG Closed Access UTM Complete Unpublished Completion application/pdf Universiti Teknologi Malaysia
spellingShingle Electrical engineering
Tajul Ariffin Aman
Prediction modelling of power transformer health index
thesis_level Master
title Prediction modelling of power transformer health index
title_full Prediction modelling of power transformer health index
title_fullStr Prediction modelling of power transformer health index
title_full_unstemmed Prediction modelling of power transformer health index
title_short Prediction modelling of power transformer health index
title_sort prediction modelling of power transformer health index
topic Electrical engineering
url https://utmik.utm.my/handle/123456789/39821
work_keys_str_mv AT tajulariffinaman predictionmodellingofpowertransformerhealthindex