Please use this identifier to cite or link to this item: http://prr.hec.gov.pk/jspui/handle/123456789/17115
Title: Methodology for fault Detection and Health Monitoring of Power Transformers
Authors: Aslam, Muhammad
Keywords: Engineering & Technology
Electrical Power Engineering
Issue Date: 2021
Publisher: University of Engineering & Technology Peshawar
Abstract: Power transformer is an important and the most expensive component of electrical power system. It is power transformer whose efficient and reliable operation ensures the reliable supply of electricity to the consumers. Any defects or failures in it can have serious impacts, both economically and technically. Moreover, aging in power transformers is a critical issue faced by the utility companies for years. A lot of failure cases have been reported in the recent years, which caused a substantial loss to the power sector and to the country. The replacement of such transformers requires a lot of time and cost which arises the need of health monitoring of power transformers. This study aims to use the concept of real-time monitoring of a three-phase transformer and examine its operation under different conditions in MATLAB Simulink. A transformer model is developed which can accurately evaluate the health condition and life expectancy by using the real-time data of 10/13 MVA, 132/11 kV grid power transformer. Moreover, a Transformer Monitoring Unit (TMU) for the transformer has been utilized to record the real time data from the grid power transformer. On the basis of simulation, a prototype testing facility was developed with thermal and UHF sensors incorporated in the high voltage laboratory of University of Engineering and Technology, Peshawar. The results of top-oil temperature with load cycle were consistent with the MATLAB Simulink results. The model is simulated with the recorded data and the health assessment has been done through Signal to-Noise ratio (SNR) technique in Simulink and real-time application. It was concluded that the noise voltage from UHF sensors was displayed as SNR with no PD activity was established to be about at +40dB. The actual results and simulated results with MATLAB were consistent. Thus the MATLAB/Simulink simulations can be used as predictive tool for obtaining information related to transformer health. Keywords: Health monitoring, Power-transformer, Partial Discharges, MATLAB-Simulink, Signal-to-Noise Ratio (SNR), Transformer Monitoring unit (TMU)
Gov't Doc #: 23327
URI: http://prr.hec.gov.pk/jspui/handle/123456789/17115
Appears in Collections:PhD Thesis of All Public / Private Sector Universities / DAIs.

Files in This Item:
File Description SizeFormat 
Muhammad Aslam 2021 power engg UET peshawar.pdfphd.Thesis4.45 MBAdobe PDFView/Open


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.