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Electrical Power Transformer Modeling and Simulation for the Implementation of a Predictive Maintenance Approach

EasyChair Preprint no. 8082

5 pagesDate: May 24, 2022

Abstract

Transformer stations are key components of the electrical power transmission and distribution systems. Their failures are very costly, mainly because of the unavailability of electrical service they cause. Rapid and accurate identification of internal transformer faults is therefore a key function for efficient and safe operation.

Fault diagnosis of power transformers and related components is a vast field, requiring the correlation of various types of information such as oil analysis, electrical tests, protection tripping, etc. Such a diagnosis is usually established by a human expert from electrical or chemical test results, protection tripping or the history of the device. [13]

In this paper, we present the difference between a dry-type transformer and an oil transformer, in terms of several criteria. Then, we describe the failure modes and the diagnostic techniques, in order to give later an equivalent mathematical model of a single-phase transformer, to visualize the impact of the faults on the exploitable electrical components.

Keyphrases: diagnosis, failure modes, Faults, power transformer, Transformer maintenance

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:8082,
  author = {Hamza Ayar and Hasna Nhaila and M El Khaili},
  title = {Electrical Power Transformer Modeling and Simulation for the Implementation of a Predictive Maintenance Approach},
  howpublished = {EasyChair Preprint no. 8082},

  year = {EasyChair, 2022}}
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