Fault identification of in-service power transformer using depolarization current analysis
Preventive diagnostic testing of in-service power transformers require system outage and expert's knowledge and experiences in interpreting the measurement results. The chemical oil analysis may cause significant variance to measurement results due to the different practices in oil sampling, st...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Published: |
Institute of Advanced Engineering and Science
2017
|
| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/77100/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020889936&doi=10.11591%2fijece.v7i2.pp559-567&partnerID=40&md5=c1828a553d06f5cc16037adea7f3dea9 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | Preventive diagnostic testing of in-service power transformers require system outage and expert's knowledge and experiences in interpreting the measurement results. The chemical oil analysis may cause significant variance to measurement results due to the different practices in oil sampling, storage, handling and transportation. Thus, a cost effective measuring technique by means of a simpler method that is able provide an accurate measurement results is highly required. The extended application of Polarization and Depolarization Current (PDC) measurement for characterization of different faults conditions on in-service power transformer has been presented in this paper. The oil sample from in-service power transformers with normal and 3 different faults type conditions were sampled and tested for Dissolved Gases Analysis (DGA) and PDC measurement. The DGA results was used to confirm type of faults inside the transformer while the PDC pattern of oil with normal, partial discharge, overheating and arcing were correlated to the oil sample conditions. The analysis result shows that depolarization current provides significant information to defferenciate fault types in power transformer. Thus this finding provides a new alternative in identifying incipient faults and such knowledge can be used to avoid catastrophic failures of power transformers. |
|---|