Condition Monitoring of Oil Filled Transformer using Artificial Neural Network @ Review |
Author(s): |
| Trivedi Jay Jayesh , GEC Bhuj |
Keywords: |
| Oil Filled transformer, Artificial Neural Network, Dissolved Gas Analysis |
Abstract |
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Transformers are widely used equipment in power system. Continuity of power is one of the major requirements of today’s power system. Any fault in power transformer will lead to serious problem and continuity of power supply is affected. In order to avoid catastrophic failure and reduce outage rates fault detection in its initial stage is required. Incipient faults lead to thermal and electrical stresses on transformer leading to decomposition of oil and insulation. This decomposition will generate gases due to decomposition. Thus based on this gas concentration a Dissolved gas Analysis (DGA) is used. In this paper various DGA techniques are studied through various papers. Then an ANN approach to this method has also been reviewed. After applying ANN approach to conventional methods. Accuracy was found to have improved considerably. |
Other Details |
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Paper ID: IJSRDV6I20227 Published in: Volume : 6, Issue : 2 Publication Date: 01/05/2018 Page(s): 232-234 |
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