AUTOMATIC DIAGNOSIS OF POWER TRANSFORMERS BASED ON DISSOLVED GAS ANALYSIS - FIRST LEVEL OF DIAGNOSIS USING VAC AND VSC INFERENCE METHODS |
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| Mladen Banovic, Josip Butorac |
- Abstract:
- Assessment of power transformer condition is very important for utilities, to ensure continuous power transmission and power supply. Therefore, different techniques are used for condition assessment, as off-line diagnostics and on-line monitoring. The off-line diagnostics has some time period between consecutive diagnoses, and during that period the condition is unknown. Diagnostic tools in monitoring system usually comprise comparison of values of monitored quantities to preset limits, and alarming if these limits are exceeded. In this way weak diagnostic capabilities are achieved.
Therefore, a new diagnosis model for assessment of condition of oil immersed power transformers was developed. This model is aimed to continuously and automatically diagnose transformer condition. The diagnosis principle is interpretation of dissolved gas analysis (DGA) data using several standardized interpretation methods. Then, on the basis of obtained diagnoses an overall diagnosis is inferred using VAC, VEV or VSC inference methods in a similar way as it is done by the human diagnostician.
The diagnostic model shows excellent application flexibility, high robustness and significant diagnostic accuracy. - Keywords:
- automatic diagnosis, power transformer, inference method
- Download:
- IMEKO-WC-2009-TC10-357.pdf
- DOI:
- -
- Event details
- Event name:
- XIX IMEKO World Congress
- Title:
Fundamental and Applied Metrology
- Place:
- Lisbon, PORTUGAL
- Time:
- 06 September 2009 - 11 September 2009