Using a neural network for transformer protection
Conference
·
OSTI ID:438728
- Powertech Labs. Inc., Surrey, British Columbia (Canada)
- Univ. of Saskatchewan, Saskatoon, Saskatchewan (Canada)
- Univ. of British Columbia, Vancouver, British Columbia (Canada)
A new method of using artificial neural networks (ANN) to identify the magnetizing inrush currents that may occur in transformers during start-up is developed in this paper. The method is based on the fact that magnetizing inrush current has large harmonic components. Using the back-propagation algorithm, a feed-forward neural network (FFNN) has been trained to discriminate between transformer magnetizing inrush and no-inrush currents. The trained network was verified using test data from a laboratory transformer. Results presented in this paper indicate that the ANN based inrush detector is efficient with good performance and reliability.
- OSTI ID:
- 438728
- Report Number(s):
- CONF-951136--; ISBN 0-7803-2981-3
- Country of Publication:
- United States
- Language:
- English
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