An approach to evaluate switching overvoltages during power system restoration
Transformer switching is one of the important stages during power system restoration. This switching can cause harmonic overvoltages that might damage some equipment and delay power system restoration. Core saturation on the energisation of a transformer with residual flux is a noticeable f...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Faculty of Technical Sciences in Cacak
2012-01-01
|
| Series: | Serbian Journal of Electrical Engineering |
| Subjects: | |
| Online Access: | http://www.doiserbia.nb.rs/img/doi/1451-4869/2012/1451-48691202171S.pdf |
| Summary: | Transformer switching is one of the important stages during power system
restoration. This switching can cause harmonic overvoltages that might damage
some equipment and delay power system restoration. Core saturation on the
energisation of a transformer with residual flux is a noticeable factor in
harmonic overvoltages. This work uses artificial neural networks (ANN) in
order to estimate the temporary overvoltages (TOVs) due to transformer
energisation. In the proposed methodology, the Levenberg-Marquardt method is
used to train the multilayer perceptron. The developed ANN is trained with
the worst case of switching condition, and tested for typical cases.
Simulated results for a partial 39-bus New England test system, show the
proposed technique can accurately estimate the peak values and durations of
switching overvoltages. |
|---|---|
| ISSN: | 1451-4869 2217-7183 |