| dc.contributor.author |
Ekonomou, L |
en |
| dc.contributor.author |
Oikonomou, DS |
en |
| dc.contributor.author |
Maris, TI |
en |
| dc.date.accessioned |
2014-06-06T06:48:11Z |
|
| dc.date.available |
2014-06-06T06:48:11Z |
|
| dc.date.issued |
2008 |
en |
| dc.identifier.uri |
http://dx.doi.org/10.1109/NEUREL.2008.4685562 |
en |
| dc.identifier.uri |
http://62.217.125.90/xmlui/handle/123456789/4001 |
|
| dc.subject |
Artificial neural networks |
en |
| dc.subject |
Critical flashover voltage |
en |
| dc.subject |
Lightning performance |
en |
| dc.subject |
Multi layer perceptrons |
en |
| dc.subject |
Polluted insulators |
en |
| dc.subject |
Radial basis function networks |
en |
| dc.subject |
Transmission lines |
en |
| dc.subject.other |
Artificial intelligence |
en |
| dc.subject.other |
Attitude control |
en |
| dc.subject.other |
Backpropagation |
en |
| dc.subject.other |
Cybernetics |
en |
| dc.subject.other |
DC generators |
en |
| dc.subject.other |
Electric insulators |
en |
| dc.subject.other |
Electric lines |
en |
| dc.subject.other |
Feedforward neural networks |
en |
| dc.subject.other |
Flashover |
en |
| dc.subject.other |
Image segmentation |
en |
| dc.subject.other |
Lightning |
en |
| dc.subject.other |
Metropolitan area networks |
en |
| dc.subject.other |
Networks (circuits) |
en |
| dc.subject.other |
Outages |
en |
| dc.subject.other |
Pattern recognition systems |
en |
| dc.subject.other |
Power transmission |
en |
| dc.subject.other |
Radial basis function networks |
en |
| dc.subject.other |
Transmission line theory |
en |
| dc.subject.other |
Vegetation |
en |
| dc.subject.other |
Wireless sensor networks |
en |
| dc.subject.other |
Artificial neural networks |
en |
| dc.subject.other |
Critical flashover voltage |
en |
| dc.subject.other |
Lightning performance |
en |
| dc.subject.other |
Multi layer perceptrons |
en |
| dc.subject.other |
Polluted insulators |
en |
| dc.subject.other |
Transmission lines |
en |
| dc.subject.other |
Neural networks |
en |
| dc.title |
Outages calculations for overhead high voltage transmission lines using artificial neural networks |
en |
| heal.type |
conferenceItem |
en |
| heal.identifier.primary |
10.1109/NEUREL.2008.4685562 |
en |
| heal.identifier.secondary |
4685562 |
en |
| heal.publicationDate |
2008 |
en |
| heal.abstract |
The paper presents an alternative approach for the outages calculations of transmission lines using artificial intelligence and more specifically artificial neural networks (ANNs). In contrast to the existing conventional-analytical techniques and simulations which are using in the calculations empirical and/or approximating equations, this approach is based only on actual field data and measurements. The proposed approach is applied on high voltage transmission lines in order to calculate the lightning outages and on polluted insulators in order to calculate the critical flashover voltage. The obtained results are very close to the actual ones for both case studies, something which clearly implies that the ANN approach is well working and has an acceptable accuracy. ©2008 IEEE. |
en |
| heal.journalName |
9th Symposium on Neural Network Applications in Electrical Engineering, NEUREL 2008 Proceedings |
en |
| dc.identifier.doi |
10.1109/NEUREL.2008.4685562 |
en |
| dc.identifier.spage |
57 |
en |
| dc.identifier.epage |
61 |
en |