dc.contributor.author |
Ekonomou, L |
en |
dc.contributor.author |
Kontargyri, VT |
en |
dc.contributor.author |
Kourtesi, St |
en |
dc.contributor.author |
Maris, TI |
en |
dc.contributor.author |
Stathopulos, IA |
en |
dc.date.accessioned |
2014-03-01T01:25:56Z |
|
dc.date.available |
2014-03-01T01:25:56Z |
|
dc.date.issued |
2007 |
en |
dc.identifier.issn |
0957-0233 |
en |
dc.identifier.uri |
https://dspace.lib.ntua.gr/xmlui/handle/123456789/17831 |
|
dc.subject |
Artificial neural networks |
en |
dc.subject |
Critical flashover voltage |
en |
dc.subject |
High voltage transmission lines |
en |
dc.subject |
Polluted insulators |
en |
dc.subject.classification |
Engineering, Multidisciplinary |
en |
dc.subject.classification |
Instruments & Instrumentation |
en |
dc.subject.other |
Computation theory |
en |
dc.subject.other |
Electric potential |
en |
dc.subject.other |
Mathematical models |
en |
dc.subject.other |
Neural networks |
en |
dc.subject.other |
Problem solving |
en |
dc.subject.other |
Critical flashover voltage |
en |
dc.subject.other |
High voltage transmission lines |
en |
dc.subject.other |
Polluted insulators |
en |
dc.subject.other |
Electric lines |
en |
dc.subject.other |
Computation theory |
en |
dc.subject.other |
Electric lines |
en |
dc.subject.other |
Electric potential |
en |
dc.subject.other |
Mathematical models |
en |
dc.subject.other |
Neural networks |
en |
dc.subject.other |
Problem solving |
en |
dc.title |
Artificial neural networks in high voltage transmission line problems |
en |
heal.type |
journalArticle |
en |
heal.identifier.primary |
10.1088/0957-0233/18/7/058 |
en |
heal.identifier.secondary |
http://dx.doi.org/10.1088/0957-0233/18/7/058 |
en |
heal.identifier.secondary |
058 |
en |
heal.language |
English |
en |
heal.publicationDate |
2007 |
en |
heal.abstract |
According to the literature high voltage transmission line problems are faced using conventional analytical methods, which include in most cases empirical and/or approximating equations. Artificial intelligence and more specifically artificial neural networks (ANN) are addressed in this work, in order to give accurate solutions to high voltage transmission line problems using in the calculations only actual field data. Two different case studies are studied, i.e., the estimation of critical flashover voltage on polluted insulators and the estimation of lightning performance of high voltage transmission lines. ANN models are developed and are tested on operating high voltage transmission lines and polluted insulators, producing very satisfactory results. These two ANN models can be used in electrical engineers' studies aiming at the more effective protection of high voltage equipment. © 2007 IOP Publishing Ltd. |
en |
heal.publisher |
IOP PUBLISHING LTD |
en |
heal.journalName |
Measurement Science and Technology |
en |
dc.identifier.doi |
10.1088/0957-0233/18/7/058 |
en |
dc.identifier.isi |
ISI:000247400800062 |
en |
dc.identifier.volume |
18 |
en |
dc.identifier.issue |
7 |
en |
dc.identifier.spage |
2239 |
en |
dc.identifier.epage |
2244 |
en |