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Artificial neural networks in high voltage transmission line problems

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Εθνικό Μετσόβιο Πολυτεχνείο   

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Artificial neural networks in high voltage transmission line problems (EN)
Maris, TI (EN)
Ekonomou, L (EN)
Stathopulos, IA (EN)
Kontargyri, VT (EN)
Kourtesi, St (EN)
journalArticle (EN)
2014-03-01T01:25:56Z
2007 (EN)
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)
Engineering, Multidisciplinary (EN)
Instruments & Instrumentation (EN)
Electric potential (EN)
Critical flashover voltage (EN)
Electric lines (EN)
High voltage transmission lines (EN)
Computation theory (EN)
Neural networks (EN)
Artificial neural networks (EN)
Problem solving (EN)
Mathematical models (EN)
Polluted insulators (EN)
Measurement Science and Technology (EN)
English
IOP PUBLISHING LTD (EN)
Εθνικό Μετσόβιο Πολυτεχνείο
Ψηφιακό Αποθετήριο της Κεντρικής Βιβλιοθήκης του ΕΜΠ | Dspace@NTUA
Κεντρική Βιβλιοθήκη Ε.Μ.Π.
Ιδρυματικό Αποθετήριο
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