Optimal distribution transformers assembly using an adaptable neural network-generic algorithm scheme

Doulamis, ND; Doulamis, AD

dc.contributor.author	Doulamis, ND	en
dc.contributor.author	Doulamis, AD	en
dc.date.accessioned	2014-03-01T02:42:08Z
dc.date.available	2014-03-01T02:42:08Z
dc.date.issued	2002	en
dc.identifier.issn	08843627	en
dc.identifier.uri	https://dspace.lib.ntua.gr/xmlui/handle/123456789/30808
dc.subject	Iron Loss Prediction	en
dc.subject	Neural networks-Genetic	en
dc.subject.other	Electric transformers	en
dc.subject.other	Genetic algorithms	en
dc.subject.other	Iron	en
dc.subject.other	Optimal distribution transformers	en
dc.subject.other	Neural networks	en
dc.title	Optimal distribution transformers assembly using an adaptable neural network-generic algorithm scheme	en
heal.type	conferenceItem	en
heal.identifier.primary	10.1109/ICSMC.2002.1176345	en
heal.identifier.secondary	http://dx.doi.org/10.1109/ICSMC.2002.1176345	en
heal.publicationDate	2002	en
heal.abstract	This paper presents an effective method to reduce the iron losses of wound core distribution transformers based on a combined neural network-genetic algorithm approach. The originality of the work presented in this paper is that it tackles the iron loss reduction problem during the transformer production phase, while previous works were concentrated on the design phase. More specifically, neural networks effectively use measurements taken at the first stages of core construction hi order to predict the iron tosses of the assembled transformers, while genetic algorithms are used to improve the grouping process of the individual cores by reducing iron losses of assembled transformers. The proposed method has been tested on a transformer manufacturing industry. The results demonstrate the feasibility and practicality of this approach. Significant reduction of transformer iron losses is observed in comparison to the current practice leading to important economic savings for the transformer manufacturer.	en
heal.journalName	Proceedings of the IEEE International Conference on Systems, Man and Cybernetics	en
dc.identifier.doi	10.1109/ICSMC.2002.1176345	en
dc.identifier.volume	5	en
dc.identifier.spage	151	en
dc.identifier.epage	156	en