Spotlight on transformer design

Author

Georgilakis, Pavlos S. ; Amoiralis, Eleftherios I.

Author_Institution

Dept. of Production Eng. & Manage., Tech. Univ. Crete, Chania

Volume

5

Issue

1

fYear

2007

Firstpage

40

Lastpage

50

Abstract

This paper presents an integrated artificial intelligence technique to achieve an optimum design of a transformer. AI is used to reach an optimum transformer design solution for the winding material selection problem. To be more precise, decision trees (DTs) and adaptive trained neural networks (ATNNs) are combined with the aim of selecting the appropriate winding material (Cu or Al) to design an optimum distribution transformer. Both methodologies have emerged as important tools for classification

Keywords

aluminium; artificial intelligence; copper; decision trees; design engineering; electric machine analysis computing; neural nets; power transformers; transformer windings; adaptive trained neural networks; decision trees; integrated artificial intelligence technique; optimum distribution transformer; transformer design; winding material selection; Artificial intelligence; Copper; Cost function; Design optimization; Electrical equipment industry; Environmental economics; Manufacturing industries; Power generation economics; Stock markets; Windings;

fLanguage

English

Journal_Title

Power and Energy Magazine, IEEE

Publisher

ieee

ISSN

1540-7977

Type

jour

DOI

10.1109/MPAE.2007.264851

Filename

4042139