Title :
Spotlight on transformer design
Author :
Georgilakis, Pavlos S. ; Amoiralis, Eleftherios I.
Author_Institution :
Dept. of Production Eng. & Manage., Tech. Univ. Crete, Chania
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;
Journal_Title :
Power and Energy Magazine, IEEE
DOI :
10.1109/MPAE.2007.264851
