Title :
Optimal transposition design of transformer windings by Genetic Algorithms
Author :
Bai Baodong ; Xie Dexin ; Cui Jiefan ; Mohammed, Osama A.
Author_Institution :
Shenyang Polytech. Univ.
fDate :
11/1/1995 12:00:00 AM
Abstract :
An optimal transposition design of transformer windings using Genetic Algorithms (GAs) is presented. The objective is to provide the best transposition positions to obtain the lowest circulating current losses in the parallel conductors. The GAs procedure for solving multiparameter and constrained problems is described in detail. In the optimization process, the losses are calculated by a combined method of Magnetic field and Electric circuit. The proper value ranges of GAs operators (mutation and recombination) are examined in performance experiments. The improved transposition data are achieved by applying the approach to a large transformer
Keywords :
finite element analysis; genetic algorithms; power transformers; transformer magnetic circuits; transformer windings; electric circuit; genetic algorithms; lowest circulating current losses; magnetic field; mutation; optimal transposition design; parallel conductors; recombination; transformer windings; Algorithm design and analysis; Biological cells; Conductors; Genetic algorithms; Genetic mutations; Magnetic circuits; Magnetic fields; Optimization methods; Power transformers; Windings;
Journal_Title :
Magnetics, IEEE Transactions on