Title :
GA design for efficiency optimization of a superconducting generator
Author :
Han, Sang-II ; Muta, Itsuya ; Hoshino, Tsutomu ; Nakamura, Taketsune
Author_Institution :
Graduate Sch. of Eng., Kyoto Univ., Japan
Abstract :
This paper deals with a design method for the efficiency optimization of 223 MVA class superconducting generator. In consideration of the electrical characteristics based on electromagnetic analysis, GA (genetic algorithm), which has been successfully applied to various design problems in electric machines and devices, is used as an approach method of the optimized design with some variables and constraints. The results designed by this method are found to be reasonable and effective as compared with those obtained by the methods of trial and error until now
Keywords :
AC generators; genetic algorithms; superconducting coils; superconducting machines; 223 MVA; efficiency optimization; electric machines; electrical characteristics; electromagnetic analysis; genetic algorithm; optimized design; superconducting coil; superconducting generator; Air gaps; Algorithm design and analysis; Design methodology; Design optimization; Magnetic flux; Magnetic materials; Rotors; Superconducting coils; Superconducting magnets; Superconducting materials;
Conference_Titel :
Electrical Machines and Systems, 2001. ICEMS 2001. Proceedings of the Fifth International Conference on
Conference_Location :
Shenyang
Print_ISBN :
7-5062-5115-9
DOI :
10.1109/ICEMS.2001.970631
