Title :
Research of transformer optimal design modeling and intelligent algorithm
Author :
Shuang Zhang ; Qinghe Hu ; Xingwei Wang ; Dingwei Wang
Author_Institution :
Software Coll., Northeastern Univ., Shenyang, China
Abstract :
The paper studies transformer optimal design, establishes optimal transformer model based on total owning cost. It adopts penalty function to process objective function with weighted coefficients. For prematurity and low speed of convergence of Simple Genetic Algorithm, improved adaptive genetic algorithm is adopted. It increases crossover and mutation rates, and improves fitness function. It is adopted to search for minimum total owning cost of transformer. The result shows that the algorithm performs well, increases converging speed and improves quality of solution.
Keywords :
genetic algorithms; power transformers; fitness function; intelligent algorithm; penalty function; simple genetic algorithm; total owning cost; transformer optimal design modeling; Algorithm design and analysis; Genetic algorithms; Genetics; Oil insulation; Optimization; Windings; Wires; Genetic algorithm; Optimal design; Total owning cost; Transformer;
Conference_Titel :
Control and Decision Conference (CCDC), 2011 Chinese
Conference_Location :
Mianyang
Print_ISBN :
978-1-4244-8737-0
DOI :
10.1109/CCDC.2011.5968174