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An Improved Genetic Algorithm for Optimum Design of Power Transformers
作者姓名:HAN Li  LI Hui  YANG Shun chang  HE Bei
摘    要:In order to enhance the ability of global searching for genetic algorithm in power transformers optimization design, some interrelated key technique problems such as encoding method, genetic operators, restrict condition, fitness function for the traditional genetic algorithm are further reformed. An Improved Genetic Algorithm (IGA) is developed. The optimal results of a representative mathematical example show that IGA has high efficiency of global searching. At the same time, a multi-objective algorithm based on IGA is studied in this paper. IGA is applied to the single and multi-objective optimum design of S9 power transformers for the first time. All the achievements in the paper are verified a practical S9-1000/10 kV power transformer. All the optimization results are satisfactory and show that IGA has powerful ability of global searching, excellent solution precision and has a bright application prospect in the fields of power transformers design.

关 键 词:power  transformers  optimum  design  improved  genetic  algorithm

An Improved Genetic Algorithm for Optimum Design of Power Transformers
HAN Li,LI Hui,YANG Shun chang,HE Bei.An Improved Genetic Algorithm for Optimum Design of Power Transformers[J].Storage & Process,2002(9):8.
Authors:HAN Li  LI Hui  YANG Shun chang  HE Bei
Abstract:In order to enhance the ability of global searching for genetic algorithm in power transformers optimization design, some interrelated key technique problems such as encoding method, genetic operators, restrict condition, fitness function for the traditional genetic algorithm are further reformed. An Improved Genetic Algorithm (IGA) is developed. The optimal results of a representative mathematical example show that IGA has high efficiency of global searching. At the same time, a multi-objective algorithm based on IGA is studied in this paper. IGA is applied to the single and multi-objective optimum design of S9 power transformers for the first time. All the achievements in the paper are verified a practical S9-1000/10 kV power transformer. All the optimization results are satisfactory and show that IGA has powerful ability of global searching, excellent solution precision and has a bright application prospect in the fields of power transformers design.
Keywords:power transformers  optimum design  improved genetic algorithm
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