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Design Optimization of High-Frequency Power Transformer by Genetic Algorithm and Simulated Annealing

机译:基于遗传算法和模拟退火算法的高频电力变压器设计优化

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This paper highlights the transformer design optimization problem. The objective of transformer design optimization problem requires minimizing the total mass (or cost) of the core and wire material by satisfying constraints imposed by international standards and transformer user specification. The constraints include appropriate limits on efficiency, voltage regulation, temperature rise, no-load current and winding fill factor. The design optimizations seek a constrained minimum mass (or cost) solution by optimally setting the transformer geometry parameters and require magnetic properties. This paper shows the above design problems can be formulated in genetic algorithm(GA) and simulated annealing (SA) format. The importance of the GA and SA format stems for two main features. First it provides efficient and reliable solution for the design optimization problem with several variables. Second, it guaranteed that the obtained solution is global optimum. This paper includes a demonstration of the application of the GP technique to transformer design. Key word—Optimization, Power Transformer, Genetic Algorithm (GA), Simulated Annealing Technique (SA)
机译:本文重点介绍了变压器设计的优化问题。变压器设计优化问题的目的是通过满足国际标准和变压器用户规范施加的约束,使铁芯和线材的总质量(或成本)最小化。这些限制包括对效率,电压调节,温度上升,空载电流和绕组填充系数的适当限制。设计优化通过优化设置变压器几何参数并要求磁性能来寻求受约束的最小质量(或成本)解决方案。本文表明上述设计问题可以用遗传算法(GA)和模拟退火(SA)格式来表达。 GA和SA格式的重要性源于两个主要特征。首先,它为具有多个变量的设计优化问题提供了高效可靠的解决方案。其次,它保证了所获得的解决方案是全局最优的。本文演示了GP技术在变压器设计中的应用。关键词—优化,电力变压器,遗传算法(GA),模拟退火技术(SA)

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