期刊名称：International Journal of Electrical and Computer Engineering
电子版ISSN：2088-8708
出版年度：2011
卷号：1
期号：2
页码：102-109
语种：English
出版社：Institute of Advanced Engineering and Science (IAES)
摘要：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)DOI:http://dx.doi.org/10.11591/ijece.v1i2.88
其他摘要：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) DOI: http://dx.doi.org/10.11591/ijece.v1i2.88
Loading...
