Rectifier power transformer design by intelligent optimization techniques
Two stochastic methods for locating global minimum and optimal design parameters of a rectifier power transformer, by Genetic Algorithm (GA) and Simulated Annealing (SA) are presented. A closed form expression for actual phase current waveform of the rectifier transformer is derived and a comparison...
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| 主要な著者: | , |
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| フォーマット: | Conference or Workshop Item |
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2008
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| オンライン･アクセス: | http://eprints.utp.edu.my/261/1/paper.pdf http://www.scopus.com/inward/record.url?eid=2-s2.0-63049101223&partnerID=40&md5=84d7b281d32faa3b6ce2fa37c7769d75 http://eprints.utp.edu.my/261/ |
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| 要約: | Two stochastic methods for locating global minimum and optimal design parameters of a rectifier power transformer, by Genetic Algorithm (GA) and Simulated Annealing (SA) are presented. A closed form expression for actual phase current waveform of the rectifier transformer is derived and a comparison is made with the approximate waveform normally considered for fixing the transformer rating. The design parameters of the transformer obtained by Powell's direct search method are compared with those from GA and SA. The optimal results demonstrated by an example show the potential for implementation of GA as an efficient search technique for design optimization of rectifier power transformers. A discussion on the limitations and variation of GA parameters while minimizing the single and multi-objective functions satisfying the performance constraints on the proposed optimal design concludes the paper. © 2008 IEEE.
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