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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Main Authors: K.S., Rama Rao, Md. Hasan , K.N.
Format: Conference or Workshop Item
Language:English
Published: 2008
Subjects:
Online Access:http://scholars.utp.edu.my/id/eprint/261/
http://scholars.utp.edu.my/id/eprint/261/1/paper.pdf
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author K.S., Rama Rao
Md. Hasan , K.N.
author_facet K.S., Rama Rao
Md. Hasan , K.N.
author_sort K.S., Rama Rao
building UTP Institutional Repository
collection Online Access
description 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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institution Universiti Teknologi Petronas
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spelling oai:scholars.utp.edu.my:2612017-01-19T08:26:32Z http://scholars.utp.edu.my/id/eprint/261/ Rectifier power transformer design by intelligent optimization techniques K.S., Rama Rao Md. Hasan , K.N. TK Electrical engineering. Electronics Nuclear engineering 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. 2008 Conference or Workshop Item NonPeerReviewed application/pdf en http://scholars.utp.edu.my/id/eprint/261/1/paper.pdf K.S., Rama Rao and Md. Hasan , K.N. (2008) Rectifier power transformer design by intelligent optimization techniques. In: 2008 IEEE Electrical Power and Energy Conference - Energy Innovation, 6 October 2008 through 7 October 2008, Vancouver, BC. http://www.scopus.com/inward/record.url?eid=2-s2.0-63049101223&partnerID=40&md5=84d7b281d32faa3b6ce2fa37c7769d75
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
K.S., Rama Rao
Md. Hasan , K.N.
Rectifier power transformer design by intelligent optimization techniques
title Rectifier power transformer design by intelligent optimization techniques
title_full Rectifier power transformer design by intelligent optimization techniques
title_fullStr Rectifier power transformer design by intelligent optimization techniques
title_full_unstemmed Rectifier power transformer design by intelligent optimization techniques
title_short Rectifier power transformer design by intelligent optimization techniques
title_sort rectifier power transformer design by intelligent optimization techniques
topic TK Electrical engineering. Electronics Nuclear engineering
url http://scholars.utp.edu.my/id/eprint/261/
http://scholars.utp.edu.my/id/eprint/261/
http://scholars.utp.edu.my/id/eprint/261/1/paper.pdf