Neural network approach of harmonics detection
This paper describes a novel approach of harmonics detection in a power system which can be used as an alternative to the conventional approaches. The proposed approach uses the multilayer feed forward neural network to determine the harmonic components in a six-pulse bridge converter. In this paper...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | en |
| Published: |
1998
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| Subjects: | |
| Online Access: | http://eprints.utm.my/1975/1/Zin1998_NeuralNetworkApproachOfHarmonicsDetection.pdf http://eprints.utm.my/1975/ |
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| author | Zin, A.A.M Rokonuzzaman, M. Shaibon, H. Lo, K.I. |
| author_facet | Zin, A.A.M Rokonuzzaman, M. Shaibon, H. Lo, K.I. |
| author_sort | Zin, A.A.M |
| building | UTM Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Malaysia |
| content_source | UTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | This paper describes a novel approach of harmonics detection in a power system which can be used as an alternative to the conventional approaches. The proposed approach uses the multilayer feed forward neural network to determine the harmonic components in a six-pulse bridge converter. In this paper the detection of 5th, 7th, and 11th harmonic components from the distorted waves has been verified by means of the computer simulation. It is found that once trained by the learning algorithm, the neural network can determine each harmonic component very effectively and efficiently |
| format | Article |
| id | my.utm.eprints-1975 |
| institution | Universiti Teknologi Malaysia |
| language | en |
| publishDate | 1998 |
| record_format | eprints |
| spelling | my.utm.eprints-19752010-06-01T03:00:01Z http://eprints.utm.my/1975/ Neural network approach of harmonics detection Zin, A.A.M Rokonuzzaman, M. Shaibon, H. Lo, K.I. TK Electrical engineering. Electronics Nuclear engineering This paper describes a novel approach of harmonics detection in a power system which can be used as an alternative to the conventional approaches. The proposed approach uses the multilayer feed forward neural network to determine the harmonic components in a six-pulse bridge converter. In this paper the detection of 5th, 7th, and 11th harmonic components from the distorted waves has been verified by means of the computer simulation. It is found that once trained by the learning algorithm, the neural network can determine each harmonic component very effectively and efficiently 1998-03-03 Article PeerReviewed application/pdf en http://eprints.utm.my/1975/1/Zin1998_NeuralNetworkApproachOfHarmonicsDetection.pdf Zin, A.A.M and Rokonuzzaman, M. and Shaibon, H. and Lo, K.I. (1998) Neural network approach of harmonics detection. Energy Management and Power Delivery, 1998. Proceedings of EMPD '98. 1998 International Conference on , 2 . pp. 467-472. |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Zin, A.A.M Rokonuzzaman, M. Shaibon, H. Lo, K.I. Neural network approach of harmonics detection |
| title | Neural network approach of harmonics detection |
| title_full | Neural network approach of harmonics detection |
| title_fullStr | Neural network approach of harmonics detection |
| title_full_unstemmed | Neural network approach of harmonics detection |
| title_short | Neural network approach of harmonics detection |
| title_sort | neural network approach of harmonics detection |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://eprints.utm.my/1975/1/Zin1998_NeuralNetworkApproachOfHarmonicsDetection.pdf http://eprints.utm.my/1975/ |
| url_provider | http://eprints.utm.my/ |