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Practical neural network approach for power generation automation

This paper presents a practical artificial neural network (ANN) based technique for the automation of power generation scheduling based on the consumer's load profile. A multi-layered neural network with back propagation learning algorithm is used to predict the required power generation to ful...

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主要な著者: Moghavvemi, M., Yang, S.S., Kashem, M.A.
フォーマット: Conference or Workshop Item
出版事項: 1998
主題:
TA Engineering (General). Civil engineering (General)
オンライン･アクセス:http://eprints.um.edu.my/9709/
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record_format eprints
spelling my.um.eprints.97092017-11-23T01:46:11Z http://eprints.um.edu.my/9709/ Practical neural network approach for power generation automation Moghavvemi, M. Yang, S.S. Kashem, M.A. TA Engineering (General). Civil engineering (General) This paper presents a practical artificial neural network (ANN) based technique for the automation of power generation scheduling based on the consumer's load profile. A multi-layered neural network with back propagation learning algorithm is used to predict the required power generation to fulfill the consumer's demands. The proposed technique has been applied to a typical co-generation power plant of 4×8 MW rating. Test results indicates that the ANN model can automatically perform generator scheduling accurately. 1998 Conference or Workshop Item PeerReviewed Moghavvemi, M. and Yang, S.S. and Kashem, M.A. (1998) Practical neural network approach for power generation automation. In: Proceedings of the 1998 2nd International Conference on Energy Management and Power Delivery (EMPD'98), 3 - 5 March 1998, Singapore.
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic TA Engineering (General). Civil engineering (General)
spellingShingle TA Engineering (General). Civil engineering (General)
Moghavvemi, M.
Yang, S.S.
Kashem, M.A.
Practical neural network approach for power generation automation
description This paper presents a practical artificial neural network (ANN) based technique for the automation of power generation scheduling based on the consumer's load profile. A multi-layered neural network with back propagation learning algorithm is used to predict the required power generation to fulfill the consumer's demands. The proposed technique has been applied to a typical co-generation power plant of 4×8 MW rating. Test results indicates that the ANN model can automatically perform generator scheduling accurately.
format Conference or Workshop Item
author Moghavvemi, M.
Yang, S.S.
Kashem, M.A.
author_facet Moghavvemi, M.
Yang, S.S.
Kashem, M.A.
author_sort Moghavvemi, M.
title Practical neural network approach for power generation automation
title_short Practical neural network approach for power generation automation
title_full Practical neural network approach for power generation automation
title_fullStr Practical neural network approach for power generation automation
title_full_unstemmed Practical neural network approach for power generation automation
title_sort practical neural network approach for power generation automation
publishDate 1998
url http://eprints.um.edu.my/9709/
_version_ 1643688634375733248
score 13.250519

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