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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1998
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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 |
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| continent |
Asia |
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Malaysia |
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Universiti Malaya |
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http://eprints.um.edu.my/ |
| topic |
TA Engineering (General). Civil engineering (General) |
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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.
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| 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 |
13.250246 |