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Article
A practical neural network approach for power generation automation
Proceedings of the International Conference on Energy Management and Power Delivery, EMPD 1 (1998)
  • Prof Mahmoud Moghavvemi, University of Malaya
  • S.S. Yang
  • M.A. Kashem
Abstract

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 backpropagation 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

Keywords
  • Artificial neural networks,
  • Automation,
  • Biological neural networks,
  • Hybrid power systems,
  • Neural networks,
  • Neurons,
  • Power generation,
  • Power generation economics,
  • Power system modeling,
  • Scheduling
Publication Date
1998
Citation Information
Prof Mahmoud Moghavvemi, S.S. Yang and M.A. Kashem. "A practical neural network approach for power generation automation" Proceedings of the International Conference on Energy Management and Power Delivery, EMPD 1 Vol. 1 (1998)
Available at: http://works.bepress.com/mahmoud_moghavvemi/130/