Title
Clustering-based performance optimization of the boiler-turbine system
Document Type
Article
Peer Reviewed
1
Publication Date
1-1-2008
Journal/Book/Conference Title
IEEE Transactions on Energy Conversion
Volume
23
Abstract
In this paper, two optimization models for improvement of the boiler-turbine system performance are formulated. The models are constructed using a data-mining approach. Historical process data is clustered and the discovered patterns are selected for performance improvement of the boiler-turbine system. The first model optimizes a widely used performance index, the unit heat rate. The second model minimizes the total fuel consumption while meeting the electricity demand. The strengths and weaknesses of the two models are discussed. An industrial case study illustrates the concepts presented in the paper. 2008 IEEE.
Keywords
Sustainability, In this paper, two optimization models for improvement of the boiler-turbine system performance are formulated. The models are constructed using a data-mining approach. Historical process data is clustered and the discovered patterns are selected for performance improvement of the boiler-turbine system. The first model optimizes a widely used performance index, the unit heat rate. The second model minimizes the total fuel consumption while meeting the electricity demand. The strengths and weaknesses of the two models are discussed. An industrial case study illustrates the concepts presented in the paper. 2008 IEEE.
Published Article/Book Citation
IEEE Transactions on Energy Conversion, 23:2 (2008) pp.651-658.
URL
http://ir.uiowa.edu/cee_pubs/455