DocumentCode
1080644
Title
Clustering-Based Performance Optimization of the Boiler–Turbine System
Author
Kusiak, Andrew ; Song, Zhe
Author_Institution
Dept. of Mech. & Ind. Eng., Univ. of Iowa, Iowa City, IA
Volume
23
Issue
2
fYear
2008
fDate
6/1/2008 12:00:00 AM
Firstpage
651
Lastpage
658
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.
Keywords
boilers; data mining; power engineering computing; turbines; boiler-turbine system performance; clustering-based performance optimization; data-mining approach; performance index; Boiler–turbine system; Boiler--turbine system; clustering; data mining; performance optimization;
fLanguage
English
Journal_Title
Energy Conversion, IEEE Transactions on
Publisher
ieee
ISSN
0885-8969
Type
jour
DOI
10.1109/TEC.2007.914183
Filename
4456516
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