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Mathematical modelling for coal fired supercritical power plants and model parameter identification using genetic algorithms
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Mohamed, Omar, Wang, Jihong, Guo, Shen, Wei, Jianlin, Al-Duri, Bushra, Lv, Junfu and Gao, Qirui (2011) Mathematical modelling for coal fired supercritical power plants and model parameter identification using genetic algorithms. In: Ao, S.I. and Gelman, L., (eds.) Electrical Engineering and Applied Computing. Lecture Notes in Electrical Engineering, Vol.90 . Dordrecht, Netherlands: Springer Science+Business Media B.V., pp. 1-13. ISBN 978-94-007-1191-4
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Official URL: http://dx.doi.org/10.1007/978-94-007-1192-1_1
Abstract
The paper presents the progress of our study of the whole process mathematical model for a supercritical coal-fired power plant. The modelling procedure is rooted from thermodynamic and engineering principles with reference to the previously published literatures. Model unknown parameters are identified using Genetic Algorithms (GAs) with 600MW supercritical power plant on-site measurement data. The identified parameters are verified with different sets of measured plant data. Although some assumptions are made in the modelling process to simplify the model structure at a certain level, the supercritical coal-fired power plant model reported in the paper can represent the main features of the real plant once-through unit operation and the simulation results show that the main variation trends of the process have good agreement with the measured dynamic responses from the power plants.
Item Type: | Book Item | ||||
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Subjects: | T Technology > TJ Mechanical engineering and machinery T Technology > TK Electrical engineering. Electronics Nuclear engineering |
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Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||
Series Name: | Lecture Notes in Electrical Engineering | ||||
Publisher: | Springer Science+Business Media B.V. | ||||
Place of Publication: | Dordrecht, Netherlands | ||||
ISBN: | 978-94-007-1191-4 | ||||
ISSN: | 1876-1100 | ||||
Book Title: | Electrical Engineering and Applied Computing | ||||
Editor: | Ao, S.I. and Gelman, L. | ||||
Official Date: | 2011 | ||||
Dates: |
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Volume: | Vol.90 | ||||
Number of Pages: | 13 | ||||
Page Range: | pp. 1-13 | ||||
DOI: | 10.1007/978-94-007-1192-1_1 | ||||
Status: | Not Peer Reviewed | ||||
Publication Status: | Published | ||||
Access rights to Published version: | Restricted or Subscription Access | ||||
Funder: | Engineering and Physical Sciences Research Council (EPSRC), ERDA/AWM Birmingham Science City Energy Efficiency and Demand Reduction Project | ||||
Grant number: | RG/G062889/1 (EPSRC) |
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