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Identifying a simplified model for heavy duty gas turbine

Bahrami, Saeed; Ghaffari, Ali; Sadati, S. Hossein and Thern, Marcus LU (2014) In Journal of Mechanical Science and Technology 28(6). p.2399-2408
Abstract
A dynamic model was developed for long-term simulation of a heavy duty gas turbine. The model includes the essential control algorithm of the gas turbine as well as the most common outputs and other important intermediate variables. Control algorithm details, such as wind up protection and load limiter algorithm which have large effect on gas turbine transient behavior, are included. The model parameters are identified by applying genetic algorithm and least squares algorithm on regular operational data from a real plant to better match the model response to the real plant. The simulation results have been validated with real plant data and shown to have valid accuracy for many engineering applications.
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
Genetic algorithm, Heavy duty gas turbine, Least squares, Power, generation, System identification
in
Journal of Mechanical Science and Technology
volume
28
issue
6
pages
2399 - 2408
publisher
Springer
external identifiers
  • wos:000338119100045
  • scopus:84902358136
ISSN
1738-494X
DOI
10.1007/s12206-014-0532-5
language
English
LU publication?
yes
id
bf48f4a2-2c0a-4ba0-ac12-5c75c1d99195 (old id 4608706)
date added to LUP
2014-09-04 12:11:10
date last changed
2017-03-05 03:02:02
@article{bf48f4a2-2c0a-4ba0-ac12-5c75c1d99195,
  abstract     = {A dynamic model was developed for long-term simulation of a heavy duty gas turbine. The model includes the essential control algorithm of the gas turbine as well as the most common outputs and other important intermediate variables. Control algorithm details, such as wind up protection and load limiter algorithm which have large effect on gas turbine transient behavior, are included. The model parameters are identified by applying genetic algorithm and least squares algorithm on regular operational data from a real plant to better match the model response to the real plant. The simulation results have been validated with real plant data and shown to have valid accuracy for many engineering applications.},
  author       = {Bahrami, Saeed and Ghaffari, Ali and Sadati, S. Hossein and Thern, Marcus},
  issn         = {1738-494X},
  keyword      = {Genetic algorithm,Heavy duty gas turbine,Least squares,Power,generation,System identification},
  language     = {eng},
  number       = {6},
  pages        = {2399--2408},
  publisher    = {Springer},
  series       = {Journal of Mechanical Science and Technology},
  title        = {Identifying a simplified model for heavy duty gas turbine},
  url          = {http://dx.doi.org/10.1007/s12206-014-0532-5},
  volume       = {28},
  year         = {2014},
}