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Nonlinear Model Predictive Control for Combined Cycle Power Plants

Johnsson, Anna (2013)
Department of Automatic Control
Abstract (Swedish)
This master thesis project serves to investigate the possibilities of Nonlinear Model Predictive Control (NMPC) using the example of enthalpy control of the BENSON HRSG (heat recovery steam generator) of a combined cycle power plant (CCPP). The general idea of NMPC is to solve an optimization problem, to nd the next control action, and this optimization problem is based on a model of the system. The models used in the controller implementation are Modelica-based, and the system is described by algebraic dierential equations (DAEs).

The controller was implemented in the Python interface of JModelica.org (Modelica-based modeling tool, supporting the Modelica extension Optimica for optimization), together with an extended Kalman lter (EKF)... (More)
This master thesis project serves to investigate the possibilities of Nonlinear Model Predictive Control (NMPC) using the example of enthalpy control of the BENSON HRSG (heat recovery steam generator) of a combined cycle power plant (CCPP). The general idea of NMPC is to solve an optimization problem, to nd the next control action, and this optimization problem is based on a model of the system. The models used in the controller implementation are Modelica-based, and the system is described by algebraic dierential equations (DAEs).

The controller was implemented in the Python interface of JModelica.org (Modelica-based modeling tool, supporting the Modelica extension Optimica for optimization), together with an extended Kalman lter (EKF) for state estimation. The control algorithm was only evaluated for a setup where the controller model is very similar to the model representing the real process; both models are simplied representations of the real process. (Less)
Please use this url to cite or link to this publication:
author
Johnsson, Anna
supervisor
organization
year
type
H3 - Professional qualifications (4 Years - )
subject
keywords
Optimization, Nonlinear Model Predictive Control, Extended Kalman lter, Modelica, Optimica, JModelica.org
ISSN
0280-5316
other publication id
ISRN LUTFD2/TFRT--5926--SE
language
English
id
4175598
date added to LUP
2013-12-02 09:45:02
date last changed
2013-12-02 09:45:02
@misc{4175598,
  abstract     = {This master thesis project serves to investigate the possibilities of Nonlinear Model Predictive Control (NMPC) using the example of enthalpy control of the BENSON HRSG (heat recovery steam generator) of a combined cycle power plant (CCPP). The general idea of NMPC is to solve an optimization problem, to nd the next control action, and this optimization problem is based on a model of the system. The models used in the controller implementation are Modelica-based, and the system is described by algebraic dierential equations (DAEs).

The controller was implemented in the Python interface of JModelica.org (Modelica-based modeling tool, supporting the Modelica extension Optimica for optimization), together with an extended Kalman lter (EKF) for state estimation. The control algorithm was only evaluated for a setup where the controller model is very similar to the model representing the real process; both models are simplied representations of the real process.},
  author       = {Johnsson, Anna},
  issn         = {0280-5316},
  keyword      = {Optimization,Nonlinear Model Predictive Control,Extended Kalman lter,Modelica,Optimica,JModelica.org},
  language     = {eng},
  note         = {Student Paper},
  title        = {Nonlinear Model Predictive Control for Combined Cycle Power Plants},
  year         = {2013},
}