Nonlinear Model Predictive Control for Combined Cycle Power Plants
(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:
http://lup.lub.lu.se/student-papers/record/4175598
- author
- Johnsson, Anna
- supervisor
- organization
- year
- 2013
- 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}}, language = {{eng}}, note = {{Student Paper}}, title = {{Nonlinear Model Predictive Control for Combined Cycle Power Plants}}, year = {{2013}}, }