Nonlinear Model Predictive Control for Combined Cycle Power Plants
نویسنده
چکیده
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 find 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 differential 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 filter (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 simplified representations of the real process.
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