Boiler modeling and optimizing steam temperature

Boiler modeling and optimizing steam temperature

Abstract: Achieving accurate control of main steam temperature is a very difficult task in Thermal power plants due to the large process lag (8 to 10 minutes) associated with the superheater system. A control oriented boiler model and an appropriate optimal control strategy are the essential tools for improving the accuracy of this control system. This paper offers a comprehensive integrated 8th order mathematical model for the boiler and a Kalman Filter based state predictive controller for effectively controlling the main steam temperature and to enhance the efficiency of the boiler. In order to demonstrate the effectiveness of the control system, three more advanced control methods are experimented with the boiler model - Pole placement controller, Optimal controller with state observer
and Optimal controller with Kalman filter. Simulation results have illustrated that the Predictive controller method with Kalman filter state estimator and predictor is the most appropriate one for the optimization of main steam temperature control. At present, we are in the process of implementing this control strategy in running Thermal power plants.



Keywords:Large Process lag, Boiler model, Stochastic model, State observer, Kalman filter, N-stepprediction, Process identification, Pole placement controller, Optimal Controller, Adaptive predictive controller.



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