Boiler Modelling and Optimal Control of Steam Temperature in Thermal Power Plants

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 and there exists a deviation of ± 10 °C in closed loop control. 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 within ± 2 °C and to enhance the efficiency of the boiler. It is proved through simulation 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 as compared to other methods. This control system is under field implementation in a 210 MW boiler of a thermal power plant.