Modelling And Optimal Control Of Direct-fired Pulverizing System In Thermal Power Plant

At present medium speed coal mill direct-fired pulverizing system is commonly used in large capacity boiler units. For the coal of low coefficient of grinding, strong abrasion and high coal fineness requirements, the ball mill with double inlets and outlets direct-fired pulverizing system is also adopted. Currently in most control strategies, simple multi-loop design methods are adopted. To ensure the control quality of pulverizing system under disturbances and all operating conditions and to improve the operation levels of optimal energy saving of the pulverizing system, the research of the operating characteristics of the pulverizing system, the building of dynamic mathematical model and the realization of optimal energy saving control of multivariable system are needed.The dynamic operating characteristics of the MPS-type medium speed coal mill are analyzed. Based on mass and energy balance a dynamic mathematical model of medium speed coal mill is established, the effect of coal moisture and pulverized coal moisture on the pulverizing system is considered in establishing a mass and energy balance based dynamic mathematical model of coal mill. The parameters of the model are identified by using the genetic algorithm and later validated with measurements. An extended Kalman filter is designed to estimate and verify the internal states of the coal mill. Based on the dynamic mathematical model of coal mill, pulverized coal moisture is used as a feed-forward signal, and a feed-forward compensation controller is designed to optimize the coal mill outlet temperature. Simulation results show that the dynamic characteristic of the mill can be forecasted effectively with the established model. Moreover, pulverized coal moisture is reduced with feed-forward compensation, thereby improving the efficiency of boiler and the utilization of flue gas.The dynamic operating characteristics of the ball mill with double inlets and outlets are analyzed. Based on mass and energy balance a dynamic mathematical model of ball mill with double inlets and outlets is established, where the influence of coal moisture on energy balance is taken into consideration. The model parameters are identified by combining historical data and prediction error minimization algorithm. Extended Kalman filtering is designed to estimate coal moisture. Based on the model above, a new extended state space predictive control method is applied to establish multi-variable control system instead of single-loop PID control strategy. The set points of primary air flow and pulverized coal flow are optimized through the load instruction and the relationship of primary air flow and pulverized coal flow. Simulation results show that the established mill model can effectively predict the dynamic characteristic of coal mill and the adopted control strategy is able to achieve the fast tracking of load changes and overcome the disturbances of coal moisture and other outputs.