Study of a multivariable coordinate control for a supercritical power plant process

The paper presents the recent research work in study of a novel multivariable coordinate control for a 600MW supercritical (SC) power plant. The mathematical model of the plant is described in the first part of the paper. Then, a control strategy is designed based on Model Predictive Control (MPC) theory. It is noticed that the linear MPC alone performs well only within limited small load changes under a constant level of disturbances and measurement noises generalized from the prediction algorithms. So, a dynamic compensator is proposed to work in parallel with the MPC to track large load changes. Because the model has been identified with on-site closed loop response data, the multivariable optimal control signals have been used as a correction to the reference of the plant local controls instead of direct control signal applications. The simulation results show the good performance of the controller in response to the large load changes. Furthermore, it has been proved that the plant dynamic response can be improved by increasing the coal grinding capability and pulverized coal discharging through implementation of suitable coal mill controllers.