Predictive control strategy for a supercritical power plant and study of influences of coal mills control on its dynamic responses

The paper is to investigate dynamic responses of supercritical power plants (SCPP) and study the potential strategies for improvement of their responses for Grid Code compliance. An approximate mathematical model that reflects the main features of SCPP is developed. The model unknown parameters are identified using Genetic Algorithms (GA) and the model is validated over a wide operating range. A model based predictive control (MPC) is then proposed to speed up the dynamic responses of the power plant by adjusting the reference of the plant local controls instead of direct control signal applications. Simulation results have shown encouraging improvement in performance of the plant with no interference with its associated local controllers.