In order to meet the requirements of power grid

a supercritical power generating unit often operates under wide-range load-changing conditions.The conventional coordinated control strategy can not well adapt to the load deep regulation situations

and often leads to slow load response and large main steam pressure fluctuations.Therefore

a model predictive optimal control(MPOC)method for coordinated control of the supercritical units was proposed

on the basis of neural network model and particle swarm optimization(PSO)algorithm.The proposed MPOC scheme was programmed with MATLAB software and tested by extensive control simulation experiments in the full-scope simulator of a 600 MW supercritical power generating unit.The simulation results show that the proposed MPOC method can improve the load dynamic response speed greatly and keep main steam pressure within safety limits.