摘要
The control of ultra-supercritical(USC) power unit is a difficult issue for its characteristic of the nonlinearity, large dead time and coupling of the unit. In this paper, model predictive control(MPC) based on multi-model and double layered optimization is introduced for coordinated control of USC unit. The linear programming(LP) combined with quadratic programming(QP) is used in steady optimization for computation of the ideal value of dynamic optimization. Three inputs(i.e. valve opening, coal flow and feedwater flow) are employed to control three outputs(i.e. load, main steam temperature and main steam pressure). The step response models for the dynamic matrix control(DMC) are constructed using the three inputs and the three outputs. Piecewise models are built at selected operation points. Double-layered multi-model predictive controller is implemented in simulation with satisfactory performance.
The control of ultra-supercritical （USC） power unit is a difficult issue for its characteristic of the nonlinearity, large dead time and coupling of the unit. In this paper, model predictive control （MPC） based on multi-model and double layered optimization is introduced for coordinated control of USC unit. The linear programming （LP） combined with quadratic programming （QP） is used in steady optimization for computation of the ideal value of dynamic optimization. Three inputs （i.e. valve opening, coal flow and feedwater flow） are employed to control three outputs （i.e. load, main steam temperature and main steam pressure）. The step response models for the dynamic matrix control （DMC） are constructed using the three inputs and the three outputs. Piecewise models are built at selected operation points. Double-layered multi-model predictive controller is implemented in simulation with satisfactory performance.
基金
Supported by the National Natural Science Foundation of China(60974119)
