Fuzzy gain scheduling prediction control-based control method for boiler-turbine coordination system

Abstract

The invention discloses a fuzzy gain scheduling prediction control-based control method for a boiler-turbine coordination system. The control method is an intelligent control method organically combining a nonlinear modeling method, a fuzzy logic reasoning theory and a predictive control technology. Firstly, a multivariable nonlinear discrete dynamic model of the local working condition of the turbine-boiler coordination system is established based on a state space nonlinear modeling method; state variables reflecting dynamic characteristics of the turbine-boiler coordination system are selected as fuzzy scheduling variables, a global multivariable nonlinear discrete fuzzy model of the turbine-boiler coordination system is reasoned according to fuzzy logic; a predictive control technologyis applied on the basis of the model to predict the multi-step output of the model, and control action constraints are considered, and a rolling optimization strategy is implemented. According to themethod, the load can be rapidly tracked in a full working condition range, the constraint optimization problem of a control effect can be solved, the good robustness is achieved while the global optimum of a control system is ensured. The method has important significance in operation optimization of a thermal power generating unit for deep peak regulation.

Description

technical field [0001] The invention relates to the field of thermal power engineering and automatic control, in particular to a control method for a machine furnace coordination system based on fuzzy gain scheduling predictive control. Background technique [0002] The boiler-boiler coordinated control system is the core of the thermal system of a thermal power plant. It coordinates and comprehensively controls the boiler and steam turbine so that the unit can quickly respond to the load requirements of the grid. At present, most of them use PID control, but when the characteristics of the objects change, it is difficult to ensure that the system Obtain the best quality and affect the economical operation of the unit. Model predictive control (MPC) has a good control effect on multi-capacitance inertial objects, with fast response of the controlled variable and small overshoot. It also has good robustness and the ability to deal with constraints, which is beneficial to the ...

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Problems solved by technology

With the rapid development of renewable clean energy power generation technology in China, coal-fired thermal power capacity is overcapacitated, and the peak-to-valley load difference of the power grid is relatively large. Under the requirements of deep peak regulation, thermal power units must adjust the load in a wide range according to the requirements of the power grid, and the coordination of machines and furnaces The dynamic characteristics of the system objects change greatly, and there are serious nonlinearities. However, the traditional coordinated control system of the boiler and furnace is only designed according to the object characteristics of the thermal power unit at a certain load point, and cannot guarantee that the unit is global within the entire load range. optimal, so we need to explore other better control schemes

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