Modeling And Optimization Control On The Combustion System Of Circulating Fluidized Bed Boiler

With the improvement of energy and environmental protection requirements, the low efficiency of burning coal boiler has brought great pressure on the intensive use of energy and environmental protection. C irculating fluidized bed boiler has been widely used in electric power, heating and industrial steam production because of its high efficiency, wide range of fuel adaptation, good load regulation performance, furnace desulfurization, and so on. As the boiler combustion process has a large lag, nonlinear, multi variable coupling characteristics, so that the operating conditions of the circulating fluidized bed is difficult to meet the design requirements. Therefore, it has great practical significance to study the modeling and optimizing control of CFB boiler combustion system.Firstly, the structure and combustion c haracteristics of CFB boiler combustion system are analyzed in this paper, its main characteristics include the large inertia, strong coupling, nonlinear, etc., on the basis of these characteristics, the main thermal parameters of the combustion system control method is studied. Although the theoretical system of mechanism modeling has been improved, the data of the operation of the unit and the simulation system are the basis of intelligent identification. In view of the experimental modeling of the combustion control system is a complex optimization problem that needs to identify multi-dimensional variables, this paper adopts the standard particle swarm optimization algorithm, which lays a good foundation for the experimental modeling. In the next work, according to the general method of experimental modeling, using the particle swarm optimization algorithm to obtain the transfer function of the model, and to verify the validity of the model transfer function by using other data that is independent of the identification data. In the end, this paper is to control the bed temperature by using the primary air, regulating the supply of coal feeder speed is used to control the main steam pressure, in order to optimizes the SAMA diagram of the original bed temperature control loop and the main steam pressure control loop, and the principle of feed- forward compensation control is applied to the control of the combustion system. In combination with the control scheme and identification of object model, the controller parameters are optimized by using the particle swarm optimization algorithm. By comparing before and after optimization control effect, found that the optimized control system not only can improve the automation level of boiler control system, but also has important significance to improve the energy utilization efficiency.