| In thermal power generation,circulating fluidized bed(CFB)boilers are widely used for their high combustion and high thermal efficiency.Nitrogen oxides(NOx)are one of the major gaseous contaminants produced by CFB boilers during combustion.NOx not only directly harms human health,but its indirect acid rain and ozone layer reduction also pose a serious threat to the environment and human health.CFB boilers typically use SNCR(selective non-catalytic reduction)for denitration.The SNCR denitration system is a typical large delay,nonlinear system,especially the frequent changes of load commands lead to more complex nonlinear behavior,which makes the system modeling and control design difficult.Traditional linear modeling methods and linear control strategies often exhibit excessive use of reducing agents and even NOx emissions are not up to standard,resulting in increased operating costs for power plants.In order to solve the above problems,this paper studies the system modeling and controller design for the large delay and nonlinear characteristics of the SNCR denitration process.Based on the subspace identification,a dynamic model from the urea flow rate to the NOx concentration at the SNCR outlet is established.The submodels are combined by using the information of the switching points between themodels,and the corresponding switching laws are designed.A multi-model predictive control design method is proposed.A 2 × 200 MW extraction steam condensing steam turbine generator set and a 2×705t/h circulating fluidized bed boiler were used as test units to analyze and verify the SNCR denitration system.The research contents of this paper are as follows:(1)Analyze the process flow of SNCR denitration system in detail,and establish a nonlinear model of denitration process based on the principle of denitrification.For the nonlinear model with large delay,the dynamic model of the denitration system is obtained by the system identification method.Specifically,the real historical data of the power plant is collected,and the typical operating conditions of the system are obtained by using the nuclear density estimation and rationally divided.Full consideration is given to the difference in delay of the SNCR denitration system at each typical operating point,and the correlation time method is used to obtain the pure time delay of each typical operating point.After the data analysis is completed,the subspace identification method is used to obtain the dynamic model of the system,and the switching point information and the similarity transformation are further utilized to obtain the global nonlinear model of the SNCR denitration system.The model and analysis of the SNCR denitration system model are carried out.The results show that the model can effectively describe the large delay and nonlinear links of the SNCRdenitration system and has high modeling accuracy.(2)According to the urea pump power and NOx emission constraints during the actual operation of the denitration system of the power plant,the corresponding model predictive control strategy is proposed.The online solution process of the model predictive control based on quadratic programming(QP)under constraint conditions is analyzed in detail.The power plant load command is used as the scheduling variable,and the corresponding switching strategy is designed.Finally,the multi-model predictive control scheme is proposed to effectively solve the problem that the fixed model is difficult to meet the NOx concentration exceeding the standard of the SNCR when the power plant has a large load change.Compared with the traditional PID control strategy,the simulation results show that the controller designed in this paper can meet the ultra-low emission when the plant is under variable load operation.Finally,summarize the work of this paper and look into future potential research issues. |
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