Modeling Of Flue Gas Denitration System In Thermal Power Plants And Optimization Of Ammonia Injection Quantity

With the continuous development of China's economy,the total amount of nitrogen oxides emitted from coal-fired power plants has increased year by year,China's air pollution is severe,and the emission requirements for nitrogen oxides have become increasingly stringent,thus reducing the emission of nitrogen oxides from power plants.Has become an urgent issue.Selective catalytic reduction(SCR)flue gas denitration technology has been widely used in China's coal-fired power plants,but there are still many deficiencies in the actual control and operation of the SCR denitration system.The research object of this paper is the SCR denitrification system of a 200 MW ultra-high pressure unit in a power plant.Firstly,the status quo of the denitrification technologied at home and abroad is reviewed,and the technical characteristics and reaction principles of the ammonia injection control of denitration systems are analyzed in depth.Secondly,using Langmuir and Eley-Rideal mechanism,the mechanism model of SCR is established.The particle model algorithm is used to optimize the parameters of the mechanism model,determine the parameter values,and test the model accuracy.Then,the mathematical model of the nitrogen oxide concentration at the outlet of the radial basis function neural network(RBF)is established using data from the SCR system of the power plant.The model is tested by means of mean absolute error(MAE)and root mean squared erroe(RMSE).The model has high control accuracy.Finally,the SCR mechanism model is used as the control object,and the data model is used as the prediction model.The chaos particle swarm optimization(CPSO)algorithm is used to perform the rolling optimization of the model.The SCR system model is built on the MATLAB software platform.By comparing the traditional ammonia injection control with the neural network predictive control,it can be seen that the neural network has higher control accuracy and reduces the escape rate of ammonia gas.