Simulation And Economic Study On Denitrification Of Co-combustion Of Coal And Sludge In Cement Calciner

With the advancement of urbanization,the high output of cement in China leads to the high NO_x emission of cement industry for a long time,which is only lower than that of electric power industry and automobile exhaust.The catalytic effect of raw meal calcined on NO_xgeneration and HCN,NH₃oxidation also aggravates the denitration problem of cement kiln.Facing the huge output of municipal sludge,it is a resource-based and harmless sludge treatment method to burn sludge in industrial furnace and power station furnace.Based on the composition of nitrogen compounds in municipal sludge,it has a significant effect on reducing NO_xgeneration in combustion,Therefore,a method of NO_xremoval by co-combustion of sludge and coal with selective non-catalytic reduction（SNCR）denitrification is a more effective denitrification method.Through CFD numerical simulation analysis,the pyrolysis,combustion characteristics and NO_xgeneration process of pulverized coal and sludge in the calciner can be well studied,and the co-combustion condition of sludge and coal can be optimized to obtain the best denitration effect;through the intelligent algorithm to establish the denitration operation cost function for economic analysis and optimize the main operation parameters,it also has important guiding significance for the denitration system engineering operation.This paper takes a 6000t/d cement production line in Guangdong Province as the research object,and the physical model of calciner was established through field investigation,the physical and chemical process of fuel combustion,raw meal calcination and NO generation characteristics were numerically simulated by relevant mathematical models.Firstly,different fuel conditions were compared to search the rule of reducing NO generation by co-combustion of sludge and coal.Secondly,through different proportion of heat and moisture content of sludge,the sludge blending condition was optimized,and the sludge blending condition with the best NO removal effect was obtained.On the other hand,according to the field test results,the main operating parameters such as sludge blending,ammonia injection and tertiary air temperature are taken as input variables,and the adaptive genetic algorithm is used to optimize BP neural network（AGA-BPNN）,small batch gradient descent（MBGD）and L2 regularization algorithms are adopted,and through 5-fold cross validation,the NO_x emission prediction model of cement plant is established.Then,based on the prediction model,the on-site denitration cost function is established.Taking the minimum value of the function as the objective,multigroup parallel genetic algorithm（MPGA）is mainly used to optimize the above main operating parameters to obtain the operating parameters of the cement plant with the lowest denitration cost.The main conclusions are as follows:（1）by comparing the condition of co-combustion of coal and sludge with that of coal mono-combustion,the significant effect of co-combustion of coal and sludge on reducing NO_x emission of calciner is obtained.The results show that the NO concentration at the outlet can be reduced by 35.3%and the decomposition rate of raw meal can meet the production process index of cement.（2）The simulation and optimization experiments of sludge combustion parameters were carried out to reveal the change rule of proportion of sludge heat and sludge moisture content on NO_xgeneration.The results show that the NO concentration at the outlet of decomposing furnace first decreases and then increases with the increase of proportion of sludge heat when the sludge moisture content remains unchanged;the NO concentration at the outlet of decomposing furnace gradually decreases with the decrease of sludge moisture content when the proportion of sludge heat remains unchanged,and finally tends to be flat.When the proportion of heat and moisture content of sludge is 24.97%and 22%,the optimal outlet no concentration is 263.55mg/nm3,which is 18.76%less than that of original sludge.（3）The AGA-BPNN NO_x emission prediction network model based on MBGD and L2regularization algorithm is established.Compared with the traditional neural network modeling method,the NO_x emission prediction network model established in this paper is verified by 5-fold cross validation.The average relative error is 2.63%,and the average correlation coefficient is 0.978,which has high accuracy and strong generalization.（4）Through the comparison and optimization of denitration parameters by different optimization algorithms,the optimal operating conditions of the system are obtained.The results show that MPGA has better global search ability and evolutionary ability than genetic algorithm（GA）and particle swarm optimization（PSO）algorithm,and is more suitable for high-dimensional nonlinear solution space.Through MPGA,when the temperature of tertiary air is controlled at about 850℃,the amount of sludge mixed burning is controlled at 18 T/h,and the amount of ammonia injection is about 500 L/h,the lowest denitration operation cost can be obtained,which is about 1900 yuan/h.The above methods and conclusions have certain guidance and reference significance for the determination of the optimal process conditions and operation parameters of denitrification by co-combustion of coal and sludge in cement kiln.