A method and system for optimizing parameters of an inline SNCR of a grate coupled to a pellet production

Abstract

This invention discloses a method and system for optimizing embedded SNCR parameters of a chain grate machine coupled with pellet production. The method includes: constructing a geometric model for numerical simulation of the chain grate machine based on its structural dimensions; determining the reaction control equations of the geometric model; initializing the operating parameters of the geometric model and meshing the model; performing simulation based on the meshed geometric model until the selected optimization criteria meet preset conditions, then outputting the SNCR injection parameters. This method establishes a numerical simulation model coupling the pellet production process with the embedded SNCR denitrification process, and optimizes key injection parameters under a fixed injection structure, effectively improving denitrification efficiency and reducing ammonia slip.

Description

Technical Field

[0001] This invention relates to the field of flue gas denitrification technology in pellet production, and particularly to a method and system for optimizing SNCR parameters embedded in a chain grate machine coupled with pellet production. Background Technology

[0002] The chain grate-rotary kiln process is one of the mainstream technologies in iron ore pellet production. This process generates a large amount of nitrogen oxides (NOx), a major air pollutant in the pelletizing process. With increasingly stringent environmental requirements, efficient control of NOx has become a key aspect of promoting the green and low-carbon development of pelletizing production. Selective non-catalytic reduction (SNCR) technology has received widespread attention in the field of flue gas denitrification in pelletizing due to its relatively simple process flow and lower investment and operating costs. Applying SNCR technology to the preheating stage of the chain grate, by injecting a reducing agent into a suitable temperature zone, allows it to react with NOx in the flue gas, thereby reducing NOx emissions, which shows promising application prospects.

[0003] However, this technology still faces significant challenges in practical applications. The interaction between the flow and mixing of high-temperature flue gas inside the chain grate, and the heat and mass transfer processes between the flue gas and the pellet bed, couples the evaporation, diffusion, and NOx reduction reactions of the reducing agent after injection with the pellet production process. As a result, the SNCR denitrification process within the chain grate is complex and highly sensitive to operating parameters. Relying solely on field experience to determine injection parameters often makes it difficult to simultaneously achieve high denitrification efficiency and low ammonia slip.

[0004] Current research on SNCR denitrification within chain grate machines largely focuses on the independent adjustment of single operating parameters, lacking coupled numerical simulation and parameter optimization methods that simultaneously consider the pellet production process and the denitrification reaction process. Especially under conditions where the embedded SNCR injection structure is fixed and on-site adjustable parameters are limited, effective technical means are still lacking for optimizing key operating parameters such as injection speed, ammonia-nitrogen molar ratio, and ammonia concentration to improve denitrification efficiency while reducing ammonia slip. Summary of the Invention

[0005] To address the technical problems in existing technologies that lack simultaneous consideration of the coupling relationship between the pellet production process and the SNCR denitrification process, and the difficulty in optimizing injection parameters under the condition of a fixed embedded injection structure and limited adjustable parameters, this invention provides a method and system for optimizing embedded SNCR parameters of a chain grate machine coupled with pellet production. The method establishes a numerical simulation model that couples the pellet production process with the embedded SNCR denitrification process, and optimizes key injection parameters under the condition of a fixed injection structure, thereby effectively improving denitrification efficiency and reducing ammonia slip.

[0006] To achieve the above-mentioned technical objectives, the present invention provides the following technical solution: In a first aspect, the present invention provides a method for optimizing embedded SNCR parameters in a chain grate machine used in coupled pellet production, comprising: S1: Construct a geometric model for numerical simulation of the chain grate machine based on its structural dimensional parameters; S2: Determine the reaction control equation of the geometric model; the reaction control equation is used to simulate the process of pellet production in the chain grate and coupled with embedded SNCR denitrification, including the physical process, chemical reaction and embedded SNCR denitrification process in the pellet production process; S3: Initialize the running parameters of the geometric model and mesh the geometric model; wherein, the running parameters are the corresponding boundary conditions and the initial values ​​of the SNCR injection parameters; S4: Based on the geometric model of mesh generation, the reaction parameters inside the chain grate are obtained by simulation calculation, and the temperature field distribution, flow field distribution, ammonia concentration field distribution, NOx concentration field distribution, denitrification efficiency and ammonia slip results are obtained based on the reaction parameters; Among them, denitrification efficiency, ammonia slip results and SNCR injection parameters were selected as the optimization basis; S5: Determine whether the selected optimization criteria meet the preset conditions: if yes, output the SNCR injection parameters; if no, adjust the SNCR injection parameters in the chain grate machine based on the optimization criteria and return to S3.

[0007] Furthermore, in S1, the geometric model includes a fume hood, a wind box, a material layer area, and an embedded SNCR denitrification spray structure; the embedded SNCR denitrification spray structure includes at least the number of spray guns, the position of the spray guns, and the nozzle diameter.

[0008] Furthermore, the governing equations for the gas flow, material layer movement, and interphase interactions within the chain grate specifically include: Total mass conservation equation: ; ; In the formula, The average density is kg / m³. 3 ; For time; It is a velocity vector with direction; for Phase volume fraction; for Phase density, kg / m³ 3 ; for Phase transfer to Phase quality; for Phase transfer to Phase quality; For chemical reaction source terms; The total number of phases in a multiphase system. ; The mass fraction of the gas phase satisfies the following equation: ; In the formula, for Phase density; For the first Mass fraction of each substance; This represents the total mass within the corresponding grid. For time; For Hamiltonian differential operators; for The velocity vector of the phase; For the first The diffusion flux vector of a substance; For the first The net diffusion flux divergence term of a substance due to diffusion; For the first The net reaction rate term for the formation or consumption of a substance due to a chemical reaction; For the first Additional source terms for each substance; Momentum conservation equation: ; In the formula, for Phase velocity; for Unsteady-state terms of the phase momentum conservation equation; for The convection term of the phase momentum conservation equation; for The pressure term in the phase momentum conservation equation; For pressure gradient; It is the vector of gravitational acceleration; for The diffusion term of the phase momentum conservation equation; for The gravity term in the equation of conservation of phase momentum; for The pressure strain tensor of the phase; For the momentum transfer of forces between two phases; For the reason Phase transfer to Interphase mass transfer rate; To act on Other volume force terms of the phase; To act on Turbulent diffusion force term of the phase; Energy conservation equation: ; In the formula, for Enthalpy of phase; For the transfer of heat between two phases; for The velocity vector of the phase; for Phase pressure; for The heat flux density vector of the phase; For source terms; for The work term done by viscous forces in the phase energy conservation equation.

[0009] Furthermore, the physical processes include the evaporation and condensation of moisture in the pellets; The governing equation for water evaporation is: ; ; Among them; among them, This represents the rate of water evaporation. The porosity is set to 0.35. ρ is the mass transfer coefficient of water vapor in the gas phase, in m / s; Specific surface area, unit: m 2 / m 3 ; The equilibrium concentration of water vapor in the gas-solid system, in kg. 3 / m 3 ; Water content in gases, unit: kg 3 / m 3 ; The critical value used to divide the two stages of evaporation is expressed in kg / kg, which indicates how many kg of water are contained in each kg of pellets. This represents the current moisture content of the pellets, in kg / kg. Radius of the pellet, in meters (m). The current wetting radius of the pellet, in meters (m). The effective diffusion coefficient of water vapor, in meters. 2 / s; The governing equation for the condensation process is: ; In the formula, The condensation rate of moisture is expressed in kg / (m²). 3 ·s).

[0010] Furthermore, the chemical reaction includes the oxidation of magnetite, specifically the oxidation of magnetite to... Then gradually transformed into The chemical equations for its two stages are shown below: ; ; The global reaction equation can be expressed as follows: ; The chemical reaction equation is as follows: ; In the formula, The chemical reaction rate of the material layer; Specific surface area; Oxygen concentration in the gas phase, unit: mol / m³ 3 ; The equilibrium concentration of oxygen in the gas phase, unit: mol / m³ 3 ; ρ is the mass transfer coefficient of oxygen, in m / s; The radius of the unreacted magnetite nucleus; Radius of the pellet, in meters (m). Oxygen diffusion coefficient, unit: m 2 / s; The value represents the oxidation rate of magnetite, in m / s.

[0011] Furthermore, the embedded SNCR denitrification process includes ammonia evaporation and NOx reduction reaction, with the following mechanism: ; .

[0012] Furthermore, the boundary conditions include at least one or more of the following: flue gas temperature, flow rate, composition, machine speed, and material layer thickness in each section of the chain grate machine.

[0013] Furthermore, the preset conditions satisfied by the optimization criteria in S4 are specifically as follows: When the denitrification efficiency is greater than or equal to the preset denitrification efficiency threshold, the ammonia slip concentration is less than or equal to the preset ammonia slip threshold, and all operating parameters are within the preset value range, it indicates that the preset conditions are met; among them, the operating parameters include the simultaneous ammonia-nitrogen molar ratio, ammonia concentration, and injection speed.

[0014] Furthermore, the SNCR injection parameters include one or more of the following: injection speed, ammonia-nitrogen molar ratio, and ammonia concentration.

[0015] Furthermore, the specific process of adjusting the SNCR injection parameters within the chain grate using optimization criteria is as follows: Based on the value range of each SNCR injection parameter and the current value corresponding to the optimization criteria, the values ​​of each SNCR injection parameter in the simulated pellet production process within the chain grate are adjusted; where the value range is obtained by taking the values ​​of each SNCR injection parameter under the actual operating conditions of the chain grate production site as a benchmark, and preset the amount of fluctuation based on the benchmark value; the specific adjustment strategy is: when the denitrification efficiency is lower than the preset denitrification efficiency threshold and the ammonia slip concentration does not exceed the threshold... When the ammonia slip threshold is exceeded, the ammonia-nitrogen molar ratio or ammonia concentration is increased, and the injection speed is increased to increase the reducing agent dosage and enhance the mixing of NH3 and NOx. When the ammonia slip concentration exceeds the preset ammonia slip threshold, the ammonia-nitrogen molar ratio or ammonia concentration is decreased, and the injection speed is adjusted to ensure that the reducing agent is fully mixed and reacted within the effective temperature window. When neither the denitrification efficiency nor the ammonia slip meets the preset conditions, the ammonia-nitrogen molar ratio, ammonia concentration, and injection speed are comprehensively adjusted until the denitrification efficiency is greater than or equal to the preset denitrification efficiency threshold, and the ammonia slip concentration is less than or equal to the preset ammonia slip threshold.

[0016] Secondly, the present invention provides an embedded SNCR parameter optimization system for a chain grate machine used in coupled pellet production, the system being used to perform the steps of the method described above, including: Geometric model construction module: used to construct the geometric model of the chain grate machine for numerical simulation based on the structural dimensional parameters of the chain grate machine; Reaction control equation determination module: used to determine the reaction control equation of the geometric model; the reaction control equation is used to simulate the process of pellet production in the chain grate and coupled with embedded SNCR denitrification, including the physical process, chemical reaction and embedded SNCR denitrification process in the pellet production process; Parameter setting and simulation module: Initializes the operating parameters of the geometric model and performs mesh generation on the geometric model; wherein, the operating parameters are the corresponding boundary conditions and initial values ​​of SNCR injection parameters; based on the meshed geometric model, simulation calculations are performed to obtain the reaction parameters within the chain grate machine, and based on the reaction parameters, the temperature field distribution, flow field distribution, ammonia concentration field distribution, NOx concentration field distribution, denitrification efficiency, and ammonia slip results are obtained; wherein, the denitrification efficiency, ammonia slip results, and SNCR injection parameters are selected as optimization criteria; Model optimization module: Determines whether the selected optimization criteria meet the preset conditions: if yes, outputs the SNCR injection parameters; if no, adjusts the SNCR injection parameters in the chain grate machine based on the optimization criteria and returns to the parameter setting and simulation module.

[0017] This invention proposes a method and system for optimizing embedded SNCR parameters in a chain grate machine coupled with pellet production. The method establishes a numerical simulation model coupling the pellet production process within the chain grate machine with the embedded SNCR denitrification process. Under the condition that the embedded SNCR injection structure is fixed and adjustable parameters are limited, one or more of the following parameters—injection velocity, ammonia-nitrogen molar ratio, and ammonia concentration—are selected as optimization variables. Different parameter combinations are analyzed to optimize the operating parameters in the embedded SNCR denitrification process. This provides a technical basis for parameter setting, operation control, and engineering implementation of the embedded SNCR denitrification process within the chain grate machine. It also helps to effectively improve denitrification efficiency and reduce ammonia slip in actual production, which is of great significance for improving the control of nitrogen oxides in the pelletizing process and promoting the green and low-carbon development of pellet production. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the embedded SNCR parameter optimization method for chain grate machine in coupled pellet production provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of the physical geometric model of the chain grate machine provided in an embodiment of the present invention; Figure 3 This is a diagram showing the position of the embedded SNCR spray gun provided in an embodiment of the present invention; Figure 4 This is a cloud map of the temperature distribution in the pH range under the optimal parameters of this embodiment of the invention; Figure 5 This is a cloud map showing the NO concentration distribution in the pH range under the optimal parameters of this embodiment of the invention. Detailed Implementation

[0020] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be described in detail below. Obviously, the described embodiments are merely some embodiments of this invention, and not all embodiments. Based on the embodiments of this invention, all other implementation methods obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0021] Example 1

[0022] like Figure 1As shown, this embodiment provides a method for optimizing embedded SNCR parameters of a chain grate machine used in coupled pellet production, including: S1: Construct a geometric model for numerical simulation of the chain grate machine based on its structural dimensional parameters.

[0023] Specifically, the geometric model includes a fume hood, a wind box, a material layer area, and an embedded SNCR denitrification spray structure; the embedded SNCR denitrification spray structure includes at least the number of spray guns, the position of the spray guns, and the nozzle diameter.

[0024] In practice, a physical geometric model of the chain grate machine is established based on the actual structural dimensions of the chain grate machine currently in production at a certain pelletizing plant, such as... Figure 2 As shown, in this embodiment, the embedded SNCR injection structure is located in the preheating stage two fume hood area of ​​the chain grate machine (the location is not limited; this is just an example, and the location can be adjusted according to the actual application scenario). Based on the actual on-site layout, the main structure of the chain grate machine and the embedded SNCR injection structure are modeled so that subsequent numerical simulations can realistically simulate and reflect the pellet production process and SNCR denitrification process inside the chain grate machine.

[0025] S2: Determine the reaction control equation of the geometric model; the reaction control equation is used to simulate the process of pellet production in the chain grate and coupled with embedded SNCR denitrification, including the physical process, chemical reaction and embedded SNCR denitrification process in the pellet production process.

[0026] Based on the pellet production process within the chain grate machine, governing equations are established to describe the gas phase flow, material layer movement, and their interphase interactions within the chain grate machine. Both the gas phase and material layer regions are considered continuous media, and two or more equations are used to describe the motion of the multiphase fluid, including mass, momentum, and energy conservation equations.

[0027] Total mass conservation equation: ; ; In the formula, Average density, unit: kg / m³ 3 ; For time; It is a velocity vector with direction; for Phase volume fraction; for Phase density; for Phase transfer to Phase quality; for Phase transfer to Phase quality; For chemical reaction source terms; In this embodiment, the total number of phases in the multiphase system is denoted as . . Harmony Both phases are multi-component systems.

[0028] The local mass fraction of each substance in the gas and solid phases is calculated by solving the convection-diffusion equations for each substance. The mass fraction in the gas phase satisfies the following equation: ; In the formula, for Phase density; For the first Mass fraction of each substance; This represents the total mass within the corresponding grid. For time; For Hamiltonian differential operators; for The velocity vector of the phase; For the first The diffusion flux vector of a substance; For the first The net diffusion flux divergence term of a substance due to diffusion; For the first The net reaction rate term for the formation or consumption of a substance due to a chemical reaction; For the first Additional source terms for each substance.

[0029] Momentum conservation equation: ; In the formula, for Phase velocity; for Unsteady-state terms of the phase momentum conservation equation; for The convection term of the phase momentum conservation equation; for The pressure term in the phase momentum conservation equation; For pressure gradient; It is the vector of gravitational acceleration; for The diffusion term of the phase momentum conservation equation; for The gravity term in the equation of conservation of phase momentum; for The pressure strain tensor of the phase; For the momentum transfer of forces between two phases; For the reason Phase transfer to Interphase mass transfer rate; To act on Other volume force terms of the phase; To act on Turbulent diffusion force term of the phase.

[0030] Energy conservation equation: ; In the formula, for Enthalpy of phase; For the transfer of heat between two phases; for The velocity vector of the phase; for Phase pressure; for The heat flux density vector of the phase; For source terms; for The work term done by viscous forces in the phase energy conservation equation.

[0031] In the pellet production process, both the physical and chemical processes of the pellets within the chain grate are considered. The physical processes include the evaporation and condensation of moisture within the pellets. Moisture evaporation, i.e., the drying process of the pellets, requires consideration of the characteristics of moisture evaporation and condensation within the pellets. The drying process includes a constant-rate drying stage and a falling-rate drying stage.

[0032] During the constant-rate drying stage, the drying medium begins to come into contact with the wet pellets. The pellet surface absorbs heat, and the temperature gradually rises. The drying interface (pellet surface) begins the evaporation process. During this process, a humidity difference is formed inside the pellets, causing moisture inside the pellets to migrate to the pellet surface to complete the evaporation process, until the moisture content in the pellets drops to a critical value. The driving force of this drying process is the pressure difference between the vapor pressure at the drying interface and the partial pressure of water vapor in the drying medium. The drying rate is only affected by the properties of the gas and is independent of the moisture content of the pellets.

[0033] During the falling-rate drying stage, the moisture content of the pellets falls below the critical value. At this point, the drying interface gradually moves towards the interior of the pellets until drying is complete. Water vapor diffusion within the dried pellets then becomes the controlling factor for the entire drying process.

[0034] The governing equation for water evaporation is: ; ; in, The evaporation rate of water is expressed in kg / (m²). 3 ·s) The porosity is set to 0.35. ρ is the mass transfer coefficient of water vapor in the gas phase, in m / s; Specific surface area; m 2 / m 3 ; The equilibrium concentration of water vapor in the gas-solid system is kg. 3 / m 3 ; Water content of gas, kg 3 / m 3 ; The critical value used to divide the two stages of evaporation is expressed in kg / kg, which indicates how many kg of water are contained in each kg of pellets. This represents the current moisture content of the pellets. Let be the radius of the pellet, in meters. Let be the current wetting radius of the pellet, in meters (m). m is the effective diffusion coefficient of water vapor. 2 / s.

[0035] When the surface water vapor concentration of the pellets is higher than that in the gas, water vapor in the gas flow condenses and precipitates on the pellet surface. The pellet bed gains weight due to moisture absorption; this process is called the water vapor condensation process in the pellet bed. The condensation rate is affected by factors such as the pellet surface temperature and the moisture content of the gas.

[0036] The governing equation for the condensation process is: ; In the formula, The condensation rate of moisture is expressed in kg / (m²). 3 ·s).

[0037] The chemical reaction includes the magnetite oxidation reaction. The essence of this reaction process is that oxygen in the air reacts with magnetite on the surface of the pellets and inside the pellet layer, which can be simply understood as the diffusion process of oxygen. This process mainly consists of three steps: First, oxygen in the gas phase reacts with magnetite on the surface of the pellets, consuming the oxygen near the surface of the pellets and creating a concentration difference. Therefore, oxygen in the gas phase diffuses to the surface of the pellets (intraphase mass transfer), and at this time, the unreacted nucleus surface is the pellet surface; Second, oxygen diffuses from the gas phase to the interior of the pellets (interphase mass transfer), and at this time, the unreacted nucleus surface gradually moves into the interior of the pellets; Third, oxygen diffuses in the magnetite layer (hematite) that has completed the oxidation reaction (interphase mass transfer), and at this time, the unreacted nucleus surface gradually moves deeper into the interior of the pellets.

[0038] The oxidation of magnetite begins at 200℃ and ends at around 1000℃. The oxidation process occurs in two stages: magnetite is oxidized to... Then by Then gradually transform into The chemical equations for its two stages are shown below: ; ; The global reaction equation can be expressed as follows: ; The chemical reaction equation is as follows: ; In the formula, The chemical reaction rate of the material layer; Specific surface area; Oxygen concentration in the gas phase, unit: mol / m³ 3 ; The equilibrium concentration of oxygen in the gas phase, unit: mol / m³ 3 ; ρ is the mass transfer coefficient of oxygen, in m / s; Radius of the unreacted magnetite nucleus, in meters (m). Radius of the pellet, in meters (m). Oxygen diffusion coefficient, unit: m 2 / s; The value represents the oxidation rate of magnetite, in m / s.

[0039] The chemical reaction in the embedded SNCR denitrification process is as follows: when ammonia droplets are sprayed into the high-temperature flue gas area of ​​the second stage of the chain grate machine, the droplets first evaporate and release ammonia gas. The generated ammonia gas then undergoes a selective non-catalytic reduction reaction with nitrogen oxides in the flue gas within a suitable temperature window, thereby achieving denitrification.

[0040] To illustrate this process, this embodiment employs a two-step competing reaction mechanism to describe the SNCR denitrification process. This mechanism describes the main characteristics of the SNCR reaction, specifically including ammonia evaporation and NOx reduction, as follows: ; .

[0041] The reaction kinetic mechanism is shown in Table 1.

[0042] Table 1 Kinetic mechanism of denitrification reaction

[0043] The parameters in the table are as follows: Pre-exponential factors; Temperature index; It is the activation energy; The rate constant of the first reaction; is the reaction rate constant for the second reaction.

[0044] S3: Initialize the running parameters of the geometric model and mesh the geometric model; wherein, the running parameters are the corresponding boundary conditions and the initial values ​​of the SNCR injection parameters.

[0045] In practice, actual production data is collected under stable operating conditions of the chain grate machine. The collected data is processed, and abnormal data is removed based on data from a stable production period. Boundary conditions are jointly determined by combining the test results. The boundary conditions include at least one or more of the following: flue gas temperature, flow rate, composition, machine speed, and material layer thickness in each section of the chain grate machine.

[0046] like Figure 3 As shown, the number of spray guns, their arrangement, diameter, and nozzle diameter are predetermined by the embedded SNCR spray structure. Given the fixed embedded SNCR spray structure and limited adjustable parameters on-site, one or more of the following are selected as SNCR spray parameters: spray speed, ammonia-nitrogen molar ratio, and ammonia concentration. Each SNCR spray parameter is based on the actual operating conditions of the chain grate machine in production. Certain variations are set on these base values ​​to create different value ranges and levels, which are then used for subsequent parameter combination simulation analysis. Therefore, this embodiment only focuses on optimizing the aforementioned adjustable on-site operating parameters.

[0047] S4: Based on the geometric model of mesh generation, the reaction parameters inside the chain grate are obtained through simulation calculation. Based on the reaction parameters, the temperature field distribution, flow field distribution, ammonia concentration field distribution, NOx concentration field distribution, denitrification efficiency, and ammonia slip results are obtained. Among them, the denitrification efficiency, ammonia slip results, and operating parameters are selected as the basis for optimization.

[0048] In practical implementation, after determining the adjustment variables and their value ranges for the SNCR injection parameters, a numerical simulation is performed on the process of pellet production within the chain grate and its coupling with embedded SNCR denitrification. During the simulation, single-factor parameter optimization analyses are conducted for the injection velocity, ammonia-nitrogen molar ratio, and ammonia concentration. Taking each set of single-factor parameter conditions as an example, the pellet production process within the chain grate, as well as the processes of reducing agent injection, evaporation, mixing and diffusion, and NOx reduction reaction, are simulated to obtain the denitrification efficiency and ammonia slip results under the corresponding conditions. Preferably, the temperature field distribution, flow field distribution, ammonia concentration field distribution, and NOx concentration field distribution within the chain grate can also be output simultaneously to assist in analyzing the influence of different parameter changes on the embedded SNCR denitrification effect.

[0049] S4: Determine whether the selected optimization criteria meet the preset conditions: if yes, output the SNCR injection parameters; if no, adjust the SNCR injection parameters in the chain grate machine based on the optimization criteria and return to S3.

[0050] More specifically, the preset conditions that the optimization criteria satisfy are as follows: When the denitrification efficiency is greater than or equal to the preset denitrification efficiency threshold, the ammonia slip concentration is less than or equal to the preset ammonia slip threshold, and all operating parameters are within the preset value range, it indicates that the preset conditions are met; among them, the operating parameters include the simultaneous ammonia-nitrogen molar ratio, ammonia concentration, and injection speed.

[0051] The specific process of adjusting the SNCR injection parameters in the chain grate machine based on optimization criteria is as follows: Based on the value ranges of each SNCR injection parameter and the current value corresponding to the optimization criteria, the values ​​of each SNCR injection parameter in the simulated pellet production process within the chain grate machine are adjusted. The value range is obtained by setting a preset fluctuation amount based on the actual operating conditions of each SNCR injection parameter under the chain grate machine production site. Specifically, the adjustment strategy is as follows: when the denitrification efficiency is lower than the preset denitrification efficiency threshold and the ammonia slip concentration does not exceed the preset ammonia... When the escape threshold is reached, increase the ammonia-nitrogen molar ratio or ammonia concentration and increase the injection speed to increase the reducing agent dosage and enhance the mixing of NH3 and NOx; when the ammonia escape concentration exceeds the preset ammonia escape threshold, decrease the ammonia-nitrogen molar ratio or ammonia concentration and adjust the injection speed to ensure that the reducing agent is fully mixed and reacted within the effective temperature window; when neither the denitrification efficiency nor the ammonia escape meets the preset conditions, comprehensively adjust the ammonia-nitrogen molar ratio, ammonia concentration, and injection speed until the denitrification efficiency is greater than or equal to the preset denitrification efficiency threshold and the ammonia escape concentration is less than or equal to the preset ammonia escape threshold.

[0052] In specific implementation, this embodiment conducts single-factor simulation analysis on injection speed, ammonia-nitrogen molar ratio, and ammonia concentration to clarify the influence trend of each SNCR injection parameter on the embedded SNCR denitrification efficiency and ammonia escape in the chain grate machine, and determines the value range and optimal value of each parameter accordingly, providing a basis for determining the optimal injection parameters in the future.

[0053] This embodiment examines the denitrification efficiency and ammonia slip effect under different injection speeds, ammonia-nitrogen molar ratios, and ammonia concentrations, as shown in Table 2. The table reveals an optimal set of parameters: injection speed 100 m / s, ammonia-nitrogen ratio 1.4, and ammonia concentration 20%. The NO concentration distribution cloud map within the pH range under these optimal parameters is shown below. Figure 5 As shown, the temperature distribution cloud map of the pH range under optimal parameters is as follows: Figure 4 As shown.

[0054] Table 2 Denitrification efficiency and ammonia slip under different parameters

[0055] Example 2

[0056] This embodiment provides an embedded SNCR parameter optimization system for a chain grate machine used in coupled pellet production, including: Geometric model construction module: used to construct the geometric model of the chain grate machine for numerical simulation based on the structural dimensional parameters of the chain grate machine; Reaction control equation determination module: used to determine the reaction control equation of the geometric model; the reaction control equation is used to simulate the process of pellet production in the chain grate and coupled with embedded SNCR denitrification, including the physical process, chemical reaction and embedded SNCR denitrification process in the pellet production process; Parameter setting and simulation module: Initializes the operating parameters of the geometric model and performs mesh generation on the geometric model; wherein, the operating parameters are the corresponding boundary conditions and initial values ​​of SNCR injection parameters; based on the meshed geometric model, simulation calculations are performed to obtain the reaction parameters within the chain grate machine, and based on the reaction parameters, the temperature field distribution, flow field distribution, ammonia concentration field distribution, NOx concentration field distribution, denitrification efficiency, and ammonia slip results are obtained; wherein, the denitrification efficiency, ammonia slip results, and SNCR injection parameters are selected as optimization criteria; Model optimization module: Determines whether the selected optimization criteria meet the preset conditions: if yes, outputs the SNCR injection parameters; if no, adjusts the SNCR injection parameters in the chain grate machine based on the optimization criteria and returns to the parameter setting and simulation module.

[0057] It is understood that the same or similar parts in the above embodiments can be referred to each other, and the contents not described in detail in some embodiments can be referred to the same or similar contents in other embodiments.

[0058] Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Those skilled in the art can make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention.

Claims

1. A method for optimizing embedded SNCR parameters in a chain grate machine for coupled pellet production, characterized in that, include: S1: Construct a geometric model for numerical simulation of the chain grate machine based on its structural dimensional parameters; S2: Determine the reaction control equation of the geometric model; the reaction control equation is used to simulate the process of pellet production in the chain grate and coupled with embedded SNCR denitrification, including the physical process, chemical reaction and embedded SNCR denitrification process in the pellet production process; S3: Initialize the running parameters of the geometric model and mesh the geometric model; wherein, the running parameters are the corresponding boundary conditions and the initial values ​​of the SNCR injection parameters; S4: Based on the geometric model of mesh generation, the reaction parameters inside the chain grate are obtained by simulation calculation, and the temperature field distribution, flow field distribution, ammonia concentration field distribution, NOx concentration field distribution, denitrification efficiency and ammonia slip results are obtained based on the reaction parameters; Among them, denitrification efficiency, ammonia slip results and SNCR injection parameters were selected as the optimization basis; S5: Determine whether the selected optimization criteria meet the preset conditions: if yes, output the SNCR injection parameters; if no, adjust the SNCR injection parameters in the chain grate machine based on the optimization criteria and return to S3.

2. The method according to claim 1, characterized in that, In S1, the geometric model includes a fume hood, a wind box, a material layer area, and an embedded SNCR denitrification spray structure; the embedded SNCR denitrification spray structure includes at least the number of spray guns, the position of the spray guns, and the nozzle diameter. Furthermore, the governing equations for the gas flow, material layer movement, and interphase interactions within the chain grate specifically include: Total mass conservation equation: ； ； In the formula, The average density is kg / m³. 3 ; For time; It is a velocity vector with direction; for Phase volume fraction; for Phase density; for Phase transfer to Phase quality; for Phase transfer to Phase quality; For chemical reaction source terms; The total number of phases in a multiphase system; The mass fraction of the gas phase satisfies the following equation: ； In the formula, for Phase density; For the first Mass fraction of each substance; This represents the total mass within the corresponding grid. For time; For Hamiltonian differential operators; for The velocity vector of the phase; For the first The diffusion flux vector of a substance; For the first The net diffusion flux divergence term of a substance due to diffusion; For the first The net reaction rate term for the formation or consumption of a substance due to a chemical reaction; For the first Additional source terms for each substance; Momentum conservation equation: ； In the formula, for Phase velocity; for Unsteady-state terms of the phase momentum conservation equation; for The convection term of the phase momentum conservation equation; for The pressure term in the phase momentum conservation equation; For pressure gradient; It is the vector of gravitational acceleration; for The diffusion term of the phase momentum conservation equation; for The gravity term in the equation of conservation of phase momentum; for The pressure strain tensor of the phase; For the momentum transfer of forces between two phases; For the reason Phase transfer to Interphase mass transfer rate; To act on Other volume force terms of the phase; To act on Turbulent diffusion force term of the phase; Energy conservation equation: ； In the formula, for Enthalpy of phase; For the transfer of heat between two phases; for The velocity vector of the phase; for Phase pressure; for The heat flux density vector of the phase; For source terms; for The work term done by viscous forces in the phase energy conservation equation.

3. The method according to claim 1, characterized in that, The physical processes include the evaporation and condensation of moisture in the pellets; The governing equation for water evaporation is: ； ； in, This represents the rate of water evaporation. Porosity; is the mass transfer coefficient of gaseous water vapor; Specific surface area; This represents the equilibrium concentration of water vapor in the gas-solid system. This refers to the water content of the gas. The critical value used to divide the evaporation process into two stages; This represents the current moisture content of the pellets. The radius of the pellet; Let be the current wetting radius of the pellet, in meters (m). The effective diffusion coefficient of water vapor; The governing equation for the condensation process is: ； In the formula, The condensation rate of moisture is expressed in kg / (m²). 3 ·s).

4. The method according to claim 1, characterized in that, The chemical reaction includes the oxidation of magnetite, specifically the oxidation of magnetite to... Then gradually transformed into The chemical equations for its two stages are shown below: ； ； The global reaction equation can be expressed as follows: ； The chemical reaction equation is as follows: ； In the formula, The chemical reaction rate of the material layer; Specific surface area; This represents the oxygen concentration in the gas phase. This represents the equilibrium concentration of oxygen in the gas phase. is the mass transfer coefficient of oxygen; The radius of the unreacted magnetite nucleus; The radius of the pellet; The oxygen diffusion coefficient; The value represents the oxidation rate of magnetite.

5. The method according to claim 1, characterized in that, The embedded SNCR denitrification process includes ammonia evaporation and NOx reduction reaction, and the mechanism is as follows: ； 。 6. The method according to claim 1, characterized in that, The boundary conditions include at least one or more of the following: flue gas temperature, flow rate, composition, machine speed, and material layer thickness in each section of the chain grate machine.

7. The method according to claim 1, characterized in that, The SNCR injection parameters include one or more of the following: injection speed, ammonia-nitrogen molar ratio, and ammonia concentration.

8. The method according to claim 1, characterized in that, The optimization criteria in S4 are based on the following preset conditions: When the denitrification efficiency is greater than or equal to the preset denitrification efficiency threshold, the ammonia escape concentration is less than or equal to the preset ammonia escape threshold, and the SNCR injection parameters are within the preset value range, it indicates that the preset conditions are met.

9. The method according to claim 1, characterized in that, The specific process of adjusting the SNCR injection parameters in the chain grate machine based on optimization criteria is as follows: Based on the value ranges of each SNCR injection parameter and the current value corresponding to the optimization criteria, the values ​​of each SNCR injection parameter in the simulated pellet production process within the chain grate machine are adjusted. The value range is obtained by setting a preset fluctuation amount based on the actual operating conditions of each SNCR injection parameter under the chain grate machine production site. The specific adjustment strategy is as follows: when the denitrification efficiency is lower than the preset denitrification efficiency threshold and the ammonia slip concentration does not exceed the preset threshold... When the ammonia slip threshold is reached, increase the ammonia-nitrogen molar ratio or ammonia concentration and increase the injection speed to increase the reducing agent dosage and enhance the mixing of NH3 and NOx; when the ammonia slip concentration exceeds the preset ammonia slip threshold, decrease the ammonia-nitrogen molar ratio or ammonia concentration and adjust the injection speed to ensure that the reducing agent is fully mixed and reacted within the effective temperature window; when neither the denitrification efficiency nor the ammonia slip meets the preset conditions, comprehensively adjust the ammonia-nitrogen molar ratio, ammonia concentration, and injection speed until the denitrification efficiency is greater than or equal to the preset denitrification efficiency threshold and the ammonia slip concentration is less than or equal to the preset ammonia slip threshold.

10. An embedded SNCR parameter optimization system for a chain grate machine used in coupled pellet production, the system being used to perform the steps of the method according to any one of claims 1-9, characterized in that, include: Geometric model construction module: used to construct the geometric model of the chain grate machine for numerical simulation based on the structural dimensional parameters of the chain grate machine; Reaction control equation determination module: used to determine the reaction control equation of the geometric model; the reaction control equation is used to simulate the process of pellet production in the chain grate and coupled with embedded SNCR denitrification, including the physical process, chemical reaction and embedded SNCR denitrification process in the pellet production process; Parameter setting and simulation module: Initializes the operating parameters of the geometric model and performs mesh generation on the geometric model; wherein, the operating parameters are the corresponding boundary conditions and initial values ​​of SNCR injection parameters; based on the meshed geometric model, simulation calculations are performed to obtain the reaction parameters within the chain grate machine, and based on the reaction parameters, the temperature field distribution, flow field distribution, ammonia concentration field distribution, NOx concentration field distribution, denitrification efficiency, and ammonia slip results are obtained; wherein, the denitrification efficiency, ammonia slip results, and SNCR injection parameters are selected as optimization criteria; Model optimization module: Determines whether the selected optimization criteria meet the preset conditions: if yes, outputs the SNCR injection parameters; if no, adjusts the SNCR injection parameters in the chain grate machine based on the optimization criteria and returns to the parameter setting and simulation module.

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