Combustion control method and system suitable for preventing coking of Zhundong coal

Abstract

The invention provides a combustion control method and system suitable for Zhundong coal anti-coking, and relates to the technical field of combustion control, and the combustion control method comprises the following steps: determining combustion characteristic parameters of Zhundong coal; based on the combustion characteristic parameters of the Zhundong coal, establishing a combustion mathematical model of the Zhundong coal combustion process; the optimal combustion parameters of the Zhundong coal under different combustion working conditions are obtained through the combustion mathematical model, the three-dimensional numerical solution of the Zhundong coal in the combustion and coking process in the hearth is obtained through numerical simulation on the basis of the optimal combustion parameters, all the combustion parameters are optimized, and the optimal matching scheme for preventing coking combustion is obtained; the operation parameters of the combustion system and the coal pulverizing system are automatically adjusted, the opening degree of electric adjusting valves on a primary air pipe and a secondary air pipe is adjusted, the rotating speed of an air blower is adjusted through a frequency converter, the coal feeding amount and the primary air temperature of the coal pulverizing system are adjusted, and precise control and anti-coking optimization of the east Junggar coal combustion process are achieved.

Description

Technical Field

[0001] The invention relates to a combustion control technology, and in particular to a combustion control method and system suitable for preventing coking of Zhundong coal. Background Art

[0002] Zhundong coal is one of the important coal resources in my country. It has the advantages of low ash, ultra-low sulfur, and high calorific value, but it also has the characteristics of easy coking. In thermal power plants, the use of Zhundong coal often faces the problem of coking, which not only reduces the thermal efficiency of the boiler, but also may cause equipment damage and safety hazards.

[0003] Traditional anti-coking methods mainly include mechanical ash cleaning, soot blowing and water washing, but these methods often interrupt the normal operation of the boiler and reduce power generation efficiency. In addition, these methods are passive treatments and cannot fundamentally solve the coking problem of Zhundong coal.

[0004] In recent years, some researchers have tried to reduce coking by optimizing combustion control. For example, the coking tendency can be reduced by adjusting the ratio of primary air to secondary air and controlling the furnace temperature distribution. However, these methods are often based on static control based on experience and are difficult to adapt to the influence of dynamic factors such as coal quality fluctuations and load changes.

[0005] At present, the combustion control system of Zhundong coal generally has the following problems:

[0006] The lack of precise modeling of the characteristics of Zhundong coal makes it difficult to accurately predict the coking trend; the control strategy is relatively simple and cannot effectively coordinate multiple control variables; it is difficult to achieve real-time optimization and adaptive adjustment, and the ability to cope with changes in coal quality and load is limited; and it fails to fully utilize advanced control theories and intelligent algorithms to improve control effects.

[0007] Therefore, it is of great practical significance and application value to develop an intelligent anti-coking combustion control system suitable for Zhundong coal to achieve precise control of the combustion process and anti-coking optimization. Summary of the invention

[0008] The embodiments of the present invention provide a combustion control method and system suitable for preventing coking of Zhundong coal, which can solve the problems in the prior art.

[0009] According to a first aspect of the embodiments of the present invention,

[0010] Provide combustion control methods suitable for preventing coking of Zhundong coal, including:

[0011] The pre-obtained Zhundong coal sample is crushed and reduced to obtain a coal sample for analysis; the coal sample for analysis is subjected to industrial analysis, elemental analysis and ash composition analysis to determine the combustion characteristic parameters of the Zhundong coal, wherein the combustion characteristic parameters include the theoretical combustion temperature of the Zhundong coal under given excess air coefficient, coal inlet temperature and primary air temperature, the combustion activation energy of the Zhundong coal under different particle sizes and heating rates, and the coking index of the Zhundong coal;

[0012] Based on the combustion characteristic parameters of Zhundong coal, a combustion mathematical model of the combustion process of the Zhundong coal is established, and the combustion mathematical model includes a three-dimensional heat transfer equation of the combustion process of the Zhundong coal in the furnace, a chemical reaction kinetic equation of the combustion product, and a fluid dynamics equation; using the combustion mathematical model, the optimal combustion parameters of the Zhundong coal under different combustion conditions are obtained, and based on the optimal combustion parameters, a three-dimensional numerical solution of the combustion and coking process of the Zhundong coal in the furnace is obtained through numerical simulation, and each combustion parameter is optimized to obtain the best matching scheme for anti-coking combustion; the optimal combustion parameters include at least one of primary air temperature, secondary air temperature, primary air speed, secondary air speed, coal powder particle size, excess air coefficient, and burnout air speed;

[0013] According to the optimal matching scheme, the operating parameters of the combustion system and the pulverizing system are automatically adjusted, including adjusting the opening of the electric regulating valves on the primary and secondary air ducts, adjusting the speed of the blower through the frequency converter, and adjusting the coal feed rate and primary air temperature of the pulverizing system, so as to achieve precise control of the Zhundong coal combustion process and anti-coking optimization.

[0014] In an optional embodiment,

[0015] The pre-obtained Zhundong coal sample is crushed and reduced to obtain a coal sample for analysis; the coal sample for analysis is subjected to industrial analysis, elemental analysis and ash composition analysis to determine the combustion characteristic parameters of the Zhundong coal, including:

[0016] The pre-acquired Zhundong coal sample is crushed and reduced to obtain a coal sample for analysis; the coal sample for analysis is subjected to industrial analysis to determine the industrial air-dried basis components of the coal sample for analysis, wherein the industrial air-dried basis components include at least one of the mass fractions of water, ash, volatile matter and fixed carbon; the coal sample for analysis is subjected to elemental analysis to determine the elemental air-dried basis components of the coal sample for analysis, wherein the elemental air-dried basis components include the mass fractions of C, H, O, N and S elements; the coal sample for analysis is subjected to ash component analysis by X-ray fluorescence spectrometry to determine the mass fractions of major oxides in the ash of the coal sample for analysis;

[0017] The dry ash-free basis high calorific value of the coal sample for analysis is measured by a calorimeter, and the air-dry basis low calorific value of the coal sample for analysis is calculated according to the industrial air-dry basis components and the elemental air-dry basis components; based on the air-dry basis low calorific value and in combination with the material energy conservation equation, the theoretical combustion temperature of the coal sample for analysis under the conditions of given excess air coefficient, coal inlet temperature and primary air temperature is determined;

[0018] Conducting a thermogravimetric analysis experiment on the coal sample for analysis to obtain thermogravimetric curve data of the coal sample for analysis under different heating rate conditions; performing a linear fit on the reciprocal of the absolute temperature using the pyrolysis conversion rate based on the thermogravimetric curve data, and determining the combustion activation energy of the coal sample for analysis under different particle sizes and heating rate conditions through the slope of the fitting line;

[0019] The coking index of the Zhundong coal is obtained by calculating the mass fraction of the main oxides in the ash of the analytical coal sample determined by the ash composition analysis using the coking tendency index calculation formula.

[0020] In an optional embodiment,

[0021] Based on the combustion characteristic parameters of the Zhundong coal, a combustion mathematical model of the Zhundong coal combustion process is established. The combustion mathematical model includes a three-dimensional heat transfer equation of the Zhundong coal combustion process in the furnace, a chemical reaction kinetic equation of the combustion product, and a fluid dynamics equation including:

[0022] Divide the computational grid and set boundary conditions according to the geometric structure and operating parameters of the coal-fired boiler furnace;

[0023] A heat transfer model describing the radiation heat transfer during coal pulverized combustion is established, and the P-1 model is used to solve the radiation transfer equation to obtain the radiation heat flux density distribution; the P-1 model expands the radiation intensity into a spherical harmonic function series, truncated to the first-order term, and obtains the diffusion equation for the incident radiation;

[0024] A heat transfer model describing the convective heat transfer during coal powder combustion is established. Combined with the velocity field and temperature field obtained by gas-solid two-phase flow calculation, the convective heat transfer coefficient is solved using the criterion number correlation formula to obtain the convective heat flux density distribution. The criterion number correlation formula is based on the empirical formula under different flow conditions, and the convective heat transfer coefficient is expressed as a function of the dimensionless parameters of the Reynolds number and the Prandtl number.

[0025] A heat transfer model describing the sensible heat release during pulverized coal combustion is established. The sensible heat source term distribution is obtained based on the fuel consumption rate calculated by the combustion model and the low calorific value of the fuel.

[0026] The three heat transfer mechanisms of radiation, convection and sensible heat release are comprehensively considered to construct the total energy conservation equation of the combustion process in the furnace; the variables of the velocity field, temperature field and component concentration field of the gas and solid phases are introduced to combine the fluid flow and chemical reaction kinetics equations to form a closed mathematical model;

[0027] The established three-dimensional heat transfer mathematical model is numerically solved, and the control equation is discretized using the finite volume method to obtain the spatial distribution of the parameters of the temperature field and heat flux field in the furnace.

[0028] In an optional embodiment,

[0029] The combustion mathematical model is used to obtain the optimal combustion parameters of the Zhundong coal under different combustion conditions. Based on the optimal combustion parameters, a three-dimensional numerical solution of the combustion and coking process of the Zhundong coal in the furnace is obtained through numerical simulation. The combustion parameters are optimized to obtain the best matching solution for anti-coking combustion, including:

[0030] Using the three-dimensional mathematical model of Zhundong coal combustion, the performance parameters of Zhundong coal combustion under different working conditions are obtained through numerical simulation, and the different working conditions include baseline working conditions, variable load working conditions, variable coal type working conditions, variable coal grinding fineness working conditions and variable burner structure working conditions; based on the numerical simulation results, the influence of various operating parameters on the combustion performance of Zhundong coal is evaluated, the main control factors affecting the combustion of Zhundong coal are screened out, and the best matching parameters for the combustion of Zhundong coal are obtained, and the best matching parameters include the primary and secondary air nozzle deflection angles of the burner, the coal mill fineness, and the cyclone structure parameters;

[0031] Based on the optimal matching parameters of the Zhundong coal combustion, a viscosity mathematical model describing the softening and melting characteristics of Zhundong coal ash is established, and the viscosity mathematical model is embedded in the three-dimensional mathematical model of Zhundong coal combustion. At the same time, considering the force analysis of slag particles in high-temperature flue gas, a three-dimensional coking mathematical model describing the softening, melting, flow and condensation process of slag in the furnace is established;

[0032] The Lagrangian method is used to track the movement trajectory of slag particles and obtain the change history of the temperature, viscosity and velocity parameters of the slag particles. When the slag particles hit the furnace wall or the heating surface, the collision Weber number criterion is used to determine whether the slag particles are coked. The three-dimensional numerical simulation of the movement and coking process of a large number of slag particles in the furnace is carried out to obtain the three-dimensional numerical simulation results of the coking process of Zhundong coal.

[0033] Based on the three-dimensional numerical simulation results of the Zhundong coal coking process, the following anti-coking combustion measures are optimized and matched from the aspects of burner design optimization, coal powder fineness adjustment, and coal blending ratio optimization:

[0034] By rationally arranging the injection angles and injection velocities of each air outlet of the burner, the position of the main combustion zone and the flame shape in the furnace are adjusted; the structural parameters of the secondary air baffle and swirler of the burner are optimized to promote the full mixing of coal powder and air; through the comprehensive use of the above anti-coking combustion measures, on the basis of the best matching parameters of Zhundong coal combustion, the best combustion scheme that takes into account both efficient combustion and coking inhibition is obtained.

[0035] In an optional embodiment,

[0036] According to the optimal matching scheme, the operating parameters of the combustion system and the pulverizing system are automatically adjusted, including adjusting the opening of the electric regulating valves on the primary and secondary air ducts, adjusting the speed of the blower through the frequency converter, and adjusting the coal feed rate and primary air temperature of the pulverizing system, so as to achieve precise control of the Zhundong coal combustion process and anti-coking optimization, including:

[0037] According to the best matching scheme of Zhundong coal combustion optimization and anti-coking, a state space mathematical model describing the dynamic characteristics of the boiler combustion system and the pulverizing system is established. The state variables of the mathematical model include boiler combustion efficiency, NOx emission concentration and furnace outlet flue gas temperature. The control variables include the opening of the electric regulating valves of the primary and secondary air ducts, the frequency setting value of the blower inverter, the coal feed rate of the pulverizing system and the primary air temperature setting value. The disturbance variables include coal quality fluctuations and load changes.

[0038] Based on the state space mathematical model of the boiler combustion system and the pulverizing system, a multivariable model predictive control (MMPC) optimization model is established, with combustion efficiency, NOx emission and coking amount as control targets, the opening of the electric regulating valves of the primary and secondary air ducts, the frequency setting value of the blower inverter, the coal feeding amount of the pulverizing system and the primary air temperature setting value as optimization control variables, and the MMPC optimization control objective function and constraint condition equations are established;

[0039] The MMPC optimization model is transformed into a quadratic programming (QP) problem, and the sequential quadratic programming (SQP) algorithm is used to solve it, and the optimal adjustment amount of each control variable in several future sampling moments is obtained; the optimization results are used to guide the setting of the parameters of the combustion control system in real time, and the opening of the electric regulating valves on the primary and secondary air ducts are adjusted through the corresponding actuators, the speed of the blower is adjusted through the frequency converter, and the coal feed rate and primary air temperature of the pulverizing system are adjusted to achieve precise control of the combustion process.

[0040] In an optional embodiment,

[0041] The method further comprises:

[0042] During the combustion process, the flue gas temperature at different positions in the furnace is detected in real time using thermocouples, the furnace wall temperature distribution is scanned in real time using infrared thermometers, and the flue gas components are detected online using flue gas analyzers.

[0043] The above-mentioned test results are compared with the standard values ​​under the optimal combustion state in real time. When the temperature field deviation or the key flue gas component deviation exceeds the preset threshold, the adaptive optimization control strategy of the combustion parameters is initiated. The dynamic adjustment of the combustion parameters is achieved through the self-learning algorithm and the expert experience knowledge base, and the combustion state is maintained within the optimal operating range for anti-coking, thus realizing the intelligent optimization control of the Zhundong coal combustion system.

[0044] According to a second aspect of the embodiments of the present invention,

[0045] Provide a combustion control system suitable for Zhundong coal coking prevention, including:

[0046] The first unit is used to crush and reduce the pre-acquired Zhundong coal sample to obtain a coal sample for analysis; perform industrial analysis, elemental analysis and ash composition analysis on the coal sample for analysis to determine the combustion characteristic parameters of the Zhundong coal, wherein the combustion characteristic parameters include the theoretical combustion temperature of the Zhundong coal under given excess air coefficient, coal inlet temperature and primary air temperature, the combustion activation energy of the Zhundong coal under different particle sizes and heating rates, and the coking index of the Zhundong coal;

[0047] The second unit is used to establish a combustion mathematical model of the combustion process of the Zhundong coal based on the combustion characteristic parameters of the Zhundong coal, wherein the combustion mathematical model includes a three-dimensional heat transfer equation of the combustion process of the Zhundong coal in the furnace, a chemical reaction kinetic equation of the combustion product, and a fluid dynamics equation; using the combustion mathematical model, the optimal combustion parameters of the Zhundong coal under different combustion conditions are obtained, and based on the optimal combustion parameters, a three-dimensional numerical solution of the combustion and coking process of the Zhundong coal in the furnace is obtained through numerical simulation, and each combustion parameter is optimized to obtain the best matching scheme for anti-coking combustion; the optimal combustion parameters include at least one of primary air temperature, secondary air temperature, primary air speed, secondary air speed, coal powder particle size, excess air coefficient, and burnout air speed;

[0048] The third unit is used to automatically adjust the operating parameters of the combustion system and the pulverizing system according to the optimal matching scheme, including adjusting the opening of the electric regulating valves on the primary air duct and the secondary air duct, adjusting the speed of the blower through the frequency converter, and adjusting the coal feed rate and primary air temperature of the pulverizing system, so as to achieve precise control of the Zhundong coal combustion process and anti-coking optimization.

[0049] According to a third aspect of the embodiments of the present invention,

[0050] An electronic device is provided, comprising:

[0051] processor;

[0052] a memory for storing processor-executable instructions;

[0053] The processor is configured to call the instructions stored in the memory to execute the aforementioned method.

[0054] A fourth aspect of the embodiments of the present invention is:

[0055] A computer-readable storage medium is provided, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the aforementioned method is implemented.

[0056] The combustion mathematical model of this application provides a powerful tool for optimizing the combustion process of Zhundong coal. The model can predict the combustion effect under different operating parameters, such as the impact of adjusting the primary air ratio, secondary air speed, etc. on the combustion temperature field and pollutant generation. For example, increasing the secondary air speed can improve the mixing effect in the burner area, but may lead to increased NOx generation. The model results can also be used to guide boiler design, such as optimizing the burner layout, determining the heating surface layout, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0057] Figure 1 The figure is a flow chart of a combustion control method for preventing coking of Zhundong coal according to an embodiment of the present invention;

[0058] Figure 2 The present invention is a schematic diagram of the structure of a combustion control system suitable for preventing coking of Zhundong coal. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] The technical solution of the present invention is described in detail with specific embodiments below. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described in detail in some embodiments.

[0061] Figure 1 FIG. 1 is a flow chart of a combustion control method for preventing coking of Zhundong coal according to an embodiment of the present invention. Figure 1 As shown, the method includes:

[0062] S101. crushing and reducing the pre-acquired Zhundong coal sample to obtain a coal sample for analysis; performing industrial analysis, elemental analysis and ash composition analysis on the coal sample for analysis to determine the combustion characteristic parameters of the Zhundong coal, wherein the combustion characteristic parameters include the theoretical combustion temperature of the Zhundong coal under given excess air coefficient, coal inlet temperature and primary air temperature, the combustion activation energy of the Zhundong coal under different particle sizes and heating rates, and the coking index of the Zhundong coal;

[0063] S102. Based on the combustion characteristic parameters of Zhundong coal, a combustion mathematical model of the combustion process of the Zhundong coal is established, wherein the combustion mathematical model includes a three-dimensional heat transfer equation of the combustion process of the Zhundong coal in the furnace, a chemical reaction kinetic equation of the combustion products, and a fluid dynamics equation; using the combustion mathematical model, the optimal combustion parameters of the Zhundong coal under different combustion conditions are obtained, and based on the optimal combustion parameters, a three-dimensional numerical solution of the combustion and coking process of the Zhundong coal in the furnace is obtained through numerical simulation, and each combustion parameter is optimized to obtain the best matching scheme for anti-coking combustion; the optimal combustion parameters include at least one of primary air temperature, secondary air temperature, primary air speed, secondary air speed, coal powder particle size, excess air coefficient, and burnout air speed;

[0064] S103. According to the optimal matching scheme, the operating parameters of the combustion system and the pulverizing system are automatically adjusted, including adjusting the opening of the electric regulating valves on the primary air duct and the secondary air duct, adjusting the speed of the blower through the frequency converter, and adjusting the coal feed rate and primary air temperature of the pulverizing system, so as to achieve precise control of the Zhundong coal combustion process and anti-coking optimization.

[0065] Exemplarily, the Zhundong coal sample is first pretreated and analyzed. A representative Zhundong coal sample is collected from the coal yard of the power plant, and the coal sample is crushed to less than 5 mm using a jaw crusher, and then the sample is reduced to about 500 g using the quartering method. The moisture, ash, volatile matter and fixed carbon content of the coal sample are measured using an industrial analyzer. The carbon, hydrogen, oxygen, nitrogen and sulfur content of the coal sample is measured using an elemental analyzer. The main chemical components of the coal ash are analyzed using an X-ray fluorescence spectrometer.

[0066] Through the above analysis, the typical combustion characteristic parameters of Zhundong coal are obtained. For example, under the conditions of excess air coefficient of 1.2, coal inlet temperature of 25℃ and primary air temperature of 350℃, the theoretical combustion temperature of Zhundong coal is 2150℃. Thermogravimetric analysis was used to determine the combustion activation energy under different particle sizes (such as <75μm, 75-150μm, 150-200μm) and different heating rates (such as 10℃ / min, 20℃ / min, 30℃ / min). The results showed that the average combustion activation energy of Zhundong coal was 120kJ / mol. The coking index of Zhundong coal was determined to be 0.8 using a high-temperature melting microscope.

[0067] Based on the combustion characteristic parameters obtained, a mathematical model of the Zhundong coal combustion process is established. The model includes the energy conservation equation describing the heat transfer in the furnace, the mass conservation equation describing the chemical reaction of the combustion products, and the momentum conservation equation describing the fluid motion. Computational fluid dynamics (CFD) software, such as ANSYS Fluent, is used to solve the above equations and simulate the combustion process under different working conditions.

[0068] The optimal combustion parameters are determined through parametric research. For example, multiple groups of simulation calculations are performed by adjusting the primary air temperature from 300℃ to 400℃, the secondary air temperature from 900℃ to 1100℃, the primary air speed from 18m / s to 25m / s, the secondary air speed from 45m / s to 60m / s, the coal powder particle size from 60μm to 90μm, the excess air coefficient from 1.15 to 1.25, the burnout air speed from 30m / s to 40m / s, and other parameters. Evaluation indicators include combustion efficiency, NOx emission concentration, ash melting characteristics, etc.

[0069] According to the simulation results, the best matching scheme for anti-coking combustion is obtained. For example, the primary air temperature is 370℃, the secondary air temperature is 1050℃, the primary air speed is 22m / s, the secondary air speed is 55m / s, the average particle size of the coal powder is 75μm, the excess air coefficient is 1.2, and the burnout air speed is 35m / s. Under this scheme, the predicted combustion efficiency can reach 98.5%, and the NOx emission concentration is less than 200mg / Nm 3 The ash melting point is higher than 1400℃, which effectively reduces the coking tendency.

[0070] The best matching scheme is applied to the actual combustion control system. The corresponding control logic is set in the distributed control system (DCS) to realize the automatic adjustment of the combustion parameters. Specifically, the primary air temperature is controlled at 370±5℃ by adjusting the opening of the electric regulating valve on the primary air duct; the secondary air temperature is controlled at 1050±10℃ by adjusting the opening of the electric regulating valve on the secondary air duct; the primary air speed is adjusted by the frequency converter to keep the primary air speed at 22±1m / s; the secondary air speed is adjusted to keep the secondary air speed at 55±2m / s.

[0071] At the same time, the pulverizing system is adjusted accordingly. The coal feeding amount is controlled by the variable frequency coal feeder, and the feedback from the coal quality online analyzer is combined to ensure that the excess air coefficient is within the range of 1.2±0.02. The separator speed of the coal mill is adjusted to ensure that the average particle size of the coal powder is 75±5μm. In addition, the hot air temperature entering the coal mill is controlled by adjusting the opening of the hot air gate to maintain the primary air temperature near the set value.

[0072] To further optimize the control effect, an advanced control strategy based on model predictive control (MPC) is adopted. A dynamic prediction model for key indicators including boiler combustion efficiency, NOx emission concentration, furnace outlet flue gas temperature, etc. is established. The primary air temperature, secondary air temperature, primary air speed, secondary air speed, coal feed rate, etc. are used as control variables, and disturbance factors such as coal quality fluctuations and load changes are considered. The multi-objective optimization problem is solved online to obtain the optimal control sequence.

[0073] Through the implementation of the above technical solution, the operating data of a 660MW subcritical boiler showed that the boiler combustion efficiency increased by 0.8 percentage points to 98.7%; the NOx emission concentration decreased by 25% and stabilized at 180mg / Nm 3 The flue gas temperature at the furnace outlet was reduced by 35°C, effectively alleviating the coking problem on the heating surface of the high-temperature section; the continuous operation cycle of the boiler was extended from the original 3 months to 5 months, significantly improving the reliability and economy of the unit.

[0074] This anti-coking combustion control method is not only applicable to Zhundong coal, but can also be applied to other types of coal that are prone to coking, providing technical support for the clean and efficient operation of coal-fired power plants. Future research directions include introducing artificial intelligence technology into the control system to further improve the system's adaptability and robustness to cope with more complex and changeable working conditions.

[0075] In an optional embodiment,

[0076] The pre-obtained Zhundong coal sample is crushed and reduced to obtain a coal sample for analysis; the coal sample for analysis is subjected to industrial analysis, elemental analysis and ash composition analysis to determine the combustion characteristic parameters of the Zhundong coal, including:

[0077] The pre-acquired Zhundong coal sample is crushed and reduced to obtain a coal sample for analysis; the coal sample for analysis is subjected to industrial analysis to determine the industrial air-dried basis components of the coal sample for analysis, wherein the industrial air-dried basis components include at least one of the mass fractions of water, ash, volatile matter and fixed carbon; the coal sample for analysis is subjected to elemental analysis to determine the elemental air-dried basis components of the coal sample for analysis, wherein the elemental air-dried basis components include the mass fractions of C, H, O, N and S elements; the coal sample for analysis is subjected to ash component analysis by X-ray fluorescence spectrometry to determine the mass fractions of major oxides in the ash of the coal sample for analysis;

[0078] The dry ash-free basis high calorific value of the coal sample for analysis is measured by a calorimeter, and the air-dry basis low calorific value of the coal sample for analysis is calculated according to the industrial air-dry basis components and the elemental air-dry basis components; based on the air-dry basis low calorific value and in combination with the material energy conservation equation, the theoretical combustion temperature of the coal sample for analysis under the conditions of given excess air coefficient, coal inlet temperature and primary air temperature is determined;

[0079] Conducting a thermogravimetric analysis experiment on the coal sample for analysis to obtain thermogravimetric curve data of the coal sample for analysis under different heating rate conditions; performing a linear fit on the reciprocal of the absolute temperature using the pyrolysis conversion rate based on the thermogravimetric curve data, and determining the combustion activation energy of the coal sample for analysis under different particle sizes and heating rate conditions through the slope of the fitting line;

[0080] The coking index of the Zhundong coal is obtained by calculating the mass fraction of the main oxides in the ash of the analytical coal sample determined by the ash composition analysis using the coking tendency index calculation formula.

[0081] For example, the Zhundong coal sample is first pre-treated. A representative Zhundong coal sample is collected from the coal yard of a power plant, crushed to less than 5 mm using a jaw crusher, and then reduced to about 500 g using the quartering method to obtain a coal sample for analysis. This process ensures the representativeness and uniformity of the sample.

[0082] The coal samples for analysis were subjected to industrial analysis to determine their industrial air-dried components. The mass fractions of moisture, ash, volatile matter and fixed carbon were determined using a fully automatic industrial analyzer using the GBYT 212-2008 standard method. Taking a certain test result as an example, the moisture content of Zhundong coal was 9.2%, the ash content was 6.8%, the volatile matter was 29.5%, and the fixed carbon was 54.5%. These data reflect the basic physical properties of the coal samples.

[0083] Then, elemental analysis was performed to determine the air-dried composition of the coal sample. The mass fractions of C, H, O, N, and S were determined using an elemental analyzer using the GBYT 476-2008 standard method. The typical elemental composition of Zhundong coal is: C72.5%, H 4.2%, O 15.8%, N 0.9%, and S 0.4%. These data provide the basis for subsequent combustion calculations.

[0084] The ash composition of the coal sample for analysis was analyzed by X-ray fluorescence spectrometry. The mass fraction of the main oxides in the coal ash was determined using an X-ray fluorescence spectrometer. The typical composition of Zhundong coal ash is: SiO250.2%, Al2O3 28.5%, Fe2O37.8%, CaO 5.1%, MgO 1.9%, Na2O 0.7%, K2O 1.2%, TiO2 1.5%. These data are crucial for evaluating the melting characteristics and coking tendency of coal ash.

[0085] The dry ash-free higher calorific value of the coal sample for analysis was measured using a calorimeter. The GBYT 213-2008 standard method was used and an isothermal calorimeter was used for measurement. The test results showed that the dry ash-free higher calorific value of Zhundong coal was 30.5MJ / kg.

[0086] Based on the results of industrial analysis and elemental analysis, the air-dried lower calorific value of the coal sample for analysis is calculated by the Dulong formula. The calculation process takes into account the latent heat of water vapor generated by the combustion of hydrogen. Taking the above data as an example, the calculated air-dried lower calorific value of Zhundong coal is 27.8MJ / kg.

[0087] Based on the low calorific value of air dry basis and combined with the material energy conservation equation, the theoretical combustion temperature of the coal sample for analysis under given conditions is determined. Assuming the excess air coefficient is 1.2, the coal inlet temperature is 25°C, the primary air temperature is 350°C, and considering the heat capacity and dissociation of the combustion products, the theoretical combustion temperature of Zhundong coal is calculated to be 2150°C.

[0088] Thermogravimetric analysis experiments were conducted on the coal samples for analysis. Using a synchronous thermal analyzer, thermogravimetric analysis was performed at three heating rates of 10℃ / min, 20℃ / min, and 30℃ / min in a nitrogen atmosphere to obtain thermogravimetric curve data under different heating rate conditions.

[0089] Based on the thermogravimetric curve data, the reciprocal of the absolute temperature was linearly fitted with the pyrolysis conversion rate. The data was processed by the Coates-Redfern integration method to obtain a fitting straight line. According to the slope of the fitting straight line, the combustion activation energy of the coal sample for analysis at different particle sizes (such as <75μm, 75-150μm, 150-200μm) and heating rate conditions was determined. The results showed that the average combustion activation energy of Zhundong coal was 120kJ / mol.

[0090] According to the results of ash composition analysis, the coking index of Zhundong coal is calculated by the coking tendency index calculation formula. This formula takes into account the mass fraction of each main oxide in the ash and its effect on coking. The coking index of Zhundong coal is calculated to be 0.8, indicating that it has a medium coking tendency.

[0091] Through the above analysis methods, the combustion characteristics of Zhundong coal were fully characterized. These data provide an important basis for the subsequent establishment of combustion mathematical models, optimization of combustion parameters and formulation of anti-coking strategies. For example, higher fixed carbon content and lower volatile matter content indicate that the combustion temperature and residence time need to be reasonably controlled; lower sulfur content is conducive to reducing SO2 emissions; higher theoretical combustion temperature indicates that attention should be paid to high-temperature corrosion problems; and medium coking index indicates that appropriate anti-coking measures need to be taken.

[0092] This set of analysis methods is not only applicable to Zhundong coal, but can also be promoted and applied to the combustion characteristics of other types of coal. In the future, it is possible to consider introducing advanced online analysis technologies, such as laser induced breakdown spectroscopy (LIBS), to achieve real-time monitoring of coal quality and provide more timely and accurate data support for combustion optimization control.

[0093] In an optional embodiment,

[0094] Based on the combustion characteristic parameters of the Zhundong coal, a combustion mathematical model of the Zhundong coal combustion process is established. The combustion mathematical model includes a three-dimensional heat transfer equation of the Zhundong coal combustion process in the furnace, a chemical reaction kinetic equation of the combustion product, and a fluid dynamics equation including:

[0095] Divide the computational grid and set boundary conditions according to the geometric structure and operating parameters of the coal-fired boiler furnace;

[0096] A heat transfer model describing the radiation heat transfer during coal pulverized combustion is established, and the P-1 model is used to solve the radiation transfer equation to obtain the radiation heat flux density distribution; the P-1 model expands the radiation intensity into a spherical harmonic function series, truncated to the first-order term, and obtains the diffusion equation for the incident radiation;

[0097] A heat transfer model describing the convective heat transfer during coal powder combustion is established. Combined with the velocity field and temperature field obtained by gas-solid two-phase flow calculation, the convective heat transfer coefficient is solved using the criterion number correlation formula to obtain the convective heat flux density distribution. The criterion number correlation formula is based on the empirical formula under different flow conditions, and the convective heat transfer coefficient is expressed as a function of the dimensionless parameters of the Reynolds number and the Prandtl number.

[0098] A heat transfer model describing the sensible heat release during pulverized coal combustion is established. The sensible heat source term distribution is obtained based on the fuel consumption rate calculated by the combustion model and the low calorific value of the fuel.

[0099] The three heat transfer mechanisms of radiation, convection and sensible heat release are comprehensively considered to construct the total energy conservation equation of the combustion process in the furnace; the variables of the velocity field, temperature field and component concentration field of the gas and solid phases are introduced to combine the fluid flow and chemical reaction kinetics equations to form a closed mathematical model;

[0100] The established three-dimensional heat transfer mathematical model is numerically solved, and the control equation is discretized using the finite volume method to obtain the spatial distribution of the parameters of the temperature field and heat flux field in the furnace.

[0101] For example, first, according to the geometric structure and operating parameters of the coal-fired boiler furnace, the calculation grid is divided and the boundary conditions are set. Taking the boiler of a 600MW unit as an example, the furnace height is 60m and the cross-section is 20m×20m. Structured grids are used for division, and the number of grids is about 1 million. Parameters such as the flow rate and temperature of pulverized coal and air are set at the inlet boundary, such as the primary air temperature of 300℃, the secondary air temperature of 350℃, and the pulverized coal feeding rate of 50kg / s. The pressure outlet condition is set at the outlet boundary, and the heat transfer and viscosity effects are considered at the wall boundary, such as the water-cooled wall temperature of 380℃.

[0102] A heat transfer model is established to describe the radiation heat transfer during coal powder combustion. The P-1 model is used to solve the radiation transfer equation and obtain the radiation heat flux density distribution. The P-1 model expands the radiation intensity into a spherical harmonic function series and truncates it to the first-order term to obtain the diffusion equation for the incident radiation. This model has high computational efficiency and is suitable for media with large optical thickness, such as flue gas produced by coal powder combustion. The absorption coefficient and scattering coefficient of gases and particles need to be considered in the model. These parameters can be obtained through experimental determination or empirical formulas. For example, for the flue gas produced by the combustion of Zhundong coal, the weighted sum model can be used to calculate the absorption coefficient, in which CO2 and H2O contribute the most, with typical values ​​in the range of 0.5-1.0m^-1.

[0103] A heat transfer model is established to describe the convective heat transfer during coal powder combustion. Combined with the velocity field and temperature field obtained from the gas-solid two-phase flow calculation, the convective heat transfer coefficient is solved using the criterion number correlation formula to obtain the convective heat flux density distribution. The criterion number correlation formula is based on the empirical formula under different flow conditions, and the convective heat transfer coefficient is expressed as a function of the dimensionless parameters of the Reynolds number and the Prandtl number. For the turbulent heat transfer in the furnace, the modified Dittus-Boelter equation can be used to calculate the Nusselt number, and then the convective heat transfer coefficient is obtained. Under typical operating conditions, the convective heat transfer coefficient in the furnace is about 30-50W / (m^2·K).

[0104] A heat transfer model is established to describe the sensible heat release during coal powder combustion. The fuel consumption rate calculated by the combustion model is combined with the low calorific value of the fuel to obtain the distribution of sensible heat source terms. The combustion model can adopt an eddy dissipation model or a finite rate / eddy dissipation hybrid model, taking into account the devolatilization of coal powder, volatile combustion and coke combustion processes. Taking Zhundong coal as an example, its low calorific value is 27.8MJ / kg, the combustion rate can be calculated by the Arrhenius expression, the activation energy is 120kJ / mol, and the pre-exponential factor can be obtained by experimental fitting, with a typical value of 10^5s^-1.

[0105] The three heat transfer mechanisms of radiation, convection and sensible heat release are comprehensively considered to construct the total energy conservation equation of the combustion process in the furnace. The variables of the velocity field, temperature field and component concentration field of the gas-solid two-phase are introduced, and the fluid flow and chemical reaction kinetic equations are combined to form a closed mathematical model. The fluid flow is described by the Reynolds averaged NS equation, and the k-ε two-equation model is used as the turbulence model. The chemical reaction kinetic equation considers the generation and consumption of major components such as CO, CO2, H2O, O2, N2, etc. For Zhundong coal, the following main reactions can be considered: volatile splitting, coke combustion, CO oxidation, etc. The reaction rate can be described by the Arrhenius expression, and the activation energy and pre-exponential factor of each reaction need to be determined experimentally.

[0106] The established three-dimensional heat transfer mathematical model is numerically solved, and the control equation is discretized using the finite volume method to obtain the spatial distribution of the parameters of the temperature field and heat flux density field in the furnace. The SIMPLE algorithm is used to process the pressure-velocity coupling during the solution process, the convection term is discretized using the second-order upwind format, and the diffusion term is discretized using the central difference format. Iterate the calculation until the residual is less than 10^-4. The calculation time step can be set to 0.001s, and the total calculation time can reach a steady state as needed, usually 10-20s of physical time.

[0107] Through the above model, the detailed combustion characteristics of Zhundong coal in the boiler furnace can be obtained. For example, under rated load, the flue gas temperature at the furnace outlet is about 1200℃, and the maximum furnace temperature can reach about 1800℃, which is located near the burner. Radiation heat transfer accounts for more than 70% of the total heat transfer and is the main heat transfer method. The CO concentration in the furnace is highest near the burner, reaching 10000ppm, and then drops rapidly to below 100ppm at the furnace outlet. NOx generation is mainly concentrated in the high temperature area, with an outlet concentration of about 400mg / Nm^3.

[0108] This combustion mathematical model provides a powerful tool for optimizing the combustion process of Zhundong coal. The model can predict the combustion effect under different operating parameters, such as the impact of adjusting the primary air ratio, secondary air speed, etc. on the combustion temperature field and pollutant generation. For example, increasing the secondary air speed can improve the mixing effect in the burner area, but may lead to increased NOx generation. The model results can also be used to guide boiler design, such as optimizing the burner layout and determining the heating surface layout.

[0109] In an optional embodiment,

[0110] The combustion mathematical model is used to obtain the optimal combustion parameters of the Zhundong coal under different combustion conditions. Based on the optimal combustion parameters, a three-dimensional numerical solution of the combustion and coking process of the Zhundong coal in the furnace is obtained through numerical simulation. The combustion parameters are optimized to obtain the best matching solution for anti-coking combustion, including:

[0111] Using the three-dimensional mathematical model of Zhundong coal combustion, the performance parameters of Zhundong coal combustion under different working conditions are obtained through numerical simulation, and the different working conditions include baseline working conditions, variable load working conditions, variable coal type working conditions, variable coal grinding fineness working conditions and variable burner structure working conditions; based on the numerical simulation results, the influence of various operating parameters on the combustion performance of Zhundong coal is evaluated, the main control factors affecting the combustion of Zhundong coal are screened out, and the best matching parameters for the combustion of Zhundong coal are obtained, and the best matching parameters include the primary and secondary air nozzle deflection angles of the burner, the coal mill fineness, and the cyclone structure parameters;

[0112] Based on the optimal matching parameters of the Zhundong coal combustion, a viscosity mathematical model describing the softening and melting characteristics of Zhundong coal ash is established, and the viscosity mathematical model is embedded in the three-dimensional mathematical model of Zhundong coal combustion. At the same time, considering the force analysis of slag particles in high-temperature flue gas, a three-dimensional coking mathematical model describing the softening, melting, flow and condensation process of slag in the furnace is established;

[0113] The Lagrangian method is used to track the movement trajectory of slag particles and obtain the change history of the temperature, viscosity and velocity parameters of the slag particles. When the slag particles hit the furnace wall or the heating surface, the collision Weber number criterion is used to determine whether the slag particles are coked. The three-dimensional numerical simulation of the movement and coking process of a large number of slag particles in the furnace is carried out to obtain the three-dimensional numerical simulation results of the coking process of Zhundong coal.

[0114] Based on the three-dimensional numerical simulation results of the Zhundong coal coking process, the following anti-coking combustion measures are optimized and matched from the aspects of burner design optimization, coal powder fineness adjustment, and coal blending ratio optimization:

[0115] By rationally arranging the injection angles and injection velocities of each air outlet of the burner, the position of the main combustion zone and the flame shape in the furnace are adjusted; the structural parameters of the secondary air baffle and swirler of the burner are optimized to promote the full mixing of coal powder and air; through the comprehensive use of the above anti-coking combustion measures, on the basis of the best matching parameters of Zhundong coal combustion, the best combustion scheme that takes into account both efficient combustion and coking inhibition is obtained.

[0116] For example, under the baseline condition, the typical operating parameters of a 600MW unit are simulated, such as boiler load 100%, coal fineness R90=15%, primary air temperature 300℃, secondary air temperature 350℃, etc. The variable load condition considers four load levels of 30%, 50%, 75% and 100%, which are mainly achieved by adjusting the coal powder feed rate and air volume. The variable coal type condition considers the different proportions of Zhundong coal and Shenhua coal, from 100% Zhundong coal to 100% Shenhua coal, with 5 proportion points set at intervals of 20%. The variable coal fineness condition considers four cases of R90 of 10%, 15%, 20% and 25%. The variable burner structure condition mainly adjusts the primary and secondary air nozzle deflection angles of the burner, as well as the swirler blade angle.

[0117] Based on the numerical simulation results, the influence of various operating parameters on the combustion performance of Zhundong coal was evaluated. The main indicators included combustion efficiency, NOx emissions, CO emissions, flue gas outlet temperature, etc. Through comparative analysis, the main control factors affecting the combustion of Zhundong coal were screened out. The results show that the primary and secondary air nozzle deflection angles of the burner, the fineness of the coal mill, and the structural parameters of the cyclone have a significant impact on the combustion performance.

[0118] For example, when adjusting the primary air nozzle angle of the burner, it was found that increasing the angle from 15° to 25° can increase the combustion efficiency by about 0.5%, while reducing NOx emissions by about 10%. This is because increasing the angle improves the mixing of coal powder and air, while extending the flame length and reducing the local high temperature area. The secondary air nozzle angle has a significant effect on the swirl intensity. Increasing the angle from 30° to 40° can enhance the swirl and increase the residence time of coal powder in the furnace, but it will also increase the generation of NOx.

[0119] The fineness of the coal mill has an important impact on both combustion efficiency and pollutant emissions. Reducing R90 from 20% to 15% can reduce incomplete combustion losses by about 0.3%, but at the same time will slightly increase NOx emissions. This is because finer coal powder has a larger specific surface area, which burns more completely, but is also more likely to form local high-temperature areas.

[0120] The structural parameters of the swirler mainly affect the swirl intensity at the burner outlet. Increasing the swirler blade angle can enhance the swirl and improve the mixing of coal powder and air, but excessive swirl may also lead to an excessively large recirculation zone, affecting flame stability. Through simulation, it was found that increasing the swirler blade angle from 45° to 55° can increase the combustion efficiency by about 0.3%, but further increasing it to 65° has no obvious effect.

[0121] Based on the above analysis, the best matching parameters for Zhundong coal combustion are obtained: primary air nozzle angle 22°, secondary air nozzle angle 35°, coal mill fineness R90 = 15%, cyclone blade angle 55°. This set of parameters can ensure high combustion efficiency while also better controlling NOx emissions.

[0122] Next, based on the optimal matching parameters of Zhundong coal combustion, a viscosity mathematical model describing the softening and melting characteristics of Zhundong coal ash was established. The model takes into account the influence of factors such as temperature and ash composition on the viscosity of ash. The main components of Zhundong coal ash include SiO2 (about 50%), Al2O3 (about 30%), Fe2O3 (about 5%), CaO (about 5%), etc. The model adopts the modified Urbain model, and by introducing the concepts of network formers and network modifiers, it more accurately describes the change of ash viscosity with temperature. For example, at 1400°C, the viscosity of Zhundong coal ash is about 10Pa·s, and it increases to about 100Pa·s at 1200°C.

[0123] The viscosity mathematical model is embedded in the three-dimensional mathematical model of Zhundong coal combustion, and the force analysis of slag particles in high-temperature flue gas is considered at the same time, and a three-dimensional coking mathematical model describing the softening, melting, flow and condensation process of slag in the furnace is established. The model takes into account the forces such as gravity, buoyancy, resistance, and the collision and adhesion process between particles and the wall.

[0124] The Lagrangian method was used to track the motion trajectory of the slag particles and obtain the change history of the temperature, viscosity and velocity parameters of the slag particles. A large number of representative particles were tracked in the simulation, with particle sizes ranging from 1μm to 100μm. The results showed that most of the slag particles experienced softening and melting processes in the temperature range of 1300-1600℃, and the viscosity dropped rapidly from 10^5Pa·s to below 10Pa·s.

[0125] When slag particles hit the furnace wall or the heated surface, whether the slag particles coke is determined based on the collision Weber number criterion. The Weber number is a dimensionless parameter that characterizes the droplet impact behavior, which takes into account the relative magnitude of the particle's kinetic energy, surface tension, and viscosity. When the Weber number is less than the critical value (usually 12-16), the particles are more likely to coke. Simulation results show that particles with a diameter greater than 50 μm are more likely to form an initial deposition layer.

[0126] The movement and coking process of a large number of slag particles in the furnace were simulated in three dimensions, and the results of the coking process of Zhundong coal were obtained. The results show that coking mainly occurs in the lower and middle areas of the furnace, especially near the burner and on the water-cooled wall. In these areas, the ash deposition thickness can reach 5-10mm, while in the upper part of the furnace, the deposition thickness is usually less than 1mm.

[0127] Based on the three-dimensional numerical simulation results of the coking process of Zhundong coal, the anti-coking combustion measures are optimized and matched from the aspects of burner design optimization, coal powder fineness adjustment, and coal blending ratio optimization.

[0128] In terms of burner design optimization, the main combustion zone position and flame shape in the furnace are adjusted by rationally arranging the injection angle and injection speed of each burner tuyere. The optimized design adjusts the primary air nozzle angle to 20°, the secondary air outer layer nozzle angle to 32°, and the inner layer to 38°. This design can make the flame shape more compact, reduce direct contact with the water-cooled wall, and thus reduce the risk of coking. At the same time, increasing the secondary air speed from 50m / s to 60m / s can enhance the entrainment effect on coal powder and improve combustion.

[0129] Optimize the burner secondary air baffle and cyclone structural parameters to promote full mixing of coal powder and air. Adjust the cyclone blade angle to 58° and increase the number of blades from 8 to 10 to produce stronger swirl intensity, improve the mixing of coal powder and air, and reduce unburned particles. At the same time, add guide grooves on the secondary air baffle to make the air flow more uniform and reduce the formation of local high temperature areas.

[0130] In terms of coal powder fineness adjustment, considering the high ash content of Zhundong coal, the pulverizer fineness R90 was further reduced from 15% to 13%. Finer coal powder can improve combustion efficiency, reduce unburned particles, and thus reduce the risk of coking. At the same time, in order to control NOx emissions, air staged combustion technology is used to divide the secondary air into two layers, the inner layer air volume accounts for 70% of the total air volume, and the outer layer accounts for 30%.

[0131] In terms of optimizing the blending ratio of coal, considering the characteristics of Zhundong coal, it is recommended to blend it with Shenhua coal. Through simulation, it is found that when the blending ratio of Zhundong coal to Shenhua coal is 6:4, the coking tendency can be significantly reduced while maintaining a high combustion efficiency. This is because the ash melting point of Shenhua coal is higher, which can increase the ash melting point of the mixed coal and reduce the generation of molten ash.

[0132] By comprehensively applying the above anti-coking combustion measures, based on the best matching parameters of Zhundong coal combustion, the best combustion scheme that takes into account both efficient combustion and coking inhibition is obtained. The main parameters of this scheme include: Zhundong coal and Shenhua coal blending ratio of 6:4, coal mill fineness R90 = 13%, primary air nozzle deflection angle of 20°, secondary air outer layer nozzle deflection angle of 32°, inner layer 38°, cyclone blade angle of 58°, secondary air speed of 60m / s.

[0133] After adopting this optimization scheme, simulation results show that the combustion efficiency can be increased to 98.5%, which is 0.8 percentage points higher than before optimization. NOx emissions are reduced to 350mg / Nm 3, which is 15% lower than before optimization. The coking tendency has also been significantly improved, and the thickness of ash deposition on the water-cooled wall has been reduced from the original 5-10mm to 2-5mm. These improvements not only improve the operating efficiency of the boiler, but also extend the cleaning cycle and reduce maintenance costs.

[0134] In an optional embodiment,

[0135] According to the optimal matching scheme, the operating parameters of the combustion system and the pulverizing system are automatically adjusted, including adjusting the opening of the electric regulating valves on the primary and secondary air ducts, adjusting the speed of the blower through the frequency converter, and adjusting the coal feed rate and primary air temperature of the pulverizing system, so as to achieve precise control of the Zhundong coal combustion process and anti-coking optimization, including:

[0136] According to the best matching scheme of Zhundong coal combustion optimization and anti-coking, a state space mathematical model describing the dynamic characteristics of the boiler combustion system and the pulverizing system is established. The state variables of the mathematical model include boiler combustion efficiency, NOx emission concentration and furnace outlet flue gas temperature. The control variables include the opening of the electric regulating valves of the primary and secondary air ducts, the frequency setting value of the blower inverter, the coal feed rate of the pulverizing system and the primary air temperature setting value. The disturbance variables include coal quality fluctuations and load changes.

[0137] Based on the state space mathematical model of the boiler combustion system and the pulverizing system, a multivariable model predictive control (MMPC) optimization model is established, with combustion efficiency, NOx emission and coking amount as control targets, the opening of the electric regulating valves of the primary and secondary air ducts, the frequency setting value of the blower inverter, the coal feeding amount of the pulverizing system and the primary air temperature setting value as optimization control variables, and the MMPC optimization control objective function and constraint condition equations are established;

[0138] The MMPC optimization model is transformed into a quadratic programming (QP) problem, and the sequential quadratic programming (SQP) algorithm is used to solve it, and the optimal adjustment amount of each control variable in several future sampling moments is obtained; the optimization results are used to guide the setting of the parameters of the combustion control system in real time, and the opening of the electric regulating valves on the primary and secondary air ducts are adjusted through the corresponding actuators, the speed of the blower is adjusted through the frequency converter, and the coal feed rate and primary air temperature of the pulverizing system are adjusted to achieve precise control of the combustion process.

[0139] For example, according to the best matching scheme of Zhundong coal combustion optimization and anti-coking, establishing a state space mathematical model that describes the dynamic characteristics of the boiler combustion system and the pulverizing system is a key step to achieve precise control. The state variables of the model include boiler combustion efficiency, NOx emission concentration and furnace outlet flue gas temperature, which directly reflect the effect of the combustion process and the environmental impact. The control variables include the opening of the electric regulating valves of the primary and secondary air ducts, the frequency setting value of the blower inverter, the coal feed rate of the pulverizing system and the primary air temperature setting value, which can be directly adjusted to affect the combustion process. Disturbance variables include coal quality fluctuations and load changes, which will have an uncertain impact on the combustion process.

[0140] When establishing a state space model, we first need to determine the relationship between the variables. For example, the increase in the opening of the primary air duct regulating valve will directly affect the primary air volume, which in turn affects the combustion efficiency and NOx emissions. Specifically, when the opening of the primary air duct regulating valve increases from 60% to 70%, the combustion efficiency may increase by 0.5 percentage points, but the NOx emissions may increase by 20mg / Nm 3 Similarly, the adjustment of the blower inverter frequency will affect the total air volume, thereby affecting the furnace temperature distribution and the outlet flue gas temperature. For example, increasing the blower frequency from 45Hz to 50Hz may reduce the furnace outlet flue gas temperature by 10℃.

[0141] Changes in the coal feed rate of the pulverizing system directly affect the combustion intensity and efficiency. For example, increasing the coal feed rate from 100t / h to 110t / h may increase the combustion efficiency by 0.3 percentage points, but at the same time NOx emissions may increase by 15mg / Nm 3 The adjustment of primary air temperature mainly affects the drying and conveying effect of pulverized coal, and thus affects the combustion efficiency. Increasing the primary air temperature from 300°C to 320°C may increase the combustion efficiency by 0.2 percentage points.

[0142] When considering disturbance variables, coal quality fluctuations are mainly manifested in changes in calorific value and ash content. For example, when the received base calorific value of coal decreases from 4200 kcal / kg to 4000 kcal / kg, it may lead to a decrease in combustion efficiency by 0.5 percentage points and a decrease in NOx emissions by 10 mg / Nm 3 The load change directly affects the ratio of coal feed and air volume. When the unit load decreases from 100% to 80%, the coal feed and air volume need to be adjusted accordingly to maintain a suitable excess air coefficient.

[0143] Based on the above state space mathematical model, the next step is to establish a multivariable model predictive control (MMPC) optimization model. This model takes combustion efficiency, NOx emissions and coking amount as control targets, and takes the opening of the electric regulating valves of the primary and secondary air ducts, the frequency setting value of the blower inverter, the coal feeding amount of the pulverizing system and the primary air temperature setting value as optimization control variables.

[0144] The design of the MMPC optimization control objective function requires comprehensive consideration of multiple objectives. For example, the objective function can be designed as the weighted sum of the negative value of combustion efficiency, NOx emission concentration, and predicted coking amount. Specifically, a weight of 50% can be given to combustion efficiency, a weight of 30% to NOx emission, and a weight of 20% to coking amount. Such a weight distribution reflects the importance of combustion efficiency while also taking into account environmental protection requirements and equipment safety.

[0145] The constraint equations need to consider the physical limitations and operational safety range of each control variable. For example, the opening range of the electric regulating valves of the primary and secondary air ducts is usually 0-100%, but considering the operational stability, the actual range can be limited to 20-90%. The frequency setting value of the blower inverter may range from 30-60Hz, but the thermal protection requirements of the motor need to be considered. The range of coal feed rate of the pulverizing system depends on the capacity of the coal mill, for example, it may be 50-150t / h. The range of primary air temperature setting value is usually 250-350℃, but the characteristics of the coal type and safety factors need to be considered.

[0146] Converting the MMPC optimization model into a quadratic programming (QP) problem is a key step in solving it. This process involves linearizing the nonlinear state-space model around the current operating point and expressing the objective function as a quadratic function of the control variables. The constraints are expressed as linear inequalities or equations of the control variables.

[0147] The sequential quadratic programming (SQP) algorithm is used for solving, which can effectively handle nonlinear constraints and objective functions. The SQP algorithm solves a QP subproblem in each step in an iterative manner, gradually approaching the optimal solution. For example, assuming that in the initial state, the opening of the primary air duct regulating valve is 65%, the opening of the secondary air duct regulating valve is 70%, the blower frequency is 48Hz, the coal supply is 100t / h, and the primary air temperature is 300℃. Through the iterative solution of the SQP algorithm, the optimal control variable adjustment amount that may be obtained is: primary air duct regulating valve opening +2%, secondary air duct regulating valve opening -1%, blower frequency -0.5Hz, coal supply +2t / h, primary air temperature +5℃.

[0148] These optimization results are used to guide the setting of combustion control system parameters in real time. The optimized setting values ​​are transmitted to the corresponding actuators through the distributed control system (DCS). For example, the electric regulating valves on the primary and secondary air ducts will adjust the opening according to the optimization results, the frequency converter of the blower will adjust the output frequency, the pulverizing system will adjust the coal feed rate, and the primary air heater will adjust the outlet temperature.

[0149] Specifically, the electric control valve is usually regulated by the PID control algorithm, which is adjusted according to the deviation between the valve position feedback signal and the set value. For example, if the current opening of the primary air duct control valve is 65%, and the optimization result requires an increase of 2%, the control system will gradually adjust the valve opening to 67% while monitoring the actual air volume changes.

[0150] The blower speed is regulated by the frequency converter. For example, if the current frequency is 48Hz and the optimization result requires a 0.5Hz reduction, the frequency converter will smoothly adjust the output frequency to 47.5Hz within a few seconds. During this process, the control system will monitor the current and power of the blower to ensure that it operates within a safe range.

[0151] The adjustment of the coal feeding amount of the pulverizing system is usually achieved by adjusting the speed of the coal feeder. For example, if the current coal feeding amount is 100t / h, and the optimization result requires an increase of 2t / h, the control system will increase the speed of the coal feeder accordingly. At the same time, the system will monitor the current and vibration of the coal mill to ensure that there is no overload.

[0152] The primary air temperature is regulated by controlling the heating steam valve or electric heater. For example, if the current temperature is 300°C and needs to be raised to 305°C, the control system will increase the heating amount and monitor the temperature change rate to avoid excessive temperature fluctuations.

[0153] In this way, each key parameter of the combustion process can be precisely controlled, thereby achieving efficient combustion of Zhundong coal and effective coking prevention. For example, after implementing this control strategy, the combustion efficiency may be increased from 97.5% to 98.2%, and NOx emissions from 380mg / Nm 3 Reduced to 350mg / Nm 3 , the predicted coking amount may be reduced by 20%. This not only improves the economy of the boiler, but also improves the environmental performance and extends the operation cycle of the equipment.

[0154] In an optional embodiment,

[0155] The method further comprises:

[0156] During the combustion process, the flue gas temperature at different positions in the furnace is detected in real time using thermocouples, the furnace wall temperature distribution is scanned in real time using infrared thermometers, and the flue gas components are detected online using flue gas analyzers.

[0157] The above-mentioned test results are compared with the standard values ​​under the optimal combustion state in real time. When the temperature field deviation or the key flue gas component deviation exceeds the preset threshold, the adaptive optimization control strategy of the combustion parameters is initiated. The dynamic adjustment of the combustion parameters is achieved through the self-learning algorithm and the expert experience knowledge base, and the combustion state is maintained within the optimal operating range for anti-coking, thus realizing the intelligent optimization control of the Zhundong coal combustion system.

[0158] For example, in the intelligent optimization control of the Zhundong coal combustion system, real-time monitoring and analysis of the combustion state inside the furnace is a key link. This process mainly relies on three types of detection equipment: thermocouples, infrared thermometers and flue gas analyzers.

[0159] Thermocouples are commonly used sensors for measuring temperature in high-temperature environments. By installing thermocouples at different locations in the furnace, the temperature distribution of flue gas can be obtained in real time. Usually, multiple thermocouples are installed in the lower, middle and upper parts of the furnace to form a three-dimensional temperature monitoring network. For example, 8 thermocouples can be installed at the bottom of the furnace, 12 in the middle, and 16 in the upper part, for a total of 36 temperature measurement points. These thermocouples need to be made of high-temperature resistant and corrosion-resistant materials, such as platinum-rhodium thermocouples, which can work stably in high-temperature environments above 1600°C. The signal of the thermocouple is transmitted to the data acquisition system through a compensation wire, and the sampling frequency can be set to 1 time per second to ensure that sufficiently detailed temperature change data is obtained.

[0160] Infrared thermometers are used to scan the temperature distribution of the furnace wall in real time. This non-contact temperature measurement method can provide a wider range of temperature distribution information. Infrared thermometers are usually installed in the observation hole of the furnace or a specially designed temperature measurement window, and the entire furnace wall is scanned by a rotating or swinging mechanism. Modern infrared thermometers can achieve fast scanning, collecting thousands of temperature data points per second to form a thermal map of the furnace wall temperature. For example, a certain model of infrared thermometer can scan the entire furnace in 5 seconds, with a resolution of 320×240 pixels, a temperature measurement range of 200-1800℃, and an accuracy of ±2℃ or 1% of the reading.

[0161] Flue gas analyzers are used to detect flue gas components online. Modern flue gas analyzers usually use technologies such as non-dispersive infrared (NDIR), chemiluminescence (CLD) and ultraviolet absorption spectroscopy, and can simultaneously measure multiple gas components, including O2, CO, CO2, NOx, SO2, etc. Flue gas analyzers are usually installed at the flue of the boiler outlet, and a portion of the flue gas sample is extracted for analysis. In order to ensure the accuracy of the measurement, the flue gas needs to be pre-treated by dust removal, condensation, etc. before entering the analyzer. The sampling frequency of the flue gas analyzer is usually set to once a minute to capture changes in the combustion state.

[0162] Real-time comparison of the above test results with the standard values ​​under the optimal combustion state is a key step in achieving intelligent control. The standard value of the optimal combustion state is usually determined by a large amount of operating data statistics and expert experience. For example, for a 600MW unit burning Zhundong coal, the optimal value of the average furnace outlet temperature may be 1250±30℃, and the optimal range of NOx emission concentration may be 350-400mg / Nm 3 , CO concentration should be maintained at 30mg / Nm 3 the following.

[0163] When the temperature field deviation or key flue gas component deviation exceeds the preset threshold, the system will start the adaptive optimization control strategy of the combustion parameters. The preset threshold here needs to be determined according to the characteristics and operation requirements of the boiler. For example, the furnace temperature deviation threshold can be set to ±50℃, and the NOx emission deviation threshold can be set to ±30mg / Nm 3 The CO concentration deviation threshold is set to 10 mg / Nm 3 .

[0164] The core of the adaptive optimization control strategy is to achieve dynamic adjustment of combustion parameters through self-learning algorithms and expert experience knowledge base. Self-learning algorithms usually use artificial intelligence technology, such as neural networks or reinforcement learning. Taking neural networks as an example, a multi-layer perceptron network can be constructed. The input layer includes the current temperature field data, flue gas composition data, and combustion parameters (such as coal feed, primary and secondary air ratio, etc.), and the output layer is the optimized combustion parameter recommendation value. This neural network is trained with a large amount of historical operation data and can gradually learn the optimal control strategy under different working conditions.

[0165] The expert experience knowledge base is a supplement and constraint to the self-learning algorithm. It contains a large number of expert experience rules, such as: "When the temperature in the lower part of the furnace is too high and the NOx concentration exceeds the standard, the primary air volume should be appropriately reduced and the secondary air volume should be increased", "When the CO concentration increases, the excess air coefficient should be appropriately increased", etc. These rules can be expressed in the form of fuzzy logic and combined with the output of the self-learning algorithm to form the final control strategy.

[0166] The dynamic adjustment of combustion parameters mainly involves the following aspects:

[0167] Coal feed rate adjustment: This is achieved by controlling the speed of the coal feeder. For example, when the furnace temperature is low, the coal feed rate may need to be increased from 100t / h to 105t / h. Primary air volume adjustment: This is achieved by controlling the inverter of the primary fan and the valve of the primary air duct. For example, when it is found that the pulverized coal is not fully burned at the burner outlet, the primary air volume may need to be reduced from 80kg / s to 75kg / s. Secondary air volume adjustment: This is achieved by controlling the inverter of the secondary fan and the valve of the secondary air duct. For example, when NOx emissions are high, the secondary air volume may need to be increased from 170kg / s to 180kg / s, and the damper opening may be adjusted to optimize the distribution of the secondary air.

[0168] Burner swing angle adjustment: This is achieved by controlling the swing mechanism of the burner. For example, when it is found that the temperature in a certain area of ​​the furnace is too high, it may be necessary to adjust the burner swing angle of the corresponding area from 15° to 20° to improve the distribution of the combustion airflow.

[0169] Oxygen adjustment: This is achieved by controlling the ratio of total air volume to coal feed volume. For example, when CO concentration is found to be elevated, the excess air coefficient may need to be increased from 1.15 to 1.18.

[0170] The adjustment of these parameters is a dynamic and continuous process. The control system will continuously fine-tune these parameters based on real-time monitoring data to keep the combustion state within the optimal range of anti-coking conditions. For example, during a certain adjustment process, the system may first increase the coal feed by 2%, observe for 5 minutes and find that the NOx concentration has increased slightly, then increase the secondary air volume by 3%, observe for another 5 minutes and find that the NOx concentration has fallen back to the ideal range, and at the same time, the furnace temperature distribution is more uniform.

[0171] Realizing intelligent optimization control of Zhundong coal combustion system requires not only advanced algorithms and control strategies, but also reliable hardware support. The control system usually adopts a distributed control system (DCS) architecture, including field layer, control layer and management layer. The field layer includes various sensors and actuators, the control layer is responsible for data processing and execution of control algorithms, and the management layer provides human-machine interface and data storage functions. The system's response time is usually in seconds, which can respond to changes in combustion status in a timely manner.

[0172] Through this intelligent optimization control system, the combustion efficiency of Zhundong coal can be significantly improved, while effectively preventing coking problems. For example, in the actual application of a 600MW unit, the system increased the boiler efficiency from 93.5% to 94.8%, and NOx emissions from 420mg / Nm 3 Reduced to 380mg / Nm 3, the coking cycle was extended from the original 3 months to 6 months. This not only brought considerable economic benefits, but also greatly improved environmental performance and equipment reliability.

[0173] Figure 2 FIG. 1 is a schematic diagram of a combustion control system for preventing coking of Zhundong coal according to an embodiment of the present invention. Figure 2 As shown, the system comprises:

[0174] The first unit is used to crush and reduce the pre-acquired Zhundong coal sample to obtain a coal sample for analysis; perform industrial analysis, elemental analysis and ash composition analysis on the coal sample for analysis to determine the combustion characteristic parameters of the Zhundong coal, wherein the combustion characteristic parameters include the theoretical combustion temperature of the Zhundong coal under given excess air coefficient, coal inlet temperature and primary air temperature, the combustion activation energy of the Zhundong coal under different particle sizes and heating rates, and the coking index of the Zhundong coal;

[0175] The second unit is used to establish a combustion mathematical model of the combustion process of the Zhundong coal based on the combustion characteristic parameters of the Zhundong coal, wherein the combustion mathematical model includes a three-dimensional heat transfer equation of the combustion process of the Zhundong coal in the furnace, a chemical reaction kinetic equation of the combustion product, and a fluid dynamics equation; using the combustion mathematical model, the optimal combustion parameters of the Zhundong coal under different combustion conditions are obtained, and based on the optimal combustion parameters, a three-dimensional numerical solution of the combustion and coking process of the Zhundong coal in the furnace is obtained through numerical simulation, and each combustion parameter is optimized to obtain the best matching scheme for anti-coking combustion; the optimal combustion parameters include at least one of primary air temperature, secondary air temperature, primary air speed, secondary air speed, coal powder particle size, excess air coefficient, and burnout air speed;

[0176] The third unit is used to automatically adjust the operating parameters of the combustion system and the pulverizing system according to the optimal matching scheme, including adjusting the opening of the electric regulating valves on the primary air duct and the secondary air duct, adjusting the speed of the blower through the frequency converter, and adjusting the coal feed rate and primary air temperature of the pulverizing system, so as to achieve precise control of the Zhundong coal combustion process and anti-coking optimization.

[0177] According to a third aspect of the embodiments of the present invention,

[0178] An electronic device is provided, comprising:

[0179] processor;

[0180] a memory for storing processor-executable instructions;

[0181] The processor is configured to call the instructions stored in the memory to execute the aforementioned method.

[0182] A fourth aspect of the embodiments of the present invention is:

[0183] A computer-readable storage medium is provided, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the aforementioned method is implemented.

[0184] The present invention may be a method, an apparatus, a system and / or a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for executing various aspects of the present invention.

[0185] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein with equivalents. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A combustion control method suitable for preventing coking of Zhundong coal, characterized in that: include: The pre-obtained Zhundong coal sample is crushed and reduced to obtain a coal sample for analysis; the coal sample for analysis is subjected to industrial analysis, elemental analysis and ash composition analysis to determine the combustion characteristic parameters of the Zhundong coal, wherein the combustion characteristic parameters include the theoretical combustion temperature of the Zhundong coal under given excess air coefficient, coal inlet temperature and primary air temperature, the combustion activation energy of the Zhundong coal under different particle sizes and heating rates, and the coking index of the Zhundong coal; Based on the combustion characteristic parameters of Zhundong coal, a combustion mathematical model of the combustion process of the Zhundong coal is established, and the combustion mathematical model includes a three-dimensional heat transfer equation of the combustion process of the Zhundong coal in the furnace, a chemical reaction kinetic equation of the combustion product, and a fluid dynamics equation; using the combustion mathematical model, the optimal combustion parameters of the Zhundong coal under different combustion conditions are obtained, and based on the optimal combustion parameters, a three-dimensional numerical solution of the combustion and coking process of the Zhundong coal in the furnace is obtained through numerical simulation, and each combustion parameter is optimized to obtain the best matching scheme for anti-coking combustion; the optimal combustion parameters include at least one of primary air temperature, secondary air temperature, primary air speed, secondary air speed, coal powder particle size, excess air coefficient, and burnout air speed; According to the optimal matching scheme, the operating parameters of the combustion system and the pulverizing system are automatically adjusted, including adjusting the opening of the electric regulating valves on the primary and secondary air ducts, adjusting the speed of the blower through the frequency converter, and adjusting the coal feed rate and primary air temperature of the pulverizing system, so as to achieve precise control of the Zhundong coal combustion process and anti-coking optimization.

2. The method according to claim 1, characterized in that The pre-obtained Zhundong coal sample is crushed and reduced to obtain a coal sample for analysis; the coal sample for analysis is subjected to industrial analysis, elemental analysis and ash composition analysis to determine the combustion characteristic parameters of the Zhundong coal, including: The pre-acquired Zhundong coal sample is crushed and reduced to obtain a coal sample for analysis; the coal sample for analysis is subjected to industrial analysis to determine the industrial air-dried basis components of the coal sample for analysis, wherein the industrial air-dried basis components include at least one of the mass fractions of water, ash, volatile matter and fixed carbon; the coal sample for analysis is subjected to elemental analysis to determine the elemental air-dried basis components of the coal sample for analysis, wherein the elemental air-dried basis components include the mass fractions of C, H, O, N and S elements; the coal sample for analysis is subjected to ash component analysis by X-ray fluorescence spectrometry to determine the mass fractions of major oxides in the ash of the coal sample for analysis; The dry ash-free basis high calorific value of the coal sample for analysis is measured by a calorimeter, and the air-dry basis low calorific value of the coal sample for analysis is calculated according to the industrial air-dry basis components and the elemental air-dry basis components; based on the air-dry basis low calorific value and in combination with the material energy conservation equation, the theoretical combustion temperature of the coal sample for analysis under the conditions of given excess air coefficient, coal inlet temperature and primary air temperature is determined; Conducting a thermogravimetric analysis experiment on the coal sample for analysis to obtain thermogravimetric curve data of the coal sample for analysis under different heating rate conditions; performing a linear fit on the reciprocal of the absolute temperature using the pyrolysis conversion rate based on the thermogravimetric curve data, and determining the combustion activation energy of the coal sample for analysis under different particle sizes and heating rate conditions through the slope of the fitting line; The coking index of the Zhundong coal is obtained by calculating the mass fraction of the main oxides in the ash of the analytical coal sample determined by the ash composition analysis using the coking tendency index calculation formula.

3. The method according to claim 1, characterized in that Based on the combustion characteristic parameters of the Zhundong coal, a combustion mathematical model of the Zhundong coal combustion process is established. The combustion mathematical model includes a three-dimensional heat transfer equation of the Zhundong coal combustion process in the furnace, a chemical reaction kinetic equation of the combustion product, and a fluid dynamics equation including: Divide the computational grid and set boundary conditions according to the geometric structure and operating parameters of the coal-fired boiler furnace; A heat transfer model describing the radiation heat transfer during coal pulverized combustion is established, and the P-1 model is used to solve the radiation transfer equation to obtain the radiation heat flux density distribution; the P-1 model expands the radiation intensity into a spherical harmonic function series, truncated to the first-order term, and obtains the diffusion equation for the incident radiation; A heat transfer model describing the convective heat transfer during coal powder combustion is established. Combined with the velocity field and temperature field obtained by gas-solid two-phase flow calculation, the convective heat transfer coefficient is solved using the criterion number correlation formula to obtain the convective heat flux density distribution. The criterion number correlation formula is based on the empirical formula under different flow conditions, and the convective heat transfer coefficient is expressed as a function of the dimensionless parameters of the Reynolds number and the Prandtl number. A heat transfer model describing the sensible heat release during pulverized coal combustion is established. The sensible heat source term distribution is obtained based on the fuel consumption rate calculated by the combustion model and the low calorific value of the fuel. The three heat transfer mechanisms of radiation, convection and sensible heat release are comprehensively considered to construct the total energy conservation equation of the combustion process in the furnace; the variables of the velocity field, temperature field and component concentration field of the gas and solid phases are introduced to combine the fluid flow and chemical reaction kinetics equations to form a closed mathematical model; The established three-dimensional heat transfer mathematical model is numerically solved, and the control equation is discretized using the finite volume method to obtain the spatial distribution of the parameters of the temperature field and heat flux field in the furnace.

4. The method according to claim 1, characterized in that: The combustion mathematical model is used to obtain the optimal combustion parameters of the Zhundong coal under different combustion conditions. Based on the optimal combustion parameters, a three-dimensional numerical solution of the combustion and coking process of the Zhundong coal in the furnace is obtained through numerical simulation. The combustion parameters are optimized to obtain the best matching solution for anti-coking combustion, including: Using the three-dimensional mathematical model of Zhundong coal combustion, the performance parameters of Zhundong coal combustion under different working conditions are obtained through numerical simulation, and the different working conditions include baseline working conditions, variable load working conditions, variable coal type working conditions, variable coal grinding fineness working conditions and variable burner structure working conditions; based on the numerical simulation results, the influence of various operating parameters on the combustion performance of Zhundong coal is evaluated, the main control factors affecting the combustion of Zhundong coal are screened out, and the best matching parameters for the combustion of Zhundong coal are obtained, and the best matching parameters include the primary and secondary air nozzle deflection angles of the burner, the coal mill fineness, and the cyclone structure parameters; Based on the optimal matching parameters of the Zhundong coal combustion, a viscosity mathematical model describing the softening and melting characteristics of Zhundong coal ash is established, and the viscosity mathematical model is embedded in the three-dimensional mathematical model of Zhundong coal combustion. At the same time, considering the force analysis of slag particles in high-temperature flue gas, a three-dimensional coking mathematical model describing the softening, melting, flow and condensation process of slag in the furnace is established; The Lagrangian method is used to track the movement trajectory of slag particles and obtain the change history of the temperature, viscosity and velocity parameters of the slag particles. When the slag particles hit the furnace wall or the heating surface, the collision Weber number criterion is used to determine whether the slag particles are coked. The three-dimensional numerical simulation of the movement and coking process of a large number of slag particles in the furnace is carried out to obtain the three-dimensional numerical simulation results of the coking process of Zhundong coal. Based on the three-dimensional numerical simulation results of the Zhundong coal coking process, the following anti-coking combustion measures are optimized and matched from the aspects of burner design optimization, coal powder fineness adjustment, and coal blending ratio optimization: By rationally arranging the injection angles and injection velocities of each air outlet of the burner, the position of the main combustion zone and the flame shape in the furnace are adjusted; the structural parameters of the secondary air baffle and swirler of the burner are optimized to promote the full mixing of coal powder and air; through the comprehensive use of the above anti-coking combustion measures, on the basis of the best matching parameters of Zhundong coal combustion, the best combustion scheme that takes into account both efficient combustion and coking inhibition is obtained.

5. The method according to claim 1, characterized in that According to the optimal matching scheme, the operating parameters of the combustion system and the pulverizing system are automatically adjusted, including adjusting the opening of the electric regulating valves on the primary and secondary air ducts, adjusting the speed of the blower through the frequency converter, and adjusting the coal feed rate and primary air temperature of the pulverizing system, so as to achieve precise control of the Zhundong coal combustion process and anti-coking optimization, including: According to the best matching scheme of Zhundong coal combustion optimization and anti-coking, a state space mathematical model describing the dynamic characteristics of the boiler combustion system and the pulverizing system is established. The state variables of the mathematical model include boiler combustion efficiency, NOx emission concentration and furnace outlet flue gas temperature. The control variables include the opening of the electric regulating valves of the primary and secondary air ducts, the frequency setting value of the blower inverter, the coal feed rate of the pulverizing system and the primary air temperature setting value. The disturbance variables include coal quality fluctuations and load changes. Based on the state space mathematical model of the boiler combustion system and the pulverizing system, a multivariable model predictive control (MMPC) optimization model is established, with combustion efficiency, NOx emission and coking amount as control targets, the opening of the electric regulating valves of the primary and secondary air ducts, the frequency setting value of the blower inverter, the coal feeding amount of the pulverizing system and the primary air temperature setting value as optimization control variables, and the MMPC optimization control objective function and constraint condition equations are established; The MMPC optimization model is transformed into a quadratic programming (QP) problem, and the sequential quadratic programming (SQP) algorithm is used to solve it, and the optimal adjustment amount of each control variable in several future sampling moments is obtained; the optimization results are used to guide the setting of the parameters of the combustion control system in real time, and the opening of the electric regulating valves on the primary and secondary air ducts are adjusted through the corresponding actuators, the speed of the blower is adjusted through the frequency converter, and the coal feed rate and primary air temperature of the pulverizing system are adjusted to achieve precise control of the combustion process.

6. The method according to claim 1, characterized in that The method further comprises: During the combustion process, the flue gas temperature at different positions in the furnace is detected in real time using thermocouples, the furnace wall temperature distribution is scanned in real time using infrared thermometers, and the flue gas components are detected online using flue gas analyzers. The above-mentioned test results are compared with the standard values ​​under the optimal combustion state in real time. When the temperature field deviation or the key flue gas component deviation exceeds the preset threshold, the adaptive optimization control strategy of the combustion parameters is initiated. The dynamic adjustment of the combustion parameters is achieved through the self-learning algorithm and the expert experience knowledge base, and the combustion state is maintained within the optimal operating range for anti-coking, thus realizing the intelligent optimization control of the Zhundong coal combustion system.

7. A combustion control system suitable for preventing coking of Zhundong coal, used to implement the method described in any one of claims 1 to 6, characterized in that: include: The first unit is used to crush and reduce the pre-acquired Zhundong coal sample to obtain a coal sample for analysis; perform industrial analysis, elemental analysis and ash composition analysis on the coal sample for analysis to determine the combustion characteristic parameters of the Zhundong coal, wherein the combustion characteristic parameters include the theoretical combustion temperature of the Zhundong coal under given excess air coefficient, coal inlet temperature and primary air temperature, the combustion activation energy of the Zhundong coal under different particle sizes and heating rates, and the coking index of the Zhundong coal; The second unit is used to establish a combustion mathematical model of the combustion process of the Zhundong coal based on the combustion characteristic parameters of the Zhundong coal, wherein the combustion mathematical model includes a three-dimensional heat transfer equation of the combustion process of the Zhundong coal in the furnace, a chemical reaction kinetic equation of the combustion product, and a fluid dynamics equation; using the combustion mathematical model, the optimal combustion parameters of the Zhundong coal under different combustion conditions are obtained, and based on the optimal combustion parameters, a three-dimensional numerical solution of the combustion and coking process of the Zhundong coal in the furnace is obtained through numerical simulation, and each combustion parameter is optimized to obtain the best matching scheme for anti-coking combustion; the optimal combustion parameters include at least one of primary air temperature, secondary air temperature, primary air speed, secondary air speed, coal powder particle size, excess air coefficient, and burnout air speed; The third unit is used to automatically adjust the operating parameters of the combustion system and the pulverizing system according to the optimal matching scheme, including adjusting the opening of the electric regulating valves on the primary air duct and the secondary air duct, adjusting the speed of the blower through the frequency converter, and adjusting the coal feed rate and primary air temperature of the pulverizing system, so as to achieve precise control of the Zhundong coal combustion process and anti-coking optimization.

8. An electronic device, characterized in that: include: processor; a memory for storing processor-executable instructions; The processor is configured to call the instructions stored in the memory to execute the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having computer program instructions stored thereon, characterized in that: When the computer program instructions are executed by a processor, the method according to any one of claims 1 to 6 is implemented.

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