Thermal power plant denitration system ammonia injection optimization control method considering characteristics of coal as received plant

Abstract

The invention provides a thermal power plant denitration system ammonia injection optimization control method considering the characteristics of coal as received, a denitration ammonia injection amount total amount control method mainly adopts a two-stage intelligent controller for control, and a total amount main intelligent controller controls the ammonia injection amount according to an outlet NOx concentration value deviation value, a denitration inlet NOx concentration value and a flue gas amount value feed-forward value. The total amount auxiliary intelligent controller controls the opening degree of a total amount valve according to the ammonia spraying amount deviation value; according to the denitration ammonia spraying amount partition control method, the opening degree of an adjusting valve of each partition is obtained according to the NOx concentration deviation value of an outlet of each partition and the total ammonia spraying amount as constraint conditions; the construction of the total quantity control and partition control parameters under different coal quality characteristics mainly comprises the step of establishing parameter values of controllers at all levels according to different ash contents, volatile components, moisture and calorific values of coal entering a thermal power plant. Under the condition of the lowest ammonia spraying amount, the NOx concentration at the outlet of the denitration reactor reaches the standard for emission, and the device has important significance on reduction of emission pollutants and cost of a thermal power plant.

Description

Technical Field

[0001] The invention relates to the technical field of flue gas denitration in coal-fired power plants, and in particular to an ammonia injection optimization control method for a denitration system in a thermal power plant taking into account the characteristics of incoming coal. Background Art

[0002] After the ultra-low emission transformation of power plant flue gas, the NOx emission concentration of coal-fired power plants must be lower than 50mg / m 3 At present, the most widely used denitrification technology at home and abroad is SCR (Selective Catalytic Reduction) flue gas denitrification technology, in which the control of ammonia injection is an important process. When the amount of ammonia injection is too little, the outlet NOx emissions will exceed the standard; when the amount of ammonia injection is excessive, the ammonia escape rate will increase, causing the downstream air preheater to be blocked and corroded. Therefore, the control of ammonia amount is crucial to the denitrification system.

[0003] At present, the commonly used method is the total amount of ammonia injection control method, which often uses a single-loop outlet NOx fixed value control method, a fixed molar ratio control method or a cascade PID control method, but the control process of the above methods has a certain lag and the control effect is poor. At the same time, due to the unevenness of the flow field of the denitrification system itself, a single denitrification outlet NOx measurement often cannot represent the characteristics of the entire system, so the control effect is poor, and sometimes the NOx emission concentration exceeds 50mg / m 3 .

[0004] Therefore, in order to achieve the economical and environmentally friendly goal of NOx concentration at the outlet of the denitrification reactor, the appropriateness of adjusting the total amount of ammonia injection and the uniformity of ammonia injection are issues that need to be urgently addressed in the current denitrification field. Summary of the invention

[0005] The purpose of the present invention is to provide a method for optimizing the control of ammonia injection in a denitration system of a thermal power plant taking into account the characteristics of the incoming coal, which can achieve the emission of NOx concentration at the outlet of the denitration reactor meeting the emission standards under the condition of the minimum ammonia injection amount, and is of great significance for reducing the emission of pollutants and costs in thermal power plants.

[0006] According to the purpose of the present invention, the present invention provides a method for optimizing ammonia injection in a thermal power plant denitrification system considering the characteristics of incoming coal, the method includes a method for controlling the total amount of ammonia injection for denitrification, a method for controlling the amount of ammonia injection for denitrification by zoning, and constructing total amount control and zoning control parameters under different coal quality characteristics; the method includes the following steps:

[0007] Step 100, the total amount control method of ammonia injection for denitration is mainly controlled by a two-stage intelligent controller, the total amount main intelligent controller controls the ammonia injection amount according to the outlet NOx concentration value deviation value and the denitration inlet NOx concentration value and the flue gas volume value feedforward value, and the total amount sub-intelligent controller controls the total amount valve opening according to the ammonia injection amount deviation value;

[0008] Step 200, the denitration ammonia injection amount zoning control method obtains the opening of each zone regulating valve according to the NOx concentration deviation value at the outlet of each zone and the total ammonia injection amount as constraint conditions;

[0009] Step 300, constructing total control and zoning control parameters under different coal quality characteristics is mainly based on the different ash, volatile matter, moisture, and calorific value of the coal entering the thermal power plant, and establishing parameter values ​​for controllers at all levels.

[0010] Furthermore, the input of the total amount main intelligent controller is mainly the deviation between the outlet NOx concentration set value and the average value of the NOx concentration measured at the outlet of each partition; the output of the total amount main intelligent controller is mainly the calculated value of the ammonia injection amount; the input of the total amount sub-intelligent controller is mainly the calculated value of the ammonia injection amount and the theoretical ammonia injection amount; the output of the total amount sub-intelligent controller is the total amount control valve of the denitration reactor. The total amount of ammonia injection is controlled by the opening size of the total amount control valve, thereby controlling the NOx concentration value at the outlet of the denitration reactor.

[0011] Furthermore, the total amount main intelligent controller and the total amount sub-intelligent controller adopt PID control, or model predictive control, and their parameters are optimized by genetic algorithm; the partition intelligent controller adopts PID control or model predictive control, and its parameters are optimized by genetic algorithm.

[0012] Furthermore, the denitrification ammonia injection amount zoning control method adopts a zoning intelligent controller, the input of the zoning intelligent controller is the deviation between the average value of the NOx concentration measurement value at the outlet of each zone and the NOx concentration measurement value at the outlet of each zone, and the output of the zoning intelligent controller is the calculated value of the ammonia injection amount of each zone; according to the calculated value of the ammonia injection amount of each zone and the theoretically required ammonia injection amount of each zone, the opening of the control valve of each zone is obtained, the ammonia injection amount of each zone is controlled, and then the NOx concentration value at the outlet of each zone is controlled.

[0013] Furthermore, in step 300, different incoming coals are determined according to the ash content, volatile matter, moisture content, and calorific value parameters of the incoming coals, and the NOx concentration at the inlet of the denitrification reactor, the flue gas volume, the total amount main intelligent controller, the total amount sub-intelligent controller, and the partitioned intelligent controller are different under different incoming coals; according to different incoming coals, the parameters under the above-mentioned models are established, and a parameter library for different incoming coals is constructed; in the subsequent control process, different model parameters are selected from the incoming coal parameter library according to the fact that the incoming coal is opaque.

[0014] Furthermore, the theoretical ammonia injection amount is mainly obtained based on the product of the NOx concentration value at the SCR inlet, the flue gas volume and the ammonia nitrogen molar ratio.

[0015] Furthermore, the NOx concentration value at the SCR inlet is mainly predicted based on the BP neural network algorithm; the influencing factors related to the inlet NOx concentration are analyzed based on the SCR inlet NOx concentration generation mechanism, including unit load, total air volume, total coal volume, and primary air volume, and these parameters are used as input parameters of the BP neural network; the output is the SCR inlet NOx concentration.

[0016] Furthermore, the flue gas volume is predicted according to the BP neural network algorithm; the influencing factors related to the flue gas volume are analyzed according to the flue gas generation mechanism, including unit load, total air volume, and oxygen content, and these parameters are used as input parameters of the BP neural network; and the output is the flue gas volume.

[0017] Furthermore, the BP neural network adopts a three-layer structure of input layer, hidden layer and output layer, and its parameters include weights and thresholds between the input layer and the hidden layer, and weights and threshold parameters between the hidden layer and the output layer. The parameters are mainly obtained by continuously optimizing the error function between the predicted value and the measured value.

[0018] Furthermore, the average value of the NOx concentration measurement value at the outlet of each partition is calculated according to formula (1):

[0019] Ave_NOx=(A1_NOx+A2_NOx+……+An_NOx) / n; formula (1)

[0020] Where A1_NOx, A2_NOx, An_NOx are the outlet NOx concentration values ​​of the 1st partition, the 2nd partition, and the nth partition respectively; n is the number of partitions.

[0021] Furthermore, the theoretical required ammonia injection amount of each partition is mainly obtained according to the total ammonia injection amount and the weight of each partition; the weight of each partition is mainly obtained according to the proportion of the NOx concentration value at the outlet of each partition, which is specifically obtained according to formula (2):

[0022]

[0023] Where Ai_NOx is the NOx concentration at the outlet of the ith partition, λ i is the weight of the i-th partition;

[0024] The theoretical required ammonia injection amount for the i-th partition is calculated according to formula (3):

[0025] Ai_NH3=λ i *Total_NH3; formula (3)

[0026] Wherein, Ai_NH3 is the theoretical amount of ammonia sprayed in the ith partition; Total_NH3 is the total amount of ammonia sprayed.

[0027] The technical solution of the present invention can predict the NOx concentration and flue gas volume at the inlet of the SCR reactor in advance, solve the problems of large lag and inaccurate measurement existing in the measurement of self-contained instruments and equipment, and comprehensively consider the differences in data characteristics under various loads during the establishment of the intelligent controller. The genetic algorithm is used to optimize the parameters under different loads to obtain the optimal controller parameters; the NOx concentration value at the outlet of each partition can be effectively controlled to make the NOx concentration at the outlet of each partition evenly distributed, which is more conducive to total control; controller parameter values ​​under different coal quality characteristics are also constructed in the modeling process, and the system can adjust different parameters according to the different coal entering the factory, so as to achieve better control effect; the outlet NOx concentration value can be stabilized near the set value, the whole process is simple to operate and quick to adjust, and the outlet NOx emission is controlled to meet the standard with the optimal ammonia injection amount. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0029] Figure 1 This is a flow chart of the ammonia injection optimization control method according to an embodiment of the present invention;

[0030] Figure 2 This is a flow chart of a method for controlling the total amount of ammonia sprayed for denitration according to an embodiment of the present invention;

[0031] Figure 3 This is a flow chart of the method for controlling the amount of ammonia sprayed for denitrification according to an embodiment of the present invention. DETAILED DESCRIPTION

[0032] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are part of the embodiments of the present invention, rather than 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.

[0033] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "length", "width", "thickness", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside", "clockwise", "counterclockwise" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the referred device or element must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be understood as limiting the present invention.

[0034] In addition, the terms "first" and "second" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features. In the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined. In addition, the terms "installed", "connected" and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal connection of two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0035] Example 1

[0036] like Figure 1 As shown, a method for optimizing ammonia injection in a denitrification system of a thermal power plant considering the characteristics of incoming coal is provided, including a total amount control method for denitrification ammonia injection, a zoning control method for denitrification ammonia injection, and construction of total amount control and zoning control parameters under different coal quality characteristics.

[0037] The specific steps include:

[0038] Step 100, the total amount control method of denitrification ammonia injection is mainly controlled by a two-level intelligent controller. The total amount main intelligent controller controls the ammonia injection amount according to the outlet NOx concentration value deviation value and the denitrification inlet NOx concentration value and the flue gas volume value feedforward value, and the total amount sub-intelligent controller controls the total amount valve opening according to the ammonia injection amount deviation value.

[0039] Step 200, the denitrification ammonia injection amount zoning control method obtains the opening of each zone regulating valve based on the NOx concentration deviation value at the outlet of each zone and the total ammonia injection amount as constraint conditions.

[0040] Step 300, the construction of total control and zoning control parameters under different coal quality characteristics is mainly based on the different ash, volatile matter, moisture and calorific value of the coal entering the thermal power plant, and the establishment of parameter values ​​of controllers at various levels.

[0041] like Figure 2 As shown, the input of the total amount main intelligent controller is mainly the deviation between the outlet NOx concentration set value and the average value of the outlet NOx concentration measurement value of each partition; the output of the total amount main intelligent controller is mainly the calculated value of the injection amount of ammonia;

[0042] Specifically, the input of the total amount sub-intelligent controller is mainly the calculated value of the ammonia injection amount and the theoretical ammonia injection amount; the output of the total amount sub-intelligent controller is the total amount control valve of the denitrification reactor. The total ammonia injection amount is controlled by the opening size of the total amount control valve, thereby controlling the NOx concentration value at the outlet of the denitrification reactor.

[0043] Specifically, the total amount main intelligent controller and the total amount sub-intelligent controller can adopt PID control or model predictive control, and their parameters are optimized by genetic algorithm.

[0044] Specifically, the theoretical ammonia injection amount is mainly obtained based on the product of the NOx concentration value at the SCR inlet, the flue gas volume and the ammonia nitrogen molar ratio.

[0045] Specifically, the SCR inlet NOx concentration value is mainly predicted based on the BP neural network algorithm. According to the SCR inlet NOx concentration generation mechanism, the influencing factors related to the inlet NOx concentration are analyzed, including unit load, total air volume, total coal volume, and primary air volume. These parameters are used as input parameters of the BP neural network; the output is the SCR inlet NOx concentration.

[0046] Specifically, the flue gas volume is also predicted based on the BP neural network algorithm. According to the flue gas generation mechanism, the factors related to the flue gas volume are analyzed, including unit load, total air volume, and oxygen content. These parameters are used as input parameters of the BP neural network; the output is the flue gas volume.

[0047] Specifically, the BP neural network adopts a three-layer structure of input layer, hidden layer, and output layer. Its parameters include the weight and threshold between the input layer and the hidden layer, and the weight and threshold parameters between the hidden layer and the output layer. The parameters are mainly obtained by continuously optimizing the error function between the predicted value and the measured value.

[0048] like Figure 3As shown, specifically, the denitrification ammonia injection amount zoning control method adopts a zoning intelligent controller, the input of the zoning intelligent controller is the deviation between the average value of the NOx concentration measurement value at the outlet of each zoning and the NOx concentration measurement value at the outlet of each zoning, and the output is the calculated value of the ammonia injection amount of each zoning. According to the calculated value of the ammonia injection amount of each zoning and the theoretical required ammonia injection amount of each zoning, the opening of the control valve of each zoning is obtained, the ammonia injection amount of each zoning is controlled, and then the NOx concentration value at the outlet of each zoning is controlled.

[0049] Specifically, the partition intelligent controller can adopt PID control or model predictive control, and its parameters are optimized by genetic algorithm.

[0050] Specifically, the average value of the NOx concentration measurement value at the outlet of each partition is calculated according to formula (1).

[0051] Ave_NOx=(A1_NOx+A2_NOx+……+ An_NOx) / n; Formula (1)

[0052] Where A1_NOx, A2_NOx, An_NOx are the outlet NOx concentration values ​​of the 1st partition, the 2nd partition, and the nth partition respectively; n is the number of partitions, which is usually divided into 4-6 partitions.

[0053] Specifically, the theoretical required ammonia injection amount of each partition is mainly obtained based on the total ammonia injection amount and the weight of each partition. The weight of each partition is mainly obtained based on the proportion of the NOx concentration value at the outlet of each partition, which is specifically calculated according to formula (2).

[0054]

[0055] Where Ai_NOx is the NOx concentration at the outlet of the ith partition, λ i is the weight of the i-th partition.

[0056] The theoretical required ammonia injection amount for the i-th partition is calculated according to formula (3).

[0057] Ai_NH3=λ i *Total_NH3; formula (3)

[0058] Wherein, Ai_NH3 is the theoretical amount of ammonia sprayed in the ith partition; Total_NH3 is the total amount of ammonia sprayed.

[0059] Specifically, step 300 determines different incoming coals according to the ash content, volatile matter, moisture content, and calorific value parameters of the incoming coals. The NOx concentration at the inlet of the denitrification reactor, the flue gas volume, the total amount main intelligent controller, the total amount sub-intelligent controller, and the partition intelligent controller parameters are different for different incoming coals. According to different incoming coals, the parameters under the above models are established, and a parameter library of different incoming coals is constructed. In the subsequent control process, different model parameters are selected in the incoming coal parameter library according to the opacity of the incoming coal.

[0060] The present invention overcomes the problems of delayed measurement of NOx concentration at the inlet of the denitration reactor, inaccurate measurement of flue gas volume, uneven ammonia injection, etc., and can achieve emission of NOx concentration at the outlet of the denitration reactor meeting the standards under the condition of minimum ammonia injection, which is of great significance for reducing pollutant emissions and costs in thermal power plants.

[0061] The SCR reactor inlet NOx concentration prediction method and flue gas volume calculation method based on the BP neural network algorithm of the present invention can predict the SCR reactor inlet NOx concentration and flue gas volume values ​​in advance, and solve the problems of large lag and inaccurate measurement existing in the measurement of self-contained instruments and equipment.

[0062] The present invention is based on a total ammonia injection control method controlled by a two-stage intelligent controller. During the establishment of the intelligent controller, differences in data characteristics under various loads are comprehensively considered, and a genetic algorithm is used to optimize parameters under different loads to obtain optimal controller parameters.

[0063] The zoning control method based on the intelligent controller of the present invention can effectively control the NOx concentration value of each zone outlet, so that the NOx concentration of each zone outlet is evenly distributed, which is more conducive to total amount control.

[0064] The present invention takes into account that the characteristics of the incoming coal have a great influence on the NOx concentration and flue gas volume at the inlet of the denitrification reactor. During the modeling process, controller parameter values ​​under different coal quality characteristics are also constructed. The system can adjust different parameters according to the different incoming coal to achieve better control effect.

[0065] The present invention can stabilize the outlet NOx concentration value near the set value, the whole process is simple to operate and quick to adjust, and the outlet NOx emission is controlled to meet the standard with the optimal ammonia injection amount.

[0066] 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 method for optimizing the control of ammonia injection in a thermal power plant denitrification system taking into account the characteristics of incoming coal, characterized in that: It includes the total amount control method of denitrification ammonia injection, the zoning control method of denitrification ammonia injection, and the construction of total amount control and zoning control parameters under different coal quality characteristics; The following steps are involved: Step 100, the total amount control method of ammonia injection for denitration is mainly controlled by a two-stage intelligent controller, the total amount main intelligent controller controls the ammonia injection amount according to the outlet NOx concentration value deviation value and the denitration inlet NOx concentration value and the flue gas volume value feedforward value, and the total amount sub-intelligent controller controls the total amount valve opening according to the ammonia injection amount deviation value; Step 200, the denitration ammonia injection amount zoning control method obtains the opening of each zone regulating valve according to the NOx concentration deviation value at the outlet of each zone and the total ammonia injection amount as constraint conditions; Step 300, constructing total control and zoning control parameters under different coal quality characteristics is mainly based on the different ash, volatile matter, moisture, and calorific value of the coal entering the thermal power plant, and establishing parameter values ​​for controllers at all levels.

2. The method for optimizing ammonia injection control of a thermal power plant denitrification system considering the characteristics of incoming coal according to claim 1, characterized in that: The input of the total amount main intelligent controller is the deviation between the outlet NOx concentration set value and the average value of the outlet NOx concentration measurement value of each partition; the output of the total amount main intelligent controller is mainly the calculated value of the injection amount of ammonia; The input of the total amount sub-intelligent controller is the calculated value of the ammonia injection amount and the theoretical ammonia injection amount; the output of the total amount sub-intelligent controller is the total amount control valve of the denitration reactor, and the total ammonia injection amount is controlled by the opening size of the total amount control valve, thereby controlling the NOx concentration value at the outlet of the denitration reactor; The total amount main intelligent controller and the total amount sub-intelligent controller adopt PID control or model predictive control, and their parameters are optimized by genetic algorithm.

3. The method for optimizing ammonia injection control of a thermal power plant denitrification system considering the characteristics of incoming coal according to claim 1, characterized in that: The denitrification ammonia injection amount zoning control method adopts a zoning intelligent controller, the input of the zoning intelligent controller is the deviation between the average value of the NOx concentration measurement value at the outlet of each zone and the NOx concentration measurement value at the outlet of each zone, and the output of the zoning intelligent controller is the calculated value of the ammonia injection amount of each zone; The opening of each zone control valve is obtained according to the calculated value of the ammonia injection amount of each zone and the theoretically required ammonia injection amount of each zone, and the ammonia injection amount of each zone is controlled, thereby controlling the NOx concentration value at the outlet of each zone. The partition intelligent controller can adopt PID control or model predictive control, and its parameters are optimized by genetic algorithm.

4. The method for optimizing ammonia injection control of a thermal power plant denitrification system considering the characteristics of incoming coal according to claim 1, characterized in that: In step 300, different incoming coals are determined according to the ash content, volatile matter, moisture content, and calorific value parameters of the incoming coals. The NOx concentration at the inlet of the denitrification reactor, the flue gas volume, the total amount main intelligent controller, the total amount sub-intelligent controller, and the partition intelligent controller are different under different incoming coals; according to different incoming coals, the parameters under the above-mentioned models are established, and a parameter library for different incoming coals is constructed; in the subsequent control process, different model parameters are selected from the incoming coal parameter library according to the opacity of the incoming coal.

5. The method for optimizing ammonia injection control of a thermal power plant denitrification system considering the characteristics of incoming coal according to claim 2, characterized in that: The theoretical ammonia injection amount is obtained according to the product of the NOx concentration value at the SCR inlet, the flue gas volume and the ammonia nitrogen molar ratio.

6. The method for optimizing ammonia injection control of a thermal power plant denitrification system considering the characteristics of incoming coal according to claim 2, characterized in that: The NOx concentration value at the SCR inlet is predicted based on the BP neural network algorithm. The influencing factors related to the inlet NOx concentration are analyzed based on the SCR inlet NOx concentration generation mechanism, including unit load, total air volume, total coal volume, and primary air volume. These parameters are used as input parameters of the BP neural network. The output is the SCR inlet NOx concentration.

7. The method for optimizing ammonia injection control of a thermal power plant denitrification system considering the characteristics of incoming coal according to claim 2, characterized in that: The flue gas volume is predicted based on the BP neural network algorithm; the influencing factors related to the flue gas volume are analyzed based on the flue gas generation mechanism, including unit load, total air volume, and oxygen content, which are used as input parameters of the BP neural network; the output is the flue gas volume.

8. The method for optimizing ammonia injection control of a thermal power plant denitrification system considering the characteristics of incoming coal according to claim 2, characterized in that: The BP neural network adopts a three-layer structure of input layer, hidden layer and output layer. Its parameters include the weight and threshold between the input layer and the hidden layer, and the weight and threshold parameters between the hidden layer and the output layer. The parameters are mainly obtained by continuously optimizing the error function between the predicted value and the measured value.

9. The method for optimizing ammonia injection control of a thermal power plant denitrification system considering the characteristics of incoming coal according to claim 3, characterized in that: The average value of the NOx concentration measured at the outlet of each partition is calculated according to formula (1): Ave_NOx=(A1_NOx+A2_NOx+……+ An_NOx) / n; (Formula 1) Where A1_NOx, A2_NOx, An_NOx are the outlet NOx concentration values ​​of the 1st partition, the 2nd partition, and the nth partition respectively; n is the number of partitions.

10. The method for optimizing ammonia injection control of a thermal power plant denitrification system considering the characteristics of incoming coal according to claim 3, characterized in that: The theoretical amount of ammonia sprayed in each zone is mainly obtained based on the total amount of ammonia sprayed and the weight of each zone; the weight of each zone is mainly obtained based on the proportion of the NOx concentration value at the outlet of each zone, which is specifically obtained according to formula (2): Where Ai_NOx is the NOx concentration at the outlet of the ith partition, λ i is the weight of the i-th partition; The theoretical required ammonia injection amount for the ith partition is calculated according to Formula 3: Ai_NH3=λ i *Total_NH3; (Formula 3) Wherein, Ai_NH3 is the theoretical amount of ammonia sprayed in the ith partition; Total_NH3 is the total amount of ammonia sprayed.

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