Ammonia escape comprehensive control method for high-concentration NOx flue gas denitration

Abstract

The invention provides an ammonia escape comprehensive control method for high-concentration NOx flue gas denitration, and relates to the technical field of flue gas treatment.The method comprises the following steps that a multi-stage denitration section system arranged in a flue is built, and each stage of system comprises an ammonia spraying system, a catalyst layer and a heat exchanger behind the ammonia spraying system; temperature measuring points are arranged in front of and behind each stage of catalyst layer and behind the heat exchanger, and the flue gas temperature is monitored in real time; nitrogen oxide concentration monitoring devices are arranged at an inlet and an outlet of each stage of denitration section system; the ammonia spraying system sprays ammonia, the ammonia spraying system is matched with the catalyst layers for staged treatment, the flue gas temperature before and after each stage of catalyst layer and behind a heat exchanger and the NOx concentration in the flue gas at an inlet and an outlet of each stage of denitration section system are collected, an algorithm control system is matched, and the ammonia spraying amount is calculated in combination with flow before each stage of treatment; therefore, the ammonia spraying amount of each stage is accurately controlled in real time, the situation of excessive ammonia spraying is completely eradicated, ammonia gas utilization is maximized, each stage is managed in a partitioned mode, and ammonia is accurately controlled.

Description

Technical Field

[0001] The present invention relates to the technical field of flue gas treatment, and in particular to a comprehensive control method for ammonia escape in high-concentration NOx flue gas denitrification. Background Art

[0002] High-concentration NOx (nitrogen oxides) flue gas mainly comes from industrial processes, especially the combustion of fossil fuels, such as coal-fired power plants, internal combustion engines, industrial kilns, etc. These processes will produce a large amount of NOx at high temperatures, mainly including nitric oxide (NO) and nitrogen dioxide (NO2). High-concentration NOx flue gas has significant harm to the environment and human health. NOx combines with water vapor in the atmosphere to form acidic substances, causing acid rain. Acid rain can destroy soil structure, cause soil impoverishment, affect plant growth, and corrode buildings and public facilities. NOx and volatile organic compounds will undergo photochemical reactions under the action of sunlight to generate photochemical Photochemical smog can irritate people's eyes and respiratory system, damage plant leaves, and aggravate the greenhouse effect of the atmosphere. NOx has a destructive effect on the ozone layer and accelerates the depletion of the ozone layer. The destruction of the ozone layer will lead to enhanced ultraviolet radiation, which will have an adverse effect on human health and the ecological environment. NOx can irritate people's respiratory tract and cause symptoms such as coughing and asthma. Long-term exposure to high concentrations of NOx may cause respiratory diseases such as chronic obstructive pulmonary disease. NOx can have a negative impact on the cardiovascular system and increase the risk of heart disease, stroke and other diseases. NOx has a certain degree of carcinogenicity. Long-term exposure may increase the risk of malignant tumors such as lung cancer. Therefore, it is necessary to denitrify the high-concentration NOx flue gas. The prior art generally uses a spray gun to spray ammonia in combination with a catalyst layer to treat the flue gas. Ammonia is generally sprayed at a maximum flow rate to achieve the purpose of complete treatment, which will cause insufficient mixing of ammonia and flue gas. Most of the ammonia escapes without reacting and cannot adapt to changes in load and denitrification inlet NOx. Therefore, the present invention proposes a comprehensive control method for ammonia escape in high-concentration NOx flue gas denitrification to solve the problems existing in the prior art. Summary of the invention

[0003] In view of the above problems, the present invention proposes a comprehensive control method for ammonia escape of high-concentration NOx flue gas denitrification. The comprehensive control method for ammonia escape of high-concentration NOx flue gas denitrification controls the amount of ammonia sprayed at each stage in real time and accurately prevents excessive ammonia spraying, thereby maximizing the utilization of ammonia, managing each stage in a zoned manner, and accurately controlling ammonia.

[0004] To achieve the purpose of the present invention, the present invention is implemented by the following technical scheme: a comprehensive control method for ammonia escape of high-concentration NOx flue gas denitrification, comprising the following steps: S1: Construct a multi-stage denitrification system built into the flue, each stage of the system includes an ammonia injection system, a catalyst layer and a heat exchanger at the rear; S2: Set temperature measuring points before and after each catalyst layer and behind the heat exchanger to monitor the flue gas temperature in real time; S3: A nitrogen oxide concentration monitoring device is installed at the inlet and outlet of each stage of the denitrification system to monitor the NOx concentration in the flue gas in real time; S4: Construct an algorithm control system to calculate the amount of ammonia injection based on the current detected flue gas NOx concentration and flue gas temperature combined with the flow rate before each stage of treatment; S5: A monitoring space is reserved between each stage of the denitrification system, and an ammonia monitoring device is built in to identify possible ammonia escape values; S6: Construct a neuron compensation system, bring the ammonia escape value of the current stage into the ammonia injection amount of the current stage, calculate the compensation value, and correct the ammonia injection amount; S7: Establish a catalyst layer timing module to calculate the usage time of each catalyst layer according to the flue gas delivery time, and remind maintenance when the usage threshold is reached.

[0005] Further improvements are as follows: in S1, the ammonia injection system is used to spray ammonia or urea into the flue gas, and the ammonia injection system includes an ammonia storage tank, an ammonia / air mixer, an ammonia injection grid and a nozzle. After the ammonia is fully mixed with the air through the ammonia / air mixer, it is evenly sprayed into the flue gas through the ammonia injection grid and fully mixed with the flue gas; the catalyst layer is filled with an SCR catalyst for catalyzing the selective reduction reaction of ammonia and NOx in the flue gas to generate nitrogen and water; the heat exchanger is located behind the catalyst layer for recovering waste heat in the flue gas and adjusting the flue gas temperature to parameters suitable for subsequent treatment.

[0006] A further improvement is that in S2, temperature measuring points are set before and after each stage of the catalyst layer and behind the heat exchanger to monitor the temperature of the flue gas before and after treatment, thereby controlling the heat exchanger to adjust the temperature. After temperature adjustment, the current flue gas temperature is monitored. Before entering the next stage of the denitrification system, the current flue gas temperature is monitored again. The current flue gas temperature is compared with the temperature of the previous stage of the heat exchanger after temperature adjustment, the difference is calculated, and the adjustment value is converted to adjust the temperature adjustment parameters of each stage of the heat exchanger.

[0007] A further improvement is that in S3, a nitrogen oxide concentration monitoring device is set at the inlet and outlet of each stage of the denitrification system, and an air volume sensor is arranged in the nitrogen oxide concentration monitoring device at the inlet of each stage of the denitrification system, so as to monitor the flue gas flow entering each stage of the denitrification system while detecting the NOx concentration in the flue gas in real time.

[0008] A further improvement is that: said S4 comprises the following steps: Build an algorithm control system to dynamically adjust the amount of ammonia injection based on flue gas NOx concentration, flue gas temperature and flow rate; Input parameters: flue gas NOx concentration, flue gas temperature, flue gas flow rate; output parameters: ammonia injection amount, in NH 3 Expressed as molar amount or volume flow rate; The calculation is based on the chemical reaction equation and the NOx reduction efficiency. First, the required NOx molar amount is calculated based on the current NOx concentration and flow rate, and the required NH 3 molar amount; The ammonia injection amount is adjusted to compensate for the temperature value, and the feedback of the NOx concentration at the outlet of the denitrification system is introduced. The ammonia injection amount is calculated according to the optimal treatment NOx concentration of the current stage through the PID proportional-integral-differential controller.

[0009] Further improvements are: when the NOx concentration is too high, the amount of ammonia injection is increased; when the NOx concentration decreases, the amount of ammonia injection is reduced. In combination with the load fluctuation amplitude and the fluctuation amplitude of the NOx concentration at the inlet of the denitrification section system, the amount of ammonia injection is dynamically adjusted to minimize ammonia escape and maintain denitrification efficiency as the benchmark for dynamic control.

[0010] A further improvement is that in S5, an openable sealed door is arranged on the monitoring space, and an ammonia monitoring device is arranged on the inner side of the door to detect ammonia and its concentration that may exist in the flue gas after each stage of denitration system processing.

[0011] A further improvement is that: S6 comprises the following steps: Collect historical data of ammonia monitoring devices after each stage of denitrification system, including ammonia escape values ​​and corresponding ammonia injection amounts under different operating conditions, as well as flue gas temperature and catalyst status data; Using the collected historical data to train the neural network, during the training process, the weights and biases of the neural network are adjusted by minimizing the error between the predicted compensation value and the actual compensation value; Use gradient descent or Adam optimizer to update weights and biases; The trained neural network model is deployed to the actual control system, and the ammonia escape value and other relevant parameters at the current level are collected in real time and input into the neural network model.

[0012] The compensation value of the ammonia injection amount is calculated according to the input data, and the ammonia injection amount is adjusted based on the compensation value, and then the ammonia slip value is continuously monitored for the next round of feedback adjustment.

[0013] Further improvements are: after data collection, the data is cleaned and preprocessed to remove noise and outliers and normalize them.

[0014] Further improvement is to set up a catalyst layer timing module to calculate the usage time of each catalyst layer, use this time as the state vector data of the catalyst layer, and use this state vector data as an influencing factor in the calculation of the neuron compensation system.

[0015] The beneficial effects of the present invention are: 1. The present invention sprays ammonia through an ammonia spraying system and cooperates with a catalyst layer for graded treatment to improve the utilization rate of ammonia. By collecting the flue gas temperature before and after each stage of the catalyst layer and behind the heat exchanger and the NOx concentration in the flue gas at the inlet and outlet of each stage of the denitrification section system, and cooperating with an algorithm control system, the ammonia spraying amount is calculated in combination with the flow rate before each stage of treatment, thereby controlling the ammonia spraying amount of each stage in real time and accurately, eliminating the situation of excessive ammonia spraying, maximizing the utilization of ammonia, managing each stage in different areas, and accurately controlling ammonia.

[0016] 2. The present invention reserves monitoring space between each stage of the denitrification system to identify possible ammonia escape values, cooperates with the neuron compensation system, combines the flue gas temperature and catalyst status data, calculates the compensation value of the ammonia injection amount, and adjusts the ammonia injection amount based on the compensation value, so as to compensate for the floating value that may exist under the ammonia control, make the regulation of ammonia more precise, and further reduce ammonia escape.

[0017] 3. The present invention establishes a catalyst layer timing module to calculate the usage time of each catalyst layer, and uses the time as the state vector data of the catalyst layer as an influencing factor for ammonia control, thereby making the calculation data more diversified and ensuring the normal operation of the catalyst layer. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 It is a flow chart of the present invention. DETAILED DESCRIPTION

[0019] In order to deepen the understanding of the present invention, the present invention will be further described in detail below in conjunction with examples. The examples are only used to explain the present invention and do not constitute a limitation on the protection scope of the present invention.

[0020] Embodiment 1 according to Figure 1 As shown, this embodiment proposes a comprehensive control method for ammonia escape in high-concentration NOx flue gas denitrification, comprising the following steps: S1: Construct a multi-stage denitrification system built into the flue, each stage of the system includes an ammonia injection system, a catalyst layer and a heat exchanger at the rear; S2: Set temperature measuring points before and after each catalyst layer and behind the heat exchanger to monitor the flue gas temperature in real time; S3: A nitrogen oxide concentration monitoring device is installed at the inlet and outlet of each stage of the denitrification system to monitor the NOx concentration in the flue gas in real time; S4: Construct an algorithm control system to calculate the amount of ammonia injection based on the current detected flue gas NOx concentration and flue gas temperature combined with the flow rate before each stage of treatment; S5: A monitoring space is reserved between each stage of the denitrification system, and an ammonia monitoring device is built in to identify possible ammonia escape values; S6: Construct a neuron compensation system, bring the ammonia escape value of the current stage into the ammonia injection amount of the current stage, calculate the compensation value, and correct the ammonia injection amount; S7: Establish a catalyst layer timing module to calculate the usage time of each catalyst layer according to the flue gas delivery time, and remind maintenance when the usage threshold is reached.

[0021] The present invention sprays ammonia through an ammonia spraying system, cooperates with a catalyst layer to carry out graded treatment, improves the utilization rate of ammonia, collects the flue gas temperature before and after each stage of the catalyst layer and behind the heat exchanger and the NOx concentration in the flue gas at the inlet and outlet of each stage of the denitrification section system, cooperates with an algorithm control system, and calculates the sprayed ammonia amount in combination with the flow rate before each stage of treatment, thereby controlling the sprayed ammonia amount of each stage in real time and accurately, eliminating the situation of excessive ammonia spraying, maximizing the utilization of ammonia, and managing each stage in a zone to accurately control ammonia.

[0022] Embodiment 2 according to Figure 1 As shown, this embodiment proposes a comprehensive control method for ammonia escape in high-concentration NOx flue gas denitrification, comprising the following steps: S1: Construct a multi-stage denitrification system built into the flue, each stage of the system includes an ammonia injection system, a catalyst layer and a heat exchanger at the rear; the ammonia injection system is used to spray ammonia or urea into the flue gas, and the ammonia injection system includes an ammonia storage tank, an ammonia / air mixer, an ammonia injection grid and a nozzle. After ammonia is fully mixed with air through the ammonia / air mixer, it is evenly sprayed into the flue gas through the ammonia injection grid and fully mixed with the flue gas; the catalyst layer is filled with an SCR catalyst, which is used to catalyze the selective reduction reaction of ammonia and NOx in the flue gas to generate nitrogen and water; the heat exchanger is located behind the catalyst layer, which is used to recover the waste heat in the flue gas and adjust the flue gas temperature to parameters suitable for subsequent treatment.

[0023] S2: Set temperature measuring points before and after each catalyst layer and behind the heat exchanger to monitor the flue gas temperature in real time; Set temperature measuring points before and after each catalyst layer and behind the heat exchanger to monitor the flue gas temperature before and after treatment, thereby controlling the heat exchanger to adjust the temperature. After temperature adjustment, monitor the current flue gas temperature. Before entering the next stage of the denitrification system, monitor the current flue gas temperature again. Compare the current flue gas temperature with the temperature after temperature adjustment of the previous stage of the heat exchanger, calculate the difference, and convert the adjustment value to adjust the temperature adjustment parameters of each stage of the heat exchanger. Therefore, according to the fluctuation of the difference, the heat exchange efficiency of the heat exchanger is dynamically adjusted to improve the treatment effect of the flue gas temperature and the utilization rate of ammonia.

[0024] S3: A nitrogen oxide concentration monitoring device is installed at the inlet and outlet of each stage of the denitrification system to monitor the NOx concentration in the flue gas in real time; a nitrogen oxide concentration monitoring device is installed at the inlet and outlet of each stage of the denitrification system, and an air volume sensor is arranged in the nitrogen oxide concentration monitoring device at the inlet of each stage of the denitrification system to monitor the flue gas flow entering each stage of the denitrification system while detecting the NOx concentration in the flue gas in real time.

[0025] S4: Construct an algorithm control system. Before each level of treatment, the amount of ammonia sprayed is calculated based on the currently detected flue gas NOx concentration and flue gas temperature combined with the flow rate. The specific steps include: construct an algorithm control system that dynamically adjusts the amount of ammonia sprayed based on the flue gas NOx concentration, flue gas temperature and flow rate; input parameters are flue gas NOx concentration, flue gas temperature, and flue gas flow rate; output parameters are the amount of ammonia sprayed, in terms of NH 3 The molar amount or volume flow rate is expressed; it is calculated based on the chemical reaction equation and the NOx reduction efficiency. First, the required NOx molar amount is calculated based on the current NOx concentration and flow rate, and the required NH 3 Molar amount; adjust the ammonia injection amount to compensate for the temperature value, introduce the feedback of the NOx concentration at the outlet of the denitrification section system, and calculate the ammonia injection amount according to the optimal NOx concentration at the current level through the PID proportional-integral-differential controller. When the NOx concentration is too high, increase the ammonia injection amount; when the NOx concentration decreases, reduce the ammonia injection amount, and dynamically adjust the ammonia injection amount in combination with the load fluctuation amplitude and the fluctuation amplitude of the NOx concentration at the inlet of the denitrification section system, so as to minimize ammonia slip and maintain the denitrification efficiency as the benchmark for dynamic control. Total inlet nitrogen oxides: air volume × nitrogen oxide concentration, calculate the ammonia consumption rate n (inlet NOx concentration - outlet NOx concentration) × boiler smoke volume / ammonia flow), where the n value is (NH3) / n (NOx) ratio.

[0026] S5: A monitoring space is reserved between each stage of the denitration system, and an ammonia monitoring device is built in to identify possible ammonia escape values; an openable sealed door is arranged in the monitoring space, and an ammonia monitoring device is arranged on the inside of the door to detect possible ammonia and its concentration in the flue gas after each stage of the denitration system is processed. Through the sealed door, the flue can be opened to maintain and replace the catalyst layer to achieve the best treatment effect.

[0027] S6: Construct a neural compensation system, bring the ammonia escape value of the current stage into the ammonia injection amount of the current stage, calculate the compensation value, and correct the ammonia injection amount; specifically include the following steps: collect historical data of the ammonia monitoring device after each stage of the denitrification system, including the ammonia escape value and the corresponding ammonia injection amount under different working conditions, as well as the flue gas temperature and catalyst status data; after data collection, clean and preprocess the data, remove noise and outliers, and perform normalization; use the collected historical data to train the neural network, and during the training process, adjust the weight and bias of the neural network by minimizing the error between the predicted compensation value and the actual compensation value; use the gradient descent method or Adam optimizer to update the weight and bias; deploy the trained neural network model to the actual control system, collect the ammonia escape value and other related parameters of the current stage in real time, and input them into the neural network model. Calculate the compensation value of the ammonia injection amount based on the input data, adjust the ammonia injection amount based on the compensation value, and then continue to monitor the ammonia escape value for the next round of feedback adjustment. Neural network model design: The input layer contains the ammonia escape value of the current level as the main input, and can also include other relevant parameters (such as flue gas temperature, pressure, flow rate, etc.) as auxiliary inputs. Design one or more hidden layers, each of which contains a certain number of neurons. The number of hidden layers and the number of neurons in each hidden layer can be adjusted according to the complexity of the problem and the characteristics of the data. Activation functions (such as ReLU, Sigmoid, or Tanh) are used to introduce nonlinearity between neurons so that the model can learn complex mapping relationships. The output layer contains a neuron that outputs the compensation value of the ammonia injection amount. This compensation value can be a direct ammonia injection adjustment value or a percentage change relative to the current ammonia injection amount. Training the neural network: Use the collected historical data to train the neural network. During the training process, the weights and biases of the neural network are optimized by minimizing the error (such as mean square error MSE) between the predicted compensation value and the actual compensation value. The gradient descent method or its variants (such as Adam optimizer) are used to update the weights and biases. Appropriate hyperparameters such as learning rate, batch size, number of iterations, etc. are set during the training process, and appropriate validation and testing are performed to prevent overfitting. Deploy the trained neural network model to the actual control system. During the operation of the system, the ammonia escape value and other relevant parameters of the current level are collected in real time and input into the neural network model. The model calculates the compensation value of the ammonia injection amount based on the input data, and sends the compensation value to the control system to adjust the ammonia injection amount. The control system performs actual operations based on the adjusted ammonia injection amount and continues to monitor the ammonia escape value for the next round of feedback adjustment. Regularly evaluate the performance of the neural network model, and update and optimize the model based on new data or new requirements. Introduce new features or improve the model structure to improve prediction accuracy and robustness.

[0028] S7: Set up a catalyst layer timing module to calculate the usage time of each catalyst layer according to the time of flue gas delivery, and remind maintenance when the usage threshold is reached. Set up a catalyst layer timing module to calculate the usage time of each catalyst layer, and use this time as the state vector data of the catalyst layer. In the calculation of the neuron compensation system, this state vector data is used as an influencing factor and brought into the calculation.

[0029] The comprehensive control method for ammonia escape of high-concentration NOx flue gas denitrification sprays ammonia through an ammonia spraying system, cooperates with a catalyst layer for graded treatment, improves ammonia utilization, collects the flue gas temperature before and after each catalyst layer and behind the heat exchanger and the NOx concentration in the flue gas at the inlet and outlet of each denitrification section system, cooperates with an algorithm control system, and converts the ammonia spraying amount in combination with the flow rate before each stage of treatment, thereby performing real-time and accurate control of the ammonia spraying amount at each stage, eliminating the situation of excessive ammonia spraying, maximizing ammonia utilization, and accurately controlling ammonia by partitioning management at each stage. In addition, the present invention reserves monitoring space between each stage of the denitrification section system, identifies possible ammonia escape values, cooperates with a neuron compensation system, combines flue gas temperature and catalyst state data, calculates the compensation value of the ammonia spraying amount, and adjusts the ammonia spraying amount based on the compensation value, which is convenient for compensating for the floating value that may exist under ammonia control, making the regulation of ammonia more accurate and further reducing ammonia escape. At the same time, the present invention establishes a catalyst layer timing module to calculate the usage time of each catalyst layer, and uses the time as the state vector data of the catalyst layer as an influencing factor for ammonia control, making the calculation data more diversified and ensuring the normal operation of the catalyst layer.

[0030] The above shows and describes the basic principles, main features and advantages of the present invention. It should be understood by those skilled in the art that the present invention is not limited to the above embodiments. The above embodiments and descriptions are only for explaining the principles of the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A comprehensive control method for ammonia escape in high-concentration NOx flue gas denitrification, characterized in that: The following steps are involved: S1: Construct a multi-stage denitrification system built into the flue, each stage of the system includes an ammonia injection system, a catalyst layer and a heat exchanger at the rear; S2: Set temperature measuring points before and after each catalyst layer and behind the heat exchanger to monitor the flue gas temperature in real time; S3: A nitrogen oxide concentration monitoring device is installed at the inlet and outlet of each stage of the denitrification system to monitor the NOx concentration in the flue gas in real time; S4: Construct an algorithm control system to calculate the amount of ammonia injection based on the current detected flue gas NOx concentration and flue gas temperature combined with the flow rate before each stage of treatment; S5: A monitoring space is reserved between each stage of the denitrification system, and an ammonia monitoring device is built in to identify possible ammonia escape values; S6: Construct a neuron compensation system, bring the ammonia escape value of the current stage into the ammonia injection amount of the current stage, calculate the compensation value, and correct the ammonia injection amount; S7: Establish a catalyst layer timing module to calculate the usage time of each catalyst layer according to the flue gas delivery time, and remind maintenance when the usage threshold is reached.

2. The comprehensive control method for ammonia slip of high-concentration NOx flue gas denitrification according to claim 1 is characterized in that: In S1, the ammonia injection system is used to spray ammonia or urea into the flue gas, and the ammonia injection system includes an ammonia storage tank, an ammonia / air mixer, an ammonia injection grid and a nozzle. After the ammonia is fully mixed with the air through the ammonia / air mixer, it is evenly sprayed into the flue gas through the ammonia injection grid and fully mixed with the flue gas; the catalyst layer is filled with an SCR catalyst, which is used to catalyze the selective reduction reaction of ammonia and NOx in the flue gas to generate nitrogen and water; the heat exchanger is located behind the catalyst layer, which is used to recover the waste heat in the flue gas and adjust the flue gas temperature to parameters suitable for subsequent treatment.

3. The comprehensive control method for ammonia slip of high-concentration NOx flue gas denitrification according to claim 1 is characterized in that: In S2, temperature measuring points are set before and after each stage of the catalyst layer and behind the heat exchanger to monitor the temperature of the flue gas before and after treatment, thereby controlling the heat exchanger to adjust the temperature. After the temperature adjustment, the current flue gas temperature is monitored. Before entering the next stage of the denitrification system, the current flue gas temperature is monitored again. The current flue gas temperature is compared with the temperature of the previous stage of the heat exchanger after temperature adjustment, the difference is calculated, and the adjustment value is converted to adjust the temperature adjustment parameters of each stage of the heat exchanger.

4. The comprehensive control method for ammonia slip of high-concentration NOx flue gas denitrification according to claim 1 is characterized in that: In S3, a nitrogen oxide concentration monitoring device is set at the inlet and outlet of each stage of the denitrification system, and an air volume sensor is arranged in the nitrogen oxide concentration monitoring device at the inlet of each stage of the denitrification system to monitor the flue gas flow entering each stage of the denitrification system while detecting the NOx concentration in the flue gas in real time.

5. The comprehensive control method for ammonia slip of high-concentration NOx flue gas denitrification according to claim 1 is characterized by: The S4 comprises the following steps: Build an algorithm control system to dynamically adjust the amount of ammonia injection based on flue gas NOx concentration, flue gas temperature and flow rate; Input parameters are flue gas NOx concentration, flue gas temperature, and flue gas flow rate; output parameters are ammonia injection amount, expressed in molar amount or volume flow rate of NH3; The calculation is based on the chemical reaction equation and NOx reduction efficiency. First, the required NOx molar amount is calculated based on the current NOx concentration and flow rate, and the required NH3 molar amount is calculated based on the stoichiometric ratio; The ammonia injection amount is adjusted to compensate for the temperature value, and the feedback of the NOx concentration at the outlet of the denitrification system is introduced. The ammonia injection amount is calculated according to the optimal treatment NOx concentration of the current stage through the PID proportional-integral-differential controller.

6. The comprehensive control method for ammonia slip of high-concentration NOx flue gas denitrification according to claim 5 is characterized by: When the NOx concentration is too high, increase the amount of ammonia injection; when the NOx concentration decreases, reduce the amount of ammonia injection. Combined with the load fluctuation amplitude and the fluctuation amplitude of the NOx concentration at the inlet of the denitrification system, dynamically adjust the amount of ammonia injection to minimize ammonia escape and maintain denitrification efficiency as the benchmark for dynamic control.

7. The comprehensive control method for ammonia slip of high-concentration NOx flue gas denitrification according to claim 1 is characterized by: In S5, an openable sealed door is arranged on the monitoring space, and an ammonia monitoring device is arranged on the inner side of the door to detect ammonia and its concentration that may exist in the flue gas after each stage of denitration system processing.

8. The comprehensive control method for ammonia slip of high-concentration NOx flue gas denitrification according to claim 1, characterized in that: The S6 comprises the following steps: Collect historical data of ammonia monitoring devices after each stage of denitrification system, including ammonia escape values ​​and corresponding ammonia injection amounts under different operating conditions, as well as flue gas temperature and catalyst status data; Using the collected historical data to train the neural network, during the training process, the weights and biases of the neural network are adjusted by minimizing the error between the predicted compensation value and the actual compensation value; Use gradient descent or Adam optimizer to update weights and biases; Deploy the trained neural network model to the actual control system, collect the ammonia slip value and other relevant parameters of the current level in real time, and input them into the neural network model; The compensation value of the ammonia injection amount is calculated according to the input data, and the ammonia injection amount is adjusted based on the compensation value, and then the ammonia slip value is continuously monitored for the next round of feedback adjustment.

9. A comprehensive control method for ammonia slip in high-concentration NOx flue gas denitrification according to claim 8, characterized in that: After data collection, the data was cleaned and preprocessed to remove noise and outliers and normalize them.

10. The comprehensive control method for ammonia slip of high-concentration NOx flue gas denitrification according to claim 8, characterized in that: A catalyst layer timing module is established to calculate the usage time of each catalyst layer, and the time is used as the state vector data of the catalyst layer. In the calculation of the neuron compensation system, the state vector data is used as an influencing factor and brought into the calculation.

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