Denitration automatic adjusting method and system based on multi-parameter coupling optimization

Abstract

The invention belongs to the technical field of flue gas denitration, and relates to a denitration automatic adjusting method and system based on multi-parameter coupling optimization, and the method comprises the following steps: S1, collecting current operation data in real time, and preprocessing the current operation data; s2, constructing a multi-parameter coupling relation model to obtain the current predicted denitration efficiency and the current predicted ammonia consumption; s3, obtaining the currently predicted optimal ammonia water injection amount, ammonia water injection temperature and ammonia water injection angle; s4, ammonia water injection amount adjustment, ammonia water injection temperature adjustment and ammonia water injection angle adjustment are automatically carried out on the denitration equipment; and S5, monitoring the operation data after denitration treatment in real time through a feedback monitoring module, and feeding back the operation data after denitration treatment to the step S2 for preprocessing. The problems that an existing denitration adjusting strategy is single and not optimized enough and the adjusting response is slow are solved by adjusting the ammonia water spraying amount, the ammonia water spraying temperature and the ammonia water spraying angle.

Description

Technical Field

[0001] The present invention relates to the technical field of flue gas denitrification, and particularly discloses a denitrification automatic adjustment method and system based on multi-parameter coupling optimization. Background Art

[0002] With increasingly stringent environmental protection requirements, the emission control of nitrogen oxides (NOx) has become a key link in industrial flue gas treatment. Denitrification technologies such as selective catalytic reduction (SCR) and selective non-catalytic reduction (SNCR) are widely used. However, the current automatic denitrification control technology generally has the following problems: First, it is only adjusted based on a single NOx emission concentration or ammonia escape rate, which makes the control strategy single and difficult to balance the denitrification efficiency and ammonia consumption, resulting in high denitrification costs; second, the control response to changes in operating conditions is slow. In the case of boiler load fluctuations, temperature window changes, and catalyst activity attenuation, the denitrification equipment parameter data cannot be adjusted in time, affecting the stability of denitrification; third, there is a lack of in-depth analysis and effective utilization of the coupling relationship between multiple parameters in the denitrification process, resulting in a less than optimized control strategy. Therefore, there is an urgent need for a denitrification technology that can comprehensively consider multiple factors and achieve precise automatic adjustment. Summary of the Invention

[0003] The purpose of the present invention is to provide a denitrification automatic adjustment method and system based on multi-parameter coupling optimization to solve the problems of single and insufficient optimization of existing denitrification adjustment strategies and slow adjustment response.

[0004] The specific scheme of the present invention is as follows:

[0005] A denitrification automatic adjustment method based on multi-parameter coupling optimization, comprising:

[0006] Step S1: collecting current operation data of the denitrification process in real time and preprocessing the current operation data;

[0007] Step S2: Based on the pre-processed current operating data and the acquired historical operating data, a multi-parameter coupling relationship model is constructed using a machine learning algorithm, and denitrification prediction is performed on the current operating data using the multi-parameter coupling relationship model to obtain a current predicted denitrification efficiency and a current predicted ammonia consumption;

[0008] Step S3: Based on the current predicted denitration efficiency and the current predicted ammonia consumption, as well as the preset denitration efficiency target and ammonia consumption constraint, an optimization algorithm and a multi-parameter coupling relationship model are used to perform optimization processing to obtain the currently predicted optimal ammonia injection amount, ammonia injection temperature, and ammonia injection angle;

[0009] Step S4, automatically adjusting the ammonia injection amount, ammonia injection temperature, and ammonia injection angle of the denitrification equipment based on the currently predicted optimal ammonia injection amount, ammonia injection temperature, and ammonia injection angle;

[0010] Step S5: Denitrification is performed according to the automatically adjusted ammonia injection amount, ammonia injection temperature, and ammonia injection angle. The operation data after the denitrification is monitored in real time through the feedback monitoring module, and the operation data after the denitrification is fed back to step S2 for preprocessing.

[0011] In some embodiments, the ammonia consumption constraint is:

[0012] M min <M<M max ,

[0013] Among them, M is the ammonia consumption, M min is the minimum ammonia consumption, M max It is the maximum ammonia consumption.

[0014] In some embodiments, the optimization process includes optimizing the ammonia injection temperature. The calculation formula for optimizing the ammonia injection temperature is:

[0015] T_{set}=f(T_{flue gas},η_{catalyst})+ΔT_{compensation},

[0016] Wherein, T_{set} is the set value of the ammonia injection temperature; f(T_{flue gas}, η_{catalyst}) is the current flue gas temperature; ΔT_{compensation} is the ammonia injection temperature compensation amount calculated based on the catalyst activity decay rate. For every 10% decrease in the catalyst activity decay rate, the ammonia injection temperature compensation amount is compensated by +5°C.

[0017] In some embodiments, the optimization process further includes optimizing the ammonia injection angle, and the ammonia injection angle optimization includes generating an ammonia injection angle adjustment degree based on the acquired flue gas flow rate change rate, NOx concentration distribution standard deviation, and ammonia slip excess value.

[0018] In some embodiments, generating an ammonia water injection angle adjustment degree based on the obtained flue gas flow rate change rate, NOx concentration distribution standard deviation, and ammonia slip excess value includes:

[0019] When the flue gas flow rate change rate is greater than +10%, the NOx distribution standard deviation is greater than 2.5 mg / m 3 When the ammonia slip exceeds the standard value of more than 3ppm, the ammonia injection angle adjustment is +10°;

[0020] When the flue gas flow rate change rate is greater than +10%, the NOx distribution standard deviation is less than or equal to 2.5 mg / m 3 When the ammonia slip exceeds the standard value of more than 3ppm, the ammonia injection angle adjustment is 8°;

[0021] When the flue gas flow rate change rate is greater than +10%, the NOx distribution standard deviation is less than or equal to 2.5 mg / m3 When the ammonia slip exceeds the standard value of 3ppm or less, the ammonia injection angle adjustment is 6°;

[0022] When the flue gas flow rate change rate is less than -10%, the NOx distribution standard deviation is greater than 2.5 mg / m 3 When the ammonia slip exceeds the standard value of more than 3ppm, the ammonia injection angle adjustment is -8°;

[0023] When the flue gas flow rate change rate is less than -10%, the NOx distribution standard deviation is less than or equal to 2.5 mg / m 3 When the ammonia slip exceeds the standard value of more than 3ppm, the ammonia injection angle adjustment is -6°;

[0024] When the flue gas flow rate change rate is less than -10%, the NOx distribution standard deviation is less than or equal to 2.5 mg / m 3 When the ammonia slip exceeds the standard value of 3ppm or less, the ammonia injection angle adjustment is -4°;

[0025] When the flue gas flow rate change rate is less than or equal to +10% and greater than or equal to -10%, the NOx distribution standard deviation is greater than 2.5 mg / m 3 When the ammonia slip exceeds the standard value of more than 3ppm, the ammonia injection angle adjustment is 4°;

[0026] When the flue gas flow rate change rate is less than or equal to +10% and greater than or equal to -10%, the NOx distribution standard deviation is less than or equal to 2.5 mg / m 3 When the ammonia slip exceeds the standard value of more than 3ppm, the ammonia injection angle adjustment is 2°;

[0027] When the flue gas flow rate change rate is less than or equal to +10% and greater than or equal to -10%, the NOx distribution standard deviation is less than or equal to 2.5 mg / m 3 When the ammonia slip exceeds the standard value less than or equal to 3ppm, the ammonia injection angle adjustment degree is 0°.

[0028] In some embodiments, adjusting the ammonia injection amount includes controlling the flow rate of a metering pump through a frequency converter so that the ammonia injection amount matches the change in NOx concentration in the flue gas in real time.

[0029] In some embodiments, regulating the ammonia injection temperature includes:

[0030] Start the heating device and adjust the electric heater power or steam heat exchange valve opening through the PID controller;

[0031] Or perform feed-forward compensation on the boiler load according to the set temperature-load linkage curve.

[0032] In some embodiments, adjusting the ammonia injection angle includes:

[0033] The deflection angle of the spray gun is driven by a servo motor;

[0034] Or adopt a multi-gun partitioned injection strategy and dynamically adjust the angle of each gun based on the computational fluid dynamics (CFD) simulation results.

[0035] In some embodiments, preprocessing includes data filtering, outlier removal, and normalization.

[0036] The present invention also relates to a denitration automatic adjustment system based on multi-parameter coupling optimization, which is used in the above-mentioned denitration automatic adjustment method based on multi-parameter coupling optimization, comprising:

[0037] Data acquisition module, used to collect current operation data of denitrification treatment in real time;

[0038] A data processing module is used to pre-process the collected current operation data;

[0039] The data analysis module is used to construct a multi-parameter coupling relationship model based on the pre-processed current operating data and the acquired historical operating data through a machine learning algorithm, and perform denitrification prediction on the current operating data using the multi-parameter coupling relationship model to obtain the current predicted denitrification efficiency and the current predicted ammonia consumption;

[0040] The optimization decision module is used to obtain the currently predicted optimal ammonia injection amount, ammonia injection temperature, and ammonia injection angle through optimization processing using an optimization algorithm and a multi-parameter coupling relationship model based on the currently predicted denitrification efficiency and the currently predicted ammonia consumption, as well as the preset denitrification efficiency target and ammonia consumption constraint conditions;

[0041] a control execution module for automatically adjusting the ammonia injection amount, ammonia injection temperature, and ammonia injection angle of the denitrification equipment based on the currently predicted optimal ammonia injection amount, ammonia injection temperature, and ammonia injection angle, and performing denitrification processing according to the automatically adjusted ammonia injection amount, ammonia injection temperature, and ammonia injection angle;

[0042] The feedback monitoring module is used to monitor the operating data after denitrification treatment in real time, and feed back the operating data after denitrification treatment to the data processing module for preprocessing.

[0043] Compared with the prior art, the present invention has the following advantages and beneficial effects:

[0044] 1. The present invention performs denitration prediction based on current operating data through a multi-parameter coupling relationship model to obtain the current predicted denitration efficiency and the current predicted ammonia consumption. Based on the current predicted denitration efficiency and the current predicted ammonia consumption, as well as the preset denitration efficiency target and ammonia consumption restriction condition, the optimization algorithm and the multi-parameter coupling relationship model are used for optimization processing to obtain the currently predicted optimal ammonia injection amount, ammonia injection temperature and ammonia injection angle. Based on the currently predicted optimal ammonia injection amount, ammonia injection temperature and ammonia injection angle, the denitration equipment is automatically adjusted for ammonia injection amount, ammonia injection temperature and ammonia injection angle. Denitration is performed according to the automatically adjusted ammonia injection amount, ammonia injection temperature and ammonia injection angle. The operating data after the denitration treatment is monitored in real time through a feedback monitoring module, and the operating data after the denitration treatment is fed back to the data processing module for preprocessing to form a closed-loop control. The adjustment strategy is optimized from multiple aspects, the parameter data of the denitration equipment is adjusted in time, the adjustment response rate speed is improved, the denitration efficiency and ammonia consumption are balanced, and the denitration cost is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] Figure 1 The present invention is a flowchart of a method for automatic denitrification adjustment based on multi-parameter coupling optimization in an embodiment of the present invention.

[0046] Figure 2 This is a block diagram of a denitrification automatic adjustment system based on multi-parameter coupling optimization in an embodiment of the present invention. DETAILED DESCRIPTION

[0047] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of 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. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0048] A denitrification automatic adjustment method based on multi-parameter coupling optimization, such as Figure 1 As shown, the following steps are included:

[0049] S1. Real-time collection of parameter data of various denitrification equipment in denitrification treatment to obtain current operation data;

[0050] The current operating data includes parameters such as flue gas flow, flue gas temperature, initial NOx concentration, ammonia escape rate, catalyst activity and boiler load.

[0051] The flue gas flow rate is measured by a thermal gas mass flowmeter, the flue gas temperature is measured by a thermocouple, the initial NOx concentration is detected by a NOx concentration analyzer, the ammonia escape rate is monitored by an ammonia escape online monitor, the catalyst activity is obtained by a catalyst activity detection device, and the boiler load is obtained by communicating with the boiler control system.

[0052] S2. Preprocessing the collected current operation data;

[0053] Preprocessing includes data filtering, outlier removal, normalization, etc.

[0054] Data filtering uses a variable-step-size LMS adaptive filtering algorithm to filter initial NOx concentration, flue gas volume, and flue gas temperature. This removes noise and interference, ensuring a higher signal-to-noise ratio for the identification of each parameter in the denitrification process, improving data accuracy and thus enhancing the stability and overall effectiveness of the denitrification process. By adjusting the step size to balance convergence speed and stability, the filtering effect is optimal when the cutoff frequency is 0.9.

[0055] Outlier removal refers to the use of algorithms to identify and remove outliers in various parameter data, such as NOx concentration, flue gas temperature, ammonia escape rate, etc., to ensure accurate and reliable denitrification.

[0056] Methods for removing outliers include standard deviation thresholding, boxplots, cluster analysis, and intelligent supervised filtering. The standard deviation thresholding method can quickly identify outliers that deviate from the mean by ±3σ; the boxplot method can resist interference from extreme values ​​based on the interquartile range; cluster analysis can automatically separate outlier clusters and adapt to nonlinear systems; and the intelligent supervised filtering method can integrate the differential autoregressive moving average (CARIMA) model with parameter convergence checks to prevent misjudgments.

[0057] Normalization involves mathematically transforming parameter data of varying dimensions and magnitudes into a specific standard range. Denitrification requires processing multiple parameter data of varying dimensions simultaneously. Min-Max scaling or Z-score normalization can be used to map parameters such as flue gas flow, flue gas temperature, NOx concentration, ammonia escape rate, catalyst activity, and boiler load to a uniform interval, such as [0,1] or [-1,1], to avoid data bias due to dimensional differences. Furthermore, denitrification requires integrating parameter data from multiple sources. Normalization can accelerate convergence, reduce the risk of gradient vanishing or explosion, and improve response speed and stability.

[0058] By preprocessing the collected current operation data, the accuracy and reliability of the data are improved, providing a guarantee for subsequent data analysis.

[0059] S3. Based on the pre-processed current operating data and the acquired historical operating data, a multi-parameter coupling relationship model is constructed using a machine learning algorithm, and denitrification prediction is performed on the current operating data using the multi-parameter coupling relationship model to obtain a current prediction result;

[0060] The current prediction results include the current predicted denitrification efficiency and the current predicted ammonia consumption.

[0061] Machine learning algorithms include neural networks and support vector machines, among others.

[0062] Constructing a multi-parameter coupling relationship model includes: using pre-processed current operation data and historical operation data to train a neural network or a support vector machine.

[0063] The multi-parameter coupling relationship model is used to analyze the mutual influence and action rules between various parameter data in the operation data.

[0064] S4. Based on the current prediction results and the preset denitrification efficiency target and ammonia consumption limit conditions, the current predicted optimal denitrification index data is obtained through optimization processing using an optimization algorithm and a multi-parameter coupling relationship model;

[0065] The ammonia consumption limit conditions are:

[0066] M min <M<M max ,

[0067] Among them, M is the ammonia consumption, M min is the minimum ammonia consumption, M max It is the maximum ammonia consumption.

[0068] Optimization algorithms include genetic algorithms and particle swarm optimization. Genetic algorithms are heuristic search algorithms that simulate the principles of natural selection and genetics, optimizing solutions through selection, crossover, and mutation. Particle swarm optimization is an optimization tool based on swarm intelligence that mimics the social behavior of flocks of birds or schools of fish to find optimal solutions. Each particle represents a candidate solution in the problem space and adjusts its position by tracking its own best historical position and the best position of the entire swarm.

[0069] The currently predicted optimal denitrification index data include the currently predicted optimal ammonia injection amount, ammonia injection temperature and ammonia injection angle.

[0070] The amount of ammonia injection directly affects the denitrification efficiency. Too much ammonia injection may cause ammonia escape, while too little ammonia injection will lead to poor denitrification effect.

[0071] The ammonia injection temperature is used to ensure catalyst activity and suppress by-product formation. The denitration reaction must occur within a specific temperature window, typically between 300°C and 400°C. When the ammonia injection temperature is below the lower limit, catalyst activity decreases, reducing the NOx reduction rate. When the ammonia injection temperature is above the upper limit, catalyst sintering and deactivation or ammonia decomposition can occur. These changes in catalyst activity affect denitration efficiency and ammonia escape rates. For example, in selective catalytic reduction (SCR), when the ammonia injection temperature is less than 300°C, denitration efficiency drops by more than 30%, and the risk of ammonia escape increases threefold. When the ammonia injection temperature exceeds 400°C, the rate of SO2 oxidation to SO3 accelerates, reacting with excess ammonia to form corrosive ammonium bisulfate. When the ammonia injection temperature is less than 300°C, ammonium bisulfate (ABS) is deposited in the low-temperature section of the air preheater, causing damage.

[0072] The ammonia injection angle directly affects the distribution of the reducing agent and the atomization and mixing effect. It also influences the uniformity of the mixing of ammonia and flue gas. For example, in cement selective non-catalytic reduction (SNCR) systems, adjusting the ammonia injection angle downward by 15°–30° can extend the reducing agent's residence time in the high-temperature zone to greater than or equal to 0.5 seconds, improving denitrification efficiency by 15%. In selective catalytic reduction (SCR) systems, a multi-lance zone layout and optimized ammonia injection angle based on computational fluid dynamics (CFD) simulation results can reduce NOx concentration unevenness to less than 15%, preventing localized ammonia excess and leading to ammonia escape, thereby reducing the ammonia escape rate. Matching the ammonia injection angle to the airflow direction, such as injecting ammonia in the opposite direction, can increase turbulence intensity, promote ammonia droplet breakup, shorten reaction time, and improve denitrification efficiency.

[0073] The optimization rule for the ammonia injection amount is that the ammonia injection amount always matches the change of NOx concentration in the flue gas.

[0074] The optimization formula for ammonia injection temperature is:

[0075] T_{set}=f(T_{flue gas},η_{catalyst})+ΔT_{compensation},

[0076] Wherein, T_{set} is the set value of the ammonia injection temperature; f(T_{flue gas}, η_{catalyst}) is the current flue gas temperature; ΔT_{compensation} is the ammonia injection temperature compensation amount calculated based on the catalyst activity decay rate. For every 10% decrease in the catalyst activity decay rate, the ammonia injection temperature compensation amount is compensated by +5°C.

[0077] The optimization rule for the ammonia injection angle is to generate the ammonia injection angle adjustment degree based on the obtained flue gas flow rate change rate, NOx concentration distribution unevenness (i.e., NOx concentration distribution standard deviation), and ammonia slip excess value. Specifically, it is:

[0078] When the flue gas flow rate change rate is greater than +10%, the NOx distribution standard deviation is greater than 2.5 mg / m 3 When the ammonia slip exceeds the standard value of more than 3ppm, the ammonia injection angle adjustment is +10°;

[0079] When the flue gas flow rate change rate is greater than +10%, the NOx distribution standard deviation is less than or equal to 2.5 mg / m 3 When the ammonia slip exceeds the standard value of more than 3ppm, the ammonia injection angle adjustment is 8°;

[0080] When the flue gas flow rate change rate is greater than +10%, the NOx distribution standard deviation is less than or equal to 2.5 mg / m 3 When the ammonia slip exceeds the standard value of 3ppm or less, the ammonia injection angle adjustment is 6°;

[0081] When the flue gas flow rate change rate is less than -10%, the NOx distribution standard deviation is greater than 2.5 mg / m 3 When the ammonia slip exceeds the standard value of more than 3ppm, the ammonia injection angle adjustment is -8°;

[0082] When the flue gas flow rate change rate is less than -10%, the NOx distribution standard deviation is less than or equal to 2.5 mg / m 3 When the ammonia slip exceeds the standard value of more than 3ppm, the ammonia injection angle adjustment is -6°;

[0083] When the flue gas flow rate change rate is less than -10%, the NOx distribution standard deviation is less than or equal to 2.5 mg / m 3 When the ammonia slip exceeds the standard value of 3ppm or less, the ammonia injection angle adjustment is -4°;

[0084] When the flue gas flow rate change rate is less than or equal to +10% and greater than or equal to -10%, the NOx distribution standard deviation is greater than 2.5 mg / m 3 When the ammonia slip exceeds the standard value of more than 3ppm, the ammonia injection angle adjustment is 4°;

[0085] When the flue gas flow rate change rate is less than or equal to +10% and greater than or equal to -10%, the NOx distribution standard deviation is less than or equal to 2.5 mg / m 3 When the ammonia slip exceeds the standard value of more than 3ppm, the ammonia injection angle adjustment is 2°;

[0086] When the flue gas flow rate change rate is less than or equal to +10% and greater than or equal to -10%, the NOx distribution standard deviation is less than or equal to 2.5 mg / m 3 When the ammonia slip exceeds the standard value less than or equal to 3ppm, the ammonia injection angle adjustment degree is 0°.

[0087] S5. Automatically adjust denitration equipment parameter data based on the currently predicted optimal denitration index data;

[0088] Based on the currently predicted optimal ammonia injection amount, ammonia injection temperature and ammonia injection angle, the denitrification equipment is automatically adjusted for ammonia injection amount, ammonia injection temperature and ammonia injection angle.

[0089] The ammonia injection amount adjustment includes controlling the flow of the metering pump through the frequency converter so that the ammonia injection amount matches the change of NOx concentration in the flue gas in real time.

[0090] Ammonia injection temperature regulation includes: starting the heating device, adjusting the electric heater power or steam heat exchange valve opening through the PID controller; or performing feedforward compensation on the boiler load 20 seconds in advance according to the set temperature-load linkage curve.

[0091] The conditions for adjusting the ammonia injection temperature include: when the flue gas temperature is lower than the temperature window of 300℃-400℃ where the catalyst activity is optimal, the heating device needs to be started, and the electric heater power or the steam heat exchange valve opening is adjusted through the PID controller to maintain the ammonia injection temperature within the temperature window; when the catalyst activity decays, the ammonia injection temperature compensation amount needs to be increased to maintain the ammonia injection temperature within the temperature window; when the boiler load drops sharply, causing the flue gas temperature to drop, the boiler load needs to be feed-forward compensated 20 seconds in advance according to the set temperature-load linkage curve to dynamically increase the ammonia injection temperature.

[0092] The ammonia injection angle adjustment includes: driving the spray gun deflection angle through a servo motor so that the ammonia injection angle adjustment range is 0° to 30°; or adopting a multi-spray gun partition injection strategy to dynamically adjust the angle of each spray gun based on the computational fluid dynamics (CFD) simulation results.

[0093] The conditions for adjusting the ammonia injection angle include: the flue gas flow rate change rate exceeds ±10%; the NOx concentration distribution unevenness is greater than 15%, that is, the NOx distribution standard deviation is greater than 2.5 mg / m 3 ; The ammonia escape exceeds the standard value by more than 3ppm.

[0094] S6. Perform denitration according to the automatically adjusted denitration equipment parameter data, monitor the operation data after the denitration in real time through the feedback monitoring module, and feed back the operation data after the denitration to step S2 for preprocessing.

[0095] The operating data after denitrification treatment includes NOx emission concentration and ammonia escape rate, etc. The operating data after denitrification treatment is fed back to step S2 for pre-processing through the feedback monitoring module, forming a closed-loop control so that the denitrification equipment parameter data can be adjusted in time to ensure that the denitrification treatment is always in the best operating state.

[0096] The present invention performs denitrification prediction based on current operating data through a constructed multi-parameter coupling relationship model to obtain the current predicted denitrification efficiency and the current predicted ammonia consumption. Based on the current predicted denitrification efficiency and the current predicted ammonia consumption, as well as preset denitrification efficiency targets and ammonia consumption constraints, optimization processing is performed through an optimization algorithm and a multi-parameter coupling relationship model to obtain the currently predicted optimal ammonia injection amount, ammonia injection temperature and ammonia injection angle. Based on the currently predicted optimal ammonia injection amount, ammonia injection temperature and ammonia injection angle, the ammonia injection amount, ammonia injection temperature and ammonia injection angle of the denitrification equipment are automatically adjusted. Denitrification is performed according to the automatically adjusted ammonia injection amount, ammonia injection temperature and ammonia injection angle. The operating data after the denitrification treatment is monitored in real time through a feedback monitoring module, and the operating data after the denitrification treatment is fed back to a data processing module for preprocessing to form a closed-loop control. The adjustment strategy is optimized from multiple aspects, the parameter data of the denitrification equipment is adjusted in time, the adjustment response rate speed is improved, the denitrification efficiency and ammonia consumption are balanced, and the denitrification cost is reduced.

[0097] The present invention also relates to a denitrification automatic adjustment system based on multi-parameter coupling optimization, such as Figure 2 As shown, including:

[0098] The data acquisition module is used to collect parameter data of various denitrification equipment in the denitrification process in real time to obtain current operation data.

[0099] Among them, the current operating data includes parameter data such as flue gas flow, flue gas temperature, initial NOx concentration, ammonia escape rate, catalyst activity and boiler load; the data acquisition module includes a variety of sensors, for example, the flue gas flow is measured by a thermal gas mass flowmeter, the flue gas temperature is measured by a thermocouple, the initial NOx concentration is detected by a NOx concentration analyzer, the ammonia escape rate is monitored by an ammonia escape online monitor, and the catalyst activity is obtained by a catalyst activity detection device.

[0100] The data processing module is used to pre-process the collected current operation data.

[0101] Among them, preprocessing includes data filtering, outlier removal, normalization, etc.

[0102] The data analysis module is used to construct a multi-parameter coupling relationship model based on the pre-processed current operating data and the acquired historical operating data through a machine learning algorithm, and to perform denitrification prediction on the current operating data through the multi-parameter coupling relationship model to obtain the current prediction result.

[0103] The multi-parameter coupling relationship model is obtained by training a neural network or support vector machine using pre-processed current operation data and historical operation data. The current prediction results include the current predicted denitrification efficiency and the current predicted ammonia consumption.

[0104] The optimization decision module is used to obtain the current predicted optimal denitrification index data through optimization processing through optimization algorithm and multi-parameter coupling relationship model based on the current prediction results and the preset denitrification efficiency target and ammonia consumption limit conditions.

[0105] Among them, the currently predicted optimal denitrification index data includes the currently predicted optimal ammonia injection amount, ammonia injection temperature and ammonia injection angle.

[0106] The control execution module is used to automatically adjust the denitration equipment parameter data based on the current predicted optimal denitration index data, and perform denitration processing according to the automatically adjusted denitration equipment parameter data.

[0107] Among them, the automatic adjustment of the denitrification equipment parameter data includes ammonia injection amount adjustment, ammonia injection temperature adjustment and ammonia injection angle adjustment.

[0108] The control execution module also includes a linkage execution unit, which includes: synchronous and coordinated adjustment of the ammonia injection temperature and the ammonia injection angle; when the boiler load suddenly changes, synchronously starting the feedforward compensation of the boiler load and the adjustment of the ammonia injection angle 20 seconds in advance according to the set temperature-load linkage curve; when the ammonia escape exceeds the standard, the ammonia injection amount is linked to be reduced and the ammonia injection angle is optimized.

[0109] The feedback monitoring module is used to monitor the operating data after denitrification treatment in real time, and feed back the operating data after denitrification treatment to the data processing module for preprocessing.

[0110] The operational data after denitrification treatment includes NOx emission concentration and ammonia escape rate, etc. The operational data after denitrification treatment is fed back to the data processing module through the feedback monitoring module for pre-processing, forming a closed-loop control.

[0111] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A denitrification automatic adjustment method based on multi-parameter coupling optimization, characterized in that: include: Step S1: collecting current operation data of the denitrification process in real time and preprocessing the current operation data; Step S2: Based on the pre-processed current operating data and the acquired historical operating data, a multi-parameter coupling relationship model is constructed using a machine learning algorithm, and denitrification prediction is performed on the current operating data using the multi-parameter coupling relationship model to obtain a current predicted denitrification efficiency and a current predicted ammonia consumption; Step S3: Based on the current predicted denitration efficiency and the current predicted ammonia consumption, as well as the preset denitration efficiency target and ammonia consumption constraint, an optimization algorithm and a multi-parameter coupling relationship model are used to perform optimization processing to obtain the currently predicted optimal ammonia injection amount, ammonia injection temperature, and ammonia injection angle; Step S4, automatically adjusting the ammonia injection amount, ammonia injection temperature, and ammonia injection angle of the denitrification equipment based on the currently predicted optimal ammonia injection amount, ammonia injection temperature, and ammonia injection angle; Step S5: Denitrification is performed according to the automatically adjusted ammonia injection amount, ammonia injection temperature, and ammonia injection angle. The operation data after the denitrification is monitored in real time through the feedback monitoring module, and the operation data after the denitrification is fed back to step S2 for preprocessing.

2. The denitrification automatic adjustment method based on multi-parameter coupling optimization according to claim 1, characterized in that: The ammonia consumption limiting conditions are: M min <M<M max , Among them, M is the ammonia consumption, M min is the minimum ammonia consumption, M max It is the maximum ammonia consumption.

3. The denitrification automatic adjustment method based on multi-parameter coupling optimization according to claim 1, characterized in that: The optimization process includes optimizing the ammonia water injection temperature. The calculation formula for optimizing the ammonia water injection temperature is: T_{set}=f(T_{flue gas},η_{catalyst})+ΔT_{compensation}, Wherein, T_{set} is the set value of the ammonia injection temperature; f(T_{flue gas}, η_{catalyst}) is the current flue gas temperature; ΔT_{compensation} is the ammonia injection temperature compensation amount calculated based on the catalyst activity decay rate. For every 10% decrease in the catalyst activity decay rate, the ammonia injection temperature compensation amount is compensated by +5°C.

4. The denitrification automatic adjustment method based on multi-parameter coupling optimization according to claim 1, characterized in that: The optimization process also includes optimizing the ammonia injection angle, and the optimization of the ammonia injection angle includes generating an ammonia injection angle adjustment degree based on the acquired flue gas flow rate change rate, NOx concentration distribution standard deviation and ammonia slip excess value.

5. The denitrification automatic adjustment method based on multi-parameter coupling optimization according to claim 4 is characterized in that: The generating of the ammonia water injection angle adjustment degree based on the obtained flue gas flow rate change rate, NOx concentration distribution standard deviation and ammonia slip excess value includes: When the flue gas flow rate change rate is greater than +10%, the NOx distribution standard deviation is greater than 2.5 mg / m 3 When the ammonia slip exceeds the standard value of more than 3ppm, the ammonia injection angle adjustment is +10°; When the flue gas flow rate change rate is greater than +10%, the NOx distribution standard deviation is less than or equal to 2.5 mg / m 3 When the ammonia slip exceeds the standard value of more than 3ppm, the ammonia injection angle adjustment is 8°; When the flue gas flow rate change rate is greater than +10%, the NOx distribution standard deviation is less than or equal to 2.5 mg / m 3 When the ammonia slip exceeds the standard value of 3ppm or less, the ammonia injection angle adjustment is 6°; When the flue gas flow rate change rate is less than -10%, the NOx distribution standard deviation is greater than 2.5 mg / m 3 When the ammonia slip exceeds the standard value of more than 3ppm, the ammonia injection angle adjustment is -8°; When the flue gas flow rate change rate is less than -10%, the NOx distribution standard deviation is less than or equal to 2.5 mg / m 3 When the ammonia slip exceeds the standard value of more than 3ppm, the ammonia injection angle adjustment is -6°; When the flue gas flow rate change rate is less than -10%, the NOx distribution standard deviation is less than or equal to 2.5 mg / m 3 When the ammonia slip exceeds the standard value of 3ppm or less, the ammonia injection angle adjustment is -4°; When the flue gas flow rate change rate is less than or equal to +10% and greater than or equal to -10%, the NOx distribution standard deviation is greater than 2.5 mg / m 3 When the ammonia slip exceeds the standard value of more than 3ppm, the ammonia injection angle adjustment is 4°; When the flue gas flow rate change rate is less than or equal to +10% and greater than or equal to -10%, the NOx distribution standard deviation is less than or equal to 2.5 mg / m 3 When the ammonia slip exceeds the standard value of more than 3ppm, the ammonia injection angle adjustment is 2°; When the flue gas flow rate change rate is less than or equal to +10% and greater than or equal to -10%, the NOx distribution standard deviation is less than or equal to 2.5 mg / m 3 When the ammonia slip exceeds the standard value less than or equal to 3ppm, the ammonia injection angle adjustment degree is 0°.

6. The denitrification automatic adjustment method based on multi-parameter coupling optimization according to claim 1, characterized in that: The ammonia water injection amount adjustment includes controlling the flow rate of the metering pump through a frequency converter so that the ammonia water injection amount matches the change of NOx concentration in the flue gas in real time.

7. The denitrification automatic adjustment method based on multi-parameter coupling optimization according to claim 1, characterized in that: The ammonia water injection temperature regulation includes: Start the heating device and adjust the electric heater power or steam heat exchange valve opening through the PID controller; Or perform feed-forward compensation on the boiler load according to the set temperature-load linkage curve.

8. The denitrification automatic adjustment method based on multi-parameter coupling optimization according to claim 1, characterized in that: The ammonia water injection angle adjustment includes: The deflection angle of the spray gun is driven by a servo motor; Or adopt a multi-gun partitioned injection strategy and dynamically adjust the angle of each gun based on the computational fluid dynamics (CFD) simulation results.

9. The denitrification automatic adjustment method based on multi-parameter coupling optimization according to claim 1, characterized in that: The preprocessing includes data filtering, outlier removal, and normalization.

10. A denitrification automatic adjustment system based on multi-parameter coupling optimization, characterized in that: A denitrification automatic adjustment method based on multi-parameter coupling optimization for use in any one of claims 1 to 9, comprising: Data acquisition module, used to collect current operation data of denitrification treatment in real time; A data processing module is used to pre-process the collected current operation data; The data analysis module is used to construct a multi-parameter coupling relationship model based on the pre-processed current operating data and the acquired historical operating data through a machine learning algorithm, and perform denitrification prediction on the current operating data using the multi-parameter coupling relationship model to obtain the current predicted denitrification efficiency and the current predicted ammonia consumption; The optimization decision module is used to obtain the currently predicted optimal ammonia injection amount, ammonia injection temperature, and ammonia injection angle through optimization processing using an optimization algorithm and a multi-parameter coupling relationship model based on the currently predicted denitrification efficiency and the currently predicted ammonia consumption, as well as the preset denitrification efficiency target and ammonia consumption constraint conditions; a control execution module for automatically adjusting the ammonia injection amount, ammonia injection temperature, and ammonia injection angle of the denitrification equipment based on the currently predicted optimal ammonia injection amount, ammonia injection temperature, and ammonia injection angle, and performing denitrification processing according to the automatically adjusted ammonia injection amount, ammonia injection temperature, and ammonia injection angle; The feedback monitoring module is used to monitor the operating data after denitrification treatment in real time, and feed back the operating data after denitrification treatment to the data processing module for preprocessing.

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