Thermal power coal-fired unit denitration intelligent ammonia spraying automatic control system and method

Abstract

The invention relates to the technical field of denitration and ammonia spraying, in particular to an intelligent denitration and ammonia spraying automatic control system and method for a thermal power coal-fired unit, and the system comprises a control module which is used for controlling and monitoring the whole denitration process; the data analysis and prediction module is used for analyzing by utilizing historical data and real-time data, predicting NOx concentration change and providing decision support for ammonia injection control; the balancing module is responsible for accurately controlling and optimizing the ammonia spraying amount; the monitoring and feedback module is used for monitoring the concentration of NOx and ammonia escape in real time and providing a feedback signal for the control system; and the communication module is responsible for data transmission between the denitration control system module and the DCS program. The method has the beneficial effects that the time stability and the space uniformity of NOx at an SCR outlet are improved through an intelligent feed-forward algorithm and an override algorithm, excessive ammonia spraying is reduced by utilizing an ammonia escape correction system, the ammonia escape rate is effectively reduced, the operation reliability of a unit is improved, and the resistance increase of a flue gas system caused by blockage of an air pre-heater is reduced.

Description

Technical Field

[0001] The present invention relates to the technical field of denitrification ammonia injection, and particularly to an intelligent ammonia injection automatic control system and method for denitrification of thermal power coal-fired units. Background Art

[0002] The existing SCR (Selective Catalytic Reduction) denitrification technology has significant deficiencies in practical applications. It is mainly manifested that the automatic control quality of NOx (nitrogen oxides) emission control is closely related to the long-term operation cost of the power plant. However, the response pure delay time of the denitrification controlled object (NH3 flow - NOx concentration at the chimney inlet) is close to 3 minutes, and the entire response process lasts for more than ten minutes, showing typical large lag characteristics. In addition, the SCR denitrification process is a complex non-linear chemical reaction process, and its dynamic characteristics will change greatly with the consumption of the catalyst. Therefore, it is very difficult to achieve an ideal control effect by using a simple Proportional-Integral-Derivative (PID) controller, resulting in overspray of ammonia becoming normal, increased ammonia escape, reduced unit reliability, increased power consumption and cost, and uneven distribution of NOx at the SCR outlet. These are all challenges that need to be urgently solved in the existing technology. Summary of the Invention

[0003] In view of the above problems existing in the above or the prior art, the present invention is proposed.

[0004] Therefore, the purpose of the present invention is to provide an intelligent ammonia injection automatic control method for denitrification of thermal power coal-fired units, which can solve the problems of low control quality, waste of ammonia, increased ammonia escape, and uneven distribution of NOx at the SCR outlet, resulting in unsatisfactory environmental protection effects and economic benefits.

[0005] To solve the above technical problems, the present invention provides the following technical solution: An intelligent ammonia injection automatic control system for a thermal power coal-fired unit denitrification, which includes a control module: used to control and monitor the entire denitrification process;

[0006] A data analysis and prediction module: analyzes historical data and real-time data to predict NOx concentration changes and provides decision-making support for ammonia injection control;

[0007] An equilibrium module: responsible for precise control and optimization of the ammonia injection volume;

[0008] A monitoring and feedback module: monitors the concentrations of NOx and ammonia escape in real time and provides feedback signals for the control system;

[0009] A communication module: responsible for data transmission between the denitrification control system module and the DCS program.

[0010] As a preferred embodiment of the intelligent ammonia injection automatic control system for denitrification of thermal power coal-fired units in the present invention, the control module includes a DCS program and a NOx analyzer;

[0011] The DCS program is used to receive the advanced control strategy calculated by the ammonia injection grid equalization control algorithm and issue corresponding opening adjustment instructions to each partition adjustment valve;

[0012] The NOx analyzer is a NOx analyzer that combines the dilution method and the chemiluminescence method, and is used to measure the NOx concentration in the flue gas.

[0013] As a preferred embodiment of the intelligent ammonia injection automatic control system for denitrification of thermal power coal-fired units in the present invention, the data analysis and prediction module includes an inlet NOx prediction model;

[0014] The inlet NOx prediction model is used to predict the inlet NOx concentration to overcome the problem of slow response in sampling and measurement of NOx measuring instruments.

[0015] As a preferred embodiment of the intelligent ammonia injection automatic control system for denitrification of thermal power coal-fired units in the present invention, the equalization module includes an ammonia injection grid equalization controller and a main ammonia injection loop predictive control;

[0016] The ammonia injection grid equalization controller includes an ammonia injection grid equalization control algorithm, which performs comparison calculations based on the real-time measurement value and historical data of the outlet NOx to achieve the best outlet NOx equalization control;

[0017] The intelligent ammonia injection grid equalization control algorithm ensures uniform distribution of the NOx concentration at the SCR outlet, minimizes ammonia slip, and improves the response speed and control accuracy of the system;

[0018] The main ammonia injection loop predictive control is used to replace the traditional PID control algorithm, predict the change of NOx concentration and adjust the opening of the ammonia injection control valve in advance.

[0019] As a preferred embodiment of the intelligent ammonia injection automatic control system for denitrification of thermal power coal-fired units in the present invention, the monitoring and feedback module includes an ammonia slip monitor;

[0020] The ammonia slip monitor monitors the ammonia slip situation and is used to correct the total ammonia injection amount to reduce the excessive ammonia injection and lower the ammonia slip rate.

[0021] As a preferred embodiment of the intelligent ammonia injection automatic control system for denitrification of thermal power coal-fired units in the present invention, the communication module includes a network switch and communication cables;

[0022] The communication module realizes data transmission through OPC or MODBUS communication, and connects the optimization control server and the DCS program.

[0023] To solve the above technical problems, the present invention also provides the following technical solutions: An intelligent ammonia injection automatic control method for a thermal power coal-fired unit denitration, which includes using intelligent feedforward and override algorithms, based on the inlet NOx prediction model, optimizing the total ammonia injection amount, and enhancing the stability and uniformity of the NOx at the SCR outlet;

[0024] Reducing excessive ammonia injection through ammonia slip correction and lowering ammonia slip;

[0025] Through the cooperation of the data analysis and prediction module and the balancing module, comprehensively control NOx;

[0026] Through historical data analysis, develop an ammonia injection grid balancing control algorithm to optimize the NOx balance at the outlet;

[0027] Establish an inlet NOx prediction model, predict and adjust the ammonia injection amount according to the change of NOx concentration;

[0028] Control the NOx concentration by replacing PID with a predictive control strategy.

[0029] As a preferred scheme of the intelligent ammonia injection automatic control method for the thermal power coal-fired unit denitration of the present invention, wherein: The intelligent feedforward algorithm can predict the change of NOx concentration at the outlet of the SCR reactor by real-time monitoring and predicting the inlet NOx concentration, and adjust the ammonia injection amount in advance to achieve rapid response and precise control of NOx emissions;

[0030] The override algorithm means that on the basis of intelligent feedforward, further optimize the control strategy, and compensate for system delay and nonlinear characteristics by real-time adjusting the ammonia injection amount to improve the stability and uniformity of NOx at the SCR outlet;

[0031] The inlet NOx prediction model is based on historical data and real-time data, establishes an inlet NOx prediction model, predicts the NOx concentration generated by boiler combustion, and provides an accurate feedforward signal for ammonia injection control.

[0032] As a preferred scheme of the intelligent ammonia injection automatic control method for the thermal power coal-fired unit denitration of the present invention, wherein: Ammonia slip correction means adjusting the ammonia injection strategy according to the monitoring data of ammonia slip;

[0033] Ammonia slip monitoring means real-time monitoring of ammonia slip, and obtaining real-time data of ammonia slip through devices such as chemical sensors.

[0034] As a preferred scheme of the intelligent ammonia injection automatic control method for the thermal power coal-fired unit denitration of the present invention, wherein: The ammonia injection grid balancing control algorithm is a developed algorithm, which dynamically adjusts the opening of the ammonia injection grid according to the real-time and historical data of the NOx at the outlet to achieve an even distribution of the NOx at the outlet.

[0035] Advantages of the present invention: By means of the intelligent feedforward algorithm and the override algorithm, the present invention improves the temporal stability and spatial uniformity of NOx at the SCR outlet, reduces excessive ammonia injection by using the ammonia slip correction system, effectively reduces the ammonia slip rate, reduces environmental pollution, optimizes the ammonia injection amount, reduces ammonia waste, reduces operating costs and maintenance costs, reduces the corrosion of NH4HSO4 generated by the reaction of ammonia with SO3 to the catalyst, air preheater and low-temperature economizer, improves the operating reliability of the unit, reduces the increase in flue gas system resistance caused by air preheater blockage, reduces the power consumption of the induced draft fan, reduces the number of unplanned unit shutdowns through intelligent control, improves the operating safety of the unit. In addition, by reducing the emissions of NOx and ammonia, it plays a positive role in environmental governance and protection. Description of the Drawings

[0036] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings. Among them:

[0037] Figure 1 It is a schematic diagram of the overall scheme of the intelligent ammonia injection automatic control system for denitrification of thermal power coal-fired units.

[0038] Figure 2 It is a schematic diagram of the overall layout of the intelligent ammonia injection automatic control system for denitrification of thermal power coal-fired units.

[0039] Figure 3 It is a schematic diagram of the equalizing control principle of the ammonia injection grid of the intelligent ammonia injection automatic control system for denitrification of thermal power coal-fired units.

[0040] Figure 4 It is a schematic diagram of the denitrification ammonia injection optimization of the intelligent ammonia injection automatic control system for denitrification of thermal power coal-fired units.

[0041] Figure 5 It is a schematic diagram of the total ammonia injection control principle of the intelligent ammonia injection automatic control system for denitrification of thermal power coal-fired units.

[0042] Figure 6 It is the first implementation mode of the total ammonia injection control of the intelligent ammonia injection automatic control method for denitrification of thermal power coal-fired units.

[0043] Figure 7 It is the second implementation mode of the total ammonia injection control of the intelligent ammonia injection automatic control method for denitrification of thermal power coal-fired units. Detailed Embodiments

[0044] In order to make the above objects, features and advantages of the present invention more obvious and understandable, the detailed embodiments of the present invention will be described below with reference to the drawings of the specification.

[0045] In the following description, many specific details are set forth in order to provide a thorough understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Persons skilled in the art can make similar extensions without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0046] Secondly, as used herein, an "embodiment" or "embodiments" refers to specific features, structures, or characteristics that may be included in at least one implementation manner of the present invention. The phrase "in an embodiment" appearing in different places in this specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments.

[0047] Embodiment 1

[0048] Referring to Figure 1 , which is the first embodiment of the present invention. This embodiment provides an intelligent ammonia injection automatic control method for thermal power coal-fired units' denitration, which can solve the problems of low control quality, ammonia waste, increased ammonia slip, and uneven distribution of NOx at the SCR outlet, resulting in unsatisfactory environmental protection effects and economic benefits.

[0049] Specifically, the control module 100: is used to control and monitor the entire denitration process;

[0050] The data analysis and prediction module 200: analyzes historical data and real-time data to predict the change of NOx concentration and provides decision-making support for ammonia injection control;

[0051] The balancing module 300: is responsible for the precise control and optimization of the ammonia injection amount;

[0052] The monitoring and feedback module 400: monitors the concentrations of NOx and ammonia slip in real time and provides feedback signals to the control system;

[0053] The communication module 500: is responsible for data transmission between the denitration control system module and the DCS program 101.

[0054] Furthermore, the control module 100 includes a DCS program 101 and a NOx analyzer 102;

[0055] The DCS program 101 is used to receive the advanced control strategy calculated by the ammonia injection grid balancing control algorithm and issue corresponding opening adjustment instructions to each partition adjustment valve;

[0056] The NOx analyzer 102 is a NOx analyzer 102 that combines the dilution method and the chemiluminescence method and is used to measure the NOx concentration in the flue gas.

[0057] It should be noted that DCS is the abbreviation of Distributed Control System, which is a computer control system used for industrial process control. By dispersing control functions to multiple control nodes, DCS realizes centralized monitoring and management of the entire thermal power plant production process. Among them, DCS consists of multiple modules, each module is responsible for specific control tasks, and these modules are connected through a network to achieve the exchange of data and control signals. DCS includes, but is not limited to, process control module 100, data acquisition and processing module, communication module, and safety and redundancy module;

[0058] Among them, the process control module 100 includes an I / O (input / output) module: responsible for collecting on-site sensor signals and sending control signals to actuators; a control algorithm module: implementing PID control, advanced control algorithms, etc.; a logic control module 100: processing logic control tasks such as sequence control and conditional control;

[0059] The data acquisition and processing module includes a data acquisition module: collecting process variables in real time, such as temperature, pressure, flow rate, etc.; a data recording module: recording historical data for trend analysis and fault diagnosis;

[0060] The communication module includes a network communication module: responsible for data communication between internal modules of DCS and with external systems; a remote I / O module: expanding the I / O capabilities of the system, suitable for remote or distributed sensors and actuators;

[0061] The safety and redundancy module includes a redundant control module 100: ensuring redundancy of key control tasks and improving system reliability; a safety instrument system (SIS) interface module: interfacing with the safety instrument system to ensure process safety.

[0062] Furthermore, the data analysis and prediction module 200 includes an inlet NOx prediction model 201;

[0063] The inlet NOx prediction model 201 is used to predict the inlet NOx concentration to overcome the problem of slow sampling and measurement response of NOx measuring instruments.

[0064] It should be noted that the inlet NOx prediction model 201 is constructed through data-driven methods and physical model methods. Among them, in this solution, the data-driven method specifically includes collecting historical data of boiler operation, including fuel type, combustion conditions, temperature, pressure, air volume, etc.; analyzing these data using statistical methods to determine the key factors affecting NOx generation; using machine learning algorithms (such as neural networks, support vector machines, or multiple linear regression) to train the model to identify the relationship between input variables and NOx concentration.

[0065] The physical model method specifically includes establishing a physical model for NOx generation based on the chemical reaction kinetics during the combustion process, and considering the influence of thermodynamic parameters such as temperature, pressure, and oxygen concentration in the boiler on NOx generation.

[0066] The model structure of the inlet NOx prediction model 201 includes an input layer, a hidden layer, and an output layer. Among them, the input layer includes all input variables that affect NOx generation, such as fuel quantity, air volume, oxygen content, etc.; in the neural network model, the hidden layer is used to extract the non-linear features of the input data; the predicted NOx concentration of the output layer is used as the output of the model.

[0067] After the inlet NOx prediction model 201 is constructed, it is necessary to verify the accuracy of the model by comparing it with the actual NOx concentration, and regularly update the model according to the new operation data to adapt to the changes in the boiler operation conditions.

[0068] When in use, the inlet NOx prediction model 201 collects the boiler operation parameters in real time, inputs the real-time data into the model, and calculates the predicted NOx concentration. Among them, the predicted NOx concentration output by the model is used to generate a control signal to guide the adjustment of the ammonia injection control valve.

[0069] It should be noted that the multiple linear regression model is used to calculate the predicted NOx concentration of the inlet NOx prediction model 201, and its formula is as follows:

[0070] NOx = β 0 + β 1 × fuel quantity + β 2 × air volume + β 3 × temperature + ∈

[0071] Among them, β 0 , β 1 , β 2 , β 3 are the model coefficients, and ∈ is the error term.

[0072] Furthermore, the equalization module 300 includes the ammonia injection grid equalization controller 301 and the ammonia injection main loop predictive control 302;

[0073] The ammonia injection grid equalization controller 301 includes the ammonia injection grid equalization control algorithm, which performs comparison calculations based on the real-time measurement value and historical data of the outlet NOx to achieve the best outlet NOx equalization control. Among them, the formula of the ammonia injection grid equalization control algorithm is as follows:

[0074] The calculation formula for the ammonia injection quantity based on the NOx concentration and the ammonia-nitrogen ratio (NH3 / NOx):

[0075] Ammonia injection quantity = NOx concentration × ammonia-nitrogen ratio × flue gas volume

[0076] Among them, the NOx concentration is measured by a NOx analyzer, the ammonia-nitrogen ratio is determined according to the denitrification efficiency and ammonia slip rate, and the flue gas volume is calculated according to the flue gas flow rate and the flue duct cross-sectional area. The calculation formula for the flue gas volume is as follows:

[0077] Flue gas volume = flue gas flow rate × flue duct cross-sectional area × time

[0078] Among them, the flue gas flow rate is usually in meters per second (m / s); the flue duct cross-sectional area is usually in square meters (m 2 ); the time is usually in seconds (s);

[0079] Outlet NOx prediction formula based on historical data and real-time data:

[0080] Outlet NOx 预测 = f(Inlet NOx, ammonia injection amount, catalyst efficiency, temperature, pressure)

[0081] Among them, f is a prediction function trained based on historical data, which can be a learning model of multiple linear regression or neural network;

[0082] In this solution, the multiple linear regression method is selected for model establishment, and its formula is as follows:

[0083] NOx 预测 = β 0 + β 1 × Inlet NOx + β 2 × Ammonia injection amount + β 3 × Temperature + β 4 × Pressure + β 5 × Air volume + ∈

[0084] Among them, β 0 , β 1 , β 2 , β 3 , β 4 , β 5 are regression coefficients, and ∈ is the error term.

[0085] Ammonia injection grid balance control formula based on the outlet NOx distribution:

[0086] Ammonia injection grid opening = g(Outlet NOx distribution, ammonia injection amount, catalyst distribution)

[0087] Among them, g is a control function calculated according to the outlet NOx distribution and the ammonia injection amount;

[0088] Specifically, for the control function represented by g, this solution uses Model Predictive Control (MPC) for calculation. First, a cost function J is defined. Let the outlet NOx distribution be y, the ammonia injection rate be r, and the catalyst distribution be u, which is used to evaluate the deviation between the system output and the reference value, as well as the smoothness of the control input. The formula is as follows:

[0089]

[0090] where N is the prediction time horizon; y(t + k|t) is the system output concentration of the outlet NOx at the future time t + k predicted at time t; r(t + k|t) is the reference value of the ammonia injection rate, where the ammonia injection rate is calculated by the above ammonia injection rate calculation formula; u(t + k|t) is the distribution of the catalyst at the future time t + k predicted at time t; λ is the weight factor used to balance the output deviation and the smoothness of the control input;

[0091] The result of the control function g is calculated through this defined function to obtain the opening degree of the ammonia injection grid;

[0092] The intelligent ammonia injection grid equalization control algorithm ensures a uniform distribution of the NOx concentration at the SCR outlet, while minimizing ammonia slip, and improving the system's response speed and control accuracy;

[0093] where the ammonia slip value can be obtained by subtracting the NOx reduction amount from the ammonia injection rate obtained in the above calculation;

[0094] The predictive control of the main ammonia injection loop 302 is used to replace the traditional PID control algorithm to predict the change of the NOx concentration and adjust the opening degree of the ammonia injection valve in advance.

[0095] It should be noted that the intelligent ammonia injection grid equalization control algorithm is used to optimize the ammonia injection distribution in the SCR of thermal power coal-fired units, ensure a uniform distribution of the NOx concentration at the outlet of the SCR reactor in time and space, minimize the escape of unreacted ammonia into the atmosphere, reduce environmental pollution and improve economy.

[0096] Specifically, as Figure 3 shown, in this solution, the intelligent ammonia injection grid equalization control algorithm builds a model by collecting real-time measurement values of NOx at the SCR outlet and analyzing historical NOx distribution data, including NOx concentration and ammonia injection rate under different working conditions. The established model includes an ammonia injection diffusion model and a catalyst performance field model. Among them, the ammonia injection diffusion model simulates the diffusion process of ammonia in the flue gas and predicts the influence of different ammonia injection points on the outlet NOx; the catalyst performance field model considers the activity distribution and degradation of the catalyst and simulates the influence of the catalyst on NOx reduction.

[0097] The control strategy of the intelligent ammonia injection grid balance control algorithm includes multivariable control and predictive control. Among them, multivariable control coordinates the ammonia injection amounts at multiple ammonia injection points to achieve overall NOx concentration control; predictive control is based on model predictive control (MPC) technology, predicts future NOx concentration changes, and adjusts the ammonia injection strategy in advance.

[0098] The intelligent ammonia injection grid balance control algorithm dynamically adjusts the opening degree of the ammonia injection grid by monitoring the NOx concentration and ammonia slip at the SCR outlet in real time, and adapts to the changes in working conditions according to the real-time data and prediction model.

[0099] Among them, the prediction model adopts a neural network model, and its formula is as follows:

[0100]

[0101] Among them, n is the number of input features; w i is the weight of the i-th input feature, indicating the influence degree of this feature on the prediction result; xi is the value of the i-th input feature; b is the bias term, which is a constant used to adjust the output of the model so that the model can better fit the data.

[0102] Furthermore, the monitoring and feedback module 400 includes an ammonia slip monitor 401;

[0103] The ammonia slip monitor 401 monitors the ammonia slip situation and is used to correct the total ammonia injection amount to reduce the excessive ammonia injection and lower the ammonia slip rate.

[0104] Furthermore, the communication module 500 includes a network switch 501 and communication cables 502;

[0105] The communication module 500 realizes data transmission through OPC or MODBUS communication, and connects to the optimization control server and the DCS program 101. Among them, OPC stands for OLE for Process Control, which is OLE (Object Linking and Embedding) for process control. OPC is based on OLE technology and is an industrial communication protocol used to achieve data exchange and communication between devices and systems of different manufacturers; MODBUS is a widely used industrial serial communication protocol mainly used in the field of industrial automation, allowing communication between controllers and other devices. The MODBUS protocol supports multiple communication methods, including RS-232, RS-485, and Ethernet. It allows a master device, such as a PLC, to control multiple slave devices, such as sensors and actuators, to achieve data acquisition, monitoring, and control.

[0106] It should be noted that the intelligent ammonia injection grid equalization control algorithm is implemented in an externally connected dedicated industrial control server and performs real-time calculations through a high-performance industrial control computer. The calculation results are transmitted to the DCS program 101 in real time through OPC or MODBUS communication methods.

[0107] In summary, through the intelligent feedforward algorithm and override algorithm, the present invention improves the time stability and spatial uniformity of NOx at the SCR outlet, reduces excessive ammonia injection by using the ammonia slip correction system, effectively reduces the ammonia slip rate, reduces environmental pollution, optimizes the ammonia injection amount, reduces ammonia waste, reduces operating costs and maintenance costs, reduces the corrosion of NH4HSO4 generated by the reaction of ammonia and SO3 on the catalyst, air preheater and low-temperature economizer, improves the operating reliability of the unit, reduces the increase in flue gas system resistance caused by air preheater blockage, reduces the power consumption of the induced draft fan, reduces the number of unplanned unit outages through intelligent control, improves the operating safety of the unit. In addition, by reducing the emissions of NOx and ammonia, it plays a positive role in environmental governance and protection.

[0108] Embodiment 2

[0109] Refer to Figure 2 or Figure 3 , which is the second embodiment of the present invention. This embodiment provides a denitration intelligent ammonia injection automatic control system for thermal power coal-fired units, which can solve the problems of low control quality, ammonia waste, increased ammonia slip, and uneven distribution of NOx at the SCR outlet, resulting in unsatisfactory environmental protection effects and economic benefits.

[0110] Specifically, by using the intelligent feedforward and override algorithms, based on the inlet NOx prediction model, the total ammonia injection amount is optimized to enhance the stability and uniformity of NOx at the SCR outlet;

[0111] Reduce excessive ammonia injection through ammonia slip correction and reduce ammonia slip;

[0112] Through the cooperation of the data analysis and prediction module and the equalization module, comprehensive control of NOx is carried out;

[0113] Among them, f is the activation function, w i is the weight, x i is the input variable, and b is the bias.

[0114] Through historical data analysis, develop an ammonia injection grid equalization control algorithm to optimize the NOx equalization at the outlet;

[0115] Establish an inlet NOx prediction model, predict and adjust the ammonia injection amount according to the change of NOx concentration;

[0116] Control the NOx concentration by replacing PID with a predictive control strategy.

[0117] Furthermore, the intelligent feedforward algorithm can predict the change of NOx concentration at the outlet of the SCR reactor by real-time monitoring and predicting the inlet NOx concentration, and adjust the ammonia injection amount in advance to achieve rapid response and precise control of NOx emissions;

[0118] The override algorithm further optimizes the control strategy on the basis of intelligent feedforward, compensates for system delay and nonlinear characteristics by real-time adjusting the ammonia injection amount, and improves the stability and uniformity of NOx at the SCR outlet;

[0119] The inlet NOx prediction model is based on historical data and real-time data, establishes an inlet NOx prediction model, predicts the NOx concentration generated by boiler combustion, and provides an accurate feedforward signal for ammonia injection control.

[0120] Furthermore, ammonia slip correction refers to adjusting the ammonia injection strategy according to the monitoring data of ammonia slip;

[0121] Ammonia slip monitoring refers to real-time monitoring of ammonia slip conditions and obtaining real-time data of ammonia slip through devices such as chemical sensors.

[0122] Furthermore, the ammonia injection grid equalization control algorithm is a developed algorithm that dynamically adjusts the opening of the ammonia injection grid according to the real-time and historical data of NOx at the outlet to achieve an even distribution of NOx at the outlet.

[0123] It should be noted that the ammonia injection grid equalization control algorithm not only needs to consider the real-time measurement value of NOx at the outlet, but also combines the historical data of NOx at the outlet. An optimal NOx equalization control model at the outlet based on the ammonia injection diffusion model and the catalyst performance field model is proposed.

[0124] In summary, the present invention improves the temporal stability and spatial uniformity of NOx at the SCR outlet through the intelligent feedforward algorithm and the override algorithm, reduces excessive ammonia injection by using the ammonia slip correction system, effectively reduces the ammonia slip rate, reduces environmental pollution, optimizes the ammonia injection amount, reduces ammonia waste, reduces operating costs and maintenance costs, reduces the corrosion of NH4HSO4 generated by the reaction of ammonia and SO3 on the catalyst, air preheater and low-temperature economizer, improves the operation reliability of the unit, reduces the increase in flue gas system resistance caused by air preheater blockage, reduces the power consumption of the induced draft fan, reduces the number of unplanned shutdowns of the unit through intelligent control, improves the operation safety of the unit. In addition, by reducing the emissions of NOx and ammonia, it plays a positive role in environmental governance and protection. The application of the frequency gate recognition system in the intelligent warehousing system is more efficient and stable, and at the same time improves the user experience.

[0125] Example 3

[0126] Refer to Figures 4 to 7, which is the third embodiment of the present invention. This embodiment provides an intelligent ammonia injection automatic control method for thermal power coal-fired units, which can improve the temporal stability and spatial uniformity of NOx at the SCR outlet through the optimization of the control system. On the premise of ensuring environmental protection indicators, the ammonia slip is minimized.

[0127] Specifically, this solution is based on an intelligent feedforward algorithm and an override algorithm for the total ammonia injection optimization control system based on the inlet NOx prediction model, and a denitration optimization control system based on ammonia slip correction.

[0128] It should be noted that the formula of the intelligent feedforward algorithm is as follows:

[0129]

[0130] Among them, u(t) is the control input, e(t) is the deviation (the difference between the set value and the actual value), K p , K i , K d are the proportional, integral, and derivative gains of the PID controller, and u ff(t) is the feedforward control input;

[0131] Among them, the formula for the feedforward control input is:

[0132] uff(t) = G -1 (p)R(t) + G -1 (p)H(p)Y(t)

[0133] Among them, G -1 (p) is the inverse of the process transfer function, R(t) is the reference input (set value), H(p) is the disturbance transfer function, and Y(t) is the disturbance;

[0134] The formula of the override algorithm is as follows:

[0135] u(t) = u PID(t) + u ov(t)

[0136] Among them, u PID(t) is the PID control output, and u ov(t) is the override control output;

[0137] Among them, the formula for the override control output is:

[0138]

[0139] Among them, K ov is the override gain, e(t) is the deviation, e set is the set deviation, and e threshold is the threshold for triggering the override control.

[0140] The denitration optimization system algorithm based on NOx partition measurement and ammonia slip loop correction is complex. The denitration optimization system model based on NOx partition measurement and ammonia slip loop correction will call real-time data for rolling analysis and learning.

[0141] The NOx emission control optimization technology specifically includes:

[0142] Adopt a NOx analyzer that combines the dilution method and the chemiluminescence method. The combination of the flue gas extraction method of the dilution method and the chemiluminescence method has the advantages of not requiring water removal and a simple system, greatly reducing the probability of failure shutdown and maintenance costs;

[0143] Adopt an intelligent ammonia injection grid balanced control algorithm based on historical data analysis. The ammonia injection grid balanced control algorithm should not only consider the real-time measurement value of the outlet NOx, but also combine the historical data of the outlet NOx. Propose an optimal outlet NOx balanced control model based on the ammonia injection diffusion model and the catalyst performance field model. The DCS program uses the balanced control algorithm to calculate the advanced control strategy and sends corresponding opening adjustment commands to the regulating valves of each partition. Figure c is the schematic diagram of the ammonia injection grid balanced controller;

[0144] Adopt an accurate prediction model of inlet NOx based on a large number of measured data. The accurate prediction model can overcome the problem of slow response of the NOx measurement instrument sampling measurement. First, based on the technological process of inlet NOx generation, analyze the causal relationship between it and the fuel quantity, air volume, and various combustion conditions input into the boiler, and adopt a dynamic multiple linear regression model for prediction. The measurement result of inlet NOx for the correction and fitting of the model is long-term, and it is necessary to use the measurement results of continuous 24-hour sampling for verification and correction to recursively obtain a relatively accurate and timely soft measurement result. There is a large lag in the measurement of NOx at the inlet and outlet of the denitration system, making the control loop unable to adapt to the characteristics of nonlinearity, large lag, and fast time-variation of the denitration process. Therefore, the implementation of advanced control technology first requires the establishment of an accurate prediction simulation of inlet NOx to predict the inlet NOx value before the meter. This feedforward algorithm can greatly improve the accuracy of ammonia injection and the quality of denitration control;

[0145] Adopt predictive control of the ammonia injection main loop to replace the traditional PID control algorithm. As Figure 4 shown, it is the general diagram of the denitration ammonia injection optimization system. The predictive control of the ammonia injection main loop is a very effective large-lag control strategy. Through it, the change of NOx concentration in the future period can be predicted, so as to adjust the opening of the ammonia injection regulating valve in advance and effectively suppress the change of NOx concentration.

[0146] In addition, through the soft measurement technology of inlet NOx, the inlet NOx is predicted, which is an important parameter for ammonia injection feedforward and participates in the closed-loop control of the total ammonia injection amount, solving the problem of measurement lag of inlet NOx. At the same time, the ammonia slip is used to correct the main loop. On the other hand, the transfer function of the SCR reactor under different loads is obtained through experiments, and then the advanced control algorithm model is implemented targeted.

[0147] The system gradually accumulates the measured data, automatically learns, and gradually achieves rapid judgment and adjustment when combined with burners and fuel changes. (It can timely detect problems such as blockage and wear failure of the SCR device according to the data change trend and adjust the operation mode in time) and gradually reduces the frequency of real-time testing, and finally realizes the intelligent and refined control of the SCR system.

[0148] It should be noted that the advanced control algorithm of this project is arranged in the dedicated industrial control server on the external. The ammonia injection optimization control server collects relevant data of the DCS, performs real-time calculations in the server, and the optimization control server is implemented with a high-performance industrial control computer. The calculation results are then sent to the DCS in real time to guide the DCS to achieve denitrification optimization. Among them, the communication method can be achieved through OPC or MODBUS communication. The optimization server communicates and transmits the control strategy obtained by the equalization control algorithm to the DCS, and the DCS program issues the opening adjustment instructions for the regulating valves in each zone.

[0149] In summary, through the intelligent feedforward algorithm and the override algorithm, the present invention improves the time stability and spatial uniformity of the SCR outlet NOx, uses the ammonia slip correction system to reduce excessive ammonia injection, effectively reduces the ammonia slip rate, reduces environmental pollution, optimizes the ammonia injection amount, reduces ammonia waste, reduces the operation cost and maintenance cost, reduces the corrosion of NH4HSO4 generated by the reaction of ammonia and SO3 to the catalyst, air preheater and low-temperature economizer, improves the operation reliability of the unit, reduces the increase in the flue gas system resistance caused by air preheater blockage, reduces the power consumption of the induced draft fan, reduces the number of unplanned shutdowns of the unit through intelligent control, improves the operation safety of the unit. In addition, by reducing the emissions of NOx and ammonia, it plays a positive role in environmental governance and protection.

[0150] Importantly, it should be noted that the construction and arrangement of the present application shown in multiple different exemplary embodiments are merely illustrative. Although only a few embodiments are described in detail in this disclosure, those who refer to this disclosure should easily understand that many modifications are possible without materially departing from the novel teachings and advantages of the subject matter described in this application (such as installation arrangements, use of materials, color, orientation changes, etc.). For example, an element shown as integrally formed may be composed of multiple parts or elements, the position of the element may be inverted or otherwise changed, and the nature, number, or position of discrete elements may be altered or changed. Therefore, all such modifications are intended to be included within the scope of the present invention. The order or sequence of any process or method steps may be changed or reordered according to alternative embodiments. In the claims, any "means-plus-function" clauses are intended to cover the structures that perform the functions described herein, and not only structural equivalents but also equivalent structures. Other substitutions, modifications, changes, and omissions may be made in the design, operating conditions, and arrangement of the exemplary embodiments without departing from the scope of the present invention. Therefore, the present invention is not limited to specific embodiments, but extends to various modifications that still fall within the scope of the appended claims.

[0151] In addition, to provide a concise description of the exemplary embodiments, all features of the actual embodiments may not be described.

[0152] It should be understood that in the development of any actual implementation, as in any engineering or design project, numerous specific implementation decisions may be made. Such development efforts may be complex and time-consuming, but for those of ordinary skill in the art who benefit from this disclosure, without excessive experimentation, the development efforts will be a routine task of design, manufacturing, and production.

[0153] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit them. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical solutions of the present invention may be modified or equivalently replaced without departing from the spirit and scope of the technical solutions of the present invention, and they should all be covered by the scope of the claims of the present invention.

Claims

1. An intelligent ammonia injection automatic control system for denitration of coal-fired power units, characterized by: include, Control module (100): used to control and monitor the entire denitrification process; Data analysis and prediction module (200): using historical data and real-time data to analyze and predict NOx concentration changes, providing decision support for ammonia injection control; Balance module (300): responsible for precise control and optimization of ammonia injection amount; Monitoring and feedback module (400): real-time monitoring of the concentration of NOx and ammonia escape, and providing feedback signals to the control system; Communication module (500): responsible for data transmission between the denitration control system module and the DCS program (101).

2. The intelligent ammonia injection automatic control system for denitration of coal-fired power units according to claim 1, characterized in that: The control module (100) includes a DCS program (101) and a NOx analyzer (102); The DCS program (101) is used to receive the advanced control strategy calculated by the ammonia injection grid balance control algorithm, and issue corresponding opening adjustment instructions to each partition regulating valve; The NOx analyzer (102) is a NOx analyzer (102) that combines a dilution method with a chemiluminescence method and is used to measure the NOx concentration in the flue gas.

3. The intelligent ammonia injection automatic control system for denitration of coal-fired power units according to claim 2, characterized in that: The data analysis and prediction module (200) includes an inlet NOx prediction model (201); The inlet NOx prediction model (201) is used to predict the inlet NOx concentration to overcome the problem of slow sampling measurement response of the NOx measuring instrument.

4. The intelligent ammonia injection automatic control system for denitration of coal-fired power units according to claim 3, characterized in that: The balancing module (300) includes an ammonia injection grid balancing controller (301) and an ammonia injection main loop predictive control (302); The ammonia injection grid balance controller (301) includes an ammonia injection grid balance control algorithm, which performs comparison calculation based on the real-time measurement value of outlet NOx and historical data to achieve optimal outlet NOx balance control; The intelligent ammonia injection grid balanced control algorithm ensures uniform distribution of NOx concentration at the SCR outlet, while minimizing ammonia escape and improving the system's response speed and control accuracy; The ammonia injection main loop predictive control (302) is used to replace the traditional PID control algorithm, predict the NOx concentration change and adjust the opening of the ammonia injection valve in advance.

5. The intelligent ammonia injection automatic control system for denitration of coal-fired power units according to claim 4, characterized in that: The monitoring and feedback module (400) comprises an ammonia slip monitor (401); The ammonia slip monitor (401) monitors the ammonia slip situation and is used to correct the total amount of ammonia injection to reduce excessive ammonia injection and reduce the ammonia slip rate.

6. The intelligent ammonia injection automatic control system for denitration of coal-fired power generation units according to claim 5, characterized in that: The communication module (500) comprises a network switch (501) and a communication cable (502); The communication module (500) realizes data transmission through OPC or MODBUS communication, and connects the optimization control server and the DCS program (101).

7. A method for automatic control of denitration intelligent ammonia injection for coal-fired thermal power generation units, based on the above-mentioned automatic control system for denitration intelligent ammonia injection for coal-fired thermal power generation units, characterized in that: include, Utilize intelligent feedforward and override algorithms to optimize the total amount of ammonia injection based on the inlet NOx prediction model and enhance the stability and uniformity of SCR outlet NOx; Reduce excessive ammonia injection and ammonia slip through ammonia slip correction; Through the cooperation of data analysis and prediction module and equalization module, NOx is comprehensively controlled; Through historical data analysis, we developed an ammonia injection grid balance control algorithm to optimize the outlet NOx balance; Establish an inlet NOx prediction model to predict and adjust the amount of ammonia injection according to changes in NOx concentration; The NOx concentration is controlled by replacing PID with a predictive control strategy.

8. The intelligent ammonia injection automatic control system for denitration of coal-fired power generation units according to claim 7, characterized in that: The intelligent feedforward algorithm can predict the change of NOx concentration at the outlet of the SCR reactor by real-time monitoring and prediction of the inlet NOx concentration, and adjust the ammonia injection amount in advance to achieve rapid response and precise control of NOx emissions; The override algorithm further optimizes the control strategy based on intelligent feedforward, and compensates for system delay and nonlinear characteristics by adjusting the amount of ammonia injection in real time to improve the stability and uniformity of NOx at the SCR outlet; The inlet NOx prediction model is based on historical data and real-time data to establish an inlet NOx prediction model, predict the NOx concentration generated by boiler combustion, and provide an accurate feedforward signal for ammonia injection control.

9. The method for intelligent ammonia injection automatic control of denitration of coal-fired power generation units according to claim 8, characterized in that: The ammonia slip correction refers to adjusting the ammonia injection strategy according to the monitoring data of ammonia slip; The ammonia escape monitoring refers to real-time monitoring of ammonia escape conditions, and obtaining real-time data of ammonia escape through chemical sensors and other equipment.

10. The method for intelligent ammonia injection automatic control of denitration of coal-fired power generation units according to claim 9, characterized in that: The ammonia injection grid balanced control algorithm is a development algorithm, which dynamically adjusts the opening of the ammonia injection grid according to the real-time and historical data of outlet NOx to achieve balanced distribution of outlet NOx.

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