An intelligent control system for ammonia injection in flue gas purification of a waste incinerator

Abstract

The application relates to the technical field of flue gas purification control, and discloses a garbage incinerator flue gas purification ammonia spraying intelligent control system, which comprises a collecting unit, a signal unit, a NOx optimization unit, an SNCR control unit, an SCR control unit, a flue gas control unit and a diagnosis unit. The NOx optimization unit adjusts the ammonia water consumption and distributes the ammonia water consumption into SNCR ammonia water consumption Q1 and SCR ammonia water consumption Q2. The SNCR control unit controls the SNCR ammonia water flow and the soft water ratio according to the SNCR ammonia water consumption Q1. The SCR control unit controls the SCR ammonia water flow according to the SCR ammonia water consumption Q2. The flue gas control unit controls the SCR flue gas temperature. The diagnosis unit executes a safety protection action when the system is abnormal. The application dynamically evaluates the current denitration efficiency of the SNCR and the SCR, calculates total ammonia water consumption prediction value Q and corresponding SNCR ammonia water consumption Q1 and SCR ammonia water consumption Q2, so as to realize dynamic and accurate distribution of the total ammonia water consumption.

Description

Technical Field

[0001] This invention relates to the field of flue gas purification and control technology, and more specifically to an intelligent control system for ammonia injection in flue gas purification of a waste incinerator. Background Technology

[0002] With increasingly stringent environmental protection requirements, the waste-to-energy industry is constantly raising its standards for controlling the concentration of nitrogen oxides (NOx) emissions in flue gas. Currently, large-scale waste incinerators generally adopt a two-stage denitrification process of "SNCR (Selective Non-Catalytic Reduction) + SCR (Selective Catalytic Reduction)". SNCR denitrification reduces NOx to nitrogen and water by injecting a reducing agent (such as ammonia) into the high-temperature zone of the furnace (850℃~1050℃). SCR denitrification further removes residual NOx through a catalyst at a lower temperature window (180℃~400℃). Using these two stages in series can achieve a high overall denitrification efficiency. However, existing ammonia injection control systems for denitrification have the following problems: Existing SNCR and SCR systems mostly use independent control loops, requiring operators to manually set the opening of each ammonia injection regulating valve. This makes it impossible to dynamically allocate the total ammonia usage based on the actual efficiency of the two-stage denitrification units. The existing system lacks closed-loop feedback control for ammonia slip concentration. Under conditions of frequent load fluctuations in the waste incinerator, manual adjustments are difficult to respond in time, leading to excessive ammonia slip concentration, catalyst blockage and failure, and secondary pollution. The denitrification process has characteristics of hysteresis, strong nonlinearity, and multivariate coupling. Furthermore, environmental assessments use hourly averages, and the current lack of time-average predictive control capabilities results in instantaneous values ​​meeting standards but hourly averages exceeding standards or excessive ammonia injection. Summary of the Invention

[0003] In order to overcome the above-mentioned defects of the prior art, the embodiments of the present invention provide an intelligent control system for ammonia injection in flue gas purification of waste incinerators to solve the technical problems mentioned in the background art.

[0004] To achieve the above objectives, the present invention provides the following technical solution: an intelligent control system for ammonia injection in flue gas purification of a waste incinerator, comprising a data acquisition unit, a signal unit, a NOx optimization unit, an SNCR control unit, an SCR control unit, a flue gas control unit, and a diagnostic unit; the data acquisition unit acquires process parameters during denitrification in real time; the signal unit performs quality judgment on the acquired signals and transmits valid signals to the NOx optimization unit; the NOx optimization unit calculates the predicted total ammonia usage Q and allocates it as SNCR ammonia usage Q1 and SCR ammonia usage Q2, respectively, and outputs them to the SNCR control unit and the SCR control unit; the SNCR control unit controls the SNCR ammonia flow rate and soft water ratio according to the SNCR ammonia usage Q1; the SCR control unit controls the SCR ammonia flow rate according to the SCR ammonia usage Q2; the flue gas control unit controls the SCR flue gas temperature; and the diagnostic unit performs safety protection actions when the system malfunctions.

[0005] In a preferred embodiment, the process parameters collected in real time by the acquisition unit include: NOx concentration setpoint, measured NOx concentration, flue gas flow rate, flue gas oxygen content, flue gas velocity, furnace temperature, SCR inlet flue gas temperature, SCR outlet flue gas temperature, ammonia water flow rate, soft water flow rate, and ammonia slip concentration. The signal unit performs quality judgment on the signals collected by the acquisition unit, detecting whether the signal change rate exceeds a preset threshold or whether the signal exceeds the measurement range. If it exceeds or exceeds the threshold, it is determined to be a signal fault and automatically rejected. If it does not exceed the preset threshold or the signal does not exceed the measurement range, it is transmitted normally.

[0006] In a preferred embodiment, the NOx optimization unit monitors the current instantaneous value A of the NOx concentration and the historical average value B within the past time period T in real time. It calculates the predicted average concentration D of the NOx concentration to be reached in the remaining time period according to the constraint relationship based on the hourly average. The constraint relationship is [B×T+D×(60-T)] / 60≤S, where S is the hourly average value setpoint of the NOx concentration. The average concentration D is used as the predicted control target at the current moment. The difference between A and D is calculated. When the absolute value of the difference exceeds the preset dead zone, the ammonia water usage adjustment is initiated. The theoretical ammonia water demand R is calculated based on the flue gas flow rate F, the target removal amount, and the ammonia nitrogen chemical reaction molar ratio. The theoretical value is corrected by the correction coefficient k updated by sliding the data of the most recent 72 hours of operation to obtain the predicted value Q of the total ammonia water usage, where Q=k×R.

[0007] In a preferred embodiment, the NOx optimization unit updates the model parameters online using the most recent 72 hours of operating data as a sliding time window based on the ammonia-nitrogen molar ratio model, dynamically evaluates the current denitrification efficiency of SNCR and SCR, allocates the predicted total ammonia usage Q to the SNCR control unit and the SCR control unit, and the SNCR control unit and the SCR control unit respectively obtain the SNCR ammonia usage Q1 and the SCR ammonia usage Q2, and Q = Q1 + Q2. The calculation formula for the SNCR ammonia usage Q1 is Q1 = β × Q, where β is the allocation coefficient, and the calculation formula for the SCR ammonia usage Q2 is Q2 = (1 - β) × Q.

[0008] In a preferred embodiment, the SNCR control unit dynamically calculates the soft water flow rate setpoint RS based on the SNCR ammonia water usage Q1 output by the NOx optimization unit and the measured value of the atomization mixing pressure. The calculation formula is RS=WZ-Q1, where WZ is the target value of the total atomization flow rate, and the lower limit of the soft water flow rate setpoint RS is not less than 50% of Q1.

[0009] In a preferred embodiment, the SCR control unit receives the SCR ammonia dosage Q2 output by the NOx optimization unit, and calculates a correction amount XZ based on the deviation between the measured ammonia slip concentration at the SCR outlet and the target value. When the measured ammonia slip is greater than the target value, the correction amount XZ is negative; when the measured ammonia slip is less than the target value, the correction amount XZ is positive, and the correction amount is limited to ±10% of Q2. Q2 is then summed with the correction amount XZ as the total setpoint. A model predictive control algorithm is used to adjust the opening of the SCR ammonia regulating valve to control the ammonia slip concentration at 8 mg / Nm³. 3 the following.

[0010] In a preferred embodiment, when calculating the correction amount XZ in the SCR control unit, the deviation value PX is first calculated. When calculating the deviation value PX, the ammonia slip target value is set to TM, and the measured value is SC. Then, the formula for calculating the deviation value PX is PX=SC-TM. When the deviation value PX>0, the correction amount XZ=-XS×PX. When the deviation value PX≤0, the correction amount XZ=XS×|PX|, where XS is the correction coefficient.

[0011] In a preferred embodiment, the flue gas control unit adopts an adaptive PID control method, which automatically adjusts the flue gas temperature entering the SCR device based on the comparison between the measured value of the SCR inlet flue gas temperature and the optimal reaction temperature window. The optimal reaction temperature window is 180℃~190℃. The PID parameters are automatically adjusted according to the temperature deviation and the rate of change of the deviation. When the temperature deviation is greater than 10℃, the proportional gain is increased, and when the temperature deviation is less than 3℃, the integral gain is increased. When the SCR inlet temperature is lower than the preset low temperature threshold of 170℃, the opening command of the SCR ammonia water regulating valve is automatically blocked, and a low temperature alarm is triggered at the same time.

[0012] In a preferred embodiment, when a fault occurs in the optimized system or equipment affecting automatic control, the diagnostic unit seamlessly switches all affected equipment to manual control mode and triggers an audible and visual alarm; when an automatic control loop is disconnected due to excessive signal deviation or equipment failure, an independent level voice alarm is triggered; the manually set control target value is speed-limited and its correctness is judged, and input is rejected when the set value exceeds the normal operating range; when the acquired signal shows jitter or disconnection, bad value processing is automatically performed, and the corresponding control loop is seamlessly switched to manual mode and an alarm is triggered.

[0013] In a preferred embodiment, the diagnostic unit performs fault handling according to priority: First priority: when a loss of valve position feedback is detected in the SCR ammonia regulating valve, all automatic regulating loops are switched to manual mode without disturbance within 1 second, triggering a red flashing alarm and simultaneously broadcasting the voice fault message; Second priority: when a fault is detected in one redundant signal, the fault signal is automatically eliminated and switched to the backup signal; the corresponding control loop is switched to manual and an alarm is triggered only when there is no backup signal and the current signal is abnormal; Third priority: when the manually input NOx concentration setpoint exceeds 20–80 mg / Nm³... 3 If the input is not within the safe range, the input will be rejected and a prompt box will pop up.

[0014] The technical effects and advantages of this invention are as follows: 1. This invention uses a NOx optimization unit based on an ammonia-nitrogen molar ratio model to update model parameters online using the most recent 72 hours of operating data as a sliding time window. It dynamically evaluates the current denitrification efficiency of SNCR and SCR, calculates the predicted total ammonia water usage Q and the corresponding SNCR ammonia water usage Q1 and SCR ammonia water usage Q2, thereby achieving dynamic and accurate allocation of total ammonia water usage. 2. This invention receives the SCR ammonia dosage Q2 output by the NOx optimization unit through the SCR control unit, and calculates the correction amount XZ based on the deviation between the measured value and the target value of the SCR outlet ammonia slip concentration. The SCR ammonia dosage Q2 is superimposed with XZ as the total set value. The opening of the SCR ammonia regulating valve is adjusted by the model predictive control algorithm. When the ammonia slip concentration change rate continues to rise, a predictive reduction signal is output in advance, thereby accurately controlling the ammonia slip concentration. 3. This invention uses a NOx optimization unit to monitor the current instantaneous value A of NOx concentration and the historical average value B within the past time period T. It calculates the predicted average concentration D that the NOx concentration should reach in the remaining time period according to the hourly average target constraint formula. D is used as the predictive control target and compared with the current instantaneous value A. The theoretical ammonia demand is corrected by the correction coefficient k updated by sliding data from the most recent 72 hours of operation, thus realizing feedforward predictive control based on time average constraints. Attached Figure Description

[0015] Figure 1 This is a schematic diagram of the system composition structure of the present invention. Detailed Implementation

[0016] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. In addition, the forms of the various structures described in the following embodiments are merely illustrative. The intelligent control system for flue gas purification and ammonia injection of a waste incinerator involved in the present invention is not limited to the structures described in the following embodiments. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] Reference Figure 1 This invention provides an intelligent control system for ammonia injection in flue gas purification of a waste incinerator, including a data acquisition unit, a signal unit, a NOx optimization unit, an SNCR control unit, an SCR control unit, a flue gas control unit, and a diagnostic unit. The data acquisition unit collects process parameters during denitrification in real time. The signal unit performs quality judgment on the collected signals and transmits valid signals to the NOx optimization unit. The NOx optimization unit calculates the predicted total ammonia usage Q and allocates it as SNCR ammonia usage Q1 and SCR ammonia usage Q2, respectively, and outputs them to the SNCR control unit and the SCR control unit. The SNCR control unit controls the SNCR ammonia flow rate and soft water ratio according to the SNCR ammonia usage Q1. The SCR control unit controls the SCR ammonia flow rate according to the SCR ammonia usage Q2. The flue gas control unit controls the SCR flue gas temperature. The diagnostic unit performs safety protection actions when the system is abnormal.

[0018] In this embodiment, the application achieves fully automated control of the two-stage denitrification process of SNCR and SCR through modular division of labor and collaborative work of each unit. Each unit has a clear responsibility and a clear data flow. The NOx optimization unit, as the decision-making core, makes the two-stage denitrification an organic whole rather than two independent subsystems. Moreover, it can automatically adjust during operation without the need for frequent intervention by operators.

[0019] Reference Figure 1 The process parameters collected in real time by the acquisition unit include: NOx concentration setpoint, measured NOx concentration, flue gas flow rate, flue gas oxygen content, flue gas velocity, furnace temperature, SCR inlet flue gas temperature, SCR outlet flue gas temperature, ammonia water flow rate, soft water flow rate, and ammonia slip concentration. The signal unit performs quality judgment on the signals collected by the acquisition unit, detecting whether the signal change rate exceeds a preset threshold or whether the signal exceeds the measurement range. If it exceeds the threshold or exceeds the measurement range, it is judged as a signal fault and automatically rejected. If it does not exceed the preset threshold or does not exceed the measurement range, it is transmitted normally.

[0020] In this embodiment, the parameters collected by the acquisition unit cover all the key variables required for the denitrification reaction. The set value and measured value of NOx concentration constitute a control feedback closed loop. Flue gas flow rate, oxygen content, flow rate, and furnace temperature are used to establish an ammonia-nitrogen molar ratio mechanism model to calculate the theoretical ammonia water demand. The flue gas temperatures at the SCR inlet and outlet are used to ensure catalyst activity conditions. The ammonia water and soft water flow rates are used for closed-loop execution of ammonia injection. The ammonia slip concentration is used to correct the ammonia injection amount to prevent over-injection. The complete parameter acquisition provides a sufficient data foundation for the time-average prediction of NOx optimization unit, self-learning of ammonia water usage, and coordinated allocation of SNCR / SCR. In addition, the signal unit processes fault signals to ensure the accuracy of subsequent processing.

[0021] Reference Figure 1 The NOx optimization unit monitors the current instantaneous value A of NOx concentration and the historical average value B within the past time period T in real time. It calculates the predicted average concentration D of NOx concentration to be reached in the remaining time period according to the constraint relationship based on the hourly average value. The constraint relationship is [B×T+D×(60-T)] / 60≤S, where S is the hourly average value setpoint of NOx concentration. The average concentration D is used as the predicted control target at the current moment. The difference between A and D is calculated. When the absolute value of the difference exceeds the preset dead zone, the ammonia water usage adjustment is initiated. The theoretical ammonia water demand R is calculated based on the flue gas flow rate F, the target removal amount, and the ammonia nitrogen chemical reaction molar ratio. The theoretical value is corrected by the correction coefficient k updated by sliding the data of the most recent 72 hours of operation to obtain the predicted value Q of total ammonia water usage, where Q=k×R, the target removal amount is the difference between the instantaneous value A and the average concentration D, and 60 represents 60 minutes per hour.

[0022] In this embodiment, the present application solves the technical problem that conventional systems, which rely solely on instantaneous values ​​for adjustment, struggle to guarantee hourly average values ​​are met through time-average predictive control. The NOx setpoint is S = 40 mg / Nm³. 3 For example, if the historical average value B = 38 mg / Nm³ has been recorded for the past 30 minutes. 3 The current instantaneous value A = 55 mg / Nm 3 Therefore, calculations using the formula show that D only needs to be controlled at 42 mg / Nm³ for the next 30 minutes. 3 The following will ensure that the average concentration throughout the hour does not exceed 40 mg / Nm³. 3 The predicted target D = 42 mg / Nm 3 Below the current instantaneous value of 55 mg / Nm 3 This application initiates ammonia increment adjustment to achieve "pre-emptive prediction and early intervention" rather than "post-event remediation." Simultaneously, the 72-hour sliding window self-learning enables the correction coefficient k to track equipment aging and changes in operating conditions, matching the theoretical model with actual operating conditions, making the prediction of total ammonia consumption Q more accurate, and preventing the fixed model from failing after operating condition drift.

[0023] Reference Figure 1 The NOx optimization unit is based on the ammonia-nitrogen molar ratio model. It updates the model parameters online using the most recent 72 hours of operating data as a sliding time window, dynamically evaluates the current denitrification efficiency of SNCR and SCR, and allocates the predicted total ammonia water usage Q to the SNCR control unit and the SCR control unit. The SNCR control unit and the SCR control unit respectively obtain the SNCR ammonia water usage Q1 and the SCR ammonia water usage Q2, and Q = Q1 + Q2. The calculation formula for the SNCR ammonia water usage Q1 is Q1 = β × Q, where β is the allocation coefficient. The calculation formula for the SCR ammonia water usage Q2 is Q2 = (1 - β) × Q, and the value range of the allocation coefficient β is 0.3 to 0.7.

[0024] In this embodiment, the application continuously evaluates the real-time changes in the efficiency of the two-stage denitrification through a 72-hour sliding window. When the temperature window of the SNCR efficiency zone is good, β takes a higher value (e.g., 0.6), and the lower-cost SNCR is preferentially used for denitrification. When the SNCR temperature window is not ideal, β takes a lower value (e.g., 0.4), and more ammonia water is allocated to the SCR to avoid excessive ammonia injection in the low-temperature and low-efficiency zone of the SNCR, which would cause waste and ammonia escape. The value range of β from 0.3 to 0.7 ensures that no single-stage denitrification device is allocated too low or too high ammonia water, thus ensuring process safety.

[0025] Reference Figure 1The SNCR control unit dynamically calculates the soft water flow rate setpoint RS based on the SNCR ammonia water usage Q1 output by the NOx optimization unit and the measured value of the atomization mixing pressure. The calculation formula is RS=WZ-Q1, where WZ is the target value of the total atomization flow rate, and the lower limit of the soft water flow rate setpoint RS is not less than 50% of Q1.

[0026] In this embodiment, to ensure the atomization effect of the SNCR spray gun, ammonia water needs to be mixed with soft water before spraying. If the soft water flow rate is too small, the ammonia water cannot be fully atomized, resulting in insufficient spray range, uneven mixing of the reducing agent and flue gas, and a decrease in denitrification efficiency. If the soft water flow rate is too large, the ammonia water concentration will be diluted, reducing the reaction efficiency. This application dynamically calculates the soft water flow rate RS based on the SNCR ammonia water dosage Q1, and maintains a reasonable RS / Q1 ratio (not less than 50%) when the ammonia water dosage fluctuates. At the same time, the measured atomization mixing pressure value is used to correct WZ in a closed loop to cope with disturbances such as nozzle wear and changes in pipeline resistance, ensuring that the spray gun always works in the optimal atomization pressure range.

[0027] Reference Figure 1 The SCR control unit receives the SCR ammonia dosage Q2 output by the NOx optimization unit, and calculates a correction amount XZ based on the deviation between the measured ammonia slip concentration at the SCR outlet and the target value. When the measured ammonia slip is greater than the target value, the correction amount XZ is negative; when the measured ammonia slip is less than the target value, the correction amount XZ is positive, and the correction amount is limited to ±10% of Q2. Q2 is then summed with the correction amount XZ as the total setpoint. A model predictive control algorithm is used to adjust the opening of the SCR ammonia regulating valve to control the ammonia slip concentration at 8 mg / Nm³. 3 In the following, when calculating the correction amount XZ in the SCR control unit, the deviation value PX is first calculated. When calculating the deviation value PX, the ammonia slip target value is set to TM, and the measured value is SC. Then the formula for calculating the deviation value PX is PX=SC-TM. When the deviation value PX>0, the correction amount XZ=-XS×PX. When the deviation value PX≤0, the correction amount XZ=XS×|PX|, where XS is the correction coefficient.

[0028] In this embodiment, ammonia slip is a direct indicator of whether ammonia injection is excessive. When the measured value is higher than the target value, it indicates that the reducing agent is excessive, and the correction amount is automatically negative to reduce ammonia injection. When the measured value is lower than the target value, it indicates that there is still room for increasing the amount, and the correction amount is automatically positive to increase ammonia injection. The ±10% limit prevents excessive single correction from causing system oscillation. The model predictive control algorithm overcomes the time delay between ammonia injection and ammonia slip response. The correction coefficient XS determines the sensitivity of the correction, with TM=3mg / Nm 3 Measured SC = 3.5 mg / Nm 3 For example, PX = +0.5 mg / Nm 3If the correction is negative, immediately reduce ammonia injection when SC = 2.5 mg / Nm³. 3 At that time, PX = -0.5 mg / Nm 3 If the correction amount is positive and the ammonia injection is moderately increased, this application can provide a predictive reduction signal. When the ammonia escape concentration change rate continues to rise, it indicates that it is approaching the over-injection state. At this time, even if the current absolute value has not exceeded the standard, a reduction signal will be output in advance to achieve proactive control rather than passive response, effectively avoiding short-term peak exceedance of ammonia escape.

[0029] Reference Figure 1 The flue gas control unit adopts an adaptive PID control method, which automatically adjusts the flue gas temperature entering the SCR device based on the comparison between the measured value of the flue gas temperature at the SCR inlet and the optimal reaction temperature window. The optimal reaction temperature window is 180℃~190℃. The PID parameters are automatically adjusted according to the temperature deviation and the rate of change of the deviation. When the temperature deviation is greater than 10℃, the proportional gain is increased, and when the temperature deviation is less than 3℃, the integral gain is increased. When the SCR inlet temperature is lower than the preset low temperature threshold of 170℃, the opening command of the SCR ammonia water regulating valve is automatically blocked, and a low temperature alarm is triggered at the same time.

[0030] In this embodiment, the SCR catalyst activity is significantly affected by temperature. When the temperature is too low, the catalyst activity is insufficient and the denitrification efficiency decreases. When the temperature is too high, the catalyst thermal aging is accelerated. By stabilizing the temperature within the optimal window of 180℃ to 190℃, the SCR denitrification efficiency can be ensured to remain stable at the design value (70% to 90%). The adaptive PID dynamically adjusts the control parameters according to the deviation. When the deviation is large, the proportional action is enhanced for a fast response, and when the deviation is small, the integral action is enhanced to eliminate residual error. When the temperature is below 170℃, the ammonia water injection command is automatically blocked to prevent ammonia injection from failing to react fully under low temperature conditions and directly penetrating the catalyst layer, causing ammonia escape spikes and catalyst micropore blockage.

[0031] Reference Figure 1When the system optimization or equipment affecting automatic control malfunctions, the diagnostic unit seamlessly switches all affected equipment to manual control mode and triggers audible and visual alarms. When an automatic control loop is disconnected due to excessive signal deviation or equipment failure, an independent level-based voice alarm is triggered. The unit performs speed limiting and accuracy checks on manually set control target values, rejecting input when the set value exceeds the normal operating range. When the acquired signal exhibits jitter or disconnection, it automatically handles bad values, seamlessly switching the corresponding control loop to manual mode and triggering an alarm. The diagnostic unit performs fault handling according to priority: First priority: When the SCR ammonia regulating valve position feedback is detected as lost, all automatic regulating loops are seamlessly switched to manual mode within 1 second, triggering a red flashing alarm and simultaneously broadcasting the voice fault content. Second priority: When a redundant signal is detected as faulty, the faulty signal is automatically discarded and switched to a backup signal; the corresponding control loop is switched to manual mode and an alarm is triggered only when there is no backup signal and the current signal is abnormal. Third priority: When the manually input NOx concentration set value exceeds 20–80 mg / Nm³... 3 If the input is not within the safe range, the input will be rejected and a prompt box will pop up.

[0032] In this embodiment, the application automatically and seamlessly switches to manual mode when equipment fails, preventing the control system from malfunctioning under fault conditions. The voice alarm differs from conventional DCS screen alarms, ensuring that operators can perceive abnormalities immediately in noisy control room environments. Bad value handling ensures that a single signal fault will not cause the entire circuit to malfunction, guaranteeing a safe transition and manual controllability under abnormal operating conditions. The three-level priority division of this application gives fault handling a processing order. The first priority is for serious faults at the actuator level, which quickly switches within 1 second and simultaneously broadcasts the specific content via voice, ensuring that operators can take manual intervention immediately. This is the most urgent protective action. The second priority is for general faults at the instrument signal level. When redundant configuration is used, it automatically switches without manual intervention and only switches to manual mode when there is no backup signal, avoiding unnecessary automatic exit. The third priority is for manual input errors, which prevents risks from occurring by rejecting input and providing prompts.

[0033] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented in software, the above embodiments can be implemented, in whole or in part, as a computer program product. The units and algorithm steps of the various examples described in the embodiments can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0034] In the several embodiments provided in this application, it should be understood that the disclosed systems, apparatuses, and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0035] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the technical scope disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

[0036] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An intelligent control system for ammonia injection in flue gas purification of a waste incinerator, characterized in that: The system includes a data acquisition unit, a signal unit, a NOx optimization unit, an SNCR control unit, an SCR control unit, a flue gas control unit, and a diagnostic unit. The data acquisition unit collects process parameters during denitrification in real time. The signal unit performs quality judgment on the collected signals and transmits valid signals to the NOx optimization unit. The NOx optimization unit calculates the predicted total ammonia usage Q and allocates it as SNCR ammonia usage Q1 and SCR ammonia usage Q2, respectively, and outputs them to the SNCR control unit and the SCR control unit. The SNCR control unit controls the SNCR ammonia flow rate and soft water ratio based on the SNCR ammonia usage Q1. The SCR control unit controls the SCR ammonia flow rate based on the SCR ammonia usage Q2. The flue gas control unit controls the SCR flue gas temperature. The diagnostic unit performs safety protection actions when the system malfunctions.

2. The intelligent control system for ammonia injection and purification of flue gas in a waste incinerator according to claim 1, characterized in that: The process parameters collected in real time by the acquisition unit include: NOx concentration setpoint, measured NOx concentration, flue gas flow rate, flue gas oxygen content, flue gas velocity, furnace temperature, SCR inlet flue gas temperature, SCR outlet flue gas temperature, ammonia water flow rate, soft water flow rate, and ammonia slip concentration. The signal unit performs quality judgment on the signals collected by the acquisition unit, detecting whether the signal change rate exceeds a preset threshold or whether the signal exceeds the measurement range. If it exceeds or exceeds the threshold, it is judged as a signal fault and automatically rejected. If it does not exceed the preset threshold or does not exceed the measurement range, it is transmitted normally.

3. The intelligent control system for ammonia injection and purification of flue gas in a waste incinerator according to claim 1, characterized in that: The NOx optimization unit monitors the current instantaneous value A of NOx concentration and the historical average value B within the past time period T in real time. It calculates the predicted average concentration D of NOx concentration to be reached in the remaining time period according to the constraint relationship based on the hourly average. The constraint relationship is [B×T+D×(60-T)] / 60≤S, where S is the hourly average value setpoint of NOx concentration. The average concentration D is used as the predicted control target at the current moment. The difference between A and D is calculated. When the absolute value of the difference exceeds the preset dead zone, the ammonia water usage adjustment is initiated. The theoretical ammonia water demand R is calculated based on the flue gas flow rate F, the target removal amount, and the ammonia nitrogen chemical reaction molar ratio. The theoretical value is corrected by the correction coefficient k updated by sliding the data of the most recent 72 hours of operation to obtain the predicted value Q of total ammonia water usage, where Q=k×R.

4. The intelligent control system for ammonia injection and purification of flue gas in a waste incinerator according to claim 3, characterized in that: The NOx optimization unit is based on the ammonia-nitrogen molar ratio model. It updates the model parameters online using the most recent 72 hours of operating data as a sliding time window, dynamically evaluates the current denitrification efficiency of SNCR and SCR, and allocates the predicted total ammonia water usage Q to the SNCR control unit and the SCR control unit. The SNCR control unit and the SCR control unit respectively obtain the SNCR ammonia water usage Q1 and the SCR ammonia water usage Q2, and Q = Q1 + Q2. The calculation formula for the SNCR ammonia water usage Q1 is Q1 = β × Q, where β is the allocation coefficient. The calculation formula for the SCR ammonia water usage Q2 is Q2 = (1 - β) × Q.

5. The intelligent control system for ammonia injection and purification of flue gas in a waste incinerator according to claim 1, characterized in that: The SNCR control unit dynamically calculates the soft water flow rate setpoint RS based on the SNCR ammonia water usage Q1 output by the NOx optimization unit and the measured value of the atomization mixing pressure. The calculation formula is RS=WZ-Q1, where WZ is the target value of the total atomization flow rate, and the lower limit of the soft water flow rate setpoint RS is not less than 50% of Q1.

6. The intelligent control system for ammonia injection and purification of flue gas in a waste incinerator according to claim 1, characterized in that: The SCR control unit receives the SCR ammonia dosage Q2 output by the NOx optimization unit and calculates a correction amount XZ based on the deviation between the measured ammonia slip concentration at the SCR outlet and the target value. When the measured ammonia slip is greater than the target value, the correction amount XZ is negative; when the measured ammonia slip is less than the target value, the correction amount XZ is positive, and the correction amount is limited to ±10% of Q2. Q2 is then summed with the correction amount XZ as the total setpoint. A model predictive control algorithm is used to adjust the opening of the SCR ammonia regulating valve to control the ammonia slip concentration at 8 mg / Nm³. 3 the following.

7. The intelligent control system for ammonia injection and purification of flue gas in a waste incinerator according to claim 6, characterized in that: Within the SCR control unit, when calculating the correction amount XZ, the deviation value PX is first calculated. When calculating the deviation value PX, the ammonia slip target value is set to TM, and the measured value is SC. Then, the formula for calculating the deviation value PX is PX=SC-TM. When the deviation value PX>0, the correction amount XZ=-XS×PX. When the deviation value PX≤0, the correction amount XZ=XS×|PX|, where XS is the correction coefficient.

8. The intelligent control system for ammonia injection and purification of flue gas in a waste incinerator according to claim 1, characterized in that: The flue gas control unit adopts an adaptive PID control method, which automatically adjusts the flue gas temperature entering the SCR device based on the comparison between the measured value of the SCR inlet flue gas temperature and the optimal reaction temperature window. The optimal reaction temperature window is 180℃~190℃. The PID parameters are automatically adjusted according to the temperature deviation and the rate of change of the deviation. When the temperature deviation is greater than 10℃, the proportional gain is increased, and when the temperature deviation is less than 3℃, the integral gain is increased. When the SCR inlet temperature is lower than the preset low temperature threshold of 170℃, the opening command of the SCR ammonia water regulating valve is automatically blocked, and a low temperature alarm is triggered at the same time.

9. The intelligent control system for ammonia injection and purification of flue gas in a waste incinerator according to claim 1, characterized in that: When the system optimization or equipment affecting automatic control malfunctions, the diagnostic unit seamlessly switches all affected equipment to manual control mode and triggers audible and visual alarms; when an automatic control loop is disconnected due to excessive signal deviation or equipment failure, an independent level voice alarm is triggered; the unit limits the speed and judges the correctness of manually set control target values, and rejects input when the set value exceeds the normal operating range; when the acquired signal shows jitter or disconnection, it automatically performs bad value processing, seamlessly switches the corresponding control loop to manual mode, and triggers an alarm.

10. The intelligent control system for ammonia injection and purification of flue gas in a waste incinerator according to claim 1, characterized in that: The diagnostic unit performs fault handling according to priority: First priority: when the valve position feedback of the SCR ammonia regulating valve is lost, all automatic regulating loops are switched to manual mode without disturbance within 1 second, triggering a red flashing alarm and simultaneously broadcasting the fault message; Second priority: when a fault is detected in one redundant signal, the faulty signal is automatically eliminated and switched to the backup signal, and the corresponding control loop is switched to manual and an alarm is triggered only when there is no backup signal and the current signal is abnormal; Third priority: when the manually input NOx concentration setpoint exceeds 20-80 mg / Nm³... 3 If the input is not within the safe range, the input will be rejected and a prompt box will pop up.

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