Accurate ammonia spraying control method and system suitable for coke oven flue gas denitration

Abstract

The invention discloses a precise ammonia spraying control method and system suitable for coke oven flue gas denitration, and the method comprises the steps: collecting historical data and real-time data of coke oven flue gas flow and NOx concentration, carrying out the modeling of the collected historical data of the flue gas flow and NOx concentration through a time series prediction algorithm, and carrying out the calculation of the model; the flue gas flow and the NOx emission value in a period of time in the future are predicted, the corresponding ammonia spraying amount is calculated based on the flue gas flow and the NOx emission value predicted by the model, the system monitors the actual NOx emission value in real time and compares the actual NOx emission value with the predicted value, and if obvious deviation exists, the ammonia spraying amount is determined. If yes, the prediction model is corrected in the next period, the calculated ammonia spraying amount data is transmitted to a denitration master control system, the denitration master control system automatically adjusts an ammonia supply valve, if the denitration precise ammonia spraying control system breaks down, an alarm is triggered immediately, the mode is automatically switched to a manual control mode, and the manual control mode is switched to a manual control mode. Accurate control and stability of total ammonia regulation of the denitration system are realized.

Description

Technical Field

[0001] The present invention relates to the technical field of industrial pollution control, and in particular to a precise ammonia injection control method and system suitable for denitrification of coke oven flue gas. Background Art

[0002] During the production process of the coking plant, the coke oven flue gas contains a relatively high concentration of nitrogen oxides (NOx), causing serious pollution to the environment.

[0003] At present, the medium and low temperature SCR denitrification process is generally sampled to purify NOx in flue gas. Since the NOx value in coke oven flue gas ...

[0004] Therefore, there is an urgent need for a denitrification control system that can predict NOx emissions based on historical data and accurately adjust the amount of ammonia injection to improve the denitrification effect and reduce the ammonia escape rate. Summary of the invention

[0005] The purpose of this section is to summarize some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this section and the specification abstract and the invention title of this application to avoid blurring the purpose of this section, the specification abstract and the invention title, and such simplifications or omissions cannot be used to limit the scope of the present invention.

[0006] Therefore, the purpose of the present invention is to provide a precise ammonia injection system and a control method suitable for coke oven flue gas denitrification, so as to achieve accurate control of the total ammonia regulation of the denitrification system, and at the same time improve the timeliness, accuracy, reliability and stability of the denitrification ammonia injection system.

[0007] To solve the above technical problems, according to one aspect of the present invention, the present invention provides the following technical solutions:

[0008] A precise ammonia injection control method suitable for coke oven flue gas denitrification comprises the following steps:

[0009] S1. Collect historical and real-time data of coke oven flue gas flow and NOx concentration, and store them in the on-site database;

[0010] S2. Use time series prediction algorithm to model the collected historical data of flue gas flow and NOx concentration to predict the NOx emission value in the future;

[0011] S3. Based on the NOx emission value predicted by the model, the corresponding ammonia injection amount is calculated. The system monitors the actual NOx emission value in real time and compares it with the predicted value. If there is a significant deviation, the prediction model will be corrected in the next cycle.

[0012] S4. The calculated ammonia injection amount data is transmitted to the denitrification main control system, which automatically adjusts the ammonia injection valve. If the denitrification precise ammonia injection system fails, an alarm is immediately triggered and the system automatically switches to manual control mode.

[0013] As a preferred solution of the precise ammonia injection control method for coke oven flue gas denitrification described in the present invention, in step S1, the NOx data is stored in the DCS system, and the data is collected through the modbus TCP protocol.

[0014] As a preferred solution of the precise ammonia injection control method for coke oven flue gas denitrification described in the present invention, in step S2, the time series prediction algorithm is used to model the collected flue gas flow and NOx concentration historical data, and the specific steps of predicting the NOx emission value in the future period are as follows:

[0015] Clean the NOx time series training data, remove outliers, fill in missing values, and ensure the accuracy and completeness of the data;

[0016] Resample the data according to a certain time period. Divide the data into training sets and test sets for model training and verification;

[0017] The TPR time series prediction algorithm is used to train the data, and the error of the model prediction is verified on the test set. The error uses the MASE mean absolute ratio error, and the calculation formula is as follows:

[0018]

[0019] Where Ft is the predicted value at time t, At is the actual value at time t, n is the number of predicted time points, and N is the total number of actual values;

[0020] According to the evaluation results, all the training data are used for training to form the final model, which is fixed as the model for actual total NOx emission prediction.

[0021] As a preferred solution of the precise ammonia injection control method for coke oven flue gas denitrification described in the present invention, in step S3, the system monitors the actual NOx emission value in real time and compares it with the predicted value. If there is an obvious deviation, the specific steps of correcting the prediction model in the next cycle are as follows:

[0022] The predicted values ​​of flue gas flow and NOx concentration are compared with the actual operating values, and the total amount of ammonia injection is corrected once. Then, the total amount of ammonia injection is corrected twice according to the hourly average values ​​of NOx and ammonia escape actually emitted from the CEMS exhaust port.

[0023] During the actual operation, the predicted values ​​of flue gas flow and NOx concentration are compared with the actual operating values. The total ammonia supply is corrected once according to the difference. Then, based on the hourly average values ​​of NOx and ammonia escape actually emitted from the CEMS exhaust port, the total ammonia supply is corrected twice to achieve the hourly average environmental protection emission indicators.

[0024] As a preferred scheme of the precise ammonia injection control method suitable for coke oven flue gas denitrification described in the present invention, the ammonia injection amount is calculated in real time, and the upper and lower limits of the ammonia injection amount are set according to the on-site operating conditions. The first correction is made by comparing the difference between the predicted value and the actual measured value. If the absolute value of the difference is greater than a certain limit, the data input for the next prediction is adjusted. The second correction is only made for the second half of each hour, and the correction range is calculated with reference to the excess emission range in the first half.

[0025] A precise ammonia injection control system suitable for coke oven flue gas denitrification, to realize the precise ammonia injection control method suitable for coke oven flue gas denitrification as claimed in any one of claims 1 to 5, characterized in that it comprises:

[0026] The data collection module is configured to: collect historical data and real-time data of coke oven flue gas flow and NOx concentration, and store them in a field database;

[0027] The model training prediction module is configured to: use the time series prediction algorithm to model the collected flue gas flow and NOx concentration historical data to predict the NOx emission value in the future;

[0028] The calculation and correction module is configured to: calculate the corresponding ammonia injection amount based on the NOx emission value predicted by the model, and the system monitors the actual NOx emission value in real time and compares it with the predicted value. If there is a significant deviation, the prediction model will be corrected in the next cycle;

[0029] The control module is configured to: transmit the calculated ammonia injection amount data to the denitrification main control system, and the denitrification main control system automatically adjusts the ammonia injection valve. If the denitrification precise ammonia injection system fails, an alarm is immediately triggered and the system automatically switches to manual control mode.

[0030] As a preferred solution of the precise ammonia injection control system suitable for coke oven flue gas denitrification described in the present invention, it also includes a kinetic catalytic reaction platform module, which is configured to: simulate the actual catalyst performance of the target denitrification device, combine the experimental data of the catalyst manufacturer and the operation data of the coking plant, and fit it into a multi-dimensional continuous reaction model platform through a neural network intelligent algorithm. It is beneficial to optimize the operation of the precise ammonia injection prediction control system through the reaction model platform before production operation, which has a guiding role in actual production;

[0031] Among them, the data includes flue gas flow, denitrification reaction temperature, catalyst attenuation parameters, denitrification inlet NOx value, denitrification outlet NOx value, total ammonia supply and ammonia escape emission.

[0032] Compared with the prior art, the present invention has the following beneficial effects: by combining the time series prediction algorithm, the present invention can predict the NOx trend of the denitrification inlet in advance, accurately adjust the amount of ammonia spray, and improve the denitrification efficiency and ammonia utilization rate. The kinetic catalytic reaction model platform is used for simulation operation to optimize the precise ammonia spray control system and improve its operating stability. The introduction of correction logic improves the system's ability to respond to changes in actual operating conditions, and the upper and lower limits of the ammonia spray amount ensure the safe operation of the system. At the same time, the design of automatic fault alarm and switching to manual mode improves the reliability of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the present invention will be described in detail below in combination with the accompanying drawings and detailed embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative labor. Among them:

[0034] Figure 1 The present invention is a flow chart of a precise ammonia injection control method suitable for denitrification of coke oven flue gas. DETAILED DESCRIPTION

[0035] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0036] Secondly, the present invention is described in detail with reference to schematic diagrams. When describing the embodiments of the present invention in detail, for the sake of convenience, the cross-sectional diagrams showing the device structure will not be partially enlarged according to the general scale, and the schematic diagrams are only examples, which should not limit the scope of protection of the present invention. In addition, in actual production, the three-dimensional dimensions of length, width and depth should be included.

[0037] To make the objectives, technical solutions and advantages of the present invention more clear, the embodiments of the present invention will be further described in detail below with reference to the accompanying drawings.

[0038] The present invention provides a precise ammonia injection system suitable for coke oven flue gas denitration and a control method thereof, which realizes accurate control of total ammonia regulation of the denitration system and simultaneously improves the timeliness, accuracy, reliability and stability of the denitration ammonia injection system.

[0039] Figure 1 The flowchart of the precise ammonia injection control method for coke oven flue gas denitrification according to the present invention is shown. Figure 1 , a precise ammonia injection control method applicable to coke oven flue gas denitrification in this embodiment, the specific steps are as follows:

[0040] S1. Collect historical data and real-time data of coke oven flue gas flow and NOx concentration, and store them in a field database, wherein the NOx data is stored in a control system and the data is collected through the modbus TCP protocol.

[0041] S2. Use the time series prediction algorithm to model the collected historical data of flue gas flow and NOx concentration to predict the NOx emission value in the future, including:

[0042] Clean the NOx time series training data, remove outliers, fill in missing values, and ensure the accuracy and completeness of the data;

[0043] Resample the data according to a certain time period. Divide the data into training sets and test sets for model training and verification;

[0044] The TPR time series prediction algorithm is used to train the data, and the error of the model prediction is verified on the test set. The error uses the MASE mean absolute ratio error, and the calculation formula is as follows:

[0045]

[0046] Where Ft is the predicted value at time t, At is the actual value at time t, n is the number of predicted time points, and N is the total number of actual values;

[0047] According to the evaluation results, all the training data are used for training to form the final model, which is fixed as the model for actual total NOx emission prediction.

[0048] S3. Based on the NOx emission value predicted by the model, the corresponding ammonia injection amount is calculated. The system monitors the actual NOx emission value in real time and compares it with the predicted value. If there is an obvious deviation, the prediction model will be corrected in the next cycle. Specifically, the predicted value of flue gas flow and NOx concentration is compared with the actual operating value. The total ammonia supply is corrected once according to the difference. Then, the total ammonia supply is corrected twice according to the hourly average value of NOx and ammonia escape actually emitted from the CEMS outlet. More specifically: the ammonia injection amount is calculated in real time, and the upper and lower limits of the ammonia injection amount are set according to the on-site operation conditions. The first correction is made by comparing the difference between the predicted value and the actual measured value. If the absolute value of the difference is greater than a certain limit, the data input for the next prediction is adjusted. The second correction is only made for the second half of each hour, and the correction range is calculated with reference to the excess emission range in the first half.

[0049] S4. The calculated ammonia injection amount data is transmitted to the denitrification main control system, which automatically adjusts the ammonia supply valve. If the denitrification precise ammonia injection system fails, an alarm is immediately triggered and the system automatically switches to manual control mode.

[0050] In order to implement the above method steps, the present invention also provides a precise ammonia injection control system suitable for coke oven flue gas denitrification, which specifically includes a data collection module, a model training prediction module, a calculation correction module and a control module.

[0051] The data collection module is configured to: collect historical data and real-time data of coke oven flue gas flow and NOx concentration, and store them in a field database;

[0052] The model training prediction module is configured to: use the time series prediction algorithm to model the collected flue gas flow and NOx concentration historical data to predict the NOx emission value in the future;

[0053] The calculation and correction module is configured to: calculate the corresponding ammonia injection amount based on the NOx emission value predicted by the model, and the system monitors the actual NOx emission value in real time and compares it with the predicted value. If there is a significant deviation, the prediction model will be corrected in the next cycle;

[0054] The control module is configured to transmit the calculated ammonia injection amount data to the denitrification main control system, which automatically adjusts the ammonia supply valve. If the denitrification precise ammonia injection system fails, an alarm is immediately triggered and the system automatically switches to manual control mode.

[0055] Furthermore, it also includes a kinetic catalytic reaction platform module, which is configured to: simulate according to the actual catalyst performance of the target denitrification device, combine the experimental data of the catalyst manufacturer and the operation data of the coking plant, and fit it into a multi-dimensional continuous reaction model through a neural network intelligent algorithm, wherein the data includes flue gas flow, denitrification reaction temperature, catalyst attenuation parameters, denitrification inlet NOx value, denitrification outlet NOx value, total ammonia supply and ammonia escape emission.

[0056] Although the present invention has been described above with reference to the embodiments, various modifications may be made thereto and parts thereof may be replaced by equivalents without departing from the scope of the present invention. In particular, as long as there is no structural conflict, the various features in the embodiments disclosed in the present invention may be used in combination with each other in any manner, and the fact that these combinations are not exhaustively described in this specification is only for the sake of omitting space and saving resources. Therefore, the present invention is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A precise ammonia injection control method suitable for denitrification of coke oven flue gas, characterized in that: The steps include: S1. Collect historical and real-time data of coke oven flue gas flow and NOx concentration, and store them in the on-site database; S2. Use time series prediction algorithm to model the collected historical data of flue gas flow and NOx concentration to predict the NOx emission value in the future; S3. Based on the NOx emission value predicted by the model, the corresponding ammonia injection amount is calculated. The system monitors the actual NOx emission value in real time and compares it with the predicted value. If there is a significant deviation, the prediction model will be corrected in the next cycle. S4. The calculated ammonia injection amount data is transmitted to the denitrification main control system, which adjusts the ammonia supply valve. If the precise ammonia injection system fails, an alarm is triggered immediately and the system automatically switches to manual control mode.

2. The precise ammonia injection control method for coke oven flue gas denitrification according to claim 1, characterized in that: In step S1, the NOx data is stored in the DCS system, and the data is collected through the modbus TCP protocol.

3. The precise ammonia injection control method for coke oven flue gas denitrification according to claim 1, characterized in that: In step S2, the time series prediction algorithm is used to model the collected historical data of flue gas flow and NOx concentration. The specific steps for predicting the NOx emission value in the future are as follows: Clean the NOx time series training data, remove outliers, fill in missing values, and ensure the accuracy and completeness of the data; Resample the data according to a certain time period. Divide the data into training sets and test sets for model training and verification; The TPR time series prediction algorithm is used to train the data, and the error of the model prediction is verified on the test set. The error uses the MASE mean absolute ratio error, and the calculation formula is as follows: Where Ft is the predicted value at time t, At is the actual value at time t, n is the number of predicted time points, and N is the total number of actual values; According to the evaluation results, all training data are used for training to form the final model, which is fixed as the model for actual total NOx emission prediction.

4. The precise ammonia injection control method for coke oven flue gas denitrification according to claim 1, characterized in that: In step S3, the system monitors the actual NOx emission value in real time and compares it with the predicted value. If there is a significant deviation, the specific steps for correcting the prediction model in the next cycle are as follows: During operation, the predicted values ​​of flue gas flow and NOx concentration are compared with the actual operating values. The total ammonia supply is corrected once according to the difference, and then the total ammonia supply is corrected twice according to the actual NOx emissions from the CEMS exhaust port and the hourly average of ammonia escape.

5. The precise ammonia injection control method for coke oven flue gas denitrification according to claim 4, characterized in that: The ammonia injection amount is calculated in real time, and the upper and lower limits of the ammonia injection amount are set according to the on-site operating conditions. The first correction is made by comparing the difference between the predicted value and the actual measured value. If the absolute value of the difference is greater than a certain limit, the data input for the next prediction is adjusted. The second correction is only made for the second half of each hour, and the correction range is calculated based on the excess emission range in the first half.

6. A precise ammonia injection control system suitable for coke oven flue gas denitrification, to realize the precise ammonia injection control method suitable for coke oven flue gas denitrification as claimed in any one of claims 1 to 5, characterized in that: include: The data collection module is configured to: collect historical data and real-time data of coke oven flue gas flow and NOx concentration, and store them in a field database; The model training prediction module is configured to: use the time series prediction algorithm to model the collected flue gas flow and NOx concentration historical data to predict the NOx emission value in the future; The calculation and correction module is configured to: calculate the corresponding ammonia injection amount based on the NOx emission value predicted by the model, and the system monitors the actual NOx emission value in real time and compares it with the predicted value. If there is a significant deviation, the prediction model will be corrected in the next cycle; The control module is configured to: transmit the calculated ammonia injection amount data to the denitrification main control system, and the denitrification main control system adjusts the ammonia supply valve. If the denitrification main control system fails, an alarm is immediately triggered and the system automatically switches to manual control mode.

7. The precise ammonia injection control system for coke oven flue gas denitrification according to claim 6, characterized in that: It also includes a kinetic catalytic reaction platform module, which is configured to: simulate the actual catalyst performance of the target denitration device, combine the experimental data of the catalyst manufacturer and the operation data of the coking plant, and fit it into a multi-dimensional continuous reaction model platform through a neural network intelligent algorithm; Among them, the reaction model platform data includes flue gas flow, denitrification reaction temperature, catalyst attenuation parameters, denitrification inlet NOx value, denitrification outlet NOx value, total ammonia supply and ammonia escape emission.

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