Carbon source accurate feeding self-control method based on NO3-N feedforward regulation and N2O feedback optimization

Abstract

The invention discloses a carbon source accurate adding self-control method based on NO3--N feedforward regulation and N2O feedback optimization, which comprises the following steps: reading self-check data fed back by a NO3--N sensor and a N2O sensor on line to judge whether the NO3--N sensor and the N2O sensor are normal or not; if the judgment result is normal, a NO3--N measured value detected by a NO3--N sensor is obtained, and the carbon source adding dosage adjusted this time is predicted according to the C / N ratio in the anoxic tank; meanwhile, an N2O measured value detected by an N2O sensor is obtained and used for judging whether the lowest emission standard of N2O in the anoxic tank is met or not, and when the lowest emission standard of N2O in the anoxic tank is not met, the concentration of DO is controlled through an O tank to reduce the concentration of N2O at the tail end of the anoxic tank; if the DO concentration is controlled by the O tank and the N2O concentration of the anoxic tail end cannot be reduced to the lowest emission standard, the carbon source adding dosage is adjusted according to the N2O concentration deviation value of the tail end of the anoxic tank to obtain a new carbon source adding dosage, and the frequency of a dosing pump frequency converter is correspondingly adjusted according to the new carbon source adding dosage to complete the adding operation.

Description

Technical Field

[0001] The present invention belongs to the technical field of carbon emission reduction, and specifically relates to a method based on NO3 - -A self-control method for precise carbon source addition based on N feedforward regulation and N2O feedback optimization. Background Art

[0002] The denitrification process is one of the key steps in biological denitrification of sewage. The influencing factors include carbon source in sewage, temperature, nitrification liquid reflux ratio, etc., among which carbon source is an important influencing factor. In the sewage treatment process, the denitrification process has a high requirement for the carbon-nitrogen ratio (C / N). When the influent biochemical oxygen demand / total nitrogen (BOD5 / TN) is greater than 4, it is considered that the raw water contains sufficient carbon source. However, studies have shown that there is a general problem of insufficient carbon source in the influent of my country's sewage treatment plants. Insufficient soluble organic matter often leads to incomplete denitrification, resulting in substandard TN in the effluent. In order to meet the requirements of the effluent quality of sewage treatment plants, additional organic carbon sources such as methanol and glucose need to be added to the biological treatment system to enhance the biological denitrification effect.

[0003] At the same time, in the sewage treatment process, the more carbon sources, the better. Insufficient addition of external carbon sources will lead to insufficient denitrification; excessive addition of external carbon sources will increase operating costs and the COD load of subsequent treatment processes, leading to the risk of effluent COD exceeding the standard, making it difficult for the sewage treatment system to perform at its best.

[0004] In summary, determining the optimal dosage of carbon source is an important measure for sewage treatment plants to achieve economic, efficient and low-carbon operation. The dosage of added carbon source is affected by many factors in actual operation, such as the volatility of influent quality and water volume of sewage treatment plants, the structure of microbial communities in biochemical systems, etc., which makes the theoretical value calculated by the traditional carbon source addition formula very limited in guiding actual process operation.

[0005] Therefore, there is an urgent need for a NO3 - -The carbon source precise dosing self-control method with N feedforward regulation and N2O feedback optimization determines the carbon source dosage in a more precise and scientific way, helping sewage treatment plants to achieve synergistic efficiency in reducing pollution and carbon emissions. Summary of the invention

[0006] In view of this, the object of the present invention is to provide a method for preparing a novel nanostructured carbon foam based on NO3 - -N feedforward regulation and N2O feedback optimization of carbon source precise dosing self-control method is used to solve the above technical problems.

[0007] In order to achieve the above object, the present invention provides the following technical solutions:

[0008] A NO3-based --N feedforward regulation and N2O feedback optimization of carbon source precise dosing self-control method, including:

[0009] Place NO3 in the anoxic pool in advance - -N sensor, and a N2O sensor placed at the end of the anoxic tank;

[0010] Online reading of NO3 - -Self-test data from N sensor and N2O sensor is used to determine NO3 - -Whether the N sensor and N2O sensor are normal;

[0011] If the result is normal, get NO3 - - NO3 detected by N sensor - -N measurement value, and according to the C / N ratio in the anoxic tank, predict the carbon source dosage for this adjustment;

[0012] At the same time, the N2O measurement value detected by the N2O sensor is obtained to determine whether the minimum emission standard of N2O in the anoxic pool is met, and if it is not met, the DO concentration is controlled by the O pool to reduce the N2O concentration at the end of the anoxic pool;

[0013] If the DO concentration cannot be reduced to the minimum emission standard by controlling the DO concentration in the O pool, the carbon source dosage is adjusted according to the N2O concentration deviation value at the end of the anoxic pool to obtain a new carbon source dosage, and the dosing pump inverter frequency is adjusted accordingly according to the new carbon source dosage to complete the dosing operation.

[0014] Furthermore, a NO3-based - -N feedforward regulation and N2O feedback optimization of carbon source precise dosing self-control method also includes:

[0015] If the judgment result is NO3 - - If either the N sensor or the N2O sensor is abnormal, the sensor will automatically perform self-checking and send a prompt signal to the management personnel if the self-checking fails to restore the sensor to normal;

[0016] Continue working until all abnormal sensor devices return to normal.

[0017] Furthermore, a NO3-based - The carbon source precise dosing self-control method with -N feedforward regulation and N2O feedback optimization also includes: if the N2O measurement value meets the minimum emission standard of N2O at the end of the anoxic tank, or the N2O concentration at the end of the anoxic tank can be reduced to the minimum emission standard by controlling the DO concentration in the O tank, then no carbon source is added, and the operating state of the carbon source precise dosing self-control system after adjusting the DO concentration is maintained.

[0018] Further, obtain NO3 -- NO3 detected by N sensor - -N measured value, and based on the C / N ratio in the anoxic tank, predict the carbon source dosage for this adjustment, including:

[0019] Obtain NO3 - - NO3 detected by N sensor - -N measurement value, used to determine the organic matter and nitrogen concentrations in the anoxic tank, and calculate the C / N ratio in the anoxic tank based on the organic matter and nitrogen concentrations;

[0020] Determine whether the C / N ratio in the anoxic tank exceeds the preset range;

[0021] If not, the carbon source dosage is zero;

[0022] If yes, according to the deviation of the C / N ratio in the anoxic tank from the preset range and the NO3 - -N measured value, predict the carbon source dosage for this adjustment.

[0023] Furthermore, the DO concentration is controlled by the O pool to reduce the N2O concentration at the end of the anoxic pool, including:

[0024] When the N2O concentration at the end of the anoxic pool is higher than the minimum emission standard, the O pool status is obtained; the O pool status includes the DO content status, ammonia nitrogen content status and NO2 - -N accumulation content status;

[0025] According to the state of the O pool, the corresponding adjustment strategy pre-stored in the database is obtained to adjust the DO content in the O pool to reduce the N2O concentration at the end of the anoxic pool.

[0026] Furthermore, the N2O concentration deviation value at the end of the anoxic tank is the difference between the actual detection value of the N2O concentration at the end of the anoxic tank and the minimum emission standard of the N2O concentration.

[0027] Furthermore, a NO3-based - -N feedforward regulation and N2O feedback optimization of carbon source precise dosing self-control method also includes:

[0028] Also includes:

[0029] Generate corresponding dosing control instructions according to the new carbon source dosing dosage;

[0030] The time after the dosing control instruction is generated and transmitted to the dosing pump, and the time when the dosing pump adds the carbon source into the anoxic tank is taken as the lag time;

[0031] Obtain the increasing potential change of N2O concentration at the end of the anoxic pool before and after the lag time as the lag compensation value;

[0032] During the normal carbon source addition process, a number of hysteresis compensation values ​​that change with time are obtained, and when the number of the obtained hysteresis compensation values ​​meets the preset inspection number, a time series is generated according to the obtained hysteresis compensation values;

[0033] According to the time series stationary test method, the data stationary test of the time series is carried out in real time to generate the test result; wherein the time series stationary test method includes one or more combinations of the KPSS test method and the ADF test method;

[0034] When the verification result shows that the lag compensation value in the time series is stable, a dynamic regression model is generated based on the training of all lag compensation values ​​in the time series, and the future lag compensation value is predicted based on the trained dynamic regression model;

[0035] According to the future hysteresis compensation value, the new carbon source dosage is adjusted again to obtain the standard carbon source dosage. According to the standard carbon source dosage, the frequency of the dosing pump inverter is adjusted accordingly to complete the dosing operation.

[0036] Furthermore, a NO3-based - -N feedforward regulation and N2O feedback optimization of carbon source precise dosing self-control method also includes:

[0037] The number of elements in the time series is fixed, and the fixed number is the preset test number. When there is a new lag compensation value ready to be added to the time series, the original elements in the time series follow the first-in-first-out principle, and the elements in the time series are subtracted by one. At the same time, the new lag compensation value is added to the time series after the subtraction operation;

[0038] When the verification result shows that the lag compensation value in the time series is not stable, a new lag compensation value is obtained and added to the time series to form a new time series. According to the time series stability test method, the data stability test is performed on the new time series to generate a new verification result.

[0039] If the verification result still shows that the lag compensation value in the time series is not stable, the above time series updating operation is repeated until the verification result shows that the lag compensation value in the time series is stable.

[0040] Furthermore, a NO3-based - -N feedforward regulation and N2O feedback optimization of carbon source precise dosing self-control method also includes:

[0041] After the dynamic regression model is trained, the lag compensation value that changes with time is continuously obtained and added to the time series to update the time series and judge the stationarity of the updated time series in real time;

[0042] If the updated time series is stable, the lag compensation value newly added to the time series is used to continue training the dynamic regression model;

[0043] If the updated time series is not stationary, temporarily stop predicting the future lag compensation value based on the dynamic regression model, and continue to obtain the lag compensation value that changes with time and add it to the time series until the updated time series is stationary. Delete the variables in the dynamic regression model corresponding to the lag compensation value deleted in the time series to adjust the model parameters to adapt to the new lag compensation value data characteristics, and use the new lag compensation value in the time series to continue training the dynamic regression model.

[0044] The beneficial effects of the present invention are:

[0045] The present invention proposes a method based on NO3 - -N feedforward regulation and N2O feedback optimization of carbon source precise dosing self-control method, to solve the problem of low denitrification efficiency or high operating cost caused by users' difficulty in accurately controlling the dosage of carbon source when there is an imbalance in C / N ratio in sewage. It is beneficial to reduce the input cost in the process of carbon source addition and improve the real-time precise control accuracy of carbon source, thereby reducing the release of N2O in the system, achieving low-cost and high-precision carbon emission reduction, and reducing greenhouse gas emissions.

[0046] Other advantages, objectives and features of the present invention will be described in the following description and will be apparent to those skilled in the art to some extent, or they may be taught from the practice of the present invention. The purposes and other advantages of the present invention may be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0047] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0049] Figure 1 In the embodiment of the present invention, a method based on NO3 - - Flow chart of the control mode of the carbon source precise dosing self-control method with N feedforward regulation and N2O feedback optimization;

[0050] Figure 2 In the embodiment of the present invention, a method based on NO3 - - Schematic diagram of control logic of carbon source precise dosing self-control method with N feedforward regulation and N2O feedback optimization;

[0051] Figure 3 In the embodiment of the present invention, a method based on NO3 - Schematic diagram of the application of the carbon source precise dosing self-control method based on -N feedforward regulation and N2O feedback optimization in the AO process. DETAILED DESCRIPTION

[0052] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0053] like Figure 1 , Figure 2 and Figure 3 As shown, the present invention proposes a method based on NO3 - -N feedforward regulation and N2O feedback optimization of carbon source precise dosing self-control method, including:

[0054] Place NO3 in the anoxic pool in advance - -N sensor, and a N2O sensor placed at the end of the anoxic tank;

[0055] Online reading of NO3 - -Self-test data from N sensor and N2O sensor is used to determine NO3 - -Whether the N sensor and N2O sensor are normal;

[0056] If the result is normal, get NO3 - - NO3 detected by N sensor - -N measurement value, and according to the C / N ratio in the anoxic tank, predict the carbon source dosage for this adjustment;

[0057] At the same time, the N2O measurement value detected by the N2O sensor is obtained to determine whether the minimum emission standard of N2O in the anoxic pool is met, and if it is not met, the DO concentration is controlled by the O pool to reduce the N2O concentration at the end of the anoxic pool;

[0058] If the DO concentration cannot be reduced to the minimum emission standard by controlling the DO concentration in the O pool, the carbon source dosage is adjusted according to the N2O concentration deviation value at the end of the anoxic pool to obtain a new carbon source dosage, and the dosing pump inverter frequency is adjusted accordingly according to the new carbon source dosage to complete the dosing operation;

[0059] The working principle of the above technical solution is: NO3 is placed in the anoxic pool in advance. - -N sensor, and a N2O sensor placed at the end of the anoxic tank;

[0060] Online reading of NO3 - -Self-test data from N sensor and N2O sensor is used to determine NO3- -Whether the N sensor and N2O sensor are normal;

[0061] If the judgment result is NO3 - - If either the N sensor or the N2O sensor is abnormal, the sensor will automatically perform self-checking and send a prompt signal to the management personnel if the self-checking fails to restore the sensor to normal;

[0062] Continue to work until all abnormal sensor devices return to normal; that is, continue to execute the following process;

[0063] If the result is normal, get NO3 - - NO3 detected by N sensor - -N measurement value, and according to the C / N ratio in the anoxic tank, predict the carbon source dosage for this adjustment;

[0064] Obtain NO3 - - NO3 detected by N sensor - -N measured value, and based on the C / N ratio in the anoxic tank, predict the carbon source dosage for this adjustment, including:

[0065] Obtain NO3 - - NO3 detected by N sensor - -N measurement value, used to determine the organic matter and nitrogen concentrations in the anoxic tank, and calculate the C / N ratio in the anoxic tank based on the organic matter and nitrogen concentrations;

[0066] Determine whether the C / N ratio in the anoxic tank exceeds the preset range;

[0067] If not, the carbon source dosage is zero;

[0068] If yes, according to the deviation of the C / N ratio in the anoxic tank from the preset range and the NO3 - -N measurement value, predict the carbon source dosage for this adjustment;

[0069] At the same time, the N2O measurement value detected by the N2O sensor is obtained to determine whether the minimum emission standard of N2O in the anoxic tank is met, and if it is not met, the DO concentration is controlled by the O tank to reduce the N2O concentration at the end of the anoxic tank; the O tank is an aerobic tank, and DO is dissolved oxygen;

[0070] Controlling DO concentration through the O pool reduces the N2O concentration at the end of the anoxic pool, including:

[0071] When the N2O concentration at the end of the anoxic pool is higher than the minimum emission standard, the O pool status is obtained; the O pool status includes the DO content status, ammonia nitrogen content status and NO2 - -N accumulation content status;

[0072] According to the state of the O pool, the corresponding adjustment strategy pre-stored in the database is obtained to adjust the DO content in the O pool to reduce the N2O concentration at the end of the anoxic pool;

[0073] If the DO concentration cannot be reduced to the minimum emission standard by controlling the DO concentration in the O pool, the carbon source dosage is adjusted according to the N2O concentration deviation value at the end of the anoxic pool to obtain a new carbon source dosage, and the dosing pump inverter frequency is adjusted accordingly according to the new carbon source dosage to complete the dosing operation; wherein, the N2O concentration deviation value at the end of the anoxic pool is the difference between the actual detection value of the N2O concentration at the end of the anoxic pool and the minimum emission standard of the N2O concentration;

[0074] It is worth noting that if the N2O measurement value meets the minimum emission standard of N2O at the end of the anoxic tank, or the DO concentration can be controlled by the O tank to reduce the N2O concentration at the end of the anoxic tank to the minimum emission standard, no carbon source is added, and the operation state of the carbon source precise addition self-control system after adjusting the DO concentration is maintained; through this scheme, the N2O feedback optimization is used to reduce the cost of carbon source addition;

[0075] The change of the frequency of the dosing pump inverter is related to the flow value of the dosing pump. If the flow value of the dosing pump cannot meet the carbon source dosage, that is, the added deviation value of the dosing pump flow value does not meet the preset second setting range, the frequency of the dosing pump inverter is changed to meet the preset second setting range; the selection of the preset second setting range is related to the carbon source dosage;

[0076] The beneficial effects of the above technical solution are as follows: through the above technical solution, the present invention proposes a method based on NO3 - -N feedforward regulation and N2O feedback optimization of carbon source precise dosing self-control method, through NO3 - -N feedforward regulation predicts the carbon source dosage, and reduces the carbon source dosage cost or accurately adjusts the carbon source dosage through N2O feedback optimization. It is used to solve the problem of low denitrification efficiency or high operating cost caused by users' difficulty in accurately controlling the carbon source dosage when there is an imbalance in the C / N ratio in the sewage. It is beneficial to reduce the input cost in the carbon source addition process and improve the real-time and precise control accuracy of the carbon source, thereby reducing the release of N2O in the system, achieving low-cost and high-precision carbon emission reduction, and reducing greenhouse gas emissions.

[0077] In one embodiment, a NO3-based - -N feedforward regulation and N2O feedback optimization of carbon source precise dosing self-control method also includes:

[0078] Generate corresponding dosing control instructions according to the new carbon source dosing dosage;

[0079] The time after the dosing control instruction is generated and transmitted to the dosing pump, and the time when the dosing pump adds the carbon source into the anoxic tank is taken as the lag time;

[0080] Obtain the increasing potential change of N2O concentration at the end of the anoxic pool before and after the lag time as the lag compensation value;

[0081] During the normal carbon source addition process, a number of hysteresis compensation values ​​that change with time are obtained, and when the number of the obtained hysteresis compensation values ​​meets the preset inspection number, a time series is generated according to the obtained hysteresis compensation values;

[0082] According to the time series stationary test method, the data stationary test of the time series is carried out in real time to generate the test result; wherein the time series stationary test method includes one or more combinations of the KPSS test method and the ADF test method;

[0083] When the verification result shows that the lag compensation value in the time series is stable, a dynamic regression model is generated based on the training of all lag compensation values ​​in the time series, and the future lag compensation value is predicted based on the trained dynamic regression model;

[0084] According to the future hysteresis compensation value, the new carbon source dosage is adjusted again to obtain the standard carbon source dosage, and the dosing pump inverter frequency is adjusted accordingly to complete the dosing operation according to the standard carbon source dosage;

[0085] The working principle of the above technical solution is as follows: in the actual application of sewage treatment, the existing dosing control mechanism has a large time lag problem, such as the time delay from the issuance of the instruction to the execution, which will greatly affect the accuracy of carbon source dosing. In order to minimize the impact of the dosing pump on the accuracy of carbon source dosing, this application proposes a hysteresis compensation mechanism to perform hysteresis compensation adjustment on the delivery of the carbon source to improve the accuracy of carbon source delivery;

[0086] Specifically, first, the carbon source dosage is obtained after the feedforward regulation is completed and the feedback optimization adjustment is completed, the instruction is transmitted to the dosing pump, and the time for adding the carbon source to the anoxic tank is used as the lag time; it is worth noting that whether the carbon source is added in the end will be determined according to the deviation value of the N2O concentration at the end of the anoxic tank. Therefore, after the lag time is determined, the increase in the N2O concentration at the end of the anoxic tank before and after the lag time is taken as the lag compensation value. The ...

[0087] During the normal carbon source addition process, a number of hysteresis compensation values ​​that change with time are obtained. When the number of hysteresis compensation values ​​obtained meets the preset test number, a time series is generated according to the obtained hysteresis compensation values, and a data stability check is performed on all hysteresis compensation values ​​in real time according to a time series stability test method to generate a test result; wherein the preset check number is preferably determined according to the selected time series stability method, and the time series stability test method includes one or more combinations of a KPSS test method and an ADF test method;

[0088] When the verification result shows that the time series composed of the obtained lag compensation values ​​is stable, a dynamic regression model is generated according to the training of all the lag compensation values ​​in the time series, and the future lag compensation values ​​are predicted according to the trained dynamic regression model; wherein, since the data in the time series meets the conditions of the dependent variable and one independent variable, the specific method of generating the dynamic regression model according to the lag compensation values ​​in the time series is a common technical means of those skilled in the art, and will not be described in detail here; it is worth noting that when performing the initial training, the selected initial dynamic regression model preferably adopts the classic ARIMA model applicable to the univariate time series;

[0089] Finally, according to the future hysteresis compensation value, the predicted carbon source dosage or the adjusted carbon source dosage is adjusted again to obtain the standard carbon source dosage, and the dosing pump inverter frequency is adjusted accordingly according to the standard carbon source dosage to complete the dosing operation;

[0090] The beneficial effect of the above technical solution is: through the above technical solution, a hysteresis compensation mechanism of the dosing pump is proposed, and the hysteresis compensation adjustment of the delivery of the carbon source is performed, which is beneficial to improving the accuracy of the delivery of the carbon source.

[0091] In one embodiment, a NO3-based - -N feedforward regulation and N2O feedback optimization of carbon source precise dosing self-control method also includes:

[0092] The number of elements in the time series is fixed, and the fixed number is the preset test number. When there is a new lag compensation value ready to be added to the time series, the original elements in the time series follow the first-in-first-out principle, and the elements in the time series are subtracted by one. At the same time, the new lag compensation value is added to the time series after the subtraction operation;

[0093] When the verification result shows that the lag compensation value in the time series is not stable, a new lag compensation value is obtained and added to the time series to form a new time series. According to the time series stability test method, the data stability test is performed on the new time series to generate a new verification result.

[0094] If the verification result still shows that the lag compensation value in the time series is not stable, repeat the above time series update operation until the verification result shows that the lag compensation value in the time series is stable;

[0095] The beneficial effects of the above technical solution are: through the above technical solution, the number of elements in the time series is kept stable, which is beneficial to reduce the impact of historical data on the current time series, improve the representativeness of the time series for the stability of the current lag compensation value, and thus improve the subsequent dynamic regression model generated according to the time series for the prediction accuracy of future lag compensation values.

[0096] In one embodiment, a NO3-based - -N feedforward regulation and N2O feedback optimization of carbon source precise dosing self-control method also includes:

[0097] After the dynamic regression model is trained, the lag compensation value that changes with time is continuously obtained and added to the time series to update the time series and judge the stationarity of the updated time series in real time;

[0098] If the updated time series is stable, the lag compensation value newly added to the time series is used to continue training the dynamic regression model;

[0099] If the updated time series is not stable, temporarily stop predicting the future lag compensation value according to the dynamic regression model, and continue to obtain the lag compensation value that changes with time and add it to the time series until the updated time series is stable. Delete the variable corresponding to the deleted lag compensation value in the dynamic regression model to adjust the model parameters to adapt to the new lag compensation value data characteristics, and use the new lag compensation value in the time series to continue training the dynamic regression model.

[0100] The working principle and beneficial effects of the above technical solution are as follows: after the dynamic regression model is trained, the lag compensation value that changes with time is continuously obtained and added to the time series, and the stationarity of the time series is judged in real time; if the time series is stationary, the lag compensation value newly added to the time series is used to continue training the dynamic regression model; more real-time data is used to maintain the timeliness and accuracy of the dynamic regression model, and further solve the problem of decreased accuracy of carbon source delivery caused by the lag of the dosing pump;

[0101] At the same time, if the time series is not stationary, temporarily stop predicting the future lag compensation value according to the dynamic regression model, and continue to obtain the lag compensation value that changes with time and add it to the time series until the updated time series is stationary. Delete the variables in the dynamic regression model corresponding to the lag compensation value deleted in the time series to adjust the model parameters to adapt to the new lag compensation value data characteristics. At the same time, the new lag compensation value in the time series is used to continue training the dynamic regression model, thereby further solving the problem of reduced accuracy of carbon source delivery due to the lag of the dosing pump. At the same time, compared with directly deleting the model, it reduces the additional computational cost and time cost of frequently rebuilding the model.

[0102] Finally, it should be noted that the above preferred embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail through the above preferred embodiments, those skilled in the art should understand that various changes can be made in form and details without departing from the scope defined by the claims of the present invention.

Claims

1. A NO3-based ― -N feedforward regulation and N2O feedback optimization carbon source precise dosing self-control method, characterized in that, include: Place NO3 in the anoxic pool in advance ― -N sensor, and a N2O sensor placed at the end of the anoxic tank; Online reading of NO3 ― -Self-test data from N sensor and N2O sensor is used to determine NO3 ― -Whether the N sensor and N2O sensor are normal; If the result is normal, get NO3 ― - NO3 detected by N sensor ― -N measurement value, and according to the C / N ratio in the anoxic tank, predict the carbon source dosage for this adjustment; At the same time, the N2O measurement value detected by the N2O sensor is obtained to determine whether the minimum emission standard of N2O in the anoxic pool is met, and if it is not met, the DO concentration is controlled by the O pool to reduce the N2O concentration at the end of the anoxic pool; If the DO concentration cannot be reduced to the minimum emission standard by controlling the DO concentration in the O pool, the carbon source dosage is adjusted according to the N2O concentration deviation value at the end of the anoxic pool to obtain a new carbon source dosage, and the dosing pump inverter frequency is adjusted accordingly according to the new carbon source dosage to complete the dosing operation.

2. A method according to claim 1 based on NO3 ― -N feedforward regulation and N2O feedback optimization carbon source precise dosing self-control method, characterized in that, Also includes: If the judgment result is NO3 ― - If any of the N sensor or N2O sensor is abnormal, the sensor will automatically perform self-checking operation, and send a prompt signal to the management personnel if the self-check cannot restore to normal; Continue working until all abnormal sensor devices return to normal.

3. A method based on NO3 according to claim 1. ― -N feedforward regulation and N2O feedback optimization carbon source precise dosing self-control method, characterized in that, It also includes: if the N2O measurement value meets the minimum emission standard of N2O at the end of the anoxic tank, or the N2O concentration at the end of the anoxic tank can be reduced to the minimum emission standard by controlling the DO concentration through the O tank, no carbon source will be added, and the operating state of the carbon source precise addition self-control system will be maintained after adjusting the DO concentration.

4. A method according to claim 1 based on NO3 ― -N feedforward regulation and N2O feedback optimization carbon source precise dosing self-control method, characterized in that, Obtain NO3 ― - NO3 detected by N sensor ― -N measured value, and according to the C / N ratio in the anoxic tank, predict the carbon source dosage for this adjustment, including: Obtain NO3 ― - NO3 detected by N sensor ― -N measurement value, used to determine the organic matter and nitrogen concentrations in the anoxic tank, and calculate the C / N ratio in the anoxic tank based on the organic matter and nitrogen concentrations; Determine whether the C / N ratio in the anoxic tank exceeds the preset range; If not, the carbon source dosage is zero; If yes, according to the deviation of the C / N ratio in the anoxic tank from the preset range and the NO3 ― -N measured value, predict the carbon source dosage for this adjustment.

5. A method according to claim 1 based on NO3 ― -N feedforward regulation and N2O feedback optimization carbon source precise dosing self-control method, characterized in that, Controlling DO concentration through the O pool reduces the N2O concentration at the end of the anoxic pool, including: When the N2O concentration at the end of the anoxic pool is higher than the minimum emission standard, the O pool status is obtained; the O pool status includes the DO content status, ammonia nitrogen content status and NO2 ― -N accumulation content status; According to the state of the O pool, the corresponding adjustment strategy pre-stored in the database is obtained to adjust the DO content in the O pool to reduce the N2O concentration at the end of the anoxic pool.

6. A method according to claim 1 based on NO3 ― -N feedforward regulation and N2O feedback optimization carbon source precise dosing self-control method, characterized in that, The N2O concentration deviation value at the end of the anoxic pool is the difference between the actual detection value of the N2O concentration at the end of the anoxic pool and the minimum emission standard of the N2O concentration.

7. A method according to claim 1 based on NO3 ― -N feedforward regulation and N2O feedback optimization carbon source precise dosing self-control method, characterized in that, Also includes: Generate corresponding dosing control instructions according to the new carbon source dosing dosage; The time after the dosing control instruction is generated and transmitted to the dosing pump, and the time when the dosing pump adds the carbon source into the anoxic tank is taken as the lag time; Obtain the increasing potential change of N2O concentration at the end of the anoxic pool before and after the lag time as the lag compensation value; During the normal carbon source addition process, a number of hysteresis compensation values ​​that change with time are obtained, and when the number of the obtained hysteresis compensation values ​​meets the preset inspection number, a time series is generated according to the obtained hysteresis compensation values; According to the time series stationary test method, the data stationary test of the time series is carried out in real time to generate the test result; wherein the time series stationary test method includes one or more combinations of the KPSS test method and the ADF test method; When the verification result shows that the lag compensation value in the time series is stable, a dynamic regression model is generated based on the training of all lag compensation values ​​in the time series, and the future lag compensation value is predicted based on the trained dynamic regression model; According to the future hysteresis compensation value, the new carbon source dosage is adjusted again to obtain the standard carbon source dosage. According to the standard carbon source dosage, the frequency of the dosing pump inverter is adjusted accordingly to complete the dosing operation.

8. A method according to claim 7 based on NO3 ― -N feedforward regulation and N2O feedback optimization carbon source precise dosing self-control method, characterized in that, Also includes: The number of elements in the time series is fixed, and the fixed number is the preset test number. When there is a new lag compensation value ready to be added to the time series, the original elements in the time series follow the first-in-first-out principle, and the elements in the time series are subtracted by one. At the same time, the new lag compensation value is added to the time series after the subtraction operation; When the verification result shows that the lag compensation value in the time series is not stable, a new lag compensation value is obtained and added to the time series to form a new time series. According to the time series stability test method, the data stability test is performed on the new time series to generate a new verification result. If the verification result still shows that the lag compensation value in the time series is not stable, the above time series updating operation is repeated until the verification result shows that the lag compensation value in the time series is stable.

9. A method according to claim 8 based on NO3 ― -N feedforward regulation and N2O feedback optimization carbon source precise dosing self-control method, characterized in that, Also includes: After the dynamic regression model is trained, the lag compensation value that changes with time is continuously obtained and added to the time series to update the time series and judge the stationarity of the updated time series in real time; If the updated time series is stable, the lag compensation value newly added to the time series is used to continue training the dynamic regression model; If the updated time series is not stationary, temporarily stop predicting the future lag compensation value based on the dynamic regression model, and continue to obtain the lag compensation value that changes with time and add it to the time series until the updated time series is stationary. Delete the variables in the dynamic regression model corresponding to the lag compensation value deleted in the time series to adjust the model parameters to adapt to the new lag compensation value data characteristics, and use the new lag compensation value in the time series to continue training the dynamic regression model.

Images