A method for precise dosing of carbon source based on NO3 - Self-control method for precise dosing of carbon source based on NO3

Abstract

The application discloses a kind of based on NO3 ― -N feedforward regulation and N2O feedback optimization carbon source precision dosing self-control method, comprising: online reading NO3 ― -N sensor and N2O sensor feedback self-checking data, for judging NO3 ― -N sensor and N2O sensor whether normal;If the judgment result is normal, obtain NO3 ― -N sensor detected NO3 ― -N determination value, and according to the C / N ratio in anoxic tank, predict the carbon source dosing dose of this adjustment;At the same time, obtain N2O determination value detected by N2O sensor, for judging whether to meet the minimum emission standard of N2O in anoxic tank, and when not meeting, reduce N2O concentration at the end of anoxic tank by controlling DO concentration of O pool;If N2O concentration at the end of anoxic tank cannot be reduced to the minimum emission standard by controlling DO concentration of O pool, adjust carbon source dosing dose according to N2O concentration deviation value at the end of anoxic tank to obtain new carbon source dosing dose, and complete dosing operation according to the corresponding adjustment of frequency of dosing pump frequency converter of new carbon source dosing dose.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of carbon emission reduction, and particularly relates to a NO3 - The application belongs to the technical field of carbon emission reduction, and particularly relates to a NO3 BACKGROUND

[0002] The denitrification process is one of the key steps of biological nitrogen removal in wastewater, and the influencing factors include carbon source, temperature, nitrification liquid reflux ratio, etc., in which the carbon source is an important influencing factor. In the wastewater treatment process, the denitrification process has a high requirement for the carbon-nitrogen ratio (C / N), and when the biochemical oxygen demand / total nitrogen (BOD5 / TN) of the influent is greater than 4, it is considered that the raw water contains sufficient carbon source. However, researches show that the influent of wastewater treatment plants in China generally has a problem of insufficient carbon source, and the insufficient soluble organic matter often leads to incomplete denitrification, resulting in that the effluent TN is not up to standard. In order to meet the requirement that the effluent quality of the wastewater treatment plant is up to standard, 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] Meanwhile, in the wastewater treatment process, the carbon source is not the more the better. If the additional carbon source is insufficiently added, the denitrification is insufficient; if the additional carbon source is excessively added, the operation cost is increased, and the COD load of the subsequent treatment process is also increased, which faces the risk that the effluent COD is out of standard, so that the wastewater treatment system is difficult to play the best performance.

[0004] In summary, determining the optimal addition amount of the carbon source is an important measure for the wastewater treatment plant to realize economic, efficient and low-carbon operation. The addition amount of the additional carbon source is affected by various factors in actual operation, such as the fluctuation of the influent quality and quantity of the wastewater treatment plant, the microbial community structure in the biochemical system, etc., which makes the theoretical value calculated by the traditional carbon source addition formula have great limitations in guiding the actual process operation.

[0005] Therefore, a NO3 - The application belongs to the technical field of carbon emission reduction, and particularly relates to a NO3 SUMMARY

[0006] Therefore, a NO3 - The application belongs to the technical field of carbon emission reduction, and particularly relates to a NO3

[0007] In order to achieve the above object, the application provides the following technical scheme.

[0008] A NO3 -A self-control method for precise carbon source dosing based on NO3

[0009] Pre-deposit NO3 - - N sensor, and N2O sensor at the end of the anoxic tank;

[0010] Online reading of NO3 - - N sensor and N2O sensor feedback self-check data for judging NO3 - - N sensor and N2O sensor are normal;

[0011] If the judgment result is normal, obtain NO3 - - N sensor detects NO3 - - measured value, and according to the C / N ratio in the anoxic tank, predict the carbon source dosing dose of this adjustment;

[0012] At the same time, obtain the N2O measured value detected by the N2O sensor, for judging whether the minimum emission standard of N2O in the anoxic tank is met, and when not met, reduce the N2O concentration at the end of the anoxic tank by controlling the DO concentration of the O tank;

[0013] If the N2O concentration at the end of the anoxic tank cannot be reduced to the minimum emission standard by controlling the DO concentration of the O tank, adjust the carbon source dosing dose according to the N2O concentration deviation at the end of the anoxic tank to obtain a new carbon source dosing dose, and adjust the frequency of the dosing pump frequency converter according to the new carbon source dosing dose to complete the dosing operation.

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

[0015] If the judgment result is NO3 - - N sensor or N2O sensor, any one of the devices is not normal, automatically execute sensor self-check operation, and send a prompt signal to the management personnel when the self-check cannot restore normal;

[0016] Continue to work until all the abnormal sensor devices are restored to normal.

[0017] Further, a self-control method for precise carbon source dosing based on NO3 - - N feedforward regulation and N2O feedback optimization also includes: If the N2O measured 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 of the O tank, no carbon source dosing is performed, and the running state of the carbon source precise dosing self-control system after adjusting the DO concentration is maintained.

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

[0019] Obtain NO3 - -N measured value, and according to the C / N ratio in the anoxic tank, predict the carbon source dosage of this adjustment, including: - -N measured value, for determining the organic matter and nitrogen concentration in the anoxic tank, and calculating the C / N ratio in the anoxic tank according to the organic matter and nitrogen concentration;

[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 value of the C / N ratio in the anoxic tank from the preset range, and the NO3 - -N measured value, predict the carbon source dosage of this adjustment.

[0023] Further, by controlling the DO concentration in the O tank to reduce the N2O concentration at the end of the anoxic tank, including:

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

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

[0026] Further, 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] Further, a carbon source precise dosing self-control method based on NO3 - -N feedforward regulation and N2O feedback optimization also includes:

[0028] Also includes:

[0029] According to the new carbon source dosage, generate corresponding dosing control instructions;

[0030] Obtain the lag time as the time when the dosing control instructions are generated and transmitted to the dosing pump, and the dosing pump adds the carbon source to the anoxic tank;

[0031] Obtain the growth change amount of N2O concentration at the end of the anoxic tank at the time before and after the lag time as the lag compensation value;

[0032] In the normal carbon source adding process, a plurality of time-varying lag compensation values are obtained, when the number of obtained lag compensation values meets a preset inspection number, a time series is generated according to the obtained lag compensation values;

[0033] According to the time series stationarity inspection method, the data stationarity of the time series is checked in real time to generate a checking result; wherein the time series stationarity inspection method includes one or more of the combination of the KPSS inspection method and the ADF inspection method;

[0034] When the checking result is that the lag compensation values in the time series are stationary, a dynamic regression model is trained according to all the lag compensation values in the time series, and the future lag compensation values are predicted according to the trained dynamic regression model;

[0035] According to the future lag compensation values, the new carbon source adding dosage is adjusted again to obtain a standard carbon source adding dosage, and the frequency of the dosing pump frequency converter is adjusted according to the standard carbon source adding dosage to complete the adding operation.

[0036] Further, a NO3 - The carbon source precise adding self-control method based on NO3

[0037] The number of elements in the time series is fixed, and the fixed number is a preset inspection number, when a new lag compensation value is 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 reduced by one, and the new lag compensation value is added to the time series after the reduction operation;

[0038] When the checking result is that the lag compensation values in the time series are not stationary, a new lag compensation value is obtained to join the time series to form a new time series, and the data stationarity of the new time series is checked according to the time series stationarity inspection method to generate a new checking result;

[0039] If the checking result is still that the lag compensation values in the time series are not stationary, the above time series updating operation is repeated until the checking result is that the lag compensation values in the time series are stationary.

[0040] Further, a NO3 - The carbon source precise adding self-control method based on NO3

[0041] After the dynamic regression model is trained, time-varying lag compensation values are continuously obtained and added to the time series to update the time series, and the stationarity of the updated time series is judged in real time;

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

[0043] If the updated time series is not stationary, temporarily stop predicting future lag compensation values according to the dynamic regression model, continuously obtain the lag compensation values changing with time and add them to the time series, until the updated time series is stationary, delete the variables in the dynamic regression model corresponding to the deleted lag compensation values in the time series, to adjust the model parameters to adapt to the new lag compensation value data characteristics, and at the same time, the new lag compensation value in the time series is used to continue training the dynamic regression model.

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

[0045] The present application provides a kind of based on NO3 - -N feedforward regulation and N2O feedback optimization's carbon source precision dosing self-control method, solve when there is C / N ratio imbalance in sewage, user is difficult to accurately control the dosing dose of carbon source and lead to low denitrification efficiency or high operating cost problem, beneficial to reduce the input cost in the process of carbon source dosing, and improve the real-time precision control accuracy of carbon source, to reduce the release amount of system N2O, realize low cost high precision carbon emission reduction, reduce the emission of greenhouse gases.

[0046] Other advantages, objects and features of the present application will be set forth in the following specification and will become apparent to those skilled in the art from the practice of the present application. The objects and other advantages of the present application will be realized and attained by the structure particularly pointed out in the written description and claims thereof as well as the appended drawings.

[0047] The technical solutions of the present application will be described in detail below with the help of drawings and examples. BRIEF DESCRIPTION OF DRAWINGS

[0048] The accompanying drawings are included to provide a further understanding of the present application and are incorporated in and constitute a part of this specification, illustrate embodiments of the present application and serve to explain the present application, and do not constitute a limitation on the present application. In the drawings:

[0049] Figure 1 For the control mode flow chart of the present application embodiment based on NO3 - -N feedforward regulation and N2O feedback optimization's carbon source precision dosing self-control method;

[0050] Figure 2 For the control logic schematic diagram of the present application embodiment based on NO3 - -N feedforward regulation and N2O feedback optimization's carbon source precision dosing self-control method;

[0051] Figure 3 The application provides a NO3 - The application provides a NO3 DETAILED DESCRIPTION

[0052] The preferred embodiments of the application will be described in detail below with reference to the drawings. It should be understood that the preferred embodiments described herein are only used to explain and illustrate the application, and are not used to limit the application.

[0053] As shown in Figure 1 , Figure 2 and Figure 3 The application provides a NO3 - The application provides a NO3

[0054] The application provides a NO3 - -N sensor is arranged in the anoxic tank, and an N2O sensor is arranged at the end of the anoxic tank;

[0055] The application provides a NO3 - -N sensor and the N2O sensor are used to judge whether the NO3 - -N sensor and the N2O sensor are normal;

[0056] The application provides a NO3 - -N sensor and the N2O sensor are used to judge whether the NO3 - -N sensor and the N2O sensor are normal;

[0057] The application provides a NO3 - -N sensor and the N2O sensor are used to judge whether the NO3 - -N sensor and the N2O sensor are normal;

[0058] The application provides a NO3 - -N sensor and the N2O sensor are used to judge whether the NO3 - -N sensor and the N2O sensor are normal;

[0059] The application provides a NO3 - -N sensor is arranged in the anoxic tank, and an N2O sensor is arranged at the end of the anoxic tank;

[0060] The application provides a NO3 - -N sensor and the N2O sensor are used to judge whether the NO3- whether the N sensor and the N2O sensor are normal;

[0061] If the result of the judgment is NO3 - If either the N sensor or the N2O sensor is abnormal, automatically perform a sensor self-checking operation, and send a prompt signal to the administrator when the self-checking fails to restore normality;

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

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

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

[0065] Obtain NO3 - -N measured by the N sensor; - -N measured value, for determining the organic matter and nitrogen concentration in the anoxic tank, and calculating the C / N ratio in the anoxic tank according to the organic matter and nitrogen concentration;

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

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

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

[0069] At the same time, obtain the N2O measured value detected by the N2O sensor, for judging whether the minimum emission standard of N2O in the anoxic tank is met, and reducing the N2O concentration at the end of the anoxic tank by controlling the DO concentration of the O tank when it is not met; the O tank is an aerobic tank, and DO is dissolved oxygen;

[0070] Reduce the N2O concentration at the end of the anoxic tank by controlling the DO concentration of the O tank, including:

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

[0072] According to the O pool state, the corresponding adjustment strategy pre-stored in the database is obtained, the DO content in the O pool is adjusted, and the N2O concentration at the end of the anoxic tank is reduced.

[0073] If the N2O concentration at the end of the anoxic tank cannot be reduced to the minimum emission standard by controlling the DO concentration in the O pool, a new carbon source addition dosage is obtained according to the deviation value of the N2O concentration at the end of the anoxic tank, and the frequency of the dosing pump frequency converter is adjusted according to the new carbon source addition dosage to complete the addition operation; wherein the deviation value of the N2O concentration 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.

[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 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 pool, the carbon source addition is not performed, and the operation state of the carbon source precise addition self-control system after adjusting the DO concentration is maintained; by this scheme, the N2O feedback optimization is used to reduce the addition cost of the carbon source;

[0075] The change of the frequency of the dosing pump frequency converter is related to the flow value of the dosing pump, if the flow value of the dosing pump cannot meet the carbon source addition dosage, that is, the addition deviation value of the flow value of the dosing pump does not meet the pre-set second set range, the frequency of the dosing pump frequency converter is changed to meet the pre-set second set range; the selection of the pre-set second set range is related to the carbon source addition dosage;

[0076] The beneficial effects of the above technical scheme are: through the above technical scheme, the present application proposes a carbon source precise addition self-control method based on NO3 - The N2O feedback optimization is used to reduce the addition cost of the carbon source or accurately adjust the carbon source addition dosage, which is used to solve the problem of low denitrification efficiency or high operation cost caused by the user's difficulty in accurately controlling the carbon source addition dosage when the C / N ratio in the sewage is imbalanced, which is beneficial to reduce the input cost in the carbon source addition process, improve the real-time precision control accuracy of the carbon source, and further reduce the release amount of N2O in the system, realize low-cost high-precision carbon emission reduction, and reduce the emission of greenhouse gases. - The N2O feedback optimization is used to reduce the addition cost of the carbon source or accurately adjust the carbon source addition dosage, which is used to solve the problem of low denitrification efficiency or high operation cost caused by the user's difficulty in accurately controlling the carbon source addition dosage when the C / N ratio in the sewage is imbalanced, which is beneficial to reduce the input cost in the carbon source addition process, improve the real-time precision control accuracy of the carbon source, and further reduce the release amount of N2O in the system, realize low-cost high-precision carbon emission reduction, and reduce the emission of greenhouse gases.

[0077] In one embodiment, a carbon source precise addition self-control method based on NO3 - The carbon source precise addition self-control method based on NO3

[0078] A corresponding addition control instruction is generated according to the new carbon source addition dosage;

[0079] The lag time is obtained before and after the time when the carbon source is added to the anoxic tank by the dosing pump after the dosing control instruction is generated and transmitted to the dosing pump.

[0080] The increment change amount of the N2O concentration at the end of the anoxic tank at the time before and after the lag time is obtained as the lag compensation value.

[0081] During the normal carbon source addition process, a plurality of lag compensation values changing with time are obtained, and when the number of obtained lag compensation values meets a preset verification number, a time series is generated according to the obtained lag compensation values.

[0082] According to the time series stationarity verification method, the data stationarity of the time series is verified in real time to generate a verification result. The time series stationarity verification method includes one or more of the KPSS verification method and the ADF verification method.

[0083] When the verification result is that the lag compensation values in the time series are stationary, a dynamic regression model is trained according to all the lag compensation values in the time series, and future lag compensation values are predicted according to the trained dynamic regression model.

[0084] According to the future lag compensation values, the new carbon source addition dose is adjusted again to obtain a standard carbon source addition dose, and the frequency of the dosing pump frequency converter is adjusted according to the standard carbon source addition dose to complete the addition operation.

[0085] The working principle of the above technical solution is that in the actual application of sewage treatment, the existing dosing control mechanism has a large time lag problem, for example, the time delay from instruction issuance to execution, which greatly affects the accuracy of carbon source addition. In order to minimize the impact of the dosing pump on the accuracy of carbon source addition, the present application proposes a lag compensation mechanism to adjust the lag compensation of carbon source addition to improve the accuracy of carbon source addition.

[0086] Specifically, first, the time when the carbon source addition dose is transmitted to the dosing pump and the carbon source is added to the anoxic tank after the feedforward regulation is completed and the feedback optimization adjustment is completed is obtained as the lag time. It should be noted that since whether the carbon source is added finally is determined according to the deviation value of the N2O concentration at the end of the anoxic tank, after the determination of the lag time is completed, the increment change amount of the N2O concentration at the end of the anoxic tank at the time before and after the lag time is obtained as the lag compensation value. The increment change amount is the change amount of the N2O concentration increased at the next time compared with the previous time. If the N2O concentration at the next time is reduced compared with the previous time, the lag compensation value is not counted this time.

[0087] In the normal carbon source adding process, a plurality of time-varying lag compensation values are obtained, when the number of obtained lag compensation values meets a preset verification number, a time series is generated according to the obtained lag compensation values, and all lag compensation values are checked for data stationarity in real time according to a time series stationarity checking method to generate a checking result; wherein the preset verification number is preferably determined according to the selected time series stationarity method, and the time series stationarity checking method includes one or more of the KPSS checking method and the ADF checking method;

[0088] When the checking result is that the time series composed of the obtained lag compensation values is stationary, a dynamic regression model is trained and generated according to all lag compensation values in the time series, and future lag compensation values are predicted according to the trained dynamic regression model; wherein, since the data in the time series meets the condition of dependent variable and one independent variable, the specific method of training and generating a dynamic regression model according to the lag compensation values in the time series is a common technical means for those skilled in the art, which will not be described here; it is worth noting that in the initial training, the selected initial dynamic regression model preferably adopts the classical ARIMA model suitable for single variable time series;

[0089] Finally, the predicted carbon source adding dosage or the adjusted carbon source adding dosage is adjusted again according to the future lag compensation value to obtain a standard carbon source adding dosage, and the frequency of the dosing pump frequency converter is adjusted according to the standard carbon source adding dosage to complete the adding operation;

[0090] The beneficial effects of the above technical solution are: through the above technical solution, a dosing pump lag compensation mechanism is proposed to adjust the lag compensation of the carbon source, which is beneficial to improve the accuracy of carbon source addition.

[0091] In one embodiment, a method for precise carbon source addition self-control based on NO3 - The carbon source precise addition self-control method based on N pre-feedforward regulation and N2O feedback optimization further comprises:

[0092] The number of elements in the time series is fixed, and the fixed number is the preset verification number. When a new lag compensation value is 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 decremented by one, and the new lag compensation value is added to the time series after the decrement operation;

[0093] When the checking result is that the lag compensation values in the time series are not stationary, a new lag compensation value is obtained to join the time series to form a new time series, and the new time series is checked for data stationarity according to the time series stationarity checking method to generate a new checking result;

[0094] If the check result is still that the lag compensation value in the time series is not stationary, repeat the above time series updating operation until the check result is that the lag compensation value in the time series is stationary.

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

[0096] In one embodiment, a NO3 - The N feedforward regulation and N2O feedback optimization carbon source precise dosing self-control method further comprises:

[0097] After the dynamic regression model is trained, the lag compensation value changing over time is continuously obtained and added to the time series for updating the time series, and the stationarity of the updated time series is judged in real time;

[0098] If the updated time series is stationary, the lag compensation value newly added to the time series is used for continuing training of the dynamic regression model;

[0099] If the updated time series is not stationary, the prediction of the future lag compensation value according to the dynamic regression model is temporarily stopped, the lag compensation value changing over time is continuously obtained and added to the time series, until the updated time series is stationary, the variable corresponding to the deleted lag compensation value in the time series in the dynamic regression model is deleted for adjusting the model parameters to adapt to the new lag compensation value data characteristics, and the new lag compensation value in the time series is used for continuing training of the dynamic regression model;

[0100] The working principle and beneficial effects of the above technical solution are: after the dynamic regression model is trained, the lag compensation value changing over 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 for continuing training of the dynamic regression model; more real-time data is used, so that the timeliness and accuracy of the dynamic regression model can be maintained, and the problem of decrease in carbon source dosing precision caused by the hysteresis of the dosing pump is further solved;

[0101] Meanwhile, if the time series is not stationary, temporarily stop predicting the future lag compensation value according to the dynamic regression model, continuously obtain the lag compensation value changing over time and add it to the time series, until the updated time series is stationary, delete the variable corresponding to the deleted lag compensation value in the time series in the dynamic regression model, adjust the model parameters to adapt to the new lag compensation value data characteristics, and at the same time, use the new lag compensation value in the time series to continue training the dynamic regression model, thereby further solving the problem of the decrease in the precision of the carbon source putting caused by the lag of the dosing pump, and at the same time, compared with directly deleting the model, reducing the calculation cost and time cost of frequent reconstruction of the model.

[0102] Finally, it should be pointed out that the above preferred embodiments are only used to illustrate the technical solutions of the present application and are not limiting. Although the present application 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 application.

Claims

1. A method based on NO3 - A self-control method for precise carbon source dosing based on -N feedforward regulation and N2O feedback optimization, characterized in that... include: NO3 was placed in the anoxic pool beforehand. - -N sensor, and N2O sensor placed at the end of the anoxic pool; Read NO3 online - The self-test data fed back by the -N and N2O sensors is used to determine NO3. - Are the -N sensor and N2O sensor functioning properly? If the judgment result is normal, obtain NO3. - NO3 detected by -N sensor - -N measurement value, and predict the carbon source dosage for this adjustment based on the C / N ratio in the anoxic tank; 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 not, the N2O concentration at the end of the anoxic pool is reduced by controlling the DO concentration through the O pool. If controlling the DO concentration in the O pool fails to reduce the N2O concentration at the end of the anoxic phase to the minimum emission standard, the carbon source dosage is adjusted based on the N2O concentration deviation at the end of the anoxic pool to obtain a new carbon source dosage, and a corresponding dosing control command is generated based on the new carbon source dosage. The time it takes for the dosing control command to be generated and transmitted to the dosing pump, and for the dosing pump to add the carbon source into the anoxic tank, is taken as the lag time. The change in the concentration of N2O at the end of the anoxic pool before and after the lag time is obtained as the lag compensation value. During the normal carbon source addition process, several lag compensation values ​​that change over time are obtained. When the number of lag compensation values ​​obtained meets the preset test quantity, a time series is generated based on the obtained lag compensation values. Based on the time series stationarity test method, the stationarity of the time series is checked in real time, and the check results are generated; the time series stationarity test method includes one or more of the KPSS test method and the ADF test method in combination. When the verification result shows that the lag compensation value in the time series is stationary, a dynamic regression model is trained based on all the lag compensation values ​​in the time series, and the future lag compensation value is predicted based on the trained dynamic regression model. Based on the future lag compensation value, the new carbon source dosage is readjusted to obtain the standard carbon source dosage. The frequency of the dosing pump inverter is then adjusted accordingly based on the standard carbon source dosage to complete the dosing operation.

2. A method based on NO3 according to claim 1 - A self-control method for precise carbon source dosing based on -N feedforward regulation and N2O feedback optimization, characterized in that... Also includes: If the judgment result is NO3 - If either the -N sensor or the N2O sensor malfunctions, the sensor will automatically perform a self-test and send a prompt signal to the administrator if the self-test fails to restore normal operation. It will continue to operate only after all malfunctioning sensor devices have been restored to normal.

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

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

5. A method based on NO3 according to claim 1 - A self-control method for precise carbon source dosing based on -N feedforward regulation and N2O feedback optimization, characterized in that... The N2O concentration at the end of the anoxic tank is reduced by controlling the DO concentration in the O tank, including: When the N2O concentration at the end of the anoxic tank exceeds the minimum emission standard, the O-tank status is obtained; the O-tank status includes DO content status, ammonia nitrogen content status, and NO2 content status. - -N accumulation status; Based on the state of the O pool, the corresponding adjustment strategy pre-stored in the database is obtained, and the DO content in the O pool is adjusted to reduce the N2O concentration at the end of the anoxic pool.

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

7. A method based on NO3 according to claim 1 - A self-control method for precise carbon source dosing based on -N feedforward regulation and N2O feedback optimization, characterized in that... Also includes: The number of elements in the time series is fixed, which is the preset test number. When a new lag compensation value is ready to be added to the time series, the original elements in the time series follow the first-in-first-out principle. The elements in the time series are decremented by one, and the new lag compensation value is added to the time series after the decrement operation. When the verification result shows that the lag compensation value in the time series is not stationary, a new lag compensation value is obtained and added to the time series to form a new time series. According to the time series stationarity test method, the new time series is tested for data stationarity and a new verification result is generated. If the verification result still indicates that the lag compensation value in the time series is not stationary, repeat the above time series update operation until the verification result indicates that the lag compensation value in the time series is stationary.

8. A method based on NO3 according to claim 7 - A self-control method for precise carbon source dosing based on -N feedforward regulation and N2O feedback optimization, characterized in that... Also includes: After the dynamic regression model is trained, the lag compensation value that changes over time is continuously acquired and added to the time series to update the time series, and the stationarity of the updated time series is judged in real time. If the updated time series is stationary, the lag compensation value of the newly added time series will be used to continue training the dynamic regression model. If the updated time series is not stationary, temporarily stop predicting future lag compensation values ​​based on the dynamic regression model, and continue to acquire lag compensation values ​​that change over time and add them to the time series until the updated time series becomes stationary. Then, delete the variables in the dynamic regression model that correspond to the deleted lag compensation values ​​in the time series to adjust the model parameters to adapt to the new lag compensation value data characteristics. At the same time, use the new lag compensation values ​​in the time series to continue training the dynamic regression model.

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