CN115745176A

CN115745176A - Method and device for realizing stable low-carbon denitrification of municipal sewage by utilizing PN/A

Info

Publication number: CN115745176A
Application number: CN202211423722.9A
Authority: CN
Inventors: 李天豪; 谢懿; 夏俊; 张晓琳; 刘建勇
Original assignee: Shanghai Urban Construction City Operation Group Co ltd; Shanghai Urban Construction Maintaince Management Co ltd; University of Shanghai for Science and Technology
Current assignee: Shanghai Urban Construction City Operation Group Co ltd; Shanghai Urban Construction Maintaince Management Co ltd; University of Shanghai for Science and Technology
Priority date: 2022-11-15
Filing date: 2022-11-15
Publication date: 2023-03-07

Abstract

The invention discloses a method for realizing stable low-carbon denitrification of municipal sewage by utilizing PN/A, which is characterized in that a mainstream reactor and a side-stream reactor are cooperatively used for reaction in the side-stream reactor, and after short-cut nitrification reaction, sludge reaching the standard in the side-stream reactor and sewage with the ammonia nitrogen concentration reaching the standard in effluent in the side-stream reactor are conveyed into the mainstream reactor for reaction; in the mainstream reactor, converting ammonia nitrogen and nitrite in the sewage into nitrogen through oxidation operation and discharging the nitrogen; in the mainstream reactor and the sidestream reactor, a neural network is used for simulating a complex reaction process in an FA inhibition unit to obtain an accurate output predicted value, and the pH value and the ammonia nitrogen concentration are regulated and controlled in time, so that the active inhibition of mainstream NOB is realized, and the method for realizing stable low-carbon denitrification of urban sewage by utilizing PN/A is realized.

Description

Method and device for realizing stable low-carbon denitrification of municipal sewage by utilizing PN/A

Technical Field

The invention relates to the technical field of low-carbon treatment of urban sewage, in particular to a method and a device for realizing stable low-carbon denitrification of the urban sewage by utilizing PN/A.

Background

PN/A is a novel, sustainable biological denitrification process. Compared with the traditional nitrification and denitrification processes, the PN/A process can save 60 percent of aeration consumption and nearly 100 percent of organic carbon requirement. Up to now, the single-stage PN/A process has been successfully applied to the treatment of high-concentration ammonia nitrogen wastewater. The use of the PN/a process is also of great importance for sewage treatment, since it has the potential to make sewage treatment plants nearly energy autonomous.

Although more and more successful experimental evidences exist, the case that PN/A is comprehensively applied to directly treat urban main stream sewage with low ammonia nitrogen concentration does not exist. One of the most critical and difficult bottlenecks for anammox treatment of wastewater is the continuous inhibition of nitrite-oxidizing bacteria (NOB) by the short-cut nitrification process. The growth of NOB in the PN/A sewage treatment process is widely reported, and the enrichment of NOB can improve the nitrate content of effluent and reduce the denitrification efficiency of anaerobic ammonia oxidation. Therefore, the NOB activity can be effectively inhibited, and the method has important significance for stable operation and comprehensive application of the PN/A denitrification process.

In the existing NOB inhibition technology, high Free Ammonia (FA) in a high ammonia nitrogen concentration solution of a sidestream of an urban sewage plant is utilized to inhibit NOB activity, so that the NOB inhibition technology has certain application potential, but the process relates to exchange of mainstream sidestream sludge and interaction of various microorganisms, has the characteristics of high complexity, nonlinearity, large time lag and the like, and is difficult to realize effective application.

Disclosure of Invention

In view of the defects of the prior art, the invention aims to solve the technical problems that the existing PN/A can not directly treat urban main stream sewage with low ammonia nitrogen concentration, and the shortcut nitrification process can not effectively and continuously inhibit Nitrite Oxidizing Bacteria (NOB), thereby reducing the efficiency of anammox denitrification. Aiming at the problems, the invention provides a method and a device for realizing stable low-carbon denitrification of urban sewage by utilizing PN/A, which can realize the stable inhibition of NOB in the urban sewage short-cut nitrification process and the stable operation of the main flow PN/A denitrification process of the urban sewage by utilizing the prediction and control of NOB activity in an FA inhibition unit by utilizing a neural network.

In order to achieve the purpose, the invention provides a method for realizing stable low-carbon denitrification of municipal sewage by utilizing PN/A, which is cooperatively completed by using a mainstream reactor and a side-stream reactor, wherein sludge generated after pretreatment or biochemical treatment of the municipal sewage is concentrated, liquid flowing out after methane and biogas residues are generated by anaerobic nitrification enters the side-stream reactor for reaction, and after short-cut nitrification reaction, sludge reaching the standard in the side-stream reactor and sewage reaching the ammonia nitrogen concentration of effluent in the side-stream reactor are conveyed into the mainstream reactor for reaction; in the mainstream reactor, converting ammonia nitrogen and nitrite in sewage into nitrogen through oxidation operation and discharging the nitrogen;

in the mainstream reactor and the sidestream reactor, a neural network is used for simulating a complex reaction process in an FA inhibition unit to obtain an accurate output predicted value, and the pH value and the ammonia nitrogen concentration are regulated and controlled in time, so that the active inhibition of mainstream NOB is realized, and the method for realizing stable low-carbon denitrification of urban sewage by using PN/A is realized.

Further, the reaction within the side-flow reactor comprises the steps of:

performing HRAS/CEPT treatment on municipal sewage, inputting the treated sewage into a water inlet barrel of a mainstream reactor, concentrating the treated sludge, and inputting the concentrated sludge serving as high-concentration ammonia nitrogen wastewater into a water inlet barrel of a sidestream reactor after anaerobic digestion;

conveying the sewage in the side-flow water inlet barrel to an FA inhibition unit through a first pipeline, simultaneously conveying the sludge with the NOB activity exceeding the standard in the mainstream reactor to the FA inhibition unit through a second pipeline, and finally adding alkali into the inhibition unit as an adjustment amount;

measuring pH, temperature, ammonia nitrogen concentration, sludge concentration and inhibition time in the current FA inhibition unit by using a data collector, using the measured pH, temperature, ammonia nitrogen concentration, sludge concentration and inhibition time as an input layer of a neural network, and obtaining the activity prediction values of NOB and AOB in the effluent sludge treated by the FA inhibition unit through the neural network;

and conveying the sewage or sludge treated by the FA inhibition unit to the side flow reactor.

Further, the reaction within the mainstream reactor comprises the steps of:

the pretreated urban sewage stored in the main flow water inlet barrel and the sewage with the ammonia nitrogen concentration reaching the standard after the treatment of the side flow reactor are conveyed into the main flow reactor together, and the ammonia nitrogen and nitrite in the sewage are converted into nitrogen through oxidation and discharged;

the data acquisition unit is used for measuring the pH, the temperature, the ammonia nitrogen concentration, the total nitrogen concentration and the DO concentration in the mainstream reactor, the measured values and the set values of the parameters are compared, the reaction effect in the mainstream reactor is adjusted through the fan, the sewage and the nitrogen which reach the standard in treatment are discharged, and the stable denitrification treatment of the urban sewage is completed.

Further, the pH, the temperature, the ammonia nitrogen concentration, the sludge concentration and the inhibition time in the current FA inhibition unit are measured by a data collector and are used as an input layer of a neural network, and the activity prediction values of NOB and AOB in the effluent sludge treated by the FA inhibition unit are obtained through the neural network, and the method specifically comprises the following steps:

the pH, the temperature, the ammonia nitrogen concentration, the sludge concentration and the inhibition time of an FA inhibition unit during water inflow are used as an input layer of a neural network, the NOB and AOB activities of the FA inhibition unit during water outflow are used as an output layer of the neural network, the neural network is trained, verified and tested by using a certain amount of experimental data, the number of neurons of an optimal hidden layer is determined, the pH, the temperature, the ammonia nitrogen concentration, the sludge concentration and the inhibition time of the FA inhibition unit during water inflow are input into a trained neural network model, and the complex reaction process in the FA inhibition unit is simulated by the neural network, so that the NOB and AOB activities identified by the neural network are obtained.

Furthermore, the control strategy of the upper limit and the lower limit of the NOB activity always controls the NOB activity to be 0.2-0.4mg (NO) ₃ ^- -N)/g (MLVSS)/h range; when NOB activity in the effluent sludge output by the neural network is more than 0.4mg (NO) ₃ ^- When the concentration of ammonia nitrogen is determined to be unchanged, the alkali adding amount is increased by adjusting a flow regulator on an alkali tank according to an FA concentration calculation equation so as to increase the pH value in an FA inhibition unit; when NOB activity in the effluent sludge output by the neural network is less than 0.2mg (NO) ₃ ^- When the concentration of ammonia nitrogen is determined to be unchanged, the alkali addition is stopped by closing a flow regulator on the alkali tank according to an FA concentration calculation equation under the condition that the concentration of ammonia nitrogen and the temperature are determined to be unchanged, so that the pH value in an FA inhibition unit is kept stable.

Further, the temperature of the FA suppression unit was constantly kept constant at 35 ℃ using a heating rod.

Further, the pH value is set to be in the range of 7.5-8.6, and when the pH value in the input layer is greater than 8.6, the alkali adding is stopped by closing a flow regulator on the alkali tank; when the pH value is less than 7.5, the pH value in the FA inhibition unit is increased by adjusting a flow regulator on the alkali tank and increasing the alkali adding amount. Wherein the pH measurement of the input layer is measured by a pH probe.

Further, the ammonia nitrogen concentration is set to be 1000-2000mg/L; when the ammonia nitrogen concentration measurement value is lower than 1000mg/L, the flow Q2 of the floating mud discharged by the mainstream reactor is reduced, so that the ammonia nitrogen concentration is increased; and when the measured value of the ammonia nitrogen concentration is higher than 2000mg/L, increasing Q2 so as to reduce the ammonia nitrogen concentration.

Furthermore, free ammonia is arranged in the FA inhibition unit, and the free ammonia can inhibit the activity of nitrite oxidizing bacteria NOB and maintain the activity of ammonia oxidizing bacteria AOB.

The invention also provides a device for realizing stable low-carbon denitrification of municipal sewage by utilizing PN/A, which comprises a side-flow water inlet barrel, an FA inhibition unit, an alkali tank, a shortcut nitrification reactor, a main-flow water inlet barrel and a shortcut nitrification-anaerobic ammonia oxidation reactor, wherein:

the side-flow water inlet barrel is used for storing pretreated high-concentration ammonia nitrogen wastewater and is communicated with an inlet of an FA inhibition unit, the flow rate of the side-flow water inlet barrel is Q1 (Q1 is generally unadjustable), the alkali tank is communicated with the inlet of the FA inhibition unit, an outlet of the FA inhibition unit is communicated with an inlet of a shortcut nitrification reactor, and an outlet of the shortcut nitrification reactor is communicated with an inlet of the shortcut nitrification-anaerobic ammonia oxidation reactor;

the main flow water inlet barrel is used for storing the pretreated low-concentration ammonia nitrogen wastewater and is communicated with an inlet of the shortcut nitrification-anaerobic ammonia oxidation reactor, a second outlet of the shortcut nitrification-anaerobic ammonia oxidation reactor is communicated with an inlet of the FA inhibition unit, the flow rate of the FA inhibition unit is Q2, and a first outlet of the shortcut nitrification-anaerobic ammonia oxidation reactor is used for discharging the treated municipal sewage;

wherein the FA inhibition unit is a reaction tank.

Technical effects

The invention provides a method and a device for realizing stable low-carbon denitrification of municipal sewage by utilizing PN/A, which not only provides a stable nitrite nitrogen source for a shortcut nitrification-anaerobic ammonia oxidation process, but also reduces the influence of the characteristics of high complexity, nonlinearity, large time lag and the like of FA inhibition NOB activity on the shortcut nitrification-anaerobic ammonia oxidation process by pretreating the municipal sewage, then inputting the sewage with high ammonia nitrogen concentration into a mainstream reactor for treatment, inputting the sewage with low ammonia nitrogen concentration into a mainstream reactor for treatment, and predicting and controlling the NOB activity in an FA inhibition unit by utilizing the cooperation treatment of the sidestream and the mainstream, so that the shortcut nitrification-anaerobic ammonia oxidation process can keep the characteristics of long-term high efficiency and stability, and the denitrification efficiency of the municipal sewage is effectively improved. The method for realizing the stable low-carbon denitrification of the municipal sewage by utilizing the PN/A is a novel and sustainable biological denitrification process. Compared with the traditional nitrification and denitrification processes, the PN/A process can save 60 percent of aeration consumption and nearly 100 percent of organic carbon requirement.

The conception, the specific structure and the technical effects of the present invention will be further described with reference to the accompanying drawings to fully understand the objects, the features and the effects of the present invention.

Drawings

FIG. 1 is a schematic flow chart of a method for stable low-carbon denitrification of municipal sewage by using PN/A according to a preferred embodiment of the invention;

FIG. 2 is a schematic flow chart of an FA inhibition unit of a stable low-carbon denitrification method for municipal sewage by using PN/A according to a preferred embodiment of the present invention;

FIG. 3 is a schematic diagram of a neural network for implementing a stable low-carbon denitrification method for municipal sewage by using PN/A according to a preferred embodiment of the present invention;

FIG. 4 is a schematic flow chart of the method for realizing stable low-carbon denitrification of municipal sewage by using PN/A and predicting and controlling NOB activity in an FA inhibition unit based on a neural network according to a preferred embodiment of the invention.

Detailed Description

In order to make the technical problems, technical solutions and advantageous effects to be solved by the present invention more clearly apparent, the present invention is further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular internal procedures, techniques, etc. in order to provide a thorough understanding of embodiments of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present invention with unnecessary detail.

As shown in fig. 1, an embodiment of the present invention provides a method for realizing stable low-carbon nitrogen removal of municipal sewage by using PN/a, which is cooperatively completed by using a mainstream reactor and a sidestream reactor, wherein sludge generated after pretreatment or biochemical treatment of the municipal sewage is concentrated, and then flows out of the mainstream reactor after anaerobic nitrification is performed to generate methane and biogas residues, and then flows into the sidestream reactor to react, and after a short-cut nitrification reaction, sludge reaching the standard in the sidestream reactor and sewage with ammonia nitrogen concentration reaching the standard in effluent from the sidestream reactor are conveyed into the mainstream reactor to react; in the mainstream reactor, converting ammonia nitrogen and nitrite in the sewage into nitrogen through oxidation operation and discharging the nitrogen;

The reaction in the sidestream reactor (i.e. short path nitration reactor) comprises the steps of:

treating urban sewage by HRAS/CEPT, inputting the treated sewage into a water inlet barrel of a mainstream reactor, concentrating the treated sludge, and inputting the concentrated sludge serving as high-concentration ammonia nitrogen wastewater into a water inlet barrel of a sidestream reactor after anaerobic digestion;

In the short-cut nitrification reactor, ammonia nitrogen in sewage is completely converted into nitrite through oxidation, simultaneously FNA inhibition is carried out, NOB activity is inhibited in a near step, pH, temperature, sludge concentration, DO concentration and effluent ammonia nitrogen concentration in the side flow reactor are measured in real time through a data acquisition unit, comparison is carried out according to the measured values and set values of the parameters, and then the reaction effect in the side flow reactor is adjusted through a fan. And conveying the sludge which reaches the standard in the side flow reactor, namely the sludge with the NOB activity stably inhibited and the AOB activity unaffected to the mainstream reactor, and simultaneously conveying the sewage with the effluent ammonia nitrogen concentration reaching the standard in the side flow reactor to the mainstream reactor so as to carry out the reaction in the mainstream reactor.

Free ammonia is arranged in the FA inhibition unit, and the free ammonia can inhibit the activity of nitrite oxidizing bacteria NOB and maintain the activity of ammonia oxidizing bacteria AOB. AOB and Free Nitrous Acid (FNA) are arranged in the short-distance nitration reactor, the AOB can completely oxidize ammonia nitrogen into nitrite by using oxygen in the reactor, and the FNA can inhibit the activity of NOB and maintain the activity of AOB.

As shown in fig. 2, the FA inhibitory unit is mainly affected by free ammonia, so the FA concentration is the variable we need to control. According to the FA concentration calculation formula, the number of variables influencing the FA concentration is three, namely ammonia nitrogen concentration, pH and temperature. The ammonia nitrogen concentration is determined by the ratio of the flow rate (Q1) of the high-concentration ammonia nitrogen wastewater to the flow rate (Q2) of the floating mud discharged from the mainstream reactor, namely Q1/Q2. In the experiment, when the ammonia nitrogen concentration and the temperature are kept at fixed values, the pH value becomes the only variable for changing the FA concentration. While the sludge concentration and the inhibition time are also factors that affect the reaction, they affect the reaction within the FA inhibition unit, although they do not change the FA concentration. The sludge concentration can be directly measured by an MLSS probe; the inhibition time, i.e. the Hydraulic Retention Time (HRT), is determined by the ratio of the reactor working volume to the flow rate. The five parameters form an input layer of the neural network, and the AOB/NOB activity prediction value is obtained through prediction and recognition of the neural network model. When training the neural network, the predicted value and the actual value need to be compared, and the weight and the deviation in the neural network model are corrected through back propagation, so that the optimal model is obtained. The trained neural network model can well output the activity prediction value of the AOB/NOB, and then the condition of the AOB/NOB activity in the reactor is judged, and the activity of the AOB/NOB is regulated through simple feedback control. In the method, the pH and the ammonia nitrogen concentration are adjusted, the ammonia nitrogen concentration is kept at a fixed value under the common condition, and if the pH is not adjusted ideally, the ammonia nitrogen concentration can be adjusted.

The reaction in the mainstream reactor (i.e. the shortcut nitrification-anaerobic ammonia oxidation reactor) comprises the following steps:

Short-cut nitrifying bacteria and anaerobic ammonia oxidizing bacteria are arranged in the short-cut nitrifying-anaerobic ammonia oxidation reactor, and the anaerobic ammonia oxidizing bacteria can utilize nitrite nitrogen and ammonia nitrogen to carry out anaerobic ammonia oxidation to generate nitrogen.

The urban sewage treatment plant is generally divided into a main stream and a side stream (the flow accounts for 1 percent of the main stream), wherein the main stream refers to a sewage line (namely, wastewater with low ammonia nitrogen concentration is generally 10-50 mg/L), the side stream refers to liquid flowing out after sludge generated after pretreatment or biochemical treatment is concentrated and then is subjected to anaerobic digestion to generate methane and biogas residues, and the part of the sewage is also treated, and is characterized in that the ammonia nitrogen concentration is high and is generally 1000-2000mg/L.

The embodiment of the invention utilizes the artificial neural network to simulate the complex reaction process of sewage treatment so as to achieve the aim of accurately predicting the water outlet condition. An Artificial Neural Network (ANN) is an information processing system for simulating the structure and function of human brain, is a mathematical tool with nonlinear mapping capability, and can model complex objects which are difficult to accurately describe. The multilayer perceptron neural network (MLPNN) is the simplest and most common neural network, and the structure of the MLPNN mainly comprises a human input layer, a hidden layer and an output layer, each layer comprises a plurality of neuron nodes, and each neuron node structure comprises three parts of connection weight, threshold and activation function. The learning process of the neural network consists of two parts, namely signal forward propagation for network calculation and back propagation for layer-by-layer error transmission, and the learning rule of the neural network is to constantly adjust the threshold value and the weight value of the network through the forward and back propagation to minimize the error square sum of actual output and expected output. The MLPNN using the back propagation algorithm (BP algorithm) is called a BP neural network, which is also the most widely used neural network in the environmental field.

The database of the neural network is mainly formed by experimental data for realizing the stable low-carbon denitrification process of the urban sewage by utilizing shortcut nitrification-anaerobic ammonia oxidation (PN/A), and more than 100 groups of experimental data are drawn up for the neural network to have higher accuracy and generalization capability.

The overall process of establishing the neural network model is divided into 3 parts:

1. data acquisition: data will be collected in real time by the online meter;

2. data processing: preprocessing the data acquired in the first step, and selecting enough samples and appropriate variable parameters from the preprocessed data;

3. model establishment: modeling the processed data, firstly selecting a proper model, training, correcting and testing, and performing online prediction, process monitoring and sensor monitoring after meeting the precision requirement.

The neural network of the embodiment of the invention mainly uses MATLAB and Simulink to simulate and test in the aspect of software programming, programs PLC by using a journey V16, and mainly uses Siemens S7-1200 series PLC to control in the aspect of hardware.

As shown in fig. 3, in the embodiment of the present invention, a data acquisition device is used to measure pH, temperature, ammonia nitrogen concentration, sludge concentration, and inhibition time in a current FA inhibition unit, and the measured pH, temperature, ammonia nitrogen concentration, sludge concentration, and inhibition time are used as an input layer of a neural network, and a predicted value of activity of NOB and AOB in effluent sludge treated by the FA inhibition unit is obtained through the neural network, specifically including:

the pH, the temperature, the ammonia nitrogen concentration, the sludge concentration and the inhibition time of an FA inhibition unit during water inflow are used as an input layer of a neural network, the NOB and AOB activities of the FA inhibition unit during water outflow are used as an output layer of the neural network, the neural network is trained, verified and tested by using a certain amount of experimental data, the number of neurons of an optimal hidden layer is determined, the pH, the temperature, the ammonia nitrogen concentration, the sludge concentration and the inhibition time of the FA inhibition unit during water inflow are input into a trained neural network model, and the complex reaction process in the FA inhibition unit is simulated by the neural network, so that the NOB and AOB activities identified by the neural network are obtained. And a relatively accurate output predicted value is obtained through the neural network, the pH and ammonia nitrogen concentration are regulated and controlled by the PLC in time, the effective inhibition on the activity of the mainstream NOB is realized, the method for realizing stable low-carbon denitrification of the urban sewage by utilizing the PN/A is further realized, and the self-learning process of the neural network is really realized. Wherein, the pH, the temperature, the ammonia nitrogen concentration, the sludge concentration and the inhibition time are used as input layers of the neural network, and have certain influence on output layers of the neural network.

FIG. 4 is a schematic flow diagram of neural network-based prediction and control of NOB activity in FA inhibition units. Firstly, sample data is normalized, then about 70% of data sets in the sample are taken as a training set of a neural network, 15% of the data sets are taken as a verification set, the remaining 15% of the data sets are taken as a test set, and the data sets comprise actual input parameters and actual corresponding outputs in an experiment. Weights and deviations among the neurons are calculated through the training set, the fitting effect of the network model is preliminarily evaluated through the verification set, and finally the model is preliminarily qualified through the test set. Inputting the brand new parameters into the neural network model, calculating the predicted value of AOB/NOB activity, and comparing the value identified by the model with the actual value determined by the experiment to obtain an error. If the error is larger than the set value, for example, the activity prediction error of NOB is determined to be +/-0.02 mg (NO) ₃ ^- -N)/g (MLVSS)/h, if the error is greater than this value, correcting the weighting coefficients layer by layer from the output layer to the input layer, from back to front, by back propagation algorithm, inputting the new parameters into the neural network model again, comparing the identified value with the actual value until the error is within the set value range, completing the training.

And introducing new input variable data, performing simulation prediction by using a BP neural network qualified by training, outputting a predicted value of AOB/NOB activity, adjusting pH if the AOB concentration is too low and the NOB concentration is too high, and adjusting the ammonia nitrogen concentration if necessary until the control requirement is met.

The control strategy of upper and lower limits of NOB activity is to control NOB activity to be 0.2-0.4mg (NO) ₃ ^- -N)/g (MLVSS)/h range; when NOB activity in the effluent sludge output by the neural network is more than 0.4mg (NO) ₃ ^- When the concentration of ammonia nitrogen is determined to be unchanged, the alkali adding amount is increased by adjusting a flow regulator on an alkali tank according to an FA concentration calculation equation under the condition that the ammonia nitrogen concentration and the temperature are determined to be unchanged, so that the pH value in an FA inhibition unit is increased, the purpose of increasing the FA concentration is achieved, and the NOB activity can be further inhibited; when NOB activity in the effluent sludge output by the neural network is less than 0.2mg (NO) ₃ ^- And when the concentration of ammonia nitrogen is determined to be negative N)/g (MLVSS)/h, according to an FA concentration calculation equation, under the condition that the concentration of ammonia nitrogen and the temperature are not changed, the alkali addition is stopped by closing a flow regulator on an alkali tank, so that the pH value in an FA inhibition unit is kept stable, the effect of stably inhibiting the NOB activity is achieved, and the alkali waste is avoided.

The heating rod is used in the FA inhibition unit, so that the temperature of the FA inhibition unit is always kept at 35 ℃ fixedly.

Further, the pH value is set to be within the range of 7.5-8.6, when the measured value of the pH value in the input layer is greater than 8.6, the alkali adding is stopped by closing the flow regulator on the alkali tank, and the FNA concentration in the subsequent side flow reactor can be reduced by the overhigh pH value, so that the inhibition effect of NOB activity is adversely affected, and the biochemical reaction process of the side flow PN is also not facilitated; when the pH measured value is less than 7.5, the flow regulator on the alkali tank is adjusted, the alkali adding amount is increased, the pH value in the FA inhibition unit is increased, and the adverse effect of the too low FA concentration on the NOB activity inhibition effect is avoided.

Further, the ammonia nitrogen concentration is set to be 1000-2000mg/L; when the ammonia nitrogen concentration measurement value is lower than 1000mg/L, the flow Q2 of the floating mud discharged by the mainstream reactor is reduced, so that the ammonia nitrogen concentration is increased; when the measured value of the ammonia nitrogen concentration is higher than 2000mg/L, the ammonia nitrogen concentration is reduced by increasing Q2.

In addition, the concentration of ammonia nitrogen can also influence the concentration of FA, the concentration of ammonia nitrogen and the concentration of FA have a direct proportion relation, and according to the process requirements, the concentration of ammonia nitrogen is generally kept fixed, and the concentration of FA is influenced by adjusting pH preferentially.

The sludge concentration and the inhibition time in the FA inhibition unit are also adjusted by the flow rate of Q2, and the flow rate of Q2 is also fixed in general.

The device for realizing stable low-carbon denitrification of municipal sewage by utilizing PN/A in the embodiment of the invention comprises a side-flow water inlet barrel, an FA inhibition unit (reaction tank), an alkali tank, a shortcut nitrification reactor, a main-flow water inlet barrel and a shortcut nitrification-anaerobic ammonia oxidation reactor, wherein:

the main flow water inlet barrel is used for storing the pretreated low-concentration ammonia nitrogen wastewater and is communicated with an inlet of the shortcut nitrification-anaerobic ammonia oxidation reactor, a second outlet of the shortcut nitrification-anaerobic ammonia oxidation reactor is communicated with an inlet of the FA inhibition unit, the flow rate of the FA inhibition unit is Q2, and a first outlet of the shortcut nitrification-anaerobic ammonia oxidation reactor is used for discharging the treated municipal sewage.

Example 1

The embodiment provides a method and a device for realizing stable low-carbon denitrification of municipal sewage by utilizing PN/A (pseudo noise)/A (nitrogen oxide), and the device comprises a side-flow water inlet barrel, an FA (FA) inhibition unit, an alkali tank, a short-cut nitrification reactor, a main-flow water inlet barrel and a short-cut nitrification-anaerobic ammonia oxidation reactor, wherein the side-flow water inlet barrel comprises:

the main flow water inlet barrel is used for storing the pretreated low-concentration ammonia nitrogen wastewater and is communicated with an inlet of the shortcut nitrification-anaerobic ammonia oxidation reactor, a second outlet of the shortcut nitrification-anaerobic ammonia oxidation reactor is communicated with an inlet of the FA inhibition unit, the flow rate of the FA inhibition unit is Q2, and a first outlet of the FA inhibition unit is used for discharging the treated municipal sewage.

And the second pipeline is provided with a flow regulator for regulating the flow of the floating mud entering the FA inhibition unit.

In addition, the data collector is connected with the water inlet of the FA inhibition unit and used for measuring the pH value, the temperature, the ammonia nitrogen concentration, the sludge concentration and the inhibition time at the water inlet of the FA inhibition unit, and the AOB/NOB activity predicted value at the water outlet of the FA inhibition unit is obtained by inputting the set values into the trained neural network. By setting the upper and lower limit values to be compared with the predicted value, the flow regulating valve on the corresponding pipeline is regulated by an intelligent control unit, namely PLC, so that the Q2 and the alkali flow are changed.

Specifically, the method comprises the following steps: through determination, the pH value of the water inlet of the FA inhibition unit is 7.6, the temperature is 32 ℃, the ammonia nitrogen concentration is 1510mg/L, the sludge concentration is 30g/L, and the accumulated inhibition time is 24h;

the measured data is transmitted to the trained neural network input layer through the data collector, and the obtained AOB activity predicted value at the water outlet of the FA inhibition unit is 8.5mg (NO) ₃ ^- -N)/g (MLVSS)/h, NOB activity prediction 0.8mg (NO) ₃ ^- -N)/g (MLVSS)/h; the predicted value of AOB activity is within the normal range, while the predicted value of NOB activity is greater than 0.4mg (NO) ₃ ^- -N)/g (MLVSS)/h, under the condition that the rest input amount is in the set range, automatically adjusting a flow adjusting valve on an alkali tank through an intelligent control system to increase the alkali agent input into the FA inhibition unit to enable the pH to reach 8.3, and obtaining the AOB activity predicted value at the water outlet of the FA inhibition unit at the moment to be 8.1mg (NO) ₃ ^- -N)/g (MLVSS)/h, NOB activity prediction 0.4mg (NO) ₃ ^- -N)/g (MLVSS)/h; all are within the normal range, and the regulation is successful.

Example 2

The apparatus and connections of this embodiment are the same as those of embodiment 1, and will not be described herein again. In the embodiment, through determination, the pH value of the water inlet of the FA inhibition unit is 8.6, the temperature is 35 ℃, the ammonia nitrogen concentration is 1200mg/L, the sludge concentration is 30g/L, and the accumulated inhibition time is 24h;

the measured data is transmitted to the trained neural network input layer through the data collector, and the obtained AOB activity predicted value at the water outlet of the FA inhibition unit is 5.2mg (NO) ₃ ^- -N)/g (MLVSS)/h, NOB activity prediction 0.1mg (NO) ₃ ^- -N)/g (MLVSS)/h; the predicted value of AOB activity is within the normal range, while the predicted value of NOB activity is less than 0.2mg (NO) ₃ ^- -N)/g (MLVSS)/h, under the condition that the rest input quantity is in a set range, automatically adjusting a flow adjusting valve on an alkali tank through an intelligent control system to stop inputting the alkali agent into the FA inhibition unit, after reacting for a period of time, reducing the pH to 8.4, and obtaining that the predicted value of the AOB activity at the water outlet of the FA inhibition unit at the moment is 5.8mg (NO) ₃ ^- -N)/g (MLVSS)/h, NOB activity prediction value is 0.3mg (NO) ₃ ^- -N)/g (MLVSS)/h; all are within the normal range, and the regulation is successful.

The foregoing detailed description of the preferred embodiments of the invention has been presented. It should be understood that numerous modifications and variations could be devised by those skilled in the art in light of the present teachings without departing from the inventive concepts. Therefore, the technical solutions available to those skilled in the art through logic analysis, reasoning and limited experiments based on the prior art according to the concept of the present invention should be within the scope of protection defined by the claims.

Claims

1. A method for realizing stable low-carbon denitrification of municipal sewage by utilizing PN/A is characterized in that a mainstream reactor and a side flow reactor are cooperatively used, sludge generated after pretreatment or biochemical treatment of the municipal sewage is concentrated, liquid flowing out after methane and biogas residues are generated by anaerobic nitrification enters the side flow reactor for reaction, and after short-cut nitrification reaction, sludge reaching the standard in the side flow reactor and sewage reaching the ammonia nitrogen concentration of effluent in the side flow reactor are conveyed into the mainstream reactor for reaction; in the mainstream reactor, converting ammonia nitrogen and nitrite in the sewage into nitrogen through oxidation operation and discharging the nitrogen;

in the mainstream reactor and the sidestream reactor, a neural network is used for simulating a complex reaction process in an FA inhibition unit to obtain an accurate output predicted value, and the pH value and the ammonia nitrogen concentration are regulated and controlled in time, so that the active inhibition of mainstream NOB is realized, and the method for realizing the stable low-carbon denitrification of urban sewage by using PN/A is realized.

2. The method for realizing the stable low-carbon denitrification of the municipal sewage by using the PN/A as claimed in claim 1, wherein the reaction in the side-flow reactor comprises the following steps:

conveying the sewage in the side-flow water inlet barrel to an FA inhibition unit through a first pipeline, simultaneously conveying the sludge with the NOB exceeding the activity standard in the mainstream reactor to the FA inhibition unit through a second pipeline, and finally adding alkali into the inhibition unit as an adjustment amount;

3. The method for realizing the stable low-carbon denitrification of the municipal sewage by using the PN/A as claimed in claim 2, wherein the reaction in the mainstream reactor comprises the following steps:

the method comprises the steps of measuring the pH, the temperature, the ammonia nitrogen concentration, the total nitrogen concentration and the DO concentration in the mainstream reactor by using a data collector, comparing the measured values and the set values of the parameters, adjusting the reaction effect in the mainstream reactor by using a fan, discharging the sewage and the nitrogen which reach the standard to be treated, and finishing the stable denitrification treatment of the municipal sewage.

4. The method for realizing stable low-carbon denitrification of municipal sewage by utilizing PN/A as claimed in claim 2, wherein a data collector is used to measure pH, temperature, ammonia nitrogen concentration, sludge concentration and inhibition time in the current FA inhibition unit, and the measured values are used as an input layer of a neural network, and the predicted values of NOB and AOB activity in the effluent sludge treated by the FA inhibition unit are obtained through the neural network, specifically comprising:

the pH, the temperature, the ammonia nitrogen concentration, the sludge concentration and the inhibition time of the FA inhibition unit during water inflow are used as an input layer of a neural network, the NOB and AOB activities of the FA inhibition unit during water outflow are used as an output layer of the neural network, the neural network is trained, verified and tested by using a certain amount of experimental data, the number of the neurons of the optimal hidden layer is determined, the pH, the temperature, the ammonia nitrogen concentration, the sludge concentration and the inhibition time of the FA inhibition unit during water inflow are input into a trained neural network model, and the complex reaction process in the FA inhibition unit is simulated by the neural network, so that the NOB and AOB activities recognized by the neural network are obtained.

5. The method for realizing the stable low-carbon denitrification of the municipal sewage by using the PN/A as claimed in claim 4, wherein the upper and lower limits of the NOB activity are controlled by the control strategy of the NOB activity, and the NOB activity is always controlled to be 0.2-0.4mg (NO) ₃ ^- -N)/g (MLVSS)/h range; when NOB activity in the effluent sludge output by the neural network is more than 0.4mg (NO) ₃ ^- When the concentration of ammonia nitrogen is determined to be unchanged, the alkali adding amount is increased by adjusting a flow regulator on an alkali tank according to an FA concentration calculation equation so as to increase the pH value in an FA inhibition unit; when NOB activity in the effluent sludge output by the neural network is less than 0.2mg (NO) ₃ ^- When the concentration of ammonia nitrogen is determined to be unchanged, the alkali addition is stopped by closing a flow regulator on the alkali tank according to an FA concentration calculation equation under the condition that the concentration of ammonia nitrogen and the temperature are determined to be unchanged, so that the pH value in an FA inhibition unit is kept stable.

6. The method for realizing the stable low-carbon denitrification of the municipal sewage by using the PN/A as claimed in claim 5, wherein the temperature of the FA inhibition unit is always kept constant at 35 ℃ by using a heating rod.

7. The method for realizing the stable low-carbon denitrification of the municipal sewage by using the PN/A as claimed in claim 4, wherein the pH is set to be in the range of 7.5 to 8.6, and when the pH measured value in the input layer is more than 8.6, the alkali addition is stopped by closing a flow regulator on the alkali tank; when the pH value is less than 7.5, the pH value in the FA inhibition unit is increased by adjusting a flow regulator on the alkali tank and increasing the alkali adding amount.

8. The method for realizing the stable low-carbon denitrification of the municipal sewage by using the PN/A as claimed in claim 4, wherein the ammonia nitrogen concentration is set to 1000-2000mg/L; when the ammonia nitrogen concentration measurement value is lower than 1000mg/L, the flow Q2 of the floating mud discharged by the mainstream reactor is reduced, so that the ammonia nitrogen concentration is increased; and when the measured value of the ammonia nitrogen concentration is higher than 2000mg/L, increasing Q2 so as to reduce the ammonia nitrogen concentration.

9. The method for realizing the stable low-carbon denitrification of the municipal sewage by using the PN/A as claimed in claim 4, wherein the FA inhibition unit is internally provided with free ammonia, and the free ammonia can inhibit the activity of Nitrite Oxidizing Bacteria (NOB) and maintain the activity of Ammonia Oxidizing Bacteria (AOB).

10. An apparatus for implementing stable low-carbon denitrification of municipal sewage by using PN/A according to any one of claims 1 to 9, comprising a side-stream water inlet tank, an FA inhibition unit (reaction tank), an alkali tank, a shortcut nitrification reactor, a main-stream water inlet tank, a shortcut nitrification-anaerobic ammonia oxidation reactor, wherein:

the side-flow water inlet barrel is used for storing pretreated high-concentration ammonia nitrogen wastewater and is communicated with an inlet of an FA inhibition unit, the flow rate of the side-flow water inlet barrel is Q1, the Q1 is generally unadjustable, the alkali tank is communicated with the inlet of the FA inhibition unit, an outlet of the FA inhibition unit is communicated with an inlet of a shortcut nitrification reactor, and an outlet of the shortcut nitrification reactor is communicated with an inlet of the shortcut nitrification-anaerobic ammonia oxidation reactor;