Circulating cooling blowdown water treatment method and system

Abstract

The invention provides a circulating cooling sewage treatment method and system, and the method comprises the steps: constructing a water quality prediction model based on historical circulating cooling sewage data and a preset neural network model; inputting real-time circulating cooling sewage water data into the water quality prediction model to obtain water quality parameter dynamic prediction data; based on the water quality parameter dynamic prediction data, obtaining a circulating cooling sewage treatment parameter combination; generating a corresponding sewage treatment regulation and control strategy based on the real-time circulating cooling sewage water data and the circulating cooling sewage water treatment parameter combination; and based on the corresponding sewage treatment regulation and control strategy, a plurality of sewage treatment modules are recombined, and the circulating cooling sewage treatment process pipeline is updated, so that circulating cooling sewage is treated. The circulating cooling sewage treatment strategy is flexibly adjusted and executed, the concentration of pollutants in the circulating cooling sewage is effectively reduced to reach the sewage discharge standard, and the sewage treatment reliability is improved.

Description

Technical Field

[0001] The present invention relates to the field of sewage treatment, and in particular, to a method and system for treating circulating cooling blowdown sewage. Background Art

[0002] Circulating cooling towers are set up in power plants, which have become departments with a relatively large proportion of water consumption. The blowdown sewage generated by circulating cooling towers mainly has the risk of exceeding the standards of total nitrogen, total phosphorus, suspended solids and COD. Therefore, in order to be discharged, the circulating cooling blowdown sewage needs to strictly meet the discharge standards.

[0003] Currently, traditional technologies use coagulation clarification and filtration to remove suspended solids in the blowdown sewage, and then combine with the upgrading treatment process of industrial wastewater to treat total nitrogen, COD and total phosphorus pollutants, such as "composite biological filter + activated sand filter". However, the drainage volume of the circulating cooling tower is large, resulting in large fluctuations in the water quality of the circulating cooling blowdown sewage. Under the condition of large fluctuations in water quality, the existing technical process cannot effectively reduce the pollutant concentration in the circulating cooling blowdown sewage to meet the sewage discharge standards, with poor overall adaptability and problems of poor reliability in sewage treatment. Summary of the Invention

[0004] In order to solve the above problems, the present invention proposes a method and system for treating circulating cooling blowdown sewage, which can flexibly adjust and implement the sewage treatment strategy for circulating cooling blowdown, effectively reduce the pollutant concentration in the circulating cooling blowdown sewage to meet the sewage discharge standards, and improve the reliability of sewage treatment.

[0005] To achieve the above object, an embodiment of the present invention provides a method for treating circulating cooling blowdown sewage, which is applied to a process pipeline for treating circulating cooling blowdown sewage. The process pipeline for treating circulating cooling blowdown sewage is composed of several sewage treatment modules, and includes: constructing a water quality prediction model based on historical circulating cooling blowdown sewage data and a preset neural network model; inputting real-time circulating cooling blowdown sewage data into the water quality prediction model to obtain dynamic prediction data of water quality parameters; obtaining a combination of sewage treatment parameters for circulating cooling blowdown based on the dynamic prediction data of water quality parameters; generating a corresponding sewage treatment regulation strategy based on the real-time circulating cooling blowdown sewage data and the combination of sewage treatment parameters for circulating cooling blowdown; and recombining several sewage treatment modules based on the corresponding sewage treatment regulation strategy to update the process pipeline for treating circulating cooling blowdown sewage, so as to treat the circulating cooling blowdown sewage.

[0006] An embodiment of the present invention provides a method for treating circulating cooling blowdown sewage. By combining historical circulating cooling blowdown sewage data and a neural network model, a water quality prediction model is constructed. Then, the circulating cooling blowdown sewage data is monitored in real time, and dynamic prediction data of water quality parameters is obtained through the water quality prediction model. The neural network model is used to learn the fluctuation changes of historical water quality and accurately predict future water quality changes to better adapt to the water quality fluctuation conditions caused by large drainage volumes. Then, based on the dynamic prediction data of water quality parameters, a combination of sewage treatment parameters for circulating cooling blowdown is obtained. Then, according to the real-time circulating cooling blowdown sewage data and the combination of sewage treatment parameters for circulating cooling blowdown, a corresponding sewage treatment control strategy is generated, and several sewage treatment modules are recombined, and the process pipeline for treating circulating cooling blowdown is updated to treat the circulating cooling blowdown sewage. Thus, a combination of sewage treatment parameters for circulating cooling blowdown is obtained through dynamic prediction data, a flexible adjustment strategy is provided by combining real-time circulating cooling blowdown sewage data, and the process pipeline for treating circulating cooling blowdown is updated and optimized through the corresponding sewage treatment control strategy to treat the circulating cooling blowdown sewage, so as to cope with water quality fluctuation conditions and effectively reduce the concentration of pollutants in the circulating cooling blowdown sewage to meet the sewage discharge standard and improve the reliability of sewage treatment.

[0007] Further, based on historical circulating cooling blowdown sewage data and a preset neural network model, a water quality prediction model is constructed, including: obtaining historical water quality parameters based on historical circulating cooling blowdown sewage data; constructing a training set of water quality parameters based on the historical water quality parameters; serializing the data of the training set of water quality parameters to obtain a serialized training set of water quality parameters; and constructing a water quality prediction model based on the serialized training set of water quality parameters and the preset neural network model.

[0008] Through the above solution, by collecting historical circulating cooling blowdown sewage data, historical water quality parameters affecting water quality are analyzed, and then the data of the training set of water quality parameters is serialized to obtain a reliable and accurate data training set. Then, through serialization processing and in combination with a preset neural learning model, a water quality prediction model is constructed. Thus, a reliable data training set is provided for the neural learning model to learn the water quality parameters and the change trend of water quality parameters affecting water quality changes, providing a good data basis for subsequent prediction of water quality fluctuations and corresponding strategy adjustments, and improving the reliability of sewage treatment.

[0009] Further, based on the serialized training set of water quality parameters and a preset neural network model, a water quality prediction model is constructed, including: inputting the serialized training set of water quality parameters into the preset neural network model for the first neural learning training to obtain preliminary prediction data; inputting the preliminary prediction data into the preset neural network model for the second neural learning training to obtain deep prediction data; and updating the model parameters of the preset neural network model based on the deep prediction data to obtain a water quality prediction model.

[0010] Through the above solution, a preset neural network model is trained with an accurate and reliable serialized water quality parameter training set, enabling the neural network model to learn the water quality parameters affecting water quality changes and the changing trends of water quality parameters. During the training process, the model training is carried out in a phased manner. First, the first neural learning training is performed to obtain preliminary prediction data, and then the second neural learning training is carried out to obtain in-depth prediction data. By training in phases, the complexity of the joint training of the neural network model is reduced, enabling the preset neural model to more accurately learn the water quality parameters affecting water quality changes and the changing trends of water quality parameters, thereby improving the prediction accuracy of the water quality prediction model, and further affecting the accuracy of subsequent corresponding strategy adjustments, thus improving the reliability of sewage treatment.

[0011] Furthermore, based on the dynamic prediction data of water quality parameters, a combination of sewage treatment parameters for circulating cooling blowdown is obtained, including: based on historical experimental data and historical sewage treatment strategies for circulating cooling blowdown, the dynamic prediction data of water quality parameters is input into a preset artificial intelligence model to match the corresponding sewage treatment parameters for circulating cooling blowdown; based on the dynamic prediction data of water quality parameters and the corresponding sewage treatment parameters for circulating cooling blowdown, a combination of sewage treatment parameters for circulating cooling blowdown is constructed.

[0012] Through the above solution, historical experimental data and historical sewage treatment strategies for circulating cooling blowdown are used to match the corresponding sewage treatment parameters for circulating cooling blowdown in a preset artificial intelligence model. Based on historical cases, the sewage treatment parameters for circulating cooling blowdown are matched, which can verify the dynamic prediction data of water quality parameters and match the dynamic changing trends of water quality parameters to historical cases. By constructing a combination of sewage treatment parameters for circulating cooling blowdown in combination with historical treatment experience, the reliability of subsequent strategy adjustments can be guaranteed, and the reliability of sewage treatment can be improved.

[0013] Furthermore, based on the real-time circulating cooling blowdown data and the combination of sewage treatment parameters for circulating cooling blowdown, a corresponding sewage treatment regulation strategy is generated to treat the circulating cooling blowdown, including: based on the real-time circulating cooling blowdown data, a real-time water quality parameter combination is obtained; based on the real-time water quality parameter combination, a combination of sewage treatment parameters for circulating cooling blowdown that meets the preset requirements is matched; based on the preset artificial intelligence model and the combination of sewage treatment parameters for circulating cooling blowdown, a corresponding sewage treatment regulation strategy is generated;

[0014] Through the above solution, analyze the real-time circulating cooling sewage discharge data to obtain real-time water quality parameters, then match the sewage treatment parameter combinations for circulating cooling sewage discharge constructed based on historical treatment experience, and then generate corresponding sewage treatment regulation strategies by a preset artificial intelligence model using the sewage treatment parameter combinations for circulating cooling sewage discharge, and treat the circulating cooling sewage discharge. By combining the real-time circulating cooling sewage discharge data, provide a flexible adjustment strategy, and through the corresponding sewage treatment regulation strategy, optimize the circulating cooling sewage discharge treatment process, cope with the fluctuating water quality conditions, effectively reduce the pollutant concentration in the circulating cooling sewage discharge to meet the sewage discharge standard, and improve the reliability of sewage treatment.

[0015] Furthermore, based on the corresponding sewage treatment regulation strategy, recombine several sewage treatment modules and update the sewage treatment process pipeline for circulating cooling sewage discharge to treat the circulating cooling sewage discharge, including: obtaining the sewage treatment target for circulating cooling sewage discharge based on the corresponding sewage treatment regulation strategy; selecting several sewage treatment modules based on the sewage treatment target for circulating cooling sewage discharge to obtain several target sewage treatment modules; combining several target sewage treatment modules to update the sewage treatment process pipeline for circulating cooling sewage discharge to obtain the target sewage treatment process pipeline for circulating cooling sewage discharge; and treating the circulating cooling sewage discharge based on the target sewage treatment process pipeline for circulating cooling sewage discharge.

[0016] Through the above solution, obtain the sewage treatment target for circulating cooling sewage discharge according to the corresponding sewage treatment regulation strategy, thereby select the required target sewage treatment modules, combine the target sewage treatment modules, update the sewage treatment process pipeline for circulating cooling sewage discharge to obtain the target sewage treatment process pipeline for circulating cooling sewage discharge, and treat the circulating cooling sewage discharge. By providing a flexible adjustment strategy in the sewage treatment process pipeline for circulating cooling sewage discharge, recombine the sewage treatment modules, only use the required sewage treatment modules, and optimize the sewage treatment process pipeline for circulating cooling sewage discharge to cope with the fluctuating water quality conditions, effectively reduce the pollutant concentration in the circulating cooling sewage discharge to meet the sewage discharge standard, and improve the reliability of sewage treatment.

[0017] Further, the sewage treatment module includes: an upflow anoxic sludge film tank, a flocculation sedimentation tank, an ozone catalytic oxidation tank, and a biological aerated filter; based on the target process pipeline for treating circulating cooling blowdown sewage, the circulating cooling blowdown sewage is treated, including: if the target process pipeline for treating circulating cooling blowdown sewage includes an upflow anoxic sludge film tank, the chemical dosing strategy for the upflow anoxic sludge film tank is obtained according to the corresponding sewage treatment control strategy, and the circulating cooling blowdown sewage is treated; if the target process pipeline for treating circulating cooling blowdown sewage includes a flocculation sedimentation tank, the chemical dosing strategy for the flocculation sedimentation tank is obtained according to the corresponding sewage treatment control strategy, and the circulating cooling blowdown sewage is treated; if the target process pipeline for treating circulating cooling blowdown sewage includes an ozone catalytic oxidation tank, the chemical dosing strategy for the ozone catalytic oxidation tank is obtained according to the corresponding sewage treatment control strategy, and the circulating cooling blowdown sewage is treated; if the target process pipeline for treating circulating cooling blowdown sewage includes a biological aerated filter, the operation strategy for the biological aerated filter is obtained according to the corresponding sewage treatment control strategy, and the circulating cooling blowdown sewage is treated.

[0018] Through the above solution, by adjusting the chemical dosing strategies for the upflow anoxic sludge film tank, the flocculation sedimentation tank, the ozone catalytic oxidation tank, and the operation strategy for the biological aerated filter, the usage strategies of the chemicals are reasonably set to treat the circulating cooling blowdown sewage. Thus, a flexible adjustment strategy is provided in the process pipeline for treating circulating cooling blowdown sewage to cope with the water quality fluctuation situation and effectively reduce the pollutant concentration in the circulating cooling blowdown sewage to meet the sewage discharge standard, improving the reliability of sewage treatment.

[0019] The embodiment of the present invention further provides a circulating cooling blowdown sewage treatment system, including: a water quality prediction model construction module, a water quality parameter dynamic prediction module, a circulating cooling blowdown sewage parameter combination module, a sewage treatment strategy acquisition module, and a circulating cooling blowdown sewage treatment module; the water quality prediction model construction module is used to construct a water quality prediction model based on historical circulating cooling blowdown sewage data and a preset neural network model; the water quality parameter dynamic prediction module is used to input real-time circulating cooling blowdown sewage data into the water quality prediction model to obtain water quality parameter dynamic prediction data; the circulating cooling blowdown sewage parameter combination module is used to obtain a circulating cooling blowdown sewage treatment parameter combination based on the water quality parameter dynamic prediction data; the sewage treatment strategy acquisition module is used to generate a corresponding sewage treatment control strategy based on real-time circulating cooling blowdown sewage data and the circulating cooling blowdown sewage treatment parameter combination; the circulating cooling blowdown sewage treatment module is used to recombine several sewage treatment modules based on the corresponding sewage treatment control strategy, update the process pipeline for treating circulating cooling blowdown sewage, and treat the circulating cooling blowdown sewage.

[0020] An embodiment of the present invention provides a circulating cooling sewage treatment system. The water quality prediction model construction module constructs a water quality prediction model by combining historical circulating cooling sewage data and a neural network model. The water quality parameter dynamic prediction module then monitors the circulating cooling sewage data in real time, and predicts the dynamic prediction data of water quality parameters through the water quality prediction model. The neural network model is used to learn the fluctuation changes of historical water quality and accurately predict the future water quality changes to better adapt to the water quality fluctuation conditions caused by large drainage volume. The circulating cooling sewage treatment parameter combination module then obtains the circulating cooling sewage treatment parameter combination through the dynamic prediction data of water quality parameters. The sewage treatment strategy acquisition module and the circulating cooling sewage treatment module then generate corresponding sewage treatment control strategies according to the real-time circulating cooling sewage data and the circulating cooling sewage treatment parameter combination, and recombine several sewage treatment modules to update the circulating cooling sewage treatment process pipeline to treat the circulating cooling sewage. Thus, the circulating cooling sewage treatment parameter combination is obtained through the dynamic prediction data, and a flexible adjustment strategy is provided by combining the real-time circulating cooling sewage data. Through the corresponding sewage treatment control strategy, the circulating cooling sewage treatment process pipeline is updated and optimized to treat the circulating cooling sewage to cope with the water quality fluctuation conditions and effectively reduce the pollutant concentration in the circulating cooling sewage to meet the sewage discharge standard, improving the reliability of sewage treatment.

[0021] Further, the circulating cooling sewage treatment module is used to recombine several sewage treatment modules based on the corresponding sewage treatment control strategy and update the circulating cooling sewage treatment process pipeline to treat the circulating cooling sewage, including: a treatment target acquisition unit, a treatment module selection unit, a process pipeline update unit, and a target treatment unit; the treatment target acquisition unit is used to obtain the circulating cooling sewage treatment target based on the corresponding sewage treatment control strategy; the treatment module selection unit is used to select several sewage treatment modules based on the circulating cooling sewage treatment target to obtain several target sewage treatment modules; the process pipeline update unit is used to combine several target sewage treatment modules to update the circulating cooling sewage treatment process pipeline to obtain the target circulating cooling sewage treatment process pipeline; the target treatment unit is used to treat the circulating cooling sewage based on the target circulating cooling sewage treatment process pipeline.

[0022] Through the above solution, according to the corresponding sewage treatment regulation strategy, the sewage treatment target of the circulating cooling blowdown is obtained. Then, the required target sewage treatment modules are selected, and the target sewage treatment modules are combined to update the sewage treatment process pipeline of the circulating cooling blowdown, obtaining the target sewage treatment process pipeline of the circulating cooling blowdown. The circulating cooling blowdown is treated. By providing a flexible adjustment strategy in the sewage treatment process pipeline of the circulating cooling blowdown, recombining the sewage treatment modules, and only using the required sewage treatment modules, the sewage treatment process pipeline of the circulating cooling blowdown is optimized to cope with the water quality fluctuation situation and effectively reduce the pollutant concentration in the circulating cooling blowdown to meet the sewage discharge standard, improving the reliability of sewage treatment.

[0023] Further, the sewage treatment module includes: an upflow anoxic sludge film tank, a flocculation sedimentation tank, an ozone catalytic oxidation tank, and a biological aerated filter. The target treatment unit is used to treat the circulating cooling blowdown based on the target sewage treatment process pipeline of the circulating cooling blowdown, including: a first circulating cooling blowdown sewage treatment subunit, a second circulating cooling blowdown sewage treatment subunit, a third circulating cooling blowdown sewage treatment subunit, and a fourth circulating cooling blowdown sewage treatment subunit. The first circulating cooling blowdown sewage treatment subunit is used to, if the target sewage treatment process pipeline of the circulating cooling blowdown includes an upflow anoxic sludge film tank, obtain the chemical dosing strategy of the upflow anoxic sludge film tank according to the corresponding sewage treatment regulation strategy and treat the circulating cooling blowdown. The second circulating cooling blowdown sewage treatment subunit is used to, if the target sewage treatment process pipeline of the circulating cooling blowdown includes a flocculation sedimentation tank, obtain the chemical dosing strategy of the flocculation sedimentation tank according to the corresponding sewage treatment regulation strategy and treat the circulating cooling blowdown. The third circulating cooling blowdown sewage treatment subunit is used to, if the target sewage treatment process pipeline of the circulating cooling blowdown includes an ozone catalytic oxidation tank, obtain the chemical dosing strategy of the ozone catalytic oxidation tank according to the corresponding sewage treatment regulation strategy and treat the circulating cooling blowdown. The fourth circulating cooling blowdown sewage treatment subunit is used to, if the target sewage treatment process pipeline of the circulating cooling blowdown includes a biological aerated filter, obtain the operation strategy of the biological aerated filter according to the corresponding sewage treatment regulation strategy and treat the circulating cooling blowdown.

[0024] Through the above solution, by adjusting the chemical dosing strategy of the upflow anoxic sludge film tank, the chemical dosing strategy of the flocculation sedimentation tank, the chemical dosing strategy of the ozone catalytic oxidation tank, and the operation strategy of the biological aerated filter, the use strategy of the chemicals is reasonably set to treat the circulating cooling blowdown. Thus, a flexible adjustment strategy is provided in the sewage treatment process pipeline of the circulating cooling blowdown to cope with the water quality fluctuation situation and effectively reduce the pollutant concentration in the circulating cooling blowdown to meet the sewage discharge standard, improving the reliability of sewage treatment. Description of the Drawings

[0025] Figure 1Schematic diagram of the process steps of a circulating cooling sewage treatment method provided by an embodiment of the present invention;

[0026] Figure 2 Schematic diagram of the structure of the process pipeline for a circulating cooling sewage treatment method provided by an embodiment of the present invention;

[0027] Figure 3 Schematic diagram of the module structure of a circulating cooling sewage treatment system provided by an embodiment of the present invention;

[0028] Reference numerals: 1, inlet bucket of the circulating cooling tower; 2, upflow anoxic sludge film tank; 3, flocculation sedimentation tank; 4, ozone catalytic oxidation tank; 5, biological aerated filter; 6, first bypass pipeline; 7, second bypass pipeline; 8, third bypass pipeline; 9, outlet; 10, circulating cooling sewage inlet pump; 11, biological aerated filter inlet pump; 12, carbon source dosing pump; 13, sludge film tank reflux pump; 14, stirrer; 15, PAC dosing pump; 16, PAM dosing pump; 17, ozone generator; 18, biological aerated filter reflux pump; 19, fan. Detailed implementation manners

[0029] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0030] Explanation of some keywords in this embodiment:

[0031] (1) Denitrification refers to the process in which under anoxic or anaerobic conditions, denitrifying bacteria use nitrate or nitrite as electron acceptors and reduce them to nitrogen gas;

[0032] (2) The ozone catalytic oxidation technology utilizes the strong oxidizing property of ozone. Under the action of a catalyst, the refractory organic matter in sewage is rapidly decomposed into harmless substances. The redox potential of ozone is 2.07 eV, and its oxidation ability is higher than that of potassium permanganate, chlorine dioxide, hydrogen peroxide, and oxygen. The reaction between ozone and organic matter is mainly achieved through two ways: (2.1) Direct reaction: Ozone molecules directly react with organic matter; (2.2) Indirect reaction: Ozone decomposes in water to produce strongly oxidizing free radicals (such as hydroxyl radicals ·OH), and these free radicals react with organic matter, having stronger oxidation ability and faster reaction rate. The role of the catalyst is to accelerate the decomposition of ozone, generate more free radicals, and thus improve the oxidation efficiency;

[0033] (3) The high - efficiency coagulation - precipitation technology is a physicochemical method commonly used in the field of water treatment. By adding coagulants to water, the pollutants such as suspended solids, colloidal substances, and dissolved organic matter in the water are separated from the water through their chemical reactions in water, thereby improving water quality. This technology combines the processes of coagulation, flocculation, and precipitation, and has the advantages of high treatment efficiency, strong adaptability, and simple operation. It is widely used in municipal sewage treatment, industrial wastewater treatment, drinking water purification and other fields. The core of the high - efficiency coagulation - precipitation technology lies in the two stages of "coagulation" and "precipitation". Its basic principle is to make the pollutants in the water react with the coagulant by adding an appropriate amount of coagulant to form larger - sized flocs, and then separate these flocs from the water through precipitation, ultimately achieving the purpose of removing pollutants in the water. Chemical phosphorus removal separates phosphorus from water in the form of precipitation or adsorption by adding chemical agents. Its core is to convert dissolved phosphorus into insoluble precipitates through chemical reactions, thereby achieving the removal of dissolved phosphorus. Coagulation - precipitation and chemical phosphorus removal can work together and be combined into one unit;

[0034] (4) The BAF process, namely the biological aerated filter process, the core of the BAF process is to purify sewage by using the biofilm attached to the surface of the filter media. The filter tank is filled with granular filter media with a smaller particle size. The surface of the filter media is attached with a biofilm, and the inside of the filter tank is aerated. When sewage flows through the filter media, pollutants, dissolved oxygen, and other substances diffuse to the surface and inside of the biofilm through the liquid phase, and the sewage is purified by using the oxidation and degradation ability of the biofilm. At the same time, the interception effect of the filter media can remove suspended solids in the sewage, and the detached biofilm will not float out with the water. After running for a period of time, due to the increase in head loss, the filter tank needs to be backwashed to release the intercepted suspended solids and update the biofilm. The BAF has the functions of removing SS (suspended solids), COD (chemical oxygen demand), BOD (biochemical oxygen demand), nitrification, denitrification, phosphorus removal, and removing harmful substances by adjusting the operation mode;

[0035] (5) Gaussian process regression (GPR) is a non - parametric Bayesian method used for regression analysis.

[0036] In the prior art, for the treatment method of circulating cooling blowdown water, there are processes such as "composite biological filter + activated sand filter" and "aerated biological fluidized bed → coagulation clarifier → ozone catalytic oxidation → aerated biological activated carbon filter → quartz sand filter". In the case of circulating cooling blowdown water with a high proportion of refractory biodegradable organic matter in the former process, the biodegradation ability of the biofilm in the composite biological filter for these organic matters is limited. Therefore, the effluent COD cannot ensure compliance with the discharge standard, the filter material of the composite biological filter is prone to blockage, resulting in deterioration of the effluent water quality, the removal ability for dissolved organic matter and total nitrogen is limited, and it has poor adaptability to circulating cooling blowdown water with large water quality fluctuations, and the reliability of sewage treatment is poor; in the latter process, the aerated biological fluidized bed basically has no effect when the winter temperature is relatively low, resulting in a significant decrease in the treatment efficiency. Under low-temperature conditions, the growth and metabolic rate of microorganisms decrease, resulting in weakened biodegradation ability, which in turn affects the removal effect of organic matter and ammonia nitrogen. In the case of treating circulating cooling blowdown water with large water quality fluctuations, the dosage of ozone in the latter process needs to be dynamically adjusted according to the influent water quality, but it is difficult to achieve precise control in actual operation, resulting in incomplete oxidation of some refractory organic matter. Therefore, aiming at the defects existing in the prior art, the present application proposes a method and system for treating circulating cooling blowdown water, which can flexibly adjust and implement the circulating cooling blowdown water treatment strategy, effectively reduce the pollutant concentration in the circulating cooling blowdown water to meet the sewage discharge standard, and improve the reliability of sewage treatment, specifically as follows:

[0037] Example 1

[0038] See Figure 1 , Figure 1 which is a schematic flow chart of the steps of a method for treating circulating cooling blowdown water provided in an embodiment of the present invention. As Figure 1 shown, the embodiment of the present invention provides a method for treating circulating cooling blowdown water, which is applied to the process pipeline for treating circulating cooling blowdown water. The process pipeline for treating circulating cooling blowdown water is composed of several sewage treatment modules, including the following steps:

[0039] Step 101, based on the historical circulating cooling blowdown water data and a preset neural network model, construct a water quality prediction model;

[0040] Step 102, input the real-time circulating cooling blowdown water data into the water quality prediction model to obtain dynamic prediction data of water quality parameters;

[0041] Step 103, based on the dynamic prediction data of water quality parameters, obtain a combination of circulating cooling blowdown water treatment parameters;

[0042] Step 104, based on the real-time circulating cooling blowdown water data and the combination of circulating cooling blowdown water treatment parameters, generate a corresponding sewage treatment regulation strategy;

[0043] Step 105: Based on the corresponding sewage treatment regulation strategy, recombine several sewage treatment modules and update the sewage treatment process pipeline for circulating cooling blowdown to treat the circulating cooling blowdown.

[0044] In a specific implementable manner, an embodiment of the present invention provides a method for treating circulating cooling blowdown, which is applied to the sewage treatment process pipeline for circulating cooling blowdown. The sewage treatment process pipeline for circulating cooling blowdown is composed of several sewage treatment modules. By collecting a large amount of historical circulating cooling blowdown data, a water quality prediction model is constructed using a TCN-GPR deep learning model (equivalent to a preset neural network model). At the same time, real-time circulating cooling blowdown data is collected by real-time monitoring equipment and input into the water quality prediction model to predict the water quality change trend of the circulating cooling blowdown and generate dynamic water quality parameter prediction data. Then, according to the dynamic water quality parameter prediction data, such as effluent concentration and water volume, etc., key parameters such as carbon source, PAC / PAM, ozone, and BAF aeration volume that match the dynamic water quality parameter prediction data are obtained to get a combination of sewage treatment parameters for circulating cooling blowdown. Then, according to the combination of sewage treatment parameters for circulating cooling blowdown, a sewage treatment regulation strategy is obtained. Finally, according to the sewage treatment regulation strategy, sewage treatment modules are selected, and the selected sewage treatment modules are recombined to obtain a new sewage treatment process pipeline for circulating cooling blowdown, thereby treating the circulating cooling blowdown for different working conditions.

[0045] An embodiment of the present invention proposes a method for treating circulating cooling blowdown. By combining historical circulating cooling blowdown data and a neural network model to construct a water quality prediction model, and then real-time monitoring the circulating cooling blowdown data, dynamic water quality parameter prediction data is predicted through the water quality prediction model. The neural network model is used to learn the fluctuation changes of historical water quality and accurately predict future water quality changes to better adapt to the water quality fluctuation conditions caused by large drainage volumes. Then, through the dynamic water quality parameter prediction data, a combination of sewage treatment parameters for circulating cooling blowdown is obtained. Then, according to the real-time circulating cooling blowdown data and the combination of sewage treatment parameters for circulating cooling blowdown, a corresponding sewage treatment regulation strategy is generated, and several sewage treatment modules are recombined to update the sewage treatment process pipeline for circulating cooling blowdown to treat the circulating cooling blowdown. Thus, through the dynamic prediction data, a combination of sewage treatment parameters for circulating cooling blowdown is obtained, a flexible adjustment strategy is provided by combining the real-time circulating cooling blowdown data, and through the corresponding sewage treatment regulation strategy, the sewage treatment process pipeline for circulating cooling blowdown is updated and optimized to treat the circulating cooling blowdown to cope with the water quality fluctuation conditions and effectively reduce the pollutant concentration in the circulating cooling blowdown to meet the sewage discharge standard, improving the reliability of sewage treatment.

[0046] As an example of an embodiment of the present invention, performing step 101 includes: obtaining historical water quality parameters based on historical circulating cooling blowdown data; constructing a water quality parameter training set based on the historical water quality parameters; performing data serialization on the water quality parameter training set to obtain a serialized water quality parameter training set; and constructing a water quality prediction model based on the serialized water quality parameter training set and a preset neural network model.

[0047] In a specific implementable manner, a large amount of historical circulating cooling blowdown data is collected, and relevant historical water quality parameters are used as input variables and output variables. The linear function normalization algorithm is used to normalize the water quality parameter training set. The specific calculation formula is as follows:

[0048]

[0049] In the formula, Y is the normalized data, x represents the original value of the corresponding variable, x max and x min are the maximum and minimum values of the corresponding variable;

[0050] After completing the data normalization process, a water quality parameter training set is constructed based on the normalized data, and the data set is constructed in matrix form. The specific calculation formula is as follows:

[0051]

[0052] In the formula, the row vector of the data set matrix represents water quality parameters of different categories, the column vector represents water quality parameters of the same category at different times, and m is the data length of each category of water quality parameters in the data set; then, the water quality parameter set is divided into a training set and a test set;

[0053] After completing the data set construction, according to the requirement of the input data size of the water quality prediction model, data serialization is performed on the water quality parameter training set. The specific calculation formula is as follows:

[0054]

[0055] In the formula, k is the number of categories of the training set, t is the data length of the training set, and Train’ is the result after the serialization process of the training set; it is worth mentioning that the test set is serially processed using a serialization method associated with the training set.

[0056] Finally, based on the serialized water quality parameter training set, a water quality prediction model is constructed using a preset neural network model, such as the TCN-GPR neural network model.

[0057] Through the above solution, by collecting historical circulating cooling blowdown water data, analyzing the historical water quality parameters affecting the water quality, serializing the water quality parameter training set, obtaining a reliable and accurate data training set, and then through serialization processing and in combination with a preset neural learning model, a water quality prediction model is constructed. Thus, a reliable data training set is provided to enable the neural learning model to learn the water quality parameters affecting water quality changes and the change trends of water quality parameters, providing a good data basis for subsequent prediction of water quality fluctuations and corresponding strategy adjustments, and improving the reliability of sewage treatment.

[0058] As an example of an embodiment of the present invention, based on the serialized water quality parameter training set and a preset neural network model, a water quality prediction model is constructed, including: inputting the serialized water quality parameter training set into the preset neural network model for the first neural learning training to obtain preliminary prediction data; inputting the preliminary prediction data into the preset neural network model for the second neural learning training to obtain deep prediction data; and based on the deep prediction data, updating the model parameters of the preset neural network model to obtain the water quality prediction model.

[0059] A specific implementable manner is explained by taking the TCN-GPR neural network model as an example. First, the TCN-GPR neural network model is constructed to include an input layer, a TCN layer, a TCN output layer, a GPR layer, and a final output layer. The training process of the TCN-GPR neural network model is divided into two stages. The first stage is the construction of the TCN neural network (equivalent to the first neural learning training), and the second stage is the construction of the GPR neural network (equivalent to the second neural learning training). Among them, in the construction of the TCN neural network in the first stage, the hidden layer of the TCN neural network (equivalent to the TCN layer) is first constructed. The hyperparameters of the TCN neural network model are set as follows: the number of TCN layers is 1, the number of convolution kernels is 64, the size of the convolution kernel is 3, and the dilation coefficients d are 1, 2, 4, 8, and 16 respectively. The remaining parameters are default parameters and will not be elaborated here. Then, the Adam model optimizer is used for learning, the loss function is set as mse, the iteration frequency is set to 300, and the batchsize is set to 32. In the design of the output layer of the TCN, the final predicted output is obtained through a series of calculations and conversions. The specific calculation formula is as follows:

[0060]

[0061] where W is the weight matrix of the fully connected layer and b is the bias vector; thus, the training of the TCN neural network is completed;

[0062] In the construction of the second-stage GPR neural network, first obtain the input training set data. The GPR layer generates a prediction result with a Gaussian distribution based on prior information. The output includes not only the expected value but also the variance information. Then, according to the kernel function, the similarity between the input data is measured, so as to predict new data and update the model parameters. In the embodiment of the present invention, the kernel function is set to RationalQuadratic(1.0, 1.0, (1e-6, 1e6), (1e-6, 1e6)). The final output layer is the output of the GPR layer, which outputs not only a definite predicted value but also the probability distribution of the prediction;

[0063] After completing the neural network learning in the first stage and the second stage, train the TCN-GPR model. Input the serialized water quality parameter training set into the TCN layer to obtain the predicted output of the TCN output layer. Use the predicted output of the TCN output layer (equivalent to the preliminary prediction data) as the input of the GPR layer, and the predicted output of the GPR layer (equivalent to the deep prediction data) as the output of the neural network model to obtain the output result of the GPR layer. Based on this process, after completing the training of the TCN-GPR model, a water quality prediction model is obtained.

[0064] Through the above solution, train the preset neural network model with an accurate and reliable serialized water quality parameter training set, so that the neural network model learns the water quality parameters and the change trend of the water quality parameters that affect the water quality change. During the training process, the model training is carried out in a phased manner. First, perform the first neural learning training to obtain the preliminary prediction data, and then perform the second neural learning training to obtain the deep prediction data. By training in a phased manner, reduce the complexity of the joint training of the neural network model, so that the preset neural model can more accurately learn the water quality parameters and the change trend of the water quality parameters that affect the water quality change, thereby improving the prediction accuracy of the water quality prediction model, and further affecting the accuracy of the subsequent corresponding strategy adjustment, thereby improving the reliability of sewage treatment.

[0065] As an example of the embodiment of the present invention, execute step 102. By real-time monitoring the circulating cooling blowdown water data and inputting the circulating cooling blowdown water data into the water quality prediction model, dynamic prediction data of water quality parameters is obtained. In this embodiment, sensors or on-line monitoring devices can be used to monitor the real-time circulating cooling blowdown water data.

[0066] As an example of the embodiment of the present invention, execute step 103, which includes: based on the historical experimental data and the historical circulating cooling blowdown water treatment strategy, input the dynamic prediction data of water quality parameters into the preset artificial intelligence model to match the corresponding circulating cooling blowdown water treatment parameters; based on the dynamic prediction data of water quality parameters and the corresponding circulating cooling blowdown water treatment parameters, construct a circulating cooling blowdown water treatment parameter combination.

[0067] In a specific implementable manner, the dynamic prediction data of water quality parameters is deeply integrated with a preset artificial intelligence model, combined with laboratory experiment data, on-site pilot test data, historical sewage treatment case data of similar processes, and Internet-related data (equivalent to historical experiment data and historical circulating cooling sewage treatment strategies). By inputting the dynamic prediction data of water quality parameters such as effluent concentration and water volume into the preset artificial intelligence model, the preset artificial intelligence model matches key parameters such as carbon source, PAC / PAM, ozone, and BAF aeration volume according to the historical experiment data and historical circulating cooling sewage treatment strategies. In this embodiment, in order to generate a more accurate regulation strategy subsequently, it is necessary to further select the optimal combination relationship between each key parameter. For example, for the prediction data: the output ammonia nitrogen concentration, total nitrogen concentration, total phosphorus concentration, and COD concentration, the key parameters corresponding to the optimal combination relationship include: the output carbon source dosing COD equivalent, the output PAC dosing amount, the output PAM dosing amount, the output ozone dosing amount, and the output BAF aeration volume.

[0068] Through the above solution, the historical experiment data and historical circulating cooling sewage treatment strategies are used to match the corresponding circulating cooling sewage treatment parameters in the preset artificial intelligence model. Based on historical cases, the circulating cooling sewage treatment parameters are matched, which can verify the dynamic prediction data of water quality parameters, match the dynamic change trend of water quality parameters to historical cases, and construct a circulating cooling sewage treatment parameter combination in combination with historical treatment experience, which can ensure the reliability of subsequent strategy adjustment and improve the reliability of sewage treatment.

[0069] As an example of the embodiment of the present invention, performing step 104 includes: obtaining a real-time water quality parameter combination based on the real-time circulating cooling sewage data; matching a circulating cooling sewage treatment parameter combination that meets the preset requirements based on the real-time water quality parameter combination; generating a corresponding sewage treatment regulation strategy based on the preset artificial intelligence model and the circulating cooling sewage treatment parameter combination;

[0070] In a specific implementable manner, according to the real-time monitored circulating cooling sewage data, a real-time water quality parameter combination is obtained. The water quality parameters include: the output ammonia nitrogen concentration, total nitrogen concentration, total phosphorus concentration, COD concentration, etc. According to the water quality parameter combination, a circulating cooling sewage treatment parameter combination is matched. The matched circulating cooling sewage treatment parameters include: the output carbon source dosing COD equivalent, the output PAC dosing amount, the output PAM dosing amount, the output ozone dosing amount, and the output BAF aeration volume, etc. Then, according to the circulating cooling sewage treatment parameter combination, the preset artificial intelligence model outputs a corresponding sewage treatment regulation strategy. In this embodiment, the real-time water quality parameter combination is used to match a circulating cooling sewage treatment parameter combination that meets the preset requirements (equivalent to the optimal combination relationship). Specific examples are as follows:

[0071] Scenario 1: The ammonia nitrogen concentration output by the water quality prediction model is 0.95 mg / L, the total nitrogen concentration is 34.5 mg / L, the total phosphorus concentration is 1.14 mg / L, and the COD concentration is 37.9 mg / L. The optimal combination relationship is as follows: the output COD equivalent of carbon source dosing is (34.5 - 15) * 4 = 78 g COD / t wastewater, the output PAC dosing amount is 150 * 1.14 = 171 g PAC / t wastewater, the output PAM dosing amount is 171 / 35 = 4.89 g PAM / t wastewater, the output ozone dosing amount is (34.5 * 2 - 40) * 2.5 = 72.5 g ozone / t wastewater, the output BAF aeration volume = (40 - 10) * 0.2 = 2 L / min air flow / t wastewater, and the sewage treatment control strategy is: all sewage treatment modules operate normally;

[0072] Scenario 2: The ammonia nitrogen concentration output by the water quality prediction model is 0.61 mg / L, the total nitrogen concentration is 14.5 mg / L, the total phosphorus concentration is 1.59 mg / L, and the COD concentration is 89.3 mg / L. The optimal combination relationship is as follows: the output COD equivalent of carbon source dosing is (14.5 - 15) * 4 = 0 g COD / t wastewater, the output PAC dosing amount is 150 * 1.59 = 239 g PAC / t wastewater, the output PAM dosing amount is 239 / 35 = 6.83 g PAM / t wastewater, the output ozone dosing amount is (89.3 * 1.8 - 50) * 2.5 = 276.85 g ozone / t wastewater, the output BAF aeration volume = (50 - 10) * 0.2 = 4 L / min air flow / t wastewater, and the sewage treatment control strategy is: the sewage treatment module responsible for treating the output COD of carbon source dosing does not operate, and the rest of the sewage treatment modules operate normally;

[0073] Scenario 3: The ammonia nitrogen concentration output by the water quality prediction model is 0.89 mg / L, the total nitrogen concentration is 47.1 mg / L, the total phosphorus concentration is 0.28 mg / L, and the COD concentration is 35.2 mg / L. The optimal combination relationship is as follows: the output COD equivalent of carbon source dosing is (47.1 - 15) * 4 = 128.4 g COD / t wastewater, the output PAC dosing amount is 150 * 0 = 0 g PAC / t wastewater, the output PAM dosing amount is 0 / 35 = 0 g PAM / t wastewater, the output ozone dosing amount is (35.2 * 2 - 40) * 2.5 = 76 g ozone / t wastewater, the output BAF aeration volume = (40 - 10) * 0.2 = 2 L / min air flow / t wastewater; the sewage treatment control strategy is: the sewage treatment modules responsible for treating the output PAC dosing and the output PAM dosing do not operate, and the rest of the sewage treatment modules operate normally;

[0074] Scenario 4: The ammonia nitrogen concentration is 1.5 mg / L, the total nitrogen concentration is 27.1 mg / L, the total phosphorus concentration is 0.38 mg / L, and the COD concentration is 25 mg / L as output by the water quality prediction model. At this time, the optimal combination relationship is as follows: the output carbon source dosing COD equivalent is (27.1 - 15) * 4 = 48.4 g COD / t wastewater, the output PAC dosing amount is 150 * 0.38 = 57 g PAC / t wastewater, the output PAM dosing amount is 57 / 35 = 1.63 g PAM / t wastewater, the output ozone dosing amount is (25 * 2 - 20) * 2.5 = 75 g ozone / t wastewater, the output BAF aeration volume = 0 * 0.2 = 0 L / min air flow / t wastewater, and the sewage treatment control strategy is: the sewage treatment module responsible for treating the output BAF aeration does not operate, and the other sewage treatment modules operate normally.

[0075] Through the above solution, analyze the real-time circulating cooling blowdown data to obtain real-time water quality parameters, then match the sewage treatment parameter combinations for circulating cooling blowdown constructed based on historical treatment experience, and then generate corresponding sewage treatment control strategies by the preset artificial intelligence model with the sewage treatment parameter combinations for circulating cooling blowdown to treat the circulating cooling blowdown. Provide a flexible adjustment strategy by combining the real-time circulating cooling blowdown data, optimize the circulating cooling blowdown treatment process through the corresponding sewage treatment control strategy, cope with the water quality fluctuation conditions and effectively reduce the pollutant concentration in the circulating cooling blowdown to meet the sewage discharge standard, and improve the reliability of sewage treatment.

[0076] As an example of an embodiment of the present invention, performing step 105 includes: obtaining the sewage treatment target for circulating cooling blowdown based on the corresponding sewage treatment control strategy; selecting a number of sewage treatment modules based on the sewage treatment target for circulating cooling blowdown to obtain a number of target sewage treatment modules; combining the number of target sewage treatment modules to update the sewage treatment process pipeline for circulating cooling blowdown to obtain the target sewage treatment process pipeline for circulating cooling blowdown; and treating the circulating cooling blowdown based on the target sewage treatment process pipeline for circulating cooling blowdown.

[0077] In a specific implementable manner, according to the sewage treatment control strategy, obtain the sewage treatment target for circulating cooling blowdown. According to the sewage treatment target for circulating cooling blowdown, it is possible to identify the sewage treatment modules that need to operate, and then select the sewage treatment modules that need to operate for recombination to construct a new target sewage treatment process pipeline for circulating cooling blowdown. Treat the circulating cooling blowdown based on the target sewage treatment process pipeline for circulating cooling blowdown. For example: the sewage treatment control strategy is that the sewage treatment module responsible for treating the output carbon source dosing COD does not operate, and the other sewage treatment modules operate normally. Then select the sewage treatment modules that are not responsible for treating the output carbon source dosing COD for combination to obtain a new circulating cooling blowdown treatment loop.

[0078] Through the above solution, according to the corresponding sewage treatment regulation strategy, the sewage treatment target of the circulating cooling blowdown is obtained. Then, the required target sewage treatment modules are selected, combined, and the sewage treatment process pipeline of the circulating cooling blowdown is updated to obtain the target sewage treatment process pipeline of the circulating cooling blowdown. The circulating cooling blowdown is treated by providing a flexible adjustment strategy in the sewage treatment process pipeline of the circulating cooling blowdown, recombining the sewage treatment modules, only using the required sewage treatment modules, and optimizing the sewage treatment process pipeline of the circulating cooling blowdown to cope with the water quality fluctuation situation and effectively reduce the pollutant concentration in the circulating cooling blowdown to meet the sewage discharge standard, thereby improving the reliability of sewage treatment.

[0079] As an example of an embodiment of the present invention, the sewage treatment module includes: an upflow anoxic sludge film tank 2, a flocculation sedimentation tank 3, an ozone catalytic oxidation tank 4, and a biological aerated filter 5. Treating the circulating cooling blowdown based on the target sewage treatment process pipeline of the circulating cooling blowdown includes: if the target sewage treatment process pipeline of the circulating cooling blowdown includes the upflow anoxic sludge film tank 2, obtaining the chemical dosing strategy of the upflow anoxic sludge film tank according to the corresponding sewage treatment regulation strategy and treating the circulating cooling blowdown; if the target sewage treatment process pipeline of the circulating cooling blowdown includes the flocculation sedimentation tank 3, obtaining the chemical dosing strategy of the flocculation sedimentation tank according to the corresponding sewage treatment regulation strategy and treating the circulating cooling blowdown; if the target sewage treatment process pipeline of the circulating cooling blowdown includes the ozone catalytic oxidation tank 4, obtaining the chemical dosing strategy of the ozone catalytic oxidation tank according to the corresponding sewage treatment regulation strategy and treating the circulating cooling blowdown; if the target sewage treatment process pipeline of the circulating cooling blowdown includes the biological aerated filter 5, obtaining the operation strategy of the biological aerated filter according to the corresponding sewage treatment regulation strategy and treating the circulating cooling blowdown.

[0080] A specific implementable manner is shown in Figure 2 , Figure 2 is a structural schematic diagram of the sewage treatment process pipeline of a circulating cooling blowdown treatment method provided by an embodiment of the present invention; as Figure 2As shown in the figure, in the embodiment of the present invention, the process pipeline for treating circulating cooling blowdown sewage includes: a circulating cooling tower inlet bucket 1, an upflow anoxic sludge film tank 2, a flocculation sedimentation tank 3, an ozone catalytic oxidation tank 4, a biological aerated filter 5, a first bypass pipeline 6, a second bypass pipeline 7, a third bypass pipeline 8, an outlet 9 and several pumps. The circulating cooling tower inlet bucket 1 is connected to the bottom of the upflow anoxic sludge film tank 2. The upflow anoxic sludge film tank 2 is connected to the flocculation sedimentation tank 3. The flocculation sedimentation tank 3 is connected to the bottom of the ozone catalytic oxidation tank 4. The biological aerated filter 5 is arranged between the ozone catalytic oxidation tank 4 and the outlet 9 and is respectively connected to the ozone catalytic oxidation tank 4 and the outlet 9. The first bypass pipeline 6 connects the circulating cooling tower inlet bucket 1 and the flocculation sedimentation tank 3. The second bypass pipeline 7 connects the upflow anoxic sludge film tank 2 and the ozone catalytic oxidation tank 4. The third bypass pipeline 8 connects the ozone catalytic oxidation tank 4 and the outlet 9. The specific working principle of the process pipeline for treating circulating cooling blowdown sewage is as follows: The circulating cooling blowdown sewage is stored in the circulating cooling tower inlet bucket 1 and is pumped into the bottom of the upflow anoxic sludge film tank 2 by the circulating cooling blowdown sewage inlet pump 10. The water discharged from the upflow anoxic sludge film tank 2 flows by gravity into the flocculation sedimentation tank 3. The flocculation sedimentation tank 3 includes a flocculation tank and a sedimentation tank. The water discharged from the flocculation tank flows by gravity into the sedimentation tank. After the sedimentation tank completes the separation of mud and water, the supernatant flows by gravity into the ozone catalytic oxidation tank 4. The biological aerated filter inlet pump 11 pumps the circulating cooling sewage treated by ozone into the biological aerated filter 5. The treated circulating cooling blowdown sewage flows out through the outlet after passing through. The above is the most basic operating principle of a process pipeline for treating circulating cooling blowdown sewage proposed in this embodiment. Among them, according to the dosing strategy of the upflow anoxic sludge film tank, the carbon source dosing pump 12 pumps the carbon source into the upflow anoxic sludge film tank 2 to provide the substrate required for the denitrification reaction. The upflow anoxic sludge film tank 2 performs internal reflux through the sludge film tank reflux pump 13 to enhance mass transfer of the substrate and improve the nitrogen removal effect of the upflow anoxic sludge film tank 2. According to the dosing strategy of the flocculation sedimentation tank, the flocculation sedimentation tank 3 is stirred by the stirrer 14 to fully mix the water discharged from the upflow anoxic sludge film tank 2 with the PAC agent dosed by the PAC dosing pump 15 and the PAM dosed by the PAM dosing pump 16, so as to achieve the purpose of removing total phosphorus / SS pollutants. According to the dosing strategy of the ozone catalytic oxidation tank, the ozone generator 17 generates ozone and introduces it into the ozone catalytic oxidation tank 4. The ozone catalytic oxidation tank 4 is filled with ozone catalytic oxidation packing. According to the operation strategy of the biological aerated filter, the ozone catalytic oxidation tank 4 is connected to the biological aerated filter inlet pump 11 to pump the circulating cooling sewage treated by ozone into the biological aerated filter 5 for biochemical nitrogen removal / carbon removal treatment. The biological aerated filter 5 is filled with ceramsite packing. The biological aerated filter 5 performs internal reflux circulation through the biological aerated filter reflux pump 18. The treated and qualified wastewater is discharged through the biological aerated filter 5. The outlet of the fan 19 is connected to the bottom of the biological aerated filter 5, and oxygen is supplied to the microorganisms attached to the packing filled in the biological aerated filter 5 through the fan 19 for biochemical reactions;In this embodiment, the carbon source dosing pump 12, PAC dosing pump 15, ozone generator 17, fan 19, etc. are all controlled by the PLC artificial intelligence control system. Among them, the operation strategy of the biological aerated filter is as follows: when the influent ammonia nitrogen concentration is low and the COD concentration is high, it automatically switches to the aerobic operation mode. In this mode, the BAF process mainly utilizes the metabolic action of aerobic microorganisms to efficiently degrade the organic pollutants (COD) in the water, and at the same time further removes the residual ammonia nitrogen to ensure that the effluent water quality meets the standards stably, so the consumption of ozone at the front end can be reduced. When the influent total nitrogen concentration is high and the COD concentration is low, it automatically switches to the anoxic operation mode. In this mode, the BAF process uses nitrate in the water as an electron acceptor through denitrification to reduce nitrate to nitrogen, thereby achieving efficient total nitrogen removal. At the same time, the BAF can utilize the small molecular organic matter produced by the ozone oxidation of refractory organic matter, which can save the carbon source dosing amount of the upflow sludge film tank at the front end.

[0081] For the chemical dosing strategies of the upflow anoxic sludge film tank, flocculation sedimentation tank, and ozone catalytic oxidation tank, further explanations are given taking Scenario 2, Scenario 3, and Scenario 4 as examples:

[0082] Scenario 2: The ammonia nitrogen concentration output by the water quality prediction model is 0.61 mg / L, the total nitrogen concentration is 14.5 mg / L, the total phosphorus concentration is 1.59 mg / L, and the COD concentration is 89.3 mg / L. The optimal combination relationship is as follows: The output COD equivalent of carbon source addition is (14.5 - 15) * 4 = 0 gCOD / t wastewater, the output PAC addition amount is 150 * 1.59 = 239 gPAC / t wastewater, the output PAM addition amount is 239 / 35 = 6.83 gPAM / t wastewater, the output ozone addition amount is (89.3 * 1.8 - 50) * 2.5 = 276.85 g ozone / t wastewater, the output BAF aeration volume = (50 - 10) * 0.2 = 4 L / min air flow / t wastewater. The sewage treatment control strategy is: The sewage treatment module responsible for treating the output COD of carbon source addition does not operate, and the other sewage treatment modules operate normally; According to the sewage treatment control strategy, the PLC artificial intelligence control system controls the opening of the first bypass pipeline, so that the upflow anoxic sludge membrane tank 2 does not operate, and then updates the circulating cooling sewage treatment process pipeline to: circulating cooling tower water inlet bucket 1 - first bypass pipeline 6 - flocculation sedimentation tank 3 - ozone catalytic oxidation tank 4 - biological aerated filter 5 - water outlet 9; In Scenario 2, the water quality parameters output by the water quality prediction model show that the total nitrogen is lower than the Class IV surface water discharge standard (except for total nitrogen, the total nitrogen requirement is less than 15 mg / L). Therefore, the first bypass pipeline 6 is opened, so that the circulating cooling sewage does not need to be treated by the upflow sludge membrane tank 2, and only the flocculation sedimentation tank chemical dosing strategy, the ozone catalytic oxidation tank chemical dosing strategy, and the biological aerated filter operation strategy are implemented, shortening the system residence time, reducing the system carbon source addition amount, and reducing the SS concentration entering the flocculation sedimentation tank 3;

[0083] Scenario 3: The ammonia nitrogen concentration output by the water quality prediction model is 0.89 mg / L, the total nitrogen concentration is 47.1 mg / L, the total phosphorus concentration is 0.28 mg / L, and the COD concentration is 35.2 mg / L. The optimal combination relationship is as follows: the output COD equivalent of carbon source addition is (47.1 - 15) * 4 = 128.4 gCOD / t wastewater, the output PAC addition amount is 150 * 0 = 0 gPAC / t wastewater, the output PAM addition amount is 0 / 35 = 0 gPAM / t wastewater, the output ozone addition amount is (35.2 * 2 - 40) * 2.5 = 76 g ozone / t wastewater, and the output BAF aeration volume = (40 - 10) * 0.2 = 2 L / min air flow / t wastewater; The sewage treatment control strategy is: the sewage treatment modules responsible for processing the output PAC addition and the output PAM addition do not operate, and the other sewage treatment modules operate normally; According to the sewage treatment control strategy, the PLC artificial intelligence control system controls the opening of the second bypass pipeline 7, so that the flocculation sedimentation tank 3 does not operate, and then updates the circulating cooling sewage treatment process pipeline to: circulating cooling tower water inlet bucket 1 - upflow anoxic sludge film tank 2 - second bypass pipeline 7 - ozone catalytic oxidation tank 4 - biological aerated filter 5 - water outlet 9; In Scenario 3, the water quality parameters output by the water quality prediction model show that the total phosphorus is lower than the Class IV surface water discharge standard (except for total nitrogen, the total nitrogen requirement is less than 15 mg / L) (total phosphorus < 0.3 mg / L). Therefore, the second bypass pipeline 7 is opened, so that the circulating cooling sewage does not need to be treated by the flocculation sedimentation tank 3, and only the dosing strategies of the upflow anoxic sludge film tank, the ozone catalytic oxidation tank, and the operation strategy of the biological aerated filter are implemented, shortening the system residence time and reducing the system coagulant and flocculant dosage;

[0084] Scenario 4: The ammonia nitrogen concentration is 1.5 mg / L, the total nitrogen concentration is 27.1 mg / L, the total phosphorus concentration is 0.38 mg / L, and the COD concentration is 25 mg / L as output by the water quality prediction model. The optimal combination relationship is as follows: The output carbon source dosage in terms of COD equivalent is (27.1 - 15) * 4 = 48.4 g COD / t of wastewater; the output PAC dosage is 150 * 0.38 = 57 g PAC / t of wastewater; the output PAM dosage is 57 / 35 = 1.63 g PAM / t of wastewater; the output ozone dosage is (25 * 2 - 20) * 2.5 = 75 g ozone / t of wastewater; the output BAF aeration volume = 0 * 0.2 = 0 L / min of air flow / t of wastewater. The sewage treatment control strategy is: The sewage treatment module responsible for BAF aeration does not operate, and the other sewage treatment modules operate normally. According to the sewage treatment control strategy, the PLC artificial intelligence control system controls the opening of the third bypass pipeline 8, so that the biological aerated filter 5 does not operate, and then the sewage treatment process pipeline for circulating cooling blowdown is updated to: the water inlet bucket of the circulating cooling tower 1 - upflow anoxic sludge film tank 2 - flocculation sedimentation tank 3 - ozone catalytic oxidation tank 4 - third bypass pipeline 8 - water outlet 9. In Scenario 4, the water quality parameters output by the water quality prediction model show that the COD is relatively low. After being treated by the ozone catalytic oxidation tank 4 with the lowest ozone dosage, it can be stably lower than the Class IV surface water discharge standard (except for total nitrogen, the total nitrogen requirement is less than 15 mg / L) (COD < 30 mg / L). Therefore, by opening the third bypass pipeline 8, the circulating cooling blowdown does not need to pass through the treatment of the biological aerated filter 5, and only the chemical dosing strategies of the upflow anoxic sludge film tank, the flocculation sedimentation tank, and the ozone catalytic oxidation tank are implemented, shortening the system residence time and reducing the system energy consumption.

[0085] Through the above solution, by adjusting the chemical dosing strategies of the upflow anoxic sludge film tank, the flocculation sedimentation tank, the ozone catalytic oxidation tank, and the operation strategy of the biological aerated filter, the use strategy of the chemicals is reasonably set to treat the circulating cooling blowdown, thereby providing a flexible adjustment strategy in the sewage treatment process pipeline for circulating cooling blowdown, coping with the water quality fluctuation condition and effectively reducing the pollutant concentration in the circulating cooling blowdown to meet the sewage discharge standard, and improving the reliability of sewage treatment.

[0086] Example 2

[0087] See Figure 3 , Figure 3 which is a schematic diagram of the module structure of a circulating cooling blowdown treatment system provided by an embodiment of the present invention. As Figure 2As shown in the figure, an embodiment of the present invention provides a circulating cooling sewage treatment system, including: a water quality prediction model construction module 201, a water quality parameter dynamic prediction module 202, a circulating cooling sewage parameter combination module 203, a sewage treatment strategy acquisition module 204, and a circulating cooling sewage treatment module 205; the water quality prediction model construction module 201 is used to construct a water quality prediction model based on historical circulating cooling sewage data and a preset neural network model; the water quality parameter dynamic prediction module 202 is used to input real-time circulating cooling sewage data into the water quality prediction model to obtain water quality parameter dynamic prediction data; the circulating cooling sewage parameter combination module 203 is used to obtain a circulating cooling sewage treatment parameter combination based on the water quality parameter dynamic prediction data; the sewage treatment strategy acquisition module 204 is used to generate a corresponding sewage treatment regulation strategy based on the real-time circulating cooling sewage data and the circulating cooling sewage treatment parameter combination; the circulating cooling sewage treatment module 205 is used to recombine a number of sewage treatment modules based on the corresponding sewage treatment regulation strategy, update the circulating cooling sewage treatment process pipeline, and treat the circulating cooling sewage.

[0088] Specifically, an implementable embodiment of the present invention provides a circulating cooling sewage treatment system that executes a circulating cooling sewage treatment method and is applied to a circulating cooling sewage treatment process pipeline. The circulating cooling sewage treatment process pipeline is composed of a number of sewage treatment modules. The water quality prediction model construction module 201 constructs a water quality prediction model by collecting a large amount of historical circulating cooling sewage data and using a TCN-GPR deep learning model (equivalent to a preset neural network model). At the same time, the water quality parameter dynamic prediction module 202 collects real-time circulating cooling sewage data according to real-time monitoring equipment and inputs it into the water quality prediction model to predict the water quality change trend of the circulating cooling sewage and generate water quality parameter dynamic prediction data. Then, the circulating cooling sewage parameter combination module 203 obtains key parameters such as carbon source, PAC / PAM, ozone, and BAF aeration volume that match the water quality parameter dynamic prediction data, such as effluent concentration and water volume, to obtain a circulating cooling sewage treatment parameter combination. The sewage treatment strategy acquisition module 204 then obtains a sewage treatment regulation strategy according to the circulating cooling sewage treatment parameter combination. Finally, the circulating cooling sewage treatment module 205 selects sewage treatment modules according to the sewage treatment regulation strategy, recombines the selected sewage treatment modules to obtain a new circulating cooling sewage treatment process pipeline, and thus treats the circulating cooling sewage for different working conditions.

[0089] An embodiment of the present invention provides a circulating cooling sewage treatment system. The water quality prediction model construction module constructs a water quality prediction model by combining historical circulating cooling sewage data and a neural network model. The water quality parameter dynamic prediction module then monitors the circulating cooling sewage data in real time, and obtains the dynamic prediction data of water quality parameters through the water quality prediction model. The neural network model is used to learn the fluctuation changes of historical water quality and accurately predict the future water quality changes, so as to better adapt to the water quality fluctuation conditions caused by large drainage volume. The circulating cooling sewage treatment parameter combination module then obtains the circulating cooling sewage treatment parameter combination through the dynamic prediction data of water quality parameters. The sewage treatment strategy acquisition module and the circulating cooling sewage treatment module then generate corresponding sewage treatment control strategies according to the real-time circulating cooling sewage data and the circulating cooling sewage treatment parameter combination, and recombine several sewage treatment modules to update the circulating cooling sewage treatment process pipeline and treat the circulating cooling sewage. Thus, the circulating cooling sewage treatment parameter combination is obtained through the dynamic prediction data, a flexible adjustment strategy is provided by combining the real-time circulating cooling sewage data, the circulating cooling sewage treatment process pipeline is updated and optimized through the corresponding sewage treatment control strategy, and the circulating cooling sewage is treated to cope with the water quality fluctuation conditions and effectively reduce the pollutant concentration in the circulating cooling sewage to meet the sewage discharge standard, improving the reliability of sewage treatment.

[0090] As an example of the embodiment of the present invention, the circulating cooling sewage treatment module is used to recombine several sewage treatment modules based on the corresponding sewage treatment control strategy, update the circulating cooling sewage treatment process pipeline to treat the circulating cooling sewage, including: a treatment target acquisition unit, a treatment module selection unit, a process pipeline update unit, and a target treatment unit; the treatment target acquisition unit is used to obtain the circulating cooling sewage treatment target based on the corresponding sewage treatment control strategy; the treatment module selection unit is used to select several sewage treatment modules based on the circulating cooling sewage treatment target to obtain several target sewage treatment modules; the process pipeline update unit is used to combine several target sewage treatment modules to update the circulating cooling sewage treatment process pipeline to obtain the target circulating cooling sewage treatment process pipeline; the target treatment unit is used to treat the circulating cooling sewage based on the target circulating cooling sewage treatment process pipeline.

[0091] In a specific implementable manner, the processing target acquisition unit acquires the sewage treatment target for circulating cooling blowdown according to the sewage treatment regulation strategy. The processing module selection unit can identify the sewage treatment modules that need to operate based on the sewage treatment target for circulating cooling blowdown, and then select the sewage treatment modules that need to operate for recombination. The process pipeline update unit constructs a new target sewage treatment process pipeline for circulating cooling blowdown. The target processing unit treats the circulating cooling blowdown based on the target sewage treatment process pipeline for circulating cooling blowdown. For example, if the sewage treatment regulation strategy is that the sewage treatment module responsible for treating and outputting carbon source addition COD does not operate, and the other sewage treatment modules operate normally, then select the sewage treatment modules that are not responsible for treating and outputting carbon source addition COD for combination to obtain a new sewage treatment loop for circulating cooling blowdown.

[0092] Through the above solution, according to the corresponding sewage treatment regulation strategy, the sewage treatment target for circulating cooling blowdown is acquired. Thereby, the required target sewage treatment modules are selected, the target sewage treatment modules are combined, the sewage treatment process pipeline for circulating cooling blowdown is updated to obtain the target sewage treatment process pipeline for circulating cooling blowdown, and the circulating cooling blowdown is treated. By providing a flexible adjustment strategy in the sewage treatment process pipeline for circulating cooling blowdown, recombining the sewage treatment modules, only using the required sewage treatment modules, optimizing the sewage treatment process pipeline for circulating cooling blowdown, to cope with the water quality fluctuation situation and effectively reduce the pollutant concentration in the circulating cooling blowdown to meet the sewage discharge standard, and improve the reliability of sewage treatment.

[0093] As an example of an embodiment of the present invention, the sewage treatment module includes: an upflow anoxic sludge film tank 2, a flocculation sedimentation tank 3, an ozone catalytic oxidation tank 4, and an aerated biological filter 5; the target treatment unit is used to treat the circulating cooling blowdown sewage based on the target circulating cooling blowdown sewage treatment process pipeline, including: a first circulating cooling blowdown sewage treatment sub-unit, a second circulating cooling blowdown sewage treatment sub-unit, a third circulating cooling blowdown sewage treatment sub-unit, and a fourth circulating cooling blowdown sewage treatment sub-unit; the first circulating cooling blowdown sewage treatment sub-unit is used to, if the target circulating cooling blowdown sewage treatment process pipeline includes the upflow anoxic sludge film tank 2, obtain the chemical dosing strategy for the upflow anoxic sludge film tank according to the corresponding sewage treatment control strategy, and treat the circulating cooling blowdown sewage; the second circulating cooling blowdown sewage treatment sub-unit is used to, if the target circulating cooling blowdown sewage treatment process pipeline includes the flocculation sedimentation tank 3, obtain the chemical dosing strategy for the flocculation sedimentation tank according to the corresponding sewage treatment control strategy, and treat the circulating cooling blowdown sewage; the third circulating cooling blowdown sewage treatment sub-unit is used to, if the target circulating cooling blowdown sewage treatment process pipeline includes the ozone catalytic oxidation tank 4, obtain the chemical dosing strategy for the ozone catalytic oxidation tank according to the corresponding sewage treatment control strategy, and treat the circulating cooling blowdown sewage; the fourth circulating cooling blowdown sewage treatment sub-unit is used to, if the target circulating cooling blowdown sewage treatment process pipeline includes the aerated biological filter 5, obtain the operation strategy for the aerated biological filter according to the corresponding sewage treatment control strategy, and treat the circulating cooling blowdown sewage.

[0094] For a specific implementable manner, refer to Figure 2 , Figure 2 is a structural schematic diagram of the circulating cooling blowdown sewage treatment process pipeline of a circulating cooling blowdown sewage treatment method provided by an embodiment of the present invention; as Figure 2As shown in the figure, in the embodiment of the present invention, the process pipeline for treating circulating cooling blowdown sewage includes: a circulating cooling tower inlet bucket 1, an upflow anoxic sludge film tank 2, a flocculation sedimentation tank 3, an ozone catalytic oxidation tank 4, a biological aerated filter 5, a first bypass pipeline 6, a second bypass pipeline 7, a third bypass pipeline 8, a water outlet 9 and several pumps. The circulating cooling tower inlet bucket 1 is connected to the bottom of the upflow anoxic sludge film tank 2, the upflow anoxic sludge film tank 2 is connected to the flocculation sedimentation tank 3, the flocculation sedimentation tank 3 is connected to the bottom of the ozone catalytic oxidation tank 4, and the biological aerated filter 5 is arranged between the ozone catalytic oxidation tank 4 and the water outlet 9 and is respectively connected to the ozone catalytic oxidation tank 4 and the water outlet 9; the first bypass pipeline 6 connects the circulating cooling tower inlet bucket 1 and the flocculation sedimentation tank 3, the second bypass pipeline 7 connects the upflow anoxic sludge film tank 2 and the ozone catalytic oxidation tank 4; the third bypass pipeline 8 connects the ozone catalytic oxidation tank 4 and the water outlet 9; the specific working principle of the process pipeline for treating circulating cooling blowdown sewage is as follows: the circulating cooling blowdown sewage is stored in the circulating cooling tower inlet bucket 1 and is pumped into the bottom of the upflow anoxic sludge film tank 2 by a circulating cooling blowdown sewage inlet pump 10. The water discharged from the upflow anoxic sludge film tank 2 flows into the flocculation sedimentation tank 3 by gravity. The flocculation sedimentation tank 3 includes a flocculation tank and a sedimentation tank. The water discharged from the flocculation tank flows into the sedimentation tank by gravity. After the sedimentation tank completes the separation of mud and water, the supernatant flows into the ozone catalytic oxidation tank 4 by gravity. A biological aerated filter inlet pump 11 pumps the circulating cooling sewage treated by ozone into the biological aerated filter 5, and the treated circulating cooling blowdown sewage flows out through the water outlet by gravity. The above is the most basic operation principle of a process pipeline for treating circulating cooling blowdown sewage proposed in this embodiment. Among them, for the first sub-unit for treating circulating cooling blowdown sewage, according to the dosing strategy of the upflow anoxic sludge film tank, a carbon source dosing pump 12 pumps a carbon source into the upflow anoxic sludge film tank 2 to provide the substrate required for the denitrification reaction. The upflow anoxic sludge film tank 2 performs internal reflux through a sludge film tank reflux pump 13 to enhance mass transfer of the substrate and improve the nitrogen removal effect of the upflow anoxic sludge film tank 2; for the second sub-unit for treating circulating cooling blowdown sewage, according to the dosing strategy of the flocculation sedimentation tank, the flocculation sedimentation tank 3 is stirred by a stirrer 14 to fully mix the water discharged from the upflow anoxic sludge film tank 2 with the PAC agent dosed by a PAC dosing pump 15 and the PAM dosed by a PAM dosing pump 16, so as to achieve the purpose of removing total phosphorus / SS pollutants; for the third sub-unit for treating circulating cooling blowdown sewage, according to the dosing strategy of the ozone catalytic oxidation tank, an ozone generator 17 generates ozone and introduces it into the ozone catalytic oxidation tank 4, and the ozone catalytic oxidation tank 4 is filled with ozone catalytic oxidation fillers;The fourth cycle cooling wastewater treatment sub-unit, according to the operation strategy of the biological aerated filter, connects the ozone catalytic oxidation tank 4 to the inlet water pump 11 of the biological aerated filter to pump the circulating cooling wastewater after ozone treatment into the biological aerated filter 5 for biochemical denitrification / carbon removal treatment. The biological aerated filter 5 is filled with ceramsite packing. The biological aerated filter 5 performs internal reflux circulation through the biological aerated filter reflux pump 18. The treated and up-to-standard wastewater is discharged through the biological aerated filter 5. The outlet of the blower 19 is connected to the bottom of the biological aerated filter 5, and the blower 19 supplies oxygen to the microorganisms attached to the packing filled in the biological aerated filter 5 for biochemical reactions; in this embodiment, the carbon source dosing pump 12, PAC dosing pump 15, ozone generator 17, blower 19, etc. are all controlled by the PLC artificial intelligence control system; among them, the operation strategy of the biological aerated filter is: when the influent ammonia nitrogen concentration is low and the COD concentration is high, it automatically switches to the aerobic operation mode. In this mode, the BAF process mainly uses the metabolic action of aerobic microorganisms to efficiently degrade the organic pollutants (COD) in the water, and at the same time further removes the residual ammonia nitrogen to ensure that the effluent water quality meets the standards stably, so the consumption of ozone at the front end can be reduced; when the influent total nitrogen concentration is high and the COD concentration is low, it automatically switches to the anoxic operation mode. In this mode, the BAF process uses the nitrate in the water as an electron acceptor through denitrification to reduce the nitrate to nitrogen, so as to achieve efficient total nitrogen removal. At the same time, the BAF can use the small molecular organic matter generated by the ozone oxidation of refractory organic matter, which can save the carbon source dosing amount of the upflow sludge film tank at the front end;

[0095] For the chemical dosing strategies of the upflow anoxic sludge film tank, flocculation sedimentation tank, and ozone catalytic oxidation tank, further explanations are given by taking Scenario 2, Scenario 3, and Scenario 4 as examples:

[0096] Scenario 2: The ammonia nitrogen concentration output by the water quality prediction model is 0.61 mg / L, the total nitrogen concentration is 14.5 mg / L, the total phosphorus concentration is 1.59 mg / L, and the COD concentration is 89.3 mg / L. The optimal combination relationship at this time is as follows: the output COD equivalent of carbon source addition is (14.5 - 15) * 4 = 0 g COD / t wastewater, the output PAC addition amount is 150 * 1.59 = 239 g PAC / t wastewater, the output PAM addition amount is 239 / 35 = 6.83 g PAM / t wastewater, the output ozone addition amount is (89.3 * 1.8 - 50) * 2.5 = 276.85 g ozone / t wastewater, the output BAF aeration volume = (50 - 10) * 0.2 = 4 L / min air flow / t wastewater. The sewage treatment control strategy is: the sewage treatment module responsible for treating the output COD of carbon source addition does not operate, and the other sewage treatment modules operate normally; according to the sewage treatment control strategy, the PLC artificial intelligence control system controls the opening of the first bypass pipeline, so that the upflow anoxic sludge film tank 2 does not operate, and then updates the circulating cooling sewage treatment process pipeline to: circulating cooling tower inlet bucket 1 - first bypass pipeline 6 - flocculation sedimentation tank 3 - ozone catalytic oxidation tank 4 - biological aerated filter 5 - outlet 9; in Scenario 2, the water quality parameters output by the water quality prediction model are that the total nitrogen is lower than the Class IV surface water discharge standard (except for total nitrogen, the total nitrogen requirement is less than 15 mg / L). Therefore, the first bypass pipeline 6 is opened, so that the circulating cooling sewage does not need to be treated by the upflow sludge film tank 2, and only the flocculation sedimentation tank chemical addition strategy, the ozone catalytic oxidation tank chemical addition strategy and the biological aerated filter operation strategy are implemented, shortening the system residence time, reducing the system carbon source addition amount, and reducing the SS concentration entering the flocculation sedimentation tank 3;

[0097] Scenario 3: The ammonia nitrogen concentration output by the water quality prediction model is 0.89 mg / L, the total nitrogen concentration is 47.1 mg / L, the total phosphorus concentration is 0.28 mg / L, and the COD concentration is 35.2 mg / L. The optimal combination relationship is as follows: the output COD equivalent of carbon source addition is (47.1 - 15) * 4 = 128.4 g COD / t wastewater, the output PAC addition amount is 150 * 0 = 0 g PAC / t wastewater, the output PAM addition amount is 0 / 35 = 0 g PAM / t wastewater, the output ozone addition amount is (35.2 * 2 - 40) * 2.5 = 76 g ozone / t wastewater, and the output BAF aeration volume = (40 - 10) * 0.2 = 2 L / min air flow / t wastewater; the sewage treatment control strategy is: the sewage treatment modules responsible for processing the output PAC addition and the output PAM addition do not operate, and the rest of the sewage treatment modules operate normally; according to the sewage treatment control strategy, the PLC artificial intelligence control system controls the opening of the second bypass pipeline 7, so that the flocculation sedimentation tank 3 does not operate, and then updates the circulating cooling sewage treatment process pipeline to: the circulating cooling tower inlet bucket 1 - upflow anoxic sludge film tank 2 - second bypass pipeline 7 - ozone catalytic oxidation tank 4 - biological aerated filter 5 - water outlet 9; in Scenario 3, the water quality parameters output by the water quality prediction model show that the total phosphorus is lower than the Class IV surface water discharge standard (except for total nitrogen, the total nitrogen requirement is less than 15 mg / L) (total phosphorus < 0.3 mg / L). Therefore, the second bypass pipeline 7 is opened, so that the circulating cooling sewage does not need to be treated by the flocculation sedimentation tank 3, and only the chemical addition strategy of the upflow anoxic sludge film tank, the chemical addition strategy of the ozone catalytic oxidation tank, and the operation strategy of the biological aerated filter are implemented, shortening the system residence time and reducing the system coagulant and flocculant addition amounts;

[0098] Scenario 4: The ammonia nitrogen concentration output by the water quality prediction model is 1.5 mg / L, the total nitrogen concentration is 27.1 mg / L, the total phosphorus concentration is 0.38 mg / L, and the COD concentration is 25 mg / L. The optimal combination relationship is as follows: The output COD equivalent of the carbon source addition is (27.1 - 15) * 4 = 48.4 g COD / t wastewater, the output PAC addition amount is 150 * 0.38 = 57 g PAC / t wastewater, the output PAM addition amount is 57 / 35 = 1.63 g PAM / t wastewater, the output ozone addition amount is (25 * 2 - 20) * 2.5 = 75 g ozone / t wastewater, the output BAF aeration volume = 0 * 0.2 = 0 L / min air flow / t wastewater. The sewage treatment control strategy is: The sewage treatment module responsible for the output BAF aeration does not operate, and the other sewage treatment modules operate normally; According to the sewage treatment control strategy, the PLC artificial intelligence control system controls the opening of the third bypass pipeline 8, so that the biological aerated filter 5 does not operate, and then updates the circulating cooling sewage treatment process pipeline to: circulating cooling tower water inlet bucket 1 - upflow anoxic sludge film tank 2 - flocculation sedimentation tank 3 - ozone catalytic oxidation tank 4 - third bypass pipeline 8 - water outlet 9; In Scenario 4, the water quality parameters output by the water quality prediction model have a lower COD. After being treated by the ozone catalytic oxidation tank 4 with the lowest ozone addition amount, it can be stably lower than the Class IV surface water discharge standard (except for total nitrogen, the total nitrogen requirement is less than 15 mg / L) (COD < 30 mg / L). Therefore, the third bypass pipeline 8 is opened, so that the circulating cooling sewage does not need to be treated by the biological aerated filter 5, and only the chemical addition strategies of the upflow anoxic sludge film tank, the flocculation sedimentation tank, and the ozone catalytic oxidation tank are implemented, shortening the system residence time and reducing the system energy consumption.

[0099] Through the above solution, by adjusting the chemical addition strategies of the upflow anoxic sludge film tank, the flocculation sedimentation tank, the ozone catalytic oxidation tank, and the operation strategy of the biological aerated filter, the use strategy of the chemicals is reasonably set to treat the circulating cooling sewage, thereby providing a flexible adjustment strategy in the circulating cooling sewage treatment process pipeline, coping with the water quality fluctuation situation and effectively reducing the pollutant concentration in the circulating cooling sewage to meet the sewage discharge standard, and improving the reliability of sewage treatment.

[0100] The above is only the preferred embodiment of the present invention. It should be noted that for those of ordinary skill in the art, without departing from the technical principle of the present invention, several improvements and deformations can be made, and these improvements and deformations should also be regarded as the protection scope of the present invention.

[0101] In the description of this specification, the description with reference to terms such as "one embodiment", "some embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present application. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, without contradiction, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0102] In addition, the terms "first" and "second" are used only for descriptive purposes and cannot be construed as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include at least one such feature. In the description of the present application, "a plurality of" means two or more unless otherwise specifically defined.

Claims

1. A method for treating circulating cooling sewage, which is applied to the sewage treatment process pipeline of circulating cooling sewage. The sewage treatment process pipeline of circulating cooling sewage is composed of several sewage treatment modules, and is characterized in that, The described method for treating circulating cooling blowdown sewage includes: Constructing a water quality prediction model based on historical circulating cooling blowdown sewage data and a preset neural network model; Inputting the real-time circulating cooling blowdown sewage data into the water quality prediction model to obtain dynamic prediction data of water quality parameters; Obtaining a combination of sewage treatment parameters for circulating cooling based on the dynamic prediction data of water quality parameters; Generating a corresponding sewage treatment regulation strategy based on the real-time circulating cooling blowdown sewage data and the combination of sewage treatment parameters for circulating cooling; Based on the corresponding sewage treatment regulation strategy, recombining several of the sewage treatment modules and updating the process pipeline for treating circulating cooling blowdown sewage to treat the circulating cooling blowdown sewage.

2. The method for treating circulating cooling wastewater according to claim 1, wherein, The constructing of a water quality prediction model based on historical circulating cooling blowdown sewage data and a preset neural network model includes: Obtaining historical water quality parameters based on historical circulating cooling blowdown sewage data; Constructing a training set of water quality parameters based on the historical water quality parameters; Serializing the data of the training set of water quality parameters to obtain a serialized training set of water quality parameters; Constructing a water quality prediction model based on the serialized training set of water quality parameters and the preset neural network model.

3. The method for treating circulating cooling sewage as claimed in claim 2, wherein, The constructing of a water quality prediction model based on the serialized training set of water quality parameters and the preset neural network model includes: Inputting the serialized training set of water quality parameters into the preset neural network model for the first neural learning training to obtain preliminary prediction data; Inputting the preliminary prediction data into the preset neural network model for the second neural learning training to obtain deep prediction data; Updating the model parameters of the preset neural network model based on the deep prediction data to obtain a water quality prediction model.

4. The method for treating recycled cooling wastewater according to claim 3, characterized in that, The obtaining of a combination of sewage treatment parameters for circulating cooling based on the dynamic prediction data of water quality parameters includes: Based on historical experimental data and historical sewage treatment strategies for circulating cooling, inputting the dynamic prediction data of water quality parameters into a preset artificial intelligence model to match corresponding sewage treatment parameters for circulating cooling; Constructing a combination of sewage treatment parameters for circulating cooling based on the dynamic prediction data of water quality parameters and the corresponding sewage treatment parameters for circulating cooling.

5. The method for treating circulating cooling sewage according to claim 4, wherein The generating of a corresponding sewage treatment regulation strategy based on the real-time circulating cooling blowdown sewage data and the combination of sewage treatment parameters for circulating cooling to treat the circulating cooling blowdown sewage includes: Obtaining a real-time combination of water quality parameters based on the real-time circulating cooling blowdown sewage data; Matching the combination of sewage treatment parameters for circulating cooling that meets the preset requirements based on the real-time combination of water quality parameters; Generating a corresponding sewage treatment regulation strategy based on the preset artificial intelligence model and the combination of sewage treatment parameters for circulating cooling.

6. The method for treating recycled cooling wastewater according to claim 5, wherein, The recombining of several of the sewage treatment modules and updating the process pipeline for treating circulating cooling blowdown sewage based on the corresponding sewage treatment regulation strategy to treat the circulating cooling blowdown sewage includes: Obtaining a sewage treatment target for circulating cooling based on the corresponding sewage treatment regulation strategy; Selecting several of the sewage treatment modules based on the sewage treatment target for circulating cooling to obtain several target sewage treatment modules; Combine several of the target sewage treatment modules to update the process pipeline for treating circulating cooling blowdown sewage, and obtain a target process pipeline for treating circulating cooling blowdown sewage; Based on the target process pipeline for treating circulating cooling blowdown sewage, treat the circulating cooling blowdown sewage.

7. The sewage treatment method for circulating cooling as claimed in claim 6, wherein, The sewage treatment module includes: an upflow anoxic sludge film tank, a flocculation sedimentation tank, an ozone catalytic oxidation tank, and a biological aerated filter; Based on the target process pipeline for treating circulating cooling blowdown sewage, treating the circulating cooling blowdown sewage includes: If the target process pipeline for treating circulating cooling blowdown sewage includes an upflow anoxic sludge film tank, obtain the chemical dosing strategy for the upflow anoxic sludge film tank according to the corresponding sewage treatment control strategy, and treat the circulating cooling blowdown sewage; If the target process pipeline for treating circulating cooling blowdown sewage includes a flocculation sedimentation tank, obtain the chemical dosing strategy for the flocculation sedimentation tank according to the corresponding sewage treatment control strategy, and treat the circulating cooling blowdown sewage; If the target process pipeline for treating circulating cooling blowdown sewage includes an ozone catalytic oxidation tank, obtain the chemical dosing strategy for the ozone catalytic oxidation tank according to the corresponding sewage treatment control strategy, and treat the circulating cooling blowdown sewage; If the target process pipeline for treating circulating cooling blowdown sewage includes a biological aerated filter, obtain the operation strategy for the biological aerated filter according to the corresponding sewage treatment control strategy, and treat the circulating cooling blowdown sewage.

8. A circulating cooling sewage treatment system, characterized in that, It includes: a water quality prediction model construction module, a water quality parameter dynamic prediction module, a circulating cooling blowdown sewage parameter combination module, a sewage treatment strategy acquisition module, and a circulating cooling blowdown sewage treatment module; The water quality prediction model construction module is used to construct a water quality prediction model based on historical circulating cooling blowdown sewage data and a preset neural network model; The water quality parameter dynamic prediction module is used to input real-time circulating cooling blowdown sewage data into the water quality prediction model to obtain water quality parameter dynamic prediction data; The circulating cooling blowdown sewage parameter combination module is used to obtain a circulating cooling blowdown sewage treatment parameter combination based on the water quality parameter dynamic prediction data; The sewage treatment strategy acquisition module is used to generate a corresponding sewage treatment control strategy based on the real-time circulating cooling blowdown sewage data and the circulating cooling blowdown sewage treatment parameter combination; The circulating cooling blowdown sewage treatment module is used to recombine several of the sewage treatment modules based on the corresponding sewage treatment control strategy, update the process pipeline for treating circulating cooling blowdown sewage, and treat the circulating cooling blowdown sewage.

9. The circulating cooling sewage treatment system according to claim 8, characterized in that, The circulating cooling blowdown sewage treatment module is used to recombine several of the sewage treatment modules based on the corresponding sewage treatment control strategy, update the process pipeline for treating circulating cooling blowdown sewage, and treat the circulating cooling blowdown sewage, including: a treatment target acquisition unit, a treatment module selection unit, a process pipeline update unit, and a target treatment unit; The treatment target acquisition unit is used to obtain a circulating cooling blowdown sewage treatment target based on the corresponding sewage treatment control strategy; The treatment module selection unit is used to select several of the sewage treatment modules based on the circulating cooling blowdown sewage treatment target to obtain several target sewage treatment modules; The process pipeline update unit is used to combine a plurality of the target sewage treatment modules to update the process pipeline of the circulating cooling blowdown sewage treatment, so as to obtain a target process pipeline for circulating cooling blowdown sewage treatment; The target treatment unit is used to treat the circulating cooling blowdown sewage based on the target process pipeline for circulating cooling blowdown sewage treatment.

10. A circulating cooling sewage treatment system according to claim 9, characterized in that, The sewage treatment module includes: an upflow anoxic sludge film tank, a flocculation sedimentation tank, an ozone catalytic oxidation tank, and a biological aerated filter; The target treatment unit is used to treat the circulating cooling blowdown sewage based on the target process pipeline for circulating cooling blowdown sewage treatment, including: A first circulating cooling blowdown sewage treatment subunit, a second circulating cooling blowdown sewage treatment subunit, a third circulating cooling blowdown sewage treatment subunit, and a fourth circulating cooling blowdown sewage treatment subunit; If the target process pipeline for circulating cooling blowdown sewage treatment includes an upflow anoxic sludge film tank, the first circulating cooling blowdown sewage treatment subunit is used to obtain the chemical dosing strategy for the upflow anoxic sludge film tank according to the corresponding sewage treatment control strategy, and treat the circulating cooling blowdown sewage; If the target process pipeline for circulating cooling blowdown sewage treatment includes a flocculation sedimentation tank, the second circulating cooling blowdown sewage treatment subunit is used to obtain the chemical dosing strategy for the flocculation sedimentation tank according to the corresponding sewage treatment control strategy, and treat the circulating cooling blowdown sewage; If the target process pipeline for circulating cooling blowdown sewage treatment includes an ozone catalytic oxidation tank, the third circulating cooling blowdown sewage treatment subunit is used to obtain the chemical dosing strategy for the ozone catalytic oxidation tank according to the corresponding sewage treatment control strategy, and treat the circulating cooling blowdown sewage; If the target process pipeline for circulating cooling blowdown sewage treatment includes a biological aerated filter, the fourth circulating cooling blowdown sewage treatment subunit is used to obtain the operation strategy for the biological aerated filter according to the corresponding sewage treatment control strategy, and treat the circulating cooling blowdown sewage.

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