A method for wastewater treatment based on MABR and carbon capture

Abstract

This application relates to a wastewater treatment method based on MABR and carbon capture. In this method and system, the MABR reactor purifies wastewater using MABR technology. The purified wastewater flows into an algae pond, where carbon dioxide and other waste gases generated during the process are also introduced. Algae in the pond absorb these gases for growth and simultaneously purify the wastewater. The purified wastewater then flows into an aquatic plant pond, where the aquatic plants further purify the wastewater through their self-cleaning function before discharging it. After this treatment process, carbon emissions are reduced, the utilization rate of the treated wastewater is improved, and the discharged wastewater meets emission standards after multiple purification stages, making wastewater treatment in a more environmentally friendly manner for small and medium-sized wastewater treatment plants.

Description

Technical Field

[0001] This application relates to the field of wastewater treatment technology, and in particular to a wastewater treatment method based on MABR and carbon capture. Background Technology

[0002] Currently, ecological, low-carbon, and sustainable wastewater treatment technology is a wastewater treatment method that can reduce energy consumption, lower carbon emissions, and achieve efficient resource utilization.

[0003] In related technologies, large-scale wastewater treatment plants typically use carbon capture and energy recovery technologies to treat wastewater. Carbon capture technology separates and captures carbon dioxide from industrial or energy production sources, then utilizes it geologically, chemically, or biologically, or transports it to suitable sites for long-term storage, isolating the carbon dioxide from the atmosphere. Energy recovery technology, based on the law of conservation of energy, captures and utilizes waste energy, converting it into usable energy.

[0004] Because carbon capture technology is suitable for wastewater treatment plants with high carbon emissions, and energy recovery technology is suitable for large-scale wastewater treatment plants with high energy flow, small and medium-sized wastewater treatment plants with limited resources face problems such as high investment costs, high maintenance costs, and poor efficiency when using these two technologies. Therefore, small and medium-sized wastewater treatment plants currently lack a wastewater treatment method with ecological, low-carbon, and sustainable effects. Summary of the Invention

[0005] To enable small and medium-sized wastewater treatment plants to treat wastewater in a more environmentally friendly manner, this application provides a wastewater treatment method based on MABR and carbon capture.

[0006] This application provides a wastewater treatment method based on MABR and carbon capture, employing the following technical solution:

[0007] A wastewater treatment method based on MABR and carbon capture, wherein the wastewater treatment method is applied to a wastewater treatment system based on MABR and carbon capture.

[0008] The system includes: a MABR reactor, an algae pond, and an aquatic plant pond;

[0009] The MABR reactor is used to purify incoming wastewater using MABR technology;

[0010] The algae pond is connected to the exhaust port and the drain port of the MABR reactor, respectively, and is used to cultivate algae using waste gas and treated wastewater, purify wastewater, and release oxygen.

[0011] The aquatic plant pond is connected to the drainage outlet of the algae pond and is used to cultivate aquatic plants. The aquatic plants absorb harmful substances in the sewage flowing out of the algae pond. The treated sewage flows out through the drainage outlet of the aquatic plant pond (4).

[0012] The system also includes a sedimentation tank;

[0013] The inlet of the sedimentation tank is connected to the outlet of the MABR reaction, and the outlet of the sedimentation tank is connected to the inlet of the algae pond. The sedimentation tank is used to separate sewage and sludge, and the treated sewage flows out through the outlet of the sedimentation tank.

[0014] The sedimentation tank is equipped with a sludge discharge port, which is connected to the sludge inlet of the MABR reactor and also to the outside environment.

[0015] The method includes:

[0016] The wastewater to be purified is fed into the MABR reactor to output the first treated gas and the first treated water.

[0017] The first treated gas and the first treated water are input into the algae pond to output the second discharged gas and the second treated water, wherein the second discharged gas is used for discharge.

[0018] The second treated water is fed into an aquatic plant pond to obtain the third discharged water.

[0019] By adopting the above technical solution, the MABR reactor can purify wastewater using MABR technology. The purified wastewater flows into an algae pond, where carbon dioxide and other waste gases generated during the process are also introduced. This allows the algae in the pond to absorb these gases and grow, while simultaneously purifying the wastewater. The purified wastewater then flows into an aquatic plant pond, where the aquatic plants further purify the wastewater through their self-cleaning function before discharging it. After treatment by this device, carbon emissions are reduced, the utilization rate of the treated wastewater is improved, and the discharged wastewater, after multiple purification stages, meets emission standards, making wastewater treatment in a more environmentally friendly manner for small and medium-sized wastewater treatment plants.

[0020] Optional, also includes:

[0021] The first treated water is input into the sedimentation tank to output a fourth output water and a fourth discharge water. The fourth output water is used to input into the algae pond, and the fourth discharge water is used for discharge.

[0022] Optional, also includes:

[0023] After the first treated water is fed into the sedimentation tank, the sedimentation tank (2) also outputs a fourth return sludge, which is used to feed into the MABR reactor.

[0024] Optionally, the MABR reactor is a closed structure, and the MABR reactor is inoculated with activated sludge at a concentration of 6-10 mg / L, a hydraulic retention time of 8-10 h, a dissolved oxygen content of 0.6-1.2 mg / L, an air supply pressure of 0-60 kPa at the air inlet of the MABR reactor, and a stirrer speed of 100-150 rpm inside the MABR reactor.

[0025] Optionally, the working rate of the sedimentation tank is 0.2~0.3 m / h.

[0026] Optionally, the method further includes a wastewater treatment control method, the control method comprising:

[0027] Obtain real-time operating parameters, which are parameters affecting carbon emissions, sludge emissions, and pollutant content in wastewater in the wastewater treatment system based on MABR and carbon capture.

[0028] When one of the operating parameters does not conform to the corresponding normal parameter range

[0029] The parameter change model is retrieved. The parameter change model includes each operating parameter that changes when each controllable parameter is adjusted by different amounts, and the time it takes for the operating parameter to reach a stable state. The controllable parameter is a parameter that has an impact on the operating parameter and is controllable.

[0030] Based on the parameter change model, multiple adjustment schemes are determined according to operating parameters that do not conform to the normal parameter range;

[0031] Determine the overall cost of each of the aforementioned adjustment schemes;

[0032] The adjustment scheme with the lowest overall cost is selected as the final scheme.

[0033] Adjust the controllable parameters involved according to the final solution described above.

[0034] By adopting the above technical solutions, when the real-time carbon emissions, sludge emissions, or pollutant content in the wastewater of the MABR and carbon capture-based wastewater treatment system are about to exceed the emission standards, multiple adjustment schemes can be obtained based on the parameter change model and real-time operating parameters. Then, the adjustment scheme with the lowest overall cost can be selected to adjust the corresponding operating parameters, thereby enabling the MABR and carbon capture-based wastewater treatment system to reach an operating state that meets the emission standards.

[0035] Optionally, determining multiple adjustment schemes based on the parameter change model and operating parameters that do not conform to the normal parameter range includes:

[0036] Identify all controllable parameters in the parameter change model that affect the operating parameters that do not conform to the normal parameter range, and denote them as target controllable parameters;

[0037] The first variable required to bring the operating parameters that do not conform to the normal parameter range to the normal parameter range is determined according to the parameter change model.

[0038] Based on the parameter change model, the second variable is generated by the affected operating parameters after the first variable is adjusted according to the target controllable parameter;

[0039] The operating parameters that the second variable cannot make keep the corresponding operating parameters within the normal parameter range are denoted as the target operating parameters.

[0040] Based on the parameter change model, the newly added controllable parameters and the corresponding third variables are determined according to the target operating parameters and the corresponding second variables.

[0041] The adjustment scheme is determined based on the target controllable parameter, the first variable, the newly added controllable parameter, and the third variable;

[0042] By iterating through each of the target controllable parameters, multiple adjustment schemes are obtained.

[0043] Optionally, determining the overall cost of each of the adjustment schemes includes:

[0044] Determine the number of controllable parameters that need to be adjusted according to the adjustment plan, and the adjustment amount for each controllable parameter that needs to be adjusted;

[0045] Determine the degree of influence between the controllable parameters that need to be adjusted;

[0046] The time required to adjust the operating parameters that do not conform to the normal parameter range to the normal parameter range is determined based on the parameter change model.

[0047] The overall cost is determined based on the number of controllable parameters that need to be adjusted, the adjustment amount of each controllable parameter, the degree of influence, and the time required to adjust the operating parameters that do not conform to the normal parameter range to the normal parameter range.

[0048] In summary, this application includes at least one of the following beneficial technical effects:

[0049] In this application, the MABR reactor utilizes MABR technology to purify wastewater. The purified wastewater flows into an algae pond, where carbon dioxide and other waste gases generated during the process are also introduced. This allows the algae in the pond to absorb these gases and grow, simultaneously purifying the wastewater. The purified wastewater then flows through the algae pond into an aquatic plant pond, where the aquatic plants further purify the wastewater through their self-cleaning function before discharging it. After treatment by this device, carbon emissions are reduced, the utilization rate of the treated wastewater is improved, and the discharged wastewater, after multiple purification stages, meets emission standards, making wastewater treatment in a more environmentally friendly manner for small and medium-sized wastewater treatment plants. Attached Figure Description

[0050] Figure 1 This is a schematic diagram of a wastewater treatment system based on MABR and carbon capture according to an embodiment of this application.

[0051] Figure 2 This is a schematic flowchart illustrating the control method configured within the control module of a wastewater treatment system based on MABR and carbon capture, according to an embodiment of this application.

[0052] Explanation of reference numerals in the attached diagram: 1. MABR reactor; 2. Sedimentation tank; 3. Algae pond; 31. Water storage tank; 32. Gas chamber; 33. Plant growth lamp; 34. Filter screen; 4. Aquatic plant pond; 5. One-way valve. Detailed Implementation

[0053] To make the purpose, technical solution, and advantages of this application clearer, the following description is provided in conjunction with the appendix. Figure 1-2 The present application will be further described in detail below with reference to embodiments. It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the application.

[0054] This application discloses a wastewater treatment system based on MABR and carbon capture.

[0055] Reference Figure 1 The wastewater treatment system based on MABR and carbon capture includes a MABR reactor 1, a sedimentation tank 2, an algae pond 3, and an aquatic plant pond 4. The MABR reactor 1, sedimentation tank 2, algae pond 3, and aquatic plant pond 4 are connected by pipelines to treat and purify wastewater. The carbon dioxide generated during wastewater treatment can be absorbed by the algae cultivated in the algae pond 3, thus enabling small and medium-sized wastewater treatment plants to meet emission standards for both carbon emissions and wastewater discharge.

[0056] Specifically, MABR reactor 1 is used to purify the incoming wastewater using MABR technology.

[0057] MABR technology is a novel wastewater treatment technology that combines gas membrane technology and biofilm technology with bubble-free oxygen supply, heterogeneous mass transfer, and a stratified structure. MABR technology utilizes microporous membranes or permeable dense membranes for bubble-free oxygen supply. Oxygen and nutrients enter the biofilm from opposite sides. Combined with mass transfer resistance, a concentration gradient of oxygen and nutrients appears within the biofilm, resulting in stratification into aerobic, anoxic, and anaerobic zones. This allows for simultaneous nitrification and denitrification processes on the biofilm, achieving one-stage nitrogen and carbon removal. Taking nitrification and denitrification as an example, due to the significant concentration gradient of oxygen and substrate within the microbial membrane, the outermost layer has a lower dissolved oxygen concentration but abundant organic carbon sources, suitable for denitrification; while the inner layer of the biofilm has a high dissolved oxygen concentration and a low organic carbon concentration, suitable for nitrification. Therefore, MABR is highly suitable for performing simultaneous nitrification and denitrification.

[0058] Specifically, MABR reactor 1 is a relatively closed reaction tank. Wastewater to be treated is introduced into the reaction tank, which is equipped with MABR membrane modules. The MABR membrane modules mainly consist of an aeration membrane and a microbial membrane attached to the aeration membrane. Air / oxygen enters the aeration membrane module under a certain pressure. Oxygen penetrates the aeration membrane to the microbial membrane, and due to the concentration gradient, it also diffuses through the microbial membrane into the wastewater, where it is utilized by aerobic microorganisms such as ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB). Simultaneously, wastewater pollutants permeate into the interior of the biofilm, forming a reverse diffusion mechanism suitable for both aerobic and anaerobic bacteria, promoting nitrogen removal in a symbiotic and controllable environment. The anoxic zone at the biofilm-liquid interface is more suitable for the growth of denitrifying bacteria. Therefore, nitrogen and carbon removal can be achieved by using a single biofilm system to simultaneously carry out nitrification and denitrification reactions.

[0059] Specifically, the MABR reactor 1 is a closed structure with an inlet, an outlet, an air inlet, an exhaust outlet, and a sludge inlet. The inlet is for wastewater to flow in. The outlet is for treated wastewater to flow out. The air inlet is for compressed oxygen or air to flow into the MABR membrane module. The exhaust outlet is for the discharge of waste gases such as carbon dioxide generated during wastewater purification. The sludge inlet is for introducing sludge.

[0060] Here, the MABR membrane module in MABR reactor 1 can be a blind end structure, or the MABR membrane module can be equipped with an outlet. By controlling the outlet, the discharge of waste gas and wastewater generated by the reaction inside the MABR membrane module can be controlled, which is beneficial to improving the oxygen supply concentration of the MABR membrane module.

[0061] The MABR reactor 1 is also equipped with a mixer. Activated sludge is pre-planted inside the MABR reactor 1, and a MABR membrane is also placed there. When wastewater is pumped into the MABR reactor 1, and oxygen (or other oxygen-containing gas such as air) is supplied using an oxygen generator or blower, the oxygen diffuses along the MABR membrane filaments towards the membrane wall. With sufficient oxygen around the membrane wall, the activated sludge accumulates on the membrane wall, forming a biofilm. Oxygen penetrates the membrane wall into the biofilm and, due to the concentration gradient, diffuses across the entire biofilm layer into the wastewater, where it is utilized by aerobic microorganisms such as ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB). Simultaneously, wastewater pollutants permeate into the interior of the biofilm, forming a reverse diffusion mechanism suitable for both aerobic and anaerobic bacteria, promoting nitrogen removal in a symbiotic and controllable environment. The anoxic zone at the biofilm-liquid interface is more suitable for the growth of denitrifying bacteria. Therefore, nitrogen and carbon removal can be achieved by using a single biofilm system to simultaneously perform nitrification and denitrification reactions.

[0062] Understandably, in the aforementioned biochemical reaction process, oxygen supplied by an oxygen generator or blower enters the MABR biofilm under pressure differential. The oxygen pressure is consistently maintained below the bubble point pressure of the MABR biofilm, ensuring oxygen transfer while preventing the generation of bubbles that would lead to the emission of waste gas containing aerosols and volatile organic compounds. Simultaneously, by controlling the operation of the agitator, the sludge-water mixture in MABR reactor 1 can be completely mixed, allowing for more thorough biochemical reactions and achieving wastewater purification. Since MABR technology does not require compressed air for aeration, energy consumption is significantly reduced. Furthermore, because oxygen enters the MABR biofilm through free diffusion, oxygen mass transfer efficiency is improved, further reducing energy consumption.

[0063] To achieve the above effects, in this embodiment, the MABR membrane can be a permeable membrane such as a selectively permeable membrane to prevent pollutants in wastewater from entering the MABR biofilm. Furthermore, the activated sludge concentration is controlled at 6-10 mg / L, the hydraulic retention time is 8-10 h, the air supply pressure is maintained at 0-60 kPa, the dissolved oxygen content is controlled at 0.6-1.2 mg / L, and the mixer speed is maintained at 100-150 rpm.

[0064] The inlet of sedimentation tank 2 is connected to the outlet of MABR reactor 1 through a pipe. Sedimentation tank 2 is used to separate sewage and activated sludge.

[0065] Understandably, although the wastewater discharged from MABR reactor 1 has undergone biochemical reactions, it will contain a certain amount of activated sludge. Long-term discharge of wastewater containing activated sludge into the environment will also have a certain impact on the ecosystem. Therefore, sedimentation tank 2 is needed to separate the wastewater from the activated sludge.

[0066] In some specific embodiments, the sedimentation tank 2 can be a vertical flow sedimentation tank 2, a horizontal flow sedimentation tank 2, or a coaxial pipe sedimentation tank 2. The operating rate of the sedimentation tank 2 needs to be controlled at 0.2~0.3 m / h. The wastewater treated by the sedimentation tank 2 flows out from its drain outlet.

[0067] In some specific embodiments, the sedimentation tank 2 may also be equipped with a sludge discharge port. The pipe connected to the sludge discharge port of the sedimentation tank 2 is not only connected to the outside world, but also to the sludge inlet of the MABR reactor 1. In practical applications, after the wastewater treatment system based on MABR and carbon capture has been operating for a period of time, the amount of activated sludge in the MABR reactor 1 will decrease, while the amount of activated sludge accumulated in the sedimentation tank 2 will increase. In order to minimize the amount of sludge discharged to the outside world, the sludge in the sedimentation tank 2 will first be returned to the MABR reactor 1 until the amount of sludge in the MABR reactor 1 reaches the corresponding threshold, at which point the sludge in the sedimentation tank 2 will be discharged to the outside world. This reduces the amount of sludge discharged to the outside world. For this purpose, one-way valves 5 need to be installed on the pipe connecting the sludge discharge port to the outside world and on the pipe connecting to the sludge inlet of the MABR reactor 1.

[0068] Algae pond 3 is connected to the exhaust port of MABR reactor 1 and the drainage port of sedimentation tank 2, respectively, and is used to cultivate algae using waste gases such as carbon dioxide and treated wastewater, purify wastewater, and release oxygen.

[0069] Specifically, the algae pond 3 comprises two parts: a water storage tank 31 and an air chamber 32. The inlet of the water storage tank 31 is connected to the outlet of the sedimentation tank 2 via a pipe. The water storage tank 31 stores water for algae growth. To provide a suitable environment for algae, plant growth lights 33 are installed within the water storage tank 31. To prevent algae from flowing out of the outlet of the water storage tank 31 along the water flow direction, a filter screen 34 is also installed at the outlet.

[0070] The gas chamber 32 is located above the water storage tank 31. The air inlet of the gas chamber 32 is connected to the exhaust port of the MABR reactor 1 through a pipe, and the exhaust port of the gas chamber 32 is connected to the outside.

[0071] It is understood that algae, as a type of single-celled microorganism with extremely high photosynthetic efficiency, can not only efficiently absorb carbon dioxide and release oxygen through photosynthesis, but also convert carbon dioxide into various bioactive substances such as proteins, lipids, and polysaccharides. In some specific embodiments, Spirulina can be selected as the main algae for cultivation in algae pond 3. Furthermore, algae can also utilize their self-purification function to perform secondary purification of treated wastewater.

[0072] Similarly, in order to facilitate the control of the direction of water flow, a one-way valve 5 needs to be installed on the pipe connecting the drain outlet of sedimentation tank 2 and the inlet of algae pond 3.

[0073] In one specific embodiment, multiple algae ponds 3 may be provided. The air inlet of each algae pond 3 is connected to the exhaust port of the MABR reactor 1.

[0074] The aquatic plant pond 4 is connected to the drainage outlet of the algae pond 3 and is used to cultivate aquatic plants. These plants absorb harmful substances from the wastewater flowing out of the algae pond 3. Similarly, plant growth lights 33 are also installed in the aquatic plant pond 4. Since the aquatic plants cultivated in the aquatic plant pond 4 also have a self-purification function, the wastewater flowing into the aquatic plant pond 4 from the algae pond 3 can be purified by the self-purification action of the aquatic plants, and thus the wastewater discharged from the drainage outlet of the aquatic plant pond 4 can meet the discharge standards.

[0075] Of course, in some specific embodiments, it is also possible to omit the sedimentation tank 2 and instead connect the inlet of the algae pond 3 directly to the outlet of the MABR reactor 1. Compared to the schemes mentioned above, this approach may result in an increase in the amount of sludge discharged.

[0076] To facilitate the control of the MABR-based carbon capture wastewater treatment system, the system is also equipped with a control module containing a control method. This control method, applied to the control module of the MABR-based carbon capture wastewater treatment system disclosed in the above embodiments, can adjust various operating parameters of the MABR-based carbon capture wastewater treatment system in real time, thereby ensuring that the carbon emissions, sludge emissions, and pollutant content in the wastewater are maintained within emission standards over a long period.

[0077] Reference Figure 2 The control method is mainly designed for situations where an operating parameter in a wastewater treatment system based on MABR and carbon capture does not fall within the normal range. The control method configured within the control module specifically includes the following steps:

[0078] Step S100: Obtain real-time operating parameters.

[0079] The operating parameters are those that affect carbon emissions, sludge discharge, and pollutant content in wastewater within a MABR-based carbon capture wastewater treatment system. These operating parameters can be obtained through various sensing devices installed in the MABR-based carbon capture wastewater treatment system.

[0080] Step S200: Retrieve the parameter variation model.

[0081] The parameter variation model includes each operating parameter that changes when each controllable parameter is adjusted by different amounts, and the time it takes for the operating parameter to reach a steady state. Controllable parameters are those that affect the operating parameters and are controllable.

[0082] Understandably, when adjusting controllable parameters, the magnitude of the change may affect different numbers of operating parameters, and may also affect the magnitude of the change in each operating parameter. Therefore, multiple experiments are needed to obtain the corresponding data in order to establish an accurate parameter change model. When adjusting a controllable parameter, the stability of the operating parameter can be determined based on its fluctuation range over a period of time. That is, a threshold of the allowable fluctuation range corresponding to the stable state is pre-set. When the fluctuation range of the same operating parameter is within the allowable fluctuation range threshold over a period of time, the operating parameter can be considered to have reached a stable state.

[0083] After establishing the parameter variation model, it can be pre-stored in a storage device such as a memory. When it is necessary to adjust the operating parameters of the wastewater treatment system based on MABR and carbon capture, the parameter variation model can be retrieved.

[0084] Step S300: Based on the parameter change model, determine multiple adjustment schemes according to the operating parameters that do not conform to the normal parameter range.

[0085] Optionally, step S300 includes the following steps: (steps S310 to S370)

[0086] Step S310: Determine all controllable parameters in the parameter change model that affect the operating parameters that do not conform to the normal parameter range, and denot them as target controllable parameters.

[0087] It is understandable that when adjusting a controllable parameter, the number of affected operating parameters increases with the magnitude of the change in that controllable parameter. Therefore, to adjust an operating parameter, one can do so by adjusting different controllable parameters. Since the parameter change model records the operating parameters affected when adjusting each controllable parameter, it is possible to determine all controllable parameters that affect operating parameters that do not conform to the normal parameter range, and record these controllable parameters as target controllable parameters.

[0088] Since different target controllable parameters can be selected as the main controllable parameters for adjustment, so as to adjust the operating parameters that do not conform to the normal parameter range, multiple adjustment schemes can be obtained.

[0089] The following section explains the method for determining the adjustment scheme by selecting a target controllable parameter as the main controllable parameter to be adjusted.

[0090] Step S320: Determine the first variable required to bring the operating parameters that do not conform to the normal parameter range to the normal parameter range based on the parameter change model.

[0091] It is important to note that when determining the amount of change required for an operating parameter that does not fall within the normal parameter range to reach the normal parameter range, the median value of the normal parameter range corresponding to that operating parameter can be used as the standard value. This will ensure that the various emissions of the adjusted wastewater treatment system based on MABR and carbon capture can continuously meet the emission standards.

[0092] Furthermore, once the amount of change required for an operating parameter that does not conform to the normal parameter range to reach the corresponding standard value is determined, the first variable of each target controllable parameter can be determined based on the parameter change model.

[0093] Step S330: Determine the second variable generated by the affected operating parameters after adjusting the first variable according to the parameter change model.

[0094] It is understandable that although adjusting the target controllable parameter to the first variable can bring the operating parameters that do not conform to the normal parameter range to the normal parameter range, it will also affect other operating parameters, and may even cause some operating parameters that are in the normal parameter range to exceed the normal parameter range. Therefore, it is necessary to calculate the second variable generated by all affected operating parameters after adjusting the target controllable parameter to the first variable according to the parameter change model.

[0095] Step S340: Determine the operating parameters that the second variable cannot make the corresponding operating parameters remain within the normal parameter range, and denot them as the target operating parameters.

[0096] Specifically, the current value of the running parameter is superimposed on the corresponding second variable. The result is then compared with the normal parameter range for that running parameter. Running parameters whose superimposed result exceeds the normal parameter range are identified and denoted as target running parameters. Further adjustments are needed to ensure the target running parameters remain within the normal parameter range.

[0097] It is worth noting that, considering the need to continuously maintain the carbon emissions, sludge emissions, and pollutant content in wastewater treated by the MABR-based carbon capture wastewater treatment system within emission standards, it is necessary to set thresholds for the parameter ranges. When the combined result exceeds the corresponding parameter range threshold, the relevant operating parameters are recorded as the target operating parameters.

[0098] Step S350: Based on the parameter change model, determine the newly added controllable parameters and the corresponding third variables according to the target operating parameters and the corresponding second variables.

[0099] Among them, the newly added controllable parameters are controllable parameters that can adjust the target operating parameters without affecting the operating parameters that are affected by the aforementioned target controllable parameters.

[0100] Once the first variable is determined, operating parameters that do not conform to the normal parameter range can be brought within the normal parameter range, while the target operating parameter will exceed the corresponding normal parameter range. Similarly, the median value of the normal parameter range can be used as the standard value, and the amount of adjustment required for the target operating parameter can be determined based on the current value of the target operating parameter and the second variable.

[0101] Furthermore, the first step is to determine the new controllable parameters based on the parameter change model. This involves identifying controllable parameters from the model that can adjust the target operating parameters without affecting the operating parameters already influenced by the target controllable parameters. If no controllable parameter meets these conditions, then the controllable parameter that has the least impact on the operating parameters already influenced by the target controllable parameters can be selected.

[0102] Then, based on the amount of change required to adjust the target operating parameters, the amount of change of the newly added controllable parameters is determined, which is the amount of change of the newly added controllable parameters required for the target operating parameters to reach the normal parameter range, i.e., the third variable.

[0103] Step S360: Determine the adjustment scheme based on the target controllable parameter, the first variable, the newly added controllable parameter, and the third variable.

[0104] Once the target controllable parameter, the first variable of the target controllable parameter, the newly added controllable parameter, and the third variable of the newly added controllable parameter are determined, an adjustment scheme can be formed from the determined target controllable parameter, the first variable of the target controllable parameter, the newly added controllable parameter, and the third variable of the newly added controllable parameter.

[0105] Understandably, if multiple different newly added controllable parameters can be identified in the parameter change model, different adjustment schemes can be obtained based on these different parameters. In other words, when a certain target controllable parameter is used as the main controllable parameter for adjustment, one or more adjustment schemes can be obtained.

[0106] In some specific embodiments, if after determining the target controllable parameter, the first variable of the target controllable parameter, the newly added controllable parameter, and the third variable of the newly added controllable parameter, there are still operating parameters that exceed the normal parameter range, then the controllable parameters that need to be adjusted and the amount of change that needs to be adjusted can be determined by following the above method.

[0107] Step S370: Traverse each of the target controllable parameters to obtain multiple adjustment schemes.

[0108] By iterating through each controllable parameter of the target using the method described above, one or more adjustment schemes can be obtained. After completing the iteration, multiple adjustment schemes can be obtained.

[0109] Step S400: Determine the overall cost of each of the aforementioned adjustment schemes.

[0110] Understandably, each adjustment scheme is different, and the overall cost will also vary. When selecting an adjustment scheme as the final solution, it should be chosen to achieve high efficiency and low carbon emissions as much as possible.

[0111] The overall cost mainly considers the number of controllable parameters to be adjusted, the corresponding adjustment amount, the degree of correlation between controllable parameters, and the time required to adjust operating parameters that do not conform to the normal parameter range to the normal parameter range.

[0112] Specifically, first determine the number of controllable parameters that need to be adjusted for each adjustment scheme, and the adjustment amount for each controllable parameter that needs to be adjusted.

[0113] Next, determine the degree of influence between the controllable parameters that need to be adjusted. The greater the degree of influence between the controllable parameters, the more difficult and complicated it is to adjust the operating parameters that do not conform to the normal parameter range to the normal parameter range.

[0114] In a specific embodiment, the influence between controllable parameters can be measured by the degree of overlap between the operating parameters influenced by one controllable parameter and those influenced by another. That is, the higher the overlap, the greater the influence. Of course, two related operating parameters can be considered overlapping operating parameters. In a specific example, if controllable parameter A1 influences operating parameters B1 and B2, and controllable parameter A2 influences operating parameters C1, C2, and C3, and operating parameters B2 and C1 have a direct or inverse relationship, then operating parameters B2 and C1 can be considered overlapping operating parameters. Specifically, the influence can be calculated as follows: Influence = Number of overlapping operating parameters / Sum of the number of operating parameters. Here, the sum of the number of operating parameters represents the number of different operating parameters. Taking the above example, the influence = 1 / 4.

[0115] Of course, for an adjustment plan involving multiple controllable parameters, the influence between any two controllable parameters can be determined first, and then the maximum influence value can be selected as the final influence value.

[0116] When determining the time required to adjust operating parameters that do not conform to the normal parameter range to the normal parameter range, since the adjustment plan involves the adjustment of multiple controllable parameters, the time required to adjust each controllable parameter must be considered. That is, the time required to adjust operating parameters that do not conform to the normal parameter range to the normal parameter range should be the maximum value of the time required to adjust different controllable parameters.

[0117] Furthermore, the overall cost is determined by the number of controllable parameters that need to be adjusted, the adjustment amount of each controllable parameter, the degree of influence, and the time required to adjust operating parameters that do not conform to the normal parameter range to the normal parameter range.

[0118] In a specific embodiment, the number of controllable parameters that need to be adjusted in each adjustment scheme, as well as the adjustment amount, impact, and time required to adjust the operating parameters that do not conform to the normal parameter range to the normal parameter range, can be quantified to obtain the corresponding scores. Then, the average value of each adjustment scheme can be calculated to obtain the comprehensive cost.

[0119] To determine the number of controllable parameters that need adjustment, first identify the minimum number of controllable parameters to be adjusted among all adjustment schemes, and then quantify the number of controllable parameters to be adjusted for that scheme as 100%. The number of controllable parameters to be adjusted for the remaining adjustment schemes can be quantified using the following formula: Score = 100% - Difference in the number of controllable parameters * Coefficient. The coefficient can be set according to the actual situation.

[0120] To determine the adjustment amount for controllable parameters that need adjustment, we can first calculate the total adjustment amount required for each adjustment scheme, which is the sum of the adjustment amounts for each controllable parameter. Then, we can quantify the adjustment amount of the controllable parameters required for each adjustment scheme according to the quantification method for the number of controllable parameters.

[0121] Similarly, the time required to adjust operating parameters that do not conform to the normal parameter range to the normal parameter range can also be quantified in the above way.

[0122] Step S500: Select the adjustment scheme with the lowest overall cost as the final scheme.

[0123] Step S600: Adjust the controllable parameters involved according to the final scheme.

[0124] In a more preferred embodiment, to further enhance the adaptability and control accuracy of the control method, this application introduces enhanced control logic based on probabilistic online learning and rolling time-domain optimization, building upon the aforementioned steps S100 to S600. This enhanced logic can serve as a parallel module or advanced alternative to the original control method, and is automatically activated when the system detects frequent fluctuations in operating parameters or model prediction errors exceeding a set threshold.

[0125] Specifically, at the beginning of each control cycle (e.g., every 15 minutes), the system first obtains the current operating parameter vector. .in, This refers to the total number of operating parameters, including but not limited to: activated sludge concentration, dissolved oxygen content, hydraulic retention time, air supply pressure, agitator speed, sedimentation tank operating rate, algae concentration in the algae pond, and the final output of the system: carbon emissions, sludge emissions, and concentrations of various pollutants. These data are collected at a fixed sampling frequency (e.g., 1 minute) by sensors deployed in each treatment unit and preprocessed using Kalman filtering or moving average filtering to form a historical dataset. ,in This is the historical window length (e.g., 24 hours). Simultaneously, the system maintains a set of controllable parameter vectors. , The number of controllable parameters includes aeration pressure, mixer speed, sludge return flow rate, and plant growth lamp intensity. The allowable adjustment range of each parameter is predetermined by process design and equipment limitations.

[0126] To achieve accurate prediction of system dynamics without needing to pre-establish a static parameter variation model, the system employs a sparse Gaussian process (SGP) for online probabilistic modeling of the wastewater treatment process. The wastewater treatment system is treated as an unknown nonlinear stochastic dynamic system:

[0127]

[0128] in For an unknown system transfer function, It is independent and identically distributed Gaussian noise. This is a diagonal covariance matrix. For each output dimension... Use a separate Gaussian process for the function Modeling is performed. Define the augmented input vector. Then the prior of the Gaussian process is:

[0129]

[0130] Kernel function The quadratic exponent kernel is used for Automatic Relevance Determination (ARD):

[0131]

[0132] For the first The variance of the output signal. For the first The output pair of the first The length scale of each input dimension. To maintain the efficiency of online computation, the system uses... Inducing points (usually taken as 1) A sparse approximation is performed, and the model hyperparameters are updated online through incremental variational inference. Each new observation data... Upon arrival, the system calculates the computational complexity. This allows for updating the posterior distribution of the Gaussian process, enabling real-time output of any candidate control action. Next future operating parameters The predicted mean and the predicted covariance matrix ,in It is a diagonal matrix, with diagonal elements representing the prediction variance of each output dimension. .

[0133] Based on the above probabilistic prediction model, the system constructs a rolling time-domain optimization problem to determine the optimal control action for the current period. Define the prediction time domain as One control cycle (e.g.) (corresponding to 2 hours). For any candidate control action sequence The system uses a Gaussian process model to autoregressively predict the future state distribution: from the current true state Departure, for Given ,predict The distribution is To account for the impact of prediction uncertainty on control costs, the system uses expected cost as the optimization objective:

[0134]

[0135] in This is a discount factor used to balance near-term and long-term costs; To control the sparsity penalty coefficient; The L1 norm is used to encourage adjusting only a small number of controllable parameters. Cost function. Defined as the weighted sum of squares of deviations of the operating parameters from their expected operating range:

[0136]

[0137] in For the first The normal range of each operating parameter The weighting coefficients for each parameter (which can be pre-set according to environmental emission standards or process importance) are used. This cost function only produces positive values ​​when the operating parameters exceed the normal range, and the penalty increases with the deviation. Since Gaussian process prediction provides an analytical form of the distribution, the expected cost can be approximated: for each prediction time, Monte Carlo sampling (e.g., sampling) is used. The average cost can be calculated using the trajectory, or analytical integration can be performed using the cumulative distribution function of the Gaussian distribution.

[0138] To efficiently solve the aforementioned nonlinear stochastic optimization problem, the system employs a hybrid solver based on Bayesian optimization and cross-entropy methods. First, parameters are randomly generated within the controllable parameter space. There are 1 initial candidate action sequences (each sequence has a length of 1). For each candidate sequence, rolling prediction is performed using a Gaussian process model, and the approximate expected cost is calculated. Then select the one with the lowest cost. Elite sequences (e.g.) Using these elite sequences as centers, new candidate sequences are generated using a multivariate Gaussian distribution, where the covariance matrix of the Gaussian distribution adaptively decreases with the number of iterations. This process is repeated. For example Finally, an approximately optimal action sequence is obtained. and only the first action is performed. In the next control cycle, the system will be in a new real state. Re-planning to achieve rolling time-domain control.

[0139] In practical wastewater treatment systems, certain operating parameters (such as pollutant discharge concentrations) are subject to strict safety constraints and must not exceed legal discharge standards. To ensure absolute safety in control actions, the system solves for... Subsequently, a safety correction based on the Control Barrier Function (CBF) is introduced. The safety set is defined as the set of states where all operating parameters are strictly within the safety boundary, which is typically taken as 95% of the normal range or the legal emission standard. For the first... Each runtime parameter defines its security function:

[0140]

[0141] in For the first The safety threshold for each running parameter (e.g., 95% of the upper limit of the normal range). Then the global safety function is... The system is in a safe state if and only if The control barrier function requires control actions. satisfy:

[0142]

[0143] in For the decay rate, this condition guarantees that the safety function will not decay faster than... The rate of decay. Due to the real Unknown, using the predicted mean of a Gaussian process approximate . Notice Can be in the current state Numerical calculations are performed at this point, while yes The linear function (because the mean of a Gaussian process is a linear combination of the kernel function and the training target) thus the above constraints become about The linear inequality. When calculated... When this safety constraint is not satisfied, the system solves the following quadratic programming problem to obtain the safety correction action. :

[0144]

[0145] in , , To and The irrelevant mean portion. This quadratic programming problem has a closed-form solution or can be quickly computed using a standard solver. The final action performed is... .

[0146] After each control cycle executes an action, the system collects the actual observations. It is then compared with the prediction mean of the Gaussian process model to calculate the prediction error vector. This error serves two purposes: first, to adjust the new data points... First, it adds the data to the training set and triggers an incremental variational update of the Gaussian process model, updating the induced points and hyperparameters; second, it is used to dynamically adjust the weight coefficients in the cost function. and Specifically, the system maintains a length of A sliding window of error (e.g., 100) is used to calculate the root mean square of the error within the window. If three consecutive cycles If the error exceeds 1.5 times the historical average, it is considered that a significant change has occurred in the system dynamics (such as sudden changes in water quality or equipment aging). In this case, [the following will be considered]. Temporarily increase by 20% to curb aggressive adjustments, and The error was reduced to 0.8 to minimize the impact of the prediction time domain, allowing the system to respond to changes more quickly; once the error returned to the normal range, and The value is restored to its original value through exponential decay. Furthermore, every 24 hours, the system re-optimizes the length scale of the kernel function by maximizing the marginal likelihood of the Gaussian process, using all accumulated data from that day. and signal variance Simultaneously, Bayesian optimization is used to adjust hyperparameters. The baseline value enables the model and control strategy to adapt to long-term seasonal fluctuations and equipment performance drift.

[0147] The above-mentioned optimization scheme is fully embedded into the original control method implementation. In actual operation, the system first executes steps S100 to S600 of the original method, that is, generates an adjustment scheme based on the pre-established parameter change model and executes the optimal one. When the system detects that the model prediction error exceeds a preset threshold multiple times (e.g., accumulating more than 5 times) or the operator manually enables the advanced control mode, it switches to the enhanced control logic described in this optimization scheme. This optimization scheme does not rely on the pre-stored parameter change model, but instead captures the system dynamics in real time through online learning and outputs control actions in the form of rolling time-domain optimization and safety barrier correction, thereby further improving the adaptive capability, robustness, and safety of the control system on the basis of the original method.

[0148] Secondly, this application provides a wastewater treatment method based on MABR and carbon capture, comprising:

[0149] The wastewater to be purified is fed into the MABR reactor (1) to output the first treated gas and the first treated water.

[0150] The first treatment gas and the first treatment water are input into the algae pond (3) to output the second discharge gas and the second treatment water, wherein the second discharge gas is used for discharge;

[0151] The second treated water is fed into the aquatic plant pond (4) to obtain the third discharged water.

[0152] By adopting the above technical solution, the MABR reactor can purify wastewater using MABR technology. The purified wastewater flows into an algae pond, where carbon dioxide and other waste gases generated during the process are also introduced. This allows the algae in the pond to absorb these gases and grow, while simultaneously purifying the wastewater. The purified wastewater then flows into an aquatic plant pond, where the aquatic plants further purify the wastewater through their self-cleaning function before discharging it. After treatment by this device, carbon emissions are reduced, the utilization rate of the treated wastewater is improved, and the discharged wastewater, after multiple purification stages, meets emission standards, making wastewater treatment in a more environmentally friendly manner for small and medium-sized wastewater treatment plants.

[0153] Optional, also includes:

[0154] The first treated water body is input into the sedimentation tank (2) to output a fourth output water body and a fourth discharge water body. The fourth output water body is used to input into the algae pond (3), and the fourth discharge water body is used for discharge.

[0155] Optional, also includes:

[0156] After the first treated water is fed into the sedimentation tank (2), the sedimentation tank (2) also outputs a fourth return sludge, which is used to feed into the MABR reactor (1).

[0157] Optionally, the MABR reactor (1) is a closed structure, and activated sludge is inoculated inside the MABR reactor (1). The concentration of the activated sludge is 6~10mg / L, the hydraulic retention time is 8~10h, the dissolved oxygen content in the tank is 0.6~1.2mg / L, the air supply pressure at the air inlet of the MABR reactor (1) is 0~60KPa, and the speed of the agitator inside the MABR reactor (1) is 100~150rpm.

[0158] Optionally, the working rate of the sedimentation tank (2) is 0.2~0.3 m / h.

[0159] The method may also include a wastewater treatment control method, which may refer to the control method executed within the system's control module, and will not be elaborated here.

[0160] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working process of the described method can be referred to the corresponding process in the foregoing system embodiments, and will not be repeated here.

[0161] The above are all preferred embodiments of this application and are not intended to limit the scope of protection of this application. Any feature disclosed in this specification (including the abstract and drawings) may be replaced by other equivalent or similar features unless specifically stated otherwise. That is, unless specifically stated otherwise, each feature is only one example of a series of equivalent or similar features.

Claims

1. A wastewater treatment method based on MABR and carbon capture, characterized in that, The wastewater treatment method is applied to a wastewater treatment system based on MABR and carbon capture. The system includes: a MABR reactor (1), an algae pond (3), and an aquatic plant pond (4); The MABR reactor (1) is used to purify the incoming wastewater using MABR technology; The algae pond (3) is connected to the exhaust port and the drain port of the MABR reactor (1) respectively, and is used to cultivate algae using waste gas and treated sewage, purify sewage and release oxygen; The aquatic plant pond (4) is connected to the drain outlet of the algae pond (3) and is used to cultivate aquatic plants. The aquatic plants absorb harmful substances in the sewage flowing out of the algae pond (3). The treated sewage flows out through the drain outlet of the aquatic plant pond (4). The system also includes a sedimentation tank (2); The inlet of the sedimentation tank (2) is connected to the outlet of the MABR reactor (1), and the outlet of the sedimentation tank (2) is connected to the inlet of the algae pond (3). The sedimentation tank (2) is used to separate sewage and sludge, and the treated sewage flows out through the outlet of the sedimentation tank (2). The sedimentation tank (2) is equipped with a sludge discharge port, which is connected to the sludge inlet of the MABR reactor (1) and also connected to the outside. The method includes: The wastewater to be purified is fed into the MABR reactor (1) to output the first treated gas and the first treated water. The first treatment gas and the first treatment water are input into the algae pond (3) to output the second discharge gas and the second treatment water, wherein the second discharge gas is used for discharge; The second treated water is fed into the aquatic plant pond (4) to obtain the third discharged water.

2. The wastewater treatment method based on MABR and carbon capture according to claim 1, characterized in that, Also includes: The first treated water body is input into the sedimentation tank (2) to output a fourth output water body and a fourth discharge water body. The fourth output water body is used to input into the algae pond (3), and the fourth discharge water body is used for discharge.

3. The wastewater treatment method based on MABR and carbon capture according to claim 2, characterized in that, Also includes: After the first treated water is fed into the sedimentation tank (2), the sedimentation tank (2) also outputs a fourth return sludge, which is used to feed into the MABR reactor (1).

4. A wastewater treatment method based on MABR and carbon capture according to claim 3, characterized in that, The MABR reactor (1) is a closed structure. The MABR reactor (1) is inoculated with activated sludge. The concentration of the activated sludge is 6~10 mg / L, the hydraulic retention time is 8~10 h, the dissolved oxygen content in the tank is 0.6~1.2 mg / L, the air supply pressure at the air inlet of the MABR reactor (1) is 0~60 kPa, and the speed of the agitator in the MABR reactor (1) is 100~150 rpm.

5. A wastewater treatment method based on MABR and carbon capture according to claim 4, characterized in that, The working rate of the sedimentation tank (2) is 0.2~0.3 m / h.

6. A wastewater treatment method based on MABR and carbon capture according to any one of claims 1-5, characterized in that, The method further includes a wastewater treatment control method, the control method comprising: Obtain real-time operating parameters, which are parameters affecting carbon emissions, sludge emissions, and pollutant content in wastewater in the wastewater treatment system based on MABR and carbon capture. When one of the operating parameters does not conform to the corresponding normal parameter range The parameter change model is retrieved. The parameter change model includes each operating parameter that changes when each controllable parameter is adjusted by different amounts, and the time it takes for the operating parameter to reach a stable state. The controllable parameter is a parameter that has an impact on the operating parameter and is controllable. Based on the parameter change model, multiple adjustment schemes are determined according to operating parameters that do not conform to the normal parameter range; Determine the overall cost of each of the aforementioned adjustment schemes; The adjustment scheme with the lowest overall cost is selected as the final scheme. Adjust the controllable parameters involved according to the final solution described above.

7. A wastewater treatment method based on MABR and carbon capture according to claim 6, characterized in that: The determination of multiple adjustment schemes based on the parameter change model and operating parameters that do not fall within the normal parameter range includes: Identify all controllable parameters in the parameter change model that affect the operating parameters that do not conform to the normal parameter range, and denote them as target controllable parameters; The first variable required to bring the operating parameters that do not conform to the normal parameter range to the normal parameter range is determined according to the parameter change model. Based on the parameter change model, the second variable is generated by the affected operating parameters after the first variable is adjusted according to the target controllable parameter; The operating parameters that the second variable cannot make keep the corresponding operating parameters within the normal parameter range are denoted as the target operating parameters. Based on the parameter change model, the newly added controllable parameters and the corresponding third variables are determined according to the target operating parameters and the corresponding second variables. The adjustment scheme is determined based on the target controllable parameter, the first variable, the newly added controllable parameter, and the third variable; By iterating through each of the target controllable parameters, multiple adjustment schemes are obtained.

8. A wastewater treatment method based on MABR and carbon capture according to claim 7, characterized in that: The determination of the overall cost of each of the adjustment schemes includes: Determine the number of controllable parameters that need to be adjusted according to the adjustment plan, and the adjustment amount for each controllable parameter that needs to be adjusted; Determine the degree of influence between the controllable parameters that need to be adjusted; The time required to adjust the operating parameters that do not conform to the normal parameter range to the normal parameter range is determined based on the parameter change model. The overall cost is determined based on the number of controllable parameters that need to be adjusted, the adjustment amount of each controllable parameter, the degree of influence, and the time required to adjust the operating parameters that do not conform to the normal parameter range to the normal parameter range.

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