Microbial reinforcement-based aquaculture tail water denitrification and phosphorus removal method

Abstract

The application discloses a breeding tail water denitrification and dephosphorization method based on microbial reinforcement, and belongs to the technical field of breeding tail water treatment. The method comprises the following steps: obtaining water quality characteristic parameters, carbon source reserve parameters and initial abundance parameters of functional bacterial flora of breeding tail water; constructing a metabolic interaction matrix among the functional bacterial flora according to the above parameters; based on the metabolic interaction matrix, using a multiple tabu optimization algorithm to solve the dosing ratio of each functional bacterial flora, the carbon source dosing amount, and the target values of the dissolved oxygen concentration, the pH value and the temperature within a specified time window, to obtain a microbial reinforcement strategy; and adding the microbial reinforcement agent according to the strategy and synchronously adjusting the dissolved oxygen concentration, the pH value and the temperature to perform denitrification and dephosphorization treatment on the breeding tail water. The method can dynamically optimize the dosing strategy and the process parameters, improve the denitrification and dephosphorization efficiency, and reduce the carbon source consumption by constructing the metabolic interaction matrix and the multiple tabu optimization.

Description

Technical Field

[0001] This invention relates to the field of aquaculture wastewater treatment technology, specifically a method for nitrogen and phosphorus removal from aquaculture wastewater based on microbial enhancement. Background Technology

[0002] Aquaculture wastewater contains high concentrations of nitrogen and phosphorus pollutants, and direct discharge can easily lead to eutrophication. Biological nitrogen and phosphorus removal using functional microbial communities such as anaerobic ammonia-oxidizing bacteria, denitrifying phosphorus-accumulating bacteria, aerobic denitrifying bacteria, and nitrifying bacteria is a common method for treating aquaculture wastewater. In existing microbial enhanced treatment methods, fixed proportions of compound microbial agents are typically added to the wastewater based on experience, and dissolved oxygen, pH, and temperature are controlled according to preset process parameters. Some schemes use single kinetic models to estimate the dosage of microbial agents, but most models only consider the metabolic characteristics of single bacterial species, neglecting the competition for substrates among different functional microbial communities and the cross-promoting or inhibiting effects of metabolites.

[0003] Due to the complex substrate competition and metabolic interactions among different bacterial communities, fixed-ratio dosing can easily lead to the suppression of activity in some communities due to insufficient substrate or product accumulation, while others proliferate excessively without effectively contributing to total nitrogen and phosphorus removal. This results in unstable overall nitrogen and phosphorus removal efficiency, inefficient carbon source utilization, and increased reagent costs. When influent water quality fluctuates, empirical adjustments show significant lag, making it difficult to match process parameters with the actual metabolic needs of the bacterial communities in real time, increasing the risk of effluent water quality not meeting standards. Furthermore, it is necessary to simultaneously coordinate multiple conflicting objectives such as nitrogen removal efficiency, phosphorus removal efficiency, and carbon source consumption. Existing methods lack efficient means to optimize the dosage and operating parameters of multiple functional bacterial communities under dynamic conditions, failing to guarantee a microbial enhancement strategy that takes into account multiple objectives globally. To address these issues, there is an urgent need for a nitrogen and phosphorus removal method that dynamically optimizes the dosage ratio of multiple bacterial communities and process parameters based on a quantitative description of the metabolic interactions among bacterial communities. Summary of the Invention

[0004] This invention provides a method for nitrogen and phosphorus removal from aquaculture wastewater based on microbial enhancement. The aim is to overcome the problems of unstable nitrogen and phosphorus removal efficiency and high carbon source consumption caused by existing methods that do not consider the metabolic interactions of functional microbial communities and lack global multi-objective optimization. By constructing a metabolic interaction matrix and using a multiple taboo optimization algorithm to obtain a dynamic microbial enhancement strategy, a highly efficient and low-consumption nitrogen and phosphorus removal treatment of aquaculture wastewater can be achieved.

[0005] To achieve the above objectives, this invention provides the following technical solution: This invention provides a method for nitrogen and phosphorus removal from aquaculture wastewater based on microbial enhancement, comprising the following steps: obtaining water quality characteristic parameters, carbon source reserve parameters, and initial abundance parameters of functional microbial communities in the aquaculture wastewater; constructing a metabolic interaction matrix among functional microbial communities based on the water quality characteristic parameters, carbon source reserve parameters, and initial abundance parameters; using a multiple taboo search algorithm to solve for the target values ​​of the addition ratio, carbon source addition amount, dissolved oxygen concentration, pH value, and temperature of each functional microbial community within a specified time window, based on the metabolic interaction matrix, to obtain a microbial enhancement strategy; adding a microbial enhancer to the aquaculture wastewater according to the addition ratio in the microbial enhancement strategy, and synchronously adjusting the dissolved oxygen concentration, pH value, and temperature according to the target values ​​to perform nitrogen and phosphorus removal treatment on the aquaculture wastewater. The above technical solution integrates water quality characteristics, carbon source reserves, and the initial abundance of functional microbial communities into a fusion model, and dynamically generates addition and process control strategies using a multiple taboo search algorithm, achieving a comprehensive effect of deep nitrogen and phosphorus removal, reduced carbon source consumption, and maintenance of microbial community metabolic balance.

[0006] As a preferred technical solution of the present invention, the acquisition of water quality characteristic parameters, carbon source reserve parameters, and initial abundance parameters of functional microbial communities in aquaculture wastewater specifically includes: collecting water samples from the inlet, anaerobic zone, anoxic zone, aerobic zone, and outlet of the aquaculture wastewater treatment system; detecting the concentrations of ammonia nitrogen, nitrite nitrogen, nitrate nitrogen, total phosphorus, and chemical oxygen demand in the water samples at each sampling point, and weighting the detected values ​​at each sampling point according to the hydraulic retention time to obtain the water quality characteristic parameters; reading the carbon source liquid level and effective carbon source component concentration in the carbon source storage tank, and multiplying the two as the carbon source reserve parameters; extracting total microbial DNA from the water samples at each sampling point and performing 16S rRNA gene high-throughput sequencing, and determining the initial abundance parameters of anaerobic ammonia oxidizing bacteria, denitrifying polyphosphate-accumulating bacteria, aerobic denitrifying bacteria, and nitrifying bacteria based on the sequence abundance in the sequencing results. By combining multi-point weighted sampling with molecular biological detection, the water quality status and key bacterial distribution of each functional area of ​​the system can be reflected in real time and accurately, providing a precise initial basis for subsequent model construction.

[0007] Furthermore, the construction of the metabolic interaction matrix among functional microbial communities includes: obtaining the half-saturation constants, maximum specific degradation rate constants, and product inhibition constants of anaerobic ammonia oxidizing bacteria, denitrifying polyphosphate-accumulating bacteria, aerobic denitrifying bacteria, and nitrifying bacteria for ammonia nitrogen, nitrite nitrogen, nitrate nitrogen, total phosphorus, and organic carbon sources from a pre-defined microbial metabolic database; calculating the competition coefficients for the same substrate between each pair of anaerobic ammonia oxidizing bacteria, denitrifying polyphosphate-accumulating bacteria, aerobic denitrifying bacteria, and nitrifying bacteria based on the water quality characteristic parameters and the initial abundance parameters, and calculating the promotion or inhibition coefficients of the metabolic products of one functional microbial community on the growth of another functional microbial community; filling the competition coefficients, promotion coefficients, and inhibition coefficients into matrix elements according to the order of the functional microbial communities to obtain the metabolic interaction matrix. This matrix precisely quantifies the competition, promotion, and inhibition relationships among microbial communities, enabling the formulation of subsequent dosing strategies to specifically optimize the microbial community structure and avoid antagonistic effects between functional microbial communities.

[0008] Furthermore, based on the metabolic interaction matrix, a multi-taboo optimization algorithm is used to solve for the target values ​​of the addition ratio, carbon source addition amount, dissolved oxygen concentration, pH value, and temperature of each functional microbial community within a specified time window, thereby obtaining a microbial enhancement strategy. This strategy includes: using the addition ratio, carbon source addition amount, dissolved oxygen concentration, pH value, and temperature of each functional microbial community as decision variables, and denitrification efficiency, phosphorus removal efficiency, carbon source consumption, and the balance of microbial community metabolic interactions as optimization objectives, to construct a multi-objective optimization model; according to the metabolic interaction matrix, an initial candidate solution set for the decision variables is set, and a first taboo table for recording visited solutions and a taboo table for... A second taboo list is used to record frequently searched regions. Multiple candidate solutions are selected from the initial candidate solution set as the current solution. A neighborhood search is performed on the current solution. During the search, the first taboo list is used to avoid repeatedly accessing solutions already searched, and the second taboo list is used to dynamically adjust the search step size. When the number of iterations reaches a preset upper limit or the optimization objective shows no improvement for multiple consecutive iterations, the multiple candidate solutions obtained are sorted according to a preset evaluation function, and the top-ranked candidate solutions are selected as the candidate microbial enhancement strategy set. The solution with the highest comprehensive fitness is selected from the candidate microbial enhancement strategy set as the microbial enhancement strategy. This multiple taboo optimization mechanism can efficiently escape local optima and quickly locate the globally optimal solution in a complex solution space that balances nitrogen and phosphorus removal efficiency, carbon source economy, and community coordination.

[0009] Furthermore, the neighborhood search for the current solution includes: performing a swap operation, an insertion operation, and a reversal operation on each current solution to obtain multiple neighborhood solutions; calculating the difference between each neighborhood solution and the visited solutions recorded in the first tabu list, and adding neighborhood solutions with a difference greater than a preset difference threshold to the candidate neighborhood solution set; selecting the neighborhood solution with the highest comprehensive fitness of the optimization objective from the candidate neighborhood solution set as the new current solution, and adding the new current solution to the first tabu list. The aforementioned diverse neighborhood operations and difference filtering mechanism enrich the search directions and increase the probability of finding a better placement strategy.

[0010] As a specific implementation, selecting the solution with the highest overall fitness from the candidate microbial enhancement strategy set as the microbial enhancement strategy includes: calculating the normalized fitness value of each solution in the candidate microbial enhancement strategy set on four objectives: denitrification efficiency, phosphorus removal efficiency, carbon source consumption, and microbial community metabolic interaction balance; determining the weight of each objective using order relation analysis, and performing a weighted summation of the normalized fitness value of each solution according to the weights to obtain the overall fitness value of each solution; selecting the solution with the highest overall fitness value as the strategy to be verified, and performing constraint verification; the constraint verification includes: [The text abruptly ends here, so the translation stops here as well.] The following checks are performed: whether the sum of the added proportions equals the preset total; whether the carbon source addition does not exceed the carbon source reserve parameter; whether the dissolved oxygen concentration setting is within the adjustable range of the aeration device; whether the pH setting is within the adjustable range of the acid-base adjustment device; and whether the temperature setting is within the adjustable range of the temperature control device. If the constraint verification passes, the strategy to be verified is adopted as the microbial enhancement strategy. If the constraint verification fails, the strategy to be verified is removed from the candidate microbial enhancement strategy set, and the solution with the highest overall fitness after removal is re-verified under constraints until a solution that passes the constraint verification is obtained as the microbial enhancement strategy. Through target weighting and layer-by-layer constraint verification, it is ensured that the final output strategy achieves optimal overall performance while fully matching the on-site equipment capabilities and carbon source reserve status.

[0011] As another preferred technical solution of the present invention, the step of adding microbial enhancers to aquaculture wastewater according to the dosage ratio in the microbial enhancement strategy, and simultaneously adjusting dissolved oxygen concentration, pH value, and temperature according to the target values ​​to treat aquaculture wastewater for nitrogen and phosphorus removal, includes: dividing the microbial enhancers into multiple batches according to the dosage ratio in the microbial enhancement strategy, and adding them sequentially to the aquaculture wastewater according to the specified time window; before each batch is added, detecting the current concentrations of ammonia nitrogen, nitrite nitrogen, nitrate nitrogen, and total phosphorus in the aquaculture wastewater, and adjusting the carbon source dosage of this batch according to the difference between the current detected values ​​and the preset emission limits; within the specified time window, adjusting the dissolved oxygen concentration, pH value, and temperature according to the target range set in the microbial enhancement strategy using an aeration device, an acid-base adjustment device, and a temperature control device; after each time window of addition and adjustment is completed, updating the decision variables for subsequent time windows in the microbial enhancement strategy. By adopting a dynamic control method of batch addition and online feedback correction, it can compensate for fluctuations in influent water quality and changes in the metabolic state of microbial communities in real time, maintain the optimal growth environment for functional microbial communities, and ensure the continuous and stable effect of nitrogen and phosphorus removal.

[0012] In a more preferred embodiment, the adjustment via an aeration device, a pH adjustment device, and a temperature control device specifically includes: acquiring the target ranges for dissolved oxygen, pH, and temperature within the current time window; adjusting the frequency of the variable frequency fan in the aeration device and controlling the opening of the microporous aeration discs based on the difference between the target dissolved oxygen range and the real-time dissolved oxygen value; adding alkali or acid solution to the aquaculture wastewater using an alkali or acid solution addition pump based on the difference between the target pH range and the real-time pH value; controlling the heat transfer medium flow rate or refrigerant flow rate in the heat exchanger based on the difference between the target temperature range and the real-time temperature; and using the adjusted dissolved oxygen, pH, and temperature as feedback data to correct the target ranges for subsequent time windows. This closed-loop adjustment and feedback correction mechanism significantly improves the system's response speed and control accuracy to changes in operating conditions.

[0013] Furthermore, the step of adding the microbial enhancer to the aquaculture effluent according to the dosage ratio in the microbial enhancement strategy further includes: distributing the microbial enhancer to anaerobic, anoxic, and aerobic dosing points according to the dosage ratio; adding anaerobic ammonia-oxidizing bacteria to the anaerobic dosing points, adding denitrifying polyphosphate-accumulating bacteria and aerobic denitrifying bacteria to the anoxic dosing points, and adding nitrifying bacteria to the aerobic dosing points; each dosing point performs the dosing action according to the specified time window and corresponding dosage ratio, and controlling the start and stop of the stirring device in the area where the dosing point is located after the dosing action is completed. This allows each functional bacterial community to accurately colonize in its optimal habitat, fully utilize its respective nitrogen and phosphorus removal metabolic functions, and promotes uniform mixing of the bacterial agent and effluent through stirring control.

[0014] The technical effects and advantages provided by the present invention in the above technical solution are as follows:

[0015] By acquiring water quality characteristic parameters, carbon source reserve parameters, and initial abundance parameters of functional bacterial communities, a metabolic interaction matrix was constructed among anaerobic ammonia-oxidizing bacteria, denitrifying phosphorus-accumulating bacteria, aerobic denitrifying bacteria, and nitrifying bacteria. During the matrix construction process, competition coefficients for the same substrate between pairs of bacterial communities, as well as the promoting or inhibiting coefficients of one bacterial community's metabolites on the growth of another, were introduced to quantify the complex synergistic and antagonistic relationships among bacterial communities into unified matrix elements. When generating strategies based on this matrix, the determination of the dosage ratio no longer depends on the maximum specific growth rate of a single bacterial species, but rather on the targeted adjustment of the quantity ratio of each bacterial community according to the real-time interaction intensity reflected by the matrix. This avoids mutual inhibition of functional bacterial communities due to substrate competition, while utilizing the promoting effect of metabolites to enhance the synergistic nitrogen and phosphorus removal capacity of the bacterial communities. Regarding the regulation of carbon source dosage, the competition and promoting information provided by the metabolic interaction matrix ensures that carbon source allocation matches the actual carbon source demand of the bacterial communities, reducing carbon source waste and effluent organic matter residue caused by excessive dosage, and achieving higher nitrogen and phosphorus removal rates per unit of carbon source consumption.

[0016] After obtaining the metabolic interaction matrix, a multi-objective optimization model was constructed using the dosage ratio of each functional microbial community, carbon source dosage, dissolved oxygen concentration, pH value, and temperature as decision variables, and denitrification efficiency, phosphorus removal efficiency, carbon source consumption, and the balance of microbial community metabolic interactions as optimization objectives. This model was then solved using a multiple taboo search algorithm. During the optimization process, a first taboo table was established to record visited solutions, and a second taboo table was established to record frequently searched regions. Neighborhood searches were performed in parallel from multiple initial candidate solutions. The first taboo table avoided redundant calculations of already searched solutions, significantly improving search efficiency. Simultaneously, the second taboo table identified regions with excessively high search density, dynamically adjusting the search step size to help the search escape local optima and explore a wider range of combinations of dosage ratios and process parameters. Neighborhood searches used exchange, insertion, and reversal operations to generate differentiated neighborhood solutions, which were then filtered based on their differences from solutions already visited in the first taboo table, ensuring the diversity and novelty of candidate solutions. After the iteration terminates, the solution with the highest overall fitness is selected from the candidate strategy set as the microbial enhancement strategy, and it is constrained and verified to ensure that the dosage ratio, carbon source dosage, and process parameter settings are all within the adjustable range of the actual equipment. The resulting microbial enhancement strategy can provide dynamically matched dosage schemes and operating condition target values ​​at different time windows. When the influent water quality changes or the abundance of the microbial community evolves, the strategy adaptively adjusts with the update of the metabolic interaction matrix, continuously maintaining the nitrogen and phosphorus removal system at a high efficiency level, while reducing carbon source consumption and maintaining the balance of microbial community metabolic interactions, thus improving the stability and economy of aquaculture wastewater treatment. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0018] Figure 1 This is a flowchart of a method for nitrogen and phosphorus removal from aquaculture wastewater based on microbial enhancement.

[0019] Figure 2 This is a flowchart of an adaptive control method for batch-addition of microorganisms to aquaculture wastewater.

[0020] Figure 3 This is a scatter plot showing the denitrification and phosphorus removal efficiency of microbial enhancement strategies optimized by a multiple taboo search algorithm.

[0021] Figure 4 It is a real-time monitoring curve of dissolved oxygen concentration, pH value and temperature in the aquaculture wastewater treatment system. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0023] See Figure 1 This invention provides a method for nitrogen and phosphorus removal from aquaculture wastewater based on microbial enhancement. The method includes: obtaining water quality characteristic parameters, carbon source reserve parameters, and initial abundance parameters of functional microbial communities in the aquaculture wastewater; constructing a metabolic interaction matrix among functional microbial communities based on the water quality characteristic parameters, carbon source reserve parameters, and initial abundance parameters; using a multiple taboo search algorithm based on the metabolic interaction matrix to solve for the target values ​​of the addition ratio, carbon source addition amount, dissolved oxygen concentration, pH value, and temperature of each functional microbial community within a specified time window, thereby obtaining a microbial enhancement strategy; adding microbial enhancers to the aquaculture wastewater according to the addition ratio in the microbial enhancement strategy, and simultaneously adjusting the dissolved oxygen concentration, pH value, and temperature according to the target values ​​to treat the aquaculture wastewater for nitrogen and phosphorus removal.

[0024] Example 1: In practice, water samples were collected from the inlet, anaerobic zone, anoxic zone, aerobic zone, and outlet of the aquaculture wastewater treatment system to obtain water samples at each sampling point. During water sample collection, an automatic sampler was used to continuously collect a mixed water sample for 24 hours at the inlet. At the anaerobic zone, anoxic zone, aerobic zone, and outlet, instantaneous water samples were collected at the midpoint of the water depth in each reaction zone. Three water samples were collected in parallel at each sampling point, and the three samples were mixed thoroughly to obtain the corresponding water sample for that sampling point.

[0025] The concentrations of ammonia nitrogen, nitrite nitrogen, nitrate nitrogen, total phosphorus, and chemical oxygen demand (COD) in water samples from each sampling point were measured. Ammonia nitrogen concentration was determined using Nessler's reagent spectrophotometry; nitrite nitrogen concentration using N-(1-naphthyl)-ethylenediamine spectrophotometry; nitrate nitrogen concentration using ultraviolet spectrophotometry; total phosphorus concentration using ammonium molybdate spectrophotometry; and COD concentration using the dichromate method. The concentrations of ammonia nitrogen, nitrite nitrogen, nitrate nitrogen, total phosphorus, and COD at the inlet, anaerobic zone, anoxic zone, aerobic zone, and outlet were obtained respectively.

[0026] The water quality characteristic parameters are obtained by weighting the measured values ​​from each sampling point according to the hydraulic residence time. The weighted average is calculated using the following formula:

[0027]

[0028] in, This represents any one of the water quality characteristic parameters, which includes the weighted average of ammonia nitrogen concentration, the weighted average of nitrite nitrogen concentration, the weighted average of nitrate nitrogen concentration, the weighted average of total phosphorus concentration, and the weighted average of chemical oxygen demand concentration. Indicates the sequence number of the sampling point. The value range is 1 to 5, corresponding to the inlet, anaerobic zone, anoxic zone, aerobic zone and outlet respectively, and the serial numbers are arranged in order of water flow direction. Indicates the first The measured concentration of any of the above indicators at each sampling point; Indicates the first The hydraulic residence time at each sampling point, whereby the hydraulic residence time is the actual hydraulic residence time of the corresponding reaction zone or pipe section, obtained through tracer experiments or hydraulic model calculations, and is expressed in hours. For the inlet, The value is taken as the hydraulic retention time in the inlet pipe; for anaerobic, anoxic, and aerobic zones, The value is taken as the design hydraulic residence time of the corresponding reaction zone; for the outlet, The value is the hydraulic residence time in the outlet pipe. The weighted average concentrations of ammonia nitrogen, nitrite nitrogen, nitrate nitrogen, total phosphorus, and chemical oxygen demand are calculated using the formulas described above. These five weighted averages constitute the water quality characteristic parameters.

[0029] In some embodiments, the carbon source storage tank is equipped with a radar level gauge and an online carbon source effective component concentration analyzer. The carbon source level and effective component concentration in the storage tank are read in real time using the radar level gauge, and the effective component concentration is analyzed in real time using the online carbon source effective component concentration analyzer. The effective component concentration refers to the mass concentration of usable carbon source in the carbon source solution. The product of the read carbon source level and the effective component concentration is used as the carbon source reserve parameter, which characterizes the total mass of remaining usable carbon source in the storage tank.

[0030] Total microbial DNA was extracted from water samples at each sampling point, and 16S rRNA gene high-throughput sequencing was performed. The initial abundance parameters of anaerobic ammonia-oxidizing bacteria, denitrifying polyphosphate-accumulating bacteria, aerobic denitrifying bacteria, and nitrifying bacteria were determined based on the sequence abundance results. Total microbial DNA was extracted using a soil / water DNA extraction kit. DNA was extracted from water samples at each sampling point according to the kit's instructions. The total DNA from each sampling point was then subjected to PCR amplification of the hypervariable region of the 16S rRNA gene V3-V4. Universal primers 338F and 806R were used for amplification. After purification and quantification, sequencing libraries were constructed, and high-throughput sequencing of the paired ends (250 bp) was performed on an Illumina NovaSeq 6000 sequencing platform.

[0031] After quality control and assembly, the raw sequencing data were used to reduce noise and generate amplicon sequence variants using QIIME2 software, resulting in an amplicon sequence variant abundance table for each water sample. Representative sequences of the amplicon sequence variants were then compared with the SILVA138 reference database for species annotation. Based on species annotation results, the initial abundance parameters for anaerobic ammonia-oxidizing bacteria were the sum of the relative abundances of amplicon sequence variants annotated as belonging to the genera *Candidatus Brocadia*, *Candidatus Kuenenia*, *Candidatus Scalindua*, and *Candidatus Anammoxoglobus*. The initial abundance parameters for denitrifying phosphorus-accumulating bacteria were the sum of the relative abundances of amplicon sequence variants annotated as belonging to the genera *Accumulibacter*, *Dechloromonas*, and *Pseudomonas* that also possess denitrifying phosphorus-accumulating function. The initial abundance parameters for aerobic denitrifying bacteria were the sum of the relative abundances of amplicon sequence variants annotated as belonging to the genera *Paracoccus*, *Alcaligenes*, and *Acinetobacter* that also possess aerobic denitrification function. The initial abundance parameters for nitrifying bacteria were the sum of the relative abundances of amplicon sequence variants annotated as belonging to the genera *Nitrosomonas* and *Nitrobacter*. The initial abundance parameters of functional bacterial communities in water samples from each sampling point were calculated independently without weighted averaging and were directly used as the initial abundance parameters for the corresponding functional bacterial communities.

[0032] Example 2: In practical implementation, a pre-defined microbial metabolism database is used to store the half-saturation constants, maximum specific degradation rate constants, and product inhibition constants of anaerobic ammonia-oxidizing bacteria, denitrifying phosphorus-accumulating bacteria, aerobic denitrifying bacteria, and nitrifying bacteria for ammonia nitrogen, nitrite nitrogen, nitrate nitrogen, total phosphorus, and organic carbon sources. The pre-defined microbial metabolism database adopts a relational data table structure, with each table containing fields for: microbial community name, substrate name, half-saturation constant, maximum specific degradation rate constant, product inhibition constant, and product name. The microbial community name field takes the value of one of the following: anaerobic ammonia-oxidizing bacteria, denitrifying phosphorus-accumulating bacteria, aerobic denitrifying bacteria, or nitrifying bacteria. The substrate name field takes the value of one of the following: ammonia nitrogen, nitrite nitrogen, nitrate nitrogen, total phosphorus, or organic carbon source. The half-saturation constant and maximum specific degradation rate constant record the Monod equation parameters for the corresponding microbial community under single substrate limitation conditions. The product inhibition constant records the non-competitive inhibition constant of a certain metabolite of the corresponding microbial community on the community itself. The product name field records the types of inhibitory metabolites.

[0033] The system retrieves the half-saturation constants, maximum specific degradation rate constants, and product inhibition constants for ammonia nitrogen, nitrite nitrogen, nitrate nitrogen, total phosphorus, and organic carbon sources from a pre-defined microbial metabolic database using SQL queries. For example, the query condition for anaerobic ammonia oxidizing bacteria is that the bacterial community name equals "anaerobic ammonia oxidizing bacteria" and the substrate name equals "ammonia nitrogen," returning the half-saturation constants. and maximum specific degradation rate constant The query criteria are: bacterial community name equal to "anaerobic ammonia oxidizing bacteria" and substrate name equal to "nitrite nitrogen". The result is the half-saturation constant. and maximum specific degradation rate constant And the product inhibition constant, the product name corresponding to the product inhibition constant is nitrite nitrogen, which represents the product inhibition constant of nitrite nitrogen on the anaerobic ammonia oxidizing bacteria themselves. Using the same query method, the half-saturation constants, maximum specific degradation rate constants, and product inhibition constants of the metabolites of each functional bacterial community on themselves and other bacterial communities were obtained for all substrates.

[0034] Based on water quality characteristic parameters and initial abundance parameters, the competition coefficients for the same substrate among anaerobic ammonia-oxidizing bacteria, denitrifying phosphorus-accumulating bacteria, aerobic denitrifying bacteria, and nitrifying bacteria were calculated. The formula for calculating the competition coefficient is as follows:

[0035]

[0036] in, and These represent two different functional bacterial groups. and The value range is {AnAOB,DPB,AD,NOB}, where AnAOB represents anaerobic ammonia oxidizing bacteria, DPB represents denitrifying polyphosphate-accumulating bacteria, AD represents aerobic denitrifying bacteria, and NOB represents nitrifying bacteria. Indicating the same substrate, The range of values ​​for is { , , ,TP,Corg}, Represents ammonia nitrogen. Represents nitrite nitrogen. TP represents nitrate nitrogen, Corg represents total phosphorus, and Corg represents organic carbon source. Indicating functional flora Compared to functional flora For the substrate The competition coefficient; Functional flora For the substrate The maximum specific degradation rate constant is obtained from a pre-defined microbial metabolism database; Functional flora For the substrate The half-saturation constant is obtained from a pre-defined microbial metabolism database; Functional flora For the substrate The maximum specific degradation rate constant; Functional flora For the substrate The half-saturation constant. When calculating the competition coefficient for ammonia nitrogen between anaerobic ammonia-oxidizing bacteria and denitrifying phosphorus-accumulating bacteria, Take AnAOB, Take DPB, Pick Substituting the corresponding half-saturation constant and maximum specific degradation rate constant, we obtain the competition coefficient. For the same functional bacterial group and For the substrate The competition coefficient is set to a fixed value of 1.

[0037] Calculate the promotion or inhibition coefficient of the metabolites of one functional bacterial community on the growth of another functional bacterial community. Use the weighted average of nitrite nitrogen concentration and the weighted average of nitrate nitrogen concentration in the water quality characteristic parameters as the current concentration of the corresponding metabolite. Taking the inhibition coefficient of nitrite nitrogen, a metabolite of anaerobic ammonia oxidizing bacteria, on nitrifying bacteria as an example, the inhibition coefficient... The calculation method is as follows: obtain the product inhibition constant of nitrifying bacteria on nitrite nitrogen from a preset microbial metabolism database. Suppression coefficient Values ,in This is the weighted average of nitrite nitrogen concentration among water quality characteristic parameters. If a certain metabolite promotes the growth of another functional bacterial community, the promotion coefficient is positive. It is calculated as the ratio of the metabolite concentration to a preset half-effect concentration, which is obtained from the promotion effect data stored in a preset microbial metabolism database.

[0038] The metabolic interaction matrix is ​​obtained by filling the matrix elements with competition coefficients, promotion coefficients, and inhibition coefficients according to the species order of the functional microbiota. The species order of the functional microbiota is: anaerobic ammonia oxidizing bacteria, denitrifying phosphorus-accumulating bacteria, aerobic denitrifying bacteria, and nitrifying bacteria, which are assigned row indices 1, 2, 3, 4 and column indices 1, 2, 3, 4, respectively. The metabolic interaction matrix M is a 4x4 matrix, and the matrix elements are... This is a data structure containing competition coefficients for all substrates between functional bacterial community r and functional bacterial community c, as well as the promoting or inhibiting coefficients of metabolites of functional bacterial community r on functional bacterial community c. For example, Competition coefficient between anaerobic ammonia-oxidizing bacteria and denitrifying phosphorus-accumulating bacteria , , , , And the promoting or inhibiting coefficients of anaerobic ammonia oxidizing bacteria metabolites (nitrite nitrogen) on denitrifying polyphosphate-accumulating bacteria. The diagonal elements contain only the competition coefficient (1) of the same functional bacterial community for different substrates, and the product inhibition coefficient of a metabolite on itself. After filling in all the coefficients in row and column order, the complete metabolic interaction matrix is ​​obtained.

[0039] Example 3: In practical implementation, a multi-objective optimization model is constructed using the addition ratio of each functional microbial community, carbon source addition amount, dissolved oxygen concentration, pH value, and temperature as decision variables, and denitrification efficiency, phosphorus removal efficiency, carbon source consumption, and the balance of microbial community metabolic interactions as optimization objectives. The addition ratio of each functional microbial community refers to the proportion of anaerobic ammonia-oxidizing bacteria, denitrifying phosphorus-accumulating bacteria, aerobic denitrifying bacteria, and nitrifying bacteria in the total amount of microbial enhancer, with the sum of these ratios being 1. Carbon source addition amount refers to the volume of carbon source reserve liquid added to the aquaculture wastewater treatment system within each time window. Dissolved oxygen concentration refers to the target dissolved oxygen concentration in the aerobic zone, the anoxic zone, and the anaerobic zone. pH value refers to the target pH value in each reaction zone of the aquaculture wastewater treatment system. Temperature refers to the target temperature in each reaction zone of the aquaculture wastewater treatment system. The multi-objective optimization model includes four objective functions: nitrogen removal efficiency objective function. Phosphorus removal efficiency objective function Objective function for carbon source consumption Objective function for the balance of metabolic interactions between the microbial community Denitrification efficiency objective function The calculation method is to subtract the ratio of the total nitrogen concentration in the effluent to the total nitrogen concentration in the influent from 1. The total nitrogen concentration in the effluent is obtained through a process model that includes the proportion of functional bacteria added, the amount of carbon source added, the dissolved oxygen concentration, pH value, and temperature. The objective function for phosphorus removal efficiency is... The calculation method is to subtract the ratio of the effluent total phosphorus concentration to the influent total phosphorus concentration from 1. The effluent total phosphorus concentration is obtained through a process model that includes the functional microbial community addition ratio, carbon source addition amount, dissolved oxygen concentration, pH value, and temperature. The objective function for carbon source consumption is... The calculation method is the ratio of the sum of carbon source additions in each time window to the carbon source reserve parameter. Objective function for microbial community metabolic interaction balance. Calculated based on the metabolic interaction matrix, the method is to find the ratio of the sum of the absolute values ​​of all promoting coefficients to all inhibiting coefficients in the metabolic interaction matrix. Multi-objective optimization model. The expression is:

[0040]

[0041] in, Represents a vector of decision variables. , The dosage ratio of anaerobic ammonia-oxidizing bacteria, The dosage ratio of denitrifying polyphosphate-accumulating bacteria, The dosage ratio of aerobic denitrifying bacteria, The dosage ratio of nitrifying bacteria, For carbon source addition amount, Dissolved oxygen concentration, pH value, temperature variable It can be used alone as a constraint in the model solution; The value range of each component is determined by the capacity of the process equipment. to Each of them takes values ​​in the range [0,1] and the sum of the four is equal to 1. The value range of is [0, carbon source reserve parameter], The value range is the adjustable dissolved oxygen concentration range of the aeration device. The value range is the pH range that the acid-base adjustment device can adjust.

[0042] Based on the metabolic interaction matrix, an initial candidate solution set is set for the decision variables, and a first tabu table is established to record visited solutions, and a second tabu table is established to record frequently searched regions. The initial candidate solution set is set as follows: in the decision variable vector... Within the range of values ​​for each dimension, 100 initial candidate solutions are generated using the Latin hypercube sampling method. Each initial candidate solution is a decision variable vector uniformly distributed within the value space of each dimension. The first tabu list is a fixed-length queue data structure with a queue length of 50. The first tabu list stores the decision variable vectors that have been accessed, and the stored content is the decision variable vector. The second tabu list is a fixed-length queue data structure with a queue length of 20. It stores the coordinates of the center point and radius of frequently searched regions. The center point coordinates of the frequently searched regions are represented by a decision variable vector. This indicates that the region radius is a scalar value. Both the first and second tabu lists are initialized to empty queues.

[0043] Multiple candidate solutions are selected from the initial candidate solution set as the current solutions. The selection method is as follows: the 100 initial candidate solutions in the initial candidate solution set are substituted into the four objective functions of the multi-objective optimization model for calculation. The Pareto non-dominated sorting method is used to sort the 100 initial candidate solutions. The 10 initial candidate solutions with the largest crowding distance on the Pareto front are selected as the current solutions. Each current solution is an independent decision variable vector.

[0044] A neighborhood search is performed on the current solution. During the search, a first tabu list is used to avoid repeatedly visiting solutions already searched, and a second tabu list is used to dynamically adjust the search step size. The specific implementation of the neighborhood search is as follows: for each current solution, a swap operation, an insertion operation, and a reversal operation are performed to obtain multiple neighborhood solutions. The swap operation involves randomly swapping the functional microbial community dosage ratios of any two time windows in the current solution. During the operation, two time window indices are randomly selected, and the dosage ratios of the four functional microbial communities corresponding to the two time windows are interchanged. The insertion operation involves moving the carbon source dosage value from one time window to a specified position in the carbon source dosage value sequence of another time window. During the operation, a carbon source dosage value from a random time window is selected from the carbon source dosage value sequence, deleted from its original position, and then a random insertion position is selected in another time window, inserting the deleted carbon source dosage value before that position. The reverse operation involves reversing the order of decision variables across multiple consecutive time windows in the current solution. During the operation, a start time window number and an end time window number are randomly selected, and the decision variable value sequences corresponding to all time windows between the start and end time window numbers are reversed. Each of these three operations is performed once for each current solution, generating three neighborhood solutions for each current solution.

[0045] Calculate the difference between each neighborhood solution and the visited solutions recorded in the first tabu list. The difference is defined as the Euclidean distance between the two decision variable vectors. A preset difference threshold of 0.01 is set, and neighborhood solutions with a difference greater than 0.01 are added to the candidate neighborhood solution set. The neighborhood solution with the highest overall fitness of the optimization objective is selected from the candidate neighborhood solution set as the new current solution, and added to the first tabu list. The overall fitness of the optimization objective is calculated as follows: the four objective function values ​​of the multi-objective optimization model are normalized using a min-max method. A weighted summation method is used to sum the normalized four objective function values. The weights for nitrogen removal efficiency, phosphorus removal efficiency, carbon source consumption, and microbial metabolic interaction balance are set to 0.3, 0.25, and 0.2 respectively. The weighted summation value is the overall fitness of the optimization objective. The neighborhood solution with the highest overall fitness of the optimization objective is selected from the candidate neighborhood solution set and replaces the corresponding current solution in the original current solution set.

[0046] During the search process, the mechanism for dynamically adjusting the search step size using the second tabu list is as follows: In each iteration, the distribution of the current solution in the decision variable space is statistically analyzed. If more than half of the current solutions fall within the radius of a frequently searched region recorded in the second tabu list, the coordinates of the center point of that frequently searched region are added to the second tabu list, and the radius of that frequently searched region is expanded to 1.5 times its original radius. When generating neighborhood solutions, if the coordinates of a neighborhood solution fall within the radius of any frequently searched region in the second tabu list, a penalty is imposed on that neighborhood solution by subtracting a penalty term from the overall fitness value of the neighborhood solution's optimization objective. The penalty term has a value of 0.1.

[0047] When the number of iterations reaches a preset upper limit or the optimization objective fails to improve for multiple consecutive iterations, the multiple candidate solutions obtained are sorted according to a preset evaluation function, and the top-ranked candidate solutions are selected as the candidate microbial enhancement strategy set. The preset upper limit is set to 500 iterations. The criterion for determining that the optimization objective fails to improve for multiple consecutive iterations is: in 20 consecutive iterations, the optimal value of the optimization objective's comprehensive fitness in the current solution set changes by less than 0.001. The preset evaluation function uses the same weighted summation calculation method as the optimization objective's comprehensive fitness. At the end of the iteration, all decision variable vectors in the current solution set are sorted from smallest to largest according to the values ​​calculated by the preset evaluation function. The top-ranked vectors are those with the smallest preset evaluation function value. The top 10 sorted decision variable vectors are selected as the candidate microbial enhancement strategy set.

[0048] The solution with the highest overall fitness from the candidate microbial enhancement strategy set was selected as the microbial enhancement strategy. The normalized fitness value of each solution in the candidate microbial enhancement strategy set was calculated for the four objectives: nitrogen removal efficiency, phosphorus removal efficiency, carbon source consumption, and microbial community metabolic interaction balance. The normalized fitness value was calculated by performing min-max normalization on the same objective function value of all solutions in the candidate microbial enhancement strategy set. The weights of nitrogen removal efficiency, phosphorus removal efficiency, carbon source consumption, and microbial community metabolic interaction balance were determined using order relation analysis. The specific steps of the order relation analysis method are as follows: Domain experts rank the importance of the four optimization objectives, determining the order of importance as follows: nitrogen removal efficiency > phosphorus removal efficiency > carbon source consumption > microbial community metabolic interaction balance. The importance ratios between adjacent objectives are set: the ratio of nitrogen removal efficiency to phosphorus removal efficiency is set to 1.2, the ratio of phosphorus removal efficiency to carbon source consumption is set to 1.1, and the ratio of carbon source consumption to microbial community metabolic interaction balance is set to 1.0. The weight values ​​of the four objectives are calculated according to the weight recursive formula of the order relation analysis method, resulting in a weight of 0.33 for nitrogen removal efficiency, 0.28 for phosphorus removal efficiency, 0.25 for carbon source consumption, and 0.14 for microbial community metabolic interaction balance. The normalized fitness values ​​of each solution are weighted and summed according to these weights to obtain the comprehensive fitness value of each solution. The solution with the highest comprehensive fitness value is selected as the strategy to be validated.

[0049] The strategy to be validated needs to undergo constraint validation, which includes: whether the sum of the addition ratios equals the preset total (1); whether the carbon source addition does not exceed the carbon source reserve parameter; whether the dissolved oxygen concentration setpoint is within the adjustable range of the aeration device (0 to 10 mg / L); whether the pH setpoint is within the adjustable range of the acid-base adjustment device (5.5 to 9.5); and whether the temperature setpoint is within the adjustable range of the temperature control device (10℃ to 40℃). If all constraint validations of the strategy to be validated pass, the strategy to be validated is adopted as the microbial enhancement strategy. If the constraint validation fails, the strategy to be validated is removed from the candidate microbial enhancement strategy set, and the solution with the highest overall fitness is reselected from the remaining solutions in the candidate microbial enhancement strategy set for constraint validation. This process is repeated until a solution that passes the constraint validation is obtained, and this solution is adopted as the microbial enhancement strategy.

[0050] The overall process of the multiple tabu optimization algorithm is as follows: Based on the metabolic interaction matrix, an initial candidate solution set for the decision variables is set, and a first tabu table is established to record visited solutions, and a second tabu table is established to record frequently searched regions. Multiple candidate solutions are selected from the initial candidate solution set as the current solution, and a neighborhood search is performed on the current solution. During the search, the first tabu table is used to avoid repeatedly visiting solutions already searched, and the second tabu table is used to dynamically adjust the search step size. When the number of iterations reaches a preset upper limit or the optimization objective shows no improvement for several consecutive iterations, the search is terminated, and the current optimal solution is output as the microbial reinforcement strategy. During the iteration process, the contents of the first and second tabu tables are updated with each iteration. The first tabu table uses a first-in-first-out (FIFO) strategy to maintain a queue length of no more than 50, and the second tabu table uses a FIFO strategy to maintain a queue length of no more than 20. When the number of iterations reaches 500, the search is forcibly terminated; when the optimization objective shows no improvement for 20 consecutive iterations, the search is forcibly terminated. After the search is terminated, the decision variable vector with the highest comprehensive fitness of the optimization objective in the current solution set is output as the current optimal solution.

[0051] See Figure 3 The graph shows that the horizontal axis represents denitrification efficiency, ranging from 0.84 to 1.00, and the vertical axis represents phosphorus removal efficiency, ranging from 0.75 to 1.00. Each scatter point in the graph represents the paired value of denitrification and phosphorus removal efficiencies for a candidate solution of a microbial enhancement strategy. The color of the scatter point is indicated by a color scale on the right, representing the overall fitness value of that candidate solution, with the color gradually changing from dark purple to yellow, and the overall fitness value ranging from approximately 0.3 to 1.0. Overall, the scatter points are mainly clustered in the high-efficiency range of denitrification efficiency (0.90 to 1.00) and phosphorus removal efficiency (0.90 to 0.99), indicating that most candidate strategies perform well in both denitrification and phosphorus removal.

[0052] The Pareto front, marked with a red hollow circle in the upper right corner of the figure, represents the region of optimal solution concentration. The denitrification and phosphorus removal efficiencies at this point are both close to 1.00, indicating that high denitrification efficiency can be achieved simultaneously with high phosphorus removal efficiency during multi-objective optimization. The overall fitness value of the Pareto point is close to yellow, indicating its excellent overall performance.

[0053] As described in Example 3, the multi-objective optimization model aims to optimize decision variables such as nitrogen removal efficiency, phosphorus removal efficiency, carbon source consumption, and the balance of microbial community metabolic interactions. It employs a multiple taboo search algorithm to optimize these variables, including the proportion of microbial community feed, carbon source feed, dissolved oxygen concentration, pH, and temperature. The scatter plots of nitrogen removal efficiency and phosphorus removal efficiency shown in the figure, along with their corresponding comprehensive fitness values, reflect the performance of candidate strategies during the optimization process. The scatter plots corresponding to high comprehensive fitness values ​​are concentrated in regions where both nitrogen removal efficiency and phosphorus removal efficiency are high, indicating that the optimization algorithm effectively finds a solution set that balances both key indicators.

[0054] The distribution trend of the scatter points in the figure shows that when the nitrogen removal efficiency is greater than 0.95, the phosphorus removal efficiency remains above 0.90, further confirming the synergistic optimization ability of the microbial enhancement strategy in controlling nitrogen removal while simultaneously improving phosphorus removal efficiency. The scatter points with lower overall fitness are mostly concentrated in areas where either the nitrogen removal efficiency or the phosphorus removal efficiency is below 0.90, suggesting that this type of strategy may have shortcomings in practical applications.

[0055] Example 4: In specific implementation, please refer to Figure 2 Based on the dosage ratios in the microbial enhancement strategy, the microbial enhancer was divided into multiple batches and added sequentially to the aquaculture wastewater according to specified time windows. The microbial enhancement strategy comprises one batch of K specified time windows, where K is determined by the total treatment cycle of the aquaculture wastewater. Each specified time window is of equal length and set to a fixed duration T. The dosage ratios of anaerobic ammonia-oxidizing bacteria, denitrifying polyphosphate-accumulating bacteria, aerobic denitrifying bacteria, and nitrifying bacteria corresponding to each specified time window in the microbial enhancement strategy were extracted, resulting in a dosage ratio sequence for the four functional bacterial groups from the first to the Kth specified time windows. According to the carbon source dosage in each specified time window of the microbial enhancement strategy, the total carbon source dosage was allocated to each specified time window. The dosage ratios of the four functional bacterial groups corresponding to each specified time window and the corresponding carbon source dosage constitute a batch dosage scheme. The entire microbial enhancement strategy generates K batch dosage schemes. According to the time sequence of the specified time window, starting from the first specified time window, the dosing plan for each batch is executed sequentially, and each batch corresponds to a complete time window operation cycle.

[0056] Before each batch of addition, the current concentrations of ammonia nitrogen, nitrite nitrogen, nitrate nitrogen, and total phosphorus in the aquaculture wastewater are measured. The carbon source addition amount for this batch is adjusted based on the difference between the current measured values ​​and the preset emission limits. Taking the p-th specified time window batch as an example, where p is the batch number and its value ranges from 1 to K, at the start of the p-th batch addition, water samples are collected from the end of the aerobic zone or the outlet of the aquaculture wastewater treatment system. The concentrations of ammonia nitrogen, nitrite nitrogen, nitrate nitrogen, and total phosphorus in the water samples are measured and recorded as follows: , , and The superscript p-1 indicates the measured concentration value at the end of the previous time window before the p-th batch is implemented. The ammonia nitrogen emission limit is denoted as... The emission limit for nitrite nitrogen is denoted as The emission limit for nitrate nitrogen is denoted as The total phosphorus emission limit is denoted as The following formula is used to calculate the adjustment of the carbon source dosage for this batch:

[0057]

[0058] in, This represents the carbon source dosage adjusted for the p-th time window, in liters. This represents the initial carbon source dosage in the p-th time window of the microbial enhancement strategy, in liters. The gain coefficient for the carbon source is adjusted, with a value ranging from 0.5 to 2.0. Here it is set to 1.0, which means that when there is a deviation between the measured concentration and the emission limit, the carbon source dosage is adjusted proportionally according to the deviation. The basis for setting it to 1.0 is that it is adjusted according to the standard response intensity during the initial operation, and can be corrected online according to the treatment effect in the future. The ammonia nitrogen deviation influence factor is set to 0.8; The nitrite nitrogen deviation influence factor is set to 0.3; The nitrate nitrogen deviation influence factor is set to 0.5; The total phosphorus deviation impact factor is set to 1.2. The values ​​of these impact factors are standardized regression coefficients obtained through multiple linear regression analysis of the deviations of influent ammonia nitrogen, nitrite nitrogen, nitrate nitrogen, and total phosphorus concentrations from emission limits in historical operating data, and the required carbon source dosage compensation. These coefficients are rounded to one decimal place and reflect the sensitivity of different pollutants to carbon source demand. The adjusted carbon source dosage... If the amount of carbon source added exceeds the permitted range, then the lower or upper limit of the permitted range shall be used respectively.

[0059] Within a specified time window, the dissolved oxygen concentration, pH value, and temperature are adjusted according to the target ranges set in the microbial enhancement strategy using aeration, pH adjustment, and temperature control devices. The target ranges for dissolved oxygen, pH, and temperature within the current time window are obtained. The target range for dissolved oxygen, pH, and temperature is provided by the microbial enhancement strategy and includes the lower limit of the target dissolved oxygen value. and the upper limit of dissolved oxygen target The target pH range includes the lower limit of the target pH value. and pH target upper limit The temperature target range includes the lower limit of the temperature target. and the upper limit of the temperature target The target ranges for dissolved oxygen, pH, and temperature in the p-th time window are all directly provided by the microbial enhancement strategy.

[0060] Based on the difference between the target dissolved oxygen range and the real-time dissolved oxygen value, the frequency of the variable frequency fan in the aeration device is adjusted, and the opening of the microporous aeration discs is controlled. Online dissolved oxygen sensors are installed in the aerobic, anoxic, and anaerobic zones, and real-time dissolved oxygen values ​​are collected every 30 seconds. For the aerobic zone, the real-time dissolved oxygen value is compared with the target dissolved oxygen range for the aerobic zone. If the real-time dissolved oxygen value is lower than the target range, the system will detect the difference. If the real-time dissolved oxygen value is higher than the preset ratio, the output frequency of the variable frequency fan will be increased, and the opening of the microporous aeration disc will be increased simultaneously. If the frequency of the variable frequency fan is reduced by a preset ratio, the opening of the microporous aeration disc will also be reduced. The dissolved oxygen adjustment method for the anoxic and anaerobic zones is the same as that for the aerobic zone, using the respective dissolved oxygen target range for each zone. The frequency adjustment range of the variable frequency fan is 0Hz to 50Hz, and the adjustment range of the microporous aeration disc opening is 0% to 100%.

[0061] Based on the difference between the target pH range and the real-time pH value, alkali or acid solutions are added to the aquaculture wastewater using an alkali or acid solution dosing pump. Online pH sensors are installed in each reaction zone, collecting real-time pH values ​​every 30 seconds. The real-time pH value is compared to the target pH range; if the real-time pH value is lower than the target range... Then start the alkali dosing pump and add a 0.5 mol / L sodium hydroxide solution to the aquaculture wastewater. Each addition should last 5 seconds, with an interval of 60 seconds between additions. If the real-time pH value is higher than... Then start the acid dosing pump and add a 0.25 mol / L hydrochloric acid solution to the aquaculture wastewater. The duration of each dosing is fixed at 5 seconds, and the dosing interval is 60 seconds.

[0062] The heat or refrigerant flow rate of the heat exchanger is controlled based on the difference between the target temperature range and the real-time temperature. Online temperature sensors are installed in each reaction zone, collecting real-time temperature data every 30 seconds. The real-time temperature is compared with the target temperature range; if the real-time temperature is lower than the target temperature range... If the temperature is higher than 5 cubic meters per hour, increase the flow rate of the heat exchanger. The heat medium is warm water, and the flow rate can be adjusted from 0 to 5 cubic meters per hour. To increase the refrigerant flow rate in the heat exchanger, the refrigerant is chilled water, and the flow rate can be adjusted from 0 to 5 cubic meters per hour. The heat exchanger uses a coil-type heat exchanger, installed on the tank wall of each reaction zone.

[0063] The adjusted dissolved oxygen, pH, and temperature values ​​are used as feedback data to correct the target range for subsequent time windows. After the p-th time window ends, the arithmetic mean of all real-time dissolved oxygen values ​​recorded within that time window is taken to obtain the average dissolved oxygen value. The arithmetic mean of all real-time pH values ​​recorded within the time window is taken to obtain the average pH value. The arithmetic mean of all real-time temperature values ​​recorded within the time window is taken to obtain the average temperature value. Calculate the average dissolved oxygen value and the median of the target dissolved oxygen range. The difference is used to obtain the dissolved oxygen deviation value; the average pH value and the median of the pH target range are calculated. The difference is used to obtain the pH deviation value; the average temperature value and the median of the temperature target interval are calculated. The difference is used to obtain the temperature deviation value. The dissolved oxygen deviation value, pH deviation value and temperature deviation value are multiplied by the preset feedback correction factor of 0.3 respectively, and the result is used as the correction amount. This correction amount is then added to the median of the target interval of all subsequent unexecuted time windows, thereby updating the target interval of subsequent time windows.

[0064] The microbial enhancers were distributed to the anaerobic, anoxic, and aerobic dosing points according to the dosage ratio. The microbial enhancers consisted of four separately packaged lyophilized powders of different functional bacterial groups. Before dosing, the dosage of the anaerobic ammonia-oxidizing bacteria lyophilized powder, denitrifying polyphosphate-accumulating bacteria lyophilized powder, aerobic denitrifying bacteria lyophilized powder, and nitrifying bacteria lyophilized powder were calculated based on the dosage ratio of the four functional bacterial groups corresponding to the current batch in the microbial enhancement strategy. The anaerobic dosing point was located at the inlet of the anaerobic zone, the anoxic zone dosing point at the inlet of the anoxic zone, and the aerobic zone dosing point at the inlet of the aerobic zone. The anaerobic ammonia-oxidizing bacteria lyophilized powder was added to the anaerobic zone dosing point by pouring the weighed powder into a dosing container containing a small amount of aquaculture wastewater, stirring to form a suspension, and then injecting it uniformly into the anaerobic zone dosing point over 10 minutes using a peristaltic pump. In the anoxic zone, add lyophilized powders of denitrifying polyphosphate-accumulating bacteria and aerobic denitrifying bacteria. Weigh the two lyophilized powders according to the specified ratio and pour them together into the addition container to form a mixed suspension. Then, use a peristaltic pump to inject this suspension into the anoxic zone addition point at a uniform rate over 10 minutes. Similarly, add lyophilized powders of nitrifying bacteria to the aerobic zone addition point, forming a suspension, and then use a peristaltic pump to inject this suspension into the aerobic zone addition point at a uniform rate over 10 minutes. The addition process should be performed at each addition point according to the specified time window and corresponding addition ratio.

[0065] After the addition process is completed, the mixing devices in the area where the addition point is located are controlled to start and stop. Submersible mixers are installed in the anaerobic, anoxic, and aerobic zones. Immediately after the addition process is completed, the submersible mixer in the corresponding zone is activated, and the mixing time is 15 minutes at a speed of 60 rpm, ensuring thorough mixing of the added microbial enhancer with the aquaculture wastewater. After 15 minutes, the submersible mixers are turned off, allowing the original water flow conditions in each reaction zone to return to normal.

[0066] After each time window of addition and adjustment is completed, the decision variables for subsequent time windows in the microbial enhancement strategy are updated. After the p-th time window is completed, the value of p increases from 1. When p has not reached K, the state of the aquaculture wastewater treatment system after the current time window ends is taken as the new initial state. The water quality characteristic parameters, carbon source reserve parameters, and initial abundance parameters of functional microorganisms of the aquaculture wastewater are re-acquired. The metabolic interaction matrix between functional microorganisms is reconstructed based on the re-acquired water quality characteristic parameters, carbon source reserve parameters, and initial abundance parameters. Then, the multiple taboo optimization algorithm is used to solve for the target values ​​of the addition ratio of each functional microorganism, carbon source addition amount, dissolved oxygen concentration, pH value, and temperature from the p+1-th specified time window to the K-th specified time window, resulting in the updated microbial enhancement strategy. The updated microbial enhancement strategy covers all remaining unexecuted time windows. The method for re-acquiring water quality characteristic parameters is consistent with the previously described method of collecting water samples and testing relevant indicators at the inlet, anaerobic zone, anoxic zone, aerobic zone, and outlet, and then weighting the average based on hydraulic retention time. The carbon source reserve parameters are still obtained by reading the product of the carbon source level and the effective carbon source concentration in the carbon source storage tank. The initial abundance parameters of the functional microbial community are still determined by extracting total microbial DNA from water samples at each sampling point, performing high-throughput 16S rRNA gene sequencing, and then analyzing the sequence abundance. Based on the newly generated and updated microbial enhancement strategy, the p+1th batch of addition and adjustment continues until all K time windows have been completed.

[0067] See Figure 4 The figure shows the dynamic changes in dissolved oxygen concentration, temperature, and pH value of the aquaculture wastewater treatment system in Example 4 within a specified time window. The horizontal axis represents time in minutes; the left vertical axis corresponds to dissolved oxygen concentration (mg / L) and temperature (°C), and the right vertical axis corresponds to pH value. The blue curve represents dissolved oxygen concentration, the green curve represents temperature, and the orange curve represents pH value. The background area in the figure represents the entire observation time range.

[0068] The dissolved oxygen concentration was maintained within the target control range of 2.0 mg / L to 3.5 mg / L, as indicated by the blue dashed line in the figure. The dissolved oxygen concentration curve showed slight fluctuations on the time axis but remained generally stable, indicating that the aeration device effectively regulated the dissolved oxygen in the water by adjusting the frequency of the variable frequency fan and the opening of the microporous aeration discs, thus meeting the target dissolved oxygen concentration requirements of the aerobic zone.

[0069] The temperature was controlled within the target range of 22.5℃ to 24.5℃, which is represented by the green dotted line in the graph. The temperature curve shows a slow fluctuation trend, remaining within the set temperature target range overall. This indicates that the temperature control device effectively maintains system temperature stability by adjusting the flow rates of the heat and cold media through the heat exchanger, thus ensuring the activity and metabolic environment of microorganisms.

[0070] The target pH range is set between 7.2 and 7.8, indicated by the orange dotted line in the graph. The pH curve fluctuates significantly, initially hovering within the 7.2-7.8 range, followed by several short-term dips below 7.0 before returning to the target range. This fluctuation trend indicates that the acid-base regulating device intermittently activates the alkali or acid dosing pump based on real-time pH sensor data to maintain the overall pH value within the target range.

[0071] Example 5: In practice, the normalized fitness value of each solution in the candidate microbial enhancement strategy set is calculated across four objectives: denitrification efficiency, phosphorus removal efficiency, carbon source consumption, and microbial community metabolic interaction balance. The candidate microbial enhancement strategy set is denoted as... ,in This represents the total number of concentrated solutions for candidate microbial enhancement strategies. Let represent the q-th candidate solution, where q is an integer from 1 to Q. For the q-th candidate solution... Its original value for denitrification efficiency is denoted as The original value of phosphorus removal efficiency is denoted as The original value of carbon source consumption is denoted as The original value of the metabolic interaction balance of the microbial community is denoted as The original values ​​of the four objectives mentioned above were all calculated using the corresponding objective functions in the multi-objective optimization model.

[0072] The raw denitrification efficiency values ​​of all solutions in the candidate microbial enhancement strategy set are normalized using a min-max method. Then, all Q candidate solutions are iterated through to find the maximum value of the raw denitrification efficiency. and minimum value ,in , .like equal Then the normalized fitness value of the denitrification efficiency of all candidate solutions is set to 1.0; if Not equal to Then the normalized fitness value of the denitrification efficiency of the q-th candidate solution The calculation method is as follows:

[0073]

[0074] in, represents the normalized fitness value of the nitrogen removal efficiency of the q-th candidate solution, which is dimensionless and ranges from [0,1]. This represents the original value of the denitrification efficiency of the q-th candidate solution; This represents the minimum original value of the denitrification efficiency of all candidate solutions in the candidate microbial enhancement strategy set; This represents the maximum original value of the denitrification efficiency of all candidate solutions in the candidate microbial enhancement strategy set.

[0075] Following the same method as for nitrogen removal efficiency normalization, the original values ​​of phosphorus removal efficiency, carbon source consumption, and microbial metabolic interaction balance were each normalized using a min-max normalization process. For phosphorus removal efficiency, the maximum value of the original phosphorus removal efficiency was identified. and minimum value The normalized fitness value of the phosphorus removal efficiency of the q-th candidate solution The calculation method is as follows: when Not equal to hour, ;when equal hour, Set to 1.0. For carbon source consumption, which is a cost-based indicator, a smaller value is better. After min-max normalization, a reverse processing is needed, i.e., when... Not equal to First calculate the intermediate value. Then convert the intermediate value into a normalized fitness value for carbon source consumption. ;when equal hour, Set to 1.0, where This represents the maximum value of the original carbon source consumption. This represents the minimum value of the original carbon source consumption. For the balance of metabolic interactions within the microbial community, when... Not equal to At that time, the normalized fitness value of the bacterial community metabolic interaction balance of the q-th candidate solution. ;when equal hour, Set to 1.0, where This represents the maximum value of the original value of the balance of metabolic interactions within the microbial community. This represents the minimum value of the original value of the bacterial community metabolic interaction balance. After completing the above calculations, each candidate solution... Corresponding to the four normalized fitness values: , , and .

[0076] The weights of denitrification efficiency, phosphorus removal efficiency, carbon source consumption, and microbial metabolic balance were determined using order relation analysis. The procedure for order relation analysis was as follows: experts in aquaculture wastewater treatment determined the importance order among the four evaluation indicators. The importance order was: denitrification efficiency was more important than phosphorus removal efficiency, phosphorus removal efficiency was more important than carbon source consumption, and carbon source consumption was more important than microbial metabolic balance. This is represented by the following symbols: ,in Indicates the nitrogen removal efficiency index. This indicates the phosphorus removal efficiency index. Indicators representing carbon source consumption. Indicators representing the balance of metabolic interactions within the microbial community, symbolized by... This indicates that the left-side indicators are significantly more important than the right-side indicators.

[0077] The importance ratio between adjacent indicators is determined by experts. Adjacent indicators and The importance ratio is denoted as , The definition of an indicator Weights and Indicators The weight ratio, where m ranges from 2, 3, to 4. This indicates the ratio of the importance of nitrogen removal efficiency to phosphorus removal efficiency. The value is set to 1.2. The basis for this setting is that the importance of nitrogen removal efficiency in the standard discharge of aquaculture wastewater is slightly higher than that of phosphorus removal efficiency, and the control requirements for total nitrogen in aquaculture wastewater discharge standards are usually more stringent. This represents the ratio of the importance of phosphorus removal efficiency to carbon source consumption. The value is set to 1.1. The basis for this setting is that phosphorus removal efficiency is slightly more important to water quality compliance than carbon source consumption. Carbon source consumption will be reduced only after phosphorus removal requirements are met. This represents the ratio of the importance of carbon source consumption to the balance of metabolic interactions within the microbial community. The value is set to 1.0. The basis for this setting is that the two indicators, carbon source consumption and microbial community metabolic interaction balance, have a similar constraining effect on strategy selection. Carbon source consumption reflects economic costs, while microbial community metabolic interaction balance reflects the basic conditions for the long-term stability of functional microbial communities.

[0078] The weight values ​​of the four indicators are calculated using the weight recursion formula of the order relation analysis method. The weight of the m-th indicator is... The calculation method is as follows: First, calculate the weight of the fourth indicator, namely the balance of microbial metabolic interactions. , Here, k and t are intermediate variables for the addition and multiplication operations, with k ranging from 2 to 4 and t ranging from k to 4. The calculation process is as follows: First calculate... , then calculate , then calculate Summing yields ,therefore Then, based on the recursive relationship... Calculate the weights of the metabolic interaction balance of the microbial community in sequence. The weight of carbon source consumption is 0.23. Weighting of phosphorus removal efficiency Weight of denitrification efficiency The four weight values ​​are normalized so that their sum is exactly 1, thus obtaining the weights for denitrification efficiency. The weight of phosphorus removal efficiency is 0.30. The weight of carbon source consumption is 0.25. The weight of the microbial community metabolic interaction balance is 0.23. It is 0.22.

[0079] The normalized fitness values ​​of each solution are weighted and summed according to the above weights to obtain the comprehensive fitness value of each solution. The comprehensive fitness value of the q-th candidate solution is... The calculation method is as follows:

[0080]

[0081] After calculating the comprehensive fitness values ​​of all Q candidate solutions in the candidate microbial enhancement strategy set, a comprehensive fitness value sequence is obtained. Find the candidate solution with the highest overall fitness value from the sequence, and use it as the strategy to be validated, denoted as... .

[0082] Strategy to be verified Constraint verification is required. The first constraint verification item is whether the sum of the addition ratios equals the preset total amount, which is set to 1. This is based on the strategy to be verified. The proportion of anaerobic ammonia oxidizing bacteria extracted and added The proportion of denitrifying polyphosphate-accumulating bacteria added aerobic denitrifying bacteria dosage ratio and the ratio of nitrifying bacteria addition Calculate the sum of the four. Determine whether the sum of the four values ​​equals 1.0, with an allowable error range of ±0.001.

[0083] The second constraint verification item is whether the carbon source addition amount does not exceed the carbon source reserve parameter. This is based on the strategy to be verified. Carbon source addition amount ,Will With carbon source reserve parameters Comparison of carbon source reserve parameters This is the product of the carbon source liquid level in the carbon source storage tank and the concentration of the effective component of the carbon source. (Judgment) Whether it is valid or not.

[0084] The third constraint verification item is whether the dissolved oxygen concentration setpoint is within the adjustable range of the aeration device. The frequency adjustment range of the variable frequency blower of the aeration device corresponds to an adjustable dissolved oxygen concentration range of 0.2 mg / L to 8.0 mg / L. From the strategy to be verified... Extract dissolved oxygen concentration set value ,judge Does it meet the requirements? .

[0085] The fourth constraint verification item is whether the pH setpoint is within the adjustable range of the acid-base regulating device. The acid-base regulating device provides a 0.5 mol / L sodium hydroxide solution as the alkali and a 0.25 mol / L hydrochloric acid solution as the acid. The combined dosing capacity of the alkali and acid dosing pumps corresponds to a pH adjustable range of 6.0 to 9.0. From the strategy to be verified... Extract pH set value ,judge Does it meet the requirements? .

[0086] The fifth constraint verification item is whether the temperature setpoint is within the adjustable range of the temperature control device. The heat transfer medium of the temperature control device is warm water, the refrigerant is cold water, and the heat exchanger's heat exchange capacity corresponds to a temperature adjustable range of 15℃ to 35℃. From the strategy to be verified... Extracting temperature setpoint ,judge Does it meet the requirements? .

[0087] If all five constraints above pass the verification, then the strategy to be verified will be... This serves as the output of the microbial enhancement strategy. If any one of the five constraint checks fails, the strategy to be checked is removed from the candidate microbial enhancement strategy set. The removal operation refers to removing the strategy to be verified. From candidate microbial enhancement strategy set After deletion, the number of remaining solutions in the candidate microbial enhancement strategy set becomes... From the remaining solutions, select the solution with the highest overall fitness value as the new strategy to be validated, and re-execute the above five constraint checks. Repeat this elimination and reselection process until a solution that passes all five constraint checks is found, and output this solution as the microbial enhancement strategy. If no solution that passes the constraint checks is found after all solutions in the candidate microbial enhancement strategy set have been eliminated, return to the multiple tabu optimization algorithm, regenerate the candidate microbial enhancement strategy set with stricter decision variable boundary constraints, and execute the overall fitness calculation and constraint check process again until a microbial enhancement strategy that meets all constraint conditions is output.

[0088] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any changes or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application.

Claims

1. A method for nitrogen and phosphorus removal from aquaculture wastewater based on microbial enhancement, characterized in that, include: Obtain water quality characteristics, carbon source reserves, and initial abundance parameters of functional microbial communities from aquaculture wastewater; Based on the water quality characteristic parameters, the carbon source reserve parameters, and the initial abundance parameters, a metabolic interaction matrix among functional microbial communities is constructed. Based on the metabolic interaction matrix, the target values ​​of addition ratio, carbon source addition amount, dissolved oxygen concentration, pH value and temperature of each functional microbial community within a specified time window are solved by using the multiple taboo optimization algorithm to obtain the microbial enhancement strategy. Microbial enhancers are added to the aquaculture wastewater according to the dosage ratio in the microbial enhancement strategy, and the dissolved oxygen concentration, pH value and temperature are adjusted synchronously according to the target values ​​to treat the aquaculture wastewater for nitrogen and phosphorus removal.

2. The method for nitrogen and phosphorus removal from aquaculture wastewater based on microbial enhancement according to claim 1, characterized in that, The acquisition of water quality characteristic parameters, carbon source reserve parameters, and initial abundance parameters of functional microbial communities in aquaculture wastewater includes: Water samples were collected from the inlet, anaerobic zone, anoxic zone, aerobic zone and outlet of the aquaculture wastewater treatment system to obtain water samples from each sampling point. The concentrations of ammonia nitrogen, nitrite nitrogen, nitrate nitrogen, total phosphorus, and chemical oxygen demand in water samples from each sampling point were measured. The measured values ​​from each sampling point were weighted and averaged according to the hydraulic retention time to obtain the water quality characteristic parameters. Read the carbon source liquid level and the concentration of effective carbon source components in the carbon source storage tank, and use the product of the carbon source liquid level and the concentration of effective carbon source components as the carbon source storage parameter; Total microbial DNA was extracted from water samples at each sampling point, and 16S rRNA gene high-throughput sequencing was performed. The initial abundance parameters of anaerobic ammonia oxidizing bacteria, denitrifying polyphosphate-accumulating bacteria, aerobic denitrifying bacteria, and nitrifying bacteria were determined based on the sequence abundance in the sequencing results.

3. The method for nitrogen and phosphorus removal from aquaculture wastewater based on microbial enhancement according to claim 1, characterized in that, The step of constructing a metabolic interaction matrix among functional microbial communities based on the water quality characteristic parameters, the carbon source reserve parameters, and the initial abundance parameters includes: The half-saturation constants, maximum specific degradation rate constants, and product inhibition constants of anaerobic ammonia oxidizing bacteria, denitrifying polyphosphate-accumulating bacteria, aerobic denitrifying bacteria, and nitrifying bacteria for ammonia nitrogen, nitrite nitrogen, nitrate nitrogen, total phosphorus, and organic carbon sources were obtained from a pre-defined microbial metabolism database. Based on the water quality characteristic parameters and the initial abundance parameters, calculate the competition coefficients of anaerobic ammonia oxidizing bacteria, denitrifying phosphorus-accumulating bacteria, aerobic denitrifying bacteria and nitrifying bacteria for the same substrate, and calculate the promotion or inhibition coefficients of the metabolites of one functional bacterial group on the growth of another functional bacterial group. The metabolic interaction matrix is ​​obtained by filling the competition coefficient, the promotion coefficient, and the inhibition coefficient into matrix elements according to the sorting order of the functional bacterial communities.

4. The method for nitrogen and phosphorus removal from aquaculture wastewater based on microbial enhancement according to claim 1, characterized in that, Based on the metabolic interaction matrix, a multi-taboo optimization algorithm is used to solve for the target values ​​of the addition ratio, carbon source addition amount, dissolved oxygen concentration, pH value, and temperature of each functional microbial community within a specified time window, thereby obtaining a microbial enhancement strategy, including: Using the addition ratio of each functional microbial community, the amount of carbon source added, the dissolved oxygen concentration, pH value and temperature as decision variables, and the denitrification efficiency, phosphorus removal efficiency, carbon source consumption and the balance of microbial community metabolic interaction as optimization objectives, a multi-objective optimization model was constructed. Based on the metabolic interaction matrix, an initial candidate solution set for the decision variables is set, and a first tabu table for recording visited solutions and a second tabu table for recording frequently searched regions are established. Multiple candidate solutions are selected from the initial candidate solution set as the current solution. A neighborhood search is performed on the current solution. During the search process, the first tabu list is used to avoid repeatedly visiting solutions that have already been searched, and the second tabu list is used to dynamically adjust the search step size. When the number of iterations reaches the preset upper limit or the optimization objective fails to improve for several consecutive times, the multiple candidate solutions obtained are sorted according to the preset evaluation function, and the candidate solutions with the highest ranking are selected as the candidate microbial enhancement strategy set. The solution with the highest overall fitness is selected from the set of candidate microbial enhancement strategies as the microbial enhancement strategy.

5. The method for nitrogen and phosphorus removal from aquaculture wastewater based on microbial enhancement according to claim 4, characterized in that, The neighborhood search of the current solution includes: For each current solution, perform a swap operation, an insertion operation, and a reversal operation to obtain multiple neighborhood solutions. The swap operation is to randomly swap the functional microbial community addition ratios of any two time windows in the current solution. The insertion operation is to move the carbon source addition value of one time window to a specified position in the carbon source addition value sequence of another time window. The reversal operation is to reverse the order of the decision variables of multiple consecutive time windows in the current solution. Calculate the difference between each neighborhood solution and the visited solutions recorded in the first tabu table, and add neighborhood solutions with a difference greater than a preset difference threshold to the candidate neighborhood solution set; Select the neighborhood solution with the highest comprehensive fitness of the optimization objective from the candidate neighborhood solution set, and add the new current solution to the first tabu list.

6. The method for nitrogen and phosphorus removal from aquaculture wastewater based on microbial enhancement according to claim 1, characterized in that, The process of denitrifying and removing phosphorus from aquaculture wastewater includes: According to the dosage ratio in the microbial enhancement strategy, the microbial enhancer is divided into multiple batches and added sequentially to the aquaculture wastewater according to the specified time window. Before each batch of addition, the current concentrations of ammonia nitrogen, nitrite nitrogen, nitrate nitrogen, and total phosphorus in the aquaculture wastewater are tested, and the carbon source addition amount for this batch is adjusted based on the difference between the current test values ​​and the preset emission limits. Within the specified time window, the dissolved oxygen concentration, pH value, and temperature are adjusted according to the target range set in the microbial enhancement strategy using an aeration device, an acid-base adjustment device, and a temperature control device. After each time window of addition and adjustment is completed, the decision variables for subsequent time windows in the microbial enhancement strategy are updated.

7. The method for nitrogen and phosphorus removal from aquaculture wastewater based on microbial enhancement according to claim 6, characterized in that, The adjustment is achieved through an aeration device, an acid-base adjustment device, and a temperature control device, including: Obtain the target ranges for dissolved oxygen, pH, and temperature for the current time window; Based on the difference between the target dissolved oxygen range and the real-time dissolved oxygen value, the frequency of the variable frequency fan of the aeration device is adjusted, and the opening of the microporous aeration disc is controlled. Based on the difference between the target pH range and the real-time pH value, alkali or acid solution is added to the aquaculture wastewater using an alkali solution addition pump or an acid solution addition pump. The heat transfer fluid flow rate or refrigerant flow rate of the heat exchanger is controlled based on the difference between the target temperature range and the real-time temperature. The adjusted dissolved oxygen, pH, and temperature values ​​are used as feedback data to correct the target range for subsequent time windows.

8. The method for nitrogen and phosphorus removal from aquaculture wastewater based on microbial enhancement according to claim 1, characterized in that, The addition of microbial enhancers to the aquaculture wastewater according to the dosage ratio in the microbial enhancement strategy includes: The microbial enhancer is distributed to the anaerobic zone addition point, the anoxic zone addition point, and the aerobic zone addition point according to the specified addition ratio; Anaerobic ammonia-oxidizing bacteria are added at the addition point in the anaerobic zone, denitrifying polyphosphate-accumulating bacteria and aerobic denitrifying bacteria are added at the addition point in the anoxic zone, and nitrifying bacteria are added at the addition point in the aerobic zone. Each dosing point performs the dosing action according to the specified time window and the corresponding dosing ratio, and controls the start and stop of the stirring device in the area where the dosing point is located after the dosing action is completed.

9. A method for nitrogen and phosphorus removal from aquaculture wastewater based on microbial enhancement according to claim 4, characterized in that, The step of selecting the solution with the highest overall fitness from the set of candidate microbial enhancement strategies as the microbial enhancement strategy includes: Calculate the normalized fitness value of each solution in the candidate microbial enhancement strategy set on four objectives: denitrification efficiency, phosphorus removal efficiency, carbon source consumption, and microbial community metabolic interaction balance. The weights of denitrification efficiency, phosphorus removal efficiency, carbon source consumption, and microbial community metabolic interaction balance were determined by order relation analysis. The normalized fitness values ​​of each solution were then weighted and summed according to the weights to obtain the comprehensive fitness value of each solution. The solution with the highest overall fitness value is selected as the strategy to be verified, and constraint verification is performed. The constraint verification includes: whether the sum of the addition ratios is equal to the preset total amount, whether the carbon source addition amount does not exceed the carbon source reserve parameter, whether the dissolved oxygen concentration setting value is within the adjustable range of the aeration device, whether the pH value setting value is within the adjustable range of the acid-base adjustment device, and whether the temperature setting value is within the adjustable range of the temperature control device. If the constraint verification passes, the strategy to be verified is adopted as the microbial enhancement strategy; if the constraint verification fails, the strategy to be verified is removed from the set of candidate microbial enhancement strategies, and the constraint verification is performed again on the solution with the highest comprehensive fitness after removal, until a solution that passes the constraint verification is obtained as the microbial enhancement strategy.

10. A method for nitrogen and phosphorus removal from aquaculture wastewater based on microbial enhancement according to claim 1, characterized in that, The multiple tabu search algorithm includes: Based on the metabolic interaction matrix, an initial candidate solution set for the decision variables is set, and a first tabu table for recording visited solutions and a second tabu table for recording frequently searched regions are established. Multiple candidate solutions are selected from the initial candidate solution set as the current solution. A neighborhood search is performed on the current solution. During the search process, the first tabu list is used to avoid repeatedly visiting solutions that have already been searched, and the second tabu list is used to dynamically adjust the search step size. When the number of iterations reaches the preset limit or the optimization objective fails to improve after multiple iterations, the search is terminated and the current optimal solution is output as the microbial enhancement strategy.

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