Construction method of modelica-based mechanism-data hybrid simulation model for municipal wastewater treatment

Abstract

The application discloses a kind of mechanism-data hybrid urban sewage treatment simulation model based on Modelica's construction method, comprising: six kinds of unit equipment models of primary sedimentation tank, nitrification tank, denitrification tank, secondary sedimentation tank, 2 flow-diverter and 2 flow-combiner are constructed;According to actual working condition, the simulation model of urban sewage treatment system is constructed, and water quality and flow are output;Determine the model mechanism parameters that need to be adjusted in the system simulation model as input;Optimization module is constructed, with simulation result and actual data deviation as evaluation index, and the optimal parameter is output;Parameter identification correction is carried out by combining calculation of the optimization module and the system simulation model, so as to construct the simulation model of urban sewage treatment system.The present application is based on Modelica modeling, which overcomes the technical problems of traditional modeling method, such as incompleteness, causality, difficulty in modification and reuse, thereby improving the accuracy and reusability of the urban sewage treatment simulation model.

Description

Technical Field

[0001] This application relates to the field of simulation modeling technology for urban wastewater treatment equipment, and in particular to a method for constructing a mechanism-data hybrid simulation model for urban wastewater treatment based on Modelica. Background Technology

[0002] Urban wastewater treatment plants play a crucial role in the urban water cycle system, treating domestic sewage and industrial wastewater to remove pollutants. These plants typically comprise complex physical, chemical, and biological treatment units, such as primary sedimentation tanks, aeration tanks, and secondary sedimentation tanks. These units work together to purify the wastewater. During wastewater treatment, the flow rate, water composition, and treatment process parameters all change over time, exhibiting high complexity and nonlinear characteristics.

[0003] With the increasing severity of global water scarcity, urban wastewater treatment has become a crucial link in ensuring the sustainable use of water resources and improving the urban environment. Therefore, technologies for predicting wastewater treatment outcomes through modeling have attracted significant attention. The complexity and nonlinear characteristics of urban wastewater systems make modeling an extremely challenging task. Traditional wastewater treatment mechanism models often suffer from problems such as difficulty in accurately estimating parameters, limited model accuracy, and an inability to fully reflect the dynamic changes in actual wastewater treatment processes. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this application provides a method for constructing a mechanism-data hybrid urban wastewater treatment simulation model based on Modelica.

[0005] According to a first aspect of the embodiments of this application, a method for constructing a mechanism-data hybrid simulation model for urban wastewater treatment based on Modelica is provided, comprising:

[0006] Based on the sedimentation principle in primary treatment of urban sewage, a primary sedimentation tank model is constructed using Modelica, and the inputs and outputs are determined. The primary sedimentation tank model is used to calculate the water quality of the primary sedimentation effluent from urban sewage treatment.

[0007] Based on the nitrification reaction mechanism of biological denitrification process, a nitrification tank model is constructed based on Modelica, and the input and output are determined. The nitrification tank model is used to calculate the effluent quality of nitrification reaction in urban wastewater treatment.

[0008] Based on the denitrification biological reaction mechanism under anoxic conditions, a denitrification tank model was constructed using Modelica, and the inputs and outputs were determined. The denitrification tank model was used to calculate the effluent quality of denitrification reaction in urban wastewater treatment.

[0009] Based on the one-dimensional flux model theory of secondary sedimentation tanks, a secondary sedimentation tank model is constructed using Modelica, and the inputs and outputs are determined. The secondary sedimentation tank model is used to calculate the water quality of secondary sedimentation effluent from urban wastewater treatment.

[0010] Based on the law of conservation of mass, a 2-flow-splitter model is constructed using Modelica, and the input and output are determined. This 2-flow-splitter model is used to calculate the flow rate of the splitter in urban wastewater treatment.

[0011] Based on the law of conservation of mass, a two-flow-combiner model is constructed using Modelica, and the input and output are determined. The two-flow-combiner model is used to calculate the flow rate of the combined flowmeter in urban sewage treatment.

[0012] Based on the physical topology, actual operating process and conditions of urban wastewater treatment, the primary sedimentation tank model, nitrification tank model, denitrification tank model, secondary sedimentation tank model, 2-flow-divider model and 2-flow-merge model are called to construct a simulation model of the urban wastewater treatment system;

[0013] Based on the working principle of urban sewage treatment, the model mechanism parameters that need to be adjusted in the simulation model of urban sewage treatment system are determined based on the actual operating conditions. The input of the simulation model of urban sewage treatment system is the model mechanism parameters, and the output is the treated water quality parameters and flow rate.

[0014] Based on the working principle of the optimization algorithm, an optimization module is constructed using the MATLAB optimization toolbox. The deviation between the output of the urban sewage treatment system simulation model and the actual sewage treatment plant data is used as the evaluation index. The input of the optimization module is the model mechanism parameters, and the output is the minimum value of the evaluation index and the corresponding model mechanism parameters.

[0015] The optimization module and the urban sewage treatment system simulation model are combined for calculation to identify and correct the mechanism parameters of the sewage treatment system simulation model, and an actual urban sewage treatment system simulation model is constructed based on the actual operating conditions.

[0016] According to a second aspect of the embodiments of this application, an apparatus for constructing a mechanism-data hybrid simulation model of urban wastewater treatment based on Modelica is provided, comprising:

[0017] The first construction determination module is used to construct a nitrification tank model based on Modelica according to the sedimentation principle in the primary treatment of urban sewage, and to determine the input and output. The nitrification tank model is used to calculate the effluent quality of the nitrification reaction in urban sewage treatment.

[0018] The second construction determination module is used to construct a nitrification tank model based on Modelica according to the nitrification reaction mechanism of the biological denitrification process, and to determine the input and output. The nitrification tank model is used to calculate the effluent quality of the nitrification reaction in urban wastewater treatment.

[0019] The third construction determination module is used to construct a denitrification tank model based on Modelica according to the denitrification biological reaction mechanism under anoxic conditions, and to determine the input and output. The denitrification tank model is used to calculate the effluent quality of the denitrification reaction in urban sewage treatment.

[0020] The fourth module is used to construct a secondary sedimentation tank model based on Modelica according to the one-dimensional flux model theory of the secondary sedimentation tank, and to determine the input and output. The secondary sedimentation tank model is used to calculate the water quality of the secondary sedimentation effluent from urban sewage treatment.

[0021] The fifth construction and determination module is used to construct a 2-flow-splitter model based on Modelica according to the law of conservation of mass, and to determine the input and output. The 2-flow-splitter model is used to calculate the flow rate of the splitter in urban sewage treatment.

[0022] The sixth module is used to construct a two-flow-merging-confluencer model based on Modelica according to the law of conservation of mass, and to determine the input and output. The two-flow-merging-confluencer model is used to calculate the flow rate of the merged flow in urban sewage treatment.

[0023] The seventh module is used to construct a simulation model of the urban wastewater treatment system by calling the primary sedimentation tank model, nitrification tank model, denitrification tank model, secondary sedimentation tank model, two-flow-divider model and two-flow-merge model, based on the physical topology, actual operating process and operating conditions of the urban wastewater treatment system.

[0024] The eighth module is used to determine the model mechanism parameters that need to be adjusted in the simulation model of the urban sewage treatment system based on the working principle of urban sewage treatment and the actual operating conditions. The input of the simulation model of the urban sewage treatment system is the model mechanism parameters, and the output is the treated water quality parameters and flow rate.

[0025] The ninth module is a determination module, which is used to construct an optimization module based on the working principle of the optimization algorithm and the MATLAB optimization toolbox. The deviation between the output results of the urban sewage treatment system simulation model and the actual sewage treatment plant data is used as the evaluation index. The input of the optimization module is the model mechanism parameters, and the output is the minimum value of the evaluation index and the corresponding model mechanism parameters.

[0026] The construction module is used to combine the optimization module and the urban sewage treatment system simulation model for calculation, identify and correct the model mechanism parameters, and construct an actual urban sewage treatment system simulation model based on actual operating conditions.

[0027] According to a third aspect of the embodiments of this application, an electronic device is provided, comprising:

[0028] One or more processors;

[0029] Memory, used to store one or more programs;

[0030] When the one or more programs are executed by the one or more processors, the one or more processors perform the method as described in the first aspect.

[0031] The technical solutions provided by the embodiments of this application may include the following beneficial effects:

[0032] As can be seen from the above embodiments, this application constructs primary sedimentation tank models, nitrification tank models, denitrification tank models, secondary sedimentation tank models, two-flow-divider models, and two-flow-merge models based on Modelica according to the working principles of each unit device, and determines the inputs and outputs of the models; according to the physical topology, actual operating process, and operating conditions of urban wastewater treatment, the primary sedimentation tank model, nitrification tank model, denitrification tank model, secondary sedimentation tank model, two-flow-divider model, and two-flow-merge model are called, and inlet and outlet parameters are set to construct a simulation model of the urban wastewater treatment system; according to the working principles of urban wastewater treatment, the simulation model of the urban wastewater treatment system that needs to be adjusted is determined based on the actual operating conditions. The model mechanism parameters are used as inputs to the urban wastewater treatment system simulation model, and the outputs are treated water quality parameters and flow rate. Based on the working principle of the optimization algorithm, an optimization module is constructed using the MATLAB optimization toolbox. The deviation between the output of the urban wastewater treatment system simulation model and the actual wastewater treatment plant data is used as the evaluation index. The optimization module's input is the model mechanism parameters, and its output is the minimum value of the evaluation index and the corresponding model mechanism parameters. The optimization module and the urban wastewater treatment system simulation model are combined for calculation to identify and correct the model mechanism parameters, optimizing the urban wastewater treatment system simulation model according to actual operating conditions. Modelica-based modeling overcomes the technical problems of traditional modeling methods, such as incompleteness, lack of consideration for causality, and difficulty in modification and reuse, thereby improving the accuracy and reusability of the urban wastewater treatment system simulation model. Applying Modelica to the modeling and simulation of urban wastewater treatment systems, combined with the MATLAB-based optimization module, allows for convenient analysis of the comprehensive performance of urban wastewater treatment systems, shortening the development cycle and reducing development costs.

[0033] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description

[0034] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0035] Figure 1 This is a flowchart illustrating a method for constructing a mechanism-data hybrid urban wastewater treatment simulation model based on Modelica, according to an exemplary embodiment.

[0036] Figure 2 This is a schematic diagram of a simulation model of urban wastewater treatment according to an exemplary embodiment.

[0037] Figure 3 This is a schematic diagram of an optimization module according to an exemplary embodiment.

[0038] Figure 4 This is a block diagram illustrating an apparatus for constructing a mechanism-data hybrid urban wastewater treatment simulation model based on Modelica, according to an exemplary embodiment. Detailed Implementation

[0039] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0040] The terminology used in this application is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The singular forms “a,” “the,” and “the” used in this application and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise. It should also be understood that the term “and / or” as used herein refers to and includes any or all possible combinations of one or more of the associated listed items.

[0041] It should be understood that although the terms first, second, third, etc., may be used in this application to describe various information, such information should not be limited to these terms. These terms are only used to distinguish information of the same type from one another. For example, without departing from the scope of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the word "if" as used herein may be interpreted as "when," "when," or "in response to determination."

[0042] Figure 1 This is a flowchart illustrating a method for constructing a mechanism-data hybrid simulation model of urban wastewater treatment based on Modelica, according to an exemplary embodiment. Figure 1 As shown, this method, when applied to a terminal, may include the following steps:

[0043] In the specific implementation of S1: Based on the sedimentation principle in primary treatment of urban wastewater, a primary sedimentation tank model is constructed using Modelica, and the inputs and outputs are determined. This primary sedimentation tank model is used to calculate the water quality of the primary sedimentation effluent from urban wastewater treatment. This step may include the following sub-steps:

[0044] S11: Based on the size of the primary sedimentation tank and the influent flow rate, obtain the hydraulic retention time of the primary sedimentation tank;

[0045] Specifically, the hydraulic retention time of the primary sedimentation tank is obtained based on the dimensions and influent flow rate of the primary sedimentation tank provided by the manufacturer, as well as the hydraulic retention time calculation formula.

[0046]

[0047] In the formula, The hydraulic retention time of the primary sedimentation tank under different operating conditions is expressed in hours. This refers to the volume of the primary sedimentation tank, in cubic meters. The influent flow rate to the primary sedimentation tank is expressed in cubic meters per day.

[0048] S12: Based on the hydraulic retention time in the primary sedimentation tank, the known total chemical oxygen demand (COD), and the known non-dissolved COD, obtain the removal ratio of water components at different hydraulic retention times;

[0049] Specifically, based on the calculated hydraulic retention time and dynamic model of the primary sedimentation tank, the chemical oxygen demand (COD) removal rate can be obtained. Based on the calculated COD removal rate, combined with the known total COD and the known non-dissolved COD, the removal ratio of water components at different hydraulic retention times can be obtained.

[0050]

[0051]

[0052] In the formula, Chemical oxygen demand (COD) removal rate The hydraulic residence time calculated in step S11. The proportion of water components removed. Total chemical oxygen demand, This refers to non-soluble chemical oxygen demand.

[0053] S13: Based on the removal ratio of water components at different hydraulic retention times in the primary sedimentation tank and the law of conservation of mass, obtain the water quality components, sludge components, and effluent flow rate of the primary sedimentation tank effluent.

[0054] Specifically,

[0055]

[0056]

[0057]

[0058] In the formula: This represents the concentration of a certain soluble component when it enters the primary sedimentation tank. This represents the concentration of a certain dissolved component when it flows out of the primary sedimentation tank. The calculated removal ratio of water quality components, This represents the concentration of a certain particulate component when it enters the primary sedimentation tank. The concentration of a certain particulate component when it flows out of the primary sedimentation tank from the outlet. This refers to the concentration of a certain particulate component when it flows out of the primary sedimentation tank from the sludge discharge outlet. This represents the volume of the primary sedimentation tank. This refers to the influent flow rate of the primary sedimentation tank. The flow rate at the outlet of the primary sedimentation tank. This refers to the sludge discharge flow rate at the primary sedimentation tank outlet.

[0059] S14: Based on the physical topology and functional relationships in the model, determine the input and output. The input of the primary sedimentation tank model is the influent water quality parameters, influent flow rate and effluent sludge flow rate of the primary sedimentation tank, and the output is the effluent water quality components, effluent sludge components and effluent flow rate of the primary sedimentation tank.

[0060] The primary sedimentation tank model is constructed by the above steps. The primary sedimentation tank model is used to calculate the water quality of the primary sedimentation effluent from urban sewage treatment. It can describe the sedimentation characteristic curves of primary sewage treatment under different working scenarios, thereby increasing the ease of use and versatility of the primary sedimentation tank model.

[0061] In the specific implementation of S2: Based on the nitrification reaction mechanism of the biological nitrogen removal process, a nitrification tank model is constructed using Modelica, and the inputs and outputs are determined. This nitrification tank model is used to calculate the effluent quality of the nitrification reaction in urban wastewater treatment. This step may include the following sub-steps:

[0062] S21: Based on the activated sludge model No. 2d, obtain the functional relationship between the biological phosphorus removal and biological nitrogen removal reactions in the nitrification tank;

[0063] Specifically, the Activated Sludge Model 2d (ASM2d) uses a matrix format to describe the changing patterns and interrelationships of various components in the nitrification reaction of the activated sludge system. Row numbers are represented by 'j', and column numbers by 'i'. This matrix format can describe the impact of all possible transformation processes on all components and the apparent transformation rates of each component. Based on the information provided in the table, the formula for calculating the reaction rate of a certain component is:

[0064]

[0065] In the formula: Let i be the stoichiometric coefficient of column i and row j; Let i be the reaction rate of the i-th row.

[0066] S22: Based on the law of conservation of mass and the functional relationship between the biological phosphorus removal and biological nitrogen removal reactions of the nitrification reaction, obtain the relationship between the inlet flow rate and water quality components of the nitrification tank and the outlet flow rate and water quality components of the nitrification tank;

[0067] Specifically, the basic relationship for the overall mass balance of a given system is: Inflow - Outflow + Reaction = Accumulation. Inside the nitrification tank, the actual effluent flow rate equals the inflow flow rate, and the effluent concentration equals the concentration in the denitrification tank. The calculation formulas for soluble and particulate components are as follows:

[0068]

[0069]

[0070] In the formula: This represents the concentration of a soluble component when it enters the nitrification tank. This represents the concentration of a soluble component as it flows out of the nitrification tank. This represents the concentration of a certain particulate component when it enters the nitrification tank. This represents the concentration of a certain particulate component when it flows out of the nitrification tank. The reaction rate of a certain component, The volume of the nitrification tank. This refers to the influent flow rate of the nitrification tank. This refers to the flow rate at the outlet of the nitrification tank.

[0071] S23: Based on the physical topology and functional relationships in the model, determine the input and output. The input of the nitrification tank is the inlet flow rate and water quality components, and the output is the nitrification tank outlet flow rate and water quality components.

[0072] The above steps construct a nitrification tank model, which is used to calculate the effluent quality of the denitrification tank in urban wastewater treatment. It can describe the nitrification reaction mechanism and water quality change characteristic curves of the biological denitrification process under different working scenarios, thereby increasing the ease of use and versatility of the nitrification tank model.

[0073] In the specific implementation of S3: Based on the denitrification biological reaction mechanism under anoxic conditions, a denitrification tank model is constructed using Modelica, and the inputs and outputs are determined. This denitrification tank model is used to calculate the effluent quality of denitrification reaction water from urban wastewater treatment. This step may include the following sub-steps:

[0074] S31: Based on the activated sludge model 2d, obtain the functional relationship between biological phosphorus removal and biological nitrogen removal reactions in the denitrification tank;

[0075] Specifically, the Activated Sludge Model 2d (ASM2d) uses a matrix format to describe the changing patterns and interrelationships of various components in the denitrification reaction of the activated sludge system. Row numbers are represented by 'j', and column numbers by 'i'. This matrix format can describe the impact of all possible transformation processes on all components and the apparent transformation rates of each component. Based on the information provided in the table, the formula for calculating the reaction rate of a certain component is:

[0076]

[0077] In the formula: Let i be the stoichiometric coefficient of column i and row j; Let i be the reaction rate of the i-th row.

[0078] S32: Based on the law of conservation of mass and the functional relationship between the biological phosphorus removal and biological nitrogen removal reactions in the denitrification reaction, obtain the relationship between the inlet flow rate and water quality composition of the denitrification tank and the outlet flow rate and water quality composition of the denitrification tank;

[0079] Specifically, the basic relationship for the total mass balance of a given system is: Inflow - Outflow + Reaction = Accumulation. The inflow and outflow terms are transport terms determined by the physical characteristics of the simulated system. Inside the denitrification tank, the actual effluent flow rate equals the inflow flow rate, and the effluent concentration equals the concentration in the denitrification tank. The calculation formulas for dissolved and particulate components are as follows:

[0080]

[0081]

[0082] In the formula: This represents the concentration of a soluble component when it enters the denitrification tank. This represents the concentration of a soluble component as it exits the denitrification tank. This represents the concentration of a certain particulate component when it enters the denitrification tank. This represents the concentration of a certain particulate component when it exits the denitrification tank. The reaction rate of a certain component, The volume of the denitrification tank. This refers to the influent flow rate of the denitrification tank. This refers to the flow rate at the outlet of the denitrification tank.

[0083] S33: Based on the physical topology and the functional relationships described in the model, determine the input and output. The input of the denitrification tank is the inlet flow rate and water quality components of the denitrification tank, and the output is the outlet flow rate and water quality components of the denitrification tank.

[0084] The above steps construct a denitrification tank model, which is used to calculate the effluent quality of denitrification tanks in urban wastewater treatment. It can describe the denitrification biological reaction mechanism and water quality change characteristic curves under anoxic conditions in different working scenarios, thereby increasing the ease of use and versatility of the denitrification tank model.

[0085] In the specific implementation of S4: Based on the one-dimensional flux model theory of secondary sedimentation tanks, a secondary sedimentation tank model is constructed using Modelica, and the inputs and outputs are determined. This secondary sedimentation tank model is used to calculate the water quality of the secondary sedimentation effluent from urban wastewater treatment. This step may include the following sub-steps:

[0086] S41: According to the one-dimensional flux model theory of the secondary sedimentation tank, the secondary sedimentation tank is divided into five layers: top layer, clarification layer, influent layer, concentration layer and bottom layer. The substances entering and leaving each layer will constitute the material balance of each layer.

[0087] Specifically, in the secondary sedimentation tank, the total sludge flux... From expansion flux and settling flux It consists of two parts. V is the vertical expansion velocity. X is the sludge settling rate, and X is the sludge concentration.

[0088]

[0089] According to the law of conservation of mass: cumulative amount = inflow - outflow + reaction amount, inside the reactor, the actual effluent flow rate equals the inflow flow rate, and the effluent concentration equals the concentration in the reactor. Taking the influent layer as an example, the formulas for calculating the dissolved component and sludge concentration in the stratified model are as follows:

[0090]

[0091]

[0092] In the formula: The concentration of a soluble component when it enters the reactor. The concentration of a certain soluble component when it flows out of the reactor. This refers to the concentration of sludge when it enters the reactor. The concentration of sludge when it flows out of the reactor. The cross-sectional area of ​​the inlet layer. For the height of the inlet layer, This is the reactor inlet water flow rate. This refers to the effluent flow rate from the secondary sedimentation tank. This refers to the sludge flow rate from the reactor. This refers to the sludge return flow rate.

[0093] S42: Based on the Takacs double exponential settling velocity model, the dynamic influent and steady-state settling process of the secondary settling tank is simulated using first-order partial differential equations, and the settling velocity of particulate components in different layers of the secondary settling tank is calculated.

[0094] Specifically, the settling velocity of the particulate components in the secondary sedimentation tank was calculated based on the Takacs double-exponential settling velocity model, as shown below:

[0095]

[0096] In the formula Settling velocity of solid particles in layer j That is the maximum settlement velocity. It is the sedimentation constant of the interference settling zone. It is the sedimentation constant of the flocculation and settling zone. It is the concentration of suspended solids in the j-th layer. It is the minimum achievable suspended solids concentration. It is the proportion of the non-settling part. It is the concentration of suspended solids flowing in.

[0097] S43: Based on the law of conservation of mass, obtain the dissolved components of water and sludge flux in different layers of the secondary sedimentation tank;

[0098] Specifically, according to the law of conservation of mass: cumulative amount = inflow - outflow + reaction amount, inside the reactor, the actual effluent flow rate equals the inflow flow rate, and the effluent concentration equals the concentration in the reactor. Taking the influent layer as an example, the calculation formulas for dissolved components and sludge concentration in the stratified model are as follows:

[0099]

[0100]

[0101] In the formula: This represents the concentration of a soluble component when it enters the secondary sedimentation tank. The concentration of a certain soluble component when it flows out of the secondary settling tank. This refers to the concentration of sludge when it enters the secondary sedimentation tank. This refers to the concentration of sludge when it flows out of the secondary settling tank. The cross-sectional area of ​​the inlet layer. For the height of the inlet layer, This refers to the influent flow rate of the secondary sedimentation tank. This refers to the effluent flow rate from the secondary sedimentation tank. This refers to the sludge discharge flow rate from the secondary sedimentation tank. This refers to the sludge return flow rate in the secondary sedimentation tank.

[0102] S44: Based on the physical topology and functional relationships in the model, determine the input and output. The input of the secondary sedimentation tank model is the inlet flow rate and water quality components of the secondary sedimentation tank, and the output is the outlet flow rate and water quality components of the secondary sedimentation tank.

[0103] The above steps construct a secondary sedimentation tank model, which is used to calculate the effluent quality of the secondary sedimentation tank in urban sewage treatment. It can describe the sedimentation mechanism and water quality change characteristic curves of the secondary sedimentation tank under different working scenarios, thereby increasing the ease of use and versatility of the secondary sedimentation tank model.

[0104] In the specific implementation of S5: Based on the law of conservation of mass, a 2-flow-splitter model is constructed using Modelica, and the inputs and outputs are determined. This 2-flow-splitter model is used to calculate the flow rate of the splitter in urban wastewater treatment. This step may include the following sub-steps:

[0105] S51: Based on the design parameters and the law of conservation of mass provided by the manufacturer, obtain the relationship between the flow rate at outlet 1 and the flow rate at outlet 2 of the 2-flow splitter;

[0106] Specifically, assuming the working fluid in the model is a single phase, and backflow is not allowed, the single fluid stream is instantaneously and uniformly split within the separation model. The component changes within the splitter follow the law of conservation of mass, and the concentration of dissolved components in the effluent from the splitter is equal to the concentration in the reactor. Therefore, the calculation formulas for the dissolved and particulate components at the effluent outlet are as follows:

[0107]

[0108]

[0109] In the formula: The concentration of a soluble component when it enters the two-stream splitter. The concentration of a certain soluble component when it flows out of the 2-stream splitter outlet 1. The concentration of a certain soluble component when it flows out of the outlet 2 of the splitter. The concentration of sludge entering the two-stream splitter. The concentration of sludge at the outlet of the sludge diverter (flow 2 - outlet 1) is [value missing]. The concentration of sludge at outlet 2 of the diverter. The inlet flow rate of the 2-flow splitter For a 2-flow splitter outlet flow rate of 1, The flow rate at the outlet of the 2-flow splitter is 2.

[0110] S52: Based on the physical topology and functional relationships in the model, determine the input and output. The input of the 2-flow-splitter model is the inlet flow rate and water quality components of the 2-flow-splitter, and the output is the outlet flow rate of the 2-flow-splitter, the water quality components of outlet 1, the flow rate of outlet 2, and the water quality components of outlet 2.

[0111] The above steps construct a 2-flow-diverter model, which is used to calculate the effluent flow rate and water quality of the 2-flow-diverter in urban sewage treatment. It can describe the diversion principle and flow rate change characteristic curve of the 2-flow-diverter under different working scenarios, thereby increasing the ease of use and versatility of the 2-flow-diverter model.

[0112] In the specific implementation of S6: Based on the law of conservation of mass, a two-flow-combiner model is constructed using Modelica, and the inputs and outputs are determined. This two-flow-combiner model is used to calculate the flow rate of the combined sewer in urban wastewater treatment. This step may include the following sub-steps:

[0113] S61: Obtain the outlet flow rate of the 2-flow-merge converter based on the design parameters and the law of conservation of mass provided by the manufacturer;

[0114] Specifically, assuming the model uses a single-phase working fluid, backflow is not allowed, and the single fluid stream is instantaneously and uniformly mixed within the mixing model. The compositional changes within the confluence tank follow the law of conservation of mass; the concentration of dissolved components in the effluent from the confluence tank is equal to the concentration in the reactor. Therefore, the calculation formulas for the dissolved and particulate components at the effluent outlet are as follows:

[0115]

[0116]

[0117] In the formula: Let be the concentration of a certain soluble component when it enters inlet 1 of the 2-flow-merge converter. Let be the concentration of a certain soluble component when it enters inlet 2 of the 2-flow-merge converter. The concentration of a certain soluble component when it exits the two-stream-merging device. The concentration of sludge entering inlet 1 of the 2-flow-combiner. The concentration of sludge entering inlet 2 of the two-flow-combiner. The concentration of sludge when it flows out of the two-stream-merging unit. The inlet flow rate of the 2-flow-merge inlet 1 is... The inlet flow rate of the 2-flow-merge inlet is 2. For the flow rate of the 2-flow-combiner.

[0118] S62: Based on the physical topology and functional relationships in the model, determine the input and output. The input of the 2-flow-merging model is the flow rate of 1 inlet of the 2-flow-merging, the water quality components of 1 inlet, the flow rate of 2 inlet, and the water quality components of 2 inlet. The output is the flow rate and water quality components of the 2-flow-merging outlet.

[0119] The above steps construct a two-flow-combiner model, which is used to calculate the effluent flow rate and water quality of the two-flow-combiner in urban sewage treatment. It can describe the mixing principle and flow rate change characteristic curve of the two-flow-combiner under different working scenarios, thereby increasing the ease of use and versatility of the two-flow-combiner model.

[0120] In the specific implementation of S7: Based on the physical topology, actual operating process, and working conditions of urban wastewater treatment, a simulation model of the urban wastewater treatment system is constructed by calling upon the primary sedimentation tank model, nitrification tank model, denitrification tank model, secondary sedimentation tank model, two-flow-divider model, and two-flow-merge model. This step may include the following sub-steps:

[0121] S71: Based on the physical topology and actual operation process of urban sewage treatment, determine the number of each equipment model included in the sewage treatment plant system simulation model and the direction of internal and external backflow, and construct the urban sewage treatment system simulation model.

[0122] Specifically, Figure 2 This is a schematic diagram of a simulation model for urban wastewater treatment, illustrating the actual operation of the process. As shown in the diagram, the wastewater treatment process includes one primary sedimentation tank model, one nitrification tank model, one denitrification tank model, two secondary sedimentation tank models, three two-flow splitters, and two two-flow mergers. The simulation model also includes an external return flow from the secondary sedimentation tank to the nitrification tank. Based on this information, the simulation model of the urban wastewater treatment system is constructed by calling upon the primary sedimentation tank model, nitrification tank model, denitrification tank model, secondary sedimentation tank model, two-flow splitter model, and two-flow merger model.

[0123] S72: Based on the operating conditions of urban sewage treatment, determine the process operation parameters in the simulation model of the sewage treatment plant system, including raw wastewater quality parameters and flow rate, dimensions of each unit equipment and inlet / outlet flow rate, aeration rate, internal and external reflux rates, and may also include ambient temperature and atmospheric pressure.

[0124] Specifically, the process operating parameters in the wastewater treatment plant system simulation model, such as the raw wastewater quality parameters and flow rate, the dimensions of each unit equipment and the inlet and outlet flow rates, aeration volume, internal return rate, and external return rate, have a significant impact on the wastewater treatment effect. Inputting specific values ​​provided by the actual wastewater treatment plant into the wastewater treatment system simulation model can help improve the accuracy of the model simulation results. Changes in ambient temperature and atmospheric pressure can affect the growth, reproduction, and decline of microorganisms in the activated sludge process of wastewater treatment, thereby affecting the wastewater treatment results.

[0125] The above steps are used to construct a simulation model of the urban sewage treatment system. This simulation model is used to calculate the effluent results of the actual urban sewage treatment system and can describe the effluent characteristic curves of the urban sewage treatment system under different operating conditions.

[0126] In the specific implementation of S8: Based on the working principle of urban wastewater treatment, the model mechanism parameters that need to be adjusted in the simulation model of the urban wastewater treatment system are determined based on the actual operating conditions. The input of the urban wastewater treatment system simulation model is the model mechanism parameters, and the output is the treated water quality parameters and flow rate. This step may include the following sub-steps:

[0127] S81: Based on the working principle and actual operating conditions of urban sewage treatment, determine the maximum growth rate of heterotrophic bacteria based on the substrate, the lysis rate constant of heterotrophic bacteria, and the oxygen saturation / inhibition coefficient of heterotrophic bacteria as the model mechanism parameters that need to be adjusted in the simulation model of urban sewage treatment system. These parameters may also include the maximum growth rate of nitrifying bacteria, the decay rate of nitrifying bacteria, the maximum growth rate of polyphosphate-accumulating bacteria, and the lysis rate constant of polyphosphate-accumulating bacteria.

[0128] Specifically, the aforementioned model mechanism parameters are all kinetic parameters from the activated sludge model No. 2d. This model includes various kinetic parameters related to hydrolysis, heterotrophic bacteria, polyphosphate-accumulating bacteria, nitrifying bacteria, and sedimentation, as well as their typical values ​​at 10℃ and 20℃. However, because the actual reaction environment is more complex than typical conditions, these mechanism parameters may change. Therefore, sensitivity analysis is needed to determine the model mechanism parameters that need to be adjusted in the urban wastewater treatment system simulation model.

[0129] In the specific implementation of S9: Based on the working principle of the optimization algorithm, an optimization module is constructed using the MATLAB optimization toolbox. The deviation between the output of the urban wastewater treatment system simulation model and the actual wastewater treatment plant data is used as the evaluation index. The input of the optimization module is the model mechanism parameters, and the output is the minimum value of the evaluation index and the corresponding model mechanism parameters. The optimization module is used for data-driven calculations of the urban wastewater treatment system simulation model. This step may include the following sub-steps:

[0130] S91: Based on the working principle of urban sewage treatment and the aforementioned evaluation indicators, this problem is determined to be a multi-objective optimization problem;

[0131] Specifically, based on the working principle of urban wastewater treatment, the deviation between the output results of chemical oxygen demand (COD), total nitrogen (TNO), and total phosphorus (TP) of the simulation model of the urban wastewater treatment system and the actual output data of COD, TNO, and TP of the wastewater treatment plant is determined as the evaluation index. Therefore, this problem is a multi-objective optimization problem with three objectives.

[0132] S92: Based on the MATLAB Optimization Toolbox, a multi-objective genetic algorithm is selected to construct an optimization module for data-driven calculation of the urban sewage treatment system simulation model. The objective of the optimization module is to find the minimum value of the evaluation index.

[0133] Specifically, based on the MATLAB Optimization Toolbox, a multi-objective genetic algorithm is selected to construct an optimization module. The model mechanism parameters are set as inputs, and the minimum value of the evaluation index and the corresponding model mechanism parameters are set as the outputs of the optimization module, thus completing the optimization module setup.

[0134] The optimization module is constructed by the above steps. The optimization module is used for data-driven calculation of urban sewage treatment system simulation models under different scenarios, thereby increasing the usability and versatility of the optimization module.

[0135] In the specific implementation of S10: the optimization module and the urban sewage treatment system simulation model are combined for calculation, the model mechanism parameters are identified and corrected, and the actual urban sewage treatment system model is optimized according to the actual operating conditions.

[0136] Specifically, such as Figure 3 As shown, the optimization module and the urban sewage treatment system simulation model are combined for calculation. The optimal value of the fitness function of the optimization module is calculated based on the output result of the urban sewage treatment system simulation model. The optimization module will output the model mechanism parameters under the condition of the minimum value of the evaluation index, that is, the parameter identification and correction of the mechanism parameters of the sewage treatment system simulation model is completed.

[0137] As can be seen from the above embodiments, this application constructs primary sedimentation tank models, nitrification tank models, denitrification tank models, secondary sedimentation tank models, two-flow-divider models, and two-flow-merge models based on Modelica according to the working principles of each unit device, and determines the inputs and outputs of the models; according to the physical topology, actual operating process, and operating conditions of urban wastewater treatment, the primary sedimentation tank model, nitrification tank model, denitrification tank model, secondary sedimentation tank model, two-flow-divider model, and two-flow-merge model are called, and inlet and outlet parameters are set to construct a simulation model of the urban wastewater treatment system; according to the working principles of urban wastewater treatment, the simulation model of the urban wastewater treatment system that needs to be adjusted is determined based on the actual operating conditions. The model mechanism parameters are used as inputs to the urban wastewater treatment system simulation model, and the outputs are treated water quality parameters and flow rate. Based on the working principle of the optimization algorithm, an optimization module is constructed using the MATLAB optimization toolbox. The deviation between the output of the urban wastewater treatment system simulation model and the actual wastewater treatment plant data is used as the evaluation index. The optimization module's input is the model mechanism parameters, and its output is the minimum value of the evaluation index and the corresponding model mechanism parameters. The optimization module and the urban wastewater treatment system simulation model are combined for calculation to identify and correct the model mechanism parameters, optimizing the urban wastewater treatment system simulation model according to actual operating conditions. Modelica-based modeling overcomes the technical problems of traditional modeling methods, such as incompleteness, lack of consideration for causality, and difficulty in modification and reuse, thereby improving the accuracy and reusability of the urban wastewater treatment system simulation model. Applying Modelica to the modeling and simulation of urban wastewater treatment systems, combined with the MATLAB-based optimization module, allows for convenient analysis of the comprehensive performance of urban wastewater treatment systems, shortening the development cycle and reducing development costs.

[0138] Corresponding to the aforementioned embodiments of the method for constructing a mechanism-data hybrid urban wastewater simulation model based on Modelica, this application also provides embodiments of an apparatus for constructing a mechanism-data hybrid urban wastewater simulation model based on Modelica.

[0139] Figure 4 This is a block diagram illustrating a mechanism-data hybrid urban wastewater simulation model based on Modelica, according to an exemplary embodiment. (Refer to...) Figure 4 The device includes:

[0140] The first construction determination module 1 is used to construct a nitrification tank model based on Modelica according to the sedimentation principle in the primary treatment of urban sewage, and to determine the input and output. The nitrification tank model is used to calculate the nitrification reaction effluent of urban sewage treatment.

[0141] The second construction determination module 2 is used to construct a nitrification tank model based on Modelica according to the nitrification reaction mechanism of the biological denitrification process, and to determine the input and output. The nitrification tank model is used to calculate the nitrification reaction effluent of urban sewage treatment.

[0142] The third construction and determination module 3 is used to construct a denitrification tank model based on Modelica according to the denitrification biological reaction mechanism under anoxic conditions, and to determine the input and output. The denitrification tank model is used to calculate the denitrification reaction effluent of urban sewage treatment.

[0143] The fourth construction and determination module 4 is used to construct a secondary sedimentation tank model based on Modelica according to the one-dimensional flux model theory of the secondary sedimentation tank, and to determine the input and output. The secondary sedimentation tank model is used to calculate the secondary sedimentation effluent of urban sewage treatment.

[0144] The fifth construction and determination module 5 is used to construct a 2-flow-splitter model based on Modelica according to the law of conservation of mass, and to determine the input and output. The 2-flow-splitter model is used to calculate the flow rate of the splitter in urban sewage treatment.

[0145] The sixth module 6 is used to construct a 2-flow-merging-confluencer model based on Modelica according to the law of conservation of mass, and to determine the input and output. The 2-flow-merging-confluencer model is used to calculate the flow rate of the merged flow in urban sewage treatment.

[0146] The seventh module 7 is used to construct a simulation model of the urban wastewater treatment system by calling the primary sedimentation tank model, nitrification tank model, denitrification tank model, secondary sedimentation tank model, two-flow-divider model and two-flow-merge model according to the physical topology, actual operation process and working conditions of urban wastewater treatment.

[0147] The eighth construction and determination module 8 is used to determine the model mechanism parameters that need to be adjusted in the simulation model of the urban sewage treatment system based on the working principle of urban sewage treatment and the actual operating conditions. The input of the simulation model of the urban sewage treatment system is the model mechanism parameters, and the output is the treated water quality parameters and flow rate.

[0148] The ninth module 9 is used to construct an optimization module based on the working principle of the optimization algorithm and the MATLAB optimization toolbox. The deviation between the output of the simulation model of the urban sewage treatment system and the actual sewage treatment plant data is used as the evaluation index. The input of the optimization module is the model mechanism parameters, and the output is the minimum value of the evaluation index and the corresponding model mechanism parameters.

[0149] The construction module 10 is used to combine the optimization module and the urban sewage treatment system simulation model for calculation, identify and correct the model mechanism parameters, and construct an actual urban sewage treatment system model based on the actual operating conditions.

[0150] Regarding the apparatus in the above embodiments, the specific manner in which each module performs its operation has been described in detail in the embodiments related to the method, and will not be elaborated upon here.

[0151] For the device embodiments, since they basically correspond to the method embodiments, the relevant parts can be referred to in the description of the method embodiments. The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this application according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0152] Accordingly, this application also provides an electronic device, comprising: one or more processors; a memory for storing one or more programs; and when the one or more programs are executed by the one or more processors, causing the one or more processors to implement the above-described method for constructing a mechanism-data hybrid urban wastewater simulation model based on Modelica.

[0153] Accordingly, this application also provides a computer-readable storage medium storing computer instructions that, when executed by a processor, implement the above-described method for constructing a mechanism-data hybrid urban wastewater simulation model based on Modelica.

[0154] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of this application are indicated by the claims.

[0155] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.

Claims

1. A method for constructing a Modelica-based mechanism-data hybrid municipal sewage treatment simulation model, characterized in that, The application relates to a simulation method for a municipal sewage treatment system, and belongs to the field of municipal sewage treatment simulation. According to the settlement principle in primary treatment of municipal sewage, a primary sedimentation tank model is built based on Modelica, and inputs and outputs are determined, the primary sedimentation tank model being used for calculating the effluent water quality of primary sedimentation of municipal sewage treatment; According to the nitrification reaction mechanism of the biological denitrification process, a nitrification tank model is built based on Modelica, and inputs and outputs are determined, the nitrification tank model being used for calculating the effluent water quality of the nitrification reaction of municipal sewage treatment; According to the denitrification biological reaction mechanism under anoxic environment, a denitrification tank model is built based on Modelica, and inputs and outputs are determined, the denitrification tank model being used for calculating the effluent water quality of the denitrification reaction of municipal sewage treatment; According to the one-dimensional flux model theory of a secondary sedimentation tank, a secondary sedimentation tank model is built based on Modelica, and inputs and outputs are determined, the secondary sedimentation tank model being used for calculating the effluent water quality of secondary sedimentation of municipal sewage treatment; According to the mass conservation law, a two-flow diverter model is built based on Modelica, and inputs and outputs are determined, the two-flow diverter model being used for calculating the flow of the diverter of municipal sewage treatment; According to the mass conservation law, a two-flow combiner model is built based on Modelica, and inputs and outputs are determined, the two-flow combiner model being used for calculating the flow of the combiner of municipal sewage treatment; According to the physical topology, actual operation process and working condition of municipal sewage treatment, the primary sedimentation tank model, the nitrification tank model, the denitrification tank model, the secondary sedimentation tank model, the two-flow diverter model and the two-flow combiner model are called to build a municipal sewage treatment system simulation model; According to the working principle of municipal sewage treatment, model mechanism parameters that need to be adjusted in the municipal sewage treatment system simulation model are determined based on actual operation conditions, the municipal sewage treatment system simulation model inputting the model mechanism parameters and outputting treatment water quality parameters and flow; According to the working principle of an optimization algorithm, an optimization module is built based on a MATLAB optimization toolbox, the deviation between the output results of the municipal sewage treatment system simulation model and actual data is taken as an evaluation index, the inputs and outputs of the optimization module are determined, the optimization module inputting the model mechanism parameters and outputting the evaluation index; The optimization module and the municipal sewage treatment system simulation model are combined to calculate, the model mechanism parameters are parameter-identified and corrected, and an actual municipal sewage treatment system simulation model is built according to actual operation conditions.

2. The method of claim 1, wherein, According to the settlement principle in primary treatment of municipal sewage, a primary sedimentation tank model is built based on Modelica, and inputs and outputs are determined, including: According to the settlement principle in primary treatment of municipal sewage, the primary sedimentation tank hydraulic retention time is calculated through the known primary sedimentation tank size and inflow; According to the primary sedimentation tank hydraulic retention time, the known total chemical oxygen demand and the known non-dissolved chemical oxygen demand, the water quality component removal ratio at different hydraulic retention times is obtained; According to the water quality component removal ratio at different hydraulic retention times and the mass conservation law, the primary sedimentation tank effluent water quality component, sludge component and effluent flow are obtained; According to the physical topology and the sedimentation principle, the input and output are determined, the input of the primary sedimentation tank model is the water quality parameter, the inflow and the sludge outflow, and the output is the water quality component, the sludge component and the outflow of the primary sedimentation tank.

3. The method of claim 1, wherein, According to the nitrification reaction mechanism of the biological denitrification process, a nitrification tank model is constructed based on Modelica, and the input and output are determined, including: According to the activated sludge 2d model, the functional relationship between the nitrification reaction biological phosphorus removal and the biological denitrification reaction in the nitrification tank is obtained; According to the mass conservation law and the functional relationship between the nitrification reaction biological phosphorus removal and the biological denitrification reaction, the relationship between the inlet flow and the water quality component of the nitrification tank and the outlet flow and the water quality component of the nitrification tank is obtained; According to the physical topology and the functional relationship in the model, the input and output of the nitrification tank are determined, the input of the nitrification tank is the inlet flow and the water quality component, and the output is the outlet flow and the water quality component of the nitrification tank.

4. The method of claim 1, wherein, According to the denitrification biological reaction mechanism under anoxic environment, a denitrification tank model is constructed based on Modelica, and the input and output are determined, including: According to the activated sludge 2d model, the functional relationship between the denitrification reaction biological phosphorus removal and the biological denitrification reaction in the denitrification tank is obtained; According to the mass conservation law and the functional relationship between the denitrification reaction biological phosphorus removal and the biological denitrification reaction, the relationship between the inlet flow and the water quality component of the denitrification tank and the outlet flow and the water quality component of the denitrification tank is obtained; According to the physical topology and the functional relationship in the model, the input and output of the denitrification tank are determined, the input of the denitrification tank is the inlet flow and the water quality component of the denitrification tank, and the output is the outlet flow and the water quality component of the denitrification tank.

5. The method of claim 1, wherein, According to the one-dimensional flux model theory of the secondary sedimentation tank, a secondary sedimentation tank model is constructed based on Modelica, and the input and output are determined, including: According to the one-dimensional flux model theory of the secondary sedimentation tank, the secondary sedimentation tank is divided into five levels, including the top layer, the clarification layer, the inlet water layer, the thickening layer and the bottom layer, and the material balance of each layer is formed by the material entering and flowing out of each layer; According to Takacs double exponential settling velocity model, the dynamic inflow and steady-state settling process of the secondary sedimentation tank are simulated by using first-order partial differential equation, and the settling velocity of the granular component in different layers of the secondary sedimentation tank is calculated; According to the mass conservation law, the water quality dissolved component and the sludge flux in different layers of the secondary sedimentation tank are obtained; According to the physical topology and the functional relationship in the model, the input and output of the secondary sedimentation tank model are determined, the input of the secondary sedimentation tank model is the inlet flow and the water quality component of the secondary sedimentation tank, and the output is the outlet flow and the water quality component of the secondary sedimentation tank.

6. The method of claim 1, wherein, According to the mass conservation law, a 2-flow splitter model is constructed based on Modelica, and the input and output are determined, including: According to the design parameters provided by the manufacturer, the relationship between the outlet 1 flow and the outlet 2 flow of the 2-flow splitter is obtained; According to the physical topology and the functional relationship in the model, the input and output of the 2-flow splitter model are determined, the input of the 2-flow splitter model is the inlet flow and the water quality component of the 2-flow splitter, and the output is the outlet 1 flow, the outlet 1 water quality component, the outlet 2 flow and the outlet 2 water quality component of the 2-flow splitter.

7. The method of claim 1, wherein, According to the mass conservation law, a 2-flow combiner model is constructed based on Modelica, and the input and output are determined, including: According to the design parameters provided by the manufacturer and the law of conservation of mass, the 2-flow-merging device outlet flow is obtained; According to the physical topology and the function relationship in the model, the input and output are determined, the input of the 2-flow-merging device model is the 2-flow-merging device inlet 1 flow, inlet 1 water quality component, inlet 2 flow and inlet 2 water quality component, and the output is the 2-flow-merging device outlet flow and water quality component.

8. The method of claim 1, wherein, According to the physical topology, actual operation process and working condition of the urban sewage treatment, the primary sedimentation tank model, the nitrification tank model, the denitrification tank model, the secondary sedimentation tank model, the 2-flow-splitting device model and the 2-flow-merging device model are called to construct the urban sewage treatment system simulation model, including: According to the physical topology and actual operation process of the urban sewage treatment, the number of each device model contained in the sewage treatment plant system simulation model and the direction information of internal and external reflux are determined to construct the urban sewage treatment system simulation model, which is used to describe the biological phosphorus removal and biological nitrogen removal process of urban sewage through the urban sewage treatment system; According to the working condition of the urban sewage treatment, the process operation parameters in the sewage treatment plant system simulation model are determined, including aeration quantity, internal reflux rate and external reflux rate.

9. A device for constructing a Modelica-based mechanism-data hybrid urban sewage treatment simulation model, characterized in that, Including: The first construction determination module is configured to construct a primary sedimentation tank model based on Modelica according to the sedimentation principle in the primary treatment of urban sewage, and determine the input and output, the primary sedimentation tank model being used to calculate the effluent water quality of the primary sedimentation of urban sewage treatment; The second construction determination module is configured to construct a nitrification tank model based on Modelica according to the nitrification reaction mechanism of the biological denitrification process, and determine the input and output, the nitrification tank model being used to calculate the effluent water quality of the nitrification reaction of urban sewage treatment; The third construction determination module is configured to construct a denitrification tank model based on Modelica according to the denitrification biological reaction mechanism in anoxic environment, and determine the input and output, the denitrification tank model being used to calculate the effluent water quality of the denitrification reaction of urban sewage treatment; The fourth construction determination module is configured to construct a secondary sedimentation tank model based on Modelica according to the one-dimensional flux model theory of the secondary sedimentation tank, and determine the input and output, the secondary sedimentation tank model being used to calculate the effluent water quality of the secondary sedimentation of urban sewage treatment; The fifth construction determination module is configured to construct a 2-flow-splitting device model based on Modelica according to the law of conservation of mass, and determine the input and output, the 2-flow-splitting device model being used to calculate the flow of the splitter of urban sewage treatment; The sixth construction determination module is configured to construct a 2-flow-merging device model based on Modelica according to the law of conservation of mass, and determine the input and output, the 2-flow-merging device model being used to calculate the flow of the merging device of urban sewage treatment; The seventh construction determination module is configured to construct an urban sewage treatment system simulation model by calling the primary sedimentation tank model, the nitrification tank model, the denitrification tank model, the secondary sedimentation tank model, the 2-flow-splitting device model and the 2-flow-merging device model according to the physical topology, actual operation process and working condition of the urban sewage treatment. an eighth construction determining module configured to determine model mechanism parameters in a municipal wastewater treatment system simulation model that need to be adjusted based on actual operation conditions according to a working principle of municipal wastewater treatment, wherein the municipal wastewater treatment system simulation model is inputted with the model mechanism parameters and is outputted with water quality parameters and flow of treated water; a ninth construction determining module configured to construct an optimization module based on a MATLAB optimization toolbox according to a working principle of an optimization algorithm, wherein a deviation between output results of the municipal wastewater treatment system simulation model and actual data of a wastewater treatment plant is used as an evaluation index, the optimization module is inputted with the model mechanism parameters, and the optimization module is outputted with a minimum value of the evaluation index and corresponding model mechanism parameters; a construction module configured to combine the optimization module and the municipal wastewater treatment system simulation model to calculate, to perform parameter identification correction on the model mechanism parameters, and to construct an actual municipal wastewater treatment system simulation model according to actual operation conditions.

10. An electronic device, comprising: comprise: one or more processors; a memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the method in any one of claims 1-8.

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